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Purpose – The purpose of this research is to design and build a wild animal pest repellent device with combination of passive infrared (PIR) sensor and ultrasonic signal based on microcontroller as system controller. The PIR sensor is used to detect the presence of wild animal objects and ultrasonic signals to interfere with the hearing.

Design/Methodology/Approach – The design of the system is built based on microcontroller as the system controller. The system as a whole includes hardware and software. The design of hardware consists of the system design on the transmitter side and the system design on the receiver side, while the software in the of system are algorithms using C language programming.

Findings – The resulting repellent device can detect animals approaching up to a distance of 5 m and may interfere with its hearing with a 40 kHz ultrasonic frequency up to a distance of 20 m. The system also uses remote monitoring devices using 433 MHz radio frequency up to a distance of 60 m.

Research Limitations/Implications – Each animal has different hearing frequencies, as well as some wild animals, but the hearing frequencies of wild animals are generally at ultrasonic frequencies. The frequency of animal hearing may vary from audio frequency to ultrasonic frequency, so ultrasonic wave emission testing with varying frequencies is required.

Practical Implications – This research combines systems on transmitters and receivers, with real-time monitoring of wild animal positions, and it can be possible to monitor the position of more detailed animals by installing more types of sensors as well as increasing the number of sensors.

Originality/Value – This paper may provide additional insight into the hearing frequencies of animals and may also serve as comparable papers for similar studies.

The purpose of this paper is to explore the attitude of pig farmers toward animal welfare in light of the state‐of‐the‐art legislation on animal welfare and production schemes in Italy.

The general framework regarding pig production, legislation and production schemes will be described by a literature review and personal communications from experts in the field. The results of farmers' attitudes toward animal welfare are based on a survey carried out among pig producers.

The main findings of the research are related to the survey results among pig producers. The paper presents a short description of the Italian pig sector and the results of the animal welfare legislation and production schemes.

The main limitation of the study is the relatively limited number of survey interviews. For this reason the sample cannot be considered statistically representative of the whole country.

The information collected in this article could represent a useful source for farmers, policy makers, and retailers, as well as consumers interested in animal welfare issues.

This is the first time that pig producers have been asked to express their opinion on animal welfare as defined by the legislation in force and the existing production schemes.

The purpose of this paper is to describe the main characteristics of the animal welfare specifications in different quality schemes of the French pig sector; to present the French pig farmers' attitudes towards animal welfare in general, and illustrate different quality schemes.

Prime source of data is interviews with 60 pig farmers. Supplementary sources are research reports and statistics, specifications of the quality schemes.

On many themes, the responses and attitudes of the farmers differ according to their participation or not in a quality assurance scheme, and according to the level of stringency of their scheme regarding animal welfare. For instance, farmers in the most stringent schemes define animal welfare as providing natural living conditions for the animals, whereas for farmers in no schemes, or in more intensive schemes, animal welfare is above all an animal in good health, for which one must provide correct housing and a balanced and sufficient diet. Animal welfare is almost always a part of more global quality schemes including environmental and high flavour quality aspects.

The paper provides insights into the different definitions of good animal welfare by French pig farmers, as well as their attitudes towards public regulations and different types of private schemes. This is interesting from a scientific point of view and to fuel the debate between a high level of regulation for all farmers, a market segmentation based on welfare specification, or a market segmentation in which animal welfare is one aspect of the specifications.

This paper reviews the possibilities of coronavirus disease 2019 (COVID-19) spreading from infected humans to pet animals and from pet animals to other animals and humans.

A systematic literature review and meta-analysis were performed on research articles from November 2019 to August 2020. This study explored urgently needed research issues on COVID-19 infection spreading across animals and humans and vice versa.

Essential and much needed precautionary measures and necessary preventive steps to protect pet animals from infection were highlighted.

Essential investigation and experiment results were highlighted. The necessary measure to prevent the spread of infection among and across species and people was analyzed.

Although virtual anchors have emerged as potent marketing tools, their acceptance by consumers is controversial. Specifically, the relative efficacy of selecting an all-human-like or animal-human-like virtual anchor is not well-defined. However, anthropomorphic visual cues are vital in enhancing live streaming. This study aims to analyze the disparate effects of an animal-human-like or all-human-like virtual anchor on purchase intention as well as evaluate the possible underlying influential mechanisms and boundary conditions.

In this research, three different studies were carried out to elucidate the impact of virtual anchors on purchase intention. Study 1 evaluated the core impact of an animal-human-like and all-human-like virtual anchor on purchase intention, as well as the mediating role of perceived warmth and competence. Studies 2 and 3 were then performed to investigate the moderating impacts of product type and certainty of consumer needs, respectively. Furthermore, research data for these studies was collected using the Credamo tool and analyzed via SPSS, using PROCESS for moderation and mediation analyses.

The research findings indicate that virtual anchors can trigger purchase intention, with perceived warmth and competence acting as mediating factors. Based on the utilitarian products and high certainty of consumer needs, the influence of perceived competence on purchase intention is augmented. Therefore, an all-human-like virtual anchor increases purchase intention. In contrast, the impact of perceived warmth on purchase intention is supplemented for hedonic products and low certainty of consumer needs. Thus, an animal-human-like virtual anchor increases purchase intention.

This research study evaluated consumer reactions to all-human-like and animal-human-like virtual anchors for different product types and the certainty of consumer needs to optimize the comprehension of a virtual anchor. Furthermore, the assessment of the mediating roles of perceived warmth and competence provided valuable insights into the influential mechanisms by which virtual anchors affect purchase intention. Moreover, this study provided managerial implications to guide retailers and brands on the strategic adoption of virtual anchors to enhance purchase intention based on the product type and the certainty of consumer needs.

Limiting the use of antibiotics in food animals is a cornerstone of contemporary EU policy. Despite that marketing of antibiotics for growth promotion and nutrition has been banned since 2006, the use is still high and varied. This paper aims to investigate the forces behind the different usage patterns in Italy, with one of the EU’s most extensive use of antibiotics in animals, versus Sweden, with the union’s most restricted use, including how these usage patterns are related to EU and national policies.

The industrial network approach/the 4R resources interaction model is adopted to investigate the major forces behind the different antibiotic usage patterns. Furthermore, the study relies on the notion of three main characteristics related to the use of a resource activated in several user settings (Håkansson and Waluszewski, 2008, pp. 20–22). The paper investigates the Swedish and the Italian using settings, with a minimised, respectively, extensive usage of antibiotics. The study is exploratory in nature and based on qualitative data collected through a combination of primary and secondary sources.

The paper underlines the importance of integrating forces for policy to succeed in attempts to reduce the use of a particular resource. It reveals that Sweden’s radically reduced use was based on great awareness, close interactions between animal-based food producers and policy – and that integrating forces were supported by an era of state-protected food production, with promising ability to distribute the cost of change. The Italian characteristics hindering the integration of forces mounting for reduced use were restricted awareness, top-down business and policy interactions – and a great awareness about the difficulties of distributing the cost of change.

The study deals with the analysis of forces affecting the different usage of antibiotics within two EU settings. The investigation, based on the industrial network approach’s notion of connectivity of economic resources, that is, of exchange having a content and substance beyond discrete transactions, reveals how indirect related contextual forces, neglected by policy, have an important influence on the ability to achieve change, in this case of antibiotics usage patterns.

With the rapid advancement of lifestyle and technology, human lives are becoming increasingly threatened. Accidents, exposure to dangerous substances and animal strikes are all possible threats. Human lives are increasingly being harmed as a result of attacks by wild animals. Further investigation into the cases reported revealed that such events can be detected early on. Techniques such as machine learning and deep learning will be used to solve this challenge. The upgraded VGG-16 model with deep learning-based detection is appropriate for such real-time applications because it overcomes the low accuracy and poor real-time performance of traditional detection methods and detects medium- and long-distance objects more accurately. Many organizations use various safety and security measures, particularly CCTV/video surveillance systems, to address physical security concerns. CCTV/video monitoring systems are quite good at visually detecting a range of attacks associated with suspicious behavior on the premises and in the workplace. Many have indeed begun to use automated systems such as video analytics solutions such as motion detection, object/perimeter detection, face recognition and artificial intelligence/machine learning, among others. Anomaly identification can be performed with the data collected from the CCTV cameras. The camera surveillance can generate enormous quantities of data, which is laborious and expensive to screen for the species of interest. Many cases have been recorded where wild animals enter public places, causing havoc and damaging lives and property. There are many cases where people have lost their lives to wild attacks. The conventional approach of sifting through images by eye can be expensive and risky. Therefore, an automated wild animal detection system is required to avoid these circumstances.

The proposed system consists of a wild animal detection module, a classifier and an alarm module, for which video frames are fed as input and the output is prediction results. Frames extracted from videos are pre-processed and then delivered to the neural network classifier as filtered frames. The classifier module categorizes the identified animal into one of the several categories. An email or WhatsApp notice is issued to the appropriate authorities or users based on the classifier outcome.

Evaluation metrics are used to assess the quality of a statistical or machine learning model. Any system will include a review of machine learning models or algorithms. A number of evaluation measures can be performed to put a model to the test. Among them are classification accuracy, logarithmic loss, confusion matrix and other metrics. The model must be evaluated using a range of evaluation metrics. This is because a model may perform well when one measurement from one evaluation metric is used but perform poorly when another measurement from another evaluation metric is used. We must utilize evaluation metrics to guarantee that the model is running correctly and optimally.

The output of conv5 3 will be of size 7*7*512 in the ImageNet VGG-16 in Figure 4, which operates on images of size 224*224*3. Therefore, the parameters of fc6 with a flattened input size of 7*7*512 and an output size of 4,096 are 4,096, 7*7*512. With reshaped parameters of dimensions 4,096*7*7*512, the comparable convolutional layer conv6 has a 7*7 kernel size and 4,096 output channels. The parameters of fc7 with an input size of 4,096 (i.e. the output size of fc6) and an output size of 4,096 are 4,096, 4,096. The input can be thought of as a one-of-a-kind image with 4,096 input channels. With reshaped parameters of dimensions 4,096*1*1*4,096, the comparable convolutional layer conv7 has a 1*1 kernel size and 4,096 output channels. It is clear that conv6 has 4,096 filters, each with dimensions 7*7*512, and conv7 has 4,096 filters, each with dimensions 1*1*4,096. These filters are numerous, large and computationally expensive. To remedy this, the authors opt to reduce both their number and the size of each filter by subsampling parameters from the converted convolutional layers. Conv6 will use 1,024 filters, each with dimensions 3*3*512. Therefore, the parameters are subsampled from 4,096*7*7*512 to 1,024*3*3*512. Conv7 will use 1,024 filters, each with dimensions 1*1*1,024. Therefore, the parameters are subsampled from 4,096*1*1*4,096 to 1,024*1*1*1,024.

This chapter reviews factors responsible for climate change, impacts of the change on animal health, zoonotic diseases, and their linkage with One-Health program.

This chapter is based on the available literature related to climate change and its effect on animal health and production from different points. The causes and change forcers of climate change, direct and indirect effects of the change on animal health management, host–pathogen–vector interaction, and zoonotic diseases are included. Inter-linkage between climate change and One-Health program are also assessed.

Beside natural causes of climatic change, greenhouse gases are increasing due to human activities, causing global climate changes which have direct and indirect animal health and production performance impacts. The direct impacts are increased ambient temperature, floods, and droughts, while the indirect are reduced availability of water and food. The change and effect also promote diseases spread, increase survival and availability of the pathogen and its intermediate vector host, responsible for distribution and prevalence of tremendous zoonotic, infectious, and vector-borne diseases. The adverse effect on the biodiversity, distribution of animals and micro flora, genetic makeup of microbials which may lead to emerging and re-emerging disease and their outbreaks make the strong linkage between climate change and One-Health.

Global climate change is receiving increasing international attention where international organizations are increasing their focus on tackling the health impacts. Thus, there is a need for parallel mitigation of climate change and animal diseases in a global form.

Most research on climate change is limited to environmental protection, however this chapter provides a nexus between climate change, animal health, livestock production, and the One-Health program for better livelihood.