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An internal geomembrane (GMB)–clay seepage control system is an important form of seepage control structure for rockfill dams. In order to investigate the stress and deformation characteristics of GMB in GMB–clay core-wall rockfill dams (GMCWRD) under different construction and operation conditions, the stress and deformation fields of GMCWRDs were calculated by numerical simulation under a variety of working conditions. The stress and deformation characteristics of the dam and GMB during the impoundment period were investigated, and the influences of the spreading thickness of the clay core-wall and the location of the GMB defects and hydraulic head on the stress and deformation of the GMB were analyzed. The results show that the maximum tensile strain of the GMB upstream of the clay core-wall during the impoundment period occurs at the anchorage of the GMB and the concrete cut-off, with a maximum tensile strain of 2.70%. With the increase in the spreading thickness of the clay core-wall, the maximum tensile stress and strain of the GMB fluctuated. Under the dam construction and foundation conditions in this paper, when the spreading thickness of the clay core-wall was 2 m, the tensile stress and strain of GMB were at the lowest level. As the defect location of the GMB decreases, the phreatic line of the dam gradually increases, and the seepage discharge of the dam and the tensile strain of the GMB gradually increase, with the maximum tensile strain of 3.98%. The maximum deformation of the GMB in each case is much smaller than the maximum elastic deformation range of the selected PVC GMB, and the conclusion of the study provides a certain scientific basis for the design and construction of the seepage control of the core rockfill dam.

Among the marine gravity field models derived from satellite altimetry, the Scripps Institution of Oceanography (SIO) series and Denmark Technical University (DTU) series models are the most representative and are often used to integrate global gravity field models, which were inverted by the deflection of vertical method and sea surface height method, respectively. The fusion method based on the offshore distance used in the EGM2008 model is just model stitching, which cannot realize the true fusion of the two types of marine gravity field models. In the paper, a new fusion method based on water depth segmentation is proposed, which established the Precision–Depth relationship of each model in each water depth segment in the investigated area, then constructed the FUSION model by weighted fusion based on the precision predicted from the Precision–Depth relationship at each grid in the whole region. The application in the South China Sea shows that the FUSION model built by the new fusion method has better accuracy than SIO28 and DTU17, especially in shallow water and offshore areas. Within 20 km offshore, the RMS of the FUSION model is 5.10 mGal, which is 8% and 4% better than original models, respectively. Within 100 m of shallow water, the accuracy of the FUSION model is 4.01 mGal, which is 14% and 12% higher than the original models, respectively. A further analysis shows that the fusion model is in better agreement with the seabed topography than original models. The new fusion method can blend the effective information of original models to provide a higher-precision marine gravity field.

Germanium (Ge) has played a key role in silicon photonics as an enabling material for datacom applications. Indeed, the unique properties of Ge have been leveraged to develop high performance integrated photodectors, which are now mature devices. Ge is also very useful for the achievement of compact modulators and monolithically integrated laser sources on silicon. Interestingly, research efforts in these domains also put forward the current revolution of mid-IR photonics. Ge and Ge-based alloys also present strong advantages for mid-infrared photonic platform such as the extension of the transparency window for these materials, which can operate at wavelengths beyond 8 μm. Different platforms have been proposed to take benefit from the broad transparency of Ge up to 15 μm, and the main passive building blocks are now being developed. In this review, we will present the most relevant Ge-based platforms reported so far that have led to the demonstration of several passive and active building blocks for mid-IR photonics. Seminal works on mid-IR optical sensing using integrated platforms will also be reviewed.

This study presents an optimized design for a Segmented Sinusoidal Parameter Winding with Magnetic Wedge Variable Reluctance Resolver (SSPWMW-VRR), addressing challenges like winding asymmetry and harmonic distortion in conventional designs. By integrating particle swarm optimization (PSO) for winding design, magnetic equivalent circuit (MEC) analysis for leakage flux, and machine learning techniques (XGBoost and Multi-Layer Perceptron), the stator slot shape was fine-tuned for improved accuracy. XGBoost outperformed MLP in prediction accuracy with a mean absolute error (MAE) of 0.1172. Finite element analysis (FEA) simulations and experimental validation demonstrated a reduction in position errors from ±30′ in conventional VRRs to ±5′ in the optimized design, along with significant harmonic reduction.

This study aims to explore the association between hearing impairment, visual impairment, dual sensory impairment, and depressive symptoms in middle-aged and elderly populations in China, with an analysis of gender differences. This research is based on data from the nationally representative sample survey CHARLS, conducted from 2013 to 2020. A total of 9,780 participants were included in the study. These participants were divided into four groups based on their hearing and vision status: no impairment, hearing impairment only, visual impairment only, and dual sensory impairment. A longitudinal analysis was conducted using Cox regression models to assess the hazard ratios (HR) for the occurrence of depressive symptoms associated with hearing, visual, and dual sensory impairments. The Cox regression model indicated that, in the unadjusted model, hearing impairment, visual impairment, and dual sensory impairment were all risk factors for depression ( P  < 0.05). After adjusting for multiple confounding factors, compared to the no impairment group, the risk of depressive symptoms was 1.017 times higher (95% CI 0.886–1.167) in the hearing impairment group, with a gender-specific risk of 1.072 times (95% CI  0.880–1.305) for males and 0.962 times (95% CI  0.793–1.168) for females. The visual impairment group had a 1.118 times higher risk (95% CI  1.017–1.231), with a risk of 1.092 times (95% CI  0.946–1.262) for males and 1.155 times (95% CI  1.017–1.311) for females. The dual sensory impairment group had a 1.274 times higher risk (95% CI  1.165–1.393), with a gender-specific risk of 1.291 times (95% CI  1.131–1.473) for males and 1.267 times (95% CI  1.123–1.429) for females. Visual impairment and dual sensory impairment are independent risk factors for the occurrence of depressive symptoms, with notable gender differences. Understanding these associations and gender differences can help in developing more effective interventions to improve the mental health of middle-aged and elderly populations.

NRC publication: Yes

Selective pressure targeting male functions plays a crucial role in the evolution of floral morphological traits. In some angiosperm groups, flowers contain two or more sets of stamens that vary in size, color, and morphology, a phenomenon known as heteranthery. This reflects an evolutionary adaptation of stamens. However, the developmental basis and molecular mechanisms remain poorly understood. This study integrates transcriptomic and developmental approaches to elucidate the molecular and morphological mechanisms underlying intra-floral stamen differentiation in Cassia fistula L., an economic leguminous tree exhibiting heteranthery with three distinct stamen types: long stamens (LS), short stamens (SS), and degenerated stamens (St). We documented asynchronous stamen primordia initiation and development trajectories across stamen types. Transcriptomic profiling and protein–protein interaction analysis identified differentially expressed genes (DEGs) between filaments of the three stamen sets, with significant enrichment in brassinosteroid (BR) related pathways. CYP90D1 (Cf_f49903) and CYP90C1 (Cf_f56973) emerged as candidate genes related to stamen length differentiation in C. fistula. This study not only helped elucidate the developmental and genetic framework of heteranthery in C. fistula but also provided new insights for exploring floral organ evolution in leguminous plants.

Cancer-related cognitive impairment is a significant clinical challenge observed in patients with breast cancer, manifesting during or after treatment. This impairment leads to deteriorations in memory, processing speed, attention, and executive functioning, which profoundly impact patients' occupational performance, daily living activities, and overall quality of life. Grounded in the Symptom Science Model 2.0, this study investigates the contributing factors to Cancer-related cognitive impairment in breast cancer patients and develops a predictive nomogram for this demographic. Employing both univariate and multivariate logistic regression analyses, this investigation delineates the predictive factors influencing outcomes in breast cancer patients. A nomogram was constructed leveraging these identified predictive factors, accompanied by internal validation through bootstrap resampling methodology (1000 bootstrap samples). The efficacy of the predictive model was assessed by employing the Hosmer–Lemeshow goodness-of-fit test and calibration curves. The prevalence of cognitive impairment in breast cancer patients was identified to be 45.83%.Multivariate logistic regression analysis identified the independent predictors of Cancer-related cognitive impairment in breast cancer patients as place of residence, educational level, chemotherapy, benefit finding, post-traumatic growth, anxiety, fear of cancer progression, and fasting blood glucose levels. these factors were integrated into the nomogram. The Hosmer–Lemeshow goodness-of-fit test demonstrated that the prediction model was appropriately calibrated (χ 2  = 11.520, P  = 0.174). Furthermore, the model exhibited an area under the curve of 0.955 (95% CI 0.939 to 0.971) and a sensitivity of 0.906, evidencing its robust discriminative capacity and accuracy. Utilizing the Symptom Science Model 2.0 as a framework, this study comprehensively examines the multifaceted factors influencing Cancer-related cognitive impairment in breast cancer patients, spanning five critical domains: complex symptoms, phenotypic characterization, biobehavioral factors, social determinants of health, and patient-centered experiences. A predictive nomogram model was established, demonstrating satisfactory predictive accuracy and capability. This model is capable of identifying breast cancer patients with cognitive impairments with high precision. The findings furnish empirical evidence in support of the early detection, diagnosis, and intervention strategies for high-risk breast cancer patients afflicted with Cancer-related cognitive impairment.

HY-2A (Haiyang-2A), launched in 2011, is the first ocean dynamic environment satellite of China and is equipped with a radar altimeter as one of the primary payloads. HY-2A shifted the drift orbit in March 2016 and has been accumulating geodetic mission (GM) data for more than three years with 168-day cycle. In this paper, we present the preliminary gravity field inverted by the HY-2A/GM data from March 2016 to December 2017 near Taiwan (21°–26°N, 119°–123°E). The gravity anomaly is computed by Inverse Vening Meinesz (IVM) formula with a one-dimensional FFT method during remove-restore procedure with the EGM2008 gravity model as the reference field. For comparison, CryoSat-2 altimeter data are used to inverse the gravity field near Taiwan Island by the same method. Comparing with the gravity field derived from CryoSat-2, a good agreement between the two data sets is found. The global ocean gravity models and National Geophysical Data Center (NGDC) shipboard gravity data also are used to assess the performance of HY-2A/GM data. The evaluations show that HY-2A and CryoSat-2 are at the same level in terms of gravity field recovery and the HY-2A/GM altimeter-derived gravity field has an accuracy of 2.922 mGal. Therefore, we can believe that HY-2A will be a new reliable data source for marine gravity field inversion and has the potentiality to improve the accuracy and resolution of the global marine gravity field.

Background Salinity stress impairs cotton growth and fiber quality. Protoplasts enable elucidation of early salt-responsive signaling. Elucidating crop tolerance mechanisms that ameliorate these diverse salinity-induced stresses is key for improving agricultural productivity under saline conditions. Results Herein, we performed transcriptome profiling of Gossypium arboreum root tips and root tips-derived protoplasts to uncover salt tolerance genes and mechanisms. Differentially expressed genes (DEGs) were significantly enriched in the plant hormone signal transduction and MAPK signaling pathways. Transcriptome based weighted gene coexpression network analysis (WGCNA) clustered 885 commonly differentially expressed genes into four distinct modules. Black and yellow modules were highly upregulated under salt treatment, containing hub genes integral to signaling and transport, highlighting their importance. Differential expression analysis revealed more dynamic changes in protoplasts, identifying key genes including the Ga-α-expansin 4 ( GaEXPA4) . Silencing of the GaEXPA4 gene through virus-induced gene silencing heightened cotton’s sensitivity to salt stress, leading to increased wilting, elevated lipid peroxidation, and impaired antioxidant activity under salt conditions compared to controls. Conclusion These findings underscore the functional significance of GaEXPA4 in the salt stress response. Future research should focus on elucidating the precise mechanisms of putative salt tolerance genes like GaEXPA4 and evaluating the potential of signaling pathways, such as MAPK, for engineering enhanced salt resilience in cotton. Integrating multi-omics approaches could further expand the genetic resources available for improving cotton cultivation in saline environments.