Nowadays, organized retailing has witnessed a newer trend in the upcoming generations. Globally, these changes are attributed to growing family income, increased female participation, the transformation from joint to nuclear family structure, and technological advancements. Moreover, other variables such as lower supply chain costs, growing sales, rising consumer demands, changing market structure, and increasing competition also influenced supply chain networks. It is observed that the organizational nonlivestock supply chain performance is affected by strategic, operational, and environmental aspects. AI is helping to deliver powerful optimization capabilities, which are required for more accurate capacity planning, improved productivity, high quality, lower costs, and greater output, all while fostering safer working conditions. These benefits are all made possible thanks to the introduction of AI in supply chains. By conducting a comprehensive analysis of the relevant previous research, the purpose of this work is to determine the specific contributions that artificial intelligence (AI) has made to supply chain management. This research attempted to discover the present as well as possible AI strategies that may increase both the study of Supply Chain Management as well as the practice of it. This was done in order to solve the current scientific gap of AI in Supply Chain Management. It was also found that there are holes in the existing study that need to be filled by more scientific investigation. To be more exact, the following four facets were discussed: (1) the AI approaches that are most often used in Supply Chain Management; (2) the AI techniques that have the potential to be used in Supply Chain Management; (3) the Supply Chain Management subfields that have benefited from the application of AI so far; and (4) the subfields that have a high potential to be improved by AI. Identifying and evaluating articles from the four supply chain management domains of logistics, marketing, supply chain management, and manufacturing require the use of a predetermined set of inclusion and exclusion criteria. In this study, insights are provided via the use of methodical analysis and synthesis. A better understanding of these parameters not only improves the nonlivestock supply chain processes but also ensures competitive advantage. The present research aims to test the following elements that including supply chain speed, customer retention, supply chain management integration, and various management. The proposed work categorizes the performance of the supply chain using the Improved Feed Forward Network with Particle Swarm Optimization technique. Results indicate that inventory management, customer happiness, profitability, and client base identification are listed as competitive advantage elements. On the other hand, stakeholder satisfaction, innovation and learning, market performance, customer satisfaction, and financial success are the six recognized organizational performance criteria. Resultantly, the overall performance metrics of the proposed work is 94.12%, while accuracy rate, specificity, and sensitivity rate are found to be 94.12%, 92.15%, and 89.14%, respectively. The research can be helpful for industrial managers to optimize the performance of supply chain systems using artificial intelligence. A supply chain is comprised of all of the actions that go into satisfying the needs and requests of customers. From the stage of raw materials to the stage of finished products, these activities are related to the movement and transformation of commodities, information, and finance flows. “A supply chain is a network of facilities and distribution options that performs the functions of procurement of materials, the transformation of these materials into intermediate and finished products, and the distribution of these finished products to customers.” “A supply chain is a network of facilities and distribution options that performs the functions of transformation of these materials into intermediate and finished products” .Even though the effect that manufacturing activities have on the natural environment is a major cause for concern in developed nations, very little is known about the consequences of manufacturing activities in developing nations. This is despite the fact that industrial operations have a significant impact on natural environments. The industrial sector in developing countries is especially polluting, which has led to a large rise in the amount of pressure that is being imposed on the environment. The deterioration of the environment and increased pressure suggest that stringent environmental rules should be implemented in emerging nations in order to prevent environmental degradation from occurring simultaneously with economic growth . Such ruAccording to the United Nations Development Programme , if everAccording to Chirstmann and Taylor's 2001) results in their research, export and commerce with foreign clients are the most important drivers of improvement in environmental conditions in Chinese industry. This is according to the findings of Chirstmann and Taylor's study. Reference  came to 01 resultAn attempt has been undertaken to conduct a study of the literature on various performance indicators for global supply chain management. This study will be based on previous research (GSCM). According to the research that has been done, there are primarily three different types of performance metrics that may be used for GSCM. There are three distinct categories of drivers: drivers, obstacles, and environmentally responsible business practices. The results of the literature review uncovered some holes that need to be filled, which are summarized below. There is no study that has been published in the Indian context that depicts the hierarchy and interaction between the various performance measures of the Global Supply Chain Management (GSCM). GSCM stands for “global supply chain management.” A significant number of the studies that have been published have focused their attention on a limited number of GSCM performance metrics rather than taking into account the wide variety of performance measures that can be broken down into three categories: drivers, barriers, and environmentally friendly practices. At the moment, there is no study that has been published in the relevant literature that assesses various performance measures based on how relevant they are from a variety of perspectives. In the present research, there are four primary points of view that have been taken into account in order to evaluate the various performance criteria. These four perspectives are the most essential participants in the process of implementing GSCM in India's manufacturing industry, which is now in the process of doing so. According to the findings of the investigation of the relevant literature, there are only a small number of studies that can be found in the relevant literature that have produced models for the various performance indicators making use of Exploratory Factor Analysis up to this point. In addition, a confirmatory factor analysis is carried out in order to validate the EFA model that has already been developed. In light of the findings made above, there is a glaring lack of concerted effort being put out to explore the various performance measures of GSCM with the intention of establishing the impact that these metrics have on the industrial sectors. The current research endeavor makes an attempt to investigate the various performance indicators of GSCM and their influence on the manufacturing sectors in order to facilitate the adoption of GSCM in a rising globalized and competitive environment in the context of India. This is done in an effort to make the adoption of GSCM easier in a globalized and competitive environment. The goal of this research was to carry out a questionnaire survey in order to investigate the many performance indicators that are used by manufacturing companies in India. In spite of the fact that a number of studies that are comparable have been reported in the published study, there is an undeniable need for more research that is more in-depth regarding the many performance indicators of GSCM in the context of India.This research takes into account four phases in the supply chain: vendors, production facilities, warehouses, and distribution centers. These steps are listed in the order of their importance to the supply chain in this study attempt. On benchmark tests, it should be noted that when compared to other algorithms, the Non-Linear Inertia Weight Particle Swarm Optimization (NLIW-PSO) method surpassed other PSO versions as well as the Genetic algorithm with good performance. Prior chapters discussed the details of comparative evaluation for the three-echelon supply chain network problem, which was carried out using all PSO variants and GA. It was shown that the NLIW-PSO outperformed all of the other PSO variations and all of the GA in the previous section. Because of this, a technique known as nonlinear inertia weight particle swarm optimization (NLIW-PSO) has been developed for the aim of optimizing the four-echelon supply chain architecture in this research. When it comes to the supply chain network, the total supply chain operating cost (TSCC) and profit of the supply chain network are considered to be performance indicators.The automotive industry throughout the globe seems to be undergoing unplanned shifts, with the enhancement of supply chains being one of the primary areas of concentration alongside the reduction of costs, the optimization of processes, and the enhancement of timely throughput. Having an efficient traceability system in place is the general success metric that must be reached in order to get a superior output in all of the aforementioned priority areas. In the automobile business, “traceability” refers to a system that documents the lineage of the individual components that went into the production of a certain item. Even if businesses have committed a significant amount of resources toward the goal of improving their supply chain and establishing traceability, it has been observed that these businesses still have little visibility and insight into their supply chain at any particular instant. [Case in point] This study intends to utilize blockchain technology in order to eliminate inefficiencies that are present in conventional automotive supply chains. These inefficiencies can be eliminated by increasing transparency, streamlining processes, and decentralizing the network. Additionally, this study will provide stakeholders and companies with a host of value-adding features that will ensure transactions are completed more quickly and smoothly. The research highlights the benefits that may be gained by enabling automotive supply chains with blockchain technology. The establishment of the aforementioned network is accomplished with the help of Hyperledger Composer.There are four components to this objective function (Equations 4.1 to 4.4). It is included in the first part, named overall supplier cost of material (TSMC), that the overall cost of raw materials from all suppliers to the production units are included. Entire total transportation cost (TTC) refers to the total transportation cost incurred from all 139 suppliers to plants, as well as the total transportation cost incurred from plants to warehouses, which is shown in the second portion of the table. In the manufacturing industry, TMC is an abbreviation for Total Manufacturing Cost incurred at the plants, and TWC is an abbreviation for Total Warehouse Cost, which includes the costs of maintaining warehouse inventory as well as the costs of shipping finished goods from warehouses to respective distribution centers in order to meet demand. The total manufacturing cost (TMC) and the total working cost (TWC) are two components of the total manufacturing cost (TMC).(a)Total supplier materials cost(b)Total transportation cost(c)Total manufacturing cost(d)Total warehouse cost(e)Total supply chain operating cost(f)Profit of SCN(g)Revenue generated by SCNIn order to compute the second objective function, which is the total supply chain network Profit (PROF), it is split into five sections (equations 4.1 to 4.4 and equation 4.7) and multiplied together (equation 4.9). To begin, the total revenue generated by sales at warehouse distribution centers is represented by half of the equation. The total supplier material cost will be shown in the second part of the report (TSMC). The total transportation costs (TTC) incurred from all suppliers to plants, as well as the total transportation costs (TTC) incurred from plants to warehouses, are included in the third part. The fourth component represents the total manufacturing cost (TMC) borne by manufacturing facilities. In order to fulfil demand, the fifth component, total warehouse costs (TWC), comprises of the expenses of inventory holding at warehouses as well as the costs of delivering completed items from warehouses to distribution centres. In order to fulfil demand, the total warehouse cost (TWC) is computed as the sum of inventory carrying costs at warehouses and the shipping costs of completed items from warehouses to distribution centres. TWC is calculated as a percentage of the total warehouse cost.In the proposed algorithm, the network learning parameter is first initialized. Here, the change of weight for output layer and hidden layer is determined using cost function equations (5.7) and (5.8). respectively.Initialize the parameter to some random valuesAssign Threshold value to a fixed value based on the sigmoid function.Calculate linear output using equation (5.2)Calculate non-linear output using sigmoid function as in equation (5.3)Calculate weight change for output layer using equation (5.7)Calculate the weight change for hidden layer using equation (5.8)Calculate the mean square errorIf the mean square error value is greater than threshold value, then the above steps from 3 to 7 is repeatedIf the mean square error value is less than threshold value, then declare that the network is trainedThe ideal mathematical model presented in this section was implemented with the help of the MATLAB simulation programme. This model was then used to showcase the optimal A supply chain data approach in PMU, as seen in The proposed method in the PMU has been considered in the presence of Gaussian noise, as shown above in On the other hand, when there was non-Gaussian noise present, the outcomes of the simulation were taken into account and shown in Figures Similarly, the multi objective analysis was performed for the second set of objectives, which were TSCC and GMROI for the four stage multi echelon supply chain network architecture. Assuming that the objectives had different weights but were of equal importance, the performance analysis was carried out for the different service levels, which were 50%, 84%, 97%, and 99.9%, and the results are tabulated in The decision-making elements that are linked with the various service levels are listed in Other major techniques that can be considered prevalent in the literature include: GAs, a type of search technique that mimics natural selection and is capable of tackling various categories of combinatorial decision problems; data mining, which can be employed to provide insights and make decisions from large data sets; CBR, a cognitive psychological-based technique that solves new problems by retrieving gathered and saved cases of analogous problem-solving episodes and adapting them to the new problem at hand; and CBR is a technique that can be considered Other forms of artificial intelligence that are used in studies of SCM include simulated annealing, automated planning, association rules, tree-based models, hill climbing, k-means clustering, expert systems, heuristics, robot programming, stochastic simulation, Bayesian networks, the Physarum model, RBR, decision trees, and Gaussian models. These forms of AI are used less frequently than others. Studies on SCM have made use of these approaches, but not as often as studies have made use of ANNs, FL, ABSs, GA, data mining, CBR, swarm intelligence, or SVMs. This creates an intriguing gap that need to be addressed in further study and is something that has been done. In addition, our findings indicate that a number of AI techniques, such as NLP (machine–human interactions), TS , and MDP, require additional research and the adoption of these techniques in the industrial sector (a framework for modelling the decision-making process) –25.It has been proven in this suggested work that a variety of unique concepts, approaches, and algorithms may be utilised to the design of integrated supply chain network architecture in order to optimise a structured supply chain network. On the other side, the six recognised organisational performance criteria are stakeholder satisfaction, innovation and learning, market performance, customer satisfaction, and financial success. As a consequence of this, the total performance metrics of the job that was presented are 94.12 percent, and the rates of accuracy, specificity, and sensitivity were discovered to be 94.12 percent, 92.15 percent, and 89.14 percent accordingly.In addition, we discovered that the network-based structure of SCM and logistics gives a natural framework in which to deploy AI. This was discovered via our research. For example, a network of suppliers results in the production of significant quantities of data and calls for swift decision-making. As a result of this, using AI technologies for the study of large data and DSSs is highly suggested. In addition, supply chain management organisations are reliant on both physical and digital networks, both of which need to operate in harmony in order to be successful in the face of high volumes, lean asset allocation, poor margins, and stringent deadlines. AI makes it possible to optimise and improve network orchestration in a way that is both efficient and effective, both of which are impossible for humans to do. Therefore, research on interactive decision-making systems encourages a greater knowledge of AI solutions, and as a result, such study increases the capabilities of AI solutions. The utilisation of such systems makes it possible for AI to assist in the industry in question in redefining the practises that are currently in use by shifting operations from being reactive to being proactive, processes from being manual to being autonomous, services from being standardised to being personalised, and production planning from being predictive to being forecasting. The broad use of artificial intelligence is contingent on the development of more advanced computer chip technology. Because transportation is at the heart of logistics, the use of computer chips as a tracking mechanism is an absolutely necessary step. Research on such processes for the result of these technologies is required since tracking creates vast volumes of data that may be analysed and interpreted for a wide variety of applications. Automation of consumer interactions is a relatively new but potentially fruitful field that plays a major role in marketing. Voice or chatbots are examples of the next generation of customer care, which boasts excellent levels of efficiency and satisfactory returns on investment. The employment of these virtual assistants, which are designed to enable more in-depth conversations to take place between businesses and their clients, may prove to be very useful in the automation of customer support inquiries .


The study constructs a theoretical model of social capital, farm household financing, and scale operation and their environmental effects, and conducts an empirical test based on data from China Family Panel Studies (CFPS) which is conducted in 2018 using causal mediation analysis. The results showed that farmers who spent more on human interaction have a higher probability of choosing scale operation by renting land, the mechanism of which is that the social capital accumulated by farmers based on human interaction facilitates their access to formal and informal financing, which in turn alleviates the financing constraint of scale operation. In addition, we found that the farmers with low education were more dependent on social capital to obtain informal financing to achieve scale operation. The environmental effects of scale operation found that the farmers significantly reduced the proportion of fertilizer and pesticide use, which could effectively mitigate possible pollution problems caused by excessive fertilizer and pesticide use. These findings confirm that social capital can alleviate the financing constraints of farmers to expand their operation scale through formal and informal financing, which in turn has a positive environmental effect. Agricultural scale operation is an important agricultural policy in China. The policy is to achieve large-scale production by promoting land transfer among farmers to achieve multiple goals such as increasing farmers' income, improving agricultural production efficiency, and achieving green development in agriculture. In the past, small-scale farmers often used excessive pesticides, plastic films, and chemical fertilizers, which caused serious environmental pollution and threatened the health of citizens  whose social capital status is denoted as T. To simplify the analysis, here the social capital status of farmers is set to T = 1 (treatment group) i.e., having strong social capital and T = 0 having weak social capital two cases.Firstly, according to the potential outcome framework of Rubin , we assuIn the real world, we cannot observe the potential outcomes of a farmer with both high and low-level social capital, so we introduce average total effects (ATE) asfinan) as a mediating variable to investigate the causal mediation mechanism through which farmer social capital status (T) affects financing and thus farmers' scale operation  according to the causal mediation analysis method.to study the causal effects between social capital and farmers' scale operation from a general perspective. Afterward, we introduced farmer financing status (finani(0) and finani(1) under the different intensity of social capital status, the potential outcome scalei) of farmers' scale operation has four potential outcomes under different values of mediating variable finani(t) and treatment variable T: scalei), scalei), scalei), scalei). Fixing the value of T in scalei and simply varying the value of finani(t) at different T, the change of scalei can indicate the mediating effect of conduction through finani, i.e., the causal mediating effect. Based on the above analysis, the average causal mediation effects (ACME) can be used asCorresponding to two potential values of financing finan. Similarly, after excluding the effect of informal financing, the causal effect of social capital influencing farmers' scale operation can be expressed asto represent the causal mediating effect transmitted through the mediating variable i.e., average direct effects (ADE). In addition, under the assumption of no interaction between the treatment variable (T) and the mediating variable (finan), there is the following relationship:i by Xi and m as the value of the mediating variable finan, the sequential ignorability assumption can be written asAccording to the causal mediating effects model, to estimate ACME and ADE, a set of assumptions, called the sequential ignorability (SI) assumption, needs to be made for the model. By denoting the observed pretreatment confounders of farmer Xi to strengthen the plausibility of the hypothesis.Equation 5 indicates that after controlling for a set of confounding variables, the distribution of each farmer's social capital status is randomized, independent of the farmer's financing status and the farmer's scale operation status. In this study, the social capital of farm households refers to the trust, interaction, and mutual assistance between farm households and people within the village based on the rural acquaintance society. The scale operation status and financing status of farmers do not have a direct effect on this interaction status. Considering the possible indirect effects, for example, farmers who operate on a large scale may have stronger economic power, or households with borrowing may be those whose own family economic power may be weaker. In turn, social circles tend to expand or contract and thus expand as economic strength expands or contracts. Thus, annual household income, household size and a range of household head characteristics, and household characteristics are controlled for in the covariate scalei and finani. Many factors affect both variables, such as farmers with risk appetite tend to finance and tend to expand production; farmers with sufficient household savings do not finance while expanding production, or participation in agricultural cooperatives affects both financing and scale of operation. Although a range of individual, household, and village characteristics and obvious confounding factors were controlled for in the Xi variable as much as possible, this assumption was difficult to fully satisfy due to data availability and objective conditions. Therefore, a sensitivity analysis is used later to further measure the extent to which unobserved confounding factors can have an impact on the robustness of the results.Equation 6 indicates that after controlling for a set of confounding variables and farmers' social capital status, there are no unobservable factors that are simultaneously associated with The traditional mediating effects model examines the mediating effects through the following set of equations  in this study is an ordered multivalued variable. Therefore, it is not possible to estimate consistent estimates of ACME and ADE by estimating the above linear equations. Imai et al.  to reflect the social, economic, and educational changes in China by tracking data at three levels: individual, family, and community. A questionnaire was used, including a household member questionnaire, a household economic questionnaire, an individual self-response questionnaire, and a proxy questionnaire for parents of young children, containing a total of 14,241 household samples and 58,504 individual samples. The data were processed using the following steps: (i) Household members questionnaire, household economic questionnaire, and individual self-answer questionnaire was combined horizontally; (ii) Rural households were filtered out as samples using individual households in the household economic questionnaire; and (iii) Missing values and outliers of related variables were excluded. After the above processing, a final sample of 6,060 households covering 28 provincial administrative regions and a population of 19,163 people was obtained.The definitions of variables are given in Scale operation is a policy term, not a precise economic term in itself. To justify its measurement, two questions need to be clarified: first, how to define “scale”; and second, why do farmers rent land to represent scale operation.From the perspective of traditional economic theory, “scale” basically consists of two meanings: first, it is defined from the perspective of production, and second, it is defined from the perspective of input quantity of production factors. From the perspective of production, different agricultural products are not homogeneous or similar, and it is difficult to measure the production of different crops by one standard; from the perspective of production factors, agricultural scale operation can be manifested both as the increase of a single production factor input and as the combined effect of multiple production factors. The factors of production in agriculture contain land, labor, capital, etc., and the core of agricultural scale operation is agricultural scale production based on the scale of land. Therefore, this study uses land scale as the measure of “scale”.There are two important institutional contexts in which we use whether farmers rent land to characterize farmers' scale operation. First, since the 1980s, the household contract responsibility system has been implemented, under which each village distributes land equally to each household within the village. Due to the objective conditions of China's large population and small land area, it is often difficult to achieve large-scale production on these shared lands. Second, in China, rural land is subject to a system of “three rights”, which divides the property rights of land into ownership, contractual rights, and operation rights. The ownership right is owned by the village collective, while the contractual right and operation right are owned by the farmers. Therefore, the majority of land transfers in China are realized by renting land to form scale operations. Therefore, this paper uses whether a farmer rents land as a reasonable measure of whether a farmer operates on a large scale.Social capital is a concept with a wide range of meanings in itself, and Zhang argues that social capital is divided into institutional capital and relational capital. There is a strong link between the concepts of institutional and relational capital, which exist in a mutually reinforcing and interdependent relationship  and (9) were first fitted and the results are given in To further explore the mediating mechanism and its effect, we estimated each average effect of the mediating mechanism in a counterfactual framework using causal mediation analysis, and the results are presented in The causal mediating effect requires adherence to the SI hypothesis, but it is not possible to test for compliance with that hypothesis with the observed data. Sensitivity analysis can yield the extent to which the study violates this hypothesis and the results remain robust. Specifically, there may be some factors such as villagers joining specialized cooperatives that make it easier for farmers to access informal sources of finance and at the same time increase the likelihood of farmers operating at scale. However, it is not possible to control for all confounding factors due to data availability and other reasons. Sensitivity analysis can capture the extent to which the estimates remain robust to the effects of confounding factors.The results in From the above study, we found that the financing role of social capital is mainly reflected in informal financing, and for this reason, it is necessary to further explore the heterogeneity of its effects to provide us with a deeper understanding of the mechanisms at play. For this purpose, we conduct a more in-depth study on the gender and education of the farm household.In the perception of traditional rural areas, males and females engage in socialization for different purposes. Men are more purposeful in socializing, favoring access to relevant social resources. Women are more inclined to emotional bonding, and thus they believe that male heads of households may be better able to play the role of financing social capital. We estimated the mediating effects separately for female and male household heads, and the regression results are shown in Model 3 of We simultaneously estimated the mediating effects at different levels of education. We estimated their mediation effects separately using the household head's primary education level as low education and high school education level as high education. As shown in model 4 of In the next step, we estimated the environmental effects of farmers' scale operation by testing hypothesis 3. To do this we constructed a simple regression equation to verify whether scale farmers have lower costs of fertilizer and pesticides per acre.i per acre of land, Xi denotes the matrix of control variables, β1 and γ denotes the estimated coefficients of individual scalars, and α is the constant term. Since data is truncated, we used the Tobit model for regression and OLS for auxiliary illustration , Taishan Scholar Foundation of Shandong Province, China.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Montenegro and Serbia, showing overall a high risk.In Europe, African swine fever (ASF) can be sustained within wild boar populations, thus representing a constant source of virus and a huge challenge in the management of the disease. Hunters are the key stakeholders for the prevention, detection and control of ASF in wild boar. Their behavior and the biosecurity standards applied in infected or at-risk hunting grounds have a huge impact on disease dynamics and management. The Food and Agriculture Organization (FAO) has developed a semi-quantitative survey-based novel tool to assess the risk of ASF in hunting grounds  and how such risks could be reduced if mitigation or corrective measures were applied at low, medium and high effort. The weight of risk factors was determined through an expert knowledge elicitation (EKE). The surveys for each hunting ground were filled in by their respective managers. The tool’s outputs allow users to visualize the different ASF risks of hunting grounds, whether as numerical values or color-coded maps, at sub-national, national and regional levels. These outputs can be used to guide policy makers, highlighting gaps or geographical areas to prioritize. The tool was used to assess hunting grounds in Kosovo Asfaviridae family; genus Asfivirus, with high lethality rates for any age and sex, which is responsible for serious economic and production losses [African swine fever (ASF) is a highly contagious viral disease of domestic and wild pigs caused by a virus belonging to the n losses . There in losses  and genoIn the Balkans, the first case of ASF was reported in July 2019 in domestic backyard pigs in the village of Rabrovac in central Serbia . At the The presence of ASF virus in wild boar populations often leads to outbreaks in domestic pigs, usually those kept outdoors and on non-commercial farms, also known as “backyard” farms where biosecurity tends to be lowest , but alsThe continuous presence of the virus in the affected wild boar habitats represents a great challenge to the pig production sector, the wildlife management authorities and the hunting sector. The experiences of infected countries when encountering ASF in wild boar have shown that immediate and coordinated implementation of control measures in wild boar habitats, while the infection is still restricted to a limited area, is crucial to have a chance at confining and eventually eradicating the disease, as happened in Belgium and the Czech Republic ,14. For The human–animal interface, particularly between hunters and wild boar, represents one of the most challenging but necessary aspects to consider when managing this disease. The role that hunters play in the surveillance of wild animal diseases is widely recognized by the international community . Vergne There are multiple checklists and tools available to assess biosecurity, and the risk for disease introduction, detection and spread amongst farms. There is also a study that assessed the routes of ASF infection from wild to domestic pigs . HoweverThe flowchart of the tool, showing the steps and outputs, is presented in The study targeted Kosovo, Montenegro and Serbia, all within the Balkans. Their main characteristics are summarized in A questionnaire was developed to assess the biosecurity applied in hunting grounds, the behavior and practices of hunters, and management practices and characteristics of hunting grounds relevant to disease transmission . The queThe questions were grouped into different sections, namely: Hunting ground characteristics; Status of the hunting ground depending on the ASF risk zone; Active and passive surveillance for ASF; Domestic and wild pigs interface; Control of wild boar hunting procedures; Disinfection measures; Control of the procedures for the safe removal of offal or dead animals; Awareness; Feed ban control; and Previous controls.In Montenegro, the questionnaire was filled in through face-to-face interviews with hunting ground managers and answers were recorded on paper and then copied into an Excel spreadsheet. In the case of Kosovo and Serbia, replies to the questionnaire were captured electronically using an online platform (Epicollect5).When assessing the Risk of ASF Introduction and the Risk of ASF Spread, the model only considered the spread into or between the hunting grounds, not into domestic pigs. Similarly, the ASF Detection Capability only refers to detection in wild boar.At the time of the survey, Serbia had assigned risk categories to each hunting ground , which requires certain additional hunting biosecurity measures to be followed by the hunting grounds. This variable was not taken into account, because even if measures are prescribed, they do not ensure that they are actually implemented in the field.An EKE was developed to weigh the importance of the various risk factors for the three risks to be assessed  based on a scale from 0 to 5 . Experts for the EKE were selected using the snowball sampling method, i.e., a recruitment strategy in which the participants are asked to identify other potential subjects with relevant expertise . Eight eExpert scores for each risk factor were reported as means, medians and standard deviation. Spearman’s rank test was used to assess the correlation between scores for perceived importance of different risk factor categories. To understand the agreement among the experts, the absolute value of the difference between scores was calculated for each pair of experts and each risk factor. The raw agreement was calculated as the percentage of comparison with total agreement (difference of 0) and percentage of deviation by different amounts between two experts (difference from 0 to 5). The Wilcoxon–Mann–Whitney test was applied to investigate differences in the median scores for the perceived importance between risk factors. The proportion of total variance was assessed as intra-class correlation coefficients (ICC) with non-parametric repeated measures ANOVA models as in Kuster et al. . The outThe process to obtain the final risk values for each hunting ground follows several steps . The iniAn additional questionnaire, Likert type items, was developed and addressed to the hunting ground managers via telephone surveys (Kosovo) or within the general survey (Montenegro and Serbia) to assess the feasibility of different mitigation measures on the hunting grounds. For each selected risk factor, a question was formulated to assess the feasibility of implementing a mitigation measure in a range from 1 to 6 . Only risk factors with a mean score higher than 3.5 were considered for the feasibility assessment.A total of 258 hunting grounds were surveyed. In Kosovo, a consultant and staff member of the Food and Veterinary Agency surveyed 18 hunting grounds  between October 2020 and April 2021. In Montenegro, the Hunting Association of Montenegro surveyed 35 hunting grounds  between September and October 2021. In Serbia, the Ministry of Agriculture, Forestry and Water Management surveyed 205 hunting grounds  between July 2021 and January 2022.High number of visitors in the hunting ground” and “Absence of disinfection point for every visitor”, were not included into the risk score, because it was not possible to collect data on the number of visitors of each hunting ground due to privacy reasons and the presence of a disinfection point is not usual in the study area.From a questionnaire with more than 300 questions, 62 were selected because of their importance to assess the Risk of ASF Introduction, the Risk of ASF Spread, and the ASF Detection Capability. These questions contribute, in varying proportions, to a total of 37 risk factors, which were subjected to an EKE . Out of A total of 136 experts were referred along the snowball procedures. The minimum cut-off value  to include an expert in the elicitation was three. This led to the selection of 33 experts, of which 24 answered the elicitation (answer rate of 70%). For incomplete questionnaires, a reminder was sent to avoid missing values. The experts were mainly veterinarians (15), categorized as epidemiologists (5), animal health officers (2), wildlife managers (2), and not specified (6). The remaining nine experts were wildlife biologists. The experts were based in the following countries: Spain (7), Germany (4), Italy (3), Czech Republic (2), France (2), Belgium, Bulgaria, Latvia, Lithuania, Poland and Sweden (1).The results of the network analysis study conducted to understand the level of saturation reached is presented in p-value < 0.01).The reliability (degree of correlation and agreement between measurements) was calculated for the Risk of ASF Introduction (624 measurements), Risk of ASF Spread (552) and ASF Detection Capability (312) looking into two factors: (1) The two-way random effect model chosen because of the generalization of the results to any expert who possesses the same characteristics as the selected one in each reliability study; and (2) The absolute agreement calculation used to understand the extent to which different experts assigned the same score to the same risk factor  , followed by “absence of disinfection barriers”, “absence of transport or storage space used only for wild boar meat to avoid cross contamination”, “movement of wild boar” and “wild boar being transient”, which were highly correlated (r > 0.8). “Low proportion of fenced area” had a medium correlation (r > 0.5).Positive significant correlations among EKE scores were found only between the scores of Risk of ASF Introduction and that of Risk of ASF Spread. The final scores for each risk and each country or territory are depicted in Additionally, there was no significant difference between the Overall ASF Risk scores of hunting grounds categorized by Serbia as “infected” and non-infected hunting grounds . This analysis was just conducted for the Serbian hunting grounds since it was the only ASF-affected country within the study area.p-value < 0.05) and there is good agreement between all of the permutation tests performed  when applying a nonparametric comparison of multivariate samples as reported in Burchett et al. [Results from the Kruskal–Wallis test described no statistically significant difference between the feasibility scores for each question. Output of the ordered logistic regression showed that the infectious status has a highly significant effect on the scores .Regarding specific outcomes by country or territory, in Kosovo, movement of wild boar and sharing personnel were not included in the analysis because it was already enforced by law and the answers were all 6s . Additionally, adopting leak-proof bags to transport carcasses or offal was considered to be very difficult by 81.2% of the respondents. Having a disposal plan in case of an ASF outbreak was considered possible with little effort by 68.8%. Cleaning and disinfecting vehicles before they leave the hunting ground and avoiding kitchen waste or swill for feeding was considered difficult by 65% of the hunting ground managers.In Serbia, decreasing wild boar density through increased hunting pressure and avoiding supplementary feeding was considered possible with little effort by 60% of the hunting ground managers. Personal disinfection after dressing wild boar and avoiding sharing vehicles and personnel between the hunting grounds was considered difficult by half. Conversely, avoiding kitchen waste and other sources of animal protein to feed wild boar was considered possible with little effort by 70%.Hunters in Montenegro appeared less willing to cooperate in terms of implementing sanitary measures and changing their general behavior. Forbid driven hunts, not allowing visitors to bring meat into the hunting ground, and forbid pig workers or pig owners to hunt were considered measures impossible to implement by more than 80% of the hunters. Decreasing the density of the wild boar population and avoiding the use of kitchen waste or other protein to feed the wild boar was considered very difficult by the 83% of the hunters.The control and eradication of ASF in wild boar is and will likely remain a key component of the overall ASF control strategy in Europe, as well as in other parts of the world where wild boar or feral pigs are present, whether naturally or introduced. Until there is a commercially available vaccine for wild boar, close coordination and collaboration with the hunting sector and wildlife authorities remains the main strategy to limit the spread of the disease. A better understanding of how hunting grounds are managed and their biosecurity level will allow us to identify the strengths and gaps of the ASF management in wild boar populations and to tailor the mitigation measures that could reduce the risk. This is the purpose of the tool presented in this paper.The tool was used to assess the hunting grounds in Kosovo, Serbia and Montenegro. Our study found that, currently, the hunting grounds within the study region were at high risk of ASF, specifically the risks of ASF introduction and spread, and the risk that ASF will not be detected. Kosovo had the highest risks overall, with Serbia scoring best. The latter can be partially attributed to the fact that Serbia is already an ASF-infected country and, therefore, a series of mitigation measures have already been implemented. Surprisingly, no significant difference was found between the risk scores in ASF-infected and ASF-free hunting grounds in Serbia, perhaps showing that measures were implemented across the whole country.The assessment allowed us to identify the most common gaps across the study region, but also specific ones. In Serbia, both active and passive surveillance for ASF in wild boar are in place. The number of found dead wild boar has increased when comparing the results of 2021 and 2022; however, the ASF-affected hunting grounds contribute most of the found wild boar and samples submitted, while unaffected areas have a low submission rate. Montenegro also relies on passive surveillance, but the overall number of found dead wild boar per year is very low compared to the wild boar population of the country. In Kosovo, at the time of the study, there was no systematic effort to detect the disease in wild boar.On the spot evisceration of hunted wild boar is still widely practiced. In the case of Serbia, more than half of the hunting grounds surveyed have a temporary game meat storage to store meat until the PCR test results arrive. In Montenegro and Kosovo, none of the hunting grounds have game meat storage facilities. Only in Serbia is disinfection widely used to clean and disinfect facilities. The majority of hunters regularly disinfect their hands, clothing, footwear and equipment after the manipulation or handling of offal or dead animals .Supplementary feeding of wild boar is still a general practice in ASF-free hunting grounds. Additionally, there is no increased hunting pressure nor selective hunting of adult or subadult females to decrease the wild boar population.Based on the key findings and the feasibility study, a thorough written report with recommendations and maps was provided to each country.identify the weakest hunting grounds .categorize the hunting grounds based on their Overall ASF Risk score.pinpoint where the ASF surveillance in wild boar is weakest, i.e., where the uncertainty of freedom of disease is the highest.identify the easiest or cheapest  mitigation measures to decrease the ASF risk, whether at individual hunting grounds or the whole country.compare the level of hunting biosecurity between countries or regions.monitor the change of risk over time, by repeating the surveys and analyses.guide decision making at hunting grounds during outbreaks, by prioritizing actions not just because of proximity, but also at those hunting grounds with high-risk scores.The tool allows users to visualize the different ASF risks of hunting grounds, whether as numerical values or maps, at sub-national, national and regional levels. The different maps  can be used to guide policy makers by highlighting which aspects of hunting biosecurity and management, or which geographical areas should be prioritized:Implementing the surveys is labor-intensive. When there are many hunting grounds, data collection can take a long time. However, data collection should be completed in the shortest possible time, especially if ASF is already present in the country or region. When a hunting ground is affected with ASF, the relevant competent authorities will likely implement measures, which will change the risk scores.The tool was designed to be implemented in certain hunting management systems, more specifically, in Eastern Bloc countries. Therefore, if planning to use the tool in other countries with different systems, e.g., in Western Europe, certain modifications and adaptations will be necessary. Furthermore, such adaptations might make it impossible to compare the results with other countries.The risk factors identified and scored during the EKE are mostly generic and could be extrapolated to other geographical regions. However, they were selected with European settings in mind and had a high degree of accordance with the risk factors found by de la Torre et al. . Some riThis tool does not directly consider the ASF status . However, it is already reflected in the type and stringency of the measures implemented. This could be one of the reasons why Serbia (the only infected country) scored better, i.e., because they are taking more and stricter measures.Finally, while the questions in the hunting ground survey are objective, the feasibility study is subject to the personal views of the hunting ground managers interviewed. While there could be a conflict of interest when filling in the survey, the fact that the results are in line with expectations  suggests that the hunting ground managers were truthful when answering and critical of the gaps and limitations of their hunting grounds.Future work on the tool will aim to assess additional countries. A guideline will be developed to provide instructions for each step of the workflow together with various templates for key steps. Work to improve the tool will continue to enhance the user experience. First, to incorporate internal logical checks within the electronic questionnaire to verify the consistency of answers given and to highlight errors. Second, to automate calculations so that risk scores become immediately available as soon as the surveys are filled in. The third and most ambitious option is to develop a web-based interface so that data providers can select their preferred language, have immediate access to the questionnaire and obtain their risk scores immediately. If hunting ground shape files are available, the scores could also be immediately visualized.


Control of infectious diseases requires the handling of infectious materials by both clinical and public health laboratories with exposure risks for laboratory personnel and environment. A comprehensive tool for assessing the capacity to manage these risks could enable the development of action plans for mitigation. Under the framework of the Global Health Security Agenda action package for biosafety and biosecurity, the authors developed a tool dedicated to assessing laboratory biosafety and biosecurity. The Biosafety and Biosecurity Laboratory Assessment Tool (BSS LAT) assesses the status of all laboratory biosafety core requirements across 10 different modules. It consists of a standardized spreadsheet-based tool that provides automatic scoring. It is designed to support national, regional, and global efforts to strengthen biosafety in clinical, public health, and veterinary laboratories. The BSS LAT was first used in Burkina Faso in collaboration with the African Society for Laboratory Medicine and the US Centers for Disease Control and Prevention to support the country in strengthening their biorisk management system. Since then, it has been successfully used in other countries , various settings , and translated into several languages . The BSS LAT is a multipurpose tool that assists with standardization of biosafety and biosecurity requirements for all laboratories working with infectious materials, serves as a self-assessment guide for laboratories to develop improvement plans and reinforce capacities, and serves as a training guide for individual laboratories and networks or at the national level. The BSS LAT can also be used as a monitoring tool for the assessment of biosafety and biosecurity across all laboratories working with infectious materials at the national, regional, and global levels. To support countries to fulfill IHR requirements, the Global Health Security Agenda (GHSA) was established in 2014, with a focus on the threats posed by infectious disease. The GHSA is a partnership of more than 70 countries and several international organizations, nongovernmental organizations, and private sector companies jointly working against infectious diseases.2 It leverages this multisectoral partnership to build and improve country capacity and leadership in the prevention and early detection of, and effective response to, infectious disease threats. The GHSA is composed of 11 action packages, including 1 on biosafety and biosecurity that is aimed at reducing the capability of dangerous pathogens to spread rapidly, within and across borders.3The World Health Organization (WHO) International Health Regulations 2005 (IHR)4-6 These risks continue to be magnified by globalization and by the continuous emergence or reemergence of zoonotic diseases. All infectious disease laboratories by the nature of their work deal with materials that, if inappropriately handled or improperly contained or stored, can pose serious concerns to health, including a public health event of international concern.7Laboratory biosafety and biosecurity is of heightened interest due to concerns about accidental exposure to biological materials, deliberate misuse of biological materials, and emerging and reemerging biological risks.8Despite recent advancements in disease detection capacity globally, the design and implementation of associated laboratory safety and biosafety programs lags and is inconsistent due to a variety of factors including differences in national and local infrastructures, available funding and priorities, regulatory frameworks, and accessibility to expertise, training, and equipment resources.Laboratory Biosafety Manual9; the Biorisk Assessment Model developed by Sandia National Laboratories10; the Danish biosecurity book, An Efficient and Practical Approach to Biosecurity11; the safety module of the Food and Agriculture Organization's Laboratory Mapping Tool8; the Biosecurity Self-Scan Toolkit;12 and the Biosecurity Vulnerability Scan.13In line with the IHR and the GHSA initiative, worldwide laboratory capacities are expanding, which calls for concrete actions to improve laboratory biosafety and biosecurity practices to protect workers and the community. Biosafety and biosecurity have been elevated globally as a major concern, yet few action-oriented and practical tools for assessment and implementation exist. Different biorisk assessment instruments or guidelines to establish biosafety and biosecurity initiatives are available, such as the WHO 14 but it was only field tested in and adapted for Indonesia, thus limiting its applicability to other settings.Interesting initiatives have also taken place but with limited scope. For example, the University of Indonesia developed a checklist tool for biorisk management,Although different instruments and guidance are available to assess biosafety and biosecurity programs within institutions or to identify biosecurity gaps at the national level, to our knowledge, there is currently no publicly available biosafety checklist for laboratory assessments. To this end, we developed a prototype assessment tool, based on Microsoft Excel, as part of the GHSA initiative to reinforce capacity and strengthen the laboratory system in Burkina Faso. In this article, we describe the tool, including how it is organized, its process of development and field testing, how to obtain it, as well as our experience using it and the impact it can have.The Biosafety and Biosecurity Laboratory Assessment Tool (BSS LAT) is based on a Microsoft Excel worksheet and consists of a standardized questionnaire. Using an Excel spreadsheet maintains an open and unlocked system, which can be modified; relies on a software system that is widely known and understood; is widely available commercially or has free counterparts that are widely available ; and facilitates the use and export of data into other formats, reports, or software.The BSS LAT is divided into 8 nonnumbered and 10 numbered modules and has 538 questions, with an additional 108 questions for the biosafety level (BSL) 3-specific laboratory module. The tool begins with nonnumbered tabs, including a cover page, a list of abbreviations, and a general tab, which is used to gather basic information such as the name of the facility, information about assessors, contact details about the respondents, activities being performed in the laboratory as well as the associated workloads, GPS coordinates for geographic information system display of the results, and the laboratory BSL. Numbered topic-specific tabs follow, each including related indicators and questions .15-17 (1) premises and workflow; (2) staff management and training; (3) good laboratory practices; (4) cleaning, disinfecting, sterilization, and waste management; (5) emergencies; (6) risk management; (7) documentation and regulations; (8) biosecurity; (9) other risks; and (10) BSL-3 laboratories. Each module contains various indicators and each indicator consists of several questions with closed answers (Table).The numbered BSS LAT modules were identified through the main biosafety and biosecurity topics commonly described in international references:Each question and indicator can be completed either by using the closed drop-down menu or by filling in an open comment cell to provide more information about the specific question or indicator . The droQuestions – for each question, the score is calculated as either 0% if the answer is unsatisfactory  or 100% if the answer is satisfactory Indicators – for each indicator, the score is calculated as the average of all related question scores/component indicatorModules – for each module, the score is calculated as the average of all related indicator scores/component moduleLaboratory – an overall assessment score for the laboratory  is calculated as the average of all module scoresScoring is based on a percentage of a maximum score of 100%. The results of the checklist are presented in each module and in the summary tab using a color-coded system of red (0% to 50%), orange (50% to 80%), and green (80% to 100%). The tool includes summary pages, organized by indicator and module, with a graphic depiction and data export to a database or GIS mapping software or other software .Although the sequential tabs ideally should be completed chronologically from left to right, it is not required. The cells to be completed are indicated with gray shading as a visual clue to show users where answers are needed. Users can save their session in the tool at any time and can resume later to facilitate the ease of the assessment and reporting process. It ends with a conclusion page where the assessor can enter findings and recommendations.The BSS LAT is multilingual—currently available in English, French, Russian, and Armenian—and users can select the desired language from a drop-down menu. All language versions are contained in the same file, within the language tab . All verThe BSS LAT was developed to be as intuitive, user-friendly, and flexible as possible. The tool can be completed in 1 or more sessions . All responses that lead to the calculation of an indicator score are entered using drop-down menus with a data validation mechanism to prevent mistakes. Although most of the questions in the tool are closed, each question has a comment field where assessors can add more details or specifics. The questions from the BSS LAT were formulated to limit subjectivity on the part of the assessor.In addition, it is generally recommended that the assessor select a negative answer to questions if the element from the question is not fully in place, established, mastered, followed by all, or not fully completed  does not have their personnel file available).The recommended laboratory assessment process is as follows: (1) a courtesy visit to the laboratory management, (2) an explanation of the assessment process , (3) a detailed laboratory visit following sample flow , and (4) completion of the tool during a plenary session. This can be most easily accomplished by presenting the tool  to relevant, interested, and available staff.The assessor should fill in all cells that have gray shading. Upon completion, it is recommended to present the immediate results to the assessed team and/or to the top management, and provide facilitated comments on the results. The entire assessment process for a laboratory is estimated to be a full work day. In our experience, however, the assessor must be flexible. No specific preparation is expected by the laboratory staff before the assessment. However, full availability is expected on the day of the evaluation from the managers and at least 1 person representing the technical staff. Depending on the size of the laboratory, the workload, the number of staff, the interest from assessed laboratory's staff, and the assessor's experience with the BSS LAT, the assessment process can be performed quicker or may take several days, especially if a plan of action is subsequently developed jointly by the assessment team and laboratory staff. As far as possible, we recommend approaching this exercise not as a simple assessment performed by an external party, but as an opportunity to sensitize staff to biosafety and biosecurity concepts, teach and train people on biosafety, provide supplementary documentation , and answer questions on biosafety and biosecurity and in particular, in the current setting of the laboratory or the network.The conclusion module/tab can be filled later by the assessor, along with recommendations enacted to the laboratory. The final BSS LAT, including conclusion and recommendations, should be provided to the assessed laboratory as soon as possible, for them to implement preventive and corrective actions. As much as possible, the assessor should organize recommendations in order by priority .Until recently, biosafety and biosecurity were not among the biggest concerns in laboratory science, especially in resource-limited countries. The BSS LAT was developed to gather and summarize the important aspects of biosafety and biosecurity in a laboratory setting, which have been unevenly treated depending on the source of the guidance or standard, as no official global standard currently exists.Laboratory Biosafety Manual9; the WHO Biorisk Management: Laboratory Biosecurity Guidance16; the World Organisation for Animal Health Manual of Diagnostic Tests and Vaccines for Terrestrial Animals17; the US Centers for Disease Control and Prevention (CDC) and the National Institutes of Health Biosafety in Microbiological and Biomedical Laboratories15; ISO 15190:2003, which pertains to medical laboratory safe practices18; the European Committee for Standardization (CEN) Workshop Agreement (CWA) 15793 laboratory biorisk management standard supplemented by CWA 1639319; the National Institutes of Health Design Requirements Manual for biomedical laboratories and animal research facilities20; the National Institutes of Health inspection checklist for BSL-3 laboratories21; and our knowledge and experience from the field and from various general assessments performed worldwide. At the time of the tool's development, the following guidance and standards were not in existence or published, but were considered during the adaptation of consecutive versions of the tool: ISO 45001, for occupational health and safety22; the ISO 35001, for laboratory biorisk management23; and the fourth edition of the WHO Laboratory Biosafety Manual.24 Several standards have since been updated, such as ISO 15190:2003, which has been replaced by ISO15190:2020.18The BSS LAT was built using the available international references and standards including the WHO The BSS LAT was originally developed by Integrated Quality Laboratory Services in 2017 to perform assessments in Burkina Faso for the African Society for Laboratory Medicine as part of CDC-led efforts under the GHSA. The tool has since been field tested in an additional 7 countries, revised, and supplemented with additional questions and indicators. Before each use, the tool was refined through the removal of redundant elements, reformulation of questions (to increase precision and improve wording), correction of calculations, reorganization of some questions and indicators, development of new modules , translation of the tool into several languages , and improvements to the layout.Field testing occurred in Ghana in 2017 (which led to the addition of the English version of the tool and to field testing in a West African English-speaking country); in Armenia in 2018 ; in Burundi, Cameroon, and Guinea in 2019 ; in Kazakhstan in 2019 ; and in Liberia in 2019 . Importantly, all of the countries and laboratories were at different levels of initial biosafety implementation. Over the course of field testing, the BSS LAT benefited from being used by various experts and evaluators from different backgrounds and with different specializations, whose input we used to refine the tool by incorporating specific pathogens or scenarios into the formulation of questions. We are confident that this comprehensive field testing enabled us to deeply and extensively test the BSS LAT under broad and various conditions.Through this iterative process, the BSS LAT has reached version 9.0 and is highly comprehensive, interactive, and robust. It provides a high level of confidence in its suitability and adaptability to a broad One Health spectrum of laboratories in different countries and continents.https://www.iqls.net/docs/IQLS_Biosafety_LAT_v9_Oct2019_EN_FR_RU.zip. It consists of the open Excel tool, a printable PDF version, and a brief user guide.The most recent version of the BSS LAT is available as a zipped file: In our experience, all of the assessments we performed during the field testing period demonstrated that the tool can be used to introduce biosafety and biosecurity key concepts directly in the laboratory and among staff. Using this tool provides an opportunity to sensitize staff on biosafety and biosecurity issues and to answer practical questions. Results from the assessment provide direct onsite observations and recommendations that enable immediate preventive and corrective actions.Additionally, our numerous BSS LAT tests demonstrated that the tool was effective in identifying the main gaps in a laboratory (or in a group of laboratories and/or at country level), which was a key factor in preparing a suitable plan of action to strengthen capacities and better target training needs.25 The assessment process was a decisive step in the selection of activities that were more likely to improve the laboratory system in Burkina Faso.If mastered at a high level, this tool could be applied on a regular basis to (1) monitor the biosafety and biosecurity level of laboratories across regions, a country, or countries; (2) design interventions; and (3) measure their impact. The detailed experience from Burkina Faso and how the BSS LAT was used in a global approach to strengthen biosafety and biosecurity capacities at national and regional levels is detailed in a joint publication.In the countries where we administered the BSS LAT a second time, after initial assessment and training, the tool provided a convenient measure of the impact of implemented activities and helped to quantify improvements in biosafety and biosecurity.It is important to mention that although the BSS LAT has been found to be beneficial to laboratories and staff members, it remains a tool; it cannot replace the commitment by leadership to strengthen biosafety and biosecurity or to fund gaps and needs.25 The BSS LAT was designed so that it can be used in any infectious disease laboratory at national or regional levels, and can be used by either external assessors or by laboratories for self-assessment.The BSS LAT is simple to use and multilingual . It relies on widely available software and is shared in an open format to facilitate adaptation . It has been successfully tested in 8 countries to date, at the central and regional levels, in medical and veterinary laboratories, and in a specialized pathogen-specific laboratory setting. The BSS LAT has been used for various aims in different settings and at different levels, which (1) contributed to minor enhancements and simplifications to make it both comprehensive and straightforward and (2) clearly demonstrated important outcomes and benefits for strengthening biosafety and biosecurity capacities—the most detailed example of which is the experience from Burkina Faso.Performing a biosafety and safety assessment using the BSS LAT has numerous benefits. It has a simple but effective checklist format and a standardized assessment process  that prevents oversights or bias from assessors. The BSS LAT facilitates a detailed and complete assessment that can be used to guide sustainable improvements as envisioned under IHR and the GHSA. It also provides laboratories with an objective assessment, as the results are automatically calculated and summarized in a table by topic, module, and/or graphic depictions. The tool can also be used for monitoring, either by the laboratory that was assessed  or by the assessor . In addition to the practical assessment dimension of the tool, the BSS LAT can also be used to provide guidance and to sensitize laboratory staff to biosafety concepts, knowledge, and practices to strengthen biosafety awareness and practices that are increasingly critical globally.In addition, the BSS LAT becomes a live monitoring tool after initial assessment to be used by laboratory management and staff to rapidly identify and prioritize what remains to be done and to document the implementation of corrective actions.The BSS LAT can provide a strong foundation for countries or laboratory networks that would like to enhance or develop their biosafety capabilities or to develop national biosafety standards. For example, Kazakhstan used the BSS LAT to develop a national biosafety and safety checklist. In Burkina Faso, the tool was used to prioritize biosafety and biosecurity improvements across the national laboratory network. The BSS LAT is also in the process of being adapted for use in South America based on experiences from their COVID-19 response. These examples show the versatility of the tool and its adaptability in diverse settings.The BSS LAT can be improved further and the authors welcome any suggestions. Any organization, national body, or bureau wishing to use the BSS LAT in a different language should contact the authors so they can support the translation process and include the new version in the tool's distribution package.


With the continuous development of the times, music education in primary and secondary schools is constantly innovating in terms of teaching concepts, teaching methods, and implementation methods. The reform of basic music education has aroused the reflection of music teacher education in colleges and universities, and the talent training model of music teachers has become a hot issue that has been widely concerned in the new era. To explore the educational significance and influencing factors of entrepreneurship education in college music education and examine the mediating role of self-efficacy and gender adjustment in entrepreneurial education, based on the analysis of music education and entrepreneurial talent training in colleges and universities, a questionnaire survey, statistics, and data processing were adopted in this work. In this work, a path model was established based on the mediating effect and the moderating effect, and the equation model was tested. The results show that music education has a positive correlation with entrepreneurial self-efficacy and a negative correlation with entrepreneurial intention, which has not been proved to have a certain effect on entrepreneurial intention. Entrepreneurial self-efficacy has a positive correlation with entrepreneurial intention, and the mediating effect between music professional education and entrepreneurial intention has also been proved. Since there are gender differences and certain stereotypes that cannot be ignored in music education learning, gender adjustment also has a certain influence on entrepreneurial self-efficacy based on music professional education, thereby having a moderating effect on entrepreneurial intentions. Entrepreneurship education can improve the comprehensive competitiveness of students. As a result, entrepreneurship education can improve the innovation and entrepreneurship education model and the music education system in colleges and universities by combining with the relationship between entrepreneurial efficacy and intention, and it contributes to the overall cultivation of talent in colleges and universities. With the development of the concept of quality-oriented education, the demand for comprehensive talent in college education is increasing. While constantly improving their professional knowledge and technical level, students should also pay attention to the ability training in innovation, entrepreneurship, and aesthetic education to improve their comprehensive quality and competitiveness. Entrepreneurship education is one of the important manifestations of educational reform and innovation in colleges and universities. At present, innovation and entrepreneurship education have a clear policy promulgation and task objectives. There are many shortcomings in traditional college music education, and the lack of innovation in the education system makes it difficult for students to improve their innovation ability . The exi2020 College Student Employment Report, only 2.5% of 2019 graduates started their own businesses after graduation compared with 2.9 percent in 2017 and 2.7 percent in 2018. Research has shown that whether graduates are willing to carry out innovation and entrepreneurship mainly depends on their views on entrepreneurship. When personal traits are enhanced through comprehensive learning, the psychology of autonomy will affect the entrepreneurial intention of college students. Such psychology will subtly change the way college students think and behave to effectively compensate for the lack of entrepreneurial talent among college students. Music education is regarded as an important means and way to cultivate and implement all-round talent reserves in international research. In this kind of education, students will not only emphasize the learning of skill-based content but also pay attention to music itself. To cultivate students’ overall humanistic quality, Harvard University takes up a large proportion of the humanities, among which there are 45 “literature and art” courses and 7 music courses  24.0, and AMOS (Advanced Mortar System) 22.0 was used for statistical analysis of the entered data  were obtained. The results of the deviation calibration are shown in In AMOS 22.0, a total of 300 samples were obtained by random repeated sampling and estimated within a 90% confidence interval. Point estimates, SE (standard error), and P  for the publication of any potentially identifiable images or data included in this article.The author confirms being the sole contributor of this work and has approved it for publication.The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


P < 0.01).Due to the continuous progress of social economy, medical and health technology and the development of disciplines have shown a trend of rapid development. In the current medical environment, quality nursing services are constantly promoted. Nursing staff are dedicated to their work to the best of their ability. Meanwhile, they should be rewarded with corresponding happiness and joy in their work. This study starts from the perspective of nursing management and psychology. On this basis, it investigates the occupational identity and work stress status of nursing staff. At the same time, the data are analyzed, and the relationship between occupational identity and work pressure is analyzed. This article provides a certain theoretical basis and support for the decision-making of relevant nursing managers, and also makes efforts to improve the professional identity and work happiness of nursing staff. In this study, which surveyed 596 rehabilitation nurses, the nurses' total occupational stress score was 74.52, with an average score of 2.12 points. The overall score for professional identity was 102.00, with an average score of 3.40 points. This belonged to the medium level. It showed that the occupational pressure of nurses should be paid attention to by relevant managers. Two of the five dimensions with the highest scores were occupational social support and occupational self-reflection. A negative correlation was found between occupational stress and its dimensions and occupational identity and its dimensions ( Nursing staff are on the clinical front line of caring for patients. Nursing staff have high occupational risks, high workload, fierce social competition, and fast-paced life, witnessing the pain of patients in their daily work, which has higher requirements on their physical, emotional, and spiritual aspects. Workplace stress is a globally recognized risk factor for employee health and safety. Nursing staff's repeated exposure to unpredictable challenges in nursing practice may cause them to experience symptoms of anxiety, exhaustion and stress, and excessive work stress. It not only affects their physical and mental health and aggravates work fatigue, but also affects the quality of work, which is not conducive to patient safety. In terms of teaching, it can provide theoretical support for the optimization of nursing professional personnel training programs for medical colleges and universities. In terms of medical treatment, it can provide a reference for managers to reduce the work pressure of nursing staff and strengthen the management of nursing deficiency. This study explores the root causes of nursing deficits from the perspective of work stress and understands the mechanism of occupational identity. This not only helps managers to formulate countermeasures to reduce the impact of nursing staff's work pressure on nursing deficiency and helps nursing managers to pay attention to the positive impact of professional identity, but also helps stabilize the nursing talent team and reduce nursing deficiency. It is hoped that through this study, the stress status of nursing staff can be better understood, and the relationship between work stress and occupational identity and nursing deficiency can be explored, thus attracting the attention of hospitals and medical colleges, and reducing the work pressure of nursing staff, so as to improve their professional identity and strengthen professional emotion as well as stabilize the nursing team. At the same time, the study of nursing deficiency in this study has certain practical significance for promoting the recovery of patients.Stress resilience is a trait and skill that caregivers can develop. Leng's research examined the current status and influencing factors of nursing staff's ability to cope with stress, as well as the work stress felt by nursing staff. Studies have found that nursing staff's ability to withstand stress is significantly related to age, working years, clinical grade, and education level . EmishawResearch by Frechette found that professional identity can improve nursing staff retention and quality of care. This study was conducted using an explanatory phenomenological design, with data collection through face-to-face interviews, photographs, participant observations, and document review . ParamedNursing workers are an indispensable strong force in the medical industry. With the aging of the Chinese population, the demand for nursing workers is increasing . In the As shown in Traditional machine learning algorithms usually have problems with relatively simple mathematical expressions, which cannot accurately describe the characteristics of features. Therefore, the neural network algorithm based on multilayer perceptron has received extensive attention from researchers . Neural As shown in As shown in Short-time Fourier transform is often unable to cope with various physiological signals with complex distribution, while wavelet transform is widely used in the analysis of nonstationary physiological signals due to its variable window length . For disThe essence of discrete wavelet transform is to divide the signal into a high-frequency details coefficient (cD) and a low-frequency approximation coefficient (cA) through high- and low-frequency filters, further decomposing the approximate components until the number of decomposition layers reaches the wavelet transform to the set number of layers.(1)The in-band energy of a certain layer is calculated as shown in the following formula based on Pascal's theorem:(2)For the frequency band energy ratio, the calculation is performed as follows:The frequency domain feature used in this article is the proportion of the frequency band energy of each layer in the total energy after wavelet transform, and its mathematical expression is as follows:D, D wants to identify as accurately as possible whether the input is from the generative network G or the real data, that is to maximize the expression, as shown in the following formula:For the discriminator G, G hopes to generate data that cannot be accurately distinguished as “real” by D through training. That is, through training, the objective function shown in the following formula can be minimized:For the generator G and D need to be trained separately to be optimal. Therefore, the parameter update formula based on gradient ascent for the discriminator D is shown in the following formula:The training of GAN is carried out in stages, because k times of training, the discriminator D is fixed, and the parameter update formula based on gradient descent is applied to the generator G, as shown in the following formula: After k is too large, the update of D will be too frequent, which will lead to serious gradient disappearance in the training of G.If the value of Therefore, after GAN was proposed, a large number of researchers optimized the native model of GAN. The optimized model has been applied to solve various problems that are difficult to solve by traditional neural networks. Among them, the design concepts of adversarial networks and discriminators have been deeply developed and improved. They have been used by some researchers to optimize interference information in recognition problems.Most existing decision tree algorithms focus on feature selection metrics or improved pruning algorithms. The number of relevant rules extracted by many relevant rule extraction algorithms is always surprisingly large without any contribution to the extraction result. In order to build new features through association rules, it is important to know which rules to use.In the approximate exact rule algorithm, a set of rules are generated and the previous rule elements are combined with new features and added to the original dataset.1 is shown as follows:The value of the new attribute ABRi feature to be evaluated is the root node of the decision tree. The information content of the root node is shown as follows: m represents the total number of records in the sample dataset and mj is the number of the jth value of the ranking attribute.First, the candidate ABRi attribute, the number of data records for = ABRi1 attribute is M1, as shown in the following formula: If the sample data are classified and evaluated by ABRABRi = 1, the number of records of category attribute B=bi is N2, as shown in the following formula:In the data record of attribute a = ABRi1 attribute has an unknown number of B-type attribute values of bi. The amount of information contained in this type of data is ignored here, since exact approximation algorithms are used to generate exact approximation rules. Therefore, the amount of information contained in the records of the dataset matching = ABRi1 is shown in the following formula: On the other hand, a record with In the decision tree algorithm C4.5, the test condition for feature selection in the decision tree model is the information gain rate. It represents the amount of categorical information required for a given data sample, as shown in the following formula:pi is the proportion of Ci in the sample, which can generally be calculated by Ci/d.where D) is an entropy concept when the value of attribute A is used as the basis for sample splitting, as shown in the following formula:Based on the information gain, the information gain rate is formulated. SplitInfoA .It can be seen from the schematic diagram of the network structure that two classifiers participate in training at the same time. Therefore, the loss function of the training process consists of three parts.In this article, the focal loss function is used in the three-category/two-category problem to solve the problem of class imbalance. The loss function of the pressure classification part is shown in the following formula:Considering that the number of samples of each person is roughly the same and does not require special processing for balancing, this article chooses the cross-entropy function as the identity classification function, and the calculation formula is shown in the following formula:Combining the above various loss functions, it is necessary to use different coefficients to make each loss function similar in magnitude to prevent the training process from being biased. Therefore, the overall loss function is shown in the following formula:This study used a cross-sectional study and convenience sampling method. The survey method was a questionnaire survey. There were two ways to conduct this survey. The first way was to distribute them uniformly to research subjects by trained investigators. After the investigator stated the research purpose, the research subjects participated voluntarily, filled in anonymously, and took it back on the spot. The whole process took about 30 minutes, and the valid questionnaire was returned after filling out. The second way was to distribute the online software to the research subjects by the person in charge, and valid questionnaires were collected after online submission. Before the questionnaire survey, a research group has been established, and the questionnaire survey was completed by the staff of the research group.On the basis of surveying the general data, firstly the occupational identity and work pressure were investigated, respectively, and the univariate analysis and multivariate analysis were completed, and then carry out the correlation analysis between occupational identity and work pressure. Univariate and multivariate analyses were performed. Then, the correlation analysis between occupational identity and job stress was carried out. Finally, the corresponding conclusions and results were drawn and analyzed. The pre-investigation has been completed in our hospital before the formal investigation, which ensured the accuracy and scientificity of the results.This study was sampled according to the inclusion and exclusion criteria. Before distributing the questionnaires, the hospital leaders were contacted. After obtaining their approval, the researchers then contacted the department head nurses on a case-by-case basis. After asking for their consent, the significance of the research, matters needed attention, etc. were explained to them. It was indicated that the personal name was not required to be written on the questionnaire, and the obtained data were only used as the information of this research, which would not be leaked so that the nursing staff could fill in the truth. After the questionnaires were distributed, the time when the questionnaires would be returned was agreed. During this period, the head of the nursing staff or the person in charge of the department needed to be communicated with from time to time. After the questionnaires were collected uniformly, the researchers repeatedly reviewed the completeness and logic of the questionnaires one by one, and then unified coding after eliminating invalid questionnaires. Data entry was performed using Exce12016. After recording, the accuracy of the entry was checked. Specifically, all variables entered were analyzed using SPSS 21.0 line frequency. If there are missing values and answering logic confusion, they should be supplemented and corrected in time. Finally, all data were checked against the original data.A total of 596 nursing staff were surveyed in this study. Among the departments, surgical nursing staff accounted for the largest proportion, accounting for 48.7% of the total number of nursing staff. The number of women was much higher than that of men, accounting for 97.3%. The age range was from 21 to 55 years, with the most nursing staff in the age group of 25 to 34 years, accounting for 58.7%. Some basic information is shown in As shown in Nursing staff work stress and dimension scores are shown in As shown in After analysis, the work stress score of nursing staff was reflected in different departments, gender, age, working hours per week, the number of hours delayed from getting off work every day, and the number of patients in charge. Figures As shown in Figures There were differences in job stress scores among nursing staff with different demographic characteristics. Nursing staff aged ≤24 years had lower work pressure than those of other age groups. The job title of nursing staff was less stressful than that of nurses and nurses in charge. The analysis showed that nursing staff of this age group had just entered the workplace, who were less affected by external factors and were more likely to self-regulate. Married caregivers in the survey were more stressed than unmarried ones. Caregivers with children were more stressed than those without children. It reflected that nursing staff were greatly influenced by family factors when they faced work pressure. Nursing staff who worked for 5–9 years and ≥10 years had higher stress than those who worked for 2–4 years. It might be because nursing staff with long working years often lost the freshness of daily work and were mostly responsible for department management, education, and scientific research. Nursing managers needed to be prompted to pay attention to their psychological state, provide emotional support, and reasonably allocate workload. The stress of nursing staff who worked >60 hours per week was higher than those who worked ≤40 hours, 41–50 hours, and 51–60 hours. The working pressure of the nursing staff who delayed leaving work for 0.1–0.5 h, 0.6–1 h, and >1 h per day was higher than that of the nursing staff who did not leave work late. Nursing staff were more likely to feel fatigued if they worked longer or the number of patients they were in charge of was larger. They worried about making mistakes in their nursing work, thereby increasing the psychological burden. Under-staffed caregivers were more stressful than fully staffed. The working pressure of nurses with an average or poor working environment in the department was higher than those with a good working environment. Nursing staff with a poor working environment were also more stressed than those with a normal working environment. It showed that the better the working environment of the department, the less the working pressure of the nursing staff, which reflected the importance of the staffing of hospital nursing staff and the working environment.The occupational identity and dimension scores of nursing staff are shown in As shown in Figures As shown in Figures This survey used occupational identity as a dependent variable. Single factors such as years of work, job title, marriage, and child scores were used as independent variables. Then, after performing multiple linear regression analysis, the multivariate analysis of factors affecting the occupational identity of nursing staff is shown in P < 0.05). Length of service (6–10 years), job title (nursing staff), marriage (married), and children (one child) are factors of occupational identity. The results of multiple linear regression analysis showed that working years, professional title, marriage, and children were the main factors affecting nurses' professional identity (P < 0.05).As shown in The relationship between work stress and professional identity of nursing staff is shown in P < 0.01). In addition, occupational social skills scored the lowest in this study. This may be related to the scheduling of nursing staff. Nursing staff are busy with their daily work, with less time at their disposal, and have less social and recreational activities. In addition to family members, the people who have the most contact with nursing staff are patients and their families. At present, the relationship between doctors and patients and nurses is tense. Nursing staff are cautious in their work and pay less attention to social skills than nursing knowledge and skills.From the results in There were differences in the occupational identity scores of nursing staff with different demographic characteristics. Both obstetrics and ICU nursing staff had higher occupational identity scores than medical nursing staff. This is slightly different from previous studies possibly because of a different sample source. Nurses aged 35–44 years scored lower than those aged ≤24 and ≥ 45 years. It might be because the subject in this survey was a tertiary first-class general hospital, and the nursing staff of this age group had to not only face the pressure of family, but also face the pressure of hospital assessment and self-development. If they do not handle it properly, they are prone to burnout, leading to a low level of professional identity. Nurses who did not leave work late each day scored higher than those who were late. Nursing staff with ≤6 and 7–8 patients who were often responsible for the number of patients scored higher than those with >12 patients. Nursing staff who left work late every day and were responsible for a large number of patients were prone to burnout in nursing work and experience less sense of value in their work.In this study, the total score of nursing staff's work stress was 74.52 points, and the average score was 2.12 points, which belonged to the middle level. It showed that the work pressure of nursing staff needs to be paid attention to by relevant managers. Five dimensions scored higher. The time allocation and workload dimensions were 2.41 points, and the nursing and work dimensions were 2.28 points. Two of the highest scores on these five dimensions were professional social support and professional self-reflection, which might be due to patients, their families, and colleagues being more supportive of the work of caregivers. The support of patients, families, and colleagues played a pivotal role in the professional identity of nursing staff. This support not only enhances the well-being and values of caregivers, but also makes them more cherished and engaged in care work, effectively relieving their work stress, which reduces burnout and encourages caregivers to remain relaxed and positive at work. The research showed that nursing staff had moderate levels of job stress and a moderate sense of professional identity. The higher the occupational stress of nursing staff is, the lower the occupational identity level of nursing staff will be. This study only conducted a cross-sectional survey of nurses, and did not conduct qualitative research and intervention research, which can be carried out in the future to make the results and conclusions more convincing.