Miracle-dz/UniFAR-FTUs huggingface dataset:
Lecithin-based organogel for an industrialized butter from Platonia insignis Mart. seeds and its anti-inflammatory potential: Formulation and preclinical studies

: Platonia insignis Mart. (Clusiaceae) is a medicinal plant from Brazilian Amazon rainforest. In traditional medical practices, seeds oil extracted from “bacuri” is used in the treatment of wounds, eczema, herpes or other skin diseases. In view of the therapeutic potential of seeds butter from “bacuri” (BBI), the present study aims to propose a topical formulation using an industrially obtained BBI (F-BBI) and its anti-inflammatory pre-clinical assessment in the carrageenan-induced paw edema in rats. The results of this study suggest that BBI are able to act in different phases of inflammatory response depending on the administration route. The proposed F-BBI are able to act in all phases of inflammatory response. This report suggests a new application for Platonia insignis seeds extract as a promising topical anti-inflammatory agent, and encourage further studies in order to elucidate mechanisms involved in this effect.
Fluvial sediment in the environment: a national challenge

Sediment and sediment-associated constituents can contribute substantially to water-quality impairment. In the past, sediment was viewed mainly as an engineering problem that affected reservoir storage capacity, shipping channel maintenance, and bridge scour, as well as the loss of agricultural soil. Sediment is now recognized as a major cause of aquatic system degradation in many rivers and streams as a result of light attenuation, loss of spawning substrate due to fine-grained sediment infilling, reduction in primary productivity, decreases in biotic diversity, and effects from sediment-associated chemical constituents. Recent advances in sediment measurement, assessment, source-identification, and analytical protocols provide new capabilities to quantify sediment and solid-phase chemical fluxes in aquatic systems. Developing, maintaining, and augmenting current sedimentand water-quality-monitoring networks is essential for determining the health of U.S. waterways and for evaluating the effectiveness of management actions in reducing sediment-related problems. The application of new scientific capabilities that address the adverse effects of sediment and sedimentassociated constituents represents a major step in managing the Nation’s water quality. A robust Federal, national-scale effort, in collaboration with vested stakeholders, is needed to address these sediment-related water-quality issues across the United States.
SerbOCR - Optical Character Recognizer of the Serbian Cyrillic Alphabet

 Abstract —This paper presents a technique for optical character recognition of machine-written Serbian Cyrillic text based on deep Convolutional Neural Networks. The described OCR system makes use of distinct preprocessing, character segmentation and character classification modules. For preprocessing, an adaptive gaussian threshold was used, while character segmentation used horizontal and vertical projection as well as connected component analysis. The classifier itself is a deep convolutional neural network. The entire system gave good results, with scanned documents yielding strings with a Levenshtein distance of less than 1% of the string length to the actual value present on the image.
Glucocorticoid Receptor Gene (NR3C1) Polymorphisms and Metabolic Syndrome: Insights from the Mennonite Population

The regulation of the hypothalamic-pituitary-adrenal (HPA) axis is associated with polymorphisms and the methylation degree of the glucocorticoid receptor gene (NR3C1) and is potentially involved in the development of metabolic syndrome (MetS). In order to evaluate the association between MetS with the polymorphisms, methylation, and gene expression of the NR3C1 in the genetically isolated Brazilian Mennonite population, we genotyped 20 NR3C1 polymorphisms in 74 affected (MetS) and 138 unaffected individuals without affected first-degree relatives (Co), using exome sequencing, as well as five variants from non-exonic regions, in 70 MetS and 166 Co, using mass spectrometry. The methylation levels of 11 1F CpG sites were quantified using pyrosequencing (66 MetS and 141 Co), and the NR3C1 expression was evaluated via RT-qPCR (14 MetS and 25 Co). Age, physical activity, and family environment during childhood were associated with MetS. Susceptibility to MetS, independent of these factors, was associated with homozygosity for rs10482605*C (OR = 4.74, pcorr = 0.024) and the haplotype containing TTCGTTGATT (rs3806855*T_ rs3806854*T_rs10482605*C_rs10482614*G_rs6188*T_rs258813*T_rs33944801*G_rs34176759*A_rs17209258*T_rs6196*T, OR = 4.74, pcorr = 0.048), as well as for the CCT haplotype (rs41423247*C_ rs6877893*C_rs258763*T), OR = 6.02, pcorr = 0.030), but not to the differences in methylation or gene expression. Thus, NR3C1 polymorphisms seem to modulate the susceptibility to MetS in Mennonites, independently of lifestyle and early childhood events, and their role seems to be unrelated to DNA methylation and gene expression.
THE INFLUENCE OF ELECTRONIC SERVICE QUALITY ON DIGITAL BANK APPLICATION

The advancement of technology and prevalence of smartphones in society influence the transition from offline to online purchases. The ability to carry out financial transactions from anywhere and at any time has become a necessity for the community, and banks have adapted to meet this demand. Customers' expectations for easy, safe, and more personalized services, as well as the ability to evaluate the quality of products and services, have led banks to go digital. This study utilizes two digital banks as research samples, with this digital bank being the one with the greatest number of downloads. However, compared to all other digital banks, these two have relatively lower ratings. This study employs a quantitative methodology and gathers data from 400 participants using an online questionnaire; all respondents had prior experience digital bank application. This study will investigate the factors that influence the loyalty of digital bank application users, as well as the amount to which each component influences the user's loyalty to digital bank applications. This study investigated the factors involved in utilizing the Electronic Service Quality model with variables consisting of ease of use, customer contact, reliability, responsiveness, security/privacy, and application design. This study employed Partial Least Squares Structural Equation Modeling (PLS-SEM), and the SmartPLS program was used to analyze the collected data. All variables except application design have positive and significant influence on customer loyalty. All factors have a positive and significant influence on customer satisfaction. Additionally, the satisfaction determined to have a positive and significant influence on customer loyalty. This research is presumed to assist Digital Bank in enhancing and improving their banking applications and improving their services, so that customer satisfaction and loyalty keep on improving.
Implementation of BGP in a network simulator

Border Gateway Protocol (BGP) is the inter-domain routing protocol currently employed in Internet. Internet growth imposes increased requirements on BGP performance. Recent studies revealed that performance degradations in BGP are due to the highly dynamic nature of the Internet. In this paper, we describe the design of the nsBGP model and its implementation in the ns-2 network simulator. We describe a validation test for route reflection and provide a scalability performance analysis of the nsBGP model.
Incidence and severity of pulmonary hypertension among patients Incidence and severity of pulmonary hypertension among patients with chronic kidney disease with chronic kidney disease

Introduction : Chronic kidney disease (CKD) is a major health problem and is closely linked with cardiovascular disease. Pulmonary hypertension (PH) is considered a common comorbidity in CKD patients. Methods : In all, 100 patients were included in our study. Transthoracic echo Doppler study was performed to measure pulmonary artery systolic pressure based on tricuspid jet. Result : The prevalence of PH in CKD patients in our study was 60%; prevalence and severity had signi ﬁ cant association. The hemodialyzed group showed a higher prevalence of PH with a more severe PH. Conclusion : Our study had provided evidence that PH is a common comorbidity in CKD patients and is directly proportional with the stage and duration of CKD.
Assessing the association between supplemented puppyhood dietary fat sources and owner-reported epilepsy in adulthood, among Finnish companion dogs

Introduction Epilepsy is a serious and common neurological condition in dogs, despite the wide number of antiepileptic drugs available, in approximately one third of the patients, epilepsy remains unsatisfactorily controlled. We aim to analyze whether feeding dietary fat sources during puppyhood was associated with canine epilepsy in adulthood. Methods A nested case–control study was compiled from the validated DogRisk food frequency questionnaire (DogRisk FFQ). DogRisk FFQ collected feeding, disease, and background data about the dog. The study sample consisted of 108 owner-reported epileptic cases and 397 non-epileptic controls. Each case was matched with up to four controls for the key confounding factors of sex, breed, and age. We analyzed associations between feeding as a puppy and owner-reported epilepsy as an adult dog using Cox regression. We tested 55 different food variables. Results We found that feeding fish fat from dietary sources at least once a week during puppyhood was inversely associated with epilepsy in later life in the unadjusted analysis [OR 0.46 (95% CI 0.25–0.83), p=0.01], while when adjusting for keeping conditions and dog characteristics the association was [OR 0.45 (95% CI 0.23–0.88), p=0.02]. When adjusted for keeping conditions, dog characteristics, and other feeding factors, the association was of similar magnitude but not significance [OR 0.56 (95% CI 0.27–1.15), p=0.12]. Discussion The study indicates possible protective associations of feeding the dog with dietary sources of fish fat against epilepsy, although the result could be confounded by other feeding factors. Findings are compatible with current knowledge regarding the role of omega-3 fatty acids and ketogenic diet, a low carbohydrate, high fat diet as supportive treatments of epilepsy. As our findings are based on observations, we suggest the possibility of causality but do not prove it. Dietary intervention studies should now be conducted to confirm our findings.
An In Silico Design of Peptides Targeting the S1/S2 Cleavage Site of the SARS-CoV-2 Spike Protein

SARS-CoV-2, responsible for the COVID-19 pandemic, invades host cells via its spike protein, which includes critical binding regions, such as the receptor-binding domain (RBD), the S1/S2 cleavage site, the S2 cleavage site, and heptad-repeat (HR) sections. Peptides targeting the RBD and HR1 inhibit binding to host ACE2 receptors and the formation of the fusion core. Other peptides target proteases, such as TMPRSS2 and cathepsin L, to prevent the cleavage of the S protein. However, research has largely ignored peptides targeting the S1/S2 cleavage site. In this study, bioinformatics was used to investigate the binding of the S1/S2 cleavage site to host proteases, including furin, trypsin, TMPRSS2, matriptase, cathepsin B, and cathepsin L. Peptides targeting the S1/S2 site were designed by identifying binding residues. Peptides were docked to the S1/S2 site using HADDOCK (High-Ambiguity-Driven protein–protein DOCKing). Nine peptides with the lowest HADDOCK scores and strong binding affinities were selected, which was followed by molecular dynamics simulations (MDSs) for further investigation. Among these peptides, BR582 and BR599 stand out. They exhibited relatively high interaction energies with the S protein at −1004.769 ± 21.2 kJ/mol and −1040.334 ± 24.1 kJ/mol, respectively. It is noteworthy that the binding of these peptides to the S protein remained stable during the MDSs. In conclusion, this research highlights the potential of peptides targeting the S1/S2 cleavage site as a means to prevent SARS-CoV-2 from entering cells, and contributes to the development of therapeutic interventions against COVID-19.
Improved the locally aligned ant technique (LAAT) strategy to recover manifolds embedded in strong noise

The automatic detection, extraction, and modeling of manifold structures from large data-sets are of great interest, especially in Astronomy. Existing manifold learning techniques for feature extraction in Computer Vision, Bioinformatics and signal denoising typically fail in astronomical scenarios, since they mostly assume low levels of noise and one manifold of fixed dimension. Therefore, the Locally Aligned Ant Technique (LAAT) was recently proposed to discover multiple faint and noisy structures of varying dimensionality embedded in large amounts of background noise. Although it demonstrates excellent results in multiple scenarios, its performance depends on global thresholding and user tuning. Here, we improve LAAT and replace the global threshold by a flexible local strategy.
Intra-hour Direct Normal Irradiance solar forecasting using genetic programming

The development and utilization of solar energy has resulted in increased interest in solar irradiance forecasting. Ground level insolation has a natural variability due to atmospheric processes that are directly tied to the local meteorological conditions. Independent System Operators (ISOs) find that forecasting errors for small timescales are highly dependent on the characteristics and dynamics of the local cloud cover. This work seeks to explore the use of Genetic Programming to develop forecasting programs that surpass the performance of persistence forecasting. Specifically, our interest lies in forecasting a 30-second average Direct Normal Irradiance with a time horizon of five minutes. The GP-produced forecasting programs will be compared to the performance of persistence forecasting in the terms of Root Means-Squared Errors (RMSE). These proof-of-concept experiments have demonstrated that GP is a promising approach, producing forecasting programs with a 10% performance improvement over persistence forecasts
ACCURACY MEASUREMENTS OF INDUSTRIAL ROBOTS

Abstract: The robots are frequently used in logistic problems and the increasing quality requirements of the production can be fulfilled only by high positioning accuracy. In this paper we analyse a KUKA KR 15/2 and a Fanuc LR Mate 200iC robot, which are measured by laser interferometer Renishaw XL-80. Both robots are six DOF, articulated manipulator (RRR), and their descriptions of Denavit-Hartenberg parameters are very similar. The measurement are restricted on relatively small working area, i.e., ±50mm displacement in X and Y directions. The goal of the measurements is to determining the positioning accuracy and it repetition. In addition to the measurement analytic formulae are given by help of Denavit-Hartenberg parameters. This gives the possibility to compare to joint angles obtained by theoretical formulae and given by controller.
Unlocking the Potential: Amino Acids’ Role in Predicting and Exploring Therapeutic Avenues for Type 2 Diabetes Mellitus

Diabetes mellitus, particularly type 2 diabetes mellitus (T2DM), imposes a significant global burden with adverse clinical outcomes and escalating healthcare expenditures. Early identification of biomarkers can facilitate better screening, earlier diagnosis, and the prevention of diabetes. However, current clinical predictors often fail to detect abnormalities during the prediabetic state. Emerging studies have identified specific amino acids as potential biomarkers for predicting the onset and progression of diabetes. Understanding the underlying pathophysiological mechanisms can offer valuable insights into disease prevention and therapeutic interventions. This review provides a comprehensive summary of evidence supporting the use of amino acids and metabolites as clinical biomarkers for insulin resistance and diabetes. We discuss promising combinations of amino acids, including branched-chain amino acids, aromatic amino acids, glycine, asparagine and aspartate, in the prediction of T2DM. Furthermore, we delve into the mechanisms involving various signaling pathways and the metabolism underlying the role of amino acids in disease development. Finally, we highlight the potential of targeting predictive amino acids for preventive and therapeutic interventions, aiming to inspire further clinical investigations and mitigate the progression of T2DM, particularly in the prediabetic stage.
Contingency factors and entrepreneurship: Influence on business activity

Purpose The aim of this study is to analyse the determinants of the survival of Spanish companies. Design/Methodology/Approach Two approaches are used and they are complementary. The first approach analyses the determinants of survival probability. For this purpose, a binary choice model is built and estimated using a sample of companies from the main economic sectors taken from the SABI database. Likewise, the Blinder-Oaxaca decomposition is applied to quantify the difference between companies with employees and without employees and the proportion of this difference that owes to observed factors or unobserved factors. Finally, the second approach is a survival analysis carried out through the Cox proportional hazard model that identifies the determinants of the duration of business activity.
Growth inhibition of the larval stage of Echinococcus granulosus of sheep origin by apricot, Prunus armeniaca seed extract in vitro

Cystic echinococcosis is one of the serious disease that affecting humans and this domesticated animals. In vitro , the bioactivity of the apricot, Prunus armeniaca seed extract on the vitality of the larval stage (protoscolices) of Echinococcus granulosus of sheep origin had been investigated. The protoscolices were significantly affected by applying concentrations of 50, 100, 150 and 200 mg.ml -1 . The concentration 200 mg.ml -1 caused 100% mortality within 15 minutes. The vitality inhibition was proportioned to extract concentration and time exposure.
Testing for independence in arbitrary distributions

SUMMARY Statistics are proposed for testing the hypothesis that arbitrary random variables are mutually independent. The tests are consistent and well behaved for any marginal distributions; they can be used, for example, for contingency tables which are sparse or whose dimension depends on the sample size, as well as for mixed data. No regularity conditions, data jittering, or binning mechanisms are required. The statistics are rank-based functionals of Cramer–von Mises type whose asymptotic behaviour derives from the empirical multilinear copula process. Approximate $p$-values are computed using a wild bootstrap. The procedures are simple to implement and computationally efficient, and maintain their level well in moderate to large samples. Simulations suggest that the tests are robust with respect to the number of ties in the data, can easily detect a broad range of alternatives, and outperform existing procedures in many settings. Additional insight into their performance is provided through asymptotic local power calculations under contiguous alternatives. The procedures are illustrated on traumatic brain injury data.
Multi3Generation 2023 Proceedings of the 1st International Workshop on Multilingual, Multimodal and Multitask Language Generation (Multi3Generation)

Significant difficulty in translation tasks is usually caused by the possibility of having multiple correct results. That is where human translators usually beat modern machine learning models, as they have much more external context, which can be useful to create a correct translation both from the meaning and style sides. The purpose of this article is to provide a possible solution for the lack of context during machine translation, which would provide an ability to increase the controllability of existing machine translation architectures. We propose a new architecture, which would incorporate this additional embedded context into the translation and compare this new approach to some classic ones like just transfer learning of some new features using an existing, trained model. We conducted some experiments using the proposed architecture to check if it indeed allows controlling of the translation process and measured the new model using both token and embedding metrics.
Adaptive Dynamic Programming Based Linear Quadratic Regulator Design for Rotary Inverted Pendulum System

The rotary inverted pendulum system is an inherently unstable system with highly nonlinear dynamics. It is used for design, testing, evaluating and comparing of different classical and contemporary control techniques. The goal of this project is to design an ADP based LQR controller for the rotary inverted pendulum system. Here model-based policy iteration algorithm is used to design the ADP based LQR controller. The swing-up and balance control is also implemented for the rotary inverted pendulum system using ADP based LQR controller gain. The response of the rotary inverted pendulum system with conventional LQR controller, ADP based LQR controller, swing-up and balance control is illustrated using MATLAB – SIMULINK platform. The result obtained after comparing the ADP based LQR controller response with conventional LQR controller, the rotary inverted pendulum system is stabilized faster with ADP based LQR controller and the swing-up and balance control response of the rotary inverted pendulum system has also improved due to ADP based LQR controller gain.
Modelling the C-ITS architectures: C-MobILE case study

C-MobILE (Accelerating C-ITS Mobility Innovation and deployment in Europe) is a project co-founded by the European Commission that aims to stimulate large-scale C-ITS deployments interoperable across Europe. The main aim is to have well-defined operational procedures leading to decentralized and dynamic coupling of systems, services and stakeholders across national and organizational borders in an open, but secure C-ITS ecosystem, based on different access technologies across different transport modes, environments and countries. C-MobILE defines the C-ITS architecture framework conforming to the ISO/IEC/IEEE 42010 international standard and specifies stakeholders, concerns, model kinds and six core viewpoints: Context, Functional, Information, Implementation, Physical, and Communication. This paper describes the C-MobILE architectures conforming to the C-ITS architecture framework and modelling approach.
The relevance of hyper-parameters in convolutional neural networks: a case study with Fashion-MNIST

Artificial vision usually extracts features of images and tries to give an interpretation of them for their application in the solution of certain problems. One of the main applications of computer vision is object detection, which consists in identifying whether an object is present in an image. In this work, a convolutional neural network is used to detect the type of garment present in an image. The purpose of the study is to verify how relevant a correct choice of hyper-parameters can be for convolutional neural networks. The Fashion-MNIST dataset is used for the training and testing phases.