DSM criteria are polythetic, allowing for heterogeneity of symptoms among individuals with the same disorder. In empirical research, most combinations were not found or only rarely found, prompting criticism of this heterogeneity. To elaborate how symptom-based definitions and assessments contribute to a distinct probability pattern for the occurrence of symptom combinations. This cross-sectional study involved a theoretical argument, simulation, and secondary data analysis of 4 preexisting datasets, each consisting of symptoms from 1 of the following syndromes: posttraumatic stress disorder, depression, schizophrenia, and anxiety. Data were obtained from various sources, including the National Institute of Mental Health Data Archive and Department of Veteran Affairs. A total of 155 474 participants were included (individual studies were 3930 to 63 742 individuals in size). Data were analyzed between July 2021 and January 2024. For each participant, the presence or absence of each assessed symptom and their combination was determined. The number of all combinations and their individual frequencies were assessed. Probability or frequency of unique symptom combinations and their distribution. Among the 155 474 participants, the mean (SD) age was 47.5 (14.8) years; 33 933 (21.8%) self-identified as female and 121 541 (78.2%) as male. Because of the interrelation between symptoms, some symptom combinations were significantly more likely than others. The distribution of the combinations' probability was heavily skewed with most combinations having a very low probability. Across all 4 empirical samples, the 1% most common combinations were prevalent in a total of 33.1% to 78.6% of the corresponding sample. At the same time, many combinations (ranging from 41.7% to 99.8%) were reported by less than 1% of the sample. This study found that within-disorder symptom heterogeneity followed a specific pattern consisting of few prevalent, prototypical combinations and numerous combinations with a very low probability of occurrence. Future discussions about the revision of diagnostic criteria should take this specific pattern into account by focusing not only on the absolute number of symptom combinations but also on their individual and cumulative probabilities. Findings from clinical populations using common diagnostic criteria may have limited generalizability to the large group of individuals with a low-probability symptom combination.
Predicting population abundance while accounting for uncertainty is an essential task for managers of endangered species but is often hindered by the challenge and expense of comprehensive data collection. Many traditional methods for estimating abundance of rare or elusive species are costly and logistically difficult, with occupancy-based methods being a popular alternative. While the theoretical relationship between occupancy and abundance is well studied, there are few examples of methodological approaches for predicting abundance from occupancy. This study presents a novel approach to bridge the gap between abundance and occurrence for species with low capture probability, using the Pacific pocket mouse (Perognathus longimembris pacificus; PPM) in Southern California, USA, as a model system. PPM have been monitored across three subpopulations in this region using track tubes to inform occupancy over space and time and live captures to inform PPM demography and phenology. Paired capture-recapture data and presence-absence data collected between 2012 and 2022 were used to estimate density, occupancy, and detection, respectively. Density was modeled as a function of both occupancy and detection, and abundance at monthly and annual scales was predicted from estimates of density for all subpopulations. Our methodology leverages all available data in an integrated Bayesian analysis where uncertainty in site-level abundance is naturally accounted for when scaling abundance estimates to the population level. While occupancy and detection were both predictive of and positively correlated with density, a meaningful amount of variation in density was not explained by our model, revealing avenues for future study as well as providing a realistic assessment of uncertainty in population-level abundance predictions. In addition to advancing the current understanding of Pacific pocket mouse population dynamics, this approach is applicable to a wide array of species and ecosystems where population management is necessary, but individuals have low capture probability and available resources may preclude direct estimation of density at relevant spatial scales. From a design perspective, our results demonstrate the utility of strategically deploying density-based monitoring methods within long-term occupancy monitoring programs. More generally, our findings underscore the potential of this approach to inform methods to include abundance estimation in spatial occupancy monitoring programs for endangered species.
The rise in frequency of extreme climate events has led to notable variation in water storage capacity within many basins around the world, resulting in the simultaneous occurrence of seasonal water shortages and flooding issues. The development of a basin landscape ecological network that is grounded in hydrological connectivity has the potential to markedly improve ecosystem resilience in the basin as well as to facilitate the integrated advancement of ecological conservation and water resource management. This study assessed the hydrological connectivity of the Dongjiang River Basin, China, in terms of Euclidean distance, over the period from 2000 to 2023. Additionally, a boosted regression tree (BRT) model was utilized to ascertain the weights of various ecological resistance factors. The minimum cumulative resistance (MCR) model was subsequently applied to construct a landscape ecological network and to facilitate the identification of ecological pinch points and barriers. Results showed that the mean hydrological connectivity within the Dongjiang River Basin varied between 160 m and 220 m. The overall probability density distribution of hydrological connectivity exhibited characteristics consistent with a semi-normal distribution. The respective contribution rates of elevation, annual average temperature, annual precipitation, and land use type to hydrological connectivity were quantified as 0.57, 0.22, 0.20, and 0.01. In this study, 31 ecological corridors, spanning a cumulative length of 1043.85 km, were identified. Among these corridors, certain ones exhibited a high degree of alignment with the actual distribution of surface water, covering 11.95% of the area, whereas others predominantly traversed forested regions, accounting for 68.58%. The areas designated as ecological pinch points and ecological barriers encompassed 21.78 km2 and 183.37 km2, respectively. These findings offer valuable scientific insights for the ecological protection of basins, the planning and management of water resources, and the prevention and control of flooding in both urban and rural contexts.
Understanding the coordinated transformation of green ecological-living-production space is an important task for 26 mountainous counties of Zhejiang Province to achieve leapfrog high-quality development. Following the framework of ecological-living-production space, we analyzed the dynamics and driving factors of the coupling transformation of the ecological-living-production system in 26 mountainous counties from 2010 to 2021, based on coupling coordination model, kernel density estimation, spatial Markov chain model and optimal parameter geodetector model. The results showed that, the coupling coordination degree of the green transformation of the ecological-living-production system had significantly increased, and the gap among counties had shown an evolutionary trend of stepwise narrowing. In 2016, there was a polarization phenomenon. The coupling coordination degree of the green transformation of the ecological-living-production system presented a spatial pattern of "high in the east and low in the west, high in the north and low in the south". The spatial directivity characteristics were gradually obvious, while the spatial structure evolution showed the characteristics of collaborative response. There was an obvious "club convergence" phenomenon in the coordinated transformation of the ecological-living-production, and each convergence club had strong stability. It was difficult for the coupling coordination type to achieve leap-forward transfer in adjacent years, and there were still "path dependence" and self-enhancement "lock-in effect". The spatial lag factor had a greater influence on the type of coupling coordination. The counties with higher coupling coordination degree had a greater probability of driving the neighboring counties to move upward, whereas the counties with low coupling coordination degree may inhibit the improvement of the coupling coordination degree of the surrounding counties. The coordinated transformation of the ecological-living-production system in 2010, 2015, and 2021 was driven by the progress of social civilization, opening up and economic development, economic development and scientific and technological development, respectively. Our results had important supporting value for the green transformation of collaborative regional ecological, living, and production spaces. 开展绿色“三生空间”协同转型的研究是浙江省山区26县实现跨越式高质量发展的重要任务。本研究基于生态-生活-生产空间视角,采用耦合协调模型、核密度估计、空间马尔科夫链模型和最优参数地理探测器模型等方法,探析2010—2021年浙江山区26县“三生”系统耦合转型的动态演进过程和驱动因素。结果表明: 2010—2021年,研究区“三生”系统绿色转型的耦合协调度显著上升,各县域差距呈阶梯状缩小的演化趋势,2016年出现两极分化现象;“三生”系统绿色转型的耦合协调度呈现“东高西低,北高南低”的空间分布格局,空间指向性特征逐渐明显,空间结构演进表现为协同响应的特征;“三生”系统协调转型存在明显“俱乐部收敛”现象,各趋同俱乐部存在较强的稳定性,耦合协调类型在相邻年份较难实现跨越式转移,仍然存在“路径依赖”和自我增强的“锁定效应”。空间滞后因素对耦合协调类型的影响较大,耦合协调度较高的县域较大概率会带动邻近县域向上转移,而耦合协调度低的县域有可能会抑制周边县域耦合协调度的提升;“三生”系统协调转型在2010、2015、2021年分别以社会文明进步为驱动、对外开放和经济发展为驱动、经济发展和科技发展为驱动的变化特征。研究结果对于协同区域生态、生活、生产空间的绿色转型具有重要的支撑价值。.
Traditional dogma suggests that acute pulmonary embolism (PE) occurs rarely in children <18 years. However, in the emergency department (ED) setting, the frequency of PE diagnosis in children with signs or symptoms that raise suspicion for PE is unknown. This uncertainty is fueled by the lack of prospective studies of PE exclusion and diagnosis in children. Children occasionally die unexpectedly from an acute PE that was missed during the initial evaluation by a physician. However, over-testing also carries risks. This review addresses the risks of over-testing and radiation exposure, and the use of clinical criteria to assess the pretest probability of PE to decide when to test for this condition in children. We discuss what is known about the theoretical test threshold and the unstructured and structured pretest probability of PE assessment in children. Additionally, we review the theory behind the D-dimer assay and the current literature that has reported the diagnostic accuracy of the D-dimer for PE in children. We propose a hypothetical clinical algorithm that incorporates the use of a prediction rule that relies upon both unstructured and structured pretest probability assessments, coupled with the D-dimer to safely rule out the diagnosis of PE in children without the use of radiation.
The unique features of the X chromosome can be crucial to complement autosomal profiling or to disentangle complex kinship problems, providing in some cases a similar or even greater power than autosomes in paternity/maternity investigations. While theoretical and informatics approaches for pairwise X-linked kinship analyses are well established for euploid individuals, these are still lacking for individuals with an X chromosome aneuploidy. To trigger the fulfilment of this gap, this research presents a mathematical framework that enables the quantification of DNA evidence in pairwise kinship analyses, involving two non-inbred individuals, one of whom with a non-mosaic X chromosome aneuploidy: Trisomy X (47, XXX), Klinefelter (47, XXY) or Turner (45, X0) syndrome. As previously developed for a regular number of chromosomes, this approach relies on the probability of related individuals sharing identical-by-descent (IBD) alleles at one specific locus and it can be applied to any set of independently transmitted markers, with no gametic association in the population. The kinship hypotheses mostly considered in forensic casework are specifically addressed in this work, but the reasoning and procedure can be applied to virtually any pairwise kinship problem under the referred assumptions. Algebraic formulae for joint genotypic probabilities cover all the possible genotypic configurations and pedigrees. Compared with the analyses assuming individuals with a regular number of chromosomes, complicating factors rely on the different possibilities for both the parental origin of the error (either maternal or paternal), and the type of error occurred (either meiotic or post-zygotic mitotic). These imply that a non-inbred female with Triple X or a male with Klinefelter syndrome may carry two IBD alleles at the same locus. Thus, and contrarily to what occurs for the standard case, IBD partitions depend not only on the kinship hypothesis under analysis but also on the genotypic configuration of the analyzed individuals. For some cases, parameters of interest can be inferred, while for others recommended values based on the available literature are provided. This work is the starting point to analyze X-chromosomal data under the scope of kinship problems, involving individuals with aneuploidies, as it will enhance the quantification of the DNA evidence not only in forensics but also in the medical genetics field. We hope it will trigger the development of approaches including other complicating factors, as a greater number of individuals, possibility of the occurrence of mutations and/or silent alleles, as well as the analysis of linked markers.
The rapid growth of internet health care (IH) offers older adults convenient medical services like remote consultations and health monitoring. However, its adoption among this group remains low, highlighting a significant digital divide. Understanding the behavioral patterns and determinants of IH use in the older population is crucial for optimizing digital health design and improving service accessibility. This study aimed to analyze the multidimensional influencing factors of Chinese older adults' use of IH services based on the integrated framework of the technology acceptance model and social ecological model, and explore their behavioral patterns and key driving factors. A cross-sectional study design was adopted to conduct a multistage stratified cluster random sampling survey in 3 cities in Shandong Province from May 2024 to July 2024, with a total of 1828 older adults aged 60 to 75 years included. The study uses latent category analysis to classify the use of IH service behaviors and employs multiple logistic regression, decision tree models, and structural equation modeling to analyze influencing factors and mediating pathways. Five distinct user groups were identified: nonusers (n=911), registration-dominant users (n=286), low-activity users (n=320), moderate comprehensive users (n=288), and full-service users (n=23). Multinomial logistic regression with nonusers as the reference group identified key determinants: individuals with below primary education had 96% lower odds of membership (odds ratios [OR] 0.039, 95% CI 0.012-0.084) compared to the reference group with junior college education or above in moderate comprehensive users, while male participants had higher odds of being full-service (OR 1.980, 95% CI 1.126-3.514) or moderate comprehensive (OR 1.310, 95% CI 1.012-1.705) users. Older age was consistently associated with lower adoption across all classes. Full-service users exhibited exceptionally high social support (OR 4.502, 95% CI 3.601-5.627), while moderate comprehensive users showed the highest technology acceptance (OR 2.803, 95% CI 2.355-3.342). The decision tree model (area under the curve of 0.94) found the optimal path: sufficient social support (≥2), good health status (>5), and high technical acceptance (≥30) yield the highest use probability (92%→96%). Mediation analysis indicated that social support influences usage willingness through both direct and indirect pathways. The direct effect was 0.712 (95% CI 0.552-0.972; P<.001). Among indirect pathways, technology availability and practicality accounted for the largest proportion of mediation (19.7%, 95% CI 16.8%-22.6%), followed by technology acceptance (13.7%, 95% CI 11.1%-16.3%) and social influence (8.9%, 95% CI 6.9%-10.9%). Optimizing age-friendly design, strengthening social support networks, and improving technological usability are keys to increasing the adoption of IH services among the older population. Future policies should develop targeted intervention strategies for different user groups to narrow the digital health divide.
This letter presents a novel approach to sparse Bayesian underwater acoustic signal direction estimation. The proposed method incorporates interpolation of the coprime array and signal subspace fitting. It addresses the limitations of the hydrophone coprime array in utilizing all array elements' information and mitigates the interference of ocean noise in shallow waters, which impairs the accuracy and resolution of target direction estimation. Firstly, the hydroacoustic signals are received using a coprime array, then the missing information is filled by interpolating the virtual array elements in the virtual domain, and by optimizing the design of the atomic norm and reconstructing the covariance matrix, the direction-of-arrival (DOA) estimation is performed using all the information of the received signal. Then, the received signal is reconstructed in conjunction with the reconstructed covariance signal subspace, which effectively reduces the impact of background noise. Finally, we derive an off-grid sparse model for the reconstructed signal by exploiting sparsity in the null domain and use Bayesian learning to compute the maximum a posteriori probability of the source signal, thus achieving DOA estimation. The results of numerical simulations and sea trial experimental data indicate that the use of subarrays comprising 5 and 3 array elements, respectively, is sufficient to effectively estimate 12 source angles. Furthermore, the estimation of the DOA can be accurately carried out under low signal-to-noise ratio conditions. This method effectively utilizes the degrees of freedom provided by the virtual array, reducing noise interference, and exhibiting better performance in terms of positioning accuracy and algorithm stability.
The Global Burden of Diseases (GBD) network has proposed theoretical minimum risk exposure level (TMREL) for leading risk factors associated with diet that minimize the risk of morbimortality from chronic diseases. TMREL can be applied to develop follow-up or evaluation indicators in individual studies. The validity of these scores can be tested by assessing associations with health outcomes in prospective cohorts. In this study conducted within the NutriNet-Santé cohort, four dietary scores (TMREL-Risk Score, TMREL-Probability of adequacy, TMREL-standardized distance, and TMREL dietary score) using different scoring methods were developed, with higher scores reflecting less healthy diets. Associations of these scores with the risk of type 2 diabetes, cancer, cardiovascular diseases (CVD) and mortality were estimated using multivariable Cox proportional hazards models, adjusted for a wide range of covariates. Counterfactual and marginal structural models were used to infer causality. Analyses were conducted in a sample of up to103,324 participants ((78.3% women, mean age of 43.6 years old (y) (SD = 14.6)), followed for a median of 8.47 (IQR = 14.7) years (2009-2024). The association with dietary scores (for 1SD-increase) varied in magnitude for each health outcome. For mortality, HR varied from 1.12 (95%CI = 1.07-1.18, ) to 1.18 (95%CI = 1.12-1.24) for TMREL-Stdis and TMREL-DI, for overall cancer from 1.07 (95%CI = 1.03-1.12) to 1.09 (1.04-1.13) for TMREL-RS and TMREL-PA, for CVD from 1.07 (95%CI = 1.00-1.16) to 1.12 (95%CI = 1.04-1.20) for TMREL-PA and TMREL-RS, and for type 2 diabetes from 1.33 (95%CI = 1.23-1.43) to 1.47 (95%CI = 1.36-1.59) for TMREL-DI and TMREL-PA. Marginal structural Cox models strengthened all associations compared to classical analyses. Standardized survival curves showed clear associations, especially for the risk of cancer and type 2 diabetes. Dietary scores based on GBD TMREL can serve as key indicators for characterizing diet quality in relation to long-term health, and using different scoring systems helped evaluate the robustness of these associations.
Slope reliability analysis often assumes isotropic or anisotropic random fields with horizontal orientation to characterize the spatial variability of soil parameters. However, this neglects the influence of rotated anisotropic spatial variability, leading to conservative and unrealistic failure probability estimates. To overcome this limitation, we propose a novel method based on the Hierarchical Recurrent Highway Network (HRHN) with attention mechanisms. This method is applied to a time-dependent reliability assessment of the Baishuihe landslide. By incorporating the spatial variability of geotechnical properties-especially the direction of maximum fluctuation-the study constructs both the most adverse and favorable extreme scenarios, enabling the exploration of failure probability evolution under reservoir drawdown and rainfall infiltration. Compared with traditional horizontally anisotropic random fields, the proposed model produces a range of failure probabilities rather than a single curve. This interval range-formed by maximum and minimum failure probabilities-better captures the uncertainty of the model and accounts for external factors such as rainfall and geological changes. Our approach offers a more comprehensive and realistic perspective for geotechnical risk assessment.
As a flagship species in marine, the conservation of Acipenser sinensis habitat is of great significance for biodiversity maintenance. Based on 339 records of A. sinensis bycatch in the ocean and related environmental data from 2022 to 2023, we investigated its distribution characteristics and habitat selection using the MaxEnt model. The results showed that A. sinensis was primarily distributed in the waters of Hangzhou Bay and the Xiangshan area, with a relatively broad range in spring and winter, while the distribution was more concentrated in summer and autumn. The MaxEnt model revealed that key environmental factors influencing the potential habitat of A. sinensis were bottom water temperature, silicate concentration, and pH. When the temperature of bottom water ranged between 19-23 ℃, the silicate concentration exceeded 15 mmol·m-3, and pH was between 8.2 and 8.5, the probability of A. sinensis presence was higher. Within the study area, the highly suitable zone covered an area of 258.71 km2 (6.9% of the total), while the suboptimally suitable zone spanned 703.46 km2 (18.7%). The main highly suitable zones were located in the waters of Hangzhou Bay, the Xiangshan Port-Jiushan Archipelago-Sanmen Bay-Jiaojiang area, while the suboptimally suitable zones were primarily found in the waters near Zhoushan-Ningbo-Taizhou to the east and south, as well as the coastal waters of Jiangsu. 中华鲟作为海洋生态系统旗舰种,其栖息地保护对生物多样性维持具有重要意义。本研究根据2022—2023年339则中华鲟海洋误捕信息及相关环境数据,结合最大熵(MaxEnt)模型,对其分布特征及栖息地选择进行研究。结果表明: 中华鲟主要分布于杭州湾海域及象山海域,在春季和冬季分布范围较广,夏季和秋季分布范围相对集中。MaxEnt模型显示,影响中华鲟潜在栖息地的关键环境因子为底层水温、硅酸盐浓度、pH,当底层水温介于19～23 ℃、硅酸盐浓度大于15 mmol·m-3、pH介于8.2～8.5时,中华鲟的存在概率较高。研究区域内,中华鲟的高适生区面积为258.71 km2(占比6.9%),次高适生区面积为703.46 km2(占比18.7%),杭州湾海域及象山港-韭山列岛-三门湾-椒江附近海域为主要高适生区,其以东、以南的舟山-宁波-台州附近海域及江苏沿岸海域为主要次高适生区。.
The clinical learning environment (CLE) plays a crucial role in shaping the learning experiences and professional development of medical professionals. Understanding and optimising this environment is essential for improving doctors' knowledge acquisition, clinical skills, and overall well-being. The development of the Postgraduate Hospital Educational Environment Measure (PHEEM) and its translation to numerous languages has been a milestone in clinical education. Even though PHEEM was recently translated into Arabic, its psychometric properties in this form remain unevaluated. Therefore, this study aims to conduct a comprehensive psychometric analysis of the Arabic version of the PHEEM questionnaire. This is a cross-sectional questionnaire survey validation study. The defined population were medical residents in Damascus, Syria. A paper-based survey as well as an online-based one were conducted using several non-probability sampling methods namely, convenience, river and, snowball sampling between June 15, 2023, and June 21, 2023. Both exploratory (EFA) and confirmatory (CFA) factor analyses were conducted. Several psychometric criteria were applied including scree plot, eigenvalue > 1.5 and the 'proportion of variance accounted for' criterion. A total of 543 participants completed the questionnaire (56.9% female). Kaiser-Meyer-Olkin measure for sample adequacy was high (0.937) and the P-value for Bartlett's test was < 0.001. EFA revealed five meaningful factors which were labelled: perception of teachers, learner's engagement and social participation, external regulation, work culture, and living conditions. These factors had the following eigenvalues: 12.6, 2.18, 2.03, 1.86, and 1.41 respectively, with a total explained variance of 43.45%. Cronbach's Alpha was 0.938. CFA confirmed the model structure of EFA (SRMR = 0.067 and RMSEA = 0.066). The Average Variance Explained (AVE) value of any given factor was > 0.7. The Arabic PHEEM inventory demonstrated satisfactory psychometric properties. The extracted domains are of theoretical relevance to the psychosocial-material conceptual framework for learning environment. Nonetheless, this validation was performed in the Syrian context; therefore, future studies in other Arabic countries are recommended to support the applicability of Arabic PHEEM in the wide Arab World.
Supplemental private health insurance (PHI) plays a crucial role in complementing China's social health insurance (SHI). However, the effectiveness of incorporating PHI as supplementary coverage lacks conclusive evidence regarding its impact on healthcare utilization and seeking behavior among SHI-covered individuals. Therefore, investigating the effects of supplementary PHI on health care utilization and seeking behavior of residents covered by social health insurance is essential to provide empirical evidence for informed decision-making within the Chinese healthcare system. Data from the 2018 China National Health Services Survey were analyzed to compare outpatient and inpatient healthcare utilization and choices between PHI purchasers and non-purchasers across three SHI schemes: urban employee-based basic medical insurance (UEBMI), urban resident-based basic medical insurance (URBMI), and the new rural cooperative medical scheme (NRCMS). Using the Andersen Healthcare Services Utilization Behavior Model as the theoretical framework,binary logistic regression and multinomial logistic regression (MNL) models were employed to assess the impact of PHI on healthcare utilization and provider preferences. Among UEBMI, URBMI, and NRCMS participants with PHI, outpatient visit rates were 17.9, 19.8, and 21.7%, and inpatient admission rates were 12.4, 9.9, and 12.9%, respectively. Participants without PHI exhibited higher rates for outpatient visits (23.6, 24.3, and 25.6%) and inpatient admissions (15.2, 12.8, and 14.5%). Binomial logistic regression analyses revealed a higher probability of outpatient visits and inpatient admissions among UEBMI participants with PHI (p < 0.05). NRCMS participants with PHI showed a lower probability of outpatient visits but a higher probability of inpatient admissions (p < 0.05). Multinomial logistic regression indicated that NRCMS participants with PHI were more likely to choose higher-level hospitals, with a 17% increase for county hospitals and 27% for provincial or higher-level hospitals compared to primary care facilities. The findings indicate that the possession of PHI correlated with increased utilization of outpatient and inpatient healthcare services among participants covered by UEBMI. Moreover, for participants under the NRCMS, the presence of PHI is linked to a proclivity for seeking outpatient care at higher-level hospitals and heightened utilization of inpatient services. These results underscore the nuanced influence of supplementary PHI on healthcare-seeking behavior, emphasizing variations across individuals covered by distinct SHI schemes.
A multidimensional and comprehensive evaluation of the impact of energy conservation and emission reduction (ECER) on residents' health and welfare is conducive to resolving conflicts between economy and environment on a worldwide scale. Based on China's ECER demonstration city policy, this paper uses a staggered difference-in-differences method to examine the impact of ECER on residents' health and labor market performance, and conservatively estimates the welfare effect of ECER in conjunction with a theoretical model. The results show that ECER significantly improves residents' health, raises self-rated health (β = 0.06, p < 0.05, 95% CI = -0.17 to 0.13), reduces the probability of illness affecting work (β = -0.004, p < 0.05, 95% CI = -0.01 to 0.01), and lowers medical expenditures (β = -0.183, p < 0.05, 95% CI = -0.64 to 0.10). However, ECER negatively affects residents' labor market performance, reducing employment status (β = -0.032, p < 0.10, 95% CI = -0.11 to 0.06) and wage (β = -0.055, p < 0.05, 95% CI = -0.23 to 0.00). Mechanism analysis suggests that ECER primarily improves health by reducing emissions of pollutants such as urban industrial wastewater, industrial sulphur dioxide, and industrial fumes and dust, and negatively influences labor market performance by promoting industrial restructuring. Heterogeneity analysis shows that there is a selection effect in the impacts, the health benefits and economic costs of ECER are mostly achieved and borne by groups in rural areas, non-provincial capitals, and those suffering from chronic diseases and not engaging in physical activity. Welfare analysis suggests that the health benefits of ECER result in higher welfare gains than the negative welfare impacts of its economic effects. Future policies should progressively move towards an integrated assessment of the costs and benefits of ECER, paying particular attention to welfare losses among groups that bear higher costs.
The karst region in southwestern China is particularly prominent and has become a core issue constraining ecological environment restoration and sustainable development in this area. This study utilized long-term remote sensing data to reveal the spatial pattern evolution characteristics of rocky desertification in the region in 2000, 2010, and 2020. Meanwhile, it analyzed the dynamic trend of vegetation coverage recovery in the area from 2000 to 2020, as well as the analysis of related factors. The results showed that the spatial distribution of the Normalized Difference Vegetation Index (NDVI) remained highly clustered, though the clustering gradually weakened over time. When NDVI exceeded 0.6, the probability of rocky desertification reversal increased. Currently, a core contradiction of "quantity increases but quality stagnates" exists in regional vegetation cover, characterized by a continuous rise in NDVI mean values coexisting with reduced spatial clustering. This phenomenon reflects the evolution of vegetation patterns under the combined effects of ecological engineering interventions, adjustments in human-land relationships, and constraints of karst landforms. Through factor analysis, slope and humidity were identified as key factors influencing vegetation restoration. The findings provide an important theoretical foundation and practical reference for targeted rocky desertification management, optimization of ecological restoration projects, and coordinated human-land development in karst regions.
In recent years, the diverse applications of electroencephalography (EEG) - based affective brain-computer interfaces (aBCIs) are being extensively explored. However, due to adverse factors like noise and physiological variability, the recognition capability of aBCIs can unforeseeably suffer abrupt declines. Since the timing of these aBCI failures is unknown, placing trust in aBCIs without scrutiny can lead to undesirable consequences. To alleviate this issue, we propose an algorithm for estimating the reliability of aBCI (primarily Graph Convolutional Network), synchronously delivering a probabilistic confidence score upon aBCI decision completion, thereby reflecting the aBCI's real-time recognition capabilities. Methodologically, we use the Maximum Softmax Probability (MSP) from EEG recognition networks as confidence scores and leverage the Scaling Operator to calibrate them. Then, the Projection Operator is employed to address confidence estimation biases caused by noise and subject variability. For the numerical concentration of MSP, we provide fresh insights into its causes and propose corresponding solutions. The derivation of the estimator from the Maximum Entropy Principle is also substantiated for robust theoretical underpinnings. Finally, we confirm theoretically that the estimator does not compromise BCI performance. In experiments conducted on public datasets SEED and SEED-IV, the proposed algorithm demonstrates superior performance in estimating aBCIs reliability compared to other benchmarks, and commendable adaptability to new subjects. This research has the potential to lead to more trustworthy aBCIs and advance their broader application in complex real-world scenarios.
Avoiding error in handling artifacts is crucial for achieving a high level of system reliability and safety assessment. This study develops a predictive and ranking model of use error (PRUE). In the first phase, use errors are systematically detected and anticipated via an inquiry process in two levels (activity and function). In the second phase, the fuzzy best-worst method (F-BWM) is employed to determine relative weights of three criteria including consequence of use error (CUE), detection of use error (DUE) and probability of use error (PUE). Fuzzy TOPSIS is then employed to rank use errors according to their risk level. The use errors of an infant ventilator device are assessed to demonstrate applicability of the PRUE method. The results of the present study confirm the reliability and applicability of this approach to assess artifact use errors. Moreover, the PRUE method can be utilized in investigation of user interface design.
Global projections of ecosystem responses to increasing climatic and anthropogenic pressures are needed to inform adaptation planning. However, data of appropriate spatiotemporal resolution are often not available to parameterize complex environmental processes at the global scale. Modeling approaches that can project the probability of ecosystem persistence when parameter uncertainty is high may offer a way forward. In particular, the conservation of coastal ecosystems with complex dynamics, like mangrove forests, may benefit from knowing where their future persistence is highly probable or, alternatively, cannot be reliably estimated without additional data of appropriate resolution. Here, we simulated network models to make probabilistic projections of the direction of net change in mangrove ecosystems worldwide under the SSP5-8.5 climate emissions scenario by the years 2040-2060. Seaward net loss was the most probable outcome in 77% [37%-78%; 95% confidence interval (CI)] of mangrove forest units, while 30% [15%-59%; CI] were projected to experience landward net gain or stability. In more than 50% of forest units, projections were ambiguous and therefore unreliable, with a near equal probability of net loss or gain. Quantitative models parameterized with locally accurate data could resolve uncertainty in the future persistence of mangroves in places with unreliable probabilistic projections. Projections made under conservation scenarios also showed that, with action to manage or restore, the number of mangrove forest units likely to experience net gain or stability in the future could nearly double. Our approach to simulating ecosystem responses to climatic and anthropogenic pressures provides a clear indication of how certain (or uncertain) ecosystem persistence is and thus can inform conservation planning.
Extensive research has investigated the linkage between environmental, social, and governance (ESG) practices and corporate financial outcomes; however, the specific implications of pollution prevention (PP) measures for firm performance remain comparatively understudied. Drawing upon theoretical insights from the resource-based view (RBV) and the natural resource-based view (NRBV), this study seeks to bridge this gap by providing an integrated examination of how PP practices influence firm performance over varying time horizons. This paper aims to empirically assess the short-term and long-term impacts of PP strategies on firm performance. Specifically, it investigates immediate financial metrics, such as profitability, solvency, and operational efficiency, as well as long-term outcomes measured by market valuation. In doing so, the study contributes to the understanding of whether initial compliance costs are ultimately offset by sustained competitive advantages derived from PP initiatives. Utilizing a comprehensive panel dataset covering publicly listed U.S. firms from 2011 to 2019, this study employs rigorous econometric methodologies, notably propensity score matching (PSM) and augmented inverse probability weighting (AIPW), to address potential selection bias. The analysis incorporates industry fixed effects alongside extensive controls for firm-specific characteristics, including management robustness, board composition and size, financial leverage, and capital structure. The empirical findings reveal a complex relationship between PP practices and firm performance. While firms initially experience adverse short-term effects, including declines in profitability, operational efficiency, and solvency due to compliance-related expenditures, these negative impacts are subsequently mitigated in the long run. Indeed, sustained commitments to PP practices correlate positively with enhanced market valuation. The results highlight the pivotal role of robust governance structures, diverse and adequately sized boards, prudent capital management, and strategic leverage decisions in successfully navigating the trade-offs associated with pollution prevention. Consequently, managers and policymakers are advised to carefully balance short-term financial constraints with long-term strategic investments to optimize the value derived from environmentally responsible practices.
Anterior cruciate ligament (ACL) rupture can be treated surgically or non-surgically, with several surgical interventions available at present. However, the comparatively effective surgical intervention with relatively fewer side effects remains unknown. This study aims to fill in this gap by conducting a Bayesian network meta-analysis (NMA) and provide a theoretical basis for the clinical application. We will perform a Bayesian NMA and will include randomised controlled trials (RCTs) published in English or Chinese that compare surgical intervention (ie, standard ACL reconstruction, ACL remnant-preserving reconstruction and ACL repair with suture augmentation to conservative therapy or studies that compare one surgical intervention to another for the symptom relief and function recovery of patients with ACL rupture. Primary outcome will be the proportion of patients with symptomatic and functional improvement measured by the Knee Injury and Osteoarthritis Outcome Score before and 6 months after treatment, with scores ranging from 0 (worst) to 100 (best). Secondary outcomes will be knee-specific quality of life (ACL QoL), return to activity and level of sport participation (Tegner or modified Tegner score), health-related QoL (EuroQol Group 5-Dimension 5-Level, EQ-5D-5L), resource use, intervention-related complications and patient satisfaction. We have developed search strategies for PubMed, Embase, the Cochrane Library and Web of Science, retrieving RCTs that meet the inclusion criteria from database inception to 1 December 2023. The methodological quality of the included RCTs will be assessed based on the Cochrane risk of bias table. The relative ranking probability of the best intervention will be estimated using the surface under the cumulative ranking curve. The Bayesian NMA will be conducted by using WinBUGS V.1.4.3. The Grading of Recommendations Assessment, Development and Evaluation approach will be applied to determine our confidence in an overall treatment ranking from the NMA. Ethical approval for this study is not required because no private or confidential patient data will be used in this study. Findings of this study would be disseminated through the publication in a peer-reviewed medical journal. CRD42023437115.