title: Semi-Supervised Approach to Monitoring Clinical Depressive Symptoms in Social Media

abstract: With the rise of social media, millions of people are routinely expressing their moods, feelings, and daily struggles with mental health issues on social media platforms like Twitter. Unlike traditional observational cohort studies conducted through questionnaires and self-reported surveys, we explore the reliable detection of clinical depression from tweets obtained unobtrusively. Based on the analysis of tweets crawled from users with self-reported depressive symptoms in their Twitter profiles, we demonstrate the potential for detecting clinical depression symptoms which emulate the PHQ-9 questionnaire clinicians use today. Our study uses a semi-supervised statistical model to evaluate how the duration of these symptoms and their expression on Twitter (in terms of word usage patterns and topical preferences) align with the medical findings reported via the PHQ-9. Our proactive and automatic screening tool is able to identify clinical depressive symptoms with an accuracy of 68% and precision of 72%.


title: Watching Subtitled Films Can Help Learning Foreign Languages

abstract: Watching English-spoken films with subtitles is becoming increasingly popular throughout the world. One reason for this trend is the assumption that perceptual learning of the sounds of a foreign language, English, will improve perception skills in non-English speakers. Yet, solid proof for this is scarce. In order to test the potential learning effects derived from watching subtitled media, a group of intermediate Spanish students of English as a foreign language watched a 1h-long episode of a TV drama in its original English version, with English, Spanish or no subtitles overlaid. Before and after the viewing, participants took a listening and vocabulary test to evaluate their speech perception and vocabulary acquisition in English, plus a final plot comprehension test. The results of the listening skills tests revealed that after watching the English subtitled version, participants improved these skills significantly more than after watching the Spanish subtitled or no-subtitles versions. The vocabulary test showed no reliable differences between subtitled conditions. Finally, as one could expect, plot comprehension was best under native, Spanish subtitles. These learning effects with just 1 hour exposure might have major implications with longer exposure times.


title: Hamstring Activation During Lower Body Resistance Training Exercises

abstract: Purpose: The purpose of this study was to evaluate differences in hamstring activation during lower body resistance training exercises. This study also sought to assess differences in hamstring-to-quadriceps muscle activation ratios and gender differences therein. Methods: A randomized repeated measures design was used to compare six resistance training exercises that are commonly believed to train the hamstrings, including the squat, seated leg curl, stiff leg dead lift, single leg stiff leg dead lift, good morning, and Russian curl. Subjects included 34 college athletes. Outcome measures included the biceps femoris (H) and rectus femoris (Q) electromyography (EMG) and the H-to-Q EMG ratio, for each exercise. Results: Main effects were found for the H (P < 0.001) and Q (P < 0.001). Post hoc analysis identified the specific differences between exercises. In addition, main effects were found for the H-to-Q ratio when analyzed for all subjects (P < 0.001). Further analysis revealed that women achieved betwe...


title: Vessels in femoral triangle in a rare relationship.

abstract: The femoral region of the thigh is utilised for various clinical procedures, both open and closed, particularly in respect to arterial and venous cannulations. A rare vascular pattern was observed during the dissection of the femoral region on both sides of the intact formaldehyde-preserved cadaver of a 42-year-old Indian man from West Bengal. The relationships and patterns found were contrary to the belief that the femoral vein is always medial to the artery, just below the inguinal ligament and the common femoral artery. The femoral artery crossed the vein just deep to the inguinal ligament so that the femoral vein was lying deep to the artery at the base of the femoral triangle. Just deep to the inguinal ligament, the profunda femoris artery (deep femoral artery) arose from the femoral artery, and the long saphenous vein drained into the femoral vein. The embryological and clinical correlations are discussed.


title: Comparing search algorithms using sorting and hashing on disk and in memory

abstract: We compare sorting and hashing for implicit graph search using disk storage. We first describe efficient pipelined implementations of both algorithms, which reduce disk I/O. We then compare the two algorithms and find that hashing is faster, but that sorting requires less disk storage. We also compare disk-based with in-memory search, and surprisingly find that there is little or no time overhead associated with disk-based search. We present experimental results on the sliding-tile puzzles, Rubik's Cube, and the 4-peg Towers of Hanoi.


title: Fully Convolutional Speech Recognition

abstract: Current state-of-the-art speech recognition systems build on recurrent neural networks for acoustic and/or language modeling, and rely on feature extraction pipelines to extract mel-filterbanks or cepstral coefficients. In this paper we present an alternative approach based solely on convolutional neural networks, leveraging recent advances in acoustic models from the raw waveform and language modeling. This fully convolutional approach is trained end-to-end to predict characters from the raw waveform, removing the feature extraction step altogether. An external convolutional language model is used to decode words. On Wall Street Journal, our model matches the current state-of-the-art. On Librispeech, we report state-of-the-art performance among end-to-end models, including Deep Speech 2 trained with 12 times more acoustic data and significantly more linguistic data.


title: Effect of Training Class Label Noise on Classification Performances for Land Cover Mapping with Satellite Image Time Series

abstract: Supervised classification systems used for land cover mapping require accurate reference databases. These reference data come generally from different sources such as field measurements, thematic maps, or aerial photographs. Due to misregistration, update delay, or land cover complexity, they may contain class label noise, i.e., a wrong label assignment. This study aims at evaluating the impact of mislabeled training data on classification performances for land cover mapping. Particularly, it addresses the random and systematic label noise problem for the classification of high resolution satellite image time series. Experiments are carried out on synthetic and real datasets with two traditional classifiers: Support Vector Machines (SVM) and Random Forests (RF). A synthetic dataset has been designed for this study, simulating vegetation profiles over one year. The real dataset is composed of Landsat-8 and SPOT-4 images acquired during one year in the south of France. The results show that both classifiers are little influenced for low random noise levels up to 25%–30%, but their performances drop down for higher noise levels. Different classification configurations are tested by increasing the number of classes, using different input feature vectors, and changing the number of training instances. Algorithm complexities are also analyzed. The RF classifier achieves high robustness to random and systematic label noise for all the tested configurations; whereas the SVM classifier is more sensitive to the kernel choice and to the input feature vectors. Finally, this work reveals that the cross-validation procedure is impacted by the presence of class label noise.