title: Development of 300 mm TSV interposer with redistribution layers on both sides using MEMS processes

abstract: A Silicon interposer with through silicon via (TSV) has become important key components of 3D integration. It is used as an intermediate carrier and a wiring device for IC components like logics, memories, sensors, and so on. Due to wiring with custom design on front and back side, a TSV interposer enables to adapt the fine pitch IO terminals of the mounted ICs to the IO geometries of the package level. However the key problem facing the TSV interposer is a cost issue. In this paper, TSV based interposer fabrication process for 3D packaging has been presented and the process uniformity with 300 mm wafer was evaluated for cost reduction and yield improvement. TSVs of 50 μm in diameter were formed on a 300 mm wafer of 500 μm in thickness by deep reactive ion etching (DRIE) process and the vias were isolated with SiO2 layer, followed by barrier/seed layers of Ti/Cu deposition. The TSVs were filled with solid Copper (Cu) using electroplating of optimized periodic pulse reverse (PPR) and chemical mechanical polishing (CMP) process also developed to remove the Cu overburden. For void free TSV interconnects and uniformity improvement, the Cu electroplating process was simulated with 300 mm wafer and developed with the simulation result. The process uniformity of Cu electroplating was equivalent to the simulation result and void free TSV interconnects were successfully formed. The RDL lines were formed on the TSV by Cu electroplating and the RDL lines were electrically isolated with the dielectric PBO film. The TSV interposer of 500 μm thickness has been fabricated successfully with MEMS processes and the vias were in good conductivity from the top to the bottom. The distribution of via etching process, via filling process and CMP process were evaluated and no significant failures were observed. The uniformity of the via etching process was less than 5 %. The distribution of Cu overburden thickness was less than 100 μm. The dishing amount of Cu via after CMP was less than 10 μm. The electric characteristics of RDL leakage current and via resistance were measured. The leakage current between RDL lines was about 10-9 A so that the RDL lines were electrically isolated. The average value of via resistances was 2.43 ohm and via resistances were normally distributed with tangible electric characteristics. The fabrication process of TSV based silicon interposer with 300 mm wafer by MEMS processes was successfully demonstrated in terms of mass production.


title: Video frame-matching algorithm using dynamic programming

abstract: We propose a frame-matching algorithm for video sequences, when a video sequence is modified from its original through frame removal, insertion, shuffling, and data compression. The proposed matching algorithm defines an effective matching cost function and minimizes cost using dynamic programming. Experimental results show that the proposed algorithm provides a significantly lower probability of matching errors than the conventional algorithm.


title: Smart Contract Templates: foundations, design landscape and research directions

abstract: In this position paper, we consider some foundational topics regarding smart contracts (such as terminology, automation, enforceability, and semantics) and define a smart contract as an automatable and enforceable agreement. We explore a simple semantic framework for smart contracts, covering both operational and non-operational aspects, and describe templates and agreements for legally-enforceable smart contracts, based on legal documents. Building upon the Ricardian Contract, we identify operational parameters in the legal documents and use these to connect legal agreements to standardised code. We also explore the design landscape, including increasing sophistication of parameters, increasing use of common standardised code, and long-term research.


title: Empirical Validation of Variable based Test Case Prioritization/Selection Technique

abstract: Regression test case prioritization optimizes the ordering of test cases to be executed to meet some criteria like maximum code coverage or high rate of fault detection. In prior work we prioritized test cases according to a hybrid technique using variable based method that combined both selection and prioritization. We inferred in our approach that variables are vital source of changes in the program and test cases should be prioritized according to the variables of any changed statement and variables computed from the variables of changed statements. In support of our prioritization approach we extend our work to validate the effectiveness of prioritized test cases with respect to data flow technique. This paper reports an experimental study investigating the effectiveness of our prioritization approach given in [2] by considering programs. The results obtained are encouraging and support our work to validate the prioritization technique with respect to DU/DC paths of data flow testing technique.


title: A polynomial time approximation scheme for minimum routing cost spanning trees

abstract: Given an undirected graph with nonnegative costs on the edges, the routing cost of any of its spanning trees is the sum over all pairs of vertices of the cost of the path between the pair in the tree. Finding a spanning tree of minimum routing cost is NP-hard, even when the costs obey the triangle inequality. We show that the general case is in fact reducible to the metric case and present a polynomial-time approximation scheme valid for both versions of the problem. In particular, we show how to build a spanning tree of an n-vertex weighted graph with routing cost at most $(1+\epsilon)$ of the minimum in time $O(n^{O({\frac{1}{\epsilon}}% )})$. Besides the obvious connection to network design, trees with small routing cost also find application in the construction of good multiple sequence alignments in computational biology. ::: The communication cost spanning tree problem is a generalization of the minimum routing cost tree problem where the routing costs of different pairs are weighted by different requirement amounts. We observe that a randomized O(log n log log n)-approximation for this problem follows directly from a recent result of Bartal, where n is the number of nodes in a metric graph. This also yields the same approximation for the generalized sum-of-pairs alignment problem in computational biology.


title: DWT and BPNN based fault detection, classification and estimation of location of HVAC transmission line

abstract: The paper presents a technique for detection classification and diagnosis of fault location on overhead transmission lines for different types of fault. Discrete wavelet transform (DWT) has been used for extraction of features of signals of current under faulted condition and back propagation neural network (BPNN) have been used for training the features of current signal for different fault location. It has been found that the coefficients of discrete wavelet transform of fault signal and BPNN satisfactorily detect, classify and locate the fault location.


title: Robot assisted gait training with active leg exoskeleton (ALEX)

abstract: Gait training of stroke survivors is crucial to facilitate neuromuscular plasticity needed for improvements in functional walking ability. Robot assisted gait training (RAGT) was developed for stroke survivors using active leg exoskeleton (ALEX) and a force-field controller, which uses assist-as-needed paradigm for rehabilitation. In this paradigm undesirable gait motion is resisted and assistance is provided towards desired motion. The force-field controller achieves this paradigm by effectively applying forces at the ankle of the subject through actuators on the hip and knee joints. Two stroke survivors participated in a 15-session gait training study each with ALEX. The results show that by the end of the training the gait pattern of the patients improved and became closer to a healthy subject's gait pattern. Improvement is seen as an increase in the size of the patients' gait pattern, increased knee and ankle joint excursions and increase in their walking speeds on the treadmill.


title: Multi-agent-based smart cargo tracking system

abstract: Cargo tracking system plays an important role in logistics and supply chain management. This paper presents an agent-based intelligent cargo tracking system including agent structures and system architecture which is based on the internet of things. At first, the concept and methods of cargo information modelling are introduced. Cargo information includes static information and dynamic information. The cargo information model can be used in the whole life cycle of a cargo and includes all information needed for logistics chain management. Then, the cargo information contents and structure are explained prior to the proposed intelligent cargo tracking system. In this system, a model that includes all information needed in logistics chain management is used in the tracking of a product lifecycle. The paper illustrates the implementation of the proposed intelligent cargo tracking system and its application. Effective monitoring and controlling of the entire cargo conveyance process with anytime-anywhere features is implemented.


A Review of Digital Image Steganography using LSB and LSB Array


title: ProbView: a flexible probabilistic database system

abstract: Probability theory is mathematically the best understood paradigm for modeling and manipulating uncertain information. Probabilities of complex events can be computed from those of basic events on which they depend, using any of a number of strategies. Which strategy is appropriate depends very much on the known interdependencies among the events involved. Previous work on probabilistic databases has assumed a fixed and restrictive combination strategy (e.g., assuming all events are pairwise independent). In this article, we characterize, using postulates, whole classes of strategies for conjunction, disjunction, and negation, meaningful from the viewpoint of probability theory. (1) We propose a probabilistic relational data model and a generic probabilistic relational algebra that neatly captures various strategies satisfying the postulates, within a single unified framework. (2) We show that as long as the chosen strategies can be computed in polynomial time, queries in the positive fragment of the probabilistic relational algebra have essentially the same data complexity as classical relational algebra. (3) We establish various containments and equivalences between algebraic expressions, similar in spirit to those in classical algebra. (4) We develop algorithms for maintaining materialized probabilistic views. (5) Based on these ideas, we have developed a prototype probabilistic database system called ProbView on top of Dbase V.0. We validate our complexity results with experiments and show that rewriting certain types of queries to other equivalent forms often yields substantial savings.


title: Follow-up study identifies two novel susceptibility loci PRKCB and 8p11.21 for systemic lupus erythematosus.

abstract: OBJECTIVE ::: We have performed a large-scale replication study based on our previous genome-wide association study (GWAS) of SLE in the Chinese Han population to further explore additional genetic variants affecting susceptibility to SLE. ::: ::: ::: METHODS ::: Thirty-eight single nucleotide polymorphisms from our GWAS were genotyped in two additional Chinese Han cohorts (total 3152 cases and 7050 controls) using the Sequenom Massarray system. Association analyses were performed using logistic regression with gender or sample cohorts as a covariate. ::: ::: ::: RESULTS ::: Association evidence for rs16972959 (PRKCB at 16p11.2) and rs12676482 (8p11.21) with SLE was replicated independently in both replication cohorts (P < 0.05), showing high significance for SLE in combined all 4199 cases and 8255 controls of Chinese Han [rs16972959: odds ratio (OR) = 0.81; 95% CI 0.76, 0.87; P(combined) = 1.35 × 10(-9); rs12676482: OR = 1.26; 95% CI 1.15, 1.38; P(combined) = 6.68 × 10(-7)). PRKCB is related to the established SLE immune-related pathway (NF-κB) and 8p11.21 contains important candidate genes such as IKBKB and DKK4. IKBKB is a critical component of NF-κB and DKK4 is an inhibitor of canonical Wnt signalling pathway. Interestingly, PRKCB is required for recruiting IKBKB into lipid rafts, up-regulating NF-κB-dependent survival signal. ::: ::: ::: CONCLUSIONS ::: Our findings provided novel insights into the genetic architecture of SLE and emphasized the contribution of multiple variants of modest effect. Further study focused on PRKCB, 8p11.21, should advance our understanding on the pathogenesis of SLE.


Classification of Brain MR Images using Texture Feature Extraction


title: Defects in IL-2R Signaling Contribute to Diminished Maintenance of FOXP3 Expression in CD4+CD25+ Regulatory T-Cells of Type 1 Diabetic Subjects

abstract: OBJECTIVE In humans, multiple genes in the interleukin (IL)-2/IL-2 receptor (IL-2R) pathway are associated with type 1 diabetes. However, no link between IL-2 responsiveness and CD4 + CD25 + FOXP3 + regulatory T-cells (Tregs) has been demonstrated in type 1 diabetic subjects despite the role of these IL-2–dependent cells in controlling autoimmunity. Here, we address whether altered IL-2 responsiveness impacts persistence of FOXP3 expression in Tregs of type 1 diabetic subjects. RESEARCH DESIGN AND METHODS Persistence of Tregs was assessed by culturing sorted CD4 + CD25 hi natural Tregs with IL-2 and measuring FOXP3 expression over time by flow cytometry for control and type 1 diabetic populations. The effects of IL-2 on FOXP3 induction were assessed 48 h after activation of CD4 + CD25 − T-cells with anti-CD3 antibody. Cytokine receptor expression and signaling upon exposure to IL-2, IL-7, and IL-15 were determined by flow cytometry and Western blot analysis. RESULTS Maintenance of FOXP3 expression in CD4 + CD25 + Tregs of type 1 diabetic subjects was diminished in the presence of IL-2, but not IL-7. Impaired responsiveness was not linked to altered expression of the IL-2R complex. Instead, IL-2R signaling was reduced in Tregs and total CD4 + T-cells of type 1 diabetic subjects. In some individuals, decreased signal transducer and activator of transcription 5 phosphorylation correlated with significantly higher expression of protein tyrosine phosphatase N2, a negative regulator of IL-2R signaling. CONCLUSIONS Aberrant IL-2R signaling in CD4 + T-cells of type 1 diabetic subjects contributes to decreased persistence of FOXP3 expression that may impact establishment of tolerance. These findings suggest novel targets for treatment of type 1 diabetes within the IL-2R pathway and suggest that an altered IL-2R signaling signature may be a biomarker for type 1 diabetes.


title: CareLog: a selective archiving tool for behavior management in schools

abstract: Identifying the function of problem behavior can lead to the development of more effective interventions. One way to identify the function is through functional behavior assessment (FBA). Teachers conduct FBA in schools. However, the task load of recording the data manually is high, and the challenge of accurately identifying antecedents and consequences is significant while interacting with students. These issues often result in imperfect information capture. CareLog allows teachers more easily to conduct FBAs and enhances the capture of relevant information. In this paper, we describe the design process that led to five design principles that governed the development of CareLog. We present results from a five-month, quasi-controlled study aimed at validating those design principles. We reflect on how various constraints imposed by special education settings impact the design and evaluation process for HCI practitioners and researchers.


title: Automatic page-turning mechanism with near-field electroadhesive force for linearly correctable imaging

abstract: Recently in tandem with the spread of portable devices for reading electronic books, devices for digitizing paper books, called book scanners, are developed to meet the increased demand for digitizing privately owned books. However, conventional book scanners still have complex components to mechanically turn pages and to rectify the acquired images that are inevitably distorted by the curvy book surface. Here, we present the multi-scale mechanism that turns pages electronically using electroadhesive force generated by a micro-scale structure. Its another advantage is that perspective correction of image processing is applicable to readily reconstruct the distorted images of pages. Specifically, to turn one page at a time not two pages, we employ a micro-scale structure to generate near-field electroadhesive force that decays rapidly and accordingly attracts objects within tens of micrometers. We analyze geometrical parameters of the micro-scale structure to improve the decay characteristics. We find that the decay characteristics of electroadhesive force definitely depends upon the geometrical period of the micro-scale structure, while its magnitude depends on a variety of parameters. Based on this observation, we propose a novel electrode configuration with improved decay characteristics. Dynamical stability and kinematic requirements are also examined to successfully introduce near-field electroadhesive force into our digitizing process.


title: Moneta: A High-Performance Storage Array Architecture for Next-Generation, Non-volatile Memories

abstract: Emerging non-volatile memory technologies such as phase change memory (PCM) promise to increase storage system performance by a wide margin relative to both conventional disks and flash-based SSDs. Realizing this potential will require significant changes to the way systems interact with storage devices as well as a rethinking of the storage devices themselves. This paper describes the architecture of a prototype PCIe-attached storage array built from emulated PCM storage called Moneta. Moneta provides a carefully designed hardware/software interface that makes issuing and completing accesses atomic. The atomic management interface, combined with hardware scheduling optimizations, and an optimized storage stack increases performance for small, random accesses by 18x and reduces software overheads by 60%. Moneta array sustain 2.8~GB/s for sequential transfers and 541K random 4~KB~IO operations per second (8x higher than a state-of-the-art flash-based SSD). Moneta can perform a 512-byte write in 9~us (5.6x faster than the SSD). Moneta provides a harmonic mean speedup of 2.1x and a maximum speed up of 9x across a range of file system, paging, and database workloads. We also explore trade-offs in Moneta's architecture between performance, power, memory organization, and memory latency.


title: Thompson Sampling for Complex Bandit Problems

abstract: We consider stochastic multi-armed bandit problems with complex actions over a set of basic arms, where the decision maker plays a complex action rather than a basic arm in each round. The reward of the complex action is some function of the basic arms' rewards, and the feedback observed may not necessarily be the reward perarm. For instance, when the complex actions are subsets of the arms, we may only observe the maximum reward over the chosen subset. Thus, feedback across complex actions may be coupled due to the nature of the reward function. We prove a frequentist regret bound for Thompson sampling in a very general setting involving parameter, action and observation spaces and a likelihood function over them. The bound holds for discretely-supported priors over the parameter space without additional structural properties such as closed-form posteriors, conjugate prior structure or independence across arms. The regret bound scales logarithmically with time but, more importantly, with an improved constant that non-trivially captures the coupling across complex actions due to the structure of the rewards. As applications, we derive improved regret bounds for classes of complex bandit problems involving selecting subsets of arms, including the first nontrivial regret bounds for nonlinear MAX reward feedback from subsets. Using particle filters for computing posterior distributions which lack an explicit closed-form, we present numerical results for the performance of Thompson sampling for subset-selection and job scheduling problems.


title: A comparative study of face landmarking techniques

abstract: Face landmarking, defined as the detection and localization of certain characteristic points on the face, is an important intermediary step for many subsequent face processing operations that range from biometric recognition to the understanding of mental states. Despite its conceptual simplicity, this computer vision problem has proven extremely challenging due to inherent face variability as well as the multitude of confounding factors such as pose, expression, illumination and occlusions. The purpose of this survey is to give an overview of landmarking algorithms and their progress over the last decade, categorize them and show comparative performance statistics of the state of the art. We discuss the main trends and indicate current shortcomings with the expectation that this survey will provide further impetus for the much needed high-performance, real-life face landmarking operating at video rates.


title: A wireless smart parking system

abstract: Recently, there has been significant research focus on smart cities and how to use resources efficiently. Parking space, in particular, is scarce in most metropolitan areas and intelligent systems are required to coordinate parking. This paper presents a wireless system for locating parking spots remotely via a smartphone, and a wireless sensor node which determines if parking spots are vacant or not. It is found that the system is highly efficient and has high accuracy, even at long ranges.


title: Understanding Social Loafing: The Role of Justice Perceptions and Exchange Relationships

abstract: We proposed that the social exchange relationships individuals form in the workplace would mediate the relation between perceptions of interactional and distributive justice and social loafing. Specifically, we argued that both leader-member exchanges (LMX) and team-member exchanges (TMX) would mediate the relation between interactional justice and social loafing, and that LMX would mediate the relation between distributive justice and social loafing. In a field study, 124 manufacturing employees responded to questionnaires and their immediate supervisors were interviewed. The results indicated significant relationships between interactional justice and LMX, and between interactional justice and TMX. LMX, but not TMX, was negatively related to social loafing. Distributive justice was not significantly related to LMX. Thus no support was found for LMX as a mediator of the relationship between distributive justice and social loafing.


title: Resume Information Extraction With Cascaded Hybrid Model

abstract: This paper presents an effective approach for resume information extraction to support automatic resume management and routing. A cascaded information extraction (IE) framework is designed. In the first pass, a resume is segmented into a consecutive blocks attached with labels indicating the information types. Then in the second pass, the detailed information, such as Name and Address, are identified in certain blocks (e.g. blocks labelled with Personal Information), instead of searching globally in the entire resume. The most appropriate model is selected through experiments for each IE task in different passes. The experimental results show that this cascaded hybrid model achieves better F-score than flat models that do not apply the hierarchical structure of resumes. It also shows that applying different IE models in different passes according to the contextual structure is effective.


title: Towards End-to-End Speech Recognition

abstract: Standard automatic speech recognition (ASR) systems follow a divide and conquer approach to convert speech into text. Alternately, the end goal is achieved by a combination of sub-tasks, namely, feature extraction, acoustic modeling and sequence decoding, which are optimized in an independent manner. More recently, in the machine learning community deep learning approaches have emerged which allow training of systems in an end-to-end manner. Such approaches have found success in the area of natural language processing and computer vision community, and have consequently peaked interest in the speech community. The present thesis builds on these recent advances to investigate approaches to develop speech recognition systems in end-to-end manner. In that respect, the thesis follows two main axes of research. The first axis of research focuses on joint learning of features and classifiers for acoustic modeling. The second axis of research focuses on joint modeling of the acoustic model and the decoder. Along the first axis of research, in the framework of hybrid hidden Markov model/artificial neural networks (HMM/ANN) based ASR, we develop a convolution neural networks (CNNs) based acoustic modeling approach that takes raw speech signal as input and estimates phone class conditional probabilities. Specifically, the CNN has several convolution layers (feature stage) followed by multilayer perceptron (classifier stage), which are jointly optimized during the training. Through ASR studies on multiple languages and extensive analysis of the approach, we show that the proposed approach, with minimal prior knowledge, is able to learn automatically the relevant features from the raw speech signal. This approach yields systems that have less number of parameters and achieves better performance, when compared to the conventional approach of cepstral feature extraction followed by classifier training. As the features are automatically learned from the signal, a natural question that arises is: are such systems robust to noise? Towards that we propose a robust CNN approach referred to as normalized CNN approach, which yields systems that are as robust as or better than the conventional ASR systems using cepstral features (with feature level normalizations). The second axis of research focuses on end-to-end sequence-to-sequence conversion. We first propose an end-to-end phoneme recognition system. In this system the relevant features, classifier and the decoder (based on conditional random fields) are jointly modeled during training. We demonstrate the viability of the approach on TIMIT phoneme recognition task. Building on top of that, we investigate a ``weakly supervised'' training that alleviates the necessity for frame level alignments. Finally, we extend the weakly supervised approach to propose a novel keyword spotting technique. In this technique, a CNN first process the input observation sequence to output word level scores, which are subsequently aggregated to detect or spot words. We demonstrate the potential of the approach through a comparative study on LibriSpeech with the standard approach of keyword word spotting based on lattice indexing using ASR system.


title: Feature extraction and classification phishing websites based on URL

abstract: In this study we extracted websites' URL features and analyzed subset based feature selection methods and classification algorithms for phishing websites detection.


title: Rating through Voting: An Iterative Method for Robust Rating

abstract: In this paper we introduce an iterative voting algorithm and then use it to obtain a rating method which is very robust against collusion attacks as well as random and biased raters. Unlike the previous iterative methods, our method is not based on comparing submitted evaluations to an approximation of the final rating scores, and it entirely decouples credibility assessment of the cast evaluations from the ranking itself. The convergence of our algorithm relies on the existence of a fixed point of a continuous mapping which is also a stationary point of a constrained optimization objective. We have implemented and tested our rating method using both simulated data as well as real world data. In particular, we have applied our method to movie evaluations obtained from MovieLens and compared our results with IMDb and Rotten Tomatoes movie rating sites. Not only are the ratings provided by our system very close to IMDb rating scores, but when we differ from the IMDb ratings, the direction of such differences is essentially always towards the ratings provided by the critics in Rotten Tomatoes. Our tests demonstrate high efficiency of our method, especially for very large online rating systems, for which trust management is both of the highest importance and one of the most challenging problems.


title: Checkerboard EBG Surfaces for Wideband Radar Cross Section Reduction

abstract: Electromagnetic band-gap (EBG) structures have noteworthy electromagnetic characteristics that include their reflection phase variations with frequency. This paper applies this unique reflection phase property to alter the direction of the fields scattered by a radar target to reduce its radar cross section (RCS). This redirecting of the scattered fields occurs when a surface is covered with a checkerboard of alternating EBG structures, and results in a wider frequency band RCS reduction. RCS reduction compared to a PEC surface of 10 dB can be realized over 60% frequency bandwidth. Simulations of monostatic and bistatic RCSs of two dual EBG checkerboard surfaces, square and hexagonal, are compared with those of equal-sized PEC ground planes. The simulated monostatic RCS is also compared with measurements. Both $\bf{TE}^{\bf{z}}$ and $\bf{TM}^{\bf{z}}$ polarizations for oblique incidence are considered. Excellent agreement is obtained between simulated and measured patterns, for both the square and the hexagonal EBG checkerboard surfaces. An approximate analytical expression is provided as a guideline for a 10-dB RCS reduction of a dual EBG checkerboard surface compared to that of a PEC.


title: Wireless Sensor Networks for Home Health Care

abstract: Sophisticated electronics are within reach of average users. Cooperation between wireless sensor networks and existing consumer electronic infrastructures can assist in the areas of health care and patient monitoring. This will improve the quality of life of patients, provide early detection for certain ailments, and improve doctor-patient efficiency. The goal of our work is to focus on health-related applications of wireless sensor networks. In this paper we detail our experiences building several prototypes and discuss the driving force behind home health monitoring and how current (and future) technologies will enable automated home health monitoring.


title: A Complete Model for Underwater Optical Wireless Communications System

abstract: In this paper, we propose a system model by considering turbulence, scattering and absorption effects and noises including shot noise, thermal noise and background noise, for underwater optical wireless communications. The results are shown for the three different types of water by considering the different effects in the model. The results are shown for the eye diagrams as well as the bit error rates over a range of transmission span.


title: Dynamic time warping for gesture-based user identification and authentication with Kinect

abstract: The Kinect has primarily been used as a gesture-driven device for motion-based controls. To date, Kinect-based research has predominantly focused on improving tracking and gesture recognition across a wide base of users. In this paper, we propose to use the Kinect for biometrics; rather than accommodating a wide range of users we exploit each user's uniqueness in terms of gestures. Unlike pure biometrics, such as iris scanners, face detectors, and fingerprint recognition which depend on irrevocable biometric data, the Kinect can provide additional revocable gesture information. We propose a dynamic time-warping (DTW) based framework applied to the Kinect's skeletal information for user access control. Our approach is validated in two scenarios: user identification, and user authentication on a dataset of 20 individuals performing 8 unique gestures. We obtain an overall 4.14%, and 1.89% Equal Error Rate (EER) in user identification, and user authentication, respectively, for a gesture and consistently outperform related work on this dataset. Given the natural noise present in the real-time depth sensor this yields promising results.


title: An integrated approach for main path analysis: Development of the Hirsch index as an example

abstract: This study enhances main path analysis by proposing several variants to the original approach. Main path analysis is a bibliometric method capable of tracing the most significant paths in a citation network and is commonly used to trace the development trajectory of a research field. We highlight several limitations of the original main path analysis and suggest new, complementary approaches to overcome these limitations. In contrast to the original local main path, the new approaches generate the global main path, the backward local main path, multiple main paths, and key-route main paths. Each of them is obtained via a perspective different from the original approach. By simultaneously conducting the new, complementary approaches, one uncovers the key development of the target discipline from a broader view. To demonstrate the value of these new approaches, we simultaneously apply them to a set of academic articles related to the Hirsch index. The results show that the integrated approach discovers several paths that are not captured by the original approach. Among these new approaches, the key-route approach is especially useful and hints at a divergence–convergence–divergence structure in the development of the Hirsch index. © 2012 Wiley Periodicals, Inc.


title: Bank Liquidity Creation

abstract: Although the modern theory of financial intermediation portrays liquidity creation as an essential role of banks, comprehensive measures of bank liquidity creation do not exist. We construct four measures and apply them to data on virtually all U.S. banks from 1993 to 2003. We find that bank liquidity creation increased every year and exceeded $2.8 trillion in 2003. Large banks, multibank holding company members, retail banks, and recently merged banks created the most liquidity. Bank liquidity creation is positively correlated with bank value. Testing recent theories of the relationship between capital and liquidity creation, we find that the relationship is positive for large banks and negative for small banks. The Author 2009. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please e-mail: journals.permissions@oxfordjournals.org., Oxford University Press.


title: Temporally Coherent GANs for Video Super-Resolution (TecoGAN).

abstract: Adversarial training has been highly successful for single-image super-resolution, as it yields realistic and highly detailed results. Despite this success, current state-of-the-art methods for video super-resolution still favor simpler norms such as $L_2$ over adversarial loss functions. The averaging nature of direct vector norms as loss functions easily leads to temporal smoothness and coherence caused by an undesirable lack of spatial detail in the generated images. In our work, we instead propose an adversarial training for video super-resolution that leads to temporally coherent solutions without sacrificing spatial detail. ::: Our work focuses on novel loss formulations for video super-resolution, the power of which we demonstrate based on an established generator framework. We show that temporal adversarial learning is the key to achieving photo-realistic and temporally coherent detail. Besides the spatio-temporal discriminator, we propose a novel Ping-Pong loss that can effectively remove temporal artifacts in recurrent networks without reducing perceptual quality. Quantifying the temporal coherence for video super-resolution tasks has also not been addressed previously. We propose a first set of metrics to evaluate the accuracy as well as the perceptual quality of the temporal evolution. A series of user studies also confirm the ranking achieved via these metrics. Overall, our method outperforms previous work by yielding more detailed images with natural temporal changes.


title: Beyond Trending Topics: Real-World Event Identification on Twitter

abstract: User-contributed messages on social media sites such as Twitter have emerged aspowerful, real-time means of information sharing on the Web. These short messages tend to reflect a variety of events in real time, making Twitter particularly well suited as a source of real-time event content. In this paper, we explore approaches for analyzing the stream of Twitter messages to distinguish between messages about real-world events andnon-event messages. Our approach relies on a rich family of aggregatestatistics of topically similar message clusters. Large-scale experiments over millions of Twitter messages show the effectiveness of our approach for surfacing real-world event content on Twitter.


title: Mentalization in adult attachment narratives: Reflective functioning, mental states, and affect elaboration compared.

abstract: Relationships between three measures of mentalization (reflective function, mental states, and verbal elaboration of affect), attachment status, and the severity of axis I and axis II pathology were examined. Seventy-three adults, both ex-psychiatric patients and nonclinical volunteers were administered the Adult Attachment Interview (AAI). Comparisons between the three measures indicate that they share some aspect of a core mentalization process and that each illuminates a specific component. Reflective function was the only predictor of attachment status. The number of axis I diagnoses is partly explained by attachment insecurity, but the capacity to generate high-level defensive mental states as well as increments in verbal affect elaboration further contribute to the model. Finally, increments in affect elaboration, as well as augmentations in high-level defensive activity and reflective function are all associated with decreases in the number of axis II diagnoses, over and above the contribution of attachment status and axis I pathology.


title: Improved marching cubes using novel adjacent lookup table and random sampling for medical object-specific 3D visualization

abstract: The marching cubes (MC) algorithm is a common routine to extract isosurfaces from volumetric dataset. This method suffers from the exhaustive accessingcubes sequentially and the failure of directly separating theisosurfaces. To address this, an improved MC algorithmcalled AlutMC is proposed to track connected surfaces bycombining a new adjacent lookup table and random sam-pling technique. AlutMC has a natural ability to separatethe isosurfaces related to different components, which canefﬁciently segment 3D objects without extra expenditure andhelpful for visualizing medical objects. Experimental resultson three test data sets show the computational efﬁciencyin identifying isosurfaces. Additionally, it is simple and efﬁcient, not requiring complex data structure, and can beused as is into the MC and its improvements because it isquite cost-effective and self-contained.


title: Let your fingers do the walking: A unified approach for efficient short-, medium-, and long-distance travel in VR

abstract: The tradeoff between speed and precision is one of the challenging problems of travel interfaces. Sometimes users want to travel long distances (e.g., fly) and care less about precise movement, while other times they want to approach nearby objects in a more-precise way (e.g., walk), and care less about how quickly they move. Between these two extremes there are scenarios when both speed and precision become equally important. In real life, we often seamlessly combine these modes. However, most VR systems support a single travel metaphor, which may only be good for one range of travel, but not others. We present a new VR travel framework which supports three separate multi-touch travel techniques, one for each distance range, but that all use the same device. We use a unifying metaphor of the user's fingers becoming their legs for each of the techniques. We are investigating the usability and user acceptance of the fingers-as-legs metaphor, as well as the efficiency and naturalness of switching between the different travel modes. We conducted an experiment focusing on user performance using the three travel modes, and compared our multi-touch, gesture-based approach with a traditional Gamepad travel interface. The results suggest that participants using a Gamepad interface are more time efficient. However, the quality of completing the tasks with the two input devices was similar, while ForcePad user response was faster for switching between travel modes.


title: Colour Image Retrieval and Object Recognition Using the Multimodal Neighbourhood Signature

abstract: A novel approach to colour-based object recognition and image retrieval -the multimodal neighbourhood signature- is proposed. Object appearance is represented by colour-based features computed from image neighbourhoods with multi-modal colour density function. Stable invariants are derived from modes of the density function that are robustly located by the mean shift algorithm. The problem of extracting local invariant colour features is addressed directly, without a need for prior segmentation or edge detection. The signature is concise - an image is typically represented by a few hundred bytes, a few thousands for very complex scenes. ::: ::: The algorithm's performance is first tested on a region-based image retrieval task achieving a good (92%) hit rate at a speed of 600 image comparisons per second. The method is shown to operate successfully under changing illumination, viewpoint and object pose, as well as non-rigid object deformation, partial occlusion and the presence of background clutter dominating the scene. The performance of the multimodal neighbourhood signature method is also evaluated on a standard colour object recognition task using a publicly available dataset. Very good recognition performance (average match percentile 99.5%) was achieved in real time (average 0.28 seconds for recognising a single image) which compares favourably with results reported in the literature.


title: Strengths and Challenges in the Use of Interpretive Description: Reflections Arising From a Study of the Moral Experience of Health Professionals in Humanitarian Work

abstract: Interpretive description is a qualitative research methodology aligned with a constructivist and naturalistic orientation to inquiry. The aim of interpretive description, a relatively new qualitative methodology, is to generate knowledge relevant for the clinical context of applied health disciplines. To date there has been little discussion in the literature of the particular merits and limitations of this methodological framework. In this article I draw on my experience of using interpretive description as methodology for an inquiry into the moral experience of clinicians in humanitarian work. I identify and discuss strengths and challenges that can arise in the application of interpretive description. Strengths identified include a coherent logic and structure, an orientation toward the generation of practice-relevant findings, and attention to disciplinary biases and commitments. Challenges include limited resources for situating the methodology, challenges in employing a lesser-known methodology, and...


title: GaN MMIC amplifiers for W-band transceivers

abstract: This paper presents W-band monolithic microwave integrated circuit (MMIC) amplifiers with grounded coplanar waveguide (GCPW) in 0.12µm GaN HEMT technology. A fabricated four-stage low-noise amplifier (LNA) exhibited a record gain of 23 dB at 76.5 GHz and a first reported noise figure (NF) of 3.8 dB at 80 GHz for any W-band GaN MMIC. Another MMIC power amplifier (PA) delivered an output power of 25.4 dBm at 76.5 GHz with continuous wave (CW) operation. To our knowledge, this is the first demonstration of GaN LNA as well as GaN MMICs with GCPW in the W-band. In addition, a practical design technique to prevent instability of the W-band MMIC is described.


title: Balanced antipodal Vivaldi antenna array for microwave tomography

abstract: This paper presents simulation studies for an array comprised of twelve balanced antipodal Vivaldi antennas for microwave tomography in the presence of a simple numerical breast phantom. This type of antennas bas been proposed previously in UWB breast imaging, but their use is a microwave tomographic setup is studied for the first time. The coupling effect of array elements and the electric field patterns are investigated with and without the phantom in the frequency range of interest between 0.5 and 5 GHz.


title: A role for ethylene in low-oxygen signaling in rice roots

abstract: Inhibitors of action and synthesis of ethylene (Ag(+), norbornadien, Co(2+)) were able to reduce the level of gamma-aminobutyric acid (Gaba) in rice roots during the development of an anaerobic environment. The inhibitory effect was reversed by the addition of the G protein activator 5'-guanylylimidodiphosphate. Gaba accumulation was modulated by the presence of CO(2) (inhibitor of ethylene action and synthesis) and stimulated by 2-chloroethylphosphonic acid (ethefon). These findings are consistent with a role of ethylene during a low-oxygen stress.


title: Comprehensive evaluation of deep learning architectures for prediction of DNA/RNA sequence binding specificities

abstract: MOTIVATION ::: Deep learning architectures have recently demonstrated their power in predicting DNA- and RNA-binding specificity. Existing methods fall into three classes: Some are based on convolutional neural networks (CNNs), others use recurrent neural networks (RNNs) and others rely on hybrid architectures combining CNNs and RNNs. However, based on existing studies the relative merit of the various architectures remains unclear. ::: ::: ::: RESULTS ::: In this study we present a systematic exploration of deep learning architectures for predicting DNA- and RNA-binding specificity. For this purpose, we present deepRAM, an end-to-end deep learning tool that provides an implementation of a wide selection of architectures; its fully automatic model selection procedure allows us to perform a fair and unbiased comparison of deep learning architectures. We find that deeper more complex architectures provide a clear advantage with sufficient training data, and that hybrid CNN/RNN architectures outperform other methods in terms of accuracy. Our work provides guidelines that can assist the practitioner in choosing an appropriate network architecture, and provides insight on the difference between the models learned by convolutional and recurrent networks. In particular, we find that although recurrent networks improve model accuracy, this comes at the expense of a loss in the interpretability of the features learned by the model. ::: ::: ::: AVAILABILITY AND IMPLEMENTATION ::: The source code for deepRAM is available at https://github.com/MedChaabane/deepRAM. ::: ::: ::: SUPPLEMENTARY INFORMATION ::: Supplementary data are available at Bioinformatics online.


title: Emergency Control of AR Drone Quadrotor UAV Suffering a Total Loss of One Rotor

abstract: In this paper, an emergency fault-tolerant controller is developed for quadrotor unmanned aerial vehicles (UAVs) suffering a total loss of one actuator (rotor/motor). The proposed controller is based on control allocation where the infected actuator is exempted from the control effect, and control efforts are redistributed among healthy actuators. As a result, the emergency controller transforms the infected quadrotor into a trirotor and uses the remaining actuators to ensure that the UAV continues following its path. The main advantage of the new controller is that it uses the same simple proportional-integral-derivative (PID) controller applied in fault-free cases by redistributing its controls, rather than designing complex and memory consumable controllers. Experimental results using the augmented reality (AR) Drone 2 platform show that by implementing the quadrotor to trirotor conversion maneuver, the nominal PID controller gains powerful fault-tolerant capabilities and the infected UAV is successful in maintaining its desired path. Performance degradation seen as oscillations did not cause the drone to crash despite the total loss of yaw control, the presence of activation delay, the nonsymmetric structure of the trirotor, and its odd number of rotors that produces imbalance of the rotor moments.


title: Multiple anatomical systems embedded within the primate medial temporal lobe: Implications for hippocampal function

abstract: A review of medial temporal lobe connections reveals three distinct groupings of hippocampal efferents. These efferent systems and their putative memory functions are: (1) The ‘extended-hippocampal system’ for episodic memory, which involves the anterior thalamic nuclei, mammillary bodies and retrosplenial cortex, originates in the subicular cortices, and has a largely laminar organisation; (2) The ‘rostral hippocampal system’ for affective and social learning, which involves prefrontal cortex, amygdala and nucleus accumbens, has a columnar organisation, and originates from rostral CA1 and subiculum; (3) The ‘reciprocal hippocampal–parahippocampal system’ for sensory processing and integration, which originates from the length of CA1 and the subiculum, and is characterised by columnar, connections with reciprocal topographies. A fourth system, the ‘parahippocampal–prefrontal system’ that supports familiarity signalling and retrieval processing, has more widespread prefrontal connections than those of the hippocampus, along with different thalamic inputs. Despite many interactions between these four systems, they may retain different roles in memory which when combined explain the importance of the medial temporal lobe for the formation of declarative memories.


title: A dynamic-range-based algorithm for reader-tag collision avoidance deployment in RFID networks

abstract: Recently, the problem of scheduling readers to read maximum tags such that readers and tags can be avoided collision within a given multiple interrogation ranges of reader has received a great deal of attention in Radio frequency identification (RFID) systems. Many methods have been proposed for the RFID systems such that readers can read maximum tags. However, most of previous works often require lots of readers or exist reader-tag collisions. In this paper, we propose a new algorithm, called the Dynamic-Range-based algorithm (DRBA), to maximize the number of read tags and avoid collisions within the multiple interrogation ranges of readers. Simulation results show that the DRBA has better performance than other existing methods.


Origami in Engineering and Architecture An art and science spanning Mathematics , Engineering and Architecture


title: A flexible and dynamic mission planning architecture for UAV swarm coordination

abstract: In this paper a scalable and flexible Architecture for real-time mission planning and dynamic agent-to-task assignment for a swarm of Unmanned Aerial Vehicles (UAV) is presented. The proposed mission planning architecture consists of a Global Mission Planner (GMP) which is responsible of assigning and monitoring different high-level missions through an Agent Mission Planner (AMP), which is in charge of providing and monitoring each task of the mission to each UAV in the swarm. The objective of the proposed architecture is to carry out high-level missions such as autonomous multi-agent exploration, automatic target detection and recognition, search and rescue, and other different missions with the ability of dynamically re-adapt the mission in real-time. The proposed architecture has been evaluated in simulation and real indoor flights demonstrating its robustness in different scenarios and its flexibility for real-time mission re-planning and dynamic agent-to-task assignment.


title: Detecting Both Machine and Human Created Fake Face Images In the Wild

abstract: Due to the significant advancements in image processing and machine learning algorithms, it is much easier to create, edit, and produce high quality images. However, attackers can maliciously use these tools to create legitimate looking but fake images to harm others, bypass image detection algorithms, or fool image recognition classifiers. In this work, we propose neural network based classifiers to detect fake human faces created by both 1) machines and 2) humans. We use ensemble methods to detect GANs-created fake images and employ pre-processing techniques to improve fake face image detection created by humans. Our approaches focus on image contents for classification and do not use meta-data of images. Our preliminary results show that we can effectively detect both GANs-created images, and human-created fake images with 94% and 74.9% AUROC score.


title: What does research reproducibility mean?

abstract: The language and conceptual framework of “research reproducibility” are nonstandard and unsettled across the sciences. In this Perspective, we review an array of explicit and implicit definitions of reproducibility and related terminology, and discuss how to avoid potential misunderstandings when these terms are used as a surrogate for “truth.”


title: Syntactic Contexts for Finding Semantically Related Words

abstract: Finding semantically related words is a first step in the direction of automatic ontology building. Guided by the view that similar words occur in similar contexts, we looked at the syntactic context of words to measure their semantic similarity. Words that occur in a direct object relation with the verb drink, for instance, have something in common (liquidity, ...). Co-occurrence data for common nouns and proper names, for several syntactic relations, was collected from an automatically parsed corpus of 78 million words of newspaper text. We used several vector-based methods to compute the distributional similarity between words. Using Dutch EuroWordNet as evaluation standard, we investigated which vector-based method and which combination of syntactic relations is the strongest predictor of semantic similarity.


title: Scalable Distributed DNN Training using TensorFlow and CUDA-Aware MPI: Characterization, Designs, and Performance Evaluation

abstract: The current wave of advances in Deep Learning (DL) have been triggered by the availability of large-scale datasets, efficient CPU and GPU hardware, and development of software frameworks like TensorFlow (TF). However, little exists in literature that addresses TensorFlow's distributed training capabilities. In this paper, we provide an in-depth performance characterization and design analysis for distributed TensorFlow. We present three key insights: 1) Horovod designs achieve better performance compared to the official gRPC-based approaches, 2) performance of Horovod design is heavily influenced by the time spent in gradient aggregation that uses the Allreduce primitive, and 3) performance of existing Horovod-MPI implementation is significantly worse compared to Horovod-NCCL. To address this limitation in Horovod-MPI, we propose a novel and efficient CUDA-Aware MPI Allreduce design that 1) exploits CUDA kernels to perform large reductions on the GPU, 2) uses a com-bination of bandwidth-optimal and latency-optimal algorithms, and 3) maintains a pointer cache to avoid CUDA-driver query overheads in the critical path. The proposed designs deliver 5×, 17×, and 29% better performance compared to NCCL2 for small, medium, and large messages. Our designs enable Horovod-MPI to beat state-of-the-art Horovod-NCCL2 by 3% and achieve 90% scaling efficiency for ResNet-50 training on 64 Pascal GPUs.


title: Business & IT Alignment in Theory and Practice

abstract: A key success factor for a successful company in a dynamic environment is effective and efficient information technology (IT) supporting business strategies and processes. In recent surveys however it is concluded that in most companies IT is not aligned with business strategy. The alignment between business needs and IT capabilities is therefore still a prominent area of concern. This paper reports the first stages of a research program exploring the differences of business & IT alignment (BIA) in theory and in practice. The paper presents an overview of the development of theory on BIA and reports the issues with aligning IT to business in practice based on a number of focus-group discussions with CIOs and IT managers. In line with the practical approach to BIA that the CIOs and IT managers in the focus-groups took, the last part of the paper builds upon Luftman's BIA maturity model and reports the application of the model to 12 Dutch firms


title: Design of a Circularly Polarized Ground Radiation Antenna for Biomedical Applications

abstract: A ground radiation antenna with circularly polarized (CP) properties is proposed and studied for biomedical applications. A square ground with a small clearance is implemented in the proposed antenna. Reactive components are included to realize the impedance matching, as well as those requirements for the generation of CP waves. Simulations are conducted within a single-layer tissue model to evaluate the antenna’s performance. The proposed antenna exhibits a low profile, which is smaller than 1 mm even including two coating layers. The antenna also behaves good robustness to different implant depths and thicknesses of biocompatible coating, due to its wide axial ratio bandwidth ranging from 2.331 to 2.582 GHz. A prototype is fabricated and experimentally demonstrated in a solid skin-mimicking phantom. A measured impedance bandwidth of 621 MHz is achieved for the 2.4–2.48-GHz Industrial Scientific Medical band. Good agreement between simulation and measurement can be observed in the far-field measurement. The link budget is also evaluated, together with an exterior CP patch antenna.


title: In vitro drug release studies of polymeric freeze-dried wafers and solvent-cast films using paracetamol as a model soluble drug.

abstract: Drug dissolution and release characteristics from freeze-dried wafers and solvent-cast films prepared from sodium carboxymethylcellulose (CMC) have been investigated to determine the mechanisms of drug release from the two systems. The formulations were prepared by freeze-drying (wafers) or drying in air (films), the hydrated gel of the polymer containing paracetamol as a model soluble drug. Scanning electron microscopy (SEM) was used to examine differences between the physical structure of the wafers and films. Dissolution studies were performed using an exchange cell and drug release was measured by UV spectroscopy at 242 nm. The effects of drug loading, polymer content and amount of glycerol (films) on the release characteristics of paracetamol were investigated. The release profiles of paracetamol from the wafers and films were also compared. A digital camera was used to observe the times to complete hydration and dissolution of the wafers containing different amounts of CMC and how that impacts on drug release rates. Both formulations showed sustained type drug release that was modelled by the Korsmeyer-Peppas equation. Changes in the concentration of drug and glycerol (films) did not significantly alter the rate of drug release while increasing polymer content significantly decreased the rate of drug release from both formulations. The results show that the rate of paracetamol release was faster from the wafers than the corresponding films due to differences in their physical structures. The wafers which formed a porous network, hydrated faster than the more dense and continuous, (non-porous) sheet-like structure of the films.


title: Energy efficient spiking neural network design with RRAM devices

abstract: The brain-inspired neural networks have demonstrated great potential in big data analysis. The spiking neural network (SNN), which encodes the real world data into spike trains, promises great performance in computational ability and energy efficiency. Moreover, it is much more biologically plausible than the traditional artificial neural network (ANN), which keeps the input data in its original form. In this paper, we introduce an RRAM-based energy efficient implementation of STDP-based spiking neural network cascaded with ANN classifier. The recognition accuracy and power consumption are compared between SNN and traditional three-layer ANN. The experiments on the MNIST database demonstrate that the proposed RRAM-based spiking neural network requires only 14% of power consumption compared with RRAM-based artificial neural network with a slight accuracy decay (~2%).


title: Too many shots? Parent, nurse, and physician attitudes toward multiple simultaneous childhood vaccinations.

abstract: OBJECTIVE ::: To learn about parent, nurse, and family physician attitudes toward multiple simultaneous childhood vaccinations. ::: ::: ::: DESIGN ::: Survey. ::: ::: ::: SETTING ::: Thirty-two family practice clinics in Minnesota. ::: ::: ::: PATIENTS/PARTICIPANTS ::: Forty-six volunteer Minnesota Academy of Family Physicians Research Network members, 42 of their nurses, and 342 parents of their patients aged less than 6 years who have had at least one injection. ::: ::: ::: MAIN OUTCOME MEASURES ::: Number of injections believed to be too many for a child to receive simultaneously and comfort level associated with children's receiving three simultaneous injectable vaccinations. ::: ::: ::: RESULTS ::: Most parents, nurses, and physicians (71%, 76%, and 59%, respectively) think that three injections are too many for a child to receive at one visit. Similar percentages of parents, nurses, and physicians are uncomfortable with a child's receiving three injections at one visit. Sixty-seven percent of the physicians who do not offer universal newborn hepatitis B vaccinations cite the number of required simultaneous injections as a factor in that decision. Only 15% of physicians order all three recommended injections for most of their 15-month-old patients. ::: ::: ::: CONCLUSIONS ::: Most parents, nurses, and physicians are uncomfortable with three simultaneous injections for children. This discomfort may be a significant barrier to the adoption of the new immunization recommendations. The development of effective combination vaccines should be a research priority.


title: Early aberrant DNA methylation events in a mouse model of acute myeloid leukemia

abstract: BackgroundAberrant DNA methylation is frequently found in human malignancies including acute myeloid leukemia (AML). While most studies focus on later disease stages, the onset of aberrant DNA methylation events and their dynamics during leukemic progression are largely unknown.MethodsWe screened genome-wide for aberrant CpG island methylation in three disease stages of a murine AML model that is driven by hypomorphic expression of the hematopoietic transcription factor PU.1. DNA methylation levels of selected genes were correlated with methylation levels of CD34+ cells and lineage negative, CD127-, c-Kit+, Sca-1+ cells; common myeloid progenitors; granulocyte-macrophage progenitors; and megakaryocyte-erythroid progenitors.ResultsWe identified 1,184 hypermethylated array probes covering 762 associated genes in the preleukemic stage. During disease progression, the number of hypermethylated genes increased to 5,465 in the late leukemic disease stage. Using publicly available data, we found a significant enrichment of PU.1 binding sites in the preleukemic hypermethylated genes, suggesting that shortage of PU.1 makes PU.1 binding sites in the DNA accessible for aberrant methylation. Many known AML associated genes such as RUNX1 and HIC1 were found among the preleukemic hypermethylated genes. Nine novel hypermethylated genes, FZD5, FZD8, PRDM16, ROBO3, CXCL14, BCOR, ITPKA, HES6 and TAL1, the latter four being potential PU.1 targets, were confirmed to be hypermethylated in human normal karyotype AML patients, underscoring the relevance of the mouse model for human AML.ConclusionsOur study identified early aberrantly methylated genes as potential contributors to onset and progression of AML.


title: A Longitudinal Study of a Business Model of On-line Shopping Behavior Using a Latent Growth Curve Approach

abstract: In spite of the fact that we are in a digital economy, online sales represent less than 2% of the overall retail business. Online retail sales are expected to grow significantly in the future. This presents a significant opportunity for businesses to increase their share of the online retail business and in the process contribute towards the digital economy. In this longitudinal study, we introduce and empirically test over a period of time a business model of online shopping behavior using multinational data. Our study is based on the premise that online shopping behavior may change over time and it is important to undertake a research study to ascertain as to which of these antecedents may remain significant over time. We believe this will allow businesses to come up with a better online shopping channel. To the best of our knowledge, this is the first time a longitudinal study has been conducted in this area to investigate the antecedents of online shopping behavior. Another contribution of this research is the introduction of a powerful structural equation modeling technique, the latent growth curve (LGC) approach, to the information systems literature. We used this approach to validate the on-line shopping model. Our results show that over time trust and economic condition play a significant and positive role in online shopper’s behavior.


title: Keypoint Design and Evaluation for Place Recognition in 2D Lidar Maps

abstract: We address the place recognition problem, which we define as the problem of establishing whether an observed location has been previously seen, and if so, determining the transformation aligning the current observations to an existing map. In the contexts of robot navigation and mapping, place recognition amounts to globally localizing a robot or map segment without being given any prior estimate. An efficient method of solving this problem involves first selecting a set of keypoints in the scene which store an encoding of their local region, and then utilizing a sublinear-time search into a database of keypoints previously generated from the global map to identify places with common features. We present an algorithm to embed arbitrary keypoint descriptors in a reduced-dimension metric space, in order to frame the problem as an efficient nearest neighbor search. Given that there are a multitude of possibilities for keypoint design, we propose a general methodology for comparing keypoint location selection heuristics and descriptor models that describe the region around the keypoint. With respect to selecting keypoint locations, we introduce a metric that encodes how likely it is that the keypoint will be found in the presence of noise and occlusions during mapping passes. Metrics for keypoint descriptors are used to assess the distinguishability between the distributions of matches and non-matches and the probability the correct match will be found in an approximate k-nearest neighbors search. Verification of the test outcomes is done by comparing the various keypoint designs on a kilometers-scale place recognition problem. We apply our design evaluation methodology to three keypoint selection heuristics and six keypoint descriptor models. A full place recognition system is presented, including a series of match verification algorithms which effectively filter out false positives. Results from city-scale and long-term mapping problems illustrate our approach for both offline and online SLAM, map merging, and global localization and demonstrate that our algorithm is able to produce accurate maps over trajectories of hundreds of kilometers.


title: Consultants and Enterprise Resource Planning (ERP) Systems

abstract: Enterprise Resource Planning (ERP) systems have been implemented in the majority of large companies in Europe and the US over the last five years [1]. This paper seeks to address three issues arising from this deployment. Firstly, to consider ERP systems in relation to previous approaches to deploying information systems in organisations. Secondly, to indicate how the mediation by consultants is of importance in the deployment of ERP systems. Thirdly, based on our analysis, to seek to predict future trends and issues in the use of information and communication technologies by organisations.


title: An Ensemble Deep Learning Method for Vehicle Type Classification on Visual Traffic Surveillance Sensors

abstract: Visual traffic surveillance systems play important roles in intelligent transport systems nowadays. The first step of a visual traffic surveillance system usually needs to correctly detect objects from images or videos and classify them into different categories (e.g., car, truck, and bus). This paper aims to introduce a new vehicle type classification scheme on the images acquired from multi-view visual traffic surveillance sensors. Most image classification algorithms focus on maximizing the percentage of the correct predictions, which have a deficiency that the images from minority categories are prone to be misclassified as the dominant categories. To address this challenge of classifying imbalanced data acquired from visual traffic surveillance sensors, we propose a method, which integrates deep neural networks with balanced sampling in this paper. The proposed method consists of two main stages. In the first stage, data augmentation with balanced sampling is applied to alleviate the unbalanced data set problem. In the second stage, an ensemble of convolutional neural network models with different architectures is constructed with parameters learned on the augmented training data set. Experiments on the MIOvision traffic camera dataset classification challenge data set demonstrate that the proposed method is able to enhance the mean precision of all categories, in the condition of high overall accuracy, compared with the baseline algorithms.


Jailed balloon protection and rescue balloon jailing techniques set the field for safer bifurcation provisional stenting.


Blind Spot : Do You Know the Effectiveness of Your Information Security Awareness-Raising Program ?


Diabetes: Methylglyoxal mediates hyperalgesia in patients with painful diabetic neuropathy


title: Comparative study of automatic speech recognition techniques

abstract: Over the past decades, extensive research has been carried out on various possible implementations of automatic speech recognition (ASR) systems. The most renowned algorithms in the field of ASR are the mel-frequency cepstral coefficients and the hidden Markov models. However, there are also other methods, such as wavelet-based transforms, artificial neural networks and support vector machines, which are becoming more popular. This review article presents a comparative study on different approaches that were proposed for the task of ASR, and which are widely used nowadays.


title: Randomized Controlled Trial of Motivational Interviewing, Cognitive Behavior Therapy, and Family Intervention for Patients With Comorbid Schizophrenia and Substance Use Disorders

abstract: OBJECTIVE: Comorbidity of substance abuse disorders with schizophrenia is associated with a greater risk for serious illness complications and poorer outcome. Methodologically sound studies investigating treatment approaches for patients with these disorders are rare, although recommendations for integrated and comprehensive treatment programs abound. This study investigates the relative benefit of adding an integrated psychological and psychosocial treatment program to routine psychiatric care for patients with schizophrenia and substance use disorders. METHOD: The authors conducted a randomized, single-blind controlled comparison of routine care with a program of routine care integrated with motivational interviewing, cognitive behavior therapy, and family or caregiver intervention. RESULTS: The integrated treatment program resulted in significantly greater improvement in patients’ general functioning than routine care alone at the end of treatment and 12 months after the beginning of the study. Other b...


title: Comparative analyses of CTCF and BORIS occupancies uncover two distinct classes of CTCF binding genomic regions

abstract: BackgroundCTCF and BORIS (CTCFL), two paralogous mammalian proteins sharing nearly identical DNA binding domains, are thought to function in a mutually exclusive manner in DNA binding and transcriptional regulation.ResultsHere we show that these two proteins co-occupy a specific subset of regulatory elements consisting of clustered CTCF binding motifs (termed 2xCTSes). BORIS occupancy at 2xCTSes is largely invariant in BORIS-positive cancer cells, with the genomic pattern recapitulating the germline-specific BORIS binding to chromatin. In contrast to the single-motif CTCF target sites (1xCTSes), the 2xCTS elements are preferentially found at active promoters and enhancers, both in cancer and germ cells. 2xCTSes are also enriched in genomic regions that escape histone to protamine replacement in human and mouse sperm. Depletion of the BORIS gene leads to altered transcription of a large number of genes and the differentiation of K562 cells, while the ectopic expression of this CTCF paralog leads to specific changes in transcription in MCF7 cells.ConclusionsWe discover two functionally and structurally different classes of CTCF binding regions, 2xCTSes and 1xCTSes, revealed by their predisposition to bind BORIS. We propose that 2xCTSes play key roles in the transcriptional program of cancer and germ cells.


title: Simultaneous map building and localization for an autonomous mobile robot

abstract: Discusses a significant open problem in mobile robotics: simultaneous map building and localization, which the authors define as long-term globally referenced position estimation without a priori information. This problem is difficult because of the following paradox: to move precisely, a mobile robot must have an accurate environment map; however, to build an accurate map, the mobile robot's sensing locations must be known precisely. In this way, simultaneous map building and localization can be seen to present a question of 'which came first, the chicken or the egg?' (The map or the motion?) When using ultrasonic sensing, to overcome this issue the authors equip the vehicle with multiple servo-mounted sonar sensors, to provide a means in which a subset of environment features can be precisely learned from the robot's initial location and subsequently tracked to provide precise positioning. >


title: MSMOTE: Improving Classification Performance When Training Data is Imbalanced

abstract: Learning from data sets that contain very few instances of the minority class usually produces biased classifiers that have a higher predictive accuracy over the majority class, but poorer predictive accuracy over the minority class. SMOTE (Synthetic Minority Over-sampling Technique) is specifically designed for learning from imbalanced data sets. This paper presents a modified approach (MSMOTE) for learning from imbalanced data sets, based on the SMOTE algorithm. MSMOTE not only considers the distribution of minority class samples, but also eliminates noise samples by adaptive mediation. The combination of MSMOTE and AdaBoost are applied to several highly and moderately imbalanced data sets. The experimental results show that the prediction performance of MSMOTE is better than SMOTEBoost in the minority class and F-values are also improved.


title: Sustainability and the European Waste Management Industry

abstract: Waste raises a range of environmental problems within Europe and sustainability has become an increasingly important ::: challenge for the waste management industry. The aim of this paper is to offer an exploratory review of the approaches ::: to sustainability within the European waste management industry. The paper begins with brief outlines of waste and the ::: waste management industry in Europe and the growing interest in sustainability reporting. This is followed by a review of ::: the sustainability reporting by some of the leading waste management companies operating within Europe and the paper ::: concludes by offering some reflections on current approaches to sustainability within the industry. The findings reveal ::: that the sustainability reports included details of a wide range of environmental, social and economic issues but more ::: generally, the reports had a number of weaknesses that undermined their transparency and credibility. The authors also ::: argue that the selected companies’ definitions of, and commitments to, sustainability are principally driven as much by ::: business imperatives as by any fundamental concern to maintain the viability and integrity of natural and social capital.


title: Effects of a 25-km trial on psychological, physiological and stroke characteristics of short- and mid-distance swimmers.

abstract: AIM ::: The aim of this paper was to evaluate the effects of a very long distance swimming task on psychological, biomechanical and physiological responses. Eight swimmers (age 21.0 ± 1.2 years; stature 1.80 ± 0.07 m; body mass 76.7 ± 11.0 kg; means ± SD) participated in a 25-km trial in a swimming pool. ::: ::: ::: METHODS ::: Before and immediately after the trial, swimmers underwent a 50-m sprint test, during which we assessed velocity, stroke rate (SR), stroke length (SL) and psychological condition (rate of perceived exertion [RPE] and profile of mood state [POMS] questionnaire). During the 25-km trial we determined also elbow angle, heart rate (HR) and lactate concentration ([La]). ::: ::: ::: RESULTS ::: Velocity, SR and SL during the sprint test after the trial decreased compared to before from 1.91 ± 0.01 m·s⁻¹, 0.94 ± 0.01 cycles·s⁻¹ and 1.99 ± 0.02 m·cycle⁻¹ to 1.45 ± 0.01 m·s⁻¹, 0.78 ± 0.01 cycles·s⁻¹ and 1.84 ± 0.03 m·cycle⁻¹, respectively (P<0.05). During the 25-km trial, velocity and SL decreased significantly, while SR and elbow angle did not change. Velocity and SR during the sprint test after the trial were significantly higher than those during the trial. RPE and fatigue (POMS subscale) increased significantly, while the other negative POMS subscales and vigor decreased significantly. HR decreased significantly at 20 km, then increasing significantly at 25 km, while [La] did not change. ::: ::: ::: CONCLUSION ::: These results suggest that, despite the occurrence of fatigue, as evidenced by the drop in velocity and changes in psychological profile, swimmers were able to complete the 25-km trial by adopting a conservative pacing, unveiling also a reserve in maximum performance.


title: Probabilistic reachability for parametric Markov models

abstract: Given a parametric Markov model, we consider the problem of computing the rational function expressing the probability of reaching a given set of states. To attack this principal problem, Daws has suggested to first convert the Markov chain into a finite automaton, from which a regular expression is computed. Afterwards, this expression is evaluated to a closed form function representing the reachability probability. This paper investigates how this idea can be turned into an effective procedure. It turns out that the bottleneck lies in the growth of the regular expression relative to the number of states (n Θ(log n)). We therefore proceed differently, by tightly intertwining the regular expression computation with its evaluation. This allows us to arrive at an effective method that avoids this blow up in most practical cases. We give a detailed account of the approach, also extending to parametric models with rewards and with non-determinism. Experimental evidence is provided, illustrating that our implementation provides meaningful insights on non-trivial models.


title: A Study on Garbage Collection Algorithms for Big Data Environments

abstract: The need to process and store massive amounts of data—Big Data—is a reality. In areas such as scientific experiments, social networks management, credit card fraud detection, targeted advertisement, and financial analysis, massive amounts of information are generated and processed daily to extract valuable, summarized information. Due to its fast development cycle (i.e., less expensive to develop), mainly because of automatic memory management, and rich community resources, managed object-oriented programming languages (e.g., Java) are the first choice to develop Big Data platforms (e.g., Cassandra, Spark) on which such Big Data applications are executed. ::: ::: However, automatic memory management comes at a cost. This cost is introduced by the garbage collector, which is responsible for collecting objects that are no longer being used. Although current (classic) garbage collection algorithms may be applicable to small-scale applications, these algorithms are not appropriate for large-scale Big Data environments, as they do not scale in terms of throughput and pause times. ::: ::: In this work, current Big Data platforms and their memory profiles are studied to understand why classic algorithms (which are still the most commonly used) are not appropriate, and also to analyze recently proposed and relevant memory management algorithms, targeted to Big Data environments. The scalability of recent memory management algorithms is characterized in terms of throughput (improves the throughput of the application) and pause time (reduces the latency of the application) when compared to classic algorithms. The study is concluded by presenting a taxonomy of the described works and some open problems, with regard to Big Data memory management, that could be addressed in future works.


title: Statewide differences in personality: toward a psychological geography of the United States.

abstract: There is overwhelming evidence from research in the regional sciences that the attitudes, values, and behaviors of Americans are geographically clustered. Psychologists, however, have historically had little to say about regional differences. This article aims to redress that neglect. In so doing, I provide evidence that there are statewide personality differences across the United States, offer potential explanations for those differences, and show that regional personality differences are linked to a variety of important social indicators. I also explain how a regional perspective can inform research in a variety of areas in psychology and suggest ways in which researchers can study regional differences in their own work. Ultimately, this work is intended to raise awareness in psychology about the value that a regional perspective can add to theory and research.


title: Classification of digital camera-models based on demosaicing artifacts

abstract: We utilize traces of demosaicing operation in digital cameras to identify the source camera-model of a digital image. To identify demosaicing artifacts associated with different camera-models, we employ two methods and define a set of image characteristics which are used as features in designing classifiers that distinguish between digital camera-models. The first method tries to estimate demosaicing parameters assuming linear model while the second one extracts periodicity features to detect simple forms of demosaicing. To determine the reliability of the designated image features in differentiating the source camera-model, we consider both images taken under similar settings at fixed sceneries and images taken under independent conditions. In order to show how to use these methods as a forensics tool, we consider several scenarios where we try to (i) determine which camera-model was used to capture a given image among three, four, and five camera-models, (ii) decide whether or not a given image was taken by a particular camera-model among very large number of camera-models (in the order of hundreds), and (iii) more reliably identify the individual camera, that captured a given image, by incorporating demosaicing artifacts with noise characteristics of the imaging sensor of the camera.


title: PS-15 Floating-Gate Based CMUT Sensing Circuit Using Capacitive Feedback Charge Amplifier

abstract: This paper describes the use of a floating-gate based capacitive feedback charge amplifier as a receive circuit for CMUT and investigates the charging effects. Detailed analysis of the capacitive sensing charge amplifier along with a floating-node charge adaptation circuit is presented. Compared with conventional approaches, using a charge amplifier, instead of a transimpedance amplifier, to detect capacitance variation avoids the dilemma of sensitivity-bandwidth trade-off. A version of the capacitive sensing charge amplifier is fabricated in a 0.5 mum CMOS process. The chip contains a 8-to-1 multiplexer and is interfaced with a CMUT annular-ring array, which is designed for forward-looking intravascular ultrasound imaging applications. Pulse-echo experiment is performed in an oil bath using a planar target 3 mm away from the array and the measurement result shows the signal-to-noise ratio of 16.65 dB with 122 muW power consumption around 3 MHz. In another implementation, channel hot electron (CHE) injection and Fowler-Nordheim tunneling currents are used to adjust the charge on the floating node and stabilize the output voltage. By using open-loop configuration, the leakage current of a CMUT device is characterized


title: Comparison of recoil effects in graphite as observed by photoemission, electron scattering, and neutron scattering

abstract: Received 21 April 2008; revised manuscript received 25 May 2008; published 2 July 2008Recoil effects have been observed for neutron and electron scatterings, and in photoemission. In all caseshighly oriented pyrolytic graphite was used as a testing material and dependencies of recoil effects on thecrystal orientation were found but these results have, so far, not been compared. We show that the same theorycan describe the results of all three experiments in a quantitative way.DOI: 10.1103/PhysRevB.78.024301 PACS number s : 79.60. i, 78.70.Nx, 79.20.Kz


title: Environmental effects on the maturation of the endodermis and multiseriate exodermis of Iris germanica roots

abstract: BACKGROUND AND AIMS ::: Most studies of exodermal structure and function have involved species with a uniseriate exodermis. To extend this work, the development and apoplastic permeability of Iris germanica roots with a multiseriate exodermis (MEX) were investigated. The effects of different growth conditions on MEX maturation were also tested. In addition, the exodermises of eight Iris species were observed to determine if their mature anatomy correlated with habitat. ::: ::: ::: METHODS ::: Plants were grown in soil, hydroponics (with and without a humid air gap) or aeroponics. Roots were sectioned and stained with various dyes to detect MEX development from the root apical meristem, Casparian bands, suberin lamellae and tertiary wall thickenings. Apoplastic permeability was tested using dye (berberine) and ionic (ferric) tracers. ::: ::: ::: KEY RESULTS ::: The root apical meristem was open and MEX development non-uniform. In soil-grown roots, the exodermis started maturing (i.e. Casparian bands and suberin lamellae were deposited) 10 mm from the tip, and two layers had matured by 70 mm. In both hydro- and aeroponically grown roots, exodermal maturation was delayed. However, in areas of roots exposed to an air gap in the hydroponic system, MEX maturation was accelerated. In contrast, maturation of the endodermis was not influenced by the growth conditions. The mature MEX had an atypical Casparian band that was continuous around the root circumference. The MEX prevented the influx and efflux of berberine, but had variable resistance to ferric ions due to their toxic effects. Iris species living in well-drained soils developed a MEX, but species in water-saturated substrates had a uniseriate exodermis and aerenchyma. ::: ::: ::: CONCLUSIONS ::: MEX maturation was influenced by the roots' growth medium. The MEX matures very close to the root tip in soil, but much further from the tip in hydro- and aeroponic culture. The air gap accelerated maturation of the second exodermal layer. In Iris, the type of exodermis was correlated with natural habitat suggesting that a MEX may be advantageous for drought tolerance.


title: IT project managers' construction of successful project management practice: a repertory grid investigation

abstract: Although effective project management is critical to the success of information technology (IT) projects, little empirical research has investigated skill requirements for IT project managers (PMs). This study addressed this gap by asking 19 practicing IT PMs to describe the skills that successful IT PMs exhibit. A semi-structured interview method known as the repertory grid (RepGrid) technique was used to elicit these skills. Nine skill categories emerged: client management, communication, general management, leadership, personal integrity, planning and control, problem solving, systems development and team development. Our study complements existing research by providing a richer understanding of several skills that were narrowly defined (client management, planning and control, and problem solving) and by introducing two new skill categories that had not been previously discussed (personal integrity and team development). Analysis of the individual RepGrids revealed four distinct ways in which study participants combined skill categories to form archetypes of effective IT PMs. We describe these four IT PM archetypes – General Manager, Problem Solver, Client Representative and Balanced Manager – and discuss how this knowledge can be useful for practitioners, researchers and educators. The paper concludes with suggestions for future research.


title: Undergraduate medical education for the 21st century: leadership and teamwork.

abstract: BACKGROUND ::: The health care delivery system is experiencing enormous flux. The knowledge and skills sets required of today's physicians include expertise in competency areas that have not been included in the traditional medical curricula. The Undergraduate Medical Education for the 21st Century (UME-21) project was designed to develop innovative curricula that addressed the training necessary for medical students to gain skills required to provide high-quality, accessible, and affordable care in the modern health care environment. One of the nine UME-21 content areas, leadership and teamwork, has historically received relatively little attention in medical education. ::: ::: ::: METHODS ::: Each school participating in the UME-21 project submitted a final report that provided information for this descriptive summary of curricular innovations for teaching the concepts of leadership and teamwork to medical students. A classification lexicon for the curricular content and experiences in this content area was derived from these UME-21 project reports. Each school evaluated its curricular innovations independently using a variety of methods, largely descriptive and qualitative in nature. ::: ::: ::: RESULTS ::: Eight UME-21 schools developed curricula addressing the content area of leadership and teamwork. The majority of these curricula used the clinical care teams in the clinical rotations to demonstrate the principles and importance of leadership and teamwork. Three of the schools implemented didactic sessions and workshops to explicitly address leadership and teamwork. One school used the gross anatomy dissection teams as the "laboratory" for demonstrating this content material. The evaluations of these curricular efforts showed them to be positively regarded by the medical students. Outcomes of measurable changes in competency in this area of expertise were not evaluated. ::: ::: ::: CONCLUSIONS ::: There is little past experience in teaching leadership and teamwork in medical school. The UME-21 project supported the design and implementation of several curricular innovations in this content area, which were well received by learners. These eight leadership and teamwork curricula are described, a lexicon outlining the specific content that was addressed in this content area is presented, and lessons learned are included in this report. Further efforts to demonstrate the mastery of new skills in this important content area, based on curricula such as these, are needed.


title: Enhanced Low-Rank Matrix Approximation

abstract: This letter proposes to estimate low-rank matrices by formulating a convex optimization problem with non-convex regularization. We employ parameterized non-convex penalty functions to estimate the non-zero singular values more accurately than the nuclear norm. A closed-form solution for the global optimum of the proposed objective function (sum of data fidelity and the non-convex regularizer) is also derived. The solution reduces to singular value thresholding method as a special case. The proposed method is demonstrated for image denoising.


title: Design and Experimental Validation of a Cooperative Driving System in the Grand Cooperative Driving Challenge

abstract: In this paper, we present the Cooperative Adaptive Cruise Control (CACC) architecture, which was proposed and implemented by the team from Chalmers University of Technology, Goteborg, Sweden, that joined the Grand Cooperative Driving Challenge (GCDC) in 2011. The proposed CACC architecture consists of the following three main components, which are described in detail: 1) communication; 2) sensor fusion; and 3) control. Both simulation and experimental results are provided, demonstrating that the proposed CACC system can drive within a vehicle platoon while minimizing the inter-vehicle spacing within the allowed range of safety distances, tracking a desired speed profile, and attenuating acceleration shockwaves.


title: MVC architecture driven restructuring to achieve client-side web page composition

abstract: This paper presents a restructuring approach to relocating web page composition from servers to browsers for Java web applications. The objective is to reduce redundant manipulation and transfer of code/data that are shared by web pages. The reduction is carried out through a restructuring algorithm, effectively keeping consistency between source and target applications from the perspective of the model-view-controller (MVC) architecture, because the problem requires the target application to preserve the observable behavior of its source application. Case studies show that our restructuring tool can efficiently support the restructuring process.


title: Wireless Body Area Network (WBAN): A Survey on Reliability, Fault Tolerance, and Technologies Coexistence

abstract: Wireless Body Area Network (WBAN) has been a key element in e-health to monitor bodies. This technology enables new applications under the umbrella of different domains, including the medical field, the entertainment and ambient intelligence areas. This survey paper places substantial emphasis on the concept and key features of the WBAN technology. First, the WBAN concept is introduced and a review of key applications facilitated by this networking technology is provided. The study then explores a wide variety of communication standards and methods deployed in this technology. Due to the sensitivity and criticality of the data carried and handled by WBAN, fault tolerance is a critical issue and widely discussed in this paper. Hence, this survey investigates thoroughly the reliability and fault tolerance paradigms suggested for WBANs. Open research and challenging issues pertaining to fault tolerance, coexistence and interference management and power consumption are also discussed along with some suggested trends in these aspects.


title: Sources and Perceived Credibility of Vaccine-Safety Information for Parents

abstract: RESULTS: The response rate was 62%. Parents reported trusting their children’s doctor for vaccine-safety information most often (76% endorsed a lot of trust), followed by other health care providers (26%), government vaccine experts/officials (23%), and family and friends (15%). In contrast, celebrities were trusted a lot by 2% of the respondents and not at all by 76% of the respondents. Levels of trust in specific sources of vaccine-safety information varied significantly by gender (women men) and race/ethnicity (Hispanics other groups). CONCLUSIONS: Although most parents place a lot of trust in their child(ren)’s physician, parents’ trust in non– health professional sources for such information should not be discounted. Those who design public health efforts to provide evidence-based information must recognize that different strategies may be required to reach some groups of parents who use other information sources. Pediatrics 2011;127:S107–S112