Search Results (1,836)

How to coordinate the relationship between nature reserves and surrounding communities to achieve a win–win situation for protection and development has become an urgent issue that governments around the world need to address. The concept of community co-management emerged in this context, aiming to promote cooperation and interaction between protected areas and surrounding communities, achieve sustainable use of natural resources, and promote the healthy development of the community economy. This study conducted empirical analysis using the Xishuangbanna National Nature Reserve and surrounding communities in China as a case study. This study aims to reveal the key factors affecting the perception of the households in the surrounding communities of the national nature reserve through an in-depth analysis of their perceptions, attitudes, and actual effects on the innovative management model of community co-management. At the same time, it provides empirical evidence and theoretical support for the construction of a more reasonable, efficient, and win–win nature reserve management model. Based on field research and interviews, combined with a questionnaire survey of stakeholders, this study utilized the Q method to conduct a comprehensive analysis of household perceptions under community co-management. The research results indicate that community co-management is an effective path to promote the coordinated development of the local economy, society, and ecology. Specifically, this model not only significantly promotes employment and entrepreneurship among community residents but also achieves economic self-sufficiency and steady growth by cultivating characteristic industries and building distinctive brands. Further analysis reveals that improving residents’ well-being is the core value of community co-management. Meanwhile, system reform is seen as the key to promoting the deepening development of community co-management. This study not only helps to enhance households’ understanding and participation in ecological protection and promotes the deep integration of ecological protection and community development but also provides valuable experience and inspiration for the management of nature reserves in other regions around the world. Full article

The IgLON family of tumor suppressor genes (TSG) impact a variety of cellular processes involved in cancer and non-cancer biology. OPCML is a member of this family and its inactivation is an important control point in oncogenesis and tumor growth. Here, we analyze RNA-Seq expression ratios in ovarian cancers from The Cancer Genome Atlas (TCGA) (189 subjects at Stage III) to identify genes that exhibit a cooperative survival impact (via Kaplan–Meier survival curves) with OPCML expression. Using enrichment analyses, we reconstruct functional pathway impacts revealing interactions of OPCML, and then validate these in independent cohorts of ovarian cancer. These results emphasize the role of OPCML’s regulation of receptor tyrosine kinase (RTK) signaling pathways (PI3K/AKT and MEK/ERK) while identifying three new potential RTK transcriptomic linkages to KIT, TEK, and ROS1 in ovarian cancer. We show that other known extracellular signaling receptor ligands are also transcriptionally linked to OPCML. Several key genes were validated in GEO datasets, including KIT and TEK. Considering the range of OPCML impacts evident in our analyses on both external membrane interactions and cytosolic signal transduction, we expand the understanding of OPCML’s broad cellular influences, demonstrating a multi-functional, pleiotropic, tumor suppressor, in keeping with prior published studies of OPCML function. Full article

Background: Emerging and re-emerging infectious diseases (EIDs and Re-EIDs) cause significant economic crises and public health problems worldwide. Epidemics appear to be more frequent, complex, and harder to prevent. Early warning systems can significantly reduce outbreak response times, contributing to better patient outcomes. Improving early warning systems and methods might be one of the most effective responses. This study employs a bibliometric analysis to dissect the global research hotspots and evolutionary trends in the field of infectious disease early warning, with the aim of providing guidance for optimizing public health emergency management strategies. Methods: Publications related to the role of early warning systems in detecting and responding to infectious disease outbreaks from 1999 to 2024 were retrieved from the Web of Science Core Collection (WoSCC) database. CiteSpace software was used to analyze the datasets and generate knowledge visualization maps. Results: A total of 798 relevant publications are included. The number of annual publications has sharply increased since 2000. The USA produced the highest number of publications and established the most extensive cooperation relationships. The Chinese Center for Disease Control & Prevention was the most productive institution. Drake, John M was the most prolific author, while the World Health Organization and AHMED W were the most cited authors. The top two cited references mainly focused on wastewater surveillance of SARS-CoV-2. The most common keywords were “infectious disease”, “outbreak”, “transmission”, “virus”, and “climate change”. The basic keyword “climate” ranked the first and long duration with the strongest citation burst. “SARS-CoV-2”, “One Health”, “early warning system”, “artificial intelligence (AI)”, and “wastewater-based epidemiology (WBE)” were emerging research foci. Conclusions: Over the past two decades, research on early warning of infectious diseases has focused on climate change, influenza, SARS, virus, machine learning, warning signals and systems, artificial intelligence, and so on. Current research hotspots include wastewater-based epidemiology, sewage, One Health, and artificial intelligence, as well as the early warning and monitoring of COVID-19. Research foci in this area have evolved from focusing on climate–disease interactions to pathogen monitoring systems, and ultimately to the “One Health” integrated framework. Our research findings underscore the imperative for public health policymakers to prioritize investments in real-time surveillance infrastructure, particularly wastewater-based epidemiology and AI-driven predictive models, and strengthen interdisciplinary collaboration frameworks under the One Health paradigm. Developing an integrated human–animal–environment monitoring system will serve as a critical development direction for early warning systems for epidemics. Full article

The diffusion of green energy technological innovation based on international green energy cooperation is a critical pathway to achieving global low-carbon emission reductions. However, few studies have considered the innovation diffusion pathways of green energy technologies under bilateral policy uncertainties. This paper constructs an evolutionary game model for the diffusion of green energy technological innovation in a complex network environment, with a focus on analyzing the impacts of key parameters such as policy spillover effects, technological heterogeneity, technical leakage risks, and free-riding risks on the equilibrium outcomes of evolutionary strategies. The results of the study are as follows: (1) Technological synergy and technological heterogeneity have a significant role in promoting the diffusion of green energy technological innovation, but when technological heterogeneity is too high, it is difficult for the two parties to find more common interests and areas of technological interaction, and the cooperative innovation will be turned into an empty shell that has a name but no reality. (2) Policy uncertainty has a significant impact on the diffusion of green energy technology innovation, and the specific impact depends on the type of policy, policy intensity, policy spillover effects, and other key parameters. (3) The risk of technological obsolescence has prompted countries to deeply participate in green energy international cooperation to realize the “curved road overtaking” of green energy technology based on technological locking and latecomer advantages; due to the existence of the phenomenon of “free-riding”, the logic of value creation based on win–win cooperation is replaced by the opportunism of “enjoying the benefits”, and cooperative innovation may be turned into a one-time “handshake agreement”. The existence of the risk of technology leakage can turn collaborative innovation into a “witch hunt” by the underdog against the overdog, and the diffusion process of green energy technology innovation is led in the wrong direction. Full article

Insulin-degrading enzyme is a zinc metalloprotease that degrades low-molecular-weight substrates, including insulin. Ubiquitous expression, high evolutionary conservation, upregulation of Ide in stress situations, and literature findings suggest a broader function of Ide in cell physiology and protein homeostasis that remains to be elucidated. We used proteomics and transcriptomics approaches to search for leads related to a broader role of Ide in protein homeostasis. We combined an analysis of the proteome and single-cell transcriptome of Ide^+/+ and Ide^−/− pancreatic islet cells with an examination of the interactome of human cytosolic Ide using proximity biotinylation. We observe an upregulation of pathways related to RNA processing, translation and splicing in Ide^+/+ relative to Ide^−/− islet cells. Corroborating these results and providing a potential mechanistic explanation, proximity biotinylation reveals interaction of Ide with several subunits of CCR4-NOT, a key mRNA deadenylase regulating gene expression “from birth to death”. We propose a speculative model in which human and murine Ide cooperate with CCR4-NOT to control protein expression in proteotoxic and metabolic stress situations through cooperation between their deadenylase and protease functions. Full article

Structural microheterogeneity arising from the cooperative nature of hydrogen bonding is a critical yet often overlooked factor in the mechanistic understanding of physicochemical and biological processes occurring in aqueous environments. MD simulations using a potential that accounts for molecular flexibility and directional interactions revealed inhomogeneity arising from patches of continuously connected, four-bonded molecules embedded within a less ordered, space-filling hydrogen-bond network. The size of these patches follows a statistical distribution that is strongly temperature-dependent. With increasing temperature, the average size of the patches decreases, whereas the contribution of molecules forming the inter-patch zones becomes more pronounced. The nature of microheterogeneity is evidenced by temperature-dependent changes in the asymmetry of calculated power spectra as well as in the measured IR absorption within the stretching, bending, and combination band regions. A novel method for band analysis incorporates the calculation of skewness and a mirroring procedure for more accurate determination of FWHM of asymmetric bands. Discontinuities in the temperature dependence of spectral parameters observed within the 5–80 °C range correspond to the thermodynamic anomalies of liquid water. We show that structural microheterogeneity persists near 100 °C, suggesting that aqueous processes are better described by statistical distributions than by uniform models. Molecular simulations and IR spectroscopy offer key insights into these distributions. Full article

The rapid urbanization of the world has brought significant environmental, social, and economic challenges to human society. To build a sustainable county, there are many limiting factors, such as the environment, financial resources, and population. Based on this, the purpose of this study is to investigate how countries can empower their development through a sustainable design path for parks with the participation of all. The core of public participation in co-construction lies in the interactive relationship between the government, society, citizens, and many other groups. That is, “co-construction, co-governance, and sharing” is the basic content of the new pattern of social governance from the perspective of the park city; at its core is joint participation, division of labor, and cooperation. Using qualitative research methods, Kaiyuan, a county in Yunnan Province, was selected as a case study, focusing on the Phoenix Ecological Park and Happiness Lawn; citizens and managers were interviewed to explore paths for sustainable design in the counties. The contribution of this study is a research model of sustainable design for county parks with the participation of all the people. The study found that public participation should consider multiple co-constructions and formulate a sound sustainable design path from three dimensions: counties, managers, and citizens. Combined with the local characteristics of counties, the government has called on enterprises, organizations, and citizens to participate together in improving the quality of life and happiness of county residents. The results can be further verified in other counties. Full article

This study addresses the increasing emphasis on sustainability and the importance of understanding how environmental risk influences business failure, a factor unexplored in traditional financial prediction models. Environmental risk, or environmental financial exposure, refers to the potential percentage of a company’s revenue at risk due to the environmental damage it causes. Previous research has not sufficiently integrated environmental variables into failure prediction models. This study aims to determine whether environmental risk significantly predicts business failure and how it interacts with conventional financial indicators. Utilizing data from 971 Spanish cooperative companies in 2022, including financial ratios, the VADIS bankruptcy propensity indicator, and the TRUCAM environmental risk score, the study employs the Extreme Gradient Boosting (XGBoost) machine learning algorithm, chosen for its robustness in handling multicollinearity and nonlinear relationships. The methodology involves training and validation samples, cross-validation for hyperparameter tuning, and interpretability techniques such as variable importance analysis and partial dependence plots. Results demonstrate that the variable related to environmental risk (TRUCAM) ranks among the top predictors, alongside liquidity, profitability, and labor costs, with higher TRUCAM values correlating positively with failure risk, underscoring the importance of sustainable cost management. These findings suggest that firms facing substantial environmental risk are more prone to financial distress. By incorporating this environmental variable into a machine learning framework, this work contributes to the interaction between sustainability practices and corporate viability. Full article

Augmented Reality (AR) seamlessly blends the real-world environment with digitally generated content, creating an interactive hybrid experience where both realities coexist. This paper explores an augmented reality application developed for natural heritage education, specifically designed to enhance indoor learning. The focus is on a learning activity titled Exploring the Aquarium, implemented by the Education Centre for the Environment and Sustainability (E.S.E.C.) of Kastoria as part of an environmental education program. The activity enriches students’ knowledge and experiences during their aquarium visit, fosters active participation in the learning process, stimulates cognitive interest, and encourages actions that support the ecological restoration of aquatic ecosystems. This paper presents the application’s design criteria, thematic focus, learning objectives, and core functionalities. Additionally, the paper presents findings from quantitative research evaluating the learning experience. A questionnaire tailored for AR applications was employed to assess aspects such as challenge, educational value (knowledge gained), user collaboration, and intention to reuse the app. Data were collected from 148 K-12 students during the 2023–2024 school year. Descriptive statistical analysis revealed that all factors were evaluated highly. The results indicate that the AR-enhanced educational activity captured the students’ interest and facilitated a collaborative learning environment. The application was positively rated for its functionality, usability, informational content, and the satisfaction it provided, as well as its ability to encourage cooperation and future reuse. Full article

Valerian root extracts are widely used as mild sedatives to promote sleep, with clinical studies confirming their efficacy. Their sleep-promoting effects are associated with the adenosine A1 receptor (A1AR), a key regulator of sleep through neural activity inhibition. Adenosine, a neuromodulator that accumulates during wakefulness, activates A1ARs to facilitate sleep transitions. Using advanced analytics, we detected adenosine at 0.05% in the valerian extract Ze 911, supporting direct A1AR activation in vitro. Additionally, we explored A1ARs’ allosteric sites for modulatory activity. Valerenic acid and pinoresinol, key constituents of Ze 911, were identified as positive allosteric modulators (PAMs) of A1ARs. Valerenic acid exhibited strong PAM activity, with high cooperativity (αβ = 4.79 for adenosine and αβ = 23.38 for CPA) and intrinsic efficacy (τB = 5.98 for adenosine and τB = 3.14 for CPA). Pinoresinol displayed weaker PAM activity, with moderate cooperativity (αβ = 3.42 for adenosine and αβ = 0.79 for CPA) and limited efficacy (τB = 0.93 for adenosine and τB = 1.66 for CPA). The allosteric modulation observed in valerian extract Ze 911 suggests a mechanism of action in which valerenic acid and pinoresinol enhance receptor activation through allosteric interactions, potentially amplifying the effects of endogenous adenosine. By targeting A1ARs’ allosteric sites, valerian extract Ze 911 offers increased therapeutic selectivity and reduced off-target effects, emphasizing its potential for managing sleep disorders. Full article

Farmer professional cooperatives are the focus objects of agricultural carbon emission reduction; with the use of the advantages of scale economy and technology, one can promote the development of low-carbon agriculture. In order to study the influencing factors of agricultural carbon emission reduction on farmer professional cooperatives, we explore the interaction effects of carbon emission reduction behavior between farmer professional cooperatives and farmers under government interventions. This paper introduces a carbon transaction mechanism as well as reward and punishment polices into a tripartite evolutionary game model between farmer professional cooperatives, governments, and farmers. Based on the model, we identify a stable evolution strategy and perform simulation analysis. The results indicate that the carbon transaction mechanism can effectively suppress the negative effect of increased costs through higher revenues of the carbon transaction, and carbon prices above 60 CNY/ton enable cooperatives to reduce regional emissions. Higher revenues can promote positive carbon emission reduction behaviors of farmer professional cooperatives and farmers. The sharing ratio increases from 20% to 80%, and farmers gain additional benefits by cooperating in the farmer professional cooperative practices to reduce emissions. Rational regulation of carbon transaction price and quota can promote the participation of farmer professional cooperatives in carbon emission reduction practices and promote the farmers’ inclusion into farmer professional cooperatives. Full article

Marine oil spills significantly adversely affect the socio-economic environment and marine ecosystems. Establishing an efficient emergency cooperation mechanism that enables swift and coordinated responses from all stakeholders is crucial to mitigate the harmful consequences of such spills and protect regional security. This study uses stochastic evolutionary game theory to develop an emergency cooperation model, focusing on the strategic interactions and dynamic evolution between three main parties: the local government, port enterprises, and specialized oil spill cleanup units. The findings indicate the following: (1) The strategy choice of the local government plays a dominant role in the three-party game and has a significant guiding effect on the behavioral decisions of port enterprises and specialized oil spill cleanup units. (2) The strength of the government’s reward and punishment mechanism directly affects the cooperation tendency of the port enterprises and specialized oil spill cleanup units. (3) When the emergency response is more efficient and the cooperation effect is significant, the cleanup units may choose negative cooperation based on payoff maximization in order to prolong the cleaning time. (4) In the process of system evolution, the strategies of local governments and port enterprises are more stable and less affected by random perturbations, while the strategy fluctuations of cleanup units are more sensitive. The findings enrich the theoretical framework for handling marine oil spill emergencies and provide valuable insights for developing efficient collaborative mechanisms and formulating well-grounded regulatory incentive policies. Full article

Background: In response to the urgent need for new antibiotics targeting high-priority MDR pathogens, bacteriophages (phages) have emerged as promising non-traditional antimicrobial agents. Phages are viruses that infect bacteria and induce cell lysis through mechanisms distinct from those of antibiotics, making them largely unaffected by most antibiotic resistance mechanisms. Importantly, phages have been shown to work cooperatively with an array of clinically useful antibiotics, and phage–antibiotic synergy (PAS) represents a sophisticated strategy that may improve treatment outcomes. However, the interactions between phages and antibiotics are diverse, ranging from synergistic to antagonistic, and understanding the mechanisms underlying these interactions is crucial for developing effective PAS treatments. In this review, we summarize the potential evolutionary and molecular mechanisms that drive PAS and the current landscape of phage–antibiotic interactions. Conclusions: Towards the development of robust PAS strategies, we review in vitro methods for assessing PAS and considerations for choosing and employing candidate phage–antibiotic combinations. Full article

Boating tourism in coastal–maritime areas often overlaps spatially and temporally with other economic activities, such as fishing, leading to complex interactions. These interactions can create opportunities for positive cooperation or generate conflicts that pressure natural resources and stakeholders. The aim of this study is to show whether or not there is evidence of interactions between fishing (n_f = 43) and tourism/recreation (n_t = 65) vessels. This study focuses on the interaction between maritime tourism activities and fishing in southern Portugal, using a social network analysis (SNA) approach based on automatic identification system (AIS) data to evaluate spatial and temporal patterns. The findings reveal that tourism activities dominate zones closer to the coast, with intermediate areas serving as shared spaces where interactions between vessel activities are more likely to occur. There was evidence of occasional interactions between a few recreational and fishing vessels (two passengers and three seiners), but the inferences from the results are insufficient to demonstrate how beneficial they are for both activities. Full article

The rapid emergence of the platform economy has accelerated the practice of embedded innovation, with ecosystem partner selection serving as a critical first step in platform enterprises’ innovation collaborations and playing a key role in enhancing innovation efficiency and outcomes. Based on the theory of embedded innovation, this study identifies the core innovation demands of platform enterprises at distinct stages. It then employs QFD to quantify decision indicator weights for ecosystem partner selection. By integrating Prospect Theory with Field Theory, this study develops both a decision evaluation model and an optimization model to achieve the optimal screening of ecosystem partners. Specifically, this study contributes in the following ways: (1) It constructs an embedded innovation direction selection model to uncover the evolving innovation demands at each stage. Within the QFD framework, we map these demands onto selection evaluation indicators, assess their importance via the maximum entropy principle, and determine indicator weights through a correlation matrix. (2) It proposes a Prospect Theory-based TOPSIS evaluation model, incorporating decision-makers’ psychological preferences to mitigate bias arising from singular or excessive risk attitudes. This model ranks potential partners according to their closeness to an ideal solution. Finally, (3) it designs a Field Theory-based optimization model that accounts for the platform enterprise’s perspective, partner-matching rationality, and continuity of interaction. This model emphasizes the complementarity and synergy of innovation resources to enhance cooperation fit and strategic alignment between the platform and its partners. Finally, this study conducts an empirical analysis on platform enterprise XM and validates the model’s feasibility and stability through sensitivity testing and comparative analyses. This study enriches the understanding of ecosystem partner selection within platform ecosystems by advancing methods for quantifying partner demands and refining the selection of evaluation indicators. It also deepens the depiction of non-rational characteristics in behavioral decision-making and elucidates the mechanisms underlying the ongoing interactions between platform enterprises and their ecosystem partners. These theoretical contributions not only extend the scope of research on platform ecosystems and embedded innovation but also provide feasible approaches for platform enterprises to improve partner governance and foster collaborative innovation in dynamic and complex environments. Ultimately, the findings offer strong support for enhancing innovation performance and building sustainable competitive advantages. Full article