Miracle-dz/UniFAR-FTUs huggingface dataset:
Model of Chronoamperometric Response towards Glucose Sensing by Arrays of Gold Nanostructures Obtained by Laser, Thermal and Wet Processes

Non-enzymatic electrochemical glucose sensors are of great importance in biomedical applications, for the realization of portable diabetic testing kits and continuous glucose monitoring systems. Nanostructured materials show a number of advantages in the applications of analytical electrochemistry, compared to macroscopic electrodes, such as great sensitivity and little dependence on analyte diffusion close to the electrode–solution interface. Obtaining electrodes based on nanomaterials without using expensive lithographic techniques represents a great added value. In this paper, we modeled the chronoamperometric response towards glucose determination by four electrodes consisting of nanostructured gold onto graphene paper (GP). The nanostructures were obtained by electrochemical etch, thermal and laser processes of thin gold layer. We addressed experiments obtaining different size and shape of gold nanostructures. Electrodes have been characterized by field emission scanning electron microscopy (FE-SEM), X-ray photoelectron spectroscopy (XPS), cyclic voltammetry, and chronoamperometry. We modeled the current-time response at the potential corresponding to two-electrons oxidation process of glucose by the different nanostructured gold systems. The finest nanostructures of 10–200 nm were obtained by laser dewetting of 17 nm thin and 300 °C thermal dewetting of 8 nm thin gold layers, and they show that semi-infinite linear diffusion mechanism predominates over radial diffusion. Electrochemical etching and 17 nm thin gold layer dewetted at 400 °C consist of larger gold islands up to 1 μm. In the latter case, the current-time curves can be fitted by a two-phase exponential decay function that relies on the mixed second-order formation of adsorbed glucose intermediate followed by its first-order decay to gluconolactone.
Epidemiology and Outcome of Early-Onset Acute Kidney Injury and Recovery in Critically Ill COVID-19 Patients: A Retrospective Analysis

Background: The clinical significance of early-onset acute kidney injury (EO-AKI) and recovery in severe COVID-19 intensive care unit (ICU) patients is poorly documented. Objective: The aim of the study was to assess the epidemiology and outcome of EO-AKI and recovery in ICU patients admitted for SARS-CoV-2 pneumonia. Design: This was a retrospective single-centre study. Setting: The study was carried out at the medical ICU of the university hospital of Clermont-Ferrand, France. Patients: All consecutive adult patients aged ≥18 years admitted between 20 March 2020 and 31 August 2021 for SARS-CoV-2 pneumonia were enrolled. Patients with chronic kidney disease, referred from another ICU, and with an ICU length of stay (LOS) ≤72 h were excluded. Interventions: EO-AKI was defined on the basis of serum creatinine levels according to the Kidney Disease Improving Global Outcomes criteria, developing ≤7 days. Depending on renal recovery, defined by the normalization of serum creatinine levels, EO-AKI was transient (recovery within 48 h), persistent (recovery between 3 and 7 days) or AKD (no recovery within 7 days after EO-AKI onset). Measurements: Uni- and multivariate analyses were performed to determine factors associated with EO-AKI and EO-AKI recovery. Main Results: EO-AKI occurred in 84/266 (31.5%) study patients, of whom 42 (50%), 17 (20.2%) and 25 (29.7%) had EO-AKI stages 1, 2 and 3, respectively. EO-AKI was classified as transient, persistent and AKD in 40 (47.6%), 15 (17.8%) and 29 (34.6%) patients, respectively. The 90-day mortality was 87/244 (35.6%) and increased with EO-AKI occurrence and severity: no EO-AKI, 38/168 (22.6%); EO-AKI stage 1, 22/39 (56.4%); stage 2, 9/15 (60%); and stage 3, 18/22 (81.8%) (p < 0.01). The 90-day mortality in patients with transient or persistent AKI and AKD was 20/36 (55.6%), 8/14 (57.1%) and 21/26 (80.8%), respectively (p < 0.01). MAKE-90 occurred in 42.6% of all patients. Conclusions: In ICU patients admitted for SARS-CoV-2 pneumonia, the development of EO-AKI and time to recovery beyond day 7 of onset were associated with poor outcome.
Coordinating supply and demand applied Bass diffusion modelling

Demand management concerns what customers need and want, while supply management focuses on producing products/services to fulfill demand. It is challenging in coordinating demand and supply from both sides. Multi-method modeling, which is an interesting combination between system dynamics and agent-based models, is adapted to address this issue through the Bass diffusion model to replicate a non-competitive supply chain, including a retailer, a wholesaler, and a factory in this study. The research findings show that there is a bullwhip effect on the supply chain due to sudden changes in demand impacted by marketing efforts, namely advertising, words of mouth, and electronic words of mouth. It is recommended that in the process of sales and operations planning, businesses should implement, measure, and estimate marketing effectiveness corresponding with supply capabilities. Additionally, through the study, the strengths and weaknesses of the multi-method simulation in facilitating business research reflect through multiple scenarios running with cost and time efficiency, as well as the validity of the study findings associated with modelers’ decisions on the model’s level of simplicity and elaboration.
3D cell culture model: From ground experiment to microgravity study

Microgravity has been shown to induce many changes in cell growth and differentiation due to offloading the gravitational strain normally exerted on cells. Although many studies have used two-dimensional (2D) cell culture systems to investigate the effects of microgravity on cell growth, three-dimensional (3D) culture scaffolds can offer more direct indications of the modified cell response to microgravity-related dysregulations compared to 2D culture methods. Thus, knowledge of 3D cell culture is essential for better understanding the in vivo tissue function and physiological response under microgravity conditions. This review discusses the advances in 2D and 3D cell culture studies, particularly emphasizing the role of hydrogels, which can provide cells with a mimic in vivo environment to collect a more natural response. We also summarized recent studies about cell growth and differentiation under real microgravity or simulated microgravity conditions using ground-based equipment. Finally, we anticipate that hydrogel-based 3D culture models will play an essential role in constructing organoids, discovering the causes of microgravity-dependent molecular and cellular changes, improving space tissue regeneration, and developing innovative therapeutic strategies. Future research into the 3D culture in microgravity conditions could lead to valuable therapeutic applications in health and pharmaceuticals.
The Relationship Between Psychological Flexibility and Depression, Anxiety and Stress: A Latent Profile Analysis

Purpose To explore the potential classification of psychological flexibility (PF) among Chinese college students, analyze whether there is group heterogeneity in PF, and discuss the differences in the latent profile of PF in the negative emotions of depression, anxiety, and stress. Methods A total of 1769 college students were investigated using the Psychological Flexibility Questionnaire and Depression-Anxiety-Stress Self-rating Scale, and heterogeneity was tested by latent profile analysis. Results The PF of college students can be divided into three latent profiles: self-contradiction group (19.2%), high PF group (34.1%), and low PF group (46.7%). The scores of depression, anxiety, and stress are significantly different among the groups. Conclusion There is obvious group heterogeneity in the PF of college students, and they can be divided into the self-contradiction group, the high PF group, and the low PF group. The self-contradiction and low PF groups score significantly higher on the negative emotions of depression, anxiety, and stress than the high PF group.
The Effects of Static Stretching Intensity on Range of Motion and Strength: A Systematic Review

The aim of this study was to systematically review the evidence on the outcomes of using different intensities of static stretching on range of motion (ROM) and strength. PubMed, Web of Science and Cochrane controlled trials databases were searched between October 2021 and February 2022 for studies that examined the effects of different static stretching intensities on range of motion and strength. Out of 6285 identified records, 18 studies were included in the review. Sixteen studies examined outcomes on ROM and four on strength (two studies included outcomes on both ROM and strength). All studies demonstrated that static stretching increased ROM; however, eight studies demonstrated that higher static stretching intensities led to larger increases in ROM. Two of the four studies demonstrated that strength decreased more following higher intensity stretching versus lower intensity stretching. It appears that higher intensity static stretching above the point of discomfort and pain may lead to greater increases in ROM, but further research is needed to confirm this. It is unclear if high-intensity static stretching leads to a larger acute decrease in strength than lower intensity static stretching.
Positive Touch Deprivation during the COVID-19 Pandemic: Effects on Anxiety, Stress, and Depression among Italian General Population

Physical distancing due to the COVID-19 Pandemic has limited the opportunities for family members, friends, and significant others to show physical affection (i.e., hugs, kisses, caresses, holding hands) during social interactions. The present study investigated the effects of positive touch and psychological distress in 991 Italian participants (Mage = 34.43, SD = 14.27). Results showed the frequency of hugs with the cohabiting partner significantly decreased the symptoms of depression (β = −1.187, p = 0.018, eβ = 0.30, 95% CI = 0.11–0.82), whereas the frequency of caresses with cohabiting relatives predicted the symptoms of anxiety (β = 0.575, p = 0.034, eβ = 1.78, 95% CI = 1.04–3.03). The frequency of hugs (β = −0.609, p = 0.049, eβ = 0.54, 95% CI = 0.30–1.00), and kisses (β = 0.663, p = 0.045, eβ = 1.94, 95% CI = 1.01–3.71) with non-cohabiting relatives predicted the symptoms of anxiety (χ2 = 1.35, df = 5, p = 0.93). These results suggest the importance of positive touch on psychological well-being in the social context.
Facile method for immobilization of protein on elastic nanofibrous polymer membranes

Surface modification of polymeric scaffolds for biomedical applications is a versatile and widely used method to improve interactions between scaffolds and cells. Specifically, chemical immobilization of proteins to polymeric scaffolds provides significant advantages such as stable and biocompatible properties, however, it generally requires expensive instruments or complex steps. In this study, the facile method is presented that changes poly (l-lactide-co-caprolactone) electrospun nanofibrous membranes to be cell-friendly and bioactive by chemical immobilization of proteins onto membranes. The model protein, bovine serum albumin was bound onto the nanofibrous membranes via aminolysis and subsequent covalent grafting. The surface modification effects of the nanofibrous membranes including surface morphologies, mechanical properties, and wettability were investigated. In addition, in vitro studies have demonstrated that adhesion and proliferation of human dermal fibroblasts are promoted in protein-immobilized membranes compared to bare nanofibrous membranes.
Genome-Wide Characterization and Expression Analysis of Transcription Factor Families in Desert Moss Syntrichia caninervis under Abiotic Stresses

Transcription factor (TF) families play important roles in plant stress responses. S. caninervis is a new model moss for plant desiccation tolerance studies. Here, we report a high-confidence identification and characterization of 591 TFs representing 52 families that covered all chromosomes in S. caninervis. GO term and KEGG pathway analysis showed that TFs were involved in the regulation of transcription, DNA-templated, gene expression, binding activities, plant hormone signal transduction, and circadian rhythm. A number of TF promoter regions have a mixture of various hormones-related cis-regulatory elements. AP2/ERF, bHLH, MYB, and C2H2-zinc finger TFs were the overrepresented TF families in S. caninervis, and the detailed classification of each family is performed based on structural features. Transcriptome analysis revealed the transcript abundances of some ScAP2/ERF, bHLH, MYB, and C2H2 genes were accumulated in the treated S. caninervis under cold, dehydration, and rehydration stresses. The RT-qPCR results strongly agreed with RNA-seq analysis, indicating these TFs might play a key role in S. caninervis response to abiotic stress. Our comparative TF characterization and classification provide the foundations for functional investigations of the dominant TF genes involved in S. caninervis stress response, as well as excellent stress tolerance gene resources for plant stress resistance breeding.
Characterization of the Protein Corona of Three Chairside Hemoderivatives on Melt Electrowritten Polycaprolactone Scaffolds

In tissue engineering, the relationship between a biomaterial surface and the host’s immune response during wound healing is crucial for tissue regeneration. Despite hemoderivative functionalization of biomaterials becoming a common tissue-engineering strategy for enhanced regeneration, the characteristics of the protein–biomaterial interface have not been fully elucidated. This study characterized the interface formed by the adsorbed proteins from various hemoderivatives with pristine and calcium phosphate (CaP)-coated polycaprolactone (PCL) melt electrowritten scaffolds. PCL scaffolds were fabricated by using melt electrospinning writing (MEW). Three hemoderivatives (pure platelet-rich plasma (P-PRP), leucocyte platelet-rich plasma (L-PRP) and injectable platelet-rich fibrin (i-PRF)) and total blood PLASMA (control) were prepared from ovine blood. Hemoderivatives were characterized via SEM/EDX, cross-linking assay, weight loss, pH and protein quantification. The interface between PCL/CaP and hemoderivative was examined via FTIR, XPS and electrophoresis. i-PRF/PCL-CaP (1653 cm−1), PLASMA/PCL-CaP (1652 cm−1) and i-PRF/PCL (1651 cm−1) demonstrated a strong signal at the Amide I region. PLASMA and i-PRF presented similar N1s spectra, with most of the nitrogen involved in N-C=O bonds (≈400 eV). i-PRF resulted in higher adsorption of low molecular weight (LMW) proteins at 60 min, while PLASMA exhibited the lowest adsorption. L-PRP and P-PRP had a similar pattern of protein adsorption. The characteristics of biomaterial interfaces can be customized, thus creating a specific hemoderivative-defined layer on the PCL surface. i-PRF demonstrated a predominant adsorption of LMW proteins. Further investigation of hemoderivative functionalized biomaterials is required to identify the differential protein corona composition, and the resultant immune response and regenerative capacity.
Bidirectional effects of oral anticoagulants on gut microbiota in patients with atrial fibrillation

Background The imbalance of gut microbiota (GM) is associated with a higher risk of thrombosis in patients with atrial fibrillation (AF). Oral anticoagulants (OACs) have been found to significantly reduce the risk of thromboembolism and increase the risk of bleeding. However, the OAC-induced alterations in gut microbiota in patients with AF remain elusive. Methods In this study, the microbial composition in 42 AF patients who received long-term OAC treatment (AF-OAC group), 47 AF patients who did not (AF group), and 40 volunteers with the risk of AF (control group) were analyzed by 16S rRNA gene sequencing of fecal bacterial DNA. The metagenomic functional prediction of major bacterial taxa was performed using the Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) software package. Results The gut microbiota differed between the AF-OAC and AF groups. The abundance of Bifidobacterium and Lactobacillus decreased in the two disease groups at the genus level, but OACs treatment mitigated the decreasing tendency and increased beneficial bacterial genera, such as Megamonas. In addition, OACs reduced the abundance of pro-inflammatory taxa on the genus Ruminococcus but increased certain potential pathogenic taxa, such as genera Streptococcus, Escherichia-Shigella, and Klebsiella. The Subgroup Linear discriminant analysis effect size (LEfSe) analyses revealed that Bacteroidetes, Brucella, and Ochrobactrum were more abundant in the anticoagulated bleeding AF patients, Akkermansia and Faecalibacterium were more abundant in the non-anticoagulated-bleeding-AF patients. The neutrophil-to-lymphocyte ratio (NLR) was lower in the AF-OAC group compared with the AF group (P < 0.05). Ruminococcus was positively correlated with the NLR and negatively correlated with the CHA2DS2-VASc score (P < 0.05), and the OACs-enriched species (Megamonas and Actinobacteria) was positively correlated with the prothrombin time (PT) (P < 0.05). Ruminococcus and Roseburia were negatively associated with bleeding events (P < 0.05). Conclusions Our study suggested that OACs might benefit AF patients by reducing the inflammatory response and modulating the composition and abundance of gut microbiota. In particular, OACs increased the abundance of some gut microbiota involved in bleeding and gastrointestinal dysfunction indicating that the exogenous supplementation with Faecalibacterium and Akkermansia might be a prophylactic strategy for AF-OAC patients to lower the risk of bleeding after anticoagulation.
Formation of large-volume, high-pressure plasmas in microhollow cathode discharges

We have developed two electrode configurations that employ one primary supply circuit with a variable resistor for large-volume, high-pressure glow discharges without glow-to-arc transitions, and have investigated their electrical and the photoimages in microhollow cathode sustained discharges. The applied voltage and the discharge current between electrodes were controlled by changing the resistance of a variable resistor, which could replace the secondary supply circuit in microhollow cathode sustained discharges for the formation of secondary discharge. The electrical and the optical measurements showed that the discharge passed through three distinct stages: no discharges, microhollow cathode discharges, and microhollow cathode sustained discharges. Compared with the two-supply circuit system that has a primary and a secondary supply circuit, this electrode configuration is very simple and inexpensive process in generating large-volume plasmas at high pressures.
Physically Based Satellite Retrieval of Precipitation Using a 3D Passive Microwave Radiative Transfer Model

Abstract A precipitation retrieval algorithm based on the application of a 3D radiative transfer model to a hybrid physical-stochastic 3D cloud model is described. The cloud model uses a statistical rainfall clustering scheme to generate 3D cloud structure while ensuring that the stochastically generated quantities remain physically plausible. The radiative transfer model is applied to the cloud structures to simulate satellite remotely sensed upwelling microwave brightness temperatures TB's. Regression-derived relationships between model TB's and surface rainfall rates for Special Sensor Microwave/Imager (SSM/I) frequencies are used as the foundation of the retrieval algorithm, which is valid over oceans. A case study calibrates the retrieval algorithm to the European Centre for Medium-Range Weather Forecasts (ECMWF) numerical weather prediction model and applies the algorithm to SSM/I data obtained during the Tropical Ocean Global Atmosphere Coupled Ocean-Atmosphere Response Experiment. Comparisons betw.
Three-dimensional mesh simplification by subdivided edge classification

We propose a new quadric error metric (QEM) to simplify 3D mesh models. The new metric is based on the subdivided edge classification to preserve object discontinuities efficiently. After we classify edges into four different types: interior, boundary, boundary incident, and complex edges, we process them according to their types and features in the 3D model. We have tested the proposed algorithm with various VRML models. Simulation results show that the proposed metric is superior to the conventional QEM in maintaining object discontinuities efficiently.
ROC: Estimation of the Area Under a Receiver Operating Characteristic Curve

Appreciation and use of receiver operating characteristic (ROC) methods for diagnostic purposes is increasing rapidly (Hsiao, Bartko, & Potter, 1989; Murphy, Berwick, Weinstein, Borus, Budman, & Klerman, 1987). Hanley and McNeil (1982) provided a practical method of estimating the area under a ROC using the Wilcoxon statistic. They also developed a nonparametric method for comparing ROC curves from the same sample (Hanley & McNeil, 1983).
Decision trees from uncertain learning sets

Decision trees are structures which form a partition of some given measurement space for the purpose of classifying new measurements. Typically, the construction of the decision tree is performed using a learning set (or training set) where the class of each observation is certain. An uncertain learning set is a collection of measurements and probability masses over the set of classes for each measurement. The uncertainty in the learning set affects several of the results on decision trees previously presented in the literature. This paper suggests several new splitting criteria for constructing trees using uncertain learning sets. Additional extensions are provided for developing new misclassification estimates and test sample estimates for the decision tree. Finally, an application of these techniques in sensor fusion is outlined. <<ETX>>
Extracting causation knowledge from natural language texts

SEKE is a semantic expectation-based knowledge extraction system for extracting causation knowledge from natural language texts. It is inspired by human behavior on analyzing texts and capturing information with semantic expectations. The framework of SEKE consists of different kinds of generic templates organized in a hierarchical fashion. There are semantic templates, sentence templates, reason templates, and consequence templates. The design of templates is based on the expected semantics of causation knowledge. They are robust and flexible. The semantic template represents the target relation. The sentence templates act as a middle layer to reconcile the semantic templates with natural language texts. With the designed templates, SEKE is able to extract causation knowledge from complex sentences. Another characteristic of SEKE is that it can discover unseen knowledge for reason and consequence by means of pattern discovery. Using simple linguistic information, SEKE can discover extraction pattern from previously extracted causation knowledge and apply the newly generated patterns for knowledge discovery. To demonstrate the adaptability of SEKE for different domains, we investigate the application of SEKE on two domain areas of news articles, namely the Hong Kong stock market movement domain and the global warming domain. Although these two domain areas are completely different, in respect to their expected semantics in reason and consequence, SEKE can effectively handle the natural language texts in these two domains for causation knowledge extraction. © 2005 Wiley Periodicals, Inc. Int J Int Syst 20: 327–358, 2005.