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In recent times, video inpainting techniques have intended to fill the missing areas or gaps in a video by utilizing known pixels. The variety in brightness or difference of the patches causes the state-of-the-art video inpainting techniques to exhibit high computation complexity and create seams in the target areas. To resolve these issues, this paper introduces a novel video inpainting technique that employs the Morphological Haar Wavelet Transform combined with the Krill Herd based Criminisi algorithm (MHWT-KHCA) to address the challenges of high computational demand and visible seam artifacts in current inpainting practices. The proposed MHWT-KHCA algorithm strategically reduces computation times and enhances the seamlessness of the inpainting process in videos. Through a series of experiments, the technique is validated against standard metrics such as peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM), where it demonstrates superior performance compared to existing methods. Additionally, the paper outlines potential real-world applications ranging from video restoration to real-time surveillance enhancement, highlighting the technique's versatility and effectiveness. Future research directions include optimizing the algorithm for diverse video formats and integrating machine learning models to advance its capabilities further. [ABSTRACT FROM AUTHOR]

The present research captured a series of aspects related to the global pork market, focusing, above all, on the 2015-2021 interval. The main indicators that had to be analysed are: worldwide pig herds, worldwide pork production, global pork consumption, worldwide imports and exports of pork. Regarding pork, it was found that it is part of the food consumption model for part of the world's population, because it presents several characteristics agreed by consumers. The statistical data that were presented and analyzed in the study were provided by the FAOSTAT website. In order to better capture the evolution of the worldwide pork market, numerous specialized materials were consulted. In 2021, Asia achieved 52.4% of the production share of pig meat with the bone, fresh or chilled obtained worldwide. The top three pork consuming countries in 2021 were: Korea (31.6 kg/inhabitant); Vietnam (25.9 kg/inhabitant) and Chile (25.0 kg/inhabitant). [ABSTRACT FROM AUTHOR]

Lumpy skin disease (LSD) is a critical problem for cattle populations, affecting both individual cows and the entire herd. Given cattle's critical role in meeting human needs, effective management of this disease is essential to prevent significant losses. The study proposes a deep learning approach using the MobileNetV2 model and the RMSprop optimizer to address this challenge. Tests on a dataset of healthy and lumpy cattle images show an impressive accuracy of 95%, outperforming existing benchmarks by 4–10%. These results underline the potential of the proposed methodology to revolutionize the diagnosis and management of skin diseases in cattle farming. Researchers and graduate students are the audience for our paper. [ABSTRACT FROM AUTHOR]

Simple Summary: In recent years, the interest in virtual fencing systems for flexible animal enclosure management has increased. However, implementing such systems requires significant investment due to the need for individual collars, hindering large-scale adoption. This study examines the spatial distribution of a cow herd using GPS locations from the Nofence© system, aiming to minimize the number of collars required by identifying patterns in positions and ranks to derive a hierarchy. Contrary to expectations, no distinct pattern emerged, suggesting future studies should focus on individual interactions rather than viewing the herd as a single unit. Interest in virtual fencing has increased due to its flexibility for agriculture and rewilding. However, systems like Nofence© require large financial investments, and the need for individual collars complicates large-scale use. If cattle herds maintain cohesive groups around leading individuals, fewer collars could be used, thereby enhancing cost efficiency. This study investigates the pattern in spatial distribution in a herd of 17 Angus cows on Fanø in Denmark with GPS locations, using a Nofence© system. The aim of this paper is to determine how individuals position themselves in a herd, spatially, and identify a pattern in ranks. The method used in this study examines the distances between an individual to the rest of the herdmates using nearest neighbour and descriptive statistics. Contrary to expectations, this study did not reveal a distinct pattern in herd distribution. While some tendencies in spatial distribution patterns were observed, only a low concordance could be found ( W = 0.15 , p < 0.001 ), indicating great variability in the cattle's ranks. A cumulative curve of the ranks estimated over the entire periods, however, allowed a rough estimation of the hierarchy and allowed identification of the highest-ranked cows, making the use of a cumulative curve a possible solution to finding the high-ranked cows. This research underscores the complexity of cattle social structures and highlights the need for extended observation periods and alternative methodologies to enhance the cost-effectiveness and scalability of virtual fencing in agricultural and rewilding contexts. [ABSTRACT FROM AUTHOR]

In this paper, an intelligent stochastic model is recommended for the optimization of a hybrid system that encompasses wind energy sources, battery storage, combined heat and power generation, and thermal energy storage (Wind/Battery/CHP/TES), with the inclusion of electric and thermal storages through the cloud theory model. The framework aims to minimize the costs of planning, such as construction, maintenance, operation, and environmental pollution costs, to determine the best configuration of the resources and storage units to ensure efficient electricity and heat supply simultaneously. A novel meta-heuristic optimization algorithm named improved horse herd optimizer (IHHO) is applied to find the decision variables. Rosenbrock's direct rotational technique is applied to the conventional horse herd optimizer (HHO) to improve the algorithm's performance against premature convergence in the optimization due to the complexity of the problem, and its capability is evaluated with particle swarm optimization (PSO) and manta ray foraging optimization (MRFO) methods. Also, the cloud theory-based stochastic model is recommended for solving problems with uncertainties of system generation and demand. The obtained results are evaluated in three simulation scenarios including (1) Wind/Battery, (2) Wind/Battery/CHP, and (3) Wind/Battery/CHP/TES systems to implement the proposed methodology and evaluate its effectiveness. The results show that scenario 3 is the best configuration to meet electrical and thermal loads, with the lowest planning cost (12.98% less than scenario 1). Also, the superiority of the IHHO is proven with more accurate answers and higher convergence rates in contrast to the conventional HHO, PSO, and MRFO. Moreover, the results show that when considering the cloud theory-based stochastic model, the costs of annual planning are increased for scenarios 1 to 3 by 4.00%, 4.20%, and 3.96%, respectively, compared to the deterministic model. [ABSTRACT FROM AUTHOR]

In this paper, focusing on individualistic generalist predators and prey living in herds which coexist in a common area, we propose a generalization of a previous model, namely, a two-population system that accounts for the prey response to predator attacks. In particular, we suggest a new prey-predator interaction term with a denominator of the Beddington-DeAngelis form and a function in the numerator that behaves as N for small values of N, and as N α for large values of N, where N denotes the number of prey. We can take the savanna biome as a reference example, concentrating on large herbivores inhabiting it and some predators that feed on them. Only two conditionally stable equilibrium points have emerged from the model analysis: the predator-only equilibrium and the coexistence one. Transcritical bifurcations from the former to the latter type of equilibrium, as well as saddle-node bifurcations of the coexistence equilibrium have been identified numerically by using MATLAB. In addition, the model was found to exhibit bistability. Bistability is studied by using the MATLAB toolbox bSTAB, paying particular attention to the basin stability values. Comparison of coexistence equilibria with other prey-predator models in the literature essentially shows that, in this case, prey thrive in greater numbers and predators in smaller numbers. The population changes due to parameter variations were found to be significantly less pronounced. [ABSTRACT FROM AUTHOR]

The most common life-threatening disease, acute lymphoblastic leukemia (ALL), can be lethal within a few weeks if untreated. The early detection and analysis of leukemia is a key dilemma in the field of disease diagnosis, and the methods available for the classification process are time-consuming. To overcome the issues, this paper develops a robust classification technique named Horse Herd Whale Optimization-enabled Deep Neuro-Fuzzy Network (HHWO-enabled DNFN method) for ALL classification and severity analysis using the MapReduce framework. The input image is first preprocessed and segmented, and the useful features necessary for improving the classification performance are extracted during the mapper phase, known as HHWO, which incorporates Horse Herd Optimization Algorithm (HOA) and Whale Optimization Algorithm (WOA). Finally, severity analysis of ALL is done to classify the levels of leukemia to offer optimal treatment. As a result, the developed method performed better than other existing methods, achieving superior performance with a greater testing accuracy of 0.959, sensitivity of 0.965, and specificity of 0.966, respectively. [ABSTRACT FROM AUTHOR]

This paper introduces an approach to the automated measurement and analysis of dairy cows using 3D point cloud technology. The integration of advanced sensing techniques enables the collection of non-intrusive, precise data, facilitating comprehensive monitoring of key parameters related to the health, well-being, and productivity of dairy cows. The proposed system employs 3D imaging sensors to capture detailed information about various parts of dairy cows, generating accurate, high-resolution point clouds. A robust automated algorithm has been developed to process these point clouds and extract relevant metrics such as dairy cow stature height, rump width, rump angle, and front teat length. Based on the measured data combined with expert assessments of dairy cows, the quality indices of dairy cows are automatically evaluated and extracted. By leveraging this technology, dairy farmers can gain real-time insights into the health status of individual cows and the overall herd. Additionally, the automated analysis facilitates efficient management practices and optimizes feeding strategies and resource allocation. The results of field trials and validation studies demonstrate the effectiveness and reliability of the automated 3D point cloud approach in dairy farm environments. The errors between manually measured values of dairy cow height, rump angle, and front teat length, and those calculated by the auto-measurement algorithm were within 0.7 cm, with no observed exceedance of errors in comparison to manual measurements. This research contributes to the burgeoning field of precision livestock farming, offering a technological solution that not only enhances productivity but also aligns with contemporary standards for sustainable and ethical animal husbandry practices. [ABSTRACT FROM AUTHOR]

Simple Summary: Spontaneous humeral fractures in first- and second-lactation dairy cows are recognized as a serious welfare problem in New Zealand. However, the condition is sporadic, which means that simple epidemiological descriptions and estimates of the extent of the problem are lacking. By combining the data from four independent studies using a multi-method approach, we found that their occurrence is more common than previously thought, with potentially up to 12% of farms and 4,620 dairy cattle affected in the 2013/2014 lactation season. Furthermore, the condition exclusively affects first- and second-lactation spring calving dairy cows, up to 4 months post-partum, and may affect multiple animals on the same farm, in the same season, and over multiple seasons, which are not always consecutive. We suggest that the evidence presented in this paper places an urgent requirement on the New Zealand dairy industry to undertake prompt action to understand the determinants of this epidemic. A multi-method approach integrating data from four independent sources was used to describe some key features of the epidemiology and estimate the herd and within-herd incidence of fractured humeri in New Zealand dairy cattle for the period 2007–2015. The first dataset was from a national case series where cases of humeral fractures in dairy cattle were identified by veterinarians across New Zealand between the 2007/2008 and 2011/2012 lactation seasons. The second dataset was from a pet food company based in the Waikato region, which collated the number of casualty first- and second-lactation cows found to have a fractured humerus post-slaughter in the 2014/2015 lactation season, and the third dataset was a case series conducted by veterinarians employed in a Waikato veterinary business, also from the 2014/2015 lactation season. For the final dataset, 505 randomly selected New Zealand dairy farmers completed a phone survey on the incidence of non-responsive, non-weight-bearing forelimb lameness in first- and second-lactation cows in the 2014/2015 lactation season. Using the telephone survey results, the within-herd and herd-level incidence of cases for first- and second-lactation dairy animals was calculated. The national case series reported 149 cases of humeral fractures in 22 dairy herds; the pet food case series identified 61 cases from 41 farms; and the practice-based case series found 14 cases from 10 farms. Humeral fractures exclusively affected first- and second-lactation dairy cows and had a peak incidence between calving and early mating. The national telephone survey found that non-weight-bearing forelimb lameness requiring euthanasia of first- or second-lactation cows occurred in 11.7% of herds, with a mean within-herd incidence of 2.6% for first lactation cows and 2.8% for second-lactation cows for affected herds. These combined datasets demonstrate that humeral fractures in young, lactating dairy cattle are more common than previously suspected and that they occur nationally and over multiple years on some farms. Further work on this condition is urgently required in New Zealand to establish cost-effective management practices that will reduce unnecessary animal suffering and waste. [ABSTRACT FROM AUTHOR]

Simple Summary: Dairy cow behavior detection is of great significance for cattle health management. Through the detection of the four behaviors of dairy cows—standing, lying, eating, and drinking—we can gain valuable insights into the well-being of cows. For example, hoof disease can increase the amount of time a cow lies down, and digestive system issues can cause a decrease in food intake. Visual inspection of cow behavior can keep track of changes in cow behavior, and non-invasive detection can reduce cow discomfort and improve animal welfare. In this study, we employed computer vision-based deep learning techniques for the detection of cow behavior, and experimental results demonstrated its promising application in real farm settings. Dairy cow behavior carries important health information. Timely and accurate detection of behaviors such as drinking, feeding, lying, and standing is meaningful for monitoring individual cows and herd management. In this study, a model called Res-DenseYOLO is proposed for accurately detecting the individual behavior of dairy cows living in cowsheds. Specifically, a dense module was integrated into the backbone network of YOLOv5 to strengthen feature extraction for actual cowshed environments. A CoordAtt attention mechanism and SioU loss function were added to enhance feature learning and training convergence. Multi-scale detection heads were designed to improve small target detection. The model was trained and tested on 5516 images collected from monitoring videos of a dairy cowshed. The experimental results showed that the performance of Res-DenseYOLO proposed in this paper is better than that of Fast-RCNN, SSD, YOLOv4, YOLOv7, and other detection models in terms of precision, recall, and mAP metrics. Specifically, Res-DenseYOLO achieved 94.7% precision, 91.2% recall, and 96.3% mAP, outperforming the baseline YOLOv5 model by 0.7%, 4.2%, and 3.7%, respectively. This research developed a useful solution for real-time and accurate detection of dairy cow behaviors with video monitoring only, providing valuable behavioral data for animal welfare and production management. [ABSTRACT FROM AUTHOR]

AbstractIn this paper, consideration is given to contemporary culture’s impact on language and its communicative potential. Drawing on psychoanalytic understanding of the human herd instinct, particularly in time of strife, this essay outlines what the “talking cure” has to offer as counterpoint to group think and as a means to enter into all that is idiosyncratic and individual in the use of language. [ABSTRACT FROM AUTHOR]

The paper explores how beneficiaries of South Africa's land reform programme attempt to navigate the contradictory dynamics of production and social reproduction in collectively owned agricultural enterprises. The Mphuzanyoni Communal Property Association in KwaZulu‐Natal province farms with commercial beef herds and the Mayime Cooperative in the Eastern Cape province is engaged in a joint venture dairy farming scheme in partnership with an agribusiness firm. Severe tensions are evident between the social reproduction of households and the requirements of simple or expanded reproduction of agricultural enterprises. Bernstein's concept of competing 'funds' is used to examine struggles over production and reproduction on the farms, in which members of socially differentiated households contest divergent visions for the collective enterprises. Conflicts centre on how labour and capital should be mobilised, how income and other benefits in kind should be distributed to households and whether or not income should be invested for purposes of simple or expanded reproduction of the enterprise. Challenges of governance are rooted in these conflicts rather than in group ownership as a form of property right. [ABSTRACT FROM AUTHOR]

In the realm of blockchain technology, the quest for scalable and high-quality-of-service (QoS) systems remains a formidable challenge. Existing blockchain models often grapple with trade-offs between efficiency, speed, and security, particularly in the face of growing demands for energy-efficient and swift data processing. This paper introduces an innovative approach to address these limitations, leveraging Q Learning for context-based shard management, coupled with Elephant Herd Fish Swarm Optimization (EHFSO) process. This novel combination is specifically engineered to dynamically select hashing and encryption techniques tailored to each context-based shard, thereby enhancing the overall performance of blockchain systems. The proposed model marks a significant departure from traditional blockchain architectures. By integrating Q Learning, the system intelligently adapts to varying data contexts, ensuring optimal shard management operations. The EHFSO algorithm, drawing inspiration from natural swarm behavior, further refines the selection process for hashing and encryption techniques. This dual approach not only fortifies security but also augments efficiency levels. The practical efficacy of this model is underscored by its performance on multiple medical datasets & its samples. The results are compelling: an 8.5% improvement in mining energy efficiency, a 4.9% increase in mining speed, 5.9% higher throughput, 4.5% more consistent mining, and a noteworthy 5.9% reduction in storage costs compared to existing methods. Primarily, the work paves the way for more sustainable and efficient blockchain operations, particularly crucial in energy-sensitive sectors. Additionally, the enhanced throughput and mining consistency significantly improve the blockchain's applicability in real-world scenarios, where speed and reliability are paramount in real-time use cases. This research not only addresses the current limitations of blockchain technology but also sets a new benchmark for future developments in this field for different scenarios. [ABSTRACT FROM AUTHOR]

Context: Managing people outside the farm family unit is a new issue for many Irish dairy farmers. In the context of rapid growth, the demand for employees has increased, creating the need for Irish dairy farmers to have human resource management (HRM) skills. Aims: This paper explores the extent and type of HRM practices adopted by Irish dairy farmers and the factors that influence their adoption. Methods: A questionnaire was developed, piloted, and issued to farmers on the basis of herd size and location. Data from 203 dairy farmers who employ people were analysed to examine the adoption of different HRM practices and the influence of farm characteristics, farmer demographics and farmer attitudes on their adoption. HRM practices included compliance with employment legislation, health and safety, different approaches to recruitment, workforce management and retention. The questionnaire included one or more variables for each of these HRM practices. Where more than one variable was included, an aggregate variable was developed for that practice. Key results: Whereas, overall, there was a low level of adoption of best HRM practices, farm characteristics such as herd size and number of employees had a significant influence on farmers' adoption of compliance with employment legislation, health and safety, recruitment, workforce management and retention practices. Demographic factors such as age, level of education, and average hours worked influenced farmers compliance with employment law legislation, workforce management practices and retention practices. Conclusions: The study highlighted an overall low compliance with employment legislation and low adoption of best practices in managing staff among dairy farmers in Ireland. Implications: This study highlighted that improvement is needed in all areas of HRM on Irish dairy farms. The findings of this study would be useful to farm advisors who support dairy farmers in improving their management of their businesses. Overall, this study has contributed to a greater understanding of the challenges in managing people in agriculture and how certain factors influences the adoption of HRM practices on dairy farms. The dairy industry's recent growth in Ireland has resulted in a high demand for additional workers, increasing the requirement for farmers to be skilled in Human Resource Management (HRM). This study identified that the adoption of HRM practices is influenced by farm characteristics, in particular herd size, the number of employees on the farm. This study has contributed insights into the prevalence of specific HRM practices on Irish dairy farms, and indicated that there is a significant scope for improvement. A novel aspect of this study was the focus on the potential factors that influence the adoption of HRM practices on Irish dairy farms. The findings of this study could be used by agricultural advisors and those working in HRM to provide tailored advice to support dairy farmers and other small business owners in managing their employees. [ABSTRACT FROM AUTHOR]

Decision support systems (DSSs) enable dairy farmers to make informed and timely decisions on herd health management. However, the lack of a disease scoring system by category and severity limits the application of this approach. In this study, we developed an innovative approach to dairy herd health management by establishing a novel scoring system for dairy herd health management aimed at providing a more nuanced understanding of disease impact. For this purpose, we retrieved 5-year data from 2 558 disease diary records of 798 primiparous and multiparous cows housed on a Czech farm and classified 125 production diseases into six categories, namely lameness, mastitis, postpartum diseases, digestive system, reproductive diseases and other diseases. Based on this metric, we developed a data-driven DSS for farm management. Using this DSS, we identified markers of disease categories for efficient veterinary monitoring on dairy farms. This DSS highlighted a decreasing trend of average monthly disease scores, yet the prevalence of postpartum and other diseases increased during the same period, due to changes in reproduction management within the herd. These findings underscore the need for data-driven targeted interventions for promoting the herd health. Therefore, our scoring model not only provides a comprehensive framework for dairy herd health monitoring and improvement but also advances dairy farming by providing a decision support system easily applicable to dairy farms based on available data recorded in disease diaries. [ABSTRACT FROM AUTHOR]

The article examines the herd behaviour at sector level in the National Stock Exchange of India. The novel objective of the paper is to analyse the presence of herd behaviour during the whole, pre- and post-coronavirus disease 2019 (COVID-19) pandemic outbreak period. The popular model proposed by Chang et al. (2000) has been deployed to examine herd formation in each sector. Five major sectors namely auto, bank, fast moving consumer goods, information technology and pharma have been considered along with NIFTY50 consisting daily closing prices of 106 companies comprising 58 from five sectoral indices and 48 from NIFTY50 for the period from 2011 to 2021 considering 1 January 2011–29 January 2020 as before COVID-19 outbreak period and 30 January 2020–31 December 2021 as after COVID-19 outbreak period. Results revealed significant evidence of anti-herd behaviour before COVID19 outbreak. At the same time, significant evidence of the existence of herd behaviour in FMCG, auto and pharma sectors have been detected after the outbreak of COVID-19 pandemic which assumes that investors tend to imitate the investment decisions of other market participants during such adverse macro events around the globe. The study tried to enhance the knowledge of investors to develop their trading strategies in the volatile market conditions by investing vigilantly and keeping such phenomenon in concern. [ABSTRACT FROM AUTHOR]

The 2015 EU milk quota abolition initiated considerable expansion in the dairy sector. This expansion has increased the demand for additional labour in some EU countries, most significantly in Ireland. This paper explores the role of hired labour on Irish dairy farms' technical efficiency (TE). We use a detailed farm‐level panel data set of a representative sample from 2000 to 2018. To estimate transient, persistent, and overall TE over time, we apply a 4‐component stochastic frontier model. Our findings show significant variation in TE scores over the period. We also control for endogeneity to obtain marginal effects of hired labour on TE. The results reveal that hired labour has a significant yet small, positive effect on farms' TE. Our findings suggest that the effect of hired labour on TE is larger for small and medium‐sized farms. This effect is larger when herd size increases. [ABSTRACT FROM AUTHOR]

In this paper charcoals from the Syrian sites Tell Mozan and Tell Jerablus are investigated to understand the impact of 4th to 2nd millennium BC settlement on the vegetation. Charcoals from these sites have been identified and oak fragments have been measured for their maximal diameter and annual ring widths. Our results show that while oak had reached its maximal expansion in the Mid-Holocene, and vegetation in the Euphrates Valley was lusher than today, strong anthropogenic impact on the vegetation was occurring, probably already prior to the Late Chalcolithic period. Due to potentially enormous herds of sheep and goat, and possibly large-scale agriculture with perhaps some understory cropping, oak was growing very slowly, to the degree that it must often have had a shrub-like appearance. People did not apply systematic oak woodland management practices, such as coppicing or pollarding. They used dung as an additional fuel, probably to cover for shortages in wood resources. The land appears to have been used both intensively and extensively to a degree that was not sustainable in the long term. This, combined with aridity impact on the oak, probably led to a decrease in oak proportion at Mozan in the Middle Bronze Age. [ABSTRACT FROM AUTHOR]

This paper proposes a novel nature-inspired swarm-based optimization algorithm called elk herd optimizer (EHO). It is inspired by the breeding process of the elk herd. Elks have two main breeding seasons: rutting and calving. In the rutting season, the elk herd splits into different families of various sizes. This division is based on fighting for dominance between bulls, where the stronger bull can form a family with large numbers of harems. In the calving season, each family breeds new calves from its bull and harems. This inspiration is set in an optimization context where the optimization loop consists of three operators: rutting season, calving season, and selection season. During the selection season, all families are merged, including bulls, harems, and calves. The fittest elk herd will be selected for use in the upcoming rutting and calving seasons. In simple words, EHO divides the population into a set of groups, each with one leader and several followers in the rutting season. The number of followers is determined based on the fitness value of its leader group. Each group will generate new solutions based on its leader and followers in the calving season. The members of all groups including leaders, followers, and new solutions are combined and the fittest population is selected in the selection season. The performance of EHO is assessed using 29 benchmark optimization problems utilized in the CEC-2017 special sessions on real-parameter optimization and four traditional real-world engineering design problems. The comparative results were conducted against ten well-established metaheuristic algorithms and showed that the proposed EHO yielded the best results for almost all the benchmark functions used. Statistical testing using Friedman's test post-hocked by Holm's test function confirms the superiority of the proposed EHO when compared to other methods. In a nutshell, EHO is an efficient nature-inspired swarm-based optimization algorithm that can be used to tackle several optimization problems. [ABSTRACT FROM AUTHOR]

Since the implementation of herding in the Neolithic period, specialized areas for livestock activities have emerged in the Western Mediterranean region, such as some caves and shelters, which were systematically used for the stabling of herds. By definition, this type of sites has a great potential for the study of the beginning of livestock practices and offer high-resolution information on the exploitation and management of herds. Different disciplines analyze these activities through the analysis of faunal, archaeobotanical or sedimentological remains from these sites. In this paper, we offer a state of the art on the contribution to the study of early husbandry practices of zooarchaeological studies of faunal assemblages from sheepfold caves. [ABSTRACT FROM AUTHOR]

The return of wolves to Swiss mountains and the damage they cause to sheep and goat herds in the region have raised concerns about a consequent wave of farm closures. In this paper, we examine the relationship between wolf attacks and the decline of Alpine summer farms, a specific high‐altitude farm type. We collected farm structure data and monitoring data on wolf attacks between 2004 and 2021 and analysed them using a causal random forest method, enabling a detailed analysis of the relation between wolf attacks and the number of different types of Alpine summer farms at a regional level. The results show that the farming systems are unaffected by incidental and infrequent wolf attacks, but that a high number of wolf attacks in a region is related to faster decrease in number of grazing systems where sheep are most vulnerable to such attacks. In contrast, systems that allow for better herd protection tend to show an increase in areas with frequent wolf attacks. [ABSTRACT FROM AUTHOR]

Energy efficiency and security have become prominent aspects of Wireless Sensor Networks (WSNs) for transmitting data. The major challenge is to increase the "Quality of Service" (QoS) since it is restricted by fewer constrained resources. Although the existing routing protocols acquire efficient transmission, they are still subsisting with the challenges of improving security and energy conservation. It will be helpful in practical implications like the military, weather forecasting and healthcare industry. As the nodes are operated by the energy preservation of the battery, developing an energy-efficient protocol is challenging. Since WSN possesses massive numbers of sensor nodes, it also has to avoid long-term communication, and the clustering mechanism is a prerequisite. Considering the diverse objectives like delay, energy and distance, there are still remarkable challenges to develop the routing protocol. Moreover, security enhancement becomes another challenging issue over the network for data transmission through the sensor nodes. To overcome these issues, a novel energy-efficient routing model is designed in this paper by using a hybrid algorithm and the multi-objective derivatives. Initially, the clustering approach is employed to reduce the complexity and improve the security in an energy-efficient manner. Therefore, the Cluster Head (CH) is selected significantly using the novel Hybrid Horse Herd-Dragonfly Optimisation (HHHDO). The hybrid algorithm is developed by integrating Horse Herd Optimisation (HHO) and Dragonfly Algorithm (DA). Here, the optimal CH selection is achieved by deriving the multi-objective function regarding "distance, delay, energy, load and trust of nodes". Trust is measured with the Neural Network (NN)-based HHHDO (NN-HHHDO) model. Depending on the trust evaluation and energy efficiency, the proposed model obtains better communication between the nodes. In the end, the experimentation of the recommended model is made using various measures and it's ensured that the suggested technique enhances trust among the nodes and energy conservation in comparison to the existing algorithms. [ABSTRACT FROM AUTHOR]

The article focuses on analyzing developments in the academic literature regarding the relationship between monetary policy and herd behavior in the stock market. The main research method used in this article is a systematic review of the literature, including methods of synthesis and bibliographic analysis. Accordingly, the bibliographic method is employed to organise and analyze the standard deviation associated with behavioral economics research. The research offers scholarly publications that include the term "monetary policy and herd behavior" from Dimensions database between the middle of 2014 to the beginning of 2023. The results show that there are two main research trends on the relationship between monetary policy and herd behavior, which are based on theory and market effects. Accordingly, the theoretical background to explain this interaction includes the micro-foundation of economics, behavioral macroeconomics, and the mediation of the stock market cycle. However, like most other micro-factors, crowd psychology has not been studied and appreciated in terms of its influence on economic policy, even though they are purely a crucial components causing asset bubbles are beyond the control and adjustment of monetary policy. Therefore, future studies should have a specific definition, as well as a proper assessment of the role of the crowd in the ability to make investment decisions as well as the market's risk tolerance in order to have specific recommendations for monetary policy. [ABSTRACT FROM AUTHOR]

Survival rate (SR) number of parities and length of productive herd life (LPHL) were evaluated for Holstein Friesian cows that calved beginning January 1, 2000 through May 2021 in a research dairy farm. A total of 870 lactation records were examined. Average Survival Rates (SRs) were 75.8% to parity 2, 49.7% to parity 3, 37.3% to parity 4, 18.6% to parity 5, 11% to parity 6, 6.3% to parity 7 and 3.3% to parity 8. A change for a better survival rate of cows over the span, years 2011-2021 compared with 2000-2010 was found to parity 2 and to parity 3 (significant differences). For the rest of parities (to 4, to 5, to 6, to 7 and to 8) the differences were non-significant. Average number of parities over the spam years 2000 to 2015 was 2.81. Linear regression of average of parities on year of first calving was positive (R=0.2786) and this means that was a weak direct relationship between variables. A change in the year of first calving with 1 impacted a change in the number of parities with 0.006. Average productive herd life (months) over the span years 2000 to 2015 was 33.86. Linear regression of average LPHL by year of first calving was positive (R=0.6513) and this means that was a strong direct relationship between variables. A change in the year of first calving with 1, impacted a change in the number of parities with 0.1889. The results of this study can give important information for economic studies on dairy herd management [ABSTRACT FROM AUTHOR]

• Lactose tolerance and the co-spreading of LCT/MCM6 and the high-risk MS allele, HLA-DRB1*15:01, throughout Europe. • Exposure to dairy-animal pathogen, Clostridium perfringens Epsilon neurotoxin (ETX) • Environmental trigger for multiple sclerosis (MS) On January 10th, 2024, Barrie et al. published a landmark paper identifying the ancestral European origin of the high-risk, multiple sclerosis (MS) allele, HLA-DRB1*15:01. The authors hypothesize that Bronze Age, Yamnaya migration to, and their population of Scandinavia and the British Isles, accounts for the high incidence of MS in these regions, stemming from the geographical spread of HLA-DRB1*15:01 as evidenced by their data. These data further indicate that this immune-related allele likely underwent positive-selection pressures, suggesting that HLA-DRB1*15:01 may have conferred increased immunological resistance to zoonotic pathogens that the Yamnaya would have been exposed to from a lifestyle of sheep, goat, and cattle herding, as well as from the prevalent consumption of dairy products harvested from these animals. We wish to expand the scope of the Barrie et al. hypothesis to include the other gene that emerged in their extensive genomic analysis; the lactase persistence allele, LCT/MCM6, which allows adults to consume milk beyond childhood without adverse physical effects. We propose that, in addition to the Yamnaya spread of HLA-DRB1*15:01, their spread of LCT/MCM6 engendered a cultural propensity for milk consumption that may play a significant role in the present-day, global distribution of MS. Specifically, we hypothesize that lactose tolerance, and the prominent dairy consumption it enables, may expose individuals to the enteric, dairy-animal pathogen, Clostridium perfringens type B/D and its Epsilon neurotoxin that targets the precise brain tissues damaged during each MS relapse. [ABSTRACT FROM AUTHOR]

Emerging infectious diseases with zoonotic potential often have complex socioecological dynamics and limited ecological data, requiring integration of epidemiological modeling with surveillance. Although our understanding of SARS-CoV-2 has advanced considerably since its detection in late 2019, the factors influencing its introduction and transmission in wildlife hosts, particularly white-tailed deer (Odocoileus virginianus), remain poorly understood. We use a Susceptible-Infected-Recovered-Susceptible epidemiological model to investigate the spillover risk and transmission dynamics of SARS-CoV-2 in wild and captive white-tailed deer populations across various simulated scenarios. We found that captive scenarios pose a higher risk of SARS-CoV-2 introduction from humans into deer herds and subsequent transmission among deer, compared to wild herds. However, even in wild herds, the transmission risk is often substantial enough to sustain infections. Furthermore, we demonstrate that the strength of introduction from humans influences outbreak characteristics only to a certain extent. Transmission among deer was frequently sufficient for widespread outbreaks in deer populations, regardless of the initial level of introduction. We also explore the potential for fence line interactions between captive and wild deer to elevate outbreak metrics in wild herds that have the lowest risk of introduction and sustained transmission. Our results indicate that SARS-CoV-2 could be introduced and maintained in deer herds across a range of circumstances based on testing a range of introduction and transmission risks in various captive and wild scenarios. Our approach and findings will aid One Health strategies that mitigate persistent SARS-CoV-2 outbreaks in white-tailed deer populations and potential spillback to humans. Author summary: Novel zoonotic diseases persist and evolve in both human and non-human hosts, posing challenges for human and animal health. SARS-CoV-2, the virus responsible for the COVID-19 pandemic in humans, has been detected in white-tailed deer (Odocoileus virginianus) yet we have limited understanding of its introduction and transmission within deer populations. Here, we use epidemiological models to describe SARS-CoV-2 introduction and transmission patterns within wild and captive white-tailed deer populations. We found that captive deer herds faced a higher risk of spillover of SARS-CoV-2 from humans and higher transmission rate compared to wild deer. Despite these differences in wild and captive contexts, we found that transmission in both wild and captive contexts often resulted in persisting circulation of SARS-CoV-2. This circulation was determined by deer-deer transmission in both wild and captive contexts, rather than by high rates of introduction from humans. Outbreaks in wild populations were greater when these animals could interact with captive deer populations circulating SARS-CoV-2. SARS-CoV-2 appears to circulate in both captive and wild deer across a range of circumstances. Our findings help to inform how to best mitigate the introduction and spread of SARS-CoV-2 in deer, with benefits to protecting human health. [ABSTRACT FROM AUTHOR]

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Bovine mastitis, as a significant and prevalent health problem in dairy herds, is primarily attributed to bacterial infections. Yeasts, although considered relatively rare causative agents, have also been associated with mastitis in dairy cattle. Current mastitis treatment predominantly relies on antibiotics, with limited emphasis on antifungal treatment. However, mycotic mastitis is challenging to treat, since these fungi are often resistant to antibiotics and may even utilize them for energy. In the current research, the in vivo antimicrobial activity of the essential oil-based formulation (Phyto-Bomat), as a possible alternative mastitis treatment associated with yeasts, was studied. This study involved a total of 68 animals from two dairy farms with diagnosed mastitis, and three treatment groups were established: conventional antibiotic treatment, Phyto-Bomat treatment, and the combination of both. The findings suggest significant variations in the presence of Candida samples based on the treatment administered, and the most significant difference was noted in cows treated with the combination (Phyto-Bomat and antibiotics). Yet, it is important to note that the results reveal that, regardless of the treatment type, there are statistically significant differences in the presence of Candida samples across the examined time points. These results aim to provide valuable insights into the potential of EOs as an alternative therapy in bovine mastitis, specifically targeting yeasts. Such findings could offer new strategies in the mycotic mastitis control and reducing the occurrence of secondary infections following antibiotic treatment. [ABSTRACT FROM AUTHOR]

Trueperella (T.) pyogenes is a mastitis-causing pathogen formerly known to cause severe clinical mastitis (CM), especially during the summer, leading to milk losses and low recovery rates. Unfortunately, its transmission behavior within herds is unclear. The diversity and occurrence of T. pyogenes were monitored to gain an initial insight into the infection transmission behavior of T. pyogenes in dairy herds and to lay a foundation for following targeted investigations. CM milk samples were collected from German herds, and one Swedish farm was sampled for isolates from subclinical mastitis. All in all, 151 T. pyogenes isolates from 16 herds were isolated, identified by MALDI TOF analysis and typed with RAPD PCR. Of these, 17 isolates originated from subclinical mastitis cases. We found that T. pyogenes mastitis occurred year-round, and clinical mastitis cases were caused by multiple strains (31 affected animals/28 strains). Instances of multiple cows being infected with the same T. pyogenes strain were rare and typically only involved a small number of animals at a time. However, if several quarters of a cow were affected, it was likely the same strain. Unlike clinical infections, subclinical T. pyogenes infections, in one investigated farm, harbored a dominant strain. Additionally, we found that T. pyogenes infections tended to persist and stay within a herd for a minimum of 7 months in the same or different cows. [ABSTRACT FROM AUTHOR]

Simple Summary: Brucella abortus strain 19 vaccines, including A19 and S19 vaccines, are widely used to prevent bovine brucellosis. Vaccine-induced antibodies are usually considered to last for no more than 12 months. After this period, individuals testing positive are excluded because they are presumed to be infected with Brucella field strains. In Ningxia, China, immunization with the Brucella abortus strain A19 vaccine is being implemented as part of a brucellosis eradication program. We conducted a serological survey of cattle immunized with the A19 vaccine for over 12 months in Lingwu, Ningxia, from 2021 to 2023. It was found that there was a certain proportion of cows with a persistent antibody titer who were not infected with brucellosis. Therefore, cattle with positive antibodies cannot be eliminated through simple serological detection. Otherwise, a large number of healthy cattle would be mistakenly culled, resulting in significant economic losses. We have also developed a PCR method to distinguish Brucella strain 19 from non-19 Brucella strains and successfully detected 10 Brucella abortus field strains from five dairy farms. (1) Background: One method of eradicating brucellosis is to cull cattle that test positive for antibodies 12 months after being vaccinated with the 19-strain vaccine. Variations in immunization regimens and feeding practices may contribute to differences in the rate of persistent antibodies. We conducted this study to investigate the real positive rate of Brucella antibody in field strains of Brucella spp. after immunization over 12 months in dairy cows. This research aims to provide data to support the development of strategies for preventing, controlling, and eradicating brucellosis. (2) Method: We employed the baseline sampling method to collect samples from cows immunized with the A19 vaccine for over 12 months in Lingwu City from 2021 to 2023. Serological detection was conducted using the RBPT method. An established PCR method that could distinguish between 19 and non-19 strains of Brucella was utilized to investigate the field strains of Brucella on 10 dairy farms based on six samples mixed into one using the Mathematical Expectation strategy. (3) Results: We analyzed the rates of individual seropositivity and herd seropositive rates in dairy cattle in Lingwu City from 2021 to 2023 and revealed that antibodies induced by the Brucella abortus strain A19 vaccine persist in dairy herds for more than 12 months. We established a PCR method for identifying both Brucella A19 and non-A19 strains, resulting in the detection of 10 field strains of Brucella abortus from 1537 dairy cows. By employing a Mathematical Expectation strategy, we completed testing of 1537 samples after conducting only 306 tests, thereby reducing the workload by 80.1%. (4) Conclusions: There was a certain proportion of cows with a persistent antibody titer, but there was no evidence that all of these cattle were naturally infected with Brucella. The established PCR method for distinguishing between Brucella abortus strain 19 and non-19 strains can be specifically utilized for detecting natural Brucella infection in immunized cattle. We propose that relying solely on the detection of antibodies in cattle immunized with the A19 vaccine more than 12 months previously should not be solely relied upon as a diagnostic basis for brucellosis, and it is essential to complement this approach with PCR analysis to specifically identify field Brucella spp. Brucella abortus was the predominant strain identified in the field during this study. Detection based on the Mathematical Expectation strategy can significantly enhance detection efficiency. [ABSTRACT FROM AUTHOR]

The Pregnancy-Associated Glycoproteins (PAGs) belong to aspartic protease family and are synthesized by trophoblast cells of ruminant placenta and secreted into maternal blood and milk. These biomarkers very closely associated to pregnancy have demonstrated their efficiency and reliability in detection of vital embryos or pregnancy loss. In order to measure the concentration of PAGs in bovine serum, a direct radioimmunoassay (RIA) system was developed and validated. The radioiodinated bPAG tracer was prepared by chloramine-T direct method and the solid phase was used in RIA/PAGs as a separation system. The optimization tests allowed to set the assays procedure as working buffers, time and temperature of the assays incubation. Assay sensitivity was 0.63 ng/mL, the intra and inter-assay CVs were 7.7% and 5.3% respectively and the accuracy of the assays was expressed by a good parallelism and recovery tests. The serums bPAG values determinated by this developed system were consistent with the reproduction status and pregnancy stages of cows. The developed RIA/PAG system can provide the laboratory with an efficient method for the accurate detection of pregnancy, which could offer veterinarians and farmers an important tool for the reproductive management in dairy herds. Moreover, this diagnostic tool can also be developed for other livestock species. [ABSTRACT FROM AUTHOR]

Bovine trypanosomosis, caused by Trypanosoma vivax, currently affects cattle and has a significant economic impact in sub-Saharan Africa and South America. The development of new diagnostic antigens is essential to improve and refine existing methods. Our study evaluated the efficacy of two recombinant antigens in detecting specific antibodies in cattle. These antigens are derivatives of an invariant surface glycoprotein (ISG) from T. vivax. A fraction of a previously described antigen (TvY486_0045500), designated TvISGAf, from an African strain was evaluated, and a new ISG antigen from an American isolate, TvISGAm, was identified. The two antigens were expressed as fusion proteins in Escherichia coli: TvISGAf was fused to the MBP-His-tag, and TvISGAm was obtained as a His-tag fused protein. An ELISA evaluation was conducted using these antigens on 149 positive and 63 negative bovine samples. The diagnostic performance was enhanced by the use of a combination of both antigens (referred to as TvISG-based ELISA), achieving a sensitivity of 89.6% and specificity of 93.8%. Following the validation of the TvISG-based ELISA, the seroprevalence of T. vivax infection in 892 field samples from cattle in the central region of Argentina was determined. The mean seroprevalence of T. vivax was 53%, with variation ranging from 21% to 69% among the six departments studied. These results support the use of the TvISG ELISA as a valuable serological tool for the detection and monitoring of T. vivax infection in cattle. Furthermore, we report for the first time the seroprevalence of T. vivax in Argentina, which highlights the widespread endemic nature of the disease in the region. In order to effectively manage the increasing spread of T. vivax in the vast livestock production areas of South America, it is essential to implement consistent surveillance programs and to adopt preventive strategies. Author summary: Bovine trypanosomosis is a disease that threatens cattle health and agriculture in South America and Africa. It is mainly caused by the parasite Trypanosoma vivax. Diagnosis of this infection has been challenging, hampering efforts to monitor and control outbreaks. In this study, we developed a more accurate and sensitive test for detecting T. vivax in cattle. Using recombinant proteins tailored to parasite strains in the Americas, this new test can identify infection rates and patterns within cattle herds and regions. By analyzing over 800 cattle blood samples from Argentina ranchlands, we discovered over 50% seropositivity, indicating a far higher prevalence than previously recognized. These results highlight the urgent need for surveillance and preventive strategies, although diagnostic tools provide a means for tracking regional spread. By enhancing the diagnosis of this livestock disease, this study lays the foundation for protecting cattle health and associated livelihoods across at-risk communities in the developing world. This study exemplifies how molecular innovations can address veterinary challenges and promote food security within resource-constrained farming systems. [ABSTRACT FROM AUTHOR]

Dairy production in the UK has undergone substantial restructuring over the last few decades. Farming intensification has led to a reduction in the total numbers of farms and animals, while the average herd size per holding has increased. These ever-changing circumstances have important implications for the health and welfare of dairy cows, as well as the overall business performance of farms. For decision-making in dairy farming, it is essential to understand the underlying causes of the inefficiencies and their relative impact. The investigation of yield gaps regarding dairy cattle has been focused on specific causes. However, in addition to the risk of overestimating the impact of a specific ailment, this approach does not allow understanding of the relative contribution to the total, nor does it allow understanding of how well-described that gap is in terms of underlying causes. Using the English and Welsh dairy sectors as an example, this work estimates the Loss Gap–composed of yield losses and health expenditure ‐ using a benchmarking approach and scenario analysis. The Loss Gap was estimated by comparing the current performance of dairy herds as a baseline with that of scenarios where assumptions were made about the milk production of cows, production costs, market prices, mortality, and expenditure related to health events. A deterministic model was developed, consisting of an enterprise budget, in which the cow was the unit, with milking herd and young stock treated separately. When constraining milk production, the model estimated an annual Loss Gap of £148 to £227 million for the whole sector. The reduction in costs of veterinary services and medicines, alongside herd replacement costs, were important contributors to the estimate with some variation between the scenarios. Milk price had a substantial impact in the estimate, with revenue from milk yield representing more than 30% of the Loss Gap, when milk price was benchmarked against that of the top performing farms. This framework provides the boundaries for understanding the relative burden from specific causes in English and Welsh dairy cattle, ensuring that the sum of the estimated losses due to particular problem does not exceed the losses from all-causes, health or non-health related. [ABSTRACT FROM AUTHOR]

Background: Staphylococcus aureus can colonize and infect a variety of animal species. In dairy herds, it is one of the leading causes of mastitis cases. The objective of this study was to characterize the S. aureus isolates recovered from nasal swabs of 249 healthy cows and 21 breeders of 21 dairy farms located in two provinces of Algeria (Tizi Ouzou and Bouira). Methods: The detection of enterotoxin genes was investigated by multiplex PCRs. Resistance of recovered isolates to 8 antimicrobial agents was determined by disc-diffusion method. The slime production and biofilm formation of S. aureus isolates were assessed using congo-red agar (CRA) and microtiter-plate assay. Molecular characterization of selected isolates was carried out by spa-typing and Multi-Locus-Sequence-Typing (MLST). Results: S. aureus was detected in 30/249 (12%) and 6/13 (28.6%) of nasal swabs in cows and breeders, respectively, and a total of 72 isolates were recovered from positive samples (59 isolates from cows and 13 from breeders). Twenty-six of these isolates (36.1%) harbored genes encoding for staphylococcal enterotoxins, including 17/59 (28.8%) isolates from cows and 9/13 (69.2%) from breeders. Moreover, 49.1% and 92.3% of isolates from cows and breeders, respectively, showed penicillin resistance. All isolates were considered as methicillin-susceptible (MSSA). Forty-five (76.3%) of the isolates from cows were slime producers and 52 (88.1%) of them had the ability to form biofilm in microtiter plates. Evidence of a possible zoonotic transmission was observed in two farms, since S. aureus isolates recovered in these farms from cows and breeders belonged to the same clonal lineage (CC15-ST15-t084 or CC30-ST34-t2228). Conclusions: Although healthy cows in this study did not harbor methicillin-resistant S. aureus isolates, the nares of healthy cows could be a reservoir of enterotoxigenic and biofilm producing isolates which could have implications in human and animal health. [ABSTRACT FROM AUTHOR]

Several pathotypes of enteric E. coli have been identified. The group represented by Shiga toxin-producing E. coli (STEC) is of particular interest. Raw milk and raw milk products are significant sources of STEC infection in humans; therefore, identifying pathogens at the herd level is crucial for public health. Most national surveillance programs focus solely on raw milk and raw milk cheeses that are ready for retail sale, neglecting the possibility of evaluating the source of contamination directly at the beginning of the dairy chain. To assess the viability of the application of new molecular methodologies to STEC identification in raw milk filters and in calf feces, we analyzed 290 samples from 18 different dairy herds, including 88 bulk tank milk (BTM), 104 raw milk filters (RMF), and 98 calf feces samples. In total 3.4% of BTM, 41.4% of RMF, and 73.4% of calves' feces were positive for stx, supporting our hypothesis that BTM is not a suitable matrix to assess the presence of STEC at herd level, underestimating it. Our conclusion is that the surveillance program needs critical and extensive improvements such as RMF and calves' feces analysis implementation to be more efficient in detecting and preventing STEC infections. The epidemiology of these infections and the characteristics of the pathogen clearly show how a One Health approach will be pivotal in improving our capabilities to control the spread of these infections. [ABSTRACT FROM AUTHOR]

This study explores the similarities and differences in herding behaviour and influencers by gender, specifically for the millennial generation. We find evidence that both groups exhibit very similar behaviour when it comes to herding and the influencers they choose to listen to. The two groups differ somewhat in the influence parents and siblings have on them, with females experiencing more influence from them. These findings are significant as they are contrary to most existing literature which suggests that males and females are quite different while making investment decisions. Regression model for the impact of influencers on herding behaviour was also similar for both genders. Both groups listen to experts but do not herd based on this. Both groups tend to herd more based on friends, relatives, siblings and parents. The insights from the study will be useful for services marketing professionals and financial planners who can use the influencers who will be effective in communicating information as well as enrol those influencers who male and female millennials herd with for their financial investment decisions. This should help them achieve more targeted communication strategies. [ABSTRACT FROM AUTHOR]

The High Energy Cosmic Radiation Detection (HERD) facility will be installed on the China space station, and the critical sub-detector is the homogeneous, isotropic, and finely segmented 3D calorimeter (CALO), composed of 7500 LYSO cubes. In this paper, GEANT4 was used to simulate the optical photon propagation inside a single LYSO crystal including the Wavelength Shifting Fiber (WLSF) and photodiode (PD) and compared with experimental results. The results show that only a tiny fraction of the photons produced in the LYSO can be collected through the WLSF and PD, and the light output can be enhanced by increasing the number of rough surfaces. Additionally, the variability in WLSF and PD light output when particles entered the LYSO crystal from varying positions, known as non-uniformity, was examined through simulation. The simulated non-uniformity using thin X-ray beams is compatible within the experimental errors and can be improved at higher light output. Finally, the non-uniformity is highly sensitive to the polishing condition of the crystal surface, and better polishing conditions are preferred. [ABSTRACT FROM AUTHOR]

The increasing use of the payment for ecosystem services (PES) represents a prominent institutional shock triggered by external interventions on livelihoods of natural resource managers. To reconcile the needs for both conservation and development, a deep understanding on the influence mechanisms of PES on farmer livelihood resilience is paramount, particularly in dynamic and uncertain contexts. Taking the Rangeland Ecological Protection Subsidy and Reward scheme that has been implemented in pastoral China since 2011 as a case study, the paper empirically investigates the impacts of PES on livelihood resilience of livestock farmers in Qinghai Province. Based on a comprehensive evaluation of herder livelihood resilience from three dimensions—buffering, self-organizing and learning capacities, multiple linear regression was applied to examine the PES impacts. Resilience enhancement was mainly found in buffering capacity for herders with a medium to large herd size. Results of univariate parallel mediation models further reveal that household income growth and diversification and livestock upsizing were three key intermediary processes that mediated the enhancement and together contributed 28.83% of the total effect. The findings help narrow a knowledge gap in understanding whether, how and for whom PES contributes to improve farmer livelihood resilience. To achieve "win-win" outcomes, we stress that greater attention should be given to tailoring design and implementation of PES programs to align with the specificity of local contexts. • Impacts of one rangeland PES program on herder livelihood resilience are examined. • Ecological compensation has significantly enhanced the livelihood resilience of herders. • Buffering capacity is enhanced more than self-organizing and learning capacity. • Income growth and diversification as well as herd upsizing are three crucial mediators. • Larger-scale herders are improved stronger than smaller-scale ones. [ABSTRACT FROM AUTHOR]

This article focuses on optimizing electric vehicle charging in distribution networks, emphasizing technical and economic considerations. Unlike traditional methods, the proposed intelligent approach tailors each EV's charging based on specific daily trip energy requirements. Vehicle owners provide trip data to the charge management system, enabling precise charging calculations considering factors such as energy tariffs, distribution network limits, and charging levels. The paper introduces the horse herd optimization algorithm, inspired by horse herd behavior, offering advantages like reduced computational time and improved convergence in maximizing power generation, especially under shading conditions. The comparative analysis of smart EV charging under normal and fast conditions, considering various constraints and load response programs, demonstrates the proposed method's effectiveness. Numerical results reveal a 46.02 % average load reduction and a 20.53 % peak load decrease with a Load Response Program. Charging costs are optimized, with Case 2 exhibiting a 2.61 % cost reduction compared to Case 3. The study delves into charging frequencies, discharge frequencies, total unsupplied energy, and unloaded energy for each case, providing crucial insights into algorithmic performance. The horse herd optimization algorithm-based approach proves superior, offering a promising solution for efficient and cost-effective electric vehicle charging in distribution networks. Furthermore, graphical representations illustrate the algorithm's impact on charging power, energy allocation, power passing through distribution posts, and megavolt-ampere flow through network lines. These numerical and graphical analyses provide a comprehensive understanding of the horse herd optimization algorithm capabilities, emphasizing its potential to optimize power distribution, reduce costs, and enhance the resilience of residential distribution networks. • Prioritizes EV charging based on daily travel and battery levels using discrete charge rates. • Compares normal and fast charging rates, considering transformer overloads. • Adapts network and load model from real data, balancing subscriber and operator interests. • Assesses method's impact with and without a load response program for adaptability. • Introduces the Horse Herd Optimization Algorithm (HOA) inspired by horse herd behavior. [ABSTRACT FROM AUTHOR]

Bovine tuberculosis (bTB) is a chronic zoonotic disease affecting cattle of all age groups including wild animals. It poses a significant threat to public health and high economic losses to dairy farmers. While the disease has been eradicated from most of the developed countries through extensive surveillance, testing and culling strategy, it is endemic in Africa, Asia, and the Middle East countries. Currently, there is limited research regarding the prevalence of bTB in cattle in Bhutan. This study aimed to determine the seroprevalence of bTB in cattle in six districts of eastern Bhutan. A two-stage probability proportional to size (PPS) sampling strategy was used to determine the number of animals from which serum samples needed to be collected in each district and sub-district. All farms and cattle for sampling were randomly selected from the data in the annual livestock census of 2020. The samples were tested using bTB ELISA test kit. The seroprevalence and their 95% confidence intervals were calculated. Logistic regression models were constructed to assess the influence of various individual animal and environmental risk factors (breed, age, sex, source of animal, body condition scores of animals, respiratory system status) associated with sero-positivity in animals. The study revealed an apparent seroprevalence of 2.57% (25/971 cattle; 95% CI:1.58–3.57), with an estimated true seroprevalence of 0.91% (95% CI: 0.0–2.81). However, none of the variables were found to be significantly associated with bTB seroprevalence in cattle. We recommend, further sampling and employment of confirmatory testing to fully ascertain the extent of bTB in the cattle herds in eastern Bhutan for prevention and control. Author summary: Bovine tuberculosis (bTB) is a bacterial zoonotic disease caused by Mycobacterium bovis, affecting cattle of all ages. Mycobacterium bovis imposes significant economic burdens on livestock farmers, primarily through reduced production, trade restrictions for live animals and animal products, and the costs of control measures. The disease can be transmitted to humans via consumption of raw milk or through inhalation of infected aerosols. Worldwide, the bovine tuberculosis accounts for 10% of the human tuberculosis cases. In Bhutan, the prevalence and incidence of bTB in both cattle and humans are unknown. In this study, we estimated the seroprevalence of bTB among cattle in six eastern districts of Bhutan. We collected serum samples from 971 cattle and tested them for bovine tuberculosis using ELISA. Our study demonstrated an apparent prevalence of 2.57% (95% CI:1.58–3.57) and a true prevalence of 0.91% (95% CI: 0.0–2.81). Additionally, we assessed factors such as age, breed and farm location that could affect the prevalence of bTB, but none of these factors were significantly associated with the prevalence of bTB. Our study revealed a very low seroprevalence of bTB, among cattle in eastern Bhutan. The findings from this study will contribute to design prevention and control measures for bTB in cattle in Bhutan. [ABSTRACT FROM AUTHOR]

Currently, PRRSV-1 causes a large number of clinical infections in Chinese swine herds, and the prevalence of new strains has presented great challenges. In this study, the novel PRRSV-1 strain SL-01 was isolated, with a genome length of 14,978 bp, and genetic evolution analysis revealed that it belonged to a new subtype branch. Sequence homology analysis showed that the strain was only 82.2%–86.7% identical to the current classical PRRSV-1 strains. In particular, the novel strain exhibited a unique deletion pattern in Nsp2. In addition, GP3 and GP4 of the SL-01 strain showed four consecutive amino acid deletions in the highly variable regions at amino acids 243–248 and 63–68, respectively. Further challenges in piglet and pregnant sow demonstrated that the SL-01 strain could cause the piglet fever and death but less pathogenic to pregnant sow. Overall, the characterization and pathogenicity of a novel PRRSV-1 strain were first explored and provide a prevention for pig farms. [ABSTRACT FROM AUTHOR]

Simple Summary: One key factor in the emergence of antimicrobial resistance (AMR) in microorganisms is antimicrobial usage in veterinary and human medicine. In dairy cattle, the prevalence of AMR E. coli is age-dependent, with a higher prevalence detected during the early stages of life. In veal calf fattening herds, the high degree of commingling calves from different farms of origin can lead to the rapid spread of infections within the farm. This can cause severe health issues, necessitating greater use of antimicrobial agents. Antimicrobial use has been reported to be higher in the veal calf fattening sector compared to the other production branches of livestock production. This represents an unquantified risk to human health, as antimicrobial-resistant bacteria and the genetic elements mediating resistance can potentially spread through foodborne transmission or environmental dissemination. This surveillance study was conducted, using data available from routine diagnostic activity, to: (i) determine the proportion of antimicrobial-resistant strains and AMR profiles of E. coli isolated from the intestinal contents of veal and dairy calves in the Veneto Region (Northeaster Italy); (ii) investigate potential variation in the AMR profiles of isolates between the two categories of calves and, (iii) identify potential AMR variations over the period considered (2017–2022). This surveillance study aimed to estimate the proportion of antimicrobial resistant strains and antimicrobial resistance (AMR) profiles of E. coli isolates detected from the intestinal contents of veal and dairy calves in the Veneto Region, Northeaster Italy. Additionally, we investigated the differences in AMR profiles between dairy and veal calves over the period 2017–2022. Overall 1150 E. coli isolates were tested from calves exhibiting enteric disease, with 868 from dairy and 282 from veal calves. The percentage of resistant isolates to nine antimicrobials was notably higher in veal calves compared to dairy calves, except for ampicillin. Throughout the study period, we observed a significant increase in the proportion of resistant isolates to florfenicol, gentamycin, paromomycin, tetracycline and trimethoprim/sulfamethoxazole in dairy calves, while we did not detect any significant increase in the proportion of resistant isolates among veal calves. A substantial proportion (75.9%) of the isolated E. coli exhibited multi-drug resistance (MDR). The proportion of multi-drug resistant isolates was significantly higher in veal calves (91.7%) compared to dairy calves (74.3%) all through the surveillance period (2017–2022), with no significant variation in MDR proportion among veal calves between 2017 and 2022 but a significant increase among dairy calves. [ABSTRACT FROM AUTHOR]

Background: Cross‐border livestock mobility through transhumance is mainly practiced in West African countries for seasonal access to resources and market. Cross‐border herds are involved in the dynamic of transboundary animal diseases among them brucellosis taken as model. Brucellosis is a zoonotic disease causing abortion. Objectives: This study explores the seroprevalence of brucellosis according to mobility and infection spread between Mali and Côte d'Ivoire in the context of seasonal cross‐border transhumance. Methods: From February to April 2021, a transversal serological survey of brucellosis was conducted on 521 cattle from 111 transhumant herds and 283 cattle from 59 sedentary herds, all from Mali. Results: The global individual seroprevalence for Brucella spp. in transhumant and sedentary cattle from Mali was 8.2% (95% CI = 6.0–10.5). At herd level, seroprevalence was 21.2% with a significant variation between transhumant (11.7%) and sedentary (39.0%) herds. For herds in transhumance, cattle seropositivity was associated with a previous infection suspected by herdsmen odds ratio (OR = 4.4; 95% CI = 1.1–18.1) and unknown abortion aetiology (OR = 4.3; 95% CI = 1.0–17.3). The departure region (coming from Sikasso) and previous brucellosis infection or unexplained abortion could be used to predict Brucella infection in transhumant herds with a probability of around 60%. The risk of brucellosis introduction in host regions was high despite the individual animal seroprevalence of 3.6% and a low sale rate in transhumant cattle. Conclusions: The findings suggest that testing transhumant during border control and survey of cattle markets and sales could improve risk control of the spread of disease at regional scale. [ABSTRACT FROM AUTHOR]

Sending children, especially six-year-old ones, to school put pressure on pastoralist or herder households to balance their livestock herding needs and their children's schooling needs at the same time. Due to remote campsites located in isolated rural areas far from any schools, pastoralists need to arrange a place for their children to stay during the school year. In this interpretive phenomenological study, we explored pastoralist parents' experiences in managing different living arrangements for their primary school children during the school year. We conducted semi-structured interviews with five pastoralist parents from a remote county (an administrative division under a province) in Mongolia. Living arrangement options included staying in a boarding school dormitory, staying at a relative's place, and staying with mothers in split households. The pastoralist parents' own school experiences, the presence of first-grade school children, boarding school conditions, and family resources were found to be important factors for deciding the best living arrangement. We recommend that the government agencies should work on improving conditions of school dormitories and on providing better educational opportunities for pastoralists and their children. [ABSTRACT FROM AUTHOR]