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Equitable and effective vaccine uptake is a key issue in addressing COVID-19. To achieve this, we must comprehensively characterize the context-specific socio-behavioral and structural determinants of vaccine uptake. However, to quickly focus public health interventions, state agencies and planners often rely on already existing indexes of “vulnerability.” Many such “vulnerability indexes” exist and become benchmarks for targeting interventions in wide ranging scenarios, but they vary considerably in the factors and themes that they cover. Some are even uncritical of the use of the word “vulnerable,” which should take on different meanings in different contexts. The objective of this study is to compare four vulnerability indexes produced by private, federal, and state institutions to assess the application of these measures to the needs of the COVID-19 pandemic and other emergent crises. We focus on federal, state, and private industries’ vulnerability indexes for the Commonwealth of Virginia. Qualitative comparison is done by considering each index’s methodologies to see how and why they defined and measured “vulnerability.” We also quantitatively compare them using percent agreement and illustrate the overlaps in localities identified as among the most vulnerable on a choropleth map. Finally, we provide a short case study that explores vaccine uptake in the six localities that were identified by at least three indexes as most vulnerable, and six localities with very low vaccine coverage that were identified by two or fewer indexes as highly vulnerable. By comparing the methodologies and index (dis)agreements, we discuss the appropriateness of using pre-existing vulnerability indexes as a public health decision-making tool for emergent crises, using COVID-19 vaccine uptake as a case study. The inconsistencies reflected by these indexes show both the need for context-specific and time-sensitive data collection in public health and policy response, and a critical critique of measured “vulnerability.”

By integrating the vulnerability index of buildings, earthquake disaster matrix, and historical earthquake disaster data, the vulnerability of typical buildings and compounds in rural areas of China are analyzed. The disaster matrix of buildings in historical earthquakes was obtained by analyzing historical earthquake disaster data. By integrating the historical disaster matrix and vulnerability analysis of typical structures in rural areas, a seismic disaster matrix was established to assess the seismic performance of regional compounds. Combined with the historical earthquake disaster matrix and vulnerability index, the lognormal distribution function was used to analyze the vulnerability index of regional structures and compounds to obtain the disaster matrix of structures under different seismic intensities. Considering the structures and compounds in the rural areas in the Tianjin district as an example, the seismic vulnerability of typical structures was investigated. The regional structure disaster matrix of the study region was established and the vulnerability indices of different types of structures and compounds were obtained to clarify the regional disaster prevention ability. [ABSTRACT FROM AUTHOR]

Floods are a frequent natural calamity in Bangladesh, where many areas get affected almost every year. An indicator-based vulnerability assessment can help efficiently manage the disaster. Therefore, this study intends to assess the community vulnerability in the Jamuna floodplain, one of the most flood-affected areas, using an indexing method. The index involves many indicators of flood exposure, sensitivity, and adaptive capacity along with their weights, determined based on an extensive literature review. A pretested questionnaire was employed to collect primary data from the study area through 400 household-level interviews. Using multistage sampling techniques, five upazilas from Jamalpur district, i.e., Dewanganj, Islampur, Madarganj, Melandaha, and Sharishabari, were purposefully chosen based on past flood damage reports. The percentage values were derived using SPSS for every variable from the field-level data. The variable vulnerability index (VVI) was computed by dividing the indicator's weight by its percentage value. Then, exposure, sensitivity, and adaptive capacity indices were calculated using the VVI values. Finally, the composite vulnerability index (CVI) of the five Upazilas has been computed using an established and recognized index formula. The CVI scores for Dewanganj, Islampur, Madarganj, Melandaha, and Sharishabari are 0.86, 0.84, 0.71, 0.70, and 0.65, respectively, which suggest a high overall vulnerability. The scores of the exposure and adaptive capacity indices reveal that Dewanganj and Islampur Upazilas have higher vulnerability than the other three upazilas, especially due to poor socioeconomic conditions, low adaptive capacity, and high exposure. This study recommends some infrastructural development, such as sustainable flood-resistant dams, as the study sites are in a flood-prone zone. Houses should be built using flood-resistant materials like bricks and concrete, which are more resilient than mud. Improvements in education and multiple income sources will help the affected people increase their coping capacity. [ABSTRACT FROM AUTHOR]

Anatomical characteristics play a pivotal role in understanding the evolutionary relationship among various plant taxa and identifying species of pharmacological importance. Though the anatomical features of the family Apocynaceae have been widely recognized, there is limited research on the stem wood anatomy of Kopsia fruticosa, whereas nothing was previously known about its root wood anatomy. The present work describes and analyses its anatomy and correlates the anatomical features with the habitat and ecology of this plant. The oval shape of the young stem and the presence of unicellular trichomes, stone cells in the pith region, laticiferous canals, calcium oxalate crystals, and vascular bundles of two different sizes, viz., smaller in the broad, flattened region and more prominent on the two narrow sides, are remarkable features of the plant, which collectively may often be helpful in distinguishing K. fruticosa from other species of this genus. Apart from the previously known qualitative characteristics of the family Apocynaceae, the coalescence of pit aperture and storied pattern of vessels of K. fruticosa are newly observed features of the subfamily Rauvofiòideae. On the other hand, in the root wood, vessels are wider (33–64 μm), less frequent (about 53% more in the stem), and shorter, and the rays are larger (21–46 cells in height) and more frequent than those of stem wood; these are the valuable findings which strongly support the non-climbing nature of the studied plant. The vulnerability and mesomorphy indices for stem wood are 0.914 and 349, respectively, indicating plants' adaptation toward a mesic habitat. The correlation of the anatomical traits of plants with the habitat and ecology represents their survivability in different situations. Consequently, anatomical features such as intraxylary phloem, vessel grouping, the storied pattern of vessels, the simple perforation plate, and intervascular vestured pits suggest that plants can tolerate drought. We firmly believe that the present study's outcome can fulfil the research gaps of this hardy plant. [ABSTRACT FROM AUTHOR]

In the context of unprecedented extreme weather and climate events, the internal structural factors of society play a decisive role in the extent to which human beings are affected by disasters and their ability to respond to disasters. In the past few decades, the rapid urbanization process in developing countries represented by China has also greatly increased social vulnerability. The process has generated uneven living conditions and created many vulnerable groups, including urban poverty, migrants, and socially and geographically marginalized groups, who face difficulties in living conditions, education, livelihood stability, and so on. This study sets up indicators from a micro perspective: three indicators of exposure, four of sensitivity, and eight of adaptive capacity are involved. Based on this evaluation index system, this study conducts a social vulnerability assessment of the populations in Hongshan District, Wuhan City, China through individual questionnaire surveys. A-means cluster analysis was used to get the high, medium, and low levels of social vulnerability, which has achieved the comparison of different community types and the identification of vulnerable groups. The results show the close interrelationships between different types of communities in terms of physical and built environments, and different levels of social vulnerability to disasters, in particular pointing to the massive cluster of rural-to-urban migrants living in inferior urban villages, informal settlements in the city, and suffering especially from instability of livelihoods. The quantitative understanding of the dissimilarity in the degree of social vulnerability between different communities and populations is of great significance for the reduction of social vulnerability and disaster risk specifically and pointedly. [ABSTRACT FROM AUTHOR]

The frequent occurrence of climate related events and changes in average temperature, are predicted to increase the vulnerability of the coastal population of Sindh. A climate vulnerability index (CVI) was established and applied to the coastal subdistricts of Badin, Sindh, Pakistan. This study aimed to recognize the vulnerabilities of the coastal population of Sindh exposed to climate change. According to the study, the subdistricts of Badin have been exposed to high temperatures and significant climatic tragedies during the last two decades. The highest vulnerability to climate variability was found in Tando Bago (0.72) and Badin (0.70). Matli is better off in adaptive capacity through sociodemographic (0.29). The vulnerability to resource dependency and knowledge and skill was low in the sub-district of Talhar. In terms of sensitivity, Tando Bago is the most sensitive subdistrict in terms of health (0.55) and resource variability (0.80). The study raises concerns related to coastal communities and their aptitude to address present and upcoming challenges connected with climate change and increased insecurity. The CVI calculated (0.59) can be utilized to improve adaptive capacity, minimize sensitivity, and mitigate exposure to climatic extremes in adaptation planning. [ABSTRACT FROM AUTHOR]

Since the declaration of COVID-19 as a pandemic in March 2020, a large amount of statistical data analysis has been carried out to monitor the pandemic. However, to effectively manage its spread, it is necessary to analyze these data from a geospatial approach, which is why the integration of statistical and geospatial data at different levels of geographical disaggregation has become essential, which allows the development and implementation of new methodologies, such as index construction and calculations, to obtain data at a common spatial level to support decision making. In this way, the objective of this article is to present the methodology designed by DANE and implemented in the Central American region by UNGGIM: Americas and the PAIGH, for the integration of geospatial data, and the calculation of the "COVID-19 Vulnerability Index", as well as showing the results obtained, which are aimed at providing an effective response to the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

Frequently occurring extreme weather events have caused agricultural production losses in considerable amounts in the dry zone of Sri Lanka. Hence, it is important to understand the farmer groups and the systems that are highly vulnerable to climate change before proposing remedial measures. Paddy is the main crop cultivated by the dry zone farmers in Sri Lanka. The majority of the farmers cultivate paddy during the Maha season while Other Field Crops (OFC) are cultivated in the Yala season in the same land due to water scarcity. This study developed a climate vulnerability index for OFC farmers and tested the applicability of the developed vulnerability index using major and minor irrigation systems. For this study, secondary data was collected from relevant government institutions and field- level organizations. Yield data, demographic data, socioeconomic data, and marketing data were collected through a questionnaire survey. Indicators were selected under three dimensions of vulnerability, representing physical and environmental factors, socioeconomic factors, and external assistance factors. All indicators were calculated for each major and minor irrigation system separately. The results revealed that, farmers in both irrigation systems are highly vulnerable to the external assistance index while scoring low in the physical and environmental index and the socio-economic index. The minor irrigation scheme has a high external assistance to climate change compared to the major irrigation scheme. Overall vulnerability index results Indicated that, the climatic vulnerability of farmers in minor irrigation system is higher (61.6) than in major irrigation systems (57.1). Thus, these types of indices are useful in assessing the status of the farmers so that interventions can be applied to reduce their vulnerability and facilitate their livelihoods. [ABSTRACT FROM AUTHOR]

This paper presents a method for evaluation floor water inrush risk using combined weighting and analytic hierarchy process. The method is validated by a case study at the Pengzhuang coal mine in Shandong Province, China. First, the relevant geological background, hydrogeological data and related data were collected and analyzed, and the risk evaluation index of water inrush from the floor was determined. Then, combined with principal component analysis, entropy weight method and analytic hierarchy process, a comprehensive evaluation model was constructed to determine the comprehensive weights of each surge evaluation index. Finally, based on the GIS geographic information processing system, the optimized comprehensive weighting mathematical model was combined with the vulnerability index method to determine the water inrush risk division. The results show that the improved integrated weighting model is more accurate than the improved comprehensive weighting model. At the same time, the evaluation results obtained by comparing the traditional water inrush coefficient method have verified the reasonableness of the evaluation model. The results can provide a theoretical basis for the safe mining of coal seam above confined groundwater. [ABSTRACT FROM AUTHOR]

The present study aims at conducting a comprehensive seismic risk assessment for the North Eastern Region of India at regional and sub-regional levels by integrating probabilistic seismic hazard and social vulnerability assessments. Bedrock-level peak ground acceleration varied from 0.14 to 0.69g for the return period of 475 years. Using PCA, the social vulnerability index (SVI) was generated considering district-level socioeconomic indicators. Built environment quality, illiteracy, access to amenities, dependent population, and employment opportunities contributed to high SVI. Most vulnerable districts were concentrated in the Brahmaputra floodplains, Tripura fold belt, and Imphal valley. At the regional level, significant parts of Assam, Meghalaya, Arunachal Pradesh, and Tripura lie in moderate to very high-risk zones. At the sub-regional level, Nagaland accounts for the highest proportion of areas in high to very high-risk zones. The findings will aid site-specific resilient infrastructure design, disaster risk reduction, and effective resource allocation for the risk-prone areas. [ABSTRACT FROM AUTHOR]

Silt liquefaction can occur due to the rapid cyclic loading of sediments. This can result in the loss of the bearing capacity of the underlying sediments and damage to the foundations and infrastructure. Therefore, assessing liquefaction hazards is an important aspect of disaster prevention and risk assessment in geologically unstable areas. The purpose of this study is to assess the liquefaction hazards of silt sediments by using the horizontal-to-vertical spectral ratio method. Single-station noise recording was carried out in the northern plain of the Yellow River Delta, and a new method was adopted to identify the fundamental frequency. The dynamic parameters of the silt, such as the fundamental frequency, amplification, and vulnerability index, were used as indicators to assess the liquefaction potential. The results show that the silty soils in different areas have different stable ranges of values of the fundamental frequency. Moreover, the distribution of the observations is in good agreement with the geological conditions in the area, which indicates the potential applicability and reliability of the new method for identifying fundamental frequency. The vulnerability index is inversely related to the fundamental frequency, with the southwestern part of the study area having a lower fundamental frequency and a higher vulnerability index, meaning a greater liquefaction risk compared to other areas. The horizontal-to-vertical spectral ratio method has great advantages in characterizing subsurface dynamic parameters and can be applied to liquefaction hazard assessments of silt sediments in large areas, which is critically important in terms of providing information and guidance for urban construction and planning. [ABSTRACT FROM AUTHOR]

In recent decades, coastal erosion phenomena have increased due to climate change. The increased frequency and intensity of extreme events and the poor sediment supply by anthropized river basins (dams, river weirs, culverts, etc.) have a crucial role in coastal erosion. Therefore, an integrated analysis of coastal erosion is crucial to produce detailed and accurate coastal erosion vulnerability information to support mitigation strategies. This research aimed to assess the erosion vulnerability of the Sicilian coast, also including a validation procedure of the obtained scenario. The coastal vulnerability was computed by means of the CeVI (Coastal Erosion Vulnerability Index) approach, which considers physical indicators such as geomorphology and geology, coastal slope, sea storms, wave maxima energy flux and sediment supply to river mouths. Each indicator was quantified using indexes which were assessed considering transects orthogonal to the coastline in 2020. These transects were clustered inside natural compartments called littoral cells. Each cell was assumed to contain a complete cycle of sedimentation and not to have sediment exchange with the near cells. Physical parameters were identified to define a new erosion vulnerability index for the Sicilian coast. By using physical indexes (geological/geomorphological, erosion/sediment supply, sea storms, etc.), the CeVI was calculated both for each littoral cell and for the transects that fall into retreating/advancing coastal areas. The vulnerability index was then validated by comparing CeVI values and the coastline change over time. The validation study showed a direct link between the coastline retreat and high values of CeVI. The proposed method allowed for a detailed mapping of the Sicilian coastal vulnerability, and it will be useful for coastal erosion risk management purposes. [ABSTRACT FROM AUTHOR]

DRASTIC is a very simple and common model used for the assessment of groundwater to contamination. This model is widely used across the world in various hydrogeological environments for groundwater vulnerability assessment. The Ohio Water Well Association (OWWA) developed DRASTIC model in 1987. Over the years, several modifications have been made in this model as per the need of the regional assessment of groundwater to contamination. This model has fixed weights for its parameters and fixed ratings for the sub-parameters under the main parameters. The weights and ratings of DRASTIC parameters were fixed on the basis of Delphi network technique, which is the best technique for the consensus-building of experts, but it lacks scientific explanations. Over the years, several optimization techniques have been used to optimize these weights and ratings. This work intends to present a critical analysis of decision optimization techniques used to get the optimum values of weights and ratings. The inherent pros and cons and the optimization challenges associated with these techniques have also been discussed. The finding of this study is that the application of MCDA optimization techniques used to optimize the weights and ratings of DRASTIC model to assess the vulnerability of groundwater depend on the availability of hydrogeological data, the pilot study area and the level of required accuracy for earmarking the vulnerable regions. It is recommended that one must choose the appropriate MCDA technique for the particular region because unnecessary complex structure for optimization process takes more time, efforts, resources, and implementation costs.

Climate change vulnerability is highly counter-productive for agriculture among the arid and semi-arid regions. The study constructs the agriculture vulnerability index for Karnataka, a south Indian state. The state has faced frequent climate-related shocks in the last decade. The district-wise vulnerability index is estimated using longitudinal data considering exposure, sensitivity and adaptive capacity as sub-indices. The results show that the districts in the north interior region of Karnataka are highly vulnerable to the climate change followed by the districts in the south interior and coastal regions. There is an urgent need to prioritize the most vulnerable districts while formulating the development policies to minimize the risk of climate change on agriculture. Specific technical knowledge and support need to be made available to the farmers for informative climate resilience action. HIGHLIGHTS We developed a framework to derive the vulnerability index considering the impacts of climate change.; Three indices were calculated to estimate the overall vulnerability index.; Exposure − sensitivity − adaptive capacity, which include agriculture, social and climate indicators, were used to build the vulnerability index for the state.;

Background: Diarrhea and typhoid, ancient water-borne diseases which are highly connected to rainfall are serious public health challenges in the blocks of Kalahandi district of Odisha, India. Objectives: Corroboration of rainfall and waterborne diseases are available in abundance; therefore, the objective of this article is to calculate the climate and disease vulnerability index (CDVI) value for each block of Kalahandi. Methods: We have applied the livelihood vulnerability index with some modifications and classify the three major categories, i.e., exposure, sensitivity, and adaptive capacity into six subcategories. These six subcategories are further divided into 26 vulnerability indicators based on a detailed literature review. Results: The result indicated that the Thuamul Rampur block, the southernmost part of the district is highly exposed to the annual and seasonal mean rainfall, and the Madanpur Rampur block lies in the northernmost part of the district is highly exposed to diarrhea and typhoid. Based on the calculation of the final CDVI value, nearly 50% of blocks of the Kalahandi district fall in the category of very high to high vulnerable zones. Furthermore, it has been observed that factors such as rainfall and disease distribution, vulnerable population and infrastructure, and education and health-care capacities had a notable influence on vulnerability. Conclusion: It is rare to find a health vulnerability-related study in India at this microlevel based on the suitable indicators selected for a tribal and backward region.

Historical heritage plays a fundamental role in society. One of the primary targets for European countries is to ensure its safeguarding so that it can be enjoyed by future generations. This paper defines a procedure for the safeguarding of cultural heritage which is often in an advanced state of degradation and threatened by climate change and the increasing number of tourists. The methodology consists of three basic steps: the identification of the technical elements on which intervention is necessary, the assessment of the vulnerability level of these elements considering exogenous factors and the hierarchization of the most vulnerable elements through the application of the Analytic Hierarchy Process. The case study is the “Patio de los Leones” a world-famous site within the Alhambra and Generalife which every year attracts over 2 million tourists to Granada, Spain. The aim is to set priorities for intervention on the 124 “Macael” marble columns according to the need for restoration. The validation of the methodology and management of the data to achieve the hierarchy among the columns was done using an HBIM model.

Water resources vulnerability assessment provides the basis for the policymakers and the stakeholders regarding the state of the river basin to be focused for its better management. This research aims to assess the vulnerability index (VI) of the upper part of the Dong Nai (UPDN) river basin, which plays a crucial role for the socio-economic development of Ho Chi Minh City and 10 other provinces in the Southeast Vietnam, as well as its sub-basins. This study accounts from the year 1994 to 2030 (36 years) by using an integrated solution between the GIS, remote sensing (RS) and SWAT model in collaboration with guidelines prepared by United Nations Environment Programme (UNEP) and Peking University. Results from the land cover classification of Landsat images in the period of 1994–2020 revealed that the forest area decreased by 324,586 ha (approximately 29.4% of the basin area) and greatly influenced the VI. The UPDN basin's water vulnerability was a moderate level of which VI was 0.276, 0.303 and 0.310 in 1994, 2004 and 2014, respectively. By 2030, the projected VI value could expect to be 0.318 under the climate change scenarios of the representative concentration pathway (RCP4.5). At the sub-basins, Dak Nong and Dak R'Keh were two of the most vulnerable sub-basins of which VIs have could reach approximately 0.4 categorized as highly vulnerable areas. The results evidenced that the integrated techniques could be an efficient approach to provide useful information on the status of water resources to stakeholders in evaluating comprehensive options in terms of sustainable water resources management. [ABSTRACT FROM AUTHOR]

In power systems, the unintentional outage of a grid element can lead to overload and outage of other equipment and, through a domino effect, all or a large part of a power system may collapse. The resulting events are called cascading, consecutive, or sequential failures. So far, various methods have been proposed to identify the initial events of cascading failures with different levels of accuracy and computational load. In this paper, an effective approach is employed which, by calculating the maximum flow of independent paths between generators and loads in the network graph, identifies the critical lines and transformers of the network so-called the initial events of cascade failures. To validate this method, the enumeration method is utilized. The proposed method is implemented in IEEE 118-bus test system and the results are indicative of its efficiency, accuracy and fastness compared to other methods. [ABSTRACT FROM AUTHOR]

Drone expansion needs to be considered as a menace in cases of negligent, illicit, or non-cooperative use. In the case of airports, a complete protection against drone intrusion should rely on an intrusion management system, aiming at avoiding the closure of the airport. This system requires the setting of proper risk assessment methodologies for airport operations, to explicitly consider the features of drone intrusion, possibly from a quantitative point of view. This work proposes a methodological framework for the risk assessment of drone intrusions in airports, tailored on drone-intrusion features, airport features, and current operations, and considering both safety-related and security-related causes. The framework is based on the combination of model-based and data-driven approaches in order to: (i) estimate an airport vulnerability index, to measure the susceptibility of the airport to drone intrusions, based on reference datasets; (ii) specify a set of event trees to evaluate the risks of the different threat scenarios related to drone intrusions. The proposed methodological framework is applied to a concrete case study, related to Milan Malpensa airport. The achieved results show the effectiveness of the approach and elicit further requirements for counter-drone systems in airports based on the assessed risks. [ABSTRACT FROM AUTHOR]

Identifying conservation strategy is essential regarding prioritization, planning, and managing biodiversity. The Eastern Himalayan freshwater reaches contain diverse taxa of fish species. Despite having several coarse scales of assessment, the information regarding the fine-scale conservation priorities is scanty. The development of indices from multimeric attributes has been proved efficient, aiding conservation planning, in-depth research, exploitation, policy-making, and public awareness. Therefore, this study aims to provide detailed indexing of conservation values for the freshwater fish species inhabiting the sub-Himalayan Terai–Dooars ecoregion of the Eastern Himalayas. Based on three years of extended sampling in six freshwater reaches, 170 indigenous fish species were identified. Each fish species was assigned a discrete conservation value following their rarity, taxonomic singularity, contribution to β diversity, global threat status, regional importance, and maximal achievable body lengths. Neolissochilus hexagonolepis has the highest conservation value. In contrast, the lowest values were observed for Pethia gelius, Pethia guganio, and Pethia phutunio. The freshwater habitats of upper and lower elevation harbor essential fish species for conservation, driven by precipitation, topographic, and land cover variability. Such results were accomplished through spatial interpolation and prioritization regarding fish conservation, protection, and vulnerability toward the human footprint for this region of the Eastern Himalayas. [ABSTRACT FROM AUTHOR]

Geophysical investigation employing vertical electrical sounding (VES), pumping test and in situ groundwater conductivity measurement were carried out in Mosogar, Delta State in order to determine the aquifer properties and vulnerability indices. The Schlumberger electrode configuration was used for the vertical electrical sounding (VES) survey to acquire electrical resistivity data which were interpreted using the WinResist software, version 1.0 (2004). The results revealed that the lithology is composed mainly of sand with various grades with four to five delineated geoelectric layers. Results of hydraulic conductivity, transmissivity and formation factor of the aquifer were found to vary from 7.9233 to 9.2799 m/day, 45.670 - 235.323 m2/day and 0.545 - 23.664 respectively. Aquifer vulnerability indices within the study location indicate moderate to extremely high vulnerability as classified by aquifer protective capacity (APC), aquifer vulnerability index (AVI), Geo-electric layer susceptibility index (GLSI) and groundwater confinement, overlying strata and groundwater depth index (GOD) models employed, with values ranging from 0.00766 - 0.038728, -0.5631- 0.3025, 2.25 - 3.00 and 0.4 -0.8 respectively. The results revealed that the groundwater is prone to contamination because of weak protection provided by overlying geologic units. Using the Golden surfer 10 software, maps of geo-hydraulic parameters and vulnerability indices were constructed which characterises the aquifer parameters in the area. This study provides an important tool for sustainable groundwater exploration and management in Mosogar. [ABSTRACT FROM AUTHOR]

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An effective infrastructure asset management (AM) system is crucial for utilities, city officers, government agencies, and other asset-owning organizations to facilitate navigating the numerous challenges associated with operating and managing infrastructure assets. In this paper, the AM system itself is represented as a complex network (comprised of nodes and links) that describes the major components necessary for its operation within an organization and the information connections between such components. ISO 55001, a widely accepted international standard, specifies the requirements for an effective AM system and outlines the criticality levels of different system components—reflected in the corresponding network by the link weights. The main challenges facing managing an AM system (i.e., metamanagement) pertain to (1) information asymmetry (i.e., not relying on consistent information for decision making) between AM system components; and (2) information overload (i.e., excessive information undermining decision making) within the AM system components. These challenges cause systemic risks (possibility of dependence-induced disruptions) within the system network due to the connectedness of system components. Systemic risks can be mitigated through built-in network resilience by restructuring the system component connections. Such network reconfiguration presents a complex nonconvex optimization problem with multiple potential solutions depending on the number of new connections to be added to the AM system, the length of those connections, and the target risk mitigation level. Through this metamanagement (managing the management system) lens, a genetic algorithm approach was employed to explore the optimal AM network configurations considering different objective functions. These objective functions were based on different complex network measures including the betweenness-, closeness-, and eigenvector-centrality, as well as the vulnerability index. The devised objective functions were employed to the cases of adding 1 to 15 links only to limit network overconnectedness (i.e., information overload). Considering all objective functions evaluated, adding a small number of links (fewer than five) provided a significant reduction in systemic risk (18% to 49%). Finally, managerial insights are presented to explain how to employ the developed approach to mitigate the systemic risks within an organization's AM system based on different metrics valuations and stakeholder inputs. The effective implementation of infrastructure asset management systems within organizations that own, operate, and manage infrastructure assets is critical to address the pressing challenges facing the infrastructure decision makers (e.g., infrastructure ageing and deterioration, maintenance backlogs, strict regulatory operating conditions, limited financial resources, and losing valuable experience through retirements). Infrastructure asset management systems contain connectivity between major operational components that can lead to systemic risks (i.e., dependence-induced possible disruptions). Such systemic risks are typically caused by information asymmetry, when (some) asset management stakeholders operate in silos, and/or information overload, when asset management stakeholders are overwhelmed by too much/irrelevant information thus, hindering their decision-making effectiveness. The approach described in this paper empowers infrastructure asset managers with the necessary means to reduce their organizations' systemic risk exposure, and subsequently enhance their organization resilience to information asymmetry and/or overload. This study is meant to be applied by organizations that align their asset management system with an accepted system that includes 39 separate asset management subject areas. [ABSTRACT FROM AUTHOR]

Biological agents as weapons of agro‐crime or agro‐terrorism pose threats to peace and economic stability. Such agents pre‐exist worldwide as hazards, adversely affecting animal health, as well as imposing substantial burdens on many nations. Few studies have quantified the global risks and vulnerabilities of countries and regions to potential terrorist or criminal operations targeting animal health. We present here a risk‐based mutual insurance premium framework for animal health outcomes built upon the World Organisation for Animal Health (WOAH) quantitative risk assessment paradigm. Our objective was to generate dimensionless and relative domain indices related to release and exposure for several biological factors, as well as to assess the preparedness and response ability of each country. We also considered disease‐specific measures relating to pathogens, targeted animal populations, the ongoing disease situation, within‐ and among‐country peace or conflict, disease‐specific control measures, and the availability of technical tools and personnel for successful disease management. National economic, political, and research and development competencies were used to assess each WOAH Member's potential for resilience. We formulated indices of vulnerability for 25 WOAH Members selected from five worldwide regions; initially, against four transboundary infectious animal diseases that target diverse animal species. We developed these indices using variables obtained from public databases arising from multiple intergovernmental organizations. Subsequently, we compared the relative vulnerability indices among countries for each given disease using three different index building methods: arithmetic mean, distance matrix, and principal component analysis (PCA). The PCA‐based approach provided the greatest ability to discriminate among the components and among countries and regions. Due to its transparency and reliance on publicly available datasets, the risk premium framework proposed herein may readily be adjusted by policymakers and agencies and utilized to improve risk management strategies against agro‐crime or agro‐terror events, as well as for unintentional disease introductions. [ABSTRACT FROM AUTHOR]

Identification of spatial gradient in the vulnerability of white leg shrimp production to climate change is imperative in the formulation and implementation of suitable adaptive measures. A composite vulnerability index was computed by employing 36 variables pertaining to exposure (11), sensitivity (11) and adaptive capacity (14) dimensions to map the extent of vulnerability in white leg shrimp production across Indian states. Based on its magnitude, the vulnerability index was categorized into three groups, namely low, moderate and high. Results showed that the mean composite vulnerability index was 0.65 and ranged from 0.34 to 0.99 indicating that there was a strong spatial pattern. Among the nine states, Goa (0.99), Kerala (0.84) and Odisha (0.77) were highly vulnerable; Gujarat (0.75), Karnataka (0.57) and West Bengal (0.56) were moderately vulnerable; and Tamil Nadu (0.54), Andhra Pradesh (0.46) and Maharashtra (0.34) were less vulnerable to shrimp production. About one‐fourth of the production and culture area of white leg shrimp were in moderate and highly vulnerable regions. The impact of climate change on shrimp production is diverse but can be reduced by implementing adaptive measures—suitable policies and investment plans—which should be region‐specific. [ABSTRACT FROM AUTHOR]

This paper proposes a new method to identify the vulnerable lines in power grids and predicts the cascading failure path by constructing a cascading failure model of power grids. The line vulnerability index (LVI) of power grids based on line degree and line overload risk is firstly proposed. Then, a cascading failure model of power grids based on LVI is presented while overload emergency control strategy is employed to reduce generation and load powers. Roulette algorithm is used to select sub-fault lines. Finally, the model is applied to the IEEE 39-bus system for simulation. Based on LVI with different weights, simulation results analyze the impact of cascading failure on power grids structure and power balance. It shows that the grid cascading failure model based on the proposed line vulnerability index can simulate the process of cascading failure, comprehensively identify the vulnerable lines of power grid and accurately predict the path of cascading failure. [ABSTRACT FROM AUTHOR]

Turkey includes the major and active tectonic structures, which are the North Anatolian Fault Zone, the East Anatolian Fault Zone, Aegean extension region and Bitlis-Zağros thrust belt. Many destructive earthquakes have occurred on these tectonic structures and caused loss of life and property. Therefore, determining the soil properties that increase the destructive effect of earthquakes is an important parameter for the construction around these tectonic structures. In this study, it is aimed to investigate the soil properties (the soil predominant period, bedrock depth, Vs30) using 103 earthquake acceleration data (in the range of 3.5 ≤ Mw ≤ 6.8) recorded by 27 strong ground motion stations in the Eastern Pontides, Turkey. Moreover, the study area includes provinces (Samsun, Trabzon, Ordu, Giresun, etc.) with a high population density that may be affected by a destructive earthquake. The H/V spectral curve and the geometric mean of these curves were calculated for the earthquakes recorded by each station to assess the soil column. First, the predominant period and amplification factor of the soils were obtained from these curves. The predominant period values vary from 0.4 to 0.6 s and the amplification factor values change from 1.6 to 7.0. The stations with the largest period and amplification factors are 5301 and 5507, respectively. Furthermore, the soil vulnerability index (Kg), the bedrock depth, Vs30 values were obtained from these two parameters using empirical equations. Kg values are observed between 0.4 and 36. The highest Kg values were obtained at stations 5505 and 5507 in Samsun. The bedrock depth was calculated using twelve different empirical relations. The higher bedrock depth was obtained around Samsun–Giresun and the north of Erzurum. In addition to these evaluations, the empirical Vs30 relations were tested for the study area to determine the most suitable relation. As a result of all analyses, it was determined that Samsun province is a risky region in terms of soil. Detailed microzonation studies should be carried out to determine soil properties for this region. [ABSTRACT FROM AUTHOR]

This study investigated and classified typical structures in rural village and analyzed the vulnerability. Based on the statistics of earthquake damages with magnitudes above 5 from 1996 to 2013 in China, the damage matrixes of types of structures in rural village are obtained. The vulnerability index and equation of structure are crucial to assess the earthquake losses of typical structures under different magnitudes earthquakes. According to the seismic loss of different types of structures under different earthquake magnitudes, there are possible to improve the seismic resilience of the buildings in rural village. Moreover, the regional vulnerability is analyzed by β probability distribution function. The comprehensive seismic vulnerability index of different types of structures in rural villages is obtained. The main research is to predict the loss of different types of structures under different earthquake magnitudes in the future, and to provide technical support for types of buildings in rural village reinforcement. [ABSTRACT FROM AUTHOR]

Climate change (CC) is a significant concern for many climate-sensitive socio-economic sectors, such as agriculture and food production. The current study aimed at analyzing the current vulnerability of the Moroccan agricultural sector to CC and anthropogenic impact and identifying the relevant vulnerability factors in the Beni Mellal-Khénifra region. In this regard, a multidisciplinary approach was used to assess the vulnerability. To do this, an index based on five components was designed, including climate, plant production, animal production, geography, and anthropogenic aspects. The numerical model has benefited from data retrieved from three recognized indices such as Normalized Difference Vegetation Index (NDVI), Standardized Precipitation Index (SPI), and Vegetation Condition Index (VCI), and from the reported data of the agricultural, environmental, and socio-economic governmental departments. The results showed that there was a significant vulnerability of all the five components to CC. Particularly, the province of Azilal was the most vulnerable, followed by Khénifra, Fquih Ben Salah, and Beni Mellal, while Khouribga was the least vulnerable. These components might help to determine the mechanisms and priority sectors, the most vulnerable to CC and anthropogenic effects, to take urgent measures. These may guide decision makers to carry out effective actions, namely, the amounts to be spent to mitigate this vulnerability. It will also make it possible to know where, when, and how the adaptation should take place. [ABSTRACT FROM AUTHOR]

Abstract Evidence has demonstrated that microRNA-342-5p (miR-342-5p) is implicated in atherosclerosis (AS), but little is known regarding its intrinsic regulatory mechanisms. Here, we aimed to explore the effect of miR-342-5p targeting Wnt3a on formation of vulnerable plaques and angiogenesis of AS. ApoE−/− mice were fed with high-fat feed for 16 w to replicate the AS vulnerable plaque model. miR-342-5p and Wnt3a expression in aortic tissues of AS were detected. The target relationship between miR-342-5p and Wnt3a was verified. Moreover, ApoE−/− mice were injected with miR-342-5p antagomir and overexpression-Wnt3a vector to test their functions in serum lipid levels, inflammatory and oxidative stress-related cytokines, aortic plaque stability and angiogenesis in plaque of AS mice. miR-342-5p expression was enhanced and Wnt3a expression was degraded in aortic tissues of AS mice and miR-342-5p directly targeted Wnt3a. Up-regulating Wnt3a or down-regulating miR-342-5p reduced blood lipid content, inflammatory and oxidative stress levels, the vulnerability of aortic tissue plaque and inhibited angiogenesis in aortic plaque of AS mice. Functional studies show that depleting miR-342-5p can stabilize aortic tissue plaque and reduce angiogenesis in plaque in AS mice via restoring Wnt3a.

Threats caused to the environment and human life by climate change have become an urgent issue. Climate change often aggravates hazards in a given area and has harmful effects on the people residing there. Affected by massive floods, land erosion, and the destruction of agricultural lands, char people live a risky life. Char dwellers are among the communities that suffer the most as a result of the effects of climate change. Few studies discuss the vulnerabilities of communities living in char areas to climate change. This paper attempts to summarize the existing research. It also discusses data-related issues in the measurement of vulnerability to climate change. It ends by raising some policy-related considerations.

While nuclear power plants (NPP) are built back in Germany, the exposure risk will remain for some time being. This study conducts a geospatial analysis in exposure radii from 5 to 80 km around 41 NPP sites in and around Germany. The results show that 40 out of 113 major cities are exposed, and that vulnerability patterns vary. Foreigners and women live closer to NPPs, while it is the opposite with young and elderly people. This non-regular spatial distribution of population groups can be important to guide evacuation and emergency planning.

Abstract Background This research estimates the effects of vulnerability on the spread of COVID-19 cases across U.S. counties. Vulnerability factors (Socioeconomic Status, Minority Status & Language, Housing type, Transportation, Household Composition & Disability, Epidemiological Factors, Healthcare system Factors, High-risk Environments, and Population density) do not only influence an individual’s likelihood of getting infected but also influence the likelihood of his/her neighbors getting infected. Thus, spatial interactions occurring among individuals are likely to lead to spillover effects which may cause further virus transmission. Methods This research uses the COVID-19 community index (CCVI), which defines communities likely vulnerable to the impact of the pandemic and captures the multi-dimensionality of vulnerability. The spatial Durbin model was used to estimate the spillover effects of vulnerability to COVID-19 in U.S. counties, from May 1 to December 15, 2020. Results The findings confirm the existence of spatial spillover effects; with indirect effects (from neighboring counties) dominating the direct effects (from county-own vulnerability level). This not only validates social distancing as a strategy to contain the spread of the pandemic but also calls for comprehensive and coordinated approach to fight its effects. By keeping vulnerability factors constant but varying the number of reported infected cases every 2 weeks, we found that marginal effects of vulnerability vary significantly across counties. This might be the reflection of both the changing intensity of the pandemic itself but also the lack of consistency in the measures implemented to combat it. Conclusion Overall, the results indicate that high vulnerability in Minority, Epidemiological factors, Healthcare System Factors, and High-Risk Environments in each county and adjacent counties leads to an increase in COVID-19 confirmed cases.

Abstract Background The adverse effects of climate variability and extremes exert increasing pressure on rural farm households whose livelihoods are dependent on nature. However, integrated and area-specific vulnerability assessments in Ethiopia in general and the study area, in particular, are scarce and insufficient for policy implications. Therefore, this study aims to quantify, map, classify, and prioritize the level of vulnerability in terms of the components of exposure, sensitivity, and adaptive capacity in the Northeastern Highlands of Ethiopia. The study area is divided into six livelihood zones, namely, Abay-Beshilo Basin (ABB), South Wollo and Oromia eastern lowland sorghum and cattle (SWS), Chefa Valley (CHV), Meher-Belg, Belg, and Meher. A total of 361 sample households were selected using proportional probability sampling techniques. Survey questionnaire, key informant interview, and focus group discussions were used to collect the necessary data. Rainfall and temperature data were also used. Following the IPCC’s climate change vulnerability assessment approach, the climate vulnerability index (CVI) framework of Sullivan and Meigh’s model was used to assess the relative vulnerability of livelihoods of rural households. Twenty-four vulnerability indicators were identified for exposure, sensitivity, and adaptive capacity components. In this regard, Iyengar and Sudarshan’s unequal weighting system was applied to assign a weight to indicators. Results The results revealed that Belg and Meher were found to be the highest exposure livelihood zones to vulnerability with an aggregated value of 0.71. Equally, SWS, ABB, Belg, and CHV livelihood zones showed moderate level of sensitivity to vulnerability with an aggregated value between 0.45 and 0.60. The study noted that livelihood zone of Belg (0.75) was found to be at high level of livelihood vulnerability. ABB (0.57) and CHV (0.45) were at a moderate level of livelihood vulnerability while Meher-Belg (0.22) was the least vulnerable livelihood zone due to a high level of adaptive capacity such as infrastructure, asset accumulation, and social networks. Conclusion It was identified that disparities of livelihood vulnerability levels of rural households were detected across the study livelihood zones due to differences in the interaction of exposure, sensitivity, and adaptive capacity components. The highest levels of exposure and sensitivity combined with low level of adaptive capacity have increased households’ livelihood vulnerability. More importantly, the biophysical and socioeconomic sensitivity to livelihood vulnerability were exacerbated by slope/topography, soil erodibility, and population pressure. Therefore, designing livelihood zone-based identifiable adaptation strategies are essential to reduce the exposure and sensitivity of crop-livestock mixed agricultural systems to climate calamity.

The Nilüfer district experienced the most recent urbanization among the central districts of Bursa in South Marmara region with the completion of rapid construction. Since 358 BCE, many destructive earthquakes were reported on the branches of the North Anatolian Fault (NAF) which caused extensive damage to buildings and loss of life near Bursa city. Besides some studies conducted to define the soil behavior in the vicinity of Bursa, a seismic hazard study in Nilüfer is still lacking. We, therefore, carried out a microzonation study including the following steps. First, an earthquake hazard analysis was conducted and the peak ground acceleration (PGA) values were determined for an expected earthquake. In the next step, MASW (Multi-Channel Analysis of Surface Wave) measurements conducted at 54 points in 28 neighbourhoods of Nilüfer district were evaluated. Soil mechanical parameters were determined at 11 boreholes to assess the liquefaction potential. It was found that almost half of the study area suffers from low damage considering only the vulnerability index (Kg) index, which depends on the site effect. Therefore, in addition to the Kg values, we created a microzonation map using the results of soil liquefaction, settlement, changes in groundwater level, and the average values of spectral acceleration. The study area is classified by four damage levels changing from low to high. Using only the Kg index could not quantify the potential damage level in the study area, thus we showed that the districts of Altınşehir, Hippodrome, Ürünlü and Alaaddinbey, Ertuğrul, 29 Ekim, 23 Nisan, Ahmetyesevi and Minareliçavuş were identified at potentially high-risk damage zones. The results of this study clearly showed that considering the Kg index, which depends only on the local site effect, may lead to inadequate damage values. • The district of Nilüfer in the Bursa City will have high damage from any future potential earthquake in the middle branch of the North Anatolian Fault • Site effect and liquefaction are important problems in the study area. • Kg index, which depends only on the local site effect, may lead to inadequate damage values. • Microzonation studies and the Kg index have to been evaluated together for an resilience city management in urban planning. [ABSTRACT FROM AUTHOR]

The analysis of seepage through earthen levees is fundamental to investigate the levee safety condition, since that the seepage phenomenon can often lead to piping causing the collapse of the levee (Saghaee et al., 2012). This work proposes a new approach for identifying the location of the saturation line through the earthen levee by using a multilayer soil approach that assumes the levee body and the levee foundation as two different layers, characterized by using a different hydraulic conductivity parameter. The main purpose is to investigate the difference in the predicted saturation line identified through the proposed method and the one based on the single layer analytical solution of the seepage flow suggested by Marchi (1961). On comparison of the saturation lines provided by two different approaches, the ratio between the river water head and the groundwater thickness or depth increases; allowing the determination of a ratio threshold above which the Marchi equation should no longer be applied. The proposed multilayer (levee and foundation) soil approach is also used to assess the seepage vulnerability of the methodology proposed by Barbetta et al. (2017). The results show that the differences between the seepage vulnerabilities evaluated using the multilayer approach and the single layer method are quite low. Although notably, significant modifications of the seepage probability are observed when the distance between the ground level and the groundwater table changes. [ABSTRACT FROM AUTHOR]

Vulnerability analysis is a crucial step in developing adaptation strategies against the climate change. The communities residing in Himachal Pradesh are more vulnerable to suffer harm due to their inherent socio-economic and geographical characteristics. The present study evaluates the district-level vulnerability of the state by analysing the secondary data on sixteen indicators; which is segregated into its three components (exposure, sensitivity and adaptive capacity) over a period of 34 years (1985-2018). The results reveal that Mandi (0.334) is most vulnerable to climate change, while Lahaul-Spiti (0.074) district is the least one. Out of twelve districts, only three viz., Bilaspur, Lahaul-Spiti and Kinnaur have experienced a declining trend, while, a rising trend has been experienced in the vulnerability of Hamirpur, Kangra, Mandi, Sirmour, Solan and Una districts. Sirmour (31.10) has the highest instability in the vulnerability, whereas lowest instability is observed in Hamirpur district (7.79). The three components of vulnerability index viz., exposure, sensitivity and adaptive capacity have been observed to be highest in Mandi (0.269), Hamirpur (0.146) and Kullu (0.055) and are lowest in Lahaul-Spiti (0.041), Sirmour (0.067) and Kullu (0.040), respectively. [ABSTRACT FROM AUTHOR]

The coastal zone of mainland Portugal is characterized by its morpho-sedimentary diversity such as estuaries, lagoons, barrier islands, beaches, dunes and cliffs. The high population density and the multiplicity of land use, occupation and activities, makes it an area of great national strategic value. This transforms the coastal zone into a multi-hazard zone, where the occurrences related to coastal flooding and overtopping stand out. In the present work, a multidimensional methodology called Coastal Territorial Vulnerability Index (CTVI) was developed and applied in three selected areas with a historical record of coastal impacts, to analyze, evaluate and interpret the local vulnerability. The methodology considers four components of coastal territorial vulnerability: morphology, land value, buildings and public areas characteristics. These four components are combined to calculate the CTVI. The results highlight the differences for the analyzed areas, allowing the differentiation of natural and artificial areas. In the natural areas a moderate CTVI predominates, while in the latter, a high and very high CTVI stands out. The results contribute to the development of a comprehensive coastal flood risk assessment and forecasting the impacts. [ABSTRACT FROM AUTHOR]

Strengthened masonry buildings are one of the most common types of old structure usually located in the ancient Algerian urban nuclei. The present study focused on common strengthened masonry buildings. Feedback from seismic experiments has shown that their dynamic behavior is generally nonlinear and highly vulnerable to earthquakes. Also, in order to predict the rate of damage that could occur to this type of structure in the event of earthquakes, empirical fragility curves based on a probabilistic method have been developed. In this study, seismic fragility analysis has been performed using the vulnerability index and the average damage rate. The vulnerability index will belong to one of three vulnerability classes determined by nonlinear dynamic analysis. The average damage is obtained using a deterministic method taking into account the vulnerability index and the seismic intensity. The fragility curves, which give the probability of achieving or exceeding a certain damage level for the three classes of vulnerability considered, have been compared to different studies that developed similar analyses. A seismic scenario was performed using a geographic information system and applied to strengthened masonry buildings located in Algiers city, which was built before the first Algerian seismic regulations of 1981. [ABSTRACT FROM AUTHOR]

Climate variability is widely recognized as a major concern, particularly in resource-scarce regions where it limits livelihood opportunities by putting additional strain on already depleting resources, resulting in human insecurity and conflicts. Some vulnerability assessments have created a nexus between climate variability and conflicts. The Climate-Water Conflict Vulnerability Index (CWCVI) and the Climate-Agriculture Conflict Vulnerability Index (CACVI) are applied as a tool for exploring the climate and conflict interactions, as well as contrasting the vulnerabilities of the coastal districts of Badin, Thatta, and Sujawal. The analysis incorporates a dual exposure of communities in the form of climate variability and conflict over water and agricultural resources. The study finds that aggression and feelings of insecurity about depleting resources are the main contributing indicators of climate-conflict vulnerability in the coastal districts. District Sujawal showed higher vulnerability in adaptive capacity as compared to the other districts due to poor infrastructure and high dependency on natural resources. However, the district of Badin demonstrated high vulnerability in terms of sensitivity and its exposure to conflicts over agricultural resources is high. The overall CWCVI and CACVI scores were higher in Badin and Thatta, respectively. This study identifies a number of indicators that can be used to improve the efficacy of mitigation strategies to reduce conflict vulnerability in future policy directions and resource planning. [ABSTRACT FROM AUTHOR]

This study aimed to evaluate the vulnerability index of water resources towards the climate variability of the upper Citarum watershed in West Java Province. The vulnerability was estimated using the IPCC concept, where vulnerability is a function of exposure, sensitivity, and adaptive capacity. The criteria and indicators of exposure, sensitivity, and adaptive capacity were obtained via analysis of secondary data consisting of climate data, hydrological data, and the ability of the community to adapt to events of water resource vulnerability. The criteria and indicators were then scored and weighted according to their degree of interest; they were then presented spatially and overlaid to obtain the vulnerability maps. This study also predicted the rainfall intensity in Citarum Watershed until 2040. Rainfall is predicted to increase until 2040, especially in wet months (January-March); dry months are predicted to have no significant increase in rainfall. A vulnerability map was then prepared to show each watershed percentage with categories of high, medium, and low vulnerability levels. This review can be used for watershed management or other shareholders to construct a strategy, plans, and actions that overcome issues of water resource vulnerability. [ABSTRACT FROM AUTHOR]

The seismic vulnerability index (Kg) is based on soil dynamic properties. To create a seismic vulnerability index map, horizontal-to-vertical spectral ratio (HVSR) microtremor measurements were taken at over 260 locations throughout the Makkah Al-Mukarramah urban region. The fundamental resonance frequency and accompanying maximum relative amplification maps have been developed based on the H/V results. According to these maps, portions of the wadis in Makkah have fundamental resonance frequencies ranging from 0.26 and 17.27 Hz and may amplify bedrock ground motion by up to 14 times with the estimated amplification factor of 0.87 to 14.68 for the studied sites. The vulnerability index reveals the structural damage before destructive earthquakes. The values of the vulnerability index range from 0.13 to 284, with a high value of vulnerability indicating that the area in this value is located on the thickest layer of soft soil, posing the greatest risk. In the Al-Sharai’a, Ar Rashidiyyah, Al Khadra, AN Nassem, Al Shoqiah, and AZ Zahir districts, in the An nuzah, Batha Quraish, and Umm Al Qura University districts, a moderate result of the vulnerability index indicates that the location is located in stiff soil, which poses a moderate risk. The Makkah Al-Mukarramah municipality’s civil engineers and urban designers will benefit from these findings. In addition, these results can be used to improve the Saudi Building Code. [ABSTRACT FROM AUTHOR]

Although smart grids are characterized by self-healing, economy, high efficiency, and security, many hidden dangers exist in the development of smart grids due to a gradually expanding power grid and the continuous access of new energy to the power grid. Therefore, the development of smart grids, especially their reliability, security, and vulnerability, warrants further investigation. In this study, the vulnerability of smart grids is identified, and the vulnerability elements of smart grids are selected. Based on relevant theories, such as credibility and the combination of the credibility-based moment-generating function and the distortion function, a calculation model and framework of the vulnerability index of a smart grid are constructed. An empirical analysis is also conducted. This study provides a scientific basis for analyzing the vulnerability of smart grids and suggesting reasonable preventive measures and auxiliary decision-making information for relevant planning, design, and operation personnel, which contributes to the sustainable and healthy development of smart grids. [ABSTRACT FROM AUTHOR]

Dryland farming is highly affected by climate variability as its coefficient of variation with precipitation is high. The vulnerability assessment is a useful and effective tool for determining the impact of climate change on dryland farmers towards adaptation. The factors assessment plays an important role in designing and implementing policy research on a local scale in developing nations. The study aims to calculate the vulnerability level and factors affecting it in the dryland community in Southern India using Vulnerability index calculation and Machine Learning (ML) techniques. The primary data were collected with a structured questionnaire from randomly selected 200 farming households from ten villages. This study introduced new contextual variables in the vulnerability assessment and compared different ML techniques to analyse the vulnerability factors. The study showed that the dryland community is moderately vulnerable because of its higher adaptive capacity. The results of the ML techniques showed that the factors "Involvement in the awareness programmes, income sources for food, farm size, and education status of the dryland farmers" had a significant impact on the vulnerability level of the community. Potential coping strategies were identified to reduce the vulnerability level of the dryland farmers. The present study showed a pathway that can help the policy research and development plan for the sustainable livelihood of dryland farmers at a micro-level in the climate-changing scenario. [ABSTRACT FROM AUTHOR]

In many places of the world, the interruption of touristic activities in the aftermath of a catastrophic earthquake is often neglected in the evaluation of seismic risks; however, these activities can account for a significant proportion of short-term and long-term economic impacts for these regions. In the last decade, several rapid visual screening techniques have been developed to define the typology of buildings and to estimate their seismic vulnerability and potential for damage. We adapted the existing screening procedures that have been developed for generic buildings to specific circumstances that are most common for tourist accommodations. The proposed approach considered six criteria related to structural and nonstructural elements of buildings, as well as local soil conditions. A score was assigned to each criterion as a function of the capacity of the elements to resist ground shaking. A vulnerability index in four levels of building vulnerability was developed combining the scores of the six criteria. The approach was tested in a pilot area of Montreal to a set of 70 typical buildings grouped in four categories based on their accommodation capacity. In Montreal, tourism is an important source of income for the city where 351,000 room-nights were booked with total stay expenditures of CAD 4.9 billion in 2019. The results indicated potential significant disruptions in activities related to tourism; 46% of the buildings investigated have a high to very high vulnerability index. Among them, 4/5 are located in the old city and 1/5 in the downtown area of the pilot zone.