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Smart Cities rely on the Internet of Things (IoT) which is characterised by its diverse, distributed and complex infrastructure. These complexities present a range of cybersecurity challenges, making IoT security an area of great importance. The existing vulnerabilities in IoT leaves Smart Cities susceptible to various types of malicious attacks. These vulnerabilities can be exploited, ranging from opportunistic monetary gains to acts of terrorism that disrupt the systems of rival nations. The fact that conventional cybersecurity protection systems cannot be applied to IoT environments in Smart Cities is an additional challenge. The relationship between cybersecurity and IoT security of Smart Cities has become a crucial gap that must be thoroughly investigated. Hence, this paper extensively reviewing the existing literature concerning IoT applications in Smart Cities, with emphasis on cybersecurity and IoT security concerns. This study concludes that real-time threat detection and mitigation by leveraging fog computing and artificial intelligence models represent a significant advancement in securing IoT infrastructure against cyberattacks. The research outcomes contribute to the critical understanding of the challenges regarding IoT security and paves the way for advancing the research of cybersecurity within the Smart Cities ecosystem. [ABSTRACT FROM AUTHOR]

The article focuses on managing combustible dust hazards by emphasizing the importance of accurate and applicable test data. Topics include identifying, assessing, and specifying protections against combustible dust hazards using data that is accurate, reproducible, and representative of operational conditions. It describes four case studies illustrating how such data is crucial for evaluating risks and implementing safety measures effectively across various industrial settings.

The weaponization of artificial intelligence (AI) and machine learning (ML) models in cybersecurity is a growing concern, with cybercriminal organizations and nation-states exploiting their weaknesses. The Microsoft "Tay" chatbot incident exemplifies the risks of weaponized AI, as it displayed sexist and racist behaviors due to malicious data inputs. The researcher examined 21 academic studies on AI weaponization and AI-driven cyberattacks in this systematic review. This work, a systematic review, concludes with an in-depth understanding of the scale and scope of using AI as a cyber weapon. The findings revealed that more research is necessary on weaponizing AI for offensive cybersecurity applications and the following key observations (a) a connection between AI weaponization and countermeasures, (b) AI's role in enhancing cybersecurity defenses, (c) AI weaponization offering mitigation strategies for protecting digital assets and infrastructure, and (d) AI-driven attacks exploiting vulnerabilities, enabling automation and scalability, facilitating data poisoning and manipulation, improving social engineering, and augmenting evasion obfuscation. This study contributes to a better understanding of AI weaponization and aids researchers in synthesizing current literature on the topic. [ABSTRACT FROM AUTHOR]

Predicting cyclone intensity is an important aspect of weather forecasting since it influences disaster preparation and response. This framework addresses the pressing need for precise cyclone intensity prediction by presenting a unique predictive model based on a hybrid CNN and Bi-LSTM architecture optimized using a Genetic Algorithm (GA) enhanced Fruit Fly Optimizer (FFO). Existing methods have primarily relied on traditional machine learning models and meteorological data, demonstrating limitations in capturing the complex spatial-temporal patterns inherent in cyclone evolution. These drawbacks include insufficient feature extraction abilities, underutilization of convolutional neural networks (CNN), and poor model tuning. This unique method incorporates a hybrid CNN and Bi-LSTM architecture that is tuned by a Genetic Algorithm (GA) enhanced Fruit Fly Optimizer (FFO), resulting in higher cyclone intensity prediction accuracy. The experimental results are implemented in Python software, and they reveal that this method outperforms current models by an average of 21% when compared to existing methods such as VGG-16 achieved an accuracy of 78% and Ty 5-CNN (95.23%). The suggested CNN-Bi-LSTM model predicts cyclone strength with an excellent accuracy of 99.4%. This unique approach offers a possible avenue for increasing cyclone intensity prediction, hence improving disaster preparedness and risk mitigation efforts in sensitive locations. [ABSTRACT FROM AUTHOR]

Cyberbullying has emerged as a pervasive issue in today's digitally connected society, with detrimental effects on individuals' mental health and well-being. Despite increasing awareness and efforts to address cyberbullying, there remains a significant gap in utilizing wireless network security measures as a means of mitigation. The existing literature predominantly focuses on social and psychological aspects of cyberbullying, overlooking the potential role of wireless network security in prevention and intervention strategies. This research seeks to fill this gap by exploring the effectiveness of leveraging wireless network security to secure cyberspace against cyberbullying incidents. The research employs a multifaceted methodology, beginning with the estimation of expected rates and derivative risks of cyberbullying within wireless networks. These metrics are combined into a risk index value, which serves as a basis for prioritizing mitigation efforts. Additionally, the study explores the application of cyberspace modeling techniques, specifically Support Vector Machines (SVM), to enhance screening processes and identify potential cyberbullying incidents on Wireless Network Security (WNS). The findings of this research demonstrate the efficacy of integrating wireless network security measures into cyberbullying prevention strategies. By combining risk index values and leveraging SVM-based cyberspace modeling, the study identifies and prioritizes cyberbullying risks effectively. Furthermore, the implementation of wireless network security protocols contributes to a reduction in cyberbullying incidents, fostering safer digital environments for users. [ABSTRACT FROM AUTHOR]

Bridges are key parts of transportation networks and hence, their post-hazard condition is vital for the recovery of the regions affected by natural hazards. However, the fact that they are often subjected to more than one destructive natural hazard during their life span resulting in accumulated damage that may influence their capacity has attracted relatively little research interest, while almost no design standards take it into consideration. The multiple hazard events may be successive single events, separated by considerable time intervals (e.g. an earthquake followed by a flood event), combined or cascading multiple-hazard events (e.g, landslide after an earthquake), or even simultaneous events. The main objective of this study is to propose an effective framework for the development of multiple-hazard fragility curves of bridges considering the effect of subsequent events and taking into account different possible damage scenarios of the bridge critical components, i.e. piers, bearings and the abutment-backfill systems. In this framework, the effect of the damage level of the critical components and their interdependence on the fragility assessment for multiple events is examined and compared with the bridge fragility for single events. A pilot case study is also included in the present work, aiming to highlight the effect of the initial damage state on the final fragility estimate of a typical riverine bridge. [ABSTRACT FROM AUTHOR]

This research paper presents an analytical approach to earthquake time-series forecasting using the Seasonal Autoregressive Integrated Moving Average with Exogenous Variables (SARIMAX) models. The objective of this study is to investigate the effectiveness of the SARIMAX model in earthquake forecasting by considering relevant exogenous variables, such as historical seismic activity, geological characteristics, and geodetic measurements. We start introducing the SARIMAX models, explaining its mathematical formulation and the incorporation of exogenous variables. The research methodology involves collecting earthquake time-series data from seismological databases and preprocessing the data for analysis. Various SARIMAX models are constructed and evaluated using statistical measures, such as root mean square error and mean absolute error, to assess their forecasting accuracy. Additionally, the impact of different exogenous variables on the predictive performance of the models is analyzed. The results of this research contribute to the field of earthquake prediction by demonstrating the applicability and efficacy of the SARIMAX model in capturing the temporal patterns and dynamics of seismic events. The practical reason of the results provides valuable information for decision-makers and stakeholders involved in disaster preparedness and mitigation strategies. [ABSTRACT FROM AUTHOR]

A detailed spatial-temporal analysis of the seismic activity in and around the Lake Van region was performed using several seismotectonic parameters such as b-value, Z-value, relative intensity (RI), pattern informatics (PI), and Coulomb stress changes. Correlations between these parameters were analyzed to estimate and forecast potential seismic hazards in the Lake Van region. Particular attention was paid to the parts of the study region that exhibited smaller b-values, higher Z-values, and high-stress changes at the beginning of 2022 and to the locations of earthquake hotspots determined from the composite earthquake forecast map for 2022-2032, i.e., Muradiye, Çaldıran, Özalp, Erçek, Van city center and Gevaş covering the faults of Çaldıran, Yeniköşk, Erciş, Malazgirt and the fault zones of Saray and Van. To provide more accurate interpretations regarding potential earthquake occurrences in the near future, the seismotectonic parameters analyzed in the scope of this study were compared with the corresponding seismological, geological, geodetical, and geochemical variables reported in the literature. This comparison showed that, firstly, our results are consistent with those reported in previous studies, and, secondly, all these variables should be interpreted in combination to correctly assess strong earthquake hazards. Furthermore, this type of multiple-parameter analysis may be important for the description of seismic, tectonic, and structural characteristics of the nature of the crust. Our findings show that almost all seismotectonic parameters indicative of anomaly regions, i.e., lower b-values, higher Z-values, high-stress distribution, and hotspots, were recorded in the same parts of the study region. Thus, the anomaly regions detected at the beginning of 2019 and between 2022 and 2032 may be considered to be potential zones of future great earthquakes. To summarize, the correlations among these variables may provide accurate information for assessing and forecasting earthquake hazards in this region. [ABSTRACT FROM AUTHOR]

The study explored the conduct of a service learning (SL) activity by senior high school students (N=110) in disseminating information about Disaster Readiness and Risk Reduction (DRRR) to community participants (N=139). Senior high school students from a public sector senior high school in the Philippines conducted a community service learning activity. Before conducting the service learning activity, students determined the familiar disasters that the community participants commonly experienced and then developed the DRRR brochure. Students compiled their DRRR learning into a brochure and used it to discuss disaster mitigation with the community. Researchers used standardised tests and survey forms to determine the participants' pre and post-knowledge, skills and attitudes toward disasters. Quantitative results showed that both the student and community participants perceived that the service learning activity had allowed them to gain more knowledge on disaster mitigation with an overall Disaster Related Knowledge Questionnaire (DRKQ) of p<0.05. Likewise, Civic Action and Skills Questionnaire (CASQ) revealed that the activity helped the students to improve their communication and social skills and the community participants' leadership skills at p<0.05. The qualitative data showed that both the students and the community participants better understood the DRRR concepts and perceived that the service learning activity had benefited and taught them disaster mitigation. [ABSTRACT FROM AUTHOR]

Purpose: The high potential threat of disasters that will occur in Indonesia requires anticipation from various sectors including education. The concept of natural disasters will be easy to understand if applied in an integrated manner between natural disasters and science, environment, technology, and society. Therefore, it is very important for today's youth that it has a long-term impact and reaches a very wide population so that it is possible to minimize the risk in the event of a disaster. This study aims to 1) analyze the characteristics, 2) analyze the validity of the SETS-based disaster education model in disaster mitigation and resilience 3) analyze the effectiveness of the SETS-based disaster education model in natural disaster mitigation and resilience. Design/Methodology/Approach: Participants in this study were elementary school students. The method used is development research from Borg and Gall. According to professional judgement, this study followed five of the ten procedures outlined by Borg and Gall to develop a viable product. Finding: The results showed that 1) the SETS-based disaster education learning model has six stages; 2) the SETS-based disaster education model in disaster mitigation and resilience is valid and feasible to use; 3) The results of the effectiveness test show that the SETS-based disaster education model is effective in increasing students' fatigue and resilience skills. Conclusion: This research contributes to the body of knowledge by informing the public about the importance of SETS-based disaster education for individuals to improve their mitigation and resilience skills in the event of natural disasters. Furthermore, the research findings are enhanced by the literature on SETS-based disaster education, which is currently understudied. The limitation of this study is that it was only done up till professional validation was done. Therefore, it is necessary to carry out further research with more complete and extensive stages. [ABSTRACT FROM AUTHOR]

Examining topic-level variability in modeling Twitter data can potentially yield more comprehensive insights into public perception during critical periods, thereby enhancing natural disaster mitigation and surveillance efforts. In this study, we utilized generalized linear mixed models (GLMMs) to illustrate the variability in tweet counts related to specific topics in Indonesia during the flood events that occurred in February 2021. The glmmTMB library in R was employed for this purpose. The data were assumed to follow two distinct exponential distributions: Poisson and Negative Binomial. To incorporate random effects, random intercepts and random slopes were introduced, allowing them to vary randomly across topics in the initial two models. Additionally, the final model addressed issues related to dispersion and zero-inflation. By evaluating the Akaike Information Criteria scores, we determined that a model based on the Negative Binomial distribution with random zero-inflation intercepts best fit the data. The chosen model formulation and the estimated parameters have the potential to forecast topic-specific trends in Indonesian flood-related Twitter data. [ABSTRACT FROM AUTHOR]

Industrial safety helmets are crucial personal protective gear but detecting them as small targets in complex environments is challenging. This work proposes enhancements to the YOLOv8 object detection framework, specifically incorporating a spatial-to-depth (SPD) convolution module and a large selective kernel network (LSKNet). SPD-Conv combines spatial-to-depth layers and non-strided convolutions to retain fine-grained information when downscaling feature maps, while LSKNet introduces dynamic spatial selection and attention for refined context modeling. Our customized model is trained on a dataset of construction hardhat images captured via drones. Quantitative results showcase higher precision and recall over baseline YOLOv8, surpassing competing YOLOv5 versions. An optimized final model outcomes demonstrate accuracy exceeding 90% validation in mAP metric after 200 training rounds. By tackling limitations posed by small, obscured industrial safety gears, this enhanced real-time detection approach provides indispensable technological support for bolstering workplace hazard identification and prevention. [ABSTRACT FROM AUTHOR]

Objective: Regulatory legislation in both the United States and Canada requires water users with medium to high intake volumes to monitor entrainment losses to determine effects and to assess potential mitigation strategies to reduce harm to fish. Recent studies have recommended the use of both increased sampling frequency and sampling volume to characterize fish entrainment for large power plants on the Great Lakes. There is little doubt that increasing the flow rate and volume of water collected for sampling reduces the uncertainty in estimates of annual entrainment. Depending on the type of pump and the pumping flow rate used for entrainment sampling, considerable damage to fish larvae can occur. A screw‐type centrifugal pump has many qualities that make it ideal for entrainment sampling, but it has not yet been used as a sampling device for fish entrainment applications at power plants or other large industrial water users. The objective of this study was to determine mortality of entrainable fish eggs and larvae due to passage through a screw‐type centrifugal pump. Methods: In a laboratory setting, Lake Trout Salvelinus namaycush eggs and larvae, Lake Whitefish Coregonus clupeaformis eggs, and Rainbow Trout Oncorhynchus mykiss juveniles were passed through a screw‐type centrifugal pump at three treatment flow rates: 39.5, 47.3, and 59.1 m3/h. Fish and eggs were monitored for mortality posttreatment and again at 24 and 48 h. Result: Across treatments, very few mortalities were observed. Species specific moralities were four larval Lake Trout, one Lake Whitefish egg, and one juvenile Rainbow Trout. No mortality was observed for Lake Trout eggs. Conclusion: The present study identified high egg and larval survival (≥99%) after passage through a screw‐type centrifugal pump. High survival reduces error associated with identification and counting of entrained organisms, which provides more accurate estimates of annual entrainment losses. Impact statementA screw‐type centrifugal impeller pump results in high survival of entrainable fish (eggs and larvae), which reduces error associated with estimating fish mortality due to entrainment. Reduced error improves entrainment mortality estimates that may be used to develop compensation strategies to mitigate loss of fish from aquatic systems. [ABSTRACT FROM AUTHOR]

How to deal with damage to the power grid caused by natural disasters has become one of the main research focus of disaster prevention and mitigation. This paper collates two main approaches to distribution network damage prediction and assessment under typhoon disasters: based on physical model-driven and data model-driven. Research based on physical models is divided into three parts by considering real-time wind speed correction, meteorological forecast information, and non-meteorological information. The field of data-driven models includes single-algorithm models and multi-algorithm models. These methods are known for their high accuracy, but have a strong dependence on data. Finally, the paper explores the potential benefits of integrating physical and data model-driven approaches, as well as implementing additional defensive measures based on predictive results. [ABSTRACT FROM AUTHOR]

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Children's experiences while undergoing treatment for chronic diseases (e.g. cancer) may influence their subjective wellbeing. According to design for wellbeing, introducing playful elements to daily activities (e.g. toys) contributes to improvement of positive affect and mitigation of negative affect—thus, improving subjective wellbeing overall. The primary goal of this research is to identify situations in hospital routine that can be redesigned through playful strategies to improve subjective wellbeing. A team of designers and psychologists engaged in weekly games with young patients hospitalised in the paediatric cancer unit. Participatory observations focused on feelings that children shared about their personal experiences and those with friends about the hospital routines. Thematic analysis was conducted after 10 weeks of play. Several project opportunities emerged from results. We proposed a product designed to support patients during hospitalisation through a co-design process with hospital staff aimed at improving patient's subjective wellbeing. [ABSTRACT FROM AUTHOR]

Cross-site scripting (XSS) attacks have been extensively studied in the literature, although mitigating such attacks remain a challenge for cyber defenders. In this paper, we survey the existing literature on XSS attacks, focusing on the range of attacks and potential mitigation strategies. Specifically, we review the various XSS attacks from the lens of an attacker. We use a workflow diagram to define the topological relationship among XSS attacks, and to highlight key system weaknesses (e.g., chokepoints). We also present a Hybrid XSS attack (H Y XSS A) , designed to facilitate the identification of existing and future potential attack vectors in different modalities presented as frameworks (f i). For quantification and visualization of these frameworks, the software application as a rotate view tool is developed. Moreover, we demonstrate how these derived frameworks can be implemented, and provide a guideline to defend against XSS attacks. The implementation results for the given two attack vector shows the feasibility of mapping of attack vectors to actual mathematical vectors. Finally, we present potential challenges and opportunities associated with XSS attacks. [ABSTRACT FROM AUTHOR]

Cross-site scripting (XSS) attacks have been extensively studied in the literature, although mitigating such attacks remain a challenge for cyber defenders. In this paper, we survey the existing literature on XSS attacks, focusing on the range of attacks and potential mitigation strategies. Specifically, we review the various XSS attacks from the lens of an attacker. We use a workflow diagram to define the topological relationship among XSS attacks, and to highlight key system weaknesses (e.g., chokepoints). We also present a Hybrid XSS attack (H Y XSS A) , designed to facilitate the identification of existing and future potential attack vectors in different modalities presented as frameworks (f i). For quantification and visualization of these frameworks, the software application as a rotate view tool is developed. Moreover, we demonstrate how these derived frameworks can be implemented, and provide a guideline to defend against XSS attacks. The implementation results for the given two attack vector shows the feasibility of mapping of attack vectors to actual mathematical vectors. Finally, we present potential challenges and opportunities associated with XSS attacks. [ABSTRACT FROM AUTHOR]

FEMA provides hundreds of millions of dollars for hazard mitigation projects annually through their Hazard Mitigation Assistance (HMA) grant programs. HMA funding is most accessible to resource-rich communities leaving historically underserved communities that are often more vulnerable to disasters less able to obtain federal mitigation funding. This research highlights the results of a national survey conducted with 43 State Hazard Mitigation Officers (SHMOs), assigned state-level leaders who can have great influence on mitigation equity within their state. The survey explored the role of states and territories in facilitating mitigation equity in FEMA HMA programs using a three-pillar environmental justice framework (recognition, procedural justice, and distributional justice). The results indicate state-level shortcomings, including limited understanding of underserved communities, poor procedures for identifying and engaging with underserved communities, and limited local engagement in state- or territory-sponsored conferences, trainings, meetings, and policy discussions. The results yield insight into some of the underlying processes through which inequities in federal support for mitigation emerge and provide guidance to address shortcomings. These findings have important implications for federal- and state-level policy aiming to promote equity in hazard mitigation. Specifically, they point to the need for assessments of the needs, values, and priorities of low-capacity communities, identification and outreach strategies tailored to those communities, and increased financial and technical assistance for equity-focused actions. This study underscores the value of environmental justice research in decision-making associated with multi- billion- dollar federal grant programs. • SHMO's recognition of low-capacity communities is relatively limited. • Engagement processes are not tailored to the qualities of those communities. • Assistance for recognition-based activities is necessary for equitable outcomes. [ABSTRACT FROM AUTHOR]

Wildfires represent a major concern for the forests in the Mediterranean basin regions since global climate change enhances the frequency and the severity of this natural ecological disturbance agent. Wildfire models (fire spread or fire behavior models) can be of valuable help for fire risk assessment as well as for planning mitigation actions which mainly concern forest management. These models need generalized vegetation (fuel) data sets at the scales which are significant for fire/forest management. However, despite of the efforts to develop methods for generating global fuel data sets, there is a lack of fine resolution regional scale fuel data sets for the Mediterranean basin. The aim of this work is to build a fuel data set based on existing data sources for fire/forest management, risk assessment and decision-support purposes. Thus, this paper presents a database (building methods and data) of wildland fuels for Mediterranean basin vegetation stands types and in particular for those in Corsica, which gathers together most common input parameters needed by wildfire's models at several vegetation scales (i.e., stand, elements, particles). Moreover, an example is provided where simulations are run with a specific wildfire model by using the fuel input data extracted from the database. Fuel attributes have been defined to be meaningful at regional/landscape scales and are representative of stand-level characteristics. National (French) Forest Inventory (NFI) data have been mainly used for determining the fuel attributes for forest stand types. The harmonization of European NFIs generates a reliable data source available to extend and generalize the methodology presented herein to other regions or countries. • Vegetation/Fuel database for fire risk and forest management. • Stand-level attributes meaningful at landscape scale. • Data compiled in layers to account for the structure and arrangement of vegetation/fuels. [ABSTRACT FROM AUTHOR]

This research paper explores innovative contributions to the field of disaster management in smart urban environments, with a particular focus on integrating advanced computer-aided techniques, specifically GRU-CNN. Three key contributions are highlighted: (1) the development of dynamic risk assessment algorithms utilizing GRU-CNN for real-time analysis and predictive modeling, enabling proactive disaster mitigation; (2) the establishment of an integrated sensor network infrastructure for early warning systems, leveraging various sensors and GRU-CNN-based data analytics to detect and respond to potential disasters at their nascent stages; and (3) the implementation of human-centric resilience planning, utilizing GRU-CNN-based computer-aided tools to simulate disaster scenarios and engage communities in preparedness efforts. The dynamic risk assessment algorithms presented in this paper, powered by GRU-CNN, enable continuous monitoring and analysis of diverse data sources, fostering a proactive approach to disaster preparedness. The integrated sensor network architecture enhances early warning capabilities, allowing for timely responses to emerging threats through the application of GRU-CNN methodologies. Furthermore, the human-centric resilience planning approach introduces virtual simulations using GRU-CNN to model disaster scenarios, facilitating the testing and refinement of strategies in a risk-free environment. This approach not only ensures the adaptability of plans but also engages and educates communities, fostering a culture of preparedness, with GRU-CNN playing a pivotal role in the process. Through these contributions, this research paper seeks to advance the discourse on disaster management in smart urban environments, emphasizing the integration and effectiveness of GRU-CNN in enhancing resilience and response strategies. By leveraging cutting-edge GRU-CNN technologies and prioritizing community involvement, the proposed techniques aim to provide a more robust and adaptive response to the challenges posed by natural and man-made disasters in urban settings. • Paper introduces hybrid GRU-CNN model for disaster prediction. • Highlights resilience, reducing false alarms for accurate predictions. • Emphasizes community involvement, fostering a culture of preparedness. [ABSTRACT FROM AUTHOR]

Ice jams pose a major flood hazard in communities along northern rivers, resulting in high backwater levels and overbank flooding during ice-cover breakup. Mitigation measures, including large-scale projects by government agencies and individual actions by asset owners, can help reduce flood risk and protect human life and assets. This study examines ice-jam flood risk and explores the effectiveness of adaptive strategies in mitigating such risks in Fort McMurry, Canada. It evaluates the effectiveness of top-down (government-led artificial breakup) and bottom-up (resident-led flood-proofing) strategies, comparing the Rational Choice Theory (RCT) and the Protection Motivation Theory (PMT) models. The objective is to explore the potential enhancements to the ice-jam flood risk model through the integration of the PMT as a decision-making framework under uncertainty. This study seeks to assess whether and to what extent such integration can improve the modeling of ice-jam flood risk. The findings highlight the benefits of incorporating socio-economic factors in the PMT model. Economic factors, such as income tax and the cost of flood-proofing, shape overall flood risk, especially when artificial breakup measures are not implemented. The study emphasizes the importance of considering heterogeneity in decision-making processes and diverse characteristics of individuals when designing flood risk management strategies. Response efficacy and self-efficacy coefficients are significant factors influencing flood risk and the adoption of flood-proofing measures. Enhancing individuals' belief in their actions' effectiveness and their confidence in self-protection contributes to more effective flood risk management. These findings inform the development of more effective flood risk management strategies. • Incorporating socio-economic factors in the ice-jam flood risk model improves understanding of residents' decision-making. • Economic factors, such as income tax and flood-proofing costs, significantly shape overall flood risk. • Heterogeneity in decision-making processes should be considered when designing flood risk management strategies. • Response efficacy and self-efficacy play a vital role in ice-jam flood risk and the adoption of flood-proofing measures. • Comparing the Rational Choice and Protection Motivation Theory provides valuable insights into ice-jam flood risk model. [ABSTRACT FROM AUTHOR]

Connected and autonomous vehicles (CAVs) have gained significant importance in intelligent transportation systems. However, CAVs are associated with significant cyber-risks caused by different threat-agents, which require robust mitigation strategies for secure operation. Different categories of threat-agents come with varying resources, motivation, and skills that must be addressed effectively for the secure operation of CAVs. This study offers a comprehensive analysis of cybersecurity risks from different categories of threat-agents targeting CAVs. A novel hybrid multi-criteria decision making (MCDM) technique has been developed to prioritize the threat-agent categories as part of the cyber defense mechanism. In this study, the major threat-agent categories are identified from the existing literature and cybersecurity reports. Then expert opinion is collected on the likelihood and severity of cyber-attacks undertaken by different threat-agent categories. Single-valued neutrosophic fuzzy sets (SVNFS) are implemented to consolidate the subjectivity of the linguistic opinions given by the experts. Then Best-Worst Method (BWM) is used to determine the relative criteria weightage on the cyber-attack consequences. These weights are then supplied to the ViseKriterijum-ska Optimizacija I Kompromisno Resenj (VIKOR) method for ranking the categories of threat-agents based on the risk perceived by the experts. A case study is presented with five categories of threat-agents and five loss criteria targeting CAVs to validate the viability of the proposed model. The result shows that insider attackers pose maximum risk for cybersecurity of CAVs. The proposed technique will provide helpful insights to the decision-makers for formulating effective defense strategies against cyber-attackers. • This study identifies and ranks major categories of threat agents targeting CAVs. • Model cybersecurity of CAVs as an MCDM problem with identified threat agents (alternatives) and loss criteria. • Develop a hybrid MCDM technique integrating BWM, VIKOR along with SVNFs to prioritize the threat-agent targeting CAVs. • Sensitivity analysis is done by varying the weights of maximum group utility and exchanging criteria weights among each other. • Comparative analysis is done with other MCDM methods involving SVNFS and Pythagorean fuzzy for the robustness of the method. [ABSTRACT FROM AUTHOR]

The centralized and decentralized planning approaches as affirmed through ‘Post Flood Disaster Management Institutions’ (PFDMI), at provincial management level in Punjab deliberate peculiar impacts within. A macro- level analysis of land use planning of the region will establish the optimum course of strategic disaster risk reduction approaches. For a prolific research analysis of effectivity of integrated and devolved systems of hierarchy involved in flood mitigation mechanism within Punjab,certain qualitative and quantitative methods are utilized in this research to evaluate the effectiveness of management in disaster risk reduction. Another important factor in determining a suitable approach for hierarchy depends upon type of organizations which are responsible for funding the disaster hit regions. The structure of ‘Matching Grant’ at local level in Punjab has therefore been discussed in this research paper to evaluate its effectivity and relational reference for future policies. Similarly the cohesion of prospective management in reference to disaster prone areas in Punjab, may vary with regard to various locations or regions. The macro outlook of fundamental data analysis with respect to centralized and decentralized approaches applied in flood prone areas of Punjab in Pakistan will formulate an overall viewpoint for adopting relevant strategy to deal with disaster risk reduction. [ABSTRACT FROM AUTHOR]

New psychoactive substances (NPSs) are drugs that exhibit chemical structures and pharmacological actions similar to illegal drugs. Because the health hazards caused by these drugs of abuse have become a social problem, the quick identification of NPSs is necessary for rapid regulation. We developed an automated machine learning system to predict the retention time of the gas chromatography-mass spectrometry for NPSs. The use of an automated machine learning system and Mordred that calculates molecular descriptors enables accurate retention time prediction. Because the retention time prediction is crucial for identifying NPSs, our research can contribute to the prevention of health hazards. [ABSTRACT FROM AUTHOR]

In flood hazard estimation via the analytic hierarchy process (AHP), using the pixel as the basic unit might lead to accuracy relying on the optimal weighting criteria. To this end, considering the sub-watershed as the basic unit is new. In this study, taking the Chaohu Basin in Anhui Province, China, as a study case, the accuracy of the sensitivity of the pixel-based and sub-watershed-based AHP models influenced by weighting criteria was compared. There were 48 judgment matrixes defined, following the same order of importance of the involved indicators. Validation ground truthing is constructed by the extracted flooded regions from GF-3 images. As weighting criteria changed, the results indicated that the pixel-based AHP fluctuated significantly, while the correct ratio and fit ratio derived by the sub-watershed-based AHP could improve by >35% and >5%, respectively, over the pixel-based-AHP. It indicated that the sub-watershed-based AHP has an advantage in relying less on in situ weighting criteria than the pixel-based AHP. [ABSTRACT FROM AUTHOR]

Small island tourism destinations are particularly vulnerable to (natural) hazards, disasters and crises. Although much literature considers disaster risk reduction (DRR) strategies, risk mitigation and the impacts of disasters on the tourism industry, the literature on how these strategies are implemented and managed by stakeholders with vested interests is scarce. Understanding stakeholders' awareness of threats, and their ability and knowledge to respond to sudden and/or projected natural disasters is a key dimension in helping create and implement management plans, recognised in the UNISDR goals, Hyogo and Sendai Frameworks. With tourists increasingly travelling to destinations in locations of varying risk, this paper explores the intersections of stakeholder's (natural) hazard awareness and resulting vulnerability of small island tourism destinations utilising Malta as a case study setting, focusing on decision- and policy-making dimensions. Qualitative methods were utilised to consider hazard awareness in Malta and future management of vulnerability. Results indicate a recognition of an increasing need for integrated stakeholder collaboration, with flooding, drought and storms being the three most likely hazards to affect Malta. Key outcomes are a need for (natural) hazard awareness training and development of management plans to be implemented to benefit the general population and tourism sector. [ABSTRACT FROM AUTHOR]

Life Cycle Assessment (LCA), a computational tool for enabling sustainable product design decision making, faces challenges in the interpretation phase, where conclusions are drawn for improvement recommendations. This necessitate the need to incorporate into LCA management-relevant theoretical underpinnings to strengthen decision-making processes. Comparative LCA case studies of lead-based piezoelectric material (lead zirconate titanate – PZT) and lead-free alternatives (potassium sodium niobate – KNN, sodium bismuth titanate – NBT), was employed to demonstrate how two theoretical lenses, namely Normal Accident Theory (NAT) and the Satisficing Framework, are used inductively to enhance decision making regarding unintended consequences in the value chain. By operationalising NAT, which has hitherto focused on the consequences of physical accidents, as a life cycle engineering-based methodology, NAT attributes of interactive complexity and tight coupling was revealed in piezoelectric materials, based on environmental systems' predictability, observability , and applicability. This led to the introduction of Environmental Impact Accident (EIA) as a new concept, facilitating an early assessment of the associated complexities influencing the sustainability credentials of piezoelectric materials whilst informing mitigation strategies. However, when considering multiple objectives that conflict or trade-off between alternative piezoelectric materials with different environmental and health impacts across the value chain, a conundrum is created but resolved using the Satisficing Framework. The paper concludes by proposing theoretical and practical policy options for incorporating LCA into product life cycle decision making. Of the conceptual framework detailing the methodological processes of integrating theoretical lenses of Normal Accident Theory and Satisficing Framework into LCA for sustainability decision-making. [Display omitted] [ABSTRACT FROM AUTHOR]

The harmless and high-value conversion of organic waste are the core problems to be solved by composting technology. This study introduced an innovative method of promoting targeted humification and nitrogen retention in composting by adding p -benzoquinone (PBQ), the composting without any additives was set as control group (CK). The results indicated that the addition of exogenous quinones led to a 30.1% increase in humic acid (HA) content during the heating and thermophilic phases of composting. Spectroscopic analyses confirmed that exogenous quinones form the core skeleton structure of amino-quinones in HA through composting biochemical reactions. This accelerated the transformation of quinones into recalcitrant HA in the early stages of composting, and reduced CO 2 and NH 3 by 8% and 78%, respectively. Redundancy analysis (RDA) revealed that the decrease in carbon and nitrogen losses primarily correlated with quinones enhancing HA formation and greater nitrogen incorporation into HA (P < 0.05). Furthermore, the compost treated with quinones demonstrated a decrease in phytotoxicity and earthworm mortality, alongside a significant increase in the relative abundance of actinobacteria, which are associated with the humification process. This research establishes and proposes that co-composting with quinones-containing waste is an effective approach for the sustainable recycling of hazardous solid waste. [Display omitted] • Exogenous quinones accelerated the humification process of composting. • Exogenous quinones were transformed into amino-quinones in humic acid. • Exogenous quinones promoted carbon and nitrogen sequestration into humic acid. • Co-composting products had lower biological toxicity. [ABSTRACT FROM AUTHOR]

Coastal hazards are pervasive across the Great Lakes coastline due to highly variable water levels, community utilization of the landscape, and landscape composition. These coastlines are dotted with communities that depend on the lake for socioeconomic stability. Recently, many communities have been tasked with the development of new coastal management policies to combat the record water levels and its impacts to socioenvironmental conditions. Many of those tasked with the development of such policies don't, necessarily, have backgrounds in coastal processes. This lack of background knowledge may impact coastal management strategies. Through a workshop activity, in 6 communities, local decision makers were asked to interpret imagery depicting varying coastal hazards. Additionally, participants were asked to rank the hazard based on the impacts seen in the community. Using text mining and statistical analysis, patterns in their interpretation were chronicled. Overall, we found vastly different terminology, understanding, and hazard recognition across the communities. [Display omitted] • It is essential to foster a broad collaborative relationship between decision makers and the scientific community. • Across all communities there was great awareness of erosion effects and mitigation strategies. • Beyond erosion there was lesser understanding of coastal hazards and the mitigation strategies associated. [ABSTRACT FROM AUTHOR]

• Novel BN-SPM framework proposed for robust risk assessment in infrastructure systems. • BN-SPM reveals vulnerabilities in complex infrastructures facing hazard scenarios. • Risk indices computed for multi-hazard scenarios, including mitigation strategies. • Saint Lucia's study shows the value of risk, vulnerability, and impact assessment. • The flexible framework aids resilience in urban planning and disaster management. This study proposes an integrated framework based on Bayesian Network (BN) and Strongest Path Method (SPM) to provide a robust assessment of the natural hazard risks to interconnected infrastructure systems. Leveraging Bayesian inference, the BN transforms prior failure probabilities into posterior ones, while SPM prioritizes network entities based on global impact, global vulnerability, and risk indices, calculated from key parameters including the likelihood of failure, degree of impact, and degree of dependence. The proposed integrated BN-SPM model calculates risk indices for complex interconnected networks with conditional dependencies on external nodes, such as multi-hazard, or mitigation and redundancy strategies, without predetermined parameters. Using this framework we evaluate diverse scenarios in Saint Lucia, encompassing non-hazard condition, flooding hazards, and presumptive strategies like mitigation and redundancy. The high likelihood of failure and complex interdependencies heighten risks even under non-hazard condition. Particularly, the Hewanorra International Airport (HIA) emerges as the most vulnerable entity. The established risk assessment framework offers the potential for application in evaluating risks within complex interconnected systems such as power grids, transportation networks, and communication systems facing various multi-hazard scenarios. This framework also assesses the implementation of mitigation and redundancy strategies, reducing the risk index within the affected network domain. [ABSTRACT FROM AUTHOR]

The article discusses Uganda's Occupational Safety and Health (Amendment) Bill, 2023, aimed at enhancing workplace health and safety by adapting regulations to modern work environments. Topics include the establishment of safety committees, measures to mitigate workplace hazards like noise and dust, and the adaptation to evolving sectors such as telecommunications and extractive industries.

The movement towards an animal-free testing approach for risk assessment represents a key paradigm shift in toxicology. Risk assessment of engineered and anthropogenic nanoscale materials (NM) is dependent on reliable hazard characterization, which requires validated test methods and models, and increasingly on mechanistic insights into the mode of action. The properties that make NMs so advantageous for a wide range of commercial and industrial applications also pose a challenge when it comes to safety testing under in vitro and in chemico experimental settings. Their large reactive surface area makes NMs prone to interactions with assay reagents, readout signals, or intermediate steps of many test assays, leading to the potential for biased results and data inconsistencies, collectively referred to as interferences. Therefore, methods and protocols developed and validated for conventional chemicals often require adaptation and checking for reliability in NMs' toxicity assessment. This review presents the collected scientific knowledge on NMs-induced interferences for the most common in vitro toxicity assays and methods related to cytotoxicity, oxidative stress and inflammatory response evaluation. Our analysis of existing scientific literature showed that the challenge of NMs-induced interference was not explicitly addressed in more than 90% of the papers published up to 2014 reporting the safety and toxicity of NMs. In later years, increasing number of studies tackled the interference challenge in toxicity testing of NMs, which initiated exhaustive work on standardization and validation of existing regulatory-relevant in vitro test protocols and guidelines. Due to the specificity of the different NMs and the range of ways they can potentially interfere with in vitro assays, interference and fit-for purpose controls should be included for each NM type and method applied, unless label-free assays are selected. Here, we provide a decision tree to guide researchers on how to design experiments to avoid interferences during in vitro testing by taking appropriate mitigation actions and how to include proper interference controls in their experimental design where complete avoidance is not possible. The application of this decision tree will improve the reliability, comparability and reusability of in vitro toxicity data on engineered NMs or ENMs, increasing the relevance of in silico hazard data for use in risk assessment and in science-based risk governance of NMs. The approach is applicable more broadly also, to advanced materials and to hazard assessment of anthropogenic nanoscale materials such as microplastic and tyre-wear particles. [Display omitted] • NM surfaces result in physical (scattering) & binding interferences with in vitro toxicity assays. • Analysis of literature from 2014 to 2022 shows some improvement in reporting of NMs interferences. • An approach to assess interference and design fit-for purpose controls for NM type / method is presented. • A decision tree to avoid interferences and select mitigation actions / interference controls is included. • Application of the decision tree will improve reliability and reusability of in vitro NM toxicity data.. [ABSTRACT FROM AUTHOR]

The article provides guidance for handling toxic inhalation hazard (TIH) chemicals, as well as a quantitative method for evaluating the risks associated with transporting TIH chemicals and selecting appropriate mitigate measures. Topics include the first best practice for handling toxic chemicals, main steps of a comprehensive quantitative risk assessment (QRA), and audit protocol for toxic inhalation hazard chemicals.

• Expert technical and economic rationalities overlook political aspects of sustainability. • Local experiences reveal structures and processes that shape inequitable outcomes. • Sustainable developmentality creates a triple-bind for rural mountain residents. • The triple-bind contributes to large numbers migrating from mountain dwellings. • Mountain migration and land abandonment is a political not an inevitable process. Sustainability challenges persist in the central Indian Himalayas (CIH) despite an array of solutions proffered by external experts. This paper interrogates the 'sustainability gaze' of external experts – which reflects attempts to reconcile neoliberal economic growth with environmental conservation within the logics of technical and biophysical rationalities - by exploring local experiences of rapid and uncertain social and environmental change. Three strands of policy and practice shape the gaze: (i) natural hazard mitigation for climate change adaptation; (ii) reducing social vulnerability through pro-poor development; and (iii) increasing resilience through environmental management and conservation. Results challenge narratives that overpopulation causes environmental degradation and changing patterns of migration are a natural process of modernisation in the CIH. Alternative local narratives highlight haphazard and inequitable economic growth, lack of mountain planning and disaster management, inadequate social welfare programmes, and monkey relocation policies as the major sustainability challenges. The paper discusses how the gaze produces 'sustainable developmentality' - a depoliticising process that cultivates multiple and conflicting mountain subjectivities, namely: (i) active community members responsible for mitigating natural hazards, (ii) productive farmers and flexible waged labourers, and (iii) custodians of the environment. This creates a triple-bind for smallholders which has forced huge numbers to migrate from their mountain dwellings with unsustainable outcomes. Exploring local perspectives re-politicises the debate, exposing the contradictions and tensions of the gaze and the broader systemic issues of power and inequity the gaze overlooks. Such insights are crucial for rendering development policies more relevant to mountain residents of the CIH and beyond. [ABSTRACT FROM AUTHOR]

One of the severe global threats facing the world today is flooding. Similarly, Malaysia is faced with monsoon and flash floods which are the most severe "climate-related natural disasters" for the country. The Malaysian government is the main stakeholder and provider of aid in every stage of disaster. Consequently, the involvement of flood risk communities is said to be minimal and overlooked. Researchers have also stated that there is still a lack of research on human involvement and response. Thus, addressing these gaps, we take on a social constructionist view to situate flood disaster as a social practice and discourse to investigate how government officials 'talk' about their involvement in flood disaster mitigation and management. Our analysis is based on the perspective that their 'talk' evokes specific disaster discourses which relate to the different ways of understanding flood disaster, and that these discourses in turn shape and impact their response and action for flood mitigation and management as well as community empowerment. To this end, we adopt Van Leeuwen's representation of social actors and social action framework to identify the disaster discourses drawn upon by the officials. The findings show that government officials employ various discourses that draw on the 'traditional framework of relief and rehabilitation' and a 'top-down government centric approach' that focus less on community empowerment. We see a need for the inclusion of a 'discourse of shared responsibility' that is part of a 'proactive approach', and sees all parties as partners, and in particular, flood risk communities. [ABSTRACT FROM AUTHOR]

• A quantitative approach to examine policy preference conflicts among diverse stakeholders across multiple plans. • Hazard mitigation plan incorporated the most overall stakeholder policy preferences among the four examined plans. • The regional transportation plan incorporated the fewest overall stakeholder policy preferences. • The hazard mitigation plan and the regional conservation plan had the highest level of policy consistency. • The hazard mitigation plan and regional transportation plan had the lowest level of policy consistency. The objective of this paper was to create and test a methodological framework for examining the extent to which various plans captured diverse stakeholder policy preferences related to resilience planning and management of interdependent urban systems. Policy preferences represent what were important for stakeholders and determine the priorities of stakeholders in resilience planning of urban systems. Stakeholders in different urban sectors may have conflicts of policy preferences in the resilience planning process. A comprehensive understanding of the extent to which plans incorporated and reflected policy preferences of different stakeholders would greatly improve the quality of resilience planning. Hence, we proposed a plan evaluation framework to examine the extent to which various plans captured diverse stakeholder policy preferences in resilience planning of interdependent infrastructure systems. We showed the application of the proposed framework in the evaluation of four plans affecting flood resilience planning in the Houston area. The proposed tool could help identify conflicted stakeholder policy preferences in planning and enable evaluation of policy consistency in networks of plans. [ABSTRACT FROM AUTHOR]

In the last decades, the number of natural disasters has considerably increased which has an extreme effect on the built environment. In this case, most buildings undergo severe damages and plenty of them totally breakdown which is one of the strongest impacts of a disaster. Egypt is considered as one of the countries that is exposed to unexpected natural hazards as a result of climate change, floods, earthquakes, etc. Thus, the main objective is to find solutions through temporary dwellings for displaced people to help them find an alternative residence. The paper is divided into three parts. First, it explores the fundamentals of design and construction of temporary dwellings based on diverse experiences from different contexts. Second, it analyzes the Nubian resettlement as a case study. Finally, the third part proposes a sustainable model for temporary dwelling solutions that act as a road map for flexible implementation. [ABSTRACT FROM AUTHOR]

Recently in the cybersecurity landscape, various figures have spread with different peculiarities. For instance there are the Black Hat hackers, aimed to perpetrate damage on the system or to silently exfiltrate sensitive information but there also the Ethical or White Hat hackers, aimed to investigate the vulnerabilities of a system under analysis only with the owner consent. In this context the Red Hat hackers, defined as vigilantes of the hacker world, are emerging. Their main aim is to independently found and solve vulnerabilities, by preventing cyberattacks. In this paper we propose a method aimed to automatise the vulnerability discover and mitigation process typically performed by Red Hat hackers. We exploit a tool-chain of several well-known tools and we evaluate the proposed method by exploiting the Metaesploitable Linux distro, showing that the proposed method is able to automatically mitigate vulnerabilities afflicting six widespread services.. [ABSTRACT FROM AUTHOR]

Environmental education for university level, especially in Engineering faculty, is an important issue. One of environmental issue that becomes a concern is related to flood disaster mitigation. The purpose of this study is to describe environmental attitudes (EA) and Pro-Environmental Behavior (PEB) among Engineering faculty students. The description will be used to develop a Disaster Mitigation of Flood based onOnline Learning (DIFMOL) model. The research method used is a descriptive survey technique. Instrumentsare distributed online using Google form with a sample size of 139 students taken using simple random sampling. The results show that the students' EA scores are in a very high category (89.68) and the students' PEB are in a moderate category (60.53). It indicates that the Engineering faculty students still require an educational model development to cope with flooding. One that can be developed is a DIFMOL model. In general, aspects need to be emphasized in the DIFMOL model are those related to flood disaster mitigation efforts in urban areas. The study concludes that EA is very high and PEB is still in the medium category. The DIFMOL model innovation requires further development in the next research. [ABSTRACT FROM AUTHOR]

Sea-level rise (SLR) is a hazard multiplier already impacting coastal communities and ecosystems across all sectors including transportation, utilities, health, community planning, emergency management, and natural resource management. Fortunately, our ability to understand future conditions and how they may exacerbate hazards has been rapidly increasing. Unfortunately, this rapid advancement in the science has led to gaps among the generation, access, and application of information for coastal decision making. Coastal professionals including engineers, environmental consultants, floodplain managers, and natural resource stewards are often challenged when it comes to integrating SLR into planning and project design. The professional community lacks transparent, repeatable, science-based approaches that utilize existing tools for determining how much SLR to consider while also specifically integrating the community’s values. Further, related data and data products such as where to find locally relevant projections of future conditions and impacts remain woefully underutilized. This paper reviews how to access locally relevant SLR projections, a risk-based framework for how to narrow down the available projections to a planning range, and how that information can be translated into relevant information about future conditions. Examples from projects in Jackson County, MS, and Dauphin Island, AL, are used to demonstrate how relative SLR can be integrated into projects across timelines while considering adaptability and scale. Finally, key limitations, such as aging information and complexities of risk tolerance, are described. [ABSTRACT FROM AUTHOR]

Disaster preparedness is an absolute prerequisite for the development of disaster risk reduction. This means that there is no awareness of danger disaster, then the high possibility of both physical and material losses is an inevitable matter. It is a must for humans to be sensitive and care for various possible disasters that can occur in the vicinity stay. Education on disaster mitigation needs to be introduced to the community. This is important to create residents who are responsive and ready for disaster. This paper aims to develop learning media supported by the use of smartphones to increase literacy about volcanic eruption disaster mitigation. This study using research and development with the 4D model. The results of this development are mobile encyclopedia packaged in a smartphone application as a media for volcanic eruption disaster mitigation education. Media and material validation show that the product being developed is very good and worth testing. Besides, the results of media validation by indicator: attracting attention, interactivity, presentation of learning material, feedback, quality of learning, training showed benefits and students were enthusiastic in learning using this media. This product can be an alternative media for the 21stcentury that applies mobile in the learning process. [ABSTRACT FROM AUTHOR]

The Federal Emergency Management Agency (FEMA) analyzed mitigation projects in the water sector and found, on average, every US$1 spent on federal mitigation grants prevents $6 in damage, highlighting how mitigation investments can ensure long-term savings (http://bit.ly/fema-factsheet). Risks, Utility Management, Infrastructure, Emergency Response, Emergency Planning Keywords: Risks; Utility Management; Infrastructure; Emergency Response; Emergency Planning EN Risks Utility Management Infrastructure Emergency Response Emergency Planning 84 87 4 06/05/21 20210601 NES 210601 GLO:KNS/01jun21:awwa1731-gra-0001.jpg PHOTO (COLOR): . gl I The City of Elkader, Iowa, received Federal Emergency Management Agency funding to protect their aeration lagoons and main lift station. [Extracted from the article]

To achieve community resilience and mitigate the consequences of natural hazards, community officials must balance competing priorities for local resources and funding. Besides the challenge of dealing with multiple competing priorities, community officials face another challenge: low risk awareness of natural hazards by the public and other stakeholders. Considering that virtual reality (VR) has been used to enhance learning and to change attitudes and behaviors, animating natural hazards in VR has the potential to enhance stakeholders' (e.g., the public, local/state/federal governments, insurance agencies, and property owners) risk awareness. Informed stakeholders make better decisions related to protective action. Therefore, we propose using VR to create a sense of presence and immersion that can provide stakeholders with hazard exposure, demonstrate a hazard's personalized consequences, and simulate the consequences of protective action, which, in turn, can influence attitudes and behavioral intentions of the general public to take protective action. Researchers could also apply VR to other hazardous or life-threatening situations and use interdisciplinary research to identify best methods to develop realistic and credible VR that all citizens can access to help mitigate hazards and enhance community resilience. [ABSTRACT FROM AUTHOR]

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