title: Occipital gamma activation during Vipassana meditation

abstract: Long-term Vipassana meditators sat in meditation vs. a control rest (mind-wandering) state for 21 min in a counterbalanced design with spontaneous EEG recorded. Meditation state dynamics were measured with spectral decomposition of the last 6 min of the eyes-closed silent meditation compared to control state. Meditation was associated with a decrease in frontal delta (1–4 Hz) power, especially pronounced in those participants not reporting drowsiness during meditation. Relative increase in frontal theta (4–8 Hz) power was observed during meditation, as well as significantly increased parieto-occipital gamma (35–45 Hz) power, but no other state effects were found for the theta (4–8 Hz), alpha (8–12 Hz), or beta (12–25 Hz) bands. Alpha power was sensitive to condition order, and more experienced meditators exhibited no tendency toward enhanced alpha during meditation relative to the control task. All participants tended to exhibit decreased alpha in association with reported drowsiness. Cross-experimental session occipital gamma power was the greatest in meditators with a daily practice of 10+ years, and the meditation-related gamma power increase was similarly the strongest in such advanced practitioners. The findings suggest that long-term Vipassana meditation contributes to increased occipital gamma power related to long-term meditational expertise and enhanced sensory awareness.


title: Detecting Psychopathy From Thin Slices of Behavior

abstract: This study is the first to demonstrate that features of psychopathy can be reliably and validly detected by lay raters from “thin slices” (i.e., small samples) of behavior. Brief excerpts (5 s, 10 s, and 20 s) from interviews with 96 maximum-security inmates were presented in video or audio form or in both modalities combined. Forty raters used these excerpts to complete assessments of overall psychopathy and its Factor 1 and Factor 2 components, various personality disorders, violence proneness, and attractiveness. Thin-slice ratings of psychopathy correlated moderately and significantly with psychopathy criterion measures, especially those related to interpersonal features of psychopathy, particularly in the 5- and 10-s excerpt conditions and in the video and combined channel conditions. These findings demonstrate that first impressions of psychopathy and related constructs, particularly those pertaining to interpersonal functioning, can be reasonably reliable and valid. They also raise intriguing questions regarding how individuals form first impressions and about the extent to which first impressions may influence the assessment of personality disorders.


title: Topical Application of 5-Fluorouracil Associated with Distant Seborrheic Dermatitis-like Eruption: Case Report and Review of Seborrheic Dermatitis Cutaneous Reactions after Systemic or Topical Treatment with 5-Fluorouracil

abstract: 5-Fluorouracil is a fluoropyrimidine antineoplastic medication that is used to topically treat actinic keratoses. Although local adverse effects to the drug are common and anticipated, distant skin reactions are rare and unexpected. In this case report, we describe a patient who developed seborrheic dermatitis-like eruption at a distant site after topical application of 5-fluorouracil to his arms. A 63-year-old man with actinic keratoses on his arms developed a facial seborrheic dermatitis-like reaction after topically applying 5-fluorouracil 5% cream twice daily to actinic keratoses on his forearms for 7 days. The facial dermatosis resolved shortly after discontinuation of the 5-fluorouracil; upon rechallenge of topical 5-fluorouracil on his arms, the facial seborrheic dermatitis recurred. Several case reports have been published which describe exacerbations of preexisting seborrheic dermatitis with local topical 5-fluorouracil. Additionally, one case series describes the development of scrotal dermatitis in two patients after distant treatment with 5-fluorouracil. The pathogenesis that causes this distant reaction is unclear. We describe a patient with a seborrheic dermatitis eruption after topical application of 5-fluorouracil at a distant site. The etiologic association between the drug and adverse effect was confirmed with multiple cycles of application and discontinuation of the offending agent.


title: Self-modeling curve resolution (SMCR) analysis of near-infrared (NIR) imaging data of pharmaceutical tablets

abstract: The idea of quality by design (QbD) has been proposed in pharmaceutical field. QbD is a systematic approach to control the product performance based on the scientific understanding of the product quality and its manufacturing process. In the present study, near-infrared (NIR) imaging is utilized as a tool to achieve this concept. A practical use of a chemometrics technique called self-modeling curve resolution (SMCR) is demonstrated with NIR imaging analysis of pharmaceutical tablets containing two ingredients, a soluble active ingredient, pentoxifylline (PTX), and an insoluble excipient, palmitic acid. Concentration profiles obtained by SMCR reveal that the homogenous distribution of chemical ingredients strongly depends on the grinding time and that its process plays a central role in quantitative control, say sustained-release of PTX. In addition, pure component spectra by SMCR indicate a sequential change of specific NIR peak intensities following the increase of the grinding time. The spectra change shows a molecular structure change related to its crystallinity during grinding process. Accordingly, this study clearly demonstrates that NIR imaging combined with SMCR can be a powerful tool to reveal chemical or physical mechanism induced by the manufacturing process of pharmaceutical products and that it may be a solid solution for QbD of pharmaceutical products.


title: MotionFlow: Visual Abstraction and Aggregation of Sequential Patterns in Human Motion Tracking Data

abstract: Pattern analysis of human motions, which is useful in many research areas, requires understanding and comparison of different styles of motion patterns. However, working with human motion tracking data to support such analysis poses great challenges. In this paper, we propose MotionFlow, a visual analytics system that provides an effective overview of various motion patterns based on an interactive flow visualization. This visualization formulates a motion sequence as transitions between static poses, and aggregates these sequences into a tree diagram to construct a set of motion patterns. The system also allows the users to directly reflect the context of data and their perception of pose similarities in generating representative pose states. We provide local and global controls over the partition-based clustering process. To support the users in organizing unstructured motion data into pattern groups, we designed a set of interactions that enables searching for similar motion sequences from the data, detailed exploration of data subsets, and creating and modifying the group of motion patterns. To evaluate the usability of MotionFlow, we conducted a user study with six researchers with expertise in gesture-based interaction design. They used MotionFlow to explore and organize unstructured motion tracking data. Results show that the researchers were able to easily learn how to use MotionFlow, and the system effectively supported their pattern analysis activities, including leveraging their perception and domain knowledge.


Mechanism, Teleology, and Mind


title: Synchronization of pulse-coupled excitable neurons.

abstract: Collective behavior of pulse-coupled oscillatory neurons has been investigated widely. In many cases, however, real neurons are intrinsically not oscillatory but excitable. The networks of excitable neurons can have their own characteristic dynamics, and they are of interest also from the viewpoint of functional assemblies. In the present paper, the collective behavior of pulse-coupled excitable neurons has been investigated using phase description. It is shown that full synchronization is achieved in networks of excitable leaky integrate-and-fire neurons and discrete-time Nagumo-Sato neurons. The cooperative roles of external spike inputs, decay of internal states, and feedback spikes are explained. Enhancement of synchronization by refractoriness and noise is also reported.


title: Chronic pain and the emotional brain : Specific brain activity associated with spontaneous fluctuations of intensity of chronic back pain

abstract: Living with unrelenting pain (chronic pain) is maladaptive and is thought to be associated with physiological and psychological modifications, yet there is a lack of knowledge regarding brain elements involved in such conditions. Here, we identify brain regions involved in spontaneous pain of chronic back pain (CBP) in two separate groups of patients (n = 13 and n = 11), and contrast brain activity between spontaneous pain and thermal pain (CBP and healthy subjects, n = 11 each). Continuous ratings of fluctuations of spontaneous pain during functional magnetic resonance imaging were separated into two components: high sustained pain and increasing pain. Sustained high pain of CBP resulted in increased activity in the medial prefrontal cortex (mPFC; including rostral anterior cingulate). This mPFC activity was strongly related to intensity of CBP, and the region is known to be involved in negative emotions, response conflict, and detection of unfavorable outcomes, especially in relation to the self. In contrast, the increasing phase of CBP transiently activated brain regions commonly observed for acute pain, best exemplified by the insula, which tightly reflected duration of CBP. When spontaneous pain of CBP was contrasted to thermal stimulation, we observe a double-dissociation between mPFC and insula with the former correlating only to intensity of spontaneous pain and the latter correlating only to pain intensity for thermal stimulation. These findings suggest that subjective spontaneous pain of CBP involves specific spatiotemporal neuronal mechanisms, distinct from those observed for acute experimental pain, implicating a salient role for emotional brain concerning the self.


title: Trust and commitment influences on customer retention: insights from business-to-business services

abstract: Despite the importance of trust and commitment in relationship marketing, the scholarly inquiry on the issue is rather impeded in several ways. Furthermore, when it comes to the marketing of services and specifically for business-to-business (B2B) markets, the empirical documentation is even slimmer despite the fact that services are increasingly becoming a vital component of the product that the customers buy even when it comes to tangible goods such as computers or cars. In view of this gap, the present empirical study attempts an investigation of two specific antecedents of trust and consequently of commitment: the perceived quality of the service and the customer bonding techniques used by the supplier. In doing so, the causality of the relationships between the various constructs is also examined.


title: An integrated experimental environment for distributed systems and networks

abstract: Three experimental environments traditionally support network and distributed systems research: network emulators, network simulators, and live networks. The continued use of multiple approaches highlights both the value and inadequacy of each. Netbed, a descendant of Emulab, provides an experimentation facility that integrates these approaches, allowing researchers to configure and access networks composed of emulated, simulated, and wide-area nodes and links. Netbed's primary goals are ease of use, control, and realism, achieved through consistent use of virtualization and abstraction.By providing operating system-like services, such as resource allocation and scheduling, and by virtualizing heterogeneous resources, Netbed acts as a virtual machine for network experimentation. This paper presents Netbed's overall design and implementation and demonstrates its ability to improve experimental automation and efficiency. These, in turn, lead to new methods of experimentation, including automated parameter-space studies within emulation and straightforward comparisons of simulated, emulated, and wide-area scenarios.


title: Pelvic girdle pain 3–6 months after delivery in an unselected cohort of Norwegian women

abstract: PURPOSE ::: Persistent pelvic girdle pain (PGP) after delivery is considered uncommon. The aim of this study was to assess the frequency of persistent PGP after delivery in an unselected population, its influence on the women's daily life, and potential risk factors. ::: ::: ::: METHODS ::: The study population was drawn from a previous retrospective study of pelvic pain (PP) during pregnancy. The women were followed until 3-6 months after delivery in a prospective cohort study. All women were contacted by telephone and those with persistent PP were invited to fill in questionnaires and undergo a clinical examination. ::: ::: ::: RESULTS ::: 68 of 330 women reported persistent pain in the pelvic area 3-6 months after delivery. 47 underwent a clinical examination, after which 36 women were diagnosed with either PGP alone (n = 25), or PGP combined with low back pain (LBP) (n = 11). Affected women reported a poor subjective health status, but the pain did not have a major impact on their daily life activities. Women with 3 independent risk factors: age ≥30 years, a moderate or high Oswestry Disability Index in pregnancy, and combined PP and LBP during pregnancy, had a 27-fold increased risk for persistent PGP compared with women without these risk factors. ::: ::: ::: CONCLUSION ::: 16 % of women that reported PP during pregnancy were found to have persistent PGP 3-6 months after the delivery. Women with risk factors for persistent PGP should be identified while pregnant, and offered a follow-up examination 3 months after delivery.


The Benefits of Virtual Reality in Education- A comparision Study


title: Risk assessment of ritual use of oral dimethyltryptamine (DMT) and harmala alkaloids.

abstract: AIM ::: To extend previous reviews by assessing the acute systemic toxicity and psychological hazards of a dimethyltryptamine and beta-carboline brew (ayahuasca/hoasca) used in religious ceremonies. ::: ::: ::: METHOD ::: A systematic literature search, supplemented by interviews with ceremony participants. ::: ::: ::: RESULTS ::: No laboratory animal models were located that tested the acute toxicity or the abuse potential of ayahuasca. Separate animal studies of the median lethal dose of dimethyltryptamine (DMT) and of several harmala alkaloids indicated that a lethal dose of these substances in humans is probably greater than 20 times the typical ceremonial dose. Adverse health effects may occur from casual use of ayahuasca, particularly when serotonergic substances are used in conjunction. DMT is capable of inducing aversive psychological reactions or transient psychotic episodes that resolve spontaneously in a few hours. There was no evidence that ayahuasca has substantial or persistent abuse potential. Long-term psychological benefits have been documented when ayahuasca is used in a well-established social context. ::: ::: ::: CONCLUSION ::: A decoction of DMT and harmala alkaloids used in religious ceremonies has a safety margin comparable to codeine, mescaline or methadone. The dependence potential of oral DMT and the risk of sustained psychological disturbance are minimal.


title: How Methods Make Designers

abstract: Through their combination of lifestyle and method, Silicon Valley models for tech production such as design thinking, startup incubators, lean management, etc. are spreading across the globe. These paradigms are positioned by product designers, politicians, investors and corporations alike as replicable routes to individual and national empowerment. They are portrayed as universal templates, portable across national borders and applicable to local needs. We draw from our ethnographic engagements with tech entrepreneurial efforts in Ghana, China, and Jamaica to unpack the stakes involved in their uptake, showing that while local actors produce situated alternatives, their work nevertheless often results in a continued valorization of these seemingly universal methods. We argue that design methods shape not only use practices, but have consequences for the life worlds of professional designers. This includes how they impact personal and national identities, confer legitimacy in transnational innovation circles, and secure access to social and economic resources. Ultimately, we call for an inclusion of these factors in ongoing conversations about design and design methods.


title: Self-assembled flower-like antimony trioxide microstructures with high infrared reflectance performance

abstract: A simple hydrothermal process was adopted to self-assembly prepare high infrared reflective antimony trioxide with three-dimensional flower-like microstructures. The morphologies of antimony trioxide microstructures were characterized by X-ray diffractometry (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), and high resolution transmission electron microscopy (HRTEM) respectively. It is also found that experimental parameters, such as NaOH concentration, surfactant concentration and volume ratio of ethanol–water played crucial roles in controlling the morphologies of Sb2O3 microstructures. A possible growth mechanism of flower-like Sb2O3 microstructure was proposed based on the experimental data. UV–vis–NIR spectra verified that the near infrared reflectivity of the obtained flower-like microstructures could averagely achieve as 92% with maximum reflectivity of 98%, obviously higher than that of other different morphologies of antimony trioxide microstructures. It is expected that the flower-like Sb2O3 nanostructures have some applications in optical materials and heat insulation coatings.


title: 3D Time-Lapse Reconstruction from Internet Photos

abstract: Given an Internet photo collection of a landmark, we compute a 3D time-lapse video sequence where a virtual camera moves continuously in time and space. While previous work assumed a static camera, the addition of camera motion during the time-lapse creates a very compelling impression of parallax. Achieving this goal, however, requires addressing multiple technical challenges, including solving for time-varying depth maps, regularizing 3D point color profiles over time, and reconstructing high quality, hole-free images at every frame from the projected profiles. Our results show photorealistic time-lapses of skylines and natural scenes over many years, with dramatic parallax effects.


title: Deep convolutional neural networks for segmenting 3D in vivo multiphoton images of vasculature in Alzheimer disease mouse models

abstract: The health and function of tissue rely on its vasculature network to provide reliable blood perfusion. Volumetric imaging approaches, such as multiphoton microscopy, are able to generate detailed 3D images of blood vessels that could contribute to our understanding of the role of vascular structure in normal physiology and in disease mechanisms. The segmentation of vessels, a core image analysis problem, is a bottleneck that has prevented the systematic comparison of 3D vascular architecture across experimental populations. We explored the use of convolutional neural networks to segment 3D vessels within volumetric in vivo images acquired by multiphoton microscopy. We evaluated different network architectures and machine learning techniques in the context of this segmentation problem. We show that our optimized convolutional neural network architecture with a customized loss function, which we call DeepVess, yielded a segmentation accuracy that was better than state-of-the-art methods, while also being orders of magnitude faster than the manual annotation. To explore the effects of aging and Alzheimer’s disease on capillaries, we applied DeepVess to 3D images of cortical blood vessels in young and old mouse models of Alzheimer’s disease and wild type littermates. We found little difference in the distribution of capillary diameter or tortuosity between these groups, but did note a decrease in the number of longer capillary segments (>75μm) in aged animals as compared to young, in both wild type and Alzheimer’s disease mouse models.


title: Circuit Breakers, Discovery, and API Gateways in Microservices

abstract: We review some of the most widely used patterns for the programming of microservices: circuit breaker, service discovery, and API gateway. By systematically analysing different deployment strategies for these patterns, we reach new insight especially for the application of circuit breakers. We also evaluate the applicability of Jolie, a language for the programming of microservices, for these patterns and report on other standard frameworks offering similar solutions. Finally, considerations for future developments are presented.


Reinforcement Learning and Approximate Dynamic Programming for Feedback Control


MOCA: a service framework for mobile computing devices


title: Pulmonary Nodule Detection, Characterization, and Management With Multidetector Computed Tomography

abstract: Pulmonary nodule detection and characterization con- tinue to improve with technological advancements. The noninva- sive methods available for assisting in nodule detection and for characterizing nodules as benign, malignant, or indeterminate will be discussed. Evidence-based guidelines will be reviewed to help guide the appropriate management of pulmonary nodules.


The Unwritten Contract of Solid State Drives 1


title: Recurrent neural networks for remaining useful life estimation

abstract: This paper presents an approach and solution to the IEEE 2008 Prognostics and Health Management conference challenge problem. The solution utilizes an advanced recurrent neural network architecture to estimate the remaining useful life of the system. The recurrent neural network is trained with back-propagation through time gradient calculations, an Extended Kalman Filter training method, and evolutionary algorithms to generate an accurate and compact algorithm. This solution placed second overall in the competition with a very small margin between the first and second place finishers.


title: Deterministic compressed-sensing matrices: Where Toeplitz meets Golay

abstract: Recently, the statistical restricted isometry property (STRIP) has been formulated to analyze the performance of deterministic sampling matrices for compressed sensing. In this paper, a class of deterministic matrices which satisfy STRIP with overwhelming probability are proposed, by taking advantage of concentration inequalities using Stein's method. These matrices, called orthogonal symmetric Toeplitz matrices (OSTM), guarantee successful recovery of all but an exponentially small fraction of K-sparse signals. Such matrices are deterministic, Toeplitz, and easy to generate. We derive the STRIP performance bound by exploiting the specific properties of OSTM, and obtain the near-optimal bound by setting the underlying sign sequence of OSTM as the Golay sequence. Simulation results show that these deterministic sensing matrices can offer reconstruction performance similar to that of random matrices.


title: Social Cobots: Anticipatory Decision-Making for Collaborative Robots Incorporating Unexpected Human Behaviors

abstract: We propose an architecture as a robot»s decision-making mechanism to anticipate a human»s state of mind, and so plan accordingly during a human-robot collaboration task. At the core of the architecture lies a novel stochastic decision-making mechanism that implements a partially observable Markov decision process anticipating a human»s state of mind in two-stages. In the first stage it anticipates the human»s task related availability, intent (motivation), and capability during the collaboration. In the second, it further reasons about these states to anticipate the human»s true need for help. Our contribution lies in the ability of our model to handle these unexpected conditions: 1) when the human»s intention is estimated to be irrelevant to the assigned task and may be unknown to the robot, e.g., motivation is lost, another assignment is received, onset of tiredness, and 2) when the human»s intention is relevant but the human doesn»t want the robot»s assistance in the given context, e.g., because of the human»s changing emotional states or the human»s task-relevant distrust for the robot. Our results show that integrating this model into a robot»s decision-making process increases the efficiency and naturalness of the collaboration.


title: Time Series Forecasting with PSO-Optimized Neural Networks

abstract: In this paper, we propose a new methodology to forecast values for univariate time series datasets, based on a Feed Forward Neural Network (FFNN) ensemble. Each ensemble element is trained with the Particle Swarm Optimization (PSO) algorithm, this ensemble produces a final sequence of time series forecasts via a bootstrapping procedure. Our proposed methodology is compared against Auto-Regressive Integrated Moving Average (ARIMA) models. This experiment gives us a good idea of how effective soft computing techniques can be in the field of time series modeling. The results obtained show empirically that our proposed methodology is robust and produces useful forecast error bounds that provide a clear picture of a time series' future movements.


title: Flexible Search and Navigation Using Faceted Metadata

abstract: We have developed an innovative search interface that allows non-expert users to move through large information spaces in a flexible manner without feeling lost. The design goal was to offer users a “browsing the shelves” experience seamlessly integrated with focused search. Key to achieving our goal is the explicit exposure of hierarchical faceted metadata in a manner that is intuitive and inviting to users. After several iterations of design and testing, the usability results are strikingly positive. We believe our approach marks a major step forward in search user interfaces and can serve as a model for web-based collections of up to 100,000 items. Topics: Search User Interfaces, Faceted Metadata INTRODUCTION Although general Web search is steadily improving [30], studies show that search is still the primary usability problem in web site design. A recent report by Vividence Research analyzing 69 web sites found that the most common usability problem was poorly organized search results, affecting 53% of sites studied. The second most common problem was poor information architecture, affecting 32% of sites [27]. Studies of search behavior reveal that good search involves both broadening and narrowing of the query, appropriate selection of terminology, and the ability to modify the query [31]. Still others show that users often express a concern about online search systems since they do not allow a “browsing the shelves” experience afforded by physical libraries [6] and that users like wellstructured hyperlinks but often feel lost when navigating through complex sites [23]. Our goals are to support search usability guidelines [28], while avoiding negative consequences like empty result sets or feelings of being lost. We are especially interested in large collections of similar-style items (such as product catalog sites, sites consisting of collections of images, or text documents on a topic such as medicine or law). Our approach is to follow iterative design practices from the field of human-computer interaction [29], meaning that we first assess the behavior of the target users, then prototype a system, then assess that system with target users, learn from and adjust to the problems found, and repeat until a successful interface is produced. We have applied this method to the problem of creating an information architecture that seamlessly integrates navigation and free-text search into one interface. This system builds on earlier work that shows the importance of query previews [25] for indicating next choices (thus allowing the user to use recognition over recall) and avoiding empty result sets. The approach makes use of faceted hierarchical metadata (described below) as the basis for a navigation structure showing next choices, providing alternative views, and permitting refinement and expansion in new directions, while at the same time maintaining a consistent representation of the collection’s structure [14]. This use of metadata is integrated with free-text search, allowing the user to follow links, then add search terms, then follow more links, without interrupting the interaction flow. Our most recent usability studies show strong, positive results along most measured variables. An added advantage of this framework is that it can be built using off-the-shelf database technology, and it allows the contents of the collection to be changed without requiring the web site maintainer to change the system or the interface. For these reasons, we believe these results should influence the design of information architecture of information-centric web sites. In the following sections we define the metadata-based terminology, describe the interface framework as applied to a collection of architectural images, report the results of usability studies, discuss related work, and discuss the implications of these results. Submitted for Publication METADATA Content-oriented category metadata has become more prevalent in the last few years, and many people are interested in standards for describing content in various fields (e.g., Dublin Core and the Semantic Web). Web directories such as Yahoo and the Open Directory Project are familiar examples of the use of metadata for navigation structures. Web search engines have begun to interleave search hits on category labels with other search results. Many individual collections already have rich metadata assigned to their contents; for example, biomedical journal articles have on average a dozen or more content attributes attached to them. Metadata for organizing content collections can be classified along several dimensions: • The metadata may be faceted, that is, composed of orthogonal sets of categories. For example, in the domain of architectural images, some possible facets might be Materials (concrete, brick, wood, etc.), Styles (Baroque, Gothic, Ming, etc.), View Types, People (architects, artists, developers, etc.), Locations, Periods, and so on. • The metadata (or an individual facet) may be hierarchical (“located in Berkeley, California, United States”) or flat (“by Ansel Adams”). • The metadata (or an individual facet) may be singlevalued or multi-valued. That is, the data may be constrained so that at most one value can be assigned to an item (“measures 36 cm tall”) or it may allow multiple values to be assigned to an item (“uses oil paint, ink, and watercolor”). We note that there are a number of issues associated with creation of metadata itself which we are not addressing here. The most pressing problem is how to decide which descriptors are correct or at least most appropriate for a collection of information. Another problem relates to how to assign metadata descriptors to items that currently do not have metadata assigned. We will not be addressing these issues, in part because many other researchers already are, and because the fact remains that there are many existing, important collections whose contents have hierarchical metadata already assigned. RECIPE USABILITY STUDY We are particularly concerned with supporting non-professional searchers in rich information seeking tasks. Specifically we aim to answer the following questions: do users like and understand flexible organizations of metadata from different hierarchies? Are faceted hierarchies preferable to single hierarchies? Do people prefer to follow category-based hyperlinks or do they prefer to issue a keyword-based query and sort through results listings? 1http://dublincore.org, http://www.w3.org/2001/sw 2http://www.yahoo.com, http://dmoz.org Figure 1: The opening page for both interfaces shows a text search box and the first level of metadata terms. Hovering over a facet name yields a tooltip (here shown below Locations) explaining the meaning of the facet. Before developing our system, we tested the idea of using hierarchical faceted metadata on an existing interface that exemplified some of our design goals. This preliminary study was conducted using a commercial recipe web site called Epicurious containing five flat facets, 93 metadata terms, and approximately 13,000 recipes. We compared the three available search interfaces:(1) Simple keyword search, with unsorted results list (2) Enhanced search form that exposes metadata using checkboxes and drop-down lists, with unsorted results list. (3) Browse interface that allows user to navigate through the collection, implicitly building up a query consisting of an AND across facets; Selecting a category within a facet (e.g., Pasta within Main Ingredient) narrows results set, and users are shown query previews at every step. In the interests of space, we can only provide a brief summary of this small (9 participant) study: All the participants who liked the site (7 out of 9) said they were likely to use the browse interface again. Only 4 said this about enhanced search and 0 said this about simple search. Participants especially liked the browse interface for open-ended tasks such as “plan a dinner party.” We took this as encouraging support for the faceted metadata approach. However, the recipe browse facility is lacking in several ways. Free-text search is not integrated with metadata browse, the collection and metadata are of only moderate size, and the metadata is organized into flat (non-hierarchical) facets. Finally users are only allowed to refine queries, they cannot broaden 3http://eat.epicurious.com/recipes/browse home/


title: Modeling Document Summarization as Multi-objective Optimization

abstract: In this paper, we consider document summarization as a multi-objective optimization problem involving four objective functions, namely information coverage, significance, redundancy and text coherence. These functions measure the possible summaries based on the identified core terms and main topics (i.e. a cluster of semantically or statistically related core terms). We choose the DUC 2005 and 2006 query-oriented summarization tasks to exam the proposed model. The encouraging results indicate that the multi-objective optimization based framework for document summarization is truly a promising research direction.


title: Cordyceps fungi: natural products, pharmacological functions and developmental products

abstract: OBJECTIVES ::: Parasitic Cordyceps fungi, such as Cordyceps sinensis, is a parasitic complex of fungus and caterpillar, which has been used for medicinal purposes for centuries particularly in China, Japan and other Asian countries. This article gives a general idea of the latest developments in C. sinensis research, with regard to the active chemical components, the pharmacological effects and the research and development of products in recent years. ::: ::: ::: KEY FINDINGS ::: The common names for preparations include DongChongXiaCao in Chinese, winter worm summer grass in English. It has many bioactive components, such as 3'-deoxyadenosine, cordycepic acid and Cordyceps polysaccharides. It is commonly used to replenish the kidney and soothe the lung, and for the treatment of fatigue. It also can be used to treat conditions such as night sweating, hyposexuality, hyperglycaemia, hyperlipidaemia, asthenia after severe illness, respiratory disease, renal dysfunction, renal failure, arrhythmias and other heart disease and liver disease. Because of its rarity and outstanding curative effects, several mycelia strains have been isolated from natural Cordyceps and manufactured by fermentation technology, and are commonly sold as health food products. In addition, some substitutes such as C. militaris and adulterants also have been used; therefore, quality control of C. sinensis and its products is very important to ensure their safety and efficacy. ::: ::: ::: SUMMARY ::: Recent research advances in the study of Cordyceps, including Cordyceps mushrooms, chemical components, pharmacological functions and developmental products, has been reviewed and discussed. Developing trends in the field have also been appraised.


title: Diversifying search results

abstract: We study the problem of answering ambiguous web queries in a setting where there exists a taxonomy of information, and that both queries and documents may belong to more than one category according to this taxonomy. We present a systematic approach to diversifying results that aims to minimize the risk of dissatisfaction of the average user. We propose an algorithm that well approximates this objective in general, and is provably optimal for a natural special case. Furthermore, we generalize several classical IR metrics, including NDCG, MRR, and MAP, to explicitly account for the value of diversification. We demonstrate empirically that our algorithm scores higher in these generalized metrics compared to results produced by commercial search engines.


A Study of Style in Machine Translation: Controlling the Formality of Machine Translation Output


title: A Window-Based Self-Attention approach for sentence encoding

abstract: Abstract Recently, much progress has been made in the representation of sentences for the task of natural language processing (NLP). Most of existing methods utilize deep learning methods with RNN/CNN to capture contextual information. These models typically treat each word in a sentence equally, which ignores the fact that keywords always play a leading role in expressing the sentence semantic. Especially, on the tasks of sentence classification and semantic relatedness prediction, we can judge through the information of several keywords, no need for the whole sentence. To this end, we propose a window-based intra-weighing approach to weigh words in the sentence. In calculating attentive weights, we take as input multi-window n-grams and use max-pooling for feature extraction. To evaluate our model, we conduct experiments on 6 benchmark data sets. The experimental results demonstrate the superiority of our model in calculating word importance. Although our model has fewer parameters and much lower computational complexity than state-of-the-art models, it achieves comparable results with them.


title: The learning brain: Lessons for education: a précis

abstract: This book highlights the importance of anchoring education in an evidence base derived from neuroscience. For far too long has the brain been neglected in discussions on education and often information about neuroscientific research is not easy to access. Our aim was to provide a source book that conveys the excitement of neuroscience research that is relevant to learning and education. This research has largely, but not exclusively, been carried out using neuroimaging methods in the past decade or so, ranging from investigations of brain structure and function in dyslexia and dyscalculia to investigations of the changes in the hippocampus of London taxi drivers. To speak to teachers who might not have scientific backgrounds, we have tried to use nontechnical language as far as possible and have provided an appendix illustrating the main methods and techniques currently used and a glossary, defining terms from Acetylcholine, Action Potentials and ADHD to White Matter, Word Form Area and Working Memory. We start with the idea that the brain has evolved to educate and to be educated, often instinctively and effortlessly. We believe that understanding the brain mechanisms that underlie learning and teaching could transform educational strategies and enable us to design educational programmes that optimize learning for people of all ages and of all needs. For this reason the first two-thirds of the book follows a developmental framework. The rest of the book focuses on learning in the brain at all ages. There is a vast amount brain research of direct relevance to education practice and policy. And yet neuroscience has had little impact on education. This might in part be due to a lack of interaction between educators and brain scientists. This in turn might be because of difficulties of translating the neuroscience knowledge of how learning takes place in the brain into information of value to teachers. It is here where we try to fill a gap. Interdisciplinary dialogue needs a mediator to prevent one or other discipline dominating, and, notwithstanding John Bruer’s remarks that it is cognitive psychology that ‘bridges the gap’ between neuroscience and education (Bruer, 1997), we feel that now is the time to explore the implications of brain science itself for education.


title: Intrusion detection using autonomous agents

abstract: AAFID is a distributed intrusion detection architecture and system, developed in CERIAS at Purdue University. AAFID was the first architecture that proposed the use of autonomous agents for doing intrusion detection. With its prototype implementation, it constitutes a useful framework for the research and testing of intrusion detection algorithms and mechanisms. We describe the AAFID architecture and the existing prototype, as well as some design and implementation experiences and future research issues. ” 2000 Elsevier Science B.V. All rights reserved.


title: Pattern electrical stimulation of the human retina

abstract: Experiments were conducted to study if electrical stimulation of the retinal surface can elicit visual sensation in individuals blind from end-stage retinitis pigmentosa (RP) or age-related macular degeneration (AMD). Under local anesthesia, different stimulating electrodes were inserted through the eyewall and positioned over the surface of the retina. Subjects’ psychophysical responses to electrical stimulation were recorded. Subjects perceived simple forms in response to pattern electrical stimulation of the retina. A non-flickering perception was created with stimulating frequencies between 40 and 50 Hz. The stimulation threshold was dependent on the targeted retinal area (macular versus extramacular). © 1999 Published by Elsevier Science Ltd. All rights reserved.


PUZZLE IMAGE MOSAIC


title: Mobile Social Networking Under Side-Channel Attacks: Practical Security Challenges

abstract: Mobile social networks (MSNs) are the networks of individuals with similar interests connected to each other through their mobile devices. Recently, MSNs are proliferating fast supported by emerging wireless technologies that allow to achieve more efficient communication and better networking performance across the key parameters, such as lower delay, higher data rate, and better coverage. At the same time, most of the MSN users do not fully recognize the importance of security on their handheld mobile devices. Due to this fact, multiple attacks aimed at capturing personal information and sensitive user data become a growing concern, fueled by the avalanche of new MSN applications and services. Therefore, the goal of this work is to understand whether the contemporary user equipment is susceptible to compromising its sensitive information to the attackers. As an example, various information security algorithms implemented in modern smartphones are thus tested to attempt the extraction of the said private data based on the traces registered with inexpensive contemporary audio cards. Our obtained results indicate that the sampling frequency, which constitutes the strongest limitation of the off-the-shelf side-channel attack equipment, only delivers low-informative traces. However, the success chances to recover sensitive data stored within a mobile device may increase significantly when utilizing more efficient analytical techniques as well as employing more complex attack equipment. Finally, we elaborate on the possible utilization of neural networks to improve the corresponding encrypted data extraction process, while the latter part of this paper outlines solutions and practical recommendations to protect from malicious side-channel attacks and keep the personal user information protected.


title: Secular trends in incidence of invasive beta-hemolytic streptococci and efficacy of adjunctive therapy in Quebec, Canada, 1996-2016

abstract: Objectives To examine secular changes in the incidence of invasive beta-hemolytic streptococcal infections, and to assess the efficacy of immunoglobulins and clindamycin as adjunctive therapies in the management of Streptococcus pyogenes infections. Methods Retrospective cohort study of all cases of invasive group A (GAS), B (GBS), C or G (GCGS) streptococcal infections managed in a Canadian tertiary center from 1996–2016. Population incidence was measured for diabetics and non-diabetics. Adjusted odds ratios (AOR) and their 95% confidence intervals (CI) were calculated by logistic regression. Results 741 cases were identified (GAS: 249; GBS: 304; GCGS: 188). While the incidence of invasive GAS infections fluctuated with no clear trend, incidence of invasive GBS and GCGS increased over time and were 8.4 and 6.3 times higher in diabetics. Mortality of invasive GAS infections decreased from 16% (6/37) in 1996–2001 to 4% (4/97) in 2011–15. Among patients with GAS infections, clindamycin administered concomitantly with a beta-lactam within 24 hours of admission decreased mortality (AOR: 0.04, 95%CI: 0.003–0.55, P = 0.02. Immunoglobulins had no such effect (AOR: 1.66, 95%CI: 0.16–17.36, P = 0.67). The protective effect of clindamycin was similar in patients with pneumonia/empyema compared to all others. Conclusion Incidence of GBS and GCGS infections increased due to an expansion of the high-risk population (elderly diabetics), but also rose in non-diabetics. No such secular change was seen for invasive GAS infections. The decrease in mortality in patients with invasive GAS infections presumably reflects better case-management. Adjunctive clindamycin reduced mortality in invasive GAS infections; immunoglobulins did not, but power was limited. The highest mortality was seen in patients with GAS pneumonia/empyema, for whom clindamycin was protective but underused.


title: Relation Classification via Recurrent Neural Network

abstract: Deep learning has gained much success in sentence-level relation classification. For example, convolutional neural networks (CNN) have delivered competitive performance without much effort on feature engineering as the conventional pattern-based methods. Thus a lot of works have been produced based on CNN structures. However, a key issue that has not been well addressed by the CNN-based method is the lack of capability to learn temporal features, especially long-distance dependency between nominal pairs. In this paper, we propose a simple framework based on recurrent neural networks (RNN) and compare it with CNN-based model. To show the limitation of popular used SemEval-2010 Task 8 dataset, we introduce another dataset refined from MIMLRE(Angeli et al., 2014). Experiments on two different datasets strongly indicates that the RNN-based model can deliver better performance on relation classification, and it is particularly capable of learning long-distance relation patterns. This makes it suitable for real-world applications where complicated expressions are often involved.


title: Scientific Workflow: A Survey and Research Directions

abstract: Workflow technologies are emerging as the dominant approach to coordinate groups of distributed services. However with a space filled with competing specifications, standards and frameworks from multiple domains, choosing the right tool for the job is not always a straightforward task. Researchers are often unaware of the range of technology that already exists and focus on implementing yet another proprietary workflow system. As an antidote to this common problem, this paper presents a concise survey of existing workflow technology from the business and scientific domain and makes a number of key suggestions towards the future development of scientific workflow systems.


title: HOP: achieving efficient anonymity in MANETs by combining HIP, OLSR, and pseudonyms

abstract: Offering secure and anonymous communications in mobile ad hoc networking environments is essential to achieve confidence and privacy, thus promoting widespread adoption of this kind of networks. In addition, some minimum performance levels must be achieved for any solution to be practical and become widely adopted. In this paper, we propose and implement HOP, a novel solution based on cryptographic Host Identity Protocol (HIP) that offers security and user-level anonymity in MANET environments while maintaining good performance levels. In particular, we introduce enhancements to the authentication process to achieve Host Identity Tag (HIT) relationship anonymity, along with source/destination HIT anonymity when combined with multihoming. Afterward we detail how we integrate our improved version of HIP with the OLSR routing protocol to achieve efficient support for pseudonyms. We implemented our proposal in an experimental testbed, and the results obtained show that performance levels achieved are quite good, and that the integration with OLSR is achieved with a low overhead.


title: Neutral atmospheric delay in interferometric synthetic aperture radar applications: Statistical description and mitigation

abstract: Variations in the refractive index of the atmosphere cause variations in satellite-based interferometric synthetic aperture radar (InSAR) observations. We can mitigate tropospheric effects by averaging N-independent interferograms. Because the neutral atmosphere is uncorrelated at timescales longer than 1 day, using this technique statistically reduces the variance, σ^2, of the noise by a factor of N. Using zenith neutral atmospheric delays from Global Positioning System (GPS) data from the Southern California Integrated GPS Network, we find that the average variance depends on the distance between observations, L, and height difference, H, as σ = c L^α + kH with estimated values for c, α, and k of about 2.5, 0.5, and 4.8, respectively, where σ is in mm and L and H are in km. We expect that the value of α is largely site-independent but the value of c will depend on the water vapor variability of the area of interest. This model is valid over a range of L between approximately 10 and 800 km. Height differences between 0 and 3 km have been used in this analysis. For distances of 100 and 10 km with negligible height differences, σ is estimated to be approximately 25 and 8 mm, respectively. For a given orbit revisit time and image archive duration, we calculate the number and duration (assumed constant) of interferograms required to achieve a desired sensitivity to deformation rate at a given length scale. Assuming neutral atmosphere is the dominant source of noise, a 30° look angle, and an image revisit time of 7 days, detection of a deformation rate of 1 mm yr^(−1) over distances of 10 km requires about 2.2 years of continuous observations. Given our results, we suggest a data covariance structure to use when using InSAR data to constrain geophysical models.


title: Scalable multi-label Arabic text classification

abstract: Multi-label text classification (MTC) is a natural extension of the traditional text classification (TC) in which a possibly large set of labels can be assigned to each document. The dimensionality of labels makes MTC difficult and challenging. Several ways are proposed to ease the classification process and one of them is called the problem transformation (PT) method. It is used to transform the multi-labeled data into a single-label one that is suitable for normal classification. Our paper presents a detailed study about using the supervised approach to address the MTC problem for Arabic text. Moreover, the scalability of such an approach is considered in our experiments. The MEKA system is used to convert the multi-label data into a single-label one using different PT methods: LC, BR and RT. Then, different classifiers commonly used for TC such as SVM, NB, KNN, and Decision Tree, are applied to each dataset. The results show that using SVM on the LC dataset generated the best results with 71% ML-accuracy.


title: FIJI: A Framework for the Immersion-Journalism Intersection

abstract: As journalists experiment with developing immersive journalism—first-person, interactive experiences of news events—guidelines are needed to help bridge a disconnect between the requirements of journalism and the capabilities of emerging technologies. Many journalists need to better understand the fundamental concepts of immersion and the capabilities and limitations of common immersive technologies. Similarly, developers of immersive journalism works need to know the fundamentals that define journalistic professionalism and excellence and the key requirements of various types of journalistic stories. To address these gaps, we have developed FIJI—a Framework for the Immersion-Journalism Intersection. In FIJI, we have identified four domains of knowledge that intersect to define the key requirements of immersive journalism: the fundamentals of immersion, common immersive technologies, the fundamentals of journalism, and the major types of journalistic stories. Based on these key requirements, we have formally defined four types of immersive journalism that are appropriate for public dissemination. In this paper, we discuss the history of immersive journalism, present the four domains and key intersection of FIJI, and provide a number of guidelines for journalists new to creating immersive experiences.


title: On the comparison of different kernel functionals and neighborhood geometry for nonlocal means filtering

abstract: The present work proposes a review and comparison of different Kernel functionals and neighborhood geometry for Nonlocal Means (NLM) in the task of digital image filtering. Some different alternatives to change the classical exponential kernel function used in NLM methods are explored. Moreover, some approaches that change the geometry of the neighborhood and use dimensionality reduction of the neighborhood or patches onto principal component analysis (PCA) are also analyzed, and their performance is compared with respect to the classic NLM method. Mainly, six approaches were compared using quantitative and qualitative evaluations, to do this an homogeneous framework has been established using the same simulation platform, the same computer, and same conditions for the initializing parameters. According to the obtained comparison, one can say that the NLM filtering could be improved when changing the kernel, particularly for the case of the Tukey kernel. On the other hand, the excellent performance given by recent hybrid approaches such as NLM SAP, NLM PCA (PH), and the BM3D SAPCA lead to establish that significantly improvements to the classic NLM could be obtained. Particularly, the BM3D SAPCA approach gives the best denoising results, however, the computation times were the longest.


title: Applying Machine Learning For High Performance Named-Entity Extraction

abstract: This paper describes a machine learning approach to build an ecien t, accurate and fast name spotting system. Finding names in free text is an important task in addressing real-world textbased applications. Most previous approaches have been based on carefully hand-crafted modules encoding linguistic knowledge specic to the language and document genre. Such approaches have two drawbacks: they require large amounts of time and linguistic expertise to develop, and they are not easily portable to new languages and genres. This paper describes an extensible system which automatically combines weak evidence for name extraction. This evidence is gathered from easily available sources: part-of-speech tagging, dictionary lookups, and textual information such as capitalization and punctuation. Individually, each piece of evidence is insucien t for robust name detection. However, the combination of evidence, through standard machine learning techniques, yields a system that achieves performance equivalent to the best existing hand-crafted approaches.


title: Constructing Strategies in the Indefinitely Repeated Prisoner’s Dilemma Game

abstract: We propose a new approach for running lab experiments on indefinitely repeated games with high continuation probability. This approach has two main advantages. First, it allows us to run multiple long repeated games per session. Second, it allows us to incorporate the strategy method with minimal restrictions on the set of pure strategies that can be implemented. This gives us insight into what happens in long repeated games and into the types of strategies that subjects construct. We report results obtained from the indefinitely repeated prisoner’s dilemma with a continuation probability of δ=.95. We find that during such long repeated prisoner’s dilemma games, cooperation drops from the first period of a supergame to the last period of a supergame. When analyzing strategies, we find that subjects rely on strategies similar to those found in the literature on shorter repeated games—specifically Tit-For-Tat, Grim Trigger, and Always Defect. However, we also identify features of strategies that depend on more than just the previous period that are responsible for the drop in cooperation within supergames, but that may be overlooked when using the common strategy frequency estimation approach.


ARTICULATED-CABLE EXERCISE ROBOT ( PACER ) : NOVEL HOME-BASED CABLE-DRIVEN PARALLEL PLATFORM ROBOT FOR UPPER LIMB NEUROREHABILITATION


title: Psychological health monitoring for pilots and astronauts by tracking sleep-stress-emotion changes

abstract: The effects of stress on human behavior and performance have been well recognized. However, little has been investigated on the impact of psychological stress on pilots and astronauts. Living a life of constantly altered sleeping hours, pilots or astronauts are experiencing sleep stage fragments or long working hours with little or no sleep. The relationship between sleep and stress is reciprocal. Studies have shown that even in low-stress conditions, sleep-deprived participants demonstrate anger and anxiety a lot more frequently than participants with normal sleep quality and hours. In this paper, we introduce a new psychological health-monitoring framework. The prognostics sensors include Actiwatch for sleep monitoring, BioPatch from Zephyr to collect electrocardiogram (ECG) for heart rate and heart rate variability (HRV) for emotion changing monitoring. In this paper, a new Sleep-HRV-Emotion analytical model is proposed to assess the risk of emotion changes in real time. Prognostics analysis and prediction of psychological health is performed based on the proposed new model. Based on the output of the prognostics analysis, several stress intervention strategies are suggested both for the general public as well as for pilots and astronauts in particular. These interventions include the time to rest/sleep, hours of sleep, ultrasound pulses, and Yoga breathing. As such, these intervention strategies help recover, preserve, or improve pilot and astronaut performance, especially during long-duration space flights, and, ultimately, human settlement on other planetary bodies.


Biray rewriting of an operating system kernel


title: Design of a Rule-based Stemmer for Natural Language Text in Bengali

abstract: This paper presents a rule-based approach for finding out the stems from text in Bengali, a resource-poor language. It starts by introducing the concept of orthographic syllable, the basic orthographic unit of Bengali. Then it discusses the morphological structure of the tokens for different parts of speech, formalizes the inflection rule constructs and formulates a quantitative ranking measure for potential candidate stems of a token. These concepts are applied in the design and implementation of an extensible architecture of a stemmer system for Bengali text. The accuracy of the system is calculated to be ~89% and above.


title: Characteristics of Resonance in Heart Rate Variability Stimulated by Biofeedback

abstract: As we previously reported, resonant frequency heart rate variability biofeedback increases baroreflex gain and peak expiratory flow in healthy individuals and has positive effects in treatment of asthma patients. Biofeedback readily produces large oscillations in heart rate, blood pressure, vascular tone, and pulse amplitude via paced breathing at the specific natural resonant frequency of the cardiovascular system for each individual. This paper describes how resonance properties of the cardiovascular system mediate the effects of heart rate variability biofeedback. There is evidence that resonant oscillations can train autonomic reflexes to provide therapeutic effect. The paper is based on studies described in previous papers. Here, we discuss the origin of the resonance phenomenon, describe our procedure for determining an individual's resonant frequency, and report data from 32 adult asthma patients and 24 healthy adult subjects, showing a negative relationship between resonant frequency and height, and a lower resonant frequency in men than women, but no relationship between resonant frequency and age, weight, or presence of asthma. Resonant frequency remains constant across 10 sessions of biofeedback training. It appears to be related to blood volume.


title: COMPUTER-ASSISTED POP-UP DESIGN FOR CHILDREN: COMPUTATIONALLY-ENRICHED PAPER ENGINEERING

abstract: Computationally-enriched crafts are activities that blend the advantages of computational media with the affective, social, and cognitive affordances of children's crafts. In this paper, we describe a design application, Popup Workshop, whose purpose is to introduce children to the craft (and engineering discipline) of pop-up design in paper. We describe the fundamental ideas behind computational crafts in general, present our application in its current implementation and offer a scenario for its use, explore the particular ways in which pop-up design serves as fertile ground for integrating computation and tangible design, and discuss our early pilot tests with elementary-school children, as well as ongoing and related work.


title: An online condition assessment and diagnosis system for traction transformers based on dissolved hydrogen analysis

abstract: Dissolved gas analysis (DGA) has long been recognized as the best method for the detection and identification of incipient faults in power transformers. This work presents an online condition assessment and diagnosis system for traction transformers, based on dissolved hydrogen analysis (DHA), that can provide fault diagnosis and real-time fault alarming for traction transformers.


title: Universally composable two-party and multi-party secure computation

abstract: We show how to securely realize any multi-party functionality in a universally composable way, regardless of the number of corrupted participants. That is, we consider a multi-party network with open communication and an adversary that can adaptively corrupt as many parties as it wishes. In this setting, our protocols allow any subset of the parties (with pairs of parties being a special case) to securely realize any desired functionality of their local inputs, and be guaranteed that security is preserved regardless of the activity in the rest of the network. This implies that security is preserved under concurrent composition of an unbounded number of protocol executions, it implies non-malleability with respect to arbitrary protocols, and more. Our constructions are in the common reference string model and make general intractability assumptions.


title: An analysis of mOSAIC ontology for Cloud resources annotation

abstract: The easiness of managing and configuring resources and the low cost needed for setup and maintaining Cloud services have made Cloud Computing widespread. Several commercial vendors now offer solutions based on Cloud architectures. More and more providers offer new different services every month, following their customers needs. Anyway, it is very hard to find a single provider which offers all services needed by end users. Furthermore, different vendors propose different architectures for their Cloud systems and usually these are not compatible. Very few efforts have been done in order to propose a unified standard for Cloud Computing. This is a problem, since different Cloud systems and vendors have different ways to describe and invoke their services, to specify requirements and to communicate. Hence a way to provide a common access to Cloud services and to discover and use required services in Cloud federations is appealing. mOSAIC project addresses these problems by defining a common ontology and it aims at developing an open-source platform that enables applications to negotiate Cloud services as requested by users. The main problem in defining the mOSAIC ontology is in the heterogeneity of terms used by Clouds vendors, and in the number of standards which refer to Cloud Systems with different terminology. In this work the mOSAIC Cloud Ontology is described. It has been built by analysing Cloud standards and proposals. The Ontology has been then refined by introducing individuals from real Cloud systems.


title: Photopiezoelectric Composites of Azobenzene-Functionalized Polyimides and Polyvinylidene Fluoride

abstract: Abstract : Light is a readily available and sustainable energy source. Transduction of light into mechanical work or electricity in functional materials, composites, or systems has other potential advantages derived from the ability to remotely, spatially, and temporally control triggering by light. Toward this end, this work examines photoinduced piezoelectric (photopiezoelectric) effects in laminate composites prepared from photoresponsive polymeric materials and the piezoelectric polymer polyvinylidene fluoride (PVDF). In the geometry studied here, photo piezoelectric conversion is shown to strongly depend on the photomechanical proper-ties inherent to the azobenzene-functionalized polyimides. Based on prior examinations of photo mechanical effects in azobenzene-functionalized polyimides, this investigation focuses on amorphous materials and systematically varies the concentration of azobenzene in the copolymers. The baseline photomechanical response of the set of polyimides is characterized in cantilever deflection experiments. To improve the photo-mechanical response of the materials and enhance the electrical conversion, the polyimides are drawn to increase the magnitude of the deflection as well as photogenerated stress. In laminate composites, the photomechanical response of the materials in sequenced light exposure is shown to transduce light energy into electrical energy. The frequency of the photopiezoelectric response of the composite can match the frequency of the sequenced light exposing the films.


Are Games Effective Learning Tools? A Review of Educational Games


title: Frequency-division techniques for microwave power transfer and wireless communication system with closed waveguide

abstract: Microwave power transfer is expected to support various applications. However, there are strict regulations for radio emissions and leakage levels. We attempt to avoid the regulation and transmission loss in free space by employing a waveguide method for microwave power transfer. We experimentally investigated the frequency-division multiple access techniques as a method of microwave power and communication transmission. Results indicated that the communication quality did not deteriorate for a carrier frequency distance of 7–8 MHz between the microwave power carrier and each modulated signal. The experimental prototype of the microwave power transfer system comprising a batteryless and powerless ZigBee communication unit confirmed continuous operation and use of the waveguide wireless system.


title: Ml-rbf: RBF Neural Networks for Multi-Label Learning

abstract: Multi-label learning deals with the problem where each instance is associated with multiple labels simultaneously. The task of this learning paradigm is to predict the label set for each unseen instance, through analyzing training instances with known label sets. In this paper, a neural network based multi-label learning algorithm named Ml-rbf is proposed, which is derived from the traditional radial basis function (RBF) methods. Briefly, the first layer of an Ml-rbf neural network is formed by conducting clustering analysis on instances of each possible class, where the centroid of each clustered groups is regarded as the prototype vector of a basis function. After that, second layer weights of the Ml-rbf neural network are learned by minimizing a sum-of-squares error function. Specifically, information encoded in the prototype vectors corresponding to all classes are fully exploited to optimize the weights corresponding to each specific class. Experiments on three real-world multi-label data sets show that Ml-rbf achieves highly competitive performance to other well-established multi-label learning algorithms.


title: Automated Big Traffic Analytics for Cyber Security

abstract: Network traffic analytics technology is a cornerstone for cyber security systems. We demonstrate its use through three popular and contemporary cyber security applications in intrusion detection, malware analysis and botnet detection. However, automated traffic analytics faces the challenges raised by big traffic data. In terms of big data's three characteristics --- volume, variety and velocity, we review three state of the art techniques to mitigate the key challenges including real-time traffic classification, unknown traffic classification, and efficiency of classifiers. The new techniques using statistical features, unknown discovery and correlation analytics show promising potentials to deal with big traffic data. Readers are encouraged to devote to improving the performance and practicability of automatic traffic analytic in cyber security.


title: Structured Deep Neural Network Pruning by Varying Regularization Parameters.

abstract: Convolutional Neural Networks (CNN's) are restricted by their massive computation and high storage. Parameter pruning is a promising approach for CNN compression and acceleration, which aims at eliminating redundant model parameters with tolerable performance loss. Despite its effectiveness, existing regularization-based parameter pruning methods usually assign a fixed regularization parameter to all weights, which neglects the fact that different weights may have different importance to CNN. To solve this problem, we propose a theoretically sound regularization-based pruning method to incrementally assign different regularization parameters to different weights based on their importance to the network. On AlexNet and VGG-16, our method can achieve 4x theoretical speedup with similar accuracies compared with the baselines. For ResNet-50, the proposed method also achieves 2x acceleration and only suffers 0.1% top-5 accuracy loss.


Enhanced English Universal Dependencies: An Improved Representation for Natural Language Understanding Tasks.


title: Learning Bayesian Networks is NP-Complete

abstract: Algorithms for learning Bayesian networks from data have two components: a scoring metric and a search procedure. The scoring metric computes a score reflecting the goodness-of-fit of the structure to the data. The search procedure tries to identify network structures with high scores. Heckerman et al. (1995) introduce a Bayesian metric, called the BDe metric, that computes the relative posterior probability of a network structure given data. In this paper, we show that the search problem of identifying a Bayesian network—among those where each node has at most K parents—that has a relative posterior probability greater than a given constant is NP-complete, when the BDe metric is used.


title: Local and Wide-Area PMU-Based Decentralized Dynamic State Estimation in Multi-Machine Power Systems

abstract: Accurate measurement of the rotor angle and speed of synchronous generators is instrumental in developing powerful local or wide-area control and monitoring systems to enhance power grid stability and reliability. Exogenous input signals such as field voltage and mechanical torque are critical information in this context, but obtaining them raises significant logistical challenges, which in turn complicates the estimation of the generator dynamic states from easily available terminal phasor measurement unit (PMU) signals only. To overcome these issues, the authors of this paper employ the extended Kalman filter with unknown inputs, referred to as the EKF-UI technique, for decentralized dynamic state estimation of a synchronous machine states using terminal active and reactive powers, voltage phasor and frequency measurements. The formulation is fully decentralized without single-machine infinite bus (SMIB) or excitation model assumption so that only local information is required. It is demonstrated that using the decentralized EKF-UI scheme, synchronous machine states can be estimated accurately enough to enable wide-area power system stabilizers (WA-PSS) and system integrity protection schemes (SIPS). Simulation results on New-England test system, Hydro-Quebec simplified system, and Kundur network highlight the efficiency of the proposed method under fault conditions with electromagnetic transients and full-order generator models in realistic multi-machine setups.


Study on Sustainable Development of the Transnational Power Grid Interconnection Projects under Diversified Risks Based on Variable Weight Theory and Bayesian Network


title: CAE-RLSM: Consistent and Efficient Redundant Line Segment Merging for Online Feature Map Building

abstract: In order to obtain a compact line segment-based map representation for localization and planning of mobile robots, it is necessary to merge redundant line segments which physically represent the same part of the environment in different scans. In this work, a consistent and efficient redundant line segment merging approach (CAE-RLSM) is proposed for online feature map building. The proposed CAE-RLSM is composed of two newly proposed modules: one-to-many incremental line segment merging (OTM-ILSM) and multi-processing global map adjustment (MP-GMA). Different from state-of-the-art offline merging approaches, the proposed CAE-RLSM can achieve real-time mapping performance, which not only reduces the redundancy of incremental merging with high efficiency, but also solves the problem of global map adjustment after loop closing to guarantee global consistency. Furthermore, a new correlation-based metric is proposed for the quality evaluation of line segment maps. This evaluation metric does not require manual measurement of the environmental metric information, instead it makes full use of globally consistent laser scans obtained by simultaneous localization and mapping (SLAM) systems to compare the performance of different line segment-based mapping approaches in an objective and fair manner. Comparative experimental results with respect to a mean shift-based offline redundant line segment merging approach (MS-RLSM) and an offline version of one-to-one incremental line segment merging approach (O2TO-ILSM) on both public datasets and self-recorded dataset are presented to show the superior performance of CAE-RLSM in terms of efficiency and map quality in different scenarios.


title: Identification of opinion leaders in social network

abstract: Identification of the opinion leaders in the world's largest microblogging site, Twitter, is crucial problem of social network analysis. Twitter has quick information flow and has high impact on forming opinion on mass public. This paper presents the study based on various centrality mesaure approaches for finding key players for a specific political trend on Twitter. A novel weighted approach has been proposed for finding opinion leaders based on the centrality measures. Experiment has been conducted on the Twitter's data for the sit in procession of Pakistani politician Imran Khan in 2014. It has been found that Twitter opinion leadership makes a significant contribution to individuals' involvement in political reforms.


title: Projected Changes in Wet-Bulb Globe Temperature under Alternative Climate Scenarios

abstract: The increased levels of Greenhouse Gasses (GHGs) in the atmosphere will result in increased near-surface air temperature and absolute humidity. These two factors increasingly pose a risk of heat stress to humans. The Wet-Bulb Globe Temperature (WBGT) is a widely used and validated index for assessing the environmental heat stress. Using the output from the Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations of the four Representative Concentration Pathways (RCPs), we calculated the global and regional changes in WBGT. Globally, the WBGT is projected to increase by 0.6–1.7 °C for RCP 2.6 and 2.37–4.4 °C for RCP 8.5. At the regional scale, our analysis suggests a disproportionate increase in the WBGT over northern India, China, northern Australia, Africa, Central America and Southeast Asia. An increase in WBGT has consequences not only on human health but also on social and economic factors. These consequences may be exacerbated in developing economies, which are less able to adapt to the changing environmental conditions.


title: AZR-LEACH: An Energy Efficient Routing Protocol for Wireless Sensor Networks

abstract: Reducing the energy consumption of available resources is still a problem to be solved in Wireless Sensor Networks (WSNs). Many types of existing routing protocols are developed to save power consumption. In these protocols, cluster-based routing protocols are found to be more energy efficient. A cluster head is selected to aggregate the data received from root nodes and forwards these data to the base station in cluster-based routing. The selection of cluster heads should be efficient to save energy. In our proposed protocol, we use static clustering for the efficient selection of cluster heads. The proposed routing protocol works efficiently in large as well as small areas. For an optimal number of cluster head selection we divide a large sensor field into rectangular clusters. Then these rectangular clusters are further grouped into zones for efficient communication between cluster heads and a base station. We perform MATLAB simulations to observe the network stability, throughput, energy consumption, network lifetime and the number of cluster heads. Our proposed routing protocol outperforms in large areas in comparison with the LEACH, MH-LEACH, and SEP routing protocols.


title: Psychosocial Factors That Shape Patient and Carer Experiences of Dementia Diagnosis and Treatment: A Systematic Review of Qualitative Studies

abstract: Background ::: Early diagnosis and intervention for people with dementia is increasingly considered a priority, but practitioners are concerned with the effects of earlier diagnosis and interventions on patients and caregivers. This systematic review evaluates the qualitative evidence about how people accommodate and adapt to the diagnosis of dementia and its immediate consequences, to guide practice. ::: Methods and Findings ::: We systematically reviewed qualitative studies exploring experiences of community-dwelling individuals with dementia, and their carers, around diagnosis and the transition to becoming a person with dementia. We searched PubMed, PsychINFO, Embase, CINAHL, and the British Nursing Index (all searched in May 2010 with no date restrictions; PubMed search updated in February 2012), checked reference lists, and undertook citation searches in PubMed and Google Scholar (ongoing to September 2011). We used thematic synthesis to identify key themes, commonalities, barriers to earlier diagnosis, and support identified as helpful. We identified 126 papers reporting 102 studies including a total of 3,095 participants. Three overarching themes emerged from our analysis: (1) pathways through diagnosis, including its impact on identity, roles, and relationships; (2) resolving conflicts to accommodate a diagnosis, including the acceptability of support, focusing on the present or the future, and the use or avoidance of knowledge; and (3) strategies and support to minimise the impact of dementia. Consistent barriers to diagnosis include stigma, normalisation of symptoms, and lack of knowledge. Studies report a lack of specialist support particularly post-diagnosis. ::: Conclusions ::: There is an extensive body of qualitative literature on the experiences of community-dwelling individuals with dementia on receiving and adapting to a diagnosis of dementia. We present a thematic analysis that could be useful to professionals working with people with dementia. We suggest that research emphasis should shift towards the development and evaluation of interventions, particularly those providing support after diagnosis. ::: ::: Please see later in the article for the Editors' Summary.


title: Active stiffness control of a manipulator in cartesian coordinates

abstract: A method of actively controlling the apparent stiffness of a manipulator end effecter is presented. The approach allows the programmer to specify the three transnational and three rotational stiffness of a frame located arbitrarily in hand coordinates. Control of the nominal position of the hand then permits simultaneous position and force control. Stiffness may be changed under program control to match varying task requirements. A rapid servo algorithm is made possible by transformation of the problem into joint space at run time. Applications examples are given.


title: Community response grids: E-government, social networks,

abstract: This paper explores the concept of developing community response grids (CRGs) for community emergency response and the policy implications of such a system. CRGs make use of the Internet and mobile communication devices, allowing residents and responders to share information, communicate, and coordinate activities in response to a major disaster. This paper explores the viability of using mobile communication technologies and the Web, including e-government, to develop response systems that would aid communities before, during, and after a major disaster, providing channels for contacting residents and responders, uploading information, distributing information, coordinating the responses of social networks, and facilitating resident-to-resident assistance. Drawing upon research from computer science, information studies, public policy, emergency management, and several other disciplines, the paper elaborates on the concept of and need for CRGs, examines related current efforts that can inform the development of CRGs, discusses how research about community networks can be used to instill trust and social capital in CRGs, and examines the issues of public policy, telecommunications, and e-government related to such a system.


title: Interacting dynamic Wannier-Stark ladder driven by a periodic pulse train

abstract: The electronic structures of the Floquet states of the dynamic Wannier-Stark ladder (DWSL) are examined, where the DWSL is formed by driving the biased superlattices (SLs) by the periodic pulse train (PPT) with the electric field $F(t)$\char22{}with time $t$\char22{}and the temporal period $2\ensuremath{\pi}∕\ensuremath{\omega}$. For a strong $F(t)$, interminiband interactions, namely, the ac-Zener tunneling (ac-ZT), are predominantly caused in the DWSL. Such a system is termed the interacting DWSL. In order to understand the details of the Floquet states and the modulation patterns by alteration of a couple of the PPT laser parameters, the linear absorption spectra, ${\ensuremath{\alpha}}_{\mathit{abs}}({\ensuremath{\omega}}_{p};\ensuremath{\omega})$, of optical interband transitions invoked by the monochromatic probe laser ${f}_{p}(t)$ with the frequency ${\ensuremath{\omega}}_{p}$ are calculated, where the spectra are not only linear in ${f}_{p}(t)$ but also nonlinear in $F(t)$. The exciton effect is not included for the sake of simplicity. For the PPT driving with unit-pulse shapes largely deviated from the square and saw-toothed profiles, the spectra show unexpected dent structures, differing a great deal from the corresponding ac-ZT-free spectra basically similar to those of the original SLs just showing the ascending steplike structure. To deepen the understanding of this anomaly, the spectra of ${\ensuremath{\alpha}}_{\mathit{abs}}^{0}({\ensuremath{\omega}}_{p};\ensuremath{\omega})\ensuremath{\propto}\ensuremath{\partial}{\ensuremath{\alpha}}_{\mathit{abs}}({\ensuremath{\omega}}_{p};\ensuremath{\omega})∕\ensuremath{\partial}{\ensuremath{\omega}}_{p}$ are also calculated, whereby the dent structures become spectral dips showing the negative absorption. It is found that such anomalous behavior is attributed to the ac-ZT between different minibands that accompanies emission/absorption of the nonzero net number of photons with $J\ensuremath{\omega}$ (with $J$ a nonzero integer). This anomaly also shows the unusual time dependence in the dual-time optical susceptibility associated with ${\ensuremath{\alpha}}_{\mathit{abs}}^{0}({\ensuremath{\omega}}_{p};\ensuremath{\omega})$. Moreover, the possibility of existence of the negative absorption in the more realistic excitonic spectra is speculated.


title: Mechanical properties and cell cultural response of polycaprolactone scaffolds designed and fabricated via fused deposition modeling.

abstract: A number of different processing techniques have been developed to design and fabricate three-dimensional (3D) scaffolds for tissue-engineering applications. The imperfection of the current techniques has encouraged the use of a rapid prototyping technology known as fused deposition modeling (FDM). Our results show that FDM allows the design and fabrication of highly reproducible bioresorbable 3D scaffolds with a fully interconnected pore network. The mechanical properties and in vitro biocompatibility of polycaprolactone scaffolds with a porosity of 61 ± 1% and two matrix architectures were studied. The honeycomb-like pores had a size falling within the range of 360 × 430 × 620 μm. The scaffolds with a 0/60/120° lay-down pattern had a compressive stiffness and a 1% offset yield strength in air of 41.9 ± 3.5 and 3.1 ± 0.1 MPa, respectively, and a compressive stiffness and a 1% offset yield strength in simulated physiological conditions (a saline solution at 37 °C) of 29.4 ± 4.0 and 2.3 ± 0.2 MPa, respectively. In comparison, the scaffolds with a 0/72/144/36/108° lay-down pattern had a compressive stiffness and a 1% offset yield strength in air of 20.2 ± 1.7 and 2.4 ± 0.1 MPa, respectively, and a compressive stiffness and a 1% offset yield strength in simulated physiological conditions (a saline solution at 37 °C) of 21.5 ± 2.9 and 2.0 ± 0.2 MPa, respectively. Statistical analysis confirmed that the five-angle scaffolds had significantly lower stiffness and 1% offset yield strengths under compression loading than those with a three-angle pattern under both testing conditions (p ≤ 0.05). The obtained stress–strain curves for both scaffold architectures demonstrate the typical behavior of a honeycomb structure undergoing deformation. In vitro studies were conducted with primary human fibroblasts and periosteal cells. Light, environmental scanning electron, and confocal laser microscopy as well as immunohistochemistry showed cell proliferation and extracellular matrix production on the polycaprolactone surface in the 1st culturing week. Over a period of 3–4 weeks in a culture, the fully interconnected scaffold architecture was completely 3D-filled by cellular tissue. Our cell culture study shows that fibroblasts and osteoblast-like cells can proliferate, differentiate, and produce a cellular tissue in an entirely interconnected 3D polycaprolactone matrix. © 2001 John Wiley & Sons, Inc. J Biomed Mater Res 55: 203–216, 2001


title: Discriminative FaceTopics for face recognition via latent Dirichlet allocation

abstract: Latent Dirichlet Allocation is a widely used approach for topic modeling and it has been successfully applied in several information retrieval applications. In this paper, we introduce this modeling technique for face recognition, by making an analogy between the two domains. We utilize latent Dirichlet allocation to represent facial regions in terms of FaceTopics. Further, linear discriminant analysis is utilized to obtain discriminative FaceTopics which are more suitable for classification tasks. The performance of the proposed approach is evaluated on the CMU-MultiPIE dataset under illumination and expression variations. The evaluation on over more than 50k images shows the effectiveness of the proposed approach. Further, the proposed approach shows improved identification results on e-PRIP dataset for matching composite sketches to photos.


title: Autism: cognitive deficit or cognitive style?

abstract: Autism is a developmental disorder characterized by impaired social and communicative development, and restricted interests and activities. This article will argue that we can discover more about developmental disorders such as autism through demonstrations of task success than through examples of task failure. Even in exploring and explaining what people with autism find difficult, such as social interaction, demonstration of competence on contrasting tasks has been crucial to defining the nature of the specific deficit. Deficit accounts of autism cannot explain, however, the assets seen in this disorder; for example, savant skills in maths, music and drawing, and islets of ability in visuospatial tests and rote memory. An alternative account, reviewed here, suggests that autism is characterized by a cognitive style biased towards local rather than global information processing - termed 'weak central coherence'. Evidence that weak coherence might also characterize the relatives of people with autism, and form part of the extended phenotype of this largely genetic disorder, is discussed. This review concludes by considering some outstanding questions concerning the specific cognitive mechanism for coherence and the neural basis of individual differences in this aspect of information processing.


title: High temperature nanoindentation hardness and Young’s modulus measurement in a neutron-irradiated cladding material

abstract: Abstract Nanoindentation, in combination with scanning probe microscopy, has been used to measure the hardness and Young's modulus in the hydride and matrix of a high burn-up neutron-irradiated Zircaloy-2 cladding material in the temperature range 25–300 °C. The matrix hardness was found to decrease only slightly with increasing temperature while the hydride hardness was essentially constant within the temperature range. Young's modulus decreased with increasing temperature for both the hydride and the matrix of the high burn-up fuel cladding material. The hydride Young's modulus and hardness were higher than those of the matrix in the temperature range.


title: Ultra-low-resistance 3D InFO inductors for integrated voltage regulator applications

abstract: A novel 3D InFO inductor is developed to integrate with TSMC 16nm FinFET devices for high efficiency integrated voltage regulator (IVR) design. The 3D InFO inductor is designed using thick through-InFO-via (TIV) copper, where the form factor is 1.4 × 2.2 × 0.15 mm3. It performs 2.14 nH inductance at 140 MHz and 3.2 mΩ resistance at DC. The resistance of power delivery network (PDN) between inductor and load is 1.1 mu. The InFO technology provides the low resistance 3D inductor and PDN concurrently for the IVR system design to achieve a peak power efficiency of 93%.


title: On-chip power-on reset strategy and I/O power supply detection for VLSI circuits

abstract: Many of the complex VLSI systems have separate I/O and core supplies and follow a predefined power up sequence. In this paper an on-chip power-on reset (POR) strategy and an I/O power supply detection circuit with low steady-state power consumption are proposed. Our technique allows the I/O power supply monitoring, independently from the core power supplies. The I/O power supply detection circuit can detect both ramp up and ramp down of the supply voltage and has a fixed detection threshold. The circuit can operate for any I/O supply voltage level ranging from 1.5V to 3.3V. Simulation results show a maximum steady state power consumption of 23µW. Due to this fact the proposed POR circuit is suitable for low power applications and embedding in portable device systems.


title: A low-cost soft-switching high step-up flyback converter with stacked output cells

abstract: A low-cost isolated high step-up dc-dc converter with a single switch and multiple output cells is proposed. The magnetizing inductance of the multiple-winding transformer and a multitude of capacitors are used to form a parallel LC resonant link. The capacitors create a Zero Voltage Switching (ZVS) condition at turn-on and turn-off and reduce the switching losses of the switch and diodes. Rate of voltage change (dv/dt) on all semiconductors is limited by the link capacitors, and the diodes turn off with suppressed reverse recovery transients. The converter requires no auxiliary clamps or switches to achieve soft-switching. An analytical approach is developed to establish a relationship between link parameters, input and output voltages, and link frequency. Experimental results on a 60 V to 600 V converter at 250 W are included to corroborate the design and operation.


title: Seed Selection for Spread of Influence in Social Networks: Temporal vs. Static Approach

abstract: The problem of finding optimal set of users for influencing others in the social network has been widely studied. Because it is NP-hard, some heuristics were proposed to find sub-optimal solutions. Still, one of the commonly used assumption is the one that seeds are chosen on the static network, not the dynamic one. This static approach is in fact far from the real-world networks, where new nodes may appear and old ones dynamically disappear in course of time. The main purpose of this paper is to analyse how the results of one of the typical models for spread of influence - linear threshold - differ depending on the strategy of building the social network used later for choosing seeds. To show the impact of network creation strategy on the final number of influenced nodes - outcome of spread of influence, the results for three approaches were studied: one static and two temporal with different granularities, i.e. various number of time windows. Social networks for each time window encapsulated dynamic changes in the network structure. Calculation of various node structural measures like degree or betweenness respected these changes by means of forgetting mechanism - more recent data had greater influence on node measure values. These measures were, in turn, used for node ranking and their selection for seeding. All concepts were applied to experimental verification on five real datasets. The results revealed that temporal approach is always better than static and the higher granularity in the temporal social network while seeding, the more finally influenced nodes. Additionally, outdegree measure with exponential forgetting typically outperformed other time-dependent structural measures, if used for seed candidate ranking.


title: Prevalence of K13-propeller polymorphisms in Plasmodium falciparum from China-Myanmar border in 2007–2012

abstract: BackgroundThe recent emergence and spread of artemisinin resistance in the Greater Mekong Subregion poses a great threat to malaria control and elimination. A K13-propeller gene (K13), PF3D7_1343700, has been associated lately with artemisinin resistance both in vitro and in vivo. This study aimed to investigate the K13 polymorphisms in Plasmodium falciparum parasites from the China-Myanmar border area where artemisinin use has the longest history.MethodsA total of 180 archived P. falciparum isolates containing 191 parasite clones, mainly collected in 2007–2012 from the China-Myanmar area, were used to obtain the full-length K13 gene sequences.ResultsSeventeen point mutations were identified in 46.1% (88/191) parasite clones, of which seven were new. The F446I mutation predominated in 27.2% of the parasite clones. The C580Y mutation that is correlated with artemisinin resistance was detected at a low frequency of 1.6%. Collectively, 43.1% of the parasite clones contained point mutations in the kelch domain of the K13 gene. Moreover, there was a trend of increase in the frequency of parasites carrying kelch domain mutations through the years of sample collection. In addition, a microsatellite variation in the N-terminus of the K13 protein was found to have reached a high frequency (69.1%).ConclusionsThis study documented the presence of mutations in the K13 gene in parasite populations from the China-Myanmar border. Mutations present in the kelch domain have become prevalent (>40%). A predominant mutation F446I and a prevalent microsatellite variation in the N-terminus were identified, but their importance in artemisinin resistance remains to be elucidated.


title: Privacy-Preserving Detection of Sensitive Data Exposure

abstract: Statistics from security firms, research institutions and government organizations show that the number of data-leak instances have grown rapidly in recent years. Among various data-leak cases, human mistakes are one of the main causes of data loss. There exist solutions detecting inadvertent sensitive data leaks caused by human mistakes and to provide alerts for organizations. A common approach is to screen content in storage and transmission for exposed sensitive information. Such an approach usually requires the detection operation to be conducted in secrecy. However, this secrecy requirement is challenging to satisfy in practice, as detection servers may be compromised or outsourced. In this paper, we present a privacy-preserving data-leak detection (DLD) solution to solve the issue where a special set of sensitive data digests is used in detection. The advantage of our method is that it enables the data owner to safely delegate the detection operation to a semihonest provider without revealing the sensitive data to the provider. We describe how Internet service providers can offer their customers DLD as an add-on service with strong privacy guarantees. The evaluation results show that our method can support accurate detection with very small number of false alarms under various data-leak scenarios.