Miracle-dz/UniFAR-FTUs huggingface dataset:
The immune response in autism: a new frontier for autism research

Autism spectrum disorders (ASD) are part of a broad spectrum of neurodevelopmental disorders known as pervasive developmental disorders, which occur in childhood. They are characterized by impairments in social interaction, verbal and nonverbal communication and the presence of restricted and repetitive stereotyped behaviors. At the present time, the etiology of ASD is largely unknown, but genetic, environmental, immunological, and neurological factors are thought to play a role in the development of ASD. Recently, increasing research has focused on the connections between the immune system and the nervous system, including its possible role in the development of ASD. These neuroimmune interactions begin early during embryogenesis and persist throughout an individual’s lifetime, with successful neurodevelopment contingent upon a normal balanced immune response. Immune aberrations consistent with a dysregulated immune response, which so far, have been reported in autistic children, include abnormal or skewed T helper cell type 1 (TH1)/TH2 cytokine profiles, decreased lymphocyte numbers, decreased T cell mitogen response, and the imbalance of serum immunoglobulin levels. In addition, autism has been linked with autoimmunity and an association with immune‐based genes including human leukocyte antigen (HLA)‐DRB1 and complement C4 alleles described. There is potential that such aberrant immune activity during vulnerable and critical periods of neurodevelopment could participate in the generation of neurological dysfunction characteristic of ASD. This review will examine the status of the research linking the immune response with ASD.
Medical student web-based formative assessment tool for renal pathology

Background Web-based formative assessment tools have become widely recognized in medical education as valuable resources for self-directed learning. Objectives To explore the educational value of formative assessment using online quizzes for kidney pathology learning in our renal pathophysiology course. Methods Students were given unrestricted and optional access to quizzes. Performance on quizzed and non-quizzed materials of those who used (‘quizzers’) and did not use the tool (‘non-quizzers’) was compared. Frequency of tool usage was analyzed and satisfaction surveys were utilized at the end of the course. Results In total, 82.6% of the students used quizzes. The greatest usage was observed on the day before the final exam. Students repeated interactive and more challenging quizzes more often. Average means between final exam scores for quizzed and unrelated materials were almost equal for ‘quizzers’ and ‘non-quizzers’, but ‘quizzers’ performed statistically better than ‘non-quizzers’ on both, quizzed (p=0.001) and non-quizzed (p=0.024) topics. In total, 89% of surveyed students thought quizzes improved their learning experience in this course. Conclusions Our new computer-assisted learning tool is popular, and although its use can predict the final exam outcome, it does not provide strong evidence for direct improvement in academic performance. Students who chose to use quizzes did well on all aspects of the final exam and most commonly used quizzes to practice for final exam. Our efforts to revitalize the course material and promote learning by adding interactive online formative assessments improved students’ learning experience overall.
Pseudo-coherence-based MVDR beamformer for speech enhancement with ad hoc microphone arrays

Speech enhancement with distributed arrays has been met with various methods. On the one hand, data independent methods require information about the position of sensors, so they are not suitable for dynamic geometries. On the other hand, Wiener-based methods cannot assure a distortionless output. This paper proposes minimum variance distortionless response filtering based on multichannel pseudo-coherence for speech enhancement with ad hoc microphone arrays. This method requires neither position information nor control of the trade-off used in the distortion weighted methods. Furthermore, certain performance criteria are derived in terms of the pseudo-coherence vector, and the method is compared with the multichannel Wiener filter. Evaluation shows the suitability of the proposed method in terms of noise reduction with minimum distortion in ad hoc scenarios.
On Hardware-Oriented Message Authentication with Applications towards RFID

We consider ultra light-weight constructions of message authentication in hardware applications like RFID. We propose a new type of constructions that will be less costly to implement in hardware, compared to any previous construction. These constructions are based on the framework of universal hash functions, Toeplitz matrices and epsilon-biased sample spaces. Some new theoretical results in this area are derived. The hardware-attractive new constructions come at the price of not being able to prove the exact substitution probability. The expected probability is examined both through theoretical methods as well as through simulation.
Extraction of Parallel Application Signatures for Performance Prediction

Predicting performance of parallel applications is becoming increasingly complex and the best performance predictor is the application itself, but the time required to run it thoroughly is a onerous requirement. We seek to characterize the behavior of message-passing applications on different systems by extracting a signature which will allow us to predict what system will allow the application to perform best. To achieve this goal, we have developed a method we called Parallel Application Signatures for Performance Prediction (PAS2P) that strives to describe an application based on its behavior. Based on the application’s message-passing activity, we have been able to identify and extract representative phases, with which we created a Parallel Application Signature that has allowed us to predict the application’s performance. We have experimented with different signature-extraction algorithms and found a reduction in the prediction error using different scientific applications on different clusters. We were able to predict execution times with an average accuracy of over 98%.
On the fidelity of the core mass functions derived from dust column density data

Aims: We examine the recoverability and completeness limits of the dense core mass functions (CMFs) derived for a molecular cloud using extinction data and a core identification scheme based on two-dimensional thresholding. Methods: We performed simulations where a population of artificial cores was embedded into the variable background extinction field of the Pipe nebula. We extracted the cores from the simulated extinction maps, constructed the CMFs, and compared them to the input CMFs. The simulations were repeated using a variety of extraction parameters and several core populations with differing input mass functions and differing degrees of crowding. Results: The fidelity of the observed CMF depends on the parameters selected for the core extraction algorithm for our background. More importantly, it depends on how crowded the core population is. We find that the observed CMF recovers the true CMF reliably when the mean separation of cores is larger than their mean diameter (f>1). If this condition holds, the derived CMF is accurate and complete above M > 0.8-1.5 Msun, depending on the parameters used for the core extraction. In the simulations, the best fidelity was achieved with the detection threshold of 1 or 2 times the rms-noise of the extinction data, and with the contour level spacings of 3 times the rms-noise. Choosing larger threshold and wider level spacings increases the limiting mass. The simulations show that when f>1.5, the masses of individual cores are recovered with a typical uncertainty of 25-30 %. When f=1 the uncertainty is ~60 %. In very crowded cases where f<1 the core identification algorithm is unable to recover the masses of the cores adequately. For the cores of the Pipe nebula f~2.0 and therefore the use of the method in that region is justified.
Face Spoofing Detection Based on Improved Local Graph Structure

Face spoofing attack is one of the recent security problems that face recognition systems are proven to be vulnerable to. The spoofing occurs when an attacker bypass the authentication scheme by presenting a copy of the face image for a valid user. Therefore, it's very easy to perform a face recognition spoofing attack with compare to other biometrics. This paper, presents a novel and efficient facial image representation for face spoofing called improved local graph structure (ILGS). We divide the input facial image into several regions and then we calculate local graph structure (LGS) codes for each region. On the other hand, the histograms are concatenated into an enhanced feature vector to detect spoofed facial image. Finally, performance of the proposed method is evaluated on the NUAA database.
Practical Use of Gemcitabine and Cisplatin Combination Therapy as First-Line Treatment for Japanese Patients with Advanced Biliary Tract Cancer

Gemcitabine and cisplatin combination therapy (GC) is accepted as a standard treatment for advanced biliary tract cancer (BTC). However, little information is available regarding such treatment in the clinical practice setting in Japan. We retrospectively examined the clinical data of patients with unresectable or recurrent BTC who received GC as first-line treatment. The regimen consisted of cisplatin (25 mg/m 2 ) and gemcitabine (1000 mg/m 2 ) administered intravenously on days 1 and 8 of repeated 3-week cycles. Twenty patients were analyzed. A total of 148 cycles of GC was administered, with a median of 8 and a range of 1 to 18 cycles. Treatment delay and dose reduction were noted in 35 (24%) and 41 (28%) of the 148 cycles, respectively. The major adverse events of grade 3 or 4 included neutropenia (50%), leukopenia (45%), anemia (30%), and thrombocytopenia (15%). Nonhematologic toxicities included nausea (10%), appetite loss (10%), and fatigue (10%). Median progression-free and overall survival times were 6.9 and 12.3 months, respectively. Gallbladder cancer showed a significantly higher response rate than did other types of BTC (chi-squaretest, P = 0.002). GC was thus effective and well tolerated as first-line chemotherapy for Japanese patients with advanced BTC in the clinical practice setting.
Optimal message-driven implementations of omega with mute processes

We investigate the complexity of algorithms in message-driven models. In such models, events in the computation can only be caused by message receptions, but not by the passage of time. Hutle and Widder [2005a] have shown that there is no deterministic message-driven self-stabilizing implementation of the eventually strong failure detector and thus Ω in systems with uncertainty in message delays and channels of unknown capacity using only bounded space. Under stronger assumptions it was shown that even the eventually perfect failure detector can be implemented in message-driven systems consisting of at least f + 2 processes (f being the upper bound on the number of processes that crash during an execution). In this article we show that f + 2 is in fact a lower bound in message-driven systems, even if nonstabilizing algorithms are considered. This contrasts time-driven models where f + 1 is sufficient for failure detector implementations. Moreover, we investigate algorithms where not all processes send message, that is, are active, but some (in a predetermined set) remain passive. Here, we show that the f + 2 processes required for message-driven systems must be active, while in time-driven systems it suffices that f processes are active. We also provide message-driven implementations of Ω. Our algorithms are efficient in the sense that not all processes have to send messages forever, which is an improvement to previous message-driven failure detector implementations.
Effect of Educational Intervention on Adverse Drug Reporting by Physicians: A Cross-Sectional Study

In India, the pharmacovigilance program is still in its infancy. National Pharmacovigilance Program of India was started for facilitating the pharmacovigilance activities. The ADR reporting rate is still below satisfactory in India. This cross-sectional questionnaire based study was carried out in a tertiary care teaching hospital in Uttarakhand, which is a peripheral ADR monitoring centre to assess the level of knowledge, attitude, and the practices of pharmacovigilance among the doctors and to compare it with the group of doctors attending educational CME for improving awareness of pharmacovigilance. The most important revelation of this study was that although adequate knowledge and the right attitude about adverse drug reaction reporting were instigated in the doctors after the educational intervention, the practice was still neglectful in both groups, emphasizing the need to design the strategies to develop adverse drug reaction reporting culture.
Multi-Source Iterative Adaptation for Cross-Domain Classification

Owing to the tremendous increase in the volume and variety of user generated content, train-once-apply-forever models are insufficient for supervised learning tasks. Thus, developing algorithms that adapt across domains by leveraging data from multiple domains is critical. However, existing adaptation algorithms often fail to identify the right sources to use for adaptation. In this work, we present a novel multi-source iterative domain adaptation algorithm (MSIDA) that leverages knowledge from selective sources to improve the performance in a target domain. The algorithm first chooses the best K sources from possibly numerous existing domains taking into account both similarity and complementarity properties of the domains. Then it learns target specific features in an iterative manner building on the common shared representations from the source domains. We give theoretical justifications for our source selection procedure and also give mistake bounds for the MSIDA algorithm. Experimental results justify the theory as MSIDA significantly outperforms existing cross-domain classification approaches on the real world and benchmark datasets.
SOCIO-ECONOMIC STATUS AND HEALTH: EVIDENCE FROM THE ECHP

In this paper, the effects of socioeconomic characteristics (gender, age, education level, marital status, income, occupational and health status, household size and social relationships) on individuals´ health status in Spain from 1994 to 2001 are analysed. The estimations are carried out using ordered probit models and new data from the whole waves of the European Community Household Panel (ECHP) have been used. The results indicate that personal characteristics, education level, income as well as health status and social relationships have strong influence on self-assessed health.
Metal enrichment of the intra-cluster medium by thermally and cosmic-ray driven galactic winds An analytical prescription for galactic outflows

Aims. We investigate the efficiency and time-dependence of thermally and cosmic ray driven galactic winds for the metal enrichment of the intra-cluster medium (ICM) using a new analytical approximation for the mass outflow. The spatial distribution of the metals are studied using radial metallicity profiles and 2D metallicity maps of the model clusters as they would be observed by X-ray telescopes like XMM-Newton. Methods. Analytical approximations for the mass loss by galactic winds driven by thermal and cosmic ray pressure are derived from the Bernoulli equation and implemented in combined N-body/hydrodynamic cosmological simulations with a semi-analytical galaxy formation model. Observable quantities like the mean metallicity, metallicity profiles, and 2D metal maps of the model clusters are derived from the simulations. Results. We find that galactic winds alone cannot account for the observed metallicity of the ICM. At redshift z = 0 the model clusters have metallicities originating from galactic winds which are almost a factor of 10 lower than the observed values. For massive, relaxed clusters we find, as in previous studies, a central drop in the metallicity due to a suppression of the galactic winds by the pressure of the ambient ICM. Combining ram-pressure stripping and galactic winds we find radial metallicity profiles of the model clusters which agree qualitatively with observed profiles. Only in the inner parts of massive clusters the observed profiles are steeper than in the simulations. Also the combination of galactic winds and ram-pressure stripping yields too low values for the ICM metallicities. The slope of the redshift evolution of the mean metallicity in the simulations agrees reasonably well with recent observations.
Context Matters, But How Much? Latent State–Trait Analysis of Cognitive Ability Assessments

Cognitive abilities are thought to represent temporally stable constructs, however, accumulating evidence suggests that effects of the measurement situation could affect its measurement (e.g., effects of test motivation, stress level). The present study modeled these effects explicitly in a latent variables approach. In contrast to previous studies, we investigated participants (job candidates) in repeated high-stakes settings (N5188). We found that cognitive ability measurements in high-stakes settings not only reflect a stable latent trait and random measurement error, but also systematic effects of the test setting. Our results support the application of cognitive ability tests in organizational contexts but have implications for its use in applied settings such as personnel selection.
Coaches' Perspectives on the Use and Effectiveness of Exercise as Punishment in Interuniversity Sport

The purpose of this study was to investigate the use, frequency, and perceived effectiveness of exercise as punishment (EAP) in interuniversity sport. Semi-structured interviews were conducted with eight (four male and four female) interuniversity head coaches; half of the participants coached individual sports and the other half team sports. Data were analyzed inductively and thematically. Results revealed that EAP and shame were methods often used to modify athletic behaviours. When examining coaches’ perspectives, three broad themes emerged: the nature of punishment, coaches’ conceptualization of punishment, and shame and reintegration. Participants perceived EAP to be effective and were unable to suggest alternative, non-punitive strategies to modifying athletes’ behaviours. The findings are interpreted using Goffman’s (1961) Total Institution, Hughes & Coakley’s (1991) Sports Ethic, and Braithwaite’s (1989) Shame and reintegration theory. Future recommendations include: further research on EAP in sport, development of educational initiatives and reframing punishment within the relational maltreatment framework.
Evidence implicating substantia nigra in regulation of kindled seizure threshold

We studied the effects of microinjected drugs and brainstem lesions on motor and limbic seizures in the kindling model of epilepsy. The duration of motor seizures was determined by timing the colonic and tonic movements of the extremities. The duration of limbic seizures was determined by measuring afterdischarge recorded on the electroencephalogram. Bilateral microinjection of a gamma-aminobutyric acid (GABA) agonist, muscimol, into the area of the substantia nigra (SN) markedly suppressed both motor and limbic seizures induced by stimulation of amygdala, olfactory structures, or lateral entorhinal cortex. Microinjection of saline did not suppress seizures. The suppressive effect of muscimol: (i) dissipated after several hours and was dependent on dose; (ii) was due to an elevation of the seizure threshold, since typical seizures could be elicited with electrical current far exceeding the threshold; and (iii) exhibited spatial specificity since muscimol injections 1 to 2 mm dorsal to the SN or into neocortex did not suppress the seizures. The actions of muscimol were probably mediated by its GABA agonist properties, since microinjection of an irreversible inhibitor of GABA transaminase (gamma- vinyl GABA) into the area of the SN also suppressed kindled seizures. Destruction of brainstem structures was produced by microinjection of the neurotoxin, N-methyl-D,L-aspartate. Seizures were markedly suppressed in animals with bilateral destruction of the SN but not in animals in which the SN was spared bilaterally. We interpret the data to indicate that the SN is the site at which the GABA agonists and lesions act to raise the threshold for kindled seizures. The suppression of limbic seizures indicates that this brainstem nucleus can regulate the intrinsic neuronal excitability of hemispheric sites.
How University Lecturers’ Display of Emotion Affects Students’ Emotions, Failure Attributions, and Behavioral Tendencies in Germany, Russia, and the United States

In this study, we investigate whether the cultural-educational contexts in Russia, Germany, and the United States affect university students’ emotions, failure attributions, and behavioral tendencies after receiving negative achievement feedback from a lecturer. The 383 university students from Germany, Russia, and the United States participating in the study completed an online survey in which they read text vignettes of a university lecturer giving negative feedback to a student on his performance. We used a 2 × 3 × 3 experimental design to determine whether the negative feedback situation (private vs. public), the lecturer’s display of emotion (no emotion vs. anger vs. pity), and the cultural-educational contexts (German, Russian, U.S.) affected the participants’ judgment of the student’s affective and behavioral reactions to the negative feedback. Significant main effects and significant interactions were identified, for example, participants in Germany and in the United States reported stronger emotions in response to the negative feedback than the participants in Russia indicated. Also, compared with the participants in Germany and the United States, the participants in Russia attributed the student’s failure more often to external, unstable, and controllable factors and expected the student to adopt more approach tendencies after receiving the failure feedback. Furthermore, a culturally universal effect of emotional transmission between lecturer and student was found, as participants believed the student, for example, to feel anger when his lecturer displayed anger. Overall, the interplay of cultural-educational and situational contexts can affect the way students respond to the emotions a university lecturer displays, and those emotions can shape students’ learning behavior.