Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptive Dynamic Range Optimization (ADRO): A Digital Amplification Strategy for Hearing Aids and Cochlear Implants

Adaptive dynamic range optimization (ADRO) is an amplification strategy that uses digital signal processing techniques to improve the audibility, comfort, and intelligibility of sounds for people who use cochlear implants and/or hearing aids. The strategy uses statistical analysis to select the most information-rich section of the input dynamic range in multiple-frequency channels. Fuzzy logic rules control the gain in each frequency channel so that the selected section of the dynamic range is presented at an audible and comfortable level. The ADRO processing thus adaptively optimizes the dynamic range of the signal in multiple-frequency channels. Clinical studies show that ADRO can be fitted easily to all degrees of hearing loss for hearing aids and cochlear implants in a direct and intuitive manner, taking the preferences of the listener into account. The result is high acceptance by new and experienced hearing aid users and strong preferences for ADRO compared with alternative amplification strategies. The ADRO processing is particularly well suited to bimodal and hybrid stimulation which combine electric and acoustic stimulation in opposite ears or in the same ear, respectively.
2016 Ieee International Conference on Big Data (big Data) Information Retrieval, Fusion, Completion, and Clustering for Employee Expertise Estimation

—Estimating the skills, talents, and expertise of employees is essential for human capital management in knowledge-based organizations across industries and sectors. In this paper, we describe an approach to infer the expertise of employees from their enterprise data and digital footprints. Using a novel big data workflow with components of information retrieval and search, data fusion, matrix completion, and ordinal regression clustering, we are able to automatically find evidence of expertise and determine appropriate evidence weights for different queries and data sources that we merge and present in a manner consumable by businesspeople. We illustrate the system on sample data from the IBM Corporation where it has been deployed.
Defective Neuronal Development in the Mushroom Bodies of Drosophila Fragile X Mental Retardation 1 Mutants

Fragile X mental retardation 1 (Fmr1) is a highly conserved gene with major roles in CNS structure and function. Its product, the RNA-binding protein FMRP, is believed to regulate translation of specific transcripts at postsynaptic sites in an activity-dependent manner. Hence, Fmr1 is central to the molecular mechanisms of synaptic plasticity required for normal neuronal maturation and cognitive ability. Mutations in its Drosophila ortholog, dfmr1, produce phenotypes of brain interneurons and axon terminals at the neuromuscular junction, as well as behavioral defects of circadian rhythms and courtship. We hypothesized that dfmr1 mutations would disrupt morphology of the mushroom bodies (MBs), highly plastic brain regions essential for many forms of learning and memory. We found developmental defects of MB lobe morphogenesis, of which the most common is a failure of β lobes to stop at the brain midline. A similar recessive β-lobe midline-crossing phenotype has been previously reported in the memory mutant linotte. The dfmr1 MB defects are highly sensitive to genetic background, which is reminiscent of mammalian fragile-X phenotypes. Mutations of dfmr1 also interact with one or more third-chromosome loci to promote α/β-lobe maturation. These data further support the use of the Drosophila model system for study of hereditary cognitive disorders of humans.
HACK: Hierarchical ACKs for Efficient Wireless Medium Utilization

WiFi's physical layer has increased in speed from 802.11b's 11 Mbps to the Gbps rates of emerging 802.11ac. Despite these gains, WiFi's inefficient MAC layer limits achievable end-to-end throughput. The culprit is 802.11's mandatory idle period before each medium acquisition, which has come to dwarf the duration of a packet's transmission. This overhead is especially punishing for TCP traffic, whose every two data packets elicit a short TCP ACK. Even frame aggregation and block link-layer ACKs (introduced in 802.11n) leave significant medium acquisition overhead for TCP ACKs. In this paper, we propose TCP/HACK (Hierarchical ACKnowledgment), a system that applies cross-layer optimization to TCP traffic on WiFi networks by carrying TCP ACKs within WiFi's link-layer acknowledgments. By eliminating all medium acquisitions for TCP ACKs in unidirectional TCP flows, TCP/HACK significantly improves medium utilization, and thus significantly increases achievable capacity for TCP workloads. Our measurements of a real-time, line-speed implementation for 802.11a on the SoRa software-defined radio platform and simulations of 802.11n networks at scale demonstrate that TCP/HACK significantly improves TCP throughput on WiFi networks.
Static Pattern Predictor (SPP) Based Low Power Instruction Cache Design

Energy dissipation in cache memories is becoming a major design issue in embedded microprocessors. Predictive filter cache based instruction cache hierarchy is effective in reducing the access energy substantially at the cost of certain performance degradation. Here, the energy-delay product reduction heavily depends on the prediction accuracy of the predictor. In this paper, a simplified pattern prediction algorithm, which maximizes power savings in the novel filter cache prediction hierarchy, is proposed. The prediction mechanism relies on the static nature of the hit or miss pattern of the instruction access stream over the past filter cache line accesses. These static patterns are stored in a 32-entry single-bit Pattern Table (PT). The entries could be dynamically changed during run time to provide options for real-time adaptation in a complex application. The proposed prediction algorithm results in better prediction for all the benchmarks simulated. Energy delay product reduction of up to 8.19% over existing NFPT prediction scheme was reported for the benchmarks simulated. Key-Words: Filter-Cache, Static Pattern Prediction, NFPT, Hit-Miss Pattern.
Adolescents’ perceptions of health and well-being: Influences of urban contemporary music

The study aimed to explore adolescents’ perceptions of how urban contemporary music influences health and well-being among them. Data on health and well-being effects of music consumption were gathered from a convenience sample of 16 participants (male = 50%, females = 50%) between the ages of 15 and 17 in a series of two focus group interviews. The data were analysed using thematic analysis. Findings suggest the adolescents to perceive both positive and negative influences of contemporary music on their health and well-being. Positive influences included emotional well-being and sense of social belongingness. Negative influences included promotion of risky behaviours, including substance use, misogyny, sexual behaviour and violence. The findings suggest that urban contemporary music serves as a tool of normalisation as well as a catalyst for encouraging risky behaviour in adolescence.
The Differential Effects of Anger on Trust: A Cross-Cultural Comparison of the Effects of Gender and Social Distance

Accumulating empirical evidence suggests that anger elicited in one situation can influence trust behaviors in another situation. However, the conditions under which anger influences trust are still unclear. The present study addresses this research gap and examines the ways in which anger influences trust. We hypothesized that the social distance to the trustee, and the trusting person’s gender would moderate the effect of anger on trust. To test this hypothesis, a study using a 2 (Anger vs. Control) × 2 (Low vs. High social distance) × 2 (Men vs. Women) factorial design was conducted in Germany (N = 215) and in China (N = 310). Results reveal that in both countries men’s trust behavior was not influenced by the manipulations (i.e., anger and social distance). The pattern for women, however, differed by country. In Germany, women’s trust to a stranger (i.e., high social distance) was increased by anger; while in China, women’s trust to someone who they have communicated with (i.e., low social distance) was increased by anger. These results indicate that women’s trust levels seem to be more context-sensitive than men’s.
THE EXTRACELLULAR RELEASE OF ECHINOCHROME

A study was made of the diffusion of the red pigment echinochrome from the eggs of the sea urchin, Arbacia punctulata, into sea water. Unfertilized eggs retained their pigment, over periods of hours. Outward diffusion of pigment from unfertilized eggs normally is entirely negligible, or does not occur at all. Enchancing the calcium or potassium content of the artificial sea water (while retaining isosmotic conditions) did not induce pigment release. Under anaerobic conditions, unfertilized eggs release pigment in small quantities. Fertilization alone brings about echinochrome release. Fertilized eggs invariably released pigment, whether in normal sea water, or sea water with increased calcium or potassium. This diffusion of the pigment began during the first cleavage, possibly soon after fertilization. The pigment release is not a consequence solely of the cell's permeability to echinochrome (or chromoprotein, or other pigment combination) but is preceded by events leading to a release of echinochrome from the granules in which it is concentrated within the cell. These events may be initiated by activation or by anaerobiosis. The phenomenon was not due to cytolysis.
Analytical modeling of permanent magnet excited brushed DC motor for low-cost applications

In this paper, we present an analytical modelling of permanent magnet excited brushed DC motor for cost sensitive applications. General solutions to the Laplacian/quasi-Poissonian magnetic field equations are first derived in the motor airgap. Applying the specified boundary conditions, normal and tangential components of flux density in the airgap can be analytically predicted. With distributed windings employed in the armature slots, their flux linkage, induced voltage and motor performance can also be calculated. The proposed analytical model can also be used to parameterize the brushed DC motor for optimal performance such as minimum torque ripple. The proposed model shows very good agreement with the results obtained from FEM. Furthermore, the analytical model compares the calculated results between the 12- slot armature DC motor and 10 -slot armature DC motor.
Real-time failure-tolerant control of kinematically redundant manipulators

This work considers real-time fault-tolerant control of kinematically redundant manipulators with single locked-joint failures. The fault-tolerance measure used is a worst-case quantity, given by the minimum, over all single joint failures, of the minimum singular value of the post-failure Jacobians. Given any end-effector trajectory, the goal is to continuously follow this trajectory with the manipulator in configurations that maximize the fault-tolerance measure. The computation required to track these optimal configurations with brute-force methods is prohibitive for real-time implementation. We address this issue by presenting algorithms that quickly compute estimates of the worst-case fault-tolerance measure and its gradient. Real-time implementations are presented for all these techniques, and comparisons show that the performance of the best is indistinguishable from that of brute-force implementations.
Exploring Leadership Experiences Of School Psychologists In Supporting Schools: A Phenomenological Study

The passage of the No Child Left Behind Act (NCLB) and the reauthorization of the Individuals with Disabilities Education Act in 2004 have placed increased demands on all educators and administrators. School psychologists find themselves charged with addressing a broad range of issues today, and there is an emphasis on leadership in the effective provision of services. Although the literature is replete with examples of the centrality of leadership in regards to the educational experience of students, there have not been sufficient studies that have studied this topic in school psychology. The purpose of this study was to discover, understand, and describe in rich detail the lived experience of school psychologists exercising leadership. The researcher interviewed school psychologists within a mid-size school district in Central Florida who were nominated by district administrators that supervise of them. Additionally, this study sought to identify the contexts, domains of practice, universal structures, and opportunities utilized in their experiences. School psychologists demonstrated leadership through collaboration and consultation, professional expertise, student-oriented needs, expert-problem solvers, and communication skills. The contexts of their leadership experiences varied due to the diverse roles taken on by the individual, however they were all demonstrated at the district level, school level, and with their peers. The leadership experiences identified by the study participants correspond to most of the National Association of School Psychologists (NASP) domains of practice and also correspond to transformational leadership. The results are particularly salient to school psychologist, as the information comes from the perspective of school psychologists who were noted to be "effective" and displays "leadership" and are now exercising leadership. Future research is encourage to examine leadership experiences across multiple school districts to identify experiences of other leaders across various settings.
Association between Interleukin-1β Gene −511C>T/+3954C>T Polymorphisms and Aggressive Periodontitis Susceptibility: Evidence from a Meta-Analysis

Background Interleukin-1β (IL-1β) is an important inflammatory cytokine. The associations between IL-1β gene −511C>T/+3954C>T polymorphisms and aggressive periodontitis (AgP) susceptibility have been conflicting. We therefore conducted a meta-analysis to investigate the association of IL-1β genetic polymorphisms with susceptibility to AgP. Material/Methods PubMed and Embase electronic databases were searched for relevant studies. Odds ratios (ORs) with 95% confidence interval (CIs) were used to assess the association between IL-1β polymorphisms and AgP risk. Heterogeneity, publication bias, and sensitivity analysis were performed to guarantee the statistical power. Results Twenty published studies involving 965 patients and 1234 control subjects were included. No significant association between IL-1β polymorphisms and AgP was found. For −511C>T (T vs. C: OR=0.966, 95%CI=0.696–1.341, P=0.869; CT vs. CC: OR=0.936, 95%CI=0.761–1.151; TT vs. CC: OR=0.892, 95%CI=0.464–1.715, P=0.719; CT+TT vs. CC: OR=1.026, 95%CI=0.795–1.323; TT vs. CC+CT: OR=0.864, 95%CI=0.436–1.713). For +3954C>T (T vs. C: OR=1.069, 95%CI=0.901–1.268; CT vs. CC: OR=0.921, 95%CI=0.699–1.212; TT vs. CC: OR=1.064, 95%CI=0.747–1.515; CT+TT vs. CC: OR=0.990, 95%CI=0.764–1.283; TT vs. CC+CT: OR=1.229, 95%CI=0.919–1.643). Subgroup analyses were conducted with HWE, ethnicity, and study design, and no significant association was detected. Conclusions These results demonstrate that IL-1β −511C>T and +3954C>T polymorphisms are not the risk factors for developing AgP.
Algorithm to Identify Enamel Caries and Interproximal Caries Using Dental Digital Radiographs

Diagnosis of dental diseases is conventionally carried out with the help of radiographic films. As a result of noise and other environmental interferences, use of radiographic films introduces errors. This paper presents an algorithm to use digital periapical radiographic images to detect enamel caries and interproximal caries. This will help dental practitioners to identify caries lesion with ease. This study makes use of MATLAB and it performs caries detection in three stages. First stage is the preprocessing phase where rotation of an image is performed, if necessary. Histogram study of the image is carried out to understand the intensity of carries. The second phase is image segmentation where individual tooth area is separated. Third phase is the identification phase where caries are detected. If caries are not detected, tooth is definitely healthy.
Arresting burnout: The role of Karma yoga

An outcome of aversive working conditions, burnout remains a prime cause of concern for organizational researchers. Arresting burnout in the workforce is important as it is associated with numerous negative consequences for employees as well as organizations. One of the prominent approach that explains the incidence of burnout is the conservation of resources which advocates that burnout results when individuals perceive net loss of valuable resources which cannot be replenished. In this paper, we propose Karma Yoga as a panacea to the problem of burnout. Karma Yoga is suggested in the Hindu text Bhagavad Gita as one of the ways towards Self-realization. Karma Yogis (practitioners of Karma Yoga) are likely to interpret ‘loss’ of resources as milestones in the path of self-realization rather than reflections of personal capabilities, thereby preventing them from experiencing burnout. They are also likely to be happy. Further, our findings suggest that happiness mediates the relationship between Karma Yoga and Burnout.
Inferring visiting time distributions of locations from incomplete check-in data

Online location-based services, such as Foursquare and Facebook, provide a great resource for location recommendation. As we know the time is one of the important factors on recommending places with proper time for users, since the pleasure of visiting a place could be diminished if arriving at wrong time, we propose to infer the visiting time distributions of locations. We assume the check-in data used is incomplete because in real-world scenarios it is hard or unavailable to collect all the temporal information of locations and the check-in behaviors might be abnormal. To tackle such problem, we devise a visiting time inference framework, VisTime-Miner, which considers the route-based visiting correlation of time labels to model the visiting behavior of a location. Experiments on a large-scaled Gowalla check-in data show a promising result.
Text mining tools for assisting literature curation

Today's biomedical research has become heavily dependent on the access to biological knowledge encoded in expert curated biological databases (e.g. Swiss-Prot). As the volume of biological literature grows rapidly, it becomes increasingly difficult for human curators to keep up with the literature because manual curation is an expensive and time-consuming endeavor. Past research has shown that (semi-)automated approach has the potential to greatly improve the manual curation productivity [1-3]. We recently developed PubTator, a web-based application for assisting literature curation through the use of various text mining tools [4-6]. PubTator has several unique features. First, PubTator is a web-based system, thus no installation is required and not restricted to any specific computer platforms. That is, it works on different computing platforms as long as there is a Web browser installed. Second, PubTator features a PubMed-like interface which many human curators find it to be familiar and easy to use with minimal training required. Third, PubTator integrates multiple competition-winning text mining approaches that we recently developed for recognizing important biological entities: Gene/Proteins, Diseases, Mutations, Chemical/Drugs, and Organisms [7-11]. Hence, it can guarantee the state-of-the-art performance on text-mined results. Lastly, PubTator is in sync with PubMed content through nightly updates. Interested users can access our text-mined results via a) PubTator web interface, b) RESTful API or c) ftp download. We have conducted a formal text-mining aided curation experiment, results of which showed that PubTator was able to greatly improve both the curation efficiency and accuracy [6]. More recently, PubTator has been successfully deployed in practice for the curation of CDC's human genome epidemiology knowledge-base. Hence, we conclude that our text-mining tools and PubTator can provide practical benefits to literature curation in bioinformatics research. PubTator is freely available at: http://www.ncbi. nlm.nih. gov/CBBresearch/Lu/Demo/PubTator/
A boosting approach to learning receptive fields for scene categorization

Recently, sparse coding-based algorithms have achieved high performance on several popular scene classification benchmarks. Yet extensive efforts along this direction focus on strategies for coding and dictionary learning, few works have addressed the problem of optimal pooling regions selection. In this work, we show that the Viola-Jones algorithm, which is well-known in face detection, can be tailored to learning receptive fields for the sparse coding algorithms. Specifically, using the boosting approach to receptive field learning, image/scene categorization performance can be ubiquitously enhanced on several benchmarks (UIUC sport event, 15 natural scenes and the Caltech 101 dataset) to the state-of-the-art, using only low dimensional features and small codebook sizes. Furthermore, the “salient pooling regions” can be obtained explicitly.
Intrusion Detection Technique in Mobile Adhoc Network Based on Quantitative Approach

In this paper ,we study the types of attacks in intrusion detection system in Mobile Ad Hoc network(MANET). Mobile Adhoc Networks are a relatively new and rapidly evolving area of interests. One such field concerns mobile adhoc networks (MANETs) in which mobile nodes organize themselves in a network without the help of any predefined infrastructure. Securing MANETs is an important part of deploying and utilizing them, since they are often used in critical applications where data and communications integrity in important. Many solution for intrusion detection in wireless environments have been developed but these solution may not always be sufficient, as ad-hoc networks have their own vulnerabilities that cannot be addressed by these solutions. In this paper traditional security algorithms coupled with intrusion detection mechanism. Here we using a quantitative method to detect intrusion in MANETS with mobile nodes. Our method is a behavioral anomaly based system, which makes it dynamic, scalable, configurable and robust. For simulating our mobile nodes use AODV (Adhoc on demand distance Vector)routing. It is observed that the malicious node detection rate is very good and false positive detection rate is slow.