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Purpose Building supply chain (SC) resilience is crucial for business continuity given the ever-changing environmental conditions. Based on the resource orchestration and organizational culture theories, the purpose of this paper is to investigate the business value of SC resilience with the consideration of the roles of internal integration (II) and external integration (EI), risk management culture (RMC) and SC flexibility (SCF). Design/methodology/approach This study investigates how RMC, SCF and intra and interorganizational integration affect the performance of SC resilience. It collects primary and secondary data from 194 manufacturing firms listed in the Taiwan Stock Exchange and Taipei Exchange. Findings Results validate the authors’ hypothesis that RMC, SCF and II improve the financial performance of firms through SC resilience efforts. Research limitations/implications This study uses firms from Taiwan manufacturing industry, which might introduce country and industry bias. Practical implications This study helps managers improve the financial performance of their SC resilience efforts by developing RMC, SCF, II and IE across functions and partner firms. Originality/value This study contributes to the literature by empirically testing the relationship between SC resilience and financial performance, and how the relationship is moderated by RMC, SCF, II and EI based on the theories of organizational culture and resource orchestration.

For the spaceborne synthetic aperture radar (SAR), it is difficult to obtain high resolution and wide width at the same time. This paper proposes a novel imaging system based on tandem SAR satellites, where one obtains coarse resolution and wide swath by the scanning mode, and the other obtains the undersampled echo from the same swath. The high resolution is achieved by associating the tandem SARs’ echo and using the minimum-energy-based algorithm. Finally, a high-resolution wide-swath SAR system is designed, and its imaging performance is verified by simulated data and real airborne SAR data.

This paper proposed a deep learning on-board health monitoring method for landing gear shock-absorbing systems based on dynamic responses during landing. A deep learning model is developed to conduct health monitoring for faults in shock absorbers. A certain general aviation aircraft is focused on in this paper, and a multi-body dynamic model of the nose landing gear is developed to simulate dynamic responses during landing under various health states and various landing conditions for developing a database for the proposed LDGNet. The simulated database is used to conduct model training and to test the performance of the proposed method. The feasibility and effectiveness of the proposed method are verified.

Heterogeneous photocatalysis–self-Fenton technology is a sustainable strategy for treating organic pollutants in actual water bodies with high-fluent degradation and high mineralization capacity, overcoming the limitations of the safety risks caused by adding external iron sources and hazardous chemicals in the homogeneous Fenton reaction and injecting high-intensity energy fields in photo-Fenton reaction. Herein, a photo-self-Fenton system based on resorcinol–formaldehyde (RF) resin and red mud (RM) was established to generate hydrogen peroxide (H2O2) in situ and transform into hydroxy radical (•OH) for efficient degradation of tetracycline (TC) under visible light irradiation. The capturing experiments and electron spin resonance (ESR) confirmed that the hinge for the enhanced performance of this system is the superior H2O2 yield (499 μM) through the oxygen reduction process (ORR) of the two-step single-electron over the resin and the high concentration of •OH due to activation effect of RM. In addition, the Fe2+/Fe3+ cycles are accelerated by photoelectrons to effectively initiate the photo-self-Fenton reaction. Finally, the possible degradation pathways were proposed via liquid chromatography-mass spectrometry (LC-MS). This study provides a new idea for environmental recovery in a waste-based heterogeneous photocatalytic self-Fenton system.

In the surveillance of interested regions by unmanned aerial vehicle (UAV), system performance relies greatly on the motion control strategy of the UAV and the operation characteristics of the onboard sensors. This paper investigates the 2D path planning problem for the lightweight UAV synthetic aperture radar (SAR) system in an environment of multiple regions of interest (ROIs), the sizes of which are comparable to the radar swath width. Taking into account the special requirements of the SAR system on the motion of the platform, we model path planning for UAV SAR as a constrained multiobjective optimization problem (MOP). Based on the fact that the UAV route can be designed in the map image, an image-based path planner is proposed in this paper. First, the neighboring ROIs are merged by the morphological operation. Then, the parts of routes for data collection of the ROIs can be located according to the geometric features of the ROIs and the observation geometry of UAV SAR. Lastly, the route segments for ROIs surveillance are connected by a path planning algorithm named the sampling-based sparse A* search (SSAS) algorithm. Simulation experiments in real scenarios demonstrate that the proposed sensor-oriented path planner can improve the reconnaissance performance of lightweight UAV SAR greatly compared with the conventional zigzag path planner.

systemic inflammation disorders were observed in chronic kidney disease (CKD). Whether the systemic inflammatory indicators could be optimal predictors for the survival of CKD remains less studied. In this study, participants were selected from the datasets of the National Health and Nutrition Examination Survey (NHANES) between 1999 to 2018 years. Four systemic inflammatory indicators were evaluated by the peripheral blood tests including systemic immune-inflammation index (SII, platelet*neutrophil/lymphocyte), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR). Kaplan-Meier curves, restricted cubic spline (RCS), and Cox regression analysis were used to evaluate the association between the inflammatory index with the all-cause mortality of CKD. Receiver operating characteristic (ROC) and concordance index (C-index) were used to determine the predictive accuracy of varied systemic inflammatory indicators. Sensitive analyses were conducted to validate the robustness of the main findings. A total of 6,880 participants were included in this study. The mean age was 67.03 years old. Among the study population, the mean levels of systemic inflammatory indicators were 588.35 in SII, 2.45 in NLR, 133.85 in PLR, and 3.76 in LMR, respectively. The systemic inflammatory indicators of SII, NLR, and PLR were all significantly positively associated with the all-cause mortality of CKD patients, whereas the high value of LMR played a protectable role in CKD patients. NLR and LMR were the leading predictors in the survival of CKD patients [Hazard ratio (HR) =1.21, 95% confidence interval (CI): 1.07-1.36, p = 0.003 (3 quartile), HR = 1.52, 95%CI: 1.35-1.72, p<0.001 (4 quartile) in NLR, and HR = 0.83, 95%CI: 0.75-0.92, p<0.001 (2 quartile), HR = 0.73, 95%CI: 0.65-0.82, p<0.001 (3 quartile), and = 0.74, 95%CI: 0.65-0.83, p<0.001 (4 quartile) in LMR], with a C-index of 0.612 and 0.624, respectively. The RCS curves showed non-linearity between systemic inflammatory indicators and all-cause mortality risk of the CKD population. Our study highlights that systemic inflammatory indicators are important for predicting the survival of the U.S. population with CKD. The systemic inflammatory indicators would add additional clinical value to the health care of the CKD population.

New data reveal that LINP1, a lncRNA overexpressed in triple-negative breast cancer, interacts with the Ku70–Ku80 complex and DNA-PKcs, thereby promoting NHEJ-mediated DNA double-strand-break repair. Long noncoding RNAs (lncRNAs) play critical roles during tumorigenesis by functioning as scaffolds that regulate protein-protein, protein-DNA or protein-RNA interactions. Using a clinically guided genetic screening approach, we identified lncRNA in nonhomologous end joining (NHEJ) pathway 1 (LINP1), which is overexpressed in human triple-negative breast cancer. We found that LINP1 enhances repair of DNA double-strand breaks by serving as a scaffold linking Ku80 and DNA-PKcs, thereby coordinating the NHEJ pathway. Importantly, blocking LINP1, which is regulated by p53 and epidermal growth factor receptor (EGFR) signaling, increases the sensitivity of the tumor-cell response to radiotherapy in breast cancer.

Ship wake detection stands as a pivotal task in marine environment monitoring. The main challenge in ship wake detection is to improve detection accuracy and mitigate false alarms. To address this challenge, a novel procedure for ship wake detection in a single SAR image is proposed in this study. Initially, an entropy distance similarity criterion is designed to measure nonlocal image patch similarity. Based on the proposed criterion, a low-rank and sparse decomposition method is modified using nonlocal similar patch matrix construction to separate the sparse wake. Subsequently, a field-of-experts (FOE) model is introduced to generate a series of multi-view wake feature maps, which are fused to construct an enhanced feature map. The sparse wake is further enhanced in the Radon domain with the enhanced feature map. The experimental results demonstrate the effectiveness of the proposed method on real SAR ship wake images.

Due to the complex construction conditions, long work cycles, and high uncertainty inherent in agricultural water conservancy projects, accurate construction cost prediction is crucial for investment decisions. This study presents an innovative cost prediction model for these projects, integrating BIM with neural networks. Firstly, BIM technology is utilized to digitize and visualize engineering-related information. Subsequently, a prediction model based on SSA optimized PGNN is constructed. The digital data obtained from BIM is subsequently integrated with the prediction model to estimate the construction costs of agricultural water conservancy projects. In this study, actual engineering projects are selected as case studies, utilizing material price data from January 2016 to February 2021 in Liaoning Province, along with real project data for modeling purposes. The results indicate that the maximum relative error between the predicted and actual values of the combined model is only 2.99%. Furthermore, the RMSE and R 2 of the simulated prediction results are 0.1358 and 0.9819, respectively. The proposed model demonstrates higher prediction accuracy and efficiency. Compared with the PGNN model, the RMSE is reduced by 33%, and R 2 is increased by 6%. These findings suggest that the BIM-SSA-PGNN prediction model provides more accurate and efficient construction cost predictions for agricultural water conservancy projects, promoting technological integration and innovation while optimizing construction project costs. This study provides a scientific basis for management to promote the transformation of the industry towards digital and intelligent sustainable development.

High-pressure processing (HPP) technology can significantly improve the texture and flavor of Mercenaria mercenaria. This study aimed to investigate the effect of HPP treatment with varying levels of pressure (100, 200, 300, 400, 500, and 600 MPa) and a holding time of 8 min at 20 °C on the physicochemical properties and volatile flavors of M. mercenaria. The significant changes in hardness, resilience, and water holding capacity occurred with increasing pressure (p < 0.05), resulting in improved meat quality. Scanning electron microscopy (SEM) was utilized to observe the decomposition of muscle fibers in M. mercenaria due to varying pressures, which explains the differences in texture of M. mercenaria. Different pressure treatments also had an influence on the volatile flavor of M. mercenaria, and the quantities of low-molecular-weight aldehydes (hexanal, heptanal, and nonanal) with a fishy taste decreased dramatically following 400 and 500 MPa HPP treatments. Furthermore, the level of 2-Methylbutyraldehyde, which is related to sweetness, increased significantly following 400 MPa HPP treatment. The study found that 400 MPa HPP treatment resulted in minor nutrient losses and enhanced sensory quality. The results of this study provide a theoretical basis for the application of HPP treatment to M. mercenaria.