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With the development of modernization, traditional fossil energy reserves are decreasing, and the power industry, as one of the main energy consumption forces, has begun to pay attention to increasing the proportion of clean energy generation. With the deepening of electrification, the peak-valley difference of residential electricity consumption increases, but photovoltaic and wind power generation have fluctuations and are manifested as reverse peak regulation. Thermal power plants as the main force of peak regulation gradually reduce the market share, making nuclear power plants bear the heavy responsibility of participating in peak regulation. The traditional method of adjusting operating power by inserting and removing control rods has great safety risks and wastes resources. Therefore, this paper proposes a new energy storage system that can keep the nuclear power plant running at full power and produce hydrogen to synthesize ammonia from excess power. A comprehensive evaluation model of energy storage based on z-score data standardization and objective parameter assignment AHP (analytic hierarchy process) analysis method was established to evaluate energy storage systems according to a multi-index system. With an AP1000 daily load tracking curve as the input model, the simulation model built by Aspen Plus V14 was used to calculate the operating conditions of the system. In order to provide a construction basis for practical engineering use, Haiyang Nuclear Power Plant in Shandong Province is taken as an example. The system layout scheme is proposed according to the local environmental conditions. The accident tree analysis method is combined with ALOHA 5.4.1.2 (Areal Locations of Hazardous Atmospheres) hazardous chemical analysis software and MARPLOT 5.1.1 geographic information technology. A qualitative and quantitative assessment of risk factors and the consequences of leakage, fire, and explosion accidents caused by hydrogen and ammonia storage processes is carried out to provide guidance for accident prevention and emergency rescue. The design of an "Electric-Hydrogen-Ammonia" energy storage system proposed in this paper provides a new idea for zero-carbon energy storage for the peak shaving of nuclear power plants and has a certain role in promoting the development of clean energy. [ABSTRACT FROM AUTHOR]

Adenomyosis involves the infiltration of endometrial glands and stroma deep into the uterine tissue, causing disruption to the endometrial–myometrial interface (EMI). The role of interleukin-17 (IL-17) has been extensively studied in endometriosis, but its involvement in adenomyosis remains unclear. This study aimed to investigate the expression of IL-17 in eutopic and ectopic endometrium (adenomyosis) of individuals with adenomyosis at the level of EMI. Paired tissues of eutopic endometrium and adenomyoma were collected from 16 premenopausal women undergoing hysterectomy due to adenomyosis. The IL-17 system was demonstrated in paired tissue samples at the level of EMI by the immunochemistry study. Gene expression levels of IL-17A and IL-17 receptor (IL-17R) were assessed through quantitative real-time reverse transcription polymerase chain reaction (RT-PCR). Comparative gene transcript amounts were calculated using the delta-delta Ct method. By immunohistochemical staining, CD4, IL-17A, and IL-17R proteins were detected in both eutopic endometrium and adenomyosis at the level of EMI. IL-17A and IL-17R were expressed mainly in the glandular cells, and the expression of both IL-17A and IL-17R was found to be stronger in adenomyosis than in endometrium. 3-Diaminobenzidine (DAB) staining revealed greater IL-17A expression in adenomyosis compared to eutopic endometrium. Quantitative RT-PCR showed 7.28-fold change of IL-17A and 1.99-fold change of IL-17R, and the fold change level of both IL-17A and IL-17R is significantly higher in adenomyosis (IL-17A: p = 0.047, IL-17R: p = 0.027) versus eutopic endometrium. We found significantly higher IL-17 levels in adenomyosis compared to eutopic endometrium at the level of EMI. The results showed that the IL-17 system may play a role in adenomyosis. [ABSTRACT FROM AUTHOR]

Background: The causal association of specific gut microbiota with dementia remains incompletely understood. We aimed to access the causal relationships in which one or more gut microbiota account for dementia. Method: Using data from the MiBioGen and FinnGen consortia, we employed multiple Mendelian randomization (MR) approaches including two-sample MR (TSMR), multivariable MR (MVMR), and Bayesian model averaging MR to comprehensively evaluate the causal associations between 119 genera and dementia, and to prioritize the predominant bacterium. Result: We identified 21 genera that had causal effects on dementia and suggested Barnesiella (OR = 0.827, 95%CI = 0.722–0.948, marginal inclusion probability [MIP] = 0.464; model-averaged causal estimate [MACE] = −0.068) and Allisonella (OR = 0.770, 95%CI = 0.693–0.855, MIP = 0.898, MACE = −0.204) as the predominant genera for AD and all-cause dementia. Conclusions: These findings confirm the causal relationships between specific gut microbiota and dementia, highlighting the necessity of multiple MR approaches in gut microbiota analysis, and provides promising genera as potential novel biomarkers for dementia risk. [ABSTRACT FROM AUTHOR]

In this study, we demonstrate the high luminous efficacy of 118 lm/W and the high reliability of white LEDs (WLEDs) through 450 °C thermal aging, utilizing four-inch YAG: Ce3+ phosphor-in-glass (PiG) plates designed for vehicle headlights. The sintering process of mixing glass and phosphor typically generates pores, which can scatter light and reduce the luminous efficacy of the fabricated PiG. In this study, we produced four-inch PiG plates under four different fabrication conditions to evaluate their luminous efficacy. Our results revealed that the PiG plate with a thin thickness of 0.08 mm exhibited a 16.83% increase in luminous efficacy compared to the 0.15 mm plate, attributed to reduced light interaction with the pores. Unlike silicone-based phosphor WLEDs, which offer high performance but lower reliability due to the silicone resin's low transition temperature (150 °C), our novel thin PiG plate achieves high performance and reliability. This advancement suggests that the proposed thin PiG plate could replace traditional silicone-based phosphors, enabling the development of high-quality WLEDs for vehicle headlights in automotive applications. [ABSTRACT FROM AUTHOR]

The causal association of circulating metabolites with dementia remains uncertain. We assessed the causal association of circulating metabolites with dementia utilizing Mendelian randomization (MR) methods. We performed univariable MR analysis to evaluate the associations of 486 metabolites with dementia, Alzheimer's disease (AD), and vascular dementia (VaD) risk. For secondary validation, we replicated the analyses using an additional dataset with 123 metabolites. We observed 118 metabolites relevant to the risk of dementia, 59 of which were lipids, supporting the crucial role of lipids in dementia pathogenesis. After Bonferroni adjustment, we identified nine traits of HDL particles as potential causal mediators of dementia. Regarding dementia subtypes, protective effects were observed for epiandrosterone sulfate on AD (OR = 0.60, 95% CI: 0.48–0.75) and glycoproteins on VaD (OR = 0.89, 95% CI: 0.83–0.95). Bayesian model averaging MR (MR-BMA) analysis was further conducted to prioritize the predominant metabolites for dementia risk, which highlighted the mean diameter of HDL particles and the concentration of very large HDL particles as the predominant protective factors against dementia. Moreover, pathway analysis identified 17 significant and 2 shared metabolic pathways. These findings provide support for the identification of promising predictive biomarkers and therapeutic targets for dementia. [ABSTRACT FROM AUTHOR]

With the booming of renewable clean energies towards reducing carbon emission, demands for lithium-ion batteries (LIBs) in applications to transportation vehicles and power stations are increasing exponentially. As a consequence, great pressures have been posed on the technological development and production of valuable elements key to LIBs, in addition to concerns about depletion of natural resources, environmental impacts, and management of waste batteries. In this paper, we compile recent information on lithium, nickel, and cobalt, the three most crucial elements utilized in LIBs, in terms of demands, current identified terrestrial resources, extraction technologies from primary natural resources and waste. Most nickel and cobalt are currently produced from high-grade sulfide ores via a pyrometallurgical approach. Increased demands have stimulated production of Ni and Co from low-grade laterites, which is commonly performed through the hydrometallurgical process. Most lithium exists in brines and is extracted via evaporation–precipitation in common industrial practice. It is noteworthy that at present, the pyrometallurgical process is energy-intensive and polluting in terms of gas emissions. Hydrometallurgical processes utilize large amounts of alkaline or acidic media in combination with reducing agents, generating hazardous waste streams. Traditional evaporation–precipitation consumes time, water, and land. Extraction of these elements from deep seas and recycling from waste are emerging as technologies. Advanced energy-saving and environmentally friendly processes are under extensive research and development and are crucial in the process of renewable clean energy implementation. [ABSTRACT FROM AUTHOR]

In the relay intercropping system of maize/sweet potato, the growth of the sweet potatoes is seriously limited by weak light stress in the early stage due to shade from maize plants. However, it is not clear how the weak light affects sweet potatoes and causes tuberous root loss. By setting two light intensity levels (weak light = 30% transmittance of normal light), this study evaluated the responses of two sweet potato cultivars with different tolerances to weak light in a field-based experiment and examined the divergence of gene expression related to light and photosynthesis in a pot-based experiment. The results showed that under weak light, the anatomic structure of functional leaves changed, and the leaf thickness decreased by 39.98% and 17.32% for Yuhongxinshu-4 and Wanshu-7, respectively. The ratio of S/R increased, and root length, root superficial area, and root volume all decreased. The photosynthetic enzyme rubisco was weakened, and the net photosynthetic rate (Pn) declined as well. The level of gene expression in Wanshu-7 was higher than that of Yuhongxinshu-4. The KEGG analysis showed that differentially expressed genes from the two cultivars under weak-light stress used the same enrichment pathway, mainly via glutathione metabolism and flavonoid biosynthesis. After full light levels were restored, the differentially expressed genes were all enriched in pathways such as photosynthesis, photosynthetic pigment synthesis, and carbon metabolism. These findings indicated that weak light changed the plant morphology, photosynthetic physiology and gene expression levels of sweet potatoes, which eventually caused losses in the tuberous root yield. The more light-sensitive cultivar (Wanshu-7) had stronger reactions to weak light. This study provides a theoretical basis and strategy for breeding low-light-tolerant varieties and improving relay intercropping production in sweet potatoes. [ABSTRACT FROM AUTHOR]

A novel five-surface phosphor-in-glass (FS-PiG) structure for high illumination and excellent color uniformity in large-view scale LEDs for sensor light source application is demonstrated. YAG phosphor (Y3Al5O12:Ce3+) was uniformly mixed with ceramic and sintered at 680 °C to form a phosphor wafer. Sophisticated laser engraving was employed on the phosphor wafer to form saddle-shaped large-view scale FS-PiG LEDs. The performance of the FS-PiG LEDs exhibited an illumination of 401 lm, average color temperature (CCT) of 5488 K ± 110 K, and color coordinates (CIE) of (0.3179 ± 0.003, 0.3352 ± 0.003). In contrast to convention single-surface phosphor-in-glass (SS-PiG) LEDs, the performance exhibited an illumination of 380 lm, average CCT of 5830 K ± 758 K, and CIE of (0.3083 ± 0.07, 0.3172 ± 0.07). These indicated that the performance of the FS-PiG LEDs was higher than the SS-PiG LEDs for illumination, CCT, and CIE by 1.7, 7, and 23 times, respectively. Furthermore, the FS-PiG LEDs demonstrate a lower lumen loss of 2% and a reduced chromaticity shift of 5.4 × 10−3 under accelerated aging at 350 °C for 1008 h, owing to the high ceramic melting temperature of up to 510 °C. In this study, the proposed FS-PiG large-view scale LEDs with excellent optical performance and high reliability may be promising candidates to replace the conventional phosphor-in-organic silicone material used in high-power LEDs for the next generation of sensor light sources, display, and headlight applications. [ABSTRACT FROM AUTHOR]

The adhesion of dust particles on the surface of the dust collector tends to cause great resistance to the dust collector and affects the operating efficiency. In order to visualize particles in the filtration process and to grasp the mechanism of particle viscosity and sphericity on filtration performance, a numerical simulation study was conducted to investigate the deposition behavior of particles during filtration, employing FLUENT-EDEM coupling technology. By examining the deposition process, the role of particle characteristics on dust behavior within the entire filtration system was elucidated. The effects of varying particle surface energy and particle sphericity on filtration pressure drop and cake porosity were analyzed. The findings reveal that under the force of the air, particles on the surface of the filter membrane experience compaction, leading to a reduction in the porosity of the formed cake layer. The diminution of porosity serves to impede the air, consequently augmenting the pressure drop across the filtration system and hindering the operational efficacy of the dust collector. As the surface energy of the particles increases, the adhesive forces between particles are intensified, leading to an elevation in the porosity of the cake layer and a subsequent decrease in the pressure drop. When the surface energy of the particles is increased from 0.01 J/m2 to 0.04 J/m2, the porosity experiences a modest increase of only 9.1%, yet the pressure drop is significantly reduced by half, amounting to a decrease of 1594 Pa. Under high particle surface energy, as filtration air velocity increases, particles are compressed, resulting in a decrease in cake porosity and an increase in pressure drop. Concurrently, our findings indicate that as the sphericity of particles increases, their surfaces become increasingly smooth which in turn results in a decreased porosity of the cake layer and, consequently, an elevation in the filtration pressure drop. [ABSTRACT FROM AUTHOR]

Currently, the integration of the Global Navigation Satellite System (GNSS), Ultra-Wideband (UWB), and Inertial Navigation System (INS) has become a reliable positioning method for outdoor dynamic vehicular and airborne applications, enabling high-precision and continuous positioning in complex environments. However, environmental interference and limitations of single positioning sources pose challenges. Especially in areas with limited access to satellites and UWB base stations, loosely coupled frameworks for GNSS/INS and UWB/INS are insufficient to support robust estimation. Furthermore, within a tightly coupled framework, parameter estimations from different sources can interfere with each other, and errors in computation can easily contaminate the entire positioning estimator. To balance robustness and stability in integrated positioning, this paper proposes a comprehensive quality control method. This method is based on the semi-tightly coupled concept, utilizing the INS position information and considering the dilution of precision (DOP) skillfully to achieve complementary advantages in GNSS/UWB/INS integrated positioning. In this research, reliable position and variance information obtained by INS are utilized to provide a priori references for a robust estimation of the original data from GNSS and UWB, achieving finer robustness without increasing system coupling, which fully demonstrates the advantages of semi-tight integration. Based on self-collected data, the effectiveness and superiority of the proposed quality control strategy are validated under severely occluded environments. The experimental results demonstrate that the semi-tightly coupled robust estimation method proposed in this paper is capable of accurately identifying gross errors in GNSS and UWB observation data, and it has a significant effect on improving positioning accuracy and smoothing trajectories. Additionally, based on the judgment of the DOP, this method can ensure the output of continuous and reliable positioning results in complex and variable environments. Verified by actual data, under the conditions of severe sky occlusion and NLOS (Non-Line-of-Sight), compared with the loosely coupled GNSS/INS, the positioning accuracy in the E, N, U directions of the semi-tight coupled GNSS/INS proposed in this paper has improved by 37%, 46%, and 28%. Compared with the loosely coupled UWB/INS, the accuracy in the E and N directions of the semi-tight coupled UWB/INS has improved by 60% and 34%. In such environments, GNSS employs the RTD (Real-Time Differential) algorithm, UWB utilizes the two-dimensional plane-positioning algorithm, and the positioning accuracy of the semi-tight coupled robust model of GNSS/UWB/INS in the E, N, U directions is 0.42 m, 0.55 m, and 3.20 m respectively. [ABSTRACT FROM AUTHOR]

Simple Summary: Seaweed aquaculture plays an important role in global food supply, but single-species intensive seaweed aquaculture has problems related to simple industrial structure and risk susceptibility. Therefore, there is an urgent need to establish a series of large-scale seaweed rotational culture models to address the current industrial challenges in algae culture. The culture of macroalgae is mainly affected by environmental factors such as water temperature and light. In this study, we constructed a rotational culture model by carrying out experiments with three species of macroalgae, observing in situ their photosynthetic activity responses to different temperature and light conditions. The results of this study can provide a theoretical basis for the establishment of large-scale rotational aquaculture, which can effectively improve the ecological and economic value of macroalgae aquaculture. Seaweed farming has made outstanding contributions to food supply and the restoration of the ecological environment despite the limitations in production and ecological effects due to the current intensive farming of single algae species. These limitations can be overcome by selecting suitable algal species based on their physiological characteristics and by constructing a large-scale seaweed rotation model. This study carried out a trial culture in aquaculture sea areas, and performed in situ monitoring of the environmental conditions and physiological characteristics of Saccharina japonica, Hizikia fusiformis, and Gracilariopsis lemaneiformis. Additionally, a comparative analysis of the three macroalgae at different times was conducted to determine their response characteristics to environmental factors. The results showed that: (1) The three macroalgae had varying light tolerance. The effective quantum yield of Hizikia fusiformis and Gracilariopsis lemaneiformis remained unchanged during the changes in light environment, while that of Saccharina japonica first decreased and then recovered. (2) The relative electron transport rates of the three macroalgae were significantly different under different temperature conditions. Hizikia fusiformis and Saccharina japonica exhibited the highest relative electron transport rates (70.45 and 106.75, respectively) in May (20.3 °C). Notably, Gracilariopsis lemaneiformis demonstrated good growth and exhibited the highest relative electron transport rate (93.07) in September (27.5 °C). These findings collectively support the feasibility of establishing a macroalgae rotation model. Based on the combined environmental conditions of the seas in Shandong, Zhejiang, and Fujian, a macroalgae rotation model was proposed. The application of this model in the construction of artificial seaweed farms in marine ranches can provide a stable output of large-scale seaweed production and ecological benefits. [ABSTRACT FROM AUTHOR]

Cadmium (Cd) is recognized as being linked to several liver diseases. Currently, due to the limited spectrum of drugs available for the treatment of Cd intoxication, developing and designing antidotes with superior detoxification capacity and revealing their underlying mechanisms remains a major challenge. Therefore, we developed the first next-generation probiotic E. coli 1917-pSK18a-MT that delivers metallothionein (MT) to overcome Cd-induced liver injury in C57BL/6 mice by utilizing bacterial surface display technology. The results demonstrate that E. coli 1917-pSK18a-MT could efficiently express MT without altering the growth and probiotic properties of the strain. Moreover, we found that E. coli 1917-pSK18a-MT ameliorated Cd contamination-induced hepatic steatosis, inflammatory cell infiltration, and liver fibrosis by decreasing the expression of aminotransferases along with inflammatory factors. Activation of the Nrf2-Keap1 signaling pathway also further illustrated the hepatoprotective effects of the engineered bacteria. Finally, we showed that E. coli 1917-pSK18a-MT improved the colonic barrier function impaired by Cd induction and ameliorated intestinal flora dysbiosis in Cd-poisoned mice by increasing the relative abundance of the Verrucomicrobiota. These data revealed that the combination of E. coli 1917 and MT both alleviated Cd-induced liver injury to a greater extent and restored the integrity of colonic epithelial tissues and bacterial dysbiosis. [ABSTRACT FROM AUTHOR]

A novel and efficient method for functionalizing organosulfones has been established, utilizing a visible-light-driven intermolecular radical cascade cyclization of α-allyl-β-ketosulfones. This process employs fac-Ir(ppy)3 as the photoredox catalyst and α-carbonyl alkyl bromide as the oxidizing agent. Via this approach, the substrates experience intermolecular addition of α-carbonyl alkyl radicals to the alkene bonds, initiating a sequence of C-C bond formations that culminate in the production of organosulfone derivatives. Notably, this technique features gentle reaction conditions and an exceptional compatibility with a wide array of functional groups, making it a versatile and valuable addition to the field of organic synthesis. [ABSTRACT FROM AUTHOR]

Previous studies have shown that boletes are abundant and diverse in China, especially in tropical and subtropical regions. In the present study, morphological, ecological, host relationship, and a four-locus (28S, tef1, rpb1, and rpb2) molecular phylogenetic analyses were used to study the family Boletaceae in subtropical and tropical China. Four new bluing species are described from three genera, viz. Boletellus verruculosus (Chinese name疣柄条孢牛肝菌), Xerocomellus tenuis (Chinese name细柄红绒盖牛肝菌), Xer. brunneus (Chinese name褐盖红绒盖牛肝菌), and Xerocomus zhangii (Chinese name张氏绒盖牛肝菌). Moreover, the genus Nigroboletus is treated as a synonym of Xerocomellus, and a new combination, namely Xer. roseonigrescens (Chinese name玫瑰红绒盖牛肝菌), is proposed. [ABSTRACT FROM AUTHOR]

The implantation of human embryos is a complex process involving various cytokines and receptors expressed by both endometrium and embryos. However, the role of cytokines produced by a single embryo in successful implantation is largely unknown. This study aimed to investigate the role of IL-1β expressed in a single-embryo-conditioned medium (ECM) in embryo implantation. Seventy samples of single ECM were analyzed by a specially designed magnetic-beads-based microfluidic chip from 15 women. We discovered that IL-1β level increased as the embryo developed, and the difference was significant. In addition, receiver operator characteristic (ROC) curves analysis showed a higher chance of pregnancy when the IL-1β level on day 5 ECM was below 79.37 pg/mL and the difference between day 5 and day 3 was below 24.90 pg/mL. Our study discovered a possible association between embryonic proteomic expression and successful implantation, which might facilitate single-embryo transfer in the future by helping clinicians identify the embryo with the greatest implantation potential. [ABSTRACT FROM AUTHOR]

Geological hazards cause changes in the quality of the ecological environment, affect the function and stability of ecosystems, and negatively impact the maintenance and restoration of ecological functions in ecological functional areas (EFAs). This study integrates machine learning, geographic information technology, and multivariate statistical analysis modeling to develop a technical framework for quantitative analysis of ecological risk assessment (ERA) based on the causal logic between geological hazards and ecosystems. The results of the geological disaster ERA are mapped to EFAs, effectively identifying and quantifying the risk characteristics of different EFAs. The results show that: (1) The hazard–vulnerability–exposure ERA framework effectively identifies the distribution characteristics of high ecological risk around the Qilian Mountains, with high risk in the east and low risk in the west. (2) In high ecological risk areas, high hazard–high vulnerability–low exposure is the main combination pattern, accounting for 83.3%. (3) Overall, hazard and vulnerability have a greater impact on geological disaster ecological risk than exposure, with path coefficients of 0.802 (significant at p = 0.01 level) and 0.438 (significant at p = 0.05 level), respectively, in SEM. The random forest model (R2 = 0.748) shows that social factors such as human density and road density contribute significantly more to extreme high risk than other factors, with a contribution rate of up to 44%. (4) Thirty-five ecological functional units were systematically grouped into four clusters and used to formulate a "layered" spatial policy for EFAs. The results of the research are expected to provide support for maximizing the policy impact of EFAs and formulating management decisions that serve ecological protection. [ABSTRACT FROM AUTHOR]

This paper looks into the determinants of national innovation performance from the perspective of policy regime and establishes a theoretical model on how a country's dual Science, Technology, and Innovation (STI) policy regimes, democratic and meritocratic, and national absorptive capacity (NAC) jointly determine its national innovation performance. A democratic STI policy regime promotes innovation through channels of freedom, social equality, and public participation. A meritocratic STI policy regime promotes innovation through channels of good governance and rational policymaking. The model further proposes that the relationships between STI policy regimes and national innovation performance are moderated by potential NAC (PNAC) and realized NAC (RNAC) in opposing directions. The fixed-effects panel regression of OECD countries confirms that both democratic and meritocratic STI policy regimes have positive effects on national innovation performance. Moreover, the democratic effect is positively moderated by PNAC but negatively moderated by RNAC. In contrast, the meritocratic effect is positively moderated by RNAC but negatively moderated by PNAC. The major contribution of this paper is to highlight the importance of a country's STI policy regimes as the bedrock and NAC as the leverage to generate more homegrown innovations. [ABSTRACT FROM AUTHOR]

The new tea cultivar Ziyan has a high content of anthocyanin and ester catechins in the raw material, but the conventional processing and application methods are limited. To explore its application potential, the freeze-drying method was used to prepare microcapsules with an embedding time of 30 min, solid content of 30%, and core to wall ratio of 1:10 (g/g). The anthocyanin recovery was 95.94 ± 0.50%, and the encapsulation efficiency was 96.15 ± 0.11%. The stability of microcapsules and composite wall materials was evaluated in the simulation system. Results showed that microcapsules employing a maltodextrin–gum arabic ratio of 2:8 (w/w) as the wall material significantly reduced degradation rates, extending anthocyanin half-life under various storage conditions. Characterization indicated improved physical properties of Ziyan anthocyanin powder post-microencapsulation. FT-IR and DSC- revealed the formation of a new phase between anthocyanins and wall materials, leading to increased enthalpy and enhanced thermal stability. The microencapsulation results of this experiment proved that the storage stability of anthocyanin was effectively enhanced. [ABSTRACT FROM AUTHOR]

Regional air quality and major sources can be reflected by dust. 87 dust samples in Nanchang (four residential areas and three roadside points) were collected, with particle size and carbon components determined to discuss the distribution characteristics and the sources. The distribution of dust particle size in different sampling areas was similar, composed mainly of particles larger than 10 μm (over 69.8%). Dust particle size showed a decreasing trend with increasing horizontal distance from the main road and vertical height from the ground. EC in road dust was higher than that in residential dust. EC outdoors was higher than EC indoors in the same area. OC in indoor dust was higher than that in atmospheric dust when there were obvious indoor OC emission sources. The main carbon fractions in residential dust were OC3 and EC1, and in road dust were EC2 and OC3. The distribution of carbon fractions showed that OC3 and EC2 were mainly affected by human activities and motor vehicle emissions, respectively. The ratio of OC/EC and SOC in dust decreased from autumn to winter. SOC in the dust of Nanchang was at a medium level compared to other cities/regions around world. Clustering analysis and principal component analysis indicated that combustion sources (coal and biomass combustion, etc.), motor vehicle exhaust sources (gasoline and diesel vehicles), and human sources (cooking fumes, cigarette smoking, etc.) were the main contributors to the carbon components in dust. [ABSTRACT FROM AUTHOR]

Estimating disaster relief supplies is crucial for governments coordinating and executing disaster relief operations. Rapid and accurate estimation of disaster relief supplies can assist the government to optimize the allocation of resources and better organize relief efforts. Traditional approaches for estimating disaster supplies are based on census data and regional risk assessments. However, these methods are often static and lack timely updates, which can result in significant disparities between the availability and demand of relief supplies. Social media, network maps, and other sources of big data contain a large amount of real-time disaster-related information that can promptly reflect the occurrence of a disaster and the relief requirements of the affected residents in a given region. Based on this information, this study presents a model to estimate the demand for disaster relief supplies using social media data. This study employs a deep learning approach to extract real-time disaster information from social media big data and integrates it with a spatial information diffusion model to estimate the population in need of relief in the affected regions. Additionally, this study estimates the demand for emergency materials based on the population in need of relief. These findings indicate that social media data can capture information on the demand for relief materials in disaster-affected regions. Moreover, integrating social media big data with traditional static data can effectively improve the accuracy and timeliness of estimating the demand for disaster relief supplies. [ABSTRACT FROM AUTHOR]

Microbiota is associated with our bodily functions and microenvironment. A healthy, balanced gut microbiome not only helps maintain mucosal integrity, prevents translocation of bacterial content, and contributes to immune status, but also associates with estrogen metabolism. Gut dysbiosis and estrobolome dysfunction have hence been linked to certain estrogen-dependent diseases, including endometriosis. While prior studies on microbiomes and endometriosis have shown conflicting results, most of the observed microbial differences are seen in the genital tract. This case-control study of reproductive-age women utilizes their fecal and urine samples for enzymatic, microbial, and metabolic studies to explore if patients with endometriosis have distinguishable gut microbiota or altered estrogen metabolism. While gut β-glucuronidase activities, microbial diversity, and abundance did not vary significantly between patients with or without endometriosis, fecal samples of patients with endometriosis were more enriched by the Erysipelotrichia class and had higher folds of four estrogen/estrogen metabolites. Further studies are needed to elucidate what these results imply and whether there indeed is an association or causation between gut microbiota and endometriosis. [ABSTRACT FROM AUTHOR]

Emerging evidence indicates a previously unrecognized, clinically relevant spectrum of abnormal aldosterone secretion associated with hypertension severity. It is not known whether excess aldosterone secretion contributes to hypertension during pregnancy. We quantified aldosterone concentrations and angiotensin peptides in serum (using liquid chromatography with tandem mass spectrometry) in a cohort of 128 pregnant women recruited from a high-risk obstetrics clinic and followed prospectively for the development of gestational hypertension, pre-eclampsia, superimposed pre-eclampsia, chronic hypertension, or remaining normotensive. The cohort was grouped by quartile of aldosterone concentration in serum measured in the first trimester, and blood pressure, angiotensin peptides, and hypertension outcomes compared across the four quartiles. Blood pressures and body mass index were greatest in the top and bottom quartiles, with the top quartile having the highest blood pressure throughout pregnancy. Further stratification of the top quartile based on increasing (13 patients) or decreasing (19 patients) renin activity over gestation revealed that the latter group was characterized by the highest prevalence of chronic hypertension, use of anti-hypertensive agents, pre-term birth, and intrauterine growth restriction. Serum aldosterone concentrations greater than 704 pmol/L, the 75th percentile defined within the cohort, were evident across all categories of hypertension in pregnancy, including normotensive. These findings suggest that aldosterone excess may underlie the development of hypertension in pregnancy in a significant subpopulation of individuals. [ABSTRACT FROM AUTHOR]

Over the past few decades, recognition of early lung cancers was researched for effective treatments. In early lung cancers, the invasiveness is an important factor for expected survival rates. Hence, how to effectively identify the invasiveness by computed tomography (CT) images became a hot topic in the field of biomedical science. Although a number of previous works were shown to be effective on this topic, there remain some problems unsettled still. First, it needs a large amount of marked data for a better prediction, but the manual cost is high. Second, the accuracy is always limited in imbalance data. To alleviate these problems, in this paper, we propose an effective CT invasiveness recognizer by semi-automated segmentation. In terms of semi-automated segmentation, it is easy for doctors to mark the nodules. Just based on one clicked pixel, a nodule object in a CT image can be marked by fusing two proposed segmentation methods, including thresholding-based morphology and deep learning-based mask region-based convolutional neural network (Mask-RCNN). For thresholding-based morphology, an initial segmentation is derived by adaptive pixel connections. Then, a mathematical morphology is performed to achieve a better segmentation. For deep learning-based mask-RCNN, the anchor is fixed by the clicked pixel to reduce the computational complexity. To incorporate advantages of both, the segmentation is switched between these two sub-methods. After segmenting the nodules, a boosting ensemble classification model with feature selection is executed to identify the invasiveness by equalized down-sampling. The extensive experimental results on a real dataset reveal that the proposed segmentation method performs better than the traditional segmentation ones, which can reach an average dice improvement of 392.3%. Additionally, the proposed ensemble classification model infers better performances than the compared method, which can reach an area under curve (AUC) improvement of 5.3% and a specificity improvement of 14.3%. Moreover, in comparison with the models with imbalance data, the improvements of AUC and specificity can reach 10.4% and 33.3%, respectively. [ABSTRACT FROM AUTHOR]

Crucial roles in embryo implantation and placentation in humans include the invasion of the maternal decidua by extravillous trophoblasts and the motile behavior of decidual endometrial stromal cells. The effects of the epidermal growth factor (EGF) and GnRH-II in the endometrium take part in early pregnancy. In the present study, we demonstrated the coaction of EGF- and GnRH-II-promoted motility of human decidual endometrial stromal cells, indicating the possible roles of EGF and GnRH-II in embryo implantation and early pregnancy. After obtaining informed consent, we obtained human decidual endometrial stromal cells from decidual tissues from normal pregnancies at 6 to 12 weeks of gestation in healthy women undergoing suction dilation and curettage. Cell motility was evaluated with invasion and migration assays. The mechanisms of EGF and GnRH-II were performed using real-time PCR and immunoblot analysis. The results showed that human decidual tissue and stromal cells expressed the EGF and GnRH-I receptors. GnRH-II-mediated cell motility was enhanced by EGF and was suppressed by the knockdown of the endogenous GnRH-I receptor and EGF receptor with siRNA, revealing that GnRH-II promoted the cell motility of human decidual endometrial stromal cells through the GnRH-I receptor and the activation of Twist and N-cadherin signaling. This new concept regarding the coaction of EGF- and GnRH-promoted cell motility suggests that EGF and GnRH-II potentially affect embryo implantation and the decidual programming of human pregnancy. [ABSTRACT FROM AUTHOR]

Through long-term interactions with the natural environment, the ethnic groups in the mid-Himalayas have formed unique urban environmental characteristics. Effectively identifying urban environmental characteristics is a prerequisite for implementing sustainable urban management strategies. This study took 194 towns in the mid-Himalayan as the research objects. GIS was used to statistically analyze the terrain, climate, soil, and other environmental characteristics of the towns. The SOM (Self-organizing map) method was used to classify the comprehensive environmental characteristics of the towns. The results show that the main urban environmental characteristics in this area are low-altitude towns account for a large proportion, gentle-slope towns account for a small proportion, rainfall is mainly 125–265 mm, vegetation cover is dominated by high-coverage towns, mainly distributed in central and southern parts, the soil is dominated by embryonic soil and alluvial soil. The SOM method overcomes the subjectivity and low degree of automation in traditional research on urban environmental characteristics using threshold indicator methods or feature interpretation methods. Based on environmental characteristics, the towns were divided into six categories, and the classification results showed a distinct north–south zonal distribution pattern. There were significant differences in the environmental characteristics of towns in different clusters, such as the towns in cluster 5 had high altitudes, low rainfall, and low vegetation coverage, while the towns in cluster 2 had low altitudes, high rainfall, and high vegetation coverage. Finally, based on the SOM clustering results, governance strategies were proposed for towns in different clusters to cope with climate and environmental changes and promote sustainable development in the mid-Himalayan. [ABSTRACT FROM AUTHOR]

The thalamus plays a crucial role in ensuring the faithful transfer of sensory information, except olfactory signals, to corresponding cortical areas. However, thalamic function is not simply restricted to relaying information to and from the cerebral cortex. The ability to modulate the flow of sensory information is supported by a second abundant neuronal type in the prethalamus, the inhibitory gamma-aminobutyric acid (GABAergic) neurons, which project inhibitory GABAergic axons to dorsal thalamic glutamatergic neurons. Interestingly, during the trajectory of pioneer prethalamic axons, morphogen fibroblast growth factor (FGF)-3 is expressed in the ventral chick hypothalamus. Using in vitro analyses in chick explants, we identify a chemorepellent effect of FGF3 on nearby prethalamic GABAergic axons. Furthermore, inhibition of FGF3 guidance functions indicates that FGF3 signaling is necessary to navigate prethalamic axons correctly. Gene expression analyses and loss of function studies demonstrate that FGF3 mediates prethalamic axonal guidance through the downstream pathway of the FGF receptor (FGFR)-1. Together, these results suggest that FGF3 expressed in the hypothalamus functions as a chemorepellent molecule to direct the pathway selection of neighboring GABAergic axons. [ABSTRACT FROM AUTHOR]

Subject to intense high-energy particle irradiation, various effects manifest within a material. Specifically, when high-energy particles collide with lattice atoms in a crystal material, a sequence of interactions is set in motion, initiating irradiation effects. Using GaAs solar cells as an example, this study investigates how potential barriers in different directions of atoms in sphalerite structures affect atomic displacement and establishes a probability model for lattice atomic displacement under proton irradiation. By combining Markov chains, changes in displacement threshold energy with different crystal orientations are described, and a damage model for cascading collision relationships that cause irradiation effects is established. Finally, the new model is compared to classical models, and differences in defects caused by proton impacts at several energies on GaAs crystals are simulated. [ABSTRACT FROM AUTHOR]

Cobalt (Co) is proposed to replace copper (Cu) as a conductor in the back-end-of-line (BEOL) interconnects of integrated circuits. In this study, the electric characteristics and reliability of the integration of Co with various dielectric films (SiO2, dense, and porous low-k SiOCH films) under thermal and electrical stress were compared. Thermal annealing repaired sputtering-Co-deposition-induced damage to the dielectric film but reduced the breakdown field and time-dependence-dielectric-breakdown (TDDB) times due to the diffusion of Co atoms. After annealing, the SiO2 film had the largest reductions in the breakdown field, TDDB failure time, and electric field acceleration factor, indicating that the diffusion of Co atoms dominates in the oxygen-rich surface. Under electrical stress, the drift of Co atoms favors the porous low-k film with the assistance of porosity. As a result, a barrier is required for Co metallization. To achieve barrier-free or barrier-less processing in Co metallization, the dense low-k film is the best option to integrate with Co. [ABSTRACT FROM AUTHOR]

As a vital organelle in eukaryotic cells, the Golgi apparatus is responsible for processing and transporting proteins in cells. Precisely monitoring the status of the Golgi apparatus with targeted fluorescence imaging technology is of enormous importance but remains a dramatically challenging task. In this study, we demonstrate the construction of the first Golgi apparatus-targeted near-infrared (NIR) fluorescent nanoprobe, termed Golgi-Pdots. As a starting point of our investigation, hydrophobic carbon nanodots (CNDs) with bright NIR fluorescence at 674 nm (fluorescence quantum yield: 12.18%), a narrow emission band of 23 nm, and excellent stability were easily prepared from Magnolia Denudata flowers using an ultrasonic method. Incorporating the CNDs into a polymer matrix modified with Golgi-targeting molecules allowed for the production of the water-soluble Golgi-Pdots, which showed high colloidal stability and similar optical properties compared with pristine CNDs. Further studies revealed that the Golgi-Pdots showed good biocompatibility and Golgi apparatus-targeting capability. Based on these fascinating merits, utilizing Golgi-Pdots for the long-term tracking of the Golgi apparatus inside live cells was immensely successful. [ABSTRACT FROM AUTHOR]

To address the challenges of weak model generalization and limited model capacity adaptation in traditional malware detection methods, this article presents a novel malware detection approach based on stacked depthwise separable convolutions and self-attention, termed CoAtNet. This method combines the strengths of the self-attention module's robust model adaptation and the convolutional networks' powerful generalization abilities. The initial step involves transforming the malicious code into grayscale images. These images are subsequently processed using a detection model that employs stacked depthwise separable convolutions and an attention mechanism. This model effectively recognizes and classifies the images, automatically extracting essential features from malicious software images. The effectiveness of the method was validated through comparative experiments using both the Malimg dataset and the augmented Blended+ dataset. The approach's performance was evaluated against popular models, including XceptionNet, EfficientNetB0, ResNet50, VGG16, DenseNet169, and InceptionResNetV2. The experimental results highlight that the model surpasses other malware detection models in terms of accuracy and generalization ability. In conclusion, the proposed method addresses the limitations of traditional malware detection approaches by leveraging stacked depthwise separable convolutions and self-attention. Comprehensive experiments demonstrate its superior performance compared to existing models. This research contributes to advancing the field of malware detection and provides a promising solution for enhanced accuracy and robustness. [ABSTRACT FROM AUTHOR]

Hypertension during pregnancy increases the risk of adverse maternal and fetal outcomes, but the mechanisms of pregnancy hypertension are not precisely understood. Elevated plasma renin activity and aldosterone concentrations play an important role in the normal physiologic adaptation to pregnancy. These effectors are reduced in patients with pregnancy hypertension, creating an opportunity to define the features of the renin–angiotensin–aldosterone system (RAAS) that are characteristic of this disorder. In the current study, we used a novel LC-MS/MS-based methodology to develop comprehensive profiles of RAAS peptides and effectors over gestation in a cohort of 74 pregnant women followed prospectively for the development of gestational hypertension and pre-eclampsia (HYP, 27 patients) versus those remaining normotensive (NT, 47 patients). In NT pregnancy, the plasma renin activity surrogate, (PRA-S, calculated from the sum of Angiotensin I + Angiotensin II) and aldosterone concentrations significantly increased from the first to the third trimester, accompanied by a modest increase in the concentrations of angiotensin peptide metabolites. In contrast, in HYP pregnancies, PRA-S and angiotensin peptides were largely unchanged over gestation, and third-trimester aldosterone concentrations were significantly lower compared with those in NT pregnancies. The results indicated that the predominant features of pregnancies that develop HYP are stalled or waning activation of the RAAS in the second half of pregnancy (accompanied by unchanging levels of angiotensin peptides) and the attenuated secretion of aldosterone. [ABSTRACT FROM AUTHOR]

Objectives: Based on readily available demographic data, neuropsychological assessment results, and comorbidity data, we aimed to develop and validate a 3-year survival prediction model for patients with cognitive impairment. Methods: In this prospective cohort study, 616 patients with cognitive impairment were included. Demographic information, data on comorbidities, and scores of the Mini-Mental State Examination (MMSE), Instrumental Activities of Daily Living (IADL) scale, and Neuropsychiatric Inventory Questionnaire were collected. Survival status was determined via telephone interviews and further verified in the official death register in the third year. A 7:3 ratio was used to divide patients into the training and validation sets. Variables with statistical significance (p < 0.05) in the single-factor analysis were incorporated into the binary logistic regression model. A nomogram was constructed according to multivariate analysis and validated. Results: The final cohort included 587 patients, of whom 525 (89.44%) survived and 62 (10.56%) died. Younger age, higher MMSE score, lower IADL score, absence of disinhibition, and Charlson comorbidity index score ≤ 1 were all associated with 3-year survival. These predictors yielded good discrimination with C-indices of 0.80 (0.73–0.87) and 0.85 (0.77–0.94) in the training and validation cohorts, respectively. According to the Hosmer–Lemeshow test results, neither cohort displayed any statistical significance, and calibration curves displayed a good match between predictions and results. Conclusions: Our study provided further insight into the factors contributing to the survival of patients with cognitive impairment. Clinical Implications: Our model showed good accuracy and discrimination ability, and it can be used at community hospitals or primary care facilities that lack sophisticated equipment. [ABSTRACT FROM AUTHOR]

It is noted that some uncertain variables are independent while others are not. In general, there is a symmetrical relationship between independence and dependence among uncertain variables. The utilization of conditional uncertain measures as well as conditional uncertainty distributions proves highly efficacious in resolving uncertainties pertaining to an event subsequent to the acquisition of knowledge about other events. In this paper, the theorem about the conditional uncertainty distribution of two uncertain variables is proposed. It is demonstrated that the theorem holds regardless of whether the two variables are independent or not. In addition, it is also found that uncertainty distribution possesses an inherent inverse function when it is a regular uncertainty distribution within the framework of Uncertainty Theory; therefore, this paper delves into investigating the conditional inverse uncertainty distribution, including specific cases of the conditional inverse uncertainty distributions. Meanwhile, illustrative examples are applied to clarify the findings. [ABSTRACT FROM AUTHOR]

Small data sets make developing calibration models using deep neural networks difficult because it is easy to overfit the system. We developed two deep neural network architectures by revising two existing network architectures: the U-Net and the attention mechanism. The major changes were to use 1D convolutional layers to replace the fully connected layers. We also designed and combined average pooling and maximum pooling in our revised networks, respectively. We applied these revised network architectures to three publicly available data sets and the resulting calibration models can generate acceptable results for general quantitative analysis. It also generated rather good results for data sets that concern calibration transfer. It demonstrates that constructing network architectures by properly revising existing successful network architectures may provide additional choices in the exploration of the application of deep neural network in analytical chemistry. [ABSTRACT FROM AUTHOR]

PM2.5 was sampled in four seasons of 2021 in Nanchang. Organic carbon (OC), elemental carbon (EC), and water-soluble ions were the main chemical compositions in PM2.5. The annual average of OC/PM2.5 and EC/PM2.5 was 17.1% and 2.1%, respectively, while nine water-soluble ions were 56.7%. The order of each ion percentage in PM2.5 was NO3− > SO42− > K+ > Na+ > NH4+ > Cl− > NO2− > Ca2+ > Mg2+. The OC/EC (6.54, 13.17, 8.95, 7.99) and Char-EC/Soot-EC (0.88, 0.64, 1.32, 3.74) indicated that the carbon aerosols mainly originated from coal combustion, biomass combustion, and motor-vehicle emissions. High concentrations of Cl− and Ca2+ in spring were associated with dust sources. A good correlation between Na+, SO42−, and NO3− suggests the formation of Na2SO4 and NaNO3. The results of PM2.5 source apportionment by positive matrix factorisation (PMF) showed five main sources: motor-vehicle sources (18–33%), secondary sources (16–36%), coal combustion sources (16–30%), biomass-combustion sources (10–28%), and dust sources (5–7%). Backward trajectory clustering analysis showed PM2.5 in spring and autumn were more influenced by medium distance and local air but mainly influenced by local sources in winter. [ABSTRACT FROM AUTHOR]

In order to improve laser transmission efficiency at 1053 nm and 527 nm, a potassium deuterium phosphate (DKDP) crystal (a key component of high-power laser systems) needs a bi-layer antireflection coating system on its incident surface. UV-curable polysiloxane coatings with a refractive index varying from 1.500 to 1.485 were prepared through the polycondensation of a methacryloxy propyl trimethoxylsilane (MPS) monomer with a controllable degree of hydrolysis. Additionally, the influence rule of the coating structure on the refractive index was intensively studied, and the primary factors that dominate the hydrolysis process were discussed. Further refractive index adjustment was achieved using only a small amount of dopant based on the polysiloxane coating with refractive index of 1.485, allowing for high antireflection of the bi-layer coating system at desired wavelengths to be achieved. In addition, high laser damage resistance and remarkable mechanical properties of the coating were simultaneously realized through the incorporation of a minor quantity of dopants, which benefited from the successful modulation of the intrinsic refractive index of the polysiloxane coating. [ABSTRACT FROM AUTHOR]

TiAl alloys have excellent high-temperature performance and are potentially used in the aerospace industry. By controlling the lamellar orientation through directional solidification (DS) technology, the plasticity and strength of TiAl alloy at room temperature and high temperatures can be effectively improved. However, various difficulties lie in ensuring the lamellar orientation is parallel to the growth direction. This paper reviews two fundamental thoughts for lamellar orientation control: using seed crystals and controlling the solidification path. Multiple specific methods and their progress are introduced, including α seed crystal method, the self-seeding method, the double DS self-seeding method, the quasi-seeding method, the pure metal seeding method, and controlling solidification parameters. The advantages and disadvantages of different methods are analyzed. This paper also introduces novel ways of controlling the lamellar orientation and discusses future development. [ABSTRACT FROM AUTHOR]

Although the existing literature on innovation has little focus on information transparency, we aimed to determine how information transparency affects the legitimacy of green innovation in China. Accounting data, analyst data, and external audit data are used to evaluate a company's information transparency. This paper examines the impact of corporate transparency on the legitimacy of green innovation in the context of three external information sources to which stakeholders have access, utilizing data from 4017 Chinese companies listed between 2005 and 2020. Our estimation results indicate a significant positive correlation between informational accessibility and green innovation legitimacy. The results demonstrate a stronger relationship between corporate green innovation legitimacy and greater earning quality, more analyst monitoring, more accurate analyst surplus estimations, and international audits by the Big Four. This study seeks to present new empirical findings for Chinese listed companies in order to strengthen the legality of green innovation and validate the significance of corporate information transparency via a robustness test. [ABSTRACT FROM AUTHOR]

The re-deposition of detached dust during online pulse-jet cleaning is an important issue encountered during filter regeneration. To reduce dust re-deposition, multi-pulsing jet cleaning schemes were designed and experimentally tested. A pilot-scale pulse-jet cleaning dust collector was built with one vertically installed pleated filter cartridge. The effects of pulse duration and interval on the pulse pressure were tested, and the dust re-deposition rate and mechanism were studied and analyzed. It was found that, for the single-pulsing jet, the pulse duration had a critical value of approximately 0.080 s in this test, above which the pulse pressure remained at approximately 0.75 kPa and did not increase further. For the multi-pulsing jet with a small pulse interval (less than approximately 0.10 s), the pulse flows superimposed and reached a higher pulse pressure with a slight inhibition of dust re-deposition. For the multi-pulsing jet with a long pulse interval (over 0.15 s), dust re-deposition was clearly inhibited. The re-deposition rate decreased from 63.8% in the single-pulsing scheme to 24.4% in the multi (five)-pulsing scheme with the same total pulse duration of 0.400 s. The multi-pulsing scheme lengthens the duration of reverse pulse flow, resulting in more elapsed time for the detached dust to freely fall, and inhibiting the re-deposition of dust. The elapsed time in the five-pulsing jet scheme with the recommended pulse duration of 0.080 s and interval of 0.25 s was 2.8 times higher than that of the single-pulsing jet with the same total pulse duration. [ABSTRACT FROM AUTHOR]

The main challenge of scene classification is to understand the semantic context information of high-resolution remote sensing images. Although vision transformer (ViT)-based methods have been explored to boost the long-range dependencies of high-resolution remote sensing images, the connectivity between neighboring windows is still limited. Meanwhile, ViT-based methods commonly contain a large number of parameters, resulting in a huge computational consumption. In this paper, a novel lightweight dual-branch swin transformer (LDBST) method for remote sensing scene classification is proposed, and the discriminative ability of scene features is increased through combining a ViT branch and convolutional neural network (CNN) branch. First, based on the hierarchical swin transformer model, LDBST divides the input features of each stage into two parts, which are then separately fed into the two branches. For the ViT branch, a dual multilayer perceptron structure with a depthwise convolutional layer, termed Conv-MLP, is integrated into the branch to boost the connections with neighboring windows. Then, a simple-structured CNN branch with maximum pooling preserves the strong features of the scene feature map. Specifically, the CNN branch lightens the LDBST, by avoiding complex multi-head attention and multilayer perceptron computations. To obtain better feature representation, LDBST was pretrained on the large-scale remote scene classification images of the MLRSN and RSD46-WHU datasets. These two pretrained weights were fine-tuned on target scene classification datasets. The experimental results showed that the proposed LDBST method was more effective than some other advanced remote sensing scene classification methods. [ABSTRACT FROM AUTHOR]

Endometriosis is a chronic inflammatory disease associated with bothersome symptoms in premenopausal women and is complicated with long-term systemic impacts in the post-menopausal stage. It is generally defined by the presence of endometrial-like tissue outside the uterine cavity, which causes menstrual disorders, chronic pelvic pain, and infertility. Endometriotic lesions can also spread and grow in extra-pelvic sites; the chronic inflammatory status can cause systemic effects, including metabolic disorder, immune dysregulation, and cardiovascular diseases. The uncertain etiologies of endometriosis and their diverse presentations limit the treatment efficacy. High recurrence risk and intolerable side effects result in poor compliance. Current studies for endometriosis have paid attention to the advances in hormonal, neurological, and immunological approaches to the pathophysiology and their potential pharmacological intervention. Here we provide an overview of the lifelong impacts of endometriosis and summarize the updated consensus on therapeutic strategies. [ABSTRACT FROM AUTHOR]

As wastewater treatment usually involves complicated biochemical reactions, leading to strong coupling correlation and nonlinearity in water quality parameters, it is difficult to analyze and optimize the control of the wastewater treatment plant (WWTP) with traditional mathematical models. This research focuses on how deep learning techniques can be used to model the data from a specific WWTP so as to optimize the required energy consumption. In the operation of a wastewater treatment plant, various sensors are used to record the treatment process data; these data are used to train deep neural networks (DNNs). A long short-term memory with multilayer perceptron network (LMPNet) model is proposed to model the water quality parameters and site control parameters, such as COD, pH, NH3-N, et al., and the LMPNet model prediction error is then measured by criteria such as the MSE, MAE, and R2. The experimental results show that the LMPNet model demonstrates great accuracy in the modeling of the control of WWTPs. A life-long learning strategy is also developed for the LMPNet in order to adapt to the environment that may change over time. By developing performance evaluation metrics, the purification performance can be analyzed, and the prediction reference can be provided for the subsequent control optimization and energy saving plan. [ABSTRACT FROM AUTHOR]

Low-frequency debris flows are characterized by strong concealment, high potential danger, and difficulty achieving an early warning; hence early identification of low-frequency debris flow gullies is crucial to mitigation. Here, an identification system for low-frequency debris flow gullies along the traffic arteries in the Chuanxi Plateau is proposed based on the identification and stability calculation of colluvium deposits in a hollow region (CDH) and the quantitative roundness analysis for the stones in a deposit fan. At first, for the watershed without a deposit fan, the CDH is identified and analyzed using the geomorphologic change point detection method combined with high-precision remote sensing images and field investigation. The watershed can be identified as a low-frequency debris flow gully with the safety factors (Fs) of all CDHs greater than 1. Then, the roundness of stones in the deposit fan is quantitatively analyzed. The watershed can also be identified as a low-frequency debris flow gully with the average roundness of the stones ranging from 0.30 to 0.41. Lastly, the identification system was tested and verified based on another ten watersheds along three traffic arteries. It shows that the method proposed in this paper has good applicability and high accuracy. Here we try to achieve the accurate early identification of low-frequency debris flow gullies by combining remote sensing interpretation and field investigation, which can provide theoretical support for predicting and mitigating debris flows in mountainous areas. [ABSTRACT FROM AUTHOR]

Immune checkpoint inhibitors (ICIs) represent a new hot spot in tumor therapy. Programmed cell death has an important role in the prognosis. We explore a programmed cell death gene prognostic model associated with survival and immunotherapy prediction via computational algorithms. Patient details were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus databases. We used LASSO algorithm and multiple-cox regression to establish a programmed cell death-associated gene prognostic model. Further, we explored whether this model could evaluate the sensitivity of patients to anti-PD-1/PD-L1. In total, 1342 patients were included. We constructed a programmed cell death model in TCGA cohorts, and the overall survival (OS) was significantly different between the high- and low-risk score groups (HR 2.70; 95% CI 1.94–3.75; p < 0.0001; 3-year OS AUC 0.71). Specifically, this model was associated with immunotherapy progression-free survival benefit in the validation cohort (HR 2.42; 95% CI 1.59–3.68; p = 0.015; 12-month AUC 0.87). We suggest that the programmed cell death model could provide guidance for immunotherapy in LUAD patients. [ABSTRACT FROM AUTHOR]

Nearly zero-energy-consumption buildings are the inevitable trend of future buildings. There have been a large number of studies on nearly zero building technology issues. However, there is no detailed study on how to effectively promote the development of nearly zero-energy consumption buildings according to China's national conditions. Here, by establishing an evolutionary game model, this paper discusses the dynamic game scheme selection and stability strategy of three stakeholders, namely local government, real estate companies, and construction consumers, related to the development of nearly zero-energy-consumption buildings in the development process. The conditions required for evolutionary stabilization strategies were identified. Finally, Matlab data simulation analysis is used to further illustrate the stability and equilibrium strategies of each subject and the sensitivity analysis of the main influencing factors at various stages in the development process of nearly zero-energy-consuming buildings. The research results show that the government plays a leading role in the early stage of the development of nearly zero-energy consumption buildings, and as the market matures, government intervention gradually withdraws from the market; furthermore, if the cost of supervision is prohibitively high, the government's willingness to supervise the market will be reduced. This will hinder consumers and developers from choosing nearly zero-energy-consuming buildings and if the penalties and subsidies are too low, it will be meaningless to the evolution of the optimal solution of the three parties. On this basis, targeted promotion programs are established to realize the rapid development of China's nearly zero-energy-consumption building sector. Our research results can provide important scientific basis for the development of the nearly zero-energy building industry in China. [ABSTRACT FROM AUTHOR]

A typhoon or hurricane is one of the most destructive high-impact weather events. In this study, the genesis and development processes of Typhoon Nangka (2015), which occurred over the Western Pacific in 2015, were investigated based on the comprehensive observation data from three satellites, i.e., the Himawari-8 satellite, the CloudSat satellite and the Global Precipitation Measurement mission satellite (GPM), focusing on the characteristics of typhoon structure, precipitation and cloud. The results (Results) show that during the developing stage of Typhoon Nangka, the cloud system was relatively complex and changed significantly, with large raindrops dominating the precipitation around the eyewall in the first quadrant, and the convection in the eyewall and outer rainband burst upward to 17 km. In addition, three features were obvious: stratiform precipitation was dominant in the inner rainband, both the precipitation type (stratiform or convective) and intensity were distributed unevenly in the outer rainband, and large water content was located in the warm layer of clouds. Moreover, the collision growth and breakup of water droplets tended to be stable. The precipitation in the typhoon eyewall, inner rainband and outer rainband was significantly different; stratiform precipitation mainly occurred in the inner rainband, while convective precipitation mainly appeared in the eyewall and outer rainband. The cloud system was distributed asymmetrically, and the upper-layer and lower-layer clouds were closely related, dominated by single-layer clouds. There were deep convective clouds in the eyewall, and cirrus clouds with the broadest range across the eyewall. The coverage range of cirrus clouds was close to the radius of the typhoon. There were stratocumulus, altostratus and cumulus in the low levels. [ABSTRACT FROM AUTHOR]

Sweet potato virus disease (SPVD) is one of the main virus diseases in sweet potato [Ipomoea batatas (L.) Lam] that seriously affects the yield of sweet potato. Therefore, the establishment of a simple, rapid and effective method to detect SPVD is of great significance for the early warning and prevention of this disease. In this study, the experiment was carried out in two years to compare the grafting method and side grafting method for three sweet potato varieties, and the optimal grafting method was selected. After grafting with seedlings infected with SPVD, the symptomatic diagnosis and serological detection were performed in 86 host varieties, and the differences in SPVD resistance were determined by fluorescence quantitative PCR (qRT-PCR) and nitrocellulose membrane enzyme-linked immunosorbent assay (NCM-ELISA). The results showed that the survival rate of grafting by insertion method was significantly higher than that by side grafting method, and the disease resistance of different varieties to sweet potato virus disease was tested. The detection method established in this study can provide theoretical basis for identification and screening of resistant sweet potato varieties. [ABSTRACT FROM AUTHOR]