Miracle-dz/UniFAR-FTUs huggingface dataset:
Twenty Years of Searching for (and Finding) Globular Cluster Pulsars

Globular clusters produce orders of magnitude more millisecond pulsars per unit mass than the Galactic disk. Since the first cluster pulsar was uncovered twenty years ago, at least 138 have been identified—most of which are binary millisecond pulsars. Because of their origins involving stellar encounters, many of these systems are exotic objects that would never be observed in the Galactic disk. Examples include pulsar—main sequence binaries, extremely rapid rotators (including the current record holder), and millisecond pulsars in highly eccentric orbits. These systems are allowing new probes of the interstellar medium, the equation of state of material at supra‐nuclear density, the mass distribution of neutron stars, and the dynamics of globular clusters.
Familial Syndromes Coupling with Small Renal Masses

During the past two decades, several new hereditary renal cancers have been discovered but are not yet widely known. Hereditary renal cancer syndromes can lead to multiple bilateral kidney tumors that occur at a younger age than that at which the nonhereditary renal cancers occur. The aim of our work is to review the features of hereditary renal cancers, the basic principles of genetic relevant to these syndromes, and the various histopathologic features of renal cancer. In addition, we will describe the known familial syndromes associated with small renal masses.
Revisiting scenarios and methods for variable frame rate analysis in automatic speech recognition

In this paper we present a revision and evaluation of some of the main methods used in variable frame rate (VFR) analysis, applied to speech recognition systems. The work found in the literature in this area usually deals with restricted conditions and scenarios and we have revisited the main algorithmic alternatives and evaluated them under the same experimental framework, so that we have been able to establish objective considerations for each of them, selecting the most adequate strategy. We also show till what extent VFR analysis is useful in its three main application scenarios, namely “reduction of computational load”, “improve acoustic modelling” and “handling additive noise conditions in the time domain”. From our evaluation on a difficult telephone large vocabulary task, we establish that VFR analysis does not significantly improve the results obtained using the traditional fixed frame rate analysis (FFR), except when additive noise is present in the database and specially for low SNRs.
Jordanian Kindergarten and 1st-Grade Teachers’ Beliefs About Child-Based Dimensions of School Readiness

ABSTRACT The purpose of this study was to explore the beliefs of Jordanian kindergarten and 1st-grade teachers regarding six child-based dimensions of school readiness: academic knowledge, basic thinking skills, socioemotional maturity, physical well-being and motor development, self-discipline, and communication skills. Questionnaires were used to collect data from 289 teachers; 155 kindergarten teachers and 134 1st-grade teachers were randomly selected from Zarqa, a highly populated city in Jordan. Results revealed that kindergarten and 1st-grade teachers considered all the six child-based dimensions as important to getting children ready for school. However, both groups of teachers rated the basic academic knowledge as the most important dimension and emphasized it over the other dimensions. In addition, results of the multivariate analysis of variance (MANOVA) indicated that there were statistically significant differences in the beliefs of kindergarten and 1st-grade teachers on four dimensions: academic knowledge, basic thinking skills, socioemotional development, and communication skills; meaning that kindergarten teachers rated these dimensions as more important than 1st-grade teachers did. Yet when teachers’ level of education was controlled for as a covariate, multivariate analysis of covariance results showed that significant statistical differences were only detected on the first dimension (i.e., academic knowledge). Suggestions for policymakers and for further research were offered based on the results of this study.
The Clinical Significance of the Insulin-Like Growth Factor-1 Receptor Polymorphism in Non-Small-Cell Lung Cancer with Epidermal Growth Factor Receptor Mutation

The insulin-like growth factor 1 (IGF1) signaling pathway mediates multiple cancer cell biological processes. IGF1 receptor (IGF1R) expression has been used as a reporter of the clinical significance of non-small-cell lung carcinoma (NSCLC). However, the association between IGF1R genetic variants and the clinical utility of NSCLC positive for epidermal growth factor receptor (EGFR) mutation is not clear. The current study investigated the association between the IGF1R genetic variants, the occurrence of EGFR mutations, and clinicopathological characteristics in NSCLC patients. A total of 452 participants, including 362 adenocarcinoma lung cancer and 90 squamous cell carcinoma lung cancer patients, were selected for analysis of IGF1R genetic variants (rs7166348, rs2229765, and rs8038415) using real-time polymerase chain reaction (PCR)genotyping. The results indicated that GA + AA genotypes of IGF1R rs2229765 were significantly associated with EGFR mutation in female lung adenocarcinoma patients (odds ratio (OR) = 0.39, 95% confidence interval (CI) = 0.17–0.87). Moreover, The GA + AA genotype IGF1R rs2229765 was significantly associated with EGFR L858R mutation (p = 0.02) but not with the exon 19 in-frame deletion. Furthermore, among patients without EGFR mutation, those who have at least one polymorphic A allele of IGF1R rs7166348 have an increased incidence of lymph node metastasis when compared with those patients homozygous for GG (OR, 2.75; 95% CI, 1.20–2.31). Our results showed that IGF1R genetic variants are related to EGFR mutation in female lung adenocarcinoma patients and may be a predictive factor for tumor lymph node metastasis in Taiwanese patients with NSCLC.
Cochlear Implant Insertion Forces in Microdissected Human Cochlea to Evaluate a Prototype Array

Cochlear implant array insertion forces are potentially related to cochlear trauma. We compared these forces between a standard (Digisonic SP; Neurelec, Vallauris, France) and an array prototype (Neurelec) with a smaller diameter. The arrays were inserted by a mechatronic tool in 23 dissected human cochlea specimens exposing the basilar membrane. The array progression under the basilar membrane was filmed together with dynamic force measurements. Insertion force profiles and depth of insertion were compared. The recordings showed lower insertion forces beyond 270° of insertion and deeper insertions with the thin prototype array. This will potentially allow larger cochlear coverage with less trauma.
Emotional and Behavioral Problems in Children Living With Addicted Family Members: Prevention Challenges in an Underprivileged Suburban Community

Children living with substance abusers are more likely to experience negative outcomes. Our goal was to compare caregivers' reports on the Child Behavior Checklist (CBCL) and a socioeconomic and risk form of psychological aspects of children exposed to substance abuse assisted versus not assisted by a preventive intervention program in an underprivileged community. This observational intervention study was conducted with 66 caregivers of children who attended the program and 35 caregivers of children from the same community who did not attend. Ages ranged between six and 11 years old. Chi-square and logistic regression tests indicate that children exposed to substance abusers have more mental health problems than the general population and those who did not participate in the preventive intervention program presented worse outcomes, with higher rates of behavioral/emotional problems and exposure to risk situations. Results suggest that preventive actions might be helpful to promote the mental health of children at risk, validating the need for public policies and services.
Anti-HIV Activity in Cervical-Vaginal Secretions from HIV-Positive and -Negative Women Correlate with Innate Antimicrobial Levels and IgG Antibodies

Background We investigated the impact of antimicrobials in cervicovaginal lavage (CVL) from HIV(+) and HIV(−) women on target cell infection with HIV. Since female reproductive tract (FRT) secretions contain a spectrum of antimicrobials, we hypothesized that CVL from healthy HIV(+) and (−) women inhibit HIV infection. Methodology/Principal Findings CVL from 32 HIV(+) healthy women with high CD4 counts and 15 healthy HIV(−) women were collected by gently washing the cervicovaginal area with 10 ml of sterile normal saline. Following centrifugation, anti-HIV activity in CVL was determined by incubating CVL with HIV prior to addition to TZM-bl cells. Antimicrobials and anti-gp160 HIV IgG antibodies were measured by ELISA. When CXCR4 and CCR5 tropic HIV-1 were incubated with CVL from HIV(+) women prior to addition to TZM-bl cells, anti-HIV activity in CVL ranged from none to 100% inhibition depending on the viral strains used. CVL from HIV(−) controls showed comparable anti-HIV activity. Analysis of CH077.c (clone of an R5-tropic, mucosally-transmitted founder virus) viral inhibition by CVL was comparable to laboratory strains. Measurement of CVL for antimicrobials HBD2, trappin-2/elafin, SLPI and MIP3α indicated that each was present in CVL from HIV(+) and HIV(−) women. HBD2 and MIP3α correlated with anti-HIV activity as did anti-gp160 HIV IgG antibodies in CVL from HIV(+) women. Conclusions/Significance These findings indicate that CVL from healthy HIV(+) and HIV(−) women contain innate and adaptive defense mechanisms that inhibit HIV infection. Our data suggest that innate endogenous antimicrobials and HIV-specific IgG in the FRT can act in concert to contribute toward the anti-HIV activity of the CVL and may play a role in inhibition of HIV transmission to women.
Fingerprint Enhancement Using Unsupervised Hierarchical Feature Learning

We present an approach for learning low- and high-level fingerprint structures in an unsupervised manner, which we use for enhancement of fingerprint images and estimation of orientation fields, frequency images, and region masks. We incorporate the use of a convolutional deep belief network to learn features from greyscale, clean fingerprint images. We also show that reconstruction performed by the learnt network works as a suitable enhancement of the fingerprint, and hierarchical probabilistic inference is able to estimate overall fingerprint structures as well. Our approach performs better than Gabor-based enhancement and short time Fourier transform-assisted enhancement on images it was trained on. We further use information from the learnt features in first layer, which are short and oriented ridge structures, to extract the orientation field, frequency image, and region mask of input fingerprints.
Assessment of using of emerging communication tools (cell phone, internet and satellite) among young adults and its association with anxiety, depression and stress

Introduction: According to formation of emerging communication tools and their effects in community, this study aimed to investigate the use of these tools (cell phone, internet and satellite) among young adults in Torbat-e-Heydarieh and its relation with anxiety, depression and stress. Materials and Methods: In this descriptive-correlative study that conducted in Torbat-e-Heydarieh (summer 2014) numbers of 209 young adults (129 men and 80 women) were selected through randomized sampling method and they fulfilled the questionnaires of Depression, Anxiety, Stress Scale (DASS-21), Yang Internet Addiction, Cell Phone Internet Addiction and demographic form. Data analyzed by descriptive statistics, t-test sample group, one factor variation analysis and Pearson coefficient. Â Results: The use of cell phone, internet and satellite among young adults in Torbat-e-Heydarieh were higher than mean of our community. Also the use of these tools among men and range of age 20-30 years were higher significantly (P=0.000). Â In addition, results showed that the anxiety scores were higher in use of cell phone and the anxiety and stress scores were higher in use of internet, and the depression and stress scores were higher in use of satellite significantly (P<0.05). Â Conclusion: Based on the results the use of emerging communication tools is high and increase of use of them relates to higher scores of stress, depression and anxiety.
Bangla handwritten character recognition using deep belief network

Recognition of Bangla handwritten characters is a difficult but important task for various emerging applications. For better recognition performance, good feature representation of the character images is a primary requirement. In this study, we investigate a recently proposed machine learning approach called deep learning [1] for Bangla hand written character recognition, with a focus on automatic learning of good representations. This approach differs from the traditional methods of preprocessing the characters for constructing the handcrafted features such as loops and strokes. Among different deep learning structures, we employ the deep belief network (DBN) that takes the raw character images as input and learning proceeds in two steps - an unsupervised feature learning followed by a supervised fine tuning of the network parameters. Unlike traditional neural networks, the DBN is a probabilistic generative model, i.e., we can generate samples from the model and it can fit both the semi-supervised and supervised learning settings. We demonstrate the advantages of unsupervised feature learning through the experimental studies carried on the Bangla basic characters and numerals dataset collected from the Indian Statistical Institute.
Social Media in a Subjective-science Mode: The “Facebook Likes” Study Reconfigured with Self-reference

A Cambridge University study of more than 58,000 users of the popular social medium Facebook examined the extent to which the Facebook "Likes" button predicted behaviors and attributes of a diverse nature (IQ, sexual identity, political and popular-culture preferences, religious affiliation, and the like). Despite revealing several intriguing and statistically significant relationships, the research sheds scant light on the nature of the subjectivity at play. In a Q-methodological study of a sample of subjectively communicated responses to the Cambridge research, three versions of the subjective interface between the users of Facebook and the social medium are reported. Implications for studying the social-psychological aspects of social media from the methodological principle of self-reflection are discussed. Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:200%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin;}
Evaluating MapReduce frameworks for iterative Scientific Computing applications

Scientific Computing deals with solving complex scientific problems by applying resource-hungry computer simulation and modeling tasks on-top of supercomputers, grids and clusters. Typical scientific computing applications can take months to create and debug when applying de facto parallelization solutions like Message Passing Interface (MPI), in which the bulk of the parallelization details have to be handled by the users. Frameworks based on the MapReduce model, like Hadoop, can greatly simplify creating distributed applications by handling most of the parallelization and fault recovery details automatically for the user. However, Hadoop is strictly designed for simple, embarrassingly parallel algorithms and is not suitable for complex and especially iterative algorithms often used in scientific computing. The goal of this work is to analyze alternative MapReduce frameworks to evaluate how well they suit for solving resource hungry scientific computing problems in comparison to the assumed worst (Hadoop MapReduce) and best case (MPI) implementations for iterative algorithms.
Sparse discriminative Fisher vectors in visual classification

Constructing global image representations from local feature descriptors is a common step in most visual classification tasks. Traditionally, the Bag of Features (BoF) representations involving hard vector quantization have been used ubiquitously for such tasks. Recent works have demonstrated superior performance of soft assignments over hard assignments. Fisher vector representations have been shown to outperform other global representations on most benchmark datasets. Fisher vectors (i) use soft assignments, and (ii) reduce information loss due to quantization by capturing the deviations from the mean. However, the Fisher vector representations are huge and the representation size increases linearly with the vocabulary size. Recent findings report that the classification performance of Fisher vectors is proportional to the vocabulary size. Computational and storage requirements, however, discourage the use of arbitrarily large vocabularies. Also, Fisher vectors are not inherently discriminative. In this paper, we devise a novel strategy to compute sparse Fisher representations. This allows us to increase the vocabulary size with little computation and storage overhead and still attain the performance of a larger vocabulary. Further, we describe an approach to encode class-discriminative information in the Fisher vectors. We evaluate our method on four popular datasets. Empirical results show that our representations consistently outperform the traditional Fisher Vector representations and are comparable to the state of art approaches.
Optimal parallel suffix tree construction

An O(m)-work, O(m)-space, $O(log^4 m)$-time CREW-PRAM algorithm for constructing the suffix tree of a string s of length m drawn from any fixed alphabet set is obtained. This is the first known work and space optimal parallel algorithm for this problem. It can be generalized to a string s drawn from any general alphabet set to perform in $O(log^4 m)$ time and $O(m log |\Sigma|)$ work and space, after the characters in s have been sorted alphabetically, where $|\Sigma|$ is the number of distinct characters in s. In this case too, the algorithm is work-optimal
Integrating Uncomfortable Intersection-Turns to Subjectively Optimal Route Selection Using Genetic Algorithm

Route selection is one of the most important problems for a car navigation system. Given a pair of origin and destination, there are many possible routes. Most current car navigation systems propose the shortest path from the origin to the destination. Selecting the shortest path is not a hard problem, but the shortest path is not always what the user wants; what the user really wants to have is the most comfortable route for him or her to drive. In other words, the driver wants to have a car navigation system to propose the subjectively optimal route for him or her. Finding such a route requires enumerating all the possible routes, and is known as a NP-hard problem. In order to reduce computational complexity, we have employed a GA to find a (subjectively) quasi optimal route for the driver. In this paper, we report our attempt to integrate uncomfortable-turns in to the conditions of our GA-based route selection algorithm. The numerical experiments demonstrate the feasibility of our GA-based route selection method.
Downregulation of Tetrodotoxin-Resistant Sodium Currents and Upregulation of a Rapidly Repriming Tetrodotoxin-Sensitive Sodium Current in Small Spinal Sensory Neurons after Nerve Injury

Clinical and experimental studies have shown that spinal sensory neurons become hyperexcitable after axonal injury, and electrophysiological changes have suggested that this may be attributable to changes in sodium current expression. We have demonstrated previously that sodium channel α-III mRNA levels are elevated and sodium channel α-SNS mRNA levels are reduced in rat spinal sensory neurons after axotomy. In this study we show that small (C-type) rat spinal sensory neurons express sodium currents with dramatically different kinetics after axotomy produced by sciatic nerve ligation. Uninjured C-type neurons express both slowly inactivating tetrodotoxin-resistant (TTX-R) sodium current and a fast-inactivating tetrodotoxin-sensitive (TTX-S) current that reprimes (recovers from inactivation) slowly. After axotomy, the TTX-R current density was greatly reduced. No difference was observed in the density of TTX-S currents after axotomy, and their voltage dependence was not different from controls. However, TTX-S currents in axotomized neurons reprimed four times faster than control TTX-S currents. These data indicate that axotomy of spinal neurons is followed by downregulation of TTX-R current and by the emergence of a rapidly repriming TTX-S current and suggest that this may be attributable to the upregulation of a sodium channel isoform that was unexpressed previously in these cells. These axotomy-induced changes in sodium currents are expected to alter excitability substantially and could underlie the molecular pathogenesis of some chronic pain syndromes associated with injury to the axons of spinal sensory neurons.
Preceding attention and the dorsomedial prefrontal cortex: Process specificity versus domain dependence

The dorsomedial prefrontal cortex (DMPFC) has been shown to be involved in attending different states, all including a strong emotional component. It remains unclear, though, whether neural activity in the DMPFC is predominantly determined by either a particular domain, as emotional stimuli, or by a specific process, as attention. Here, we used functional magnetic resonance imaging to test the alternative hypotheses of domain‐ versus process‐specificity in DMPFC. Subjects had to perceive pictures from three different domains, sexual, emotional, and neutral stimuli, in both a nonattended, i.e., unexpected, and attended, i.e., expected mode. Our results show DMPFC activation during attended, i.e., expected stimulus perception when compared with nonattended, i.e., unexpected stimuli perception. DMPFC activation and corresponding behavioral changes (reaction time, subjective ratings) were observed in all three domains, sexual, emotional, and neutral stimuli. As opposed to those process‐specific effects that were found predominantly in posterior DMPFC, a process by domain interaction was found to be characteristic for more anterior parts of the DMPFC. Taken together, our findings favour the hypothesis that neural activity in the posterior DMPFC is determined by a specific process, i.e., attending stimuli, and thus characterized by process‐specificity rather than by a particular domain, i.e., sexual, emotional, or neutral stimuli, reflecting domain‐specificity. This suggests that the anterior and posterior DMPFC is involved in the process of attending mental states while remaining more (posterior DMPFC) or less (anterior DMPFC) independent of the type or domain of the respective stimulus. Hum Brain Mapp, 2009. © 2007 Wiley‐Liss, Inc.