Miracle-dz/UniFAR-FTUs huggingface dataset:
Work pressure and job dissatisfaction: Challenges in Danish general practice

A main objective of the Nordic healthcare systems is to deliver timely and equal access to high-quality healthcare to the entire population. Health care providers, such as general practitioners (GPs), may therefore experience pressure to deliver care from both the health authorities and patients. However, if GPs’ gains do not outweigh their costs of providing the demanded care, it may lead to job dissatisfaction and thereby potentially to poorer quality of care. This study contributes to the literature by estimating the association between different sources of experienced work pressure and job dissatisfaction among GPs. We use data from a nation-wide survey of Danish GPs distributed in 2019. The study includes six items covering GPs’ experienced work pressure, which we categorise based on the degree to which they are related to demands from either patients or health authorities. Using a series of ordered logit models with a rich set of explanatory variables, we estimate the association between the pressure measures and GP job dissatisfaction. We find that GPs reporting high or considerable work pressure have an increased likelihood of also reporting job dissatisfaction. However, we find considerable heterogeneity in this relationship across different sources of work pressure as well as across GP, practice, and area characteristics. For example, the relationship between pressure from patients’ demands for consultations and job dissatisfaction is stronger among GPs practicing in areas with an undersupply of GPs. Solo practitioners, who cannot share their administrative burdens with colleagues, experience a stronger association between pressure from the health authorities and job dissatisfaction. Policymakers should consider this heterogeneity when implementing new schemes and organisational structures affecting GPs’ work pressure. Published: Online January 2022.
A Coupled BRDF CO2 Retrieval Method for the GF-5 GMI and Improvements in the Correction of Atmospheric Scattering

The Greenhouse Gases Monitoring Instrument (GMI), on board the Chinese Gaofen-5 (GF-5) satellite, provides rich observation data for the global remote sensing of atmospheric CO2. To meet the high-precision satellite retrieval needs of atmospheric CO2, this paper designs a coupled bidirectional reflectance distribution function (BRDF) CO2 retrieval (CBCR) method, which describes the surface reflectance characteristics by the BRDF, corrects for atmospheric scattering based on full physics retrieval theory, and ensures the stable retrieval of multiple parameters and atmospheric CO2 by enriching prior constraints. Theoretical analysis shows that the influence of atmospheric scattering induced by the surface bidirectional reflectance characteristics is significantly related to the aerosol optical depth (AOD), solar zenith angle (SZA), and viewing zenith angle (VZA). The validation of GMI CO2 retrievals shows that the CBCR method significantly reduced the influence of the surface bidirectional reflectance characteristics under high AOD and high SZA conditions, decreased the atmospheric CO2 retrieval error from 0.58 ± 5.64 ppm to −1.33 ± 3.13 ppm, and increased the correlation with the temporal variation of actual atmospheric CO2 from 34.7 to 76.8%. Our CBCR method can correct the influence of atmospheric scattering induced by the surface bidirectional reflectance characteristics on atmospheric CO2 retrieval, and this work demonstrates that describing the surface reflectance characteristics by using BRDF is a promising idea in the field of satellite CO2 retrievals.
Impact of Sleep and Training on Game Performance and Injury in Division-1 Women’s Basketball amidst the Pandemic

We investigated the impact of sleep and training load of Division - 1 women’s basketball players on their game performance and injury prediction using machine learning algorithms. The data was collected during a pandemic-condensed season with unpredictable interruptions to the games and athletic training schedules. We collected data from sleep monitoring devices, training data from coaches, injury reports from medical staff, and weekly survey data from athletes for 22 weeks.With proper data imputation, interpretable feature set, data balancing, and classifiers, we showed that we could predict game performance and injuries with more than 90% accuracy. More importantly, our F1 and F2 scores of 0.94 and 0.83 for game performance and injuries, respectively, show that we can use the prediction for informative analysis in the future for coaches to make insightful decisions. Our data analysis also showed that collegiate athletes sleep less than the recommended hours (6-7 instead of 8 hours). This coupled with a long hiatus in games and training increases the risk of injury. Varied training and higher heart rate variability (due to better quality sleep) indicated a better performance, while athletes with poor sleep patterns, were more prone to injuries.
Social Evolution in
 Jürgen Habermas
 : Towards a Weak Anthropological Naturalism between
 Kant and Darwin

Issues concerning naturalism have increasingly become the subject of philosophical reflections involving ontological, epistemological, and even ethics affairs. The most popular topic for contemporary philosophy has been the relationship between ontological results of Darwinism and epistemology. Despite the varied circumstances of its establishment, naturalism almost always produces recommendations that reflect a worldview much “ weaker ” (as in the case of Habermas) than the strong one more common among scientism. There are good structural reasons for this difference. The aim of this paper is to elucidate some of distinctive social features of Habermas ’ s conception of the human being and its implications in the Theory of Communicative Action (1982). Therefore, it is shown that his anthropology takes a naturalistic and Darwinist perspective in the weak naturalism perspective. In the first part, Darwin ́ s legacy is analysed as a research program, and Habermas ́ s studies on biological anthropology are compared with the latest research in genetics and palaeontology. In the second part, we will show Habermas ’ s proposal to confront an epistemological dualism through a weak non-reductionist naturalism as a critique of modern metaphysics, which structures a new pragmatic realism.
USBL Survey Technology in Laying Geotechnical Fabric Mattress

The USBL survey technology for positioning and control of underwater geotechnical fabric mattress is a new application technology.Based on the experience in laying geotechnical fabric mattress at Baimaosha for the construction of 12.5 m deepwater channels along the Yangtze River from Nanjing downstream under Contract Package I the paper briefly describes the USBL survey technology in laying and inspection of the geotechnical fabric mattress.Comparing with the traditional working methods,the paper points out that it is feasible to use USBL technology for checking and inspection of the underwater geotechnical fabric mattresses and recommends that the technology may be promoted for similar projects as the technology is easy to apply and the results are accurate.
A Predictive Model of Leaf Flammability Using Leaf Traits and Radiant Heat Flux for Plants of Fire-Prone Dry Sclerophyll Forest

The differential flammability of individual plant species in landscape-scale fire behaviour is an important consideration, but one that is often overlooked. This is in part due to a relative dearth in the availability of plant flammability data. Here, we present a highly accurate predictive model of the likelihood of plant leaves entering flaming combustion as a function of leaf mass per area (LMA), leaf area (LA) and radiant heat flux using species of fire-prone dry sclerophyll forests of south-eastern Australia. We validated the performance of the model on two separate datasets, and on plant species not included in the model building process. Our model gives accurate predictions (75–84%) of leaf flaming with potential application in the next generation of fire behaviour models. Given the global wealth of species’ data for LMA and LA, in stark contrast to leaf flammability data, our model has the potential to improve understanding of forest flammability in the absence of leaf flammability information.
Experiment on effect of cutter parameters of PDC bit on rate of penetration

PDC cutter size,back rake and density are very important design parameters affecting the performance of PDC bit.The effects of PDC cutter s size,back rake,and density on the rate of penetration(ROP) of PDC bit were researched through room drilling experiment.The results show that the ROP of the PDC bit designed with cutters diameter of 19 mm is the highest in the rock whose drillability grade is Ⅲ. But in the rock whose drillability grade is Ⅳ-Ⅴ,the ROP of the PDC bit designed with cutters diameter of 16 mm is the highest.When the PDC bits designed with cutters diameter of 19 mm and 16 mm are used,the highest ROP is obtained in the back rake about 15°. In the rock whose drillability grade is Ⅲ,the ROP decreases with the PDC cutter density increasing,and the effect is obvious.
Water Column Microbial Communities Vary along Salinity Gradients in the Florida Coastal Everglades Wetlands

Planktonic microbial communities mediate many vital biogeochemical processes in wetland ecosystems, yet compared to other aquatic ecosystems, like oceans, lakes, rivers or estuaries, they remain relatively underexplored. Our study site, the Florida Everglades (USA)—a vast iconic wetland consisting of a slow-moving system of shallow rivers connecting freshwater marshes with coastal mangrove forests and seagrass meadows—is a highly threatened model ecosystem for studying salinity and nutrient gradients, as well as the effects of sea level rise and saltwater intrusion. This study provides the first high-resolution phylogenetic profiles of planktonic bacterial and eukaryotic microbial communities (using 16S and 18S rRNA gene amplicons) together with nutrient concentrations and environmental parameters at 14 sites along two transects covering two distinctly different drainages: the peat-based Shark River Slough (SRS) and marl-based Taylor Slough/Panhandle (TS/Ph). Both bacterial as well as eukaryotic community structures varied significantly along the salinity gradient. Although freshwater communities were relatively similar in both transects, bacterioplankton community composition at the ecotone (where freshwater and marine water mix) differed significantly. The most abundant taxa in the freshwater marshes include heterotrophic Polynucleobacter sp. and potentially phagotrophic cryptomonads of the genus Chilomonas, both of which could be key players in the transfer of detritus-based biomass to higher trophic levels.
Knowledge compensation in the German automobile industry

In studies looking at firm survival over the industry life cycle knowledge is one of the most important determinants. Different kinds of knowledge, namely post-entry experience, pre-entry experience and knowledge acquired by innovative activity positively influence the survival chances. This article investigates how different kinds of knowledge are able to compensate each other. A statistical survival analysis is performed for the German automobile industry (1886–1939) which applies an estimation approach that links instrumental variables with the Cox regression. The results highlight that innovative activity is able to compensate for lacking post-entry experience, supporting Schumpeterian creative destruction.
Tansy (Tanacetum vulgare L.)—A Wild-Growing Aromatic Medicinal Plant with a Variable Essential Oil Composition

Tansy (Tanacetum vulgare L.) is an aromatic medicinal plant whose use is limited by the presence of toxic thujone. This research aimed to evaluate the morphological and chemical properties of tansy plants growing in various natural habitats. The research determined the content and chemical composition of the essential oil, the contents of flavonoids and phenolic acids, and the antioxidant activity levels of methanol extracts from tansy inflorescences. The highest amount of essential oil (1.05 mL·kg−1) was found in the raw material collected from the reclaimed area (R). Forty-seven compounds were identified in tansy oil, among which camphor (31.21–1.27%) and trans-chrysanthenyl acetate (76.09–0.09%) dominated, while the concentration of trans-thujone was low (2.67% on average). The highest amounts of flavonoids (0.52%) were found in the raw material collected from the ruderal (W) and reclaimed (R) sites, while the highest amount of phenolic acids (2.42%) was found in the raw material from the ruderal site (W). Tansy inflorescence extracts showed high antioxidant potential (88.41%). The reasons for the variability of the chemical composition of tansy were environmental and genetic variability factors.
Adjustment disorders in international students studying in English during a pandemic

The article presents a detailed study of clinical manifestations of adjustment disorders. The aim of our research to study the peculiarities of adjustment disorders of English speaking international students and to develop a system of its psychotherapeutic correction in a medical institution of higher education. The research methods: theoretical analysis and generalization of literature on the research topic, psychodiagnostic and mathematical-statistical methods. The study was conducted in the context in English speaking foreign students of reforming educational services in Ukrainian higher education institutions against the background of the COVID-19 pandemic and distance learning. The study based on 103 English speaking foreign students of III-Vth years of education in Kharkiv National Medical University, both sex (52 male and 51 female). The average age of the surveyed foreign students was 22.0±1.8 years. Foreign students were divided into three groups. The first group included 40 fourth-year students, the second group 40 third-year students, the third group consisted of 23 fifth-year students. The survey consisted of several stages and was conducted on-line. The first stage was carried out at the beginning of the quarantine, the second after 3 months. Psycho-corrective measures had a positive effect on the dynamics of mental state in 82.5 % of international students. In 68.7 % there was a reduction in maladaptation.
Reliable and Scalable SARS-CoV-2 qPCR Testing at a High Sample Throughput: Lessons Learned from the Belgian Initiative

We present our approach to rapidly establishing a standardized, multi-site, nation-wide COVID-19 screening program in Belgium. Under auspices of a federal government Task Force responsible for upscaling the country’s testing capacity, we were able to set up a national testing initiative with readily available resources, putting in place a robust, validated, high-throughput, and decentralized qPCR molecular testing platform with embedded proficiency testing. We demonstrate how during an acute scarcity of equipment, kits, reagents, personnel, protective equipment, and sterile plastic supplies, we introduced an approach to rapidly build a reliable, validated, high-volume, high-confidence workflow based on heterogeneous instrumentation and diverse assays, assay components, and protocols. The workflow was set up with continuous quality control monitoring, tied together through a clinical-grade information management platform for automated data analysis, real-time result reporting across different participating sites, qc monitoring, and making result data available to the requesting physician and the patient. In this overview, we address challenges in optimizing high-throughput cross-laboratory workflows with minimal manual intervention through software, instrument and assay validation and standardization, and a process for harmonized result reporting and nation-level infection statistics monitoring across the disparate testing methodologies and workflows, necessitated by a rapid scale-up as a response to the pandemic.
Artificial Intelligence Enabled Personalised Assistive Tools to Enhance Education of Children with Neurodevelopmental Disorders—A Review

Mental disorders (MDs) with onset in childhood or adolescence include neurodevelopmental disorders (NDDs) (intellectual disability and specific learning disabilities, such as dyslexia, attention deficit disorder (ADHD), and autism spectrum disorders (ASD)), as well as a broad range of mental health disorders (MHDs), including anxiety, depressive, stress-related and psychotic disorders. There is a high co-morbidity of NDDs and MHDs. Globally, there have been dramatic increases in the diagnosis of childhood-onset mental disorders, with a 2- to 3-fold rise in prevalence for several MHDs in the US over the past 20 years. Depending on the type of MD, children often grapple with social and communication deficits and difficulties adapting to changes in their environment, which can impact their ability to learn effectively. To improve outcomes for children, it is important to provide timely and effective interventions. This review summarises the range and effectiveness of AI-assisted tools, developed using machine learning models, which have been applied to address learning challenges in students with a range of NDDs. Our review summarises the evidence that AI tools can be successfully used to improve social interaction and supportive education. Based on the limitations of existing AI tools, we provide recommendations for the development of future AI tools with a focus on providing personalised learning for individuals with NDDs.
Long Transmission Line Distance Protection Based on Parameter Identification in Time Domain

The traditional distance protections applied to the long transmission line have transient overreach problem caused by influence of line distribution capacitance,so a new time-domain distance protection method with parameter identification is proposed in the paper. With distributed parameter line model,the setting-point voltage and current of the protection are calculated in accordance with voltage and current measured in local terminal,and then distance protection algorithm of differential equation is used to distinguish internal fault from external fault. In addition,using linear interpolation,voltage and current distribution along the line can be calculated by data obtained with a low frequency sampling. Simulation results show that the scheme can distinguish internal fault from external fault correctly and avoid the transient overreach effectively. It needs low sampling frequency and is not affected by line distribution capacitance current and non-periodic component,so the reliability of distance protection is higher than ever.
Research on the Blade Modeling of Aero-engine Based on UGNX

The 3-D modeling was researched for the turbine blades which are crucial parts.The blade spline modeling was established by dual cubic B spline surface based on the free surface modeling function of UGNX,and the blade space surface was constructed.Some key problems were analyzed and discussed from the point of mathematics in blade modeling for validating the feasibility of modeling and maching method.The above analysis provides an academic basis for the continual optimization design and error compensation of blades.
Abstract structures and meaning in Japanese dative structural priming

Abstract Syntactic structures and meaning appear to independently contribute to structural priming within English structural alternations. Japanese uses scrambling of case-marked phrases to create syntactic alternations, and it is not clear how meaning impacts scrambling-based structural choices. To examine this issue, meaning overlap with dative targets was manipulated in two structural priming experiments. In Experiment 1, datives primed dative targets, but structurally similar primes with idiomatic meanings did not prime. In Experiment 2, transitive primes that differed from datives in thematic roles showed as much priming as dative primes. The transitive results demonstrate that scrambling-based alternations in Japanese can be primed from structures that differ in role meaning, but the lack of idiom priming means that these structures may be less independent of meaning than those in other languages.
An Effective Fingerprint-Based Indoor Positioning Algorithm Based on Extreme Values

Wi-Fi-based fingerprint indoor positioning technology has gained special attention, but the development of this technology has been full of challenges such as positioning time cost and positioning accuracy. Therefore, selecting reasonable Wireless Access Points (APs) for positioning is essential, as the more APs used for positioning, the higher the online computation, energy and time cost. Furthermore, the received signal strength (RSS) is easily affected by diverse interference (obstacles, multipath effects, etc.), decreasing the positioning accuracy. AP selection and positioning algorithms are proposed in this paper to solve these issues. The proposed AP selection algorithm fuses RSS distribution and interval overlap degree to select a small number of APs with high importance for positioning. The proposed positioning algorithm uses the location distance between reference points (RPs) to construct a circle and leverages extreme values (maximum and minimum values) of circles to determine the possibility that the test point (TP) appears in each circle, then it finds useful APs to determine the weight of RPs. Extensive experiments are conducted in two different areas, and the results show the effectiveness of the proposed algorithm.
Efficacy of carbon nanotubes and polydimethylsiloxane interlayer in augmenting the impact strength of glass fiber/epoxy composites

An experimental investigation is carried out to explore the possibility of carbon nanotubes addition and incorporation of polydimethylsiloxane soft interlayer in improving the impact strength and energy-absorbing capability of conventional glass fiber-reinforced plastics. To this end, deformation behavior of glass fiber-reinforced plastics, carbon nanotube-modified glass fiber-reinforced plastics, and glass fiber-reinforced plastics-polydimethylsiloxane sandwich coupons under high strain rate loading are compared using the split-Hopkinson pressure bar testing technique. While neat epoxy is used to process conventional glass fiber-reinforced plastics, the carbon nanotubes-modified glass fiber-reinforced plastics samples are fabricated using 0.5 wt. % carbon nanotube-modified epoxy. The split-Hopkinson pressure bar testing reveals that the addition of carbon nanotubes improves the peak stress and energy-absorbing capacity of the epoxy matrix. The improved impact response of carbon nanotube-modified epoxy translates into enhanced peak stress and energy-absorbing capability of carbon nanotubes-modified glass fiber-reinforced plastics in comparison to conventional glass fiber-reinforced plastics under impact loading. The microscopy analysis of failed composite samples reveals that while glass fiber-reinforced plastics primarily fails at the fiber/epoxy interface, the failure initiates in the epoxy matrix in carbon nanotubes-modified glass fiber-reinforced plastics samples. The impact testing of sandwich samples shows that the insertion of neat and 0.05 wt. % carbon nanotube-modified polydimethylsiloxane interlayer helps to distribute the impact load in a wider domain and thus delays the failure of glass fiber-reinforced plastics sandwich coupons. Moreover, the carbon nanotube-modified polydimethylsiloxane interlayer is better suited to increase the damage resistance and energy-absorbing ability of glass fiber-reinforced plastics. The present study provides a feasible strategy to enhance the failure strength and energy-absorbing capacity of conventional composites using carbon nanotube-modified epoxy and polydimethylsiloxane-based interlayer.