Miracle-dz/UniFAR-FTUs huggingface dataset:
A Novel Method to Measure the Static Coefficient of Friction for Socks

Mechanical testers have commonly been used to measure the frictional properties of socks. However, the friction values may be susceptible to the level of stretchiness of tested fabrics or human variability. Thus, the aim of this study was to propose a novel method that enables friction measurement of socks in a sock-wearing condition with less human variability effects. Five socks with different frictional properties were chosen. Three experimental ramp tests were performed with an artificial structure shaped like the foot-ankle complex (last) and a ramp tester to quantify the static coefficient of friction (COF) at the foot against sock, at the sock against an insole, and the foot wearing socks against the insole, respectively. The angle where the last slipped while the ramp surface was gradually inclined was used to compute the static COF values for each sock. The reliability was 0.99, and COF values ranged from 0.271 to 0.861 at the foot-sock interface, 0.342 to 0.639 at the sock-insole interface, and 0.310 to 0.614 in the third test. Socks with different frictional properties were successfully distinguished each other. Thus, the suggested protocol could be a reliable option for measuring the static COF values in the tension similar with it found in a sock-waring condition with reduced effects of human variability.
ResNet-Based Parkinson's Disease Classification

Parkinson's disease (PD) is a brain disorder that leads to shaking, stiffness, and difficulty with walking, balance, and coordination. The symptoms usually begin gradually and get worse over time. Early diagnosis is very important because treatments are more effective and easier to perform during the early stages of PD. However, early diagnosis is challenging because the symptoms start gradually, and at the early stages, they are not very noticeable. In this article, we propose a method that uses ResNet50, a residual network that has 50 layers, to help diagnosis PD. The data used are a collection of frequency features acquired by applying spectral analysis strategies to the speech recordings of the patient. We then convert the frequency features into a 2-D heat map. This heat map is passed to ResNet50, which predicts whether the patient has PD or not. We have conducted experiments and compared the accuracy with several state-of-the-art methods. The results have demonstrated the feasibility and robustness of the proposed method.
The use of remote sensing indices to understand flood‐recharged soil moisture impacts on trees in semi‐arid floodplains: A review

Remote sensing indices (RSIs) are essential for detection, mapping and monitoring of floods, soil moisture and tree characteristics. An understanding of the nexus between flood‐recharged soil moisture (FRSM) and endangered biodiversity tree hotspots in semi‐arid floodplains is critical. Specifically, the influence of FRSM on biophysical characteristics of keystone tree species with social, economic, ecological and environmental functions is crucial. However, the use of RSIs to understand the link between episodic floods, FRSM and trees, as well as their respective spatiotemporal dynamics within the semi‐arid floodplains, remains largely unexplored. Hence, this study reviewed literature on the adoption of RSIs in understanding short‐term phenological and long‐term tree structural changes arising from flood‐related infiltration. The reviewed literature shows the predominance of the normalised difference water index, the land surface water index and normalised difference vegetation index for flood, FRSM and tree mapping. The review also shows the emergence of SAR‐based normalised difference flood index for understanding the impacts of FRSM on riparian trees. Although the review identified an increase in data availability, however, there are high costs of active commercial remote sensing data of superior quality and computing resources. Furthermore, available free data are incapable of penetrating canopies and have coarse spatial resolution constraining the use of RSIs to understand the impacts of FRSM on trees. In view of increasing free SAR data and cloud‐based computing resources, application of emerging deep learning algorithms offers prospects for the use of RSIs to understand the impacts of FRSM on riparian trees.
Driver’s Individual Risk Perception-Based Trajectory Planning: A Human-Like Method

Lane-changing is a critical issue for autonomous vehicles (AVs), especially in complex environments. In addition, different drivers have different handling preferences. How to provide personalized maneuvers for individual drivers to increase their trust is another issue for AVs. Therefore, a framework of human-like path planning is proposed in this paper, considering driver characteristics of visual-preview, subjective risk perception, and degree of aggressiveness. In the decision making module, a model is built to select the most suitable merging spot, with respect to safety factors and the driver’s degree of aggressiveness. And a novel environmental potential field (PF) suitable for arbitrary road structures is designed to describe the driver’s individual risk perception. In the trajectory planning module, a model predictive control (MPC) based path planner is designed according to the decisions in coincidence with the driver’s individual intentions of collision avoidance. Simulation results have demonstrated that the proposed path planner can provide with personalized trajectories for different combinations of driver preferences and steering characteristics, in scenarios of curved roads with different risks of collision.
Geographical Authentication of Macrohyporia cocos by a Data Fusion Method Combining Ultra-Fast Liquid Chromatography and Fourier Transform Infrared Spectroscopy

Macrohyporia cocos is a medicinal and edible fungi, which is consumed widely. The epidermis and inner part of its sclerotium are used separately. M. cocos quality is influenced by geographical origins, so an effective and accurate geographical authentication method is required. Liquid chromatograms at 242 nm and 210 nm (LC242 and LC210) and Fourier transform infrared (FTIR) spectra of two parts were applied to authenticate the geographical origin of cultivated M. cocos combined with low and mid-level data fusion strategies, and partial least squares discriminant analysis. Data pretreatment involved correlation optimized warping and second derivative. The results showed that the potential of the chromatographic fingerprint was greater than that of five triterpene acids contents. LC242-FTIR low-level fusion took full advantage of information synergy and showed good performance. Further, the predictive ability of the FTIR low-level fusion model of two parts was satisfactory. The performance of the low-level fusion strategy preceded those of the single technique and mid-level fusion strategy. The inner parts were more suitable for origin identification than the epidermis. This study proved the feasibility of the data fusion of chromatograms and spectra, and the data fusion of different parts for the accurate authentication of geographical origin. This method is meaningful for the quality control of food and the protection of geographical indication products.
Intracellular Delivery of Biologically-Active Fungal Metabolite Gliotoxin Using Magnetic Nanoparticles

Gliotoxin (GT), a secondary metabolite produced by Aspergillus molds, has been proposed as a potential anti-tumor agent. Here we have developed a nanoparticle approach to enhance delivery of GT in tumor cells and establish a basis for its potential use as therapeutical drug. GT bound to magnetic nanoparticles (MNPs) retained a high anti-tumor activity, correlating with efficient intracellular delivery, which was increased in the presence of glucose. Our results show that the attachment of GT to MNPs by covalent bonding enhances intracellular GT delivery without affecting its biological activity. This finding represents the first step to use this potent anti-tumor agent in the treatment of cancer.
Circulating microRNAs in human obesity: a systematic review

Abstract Context: Differential expression profiles of microRNAs have been reported in human obesity suggesting a miRNAs role in the development of obesity and associated disorders. Objective: To review circulating microRNAs (c-miRNAs) dysregulated in human obesity and to predict their possible target genes. Methods: We performed a systematic review on PubMed database (PROSPERO, CRD42017077742) for original works on c-miRNAs and human obesity and recorded c-miRNAs with differential expression profiles. Potential target genes and metabolic pathways for dysregulated miRNAs with at least two independent reports were searched using bioinformatic tools. Results: Twenty-two c-miRNAs are overexpressed, nine underexpressed and two c-miRNAs dysregulated in both directions in people with obesity compared to lean controls. Bioinformatic analyses suggest these c-miRNAs target on genes associated with fatty acid metabolism and PI3k/Akt pathway. Conclusion: Literature records 33 c-miRNAs confirmedly dysregulated in human obesity. Their predicted target genes are involved in pathways that could explain the development of obesity and its comorbidities. Further research will clarify the role of these miRNAs on metabolic diseases and their usefulness for the prognosis, prevention and treatment of obesity.
Exposure to Atmospheric Ultrafine Particles Induces Severe Lung Inflammatory Response and Tissue Remodeling in Mice

Exposure to particulate matter (PM) is leading to various respiratory health outcomes. Compared to coarse and fine particles, less is known about the effects of chronic exposure to ultrafine particles, despite their higher number and reactivity. In the present study, we performed a time-course experiment in mice to better analyze the lung impact of atmospheric ultrafine particles, with regard to the effects induced by fine particles collected on the same site. Trace element and PAH analysis demonstrated the almost similar chemical composition of both particle fractions. Mice were exposed intranasally to FF or UFP according to acute (10, 50 or 100 µg of PM) and repeated (10 µg of PM 3 times a week during 1 or 3 months) exposure protocols. More particle-laden macrophages and even greater chronic inflammation were observed in the UFP-exposed mice lungs. Histological analyses revealed that about 50% of lung tissues were damaged in mice exposed to UFP for three months versus only 35% in FF-exposed mice. These injuries were characterized by alveolar wall thickening, macrophage infiltrations, and cystic lesions. Taken together, these results strongly motivate the update of current regulations regarding ambient PM concentrations to include UFP and limit their emission.
Cigarette Affordability in China, 2006–2015: Findings from International Tobacco Control China Surveys

China is world’s largest market of machine-made cigarettes. In 2015, more than 315 million or around 26.9% of the adult population in China were smokers—50.6% among men and 2.2% among women. Growing affordability of cigarettes led to increased cigarette consumption in China to the detriment of public health. This study investigated whether the level and growth in cigarette affordability in China was equally shared by smokers from all demographic and socio-economic statuses (SES) and across all price tiers of cigarette brands. The data came from the urban smoker sample (≥18 years) of the International Tobacco Control China Surveys conducted in five waves over 2006–2015. Cigarette affordability was measured by Relative Income Price—percentage of per capita household income needed to purchase 100 cigarette packs of the last purchased brand. Overall and group-specific trends in affordability by age, gender, SES (e.g., income, education, and employment status), and price tiers were analyzed using generalized estimating equations method. Cigarette affordability was higher among older, female, and higher-SES smokers, and for cheaper brands. It increased overall and across all groups over time. The increase was significantly larger among younger and lower-SES smokers, a trend that poses an added challenge to tobacco control and health equity. To reduce cigarette affordability and consumption among these vulnerable groups, a uniform specific excise system should be introduced in place of the existing tiered ad valorem excise. The specific excise should be periodically adjusted to inflation and per capita income growth observed among younger and lower-SES people, who can potentially experience faster income growth than the national average. The excise tax policy can also be complimented with minimum price regulations and restrictions on price promotions.
Una visión unificada del contagio en mercados financieros : un enfoque causal en el dominio de la frecuencia

Este trabajo propone una nueva metodología para identificar la existencia de contagio durante la crisis asiática de 1997 y la crisis mexicana de 1994, usando la prueba de causalidad de Granger en el dominio de la frecuencia propuesta por Breitung y Candelon (2006). Se encuentra evidencia de contagio e interdependencia intrarregional e interregional durante dichas crisis. La metodología permite analizar los resultados teniendo en cuenta las diversas definiciones de contagio de forma unificada y a su vez obtener resultados robustos ante los problemas de medición del contagio enunciados en la literatura.
Global Profiling of Genes Expressed in the Silk Glands of Philippine-Reared Mulberry Silkworms (Bombyx mori)

Simple Summary The sericulture industry in the Philippines remains to be enhanced through efforts to improve local strains of the silkworm Bombyx mori, such as selective hybridization. Genetic trait markers could help improve breeding; however, there is a scarcity of genetic data on local strains. This study aims to bridge this gap by analyzing the gene expression profiles of Philippine-reared silkworm strains through next-generation sequencing. Transcriptome assemblies were generated, and gene expressions were compared between silkworm strains reared in different temperatures, revealing genes that may be important for development in a tropical environment. This study is the first to provide transcriptome datasets for the Philippine-reared B. mori strains, which may serve as a resource for improving local strains and increasing silk production. Abstract RNA sequencing was used to assemble transcriptome data for Philippine-reared silkworm and compare gene expression profiles of strains reared in high- and low-temperature environments. RNA was isolated from the silk glands of fifth instar larvae and mRNA-enriched libraries were sequenced using Illumina NextSeq 500. Transcriptome reads were assembled using reference-based and de novo assemblers, and assemblies were evaluated using different metrics for transcriptome quality, including the read mapping rate, E90N50, RSEM-eval, and the presence of single-copy orthologs. All transcriptome assemblies were able to reconstruct >40,000 transcripts. Differential expression analysis found 476 differentially expressed genes (DEGs; 222 upregulated, 254 downregulated) in strains reared in different temperatures. Among the top DEGs were myrosinase, heat shock proteins, serine protease inhibitors, dehydrogenases, and regulators of the juvenile hormone. Validation of some of the top DEGs using qPCR supported the findings of the in silico analysis. GO term enrichment analysis reveals an overrepresentation of GO terms related to nucleotide metabolism and biosynthesis, lipid and carbohydrate metabolic processes, regulation of transcription, nucleotide binding, protein binding, metal binding, catalytic activity, oxidoreductase activity, and hydrolase activity. The data provided here will serve as a resource for improving local strains and increasing silk production of Philippine-reared B. mori strains.
Fear, Stigma and Othering: The Impact of COVID-19 Rumours on Returnee Migrants and Muslim Populations of Nepal

The paper explores how COVID-19-related moral panics have led to fear and othering practices among returnee Nepalese migrants from India and Muslims living in Nepal. This qualitative study included in-depth interviews with 15 returnee migrants, 15 Muslims from Kapilvastu and Banke districts of Nepal, and eight interviews with media and health professionals, and representatives from migration organisations. Four themes emerged from our data analysis: (1) rumours and mis/disinformation; (2) impact of rumours on marginalised groups (with three sub-themes: (i) perceived fear; (ii) othering practices; (iii) health and social impact); (3) resistance; and (4) institutional response against rumours. Findings suggest that rumours and misinformation were fuelled by various media platforms, especially social media (e.g., Facebook, YouTube) during the initial months of the lockdown. This created a moral panic which led to returnee migrants and Muslim populations experiencing fear and social isolation. Resistance and effective institutional responses to dispel rumours were limited. A key contribution of the paper is to highlight the lived experiences of COVID-19 related rumours on marginalised groups. The paper argues that there is a need for clear government action using health promotion messages to tackle rumours (health-related or otherwise), mis/disinformation and mitigating the consequences (hatred and tensions) at the community level.
From the Balkan towards Western Europe: Range expansion of the golden jackal (Canis aureus)—A climatic niche modeling approach

Abstract In recent decades, a rapid range expansion of the golden jackal (Canis aureus) towards Northern and Western Europe has been observed. The golden jackal is a medium‐sized canid, with a broad and flexible diet. Almost 200 different parasite species have been reported worldwide from C. aureus, including many parasites that are shared with dogs and cats and parasite species of public health concern. As parasites may follow the range shifts of their host, the range expansion of the golden jackal could be accompanied by changes in the parasite fauna in the new ecosystems. In the new distribution area, the golden jackal could affect ecosystem equilibrium, e.g., through changed competition situations or predation pressure. In a niche modeling approach, we project the future climatic habitat suitability of the golden jackal in Europe in the context of whether climatic changes promote range expansion. We use an ensemble forecast based on six presence‐absence algorithms to estimate the climatic suitability of C. aureus for different time periods up to the year 2100 considering different IPCC scenarios on future development. As predictor variables, we used six bioclimatic variables provided by worldclim. Our results clearly indicate that areas with climatic conditions analogous to those of the current core distribution area of the golden jackal in Europe will strongly expand towards the north and the west in future decades. Thus, the observed range expansion may be favored by climate change. The occurrence of stable populations can be expected in Central Europe. With regard to biodiversity and public health concerns, the population and range dynamics of the golden jackal should be surveyed. Correlative niche models provide a useful and frequently applied tool for this purpose. The results can help to make monitoring more efficient by identifying areas with suitable habitat and thus a higher probability of occurrence.
ZC3H12B/MCPIP2, a new active member of the ZC3H12 family

ZC3H12B is the most enigmatic member of the ZC3H12 protein family. The founding member of this family, Regnase-1/MCPIP1/ZC3H12A, is a well-known modulator of inflammation and is involved in the degradation of inflammatory mRNAs. In this study, for the first time, we characterized the properties of the ZC3H12B protein. We show that the biological role of ZC3H12B depends on an intact NYN/PIN RNase domain. Using RNA immunoprecipitation, experiments utilizing actinomycin D and ELISA, we show that ZC3H12B binds interleukin-6 (IL-6) mRNA in vivo, regulates its turnover, and results in reduced production of IL-6 protein upon stimulation with IL-1β. We verified that regulation of IL-6 mRNA stability occurs via interaction of ZC3H12B with the stem–loop structure present in the IL-6 3′UTR. The IL-6 transcript is not the only target of ZC3H12B. ZC3H12B also interacts with other known substrates of Regnase-1 and ZC3H12D, such as the 3′UTRs of IER3 and Regnase-1, and binds IER3 mRNA in vivo. Using immunofluorescence, we examined the localization of ZC3H12B within the cell. ZC3H12B forms small, granule-like structures in the cytoplasm that are characteristic of proteins involved in mRNA turnover. The overexpression of ZC3H12B inhibits proliferation by stalling the cell cycle in the G2 phase. This effect of ZC3H12B is also NYN/PIN dependent. The analysis of the ZC3H12B mRNA level reveals its highest expression in the human brain and the neuroblastoma cell line SH-SY5Y, although the factors regulating its expression remain elusive. Down-regulation of ZC3H12B in SH-SY5Y cells by specific shRNAs results in up-regulation of ZC3H12B-target mRNAs.
Nested Transformers for Hyperspectral Image Classification

Substantial deep learning methods have been utilized for hyperspectral image (HSI) classification recently. Vision Transformer (ViT) is skilled in modeling the overall structure of images and has been introduced to HSI classification task. However, the fixed patch division operation in ViT may lead to insufficient feature extraction, especially the features of the edges between patches will be ignored. To address this problem, we devise a workflow for HSI classification based on the Nested Transformers (NesT). The NesT employs the block aggregation module to extract edge information between patches, which realizes cross-block communication of nonlocal information and optimizes global information extraction. In this paper, the NesT is used for HSI classification for the first time. The experiments are carried out on four widely used hyperspectral datasets: Indian Pines, Salinas, Tea Farm, and Xiongan New Area (Matiwan Village). The obtained results reveal that the NesT can provide competitive results compared to conventional machine learning and deep learning methods and achieve top accuracy on four datasets, which proves the superiority of the NesT in HSI classification with limited training samples.
A Novel 4H-SiC JBS-Integrated MOSFET With Self-Pinching Structure for Improved Short-Circuit Capability

Monolithic integration of junction barrier-controlled Schottky (JBS) diode with SiC MOSFET (termed JMOS) offers unique advantages. However, the short-circuit (SC) ruggedness issue stands in the way of the development of the conventional JMOS. The purpose of this numerical study is to investigate a new 4H-SiC JMOS with a self-pinching (SP) structure formed in the JFET region (termed SP-JMOS). The SP structure features that an N-type current spread layer is sandwiched between the P+ layer and the buried P-shield layer, forming a lateral JFET channel. In the forward conduction state, the lateral JFET channel self-pinches off and clamps the potential, thus limiting the saturation current of the device. In the blocking state, both the P+ layer and the buried P-shield layer collaboratively shield the Schottky contact and the SiC/SiO2 interface from a high electric field for long-term reliable operation. Numerical simulation results show that the proposed SP-JMOS not only withstands a roughly $2.6\times $ longer SC withstanding time than that of the conventional JMOS, but also shows an ultralow oxide electric field in the SP-JMOS.