Miracle-dz/UniFAR-FTUs huggingface dataset:
A model for the necking phenomenon in high-speed fiber spinning based on flow-induced crystallization

In this work we investigate the use of an inhomogeneous structural model which explicitly takes into account flow-induced crystallization for representing the necking phenomenon in high-speed fiber spinning. For simplicity, we have considered a one-dimensional (cross-section averaged) approximation for an isothermal system with no surface tension and air drag, with or without inertia. Flory’s approach [J. Chem. Phys. 15, 397–408, (1947)] is used to predict the onset of crystallization in the spinline. After the onset of crystallization, the fiber is modeled as an inhomogeneous medium with two separate (meso) phases—one semi-crystalline and the other amorphous. The amorphous phase, before and after the onset of crystallization, is modeled as a viscoelastic fluid, represented here by the extended White–Metzner model. The semi-crystalline phase is modeled as an anelastic solid. We demonstrate neck formation for a variety of processing conditions and material property values consistent with those encountered in practice. In particular, the addition of inertial effects, which can also be important in high-speed fiber spinning, shifts but does not eliminate the window in parameter space over which the inertialess model predicts neck formation. Based on these results, we propose as a mechanism for the neck formation the structural changes within the material induced by the crystallization and the ability of the semi-crystalline phase to rapidly take up high stresses.In this work we investigate the use of an inhomogeneous structural model which explicitly takes into account flow-induced crystallization for representing the necking phenomenon in high-speed fiber spinning. For simplicity, we have considered a one-dimensional (cross-section averaged) approximation for an isothermal system with no surface tension and air drag, with or without inertia. Flory’s approach [J. Chem. Phys. 15, 397–408, (1947)] is used to predict the onset of crystallization in the spinline. After the onset of crystallization, the fiber is modeled as an inhomogeneous medium with two separate (meso) phases—one semi-crystalline and the other amorphous. The amorphous phase, before and after the onset of crystallization, is modeled as a viscoelastic fluid, represented here by the extended White–Metzner model. The semi-crystalline phase is modeled as an anelastic solid. We demonstrate neck formation for a variety of processing conditions and material property values consistent with those encountered .
Glucosamine inhibits extracellular matrix accumulation in experimental diabetic nephropathy

Introduction Glucosamine, the intermediate metabolite of the hexosamine biosynthesis pathway (HBP), is widely used as a supplementary drug in patients with osteoarthritis. However, its consequences in such patients concomitantly suffering from diabetic nephropathy is unknown. Methods The aim of the study was to investigate the effect of exogenous administration of glucosamine in the diabetic kidney. A mouse model of streptozotocin-induced diabetic nephropathy in vivo and cultured endothelial cells in vitro were used in the study. The mice were treated with glucosamine for 6 months. Renal function was evaluated by metabolic cage, and histology of the kidney was estimated by periodic acid-schiff (PAS) staining. The expression of related genes was assessed by real-time PCR, immunofluorescence staining, immunoblotting and ELISA. Results There was no significant difference in urinary albumin secretion, relative kidney weight, or creatinine clearance between the groups treated with glucosamine and controls. Assessment of the kidney demonstrated reduction in mesangial expansion and fibronectin expression in the diabetic glomeruli treated with glucosamine. Glucosamine treatment significantly decreased α-smooth muscle actin (α-SMA) protein expression in both diabetic and control kidneys, whereas the expression of other fibrosis-related genes and inflammatory factors was unaltered. Moreover, α-SMA colocalized with the endothelial marker CD31 in the diabetic and control kidneys, and glucosamine reduced α-SMA+ ECs in the diabetic glomeruli. In addition, glucosamine suppressed α-SMA expression in endothelial cells treated with or without high glucose. Discussion In summary, this is the first report to show that glucosamine reduces mesangial expansion and inhibits endothelial-mesenchymal transition in diabetic nephropathy. The underlying mechanisms need to be further investigated.
The influence of social support on the physical exercise behavior of college students: The mediating role of self-efficacy

Objectives To study the influencing factors on college students’ physical exercise behavior and the mediating relationship of self-efficacy based on the theory of social support and self-efficacy; to provide theoretical support and practical guidance for college students engaging independently in physical exercise. Methods A total of 1,440 college students from six universities in the Inner Mongolia Autonomous Region of China were selected as the research objects, and three scales (Self-Efficacy Scale, Social Support Scale, and Physical Exercise Rating Scale) were used to construct a structural equation model. Results (1) A comprehensive sports facility environment is conducive to college students’ physical activities and the emotional support of friends and family and the campus cultural atmosphere cannot be ignored. (2) Peer support has a direct impact on physical exercise behavior, family support and school support indirectly affect college students’ physical exercise behavior, based on the intermediary role of self-efficacy. (3) According to the total effect, social support was ranked as school support (0.444), peer support (0.312), and family support (0.145). Conclusion Social support not only directly affects physical exercise behavior but also indirectly affects physical exercise behavior based on the mediating effect of self-efficacy.
Induction of protective interferon-β responses in murine osteoblasts following Staphylococcus aureus infection

Introduction The refractory and recurrent nature of chronic staphylococcal osteomyelitis may be due, at least in part, to the ability of Staphylococcus aureus to invade and persist within bone-forming osteoblasts. However, osteoblasts are now recognized to respond to S. aureus infection and produce numerous immune mediators and bone regulatory factors that can shape the host response. Type I interferons (IFNs) are best known for their antiviral effects, but it is becoming apparent that they impact host susceptibility to a wide range of pathogens including S. aureus. Methods Here, we have assessed the local expression of IFN-β by specific capture ELISA in an established in vivo mouse model of staphylococcal osteomyelitis. RNA Tag-Seq analysis, specific capture ELISAs, and/or immunoblot analyses, were then used to assess the expression of type I IFNs and select IFN stimulated genes (ISGs) in S. aureus infected primary murine osteoblasts. The effect of IFN-β on intracellular S. aureus burden was assessed in vitro following recombinant cytokine treatment by serial colony counts of liberated bacteria. Results We report the presence of markedly elevated IFN-β levels in infected bone tissue in a mouse model of staphylococcal osteomyelitis. RNA Tag-Seq analysis of S. aureus infected osteoblasts showed enrichment of genes associated with type I IFN signaling and ISGs, and elevated expression of mRNA encoding IFN-β and ISG products. IFN-β production was confirmed with the demonstration that S. aureus induces its rapid and robust release by osteoblasts in a dose-dependent manner. Furthermore, we showed increased protein expression of the ISG products IFIT1 and IFIT3 by infected osteoblasts and demonstrate that this occurs secondary to the release of IFN-β by these cells. Finally, we have determined that exposure of S. aureus-infected osteoblasts to IFN-β markedly reduces the number of viable bacteria harbored by these cells. Discussion Together, these findings indicate an ability of osteoblasts to respond to bacteria by producing IFN-β that can act in an autocrine and/or paracrine manner to elicit ISG expression and mitigate S. aureus infection.
Visit-to-visit variability in triglyceride-glucose index and diabetes: A 9-year prospective study in the Kailuan Study

Instruction/Aims It is unknown whether variability in the triglyceride-glucose index (TyG-index) is associated with the risk of diabetes. Here, we sought to characterize the relationship between TyG-index variability and incident diabetes. Methods We performed a prospective study of 48,013 participants in the Kailuan Study who did not have diabetes. The TyG-index was calculated as ln [triglyceride (TG, mg/dL) concentration × fasting blood glucose concentration (FBG, mg/dL)/2]. The TyG-index variability was assessed using the standard deviation (SD) of three TyG-index values that were calculated during 2006/07, 2008/09, and 2010/11. We used the Cox proportional hazard models to analyze the effect of TyG-index variability on incident diabetes. Results A total of 4,055 participants were newly diagnosed with diabetes during the study period of 8.95 years (95% confidence interval (CI) 8.48–9.29 years). After adjustment for confounding factors, participants in the highest and second-highest quartiles had significantly higher risks of new-onset diabetes versus the lowest quartile, with hazard ratios (95% CIs) of 1.18 (1.08–1.29) and 1.13 (1.03–1.24), respectively (P trend< 0.05). These higher risks remained after further adjustment for the baseline TyG-index. Conclusions A substantial fluctuation in TyG-index is associated with a higher risk of diabetes in the Chinese population, implying that it is important to maintain a normal and consistent TyG-index.
COVID-19 pandemic: Prevalence of depression, anxiety, and stress symptoms among Brazilian psychologists

Introduction Symptoms related to mental health disorders became the background of the COVID-19 pandemic, and psychologists had to adapt to the demands, while they themselves were exposed to the pandemic and its stressors. Objectives To identify demographic and professional characteristics of Brazilian psychologists in different phases of pandemic and their reported care practices, concerns, and symptoms. Methods This was an observational study conducted online in four independent phases with no pairing among the samples (May/June 2020, n = 263; November/December 2020, n = 131; May/June 2021, n = 378; November/December 2021, n = 222). Depression, Anxiety and Stress Scale was used. The validity and reliability of the data obtained with the DASS-21 were attested to by confirmatory factor analysis. Basic lexographic and similarity analysis were conducted to obtain textual information. Prevalence of variables was estimated and compared between phases using the z-test (α = 5%). Similarity analysis was performed to identify the psychologists’ concerns. Results Most of participants were women and were self-employed or employed. There was rapid adjustment to remote work and more than 70% reported changes in their mental health since the onset of pandemic. One in four participants had a previous mental health disorder, and there was a high prevalence of symptoms such as anxiety, fear, and angst. The prevalence of professionals who reported not caring about their own mental health was significant. In 2020, one cluster (health) of concern was identified, while in 2021 there were three clusters (health, family, and COVID-19). The prevalence of depression, anxiety, and stress symptoms was high and did not change during the pandemic. Conclusions Psychologists adapted to the demands of the population in the face of the pandemic. However, there was a high prevalence of mental health symptoms and a disregard for self-care among these professionals.
Crosstalk of four kinds of cell deaths defines subtypes of cutaneous melanoma for precise immunotherapy and chemotherapy

Background Cell death patterns can give therapeutic and biological clues that facilitate the development of individualized treatments for this lethal form of skin cancer. Methods We employed unsupervised clustering to establish robust classifications based on the four kinds of cell death-associated gene expression of 462 melanoma patients in the Cancer Genome Atlas (TCGA) and tested their reproducibility in two independent melanoma cohorts of 558 patients. We then used dimensionality reduction of graph learning to display the different characteristics of cell death patterns and immune microenvironments. Results We examined 570 cell death-associated gene expression data of melanoma patients for exploration, independent verification, and comprehensive classification of five reproducible melanoma subtypes (CS1 to CS5) with different genomic and clinical features. Patients in death-inactive subtypes (CS1, CS2, and CS5) had the least immune and stromal cell infiltration, and their prognosis was the poorest. A death-active subtype (CS4), on the other hand, had the highest infiltrated immune and stromal cells and elevated immune-checkpoints. As a result, these patients had the highest response to immunotherapy and the best prognosis. An additional subtype (CS3) had more diversified cell death and immune characteristics with moderate prognoses. Based on graph learning, we successfully divided the CS3 subtype into two subgroups (group A and group B) with distinct survival outcomes and immune features. Finally, we identified eight potential chemical drugs that were specifically targeted for the therapy of melanoma subtypes. Conclusions This research defines the intrinsic subtypes of melanoma based on the crosstalk of four kinds of cell deaths, which affords a blueprint for clinical strategies and guiding precise immunotherapy and chemotherapy for melanoma patients.
Proximity to major roads and the incidence of osteoporotic fractures in elderly women: The BONE study in Beijing

Background There is growing evidence to suggest that living near major roads (and suffering from the air pollution of urban streets) can have an adverse effect on bone health. However, little is known about its relationship to fractures caused by osteoporosis. Objective This study was designed to investigate the relationship between residents living near major roads and the incidence of osteoporotic fractures. Methods A retrospective cohort of 529 subjects was established based on community populations in older women aged 65–91. All participants lived in Beijing between September 27, 2007 and September 26, 2017. The distance between the residential sites of the subjects and the main roads was determined by the authors. Osteoporotic fracture diagnosis was based on medical histories and imaging examinations (DXA and X-rays). The Cox proportional hazard model was used to assess the association between traffic proximity and osteoporotic fractures, with suitable adjustments for individual and background factors. Results The age range of all participants was 65–91 years, with an average age of 75.8 years (and a standard deviation 6.8 years). Of these, 19 (3.59%) suffered from diabetes, and 48 (9%) had hypertension; 85 (14%) families had annual incomes below US $30,000 and 402 (76%) had received a secondary school education or higher. Nearly 25% of people lived within 50 m of a main road, while 50% lived within 300 m. Between 2007 and 2017, a total of 96 osteoporotic fractures were observed. For people living <50 m from a main road, the adjusted hazard ratio (HR) for osteoporotic fractures was 2.509 (95% CI 1.345–4.680), while it was 1.830 (95% CI 1.029–3.255) for those living at a distance of 50–300 m from a main road vs. those living further than 300 m away. Conclusion In this community-based cohort, living near a major road was associated with a higher incidence of osteoporotic fractures.
Theoretical Approach to the Asymmetrical Magnetization Curve

The method previously used to calculate the magnetization curve of an infinite cylinder is applied to the new Meiklejohn and Bean material which is made of Co particles in a CoO shell. It is assumed that the interface of the ferromagnetic and antiferromagnetic materials is held parallel to the cylindrical axis and does not change its direction for any value of the applied field. The crystal anisotropy is neglected.It is shown that the easiest nucleation mode for small radii is buckling and for large radii is curling. The transition from buckling to curling is at about RIsA−½=2, where R is the radius of the cylinder, Is is the saturation magnetization and A is the exchange constant.Numerical solution of the nonlinear equations involved, yields two branches in the magnetization curve, which are both stable with respect to curling perturbations. The general stability is not tested.A similar calculation is carried out for an infinite slab with the spins on the surface held at a fixed direction and with the cr.
Automatic instance segmentation of orchard canopy in unmanned aerial vehicle imagery using deep learning

The widespread use of unmanned aerial vehicles (UAV) is significant for the effective management of orchards in the context of precision agriculture. To reduce the traditional mode of continuous spraying, variable target spraying machines require detailed information about tree canopy. Although deep learning methods have been widely used in the fields of identifying individual trees, there are still phenomena of branches extending and shadows preventing segmenting edges of tree canopy precisely. Hence, a methodology (MPAPR R-CNN) for the high-precision segment method of apple trees in high-density cultivation orchards by low-altitude visible light images captured is proposed. Mask R-CNN with a path augmentation feature pyramid network (PAFPN) and PointRend algorithm was used as the base segmentation algorithm to output the precise boundaries of the apple tree canopy, which addresses the over- and under-sampling issues encountered in the pixel labeling tasks. The proposed method was tested on another miniature map of the orchard. The average precision (AP) was selected to evaluate the metric of the proposed model. The results showed that with the help of training with the PAFPN and PointRend backbone head that AP_seg and AP_box score improved by 8.96% and 8.37%, respectively. It can be concluded that our algorithm could better capture features of the canopy edges, it could improve the accuracy of the edges of canopy segmentation results.
Trophic interactions of an invasive gecko in an endemic-rich oceanic island: Insights using DNA metabarcoding

Understanding the trophic interactions of introduced predators is key for evidence-based management of biological invasions. This is particularly important in oceanic islands, where predator-prey networks often include numerous endemic and range-restricted species. Geckos are successful island colonizers and in recent years numerous species have established populations in a wide array of oceanic islands. One such species is the Moorish gecko (Tarentola mauritanica), which has colonized multiple islands across the Mediterranean basin, Caribbean and Macaronesia. The species was first reported in Madeira Island in 1993 and over the last 30 years has colonized most of the islands' southern coast and expanded to the nearby island of Porto Santo. Here, we used DNA metabarcoding to provide the first insights into the diet of this successful colonizer in its introduced range. The species' diet was mainly composed of ground-dwelling arthropods belonging to the families Porcellionidae (Isopoda), Julidae (Diplopoda) and Formicidae (Hymenoptera). The diet richness and composition were not affected by neither sex nor size of adult geckos, instead they both change across populations. However, trophic niche-width differed among size classes, with smaller geckos feeding on a wider range of prey. We identified over 160 different Operational Taxonomic Units in the diet of T. mauritanica, with 21.6% of them belonging to introduced invertebrates and 13.6% to native species. Native prey taxa included the endemic Madeira wall lizard (Teira dugesii), the sole native reptile to Madeira. We also detected several agricultural pests and disease vectors in the diet of this exotic predator, and 19 taxa identified as prey had not yet been recorded to Madeira. Of these, several are serious agricultural pests, highlighting how this introduced gecko can be used as a natural sampler, in particular for the early detection of invasive arthropod pests. This study emphasizes the importance of trophic studies for monitoring the impacts of introduced predators in fragile insular systems.
Tracking structured light pattern

The vast majority of structured light applications are dedicated to range measurement of non-moving objects. In this paper we present a method for obtaining 3D information from a complex scene with moving objects using a simple structured light pattern, namely a dot matrix. The major problem of structured light techniques - the correspondence problem - is usually solved either by involving a sophisticated pattern (color, thickness, code) or by taking advantage of the spatial properties of the pattern and the scene (rotation of the pattern, restricting the working volume, ordering constraint). Our approach enhances the spatial methods by involving the temporal properties of the scene by tracking the projected dot pattern over a sequence of images. Due to this combination of spatial and temporal information, the method solves the correspondence problem very robustly and up to 10 times faster than an algorithm based on spatial information only. Dot splitting, dot disappearance and dot occlusions are detected. We demonstrate our method on several real sequences. In order to evaluate the performance of the method, we performed extensive evaluation on simulated data. The presented method for obtaining coarse temporal 3D information is very simple and fast, which makes it attractive for various surveillance applications.