Search Results (52)

Background: The emergency medical services (EMS) sector, as a complex system, presents substantial hurdles in providing excellent treatment while operating within limited resources, prompting greater adoption of artificial intelligence (AI) as a tool for improving operational efficiency. While AI models have proved beneficial in healthcare operations, there is limited explainability and interpretability, as well as a lack of data used in their application and technological advancement. Methods: The scoping review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for scoping reviews, using PubMed, IEEE Xplore, and Web of Science, with a procedure of double screening and extraction. The search included articles published from 2018 to the beginning of 2025. Studies were excluded if they did not explicitly identify an artificial intelligence (AI) component, lacked relevance to emergency department (ED) or prehospital contexts, failed to report measurable outcomes or evaluations, or did not exploit real-world data. We analyzed the data source used, clinical subclasses, AI domains, ML algorithms, their performance, as well as potential roles for large language models (LLMs) in future applications. Results: A comprehensive PRISMA-guided methodology was used to search academic databases, finding 1181 papers on prehospital emergency treatment from 2018 to 2025, with 65 articles identified after an extensive screening procedure. The results reveal a significant increase in AI publications. A notable technological advancement in the application of AI in EMS using different types of data was explored. Conclusions: These findings highlighted that AI and ML have emerged as revolutionary innovations with huge potential in the fields of healthcare and medicine. There are several promising AI interventions that can improve prehospital emergency care, particularly for out-of-hospital cardiac arrest and triage prioritization scenarios. Implications for EMS Practice: Integrating AI methods into prehospital care can optimize the use of available resources, as well as triage and dispatch efficiency. LLMs may have the potential to improve understanding and assist in decision-making under pressure in emergency situations by combining various forms of recorded data. However, there is a need to emphasize continued research and strong collaboration between AI experts and EMS physicians to ensure the safe, ethical, and effective integration of AI into EMS practice. Full article

Lactic acid bacteria (LAB) are central to food, feed, and health biotechnology, yet their genomes have long resisted rapid, precise manipulation. This review charts the evolution of LAB genome-editing strategies from labor-intensive RecA-dependent double-crossovers to state-of-the-art CRISPR and CRISPR-associated transposase systems. Native homologous recombination, transposon mutagenesis, and phage-derived recombineering opened the door to targeted gene disruption, but low efficiencies and marker footprints limited throughput. Recent phage RecT/RecE-mediated recombineering and CRISPR/Cas counter-selection now enable scar-less point edits, seamless deletions, and multi-kilobase insertions at efficiencies approaching model organisms. Endogenous Cas9 systems, dCas-based CRISPR interference, and CRISPR-guided transposases further extend the toolbox, allowing multiplex knockouts, precise single-base mutations, conditional knockdowns, and payloads up to 10 kb. The remaining hurdles include strain-specific barriers, reliance on selection markers for large edits, and the limited host-range of recombinases. Nevertheless, convergence of phage enzymes, CRISPR counter-selection and high-throughput oligo recombineering is rapidly transforming LAB into versatile chassis for cell-factory and therapeutic applications. Full article

Plasma arc welding (PAW) is commonly employed for welding medium and thick plates due to its capability of single-side welding and double-side forming. Ensuring welding quality necessitates real-time precise identification of the melting state. However, the intricate interaction between the plasma arc and the molten pool, along with substantial signal noise, poses a significant technical hurdle for achieving accurate real-time melting state identification. This study introduces a magnetically controlled method for identifying plasma arc melt-through, which integrates arc voltage and arc pool pressure. The application of an alternating transverse magnetic field induces regular oscillations in the melt pool by the plasma arc. The frequency characteristics of the arc voltage and pressure signals during these oscillations exhibit distinct mapping relationships with various fusion states. A hybrid feature extraction model combining gray correlation analysis (GRA) and the Pearson correlation coefficient (PCC) is devised to disentangle the nonlinear, non-smooth, and high-dimensional repetitive features of the signals. This model extracts features highly correlated with the fusion state to construct a feature vector. Subsequently, this vector serves as input for the fusion classification model, CNN-SVM, facilitating fusion state identification. The experimental results of melt-through under various welding speeds demonstrate the robustness of the proposed method for identifying melt-through through magnetic field-assisted melt pool oscillation, achieving an accuracy of 96%. This method holds promise for integration into the closed-loop quality control system of plasma arc welding, enabling real-time monitoring and control of melt pool quality. Full article

As an ecologically fragile and agriculture-dominated region in China, the Tibetan area is in urgent need of green transformation. Based on the survey data of 59 farmers in 16 villages in Hezuo City, this paper empirically examines the influencing factors and decision-making logic of the green production behaviors of farmers in Hezuo City using the Double Hurdle model and the moderated model, and the results show the following: (1) Cognitive norms and environmental regulations are the key elements determining the green production intentions and behavioral responses of farmers, and the driving effect of cognitive norms on behavioral response shows a declining trend in comparison with behavioral intention. Compared with behavioral intention, the effect of cognitive norms on behavioral response showed a downward trend. (2) The consistency between group social cognition and green production cognition significantly influences the behavioral intentions and behavioral responses of farmers regarding green production in Hezuo City. This is conducive to promoting farmers’ intentions to engage in and their continuous response to green production. (3) The role of environmental regulation in enhancing green production intention and behavioral response is more consistent and significant. However, it cannot continuously promote a green production response by influencing green production intention again. The green development strategy can help to align farmers’ cognitive and behavioral responses to green production. It is recommended that the government use environmental regulation as the primary means of driving the current green transformation in Tibetan areas. Full article

Private sector investment interventions serve as essential mechanisms for creating efficient, cost-effective financial solutions and technological support for emerging farmers in developing economies, yet their successful implementation is influenced by various contextual and socioeconomic factors. Using a quantitative research approach, this study examined the factors influencing participation in private sector investment interventions among 121 emerging commercial farmers in KwaZulu-Natal, South Africa, utilizing a Poisson regression model to analyze four key intervention areas: credit access, market access, technical support, and spot supply. The first-hurdle model revealed that age and training skills negatively influenced market access while the training period showed positive influence, and similarly, the second-hurdle equation demonstrated that employment status and training period positively influenced participation intensity levels, though age maintained its negative impact. The findings of the first-hurdle model reveal that age and training skills negatively influenced market participation. The study concludes that employment status and training period positively impacted technical support adoption, with household size and training period emerging as significant determinants of intervention success. The private sector needs to develop strategic partnership models that encourage emerging farmers to participate intensively in interventions that are designed to improve their production and productivity. There is a need for targeted capacity-building programmes and enhanced extension services to improve emerging commercial farmers’ participation in private-sector initiatives. Full article

In the context of advancing the transformation and upgrading of grassland animal husbandry, encouraging and guiding the widespread adoption of livestock insurance plays an important role in promoting the sustainable development of the livestock industry. This paper explores the impact of herders’ attitudes and perceptions towards climate change risks on their livestock insurance strategies. Firstly, experimental economics methods are employed to measure the risk preferences of herders on the Tibetan Plateau. Secondly, a theoretical model incorporating risk preferences and insurance adoption behavior is constructed. Finally, the effects of herders’ risk preferences on insurance adoption behavior are empirically examined through double-hurdle models, instrumental variable models, and moderating effect models. The results reveal that (1) most herders on the Tibetan Plateau exhibit risk-averse characteristics. (2) The degree of risk preference has a significant negative impact on herders’ insurance adoption behavior, while the risk perception significantly positively influences insurance adoption. The results remain valid even after addressing issues of endogeneity and conducting robustness checks. (3) Livestock income plays a crucial moderating role in the mechanism through which risk attitudes affect insurance adoption behavior. (4) The impact of risk preference on insurance adoption behavior shows regional and income heterogeneity. Full article

Agriculture contributes to the South African economy, but this sector is highly vulnerable to climate change risks. Smallholder maize farmers are specifically susceptible to climate change impacts. The maize crop plays a crucial role in the country’s food security as is considered a staple food and feed. The study aimed at examining the socioeconomic factors influencing smallholder maize farmers’ willingness to adopt climate-smart agriculture in the Limpopo Province, South Africa. It was conducted in three different areas due to their specific agro-ecological zones. A multipurpose research design was used to gather data, and multistage random sampling was used to choose the study areas. Subsequently, 209 purposefully selected farmers were interviewed face-to-face using structured questionnaires and focus discussion groups. Descriptive results revealed that 81%, 67%, and 63% farmers in Ga-Makanye, Gabaza, and Giyani were willing to adopt CSA. Using the double-hurdle model, the t-test was significant at 1%, Prob > chi2 = 0. 0000, indicating a good model. At a 5% confidence level, education, crop diversification, and information about climate-smart agriculture (CSA) positively influenced adoption, while household size and agricultural experience negatively influenced it. It is recommended that the Department of Agriculture, Land Reform, and Rural Development provide CSA workshops and educational programs to farmers to enhance their knowledge and decision-making processes regarding adaptation strategies. Full article

Utilizing data from the 2016 Vietnam Household Living Standard Survey, we undertake an empirical investigation into the influence of energy poverty on the health expenditure of Vietnamese households. Employing a double-hurdle model, our empirical findings reveal a negative relationship between energy poverty and health expenditure. Specifically, our results indicate that for each incremental unit increase in energy poverty, there is a substantial reduction of 42.5 percentage points in the overall health expenditure of the households. Furthermore, as energy poverty deepens, we observe declines of 24.6 percentage points and 45.5 percentage points in the expenses incurred for inpatient/outpatient care and self-treatment, respectively. To validate the robustness of our results, we conduct several sensitivity analyses, including propensity score matching, double/debiased machine learning. Across all these methods, our findings consistently underscore the significant and persistent adverse impact of energy poverty on the examined outcome variables. Additionally, to examine the underlying pathways, we conduct a structural equation modeling analysis and find that the relationship between energy poverty and health expenses is mediated by household hospitalization and expenditures on essential items, such as food and daily necessities. Full article

Scaling service operations is an effective way to promote modernization among small farmers. Exploring the factors influencing grain farmers’ choices in selecting services is essential to promote the strong development of the agricultural production service market and improve the efficiency of agricultural operations in China. Based on the 2019 data on corn farmers in the China Rural Revitalization Survey (CRRS) database, and using the Double-Hurdle Model, the factors influencing the service selection behavior of corn farmers are explored, and the research conclusions are as follows: (1) agricultural service prices have a negative impact on the demand for agricultural services, which varies from service to service; (2) labor prices do not influence the demand for any kind of service; (3) land circulation rents have a negative impact on the demand for agricultural services, which varies from service to service; (4) a high family net income can significantly prompt the adoption of agricultural services, which varies from service to service; (5) small-scale farmers are more sensitive to changes in service prices than large-scale farmers; (6) the four economic factors have no effect on the sowing service market. Based on the above conclusions, this paper puts forward suggestions such as improving the market price mechanism for agricultural production services, and increasing subsidies related to agricultural production services. Full article

The Saihanba Forest Farm, a leading planted forest farm, is one of the essential ecosystem service providers for the Beijing–Tianjin–Hebei region in China. Its efforts in afforestation and landscape restoration have been recognized with the award of the Champions of the Earth from the United Nations. However, the Saihanba Forest Farm is facing the challenges of less income resulting from less commercial cutting since it has to prioritize providing ecosystem services such as water conservation, wind prevention, sand fixation, and so on, instead of timber. It is crucial to understand providers’ attitudes toward ecosystem service provision and willingness to accept payment, as it might affect the quantity and quality of ecosystem service provision in the future. In this study, the contingent valuation method was applied to measure the willingness to accept payment for the economic losses incurred due to providing ecosystem services by cutting less wood. A questionnaire survey was conducted among the staff of the Saihanba Forest Farm. A double-hurdle regression model was used to analyze the influencing factors of the willingness to accept payment, with the validation via a Tobit model. The results showed that the Saihanba Forest Farm was willing to accept a payment of CNY 9800.84 (USD 1407.24) per hectare per year for providing ecosystem services to enhance social welfare. The factors, including basic sociodemographic characteristics, attitudes toward conservation activities, and awareness on the concept of payment for ecosystem services, significantly influenced their willingness to accept payment. Full article

Agriculture is an important sector in Zimbabwe’s economy. More than 70% of the population are smallholders relying on agriculture. To support agriculture, Zimbabwe’s government introduced a Targeted Command Agriculture Programme (TCAP), in terms of which the state provides production inputs like seeds, fertilisers, protection chemicals, and extension services. In turn, the farmer is expected to produce 5 tonnes of maize per hectare for the Grain Marketing Board. The cost of inputs that the state provided is then deducted from the 5-tonne maize yield, and the farmer is paid the balance. Numerous authors have studied the design of TCAP and its impact on farmers. However, only a few have focused on the determinants of participation, especially with an empirical basis and in the Mutare District. To bridge this knowledge gap, this study implements a double-hurdle model to determine factors influencing farmers’ participation in Zimbabwe’s TCAP using a sample of 350 farmers. The study found that gender, family size, farmer type, command agriculture education, and distance from the market influenced smallholder farmers’ participation in TCAP. Therefore, policymakers should consider these factors to improve the design of the programme and enhance the participation of smallholder farmers in it. Full article

Australia’s tropical savannas are a vast landscape of grasslands with high biodiversity value. Effective biodiversity conservation in this landscape requires private contributions to complement the under-sized formal conservation estate. The landscape is dominated by rangelands, in particular extensive cattle grazing on pastoral stations which typically measure hundreds or thousands of square kilometers. The paper reports the results of a discrete–continuous (or “two-stage”) choice experiment conducted with savanna pastoralists. A discrete choice experiment explored the stated willingness to participate in two long-term conservation strategies: (i) total exclusion of cattle from designated parcels of land with management of that land for biodiversity, and (ii) the implementation of rotational grazing systems governed by the requirements of biodiversity, among other contractual attributes. An extension question asked about the area that respondents were willing to supply and a contract they were willing to accept. Double-hurdle (type II tobit) modelling was used for combined data analysis. The results show that potential participation in voluntary conservation contracts by pastoralists is primarily influenced by contract attributes, namely, the conservation action required, the stewardship payment received, contract length and whether the contract contains flexibility provisions. Land productivity is also significant. The level of stewardship payment required to incentivize participation in the conservation of grasslands is in line with opportunity costs, in particular option value. The amount of land that pastoralists are willing to supply is determined by the conservation payment as well as farm size and intrinsic motivation. This research illustrates strategies for integrating biodiversity conservation into cattle grazing operations in Australia’s tropical savannas, which are applicable to grasslands globally. It provides data of an economic nature to inform the development of multi-tenure biodiversity conservation strategies. Full article

The farmland shelterbelt is an important artificial ecological project for improving farmland microclimates, ensuring agricultural production, and promoting sustainable development in China’s ecologically fragile areas. Due to the quasi-public attribute, farmland shelterbelts were mainly constructed and managed by the government in the past. In recent years, the reform of the separation of three rights in collective forestland and the mechanism of “private supply of public goods” have prompted farmers to participate in the modern forest management system. However, there is a lack of consistency between farmers’ management intentions and actual contract operation and management behaviors, resulting in weakened management and protection in many places, which seriously restricts the construction efficiency of farmland shelterbelts. Therefore, based on the survey data and planning behavior theory (TPB) of 1106 farmers in 16 major agricultural production areas (counties) in Xinjiang, this study aims to explore the key factors affecting farmers ‘forestry management and production decision making and to verify the transformation mechanism of farmers’ behavior through path analysis. The results show that the management decisions of farmers in ecologically fragile areas follow the path form of “cognitive → intention → behavior”, in which the multi-dimensional cognition of farmers has a significant impact on farmers’ behavioral intention, while the effect on behavioral response is relatively small, which currently depends on the promotion of ecological compensation and government behavior. Finally, this study puts forward countermeasures and suggestions for continuously stimulating the farmers’ forest operation behavior and provides policy reference for promoting the sustainable development of farmland shelterbelts in ecologically fragile areas put forward countermeasures and suggestions for continuously stimulating farmers’ forestry behavior. Full article

Many tropical regions are promoting the cultivation of oil palm. In this regard, different national and international organizations promote oil palm cultivation in Thailand. However, socio-economic and institutional factors are very important to be considered in the adoption of its cultivation. This study aims first to determine the various socio-economic and institutional factors in adopting oil palm cultivation, and second, to explore the role of these stated factors in the extent of the adoption of oil palm. The data were collected through a semi-structured questionnaire in Seka of Bueng Kan province of Thailand. The double-hurdle model was used for the estimation of the farmers’ decision to adopt the new technology and the extent of adoption. Results show that the adoption and extent of adoption of oil palm cultivation were positively influenced by gender (male), oil palm training, and access to extension services, while the size of landholding per family member and age negatively influenced its adoption/extent. To increase the adoption rate of oil palm cultivation, young, educated farmers should be encouraged by providing training and credit and extension services should be made accessible. Full article

Green development of agriculture is inevitable to meet the objective demand of rural ecological environment protection and high-quality agricultural development. Livelihood capital is the basic condition for farmers to carry out the activities of production and management, while ecological cognition is the direct motivation for their behaviors. Based on field research data from 436 farm households in 4 counties of Langao, Fuping, Mian, and Yaozhou in Shaanxi Province, China, the study conducted the double-hurdle model (DHM) to empirically analyze the effects of livelihood capital and ecological cognition on farmer’s decision on green production and the degree of green production. The results show that (1) farmers’ livelihood capital is the basic condition that significantly affects farmers’ green production. Specifically, human capital and social capital have a positive contribution to farmers’ green production decision and degree of green production; natural capital and financial capital do not have a significant effect on green production decision, but have a significant positive effect on the degree of green production behavior; physical capital, as farmers’ stock capital, does not have a significant effect on green production behavior. (2) Ecological cognition plays a positive moderating role in farmers’ decisions on green production, but as a subjective cognition, its contribution to the degree of green production is not significant. This paper explores the relationship between livelihood capital, ecological cognition, and farmers’ green production behavior, and provides suggestions for improving farmers’ participation in green production. Full article