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In this study, h-BN-modified Mo 2 FeB 2 /WC composite coatings were fabricated via laser cladding. The Mo 2 FeB 2 /WC/10 wt% h-BN composite coatings were heat-treated at 400, 600, and 800 °C. The microstructure, microhardness, tribological properties, residual stress, fracture toughness and fracture morphology of the coatings were investigated. The results showed that h-BN addition combined with heat treatment promoted the distribution of elements and finer microstructure. The Mo 2 FeB 2 /WC/10 wt% h-BN coating heat-treated at 600 °C showed the highest microhardness (1416.8 HV 0.5) among the prepared coatings. The pristine and 600 °C heat-treated Mo 2 FeB 2 /WC/10 wt% h-BN coating showed excellent wear rates (1.97 and 1.84 × 10−5 mm3/Nm, respectively). The composite coatings modified with h-BN exhibited an abrasive wear mechanism after heat treatment. As the h-BN content and heat treatment temperature increased, there was a notable decrease in residual stress. Specifically, the coating subjected to heat treatment at 800 °C demonstrated the lowest residual tensile stress recorded at 168 MPa. Conversely, when heat-treated at 600 °C, the coating exhibited an optimal fracture toughness of 14.96 MPa⋅m1/2, with fracture behavior consistent with typical brittle fracture characteristics. [ABSTRACT FROM AUTHOR]

In the approach of metric-based geometric parameterization, the concept of database filtration and proper orthogonal decomposition manipulation quantitatively enhances the generation of new geometric parameters so that the problem-oriented information is reflected in aerodynamic design. Compared with the conventional approach that applies only geometric filtration, this paper incorporates performance filtration so that the problem-oriented information is no longer limited to geometric constraints, thereby enabling the guidance of optimization direction in a more informed manner. This paper focuses on the pressure distribution of samples and their relationship with geometric variations. A variational autoencoder is employed to extract the dominant features of the aerodynamic potentials that an initial geometry can attain in optimization. The authors believe that the aerodynamic potential is reflected in how the pressure distribution differs from that of the initial geometry. Then, samples have to meet the performance filtration criterion based on pressure distribution proposed by designers according to their aerodynamic understanding of the optimization problem. Finally, the remaining collection of qualified samples generates new geometric parameters via proper orthogonal decomposition. The conventional and new approaches were validated in a two-dimensional airfoil case of drag coefficient optimization; the lift-to-drag ratio improved by 17.07% using the traditional method, and by 38.20% using the new approach. The pressure distribution shows that the performance filtration approach produces more supercritical properties than the geometric filtration approach. This implies that the performance filtration approach can capture more intricate details related to the aerodynamic performance of the airfoil. [ABSTRACT FROM AUTHOR]

Idiopathic pulmonary fibrosis (IPF) is a chronic disease of unknown etiology that lacks a specific treatment. In IPF, macrophages play a key regulatory role as a major component of the lung immune system, especially during inflammation and fibrosis. However, our understanding of the cellular heterogeneity and molecular characterization of macrophages in IPF, as well as their relevance in the clinical setting, is relatively limited. In this study, we analyzed in-depth single-cell transcriptome sequencing (scRNA-seq) data from lung tissues of IPF patients, identified macrophage subpopulations in IPF, and probed their molecular characteristics and biological functions. hdWGCNA identified co-expressed gene modules of a subpopulation of IPF-associated macrophages (IPF-MΦ), and probed the IPF-MΦ by a machine-learning approach. hdWGCNA identified a subpopulation of IPF-associated macrophage subpopulations and probed the IPF-MΦ signature gene (IRMG) for its prognostic value, and a prediction model was developed on this basis. In addition, IPF-MΦ was obtained after recluster analysis of macrophages in IPF lung tissues. Coexpressed gene modules of IPF-MΦ were identified by hdWGCNA. Then, a machine learning approach was utilized to reveal the characteristic genes of IPF-MΦ, and a prediction model was built on this basis. In addition, we discovered a type of macrophage unique to IPF lung tissue named ATP5-MΦ. Its characteristic gene encodes a subunit of the mitochondrial ATP synthase complex, which is closely related to oxidative phosphorylation and proton transmembrane transport, suggesting that ATP5-MΦ may have higher ATP synthesis capacity in IPF lung tissue. This study provides new insights into the pathogenesis of IPF and provides a basis for evaluating disease prognosis and predictive medicine in IPF patients. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to conduct a bibliometric analysis of research articles on the relationship between inflammatory bowel disease (IBD) and colorectal cancer (CRC) using CiteSpace to summarize the current research status, hotspots, and trends in this field and present the results visually. Method: Research articles on the relationship between IBD and CRC published from 2000 to 2023 and in English were selected from the Web of Science Core Collection (Woscc) database. The articles were downloaded as "full record and references". CiteSpace was used to conduct cooperative, cluster, co-citation, and burst analyses. Results: The literature search revealed 4244 articles; of which, 5 duplicates were removed, resulting in the inclusion of 4239 articles in this study. The United States of America had the highest number of publications, with Mayo Clinic and Harvard University being the most active institutions, and Bas Oldenburg being the most active author. Collaboration among core authors was inadequate. JA Eaden was the most cited author, and CRC was the most common keyword. Burst analysis indicated that Sun Yat-sen University might be one of the institutions with a large contribution to this research field in the future. Cluster analysis showed that earlier research focused more on microsatellite instability, whereas "gut microbiota" and "oxidative stress" are considered current research hotspots and trends. Conclusion: At present, the primary focus areas of research are "gut microbiota" and "oxidative stress". With the improvement of healthcare policies and standards, regular endoscopic monitoring of patients with IBD has become an indispensable diagnostic and therapeutic practice. More drugs will be developed to reduce the risk of progression from IBD to CRC. The findings of this study provide valuable insights into the relationship between IBD and CRC for researchers in the same field. [ABSTRACT FROM AUTHOR]

Lymphocyte subsets are the most intuitive expression of the body's immune ability, and the lymphocyte-to-monocyte ratio (LMR) also clearly reflect the degree of chronic inflammation activity. The purpose of this study is to investigate their predictive value of lymphocyte subsets and LMR to neoadjuvant therapy (NAT) efficacy in breast cancer patients. In this study, lymphocyte subsets and LMR were compared between breast cancer patients (n = 70) and benign breast tumor female populations (n = 48). Breast cancer patients were treated with NAT, and the chemotherapy response of the breast was evaluated using established criteria. The differences in lymphocyte subsets and LMR were also compared between pathological complete response (pCR) and non-pCR patients before and after NAT. Finally, data were analyzed using SPSS. The analytical results demonstrated that breast cancer patients showed significantly lower levels of CD3 + T cells, CD4 + T cells, CD4 + /CD8 + ratio, NK cells, and LMR compared to benign breast tumor women (P < 0.05). Among breast cancer patients, those who achieved pCR had higher levels of CD4 + T cells, NK cells, and LMR before NAT (P < 0.05). NAT increased CD4 + /CD8 + ratio and decreased CD8 + T cells in pCR patients (P < 0.05). Additionally, both pCR and non-pCR patients exhibited an increase in CD3 + T cells and CD4 + T cells after treatment, but the increase was significantly higher in pCR patients (P < 0.05). Conversely, both pCR and non-pCR patients experienced a decrease in LMR after treatment. However, this decrease was significantly lower in pCR patients (P < 0.05). These indicators demonstrated their predictive value for therapeutic efficacy. In conclusion, breast cancer patients experience tumor-related immunosuppression and high chronic inflammation response. But this phenomenon can be reversed to varying degrees by NAT. It has been found that lymphocyte subsets and LMR have good predictive value for pCR. Therefore, these markers can be utilized to identify individuals who are insensitive to NAT early on, enabling the adjustment of treatment plans and achieving precise breast cancer treatment. [ABSTRACT FROM AUTHOR]

In the realm of video salient object detection (VSOD), the majority of research has traditionally been centered on third‐person perspective videos. However, this focus overlooks the unique requirements of certain first‐person tasks, such as autonomous driving or robot vision. To bridge this gap, a novel dataset and a camera‐based VSOD model, CaMSD, specifically designed for egocentric videos, is introduced. First, the SalEgo dataset, comprising 17,400 fully annotated frames for video salient object detection, is presented. Second, a computational model that incorporates a camera movement module is proposed, designed to emulate the patterns observed when humans view videos. Additionally, to achieve precise segmentation of a single salient object during switches between salient objects, as opposed to simultaneously segmenting two objects, a saliency enhancement module based on the Squeeze and Excitation Block is incorporated. Experimental results show that the approach outperforms other state‐of‐the‐art methods in egocentric video salient object detection tasks. Dataset and codes can be found at https://github.com/hzhang1999/SalEgo. [ABSTRACT FROM AUTHOR]

Hepatocellular carcinoma (HCC) results in the abnormal regulation of cellular metabolic pathways. Constraint-based modeling approaches can be utilized to dissect metabolic reprogramming, enabling the identification of biomarkers and anticancer targets for diagnosis and treatment. In this study, two genome-scale metabolic models (GSMMs) were reconstructed by employing RNA sequencing expression patterns of hepatocellular carcinoma (HCC) and their healthy counterparts. An anticancer target discovery (ACTD) framework was integrated with the two models to identify HCC targets for anticancer treatment. The ACTD framework encompassed four fuzzy objectives to assess both the suppression of cancer cell growth and the minimization of side effects during treatment. The composition of a nutrient may significantly affect target identification. Within the ACTD framework, ten distinct nutrient media were utilized to assess nutrient uptake for identifying potential anticancer enzymes. The findings revealed the successful identification of target enzymes within the cholesterol biosynthetic pathway using a cholesterol-free cell culture medium. Conversely, target enzymes in the cholesterol biosynthetic pathway were not identified when the nutrient uptake included a cholesterol component. Moreover, the enzymes PGS1 and CRL1 were detected in all ten nutrient media. Additionally, the ACTD framework comprises dual-group representations of target combinations, pairing a single-target enzyme with an additional nutrient uptake reaction. Additionally, the enzymes PGS1 and CRL1 were identified across the ten-nutrient media. Furthermore, the ACTD framework encompasses two-group representations of target combinations involving the pairing of a single-target enzyme with an additional nutrient uptake reaction. Computational analysis unveiled that cell viability for all dual-target combinations exceeded that of their respective single-target enzymes. Consequently, integrating a target enzyme while adjusting an additional exchange reaction could efficiently mitigate cell proliferation rates and ATP production in the treated cancer cells. Nevertheless, most dual-target combinations led to lower side effects in contrast to their single-target counterparts. Additionally, differential expression of metabolites between cancer cells and their healthy counterparts were assessed via parsimonious flux variability analysis employing the GSMMs to pinpoint potential biomarkers. The variabilities of the fluxes and metabolite flow rates in cancer and healthy cells were classified into seven categories. Accordingly, two secretions and thirteen uptakes (including eight essential amino acids and two conditionally essential amino acids) were identified as potential biomarkers. The findings of this study indicated that cancer cells exhibit a higher uptake of amino acids compared with their healthy counterparts. [ABSTRACT FROM AUTHOR]

Simple Summary: In poultry production, fasting can remodel ovarian function and thereby delay the aging process of chickens. However, this approach may induce various stresses on the intestinal health of chickens. So, intestinal injury, the microbiome, and the metabolome were analyzed individually and integrated to elucidate the impact of the intestinal flora on intestinal injury during fasting-induced molting (FIM). The findings revealed that fasting led to intestinal villus atrophy, inflammation in the intestines, and disruption of gut microbiota and metabolites. During the fasting period, intestinal injury is associated with an increased abundance of Escherichia_Shigella and related metabolites Citrulline and Sterobilin, as well as a decreased abundance of Ruminococcaceae_UCG-013 and Lactobacillus and related metabolites Lanthionine and reduced Glutathione. This provides an experimental basis for improving the gut microbiota and reducing intestinal inflammation during the FIM process. Fasting-induced molting (FIM) is a common method used to improve the laying performance of aged laying hens. Nevertheless, this approach may impose various stresses on chickens, such as disruptions in intestinal flora and inflammation issues within the intestines. However, the impact of an imbalance in intestinal flora on intestinal health during the FIM process remains elusive. Therefore, intestinal injury, the microbiome, and the metabolome were analyzed individually and integrated to elucidate the impact of the intestinal flora on intestinal health during the FIM process. The findings indicated that fasting resulted in a notable reduction in villus height and villus/crypt ratio, coupled with elevated levels of intestinal inflammation and permeability. During the fasting period, microbiota compositions changed. The abundance of Escherichia_Shigella increased, while the abundance of Ruminococcaceae_UCG-013 and Lactobacillus decreased. Escherichia_Shigella was positively correlated with Citrinin and Sterobilin, which lead to intestinal inflammation. Ruminococcaceae_UCG-013 and Lactobacillus exhibited positive correlations with Lanthionine and reduced Glutathione, thereby reducing intestinal inflammation. This study screened the intestinal probiotics, Ruminococcaceae UCG-013 and Lactobacillus, that influence gut health during the fasting period, providing an experimental basis for improving gut microbiota and reducing intestinal inflammation during the FIM process. [ABSTRACT FROM AUTHOR]

Double traditional metal (TM) Janus MXenes have more superior properties when compared with MXenes. The electronic and optical properties, Bader charge and quantum capacitance of ZrMCO 2 (M = Sc, Ti, V, Cr, Mn, Fe, Y, Zr, Nb, Mo, Hf, Ta, W) are explored by density functional theory (DFT). The stability of these systems is confirmed by cohesive energy. The substitution of Ti/Hf atoms results in the decrease of bandgap of ZrTiCO 2 /ZrHfCO 2 , which is induced by the redshift of conduction band minimum (CBM). ZrMCO 2 (M = Cr, Mn) are magnetic semiconductors and ZrMCO 2 (M = Sc, V, Y, Fe) are magnetic metals. All doping atoms except Hf improve the maximum quantum capacitance of ZrMCO 2 at positive bias. Wide voltage makes ZrMCO 2 (M = Nb, Ta, W) change into anode material and ZrFeCO 2 into cathode material. ZrMCO 2 (M = Sc, Mn, Y, Hf, Zr) and ZrMCO 2 (M = V, Cr) can serve as cathode and anode materials in whole voltage, respectively. Much charge accumulating between Fe and C atoms results in the smallest Fe–C bond among all M − C bonds, which indicates the strongest interaction between Fe and C atoms. Optical properties and work function are further explored. [ABSTRACT FROM AUTHOR]

The massive grid integration of renewable energy necessitates frequent and rapid response of hydropower output, which has brought enormous challenges to the hydropower operation and new opportunities for hydropower development. To investigate feasible solutions for complementary systems to cope with the energy transition in the context of the constantly changing role of the hydropower plant and the rapid evolution of wind and solar power, the short-term coordinated scheduling model is developed for the wind–solar–hydro hybrid pumped storage (WSHPS) system with peak shaving operation. The effects of different reservoir inflow conditions, different wind and solar power forecast output, and installed capacity of pumping station on the performance of WSHPS system are analyzed. The results show that compared with the wind–solar–hydro hybrid (WSH) system, the total power generation of the WSHPS system in the dry, normal, and wet year increased by 10.69%, 11.40%, and 11.27% respectively. The solar curtailment decreased by 68.97%, 61.61%, and 48.43%, respectively, and the wind curtailment decreased by 76.14%, 58.48%, and 50.91%, respectively. The high proportion of wind and solar energy connected to the grid in summer leads to large net load fluctuations and serious energy curtailment. The increase in the installed capacity of the pumping station will promote the consumption of wind and solar energy in the WSHPS system. The model proposed in this paper can improve the operational flexibility of hydropower station and promote the consumption of wind and solar energy, which provides a reference for the research of cascade hydropower energy storage system. [ABSTRACT FROM AUTHOR]

Background: Molecular biology is crucial for drug discovery, protein design, and human health. Due to the vastness of the drug-like chemical space, depending on biomedical experts to manually design molecules is exceedingly expensive. Utilizing generative methods with deep learning technology offers an effective approach to streamline the search space for molecular design and save costs. This paper introduces a novel E(3)-equivariant score-based diffusion framework for 3D molecular generation via SDEs, aiming to address the constraints of unified Gaussian diffusion methods. Within the proposed framework EMDS, the complete diffusion is decomposed into separate diffusion processes for distinct components of the molecular feature space, while the modeling processes also capture the complex dependency among these components. Moreover, angle and torsion angle information is integrated into the networks to enhance the modeling of atom coordinates and utilize spatial information more effectively. Results: Experiments on the widely utilized QM9 dataset demonstrate that our proposed framework significantly outperforms the state-of-the-art methods in all evaluation metrics for 3D molecular generation. Additionally, ablation experiments are conducted to highlight the contribution of key components in our framework, demonstrating the effectiveness of the proposed framework and the performance improvements of incorporating angle and torsion angle information for molecular generation. Finally, the comparative results of distribution show that our method is highly effective in generating molecules that closely resemble the actual scenario. Conclusion: Through the experiments and comparative results, our framework clearly outperforms previous 3D molecular generation methods, exhibiting significantly better capacity for modeling chemically realistic molecules. The excellent performance of EMDS in 3D molecular generation brings novel and encouraging opportunities for tackling challenging biomedical molecule and protein scenarios. [ABSTRACT FROM AUTHOR]

Different from the Qaidam basin with about 320 billion m3 microbial gas, only limited microbial gases were found from the Junggar basin with similarly abundant type III kerogen. To determine whether microbial gases have not yet identified, natural gas samples from the Carboniferous to Cretaceous in the Junggar basin have been analyzed for chemical and stable isotope compositions. The results reveal some of the gases from the Mahu sag, Zhongguai, Luliang and Wu-Xia areas in the basin may have mixed with microbial gas leading to straight ethane to butane trends with a "dogleg" light methane in the Chung's plot. Primary microbial gas from degradation of immature sedimentary organic matter is found to occur in the Mahu sag and secondary microbial gas from biodegradation of oils and propane occurred in the Zhongguai, Luliang and Beisantai areas where the associated oils were biodegraded to produce calcites with δ13C values from + 22.10‰ to + 22.16‰ or propane was biodegraded leading to its 13C enrichment. Microbial CH4 in the Mahu sag is most likely to have migrated up from the Lower Wuerhe Formation coal-bearing strata by the end of the Triassic, and secondary microbial gas in Zhongguai and Beisantan uplifts may have generated after the reservoirs were uplifted during the period of the Middle and Late Jurassic. This study suggests widespread distribution of microbial gas and shows the potential to find large microbial gas accumulation in the basin. [ABSTRACT FROM AUTHOR]

Objective Data Sources and Study Setting Study Design Data Collection/Extraction Methods Principal Findings Conclusions To develop a claims‐based algorithm to determine the setting of a disease diagnosis.Medicare enrollment and claims data from 2014 to 2019.We developed a claims‐based algorithm using facility indicators, revenue center codes, and place of service codes to identify settings where HCV diagnosis first appeared. When the first appearance was in a laboratory, we attempted to associate HCV diagnoses with subsequent clinical visits. Face validity was assessed by examining association of claims‐based diagnostic settings with treatment initiation.Patients newly diagnosed with HCV and continuously enrolled in traditional Medicare Parts A, B, and D (12 months before and 6 months after index diagnosis) were included.Among 104,454 patients aged 18–64 and 66,726 aged ≥65, 70.1% and 69%, respectively, were diagnosed in outpatient settings, and 20.2% and 22.7%, respectively in laboratory or unknown settings. Logistic regression revealed significantly lower odds of treatment initiation after diagnosis in emergency departments/urgent cares, hospitals, laboratories, or unclassified settings, than in outpatient visits.The algorithm identified the setting of HCV diagnosis in most cases, and found significant associations with treatment initiation, suggesting an approach that can be adapted for future claims‐based studies. [ABSTRACT FROM AUTHOR]

Chinese Painting and Calligraphy (ChP&C) holds significant cultural value, representing integral aspects of both Chinese culture and global art. A considerable amount of ChP&C works are dispersed worldwide. With the emergence of digital humanities, a vast collection of cultural artifacts data is now available online. However, the online databases of these artifacts remain decentralized and diverse, posing significant challenges to their effective organization and utilization. Addressing this, our paper focuses on the Wu Men School of Painting and proposes a framework for constructing a multimodal knowledge graph for the ChP&C domain. We construct the domain ontology by analyzing the ChP&C knowledge schema. Then, we acquire knowledge from diverse data sources, including textual and visual information. To enhance data collection around collecting historical context and subject matter, we propose methods for seal extraction and subject extraction specific to ChP&C. We validate the effectiveness of these methods on the constructed dataset. Finally, we construct the Wu Men Multimodal Knowledge Graph (WuMKG) and implement applications such as cross-modal retrieval, knowledge-based question-answering and visualization. [ABSTRACT FROM AUTHOR]

Neural networks are frequently employed to model species distribution through backpropagation methods, known as backpropagation neural networks (BPNN). However, the complex structure of BPNN introduces parameter settings challenges, such as the determination of connection weights, which can affect the accuracy of model simulation. In this paper, we integrated the Grey Wolf Optimizer (GWO) algorithm, renowned for its excellent global search capacity and rapid convergence, to enhance the performance of BPNN. Then we obtained a novel hybrid algorithm, the Grey Wolf Optimizer algorithm optimized backpropagation neural networks algorithm (GNNA), designed for predicting species’ potential distribution. We also compared the GNNA with four prevalent species distribution models (SDMs), namely the generalized boosting model (GBM), generalized linear model (GLM), maximum entropy (MaxEnt), and random forest (RF). These models were evaluated using three evaluation metrics: the area under the receiver operating characteristic curve, Cohen’s kappa, and the true skill statistic, across 23 varied species. Additionally, we examined the predictive accuracy concerning spatial distribution. The results showed that the predictive performance of GNNA was significantly improved compared to BPNN, was significantly better than that of GLM and GBM, and was even comparable to that of MaxEnt and RF in predicting species distributions with small sample sizes. Furthermore, the GNNA demonstrates exceptional powers in forecasting the potential non-native distribution of invasive plant species. [ABSTRACT FROM AUTHOR]

Monitoring hydrogen sulfide (H2S) in living organisms is very important because H2S acts as a regulator in many physiological and pathological processes. Upregulation of endogenous H2S concentration has been shown to be closely related to the occurrence and development of tumors, atherosclerosis, neurodegenerative diseases and diabetes. Herin, a novel fluorescent probe HND with aggregation-induced emission was designed. Impressively, HND exhibited a high selectivity, fast response (1 min) and low detection limit (0.61 μM) for H2S in PBS buffer (10 mM, pH = 7.42). Moreover, the reaction mechanism between HND and H2S was conducted by Job's plot, HR-MS, and DFT. In particular, HND was successfully employed to detect H2S in HeLa cells. [ABSTRACT FROM AUTHOR]

The gut microbiome has emerged as a potential target for the treatment of cardiovascular disease. Ischemia/reperfusion (I/R) after myocardial infarction is a serious complication and whether certain gut bacteria can serve as a treatment option remains unclear. Lactobacillus reuteri (L. reuteri) is a well‐studied probiotic that can colonize mammals including humans with known cholesterol‐lowering properties and anti‐inflammatory effects. Here, the prophylactic cardioprotective effects of L. reuteri or its metabolite γ‐aminobutyric acid (GABA) against acute ischemic cardiac injury caused by I/R surgery are demonstrated. The prophylactic gavage of L. reuteri or GABA confers cardioprotection mainly by suppressing cardiac inflammation upon I/R. Mechanistically, GABA gavage results in a decreased number of proinflammatory macrophages in I/R hearts and GABA gavage no longer confers any cardioprotection in I/R hearts upon the clearance of macrophages. In vitro studies with LPS‐stimulated bone marrow‐derived macrophages (BMDM) further reveal that GABA inhibits the polarization of macrophages toward the proinflammatory M1 phenotype by inhibiting lysosomal leakage and NLRP3 inflammasome activation. Together, this study demonstrates that the prophylactic oral administration of L. reuteri or its metabolite GABA attenuates macrophage‐mediated cardiac inflammation and therefore alleviates cardiac dysfunction after I/R, thus providing a new prophylactic strategy to mitigate acute ischemic cardiac injury. [ABSTRACT FROM AUTHOR]

Mesoscale eddies are ubiquitous oceanic phenomena and play an important role in ocean circulation, ocean dynamics, and the transport of material energy. Temperature anomalies are a crucial parameter that reflects the state of mesoscale eddies. This study proposes a Gaussian function model to fit the vertical temperature anomaly (TA) profile to facilitate the analysis of variations, and the principle of the model is based on the fact that each TA profile tends to fluctuate around one or more peaks. The model is extracted and validated using Argo profiles within cyclonic and anticyclonic eddies in the Northwest Pacific Ocean spanning over the period from 2002 to 2021. The validation demonstrates that the model can accurately recover the vertical TA profiles with a limited number of parameters. This makes it suitable for analysing the spatial distribution patterns that require a large sample count. The analysis indicates that eddies with different TA profiles have a spatial aggregation effect in geographic distribution. Eddies with lower extreme temperature anomalies, at depths of 200–300 m, are mainly distributed along two bands on the north side of the Kuroshio Extension (KE) and the North Equatorial Current. Eddies with extreme TAs at the deepest depth (500–600 m) are distributed along the KE. [ABSTRACT FROM AUTHOR]

Background: The association between obesity and respiratory diseases has been confirmed. However, few studies have reported the relationship between obesity and the risk and mortality of chronic inflammatory airway disease (CIAD). The aim of this study was to reveal the association between obesity and the risk of CIAD, and mortality in patients with CIAD. Methods: The study was conducted using data from the National Health and Nutrition Examination Survey (NHANES) 2013 to 2018 among adults aged 20 years and above. All participants were grouped according to body mass index (BMI) and waist circumference (WC) levels to study the relationship between obesity and CIAD. Multivariate logistic regression analysis was utilized to examine the connection between CIAD and obesity in a cross-sectional study. The association between obesity and all-cause mortality in individuals with CIAD was examined using multiple cox regression models and smooth curve fitting in a prospective cohort study. Results: When stratified based on BMI in comparison to the normal weight group, the ORs with 95%CIs of CIAD for underweight and obesity were 1.39 (1.01–1.93) and 1.42 (1.27–1.58), respectively. The OR with 95%CI of CIAD for obesity was 1.20 (1.09–1.31) when stratified according to WC. Additionally, underweight was associated with a higher mortality (HR = 2.44, 95% CI = 1.31–4.55), whereas overweight (HR = 0.58,95% CI = 0.39–0.87) and obesity (HR = 0.59,95% CI = 0.4–0.87) were associated with a lower mortality (P for trend < 0.05). There was a non-linear association between BMI and all-cause mortality (P for non-linear = 0.001). An analysis of a segmentation regression model between BMI and all-cause mortality revealed a BMI turning point value of 32.4 kg/m2. The mortality of CIAD patients was lowest when BMI was 32.4 kg/m2. When BMI ≤ 32.4 kg/m2, BMI was inversely associated with all-cause mortality in patients with CIAD (HR: 0.92, 95%CI:0.88–0.97). However, when BMI > 32.4 kg/m2, there was no association between BMI and all-cause mortality (HR:1.02, 95%CI:0.97–1.06). Conclusion: Compared to normal weight, underweight and obesity were associated with the increased risk of CIAD. Underweight was associated with increased all-cause mortality, while overweight was associated with reduced all-cause mortality. There was a non-linear association between BMI and all-cause mortality in patients with CIAD. The all-cause mortality was lowest when BMI was 32.4 kg/m2. [ABSTRACT FROM AUTHOR]

Carbonation resistance ability is one of the most important durability-related proprieties of cement-based materials. Through the carbonation depth experiment, isothermal conduction calorimetry, XRD, BET, and water vapor sorption, the effect of calcium nitrite (Ca(NO3)2) on the carbonation properties of cement-based materials is obtained. The result indicates that the addition of Ca(NO3)2 improves the carbonation resistance property of cement-based materials if the hydration of cement pastes and microstructure is modified earlier without affecting the late hydration process. In addition, the refined pores and higher tortuosity cut down the channels, thereby impeding the ingress of carbon dioxide gas into cementitious materials, as confirmed by BET and water vapor sorption. The Ca(NO3)2 exhibits high performance in improving the carbonation resistance and extending the life of strengthened concrete. [ABSTRACT FROM AUTHOR]

In order to stop and reverse land degradation and curb the loss of biodiversity, the United Nations 2030 Agenda for Sustainable Development proposes to combat desertification. In this paper, a fractional vegetation–water model in an arid flat environment is studied. The pattern behavior of the fractional model is much more complex than that of the integer order. We study the stability and Turing instability of the system, as well as the Hopf bifurcation of fractional order α , and obtain the Turing region in the parameter space. According to the amplitude equation, different types of stationary mode discoveries can be obtained, including point patterns and strip patterns. Finally, the results of the numerical simulation and theoretical analysis are consistent. We find some novel fractal patterns of the fractional vegetation–water model in an arid flat environment. When the diffusion coefficient, d, changes and other parameters remain unchanged, the pattern structure changes from stripes to spots. When the fractional order parameter, β , changes, and other parameters remain unchanged, the pattern structure becomes more stable and is not easy to destroy. The research results can provide new ideas for the prevention and control of desertification vegetation patterns. [ABSTRACT FROM AUTHOR]

Objectives: Pyogenic spondylitis after vertebral augmentation (PSVA) is a severe complication and even threatens the life of patients. How to deal with infectious bone cement is a big problem for surgeons. The application of piezosurgery has advantages in removal the infectious bone cement in limb bone and spinal laminectomy, but it is rarely used in PSVA. So, the present study aimed to introduce the application of piezosurgery in revision surgery for PSVA and report the preliminary radiological and clinical results. Methods: The data of nine patients with PSVA who had undergone revision surgery were retrospectively reviewed between May 2017 and January 2023 in our hospital. The technique of removal of infectious bone cement and lesion by piezosurgery and the reconstruction of the spinal stability were described, and the operation time and intraoperative blood loss were recorded. Postoperatively, radiographs and computed tomography scans were reviewed to evaluate the condition of bone cement removal, control of infection, and bone fusion. Oswestry disability index (ODI) and visual analog scale (VAS) were assessed pre‐ and postoperatively, and clinical outcomes were assessed using Odom's criteria. Results: All patients achieved satisfactory tainted bone cement cleaning and restoration of spinal alignment. The surgical time was 258.8 ± 63.2 (160–360) min, and the intraoperative blood loss was 613.3 ± 223.8 (300–900) mL. The VAS score decreased from 7.0 (6–8) points preoperatively to 2.4 (1–4) points postoperatively. The ODI index decreased from 71% (65%–80%) preoperatively to 20% (10%–30%) postoperatively. The patient's VAS and NDI scores after operation were significantly improved compared with those before surgery (p ≤ 0.05). Odom's outcomes were good for all patients in the last follow‐up, and all patients reported satisfactory results. Conclusions: Piezosurgery can effectively remove large blocks of infectious bone cement through a posterior approach while avoiding nerve and spinal cord damage. We cautiously suggest that a one‐stage posterior approach using piezosurgery is an alternative option for surgical treatment of PSVA. [ABSTRACT FROM AUTHOR]

[Display omitted] • 20 nm ZIF-8 nanoparticles sandwiched MXene (ZSM) were synthesized by in situ electrostatic assembly. • ZSM derived ultrathin nitrogen-doped carbon/Ti3C2Tx-TiN (NC/MX-TiN) heterostructure. • NC/MX-TiN possesses large specific surface area, outstanding conductivity, and good redox capability. • Excellent desalination performance and robust cycling stability were achieved on NC/MX-TiN. Rational design of high-performance electrode materials is crucial for enhancing desalination performance of capacitive deionization (CDI). Here, ultrathin nitrogen-doped carbon/Ti 3 C 2 T x -TiN (NC/MX-TiN) heterostructure was developed by pyrolyzing zeolite imidazolate framework-8 (ZIF-8) nanoparticles sandwiched MXene (ZSM), which were formed by assembling ultrafine ZIF-8 nanoparticles with size of 20 nm on both sides of MXene nanosheets. The introduction of ultrasmall ZIF-8 particles allowed for in situ nitridation of the MXene during pyrolysis, forming consecutive TiN layers tightly connected to the internal MXene. The two-dimensional (2D) heterostructure exhibited remarkable properties, including high specific surface area and excellent conductivity. Additionally, the resulting TiN demonstrated exceptional redox capability, which significantly enhanced the performance of CDI and ensured cycling stability. Benefiting from these advantages, the NC/MX-TiN exhibited a maximum adsorption capacity of 45.6 mg g−1 and a steady cycling performance in oxygenated saline water over 50 cycles. This work explores the rational design and construction of MXene-based 2D heterostructure and broadens new horizons for the development of novel CDI electrode materials. [ABSTRACT FROM AUTHOR]

Research into new composites utilizing cubic boron nitride (PcBN) shows promise for enhancing cutting tool performance. The unique properties of these materials stem from the addition of microfibers made of refractory compounds to their structure. This study looks at developing two-layer composites based on cBN group BL, reinforced with SiCw and Al2O3w microfibers. The goal is to improve tool stability when cutting hardened steels with impact loads. PcBN composite samples were made by sintering a mixture of cBN powder with bundles and microfibers under 7.7 GPa pressure. Bond material selection was based on analyzing the relationship between Poisson's ratio (η) and plasticity parameter (G/B). The density, Young's modulus, Poisson's ratio, and hardness of the composites were determined, and the microstructure of samples with TiCN bond was studied. Tool-life tests were conducted on two-layer cutting inserts made of PcBN reinforced with SiCw and Al2O3w microfibers during the machining of hardened KhVG steel (HRC 55) under impact loads at cutting speeds of 100 and 200 m/min. [ABSTRACT FROM AUTHOR]

To solve the problem of poor localization accuracy and robustness of visual simultaneous localization and mapping (SLAM) systems in highly dynamic environments, this paper proposes a dynamic visual SLAM algorithm called FFD-SLAM that fuses the target detection network with the optical flow method. The algorithm considers ORB-SLAM2 as the basic framework, joins the semantic thread in parallel with its tracking thread, initially obtains the set of feature points through the real-time detection of dynamic objects in the environment through YOLOv5 in the semantic thread, then filters the set of feature points obtained in the semantic thread through the optical flow module, and finally utilizes the remaining static feature points for the matching calculation. Experiments showed that the proposed algorithm showed an improvement of approximately 97% in the localization accuracy compared with the ORB-SLAM2 algorithm in a highly dynamic environment, which effectively improves the localization accuracy and robustness of the system. The proposed algorithm also showed a higher real-time performance compared with some excellent dynamic SLAM algorithms. [ABSTRACT FROM AUTHOR]

Treating the high water-content sludge with vacuum-assisted prefabricated horizontal drains (PHDs) placed inside, geotextile tubes have the advantage of multiple drainage paths, and geomembrane tubes have the superiority of high vacuum maintenance. Therefore, converting the geotextile tube into a geomembrane tube during slurry dewatering is an effective measure for greater dewatering efficiency and better dehydration effect. In this study, a profound plane-strain consolidation model considering two-dimensional seepage is developed for explaining the dewatering mechanism of sludge in the geo-tubes. Analytical solutions are given and validated by the experiment. The impact of major variables on tube efficiency is further discussed to reference the practice design. Parametric analyses reveal the critical time corresponding to the optimal efficiency of the geotextile tube, after which its consolidation efficiency decreases significantly. However, the consolidation efficiency of a geomembrane tube increases throughout the duration. Consequently, a switching point corresponding to the iso-efficiency state of the geotextile tube and geomembrane tube can be determined for the tube conversion. [ABSTRACT FROM AUTHOR]

In this work, the effect of substrate bias on the properties of amorphous carbon (a-C) films, which are fabricated by electron cyclotron resonance (ECR) ion irradiation on cemented carbide substrate is reported. The microstructure of a-C films is investigated with the aid of atom force microscope (AFM), Raman spectrometer and X-ray photoelectron spectroscopy (XPS). The mechanical and tribological properties of a-C films are analyzed through the scratch and nanoindentation experiments, and the liner reciprocating ball-on-plate tests, respectively. The results indicate that, the average roughness of a-C films is proportional to the negative substrate bias, and the increase of negative substrate bias contributes to the formation of sp 3 bond while the negative substrate biases exceed −30 V. The adhesion strength is excellent under low negative substrate biases, but the strongest adhesion strength is obtained when the substrate bias at −50 V. The average hardness decreases slightly at first and then increases to 16.2 GPa with the increment of negative substrate bias. Additionally, the influence of friction cycle to graphitization level is not obvious. Both transfer film (TF) and roughness of a-C film play significant roles in coefficient of friction (COF). This work sheds light on the fabrication of a-C films on cemented carbide by ECR ion irradiation. [ABSTRACT FROM AUTHOR]

AlN powders with different O impurity contents were used to fabricate the high thermal conductivity (TC) AlN ceramics of different grain boundary (GB) phase distributions via pressureless sintering. Bending strength, fracture toughness, R -curve characteristic, and fracture mechanism of the ceramics were then investigated. The results showed that the GB phase distributions had great influences on mechanical characteristics of the ceramics. The ceramics with the continuous/semi-continuous GB phases possessed low strength and toughness. Comparatively, the ceramics with the isolated island-like GB phases, especially the fine GB phases at the triple AlN GB junctions, owned higher strength and toughness. The AlN ceramics principally followed the intergranular fracture mode, but the GB phase distribution had great effects on the fractions of transgranular fracture. The AlN ceramics with the continuous/semi-continuous GB phases had a lower fraction of the transgranular fracture, and thus lower crack propagation resistance and reliability than the others. [ABSTRACT FROM AUTHOR]

Transparent Y 2 O 3 –Al 2 O 3 –SiO 2 (YAS) glass-ceramics were prepared by the melting-quenching method and two-step heat treatment. P 2 O 5 is one of the most widely used oxide nucleating agents in the production of glass-ceramics, which can control the crystallization temperature or the grain size. The effects of different amounts of P 2 O 5 on the nucleation, crystallization, structure, and mechanical properties of YAS glasses were studied. Raman spectra fitting showed that with increasing P 2 O 5 content from 0.50 wt% to 4.00 wt%, the content of structure units Q3 and Q4 gradually increased, indicating that P 2 O 5 mainly acted as a network former in YAS glass to enhance the connectivity of silicate glass structure. The results revealed that the increase in P 2 O 5 content led to fewer nucleation sites and lower crystallinity. As the P 2 O 5 content increased, the transmittance of YAS glass-ceramics changed slightly under the same heat treatment, but the Vickers hardness decreased significantly. Fine, granular and evenly distributed nanocrystals were precipitated from YAS precursor glasses through heat treatment at 700 °C for 10 h and 750 °C for 1 h. Additionally, the reported Vickers hardness, fracture toughness and transmittance of YAS glass-ceramic containing 0.50 wt% P 2 O 5 were 674.48 Hv, 1.09 MPa m1/2 and 87.59 %, respectively. [ABSTRACT FROM AUTHOR]

The quality of rice, evaluated using multiple quality-related traits, is the main determinant of its market competitiveness. In this study, two japonica rice varieties with significant differences in quality-related traits were used as parents to construct two populations, BC3F2 and BC3F2:3, with Kongyu131 (KY131) as the recurrent parent. A genetic linkage map was constructed using the BC3F2 population based on 151 pairs of SSR/InDel polymorphic markers selected between the parents. Grain-shape-related traits (grain length GL, grain width GW, and length-to-width ratio LWR), chalkiness-related traits (white-core rate WCR, white-belly rate WBR, white-back rate BR, and chalkiness rate CR), and amylose content (AC) were investigated in the two populations in 2017 and 2018. Except for BR and CR, the traits showed similar characteristics with a normal distribution in both populations. Genetic linkage analysis was conducted for these quality-related traits, and a total of 37 QTLs were detected in the two populations. Further validation was performed on the newly identified QTLs with larger effects, and three grain shape QTLs and four chalkiness QTLs were successfully validated in different environments. One repeatedly validated QTL, qWCR3, was selected for fine mapping and was successfully narrowed down to a 100 kb region in which only two genes, LOC_0s03g45210 and LOC_0s03g45320, exhibited sequence variations between the parents. Furthermore, the variation of LOC_Os03g45210 leads to a frameshift mutation and premature protein termination. The results of this study provide a theoretical basis for positional cloning of the qWCR3 gene, thus offering new genetic resources for rice quality improvement. [ABSTRACT FROM AUTHOR]

With large-scale grid-connected renewable energy, new power systems require more flexible and reliable energy storage power sources. Pumped storage stations play an important role in peak shaving, valley filling, and promoting renewable energy consumption. This paper presents the reasonable energy-abandonment operation of a combined power generation system (CPGS), in which a pumped storage station is the core control power, with an ultra-high proportion of renewable energy. Firstly, based on the seasonal characteristics of wind, solar, and load demand, typical days are selected through improved clustering analysis algorithms. Then, a daily optimal scheduling model for combined power generation systems (CPGS) is developed with the goals of economy, low-carbon, and stable operation. Finally, the correlation between the energy-abandonment rate and pumped storage station peak shaving and system optimization operation indicators is obtained by a reasonable energy-abandonment calculation method considering source-grid-load coordination. Taking the operation data of an energy base in the western region of China as an example, when the penetration rate of renewable energy is 60–70% in the future, the operating cost on the power side is greatly affected by the construction of the source side. When the system operates at a planned reasonable energy-abandonment rate of 2%, electricity regulation, load tracking, and daily operating costs all show better performance. [ABSTRACT FROM AUTHOR]

Background: Central nervous system (CNS) tumors originate from the spinal cord or brain. The study showed that even with aggressive treatment, malignant CNS tumors have high mortality rates. However, CNS tumor risk factors and molecular mechanisms have not been verified. Due to the reasons mentioned above, diagnosis and treatment of CNS tumors in clinical practice are currently fraught with difficulties. Circular RNAs (circRNAs), single‐stranded ncRNAs with covalently closed continuous structures, are essential to CNS tumor development. Growing evidence has proved the numeral critical biological functions of circRNAs for disease progression: sponging to miRNAs, regulating gene transcription and splicing, interacting with proteins, encoding proteins/peptides, and expressing in exosomes. Aims: This review aims to summarize current progress regarding the molecular mechanism of circRNA in CNS tumors and to explore the possibilities of clinical application based on circRNA in CNS tumors. Methods: We have summarized studies of circRNA in CNS tumors in Pubmed. Results: This review summarized their connection with CNS tumors and their functions, biogenesis, and biological properties. Furthermore, we introduced current advances in clinical RNA‐related technologies. Then we discussed the diagnostic and therapeutic potential (especially for immunotherapy, chemotherapy, and radiotherapy) of circRNA in CNS tumors in the context of the recent advanced research and application of RNA in clinics. Conclusions: CircRNA are increasingly proven to participate in decveloping CNS tumors. An in‐depth study of the causal mechanisms of circRNAs in CNS tomor progression will ultimately advance their implementation in the clinic and developing new strategies for preventing and treating CNS tumors. [ABSTRACT FROM AUTHOR]

KIFC3 is a member of Kinesin-14 family motor proteins, which play a variety of roles such as centrosome cohesion, cytokinesis, vesicles transportation and cell proliferation in mitosis. Here, we investigated the functional roles of KIFC3 in meiosis. Our findings demonstrated that KIFC3 exhibited expression and localization at centromeres during metaphase I, followed by translocation to the midbody at telophase I throughout mouse oocyte meiosis. Disruption of KIFC3 activity resulted in defective polar body extrusion. We observed aberrant meiotic spindles and misaligned chromosomes, accompanied by the loss of kinetochore-microtubule attachment, which might be due to the failed recruitment of BubR1/Bub3. Coimmunoprecipitation data revealed that KIFC3 plays a crucial role in maintaining the acetylated tubulin level mediated by Sirt2, thereby influencing microtubule stability. Additionally, our findings demonstrated an interaction between KIFC3 and PRC1 in regulating midbody formation during telophase I, which is involved in cytokinesis regulation. Collectively, these results underscore the essential contribution of KIFC3 to spindle assembly and cytokinesis during mouse oocyte meiosis. [ABSTRACT FROM AUTHOR]

The permeability–selectivity trade‐off of membrane is a major challenge limiting the development of pervaporation (PV) technology. Rational design of high‐performance mixed matrix membranes (MMMs) has the potential to break off the trade‐off. Herein, a solvent‐assisted linker exchange‐based strategy is reported to introduce fluoroalkyl into metal–organic framework‐808 (MOF‐808). The pore size of fluorinated MOF‐808 can be adjusted with fluoroalkyl of different chain length (like trifluoromethyl and pentafluoropropyl). Then, the fluorinated MOF‐808/polyether block amide (PEBA) MMMs are prepared for the PV of n‐butanol/water. Compared with pristine PEBA membrane, 20 wt% 3F‐MOF‐808(P)/PEBA MMMs (3F = ‐CF3 group; P = postmodification method) exhibit 69% increase in permeation flux and 33% increase in separation factor in the PV of 2.5 wt% n‐butanol aqueous solutions at 70 °C. Based on Grand Canonical Monte Carlo and molecular dynamics simulations, fluorinated MOF‐808 shows better butanol affinity (pull effect) and stronger water repulsion ability (push effect). And the "push–pull effect" between fluorinated MOF‐808 with butanol/water is helpful to enhance the PV performance of MMMs. The application of "push–pull effect" provides a new strategy for the rational design of high‐performance MMMs, which is of great significance for the in‐depth research and application of PV technology. [ABSTRACT FROM AUTHOR]

LiDAR has high accuracy and resolution and is widely used in various fields. In particular, phase-modulated continuous-wave (PhMCW) LiDAR has merits such as low power, high precision, and no need for laser frequency modulation. However, with decreasing signal-to-noise ratio (SNR), the noise on the signal waveform becomes so severe that the current methods to extract the time-of-flight are no longer feasible. In this paper, a novel method that uses deep neural networks to measure the pulse width is proposed. The effects of distance resolution and SNR on the performance are explored. Recognition accuracy reaches 81.4% at a 0.1 m distance resolution and the SNR is as low as 2. We simulate a scene that contains a vehicle, a tree, a house, and a background located up to 6 m away. The reconstructed point cloud has good fidelity, the object contours are clear, and the features are restored. More precisely, the three distances are 4.73 cm, 6.00 cm, and 7.19 cm, respectively, showing that the performance of the proposed method is excellent. To the best of our knowledge, this is the first work that employs a neural network to directly process LiDAR signals and to extract their time-of-flight. [ABSTRACT FROM AUTHOR]

This paper proposes a deep reinforcement learning-based framework for robot autonomous grasping and assembly skill learning. Meanwhile, a deep Q-learning-based robot grasping skill learning algorithm and a PPO-based robot assembly skill learning algorithm are presented, where a priori knowledge information is introduced to optimize the grasping action and reduce the training time and interaction data needed by the assembly strategy learning algorithm. Besides, a grasping constraint reward function and an assembly constraint reward function are designed to evaluate the robot grasping and assembly quality effectively. Finally, the effectiveness of the proposed framework and algorithms was verified in both simulated and real environments, and the average success rate of grasping in both environments was up to 90%. Under a peg-in-hole assembly tolerance of 3 mm, the assembly success rate was 86.7% and 73.3% in the simulated environment and the physical environment, respectively. [ABSTRACT FROM AUTHOR]

Using sodium lignosulfonate as feedstock, ZnCl2 and NaHCO3 co-activated the hierarchical porous carbons (HPCs) were prepared by one-pot pyrolysis with different NaHCO3 dosages (0–4 g) and carbonization temperatures (400–600 °C). Subsequently, phosphotungstate (HPW) was supported with the resulting biochar for the α-pinene hydration reaction to produce α-terpineol. The optimum preparation conditions were determined according to the yield of α-terpineol. The formation mechanism and physicochemical properties of HPCs were analyzed through TG, SEM, XPS, XRD, FT-IR, and N2 adsorption–desorption isotherms. The results demonstrated that NaHCO3 underwent a two-step reaction which liberated a substantial quantity of CO2, thereby enhancing activated carbon's macroporous and mesoporous structures. Simultaneously, NaHCO3 mitigated strong acid gas (HCl) emissions during ZnCl2 activation. Compared with AC450-4:8:0 prepared by ZnCl2 activation alone, the total pore volume of AC450-4:8:2 prepared by co-activation is increased from 0.595 mL/g to 0.754 mL/g and the mesopore rate from 47.7% to 77.8%, which is conducive to reducing the steric hindrance of the hydration reaction and improving the selectivity. Hydration experiments show that the selectivity of α-terpineol is 55.7% under HPW/AC450-4:8:2 catalysis, higher than 31.0% for HPW and 47.4% for HPW/AC450-4:8:0. [ABSTRACT FROM AUTHOR]

Luminescent anti-counterfeiting materials based on double perovskite has attracted people's attention due to its low cost, high stability, easy preparation, and environmental friendliness. However, advanced anti-counterfeiting and information encryption call for materials with multi-color emission and multimode excitation to avoid being imitated and replaced. In this study, upconversion luminescence of lanthanide Cs 2 Ag 1-x Na x BiCl 6 were investigated through adjusting the feed ratio of Ag + to Na+ and controlling the types and concentrations of the lanthanide ions. Cs 2 Ag 0.4 Na 0.6 BiCl 6 -Yb-Er emits green light under excitation at 980 and 1540 nm. Cs 2 Ag 0.4 Na 0.6 BiCl 6 -Yb-Tm and Cs 2 Ag 0.4 Na 0.6 BiCl 6 -Yb-Ho show purple and white light under excitation at 980 nm, respectively. Under excitation at 365 nm, the Cs 2 Ag 0.4 Na 0.6 BiCl 6 -Yb-Er presents yellow light, while both Cs 2 Ag 0.4 Na 0.6 BiCl 6 -Yb-Tm and Cs 2 Ag 0.4 Na 0.6 BiCl 6 -Yb-Ho exhibit orange-red light. Additionally, Yb ions doping make three samples present good near-infrared luminescent properties. At last, the high level anti-counterfeiting and information encryption applications based on lanthanide doped Cs 2 Ag 1-x Na x BiCl 6 were designed and implemented, using the characteristics of the material's luminescence properties that differ with the type of doping, excitation wavelength, and excitation power. This work indicates that lanthanide doped double perovskite has the potential to obtain more efficient anti-counterfeiting materials and information encryption materials. [ABSTRACT FROM AUTHOR]

Background: Sepsis is a severe systemic inflammatory disorder manifested by a dysregulated immune response to infection and multi-organ failure. Numerous studies have shown that elevated ferritin levels exist as an essential feature during sepsis and are able to suggest patients' prognoses. At the same time, the specific mechanism of ferritin-induced inflammatory injury remains unclear. Methods: Hyper-ferritin state during inflammation was performed by injecting ferritin into a mouse model and demonstrated that injection of ferritin could induce a systemic inflammatory response and increase neutrophil extracellular trap (NET) formation.Padi4−/−, Elane−/− and Cybb−/− mice were used for the NETs formation experiment. Western blot, immunofluorescence, ELISA, and flow cytometry examined the changes in NETs, inflammation, and related signaling pathways. Results: Ferritin induces NET formation in a peptidylarginine deiminase 4 (PAD4), neutrophil elastase (NE), and reactive oxygen species (ROS)-dependent manner, thereby exacerbating the inflammatory response. Mechanistically, ferritin induces the expression of neutrophil macrophage scavenger receptor (MSR), which promotes the formation of NETs. Clinically, high levels of ferritin in patients with severe sepsis correlate with NETs-mediated cytokines storm and are proportional to the severity of sepsis-induced lung injury. Conclusions: In conclusion, we demonstrated that hyper-ferritin can induce systemic inflammation and increase NET formation in an MSR-dependent manner. This process relies on PAD4, NE, and ROS, further aggravating acute lung injury. In the clinic, high serum ferritin levels are associated with elevated NETs and worse lung injury, which suggests a poor prognosis for patients with sepsis. Our study indicated that targeting NETs or MSR could be a potential treatment to alleviate lung damage and systemic inflammation during sepsis. CG19NQAB-3s1ZkbgUbzmoX Video Abstract [ABSTRACT FROM AUTHOR]

The influenza BM2 transmembrane domain (BM2TM), an acid-activated proton channel, is an attractive antiviral target due to its essential roles during influenza virus replication, whereas no effective inhibitors have been reported for BM2. In this study, we draw inspiration from the properties of cyclodextrins (CDs) and hypothesize that CDs of appropriate sizes may possess the potential to act as inhibitors of the B M 2 T M proton channel. To explore this possibility, molecular dynamics simulations were employed to assess their inhibitory capabilities. Our findings reveal that CD4, CD5, and CD6 are capable of binding to the B M 2 T M proton channel, resulting in disrupted water networks and reduced hydrogen bond occupancy between H19 and the solvent within the B M 2 T M channel necessary for proton conduction. Notably, CD4 completely obstructs the B M 2 T M water channel. Based on these observations, we propose that CD4, CD5, and CD6 individually contribute to diminishing the proton transfer efficiency of the BM2 protein, and CD4 demonstrates promising potential as an inhibitor for the BM2 proton channel. [ABSTRACT FROM AUTHOR]

Mechanical metamaterials are known for their prominent mechanical characteristics such as programmable deformation that are due to periodic microstructures. Recent research trends have shifted to utilizing mechanical metamaterials as structural substrates to integrate with functional materials for advanced functionalities beyond mechanical, such as active sensing. This study reports on the ultra‐stretchable kirigami piezo‐metamaterials (KPM) for sensing coupled large deformations caused by in‐ and out‐of‐plane displacements using the lead zirconate titanate (PZT) and barium titanate (BaTiO3) composite films. The KPM are fabricated by uniformly compounding and polarizing piezoelectric particles (i.e., PZT and BaTiO3) in silicon rubber and structured by cutting the piezoelectric rubbery films into ligaments. Characterizes the electrical properties of the KPM and investigates the bistable mechanical response under the coupled large deformations with the stretching ratio up to 200% strains. Finally, the PZT KPM sensors are integrated into wireless sensing systems for the detection of vehicle tire bulge, and the non‐toxic BaTiO3 KPM are applied for human posture monitoring. The reported kirigami piezo‐metamaterials open an exciting venue for the control and manipulation of mechanically functional metamaterials for active sensing under complex deformation scenarios in many applications. [ABSTRACT FROM AUTHOR]

Space infrared dim target recognition is an important applications of space situational awareness (SSA). Due to the weak observability and lack of geometric texture of the target, it may be unreliable to rely only on grayscale features for recognition. In this paper, an intelligent information decision-level fusion method for target recognition which takes full advantage of the ensemble classifier and Dempster–Shafer (DS) theory is proposed. To deal with the problem that DS produces counterintuitive results when evidence conflicts, a contraction–expansion function is introduced to modify the body of evidence to mitigate conflicts between pieces of evidence. In this method, preprocessing and feature extraction are first performed on the multi-frame dual-band infrared images to obtain the features of the target, which include long-wave radiant intensity, medium–long-wave radiant intensity, temperature, emissivity–area product, micromotion period, and velocity. Then, the radiation intensities are fed to the random convolutional kernel transform (ROCKET) architecture for recognition. For the micromotion period feature, a support vector machine (SVM) classifier is used, and the remaining categories of the features are input into the long short-term memory network (LSTM) for recognition, respectively. The posterior probabilities corresponding to each category, which are the result outputs of each classifier, are constructed using the basic probability assignment (BPA) function of the DS. Finally, the discrimination of the space target category is implemented according to improved DS fusion rules and decision rules. Continuous multi-frame infrared images of six flight scenes are used to evaluate the effectiveness of the proposed method. The experimental results indicate that the recognition accuracy of the proposed method in this paper can reach 93% under the strong noise level (signal-to-noise ratio is 5). Its performance outperforms single-feature recognition and other benchmark algorithms based on DS theory, which demonstrates that the proposed method can effectively enhance the recognition accuracy of space infrared dim targets. [ABSTRACT FROM AUTHOR]

Genome-wide association studies (GWAS) have emerged as a powerful tool for unraveling intricate genotype–phenotype association across various species. Maize (Zea mays L.), renowned for its extensive genetic diversity and rapid linkage disequilibrium (LD), stands as an exemplary candidate for GWAS. In maize, GWAS has made significant advancements by pinpointing numerous genetic loci and potential genes associated with complex traits, including responses to both abiotic and biotic stress. These discoveries hold the promise of enhancing adaptability and yield through effective breeding strategies. Nevertheless, the impact of environmental stress on crop growth and yield is evident in various agronomic traits. Therefore, understanding the complex genetic basis of these traits becomes paramount. This review delves into current and future prospectives aimed at yield, quality, and environmental stress resilience in maize and also addresses the challenges encountered during genomic selection and molecular breeding, all facilitated by the utilization of GWAS. Furthermore, the integration of omics, including genomics, transcriptomics, proteomics, metabolomics, epigenomics, and phenomics has enriched our understanding of intricate traits in maize, thereby enhancing environmental stress tolerance and boosting maize production. Collectively, these insights not only advance our understanding of the genetic mechanism regulating complex traits but also propel the utilization of marker-assisted selection in maize molecular breeding programs, where GWAS plays a pivotal role. Therefore, GWAS provides robust support for delving into the genetic mechanism underlying complex traits in maize and enhancing breeding strategies. [ABSTRACT FROM AUTHOR]

Luminescent anti-counterfeiting materials based on double perovskite has attracted people's attention due to its low cost, high stability, easy preparation, and environmental friendliness. However, advanced anti-counterfeiting and information encryption call for materials with multi-color emission and multimode excitation to avoid being imitated and replaced. In this study, upconversion luminescence of lanthanide Cs 2 Ag 1-x Na x BiCl 6 were investigated through adjusting the feed ratio of Ag + to Na+ and controlling the types and concentrations of the lanthanide ions. Cs 2 Ag 0.4 Na 0.6 BiCl 6 -Yb-Er emits green light under excitation at 980 and 1540 nm. Cs 2 Ag 0.4 Na 0.6 BiCl 6 -Yb-Tm and Cs 2 Ag 0.4 Na 0.6 BiCl 6 -Yb-Ho show purple and white light under excitation at 980 nm, respectively. Under excitation at 365 nm, the Cs 2 Ag 0.4 Na 0.6 BiCl 6 -Yb-Er presents yellow light, while both Cs 2 Ag 0.4 Na 0.6 BiCl 6 -Yb-Tm and Cs 2 Ag 0.4 Na 0.6 BiCl 6 -Yb-Ho exhibit orange-red light. Additionally, Yb ions doping make three samples present good near-infrared luminescent properties. At last, the high level anti-counterfeiting and information encryption applications based on lanthanide doped Cs 2 Ag 1-x Na x BiCl 6 were designed and implemented, using the characteristics of the material's luminescence properties that differ with the type of doping, excitation wavelength, and excitation power. This work indicates that lanthanide doped double perovskite has the potential to obtain more efficient anti-counterfeiting materials and information encryption materials. [ABSTRACT FROM AUTHOR]

When designing steel members with nonsymmetric cross sections, it is essential to consider twisting effects when performing stability checks via second-order analysis according to the ANSI/AISC 360-22. Existing line-element formulations for nonsymmetric sections are mostly derived based on thin-walled assumptions, leading to an overestimation of member strength due to the inaccurate prediction of member behavior, especially when the cross sections have moderate wall thickness. This paper proposes an efficient line-element method for second-order analysis of steel members with nonsymmetric thick-walled sections considering the warping degree of freedom (DOF) and the twisting effects along with the transverse shear deformations. Additionally, a two-dimensional (2D) finite-element cross section analysis method employing the constant strain triangle (CST) element is developed to calculate the section properties for arbitrary cross sections, including the Wagner and the shear coefficients. The proposed method is implemented in the educational structural analysis software MASTAN2 and verified through two sets of examples. [ABSTRACT FROM AUTHOR]

Livestream content has been gaining popularity in recent years. Although it has been known that livestream viewing can mitigate the adverse effects of loneliness on individuals' well-being, the specific cognitive-affective processes involved are not given due attention. Situated in the Evolutionary Theory of Loneliness, the current study draws upon a national survey data (n = 911) to demonstrate that one's hypervigilance and their negative emotional state serially mediate the relationship between their feelings of loneliness and their perceived well-being. The frequency of livestream views was also found to be moderating the serial mediation paths and the direct effect between feelings of loneliness on perceived well-being. [ABSTRACT FROM AUTHOR]

The variation of temperature modifies the magnetic behavior of ferromagnetic cores which may affect the performance of electrical equipment. Therefore, it is imperative to develop a temperature-dependent hysteresis model to precisely calculate electromagnetic characteristics of electrical equipment. In this paper, a Temporal Convolutional Network (TCN) in combination with the Play operator is developed. The proposed model incorporates the temperature-dependent spontaneous magnetization intensity as the model input to introduce the temperature effect. To enhance the accuracy of model training outcomes, the Bayesian optimization approach for automatically selecting network model parameters is provided. The results show that the proposed model can accurately predict the hysteresis characteristics of materials under varying temperature and frequency conditions. [ABSTRACT FROM AUTHOR]

Siamese‐based trackers have demonstrated robust performance in object tracking, while Transformers have achieved widespread success in object detection. Currently, many researchers use a hybrid structure of convolutional neural networks and Transformers to design the backbone network of trackers, aiming to improve performance. However, this approach often underutilises the global feature extraction capability of Transformers. The authors propose a novel Transformer‐based tracker that fuses spatial and temporal features. The tracker consists of a multilayer spatial feature fusion network (MSFFN), a temporal feature fusion network (TFFN), and a prediction head. The MSFFN includes two phases: feature extraction and feature fusion, and both phases are constructed with a Transformer. Compared with the hybrid structure of "CNNs + Transformer," the proposed method enhances the continuity of feature extraction and the ability of information interaction between features, enabling comprehensive feature extraction. Moreover, to consider the temporal dimension, the authors propose a TFFN for updating the template image. The network utilises the Transformer to fuse the tracking results of multiple frames with the initial frame, allowing the template image to continuously incorporate more information and maintain the accuracy of target features. Extensive experiments show that the tracker STFT achieves state‐of‐the‐art results on multiple benchmarks (OTB100, VOT2018, LaSOT, GOT‐10K, and UAV123). Especially, the tracker STFT achieves remarkable area under the curve score of 0.652 and 0.706 on the LaSOT and OTB100 benchmark respectively. [ABSTRACT FROM AUTHOR]