Miracle-dz/UniFAR-FTUs huggingface dataset:
Learning from Multiple Demonstrations with Different Modes of Operations

In this paper, teaching multiple types of complex trajectories at once to a robot in a robust, easy to train model using Learning from Demonstration is studied where the robot is expected to gain the capacity to differentiate between different types of demonstrated trajectories and be able to reproduce these trajectories correctly. Demonstrated trajectories are used to train a Hidden Markov Model (HMM) and a modified version of Gaussian Mixture Regression (GMR) -which utilizes state transition probabilities between states of the HMM, the most probable state the end effector of the robot belongs to in the current reproduction of the trajectory, and previous points in the current reproduction of the trajectory- is used to estimate the trajectory iteratively. A Proportional Derivative (PD) controller is employed for the reproduction. Starting points that are intended to correspond to different types of trajectories which the robot is expected to differentiate between are tested on numerical and simulation experiments. Multiple numerical experiments and simulation experiments showed that our modified algorithm produced comparable results to previous work, and in certain complex trajectories our algorithm was successful where previous work has failed to produce expected results.
A Comparative Analysis of Ensemble Classifiers for Text Categorization

Text Categorization has attracted the attention of the research community in the last decade. Algorithms like Support Vector Machines, Naïve Bayes, Genetic Algorithm have been used with good performance, confirmed by several comparative studies. Recently, ensemble-based classifiers have gained popularity in this domain. In this research work, efficient ensemble methods are addressed for developing accurate classifiers for usenet2 dataset. The proposed approach employs Naïve Bayes (NB), Support Vector Machine (SVM) and Genetic Algorithm (GA) as base classifiers along with different ensemble methods. The experimental results show that the ensemble classifiers were performing with accuracy greater than individual classifiers, and also hybrid model results are found to be better than the combined models for the usenet2 dataset. The proposed ensemble-based classifiers turn out to be good in terms of classification accuracy, which is considered to be an important criterion to develop ensemble classifiers for text categorization.
Rule Based Text Summarization for Marathi Text

Text summarization is process of selecting important information of source document or data and produce short summary. Manually summarize large document is very difficult. Summarization has been done in various Indian regional languages. But, not much work has been done for Marathi language. The present research paper, represent Marathi text summarization with rule based approach using question generation system. The rule based approach of abstractive text summarization is used for generate question on Marathi text for this Rule based POS tagger, Named Entity Recognition and Rule based stemmer techniques are applied for generate the question. After generating questions, question are classify and then questions are rank the according to frequency or noun priority and answer of the higher ranked and noun priority group together is summary of given input.
Propriétés immuno-modulatrices de la flagelline de Salmonella typhimurium : impact sur la défense anti-bactérienne et le développement d'adjuvants épithéliaux

Le systeme immunitaire des mammiferes possede deux composantes, l'immunite innee, premiere ligne de defense de l'hote, et l'immunite adaptative, phase plus tardive et specifique a de multiples antigenes. Dans le contexte infectieux, toute reponse immunitaire commence par la detection du pathogene par des recepteurs de l'immunite innee comme les "Toll-Like Receptors" ou TLR qui reconnaissent des motifs moleculaires conserves chez de nombreux microorganismes. Au cours de ce travail, j'ai etudie un motif microbien en particulier, la flagelline de Salmonella typhimurium, molecule structurale du flagelle et agoniste de TLR5. Les muqueuses respiratoires, digestives ou urogenitales sont donc des sites majeurs d'immunite anti-microbienne car la plupart des pathogenes les ciblent et les colonisent. Mon travail a consiste a dissequer les reponses immunitaires muqueuses induites par la signalisation TLR5 dans deux modeles experimentaux : (1) une administration locale de la flagelline mimant la colonisation microbienne epitheliale et (2) une administration systemique simulant l'invasion d'un pathogene dans les tissus muqueux. L'instillation de flagelline par voie respiratoire active l'epithelium broncho-alveolaire. Nos travaux ont montre que la signalisation epitheliale peut avoir un effet therapeutique par le recrutement de neutrophiles. La contribution de l'epithelium dans l'immunite adaptative muqueuse a ete analysee. Lors d'une instillation nasale de flagelline, les animaux developpent une reponse en anticorps et une reponse Th1-Th2 a la fois locale et systemique. Nos resultats indiquent que la signalisation TLR dans les cellules epitheliales du poumon est necessaire et suffisante pour promouvoir cette immunite. Ces observations ouvrent de nouvelles perspectives pour le developpement d'adjuvant muqueux a activite epitheliale et la caracterisation des interactions hote-pathogene. L'administration systemique de flagelline induit dans l'intestin et les poumons la transcription immediate mais transitoire des genes codant les interleukines IL-17A, IL-17F et IL-22, cytokines essentielles a l'elaboration d'une defense anti-microbienne muqueuse. Nous avons identifie comme source de ces cytokines, une nouvelle population de cellules lymphoides innees CD3negCD127+. Leur activation est associee a la protection contre une infection orale a Yersinia pseudotuberculosis. Nos donnees suggerent donc que les cellules CD3negCD127+ sont cruciales pour les defenses precoces contre l'invasion des tissus muqueux par les pathogenes et leur manipulation pourrait etre envisagees a des fins therapeutiques.
Improving metabolic control in humans by intranasal neuropeptide administration

The prevalence of obesity, defined as a body mass index (BMI)> 30, has been rising on a worldwide scale over recent decades. Obesity and the metabolic syndrome are associated with health impairments, e.g., insulin resistance and hypothalamic-pituitary-adrenal (HPA) axis hyperactivity, as well as reduced quality of life. Therefore, the physiological systems that regulate energy intake and body weight are of great interest not only to basic research but also as possible targets of interventions to improve metabolic control. Several endogenous neuropeptides released in association with metabolic function have been investigated for their potential to block orexigenic (appetite-stimulating) and to promote anorexigenic (appetite-suppressing) signaling cascades in the brain as well as for their insulin-sensitizing and stress-regulating properties. The present thesis aims at characterizing the role of three of these neuropeptides, i.e., oxytocin, insulin, and orexin A, in the control of food intake, HPA axis activity, and, respectively, glucose metabolism in humans. For these investigations, the intranasal administration paradigm is the method of choice because it enables neuropeptides to bypass the blood-brain barrier and reach the central nervous system quickly, efficiently, and non-invasively while peripheral uptake is minimized. Three studies were performed in which we investigated the impact of oxytocin via the intranasal route (24 IU) on eating behavior and metabolic function in obese men (mean BMI of 32.10) in comparison to normal-weight men (mean BMI of 22.66; Study I), the influence of intranasal
Content-Based Image Retrieval Techniques: A Review

Present-day, medicinal and healthcare industry needs a direct attention in the care of human organs and disease objects. They are extensively used for the analysis, treatment, and spotting of the disease. The retrieval of the appropriate images from the database is very difficult if the volume of the image database has increased. By means of this, Content-Based Image Retrieval (CBIR) acquired animmense deliberation to excerpt the pertinent information from the large image archive. It contains two activities, extracting the features and measuring the similarity. Based on these, many CBIR systems are proposed. This paper provides the exhaustive study of the recent CBIR which is used to design a mechanism for image retrieval to get better retrieval results with lesser computational complexity.
Full-Duplex Jamming and Interception Analysis of UAV-Based Intrusion Links

This letter addresses the evaluation of the performance of a full-duplex (FD) jammer and intercepting node, where the FD node attempts to disrupt the communication link of an intruding unmanned aerial vehicle (UAV). The FD node’s performance is evaluated by deriving an analytical expression of the probability of successfully interrupting the communication link between the UAV node and its control source (CS). Moreover, the analysis takes into account the channel characteristics between the interacting nodes. Simulations were conducted to examine the dynamics of the proposed system model by varying different key parameters. The conducted simulations verify the accuracy of our derived expressions, and the results highlight the importance of having low residual self-interference power in order to successfully intercept the communication link between the UAV node and its control source.
Burden of caregiving, social support and quality of life of informal caregivers of patients with cerebral palsy

The study investigated the burden of caregiving, social support and quality of life of informal caregivers of patients with CP. The study adopted a cross-sectional survey research design. A total of 78 informal caregivers participated in this study. The quality of life was assessed using the World Health Organization Quality of Life Bref (WHOQOL-Bref). Also, social support was assessed using Multidimensional Scale of Perceived Social Support (MSPSS). However, the level of burden of caring for CP patients on caregivers was estimated with the use of Caregivers Strain Index (CSI). The Spearman Rank Order Correlation test was used to test the correlation among the caregivers’ quality of life, social support, and burden and some patient and caregiver related variables. The statistical significance was accepted for a p value of <0.05. The outcome of this study showed that the degree of strain on the caregivers was significant, same as the impact on their quality of life. However, the caregivers’ level of strain has no significance on their level of perceived social support. Also, majority of the caregivers in this study experienced a considerable amount of burden and the level of perceived social support of caregivers was moderate. The caregivers also had a high quality of life in all domains. It was therefore concluded that caring for a child with CP had significant impact on the level of burden, social support and quality of life of informal caregivers. Also, the informal caregiver had a significant level of burden, a moderate of social support mainly from family and significant others and a high level of quality of life. It was thus recommended that study should be carried out to compare the level of burden, perceived social support and quality of life between informal caregivers of patients with CP and caregivers of healthy children.
Staphylococcus aureus : Production of Extracellular Compounds and Behavior in Foods - A Review.

Growth of Staphylococcus aureus is accompanied by production of such extracellular compounds as hemolysins, nuclease, coagulase, lipase, and enterotoxins. Enterotoxins that can cause food poisoning are produced by about one-third of the coagulase-positive strains of S. aureus . The enterotoxins are a heterogeneous group of heat-stable, water-soluble, single-chain globular proteins having a molecular weight between 28,000 and 35,000 daltons. Production of enterotoxin by appropriate strains of S. aureus is affected by the nutritional quality and pH of the substrate, temperature, atmosphere, sodium chloride (and hence water activity), other chemicals, and competing microorganisms. Outbreaks of staphylococcal food poisoning most often are associated with processed red meats, poultry products (especially chicken salad), sauces, dairy products (especially cheeses), and custard- or cream-filled bakery products. Ham and associated products often are involved in as many as 30% of outbreaks of staphylococcal food poisoning. Most outbreaks result from the combined effects of contamination of the food, often through unsanitary handling, with S. aureus and holding the food at the wrong temperature thus allowing growth and synthesis of enterotoxin by the pathogen.
A Teacher Proposed Heuristic for ICT Professional Teacher Development and Implementation in the South African Context

This qualitative interpretive exploratory case study investigated a sample of South African teachers’ perceptions of the requirements for successful implementation of Information and Communication Technology (ICT) Professional Teacher Development (PTD) within disadvantaged South African township schools in the Port Elizabeth district in South Africa. The participating teachers’ (n=30) perceptions and experience of ICT PTD were explored via qualitative semi-structured interviews, an open-ended questionnaire, internet user group responses, reflective journal writing and facilitator reflections. The findings indicate that they value three aspects, namely facilitator related aspects, training context aspects and school related aspects. These findings underpin the C 2 RHOAR 3 FS 2 R 2 framework offered as a heuristic for ICT related PTD and subsequent school and classroom implementation. The C 2 RHOAR 3 FS 2 R 2 acronym refers to Care, Competence, Relate, Hands-on, Ongoing, Assessment, Reflection, Read, Revise-replan, Feedback, Share, Support, Recognition and Resources. The expectations of the teachers resonate with international expectations of Professional Teacher Development and underscore the magnitude of the task for those who aspire to meet the challenge they present.
Oncocytic Variant of Medullary Thyroid Carcinoma - A Case Report

Medullary thyroid carcinoma (MTC) is a rare tumor arising from parafollicular C-cells. The oncocytic variant of MTC is an extremely rare diagnosis, with less than 20 cases reported. Here we present the case of a 36-year-old male patient with complaints of neck swelling and dysphagia. On fine needle aspiration cytology (FNAC), a Hürthle cell neoplasm was suggested. Finally with histopathology and immunohistochemistry (IHC), a diagnosis of MTC oncocytic variant was established. This tumor can be easily misdiagnosed for any thyroid Hürthle cell lesions. An accurate diagnosis is important because MTC has different treatment protocols, and its oncocytic variant is expected to be associated with poorer patient survival. Thus, the oncocytic variant of MTC is a difficult diagnosis on FNAC. Histopathology and rel- evant IHC markers are necessary for a correct diagnosis.
Creating an Ontology to Represent Qualitatively a Scene in a Virtual Reality Environment

Ontologies are widely used as a tool for representing knowledge in Artificial Intelligence more specifically in qualitatively knowledge representation and reasoning, for example, to represent concepts and their relationships. On the other hand, virtual reality has several applications in different fields: such as in medical systems, computer-aided design and education as a virtual learning environment. In both cases, qualitative representations are necessary to perform any qualitative reasoning task. In this paper, we see VRML and Java 3D. Which are formal languages are used to describe objects in 3D. We analyze the similarities between them to define an application ontology with the aim to represent virtual reality environments, independently of the programming language. Then a spatial ontology is defined to describe topological, directional and metric relation which can be used to describe the basic operations in a 3D scene to build a complex environment. Finally, these two ontologies are seen that can be constructed independently but integrated together whether needed.
Age Estimation Using Aging/Rejuvenation Features With Device-Edge Synergy

Estimating human age is a challenging task in computer vision and most researchers are trying to make age estimation via a static facial image. However, it ignores the fact that the age of a person is the specific representation of aging. In this paper, we attempt to explore the aging/rejuvenation (AR) characteristics of faces for age estimation and we called the whole network as AR-Net. Firstly, we use GAN model for learning a manifold of the aging/rejuvenation process to a face dataset with preserving personalized face features (e.g., gender, race). Secondly, we seek the correlated aging/rejuvenation characteristics from a narrow age interval, (e.g., ((0-100) $\rightarrow $ (0-5), (5-10),…, (90-100)). Thirdly, the fine-tuned GAN is used to generate aging/rejuvenation features of all age groups and these features are applied to train corresponding ELM regressors. AR-Net is deployed on every edge server, and all AR-Nets are trained offline. Afterwards, our AR-Net is constantly updated based on the face dataset collected by the edge sensors. Finally, enormous experiments on Morph-II, CACD, and captured facial dataset have been conducted to verify the performance of our fine-tuned AR-Net and the experimental results show that the approach enhanced than the current state of the art methods.
Denial of service

The contractor uses the client, the network, and the server to give a service to the customer. We put it this way to emphasise that the denial of service against which we seek to protect is the denial of service to the customer, not to the client. The attack may indeed consist of disabling or destroying the client, just as it may consist of interfering with the network or with the server. This paper does not consider issues of responsibility.
Wireless Recharging Sensor Networks Cross-Layer Optimization Based on Successive Interference Cancellation

SUMMARY In wireless sensor networks (WSN), communication interference and the energy limitation of sensor nodes seriously hamper the networkperformancesuchasthroughputandnetworklifetime. Inthispaper, we focus on the Successive Interference Cancellation (SIC) and Wireless Energy Transmission (WET) technology aiming to design a heuristic power controlalgorithmandaneﬃcientcross-layerstrategytorealizeconcurrency communicationandimprovethenetworkthroughput,channelutilizationra-tioandnetworklifetime.Werealizethatthechallengeofthisproblemis that joint consideration of communication interference and energy short-age makes the problem model more complicated. To solve the problem eﬃciently, we adopt link scheduling strategy, time-slice scheduling scheme and energy consumption optimization protocol to construct a cross-layer optimization problem, then use an approximate linearization method to transform it into a linear problem which yields identical optimal value and solve it to obtain the optimal work strategy of wireless charging equipment (WCE). SimulationresultsshowthatadoptingSICandWCEcangreatlyim-provecommunicationcapabilityandchannelutilizationratio,andincreasethroughputby200%to500%whileprolongingthenetworklifetime.
Studies on ion movement in malpighian tubules of Locusta migratoria L. with particular reference to electrical events

Intracellular microelectrodes have been used in conjunction with ion substitution, and agonists and inhibitors of known transport processes to investigate the mechanisms whereby ions cross the basal and apical cell membranes of the Malpighian tubules of Locusta. Values for basal, apical and transepithelial potentials in 'Normal' saline were -71.6 ± 0.3 mV, -82.6 ± 0.8 mV and +5.7 ± 1.0 mV (lumen positive) respectively. Ion substitution experiments, involving Na(^+),K(^+) and C1(^-) in the bathing media, indicated that the basal membrane was more permeable to K(^+) than Na(^+) and C1(^-). Two different electrical responses to high [K(^+)](_o) saline (the Type A and Type B response) were noted and these probably reflect distinct physiological states of basal membrane permeability. Experiments with ouabain and vanadate suggested that whilst Na(^+)+K(^+) ATPase activity, which has been demonstrated in microsomal preparations, was not significantly electrogenic, asymmetric ionic distribution across the basal membrane was partly maintained by thisenzyme Furthermore, 3-H ouabain-binding studies indicated that Na(^+)+K(^+) exchange 'pump' turnover was adequate to account for substantial entry and Na^ exit across the basal membrane. The electrochemicalgradient across the apical membrane suggests that exit from the cell must involve an active process with CI following passively. Data from ion substitution experiments and treatment with furosemide and bumetanide suggest that CI entry across the basalmembrane may be via cotransport with Na^ and/or K^. However, the+ —differential electrical responses to Na(^+) free and C1(^-) free salines question the role of Na(^+) in this process. The effects of c AMP, Ca(^2+) substitution and various inhibitors on basal and apical membrane potentials, taken in conjunction with the results referred to above, are discussed and a hypothetical model proposed whereby changes in intracellular Ca(^2+) and c AMP effect control of ion movements across the two cell surfaces.
Scalable Design and Dimensioning of Fog-Computing Infrastructure to Support Latency-Sensitive IoT Applications

The fog-computing paradigm has appeared as a geo distributed response to a growing focus on latency-sensitive Internet-of-Things (IoT) applications and the long delay that may be provided by cloud data centers. Although many researchers have investigated how IoT can interact with a fog, very few have tackled the question of how to construct a fog infrastructure for the expected IoT traffic. This article addresses the design and dimensioning of a fog infrastructure via a mixed-integer linear program (MILP) to construct a physical fog network design by mapping IoT virtual networks to dimensioned fog nodes. Due to the exponential nature of this MILP formulation, we also propose a column generation model with near-optimal results at a significantly reduced design and dimensioning cost. The numerical results show the viability of the column generation method in its proximity to the optimal solution and in its reasonable solution time.