Miracle-dz/UniFAR-FTUs huggingface dataset:
759C/T Variants of the Serotonin (5-HT2C) Receptor Gene and Weight Gain in Children and Adolescents in Long-Term Risperidone Treatment

Background Great inter-individual variability exists in the susceptibility to gain weight during antipsychotic treatment. Thus, we examined whether the −759C/T variants in the promoter region of the 5HT2C receptor gene were differentially associated with weight gain in children and adolescents in long-term risperidone treatment. Methods Medically healthy 7 to 17 year-olds, treated with risperidone for ≥ six months, were enrolled. Anthropometric measurements, laboratory tests, and treatment history were obtained upon enrollment and from medical records. The effect of the genotype on the trajectory of age-sex-adjusted weight and body mass index (BMI) z scores before and after the onset of risperidone treatment was investigated. Results In 124 subjects (90% males, mean age: 11.8 years) treated with risperidone for a mean of 2.8 years, weight and BMI z scores significantly increased after starting risperidone. This change was similar across the two genotype groups as were changes in several cardiometabolic variables. Conclusion In contrast to other reports, the T allele failed to confer protection against excessive weight gain or cardiometabolic abnormalities in this group of children and adolescents chronically treated with risperidone.
Efficient scene segmentation for content-based indexing in the compressed domain

Content-based indexing and retrieval of video are important in many applications, and scene-change detection plays an essential role in these tasks. We introduce a faster than real-time algorithm for sudden and gradual scene change detection in MPEG video. For sudden scene change detection, we use an adaptive threshold that is applied to the number of bi-directional predicted macroblocks within a B-frame. To direct gradual scene changes such as dissolves and fades, we divide a selected frame into sub-macroblock images, and perform an analysis of the motion vectors within this image. To refine the gradual scene change, a camera motion analysis technique is performed. Experimental results show that this algorithm is fast and robust for the detection of most abrupt and gradual scene changes in the compressed domain.
Anaerobic and Aerobic Performances in Elite Basketball Players

Abstract The purpose of this study was to propose a specific lactate minimum test for elite basketball players considering the: Running Anaerobic Sprint Test (RAST) as a hyperlactatemia inductor, short distances (specific distance, 20 m) during progressive intensity and mathematical analysis to interpret aerobic and anaerobic variables. The basketball players were assigned to four groups: All positions (n=26), Guard (n= 7), Forward (n=11) and Center (n=8). The hyperlactatemia elevation (RAST) method consisted of 6 maximum sprints over 35 m separated by 10 s of recovery. The progressive phase of the lactate minimum test consisted of 5 stages controlled by an electronic metronome (8.0, 9.0, 10.0, 11.0 and 12.0 km/h) over a 20 m distance. The RAST variables and the lactate values were analyzed using visual and mathematical models. The intensity of the lactate minimum test, determined by a visual method, reduced in relation to polynomial fits (2nd degree) for the Small Forward positions and General groups. The Power and Fatigue Index values, determined by both methods, visual and 3rd degree polynomial, were not significantly different between the groups. In conclusion, the RAST is an excellent hyperlactatemia inductor and the progressive intensity of lactate minimum test using short distances (20 m) can be specifically used to evaluate the aerobic capacity of basketball players. In addition, no differences were observed between the visual and polynomial methods for RAST variables, but lactate minimum intensity was influenced by the method of analysis
Towards a Gamified Equivalent Mutants Detection Platform

This poster presents a gamified system for equivalent mutants detection. This system can be used as a standalone tool for developers and testing teams alike - but we plan to use this system on a crowdsourcing platform to evaluate the various parameters involved in the detection of equivalent mutants, such as, expertise (coding and testing), familiarity with the code base, complexity of the code and tests, measured likelihood of equivalent mutants.
Best-fit constructional analysis

This dissertation describes a process called best-fit constructional analysis and the associated implementation called the Constructional Analyzer. The constructional analyzer takes an utterance as input and performs deep semantic analysis, mapping the utterance onto its most likely interpretation. The best-fit constructional analyzer is unique because it combines Embodied Construction Grammar with the power of best-fit processing. This combination enables the constructional analyzer to be both a cognitive model of interpretation and a practical semantic analysis system. The best-fit constructional analyzer performs incremental unification grammar parsing, using a factored probabilistic model over syntax and semantics to guide interpretation. The constructional analyzer has been applied to a range of applications: (a) It is a tool for building and testing construction grammars. (b) It is a psychologically plausible model of human interpretation that makes predictions about reading time that match experimental evidence. (c) It is a practical system for semantic analysis that has been tested on a corpus of Mandarin child-parent dialogues.
Efficient computation of distance sketches in distributed networks

Distance computation (e.g., computing shortest paths) is one of the most fundamental primitives used in communication networks. The cost of effectively and accurately computing pairwise network distances can become prohibitive in large-scale networks such as the Internet and Peer-to-Peer (P2P) networks. To negotiate the rising need for very efficient distance computation at scales never imagined before, approximation techniques for numerous variants of this question have recently received significant attention in the literature. Several different areas of theoretical research have emerged centered around this problem, such as metric embeddings, distance labelings, spanners, and distance oracles. The goal is to preprocess the graph and store a small amount of information such that whenever a query for any pairwise distance is issued, the distance can be well approximated (i.e., with small stretch) very quickly in an online fashion. Specifically, the pre-processing (usually) involves storing a small sketch with each node, such that at query time only the sketches of the concerned nodes need to be looked up to compute the approximate distance. Techniques derived from metric embeddings have been considered extensively by the networking community, usually under the name of network coordinate systems. On the other hand, while the computation of distance oracles has received considerable attention in the context of web graphs and social networks, there has been little work towards similar algorithms within the networking community. In this paper, we present the first theoretical study of distance sketches derived from distance oracles in a distributed network. We first present a fast distributed algorithm for computing approximate distance sketches, based on a distributed implementation of the distance oracle scheme of [Thorup-Zwick, JACM 2005]. We also show how to modify this basic construction to achieve different tradeoffs between the number of pairs for which the distance estimate is accurate, the size of the sketches, and the time and message complexity necessary to compute them. These tradeoffs can then be combined to give an efficient construction of small sketches with provable average-case as well as worst-case performance. Our algorithms use only small-sized messages and hence are suitable for bandwidth-constrained networks, and can be used in various networking applications such as topology discovery and construction, token management, load balancing, monitoring overlays, and several other problems in distributed algorithms.
“You don’t know half the story”: deepening the dialogue with young mothers in Australia

Pregnant and young mothers’ stories often go untold or are poorly represented within dominant health and social care discourses. Consequently, narratives of young mothers are largely absent from social and health care literature, especially in relation to how young women make sense, understand, and experience young motherhood. Drawing on 7 months of participant observation fieldwork at a community service, and 11 in-depth interviews, we discuss six metaphorical themes which capture the experiences of young mothers using a narrative approach. These include: Picking up the Pieces; Walking a Narrow and Familiar Path; Jumping over Puddles; Riding the Rapids to Motherhood; Living with Dirty Looks; and Asking for Directions. Contrary to the wider community’s deficit view and stereotypes of young mothers, what emerged from the narratives was quite a different story. Becoming a young mother meant taking a stand against stigma from the wider community; recognising motherhood as a significant and transformational turning point in their lives, one that opened doors to alternative storylines of hope, autonomy and agency, especially given a supportive context. These findings enhance our understandings by widening the lens to diverse realities that exist in young mothers’ lives and present a strong case for using a narrative approach to research and practice when working with young mothers.
Restory a Resilience Experience After a Natural Disaster

As an attempt to describe a resilience process after a landslide through narratives, this research study aims at analyzing, interpreting and describing how Chevano tenth graders restory their resilience experience after a natural disaster in their hometown. This inquiry was carried out with students at Lopez Quevedo School in Jerico - Boyaca, Colombia. The information was gathered through students’ narratives, students’ interviews, and researcher’s field notes. Narratives made part of a pedagogical intervention to explore student’s ways of coping with tragedy, and they allow students’ voices to be expressed. It was revealed that students needed to share their stories to achieve a process of resilience but it was important to give participants the time to start that process. Moreover, they needed to be involved in a social context they felt they made part of as well as in a routine in which they could set apart the negative thoughts and feelings of sadness from their present experiences.
Evaluation of 12 Commercial Tests for Detection of Epstein-Barr Virus-Specific and Heterophile Antibodies

ABSTRACT Ten microbiological departments in Norway have participated in a multicenter evaluation of the following commercial tests for detection of Epstein-Barr virus (EBV)-specific and heterophile antibodies: CAPTIA Select viral capsid antigen (VCA)-M/G/EBNA (Centocor Inc.), Enzygnost anti-EBV/immunoglobulin M (IgM) and IgG (Dade Behring), Vironostika EBV VCA IgM/IgG/EBNA enzyme-linked immunosorbent assay (ELISA) (Organon Teknika), SEROFLUOR immunofluorescence assay and EBV Combi-Test (Institute Virion Ltd.), anti-EBV recombinant IgM- and IgG-early antigen/EBNA IgG ELISA (Biotest Diagnostics), EBV IgM/IgG/EBNA ELISA (Gull Laboratories), Paul-Bunnell-Davidsohn test (Sanofi Diagnostics Pasteur), Monosticon Dri-Dot (Organon Teknika), Avitex-IM (Omega Diagnostics Ltd.), Alexon Serascan infectious mononucleosis test (Alexon Biomedical Inc.), Clearview IM (Unipath Ltd.), and Cards±OS Mono (Pacific Biotech, Inc.). The test panel included sera from patients with primary EBV infection, immunocompromised patients with recent cytomegalovirus infection, healthy persons (blood donors), and EBV-seronegative persons. Among the tests for EBV-specific antibodies the sensitivity was good, with only small differences between the different assays. However, there was a greater variation in specificity, which varied between 100% (Enzygnost) and 86% (Biotest). Tests for detection of heterophile antibodies based on purified or selected antigen (Avitex, Alexon, Clearview IM, and Cards±OS Mono) were more sensitive than the Paul-Bunnell-Davidsohn and Monosticon tests.
Effects of Semantic Richness on Lexical Processing in Monolinguals and Bilinguals

The effect of number of senses (NoS), a measure of semantic richness, was examined in monolingual English speakers (n = 17) and bilingual speakers of English and French (n = 18). Participants completed lexical decision tasks while EEG was recorded: monolinguals completed the task in English only, and bilinguals completed two lexical decision tasks, one in English and one in French. Effects of NoS were observed in both participant groups, with shorter response times and reduced N400 amplitudes to high relative to low NoS items. These effects were stronger in monolinguals than in bilinguals. Moreover, we found dissociations across languages in bilinguals, with stronger behavioral NoS effects in English and stronger event-related potential (ERP) NoS effects in French. This finding suggests that different aspects of linguistic performance may be stronger in each of a bilingual’s two languages.
On Energy Efficient Encryption for Video Streaming in Wireless Sensor Networks

Selective encryption for video streaming was proposed for efficient multimedia content protection. However, the issues on joint optimization of video quality, content protection, and communication energy efficiency in a wireless sensor network (WSN) have not been fully addressed in the literature. In this paper, we propose a scheme to optimize the energy, distortion, and encryption performance of video streaming in WSNs. The contribution of this work is twofold. First, a channel-aware selective encryption approach is proposed to minimize the extra encryption dependency overhead at the application layer. Second, an unequal error protection (UEP)-based network resource allocation scheme is proposed to improve the communication efficiency at the lower layers. Simulation experiments demonstrate that the proposed joint selective encryption and resource allocation scheme can improve the video transmission quality significantly with guaranteed content protection and energy efficiency.
Differential High-Affinity Interaction of Dectin-1 with Natural or Synthetic Glucans Is Dependent upon Primary Structure and Is Influenced by Polymer Chain Length and Side-Chain Branching

Glucans are structurally diverse fungal biopolymers that stimulate innate immunity and are fungal pathogen-associated molecular patterns. Dectin-1 is a C-type lectin-like pattern recognition receptor that binds glucans and induces innate immune responses to fungal pathogens. We examined the effect of glucan structure on recognition and binding by murine recombinant Dectin-1 with a library of natural product and synthetic (1→3)-β/(1→6)-β-glucans as well as nonglucan polymers. Dectin-1 is highly specific for glucans with a pure (1→3)-β-linked backbone structure. Although Dectin-1 is highly specific for (1→3)-β-d-glucans, it does not recognize all glucans equally. Dectin-1 differentially interacted with (1→3)-β-d-glucans over a very wide range of binding affinities (2.6 mM–2.2 pM). One of the most striking observations that emerged from this study was the remarkable high-affinity interaction of Dectin-1 with certain glucans (2.2 pM). These data also demonstrated that synthetic glucan ligands interact with Dectin-1 and that binding affinity increased in synthetic glucans containing a single glucose side-chain branch. We also observed differential recognition of glucans derived from saprophytes and pathogens. We found that glucan derived from a saprophytic yeast was recognized with higher affinity than glucan derived from the pathogen Candida albicans. Structural analysis demonstrated that glucan backbone chain length and (1→6)-β side-chain branching strongly influenced Dectin-1 binding affinity. These data demonstrate: 1) the specificity of Dectin-1 for glucans; 2) that Dectin-1 differentiates between glucan ligands based on structural determinants; and 3) that Dectin-1 can recognize and interact with both natural product and synthetic glucan ligands.
Chasing the suspect: keratoconus

The detection of keratoconus is a major concern in the screening of refractive surgical patients, since it is known that its presence weakens the corneal stroma and can lead to iatrogenic ectasia. While clinical keratoconus is reliably detected with corneal topography and slit-lamp examination, means to detect the possibility of keratoconus in its earliest stages prior to the presence of slit-lamp findings have been extensively explored, and it is generally agreed that the first detectable sign of keratoconus is a localised steepening seen with Placido corneal topography. Several terms have been put forward to describe this condition including preclinical keratoconus, keratoconus suspect and forme fruste keratoconus. While these designations have been used interchangeably, doing so has led to problems in understanding the natural history of keratoconus. Despite this short-coming, excellent longitudinal studies are being conducted and are slowly emerging in the literature. In the June issue, Shirayama-Suzuki and colleagues1 examined keratoconus progression in the fellow eye in unilateral keratoconus patients over the course of 6 years. The fellow eyes were included if they had no slit-lamp signs of keratoconus or deterioration of spectacle-corrected visual acuity. The authors found that just over 20% of the fellow eyes progressed to clinical keratoconus with evidence of increased asymmetry, spherical equivalent and higher-order irregularities, which they documented with topographic indices and Fourier analysis. As they note, keratoconus is a slowly progressing disease, and therefore it is likely that a longer follow-up would result in more of their cohort progressing to clinical keratoconus. This study provides a …
Geometric Distribution in Some Two-Dimensional Queuing Systems

The state of the system is a two dimensional random variable N = (N1, N2) with N1 ≧ 0, 1 ≦ N2 ≦ m. Transitions require negative exponential times. The vector Pn of probabilities of being in states for which N1 = n satisfy the general condition λIPn−1 + BPn + CPn+1 = 0. Two arguments are given showing Pn = RPn−1 and an iterative scheme for finding R is constructed.
Ultraviolet Disinfection of Fecal Coliform in Municipal Wastewater: Effects of Particle Size

Suspended solids interfere with the efficiency of disinfection using UV radiation by decreasing the rate of disinfection and inducing tailing. However, conventional measures of solids (total suspended solids, turbidity, and UV transmittance) do not adequately predict the presence or degree of these effects. Bacteria and viruses can become associated with particles in wastewater. A fractionation technique was developed to separate particle‐associated bacteria into three fractions, based on particle size. The results show that the degree to which particles interfere with UV disinfection efficiency is dependent on particle size. The small size fraction (<5 μm) consistently produced a statistically significant faster disinfection rate than the large fraction (>20 μm), with the unfiltered sample and the medium fraction (particles >5 μm, but <20 μm) between the two extremes. Tailing also was observed only in the large fraction. Correlations between the disinfection rate constant and the percentage of large fraction bacteria of a sample were good.
EXTRACTION OF HYPERSPECTRAL IMAGES USING MATCHING PURSUIT

Hyperspectral images contain rich and fine spectral information, an improvement of land use/cover classification accuracy is expected from the use of such images. However, the classification methods that have been successfully applied to multispectral data in the past are not as effective as to hyperspectral data. The major cause is that the size of training data set does not correspond to the increase of dimensionality of hyperspectral data. Actually, the problem of the “curse of dimensionality” emerges when a statisticbased classification method is applied to the hyperspectral data. A simpler, but sometimes very effective way of dealing with hyperspectral data is to reduce the number of dimensionality. This can be done by feature extraction that a small number of salient features are extracted from the hyperspectral data when confronted with a limited set of training samples. In this paper, we tested some proposed feature extraction methods based on the wavelet transform to reduce the high dimensionality without losing much discriminating power in the new feature space. In addition, a new feature extraction method based on the matching pursuit with wavelet packet is used to extract useful features for classification. An AVIRIS data set was tested to illustrate the classification performance of the new method and be compared with the existing wavelet-based methods of feature extraction.
Computer Anxiety and Attitudes toward Using Internet in English Language Classes among Iranian Postgraduate Student Teachers

This study was designed to investigate the level of computer anxiety and the overall attitudes of Iranian postgraduate student teachers toward using the Internet in English language classes. Using a stratified random sampling, 160 participants (64 males and 96 females) were selected to take part in the study. These respondents were English language teachers who were pursuing their studies in Teaching English as a Second Language (TESL), English Literature, and Linguistics in public universities of Malaysia. A three-part questionnaire consisting of demographic information, Computer Anxiety Rating Scale (CARS) and Internet Attitude Scale (IAS) was administered in the data collection process. A pilot test was also conducted to achieve the reliability of the instruments. In order to strengthen the results, a semi- structured interview was conducted as well. The results indicated that the level of computer anxiety and the attitudes of the respondents toward using the Internet were of a moderate level. The findings of the independent-sample t-test showed significant mean differences between males and females and their level of computer anxiety and also their attitudes toward using the Internet. In addition, findings of the Pearson correlation coefficient revealed a significant negative relationship between computer anxiety and the participants' attitude toward using the Internet in their English language classes. Meanwhile, responses gauged through interview also supported the above findings. In conclusion, to eliminate the computer anxiety of teachers and encourage them to use the Internet technology in their classes, they should be equipped with sufficient technology skills through training programmes which can convince them about the usefulness of technologies in their instruction and create positive attitudes when using technology in the teaching and learning process.