Miracle-dz/UniFAR-FTUs huggingface dataset:
The VNTR Polymorphism of the DC-SIGNR Gene and Susceptibility to HIV-1 Infection: A Meta-Analysis

Background Dendritic cell-specific intercellular adhesion molecule-3-grabbing nonintegrin related (DC-SIGNR) can bind to the human immunodeficiency virus-1 (HIV-1) gp120 envelope glycoprotein and is thus important for the host-pathogen interaction in HIV-1 infection. Studies of the association between the variable number tandem repeat (VNTR) polymorphism of the DC-SIGNR gene and HIV-1 susceptibility have produced controversial results. Methods and Findings We conducted a meta-analysis of the data contained in the literature to clarify these findings. In total, 10 studies consisting of 2683 HIV-1 patients and 3263 controls (2130 healthy controls and 1133 HIV-1 exposed but seronegative (HESN) controls) were included. Odds ratios (ORs) with 95% confidence intervals (95% CIs) were assessed in the main analyses. Further stratified analyses by ethnicity and sample size were performed. By dividing the controls into two groups, healthy controls and HIV-1 exposed but seronegative (HESN) controls, we explored different genetic models to detect any association between the VNTR polymorphism and predisposition to HIV-1 infection. The results showed that the 5-repeat allele carriers (OR = 0.84, 95% CI = 0.73–0.96) and the 5/5 homozygous (OR = 0.68, 95% CI = 0.50–0.93) had significantly reduced risk when using the HIV-1 exposed but seronegative (HESN) as controls. The stratified analyses by ethnicity and sample size confirmed these findings. However, a low to moderate degree of heterogeneity was also found across studies. Conclusions Our findings demonstrate that the VNTR polymorphism of the DC-SIGNR gene is associated with a moderate effect on host susceptibility to HIV-1 infection. Similar to the 32-bp deletion in the chemokine receptor-5 gene (CCR5Δ32), the DC-SIGNR VNTR 5-repeat allele might have a role in resistance to HIV infection, particularly in Asian populations.
SRCB at the NTCIR-13 STC-2 Task

This is the first time SRCB participates in the Short Text Conversation (STC) task of Chinese. We developed conversation systems for both retrieval-based method and generation-based method. For retrieval based method, we proposed two models to retrieve post results from the repository based on the following three steps: preprocessing, candidate comment matching by indexing posts and comments in repository, and candidate comment ranking. For generation based method, we employed the state-of-the-art architecture Seq2Seq model to generate comments for posts. The evaluation results for both methods show that our proposed approaches achieve competitive results. CCS Concepts • Information systems➝Information retrieval • Computing methodologies➝Artificial intelligence.
A Method for Rapid Feature Extraction Based on KMSE

Kernel minimum squared error (KMSE) is a mathematically tractable feature extraction method in comparison with other nonlinear methods. However, as a kernel method, it also suffers from the drawback that the classification efficiency decreases as the size of the training samples increases. In order to improve the KMSE-based classification efficiency, we propose to approximate the discriminant vector in the feature space using a certain linear combination of some samples selected from the set of the training samples. Based on this idea, we develop an algorithm to determine the samples, and a linear combination of which can approximately express the genuine discriminant vector. Experiments on benchmark dataset illustrate the effectiveness of the improvements.
Maximum likelihood adaptation of histogram equalization with constraint for robust speech recognition

In this paper, we propose a novel feature space adaptation technique to improve the robustness of speech recognition in noisy environments. Histogram equalization (HEQ) is an effective technique for improving robustness by reducing the difference between clean and noisy features. A weakness of HEQ is that it does not take into account acoustic model, resulting in possible mismatch between HEQ-processed features and the acoustic model. In this paper, we propose to adapt HEQ to maximize the likelihood of HEQ-processed features on the acoustic model, with a constraint on the parameters of HEQ. In addition, we use a Gaussian mixture model (GMM) to represent the clean feature space rather than using the acoustic model itself, and this results in both simpler implementation and better results. Experimental results show that HEQ with adaptation reduces word error rate by 7.5% and 5.7% respectively on Aurora-2 and Aurora-4 tasks over the HEQ baseline without adaptation.
Towards an open, trusted digital rights management platform

Trusted computing has received criticism from those who fear it will be used by influential market forces to exert power over the software used on consumer platforms. This paper describes an open architecture for digital rights management (DRM) enforcement on trusted computing platforms that empowers the consumer to select their operating-system and applications, including open-source options, without weakening the strength of the security functions. A key component in the architecture is a security manager that enforces mandatory access controls on shared devices, restricted information flows between virtual machines, and DRM policy on protected objects. The paper describes two use-cases: a DRM scenario with protected media content and remote home-working on sensitive medical data.
Face Expression Recognition with Audio-Visual Bi Modal Association

Most automatic expression analysis system attempt to recognize a small set of prototypic expressions, such as happiness, anger, surprise, fear, disgust and sad. We present a novel facial expression recognition framework using audio-visual information analysis. In particular, we design a single good image representation of the image sequence by weighted sum of registered face images where the weights are derived using auditory features. We use a still image based technique for the expression recognition task. We performed experiments using eNTERFACE’05 audio-visual emotional database. The analysis shows that our framework can improve the recognition performance while significantly reducing the computational cost by avoiding redundant or insignificant frame processing by incorporating auditory information. Our analyses show promising results.
Optimal location of shunt compensating facts device for solving ORPD problem using hybrid chemical reaction optimization

This paper presents a new hybrid chemical reaction optimization (HCRO) approach which is based on chemical reaction optimization (CRO) and differential evolution (DE), to find the optimal placement and parameter setting of Static Synchronous Compensator (STATCOM) which is a shunt compensating Facts device to achieve the performance of power system network optimally. However, getting optimal solution of ORPD problem is a cumbersome task for the researchers. This paper presents for optimal allocation of a static synchronous compensator (STATCOM) using hybrid chemical reaction optimization to minimize the transmission loss and voltage deviation in a power system. Moreover, to establish the superiority, the results under simulation reveals that the proposed HCRO technique is superior ascompared to the CRO and DE. The proposed algorithm is implemented and tested successfully on IEEE 30-bus test power system. It is found that the results obtained by the proposed HCRO technique are superior to those obtained by other discussed algorithms.
Error-correction of binary masks using hidden Markov models

Binary masking is a simple and efficient method for source separation, and a high increase in intelligibility can be obtained by applying the target binary mask to noisy speech. The target binary mask can only be calculated under ideal conditions and will contain errors when estimated in real-life applications. This paper proposes a method for correcting these errors. The error-correction is based on a hidden Markov model and uses the Viterbi algorithm to calculate the most probable error-free target binary mask from a target binary mask containing errors. The results demonstrate that it is possible to correct errors in the target binary mask and reduce the noise energy. However, speech energy is also reduced by the error-correction, but the impact on speech intelligibility and speech quality are not established or evaluated in the present study.
Dimensions of Familism among Hispanic and Mainstream Navy Recruits

Abstract : The dimensions of Hispanic and Mainstream familism, that is emphasis on family relationships and family interdependence, were explored with a sample of Hispanic and Mainstream Navy recruits. Hispanic and Mainstream recruits were equally willing to sacrifice (take a loan, sell own TV, borrow) to be present at a family crisis (e.g. brother died) but the Hispanics were more willing than the Mainstream to sacrifice to be present in family celebrations (e.g. nephew is being baptized). The sharpest differences indicated that Hispanics were more willing than Mainstream recruits to sacrifice to attend celebrations involving second and third degree relatives.
A multi-axis MEMS force-torque sensor for measuring the load on a microrobot actuated by magnetic fields

This paper presents the design of a multi-axis micro force-torque sensor. The sensor is able to measure forces along two axes and a torque perpendicular to these forces. The load is measured by capacitive comb drives which provide a high sensitivity. The microfabrication process, the sensor readout electronics as well as the calibration procedure are presented. The sensor was used to measure the force and torque on a magnetically actuated microrobot. This microrobot is assembled from microfabricated nickel parts for directed drug delivery inside the human body. Precise knowledge load on the microrobot is required for accurate positioning and control of the robot. The three-axis micro sensor is used to simultaneously measure the forces and torques acting on the microrobot in a magnetic field and thus provides valuable data for magnetic control methods of microrobots.
Relationship between avian growth rate and immune response depends on food availability

SUMMARY Life history theory predicts that when resources are limited growing organisms are likely to trade an immune response for competing demands of growth. To test this we examined the effect of energy intake on body mass increments and an immune response in hand-reared sand martin (Riparia riparia) nestlings. We subjected the nestlings to three different feeding regimes, mimicking the range of food availability in the wild, and then evaluated nestlings' immune response to phytohaemagglutinin (PHA). Direction of correlation between the magnitude of PHA-induced swelling response and body mass increments depended on food availability: it was negative when food was scarce and positive when resources were plentiful. There was no significant correlation between the two traits under intermediate feeding conditions. We conclude that the relative cost of immune function in young birds depends on food availability and, therefore, may be modified by external factors such as weather conditions or hatching asynchrony.
Looks Like 10 Miles of Bad Road

High-stakes accountability policies have brought about significant change in schools, but have also triggered instances of cheating and gaming at school and district levels. This undisguised case study involves the El Paso Independent School District, one of its high schools, and a popular principal accused of cheating. This context provides the foundation for a fictional scenario of a new principal attempting to reform a culture of cheating and gaming of high-stakes accountability policies. The case explores issues related to legal practices, ethics and morality, and instructional leadership practices that can be useful for principal preparation and educational policy courses.
A new and secure digital image scrambling algorithm based on 2D cellular automata

In this work, a new and secure digital image scrambling algorithm for grayscale images is presented. The main goal of this algorithm is to change and reorder the positions of the pixel values of the grayscale images according to the rules of Conway's Game of Life. For this purpose, an image scrambling matrix is proposed. The proposed algorithm is mostly applied to known benchmark images of various sizes and histograms. Moreover, the proposed algorithm is applied to noisy and low-contrast images to evaluate the performance of the algorithm in consumer applications. The scrambling performance of the algorithm is examined through the evaluation of the correlation values between adjacent pixels in horizontal, vertical, and diagonal directions and the gray difference degree between a pixel value and its neighbor pixel values of the plain and scrambled images. Furthermore, the performance of our algorithm is compared to various state-of-the-art methods. Additionally, in order to measure the reliability of the algorithm, we perform attack analyses such as damage and occlusion. Results show that the proposed algorithm is robust and ensures high security with a powerful scrambling performance. Finally, the proposed algorithm can be used in applications providing security of information, such as image encryption and watermarking.
Global Spectral and Location Effects in Auditory Perceptual Grouping

An important problem in cognitive and systems neuroscience concerns the extent to which perceptual organization can be explained by local, peripheral physiological mechanisms, or rather by more global, central, and higher-level processes. Though central in vision research, this issue has received little attention in the field of audition. One claim is that auditory-perceptual grouping mechanisms, possibly related to visual figure-from-ground segregation or pop-out, are low level, resulting from local processing in the frequency domain. However, no experiments have been performed specifically to test this question. We examined the effects of perceptual grouping on detection for reversal of two repeated target tones, one constant in frequency (1030 Hz), the other free to vary between trials (1045-8580 Hz). Detection was examined in the presence of a 1000-Hz background tone that repeated between target presentations. By varying the frequency of the high-target tone, this task was designed to modulate grouping between the background and low-target tones, thereby affecting reversal detection. We predicted that at large target frequency differences (f), the high-target tone would segregate from the background and low-target tones, and so render the background and low-target tones less distinct. We found that reversal detection declined from optimal levels with increasing f, and that performance was improved by spatially separating the location of the target and background sounds by at least 32. These results demonstrate that global frequency integration over at least three octaves occurs through grouping, and that grouping is affected by source location. This implies that auditory-perceptual grouping involves global neural processing, i.e., the participation of neurons with very broad frequency input that are also sensitive to spatial location.
Influence Maximization on Signed Social Networks with Integrated PageRank

Online social networks (OSNs) have received a lot of attentions recently since they provide a new platform for product promotion and online viral marketing. Influence maximization problem has been extensively studied on some existing influence diffusion models in number of domains. However, most of the existing studies consider OSNs as friendly networks only containing friendship relationships, whereas the hostile relations do exist in many OSNs in real life, e.g., Epinions and Slashdot. In this paper, we integrate the PageRank on signed social networks and use the integrated PageRank to study influence maximization in OSNs with both friend and hostile relations which are respected as positive edges and negative edges on signed networks. In addition, we use the extended vote model to study the influence diffusion on signed networks. We then conducted comprehensive experiments on real social networks to select initial k seeds for influence maximization, and results indicate that our integrated PageRank method performs better than other heuristic algorithms.
On Social-Temporal Group Query with Acquaintance Constraint

Three essential criteria are important for activity planning, including: (1) finding a group of attendees familiar with the initiator, (2) ensuring each attendee in the group to have tight social relations with most of the members in the group, and (3) selecting an activity period available for all attendees. Therefore, this paper proposes Social-Temporal Group Query to find the activity time and attendees with the minimum total social distance to the initiator. Moreover, this query incorporates an acquaintance constraint to avoid finding a group with mutually unfamiliar attendees. Efficient processing of the social-temporal group query is very challenging. We show that the problem is NP-hard via a proof and formulate the problem with Integer Programming. We then propose two efficient algorithms, SGSelect and STGSelect, which include effective pruning techniques and employ the idea of pivot time slots to substantially reduce the running time, for finding the optimal solutions. Experimental results indicate that the proposed algorithms are much more efficient and scalable. In the comparison of solution quality, we show that STGSelect outperforms the algorithm that represents manual coordination by the initiator.
Characterizing and detecting resource leaks in Android applications

Android phones come with a host of hardware components embedded in them, such as Camera, Media Player and Sensor. Most of these components are exclusive resources or resources consuming more memory/energy than general. And they should be explicitly released by developers. Missing release operations of these resources might cause serious problems such as performance degradation or system crash. These kinds of defects are called resource leaks. This paper focuses on resource leak problems in Android apps, and presents our lightweight static analysis tool called Relda, which can automatically analyze an application's resource operations and locate the resource leaks. We propose an automatic method for detecting resource leaks based on a modified Function Call Graph, which handles the features of event-driven mobile programming by analyzing the callbacks defined in Android framework. Our experimental data shows that Relda is effective in detecting resource leaks in real Android apps.
As Others See Us

Discrepancies are often found between self-reports and reports by others regarding psychopathology. Both the person being assessed and various informants may contribute crucial data concerning a person's functioning. Comprehensive assessment requires data from multiple informants. Such data can be easily obtained with parallel self-report and collateral-report forms. The multi-informant data can be compared, aggregated, and used in many ways. Optimal use of multi-source data is essential for clinical assessment and for discovering causes and cures of psychopathology.
Testosterone Deficiency with Erectile Dysfunction in Mongolian Men

Purpose To detect the testosterone deficiency syndrome in Mongolian men over 40 years old with erectile dysfunction (ED). Materials and Methods Total of 309 males over 40 years of age who received medical care at the ADAM Urology and Andrology Clinic from 2010 to 2011 were included in this study. An approval from the Ethics Committee of the Ministry of Health of Mongolia was obtained, and each study participant signed a consent form at the beginning of the study. The participants were assigned to either an ED group or a control group, depending on the results of the international index of erectile function (IIEF)-5 questionnaire. The ED group was further divided into three groups (moderate, severe, and very severe) based on the level of ED. The total testosterone (TT) levels were determined in the blood serum using a competitive enzyme-linked immunesorbent assay (ELISA) analytical system UBI Magiwel™ Testosterone Quantitative test, and free testosterone (FT) calculated as described by the Vermeulen calculation. Test samples were collected between 8:00 and 11:00 am in the mornings and testosterone deficiency syndrome was diagnosed based on the International Society for the Study of the Aging Male guidelines, particularly, if TT was ≤3.46 ng/ml or free testosterone FT was ≤0.072 ng/ml. Results ED of moderate, severe, and very severe levels was diagnosed in 199 (64.41%) out of 309 participants. There was an inverse relationship between the main IIEF-5 score and age (r=-0.380, p<0.01). The average TT was 5.75±2.316 ng/ml and FT was 0.091±0.0084 ng/ml. Compared to the ED group, the control group had a higher TT level: 5.6440±1.177 ng/ml and 5.812±2.316 ng/ml, respectively. In the control group, the FT level was 0.061±0.0084 ng/ml, whereas it was 0.041±0.0076 ng/ml in the ED group. Conclusions Our study showed that most of the aging males who came to the clinic had moderate to very severe ED (64.55%). The levels of TT (5.644±1.177 ng/ml) and FT (0.041±0.0036 ng/ml) were significantly lower in ED patients (p<0.05). The testosterone deficiency syndrome was detected in 24.27% of the ED group.
Tech-note: Iterative design and test of a multimodal experience

The goal of the Turtlesurf project described in this tech-note is to design, implement and evaluate a multimodal installation that should provide a good user experience in a virtual 3D world. For this purpose we combine audio-visual media forms and different types of haptic/tactile feedback. For the latter, we focus on the application of vibrational feedback, wind and water spray and heat. We follow a user-centered design approach and try to get user feedback as early as possible during the iterative design process. We present the conceptual idea of the Turtlesurf project, and the iterative design and test of prototypes that helped us to refine the final design based on collected user feedback.
Managerialist vis-à-vis learning and development goals for EAL teachers: a case study of an in-service professional development provider

Abstract Under current Western neoliberal philosophy, promotion of efficiency and resolution of issues are typically expected to result from effective management. The education sector, too, has responded well to these expectations. Amongst such expectations, engagement in professional development activities (PDAs) by teachers of English as an additional language (EAL) is widely encouraged, considered to be essential, and usually conducted with a view to facilitate effective and effortless administration. As such, institutional offerings of PDAs driven by managerialist agendas generally tend to be ad hoc attempts to facilitate administrative decisions rather than opportunities for teachers’ lifelong learning and development. Under such circumstances, providers of in-service PDAs are faced with a conflicting dilemma – that of facilitating an effortless flow of administration and, at the same time, promoting teacher learning and development. We foreground one case of such dilemma surrounding the offering of PDAs derived as interview data from an experienced provider of in-service PDAs for EAL teachers.