Search Results (65,755)

The Preliminary Exploration into Adoption Reunions (PEAR) survey examined the mental health issues faced by adoptees and first mothers. Data were collected from 1313 adoptees, first mothers, and first fathers. Study results indicate that adoption has lasting adverse effects on both adoptees and first mothers. Adoptees and first mothers are significantly more likely to attempt suicide (35 times and 37.7 times, respectively), abuse alcohol, display hypersexual behaviors, and restrict their eating compared to their peers: While first mothers have a lower life expectancy and are more likely to die by suicide than women who did not lose their children to adoption, adoptees frequently struggle with their identity and sense of belonging. They expressed experiencing trauma from their separation from their first mothers, regardless of the quality of their adoptive parents. The findings also highlight the negative impact of the secrecy surrounding adoption. Themes of secrecy and shame were prevalent in the responses from both adoptees and first mothers. The findings highlight the importance of listening to and validating the experiences of adoptees and first mothers and that there needs to be transparency in adoption practices, which may reduce the stigma associated with adoption, and facilitate healing. Full article

Cyberbullying behaviors manifest uniquely in different regions, shaped strongly by local slang, dialectal expressions, and cultural context. Code-mixed Chinese–English colloquial language (Cantonese) is commonly used in Hong Kong, Macau, and parts of southern China. Code-mixing is the use of multiple languages concurrently, and Cantonese text includes distinct phonetic, lexical, and syntactic features that are not exhibited in datasets developed for either Chinese or English applications. In this study, a privacy-aware code-mixed cyberbullying dataset (PCCD), containing 14,115 annotated tweets organized into 1668 sessions, was developed. Personally identifiable information and well-known identifiers, such as the names of famous celebrities, politicians, and organizations, were replaced with randomly generated dummy names. The anonymized data empirically demonstrated improved performance in terms of precision, recall, and F₁ score, indicating a greater generalization ability when handling unseen participants. To the best of our knowledge, the PCCD is the first code-mixed Chinese–English dataset that includes abuser and victim identity annotation. Our dataset facilitates the development of robust cyberbullying detection tools that researchers and developers can use to accurately measure aggressiveness, attack frequency, and abuser–victim power imbalance in a dialogue session. Full article

This study aimed to develop and validate a machine learning-based model for predicting 30-day mortality in cardiac surgery patients and to implement a functional, clinician-oriented web application that enables the real-time use of the model. A retrospective cohort of 325 cardiac surgery patients was analysed using supervised machine learning. After preprocessing and clinical feature selection, several models were trained and evaluated through cross-validation. XGBoost achieved the best results, with an AUC-ROC of 0.968, recall of 0.800, and Brier score of 0.058. To facilitate clinical usability, a web-based application was developed using StreamLit, enabling clinicians to input patient data and predict mortality in real time. The application includes SHAP-based explainability for each prediction, thereby ensuring model transparency. Preliminary feedback from clinicians indicated that the tool was intuitive and informative and showed potential for preoperative risk assessment. The integration of a robust ML (machine learning) model with a functional clinical application offers a practical tool for supporting decision-making in cardiac surgery. This combined approach enhances both accuracy and accessibility, which are key to real-world impacts. Future work will involve multicentre validation and user-centred refinement. Full article

Background: Lip aging is a heterogeneous and visually complex process, yet a standardized morphological classification applicable to clinical practice is still lacking. Current approaches mainly focus on volumetric loss or perioral rhytids, while the geometric features of the lips, including borders, projection, and eversion, remain poorly codified. Methods: Fifty anonymized lip images acquired under standardized conditions using digital facial imaging were independently evaluated by five physicians experienced in esthetic medicine. Images were classified according to three predefined morphotypes representing distinct patterns of lip aging. Inter-rater reliability was assessed using Fleiss’s kappa statistic. Results: Three recurrent morphotypes were consistently identified: devolumized lips, central lips, and chapped lips. Overall, 87% of images were assigned to one of the three morphotypes by at least four of five evaluators, while 13% were classified as undefined due to mixed features. Inter-rater agreement was substantial (κ = 0.89; 95% CI 0.79–0.99), confirming high reproducibility of the proposed classification. Conclusions: This study proposes a simple and reproducible image-based morphotypic classification of lip aging that captures recurrent visual patterns within this cohort. The framework may facilitate standardized clinical communication, support personalized rejuvenation strategies, and provide a foundation for future quantitative imaging studies and AI-based phenotype recognition in esthetic and reconstructive practice. Full article

Understanding the thermal decomposition behavior and kinetic characteristics of blended biomass is crucial for optimizing thermochemical conversion processes. This study systematically investigates the synergistic pyrolysis (thermal decomposition) behavior of Salix psammophila (SP) and corn stover (CS) under a nitrogen atmosphere, with particular emphasis on process behavior and reaction kinetics (and thermodynamic feasibility). Based on elemental and proximate analyses, SP provides high calorific value and lignin content, while CS contributes high volatile matter and cellulose, enabling complementary interaction during thermal conversion. Three blending ratios (CS:SP = 2:1, 3:1, and 5:2) were analyzed using scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), and kinetic evaluation via the Coats–Redfern, Flynn–Wall–Ozawa (FWO), and Kissinger–Akahira–Sunose (KAS) methods, together with thermodynamic parameter estimation (ΔH, ΔS, and ΔG). The results indicate that the 3:1 blend forms an optimized “continuous phase–dispersed phase” structure with an interfacial transition layer of 11–15 μm and uniformly distributed fine pores, promoting effective heat and mass transfer and facilitating volatile-release pathways across the blend interface. At a heating rate of 15 °C·min⁻¹, this blend exhibits the lowest onset temperature of rapid mass loss (T_onset, 209 °C), the highest comprehensive pyrolysis performance index (S_N, 3.01), and stable DTG profiles. Kinetic analysis confirmed that the 3:1 blend exhibits the lowest activation energy during the devolatilization stage, indicating enhanced reaction feasibility under inert conditions. The results provide mechanistic insight into biomass blending effects and offer guidance for process optimization in inert-atmosphere thermochemical conversion systems. Full article

With the acceleration of urbanization, opportunities for direct contact with nature have diminished, making mediated nature exposure a sustainable approach to promoting public health. Existing studies predominantly present natural stimuli from a first-person horizontal perspective, leaving it unclear whether different viewing perspectives lead to divergent restorative outcomes. To examine how environment type and perspective jointly influence cognitive and emotional restoration, this study employed a 2 (environmental type: forest vs. city) × 2 (perspective: first-person perspective (1PP) vs. third-person perspective (3PP)) × 2 (time: pre-test vs. post-test) mixed experimental design grounded in Attention Restoration Theory (ART). Results showed that viewing forest videos, compared to city videos, significantly improved directed attention and emotional state. More importantly, a functional decoupling of perspectives was observed: the first-person perspective primarily facilitated the restoration of directed attention, while the third-person perspective was more effective in alleviating negative mood. These findings provide empirical evidence for the design of sustainable interventions, guiding both the development of tailored digital nature solutions and the planning of green infrastructure that integrates multiple perspectives. Thereby, nature exposure can be transformed into an equitable public health resource, contributing to the development of resilient, sustainable cities. Full article

The governance of the rural water environment is essential for improving the quality of life of rural residents and advancing the construction of ecological civilization. However, the current governance system faces issues such as fragmented governance entities and low collaborative efficiency. Therefore, in this study, we focus on the intergovernmental collaborative governance mechanism for rural water environments. Drawing on complex network theory and evolutionary game theory, we employ complex network analysis and construct a complex network evolutionary game model among government departments, and we further conduct numerical simulations to examine the evolutionary dynamics of intergovernmental collaboration in rural water environmental governance. The findings show the following: (1) The reward and punishment mechanism, collaborative gain coefficient, and loss intensification trend coefficient all positively influence the participation rates of local governments. When these parameters exceed certain thresholds, they can rapidly and stably increase the proportion of participating nodes. (2) Nodes with stronger environmental preferences respond more directly to the collaborative gain coefficient, while the loss intensification trend coefficient promotes cooperation by amplifying the cost of non-cooperation. (3) The heterogeneity in economic preferences of local governments affects the stability of cooperation. Governments with stronger environmental priorities are more inclined to form the core of cooperation, whereas those driven by stronger economic priorities are more vulnerable to parameter fluctuations, leading to instability in overall participation levels. Reducing or eliminating this heterogeneity can improve both participation rates and the stability of cooperation. These findings offer theoretical support for designing intergovernmental collaborative governance mechanisms for rural water environments and provide practical guidance for calibrating reward–punishment schemes, identifying key coordinating departments, and stabilizing cross-departmental participation, thereby facilitating an efficient transition in rural water environmental governance models. Full article

Background/Objective: Post-COVID survivors present significant respiratory deficiency that has been associated with ongoing shortness of breath and impaired lung function. Inspiratory muscle training (IMT) is increasingly used in survivors of COVID-19 rehabilitational programs as a means to facilitate recovery of the respiratory system. Yet, its home-based effectiveness across clinically relevant outcomes remains unclear. This systematic review aimed to present current evidence on home- or tele-delivered IMT in the post-COVID-19 population. Methods: PubMed, Scopus, Cochrane library and Science Direct were systematically searched for studies evaluating home-based (or telerehabilitation) IMT, alone or as part of a respiratory muscle training program, in adults with post-COVID-19 symptoms. The primary outcome was inspiratory muscle strength. Secondary outcomes included dyspnea, pulmonary function, exercise capacity and health-related quality of life. The methodological quality of the included studies was assessed via the PEDro scale. Owing to clinical and methodological heterogeneity, we performed only a qualitative synthesis. Results: Eight studies met the inclusion criteria. Two included both inspiratory and expiratory muscles training and three included physical training as well. The methodological quality was found to be good. IMT consistently increased inspiratory muscle strength across trials. Respiratory muscle training (RMT) programs that combined inspiratory and expiratory training also improved maximal expiratory pressure. IMT reduced dyspnea versus control/sham or baseline and several studies reported improvements in exercise capacity and physical function. Spirometry/DLCO changes were small or null in most cohorts. HRQoL gains were domain-specific in anxiety and depression. Adherence was generally good. No serious adverse events attributable to IMT were reported. Conclusions: Home-based IMT for adults with post-COVID-19 conditions is safe and seems to improve inspiratory muscle strength and dyspnea, with signs of benefit for exercise capacity, physical function, and selected HRQoL domains. Effects on ventilatory efficiency and conventional lung function appear limited. Future multicenter, sham-controlled RCTs should further explore the characteristics of IMT, employ core outcome sets, include longer follow-up, and predefine phenotype-based subgroups. Full article

The valorization of protein-rich meat and bone meal (MBM) via composting is hampered by significant nitrogen loss. Genomic analysis of Aeribacillus pallidus (A. pallidus) strain 60 revealed a genetic repertoire encoding potent proteolysis and nitrogen assimilation. We hypothesized that this strain could function as a microbial catalyst to redirect nitrogen flux during MBM composting. In a laboratory-scale trial, inoculation with A. pallidus triggered a rapid thermal surge (reaching 70 °C) and proteolytic cascade, significantly accelerating maturation. Crucially, this process enhanced relative nitrogen retention, increasing final total Kjeldahl nitrogen (TKN) concentration by 10.87–13.33% and nitrate by 13.75–18.65% compared to controls. Physicochemical and microbial profiling revealed that these improvements were driven by an inoculant-induced environmental modification rather than sustained inoculant dominance. The created thermal niche facilitated a distinct two-stage succession: an initial enrichment of proteolytic genera (Thermoactinomyces, Ammoniibacillus) followed by the establishment of a putative nitrifying community dominated by Pseudoxanthomonas. This study illustrates how a pioneer inoculant can drive functional microbiome assembly through niche modulation, providing a targeted strategy for optimizing nitrogen recovery in protein-dense waste valorization. Full article

Renewable hydrogen purification is a critical yet often underemphasised step in enabling its use as a clean energy carrier. Hydrogen produced from biomass-based thermochemical and biological routes typically contains CO₂, CO, CH₄, H₂S, and other impurities that must be removed to meet stringent requirements for fuel cell, industrial, and grid-injection applications. This review provides a critical and up-to-date assessment of renewable hydrogen purification technologies, focusing on their suitability for variable and impurity-rich renewable hydrogen streams. Established benchmark technologies, including pressure swing adsorption and cryogenic separation, are described, with emphasis on their operating principles, material innovations, and process integration strategies. Recent advancements in inorganic, polymeric, and mixed-matrix membranes are highlighted, with particular focus on how advanced porous materials enhance selectivity, permeability, and flexibility. Additionally, a comparative techno-economic assessment is presented, evaluating each purification method based on technology readiness level, capital and maintenance costs, energy efficiency, and operational lifespan. By incorporating recent research trends, this approach facilitates the selection and design of purification systems that are not only efficient and scalable but also cost-effective, tailored to both decentralised and centralised renewable hydrogen production. Full article

Environmental challenges, such as climate change, resource scarcity, and pollution, increasingly demand organizational strategies that integrate artificial intelligence (AI) into sustainable innovation. This study examines how employee-level artificial intelligence capabilities (AIC) enable digital green innovation, a strategic approach that leverages AI-powered digital technologies to enhance green product development, green processes, and sustainable supply chains. Drawing on knowledge-based view (KBV) and the dynamic capability view (DCV), this study develops a theoretical framework linking AIC, knowledge-based dynamic capabilities (KBDC), and digital green innovation. Using survey data from 299 employees in Chinese High-Tech firms, results show that higher employee AIC strengthens KBDC, which in turn facilitates effective digital green innovation. The findings contribute theoretically by extending the antecedents of digital green innovation to the individual level and clarifying the multilevel mechanism through which AIC translates into organizational environmental performance, thereby enhancing both theories’ explanatory power in digital environments. Practically, the study highlights the importance for environmental managers of strengthening employee AIC and organizational KBDC to implement AI-driven sustainability strategies more effectively. Full article

Pest insect-associated microbes display great phenotypic and genotypic diversity, with many members inhabiting broader ecological niche. Several of these bacteria are ubiquitous in nature and contribute to fruit spoilage. When microbes occur in both environmental niches and insect hosts, their ability to adapt to diverse substrates may facilitate their ecological success. This study focuses on characterization of the metabolic capability of three bacterial isolates belonging to the genera Acetobacter and Pantoea associated with Drosophila suzukii collected in the Netherlands. Carbon utilization patterns and tolerance to environmental stressors were assessed under varying conditions of salinity, pH, and antibiotics. The isolates differed in their metabolic profiles but collectively demonstrated the capacity to utilize a wide range of carbon sources. In addition, they exhibited tolerance towards different chemicals including salt and antibiotics. The metabolic flexibility of bacteria associated with D. suzukii may facilitate their persistence within fruit environments and contribute to host ecology. Overall, this study provides functional insight into insect-associated bacteria and underscores the importance of metabolic characterization in understanding their ecological significance. Full article

This study aims to evaluate the impact of agricultural land property rights system reform on Agricultural Green Total Factor Productivity (AGTFP) and to uncover its underlying mechanisms. Treating the nationwide rollout of the Three Rights Separation Reform (TRSR) as a quasi-natural experiment, we employ provincial panel data from 2011 to 2023. The Super-SBM model is applied to measure AGTFP, followed by a multi-period Difference-in-Differences framework to identify the causal effects. The results indicate that the TRSR significantly enhances AGTFP, yielding an average improvement of 0.112 units. Mechanism analyses reveal that this gain is achieved through three distinct channels: promoting labor-saving technological progress, optimizing factor allocation efficiency, and facilitating agricultural green transformation. Heterogeneity analyses further demonstrate that the positive effects are more pronounced in plains regions, areas with lower rural per capita income, and jurisdictions with higher agricultural fiscal expenditure. These findings remain robust after a series of robustness and endogeneity tests. This study provides novel institutional evidence on the drivers of AGTFP and offers policy-relevant insights for advancing sustainable agricultural transformation in developing economies. Full article

Phosphorus deficiency is a key factor limiting plant growth in desertified grasslands. Elucidating the adaptive strategies of pioneer plants that integrate root morphology and microbial interactions is crucial for understanding the natural restoration of ecosystems. This study investigated the strategies employed by Kengyilia hirsuta, a pioneer grass species in desertified grasslands, to adapt to low-phosphorus environments. By conducting sand culture experiments under varying phosphorus levels (low, optimal, and high), we focused on elucidating the synergistic adaptive mechanisms involving the root–rhizosheath system. The results showed that the rhizosheath serves as a critical micro-ecological niche for enriching arbuscular mycorrhizal fungi (AMF) and enhancing phosphatase activity. Under low-phosphorus stress, the plant strengthened root hair development and its symbiotic association with AMF, which markedly increased acid phosphatase activity and led to the highest phosphorus use efficiency. At the optimal phosphorus level, the plant developed an efficient “rhizosheath–mycorrhiza” synergistic system, characterized by high AMF colonization and spore density, facilitating optimized carbon–phosphorus exchange. Under phosphorus-sufficient conditions, the adaptive strategy transitioned towards root morphological plasticity, exemplified by increased surface area and branching. Multivariate analysis revealed that the phosphorus absorption efficiency of K. hirsuta is co-regulated by both morphological adaptation and symbiotic optimization. This study elucidates the mechanisms of nutrient stress adaptation in desertified grassland plants, providing a theoretical foundation for understanding the natural restoration processes of degraded ecosystems. Full article

The construction of high-speed railways (HSRs) is the core engine for promoting the economic integration and spatial structure optimization of the Guangdong–Hong Kong–Macao Greater Bay Area (GBA). Changes in land use along HSR corridors are inextricably linked to the efficacy of regional coordinated development and ecological protection initiatives, as well as the realization of regional sustainable development. Nevertheless, past relevant studies exhibit prominent limitations. First, the lack of effective methodologies for the intuitive comparison of multiple research subjects makes it difficult to accurately portray the differential characteristics of land use across various HSR routes. Second, the insufficient comprehensive analysis of the dynamic evolution of landscape patterns along routes, coupled with the absence of intuitive spatial visualization expressions, fails to explicitly reveal the spatiotemporal differentiation of landscape fragmentation, which hinders sustainable land resource utilization and ecological protection. To address these gaps, this study introduces the intensity comparison map and the comprehensive index map of landscape fragmentation and takes six typical HSRs in the GBA to conduct an intuitive comparative analysis of land use changes along multiple routes. Results show that land use evolution along HSRs presents distinct phased characteristics, with construction land acting as the core driving factor. Its proportion increases continuously, while the proportions of cultivated land and water bodies decline dramatically. Significant disparities exist in land use evolution across different HSR routes, which are closely associated with the natural and economic conditions of the traversed regions, reflecting the heterogeneous adaptability between individual routes and regional development dynamics. High landscape fragmentation areas are predominantly distributed in the transition zones between construction land and natural landscapes; fragmentation intensifies during the planning and construction phases and stabilizes or even diminishes along certain routes during the operation phase, with human activities identified as the pivotal influencing factor. This research deepens the understanding of the interaction mechanism between transportation infrastructure and land use changes in the GBA and provides a scientific basis for sustainable HSR construction planning, the rational utilization of land resources, and the coordinated advancement of ecological protection in the GBA and other similar regions worldwide, thus facilitating the sustainable development of high-density urban agglomerations globally. Full article