Miracle-dz/UniFAR-FTUs huggingface dataset:
Meta-analysis of nonpharmacological interventions for neuropsychiatric symptoms of dementia.

OBJECTIVE Behavioral and psychological symptoms are common in dementia, and they are especially stressful for family caregivers. Nonpharmacological (or psychosocial) interventions have been shown to be effective in managing behavioral and psychological symptoms, but mainly in institutional settings. The authors reviewed the effectiveness of community-based nonpharmacological interventions delivered through family caregivers. METHOD Of 1,665 articles identified in a literature search, 23 included unique randomized or pseudorandomized nonpharmacological interventions with family caregivers and outcomes related to the frequency or severity of behavioral and psychological symptoms of dementia, caregiver reactions to these symptoms, or caregiver distress attributed to these symptoms. Studies were rated according to an evidence hierarchy for intervention research. RESULTS Nonpharmacological interventions were effective in reducing behavioral and psychological symptoms, with an overall effect size of 0.34 (95% CI=0.20-0.48; z=4.87; p<0.01), as well as in ameliorating caregiver reactions to these behaviors, with an overall effect size of 0.15 (95% CI=0.04-0.26; z=2.76; p=0.006). CONCLUSIONS Nonpharmacological interventions delivered by family caregivers have the potential to reduce the frequency and severity of behavioral and psychological symptoms of dementia, with effect sizes at least equaling those of pharmacotherapy, as well as to reduce caregivers' adverse reactions. The successful interventions identified included approximately nine to 12 sessions tailored to the needs of the person with dementia and the caregiver and were delivered individually in the home using multiple components over 3-6 months with periodic follow-up.
An efficient fusion method of distance metric learning and random forests distance for image verification

Generally, the distance metric learning method using sample classifier (such as Euclidean distance computing) can not achieve perfect classification performance for the image verification. Nevertheless, the random forests distance method (RFD) can overcome the shortcoming of distance metric learning since it can handle the heterogeneous data well. In addition, the distance metric learning method can reduce the training time of RFD because it can remove the data correlation. Therefore this paper proposes a fusion method of distance metric learning and random forests distance. We obtain a matrix M using the distance metric learning method and use it to linearly transform the sample space, then we classify new samples by RFD. We experiment on LFW, Pubfig and ToyCars datasets and the results show that our proposed fusion method outperforms the single distance metric learning method or RFD in the recognition accuracy; the training time of RFD is much less in the transformed sample space.
Recognizing terrain features on terrestrial surface using a deep learning model: an example with crater detection

This paper exploits the use of a popular deep learning model - the faster-RCNN - to support automatic terrain feature detection and classification using a mixed set of optimal remote sensing and natural images. Crater detection is used as the case study in this research since this geomorphological feature provides important information about surface aging. Craters, such as impact craters, also effect global changes in many aspects, such as geography, topography, mineral and hydrocarbon production, etc. The collected data were labeled and the network was trained through a GPU server. Experimental results show that the faster-RCNN model coupled with a widely used convolutional network ZF-net performs well in detecting craters on the terrestrial surface.
Automatic cognitive load detection from speech features

Cognitive load variations have been found to impact multimodal behaviour, in particular, features of spoken input. In this paper, we present a design and implementation of a user study aimed at soliciting natural speech at three different levels of cognitive load. Some of the speech data produced was then used to train a number of models to automatically detect cognitive load. We describe a classification approach, the cognitive load levels were detected and output as discrete level ranges. The final system achieved a 71.1% accuracy for 3 levels classification in a speaker-independent setting. The ability to detect and manage a user's cognitive load can help us to adapt intelligent interfaces that ensure optimal user performance
Large-Scale Parallel Breadth-First Search

Recently, best-first search algorithms have been introduced that store their nodes on disk, to avoid their inherent memory limitation. We introduce several improvements to the best of these, including parallel processing, to reduce their storage and time requirements. We also present a linear-time algorithm for bijectively mapping permutations to integers in lexicographic order. We use breadth-first searches of sliding-tile puzzles as testbeds. On the 3×5 Fourteen Puzzle, we reduce both the storage and time needed by a factor of 3.5 on two processors. We also performed the first complete breadth-first search of the 4×4 Fifteen Puzzle, with over 1013 states.
Real-Time 3D Facial Subtle Expression Control Based on Blended Normal Maps

Facial expression details can largely enhance the realistic facial animation. In this paper, we proposed a method to realize real-time control of 3D facial subtle expression, such as wrinkles and bulges, based on a set of normal maps. At runtime, we used a kinect to get the animation units for calculating control parameter. Normal blending technology was used to blend the base normal map and the detail normal map. A UV mask was combined with the blended normal map to achieve a good local control of facial subtle facial expression in real time.
Saccades and the Muller-Lyer illusion: implications for the two-visual-systems hypothesis

Background and aim: The cortical visual system is divided anatomically into the dorsal and ventral stream. Goodale and Milner in 1992 proposed that this division was functional: the dorsal stream processes ‘vision-for-action’ whereas the ventral stream processes ‘vision-for-perception’. This model of vision is known as the ‘two-visual-systems hypothesis’ (TVSH). Pictorial illusions, such as the Mu¨ ller-Lyer (ML) illusion, have been used by advocates of the TVSH to demonstrate dissociation between visionfor-action and vision-for-perception in healthy subjects. However, this literature is controversial, and not least in experiments investigating the magnitude of the illusion effect on saccades. This review aims to synthesise and critically evaluate evidence from saccade experiments on the effect of the ML illusion, in order to determine whether it provides support for the TVSH. Methods: Literature searches were performed using the Web of Science, Google Scholar and PubMed. Text books were referred to for additional information. Data were extracted from relevant papers and collated using Microsoft Excel. Statistical analysis was performed using SPSS. Results: Analysis revealed that saccades are affected by the ML illusion. The magnitude of the illusion effect on saccades is comparable to its effect on perception. Reflexive saccades are affected by the illusion, yet they receive little input from the ventral stream. This is inconsistent with the TVSH as it demonstrates that a dorsally controlled action is affected by a perceptual illusion. Conclusion: Evidence from experiments on the effect of the ML illusion on saccades provides no general support for the TVSH.
Two-scale particle simulation

We propose a two-scale method for particle-based fluids that allocates computing resources to regions of the fluid where complex flow behavior emerges. Our method uses a low- and a high-resolution simulation that run at the same time. While in the coarse simulation the whole fluid is represented by large particles, the fine level simulates only a subset of the fluid with small particles. The subset can be arbitrarily defined and also dynamically change over time to capture complex flows and small-scale surface details. The low- and high-resolution simulations are coupled by including feedback forces and defining appropriate boundary conditions. Our method offers the benefit that particles are of the same size within each simulation level. This avoids particle splitting and merging processes, and allows the simulation of very large resolution differences without any stability problems. The model is easy to implement, and we show how it can be integrated into a standard SPH simulation as well as into the incompressible PCISPH solver. Compared to the single-resolution simulation, our method produces similar surface details while improving the efficiency linearly to the achieved reduction rate of the particle number.
Virus-ECC-mPLoc: a multi-label predictor for predicting the subcellular localization of virus proteins with both single and multiple sites based on a general form of Chou's pseudo amino acid composition.

Protein subcellular localization aims at predicting the location of a protein within a cell using computational methods. Knowledge of subcellular localization of viral proteins in a host cell or virus-infected cell is important because it is closely related to their destructive tendencies and consequences. Prediction of viral protein subcellular localization is an important but challenging problem, particularly when proteins may simultaneously exist at, or move between, two or more different subcellular location sites. Most of the existing protein subcellular localization methods specialized for viral proteins are only used to deal with the single-location proteins. To better reflect the characteristics of multiplex proteins, a new predictor, called Virus-ECC-mPLoc, has been developed that can be used to deal with the systems containing both singleplex and multiplex proteins by introducing a powerful multi-label learning approach which exploits correlations between subcellular locations and by hybridizing the gene ontology information with the dipeptide composition information. It can be utilized to identify viral proteins among the following six locations: (1) viral capsid, (2) host cell membrane, (3) host endoplasmic reticulum, (4) host cytoplasm, (5) host nucleus, and (6) secreted. Experimental results show that the overall success rates thus obtained by Virus-ECC-mPLoc are 86.9% for jackknife test and 87.2% for independent data set test, which are significantly higher than that by any of the existing predictors. As a user-friendly web-server, Virus-ECCmPLoc is freely accessible to the public at the web-site http://levis.tongji. edu.cn:8080/bioinfo/Virus-ECC-mPLoc/.
Concurrent Core Test for SOC Using Shared Test Set and Scan Chain Disable

A concurrent core test approach is proposed to reduce the test cost of SOC. Multiple cores in SOC can be tested simultaneously by using a shared test set and scan chain disable. Prior to test, the test sets corresponding to cores under test (CUT) are merged by using the proposed merging algorithm to obtain a shared test set with minimum size. During test, the on-chip scan chain disable signal (SCDS) generator is employed to retrieve the original test vectors from the shared test set. The approach is non-intrusive and automatic test pattern generator (ATPG) independent. Moreover, the approach can reduce test cost further by combining with general test compression/decompression technique. Experimental results for ISCAS 89 benchmark circuits have proven the efficiency of the proposed approach
Energy expenditure and plasma F2-isoprostanes across the menstrual cycle.

INTRODUCTION Habitual energy expenditure seems to favorably alter oxidant/antioxidant balance. Sparse evidence suggests that hormones that fluctuate during the menstrual cycle, particularly estrogens, may influence concentrations of oxidative biomarkers and their relation to energy expenditure. METHODS We investigated the relation between energy expenditure and plasma free F2-isoprostane concentrations in 259 healthy, regularly menstruating 18- to 44-yr-old participants of the BioCycle Study. Habitual energy expenditure was measured using a baseline International Physical Activity Questionnaire and categorized as low, moderate, or high. Women were followed for one or two subsequent menstrual cycles. Past-week and past-day physical activity were measured during follow-up using questionnaires and diaries, respectively. F2-isoprostane concentrations were measured in blood samples collected at both menses (approximate cycle day 2; low serum estradiol concentration) and the late follicular phase (approximate cycle day 12; peak estradiol concentration). Generalized estimating equations were used to model the energy expenditure/isoprostane association, adjusting for confounders. RESULTS Habitual energy expenditure was positively associated with F2-isoprostane concentration (adjusted difference in median F2-isoprostane, high versus low energy expenditure: 17.4%; 95% confidence interval (CI)=3.3%-31.4%). This association was not modified by cycle phase (interaction, P=0.61) or differences in peak estradiol concentration across women (interaction, P=0.20). Past-week and past-day physical activity measures were not associated with F2-isoprostane concentration (category trend, P=0.50 and P=0.18, respectively). CONCLUSIONS These results suggest that higher habitual energy expenditure may be associated with higher concentration of F2-isoprostanes in healthy, reproductive-aged women. Estradiol concentration changes during the menstrual cycle do not seem to influence this relationship.
Linkage, aggregation, alignment and enrichment of public user profiles with Mypes

Today, users leave a plethora of traces on the Web. They fill traditional profile information at social networking services, write articles in their personal blogs or annotate social media content in resource sharing systems such as Flickr or Delicious. In this paper we present the so-called Mypes service that connects, aggregates, aligns and enriches profile information form diverse online services and makes the bundled profiles available for end-users and third-party applications. It enables end-users to overview their distributed profile data traces and provides application developers means for integrating aggregated profile data into their applications to feature personalization. Our evaluation reveals the benefits of Mypes: it generates semantically rich user profiles with high precision.
Early detection of ototoxicity using 1/6th-octave steps.

The National Center for Rehabilitative Auditory Research has developed a protocol to provide early identification of ototoxicity for patients receiving ototoxic medications. The initial work involved patients with relatively good high-frequency hearing and resulted in the use of an individualized, sensitive frequency range separated by 1/6th-octave intervals. This protocol tested pure-tone frequencies at 1/6th-octave steps above 9 kHz, but only conventional audiometric frequencies were tested below 9 kHz. More recently, the testing protocol was expanded to include 1/6th-octave testing below 9 kHz. The primary question of interest was to determine whether adding 1/6th-octave test frequencies below 9 kHz would increase the ototoxicity detection rate for patients with poorer hearing. Results indicated 76 of the 210 (36.2%) ears that demonstrated initial ototoxic hearing change would have been missed or detected later if only conventional frequency testing was conducted.Therefore, for individuals with poorer hearing, expanding the use of the 1/6th-octave test protocol provides earlier identification of ototoxicity.
Neuronal Cell Death in Scrapie‐Infected Mice Is Due to Apoptosis

Neuronal loss is a salient yet poorly understood feature in the pathology of transmissible spongiform encephalopathies (prion diseases). Cell culture experiments with neurotoxic prion protein fragments suggest that neuronal cell death in these diseases may be due to apoptosis. To test this hypothesis in vivo we used the in situ end‐labeling (ISEL) technique and electron microscopy to study cell death in an experimental scrapie system in the mouse. ISEL, which relies on the incorporation of labeled nucleotides in fragmented DNA by terminal transferase, showed labeled nuclei in the brains and retinae of mice infected with the 79A strain of scrapie, whereas no labeling was observed in control animals. In the retina the highest numbers of labeled nuclei were found in the outer nuclear layer 120 days post infection followed by massive cell loss in this layer. In the brain, labeled nuclei were mainly found in the granular layer of the cerebellum of terminally ill mice. This corresponded to the presence of small dark nuclei with condensed and occasionally fragmented chromatin at the light and electron microscopical levels. Our results support the hypothesis that neuronal loss in spongiform encephalopathies is due to apoptosis. This may explain the almost complete absence of inflammatory response in prion diseases in the face of widespread neuronal cell death, and may also have therapeutic implications in the future.
Interaction Through Technological Lenses

In 2004, the second International Association of Language and Social Psychology Task Force focused on relationships involving language and emerging communication technology, culminating in a Special Issue of the Journal of Language and Social Psychology (Vol. 23, No. 4). The present article reviews the topics and conclusions of that work and traces the continuation of study on those topics as they have evolved and influenced language and social psychology research to the present. Communication technology research offers views on the central question of how individuals adapt language to communicative action in the presence or absence of various nonverbal cue systems. This question is reflected in topics such as the expression of affect and immediacy online, the virtual presentation of self and gender, the management of online conversations, adaptation via visual grounding in electronic collaboration, and the employment of online interaction technology to reduce intergroup prejudice. As communication systems have evolved, interfaces offer new cues and representations of users, which continue to propel inquiry into these central questions about language and its usage within various technological contexts.
MFCC and Prosodic Feature Extraction Techniques: A Comparative Study

In this paper our main aim to provide the difference between cepstral and non-cepstral feature extraction techniques. Here we try to cover-up most of the comparative features of Mel Frequency Cepstral Coefficient and prosodic features. In speaker recognition, there are two type of techniques are available for feature extraction: Short-term features i.e. Mel Frequency Cepstral Coefficient (MFCC) and long-term features (Prosodic) extraction techniques. In this paper, we explore the usefulness of prosodic features for syllable classification and MFCC for feature extraction of a speech signal followed by comparison between them. The Me1 Frequency Cepstral Coefficients (MFCC) is one of the most important features extraction techniques, which is required among various kinds of speech applications. The MFCC features are extracted from the speaker phonemes in the presegmented speech sentences. Now days Prosodic features are currently used in most emotion recognition algorithms Prosodic features are relatively simple in their structures and known for their effectiveness in some speech recognition tasks. There are various ways of generating prosodic syllable contour features that have recently been applied to enhance systems for speaker recognition.
UofR at SemEval-2016 Task 8: Learning Synchronous Hyperedge Replacement Grammar for AMR Parsing

In this paper, we apply a synchronous-graph-grammar-based approach to SemEval-2016 Task 8, Meaning Representation Parsing. In particular, we learn Synchronous Hyperedge Replacement Grammar (SHRG) rules from aligned pairs of sentences and AMR graphs. Then we use Earley algorithm with cube-pruning for AMR parsing given new sentences and the learned SHRG. Experiments on the evaluation dataset demonstrate that competitive results can be achieved using a SHRG-based approach.
Analysis of human CD4 T lymphocyte proliferation induced by porcine lymphoblastoid B cell lines

Bonenfant C, Vallée I, Sun J, Brossay A, Thibault G, Guillaumin JM, Lebranchu Y, Bardos P, Butler JE, Watier H. Analysis of human CD4 T lymphocyte proliferation induced by porcine lymphoblastoid B cell lines. Xenotransplantation 2003; 10: 107–119. © Blackwell Munksgaard, 2003
Review of the State of Art of Tunable Impulse Ultra-Wideband Technology as Integrator for Wireless Sensing and Identifications Short-Range Networks

Impulse based Ultra wideband technology has been the motivation of many recent researches with the potential of many applications to be researched. The uniqueness of the physical characteristics of the generated signal combined with the high flexibility of for different data rates at the physical layer design level have been addressed in considerable number of researches recently. This paper presents in depth reviews of the different concepts of tunable impulse based ultra wideband from the different researchers views. Research proposals of Cross layer architectures as PHY-MAC aware Impulse based ultra wideband solutions, link-budget communication design with performance evaluations in different test beds implementations are investigated in this paper. Such in-depth review can help researchers in this field to have better understanding of the different possibilities of designing new impulse-based ultra wideband solutions for future potential communication scenarios. Special focus on utilizing the advantage of impulse-based ultra wideband signal design flexibility as integrator for different short to medium wireless infrastructures mainly sharing common design constraints and requirements. Finding remarks from reviewing nearest-field literature combined with researches benchmarking to inspire researches proposal for this topic.
Reliability and validity of the Functional Assessment of Cancer Therapy-Breast quality-of-life instrument.

PURPOSE This is the first published report on the validation of the Functional Assessment of Cancer Therapy-Breast (FACT-B), a 44-item self-report instrument designed to measure multidimensional quality of life (QL) in patients with breast cancer. The FACT-B consists of the FACT-General (FACT-G) plus the Breast Cancer Subscale (BCS), which complements the general scale with items specific to QL in breast cancer. The FACT-B was developed with an emphasis on patients' values and brevity and is available in nine languages. METHODS AND RESULTS Two validation samples were used for this report. The first (n = 47) was tested twice over a 2-month period to assess sensitivity to change. Significant sensitivity to change in performance status rating (PSR) was demonstrated for the FACT-B total score, the Physical Well-Being (PWB) subscale, the Functional Well-Being (FWB) subscale, and the BCS. Sensitivity to change in QL as measured by the Functional Living Index-Cancer (FLIC) was documented in the FACT-B total score, PWB, FWB, and Emotional Well-Being (EWB). Additional validity and reliability data were obtained from a larger sample (n = 295). The alpha coefficient (internal consistency) for the FACT-B total score was high (alpha = .90), with subscale alpha coefficients ranging from . 63 to . 86. Evidence supported test-retest reliability, as well as convergent, divergent, and known groups validity. CONCLUSION The FACT-B is appropriate for use in oncology clinical trials, as well as in clinical practice. It demonstrates ease of administration, brevity, reliability, validity, and sensitivity to change.