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Net primary production (NPP) can regulate global climate change and carbon balance. Although scholars have qualitatively studied the influencing factors of NPP, few have quantified the contribution of different degrees of drought aggravation or mitigation and major land-use changes to NPP changes. Based on the temporal and spatial characteristics of NPP for 2000-2015 in the Chinese Loess Plateau, we quantified the contribution of drought, land use and land cover change (LUCC), and hydrothermal conditions to changes in NPP. Particularly, we analyzed the contribution of major land-use change and different drought levels to NPP. Our results showed that the 15-years average NPP was approximately 227 gC/m.sup.2 and decreased from southeast to northwest. Overall, NPP showed a linear increasing trend over the 15-years period. The results suggested that changes in hydrothermal conditions had the strongest impact on NPP (~61%), followed by drought (~33%), and land use and land cover change had the weakest impact (~1.4%). In particular, ~13% of the NPP decreases was affected by light drought aggravation, ~10% of the NPP decreases was affected by moderate drought aggravation, and ~0.3% was affected by the conversion of cropland to grassland or non-NPP main production land. Moreover, ~12.7% of the NPP increase was affected by light drought alleviation, ~9.4% was affected by moderate drought alleviation, and ~1.1% was affected by the conversion of grassland to cropland or forestland. The mechanisms underlying the effect of drought and land-use change on NPP were clarified and provide an important reference value for future research on the carbon cycle and regional ecological environmental restoration.

In mobile edge computing, there are usually relevant dependencies between different tasks, and traditional algorithms are inefficient in solving dependent task-offloading problems and neglect the impact of the dynamic change of the channel on the offloading strategy. To solve the offloading problem of dependent tasks in a dynamic network environment, this paper establishes the dependent task model as a directed acyclic graph. A Dependent Task-Offloading Strategy (DTOS) based on deep reinforcement learning is proposed with minimizing the weighted sum of delay and energy consumption of network services as the optimization objective. DTOS transforms the dependent task offloading into an optimal policy problem under Markov decision processes. Multiple parallel deep neural networks (DNNs) are used to generate offloading decisions, cache the optimal decisions for each round, and then optimize the DNN parameters using priority experience replay mechanism to extract valuable experiences. DTOS introduces a penalty mechanism to obtain the optimal task-offloading decisions, which is triggered if the service energy consumption or service delay exceeds the threshold. The experimental results show that the algorithm produces better offloading decisions than existing algorithms, can effectively reduce the delay and energy consumption of network services, and can self-adapt to the changing network environment.

To address the issues of low accuracy and high rates of false detection and missed detection in existing methods for pavement crack identification under complex road conditions, this paper proposes a novel approach named YOLO11-MBC, based on the YOLO11 model. A Multi-scale Feature Fusion Backbone Network (MFFBN) is designed to enhance the model's capability to recognize and extract crack features in complex environments. Considering that pavement cracks often exhibit elongated topologies and are susceptible to interference from similar features like tree roots or lane markings, we combine the Bidirectional Feature Pyramid Network (BiFPN) with a Multimodal Cross-Attention (MCA) mechanism, constructing a novel BiMCNet to replace the Concat layer in the original network, thereby optimizing the detection of minute cracks. The CGeoCIoU loss function replaces the original CIoU, employing three distinct penalty terms to better reflect the alignment between predicted and ground-truth boxes. The effectiveness of the proposed method is validated through comparative and ablation experiments on the public RDD2022 dataset. Results demonstrate the following: (1) Compared to the baseline YOLO11, YOLO11-MBC achieves a 22.5% improvement in F1-score and an 8% increase in mAP50 by integrating the three proposed modules, significantly enhancing performance for complex pavement crack detection. (2) The improved algorithm demonstrates superior performance. Compared to YOLOv8, YOLOv10, and YOLO11, it achieves precision, recall, F1-score, mAP50, and mAP50-95 of 61%, 70%, 72%, 75%, and 66%, respectively, validating the correctness of our approach.

There are outstanding evolutionary questions on the recent emergence of human coronavirus SARS-CoV-2 including the role of reservoir species, the role of recombination and its time of divergence from animal viruses. We find that the sarbecoviruses—the viral subgenus containing SARS-CoV and SARS-CoV-2—undergo frequent recombination and exhibit spatially structured genetic diversity on a regional scale in China. SARS-CoV-2 itself is not a recombinant of any sarbecoviruses detected to date, and its receptor-binding motif, important for specificity to human ACE2 receptors, appears to be an ancestral trait shared with bat viruses and not one acquired recently via recombination. To employ phylogenetic dating methods, recombinant regions of a 68-genome sarbecovirus alignment were removed with three independent methods. Bayesian evolutionary rate and divergence date estimates were shown to be consistent for these three approaches and for two different prior specifications of evolutionary rates based on HCoV-OC43 and MERS-CoV. Divergence dates between SARS-CoV-2 and the bat sarbecovirus reservoir were estimated as 1948 (95% highest posterior density (HPD): 1879–1999), 1969 (95% HPD: 1930–2000) and 1982 (95% HPD: 1948–2009), indicating that the lineage giving rise to SARS-CoV-2 has been circulating unnoticed in bats for decades. In this manuscript, the authors address evolutionary questions on the emergence of SARS-CoV-2. They find that SARS-CoV-2 is not a recombinant of any sarbecoviruses detected to date, and that the bat and pangolin sequences most closely related to SARS-CoV-2 probably diverged several decades ago or possibly earlier from human SARS-CoV-2 samples.

Background There are less studies focusing on the sedative therapy of acute myocardial infarction (AMI) critical patients. This study aim to compare the impact on the prognosis of AMI critical patients of using midazolam, propofol and dexmedetomidine. Methods We collected clinical data from the Medical Information Mart for Intensive Care III (MIMIC III) database. Data on 427 AMI patients with sedatives using were recruited from in Coronary Heart Disease Intensive Care unit (CCU). Results There were 143 patients in midazolam using, 272 in propofol using and 28 in dexmedetomidine using. The rate of 28-days mortality was 23.9% in overall patients. Through logistic regression analysis, only midazolam using was significant association with increased 28-days mortality when compared with propofol or dexmedetomidine using. In the subgroup analysis of age, gender, body mass index (BMI), white blood cell (WBC), beta-block, and revascularization, the association between midazolam using and increased 28-days mortality remained significantly. Through propensity score matching, 140 patients using midazolam and 192 using non-midazolam were successfully matched, the midazolam using presented with higher rate of CCU mortality, hospital mortality and 28-days mortality, longer of mechanical ventilation time and CCU duration. E-value analysis suggested robustness to unmeasured confounding. Conclusion Propofol or dexmedetomidine are preferred to be used in AMI critical patients for sedative therapy.

Trade shows as temporary clusters have gained attention in corporate innovation research, yet their specific mechanisms remain underexplored. This paper examines the relationship between temporary clusters, knowledge transfer, and corporate innovation using the China International Sport Show as a case study (N = 368 exhibiting companies). Through questionnaire surveys and structural equation modeling (SEM), the study found that temporary clusters create a “global buzz” information exchange ecosystem comprising global co-presence, face-to-face interaction, observation, focused communities, and multiplex meetings and relationships. These elements significantly enhance knowledge transfer between participating enterprises and other knowledge entities, which subsequently promotes corporate innovation. Results confirm knowledge transfer’s mediating role between temporary clusters and corporate innovation. This study advances existing literature by decomposing temporary clusters into constituent elements and empirically validating each component’s discrete effects on knowledge transfer and corporate innovation. Drawing on evidence from China’s sports industry, the research provides systematic insights into temporary cluster mechanisms and their role in facilitating inter-organizational knowledge transfer and innovation outcomes. The findings offer both theoretical contributions to the temporary clusters literature and practical implications for innovation-oriented enterprise development strategies.

Surgery is considered a relative contraindication in sarcoma tumor. Because of the unique characteristics of heart, whether surgery is optimally chosen in primary cardiac sarcoma (PCS) is unknown. In this study, we aimed to evaluate the 1-year survival after surgery for PCS. Patients with PCS from the Surveillance, Epidemiology, and End Results Database (SEER) between 1975 and 2015 were recruited. The endpoints were defined as 1-year all-cause mortality (ACM) and 1-year cancer-specific mortality (CSM). The study population consisted of 335 patients diagnosed with PCS. The 1-year ACM and CSM were 49.0% and 42.1% respectively. The Kaplan-Meier curves revealed that decreased 1-year ACM-CSM were significantly associated with surgical treatment. Multiple COX regression analysis, surgery, and chemotherapy showed a significantly decreased rate of 1-year ACM and CSM. The adjusted hazard ratio of surgery was significant when the year of diagnosis was ≥2000, patients were aged <50 years, SEER stage was localized, and patients did not undergo chemotherapy (all p<0.05), and was insignificant when the year of diagnosis was <2000, patients were aged ≥50 years, SEER stage was distance, regional, and unstaged/unknown, and the patients underwent chemotherapy (all p>0.05). No interaction effects were detected between the variables and surgery (all p for interaction >0.05). Surgery should be highly recommended in patients with PCS to improve the 1-year survival rate, especially in younger patients with localized SEER stage and non-chemotherapy management.

A tight-binding analytic framework is combined with first-principles calculations to reveal the mechanism underlying the strain effects on electronic structures of graphene and graphene nanoribbons (GNRs). It provides a unified and precise formulation of the strain effects under various circumstances-including the shift of the Fermi (Dirac) points, the change in band gap of armchair GNRs with uniaxial strain in a zigzag pattern and its insensitivity to shear strain, and the variation of the k-range of edge states in zigzag GNRs under uniaxial and shear strains which determine the gap behavior via the spin polarization interaction.

Abstract Brain network alterations have increasingly been implicated in schizophrenia (SCZ), bipolar disorder (BD), and major depressive disorder (MDD). However, little is known about the similarities and differences in functional brain networks among patients with SCZ, BD, and MDD. A total of 512 participants (121 with SCZ, 100 with BD, 108 with MDD, and 183 healthy controls, matched for age and sex) completed resting-state functional magnetic resonance imaging at a single site. Four global measures (the clustering coefficient, the characteristic shortest path length, the normalized clustering coefficient, and the normalized characteristic path length) were computed at a voxel level to quantify segregated and integrated configurations. Inter-regional functional associations were examined based on the Euclidean distance between regions. Distance strength maps were used to localize regions with altered distances based on functional connectivity. Patient groups exhibited shifts in their network architectures toward randomized configurations, with SCZ>BD>MDD in the degree of randomization. Patient groups displayed significantly decreased short-range connectivity and increased medium-/long-range connectivity. Decreases in short-range connectivity were similar across the SZ, BD, and MDD groups and were primarily distributed in the primary sensory and association cortices and the thalamus. Increases in medium-/long-range connectivity were differentially localized within the prefrontal cortices among the patient groups. We highlight shared and distinct connectivity features in functional brain networks among patients with SCZ, BD, and MDD, which expands our understanding of the common and distinct pathophysiological mechanisms and provides crucial insights into neuroimaging-based methods for the early diagnosis of and interventions for psychiatric disorders.

Converging evidence increasingly implicates shared etiologic and pathophysiological characteristics among major psychiatric disorders (MPDs), such as schizophrenia (SZ), bipolar disorder (BD), and major depressive disorder (MDD). Examining the neurobiology of the psychotic-affective spectrum may greatly advance biological determination of psychiatric diagnosis, which is critical for the development of more effective treatments. In this study, ensemble clustering was developed to identify subtypes within a trans-diagnostic sample of MPDs. Whole brain amplitude of low-frequency fluctuations (ALFF) was used to extract the low-dimensional features for clustering in a total of 944 participants: 581 psychiatric patients (193 with SZ, 171 with BD, and 217 with MDD) and 363 healthy controls (HC). We identified two subtypes with differentiating patterns of functional imbalance between frontal and posterior brain regions, as compared to HC: (1) Archetypal MPDs (60% of MPDs) had increased frontal and decreased posterior ALFF, and decreased cortical thickness and white matter integrity in multiple brain regions that were associated with increased polygenic risk scores and enriched risk gene expression in brain tissues; (2) Atypical MPDs (40% of MPDs) had decreased frontal and increased posterior ALFF with no associated alterations in validity measures. Medicated Archetypal MPDs had lower symptom severity than their unmedicated counterparts; whereas medicated and unmedicated Atypical MPDs had no differences in symptom scores. Our findings suggest that frontal versus posterior functional imbalance as measured by ALFF is a novel putative trans-diagnostic biomarker differentiating subtypes of MPDs that could have implications for precision medicine.