Miracle-dz/UniFAR-FTUs huggingface dataset:
Calibraciones de espectrofotometría de reflectancia en el infrarrojo cercano para carbohidratos en pasto Urochloa

El objetivo fue desarrollar modelos de calibración de espectroscopia de reflectancia en el infrarrojo cercano (NIRS) para estimar el contenido de las fracciones de fibra y de carbohidratos en pastos Urochloa sp. para la zona tropical de México. Ciento ochenta y nueve muestras de tres híbridos de Urochloa fueron cosechadas cada 35 días durante un año, las cuales fueron analizadas por química húmeda para las fracciones de fibra: Fibra Detergente Neutra (NDF), Proteína insoluble en Detergente Neutro (NDIP), Fibra Detergente Ácida (ADF), Proteína Insoluble en Detergente Ácido (ADIP) y Lignina (LIG), y se estimaron los carbohidratos totales (TC), carbohidratos fibrosos (FC), carbohidratos no fibrosos (NFC) y carbohidratos indigestibles (UC). Los modelos de calibración y de validación se evaluaron por los respectivos Coeficientes de Determinación (R2); Errores Estándar de Validación Cruzada (SECV); y la desviación residual de la predicción (RPD). Además, con un conjunto de muestras externas, se realizó una prueba de sensibilidad evaluada por el Cuadrado Medio del Error de Predicción (MSPE). Las calibraciones obtenidas presentaron un adecuado ajuste y eficiencia predictiva mediante espectrofotometría NIR para NDF (RPD 2.4) y TC (RPD 2.5) lo que demuestra confiabilidad y capacidad de predicción para estas fracciones. Sin embargo, LIG, FC, NFC y UC requieren más observaciones para acrecentar su confiabilidad.
The Effect of Water Intake on Body Mass Index in Universitas Sumatera Utara Medical Students

Overweight and obesity is one of the health problems in the world. This condition is associated with various health problems such as cardiovascular disease, stroke, osteoarthritis, chronic back pain, gallbladder disease, and cancer. Consuming adequate fluids can help you lose weight. This study aimed to determine the relationship between body fluid intake and body mass index (BMI) in Medical Faculty Universitas Sumatera Utara students. A cross-sectional study was conducted on USU Medical Faculty students from October 2020 to January 2021 with a sample of 99 people. Researchers obtained primary data obtained through reporting daily fluid intake for seven consecutive days and anthropometric measurements. Furthermore, the researchers conducted the Spearman test to determine the relationship between the two variables. Based on the characteristics of the sample, the researchers obtained 51 samples that were female (51.5%), and 48 were male (48.5%) with an average age of 20.05±1.08 years. The average fluid intake consumed was around 2070.07±654.93 mL per day, whereas 48 people in the study sample consumed less fluid below 2000 mL/day (45.5%). The classification of nutritional status of the sample based on BMI showed that 44 people had normal nutritional status (44.4%), 48 people were overweight (48.5%), and seven people were obese (7.1%). The test results showed a significant relationship between daily fluid intake and BMI (p-value = 0.007).
A Data-driven Platform for Simulating Vehicular Fog Computing Environment

Edge/fog computing is a key enabling technology in 5G and beyond for fulfilling the tight latency requirements of compute-intensive vehicular applications such as cooperative driving. Concerning the spatio-temporal variation in the vehicular traffic flows and the demand for edge computing capacity generated by connected vehicles, vehicular fog computing (VFC) has been proposed as a cost-efficient deployment model that complements stationary fog nodes with mobile ones carried by moving vehicles. Accessing the feasibility and the applicability of such hybrid topology, and further planning and managing the networking and computing resources at the edge, require deep understanding of the spatio-temporal variations in the demand and the supply of edge computing capacity as well as the trade-offs between achievable Quality-of-Services and potential deployment and operating costs. To meet such requirements, we propose in this paper an open platform for simulating the VFC environment and for evaluating the performance and cost efficiency of capacity planning and resource allocation strategies under diverse physical conditions and business strategies. Compared with the existing edge/fog computing simulators, our platform supports the mobility of fog nodes and provides a realistic modeling of vehicular networking with the 5G and beyond network in the urban environment. We demonstrate the functionality of the platform using city-scale VFC capacity planning as example. The simulation results provide insights on the feasibility of different deployment strategies from both technical and financial perspectives.
A STUDY OF WAVELET ENTROPY THEORYAND ITS APPLICATION IN ELECTRIC POWER SYSTEM FAULT DETECTION

The wavelet transform result data of electrical transient signals were abundant, and there was no quantitative method, so to mine and fuse one or a series of universal applicable quantities to detect system fault and stability was essential. Combining wavelet analysis with entropy theory by exploiting the time-frequency localization ability of wavelet analysis and the ability of entropy to token system state, three wavelet entropy concepts, i.e. wavelet energy entropy(WEE), wavelet time entropy(WTE), wavelet singularity entropy(WSE) were defined, and corresponding algorithms were put forward. The mechanism that these three wavelet entropies can token system fault were disclosed. Simulation results of two theoretic signals and transmission line PSCAD/EMTDC simulation signals indicate that wavelet entropy can reflect the system change, and they can eliminate the disturbance of noise and be applied to power system fault detection.
Anorectal and Genital Mucosal Melanoma: Diagnostic Challenges, Current Knowledge and Therapeutic Opportunities of Rare Melanomas

Mucosal melanomas (MM) are rare tumors, being less than 2% of all diagnosed melanomas, comprising a variegated group of malignancies arising from melanocytes in virtually all mucosal epithelia, even if more frequently found in oral and sino-nasal cavities, ano-rectum and female genitalia (vulva and vagina). To date, there is no consensus about the optimal management strategy of MM. Furthermore, the clinical rationale of molecular tumor characterization regarding BRAF, KIT or NRAS, as well as the therapeutic value of immunotherapy, chemotherapy and targeted therapy, has not yet been deeply explored and clearly established in MM. In this overview, focused on anorectal and genital MM as models of rare melanomas deserving of a multidisciplinary approach, we highlight the need of referring these patients to centers with experts in melanoma, anorectal and uro-genital cancers treatments. Taking into account the rarity, the poor outcomes and the lack of effective treatment options for MM, tailored research needs to be promptly promoted.
STUDY ON A PARALLEL-SERIES CONNECTION OF DUAL TWO-TRANSISTOR FORWARD CONVERTER MODULES WITH OUTPUT FILTER COUPLED-INDUCTOR

To overcome the drawbacks of low voltage gain of Two-Transistor Forward Converter(TTFC) and its low output voltage application, a novel Combined Two-Transistor Forward Converter(CTTFC) is proposed in this paper, which is connected in parallel at the input-end and in series by coupled-inductor at the output-end. While the coupling coefficient of the coupled-inductor is one, the CTTFC has the highest voltage gain, which is four times that of the TTFC. So the voltage stress of the secondary side freewheeling diodes of CTTFC is one fourth of the corresponding diode of the TTFC, which improve the reverse-recovery problem of the freewheeling diodes. As a result, the CTTFC is suitable for high output voltage applications, and the secondary side freewheeling diodes can be replaced by low voltage fast recovery ones.
My data, my choice?! The difference between fitness and stress data monitoring on employees' perception of privacy

Besides the vast distribution in the private sector, employers begin to integrate wearables in occupational health management (OHM). Through the implementation of 'stress' and 'fitness monitoring', organizations are able to invest in employees' health and well-being. While employees' consent is mandatory for the implementation, these, in turn, might perceive monitoring as a risk instead of realizing the benefits going along. By conducting an experimental study, we compare employees' perceived privacy risks/costs (PRC) and benefits (PBE) regarding the two monitoring cases. According to our results, employees interpret their stress data as rather sensitive while rating the PBE of fitness monitoring higher. Further, fair communication practices towards employees plays an essential role in the successful implementation of OHM. The research article provides theoretical and practical implications and sheds light on paths for further research regarding actual use behavior, international aspects, and employers' interests.
Physics-Based Learning for Robotic Environmental Sensing

—We propose a physics-based method to learn environmental ﬁelds (EFs) using a mobile robot. Common purely data-driven methods require prohibitively many measurements to accurately learn such complex EFs. Alternatively, physics-based models provide global knowledge of EFs but require experimental validation, depend on uncertain parameters, and are intractable for mobile robots. To address these challenges, we propose a Bayesian framework to select the most likely physics-based models of EFs in real-time , from a pool of numerical solutions generated ofﬂine as a function of the uncertain parameters. Speciﬁcally, we focus on turbulent ﬂow ﬁelds and utilize Gaussian processes (GPs) to construct statistical models for them, using the pool of numerical solutions to inform their prior mean. To incorporate ﬂow measurements into these GPs, we control a custom-built mobile robot through a sequence of waypoints that maximize the information content of the measurements. We experimentally demonstrate that our proposed framework constructs a posterior distribution of the ﬂow ﬁeld that better approximates the real ﬂow compared to the prior numerical solutions and purely data-driven methods.
Does Your Smile Mean That You're Happy? - a Multi-Channel Analysis of Emotional Reactions

In Information Systems (IS) research, emotions are primarily measured using facial expressions of participants or self-reported survey results. To unite both measurement foci, we analyze the impact of facial emotional reactions to computer-induced stimuli on self-reported evaluations towards the respective stimulus by using a multi-method experimental approach with multi-channel analysis. We collected emotional expressions of happiness of 176 participants using eye-tracker and webcam technology together with a post-experimental survey. We contribute to IS research by supplementing self-reported measures of emotion with a physical emotional measure in response to a system’s feature, and by relating these measured emotional physical responses to individual behavior.
DEVELOPMENT OF AN ADVANCED PLANNING TOOL FOR SUPPORTING THE CHOICE OF OPTIMAL INVESTMENTS AIMED AT OPTIMIZING THE INFRASTRUCTURE OF POWER DISTRIBUTION SYSTEMS IN FUTURE SCENARIOS

Given the decarbonization objectives set at the European level, the evolutionary scenarios of the electric system envisage a significant paradigm shift in the use of electricity. The expected evolution, which mainly involves users connected to the distribution networks, concerns the spread of small-scale distributed generation, the growth of the electricity demand and an increasingly dynamic electrical market. In this context, the Distribution System Operator (DSO) certainly plays a central role. The planning of the distribution network must consider this evolution, improving the traditional planning criteria and developing advanced methodologies of analysis. The recent technological evolutions in the field of data analysis allow us to evaluate different investment scenarios, aiming to identify the best interventions in terms of safety, reliability, and sustainability. In this paper we describe an advanced planning tool able to support the technical/economic analyses necessary for the choice of interventions on the distribution network. The algorithm, based on a genetic approach, exploits AI techniques for the multi-objective optimization of the configuration of the grid, aiming to simultaneously optimize different parameters (e.g., costs, quality of service and load KPIs). The method allows the evaluation of the technical benefit of the interventions and their prioritization according to technical/economic criteria. The optimized network proposed by the tool on a case study network have shown significant benefits in terms of technical needs satisfaction while keeping costs under control.
The M5 Accuracy competition: Results, ﬁndings and conclusions

This paper describes the M5 Accuracy competition, the ﬁrst of two parallel challenges of the latest M competition whose objective is to advance the theory and practice of forecasting. The M5 Accuracy competition focused on a retail sales forecasting application and extended the results of the previous four competitions by: (a) signiﬁcantly expanding the number of participating methods, especially those in the category of Machine Learning, (b) including exogenous/explanatory variables in addition to the time series data, (c) using grouped, correlated time series, and (d) focusing on series that display intermittency. The paper presents the background, design, and implementation of the competition, its results, the top-performing methods, as well as its major ﬁndings and conclusions. It also discusses the implications of its ﬁndings and suggests directions for future research.
An exact algorithm for constrained k-cardinality unbalanced assignment problem

An assignment problem (AP) usually deals with how a set of persons/tasks can be assigned to a set of tasks/persons on a one-to-one basis in an optimal manner. It has been observed that balancing among the persons and jobs in several real-world situations is very hard, thus such scenarios can be seen as unbalanced assignment models (UAP) being a lack of workforce. The solution techniques presented in the literature for solving UAP’s depend on the assumption to allocate some of the tasks to fictitious persons; those tasks assigned to dummy persons are ignored at the end. However, some situations in which it is inevitable to assign more tasks to a single person. This paper addresses a practical variant of UAP called k-cardinality unbalanced assignment problem (k-UAP), in which only of persons are asked to perform jobs and all the persons should perform at least one and at most jobs. The k-UAP aims to determine the optimal assignment between persons and jobs. To tackle this problem optimally, an enumerative Lexi-search algorithm (LSA) is proposed. A comparative study is carried out to measure the efficiency of the proposed algorithm. The computational results indicate that the suggested LSA is having the great capability of solving the smaller and moderate instances optimally.
NavierStokes Calculations of RotorAirframe Interaction in Forward Flight

A method for analyzing the mutual aerodynamic interaction between a rotor and an airframe model has been developed. This technique models the rotor implicitly through the source terms of the momentum equations. A three-dimensional, incompressible, laminar, Navier-Stokes solver in cylindrical coordinates was developed for analyzing the rotor-airframe problem. The calculations are performed on a simplified rotor-airframe model at an advance ratio of 0.1. The airframe surface pressure predictions are found to be in good agreement with wind tunnel test data. Results are also presented for velocity and pressure field distributions in the wake of the rotor.
PPAR Ligands Induce Antiviral Effects Targeting Perturbed Lipid Metabolism during SARS-CoV-2, HCV, and HCMV Infection

Simple Summary The current coronavirus disease 2019 pandemic turned the attention of researchers to developing novel strategies to counteract virus infections. Despite several antiviral drugs being commercially available, there is an urgent need to identify novel molecules efficacious against viral infections that act through different mechanisms of action. In this context, our attention is focused on novel compounds acting on nuclear receptors, whose activity could be beneficial in viral infections, including coronavirus, hepatitis C virus, and cytomegalovirus. Abstract The manipulation of host metabolisms by viral infections has been demonstrated by several studies, with a marked influence on the synthesis and utilization of glucose, nucleotides, fatty acids, and amino acids. The ability of virus to perturb the metabolic status of the infected organism is directly linked to the outcome of the viral infection. A great deal of research in recent years has been focusing on these metabolic aspects, pointing at modifications induced by virus, and suggesting novel strategies to counteract the perturbed host metabolism. In this review, our attention is turned on PPARs, nuclear receptors controlling multiple metabolic actions, and on the effects played by PPAR ligands during viral infections. The role of PPAR agonists and antagonists during SARS-CoV-2, HCV, and HCMV infections will be analyzed.
Control Techniques for CRM-Based High-Frequency Soft-Switching Three-Phase Inverter Under Unbalanced Grid Conditions

This article presents control techniques for the critical conduction mode(CRM) based high-frequency soft-switching three-phase inverter under unbalanced grid conditions. The soft-switching technique with silicon carbide (SiC) power devices allows the inverter to operate at hundreds of kHz with high efficiency and high power density. To extend the soft-switching technique to more practical cases, behaviors of the inverter under unbalanced grid conditions, specifically voltage sag, are investigated. During the voltage sag, the ac voltage at the grid becomes unbalanced. This requires unbalanced ac current reference to avoid output active power oscillation. With the unbalanced grid voltage and the ac current reference, the inverter loses the soft-switching capability. Continuous conduction mode (CCM) operation occurs where discontinuous conduction mode (DCM) operation is intended leading to large turn-on loss. To eliminate the CCM issue, two improved modulation techniques are proposed by using off-time extension in the CRM phase and by skipping pulses in the DCM phase. This article discusses how the CCM operation arises and details the proposed control methods. The performance of the proposed control is validated experimentally under a variety of grid imbalance cases with an SiC-based three-phase inverter prototype.
Factores asociados a esteatosis hepática no alcohólica en pacientes del área rural del cantón Chambo

La hepatopatía crónica más prevalente en el mundo es la esteatosis hepática no alcohólica. Así, se realizó una investigación con el objetivo de determinar los factores asociados a esa patología en pacientes atendidos en el Centro de salud tipo B Chambo, Ecuador, durante 2020. Se realizó un estudio con enfoque cuantitativo, de tipo no experimental, correlacional y retrospectivo. Las historias clínicas seleccionadas aportaron los datos de las variables de interés. La media de la edad de los involucrados fue de 54,43 ± 8,10 años. El 60,38% tenía hipertensión arterial, el 52,83% diabetes mellitus, el 62,26% sobrepeso u obesidad y el 49,06% dislipidemia, determinando que estas comorbilidades tuvieron una relación significativa con la enfermedad objeto de estudio, la que resultó más incidente en edades mayores de 50 años. Las personas sedentarias o con bajos niveles de actividad física mostraron de ALT y AST.
Negative association between anterior insula activation and resilience during sustained attention: an fMRI twin study

Abstract Background While previous studies have suggested that higher levels of cognitive performance may be related to greater wellbeing and resilience, little is known about the associations between neural circuits engaged by cognitive tasks and wellbeing and resilience, and whether genetics or environment contribute to these associations. Methods The current study consisted of 253 monozygotic and dizygotic adult twins, including a subsample of 187 early-life trauma-exposed twins, with functional Magnetic Resonance Imaging data from the TWIN-E study. Wellbeing was measured using the COMPAS-W Wellbeing Scale while resilience was defined as a higher level of positive adaptation (higher levels of wellbeing) in the presence of trauma exposure. We probed both sustained attention and working memory processes using a Continuous Performance Task in the scanner. Results We found significant negative associations between resilience and activation in the bilateral anterior insula engaged during sustained attention. Multivariate twin modelling showed that the association between resilience and the left and right insula activation was mostly driven by common genetic factors, accounting for 71% and 87% of the total phenotypic correlation between these variables, respectively. There were no significant associations between wellbeing/resilience and neural activity engaged during working memory updating. Conclusions The findings suggest that greater resilience to trauma is associated with less activation of the anterior insula during a condition requiring sustained attention but not working memory updating. This possibly suggests a pattern of ‘neural efficiency’ (i.e. more efficient and/or attenuated activity) in people who may be more resilient to trauma.
The Role of Non-Bank Financials in the Formation of Long-Term Resources for Economic Growth in Russia

The development of the activities of non-bank financial institutions that accumulate the resources of the national savings system on a long-term basis is seen as a factor in increasing investment in the Russian economy and its growth rates. When carrying out the study, we used general scientific methods, methods of structural, weigh, and dynamic analysis, and comparisons of performance indicators of non-bank financial institutions. Problems in the activities of organizations in the non-banking sector of the Russian financial market are predetermined by the parameters and trends in the development of the socio-economic situation in Russia, including insufficient efficiency of regulatory practices. The positive dynamics of the development of non-bank financial intermediaries is qualified as unstable; it is not supported by the solution of the structural and institutional problems of the Russian economy. In view of this, an increase in their role in the redistribution process is associated both with decisions of a more general order and with the improvement of the regulatory and supervisory practices implemented by the Bank of Russia. The solution to the identified problems in the development of the non-banking segment of the financial market should be aimed at turning it into an effective mechanism for capital formation to ensure economic growth.