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Low-energy ion beam irradiation, combined with the introduction of impurities, presents a promising approach for nanopatterning silicon (Si) surfaces. In this research, we investigate the surface evolution of Si (100) surfaces irradiated by 75 eV helium (He) plasma, in the presence of tantalum (Ta), traditionally regarded as an impurity incapable of initiating pattern formation, as evidenced in prior studies. The Ta impurities are pre-deposited onto the Si surfaces using the magnetron sputtering method, which offers a more controlled and quantifiable approach compared with the conventional co-deposition route. After irradiation at 800 K, dense cone arrays are produced on the Si surface. The growth of the cones is explored for fluence spanning (1–10) × 1025 m−2. The cross-sectional scanning electron microscope images indicate that the cone lengths and base width are well characterized by t1/2 dependence. The kinetics of the cone growth follow Fick's law, characterized by an effective diffusive mechanism with the coefficients of diffusion: D = 6.49 ± 0.83 × 10−16 m−2 s−1. Transmission electron microscope observations reveal that the cone has distinct inner and outer parts with different microstructures and a clear interface. The growth mechanism of these cones is elucidated as a composite process involving preferential sputtering, the destabilizing influence of He bubbles, and the migration of adatoms. [ABSTRACT FROM AUTHOR]

Short nanopores find extensive applications, capitalizing on their high throughput and detection resolution. Ionic behaviors through long nanopores are mainly determined by charged inner-pore walls. When pore lengths decrease to sub-200 nm, charged exterior surfaces provide considerable modulation to ion current. We find that the charge status of inner-pore walls affects the modulation of ion current from charged exterior surfaces. For 50-nm-long nanopores with neutral inner-pore walls, the charged exterior surfaces on the voltage (surfaceV) and ground (surfaceG) sides enhance and inhibit the ion transport by forming ion enrichment and depletion zones inside nanopores, respectively. For nanopores with both charged inner-pore and exterior surfaces, continuous electric double layers enhance the ion transport through nanopores significantly. The charged surfaceV results in higher ion current by simultaneously weakening the ion depletion at pore entrances and enhancing the intra-pore ion enrichment. The charged surfaceG expedites the exit of ions from nanopores, resulting in a decrease in ion enrichment at pore exits. Through adjustment in the width of charged-ring regions near pore boundaries, the effective charged width of the charged exterior is explored at ∼20 nm. Our results may provide a theoretical guide for further optimizing the performance of nanopore-based applications, such as seawater desalination, biosensing, and osmotic energy conversion. [ABSTRACT FROM AUTHOR]

By describing the absorption, distribution, metabolism, and excretion of drugs, pharmacokinetics helps to find optimal therapies for patients and speed up drug development. In pharmacokinetics, dynamic uncertainties, such as fluctuations in hormone levels and external environment factors, are ubiquitous. Due to sparse clinical data and patient disease specificity, these uncertainties are mainly epistemic uncertainties rather than aleatory uncertainties, which cannot be handled well by probability theory based methods. Therefore, several pharmacokinetics based on uncertain differential equations under the framework of uncertainty theory were investigated, which all considered one compartment models. Noting that many drugs follow two compartment kinetics, this article proposes a two compartment pharmacokinetic model based on uncertain differential equations. Based on the proposed model, several essential pharmacokinetic parameters are investigated, which are important information required by regulatory bodies to approve drugs for public use. Estimation for unknown parameters in the model are given. Finally, a real data analysis using lidocaine drug concentration illustrates our methodology in details. [ABSTRACT FROM AUTHOR]

Glioblastoma multiforme (GBM) is the most common and aggressive primary brain tumor, making it one of the most life‐threatening human cancers. Nevertheless, research on the mechanism of action between alternative splicing (AS) and splicing factor (SF) or biomarkers in GBM is limited. AS is a crucial post‐transcriptional regulatory mechanism. More than 95% of human genes undergo AS events. AS can diversify the expression patterns of genes, thereby increasing the diversity of proteins and playing a significant role in the occurrence and development of tumors. In this study, we downloaded 599 clinical data and 169 transcriptome analysis data from The Cancer Genome Atlas (TCGA) database. Besides, we collected AS data about GBM from TCGA‐SpliceSeq. The overall survival (OS) related AS events in GBM were determined through least absolute shrinkage and selection operator (Lasso) and Cox analysis. Subsequently, the association of these 1825 OS‐related AS events with patient survival was validated using the Kaplan–Meier survival analysis, receiver operating characteristic curve, risk curve analysis, and independent prognostic analysis. Finally, we depicted the AS–SF regulatory network, illustrating the interactions between splicing factors and various AS events in GBM. Additionally, we identified three splicing factors (RNU4‐1, SEC31B, and CLK1) associated with patient survival. In conclusion, based on AS occurrences, we developed a predictive risk model and constructed an interaction network between GBM‐related AS events and SFs, aiming to shed light on the underlying mechanisms of GBM pathogenesis and progression. [ABSTRACT FROM AUTHOR]

Twinning is an important deformation mechanism for magnesium alloys, which has a significant impact on the texture evolution and mechanical properties. Pre-twinning deformation has been considered as an effective method for texture regulation. For each twinning mode, there are six crystallographically equivalent variants. Properly identifying the activated twin and understanding its variant selection criteria are essential for the development of high-performance magnesium alloys. As summarized in this paper, the observed twin variant by the commonly employed electron backscatter diffraction technique can be identified by several approaches, including misorientation analysis, trace analysis and matrix method. Schmid factor analysis was commonly performed to explain the selection of twin variants. To broaden the application scope under complex stress state, a generalized Schmid factor was derived by introducing a stress tensor. The efficiency of Schmid criteria to assess twin variant selection was confirmed to be influenced by the type of the applied stress. To consider the local effect on twin activation, in particular twin-twin transfer and slip-induced twinning, displacement gradient tensor calculation and geometrical compatibility factor analysis have been employed. It was demonstrated that local strain accommodation played a critical role in selecting the variants of cross-boundary twins in magnesium alloys. Assisted with crystal plasticity finite element modeling, the resolved shear stress on twinning and a composite Schmid factor combining the global Schmid factor and geometrical compatibility factor were obtained to better explain the activated twin variants in magnesium alloys. All the above-mentioned Schmid law based criteria and some energy based criteria as well are summarized in this paper. Their applications in evaluating twin variant selection in magnesium alloys are critically reviewed and discussed. [ABSTRACT FROM AUTHOR]

Colon cancer is one of the malignant tumors with high morbidity, lethality, and prevalence across global human health. Molecular biomarkers play key roles in its prognosis. In particular, immune-related lncRNAs (IRL) have attracted enormous interest in diagnosis and treatment, but less is known about their potential functions. We aimed to investigate dysfunctional IRL and construct a risk model for improving the outcomes of patients. Nineteen immune cell types were collected for identifying house-keeping lncRNAs (HKLncRNA). GSE39582 and TCGA-COAD were treated as the discovery and validation datasets, respectively. Four machine learning algorithms (LASSO, Random Forest, Boruta, and Xgboost) and a Gaussian mixture model were utilized to mine the optimal combination of lncRNAs. Univariate and multivariate Cox regression was utilized to construct the risk score model. We distinguished the functional difference in an immune perspective between low- and high-risk cohorts calculated by this scoring system. Finally, we provided a nomogram. By leveraging the microarray, sequencing, and clinical data for immune cells and colon cancer patients, we identified the 221 HKLncRNAs with a low cell type-specificity index. Eighty-seven lncRNAs were up-regulated in the immune compared to cancer cells. Twelve lncRNAs were beneficial in improving performance. A risk score model with three lncRNAs (CYB561D2, LINC00638, and DANCR) was proposed with robust ROC performance on an independent dataset. According to immune-related analysis, the risk score is strongly associated with the tumor immune microenvironment. Our results emphasized IRL has the potential to be a powerful and effective therapy for enhancing the prognostic of colon cancer. [ABSTRACT FROM AUTHOR]

Weakly Supervised Object Localization (WSOL) aims to utilize the features learned by a classifier on the image-level labels to locate target objects. However, these existing channel selection methods for WSOL still cannot effectively select the important channels and remove the unimportant ones. To address this issue, we propose a Clustering-inspired Channel Selection method based on Class Activation Maps (CCS-CAM). Compared with the traditional methods, the advantage of CCS-CAM is that it is very simple yet effective for channel selection due to the K-means clustering based on Class Activation Maps. It can effectively ensure both object localization and classification accuracy. The effectiveness of the proposed CCS-CAM method has been demonstrated using multiple public datasets, with GT-Know Loc reaching 87.9% and 63.71% on the CUB200-2011 and ImageNet-1k respectively, which is superior to the other state-of-the-art methods. • WSOL network extends image classification for precise object location. • CCS module filters channels, using K-means for effective object localization. • Tested on CUB200-2011, ImageNet-1K, FGVC-Aircraft, Stanford Cars with success. [ABSTRACT FROM AUTHOR]

Aspartyl dipeptidase (dipeptidase E) can hydrolyze Asp-X dipeptides (where X is any amino acid), and the enzyme plays a key role in the degradation of peptides as nutrient sources. Dipeptidase E remains uncharacterized in Streptomyces. Orf2 from Streptomyces sp. 139 is located in the exopolysaccharide biosynthesis gene cluster, which may be a novel dipeptidase E with "S134-H170-D198" catalytic triad by sequence and structure comparison. Herein, recombinant Orf2 was expressed in E. coli and characterized dipeptidase E activity using the Asp-ρNA substrate. The optimal pH and temperature for Orf2 are 7.5 and 40 ℃; Vmax and Km of Orf2 are 0.0787 mM·min−1 and 1.709 mM, respectively. Orf2 exhibits significant degradation activities to Asp-Gly-Gly, Asp-Leu, Asp-His, and isoAsp-Leu and minimal activities to Asp-Pro and Asp-Ala. Orf2 contains a Ser-His-Asp catalytic triad characterized by point mutation. In addition, the Asp147 residue of Orf2 is also proven to be critical for the enzyme's activity through molecular docking and point mutation. Transcriptome analysis reveals the upregulation of genes associated with ribosomes, amino acid biosynthesis, and aminoacyl-tRNA biosynthesis in the orf2 mutant strain. Compared with the orf2 mutant strain and WT, the yield of crude polysaccharide does not change significantly. However, crude polysaccharides from the orf2 mutant strain exhibit a wider range of molecular weight distribution. The results indicate that the Orf2 links nutrient stress to secondary metabolism as a novel dipeptidase E. Key points: • A novel dipeptidase E with a Ser-His-Asp catalytic triad was characterized from Streptomyces sp. 139. • Orf2 was involved in peptide metabolism both in vitro and in vivo. • Orf2 linked nutrient stress to mycelia formation and secondary metabolism in Streptomyces. [ABSTRACT FROM AUTHOR]

Objective: The objective of this scoping review was to investigate the effectiveness and limitations of risk prediction models for postpartum glucose intolerance in women with gestational diabetes mellitus (GDM). The aim was to provide valuable insights for healthcare professionals in the development of robust risk prediction models. Methods: A comprehensive literature search was conducted across multiple databases, including PubMed, EBSCO, Web of Science Core Collection, Ovid Full-Text Medical Journal Database, ProQuest, Elsevier ClinicalKey, China National Knowledge Infrastructure, China Biology Medicine, and WanFang Database, spanning from January 1990 to July 2023. To assess the quality of the included models, the Predictive Model Risk of Bias Assessment Tool (PROBAST) was employed. Results: Fourteen relevant studies were identified and included in the final review, all focusing on model development. The discrimination ability of the included models ranged from 0.725 to 0.940, indicating satisfactory prediction accuracy. However, a notable limitation was that nine of these models (64.3%) did not provide clear guidelines on the selection of potential predictors. Furthermore, only six models (42.86%) underwent internal validation, with none undergoing external validation. A high risk of bias was observed across the included models. Logistic regression, Cox regression, and machine learning were the primary methods employed in the construction of these models. Conclusion: The risk prediction models included in this review demonstrated favorable prediction accuracy. However, due to variations in construction methodologies, direct comparison of their performance is challenging. These models exhibited certain shortcomings, such as inadequate handling of missing data and a lack of internal and external validation, resulting in a high risk of bias. Therefore, it is recommended that these models be updated and externally validated. The development of prospective, multi-center studies is encouraged to construct predictive models with low risk of bias and high clinical applicability, ultimately guiding evidence-based clinical practice. [ABSTRACT FROM AUTHOR]

Evaluating large-scale multi-objective problems is usually time-consuming due to the vast number of decision variables. However, most of the existing algorithms for large-scale multi-objective optimization require a significant number of problem evaluations to achieve satisfactory results, which makes the optimization process very inefficient. To address this issue, a fast interpolation-based multi-objective evolutionary algorithm is proposed in this paper for solving large-scale multi-objective optimization problems with high convergence speed and accuracy. In the proposed algorithm, decision variables are generated based on a small number of variables using an interpolation function. With this approach, only a small number of variables need to be optimized, so that the convergence speed can be greatly improved to make it possible to obtain satisfactory results with relatively low computation cost. The experimental results verified the superiority of our proposed algorithm over other state-of-the-art algorithms in terms of convergence speed and convergence accuracy on 108 test instances with up to 1000 decision variables. [ABSTRACT FROM AUTHOR]

In order to discover novel anti-inflammatory agents, a series of compounds obtained by appending chalcone moieties on dehydroepiandrosterone were designed and synthesized. All compounds were screened for their anti-inflammatory activity by using an ear edema model. Most of the synthesized compounds showed potent anti-inflammatory activity at 100 mg/kg with inhibition rates ranging from 27.94% to 56.83%. It is noteworthy that compound 4e exhibited the most pronounced anti-inflammatory activity of all the compounds with an activity of 56.83%, which was higher than that of celecoxib (47.14%). [ABSTRACT FROM AUTHOR]

ZrC dispersion-strengthened W exhibits high strength/ductility, low ductile-to-brittle transition temperature, and excellent thermal shock resistance, making it a promising candidate plasma-facing material for future fusion devices. In this study, surface modification of 0.5 wt.% ZrC dispersion-strengthened W (WZrC) under low energy and high fluence He plasma irradiation at high temperature was presented. Under the energy of 90 eV and fluence ranging from 6 × 1024 He·m−2–2 × 1026 He·m−2 He irradiation at 920 °C, a typical fuzz nanostructure appeared on the W matrix of WZrC. The thickness of fuzz layer is proportional to the square root of He irradiation fluence. The fuzz showed comparable thickness and structural features to pure W, indicating limited effects of the particle's addition on resistance to high fluence He irradiation at high temperatures. Under continuous He injection, the fuzz would grow extending onto the particle area, making the particle obscured. Besides, the erosion behavior of particles under He plasma irradiation has been investigated, which is thought to be dominated by a sputtering process. Under the He influence of 6 × 1024 He·m−2, only nanopores were observed in the surface region. With fluence increasing to 5 × 1025 He·m−2, the surface became relatively uneven with larger holes. W aggregated in spots and distributed on the surface of the particle, which might be the result of subthreshold sputtering and deposition. When fluence further increased to 2 × 1026 He·m−2, the particles were eroded completely and covered by the extended fuzz, forming cavities. In addition, distinctive layered nanotendrils were observed above the cavities, which were characterized to consist of inner W-riched skeletons and outer Zr-riched layers. It indicates that the layered nanotendrils should be the result of fuzz extension combined with particle sputtering/deposition. [ABSTRACT FROM AUTHOR]

In this work, we employed L-methionine (L-M) as the functionalized reagent of AuNPs for the colorimetric and UV–vis dual-mode detection of As3+, Cd2+, and Hg2+ ions with excellent selectivity and anti-interference. After adding the target ions, the functionalized AuNPs can be cross-linked together due to the As3+/Cd2+/Hg2+ ions reacting with amino N, carbonyl or hydroxyl O of L-methionine to form the coordination bonds, resulting in the aggregation of functionalized AuNPs and cause the different red-shifts of the SPR absorption peak and color changes of functionalized AuNPs solutions. The LODs of the colorimetric sensor are 10 ppb/13 ppb/4 ppb by naked eyes and 2.35 ppb/1.68 ppb/0.32 ppb by UV–vis spectroscopy with good linear relationships between the absorbance ratios (A633nm/A519nm, A645nm/A519nm and A665nm/A519nm) and As3+, Cd2+ and Hg2+ concentrations, which can be successfully applied to sense and detect As3+/Cd2+/Hg2+ pollutants in tap water, pond water, well water, and other domestic water sources. [ABSTRACT FROM AUTHOR]

Hydrothermal geothermal energy, as a widely distributed, large reserve and easily exploitable renewable source, can be used for both power generation and building heating. In this study, a numerical simulation of heat extraction performance is conducted based on monitoring well temperature data in a geothermal field in Xiong'an New Area. The effects of the reinjection temperature, injection flow rate, and reinjection rate on the outlet temperature and the reservoir temperature during a long-term operation are analyzed. The results indicate that the lower reinjection temperature can generate a critical disturbance scope for the thermal reservoir during the exploitation process. The impact scope on the thermal reservoir can reach 210.3 m at a reinjection temperature of 25 °C, which is not conducive to maintaining the outlet temperature of production wells in the long-term. The reinjection rate significantly affects both the horizontal and vertical temperature fields of the thermal reservoir. Under reinjection conditions of 30 °C and 40 kg/s, the horizontal and vertical impact scope of the thermal reservoir are 262.3 and 588.5 m, respectively. The reinjection rate is inversely related to the outlet temperature. A decrease from 100% to 70% in the reinjection rate can increase the outlet temperature by 4.21%. However, a decrease in the reinjection rate will lead to a decline in the groundwater level. Therefore, balancing the variation in outlet temperature and groundwater level is crucial in practical engineering. [ABSTRACT FROM AUTHOR]

Salmonella enteritis in poultry can result in reduced immune function, decreased growth rate, and increased mortality. Many farm salmonella strains have developed severe drug resistance and are less susceptible to multiple antibiotics. In the post-antibiotic era, it is of great significance to identify the mechanism of salmonella-induced enteritis in chicks to protect their health and ensure food safety. This article will elucidate the activation mechanism of NOD-like receptor protein 3 (NLRP3) inflammasomes in Salmonella enteritis and review the research on interventions targeting NLRP3 inflammasomes. [Display omitted] • The NLRP3 molecule plays a crucial role in salmonellosis enteritis in chicks. • The activation mechanism of the NLRP3 inflammasome and its role in avian Salmonella enteritis. • Progress in the treatment of S.Tm infection by intervening pyroptosis. [ABSTRACT FROM AUTHOR]

In recent decades, the term "ecosystem" has garnered substantial attention in scholarly and managerial discourse, featuring prominently in academic and applied contexts. While individual scholars have made significant contributions to the study of various types of ecosystem, there appears to be a research gap marked by a lack of comprehensive synthesis and refinement of findings across diverse ecosystems. This paper systematically addresses this gap through a hybrid methodology, employing bibliometric and content analyses to systematically review the literature from 1993 to 2023. The primary research aim is to critically examine theoretical studies on different ecosystem types, specifically focusing on business, innovation, and platform ecosystems. The methodology of this study involves a content review of the identified literature, combining quantitative bibliometric analyses to differentiate patterns and content analysis for in-depth exploration. The core findings center on refining and summarizing the definitions of business, innovation, and platform ecosystems, shedding light on both commonalities and distinctions. Notably, the research unveils shared characteristics such as openness and diversity across these ecosystems while highlighting significant differences in terms of participants and objectives. Furthermore, the paper delves into the interconnections within these three ecosystem types, offering insights into their dynamics and paving the way for discussions on future research directions. This comprehensive examination not only advances our understanding of business, innovation, and platform ecosystems but also lays the groundwork for future scholarly inquiries in this dynamic and evolving field. [ABSTRACT FROM AUTHOR]

Pythagorean fuzzy sets (PFSs) are a versatile tool for handling uncertain problems and have proven effective in practical applications. However, many existing Pythagorean fuzzy distance measures have counter-intuitive situations, making it challenging to measure the difference between PFSs accurately. To address this issue, we propose two distance measures for PFSs inspired by the Hellinger distance measure. We also explore the properties of the proposed measures and provide several comparative examples with existing measures for PFSs, illustrating their superior performance in processing fuzzy information from PFSs. Finally, we further develop a new decision-making method on top of the proposed measures and evaluate its performance in two applications. [ABSTRACT FROM AUTHOR]

Deep learning-based automatic and accurate 3D pancreas segmentation plays a significant role in medical diagnosis and disease treatment, which has received a lot of attention from the medical image processing community. 3D pancreas segmentation embraces two challenges: one is that the pancreas occupies a relatively small proportion in CT images, and there is a serious class imbalance problem between foreground and background, which makes it difficult to achieve accurate segmentation. Another issue is that existing models are overly reliant on computer memory. In response to the above issues, we propose a two-stage training framework to alleviate the influence of background on segmentation results while reducing memory consumption. Among which, different from previous methods that used the entire pancreas region as input, we design a Selective Overlap Method (SOM) that can learn contextual information while reducing computing costs by selecting the most appropriate number of overlapping slices. In addition, a novel 3D segmentation model named ResConv-3DUnet (RC-3DUNet) is integrated into this framework, which not only maintains the receptive field while drastically reducing parameter number but also uses the residual information between layers to strengthen edge attention and regularizes the output by designing the supervision weights of each decoder layer. Extensive experiments were conducted on the Medical Segmentation Decathlon (MSD) pancreas segmentation and the National Institutes of Health (NIH) pancreas segmentation datasets, demonstrating that our method has a superior trade-off between accuracy and lightweight than existing approaches. [ABSTRACT FROM AUTHOR]

Carrier-based polymeric membrane potentiometric sensors are an ideal tool for detecting ionic species. However, in the fabrication of these sensors, the screening of carriers still relies on empirical trial- and error-based optimization, which requires tedious and time-consuming experimental verification. In this work, computer-aided screening of carriers is applied in the preparation of polymeric membrane potentiometric sensors. Molecular docking is used to study the host–guest interactions between receptors and targets. Binding energies are employed as the standard to screen the appropriate carrier. As a proof-of-concept experiment, the antibiotic ciprofloxacin is selected as the target model. A series of supramolecular macrocyclic receptors including cyclodextrins, cucurbiturils and calixarenes are chosen as potential receptors. The proposed sensor based on the receptor calix[4]arene screened by molecular docking shows a lower detection limit of 0.5 μmol L−1 for ciprofloxacin. It can be expected that the proposed computer-aided screening technique of carriers can provide a simple but highly efficient method for the fabrication of carrier-based electrochemical and optical sensors. [ABSTRACT FROM AUTHOR]

Ocular involvement is not uncommon in patients with COVID-19. However, the incidence of COVID-19 ophthalmopathy in COVID-19 patients is still not clear. In this prospective case series study, we recruited 2445 consecutive cases presenting at Neuro-ophthalmology clinic of our Eye Center during the last resurgence of SARS-CoV-2 infection from 8 December 2022 to 15 March 2023 in China, 149 cases were diagnosed as COVID-19 ophthalmopathy, 87 cases were female, with a mean age of 43.2 years, and the mean follow-up time was 15.4 weeks. One hundred and twenty of 149 cases suffered from systemic symptoms mostly manifesting as fever, cough and muscle pain prior to or soon after ocular involvement. The most common COVID-19 ophthalmopathy was optic neuritis (51/149), followed by acute zonal occult outer retinopathy complex disease (31/149), uveitis (17/149), ocular mobility disorder-related (third, fourth, or sixth) cranial nerve neuritis (15/149), anterior ischaemic optic neuropathy (9/149), retinal artery occlusion (8/149), retinal microangiopathy including retinal haemorrhage and cotton wool spot (8/149), viral conjunctivitis (7/149), retinal vein occlusion (3/149), viral keratitis (2/149), ptosis (2/149), and other rare ocular diseases. Except 5 cases with central retinal artery occlusion, other 144 COVID-19 ophthalmopathy cases showed good response to steroid therapy. Our study revealed an incidence of 6.09% for COVID-19 ophthalmopathy in outpatients at our Neuro-ophthalmology clinic during last resurgence of COVID-19 in China, and demonstrated that SARS-CoV-2 infection could induce an initial onset or a relapse of ophthalmic diseases, and that ocular involvement might manifest as the initial or even the only presentation of COVID-19. [ABSTRACT FROM AUTHOR]

This study reports on the formation of self-organized silicon (Si) nanostructures by 75 eV helium (He) plasma irradiation at normal incidence without the presence of impurities. In contrast to the featureless surface after normal incidence argon (Ar) ion beam irradiation without the co-deposition of impurities, the Si surface exhibits the development of faceted nanostructures under 75 eV He plasma irradiation. The faceted structures are interspersed with valleys that extend in two orthogonal directions, imparting a mountain-like morphology to the surface. Our investigation verifies that the He bubbles align themselves along the direction perpendicular to the surface underneath these valleys. Furthermore, the presence of He bubbles induces distortion in the surface layer and leads to the formation of an amorphous Si layer. The underlying mechanism driving this surface evolution could be attributed to the instability induced by the presence of He bubbles. [ABSTRACT FROM AUTHOR]

Solid-state micro/nanopores play an important role in the sensing field because of their high stability and controllable size. Aiming at problems of complex processes and high costs in pore manufacturing, we propose a convenient and low-cost micro/nanopore fabrication technique based on the needle punching method. The thin film is pierced by controlling the feed of a microscale tungsten needle, and the size variations of the micropore are monitored by the current feedback system. Based on the positive correlation between the micropore size and the current threshold, the size-controllable preparation of micropores is achieved. The preparation of nanopores is realized by the combination of needle punching and chemical etching. First, a conical defect is prepared on the film with the tungsten needle. Then, nanopores are obtained by unilateral chemical etching of the film. Using the prepared conical micropores, resistive-pulse detection of nanoparticles is performed. Significant ionic current rectification is also obtained with our conical nanopores. It is proved that the properties of micro/nanopores prepared by our method are comparable to those prepared by the track-etching method. The simple and controllable fabrication process proposed here will advance the development of low-cost micro/nanopore sensors. [ABSTRACT FROM AUTHOR]

In a previous study, we proposed an open quantum network model of a quantum battery (QB) that possesses dark states owing to its structural exchange symmetries. While in a dark state, the QB is capable of storing an exciton without any environment-induced population losses. However, when the structural exchange symmetry is broken, the QB begins to discharge the exciton towards its exit site. In this article, we start by demonstrating that this QB is not only loss-free with respect to exciton population during the storage phase, but also with respect to the QB energy. We then explore the exciton population and energy transfer dynamics of the QB during the discharge phase over a wide range of site energies, bath temperatures, and bath reorganization energies. Our results shed light on how to optimize the QB's population and energy transfer dynamics for different purposes. [ABSTRACT FROM AUTHOR]

(1) Background: Copy number variation (CNV) is a critical component of genome structural variation and has garnered significant attention. High-throughput screening of the KCNJ15 gene has revealed a correlation between the CNV region and the growth traits of goats. We aimed to identify the CNV of the KCNJ15 gene in five goat breeds and analyze its association with growth characteristics. (2) Methods: We utilized 706 goats from five breeds: Guizhou black goat (GZB), Guizhou white goat (GZW), Bohuai goat (BH), Huai goat (HH), and Taihang goat (TH). To evaluate the number of copies of the KCNJ15 gene using qPCR, we analyzed the correlation between the CNV and growth characteristics and then used a universal linear model. The findings revealed variations in the distribution of different copy number types among the different goat breeds. (3) Results: Association analysis revealed a positive influence of the CNV in the KCNJ15 gene on goat growth. In GZB, individuals with duplication types exhibited superior performance in terms of cannon bone circumference (p < 0.05). In HH, individuals with duplication types exhibited superior performance in terms of body slanting length (p < 0.05). Conversely, normal TH demonstrated better body height and body weight (p < 0.05), while in GZW, when CN = 3, it performed better than other types in terms of body weight and chest circumference (p < 0.05). However, in BH, it had no significant effect on growth traits. (4) Conclusions: We confirmed that the CNV in the KCNJ15 gene significantly influences the growth characteristics of four distinct goat breeds. The correlation between KCNJ15 gene CNVs and goat growth traits offers valuable insights to breeders, enabling them to employ precise and efficient breeding methods that enhance livestock welfare, productivity, and overall economic benefits in the industry. [ABSTRACT FROM AUTHOR]

This article, published in the Chemistry of Natural Compounds journal, discusses the identification of potent inhibitors targeting Protein Tyrosine Phosphatase 1B (PTP1B). PTP1B is an enzyme that plays a role in insulin and leptin signaling pathways and is considered a promising therapeutic target for the management of Type 2 Diabetes. The researchers synthesized and tested a series of derivatives of Ursolic acid (UA) for their PTP1B inhibitory activity. Compound 1f exhibited the most pronounced activity, with an inhibition rate of 56.22%, providing significantly improved activity compared to UA. Molecular modeling studies also supported the binding ability of compound 1f with PTP1B. The study suggests that further structural optimization could lead to the development of new potential therapeutic agents for the treatment of Type 2 Diabetes. [Extracted from the article]

High-order harmonics in solids provide a method of analyzing the intraband and interband dynamics of a solid driven by an ultrafast laser. This study analyzed the contributions of intraband and interband dynamics based on angle-resolved high-order harmonics. According to the simulations and experiments, we found that the angular divergences of the harmonics have an evident boundary at the bandgap when the laser is polarized along the asymmetric direction, which is primarily invoked by the interplay of an interband transition and an intraband electron movement, and the intraband and interband dynamics have different sensitivities of the spatial phase of driving laser. [ABSTRACT FROM AUTHOR]

The study specifically focused on the Hongliulin mining area, where a total of 40 soil samples were meticulously collected and analyzed from within a 1000 m radius extending from the tailings dam. The findings revealed that soil pH within the 0–1000 m range generally leaned towards the alkaline side. In terms of soil nutrient content, encompassing factors such as soil organic matter (SOM), total nitrogen (TN), total phosphorus (TP), total potassium (TK), alkali nitrogen (AK), available phosphorus (AP), and quick-acting potassium (AK), the variations fell within the following ranges: 2.23–13.58 g/kg, 0.12–0.73 g/kg, 0.18–1.15 g/kg, 9.54–35.82 g/kg, 2.89–6.76 mg/kg, 3.45–11.25 mg/kg, and 5.86–130.9 mg/kg. Collectively, these values indicate relatively low levels of soil nutrients. Within the 0–500 m range of soil samples, the average concentrations of Cd, Hg, Pb, and As were 0.778, 0.198, 24.87, and 17.92 mg/kg, respectively. These concentrations exceeded the established soil background values of Shaanxi Province and emerged as the primary pollutants in the study area. Within this same range, the mean values of eight toxic metals (Pi) were ranked in the following descending order: 1.726 (Hg), 1.400 (As), 1.129 (Cr), 1.109 (Pb), 0.623 (Zn), 0.536 (Cd), 0.309 (Cu), and 0.289 (Ni). With the exception of Hg, As, Cr, and Pb, which exhibited slight pollution, the other toxic metals were found to be within acceptable pollution limits for this sampling range, in line with the results obtained using the geo-accumulation index method. The average potential ecological risk index for the eight toxic metals in the study area stood at 185.0, indicating a moderate overall pollution level. When assessing individual elements, the proportions of ecological risk attributed to Hg, As, Pb, and Cd were 34.57%, 27.44%, 25.11%, and 23.11%, respectively. This suggests that the primary potential ecological risk elements in the study area are Hg and As, followed by Cd and Pb. Notably, toxic metals Hg and Pb, as well as As and Pb, exhibited significant positive correlations within the sampling area, suggesting a common source. An analysis of the relationship between soil physicochemical properties and toxic metals indicated that soil pH, SOM, TN, and TP were closely linked to toxic metal concentrations. The toxic metal elements in the research area's soil exhibit moderate variability (0.16 < CV < 0.36) to high variability (CV > 0.36). Within the range of 0–200 m, the CV values for Cd and Hg exceed 1, indicating a high level of variability. The coefficient of variation for SOM, TP, AP, AK and TK is relatively high with the of 2.93, 2.36, 2.36, 21.01, 7.54. The soil in the sampling area has undergone significant disturbances due to human activities, resulting in toxic metal pollution and nutrient deficiencies. [ABSTRACT FROM AUTHOR]

Rockbursts are hazardous phenomena of sudden and violent rock failure in deep underground excavations under high geostress conditions, which poses a serious threat to geotechnical engineering. The occurrence of rockbursts is influenced by a combination of factors. Therefore, it is necessary to find an efficient method to assess rockburst grades. In this paper, we propose a novel method that enhances the VIKOR method using a novel combination of weight and generalized weighted Mahalanobis distance. The combination weights of the evaluation indicators were calculated using game theory by combining subjective experience and objective data statistical characteristics. By introducing the generalized weighted Mahalanobis distance, the VIKOR method is improved to address the issues of inconsistent dimensions, different importance, and inconsistent correlation among indicators. The proposed method can deal with the complexity of the impact factors of rockburst evaluation and classify the rockburst intensity level. The results show that the accuracy of the improved VIKOR method with the distance formula is higher than that of the unimproved VIKOR method; the evaluation accuracy of the improved VIKOR method with the generalized weighted Mahalanobis distance is 91.67%, which outperforms the improved VIKOR methods with the Euclidean and Canberra distances. This assessment method can be easily implemented and does not depend on the discussion of the rockburst occurrence mechanism, making it widely applicable for engineering rockburst evaluation. [ABSTRACT FROM AUTHOR]

This study aimed to investigate the molecular mechanism of sporotrichosis and identify possible novel therapeutic targets. Total RNA was extracted from skin lesion samples from sporotrichosis patients and used to construct a long-chain RNA transcriptome library and miRNA transcriptome library for whole transcriptome sequencing. The differentially expressed genes (DEGs) between the groups were identified, and then Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and Gene Set Enrichment Analysis enrichment analyses were performed based on the DEGs. An lncRNA-miRNA-mRNA ceRNA network was constructed. The expressions of JAK/STAT pathway-related proteins were detected in the patient and control tissues using RT-qPCR and Western blot analysis. Enrichment analysis showed that the DEGs were mainly enriched in various infectious diseases and immune response-related signaling pathways. Competing endogenous RNA network analysis was performed and identified the hub lncRNAs, miRNAs, and mRNAs. Compared with the control group, the mRNA expressions of SOCS3, IL-6, and JAK3 were significantly upregulated, while the expression of STAT3 did not change significantly. Also, the protein expressions of SOCS3, IL-6, JAK3, and STAT3, as well as phosphorylated JAK3 and STAT3, were significantly upregulated. We identified 671 lncRNA DEGs, 3281 mRNA DEGs, and 214 miRNA DEGs to be involved in Sporothrix globosa infection. The study findings suggest that the JAK/STAT pathway may be a therapeutic target for sporotrichosis. [ABSTRACT FROM AUTHOR]

The developing countries rely heavily on imports of capital goods to spur economic growth. When the economy grows, energy consumption rises, adversely impacting climate change. The low levels of renewable energy share in total energy consumption, developing nations confront a difficult task in achieving the SDGs targets related to an increase in renewable energy share and access to affordable, reliable, and modern energy. Finding solutions to increase renewable energy usage is critical. International trade is an unavoidable part of development, prompting us to consider the impact of imports on renewable energy usage. This study explores the effects of imports of capital goods from China, EU and USA on renewable energy consumption in developing countries by using panel data from 20 countries spanning 2000–2018. It is found that capital goods imported from China in developing countries negatively impact renewable energy consumption while imports from EU have a positive impact on renewable energy consumption. However, in the case of US it is found negative but insignificant. The role of economic, social, and political globalization is explored, and it is found that three types of globalization are positively and significantly linked with renewable energy consumption. Thus, this study recommends that trade policies complement domestic efforts toward increasing renewable energy production and consumption in developing countries. [ABSTRACT FROM AUTHOR]

Aryl hydrocarbon receptor (AhR) agonists are potential therapeutic agents for ulcerative colitis (UC). Indirubin (IDR), which is a natural AhR ligand approved for leukemia treatment, ameliorates dextran sulfate sodium (DSS)-induced colitis in mice. However, the therapeutic mechanisms of IDR are unknown, limiting its application. This study explores the therapeutic mechanisms of IDR in DSS-induced colitis using transcriptomic analysis. Male BALB/c mice were categorized to six groups: normal, DSS model (2% DSS), IDR treatment (10, 20 and 40 mg/kg), and sulfasalazine (520 mg/kg) groups. The drugs were intragastrically administered for 7 consecutive days. The disease activity index (DAI) was recorded. After euthanasia, the colon length was measured, and histopathological examination, immunohistochemistry staining using F4/80, and colonic transcriptomic analysis were conducted. Quantitative reverse transcription-polymerase chain reaction (qRT-PCR) and western blotting (WB) were conducted to verify our findings. Compared with DSS, IDR treatment decreased the DAI score by 64.9% and increased colon length by 26.2%. Moreover, it alleviated mucosal injury and reduced macrophage infiltration. Transcriptomic analysis identified several downregulated genes (Igkvs and Nlrp3), as well as Nlrp3/Il1β and hemoglobin gene networks, after IDR treatment. The abundances of NF-κB p65, NLRP3, IL-1β, and HBA decreased by 69.1, 59.4, 81.1, and 83.0% respectively, after IDR treatment. Apart from the well-documented NF-κB signalling pathway, IL-17A, and NLRP3-IL-1β, the suppression of haemoglobin-induced lipid peroxidation could be a previously unknown mechanism of IDR. Our study can help improve its application for UC treatment. [ABSTRACT FROM AUTHOR]

In the last decade, low-quality unconventional oil and gas resources have become the primary source for domestic oil and gas storage and production, and hydraulic fracturing has become a crucial method for modifying unconventional reservoirs. This paper puts forward a framework for predicting hydraulic fracture parameters. It combines eXtreme Gradient Boosting and Bayesian optimization to explore data-driven machine learning techniques in fracture simulation models. Analyzing fracture propagation through mathematical models can be both time-consuming and costly under conventional conditions. In this study, we predicted the physical parameters and three-dimensional morphology of fractures across multiple time series. The physical parameters encompass fracture width, pressure, proppant concentration, and inflow capacity. Our results demonstrate that the fusion model applied can significantly improve fracture morphology prediction accuracy, exceeding 0.95, while simultaneously reducing computation time. This method enhances standard numerical calculation techniques used for predicting hydraulic fracturing while encouraging research on the extraction of unconventional oil and gas resources. [ABSTRACT FROM AUTHOR]

The three-phase imbalance in low-voltage distribution networks (LVDNs) seriously threatens the security and stability of the power system. At present, a standard solution is automatic phase commutation, but this method has limitations because it does not address the branch imbalance and premature convergence or instability of the commutation algorithm. Therefore, this paper proposes a novel refined regulation commutation system, combined with a modified optimized commutation algorithm, and designs a model and simulation for feasibility verification. The refined regulatory model incorporates branch control units into the traditional commutation system. This effectively disperses the main controller's functions to each branch and collaborates with intelligent fusion terminals for precise adjustment. The commutation algorithm designed in this paper, combined with the above model, adopts strategies such as symbol encoding, cubic chaotic mapping, and adaptive adjustment based on traditional genetic algorithms. In addition, in order to verify the effectiveness of the proposed method, this paper establishes a mathematical model with the minimum three-phase imbalance and commutation frequency as objectives and establishes a simulation model. The results of the simulation demonstrate that this method can successfully lower the three-phase imbalance of the low-voltage distribution network. It leads to a decrease of the main circuit's three-phase load imbalance rate from 27% to 6% and reduces each branch line's three-phase imbalance ratio to below 10%. After applying the method proposed in this paper, the main and branches circuit three-phase imbalance are both lower than the limit ratio of the LVDNs, which can improve the quality and safety of electricity consumption. Additionally, the results also prove that the commutation algorithm under this method has faster convergence speed, better application effect, and better stability, which has promotion and application value. [ABSTRACT FROM AUTHOR]

In contrast to conventional particles that have isotropic surfaces, Janus ("two-faced") particles have anisotropic surfaces, which leads to novel physicochemical properties and functional attributes. Janus particles with differing compositions, structures, and functional attributes have been prepared using a variety of fabrication methods. Depending on their composition, Janus particles have been classified as inorganic, polymeric, or polymeric/inorganic types. Recently, there has been growing interest in preparing Janus particles from biological macromolecules to meet the demand for a more sustainable and environmentally friendly food and pharmaceutical supply. At interfaces, Janus particles exhibit the characteristics of both surfactants and Pickering stabilizers, and so their behavior can be described using adsorption theories developed to describe these surface-active substances. Research has highlighted several potential applications of Janus particles in food and medicine, including emulsion formation and stabilization, toxin detection, antimicrobial activity, drug delivery, and medical imaging. Nevertheless, further research is needed to design and fabricate Janus particles that are suitable as functional ingredients in the food and biomedicine industries. [ABSTRACT FROM AUTHOR]

Fluorine-doped tin oxide (FTO) thin films were prepared by a radio frequency magnetron sputtering technique. The defects and charge carrier transport behavior in FTO thin films were evaluated during the transition process from amorphous to nanocrystalline structures. The stable lattice structure in FTO thin films was obtained as the annealing temperature reached 400 ° C. Positron annihilation results indicated that defect evolution in the FTO thin films was shown in two stages, formation and reduction of vacancies/vacancy clusters. The carrier mobility of the FTO thin films annealed at 600 ° C was enhanced twice the amount than that of the unannealed samples. The correlation between the results obtained from positron annihilation and the Hall effect revealed the importance of defect scattering in deciding the charge carrier mobility. A defect scattering mechanism was proposed to interpret the noticeable increment of carrier mobility in FTO thin films after thermal treatment. [ABSTRACT FROM AUTHOR]

This study explores important parameters for achieving a high-level positional control of DNA-nanoparticle hybrid structures by drop-casting onto a pre-structured silicon surface, in which the active adsorption sites were defined using electron beam lithography. By confining the adsorption sites to the scale of the DNA origami, we create multi-dimensional patterns and study the effect of diffusion and hybrid nanostructure concentration in the liquid on site occupation. We also propose a physical diffusion model that highlights the importance of surface diffusion in facilitating the adsorption of hybrid nanostructure onto active sites, particularly for two and one-dimensional adsorption sites. Our study shows prominent results of the hybrid nanostructure's selective adsorption, indicating high adsorption efficiency and precise control over the position, as well as the spatial orientation. We anticipate similar results in related systems, both in terms of different surfaces and similar DNA structures. Overall, our findings offer promising prospects for the development of large-scale nanoarrays on micrometer-scale surfaces with nanometer precision and orientation control. [ABSTRACT FROM AUTHOR]

Organic photodetectors have attracted increasing attention in the scenario of low-cost imaging, health monitoring, and near-infrared sensing. However, relatively high dark current and trap density block the sensitivity for organic photodetectors. In this manuscript, a simple yet effective strategy is proposed to enhance the detectivity of organic photodetectors by incorporating a non-conjugated polymer additive of polystyrene into the functional layers. Systematic morphological investigation reveals that this strategy can not only enable suppressed amorphous phase but also effectively tune the phase separation in the bulk heterojunction blends. Electrical results suggest the suppressed trap density in optimized organic photodetectors. Consequently, a dark current density of 5.06 × 10−10 A cm−2 is achieved for PM6:Y6-BO-based organic photodetectors, showing a peak detectivity of 6.38 × 1013 cm Hz1/2 W−1 at 850 nm. This strategy is also applicable in various representative organic-semiconductor systems, including PTB7-Th:PC71BM and P3HT:PC61BM blends, superior to other optimization techniques. [ABSTRACT FROM AUTHOR]

Dempster-Shafer theory (DST) has attracted widespread attention in many domains owing to its powerful advantages in managing uncertain and imprecise information. Nevertheless, counterintuitive results may be generated once Dempster's rule faces highly conflicting pieces of evidence. In order to handle this flaw, a new belief logarithmic similarity measure (BLSM) based on DST is proposed in this paper. Moreover, we further present an enhanced belief logarithmic similarity measure (EBLSM) to consider the internal discrepancy of subsets. In parallel, we prove that EBLSM satisfies several desirable properties, like bounded, symmetry and non-degeneracy. Finally, a new multi-source data fusion method based on EBLSM is well devised. Through its best performance in two application cases, specifically those pertaining to fault diagnosis and target recognition respectively, the rationality and effectiveness of the proposed method is sufficiently displayed. [ABSTRACT FROM AUTHOR]

FeCrAl alloy is one of potential candidates for accident‐tolerant‐fuel (ATF)‐cladding materials due to its excellent oxidation and corrosion resistance at accident temperature, combining good mechanical properties at service temperature. Alloying strategy is an important way for improving comprehensive properties of FeCrAl alloy through the precipitation of fine Laves phase. Zr alloying can stabilize the Laves phase due to its lower diffusion coefficient and solubility in body‐centered‐cubic ferrite matrix. Herein, it is found that Zr addition changes the dynamic precipitation features of Laves phase in FeCrAl alloy during high‐temperature deformation, from only one type of Fe2M (M = Nb, Mo, Ta) Laves phase to Fe2Zr combining Fe2M‐type Laves phase. The Fe2Zr‐type Laves phase precipitates dynamically first, and the interface precipitates between which with ferrite matrix creates more nucleation sites for subsequent precipitation of Fe2M Laves phase. The results can be possibly applied for alloy design and microstructure tailoring in series of FeCrAl alloys used for ATF cladding in the near future. [ABSTRACT FROM AUTHOR]

Abstract Dempster-Shafer theory (DST) has attracted wide attention in many fields thanks to its strong advantages over probability theory. Whereas the uncertainty measure of basic belief assignment (BBA) in DST is an open and essential problem. The main goal of this article is to propose a new belief Rényi entropy for the uncertainty measure of BBA, which is inspired by generalized Rényi entropy in DST. The proposed belief Rényi entropy satisfies some desirable properties of uncertainty measure. Furthermore, the proposed belief Rényi entropy can be degraded to Rényi entropy when BBA is transformed into a probability distribution. Finally, a new decision-making method is designed based on the proposed belief Rényi entropy. The validity of the proposed belief entropy is verified by some numerical examples and its application to decision-making. [ABSTRACT FROM AUTHOR]

In the field of Internet of Things (IoT), terminal security has always been an extremely important independent research topic. In the terminal security research, in addition to the security enhancement of terminal entities, the security status evaluation of terminal security has also become an independent subset of the security research in the IoT field. However, it should also be noted that the security attributes of IoT terminals can include many aspects, so judging the security of IoT terminals based on the overall security form is not enough for the security of terminal entities. This paper introduces the concept of volatility from the overall situation assessment to the meta attributes that constitute the overall security situation, and preliminarily realizes the construction of a concise model based on historical data to judge the meta attributes that may affect the overall security in the future. At the same time, a concise verification system is built based on the application scenario of the power IoT terminals currently under research to preliminarily realize trend prediction, further expand the trust evaluation of IoT terminals, and clarify the direction of further research. [ABSTRACT FROM AUTHOR]

Aggregate stability is a key factor in the evaluation of soil structure and erosion resistance, which is largely influenced by soil electric field and particle interaction. However, there are few studies on how different organic and inorganic soil conditioners change the surface electric field and interaction force of reclaimed soil to improve the aggregate stability. Therefore, a five-year field experiment was conducted to quantitatively study the effects of FeSO4 (TM), organic fertilizer (TO), fly ash (TF), maturing agent + organic fertilizer (TMO) and fly ash + organic fertilizer (TFO), compared with control (CK) treatment, on the reclaimed soil internal force and the aggregate crushing strength. The results showed that the reclaimed soil surface potential and electric field intensity increased after 5 years of application of organic and inorganic soil conditioners. Under the same electrolyte concentration and electric field conditions, the crushing strength of aggregates (<5 μm) treated with TFO, TMO, TO, TF and TM decreased by 43.70%, 35.51%, 25.97%, 8.28% and 5.49%, respectively, compared with the control treatment, and the combination of organic and inorganic treatment (TFO and TMO) had a better effect on improving the aggregate crushing resistance. With the application of soil conditioners, the reclaimed soil DLVO force and net resultant force gradually decreased, and the order of magnitude was TFO < TMO < TO < TF < TM < CK, indicating that the application of organic and inorganic soil conditioners enhanced the van der Waals attractive force and net attractive force between reclaimed soil particles, and reduced the net repulsive force between particles. The theoretical calculation results of the reclaimed soil internal force well explain the experimental results of aggregate stability against crushing, and the relationship between aggregate crushing strength and net resultant force is exponential (p < 0.01). Generally speaking, the soil conditioners increase the net attractive force between particles, reduce the possibility of violent crushing of aggregates due to the increase of electric field intensity and improve the aggregate structural stability, among which the combined application of organic and inorganic soil conditioners has a better improvement effect. The results of this study will lay a theoretical foundation for clarifying the improvement of different soil conditioners on the reclaimed soil structural stability and erosion resistance. [ABSTRACT FROM AUTHOR]

Wind erosion is one of the major meteorological hazards in Ningxia, and climate change has caused changes in wind erosion–climatic erosion activity in recent years. This study uses the wind erosion climate factor (C) proposed by the Food and Agriculture Organization of the United Nations to assess the impact of climate change on wind erosion–climate erosion, and the results show that (1) the distribution of wind erosion degree in Ningxia region is central > northern > southern. Seasonally, it is higher in spring and winter, and lower in summer and autumn. (2) Climate change has more influence on spring, autumn and winter, and less influence on summer. (3) The center of gravity is mainly located at the junction of central and northern Ningxia, and the center of gravity migrates through four migration stages—northeast–southwest–northeast–southwest—on the annual scale, and four migration stages—northwest–northeast–southeast—on the seasonal and monthly scales. The migration rate in the cold season is greater than that in the warm season. (4) The wind erosion climate factor index is influenced by sunshine hours, average temperature, average humidity, average wind speed and total precipitation, and the degree of influence has spatial and temporal variability, among which the wind erosion climate factor index is the most sensitive to the influence of average wind speed. (5) The wind erosion climate factor indices are positively correlated with NAO, AO, PDO and SOI indices, and negatively correlated with MEI and ENSO indices, and there are resonance cycles of different time scales. [ABSTRACT FROM AUTHOR]

Cr–Al-based oxynitride materials have attracted significant attention as hard protective coatings for decades. However, knowledge of the influence of the constituents on oxidation behavior is limited. Here, Cr–Al–O–N coatings with various Cr/Al ratios prepared using cathodic arc evaporation were studied with respect to their microstructure, mechanical properties, and oxidation behavior. With a decrease in the Cr/Al ratio, the coatings yielded a phase evolution from face-centered cubic CrN to rock salt-type cubic (Cr, Al) 2 O 3 to a wurtzite-type hexagonal AlN structure. The cubic structured coatings showed a comparable indentation hardness, much higher than that of the Cr-free Al–O–N coating with a wurtzite structure. Thermogravimetric together with differential scanning calorimetric (TG-DSC) analysis revealed that the ternary Cr–O–N and Al–O–N coatings were more susceptible to oxidation than the quaternary Cr–Al–O–N coatings. Moreover, isothermal oxidation experiments indicated that the addition of 66 at.% Al within the metallic species gives rise to the growth of an Al-rich oxide scale on top of the Cr–Al–O–N coating. However, this oxide scale containing substantial voids cannot prevent the underlying coating from oxidation. Oxidation kinetics study illustrates that the oxidation activation energies of (Cr x Al 1−x)–O–N coatings with x = 1.00, 0.76, 0.58, 0.33, and 0 are 252.3, 305.2, 370.7, 303.8, and 297.7 kJ/mol, respectively. The best oxidation resistance was obtained by the (Cr 0.58 Al 0.42)–O–N coating, whereas the Al-containing (Cr 0.33 Al 0.67)–O–N coating showed inferior oxidation resistance owing to its high intrinsic oxygen fraction. [ABSTRACT FROM AUTHOR]

The worldwide prevalence of antibiotic-resistant bacteria (ARB) and antibiotic resistance genes (ARGs) have become one of the most urgent issues for public health. Thus, it is critical to explore more sustainable methods with less toxicity for the long-term removal of both ARB and ARGs. In this study, we fabricated a novel material by encapsulating zinc oxide (ZnO) nanoflowers and activated carbon (AC) in an alginate biopolymer. When the dosage of ZnO was 1.0 g (≈2 g/L), the composite beads exhibited higher removal efficiency and a slight release of Zn2+ in water treatment. Fixed bed column experiments demonstrated that ZnO/AC alginate beads had excellent removal capacities. When the flow rate was 1 mL/min, and the initial concentration was 107 CFU/mL, the removal efficiency of ARB was 5.69-log, and the absolute abundance of ARGs was decreased by 2.44–2.74-log. Moreover, the mechanism demonstrated that ZnO significantly caused cell lysis, cytoplasmic leakage, and the increase of reactive oxygen species induced subsequent oxidative stress state. These findings suggested that ZnO/AC alginate beads can be a promising material for removing ARB and ARGs from wastewater with eco-friendly and sustainable properties. [ABSTRACT FROM AUTHOR]

Here, a series of ursolic acid (UA) derivatives were identified as potential PTP1B enzyme inhibitors. All of the tested compounds showed potent PTP1B inhibitory activity (87.79–96.80%) at a concentration of 20 μg/mL and dose-dependently inhibited PTP1B enzyme with IC50 values ranging from 4.15 ± 0.01 to 14.10 ± 0.45 μM. Compound 11e showed the best PTP1B inhibitory potency, with IC50 values of 4.15 ± 0.01 μM, which was slightly lower than that of the positive control. Molecular docking simulation and analysis suggested that compound 11e has a good binding interaction with the active pocket. [ABSTRACT FROM AUTHOR]

Here, a series of ursolic acid (UA) derivatives were identified as potential protein tyrosine phosphatase 1B (PTP1B) enzyme inhibitors. All of the tested compounds showed potent PTP1B inhibitory activity (47.01–67.89%). Compound 2d (67.89%) exhibited the highest activity of all the synthesized compounds, which showed higher activity than observed for the positive control UA (51.13%). Molecular docking simulation and analysis suggested that compound 2d has a good binding interaction with the active pocket. [ABSTRACT FROM AUTHOR]

A rockburst is a dynamic disaster that may result in considerable damage to mines and pose a threat to personnel safety. Accurately predicting rockburst intensity is critical for ensuring mine safety and reducing economic losses. First, based on the primary parameters that impact rockburst occurrence, the uniaxial compressive strength ( σ c ), shear–compression ratio ( σ θ / σ c ), compression–tension ratio ( σ c / σ t ), elastic deformation coefficient ( W et ), and integrity coefficient of the rock ( K V ) were selected as the evaluation indicators. Second, an improved game theory weighting method was introduced to address the problem that the combination coefficients calculated using the traditional game theory weighting method may result in negative values. The combination of indicator weights obtained using the analytic hierarchy process, the entropy method, and the coefficient of variation method were also optimized using improved game theory. Third, to address the problem of subjectivity in the traditional unascertained measurement using the confidence identification criterion, the distance discrimination idea of the Minkowski distance was used to optimize the identification criteria of the attributes in an unascertained measurement and was applied to rockburst prediction, and the obtained results were compared with the original confidence identification criterion and the original distance discrimination. The results show that the improved game theory weighting method used in this model makes the weight distribution more reasonable and reliable, which can provide a feasible reference for the weight determination method of rockburst prediction. When the Minkowski distance formula was introduced into the unascertained measurement for distance discrimination, the same rockburst predictions were obtained when the distance parameter (p) was equal to 1, 2, 3, and 4. The improved model was used to predict and analyze 40 groups of rockburst data with an accuracy of 92.5% and could determine the rockburst intensity class intuitively, providing a new way to analyze the rockburst intensity class rationally and quickly. [ABSTRACT FROM AUTHOR]

The electromagnetic shielding (EMS) fabric is an important electromagnetic protection product, which is widely applied in various fields. The improvement of its shielding effectiveness (SE) has always been the focus of research. This article proposes to implant a metamaterial structure of a "split-ring resonator (SRR)" in the EMS fabrics, so that the fabric not only maintains the porous and lightweight characteristics, but also obtains the SE improvement. With the help of the invisible embroidery technology, stainless-steel filaments were used to implant hexagonal SRRs inside the fabric. The effectiveness and influencing factors of the SRR implantation were described by testing the SE of the fabric and analyzing the experimental results. It was concluded that the SRR implantation inside the fabric can effectively improve the SE of the fabric. For the stainless-steel EMS fabric, the increase amplitude of the SE reached between 6 dB and 15 dB in most frequency bands. The overall SE of the fabric showed a decrease trend with the reduction of the outer diameter of the SRR. The decrease trend was sometimes fast and sometimes slow. The decreasing amplitudes were different in various frequency ranges. The number of embroidery threads had a certain effect on the SE of the fabric. When other parameters remained unchanged, the increase of the diameter of the embroidery thread resulted in the increase of the SE of the fabric. However, the overall improvement was not significant. Finally, this article also points out that other influencing factors of the SRR need to be explored, and the failure phenomenon may occur under certain situations. The proposed method has the advantages of the simple process, convenient design, no pore formation, SE improvement retaining the original porous characteristics of the fabric. This paper provides a new idea for the design, production, and development of new EMS fabrics. [ABSTRACT FROM AUTHOR]

Background: CD36 is the receptor of oxidised low-density lipoprotein (OxLDL) in renal tubular epithelial cells. Nuclear factor erythroid 2-related factor 2 (Nrf2) is the key factor in the activation of the Nrf2 signalling pathway and the regulation of oxidative stress. Kelch-like ECH-associated protein 1 (Keap1) is known as an Nrf2 inhibitor. Methods: We used OxLDL and Nrf2 inhibitors at different concentrations and durations to treat renal tubular epithelial cells; the expression of CD36 and cytoplasmic and nucleic Nrf2 and E-cadherin in those cells were observed by Western blot and reverse-transcription polymerase chain reaction. Results: The protein levels of Nrf2 decreased in expression after 24 hours of OxLDL treatment. At the same time, the Nrf2 protein level in the cytoplasm did not change significantly compared with that of the control group, and the Nrf2 protein level expression in the nucleus increased. Both the messenger ribonucleic acid (mRNA) and protein expression of CD36 decreased following the treatment of cells with the Nrf2 inhibitor Keap1. Kelch-like ECH-associated protein 1 was overexpressed, and CD36 mRNA and protein expression were decreased in OxLDL-treated cells. Following the overexpression of Keap1, E-cadherin expression was reduced in NRK-52E cells. Conclusion: Nuclear factor erythroid 2-related factor 2 can be activated by OxLDL; however, it can only alleviate OxLDL-induced oxidative stress by transferring from the cytoplasm to the nucleus. Additionally, Nrf2 may play a protective role by upregulating CD36. [ABSTRACT FROM AUTHOR]