Miracle-dz/UniFAR-FTUs huggingface dataset:
Confidence weighting missing feature approach for robust speech recognition

Missing feature theory (MFT) has been proposed as a solution for robust speech recognition. It improves robustness of speech recognition systems by either ignoring or compensating the unreliable components of feature vectors corrupted mainly by band-limited background noise. Since the local corruption often occurs in the frequency domain and it is smeared by the Discrete Cosine Transform (DCT) used to obtain cepstral features, algorithms utilizing the missing feature theory are usually restricted to spectral features. In many cases cepstral features might be preferable. In this paper, we propose a new missing feature approach (CWMFA) based on confidence analysis of feature vector and successfully apply it on cepstral features. In the new approach, probabilities of feature vector components are weighted with its confidence in logarithmic domain. Experimental results show that the proposed approach can manifestly improve robustness of speech recognition systems.
Optimistic bias in the perception of personal risk: patterns in schizophrenia.

OBJECTIVE Biases in the perception of personal vulnerability to risk could influence how individuals make decisions in many contexts. Schizophrenia patients, because of neurocognitive deficits and psychiatric symptoms, are often seen as compromised in their ability to appreciate risk information and in their decision-making capacity. The authors investigated whether schizophrenia patients share the same optimistic biases frequently demonstrated by non-ill adults in their perceptions of personal risk. METHOD Twenty-five schizophrenic outpatients and 23 healthy comparison subjects completed a risk perception questionnaire on which they compared their own likelihood of experiencing adverse events to that of other adults. Questionnaire items were adverse events of three types: controllable, uncontrollable, and neutral. The degree to which subjects rated their own likelihood of experiencing adverse events as lower than others' was an index of optimistic bias. RESULTS Although both groups showed an optimistic bias in general, healthy comparison subjects demonstrated a greater level of optimism than did schizophrenia patients, especially for events typically perceived as controllable. Psychiatric symptoms rated with the Brief Psychiatric Rating Scale and the Scale for the Assessment of Negative Symptoms bore little relationship to patients' ratings on the risk questionnaire. CONCLUSIONS Results showed that an unrealistically optimistic bias in the perception of personal risk was at least as evident in a healthy comparison group as in a schizophrenia group. Such a bias could influence decision making. By identifying and responding to such biases, clinicians and researchers can promote more fully informed and rational decisions in patients and healthy adults.
Human Dynamics in Large Communication Networks

How often humans communicate with each other? What are the mechanisms that explain how human actions are distributed over time? Here we answer these questions by studying the time interval between calls and SMS messages in an anonymized, large mobile network, with 3.1 million users, over 200 million phone calls and 300 million SMS messages,spanning 70 GigaBytes. Our first contribution is the Truncated Autocatalytic Process (TAP ) model, that explains the time between communication events (ie., times between phone-initiations) for a single individual. The novelty is that the model is ’autocatalytic’, in the sense that the parameters of the model change, depending on the latest inter-event time: long periods of inactivity in the past result in long periods of inactivity in the future, and vice-versa. We show that the TAP model mimics the inter-event times of the users of our dataset extremely well, despite its parsimony and simplicity. Our second contribution is the TAP-classifier , a classification method based on the interevent times and in addition to other features. We showed that the inferred sleep intervals and the reciprocity between outgoing and incoming calls are good features to classify users. Finally, analyze the network effects of each class of users and we found surprising results. Moreover, all of our methods are fast, and scale linearly with the number of customers.
Prestin Regulation and Function in Residual Outer Hair Cells after Noise-Induced Hearing Loss

The outer hair cell (OHC) motor protein prestin is necessary for electromotility, which drives cochlear amplification and produces exquisitely sharp frequency tuning. TectaC1509G transgenic mice have hearing loss, and surprisingly have increased OHC prestin levels. We hypothesized, therefore, that prestin up-regulation may represent a generalized response to compensate for a state of hearing loss. In the present study, we sought to determine the effects of noise-induced hearing loss on prestin expression. After noise exposure, we performed cytocochleograms and observed OHC loss only in the basal region of the cochlea. Next, we patch clamped OHCs from the apical turn (9–12 kHz region), where no OHCs were lost, in noise-exposed and age-matched control mice. The non-linear capacitance was significantly higher in noise-exposed mice, consistent with higher functional prestin levels. We then measured prestin protein and mRNA levels in whole-cochlea specimens. Both Western blot and qPCR studies demonstrated increased prestin expression after noise exposure. Finally, we examined the effect of the prestin increase in vivo following noise damage. Immediately after noise exposure, ABR and DPOAE thresholds were elevated by 30–40 dB. While most of the temporary threshold shifts recovered within 3 days, there were additional improvements over the next month. However, DPOAE magnitudes, basilar membrane vibration, and CAP tuning curve measurements from the 9–12 kHz cochlear region demonstrated no differences between noise-exposed mice and control mice. Taken together, these data indicate that prestin is up-regulated by 32–58% in residual OHCs after noise exposure and that the prestin is functional. These findings are consistent with the notion that prestin increases in an attempt to partially compensate for reduced force production because of missing OHCs. However, in regions where there is no OHC loss, the cochlea is able to compensate for the excess prestin in order to maintain stable auditory thresholds and frequency discrimination.
Fine Structure of Parvocellular Receptive Fields in the Primate Fovea Revealed by Laser Interferometry

Optical blurring in the eye prevents conventional physiological techniques from revealing the fine structure of the small parvocellular receptive fields in the primate fovea in vivo. We explored the organization of receptive fields in macaque parvocellular lateral geniculate nucleus cells by using sinusoidal interference fringes formed directly on the retina to measure spatial frequency tuning at different orientations. Most parvocellular cells in and near the fovea respond reliably to spatial frequencies up to and beyond 100 cycles/° of visual angle, implying center input arising mainly from a single cone. Temporal frequency and contrast response characteristics were also measured at spatial frequencies up to 130 cycles/°. We compared our spatial frequency data with the frequency responses of model receptive fields that estimate the number, configuration, and weights of cones that feed the center and surround. On the basis of these comparisons, we infer possible underlying circuits. Most cells had irregular spatial frequency–response curves that imply center input from more than one cone. The measured responses are consistent with a single cone center together with weak input from nearby cones. By exposing a fine structure that cannot be discerned by conventional techniques, interferometry allows functional measurements of the early neural mechanisms in spatial vision.
Recombinant Acylation Stimulating Protein Administration to C3−/− Mice Increases Insulin Resistance via Adipocyte Inflammatory Mechanisms

Background Complement 3 (C3), a key component of the innate immune system, is involved in early inflammatory responses. Acylation stimulating protein (ASP; aka C3adesArg), a C3 cleavage product, is produced in adipose tissue and stimulates lipid storage. We hypothesized that, depending on the diet, chronic ASP administration in C3−/− mice would affect lipid metabolism and insulin sensitivity via an adaptive adipose tissue inflammatory response. Methodology/Principal Findings C3−/− mice on normal low fat diet (ND) or high fat diet (HFD) were chronically administered recombinant ASP (rASP) for 25 days via an osmotic mini-pump. While there was no effect on food intake, there was a decrease in activity, with a relative increase in adipose tissue weight on ND, and a shift in adipocyte size distribution. While rASP administration to C3−/− mice on a ND increased insulin sensitivity, on a HFD, rASP administration had the opposite effect. Specifically, rASP administration in C3−/− HFD mice resulted in decreased gene expression of IRS1, GLUT4, SREBF1 and NFκB in muscle, and decreased C5L2 but increased JNK, CD36, CD11c, CCR2 and NFκB gene expression in adipose tissue as well as increased secretion of proinflammatory cytokines (Rantes, KC, MCP-1, IL-6 and G-CSF). In adipose tissue, although IRS1 and GLUT4 mRNA were unchanged, insulin response was reduced. Conclusion The effects of chronic rASP administration are tissue and diet specific, rASP administration enhances the HFD induced inflammatory response leading to an insulin-resistant state. These results suggest that, in humans, the increased plasma ASP associated with obesity and cardiovascular disease could be an additional factor directly contributing to development of metabolic syndrome, insulin resistance and diabetes.
Limitations of Incremental Dynamic Programs

We consider so-called “incremental” dynamic programming algorithms, and are interested in the number of subproblems produced by them. The standard dynamic programming algorithm for the n-dimensional Knapsack problem is incremental, produces nK subproblems and nK relations (wires) between the subproblems, where K is the capacity of the knapsack. We show that any incremental algorithm for this problem must produce about nK subproblems, and that about nK log K wires (relations between subproblems) are necessary.
A Storage Service based on P2P Cloud System

During the last years, cloud computing has been quickly adopted worldwide, and several solutions have emerged. Cloud computing is used to providing storage service, computing power and flexibility to end-users, in order to access data from anywhere at any time. Although, all benefits introduced by cloud computing, this technology still faces several challenges related to privacy, security, robustness, scalability and throughput. Many of these problems are due to the fact that traditional cloud computing is based on centralized servers, who are responsible for the management and storage all data. This paper proposes a P2P infrastructure as alternative platform for deploying cloud storage services. In particular, we are interested in exploring cloud computing for personal storage services.
A Cross Training Corrective Approach for Web Pages Classification

Textual document classification is one challenging area of data mining. Web page classification is a type of textual document classification. However, the text contained in web pages is not homogenous since a web page can discuss related but different subjects. Thus, results obtained by a textual classifier on web pages are not as better as those obtained on textual documents. Therefore, we need to use a method to enhance results of those classifiers or more precisely a technique to correct their results. One category of techniques that address this problem is to use the test set hidden underlying information to correct results assigned by a textual classifier. In this paper, we propose a method that belongs to this category. Our method is a Cross Training based Corrective approach (CTC) for web page classification that learns information from the test set in order to fix classes initially assigned by a text classifier on that test set. This adjustment leads to a significant improvement on classification results. We tested our approach using three traditional classification algorithms: Support Vector Machine (SVM), Naive Bayes (NB) and K Nearest Neighbors (KNN), on four subsets of the Open Directory Project (ODP). Results show that our collective and corrective approach, when applied after SVM, NB or KNN, enhances their classification results by up to 12.39%.
The Intellectual Structure of the American Behavioral Scientist: Five Decades of Research

Over the past 50 years, the American Behavioral Scientist has become one of the most representative journals within the social and behavioral sciences field. The journal has disseminated large amounts of knowledge, which has increased the complexity of having a global picture of its contributions. The aim of this research is to identify and visualize the intellectual structure of this journal in order to appreciate the changes that have taken place over the five decades since its establishment. Following a bibliometric methodology, the most active research areas of the journal, the main contributors, knowledge sources, dissemination paths, as well as the emerging tendencies are identified within this article.
On-line topical importance estimation: an effective focused crawling algorithm combining link and content analysis

Focused crawling is an important technique for topical resource discovery on the Web. The key issue in focused crawling is to prioritize uncrawled uniform resource locators (URLs) in the frontier to focus the crawling on relevant pages. Traditional focused crawlers mainly rely on content analysis. Link-based techniques are not effectively exploited despite their usefulness. In this paper, we propose a new frontier prioritizing algorithm, namely the on-line topical importance estimation (OTIE) algorithm. OTIE combines link- and content-based analysis to evaluate the priority of an uncrawled URL in the frontier. We performed real crawling experiments over 30 topics selected from the Open Directory Project (ODP) and compared harvest rate and target recall of the four crawling algorithms: breadth-first, link-context-prediction, on-line page importance computation (OPIC) and our OTIE. Experimental results showed that OTIE significantly outperforms the other three algorithms on the average target recall while maintaining an acceptable harvest rate. Moreover, OTIE is much faster than the traditional focused crawling algorithm.
Interaction of the Xanthine Nucleotide Binding Goα Mutant with G Protein-coupled Receptors*

We constructed a double mutant version of the α subunit of Go that was regulated by xanthine nucleotides instead of guanine nucleotides (GoαX). We investigated the interaction between GoαX and G protein-coupled receptors in vitro. First, we found that the activated m2 muscarinic cholinergic receptor (MAChR) could facilitate the exchange of XTPγS for XDP in the GoαXβγ heterotrimer. Second, the GoαXβγ complex was able to induce the high affinity ligand-binding state in the N-formyl peptide receptor (NFPR). These experiments demonstrated that GoαX was able to interact effectively with G protein-coupled receptors. Third, we found that the empty form of GoαX, lacking a bound nucleotide and βγ, formed a stable complex with the m2 muscarinic cholingeric receptor associated with the plasma membrane. Finally, we investigated the interaction of GoαX with receptor in COS-7 cells. The empty form of GoαX bound tightly to the receptor and was not activated because XTP was not available intracellularly. We tested the ability of GoαX to inhibit the activities of several different G protein-coupled receptors in transfected COS-7 cells and found that GoαX specifically inhibited Go-coupled receptors. Thus the modified G proteins may act as dominant-negative mutants to trap and inactivate specific subsets of receptors.
Neural control of computer cursor velocity by decoding motor cortical spiking activity in humans with tetraplegia

Computer-mediated connections between human motor cortical neurons and assistive devices promise to improve or restore lost function in people with paralysis. Recently, a pilot clinical study of an intracortical neural interface system demonstrated that a tetraplegic human was able to obtain continuous two-dimensional control of a computer cursor using neural activity recorded from his motor cortex. This control, however, was not sufficiently accurate for reliable use in many common computer control tasks. Here, we studied several central design choices for such a system including the kinematic representation for cursor movement, the decoding method that translates neuronal ensemble spiking activity into a control signal and the cursor control task used during training for optimizing the parameters of the decoding method. In two tetraplegic participants, we found that controlling a cursor's velocity resulted in more accurate closed-loop control than controlling its position directly and that cursor velocity control was achieved more rapidly than position control. Control quality was further improved over conventional linear filters by using a probabilistic method, the Kalman filter, to decode human motor cortical activity. Performance assessment based on standard metrics used for the evaluation of a wide range of pointing devices demonstrated significantly improved cursor control with velocity rather than position decoding.
Evaluation of Suicide Risk Assessment Measures in an Israel Defense Forces Military Sample

ABSTRACT The present study evaluates the psychometric properties of 4 commonly used measures of suicidal ideation and behaviors (Beck Scale for Suicide Ideation [BSS], Columbia-Suicide Severity Rating Scale [C-SSRS], Self-Harm Behavior Questionnaire [SHBQ], and Suicidal Behaviors Questionnaire—Revised [SBQ–R]) among a sample of Israel Defense Forces (IDF) soldiers. Measures were translated to Hebrew and completed by 65 active duty IDF soldiers who were recently hospitalized for at least 24 hours following a suicide attempt. Internal consistency and Pearson's r correlation analyses were conducted for all measures to test the reliability and validity of the measures. Findings support the reliability and validity of common suicide risk assessment measures among a sample of IDF soldiers. Instruments demonstrated acceptable-to-excellent internal consistency (αs = .72 to .93), save for the SBQ–R (α = .57). Further, all measures demonstrated associations as expected, suggesting convergent and divergent validity. The BSS, C-SSRS, and SHBQ can be reliably and validly used among IDF soldiers.
Adaptive geometry-based intra prediction for depth video coding

In this paper, we propose an efficient depth video coding method for the 3D video (3DV) system. Since the boundary information of depth video significantly affects the rendering quality in the 3DV system, the proposed method reduces the loss of the boundary information by producing precise intra prediction modes. The characteristics of depth video are analyzed and considered to modify the previous geometry-adaptive block partitioning in the proposed method. The proposed method guarantees a better performance of intra prediction than the method of the H.264/AVC. Experimental results have shown that 0.33 dB coding gain in terms of PSNR and subjective quality improvement of synthesized views are achieved by the proposed method.
CAVANAUGH, ALYSON M., M. S. The Role of Parent–Adolescent Relationships in Predicting Mexican American Adolescents’ Coping Strategies: Examining Variation

The primary aim of this paper was to examine associations between supportive-responsive maternal/paternal–adolescent relationships and adolescents' coping strategies and whether associations vary across adolescent gender. It was hypothesized that supportive-responsive parent–adolescent relationships (indicated by high support and knowledge and low psychological control) would predict higher levels of seeking family support, peer support, and seeking spirituality and lowered levels of anger coping and substance-use coping. Gender of parent and adolescent was considered to examine whether associations between supportive-responsive maternal/paternal and adolescent relationships would vary across boys and girls. Participants included 367 Mexican American adolescents (M age = 14.46, SD = .69; 58% female). Structural equation modeling (SEM) involving latent and manifest constructs and multigroup analyses was used to evaluate the study aims. Results generally supported the primary hypothesis in that supportive-responsive parent–adolescent relationships were associated positively with seeking support from family, peer support, and spirituality and associated negatively with anger and substance-use coping. However, some paths varied across adolescent gender indicating that the effect of parenting on adolescent coping strategies was gendered particularly for father-son adolescent relationships. These findings highlight the importance of proximal supportive and responsive relationships with mothers and fathers for boys' and girls' coping in Mexican American families. ii To my family who has been my support system and source of strength. Thank you for always believing in me and encouraging me to follow my dreams. iii APPROVAL PAGE This thesis has been approved by the following committee of the Faculty of The
Efficient and Exact Diagnosis of Multiple Stuck-At Faults

A simulation-based approach to multiple stuck-at fault diagnosis is presented. The algorithm works iteratively as it identifies and fault models a single location at a time so that the functionality of the new netlist gradually resembles that of the corrupted one. The method is based on a theoretical result along with a number of heuristics which help avoid the exponential complexity inherent to the problem. Experiments on multiple stuck-at faults confirm its effectiveness and accuracy which scales well with increasing number of faults. J. Brandon Liu Andreas Veneris Magdy S. Abadir University of Toronto University of Toronto Motorola Dept ECE Dept ECE and CS 7700 W. Parmer Toronto, ON M5S 3G4 ON M5S 3G4 Austin, TX 78729 liuji@eecg.toronto. edu veneris@eecg.toronto. edu m.abadir@motorola.com
Learning Scene-specific Object Detectors by including Context in a Topic Model Cascade

In this paper, we describe a topic-model based approach for object detection in complex and cluttered scenes. We first learn a generic object model and then refine it by including contextual knowledge. This two-step learning proceeds with minimal supervision and without negative examples. In the first step, a generic object detector identifies object from background. In the second step, noisy classification from the first step is used to reestimate object distribution by modeling background context. The two-step approach is realized by a novel framework of cascaded topic models in which topics discovered by a standard LDA model influence simultaneous topic fitting and document clustering in the proposed Context-LDA model. In effect, based on topic distributions, different (object, context) configurations are separated out. The parameters of the models are learnt via a collapsed Gibbs sampler. To demonstrate the efficacy of this method we perform multiview car detection on a challenging dataset of real-world scene images.