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Silicon‐based materials are regarded as the most promising negative electrode materials for next‐generation high‐energy lithium ion batteries due to their high theoretical capacity, low lithiation plateau and low cost, but they still suffer from dramatic volume variation during charge/discharge and sluggish kinetics, substantially restricting their practical applications. Recently, 2D MXenes are demonstrated to improve the electrochemical performances of Si‐based materials owing to their metallic conductivity, large surface aspect ratio, rich surface chemistry, good mechanical strength, etc. Serving as conductive host, MXenes can alleviate the volume expansion of Si during lithiation, enhance the electronic conductivity of the composite and facilitate the electron/ion transport, thus making the resultant Si/MXene composites exhibit excellent performance as negative electrodes of secondary batteries. Herein, an overview toward the recent advances of Si/MXene nanocomposites is presented for lithium storage applications. The preparation strategies and structural characteristics of the Si/MXene nanocomposites are introduced. The applications of diverse Si/MXene nanostructures such as powders, 3D architectures, films and fibers, in lithium ion batteries with corresponding structure‐performance relationships are discussed. Finally, the challenges and perspectives for the future research of Si/MXene nanocomposites are highlighted, aiming to provide a fundamental reference in designing advanced Si/MXene nanocomposites for high‐energy lithium ion batteries. [ABSTRACT FROM AUTHOR]

Deep learning has demonstrated notable success in mechanical signal processing with a large amount labelled data. However, the systems of the Jiaolong deep‐sea submersible prone to malfunction are typically diverse, due to the high complexity of its structure and operational environment. Consequently, this diversity gives rise to variations in the types of sensor signals and their associated data distributions that require analysis. Unsupervised domain adaptation (UDA) uses transferable knowledge derived from the source domain and applies it to an unlabelled target domain in order to improve the reusability of pre‐existing models and data. Inspired by the diffusion models that have the robust capabilities to transform data distributions across a large gap, we propose a novel diffusion‐based unsupervised domain adaptation (diffusion‐UDA) model, which leverages contrastive learning to alleviate the challenges of cross‐domain analysis for fault diagnosis within different systems of the deep‐sea submersible. Experimental results show the proposed method achieves state‐of‐the‐art performance on various benchmarks. [ABSTRACT FROM AUTHOR]

At high cutting speeds, the internal microstructure of the difficult-to-machine material Inconel 718 will change. Alterations in the internal microstructure lead to macroscopic deformations, which in turn result in the formation of adiabatic shear bands. In order to better study the formation of adiabatic shear bands during cutting Inconel 718, cutting experiments, SHPB experiments, and finite element simulations were carried out. The stored energy model for adiabatic shear bands was developed by combining the overall dislocation density and the variation of the stress field in this paper. Based on the strain gradient theory, the subroutine was compiled for secondary development to achieve multi-scale finite element simulation that can visualize the stored energy. The experiment and simulation results were combined to derive the change in stress, temperature, and overall dislocation density and to analyze the adiabatic shear bands storage energy based on the change. The analytical results are also combined with dynamic recrystallization and periodic fracture theories to characterize the formation mechanism of adiabatic shear bands. It was found that the overall dislocation density, stress, and adiabatic shear bands storage energy follow the same trend, while the temperature and shear zone storage energy follow opposite trends. [ABSTRACT FROM AUTHOR]

Electric vehicles have been considered into effective solutions to address energy problems in urban traffic systems for their remarkable performance in energy costs and carbon emissions reduction. However, the energy-saving effect of electric vehicles in urban traffic systems is restricted due to the complexities arising from mixed traffic conditions. To improve energy efficiency, this paper proposes an eco-driving-based mixed vehicular platoon control model for successive signalized intersections with connected and autonomous vehicles (CAVs), connected vehicles (CVs) and manned vehicles (MVs). Firstly, the dynamics model and spacing policy are analyzed, then the optimal platoon size and speed are calculated according to different traffic scenarios. Secondly, the mixed vehicular platoon control algorithm is established by considering traffic timing, energy consumption and string stability. Thirdly, an actual eco-driving-based platoon control system for tested electric vehicles is designed. The field test results demonstrate that all platoons can pass through intersections during green phase with minimum energy consumption, meanwhile the string stability can be guaranteed. It is noteworthy that the proposed model can greatly improve urban traffic capacity and energy efficiency. • A novel dynamical model of mixed vehicular platoon is explored by integrating different characteristics of CAV, CV, and MV. • An optimal speed algorithm of the leading vehicle to pass through successive signalized intersections is proposed according to signal timing, vehicular speed, and entry time. • The eco-driving-based mixed vehicular platoon control model is established, and the multi-objective function considering traffic environmental constraints are formulated to minimize the travel time and energy consumption. [ABSTRACT FROM AUTHOR]

Diabetes mellitus (DM) is a disease that affects millions of individuals worldwide and is characterized by abnormal glucose metabolism that can induce severe damage to numerous organs throughout the body. Sex differences have been demonstrated in a number of factors associated with diabetes and its complications, such as diabetic kidney disease and diabetic liver disease. To investigate the sex differences in DM further, the changes in the weight, food and water intake, and blood sugar of mice were recorded for 8 weeks in the present study. Hematoxylin and eosin staining, Masson's trichrome staining and transmission electron microscopy were used to observe the pathological changes of liver and kidney tissues. There is no significant difference in the water intake and blood glucose concentration between db/db female and male mice was observed. However, sex differences in liver and kidney damage including glomerular injury and hepatic fibrosis were found. In conclusion, the present study characterized the features of liver and kidney damage in db/db mice and indicated that sex differences should be taken into account in experiments using female and male experimental animals. Furthermore, sex differences should be taken into account in the selection of drug interventions in experiments and in clinical drug therapy. [ABSTRACT FROM AUTHOR]

• Epitope molecularly imprinted polymer was prepared by autoxidation of caffeic acid. • High adsorption capacity and selectivity toward ovalbumin were achieved. • The polymer was successfully applied to enrich ovalbumin in egg white samples. Food allergy can lead to severe allergic reactions that are potentially fatal for human, hence the detection of food allergens such as ovalbumin (OVA) is important. In this study, a poly(caffeic acid)-coated epitope molecularly imprinted polymer (EMIP) was prepared by chelation and autoxidation of caffeic acid with hexamethylenediamine. EMIP has not only imprinted cavities highly matched with OVA in size and spatial structure, but also externally abundant hydrophilic groups, resulting in few non-specific binding and good hydrophilicity. With high specificity, significant paramagnetism, and great reusability, EMIP can distinguish OVA from other proteins and selectively enrich OVA in egg white samples, which opens up a promising route to the determination of allergens in food products. [ABSTRACT FROM AUTHOR]

Purpose: Financial toxicity is used to describe the financial hardship experienced by cancer patients. Financial toxicity may cause negative consequences to patients, whereas little is known in Chinese context. This study aimed to explore the level of financial toxicity, coping strategies, and quality of life among Chinese patients with hematologic malignancies. Patients and methods: We conducted a prospective, observational study among 274 Chinese patients with hematologic malignancies from November 2021 to August 2022 in Sun Yat-sen University Cancer Center. Clinical data were extracted from electronic clinical records. Data on financial toxicity, coping strategies, and quality of life were collected using PRO measures. Chi-square or independent t test and multivariate logistic regression were performed to explore the associated factors of financial toxicity and quality of life, respectively. Effects of financial toxicity on coping strategies were examined using Chi-square. Results: The mean age of the participants was 50.2 (± 14.6) years. Male participants accounted for 57.3%. About half of the participants reported high financial toxicity. An average median of ¥200,000 on total medical expenditures since the diagnosis was reported. The average median monthly out-of-pocket health expenditure relating to cancer treatment was ¥20,000 (range ¥632–¥172,500) after reimbursement. Reduce daily living expenses (64.9%), borrowing money (55.7%), and choosing cheaper regimens (19.6%) were the commonly used strategies to cope with financial burden. Financial toxicity was negatively associated with quality of life (β = 0.071, P = 0.001). Conclusions: Financial toxicity was not uncommon in patients with hematological malignancies. Reducing daily living expenses, abandoning treatment sessions, and borrowing money were the strategies commonly adopted by participants to defray cancer costs. Additionally, participants with high level of financial toxicity tended to have worse quality of life. Therefore, actions from healthcare providers, policy-makers, and other stakeholders should be taken to help cancer patients mitigate their financial toxicity. [ABSTRACT FROM AUTHOR]

The droplet digital Polymerase Chain Reaction (ddPCR) has garnered recognition for its distinctive attribute of absolute quantification. And it has found practical utility in age prediction through DNA methylation profiles. However, a prevalent limitation in current ddPCR methodologies is the restricted capacity to detect only two targets concurrently in most instruments, leading to high costs, sample wastage, and labor-intensive procedures. To address the limitations, a novel high-throughput ddPCR system allowing for the simultaneous detection of eight targets was developed. Through the implementation of a new 8-plex ddPCR assay, coupled with comprehensive linear regression analyses involving primers and probes ratios, diverse inputs of single CpG sites with distinct primers and probes, and varying plex assay configurations, stable DNA methylation values for four CpGs and stable measurement precisions for distinct multiplex systems were consistently observed. These findings pave the way for advancing the field of chemistry science by enabling more efficient and cost-effective methods. Furthermore, the comparative validation of ddPCR and SNaPshot demonstrated a remarkable concordance in results, and the system also displayed well in the field of various aspects, including species specificity, DNA input, and aged samples. In this study, the recommended input of bisulfite-converted DNA was determined to be 10–50 ng due to the double-positive droplets. Notably, the Pearson correlation coefficient squared values of four CpGs were 0.4878 (ASPA), 0.4832 (IGSF1), 0.6881 (COL1A1), and 0.6475 (MEIS1-AS3). And the testing set exhibited a mean absolute error of 4.5923 years, indicating the robustness and accuracy of the age-predictive model. [Display omitted] • A high-throughput 8-plex ddPCR system was developed to detect DNA methylation. • The new ddPCR system exhibited superior efficiency and cost-effectiveness. • A comprehensive validation was conducted to illustrate key performance metrics. • The methylation values through the ddPCR system have a good correlation with age. [ABSTRACT FROM AUTHOR]