Miracle-dz/UniFAR-FTUs huggingface dataset:
A TÁBUA DE GALTON COMO FERRAMENTA DE ESTUDO DAS DISTRIBUIÇÕES BINOMIAL E NORMAL E DE SUA RELAÇÃO PELO TEOREMA CENTRAL DO LIMITE

As distribuicoes normal e binomial de probabilidades tem um papel central na modelagem de fenomenos de natureza estatistica cujas variaveis de interesse sao, respectivamente, discretas e continuas. Tomadas isoladamente, cada uma dessas distribuicoes em conjunto com suas propriedades produz incontaveis aplicacoes em diversas areas de conhecimento cientifico e tecnologico. Para alem disso, tais distribuicoes estao relacionadas atraves do Teorema Central do Limite, resultado fundamental da Teoria das Probabilidades. Neste contexto, o dispositivo desenvolvido pelo matematico ingles Francis Galton, conhecido como Tabua de Galton, produz um experimento probabilistico capaz de ilustrar o resultado contido no referido teorema e, mais do que isso, comparar os resultados do experimento com os modelos teoricos das distribuicoes normal e binomial. Dessa forma, este trabalho propoe um estudo teorico-pratico dos modelos probabilisticos binomial e normal e do Teorema Central do Limite, atraves de simulacoes experimentais probabilisticas realizadas em uma Tabua de Galton, projetada e construida durante a execucao do projeto. Procura-se ainda estabelecer em que medida o experimento proposto realiza de fato o papel a que se propoe ou, inversamente, em que medida o modelo teorico descreve o experimento. Finalmente, sao buscadas formas de refinamento do experimento em busca de uma aproximacao entre os aspectos citados.
Characterization of anthocyanin-containing colorants and fruit juices by HPLC/photodiode array detection

The anthocyanin pigment profiles of commercial black currant, blackberry, black raspberry, elderberry, cherry, plum, grape, bilberry, and red cabbage products were characterized by high-performance liquid chromatography (HPLC)/photodiode array detection. Removal of acylated anthocyanins by alkaline hydrolysis and selective removal of anthocyanins on a reversed-phase cartridge with borate buffer were auxiliary techniques that proved helpful in making peak assignments. Both the retention properties on reversed-phase HPLC and the spectral properties by photodiode array detection were used to characterize the anthocyanins. Other properties including tinctoral strength, total anthocyanin concentration, browning, titratable acidity, and Hunter tristimulus values were also determined for these colorants.
Nouvelle approche neuronale Faster R-CNN pour la recherche d’instances d’images

Les caracteristiques d'images derivees des reseaux neuronaux convolutifs (CNN) pre-entrenes sont devenues la norme dans les tâches de vision par ordinateur telle que la recuperation d'instances. Ce travail explore la pertinence de la recuperation de caracteristiques d'images et de regions a partir d'un CNN de detection d'objets tel que Faster R-CNN. Nous profitons des propositions d'objets appris par un RPN (Region Proposal Network) et de leurs caracteristiques associees prises d’un CNN pour construire un pipeline de recherche d'instances composees d’un filtrage puis d’un reclassement. Plus encore, nous etudions la pertinence des caracteristiques de Faster R-CNN lorsque le reseau est affine pour les memes objets que ceux qu’on veut recuperer. Nous evaluons la performance du systeme avec les deux datasets: Oxford Buildings 5k et Paris Buildings 6k. Les resultats obtenus par notre algorithme compare avec d’autres techniques sont encourageants.
Synthesis of a well-dispersed CaFe2O4/g-C3N4/CNT composite towards the degradation of toxic water pollutants under visible light

Herein, we fabricated a ternary photocatalyst composed of CaFe2O4, multiwalled carbon nanotubes (CNTs) and graphitic carbon nitride (g-C3N4) via a simple hydrothermal route. CaFe2O4 acted as a photosensitizer medium and the CNT acted as a co-catalyst, which remarkably enhanced the photocatalytic performances of g-C3N4 towards the degradation of hexavalent chromium (Cr(vi)) and the antibiotic tetracycline (TC) under visible light irradiation. To investigate the morphological and topological features of the photocatalyst, field-emission scanning electron microscopy (FE-SEM) and transmission electron microscopy (TEM) analyses were performed. The surface properties and oxidation state of the CaFe2O4/g-C3N4/CNT composite were determined by X-ray photoelectron spectroscopy (XPS). The recombination rate of the charge carriers and the band gap values of the as-synthesized catalysts were analyzed by photoluminescence spectroscopy (PL) and diffused reflectance spectroscopy (UV/Vis DRS) studies, respectively. Besides the degradation reactions, the high hydrogen production rate of 1050 μmol h−1 under visible light using the CaFe2O4/g-C3N4/CNT composite loaded with 5 wt% CNT was observed. The superior photocatalytic performances of the CaFe2O4/g-C3N4/CNT composite can be ascribed to the effective heterojunction formed between g-C3N4 and the CaFe2O4 matrix, in which the CNT act as a conducting bridge in the system, promoting the production of photoinduced charge carriers in the semiconductor system. Finally, the plausible photocatalytic mechanism towards the degradation of pollutants and hydrogen production was discussed carefully.
Assessing the state of knowledge of contemporary climate change and primates

In recent years, interest in understanding the effects of climate change on species and ecological systems has sharply increased. We quantify and contextualize the current state of knowledge about the effects of contemporary climate change on non‐human primates, a taxon of great ecological and anthropological significance. Specifically, we report findings from a systematic literature search designed to assess the allocation of research effort on primates and climate change and consider how the current distribution of knowledge may be influencing our understanding of the topic. We reveal significant phylogenetic and geographic gaps in our knowledge, which is strongly biased towards lemurs, apes, and a relatively small subset of primate range countries. We show that few analyses investigate changes in primate foods relative to changes in primates themselves or their habitats, and observe that few longitudinal datasets are of sufficient duration to detect effects on the generational scale. We end by identifying areas of research inquiry that would advance our theoretical understanding of primate ecology, evolution, and adaptability, and meaningfully contribute to primate conservation.
Agrarian Relations, Landlessness and Inequality: Case Study of Irrigated and Unirrigated Regions of Undivided Kalahandi

In rural areas, agriculture is the primary source of income, and the income depends on the primary factor of production, land. The higher the productivity of the land, the higher the income and general prosperity and lower the levels of poverty. However, it may not always be true if the benefit from the higher productivity accrues to a certain section of large farmers, bypassing the small ones. The study found that, the introduction of irrigation in a poverty-stricken region has promoted advanced capitalist farming and raised the level of output per unit of land. On the other hand, it has led to greater landlessness and inequality among various farm size groups. The benefit is concentrated among few farmers. In this process, there is greater ‘proletarianisation’, which needs to be stopped from worsening the situation further.
Smoking, Vaping, and the Benefits Cessation in Times of COVID-19: A Public Health Perspective

The goal of this article is to inform dental practitioners and specialists of the benefits of smoking and vaping cessation in relation to COVID-19 transmission. COVID-19 caused by the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) has affected more than 31.7 million people globally with infection rates continuing to rise rapidly. Smoking dramatically impairs lung function and gives rise to an increase in susceptibility for infection, allowing for a more difficult recovery due, in part, to the damage SARS-CoV-2 does to the lungs. Tobacco smoking is one of the primary causes of death in the United States (US), however, nearly 40 million adults still smoke cigarettes, with 4.7 million middle and high school students using at least one tobacco product, including electronic cigarettes. COVID-19 is transmitted through salivary droplets, causing severe bilateral pneumonia and significantly reduced lung function, putting smokers and vapers at greater risk through cross-contamination and face touching. So far, data from animal studies suggest that vaping leads to an increased susceptibility to infection, which coincides with evidence of increased rates of chronic bronchitis in vapers. There is yet to be data regarding the benefits of smoking and vaping cessation during the COVID-19 pandemic. However, there is evidence suggesting that 4 weeks or more of smoking cessation intervention reduces the risk of contracting COVID-19 and developing severe complications. Because of these probable connections, dental practitioners should advise their patients to stop smoking and/or vaping via the 5 As Cessation Strategy.
Current Preventions and Treatments of aGVHD: From Pharmacological Prophylaxis to Innovative Therapies

Graft versus host disease (GVHD) is one of the main causes of mortality and the reason for up to 50% of morbidity after hematopoietic stem cell transplantations (HSCT) which is the treatment of choice for many blood malignancies. Thanks to years of research and exploration, we have acquired a profound understanding of the pathophysiology and immunopathology of these disorders. This led to the proposition and development of many therapeutic approaches during the last decades, some of them with very promising results. In this review, we have focused on the recent GVHD treatments from classical chemical and pharmacological prophylaxis to more innovative treatments including gene therapy and cell therapy, most commonly based on the application of a variety of immunomodulatory cells. Furthermore, we have discussed the advantages and potentials of cell-free therapy as a newly emerging approach to treat GVHD. Among them, we have particularly focused on the implication of the TNFα-TNFR2 axis as a new immune checkpoint signaling pathway controlling different aspects of many immunoregulatory cells.
Structural Characterization of SARS-CoV-2: Where We Are, and Where We Need to Be

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has rapidly spread in humans in almost every country, causing the disease COVID-19. Since the start of the COVID-19 pandemic, research efforts have been strongly directed towards obtaining a full understanding of the biology of the viral infection, in order to develop a vaccine and therapeutic approaches. In particular, structural studies have allowed to comprehend the molecular basis underlying the role of many of the SARS-CoV-2 proteins, and to make rapid progress towards treatment and preventive therapeutics. Despite the great advances that have been provided by these studies, many knowledge gaps on the biology and molecular basis of SARS-CoV-2 infection still remain. Filling these gaps will be the key to tackle this pandemic, through development of effective treatments and specific vaccination strategies.
Investigating the Impact of the Missing Significant Objects in Scene Recognition Using Multivariate Pattern Analysis

Significant objects in a scene can make a great contribution to scene recognition. Besides the three scene-selective regions: parahippocampal place area (PPA), retrosplenial complex (RSC), and occipital place area (OPA), some neuroimaging studies have shown that the lateral occipital complex (LOC) is also engaged in scene recognition processing. In this study, the multivariate pattern analysis was adopted to explore the object-scene association in scene recognition when different amounts of significant objects were masked. The scene classification only succeeded in the intact scene in the ROIs. In addition, the average signal intensity in LOC [including the lateral occipital cortex (LO) and the posterior fusiform area (pF)] decreased when there were masked objects, but such a decrease was not observed in scene-selective regions. These results suggested that LOC was sensitive to the loss of significant objects and mainly involved in scene recognition by the object-scene semantic association. The performance of the scene-selective areas may be mainly due to the fact that they responded to the change of the scene's entire attribute, such as the spatial information, when they were employed in the scene recognition processing. These findings further enrich our knowledge of the significant objects' influence on the activation pattern during the process of scene recognition.
Familial Hypercholesterolemia in Russia: Three Decades of Genetic Studies

The first studies of familial hypercholesterolemia (FH) in Russia go back to late 1980-ies. For more than 10 years the research in this field was carried out in Saint-Petersburg, the megapolis in the North-West Russia. Studies were focused on the search for causative mutations in low-density lipoprotein receptor gene (LDLR). Gradually the research was spread to Petrozavodsk in Karelia and in the XXI century two more centers contributed in investigations of genetics of FH, i.e., in Moscow and Novosibirsk. The best studied is the spectrum of mutations in LDLR, though genetic abnormalities in APOB and PCSK9 genes were also considered. Despite that some 40% mutations in LDLR found in Saint-Petersburg and Moscow are referred to as specific for Russian population, and this proportion is even higher in Karelia (ca. 70%), rapid introduction of NGS and intensifying genetic research all over the world result in continuous decrease of these numbers as “Slavic” mutations become documented in other countries. The samplings of genetically characterized patients in Russia were relatively small, which makes difficult to specify major mutations reflecting the national specificity of FH. Moreover, the majority of studies accomplished so far did not explore possible associations of certain mutations with ethnic origin of patients. By now the only exception is the study of Karelian population showing the absence of typical Finnish mutations in the region that borders on Finland. It can be concluded that the important primary research partly characterizing the mutation spectrum in FH patients both in the European and Siberian parts of Russia has been done. However, it seems likely that the most interesting and comprehensive genetic studies of FH in Russia, concerning various mutations in different genes and the variety of ethnic groups in this multi-national country, are still to be undertaken.
Sleep Quality and Self-Control: The Mediating Roles of Positive and Negative Affects

This study examined the mediating roles of both positive and negative affects in the relationship between sleep quality and self-control. A sample of 1,507 Chinese adults (37% men; mean age = 32.5 years) completed self-report questionnaires measuring sleep quality, positive and negative emotions, and self-control. Poor sleep quality was positively correlated with negative affect and negatively correlated with positive affect and self-control. Positive affect was positively correlated with self-control, while negative affect was negatively correlated with self-control. Both positive and negative affects significantly mediated the relationship between sleep quality and self-control. Improving individuals’ sleep qualities may lead to more positive emotions and less negative emotion, and these mood changes may increase resources for self-control. Regulating positive and negative affects may reduce the negative effects of poor sleep quality on self-control.
Wireless sensors for continuous, multimodal measurements at the skin interface with lower limb prostheses

Wireless, soft sensors continuously monitor pressure and temperature at the interface between a residual limb and a prosthesis. Form, fit, and function Improper fit between the prosthetic socket and the residual limb of persons with amputation causes discomfort, pressure ulcers, and altered load bearing. Kwak and colleagues developed pressure and temperature sensors to monitor the interface between a prosthesis and residual limb. The soft sensors communicated wirelessly with portable electronic devices during walking, sitting, and standing in non-amputees wearing prosthesis simulators and in two individuals with transtibial and transfemoral amputation, respectively. Results support use of wireless sensors to monitor the skin-prosthesis interface. Precise form-fitting of prosthetic sockets is important for the comfort and well-being of persons with limb amputations. Capabilities for continuous monitoring of pressure and temperature at the skin-prosthesis interface can be valuable in the fitting process and in monitoring for the development of dangerous regions of increased pressure and temperature as limb volume changes during daily activities. Conventional pressure transducers and temperature sensors cannot provide comfortable, irritation-free measurements because of their relatively rigid construction and requirements for wired interfaces to external data acquisition hardware. Here, we introduce a millimeter-scale pressure sensor that adopts a soft, three-dimensional design that integrates into a thin, flexible battery-free, wireless platform with a built-in temperature sensor to allow operation in a noninvasive, imperceptible fashion directly at the skin-prosthesis interface. The sensor system mounts on the surface of the skin of the residual limb, in single or multiple locations of interest. A wireless reader module attached to the outside of the prosthetic socket wirelessly provides power to the sensor and wirelessly receives data from it, for continuous long-range transmission to a standard consumer electronic device such as a smartphone or tablet computer. Characterization of both the sensor and the system, together with theoretical analysis of the key responses, illustrates linear, accurate responses and the ability to address the entire range of relevant pressures and to capture skin temperature accurately, both in a continuous mode. Clinical application in two prosthesis users demonstrates the functionality and feasibility of this soft, wireless system.
Bent-shaped mesogenic oxadiazoles and thiadiazoles with terminal methyl group

Rod-shaped 4-methylbenzoic acid-N′-(4′-n-alkoxybenzoyl) hydrazide (series I) have been synthesized by the Schotten–Baumann reaction of 4-methylbenzhydrazide with 4-n-alkoxy benzoyl chloride using dry pyridine, as a solvent. The series I compounds have been cyclized to bent-shaped mesogenic 2-(4′-methylphenyl)-5-(4″-n-alkoxyphenyl)-1,3,4-oxadiazoles (series II) and 2-(4′-methylphenyl)-5-(4″-n-alkoxyphenyl)-1,3,4-thiadiazole (series III) using POCl3 and Lawesson's reagent, respectively. The synthesized compounds are characterized by the combination of elemental analysis and standard spectroscopic methods. In series II, lower and middle members are non-mesogenic. n-Dodecyloxy to n-hexadecyloxy derivatives exhibit enantiotropic nematic mesophase. In series III, all the compounds synthesized exhibit enantiotropic nematic mesophase. n-Tetradecyloxy and n-hexadecyloxy derivatives also exhibit enantiotropic SmA mesophase. The mesomorphic properties of the series II and III used in this study are compared with each other and with other structurally related compound to evaluate the effect of different heterocyclic moieties as well as terminal substituents on mesomorphism.
Conversion of Sign Language To Text And Speech Using Machine Learning Techniques

Introduction: Communication with the hearing impaired ( deaf/mute) people is a great challenge in our society today; this can be attributed to the fact that their means of communication (Sign Language or hand gestures at a local level) requires an interpreter at every instance. Conversion of images to text as well as speech can be of great benefit to the non-hearing impaired and hearing impaired people (the deaf/mute) from circadian interaction with images. To effectively achieve this, a sign language (ASL – American Sign Language) image to text as well as speech conversion was aimed at in this research. Methodology: The techniques of image segmentation and feature detection played a crucial role in implementing this system. We formulate the interaction between image segmentation and object recognition in the framework of FAST and SURF algorithms. The system goes through various phases such as data capturing using KINECT sensor, image segmentation, feature detection and extraction from ROI, supervised and unsupervised classification of images with K-Nearest Neighbour (KNN)-algorithms and text-to-speech (TTS) conversion. The combination FAST and SURF with a KNN of 10 also showed that unsupervised learning classification could determine the best matched feature from the existing database. In turn, the best match was converted to text as well as speech. Result: The introduced system achieved a 78% accuracy of unsupervised feature learning. Conclusion: The success of this work can be attributed to the effective classification that has improved the unsupervised feature learning of different images. The pre-determination of the ROI of each image using SURF and FAST, has demonstrated the ability of the proposed algorithm to limit image modelling to relevant region within the image.
Model-Aware Deep Learning Based Strategies for Clutter Suppression in Contrast Enhanced Ultrasound

—Ultrasonography is a low-cost, radiation-free in- vivo imaging modality. In particular, blood vessel imaging and the measurement of their physical parameters, such as blood ﬂow velocities are of great clinical interest. One prominent solution involves the use of encapsulated gas microbubbles for improved visualization of the vascular bed, which has recently enabled imaging with unprecedented sub-wavelength spatial resolution. A typical preprocessing step to such operations is ﬁrst separating the microbubble signal from the cluttering tissue signal. Here, we propose two main contributions. The ﬁrst, is adopting a new model for the acquired contrast enhanced ultrasound signal, which was similarly suggested in the context of ultrasound Doppler processing and dynamic magnetic resonance imaging, and is typically solved via an iterative algorithm. This model leads to a better separation of microbubble signal from the tissue signal than commonly practiced methods. The second, is to utilize the recently proposed technique of learning fast sparse approximations from the ﬁeld of deep learning to suggest a suitable network architecture for this task with improved convergence speed and accuracy over its iterative counterpart. We compare the performance of the suggested network on both simulations and in-vivo rat brain scans, with a commonly practiced deep-network architecture and the fast iterative shrinkage/thresholding algorithm. We show that our architecture exhibits better image quality and contrast.