Miracle-dz/UniFAR-FTUs huggingface dataset:
Parallel-charge series-discharge inductor-based voltage boosting technique applied to a rectifier-fed positive output DC-DC converter

The conventional power electronic boost converters have inherent limitations that they are not able to increase the low DC input voltage level into sufficiently high DC output voltage level. This is because of the fact that (1). the inductor used in the converter has certain amount of internal resistance, and (2). the power devices used in the converter are subjected to high potential stress which led to damage of the devices. A configuration of a non-isolated step-up rectifier-fed positive output power converter capable of converting low DC voltage into high DC output voltage-based on the concept of parallel-charge series-discharge inductors is proposed in this paper. The proposed converter is fed by an uncontrolled diode bridge rectifier to which an input sinusoidal AC voltage of magnitude 30 V (rms) is given. The converter is configured such that the input AC voltage of 30 V (rms) is stepped-up to around 900 V (DC) at the output of the converter, with extremely low duty ratio. The proposed converter configuration employs only two high power semiconductor switches with reduced complexity of control. In this work, the converter topology is presented, and its steady state behavior and dynamic modeling are discussed for continuous inductor current mode operation. Further, it is revealed that the voltage gain of the converter is influenced by the variation of the duty cycle of the power switches. The effectiveness of the converter is better understood through simulation in MATLAB/SIMULINK platform. The results demonstrate that the converter is able to maintain higher constant output voltage profile with significantly reduced overshoot and settling time.
The effect of pressure on a nickel aspartate framework

Abstract The hydrostatic compression of the chiral metal-organic framework [Ni(L–Asp)(H2O)2]·H2O (NiAsp–I) has been studied to 6.07 GPa by single crystal X-ray diffraction. Over the course of this pressure range the compound undergoes a phase transition between 0.58 GPa and 1.26 GPa, yielding NiAsp–II. Both polymorphs are orthorhombic, P212121, and feature 1D chains of Asp–Ni–Asp moieties. During the transition, the Ni(II) octahedra rotate, resulting in a dramatic shift in the position of the axial bonds with respect to the direction of polymer formation, and gives rise to an anisotropic compression of the unit cell dimensions.
The Dynamic of Self-Compassion Reviewed from the Characteristics of a Disease

The act of caring about oneself by treating it well unconditionally is known as self compassion. Many people take it for granted until they have to experience a suffering. This research aims to explore how the characteristics of a disease, of both the mild one and the severe one, can affect the level of someone’s self-compassion. Total number of research subjects is 101 people, who suffer from mild and severe diseases. The method used in this research is the quantitative study, the data is then analyzed descriptively to categorize the diseases. It is then followed by the comparation, correlation, and regression tests. The result of descriptive analysis shows that self-compassion level in subjects with severe diseases is higher. The correlation test results show that disease categorization is positively associated with selfcompassion. This finding reveals that when the category of a subject’s disease level up, self-compassion will improve. The regression test show that disease categorization affects self-compassion, there’s indication that the characteristics of a subject’s disease can be highly significant to their level of selfcompassion, especially with regard to their health. The worse the disease, the higher the level of selfcompassion.
Hybrid multifactor scheme for stochastic Volterra equations

We present the hybrid-exponential scheme for simulating stochastic Volterra equations. The scheme is based on an exact approximation of the kernel function near the origin and an approximation by a sum of exponentials across the rest of the domain. The first part is similar to the hybrid scheme introduced in and is needed to capture any singular behavior of the kernel. The second part follows the ideas of where rough volatility models are under consideration and results in a number of stochastic factors to be simulated, one for each exponential term, and all with linear complexity in time. Since the efficiency of our scheme relies heavily on ensuring a low number of factors, we include also a review of various methods for finding the exponential terms. We here discover the method of and show that many fewer terms are needed for the rough fractional kernel than previously established in. Lastly, we provide a proof of convergence and also numerically demonstrate the efficiency of the scheme by example on the rough Bergomi model from.
One-Dimensional Molecular Crystal of Phthalocyanine Confined into Single-Walled Carbon Nanotubes

New one-dimensional (1D) hybrid nanosystems are elaborated with metalated or metal free phthalocyanine molecules encapsulated into the hollow core of single-walled carbon nanotubes. The X-ray diffraction experiments coupled to simulation allow evidencing the 1D structural organization of the molecules inside the nanotubes. The angle between the molecule ring and the nanotube axis is close to 32° as determined from our density functional theory calculations. Confined molecules display Raman spectra hardly altered with respect to the bulk phase, suggesting a rather weak interaction with the tubes. For comparison, noncovalent functionalization at the outer surface of the tube is also investigated. The vibrational properties of the molecules functionalized at the outer surface of tubes display important modifications. A significant curvature of the phthalocyanine is induced by the interaction with the tube walls, leading to change of the central atom position within the molecular ring, in good agreement with our first-principles calculations.
Reconfigurable Anisotropic Coatings via Magnetic Field‐Directed Assembly and Translocation of Locking Magnetic Chains

A method for the generation of remotely reconfigurable anisotropic coatings is developed. To form these coatings, locking magnetic nanoparticles (LMNPs) made of a superparamagnetic core and a two‐component polymer shell are employed. Two different polymers form phase‐separated coaxial shells. The outer shell provides repulsive interactions between the LMNPs while the inner shell exerts attractive forces between the particles. Applying a non‐uniform magnetic field, one gathers the particles together, pushing them to come in contact when the internal shells could effectively hold the particles together. When the magnetic field is turned off, the particles remain locked due to these strong interactions between internal shells. The shells are thus made stimuli‐responsive, so this locking can be made reversible and the chains can be disintegrated on demand. In a non‐uniform magnetic field, the assembled chains translocate, bind to the solid substrate and form anisotropic coatings with a “locked” anisotropic structure. The coatings can be constructed, aligned, realigned, degraded, and generated again on demand by changing the magnetic field and particle environment. The mechanism of the coating formation is explained using experimental observations and a theoretical model.
STAGES OF SMOKING CESSATION AMONG ADULT CURRENT SMOKERS IN MALAYSIA: FINDINGS FROM THE NATIONAL E-CIGARETTE SURVEY 2016

Identification of the stages of smoking cessation among smokers is essential to improve the rate of smoking cessation. The aims of this study were to determine the prevalence and factors associated with stages of smoking cessation across the demographic distribution of adult smokers in Malaysia. Data were derived from a population-based study among Malaysian adults aged 18 years and above. Face-to-face interviews were carried out by trained staff using a validated questionnaire to obtain data related to smoking from 4,288 selected respondents. Of 4,288, 438 respondents are current smokers. Multivariable logistic regression analysis was used to determine factors associated with stage of smoking cessation. Approximately 60% (n=269/438) of the current smokers were in the pre-contemplation stage and 40% (n=169/438) were in the contemplation and preparation stages of smoking cessation. The proportion of pre-contemplators was higher among smokers with higher levels of nicotine addiction (71.3%), lower education attainment (71.4%), and those who were single/widowed/divorced (66.9%). Multivariable analysis showed that males, and those who reported low to high level of nicotine addiction were more likely to be in the pre-contemplation stage whilst those in the older age groups were more likely to be in the advanced stage of smoking cessation. The study revealed that the majority of current smokers in Malaysia had no intention to quit smoking within 6 months. Specific interventions targeting males, young adults and smokers with low to high nicotine addiction should be introduced to ensure the smokers proceed to the advanced stage of smoking cessation.
Estimation of the Frequency of Occurrence of Italian Phonemes in Text

The purpose of this project was to derive a reliable estimate of the frequency of occurrence of the 30 phonemes – plus consonant geminated counterpartsof the Italian language, based on four selected written texts. Since no comparable dataset was found in previous literature, the present analysis may serve as a reference in future studies. Four textual sources were considered: Come si fa una tesi di laurea: le materie umanistiche by Umberto Eco, I promessi sposi by Alessandro Manzoni, a recent article in Corriere della Sera (a popular daily Italian newspaper), and In altre parole by Jhumpa Lahiri. The sources were chosen to represent varied genres, subject matter, time periods, and writing styles. Results of the analysis, which also included an analysis of variance, showed that, for all four sources, the frequencies of occurrence reached relatively stable values after about 6,000 phonemes (approx.1,250 words), varying by <0.025%. Estimated frequencies are provided for each single source and as an average across sources.
Investor Attention and Growth Anomalies in NASDAQ Stocks-Evidence from Google Trend Volume

We study the effects of investor attention on the capital investment anomaly on NASDAQ stocks. Based on total asset growth, researchers find firms that substantially increase capital investments subsequently achieve negative benchmark-adjusted returns. On one hand, some scholars propose that investors incorrectly underreact to the empire building behavior of managers who aggressively increase investment expenditure. On the other hand, some scholars argue that investors appear to overreact to past firm growth rates. We aim to determine whether the growth anomaly is due to underreaction or overreaction in this research. We apply Google Search Volume Index as a new direct measure of investor attention to provide empirical evidence for under-reaction and over-reaction explanations of the total asset growth anomaly on NASDAQ stocks. We adopt double sorting and Fama-MacBeth regression and find the stock prices rise up when investors search actively of the underlying stock tickers. The anomaly is stronger when investors are extremely overreacting and underreacting. When investors are rational or calm down, this total asset growth effect disappears. Our empirical design disentangles the dilemma that whether the strand of growth anomalies is due to risk or mispricing. Within proponents of mispricing, our research innovatively tease out of the opposing explanations of under-reaction and over-reaction as the relevant driver of the growth anomalies.
Application of chemical composition and infusion colour difference analysis to quality estimation of jasmine‐scented tea

Summary Infusion chemical composition, colour difference indicators and volatile constituents of seventeen jasmine-scented tea samples and their correlation with sensory total quality score given by tea-tasting panel were studied by techniques of HPLC, colour difference metre and gas chromatograph. Spearman's linear correlation analysis showed that concentration of nitrogen, caffeine, catechin, epicatechin, catechin gallate, total catechins, terpineol, nerol and infusion light-black indicator ΔL, yellow-blue indicator Δb, total colour difference indicator ΔE were significantly correlated with sensory total quality score, respectively. Regression of the total quality score upon twelve components extracted from thirty-six tested indicators by principal component analysis could properly estimate total quality score of two jasmine-scented tea samples which were not included in the seventeen samples used to construct the regression model.
Mineralogy and Geochemistry of Hydrothermally altered Talcose rocks from Ila Orangun-Oyan areas, part of Southwestern Nigeria

Background/Objectives: Talcose rocks within Precambrian Basement Complex serve as relics of Archean greenstones. alterations associated with polycyclic-orogenies that affected this complex is studied to understandmineralogical and geochemical alterations. Methods: Five fresh samples of talcose rocks were collected during field mapping. These samples were cut into thin sections to reveal modal mineralogy, altered minerals and degree of alteration of such minerals. Mineral phase identification of the talcose rocks was conducted using X-ray Broker D8 ADVANCE diffractometer while whole rock analysis was carried out using Inductively Coupled PlasmaMass Spectrometry. Findings: Lithological relationship revealed fromfield evidence showed that the talc bodies occurred in close association withmicaceous schist. Themineral assemblage of talc, tremolite, actinolite, chlorite and calcite suggest low grade greenschist metamorphic facies from possible hydrothermal alteration. Geochemical results revealed the following range of concentrations; SiO2 42.19-59.03%; Al2O3 1.1 11.8%; Fe2O3 7.64-9.56%; MgO 24.47-26.639%; Ni 594-1207ppm; Co 43.2-113.9ppm; Sn 6-41ppm; V 32-75ppm and Zr 1.3-58.7ppm, and these are typical of talcose rocks. Petrogenetic studies suggest a komatiitic origin with a peridotitic komatiite precursor for the talc-chlorite-tremolite schist. Enrichment in LREE, depletion in HREE and a negative Eu anomaly suggest alteration of the parent magma for the talcose rock and plagioclase fractionation. The trends observed for the LILE, HFSE and REE suggest possible contamination or mixing of crustal and mantle materials during the formation of the protolith. https://www.indjst. org/ 4244 Omotunde et al. / Indian Journal of Science and Technology 2020;13(40):4244–4261 Ni and Co concentrations are higher than average crustal values with implication for ultrabasic to basic magma composition for the komatiitic progenitor and also suggestive of possible mineralisation. Conclusion: Mineralogical examination has revealed a talc-chlorite-tremolite composition for the talcose rockswith peridotitic komatiite precursorywhile geochemical composition supported ultrabasic magmatism similar to those with the Ilesha schist belt.
Effects of metal impuritites on the etch rate selectivity of (110)/(111) in (110) Si anisotropic etching

We have investigated the effects of metal impurities and thermal oxidation process on Si anisotropic KOH etching characteristics for fabricating microsensors and microactuators having precise deep narrow grooves or channels. The effect of metal impurities such as Al, Cr, Fe, Pb and Cu are evaluated using 30 wt percent KOH etchant at 60 degrees C. Al, Cr and Fe have no relation to the etching characteristics, however, Pb and Cu strongly affect the etching characteristics. The etching rate of Si decreases with increasing Pb and Cu concentration. The etch rate selectivity , which is an anisotropy ratio defined by the etch rate ratio of (110) and (111) plane, is not changed by Pb impurity, but extremely decreases with increasing Cu impurity. It dips form 150 to 80 when the Cu concentration is over 50ppb, and saturated over the concentration. With respect to the surface roughness within our evaluated metal impurities, Cu impurity also strongly affects the roughness of the etched surface. In addition to the effect of metal impurities, we have experienced the effect on the etching selectivity by the thermal oxidation process. The selectivity is decreased with repeating thermal oxidation process, and this tendency is more pronounced with higher oxygen concentration of evaluated Si wafers. As a result, controlling Cu impurity concentration and using a low oxygen concentration wafer are crucial considerations when fabricating sensors and actuators with narrow grooves or channels by Si anisotropic KOH etching.
Pretreatment Neutrophil-to-Lymphocyte Ratio and Platelet-to-Lymphocyte Ratio as a Stage Determination in Breast Cancer

BACKGROUND: Breast cancer tends to respond differently to treatments, which are usually determined by clinicopathological characteristics. Several studies evaluated the role of the peripheral blood test as diagnostic and prognostic markers in several types of solid cancer and neutrophil-to-lymphocyte ratio (NLR) and platelet-tolymphocyte ratio (PLR) are two of them which already tested. However, the evidence in breast cancer is still lacking. AIM: Therefore, the study aimed to investigate the value of NLR and PLR as biomarkers concerning breast cancer stage. METHODS: A retrospective study was conducted using breast cancer patients’ medical records from 2014 to 2019 at Sanglah General Hospital. The histopathological records and complete blood counts of the patients were collected and analyzed risk analysis model, receiver operator characteristics analysis, and correlation of NLR and PLR with cancer staging analysis used correlation test. RESULT: One hundred five patients data were used in this study, with 35 subjects had early-stage breast cancer while 70 subjects had an advanced stage. Breast cancer staging with NLR and PLR showed significant associations (p < 0.001). Both NLR and PLR had area under the curve >0.7 (p < 0.001). The cutoff, sensitivity, and specificity values of NLR and PLR were 2.504 (71%; 70%) and 157.1 (73%; 70%). Advanced stage of breast cancer was mostly found in high NLR and PLR value with (OR: 4.231; CI = 1.791-9.995, p < 0.001) and (OR: 3.949; 95% CI = 1.679–9.287; p < 0.001). CONCLUSION: From this preliminary study, pretreatment NLR and PLR values might determine the breast cancer stage. Further research is needed to evaluate the association between grade and patient survival.
Prediction of exposure risk associated with the dynamic behavior of aerosols during dental procedures in dental clinics in the context of the COVID-19 pandemic

ObjectivesThis study aimed to develop a risk prediction scale for COVID-19, based on an analysis of the dynamic behavior of aerosols generated during dental procedures.Materials and methodsThe dispersion of aerosols during dental procedures performed in six dental clinics was evaluated using standardized photographs. The digital images were processed to analyze the stained area and the dimensions of the drops. A logistic regression model was built with the following variables: ventilation, the distance from the mouth, the instrument used, the area in the mouth to be treated, and the location within the perimeter area.ResultsThe variables that were associated with a higher risk of exposure in the prediction scale were a distance of less than 78 cm; improper ventilation; the use of a high-speed handpiece; the location of the patient, operator, and assistant; and, to a lesser degree, the intervention of the anterior region of the mouth. The sizes of a large percentage of aerosolized particles ranged from 1 to 5 µm. The maximum settlement range from the mouth of the phantom head was 320 cm, with a high-risk cut-off distance of 78 cm.ConclusionsContamination by disseminating aerosols represents a significant risk for the dental team. Thus, it is advisable to improve ventilation, use extreme biosecurity measures and all the cleaning and disinfection measures.Clinical relevanceThe need to implement new clinical care strategies was evident. The scale is useful for predicting the risk of exposure to the contagion of COVID-19 in the dental office.
Social Preferences and Economic Decision-Making in the Wake of COVID-19: Experimental Evidence from China

We systematically examine the acute impact of exposure to a public health crisis on multiple dimensions of economic decision making and social preferences using unique experimental panel data collected just before and immediately after the outbreak of COVID-19 in China. Exploiting the geographical variation in virus prevalence and unique dataset of longitudinal experiments, we show that while social and economic preferences are largely stable, participants who were more intensely exposed to the virus became more anti-social than those with lower exposure. The effect is particularly pronounced for individuals who experienced an increase in depression or negative affect, which highlights the important role of psychological health as a potential pathway through which the virus outbreak affects behaviour. Our results have important policy implications, as pro-sociality is likely to affect how individuals adopt measures to protect themselves from COVID-19 and comply with public policy limiting its further spread.
An Introduction to Spatial Data Mining

: The goal of spatial data mining is to discover potentially useful, interesting, and non-trivial patterns from spatial data-sets (e.g., GPS trajectory of smartphones). Spatial data mining is societally important having applications in public health, public safety, climate science, etc. For example, in epidemiology, spatial data mining helps to ﬁnd areas with a high concentration of disease incidents to manage disease outbreaks. Computational methods are needed to discover spatial patterns since the volume and velocity of spatial data exceed the ability of human experts to analyze it. Spatial data has unique characteristics like spatial autocorrelation and spatial heterogeneity which violate the i.i. d (Independent and Identically Distributed) assumption of traditional statistic and data mining methods. Therefore, using traditional methods may miss patterns or may yield spurious patterns, which are costly in societal applications. Further, there are additional challenges such as MAUP (Modiﬁable Areal Unit Problem) as illustrated by a recent court case debating gerrymandering in elections. In this article, we discuss tools and computational methods of spatial data mining, focusing on the primary spatial pattern families: hotspot detection, colocation detection, spatial prediction, and spatial outlier detection. Hotspot detection methods use domain information to accurately model more active and high-density areas. Colocation detection methods ﬁnd objects whose instances are in proximity to each other in a location. Spatial prediction approaches explicitly model the neighborhood relationship of locations to predict target variables from input features. Finally, spatial outlier detection methods ﬁnd data that diﬀer from their neighbors. Lastly, we describe future research and trends in spatial data mining.