Miracle-dz/UniFAR-FTUs huggingface dataset:
Model Tingkat Kelancaran Pembayaran Kredit Bank Menggunakan Model Regresi Logistik Ordinal (Studi Kasus: Bank Rakyat Indonesia Tbk Unit Pasar Bintuhan)

Untuk mengantisipasi penyelesaian kredit macet pada PT. Bank Rakyat Indonesia (BRI) Tbk unit Pasar Bintuhan perlu dicari faktor-faktor yang dijadikan indikator untuk analisis kelayakan pemberian kredit menggunakan model Regresi Logistik Ordinal. Model penduga tingkat kelancaran pembayaran kredit modal usaha yaitu: L j ( x ) = konst_ j - 2,695* [kelamin=1] -0,060 *Umur -0,789*Jml_tanggungan + 5,340E-7*Pinjaman -7,484E-8*Agunan; dimana tingkat kelancaran lancar Konst_j nya adalah 0,902, sedangkan untuk tingkat kelancaran dalam pengawasan khusus Konst_j nya adalah 6,614. Peluang seorang debitur tersebut untuk masuk kategori lancar adalah 0,6013276, kategori dalam pengawasan khusus adalah sebesar 0,396486, dan kategori macet adalah sebesar 0,002186. Maka dapat disimpulkan bahwa pinjaman seorang debitur tersebut berpeluang besar untuk menjadi kategori lancar.
Physics-Enhanced PCA for Data Compression in Edge Devices

In smart cities, tremendous data are generated with edge devices continuously for scientific applications, such as structural health monitoring (SHM), leading to a high bandwidth burden to edge devices. Data compression is a typical technique for reducing data size and improving transmission efficiency. However, their operations for distinguishing redundant data might be unapplicable for a domain-specific scientific analysis and distort physical quantities of raw data (i.e., mode shapes of vibration data). Besides, they are too compute-intensive to be executed in resource-constraint edge devices. In this paper, we leverage physical knowledge to enhance a lightweight data compression method for edge devices in maintaining physical quantities. In particular, we propose physics-enhanced PCA for compressing data in a dynamic system — compressing the vibration data of a structure in the context of SHM. Physical knowledge is identified from a structure and guides the compression process to preserve the mode shape, an significant physical quantity for structures. We have formally analyzed the effectiveness of our approach and performed experiments to show that physical knowledge is essential for preserving mode shapes. Concretely, experiments in numerical and real-world structures show that physics-enhanced PCA can improve the accuracy by up to 56% compared with alternative baseline.
EDITING GENOMES VIA CRISPR/CAS9 AND APPLICATIONS IN MAIZE IMPROVEMENT

The CRISPR/Cas9 system is a gene editing method capable of accurately locating and altering a specific sequence of a genome. Currently, this technique stands out as a promising biotechnological tool for the improvement of different crops, overcoming the limitations of conventional breeding methods and accelerating the development of plants’ agronomic characteristics. The basic principle of genome editing via CRISPR is to cause a double-stranded DNA break at a predetermined location by a sgRNA (single guide RNA) and through internal repair mechanisms cause mutations and, consequently, genetic variability. In prokaryotic organisms, it is an immune system that naturally protects against viral infection and has been modified to create different applications in higher organisms in the field of medicine and agriculture. In agriculture, it has been used in a large number of mono and dicotyledonous plants, including those of great commercial value such as soybean, cotton and maize. In maize, this technique has been used as a biotechnological tool for increasing production, quality, nutritional value, tolerance to biotic and abiotic stresses. CRISPR-Cas9 technology has enormous potential to contribute to increased food production with great benefit to the environment. This review explores the bases for the use of CRISPR/Cas9 technology to generate genetic variability and its use in the development of maize cultivars with better agronomic characteristics.
Professional quality of life of nurses in critical care units: Influence of demographic characteristics

Background Professional quality of life, measured as compassion satisfaction, is a prerequisite for nurses working in intensive care units where patients rely on their care. Nurses who experience compassion satisfaction, or good professional quality of life, engage enthusiastically with all work activities and render quality patient care. In contrast, compassion fatigue eventually leads to disengagement from work activities and unsatisfactory patient outcomes. In this study, we described the demographic factors influencing professional quality of life of intensive care nurses working in public hospitals in Gauteng, South Africa (SA), during the first wave of the COVID-19 pandemic. Objectives To describe the demographic factors associated with professional quality of life of critical care nurses working in Gauteng, SA Methods In this cross-sectional study, we used total population sampling and invited all nurses who had worked for at least 1 year in one of the critical care units of three selected public hospitals in Gauteng to participate. One-hundred and fifty-four nurses responded and completed the ProQol-5 tool during the first wave of the COVID-19 pandemic. Data were analysed using descriptive and inferential statistics. Results The nurses’ average age was 45 years, and 59.1% (n=91) had an additional qualification in critical care nursing. Most of the nurses had a diploma (51.3%; n=79), with a mean work experience of 12.56 years. The main demographic variables that influenced professional quality of life were years of work experience (p=0.047), nurses’ education with specific reference to a bachelor’s degree (p=0.006) and nurse-patient ratio (p<0.001). Conclusion Nurses working in critical care units in public hospitals in Gauteng experienced low to moderate compassion satisfaction, moderate to high burnout and secondary traumatic stress, suggesting compassion fatigue. The high workload, which may have been associated with the COVID-19 pandemic, influenced nurses’ professional quality of life. Contributions of the study This study reports on the important problem of compassion fatigue and burnout amongst South African ICU nurses working in the public sector. Associated factors were identified, which should be addressed to improve nurses’ wellbeing.
Deterministic Operating Strategy for Multi-objective NMPC for Safe Autonomous Driving in Urban Traffic

In this paper, we introduce a deterministic operating methodology based on finite-state automata to employ multi-objective Nonlinear Model Predictive Control (NMPC) in autonomous driving applications. We begin with discussing the system’s dynamical behavior and the proposed constraints to guarantee safe driving. Then, we examine a typical urban scenario and dissect it into a set of interacting sequences, so that we develop and fine-tune separate MPC-based controllers for each of these sequences. Finally, we introduce a Finite-State Machine (FSM) that analyzes the current driving situation and accordingly selects the appropriate controller to compute the optimal control action. This approach is numerically simulated and tested with the software OCPID-DAE1 and results show its success in accordance with multi-objective NMPC.
Squalene Monooxygenase Gene SsCI80130 Regulates Sporisorium scitamineum Mating/Filamentation and Pathogenicity

Sugarcane is an important sugar crop and energy crop worldwide. Sugarcane smut caused by Sporisorium scitamineum is a serious fungal disease that occurs worldwide, seriously affecting the yield and quality of sugarcane. It is essential to reveal the molecular pathogenesis of S. scitamineum to explore a new control strategy of sugarcane smut. Based on transcriptome sequencing data of two S. scitamineum strains Ss16 and Ss47, each with a different pathogenicity, our laboratory screened out the SsCI80130 gene predicted to encode squalene monooxygenase. In this study, we obtained the knockout mutants (ΔSs80130+ and ΔSs80130−) and complementary mutants (COM80130+ and COM80130−) of this gene by the polyethylene glycol-mediated (PEG-mediated) protoplast transformation technology, and then performed a functional analysis of the gene. The results showed that the deletion of the SsCI80130 gene resulted in the increased content of squalene (substrate for squalene monooxygenase) and decreased content of ergosterol (the final product of the ergosterol synthesis pathway) in S. scitamineum. Meanwhile, the sporidial growth rate of the knockout mutants was significantly slower than that of the wild type and complementary mutants; under cell-wall stress or oxidative stress, the growth of the knockout mutants was significantly inhibited. In addition, the sexual mating ability and pathogenicity of knockout mutants were significantly weakened, while the sexual mating ability could be restored by adding exogenous small-molecular signal substance cAMP (cyclic adenosine monophosphate) or tryptophol. It is speculated that the SsCI80130 gene was involved in the ergosterol biosynthesis in S. scitamineum and played an important role in the sporidial growth, stress response to different abiotic stresses (including cell wall stress and oxidative stress), sexual mating/filamentation and pathogenicity. Moreover, the SsCI80130 gene may affect the sexual mating and pathogenicity of S. scitamineum by regulating the ergosterol synthesis and the synthesis of the small-molecular signal substance cAMP or tryptophol required for sexual mating. This study reveals for the first time that the gene encoding squalene monooxygenase is involved in regulating the sexual mating and pathogenicity of S. scitamineum, providing a basis for the molecular pathogenic mechanism of S. scitamineum.
Effects of Red Ginseng Byproducts on Rumen Fermentation, Growth Performance, Blood Metabolites, and mRNA Expression of Heat Shock Proteins in Heat-Stressed Fattening Hanwoo Steers

The objective of this study was to evaluate the effects of dietary supplementation with red ginseng byproduct (RGB) on rumen fermentation, growth performance, blood metabolites, and mRNA expression of heat shock proteins (HSP) in fattening Hanwoo steers under heat stress. Two experimental total mixed rations (TMR) were prepared: (1) a TMR meeting the requirement of fattening beef having an average daily gain (ADG) 0.8 kg/day (CON) and (2) a TMR that included 2% RGB on a dry matter (DM) basis (GINSENG). In vitro rumen fermentation and in vivo growth experiments were conducted using two experimental diets. A total of 22 Hanwoo steers were distributed to two treatments (CON vs. GINSENG) in a completely randomized block design according to body weight (BW). The experiment was conducted during the summer season for five weeks. The final BW, ADG, DM intake, and feed conversion ratio did not differ between treatments in the growth trial. In the mRNA expression results, only HSP 90 showed an increasing tendency in the GINSENG group. The use of 2%DM RGB did not improve the growth performance or alleviate heat stress in fattening Hanwoo steers during the summer season.
The Relationship between Habitual Coffee Drinking and the Prevalence of Metabolic Syndrome in Taiwanese Adults: Evidence from the Taiwan Biobank Database

Previous studies revealed inconsistent results between coffee drinking and metabolic syndrome (MetS). The aim of the study was to evaluate the relationship between habitual coffee drinking and the prevalence of MetS among men and women. We conducted a nationwide, cross-sectional study using 23,073 adults obtained from the Taiwan Biobank database (mean ± SD (range) age, 54.57 ± 0.07 (30–79) years; 8341 men and 14,731 (63.8%) women). Adults who drank more than one cup of coffee per day (n = 5118) and those who drank less than one cup per day (n = 4515) were compared with nondrinkers (n = 13,439). Multivariate logistic regression models were used to evaluate the risk of MetS between the two groups. Separate models were also estimated for sex-stratified and habitual coffee-type-stratified (black coffee (BC), coffee with creamer (CC), and coffee with milk (CM)) subgroup analyses. The MetS diagnosis was based on at least three of the five metabolic abnormalities. Coffee drinkers (≥1 cup/day) had a significantly lower prevalence of MetS than nondrinkers (AOR (95% CI): 0.80 (0.73–0.87)). Women who drank any amount of coffee and any type of coffee were more likely to have a significantly lower prevalence of MetS than nondrinkers. Only men who drank more than one cup of coffee per day or black coffee drinkers were more likely to have a lower prevalence of MetS. Our study results indicate that adults with habitual coffee drinking behaviors of more than one cup per day were associated with a lower prevalence of MetS. Moreover, women could benefit from habitual coffee drinking of all three coffee types, whereas men could only benefit from drinking BC.
AC 2011-1653: DESIGN AND EVALUATION OF A 3D CONSTRUCTION MOBILE GAME FOR THE IPHONE/IPOD TOUCH PLATFORM

The work presented in this paper describes the design and user evaluation of a 3D construction mobile game. The game, iCube, works on iPhone and iPod touch devices consisting of an application where the student performs a set of exercises about building models with unit-sized cubes in a 3D environment. There are two game modes: training and competition. The training exercises are designed so that the user can get used to the game environment. The competitions are sets of tasks, created by the teacher or administrator, which the user has to download, by logging in to the system with a username and password. Competition results are sent to the server with data on times and scores. In this work, a trial version was brought out and evaluated by twenty two testers. Users were asked to complete the training tasks available in the device as well as two competitions. About positive tool’s aspects they pointed out that game is useful for improvement of spatial ability being a fun application. However about negative aspects of it, some difficulties arose with use of tactile screen as the fingerprints caused problems while interacting with the game’s 3D environment. The results revealed that it’s necessary having in mind this item in games’ design where screen action is continuous.
Assessment on the Fermentation Quality and Bacterial Community of Mixed Silage of Faba Bean With Forage Wheat or Oat

Faba bean (Vicia faba L.), although a kind of high-quality and high-yield forage, could hardly achieve a great quality of silage because of its high buffering capacity. Mixed silage of faba bean with forage wheat (Triticum aestivum L.) or oat (Avena sativa L.) at different ratios could improve the fermentation quality and bacterial community. Compared with 100% faba bean silage (BS), mixed silage improved the fermentation quality, not only increased lactic acid production and reduced pH, but reduced the production of propionic acid and ammonia nitrogen. The chemical compositions of faba bean with forage wheat (BT) mixed silage were better than that of faba bean with oat (BO) mixed silage, and that of 3:7, 5:5 (fresh matter basis) mixing ratios were better than 1:9. However, the fermentation quality of BO mixed silage was better than that of BT, and that of 3:7 mixed silage (BO30) was the best overall. Analysis of the bacterial community showed that mixed silage increased the relative abundance of lactic acid bacteria after ensiling, and the relatively higher abundance of Lactobacillus showed the inhibitory effects on the proliferation of Serratia and Hafnia_Obesumbacterium, so that it alleviated their negative effects on silage and stabilized the fermentation quality. This present study exhibited that mixed silage of faba bean with forage wheat or oat not only had significant effects on chemical compositions and fermentation quality of materials but modified bacterial community so that improved the fermentation quality effectively. The mixed silage of 30% faba bean with 70% oat (BO30) is recommended in the faba bean mixed silage.
A Study on Design Guidelines of Learning Analytics to Facilitate Self-Regulated Learning in MOOCs *

The purpose of this study was to develop design guidelines on the learning analytics which can help to promote students’ self-regulated learning (SRL) strategies in MOOCs learning environments. First of all, to develop the first draft of design guidelines, relevant literature review and case analysis on current MOOCs platforms such as edX, K-MOOC, Coursera, Khan Academy and FutureLearn were conducted. Then, to validate the design guidelines, expert reviews (validation questionnaires and in-depth interviews) and learner evaluation (in-depth interviews) were conducted. Through the recursive validation, the design guidelines were finalized. Overall, the final version of design guidelines on learning analytics to facilitate SRL strategies was suggested. The final design guidelines consist of 15 items in 10 categories related to the information analyzed based on individual student’s learning behaviors and activities on MOOCs environments. Moreover, the results of interview also revealed that the social comparisons, learning progress reports, and personalization might contribute to the improvements of their SRL competences. This study has an implication that MOOCs could offer a higher success or completion rate to students with low SRL skills by taking advantage of the information on learning analytics
An Efficient Approximate Method for Scattering Response from Infinite Arrays of Nonlinearly Loaded Antenna in the Frequency Domain

In this paper, different arrangements of infinite arrays of nonlinearly loaded antennas are analyzed in the frequency domain by an efficient approximate method and compared with the exact one which are respectively based on the nonlinear current and harmonic balance techniques. In one hand, although the exact method is suitable for strongly nonlinear load, it is suffering from gradient operation and initial guess in the iteration process especially under multi-tone excitations. On the other hand, although the approximate method is very efficient, it is limited to weakly nonlinear loads and low-valued incident waves. Finally, acceptable ranges for application of the approximate method versus different parameters such as nonlinearity effect of the load and the magnitude of incident wave are extracted.
Revealing Genomic Footprints of Selection for Fiber and Production Traits in Three Indian Sheep Breeds

ABSTRACT The present broad range of sheep phenotypic variation is the consequence of selection for various production characteristics such as wool, milk, meat, and natural adaptability to diverse situations. In the current study, the genomic data of 79 animals from three Indian sheep breeds (Changthangi, Deccani, and Garole) were explored to decipher regions under positive selection for various productive traits using various statistical tools. We found 61, 102 regions using Tajima’s D, CLR and 58, 38, and 71 regions using FST, FLK, and hapFLK, respectively, under selective sweep. Significant candidate genes related to various important traits, such as KLHL for fibre diameter and the OMA1 gene for feed-induced thermogenesis in Changthangi, were identified. In addition, the SYCP2 and NAPAS3 genes were found to be associated with seasonal reproductivity, and BMPR1B for fertilization capacity in Garole. In a previous study, the HSPA6 gene (Garole) was found to be associated with thermo-tolerance in the Angus sheep breed. The outcomes discussed here provide a basis for detecting selective sweeps that underlie genetic variations of traits that have functional importance.
The Influence of Air Pollution on Happiness and Willingness to Pay for Clean Air in the Bohai Rim Area of China

Air pollution imposes detrimental impacts on residents’ health and the general quality of life. Quantifying the influential mechanism of air pollution on residents’ happiness and the economic value brought by environmental quality improvement could provide a scientific basis for the construction of livable cities. This study estimated urban residents’ willingness to pay for air pollution abatement by modeling the spatial relationship between air quality and self-rated happiness with a Bayesian multi-level ordinal categorical response model. Using large-scale geo-referenced survey data, collected in the Bohai Rim area of China (including 43 cities), we found that a standard deviation decrease in the number of polluted days over a year was associated with about a 15 percent increase in the odds of reporting a higher degree of happiness, after controlling for a wide range of individual- and city-scale covariate effects. On average, urban residents in the Bohai Rim region were willing to pay roughly 1.42 percent of their average monthly household income for mitigating marginal reductions in air pollution, although great spatial variability was also presented. Together, we hoped that these results could provide solid empirical evidence for China’s regional environmental policies aiming to promote individuals’ well-being.
EfficientUNet+: A Building Extraction Method for Emergency Shelters Based on Deep Learning

Quickly and accurately extracting buildings from remote sensing images is essential for urban planning, change detection, and disaster management applications. In particular, extracting buildings that cannot be sheltered in emergency shelters can help establish and improve a city’s overall disaster prevention system. However, small building extraction often involves problems, such as integrity, missed and false detection, and blurred boundaries. In this study, EfficientUNet+, an improved building extraction method from remote sensing images based on the UNet model, is proposed. This method uses EfficientNet-b0 as the encoder and embeds the spatial and channel squeeze and excitation (scSE) in the decoder to realize forward correction of features and improve the accuracy and speed of model extraction. Next, for the problem of blurred boundaries, we propose a joint loss function of building boundary-weighted cross-entropy and Dice loss to enforce constraints on building boundaries. Finally, model pretraining is performed using the WHU aerial building dataset with a large amount of data. The transfer learning method is used to complete the high-precision extraction of buildings with few training samples in specific scenarios. We created a Google building image dataset of emergency shelters within the Fifth Ring Road of Beijing and conducted experiments to verify the effectiveness of the method in this study. The proposed method is compared with the state-of-the-art methods, namely, DeepLabv3+, PSPNet, ResUNet, and HRNet. The results show that the EfficientUNet+ method is superior in terms of Precision, Recall, F1-Score, and mean intersection over union (mIoU). The accuracy of the EfficientUNet+ method for each index is the highest, reaching 93.01%, 89.17%, 91.05%, and 90.97%, respectively. This indicates that the method proposed in this study can effectively extract buildings in emergency shelters and has an important reference value for guiding urban emergency evacuation.
Technical Report on Raster field test at a Water Board

Risk assessment of unavailability of telecommunication services is an important part of an organisation’s business continuity management. We developed the Raster method to enable organisations to assess their telecommunication service unavailability risks. To validate Raster in practice we conducted two field tests in which the Raster method was applied at a typical target organisation. This document reports on the second field test, at a Water Board in the Netherlands. This report describes the research goals, method, and results of this field test, and compares the results to those of the first field test. This field test reconfirms the usefulness of the Raster method, and adds some new lessons-learned.