Search Results (1,182)

Deep neural network-based synthetic aperture radar (SAR) automatic target recognition (ATR) systems are susceptible to attack by adversarial examples, which leads to misclassification by the SAR ATR system, resulting in theoretical model robustness problems and security problems in practice. Inspired by optical images, current SAR ATR adversarial example generation is performed in the image domain. However, the imaging principle of SAR images is based on the imaging of the echo signals interacting between the SAR and objects. Generating adversarial examples only in the image domain cannot change the physical world to achieve adversarial attacks. To solve these problems, this article proposes a framework for generating SAR adversarial examples in a 3D physical scene. First, adversarial attacks are implemented in the 2D image space, and the perturbation in the image space is converted into simulated rays that constitute SAR images through backpropagation optimization methods. The mapping between the simulated rays constituting SAR images and the 3D model is established through coordinate transformation, and point correspondence to triangular faces and intensity values to texture parameters are established. Thus, the simulated rays constituting SAR images are mapped to the 3D model, and the perturbation in the 2D image space is converted back to the 3D physical space to obtain the position and intensity of the perturbation in the 3D physical space, thereby achieving physical adversarial attacks. The experimental results show that our attack method can effectively perform SAR adversarial attacks in the physical world. In the digital world, we achieved an average fooling rate of up to 99.02% for three objects in six classification networks. In the physical world, we achieved an average fooling rate of up to 97.87% for these objects, with a certain degree of transferability across the six different network architectures. To the best of our knowledge, this is the first work to implement physical attacks in a full physical simulation condition. Our research establishes a theoretical foundation for the future concealment of SAR targets in practical settings and offers valuable insights for enhancing the attack and defense capabilities of subsequent DNNs in SAR ATR systems. Full article

In a distributed wireless sensor network (DWSN), sensors continuously perceive the environment, collect data, and transmit it to remote users through the network so as to realize real-time monitoring of the environment or specific targets. However, given the openness of wireless channels and the sensitivity of collecting data, designing a robust user authentication protocol to ensure the legitimacy of user and sensors in such DWSN environments faces serious challenges. Most of the current authentication schemes fail to meet some important and often overlooked security features, such as resisting physical impersonation attack, resisting smartcard loss attack, and providing forward secrecy. In this work, we put forward a practically secure two-factor authentication scheme using a physically unclonable function to prevent a physical impersonation attack and sensor node capture attack, utilize Chebyshev chaotic mapping to provide forward secrecy, and improve the efficiency and security of session key negotiation. Furthermore, we use the fuzzy verifier technique to prevent attackers from offline guessing attacks to resist smartcard loss attacks. In addition, a BAN logic proof and heuristic security analysis show that the scheme achieves mutual authentication and key agreement as well as prevents known attacks. A comparative analysis with state-of-the-art schemes shows that the proposal not only achieves desired security features but also maintains better efficiency. Full article

Battery energy storage systems (BESSs) play a crucial role in integrating renewable energy sources into microgrids. However, robust BESS controllers are needed to carry out this function properly. Existing controllers suffer from overshoots and slow convergence issues. Moreover, as electrical grid networks become increasingly connected, the risk of cyberattacks grows, and traditional physics-based anomaly detection methods face challenges such as reliance on predefined models, high computational demands, and limited scalability for complex, large-scale data. To address the limitations of the existing approaches, this paper first proposes a novel sigma-delta modulation (SDM) controller for BESSs in solar photovoltaic (PV)-connected microgrids. The performance of SDM has been compared with those of the proportional–integral (PI) controller and fuzzy logic controller (FLC). Also, this paper proposes an improved ensemble-based method to detect the false data injection (FDI) and denial-of-service (DoS) attacks on the BESS controller. The performance of the proposed detection method has been compared with that of the traditional ensemble-based method. Four PV-connected microgrid systems, namely the solar DC microgrid, grid-connected solar AC microgrid, hybrid AC microgrid with two BESSs, and hybrid AC microgrid with a single BESS, have been considered to show the effectiveness of the proposed control and detection methods. The MATLAB/Simulink-based results show the effectiveness and better performance of the proposed controller and detection methods. Numerical results demonstrate the improved performance of the proposed SDM controller, with a 35% reduction in AC bus voltage error compared to the conventional PI controller and FLC. Similarly, the proposed SAMME AdaBoost detection method achieves superior accuracy with an F1 score of 95%, outperforming the existing ensemble approaches. Full article

Workplace violence (WV) is a ubiquitous, yet under-reported and under-studied phenomenon. Prevention measures may be ineffective because risk assessment is often based on unvalidated algorithms. After monitoring the risk of WV in a healthcare company for over 20 years, this paper presents the results collected in 2023 and details of the methodology used. Monitoring WV in health surveillance can involve three actions: (1) asking all the workers who attend periodic medical examinations in the workplace whether they have suffered physical aggression, threats, or harassment in the previous year; (2) investigating WV at the end of workplace inspections by setting up participatory ergonomics groups (PEGs) to suggest solutions; (3) investigating the characteristics and consequences of WV through anonymous online questionnaires. In 2023, 6.9% of the healthcare workers (HCWs) reported having experienced one or more physical attacks during the previous year; 12.7% reported having been threatened, and 12.9% reported other types of violent, harassing behavior. The HCWs observed an increase in violence after the pandemic years and, in the PEGs, suggested using different preventive measures in different health departments. The online survey provided further information on the characteristics of WV and its consequences. The risk of WV can be effectively characterized and measured through health surveillance. Full article

Background: Systemic inflammation, attacks, deterioration of thoracic region mechanics, medications used, and decreased physical activity level (PAL) and fitness negatively may affect respiratory muscle strength. The primary aim of this study was to evaluate dynamic inspiratory muscle strength (S-index), PAL, and physical fitness in children with asthma compared to healthy peers. The secondary aim of this study was to investigate the relationships between S-index and peak inspiratory flow (PIF) values and functional parameters in childhood asthma. Methods: This cross-sectional prospective study consisted of participants of 6–11 years of age, specifically, 20 children with asthma and 20 healthy peers. The device (POWERbreathe K5) evaluated PIF and S-index variables. PAL was determined with the Physical Activity Questionnaire-Child (PAQ-C) and fitness was evaluated with the FITNESSGRAM test battery. Results: The PIF Average (Avg): 1.8 ± 0.6, Best: 2.6 ± 0.6 (asthmatic children) vs. Avg: 2.4 ± 0.7, Best: 3.1 ± 0.9 (healthy children); p = 0.017, p = 0.027, respectively) and S-index (Avg: 34.1 ± 10.3, Best: 45.6 ± 9.9 (asthmatic children) vs. Avg: 43.2 ± 12.1, Best: 56.6 ± 14.7 (healthy children); p = 0.015, p = 0.008 respectively) values of children with asthma were significantly lower compared to healthy peers. The PAL and physical fitness of asthmatic and healthy peers were similar (p > 0.05). There were significant relationships between S-indexavg and S-indexbest with the PAQ-C score (r = 0.498, p < 0.025 r = 0.547, p < 0.013, respectively) and PIFavg and PIFbest with the PAQ-C score (r = 0.490, p < 0.028 r = 0.602, p < 0.005) in children with asthma. Conclusions: Dynamic respiratory muscle strength is negatively affected in children with asthma whereas their physical activity and fitness levels are comparable to their peers. However, it was found that children with a higher S-index and PIF rate had higher PALs. These findings suggest that pulmonary rehabilitation interventions to improve respiratory muscle function should be considered an important strategy to maintain and increase physical activity levels in children with asthma. Full article

Cementitious materials are susceptible to damage not only from mechanical loading, but also from environmental (physical, chemical, and biological) factors. For Textile-Reinforced Cementitious (TRC) composites, durability poses a significant challenge, and a reliable method to assess long-term performance is still lacking. Among various durability attacks, freeze–thaw can induce internal cracking within the cementitious matrix, and weaken the textile–matrix bond. Such cracks result from hydraulic, osmotic, and crystallization pressure arising from the thermal cycles, leading to a reduction in the stiffness in the TRC composites. Early detection of freeze–thaw deterioration can significantly reduce the cost of repair, which is only possible through periodic, full-field monitoring of the composite. Full-field monitoring provides a comprehensive view of the damage distribution, offering valuable insights into the causes and progression of damage. The crack location, size, and pattern give more information than that offered by single-point measurement. While visual inspections are commonly employed for crack assessment, they are often time-consuming. Technological advances now enable crack pattern classification based on high-quality surface images; however, these methods only provide information limited to the surface. Elastic wave-based non-destructive testing (NDT) methods are highly sensitive to the material’s mechanical properties, and therefore are widely used for damage monitoring. On the other hand, electromagnetic wave-based NDTs offer the advantage of fast, non-contact measurements. Micro- and millimeter wave frequencies offer a balance of high resolution and wave penetration, although they have not yet been sufficiently explored for detecting damage in cementitious composites. In this study, TRC specimens were subjected to up to 150 freeze–thaw cycles and monitored using a combination of active elastic and electromagnetic wave-based NDT mapping methods. For this purpose, transmission measurements were conducted at multiple points, with ultrasonic pulse velocity (UPV) employed as a benchmark and, for the first time, millimeter wave (MMW) spectrometry applied. This multi-modal mapping approach enabled the tracking of damage progression, and the identification of degraded zones. Full article

One of the most prominent actions of oxidative stress is the attack of free radicals on poylyunsaturated fatty acids (PUFAs), initiating a chain reaction to modify these PUFAs and generate oxidized modifications on all biomolecules. In the last quarter of the 20th century, intensive research was carried out to identify antibodies against such modifications. In the mid-1990s, the first enzyme-linked immunosorbent assay (ELISA) was introduced to the market, significantly accelerating research activities and knowledge gain. During this pioneering period, the main focus was on cardiovascular diseases, cancer, diabetes, and other diseases associated with oxidative stress. Subsequently, a standard range of these antibodies against oxidized LDL (oLAb) was determined in the population. Furthermore, the impact of exhaustive physical activity and diet on oLAb titers, and the correlation between newborns and mothers after delivery, as well as nutritional intake in newborns, were evaluated. Subsequently, the harmful effects of smoking and many other areas regarding oLAb titer were published, resulting in novel approaches for prognostic and therapeutic options, in particular through studies with antioxidants, which were able to influence oLAb significantly. This review presents an overview of the research activities obtained with this ELISA over the past three decades. Full article

The increasing number of domestic Internet of Things (IoT) devices in our lives leads to numerous benefits, but also comes with an increased risk of cybersecurity breaches. These breaches have psychological consequences for the users. We examined the nature of the psychological impact of cybersecurity breaches on domestic IoT by investigating emotional experiences in a scenario study (Study 1) and a field experiment (Study 2) using the five emotion components of the Component Process Model (CPM) and emotion regulation as a framework. We replicated a three-dimensional structure for emotional experiences found in a previous study, with an addition of an ancillary fourth dimension in the second study. The first dimension represents emotional intensity. The second bipolar dimension describes constructive vs. unconstructive action tendencies. On the third dimension, also bipolar, cognitive and motivational emotion features are opposed to affective emotion features. The fourth dimension, labeled distress symptoms, mainly reflects negative emotions. In Study 2, most of the introduced frequent irregularities on IoT devices were not noticed, and the intensity of emotional reactions and tendencies to react in a constructive way decreased throughout the phases of the experiment. These findings reveal that we are not emotionally equipped to identify potential threats in the cyber world. Full article

In the article, we analyse the problem of the efficiency market hypothesis using entropy in moments of transition from a normal economic situation to crises or slowdowns in European, Asian and US stock markets and the economy in the years 2007–2023 (2008–2009, U.S. financial sector crises; 2020–2021, Pandemic period; and the 2022–2023 period of Russia’s attack on Ukraine). The following hypothesis is put forward in the article: In periods of economic slowdown and economic crises, the entropy of prices and return rates decreases. According to the principles of physics, in an isolated system, entropy increases and decreases at the moment of external intervention, similar to finance, where during crises and economic slowdowns, there is interference from governments introducing new regulations and intervening in financial markets. The article uses the Shannon entropy method. This measure, as a statistical measure, does not require the assumption of stationarity of time series or a known probability distribution, unlike classical statistical methods. Our results confirm decreased entropy in stock markets during crisis. Full article

Physical adversarial attacks face significant challenges in achieving transferability across different object detection models, especially in real-world conditions. This is primarily due to variations in model architectures, training data, and detection strategies, which can make adversarial examples highly model-specific. This study introduces a multi-model adversarial training approach to improve the transferability of adversarial textures across diverse detection models, including one-stage, two-stage, and transformer-based architectures. Using the Truck Adversarial Camouflage Optimization (TACO) framework and a novel combination of YOLOv8n, YOLOv5m, and YOLOv3 models for optimization, our approach achieves an [email protected] detection score of 0.0972—over 50% lower than textures trained on single models alone. This result highlights the importance of multi-model training in enhancing attack effectiveness across object detectors, contributing to improved adversarial effectiveness. Full article

Background: This study examines child abuse in sports environments through Ecological Systems Theory, revealing the multifaceted nature of abuse and the impact of environmental factors at various levels. Methods: With a study design using the phenomenology approach, a qualitative research method, data were collected through semi-structured, in-depth interviews with 11 Turkish participants, including 5 athletes, 4 coaches, and 2 academics with coaching experience in Sports Sciences. Thematic analysis was used to evaluate the data, categorizing findings into four levels: microsystem, mesosystem, exosystem, and macrosystem. Results: Findings show that at the microsystem level, children are exposed to physical, emotional, and sexual abuse, as well as neglect, largely through interactions with coaches and teammates. Physical abuse includes non-contact forms, like dehydration and forced training, and contact abuse, such as violence from coaches and peers. Emotional abuse manifests through psychological pressures and verbal attacks, creating a toxic environment. At the mesosystem level, excessive parental trust in coaches reduces oversight, leaving children vulnerable. In the exosystem, inadequate supervision of coaches and a lack of response to abuse cases by sports clubs worsen the issue. At the macrosystem level, cultural norms and societal attitudes normalize abuse, especially affecting female athletes. Conclusions: The study highlights the need for comprehensive interventions, including family awareness, stricter coach oversight, and robust policies within sports organizations to protect children. By emphasizing the interaction of individual, familial, and societal factors, this research underscores the importance of collective efforts to ensure safer sports environments. Full article

Cluster headache is a severe, poorly understood disorder for which there are as yet virtually no rationally derived treatments. Here, Lee Kudrow’s 1983 theory, that cluster headache is an overly zealous response to hypoxia, is updated according to current understandings of hypoxia detection, signaling, and sensitization. It is shown that the distinctive clinical characteristics of cluster headache (circadian timing of attacks and circannual patterning of bouts, autonomic symptoms, and agitation), risk factors (cigarette smoking; male gender), triggers (alcohol; nitroglycerin), genetic findings (GWAS studies), anatomical substrate (paraventricular nucleus of the hypothalamus, solitary tract nucleus/NTS, and trigeminal nucleus caudalis), neurochemical features (elevated levels of galectin-3, nitric oxide, tyramine, and tryptamine), and responsiveness to treatments (verapamil, lithium, melatonin, prednisone, oxygen, and histamine desensitization) can all be understood in terms of hypoxic signaling. Novel treatment directions are hypothesized, including repurposing pharmacological antagonists of hypoxic signaling molecules (HIF-2; P2X3) for cluster headache, breath training, physical exercise, high-dose thiamine, carnosine, and the flavonoid kaempferol. The limits of current knowledge are described, and a program of basic and translational research is proposed. Full article

Rice (Oryza sativa L.) feeds half the world’s population and serves as one of the most vital staple food crops globally. The brown planthopper (BPH, Nilaparvata lugens Stål), a major piercing–sucking herbivore specific to rice, accounts for large yield losses annually in rice-growing areas. Developing rice varieties with host resistance has been acknowledged as the most effective and economical approach for BPH control. Accordingly, the foremost step is to identify BPH resistance genes and elucidate the resistance mechanism of rice. More than 70 BPH resistance genes/QTLs with wide distributions on nine chromosomes have been identified from rice and wild relatives. Among them, 17 BPH resistance genes were successfully cloned and principally encoded coiled-coil nucleotide-binding leucine-rich repeat (CC-NB-LRR) protein and lectin receptor kinase (LecRK), as well as proteins containing a B3 DNA-binding domain, leucine-rich repeat domain (LRD) and short consensus repeat (SCR) domain. Multiple mechanisms contribute to rice resistance against BPH attack, including transcription factors, physical barriers, phytohormones, defense metabolites and exocytosis pathways. Plant hormones, including jasmonic acid (JA), salicylic acid (SA), ethylene (ET), abscisic acid (ABA), gibberellins (GAs), cytokinins (CKs), brassinosteroids (BRs) and indoleacetic-3-acid (IAA), play crucial roles in coordinating rice defense responses to the BPH. Here, we summarize some recent advances in the genetic mapping, cloning and biochemical mechanisms of BPH resistance genes. We also review the latest studies on our understanding of the function and crosstalk of phytohormones in the rice immune network against BPHs. Further directions for rice BPH resistance studies and management are also proposed. Full article

Growth in forms of violence germinates from the abject soil of racism and colonialism. This article investigates religious racism in Brazil in the State of Rio de Janeiro through in-depth case studies and published data. First, I analyze how religious racism is utilized as a means to legitimize the demonization and consequent violence directed at Afro-Brazilian religions. Through an analysis of terreiro leaders’ discourses, I present a conception in which demonization and deliberate attacks imply the persecution of ways of being, existing, doing, and living of Black African origin. I use this lens to highlight the role that neo-Pentecostal churches and the theology of spiritual battle play in the resurgence of violence against Afro-religious people. Then, I problematize the harmful relationships between the demonization of terreiros and the extremely warlike conception of Christian faith. Ultimately, I argue that racist theological discourse of demonization manifests itself through verbal, physical, psychological, moral, and patrimonial aggression, putting the existence of terreiro peoples and communities at risk. Full article

Introduction: Evidence supports the relationships between socioeconomic status and access to health care, incidence of pathologies, and lifestyle. Objective: The aim of this research was to investigate whether there are associations between having a household income below the poverty line, and participation in unhealthy lifestyle habits, the prevalence of non-communicable diseases, and the number of comorbidities in US middle-aged and older adults. Methods: This cross-sectional study is based on the NHANES 2011–2020. A total of 10,788 US middle-aged and older adults (5653 males and 5135 females) participated in this research. Associations were studied through the Chi-squared test, and odds ratios were calculated using a binary logistic regression model. Results: There were associations between a household income below the poverty line and physical inactivity, unhealthy diet, and being or having been an alcoholic. Associations were found between this adverse economic situation and having hypertension, diabetes, liver disease, kidney problems, arthritis, congestive heart failure, angina pectoris, heart attack, stroke, and also with having two or more, three or more, four or more, and five or more comorbidities. Increased odds of being involved in these unhealthy habits and of suffering these diseases and multimorbidity were found for those with a family income below the poverty threshold. Conclusions: The existence of associations between having a family income under the poverty threshold and having unhealthy habits, suffering non-communicable diseases, and having multimorbidity is confirmed in US middle-aged and older adults. Increased odds for various non-communicable diseases, multimorbidity, and for being involved in these unhealthy habits were found for this low-income group. These findings should serve to draw the attention of policy makers to the increased health vulnerability of the adult population below the poverty line in the US. Full article