Search results for: risk and return analysis

Authors: Ya-Ching Wang, Yi-Maun Subeq

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Background: There is a lack of evidence to understand differences in risk for developing breast cancer between sexual minority women and heterosexual women in Taiwan. The purpose of this study is to compare differences in risk for developing breast cancer between the two groups of Taiwanese women. Methods: An online cross-sectional survey was used to collect data. A total of 238 Taiwanese women (mean age 30.69 years old, SD=8.231, range 20-60) were recruited between December 2016 and February 2017, including 115 heterosexual women and 123 sexual minority women. Results: There were no significant differences between heterosexual women and sexual minority women in body mass index, history of non-malignant breast disease, age at menarche and menopause, use of hormone replacement therapy, use of hormone replacement therapy, nor the prevalence of breast cancer. The sexual minority women had higher rates of current drinking, smoking and using breast-bindings and also reported exercise more a week; the heterosexual women had higher rates of pregnancy, children, breastfeed, miscarriages, abortion and use of birth control pills. Discussion/Conclusion: There were significant differences between heterosexual women and sexual minority women in reproductive factors and behavioral risk factors for the development of breast cancer. In particular, the finding that the sexual minority women had higher rate of using breast-bindings (56.6%) than the heterosexual women (4.7%) should be further explore, in order to understand whether long-term breast compression is associated with the development of breast cancer.

Keywords: breast cancer, risk, sexual orientation, Taiwan

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Authors: Rino Gubiani, Gianfranco Pergher

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The work focused on the statistical analysis of accidents in the forestry sector (2000-2020) in Friuli-Venezia Giulia region, located in the North-East of Italy. The aim of the work was to analyse the evolution of the casualties throughout time and to evaluate possible improvements in the sector. It was shown that even nowadays the rate of accidents in forestry work is higher compared with all the other sectors, including agriculture; moreover, it was highlighted that some accidents remained present throughout the whole analysed range, such as slipping on the soil, being hit by trees and falling down from the plants. The results showed that an increase in forestry exploitation could even increase the total number of accidents, if advanced technological machines, such as cable cranes, would not implemented, given the fact that there is also a significant number of old people (above 50 years old) working in the sector.

Keywords: safety, forestry work, accidents, risk analysis, casualties, statistical analysis

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Authors: Marzieh Karimihaghighi, Carlos Castillo

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This work studies how Machine Learning (ML) may be used to increase the effectiveness of a criminal recidivism risk assessment tool, RisCanvi. The two key dimensions of this analysis are predictive accuracy and algorithmic fairness. ML-based prediction models obtained in this study are more accurate at predicting criminal recidivism than the manually-created formula used in RisCanvi, achieving an AUC of 0.76 and 0.73 in predicting violent and general recidivism respectively. However, the improvements are small, and it is noticed that algorithmic discrimination can easily be introduced between groups such as national vs foreigner, or young vs old. It is described how effectiveness and algorithmic fairness objectives can be balanced, applying a method in which a single error disparity in terms of generalized false positive rate is minimized, while calibration is maintained across groups. Obtained results show that this bias mitigation procedure can substantially reduce generalized false positive rate disparities across multiple groups. Based on these results, it is proposed that ML-based criminal recidivism risk prediction should not be introduced without applying algorithmic bias mitigation procedures.

Keywords: algorithmic fairness, criminal risk assessment, equalized odds, recidivism

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Authors: Athdath Waduge Susantha Janaka Kumara, Xiefei Zhi, Zin Mie Mie Sein

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Understanding the air temperature variability is crucially important for disaster risk reduction and management. In this study, we used 15 synoptic meteorological stations to assess the spatiotemporal variability of air temperature over Sri Lanka during 1972–2021. The empirical orthogonal function (EOF), Principal component analysis (PCA), Mann-Kendall test, power spectrum analysis and correlation coefficient analysis were used to investigate the long-term trends of air temperature and their possible relation to sea surface temperature (SST) over the region. The results indicate that an increasing trend in air temperature was observed with the abrupt climate change noted in the year 1994. The spatial distribution of EOF1 (63.5%) shows the positive and negative loading dipole patterns from south to northeast, while EOF2 (23.4%) explains warmer (colder) in some parts of central (south and east) areas. The power spectrum of PC1 (PC2) indicates that there is a significant period of 3-4 years (quasi-2 years). Moreover, Indian Ocean Dipole (IOD) provides a strong positive correlation with the air temperature of Sri Lanka, while the EL Nino Southern Oscillation (ENSO) presents a weak negative correlation. Therefore, IOD events led to higher temperatures in the region. This study’s findings can help disaster risk reduction and management in the country.

Keywords: air temperature, interannaul variability, ENSO, IOD

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Authors: Anna Rinaldi, Pierfrancesco Dellino

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COVID-19 vaccine hesitancy can be observed at different rates in different countries. In June 2021, 1,068 people were surveyed in France and Italy to inquire about individual potential acceptance, focusing on time preferences in a risk-return framework: having the vaccination today, in a month, and in 3 months; perceived risks of vaccination and COVID-19; and expected benefit of the vaccine. A randomized controlled trial was conducted to understand how everyday stimuli like fact-based news about vaccines impact an audience's acceptance of vaccination. The main experiment involved two groups of participants and two different articles about vaccine-related thrombosis taken from two Italian newspapers. One article used a more abstract description and language, and the other used a more anecdotal description and concrete language; each group read only one of these articles. Two other groups were assigned categorization tasks; one was asked to complete a concrete categorization task, and the other an abstract categorization task. Individual preferences for vaccination were found to be variable and unstable over time, and individual choices of accepting, refusing, or delaying could be affected by the way news is written. In order to understand these dynamic preferences, the present work proposes a new model based on seven categories of human behaviors that were validated by a neural network. A treatment effect was observed: participants who read the articles shifted to vaccine hesitancy categories more than participants assigned to other treatments and control. Furthermore, there was a significant gender effect, showing that the type of language leading to a lower hesitancy rate for men is correlated with a higher hesitancy rate for women and vice versa. This outcome should be taken into consideration for an appropriate gender-based communication campaign aimed at achieving herd immunity. The trial was registered at ClinicalTrials.gov NCT05582564 (17/10/2022).

Keywords: vaccine hesitancy, risk elicitation, neural network, covid19

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Authors: Muhammad Shehu Garba

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The financial statements of the firms between the periods of 2013 and 2022 were collected using the secondary method of data collection, and the study aims to investigate the effect of ownership structure on the financial performance of listed industrial goods companies in Nigeria. 10 firms were used as the study's sample size. The study used panel data variables of the study. The ownership structure is measured with managerial ownership, institutional ownership and foreign ownership, while financial performance is measured with return on asset and return on equity; the study made use of control variables leverage and firm size. The result shows a multivariate relationship that exists between variables of the study, which shows ROA has a positive correlation with ROE (0.4053), MO (0.2001), and FS (0.3048). It has a negative correlation with FO (-0.1933), IO (-0.0919), and LEV (-0.3367). ROE has a positive correlation with ROA (0.4053), MO (0.2001), and FS (0.2640). It has a negative correlation with FO (-0.1864), IO (-0.1847), and LEV (-0.0319). It is recommended that firms should focus on increasing their ROA. Firms should also consider increasing their MO, as this can help to align the interests of managers and shareholders. Firms should also be aware of the potential impact of FO and IO on their ROA.

Keywords: firm size, ownership structure, financial performance, leaverage

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Authors: Zhang Xingnan, Huang Jingjia, Feng Yue, Burra Venkata Durga Kumar

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This paper proposes a comprehensive approach to mitigate ROP (Return-Oriented Programming) attacks by combining internal operating system protection mechanisms and hardware-assisted techniques. Through extensive literature review, we identify the effectiveness of ASLR (Address Space Layout Randomization) and LBR (Last Branch Record) in preventing ROP attacks. We present a process involving buffer overflow detection, hardware-assisted ROP attack detection, and the use of Turing detection technology to monitor control flow behavior. We envision a specialized tool that views and analyzes the last branch record, compares control flow with a baseline, and outputs differences in natural language. This tool offers a graphical interface, facilitating the prevention and detection of ROP attacks. The proposed approach and tool provide practical solutions for enhancing software security.

Keywords: operating system, ROP attacks, returning-oriented programming attacks, ASLR, LBR, CFI, DEP, code randomization, hardware-assisted CFI

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Authors: Amiel Satvedi, Richard Pyne

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Injuries in professional sports occur on a regular basis. Some may be minor, while others can cause huge impact on a player's career and earning potential. In soccer, there is a high risk of players picking up injuries during game time. This research work seeks to help soccer players reduce the risk of getting injured by predicting the likelihood of injury while playing in the near future and then providing recommendations for intervention. The injury prediction tool will use a soccer player's number of minutes played on the field, number of appearances, distance covered and performance data for the current and previous seasons as variables to conduct statistical analysis and provide injury predictive results using a machine learning linear regression model.

Keywords: injury predictor, soccer injury prevention, machine learning in soccer, big data in soccer

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Authors: Muhammad Sheraz, Vasile Preda, Silvia Dedu

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Concepts of econophysics are usually used to solve problems related to uncertainty and nonlinear dynamics. In the theory of option pricing the risk neutral probabilities play very important role. The application of entropy in finance can be regarded as the extension of both information entropy and the probability entropy. It can be an important tool in various financial methods such as measure of risk, portfolio selection, option pricing and asset pricing. Gulko applied Entropy Pricing Theory (EPT) for pricing stock options and introduced an alternative framework of Black-Scholes model for pricing European stock option. In this article, we present solutions to maximum entropy problems based on Tsallis, Weighted-Tsallis, Kaniadakis, Weighted-Kaniadakies entropies, to obtain risk-neutral densities. We have also obtained the value of European call and put in this framework.

Keywords: option pricing, Black-Scholes model, Tsallis entropy, Kaniadakis entropy, weighted entropy, risk-neutral density

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Authors: Zahra Bahadoran, Parvin Mirmiran, Fereidoun Azizi

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Background: Higher consumption of white rice has been suggested as a risk factor for development of metabolic abnormalities. In this study we investigated the association between consumption of white rice and the 3-year occurrence of metabolic syndrome (MetS) in adults with and without abdominal obesity. Methods: This longitudinal study was conducted within the framework of the Tehran Lipid and Glucose Study on 1476 adults, aged 19-70 years. Dietary intakes were measured, using a 168-food items validated semi-quantitative food frequency questionnaire at baseline. Biochemical and anthropometric measurements were evaluated at both baseline (2006-2008) and after 3-year follow-up (2009-2011). MetS and its components were defined according to the diagnostic criteria proposed by NCEP ATP III, and the new cutoff points of waist circumference for Iranian adults. Multiple logistic regression models were used to estimate the occurrence of the MetS in each quartile of white rice consumption. Results: The mean age of participants was 37.8±12.3 y, and mean BMI was 26.0±4.5 kg/m2 at baseline. The prevalence of MetS in subjects with abdominal obesity was significantly higher (40.9 vs. 16.2%, P<0.01). There was no significant difference in white rice consumption between the two groups. Mean daily intake of white rice was 93±59, 209±58, 262±60 and 432±224 g/d, in the first to fourth quartiles of white rice, respectively. Stratified analysis by categories of waist circumference showed that higher consumption of white rice was more strongly related to the risk of metabolic syndrome in participants who had abdominal obesity (OR: 2.34, 95% CI:1.14-4.41 vs. OR:0.99, 95% CI:0.60-1.65) Conclusion: We demonstrated that higher consumption of white rice may be a risk for development of metabolic syndrome in adults with abdominal obesity.

Keywords: white rice, abdominal obesity, metabolic syndrome, food science, triglycerides

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Authors: C. Y. Ng, A. M. Johan, A. E. Kajuputra

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Wave-in-deck phenomenon for fixed jacket platforms at shallow water condition has been reported as a notable risk to the workability and reliability of the platform. Reduction in reservoir pressure, due to the extraction of hydrocarbon for an extended period of time, has caused the occurrence of seabed subsidence. Platform experiencing subsidence promotes reduction of air gaps, which eventually allows the waves to attack the bottom decks. The impact of the wave-in-deck generates additional loads to the structure and therefore increases the values of the moment arms. Higher moment arms trigger instability in terms of overturning, eventually decreases the reserve strength ratio (RSR) values of the structure. The mechanics of wave-in-decks, however, is still not well understood and have not been fully incorporated into the design codes and standards. Hence, it is necessary to revisit the current design codes and standards for platform design optimization. The aim of this study is to evaluate the effects of RSR due to wave-in-deck on four-legged jacket platforms in Malaysia. Base shear values with regards to calibration and modifications of wave characteristics were obtained using SESAM GeniE. Correspondingly, pushover analysis is conducted using USFOS to retrieve the RSR. The effects of the contributing factors i.e. the wave height, wave period and water depth with regards to the RSR and base shear values were analyzed and discussed. This research proposal is important in optimizing the design life of the existing and aging offshore structures. Outcomes of this research are expected to provide a proper evaluation of the wave-in-deck mechanics and in return contribute to the current mitigation strategies in managing the issue.

Keywords: wave-in-deck loads, wave effects, water depth, fixed jacket platforms

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Authors: Batool Ismaeel, Umair Farooq, Saad Mushtaq

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Construction projects in the oil industry can be very complex, having unknown outcomes and uncertainties that cannot be easily predicted. Each project has its unique risks generated by a number of factors which, if not controlled, will impact the successful completion of the project mainly in terms of schedule, cost, quality, and safety. This paper highlights the historic risks associated with projects in the south and east region of Kuwait Oil Company (KOC) collated from the company’s lessons learned database. Starting from Contract Award through to handover of the project to the Asset owner, the gaps in project execution in terms of managing risk will be brought to discussion and where a well-defined systematic approach in project risk management reflecting many claims, change of scope, exceeding budget, delays in engineering phase as well as in the procurement and fabrication of long lead items should be adopted. This study focuses on a proposed feasible approach in risk management for engineering, procurement and construction (EPC) level projects including the various stakeholders involved in executing the works from International to local contractors and vendors in KOC. The proposed approach covers the areas categorized into organizational, design, procurement, construction, pre-commissioning, commissioning and project management in which the risks are identified and require management and mitigation. With the effective deployment and implementation of the proposed risk management system and the consideration of it as a vital key in achieving the project’s target, the outcomes will be more predictable in the future, and the risk triggers will be managed and controlled. The correct resources can be allocated on a timely basis for the company for avoiding any unpredictable outcomes during the execution of the project. It is recommended in this paper to apply this risk management approach as an integral part of project management and investigate further in the future, the effectiveness of this proposed system for newly awarded projects and compare the same with those projects of similar budget/complexity that have not applied this approach to risk management.

Keywords: construction, project completion, risk management, uncertainties

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Authors: Farid Khosravikia, Patricia Clayton

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The main objective of this work is to evaluate the advantages and disadvantages of various machine learning techniques in two key steps of seismic hazard and risk assessment of different types of structures. The first step is the development of ground-motion models, which are used for forecasting ground-motion intensity measures (IM) given source characteristics, source-to-site distance, and local site condition for future events. IMs such as peak ground acceleration and velocity (PGA and PGV, respectively) as well as 5% damped elastic pseudospectral accelerations at different periods (PSA), are indicators of the strength of shaking at the ground surface. Typically, linear regression-based models, with pre-defined equations and coefficients, are used in ground motion prediction. However, due to the restrictions of the linear regression methods, such models may not capture more complex nonlinear behaviors that exist in the data. Thus, this study comparatively investigates potential benefits from employing other machine learning techniques as statistical method in ground motion prediction such as Artificial Neural Network, Random Forest, and Support Vector Machine. The results indicate the algorithms satisfy some physically sound characteristics such as magnitude scaling distance dependency without requiring pre-defined equations or coefficients. Moreover, it is shown that, when sufficient data is available, all the alternative algorithms tend to provide more accurate estimates compared to the conventional linear regression-based method, and particularly, Random Forest outperforms the other algorithms. However, the conventional method is a better tool when limited data is available. Second, it is investigated how machine learning techniques could be beneficial for developing probabilistic seismic demand models (PSDMs), which provide the relationship between the structural demand responses (e.g., component deformations, accelerations, internal forces, etc.) and the ground motion IMs. In the risk framework, such models are used to develop fragility curves estimating exceeding probability of damage for pre-defined limit states, and therefore, control the reliability of the predictions in the risk assessment. In this study, machine learning algorithms like artificial neural network, random forest, and support vector machine are adopted and trained on the demand parameters to derive PSDMs for them. It is observed that such models can provide more accurate estimates of prediction in relatively shorter about of time compared to conventional methods. Moreover, they can be used for sensitivity analysis of fragility curves with respect to many modeling parameters without necessarily requiring more intense numerical response-history analysis.

Keywords: artificial neural network, machine learning, random forest, seismic risk analysis, seismic hazard analysis, support vector machine

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Authors: M. Miljkovic, A. Urakpo, M. Simic-Koumoutsaris

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Benefit-risk assessment (BRA) is a valuable tool that takes place in multiple stages during a medicine's lifecycle, and this assessment can be conducted in a variety of ways. The aim was to summarize current BRA methods used during approval decisions and in post-approval settings and to see possible future directions. Relevant reviews, recommendations, and guidelines published in medical literature and through regulatory agencies over the past five years have been examined. BRA implies the review of two dimensions: the dimension of benefits (determined mainly by the therapeutic efficacy) and the dimension of risks (comprises the safety profile of a drug). Regulators, industry, and academia have developed various approaches, ranging from descriptive textual (qualitative) to decision-analytic (quantitative) models, to facilitate the BRA of medicines during the product lifecycle (from Phase I trials, to authorization procedure, post-marketing surveillance and health technology assessment for inclusion in public formularies). These approaches can be classified into the following categories: stepwise structured approaches (frameworks); measures for benefits and risks that are usually endpoint specific (metrics), simulation techniques and meta-analysis (estimation techniques), and utility survey techniques to elicit stakeholders’ preferences (utilities). All these approaches share the following two common goals: to assist this analysis and to improve the communication of decisions, but each is subject to its own specific strengths and limitations. Before using any method, its utility, complexity, the extent to which it is established, and the ease of results interpretation should be considered. Despite widespread and long-time use, BRA is subject to debate, suffers from a number of limitations, and currently is still under development. The use of formal, systematic structured approaches to BRA for regulatory decision-making and quantitative methods to support BRA during the product lifecycle is a standard practice in medicine that is subject to continuous improvement and modernization, not only in methodology but also in cooperation between organizations.

Keywords: benefit-risk assessment, benefit-risk profile, product lifecycle, quantitative methods, structured approaches

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Authors: Mohammed Nishat, Ahmad Ghazali

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This study empirically examines the corporate governance and firm performance, and tries to evaluate the governance, ownership and control related variables which are hypothesized to affect on firms performance. This study tries to evaluate the effectiveness of corporate governance mechanism to achieve high level performance among companies listed on the Karachi Stock Exchange (KSE) over the period from 2005 to 2008. To measure the firm performance level this research uses three measures of performance; Return on assets (ROA), Return on Equity (ROE) and Tobin’s Q. To link the performance of firms with the corporate governance three categories of corporate governance variables are tested which includes governance, ownership and control related variables. Fixed effect regression model is used to test the link between corporate governance and firm performance for 267 KSE listed Pakistani firms. The result shows that corporate governance variables such as percentage block holding by individuals have positive impact on firm performance. When CEO is also the chairperson of board then it is found that firm performance is adversely affected. Also negative relationship is found between share held by insiders and performance of firm. Leverage has negative impact on the performance of the firm and firm size is positively related with the firms performance.

Keywords: corporate governance, performance, agency cost, Karachi stock market

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Authors: Nayab Kanwal, Noor Us Saher

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The management and utilization of food resources is becoming a big issue due to rapid urbanization, wastage and non-sustainable use of food, especially in developing countries. Therefore, the use of seafood as alternative sources is strongly promoted worldwide. Marine pollution strongly affects marine organisms, which ultimately decreases their export quality. The monitoring of contamination in marine organisms is a good indicator of the environmental quality as well as seafood quality. Monitoring the accumulation of chemical elements within various tissues of organisms has become a useful tool to survey current or chronic levels of heavy metal exposure within an environment. In this perspective, this study was carried out to compare the previous and current levels (Year 2012 and 2014) of heavy metals (Cd, Pb, Cr, Cu and Zn) in crabs marketed in Karachi and to estimate the toxicological risk associated with their intake. The accumulation of metals in marine organisms, both essential (Cu and Zn) and toxic (Pb, Cd and Cr), natural and anthropogenic, is an actual food safety issue. Significant (p>0.05) variations in metal concentrations were found in all crab species between the two years, with most of the metals showing high accumulation in 2012. For toxicological risk assessment, EWI (Estimated weekly intake), Target Hazard quotient (THQ) and cancer risk (CR) were also assessed and high EWI, Non- cancer risk (THQ < 1) showed that there is no serious threat associated with the consumption of shellfish species on Karachi coast. The Cancer risk showed the highest risk from Cd and Pb pollution if consumed in excess. We summarize key environmental health research on health effects associated with exposure to contaminated seafood. It could be concluded that considering the Pakistan coast, these edible species may be sensitive and vulnerable to the adverse effects of environmental contaminants; more attention should be paid to the Pb and Cd metal bioaccumulation and to toxicological risks to seafood and consumers.

Keywords: cancer risk, edible crabs, heavy metals pollution, risk assessment

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Authors: Jiajia Peng, Yijun Dong, Jianjun Ren, Yu Zhao

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Objectives: Understanding the association between sleep traits and tinnitus could help prevent and provide appropriate interventions against tinnitus. Therefore, this study aimed to assess the relationship between different sleep patterns and tinnitus. Design: A cross-sectional analysis using baseline data (2006–2010, n=168,064) by logistic regressions was conducted to evaluate the association between sleep traits (including the overall health sleep score and five sleep behaviors), and the occurrence (yes/no), frequency (constant/transient), and severity (upsetting/not upsetting) of tinnitus. Further, a prospective analysis of participants without tinnitus at baseline (n=9,581) was performed, who had been followed up for seven years (2012–2019) to assess the association between new-onset tinnitus and sleep characteristics. Moreover, a subgroup analysis was also carried out to estimate the differences in sex by dividing the participants into male and female groups. A sensitivity analysis was also conducted by excluding ear-related diseases to avoid their confounding effects on tinnitus (n=102,159). Results: In the cross-sectional analysis, participants with “current tinnitus” (OR: 1.13, 95% CI: 1.04–1.22, p=0.004) had a higher risk of having a poor overall healthy sleep score and unhealthy sleep behaviors such as short sleep durations (OR: 1.09, 95% CI: 1.04–1.14, p<0.001), late chronotypes (OR: 1.09, 95% CI: 1.05–1.13, p<0.001), and sleeplessness (OR: 1.16, 95% CI: 1.11–1.22, p<0.001) than those participants who “did not have current tinnitus.” However, this trend was not obvious between “constant tinnitus” and “transient tinnitus.” When considering the severity of tinnitus, the risk of “upsetting tinnitus” was obviously higher if participants had lower overall healthy sleep scores (OR: 1.31, 95% CI: 1.13–1.53, p<0.001). Additionally, short sleep duration (OR: 1.22, 95% CI: 1.12–1.33, p<0.001), late chronotypes (OR: 1.13, 95% CI: 1.04–1.22, p=0.003), and sleeplessness (OR: 1.43, 95% CI: 1.29–1.59, p<0.001) showed positive correlations with “upsetting tinnitus.” In the prospective analysis, sleeplessness presented a consistently significant association with “upsetting tinnitus” (RR: 2.28, P=0.001). Consistent results were observed in the sex subgroup analysis, where a much more pronounced trend was identified in females compared with males. The results of the sensitivity analysis were consistent with those of the cross-sectional and prospective analyses. Conclusions: Different types of sleep disturbance may be associated with the occurrence and severity of tinnitus; therefore, precise interventions for different types of sleep disturbance, particularly sleeplessness, may help in the prevention and treatment of tinnitus.

Keywords: tinnitus, sleep, sleep behaviors, sleep disturbance

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Authors: S. M. Rashed Ul Islam, Shahina Tabassum, Afsana Anwar Miti

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Objective: HIV testing and counseling center (HTC) is an important component of the HIV/AIDS detection, prevention and control interventions. The service was first initiated at the Department of Virology, Bangabandhu Sheikh Mujib Medical University (BSMMU) since the first case detection in 1989. The present study aimed to describe the demographic profile among the attendees tested HIV positive. Methods: The present study was carried out among 219 HIV positive cases detected through screening at the Department of Virology of BSMMU during the year of 2012-2016. Data were collected through pre-structured written questionnaire during the counseling session. Data were expressed as frequency and percentages and analyzed using SPSS v20.0 program. Results: Out of 219 HIV cases detected, 77.6% were males, and 22.4% were females with a mean age (mean±SD) of 35.46±9.46 years. Among them, 70.7% belonged to the 26-45 age groups representing the sexually active age. The majority of the cases were married (86.3%) and 49.8% had primary level of education whereas, 8.7% were illiterate. Nearly 42% of cases were referred from Chittagong division (south-east part of the country) followed by Dhaka division (35.6%). The bulk of study population admitted to involvement in high-risk behaviour (90%) in the past and 42% of them had worked overseas. The Pearson Chi-square (χ2) analysis revealed significant relationship of gender with marital (χ2=7.88 at 2% level) and occupation status (χ2=120.48 at 6% level); however, no association was observed with risk behaviour and educational status. Recommendations: HIV risk behavior was found to be a prime source for HIV infection among the study population. So, there is need for health education and awareness program to bring about behavioral changes to halt the yearly increase of new cases in the country with special attention to our overseas workers on HIV/AIDS risk and safety.

Keywords: Bangladesh, health education, HIV testing and counseling (HTC), HIV/AIDS, risk behavior

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Authors: Alba Ballester Ciuró, Marc Pares Franzi

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While coming decades are likely to see a higher flood risk in Europe and greater socio-economic damages, traditional flood risk management has become inefficient. In response to that, new approaches such as capacity building and public participation have recently been incorporated in natural hazards mitigation policy (i.e. Sendai Framework for Action, Intergovernmental Panel on Climate Change reports and EU Floods Directive). By integrating capacity building and public participation, we present a research concerning the promotion of participatory social capacity building actions for flood risk mitigation at the local level. Social capacities have been defined as the resources and abilities available at individual and collective level that can be used to anticipate, respond to, cope with, recover from and adapt to external stressors. Social capacity building is understood as a process of identifying communities’ social capacities and of applying collaborative strategies to improve them. This paper presents a proposal of systematization of participatory social capacity building process for flood risk mitigation, and its implementation in a high risk of flooding area in the Ebro river basin: Ribera Alta del Ebro. To develop this process, we designed and tested a tool that allows measuring and building five types of social capacities: knowledge, motivation, networks, participation and finance. The tool implementation has allowed us to assess social capacities in the area. Upon the results of the assessment we have developed a co-decision process with stakeholders and flood risk management authorities on which participatory activities could be employed to improve social capacities for flood risk mitigation. Based on the results of this process, and focused on the weaker social capacities, we developed a set of participatory actions in the area oriented to general public and stakeholders: informative sessions on flood risk management plan and flood insurances, interpretative river descents on flood risk management (with journalists, teachers, and general public), interpretative visit to the floodplain, workshop on agricultural insurance, deliberative workshop on project funding, deliberative workshops in schools on flood risk management (playing with a flood risk model). The combination of obtaining data through a mixed-methods approach of qualitative inquiry and quantitative surveys, as well as action research through co-decision processes and pilot participatory activities, show us the significant impact of public participation on social capacity building for flood risk mitigation and contributes to the understanding of which main factors intervene in this process.

Keywords: flood risk management, public participation, risk reduction, social capacities, vulnerability assessment

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Authors: Jerry Szatko, Edan L. Jorgensen, Stacia Jorgensen

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A crucial component to the success of any financial advising relationship is for the financial professional to understand the perceptions, preferences and thought-processes carried by the financial clients they serve. Armed with this information, financial professionals are more quickly able to understand how they can tailor their approach to best match the individual preferences and needs of each personal investor. Our research explores the use of a quantitative assessment tool in the financial services industry to assist in the identification of the personal investor’s consumer behaviors, especially in terms of financial risk tolerance, as it relates to their financial decision making. Through this process, the Unitifi Consumer Insight Tool (UCIT) was created and refined to capture and categorize personal investor financial behavioral categories and the financial personality tendencies of individuals prior to the initiation of a financial advisement relationship. This paper discusses the use of this tool to place individuals in one of four behavior-based financial risk tolerance categories. Our discoveries and research were aided through administration of a web-based survey to a group of over 1,000 individuals. Our findings indicate that it is possible to use a quantitative assessment tool to assist in predicting the behavioral tendencies of personal consumers when faced with consumer financial risk and decisions.

Keywords: behavior-based advising, financial relationship building, risk capacity based on behavior, risk tolerance, systematic way to assist in financial relationship building

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Authors: Feng Wang, Shencheng Ni, Shuying Han, Shanhong You

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With the development of optical communication, optical performance monitoring (OPM) has received more and more attentions. Since optical signal-to-noise ratio (OSNR) is directly related to bit error rate (BER), it is one of the important parameters in optical networks. Recently, artificial neural network (ANN) has been greatly developed. ANN has strong learning and generalization ability. In this paper, a method of OSNR monitoring based on delay-tap sampling (DTS) and ANN has been proposed. DTS technique is used to extract the eigenvalues of the signal. Then, the eigenvalues are input into the ANN to realize the OSNR monitoring. The experiments of 10 Gb/s non-return-to-zero (NRZ) on–off keying (OOK), 20 Gb/s pulse amplitude modulation (PAM4) and 20 Gb/s return-to-zero (RZ) differential phase-shift keying (DPSK) systems are demonstrated for the OSNR monitoring based on the proposed method. The experimental results show that the range of OSNR monitoring is from 15 to 30 dB and the root-mean-square errors (RMSEs) for 10 Gb/s NRZ-OOK, 20 Gb/s PAM4 and 20 Gb/s RZ-DPSK systems are 0.36 dB, 0.45 dB and 0.48 dB respectively. The impact of chromatic dispersion (CD) on the accuracy of OSNR monitoring is also investigated in the three experimental systems mentioned above.

Keywords: artificial neural network (ANN), chromatic dispersion (CD), delay-tap sampling (DTS), optical signal-to-noise ratio (OSNR)

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Authors: N. Borjalilu, P. Rabiei, A. Enjoo

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Flight Data Monitoring (FDM) program assists an operator in aviation industries to identify, quantify, assess and address operational safety risks, in order to improve safety of flight operations. FDM is a powerful tool for an aircraft operator integrated into the operator’s Safety Management System (SMS), allowing to detect, confirm, and assess safety issues and to check the effectiveness of corrective actions, associated with human errors. This article proposes a model for safety risk assessment level of flight data in a different aspect of event focus based on fuzzy set values. It permits to evaluate the operational safety level from the point of view of flight activities. The main advantages of this method are proposed qualitative safety analysis of flight data. This research applies the opinions of the aviation experts through a number of questionnaires Related to flight data in four categories of occurrence that can take place during an accident or an incident such as: Runway Excursions (RE), Controlled Flight Into Terrain (CFIT), Mid-Air Collision (MAC), Loss of Control in Flight (LOC-I). By weighting each one (by F-TOPSIS) and applying it to the number of risks of the event, the safety risk of each related events can be obtained.

Keywords: F-topsis, fuzzy set, flight data monitoring (FDM), flight safety

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Authors: Karol Konaszewski

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Background: The article is an analysis of the results of the studies conducted among juveniles (boys and girls) in the case of whom the family court applied the educational means of placing them in the youth educational centers. The aim of the study was to find out the correlations between antisocial behaviors, personality traits and the environmental determinants (support factors and risk factors) among juveniles (boys and girls). Methods: The total of 481 juveniles staying in youth educational centers participated in the study. Applied research tools: The Antisocial Behaviors Scale by L. Pytka, NEO-FFI by P. T. Costa and R. R. McCrae was used to diagnose personality traits included in a popular five-factor model (it has been adapted into Polish by B. Zawadzki, J. Strelau, P. Szczepaniak, and M. Śliwińska) and a questionnaire concerning support factors and risk factors was constructed to measure environmental determinants. The data was analysed in a regression model. Findings: The analysis model showed that the significant predictors of antisocial behaviors were neuroticism, extraversion, conscientiousness and negative relations at school. In girls group, the significant predictors of antisocial behaviors were neuroticism, conscientiousness, family support and negative relations at school, while in boys group the significant predictors of antisocial behaviors were neuroticism, extraversion and negative relations at family. Discussion: The results of this study have important implications. They allow for a better understanding of the factors that contribute to antisocial behaviors among juveniles. Future interventions could be based on the creation of personality traits, strengthening of support factors and correction of risk factors.

Keywords: antisocial behaviours, juveniles, personality, youth

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Authors: Sharon Garyn-Tal, Shoshana Shahrabani

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Military service in general, and in combat units in particular, can be physically and psychologically stressful. Therefore, type of service may have significant implications for soldiers during and after their military service including emotions, judgments and risk perceptions. Previous studies have focused on risk propensity and risky behavior among soldiers, however there is still lack of knowledge on the impact of type of army service on risk perceptions. The current study examines the effect of type of army service (combat versus non-combat service) and negative incidental emotions on risk perceptions. In 2014 a survey was conducted among 153 combat and non-combat Israeli soldiers. The survey was distributed in train stations and central bus stations in various places in Israel among soldiers waiting for the train/bus. Participants answered questions related to the levels of incidental negative emotions they felt, to their risk perceptions (chances to be hurt by terror attack, by violent crime and by car accident), and personal details including type of army service. The data in this research is unique because military service in Israel is compulsory, so that the Israeli population serving in the army is wide and diversified. The results indicate that currently serving combat participants were more pessimistic in their risk perceptions (for all type of risks) compared to the currently serving non-combat participants. Since combat participants probably experienced severe and distressing situations during their service, they became more pessimistic regarding their probabilities of being hurt in different situations in life. This result supports the availability heuristic theory and the findings of previous studies indicating that those who directly experience distressing events tend to overestimate danger. The findings also indicate that soldiers who feel higher levels of incidental fear and anger have pessimistic risk perceptions. In addition, respondents who experienced combat army service also have pessimistic risk perceptions if they feel higher levels of fear. In addition, the findings suggest that higher levels of the incidental emotions of fear and anger are related to more pessimistic risk perceptions. These results can be explained by the compulsory army service in Israel that constitutes a focused threat to soldiers' safety during their period of service. Thus, in this stressful environment, negative incidental emotions even during routine times correlate with higher risk perceptions. In conclusion, the current study results suggest that combat army service shapes risk perceptions and the way young people control their negative incidental emotions in everyday life. Recognizing the factors affecting risk perceptions among soldiers is important for better understanding the impact of army service on young people.

Keywords: army service, combat soldiers, incidental emotions, risk perceptions

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Authors: Jing Zhang

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Sustainable development in the new energy vehicles field is the requirement of the net zero aim. Green bonds are accepted as a practical financial tool to boost the transformation of relevant enterprises. The paper analyzes the interactions among governments, enterprises of new energy vehicles, and financial institutions by an evolutionary game theory model and offers advice to stakeholders in China. The decision-making subjects of green behavior are affected by experiences, interests, perception ability, and risk preference, so it is difficult for them to be completely rational. Based on the bounded rationality hypothesis, this paper applies prospect theory in the evolutionary game analysis framework and analyses the costs of government regulation of enterprises adopting green bonds. The influence of the perceived value of revenue prospect and the probability and risk transfer coefficient of the government's active regulation on the decision-making agent's strategy is verified by numerical simulation. Finally, according to the research conclusions, policy suggestions are given to promote green bonds.

Keywords: green bonds, new energy vehicles, sustainable development, evolutionary Game Theory model

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Authors: Azazhu Wassie

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This study tried to analyze the impact of the hydrologic and hydraulic parameters (catchment area, rainfall intensity, and runoff coefficient) on the referenced study area. The study was conducted in June 2023. The Aremenie River Dam has 30 years of record, which is reasonably sufficient data. It is a matter of common experience that, due to the failure of an instrument or the absence of a gauged river, the rainfall record at quite a number of stations is incomplete. From the analysis, the 50-year return period design flood is 62.685 m³/s at 1.2 hr peak time. This implies that for this watershed, the peak flood rate per km² area of the watershed is about this value, which ensures that high rainfall in the area can generate a higher rate of runoff per km² of the generating catchment. The Aremenie Rivers carry a large amount of sediment along with water. These sediments are deposited in the reservoir upstream of the dam because of the reduction in velocity. Sediment reduces the available capacity of the reservoir with continuous sedimentation; the useful life of the reservoir goes on decreasing.

Keywords: dam design, peak flood, rainfall, reservoir capacity, runoff

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Authors: M. C. Arcuri, L. Gai, F. Ielasi

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Italian Central Guarantee Fund (CGF) has the purpose to facilitate Small and Medium-sized Enterprises (SMEs)’ access to credit. The aim of the paper is to study the evaluation method adopted by the CGF with regard to SMEs requiring its intervention. This is even more important in the light of the recent CGF reform. We analyse an initial sample of more than 500.000 guarantees from 2012 to 2018. We distinguish between a counter-guarantee delivered to a mutual guarantee institution and a guarantee directly delivered to a bank. We investigate the impact of variables related to the operations and the SMEs on Altman Z’’-score and the score consistent with CGF methodology. We verify that the type of intervention affects the scores and the initial condition changes with the new assessment criterions. 

Keywords: banks, default risk, Italian guarantee fund, mutual guarantee institutions

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Authors: Midiya Khademi, Ali Nikoo, Shabnam Rahimnezhad Baghche Jooghi

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Cardiovascular diseases (CVDs) are the main cause of death globally. Most CVDs can be prevented by avoiding habitual risk factors. Separate from the habitual risk factors, there are some inherent factors in each individual that can increase the risk potential of CVDs. Vessel shapes and geometry are influential factors, having great impact on the blood flow and the hemodynamic behavior of the vessels. In the present study, the influence of bifurcation angle on blood flow characteristics is studied. In order to approach this topic, by simplifying the details of the bifurcation, three models with angles 30°, 45°, and 60° were created, then by using CFD analysis, the response of these models for stable flow and pulsatile flow was studied. In the conducted simulation in order to eliminate the influence of other geometrical factors, only the angle of the bifurcation was changed and other parameters remained constant during the research. Simulations are conducted under dynamic and stable condition. In the stable flow simulation, a steady velocity of 0.17 m/s at the inlet plug was maintained and in dynamic simulations, a typical LAD flow waveform is implemented. The results show that the bifurcation angle has an influence on the maximum speed of the flow. In the stable flow condition, increasing the angle lead to decrease the maximum flow velocity. In the dynamic flow simulations, increasing the bifurcation angle lead to an increase in the maximum velocity. Since blood flow has pulsatile characteristics, using a uniform velocity during the simulations can lead to a discrepancy between the actual results and the calculated results.

Keywords: coronary artery, cardiovascular disease, bifurcation, atherosclerosis, CFD, artery wall shear stress

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Authors: Anders Troedsson

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For us humans, risks are intimately linked to human vulnerabilities - where there is vulnerability, there is potentially insecurity, and risk. Reducing vulnerability through compensatory measures means increasing security and decreasing risk. The paper suggests that a meaningful way to approach the study of risks (including threats, assaults, crisis etc.), is to understand the vulnerabilities these external phenomena evoke in humans. As is argued, the basis of risk evaluation, as well as responses, is the more or less subjective perception by the individual person, or a group of persons, exposed to the external event or phenomena in question. This will be determined primarily by the vulnerability or vulnerabilities that the external factor are perceived to evoke. In this way, risk perception is primarily an inward dynamic, rather than an outward one. Therefore, a route towards an understanding of the perception of risks, is a closer scrutiny of the vulnerabilities which they can evoke, thereby approaching an understanding of what in the paper is called the essence of risk (including threat, assault etc.), or that which a certain perceived risk means to an individual or group of individuals. As a necessary basis for gauging the wide spectrum of potential risks and their meaning, the paper proposes a model of human vulnerabilities, drawing from i.a. a long tradition of needs theory. In order to account for the subjectivity factor, which mediates between the innate vulnerabilities on the one hand, and the event or phenomenon out there on the other hand, an ensuing ontological discussion about the timespace characteristics of risk/threat/assault as perceived by humans leads to the positing of two dimensions. These two dimensions are applied on the vulnerabilities, resulting in a modelling effort featuring four realms of vulnerabilities which are related to each other and together represent a dynamic whole. In approaching the problem of risk perception, the paper thus defines the relevant realms of vulnerabilities, depicting them as a dynamic whole. With reference to a substantial body of literature and a growing international policy trend since the 1990s, this model is put in the language of human security - a concept relevant not only for international security studies and policy, but also for other academic disciplines and spheres of human endeavor.

Keywords: human security, timespace, vulnerabilities, risk perception

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Authors: Marcus Bellett-Travers

Abstract:

Different modelling approaches have been used to determine or predict yield of crops in different geographies. Central to the methodologies are the presumption that it is the absolute yield of the crop in a given location that is of the highest priority to those requiring information on crop productivity. Most individuals, companies and organisations within the agri-food sector need to be able to balance the supply of crops with the demand for them. Different modelling approaches have been used to determine and predict crop yield. The growing need to ensure certainty of supply and stability of prices requires an approach that describes the risk in producing a crop. A review of current methodologies to evaluate the risk to food production from changes in the weather and climate is presented.

Keywords: crop production, risk, climate, modelling

Procedia PDF Downloads 371