Miracle-dz/UniFAR-FTUs huggingface dataset:
Parental socioeconomic status and the timing of first marriage: What is the role of unmarried cohabitation? Results from a cross-national comparison

BACKGROUND Previous research has shown that individuals from high-status families enter marriage later than those from low-status families. However, in many Western societies, it has become common to cohabit prior to marriage. Does this change the link between parental socioeconomic status (SES) and marriage timing? OBJECTIVE This study examines to what extent the impact of parental SES on the timing of first marriage weakens after young adults start a cohabiting union. It also examines crossnational variation in the link between parental SES and marriage timing before and after young adults cohabit and whether this variation depends on countries’ position in the cohabitation transition. METHODS We apply discrete-time hazard models and meta-analytical tools using data from 20 Western countries. To examine whether the cohabitation stage of countries explains country differences, we construct a four-stage cohabitation typology. RESULTS In most countries, higher parental SES results in later entry into marriage. The impact of parental SES on marriage timing weakens considerably after young adults entered a cohabiting union. Substantial cross-national variation is found in the strength of the link between parental SES and marriage timing. However, this variation cannot be explained by the cohabitation stage countries are in. 1 Department of Sociology, Utrecht University (UU), Utrecht, the Netherlands. Email: m.d.brons@uu.nl. 2 Nederlands Interdisciplinair Demografisch Instituut (NIDI), Den Haag, the Netherlands. 3 Vrije Universiteit Amsterdam, the Netherlands. Brons, Liefbroer & Ganzeboom: Parental socioeconomic status and the timing of first marriage 470 https://www.demographic-research.org CONTRIBUTION First, this study provides fresh evidence of the influence of parental SES on family formation in Western countries. Second, it shows the importance of a life-course perspective, as parental SES matters less after young adults start a cohabiting union. Third, it presents a theory-based and empirically-tested typology of stages in the cohabitation transition.
Exploring chord embedding spaces between musical composers and eras

—In recent years, natural language processing algorithms have become more sophisticated and powerful due to the development of deep neural networks. In this paper we have decided to exploit these powerful tools in order to generate an embedding space of musical chords using two sets of annotated corpora, containing musical scores from different eras. The resulting embedding spaces were visualized in different ways and show that the trained models managed to catch fundamental similarities between different chords. The possibility of predicting subsequent chords in context using various word representation models and a recurrent neural network was also investigated. It is shown that even using a small neural network, it is possible to achieve good results.
Simulating Metabolic Flexibility in Low Energy Expenditure Conditions Using Genome-Scale Metabolic Models

Metabolic flexibility is the ability of an organism to adapt its energy source based on nutrient availability and energy requirements. In humans, this ability has been linked to cardio-metabolic health and healthy aging. Genome-scale metabolic models have been employed to simulate metabolic flexibility by computing the Respiratory Quotient (RQ), which is defined as the ratio of carbon dioxide produced to oxygen consumed, and varies between values of 0.7 for pure fat metabolism and 1.0 for pure carbohydrate metabolism. While the nutritional determinants of metabolic flexibility are known, the role of low energy expenditure and sedentary behavior in the development of metabolic inflexibility is less studied. In this study, we present a new description of metabolic flexibility in genome-scale metabolic models which accounts for energy expenditure, and we study the interactions between physical activity and nutrition in a set of patient-derived models of skeletal muscle metabolism in older adults. The simulations show that fuel choice is sensitive to ATP consumption rate in all models tested. The ability to adapt fuel utilization to energy demands is an intrinsic property of the metabolic network.
AMDV Vaccine: Challenges and Perspectives

Aleutian mink disease virus (AMDV) is known to cause the most significant disease in the mink industry. It is globally widespread and manifested as a deadly plasmacytosis and hyperglobulinemia. So far, measures to control the viral spread have been limited to manual serological testing for AMDV-positive mink. Further, due to the persistent nature of this virus, attempts to eradicate Aleutian disease (AD) have largely failed. Therefore, effective strategies to control the viral spread are of crucial importance for wildlife protection. One potentially key tool in the fight against this disease is by the immunization of mink against AMDV. Throughout many years, several researchers have tried to develop AMDV vaccines and demonstrated varying degrees of protection in mink by those vaccines. Despite these attempts, there are currently no vaccines available against AMDV, allowing the continuation of the spread of Aleutian disease. Herein, we summarize previous AMDV immunization attempts in mink as well as other preventative measures with the purpose to shed light on future studies designing such a potentially crucial preventative tool against Aleutian disease.
Cytokine Networks in the Pathogenesis of Rheumatoid Arthritis

Rheumatoid arthritis (RA) is an autoimmune disease characterized by chronic systemic inflammation causing progressive joint damage that can lead to lifelong disability. The pathogenesis of RA involves a complex network of various cytokines and cells that trigger synovial cell proliferation and cause damage to both cartilage and bone. Involvement of the cytokines tumor necrosis factor (TNF)-α and interleukin (IL)-6 is central to the pathogenesis of RA, but recent research has revealed that other cytokines such as IL-7, IL-17, IL-21, IL-23, granulocyte macrophage colony-stimulating factor (GM-CSF), IL-1β, IL-18, IL-33, and IL-2 also play a role. Clarification of RA pathology has led to the development of therapeutic agents such as biological disease-modifying anti-rheumatic drugs (DMARDs) and Janus kinase (JAK) inhibitors, and further details of the immunological background to RA are emerging. This review covers existing knowledge regarding the roles of cytokines, related immune cells and the immune system in RA, manipulation of which may offer the potential for even safer and more effective treatments in the future.
Self-reported current sleep behaviors of adult athletes from different competitive levels and sports

ABSTRACT Objectives: To quantify self-reported current sleep behaviors in a range of adult athletes. In addition, to determine any differences in sleep duration and sleep quality, depending on sport type and competitive level. Material and Methods: In this cross-sectional study, 313 athletes (243 male, 70 female), competing in a variety of sports and competitive level, completed the Pittsburgh sleep quality index (PSQI) and a questionnaire which captured current sleep behaviors. Sleep quality was calculated using the global PSQI score (≥ 5 indicative of poor sleep quality). Results: On average, athletes self-reported sleep duration was 7:34 ± 1:00 h:min. Overall, 19% of athletes achieved less than 7 h of sleep, 50% achieved less than 8 h. Global PSQI score was 5.0 ± 2.4, with poor sleep quality found in 55% of athletes. Sleep duration was significantly shorter in runners compared to basketball, soccer and rugby players (p < 0.05). Recreational athletes slept significantly less (7:08 ± 0:54 h:min) than competitive (7:32 ± 1:00 h:min), national (7:50 ± 1:00 h:min) and elite level athletes (7:49 ± 0:51 h:min). No differences in sleep quality were found between sport or competitive level. Discussion: Half of the athletes failed to achieve 8 h of sleep per night and the majority reported compromised sleep quality. Sport type and competitive level may influence sleep duration; however, these factors do not seem to cause discrepancies in sleep quality. This study provides novel data into the sleep behaviors of adult athletes, and suggests strategies to improve sleep duration and quality may be warranted.
Control of growth and flowering of chrysanthemum ( Dendranthema x grandiflorum Kitam.) using day length extension and Red Light Night Break

Abstract In tropical areas, since the day length (DL) is shorter than the critical DL for chrysanthemum (Dendranthema x grandiflorum Kitam.), chrysanthemum flowers before reaching the required stem length (SL) for cut flower. Two experiments were conducted with the aim of determining critical DL for vegetative growth of chrysanthemum genotype; to attain a required SL and promote vegetative growth of chrysanthemum using night break (NB) with red light for spray type of chrysanthemum. In the first experiment, DL was extended by one, two, and three hours using white fluorescent light (WL) after sunset. In the second experiment, red light (RL) was applied at the middle of the night for 15, 30, or 45 minutes to break the night. The experiments were laid out in completely randomized design with four replications. The results indicated DL extension with WL and RL night breaks had significant effect on vegetative characters and biomass yield. Similarly, flower bud initiation, coloring and blooming were significantly affected. NB using RL had a significant effect on flower diameter. The three hours DL extension (12+3 hours) totally inhibited flowering of chrysanthemum genotype, which can be considered a critical DL for Hawa1. NB with RL for 15, 30, or 45 minutes effectively inhibited flowering of chrysanthemum. In conclusion, breaking the night with RL at the middle of the night for 15 minutes with small amount of intensity (9.42 µmolm-2s-1) is enough to inhibit flowering and promote stem elongation of chrysanthemum Hawa1.
Energy-Preserving Time-Varying Schroeder Allpass Filters and Multichannel Extensions

We propose time-varying Schroeder allpass filters and Gerzon allpass reverberators that remain energy preserving irrespective of arbitrary variation of their allpass gains or feedback matrices over time. We propose various ways of realizing the unitary matrix involved in the Schroeder structure, based on classic ladder and lattice filters and their generalizations. We show how to construct more elaborate structures including nestings and cascade, giving various strategies for reducing their implementation cost. Extending these algorithms to the multi-input, multi-output case yields time-varying, energy-preserving generalizations of Gerzon’s reverberator, providing a link between Schroeder allpass filters and Schelcht’s recently proposed “Allpass Feedback Delay Networks. ” Stability proofs are given for common uses of Schroeder allpass filters, such as inside of Feedback Delay Network reference structures. Finally we give a substantial review of the properties of time-invariant Schroeder allpass filters.
Antiderivative Antialiasing Techniques in Nonlinear Wave Digital Structures

The Wave Digital Filter (WDF) formalism is becoming a popular approach for the digital emulation of audio circuits. Nonlinear WDFs, like other kinds of discrete-time nonlinear filters used in Virtual Analog modeling applications, are often affected by aliasing distortion. Recently formalized Antiderivative Antialiasing (ADAA) methods are capable of significant aliasing reduction even with low oversampling factors. This paper discusses different strategies to integrate p th-order ADAA methods into stateful WDFs with a single one-port or multi-port nonlinearity while preserving the modularity property typical of traditional WDFs. The effectiveness of the proposed approach is verified by applying the discussed ADAA techniques to three nonlinear audio circuits containing diode-based nonlinearities and a BJT transistor.
Drivers and Distribution of Henipavirus-Induced Syncytia: What Do We Know?

Syncytium formation, i.e., cell–cell fusion resulting in the formation of multinucleated cells, is a hallmark of infection by paramyxoviruses and other pathogenic viruses. This natural mechanism has historically been a diagnostic marker for paramyxovirus infection in vivo and is now widely used for the study of virus-induced membrane fusion in vitro. However, the role of syncytium formation in within-host dissemination and pathogenicity of viruses remains poorly understood. The diversity of henipaviruses and their wide host range and tissue tropism make them particularly appropriate models with which to characterize the drivers of syncytium formation and the implications for virus fitness and pathogenicity. Based on the henipavirus literature, we summarized current knowledge on the mechanisms driving syncytium formation, mostly acquired from in vitro studies, and on the in vivo distribution of syncytia. While these data suggest that syncytium formation widely occurs across henipaviruses, hosts, and tissues, we identified important data gaps that undermined our understanding of the role of syncytium formation in virus pathogenesis. Based on these observations, we propose solutions of varying complexity to fill these data gaps, from better practices in data archiving and publication for in vivo studies, to experimental approaches in vitro.
HPV DeepSeq: An Ultra-Fast Method of NGS Data Analysis and Visualization Using Automated Workflows and a Customized Papillomavirus Database in CLC Genomics Workbench

Next-generation sequencing (NGS) has actualized the human papillomavirus (HPV) virome profiling for in-depth investigation of viral evolution and pathogenesis. However, viral computational analysis remains a bottleneck due to semantic discrepancies between computational tools and curated reference genomes. To address this, we developed and tested automated workflows for HPV taxonomic profiling and visualization using a customized papillomavirus database in the CLC Microbial Genomics Module. HPV genomes from Papilloma Virus Episteme were customized and incorporated into CLC “ready-to-use” workflows for stepwise data processing to include: (1) Taxonomic Analysis, (2) Estimate Alpha/Beta Diversities, and (3) Map Reads to Reference. Low-grade (n = 95) and high-grade (n = 60) Pap smears were tested with ensuing collective runtimes: Taxonomic Analysis (36 min); Alpha/Beta Diversities (5 s); Map Reads (45 min). Tabular output conversion to visualizations entailed 1–2 keystrokes. Biodiversity analysis between low- (LSIL) and high-grade squamous intraepithelial lesions (HSIL) revealed loss of species richness and gain of dominance by HPV-16 in HSIL. Integrating clinically relevant, taxonomized HPV reference genomes within automated workflows proved to be an ultra-fast method of virome profiling. The entire process named “HPV DeepSeq” provides a simple, accurate and practical means of NGS data analysis for a broad range of applications in viral research.
Measuring Corporate Culture Using Machine Learning*

Using one of the latest machine learning techniques—the word embedding model (Mikolov et al. 2013)— and 217,387 earnings call transcripts, we obtain five corporate cultural values: innovation, integrity, quality, respect, and teamwork (Guiso, Sapienza, and Zingales 2015) for 77,541 firm-year observations over the period 2001–2018. We conduct a large number of tests to validate our measures and demonstrate the advantages of our approach over several alternative methods. We show that corporate culture plays an important role in deal incidence and merger pairing, and that post-merger, acquirers’ cultural values are positively associated with their target firms’ cultural values pre-merger.
Expression of MicroRNA-1281, C-Reactive Protein, and Renal Function in Individuals with Abdominal Aortic Aneurysm and their Clinical Correlation after Endovascular Repair

Introduction: The treatment of infrarenal aortic aneurysms has changed in the last three decades. Endovascular aneurysm repair (EVAR) has become the primary treatment option in anatomically suitable patients with infrarenal aortic aneurysms. However, there is no serum biomarker to be used in EVAR follow-up. Methods: This is a prospective single-centre study of 30 consecutive patients with abdominal aortic aneurysm (AAA) who underwent EVAR. Serum dosages of micro ribonucleic acid 1281 (miRNA-1281), creatinine, total cholesterol, triglycerides, and C-reactive protein (CRP) were evaluated and angiotomographic evaluations were performed preoperatively and six months after the intervention. Results: There was a hyperexpression of miRNA-1281 in patients with AAA and a significant reduction of it after EVAR, from 1.66-fold before EVAR to 0.27 after the procedure (P<0.0001). MiRNA-1281 expression was not influenced by renal function (creatinine: 1.14±0.29, P=0.68), total cholesterol (179.9±59.9, P=0.22), or CRP (1.17±3.5; P=0.48). There is correlation between AAA size and CRP serum levels, however there was no statically significant reduction of CRP after EVAR. Discussion: MiRNA-1281 expression may be influenced by cholesterol, triglycerides levels, and renal function. We found no difference in these markers before and six months after EVAR. However, miRNA-1281 presents a significant reduction in patients with no follow-up complications. We hypothesize that miRNA-1281 expression may be related to aortic wall stress or flow changes. Conclusion: MiRNA-1281 may contribute as a possible marker of EVAR follow-up.
Using multiple cause of death information to eliminate garbage codes

BACKGROUND International comparisons of mortality largely depend on the quality of data. With more than 20% of deaths annually assigned to ill-defined cardiovascular conditions, the mortality level due to well-defined causes of death is under-registered in Poland. OBJECTIVE We aim to reclassify cardiovascular garbage codes (GCs) into well-defined causes based on multiple causes of death (MCoD) data and to approximate mortality levels due to welldefined causes of death in Poland. We examine the usefulness of the MCoD approach for correcting low-quality data on causes of death. METHODS Based on the unique MCoD dataset for Poland, death counts due to cardiovascular GCs were reassigned to well-defined underlying causes in two steps: (1) manually for death records that included MCoD information constituting a logical chain of conditions leading to death and (2) with coarsened exact matching for the remaining death records. Age-specific and age-standardised death rates for large groups of causes were calculated before and after redistribution and compared to those of other Eastern European countries with relatively good data quality. RESULTS Of deaths originally assigned to cardiovascular GCs, 86,856 were reclassified, mostly to well-defined cardiovascular diseases, cancers, endocrine, nutritional and metabolic diseases, and respiratory diseases. The age-standardised death rate due to well-defined ischaemic heart diseases increased by 43%, and the rate due to cerebrovascular diseases by 22%. Cardiovascular mortality structure by large groups of causes became similar to 1 Centre of Migration Research, University of Warsaw, Poland; and Institut des Migrations, Paris, France. ORCID identifier: 0000-0002-8747-1299. Email: a.fihel@uw.edu. pl. 2 Wittgenstein Centre for Demography and Global Human Capital (IIASA, OeAW, University of Vienna), Vienna Institute of Demography/Austrian Academy of Sciences, Austria. Fihel & Muszyńska-Spielauer: Using multiple cause of death information to eliminate garbage codes 346 https://www.demographic-research.org the structure registered in other Eastern European countries characterised by a low prevalence of GCs. CONCLUSION Coarsened exact matching performs relatively well when abundant MCoD information is available and enhances the comparability of cause-of-death data between countries.
BIM to AR matching technology of building maintenance platform using 5G-based AR

: The significance of virtual reality (AR/VR/MR) technology stands out because it can be used in various construction fields such as urban design, construction review, maintenance and education, etc. As to prove this, conglomerates such as Facebook, Google, Sony, Microsoft, and Sam-sung are increasing their investments to preoccupy the virtual reality market and are competing to dominate the contents and platform market. Virtual reality technology has a concept that collectively refers to VR (Virtual Reality), AR (Augmented Reality), and MR (Mixed Reality), but technically, the two technologies are strictly separated. While VR technology is an immersive virtual environment using computer graphic technology, AR technology is a more advanced technology that combines real data and VR data, and MR technology is a technology that combines both AR and VR. In Korea, Republic of, the use of BIM (Building Information Modeling), a 3D information model, becomes mandatory and based on this, the demand for a new market where VR/AR/MR technologies and advanced sensing equipment are combined increases. This study implemented a building maintenance platform using AR based on 5G, and developed matching technology between BIM of the building maintenance platform and AR equipment. Besides this study implemented the technology to enhance the matching rate of the matching technology and carried out the process to enhance the matching rate empirically through continuous tests. As a result, the initial target of 90% matching rate could be improved to 96%. Based on this, it is expected that effective EV (Optimum Life Cycle Cost) could be achieved at a lower cost compared to the previous one by using it for maintenance monitoring after construction and completion of the building, and can be used as an effective solution in the aspect of building maintenance as well.
Assessment of Weed Classification Using Hyperspectral Reflectance and Optimal Multispectral UAV Imagery

Weeds compete with crops and are hard to differentiate and identify due to their similarities in color, shape, and size. In this study, the weed species present in sorghum (sorghum bicolor (L.) Moench) fields, such as amaranth (Amaranthus macrocarpus), pigweed (Portulaca oleracea), mallow weed (Malva sp.), nutgrass (Cyperus rotundus), liver seed grass (Urochoa panicoides), and Bellive (Ipomea plebeian), were discriminated using hyperspectral data and were detected and analyzed using multispectral images. Discriminant analysis (DA) was used to identify the most significant spectral bands in order to discriminate weeds from sorghum using hyperspectral data. The results demonstrated good separation accuracy for Amaranthus macrocarpus, Urochoa panicoides, Malva sp. , Cyperus rotundus, and Sorghum bicolor (L.) Moench at 440, 560, 680, 710, 720, and 850 nm. Later, the multispectral images of these six bands were collected to detect weeds in the sorghum crop fields using object-based image analysis (OBIA). The results showed that the differences between sorghum and weed species were detectable using the six selected bands, with data collected using an unmanned aerial vehicle. Here, the highest spatial resolution had the highest accuracy for weed detection. It was concluded that each weed was successfully discriminated using hyperspectral data and was detectable using multispectral data with higher spatial resolution.