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Copper (Cu) and nitrogen (N) co-doped titanium dioxide (TiO2) loaded catalysts were synthesized through the sol–gel process. Butyl titanate was used as the precursor, while urea and blue vitriol served as the N and Cu sources, respectively. These materials were applied to foam ceramics using the dip-coating method, which was followed by a photocatalytic oxidation test was carried out using an RhB solution to simulated dye wastewater. The catalysts were characterized via scanning electron microscopy, X-ray diffraction, and ultraviolet–visible spectrophotometry. The results revealed that the modified TiO2 was well dispersed on the foam ceramic surface, with all nanoparticles exhibiting an anatase phase structure. Additionally, the visible light responsiveness of the TiO2 was optimal. The study further investigated the effects of Cu and N–TiO2 catalysts on the photocatalytic oxidation of dyeing wastewater under UV light. [ABSTRACT FROM AUTHOR]

Glioma is the most common malignant tumor of the central nervous system, with EZH2 playing a crucial regulatory role. This study further explores the abnormal expression of EZH2 and its mechanisms in regulating glioma progression. Additionally, it was found that IHMT-337 can potentially be a therapeutic agent for glioma. The prognosis, expression, and localization of EZH2 were determined using bioinformatics, IHC staining, Western blot (WB) analysis, and immunofluorescence (IF) localization. The effects of EZH2 on cell function were assessed using CCK-8 assays, Transwell assays, and wound healing assays. Public databases and RT-qPCR were utilized to identify downstream targets. The mechanisms regulating these downstream targets were elucidated using MS-PCR and WB analysis. The efficacy of IHMT-337 was demonstrated through IC50 measurements, WB analysis, and RT-qPCR. The effects of IHMT-337 on glioma cells in vitro were evaluated using Transwell assays, EdU incorporation assays, and flow cytometry. The potential of IHMT-337 as a treatment for glioma was assessed using a blood–brain barrier (BBB) model and an orthotopic glioma model. Our research confirms significantly elevated EZH2 expression in gliomas, correlating with patient prognosis. EZH2 facilitates glioma proliferation, migration, and invasion alongside promoting SLC12A5 DNA methylation. By regulating SLC12A5 expression, EZH2 activates the WNK1-OSR1-NKCC1 pathway, enhancing its interaction with ERM to promote glioma migration. IHMT-337 targets EZH2 in vitro to inhibit WNK1 activation, thereby suppressing glioma cell migration. Additionally, it inhibits cell proliferation and arrests the cell cycle. IHMT-337 has the potential to cross the BBB and has successfully inhibited glioma progression in vivo. This study expands our understanding of the EZH2-SLC12A5 axis in gliomas, laying a new foundation for the clinical translation of IHMT-337 and offering new insights for precision glioma therapy. [ABSTRACT FROM AUTHOR]

Against the backdrop of global warming and increased rainfall, the hazards and potential risks of landslides are increasing. The rapid generation of a landslide inventory is of great significance for landslide disaster prevention and reduction. Deep learning has been widely applied in landslide identification due to its advantages in terms of its deeper model structure, high efficiency, and high accuracy. This article first provides an overview of deep learning technology and its basic principles, as well as the current status of landslide remote sensing databases. Then, classic landslide deep learning recognition models such as AlexNet, ResNet, YOLO, Mask R-CNN, U-Net, Transformer, EfficientNet, DeeplabV3+ and PSPNet were introduced, and the advantages and limitations of each model were extensively analyzed. Finally, the current constraints of deep learning in landslide identification were summarized, and the development direction of deep learning in landslide identification was analyzed. The purpose of this article is to promote the in-depth development of landslide identification research in order to provide academic references for the prevention and mitigation of landslide disasters and post-disaster rescue work. The research results indicate that deep learning methods have the characteristics of high efficiency and accuracy in automatic landslide recognition, and more attention should be paid to the development of emerging deep learning models in landslide recognition in the future. [ABSTRACT FROM AUTHOR]

Phase‐change‐materials (PCMs) integrated photonics have attracted extensive attention in the field of optical neural networks. However, present PCMs‐integrated photonics are still far from meeting the requirements in real‐world applications due to its unsatisfactory endurance (<3000 cycles) and extinction ratio (ER<20 dB). Here, ultrahigh endurance (>30 000 cycles) and large ER (≥50 dB) are achieved in the photonic device by introducing a trench structure to the indium tin oxide (ITO) heater and utilizing tin‐doped Ge2Sb2Te5 (Sn‐GST) as PCMs. This performance represents a landmark in the PCMs‐integrated photonics, since it solves the problem of poor endurance of ITO heaters and can be comparable to the state‐of the‐art devices in terms of endurance and ER. This excellent endurance and ER stem from the trench structure and high optical contrast PCM of Sn‐GST. Trench structure improves the heating efficiency of the ITO heater and effectively alleviates the thermal stress imposed on the ITO heater, resulting in ultrahigh endurance of the device. Sn‐doping is also beneficial to the endurance and ER improvement, because it can effectively reduce the crystallization temperature and increase the absorption coefficient of the PCM layer. This work provides a new technology for the development of programmable photonics with ultrahigh endurance. [ABSTRACT FROM AUTHOR]

Using cinchonine as a raw material, a cinchonine-based isonitrile monomer was prepared after multistep transformation, and finally cinchonine-based catalyst was prepared by polymerization initiated by 4-methoxyphenylethynyl(chloro)bis(triethylphosphine)palladium(II). The new catalyst was used to catalyze asymmetric aldol reactions between cyclohexanone and aromatic aldehydes with different substituent groups. The reaction of cyclohexanone and 3-nitrobenzaldehyde in methanol afforded an enantiomeric excess (ee) value of up to 55% and a diastereomeric ratio (dr) of up to 30:70, indicating high performance of the catalyst. The synthesized compounds were characterized by HPLC, IR, and 1H NMR. [ABSTRACT FROM AUTHOR]

Heat release rate is a critical parameter in the combustion process, yet its quantification can be challenging to obtain experimentally. In this study, an acoustical measurement system based on the Rijke tube was established to investigate the heat release rate perturbations of 25 propane/air flames under different mixing conditions. For premixed flames, perturbations in CH* and OH* chemiluminescence were consistent with the heat release rate disturbances determined using the acoustical method, thereby validating the proposed acoustical method and platform. Based on these, a comprehensive analysis was carried out on the chemiluminescence results and heat release rate perturbations of flames under different fuel–air mixing conditions, revealing the condition where the chemiluminescence method no longer reliably indicates the heat release rate. The research also investigated the chemiluminescence structure of flames under different fuel–air mixing conditions, identifying a difference in the distribution of CH* and OH* chemiluminescence at higher equivalence ratios (approaching diffusion flame conditions). In fully diffusion flames, the perturbation of OH* chemiluminescence was primarily observed near the base of the flame, while the peak perturbation of CH* chemiluminescence resides within the soot reaction zone downstream of the flame front. [ABSTRACT FROM AUTHOR]

This article investigates the detection and defense method of time‐varying formation for unmanned aerial vehicles (UAVs) against external disturbance and false data injection attacks (FDIAs). First, to detection attacks, a distributed attack identification filter is constructed for each UAV. Second, two distributed extended state observers are designed to separate and estimate external disturbances and FDIAs. Third, the distributed time‐varying formation tracking protocol and defense strategy for attacks is designed by utilizing the estimated information. The formation system is shown to asymptotically track the desired formation and trajectory and meanwhile reject the disturbance and attacks if the expected formation satisfies the feasible condition by stability analysis. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

Eucalyptus globulus is widely introduced and cultivated in Yunnan province. Its foliage is mainly used to extract eucalyptus oil, but the by-product eucalyptus residue has not been fully utilized. Based on the above reasons, in this study, we sought to explore the comprehensive utilization potential of eucalyptus resources. The total composition of eucalyptus residue was analyzed by ultra performance liquid chromatography-time-of-flight mass spectrometry (UPLC-Q/TOF MS), and the active components and nutrient components of eucalyptus leaf residue were determined by chemical methods and liquid phase techniques. Meanwhile, the antitumor activity of triterpenoids in eucalyptus leaves was evaluated by tetramethylazazole blue colorimetric assay (MTT). The results of qualitative analysis indicated that 55 compounds were identified from eucalyptus residue, including 28 phloroglucinols, 17 terpenoids, 3 flavonoids, 5 fatty acids, 1 amino acid and 2 polyphenols. Among them, the pentacyclic triterpenoids, in eucalyptus residue, were mainly oleanane type and urthane type. The results of quantitative determination indicated that the content of triterpenoid compounds was 2.84% in eucalyptus residue, which could be enhanced to 82% by silicone separation. The antitumor activity results showed that triterpenoid compounds have moderate inhibitory effects on human breast cancer cell MDA-MB-231, gastric adenocarcinoma cell SGC-7901 and cervical cancer cell Hela. The half maximal inhibitory concentration (IC50) was 50.67, 43.12 and 42.65 μg/mL, respectively. In this study, the triterpenoids from eucalyptus leaf residues were analyzed to reveal that the triterpenoids from eucalyptus leaf have antitumor effects and have potential to be developed as antitumor drugs. [ABSTRACT FROM AUTHOR]

Background: Patients with brain tumors, especially pediatric brain tumors such as cerebellar medulloblastoma, always suffer from the severe side effects of radiotherapy. Regeneration of neural cells in irradiation‐induced cerebellar injury has been reported, but the underlying mechanism remains elusive. Methods: We established an irradiation‐induced developing cerebellum injury model in neonatal mice. Microarray, KEGG analysis and semi in vivo slice culture were performed for mechanistic study. Results: Nestin‐expressing progenitors (NEPs) but not granule neuron precursors (GNPs) were resistant to irradiation and able to regenerate after irradiation. NEPs underwent less apoptosis but similar DNA damage following irradiation compared with GNPs. Subsequently, they started to proliferate and contributed to granule neurons regeneration dependent on the sonic hedgehog (Shh) pathway. In addition, irradiation increased Shh ligand provided by Purkinje cells. And microglia accumulated in the irradiated cerebellum producing more IFN‐γ, which augmented Shh ligand production to promote NEP proliferation. Conclusions: NEP was radioresistant and regenerative. IFN‐γ was increased post irradiation to upregulate Shh ligand, contributing to NEP regeneration. Our study provides insight into the mechanisms of neural cell regeneration in irradiation injury of the developing cerebellum and will help to develop new therapeutic targets for minimizing the side effects of radiotherapy for brain tumors. [ABSTRACT FROM AUTHOR]

This study aimed to examine the prevalence and factors influencing domestic abuse victimization among high-income women in Japan, including physical, psychological, economic, and sexual abuse. The background factors and reality of domestic abuse faced by high-income women have not been sufficiently addressed, although some academic studies contend that economically disadvantaged women are more susceptible to domestic abuse. This study collected data from 359 high-income women in Japan using an online questionnaire survey. Binary logistic regression analysis was used to investigate the contributing factors. Approximately one-fifth of high-income women had suffered physical, economic, and sexual domestic abuse, and approximately two-fifths had experienced psychological violence. Adverse childhood experiences, the degree of approval of traditional gender norms, quarrels over opposing views on traditional gender norms, and partners' education levels considerably influenced the prevalence of domestic abuse among high-income female victims. In contrast with the literature, the earnings gap between female victims and their partners did not yield meaningful results. This study examines the experiences of four types of domestic abuse among high-income women in East Asia and highlights the factors that contribute to it, as exemplified by Japan, which is a research direction that has not received sufficient attention. It also offers valuable insight into domestic abuse support policies that target low-income women in contemporary society. [ABSTRACT FROM AUTHOR]

In this study, Ag and N-doped carbon dots (Ag–NCDs) were used to enhance the ultraweak H2O2–Co2+ (a Fenton-like reaction) chemiluminescence (CL) reaction, in which Ag–NCDs were found to have the functions of catalyst, chelator, and luminophore. Under the co-catalysis of Co2+ and Ag–NCDs, H2O2 dissociation was facilitated, resulting in increased generation of active ˙OH and ˙O2− radicals. Thus, the CL intensity of the Ag–NCDs–H2O2–Co2+ system was significantly higher than that of the H2O2–Co2+ system and the Ag–NCDs–H2O2 system. Co2+ catalyzes the reaction through complex formation with Ag–NCDs' surface amino groups, thereby accelerating H2O2 decomposition. The CL intensity of the H2O2–Co2+ system increased with increasing Co2+ concentration in the range from 0.4 μM to 40.0 μM with a detection limit of 0.07 μM. Furthermore, we observed that HQ can effectively quench the Ag–NCDs–H2O2–Co2+ CL signal. This led to the application of the CL system for HQ detection, achieving quantitative measurements within the 0.2–20.0 μM concentration range with a detection limit of 0.04 μM. It also enabled sequential determination of Co2+ and HQ in egg yolk, vitamin B12, and water samples, offering simplicity, time-saving, and higher selectivity. [ABSTRACT FROM AUTHOR]

Purpose: Anxiety, as an important public health issue, may frequently trouble the chronic GI patients with severe symptoms. In this study, we aimed to investigate the relationship between the severity of GI symptoms and anxiety symptoms and further examine whether this relationship was mediated through illness perception.Patients and Methods: A total of 295 patients with chronic GI disease from the affiliated hospital of Xuzhou Medical University were enrolled in this cross-sectional study. They were interviewed with self-reported questionnaires containing demographic variables, clinical variables, and several self-rating scales. Multivariable linear regression models were established to explore the relationship between the severity of GI symptoms and anxiety symptoms. Finally, we performed the mediation analysis to test the mediating effect of illness perception.Results: After adjustments for key demographic and clinical covariates, the severity of GI symptoms was positively associated with anxiety symptoms (β=0.214, 95% CI: 0.009– 0.028, P < 0.001). Additionally, the results of the mediation analysis suggested that illness perception partially mediated the association between the severity of GI symptoms and anxiety symptoms with a mediating ratio of 25.3%.Conclusion: Our findings indicated that chronic GI patients with more severe GI symptoms were more likely to have anxiety symptoms and this effect is partially mediated by illness perception. Therefore, illness perception is recommended to be integrated into the routine assessment of chronic GI patients, and perception-based interventions may be beneficial in relieving anxiety symptoms among patients with severe chronic GI diseases. [ABSTRACT FROM AUTHOR]

The ionic conductivity of anion exchange membranes (AEMs) directly determines the performance of anion exchange membrane fuel cells (AEMFCs), which highly depends on the hydration level of the membrane. A better understanding of the relationship between hydration level and membrane ionic conductivity is essential for membrane development and for water and thermal management analyses of AEMFCs. In this study, the effects of water activity and temperature on water uptake, equilibrium water content, and ionic conductivity of three high‐performance AEMs (Alkymer, Orion, and Pention) are quantitatively characterized via the designed experiments. The results show that Orion exhibits the lowest water uptake and highest ionic conductivity among the three membranes at high water activity and Alkymer exhibits good water‐retention capability and the highest ionic conductivity at low water activity. Empirical equations combining water activity and equilibrium water content are proposed based on fitted experimental data to define the hydration level. Empirical equations combining ionic conductivity, equilibrium water content, and temperature are fitted to illustrate the relationship between ionic conductivity and hydration level. The findings of this study can provide solid guidelines and support for the future experimental characterization and water and thermal management analyses of AEMFCs. [ABSTRACT FROM AUTHOR]

This study aimed to clarify the multidimensionality of defending by developing and validating the Adolescent Defending Behaviors Questionnaire (ADBQ) in a sample of Chinese adolescents. Results of Study 1 (N = 824, Mage = 11.25) indicated that a five-factor model, comprising (a) assertive defending, (b) aggressive defending, (c) comforting victims, (d) reporting to authority, and (e) tactical defending, yielded a good fit to the data. Study 2 (N = 1,086, Mage = 11.18) established ADBQ's reliability (α =.78–.93) and construct validity: the five defending dimensions were differentially associated with cognitive and affective empathy, aggression, sociability, peer preference, and victimization. Together, the results suggest that the ADBQ is a psychometrically valid and reliable instrument for assessing the multidimensionality of defending. [ABSTRACT FROM AUTHOR]

Enhancers are crucial cis- regulatory elements that control gene expression in a cell-type-specific manner. Despite extensive genetic and computational studies, accurately predicting enhancer activity in different cell types remains a challenge, and the grammar of enhancers is still poorly understood. Here, we present HEAP (h igh-resolution e nhancer a ctivity p rediction), an explainable deep learning framework for predicting enhancers and exploring enhancer grammar. The framework includes three modules that use grammar-based reasoning for enhancer prediction. The algorithm can incorporate DNA sequences and epigenetic modifications to obtain better accuracy. We use a novel two-step multi-task learning method, task adaptive parameter sharing (TAPS), to efficiently predict enhancers in different cell types. We first train a shared model with all cell-type datasets. Then we adapt to specific tasks by adding several task-specific subset layers. Experiments demonstrate that HEAP outperforms published methods and showcases the effectiveness of the TAPS, especially for those with limited training samples. Notably, the explainable framework HEAP utilizes post-hoc interpretation to provide insights into the prediction mechanisms from three perspectives: data, model architecture and algorithm, leading to a better understanding of model decisions and enhancer grammar. To the best of our knowledge, HEAP will be a valuable tool for insight into the complex mechanisms of enhancer activity. [ABSTRACT FROM AUTHOR]

Farnesyl diphosphate synthase (FPPS) is a crucial protein in terpenoid production. However, its industrial application is limited owing to its low solubility in Escherichia coli. In this study, we focused on ispA encoding FPPS and designed a fusion expression system to reduce inclusion body (IB) formation. Among the chosen fusion tags, the GB1-domain (GB1) exhibited the highest ability to solubilize the recombinant protein. Increased rare tRNA abundance not only improved the GB1-FPPS yield but also increased its soluble level. A "one-step" method for the acquisition of soluble FPPS was also considered. By combining GB1-FPPS expression and Tobacco Etch Virus protease (TEVp) cleavage in vivo, a controllable GB1-FPPS "self-cleavage" system was constructed. Overall, this study provides an efficient approach for obtaining soluble forms of FPPS, which show great potential for use in the soluble expression of other homologous diphosphate synthase. [ABSTRACT FROM AUTHOR]

Wind power has emerged as a crucial renewable energy source, experiencing significant growth in recent years. However, blade icing remains a pressing challenge in the operation of wind turbines, potentially resulting in systems faults and component damage. Traditional approaches to blade icing detection often rely on domain expertise, incurring additional costs. While data-driven techniques have proven effective in detecting blade icing, they require substantial amounts of labeled data for model training, which can be time-consuming and prohibitively expensive. Furthermore, blade icing detection data is often highly imbalanced since wind turbines typically operate under normal conditions for extended periods. To address these issues, we propose a novel method based on unified imbalanced semi-supervised contrastive learning (UISSCL) that can simultaneously address class imbalance scenarios and semi-supervised scenarios. UISSCL integrates unsupervised and supervised contrastive learning into a unified framework capable of extracting discriminative features from both labeled and unlabeled imbalanced data. A linear classifier is then trained based on the representations learned from the contrastive learning approach. The results obtained from computational experiments on two wind turbine blade icing datasets demonstrate that our method outperforms state-of-the-art methods in both the supervised and semi-supervised settings integrating with class imbalance scenarios. [Display omitted] • We propose a novel method called UISSCL for wind turbine blade icing detection. • UISSCL can simultaneously solve the class imbalanced and semi-supervised problem. • Contrastive learning is introduced to learn from wind turbine blade icing data. • UISSCL shows excellent blade icing detection capability on actual datasets. [ABSTRACT FROM AUTHOR]

Phosphorus (P) is abundant in wastewater sludge and can be a secondary P source that will contribute to a circular economy. Electrochemical systems are an emerging technology that can be used to release and recover P from wastewater sludge. This paper introduces and analyzes the state-of-the-art electrochemical methods for P release and recovery from wastewater sludge, both qualitatively and quantitatively. Electrochemical P release, which involves mobilizing P from the solid phase into the aqueous phase, is categorized into three major mechanisms, electro-biological release, anodic P release, and cathodic P release. Anodic P release has been most widely studied with a median P release rate of 92.4 mg d−1. Correlation analysis revealed that the type of feed sludge, sludge P contents, sludge loading rate, and current density have a significant impact on the P release performance. The released P is subsequently separated from the heavy metal laden sludge and then recovered via different electrochemical systems such as three-chamber cells, two-chamber cells, and their variations. Those systems can achieve P recovery efficiency of 50 ∼ 80% and a recovery rate of 2.0 × 102∼1.8 × 103 mg P d−1. Energy consumption of electrochemical P recovery is estimated at 50 ∼ 200 kWh kg−1 P but only 27.3% of literature reported such data. This work provides insights into the development and challenges of electrochemical P release & recovery from wastewater sludge and discusses the challenges that need to be addressed to advance the viability of electrochemical P recovery approach. [ABSTRACT FROM AUTHOR]

Little concern has been paid to the relationship between temperature and varicella among adults. Daily meteorological data and varicella cases in Qingdao among adults from 1 January 2008 to 31 December 2019 were collected. A combination of quasi-Poisson generalized additive model (GAM) and distributed lag non-linear model (DLNM) was conducted to assess the temperature-lag-varicella relationship. We also estimated the lag-response curves for different temperatures and the exposure-response relationships for different lag days. The number of varicella cases was 10,296. Compared with the minimum-varicella temperature (25°C), we found the largest effect of temperature on varicella within 21 lag days was at 1°C (RR, 6.72; 95% CI, 2.90–15.57), and then the effect declined as the temperature increased. A similar trend of rising first and then falling was found in temperature-response curves for different lag days. A reverse U-shape lag pattern was found for different levels of temperatures. Temperature may affect varicella. [ABSTRACT FROM AUTHOR]

A novel metal sulfide NaTS-2 was prepared using a simple one-step hydrothermal method to remove strontium ions from the simulated radioactive wastewater, in which metal tin was replaced by tin salts to reduce the cost of the raw materials. NaTS-2 has a layered structure with an approximate molar ratio of Na:Sn:S of 1.94:2.87:7. NaTS-2 could rapidly remove Sr2+ with a removal efficiency of 99.3% ± 0.23% within 1 min and at an equilibrium of 60 min, followed by the pseudo-second-order model and Langmuir model with a maximum adsorption capacity of 88.9 ± 0.81 mg/g at 298 K. NaTS-2 exhibited an outstanding affinity for Sr2+ (Kd ≥ (3.0 ± 0.10) × 105 mL/g) over a broad pH range of 3–11, also displayed significant affinity (Kd ≥ (1.0 ± 0.15) × 105 mL/g) and excellent removal efficiency (≥ 98.5% ± 0.48%) for typical activated corrosion products (Co2+, Mn2+ and Ni2+). NaTS-2 is a promising adsorbent in the field of radioactive wastewater treatment. [ABSTRACT FROM AUTHOR]

Tea tree oil (TTO) is a natural plant essential oil that has strong bactericidal properties and low toxicity. However, owing to its irritability, volatility, instability under light/oxygen and hydrophobicity, the application of TTO in pharmaceutical production technology and the food industry is limited. To overcome these problems, TTO nanoemulsions (TTONs) were prepared using a high‐speed shearing method. The mean droplets size of TTON was measured. TTON droplets were observed using confocal laser scanning microscopy and analysed using a Turbiscan scanning spectrum. The most suitable nanoemulsion formula was obtained as follows: TTO content, 10% (w/w); Tw‐40 content, 8% (w/w); deionised water content, 82% (w/w); shearing time, 5 minutes. The antibacterial effect of TTON was studied, and it was found that its antibacterial activity against Escherichia coli was more potent than that against Staphylococcus aureus. The antibacterial mechanism of TTON was also investigated by observing bacterial morphology using scanning electron microscopy and testing the levels of bacterial reactive oxygen species. The effect of TTON on L‐02 cells was evaluated. The results showed that the cell survival rates of L‐02 cells treated with TTON at 0.05‐0.25 μg/μL were all >90%. At each concentration, the total apoptosis rate of L‐02 cells was <10%. These results indicated the high biocompatibility and biological safety of TTON. Therefore, the preparation of TTO into a nanoemulsion can improve its bioavailability, which has positive implications for further applications of TTO. [ABSTRACT FROM AUTHOR]

Motivation Transcription factor (TF) binds to conservative DNA binding sites in different cellular environments and development stages by physical interaction with interdependent nucleotides. However, systematic computational characterization of the relationship between higher-order nucleotide dependency and TF-DNA binding mechanism in diverse cell types remains challenging. Results Here, we propose a novel multi-task learning framework HAMPLE to simultaneously predict TF binding sites (TFBS) in distinct cell types by characterizing higher-order nucleotide dependencies. Specifically, HAMPLE first represents a DNA sequence through three higher-order nucleotide dependencies, including k -mer encoding, DNA shape and histone modification. Then, HAMPLE uses the customized gate control and the channel attention convolutional architecture to further capture cell-type-specific and cell-type-shared DNA binding motifs and epigenomic languages. Finally, HAMPLE exploits the joint loss function to optimize the TFBS prediction for different cell types in an end-to-end manner. Extensive experimental results on seven datasets demonstrate that HAMPLE significantly outperforms the state-of-the-art approaches in terms of auROC. In addition, feature importance analysis illustrates that k -mer encoding, DNA shape, and histone modification have predictive power for TF-DNA binding in different cellular environments and are complementary to each other. Furthermore, ablation study, and interpretable analysis validate the effectiveness of the customized gate control and the channel attention convolutional architecture in characterizing higher-order nucleotide dependencies. Availability and implementation The source code is available at https://github.com/ZhangLab312/Hample. [ABSTRACT FROM AUTHOR]

This paper is concerned with convergence of stochastic gradient algorithms with momentum terms in the nonconvex setting. A class of stochastic momentum methods, including stochastic gradient descent, heavy ball and Nesterov's accelerated gradient, is analyzed in a general framework under mild assumptions. Based on the convergence result of expected gradients, the authors prove the almost sure convergence by a detailed discussion of the effects of momentum and the number of upcrossings. It is worth noting that there are not additional restrictions imposed on the objective function and stepsize. Another improvement over previous results is that the existing Lipschitz condition of the gradient is relaxed into the condition of Hölder continuity. As a byproduct, the authors apply a localization procedure to extend the results to stochastic stepsizes. [ABSTRACT FROM AUTHOR]

Monolayer transition metal dichalcogenides (TMDs) have drawn significant attention for their potential applications in electronics and optoelectronics. To achieve consistent electronic properties and high device yield, uniform large monolayer crystals are crucial. In this report, we describe the growth of high-quality and uniform monolayer WSe2 film using chemical vapor deposition on polycrystalline Au substrates. This method allows for the fabrication of continuous large-area WSe2 film with large-size domains. Additionally, a novel transfer-free method is used to fabricate field-effect transistors (FETs) based on the as-grown WSe2. The exceptional metal/semiconductor interfaces achieved through this fabrication method result in monolayer WSe2 FETs with extraordinary electrical performance comparable to those with thermal deposition electrodes, with a high mobility of up to ≈62.95 cm2 V−1 s−1 at room temperature. In addition, the as-fabricated transfer-free devices can maintain their original performance after weeks without obvious device decay. The transfer-free WSe2-based photodetectors exhibit prominent photoresponse with a high photoresponsivity of ~1.7 × 104 A W−1 at Vds = 1 V and Vg = −60 V and a maximum detectivity value of ~1.2 × 1013 Jones. Our study presents a robust pathway for the growth of high-quality monolayer TMDs thin films and large-scale device fabrication. [ABSTRACT FROM AUTHOR]

Background: Microarray data have been widely utilized for cancer classification. The main characteristic of microarray data is "large p and small n" in that data contain a small number of subjects but a large number of genes. It may affect the validity of the classification. Thus, there is a pressing demand of techniques able to select genes relevant to cancer classification. Results: This study proposed a novel feature (gene) selection method, Iso-GA, for cancer classification. Iso-GA hybrids the manifold learning algorithm, Isomap, in the genetic algorithm (GA) to account for the latent nonlinear structure of the gene expression in the microarray data. The Davies–Bouldin index is adopted to evaluate the candidate solutions in Isomap and to avoid the classifier dependency problem. Additionally, a probability-based framework is introduced to reduce the possibility of genes being randomly selected by GA. The performance of Iso-GA was evaluated on eight benchmark microarray datasets of cancers. Iso-GA outperformed other benchmarking gene selection methods, leading to good classification accuracy with fewer critical genes selected. Conclusions: The proposed Iso-GA method can effectively select fewer but critical genes from microarray data to achieve competitive classification performance. [ABSTRACT FROM AUTHOR]

The magmatic process within upper crust encompasses various contents such as the transition between magmatic and hydrothermal systems and changes in oxygen fugacity (ƒO2), which ultimately play key roles in the formation of porphyry Cu deposits (PCDs). However, tracing these magmatic processes, especially in porphyry systems, is not an easy task. This study reported the detailed process of magmatic fluid exsolution and systematical variation of magmatic ƒO2 within the upper crust of a Tongchang–Chang'anchong porphyry Cu deposit, based on detailed investigations of mineral crystallization sequences and compositional features of the minerals in the fertile porphyries. Results indicate that the fertile porphyries show a high initial ƒO2, with ΔFMQ ≥ +3.0 (ΔFMQ is the deviation of logƒO2 from the fayalite–magnetite–quartz (FMQ) buffer). The magmatic ƒO2 (ΔFMQ) continued to decrease to ~+2 until fluid exsolution occurred at ~790 °C due to wall-rock contamination. The magmatic fluid exsolution process caused a temporary increase in the ƒO2 (to ΔFMQ = ~+3.4). The high magmatic ƒO2 during this process (790–750 °C) resulted in a higher content of ore-forming materials in the exsolved magmatic fluid. When the temperature dropped below 750 °C, the magmatic ƒO2 began to continuously decrease and eventually reached ΔFMQ = ~+0.6. The lower magmatic ƒO2 hindered the further migration of ore-forming materials through the exsolved fluid during this process (< 750 °C). Results of this study indicate that the initial magma during the upper crustal magmatic process of PCDs generally has a high ƒO2, and the contamination of reduced components can significantly decrease the magmatic ƒO2. The early magmatic fluid exsolution process can maintain a high magmatic ƒO2 condition, thereby efficiently extracting ore-forming minerals and producing ore-forming fluids, which is the key to the formation of PCDs. The latter continuous decrease in magmatic ƒO2 during the fluid exsolution process may be the reason preventing the Tongchang–Chang'anchong porphyry Cu deposit to form a giant PCD. [ABSTRACT FROM AUTHOR]

Multiple sclerosis (MS) is a neurodegenerative disease with a complex pathogenesis. Re-lapsing-remitting multiple sclerosis (RRMS) is the most common subset of MS, accounting for approximately 85% of cases. Recent studies have shown that ferroptosis may contribute to the progression of RRMS, but the underlying mechanism remains to be elucidated. Herein, this study intended to explore the molecular network of ferroptosis associated with RRMS and establish a predictive model for efficacy diagnosis. Firstly, RRMS-related module genes were identified using weighted gene co-expression network analysis (WGCNA). Secondly, the optimal machine learning model was selected from four options: the generalized linear model (GLM), random forest model (RF), support vector machine model (SVM), and extreme gradient boosting model (XGB). Subsequently, the predictive efficacy of the diagnostic model was evaluated using receiver operator characteristic (ROC) analysis. Finally, a SVM diagnostic model based on five genes (JUN, TXNIP, NCOA4, EIF2AK4, PIK3CA) was established, and it demonstrated good predictive performance in the validation dataset. In summary, our study provides a systematic exploration of the complex relationship between ferroptosis and RRMS, which may contribute to a better understanding of the role of ferroptosis in the pathogenesis of RRMS and provide promising diagnostic strategies for RRMS patients. [ABSTRACT FROM AUTHOR]

Bi 0.5 Na 0.5 TiO 3 (BNT) lead-free ceramics have been extensively studied due to their excellent dielectric, piezoelectric and ferroelectric properties. The phase structure and functionalities of BNT can be feasibly adjusted by doping/forming solid solutions with other elements/components. In this work, Bi(Mg 2/3 Nb 1/3)O 3 (BMN) was introduced into BNT by a conventional solid-state reaction to form a homogeneous solid solution of (1-x)(Bi 0.5 Na 0.5)TiO 3 -xBi(Mg 2/3 Nb 1/3)O 3 (BNT-xBMN) with a perovskite structure. With the increase of BMN content, a phase transition from rhombohedral R3c to tetragonal P4bm has been confirmed by XRD, along with shifting the ferroelectric-paraelectric phase transition temperature to lower temperatures with broadening dielectric peaks. Furthermore, an optimized recoverable energy density of 1.405 J/cm3 was achieved for BNT-0.10BMN ceramics under a low applied electric field of 140 kV/cm, which is mainly attributed to the transformation from ferroelectric to ergodic relaxor phase. [ABSTRACT FROM AUTHOR]

Recent advances in single-cell sequencing assays for the transposase-accessibility chromatin (scATAC-seq) technique have provided cell-specific chromatin accessibility landscapes of cis-regulatory elements, providing deeper insights into cellular states and dynamics. However, few research efforts have been dedicated to modeling the relationship between regulatory grammars and single-cell chromatin accessibility and incorporating different analysis scenarios of scATAC-seq data into the general framework. To this end, we propose a unified deep learning framework based on the ProdDep Transformer Encoder, dubbed PROTRAIT, for scATAC-seq data analysis. Specifically motivated by the deep language model, PROTRAIT leverages the ProdDep Transformer Encoder to capture the syntax of transcription factor (TF)-DNA binding motifs from scATAC-seq peaks for predicting single-cell chromatin accessibility and learning single-cell embedding. Based on cell embedding, PROTRAIT annotates cell types using the Louvain algorithm. Furthermore, according to the identified likely noises of raw scATAC-seq data, PROTRAIT denoises these values based on predated chromatin accessibility. In addition, PROTRAIT employs differential accessibility analysis to infer TF activity at single-cell and single-nucleotide resolution. Extensive experiments based on the Buenrostro2018 dataset validate the effeteness of PROTRAIT for chromatin accessibility prediction, cell type annotation, and scATAC-seq data denoising, therein outperforming current approaches in terms of different evaluation metrics. Besides, we confirm the consistency between the inferred TF activity and the literature review. We also demonstrate the scalability of PROTRAIT to analyze datasets containing over one million cells. [ABSTRACT FROM AUTHOR]

Comprehensive Summary: The chemistry of alkoxy radicals was extensively explored during the period of 1960s to 1990s, but it has remained dormant for the past few decades. Recently, alkoxy radicals attract the attentions again, because new methods for generating alkoxy radical species have emerged. These newly developed methods are mainly based on the photolysis by visible light under mild conditions, thus allowing for new transformations of the carbon‐centered radical species that are generated from the β‐scission or hydrogen abstraction of the alkoxy radicals. Herein, we demonstrate that the alkoxy radicals derived from cyclic hemiacetals can be generated through visible‐light‐induced electron transfer with sodium iodide and triphenylphosphine as the catalyst. The alkoxy radicals subsequently undergo β‐scission to generate carbon‐centered radicals, which are trapped by cinnamic acids, aryl alkenes, vinylboronic acid and silyl enol ether to deliver the corresponding C—C bond forming products. This catalytic method for ring‐opening alkenylation reaction of cyclic hemiacetal derivatives under visible‐light irradiation conditions demonstrates the compatibility of the visible light‐promoted alkoxy radical generation method with various carbon radical trapping processes. This work opens up new possibilities for the application of alkoxy radicals in organic synthesis. [ABSTRACT FROM AUTHOR]

Background: To investigate the correlation between maternal glucose and lipid metabolism indexes and blood-lipid ratio in the first trimester and large-for- gestational-age (LGA) infants. Methods: Women in the first trimester of pregnancy who underwent regular obstetric examination in the obstetric outpatient department of the Affiliated Hospital of Chengde Medical College from June 2018 to March 2019 were included according to the standard. Basic information were collected based on questionnaires at the first visit of pregnant women, including early fasting blood glucose (FBG), fasting insulin (FINS), glycated hemoglobin (HbA1c), high-density lipoprotein (HDL), low-density lipoprotein (LDL), triglyceride (TG), total cholesterol (TC), apolipoprotein A1 (APO-A1), apolipoprotein B (APO-B), lipoprotein a (LP(a)), LDL/HDL, TG/HDL, TC/HDL, APO-B/APO-A1 ratio, birth weight of newborns, gestational age at delivery etc. Results: A total of 418 cases were included for analysis. The incidence rate of LGA infants was 13.88%, and that of small-for-gestational-age (SGA) infants was 4.78%. Univariate analysis revealed that the age, pre-pregnancy body mass index (BMI), weight gain during pregnancy, APO-B/APO-A1 between LGA group and appropriate-for-gestational-age (AGA) group were significantly different (P < 0.05); multivariate stepwise logistic regression analysis indicated that the correlation between maternal age, pre-pregnancy BMI, weight gain during pregnancy, APO-B/APO-A1 level and LGA were statistically significant (P < 0.05); compared with the reference range of APO-B/APO-A1 of 0.46–0.65, values < 0.46 and > 0.65 were protective factor of LGA (P < 0.05). The receiver operating curve(ROC) indicated that the area under the curve (AUC)s for predicting LGA using maternal age, pre-pregnancy BMI, weight gain during pregnancy, and early pregnancy APO-B/APO-A1 were 0.585, 0.606, 0.637, 0.531, respectively. The AUC for a combined prediction model was 0.742, showing greater predictive value than any other factors individually. Conclusion: Maternal age, pre-pregnancy BMI, weight gain during pregnancy, and APO-B/APO-A1 levels in first trimester are significant factors influencing the occurrence of LGA infants, and the combination of the four factors would have certain predictive value for LGA. [ABSTRACT FROM AUTHOR]

Variations in biomass-carbon of forest can substantially impact the prediction of global carbon dynamics. The allometric models currently used to estimate forest biomass face limitations, as model parameters can only be used for the specific species of confirmed sites. Here, we collected allometric models LnW = a + b*Ln(D) (n = 817) and LnW = a + b*Ln(D2H) (n = 612) worldwide and selected eight variables (e.g., mean annual temperature (MAT), mean annual precipitation (MAP), altitude, aspect, slope, soil organic carbon (SOC), clay, and soil type) to predict parameters a and b using Random Forest. LnW = a + b*Ln(D), drove mainly by climate factors, showed the parameter a range from − 5.16 to − 0.90 [VaR explained (model evaluation index): 66.21%], whereas parameter b ranges from 1.84 to 2.68 (VaR explained: 49.96%). Another model LnW = a + b*Ln(D2H), drove mainly by terrain factors, showed the parameter a range from − 5.45 to − 1.89 (VaR explained: 69.04%) and parameter b ranges from 0.43 to 1.93 (VaR explained: 69.53%). Furthermore, we captured actual biomass data of 249 sample trees at six sites for predicted parameters validation, showing the R2 (0.87) for LnW = a + b*Ln(D); R2 (0.93) for LnW = a + b*Ln(D2H), indicating a better result from LnW = a + b*Ln(D2H). Consequently, our results present four global maps of allometric model parameters distribution at 0.5° resolution and provides a framework for the assessment of forest biomass by validation. [ABSTRACT FROM AUTHOR]

Serine/threonine protein kinases (STKs) are important for signal transduction and involved in multiple physiological processes, including cell growth, central metabolism, and sporulation in bacteria. However, the role of STKs in solventogenic clostridia remains unclear. Here, we identified and comprehensively investigated six STK candidates in Clostridium beijerinckii. These STKs were classified into four groups with distinct characteristics via analysis of genetic organizations, prediction of protein domains, and multiple sequence alignment. Cbei0566 is a member of the PrkA family with 41% identity to PrkA from Bacillus subtilis, and both Cbei0666 and Cbei0813 are two-component-like STKs. Cbei1151 and Cbei1929 belong to the Hanks family STKs and consist of a cytoplasmic catalytic domain, a transmembrane region, and extracellular sensor domains. In-frame deletion mutants of cbei0566, cbei0666, cbei1929, and cbei2661 displayed similar cell growth with wild type. Both Δcbei0666 and Δcbei2661 improved acetone-butanol-ethanol (ABE) production by 14.3% (19.2 g/L vs. 16.8 g/L), and the sporulation frequencies of Δcbei0566, Δcbei1929, and Δcbei2661 significantly decreased to 35.5%, 55.1% and 44.8%, respectively. The restored phenotypes after genetic complementation demonstrated their direct link to STKs deletion. Remarkably, overexpressing cbei0566 contributed to 41.5% more spore formation and cbei1929 overexpression enhanced ABE production from 19.3 to 24.2 g/L, along with 25% less acids. These results revealed that Cbei0566 and Cbei1929 had prominent regulatory functions. This study expands the current knowledge of the existence and functions of STKs in prokaryotes and highlights the importance of STK-mediated signaling networks in developing superior strains. Key points: • First reported serine/threonine protein kinases in solventogenic clostridia • Six STKs with distinct properties possessed diverse functions in C. beijerinckii • Cbei1929 and Cbei0566 remarkably regulated solventogenesis and sporulation [ABSTRACT FROM AUTHOR]

Core flow distribution is closely related to the thermal–hydraulic performance and safety of reactors. For natural circulation reactors with a limited driving force, flow distribution optimization is of particular significance, which can be contrived by suitably assigning the inlet resistance of a core assembly channel in reactor design. In the present work, core flow distribution optimization during the fuel life cycle is regarded as a global optimization problem. The optimization objective is to minimize the maximal outlet temperature difference of assembly channels during the fuel life cycle, while the input variable is the inlet resistance coefficient of each assembly channel. The simulated annealing algorithm is applied to the optimization code. The results show that the maximal outlet temperature difference is significantly reduced after optimization, and the resultant core outlet temperature distribution becomes more uniformed. Further evaluation indicates that the optimal solution has good applicability and stability under different reactor conditions. A comparison of the optimization objective function using different temperature difference definitions is also studied in the current study. [ABSTRACT FROM AUTHOR]

The optimization of the ecological network structure in Nanping can provide a scientific reference for guaranteeing ecological safety in Southeast China. This study estimated ecosystem services in Nanping with the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model based on land-use data from 2020 to 2025 simulated with the CLUE-S model under the natural development scenario and ecological protection scenario and then explored their trade-offs and synergies. The ecological network structure was, thereafter, optimized in terms of the eco-matrix, eco-corridors and nodes based on simulated land use and ecosystem services. The results suggested that the average habitat quality and total soil retention increased, while the average degradation index and total water yield decreased under the ecological protection scenario, indicating that the ecological environment quality tended to be improved. In addition, soil retention had significant synergies with habitat quality and water yield, and habitat quality had significant trade-offs with ecological degradation and water yield on the regional scale under two scenarios, while ecological degradation also showed significant trade-offs with soil retention and water yield. In addition, the results suggested that 11 additional ecological sources could be added, and the number of eco-corridors increased from 15 to 136; a total of 1019 ecological break points were restored, and 1481 stepping stone patches were deployed, which jointly made network circuitry, edge/node ratio and network connectivity reach 0.45, 1.86 and 0.64, respectively, indicating that optimization could effectively improve the structure and connectivity of the ecological network. These findings can provide a theoretical basis for improving the ecological network structure and ecological service functions in Nanping and other regions. [ABSTRACT FROM AUTHOR]

Prospective identification of robust biomarkers related to prognosis and adjuvant chemotherapy has become a necessary and critical step to predict the benefits of adjuvant therapy for patients with stage II–III colorectal cancer (CRC) before clinical treatment. We proposed a single-cell-based prognostic biomarker recognition approach to identify and construct CRC up- and down-regulated prognostic signatures (CUPsig and CDPsig) by integrating scRNA-seq and bulk datasets. We found that most genes in CUPsig and CDPsig were known disease genes, and they had good prognostic abilities in CRC validation datasets. Multivariate analysis confirmed that they were two independent prognostic factors of disease-free survival (DFS). Significantly, CUPsig and CDPsig could effectively predict adjuvant chemotherapy benefits in drug-treated validation datasets. Additionally, they also performed well in patients with CMS4 subtype. Subsequent analysis of drug sensitivity showed that expressions of these two signatures were significantly associated with the sensitivities of CRC cell lines to multiple drugs. In summary, we proposed a novel prognostic biomarker identification approach, which could be used to identify novel prognostic markers for stage II–III CRC patients who will undergo adjuvant chemotherapy and facilitate their further personalized treatments. [ABSTRACT FROM AUTHOR]

C f /C–SiC composites were fabricated via liquid silicon infiltration with 2.5D needle-punched carbon fiber reinforced C f /C composites. The effect of surface topography and carbon content of the C f /C–SiC composites on the tribological properties was researched by the ball-on-disk reciprocating tribometer. The results indicate that different fiber layers and cross-section of the composites have various surface topography and show significant differences in the friction and wear properties. By the wear morphology and model analyses, the reason for the tribological anisotropy of the composites is that the distribution of carbon and SiC phases in the composites are inhomogeneous caused by the difference of the carbon fiber orientation and the relative content in each layer. Moreover, the wear rate of the short-cut fiber web layer was the lowest and there is an obvious linear decrease in coefficient of friction with increase of carbon content. The present work explains why the tribological properties of the composites are inconsistent and provides a way to adjust the friction properties of composite materials by optimizing the friction surface. [ABSTRACT FROM AUTHOR]

Among the existing bearing fault diagnosis algorithms, the diagnosis time of algorithms with high accuracy is relatively long, and the accuracy of some lightweight methods is low compared to other methods. This work proposes a bi-level binary coded fully connected classifier based on residual network 50 with bottom and deep level features (Bi-BUR) for bearing fault diagnosis, enabling both high accuracy and high-speed characteristics. The Bi-BUR has two levels of classifiers. The first level begins with a signal-to-picture method based on integer binary coding to convert the bearing fault signals into binary pictures; then, the first classification of the converted pictures is performed by the underlying feature extraction-residual network 50, which can extract both the underlying and the advanced features. The second level performs modal decomposition of the signals that are not classified successfully in the first level, performs the second classification with a fully connected classifier inserted into the underlying feature extraction module, and exports the final classification results after weighted summation of the results of each type. The Bi-BUR is simulated on the Case Western Reserve University motor, the self-priming centrifugal pump, and the axial piston hydraulic pump bearing failure datasets. All three experiments achieved more than 95% accuracy in the first level of categorization and 100% diagnosis after the second level of categorization. And the Bi-BUR is faster than other high-accuracy methods. • A bearing fault diagnosis method with fusion of speed and accuracy is considered. • A two-layer bearing fault diagnosis method is proposed. • A signal-to-picture method based on integer binary coding is proposed. • A method to extract both bottom and deep level features is proposed. • The method fills the gap of bearing fault diagnosis with high speed and accuracy. [ABSTRACT FROM AUTHOR]

To achieve environmental sustainability and low carbon emissions in the field of marine power systems, it is crucial to enhance system performance in both the fuel subsystem and power subsystem. This study introduces a solid oxide fuel cell (SOFC) engine cogeneration system utilizing methanol fuel designed specifically for marine applications. Methanol serves as a hydrogen source for the SOFC through online reforming, producing hydrogen. The engine further enhances energy efficiency by utilizing the anode tail gas from the SOFC. The study employs the energy, economy, and environment (3E) analysis method to assess the system's performance. Results demonstrate that the system exhibits high energy efficiency and low carbon emissions. The system configuration is optimized, and design points are determined through parameter optimization. The rated power generation efficiency of the system can reach 59.57 %, which is nearly 20 % absolute efficiency improvement compared to methanol engines. An analysis of the system's performance under partial load conditions reveals that, even at 53 % load, the power generation efficiency remains at 53.29 %. The total life cycle carbon emissions for the system is 319.78 g/kWh, significantly lower than the engine. The levelized cost of energy for the system are 0.1161 $/kWh, slightly higher than engine power generation costs. [Display omitted] • The fuel cell engine cogeneration system with methanol is proposed. • The system cogeneration and generation efficiency reach 85.55 % and 57.1 %. • The effects of the main parameters on the system performance were evaluated. • Partial load characteristics of the system are studied. [ABSTRACT FROM AUTHOR]

Polishing process, is an important process of ensuring surface quality and precision. However, it is difficult to achieve quantitative material removal and polish to target surface profile accurately, due to the special structure characteristic of polishing pad and the complex contact mechanism between polishing pad-abrasive particle-workpiece surface. Therefore, this study proposes a statistic model for polyurethane polishing pad surface, which take into consideration of the circular hole size (Gaussian distribution), density and location distribution (random distribution) on polishing pad surface. On the basis of the polishing pad surface model, this study further establishes a predicting model for polishing surface profile through analyzing of the effective number of abrasive particles between polishing pad and workpiece, the real contact force between a single abrasive particle and workpiece surface, the single abrasive particle footprint, the overlapping and superimposing of abrasive particle footprint. A series of polishing pad comparative analysis and SiC polishing experiments with different parameters are performed. Both of the two models are validated through qualitative and quantitative comparisons of simulation and experiment results. The proposed models not only lay the foundation for an in-depth understanding of the material removal mechanism in polishing process with polyurethane polishing pads, but also meaningful to other polishing process with polyurethane polishing pads and the optimization of polishing process. [ABSTRACT FROM AUTHOR]

Among the existing bearing fault diagnosis algorithms, the diagnosis time of algorithms with high accuracy is relatively long, and the accuracy of some lightweight methods is low compared to other methods. This work proposes a bi-level binary coded fully connected classifier based on residual network 50 with bottom and deep level features (Bi-BUR) for bearing fault diagnosis, enabling both high accuracy and high-speed characteristics. The Bi-BUR has two levels of classifiers. The first level begins with a signal-to-picture method based on integer binary coding to convert the bearing fault signals into binary pictures; then, the first classification of the converted pictures is performed by the underlying feature extraction-residual network 50, which can extract both the underlying and the advanced features. The second level performs modal decomposition of the signals that are not classified successfully in the first level, performs the second classification with a fully connected classifier inserted into the underlying feature extraction module, and exports the final classification results after weighted summation of the results of each type. The Bi-BUR is simulated on the Case Western Reserve University motor, the self-priming centrifugal pump, and the axial piston hydraulic pump bearing failure datasets. All three experiments achieved more than 95% accuracy in the first level of categorization and 100% diagnosis after the second level of categorization. And the Bi-BUR is faster than other high-accuracy methods. • A bearing fault diagnosis method with fusion of speed and accuracy is considered. • A two-layer bearing fault diagnosis method is proposed. • A signal-to-picture method based on integer binary coding is proposed. • A method to extract both bottom and deep level features is proposed. • The method fills the gap of bearing fault diagnosis with high speed and accuracy. [ABSTRACT FROM AUTHOR]

• The fuel cell/engine/battery hybrid power system with methanol is proposed. • The generation efficiency and fuel consumption peaked at 58.36 % and 283.19 g/kWh. • The carbon reduction of the system for a single voyage is 606.46 tons. • The effects of the main parameters on the system performance were evaluated. The adoption of alternative fuels and high-efficiency power systems has the potential to significantly reduce carbon emissions in maritime transportation. However, there is currently limited understanding of how new power forms affect the effective payload during actual ship operations. This study proposes a hybrid power system using methanol as fuel, integrating solid oxide fuel cells, an engine, and batteries. A mathematical model of the system was established using a modular modeling approach, and the system's performance was evaluated based on container ship scenarios. The results demonstrate that under no-refueling conditions, the hybrid power system achieves a high electrical efficiency of 58.36 %, a fuel consumption rate of 283.19 g/kWh, and carbon emissions of 389.39 g/kWh. Increasing the operating temperature and reducing the current density can enhance the thermodynamic performance of the solid oxide fuel cell and the system, with electrical efficiency exceeding 60 %. Solid oxide fuel cells exhibit poor load variation characteristics, taking approximately 200 s for their output voltage to decrease from 0.62 V to 0.57 V. In contrast, lithium batteries demonstrate rapid load response characteristics. For a single voyage, the ship requires 835.776 tons of fuel, resulting in an increase of 284.776 tons compared to diesel engines. However, carbon emissions are reduced by 606.46 tons. It is noteworthy that the weight and volume of the hybrid power system depend on the power distribution between the fuel cell and the engine. In summary, this innovative hybrid power system provides a potent means of significantly reducing carbon emissions in the shipping industry. [ABSTRACT FROM AUTHOR]

A tillage microrelief unit is the smallest spatially discontinuous area unit of tillage microrelief. Understanding the impact of tillage microrelief units on splash erosion is essential for selecting suitable tillage measures and employing soil and water conservation practices. The objective of this study was to investigate the characteristics and mechanisms of splash erosion under different tillage microrelief units in various directions and distances using the rainfall simulation experiment in the soil landscape of the Loess Plateau region in China, characterized primarily by sloping farmland as the main land use type. Three typical microrelief units, namely, artificial digging (AD), contour tillage (CT), and straight slope conditions (SSC) were designed at 0°, 3°, 5°, 10°, 15°, and 20° slopes. Tillage microrelief units with high surface roughness produced more splash erosion than flat lands. Further, the highest surface roughness increased the total splash amount by 102% relative to flat lands. The tillage microrelief unit itself was elevated with a certain slope, which increased the downslope splash of CT, SSC, and AD by 121%, 173%, and 11%, respectively. Different surface roughness values and slopes under different microrelief units were used to determine the amount of splash erosion. The results showed that the total splash amount responded significantly (P < 0.01) to the interaction between surface roughness and slope, and the sensitivity to roughness was higher than that to slope. According to the single-factor analysis, the surface roughness of all slopes significantly influenced the amount of splash erosion. Furthermore, the sensitivity of the tillage microrelief unit to the slope decreased because of the high slope under high surface roughness. Overall, the results of this study showed that in different tillage microrelief units of slopes in the Loess Plateau, SSC and CT significantly increased the outward splash erosion in this area, while AD significantly decreased the outward splash erosion. Moreover, slope did not have a considerable influence. • Splash erosion under three different tillage microrelief units was examined. • Total splash amount responded significantly to surface roughness and slope. • Response of splash amount to surface roughness was greater than that to slope. • Surface roughness of all slopes influenced the amount of splash erosion. [ABSTRACT FROM AUTHOR]

The paucity of evidence regarding the safety of gestational antipsychotic exposure has led to treatment discontinuation in pregnant women with severe mental health conditions. This systematic review and meta-analysis aimed to summarise the current evidence on the association between gestational antipsychotic exposure and attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) in children (Study protocol registered in PROSPERO:CRD42022311354). Five studies included in our meta-analysis with around 8.6 million pregnancy episodes in nine different countries/regions. Results from our meta-analysis indicate that the heightened risks of ASD and ADHD in children gestationally exposed to antipsychotics appear to be attributable to maternal characteristics, rather than having a causal relationship with the antipsychotic exposure during pregnancy. The results underscore the importance of meticulously monitoring the neurodevelopment of children born to mothers with mental illnesses, which can facilitate early interventions and provide requisite support. • Increased risks of ADHD and ASD observed in children with prenatal antipsychotic exposure appear to be attributable to maternal characteristics, rather than having a causal relation to the antipsychotics itself. • Antipsychotic treatment during pregnancy could be considered when clinically indicated. • Future research investigating the effect of individual antipsychotics or dosing regimens is suggested. [ABSTRACT FROM AUTHOR]

Prostaglandin E2 (PGE2) is a potent lipid mediator of inflammation that modulates immune cell function by binding to unique G protein‐coupled receptors (EP receptors). PGE2 production increases during microbial infection and inflammation. In this study, we assessed the effect of PGE2 on the phagocytosis of bacteria by neutrophils, which are key players during infection and inflammation. We also looked for specific EP receptor signaling pathways that contributed to the neutrophil phagocytic activity. PGE2 (50–1000 ng/ml) inhibited the phagocytosis of Escherichia coli by HL‐60 human neutrophils in a concentration‐dependent manner. Inhibition of neutrophil phagocytosis by PGE2 correlated with increased intracellular cyclic adenosine monophosphate (cAMP) production, and forskolin, an adenosyl cyclase agonist, confirmed the inhibitory effect of cAMP stimulation on neutrophil phagocytosis. The expression of EP2 receptors by HL‐60 cells was confirmed by western blot analysis, and selective agonism of EP2 receptors mimicked the inhibition of phagocytosis by PGE2. The EP2 receptor antagonist AH‐6089 partially blocked the inhibition of neutrophil phagocytosis PGE2. Specific inhibition of phosphatase and tensin homolog (PTEN) enzyme attenuated the inhibition of neutrophil phagocytosis by PGE2, and both PGE2 and increased intracellular cAMP increased neutrophil PTEN activity, which was associated with decreased PTEN phosphorylation. The results support negative regulation of the antimicrobial activity of neutrophils (i.e., phagocytosis), which has important implications for the future management of bacterial infections. [ABSTRACT FROM AUTHOR]

Athanasiadis characterized the freeness of the cones of the arrangements between braid arrangements and Shi arrangements. We are interested in the subarrangements Shi(G) of Shi arrangements associated with a graph G, which may not contain all hyperplanes of braid arrangements. We classify the cones of the arrangements Shi(G) which are free. In the meanwhile, we give the graphical interpretation of the exponents of free arrangements c (Shi(G)). [ABSTRACT FROM AUTHOR]

The integration of the strapdown inertial navigation system (SINS) and Doppler velocity log (DVL) has become a basic navigation solution for Autonomous Underwater Vehicles (AUVs). However, DVL cannot obtain the velocity relative to the ground when the distance between the AUV and seabed is over the operating range, which occurs often when AUVs are sailing in the middle layer of the ocean. When the DVL velocity relative to the current is used for an integrated filter, the unknown current velocity is coupled with the measured velocity error, which decreases the positioning accuracy. To address this problem, the effect of unknown coupled current velocity is analyzed from the perspective of filter observability, and an integrated SINS/DVL/virtual velocity navigation method is proposed. The virtual velocity based on the velocity variation extracted from the inertial measurement unit and DVL is constructed and used as an aided measurement for the Kalman filter. With the help of virtual velocity, the current velocity can be easily decoupled from measured SINS velocity error. The results of simulation and experiments demonstrated that the proposed method can effectively improve both the convergence speed and accuracy of velocity error compared with the classical method with SINS/DVL integration and, thus, significantly improve the positioning accuracy. [ABSTRACT FROM AUTHOR]

The Beiya porphyry‐skarn Au deposit is one of the largest gold deposits in China, temporally and spatially associated with Eocene intrusions in a post‐collisional setting in western Yunnan, China. In this study, we report new whole‐rock geochemistry, Sr‐Nd isotope, zircon U‐Pb geochronology and in situ zircon Hf‐O isotopes of quartz‐monzonite and biotite‐monzonite porphyries from the Beiya deposit. The porphyry‐skarn mineralization at the Beiya deposit is mainly associated with the quartz monzonite porphyry (35.8 ± 0.6 Ma), while the biotite‐monzonite porphyry (34.3 ± 0.5 Ma) represents a post‐mineralization intrusion crosscutting the main orebodies and the quartz‐monzonite porphyry. Both intrusions have high‐K and adakitic composition and are characterized by high Sr/Y ratios, high SiO2 and Al2O3 concentrations (SiO2 = 69.80–73.86 wt%; Al2O3 = 14.11–15.19 wt%), and low MgO, Cr, and Ni concentrations (MgO = 0.2–1.0 wt%; Cr = 1.76–11.13 ppm; Ni = 2.52–11.72 ppm). Their Sr‐Nd isotope compositions (87Sr/86Sr = 0.7066–0.7077; εNd(t) = –5.3 to –1.5) are consistent with the lower crustal‐derived amphibolite xenoliths (87Sr/86Sr = 0.7060–0.7100; εNd(t) = –10.0 to 0.0), indicating that they might be derived from a thickened juvenile lower crust beneath the Yangtze Craton. The biotite‐monzonite porphyry has lower zircon δ18O values of +5.3‰ to +6.8‰ and higher εHf(t) values of –2.3 to +5.5 than those of the quartz‐monzonite porphyry with δ18O values of +7.1‰ to +8.2‰ and εHf(t) values of –3.8 to +1.5, implying that they were derived from different parts of the lower crust. High Ba/La and Pb/Ce ratios suggest that the quartz‐monzonite porphyry is derived from a volatiles‐rich reservoir. Relatively higher La/Yb, Sm/Yb and Dy/Yb ratios of the biotite‐monzonite porphyry indicate residual garnet in the source, indicating a deeper source than that of the quartz‐monzonite porphyry. The hydrous components should be represented by the amphibole‐rich lithologies, which has relatively shallower depth than that of the garnet‐bearing mafic thickened lower crust. Our data suggest that the mineralized quartz‐monzonite porphyry at the Beiya deposit is derived from partial melting of amphibole‐rich lithologies in the upper part of the thickened juvenile lower crust beneath the Yangtze Craton, while the post‐mineralization biotite‐monzonite porphyry is derived from the basal, and volatiles‐poor, part of the juvenile lower crust. [ABSTRACT FROM AUTHOR]

Vertical and lateral heterostructures consisting of atomically layered two-dimensional (2D) materials exhibit intriguing properties, such as efficient charge/energy transfer, high photoresponsivity, and enhanced photocatalytic activities. However, the controlled fabrication of vertical or lateral heterojunctions on metal substrates remains challenging. Herein, we report a facile and controllable method for selective growth of WS2/MoS2 vertical or lateral heterojunctions on polycrystalline gold (Au) foil by tuning the gas flow rate of hydrogen (H2). We find that lateral growth is favored without H2, whereas vertical growth mode can be switched on by introducing 8–10 sccm H2. In addition, the areal coverage of the WS2/MoS2 vertical heterostructures is tunable in the range of 12–25%. Transmission electron microscopy (TEM) and selected area electron diffraction (SAED) results demonstrate the quality and absence of cross-contamination of the as-grown heterostructures. Furthermore, we investigate the effects of the H2 flow rate on the morphology of the heterostructures. These pave the way to develop unprecedented 2D heterostructures towards applications in (opto)electronic devices. [ABSTRACT FROM AUTHOR]