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Background: The present study aimed to investigate the potential role of perceived stress, impulsivity trait, executive dysfunction in non-suicidal self-injury (NSSI) thoughts among college students, as well as the gender differences. Methods: A sample of 890 university students completed self-report measures of NSSI thoughts in the past month, the level of perceived stress, impulsivity traits, and executive dysfunction. Results: Compared to those with low level of perceived stress, participants with high level of perceived stress reported significant higher levels of impulsivity trait and executive dysfunction, and higher frequency of NSSI thoughts, and there were no gender differences. Male participants with NSSI thoughts, compared to males without NSSI thoughts, reported significant higher levels of perceived stress and executive dysfunction. Female participants with NSSI thoughts, compared to females without NSSI thoughts, reported significant higher levels of perceived stress, impulsivity trait, and executive dysfunction. Hierarchical regression analysis revealed only executive dysfunction was associated with NSSI thoughts in males, while only perceived stress was associated with NSSI thoughts in females. Conclusion: This study revealed different influence factors for NSSI thoughts in male and female college students. NSSI thoughts in males were more likely associated with executive dysfunction while in females were due to recently perceived stress. [ABSTRACT FROM AUTHOR]

Taxol (paclitaxel) is the first approved microtubule‐stabilizing agent (MSA) by binding stoichiometrically to tubulin, which is considered to be one of the most significant advances in first‐line chemotherapy against diverse tumors. However, a large number of residue missence mutations harboring in the tubulin have been observed to cause acquired drug resistance, largely limiting the clinical application of Taxol and its analogs in chemotherapy. A systematic investigation of the intermolecular interactions between the Taxol and various tubulin mutants would help to establish a comprehensive picture of drug response to tubulin mutations in clinical treatment of cancer, and to design new MSA agents with high potency and selectivity to overcome drug resistance. In this study, we described an integration of in silico analysis and in vitro assay (iSiV) to profile Taxol against a panel of 149 clinically observed, cancer‐associated missence mutations in β‐tubulin at molecular and cellular levels, aiming to a systematic understanding of molecular mechanism and biological implication underlying drug resistance and sensitivity conferring from tubulin mutations. It is revealed that the Taxol‐resistant mutations can be classified into three types: (I) nonbonded interaction broken due to mutation, (II) steric hindrance caused by mutation, and (III) conformational change upon mutation. In addition, we identified three new Taxol‐resistant mutations (C239Y, T274I, and R320P) that can largely reduce the binding affinity of Taxol to tubulin at molecular level, in which the T274I and R320P were observed to considerably impair the antitumor activity of Taxol at cellular level. Moreover, a novel drug‐susceptible mutation (M363T) was also identified, which improves Taxol affinity by 2.6‐fold and decreases Taxol antitumor EC50 values from 29.4 to 18.7 μM. [ABSTRACT FROM AUTHOR]

Fluorescent imaging probes are crucial for exploring nucleus-related cellular events in live cells. Ideal probes should be photostable, small-sized, highly contrasted, and low in background. Here, we discovered that malachite green is a water-soluble near-infrared luminogen with aggregation-induced emission properties. Importantly, it can be used for living cell nucleus staining in a wash-free manner. [ABSTRACT FROM AUTHOR]

Carbon nanotube (CNT)/metal composites have attracted much attention due to their enhanced electrical and thermal performance. How to achieve the scalable fabrication of composites with efficient dispersion of CNTs to boost their performance remains a challenge for their wide realistic applications. Herein, the nanoscale dispersion of CNTs in the Stannum (Sn) matrix to boost thermal and electrical conductivity via facile ball milling techniques was demonstrated. The results revealed that CNTs were tightly attached to metal Sn, resulting in a much lower resistivity than that of bare Sn. The resistivity of Sn with 1 wt.% and 2 wt.% CNTs was 0.087 mΩ·cm and 0.056 mΩ·cm, respectively. The theoretical calculation showed that there was an electronic state near the Fermi level, suggesting its electrical conductivity had been improved to a certain extent. In addition, the thermal conductivity of Sn with 2 wt.% CNTs was 1.255 W·m−1·K−1. Moreover, Young's modulus of the composites with CNTs mass fraction of 10 wt.% had low values (0.933 MPa) under low strain conditions, indicating the composite shows good potential for various applications with different flexible requirements. The good electrical and thermal conductive CNT networks were formed in the metal matrix via facile ball milling techniques. This strategy can provide guidance for designing high-performance metal samples and holds a broad application potential in electronic packaging and other fields. [ABSTRACT FROM AUTHOR]

Various studies have shown that visfatin may be connected to metabolic syndrome (MS). However, epidemiological studies yielded conflicting outcomes. The purpose of this article was to highlight the relationship between the plasma visfatin level and MS risk by conducting a meta-analysis of available literature. A comprehensive literature search of eligible studies was done up to January 2023. Data were presented as standard mean difference (SMD). Observational methodological meta-analysis was conducted to assess the relationships between visfatin levels and MS. The visfatin levels between patients with MS or not were calculated by SMD and 95% confidence interval (CI) using the random-effects model. Funnel plot (visually inspect publication bias), Egger's linear regression test and Begger's linear regression test were applied to describe the risk of publication bias. A sensitivity analysis was performed via sequentially omitting each of the study one by one. In total, 16 eligible studies comprising 1016 cases and 1414 healthy controls finally enrolled in the current meta-analysis for pooling meta-analysis. Overall, the meta-analysis results revealed that visfatin levels in MS patients were significantly greater than that of controls group (SMD: 0.60, 95% CI=0.18–1.03, I2=95%, p<0.001). The results of the subgroup analysis showed that gender did not affect the results of meta-analysis. This meta-analysis shed light on the fact that circulating visfatin levels were significantly higher in patients with MS than in the controls group. Visfatin may a chance to predict the occurrence of MS. [ABSTRACT FROM AUTHOR]

Multi-view clustering (MVC) enhances the clustering performance of data by combining correlation information from different views. However, most existing MVC approaches process each sample independently and ignore the correlation amongst samples, resulting in reduced clustering performance. Although graph convolution network (GCN) can naturally capture correlation amongst samples by integrating the neighbors and structural information into representation learning, it is used in the semi-supervised learning scenario. In this paper, we propose a neighbor-aware deep MVC framework based on GCN (NMvC-GCN) for clustering multi-view samples and training GCN in a fully unsupervised manner. In addition, we design a consensus regularization to learn the common representations and introduce a clustering embedding layer to jointly optimize the clustering task and representation learning, so that the correlation amongst samples and that between the clustering task and representation learning can be fully explored. Extensive experiments on 10 datasets illustrate that NMvC-GCN significantly outperforms the state-of-the-art MVC methods. Our code will be released at https://github.com/dugzzuli/NMvC-GCN. • Graph Convolution Networks are adopted to fuse topological structure and sample features. • An unsupervised way is proposed to jointly train GCN of each view. • Consensus regularization pushes data from each view to generate consensus representation. • Experiments with real datasets are carried out to evaluate our methods. [ABSTRACT FROM AUTHOR]

The East Asian summer monsoon (EASM) was extremely strong in 2018, which substantially affected surface ozone (O3) in China. Taking 2018 and the average synthesis of 2003 and 2010 to represent the strong and weak EASM cases, respectively, GEOS-Chem with constant anthropogenic emission was employed to investigate the impact of the EASM on surface O3 in the east of China. Simulations show that surface O3 decreased in the northeast and the eastern coast of China and increased in most of the remaining regions during strong EASM. The difference in surface O3 between strong and weak EASM was around −15~7 ppbv. After analyzing relevant meteorological fields, it is found that the decrease in northeast China was mainly attributed to the large increase in vertical upward transport. The considerable decrease in the Huang-Huai-Hai region depended on the dilution and diffusion of eastward anomalous horizontal circulation. The increase in Hunan-Hubei-Guangdong Province was largely due to input from the north. In addition, the vast areas between the Yangtze River and the Yellow River were supported by higher temperatures and stronger shortwave solar radiation that promoted photochemical reactions. The reasons for changes in Shanxi-Sichuan-Yunnan Province were relatively more complex and thus require more in-depth exploration. [ABSTRACT FROM AUTHOR]

Background: Postmenopausal osteoporosis (POP) is a prevalent skeletal disease among elderly women. Previous study indicated that suppressor of cytokine signaling 3 (SOCS3) participates in the regulation of bone marrow stromal cell (BMSC) osteogenesis. Here, we further investigated the exact function and mechanism of SOCS3 in POP progression. Methods: BMSCs were isolated from Sprague–Dawley rats and treated with Dexamethasone (Dex). Alizarin Red staining and ALP activity assays were applied to assess the osteogenic differentiation of rat BMSCs under the indicated conditions. Osteogenic genes (ALP, OPN, OCN, COL1) mRNA levels were determined using quantitative RT-PCR. Luciferase reporter assay verified the interaction between SOCS3 and miR-218-5p. Rat models of POP were established in ovariectomized (OVX) rats to detect the in vivo effects of SOCS3 and miR-218-5p. Results: We found that silencing SOCS3 antagonized the suppressive effects of Dex on the osteogenic differentiation of BMSCs. SOCS3 was found to be targeted by miR-218-5p in BMSCs. The SOCS3 levels were negatively modulated by miR-218-5p in femurs of POP rats. MiR-218-5p upregulation promoted the BMSC osteogenic differentiation, while SOCS3 overexpression reversed the effects of miR-218-5p. Moreover, SOCS3 was highly expressed and miR-218-5p was downregulated in the OVX rat models, and silencing SOCS3 or overexpressing miR-218-5p alleviated POP in OVX rats by promoting osteogenesis. Conclusion: SOCS3 downregulation mediated by miR-218-5p increases osteoblast differentiation to alleviate POP. [ABSTRACT FROM AUTHOR]

Attributed network embedding (ANE) maps nodes in a network into a low-dimensional space while preserving the intrinsic essence of node attribute and network topology. Incorporating node attribute and network topology with more deeply and more harmoniously is a critical and challenging issue in the ANE, because node attribute and network topology are two kinds of heterogeneous information. Existing approaches fuse two kinds of heterogeneous information at different stages: i.e. before, during or after the learning process. In fact, fusions at different stages have their own advantages and disadvantages. To maximise the profit of utilising the attributed and networked information in ANE, we propose an Attributed Network Embedding model with Dual Fusion strategies (abbr. ANEDF), which consists of both mutually beneficial components: early fusion component for capturing the latent complementarity and late fusion component for extracting the unique and distinctive information from node attribute and network topology. The two components are co-trained during the learning process, which promotes information interaction and captures the consensus of heterogeneous information. Extensive experiments with the tasks of node classification, node clustering, link prediction and visualisation on eight publicly available networks have been conducted to evaluate the effectiveness and rationality of the proposed model. The experimental results demonstrate that ANEDF obtains the best classification, clustering and link prediction performance on 6–7 of 8 datasets, respectively. [ABSTRACT FROM AUTHOR]

Childhood witnessing domestic violence (CWDV) exerts short- and long-term negative impacts on emotional and behavioral health. The present study investigated the epidemiological features of CWDV, and its negative impact on psychological outcomes in a sample of Chinese college students. The mediating role of emotion regulation strategies on CWDV associations with psychological outcomes and gender differences in these relationships were examined. A total of 3,126 respondents (1,034 males; 2,086 females; 6 missing data in gender) completed the study questionnaire, which included demographic characteristics, CWDV, and suicide attempt history items as well as the Emotion Regulation Questionnaire (ERQ) and Affect Lability Scale-18 (ALS-18). Overall, 43.03% of the respondents reported CWDV, including 44.87% of males and 42.09% of females. Higher frequencies of CWDV were found to be related to the following factors: unstable marital status of parents; not being an only child; being a left-behind child, family financial difficulties, consumption of alcohol in the past year, and being in relatively poor physical condition. Among males, ERQ suppression scores were significantly higher for those men who experienced "often or every day" CWDV than for men who indicated that they did not have any history of CWDV (Bonferroni-corrected p = 0.047). More frequent CWDV was associated with higher ALS-18 scores and increased risk of suicide attempts in males and females (p < 0.05), and emotion regulation (suppression) was found to mediate the association between CWDV and affective lability among males. This study revealed high rates of CWDV, and serious impacts of CWDV on mental health in male and female Chinese college students. In males, but not females, emotion regulation strategy use, use of suppression, was found to act as a mediator in the association of CWDV with affective lability. Our findings suggest that interventions for individuals with CWDV should focus on the emotional regulation, which may help them improve mental health, especially in males. [ABSTRACT FROM AUTHOR]

Unsupervised domain adaptation (UDA), which can transfer knowledge from labeled source domain to unlabeled target domain, needs to access a large number of labeled source data in the process of generalization. However, the data of two domains may not be accessed at the same time due to data privacy protection. To solve this problem, source-data free domain adaptation (SFDA) began to receive attention. However, too little source information will lead to some performance gaps. To balance the issues between UDA and SFDA, a new setting called Prototype-based domain adaptation (Prototype-DA) is proposed, which further improves the practicability of UDA by using source category prototype instead of source data. At the same time, it can also ensure the privacy of source data like SFDA. Specifically, our training process can be divided into two steps. First, the source data is used to pre-train a source model, and the source category prototypes are obtained after the training of source model. Then, to generalize the source model to the target domain, category maximum mean discrepancy (Category-MMD) is defined so that the target data can be aligned with the source category prototypes. In this way, source category prototypes will transfer knowledge to the target domain together with the source model. Through source category prototypes, Prototype-DA can not only achieve the comparable results than the method using source data, but also protect the privacy of source data to some extent. Furthermore, the target category prototypes are constructed and the consistency between the labels of target category prototypes and the classification results is required. This prototype-label consistency regularization, proposed by us for the first time, helps to extract discriminative features in the target domain. Compared with the previous UDA methods and SFDA methods, extensive experiments on multiple public domain adaptation datasets show that Prototype-DA achieves the state-of-the-art results. At the same time, the traditional UDA theory is expanded to our method setting and makes a theoretical analysis to ensure the effectiveness of our method. [ABSTRACT FROM AUTHOR]

Hepatitis C virus (HCV) infected patients have been found to be more susceptible to metabolic syndrome (MetS), but the results remain unclear and lack of a meta-analysis. Databases including PubMed, Web of Science, EMBASE and the Cochrane Library were searched to identify all studies concerning HCV and MetS. Funnel plots combined with Begg's tests and Egger's tests were used to analysis the possible publication bias. The odds ratios (ORs) with 95% confidence intervals (CIs) were used to access the effect of HCV infection on the risk of MetS. Eight articles, involving a total of 57387 HCV patients were included. HCV infection was significantly associated with an increased incidence of MetS (OR = 1.73; 95% CI, 1.19–2.52). After adjustment according to the sensitivity analysis, one included article was removed to decrease the publication bias and high heterogeneity, of which the results showed that HCV infection was still associated with an increased incidence of MetS (OR = 1.93; 95% CI, 1.39–2.68). HCV patients tend to have a significant increased risk for MetS, but more large-scale studies are needed to confirm this and explore the exact mechanism. [ABSTRACT FROM AUTHOR]

• Individuals who suffered emotional neglect in childhood have reduced emotional empathy. • A history of emotional neglect leads individuals to exhibit reduced psychophysiological responses to others' pain, which is reflected in the reduction of early empathetic neural responses. • The neural mechanisms involved in emotional sharing were influenced by social relationships, which might mediate the racial biases exhibited in individual behaviors. Emotional neglect during childhood was associated with adverse long-term consequences for mental health and may impact neural responses by altering the trajectories of brain development. Pain empathy, a crucial social adaptive ability that recognizes and understands another person's pain, was found to be correlated with early developmental experiences. However, the impact of emotional neglect on neural responses related to pain empathy remains inadequately explored. Utilizing childhood trauma questionnaires and event-related potential (ERP), the electrical response of the brain to a specific stimulus, this study investigated the impact of emotional neglect experiences on pain empathy neural responses among 62 Chinese college students. The results of correlation analysis demonstrated a significant association between childhood emotional neglect scores and the empathic N2 responses (defined as pain minus non-pain conditions), representing the early emotional sharing process of pain empathy. The findings clarified the effects of specific forms of traumatic experiences on individuals' social functioning and laid the foundation for further exploring the impact of trauma on neural responses. [ABSTRACT FROM AUTHOR]

To analyze the application value of CT-enhanced scanning based on artificial intelligence algorithm in the diagnosis of gastric cancer and gastric lymphoma, the CT images of 80 patients with Borrmann type IV gastric cancer or primary gastric lymphoma diagnosed by endoscopic pathology were retrospectively collected. Meanwhile, a lymph node recognition algorithm based on OTSU threshold segmentation was proposed for CT image processing. The results showed that the missed diagnosis rate of suspected lymph nodes and the missed lymph node detection rate of this algorithm were substantially lower than those of other algorithms (P < 0.05). The probability of gastric wall motility disappearance, perigastric fat infiltration, and type A enhancement pattern in the Borrmann type IV gastric cancer group was higher than that in the gastric lymphoma group, with remarkable differences (P < 0.05). There was no remarkable difference between the Borrmann type IV gastric cancer group and the gastric lymphoma group in the probability of swollen lymph nodes under the renal hilum (P > 0.05). In addition, 5the sensitivity (83.17%), specificity (95.52%), and accuracy (93.08%) of the combined detection of the three CT signs (stomach wall motility, perigastric fat infiltration, and enhancement mode) were substantially improved compared with those of a single sign (P < 0.05). To sum up, the lymph node recognition algorithm based on OTSU threshold segmentation had better performance in detecting gastric lymph nodes than traditional algorithms. The CT image characteristics of gastric wall motility, perigastric fat infiltration, and enhancement pattern based on artificial intelligence algorithms were effective indicators for distinguishing gastric cancer and gastric lymphoma. [ABSTRACT FROM AUTHOR]

According to the gearing principle, the side mill for machining the helicoid (cylindrical helical surfaces of constant pitch) can be calculated from the parametric equation of the helicoid section curve. However, in practice, only a series of discrete point coordinates on the work-piece section curve were measured, which lead to the low calculation accuracy, especially when the section curve is composed of multi-segments, the calculation accuracy at the connection point (cusp) is lower. To improve the calculation accuracy, this paper first deduced the contact condition formula, and pointed out that the first derivation of discrete points had a great impact on the calculation accuracy. Then, an improved curve fitting method was proposed to calculate the first derivation of discrete points. In order to further improve the calculation accuracy at the cusp, a method of piecewise solving the cutter profile was proposed. Finally, calculation examples of the side mill profile of the main screw of a three screw pump, as well as a screw pump rotor, were carried out. The results show that the calculation accuracy of the improved curve fitting method is high, and the method of piecewise solving the cutter profile of discrete points is feasible. [ABSTRACT FROM AUTHOR]

A main form of information construction in colleges and universities is smart campus, which is a new model based on the improvement and perfection of digital campus construction. The development of smart campus is inseparable from the support of technologies such as Internet of Things (IoTs), cloud computing, and big data. By perceiving the teaching environment and intelligently identifying the characteristics of teachers and students, it can be used as a basis to improve the physical education, teaching environment, and digital teaching space, that is, an intelligent and diversified teaching environment for college teachers and students. In this study, we introduce an intelligent teaching mode into physical education classroom, construct the "six-pronge" intelligent classroom model, and apply the model by setting up a control and an experimental group to study the application effects of the proposed model in physical education teaching. The control group consists of the students who do not adopt the teaching mode, while students in the experimental group use the intelligent physical education teaching model. Through a comparative analysis, students' physical education classroom teaching atmosphere, students' learning interest and learning attitude, the proposed intelligent physical education classroom model are tested and verified. The analysis results show that after implementation of the "six-pronged" intelligent physical education classroom model, the physical education classroom atmosphere is active, and students have strong interest in learning and correct learning attitude. We believe that the model can help students complete pre-class preparation, in class teaching and after class practice supervision, and obtain a lot of knowledge about physical training. In addition, the model can help to cultivate students' lifelong physical education learning and exercise habits, and greatly improve the quality of physical education classroom teaching in colleges. [ABSTRACT FROM AUTHOR]

Based on computed tomography (CT) with a gradient weighted denoising algorithm, the image denoising technique was applied to diagnose bronchial and pulmonary fungal infection to discuss the features of CT images and the efficiency of the denoising algorithm. Therefore, it could assist clinicians in disease treatment. The clinical data and imaging data of 100 patients with invasive pulmonary fungal infection were collected in the hospital. All of them were rolled into a natural denoising CT group (routine group) and gradient weighted denoising algorithm-based image denoising group (algorithm group). The images from the routine group were processed by the routine natural denoising method, and the images from the algorithm group were denoised with the gradient weighted denoising algorithm. The results showed that the algorithm group had greater denoising efficiency and less denoising time compared with the routine group (P < 0.05). The diagnostic sensitivity, specificity, and accuracy of the denoised images from the algorithm group were higher markedly than the above three indicators of the routine group (P < 0.05). For bronchopulmonary infections, the sensitivity, specificity, and accuracy of the PDE model for CT denoised images were 99.00%, 96.87%, and 98.33%, the positive rate of chest CT examination was 86.2%, which was higher markedly than the rate of ordinary CT examination (70.5%), and the difference was statistically substantial (P < 0.05). Besides, the mean absolute error (MAE), peak signal to noise ratio (PSNR), and mean structural similarity index measure (MSSIM) of the algorithm group were better than those of the unprocessed images and the routine group (P < 0.05). Moreover, the algorithm group had a good visual effect. In conclusion, the gradient weighted denoising algorithm could effectively remove the noise and bar artifacts in CT images and well retain the edge details of CT images, thereby improving the quality of CT images. Therefore, it was suitable for clinical diagnosis and had practical application value. [ABSTRACT FROM AUTHOR]

Unsupervised domain adaptation aims to transfer knowledge from labeled source domain to unlabeled target domain. Traditional methods usually achieve domain adaptation by aligning the distributions between two domains once. We propose to align the distributions twice by a disentanglement and reconstruction process, named DTR (Disentanglement Then Reconstruction). Specifically, a feature extraction network shared by both source and target domains is used to obtain the original extracted features, then the domain invariant features and domain specific features are disentangled from the original extracted features. The domain distributions are explicitly aligned when disentangling domain invariant features. Based on the disentangled features, the class prototypes and domain prototypes can be estimated. Then, a reconstructor is trained by the disentangled features. By this reconstructor, we can construct prototypes in the original feature space using the corresponding class prototype and domain prototype similarly. The extracted features are forced to close the corresponding constructed prototypes. In this process, the distribution between two domains is implicitly aligned again. Experiment results on several public datasets confirm the effectiveness of our method. • Our method can use domain invariant features and domain specific features very well. • By learning more compact features, domain distributions will be aligned again. • The experiments on public datasets are conducted and the proposed method works well. • Thorough analysis experiments also illustrates the advantages of our method. [ABSTRACT FROM AUTHOR]

We evaluated the psychometric properties of the Chinese Precursors to Boredom Scales (C-PBS) with a sample of Chinese college students. The results show that the C-PBS had acceptable internal consistency reliability and criterion validity, and that the eight-factor model fit the data well. We also investigated the characteristics of precursors to boredom in Chinese college students. Apart from one factor (being underchallenged), all precursors were significantly and negatively correlated with students' self-efficacy for self-regulated learning, and with academic achievement. It is notable that low-income (vs. high-income) students who were bored during mathematics classes felt less monotony, lack of meaning, and opportunity costs. The C-PBS is, thus, a relevant instrument for the investigation of precursors to boredom in Chinese college students. [ABSTRACT FROM AUTHOR]

This study was to analyze the diagnostic effects of computed tomography (CT) and magnetic resonance imaging (MRI) in patients with cerebrovascular diseases (CVDs) based on low-rank matrix denoising (LRMD) algorithm. The LRMD algorithm was adopted for MRI diagnosis and CT diagnosis for comparative analysis. 129 CVD patients were selected as the research objects, 43 cases were diagnosed by CT, 43 cases were diagnosed by MRI under LRMD, and the other 43 cases were diagnosed by CT + MRI. The results showed that the diagnostic compliance rates (DCRs) of CT group in the cerebral hemorrhage (CH), cerebral infarction (CI), and cerebral aneurysm (CA) were 95.1%, 94.7%, and 70%, respectively, while those in the MRI group were 99.01%, 97.71%, and 100%, respectively. Thus, it was obtained that MRI diagnosis was much better than CT diagnosis, and CT + MRI showed the best diagnosis efficacy, showing statistical differences (P < 0.05). The accuracy, sensitivity, and specificity of MRI diagnosis under the LRMD algorithm were 96.28%, 88.76%, and 90.62%, respectively, which were superior to those of CT diagnosis (92.71%, 84.94%, and 80.71%, respectively). The diagnosis cost per case (DC/C) (799.73 ± 100.02 yuan) and the total diagnosis cost (TDC) (58,521.67 ± 301.62 yuan) in the MRI group were higher than those in the CT group (601.42 ± 83.61 yuan and 39,819.2 ± 198.72, respectively) (P < 0.05). In conclusion, CT + MRI under the LRMD algorithm showed good potential in diagnosis of CVD; MRI based on the LRMD algorithm showed a higher positive rate in the diagnosis of CA and was better than CT diagnosis, and CT + MRI showed the best diagnosis effect and could improve the clinical diagnosis rate. [ABSTRACT FROM AUTHOR]

We developed the Chinese version of the Achievement Emotions Questionnaire–Elementary School (AEQ-ES), and tested its internal and external validity with a sample of 426 Chinese elementary school students aged between 6 and 10 years in three academic settings (class, homework, and test) of mathematics classes. The hierarchical model of the AEQ-ES for our Chinese sample was consistent with those obtained with samples of students in similar age groups in Italy, Germany, and the United States. We assessed the achievement emotions of enjoyment, boredom, and anxiety and found that girls (vs. boys) reported more class-related enjoyment, more academic effort, less class-related anxiety, less boredom, and less homework-related boredom. Our results show that the Chinese version of the AEQ-ES is both valid and reliable; thus, it can be used in future studies. [ABSTRACT FROM AUTHOR]

Multi-view clustering aims to group similar samples into the same clusters and dissimilar samples into different clusters by integrating heterogeneous information from multi-view data. Non-negative matrix factorization (NMF) has been widely applied to multi-view clustering owing to its interpretability. However, most NMF-based algorithms only factorize multi-view data based on the shallow structure, neglecting complex hierarchical and heterogeneous information in multi-view data. In this paper, we propose a deep multiple non-negative matrix factorization (DMNMF) framework based on AutoEncoder for multi-view clustering. DMNMF consists of multiple Encoder Components and Decoder Components with deep structures. Each pair of Encoder Component and Decoder Component are used to hierarchically factorize the input data from a view for capturing the hierarchical information, and all Encoder and Decoder Components are integrated into an abstract level to learn a common low-dimensional representation for combining the heterogeneous information across multi-view data. Furthermore, graph regularizers are also introduced to preserve the local geometric information of each view. To optimize the proposed framework, an iterative updating scheme is developed. Besides, the corresponding algorithm called MVC-DMNMF is also proposed and implemented. Extensive experiments on six benchmark datasets have been conducted, and the experimental results demonstrate the superior performance of our proposed MVC-DMNMF for multi-view clustering compared to other baseline algorithms. [ABSTRACT FROM AUTHOR]

Microbial bioremediation based on nano- to micrometer-scale electron transport has been intensively studied during the past decade, but its application can be hindered by a deficiency of suitable electron acceptors or slow mass transportation at contaminated sites. Microbial long-distance electron transport (LDET), which can couple spatially separated redox reactions across distances in natural environments, has recently emerged at centimeter-length scales. LDET explains a range of globally important biogeochemical phenomena and overcomes the drawbacks of conventional bioremediation by directly linking distant electron donors and acceptors. Here, we highlight recent research outcomes in examining, characterizing, and engineering LDET, and describe how LDET can be exploited to develop advanced technologies for the bioremediation of soils and sediments. Long-distance electron transport (LDET) over a centimeter length has been discovered in natural environments worldwide. Unique geochemical fingerprints and electric signatures can be used to demonstrate the occurrence of LDET in sediments. Inspired by LDET in nature, artificial LDET with conductive materials can be created in soils and sediments. LDET in soils and sediments offers a great opportunity for developing advanced bioremediation techniques. [ABSTRACT FROM AUTHOR]

Source-free domain adaptation requires no access to the source domain training data during unsupervised domain adaption. This is critical for meeting particular data sharing, privacy, and license constraints, whilst raising novel algorithmic challenges. Existing source-free domain adaptation methods rely on either generating pseudo samples/prototypes of source or target domain style, or simply leveraging pseudo-labels (self-training). They suffer from low-quality generated samples/prototypes or noisy pseudo-label target samples. In this work, we address both limitations by introducing a novel Class Prototype Discovery (CPD) method. In contrast to all alternatives, our CPD is established on a set of semantic class prototypes each constructed for representing a specific class. By designing a classification score based prototype learning mechanism, we reformulate the source-free domain adaptation problem to class prototype optimization using all the target domain training data, and without the need for data generation. Then, class prototypes are used to cluster target features to assign them pseudo-labels, which highly complements the conventional self-training strategy. Besides, a prototype regularization is introduced for exploiting well-established distribution alignment based on pseudo-labeled target samples and class prototypes. Along with theoretical analysis, we conduct extensive experiments on three standard benchmarks to validate the performance advantages of our CPD over the state-of-the-art models. • We propose a novel Class Prototype Discovery method for solving the SFDA problem. • A prototype regularization is introduced based on distribution alignment strategy. • CPD outperforms a wide variety of state-of-the-art methods, often by a large margin. [ABSTRACT FROM AUTHOR]

Community search (CS) over attributed heterogeneous information networks (AHINs) takes both network structure and attributes of nodes into consideration, which can support personalized requirement and has gained great interest recently. Nevertheless, existing works are insensitive to the attributes that results from two limitations: (1) The structural cohesiveness metrics is insensitive to the slight quantity changes of nodes in a community. (2) The measurement adopted to measure the relevance between a community and given keywords is inappropriate. Additionally, the insensitivity may also lead to the free rider effect. To deal with these issues, in this paper, we first define structural cohesiveness by using the minimum number of neighbor nodes connected to each node in the community through a meta-path, then define keyword density with the path instances containing the given keywords, afterwards integrate both of them to propose an attribute-sensitive community model ASC that is sensitive to the attributes, and present the CS problem. In order to search community, we first propose a basic CS algorithm, then develop two index based CS algorithms to improve the efficiency, and theoretically prove that these two index based algorithms are more efficient than the basic algorithm. Comprehensive experiments conducted on five real-world datasets demonstrate the effectiveness of ASC and the efficiency of the developed algorithms. [ABSTRACT FROM AUTHOR]

Declining forests usually face uncertain regeneration dynamics and recovery trajectories, which are challenging to forest management. In this study, we investigated the decline pattern of Castanopsis fargesii and examined the effects on conspecific seedling regeneration. We found that 61.45% of adult individuals were in decline and the smaller DBH size classes of trees (10–40 cm) had a greater probability of decline. Most of the intermediate decline (94.52%) and nondecline individuals (95.23%) did not worsen, and the crowns of 21.91% of the intermediate decline trees were recovered during 2013–2018. Adult tree decline had a negative effect on seed production (mean mature seed density of nondecline, intermediate decline, and high decline individuals was 167.3, 63.3, and 2.1 seeds/m2, respectively), but no effect on key seed traits. The seed survival rate of declining trees was greater than that of nondeclining trees at both the seed production and seed dispersal stages. The seed to seedling transition rates in canopy gaps, decline habitats, and nondecline habitats were 7.94%, 9.47%, and 109.24%, respectively. The survival rate and height growth of newly germinated seedlings were positively correlated with the light condition, which was notably accelerated in the canopy gaps. Taken together, these results indicate that the reduction in seed production of some adult trees had a weakly negative effect on new seedling recruitment, while the improved environmental condition after the decline significantly enhanced the survival and growth of both advanced and new germinated seedlings. Looking at the overall life history, the short‐term defoliation and mortality of some C. fargesii adult trees can be regarded as a natural forest disturbance that favors conspecific seedling regeneration. High‐intensity management measures would be unnecessary in cases of an emerging intermediate decline in this forest. [ABSTRACT FROM AUTHOR]

Incentive-based natural resource management can increase the ecological and economic efficiency of resource utilization. An incentive-based fee scheme was proposed as an effective management scheme for grasslands in northwestern China, where grazing has been banned for ten years. The scheme combines grazing fees and payment by results (GFPBR). The aims of this case study were to assess farmers' acceptance and perception of a potential GFPBR scheme, using Yanchi County as an example, and to evaluate the driving factors. Face-to-face surveys were conducted with 128 farmers. A semi-standardized questionnaire, which included farmers' willingness to accept the GFPBR scheme, their perception and preferred characteristics, individual characteristics, family characteristics and behavioral characteristics, was developed. The results showed that the majority of farmers in this case study accepted the GFPBR scheme. The willingness of farmers to pay a fee for grazing was significantly influenced by the proportion of stockbreeding income to total income, whether grassland was independently contracted, whether non-agricultural investments were made in the past five years, and farmers' perception of ecological protection and economic development. Climate change and government executive capacity were the main risk factors considered by farmers who were unwilling to enroll in the GFPBR scheme. The farmer's perception of grassland management indicated they were more inclined to value short-term economic interest over ecological protection. We suggest that the implementation of the GFPBR scheme must take into account the grazing fee amount, the design of the scheme, the length of implementation, and property ownership. [ABSTRACT FROM AUTHOR]

Due to the increased pressure of modern life, mental anxiety and depression are becoming more prevalent. Stress and negative emotions can lead to elevation in blood pressure. This review aims to clarify the correlation and mechanism between two common states seen in hypertension: Liver qi stagnation in Chinese medicine along with anxiety and depression in psychosomatic medicine. The Chinese research database CNKI was searched using key words in Chinese and relevant articles were selected. Theoretical, experimental, and clinical research studies were reviewed to explore the mechanism of "course Liver and rectify qi" and to further analyze common factors and points of regulation in psychosomatic medicine's mechanism. Experimental research indexes included in Chinese medicine's clinical syndrome differentiation system were analyzed, providing the basis for this research. Integrating Chinese medicine's differential diagnoses with biomedicine's pathological mechanisms, correlations were identified in order to properly incorporate the concepts and methods for the clinical diagnosis and treatment of hypertension. Limitations include non-comprehensive database searching as well as potential bias in article selection. Based on this review of current literature, the role of "Liver governs dredging" theory in the pathogenesis and prevention of hypertension and its consistency with the correlated factors and mechanisms of psychosomatic medicine can be considered as a new hypothesis. [ABSTRACT FROM AUTHOR]

Compared with other regions in China, air pollution on the North China Plain (NCP) is serious. Fine particle pollution has been studied in-depth, but there is less research on long-term troposphere ozone (O3) variation. This study focuses on the summer interannual tropospheric O3 variation on the NCP and its influential factors. Our analysis relies on satellite observations (O3, nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), and formaldehyde (HCHO), determined as vertical column density of the troposphere) and dynamical processes (El Niño-Southern Oscillation (ENSO), potential vorticity (PV), the quasibiennial oscillation (QBO), and East Asian summer monsoon index (EASMI)). Our results show the vertical column density of tropospheric O3 has a transition from the increasing trend to decreasing trend during the summer of 2005–2016. The summer series of tropospheric O3 show two distinct phases: the first phase (2005–2011), with an average growth rate of 0.55 ± 0.20 DU/yr, and a second phase (2012–2016), with an average reduction rate of 0.16 ± 0.23 DU/yr. The tropospheric NO2 column in the NCP also has a transition from the increasing trend to decreasing trend during the summer of 2005–2016. Tropospheric NO2 and CO column concentrations obtained from satellite observations indicate that emission reductions might be the main cause of the tropospheric O3 decrease. Particularly, the reduction of nitrogen oxides (NOx) is more significant, and NO2 decreased by (0.45 ± 0.11) × 1015 molec·cm−2 per year in summer since 2012. However, tropospheric column HCHO shows an increase of 0.05 × 1015 molec·cm−2 per year during the whole period of 2005 to 2016. An O3-NOx-VOC sensitivity experiment in the NCP showed that the O3 is still in a NOx-saturated state in some heavily polluted cities, although the NOx emissions are decreasing overall. In addition to the chemical reactions, atmospheric dynamic processes also have an effect on tropospheric O3. Finally, we built a model to analyze the contributions of chemical processes and dynamic processes to the tropospheric O3 column in the NCP. For the chemical process variables, 69.73% of the observed trend of tropospheric O3 could be explained by the NO2 tropospheric column. Therefore, the reduction of tropospheric O3 since 2012 is associated with the reduction of NOx. For the dynamical process variables, ENSO, PV, and EASMI can explain 60.64% of the observed trend of tropospheric O3. This result indicates that the atmospheric circulation of the western Pacific Ocean in summer has a significant impact on the interannual trends of tropospheric O3 in the NCP. It is also found that chemical processes had a more important impact on interannual tropospheric O3 than dynamic processes, although the dynamic processes cannot be neglected. [ABSTRACT FROM AUTHOR]

A solar-driven self-heated sponge was developed as a novel sorbent to achieve fast collection of crude oil from spills by taking advantage of light-to-heat conversion to significantly reduce oil viscosity. The sorbent was fabricated via facile dip-coating reduced graphene oxide on a commercial melamine sponge. The photothermal effect of sorbent on absorption of crude oil was investigated through infrared thermal imaging, permeating behavior of crude oil droplet and absorption-recovery of crude oil. The results indicated that the graphene sponge revealed an outstanding light-to-heat conversion capability and stability with almost full absorption (∼98%) of sunlight. The surface temperature spontaneously increased to as high as 89 °C under one sun simulated irradiation (1.0 kW/m2) at room temperature (30 °C), which subsequently reduced the in situ viscosity of the crude oil by over two orders of magnitude. As a result, the absorption time was reduced by approximately 86% for a solar-heating sponge under one sun illumination compared with that of the sponge without light illumination. In addition, the consecutive recovery rate for pumping-driven crude oil clean-up from seawater under one sun illumination was 12 times faster than that of the sponge without light illumination. The proposed solar responsive sorbent design represents a sustainable approach to address the problem of remediation of viscous crude oil spills. Image 1 ● A solar-heated hydrophobic sorbent was fabricated for crude oil absorption. ● The sorbent revealed an outstanding light-to-heat conversion capability. ● The sorbent could efficiently recover crude oil by reduced viscosity under sunlight. ● Pumping-driven consecutive recovery was 12 times faster than that without sunlight. ● Solar-heated sorbent could be potentially used for crude oil spills remediation. [ABSTRACT FROM AUTHOR]

The "low-hanging fruits" measures that easily and quickly reduced pollution and energy intensity over the past decades are now giving rise to issues. Cleaner production may provide new opportunities to gain the "high-hanging fruits"—more challenging or costly actions that have greater environmental and energy benefits but require advanced technologies or management for implementation. This study provides empirical evidence on the effects of cleaner production audits (CPAs) on Chinese manufacturing firms' total factor energy efficiency (TFEE), whose enhancement synergizes climate mitigation and green productivity growth. The study analyzes the effects of CPAs by employing a staggered difference-in-difference strategy combined with propensity score matching to compare samples of treated and untreated industrial firms for the period of 2000–2014. The findings show that regulated firms experience a 10.4% increase in TFEE. The contributions of green pure technical efficiency and green technical progress are 7.9% and 2.7%, respectively. Additionally, non-heavy polluters, small firms, and private firms demonstrate the greatest improvements in TFEE. However, CPAs do not significantly impact the TFEE of firms with high dependence on fossil energy. Finally, the mechanism analyses demonstrate that inner resource allocation optimization may be the main solution for improving TFEE by enhancing green pure technical efficiency. Green technological innovations in energy alternatives are the most promising paths for increasing TFEE by promoting green technical progress. These findings illuminate how manufacturing firms pick the "high-hanging fruits" of energy efficiency in more cost-effective ways and suggest useful insights for cleaner production promotion. • Explores how cleaner production audits (CPAs) impact firm total factor energy efficiency (TFEE). • Resource allocation optimization may be the main path for improving TFEE. • Alternative energy production innovations are cost-effective paths for increasing TFEE. • Different firms' TFEE vary distinctively based on CPAs. • CPAs do not significantly impact TFEE of firms with high dependence on fossil energy. [ABSTRACT FROM AUTHOR]

Technological innovation is an important solution that can help improve environmental efficiency. However, the role of technological renovation in enhancing environmental efficiency has been ignored. This study provided initial evidence of the effects of cleaner production audits in China on manufacturing firms' environmental efficiency, which was measured by the emissions of sulfur dioxide and chemical oxygen demand per total output. Cleaner production audits were used as exogenous shocks. Their impact was estimated using the staggered difference-in-difference method combined with samples of ever-treated or never-treated firms using propensity score matching. The findings showed that firms that conducted cleaner production audits (vs. those that did not) experienced 4.7% and 11.9% reductions in the emission intensities of sulfur dioxide and chemical oxygen demand, respectively. Cleaner production audit implementation significantly improved firms' environmental efficiency. Additionally, a heterogeneous analysis showed that non-heavy polluters, small and medium-sized firms, and non-state-owned firms demonstrated the most improvement in environmental efficiency. Finally, the mechanism analysis results showed that firms' technological renovation in the production process is the main solution for improving environmental efficiency. This is a feasible and cost-effective way of reducing resource consumption and pollutant emissions. Accordingly, a cleaner production audit plan for different countries should be formulated with a focus on technological renovation in the production process. It should entail clean-cut incentives to stimulate firms to perform technological innovation, thereby continuously improving firms' environmental efficiency. This study sheds light on the environmental impact of cleaner production audits and regulated firms' choices between technological renovation and innovation. [Display omitted] • Effects of cleaner production audits on firms in China are investigated. • Cleaner production audits significantly improve firms' environmental efficiency. • Technological renovation in production processes improves environmental efficiency. • It is a cost-effective way to reduce resource consumption and pollutant emissions. [ABSTRACT FROM AUTHOR]

Highlights • A geosensor data forecasting tensor framework (GDFTF) for significant societal events is proposed. • A rank increasing strategy and a sliding window strategy is used to improve the prediction accuracy. • Extensive experimental evaluations illustrate the superiority of our approach compared with the state-of-the-arts. Abstract Geosensor data forecasting has high practical value in government affairs such as prompt response and decision making. However, the spatial correlation across distinct sites and the temporal correlation within each site pose challenges to accurate forecasting. In this paper, a geosensor data forecasting tensor framework for significant societal events is proposed. Specifically, a tensor pattern is used to model the geosensor data, based on which a tensor decomposition algorithm is then developed to estimate future values of geosensor data. The proposed approach not only combines and utilizes the multi-mode correlations, but also well extracts the underlying factors in each mode of tensor and mines the multi-dimensional structures of geosensor data. In addition, a rank increasing strategy is used to determine tensor rank automatically, and a sliding window strategy is used to improve the prediction accuracy. Extensive experimental evaluations illustrate the superiority of our approach compared with the state-of-the-arts. [ABSTRACT FROM AUTHOR]

Highlights • The implementation of the prohibited grazing policy has achieved remarkable ecological benefits. • Farmers of different types had different adaptation perceptions. • Farmers of different adaptation perceptions choices of adaptation strategies also varied. • The main factors that influenced farmers' adaptation strategies also included livelihood capital and farmers' perception of the policy. Abstract Due to long-term human activities, grassland ecosystems have been severely damaged. To protect grassland ecosystems, the prohibited grazing policy (PGP), a grassland ecological protection policy, was instituted for Chinese grasslands in 2002. However, it is unknown whether farmers have effectively adapted to the PGP. The adaptability of farmers to this policy has directly influenced the effective implementation of the policy and the sustainable development of the ecosystem. Previous research on adaptability has not focused on the adaptation to political change. This article uses a case study in Northwest China to investigate the adaptability of farmers to the policy. First, we study the restoration status of ecosystems. In addition, this paper studies the perceptions regarding farmers' adaptability to the policy and explores the adaptation strategies of different types of farmers. Finally, this paper discusses the main factors that influence farmers' choice of adaptation strategies. The implementation of the PGP has achieved remarkable ecological benefits. Farmers of different types had different adaptation perceptions, and their choices of adaptation strategies also varied. In addition to the farmers' perception of the policy, the main factors that influenced farmers' adaptation strategies also included livelihood capital. [ABSTRACT FROM AUTHOR]

Abstract Artificial electroactive biofilms have been developed as potential alternative to natural biofilms because the fabrication of them is simple, rapid, standardized and controllable. However, the construction of artificial electroactive biofilms usually involves cell dry process or the use of binding agents, which inevitably decreases the viability of the entrapped cells. Herein, a fast and convenient bacterial immobilization method is proposed as an attempt to construct an artificial electroactive biofilm for microbial energy harvesting, in which bacteria are captured by magnetically active nitrogen-doped Fe 3 O 4 /reduced graphene oxide composite and bring onto the electrode by means of external magnetic field. The resulting artificial electroactive biofilm produces higher current than the natural electroactive biofilm in the bioelectrochemical systems. The improved performance of the biofilm captured by nitrogen-doped Fe 3 O 4 /reduced graphene oxide can be attributed to its high surface, high affinity for the attachment of Geobacter sulfurreducens , and efficient extracellular electron transfer between microbial biofilm and electrode. Moreover, because of the magnetic activity of the resulting electroactive biofilm, the current produced from the artificial electroactive biofilm is magnetically switchable. This study offers a new approach to rapidly fabricate an artificial electroactive biofilm and provides an opportunity for the fabrication of a magnetically controllable microbial bioelectrochemical system. Graphical abstract Image 1 Highlights • G. sulfurreducens was captured by magnetically active N-doped Fe 3 O 4 /rGO. • The biocomposite was brought onto the electrode by means of external magnetic field. • Maximum current density was 0.24 ± 0.07 mA/cm2 for N-M/rGO-captured biofilm. • The magnetically active biofilm was efficient for microbial energy harvesting. [ABSTRACT FROM AUTHOR]

The development of efficient bifunctional catalysts for both oxygen reduction and oxygen evolution reactions is highly desirable but challenging in energy conversion and storage systems. Here, a simple yet cost-effective strategy is developed to produce heteroatom-doped carbon nanospheres using natural cuttlefish ink as the precursor. For the oxygen reduction reaction, the catalyst exhibits more positive onset-potential and larger diffusion limiting current density compared with benchmark platinum catalyst in alkaline medium. Moreover, the as synthesized catalyst shows low onset-potential for oxygen evolution reaction, indicating its outstanding catalytic activity. The catalyst shows a potential gap of 0.75 V between the oxygen evolution reaction potential at a current density of 10 mA cm −2 and the oxygen reduction reaction potential at the half-wave potential, outperforming most of other noble metal-free carbon catalysts in the current state of research. The remarkable catalytic performance can be assigned to heteroatoms doping, full exposure of the active sites, large surface area and enrichment of pores for sufficient contact and rapid transportation of the reactants. This study offers a new approach for the synthesis of metal-free carbon nanomaterials from natural resources, and broadens the design for the fabrication of bifunctional oxygen reduction and oxygen evolution catalysts. [ABSTRACT FROM AUTHOR]

Abstract: Influence diagrams (IDs) are one of the most commonly used graphical and mathematical decision models for reasoning under uncertainty. In conventional IDs, both probabilities representing beliefs and utilities representing preferences of decision makers are precise point‐valued parameters. However, it is usually difficult or even impossible to directly provide such parameters. In this paper, we extend conventional IDs to allow IDs with interval‐valued parameters (IIDs) and develop a counterpart method of Copper's evaluation method to evaluate IIDs. IIDs avoid the difficulties attached to the specification of precise parameters and provide the capability to model decision‐making processes in a situation that the precise parameters cannot be specified. The counterpart method to Copper's evaluation method reduces the evaluation of IIDs into inference problems of Bayesian networks with interval‐valued probabilities. An algorithm based on the approximate inference of Bayesian networks with interval‐valued probabilities is proposed, and extensive experiments are conducted. The experimental results indicate that the proposed algorithm can find the optimal strategies effectively in IIDs, and the interval‐valued expected utilities obtained by proposed algorithm are contained in those obtained by exact evaluating algorithms. The newly development approach would significantly extend the range of IDs for managerial decision support applications where parameters of variables can be specifically defined by only estimated intervals. [ABSTRACT FROM AUTHOR]

Aims/Introduction: Serum amyloid A (SAA) is an acute phase reactive protein that plays a vital role in the early diagnosis, risk prediction, efficacy observation and prognosis evaluation of infectious diseases. This study aimed to assess the association between SAA levels and the prognosis of patients with coronavirus disease 2019 (COVID‐19) and diabetes. Materials and Methods: We carried out this retrospective cohort study from March 2022 to May 2022. The population was stratified by tertiles of SAA levels: low (<8.5 mg/L), medium (8.5–36 mg/L) and high (>36 mg/L). The primary outcome was whether the patient developed severe COVID‐19, and secondary outcomes included the need for invasive mechanical ventilation and length of hospital stay. Logistic regression analyses were carried out to identify risk factors affecting the prognosis of patients with COVID‐19 and diabetes. Results: We analyzed 910 diabetes patients with COVID‐19. The median age of the patients was 69 years, and 52.3% were men. As SAA levels increased, the proportion of severe COVID‐19 (6.3% vs 7.3% vs 22.8%, P < 0.001) and the proportion of invasive mechanical ventilation also increased among the three groups. Patients with high SAA levels had a longer length of hospital stay compared with patients with medium SAA and low SAA levels. Univariate logistic regression analysis showed that SAA >36 mg/L further increased the odds ratio to 4.423 (P < 0.001) for the development of severe COVID‐19 compared with low SAA. Multivariate logistic regression analysis, adjusted for age and sex, confirmed that SAA >36 mg/L remained an independent risk factor for the development of severe COVID‐19 (adjusted odds ratio 3.038, P < 0.001). Conclusions: SAA levels are strongly associated with poor prognosis in patients with COVID‐19 and diabetes. [ABSTRACT FROM AUTHOR]

This study explored the association of the affective experience (AE) of life events on hopelessness depression (HD). Undergraduates (N = 301) participating in a 12-week prospective study completed measures of HD, cognitive style, and psychological stress. The results indicate AE is an underlying mechanism influencing the longitudinal link between life events and HD. Negative life events with clear negative AE directly promoted the development of HD. Positive life events with clear positive AE directly impeded the development of HD. Neutral life events with mixed AE directly and interacting with negative cognitive style promoted the development of HD. The results should increase understanding of the hopelessness theory of depression, and suggest that neutral life events should be important elements in depression therapy. [ABSTRACT FROM AUTHOR]

The ability of self-compassion and Confucian coping to predict anxiety and depression were examined in impoverished Chinese undergraduate students. Three hundred and thirty impoverished undergraduates completed measures of self-compassion, Confucian coping, depression, and anxiety. Results showed that higher selfcompassion predicted lower depression and anxiety in impoverished undergraduates. Higher pro-setback thinking and responsibility thinking of Confucian coping were related with lower depression and anxiety. Higher fate thinking of Confucian coping was related with higher depression and anxiety. The predictive ability for depression and anxiety of self-compassion combined with fate thinking was better than selfcompassion alone. Intervention to enhance self-compassion and reduce fate thinking may be beneficial to mental health in impoverished undergraduates. [ABSTRACT FROM AUTHOR]

[Display omitted] • Imidazolium Gemini IL effectively inhibits the swelling and dispersion of Na-MMT. • Anionic polymers can synergistically inhibit the dispersion of MMT. • Hydrogen binding, electrostatic and hydrophobic interaction participate in inhibition. • The treatment of imidazolium Gemini IL improves the permeability of sandstone. • Imidazolium Gemini IL is beneficial to expel the water intruding into the sandstone. The long-term effect of protecting water-sensitive reservoirs and enhancing permeability of water invasion reservoir is still an urgent practical problem to be solved. Here, an imidazolium Gemini ionic liquid (IL), PEG-DC 8 Im, with octyl as tail chain and polyoxyethylene chain as bridging group, was synthesized to inhibit the hydration, swelling and dispersion of clay minerals. The PEG-DC 8 Im could exert excellent anti-swelling ability (93.82 %) and outstanding washable capacity (cumulative decrease of anti-swelling rate after being washed five times: 1.32 %) at the concentration of 60 mmol/L. The inhibition effect of 20 mmol/L PEG-DC 8 Im was significantly better than that of 250 mmol/L KCl at 90 °C. And the PEG-DC 8 Im could intercalate into the interlayer space of MMT through cation exchange to play an inhibition effect, where zeta potential of MMT particles was reduced and then the dispersion ability of MMT was weakened. Subsequently, the anionic polymer poly(AM/AA) was found to cooperate with PEG-DC 8 Im to improve the inhibition effect for MMT swelling and dispersion, in which poly(AM/AA) was not intercalated into the interlayer of MMT, and only adsorbed on the surface of the particles to encapsulate the MMT particles. Simultaneously, the apparent viscosity and thixotropy of the composite solution were enhanced. Besides, after the treatment of PEG-DC 8 Im, the displacement pressure decreased and the permeability of sandstone cores increased due to the inhibition of clay mineral hydration, revealing the enhancement of injectivity. Finally, the pore connectivity of the core increased and the water wettability was weakened. The treatment of PEG-DC 8 Im was conducive to the discharge of invasive water in reservoir and the improvement of the reservoir permeability. Overall, PEG-DC 8 Im has a good application prospect as permeability-enhancing clay stabilizers. [ABSTRACT FROM AUTHOR]

Highly efficient bifunctional electrocatalysts for both oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) are essential for the development of renewable energy technologies such as fuel cells and metal-air batteries. Herein, a ceria (CeO 2 ) – modified reduced graphene oxide (CeO 2 /rGO) nanocomposite was fabricated via a facile yet cost-effective method under a mild condition. The prepared CeO 2 /rGO nanocomposite showed remarkable catalytic activity, high tolerance to methanol and durability toward ORR in alkaline media. Meanwhile, the catalyst also displayed remarkable activity for the OER with more negative onset potential and higher current compared with commercial Pt/C catalyst. The high oxygen reaction activity of the catalyst could contribute to synergistic effect of the combination of the oxygen vacancies of CeO 2 and excellent electronic conductivity of rGO. The results suggested that the CeO 2 /rGO nanocomposite has potential advantages as a bifunctional electrocatalyst in the practical applications. [ABSTRACT FROM AUTHOR]

A multi-stimuli-responsive poly(NIPA-co-HEMA-co-NVP) with spironaphthoxazine hydrogel (poly(NIPA-co-HEMA-co-NVP-co-SPO)) was prepared by radical polymerization. The structure of this hydrogel was characterized by FTIR, C NMR spectra, and SEM. Equilibrium swelling measurement and UV-vis spectra were applied into evaluating thermo-responsive, pH-responsive and light-responsive properties. These results exhibited poly(NIPA-co-HEMA-co-NVP-co-SPO) hydrogel with excellent stimuli-responsive characteristics including thermal, pH, and light stimulation. Meanwhile, the obvious change for internal microstructure of hydrogel was observed by SEM after UV irradiation and in acidic condition. In addition, the poly(NIPA-co-HEMA-co-NVP-co-SPO) hydrogel with good mechanical property can be utilized in erasable and rewritable photoimaging based on the photochromic effect, which makes it a potential application in rewritable optical memory media or imaging processes. [ABSTRACT FROM AUTHOR]

Cerium (Ce) is an easily oxidized metal and the surface oxide layer will break into powders in a few days in air, which is extremely similar to actinide metals like thorium, uranium. To protect the surface of Ce, different ultra-thin films including Al 2 O 3 , TiO 2 , TiN and ZrO 2 were deposited on the surface of Ce samples using atomic layer deposition (ALD). All these films decreased the Ce surface oxidation for one month. The Al 2 O 3 film grown by ALD provided best antioxidation effect for 70 days of air exposure. This work shows the potential of ALD in the application of surface antioxidation for actinide metals in the aspect of short time (one month) storage. • The Ce metal surfaces are protected with ultra-thin films of Al 2 O 3 , TiO 2 , TiN and ZrO 2 by atomic layer deposition (ALD). • The Al 2 O 3 film provided best antioxidation protection after 70 days of air exposure. • ALD can be used for antioxidation of actinide metals surface in the aspect of short time (one month) storage. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the outage performance of an energy harvesting underlay cognitive multi-hop relay network. In the network, energy-constrained secondary network (SN) nodes harvest energy from radio frequency signal of a power beacon (PB) node. The source node transmits information to destination node via multiple intermediate relay nodes by using a time division broadcast protocol, and the hardware impairments of SN nodes' transceiver are modeled. The outage performance of SN is analyzed and evaluated by accurately approximate and asymptotic closed-form expressions of outage probability (OP) over quasi-static mixed Rayleigh and double-Rayleigh fading channels. Additionally, due to the complexity of OP expression, a chaotic dragonfly algorithm (CDA) is proposed to jointly optimize energy harvesting ratio and PB node's abscissa, which can achieve OP minimization of SN. Extensive simulations demonstrate the correctness of theoretical analysis and the effectiveness of the proposed CDA. [ABSTRACT FROM AUTHOR]

Carbon nanofibers (CNFs) have drawn considerable attention as alternative catalysts for the oxygen reduction reaction (ORR). However, their facile, cheap, and environmentally friendly synthesis is still a great challenge. Herein, heteroatom-doped porous CNFs have been fabricated via a simple pyrolysis method using natural spider silk (SS) as a precursor. The prepared CNFs exhibit excellent ORR activity (half-wave potential of 0.85 V and on-set potential of 0.98 V vs RHE), superior to that of the Pt/C catalyst and most reported metal-free carbon catalysts in alkaline conditions. The catalytic proficiency is attributed to abundant electronegative N and S atoms within the carbon lattice, and a high surface area due to their nanofibrillar and porous structure. The prepared CNFs also exhibit excellent ORR activity in neutral solution (pH 7.0), showing potential application as cathode catalysts in microbial fuel cells (MFCs). An MFC equipped with the resulted CNF cathode presents a maximum power density of 1800 mW/m 2 , 1.56 times higher than that with a Pt/C cathode. The performance of the resulting CNFs exceed that of other metal-free carbon catalysts in the current state of research on microbial energy harvesting. [ABSTRACT FROM AUTHOR]

Detecting communities is of great importance in social network analysis. However it is an issue that has not yet been satisfactorily solved, despite the efforts made by interdisciplinary research communities over the past few years, because of the nature of complexity in deciding how community structures should be recognized. In this paper we propose an approach based on cooperative game theory for community detection in social networks. We regard individuals as players, and regard communities as coalitions formed by players, and model community detection problem as the formation and optimization of coalitions. Furthermore, we define coalition profile for players to indicate coalitions that players joined, the order of a coalition profile is defined as the number of coalitions in a coalition profile, and we introduce a utility function to measure preference of coalition profiles. Accordingly, we propose an algorithm to detect a coalition profile with maximal utility function values. We have implemented the algorithms developed in this study and experimental results demonstrate the effectiveness of our approaches. [ABSTRACT FROM AUTHOR]

The development of inexpensive metal-free catalysts with high activity and stability as substitutes for carbon-supported platinum catalysts (Pt/C) in the oxygen reduction reaction (ORR) remains a great challenge. In this paper, we report a novel type of self-constructed, carbon nanoparticle (CNP)-coated porous biocarbon prepared from a natural, readily available, and renewable plant moss ( Weisiopsis anomala ) with a single precursor using template-free heat treatment. The CNPs were self-sponsored from the moss, which were simultaneously self-packed on the moss-derived carbon matrix via strong interactions between the hydroxyl and carbonyl functional groups of the CNPs and the moss-derived carbon matrix during the hydrothermal treatment. After being further carbonized at 900 °C, the moss-derived, CNP-coated biocarbon material had a larger surface area than that of the CNP-free, moss-derived biocarbon material. Electrochemical characterization showed that the CNP-coated biocarbon had a high activity in the ORR with an onset potential of 0.935 V vs. the reversible hydrogen electrode (RHE); this value is close to that of a commercial Pt/C catalyst (0.962 V vs. RHE) and is more positive than that of a CNP-free biocarbon material. The CNP-coated biocarbons also displayed a high limited current density, excellent long-term stability and resistance to methanol crossover, offering performance characteristics superior to those of Pt/C. Moreover, a microbial fuel cell (MFC) equipped with a CNP-coated biocarbon cathode outperformed an MFC with a Pt/C cathode in terms of energy output. This study presents a new approach for the production of inexpensive nanostructured carbon materials that exhibit high performance in the ORR from a natural resource. [ABSTRACT FROM AUTHOR]