Property Damage Research Articles

Detecting high-risk road segments using kriging and inverse distance weighted methods

The detection of high-risk road segments is essential to set priorities in road rehabilitation projects. The ArcGIS tool has been used in previous studies as an alternative tool to identify high-risk segments. However, most tools use crash frequency as a safety performance measure. In this study, the aim is to investigate how ArcGIS tools, specifically kriging and inverse distance weighted (IDW) tools, can be used to find high-risk road segments using crash rate and equivalent property damage only (EPDO) metrics. A road section with a length of 85 km was selected for applying the investigated tools. Crash data with their details were collected from the official police station for 3 years. Kriging and IDW tools were processed by selecting five clusters, from the high-risk to the no-risk levels. The ranks of the segments have been compared with those resulting from the K-mean method using the t-paired test. The test results indicate that kriging and IDW yield uncorrelated segment ranks compared to the K-mean rank. In addition, using these tools produced false positives and false negative cases. According to the K-mean results, 37.8 km is diagnosed as the top highest risk segment, subjected to further crash data analysis to identify the risk factors and recommend suitable countermeasures.

Incoming flow calculation in Nam Theun 2 Reservoir

Laos is a country with a humid tropical climate, consisting of two seasons: the rainy season and the dry season. The southwest monsoon influences the region from mid-May to early October, while the northeast monsoon affects the area from early November to mid-March. Generally, the average annual rainfall ranges from 1400 mm to 2500 mm and exceeds 3500 mm in the central and southern regions. In September 2018, a hydroelectric dam encountered issues, causing part of the dam to collapse in southern Laos, Attapeu province. This disaster resulted in severe damage, with 98 people missing and 6,600 people displaced. In early September 2024, northern Laos experienced sudden flooding in Luang Namtha province, causing significant property damage. Additionally, heavy rainfall influenced by Typhoon Yagi led to the release of water from northern Laos dams for safety, including Nam Tha, Nam Ou, Nam Lik, Nam Khan 2-3, and Xayaburi dams. The issues arose from heavy rainfall and miscalculations in water flow into reservoirs, particularly in dam water management to provide early warning information to downstream communities. The purpose of this study is to assess the accuracy of the Intergrade Flood Analysis System (IFAS) model in calculating water inflow into reservoirs, specifically Nam Theun 2, to support to the water management and prevent flood-related issues. The performance of the IFAS model result used NSE (Nash-Sutcliffe efficiency), PBIAS (percent bias), R2 (coefficient of determination), and RSR (root mean square error) to compare calculated by IFAS and the water balance from 2010 to 2024, with results of NSE = 0.58, PBIAS = 8.79, R2 = 0.68, and RSR = 0.65. The 2023 study showed the highest accuracy with NSE = 0.73, PBIAS = -12, R2 = 0.83, and RSR = 0.52, Ev = 9.6 % The findings concluded that the IFAS model can calculate daily water inflow but has limitations in calculating peak and the extreme climate dry condition, such as in 2020 and 2022.

A conceptual framework for the process protocol of integration quality, safety, health and sustainable construction management systems for infrastructure projects in Indonesia

Construction accidents on infrastructure projects in Indonesia from 2017-2021 have increased by 5.65% from previous years. Construction accidents that result in property damage, death or injury to both workers and the public, pollution and environmental damage cause sustainable development goals not to be achieved. Construction accidents are not only focused on the impacts, but it is necessary to explore how the incident occurred. This is the basis for the need to integrate quality, safety, health and sustainability in construction. The current construction safety management system is not yet integrated with other management systems. This paper aims to develop a conceptual framework in the process of integrating construction quality, safety, health and sustainability management systems. Development of a conceptual framework based on literature review, ISO standards and existing construction safety planning guidelines. The development of this conceptual framework is part of a research proposal that is being formulated to develop a process protocol for integrating process of construction quality, safety, health and sustainability management systems in infrastructure projects. This process protocol can simplify the complexity and overlapping of the processes of each management system so that it is easier to understand and to implement by all project stakeholders.

Adhesive damage of class V restorations under shrinkage stress and occlusal forces using cohesive zone modeling.

This study aims to investigate adhesive damage caused by the synergistic effects of polymerization shrinkage and occlusal forces via finite element analysis (FEA), based on damage mechanics with the cohesive zone model (CZM). The objective is to obtain the adhesive damage distribution and investigate how the material properties of resin composite impact adhesive damage. A 3D reconstruction model of an mandibular first molar was constructed through CBCT imaging, and a Class V cavity was prepared using computer-aided engineering (CAE) software. Common clinical resin composite and an universal adhesive were selected for restorative filling. A 3D FEA was performed, incorporating the pre-stress induced by polymerization shrinkage of the resin composite, followed by occlusal forces. The cohesive zone model (CZM) was employed to represent the adhesive damage. To emphasize the impact of synergistic loading on adhesive damage, three types of loads were separately applied to the model: polymerization shrinkage, occlusal forces, and combined loading. Subsequently, three clinical resin composites with varying polymerization shrinkage and elastic modulus were used as restorative materials. Sensitivity analysis was conducted on dozens of hypothetical materials to provide definitive results. Polymerization shrinkage was undergone by the cured resin composite, resulting in extensive adhesive damage. Occlusal forces induced microdamage in regions already damaged by shrinkage stress, especially in the gingival wall. Predictably, the regions with severe adhesive damage were prone to marginal microleakage. The properties of the resin composite can affect adhesive damage. The adhesive damage with bulk-fill resin composite was milder than that with flowable and conventional resin composite. The extent of adhesive damage correlated markedly positively with the polymerization shrinkage of the resin composite and mildly positively with its elastic modulus. Adhesive damage has been directly implicated in marginal microleakage. The cohesive zone model (CZM) can effectively elucidate the distribution of adhesive damage and provide a clear representation of the impact of varying material properties of resin composite on adhesive damage.

PENYELESAIAN HUKUM TERHADAP PELAKU KECELAKAAN LALU LINTAS

Law Number 22 of 2009 concerning Road Traffic and Transportation, specifically Article 310 paragraph (4), states that accidents causing the death of a person due to the negligence of the perpetrator can result in criminal sanctions. This article specifies that anyone who, due to their negligence, causes a traffic accident that results in the death of another person can be sentenced to a maximum of 6 (six) years in prison and/or a fine of up to IDR 12,000,000.00 (twelve million rupiah). The method used is sociological legal research. Based on the research findings, it is known that the rights of the perpetrator and the victim in a traffic accident include that the perpetrator has the right to be treated in accordance with applicable legal principles, including the right to legal defense, the right to fair treatment in legal proceedings, and the right to amend their wrongdoing through rehabilitation or mediation if necessary. On the other hand, the victim of a traffic accident also has the right to compensation for the losses they have suffered, including medical expenses, property damage, and other losses. These rights must be guaranteed and fulfilled with full responsibility by the parties involved, whether the perpetrator, law enforcement officials, or other relevant parties. Legal resolution of traffic accident perpetrators based on Law Number 22 of 2009 concerning Road Traffic and Transportation in the jurisdiction of Polresta Pekanbaru indicates that this law provides a clear framework regarding the procedures for law enforcement against traffic accident perpetrators. The law emphasizes that perpetrators who violate traffic regulations and cause accidents must be held accountable for their actions. The legal process is expected not only to focus on imposing sanctions but also to provide space for the perpetrators to correct their mistakes through appropriate mechanisms, such as fines, imprisonment, or administrative sanctions.

Human-Animal Conflict in Jaimini Municipality, Baglung, Nepal

This study examines the factors that lead to conflict between people and animals in the Jaimini Municipality of Baglung Nepal with an emphasis on how shifting economic conditions impact livestock and agriculture. In terms of agricultural loss livestock depredation and human causation this study sought to explore the conflict between humans and wildlife. It also aims to comprehend local perspectives tolerance and compensation levels as well as the causes of losses brought by wild animals. Both qualitative and quantitative methods were employed in the study including focus groups semi-structured interviews, questionnaire, surveys and case studies. The findings indicated that the most significant harm caused by human animal conflict (HAC) was crop damage with animal attacks on settlements being more common in areas near forests. There was no discernible difference in the amount of damage caused by elephants to various socioeconomic classes making property damage the second most frequent problem encountered by the locals. The results imply that since humans want to rule over and take advantage of nature and animals they are to blame for the conflict. Anger and negativity are common reactions from victims of animal abuse. Problems with migration dependency and brain drain have resulted from the conflicts detrimental effects on the livelihoods of the local population. The study evaluated stakeholders' capacity to reduce human-wildlife conflicts which are mostly caused by mishandling community forests and problems with their applications. Policymakers practitioners, researchers can benefit from its insights into the intricate relationships between people animal's migration and social transformation.

The Feasibility of RCA Treatments Utilised in Asphalt Mixtures to Enhance their Properties and Performance: Narrative Review

Recycled concrete aggregates (RCA) can be utilised instead of virgin aggregates to produce hot asphalt mixtures. This contributes to solving the difficulty of construction waste disposal and mitigates the supply-demand dilemma associated with implementing the sustainability strategy. Nevertheless, the presence of cement mortar in the recycled concrete aggregate leads to changes in its mechanical and physical characteristics, posing a major challenge. Therefore, researchers investigated methods to mitigate the harm caused by this cement mortar through various treatments. This paper offers a narrative review of the feasibility of employing several treatments or techniques on recycled concrete aggregates to enhance the susceptibility of asphalt mixtures to fatigue, water damage, permanent deformation, and Marshall properties. Several treatments have been discussed, such as heating, coating, mechanical treatment, immersing RCA in chemical solutions, and the composite method. This review concludes that mechanical treatment is the most practical and effective, making it the most likely to succeed in practical application.

Вопросы уголовно-правовой оценки нарушения требований промышленной безопасности опасных производственных объектов при причинении крупного ущерба

The relevance of the study of issues related to damage caused by accidents and incidents at hazardous pro-duction facilities is due to the fact that such cases, as a rule, are diverse and have varying degrees of conse-quences, which are most often expressed not only in causing harm to humans, but also in property and envi-ronmental damage. These consequences only seem insignificant at first glance, but in reality everything is dif-ferent. The degree of damage and the amount of damage caused may depend on the specific type of object, its scale, etc. This article analyzes the issues of defining the concept of industrial safety of hazardous produc-tion facilities, provides recommendations for its refinement; provides examples of real consequences resulting from violations of industrial safety requirements of hazardous production facilities; examines the issues of as-sessing the consequences of violations of industrial safety requirements of hazardous production facilities and criminal law reactions to such consequences, as well as the delineation of administrative offenses from crimes; The level of latency of crimes and the causes of its occurrence is assessed. In the final part of the study, rec-ommendations are proposed for finalizing sectoral legislation and bringing it into line with criminal legislation, criteria for differentiating crimes and offenses by main and additional signs are presented.

Machine Learning-Based Ground Peak Acceleration Attenuation Prediction Model

ABSTRACT For earthquake mitigation and disaster management, it is important to rapidly predict modified Mercalli intensity (MMI) attenuation patterns across the entire earthquake-affected area. The quick prediction of hazardous areas after a destructive earthquake can effectively reduce the number of casualties and extent of property damage. Peak ground acceleration (PGA) is closely related to earthquake MMI. Traditional PGA predictions are constructed based on empirical formulas, which struggle to explain the nonlinear relation between PGA and epicentral distance. To address this issue, we propose a machine learning-based PGA attenuation model. We utilized seismic data from the Japan K-NET and KiK-net networks collected during 2000–2023 to construct a dataset and applied three different models to fit the data. The best-fit model was selected based on the performance results of these models. Using this model, three earthquake events with MJMA >6 in 2023 were predicted to evaluate potentially hazardous areas resulting from earthquakes. The results indicated that the model could effectively predict potentially hazardous areas and rapidly generate seismic MMI maps after an earthquake. Additionally, the machine learning model successfully addressed the nonlinear relation between PGA and epicentral distance.

SOCIAL FACTORS INFLUENCING SUBSTANCE ABUSE AMONG UNDERGRADUATES OF TAI SOLARIN UNIVERSITY OF EDUCATION IJAGUN, OGUN STATE, NIGERIA.

Substance abuse has long been a significant challenge in public health, persisting throughout history. There is a growing concern over the escalating use of substances among undergraduate students, posing serious threats to societies worldwide. This trend not only jeopardizes physical health but also undermines social and ethical standards. Substance abuse among undergraduates leads to property damage within educational institutions and diminishes the prospects of academic success of students. In examining the social factors influencing substance abuse among undergraduates at Tai Solarin University of Education in Ijagun, Ogun State, a descriptive survey research design was employed. The study utilized a simple random sampling technique to select a sample of eight hundred (800) undergraduates. The researcher designed a questionnaire with a reliability coefficient of 0.78 to investigate substance abuse among undergraduates, employing statistical tools such as frequency counts, percentages, and chi-square tests at a significance level of 0.05. The analysis resulted in the rejection of all three hypotheses. The study identified peer pressure, substance availability, and advertisements as significant contributors to substance abuse among undergraduates. Consequently, the study recommends mandatory medical testing for substance abuse across all undergraduate levels and advocates for active involvement of health educators in educating students, including integration of substance abuse topics into General Studies (GNS) courses. Keywords: Peer Pressure, Substance Abuse, Undergraduates.

Modelling Potential Candidates for Targeted Auger Therapy

Targeted Auger emitters are being considered as a cancer treatment owing to the high linear energy transfer of Auger electrons. When targeted to cancers, this allows for a highly efficient treatment with a low risk of damage to surrounding healthy tissue. The purpose of this study was to determine the most DNA-damaging Auger emitters from a range of radionuclides, some of which are clinically utilised. A Monte Carlo method-based software (Geant4-DNA version 10.7) was used to determine the energy deposition and number of DNA double-strand breaks from Auger (and internal conversion) electrons imposed on a tetranucleosome. The Auger emitters, 119Sb and 103Pd, have similar or slightly greater damaging properties compared to 123I, 111In, and 89Zr. 193mPt demonstrated the greatest therapeutic potency. Whilst 125I was highly damaging, its relatively long half-life (60 days) makes it less desirable for clinical use. Geant4-DNA modelling identified the radionuclide 193mPt as being highly favourable for use in radiotherapy.

Outcome of IWGT workshop on transcriptomic biomarkers for genotoxicity: Key considerations for bioinformatics.

As a part of the International Workshop on Genotoxicity Testing (IWGT) in 2022, a workgroup was formed to evaluate the level of validation and regulatory acceptance of transcriptomic biomarkers that identify genotoxic substances. Several such biomarkers have been developed using various molecular techniques and computational approaches. Within the IWGT workgroup on transcriptomic biomarkers, bioinformatics was a central topic of discussion, focusing on the current approaches used to process the underlying molecular data to distill a reliable predictive signal; that is, a gene set that is indicative of genotoxicity and can then be used in later studies to predict potential DNA damaging properties for uncharacterized chemicals. While early studies used microarray data, a technological shift occurred in the past decade to incorporate modern transcriptome measuring techniques such as high-throughput transcriptomics, which in turn is based on high-throughput sequencing. Herein, we present the workgroup's review of the current bioinformatic approaches to identify genes comprising transcriptomic biomarkers. Within the context of regulatory toxicology, the reproducibility of a given analysis is critical. Therefore, the workgroup provides consensus recommendations on how to facilitate sufficient reporting of experimental parameters for the analytical procedures used in a transcriptomic biomarker study, including the recommendation to develop a biomarker-specific reporting module within the OECD Omics Reporting Framework.

Experimental Study of Material Proportioning for Similar Modeling of Brittle Rocks

Over the past 30 years, China has emerged as the country with the world’s largest engineering construction industry. However, rockbursts induced by tunnel excavation in rock engineering have resulted in a substantial number of casualties and extensive property damage. Understanding the brittle failure behavior of rock masses and identifying the mechanism of rockbursts have become critical challenges in the field. Physical model tests can provide a more intuitive simulation of the rockburst process. The selection and proportioning of materials similar to brittle rocks are crucial factors for the success of these model tests. This study selected refined iron powder, barite powder, quartz sand, gypsum powder, and a rosin–alcohol solution to prepare rockburst simulation materials characterized by a low strength and high brittleness. The rockburst tendency and brittleness indices were introduced, and an orthogonal experimental design was used to establish 25 different formulation schemes. The influence of the material component proportions on the physical and mechanical properties of the specimens, as well as their brittleness characteristics, was systematically analyzed. A multiple linear regression analysis was conducted to derive linear regression equations for the physical and mechanical parameters of the brittle rock simulation materials. In addition, simulation materials and standard specimens of Jinping marble were prepared. The brittle failure modes and acoustic emission characteristics of the specimens under uniaxial compression and Brazilian splitting conditions were analyzed. The results indicate that component proportions significantly affected the physical and mechanical properties of the specimens. The refined iron powder–barite powder ratio, as well as the concentration of the rosin–alcohol solution, played a primary role in controlling the physical and mechanical parameters of the brittle rock simulation materials.

Safety Climate and Safety Leadership Influence on Safety Performance in East Kalimantan Heavy Equipment Employees

Background: Maintaining and repairing heavy machinery in coal mines included significant danger and may result in mishaps. Even with management's best efforts to provide acceptable employment, policies, practices, infrastructure, and safety gear, property damage and small injury occurrences nevertheless happen. Objective: Examine how safety leadership and the safety environment affect employees of East Kalimantan heavy equipment companies' performance in terms of safety. Method: A questionnaire was utilized in the study to gather data from 65 respondents who were chosen by simple random selection. Results: The safety climate is positively and significantly impacted by safety leadership, according to path analysis (path coef = 0.962). Safety performance is positively and significantly impacted by safety leadership and climate (path coef = 0.562 and 0.415, respectively). With safety climate acting as a mediator, safety leadership may influence safety performance (path coef= 0.3992). Conclusion: Safety leadership and safety climate can be antecedents for the safety performance of East Kalimantan heavy equipment company employees. Companies need to strengthen safety leadership by ensuring leaders practice safety principles, as well as creating a safety climate that is conducive to increasing employee safety commitment.

Prepare for the worst: Make evacuation plans accessible

The 2024 hurricane season had more than its fair share of hurricanes, tornadoes, and tropical storms. Hurricanes Beryl, Debby, Ernesto, Helene, and Milton caused tens of billions of dollars in property damage, including damage to college and university campuses, plus hundreds of deaths. These hurricanes, as well as other natural disasters, serve as a reminder for postsecondary institutions to engage in emergency planning.

The Impact of Tidal Floods on Poor Households in the Sayung Coast, Demak Regency, Indonesia

The Sayung coast is an area subject to the direct influence of coastal disasters, particularly tidal floods. Tis research aimed to investigate the impact of tidal floods on social and economic aspects in Sayung Subdistrict. In order to achieve the aim, data collection was conducted through a systematic process comprising structured interviews carried out using a questionnaire. The research also implemented a random sampling methodology, comprising a total of 23 informants and in-depth interviews were conducted with key informants to augment its comprehensiveness. Following this, the data processing and analysis followed a mixed-method approach where quantitative and qualitative data were analyzed using the Structural Equation Model (SEM) and grounded theory. The obtained results showed that tidal floods had a significant direct impact is able to influence physical health, employment, and property at 62.32%, 69.59% and and 65.43% respectively. Furthermore indirect impact property is able to influence property value by 62.78%, physical health, property damages and employment can influence mental health by 71.71% and physical health, employment can affect mobility by 66.89%. The finding accounts for a new insight that tidal floods have direct and indirect impacts on the community, as examined using the mixed-method approach. The study of tidal flood impacts on poor households in Sayung Coastal, Demak, offers different findings from previous ones. Some previous studies discuss the general effects of tidal floods while disregarding the framework of the direct and indirect impacts of the floods on poor households

Human Remains Detection in Natural Disasters using YOLO: A Deep Learning Approach

Natural catastrophes are defined as events whose precise location and timing are unexpected. Natural disasters can cause property damage and death. The NDRF has to coordinate rapid evacuation to help victims of natural disasters minimize their losses. In reality, the evacuation process is rather challenging. The journey begins with tackling challenging terrain and ends with equipment limitations. Most studies focus on classifying various types of disasters, estimating the amount of damage incurred during a disaster, and identifying victims in post-disaster situations. Many studies use image processing to locate victims in vulnerable locations. This study aims to establish a system for identifying human bodies after natural disasters to assist NDRF teams and volunteers find bodies in hard-to-reach areas. The You Only Look Once (YOLO) method is used in conjunction with artificial intelligence's computer vision algorithms and the Python programming language to effectively detect human bodies with an accuracy of 96%.

Navigating the storm: How can insurers better prepare for the impact of climate change

Climate change is forever changing the risk environment for insurers and their customers. A recent example of this is the intense storm witnessed by the people of Bahrain and around the region on the eve of 16th April, 2024. There were minimal preparations made by either insurers or their customers, resulting in severe disruptions to daily life and property damage. To mitigate this, insurers need risk management programmes that move beyond traditional solutions to deal with climate change. These risk management solutions must be varied to cover all aspects of an insurance operation and provide customer value. Solutions can be focused on changing policy cover terms, new product development, altered investment strategies, use of technology and innovation, and engagement with the public. There are challenges, however, such as the availability and credibility of data, affordability and social equity, uncertain regulations and rising costs. Yet, the consequences of not acting on climate change will be higher for insurers eventually.

Understanding Decadal-Scale Dynamics in the Bering Sea: Investigating Trends and Variability in Sea Ice, Winds, and Waves

Abstract Despite the societal and economic importance of the Bering Sea, recent rapid changes in surface ocean conditions are not well documented. We address this gap by characterizing the Bering Sea winter ice–wind–wave climate using satellite observations and reanalysis data. Nine of the last 10 years (2014–23) have experienced anomalously low sea ice extent relative to the 1980–2023 mean. Between 2003 and 2023, gale force wind speeds have become more common and satellite altimeter observations show significant wave height (SWH) has increased ≥6 m, and has increased by 1 m between 2003 and 2023, while 20 days yr−1 exhibit SWH > 9 m. Winters between 2018 and 2023 were the six stormiest since 2003, and the sea ice season decreases by 1–4 days yr−1. Should ice loss in the Bering Sea continue to decline, we hypothesize that the frequency of extreme waves over the Bering Sea shelf would increase, severely impacting coastal communities. In September 2022, extratropical cyclone Merbok caused unprecedented SWH (>15 m) over the shelf which were uncharacteristic for the season, and caused widespread coastal inundation and property damage. Such anomalous wave conditions exemplify the emerging threat storms pose in a future where sea ice is absent more frequently in winter, when severe storms are most common. Satellite altimeters have improved the observation of surface ocean conditions in the Bering Sea during the most intense storms, and we demonstrate that a suite of five or more altimeters is required to capture regional events adequately. Significance Statement Although the Bering Sea region has recently endured rapid sea ice loss and the decline of several species important for subsistence and commercial fishing, it has relatively few resources to monitor and mitigate changing climatic conditions. In this article, we show that extreme wind and wave conditions in the Bering Sea have strongly increased in recent years, as sea ice has declined. This points to a need for reliable and continued monitoring, and with only two wave buoys providing year-round observations, an adequate constellation of ocean remote sensing instruments is required to capture extreme ocean–ice–atmosphere events in an isolated and challenging environment.

The Relationship of Safety Knowledge and Safety Skills with Safety Behavior in Chemical Manufacturing Companies

Work accidents that occur in the workplace can harm workers and companies both materially and non-materially and temporarily or permanently. Workplace accidents are unwanted events that can cause physical injury to a person even fatal to death or lifelong disability and property damage. The main cause of accidents in the workplace is due to a lack of knowledge, skills and other factors from within the individual who will eventually tend to behave unsafely at work. This study is quantitative research with research type observational analytical research with a cross-sectional design. This study employed a total population sampling method, including all 35 participants from X Company and residents of the Z Plant area, conducted during March to April 2024. Data were collected through questionnaires and interviews. Spearman correlation analysis was used to assess the strength of the relationship. The results showed that the strong relationship between knowledge (r = 0.377) with safety behavior was in the low category. While the strong relationship between skills (r = 0.470) with safety behavior is in the medium category.