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Objectives: The objective of this study was to examine the impact of athletes achieving excellence at different ages (excellent age) on their subsequent performance development. The aim was to deepen understanding of the interplay among talent, training, and athletes' performance development. Additionally, the study aimed to provide insights for athletics coaches to better identify talent and devise more effective personalized long-term training plans. Design: This was a cross-sectional study. Method: A hierarchical linear model was employed to analyze the correlation between excellent age and subsequent performance development in a cohort of 775 elite track and field athletes. This analysis was expanded upon by the application of a general linear regression model, which was used to explore the relationship between excellent age and peak age, peak performance, as well as the growth in performance during adulthood. Results: As athletes reached excellence at later ages, their peak performance exhibited a U-shaped pattern(p <0.001), initially decreasing and then rising. Simultaneously, their peak age became increasingly advanced(p <0.001), with a progressively larger performance improvement during adulthood(p <0.001). In various disciplines, excellent age is negatively correlated with peak performance for speed athletes(p = 0.025), exhibiting a U-shaped pattern for endurance athletes(p = 0.024), and showing no significant correlation for fast-power athletes(p = 0.916). Conclusions: Athletes who achieve excellence either early or later often show more remarkable future developments. However, there are significant distinctions in the age at which these athletes reach their peak performance and the pace of improvement leading up to it. Those who excel early may possess greater innate athletic talent, whereas those who excel later may exhibit superior training adaptability. Consequently, an athlete's early performance can predict his/her future performance trajectory, offering support for individualized long-term training plans. In summary, the age at which athletes achieve excellence may bring different advantages to their future athletic performance and development. This implies that we should harness these differences to uncover each athlete's maximum potential. [ABSTRACT FROM AUTHOR]

Propose: To review published Physical Activity (PA) on the Mental Health of Children and Adolescents aged 5 to 18 years during COVID-19 pandemic-induced school closures. Methods: From the database creation to April 2022, 10 databases are retrieved, with 4427 records filtered, 14 included in this research. The research takes Agency for Healthcare Research and Quality (AHRQ) evaluation standards. Results: The thesis selects 14 studies from 6 countries, involving 400009 children and adolescents. These studies happened during the lockdown of COVID-19 (from December 2019 to April 2021). During the lockdown of COVID-19, schools were closed, which was considered part of a more extensive lockdown. Schools were closed for 1 to 4 weeks. There were 10 high quality studies (71.4%) and 4 medium quality studies (28.6%). 4 studies report that the pandemic reduces the time of PA but increases the time of watching screen and sitting. 10 studies (71.4%) identify that PA is positive for the mental health, because it helps reduce mental symptoms to a certain extent, especially anxiety, depression, and emotional disorders. 5 studies show that PA may not improve the mental health of children and adolescents under 12 during the pandemic. 4 studies indicate that the influence of PA on mental health of children and adolescents is determined by the amount of activity, including the extent, intensity, frequency, and duration, etc. Conclusions: In this narrative synthesis of reports from the class suspension period, reports that PA has a improve on the mental health of children and adolescents to a certain extent. it is found that PA may be helpful in reducing mental health symptoms of children and adolescents who are influenced by class suspension because of the COVID-19 pandemic. Therefore, stakeholders of the mental health of children and adolescents around the world should recommend PA because it is a practicable and beneficial way for long-term mental support. [ABSTRACT FROM AUTHOR]

Glioblastoma, the most aggressive form of brain cancer, poses a significant global health challenge with a considerable mortality rate. With the predicted increase in glioblastoma incidence, there is an urgent need for more effective treatment strategies. In this study, we explore the potential of caerin 1.1 and 1.9, host defence peptides derived from an Australian tree frog, in inhibiting glioblastoma U87 and U118 cell growth. Our findings demonstrate the inhibitory impact of caerin 1.1 and 1.9 on cell growth through CCK8 assays. Additionally, these peptides effectively curtail the migration of glioblastoma cells in a cell scratch assay, exhibiting varying inhibitory effects among different cell lines. Notably, the peptides hinder the G0/S phase replication in both U87 and U118 cells, pointing to their impact on the cell cycle. Furthermore, caerin 1.1 and 1.9 show the ability to enter the cytoplasm of glioblastoma cells, influencing the morphology of mitochondria. Proteomics experiments reveal intriguing insights, with a decrease in CHI3L1 expression and an increase in PZP and JUNB expression after peptide treatment. These proteins play roles in cell energy metabolism and inflammatory response, suggesting a multifaceted impact on glioblastoma cells. In conclusion, our study underscores the substantial anticancer potential of caerin 1.1 and 1.9 against glioblastoma cells. These findings propose the peptides as promising candidates for further exploration in the realm of glioblastoma management, offering new avenues for developing effective treatment strategies. [ABSTRACT FROM AUTHOR]

3D stratum roaming can visualize the complex geomorphology, underground structure and stratum distribution of geotechnical engineering. Conventional 3D stratum roaming technology is generally aimed at roaming outside the 3D stratum model but rarely roams inside the 3D stratum model, and the efficiency of switching between external and internal roaming is low. In practical engineering, especially in geological and geotechnical engineering, the underground structure and stratum situation are critical. Therefore, focusing on this problem, this paper adopts a three-dimensional roaming engine to connect the inside and outside of a three-dimensional model. Based on an internal and external boundary identification method, the combination of external roaming and internal roaming of the three-dimensional stratum model is implemented by using a stratum virtual surface, and lightweight loading is carried out by controlling the stratum virtual surface to establish the internal and external roaming of the 3D stratum model, and to give full play to the advantages of lightweight loading to provide more intuitive and comprehensive geological information for the project. [ABSTRACT FROM AUTHOR]

Non-small cell lung cancer (NSCLC) is one of the most common malignancies worldwide, and oxidative stress plays a crucial role in its development. Juglone, a naturally occurring naphthoquinone in J. mandshurica, exhibits significant cytotoxic activity against various cancer cell lines. However, whether the anticancer activity of juglone is associated with oxidative stress remains unexplored. In this study, mouse Lewis lung cancer (LLC) and human non-small cell lung cancer A549 cells were used to explore the anticancer mechanisms of juglone. Juglone inhibited LLC and A549 cells viability, with IC50 values of 10.78 μM and 9.47 μM, respectively, for 24 h, and substantially suppressed the migration and invasion of these two lung cancer cells. Additionally, juglone arrested the cell cycle, induced apoptosis, increased the cleavage of caspase 3 and the protein expression of Bax and Cyt c, and decreased the protein expression of Bcl-2 and caspase-3. Furthermore, juglone treatment considerably increased intracellular reactive oxygen species (ROS) and malondialdehyde (MDA) levels, but suppressed glutathione peroxidase 4 (GPX4) and superoxide dismutase (SOD) activities. It also inhibited the phosphatidylinositol 3-kinase (PI3K)/Akt signaling pathway, which was attenuated by 1,3-diCQA (an activator of PI3K/Akt). Moreover, N-acetylcysteine (a ROS scavenger) partially reversed the positive effects of juglone in terms of migration, invasion, ROS production, apoptosis, and PI3K/Akt pathway-associated protein expression. Finally, in tumor-bearing nude mouse models, juglone inhibited tumor growth without any apparent toxicity and significantly induced apoptosis in NSCLC cells. Collectively, our findings suggest that juglone triggers apoptosis via the ROS-mediated PI3K/Akt pathway. Therefore, juglone may serve as a potential therapeutic agent for the treatment of NSCLC. [ABSTRACT FROM AUTHOR]

The digital economy (DE) has become a major breakthrough in promoting industrial upgrading and an important engine for high-quality economic growth. However, most studies have neglected the important driving effect of regional economic and social (RES) development on DE. In this paper, we discuss the mechanism of RES development promoting the development of DE, and establish a demand-driven regional DE development model to express the general idea. With the help of spatial analysis toolbox in ArcGIS software, the spatial development characteristics of DE in the Yangtze River Delta City Cluster (YRDCC) is explored. We find the imbalance of spatial development is very significant in YRDCC, no matter at the provincial level or city level. Quantitative analysis reveals that less than 1% likelihood that the imbalanced or clustered pattern of DE development in YRDCC could be the result of random chance. Geographically weighted regression (GWR) analysis with publicly available dataset of YRDCC indicates RES development significantly promotes the development of DE. [ABSTRACT FROM AUTHOR]

As a new business model, E-commerce brings new changes to the global economy and society. So, can E-commerce development policies promote high-quality agricultural development? This article regards the pilot construction of national e-commerce demonstration cities as a quasi-natural experiment for the development of e-commerce. Based on the E-commerce pilot and economic and social development data of national prefecture-level cities from 2004 to 2018, the agricultural total factor productivity calculated by the Fare-Primont index method is used as the characterization of the quality of urban agricultural development, and an empirical model is constructed under the progressive Differences-in-Differences framework. This paper empirically tests the overall impact of E-commerce development on the high-quality development of agriculture and its sources, analyzes the heterogeneity and dynamics of the impact, and investigates the possible impact mechanism. The result shows that from the overall impact and its sources, the development of E-commerce in cities has a positive impact on the high-quality development of agriculture, and the impact is mainly due to its role in promoting technological innovation and economies of scale. From the perspective of heterogeneity, the larger the population size of a city, the more significant the level of e-conomic development or Internet development. From the perspective of the dynamic impact, the positive impact of e-commerce development becomes more significant over time. With the passage of time, the impact of E-commerce on high-quality agricultural development policies shows a trend of first increasing and then decreasing. Overall, this study provides empirical evidence for the rationality and effectiveness of policies and measures related to E-commerce to promote the high-quality development of agriculture. [ABSTRACT FROM AUTHOR]

Background: Dermatomyositis (DM) is prone to nasopharyngeal carcinoma (NPC), but the mechanism is unclear. This study aimed to explore the potential pathogenesis of DM and NPC. Methods: The datasets GSE46239, GSE142807, GSE12452, and GSE53819 were downloaded from the GEO dataset. The disease co-expression module was obtained by R-package WGCNA. We built PPI networks for the key modules. ClueGO was used to analyze functional enrichment for the key modules. DEG analysis was performed with the R-package "limma". R-package "pROC" was applied to assess the diagnostic performance of hub genes. MiRNA-mRNA networks were constructed using MiRTarBase and miRWalk databases. Results: The key modules that positively correlated with NPC and DM were found. Its intersecting genes were enriched in the negative regulation of viral gene replication pathway. Similarly, overlapping down-regulated DEGs in DM and NPC were also enriched in negatively regulated viral gene replication. Finally, we identified 10 hub genes that primarily regulate viral biological processes and type I interferon responses. Four key genes (GBP1, IFIH1, IFIT3, BST2) showed strong diagnostic performance, with AUC>0.8. In both DM and NPC, the expression of key genes was correlated with macrophage infiltration level. Based on hub genes' miRNA-mRNA network, hsa-miR-146a plays a vital role in DM-associated NPC. Conclusions: Our research discovered pivot genes between DM and NPC. Viral gene replication and response to type I interferon may be the crucial bridge between DM and NPC. By regulating hub genes, MiR-146a will provide new strategies for diagnosis and treatment in DM complicated by NPC patients. For individuals with persistent viral replication in DM, screening for nasopharyngeal cancer is necessary. [ABSTRACT FROM AUTHOR]

The purpose of this study was to examine transient plasma membrane disruptions (TPMDs) and TPMD-induced Ca++ waves (TPMD Ca++ Wvs) in human and mouse corneal epithelium (HCEC and MCEC). A multi-photon microscope was used to create laser–induced TPMDs in single cultured cells and in intact ex vivo and in vivo MCECs and ex vivo human cornea rim HCECs. Eye rubbing-induced TPMDs were studied by gentle rubbing with a cotton tipped applicator over a closed eyelid in ex vivo and in vivo MCECs. Ca++ sources for TPMD-induced Ca++ waves were explored using Ca++ channel inhibitors and Ca++-free media. TPMDs and TPMD Ca++ Wvs were observed in all cornea epithelial models examined, often times showing oscillating Ca++ levels. The sarcoplasmic reticulum Ca++ ATPase inhibitors thapsigargin and CPA reduced TPMD Ca++ Wvs. TRP V1 antagonists reduced TPMD Ca++ Wvs in MCECs but not HCECs. Ca++-free medium, 18α-GA (gap junction inhibitor), apyrase (hydrolyzes ATP), and AMTB (TRPM8 inhibitor) did not affect TPMD Ca++ Wvs. These results provide a direct demonstration of corneal epithelial cell TPMDs and TPMDs in in vivo cells from a live animal. TPMDs were observed following gentle eye rubbing, a routine corneal epithelial cell mechanical stress, indicating TPMDs and TPMD Ca++ Wvs are common features in corneal epithelial cells that likely play a role in corneal homeostasis and possibly pathophysiological conditions. Intracellular Ca++ stores are the primary Ca++ source for corneal epithelial cell TPMD Ca++ Wvs, with TRPV1 Ca++ channels providing Ca++ in MCECs but not HCECs. Corneal epithelial cell TPMD Ca++ Wv propagation is not influenced by gap junctions or ATP. [ABSTRACT FROM AUTHOR]

As the world's largest electricity-consuming country, China faces the challenge of energy conservation and environmental pollution. Therefore, it is imperative that China takes decisive action to address these issues. Based on the panel data of 30 provinces (cities, districts) in China from 2011 to 2020, we use the entropy method to measure the air pollution index in different provinces, construct two fixed effects models, panel quantile model, and spatial Durbin model to empirically analyze the impact of electricity consumption on air pollution in China's provincial regions. The experimental results show that: (1) Electricity consumption has a significant positive impact on the provincial air pollution index in China and the higher the index is, the more serious the air pollution is. When the electricity consumption increases 1%, the air pollution index will increase of by 0.0649% as accompanied. (2) Through comparison of different times, we found that the degree of increase in air pollution index caused by electricity consumption would be reduced due to the improvement of environmental protection efforts. From the perspective of different geographical locations, the electricity consumption in the southeast side of the "Hu Line" has exacerbated the impact on air pollution index. (3) According to the panel quantile regression results, the marginal effect of electricity consumption on air pollution is positive. With the increase of quantiles, the impact of electricity consumption on air pollution is increasing. (4) Spatial effect analysis shows that electricity consumption has a significant positive spatial spillover effect on air pollution index. The increase in electricity consumption not only increases the air pollution index in the local region, but also leads to an increase in the air pollution index in surrounding areas. These findings contribute to the governance of air pollution and the promotion of sustainable economic, environmental and energy development. [ABSTRACT FROM AUTHOR]

The primary treatment method for eradicating Helicobacter pylori (H. pylori) infection involves the use of antibiotic-based therapies. Due to the growing antibiotic resistance of H. pylori, there has been a surge of interest in exploring alternative therapies. Cetylpyridinium chloride (CPC) is a water-soluble and nonvolatile quaternary ammonium compound with exceptional broad-spectrum antibacterial properties. To date, there is no documented or described specific antibacterial action of CPC against H. pylori. Therefore, this study aimed to explore the in vitro activity of CPC against H. pylori and its potential antibacterial mechanism. CPC exhibited significant in vitro activity against H. pylori, with MICs ranging from 0.16 to 0.62 μg/mL and MBCs ranging from 0.31 to 1.24 μg/mL. CPC could result in morphological and physiological modifications in H. pylori, leading to the suppression of virulence and adherence genes expression, including flaA, flaB, babB, alpA, alpB, ureE, and ureF, and inhibition of urease activity. CPC has demonstrated in vitro activity against H. pylori by inhibiting its growth, inducing damage to the bacterial structure, reducing virulence and adherence factors expression, and inhibiting urease activity. [ABSTRACT FROM AUTHOR]

Improving agricultural total factor productivity is crucial for comprehensive rural revitalization and building a strong agricultural nation. Digital inclusive finance amalgamates the benefits of digital technology and inclusive finance, mitigating financial exclusion in agricultural production. It fosters rural revitalization and the modernization of agriculture by bolstering farmers' innovation, entrepreneurship, and agricultural technology advancements. Consequently, it significantly enhances overall agricultural total factor productivity. This study uses panel data from 2011 to 2020 to empirically investigate the impact and mechanism of digital inclusive finance on agricultural total factor productivity in Zhejiang Province, China. The research results show that digital inclusive finance significantly enhances agricultural total factor productivity in Zhejiang Province, which holds true even after a series of robustness tests. Analysis of the mechanism reveals that the integrated development of rural industries plays a crucial mediating role in empowering agricultural total factor productivity through digital inclusive finance. Furthermore, heterogeneity analysis indicates that the positive effect of digital inclusive finance on agricultural total factor productivity is more pronounced in the northeastern region of Zhejiang Province and in areas ranked in the second tier of agricultural development. Therefore, we recommend comprehensively enhancing the development of digital inclusive finance in rural areas, fostering a financial ecosystem that integrates rural industries, promoting the coordinated development of digital inclusive finance in different regions, and comprehensively improving agricultural total factor productivity. [ABSTRACT FROM AUTHOR]

Water quality prediction is of great significance in pollution control, prevention, and management. Deep learning models have been applied to water quality prediction in many recent studies. However, most existing deep learning models for water quality prediction are used for single-site data, only considering the time dependency of water quality data and ignoring the spatial correlation among multi-sites. This research defines and analyzes the non-aligned spatial correlations that exist in multi-site water quality data. Then deploy spatial-temporal graph convolution to process water quality data, which takes into account both the temporal and spatial correlation of multi-site water quality data. A multi-site water pollution prediction method called W-WaveNet is proposed that integrates adaptive graph convolution and Convolutional Neural Network, Long Short-Term Memory (CNN-LSTM). It integrates temporal and spatial models by interleaved stacking. Theoretical analysis shows that the method can deal with non-aligned spatial correlations in different time spans, which is suitable for water quality data processing. The model validates water quality data generated on two real river sections that have multiple sites. The experimental results were compared with the results of Support Vector Regression, CNN-LSTM, and Spatial-Temporal Graph Convolutional Networks (STGCN). It shows that when W-WaveNet predicts water quality over two river sections, the average Mean Absolute Error is 0.264, which is 45.2% lower than the commonly used CNN-LSTM model and 23.8% lower than the STGCN. The comparison experiments also demonstrate that W-WaveNet has a more stable performance in predicting longer sequences. [ABSTRACT FROM AUTHOR]

Background: Few studies on molecular epidemiology have studied people with newly diagnosed HIV infection and ART Failure Patients at the same time in rural China. With more serious HIV epidemic than in other provinces in China, Sichuan is an area suitable for this study. Objective: To analyze the characteristics of HIV-1 molecular networks and factors related to network entry among newly diagnosed HIV infection and ART Failure Patients in three county-level cities (A, B, C) in Sichuan Province, to provide scientific basis for accurate prevention and control. Methods: Nested PCR amplification method was used to amplify HIV-1 pol gene region of 530 blood samples, Sequencer 4.9 was used to edit, clean and splice the gene sequence, Bioedit correction, Fastree 2.1.8 and Figtree 1.4.2 to construct evolutionary tree and determine genotype. HyPhy2.2.4 and Cytoscape 3.6.1 software were used to construct molecular network. Logistic regression analysis was applied. Results: 523(98.68%) pol sequences were obtained, and a total of 518 valid sequences with basic information came into the final analyses. A total of 6 genotypes were detected, namely CRF01_AE (320,61.78%), CRF07_BC (149,28.76%), B (30,5.79%), CRF08_BC (11, 2.12%), CRF55_01B (6, 1.16%) and C (2, 0.39%). 186 of 518(35.91%) sequences entered the network at a genetic distance of 0.8%, forming 42 propagation clusters. "High-risk transmitters"(connected with two and more) accounted for 21.62%. Logistic regression showed that≥50 years old (OR = 2.474) were more risky than 18–49 years old, CRF07_BC sub-type (OR = 0.174) were less risky than CRF01_AE sub-type, B sub-type (OR = 6.698) is higher risky than CRF01_AE sub-type, and District B (OR = 0.077) less risky than that of A city. Conclusion: The sources of HIV infection in rural Sichuan are diversified and complicated. The prevention and control of HIV infection in Sichuan Province should focus on strengthening the long-term dynamic detection of elderly population, B strain sub-type, and in City A. [ABSTRACT FROM AUTHOR]

Improving green innovation efficiency (GIE) is the key to achieve high-quality economic development in China, and the introduction of foreign direct investment (FDI) has become an important path choice to promote the GIE. Based on the data of 30 provinces in China, this paper explores the linear and nonlinear effects of FDI on GIE from both quantity and quality perspectives, and further analyzes the mediating role of environmental regulation level. The results show that: (1) From 2011 to 2020, the GIE of all provinces in China generally shows an upward trend. (2) The quantity and quality of FDI have a significant positive impact on the improvement of GIE in China's provinces, and this impact has regional heterogeneity. (3) The quantity and quality of FDI can promote the improvement of GIE in China through the level of environmental regulation (ER). (4) With the level of knowledge accumulation and GIE as the threshold variables, the quantity and quality of FDI have a single threshold effect on the GIE of China's provinces. The conclusions of this study provide some policy implications for local governments to make full use of FDI to perform green innovation activities. [ABSTRACT FROM AUTHOR]

Introduction: Many regions in the world are using the population health approach and require a means to measure the health of their population of interest. Population health frameworks provide a theoretical grounding for conceptualization of population health and therefore a logical basis for selection of indicators. The aim of this scoping review was to provide an overview and summary of the characteristics of existing population health frameworks that have been used to conceptualize the measurement of population health. Methods: We used the Population, Concept and Context (PCC) framework to define eligibility criteria of frameworks. We were interested in frameworks applicable for general populations, that contained components of measurement of health with or without its antecedents and applied at the population level or used a population health approach. Eligible reports of eligible frameworks should include at least domains and subdomains, purpose, or indicators. We searched 5 databases (Pubmed, EMBASE, Web of Science, NYAM Grey Literature Report, and OpenGrey), governmental and organizational sites on Google and websites of selected organizations using keywords from the PCC framework. Characteristics of the frameworks were summarized descriptively and narratively. Results: Fifty-seven frameworks were included. The majority originated from the US (46%), Europe (23%) and Canada (19%). Apart from 1 framework developed for rural populations and 2 for indigenous populations, the rest were for general urban populations. The numbers of domains, subdomains and indicators were highly variable. Health status and social determinants of health were the most common domains across all frameworks. Different frameworks had different priorities and therefore focus on different domains. Conclusion: Key domains common across frameworks other than health status were social determinants of health, health behaviours and healthcare system performance. The results in this review serve as a useful resource for governments and healthcare organizations for informing their population health measurement efforts. [ABSTRACT FROM AUTHOR]

This paper methodically investigates the influence of inclusive income growth on city size, examining it through the dual lenses of "income" and "distribution." The analysis leverages meticulously collected panel data encompassing 276 Chinese cities at the prefecture level and above, spanning the period from 2005 to 2019. Theoretical analysis indicates that the effect of city size expansion on per capita income adheres to a 'U'-shaped trajectory, while its influence on the urban-rural income gap manifests an 'inverted U' pattern. Moreover, the inclusive income growth stemming from city size demonstrates notable heterogeneity across various geographic locations and city hierarchies. The findings reveal that human capital serves as the primary mechanism through which city size influences inclusive income growth. After decomposing the income inclusiveness index, it becomes evident that the expansion of city size exerts a more potent direct driving effect on the income of urban residents. On the one hand, city size expansion directly increases rural residents' income levels by improving labor productivity. On the other hand, it facilitates leapfrog income development by inducing the rural labor force to move to cities. [ABSTRACT FROM AUTHOR]

Background: Acute aortic syndrome (AAS) is an emergency associated with high peri-hospital mortality rates. Variable clinical presentation makes timely diagnosis challenging and such delays in diagnosis directly impact patient outcomes. Aims and objectives: The aims of the Collaborative Acute Aortic Syndrome Project (CAASP) are to characterise and evaluate the current AAS pathways of a cohort of hospitals in the UK, USA and New Zealand to determine if patient outcomes are influenced by the AAS pathway (time to hospital admission, diagnosis and management plan) and demographic, social, geographic and patient-specific factors (clinical presentation and comorbidities). The objectives are to describe different AAS pathways and time duration between hospital admission to diagnosis and management plan instigation, and to compare patient outcomes between pathways. Methods: The study is a multicentre, retrospective service evaluation project of adult patients diagnosed on imaging with AAS. It will be coordinated by the UK National Interventional Radiology Trainee Research (UNITE) network and Vascular and Endovascular Research Network (VERN) in conjunction with The Aortic Dissection Charitable Trust (TADCT). All AAS cases diagnosed on imaging between 1st January 2018 to 1st June 2021 will be included and followed-up for 6 months. Eligibility criteria include aortic dissection (AD) Type A, Type B, non A/B, penetrating aortic ulcer, and intramural haematoma. Exclusion criteria are non-AAS pathology, acute on chronic AAS, and age<18. This project will evaluate patient demographics, timing of presentation, patient symptoms, risk factors for AD, physical examination findings, timing to imaging and treatment, hospital stay, and mortality. Univariate and multivariate analysis will be used to identify predictors associated with prolonged time to diagnosis or treatment and mortality at 30 days. [ABSTRACT FROM AUTHOR]

This study utilizes panel data from 30 provinces in mainland China from 2011 to 2020 to investigate the impact of carbon-neutral development on economic high-quality development by constructing an economic high-quality development index and a carbon-neutral development index. Firstly, the study examines the effects of carbon-neutral development on economic high-quality development using baseline regression and spatial Durbin regression. The results indicate that carbon-neutral development has a positive direct effect on economic high-quality growth, but there are negative spatial spillover effects. Secondly, this study employs total factor productivity (TFP) as an intermediate variable in the mediation model regression. The findings demonstrate that carbon-neutral development significantly improves TFP, and the significant improvement in TFP promotes high-quality economic growth. Lastly, the study conducts regional heterogeneity analysis and finds a significant promoting effect of carbon-neutral development on economic high-quality development in the eastern and central regions of China, while it is not significant in the western region. Therefore, it is recommended that China, in the process of achieving carbon-neutral growth, consider the geographical connections between different regions to prevent negative spillover effects. Additionally, regional heterogeneity should be taken into account when formulating relevant policies to promote economic high-quality development. [ABSTRACT FROM AUTHOR]

This research was based on a nano-AAT (American Advanced Technology)-modified asphalt to which CRP (crumb rubber powder), a rubber waste, was introduced to explore the influence of CRP on AAT performance. The changes in the performance of AAT-modified asphalt after the addition of CRP were analyzed. The rubber powder with the raw material of waste tire was added to the asphalt instead of SBS modifier. While achieving waste recycling, the asphalt material has good performance. Physical analysis methods, rheological performance tests, rolling thin-film oven tests and Fourier transform infrared spectroscopy tests were used to investigate the performance of the composite-modified asphalt. The rheological properties of the composite-modified asphalt were analyzed by means of DSR, BBR and MSCR tests, and the microscopic mechanism of the modified asphalt was investigated by means of FTIR tests. The optimal nano-AAT-composite-modified formulation A3C3 (AAT-3.5%SBS-3%CRP) was selected by evaluating the overall performance. Additionally, the performances of the AAT/CRP-composite-modified asphalt and SBS-modified asphalt were compared using physical indicators, the rutting factor, creep flexibility and the stiffness modulus. The results show that the A3C3-modified asphalt had better stiffness, high-temperature (HT) performance and aging resistance than the SBS-modified asphalt, but it was less effective at low temperatures (LTs). According to FTIR, the absorption curves of A3C3 and SBS are essentially equal, with A3C3 only having a variation at 1104 cm−1. [ABSTRACT FROM AUTHOR]

A major unmet need in the cystic fibrosis (CF) therapeutic landscape is the lack of effective treatments for nonsense CFTR mutations, which affect approximately 10% of CF patients. Correction of nonsense CFTR mutations via genomic editing represents a promising therapeutic approach. In this study, we tested whether prime editing, a novel CRISPR-based genomic editing method, can be a potential therapeutic modality to correct nonsense CFTR mutations. We generated iPSCs from a CF patient homozygous for the CFTR W1282X mutation. We demonstrated that prime editing corrected one mutant allele in iPSCs, which effectively restored CFTR function in iPSC-derived airway epithelial cells and organoids. We further demonstrated that prime editing may directly repair mutations in iPSC-derived airway epithelial cells when the prime editing machinery is efficiently delivered by helper-dependent adenovirus (HDAd). Together, our data demonstrated that prime editing may potentially be applied to correct CFTR mutations such as W1282X. [ABSTRACT FROM AUTHOR]

A physical modeling approach was adopted to build a Digital Electro-Hydraulic Control (DEH) system simulation model and the fault models using the SIMULINK tool. This research combined the advantages of the gray system and neural network to build a multi-parameter gray error neural network fault prediction model for the first time. Furthermore, an embedded platform for intelligent fault diagnosis and prediction was developed using an Application Specific Integrated Circuit chip. The results show that the simulation model of the DEH system has good performance. A jam fault, internal leakage, and a device fault could be accurately identified through the fault diagnosis model. The multi-parameter gray error neural network prediction model improves the accuracy of fault prediction. The embedded platform developed by the Application Specific Integrated Circuit chip solves the problem of transmission limitation and insufficient computing power. It realizes the intelligent diagnosis and prediction of DEH system faults and guarantees the regular operation of the DEH system. [ABSTRACT FROM AUTHOR]

In nature and human societies, the effects of homogeneous and heterogeneous characteristics on the evolution of collective behaviors are quite different from each other. By incorporating pair pattern strategies and reference point strategies into an agent-based model, we have investigated the effects of homogeneous and heterogeneous investment strategies and reference points on price movement. In the market flooded with the investors with homogeneous investment strategies or homogeneous reference points, large price fluctuations occur. In the market flooded with the investors with heterogeneous investment strategies or heterogeneous reference points, moderate price fluctuations occur. The coexistence of different kinds of investment strategies can not only refrain from the occurrence of large price fluctuations but also the occurrence of no-trading states. The present model reveals that the coexistence of heterogeneous populations, whether they are the individuals with heterogeneous investment strategies or heterogeneous reference points of stock prices, is an important factor for the stability of the stock market. [ABSTRACT FROM AUTHOR]

Clustering is an unsupervised machine learning technique whose goal is to cluster unlabeled data. But traditional clustering methods only output a set of results and do not provide any explanations of the results. Although in the literature a number of methods based on decision tree have been proposed to explain the clustering results, most of them have some disadvantages, such as too many branches and too deep leaves, which lead to complex explanations and make it difficult for users to understand. In this paper, a hypercube overlay model based on multi-objective optimization is proposed to achieve succinct explanations of clustering results. The model designs two objective functions based on the number of hypercubes and the compactness of instances and then uses multi-objective optimization to find a set of nondominated solutions. Finally, an Utopia point is defined to determine the most suitable solution, in which each cluster can be covered by as few hypercubes as possible. Based on these hypercubes, an explanations of each cluster is provided. Upon verification on synthetic and real datasets respectively, it shows that the model can provide a concise and understandable explanations to users. [ABSTRACT FROM AUTHOR]

The human microbiome plays a crucial role in human health and is associated with a number of human diseases. Determining microbiome functional roles in human diseases remains a biological challenge due to the high dimensionality of metagenome gene features. However, existing models were limited in providing biological interpretability, where the functional role of microbes in human diseases is unexplored. Here we propose to utilize a neural network-based model incorporating Gene Ontology (GO) relationship network to discover the microbe functionality in human diseases. We use four benchmark datasets, including diabetes, liver cirrhosis, inflammatory bowel disease, and colorectal cancer, to explore the microbe functionality in the human diseases. Our model discovered and visualized the novel candidates' important microbiome genes and their functions by calculating the important score of each gene and GO term in the network. Furthermore, we demonstrate that our model achieves a competitive performance in predicting the disease by comparison with other non-Gene Ontology informed models. The discovered candidates' important microbiome genes and their functions provide novel insights into microbe functional contribution. [ABSTRACT FROM AUTHOR]

Though the traditional fault diagnosis method of T-connected transmission lines can identify the faults inside and outside the area, it can not identify the specific branches. To improve the accuracy and reliability of fault diagnosis of T-connection transmission lines, a new method is proposed to identify specific faulty branches of T-connection transmission lines based on multi-scale traveling wave reactive power and random forest. Based on the S-transform, the mean and sum ratios of the corresponding short-time series traveling wave reactive powers of each two traveling wave protection units at multiple frequencies are calculated respectively to form the fault feature vector sample set of the T-connection transmission line. A random forest fault branch identification model is established, and it is trained and tested by the fault feature sample set of T-connection transmission line to identify the fault branch. The simulation results show that the proposed algorithm can identify the branch where the fault is located inside and outside the protection zone of T-connection transmission line quickly and accurately under various working conditions. This method also shows good performance to identify faults even under the situation of CT saturation, noise influence and data loss. [ABSTRACT FROM AUTHOR]

The cytotoxicity of micro/nanoplastics (MNPs) is known to be strongly influenced by particle size, but the mechanism is not clear so far. We reported the ability of polystyrene MNPs to be internalized by HeLa cells could be a reason for the size dependent cytotoxicity of MNPs. We found that small MNPs (10 nm and 15 nm in radius) could be efficiently internalized by HeLa cells, MNPs of 25 nm in radius could be slightly internalized by the cells, and larger MNPs could not enter the cells at all. We showed that only MNPs, which could be internalized by cells, had a toxic effect on cell activity in a dose-dependent manner. In contrast, MNPs, which could not be internalized by cells, showed no cytotoxicity even if at extremely high concentrations. We attributed the correlation between the size-dependent uptake of MNPs and the size-dependent cytotoxicity of MNPs to the enhanced reactive oxygen species (ROS) level and abnormal gene expression. Our study pointed out that cellular uptake is one of the most fundamental mechanisms for the cytotoxicity of MNPs. [ABSTRACT FROM AUTHOR]

Castanopsis carlesii (Hemsl.) Hay. is a widely distributed and dominant tree species native to subtropical China with significant ecological and economic value. Due to serious human-related disturbance, its wild resources have been increasingly reduced, and whether may result in the loss of genetic diversity. However, no population genetics studies of natural C. carlesii have been reported to date. Microsatellite markers have been a useful tool in population genetics. Therefore, we developed EST-SSR markers based on the transcriptome sequencing of C. carlesii leaves. A total of 149,380,224 clean reads were obtained, and 63,012 nonredundant unigenes with a mean length of 1,034 bp were assembled and annotated based on sequence similarity searches in the Nr, Nt, KO, SwissProt, PFAM, KOG, and GO databases. The results showed that only 5,559 (8.82%) unigenes were annotated in all seven databases, but 46,338 (73.53%) could be annotated in at least one database. A total of 31,459 potential EST-SSRs were identified in 18,690 unigenes, with an average frequency of one SSR approximately 2 kb. Among the 100 EST-SSR primer pairs designed, 49 primer pairs successfully produced the expected product by amplification, with a success rate of 49%, but only 20 primer pairs showed abundant polymorphisms. Polymorphisms were verified using 25 samples from C. carlesii in Qimen, Anhui. A total of 119 alleles were detected, with a mean number of alleles (Na) of 5.95 per locus and a mean polymorphism information content (PIC) of 0.6125. All the 20 newly developed EST-SSR markers were verified in other Castanopsis species (C. sclerophylla, C. lamontii, C. fargesii, C. eyrei and C. jucunda). Sixteen primer pairs showed successful amplification in all five Castanopsis species (80%), and the transferability ratios ranged from 90% to 100%. These developed EST-SSR markers can be applied to population genetic and germplasm evaluations of C. carlesii and related species. [ABSTRACT FROM AUTHOR]

The morphology of the nuclei represents most of the clinical pathological information, and nuclei segmentation is a vital step in current automated histopathological image analysis. Supervised machine learning-based segmentation models have already achieved outstanding performance with sufficiently precise human annotations. Nevertheless, outlining such labels on numerous nuclei is extremely professional needing and time consuming. Automatic nuclei segmentation with minimal manual interventions is highly needed to promote the effectiveness of clinical pathological researches. Semi-supervised learning greatly reduces the dependence on labeled samples while ensuring sufficient accuracy. In this paper, we propose a Multi-Edge Feature Fusion Attention Network (MEFFA-Net) with three feature inputs including image, pseudo-mask and edge, which enhances its learning ability by considering multiple features. Only a few labeled nuclei boundaries are used to train annotations on the remaining mostly unlabeled data. The MEFFA-Net creates more precise boundary masks for nucleus segmentation based on pseudo-masks, which greatly reduces the dependence on manual labeling. The MEFFA-Block focuses on the nuclei outline and selects features conducive to segment, making full use of the multiple features in segmentation. Experimental results on public multi-organ databases including MoNuSeg, CPM-17 and CoNSeP show that the proposed model has the mean IoU segmentation evaluations of 0.706, 0.751, and 0.722, respectively. The model also achieves better results than some cutting-edge methods while the labeling work is reduced to 1/8 of common supervised strategies. Our method provides a more efficient and accurate basis for nuclei segmentations and further quantifications in pathological researches. [ABSTRACT FROM AUTHOR]

Objectives: To measure housing assistance and homelessness among persons living with HIV (PLWH) and their association with health. Methods: Exposure categories were: experiencing homelessness (per emergency shelter use or self-report), receiving housing assistance (per housing subsidy) without homelessness, or neither homelessness nor receiving housing assistance. Outcomes were: engagement (≥1 visit) and retention (≥2 visits ≥90 days apart) in HIV-related medical care and one-time (latest viral load) and durable (≥1 viral load test, all suppressed) HIV viral suppression (<200 copies/mL). Among PLWH in New York City (NYC), we calculated and conducted modified Poisson regressions of the four outcomes according to exposure category. Results: During 2018, 45% of NYC's 84,053 PLWH received housing assistance, and 8% experienced homelessness. Relative to homelessness, receipt of assistance without homelessness was associated with 3–7% higher adjusted relative risk (ARR) of engagement and retention in care and 31–64% higher ARR of one-time and durable viral suppression. Relative to not receiving assistance, receipt of assistance without homelessness was associated with 6–18% higher ARR of care and 2–5% lower ARR of viral suppression. Conclusions: Programs promoting housing stability may support HIV care and viral suppression, particularly if preventing homelessness. These may help improve HIV care and suppression rates. [ABSTRACT FROM AUTHOR]

The current COVID-19 pandemic has profoundly impacted people's lifestyles and travel behaviours, which may persist post-pandemic. An effective monitoring tool that allows us to track the level of change is vital for controlling viral transmission, predicting travel and activity demand and, in the long term, for economic recovery. In this paper, we propose a set of Twitter mobility indices to explore and visualise changes in people's travel and activity patterns, demonstrated through a case study of London. We collected over 2.3 million geotagged tweets in the Great London Area (GLA) from Jan 2019 –Feb 2021. From these, we extracted daily trips, origin-destination matrices, and spatial networks. Mobility indices were computed based on these, with the year 2019 as a pre-Covid baseline. We found that in London, (1) People are making fewer but longer trips since March 2020. (2) In 2020, travellers showed comparatively reduced interest in central and sub-central activity locations compared to those in outer areas, whereas, in 2021, there is a sign of a return to the old norm. (3) Contrary to some relevant literature on mobility and virus transmission, we found a poor spatial relationship at the Middle Layer Super Output Area (MSOA) level between reported COVID-19 cases and Twitter mobility. It indicated that daily trips detected from geotweets and their most likely associated social, exercise and commercial activities are not critical causes for disease transmission in London. Aware of the data limitations, we also discuss the representativeness of Twitter mobility by comparing our proposed measures to more established mobility indices. Overall, we conclude that mobility patterns obtained from geo-tweets are valuable for continuously monitoring urban changes at a fine spatiotemporal scale. [ABSTRACT FROM AUTHOR]

Food safety problems are becoming increasingly severe in modern society, and establishing an accurate food safety risk warning and analysis model is of positive significance in avoiding food safety accidents. We propose an algorithmic framework that integrates the analytic hierarchy process based on the entropy weight (AHP-EW) and the autoencoder-recurrent neural network (AE-RNN). Specifically, the AHP-EW method is first used to obtain the weight percentages of each detection index. The comprehensive risk value of the product samples is obtained by weighted summation with the detection data, which is used as the expected output of the AE-RNN network. The AE-RNN network is constructed to predict the comprehensive risk value of unknown products. The detailed risk analysis and control measures are taken based on the risk value. We applied this method to the detection data of a dairy product brand in China for example validation. Compared with the performance of 3 models of the back propagation algorithm (BP), the long short-term memory network (LSTM), and the LSTM based on the attention mechanism (LSTM-Attention), the AE-RNN model has a shorter convergence time, predicts data more accurately. The root mean square error (RMSE) of experimental data is only 0.0018, proving that the model is feasible in practice and helps improve the food safety supervision system in China to avoid food safety incidents. [ABSTRACT FROM AUTHOR]

Investigations from past earthquakes have shown that underground subway stations can suffer excessive deformation under strong seismic loads, leading to the damage of critical components and the collapse of structures. This study presents the results of finite element analyses on the seismic damage of underground subway stations installed under different soil constraint conditions. The plastic hinge distribution and damage characteristics of cut and cover double-storey and three-storey subway stations are analyzed using the finite element method software ABAQUS. Combined with the static analysis results of the column sections, a discriminant method for bending plastic hinges is presented. The numerical results show that the collapse of the subway stations begins with the failure of the bottom columns' bottom sections, which leads to the bending of the plates and the destruction of the whole structure. The bending deformation at the end section of columns has an approximatively linear relationship with the inter-storey drift ratio, and the change in soil conditions shows no apparent influence. The sidewall deformation behavior varies significantly under different soil conditions, and the bending deformation at the bottom section of sidewalls increases along with an increase in the soil-structure stiffness ratio at the same inter-storey drift deformation level. The sidewall bending ductility ratio of the double-storey and three-storey stations at the elastic-plastic drift ratio limit increases by 61.6% and 26.7%, respectively. In addition, the fitting curves between the component bending ductility ratio and inter-storey drift ratio based on the analysis results are also presented. The findings may provide a helpful reference for the seismic performance evaluation and design of underground subway stations. [ABSTRACT FROM AUTHOR]

In the process of multi-exposure image fusion (MEF), the appearance of various distortions will inevitably cause the deterioration of visual quality. It is essential to predict the visual quality of MEF images. In this work, a novel blind image quality assessment (IQA) method is proposed for MEF images considering the detail, structure, and color characteristics. Specifically, to better perceive the detail and structure distortion, based on the joint bilateral filtering, the MEF image is decomposed into two layers (i.e., the energy layer and the structure layer). Obviously, this is a symmetric process that the two decomposition results can independently and almost completely describe the information of MEF images. As the former layer contains rich intensity information and the latter captures some image structures, some energy-related and structure-related features are extracted from these two layers to perceive the detail and structure distortion phenomena. Besides, some color-related features are also obtained to present the color degradation which are combined with the above energy-related and structure-related features for quality regression. Experimental results on the public MEF image database demonstrate that the proposed method achieves higher performance than the state-of-the-art quality assessment ones. [ABSTRACT FROM AUTHOR]

Most of the existing emotion elicitation databases use the film clips as stimuli and do not take into account the age and gender differences of participants. Considering the short videos have the advantages of short in time, easy to understand and strong emotional appeal, we choose them to construct a standardized database of Chinese emotional short videos by the joint analysis of age and gender differences. Two experiments are performed to establish and validate our database. In the Experiment 1, we selected 240 stimuli from 2700 short videos and analyzed the subjective evaluation results of 360 participants with different ages and genders. As a result, a total of 54 short videos with three categories of emotions were picked out for 6 groups of participants, including the male and female respectively aged in 20-24, 25-29 and 30-34. In the Experiment 2, we recorded the EEG signals and subjective experience scores of 81 participants while watching different video stimuli. Both the results of EEG emotion recognition and subjective evaluation indicate that our database of 54 short videos can achieve better emotion elicitation effects compared with film clips. Furthermore, the targeted delivery of specific short videos has also been verified to be effective, helping the researchers choose appropriate emotional elicitation stimuli for different participants and promoting the study of individual differences in emotion responses. [ABSTRACT FROM AUTHOR]

Objective: This study was to determine the racial disparities in incidence, clinicopathological features and prognosis of hypopharyngeal squamous cell carcinoma (HPSCC) in the US. Methods: The National Program of Cancer Registries and Surveillance, Epidemiology, and End Results (SEER) database was used to determine racial disparity in age adjusted incidence rate (AAIR) of HPSCC and its temporal trend during 2004–2019. Using the separate SEER 17 database, we further evaluated racial disparity in clinicopathological features, and in prognosis using Kaplan-Meier curves and Cox proportional hazard models. Results: HPSCC accounted for 95.8% of all hypopharyngeal cancers and occurred much more frequently in males. Its incidence decreased in both male and females, in male non-Hispanic white (NHW), non-Hispanic black (NHB) and Hispanic as well as female NHW and NHB during the study period. NHB had the highest, whereas non-Hispanic Asian or Pacific Islanders (API) had comparable and the lowest incidence in both males and females. Among 6,172 HPSCC patients obtained from SEER 17 database, 80.6% were males and 83.9% were at the advanced stages III/IV. Five-year cancer specific and overall survival rates were 41.2% and 28.9%, respectively. NHB patients were more likely to be younger, unmarried, from the Southern region, larger sized tumor, and at the stage IV, but less likely to receive surgery. They also had higher proportions of dying from HPSCC and all causes. Multivariate analyses revealed that NHB with HPSCC at the locally advanced stage had both significantly worse cancer specific and overall survival compared with NHW, but not at early stage (I/II) or distant metastatic stage. Hispanic patients had significantly better prognosis than NHW at locally advanced and metastatic stages. NHW and API had comparable prognoses. Conclusions: HPSCC displays continuously decreased incidence and racial disparity. The majority of the disease is diagnosed at the advanced stage. NHB have the highest burden of HPSCC and a worse prognosis. More studies are needed to curtail racial disparity and improve early detection. [ABSTRACT FROM AUTHOR]

Information consumption is a kind of economic activity that directly or indirectly takes information products and information services as consumption objects. Most of the existing studies have established the "formula" of rural information consumption in promoting economic and social development, while few efforts have been devoted to study the quantitative reciprocities between them. Therefore, this study aims to investigate the relationship between information consumption in rural areas and regional economic development with a case study of Zhejiang, China. Based on rural information consumption-related indexes, basic geographic data, and other publicly available regional economic development related data, we conduct the exploration with the spatial Durbin model (SDM). The study indicates that (1) from the perspective of spatial analysis, the economic development level of all prefecture-level cities in Zhejiang, China has a significant positive spatial correlation; (2) in rural areas, the network infrastructure improvement, information industry clustering, etc. can accelerate enhancing information consumption and promote regional economic development; and (3) facilitate the development of rural information consumption is conducive to alleviate the imbalance of regional economic development. It is hoped that our study can help understand the current situation of information consumption in rural China and provide a theoretical reference for rural economic and social development. [ABSTRACT FROM AUTHOR]

In recent years, as the Ether platform has grown by leaps and bounds. Numerous unscrupulous individuals have used illegal transaction to defraud large sums of money, causing billions of dollars of losses to investors worldwide. Facing the endless stream of the illegal transaction based on Ether smart contracts problems, such as illegal transaction, money laundering, financial fraud, phishing. Currently, illegal transaction are only detected by a single view of the smart contract's contract code view feature and account transaction view feature, which is not only incomplete, but also not fully representative of the smart contract's features. More importantly, the single view detection model cannot accurately capture the global structure and semantic features between the Tokens of the view features. In this case, it is particularly important that all view features are shared among themselves. In this paper, we investigate a Transformer-based model for contrasting illegal transaction detection networks under multiple views (TranMulti-View Net). The model in this paper is based on Transformer to learn a multi-view fusion representation, which aims to maximise the fusion of the interaction information of different view features under the same condition. In this model we first use the Transformer model to learn global structure and semantic features from a sequence of Tokens tokenised by a view, capturing the remote dependencies of Tokens in the view features, and then we share the contract code view features and the account transaction view features across all views to learn important semantic information between views from each other. In addition, we find that the approach of semi-supervised training of multi-view features using contrast learning outperforms the scheme of prediction based on direct fusion of different view features, resulting in stronger correlation between view features. As a result, the underlying semantic information can be captured more accurately, leading to more accurate predictions of illegal transaction. The experimental results show that our proposed TranMulti-View Net obtains good detection results with a Precision score of 98%. [ABSTRACT FROM AUTHOR]

Plants play a very important role in landscape construction. In order to explore whether different living environment will affect people's preference for the structural features of plant organs, this study examined 26 villagers and 33 college students as the participants, and pictures of leaves, flowers and fruits of plants as the stimulus to conduct eye-tracking and EEG detection experiments. We found that eye movement indicators can explain people's visual preferences, but they are unable to find differences in preferences between groups. EEG indicators can make up for this deficiency, which further reveals the difference in psychological and physiological responses between the two groups when viewing stimuli. The final results show that the villagers and the students liked leaves best, preferring aciculiform and leathery leaves; solitary, purple and capitulum flowers; and medium-sized, spathulate, black and pear fruits. In addition, it was found that the overall attention of the villagers when watching stimuli was far lower than that of the students, but the degree of meditation was higher. With regard to eye movement and EEG, the total duration of fixations is highly positively correlated with the number of fixations, and the average pupil size has a weak negative correlation with attention. On the contrary, the average duration of fixations has a weak positive correlation with meditation. Generally speaking, we believe that Photinia×fraseri, Metasequoia glyptostroboides, Photinia serratifolia, Koelreuteria bipinnata and Cunninghamia lanceolata are superior landscape building plants in rural areas and on campuses; Pinus thunbergii, Myrica rubra, Camellia japonica and other plants with obvious features and bright colours are also the first choice in rural landscapes; and Yulania biondii, Cercis chinensis, Hibiscus mutabilis and other plants with simple structures are the first choice in campus landscapes. This study is of great significance for selecting plants for landscape construction and management according to different environments and local conditions. [ABSTRACT FROM AUTHOR]

This paper uses the Difference-in-Differences method to test the impact of the promulgation of Green Credit Guidelines, a market-oriented environmental regulation, on the enterprise market expansion strategy, based on the panel data of Chinese A-share listed companies from 2008 to 2015. We find that the promulgation of Green Credit Guidelines significantly inhibited the market expansion strategy of high pollution enterprises. Two channels through which the Green Credit Guidelines affect the market expansion strategies of high polluters are increasing the cost of financing and promoting green R&D. Heterogeneity analysis finds that the impact of Green Credit Guidelines on the market expansion of highly polluting enterprises is more significant in non-state-owned enterprises and enterprises without equity incentive. Further analysis shows that the promulgation of Green Credit Guidelines damages the corporate image and profitability of high polluting enterprises, but it doesn't increase the risk of high polluting enterprises. The results of this research could help relevant government departments to formulate practical environmental regulations and promote sustainable economic development. [ABSTRACT FROM AUTHOR]

Protein posttranslational modifications (PTMs) by O-GlcNAc globally rise during pressure-overload hypertrophy (POH). However, a major knowledge gap exists on the specific proteins undergoing changes in O-GlcNAc levels during POH primarily because this PTM is low abundance and easily lost during standard mass spectrometry (MS) conditions used for protein identification. Methodologies have emerged to enrich samples for O-GlcNAcylated proteins prior to MS analysis. Accordingly, our goal was to identify the specific proteins undergoing changes in O-GlcNAc levels during POH. We used C57/Bl6 mice subjected to Sham or transverse aortic constriction (TAC) to create POH. From the hearts, we labelled the O-GlcNAc moiety with tetramethylrhodamine azide (TAMRA) before sample enrichment by TAMRA immunoprecipitation (IP). We used LC-MS/MS to identify and quantify the captured putative O-GlcNAcylated proteins. We identified a total of 700 putative O-GlcNAcylated proteins in Sham and POH. Two hundred thirty-three of these proteins had significantly increased enrichment in POH over Sham suggesting higher O-GlcNAc levels whereas no proteins were significantly decreased by POH. We examined two MS identified metabolic enzymes, CPT1B and the PDH complex, to validate by immunoprecipitation. We corroborated increased O-GlcNAc levels during POH for CPT1B and the PDH complex. Enzyme activity assays suggests higher O-GlcNAcylation increases CPT1 activity and decreases PDH activity during POH. In summary, we generated the first comprehensive list of proteins with putative changes in O-GlcNAc levels during POH. Our results demonstrate the large number of potential proteins and cellular processes affected by O-GlcNAc and serve as a guide for testing specific O-GlcNAc-regulated mechanisms during POH. [ABSTRACT FROM AUTHOR]

Objectives: Family caregivers play a fundamental role in the care of the older blunt trauma patient. We aim to identify risk factors for negative and positive experiences of caregiving among family caregivers. Design: Prospective, nationwide, multi-center cohort study. Setting and participants: 110 family caregivers of Singaporeans aged≥55 admitted for unintentional blunt trauma with an Injury Severity Score (ISS) or New Injury Severity Score (NISS)≥10 were assessed for caregiving-related negative (disturbed schedule and poor health, lack of family support, lack of finances) and positive (esteem) experiences using the modified-Caregiver Reaction Assessment (m-CRA) three months post-injury. Methods: The association between caregiver and patient factors, and the four m-CRA domains were evaluated via linear regression. Results: Caregivers of retired patients and caregivers of functionally dependent patients (post-injury Barthel score <80) reported a worse experience in terms of disturbed schedule and poor health (β-coefficient 0.42 [95% Confidence Interval 0.10, 0.75], p =.01; 0.77 [0.33, 1.21], p =.001), while male caregivers and caregivers who had more people in the household reported a better experience (-0.39 [-0.73, -0.06], p =.02; -0.16 [-0.25, -0.07], p =.001). Caregivers of male patients, retired patients, and patients living in lower socioeconomic housing were more likely to experience lack of family support (0.28, [0.03, -0.53], p =.03; 0.26, [0.01, 0.52], p =.05; 0.34, [0.05, -0.66], p =.02). In the context of lack of finances, caregivers of male patients and caregivers of functionally dependent patients reported higher financial strain (0.74 [0.31, 1.17], p =.001; 0.84 [0.26, 1.43], p =.01). Finally, caregivers of male patients reported higher caregiver esteem (0.36 [0.15, 0.57], p =.001). Conclusions and implications: Negative and positive experiences of caregiving among caregivers of older blunt trauma patients are associated with pre-injury disability and certain patient and caregiver demographics. These factors should be considered when planning the post-discharge support of older blunt trauma patients. [ABSTRACT FROM AUTHOR]

Sustainability, as a trend of social development and the embodiment of corporate social responsibility, has begun to receive more attention. To achieve this goal, sustainable supplier selection (SSS) and order allocation (OA) are seen as the crucial activities in corporate management. In the process of SSS, the psychological behavior of decision-makers (DMs) could play a critical role in the evaluation results. Therefore, introducing it into the decision-making process may lead to decision in line with the actual situation. In the uncertain multi-criteria group decision-making (MCGDM) problem described by probability linguistic term sets (PLTS), the DMs can evaluate the criteria of each supplier based on his own preference and hesitation, which is useful to avoid the loss of information. For this reason, this study develops a novel multi-criteria group decision-making combined with fuzzy multi-objective optimization (MCGDM-FMOO) model for SSS/OA problems by considering the triple bottom line (TBL) in which includes economic, environmental and social factors. The proposed method includes four stages. (1) the best-worst method (BWM) and entropy weight method are utilized to assign the weights of criteria to obtain the comprehensive weight. According to the output weights, the an acronym for interactive and multi-criteria decision-making in Portugese (TODIM) approach is applied to rank the suppliers under PLTS environment; (2) a FMOO model that can effectively deal with uncertainties and dynamic nature of parameter is formulated for allocating optimal order quantities; (3) two novel approaches are utilized to solve the FMOO model in order to obtain the richer Pareto frontier; and (4) the final OA solution is achieved by technique for order preference by similarity to ideal solution (TOPSIS) method. Finally, the validity and practicability of proposed MCGDM-FMOO model are verified by an example and comparative analysis with other classical MCGDM methods. [ABSTRACT FROM AUTHOR]

The analysis of pathological images, such as cell counting and nuclear morphological measurement, is an essential part in clinical histopathology researches. Due to the diversity of uncertain cell boundaries after staining, automated nuclei segmentation of Hematoxylin-Eosin (HE) stained pathological images remains challenging. Although better performances could be achieved than most of classic image processing methods do, manual labeling is still necessary in a majority of current machine learning based segmentation strategies, which restricts further improvements of efficiency and accuracy. Aiming at the requirements of stable and efficient high-throughput pathological image analysis, an automated Feature Global Delivery Connection Network (FGDC-net) is proposed for nuclei segmentation of HE stained images. Firstly, training sample patches and their corresponding asymmetric labels are automatically generated based on a Full Mixup strategy from RGB to HSV color space. Secondly, in order to add connections between adjacent layers and achieve the purpose of feature selection, FGDC module is designed by removing the jumping connections between codecs commonly used in UNet-based image segmentation networks, which learns the relationships between channels in each layer and pass information selectively. Finally, a dynamic training strategy based on mixed loss is used to increase the generalization capability of the model by flexible epochs. The proposed improvements were verified by the ablation experiments on multiple open databases and own clinical meningioma dataset. Experimental results on multiple datasets showed that FGDC-net could effectively improve the segmentation performances of HE stained pathological images without manual interventions, and provide valuable references for clinical pathological analysis. [ABSTRACT FROM AUTHOR]

Using data from China Family Panel Studies (CFPS) and based on the Probit and Tobit models, this study investigates the impact of air pollution on residents' outdoor exercise behaviour from the microscopic level. Specifically, this study examined the effects of PM2.5 index changes on residents' decision to participate in outdoor exercise and the duration of outdoor exercise participation. The empirical results show that the increase of PM2.5 index has a significant inhibitory effect on residents' participation in outdoor exercise, and has passed the robustness test and endogeneity test. Further testing found that the inhibitory effect was significantly different between urban and rural areas, and in the central, north-eastern and western regions where economic development was relatively backward, the conclusion that air pollution inhibited residents' outdoor exercise behaviour still holds true. However, the level of air pollution had no significant effect on the outdoor exercise behaviour of residents in the eastern region. So, while air pollution discourages residents from participating in outdoor exercise, the results are more applicable to less economically developed areas. [ABSTRACT FROM AUTHOR]

Fibroblast growth factor 21 (FGF21), a known risk factor for atherosclerosis, is readily regulated by exercise, and it can inhibit NOD-like receptor protein 3 (NLRP3)-mediated pyroptosis. However, it is not clear whether aerobic exercise inhibits atherosclerosis via these pathways. Eight-week-old apolipoprotein E-deficient (ApoE-/-) mice on a high-fat diet were randomly divided into 1-h post-exercise (EX-1h), 24-h post-exercise (EX-24h), and sedentary (SED) groups. C57BL/6J wild-type mice fed normal chow served as controls (WT group). Mice in the EX-1h and EX-24h groups were subjected to treadmill exercise training for 12 weeks. Aerobic exercise reduced body weight; blood glucose, lipid, and inflammation levels; and aortic plaque area proportion. Aerobic exercise increased the sensitivity of FGF21 by upregulating the expression of the downstream receptor adiponectin (ApN); the serum FGF21 level after exercise increased initially, and then decreased. Aerobic exercise downregulated the expression of NLRP3 inflammasome-mediated pyroptosis-related markers in the aorta, and FGF21 may participate in the above process. Meanwhile, the liver may be the tissue source of serum FGF21 during aerobic exercise. In conclusion, aerobic exercise may inhibit atherogenesis by regulating FGF21 and NLRP3 inflammasome-mediated pyroptosis. Our study provides new information on the atherosclerosis-preventing mechanism of aerobic exercise. [ABSTRACT FROM AUTHOR]

A clustering algorithm is a solution for grouping a set of objects and for distribution centre location problems. But the common K-means clustering algorithm may give local optimal solutions. Swarm intelligent algorithms simulate the social behaviours of animals and avoid local optimal solutions. We employ three swarm intelligent algorithms to avoid these solutions. We propose a new algorithm for the clustering problem, the fruit-fly optimization K-means algorithm (FOA K-means). We designed a distribution centre location problem and three clustering indicators to evaluate the performance of algorithms. We compare the algorithms of K-means with the ant colony optimization algorithm (ACO K-means), particle swarm optimization algorithm (PSO K-means), and fruit-fly optimization algorithm. We find K-Means modified by the fruit-fly optimization algorithm (FOA K-means) has the best performance on convergence speed and three clustering indicators, compactness, separation, and integration. Thus, we can apply FOA K-means to improve the distribution centre location solution and the efficiency for distribution in the future. [ABSTRACT FROM AUTHOR]

Objective: To examine the clinical characteristics of patients with asymptomatic novel coronavirus disease 2019 (COVID-19) and compare them with those of patients with mild disease. Design: A retrospective cohort study. Setting: Multiple medical centers in Wuhan, Hubei, China. Participants: A total of 3,263 patients with laboratory-confirmed severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) infection between February 4, 2020, and April 15, 2020. Main outcome measures: Patient demographic characteristics, medical history, vital signs, and laboratory and chest computed tomography (CT) findings. Results: A total of 3,173 and 90 patients with mild and moderate, and asymptomatic COVID-19, respectively, were included. A total of 575 (18.2%) symptomatic patients and 4 (4.4%) asymptomatic patients developed the severe illness. All asymptomatic patients recovered; no deaths were observed in this group. The median duration of viral shedding in asymptomatic patients was 17 (interquartile range, 9.25–25) days. Patients with higher levels of ultrasensitive C-reactive protein (odds ratio [OR] = 1.025, 95% confidence interval [CI], 1.01–1.04), lower red blood cell volume distribution width (OR = 0.68, 95% CI 0.51–0.88), lower creatine kinase Isoenzyme(0.94, 0.89–0.98) levels, or lower lesion ratio (OR = 0.01, 95% CI 0.00–0.33) at admission were more likely than their counterparts to have asymptomatic disease. Conclusions: Patients with younger ages and fewer comorbidities are more likely to be asymptomatic. Asymptomatic patients had similar laboratory characteristics and longer virus shedding time than symptomatic patients; screen and isolation during their infection were helpful to reduce the risk of SARS-CoV-2 transmission. [ABSTRACT FROM AUTHOR]

Objectives: In this meta-analysis study, the main objective was to determine the accuracy of S-detect in effectively distinguishing malignant thyroid nodules from benign thyroid nodules. Methods: We searched the PubMed, Cochrane Library, and CBM databases from inception to August 1, 2021. Meta-analysis was conducted using STATA version 14.0 and Meta-Disc version 1.4 softwares. We calculated summary statistics for sensitivity (Sen), specificity (Spe), positive and negative likelihood ratio (LR+/LR−), diagnostic odds ratio(DOR), and receiver operating characteristic (SROC) curves. Cochran's Q-statistic and I2 test were used to evaluate potential heterogeneity between studies. A sensitivity analysis was performed to evaluate the influence of single studies on the overall estimate. We also performed meta-regression analyses to investigate the potential sources of heterogeneity. Results: In this study, a total of 17 studies meeting the requirements of the standard were used. The number of benign and malignant nodules analyzed and evaluated in this paper was 1595 and 1118 respectively. This paper mainly completes the required histological confirmation through s-detect. The pooled Sen and pooled Spe were 0.87 and 0.74, respectively, (95%CI = 0.84–0.89) and (95%CI = 0.66–0.81). Furthermore, the pooled LR+ and negative LR− were determined to be 3.37 (95%CI = 2.53–4.50) and 0.18 (95%CI = 0.15–0.21), respectively. The experimental results showed that the pooled DOR of thyroid nodules was 18.83 (95% CI = 13.21–26.84). In addition, area under SROC curve was determined to be 0.89 (SE = 0.0124). It should be pointed out that there is no evidence of bias (i.e. t = 0.25, P = 0.80). Conclusions: Through this meta-analysis, it can be seen that the accuracy of s-detect is relatively high for the effective distinction between malignant thyroid nodules and benign thyroid nodules. [ABSTRACT FROM AUTHOR]

Slope One algorithm and its descendants measure user-score distance and use the statistical score distance between users to predict unknown ratings, as opposed to the typical collaborative filtering algorithm that uses similarity for neighbor selection and prediction. Compared to collaborative filtering systems that select only similar neighbors, algorithms based on user-score distance typically include all possible related users in the process, which needs more computation time and requires more memory. To improve the scalability and accuracy of distance-based recommendation algorithm, we provide a user-item link prediction approach that combines user distance measurement with similarity-based user selection. The algorithm predicts unknown ratings based on the filtered users by calculating user similarity and removing related users with similarity below a threshold, which reduces 26 to 29 percent of neighbors and improves prediction error, ranking, and prediction accuracy overall. [ABSTRACT FROM AUTHOR]