Miracle-dz/UniFAR-FTUs huggingface dataset:
Population Analysis and Genetic Structure of Two Kazakh Cattle Breeds Using 150K SNP

Kazakh white-headed and Auliekol breeds are mostly spread through Kazakhstan and are animals with dual purpose productivity directions including meat and milk. Kazakh native cattle breeds are still largely unexplored based on the genetic markers and are of great interest in the country. In this study, we for the first time applied high-density SNP genotyping for two indigenous cattle breeds to study genetic diversity, population structure and relationships with the different foreign breeds. Using of GGP Bovine 150K SNP array the principal component analysis (PCA), populations estimates of the genetic structure (ADMIXTURE), genetic diversity and distances (Fst), and phylogenetic tree showed that the Kazakh white-headed and Auliekol breeds have certain separate genetic structure that differ from European and Russian cattle breeds The two of these Kazakh cattle breeds have their genetic background according to observed results as distinct breeds. The obtained results will be aided in the development breeding system and conservation programs of the Kazakh white-headed and Auliekol breeds of beef cattle in the Kazakhstan.
Weakly supervised brain tumor segmentation via semantic affinity deep neural network

Image segmentation tasks are considered resource intensive. These tasks require domain specialists to labor manually over long periods of time. When considering medical image segmentation tasks, the personnel and the error margin make these tasks expensive. Therefore there is a need for an automated tool. Deep learning has fast become the state of the art for such tasks, yet the methods applied require large data-sets of fully annotated examples. The need for supervision prevents researchers from developing deep learning and machine learning solutions on new datasets, which were not annotated by professional personnel. In this paper we utilize weak supervision to train a deep neural network to perform instance segmentation. The data used for this project is the Multimodal Brain Tumor Segmentation Challenge 3D MRI scans. The method used is a two-step DNN. The first step is binary classification of slices to either pathological or healthy. This is the only step which uses supervision for the training of the DNNs. In the second step, another DNN in the form of a Unet encoder-decoder network is utilized. This network encodes the input raw data and decodes each pixel to a 32 dimensional vector representing a semantic identity (semantic map). The supervision for training this second network is derived from the GradCAM of the classification DNN. Lastly, to segment the input data we determine the semantic distance between suspected lesion points and the entirety of the map. We achieve an average Dice score of 0.73 over three test sets of 38 patients each.
Effect of Mercuric Chloride (HgCl2) Stress on DNA, RNA and Enzymes Vigna mungo L. Seedlings

At elevated concentrations all heavy metals are potentially toxic. Effects of Mercuric Chloride on the morphological parameters such as DNA, RNA and Enzymes were analysed during investigation on 10th day in seedlings of Vigna mungo L. , All parameters exhibited reduced trend with increase in HgCl2 concentrations when compared to control plants but the enzyme activities increased. This indicates that, the seedlings are in the process of increase in tolerance to HgCl2 treatment. Metal toxicity affects crop yields, soil biomass and fertility. Int. J. Appl. Sci. Biotechnol. Vol 10(1): 16-20.
Optic Nerve Head and Macular Vascular Density Changes in Different Stage Glaucoma

Aim: The vascular theory is thought to have an important place in the pathophysiology of glaucoma. In the present study, we aimed to analyze the structural and vascular changes in both eyes of patients with glaucoma at different stages and to investigate the relationship between structural and vascular structures. Methods: In this prospective cross-sectional study conducted between 2018 and 2019, 54 eyes of 27 patients with bilateral asymmetric glaucoma were included. Eyes with glaucoma were evaluated into 2 groups: an earlier stage and an advanced stage. All data is provided from the optical coherence tomography angiography (OCTA) device. The retinal nerve fiber layer (RNFL), ganglion cell inner plexiform layer (GCIPL) thickness, and rim area (RA) were measured using optical coherence tomography (OCT). The optic nerve head total (tVD), peripapillary (ppVD), intradisc (idVD), macular superficial (msVD), parafoveal (pasVD), perifoveal (pesVD), and deep macular vascular density values were compared with using OCTA. The correlation was investigated between thinning in the structural parameters and a decrease in the vascular density parameters. Results: There was a significant difference in both optic nerve head vascular density parameters (tVD, ppVD) and superficial macular vascular density parameters between the eyes with asymmetric glaucoma (p<0.001). The thinning of macular GCIPL, which was very strongly correlated with the change in optic nerve perfusion (tVD, ppVD) (r=0.899 and 0.892, p<0.001), was well correlated with the change in msVD and pesVD (r=0.642 and 0.574). The correlation of RNFL with tVD and ppVD was high (r=0.741 and 0.813), and the correlation with msVD and pesVD was moderate (r=0.480 and 0.494). Macular pasVD, deep vascular density, and idVD showed no correlation with changes in structural parameters. Conclusion: As the stage progresses, both the optic nerve head and macular perfusion are impaired in glaucoma. Macular superficial vascular density is affected more than deep vascular density. Thinning in the structural parameters correlates mostly with optic nerve head tVD and ppVD parameters.
Obtendo Desempenho Através de Mobilidade Forte de Código

Dentre as propostas desenvolvidas para tirar proveito da heterogeneidade de dispositivos e sistemas operacionais disponíveis atualmente, encontra-se a mobilidade de código. Através da utilização de uma camada software subjacente em comum, este artigo apresenta uma solução que utiliza mobilidade de código para obter paralelismo na execução de tarefas. O modelo de mobilidade forte de código apresentado chama-se HoloGo. Este modelo utiliza como plataforma de execução uma máquina virtual, chamada HoloVM, que oferece suporte à programação concorrente e blackboards. A utilização do modelo proposto é materializada através da implementação de uma aplicação que visa o ganho de desempenho na execução de uma tarefa computacionalmente intensa.
Online Education of a Music Flipped Classroom Based on Artificial Intelligence and Wireless Network

Music learning is increasing day-by-day as the individual’s interest is also growing. Not all interested individuals will attend the classes in offline mode. The introduction of online education overcomes this challenge. Similar to individual learning, classroom learning in music education is taking on a new perspective in offline and online modes. This combination of online and offline teaching modes is termed the “flipped classroom. ” Flipped classrooms work with the support of two major technologies, such as artificial intelligence and wireless networking. The teachers and the students interact through an interactive device aided by intelligent networking facilities. A convolutional neural network is implemented to make the system smart by providing automatic classification of course materials. The proposed model is compared with the K-means algorithm. The findings demonstrated that the flipped classroom outperformed the existing model with an accuracy of 98.25%, which is 5.01% higher than the existing algorithm.
Monitoring Demography of Resurrected Populations of Locally Extinct and Extant Species to Investigate Drivers of Species Loss

Extinctions are predicted to rise by an order of magnitude over the next century. Although contemporary documented extinctions are uncommon, local extirpations likely provide hints about global extinction risks. Comparing responses to global change of locally extinct versus extant species pairs in a phylogenetic framework could highlight why certain species are more vulnerable to extinction than others and which anthropogenic changes are most relevant to their decline. As anthropogenic changes likely interact to affect population declines, demographic studies partitioning the effects of multifactorial stressors are needed but remain rare. I examine demographic responses to nitrogen addition and deer herbivory, two major drivers of species losses in grasslands, in experimental reintroductions of 14 locally extinct and extant confamilial native plants from Michigan prairies. Nitrogen consistently reduces survival, especially in locally extinct species, and growth of locally extinct species benefits less from nitrogen than growth of extant species. Nitrogen reduces population growth rates, largely via reductions in survival. Deer herbivory, meanwhile, had inconsistent effects on vital rates among species and did not affect population growth. Nitrogen and herbivory rarely interacted to affect vital rates. These results link community-level patterns of species loss under nitrogen addition to the population-level processes underlying those losses.
Effect of Zn(S,O,OH) Buffer Thin Films Formed on CIGS through Different Stages and Reaction Processes in Chemical Bath Deposition: Interpretations from Mechanisms and Transformation Kinetics Perspective

Herein, Zn(S,O,OH) is used as a buffer material for Cu(In,Ga)Se2 (CIGS) solar cells instead of CdS to increase the quantum efficiency and remove toxicity. To control the fine thickness of the Zn(S,O,OH) thin films in the chemical bath deposition (CBD) method, a quartz crystal microbalance (QCM) system is introduced by measuring the frequency change. As the frequency changes are adjusted according to the S/O ratio of the Zn(S,O,OH) buffer (Zn buffer) produced during the reaction, the formed phase and thickness are cross‐validated several times to obtain the accurate thickness. These different S/O ratios can be modified by different deposition mechanisms and reaction processes depending on the reaction rate of material formation. Therefore, to investigate the associated mechanism and reaction process in detail, Zn buffer thin films are formed and characterized using two different Zn sources (zinc sulfate and zinc acetate) that affect the reaction rate due to the anion effect. In addition, the optimal deposition range is obtained by comparing the performances of the solar cells with Zn thin films of the same thickness, deposited through different stages in a continuous CBD reaction. Finally, the effect of Zn buffers using different Zn sources on the interfaces with CIGS is investigated in the band alignment.
Quality in management accounting: approach by activities in large companies

This study intends to contribute to the knowledge about the approach by activities, a management accounting method that promotes the quality of information. As specific objectives, we have identified the following: to analyse the knowledge rate regarding the approach by activities, and identify whether there is a link between it and the financial officers' characteristics; to analyse the utilisation rate of the approach by activities, and the factors conditioning it; to analyse whether there is a link between a company's features, and the use of the approach by activities. The data collection method used was the application of a survey to the financial officers of the largest Portuguese companies, which yielded 61 valid responses. The results found allowed us to conclude the following: the time driven activity-based costing is very little known and used in Portugal; there is a link between the knowledge of the approach by activities and the financial officers' gender, age and educational background; there is a link between the use of the approach by activities and two company features: the legal form and the capital holding.
Human brain extraction with deep learning

Brain extraction, also known as skull stripping, from magnetic resonance images (MRIs) is an essential preprocessing step for many medical image analysis tasks and is also useful as a stand-alone task for estimating the total brain volume. Currently, many proposed methods have excellent performance on T1-weighted images, especially for healthy adults. However, such methods do not always generalize well to more challenging datasets such as pediatric, severely pathological, or heterogeneous data. In this paper, we propose an automatic deep learning framework for brain extraction on T1-weighted MRIs of adult healthy controls, Huntington’s disease patients and pediatric Aicardi Gouti`eres Syndrome (AGS) patients. We examine our method on the PREDICT-HD and the AGS datasets, which are multi-site datasets with different protocols/scanners. Compared to current state-of-the-art methods, our method produced the best segmentations with the highest Dice score, lowest average surface distance and lowest 95-percent Hausdorff distance on both datasets. These results indicate that our method has better accuracy and generalizability for heterogeneous T1-w MRI datasets.
Impacto da Migração de Máquinas Virtuais de Xen na Execução de Programas MPI

A virtualização pode ser vista como a manutenção de máquinas virtuais, cada qual com seu sistema operacional, sobre um conjunto de recursos. Para área de alto desempenho, ela possibilita criar várias máquinas virtuais em cada recurso, permitindo testes de desempenho de aplicações científicas com diversas configurações. Além disso, o conceito de virtualização abrange a idéia de migração, onde é possível transportar uma máquina virtual para um diferente recurso. Nesse contexto, a ferramenta Xen suporta as características apresentadas e foi usada para avaliar o custo da migração de máquinas virtuais que executam programas MPI. O propósito final é avaliar a viabilidade de Xen para o desenvolvimento de uma biblioteca de migração de processos MPI, tornando possível um reescalonamento eficiente deles em tempo de execução. O presente artigo apresenta os resultados sobre o impacto da migração de máquinas virtuais Xen na execução de programas MPI. Ele também aborda alguns testes de computação e comunicação com o Xen e trabalhos relacionados sobre migração com virtualização.
Network activity analysis of CryptoWall ransomware

The paper presents the analysis of the CryptoWall ransomware network behaviour. In this approach a HoneyPot technology as well as the automatic run-time malware analytical system called Maltester were used. We present the practical results of the analyses, technologies and tools used, and the gained experience with dynamic analysis of ransomware software in a dedicated environment. Most of the data was collected with the use of the HoneyPot infrastructure created and deployed in the network of the Institute of Computer Science WUT. Streszczenie. Praca przedstawia analizę zachowania sieciowego złośliwego oprogramowania CryptoWall typu ransomware. W badaniach wykorzystano technologię HoneyPot oraz system automatycznej analizy działania złośliwego oprogramowania w czasie jego wykonywania o nazwie Maltester. Zaprezentowano zarówno uzyskane wyniki analiz, wykorzystane technologie i narzędzia jak i doświadczenia zebrane podczas analizy oprogramowania typu ransomware w autorskim środowisku analitycznym. Większość danych zebrana została z wykorzystaniem infrastruktury HoneyPot stworzonej i wdrożonej w sieci Instytutu Informatyki Politechniki Warszawskiej. (Dynamiczna analiza aktywności sieciowej oprogramowania CryptoWall typu ransomware).
Robust Fuzzy Feedback Control for Nonlinear Systems With Input Quantization

In this article, we study the robust quantized feedback control problem for nonlinear discrete-time systems that are described by Takagi–Sugeno (T–S) fuzzy model with norm-bounded uncertainties. The dynamic quantizer composed of a dynamic parameter and a static quantizer is considered to quantize the control input signal. An improved two-step approach to design controller and dynamic quantizer for T–S fuzzy system is proposed based on the LMI technique. In the first step, a robust controller is designed to guarantee that the quantized fuzzy closed-loop system with norm-bounded uncertainties is asymptotically stable with prescribed $\mathcal {H}_{\infty }$ performance. Then, the parameter-dependent (membership function) scalar variable is obtained to determine the dynamic quantizer’s parameter in the second step. Finally, the simulation result of truck–trailer system is presented to validate the effectiveness and feasibility of the proposed two-step design approach.
Study on two-dimensional photonic crystal waveguide 1×5 beam splitter reversely designed by downhill-simplex algorithm

Beam splitter, whose main function is to achieve the splitting, combining and routing of optical signals, is an important component of photonic integrated circuits, passive optical network and other fields. Compared with the conventional beam splitter, photonic crystal beam splitter, which has the virtues of smaller size and higher transmission efficiency, is very suitable for high-density and large-scale integration. The traditional control variable method often used in the optimal design of photonic crystal beam splitter is time-consuming and inefficient. When parameter variables are large, it is difficult for beam splitter to achieve the optimal splitting performance. In addition, it is hard to realize flexible design of beam splitting ratio when optimizing multi-channel photonic crystal beam splitter by using this method. In this paper, a novel photonic crystal 1×5 beam splitter, in which two special Y-junction waveguides are introduced into a completely two-dimensional square lattice silicon, is proposed and optimally designed by using downhill-simplex algorithm. Firstly, to determine the optimization range of each variable, the influence of the radius of the dielectric rods in the coupling region and the radius and the lateral offset of the regulating dielectric rods in the center of the two Y-junction waveguides on the five output ports of the 1×5 beam splitter is explored respectively by using plane wave expansion method and finite difference time domain method. The results show that the optical energy coupled from the main waveguide W1 to the upper and lower Y-junction waveguides can be controlled by optimizing the radius of the dielectric rods in the coupling region. The transmittance of the five output ports can be controlled in proportion by optimizing the lateral offset of the regulating dielectric rods. The total transmittance of the five output ports can be improved and the output of each port can be adjusted by optimizing the radius of the regulating dielectric rods. Then, according to the specific target of the splitting ratio, using downhill-simplex algorithm, the 1×5 beam splitter with different splitting ratio can be reversely designed by optimizing the radius of the coupling dielectric rods and the radius and the lateral offset of the regulating dielectric rods within the selected optimization range. The total transmittance of the 1×5 beam splitter is above 99%, the additional loss is less than 0.044dB, and the response time is less than 1ps. Besides, to determine the allowable error range of each optimization variable in actual processing, the machining error of the 1×5 beam splitter is analyzed, which provides a theoretical reference for the fabrication of the device. Due to the advantages of flexible splitting ratio design, high optimization efficiency, small size and excellent performance, the proposed 1×5 beam splitter will have broad application prospects in the field of photonic integrated circuits and so on.
Effect of Betaine and Arginine on Interaction of αB-Crystallin with Glycogen Phosphorylase b

Protein–protein interactions (PPIs) play an important role in many biological processes in a living cell. Among them chaperone–client interactions are the most important. In this work PPIs of αB-crystallin and glycogen phosphorylase b (Phb) in the presence of betaine (Bet) and arginine (Arg) at 48 °C and ionic strength of 0.15 M were studied using methods of dynamic light scattering, differential scanning calorimetry, and analytical ultracentrifugation. It was shown that Bet enhanced, while Arg reduced both the stability of αB-crystallin and its adsorption capacity (AC0) to the target protein at the stage of aggregate growth. Thus, the anti-aggregation activity of αB-crystallin increased in the presence of Bet and decreased under the influence of Arg, which resulted in inhibition or acceleration of Phb aggregation, respectively. Our data show that chemical chaperones can influence the tertiary and quaternary structure of both the target protein and the protein chaperone. The presence of the substrate protein also affects the quaternary structure of αB-crystallin, causing its disassembly. This is inextricably linked to the anti-aggregation activity of αB-crystallin, which in turn affects its PPI with the target protein. Thus, our studies contribute to understanding the mechanism of interaction between chaperones and proteins.
La métrica del vivir bien: Construcción de un índice de reconciliación y equilibrio

En respuesta a cuán y cómo de bien se vive, la presente investigación tuvo como objetivo generar un índice de desarrollo considerando los fundamentos filosóficos, culturales, costumbristas y lingüísticos del paradigma prevalente del Vivir Bien. El andamiaje estadístico - matemático desarrollado se ajustó al modelo boliviano basado en los 25 principios propuestos por Choquehuanca. Partiendo de los fundamentos de la tetraléctica y la tetrasociología, se formaron pautas para desarrollar un propio modelo ontológico que ayude a definir las dimensiones y las variables que mejor describan este paradigma. Como resultado se propuso un índice conceptualmente robusto – Índice del Vivir Bien (IVB) – que supera los índices de pobreza, desarrollo humano y otras métricas, configurado en un sistema en el que la Bioeconomía juega un rol preponderante para llegar a la pentaléctica. Se resalta la importancia de habilitar una conexión con la economía, lo social y medioambiental, que permita consolidar una base ética, moral e ideológica que promueva el Vivir Bien como fundamento transversal, tanto interna como internacionalmente.
The Impact of Initial Vascular Access on Long-term Mortality in Hemodialysis Thai Patients

Background: End-stage kidney disease (ESKD) patients are significantly at risk of higher mortality than the general population. While cardiovascular disease and infection are the major causes of death in ESKD patients on hemodialysis (HD), the impact of vascular access type on long-term mortality in the Thai population remains unclear. Objective: To find an association between types of vascular access and long-term mortality in HD Thai patients. Methods: A multicenter, retrospective cohort of HD patients with a 55-month follow-up (November 2015 to December 2020) was conducted. Patients’ baseline characteristics, and HD profiles were reviewed. A logistic regression model and survival analysis were used to test the association and survival probability of each type of vascular access and mortality. Results: Of 196 HD patients over 55 months, the proportions of initial vascular access included 46.94% of arteriovenous fistula (AVF), 27.55% of arteriovenous graft (AVG), and 25.51% of tunneled dialysis catheter (TDC). The overall mean all-cause mortality in this cohort was 29.1%. Compared with AVF, TDC was associated with increased mortality (adjusted OR, 3.18; 95% CI, 1.37 - 7.37; P < .05) while the association between AVG and mortality was borderline significant (adjusted OR, 2.29; 95% CI, 0.96 - 5.46; P > .05). Conclusions: TDC as initial vascular access for incident HD Thai patients was associated with increased all-cause mortality at 55 months compared with functioning AVF.