Miracle-dz/UniFAR-FTUs huggingface dataset:
Synthèse et évaluation de modulateurs de la protéine CFTR

A la suite de la decouverte au laboratoire d'une nouvelle reaction entre le methylglyoxal et un α-aminoazaheterocycle, une nouvelle famille de modulateurs (famille I) de la proteine CFTR (Cystic Fibrosis Transmembrane conductance Regulator) a ete mise en evidence. Les dysfonctionnements de cette proteine, qui constitue un canal chlorure transmembranaire, sont responsables de plusieurs pathologies de la mucoviscidose resultant de mutations du gene correspondant. Nous avons tout d'abord cherche a confirmer la structure du pharmacophore suppose en selectionnant et evaluant des petites molecules contenant le pharmacophore ou en modifiant les groupements a proximite du pharmacophore. Cette etude a permis l'acces a de nouveaux composes issus de la reaction entre un autre α-oxoaldehyde (ethylglyoxal) et des α-aminoazaheterocycles et, a deux autres familles de composes derives de la premiere (familles II et III). Par ailleurs, en nous basant sur la structure des deux « chef de files », l'inhibiteur GPinh-5a et le potentiateur/activateur GPact-11a, nous avons developpe une pharmacomodulation de la structure de base des composes actifs qui sont des derives de purine. Un grand nombre d'analogues ont ainsi ete synthetises. Ces deux approches ont permis la mise en evidence de plusieurs nouveaux inhibiteurs et de deux nouveaux potentiateurs de la proteine CFTR. Au regard des caracteristiques et des proprietes des composes les plus actifs, leur etude biologique doit donc etre poursuivie dans le but d'aboutir a une utilisation therapeutique
Measuring Student Learning

Measuring student learning is critical in the teaching and learning processes and can serve many purposes. Instructors can use assessment results to plan future instruction, adapt current instruction, communicate levels of understanding to students, and examine the overall effectiveness of instruction and course design. The measurement of student learning can take place before, during, or after instruction. Before lessons are even developed, instructors need to know what students already know and can do related to the content. There is no point in wasting time teaching something students already know, or in starting at a level that is so advanced students don’t have the prerequisite knowledge necessary to be successful. To that end, the learner analysis in instructional design could be considered a type of assessment. Giving a pre-assessment, also called diagnostic assessment, can provide instructors with this valuable information. Measuring student learning during instruction, a formative assessment, provides instructors with important information about how students are progressing towards the learning objectives while there is still time to adjust instruction. Instructor may ask questions such as:
Fuzzy Detection Aided Real-Time and Robust Visual Tracking Under Complex Environments

Today, a new generation of artificial intelligence has brought several new research domains such as computer vision (CV). Thus, target tracking, the base of CV, has been a hotspot research domain. Correlation filter (CF)-based algorithm has been the basis of real-time tracking algorithms because of the high tracking efficiency. However, CF-based algorithms usually failed to track objects in complex environments. Therefore, this article proposes a fuzzy detection strategy to prejudge the tracking result. If the prejudge process determines that the tracking result is not good enough in the current frame, the stored target template is used for following tracking to avoid the template pollution. During testing on the OTB100 dataset, the experimental results show that the proposed auxiliary detection strategy improves the tracking robustness under complex environment by ensuring the tracking speed.
Review on the PV Hosting Capacity in Distribution Networks

The increasing penetration of Photovoltaic (PV) generation results in challenges regarding network operation, management and planning. Correspondingly, Distribution Network Operators (DNOs) are in the need of totally new understanding. The establishment of comprehensive standards for maximum PV integration into the network, without adversely impacting the normal operating conditions, is also needed. This review article provides an extensive review of the Hosting Capacity (HC) definitions based on different references and estimated HC with actual figures in different geographical areas and network conditions. Moreover, a comprehensive review of limiting factors and improvement methods for HC is presented along with voltage rise limits of different countries under PV integration. Peak load is the major reference used for HC definition and the prime limiting constraint for PV HC is the voltage violations. However, the varying definitions in different references lead to the conclusion that, neither the reference values nor the limiting factors are unique values and HC can alter depending on the reference, network conditions, topology, location, and PV deployment scenario.
Analysis and Prediction of New Media Information Dissemination of Police Microblog

: This paper aims to analyze the microblog data published by the official account in a certain province of China, and finds out the rule of Weibo that is easier to be forwarded in the new police media perspective. In this paper, a new topic-based model is proposed. Firstly, the LDA topic clustering algorithm is used to extract the topic categories with forwarding heat from the microblogs with high forwarding numbers, then the Naive Bayesian algorithm is used to topic categories. The sample data is processed to predict the type of microblog forwarding. In order to evaluate this method, a large number of microblog online data is used to analysis. The experimental results show that the proposed method can accurately predict the forwarding of Weibo. on this, we propose an experimental method to predict the forwarding behavior of Weibo. The method is based on the LDA model and is modeled using the Naïve Bayes algorithm for prediction. Experiments show that there are two popular forwarding themes in public security police microblog: social hotspot case notification and life safety. From the final recall and precision of the model, this experimental method has certain accurate prediction ability. Through the predictions of the model, the life warning class (preventing fraud, etc.) is the most popular type of microblog tweets that can be forwarded by users. It can be seen from the displayed topic category keywords that the user forwards relevant content before and after the college entrance examination.
Inflammatory patterns in fixed airflow obstruction are dependent on the presence of asthma

Rationale Fixed airflow obstruction (FAO) can complicate asthma. Inflammation is a proposed underlying mechanism. Objective Our aim in this cross-sectional investigation was to evaluate the blood leucocyte pattern and level of exhaled nitric oxide in asthmatics and non-asthmatics with or without FAO. Methods A total of 11,579 individuals aged ≥20 years from the US National Health and Nutrition Examination Survey were included. They were grouped as: controls without asthma and FAO (n = 9,935), asthmatics without FAO (n = 674), asthmatics with FAO (n = 180) and non-asthmatics with FAO (n = 790). FAO was defined as post-bronchodilator FEV1/FVC < lower limit of normal. Exhaled nitric oxide ≥ 25ppb, blood eosinophil levels ≥300 cells/μL, and blood neutrophil levels ≥5100 cells/μL were defined as elevated. Stratified analyses for smoking and smoking history were performed. Results Elevated blood eosinophil levels were more common in all groups compared to the controls, with the highest prevalence in the group with asthma and fixed airflow obstruction (p<0.01). In a multiple logistic regression model adjusted for potential confounders including smoking, the asthma groups had significantly higher odds ratios for elevated B-Eos levels compared to the control group (odds ratio 1.4, (confidence interval: 1.1–1.7) for the asthma group without fixed airflow obstruction and 2.5 (1.4–4.2) for the asthma group with fixed airflow obstruction). The group with fixed airflow obstruction without asthma had higher odds ratio for elevated blood neutrophil levels compared to the controls: 1.4 (1.1–1.8). Smoking and a history of smoking were associated to elevated B-Neu levels. Conclusion Fixed airflow obstruction in asthma was associated with elevated blood eosinophil levels, whereas fixed airflow obstruction without asthma was associated with elevated blood neutrophil levels.
PLANKTON IDENTIFICATION: MORPHOLOGY OR MOLECULES OR BOTH?

This article is an adaptation for the L&O Bulletin of a “Horizons” article that appeared recently in the Journal of Plankton Research in which a more technical discussion and complete bibliography can be found: McManus, G.B, Katz, L.A. 2009. Molecular and morphological methods for identifying plankton: what makes a successful marriage?
A Study on the Effect of Individual Characteristics on Acceptance Intention of Wearable Healthcare Devices: Focusing on the UTAUT2 and Innovativeness

The purpose of this study is to explain users’ wearable healthcare device adoption using performance expectancy, effort expectancy, facilitating condition, hedonic motivation and price value of UTAUT2, and to identify the causal relationship between intention to use wearable healthcare device and innovativeness. The research model proposed in this study is based on UTAUT2(Extended Unified Theory of Acceptance and Use of Technology). In specific, performance expectancy, effort expectancy, facilitating condition, hedonic motivation and price value of UTAUT2 and innovativeness are adopted in our research model. To validate the research model, we carry out the analysis of the survey data using Smart PLS 3.0 to test the hypotheses. According to the empirical analysis results, this study confirms that Innovativeness have significant effects on the performance expectancy, effort expectancy, Facilitating condition, Hedonic motivation, and price Value of wearable healthcare devices. It also finds that the performance expectancy, effort expectancy, Facilitating condition, hedonic motivation, and price value affects the intention to use wearable healthcare devices.
Integrating an Ensemble Surrogate Model’s Estimation into Test Data Generation

For the path coverage testing of a Message-Passing Interface (MPI) program, test data generation based on an evolutionary optimization algorithm (EOA) has been widely known. However, during the use of the above technique, it is necessary to evaluate the fitness of each evolutionary individual by executing the program, which is generally computationally expensive. In order to reduce the computational cost, this article proposes a method of integrating an ensemble surrogate model’s estimation into the process of generating test data. The proposed method first produces a number of test inputs using an EOA, and forms a training set together with their real fitness. Then, this article trains an ensemble surrogate model (ESM) based on the training set, which is employed to estimate the fitness of each individual. Finally, a small number of individuals with good estimations are selected to further execute the program, so as to have their real fitness for the subsequent evolution. This article applies the proposed method to seven benchmark MPI programs, which is compared with several state-of-the-art approaches. The experimental results show that the proposed method can generate test data with significantly low computational cost.
Correlation and path coefficient analysis between yield and its contributing traits in advance wheat (Triticum aestivum L. em. Thell) genotypes under late sown conditions

To study the correlation and path coefficient analysis between yield and its contributing traits, an experiment was carried out with 60 bread wheat genotypes under late sown conditions during Rabi 2017-18. Data of contrasting traits viz. days to 50 per cent heading, days to anthesis, canopy temperature at heading and after anthesis, grain growth rate 14, 21 and 28 days after anthesis, plant height, peduncle length, peduncle extrusion, number of effective tillers m-1, spike length, spikelet spike-1, no. of grains spike-1, 1000 grain weight, biological yield plot-1, harvest index and grain yield plot-1 were analysed. The results revealed that grain growth rate at 14 days after anthesis, effective tiller m-1, spike length, grains spike-1, biological yield plot-1, 1000 grain weight and harvest index were positive and significantly correlated with grain yield plot-1 with highest direct and positive effect on grain yield plot-1 via biological yield plot-1 followed by harvest index.
Equivalent DG Dimensions Concept for Compact Modeling of Short-Channel and Thin Body GAA MOSFETs Including Quantum Confinement

In this work, short-channel effects (SCEs) in cylindrical gate-all-around (GAA) MOSFETs with intrinsic or lightly doped channels are analytically described by using the conformal mapping technique for 2-D double-gate (DG) FETs. An equivalent capacitor model leads to an equivalent channel length concept, which allows to correctly determine the SCEs relevant center and surface potentials (<inline-formula> <tex-math notation="LaTeX">$\Phi _{{C}} $ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$\Phi _{{S}} $ </tex-math></inline-formula>) at the potential barrier. Furthermore, we make use of the rotational symmetry of GAA FETs and modify a compact drain current model of a DG device to use it for GAA transistors. Also, a mathematical correlation regarding quantum confinement for thin body transistors is derived, which shows that the mostly unwanted quantum effects occur in GAA structures already for thicker channels compared to DG transistors. Both transistor types experience a comparable influence with regard to quantization if the channel thickness of GAA FETs is 53% more than that of DG FETs. The dc behavior of our adapted model is verified with 3-D TCAD simulation data and applied to experimental data of ultrascaled silicon on insulator (SOI) omega-gate nanowire N-MOSFETs.
Clozapine prescribing patterns in hospitalised patients in everyday clinical practice

Aim: Clozapine is the gold standard for treatment-resistant schizophrenia. Despite clear recommendations for use, under-use and excessive delay in the use of clozapine are an ongoing findings in the literature. The aim of this study was to analyse the clozapine prescribing patterns in hospitalised patients in everyday clinical practice in Serbia. Methods: This cross-sectional study was conducted in Clinic for Mental Disorders “‘Dr Laza Lazarevic”’ in Belgrade and included a sample of 238 patients, discharged from hospital treatment during 2018. Demographic, data on the clinical characteristics of the subjects, dosage and combination of clozapine with other psychopharmacs were collected retrospectively, from the patients’ medical records. Descriptive and statistical hypothesis testing methods were used to analyse the primary data. Results: The incidence of clozapine administration was 23.5%. Clozapine was introduced into therapy after average treatment duration of 7.2 years and prior administration of three different antipsychotics. 68.1% of patients were treated with dual antipsychotic therapy prior to clozapine administration. In 53.8% of patients, clozapine was prescribed as antipsychotic monotherapy, while only eight per cent were not prescribed adjuvant therapy. The most commonly used antipsychotic in combination with clozapine was haloperidol (34.9%), while the most prescribed non-antipsychotic adjuvant drug was valproate (66%). Benzodiazepines were prescribed in 55.9% of subjects. In most subjects, the dose of clozapine was less than the standard dose. Conclusion: Clozapine is prescribed less frequently than expected and is often used in an irrational manner. Additional research is needed to advance its application in everyday clinical practice.
Effect of Ascorbate on Coagulation and Fibrinolytic Factors in the Septic Microvasculature

Sepsis, a systemic inflammatory response to an infection, is a significant cause of morbidity and mortality worldwide. The microcirculation during sepsis fails, in part, due to microthrombosis and the resulting plugging of capillaries, precipitating organ failure. Intravenous injection of ascorbate has been shown to reduce capillary plugging, however the mechanism of this protective effect is unclear. We hypothesized that ascorbatemediated destabilization of the microthrombi through promoting fibrinolysis could contribute to this protection. We showed that streptokinase, a pro-fibrinolytic agent, reduced the capillary plugging to a similar degree as ascorbate. This similarity provided the impetus for studying the effect of ascorbate on fibrinolysis. Sepsis increased the urokinase plasminogen activator (u-PA) and tissue plasminogen activator (t-PA) mRNA expression in the skeletal muscle and liver in mice. No effect of ascorbate was observed on u-PA or t-PA expression levels. Sepsis also increased the plasminogen activator inhibitor 1 (PAI1) mRNA and protein expression and activity in these tissues, but ascorbate did not affect these increases. The local PAI-1 release by both platelets and endothelial cells may play a critical role in microthrombus formation in capillaries. We observed that PAI-1 released by isolated endothelial cells was not affected by ascorbate. However, thrombin-induced PAI-1 release from platelets was inhibited by ascorbate pH-dependently. We have also discovered that the PAI-1 release from platelets was nitric oxide independent. It has been shown that PAI-1 has a protective role in sepsis, namely that PAI-1 knockout leads to increased bacterial content, increased neutrophil apoptosis and increased mortality. Therefore, the lack of effect of ascorbate on PAI-1 in the tissue may maintain PAI-1’s beneficial role in sepsis. Consistently, we observed that sepsis-induced increases in bacterial count, PAI-1 expression and myeloperoxidase content in various organs were not affected by ascorbate.
Robust Control of Synchronous Reluctance Motors by Means of Linear Matrix Inequalities

This article proposes an alternative for robust control of synchronous reluctance motors using linear matrix inequalities to obtain fixed gains that ensure current and speed regulation, under parameter uncertainties and variations. The proposed design procedure is based on a polytopic model, which takes into account: i) uncertainties and variations of the mechanical and electrical parameters of the motor, ii) one step delay from digital implementation of the control law, and iii) internal model based controllers to guarantee reference tracking. Less conservative linear matrix inequalities, relying on slack variables, ensure robust pole location and certify the closed-loop stability for the entire domain of uncertain and time-varying motor parameters, based on parameter-dependent Lyapunov functions. The linear matrix inequalities ensure a fast and systematic computation of the control gains, that are also easy to be implemented, not adding computational complexity when compared, for instance, to usual strategies based on PI controllers. Experimental results for a 2.2 kW commercial motor are provided, validating the proposed procedure, and illustrating good tracking of currents and speed references, with suitable dynamic responses and reduced cross-coupling effects, when compared to sliding mode and PI controllers.
A Workflow Scheduling Algorithm for Reducing Data Transfers in Cloud IaaS

The cloud IaaS easily offers to have homogeneous multi-core machines (whether they are "bare metal" machines or virtual machines). On each of these machines, there can be high-performance input-output SSD disks. That allows to distribute the files produced during the execution of the workflow to different machines in order to minimize the additional costs associated with transferring these files. In this paper, we propose a scheduling algorithm called WSRDT (Workflow Scheduling Reducing Data Transfers) whose purpose is to minimize the makespan (execution time) of data-intensive workflows by reducing transfers data between dependent tasks on the network. Intermediate files produced by tasks are stored locally on the disk of the machine where the tasks were executed. We experimentally verify that the increase in the number of cores per machine reduces the additional cost due to data transfers on the network. Experiences with a veritable workflow show those advantages of the algorithms presented. Data-driven scheduling significantly reduces the execution time and the volume of data transferred on the network, our approach outperforms one of the best state-of-the-art algorithms that we have adapted with our hypotheses.
aSNAQ: An adaptive stochastic Nesterov's accelerated quasi-Newton method for training RNNs

: Recurrent Neural Networks (RNNs) are powerful sequence models that are particularly diﬃcult to train. This paper proposes an adaptive stochastic Nesterov’s accelerated quasi-Newton (aSNAQ) method for training RNNs. Several algorithms have been proposed earlier for training RNNs. However, due to high computational complexity, very few methods use second-order curvature information despite its ability to improve convergence. The proposed method is an accelerated second-order method that attempts to incorporate curvature information while maintaining a low per iteration cost. Furthermore, direction normalization has been introduced to solve the vanishing and/or exploding gradient problem that is prominent in training RNNs. The performance of the proposed method is evaluated in Tensorﬂow on benchmark sequence modeling problems. The results show that the proposed aSNAQ method is eﬀective in training RNNs with a low per-iteration cost and improved performance compared to the second-order adaQN and ﬁrst-order Adagrad and Adam methods.
Output Homogenization and Synchronization of Heterogeneous Nonlinear Multiagent Networks

In this article, we are concerned with the output synchronization of a group of heterogeneous agents with nonlinear dynamics. It is shown that via dynamic coupling, the output synchronization problem is transformed into a family of output homogenization and internal-model-based synchronization problems. In contrast to conventional approaches, the adopted approach does not rely on the generation of a specific reference trajectory, to be tracked by all agents. Based on this premise, we propose a distributed state-feedback protocol driving all the heterogeneous multiagent individual systems onto a copy of a virtual reference signal. Invoking the results from the theory of output regulation and cooperative control, the state-feedback controller synthesis is conducted to achieve the output synchronization of heterogeneous multiagent networks. Immediate extensions of the obtained results to observer-based control are also discussed. The effectiveness of the proposed output synchronization algorithm is verified through theoretical analysis and case studies.