Miracle-dz/UniFAR-FTUs huggingface dataset:
CONSERVATION OF MEDICINAL PLANTS: A REVIEW

Ayurveda [traditional medicine of India as per WHO], the holistic science of medicine, as practised and utilized by Indians at large since centuries is now being globally accepted which has increased the demand for medicinal plants. Majority of population in the developing countries like India depends on the traditional systems of medicine like Ayurveda for their primary healthcare needs. Increasing demand of medicinal plants leads to irrational cutting deforestation leading to depletion of the wild resources. Moreover, the natural and manmade calamities lead to further depletion of medicinal plant diversity. Conservation aims at supporting sustainable development by wing the biological resources in ways that don’t deplete the world’s variety of species or destroy their ecosystems. It involves measures such as collection, propagation, evaluation, disease identification and elimination, storage and distribution. Conservation of medicinal plants and their genetic resources can be undertaken by in-situ and ex-situ conservation. Ex-situ conservation involves conservation of medium plants outside their natural habitat used to safeguard them from destruction, replacement or deterioration. Ex-situ conservation includes procedure like seed storage, DNA storage, field gene banks and botanical gardens etc
Trafﬁc Jam Direction Field Clustering

—Pollution and accidents are just some of the disas-trous consequences associated with vehicular congestion in large cities. With the help of crowdsourcing data, many countries are analyzing mobility alternatives based on the needs of citizens. Success stories have been documented in Social Network Analysis papers about massive information to support decision making. This article presents a cluster-based method to evaluate and displaying the direction ﬁeld of trafﬁc jams reports. The results show that the direction ﬁelds obtained from millions of user reports are adequate to display, in a summarized way, a lot of data in a simpler and a more informative manner.
Classification with Modified Deep Belief Network for Large Dataset

Due to the technology development, the data’s are increased in their volume, velocity and variety, referred to as large data or Big Data. From this large data, we can gain knowledge by using techniques like classification, association rule learning, outlier detection, clustering, and regression. By definition, classification canvass the specific set of data, procreate a set of grouping rules which can be used to codify the future data. The aim of classification is to meticulously forecast the target class for each case in the data. The classification stint starts with a dataset in which the class assignments are known. Available methods for classifications are support vector machines, quadratic classifiers, k-nearest neighbor, boosting, decision trees, neural network, learning vector quantization. From the above list, we use Neural Network for classification in this paper, Neural network is one of the most effective method for classification which are relatively rude electronic networks of neuron based on the neural structure of the brain. Neural network technique is either supervised or unsupervised. The supervised method contains algorithms like Back Propagation, Feed Forward, and so many. Deep neural network comprises more than one hidden layers which actually improves the accuracy in classification. The Deep belief network is an unsupervised learning. It includes more than one trained RBMs. In this paper we implemented novel Modified Deep Belief Network (MDBN) on four datasets namely SPECT, SPECTF, Pest formation in crops, readmission rate of diabetic patients in medical dataset. In all our works we gain high accuracy while comparing to the normal Deep Belief Network by introducing learning rate decay to the weight updating process.
Ionization and charge exchange rate coefficients for CTR calculations

: Microscopic collisional ionization and charge exchange cross sections for neutral, hydrogenic atoms in CTR plasmas are averaged over plasma phase-space distribution functions to obtain <av> rate coefficients. Prior calculations of this type were restricted to isotropic plasma dis tributions with injection at an energy near the mean plasma energy, however, in the present case, mirror loss-cone distributions are allowed. A discussion of methods and exemplary results in the energy range [0.1 300 keV] are presented.
Next Generation Very Large Array Memo No. 2 Calibration Strategies for the Next Generation VLA

Calibration will be a serious issue for the ngVLA. It must be considered early in the design, and consideration given to it throughout the process. I address here almost entirely phase calibration. Tying the flux scale to an absolute standard is beyond the scope of this memo. Previous experience at the VLA site has indicated clear paths for phase calibration at lower frequencies; the discussion below is therefore directed at calibration at 3mm wavelength. The several possible calibration strategies that have been suggested are discussed in the sections below. The objective of this memo is to set out the considerations of the various strategies and not to make a choice between them. Much of the discussion is independent of number or size of the antenna elements, but where it does enter, an array of 255 18m antennas is used.
Differential and experimental approaches to studying intelligence in humans and non-human animals

Why do some individuals learn more quickly than others, or perform better in complex cognitive tasks? In this article, we describe how differential and experimental research methods can be used to study intelligence in humans and non-human animals. More than one hundred years ago, Spearman (1904) discovered a general factor underpinning performance across cognitive domains in humans. Shortly thereafter, Thorndike (1935) discovered positive correlations between cognitive performance measures in the albino rat. Today, research continues to shed light on the underpinnings of the positive manifold observed among ability measures. In this review, we focus on the relationship between cognitive performance and attention control: the domain-general ability to maintain focus on task-relevant information while preventing attentional capture by task-irrelevant thoughts and events. Recent work from our lab has revealed that individual differences in attention control can largely explain the positive associations between broad cognitive abilities such as working memory capacity and fluid intelligence. In research on mice, attention control has been closely linked to a general ability factor reflecting route learning and problem solving. Taken together, both lines of research suggest that individual differences in attention control underpin performance in a variety of complex cognitive tasks, helping to explain why measures of cognitive ability correlate positively. Efforts to find confirmatory and disconfirmatory evidence across species stands to improve not only our understanding of attention control, but cognition in general.
Investigations on the mycoflora and processing effects on the nutritional quality of peanut (Arachis hypogea L. var. TS 32-1).

The microbiological and nutritional characterization of peanut (Arachis hypogea L var. TS 32-1) was investigated. Bacteria and fungi were isolated from this product. The fungal isolates were Aspergillus niger, Aspergillus flavus, Aspergillus parasiticus Speare, Aspergillus ochraceus Wilhelm and Fusarium poae. The respective mean moisture content and total acidity in samples were 8.19 ± 0.01% and 1.2 ± 0.02%. Nutritional analysis showed that peanut (Arachis hypogea L var. TS 32-1) has interesting nutritional potential. Carbohydrate content (7.84 ± 0.3%), protein content (33.88 ± 0.1%), fat (47.48 ± 0.01%) and the presence of minerals such as calcium (0.25 ± 0.05g/kg), potassium (5.21 ± 0.02g/kg) and magnesium (1.92 ± 0.03%) allowed its application as supplement in infant feeding in rural areas. Anti-nutritional factors such as oxalate and phytate were also detected in samples. This nutritional potential is significantly affect by thermal processes which can reduce essentially protein and carbohydrate contents and also anti-nutritional factor levels. However, values were lower than established toxic level. Finally, more attention should be made to its microbial quality in order to preserve children’s health.
First survey of cultivable bacteria from Rhipicephalus sanguineus sensu lato and assessment of the antagonism against five microorganisms of clinical importance

ABSTRACT Rhipicephalus sanguineus sensu lato (s.l.) is the most widespread tick in the world and is a well-recognized vector of many pathogens that affect dogs and, occasionally, humans. There is scarce information regarding bacterial endosymbionts with antagonistic activity against microorganisms of public health importance. The goal of this work was to analyse the internal cultivable microbiota associated with brown dog ticks and to assess the inhibitory activity of these microorganisms against five common clinical pathogens: Escherichia coli, Bacillus cereus, Salmonella enteritidis, Listeria monocytogenes, and Staphylococcus aureus. Seventy ticks were analysed from four sampling sites located in Nuevo León, Mexico. Bacteria were isolated and identified via the amplification and sequencing of a region of the 16S rDNA gene fragment. DNA sequence BLAST analyses grouped all the isolates into 14 strains, which belonged to 11 different species: Oceanobacillus iheyensis, Staphylococcus epidermidis, Staphylococcus saccharolyticus, Staphylococcus cohnii, Jeotgalicoccus halotolerans, Bacillus clausii, Bacillus megaterium, Serratia marcescens, Pseudomonas stutzeri, Acinetobacter lwoffii, and Micrococcus luteus. Two isolated strains of B. clausii exhibited antagonistic activity against gram-positive and gram-negative food-borne pathogens (Bacillus cereus, Listeria monocytogenes, and Staphylococcus aureus). To our knowledge, this is the first study to describe the inner cultivable microbiota of R. sanguineus s.l.
Apprendre avec les diaporamas en langue seconde

L'usage des diaporamas, comme supports de cours et accompagnement d'un discours oral, s'est largement banalise dans l'enseignement superieur mais peu d'etudes ont ete consacrees quant a leur reelle efficacite notamment lorsqu'on prend en compte a la fois le niveau d'expertise des apprenants dans le domaine etudie mais egalement le niveau atteint dans la langue utilisee dans le document projete et commente oralement. Dans la plupart des modeles multimedia, on suppose que le public domine en principe la langue de la presentation audiovisuelle, ce qui n'est pas toujours le cas dans notre environnement universitaire multilingue ou de nombreux etudiants doivent suivre des cours dans une autre langue que leur langue native. Les travaux que nous presenterons ici se basent sur la theorie de l'apprentissage multimedia (Mayer, 2014) et sur les recherches qui mettent en avant le role des langues dans la comprehension des differents medias. Nous reconsidererons les principes evoques par Mayer (2014) lorsque le public cible ne maitrise pas completement la langue de communication ou d'enseignement et doit donc disposer d'aide specifique pour comprendre et acceder facilement aux informations essentielles. Les principes multimedia qui sont censes favoriser l'apprentissage et les effets attendus lies au format de presentation (texte, diaporama et video) sont non seulement dependants du niveau d'expertise du public vise, de ses competences en langue mais egalement de facteurs plus generaux d'ordre cognitif ou affectif (motivation, attention, perception, concentration, stress, anxiete, manque de confiance). Pris dans leur ensemble, ces elements peuvent conditionner la transmission des informations (contenu) et egalement ameliorer le niveau de maitrise dans la langue enseignee ou au contraire l'alterer en provoquant un phenomene de surcharge (redondance inutile, informations trop nombreuses ou mal disposees, rythme de defilement trop eleve…). Nous evoquerons quelques propositions qui permettent de moduler et d'optimiser les presentations audiovisuelles dans la perspective de reduire la charge cognitive liee aux enseignements et augmenter leur attractivite par l'utilisation des supports multimedia sur la base d'une experience recente realisee dans notre laboratoire (Mourey & Lavaur, 2015) ou les diaporamas sont compares avec d'autres supports d'information (texte, film) dans une situation de lecture/ comprehension en langue seconde.
Microcavités de silice : Excitation par fibre des modes de galerie et fonctionnalisation par des nanocristaux de silicium

Cette these exploite les modes de galerie de microcavites optiques, qui resultent d’un guidage par reflexion totale interne et possedent des facteurs de qualite tres eleves et de faibles volumes modaux. Ce memoire rappelle dans un premier temps la description theorique des modes des microspheres et des microtores de silice. Leur fabrication est ensuite presentee, en soulignant les ameliorations apportees au cours de la these, notamment la production de spheres de diametre inferieur a 20 µm, et l’amelioration de la symetrie des tores a l’aide d’une polarisation circulaire. Nous presentons une etude detaillee de leur excitation par un coupleur fibre en insistant sur le phenomene d’interference en ondes evanescentes qui se produit dans le gap. Ce phenomene est responsable des elargissements et deplacements des resonances dont je presente une etude poussee. Cette approche debouche sur une methode tres efficace de determination de l’ordre radial. Par ailleurs, on observe des formes de resonance inattendues, qui resultent d’interferences entre deux modes du coupleur dans une configuration analogue a l’interferometre de Mach-Zehnder. Nous abordons enfin la realisation de microsources fondees sur l’emission de nanocristaux de silicium (NC Si) dans ces cavites. Les emetteurs ont des tailles controlees allant de 0,6 a 6 nm. Le chauffage au laser CO2 active la photoluminescence des NC Si autour de 750 nm, puis induit leur destruction partielle par coalescence. Le facteur de remplissage optique et les defauts de la matrice apparaissent comme les principaux obstacles a une amelioration significative des performances. Il a ete possible de collecter l’emission de NC Si couples a des microtores, en champs proche et lointain.
Hilbert-Envelope Features for Cardiac Disease Classification from Noisy Phonocardiograms

Cardiovascular disease (CVD) is considered a significant public health concern around the world. Automated early diagnostic tools for CVDs can provide substantial benefits, especially in low-resource countries. In this study, we propose a time-domain Hilbert envelope feature (HEF) extraction scheme that can effectively distinguish among different cardiac anomalies from heart sounds even in highly noisy recordings. The method is motivated by how a cardiologist listens to the heart murmur configuration, e.g., the intensity of the heart sound envelope over a cardiac cycle. The proposed feature is invariant to the heart rate, the position of the first and second heart sounds, and robust in extracting the murmur configuration pattern in the presence of respiratory noise. Experimental evaluations are performed compared to two different state-of-the-art methods in the presence of respiratory noise with signal-to-noise ratio (SNR) values ranging from 0-15dB. The proposed HEF, fused with standard acoustic and Resnet features, yields an average accuracy, sensitivity, specificity, and F1-score of, 94.78%(+/- 2.63), 87.48%(+/- 6.07), 96.87%(+/- 1.51), and 87.47%(+/- 5.94), respectively, while using a random forest (RF) classifier. Compared to the best- performing baseline model, this feature-fusion scheme provides a significant performance improvement (p < 0.05), notably achieving an absolute improvement of 6.16% in averaged sensitivity. In the case of 0dB SNR, the proposed feature alone provides a 9.2% absolute improvement in sensitivity compared to the top baseline system demonstrating the robustness of the HEF. The developed methods can significantly impact computer-aided auscultation (CAA) systems when deployed in noisy conditions, especially in low-resource settings.
Maternal perception of child weight and concern about child overweight mediates the relationship between child weight and non-responsive feeding practices

We aimed to examine the mediating effects of maternal perception of child weight (weight perception) and concern about overweight (weight concern) on the paths between child weight and non-responsive feeding practices. We recruited a convenience sample of 1164 mothers who were primary caregivers of preschool children. Child body mass index (BMI) Z-score was calculated to assess child weight. The Chinese version of the Child Feeding Questionnaire (C-CFQ) was used to measure four common non-responsive feeding practices, weight perception and weight concern. Structural equation modeling (SEM) was used to examine the associations between child BMI Z-scores, maternal feeding practices, and other covariates. Sixty percent of the mothers perceived their overweight/obese children as normal weight or even underweight. The disagreement between actual child weight and maternal weight perception was statistically significant (Kappa = 0.212, P < 0.001). SEM indicated that weight perception fully mediated the relationship between child BMI Z-scores and pressure to eat. Weight concern fully mediated the relationships between child BMI Z-scores and the other three feeding practices. The serial mediating effects of weight perception and concern were statistically significant for the paths between child BMI Z-score and monitoring ({beta} = 0.035, P < 0.001), restriction ({beta} = 0.022, P < 0.001), and food as a reward ({beta} = -0.017, P < 0.05).
Compendium of organic synthetic methods

Preface vii Introduction ix Index, Monofunctional Compounds xvii Index, Difunctional Compounds xix Abbreviations xxi About the Author xxv 1 Preparation of Alkynes 1 2 Preparation of Acid Derivatives 13 3 Preparation of Acohols 21 4 Preparation of Aldehydes 75 5 Preparation of Alkyls, Methylenes, and Arkyls 89 6 Preparation of Amides 225 7 Preparation of Amines 259 8 Preparation of Esters 303 9 Preparation of Ethers, Epoxides, and Thioethers 325 10 Preparation of Halides and Sulfonates 351 11 Preparation of Hydrides 365 12 Preparation of Ketones 371 13 Preparation of Nitriles 399 14 Preparation of Alkenes 409 15 Preparation of Oxides 433 16 Preparation of Difunctional Compounds 445 Author Index 629
Valuation system connectivity is correlated with poly-drug use in young adults

Poly-drug consumption is a dangerous, yet complex model of substance use that contributes to many cases of imprisonment and fatal overdose. Despite the growing number of studies looking at this phenomenon, there remains a lack of neuroimaging data elucidating the neural markers of poly-drug use. In particular, the valuation system, tasked with weighing the value of items and experiences, may hold significance in understanding the motivations behind poly-drug use. To this end, we sought to analyze the functional connectivity of the Valuation System (VS), Executive Control System (ECS) and Valuation-Control Complex (VCC) of drug-using participants in the Human Connectome Project Healthy Young Adult dataset (n=992). Using multivariate regression, network-averaged connectivities were correlated with various substance use measures (stimulants, cocaine, hallucinogens, opiates, sedatives and marijuana) and demographic variables (gender, parental use history). We found that the VS, ECS and VCC were all correlated with drug use behaviour either as individual systems or when paired with other substances. Both VS (R2= 0.53) and ECS (R2= 0.55) connectivity are positively correlated with stimulant use whereas both ECS (R2= 0.45) and VCC (R2= 0.045) connectivity are negatively correlated with marijuana use. VS (R2= 0.75) and VCC (R2= 0.74) connectivities are also negatively correlated with sedative use. Additionally, network connectivity was correlated with drug use behaviour via two-way interactions with other substances. These findings provide preliminary indications of the consequences of poly-drug use in healthy young adults.
Detection of transmission change points during unlock-3 and unlock-4 measures controlling COVID-19 in India

Documentation in scientific literature is not available on prospective evaluation of the efficiency of the unlock measure related to COVID-19 transmission change points in India, projecting the infected population, planning suitable measures related to future interventions and lifting of restrictions so that the economic settings are not damaged beyond repair. We have applied SIR model and Bayesian approach combined with Monte Carlo Markov algorithms on the Indian COVID-19 daily new infected cases from 1 August 2020 to 30 September 2020. We showed that the COVID-19 epidemic declined after implementing unlock-4 measure and the identified change-points were consistent with the timelines of announced unlock-3 and unlock-4 measure, on 1 August 2020 and 1 September 2020, respectively, effectiveness of which were quantified as the change in both effective transmission rates (100% reduction) and the basic reproduction number attaining 1, implying measures taken to control and mitigate the COVID-19 epidemic in India managed to flatten and recede the epidemic curve.
Calibration of vision system used on Unmanned Surface Vehicle

Vision system is the important equipment for Unmanned Surface Vehicle (USV) to find obstacles and monitor surrounding environment. There are popular calibration methods for vision system used indoor and outdoor on land. However, the USV has to be transported, hoisted and deployed, and calibrated parameters may be changed in the process. Consequently, it is desired to calibrate the vision system in running environment. Due to limited deck area, rock of the USV itself caused by wave, and wind, it is inconvenient to apply the typical calibration methods to USV. In this paper, we propose a method to calibrate the vision system automatically, using a calibration object made with a planar pattern attached to a cylinder. Experiments from simulated data and real images show that the calibration method applicable to USV and other unmanned system.
Development of an AUV “Xuanwu-1” with docking function

Ocean has always intrigued mankind. Presently, ocean inspection, monitoring and exploitation has been achieved with the development of ocean technology. The seafloor observatory network, a mature and all-weather fixed observatory platform, makes it possible to monitor ocean environment in long term and in real time, while its range of observation is limited by cable. A compact Autonomous Underwater Vehicle (AUV) namely "Xuanwu-1" was designed for mobile observatory, which can charge and transfer data by non-contract power supply and data transfer system via docking station, setting up at the Zhejiang University seafloor observatory node. The combination of the two improves the underwater continuous operation time and data transmission efficiency of a typical AUV. This paper uncovers and introduces solutions for the design and implementation of "Xuanwu-1" under limited conditions. One major effort is the overall design of this AUV, including mechanical design and control system design. Through the use of mathematical modeling and simulation, "Xuanwu-1" realized several typical motions under ideal conditions. The implementation of this AUV is time-consuming and finally it was tested under lab conditions. As the first generation of "Xuanwu" series, this open-frame compact AUV is used for oceanographic surveys from close to the surface of the sea. In the near future, this AUV can dock with the integrated docking system and to be the complement of cabled seafloor observatory network. With time, the AUV design will have to change in order to optimize its performance as the engineering technology progress.