Miracle-dz/UniFAR-FTUs huggingface dataset:
The role of serotoninergic neurons in amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (SLA) is a neurodegenerative disease characterize by the loss of upper motor neurons in the motor cortex and lower motor neurons in the brainstem and spinal cord. The loss of motor neurons leads to muscle atrophy and progressive paralysis. In 2013 our laboratory identified a new neuronal population affected in ALS. They observed the degeneration of serotoninergic neurons in ALS patients and animal models. For this, the aim of my PhD is to identify the role of serotoninergic neurons in case of ALS. We observed an upregulation of serotonin receptor 5-HT2B in ALS mice models. The investigation of the role of 5-HT2B receptor in case of ALS showed its role as a disease modulator. The loss of 5-HT2B receptor accelerated disease progression and modulated neuroinflammatory response. Moreover, our results showed that the loss of serotoninergic neurons is responsible of the development of spasticity, a painful symptom observed in ALS patients. All these opened the way for therapeutic strategies targeting spasticity and neuroinflammation in case of ALS.
A Survey on Encryption Schemes in the Clouds for Access Control

In this era, even sensitive data is stored and shared on the internet using trusted third parties and service providers. Cloud computing is one of the emerging technologies that is being used widely on these days. It makes use of the computing resources such as hardware and software that is delivered over the internet and provides remote services with user's data, software and computation. As the data is shared over the network, it is needed to be encrypted. Sharing of data means the data should be secured and proper access control should be maintained. There are many encryption schemes that provide security and access control in clouds. This paper presents a survey on various encryption schemes that provide security, scalable and flexible fine grained access control.
SPOT: A Toolbox for Interactive and Automatic Tuning in the R Environment

Sequential parameter optimization is a heuristic that combines classical and modern statistical techniques to improve the performance of search algorithms. It includes methods for tuning based on classical regression and analysis of variance techniques; tree-based models such as CART and random forest; Gaussian process models (Kriging), and combinations of different meta-modeling approaches. The suitability of these different meta models for parameter tuning is analyzed in this article. Automated and interactive approaches are compared.
Gerstenhaber-schack and Hochschild cohomologies of Hopf algebras

We show that the Gerstenhaber-Schack cohomology of a Hopf algebra determines its Hochschild cohomology, and in particular its Gerstenhaber-Schack cohomological dimension bounds its Hochschild cohomological dimension, with equality of the dimensions when the Hopf algebra is cosemisimple of Kac type. Together with some general considerations on free Yetter-Drinfeld modules over adjoint Hopf subalgebras and the monoidal invariance of Gerstenhaber-Schack cohomology, this is used to show that both Gerstenhaber-Schack and Hochschild cohomological dimensions of the coordinate algebra of the quantum permutation group are 3.
Preschoolers' Precision of the Approximate Number System Predicts Later School Mathematics Performance

The Approximate Number System (ANS) is a primitive mental system of nonverbal representations that supports an intuitive sense of number in human adults, children, infants, and other animal species. The numerical approximations produced by the ANS are characteristically imprecise and, in humans, this precision gradually improves from infancy to adulthood. Throughout development, wide ranging individual differences in ANS precision are evident within age groups. These individual differences have been linked to formal mathematics outcomes, based on concurrent, retrospective, or short-term longitudinal correlations observed during the school age years. However, it remains unknown whether this approximate number sense actually serves as a foundation for these school mathematics abilities. Here we show that ANS precision measured at preschool, prior to formal instruction in mathematics, selectively predicts performance on school mathematics at 6 years of age. In contrast, ANS precision does not predict non-numerical cognitive abilities. To our knowledge, these results provide the first evidence for early ANS precision, measured before the onset of formal education, predicting later mathematical abilities.
The Contribution of Social Network Sites in Health Education among Iranian Students.

Considering the growing application of Social network sites (SNS) as a method of health knowledge acquisition, the current study tried to illuminate the role played by SNS in educational environments and how Iranian students use them. This study was performed on 800 students of Semnan University of Medical Sciences in Iran, in 2015. The questionnaire was developed by the authors that measured the attitudes of the students in relation to organizational readiness, usefulness and the use of the SNS on a 5-point Likert type scale. The findings showed that mean score of the use of the SNS was 3.58. Mean score of the participants' attitudes towards the introduction of the SNS related to health by educational environment was 3.39, and about usefulness of the SNS to learn health -related issues was 2.45. Organizational readiness in the use of SNS had a significant and direct relationship with the use of them (B=0.796, P<0.001). The current health education system in the country has failed to take advantage of SNS, these sites have not promoted the students' health knowledge. Scientific organizations and educators are required to provide students with guidelines on how to use social media for scientific purposes. The availability of reliability measures, such as for the source of the information, the expertise and skills of the provider, and mechanisms for judging the quality of the provided information, may increase students' trust in SNS and their tendency to use these sites as educational resources.
ETSSDetector: A Tool to Automatically Detect Cross-Site Scripting Vulnerabilities

The inappropriate use of features intended to improve usability and interactivity of web applications has resulted in the emergence of various threats, including Cross-Site Scripting(XSS) attacks. In this work, we developed ETSS Detector, a generic and modular web vulnerability scanner that automatically analyzes web applications to find XSS vulnerabilities. ETSS Detector is able to identify and analyze all data entry points of the application and generate specific code injection tests for each one. The results shows that the correct filling of the input fields with only valid information ensures a better effectiveness of the tests, increasing the detection rate of XSS attacks.
Network Intrusion Detection and its strategic importance

In computer network security, a Network Intrusion Detection (NID) is an Intrusion Detection mechanism that attempts to discover unauthorized access to a computer network by analyzing traffic on the network for signs of malicious activity. There are many areas of research in this vast field of Network Intrusion Detection (NID) but in this survey paper, we will focus on its technology, development & strategic importance. Virus attacks, unauthorized access, theft of information and denial-of-service attacks were the greatest contributors to computer crime, a number of techniques have been developed in the past few years to help cyber security experts in strengthening the security of a single host or the whole computer network. Intrusion Detection is important for both Military as well as commercial sectors for the sack of their Information Security, which is the most important topic of research for the future networks.
Parkinson-Like Neurodegeneration Induced by Targeted Overexpression of α-Synuclein in the Nigrostriatal System

Recombinant adeno-associated viral vectors display efficient tropism for transduction of the dopamine neurons of the substantia nigra. Taking advantage of this unique property of recombinant adeno-associated viral vectors, we expressed wild-type and A53T mutated human α-synuclein in the nigrostriatal dopamine neurons of adult rats for up to 6 months. Cellular and axonal pathology, including α-synuclein-positive cytoplasmic inclusions and swollen, dystrophic neurites similar to those seen in brains from patients with Parkinson's disease, developed progressively over time. These pathological alterations occurred preferentially in the nigral dopamine neurons and were not observed in other nondopaminergic neurons transduced by the same vectors. The degenerative changes were accompanied by a loss of 30–80% of the nigral dopamine neurons, a 40–50% reduction of striatal dopamine, and tyrosine hydroxylase levels that was fully developed by 8 weeks. Significant motor impairment developed in those animals in which dopamine neuron cell loss exceeded a critical threshold of 50–60%. At 6 months, signs of cell body and axonal pathology had subsided, suggesting that the surviving neurons had recovered from the initial insult, despite the fact that α-synuclein expression was maintained at a high level. These results show that nigral dopamine neurons are selectively vulnerable to high levels of either wild-type or mutant α-synuclein, pointing to a key role for α-synuclein in the pathogenesis of Parkinson's disease. Targeted overexpression of α-synuclein in the nigrostriatal system may provide a new animal model of Parkinson's disease that reproduces some of the cardinal pathological, neurochemical, and behavioral features of the human disease.
A Two-Day Continuous Nicotine Infusion Is Sufficient to Demonstrate Nicotine Withdrawal in Rats as Measured Using Intracranial Self-Stimulation

Avoidance of the negative affective (emotional) symptoms of nicotine withdrawal (e.g., anhedonia, anxiety) contributes to tobacco addiction. Establishing the minimal nicotine exposure conditions required to demonstrate negative affective withdrawal signs in animals, as well as understanding moderators of these conditions, could inform tobacco addiction-related research, treatment, and policy. The goal of this study was to determine the minimal duration of continuous nicotine infusion required to demonstrate nicotine withdrawal in rats as measured by elevations in intracranial self-stimulation (ICSS) thresholds (anhedonia-like behavior). Administration of the nicotinic acetylcholine receptor antagonist mecamylamine (3.0 mg/kg, s.c.) on alternate test days throughout the course of a 2-week continuous nicotine infusion (3.2 mg/kg/day via osmotic minipump) elicited elevations in ICSS thresholds beginning on the second day of infusion. Magnitude of antagonist-precipitated withdrawal did not change with further nicotine exposure and mecamylamine injections, and was similar to that observed in a positive control group receiving mecamylamine following a 14-day nicotine infusion. Expression of a significant withdrawal effect was delayed in nicotine-infused rats receiving mecamylamine on all test days rather than on alternate test days. In a separate study, rats exhibited a transient increase in ICSS thresholds following cessation of a 2-day continuous nicotine infusion (3.2 mg/kg/day). Magnitude of this spontaneous withdrawal effect was similar to that observed in rats receiving a 9-day nicotine infusion. Our findings demonstrate that rats exhibit antagonist-precipitated and spontaneous nicotine withdrawal following a 2-day continuous nicotine infusion, at least under the experimental conditions studied here. Magnitude of these effects were similar to those observed in traditional models involving more prolonged nicotine exposure. Further development of these models, including evaluation of more clinically relevant nicotine dosing regimens and other measures of nicotine withdrawal (e.g., anxiety-like behavior, somatic signs), may be useful for understanding the development of the nicotine withdrawal syndrome.
Vitamin D and Athletic Performance: The Potential Role of Muscle

Vitamin D deficiency is a worldwide epidemic, with well known impacts on calcium metabolism and bone health, but increasingly recognized associations with chronic health problems such as bowel and colonic cancer, arthritis, diabetes and cardiovascular disease. In recent years in the Sports Medicine literature, there has been an increased focus on the potential impact that inadequate Vitamin D levels may have on athletic performance. In the early 20th Century, athletes and coaches felt that ultraviolet rays had a positive impact on athletic performance, and while remaining limited, evidence is accumulating to support this view. Muscle structure and function is recognised to play a key role in athletic performance, and both cross-sectional and longitudinal studies allude to a functional role for Vitamin D in muscle. The identification of the Vitamin D receptor in muscle tissue provides a direct pathway for Vitamin D to impact upon Skeletal Muscle structure and function. This review focuses on the current understanding of the action of Vitamin D within skeletal muscle tissue, and the potential impact on performance.
The l1 penalized decoder and its reweighted LP

Linear programming (LP) decoding for low density parity check (LDPC) codes proposed by Feldman et al. has attracted considerable attention in recent years. Despite having theoretical guarantees in some regimes, at low SNRs LP decoding is observed to have worse error performance than belief propagation (BP) decoding. In this paper, we present a novel decoding algorithm obtained by trying to solve a non-convex optimization problem using the alternating direction method of multipliers (ADMM). This non-convex problem is constructed by adding an ℓ1 penalty term to the LP decoding objective. The goal of the penalty term is to make “pseudocodewords”, which are the non-integer vertices of the LP relaxation to which the LP decoder fails, more costly. We name this the “ℓ1 penalized decoder”. We also develop a reweighted LP decoding algorithm base on this ℓ1 penalized objective. We show that this reweighted LP has an improved theoretical recovery threshold compared to the original LP. In addition, simulations show that, in comparison to LP decoding, these two decoders both achieve significantly lower error rates and are not observed to have an “error floor”. In particular, the ℓ1 penalized decoder meets or outperforms the BP decoder at all SNRs.
SentiSummary : Sentiment Summarization for User Product Reviews

This paper describes an approach to summarize and analyze user product reviews using summarization techniques found in multi-document summarization as well as sentiment analysis to extract opinions found in text. Previously, most research has focused on creating summaries for formal text such as The Wall Street Journal or other major news outlet. However, those same summarizers do not perform well on informal language such as blogs and user reviews. Our system uses sentiment analysis to analyze user product reviews for multiple products, identify and parse the positive and negative viewpoints across multiple reviews, summarize those viewpoints and display the aggregated information in a user friendly and useful manner.
Use of PSO for Obtaining Solution of the Inverse Robot Dynamic Model

The inverse dynamic model allows to compute the torques for each of the degrees of freedom of a robot knowing the positions, velocities and accelerations. In contrast, direct dynamic model is used to calculate the positions, velocities and accelerations knowing the torques for each of the degrees of freedom. Most of the times is dicult to obtain the direct dynamic model analytically because it is given by solution of the dierential equations for each variable. For that reason, we propose to compute the positions, velocities and accelerations from the inverse dynamic model using a simple and powerful intelligent algorithm called Particle Swarm Optimization (PSO) without needing to obtain the direct dynamic model.
Metabolic Responses to Exercise PHYSIOLOGICAL RESPONSES TO DOWNHILL WALKING IN OLDER AND YOUNGER INDIVIDUALS

PHYSIOLOGICAL RESPONSES TO DOWNHILL WALKING IN OLDER AND YOUNGER INDIVIDUALS. James W Navalta, Darlene A Sedlock, Kyung-Shin Park. JEPonline. 2004;7(6):45-51. The purpose of this study was to measure selected cardiovascular and metabolic responses in healthy older and younger individuals during downhill walking. Twenty subjects, ten older [age 64±3 yr (mean±SD)] and ten younger (age 23±3 yr) performed 6 min treadmill walking bouts at 80.4 m/min at grades of 5, 0, -5, -10, -15, and -20 %. Heart rate (HR), systolic (SBP) and diastolic (DBP) blood pressure, rate pressure product (RPP), oxygen uptake (VO2), pulmonary ventilation (VE), and rate of perceived exertion (RPE) were determined. Older subjects had significantly greater HR, SBP, RPP, DBP and RPE during uphill, level, and downhill walking compared to younger subjects. Older individuals exhibited similar VO2 and VE during downhill walking compared with younger subjects. There was a characteristic curvilinear response observed for HR, SBP, RPP, VO2, and VE with progressively steeper negative grades. These measures were highest at 5% grade and lowest between -5% and -10%. Downhill walking at grades between -5% and -10% reduced the cardiovascular and metabolic demand during exercise in older and younger subjects. Downhill walking is an activity that may be particularly beneficial for older individuals who are previously sedentary and at the beginning stages of an exercise training program.
Cyberbullying and Cyberthreats: Responding to the Challenge of Online Social Aggression, Threats, and Distress

Online communications can be cruel and vicious. They take place 24/7. Damaging text and images can be widely disseminated and impossible to fully remove. There are emerging reports of youth suicide, violence, and abduction related to cyberbullying and cyberthreats. In this book,the author provides school counselors, administrators, teachers and parents with cutting-edge information on how to prevent and respond to cyberbullying and cyberthreats. It covers challenging issues that occur as students embrace the Internet and other digital technologies such as: *Sending offensive, harassing messages *dissing someone or spreading nasty rumors online *Disclosing someone's intimate personal information *Breaking into someone's e-mail account and sending damaging messages under that person's name *Excluding someone from an online group *Using the Internet to intimidate The book includes detailed guidelines for managing in-school use of the Internet and personal devices, including cell phones. Appendices contain reproducible assessment and program forms, as well as parent and student handouts.
A visual attention based method for detecting traffic signs of interest

As an important component of the driver assistance system or autonomous vehicle, traffic sign detection can provide drivers or vehicles with safety and alert information about the road. Most existing methods for traffic sign detection only focus on one or several categories of signs while there are various signs in the real world. This paper proposes a biologically-inspired method for detecting almost all categories of traffic signs of interest. Based on the fact that traffic signs are designed to be salient such that they can stand out from its surroundings, this proposed method employs the bottom-up attention mechanism to select the salient objects in the image and the attentional selection is biases based on the top-down attention mechanism so as to filter out non-traffic-sign salient objects. Experimental results have shown that the proposed method is valid for detecting various types of traffic signs.
Verifying the 'consistency' of shading patterns and 3-D structures

The problem of interpreting images in terms of their shading and reflectance components has traditionally been addressed as an early vision task in a simple 2D Mondrian domain. Recently it has been appreciated that in a 3D world, such conventional approaches are inadequate; more sophisticated strategies are required. A key computation that needs to be performed for interpreting images acquired in a 3D domain is the verification of the consistency of image shading patterns and the likely 3D structure of the scene. This is the problem addressed in the paper. Considerations of robustness and generality have prompted the authors to discard available quantitative techniques in favor of a qualitative one. The two prime attributes of the technique are its use of qualitative comparisons of gray-levels instead of their precise absolute measurements and also its doing away with the need of an exact pre-specification of the surface reflectance function. This idea lends itself naturally to a linear-programming solution technique and that results obtained with some sample images are in conformity with human perception. <<ETX>>
Gene networks accelerate evolution by fitness landscape learning

We consider evolution of a large population, where fitness of each organism is defined by many phenotypical traits. These traits result from expression of many genes. We propose a new model of gene regulation, where gene expression is controlled by a gene network with a threshold mechanism and there is a feedback between that threshold and gene expression. We show that this regulation is very powerful: depending on parameters we can obtain any functional connection between thresholds and genes. Under general assumptions on fitness we prove that such model organisms are capable, to some extent, to recognize the fitness landscape. That fitness landscape learning sharply reduces the number of mutations necessary for adaptation and thus accelerates of evolution. Moreover, this learning increases phenotype robustness with respect to mutations. However, this acceleration leads to an additional risk since learning procedure can produce errors. Finally evolution acceleration reminds races on a rugged highway: when you speed up, you have more chances to crash. These results explain recent experimental data on anticipation of environment changes by some organisms.
Literature on exploration and exploitation 2

Organisational research has studied the tension between exploration and exploitation for years. In essence, this body of research agrees on the necessity of a balance between explorative and exploitative processes to prevent an organisation from falling into a learning trap. Thus, to enhance the active management of this balance in organisations, a deeper theoretical understanding of the factors that influence the development of exploration and exploitation has to be gained. One of the recently discussed factors is the interplay between exploration and exploitation on different organisational levels. This paper picks up this discussion. It provides an in-depth, computer simulation-based analysis of the performance of organisational types with varying degrees of within-group and between-group exploration and exploitation in situations of different degrees of task complexity. The findings indicate that a high share of betweengroup processes as compared to within-group processes positively influences the organisational performance level and that dependent on task complexity the optimal share of exploration and exploitation varies.