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Convolutional neural networks (CNNs) offer unrivaled performance in profiling side-channel analysis. This claim is corroborated by numerous results where CNNs break targets protected with masking and hiding countermeasures. One hiding countermeasure commonly investigated in related works is desynchronization (misalignment). The conclusions usually state that CNNs can break desynchronization as they are shift-invariant. This paper investigates that claim in more detail and reveals that the situation is more complex. While CNNs have certain shift-invariance, it is insufficient for commonly encountered scenarios in deep learning-based side-channel analysis. We investigate data augmentation to improve the shift-invariance and, in a more powerful version, ensembles of data augmentation. Our results show that the proposed techniques work very well and improve the attack significantly, even for an order of magnitude. [ABSTRACT FROM AUTHOR]

Steep surrounding rock significantly challenges tunnel stability by affecting the stress distribution and deformation behavior. The angle of dip in surrounding rock greatly influences these factors, heightening the risk of instability along bedding planes, particularly under high ground stress conditions. This paper presents a comprehensive analysis of steep rock strata mechanical properties based on a railway tunnel in Yunnan Province, China. It incorporates long-term field monitoring and various laboratory tests, including point load, triaxial, and loose circle tests. Using experimental data, this study simulated the failure processes of steep surrounding rock and tunnel structures with a custom finite element method (FEM) integrated with the volume of fluid (VOF) approach. The analysis summarized the deformation patterns, investigated the causes of inverted arch deformation and failure, and proposed countermeasures. The findings reveal that increasing the rock dip angle results in greater deformation and accelerated failure rates, with the surrounding rock's loose zone stabilizing at approximately 8 m once deformation stabilizes. At a surface deformation of 8 cm, the failure zone extends to 6 m; however, this extension occurs more rapidly with higher lateral pressure coefficients. Additionally, failure zones develop more quickly in thin, soft rock on steep slopes compared to uniform rock formations. The rise of the tunnel floor is attributed to the steeply inclined, thin surrounding rock. To enhance bottom structure stiffness, this study recommends incorporating an inverted arch structure and increasing both the number and strength of the anchor bolts. [ABSTRACT FROM AUTHOR]

As technology advances and develops, the need for strong and simple authentication mechanisms that can help protect data intensifies. The contemporary approach to giving access control is through graphical passwords comprising images, patterns, or graphical items. The objective of this review was to determine the documented security risks that are related to the use of graphical passwords, together with the measures that have been taken to prevent them. The review was intended to present an extensive literature review of the subject matter on graphical password protection and to point toward potential future research directions. Many attacks, such as shoulder surfing attacks, SQL injection attacks, and spyware attacks, can easily exploit the graphical password scheme, which is one of the most widely used. To counter these security threats, several measures have been suggested, but none of the security attacks can be completely overcome. Each of the proposed measures has its pros and cons. This study begins by elucidating some of the graphical password schemes studied between 2012 and 2023, delving into potential threats and defense mechanisms associated with these schemes. Following a thorough identification and selection process, five of the reviewed papers explain the threat of shoulder surfing and spyware attacks on graphical password schemes, while two explain the threat of brute force attacks. One paper focuses on dictionary attacks, while four other papers address social engineering, SQL injection attacks, and guessing attacks as potential threats to graphical password schemes. In addition, the papers recognize other forms of attacks, such as video recording attacks, filtering attacks, reverse engineering attacks, multiple observation attacks, key/mouse logger attacks, insider attacks, computer vision attacks, image gallery attacks, sonar attacks, reply attacks, data interception attacks, and histogram manipulation attacks. These attacks are examined in three, three, eight, one, four, one, one, one, one, one, one, and one papers, respectively. Moreover, out of all such countermeasures, most of them are based on three categories—randomization, obfuscation, and password space complexity—which are the most commonly employed strategies for improving graphical password schemes. [ABSTRACT FROM AUTHOR]

The Technology Acceptance Model (TAM) plays a pivotal role in elderly healthcare, serving as a theoretical framework. This study aimed to identify TAM's core components, practical applications, challenges arising from its applications, and propose countermeasures in elderly healthcare. This descriptive study was conducted by utilizing OpenAI's ChatGPT, with an access date of 10 January 2024. The three open-ended questions administered to ChatGPT and its responses were collected and qualitatively evaluated for reliability through previous studies. The core components of TAMs were identified as perceived usefulness, perceived ease of use, attitude toward use, behavioral intention to use, subjective norms, image, and facilitating conditions. TAM's application areas span various technologies in elderly healthcare, such as telehealth, wearable devices, mobile health apps, and more. Challenges arising from TAM applications include technological literacy barriers, digital divide concerns, privacy and security apprehensions, resistance to change, limited awareness and information, health conditions and cognitive impairment, trust and reliability concerns, a lack of tailored interventions, overcoming age stereotypes, and integration with traditional healthcare. In conclusion, customized interventions are crucial for successful tech acceptance among the elderly population. The findings of this study are expected to enhance understanding of elderly healthcare and technology adoption, with insights gained through natural language processing models like ChatGPT anticipated to provide a fresh perspective. [ABSTRACT FROM AUTHOR]

The majority of data exchanged between connected devices are confidential and must be protected against unauthorized access. To ensure data protection, so-called cryptographic algorithms are used. These algorithms have proven to be mathematically secure against brute force due to the key length, but their physical implementations are vulnerable against physical attacks. The physical implementation of these algorithms can result in the disclosure of information that can be used to access confidential data. Some of the most powerful hardware attacks presented in the literature are called fault injection attacks. These attacks involve introducing a malfunction into the normal operation of the device and then analyzing the data obtained by comparing them with the expected behavior. Some of the most common methods for injecting faults are the variation of the supply voltage and temperature or the injection of electromagnetic pulses. In this paper, a hardware design methodology using analog-to-digital converters (ADCs) is presented to detect attacks on cryptocircuits and prevent information leakage during fault injection attacks. To assess the effectiveness of the proposed design approach, FPGA-based ADC modules were designed that detect changes in temperature and supply voltage. Two setups were implemented to test the scheme against voltage and temperature variations and injections of electromagnetic pulses. The results obtained demonstrate that, in 100% of the cases, when the correct operating voltage and temperature range were established, the detectors could activate an alarm signal when the cryptographic module was attacked, thus avoiding confidential information leakage and protecting data from being exploited. [ABSTRACT FROM AUTHOR]

This paper summarizes the research on countermeasures against driver fatigue based on a comprehensive systematic literature review. Driver fatigue, induced by task monotony during conditional automated driving (CAD, SAE Level 3), can increase the risk of road accidents. There are several measures that counteract driver fatigue and aim to reduce the risk caused by a fatigued driver in the context of CAD. Twelve selected articles focusing on driver fatigue countermeasures in CAD were analyzed. The findings and conclusions are presented, focusing on the countermeasures themselves and their implementation. The countermeasures were critically discussed, especially regarding effectiveness and applicability. They seem to be effective in counteracting driver fatigue. However, the measures are not easily compared because they were studied in various experimental settings and various driver fatigue measurements were used. Different countermeasures have proven to be effective in reducing fatigue during CAD. For this reason, further investigation is needed to gain further insights into their applications, advantages, and disadvantages. Further studies will be conducted to verify the best solution regarding their effectiveness and applicability. [ABSTRACT FROM AUTHOR]

The high water content of the surrounding rock in loess tunnels will lead to the deterioration of rock strength, causing deformation and damage to the initial support structure and thereby affecting safety during construction and operation. This article first analyzes the strength characteristics of loess under different water contents through indoor physical and mechanical tests. Secondly, based on numerical simulation results, the ecological environment, and design requirements, the water content threshold is determined. Finally, a reinforcement scheme combining surface precipitation measures and curtain grouting measures is proposed, and the reinforcement effect is analyzed based on on-site monitoring data. The results show that as the water content of loess increases, the cohesion, internal friction angle, and elastic modulus of the surrounding rock all decrease, leading to an increase in the sensitivity of the surrounding rock to excavation disturbances and a deterioration in strength. During the construction process, it shows an increase in the vault settlement and sidewalls' convergence. During the process of increasing the distance between the monitoring section and the palm face, the settlement and convergence of the tunnel show a rapid growth stage, slow growth stage, and stable stage. The water content threshold is determined to be 22%. The reinforcement scheme of combining surface precipitation measures with curtain grouting measures not only meets the requirements of the ecological environment but also makes the settlement and convergence values lower than the yellow warning deformation values required by the design. [ABSTRACT FROM AUTHOR]

Proving the quality and efficiency of energy conservation and emission reduction in the construction industry and providing high-quality products and services are important forces in achieving the goal of 'double carbon'. They play a crucial role in the sustainable development of human society and nature and are the typical embodiment of the high-quality development of Chinese modernization. This paper analyzes the proportion and importance of China's construction industry policy system, spatial characteristics, energy consumption, and carbon dioxide emissions in achieving the 'double carbon' goal. The life cycle assessment (LCIA) method identifies that the materialization, operation, and use stages are the key stages of the whole process and the influencing factors of energy consumption and carbon emissions. Using the analytic hierarchy process (AHP) method, this paper explores and creates China's construction industry's '1 + 5 + N' high-quality development index system by proposing four stages: top-level design period, deep development period, consolidation achievement period, and summary planning period. These stages aim to facilitate quality improvement, efficiency enhancement, innovation drive, and whole life cycle sustainability. This system's principles are 'systematic planning, one type of one policy, collaborative efforts, safety, and economy'. The proposed system aims to enhance the policy and standard system, strengthen the implementation of policy tools, increase the investment and application of energy-saving and efficiency-increasing technologies, improve the development of energy consumption and carbon emission monitoring systems and platforms, reinforce green finance, standardize information disclosure, accelerate the renovation of outdated infrastructure, and intensify efforts to promote and guide green consumption, lifestyles, and production methods. [ABSTRACT FROM AUTHOR]

From cost and management perspectives, the sudden outbreak of COVID-19 and the subsequent countermeasures adversely affected labor-intensive construction companies owing to the restrictive guidelines. Following a systematic literature review, this study developed a theoretical framework to assess the impacts of COVID-19 and its countermeasures on construction sites. Based on a developed framework reflecting abroad cases, we explored the Republic of Korea (ROK) situation. Questionnaires were utilized to detect this impact, and were then analyzed using the relative importance index. Through interviews with site managers in the ROK, combined with text-mining and network analysis, this study aimed to pinpoint effective countermeasures and validate the framework. Results revealed that despite policy changes, construction sites in the ROK were not seriously affected during the COVID-19 pandemic. However, while foreign investment remained steady owing to robust financial contracts, labor shortages and cooperative challenges hindered productivity. Additionally, beyond telecommuting and inspections, changing hygiene regulations prompted the adoption of smart technologies. Further, site managers requested the optimization of worker management and smart systems with governance, hygiene, and quarantine policies. Although impacts from other countries have been studied, the experiences of industries in the ROK remain unanalyzed. In addition, the existing literature has only examined the economic viability of the construction industry; therefore, this study assessed the impacts and countermeasures of COVID-19 from the perspective of managers using a unified theoretical framework. [ABSTRACT FROM AUTHOR]

This study evaluated the generation of adversarial examples and the subsequent robustness of an image classification model. The attacks were performed using the Fast Gradient Sign method, the Projected Gradient Descent method, and the Carlini and Wagner attack to perturb the original images and analyze their impact on the model's classification accuracy. Additionally, image manipulation techniques were investigated as defensive measures against adversarial attacks. The results highlighted the model's vulnerability to conflicting examples: the Fast Gradient Signed Method effectively altered the original classifications, while the Carlini and Wagner method proved less effective. Promising approaches such as noise reduction, image compression, and Gaussian blurring were presented as effective countermeasures. These findings underscore the importance of addressing the vulnerability of machine learning models and the need to develop robust defenses against adversarial examples. This article emphasizes the urgency of addressing the threat posed by harmful standards in machine learning models, highlighting the relevance of implementing effective countermeasures and image manipulation techniques to mitigate the effects of adversarial attacks. These efforts are crucial to safeguarding model integrity and trust in an environment marked by constantly evolving hostile threats. An average 25% decrease in accuracy was observed for the VGG16 model when exposed to the Fast Gradient Signed Method and Projected Gradient Descent attacks, and an even more significant 35% decrease with the Carlini and Wagner method. [ABSTRACT FROM AUTHOR]

In recent years, rice–crayfish integrated farming has expanded rapidly in the Hongze Lake district of China as the booming consumer market of crayfish. However, the current rice cultivation technology limits rice yield and the economic profits of rice–crayfish integrated farming, and the characteristics and farmers' practices of rice culture under the rice–crayfish integrated farming system are unknown. To understand the present rice culture practices in rice–crayfish integrated farming by farmers and their perceptions and provide direction for improvement, a survey was carried out in 2019 and 2020 in Xuyi County, a representative region of rice–crayfish integrated farming in the Hongze Lake district of China, comprising 208 farmers engaged in RCIF, and detailed and complex information was obtained using face-to-face conversations. Based on the survey results, we found that farmers have limited knowledge of the rice cultivation request in a specific RCIF mode and well-suited rice varieties and mechanical transplanting equipment and corresponding techniques are lacking in RCIF. In addition, farmers had no reliable and scientific methods for the use of nitrogen fertilizers and pest management schemes. In accordance with the constraints mentioned above, we put forward the following suggestions for rice culture improvement: (i) the local agricultural extension department should strengthen the RCIF mode and extend techniques and training; (ii) researchers should develop RCIF-suited rice varieties, mechanical transplanters, and related seedling-raising methods; (iii) researchers should clarify the occurrence regularity of soil properties and rice pests with continuous RCIF practices and provide corresponding guidance for nitrogen application and pest control schemes. [ABSTRACT FROM AUTHOR]

Communities and villages are holistic organisms, representing a complete system formed by natural space and human activities. Since the concept of "future community" was put forward by the Drucker Foundation in the United States at the end of the 20th century, "future community" has expanded from the city to the countryside. Governments and scholars of various countries have started the practical and theoretical research into "future community". Based on the theory of "village organism", this paper constructs the structural model of the future countryside, and then constructs the health evaluation index system of the future countryside. This effectively makes up for the shortcomings of previous studies, and provides a new perspective and systematic analysis method for the study of community and village issues. Using entropy weight method and TOPSIS method, Jindong District was used as a case to conduct the quantitative evaluation of the development level of 46 administrative villages in the region. The results showed that: (1) the development level of the villages in the region was not high, and far from the requirements of future countryside, indicating that countryside revitalization has a long way to go; (2) within the region, competitive convergence occurs in the development process of all villages; (3) of the two major countryside systems in the future, the health level of the physical space system is higher than that of the social system, indicating that the local government pays more attention to the construction of the "external" image of the countryside and ignores the improvement of the "internal" function of the countryside society; (4) in the prospective construction of nine scenes of future countryside, an observable trend towards "grouping" differentiation emerges. This phenomenon underscores existing deficiencies in countryside construction, indicating that countryside areas still fail to realize the function of being "self-hematopoietic". The determination and selection of sample indicators exhibit regional cultural disparities, permitting various regions to customize indicators with their specific contextual circumstances. Nevertheless, the universal approach of treating countryside areas as holistic entities remains essential in scholarly inquiry. [ABSTRACT FROM AUTHOR]

Challenges faced in network security have significantly steered the deployment timeline of Fifth Generation (5G) communication at a global level; therefore, research in Sixth Generation (6G) security analysis is profoundly necessitated. The prerogative of this paper is to present a survey on the emerging 6G cellular communication paradigm to highlight symmetry with legacy security concepts along with asymmetric innovative aspects such Artificial Intelligence (AI), Quantum Computing, Federated Learning, etc. We present a taxonomy of the threat model in 6G communication in five security legacy concepts, including Confidentiality, Integrity, Availability, Authentication and Access control (CIA3). We also suggest categorization of threat-countering techniques specific to 6G communication into three types: cryptographic methods, entity attributes and Intrusion Detection System (IDS). Thus, with this premise, we distributed the authentication techniques in eight types, including handover authentication, mutual authentication, physical layer authentication, deniable authentication, token-based authentication, certificate-based authentication, key agreement-based authentication and multi-factor authentication. We specifically suggested a series of future research directions at the conclusive edge of this survey. [ABSTRACT FROM AUTHOR]

Simple Summary: The recent SARS-CoV-2 pandemic has underscored the impact of a single pathogen on public health and economic stability. Similarly, widespread disease outbreaks within agricultural animal populations are potentially devastating by producing food shortages and global starvation. Protecting agricultural animals from viral/bacterial disease outbreaks will depend on the development of countermeasures generating rapid innate immune protection. Accordingly, we have developed a rapidly deployable generalized immune stimulant activating innate immunity at mucosal sites. Past studies show that this platform, termed LTC (liposome-TLR complexes), can rapidly activate and recruit innate immune cells in rodents and companion animals. Moreover, prior rodent and cattle studies showed complete protection against lethal viral and bacterial challenge studies. In the studies described herein, we demonstrate that the LTC platform can be extended to demonstrate rapid activation of innate immune modulators from cell lines and immune cells from peripheral blood in three key agricultural animals: cattle, pigs, and poultry. Cell lines and immune cells from peripheral blood from all three of these species demonstrated significant increases in antibacterial and antiviral immune mediators when treated with LTC in vitro. These data provide justification for further testing of this platform in disease challenge models for these animals. Given the rapid potential spread of agricultural pathogens, and the lack of vaccines for many, there is an important unmet need for strategies to induce rapid and non-specific immunity against these viral and bacterial threats. One approach to the problem is to generate non-specific immune responses at mucosal surfaces to rapidly protect from entry and replication of both viral and bacterial pathogens. Using complexes of charged nanoparticle liposomes with both antiviral and antibacterial toll-like receptor (TLR) nucleic acid ligands (termed liposome-TLR complexes or LTC), we have previously demonstrated considerable induction of innate immune responses in nasal and oropharyngeal tissues and protection from viral and bacterial pathogens in mixed challenge studies in rodents, cattle, and companion animals. Therefore, in the present study, we used in vitro assays to evaluate the ability of the LTC immune stimulant to activate key innate immune pathways, particularly interferon pathways, in cattle, swine, and poultry. We found that LTC complexes induced strong production of type I interferons (IFNα and IFNβ) in both macrophages and leukocyte cultures from all three species. In addition, the LTC complexes induced the production of additional key protective cytokines (IL-6, IFNγ, and TNFα) in macrophages and leukocytes in cattle and poultry. These findings indicate that the LTC mucosal immunotherapeutic has the capability to activate key innate immune defenses in three major agricultural species and potentially induce broad protective immunity against both viral and bacterial pathogens. Additional animal challenge studies are warranted to evaluate the protective potential of LTC immunotherapy in cattle, swine, and poultry. [ABSTRACT FROM AUTHOR]

In this article, we present the results of an anti–drone system simulation. The system is designed to counter mini unmanned aerial vehicles. A radar system with one or several antennas and an elimination system with one or more countermeasures are included in the system. The drones are destroyed by kinetic weapons. In the developed computer model, it is possible to simulate a raid of several drones against several countermeasures in an environment without obstacles. The computer model-specific feature is a discrete-event approach that provides higher calculating performance compared with the "soft time" method. [ABSTRACT FROM AUTHOR]

Internet of Things (IoT) faces security concerns different from existing challenges in conventional information systems connected through the Internet because of their limited resources and heterogeneous network setups. This work proposes a novel framework for securing IoT objects, the key objective of which is to assign different Security Level Certificates (SLC) for IoT objects according to their hardware capabilities and protection measures implemented. Objects with SLCs, therefore, will be able to communicate with each other or with the Internet in a secure manner. The proposed framework is composed of five phases, namely: classification, mitigation guidelines, SLC assignment, communication plan, and legacy integration. The groundwork relies on the identification of a set of security attributes, termed security goals. By performing an analysis on common IoT attacks, we identify which of these security goals are violated for specific types of IoT. The feasibility and application of the proposed framework is illustrated at each phase using the smart home as a case study. We also provide qualitative arguments to demonstrate how the deployment of our framework solves IoT specific security challenges. [ABSTRACT FROM AUTHOR]

The number of elderly people is increasing worldwide, especially in Europe. Such an aging of the population has numerous consequences for society, many of which relate to transportation: older people, aware of their reduced abilities, prefer walking to driving. This leads to an increase in the elderly walking population and thus the need to understand and address the safety issues of these road users. Although these issues are well known, this topic has been little researched so far. The objective of this research is to provide a deeper insight into the safety level of elderly pedestrians by recognizing repetitive patterns leading to accidents involving them, to highlight the magnitude of the problem by analyzing a 10-year pedestrian crash database, to develop a model predicting—on the basis of the recognized patterns—the severity level of collisions involving older pedestrians, and, finally, on the basis of the highlighted factors, to propose some countermeasures to improve their safety. In order to achieve this goal, first, a statistical analysis of the database is performed, considering 13 factors that lead to accidents. Second, Kolmogorov–Smirnov and Anderson–Darling tests are performed to check if the data follow a normal distribution. Finally, an ordinal logistic regression model is proposed to determine the relationship between the crash severity level and the factors characterizing collisions. Thanks to this model, the statistical influencing factors are highlighted. Finally, based on the previous analysis, some technical and educational countermeasures are proposed. [ABSTRACT FROM AUTHOR]

Despite the highly secure content sharing and the optimized forwarding mechanism, the content delivery in a Named Data Network (NDN) still suffers from numerous vulnerabilities that can be exploited to reduce the efficiency of such architecture. Malicious attacks in NDN have become more sophisticated and the foremost challenge is to identify unknown and obfuscated malware, as the malware authors use different evasion techniques for information concealing to prevent detection by an Intrusion Detection System (IDS). For the most part, NDN faces immense negative impacts from attacks such as Cache Pollution Attacks (CPA), Cache Privacy Attacks, Cache Poisoning Attacks, and Interest Flooding Attacks (IFA), that target different security components, including availability, integrity, and confidentiality. This poses a critical challenge to the design of IDS in NDN. This paper provides the latest taxonomy, together with a review of the significant research works on IDSs up to the present time, and a classification of the proposed systems according to the taxonomy. It provides a structured and comprehensive overview of the existing IDSs so that a researcher can create an even better mechanism for the previously mentioned attacks. This paper discusses the limits of the techniques applied to design IDSs with recent findings that can be further exploited in order to optimize those detection and mitigation mechanisms. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) has provided substantial enhancements to the communication of sensors, actuators, and their controllers, particularly in the field of home automation. Home automation is experiencing a huge rise in the proliferation of IoT devices such as smart bulbs, smart switches, and control gateways. However, the main challenge for such control systems is how to maximize security under limited resources such as low-processing power, low memory, low data rate, and low-bandwidth IoT networks. In order to address this challenge the adoption of IoT devices in automation has mandated the adoption of secure communication protocols to ensure that compromised key security objectives, such as confidentiality, integrity, and availability are addressed. In light of this, this work evaluates the feasibility of MQTT-based Denial of Service (DoS) attacks, Man-in-the-Middle (MitM), and masquerade attacks on a ZigBee network, an IoT standard used in wireless mesh networks. Performed through MQTT, the attacks extend to compromise neighboring Constrained Application Protocol (CoAP) nodes, a specialized service layer protocol for resource-constrained Internet devices. By demonstrating the attacks on an IKEA TRÅDFRI lighting system, the impact of exploiting ZigBee keys, the basis of ZigBee security, is shown. The reduction of vulnerabilities to prevent attacks is imperative for application developers in this domain. Two Intrusion Detection Systems (IDSs) are proposed to mitigate against the proposed attacks, followed by recommendations for solution providers to improve IoT firmware security. The main motivation and purpose of this work is to demonstrate that conventional attacks are feasible and practical in commercial home automation IoT devices, regardless of the manufacturer. Thus, the contribution to the state-of-the-art is the design of attacks that demonstrate how known vulnerabilities can be exploited in commercial IoT devices for the purpose of motivating manufacturers to produce IoT systems with improved security. [ABSTRACT FROM AUTHOR]

Automatic speaker verification (ASV) systems play a prominent role in the security field due to the usability of voice biometrics compared to alternative biometric authentication modalities. Nevertheless, ASV systems are susceptible to malicious voice spoofing attacks. In response to such threats, countermeasures have been devised to prevent breaches and ensure the safety of user data by categorizing utterances as either genuine or spoofed. In this paper, we propose a new voice spoofing countermeasure that seeks to improve the generalization of supervised learning models. This is accomplished by alleviating the problem of intraclass variance. Specifically, the proposed approach addresses the generalization challenge by splitting the classification problem into a set of local subproblems in order to lessen the supervised learning task. The system outperformed existing state-of-the-art approaches with an EER of 0.097% on the ASVspoof challenge corpora related to replaying spoofing attacks. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) interconnects physical and virtual objects embedded with sensors, software, and other technologies, which exchange data using the Internet. This technology allows billions of devices and people to communicate, share data, and personalize services to make our lives easier. Despite the multiple benefits offered by IoT, it may also represent a critical issue due its lack of information security. Since the number of IoT devices has been rapidly increasing all over the world, they have become a target for many attackers, who try to steal sensitive information and compromise people's privacy. As part of the IoT environment, data and services should be protected with features such as confidentiality, accuracy, comprehensiveness, authentication, access control, availability, and privacy. Cybersecurity threats are unique to the Internet of Things, which has unique characteristics and limitations. In consideration of this, a variety of threats and attacks are being launched daily against IoT. Therefore, it is important to identify these types of threats and find solutions to mitigate their risks. Therefore, in this paper, we reviewed and identified the most common threats in the IoT environment, and we classified these threats based on three layers of IoT architecture. In addition, we discussed the most common countermeasures to control the IoT threats and mitigation techniques that can be used to mitigate these threats by reviewing the related publications, as well as analyzing the popular application-layer protocols employed in IoT environments and their security risks and challenges. [ABSTRACT FROM AUTHOR]

The 2022 global human monkeypox outbreak emphasizes the importance of maintaining poxvirus research, including enriching a basic understanding of animal models for developing and advancing therapeutics and vaccines. Intravenous administration of monkeypox virus in macaques is arguably one of the best animal models for evaluating the efficacy of medical countermeasures. Here we addressed one criticism of the model, a requirement for a high-titer administration of virus, as well as improving our understanding of monkeypox virus pathogenesis. To do so, we infected macaques with a challenge dose containing a characterized inoculum enriched for the extracellular form of monkeypox virus. Although there were some differences between diseases caused by the enriched preparation compared with a relatively similar unpurified preparation, we were unable to reduce the viral input with the enriched preparation and maintain severe disease. We found that inherent factors contained within the serum of nonhuman primate blood affect the stability of the monkeypox extracellular virions. As a first step to study a role of the extracellular form in transmission, we also showed the presence of this form in the oropharyngeal swabs from nonhuman primates exposed to monkeypox virus. [ABSTRACT FROM AUTHOR]

Casing deformation caused by fault and fracture sliding derived from fracturing has attracted growing attention. Casing deformation frequently occurs during the hydraulic fracturing process in the Sichuan Basin. Although its mechanism has been intensively studied, this issue is becoming increasingly severe and demands immediate solutions, especially in the shale gas blocks of Changning-Weiyuan-Zhaotong. The present study summarizes and analyzes the research progress relevant to casing deformation based on the existing literature. It is shown that the casing deformation rate of the deflection point on the shale gas horizontal well is much higher than that of other places and that shear deformation is the dominant form. The main factors influencing the casing deformation of shale gas horizontal wells include weakened strength of the collapsing casing, geological factors, cement, cement quality sheath, fracturing engineering factor, etc. We propose to reduce casing deformation by optimizing well trajectory, improving casing strength and cementing quality or optimizing fracturing operation. In addition, a hierarchical relationship between the influencing factors is also provided. However, the mechanisms of some forms of casing deformation need to be further studied, and the casing deformation in shale gas exploitation must be solved urgently. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has sharply reduced air travel demand since early 2020. This paper aims to identify factors influencing Korean passengers' air travel confidence after COVID-19 based on three countermeasure classifications: social distancing, health, and vaccination. Data were collected online from 307 Korean air passengers from December 2021 to January 2022. Structural equation modeling (SEM) was used to examine countermeasure influence on air passenger confidence. Health measures (face mask, temperature screening, and hand sanitizing) scored the highest on importance and air travel safety sensitivity. Social distancing measures (physical distancing, contactless boarding process, and sneeze guards) scored the lowest but were still perceived to be important. Only vaccine measures (vaccine pass check-in, vaccination rates, and personal vaccination status) were identified as having a significantly positive influence on Korean air travel confidence. The study's results do not support past studies showing social distancing and health measures partially or fully influencing air travel confidence. This finding has significant implications for understanding how Korean passengers' perceptions and perceived sense of safety are different or have changed two years into the crisis, as well as for achieving sustainability of the aviation and travel industries after COVID-19. [ABSTRACT FROM AUTHOR]

For over two decades, researchers have sought to improve smallpox vaccines and also develop therapies to ensure protection against smallpox or smallpox-like disease. The 2022 human monkeypox pandemic is a reminder that these efforts should persist. Advancing such therapies have involved animal models primarily using surrogate viruses such as monkeypox virus. The intravenous monkeypox model in macaques produces a disease that is clinically similar to the lesional phase of fulminant human monkeypox or smallpox. Two criticisms of the model have been the unnatural route of virus administration and the high dose required to induce severe disease. Here, we purified monkeypox virus with the goal of lowering the challenge dose by removing cellular and viral contaminants within the inoculum. We found that there are advantages to using unpurified material for intravenous exposures. [ABSTRACT FROM AUTHOR]

The use of unmanned aerial vehicles (UAVs) for different applications has increased tremendously during the past decade. The small size, high maneuverability, ability to fly at predetermined coordinates, simple construction, and affordable price have made UAVs a popular choice for diverse aerial applications. However, the small size and the ability to fly close to the terrain make the detection and tracking of UAVs challenging. Similarly, unmanned underwater vehicles (UUVs) have revolutionized underwater operations. UUVs can accomplish numerous tasks that were not possible with manned underwater vehicles. In this survey paper, we provide features and capabilities expected from current and future UAVs and UUVs, and review potential challenges and threats due to use of such UAVs/UUVs. We also overview the countermeasures against such threats, including approaches for the detection, tracking, and classification of UAVs and UUVs. [ABSTRACT FROM AUTHOR]

Access to adequate and appropriate transport options enables older people to continue as thriving community participants, to reach services and to maintain social connections. While transport needs are diverse, and tend to change over time, there is little information on current and future transport patterns, and the awareness, acceptance and adoption of new technologies. A national online survey was administered to current drivers in Australia. A sample of 705 drivers provided information on available travel modes and use of these modes, awareness of in-vehicle technologies and future use of vehicle technologies. The findings revealed high use of private vehicles, walking and taxis but little use of other travel modes (bicycles, motorcycles, rideshare, community services and public transport). Age, gender and residential location influenced the availability and use/potential use of some transport options. Overall awareness of in-vehicle technologies was generally low and particularly so amongst older and female participants. There was some appetite to use emerging technologies in the future. The findings inform the development of effective strategies and initiatives aligned with healthy ageing and wellbeing targets, increased sustainability, resilience and connectedness, creation of healthier travel choices and healthier environments to promote acceptance and use of a range of transport options and uptake of safer vehicles equipped with in-vehicle technologies to ultimately enhance safe and sustainable mobility of older road users. [ABSTRACT FROM AUTHOR]

The process of urbanization and urban regeneration is inseparable from the implementation of urban construction projects. Current studies show a large amount of collusive bidding in urban construction projects, which has seriously affected healthy and sustainable urban development. Therefore, the governance of collusive bidding in urban construction projects is crucial to sustainable urbanization and urban renewal. In reality, the collusion information dissemination (CID) is a key influential factor in the bidder's collusive willingness (BCW). Knowing the influence of CID on BCW will help city managers to have a clearer understanding of the causes and governance focus of collusive bidding. Thus, the study using the multi-agent simulation technology simulates the influence of CID on BCW in different market scales, communication intensities, and trust boundaries based on the Deffuant model. The research found that the negative impact of the CID on the market is more incredible in cities with smaller market sizes, and effectively inhibiting the CID can reduce the occurrence of collusion. Moreover, the research also found that colluders always form their collusive alliances within CID networks. These findings suggest that urban managers should strengthen the suppression of collusive bidding by weakening the dissemination of collusive information and blocking the CID networks. [ABSTRACT FROM AUTHOR]

Botulinum neurotoxins (BoNTs) are produced as protein complexes by bacteria of the genus Clostridium that are Gram-positive, anaerobic and spore forming (Clostridium botulinum, C. butyricum, C. baratii and C. argentinense spp.). BoNTs show a high immunological and genetic diversity. Therefore, fast, precise, and more reliable detection methods are still required to monitor outbreaks and ensure surveillance of botulism. The botulinum toxin field also comprises therapeutic uses, basic research studies and biodefense issues. This review presents currently available detection methods, and new methods offering the potential of enhanced precision and reproducibility. While the immunological methods offer a range of benefits, such as rapid analysis time, reproducibility and high sensitivity, their implementation is subject to the availability of suitable tools and reagents, such as specific antibodies. Currently, the mass spectrometry approach is the most sensitive in vitro method for a rapid detection of active or inactive forms of BoNTs. However, these methods require inter-laboratory validation before they can be more widely implemented in reference laboratories. In addition, these surrogate in vitro models also require full validation before they can be used as replacement bioassays of potency. Cell-based assays using neuronal cells in culture recapitulate all functional steps of toxin activity, but are still at various stages of development; they are not yet sufficiently robust, due to high batch-to-batch cell variability. Cell-based assays have a strong potential to replace the mouse bioassay (MBA) in terms of BoNT potency determination in pharmaceutical formulations; they can also help to identify suitable inhibitors while reducing the number of animals used. However, the development of safe countermeasures still requires the use of in vivo studies to complement in vitro immunological or cell-based approaches. [ABSTRACT FROM AUTHOR]

Intelligent Transport Systems (ITSs) are part of road transportation sector evolution and constitute one of the main steps towards vehicle automation. These systems use technologies that allow vehicles to communicate with each other or with road infrastructure. By increasing information quality and reliability, ITSs can improve road safety and traffic efficiency, but only if cybersecurity and data protection is ensured. With the increase in the number of cyberattacks around the world, cybersecurity is receiving increased attention, especially in the area of transportation security. However, it is equally important to examine and analyze security in depth when it concerns connected vehicles. In this paper, we propose a qualitative risk analysis of ITSs based on Threat, Risk, Vulnerability Analysis (TVRA) methodology, and we focus on ETSI ITS communication architecture. We present a review of solutions and countermeasures for identified critical attacks. [ABSTRACT FROM AUTHOR]

A Global Positioning System (GPS) spoofing attack can be launched against any commercial GPS sensor in order to interfere with its navigation capabilities. These sensors are installed in a variety of devices and vehicles (e.g., cars, planes, cell phones, ships, UAVs, and more). In this study, we focus on micro UAVs (drones) for several reasons: (1) they are small and inexpensive, (2) they rely on a built-in camera, (3) they use GPS sensors, and (4) it is difficult to add external components to micro UAVs. We propose an innovative method, based on the video stream captured by a drone's camera, for the real-time detection of GPS spoofing attacks targeting drones. The proposed method collects frames from the video stream and their location (GPS coordinates); by calculating the correlation between each frame, our method can detect GPS spoofing attacks on drones. We first analyze the performance of the suggested method in a controlled environment by conducting experiments on a flight simulator that we developed. Then, we analyze its performance in the real world using a DJI drone. Our method can provide different levels of security against GPS spoofing attacks, depending on the detection interval required; for example, it can provide a high level of security to a drone flying at altitudes of 50–100 m over an urban area at an average speed of 4 km/h in conditions of low ambient light; in this scenario, the proposed method can provide a level of security that detects any GPS spoofing attack in which the spoofed location is a distance of 1–4 m (an average of 2.5 m) from the real location. [ABSTRACT FROM AUTHOR]

This short communication reports a water inrush hazard during the construction of the Shijingshan Tunnel in Zhuhai, Guangdong, China. On 15 July 2021, a water inrush accident occurred at the construction site 1.16 km away from the tunnel entrance, resulting in 14 casualties. The purpose of this study is to investigate and discuss the water inrush process in this atypical case. The principal causes of this tunneling accident include the special geological conditions at the construction site, high hydraulic conductivity at the part that connects the underground water system and the overlying water body (the Jida Reservoir), and the impact of heavy rainfall. Moreover, four significant suggestions are proposed to prevent the possible occurrence of water inrush disaster: (1) assessing the risk level in areas prone to water inrush; (2) getting a comprehensive geological prediction based on borehole data and artificial intelligent methods; (3) establishing a monitoring system during the tunneling process; (4) strengthening the self-protection skills of construction workers. [ABSTRACT FROM AUTHOR]

Hate speech expresses prejudice and discrimination based on actual or perceived innate characteristics such as gender, race, religion, ethnicity, colour, national origin, disability or sexual orientation. Research has proven that the amount of hateful messages increases inevitably on online social media. Although hate propagators constitute a tiny minority—with less than 1% participants—they create an unproportionally high amount of hate motivated content. Thus, if not countered properly, hate speech can propagate through the whole society. In this paper we apply agent-based modelling to reproduce how the hate speech phenomenon spreads within social networks. We reuse insights from the research literature to construct and validate a baseline model for the propagation of hate speech. From this, three countermeasures are modelled and simulated to investigate their effectiveness in containing the spread of hatred: Education, deferring hateful content, and cyber activism. Our simulations suggest that: (1) Education consititutes a very successful countermeasure, but it is long term and still cannot eliminate hatred completely; (2) Deferring hateful content has a similar—although lower—positive effect than education, and it has the advantage of being a short-term countermeasure; (3) In our simulations, extreme cyber activism against hatred shows the poorest performance as a countermeasure, since it seems to increase the likelihood of resulting in highly polarised societies. [ABSTRACT FROM AUTHOR]

Industrial Internet of Things (IIoT) can be seen as an extension of the Internet of Things (IoT) services and applications to industry with the inclusion of Industry 4.0 that provides automation, reliability, and control in production and manufacturing. IIoT has tremendous potential to accelerate industry automation in many areas, including transportation, manufacturing, automobile, marketing, to name a few places. When the benefits of IIoT are visible, the development of large-scale IIoT systems faces various security challenges resulting in many large-scale cyber-attacks, including fraudulent transactions or damage to critical infrastructure. Moreover, a large number of connected devices over the Internet and resource limitations of the devices (e.g., battery, memory, and processing capability) further pose challenges to the system. The IIoT inherits the insecurities of the traditional communication and networking technologies; however, the IIoT requires further effort to customize the available security solutions with more focus on critical industrial control systems. Several proposals discuss the issue of security, privacy, and trust in IIoT systems, but comprehensive literature considering the several aspects (e.g., users, devices, applications, cascading services, or the emergence of resources) of an IIoT system is missing in the present state of the art IIoT research. In other words, the need for considering a vision for securing an IIoT system with broader security analysis and its potential countermeasures is missing in recent times. To address this issue, in this paper, we provide a comparative analysis of the available security issues present in an IIoT system. We identify a list of security issues comprising logical, technological, and architectural points of view and consider the different IIoT security requirements. We also discuss the available IIoT architectures to examine these security concerns in a systematic way. We show how the functioning of different layers of an IIoT architecture is affected by various security issues and report a list of potential countermeasures against them. This study also presents a list of future research directions towards the development of a large-scale, secure, and trustworthy IIoT system. The study helps understand the various security issues by indicating various threats and attacks present in an IIoT system. [ABSTRACT FROM AUTHOR]

Featured Application: Integration of a proposed resilience modeling framework within an approach for the optimization of measures to boost power system resilience. Severe natural events leading to wide and intense impacts on power systems are becoming more and more frequent due to climate changes. Operators are urged to set up plans to assess the possible consequences of such events, in view of counteracting them. To this aim, the application of the resilience concept can be beneficial. The paper describes a methodology for power system resilience assessment and enhancement, aimed at quantifying both system resilience indicators evaluated for severe threats, and the benefits to resilience brought by operational and grid hardening measures. The capabilities of the methodology are demonstrated on real study cases. [ABSTRACT FROM AUTHOR]

This work proposes an approach based on dynamic Bayesian networks to support the cybersecurity analysis of network-based controllers in distributed energy plants. We built a system model that exploits real world context information from both information and operational technology environments in the energy infrastructure, and we use it to demonstrate the value of security evidence for time-driven predictive and diagnostic analyses. The innovative contribution of this work is in the methodology capability of capturing the causal and temporal dependencies involved in the assessment of security threats, and in the introduction of security analytics supporting the configuration of anomaly detection platforms for digital energy infrastructures. [ABSTRACT FROM AUTHOR]

With the increasing number of side-channel attacks, countermeasure designers continue to develop various implementations to address such threats. Power-balancing (PB) methods hold the number of 1s and/or transitions (i.e., Hamming weight/distance) of internal processes constant to ensure side-channel safety in an environment in which it is difficult to use random numbers. Most existing studies employed look-up tables (LUTs) to compute those operations, except for XOR and NOT operations. However, LUT-based schemes exhibit some side-channel issues in the address bits of LUTs. In this paper, we propose the application of AND and ADD operations to PB methods based on a rule that encodes 8-bit data into a 32-bit codeword without using LUTs. Unlike previous studies that employed LUTs, our proposals overcome side-channel vulnerabilities associated with the address bits and memory wastage. In addition, we evaluate the side-channel security ensured by the proposed method in comparison with that ensured by other methods. Finally, we apply our methods to SIMON/SPECK ciphers and analyze their performance by comparing them with older schemes. [ABSTRACT FROM AUTHOR]

As threat vectors and adversarial capabilities evolve, Cloud-Assisted Connected and Autonomous Vehicles (CCAVs) are becoming more vulnerable to cyberattacks. Several established threat analysis and risk assessment (TARA) methodologies are publicly available to address the evolving threat landscape. However, these methodologies inadequately capture the threat data of CCAVs, resulting in poorly defined threat boundaries or the reduced efficacy of the TARA. This is due to multiple factors, including complex hardware-software interactions, rapid technological advancements, outdated security frameworks, heterogeneous standards and protocols, and human errors in CCAV systems. To address these factors, this study begins by systematically evaluating TARA methods and applying the Spoofing, Tampering, Repudiation, Information disclosure, Denial of service, and Elevation of privileges (STRIDE) threat model and Damage, Reproducibility, Exploitability, Affected Users, and Discoverability (DREAD) risk assessment to target system architectures. This study identifies vulnerabilities, quantifies risks, and methodically examines defined data processing components. In addition, this study offers an attack tree to delineate attack vectors and provides a novel defense taxonomy against identified risks. This article demonstrates the efficacy of the TARA in systematically capturing compromised security requirements, threats, limits, and associated risks with greater precision. By doing so, we further discuss the challenges in protecting hardware-software assets against multi-staged attacks due to emerging vulnerabilities. As a result, this research informs advanced threat analyses and risk management strategies for enhanced security engineering of cyberphysical CCAV systems.

1. Background: Fishers face many occupational hazards that include a high risk of fatal and nonfatal injuries and a variety of adverse health effects. Our purpose is to provide an overview of potential countermeasures for the control of hazards that threaten the health and safety of Gulf of Mexico (GoM) fish harvesters. 2. Method: Search terms were used to identify relevant literature; two previous reviews regarding injuries and health risk factors also inform this review. 3. Results: Countermeasures against these hazards include winch guards, lifting devices, job redesign, non-slip decks and vessel stability controls as well as using personal flotation devices, wearing gloves and high-friction footwear, increasing sleep time and using vessel motion to assist lifting. Knowledge about secondary prevention (such as rescue, first aid and making mayday calls) is also important. Learning through experience is a crucial factor that incorporates other fishers' experiences with innovations. Fatigue and lack of sleep contribute to vessel disasters and injury-related errors. 4. Conclusions: The prevention of injuries and diseases among GoM fishers depends on a combination of focusing on work-processes, instilling a broader safety culture, engineering controls, identifying and sharing fisher innovations, promoting fall overboard prevention and protection and providing culture-based incentives, training and narrative outreach. [ABSTRACT FROM AUTHOR]

Ricin, a plant-derived toxin originating from the seeds of Ricinus communis (castor beans), is one of the most lethal toxins known, particularly if inhaled. Ricin is considered a potential biological threat agent due to its high availability and ease of production. The clinical manifestation of pulmonary ricin intoxication in animal models is closely related to acute respiratory distress syndrome (ARDS), which involves pulmonary proinflammatory cytokine upregulation, massive neutrophil infiltration and severe edema. Currently, the only post-exposure measure that is effective against pulmonary ricinosis at clinically relevant time-points following intoxication in pre-clinical studies is passive immunization with anti-ricin neutralizing antibodies. The efficacy of this antitoxin treatment depends on antibody affinity and the time of treatment initiation within a limited therapeutic time window. Small-molecule compounds that interfere directly with the toxin or inhibit its intracellular trafficking may also be beneficial against ricinosis. Another approach relies on the co-administration of antitoxin antibodies with immunomodulatory drugs, thereby neutralizing the toxin while attenuating lung injury. Immunomodulators and other pharmacological-based treatment options should be tailored according to the particular pathogenesis pathways of pulmonary ricinosis. This review focuses on the current treatment options for pulmonary ricin intoxication using anti-ricin antibodies, disease-modifying countermeasures, anti-ricin small molecules and their various combinations. [ABSTRACT FROM AUTHOR]

Cloud Computing is a computingmodel that allows ubiquitous, convenient and on-demand access to a shared pool of highly configurable resources (e.g., networks, servers, storage, applications and services). Denial-of-Service (DoS) and Distributed Denial-of-Service (DDoS) attacks are serious threats to the Cloud services' availability due to numerous new vulnerabilities introduced by the nature of the Cloud, such as multi-tenancy and resource sharing. In this paper, new types of DoS and DDoS attacks in Cloud Computing are explored, especially the XML-DoS and HTTP-DoS attacks, and some possible detection and mitigation techniques are examined. This survey also provides an overview of the existing defense solutions and investigates the experiments and metrics that are usually designed and used to evaluate their performance, which is helpful for the future research in the domain. [ABSTRACT FROM AUTHOR]

The efficiency of six countermeasures (CM) for muscle atrophy was compared over 520 days of confinement during the terrestrial simulation of round space flight to Mars using surface electromyography (sEMG). Three of CM were cyclic exercises (a motor-driven and leg-driven treadmill, cycle ergometer), resistive exercises (the multifunctional dynamometer for space—MDS, and expanders), and vibration platform. Each of CM was applied for each crew member ( n = 6) once over the experiment, for 70 days in a row, in prescribed order. sEMG was collected during the “force step test” in which the subject voluntarily produced pressure by lower limb, with minimal force increment. The mean frequency (MNF) and average amplitude of sEMG were analyzed. The MNF of sEMG decreased from 104.3 ± 4.2 to 95.3 ± 2.9 Hz ( P < 0.05) in the soleus muscle after 70 days of exercising on the leg-driven treadmill and after 35 days—on vibration platform. It can be caused by earlier (10–250 ms) recruitment of the soleus in respect with the medial gastronemius on the leg-driven treadmill, while on the motor-driven treadmill synergists activated synchronously. In other lower leg muscles, MNF decreased from 180 to 200 to 165–180 Hz after 70 days of resistive exercises on the MDS device. CM caused no effect on sEMG amplitude. In conclusion, (1) the leg-driven treadmill, the MDS and vibration platform significantly depressed MNF of sEMG of lower extremity muscles; (2) the leg-driven treadmill and vibration platform specifically affected the soleus muscle. Therefore, these CM can be recommended for a more extensive use on ISS board. [ABSTRACT FROM AUTHOR]

Life on Earth has evolved continuously under Earth's 1 G force and the protection of the magnetosphere. Thus, astronauts exhibit maladaptive physiological responses during space travel. Exposure to harmful cosmic radiation and weightlessness are unique conditions to the deep-space environment responsible for several spaceflight-associated risks: visual impairment, immune dysfunction, and cancer due to cosmic radiation in astronauts. The evidence thus reviewed indicates that microgravity and cosmic radiation have deleterious effects on the cardiovascular, lymphatic, and vision systems of astronauts on long-duration space missions. The mechanisms responsible for the decline in these systems are potentially due to cytoskeletal filament rearrangement, endothelial dysfunction, and muscular atrophy. These factors may alter fluid hemodynamics within cardiovascular and lymphatic vasculatures such that greater fluid filtration causes facial and intracranial edema. Thus, microgravity induces cephalad fluid shifts contributing to spaceflight-associated neuro-ocular syndrome (SANS). Moreover, visual impairment via retinal ischemia and altered nitric oxide production may alter endothelial function. Based on rodent studies, cosmic radiation may exacerbate the effects of microgravity as observed in impaired endothelium and altered immunity. Relevant findings help understand the extent of these risks associated with spaceflight and suggest relevant countermeasures to protect astronaut health during deep-space missions. [ABSTRACT FROM AUTHOR]

Introduction: We reviewed and compared current drug shortages and shortage management practices in six selected countries (Hungary, Belgium, Spain, Switzerland, Australia, United States) based on the most comprehensive national shortage databases for each country, for four Anatomical Therapeutic Chemical (ATC) groups, to analyze the criticality of drug shortages across countries and identify best practices in shortage management strategies., Materials and Methods: Countries were selected to cover a wide geographical range of high-income nations where a lack of economic power as a potential source of drug shortages is not observable. ATC groups were selected based on a pre-examination of the databases to analyze groups most often in shortage, and groups where the absence of which could have a severe negative impact on treatment outcomes. The bias originating from the different reporting systems had to be reduced to gain comprehensive and comparable information. The first bias-reducing mechanism was transforming the raw number of shortages into proportion per million people. Secondly, critical cases were classified, and thirdly, critical cases were compared with the Word Health Organization (WHO) Essential Medicine Lists., Results: The results indicate that every European country studied reports significantly higher total and critical shortages per population compared to the US and Australia. Within Europe, Hungary reports the highest number of cases both for total and critical shortages, while Spain has the lowest results in both aspects. While in the US and Australia critical shortages were observable in similar proportions across all ATC groups, in European countries ATC groups of anti-infectives for systemic use (J) and the nervous system (N) were found to account for a notably higher proportion of critical shortages. Current shortage management practices were examined in each country and classified into five groups to identify common best practices., Conclusions: Due to the different characterization of reporting systems, several bias-reducing mechanisms should be applied to compare and evaluate shortages. In addition, European harmonization should be initiated to create mutually acknowledged definitions and reporting systems, which could be the basis of good drug shortage handling practices in Europe.

As of 2021, the biothreat policy and research communities organize their efforts around lists of priority agents, which elides consideration of novel pathogens and biotoxins. For example, the Select Agents and Toxins list is composed of agents that historic biological warfare programs had weaponized or that have previously caused great harm during natural outbreaks. Similarly, lists of priority agents promulgated by the World Health Organization and the National Institute of Allergy and Infectious Diseases are composed of previously known pathogens and biotoxins. To fill this gap, we argue that the research/scientific and biodefense/biosecurity communities should categorize agents based on how they impact their hosts to augment current list-based paradigms. Specifically, we propose integrating the results of multi-omics studies to identify bioagent-agnostic signatures (BASs) of disease—namely, patterns of biomarkers that accurately and reproducibly predict the impacts of infection or intoxication without prior knowledge of the causative agent. Here, we highlight three pathways that investigators might exploit as sources of signals to construct BASs and their applicability to this framework. The research community will need to forge robust interdisciplinary teams to surmount substantial experimental, technical, and data analytic challenges that stand in the way of our long-term vision. However, if successful, our functionality-based BAS model could present a means to more effectively surveil for and treat known and novel agents alike. [ABSTRACT FROM AUTHOR]