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The recent boom in multifunction portable electronic equipments requires the development of compact and miniaturized electronic circuits with high efficiencies, low costs and long lasting time. For the operation of most line-powered electronics, alternating current (ac) line-filters are used to attenuate the leftover ac ripples on direct current (dc) voltage busses. Today, aluminum electrolytic capacitors (AECs) are widely applied for this purpose. However, they are usually the largest components in electronic circuits. Replacing AECs by more compact capacitors will have an immense impact on future electronic devices. Here, we report a double-layer capacitor based on three-dimensional (3D) interpenetrating graphene electrodes fabricated by electrochemical reduction of graphene oxide (ErGO-DLC). At 120-hertz, the ErGO-DLC exhibited a phase angle of −84 degrees, a specific capacitance of 283 microfaradays per centimeter square and a resistor-capacitor (RC) time constant of 1.35 milliseconds, making it capable of replacing AECs for the application of 120-hertz filtering.

Long-term exposure to air pollutants and diabetes are both linked to cancer development. However, their combined effect remains unclear. This study examined the relationship between air pollutants and cancer incidence, with diabetes as a potential mediator. Data from 10,590 participants in the 2015 China Health and Retirement Longitudinal Study (CHARLS) were analyzed. Participants were grouped based on cancer diagnosis, and air pollutant exposure levels were estimated using satellite-based spatiotemporal models. Generalized linear regression and restricted cubic spline (RCS) analysis were used to assess the impact of air pollutants and diabetes in covariates-adjusted models. Further analyses, including conditional independence test, mediation effect and sensitivity analysis based on Bayesian networks, were performed to further analyze specific air pollutants. After adjusting for covariates, particulate matter (PM) (PM ≤ 1 μm in aerodynamic diameter [PM 1 ], PM 2.5 , ammonium (NH 4 ), nitrate (NO 3 ) and diabetes showed significant associations with cancer incidence. RCS analysis confirmed significant direct effects of PM 2.5 and PM 10 on cancer and the mediated effects of diabetes. The interaction between diabetes and both PM 2.5 and PM 10 was further supported by conditional independence tests, highlighting diabetes as a significant mediator in the PM 2.5 -cancer relationship. This study offers a novel perspective by identifying diabetes as a key intermediary in the association between PM 2.5 exposure and cancer risk, providing evidence that diabetes plays a significant mediating role in air pollutant-related cancer development.

The landslide hazard assessment plays a crucial role in landslide risk mitigation and land use planning. The result of landslide hazard assessment corrected by surface deformation, obtained through time-series InSAR, has usually proven to have good application capabilities. However, the issue lies in the uncertainty of InSAR results, where some deformations cannot be calculated, and some are not true deformations. This uncertainty of InSAR results will lead to errors in landslide hazard assessment. Here, we attempt to evaluate landslide hazards by considering combined rainfall and surface deformation. The main objective of this research was to mitigate the impact of bias and explore the accurate landslide hazard assessment method. A total of 201 landslides and 11 geo-environment factors were utilized for landslide susceptibility assessment by support vector machine (SVM) model in Wanzhou District, Three Gorges Reservoir Area (TGRA). The preliminary hazard is obtained by analyzing the statistical data of landslides and rainfall. Based on the SAR image data of Sentinel-1A satellites from September 2019 to October 2021, the SBAS-InSAR method was used to analyze surface deformation. The correlation between surface deformation and rainfall was analyzed, and the deformation factor variables were applied to landslide hazard assessment. The research results demonstrate that the error caused by the uncertainty of InSAR results can be effectively avoided by analyzing the relationship between rainfall and surface deformation. Our results can effectively adjust and correct the hazard results and eliminate the errors in the general hazard assessment. Our proposed method can be used to assess the landslide hazard in more detail and provide a reference for fine risk management and control.

Landslide identification in alpine and canyon areas is difficult due to the terrain limitations. The main objective of this research was to explore the method of combining small baseline subset interferometric synthetic aperture radar (SBAS-InSAR), multi-temporal optical images and field surveys to identify potential landslides in the human-modified alpine and canyon area of the Niulan River in southwestern China based on terrain visibility analysis. The visibility of the terrain is analyzed using the different incident and heading angles of the Sentinel satellite’s ascending and descending orbits. Based on the SAR image data of Sentinel-1A satellites from 2016 to 2019, the SBAS-InSAR method was used to identify landslides, and then multi-temporal optical images were used to facilitate landslide identification. Field surveys were carried out to verify the identification accuracy. A total of 28 landslides were identified, including 13 indicated by SBAS-InSAR, 8 by optical imaging and 7 by field investigation. Many landslides were induced by the impoundment and fluctuation of reservoir water. The comparison and verification of typical landslide monitoring data and reservoir water fluctuations revealed that a sudden drop of reservoir water had a great influence on landslide stability. These research results can facilitate a comprehensive understanding of landslide distribution in the reservoir area and guide the follow-up landslide risk management.

Uterine corpus endometrial carcinoma (UCEC) is becoming a main malignant cancer that threaten to women's health. Thymidine kinase 1 (TK1) is considering to be associated with tumorigenesis and development. Nevertheless, the function of TK1 in UCEC is still unclear. Herein, we analyzed the TK1 expression level in pan-cancer and found that TK1 was upregulated in a variety of cancers including UCEC. Patients of UCEC with high expression of TK1 were related to poor outcome. TK1 was also related to clinical stage, histologic grade and lymph node metastasis. Abnormal expression of TK1 in UCEC was related to promoter methylation while gene mutation was not frequent. TK1 and its associated genes appeared to be prominent in cell cycle and DNA replication, according to GO and KEGG analysis. Analysis of immune infiltration revealed a negative correlation between TK1 and CD8 + T cells, macrophages, and dendritic cells. In vitro experiments, TK1 knockdown resulted in the inhibition of proliferation, migration, invasion and EMT in UCEC cell lines.

High cut-slopes are widespread in engineering constructions and often converted into landslides. Some extreme circumstances facilitate the landslide process, such as the weak bedding plane, rainfall, and faults. Therefore, this paper intends to offer insights into the influence of the weak bedding plane, extreme rainfall as well as faults on the landslide process of the high cut-slope. In this paper, the Anling landslide in Anhui Province, China, is selected as an example. Geological surveys, displacement monitoring, data analysis, as well as numerical simulation are carried out. The entire excavation construction and landslide deformation process are simulated to reveal the formation mechanism of the landslide using the finite difference code, FLAC3D. The effects of the fault on the landslide and the effectiveness of adjusting protection measures by adding piles are investigated on the basis of the finite difference analysis. According to monitoring data and numerical simulation, the weak bedding plane and extreme rainfall are considered the main factors leading to the Anling landslide. Field investigation and numerical experiments indicate that the fault shall facilitate and accelerate the landslide process. The construction of piles in a suitable position for the landslide is a reasonable and economical measure to stabilize the landslide.

Background Neurodevelopmental disorders (NDDs), such as Attention-Deficit/Hyperactivity Disorder (ADHD), Autism Spectrum Disorder (ASD), and Tourette Syndrome (TS), have been extensively studied for their multifaceted impacts on social and emotional well-being. Recently, there has been growing interest in their potential relationship with fracture risks in adulthood. This study aims to explore the associations between these disorders and fracture rates, in order to facilitate better prevention and treatment. Methods Employing a novel approach, this study utilized Mendelian randomization (MR) analysis to investigate the complex interplay between ADHD, ASD, TS, and fractures. The MR framework, leveraging extensive genomic datasets, facilitated a systematic examination of potential causal relationships and genetic predispositions. Results The findings unveil intriguing bidirectional causal links between ADHD, ASD, and specific types of fractures. Notably, ADHD is identified as a risk factor for fractures, with pronounced associations in various anatomical regions, including the skull, trunk, and lower limbs. Conversely, individuals with specific fractures, notably those affecting the femur and lumbar spine, exhibit an increased genetic predisposition to ADHD and ASD. In this research, no correlation was found between TS and fractures, or osteoporosis.These results provide a genetic perspective on the complex relationships between NDDs and fractures, emphasizing the importance of early diagnosis, intervention, and a holistic approach to healthcare. Conclusion This research sheds new light on the intricate connections between NDDs and fractures, offering valuable insights into potential risk factors and causal links. The bidirectional causal relationships between ADHD, ASD, and specific fractures highlight the need for comprehensive clinical approaches that consider both NDDs and physical well-being.

The Cas13a system has great potential in RNA interference and molecular diagnostic fields. However, lacking guidelines for crRNA design hinders practical applications of the Cas13a system in RNA editing and single nucleotide polymorphism identification. This study posits that crRNAs with hairpin spacers improve the specificity of CRISPR/Cas13a system (termed hs‐CRISPR). Gibbs free energy analysis suggests that the hairpin‐spacer crRNAs (hs‐crRNAs) suppress Cas13a's affinity to off‐target RNA. A hepatitis B virus DNA genotyping platform is established to further validate the high‐specificity of hs‐CRISPR/Cas13a system. Compared to ordinary crRNA, hs‐crRNAs increase the specificity by threefold without sacrificing the sensitivity of the CRISPR/Cas13a system. Furthermore, the mechanism of the Cas13a/hs‐crRNA/target RNA composition is elucidated with theoretical simulations. This work builds on the fundamental understanding of Cas13a activation and offers significant improvements for the rational design of crRNA for the CRISPR/Cas13a system. This study proposes that hairpin‐spacer crRNAs (hs‐crRNA) improve the specificity of CRISPR/Cas13a system (hs‐CRISPR). Gibbs free energy analysis and experimental data demonstrate that hs‐crRNAs suppress Cas13a's activity to nonspecific targets. This work provides a fundamental understanding of Cas13a activation associated with binding energetics and an efficient strategy for high‐specificity crRNA design.

The accurate and efficient inversion of permeability coefficients is significant for the scientific assessment of seepage safety in concrete face rockfill dams. In addressing the optimization challenge of permeability coefficients with few samples, multiple parameters, and strong nonlinearity, this paper proposes a novel intelligent inversion method based on the Sobol-IDBO-SVR fusion surrogate model. Firstly, the Sobol sequence sampling method is introduced to extract high-quality combined samples of permeability coefficients, and the equivalent continuum seepage model is utilized for the forward simulation to obtain the theoretical hydraulic heads at the seepage monitoring points. Subsequently, the support vector regression surrogate model is used to establish the complex mapping relationship between the permeability coefficients and hydraulic heads, and the convergence performance of the dung beetle optimization algorithm is effectively enhanced by fusing multiple strategies. On this basis, we successfully achieve the precise inversion of permeability coefficients driven by multi-intelligence technologies. The engineering application results show that the permeability coefficients determined based on the inversion of the Sobol-IDBO-SVR model can reasonably reflect the seepage characteristics of the concrete face rockfill dam. The maximum relative error between the measured and the inversion values of the hydraulic heads at each monitoring point is only 0.63%, indicating that the inversion accuracy meets the engineering requirements. The method proposed in this study may also provide a beneficial reference for similar parameter inversion problems in engineering projects such as bridges, embankments, and pumping stations.