The objective of this study was to apply simulation and computational intelligence techniques using artificial intelligence and genetic algorithm for economic and environmental optimization of the reverse network (manufacturers, waste managers and recyclers in São Paulo, Brazil) of waste electrical and electronic equipment (WEEE) to promote circular economy. For the economic evaluation, the reduction of: fuel, drivers, insurance, depreciation, maintenance and charges was considered and for the environmental evaluation, the environmental impact was measured in the abiotic, biotic, water, land, air and greenhouse gases compartments. It is concluded that the optimized structure of the WEEE reverse chain for São Paulo, Brazil reduced the number of collections, making the most of the cubage. It also generated economic and environmental gains, contributing to the strategic actions of the circular economy. Thus, the proposed simulation allows replication in organizational practice, mainly to meet the 2030 agenda on reducing the carbon footprint generated in transport in large cities. Thus, this study can guide companies on structuring the reverse WEEE chain in São Paulo, Brazil for economic and environmental optimization, a relevant aspect considering the exponential generation of WEEE, requiring the implementation of the national solid waste policy, and subsequently the signature of the electronics sector agreement in São Paulo.

Eco-labels are an instrument for enabling informed food choices and supporting a demand-sided change towards a more and urgently needed sustainable food system. Lately, novel eco-labels that depict a product’s environmental life-cycle assessment on a multi-level scale are being tested across Europe’s retailers. This study elicits consumers preferences and willingness to pay (WTP) for a multi-level eco-label. A Discrete Choice Experiment was conducted in Austria. Individual partworth utilities were estimated by means of Hierarchical Bayes. Results show higher WTP for a positive evaluated multi-level label, revealing consumers’ perceived benefits of colorful multi-level labels over binary black-and-white designs. Even a negative evaluated multi-level label showed higher WTP compared to no label, pointing towards limited effectiveness of eco-labels. Respondents’ preferences for eco-labels were independent from their subjective eco-label knowledge, health consciousness, and environmental concern. The attribute “protein source” was most important, and preferences for animal-based protein source (beef) was strongly correlated with consumers’ meat attachment, implying that a shift towards more sustainable protein sources is challenging and sustainability labels have only a small impact on the meat product choice of average consumers.

Cellular Vehicle-to-Everything (C-V2X) is a communication technology that supports various safety, mobility, and environmental applications given its higher reliability properties compared to other communication technologies. The performance of these C-V2X-enabled Intelligent Transportation System (ITS) applications is affected by the performance of the C-V2X communication technology (mainly packet loss). Similarly, the performance of the C-V2X communication is dependent on the vehicular traffic density which is affected by the traffic mobility patterns, and vehicle routing strategies. Consequently, it is critical to develop a tool that can simulate, analyze, and evaluate the mutual interactions of the transportation and communication systems at the application level and to the evaluate the benefits of the C-V2X enabled ITS applications. In this paper, we demonstrate the benefits gained when using C-V2X Vehicle-to-Infrastructure (V2I) communication technology in an energy-efficient dynamic routing application. Specifically, we develop a Connected Energy-Efficient Dynamic Routing (C-EEDR) application using C-V2X as a communication medium in an integrated vehicular traffic and communication simulator (INTEGRATION). The results demonstrate that the C-EEDR application achieves fuel savings of up to 16.6% and 14.7% in the IDEAL and C-V2X communication cases, respectively for a peak hour demand on the downtown Los Angeles network considering a 50% level of market penetration of connected vehicles. The results demonstrate that the fuel savings increase with increasing levels of market penetration at lower traffic demand levels (25% and 50% the peak demand). At higher traffic demand levels (75% and 100%) the fuel savings increase with increasing levels of market penetration with maximum benefits at a 50% market penetration rate. Although the communication system is affected by the high density of vehicles at the high traffic demand levels (75% and 100% the peak demand), the C-EEDR application manages to perform reliably producing system-wide fuel consumption savings.The C-EEDR application achieves fuel savings of 15.2% and 11.7% for the IDEAL communication and 14% and 9% for the C-V2X communication at the 75% and 100% market penetration rates, respectively. Finally, the paper demonstrates that the C-V2X communication constraints only affect the performance of the C-EEDR application at the full demand level when the market penetration of connected vehicles exceeds 25%. This degradation, however is minimal (less than a 2.5% reduction in fuel savings).

In the age of the digital economy, the security and privacy for multimedia systems issues are increasingly manifested in the form of data. The level of data protection governance capability determines whether the security and privacy of multimedia systems can be protected. In recent years, China has introduced laws and regulations on the protection of personal information, personal privacy, data security, and cyber-security. Although data protection is still to be improved, China has been refining the provisions on data security management through practice and the adoption of supporting regulations.

In this paper, we dive into the exciting world of wireless communication, focusing on how millimeter-wave technology and Multiple-Input Multiple-Output phased array antennas are shaping the future of 5G and the upcoming 6G technologies. We cover the latest advancements in millimeter-wave and beam-forming technologies, emphasizing their role in enhancing network security and efficiency in automotive vehicles through dual radar communication. Our discussion spans the benefits, applications, challenges, and solutions of these technologies individually from millimeter-wave to beam-forming technology and joint radar communications, alongside a look at their theoretical and practical implementations. We emphasize the integration of beam-forming technology in joint radar communications for future automotive vehicles and its impact on automotive systems, smart cities, and the Internet of Things (IoT). Looking ahead, we discuss the potential of these technologies to transform future tech landscapes, while also addressing the security implications of merging communication and radar capabilities. This paper aims to provide a clear view of the advancements and prospects of millimeter-wave, beam-forming, and dual radar communication technologies.

Climate change poses a significant threat to global food security, necessitating a thorough examination across multiple dimensions. Establishing appropriate food security evaluation indicators that align with the evolving concept of food security is imperative. This study enhances food security evaluation by refining a multi-dimensional framework and analyzing the impact of climate change across various regions from 2002 to 2021. By constructing an Food Security Index system composed of a three-tier indicator system and employing the entropy method for weighting, we assess the impacts of climate change on food security using a climate-economic model. Regression analysis reveals a negative linear relationship between mean temperatures and food security (p<0.01), while precipitation impacts food security non-linearly, particularly exhibiting inverse U-shaped patterns in major grain-producing and grain-consuming areas. Extreme high temperatures consistently reduce food security, whereas extreme precipitation displays a complex, statistically significant inverse U-shaped association. In regions where production and consumption are balanced, mean temperatures have a negative effect on food security, while precipitation exhibits a positive correlation, but excessive precipitation can have adverse effects. These findings highlight the intricate interplay between climate change, regional disparities, and food security in China, emphasizing the need to consider multi-dimensional factors and regional variations in addressing food security challenges. These insights are invaluable for policy-making and planning aimed at enhancing food security in China.

The rapid and sensitive detection of pathogenic bacteria is becoming increasingly important for the timely prevention of contamination and treatment of infections. Biosensors based on nucleic acid aptamers integrat-ed with optical, electrochemical, and mass-sensitive analytical techniques have garnered intense interest for their versatility, cost-efficiency, and ability to exhibit high affinity and specificity in binding bacterial bi-omarkers, toxins, and whole cells. This review emphasizes the development of aptamers, their structural op-timization, and their use in bacterial sensing applications. Moreover, we explore barriers and develop per-spectives in applying aptamer-based bacterial detection.

Ensuring the security of vertical applications in fifth-generation (5G) mobile communication systems and previous generations is crucial. These systems must prioritize maintaining the confidentiality, integrity, and availability of services and data. Examples of vertical applications include smart cities, smart transportation, public services, Industry 4.0, smart grids, smart health, and smart agriculture. Each vertical application has specific security requirements and faces unique threats within the mobile network environment. Thus, it is essential to implement comprehensive and robust security measures. This approach helps minimize the attack surface and effectively manage risks. This survey thoroughly examines mobile networks and their security challenges in vertical applications, shedding light on associated threats and potential solutions. Our study considers the interplay between security considerations in 5G, legacy networks, and vertical applications. We emphasize the challenges, opportunities, and promising directions for future research in this field and the importance of securing vertical applications in the evolving landscape of mobile technology.

Food insecurity remains a critical challenge in developing countries like Ethiopia. Majority of its population derive their livelihood from agriculture characterized by mixed farming systems. Smallholder farmers the principal actors of agriculture are also facing a rapidly increasing population and urbanization had been unable to be self-sufficient in food. This paper examines the role of commercialization on food security and its determinants in rural settings. We used cross-sectional data from 295 households randomly selected in northwest Ethiopia. Results from bivariate Tobit regression revealed both crop and livestock commercialization improves household food security but in quite different ways. The income from crop sales was instrumental in allowing households to buy additional foods while livestock sales foster crop diversity for own consumption by allowing them to purchase nonfood items. Thus, agriculture-food security nexus may not require the production systems to be subsistent. Improving commercialization with better access to off-farm employment and institutional services (credit and market infrastructure), and enhanced awareness of the extension towards promoting commercialization and diversified food consumption seem to be more promising. The research paper concludes commercialization is vital not just for economic growth and food security, but also for the smallholder agriculture in providing additional nutrition.

This paper aims to analyze the role of natural heritage cataloging when criminal events challenge natural history museums. This study investigates the rhino horn thefts in Italian natural history museums from 2011 to 2015 to provide a comprehensive framework for these robberies while highlighting the weaknesses and strengths to prevent thefts and safeguard both rhino horns and natural history collections from future targeting

Botnet Attacks are one of the many types of ways to attack users in their day to day browsing, often of different trends and techniques to take your information without your control. Most firewalls can amply protect you against these trends and techniques, but scarily enough, recent articles and research have shown that they are starting to bypass said firewalls through layers of attacks, confusing your best line of defense. In this Report, we will be looking into exactly what are Botnets and the different subsets, what we can do to combat Botnet Attacks, where do they come from, their origin, the analysis of their kit and what we can put together from information collected. Through this we will be able to reach a conclusion of what we can use to possibly mitigate the effect they have on the internet and stop them from enacting their purpose.

The goal of this study is to categorize stakeholders in Internet of Things (IoT) security based on their roles in order to address the challenges associated with managing the large amount of data generated by IoT devices. With the increasing number of connected devices, the security risks also escalate, necessitating skilled stakeholders to mitigate these risks and prevent potential attacks. This study proposes a two-part approach that involves clustering stakeholders according to their responsibilities and determining relevant features to enhance decision-making. By grouping stakeholders into shared categories, the study aims to provide a more efficient and effective method for managing IoT security. The insights gained from this research will not only benefit stakeholders involved in IoT security but also assist policymakers and regulators in developing effective strategies.

Hundreds of millions of people on the planet are affected by malnourishment. This contributes to the vulnerability of large swaths of the population, especially children under five years old extremely vulnerable to diseases and even death in the least developed countries. Today, by providing a substantial share of global protein intake, as well as fatty acids and micronutrients, fisheries contribute to global food security. As fish stocks in the upper sea levels have already been over-exploited, there might not be enough in supplying food security, deep-sea fisheries have been increasingly discussed to address this problem. Some mesopelagic fishes show the potential to provide important nutrients. Another way of supplying food security might be through using mesopelagic fish as fish feed. However, fishing in the mesopelagic zone could lead to severe ecological problems and the impact on the biological carbon pump is uncertain. This paper highlights and juxtaposes different perspectives regarding exploitation pathways of the fish riches of deep seas and reviews best practice model projects that deal with uncertainties related to fishery management in the mesopelagic zone.

Questionnaires are useful instruments for gathering responses to specific factual questions. However, the problems of questionnaire responses impede the effective use of the questionnaire. Some of these problems including non-responses, non-completion, issues of judgement, and social desirability such as information that the respondent is not willing to disclose need to be dealt with. The situation is more compounded in a scenario where an information security practice study in a typical hospital consists of broad categories of respondents and the survey findings are to be relied on to actually address information security compliance issues. This study, therefore, shares "pitfalls" to watch when preparing a questionnaire to measure the information security practice level in a hospital which is characterized by different respondents with varying domain knowledge such as knowledge in information security, information communication technology, and that of the domain knowledge of healthcare. A synergy of a conventional pretesting method and behaviour coding were therefore used to pretest the questionnaire. Questionnaire problems including a lack of understanding of the healthcare information systems’ structure of all hospitals, unclear questions, the insignificant difference between questions, problematic questions, inadequate questions, and complex terms were among the identified pitfalls to watch. Out of a total of 118 questionnaire items that were used in the pretesting, a total of 50 questionnaire items (representing 42%) were identified to have problems after the pretesting was conducted with a total of 36 respondents in behavior coding and 21 respondents in conventional pretesting.

Blockchain technology has gotten much interest recently from academics, industry, and governments worldwide. It is regarded as a technical innovation that can disrupt various application fields affecting many aspects of our lives. Cryptocurrencies are a public blockchain application's success story that sparked extensive research and development. Scalability, energy consumption, and security, on the other hand, remain significant challenges. With low throughput, high transaction delay, and high energy consumption, most cryptocurrencies are experiencing low-efficiency difficulties. The scalability issue with public Blockchains is preventing organizations and sectors from receiving effective solutions. As a result, it is critical to bridge the gap and develop new frameworks that connect Blockchain with those goals. This paper examines the evolution of blockchain architecture and consensus protocols, provides a retrospective analysis, discusses the rationale for the various architectures and protocols' change, and captures the assumptions supporting their development and contributions to collaborative application development. However, existing research on consensus algorithms is insufficient. The features of the algorithms are discussed insufficiently in those papers, and some prominent blockchain consensus methods are not examined in terms of their scopes. The study’s findings are delivered in tabular formats, allowing for a clear representation of these algorithms. We discovered in our investigation that scalability is a result of many parameters such; transaction throughput, number of nodes, storage, block size, high communication, latency, cost. Furthermore, Due to its off-chain data storage and smaller block size, PoF is much more scalable than PoS and PoW, and Because PoA is a hybrid of PoW and PoC, it does not necessitate a large number of computational resources. As a result, it has a higher throughput than PoW. PoPF entails ranking all participating nodes and appointing n accountants to compete for adding new blocks. This article addresses the need by analyzing a wide range of consensus algorithms using a complete taxonomy of attributes and delving into the consequences of several still-present flaws in consensus algorithms.

When we talk about the Internet of Things, we are referring to the connecting of things to a1 physical network that is embedded with software, sensors, and other devices that allow information2 to be exchanged between devices. It is possible that the interconnection of devices will present3 issues in terms of security, trustworthiness, reliability, and confidentiality, among other things.4 The proposed approach is effective at detecting intrusions into the Internet of Things network.5 Initially, the privacy-preserving technology was deployed utilising a Blockchain-based methodology6 to ensure that personal information was protected. Patients’ health records (PHR) security is the7 most crucial component of encryption over the Internet because of the value and importance of these8 records, particularly in the context of the Internet of Medical Things (IoMT). The search terms access9 mechanism is one of the most common approaches used to access personal health records from a10 database, but it is vulnerable to a number of security flaws. However, while blockchain-enabled11 healthcare systems provide increased security, they may also introduce weaknesses into the current12 state of the art. Blockchain-enabled frameworks have been proposed in the literature as a means13 of resolving those challenges. These solutions, on the other hand, are primarily concerned with14 data storage, with Blockchain serving as a database. To enable secure search and keyword-based15 access to a distributed database, this study proposes the use of blockchain technology as a distributed16 database, together with a homomorphic encryption mechanism. Aside from that, the suggested17 system includes a secure key revocation mechanism that can be used to automatically update various18 policies.As a result, our proposed approach provides greater security, efficiency, and transparency19 while also being more cost-effective. We have compared the findings of our proposed models with20 those of the benchmark models, if appropriate. Our comparison research demonstrates that our21 suggested framework provides a more secure and searchable mechanism for the healthcare system22 than the current state of the art.

Blockchain and Machine Learning gives the best solutions together in performing various tasks in the Smart Health care system. With these two new emerging technologies, that have materialized in the last decade. In this paper, we proposed secure, transparent and intelligent methods in the Internate of medical things industry using Machine learning models and blockchain technology to enhance security level and train our models to improve diagnostic, prevention, treatment of the patient, patient rights, patient autonomy and equality in the health care system.

Recent reports have it that over 85\% of data breaches are still caused by the human element, of which healthcare is one of the suitable organizations mostly targeted by cybercriminals. The work of healthcare staff is often associated with high workloads, high emergency cases, and a broad range of psychological, social, and cultural factors. The significance of these factors could undermine conscious care information security (IS) practice leading to serious violations. This study comprehensively examined the correlation between the psycho-social-cultural factors, work factors with IS and privacy behaviour in a hospital that has fully adopted electronic health records (EHR) management system. The findings are to facilitate the decision-making process towards improving the cyber-security practice in healthcare. A quantitative approach was adopted where we collected responses from 212 healthcare staff through an online questionnaire survey. A broad range of constructs was selected from psychological, social, cultural perception and work factors based on earlier review work. These were therefore related to some security practices, to assess the IS knowledge, attitude and behaviour gaps among healthcare staff in a comprehensive way. From the study, IS self-reported conscious care behaviour (ISCCB) risk was relatively higher as compared to information security knowledge (ISK) risks and information security attitude (ISA) risk. Furthermore, the study revealed that work emergency has a positive correlation with ISCCB (r=1.95, p-value =0.001) risk. Conscientiousness also had positive correlation with ISCCB risk (r=0.157, p-value=0.05) however agreeableness negatively correlated with ISK risk (r=-0.166, p-value =0.05), and ISA risk (r=-0.140, p-value =0.05). Based on these findings, intrinsic and extrinsic motivation methods combined with cutting-edge technologies can be explored to discourage IS risks behaviours while enhancing conscious care security practice.

With the emerging technology connected with the internet, there is one constant issue related to that is data security. The only solution with which this issue can be resolved at a limit and can be used to protect the data is various algorithms for encryption. Though different approaches were used for the same, Cryptography seems to be efficiently protecting the data while transmitting in network from sender to receiver. Firstly the data is encrypted before sending to receiver using the most secure and reliable encryption algorithm. Secondly, at the receiver end it can be decrypted using the same decryption algorithm. Only receiver will have the key with which the data can be decrypted. In this paper, AES, DSS and RSA algorithms were implemented. These algorithms are encryption algorithms which perform encoding and decoding of data, to be sent from sender to receiver, using the keys. Each have different criteria for encryption and are then compared based on different parameters viz. delay, throughput, PDR is an acronym for packet delivery ratio, PLR represents packet loss ratio and RPC denotes Received Packet Count. The results in the form of graphs are given to analyze the security provided by each algorithm.

The novel coronavirus SARS-CoV-2, the causative agent of COVID-19, emerged in the human population in December 2019 and spread worldwide within a few short months. Much of the public health focus for preventing and mitigating the spread of COVID-19 has been on individual and collective behaviors, such as social distancing, mask-wearing, and hygiene. Yet it is equally important to recognize that these behaviors and health outcomes occur within broader social and environmental contexts. Factors within local communities, regional policy, race, history, personal beliefs, and natural- and built environmental characteristics affect underlying population health and the spread of disease. For example, COVID-19 has renewed attention to secure water and sanitation services and their importance in protecting human health. Many remote Alaskan communities are particularly vulnerable because of inadequate water and sanitation systems. In this paper, we describe how inadequate water and sewer services may place the inhabitants of remote Alaskan communities at higher risk of COVID spread. We argue that insufficient water security and inadequate sewer systems, along with household overcrowding, multigenerational residences, limited transportation options, limited medical facilities, and higher prevalence of chronic diseases could lead to a greater potential of COVID-19 transmission and to more severe disease outcomes in these communities.

Product counterfeiting is an on-going problem in supply chains and retail environments, Recently an anti-counterfeiting protocol to address this issue via cost-effective use of auto-identification technologies such as radio-frequency identification (RFID) was proposed by researchers.Yet the use case of re-selling the same product was not been fully addressed which might cause serious problem for the exciting and proposed schemes and transactions. This paper proposes an extended RFID-based anti-counterfeiting to address the use case of the original buyer reselling the same item to a second buyer. The extended scheme will be followed by a formal security analysis to show that the proposed protocol satisfies the requirements of security correctness and is resistant to compromise through security attacks.

We seek to elucidate an aspirational vision for the food system and explore whether the characteristics of such a system inadvertently set unattainable standards for rural, low wealth communities. We apply discourse analysis to the following qualitative datasets: (1) interviews with food experts and advocates, (2) scholarly and grey literature, (3) industry websites, and (4) email exchanges between food advocates. The analysis revealed eight aspirational food system discourses: Production, Distribution, and Infrastructure; Healthy, Organic, Local Food; Behavioral Health and Education; Sustainability; Finance and Investment; Huger Relief; Demand Side Preferences; Romanticized, Community Led Transformations. Study findings reveal that of eight discourses only three encompass the experiences of rural, low wealth residents. This aspirational food system may result in the disempowerment of the needs of rural, low wealth groups; a perpetuation of the failure of groups who will be unable to reach the aspirational food vision; silencing of discourses that might question those that play a role in the inequitable distribution of income while sanctioning discourses that focus on personal or community solutions; and the absence of other policy-based solutions that address issues located within the food system. Further research is needed to inform policies and programs to mitigate food insecurity in rural, low wealth populations.

Critical Infrastructures and associated real time Informational systems need some security protection mechanisms that will be able to detect and respond to possible attacks. For this reason, Anomaly Detection Systems (ADS), as part of a Security Information and Event Management (SIEM) system, are needed for constantly monitoring and identifying potential threats inside an Information Technology (IT) System. Typically, ADS collect information from various sources within a CI system using security sensors or agents and correlate those information so as to identify anomaly events. Such sensors though in a CI setting (factories, power plants, remote locations) may be placed in open areas and left unattended thus becoming targets themselves of security attacks. They can be tampering and malicious manipulated so that they provide false data that may lead an ADS or SIEM system to falsely comprehend the CI current security status. In this paper, we describe existing approaches on security monitoring in critical infrastructures and focus on how to collect security sensor - agent information in a secure and trusted way. We then introduce the concept of hardware assisted security sensor information collection that improve the level if trust (by hardware means) and also increase the responsiveness of the sensor. Thus, we propose a Hardware Security Token (HST) that when connected to a CI Host, it acts as a secure anchor for security agent information collection. We describe the HST functionality, its association with a host device, its expected role and its log monitoring mechanism. We also provide information on how security can be established between the Host device and the HST.Then, we introduce and describe the necessary Host components that need to be established in order to guarantee a high security level and correct HST functionality. We, also provide a realization-implementation of the HST overall concept in a FPGA SoC evaluation board and describe how the HST implementation can controlled. Finally, we provide indicative use case scenarios of how the HST can be used in practice to provide a variety of different security services beyond acting as a secure ADS sensor.

Synthetic biology (SynBio) is an interdisciplinary field that has developed rapidly in the last two decades. It involves the design and construction of new biological systems and processes from standardized biological components, networks and synthetic pathways. The goal of Synbio is to create logical forms of cellular control. Biological systems and their parts can be re-designed to carry out completely new functions. SynBio is poised to greatly impact human health, environment, biofuels and chemical production with huge economic benefits. SynBio presents opportunities for the highly agro-based African economies to overcome setbacks that threaten food security: The setbacks are brought about by climate change, land degradation, over-reliance on food imports, global competition, and water and energy security issues among others. With appropriate regulatory frameworks and systems in place, the benefits of harnessing SynBio to boost development in African economies by far potentially outweigh the risks. Countries that are already using GMOs such as South Africa and Kenya should find the application of SynBio seamless, as it would be a matter of expanding the already existing regulations and policies for GMO use.

Typical modern information systems are required to process copious data. Conventional manual approaches can no longer effectively analyze such massive amounts of data, and thus humans resort to smart techniques and tools to complement human effort. Currently, network security events occur frequently, and generate abundant log and alert files. Processing such vast quantities of data particularly requires smart techniques. This study reviewed several crucial developments of existent data mining algorithms, including those that compile alerts generated by heterogeneous IDSs into scenarios and employ various HMMs to detect complex network attacks. Moreover, sequential pattern mining algorithms were examined to develop multi-step intrusion detection. These studies can focus on applying these algorithms in practical settings to effectively reduce the occurrence of false alerts. This article researched the application of data mining algorithms in network security. The academic community has recently generated numerous studies on this topic.

Nowadays one of the issues interesting for researchers of political, social, and economic sciences is to investigate immigration from different angles. Accordingly, they use a diverse range of instruments, different types of graphs, descriptive indices and complex mathematical models. Immigration has always been one of the paths helping humans in their own efforts for getting compatible with the environment and coping with difficulties. Nevertheless, if this issue has been considered as an instrument regulating resources and species automatically, in the present era, its negative aspects have been evident and socioeconomic consequences of immigration in the framework of development economy and security has attracted scholars’ attentions. One of the countries attracting for immigrants particularly in the continent of Africa is South Africa. Statistics indicates that this country is the most attractive one for refugees. Somalis are one of the most important and largest groups seeking refuge in South Africa because they are usually merchants who earn money in the poor places. However, business in the poor places endangers their lives and properties because of high rate of crimes and xenophobia. As a result, the target countries face a lot of socioeconomic and security problems. The present study tries to investigate the issue of Somali immigration using network models.

The presence of wireless communication grows undeniably more prevalent each year. Since the introduction of the IEEE 802.11 standard for Wireless Local Area Networks (WLAN) in 1997, technologies have progressed to provide wireless accessibility to industries and consumers with growing ease and convenience. As the usage of personal devices, such as phones and watches, that connect to the Internet through Wi-Fi increases, wireless attacks on users are becoming more critical. This paper provides a novel attack model to offer an organized and comprehensive view of the possible attacks on WiFi latest security standards. All exiting attacks will be investigated, with emphasis on more recent attacks, such as the KRACK and PMKID Dictionary attacks. This paper will then analyze the technology offered in the new Wi-Fi Protected Access III (WPA3) security scheme and provide a comprehensive security analysis and discussion to determine whether it has addressed the vulnerabilities of its predecessor. An interesting finding of this paper is that WPA3 still lacks to address all the issues existed in WPA2 and explore other mitigations for future research.

Biometric based access control system acts as a weapon against the challenges for reliable authentication mechanism. Although there are many advantages of biometric system, still it is vulnerable to attacks, which decline its security. This leads to propose a new approach to address these open issues and challenges for biometric data security. Smart card have been already used in past with various degree of success to store biometric credentials. Match-on-card biometric framework locks the biometric data inside the microcontroller of the smart card, which leads to minimal risks if card is lost or stolen. It is fast and accurate, balancing security and convenience by never exchanging user data outside the system of smart card and performs fingerprint enrollment as well as matching within a tamperproof environment of smart card.

The article mounts an argument for public theology as an appropriate if not vital adjunct to contemporary education’s addressing of security issues in light of current world events with indisputable religious and arguably quasi-theological foundations. It will briefly expound on the history of thought that has marginalized theology as a public discipline and then move to justify the counter view that the discipline, at least in the form of public theology, has potential to address matters of such public concern in a unique and helpful way. The article will culminate with an exploration of Global Jihadism as a case study that illustrates the usefulness of public theology in understanding it better and so allowing for a response with potential to be more informed and security-assured than is commonly effected.

The article mounts an argument for public theology as an appropriate if not vital adjunct to contemporary education’s addressing of security issues in light of current world events with indisputable religious and arguably quasi-theological foundations. It will briefly expound on the history of thought that has marginalized theology as a public discipline and then move to justify the counter view that the discipline, at least in the form of public theology, has potential to address matters of such public concern in a unique and helpful way. The article will culminate with an exploration of Global Jihadism as a case study that illustrates the usefulness of public theology in understanding it better and so allowing for a response with potential to be more informed and security-assured than is commonly effected.

Achieving water security and availability for all is among the principle agenda of the UN-Sustainable Development Goals. To achieve the goal of water security, particularly in rapidly expanding cities, identification of safe and sustainable water resources is an absolute necessity. The paper conducts an exploratory investigation in the hydro geochemical characteristics of groundwater and thereby, assess the suitability of groundwater as an alternative and reliable resource for public water supply in the Indian city of Surat. A total of 33-groundwater samples, selected on the basis of aquifer depth, land use signatures, were collected from open, bore, dug wells and hand pumps. After the hydrogeochemical analysis, the study evaluated the present state of the groundwater quality and determined the spatial distribution of groundwater quality parameters such as hardness, electrical conductivity, Cl −, pH, SO42-, and NO3 − concentrations. An interpolation technique, known as ordinary kriging, was used to acquire the spatial distribution of parameters of groundwater quality parameters. Based on the permeability index, result showed that 80% of the sampled groundwater quality falls under excellent class i.e. category I with PI value ranging from 1-24%, whereas the rest 20% of the samples has fallen under good class i.e. category II with PI value ranging from 25 to 75% on the suitability of water for irrigation. The results of this study outlines the unsustainability of groundwater for direct consumption, especially without any improved onsite water treatment, but it is appropriate for the irrigation purposes.

Multiple sensor nodes known as detection stations make the sensor networks; each node is light and portable. Every sensor node contains power source, microcomputer, transducer and transceiver. Power source provides power to each node. Micro-computer is used for storing and processing the output coming from the sensors. The transducer is used to generate the signals and the transceiver is used to receive and transmit data to the central computer. Eavesdropping gets facilitated with wireless communication, and it has many useful applications in military, homeland, hostile and uncontrolled environments. So it is prone to the high level of security. The process in which information is gathered to form a summarized type for analysis is known as data aggregation, as it is used to reduce the energy consumption in wireless sensor networks. The security issues have become crucial in data aggregation, especially when gets deployed in hostile and remote environment. In wireless sensor networks many secure aggregations have been proposed. It still faces some resource constrained that’s why new techniques are needed. In our survey we will discuss those approaches and their pros and cons.

The loop and knot securities of 2 braided and 2 monofilament sutures of four diameters (3.0, 2.0, 0, 1) were evaluated with a tensiometer for four 4-throw knots known to be secure with a 2.0 polyfilament suture. Loop security of monocryl 1 is low, being 14.7 + 3.0 Newton (N) for a 3-throw half-knot (H3) and 15.4 + 2.4 N and 28.3+ 10 N for 2 (SSs) and 4-throw (SSsSsSs) symmetrical sliding half-hitches. This is lower than 18, 24, and 46 N for similar knots with vicryl. Polyfilament sutures have excellent knot security for all diameters. Occasionally, some slide to open with slightly lower knot security, especially for larger diameters, although not clinically problematic. Knot se-curity of monofilament sutures was unpredictable for all 4 knots, especially for larger diameters, resulting in many clinically insecure knots. A secure monofilament knot requires a 6-throw knot with 2 symmetrical sliding half-hitches or 2 symmetrical half-knots secured with 4 asymmetric blocking half-hitches. In conclusion, with polyfilament sutures, 4 or 5-throw half-knot or half-hitch sequences result in secure knots. For monofilament sutures, loop and knot security is much less, half-knot combinations should be avoided, and secure knots require 6-throw knots with 4 asym-metric half hitches. This conclusion is valid for gynecologic laparoscopic and open surgery, and for surgery in general.

The introduction of the Internet of Things (IoT), i.e. the interconnection of embedded devices over the Internet, has changed the world we live in from the way we measure, make calls, print information and even the way we get energy in our offices or homes. The convenience of IoT products, like CCTV cameras, IP phones, and oscilloscopes, is overwhelming for end-users. In parallel, however, security issues have emerged and it is essential for infrastructure providers to assess the associated security risks. In this paper, we propose a novel method to detect IoT devices and identify the manufacturer, device model, and the firmware version currently running on the device using the page source from the web user interface. We performed automatic scans of the large-scale network at the European Organization for Nuclear Research (CERN) to evaluate our approach. Our tools identified 233 IoT devices that fell into eleven distinct device categories and included 49 device models manufactured by 26 vendors from across the world.

In the sustainable economy, consumer preferences are gradually coming to prioritise environmentally friendly products and services. A sustainable economy is directly linked to the growth of consumer welfare and environmental culture. The success of environmental projects is largely determined by approaches to the management of complex interconnected objects. Technological integration and the value chain from raw material extraction to the marketing of environmentally friendly products add to the growth factors. In this regard, we formulate the purpose of this study: to generalise the approaches and improve the mechanism of the ecological branding of the industrial complex of a region through conscious ESG transformation. For this purpose, we studied statistics and principles of management systems of Kazakh companies and their stakeholders. We analysed the situation of industrial complexes and their partners in the external environment to identify barriers to the development and implementation of eco-branding tools. The theoretical significance of the study helps to reveal the influence of ecological principles of modern production organisation on the speed of transition to green technologies. Its practical significance is seen in the formation of a system for measuring the level of readiness of companies to promote the ecological branding of a region’s industry outside its country.

Wildlife tourism and wildlife trade may appear juxtaposed, but are two, potentially aligning, in-come generators that could benefit conservation in developing countries. Utilising data sets collated from Madagascar’s Ministère du Tourisme and CITES respectively for the period 2007 to 2018, this study estimated levels of income from wildlife tourism and wildlife trade for Madagascar. Between 2007-2018, tourism reported yearly incomes ranging from a low of US \$1.4 million up to a high of US \$15.7 million. However, it was unclear what percentage of this figure flowed to benefit local communities. Alternatively, using reported networks for the live wildlife trade, the estimated eco-nomic value reaching collectors and/or intermediaries on Madagascar was US $72,299.80 for the period 2007 to 2018. Both revenue generators operated within different geographical areas, with tourism opportunities presenting themselves to communities adjacent NPs, while wildlife trade networks were not restricted to National Parks and operated sporadically across Madagascar. Hence, the economic benefits reached different Malagasy participants across the country. The management of both activities needs great care to ensure that environmental impacts and sus-tainability are core measures on any such activities. Whilst this study shines light on economic values and novel perspectives regarding these two trade types, it also highlighted knowledge gaps. Thus, indicating where much greater research attentions was required to allow better understanding of the specific benefits and risks from engaging with both trade types for local Malagasy people and their environments.

Shear thickening fluids (STF) are a class of fluids whose viscosity significantly rises under external loads. The research on these fluids has been advancing in recent years regarding prospective practical applications, including developing impact-absorbing composites. Following the green agendas governments and legislators advocate, this study investigates the combination of STF and other sustainable materials. Cork is a naturally occurring cellular material with a negative carbon footprint and superior energy absorption properties. With varying concentrations of STF material, cork agglomerates were formed. Notably, the analysed blends are homogeneous, contrasting with previous literary works. A series of experiments were conducted in quasi-static and dynamic conditions to determine the various mechanical responses. STF appears to influence the mechanical behaviour of cork agglomerates by providing softer deceleration rates and dispersing more energy through disaggregation mechanisms.

The continuing development of industrialization and increasing population density has led to the emergence of noise as an increasingly common problem, requiring various types of sound absorption and insulation methods to address it. Meanwhile, the recycling of resources to ensure a sustainable future for the planet and mankind is also required. Therefore, this study investigates the potential of corrugated cardboard as a resource for noise reduction. The sound absorption and insulation performance of non-perforated corrugated cardboard (NPCC) were measured, and modified corrugated boards were fabricated by drilling holes either through the surface of the corrugated board alone or through the corrugated board in its entirety. The sound absorption/insulation performance both of perforated corrugated cardboard (PCC), and perforated corrugated cardboard with multi frequency resonators (PCCM) were measured using the transfer function method and the transmission matrix method. To determine the effectiveness of NPCC, PCC, and PCCM in noise reduction, the sound pressure level was analyzed by applying it to a home blender. The results showed PCCM’s sound absorption and insulation performance to be excellent. On the basis of these findings, we propose the use of PMMC as an eco-friendly noise reduction material.

With the fintech industry growing at an unprecedented rate, it is critical to protect cybersecurity and ensure data privacy. The research presented here offers a thorough examination of the challenges faced by financial technology companies, highlighting the growing risks posed by malware, phishing, and network vulnerabilities. As essential components of a proactive defense plan, the report promotes strong cybersecurity measures like frequent security assessments, encryption, and stringent access controls. The findings highlight how important it is for fintech companies to give cybersecurity equal importance with open and honest data privacy policies in order to win over customers. In order to protect the industry from cybersecurity risks regulatory compliance, intrusion detection systems, and collaborative information sharing are considered essential components. The article advises businesses to include cybersecurity and data privacy into their core business operations and customer relations, highlighting the critical role these factors play in sustaining success in the rapidly evolving fintech industry.

Given the financial demands of attending college, the transition to new living situations, abrupt changes in social support, and overall lifestyle adjustments, college students are at an increased risk of food insecurity (FI) compared to the general population. Collegiate athletes experience an even greater risk of FI as a result of greater time commitments and energy demands associated with their sports. This heightened vulnerability poses a tremendous threat to student-athletes’ academic and athletic achievements. This study aims to address the prevalence and primary determinants of FI among collegiate athletes while providing potential solutions to navigate and alleviate the effects of diminished food security among this demographic. To address these aims, a total of 18 articles were selected from both peer-reviewed and gray literature. The U.S. Household Food Security Survey Module (US-HFSSM) survey tools were predominantly utilized across universities throughout the United States to gather data on FI. Student-athletes reported experiencing FI across various regions of the United States, including universities in northeastern states (n=5), the southwest region (n=3), the southeast region (n=3), the northwest (n=1), and the Midwest (n=1). Overall, FI prevalence rates ranged from 9.9% to 65% and the most significant contributors included limited financial resources, time management, meal plans, and housing location/amenities. These findings highlight a need for screening, education, and intervention to address FI among collegiate athletes.

Grid modernization has been ushered in by rising electricity consumption, deteriorating infrastructure, and increasing reliability concerns for electric utilities. New advances, collectively referred to as the smart grid, include modern electronics, technology, telecommunications, and computing capabilities. Smart grid telecommunication frameworks provide two-way communication to support grid operations. Software-defined networking (SDN) has been proposed as a method of monitoring and controlling telecommunication networks, enabling increased smart grid visibility, control, and security. However, being connected to telecommunications infrastructure means that smart grid networks are exposed to cyber-attacks. Attackers may use unauthorized access to intercept messages, inject false data into system measurements, flood communication channels with false data packets, or target centralized controllers to cripple network control. Defense and security techniques against these threats are constantly evolving, necessitating an up-to-date, comprehensive study analyzing cyber attacks and defense methods for smart grid networks. Previous smart grid security surveys do not contain recent techniques and to our knowledge most, if not all, address only one type of attack type and/or one type of defense. This survey considers the latest security techniques, simultaneous multi-pronged cyber attacks and defensutilityes to meet the challenges of the next-generation SDN smart grid research with the goal of identifying future research needs, describing the open security challenges, and exposing both emerging threats and their potential impact on SD-SG deployment.

The industrial metaverse paradigm is generally a virtual environment that integrates various technologies such as augmented reality (AR) and mixed reality (MR) to enhance business operations and processes. It aims to streamline workflows, reduce error rates, improve efficiency, and provide a more engaging experience for employees. The promise of the industrial Metaverse to drive sustainability and resource efficiency is compelling. Utilizing advanced technologies like the Industrial Metaverse is essential for staying competitive in today’s rapidly evolving business environment. However, the environmental impact of the technologies underpinning the industrial metaverse, like data centres and network infrastructure, should not be overlooked. The ecological footprint of these technologies must be considered in the sustainability equation. Researchers have warned that by 2025, without sustainable AI practices, AI will consume more energy than the human workforce, significantly offsetting carbon-zero gains. As the metaverse persists in evolving and gaining momentum, it will be necessary for companies to prioritize sustainability and explore new ways to balance technological advancements with environmental stewardship. However, recent studies have conjectured that the Metaverse holds the potential to reduce carbon emissions, as digital replacements for physical goods become more prevalent and physical activities like mobility and construction are reduced. However, the specific extent to which this substitution can alleviate environmental concerns remains understudied, presenting a knowledge gap in understanding the real-world impact of digital replacements. Thus, the objective of this paper is to provide a comprehensive review of the industrial metaverse as well as explore the environmental impact of the industrial metaverse. The methodological approach is that of integrative literature review design wherein multiple sources from web science and databases such as ACM library, IEEE Library, and Google Scholar, were analysed to provide a comprehensive understanding of the developments in the industrial metaverse. Specifically, firstly by considering the Industrial metaverse architecture we elucidate the concept of the "industrial metaverse" and the associated enabling technologies. Secondly, an exploration through discussion, of the prevalent use cases and deployment of the emerging industrial metaverse. Thirdly, exploration of the impact of the industrial metaverse on the environment. In the fourth instance, we address novel security and privacy risks as well as upcoming research challenges, keeping in mind that the industrial metaverse is based on a strong data fabric. Results point to the Industrial Metaverse as having both positive and negative environmental effects by energy consumption, e-waste, and pollution. Overall research, however, indicates that most industrial metaverse applications have a positive environmental impact and subsequently trend toward sustainability. Ultimately for sustainability in the industrial metaverse, enterprises may consider utilizing renewable energy sources and cloud services. Furthermore, examining the effects of products on the environment as well as creating a circular economy.

With the development of Internet, big data and artificial intelligence technology, personal information protection has become the focus of social attention. The legal boundary of data protection has become increasingly prominent, involving the collection, storage, use, transmission and disclosure of personal information. This paper aims to explore the legal boundary of data protection, analyze the legal basis, legal principles and legal provisions of personal information protection, and put forward corresponding legal suggestions, in order to provide reference for the improvement of China's data protection legal system.

Lime application with other complementary sustainable management practices increases crop yield, but liming is modestly applied in Serbia. This study investigated the influence of liming (1000 kg/ha) combined with the common application of mineral fertilizers on maize yield and the chemical properties of Pseudogley soil. The experiment was conducted near Kraljevo, Western Serbia, on maize hybrid ZP 606, sown in a two-year monoculture. The experiment had three treatments: fertilizer, fertilizer+lime, and control treatment. The soil is acid, poor in humus, and contains an increased content of mobile aluminum. There was a significant increase in yield under the fertilizer and lime+fertilizer treatments, compared with the control. The yield of maize in the limed treatment was 4.4–9% higher than in the fertilizer treatment. The positive effects of liming on soil are related to an increase in pH, base saturation, and available phosphorus and a decrease in available aluminum. In the fertilizer treatment, there was a small decrease in pH and base saturation, whereas the amount of aluminum remained high, indicating that further application of fertilizers without lime can increase the aluminum content and foster its toxicity. The long-term sustainability of maize production in Serbia should include liming as a regular management practice on Pseudogley soil, with the utilization of smaller doses of lime because of the potential CO2 effects. To improve soil health, food, and environmental security, and incorporate new crops, developing a framework promoting liming as a sustainable management practice is of high importance.

The Cantareira Water Producer System (CWPS), which supplies water to the most populous Brazilian region, Metropolitan Region of São Paulo (MRSP), faces significant challenges due to climate change, threatening its water security. Climate change affects the hydrological cycle affecting water availability. The CWPS is vulnerable to periods of scarcity and instability due to increased climatic variability and increasing water consumption. Current water resource management systems do not consider the impacts of climate change, making it difficult to ensure water security in the future. This study analyzes the impact of climate change on the availability of CWPS using hydrological modeling approach with forecast precipitation data by CMIP6 and assessment of existing systems. The finds will provide a comprehensive understanding of the challenges faced by CWPS in the context of climate change, as well as support strategies and adaptive measures to ensure water security for MRSP.

Image encryption based on chaotic maps is an important way to ensure the secure communication of digital multimedia on the Internet. To improve the encryption performance and security of image encryption systems, a new image encryption algorithm is proposed by employing a compound chaotic map and random cyclic shift. Firstly, an improved Hybrid chaotic system is designed by coupling Logistic, ICMIC, Tent, and Chebyshev maps (HLITC). Comparison tests with previous chaotic maps in terms of chaotic trajectory, Lyapunov exponent, and Kolmogorov entropy illustrate the new hybrid chaotic map has better chaotic performance. Then the proposed HLITC chaotic system is used to develop a new chaotic image encryption scheme with the double cyclic shift. The improved HLITC chaotic system is performed to generate key sequences used in the image scrambling and diffusion stage. The spiral transformation controlled by chaotic sequence is used to scramble the pixels of the plaintext image, while the XOR operation based on a chaotic map is used for pixel diffusion. Extensive experiments of statistical analysis, key sensitivity, and keyspace analysis are conducted. Experimental results show the proposed encryption scheme has good robustness against brute force attacks, statistical attacks, and differential attacks, and is more effective than many existing chaotic image encryption algorithms.

Limnospira maxima is widely cultivated due to its abundance of proteins, carbohydrates, vitamins, minerals, essential fatty acids, and phycobiliproteins. However, limited information, high production costs, and nitrogen source limitations have hindered the optimal utilization of this cyanobacteria. The main goal of this study was to address these limitations by identifying ideal cultivation parameters to maximize yields, reduce costs, and contribute to global food security. It was demonstrated that the white and yellow light spectra are the most suitable for cultivating L. maxima, and the use of KNO3 as a nitrogen source proved to be the most cost-effective on a large scale. Nitrogen deficiency stimulates the production of dry biomass but also affects the concentration of key pigments such as chlorophyll and phycocyanin. A notable characteristic of L. maxima is its adaptability and survival capability in various environmental conditions, including nitrogen-deficient environments. This resilience is achieved through the degradation of phycobilisomes and the storage of glycogen. By identifying the optimal growth conditions and understanding the physiological responses of L. maxima, cultivation practices can be improved to be more efficient and sustainable.

This study provides an in-depth exploration and analysis of the complex aspects of Public Key Cryptography, focusing on the vulnerabilities, potential attack vectors, and the consequential impacts of key compromises. The discussion extends beyond the conventional technical paradigms, offering a holistic perspective that intertwines theoretical insights with practical implications, thereby contributing to a more comprehensive understanding of cryptographic security. The paper delves into the intricacies of brute-force attacks, elucidating the significance of key sizes, encryption algorithms, and the inherent resilience of cryptographic systems against such attacks. It further examines the ramifications of key compromises in Public Key Cryptography, highlighting the repercussions on confidentiality, integrity, trust, and legal and reputational standing. The study underscores the importance of maintaining the security and integrity of cryptographic keys and provides practical recommendations to mitigate the risks associated with key compromises. These include enhanced awareness and education, stringent protection of sensitive information, proactive risk management, strict compliance with regulations and standards, and the promotion of a security-centric culture. The insights gleaned from this study are pivotal in informing future research, policy development, cryptographic implementations, and the cultivation of secure practices, fostering a more secure, resilient, and ethical digital environment in the face of an evolving threat landscape. The contributions of this study are instrumental in advancing the field of cryptography and enhancing the overall understanding of the challenges and considerations inherent in implementing robust cryptographic practices.

In recent years the yield of fruits and vegetables have been decreasing in Colombia, threatening national food security. Analysis of crop production data may lead to identifying cropping systems that have shown better adaptability to changes in climatic and non-climatic factors associated with agricultural production. The open database AGRONET keeps data of the agricultural activities conducted in Colombia, allowing to find the information organized by crops, regions and years; each row of the database registers farm information in Colombia. Aiming to identify resilient crops systems, agricultural data of fruits and vegetables were analyzed. First, trends in crop production were studied by year and locations, detecting the regions and crops with highest yields in the period from 2006 until 2020. Then, mixed linear regression and principal components analysis were applied to elucidate the relation between non-climatic factors and crop yield. In Colombia, vegetable production was more efficient than fruits, observing yields of 10.23 and 13.33 t ha^-1, respectively. On the other hand, the Colombian central region showed high yields for vegetables, while for fruits this was exhibited in northern and eastern locations. In the present study, yield variation responded to changes in the location of crop systems, while years had no effect on vegetable production. Furthermore, the price of the agricultural product and the cost of fertilizers were associated with the yield of the analyzed crops systems. In Colombia, carrot, cabbage, tomato papaya and pineapple are resilient crops whose yield increases especially by the regions where they are cultivated.

Abstract Introduction. Burnout syndrome develops as a consequence of chronic stress among employees. The study objectives were to examine burnout syndrome and to evaluate the quality of life among security employees of the professional private security sector in Central Serbia. Methods. A multicenter cross-sectional questionnaire-based study was performed. The questionnaire for staff employed at institutions who are in direct contact with people (Human Services Survey, MBI-HSS) and Short Form 36 Health Survey-(SF-36). Results. A total of 353 respondents participated in the study. The response rate was 80%. Approximately one-third (32.6%) had symptoms of total burnout, and a much higher number of responders had a moderate or high level of burnout on individual subscales:- depersonalization (high 82.4%, moderate 16.2%) and emotional exhaustion (high 66.3%, moderate 19.8%) and, slightly more than one-third (34.5%) had low personal achievement, while about one-third (32.9%) had moderate personal achievement. Female sex and older age were associated with a higher risk of total burnout and the development of emotional exhaustion. Male sex, higher education, and managerial position were associated with higher personal achievement and lower risk of total burnout. Male sex, marital union, two or more children, and direct contact with clients were significantly associated with a lower quality of life of employees. Conclusion. Female sex and older age were associated with a higher risk of total burnout and the development of emotional exhaustion. Male sex, university education and managerial position were associated with greater personal achievement and were protective factors in relation to the development of burnout. Male sex, marital union, two or more children, and direct contact with clients were significantly associated with lower quality of life of employees. Keywords: burnout syndrome; security employees; professional private sector; quality of life

Tourism activities generally have a ∩-type lock on the level of tourism ecological security in an area, but when applied to the border areas of China, there are certain specificities in the spatial evolution of tourism ecological security (TES) compared to traditional findings. This paper measures tourism ecological security in China’s border areas from 2009 to 2020 by using the DPSIR model with the superefficient SBM-DEA and analyzes the spatial differences, evolutionary characteristics, and driving factors of tourism ecological security in border areas by using Pearson’s correlation coefficients, center of gravity models, and geographic probes: (1) The overall tourism ecological security index of China’s border provinces is relatively good. Tourism activities do not completely affect the traditional “∩ lock” of the border provinces. The tourism ecological security level of the border provinces presents three spatial-temporal changes (“∩” type, “U” type, “\” type) and four evolution trends (“high–high–high”, “middle–middle–medium”, “medium–low–low”, and “low–low–low”). (2) The overall tourism ecological security level in border areas is polarized between high and low levels, and the ecological security efficiency of the three large areas is spatially characterized as “Southwest Area > Northeast Area > Northwest Area”, and the center of gravity of ecological security is mostly concentrated in Xinjiang, Tibet, and Neimenggu, where the ecological security level is higher. (3) Social and environmental factors are the main factors that influence tourism ecological security in border areas, while economic factors account for a smaller proportion. Accordingly, this thesis also proposes the driving mechanism of the ecological security of tourism sites in border areas in China with a view to providing theoretical support for policy formulation.

Driven by the rapidly growing demand for information security, covert wireless communication conceived as one of the essential technology has attracted tremendous attention. However, traditional wireless covert communication is continuously exposing the inherent limitations that challenge deploying in environments with a large number of obstacles, such as cities with high-rise buildings. In this paper, we propose an intelligent reflecting surface (IRS) assisted covert communication system (CCS) with a friendly UAV, where the UAV generates artificial noise (AN) to interfere with the monitors. Furthermore, we model the power of AN emitted by UAV as an uncertainty model, with which the closed-form detection error probability (DEP) on the covert wireless communication for the monitor is derived. Under the derived DEP, we formulate the optimization problem to maximize the covert rate, and an iterative algorithm is designed to solve the optimization problem to obtain the optimal covert rate by using Dinkelbach method. Simulation results show that the proposed system achieves the maximum covert rate when the phase of the IRS units, the trajectory, and the transmit power of the UAV are jointly optimized.

The main characteristics of blockchains, such as security and traceability, have enabled their use in many distinct scenarios, such as the rise of new cryptocurrencies and decentralized applications (dApps). However, part of the information exchanged with the typical blockchains is public, which can lead to privacy issues. To avoid or mitigate these issues, some blockchains are applying mechanisms to deal with data privacy. Trusted Execution Environments, the basis of confidential computing, and secure Multi-party Computation are two technologies that can be applied in that sense. In this paper, we analyzed seven blockchain technologies that apply mechanisms to improve data privacy. We defined seven technical questions related to common requirements for decentralized applications and, to answer each question, we reviewed the available documentation and gathered information from chat channels. We briefly present each blockchain technology and the answers to each technical question. Finally, we present a table summarizing the information and showing which technologies are more prominent.

The spiral tube heat exchange is widely used in large-scale liquefaction process. However, the research on the friction pressure drop of the two-phase flow in the spiral tube is limited, especially for the offshore sloshing condition. In this paper, an experimental system is designed and built, and the effects of sloshing form (roll, pitch, heave), sloshing period (5-15s), mass flux (200-800 kg/(m2·s)), vapor quality (0.3-0.9) and operating pressure (2-4 MPa) on friction pressure drop of methane/ethane (C1/C2) mixture in spiral tube are studied. The result shows that the growth rate of time-averaged friction pressure drop during condensation under sloshing condition is less than 0, which indicates that sloshing will lead to drag reduction. And under the three sloshing parameters, the growth rate of time-averaged friction pressure drop of C1/C2 is reduced by-5.99%%, 5.97% and -6.70% respectively.

The growth in the Internet of Things (IoT) devices in the healthcare sector enables the new era of the Internet of Medical Things (IoMT). However, IoT devices are susceptible to diverse cybersecurity attacks and threats that lead to negative consequences. Cyberattacks can harm not just the IoMT devices being used but also human life. Currently, several security solutions are proposed to enhance the security of the IoMT, which uses machine learning (ML) and blockchain. ML can be used to develop detection and classification methods to identify cyberattacks targeting IoMT devices in the healthcare sector. In addition, blockchain technology enables a decentralized approach to the healthcare system and eliminates some disadvantages of a centralized system, such as a single point of failure. This paper proposes a resilient security framework integrating a Tri-layered Neural Network (TNN) and blockchain technology in the healthcare domain. The TNN detects anomalies in data measured by medical sensors to find fraudulent data. Therefore, cyberattacks are detected and discarded from the IoMT system before data is processed at the fog layer. In addition, a blockchain network is used in the fog layer to ensure that the data is not altered, boosting the integrity and privacy of the medical data. The experimental results show that the TNN and blockchain models produce the expected result. Furthermore, the accuracy of the TNN model reached 99.99% on the F1-score accuracy metric.

It is shown by numerical modelling that anisotropic diffusion can compensate and even overcome diffusion broadening - the main limiting factor of devices working at atmospheric pressure. The thickness of ion clouds coming out of the ionisation chamber is reduced ~ 1000 times in the ADMA inlet increasing the resolution. This finding has a great potential that enables construction of a device with resolution close to that of currently available desktop ion separation devices – high pressure mass spectrometers, but with much lower cost of manufacture and with smaller dimensions. Comprehensive numerical modelling along with mathematical analysis of physical concepts enables reduction of the footprint and manufacturing costs. Modelling determined that the resolving power (RP) potential of the ADMA is greater than the RP of currently available on the market devices for the airport security market. The ADMA technology enables very fast detection of threats; at least 100 times faster than currently used in Ion Mobility Spectrometers (IMS). This potentially allows an increase in passenger throughput in airports.

The Internet of Things (IoT) has become one of the most attractive domains nowadays. It works by creating a special network between physical devices such as vehicles, home equipment, and other items. In recent days, the common technologies of communication such as Wi-Fi and 2G/3G/4G cellular are insufficient for the IoT networks because they are designed to serve appliances with immense processing capabilities such as laptops and PCs. Moreover, most of these technologies are centralized and use an existing infrastructure. Currently, the new communication technologies such as Z-Wave, 6LowPAN, and Thread are dedicated to the IoT and have been developed to meet its requirements. These technologies can handle many factors such as range, data requirements, security, power demands, and battery life. Nevertheless, the security issues in IoT systems have major concerns and matters because vulnerabilities in such systems may result in fatal catastrophes. In this paper, an enhanced IoT security framework for authentication and authorization is proposed and implemented to protect the IoT protocols from different types of attacks such as man-in-the-middle attack, reply attack, and brute force attack. The proposed framework combines an enhanced token authentication that has identity verification capabilities and a new sender verification mechanism on the IoT device side based on time stamp, which in turn can mitigate the need for local identity verification methods in IoT devices. The proposed IoT security framework is tested using security analysis with different types of attacks compared with previous related frameworks. The analysis shows the high capability of the proposed framework to protect IoT networks against many types of attacks compared with current available security frameworks. Finally, the proposed framework is developed using Windows application to simulate the framework phases, check its validity through the real network, and calculate the payload time is adds.

Nowadays the practice of developing algorithms to maintain the confidentiality of data shows that there is a lack of some features, such as velocity, predictability, etc. Generating pseudorandom numbers is one such problem that lies in the basement of many algorithms, even in hardware microprograms. An unreliable generator can cause cyberattacks on it, despite the security in the upper layers. At the same time, the algorithm should be fast enough to provide uninterrupted circuit work for the entire system. The paper presents a new algorithm generating pseudorandom numbers on cellular automata, which is not only fast and easy-repeating, but unpredictable enough and can be used in cryptographic systems. Using the NIST statistical test suite for random and pseudorandom number generators (PRNG), it is shown that the presented algorithm is more than three times superior to the state-of-the-art methods and algorithms in terms of ? − ?????. A high level of the presented algorithm’s parallelization allows for implementation it effectively on calculators with parallel structure. CPU-based architecture, FPGA-based architecture, CUDA- based architecture of PRNG and different PRNG implementations are presented to confirm high performance of the proposed solution.

Background: Machine learning has revolutionized situational awareness during disaster management by classifying, clustering, and predicting impacted locations and people. Despite its importance, no review has been conducted on machine learning tools for food assistance efforts during emergency or non-emergency situations. The purpose of this scoping review is to address that gap. Methods: Keywords were defined within the concepts of food assistance and machine learning. After the database searches, PRISMA guidelines were followed to perform a partnered, two-round scoping literature review. Text mining and Latent Dirichlet Allocation topic modeling algorithms were used to determine trends. Results: 28 articles met criteria and were included in the analysis. The types of study designs included: model development (42.9%), non-study (i.e., text and opinion) (28.6%), qualitative research (14.3%), case study (10.7%), and meta-analysis (3.6%). There were no quantitative studies. The machine learning tools’ main functions were improving SNAP programs (32.1%), detecting needs and resources (25%), predicting food insecurity (21.4%), and situational awareness of current food insecurity issues (21.4%). None of these studies took place during a disaster or explicitly addressed emergency mitigation, preparedness, or recovery. All of the studies were in early phases of development and implementation. Conclusion: Machine learning tools for improving situational awareness, resource allocation, policymaking, and prediction have the potential to improve food assistance, but there is a lack of implementation and evaluation during all disaster phases. Also needed is more formative work on generating food-related queries and defining variables and features of food security.

This work attempts to answer in a clear way the following key questions regarding the optimal initialization of the Sysmon tool, towards the identification of Lateral Movement in the MS Windows ecosystem. First, from an expert’s standpoint and with reference to the relevant literature, what are the criteria of determining the possibly optimal initialization features of the Sysmon’s event monitoring tool, which are also applicable as custom rules within the config.xml configuration file? Second, based on the identified features, how can a functional configuration file, able to identify as many LM variants as possible, be generated? To answer these questions, we relied on the MITRE ATT&CK knowledge base of adversary tactics and techniques, and focused on the execution of the nine commonest LM methods. The conducted experiments, performed on a properly configured testbed, suggested a great number of interrelated networking features, that were implemented as custom rules in the Sysmon’s config.xml file. Moreover, by capitalizing on the rich corpus of the 870K Sysmon logs collected, we create and evaluate in terms of TP and FP rates an extensible Python .evtx file analyzer, dubbed PeX, which can be used towards automatizing the parsing and scrutiny of such voluminous files. Both the .evtx logs dataset and the developed PeX tool are provided publicly for further propelling future research in this interesting and rapidly evolving field.

Countries in West Africa are adversely affected by climate change (erratic rainfall and rising temperature) resulting in floods, desertification, drought and sea level rise. These events are anticipated to have negative impacts on agricultural development on the continent, ultimately, contributing to food insecurity and environmental degradation. This implies that the production capacity of agrarian communities is unable to meet the food demand of the growing urban population. Can sustainable and innovative urban farming technology such as aquaponics achieve food security as well as sustainable development in countries vulnerable to climate change? This study uses inferential statistic to examine the plant growth performance in micro-scale aquaponics and specific growth rate per day (SGR) for the fish growth performance vis-à-vis conventional urban farming production. A quantitative analysis use to examine the barriers to adoption based on survey of (five) urban aquaculture practitioners in Lagos, Nigeria. Literature review was use to assess the economic feasibility of a small-scale aquaponics system in developing countries based on Net-Discounted Benefit-Cost Rate (DBCR). The results suggest that aquaponics can improve food security through fish and vegetable production and it is likely that urban farming practitioners will adopt the technology if support mechanism are in place. Aquaponics systems present a novel opportunity to promote environmental conservation as well as sustainable food production and consumption in urban areas in Western Africa if adequate financial credit and knowledge transfer is provided.

In the age of next-generation computer, the role of the cloud, the internet and smart devices will become stronger. These days we all know the word smart well. This word is often used in our daily lives. The Internet of Things (IoT) will generate a variety of information from a variety of resources. It can store big data in the cloud. Fog computing acts as a signal between cloud and IoT. Fog extensions in this framework apply to material under IoT. IoT devices are called Fog nodes, which can be accessed anywhere within the network range. A blockchain is a novel way of recording in a secure sequence. Creating a new framework in the development of Internet of Things is one of the critical problems of wireless communication where solving such a problem can lead to continued growth in the use and popularity of IoT. Proposed research creates a framework for providing a framework for middleware on the internet of smart devices network for the internet of things using blockchains technology. Our great offering connects new research that integrates blockchains into the Internet of Things and provides secure Internet connection for smart devices. Blockchain (BC) Internet of Things (IoT) is a new technology that works with low-level, distributed, public and real-time leaders to maintain transactions between IoT sites. A blockchain is a series of blocks, each block being linked to its previous blocks. All blocks have cryptographic hash code, previous block hash, and its data. Transactions in BC are the basic components used to transfer data between IoT nodes. IoT nodes are a variety of portable but smart devices with embedded sensors, actuators, systems and the ability to communicate with other IoT nodes. The role of BC in IoT is to provide a process for processing secure data records using IoT nodes. BC is a protected technology that can be used publicly and openly. IoT requires this type of technology to allow secure communication between IoT nodes in different environments. Events in BC can be tracked and monitored by anyone who is certified to communicate within IoT.

Bangladesh has achieved tremendous progress in the fisheries sector that is making evidential contribution to food security, nutrition and livelihoods. Based on secondary data collected from the Department of Fisheries, Bangladesh and related un-published grey literature, this paper highlights the performance and challenges of the fisheries with emphasis on COVID-19 impact as well as the significance of this sector for achieving the Sustainable Development Goals (SDGs). The total fish production is increased more than six times over the last three decades (7.54 to 43.84 lakh MT) due to the dissemination of improved culture techniques and extension services. Inland closed water contributions have been increasing to 16.24%, while inland open water have declined 10.23% and marine fisheries have dropped 6.27% over the past 18 financial years (2000-2001 to 2018-2019). COVID-19, a major health crisis has also affects various issues associated with aquatic resources and communities. Transportation obstacles and complexity in the food supply, abstraction to start production, labour crisis, sudden illness, poor consumer demand, commodity price hike, creditor's pressure and reduced income were identified as affecting COVID-19 drivers. The combined effect of these drivers poses a significant threat to people’s income (SDG1- eliminate poverty), nutrition (SDG2- erase hunger), food security (SDG3- good health and wellbeing, and SDG12- responsible consumption and production) that demands comprehensive actions. Several recommendations have been elicited, which are important to implement for the achievement of SDGs as well management and imprvement of the aquatic sector (SDG14- life below and SDG16- life above water) .

In Mexico, it is estimated that due to the economic system the overexploitation of natural resources, environmental impacts and health have been generated, with high rates of overweight and obesity. This review analyzes the impacts on food safety, environmental health, and the economy in Mexico before and during the COVID-19 contingency. Derived from the analysis, among the lessons learned we can include: the health contingency due to COVID-19 had negative repercussions on food security, environmental health and the economy, which require the promotion of public policies (health, environment and economy) and migrate to a health prevention system and an agroecological model, which includes multidisciplinary and intersectoral interventions (government, academia, researchers, civil society organizations, business groups and citizens themselves) to reform and enforce the right to enjoy adequate food and a healthy environment. The contingency due to COVID19 has shown us that this must go from an ideology to being a reality and the lessons learned will have to focus on promoting an innovative and ethical culture of generating an economy, with a gender balance, resilience to climate change, management transparent technology and a priority in health and this will lead to progress in the food security of the population.

To bring to the fore the aim of this research, effects of fluctuating temperature, was measured against food and nutrition security in the region using food production index, and undernourished population growth rate as proxies; controlled over share of arable land, irrigation, population and labour share for agriculture. Dynamic panel of generalized method of moments (GMM) was adopted, the period 2000 to 2016 were considered and 29 countries in sub-Sahara Africa were selected within the empirical framework of global water balance as mentioned by Rai and Singh (2012). Findings from the study reveals that the short run effect of temperature increase in degrees pose at least -3.1% negative and significant impact effects on the food production while the long run elasticity hits -7.5% and the controlled effect on arable land revealed a positive impact on the food production to the tune of 3.9%. Contrarily, arable land expansion reduces the under nourished population by -8.55%. Population increase on the other hand increases undernourished population in the region to the tune of 11.95%. The study therefore recommended expansion in the arable land and encourages population control policy in order to negate the undesired effects of temperature on food and nutritional security.

Security patterns encompass security-related issues in secure software system development and operations that often appear in certain contexts. Since the late 1990s about 500 security patterns have been proposed. Although the technical components are well investigated, the direction, overall picture, and barriers to implementation are not. Here, a systematic literature review of 240 papers is used to devise a taxonomy for security pattern research. Our taxonomy and the survey results should improve communications among practitioners and researchers, standardize the terminology, and increase the effectiveness of security patterns.

One of the special trends in health care is the increasing availability of data and services to the cloud, especially for convenience (for example, providing a complete patient medical record without interruption) and savings (for example, economic issues). Management of health care data). However, there are limitations to using common cryptographic prototypes and access control models to address security and privacy concerns in an increasingly cloudy environment. In this paper, we explore the potential and capacity of using China's Blockchain technology to protect health care data hosted in the cloud. We also explain the real challenges of such an approach and further research is needed. Health care is a highly data-dependent domain, with large amounts of data being created, published, stored and accessed daily. For example, data are created when a patient undergoes a number of examinations (such as computed tomography or computed tomography scans) and the data need to be sent to the radiologist and then to a physician. The visit results are then stored in the hospital, and then need to be accessed later by another physician at another hospital within the network. It is clear that technology can play an important role in improving the quality of care for patients (for example, using data analytics to make informed medical decisions) and potentially costing more by allocating resources more efficiently in terms of personnel, equipment, etc. , Reduce. For example, paper-based data extraction is difficult to extract into systems (for example, it is costly and may involve data entry errors), archiving them and accessing them as needed is costly. These challenges may cause medical decisions to be incomplete, requiring repeated tests for missing information or missing data stored in another hospital in another state or country (at the expense of increased costs and no convenience). (For patients) and so on. Because of the nature of the industry, it is important to ensure the security, privacy and integrity of health care data. As a result, there is definitely a need for a secure and secure data management system.

In this COVID-19 pandemic, the use and dependency on Internet has grown exponentially. The number of people doing online activities such as e-learning, remote working, online shopping and others have increased. This has also led to increased vulnerability to cyber crimes. Cyber security attacks have become a serious problem. The common types of cyber security attacks are phishing, malware, ransomware, social engineering, identity theft and denial-of-service. The attackers target the victims in order to get their credential information or financial benefits. Those people who are doing online activities are vulnerable to cyber threats. This is because the network is not safe. The attackers are able to code according to the weaknesses of the Internet. Once the attackers hack into the devices, they have the root access and can do whatever they want to do with the device. In this research paper, the concept of cyber security attack and detailed research about real attacks are discussed. This is followed by detailed review about the recent cyber security attacks with a critical analysis. Moreover, the research paper will be proposing the latest research contribution of cyber security during COVID-19 and the implementation scenario which will give the examples about how the companies maintain privacy as well as the limitations. Then, the paper will be discussing the reasons that people are vulnerable to cyber security and the unique solution to the problems stated. Finally, this paper will conclude with an in-depth analysis and future direction for cyber security research.

The world is currently experiencing COVID-19, one of the worst pandemics that have happened in this century, affecting 10.7 million people worldwide. It has caused massive growth in the number of employees working from home. However, employees have minimal cybersecurity resources unlike organizations with security teams protecting them against attacks. Hence, cybersecurity plays an important role as users can be easily targeted by cybercriminals. This paper examines how cyberattacks have increased during this pandemic and shows how greatly they have affected health organizations, individuals and social networking applications. Results of the attacks include data breaches, false announcements and operations being disrupted. Attacks occurring during this pandemic and how they were handled are also critically discussed. The existing contributions do touch on related attacks but do not provide in-depth solutions regarding the issues. Even though there are many works and findings that were done previously, technology is ever evolving. Therefore, we need to be well versed with current and future issues and provide the latest mechanisms to prevent cybersecurity threats from occurring. On our share, we intend to present our findings on the challenges being faced by the population and its increasing threats as well as presenting unique solutions that can help organizations or related persons understand or spread awareness on the importance of cybersecurity. Through the research performed in this paper, it is found that there are many ways these issues can be alleviated. However, the issue is that there is significant lack of action and investment in terms of actual implementation and application of the available solutions.

The rapid growth of network services, Internet of Things devices and online users on the Internet have led to an increase in the amount of data transmitted daily. As more and more information is stored and transmitted on the Internet, cybercriminals are trying to gain access to the information to achieve their goals, whether it is to sell it on the dark web or for other malicious intent. Through thorough literature study relating to the causes and issues that are brought from the security and privacy segment of wireless networks, it is observed that there are various factors that can cause the networks to be an insecure; especially factors that revolve around cybercriminals with their growing expertise and the lack of preparation and efforts to combat them by relevant bodies. The aim of this paper is to showcase major and frequent security as well as privacy issues in wireless networks along with specialized solutions that can assist the related organizations or the public to fathom how great of an impact these challenges can bring if every related stakeholder took a step in reducing them. Through this paper it is discovered that there are many ways these challenges can be mitigated, however, the lack of implementation of privacy and security solutions is still largely present due to the absence of practical application of these solutions by responsible parties in real world scenarios.

The tourism sector in general and the hotelier in particular face the challenge of managing appropriate measures to deal with the covid-19 pandemic. In this sense it is useful to know what the measures are most demanded by the clientele. This research, by analyzing the variance (ANOVA) of a factor concluded that women are more demanding than men in terms of the level of demand in relation to the measures to be taken in hotels. This, as a practical application, allows to know more accurately the expectations, demands and demands of the client segmented by sex, in order to satisfy and improve the tourist experiences.

Crop domestication and breeding considerably increased productivity over centuries, but simultaneously involved unconscious selection against ‘selfish plant behavior’. Paradoxically, modern-day crop breeding largely enhances individual plant-fitness. As agriculture relies on community performance, embracing an “Agroecological Genetics and Genomics” viewpoint might maximize communal yield by matching crop genotypes to target environments.

Counterfeiting and theft have always been problems that incur high costs and results in considerable losses for the international markets. In this research paper, we will address the issue of counterfeiting while using RFID technology in retailer systems or other industries by presenting a new anti-counterfeiting and anti-theft system for the retailer market. This system will address the two above mentioned issues and provide a solution that can save the retailer systems millions of dollars yearly. This proposed system will achieve the objective of preventing or minimising the counterfeiting and theft of tagged products. At the same time, it will provide a strong indication for suspiciously sold or obtained items. Furthermore, we conducted a security analysis to prove the correctness of our protocol on the basis of the strand spaces.

Blockchain (BC) in the Internet of Things (IoT) is a novel technology that acts with decentralized, distributed, public and real-time ledger to store transactions among IoT nodes. A blockchain is a series of blocks, each block is linked to its previous blocks. Every block has the cryptographic hash code, previous block hash, and its data. The transactions in BC are the basic units that are used to transfer data between IoT nodes. The IoT nodes are different kind of physical but smart devices with embedded sensors, actuators, programs and able to communicate with other IoT nodes. The role of BC in IoT is to provide a procedure to process secured records of data through IoT nodes. BC is a secured technology that can be used publicly and openly. IoT requires this kind of technology to allow secure communication among IoT nodes in heterogeneous environment. The transactions in BC could be traced and explored through anyone who are authenticated to communicate within the IoT. The BC in IoT may help to improve the communication security. In this paper, I explored this approach, its opportunities and challenges.

This research work focused on the risks we are faced with on our day to day activities, either directly or indirectly, which can gradually accumulates and results to communal crisis, religious crisis, socio-economic agitations and tribal crises. Nasarawa Eggon Local Government Area of Nasarawa State was used as case study and a well structure close–ended questionnaire was used for data collection as it relates to Controlled Self Risk Assessment (CSRA) and linear programming technique was used to analyze. The results proved that many of this processes were neglected in these communities, making them to be prone to incessant communal crisis. The study recommend that Government should strongly, as a matter of urgency address the unemployment rate, distribution of political position, schools, primary health care and equip security personnel with the modern technology facilities, which happen to record the highest risk level.

Fisheries in Cambodia play an important role in supporting household food security and livelihoods throughout the country. Inland fisheries production is largely dependent on numerous ecosystem services, particularly the flood waters of the Tonle Sap Lake basin, which has been degraded from increased fishing pressure because of population growth and a rising demand for fish. To address the dual problem of food insecurity and overfishing, an integrated food security and climate change program involved the promotion of small-scale aquaculture through semi-intensive pond management. The objective of this study is to examine perceptions of small-scale aquaculture by participants in this program in order to assess the potential for aquaculture to contribute to household food security and conservation of the Tonle Sap Lake ecosystem. Focus group discussions and a household survey were conducted among current and previous fish farmers. Results demonstrate that most farmers continue to practice small-scale aquaculture as a means to supplement household food availability and income. Numerous barriers to adoption of small-scale aquaculture were identified, including access to water, prices of commercial fish feed, selling price of fish in markets, and concerns about profitability. Seasonal water scarcity is the most prominent challenge in promoting aquaculture technologies, so aquaculture development should be expanded in areas where there are abundant supplies of water, or where use of water storage techniques are feasible. Aquaculture technology appears to have the potential to contribute to food security, nutrition, and household income, and the expansion of the practice of small-scale aquaculture has the potential to reduce fishing pressure on the wild fisheries of the Tonle Sap Lake.

Climate variability and change has been found to be one of the factors that affect economies leading to food insecurity in various parts of the world. Kenya is no exception. This study looks at how climate variability has contributed to food insecurity in Kisii County, Kenya. The objectives of this study is therefore to, (i) to examine the rainfall and temperature trends in Kisii County for a period of approximately 30 years, (ii) to examine the effect of climate variability on food production and (iii) to assess the perception of local farmers on weather and climate information, (iv) to evaluate the coping strategies adopted at to bridge the gap on food deficit at different household level and (v) to assess the nutritional status of children and the elderly. The study was conducted in two sub-counties of Kisii County; Marani and Bomachoge Chache. The data used was mainly rainfall and temperature data from meteorological stations and sample data gathered from selected groups. The study population comprised of children between 6 months and 59 months, household heads, elderly people and agricultural officers. Purposive sampling was used to select agricultural officers while multistage sampling was used to select respondents at household level. Data was collected by use of a pre-tested questionnaire. The MUAC tape was used to collect nutritional status of children while BMI data was obtained from elderly people. Mann Kendall statistic was used to determine whether the trend of rainfall and temperature observed is significant while Chi-square test was used to determine whether the coping strategies observed varied significantly at household level. From the analysis, rainfall has not shown any significant change in Kisii County while temperature trend has been significantly increasing over the years at 95% confidence level. This could explain the observed reduction in river levels. Analysis of crop production and price trends of major food crops in Kisii County showed a decreasing trend of food production leading to increase in price over the years. This meant that farmers could not produce enough to take them to the next harvesting season making farmers to adopt different coping strategies at household level which differed significantly according to Chi-Square test. Malnutrition status of both elderly people above 59 years and children between 6-59 months were similar with 23% of both children/elderly being severely malnourished/malnourished. This study has only looked at climatic factors such as rainfall and temperature. Other aspects such as depth of underground water, ph level of soil and the effects of land fragmentation also need to be looked at. This study is important to both farmers in choosing the right crop to plant, and policy makers and planners in formulating the best mitigation and intervention strategies for Kisii County food insecurity problem. This will further contribute to national efforts towards achievement of vision 2030.

To proactively manage information security, enterprises often employ information security risk assessment techniques. Asset value - which is used to calculate the financial impact of possible threats - is one of the key parameters of information security risk. However, assets in a system are rarely independent, and their values are typically interdependent. Asset owners and IT teams may hold different views as regards these values, and there is thus the need to reduce subjectivity in a qualitative risk assessment. The research entails the development of a conceptual framework derived from the literature to minimize subjectivity, and the design of a system based on those concepts. The study uses the Unified Modeling Language as a design tool and puts forward an object-oriented model for defining asset values, in which the relationships between assets, vulnerabilities and related threats are identified. A “segregation of duties” approach is integrated into the risk management system to mitigate against subjectivity and better determine asset values. Survey responses from 16 practitioners working in the private and public sectors confirm the validity of the approach, but suggest it may be more workable in larger organisations where resources allow dedicated risk professionals to operate.

Background: The rise of cloud computing has led to the increasing number of organizations that rely on it for various tasks and services, such as education, healthcare, and e-commerce. Unfortunately, many security threats can be caused by the sudden use of cloud platforms. Objective: This paper aims to provide a comprehensive overview of these threats and how they can be mitigated. Many companies are moving toward cloud computing to sustain their business growth and provide their employees with the best possible work environment. Results: Due to the rise of cyber security threats and the unprecedented number of breaches of data, small and medium-sized enterprises are also starting to take a huge leap. The outbreak of COVID-19 has affected the lives of people all around the world. Conclusion: Due to the seriousness of the situation, the WHO has declared the COVID-19 pandemic a public health emergency. To minimize the spread of the virus, the entire world has started adopting social distancing

.Various synthetic nematicides are currently used effectively in the control of plant parasitic nematodes. However, these nematicides have adverse effects on humans and the environment. Neem oil is eco-friendly alternatives to synthetic nematicides. The effectiveness of repeated neem oil application in suppressing the root-knot nematodes infestation in figs seedlings was therefore examined in this study, both in its natural form (10 ml/L) and in its nano-emulsion form (5 and 7 ml/L). The recorded reduction parameters of M. incognita were J2/250g soil, galls and egg masses / 5g roots of infected fig seedlings were measured at that time, and the effects of these natural additives were compared with the Fosthiazate (Krenkel 75%EC). The impact of such soil amendments on some typical plant parameters, the total microbial count of soil, and the overall enzymatic activity of the fig rhizosphere were also included. Obtained results revealed that the soil population density of root knot nematode suppressed by 80.3% , reduction of nematode egg masses (60.4%) due to the application of nano-emulsion of neem oil (at 7ml/L). Present work recommend the use of nano-emulsion of neem oil as one of the effective and eco-friendly means to reduce the root- knot nematode on fig .

The global textile sector, pivotal to economic development, significantly contributes to environmental degradation, prompting a shift towards sustainable raw material sources. Embracing circular economy principles, this industry is exploring the valorization of agricultural by-products. This study introduces an innovative approach to repurposing mango waste into valuable textile fibers, a byproduct of the fruit processing industry, predominantly generated during juice and jam production. The focus is on the lignocellulosic constituents of mango waste, specifically the peel, seed, and fibrous material, traditionally considered as refuse. Previous research has predominantly utilized mango peel in pectin extraction for food applications, whereas the potential of seed and fibrous content remains underexplored. This investigation endeavors to transform these fibrous by-products into high-value materials suitable for textile manufacturing. The process involved washing, drying, and comprehensive physicochemical characterization of mango fibers, emphasizing lignin quantification, revealing a composition of 12.2% lignin. An experimental design was employed to elucidate the impact of variables such as liquid-to-solid ratio, reaction duration, and sodium hydroxide concentration on lignin dissolution through alkaline hydrolysis. Optimal conditions—10% NaOH concentration, 30 mL/g liquid-to-solid ratio over six hours—achieved an 83% reduction in lignin content. The resulting fibers exhibited properties akin to conventional natural fibers, including a favorable aspect ratio indicative of their suitability for textile applications. A subsequent softening process using propylene glycol enhanced the fibers' spinability, producing a durable, textured fabric ideal for eco-conscious fashion applications, including bags, footwear, and accessories. This research demonstrates the feasibility of converting mango waste into a textile-worthy material and underscores the importance of waste revalorization in promoting sustainability within the circular economy framework.

Ecological changes evoke many felt losses and types of grief. These affect sustainability efforts in profound ways. Scholarship on the topic is growing, but the relationship between general grief research and ecological grief has received surprisingly little attention. This interdisciplinary article applies theories of grief, loss, and bereavement to ecological grief. Special attention is given to research about “non-death loss” and other broad frameworks about grief. Dynamics related to both local and global ecological grief are discussed. Kinds of potential losses arising out of ecological issues are clarified with the frameworks of tangible/intangible loss, ambiguous loss, nonfinite loss, and shattered assumptions. Various possible types of ecological grief are illuminated by discussing the frameworks of chronic sorrow and anticipatory grief/mourning. Earlier scholarship about disenfranchised ecological grief is augmented by further distinctions about various forms it may take. The difficulties in defining complicated or prolonged grief in ecological context are discussed, and four types of “complicated ecological grief” are explored. Based on the findings, three special forms of ecological loss and grief are named and discussed: transitional loss and grief, lifeworld loss, and shattered dreams. The implications of the results for ecological grief scholarship, counselling and coping are briefly discussed. The results can be used by psychological and healthcare professionals and researchers, but also by members of the public who wish to reflect on their eco-emotions.

The eco-efficiency of cultivated land use (ECLU) is an important indicator for the construction of ecological civilization in China. Exploring the spatiotemporal dynamic evolution of the ECLU is helpful for sustainable use of arable land, ensuring food security and ecological security. However, previous studies have mostly focused on the use of a slacks-based measure (SBM) model for ECLU measurement, ignoring the more accurate epsilon-based measure (EBM) model. Therefore, in this study, firstly, we explored the conceptual framework of ECLU, and then, based on the panel data of the counties in the region around Beijing and Tianjin from 2005 to 2020, we investigated the spatial and temporal evolution of ECLU by using the Super-EBM model, kernel density estimation method, and spatial Markov chain model. Results displayed: (1) From 2005 to 2020, the ECLU in the region around Beijing and Tianjin displayed an increasing state, but the average value was only 0.55. (2) The time evolution of the ECLU has gradually polarized, the internal gap has widened, but it tends to stabilize. (3) The ECLU in the region around Beijing-Tianjin was more inclined to keep it the same and there was a "club convergence" phenomenon, which was meaningfully affected by the background of neighboring areas. In the light of local conditions, the government should reasonably formulate the path to optimize the ECLU, strengthen the linkage with the surrounding cities, and bring into play the positive spillover effect.

Background: The outbreak of the Covid-19 pandemic has significantly affected the operations of higher education institutions. Due to the limited use of video conferencing and cloud computing in these facilities, distance learning became the only option available to them. Objective: The study focused on identifying the most common types of attacks that can affect e-learning assets. Results: There was a lack of clear cybersecurity policies for educational institutes and universities in 2020, according to a report by Microsoft Security Intelligence. The report showed that the education industry was the most targeted sector for malware attacks in the last 30 days. Conclusion: The recommendations for improving the security of e-learning systems. Some of these include implementing policies that restrict access to the resources and applications, updating security patches, and using cryptographic protocols.

The growing shift toward Internet of Things (IoT)-based solutions expands the attack surface of systems by connecting an extensive network of heterogeneous devices and technologies. The heterogeneity of IoT devices and the scale of the network often make conventional security measures impractical. Therefore, recent research efforts have focused on machine learning (ML)-based device-agnostic IoT security solutions. However, most proposed solutions have focused solely on detecting malicious traffic in IoT networks. While this is important, further information about the attack is needed to provide a comprehensive defense before, during, and after the incident. To address this gap, we proposed an anomaly-based intrusion detection model that detects malicious traffic and identifies the attack category and subcategory with high accuracy, recall, precision, and F1-score. The proposed intrusion detection model is an ensemble model that integrates multiple ML models to produce more robust and reliable detections. For evaluation, we performed three sets of experiments: (1) a binary classification to detect malicious traffic; (2) a multi-class classification to detect the attack category; and (3) a multi-class classification to detect the attack subcategory. In the experiments, our model achieved an accuracy, recall, precision, and F1-score of 100% for the binary detection; a precision, recall, and F1-score of 99% and an accuracy of 100% for the multi-class category classification; and an accuracy, recall, precision, and F1-score of 88% for the multi-class subcategory classification. These results suggest that the proposed model can reliably detect anomalies in IoT devices.

This research aims to introduce a model, SectraBank, designed to mitigate cyber fraud attacks, specifically targeting SIM Swapping and Fake App schemes in mobile banking users. A quantitative methodology with an experimental design was meticulously employed to examine the rise of cyber fraud within mobile banking. The study involved a sample of 100 professionals with advanced knowledge in Information and Communication Technologies (ICTs). Surveys were utilized to measure awareness of threats and perceptions of security before and after the implementation of the proposed model. SectraBank leverages unique user identifiers such as fingerprint authentication and the International Mobile Equipment Identity (IMEI) number, in addition to geolocation and One Time Passwords (OTP) for validating electronic transactions in mobile banking. The effectiveness of the proposed model was notable, achieving a 96.1% efficacy rate in mitigating Fake App attacks and a 90.2% success rate in countering SIM Swapping attacks. These findings underscore the potential of SectraBank as a robust solution to enhance cybersecurity measures in the realm of mobile banking.

: In the realm of data management, data preservation stands as a critical undertaking aimed at preserving and upholding the integrity of data. Regardless of whether it concerns personal or enterprise data, the detrimental effects of malicious alterations implemented by attackers cannot be overlooked. Particularly in conventional industrial control environments, the prevalent practice involves the transmission of data from sensors to databases for storage purposes. However, it is essential to recognize that this process exposes the data to various vulnerabilities. Thus, to ensure the long-term security and reliability of the data, it becomes imperative to implement robust data preservation strategies within these industrial control systems. However, the reliance of these databases on physical hard disks introduces inherent vulnerabilities, including the potential for data loss due to disk damage or targeted malicious attacks. Consequently, it becomes imperative to prioritize the implementation of robust data preservation measures. These measures are crucial in mitigating the risk of disruptions and protecting critical data from compromise. By establishing effective data backup systems, employing advanced security protocols, and implementing proactive monitoring mechanisms, organizations can bolster their data preservation capabilities and safeguard against potential threats to data integrity and availability. As a result, many enterprises opt to store their data with third-party providers to ensure data integrity. However, this approach carries inherent risks. If the third-party service experiences an attack or if the data is tampered with, it becomes challenging to verify the integrity of the data. To address these concerns and ensure data preservation within the context of the Internet of Things (IoT), a growing number of individuals are integrating IoT with Distributed Ledger Technology (DLT). By leveraging DLT, the integrity of data can be ensured, reducing reliance on centralized third-party storage and enhancing security in the IoT ecosystem. In this article, IOTA is the DLT, which employs Directed Acyclic Graph (DAG) to store transaction information. Compared to Ethereum or other blockchain technologies, IOTA offers notable advantages in terms of transaction verification speed, making it highly suitable for real-time IoT environments. However, the conventional transmission path from sensors to IOTA nodes entails a complex route, involving multiple hardware devices before reaching the intended destination. This complexity poses challenges in ensuring data integrity during transmission and introduces vulnerabilities such as man-in-the-middle attacks or SQL injection attacks. To address these issues, we propose a method to streamline the transmission path between sensors and IOTA, specifically tailored for industrial fields with numerous IoT devices. Our approach involves preprocessing the data stored on the server using our method before uploading, ensuring data confidentiality, and leveraging IOTA to guarantee data integrity. To achieve the shortest path between IoT and DLT nodes, it becomes necessary to establish IOTA nodes on lower-level devices, such as Raspberry Pi or IoT controllers. By simplifying the transmission path, we can reduce the potential for tampering and enhance overall data security. Implementing our proposed method enables the assurance of data confidentiality and integrity during both transmission and storage on the server, strengthening the trustworthiness of the IoT, and IOTA integration.

This paper proposes to combat active eavesdropping by intelligent reflecting surface (IRS) backscatter techniques. To be specific, the source (Alice) sends the confidential information to the intended user (Bob), while the eavesdropper (Willie) transmits jamming signal to interrupt the transmission for more data interception. To enhance the secrecy, an IRS is deployed and connected with Alice through fiber to transform the jamming signal into the confidential signal by employing backscatter techniques. Based on the considered model, an optimization problem is formulated to maximize signal-to-interference-plus-noise ratio (SINR) at Bob under the constraints of the transmit power at Alice, the reflection vector at the IRS and the allowable maximum SINR at Willie. To address the optimization problem, an alternate optimization algorithm is developed. The simulation results verify the achievable secrecy gain of the proposed scheme.

As artificial intelligence continues to advance, researchers are increasingly using machine learning algorithms to study the factors that make people more susceptible to phishing scams. Most studies in this area have taken one of two approaches: either they explore statistical associations between various factors and susceptibility, or they use complex models such as deep neural networks to predict phishing behavior. However, these approaches have limitations in terms of providing practical insights for individuals to avoid future phishing attacks and delivering personalized explanations regarding their susceptibility to phishing. In this paper, we propose a machine learning approach that leverages explainable artificial intelligence techniques to examine the influence of human and demographic factors on susceptibility to phishing attacks. Our analysis reveals that psychological factors such as impulsivity and conscientiousness, as well as appropriate online security habits, significantly affect an individual's susceptibility to phishing attacks. Furthermore, our individualized case-by-case approach offers personalized recommendations on mitigating the risk of falling prey to phishing exploits, considering the specific circumstances of each individual.

In today's world, wherein more than 80% of world trade is carried out by maritime routes, the safety and security of the seas where this trade takes place is of vast importance for nations and the in-ternational community. For this reason, ensuring the sustainable safety and security of the seas has become an integral part of the mission of all maritime-related entities. The utilization of big data extracted from the seas and maritime activities into meaningful information with artificial intelli-gence applications and developing applications that can be used in maritime surveillance will be of great importance for augmenting maritime safety and security. In this article, data sources which can be used by a maritime surveillance system based on big data and artificial intelligence tech-nologies and which can be established around sensitive sea areas and critical coastal facilities, are identified and a model proposal using this maritime big data is put forward.

Abstract: The Internet of Things (IoT) has witnessed rapid and widespread adoption across various domains, including transportation, healthcare, education, agriculture, urban planning, smart homes, and more. Despite its transformative potential, this pervasive deployment of IoT devices has introduced new challenges, particularly concerning security and privacy threats such as unauthorized data access and device breaches. The excessive usage of these technological devices, coupled with the absence of robust security and privacy systems for user data, calls for a comprehensive approach to address these issues. In this study, we propose a novel framework designed to analyze, audit, test, and detect potential vulnerabilities within IoT environments and applications. The central components of the proposed framework include a machine learning algorithm for data classification and attack detection, along with the integration of Blockchain technology to enhance security measures. Specifically, the framework performs an in-depth analysis of user data to identify potential security or privacy vulnerabilities. Additionally, it conducts rigorous testing of smart services and automated data-collecting devices. To evaluate the effectiveness of our classification algorithm, we conducted a comprehensive implementation on a real-world IoT dataset. The results showcased the efficiency and accuracy of our approach in detecting and mitigating potential threats. Furthermore, based on our research findings, we provide valuable recommendations for enhancing security and privacy in IoT ecosystems. We also highlight emerging trends in the security and privacy domains, which can serve as valuable insights for researchers and practitioners. In conclusion, our proposed framework offers a robust and proactive approach to address the security and privacy challenges, such as unauthorized data access and device breaches posed by the widespread adoption of IoT devices. By combining machine learning algorithms and Blockchain technology, we contribute to safeguarding user data and fostering a secure environment for IoT applications. This study lays the groundwork for further advancements in the realm of IoT security and privacy, ensuring a safer and more resilient IoT landscape for the future.

In recent years web applications and on-line business transactions have grown many folds. Consequently, also cyberattacks have increased and represent a serious threat to the pervasive digital services upon which our society relies. To mitigate cyberattacks, many countermeasures are deployed on computing nodes (e.g., anti-malware software) as well as on network devices to detect and possibly block malicious packets in transit; these monitoring devices broadly go under the name of firewalls. Firewalls are designed according to two main architectural approaches: software running on a standard or embedded computer, or purposedly designed hardware, e.g., ASICs. Software-based solutions have the advantage of high flexibility and can be ported on easily upgradable hardware. However, hardware implementation represents the only viable solution for high data rates. On the market, very fast devices of the latter kind are available, but their cost is typically very high, especially considering that their ultra-optimized design makes updating them very difficult, with the consequence of a rather short lifespan. As a more balanced alternative, we wanted to investigate the use of an FPGA architecture, , which is significantly easier to update than custom-built chips, and features low-latency and high-throughput characteristics concurrently, making it preferrable to other programmable systems based on GPUs or microcontrollers. In this paper a packet sniffer that has been designed on FPGA with a 1 Gbit/s data transfer rate is presented. The system is implemented on the FPGA development board KC705 by Xilinx, can analyze Ethernet frames, checking the frame fields against a set of rules defined by the user and calculates statistics of the received Ethernet frames over time. The designed packet sniffer has been successfully tested both with Ethernet frames ad hoc generated using a packets generator, and with real web traffic by connecting the packet sniffer to the internet.

The study aims to determine the trust and presence of police officers in schools in Serbia, as well as the perception of the principals and secretaries, teachers and staff, parents and students on how successful the certain police units dedicated to schools were in fulfilling their tasks. The ex–post analysis was conducted through PEST/SWAT analysis, mapping of the key actors and using batteries of online questionnaires. Besides interviews with the MOI representatives, there were conducted: Survey with personal interviewing, Computer–aided surveying and Desk analysis and content analysis. The survey was conducted in the period from September 2021 to June 2022. The research methods were implemented in 1140 schools in Serbia and 8,617 people were included in surveys: police officers (308); principals and secretaries (1085); the team for protection against discrimination (982); teachers and staff (2988); parents (938) and students (2316). The relationships between the covariates and perception were investigated using the t–test, one–way ANOVA, multivariate linear regression, and binary regression. The results showed that a project of school police officers was not fully recognized as one of the strategically important instruments for safe schools, trust is low but presence is high. Besides that, the results suggest that the entire public believe that a police is needed in schools and that it has a very positive effect on school safety. Regarding school safety policy, it is necessary to undertake three types of measures for sustainable development of trust and presence of police in school: regulatory, informa-tive-educational and institutional-organizational.

The rapid changes in technology on a global scale, combined with the widespread adoption of business operations in cyberspace, have intensified the need for robust protection against escalating risks posed by cyber threats. This research paper aims to identify fundamental cyber resilience management attributes that enable organizations to manage cybersecurity, sustain, and adapt amidst evolving cyber risks and threats. By integrating resilience theory and security theory, this study establishes the attributes for resilience within cyber domains, making a novel contribution to cyber resilience management in organizations. The study introduces a model featuring seven main variables: Rationale, Reliable, Readiness, Resistance, Robust, Rebound, Reflective, and sub-variables across the Physical, Logical, and Social cyber domains, providing a converged framework for achieving cyber resilience. The findings of the study highlight the significance of fundamental attributes for enhancing cyber resilience management in organizations, such as clarity in purpose, vision, and values for security management, an empowered culture, availability of resources, avoidance of single points of failure, development, and coordination of resources to respond to threats and risks, promotion of continual improvement, and the sharing of information and knowledge. In conclusion, this research paper presents a model for managing cybersecurity in organizations by identifying key attributes for achieving cyber resilience.

Secure attachment, developed through consistent relationships with attachment figures in childhood, is a crucial factor in fostering healthy interpersonal relationships and a positive self-perception. This research aimed to assess how perceived security, as an indicator of secure attachment, predicts adult self-concept through the mediating effects of resilience and positive self-esteem. A quantitative, cross-sectional, and non-probabilistic study was conducted with 383 participants, of whom 76.2% were females, aged between 17 and 86 years (M = 28.52, SD = 12.23). Correlational analyses revealed significant positive associations between perceived security, self-concept, resilience, and positive self-esteem. Path analysis demonstrated that resilience and positive self-esteem sequentially mediate the relationship between perceived security during childhood and adult self-concept (Total Effect R2 = .34, F(1,381) = 193, p < .001; Indirect effect of sequential mediation b = .02, CI 95% [.01, .04]). Findings suggest that the ability to cope with ad-versity and personal acceptance underlie the impact of perceived security on self-concept. It is recommended to promote not only secure attachment in family interventions but also resilience and self-esteem in programs targeting adolescents, youth, and adults.

The Internet of Things (IoT) technology and devices constitute an exciting field in computer science that is rapidly emerging worldwide. IoT devices function by connecting real-world objects to the internet, resulting in a higher number of interconnected devices than ever witnessed in history. Through internet connectivity, these devices can be utilized in various ways, such as monitoring and tracking. Their prevalence is increasing exponentially, coinciding with advancements in wireless networking technologies. The internet’s enhanced connectivity has played a vital role in fostering the proliferation of IoT devices. Presently, almost any everyday object can be network-connected. The demand for automation and efficiency has also been a contributing factor to the advancements in this technology. This paper aims to review the emergence of IoT devices, analyze their common applications, and explore the future prospects in this promising field of computer science. The examined applications encompass healthcare, agriculture, and smart cities. Although IoT technology exhibits similar deployment trends, this paper will explore different fields to discern the subtle nuances that exist among them. IoT technology can be applied to nearly any domain, and each use case has unique requirements. To comprehend the future of IoT, it is essential to comprehend the driving forces behind its advancements in various industries. By gaining a better understanding of the emergence of IoT devices, readers will develop insights into the factors that have propelled their growth and the conditions that led to technological advancements. Moreover, a comprehensive understanding of the prevalent methodologies will enable readers to distinguish between current practices and future methods. Given the rapid rate at which IoT technology is advancing, this paper aims to provide researchers with an understanding of the factors that have brought us to this point and the ongoing efforts to shape the future of IoT.

Recently, the world has experienced severe food insecurity problems with most countries having inadequate access to affordable, nutritious and safe foods. Consequently, many food innovations and technologies have been approved to secure sustainable access to food for millions of people. This study investigated the implementation of two technologies to address food insecurity, namely genetically modified foods (GMOs) and the use of antibiotics in crops and animal production. In particular, the study explored how their implementation can be governed responsibly through approved legislation. Therefore, the knowledge, attitudes and practices as well as the governance of antibiotic resistance risks and GMO foods were assessed. In-depth key interviews were conducted for the qualitative survey with triangulation with quantitative data sources. The findings showed that 46% of the population have little knowledge about GMOs with about 79% indicating that food with GM ingredients were being consumed in the country. The main concerns reported on GM foods by most respondents were impact on environment, human health and adverse effects on traditional farming practices with 36% indicating that it intensifies contamination and 32% indicating that it contributes to loss of biodiversity. Notably, 64%) reported that GMOs are a solution to food security and that they are safe. On the use of antimicrobials mainly meant to prevent diseases and access better markets, respondents perceived their use to be associated with antimicrobial resistance a “large level of risk” (score 2 in a scale of 1-3) (M = 1.85, SD = 1.06). Overall, the study found that efforts towards promoting awareness on antibiotic resistance risks and response in human health is relatively limited as reported by 56% of the respondents. Findings show that most of the respondents have only seen minimal or small-scale awareness campaigns. On governance of the two technologies, 71% and 50% of the respondents reported that scientists and elected officials respectively have the greatest role in governance of GMOs with small scale farmers playing a negligible role. Further, it was noted that all the respondents were knowledgeable in AMR and GMO technologies and these findings are crucial to the advancement of food innovations that are geared towards achieving food security in Kenya. This study highlights the risks associated with the poor governance and implementation of technologies and the need for a framework for technological risk governance that is sensitive to local values and socio-economic circumstances that will benefit the achievement.

In the European Union, the eCall system has been mandatory since March 31, 2018. The system enabled a significant increase in safety on roads and highways, making help faster in the event of an accident. However, based on circuit-switched 2G/3G communications and an onboard device called IVS, it is generally unavailable on legacy vehicles. Some of its limitations tend to be remedied by the future NG eCall based on 4G/5G packet-switched communications. This paper discusses why IVS may be an Achilles’ heel of any future IVS-based eCall and analyzes the advantages of a smartphone-based system. The TEZE system, implemented and installed in Italian highway tunnels, is a first general-purpose safety system, and allows highly reliable smartphone-based emergency calls. It is based on a dedicated low-cost ground infrastructure that allows monitoring of the availability of emergency call service through the mobile radio networks of the operators present inside the tunnels. The system complies with the ISO/IEC 30141:2018 reference standard. Identifying functional/non-functional requirements and their verification criteria provide an overall validation of the analyzed system. The paper concludes by examining some key functionalities for vehicular services that can be implemented in an integrated system based on smartphones and heterogeneous networks.

Adequate access to drinking water for hydration and hygiene depends on many factors, such as water quality, accessibility, continuity of supply, and available quantity. We developed the Drinking Water Security Index (DWSI) to assess relative multifactorial drinking water security at different spatial and temporal scales. We apply this new index in Sudan to assess historical and future drinking water security at state, local, and maternity levels. State-level analyses found that the Red Sea and River Nile states are most vulnerable, with the lowest DWSI for both historical and future periods. The 1 km2 pixel level analysis shows large differences in water security within the major states. Analyses at maternity level showed that nearly 18.97 million people are affected by the 10% of maternities with lowest DWSI, a number projected to increase by 60% by 2030. Current and future water security indexes of maternities providing Emergency Obstetric and Newborn Care, were assessed to identify those where urgent action is needed to ensure quality health care in water secure conditions. This work provides useful information for stakeholders in the health and drinking water sectors in Sudan, to improve public health, reduce preventable mortality, and make the population more resilient to projected environmental changes.

The application of organic fertilizers plays a crucial role in achieving carbon sequestration in the agricultural sector. This paper discusses how farmers can more smoothly promote organic fertilizer extension services. An evolutionary game model is developed to describe the conflicting interests of Chinese farmers and local governments in organic fertilizer extension services, and the dynamic evolution of the game players and the influence of parameter adjustment on the strategic choices of both parties is presented. In this paper, the game model and the main results are validated with the help of simulation tools, and a sensitivity analysis of the selected parameters is performed. The results show that (1) the implementation of subsidy policy is less helpful for organic fertilizer extension services; (2) The ideal event probability of the game was found to be positively related to the cost of applying inorganic fertilizers, additional benefits to farmers, political returns to local governments, and penalties for not using organic fertilizers; (3) This is important for improving the performance of local governments, reducing government regulatory costs, improving policy support for organic fertilizer extension services, and reducing the cost of implementing organic fertilizer extension services.