Sources Of Risk Research Articles

Physicochemical, Antimicrobial Properties and Mineral Content of Several Commercially Available Honey Samples

Ensuring food safety and protecting consumers are major aspects for commercialized products. Honey, the most prominent in the class of bee products, requires special regulations due to its origin as a natural product. Mislabeling, imitation, and adulteration represent a source of risks for human health. Specific determinations and analyses are essential for controlling the sector and preventing unfair competition. To compare and establish the correct labeling of several different honeys, melissopalynological, physicochemical, mineral content, and microbiological analyses were carried out on 18 samples commercially available in different countries, namely Türkiye, Romania, Bulgaria, and Northern Cyprus. The honey labels were in accordance with the determined pollen content. The physiochemical parameters showed high variability: 4.07–5.25 (pH), 79.95–83.45 (°Brix), 0.262–1.452 µS/cm (electrical conductivity), and 14.6–18.4% (moisture). The samples were quantitatively high in K, P, Na, and Ca, with the highest cumulative mineral content being found for honeys containing Fagaceae pollen. Additionally, the antimicrobial potential of the various honey samples was evaluated against selected bacteria, employing the disk diffusion and serial dilution methods. Results revealed that the honey samples exhibited increased antibacterial activity against Gram-negative bacteria, with notable activity against S. typhimurium, and moderate activity against Gram-positive S. aureus.

Contamination, fraction, and source apportionment of heavy metals in sediment of an industrialized urban river in China

In this study, we conducted an analysis of the heavy metal concentrations, health risk assessment, fraction and source interpretation in surface and core sediments from main stream of the Pearl River and Pearl River Estuary (RRE) area. Results showed that the higher deposited heavy metal concentrations in sediments occur at the Pearl River. The concentrations of heavy metals in surface sediments from the studied locations are in a descending order: Zn > Cr > Cu > Ni > Pb > Cd. Regarding chemical fractions, Cd showed the highest proportion of acid soluble fraction (F1) among all studied heavy metals. The high mobility of Cd poses a significant threat to water bodies and the surrounding environment. The potential ecological risk index (RI) showed the Pearl River sediments exhibited significantly higher values than the estuary sediments. Cd was found to be the primary contributor to potential ecological risk, accounting for 74% of RI. The health risk assessment showed the total hazard index (HI) for child was exceeded 1 mainly driven by Zn, indicating that the child population was at risk of non-carcinogenic effects. Besides, unacceptable carcinogenic risk in both Pearl River and estuary area were observed for children. The positive matrix factorization (PMF) model was used to ascertain sources of six heavy metals and apportion their contributions in sediments. The results showed that the source contributions of natural, industrial, and mixed sources from coal combustion and traffic emissions accounted for 39.81%, 34.10%, 26.10%.

Assessment of Risk Factors Associated with and Practices of Cattle Farmers in Kirehe District Rwanda with Respect to Vector-Borne and Zoonotic Pathogens.

Rural Rwandan communities face health challenges for humans and animals, and the topography and climate of the Kirehe District of Rwanda put farmers at high risk for mosquito-borne diseases. Individuals from 92 Rwandan farms were surveyed about farm practices, as well as animal and human health histories between December 2017 and February 2018. Human, animal, and environmental factors were investigated to determine whether there is a pattern of risk for abortion incidence and/or history of malarial disease on the farm. Iterative, complementary logistic regression models were used to determine whether there was an association between variables and abortion history in animals. These factors were then used to investigate association with a reported history of malaria. Of the 92 farms in our study, 82 were family farms and 10 were commercial farms. On average, 88% of the farms had cattle, and 30% of farms had experienced a cattle abortion in the past 2 years. There was no observed statistical significance in the risk factors for history of abortion in cattle and the measured variables. Using One Health as a guiding framework, we sought to determine whether human, animal, and environmental factors were statistically associated with observed disease outcomes. From our study of the practices of the farmers with respect to biosafety and self-protection against disease, we have identified potential sources of risk that could be targeted to enhance education and protection on these farms.

Rural-urban Migration and Overweight Status in Low- and Middle-income Countries: Evidence from Longitudinal Data in Indonesia

With rapid urbanization and intensive rural-urban migration, being overweight has become an increasingly common source of health risks in low- and middle-income countries (LMICs). However, the impact of rural-urban migration on overweight status is understudied in the LMIC context. Previous studies primarily used cross-sectional data, failing to adjust for migration health selection. Furthermore, the potential gender pattern in the impact of rural-urban migration remained unclear, and the potential cumulative effect of the duration of urban residence among migrants was rarely examined with longitudinal data. Meanwhile, the mediating effects of health behavioral factors were poorly understood. Using data from the fourth and fifth waves of the Indonesia Family Life Survey (IFLS) and employing fixed-effects (FE) models (N=7267), this study provided new evidence on the impact of rural-urban migration on overweight status across time and gender. Findings suggest that rural-urban migration significantly and positively predicted being overweight, and the association was significantly stronger among women than men. The results also show that years lived in urban areas did not significantly predict overweight among migrants, and that mediating health-related behaviors did little to explain adverse weight outcomes of migrants. As the number of rural-urban migrants continues growing, LMIC governments should implement health interventions aiming for healthy weight status among migrant communities. Meanwhile, gender-specific programs targeting women should be considered. Future research should explore other potential mediators of the link between rural-urban migration and overweight.

Particulate matter in necropsy activities: experience from a health operators’ exposure monitoring campaign

BackgroundOperators in the obituary and necropsy sectors are exposed to various environmental hazards during specific tasks. Despite this exposure, occupational risks have often been underestimated, resulting in a lack of substantial evidence. The primary objectives of this study were to identify sources of chemical risk, establish procedures for monitoring and quantifying exposure during necropsy activities, and recommend adjustments to regulatory guidelines to protect the health of the operators. The study was conducted at the Legal Medicine Unit of the Umberto I General Hospital in Rome, focusing on the quantitative measurement of particulate matter (PM) exposure among at-risk operators during necropsy activities. Environmental levels of total suspended particles, PM10, PM4, PM2.5, and PM1 were assessed by evaluating the average, minimum, and maximum instantaneous indoor concentrations using an airborne analyzer.ResultsThe monitoring activities revealed that the PM concentrations were significantly lower than the recognized reference values. However, bone sawing, body removal, and cleaning were identified as high-risk maneuvers for dust suspension.ConclusionsOur study highlighted specific risks associated with necropsy activities, particularly concerning timing and certain maneuvers. These results may lead to interventions for improving current prevention procedures, implementing good practices, and developing specific guidelines to enhance operator safety.

Managing workplace AI risks and the future of work.

Artificial intelligence (AI)-the field of computer science that designs machines to perform tasks that typically require human intelligence-has seen rapid advances in the development of foundation systems such as large language models. In the workplace, the adoption of AI technologies can result in a broad range of hazards and risks to workers, as illustrated by the recent growth in industrial robotics and algorithmic management. Sources of risk from deployment of AI technologies across society and in the workplace have led to numerous government and private sector guidelines that propose principles governing the design and use of trustworthy and ethical AI. As AI capabilities become integrated in devices, machines, and systems across industry sectors, employers, workers, and occupational safety and health practitioners will be challenged to manage AI risks to worker health, safety, and well-being. Five risk management options are presented as ways to assure that only trustworthy and ethical AI enables workplace devices, machinery, and processes. AI technologies will play a significant role in the future of work. The occupational safety and health practice and research communities need to ensure that the promise of these new AI technologies results in benefit, not harm, to workers.

Contaminant of Emerging Concerns in Modder River Catchment of Free State: Implication for Environmental Risk and Water Sources Protection

This study was aimed at monitoring the occurrence and potential sources of emerging contaminants in water sources within the Modder River catchment. Selected water quality indicators were analysed by Hanna multi-parameter meters. Emerging contaminants such as acetaminophen, carbamazepine, ibuprofen, atrazine, simazine, metolachlor, terbuthylazine, 17-alpha-ethinyl-estradiol, estradiol, progesterone, and testosterone were analysed by high performance liquid chromatography mass spectrometry. The sources of emerging contaminants were determined by statistical methods such as Pearson correlation and hierarchical cluster analysis. Results showed that all the sampled water sources have some level of questionable drinking water quality and necessitate some amount of treatment to reduce the contamination before consumption, especially DO, EC, and pH. The 17-alpha-ethinyl-estradiol mean values in rivers (7.79 and 31.55 µg/L), dams (1.83 and 6.90 µg/L), and treated drinking water (0.2 and 0.73 µg/L) were the highest in summer and autumn seasons, respectively. Wastewater effluents, domestic sewage, urban surface runoff, agricultural runoff, and illegal dumping were identified as the possible sources of emerging contaminants pollution. Waste management education, proper application of herbicides, and advance wastewater treatment methods were some of the suggested mitigation strategies. The outcomes may be relevant for environmental protection and water sustainability in the catchment.

Managing Cybersecurity: Digital Footprint Threats

Abstract Managing cybersecurity and protecting data assets remain top priorities for businesses. Despite this, numerous data breaches persist due to malicious human actions, resulting in significant financial setbacks. However, many cybersecurity strategies overlook invisible or indirect threats within their scope, such as digital footprints. This paper examines the relationship between personality traits and user behavior concerning cybersecurity. The study suggests that human personality can be predicted using innovative techniques based on the digital hints individuals leave on the internet. Consequently, this information can be exploited for malicious actions against entities. As proposed, an effective strategy for improving behaviors and cultivating a security-oriented culture involves continually identifying relevant sources of cyber risks and implementing continuous awareness initiatives.

The risk and return of equity and credit index options

We develop a structural credit risk model, which allows us to price equity/credit indices and their options through the asset dynamics of index constituents. We estimate the model via MLE and find that equity and credit index option prices are well explained out-of-sample. Contrary to recent empirical findings, the two option markets are not inconsistently priced through the lens of our model. Returns on both options, while extreme, do not indicate any evidence of mispricing. Our analysis suggests that jointly addressing the pricing of various instruments requires properly attributing three different sources of systematic risk: asset, variance, and jump risks.

Detection of Road Risk Sources Based on Multi-Scale Lightweight Networks.

Timely discovery and disposal of road risk sources constitute the cornerstone of road operation safety. Presently, the detection of road risk sources frequently relies on manual inspections via inspection vehicles, a process that is both inefficient and time-consuming. To tackle this challenge, this paper introduces a novel automated approach for detecting road risk sources, termed the multi-scale lightweight network (MSLN). This method primarily focuses on identifying road surfaces, potholes, and scattered objects. To mitigate the influence of real-world factors such as noise and uneven brightness on test results, pavement images were carefully collected. Initially, the collected images underwent grayscale processing. Subsequently, the median filtering algorithm was employed to filter out noise interference. Furthermore, adaptive histogram equalization techniques were utilized to enhance the visibility of cracks and the road background. Following these preprocessing steps, the MSLN model was deployed for the detection of road risk sources. Addressing the challenges associated with two-stage network models, such as prolonged training and testing times, as well as deployment difficulties, this study adopted the lightweight feature extraction network MobileNetV2. Additionally, transfer learning was incorporated to elevate the model's training efficiency. Moreover, this paper established a mapping relationship model that transitions from the world coordinate system to the pixel coordinate system. This model enables the calculation of risk source dimensions based on detection outcomes. Experimental results reveal that the MSLN model exhibits a notably faster convergence rate. This enhanced convergence not only boosts training speed but also elevates the precision of risk source detection. Furthermore, the proposed mapping relationship coordinate transformation model proves highly effective in determining the scale of risk sources.

Exploring the sources of systemic risk and trading strategies in energy and stock markets

This study aims to investigate the impact of the energy transition on asset pricing by analyzing the different sources of systemic risk in a comprehensive system of one traditional energy ETF, one clean energy ETF, seven oil-exporting country ETFs, and six oil-importing country ETFs. We find that shocks to the traditional (clean) energy market are the primary source of short-term (long-term) systemic risk, suggesting that oil-dependent countries have started to incorporate the long-term risks associated with clean energy into the pricing of related assets. Meanwhile, we document both homogeneity within and heterogeneity between oil exporters and oil importers in the transmission patterns of systemic risk. These findings can help provide customized trading strategies for investors with diverse profiles. Additionally, we compare the regime-dependent hedging strategy with both the regime-dependent diversification strategy and the dynamic hedging strategy, demonstrating that it is the most effective for investors aiming to minimize portfolio volatility. Collectively, our results provide valuable insights that can assist policymakers, portfolio managers, and investors in adapting to the evolving dynamics of the energy transition.

Research on Construction Risk Assessment of Long-Span Cantilever Casting Concrete Arch Bridges Based on Triangular Fuzzy Theory and Bayesian Networks

Considering the complex construction processes involved, there are significant risks during the construction of long-span cantilever casting arch bridges. In this study, a risk assessment method for the construction process of cantilever casting concrete arch bridges was developed. The compositional elements and characteristics of safety risks in the construction of cantilever casting concrete arch bridges were clarified, and a safety risk source list that includes seven major risk sources and thirty-three minor risk sources was formed. Then, a Bayesian model for the risk analysis of cantilever casting concrete arch bridge construction was established, and a method was proposed to determine the prior and posterior probabilities of the Bayesian network using triangular fuzzy numbers. This method fully utilizes the experience of experts while avoiding the subjectivity of expert opinions. A cantilever casting concrete open spandrel arch bridge (Bridge A) with a total span length of 287 m was taken as an example, and a safety risk assessment was conducted during its construction process. The calculation results show that the construction safety risk level of Bridge A was level III. This engineering application verified the feasibility of determining key node parameters of the Bayesian network using triangular fuzzy numbers.

Applying the "SOTEC" framework of sociotechnical risk analysis to the development of an autonomous robot swarm for a public cloakroom.

The past decade has seen efforts to develop new forms of autonomous systems with varying applications in different domains, from underwater search and rescue to clinical diagnosis. All of these applications require risk analyses, but such analyses often focus on technical sources of risk without acknowledging its wider systemic and organizational dimensions. In this article, we illustrate this deficit and a way of redressing it by offering a more systematic analysis of the sociotechnical sources of risk in an autonomous system. To this end, the article explores the development, deployment, and operation of an autonomous robot swarm for use in a public cloakroom in light of Macrae's structural, organizational, technological, epistemic, and cultural framework of sociotechnical risk. We argue that this framework provides a useful tool for capturing the complex "nontechnical" dimensions of risk in this domain that might otherwise be overlooked in the more conventional risk analyses that inform regulation and policymaking.

Which pollutants and sources should be prioritized for control in multi-pollutants complex contaminated areas?

Risk assessment and source identification of multi-pollutants are essential for accurate control of soil contamination. However, complexity in pollutant properties and diversity in source types raise challenges to the target. Therefore, this study constructed a hierarchical ecological risk quantification method combined with risk ranking, risk of single pollutant using potential affected fraction (PAF), and joint risk of multi-pollutants employing msPAF. Taking regional contamination in South China as a case, the risk ranking was determined, while single and joint effects showed msPAF reaching 79.4 %, with risk as heavy metals (HMs) > per- and polyfluoroalkyl substances (PFASs) > polycyclic aromatic hydrocarbons (PAHs). Meanwhile, an integrated source apportionment method was established from three layers by principal component analysis to classify source types, multiple linear regression of distance to identify key sources, and positive matrix factorization to track omitted sources. Consequently, key sources were captured, with 80.8 %−93.2 % contribution of farmland and electroplating to three main HMs, 52.2 %−69.4 % contribution of roads to three main PAHs, and 71.1 %−73.2 % contribution of electroplating to two main PFASs. Further, omitted sources were tracked with contribution of 31.2 %−84.1 % to eight pollutants. The established methods can identify control targets, including high-risk pollutants and their key sources.

Heavy metal's pollution health risk assessment and source appraisal of groundwater and surface water in Irob catchment, Tigray, Northern Ethiopia

Contamination of water resources by heavy metals causes health problems for humans. This study attempts to investigate the heavy metal contamination levels, health risks and sources of appraisal of groundwater and surface water in the mountain-bounded catchment and low-grade basement rock-dominated area of ​​the Irob, Tigray. Eighteen grab water samples (13 borehole water, 2 spring water and 3 surface water) were collected and analyzed for pH, electrical conductivity, total dissolved solids and heavy metals using standard procedures. The findings were contrasted with those of the standards set by the World Health Organization and the United States Environmental Protection Agency. Integrated techniques, including indexed and statistical methods, were used to determine the contamination levels of metals, risks to human health and sources. The result shows that the pH value, electrical conductivity and total dissolved solids fluctuated between 7.4 and 7.9, 516 and 2410 µs/cm and 396.7 mg/l and 1719 mg/l, respectively. The findings indicate that 94.4% of the water samples had levels of contamination above the critical limit for all three indices: the heavy metal evaluation index (HEI), the degree of contamination (cd) and the heavy metal pollution index. The hazard index of metals for adults and children was greater than 1. 88.9% of the water samples showed a cancer risk value above the recommended value (CR > 1 × 10–4) for Cd and Cr for both adults and children. Multivariate statistical analyses indicate that weathering of bedrocks and partly anthropogenic influences are responsible for the metal contamination. The study concludes that some water samples sources are unfit for human consumption that can pose health risks over time. Therefore, it is recommended to treat contaminated water sources to protect and sustain public health.

Extreme spillovers across carbon and energy markets: A multiscale higher-order moment analysis

The complexity of carbon market mechanisms and the uncertainty in market conditions raise questions on how carbon and energy markets interact. The majority of existing studies focused on the lower-order moment spillover across carbon and energy markets, thereby posing limitations on carbon risk management and carbon market efficiency. This paper analyzes multiscale skewness and kurtosis spillovers across carbon and energy markets under different market conditions. It is found that carbon market is a short-term net skewness spillover receiver, but becomes a medium-term risk source under all market conditions, capable of transmitting skewness risk to the natural gas market. The carbon market acts as a short- and medium-term kurtosis risk source for the natural gas and electricity markets in the lower probability of extreme returns, but bears the kurtosis risk from the natural gas and coal markets when the extreme risk is high. These results indicate that policymakers should take measures to adjust carbon prices when facing long-term skewness risk and a lower probability of extreme returns in the carbon market, to prevent further spread of risk to the energy markets.

An unconventional FX tail risk story

We examine how the tail risk of currency returns over the past 20 years were impacted by central bank monetary and liquidity measures across the globe with an original and unique dataset that we make publicly available. Using a standard factor model, we derive theoretical measures of tail risks of currency returns which we then relate to the various policy instruments employed by central banks. We find empirical evidence for the existence of a cross-border transmission channel of central bank policy through the FX market. The tail impact is particularly sizeable for asset purchases and swap lines. The effects last for up to 1 month, and are proportionally higher for joint QE actions. This cross-border source of tail risk is largely undiversifiable, even after controlling for the U.S. dollar dominance and the effects of its own monetary policy stance.

The futility of economic sanctions in a globalized and interdependent world: a data-driven game theoretical study

Economic openness and globalization are under rising pressure from the proliferation of economic sanctions over the past decades. Data-driven evidence is urgently needed to inform the heated debates about the effectiveness of various sanctions and counter-sanction measures. In this research, we provide a game theoretical framework to model the interplays between the sanction sender and target at different stages of political conflicts. Using real-world international trade data, our game-theoretical framework assesses each country’s capability of and vulnerability to economic sanctions and quantifies the feasibility and effectiveness of different counter-sanction measures. Our findings suggest that expanded international trade creates the potential to weaponize economic interdependence for giant economies, imbalanced trade relationships with which is the main source of sanction risk for vulnerable economies. Complete decoupling from these highly capable countries is a costly and ineffective strategy to combat economic sanctions. Bloc-type collective retaliation against the common adversary can be effective under certain scenarios but provides little benefit for major contributors in the bloc, making it impractical in addressing real-world conflicts. Promoting cooperation and dialogue is the ultimate solution to maintaining economic and political stability and security.

Risk spillover effect of the new energy market and its hedging effectiveness: New evidence from industry chain

During China’s industrial transformation, studying risk spillover effects and clarifying risk contagion pathways within the new energy industry chain is critical for promoting high-quality development in the new energy. The risk transmission mechanism of the new energy industry chain is explored by constructing a time–frequency index using a time-varying parameter vector autoregressive model in this paper. Additionally, we also further analyze the portfolio and hedging effectiveness of the new energy market. The findings reveal that, first, the downstream market serves as the primary risk source, propagating risk through the industry chain to the midstream and upstream sectors within the new energy industry chain contagion system. Second, the risk spillover effect of the new energy market has significant heterogeneity and time-varying due to the impact of short-term frequency domain drivers and extreme events. Third, the portfolio significantly reduces the investment risk of a single asset. With the extension of the investment horizon, investors’ portfolio weights in the upstream, midstream and downstream industries gradually tend to be even.

Risk assessment and source analysis of trace elements in soils around county landfills in Tibet.

The ecology of the Qinghai‒Tibet Plateau is fragile, and the ecosystems in the region are difficult to remediate once damaged. Currently, landfilling is the mainstay of domestic waste disposal in China, and numerous, widely distributed county landfills exist. trace elements (TEs) in waste are gradually released with waste degradation and cannot be degraded in nature, affecting environmental quality and human health. To reduce the chance bias that exists in studies of individual landfills, we selected 11 representative county landfills in Tibet, total of 76 soil samples were collected, eight TEs (arsenic (As), mercury (Hg), chromium (Cr), copper (Cu), lead (Pb), cadmium (Cd), nickel (Ni), and zinc (Zn)) were determined, and analysed for the current status of pollution, risk to human health, and sources of TEs to explore the impact of the landfills. The results showed that only a few landfills had individual TEs exceeding the risk screening value of the Soil Environmental Quality Risk Control Standard for Soil Contamination (GB 15618-2018) (pH > 7.5). Most of the soils around the landfills had moderate levels of pollution, but some individual landfills had higher levels, mainly due to Cd and Hg concentrations. Source analysis showed that Hg originated mainly from atmospheric transport; the other TEs came mainly from the weathering of soil parent material and bedrock. The potential risk from TEs to human health was low, and the risk to children was greater than the risk to adults. Among the three exposure routes, oral ingestion resulted in the highest carcinogenic risk and noncarcinogenic risk, with a contribution rate of more than 95%. Among the TEs, Ni had the highest carcinogenic risk, followed by Cr and As, and As had the highest noncarcinogenic risk.