Miracle-dz/UniFAR-FTUs huggingface dataset:
Research on the Development Status of China's Renewable Energy Industry - The Impact of Capital Structure on Company Performance

China's renewable energy industry has developed rapidly. However, due to China's current energy structure, coal plants still dominate the power generation, which poses a huge challenge to China's greenhouse gas reduction. On the other hand, this situation indicates that China's renewable industry still has great development potential and the sector can make a constructive contribution to China's response to climate change. However, in the process of developing the renewable sector, how to improve the profitability of enterprises and gradually lower the dependence on traditional energy is an important issue faced by corporate and government decision-makers. Therefore, from the perspective of capital structure, this paper aims to study its impact on the performance of renewable companies in China so that the society can achieve a “win-win” situation for enterprise development as well as environmental protection. By using pooled ordinary least squares and advanced panel data models, including fixed effects model and random effects model, the empirical results show that the relationship between capital structure and company performance is statistically significant in China's renewable industry. Specifically, the sustainable growth rate is significantly positively correlated with the total net profit margin, indicating that the sustainable growth model can be used to estimate the profitability of renewable companies in China.
The Efficacy and Safety of Qiming Granule for Dry Eye Disease: A Systematic Review and Meta-Analysis

Background Dry eye disease (DED) is a common complication in clinical practice. Qiming granule, a traditional Chinese patent medicine, is widely used in treating DED in China. However, its effect is still largely unknown. Objectives This research aims to evaluate the efficacy and safety of QG on DED. Methods Three English database and four Chinese databases without restriction on language and publication bias were searched. Qualified literature was selecting according to inclusion and exclusion criteria, extracted the data, and conducted a meta-analysis. Results A total of 11 articles were included in this meta-analysis. The methodological quality of included studies was low. The results showed that QG was effective for DED (RR:1.26, 95%CI:1.12 to 1.41, P=0.0001). The results combined with random effects model showed that QG could significantly prolong the tear film break up time (MD: 2.93, 95% CI: 2.22 to 3.65, P < 0.00001), increase the amount of tears in patients with DED (MD: 2.94, 95% CI: 1.83 to 4.04, P < 0.00001) and repair the corneal defects in patients (MD: -0.71, 95% CI: -1.25 to -0.17, P < 0.00001). Conclusions This study found that despite of the apparently positive results of some outcomes, it is premature to confirm the efficacy of QG in treating DED. More high-quality studies are still needed in the future to further confirm the efficacy and safety.
Developing Undergraduate Student Teachers’ Competence in Integrative STEM Teaching

Developing students’ literacy in Science, Technology, Engineering, and Mathematics (STEM) has been a major education issue since the 1990s. STEM education aims to support students to make informed decisions on social issues and become global citizens. In contrast with the interdisciplinary nature of STEM, initial teacher training usually focuses on teaching discrete subject disciplines. Novice teachers may also lack the relevant training in design and engineering to foster the practices in the classrooms. This article reports an initiative of preparing 25 pre-service teachers for integrative STEM teaching. The 24-h course combined the learning of design concepts and teaching inquiry within teaching the science content. Lesson activities of STEM classrooms engaged the novice teachers as “students”; and then they were prompted to reflect metacognitively on how they could support the “students” as teachers. Results from the questionnaires and focus group interviews indicated the importance of engaging the novices both as learners and future teachers of STEM education.
Sensor Measures of Affective Leaning

The aim of this study was to predict self-report data for self-regulated learning with sensor data. In a longitudinal study multichannel data were collected: self-report data with questionnaires and embedded experience samples as well as sensor data like electrodermal activity (EDA) and electroencephalography (EEG). 100 students from a private university in Germany performed a learning experiment followed by final measures of intrinsic motivation, self-efficacy and gained knowledge. During the learning experiment psychophysiological data like EEG were combined with embedded experience sampling measuring motivational states like affect and interest every 270 s. Results of machine learning models show that consumer grade wearables for EEG and EDA failed to predict embedded experience sampling. EDA failed to predict outcome measures as well. This gap can be explained by some major technical difficulties, especially by lower quality of the electrodes. Nevertheless, an average activation of all EEG bands at T7 (left-hemispheric, lateral) can predict lower intrinsic motivation as outcome measure. This is in line with the personality system interactions (PSI) theory of Julius Kuhl. With more advanced sensor measures it might be possible to track affective learning in an unobtrusive way and support micro-adaptation in a digital learning environment.
Response of Microphytobenthos and Benthic Bacteria Viability to Eutrophication in a Benthic–Pelagic Coupling Mesocosm Experiment

Excessive primary productivity due to nutrient inputs is a potential problem in coastal areas when resulting in high organic matter sedimentation rates. Microphytobenthos and heterotrophic bacteria are two components of the benthic ecosystem that contribute to nutrient cycling and decomposition of organic matter. In this context, the effects of nutrient addition and the associated in situ produced organic matter on microphytobenthos community composition and benthic bacterial viability were assessed in a mesocosm experiment for 58 days. The experimental setup included triplicate mesocosms filled with sediment and water under three levels of nutrient addition (“control,” “low,” and “high”). Benthic algal community composition was assessed using chemotaxonomy and bacterial viability was estimated using flow cytometry and a double-staining protocol. Multivariate analysis detected a significant effect of treatment and time on microphytobenthic community composition indicating a difference between control and low mesocosms and also between low and high treatments at Days 12 and 24 of the experiment. Nonetheless, microphytobenthos implied high resistance and redundancy of benthic algae to disturbance as all three treatments showed no significant difference in community structure between Days 0 and 58. Bacterial viability responded quickly to the high nutrient addition and was significantly lower than in the “control” and “low” treatments at Days 6 and 12. Both pelagic and benthic environmental variables were correlated to these changes in benthic community.
Pharmacological Inhibition of MALT1 Protease Leads to a Progressive IPEX-Like Pathology

Genetic disruption or short-term pharmacological inhibition of MALT1 protease is effective in several preclinical models of autoimmunity and B cell malignancies. Despite these protective effects, the severe reduction in regulatory T cells (Tregs) and the associated IPEX-like pathology occurring upon congenital disruption of the MALT1 protease in mice has raised concerns about the long-term safety of MALT1 inhibition. Here we describe the results of a series of toxicology studies in rat and dog species using MLT-943, a novel potent and selective MALT1 protease inhibitor. While MLT-943 effectively prevented T cell-dependent B cell immune responses and reduced joint inflammation in the collagen-induced arthritis rat pharmacology model, in both preclinical species, pharmacological inhibition of MALT1 was associated with a rapid and dose-dependent reduction in Tregs and resulted in the progressive appearance of immune abnormalities and clinical signs of an IPEX-like pathology. At the 13-week time point, rats displayed severe intestinal inflammation associated with mast cell activation, high serum IgE levels, systemic T cell activation and mononuclear cell infiltration in multiple tissues. Importantly, using thymectomized rats we demonstrated that MALT1 protease inhibition affects peripheral Treg frequency independently of effects on thymic Treg output and development. Our data confirm the therapeutic potential of MALT1 protease inhibitors but highlight the safety risks and challenges to consider before potential application of such inhibitors into the clinic.
Comparative Microbiological and Whole-Genome Analysis of Staphylococcus aureus Populations in the Oro-Nasal Cavities, Skin and Diabetic Foot Ulcers of Patients With Type 2 Diabetes Reveals a Possible Oro-Nasal Reservoir for Ulcer Infection

Patients with type 2 diabetes are at higher risk for periodontal disease and diabetic foot ulcer infections (DFUIs), the latter of which are predominantly caused by staphylococcal bacteria. Staphylococci have also been detected in the mouth, nose and gums (the oro-nasal cavity) of patients with periodontal disease and can move between the mouth and nose. The present study investigated if the oro-nasal cavity and/or periodontal pockets (PPs) in diseased gum tissue can provide a microbial reservoir for DFUIs. Eighteen patients with type 2 diabetes and at least three natural teeth (13 patients with ulcers and 5 patients without ulcers) underwent non-invasive microbiological sampling of PP, oro-nasal, skin and ulcer sites. Staphylococci were recovered using selective chromogenic agar, definitively identified and subjected to DNA microarray profiling, whole-genome sequencing and core-genome multilocus sequence typing (cgMLST). Staphylococcus aureus and Staphylococcus epidermidis were recovered from both the oro-nasal and ulcer sites of 6/13 and 5/13 patients with ulcers, respectively. Molecular typing based on the staphylococcal protein A (spa) gene and DNA microarray profiling indicated that for each patient investigated, S. aureus strains from oro-nasal and ulcer sites were identical. Comparative cgMLST confirmed that isolates from multiple anatomical sites of each individual investigated grouped into closely related, patient-distinct clusters (Clusters 1–7). Isolates belonging to the same cluster exhibited an average of 2.9 allelic differences (range 0–11). In contrast, reference genomes downloaded from GenBank selected as representatives of each sequence type identified in the present study exhibited an average of 227 allelic differences from the most closely related isolate within each cluster.
Bio-Inspired Techniques in a Fully Digital Approach for Lifelong Learning

Lifelong learning has deeply underpinned the resilience of biological organisms respect to a constantly changing environment. This flexibility has allowed the evolution of parallel-distributed systems able to merge past information with new stimulus for accurate and efficient brain-computation. Nowadays, there is a strong attempt to reproduce such intelligent systems in standard artificial neural networks (ANNs). However, despite some great results in specific tasks, ANNs still appear too rigid and static in real life respect to the biological systems. Thus, it is necessary to define a new neural paradigm capable of merging the lifelong resilience of biological organisms with the great accuracy of ANNs. Here, we present a digital implementation of a novel mixed supervised-unsupervised neural network capable of performing lifelong learning. The network uses a set of convolutional filters to extract features from the input images of the MNIST and the Fashion-MNIST training datasets. This information defines an original combination of responses of both trained classes and non-trained classes by transfer learning. The responses are then used in the subsequent unsupervised learning based on spike-timing dependent plasticity (STDP). This procedure allows the clustering of non-trained information thanks to bio-inspired algorithms such as neuronal redundancy and spike-frequency adaptation. We demonstrate the implementation of the neural network in a fully digital environment, such as the Xilinx Zynq-7000 System on Chip (SoC). We illustrate a user-friendly interface to test the network by choosing the number and the type of the non-trained classes, or drawing a custom pattern on a tablet. Finally, we propose a comparison of this work with networks based on memristive synaptic devices capable of continual learning, highlighting the main differences and capabilities respect to a fully digital approach.
CD38 Predicts Favorable Prognosis by Enhancing Immune Infiltration and Antitumor Immunity in the Epithelial Ovarian Cancer Microenvironment

The identification of predictive biomarkers and novel targets to optimize immunotherapy strategies for epithelial ovarian cancer (EOC) is urgently needed. CD38 is a multifunctional glycoprotein that acts as an ectoenzyme and immune receptor. However, the underlying immunological mechanisms and prognostic value of CD38 in EOC remain unclear. CD38 gene expression in EOC was evaluated by using Gene Expression Profiling Interactive Analysis (GEPIA) and TISIDB database. The prognostic value was calculated using GEPIA and Kaplan–Meier plotter. Gene set enrichment analysis was conducted to study the roles of CD38 in the EOC microenvironment. Furthermore, the relationship between CD38 expression level and immune cell infiltration was analyzed by the Tumor Immune Estimation Resource and TISIDB. The GEPIA and TISIDB databases showed that CD38 expression in EOC was higher than that in normal tissue and was highest in the immunoreactive subtype among the four molecular types. A total of 424 cases from GEPIA revealed that high levels of CD38 were associated with longer disease-free survival [hazard ratio (HR) = 0.66, P = 0.00089] and increased overall survival rate (HR = 0.67, P = 0.0016). Kaplan–Meier plotter also confirmed the prognostic value of CD38 in EOC. Data from The Cancer Genome Atlas database demonstrated that gene signatures in many categories, such as immune response and adaptive immune response, were enriched in EOC samples with high CD38 expression. In addition, CD38 was positively correlated with immune cell infiltration, especially infiltration of activated CD8+ T cells, CD4+ T cells, and B cells. CD38 is positively correlated with prognosis and immune cell infiltration in the EOC microenvironment and contributes to the regulation of antitumor immunity. CD38 could be used as a prognostic biomarker and potential immunotherapy target.
Analysis of the Gut Microbiota and Inflammatory Factors in mGluR5-Knockout Mice

Introduction Accumulating evidence indicates that the glutamatergic system plays an important role in the development of depression. Notably, the antidepressant effect of metabotropic glutamate receptor 5 (mGluR5) modulation is inconsistent across studies. Here, we attempted to identify the involvement of the gut microbiota and inflammation in mGluR5−/− mice. Methods mGluR5−/− mice and their wild-type littermates were used in our study. We used the open field (OF) and elevated plus maze (EPM) tests to assess anxiety-like behaviors, and we used the two-day forced swim test (FST) and tail suspension test (TST) to test despair-like behaviors. 16S rDNA was used to analyze the gut microbiota. Enzyme-linked immunosorbent assays (ELISAs) were used to measure the levels of inflammatory factors. Western blotting was used to detect the levels of various proteins. Results mGluR5−/− mice had no significant increase or decrease of despair-like behavior in the absence of stress exposure. However, mGluR5−/− mice exhibited despair-like behaviors following stress exposure. No significant changes in other glutamate receptors or representative synaptic proteins were detected in the prefrontal cortex (PFC) or hippocampus of mGluR5−/− mice. Very similar bacterial groups were observed in mGluR5−/− mice and wild-type controls. In addition, there was no significant difference in the α-diversity of the microbiota between mGluR5−/− mice and wild-type controls. The levels of all measured cytokines (IL-1β, IL-2, IL-4, IL-6, IL-10, and TNF-α) did not change significantly in the PFCs or colons of mGluR5−/− mice. Conclusion In conclusion, we deduced that mGluR5−/− mice are susceptible to despair-like behavior. The systemic knockout of mGluR5 did not affect the gut microbiota or inflammatory factors in mice.
The Slr0058 Protein From Synechocystis sp. PCC 6803 Is a Novel Regulatory Protein Involved in PHB Granule Formation

During phases of nitrogen starvation, the photosynthetic cyanobacterium Synechocystis sp. PCC 6803 produces polyhydroxybutyrate (PHB). This polymer is of high biotechnological relevance because of its potential as biodegradable plastic. Analysis of the Synechocystis genome revealed an operon (slr0058-slr0061) containing several genes, which are putatively related to the PHB metabolism. While Slr0058 show similarities with the regulatory phasin PhaF, the protein Slr0060 could serve as an intracellular PHB depolymerase. Investigation of respective knock-out mutants showed no distinct phenotype for the strain lacking Slr0060, whereas the Δslr0058 mutant displayed a growth impairment as well as a change in pigmentation. During nitrogen starvation, the Δslr0058 mutant produced in average more than twice the amount of PHB granules per cell, while the overall amount of PHB remained the same. This indicates that Slr0058 plays a role in PHB granule formation and controls it surface-to-volume ratio. GFP-tagged Slr0058 did not co-localize with PHB granules during nitrogen starvation but aggregated in distinct foci during vegetative growth. This work helps to better understand the PHB metabolism of Synechocystis sp. PCC 6803, coming closer to a sustainable, industrial production of PHB.
Synthesis and Electrochemical Property of FeOOH/Graphene Oxide Composites

A facile ultrasonication method was used to uniformly mix nanospindle-shaped FeOOH (80–100 nm) and a conductive matrix of graphene oxide (GO) to form FeOOH/GO composites. No carbon peak was observed in the X-ray diffraction pattern, indicating that the graphene oxide did not stack together and that the dispersion of graphene was very high. X-ray photoelectron spectroscopy (XPS) tests showed that the formation of Fe-O-C bonds played a positive role in electron transport, revealing that it has a certain impact on the electrochemical performance of FeOOH/GO. The FeOOH/GO was further characterized by TGA, and the content of GO in the synthesized sample was 6.68%. Compared with that of FeOOH, the initial discharge capacity of FeOOH/GO could reach 1437.28 mAh/g. Additionally, compared to that of pure FeOOH, the reversibility of the electrochemical reaction of FeOOH/GO was improved, and the impedance value was reduced. Finally, FeOOH/GO was used directly as a lithium-ion battery (LIB) anode material to improve the kinetics of the Lithium ions insertion/extraction process and improve ionic conductivity.
Inhibition of Streptococcus mutans Biofilm Formation and Virulence by Lactobacillus plantarum K41 Isolated From Traditional Sichuan Pickles

Among cariogenic microbes, Streptococcus mutans is considered a major etiological pathogen of dental caries. Lactobacilli strains have been promoted as possible probiotic agents against S. mutans, although the inhibitory effect of Lactobacilli on caries has not yet been properly addressed. The objective of this study was to screen Lactobacillus strains found in traditional Sichuan pickles and to evaluate their antagonistic properties against S. mutans in vitro and in vivo. In the current study, we analyzed 54 Lactobacillus strains isolated from pickles and found that strain L. plantarum K41 showed the highest inhibitory effect on S. mutans growth as well as on the formation of exopolysaccharides (EPS) and biofilm in vitro. Scanning electron microscopy (SEM) and confocal laser scanning microscope (CLSM) revealed the reduction of both EPS and of the network-like structure in S. mutans biofilm when these bacteria were co-cultured with strain L. plantarum K41. Furthermore, when rats were treated with strain L. plantarum K41, there was a significant reduction in the incidence and severity of dental caries. Due to K41’s origin in a high salinity environment, it showed a high tolerance to acids and salts. This may give this strain an advantage in harsh oral conditions. Results showed that L. plantarum K41 isolated from traditional Sichuan pickles effectively inhibited S. mutans biofilm formation and thus possesses a potential inhibitory effect on dental caries in vivo.
Fast Unsupervised Online Drift Detection Using Incremental Kolmogorov-Smirnov Test

Data stream research has grown rapidly over the last decade. Two major features distinguish data stream from batch learning: stream data are generated on the fly, possibly in a fast and variable rate; and the underlying data distribution can be non-stationary, leading to a phenomenon known as concept drift. Therefore, most of the research on data stream classification focuses on proposing efficient models that can adapt to concept drifts and maintain a stable performance over time. However, specifically for the classification task, the majority of such methods rely on the instantaneous availability of true labels for all already classified instances. This is a strong assumption that is rarely fulfilled in practical applications. Hence there is a clear need for efficient methods that can detect concept drifts in an unsupervised way. One possibility is the well-known Kolmogorov-Smirnov test, a statistical hypothesis test that checks whether two samples differ. This work has two main contributions. The first one is the Incremental Kolmogorov-Smirnov algorithm that allows performing the Kolmogorov-Smirnov hypothesis test instantly using two samples that change over time, where the change is an insertion and/or removal of an observation. Our algorithm employs a randomized tree and is able to perform the insertion and removal operations in O(log N) with high probability and calculate the Kolmogorov-Smirnov test in O(1), where N is the number of sample observations. This is a significant speed-up compared to the O(N log N) cost of the non-incremental implementation. The second contribution is the use of the Incremental Kolmogorov-Smirnov test to detect concept drifts without true labels. Classification algorithms adapted to use the test rely on a limited portion of those labels just to update the classification model after a concept drift is detected.
Optical Pulse Compression Schemes That Use Nonlinear Bragg Gratings

Nonlinear optical pulse compression of picosecond pulses typically requires long lengths of optical fiber and multiple components. Periodic structures, such as fiber Bragg gratings, are highly dispersive at wavelengths outside of the photonic bandgap. This implies that such gratings can be used as very short all-fiber compressors. In this paper a number of such compression schemes are reviewed involving uniform and nonuniform fiber Bragg gratings, relying on both soliton and nonsoliton compression principles. Experimental results supporting the corresponding underlying theory are also presented. Finally, an extension of one of the compression schemes is shown, which allows the generation of adjustable high-repetition rate soliton trains.