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Research on the impact and mechanism of local governments’ land conveyance behavior on urban-rural integrated development—Empirical evidence from 281 prefecture-level cities in China
The land sale practices of local governments significantly impact urban-rural integration development. This paper utilizes panel data from 281 prefecture-level and above cities in China, using local government land sale practices as a logical starting point. It examines the effects and mechanisms of these practices on urban-rural integration development from two dimensions: land price competition and land finance dependence, employing a bidirectional fixed effects model among other empirical tests. The findings indicate that land price competition has a significant positive effect on urban-rural integration development, showing an inverted U-shaped relationship. In contrast, land finance dependence hinders urban-rural integration development. The impact of local government land sale practices on urban-rural integration development also varies by region, administrative level, and different aspects of urban-rural integration. Furthermore, local government land sale practices mainly influence urban-rural integration development through labor transfer effects, public service provision effects, and industrial structure upgrading effects. Labor transfer and industrial structure upgrading play significant positive moderating roles in promoting urban-rural integration development through land price competition. Public service provision and industrial structure upgrading play significant positive moderating roles in mitigating the inhibitory effects of land finance dependence on urban-rural integration development.
Survival outcomes among patients with breast cancer and leptomeningeal disease
The Impact of Inflammatory Biomarker Subphenotypes on Acute Respiratory Distress Syndrome Prognosis: A Systematic Review and Meta-analysis
Sensitivity analysis of unsafe behaviors in the spinning and weaving factories: Exploring the association with burnout and resilience using Bayesian networks
Job burnout and resilience skills are factors that can affect safety performance in the workplace. However, the contribution of these variables to unsafe behaviors through various paths has not been determined. This study aimed to investigate the association of three burnout dimensions and resilience with safety compliance and safety performance using Bayesian network modeling. This research was performed with cross-sectional design. Participants were 200 employees working in some spinning and weaving factories. Participants provided responses to printed survey items during work rest periods. The survey comprised a demographic information section, validated Persian versions of the Connor–Davidson resilience scale, the Maslach burnout questionnaire, and the safety behavior assessment. The Bayesian network was analyzed using version 2.3 of the GeNIe academic software. At the high state with a probability of 100% for each of the three burnout variables: depersonalization, emotional exhaustion, personal accomplishment, and (poor) resilience, the probability of poor safety compliance increased by 16%, 16%, 7%, and 24% and the probability of poor safety participation rose by 6%, 12%, 29%, and 17%, respectively. All variables with a probability of 100% also elevated the likelihood of diminished safety compliance and reduced safety participation by 51% and 34%, respectively. Each of the three dimensions of burnout can be associated with changes in resilience, safety compliance, and safety participation. Resilience plays a significant role in mediating the association between burnout dimensions and unsafe behaviors.
Innovation through recycling in Iron Age plaster technology at Tell el-Burak, Lebanon
Abstract Recent excavations at the Phoenician coastal site of Tell el-Burak, a large-scale agricultural production centre in use during 725–350 BCE, have uncovered the first Iron Age wine press in Lebanon. This discovery enabled a systematic, interdisciplinary study of its plaster, offering insights into ancient construction technologies. The analysis extended to two other plastered installations found in separate rooms within the complex, allowing for a comprehensive comparison. An integrated program of archaeometric analysis, including optical microscopy in polarising light, X-ray powder diffraction, scanning electron microscopy, thermogravimetry, and organic residue analysis, was applied to samples from these three structures to investigate plaster composition and technological variability. Previous studies identified the use of crushed ceramic fragments in a lime-based plaster. Now, new analyses provide deeper insights into the nature of the binder, revealing how the addition of ceramic sherds may have enhanced the plaster’s mechanical properties and hydraulicity, making it a significant early example of hydraulic mortar. These findings confirm the existence of a local, innovative tradition of lime-plaster manufacture in southern Phoenicia. This investigation not only sheds light on the specific technological practices of Tell el-Burak, but also contributes to the broader understanding of Phoenician and Punic technological advancements in the Iron Age Mediterranean.
Refining the Evidence on HFNC for Post-traumatic Lung Contusion: A Critical Perspective
G91-deletion in βA3/A1-crystallin induces cellular and molecular changes in mouse lenses leading to congenital cataract development
CRYβA1-ΔG91 (βA3ΔG91) is a mutational hotspot in CRYβA1, which causes autosomal dominant congenital nuclear cataract in humans and mice. Previous in-vitro studies of recombinant βA3ΔG91 showed defective folding, decreased solubility, and aberrant oligomerization of βA3ΔG91 with other crystallins. Emerging evidence demonstrates an association between autophagy and βA3ΔG91-induced congenital cataracts. To gain further understanding of the molecular mechanism of congenital cataract development in βA3ΔG91 mice, we examined the βA3ΔG91- vs WT- lenses for complete gene profiling, lens epithelial cell (LEC) proliferation and migration, and lens epithelial-fiber cell differentiation. We also determined the changes in crystallin proteomic profiles in water-soluble, water-insoluble-urea-soluble, and water-insoluble-urea-insoluble fractions. Our results show that relative to WT lenses, the βA3ΔG91 lenses showed: (A) downregulation of genes associated with LECs proliferation and migration (B) abnormal suture line pattern, (C) significant reduction in proliferation and migration of LECs, (D) abnormal F-actin distribution, (E) increased high molecular weight (HMW) peak, and (F) insolubilization and degradation of crystallins and other lens proteins. Together, these defects contribute to the formation of the lens opacity in βA3ΔG91 mice lenses.
Enhancing multiple object tracking accuracy via quantum annealing
Defining the Acute Respiratory Distress Syndrome – Are You a Splitter or a Lumper? The Choice Matters more than You Think
Editorial Note: Short birth spacing and its association with maternal educational status, contraceptive use, and duration of breastfeeding in Ethiopia. A systematic review and meta-analysis
Correction: Vigorous technique for augmented lifetime in WSNs
Author Response: Refining the Evidence on HFNC for Post-traumatic Lung Contusion: A Critical Perspective
Video swin-CLSTM transformer: Enhancing human action recognition with optical flow and long-term dependencies
As video data volumes soar exponentially, the significance of video content analysis, particularly Human Action Recognition (HAR), has become increasingly prominent in fields such as intelligent surveillance, sports analytics, medical rehabilitation, and virtual reality. However, current deep learning-based HAR methods encounter challenges in recognizing subtle actions within complex backgrounds, comprehending long-term semantics, and maintaining computational efficiency. To address these challenges, we introduce the Video Swin-CLSTM Transformer. Based on the Video Swin Transformer backbone, our model incorporates optical flow information at the input stage to effectively counteract background interference, employing a sparse sampling strategy. Combined with the backbone’s 3D Patch Partition and Patch Merging techniques, it efficiently extracts and fuses multi-level features from both optical flow and raw RGB inputs, thereby enhancing the model’s ability to capture motion characteristics in complex backgrounds. Additionally, by embedding Convolutional Long Short-Term Memory (ConvLSTM) units, the model’s capacity to capture and understand long-term dependencies among key actions in videos is further enhanced. Experiments on the UCF-101 dataset demonstrate that our model achieves mean Top-1/Top-5 accuracies of 92.8% and 99.4%, which are 3.2% and 2.0% higher than those of the baseline model, while the computational cost is reduced by an average of 3.3% at peak performance compared to models without optical flow. Ablation studies further validate the effectiveness of our model’s crucial components, with the integration of optical flow and the embedding of ConvLSTM modules yielding maximum improvements in mean Top-1 accuracy of 2.6% and 1.9%, respectively. Notably, employing our custom ImageNet-1K-LSTM pre-training model results in a maximum increase of 2.7% in mean Top-1 accuracy compared to traditional ImageNet-1K pre-training model. These experimental results indicate that our model offers certain advantages over other Swin Transformer-based methods for video HAR tasks.
Predictors and clinical implications of post-stroke cognitive impairment: a retrospective study
Author Response: Glycemic Variability and Outcomes in Sepsis: There\'s No Smoke without Fire!
Is non-invasive ventilation effective in improving the exercise capacity in patients with cardiac heart failure?: A randomised crossover trial
Introduction Heart failure (HF) is a prevalent global health issue, characterized by the heart’s inability to effectively pump or fill with blood, leading to inadequate cardiac output. Despite advances in medical treatments, exercise intolerance remains a significant challenge, impacting their quality of life and contributing to frequent hospitalizations. Recent studies suggest that non-invasive ventilation (NIV) may further enhance exercise performance by reducing ventilatory workload and fatigue. However, limited research has directly compared different ventilatory modes during exercise in patients with heart failure. This study aims to evaluate the effects of two NIV devices on exercise capacity. Methods A randomised crossover trial was conducted in patients with HF, reduced ejection fraction (≤ 40%), New York Heart Association functional class I-III and clinically stable. All participants underwent an initial assessment followed by an incremental exercise test to determine maximum aerobic velocity. They were then randomized to perform three constant work rate tests on separate days under three conditions: (1) with Continuous Positive Airway Pressure (CPAP), (2) with pressure support (PS) and (3) without NIV. The primary outcome was time to exhaustion. Key physiological variables were recorded during each test. Participants were recruited and completed all testing between April 29 and July 18, 2022. ClinicalTrials.gov registration number: NCT05433610. Results A total of 11 patients (mean age: 67 ± 9.6 years) completed the study. Exercise duration was significantly longer in the pressure support group (9.8 ± 6.2 minutes) compared to the CPAP group (8.9 ± 6.0 minutes) and the control group (7.3 ± 6.2 minutes) (p = 0.043). No significant differences were found in average heart rate (HR), final HR, or oxygen saturation (SpO₂) between the groups (p > 0.05). Similarly, dyspnea and leg fatigue (modified Borg scale) showed no statistically significant differences between conditions (p > 0.05). Conclusion The use of NIV, particularly the PS mode, during exercise significantly improved exercise duration in patients with HF compared to CPAP or no ventilatory support. Clinical Trial Registration ClinicalTrials.gov Identifier: NCT05433610
Combining USV ROV and multimetric indices to assess benthic habitat quality in coastal areas
Addressing ICU-acquired Weakness: A Call for Early Diagnosis and Intervention
Multilingual capabilities of GPT: A study of structural ambiguity
This study examines the multilingual capabilities of GPT, focusing on its handling of syntactic ambiguity across English, Korean, and Japanese. We investigate whether GPT can capture language-specific attachment preferences or if it relies primarily on English-centric training patterns. Using ambiguous relative clauses as a testing ground, we assess GPT’s interpretation tendencies across language contexts. Our findings reveal that, while GPT (GPT-3.5-turbo, GPT-4-turbo, GPT 4o)’s performance aligns with native English speakers’ preferred interpretations, it overgeneralizes this interpretation in Korean and lacks clear preferences in Japanese, despite distinct attachment biases among native speakers of these languages. The newer, smaller-scale models—o1-mini and o3-mini—further reinforce this trend by closely mirroring English attachment patterns in both Korean and Japanese. Overall results suggest that GPT’s multilingual proficiency is limited, likely reflecting a bias toward high-resource languages like English, although differences in model size and tuning strategies may partially mitigate the extent of English-centric generalization. While GPT models demonstrate aspects of human-like language processing, our findings underscore the need for further refinement to achieve a more nuanced engagement with linguistic diversity across languages.