Integrating visual large language model and reasoning chain for driver behavior analysis and risk assessment.

Driver behavior is a critical factor in driving safety, making the development of sophisticated distraction classification methods essential. Our study presents a Distracted Driving Classification (DDC) approach utilizing a visual Large Language Model (LLM), named the Distracted Driving Language Model (DDLM). The DDLM introduces whole-body human pose estimation to isolate and analyze key postural features-head, right hand, and left hand-for precise behavior classification and better interpretability. Recognizing the inherent limitations of LLMs, particularly their lack of logical reasoning abilities, we have integrated a reasoning chain framework within the DDLM, allowing it to generate clear, reasoned explanations for its assessments. Tailored specifically with relevant data, the DDLM demonstrates enhanced performance, providing detailed, context-aware evaluations of driver behaviors and corresponding risk levels. Notably outperforming standard models in both zero-shot and few-shot learning scenarios, as evidenced by tests on the 100-Driver dataset, the DDLM stands out as an advanced tool that promises significant contributions to driving safety by accurately detecting and analyzing driving distractions.

Comprehensive assessment of occurrence, temporal-spatial variations, and ecological risks of heavy metals in Jiaozhou Bay, China: A comprehensive study.

Heavy metals play a significant role in marine ecosystems, exerting notable impacts on the environment and human health. In this study, water, sediment, and aquatic organism samples from Jiaozhou Bay were investigated to comprehensively assess the distribution, temporal-spatial variations, and ecological risks of heavy metals. The results indicate that pollution from industrial wastewater discharge contributes to regional differences in the distribution of heavy metals, possibly being a major source of Zn, Cr, Cd, and Hg (r > 0.7, p < 0.05). Biological and physicochemical processes influence the distribution of Zn, Cr, and Pb in the water and sediment. Hg exhibits a polluted state in both the water and sediment, with As and Hg being the two highest-risk heavy metals in water and sediment, respectively. Among the organisms, crustaceans show significantly higher levels of heavy metal content and accumulation compared to mollusks and fish (p < 0.05), and the bioamplification of heavy metals occurs in the sediment-Rapana venosa-Portunus trituberculatus biological pathway. Portunus trituberculatus, Charybdis japonica, Oratosquilla oratoria, and Octopus ocellatus could pose risks to human health, especially for children and vulnerable populations. This study aims to enhance our understanding of the current status of heavy metal pollution in Jiaozhou Bay and to provide a scientific basis and favorable support for the ecological environmental protection and prevention of ecological risks associated with heavy metal pollution in Jiaozhou Bay and other bays in China.

Approaching national climate targets in China considering the challenge of regional inequality.

Achievement of national climate targets and the corresponding costs would entirely depend on regional actions within the country. However, because of substantial inequalities and heterogeneities among regions, especially in developing economies, aggressive or uniform actions may exacerbate inequity and induce huge economic losses, which in turn challenges the national climate pledges. Hence, this study extends prior research by proposing economically optimal strategies that can achieve national climate targets and ensure the greatest local and national benefits as well as regional equality. Focusing on the biggest developing country China, we find this strategy can avoid up to 1.54% of cumulative GDP losses for approaching carbon neutrality, and more than 90% of regions would obtain economic gains compared either with existing independently launched targets or with the uniform strategy that all regions achieve peak carbon emissions before 2030. We also provide optimal carbon mitigation pathways to regional peak carbon, carbon intensity and energy consumption.

Remote scoring models of rigidity and postural stability of Parkinson's disease based on indirect motions and a low-cost RGB algorithm.

Background and objectives: The Movement Disorder Society's Unified Parkinson's Disease Rating Scale Part III (MDS-UPDRS III) is mostly common used for assessing the motor symptoms of Parkinson's disease (PD). In remote circumstances, vision-based techniques have many strengths over wearable sensors. However, rigidity (item 3.3) and postural stability (item 3.12) in the MDS-UPDRS III cannot be assessed remotely since participants need to be touched by a trained examiner during testing. We developed the four scoring models of rigidity of the neck, rigidity of the lower extremities, rigidity of the upper extremities, and postural stability based on features extracted from other available and touchless motions. Methods: The red, green, and blue (RGB) computer vision algorithm and machine learning were combined with other available motions from the MDS-UPDRS III evaluation. A total of 104 patients with PD were split into a train set (89 individuals) and a test set (15 individuals). The light gradient boosting machine (LightGBM) multiclassification model was trained. Weighted kappa (k), absolute accuracy (ACC ± 0), and Spearman's correlation coefficient (rho) were used to evaluate the performance of model. Results: For model of rigidity of the upper extremities, k = 0.58 (moderate), ACC ± 0 = 0.73, and rho = 0.64 (moderate). For model of rigidity of the lower extremities, k = 0.66 (substantial), ACC ± 0 = 0.70, and rho = 0.76 (strong). For model of rigidity of the neck, k = 0.60 (moderate), ACC ± 0 = 0.73, and rho = 0.60 (moderate). For model of postural stability, k = 0.66 (substantial), ACC ± 0 = 0.73, and rho = 0.68 (moderate). Conclusion: Our study can be meaningful for remote assessments, especially when people have to maintain social distance, e.g., in situations such as the coronavirus disease-2019 (COVID-19) pandemic.

[Temporal and Spatial Characteristics of Net CO2 Emissions and Decoupling Analysis in Yangtze River Economic Belt].

Calculating the fossil energy consumption, revealing the temporal and spatial evolution characteristics of net CO2 emissions, and analyzing the decoupling effect between social development and net CO2 emissions in different regions of the Yangtze River Economic Belt (YREB) is crucial to support the different regions, allowing them to select their individual industrial development and carbon emission reduction path. The results showed that:① from 1999 to 2012, YREB became greener, the CO2 emission of the YREB increased by 2244.23 million tons, and the carbon sink increased by 148.07 million tons during the research period. ② From 2013 to 2018, the area of medium-high carbon sequestration (NPP>800 g·m-2, count for C) increased by 23.25%, compared with that from 1999-2012. ③ A highly decoupling effect between social development and net CO2 emissions was found in the downstream of the YREB. The highest decoupling cities in the upstream, midstream, and downstream accounted for 12%, 34%, and 54% of the highest decoupling cities in the YREB, respectively.

[Review on the assessment model of nutrient recycling with agricultural residues treatment technologies]. / å†œä¸šåºŸå¼ƒç‰©å »åˆ†å¾ªçŽ¯åˆ©ç”¨æŠ€æœ¯æ¨¡å¼è¯„ä¼°æ¨¡åž‹çš„ç ”ç©¶è¿›å±•.

The technology for nutrient resource utilization of agricultural residues is crucial to realizing a circular agricultural economy. The assessment model provides essential support to optimize nutrient recovery and treatment technologies. We specifically summarized research progress in the assessment framework of agricultural residues nutrient recycling technology, assessment models and evaluation indicators, data sources of models and their uncertainty analysis, and the application scale of models. We found that process mathematical models and industrial eco-logy models are the common nutrient flow assessment models. Process mathematical and industrial ecology models differed greatly in terms of the reliability of assessment results and the simulation scale. The former mainly focused at laboratory or pilot scale, with higher accuracy. The latter could achieve multi-scale simulation from microscopic to macroscopic and had higher uncertainty, due to the way its data were obtained. Finally, we provided an outlook on the research on the assessment model of agricultural residues nutrient resource utilisation technology. In order to achieve accurate assessment of waste resource utilisation technology in agricultural production systems at the regional scale, a reliable model framework and database should be established by combining process mathematical models with industrial ecology models. Meanwhile, we should carry out research on model expansion at the geographical scales of factory scale, farm scale, village scale, township scale, and regional scale.

Dignity and its related factors among older adults in long-term care facilities: A cross-sectional study.

OBJECTIVES: This study aimed to explore the dignity and related factors among older adults in long-term care facilities. METHODS: Cross-sectional data were obtained from a sample of 253 Chinese older adults dwelling in long-term care facilities. Dignity among older adults was measured using the Dignity Scale, and its potential correlates were explored using multiple linear regressions. RESULTS: Results showed that the total score of the Dignity Scale is 151.95 ± 11.75. From high to low, the different factors of dignity among older adults in long-term care facilities were as follows: caring factors (4.83 ± 0.33), social factors (4.73 ± 0.41), psychological factors (4.66 ± 0.71), value factors (4.56 ± 0.53), autonomous factors (4.50 ± 0.57), and physical factors (4.38 ± 0.55). A higher score of the Dignity Scale was associated with higher economic status, fewer chronic diseases, less medication, better daily living ability and long-time lived in cities. CONCLUSION: Older adults with low economic status, more chronic diseases, and poor daily living ability, taking more medications, or the previous residence in rural areas seem to be most at low-level dignity in long-term care facilities and thus require more attention than their peers.

Global environmental inequality: Evidence from embodied land and virtual water trade.

The trade-off between economic growth and environmental conservation is the focus of national environmental management. Previous studies have proved that global trade can bring both economic benefits and environmental costs to all countries. However, for different countries, it is not clear whether the environmental costs match their economic benefits in global trade. Also, whether the global trade exacerbates or mitigates the uneven distribution of natural resources among countries need to be further investigated. This study aims to fill these research gaps by providing evidence of global environmental inequality from land and water perspective, thus inspire new thinking on the optimization of global trade patterns. We construct an environmental inequality index based on the world Multi-Regional Input-Output (MRIO) model, and perform a case study for land and water. Results show that most of countries with low per capita land resources are net importers of embodied land, while many countries with extreme water shortages are net exporters of virtual water, such as India, Pakistan, Iran and Egypt, indicating that the global trade encourages the optimal distribution of land resources but exacerbates the uneven distribution of water resources. The environmental cost of developed countries is much lower than that of developing countries compared to their economic gains from global trade, and the inequality of virtual water trade is higher than that of embodied land trade. High-income countries mainly export high value-added products with low environmental costs, while developing countries are just the opposite. We suggest that due to the lack of a unified global natural resource market, resource tax may be an effective means to reduce global environmental inequality and resource mismatch, and policies aimed at reducing environmental inequality can help achieve coordinated management of land and water resources.

A Data-Driven Approach to Transfer Function Analysis for Superior Discriminative Power: Optimized Assessment of Dynamic Cerebral Autoregulation.

Transfer function analysis (TFA) is extensively used to assess human physiological functions. However, extracting parameters from TFA is not usually optimized for detecting impaired function. In this study, we propose to use data-driven approaches to improve the performance of TFA in assessing blood flow control in the brain (dynamic cerebral autoregulation, dCA). Data were collected from two distinct groups of subjects deemed to have normal and impaired dCA. Continuous arterial blood pressure (ABP) and cerebral blood flow velocity (CBFV) were simultaneously recorded for approximately 10 mins in 82 subjects (including 41 healthy controls) to give 328 labeled samples of the TFA variables. The recordings were further divided into 4,294 short data segments to generate 17,176 unlabeled samples of the TFA variables. We optimized TFA post-processing with a generic semi-supervised learning strategy and a novel semi-supervised stacked ensemble learning (SSEL) strategy for classification into normal and impaired dCA. The generic strategy led to a performance with no significant difference to that of the conventional dCA analysis methods, whereas the proposed new strategy boosted the performance of TFA to an accuracy of 93.3%. To our knowledge, this is the best dCA discrimination performance obtained to date and the first attempt at optimizing TFA through machine learning techniques. Equivalent methods can potentially also be applied to assessing a wide spectrum of other human physiological functions.

Performance and comparison of assessment models to predict 30-day mortality in patients with hospital-acquired pneumonia.

BACKGROUND: Hospital-acquired pneumonia (HAP) is the most common hospital-acquired infection in China with substantial morbidity and mortality. But no specific risk assessment model has been well validated in patients with HAP. The aim of this study was to investigate the published risk assessment models that could potentially be used to predict 30-day mortality in HAP patients in non-surgical departments. METHODS: This study was a single-center, retrospective study. In total, 223 patients diagnosed with HAP from 2012 to 2017 were included in this study. Clinical and laboratory data during the initial 24 hours after HAP diagnosis were collected to calculate the pneumonia severity index (PSI); consciousness, urea nitrogen, respiratory rate, blood pressure, and age ≥65 years (CURB-65); Acute Physiology and Chronic Health Evaluation II (APACHE II); Sequential Organ Failure Assessment (SOFA); and Quick Sequential Organ Failure Assessment (qSOFA) scores. The discriminatory power was tested by constructing receiver operating characteristic (ROC) curves, and the areas under the curve (AUCs) were calculated. RESULTS: The all-cause 30-day mortality rate was 18.4% (41/223). The PSI, CURB-65, SOFA, APACHE II, and qSOFA scores were significantly higher in non-survivors than in survivors (all P < 0.001). The discriminatory abilities of the APACHE II and SOFA scores were better than those of the CURB-65 and qSOFA scores (ROC AUC: APACHE II vs. CURB-65, 0.863 vs. 0.744, Z = 3.055, P = 0.002; APACHE II vs. qSOFA, 0.863 vs. 0.767, Z = 3.017, P = 0.003; SOFA vs. CURB-65, 0.856 vs. 0.744, Z = 2.589, P = 0.010; SOFA vs. qSOFA, 0.856 vs. 0.767, Z = 2.170, P = 0.030). The cut-off values we defined for the SOFA, APACHE II, and qSOFA scores were 4, 14, and 1. CONCLUSIONS: These results suggest that the APACHE II and SOFA scores determined during the initial 24 h after HAP diagnosis may be useful for the prediction of 30-day mortality in HAP patients in non-surgical departments. The qSOFA score may be a simple tool that can be used to quickly identify severe infections.

Use of Blood Lipid Indicators as a Screening Tool of Insulin Resistance among Individuals in Low-Income Country Sides of China: A Multiethnic Region Study.

OBJECTIVE: This study is aimed at evaluating the diagnostic value of blood lipid indicators (BLIs) for insulin resistance (IR) among major ethnic groups in Xinjiang, China, to identify the most valuable indicators and appropriate cut-off points for each ethnic group and to lay the foundation for the early detection, diagnosis, and treatment of metabolic diseases in remote rural areas. METHODS: Overall, 418 Uygurs, 331 Kazakhs, and 220 Hans were randomly included in our study. The homeostasis model assessment was the gold standard for identifying IR. The receiver operating characteristic (ROC) curve was used to evaluate the diagnostic value, and the nomogram was utilized to analyze the predictive value. The size of the area under the curve (AUC) reflected the accuracy of screening and prediction. RESULTS: Differences in races were observed in terms of IR and BLIs, and the Kazakhs had the highest IR level at 5.27 mmol/L. The correlation between IR and BLIs differed among the three races. For the Kazakhs and Hans, all BLIs, except total cholesterol (TC), were correlated to IR. However, for the Uygurs, only the triglyceride (TG) level, TG/high-density lipoprotein cholesterol (HDL-C) ratio, and TC/HDL-C ratio were associated with IR. After further adjustment of confounding factors, these indicators were still correlated to IR. BLIs that independently correlated to IR in the three nationalities had a certain diagnostic value for IR. In terms of the AUC size, the TG level was the highest in Uygurs, the TG/HDL-C ratio was the highest for Kazakhs and Hans, and the corresponding best cut-off points for IR were 1.515, 1.230, and 1.495 mmol/L, respectively. In addition, for each race, when the indicators with a certain diagnostic value were combined, the diagnostic value for IR was higher. CONCLUSION: BLIs had a certain diagnostic value for IR and could be used as a screening tool for IR among Uygurs, Kazakhs, and Hans in Xinjiang. These findings are extremely important for the prevention and treatment of IR and metabolic diseases in remote rural areas.

The effectiveness and influencing factors of a penalty point system in China from the perspective of risky driving behaviors.

Many countries have adopted penalty point systems (PPS) to deter drivers from breaking traffic laws. To investigate the effectiveness of PPS on reducing illegal driving behavior, this study analyzed traffic violation data of a Chinese city in 2017. This analysis revealed that 1) risky driving behaviors (RDBs) are among the main causes of traffic violations and 2) almost half of the offenders with multiple violations committed the same traffic rule violations more than once. To further explain these phenomena, a survey in another Chinese city-Tianjin-was conducted. Considering the fact that most types of RDBs will, if detected by the authorities, result in traffic violations, the present study investigated the influence of a PPS, represented by penalty experience (PE), on traffic violation behaviors from the perspective of RDBs. Moreover, the impact of cognitive processes on driving behaviors via self-efficacy was considered. We found that drivers' PE is positively associated with their RDBs and that offenders with more PE are more inclined to commit RDBs; we further observed that self-efficacy partially mediates the relationship between PE and RDBs. However, no gender difference in the effect of PE on RDBs was discovered, thus indicating that PE has the same effect on male and female drivers. Based on these findings, some strategies are suggested (such as the Increasing Block Penalty Points Policy) to improve the effectiveness of the PPS.

Increasing surfboard volume reduces energy expenditure during paddling.

The purpose of this study was to investigate how altering surfboard volume (BV) affects energy expenditure during paddling. Twenty surfers paddled in a swim flume on five surfboards in random order twice. All surfboards varied only in thickness and ranged in BV from 28.4 to 37.4 L. Measurements of heart rate (HR), oxygen consumption (VO2), pitch angle, roll angle and paddling cadence were measured. VO2 and HR significantly decreased on thicker boards [VO2: r = -0.984, p = 0.003; HR: r = -0.972, p = 0.006]. There was also a significant decrease in pitch and roll angles on thicker boards [Pitch: r = -0.995, p < 0.001; Roll: r = -0.911, p = 0.031]. Results from this study suggest that increasing BV reduces the metabolic cost of paddling as a result of lower pitch and roll angles, thus providing mechanical evidence for increased paddling efficiency on surfboards with more volume. Practioner Summary: This study investigated the impact of surfboard volume on energy expenditure during paddling. Results from this study suggest that increasing surfboard volume reduces the metabolic cost of paddling as a result of lower pitch and roll angles, thus providing mechanical evidence for increased paddling efficiency on surfboards with more volume.