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The ocean and coastal zones are rich in resources and closely related to human survival and development. In recent years, with the rapid growth of the ocean economy, issues such as the reduction of natural coastlines and coastal wetlands, decreased biodiversity, damaged typical ecosystems, frequent coastal disasters, and declining fishery resources have become increasingly apparent. How to enhance the ocean economy from a strategic perspective, promote both development and protection, and ensure the rational use of coastal zones and marine resources is an important issue in the new era. Land and ocean are inseparable components of the ecosystem, and conducting a comprehensive assessment of the resource and environmental carrying capacity of land and sea is an effective way to measure whether regional economic development and ecological environment are coordinated and sustainable. This paper systematically reviews the development process of the carrying capacity concept, compares commonly used methods for evaluating the resource and environmental carrying capacity of marine resources, preliminarily constructs an index system for evaluating the carrying capacity of marine resources based on land-sea coordination, proposes the use of entropy method to determine index weights, and adopts a state space evaluation model or TOPSIS model for comprehensive carrying capacity evaluation. This approach can reflect the interdependence and mutual constraints between land and ocean, and has strong operability. The evaluation results can reflect the spatial differences or temporal changes in the carrying capacity of regional resources and environment, and provide effective reference for the protection and utilization of oceans and coastal zones.

Chimeras are universal phenomena in the M1-generation plants obtained following radiation-induced mutagenesis; however, the mutational effects and variant inheritance mechanisms of related rice chimeras have yet to be sufficiently clarified. In this study, we used target capture-seq technology to obtain OsNramp5 mutant chimeras via carbon ion beam irradiation, and used a 10 kb liquid chip to determine the SNP/InDel mutational occurrence and genetic isolation characteristics of the chimeric M1 generation and mutational M2 genomes. The results revealed that the mutation detected in the OsNramp5 gene of M1 chimeric rice was not inherited by the M2 generation; that is, the mutation detected in somatic cells of the M1 population was not passed to the subsequent generation via the germ cells. In addition, conversion was established to be twice as common as transversion among the M1 genomic mutation types, although more than half of the variant sites were inherited by the M2 generation. However, these sites were rarely located within the functional coding regions of genes. Our findings in this study revealed the genomic variation characteristics of somatic M1-generation chimeras induced by carbon ion beam irradiation and their genetic characteristics in the M2 generation. These findings will provide a reference for further studies that seek to elucidate the mechanisms underlying chimeric mutation effects and for selecting appropriate procedures for mutagenesis breeding following carbon ion beam irradiation.

Focusing on a polarized issue—U.S. gun violence—this study examines agenda setting as an antecedent of political expression on social media. A state-of-the-art machine-learning model was used to analyze news coverage from 25 media outlets—mainstream and partisan. Those results were paired with a two-wave panel survey conducted during the 2018 U.S. midterm elections. Findings show mainstream media shape public opinion about gun violence, which then stimulates expression about the issue on social media. The study also reveals that partisan media's gun violence coverage has significant cross-cutting effects. Notably, exposure to conservative media will decrease public salience of gun violence, pivot opinion in a more conservative direction, and discourage social media expression; and all of these effects are stronger among liberals. [ABSTRACT FROM AUTHOR]

During the mining process, repetitive stress disturbances induced by mining activities can lead to alterations in the physical properties of coal, potentially resulting in rockburst occurrences within tunnels. To investigate the propagation rule of physical field characteristics and characteristics of failure in roadway surrounding rock under multiple disturbance damage caused by dynamic load, a combined experimental and theoretical analysis is conducted to study the weakening effect of rock mass under various disturbance circumstances. A model of roadway surrounding rock loosening and failure under multiple disturbances was proposed. The degree of damage is quantified by defining the weakening coefficient Di, A "weakening variable method" is proposed to confirm the main parameters of the Holmquist‐John‐son‐Cook (HJC) model under different disturbance conditions. The reliability of these findings was validated through a microseismic event at the Tangshan coal mine's 0250 working face in 2020, followed by numerical simulation studies. The results indicate that damaged coal weakens the intensity of stress waves at the same source velocity, with the strongest effect observed at interfaces between different damage zones. Furthermore, damaged coal exhibits a stronger weakening effect on stress wave propagation speed compared to undamaged coal in non‐interface areas. The study on roadway stability reveals that severely damaged coal‐rock samples significantly weaken stress waves; however, they also exhibit lower minimum energy for dynamic failure in roadway surrounding rock, indicating that low‐stress waves cause greater damage under severe damage conditions. The study investigates the impact of coal rock mass degradation on the stability of surrounding roadways under various disturbance conditions, which holds significant implications for the timely identification of potential instability risks in damaged coal bodies, optimization of support strategies, and ensuring mining safety. [ABSTRACT FROM AUTHOR]

Recently, methods based on Transformer have been widely used in the research field of hyperspectral image (HSI) change detection (CD). However, existing transformer-based CD research does not sufficiently utilize the spatial-spectral features of HSIs. In this article, we propose an interactive Siamese spatial-spectral cross-layer fusion Transformer (IS2CF-Former) network to improve the accuracy of HSI-CD. The proposed Siamese interactive module integrates the Siamese network with the Transformer structure, enhancing communication between bi-temporal images. We have made improvements to the cross-layer adaptive fusion (CAF) Transformer, where the cross-layer fusion module enhances the interaction between layers and the ability to capture local contextual features, concurrently reducing the model's parameter count to mitigate the risk of overfitting. The CAF Transformer is applied to extract spatial and spectral features. Evaluating the detection performance of the proposed model on three bi-temporal HSIs through extensive experiments demonstrates superior accuracy compared to seven excellent CD methods. [ABSTRACT FROM AUTHOR]

Objective. To explore the value of the injury severity score (ISS) and the new injury severity score (NISS) for evaluating injuries and predicting complications (pneumonia and respiratory failure) and poor prognoses (in‐hospital tracheal intubation, extended length of hospital stay, ICU admission, prolonged ICU stay, and death) in patients with thoracic trauma. Methods. The data of consecutive patients with thoracic trauma who were admitted to the department of cardiothoracic surgery of a tertiary hospital between January 2018 and December 2021 were retrospectively collected. ISS and NISS were calculated for each patient. The study outcomes were complications and poor prognoses. The differences in ISS and NISS between patients with complications and poor prognoses and patients without the abovementioned conditions were compared using the Mann‒Whitney U test. Discrimination and calibration of ISS and NISS in predicting outcomes were compared using the area under the receiver operating characteristic (ROC) curve (AUC) and Hosmer‒Lemeshow (H‐L) statistic. Results. A total of 310 patients were included. ISS and NISS of patients with complications and poor prognoses were greater than those of patients without complications and poor prognoses, respectively. The discrimination of ISS in predicting pneumonia, respiratory failure, in‐hospital tracheal intubation, extended length of hospital stay, ICU admission, prolonged ICU stay, and death (AUCs: 0.609, 0.721, 0.848, 0.784, 0.763, 0.716, and 0.804, respectively) was not statistically significantly different from that of NISS in predicting the corresponding outcomes (AUCs: 0.628, 0.712, 0.795, 0.767, 0.750, 0.750, and 0.818, respectively). ISS showed better calibration than NISS for predicting pneumonia, respiratory failure, in‐hospital tracheal intubation, extended length of hospital stay, and ICU admission but worse calibration for predicting prolonged ICU stay and death. Conclusion. ISS and NISS are both suitable for injury evaluation. There was no statistically significant difference in discrimination between ISS and NISS, but they had different calibrations when predicting different outcomes. [ABSTRACT FROM AUTHOR]

Surface-enhanced Raman scattering (SERS) is a pivotal analytical technique in sensing, yet it grapples with challenges such as reproducibility, substrate stability, and hotspot uniformity. The use of highly effective external field nanocomposites facilitates the dynamic manipulation of "hotspots"—the nanoscale gaps between metal nanoparticles—which is critical for SERS enhancement. The gap between 4-mercaptopyridine-modified (4-MPY) Fe3O4@SiO2@Au nanocomposites (FA) can be precisely reduced by applying an external magnetic field, resulting in up to a 30-fold increase in SERS signal intensity and an 8–39 times increase in the enhancement factor (EF). This approach markedly enhances SERS signal uniformity, demonstrated by the relative standard deviation of the EF dropping from 59.15–9.44% to 28.70–1.14%. By systematically studying the correlations between the SERS EF and the external-magnetic-field strength, hotspot density, and probe molecular density, sensitive magnetic, SERS platforms are established. The optimal hotspots occur in the magnetic field of 80 to 120 mT among the FA-4MPY nanocomposites, as validated by COMSOL finite-element analysis simulations. These findings offer a nuanced understanding of magnetic SERS hotspot tuning, paving the way for precise and improved molecular sensing. [ABSTRACT FROM AUTHOR]

Objectives: Subepithelial lesions (SELs) are associated with various endoscopic resection (ER) outcomes and diagnostic challenges. We aimed to establish a tool for predicting ER‐related outcomes and diagnosing SELs and to investigate the predictive value of endoscopic ultrasound (EUS). Methods: Phase 1 (system development) was performed in a retrospective cohort (n = 837) who underwent EUS before ER for SELs at eight hospitals. Prediction models for five key outcomes were developed using logistic regression. Models with satisfactory internal validation performance were included in a mobile application system, SEL endoscopic resection predictor (SELERP). In Phase 2, the models were externally validated in a prospective cohort of 200 patients. Results: An SELERP was developed using EUS characteristics, which included 10 models for five key outcomes: post‐ER ulcer management, short procedure time, long hospital stay, high medication costs, and diagnosis of SELs. In Phase 1, 10 models were derived and validated (C‐statistics, 0.67–0.99; calibration‐in‐the‐large, −0.14–0.10; calibration slopes, 0.92–1.08). In Phase 2, the derived risk prediction models showed convincing discrimination (C‐statistics, 0.64–0.73) and calibration (calibration‐in‐the‐large, −0.02–0.05; calibration slopes, 1.01–1.09) in the prospective cohort. The sensitivities and specificities of the five diagnostic models were 68.3–95.7% and 64.1–83.3%, respectively. Conclusion: We developed and prospectively validated an application system for the prediction of ER outcomes and diagnosis of SELs, which could aid clinical decision‐making and facilitate patient–physician consultation. EUS features significantly contributed to the prediction. Trial registration: Chinese Clinical Trial Registry, http://www.chictr.org.cn (ChiCTR2000040118). [ABSTRACT FROM AUTHOR]