Miracle-dz/UniFAR-FTUs huggingface dataset:
Islanding Detection of Inverter Based DG Unit Using PV System

Distributed generation (DG) units are rapidly increasing and most of them are interconnected with distribution network to supply power into the network as well as local loads Islanding operations of DG usually occur when power supply from the main utility is interrupted due to several reasons but the DG keeps supplying power into the distribution networks. a new method for islanding detection of inverter-based distributed generation (DG). Although active islanding detection techniques have smaller non detection zones than passive techniques, active methods could degrade the system power quality and are not as simple and easy to implement as passive methods. The phenomenon of unintentional islanding occurs when a distributed generator (DG) continues to feed power into the grid when power flow from the central utility source has been interrupted. A simple islanding detection scheme has been designed based on this idea. The proposed method has been studied under multiple-DG operation modes and the UL 1741 islanding tests. The simulations results, carried out by MATLAB/Simulink, show that the proposed method has a small Non detection zone.
Associated Factors with Perceived Fear of COVID-19 among Vietnamese Hospital Healthcare Workers during Fourth Wave of the COVID-19 Pandemic: Policy Implications for Interconnected and Social- and Personal-Based Health Support

(1) Background: The present study measures the fear of COVID-19 among hospital healthcare workers and identifies several factors associated with increasing fear of COVID-19. (2) Methods: A cross-sectional, hospital-based survey was conducted on healthcare workforce recruited from the National Hospital of Tropical Diseases from 1 October 2021 and 20 October 2021. We selected the participants who have been directly involved in diagnosing, treating, or providing nursing care to patients with COVID-19. The primary data was collected via sending the invitation directly to the participants, utilizing structured self-completed questionnaires. The seven-item fear of COVID-19 scale was used to measure the data. The responses of 208 hospital healthcare workers were included in the final analysis. (3) Results: Total score of COVID-19 fear was 19.62 (SD = 5.22). The COVID-19 fear score of 7 items ranged from 2.38 (SD = 0.83) to 3.21 (SD = 0.96). The lowest and highest scores were the item ‘My hands become clammy when I think about Corona’ and the item ‘I am most afraid of corona’ was the highest, respectively. Linear regression of the COVID-19 fear showed that the factors positively correlated with the fear of COVID-19 among hospital healthcare workers were: being influenced by the community (p = 0.001), feeling at very high risk of COVID-19 (p = 0.03), and experiencing traumatic stress with an academic event (p = 0.042). (4) Conclusions: Although these findings merit further elaboration, these preliminary findings suggest relatively great fear of the COVID-19 pandemic among Vietnamese hospital healthcare workers and that social and personal connections are necessary for maintaining the mental wellbeing.
Higher order s-to-z mapping functions and their application in digitizing continuous-time filters

A family of higher order numerical integration formulas and their corresponding s-to-z mapping functions are presented. Two of the main problems are stability and handling discontinuous inputs. The stability question is resolved by analyzing the stability regions of the mapping functions relative to the Nyquist sampling criterion. Sources of error in the accuracy of the output of digitized filters relative to their continuous-time counterparts are explored. Techniques for digitizing continuous-time filters, using the mapping functions, are developed for reducing different sources of error, including error resulting from discontinuous inputs. >
ARTIFICIAL INTELLIGENCE TO EVALUATE THE SHORT-TERM PROGRESS OF DEVICE ASSISTED SCOLIOSIS THERAPY ON THE EXAMPLE OF FED METHOD

X-Ray or video raster stereography are used for the progress control of the FED therapy but applied only at intervals of months. A short-term evaluation would allow to adjust the therapy parameters based on the individual therapy progression and could also provide a direct feedback for patient. Therefore, this study aims to isolate parameters for a short-term progression monitoring by applying machine learning algorithms on a set of 130 posture characteristics. A measuring procedure using the DIERS formetric 4D optical measuring system was developed and validated on six patients. The measuring procedure was repeated eight times (four days, each morning and afternoon). Eight parameters were evaluated. The Wilcoxon signed rank test and the Friedman test were used to verify the statistical significance. In order to identify small changes in posture correlating with the applied treatment a hierarchical cluster analysis was performed. The evaluation shows that the parameters pelvic tilt, kyphosis angle and lordosis angle changed significantly between the individual measuring points, but not across all eight parameters. The data is highly dependent on the daily form and cooperation of the patient. The cluster classification is not determined on the basis of the four measurement points, but on the basis of patient individuality. Hierarchical clustering can classify new patients to match them with successful treatment plans of similar cases. By further optimizing the setting parameters
Electromagnetic Analysis of Frequency Selective Surfaces Using the SSED Method

The Simplified sub-entire domain (SSED) basis function method has been introduced and modified to analyze some planar and curved Frequency selective surfaces (FSSs) with finite size. The number of unknowns and memory consumption of the methods are discussed in detail. The reflection coefficients and transmission coefficients are given, which agree well with the reference results.
IN VITRO ANTI-NEUROINFLAMMATORY EFFECT OF GENISTEIN (4',5,7-TRIHYDROXYISOFLAVONE) ON MICROGLIA HMC3 CELL LINE, AND IN SILICO EVALUATION OF ITS INTERACTION WITH ESTROGEN RECEPTOR-β

Objective: This study was aimed to evaluate the role of genistein or 4',5,7-trihydroxyisoflavone as a phytoestrogen in the treatment of estrogen deficiency-induced neuroinflammatory. The specific objectives of this study were to determine the anti-neuroinflammatory effect of genistein through measurement of MHC II and Arg1 expressions on microglia HMC3 cell line, as well as to prove that the effect occurs in an ER-dependent manner, through the measurement of free-ERβ expression. Methods: The cells were cultured in 24-well microplates, induced with 10 ng IFN-γ, and incubated for 24 h to activate the cell to M1 phenotype which has pro-inflammatory characteristics. Genistein with a concentration of 50 μM was added to the cells. The expression of MHC II, Arg1, and free-ERβ as markers was tested through an immunocytochemistry method and measured using the CLSM instrument. In silico approach was also conducted to determine the interaction between genistein and ERβ, compared to 17β-estradiol. Genistein structure was prepared with Avogadro 1.0. 1, and molecular docking was done using PyRx 0.8 software. Biovia Discovery Studio Visualizer 2016 was used to visualize the structure of genistein against 3OLS protein. The physicochemical characteristics of genistein were analyzed using the SwissADME web tool. Results: Genistein can decrease MHC II expression and increase Arg1 expression in microglia HMC3 cells compared to negative controls (p<0.005), with expression value of 472.577±26.701 AU and 114.299±6.578 AU. But, genistein cannot decrease the free-ERβ expression in cells (p<0.005). The results of in silico analysis showed that genistein is an ERβ agonist. Conclusion: Genistein shows anti-neuroinflammatory effects by decreasing the MHC II expression and increasing Arg1 expression in the microglia HMC3 cell line. However, this effect does not occur through the binding of genistein to ERβ, but it is likely to occur through the binding of genistein with other types of ER.
Multidimensional Scaling and Application in Traffic Jam Prediction

Many methods thus have been proposed to predict traffic conditions. However, it is difficult to accurately predict traffic jam, because it requires a wide range of knowledge such as statistics and informational technology. It is known that the probability of traffic jam can be evaluated by travel times of passing cars in a location of the motorway. In this paper, we restrict our attention to finding more efficient statistical methods through comparing models. For this reason, we used Multidimensional Scaling statistical methods to study the relationship between traffic conditions and travel time in different locations and times. This work aims at applying basic models to forecast traffic conditions.
Optical fibre sensor for fuel cell and other fluid concentration measurement

This work describes the development of a fibre-optic fluid concentration sensor that is based on evanescent field absorption. In addition, a second optical sensor principle is investigated by means of the development of a novel type of low insertion loss fibre-cavity. The absorption sensor probe is evaluated on several widely applied liquid mixtures, i.e., the aqueous solutions of acetone, ethanol, methanol, 1-propanol and 2-propanol. The need to efficiently monitor these fluids emerges from the ever increasing reseach activity in liquid feed fuel cells which operate on, amongst others, the four latter alcohol/water mixtures. A comprehensive investigation of the influence of different fibre parameters and geometries (e.g. fibre core radius, numerical aperture and bend radius) on the sensitivity of various sensor probes is carried out theoretically as well as experimentally. Broadband measurements in the visible wavelength area are carried out in order to select the most suitable wavelength for further experiments with a low cost LED-based hardware setup. It will be shown that the novel meander-shaped sensor probe exceeds the sensitivity of a standard U-bend sensor almost 20-fold. Fibre-cavities offer the possibility to operate absorption based optical fibre sensors in a particular configuration, the so called ringdown scheme. Current approaches suffer from high insertion loss and costly as well as stationary equipment. The cavity proposed in this investigation shows how those drawbacks can be overcome. It is treated separately in order to estimate the gain in sensitivity it can provide, independent of the type of sensor that is inserted into the cavity. The novel design reduces the insertion loss of common passive fibre-cavity designs, i.e. close to 100%, to normal fibre coupling loss. The aim of this work is to provide a fundamental investigation into a highly sensitive refractive index sensor solution that is applicable to a wide range of liquid mixtures rather than being specifically designed for a single purpose. The application range could be further extended to areas where existing sensors are based on the same elementary optical sensor principle such as pH monitoring. It will be shown that the proposed sensor solution combines high sensitivity with small sensor dimensions, a fast response time, low production and operational cost
Propriedades de fluxo de produtos pulverulentos alimentícios

Trying to provide more information about the flow of industrial solid materials, this research determined the flow properties of four powdered products manufactured by food industries and examined their levels of flowability, depending on the time of consolidation. The tests were conducted in the Jenike shear cell machine and consolidation bench. For determination of the flow index (FFC) and minimum diameter of the discharge orifice (D) Jenike's methodology was used and for minimum angle of the hopper, the Enstad's method was adopted. It may be concluded that the consolidation time studied did not affect the flow properties of powdered materials and the minimum inclination of hopper angle was 60o. It was possible to determine the discharge orifice by Jenike's method only in case of wheat flour with a minimum value of 1.1 m for 24-hour period of consolidation.
Cooperators Involvement and Satisfaction on Cooperative Society Housing Activities in Jos Plateau State, Nigeria

© 2021 The Authors. This article is licensed under a Creative Commons Attribution 4.0 License Abstract. This research aims to assess cooperators involvement and satisfaction with housing activities in Plateau State, Nigeria, to measure their degree of influence on housing activities. The study was based on various questionnaire survey methods conducted on institution-based cooperative societies engaged in suitable housing activities. The data was collected from Jos University Teaching Hospital JUTH multipurpose cooperative society cooperators and analysed using mean ranking descriptive statistical tools. Multiple regression was conducted. Regression model summary and the ANOVA result were obtained. The model produced an overall R-value of 0.421 and an R-value of 0.177 with F-statistics of 32.685, which are significant as indicated by a p-value of 0.000. The two independent variables included in the study explain about 17.7 % of the variation in housing activities. This shows that both involvement and satisfaction of cooperators influenced housing activities. The study recommended that cooperators be more involved in all housing activities from the initial stage to the completion for a more positive outcome and ensure their utmost satisfaction based on their housing demand. This will motivate them and increase patronage of the cooperative society for their housing needs at all times.
Discovering Tonal Profiles with Latent Dirichlet Allocation

Music analysis, in particular harmonic analysis, is concerned with the way pitches are organized in pieces of music, and a range of empirical applications have been developed, for example, for chord recognition or key finding. Naturally, these approaches rely on some operationalization of the concepts they aim to investigate. In this study, we take a complementary approach and discover latent tonal structures in an unsupervised manner. We use the topic model Latent Dirichlet Allocation and apply it to a large historical corpus of musical pieces from the Western classical tradition. This method conceives topics as distributions of pitch classes without assuming a priori that they correspond to either chords, keys, or other harmonic phenomena. To illustrate the generative process assumed by the model, we create an artificial corpus with arbitrary parameter settings and compare the sampled pieces to real compositions. The results we obtain by applying the topic model to the musical corpus show that the inferred topics have music-theoretically meaningful interpretations. In particular, topics cover contiguous segments on the line of fifths and mostly correspond to diatonic sets. Moreover, tracing the prominence of topics over the course of music history over ∼ 600 years reflects changes in the ways pitch classes are employed in musical compositions and reveals particularly strong changes at the transition from common-practice to extended tonality in the 19th century.
Modeling of Moisture Behavior of Wood Planks in Nonvented Flat Roofs

A computer model was extended and adapted to simulate the hygrothermal behavior of building envelope-wood components. The model was used to predict moisture movement in wood planks forming the decks of nonvented flat roofs insulated with cellulose. The gradient of water potential was considered as the driving force for moisture movement in wood. The model required the determination of convective heat- and mass-transfer coefficients, the sorption curves, the effective water conductivity for different wood species, and the hygrothermal conditions within the assembly to characterize the mass-conservation equation. Once these parameters were integrated in the computer model, this approach was then validated by carrying a simulation of the drying process of wood planks using experimental data from a large-scale test.
THE EFFECTS OF CONCEPT CARTOONS AND ARGUMENTATION BASED CONCEPT CARTOONS ON STUDENTS' ACADEMIC ACHIEVEMENTS

Although "Reproduction, Growth, and Development in Living Things" (RGDLT) is a core topic in the Turkish science curriculum, it is known that students have difficulties in understanding. Integrating concept cartoons and argumentation into the teaching of this unit has the potential to promote students' interest and understanding. This research is the first to compare the effects of concept cartoons and argumentation-based concept cartoons on students' academic achievement in teaching sixth grade RGDLT subjects. The research was performed with two experimental groups and one control group in a secondary school in Turkey. A quasi-experimental research design was used in the research. Analysis of the post-test results revealed that the success of the group using concept cartoons was higher than the control group, but more importantly, the success of the group using argumentation-based concept cartoons was higher than the group using concept cartoons. The results of this research indicate that the academic achievement of students can be increased significantly when concept cartoons and argumentation-based concept cartoon activities are used in addition to the constructivist methods in teaching these subjects. The results of the research serve as a guide for teachers and researchers interested in teaching science and biology subjects. Keywords: argumentation, biology education, concept cartoons, living things, quasi-experimental research
Measuring National Well-being - Where we Live - 2012

Measuring National Well-being - Where we Live - 2012, by Chris Randall, Office for National Statistics (2012). When people were asked what mattered most for the measurement of National Well-being, ‘where we live’ was one aspect that people considered as most important. This article on where we live is part of a series which aims to explore in more detail the different domains that have been considered as important for the measurement of National Well-being. Where we live can have a significant impact on our sense of well-being. Homes which meet our individual needs and provide us with shelter and security are made all the better by having easy access to local shops and services, and green spaces to walk or play in, which in turn can help people to live healthier and happier lives.
A novel high-resolution gridded precipitation dataset for Peruvian and Ecuadorian watersheds – development and hydrological evaluation

A novel approach for estimating precipitation patterns is developed here and applied to generate a new hydrologically corrected daily precipitation dataset, called RAIN4PE (for ‘Rain for Peru and Ecuador’), at 0.1° spatial resolution for the period 1981-2015 covering Peru and Ecuador. It is based on the application of a) the random forest method to merge multi-source precipitation estimates (gauge, satellite, and reanalysis) with terrain elevation, and b) observed and modeled streamflow data to firstly detect biases and secondly further adjust gridded precipitation by inversely applying the simulated results of the eco-hydrological model SWAT (Soil and Water Assessment Tool). Hydrological results using RAIN4PE as input for the Peruvian and Ecuadorian catchments were compared against the ones when feeding other uncorrected (CHIRP and ERA5) and gauge-corrected (CHIRPS, MSWEP, and PISCO) precipitation datasets into the model. For that, SWAT was calibrated and validated at 72 river sections for each dataset using a range of performance metrics, including hydrograph goodness of fit and flow duration curve signatures. Results showed that gauge-corrected precipitation datasets outperformed uncorrected ones for streamflow simulation. However, CHIRPS, MSWEP, and PISCO showed limitations for streamflow simulation in several catchments draining into the Paċific Ocean and the Amazon River. RAIN4PE provided the best overall performance for streamflow simulation, including flow variability (low-, high- and peak-flows) and water budget closure. The overall good performance of RAIN4PE as input for hydrological modeling provides a valuable criterion of its applicability for robust countrywide hydrometeorological applications, including hydroclimatic extremes such as droughts and floods.
An energy efficiency program analysis to understand the gaps between ex-ante and ex-post evaluations

There is a gap between whole house energy consumptions calculated by engineering models and observed consumptions as reviewed in literature. This is especially true after retrofitting actions but the reasons are not well understood. Is it due to assumptions made in models, to uncertainties on input data, notably concerning behaviour, or to a no controllable random error? In order to tackle this problem, a statistical modeling approach has been developed to study deviations before and after refurbishment on a panel of refurbished dwellings in France of which annual consumptions “before” and “after” are known. In the first step, a statistical model of deviations between the consumptions calculated by an engineering model and observed ones before retrofitting is established. Explanatory variables are building typology, energy systems data and household behaviour data. This model allows to identify the main sources of deviations before refurbishment and to quantify their effects. In the second step, a similar statistical model of the deviations between simulated and observed consumptions after retrofitting shows that the variables linked with the refurbishment (i.e. type of measure…) do not explain errors, excepting set point temperature change. But the observed effect (the error decreases with an increase of set point temperature after retrofitting) does not go to the logically expected direction. A modeling flaw seems be partly the cause for this result. Uncertainties of this work and prospects are also discussed.
Properties of the power conditioning system with a five-level cascaded converter and supercapacitor energy storage

The paper presents the power conditioning system (PCS) with a five-level cascaded H-bridge converter and supercapacitor energy storage. The paper focuses on such properties of a power electronic converter as its operation, power losses, start-up as well as the DC-link voltage balancing method and controller. A laboratory model of the PCS and its test results have been presented.
Determination of ride comfort thresholds based on international roughness index for asphalt concrete pavements

ABSTRACT The study is aimed to mathematically model the relationship between the amount of whole-body vibration exposed in a passenger car type vehicle and the ride speed of the vehicle in the same section and the International Roughness Index (IRI), which is used as a pavement performance indicator. Vibration measurements were analysed according to the evaluation method determined in the ISO 2631 standard, and frequency-weighted root-mean-square acceleration (aw) values were obtained in the vertical direction. Mathematical relationships between real measurement data performed in 1114 road sections were investigated using regression analysis, artificial neural networks (ANN) and Adaptive Neural Fuzzy Inference System (ANFIS) modelling techniques. The models' performance levels were determined using comparison metrics, and it was determined that ANFIS was the model with the best goodness of fit, with the regression coefficient 0.955, mean absolute error (MAE) 0.013, and root mean squared error (RMSE) 0.020. The threshold values affecting the ride comfort of IRI and the ride comfort values corresponding to the IRI limit values recommended by the Federal Highway Administration (FHWA) were determined through the ANFIS mathematical model. Then, a sensitivity analysis was conducted to determine the effects of a certain increase in the IRI value on discomfort.