Miracle-dz/UniFAR-FTUs huggingface dataset:
The Big Five Across Socioeconomic Status: Measurement Invariance, Relationships, and Age Trends

Associations between socioeconomic status (SES) and personality traits have important implications for theory and application. Progress in understanding these associations depends on valid measurement, unbiased estimation, and careful assessment of generalizability. In this registered report, we used data from AIID, a large online study, to address three basic questions about personality and SES. First, we evaluated the measurement invariance of a common measure of personality, the Big Five Inventory, across indicators of educational attainment, income, and occupational prestige. Fit indices showed some instances of detectable noninvariance, but with little practical impact on substantive results. Second, we estimated associations between SES and personality. Results showed that personality and SES were largely independent (most rs < .1), in contrast to predictions derived from several previous studies. Third, we tested whether age trends in personality were moderated by SES. Results did not support predictions from social investment theory, but they did suggest that age trends were largely generalizable across SES. We discuss the implications of these findings for developing and validating personality measures for use in diverse samples. We also discuss the implications for theories that propose that the Big Five are responsive to, or partially responsible for, people’s economic and social conditions.
Angiographic profile of coronary artery disease in patients with acute coronary syndrome in correlation to their glycaemic status

Background: Aim of the study was to study relationship between Glycemic control and presence of coronary artery disease on clinical presentation with acute coronary syndrome (ACS). We used blood sugar levels (Fasting and post prandial) and HbA1c as parameter for evaluation of glycemic control, Gensini score was used as a parameter for evaluation of severity of coronary artery disease. Methods: The analysis of 1200 patient’s data were performed to reveal demographic characteristics, correlation of the diabetes control with severity of the ACS. A sub-set of 200 subjects that was collected with a focus to include diabetic and non-diabetic subjects in proportion 1:2 was performed. Results: The Pearson correlation between HbA1c and Gensini score (r=0.0444) was poor the correlation between fasting blood sugar (FBS) and Gensini score (r=0.0586), and between post prandial blood sugar (PPBS) and Gensini score (r=0.0549), between random blood sugar (RBS) and Gensini score (r=0.0331) all indicative of poor correlation. Duration of diabetes and Gensini score revealed r=-0.039. The. Correlation was poor to moderate with one sided ANOVA and consistent on comparing r-sq values between, HbA1c and Gensini Score [rsq=49.62 (p<0.001)], FBS and Gensini score [rsq=32.19 (p<0.001)], PPBS and Gensini score [rsq=25.39 (<0.001)], RBS and Gensini score [rsq=42.49 (p<0.001)] and duration of diabetes and Gensini score [rsq=19.61 (p<0.001)]. Conclusions: There was no correlation evident between diabetes and Gensini dcore. The analysis was suggestive of possible strong relationship between diabetes control and IHD severity. There is no correlation between Diabetes and ACS severity. However, better diabetes control is related with better ACS profile.
Overview: Fusion of Radar Polarimetry and Numerical Atmospheric Modelling Towards an Improved Understanding of Cloud and Precipitation Processes

Abstract. Cloud and precipitation processes are still the main source of uncertainties in numerical weather prediction and climate change projections. The Priority Program "Polarimetric Radar Observations meet Atmospheric Modelling (PROM)", funded by the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG), is guided by the hypothesis, that many uncertainties relate to the lack of observations suitable to challenge the representation of cloud and precipitation processes in atmospheric models. Such observations can, however, nowadays be provided e.g. by the recently installed dual-polarization C band weather radar network of the German national meteorological service in synergy with cloud radars and other instruments at German supersites and similar national networks increasingly available worldwide. While polarimetric radars potentially provide valuable in-cloud information e.g. on hydrometeor type, quantity, and microphysical cloud and precipitation processes, and atmospheric models employ increasingly higher moment microphysical modules, still considerable knowledge gaps exist in the interpretation of the observations and large uncertainties in the optimal microphysics model process formulations. PROM is a coordinated interdisciplinary effort to intensify the use of polarimetric radar observations in data assimilation, which requires a thorough evaluation and improvement of parametrizations of moist processes in atmospheric models. As an overview article of the inter-journal special issue "Fusion of radar polarimetry and numerical atmospheric modelling towards an improved understanding of cloud and precipitation processes", it outlines the knowledge achieved in PROM during the past two years and gives perspectives for the next four years.
Tannins and Related Polyphenols of Rosaceous Medicinal Plants. XII. Roshenins A-E, Dimeric Hydrolyzable Tannins from Rosa henryi BOUL.

Five new hydrolyzable tannin dimers, roshenins A-E, and eight known tannins and related polyphenols [(+)-catechin, (-)-epicatechin, procyanidins B-3 and B-4, sanguisorbic acid dilactone, sanguiins H-2, H-6 and lambertianin A], have been isolated from the root of Rosa henryi BOUL. The structures of roshenins A-E (9-12, 19), which have a sanguisorboyl group as a linking unit between monomeric components, were established on the basis of spectral and chemical evidence.
Impact of Arbuscular Mycorrhizal Fungi with Trichoderma viride and Pseudomonas fluorescens on Growth, Yield and Oil Content in Helianthus annuus L.

Abstract: A pot experiment was performed to see the interactive potential of arbuscular mycorrhizal fungi (Glomus mosseae and Acaulospora laevis) alone or in combination with Trichoderma viride and Pseudomonas fluorescens on Helianthus annuus L. under glass house conditions. Various morphological and biochemical parameters were measured after 120 days. Overall results suggest that although, all co-inoculation treatments showed beneficial effects but inoculation with a combination of G. mosseae+A. laevis+T. viride + P. fluorescens showed maximum increment in all the growth parameters studied i.e. plant height, shoot biomass, root biomass, root length, leaf area, flower head diameter, chlorophyll content, root and shoot phosphorus, acidic and alkaline phosphatase, AM spore number, protein percent and oil content, whereas stomatal conductance was found maximum in G. mosseae+A. laevis+T. viride. The overall results demonstrate that the co-inoculation of bioinoculants like P. fluorescens and T. viride with AM fungi promotes higher AM colonization and spore number enhancing nutrient acquisition especially phosphorus (P), producing plant growth hormones resulting in improvement of rhizospheric condition of soil, altering the physiological and biochemical properties of sunflower plant.
Development of a machine-learning-based decision support mechanism for predicting chemical tanker cleaning activity

Purpose This paper aims to propose a machine learning-based automatic labeling methodology for chemical tanker activities that can be applied to any port with any number of active tankers and the identification of important predictors. The methodology can be applied to any type of activity tracking that is based on automatically generated geospatial data. Design/methodology/approach The proposed methodology uses three machine learning algorithms (artificial neural networks, support vector machines (SVMs) and random forest) along with information fusion (IF)-based sensitivity analysis to classify chemical tanker activities. The data set is split into training and test data based on vessels, with two vessels in the training data and one in the test data set. Important predictors were identified using a receiver operating characteristic comparative approach, and overall variable importance was calculated using IF from the top models. Findings Results show that an SVM model has the best balance between sensitivity and specificity, at 93.5% and 91.4%, respectively. Speed, acceleration and change in the course on the ground for the vessels are identified as the most important predictors for classifying vessel activity. Research limitations/implications The study evaluates the vessel movements waiting between different terminals in the same port, but not their movements between different ports for their tank-cleaning activities. Practical implications The findings in this study can be used by port authorities, shipping companies, vessel operators and other stakeholders for decision support, performance tracking, as well as for automated alerts. Originality/value This analysis makes original contributions to the existing literature by defining and demonstrating a methodology that can automatically label vehicle activity based on location data and identify certain characteristics of the activity by finding important location-based predictors that effectively classify the activity status.
Design of a Charge Pump Circuit and System with Input Impedance Modulation for a Flexible-Type Thermoelectric Generator with High-Output Impedance

This paper describes a charge pump system for a flexible thermoelectric generator (TEG). Even though the TEG has high-output impedance, the system controls the input voltage to keep it higher than the minimum operating voltage by modulating the input impedance of the charge pump using two-phase operation with low- and high-input impedance modes. The average input impedance can be matched with the output impedance of the TEG. How the system can be designed is also described in detail. A design demonstration was performed for the TEG with 400 Ω. The fabricated system was also measured with a flexible-type TEG based on carbon nanotubes. Even with an output impedance of 1.4 kΩ, the system converted thermal energy into electric power of 30 μW at 2.5 V to the following sensor ICs.
Use of Wavelets in Electrocardiogram Research: a Literature Review

Currently the introduction and detection of heart abnormalities using electrocardiogram (ECG) is very much. ECG conducted many research approaches in various methods, one of which is wavelet. This article aims to explain the trends of ECG research using wavelet approach in the last ten years. We reviewed journals with the keyword title "ecg wavelet" and published from 2011 to 2020. Articles classified by the most frequently discussed topics include: datasets, case studies, pre-processing, feature extraction and classification/identification methods. The increase in the number of ECG-related articles in recent years is still growing in new ways and methods. This study is very interesting because only a few researchers focus on researching about it. Several approaches from many researchers are used to obtain the best results, both by using machine learning and deep learning. This article will provide further explanation of the most widely used algorithms against ECG research with wavelet approaches. At the end of this article it is also shown that the critical aspect of ECG research can be done in the future is the use of datasets, as well as the extraction of characteristics and classifications by looking at the level of accuracy.
COVID-19 und die epidemiologische Triade

Als die genueser Kaufleute 1347 fluchtartig die von den Mongolen belagerte Handelsstadt Kaffa am Schwarzen Meer verließen und eines ihrer Schiffe Sizilien erreichte, hatte es den Großteil der Mannschaft verloren und den Erreger einer der geschichtlich verheerendsten Epidemien an Bord. Die Pestepidemie der Jahre 1347 bis 1351 – das damalige so genannte „Große Sterben“ – breitete sich entlang der Handelsrouten in ganz Europa aus, etwa ein Drittel der Bevölkerung fiel der Seuche zum Opfer. Sie war auch durch die damals neu eingeführte Quarantäne – eine Absonderung von neu eingetroffenen Schiffen für 40 Tage (ital.
Effect of composting on the microbiological and parasitic load in animal production wastes in Brazil

Purpose Animal production wastes are promising for use in agricultural production as a plant nutrient or soil conditioner. However, if not properly managed, they can contaminate the soil and plants, resulting in public health risks. Considering that the composting technique is recommended to ensure compost hygiene and agronomic viability, the present study aimed to evaluate the microbiological and parasitic load during the composting of residues from conventional and organic animal productions. Method The presence of Salmonella sp. and/or helminth eggs and the quantification of thermotolerant coliforms were determined in horse bedding and organic and conventional poultry litter during the process of composting. Results The initial load of thermotolerant coliforms was greater than 1017 MPN g-1 in the three raw materials. All of them showed a significant reduction in these bacteria at the end of the composting process, reaching 99.98%, 100.00%, and 99.80% in the horse bedding, organic poultry litter, and conventional poultry litter, respectively. All the fresh residues contained helminth eggs, with the horse bedding exhibiting the highest amount compared to the others. However, they all revealed an absence of helminth eggs at the end of the composting process. Salmonella sp. was absent in both the raw materials and the final compost. Conclusion Composting was effective in eliminating helminth eggs and reducing thermotolerant coliform levels. However, the final composts retained a higher pathogenic microbial load than that required by the current Brazilian legislation for use in agriculture.
Life Cycle Assessment of Bioethanol Production: A Review of Feedstock, Technology and Methodology

So far, a lot of efforts have been put in life cycle assessments (LCA) of bioethanol production. There are many works that have assessed bioethanol production in different points of view to illustrate the environmental impacts. This study reviewed former LCA studies on bioethanol produced from various biomass resources by considering the effect of methodological components, technical pathways and feedstock provision on the result of LCA studies. The review evaluated 48 papers published 2002–2021 with a focus on studies that included a complete set of environmental impact categories. However, due to lack of harmony among studies, comparing the LCA results was challenging but the review indicated that the final results of studies are influenced by LCA methodological components, such as system boundary, functional unit, etc. Around 80% of the reviewed papers show the reduction in global warming potential, while contrary results have been found about increasing acidification, eutrophication and photochemical oxidant formation impact categories because of the feedstock provision. Regarding technical aspects, results from the review revealed that most of the studies considered the pre-treatment as a crucial step in bioconversion processes. Despite several LCA studies of bioethanol production, there is still low attention given to uncertainty analysis in the publications.
Tribological investigation of Zamak alloys reinforced with alumina (Al2O3) and fly ash

ABSTRACT In this study, zinc aluminum alloy (Zamak) (ZA-27) composites reinforced by different weight fractions of fly ash, alumina (Al2O3), or both particles were produced using compo-casting technique. The composites were subjected to hardness and wear tests. The hardness of the composites increases with increase of the weight fractions of reinforcements. In wear test, the composites were examined under dry sliding conditions using pin on disc apparatus. The wear results revealed that the wear resistance increases with increase of the weight fractions of reinforcements. However, the effect of fly ash particles on the wear resistance of the produced composites is more statistically significant than the effect of Al2O3 particles. The morphology of the composites was examined using scanning electron microscopy (SEM) after the test. The SEM images revealed the existence of adhesion and delamination wear mechanism.
Choosing the Light Meal: Real-Time Aggregation of Calorie Information Reduces Meal Calories

Numeric labeling of calories on restaurant menus has been implemented widely, but scientific studies have generally not found substantial effects on calories ordered. The present research tests the impact of a feedback format that is more targeted at how consumers select and revise their meals: real-time aggregation of calorie content to provide dynamic feedback about meal calories via a traffic light label. Because these labels intuitively signal when a meal shifts from healthy to unhealthy (via the change from green to a yellow or red light), they prompt decision makers to course-correct in real time, before they finalize their choice. Results from five preregistered experiments (N = 11,900) show that providing real-time traffic light feedback about the total caloric content of a meal reduces calories in orders, even compared with similar aggregated feedback in numeric format. Patterns of ordering reveal this effect to be driven by people revising high-calorie orders more frequently, leading them to choose fewer and lower-calorie items. Consumers also like traffic light aggregation, indicating greater satisfaction with their order and greater intentions to return to restaurants that use them. The authors discuss how dynamic feedback using intuitive signals could yield benefits in contexts beyond food choice.
Sugar reduction in products targeted at children: Why are we not there yet?

Sugar intake among children has raised concern worldwide as it exceeds nutritional recommendations. Sugar contributes to the daily energy intake, without providing additional nutritional value and is associated with several negative health outcomes. Sugars added to foods during industrial processing have been identified as the main source of sugar in children's diets. The present work critically discusses the role of the food industry in contributing to children's excessive sugar intake worldwide, and the strategies that have been encouraged or implemented to reduce the sugar content in products targeted at children. The risk of the current sugar reduction practices in products targeted at children is discussed based on recent scientific evidence. Children's heightened preference for sweetness may not justify the availability of highly sugary products for children. Although research suggests that children readily accept less sweet products, there is still some wariness in the food industry to reduce sweetness intensity. This has strengthened the use of non-nutritive sweeteners (NNS), focusing on maintaining the sweetness level. However, emerging evidence suggests that this may not be the best approach. at children without
Review on Exploring Similarity between Two Questions Using Machine Learning

Question duplication is the main problem which is based on functionality of allowing users to ask questions . Questions are often answered, and the duplication problem is faced by question and answer sites such as Quora and Reddit, Stack-overflow, and others. Answers are segmented through various iterations of the same question due to question continuity. The aim is to detect the duplicate questions for reducing the redundancy in data. This is a worst experience of users, as the answers get segmented on various versions of the same question, it is bad for writers as well as seekers. Actually this problem also has been noticed on other platforms of Q&A. In this proposed work a simple neural architecture with natural language inference will be used. The approach gathers an attention to pound the problem into sub-problems that helps it to be solved separately, thus making it menially parallelizable. This work is just completely a new pattern, for the solution and it is also possible that it will not provide the complete solution to the problem but may help in increasing the efficiency of the model to predict the duplication's among several question pairs. Question duplication is the serious problem due to the segmentation of answers in various variants of the same question because ofduplication's in these discussion boards. Lastly, As a consequence, there is a lack of a rational search, solution indifference, knowledge separation, and an insufficiency of responses to the questioners. This could be avoided by employing Natural Language Processing as well as Machine Learning, which will help to improve the performance as well.
X-ray Photoelectron Spectroscopic Characterization of Ag Nanoparticles Embedded Bioglasses

This article reports on synthesis and X-ray photoemission spectroscopy (XPS) results regarding the development of silver nanoparticles (AgNPs) in CaO-SiO2–B2O3 bioactive glasses with three different Ag2O contents (0.7, 1, 3%). The analysis of the core level and valence band photoemission spectra is discussed in terms of AgNPs shape, size, and distribution at the sample surface for all investigated samples. A comparison with a theoretical valence band photoemission spectrum (VB-XPS) is presented to check the correlation between clusters size and electronic structure. Our data provide complete experimental evidence of the correlation between AgNPs size and electronic structure that has been predicted theoretically.
Períodos de actividad y dieta de Dasyprocta punctata (Gray, 1842) (Rodentia; Dasyproctidae) en agroecosistemas con café, San Ramón, Costa Rica

La guatusa Dasyprocta punctata (Gray, 1842) es una especie clasificada como de poblacion estable y presente en distintos habitats, no obstante, sus habitos (dieta, periodos de actividad y comportamiento) han sido poco descritos. La presente investigacion se basa en determinar los habitos D. punctata en agroecosistemas con cafe en Rincon de Mora, San Ramon, Alajuela, Costa Rica. Para ello, se colocaron cuatro camaras trampa en sitios estrategicos (fuentes de alimentacion, madrigueras, cuerpos de agua y transicion con el bosque secundario). La revision de los videos arrojo nuevos habitos en cuanto a dieta que no se habian registrado para esta especie, incluyendo el consumo de Polyporus sp. Asimismo, se observo que el mayor periodo de actividad anual en el cafetal se da en la etapa fenologica con fruto, mientras que el periodo de actividad diario se amplio el espectro en horas de la noche. De igual forma, se registraron comportamientos ya identificados, donde uno de los mas importantes es la dispersion de semillas.
Analysis Model of Risk Factors of Urban Bus Operation Based on FTA-CLR

In order to comprehensively analyze the risk factors and accurately find the high risk factors related to accidents, an analysis model of risk factors of urban bus operation is proposed, in which the advantages of the structural analysis of the Fault Tree Analysis (FTA) and the correlation analysis of the Cumulative Logistic Regression (CLR) are combined. Firstly, based on the accident data in Northeast China, FTA is used to compile the urban bus operation fault tree. In the fault tree, 16 bus operation risk factors are classified, while the risk factors are sorted and compared from three aspects: structural importance, probability importance, and critical importance. And then, the 11 higher risk factors are selected according to the discriminant principle. Secondly, bus operation accidents are divided into fatal accidents, injury accidents, and major economic loss accidents. The CLR model is used to fit the much higher risk factors that lead to urban bus operation accidents from above 11 higher risk factors. Finally, the scientific rationality and applicability of the model are verified, through the goodness of fit test and the comparison test with the actual probability of occurrence.