Miracle-dz/UniFAR-FTUs huggingface dataset:
A Model Combining Multi Branch Spectral-Temporal CNN, Efficient Channel Attention, and LightGBM for MI-BCI Classification

Accurately decoding motor imagery (MI) brain-computer interface (BCI) tasks has remained a challenge for both neuroscience research and clinical diagnosis. Unfortunately, less subject information and low signal-to-noise ratio of MI electroencephalography (EEG) signals make it difficult to decode the movement intentions of users. In this study, we proposed an end-to-end deep learning model, a multi-branch spectral-temporal convolutional neural network with channel attention and LightGBM model (MBSTCNN-ECA-LightGBM), to decode MI-EEG tasks. We first constructed a multi branch CNN module to learn spectral-temporal domain features. Subsequently, we added an efficient channel attention mechanism module to obtain more discriminative features. Finally, LightGBM was applied to decode the MI multi-classification tasks. The within-subject cross-session training strategy was used to validate classification results. The experimental results showed that the model achieved an average accuracy of 86% on the two-class MI-BCI data and an average accuracy of 74% on the four-class MI-BCI data, which outperformed current state-of-the-art methods. The proposed MBSTCNN-ECA-LightGBM can efficiently decode the spectral and temporal domain information of EEG, improving the performance of MI-based BCIs.
The PD-L1 Expression and Tumor-Infiltrating Immune Cells Predict an Unfavorable Prognosis in Pancreatic Ductal Adenocarcinoma and Adenosquamous Carcinoma

The tumor microenvironment (TME) plays a vital role in the development, progression, and metastasis of pancreatic cancer (PC). The composition of the TME and its potential prognostic value remains to be fully understood, especially in adenosquamous carcinoma of pancreas (ASCP) patients. Immunohistochemistry was used to explore the clinical significance of CD3, CD4, CD8, FoxP3, and PD-L1 expression within the TME and to identify correlations with the prognosis of PC in a series of 29 patients with ASCP and 54 patients with pancreatic ductal adenocarcinoma (PDAC). Data from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) were accessed to obtain the scRNA-seq data and transcriptome profiles. Seurat was used to process the scRNA-seq data, and CellChat was used to analyze cell–cell communication. CIBERSORT was used to approximate the constitution of tumor-infiltrating immune cell (TICs) profiles. Higher levels of PD-L1 were linked with a shorter overall survival in ASCP (p = 0.0007) and PDAC (p = 0.0594). A higher expression of CD3+ and CD8+ T-cell infiltration was significantly correlated with a better prognosis in PC. By influencing the composition of tumor-infiltrating immune cells (TICs), high levels of PD-L1 expression are linked with a shorter overall survival in ASCP and PDAC.
Effects of annealing on the structure and switching characteristics of VDF/TrFE copolymers

Abstract Structure-property relationship has been investigated in concern with the ferroelectric switching characteristics of a VDF(78)/TrFE(22) copolymer. Unoriented and oriented film samples prepared by melt-quenching and melt-extrusion, respectively, were subjected to annealing and resulting structural changes were characterized by SEM, X-ray, density and DSC measurements. It was found that annealing just above the Curie point (120–130°C) caused a marked increase in crystallinity, whereas annealing in the paraelectric state (130–145°C) induced a crystal growth into thick lamellae. Such structural changes resulted in the ferroelectric switching characteristics with larger remanent polarization and shorter switching time. The unoriented sample yielded a smaller remanent polarization than the oriented sample by a factor of π/4, which substantiated that polarization reversal occurred as a result of rotation of molecules rotation about their chain axis. The melt-extruded and well-annealed sample consisted o.
COVID-19 vaccine acceptance and associated factors among health workers in West Guji zone, Southern Ethiopia: Cross-sectional study

Background Currently, different COVID-19 vaccines are being developed and distributed worldwide to increase the proportion of the vaccinated people and as a result to halt the pandemic. However, the vaccination progress is different from place to place even among health care workers due to variation in vaccine acceptance. Therefore, this study aimed to assess the acceptance of COVID-19 vaccine and determinant factors among healthcare workers in west Guji zone, southern Ethiopia. Method and materials An institutional-based cross-sectional study design was employed to assess COVID-19 vaccine acceptance and associated factors among health care workers from July to August 2021. A simple random sampling technique was used to choose 421 representative healthcare workers from three hospitals in the west Guji Zone. The self-administrated questionnaire was used to collect data. Bivariate and multivariable logistic regression analyses were computed to identify factors associated with the acceptance of the COVID-19 vaccine. P < 0.05 was considered for significantly associated factors. Result From the representative health workers, 57, 47.02, and 57.9% of healthcare workers had good practice of COVID-19 prevention, adequate knowledge, and a positive attitude toward the COVID-19 vaccine consecutively. 38.1% of healthcare workers said they had a willingness to accept the COVI-19 vaccine. Profession (AOR-6, CI: 2.92–8.22), previous history of vaccine side effects (AOR: 3.67, CI: 2.75–11.41), positive attitude toward vaccine acceptance (AOR: 1.38, CI: 1.18–3.29), adequate knowledge toward COVID-19 vaccine (AOR: 3.33, CI: 1.36–8.12), and adequate practice of COVID-19 prevention measure (AOR: 3.45, CI: 1.39–8.61) were significant associated with COVID-19 vaccine acceptance. Conclusion The proportion of COVID-19 vaccine acceptance among health workers was found to be low. From the study variables, profession, previous history of vaccine side effects, positive attitude toward vaccine acceptance, adequate knowledge to ward off COVID-19 vaccine, and adequate practice of COVID-19 prevention measures were significantly associated with COVID-19 vaccine acceptance.
Improving nutritional and functional quality characteristics in bread by using flours obtained from fermentation of kidney beans and oats with Pleurotus ostreatus

ABSTRACT Pleurotus ostreatus is an edible fungus with several functional compounds. Previous studies have shown that solid-state fermentation of Phaseolus vulgaris and Avena sativa with P. ostreatus improves their functional properties. Since bread is a highly consumed foodstuff, the objective of this work was to improve its nutritional and functional properties based on P. vulgaris and A. sativa grains biotransformed by P. ostreatus. Results showed that bread made with flour of solid-state fermented grains, provided a higher antioxidant capacity compared to bread made without fermented grains flour. The antioxidant capacity was maintained even after in vitro simulated digestion assays. Bioaccessible protein and fiber content results showed an increase compared to commercial breads. Fermented-flour bread showed lower hardness in its crumb, changed color, and had a good sensory acceptability. This makes these flours potential ingredients in the development of baking goods, making the bread a vehicle for nutrient delivery.
Epigenetic Mechanisms and Nephrotic Syndrome: A Systematic Review

A small subset of people with nephrotic syndrome (NS) have genetically driven disease. However, the disease mechanisms for the remaining majority are unknown. Epigenetic marks are reversible but stable regulators of gene expression with utility as biomarkers and therapeutic targets. We aimed to identify and assess all published human studies of epigenetic mechanisms in NS. PubMed (MEDLINE) and Embase were searched for original research articles examining any epigenetic mechanism in samples collected from people with steroid resistant NS, steroid sensitive NS, focal segmental glomerulosclerosis or minimal change disease. Study quality was assessed by using the Joanna Briggs Institute critical appraisal tools. Forty-nine studies met our inclusion criteria. The majority of these examined micro-RNAs (n = 35, 71%). Study quality was low, with only 23 deemed higher quality, and most of these included fewer than 100 patients and failed to validate findings in a second cohort. However, there were some promising concordant results between the studies; higher levels of serum miR-191 and miR-30c, and urinary miR-23b-3p and miR-30a-5p were observed in NS compared to controls. We have identified that the epigenome, particularly DNA methylation and histone modifications, has been understudied in NS. Large clinical studies, which utilise the latest high-throughput technologies and analytical pipelines, should focus on addressing this critical gap in the literature.
An in-fiber Bragg grating sensor for contact force and stress measurements in articular joints

We present an in-fiber Bragg grating-based sensor (240 µm diameter) for contact force/stress measurements in articular joints. The contact force sensor and another Bragg grating-based pressure sensor (400 µm diameter) are used to conduct the first simultaneous measurements of contact force/stress and fluid pressure in intact cadaveric human hips. The contact force/stress sensor addresses limitations associated with stress-sensitive films, the current standard tools for contact measurements in joints, including cartilage modulus-dependent sensitivity of films and the necessity to remove biomechanically relevant anatomy to implant the films. Because stress-sensitive films require removal of anatomy, it has been impossible to validate the mechanical rationale underlying preventive or corrective surgeries, which repair these anatomies, by conducting simultaneous stress and pressure measurements in intact hips. Methods are presented to insert the Bragg grating-based sensors into the joint, while relevant anatomy is left largely intact. Sensor performance is predicted using numerical models and the predicted sensitivity is verified through experimental calibrations. Contact force/stress and pressure measurements in cadaveric joints exhibited repeatability. With further validation, the Bragg grating-based sensors could be used to study the currently unknown relationships between contact forces and pressures in both healthy and degenerated joints.
Numerical simulation of liquid-metal MHD flows in rectangular ducts

To design self-cooled liquid metal blankets for fusion reactors, one must know about the behaviour of MHD flows at high Hartmann numbers. In this work, finite difference codes are used to investigate the influence of Hartmann number M, interaction parameter N, wall conductance ratio c, and changing magnetic field, respectively, on the flow. As liquid-metal MHD flows are characterized by thin boundary layers, resolution of these layers is the limiting issue. Hartmann numbers up to 103 are reached in the two-dimensional case of fully developed flow, while in three-dimensional flows the limit is 102. However, the calculations reveal the main features of MHD flows at large M. They are governed by electric currents induced in the fluid. Knowing the paths of these currents makes it possible to predict the flow structure. Results are shown for two-dimensional flows in a square duct at different Hartmann numbers and wall conductivities. While the Hartmann number governs the thickness of the boundary layers, the wall conductivities are responsible for the pressure losses and the structure of the flows. The most distinct feature is the side layers where the velocities can exceed those at the centre by orders of magnitude. The three-dimensional results are also for a square duct. The main interest here is to investigate the redistribution of the fluid in a region where the magnetic field changes. Large axial currents are induced leading to the ‘M-shaped’ velocity profiles characteristic of MHD flow. So-called Flow Channel Inserts (FCI), of great interest in blanket design, are investigated. They serve to decouple the load carrying wall from the currents in the fluid. The calculations show that the FCI is indeed a suitable measure to reduce the pressure losses in the blanket.
Weighing the Impacts of Airbnb in Iceland: Multivariate Perspectives

This research sought to evaluate if the sharing economy leader, Airbnb, creates impacts that residents of Iceland feel they experience. The study also aimed to discover if rural and urban inhabitants have similar perspectives on Airbnb impacts. Airbnb’s entrepreneurial encroachment into the accommodation sector has caused a multitude of localities to manage an assortment of complex affairs. These matters are difficult to solve due to their changing, contradictory, and incomplete premise. The purpose of this research is to determine if Airbnb activity is prominent in Iceland and therefore causing the country to experience similar issues that officials are struggling to solve in many major cities worldwide. This was established by running descriptive statistics on data obtained through a voluntary survey. This research can aid in creating international legislative platforms to maximize the benefits and minimize the risks related to Airbnb, as matters in Iceland can show similarity to other global cities. Locally, the results discovered in Iceland will be valuable to the Icelandic Tourist Board’s ongoing research on tourism trends within the island. Tourism was pushed as a tool in Iceland after the 2008 financial crisis in response to the country’s failing fishing and aluminum industries. Tourism now accounts for upwards of 10 percent of Iceland’s Gross Domestic Product (GDP). There is a concern for the economic endeavor’s ability to diminish Iceland’s culture and nature, which are what draws tourists initially, making tourism a multiplex theme in Iceland. This research will contribute to the emerging scholarly work on tourism, Airbnb, and their impacts on sensitive polar regions that dictate the rest of the world’s climate such as Iceland.
Effect of non-extensivity during the collision between inward and outward ion acoustic solitary waves in cylindrical and spherical geometry

Abstract The head-on collision between two cylindrical/spherical ion acoustic solitary waves (IASWs) in un-magnetized plasmas comprising inertial ions and q-non-extensive electrons and positrons is investigated using the extended version of the Poincaré–Lighthill–Kuo perturbation method. How the interactions are taking place in cylindrical and spherical geometry are studied, and the collision is shown at different times. The non-planar geometry can modify analytical phase shifts following the head-on collision are derived. The effects of q-non-extensive electrons and positrons on the phase shift are studied. It is shown that the properties of the interaction of IASWs in cylindrical and spherical geometry are very different.
Identification of an Autophagy-Related Signature for Prognosis and Immunotherapy Response Prediction in Ovarian Cancer

Background: Ovarian cancer (OC) is one of the most malignant tumors in the female reproductive system, with a poor prognosis. Various responses to treatments including chemotherapy and immunotherapy are observed among patients due to their individual characteristics. Applicable prognostic markers could make it easier to refine risk stratification for OC patients. Autophagy is closely implicated in the occurrence and development of tumors, including OC. Whether autophagy -related genes can be used as prognostic markers for OC patients remains unclear. Methods: The gene transcriptome data of 374 OC patients were downloaded from The Cancer Genome Atlas (TCGA) database. The correlation between the autophagy levels and outcomes of OC patients was identified through the single sample gene set enrichment analysis (ssGSEA). Recognized molecular markers of autophagy in different clinical specimens were detected by immunohistochemistry (IHC) assay. The gene set enrichment analysis (GSEA), ESTIMATE, and CIBERSORT analysis were applied to explore the correlation of autophagy with the tumor immune microenvironment (TIME). Single-cell RNA-sequencing (scRNA-seq) data from seven OC patients were included for characterizing cell-cell interaction patterns of autophagy-high or low tumor cells. Machine learning, Stepwise Cox regression and LASSO-Cox analysis were used to screen autophagy hub genes, which were used to establish an autophagy-related signature for prognosis evaluation. Four tumor immunotherapy cohorts were obtained from the GEO (Gene Expression Omnibus) database and the literature for autophagy risk score validation. Results: The autophagy levels were closely related to the prognosis of the OC patients. Additionally, the autophagy levels were correlated with TIME status including immune score, and immune-cell infiltration. The scRNA-seq analysis found that tumor cells with high or low autophagy levels had different interactions with immune cells, especially macrophages. Eight autophagy-hub genes (ZFYVE1, AMBRA1, LAMP2, TRAF6, PDPK1, ATG2B, DAPK1 and TP53INP2) were screened for an autophagy-related signature. According to this signature, higher risk score was correlated with poor prognosis and better immunotherapy response in the OC patients. Conclusions: The autophagy-related signature is applicable to predict the prognosis and immune checkpoint inhibitors (ICIs) therapy efficiency in OC patients. It is possible to identify OC patients who will respond to ICIs therapy and have a favorable prognosis, although more verification is needed.
Pressure distribution in solid samples compressed by toroidal anvils

We report the measurements of the three-dimensional pressure distribution in a sample of NaCl compressed to 6 GPa by apposed anvils with toroidal geometry. The results were obtained by energy-dispersive synchrotron X-ray diffraction using a V4-Paris-Edinburgh (PE) press with sintered diamond anvils and the incident beam directed along the thrust axis. This particular scattering geometry may be useful for other types of diffraction experiments using the PE press at synchrotron sources.
Hausdorff dimension of sets of non-differentiability points of Cantor functions

Abstract Each number a in the segment (0, ½) produces a Cantor set, Ca, by putting b = 1 − 2a and recursively removing segments of relative length b from the centres of the interval [0, 1] and the intervals which are subsequently generated. The distribution function of the uniform probability measure on Ca is a Cantor function, fa. When a = 1/3 = b, Ca is the standard Cantor set, C, and fa is the standard Cantor function, f. The upper derivative of f is infinite at each point of C and the lower derivative of f is infinite at most points of C in the following sense: the Hausdorff dimension of C is ln(2)/ln(3) and the Hausdorff dimension of S = {x ∈ C: the lower derivative of f is finite at x} is [ln(2)/ln(3)]2. The derivative of f is zero off C, the derivative of f is infinite on C — S, and S is the set of non-differentiability points of f. Similar results are established in this paper for all Ca: the Hausdorff dimension of Ca is ln (2)/ln (1/a) and the Hausdorff dimension of Sa is [ln (2)/ln (1/a)]2. Removing k segments of relative length b and leaving k + 1 intervals of relative length a produces a Cantor set of dimension ln(k + l)/ln(1/a); the dimension of the set of non-differentiability points of the corresponding Cantor function is [ln (k + l)/ln (1/a)]2.
CO-INFECTING PHAGES IMPEDE EACH OTHER’S ENTRY INTO THE CELL

Bacteriophage lambda tunes its propensity to lysogenize based on the number of viral genome copies inside the infected cell. Viral self-counting is believed to serve as a way of inferring the abundance of available hosts in the environment. This interpretation is premised on an accurate mapping between the extracellular phage-to-bacteria ratio and the intracellular multiplicity of infection (MOI). However, here we show this premise to be untrue. By simultaneously labeling phage capsids and genomes, we find that, while the number of phages landing on each cell reliably samples the population ratio, the number of phages entering the cell does not. Single-cell infections, followed in a microfluidic device and interpreted using a stochastic model, reveal that the probability and rate of individual phage entries decrease with MOI. This decrease reflects an MOI-dependent perturbation to host physiology caused by phage landing, evidenced by compromised membrane integrity and loss of membrane potential. The dependence of phage entry dynamics on the surrounding medium is found to result in a strong impact of environmental conditions on the infection outcome, while the protracted entry of co-infecting phages increases the cell-to-cell variability in infection outcome at a given MOI. Our findings demonstrate the previously unappreciated role played by entry dynamics in determining the outcome of bacteriophage infection.
Remote sensing monitoring and analysis of coastal infrastructures’ water environment effects in the Guangdong-Hong Kong-Macao greater Bay Area

With the rapid development of the Guangdong-Hong Kong-Macao Greater Bay Area (GBA), a large number of coastal infrastructures such as subsea tunnels and cross-sea bridges have been constructed. Meanwhile, construction processes such as land reclamation, piling, and sinking pipe installation have a certain impact on the water environment. Traditional sampling methods have been applied in the water condition monitoring, however, Remote Sensing (RS) and Geographic Information System (GIS) based technology have advantages in methods, efficiency, and scale. Thus, in this study, the construction processes of both Shenzhen Bay Bridge (SZB) and Hong Kong-Zhuhai-Macao Bridge (HZMB) are surveyed by using spatial analysis, visualization, and other methods. Moreover, suspended sediment concentration (SSC) and chlorophyll-a (Chla) concentration of the surrounding water before, during, and after the construction have been monitored. A comparative analysis has been adopted to illustrate the impact of the bridge construction process on the water environment. This study can provide an essential basis by using RS and GIS technology for studying the impact of largescale coastal infrastructures on the surrounding water.
The Operational Implementation of a Great Lakes Wave Forecasting System at NOAA/NCEP*

AbstractThe development of a Great Lakes wave forecasting system at NOAA’s National Centers for Environmental Prediction (NCEP) is described. The system is an implementation of the WAVEWATCH III model, forced with atmospheric data from NCEP’s regional Weather Research and Forecasting (WRF) Model [the North American Mesoscale Model (NAM)] and the National Digital Forecast Database (NDFD). Reviews are made of previous Great Lakes wave modeling efforts. The development history of NCEP’s Great Lakes wave forecasting system is presented. A performance assessment is made of model wind speeds, as well as wave heights and periods, relative to National Data Buoy Center (NDBC) measurements. Performance comparisons are made relative to NOAA’s Great Lakes Environmental Research Laboratory (GLERL) wave prediction system. Results show that 1- and 2-day forecasts from NCEP have good skill in predicting wave heights and periods. NCEP’s system provides a better representation of measured wave periods, relative to the GLER.