Search results for: risk estimation

Authors: Raquel Balon Quintana

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This study aims to help the Students-At-Risk of Dropping Out to finish their studies in their grade/year level category for this school year by finding out students’ behavior in and out the school, community involvement in the learning process and the causes or reasons behind drop-out rate that affect the performance level of the school. This study also looked for the intervention measures to reduce the drop-out rate of the school. The Normative Survey Method of research was used to achieve its purpose and objective of conducting interview with students and their parents, subject teachers, classmates and friends; undertaking observation and monitoring to find out the whereabouts of SARDO’s on and off classes hours; using questionnaires; and conducting home visitation to be able to link the community involvement into dropping-out of student. Results of the study revealed that out of 32 Students-At-Risk of Dropping Out, 50% were over age for high school (16 years old to 21 years old) while the other 50% came from the regular high school students. These 16 students came from the 41 students who dropped-out from their classes last school year. All Students-At-Risk of Dropping-Out are single and seventy-eight percent of them are male. Top five (5) among the factors that affect their school performance were peer pressure, self-drive, malnutrition, family problem/support and truancy. The five (5) least factors that affect their schooling were problems within their community, school-administration factor, harassment, teacher factor and distance from the school.

Keywords: students-at-risk of dropping-out, drop-out rate, Leocadio Alejo Entienza High School, Philippines

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Authors: Bassey Odiong Akan

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In recent decades potentially significant changes have taken place in the world of work and these have led to the emergence of new challenges in occupational safety and health. The working environment is now not only wroth with concerns about physical, biological and chemical risks but also emerging risks which are completely new risks that have never been seen before or previously known risks that are evolving in unexpected ways with unanticipated consequences. Psychosocial risk factors and its attendant hazards happen to be one of them and can impact health directly or indirectly, mediated by work-related stress. These risks are related to the way work is designed, organised and managed, as well as the economic and social contexts of work. It has become necessary to identify, explore and anticipate the dynamics of these risks factors and hazards with regards to how it affects women. This presentation is a review of information gathered from books of distinguished authors, research work and scientific/professional journals on the psychosocial work environment intended as a guide to stimulate discussion, raise awareness and encourage research and action at different levels.

Keywords: emerging risks, psychosocial hazards, psychosocial risk factors, work related stress

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Authors: Retno A. Vinarti, Lucy M. Hederman

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This research describes a knowledge model for a system which give personalized alert to users about infectious disease risks in the context of weather, location and time. The knowledge model is based on established epidemiological concepts augmented by information gleaned from infection-related data repositories. The existing disease risk prediction research has more focuses on utilizing raw historical data and yield seasonal patterns of infectious disease risk emergence. This research incorporates both data and epidemiological concepts gathered from Atlas of Human Infectious Disease (AHID) and Centre of Disease Control (CDC) as basic reasoning of infectious disease risk prediction. Using CommonKADS methodology, the disease risk prediction task is an assignment synthetic task, starting from knowledge identification through specification, refinement to implementation. First, knowledge is gathered from AHID primarily from the epidemiology and risk group chapters for each infectious disease. The result of this stage is five major elements (Person, Infectious Disease, Weather, Location and Time) and their properties. At the knowledge specification stage, the initial tree model of each element and detailed relationships are produced. This research also includes a validation step as part of knowledge refinement: on the basis that the best model is formed using the most common features, Frequency-based Selection (FBS) is applied. The portion of the Infectious Disease risk model relating to Person comes out strongest, with Location next, and Weather weaker. For Person attribute, Age is the strongest, Activity and Habits are moderate, and Blood type is weakest. At the Location attribute, General category (e.g. continents, region, country, and island) results much stronger than Specific category (i.e. terrain feature). For Weather attribute, Less Precise category (i.e. season) comes out stronger than Precise category (i.e. exact temperature or humidity interval). However, given that some infectious diseases are significantly more serious than others, a frequency based metric may not be appropriate. Future work will incorporate epidemiological measurements of disease seriousness (e.g. odds ratio, hazard ratio and fatality rate) into the validation metrics. This research is limited to modelling existing knowledge about epidemiology and chain of infection concepts. Further step, verification in knowledge refinement stage, might cause some minor changes on the shape of tree.

Keywords: epidemiology, knowledge modelling, infectious disease, prediction, risk

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Authors: Mohammad Anwar, Shah Waliullah

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This study investigated panel data regression models. This paper used Bayesian and classical methods to study the impact of institutions on economic growth from data (1990-2014), especially in developing countries. Under the classical and Bayesian methodology, the two-panel data models were estimated, which are common effects and fixed effects. For the Bayesian approach, the prior information is used in this paper, and normal gamma prior is used for the panel data models. The analysis was done through WinBUGS14 software. The estimated results of the study showed that panel data models are valid models in Bayesian methodology. In the Bayesian approach, the effects of all independent variables were positively and significantly affected by the dependent variables. Based on the standard errors of all models, we must say that the fixed effect model is the best model in the Bayesian estimation of panel data models. Also, it was proved that the fixed effect model has the lowest value of standard error, as compared to other models.

Keywords: Bayesian approach, common effect, fixed effect, random effect, Dynamic Random Effect Model

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Authors: Sie Long Kek, Wah June Leong, Kok Lay Teo

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Linear quadratic Gaussian model is a standard mathematical model for the stochastic optimal control problem. The combination of the linear quadratic estimation and the linear quadratic regulator allows the state estimation and the optimal control policy to be designed separately. This is known as the separation principle. In this paper, an efficient computational method is proposed to solve the linear quadratic Gaussian problem. In our approach, the Hamiltonian function is defined, and the necessary conditions are derived. In addition to this, the output error is defined and the least-square optimization problem is introduced. By determining the first-order necessary condition, the gradient of the sum squares of output error is established. On this point of view, the stochastic approximation approach is employed such that the optimal control policy is updated. Within a given tolerance, the iteration procedure would be stopped and the optimal solution of the linear-quadratic Gaussian problem is obtained. For illustration, an example of the linear-quadratic Gaussian problem is studied. The result shows the efficiency of the approach proposed. In conclusion, the applicability of the approach proposed for solving the linear quadratic Gaussian problem is highly demonstrated.

Keywords: iteration procedure, least squares solution, linear quadratic Gaussian, output error, stochastic approximation

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Authors: Lamis Naddaf, Yuval Tabach

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We identified missense genetic variants with the potential to enhance resistance against cancer. Such a field has not been widely explored as researchers tend to investigate the mutations that cause diseases, in response to the suffering of patients, rather than those mutations that protect from them. In conjunction with the genomic revolution and the advances in genetic engineering and synthetic biology, identifying the protective variants will increase the power of genotype-phenotype predictions and have significant implications for improved risk estimation, diagnostics, prognosis, and even personalized therapy and drug discovery. To approach our goal, we systematically investigated the sites of the coding genomes and selected the alleles that showed a correlation with the species’ cancer resistance. Interestingly, we found several amino acids that are more generally preferred (like the Proline) or avoided (like the Cysteine) by the resistant species. Furthermore, Cancer resistance in mammals and reptiles is significantly predicted by the number of the predicted protecting variants (PVs) a species has. Moreover, PVs-enriched-genes are enriched in pathways relevant to tumor suppression. For example, they are enriched in the Hedgehog signaling and silencing pathways, which its improper activation is associated with the most common form of cancer malignancy. We also showed that the PVs are mostly more abundant in healthy people compared to cancer patients within different human races.

Keywords: cancer resistance, protecting variant, naked mole rat, comparative genomics

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Authors: Jingwen Shi, Qi Wu

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We study the role played interest rate risk in carry trade return in order to understand the forward premium puzzle. In this study, our goal is to investigate to what extent carry trade return is indeed due to compensation for risk taking and, more important, to reveal the nature of these risks. Using option data not only on exchange rates but also on interest rate swaps (swaptions), our first finding is that, besides the consensus currency risks, interest rate risks also contribute a non-negligible portion to the carry trade return. What strikes us is our second finding. We find that large downside risks of future exchange rate movements are, in fact, priced significantly in option market on interest rates. The role played by interest rate risk differs structurally from the currency risk. There is a unique premium associated with interest rate risk, though seemingly small in size, which compensates the tail risks, the left tail to be precise. On the technical front, our study relies on accurately retrieving implied distributions from currency options and interest rate swaptions simultaneously, especially the tail components of the two. For this purpose, our major modeling work is to build a new international asset pricing model where we use an orthogonal setup for pricing kernels and specify non-Gaussian dynamics in order to capture three sets of option skew accurately and consistently across currency options and interest rate swaptions, domestic and foreign, within one model. Our results open a door for studying forward premium anomaly through implied information from interest rate derivative market.

Keywords: carry trade, forward premium anomaly, FX option, interest rate swaption, implied volatility skew, uncovered interest rate parity

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Authors: Daniella Hirwa

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Attention Deficit Hyperactivity Disorder (ADHD) is associated with several risk-taking behaviors, including drug use and smoking. Such risk-taking behaviors are often a result of an attempt to self-manage symptoms associated with ADHD. The present review investigates the effects of nicotine on symptoms associated with ADHD. This systematic literature review was conducted for 2017-2024 using keywords associated with ADHD, smoking, and nicotine. The results indicate that individuals with ADHD start smoking earlier than those without ADHD, and it is believed that this prevalence and the higher rates of smoking are due to improvements in cognitive and executive function, attention, and impulsivity due to the effect that nicotine has on dopamine release. Longitudinal studies with larger sample sizes and comprehensive health history and cognitive testing are required to gain more insight into the ways that nicotine affects ADHD symptoms and the context by which smoking is used as a method of self-treatment to help aid the development of nicotine-based treatment options that do not pose the same health risks as smoking.

Keywords: ADHD, nicotine, risk-taking behaviors, smoking

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Authors: Jinseon Song, Yongwan Park

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In this paper, propose method that can user’s position that based on database is built from single camera. Previous positioning calculate distance by arrival-time of signal like GPS (Global Positioning System), RF(Radio Frequency). However, these previous method have weakness because these have large error range according to signal interference. Method for solution estimate position by camera sensor. But, signal camera is difficult to obtain relative position data and stereo camera is difficult to provide real-time position data because of a lot of image data, too. First of all, in this research we build image database at space that able to provide positioning service with single camera. Next, we judge similarity through image matching of database image and transmission image from user. Finally, we decide position of user through position of most similar database image. For verification of propose method, we experiment at real-environment like indoor and outdoor. Propose method is wide positioning range and this method can verify not only position of user but also direction.

Keywords: positioning, distance, camera, features, SURF(Speed-Up Robust Features), database, estimation

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Authors: Kartik Thakore, Anna-Roza Tamas, Adam Cole

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The world health organization (WHO) reports that by 2030 more than 23.7 million deaths annually will be caused by Cardiovascular Diseases (CVDs); with a 2008 economic impact of $3.76 T. Metabolic syndrome is a disorder of multiple metabolic risk factors strongly indicated in the development of cardiovascular diseases. Guided lifestyle intervention driven by live coaching has been shown to have a positive impact on metabolic risk factors. Individuals’ path to improved (decreased) metabolic risk factors are driven by personal motivation and personalized messages delivered by coaches and augmented by technology. Using interactions captured between 400 individuals and 3 coaches over a program period of 500 days, a preliminary model was designed. A novel real time event tracking system was created to track and classify clients based on their genetic profile, baseline questionnaires and usage of a mobile application with live coaching sessions. Classification of clients and coaches was done using a support vector machines application build on Apache Spark, Stanford Natural Language Processing Library (SNLPL) and decision-modeling.

Keywords: guided lifestyle intervention, metabolic risk factors, personal coaching, support vector machines application, Apache Spark, natural language processing

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Authors: J. K. Visser, H. T. Malan

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A need exists to identify the sources of risks associated with the process automation systems within petrochemical companies or similar energy related industries. These companies use many different process automation technologies in its value chain. A crucial part of the process automation system is the information technology component featuring in the supervisory control layer. The ever-changing technology within the process automation layers and the rate at which it advances pose a risk to safe and predictable automation system performance. The age of the automation equipment also provides challenges to the operations and maintenance managers of the plant due to obsolescence and unavailability of spare parts. The main objective of this research was to determine the risk sources associated with the equipment that is part of the process automation systems. A secondary objective was to establish whether technology managers and technicians were aware of the risks and share the same viewpoint on the importance of the risks associated with automation systems. A conceptual model for risk sources of automation systems was formulated from models and frameworks in literature. This model comprised six categories of risk which forms the basis for identifying specific risks. This model was used to develop a questionnaire that was sent to 172 instrument technicians and technology managers in the company to obtain primary data. 75 completed and useful responses were received. These responses were analyzed statistically to determine the highest risk sources and to determine whether there was difference in opinion between technology managers and technicians. The most important risks that were revealed in this study are: 1) the lack of skilled technicians, 2) integration capability of third-party system software, 3) reliability of the process automation hardware, 4) excessive costs pertaining to performing maintenance and migrations on process automation systems, and 5) requirements of having third-party communication interfacing compatibility as well as real-time communication networks.

Keywords: distributed control system, identification of risks, information technology, process automation system

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Authors: Kathryn McMillan

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A recent study of 8500 adult Australians aged 16 and over revealed 62% had experienced childhood maltreatment. In response to multiple recommendations by bodies such as the Australian Law Reform Commission, parliamentary reports and stakeholder input, a number of key initiatives have been developed to grapple with the difficulties of a federal-state system and to screen and triage high-risk families navigating their way through the court system. The Lighthouse Project (LHP) is a world-first initiative of the Federal Circuit and Family Courts in Australia (FCFOCA) to screen family law litigants for major risk factors, including family violence, child abuse, alcohol or substance abuse and mental ill-health at the point of filing in all applications that seek parenting orders. It commenced on 7 December 2020 on a pilot basis but has now been expanded to 15 registries across the country. A specialist risk screen, Family DOORS, Triage has been developed – focused on improving the safety and wellbeing of families involved in the family law system safety planning and service referral, and ¬ differentiated case management based on risk level, with the Evatt List specifically designed to manage the highest risk cases. Early signs are that this approach is meeting the needs of families with multiple risks moving through the Court system. Before the LHP, there was no data available about the prevalence of risk factors experienced by litigants entering the family courts and it was often assumed that it was the litigation process that was fueling family violence and other risks such as suicidality. Data from the 2022 FCFCOA annual report indicated that in parenting proceedings, 70% alleged a child had been or was at risk of abuse, 80% alleged a party had experienced Family Violence, 74 % of children had been exposed to Family Violence, 53% alleged through substance misuse by party children had caused or was at risk of causing harm to children and 58% of matters allege mental health issues of a party had caused or placed a child at risk of harm. Those figures reveal the significant overlap between child protection and family violence, both of which are under the responsibility of state and territory governments. Since 2020, a further key initiative has been the co-location of child protection and police officials amongst a number of registries of the FCFOCA. The ability to access in a time-effective way details of family violence or child protection orders, weapons licenses, criminal convictions or proceedings is key to managing issues across the state and federal divide. It ensures a more cohesive and effective response to family law, family violence and child protection systems.

Keywords: child protection, family violence, parenting, risk screening, triage.

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Authors: Maggie Hui

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Risk management is not a new concept; however, it is an uncharted area as applied to the translation process and translator training. Serving as one of the self-discovery activities in their practicum course, a two-cycle experiment was carried out with a class of 13 MA translation students with an attempt to explore their risk management while translating in a simulated setting that involves translator-client relations. To test the effects of the main variable of translators’ interaction with the simulated clients, the researcher employed control-group translators and two experiment groups (with Group A being the translator in Cycle 1 and the client in Cycle 2, and Group B on the client position in Cycle 1 and the translator position in Cycle 2). Experiment cycle 1 aims to explore if there would be any behavioral difference in risk management between translators with interaction with the simulated clients, i.e. experiment group A, and their counterparts without such interaction, i.e. control group. Design of Cycle 2 concerns the order of playing different roles of the translator and client in the experiment, and provides information to compare behavior of translators of the two experiment groups. Since this is process-oriented research, it is necessary to hypothesize what was happening in the translators’ minds. The researcher made use of a user-friendly screen-voice recording freeware to record subjects’ screen activities, including every word the translator typed and every change they made to the rendition, the websites they browsed and the reference tools they used, in addition to the verbalization of their thoughts throughout the process. The research observes the translation procedures subjects considered and finally adopted, and looks into the justifications for their procedures, in order to interpret their risk management. The qualitative and quantitative results of this study have some implications for translator training: (a) the experience of being a client seems to reinforce the translator’s risk aversion; (b) the use of role-playing simulation can empower students’ learning by enhancing their attitudinal or psycho-physiological competence, interpersonal competence and strategic competence; and (c) the screen-voice recordings serve as a helpful tool for learners to reflect on their rendition processes, i.e. what they performed satisfactorily and unsatisfactorily while translating and what they could do for improvement in future translation tasks.

Keywords: risk management, screen-voice recordings, simulated translator-client relations, translation pedagogy, translation process-oriented research

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Authors: Michael Ajide Oyinloye

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The natural environment is made up of air, water and soil. The release of emission of industrial waste into anyone of the components of the environment causes pollution. Industrial pollution significantly threatens the inherent right of people, to the enjoyment of a safe and secure environment. The aim of this paper is to assess the effect of environmental pollution and health risks of residents living near Ewekoro Cement factory. The research made use of IKONOS imagery for Geographical Information System (GIS) to buffer and extract buildings that are less than 1 km to the plant, within 1 km to 5 km and above 5 km to the factory. Also, a questionnaire was used to elicit information on the socio-economic factors, the effect of environmental pollution on residents and measures adopted to control industrial pollution on the residents. Findings show that most buildings that between less than 1 km and 1 km to 5 km to the factory have high health risk in the study area. The study recommended total relocation for the residents of the study area to reduce risk health problems.

Keywords: environmental pollution, health risk, GIS, satellite imagery, ewekoro

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Authors: Jin-Hong Kim

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Roles of the vegetation to mitigate the erosion of the stream bed or to facilitate the deposition of the fine sediments by the species of the aquatic plants were presented. Field investigation on the estimation of the change of the bed level and the estimation of the flow characteristics were performed. The results showed that Phragmites japonica has the mitigation function of 0.3m-0.4m of the erosion in the range of higher than 1.0m/s of flow velocity at the vegetated region. Phragmites communis has the mitigation function of 0.2m-0.3m of the erosion in the range of higher than 0.7m/s of flow velocity at the vegetated region. Salix gracilistyla has greater role than Phragmites japonica and Phragmites communis to sustain the stable channel. It has the mitigation function of 0.4m-0.5m of the erosion in the range of higher than 1.4m/s of flow velocity. Miscanthus sacchariflorus has a weak role compared with that of Phragmites japonica and Salix gracilistyla, but it has still function for sustaining the stable bed. From these results, the vegetation has effective roles to mitigate the erosion or to facilitate the deposition of the stream bed.

Keywords: aquatic plants, Phragmites japonica, Phragmites communis, Salix gracilistyla

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Authors: Nevila Bardhi, Joanna Magda, Kolapo Alex-Oni, Slavenka Sedlar, Paromita Hore

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The New York City Department of Health and Mental Hygiene (NYC DOHMH) receives blood lead test results for NYC residents and conducts lead poisoning case investigations for individuals with elevated blood lead levels exposed to lead occupationally and non-occupationally. To (1) improve participant engagement, (2) aid the identification of potential lead sources, and (3) better tailor recommendations to reduce lead exposure, Motivational Interviewing (MI) techniques were incorporated during risk assessment interviews of non-pregnant adults by DOHMH’s Adult Lead Poisoning Prevention (ALP) Program. MI is an evidence-based counselling method used in clinical settings that have been effective in promoting behavior change by resolving ambivalence and enhancing motivation in treating both physiological and psychological health conditions. The incorporation of MI techniques in the ALP risk assessment interview was effective in improving the identification of lead sources for non-pregnant adult cases, thus, allowing for the opportunity to better tailor lead poisoning prevention recommendations. The embedding of MI cues in the ALP risk assessment interview also significantly increased engagement in the interview process, resulting in approximately 50 more interviews conducted per year and a decrease in interview refusals during case investigations. Additionally, the pre-MI interview completion rate was 57%, while the post-MI Interview completion rate was 68%. We recommend MI techniques to be used by other lead poisoning prevention programs during lead poisoning investigations in similar diverse populations.

Keywords: lead poisoning prevention, motivational interviewing, behavior change, lead poisoning risk factors, self-efficacy

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Authors: Ram Sharan Mehta, Dina Khanal, Pushpa Parajuli, Gayanand Mandal, Bijaya Bartuala

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Background: Cardiovascular disease (CVD) is the leading cause of death worldwide. Adequate awareness of risk factors of CVD is the first step towards effective preventive strategies to combat the CVD burden in diabetes patients.This study aims to assess the awareness on risk factors of CVD among patients with diabetes mellitus attending diabetic clinic of BPKIHS and to find the association between awareness with their selected socio demographic variables. Methods and Material: A descriptive cross sectional study was conducted among 112 patients with diabetes in diabetic clinic of BPKIHS. Convenient sampling technique was used for data collection over duration of one month using interview schedule by HDFQ II tool. Data were analyzed by using descriptive and inferential statistics. (Chi square). Results: The mean age of respondents was 55.4±12.13 years. That mean HDFQ score was 14.31± 5.08. Only 33% of the respondents had adequate level of awareness whereas majority of the respondents (67%) had inadequate level of awareness. Majority of the respondent (83.9%) were aware about smoking, (78.6%) physical activity, (75%) increasing age, (75.9%) high blood pressure, (71.4%) overweight respectively. Whereas most of the respondents were not aware of high cholesterol, fatty diet, preventive strategies and association of diabetes with CVD. Awareness was statistically significant with (p=0.043) educational status, (p=0.025) monthly income, (p=0.05) residence, (p=0.006) CVD information received and (p=0.022) co morbid condition as a heart disease. Conclusion: The findings of this study concluded most of the respondents had an inadequate level of awareness on risk factors of CVD. So Effective education and appropriate preventive strategies of CVD are indeed important to reduce CVD burden in diabetes patients.

Keywords: cardiovascular disease, awareness, diabetes patients, risk

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Authors: Ehsan Ahmed Yahia

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Introduction: The nursing role in nutrition screening and assessing hospitalized patients is important. Malnutrition is a common and costly problem, particularly among hospitalized patients, and can have an adverse effect on the healing process. The study's goal is to assess the prevalence of malnutrition among adult hospitalized orthopedic patients and to detect the barriers to the nutrition screening process. Aim of the study: This study aimed to (a) assess the prevalence of malnutrition in hospitalized orthopedic patients and (b) evaluate the relationship between malnutrition and selected clinical outcomes. Material and Methods: This prospective field study was conducted for three months between 03/2022 and 06/2022 in the selected orthopedic departments in a teaching hospital affiliated withCairo University, Egypt. with a total number of one hundred twenty (120) patients. Patients' assessment included checking for malnutrition using the Nutritional Risk Screening Questionnaire. Patients at risk for malnourishment were defined as NRS score ≥ 3. Clinical outcomes under consideration included 1) length of hospitalization, 2) mobilization after surgery and conservative treatment, and 3) rate of adverse events. Results: This study found that malnutrition is a significant problem among patients hospitalized in an orthopedic ward. The prevalence of malnutrition was the highest in patients with lumbar spine and pelvis fractures, followed by the proximal femur and proximal humerus fractures. Patients at risk for malnutrition had significantly prolonged hospitalization, delayed postoperative mobilization, and increased incidence of adverse events.27.8% of the study sample were at risk for malnutrition. The highest prevalence of malnourishment was found in Septic Surgery with 32%, followed by Traumatology with 19.6% and Arthroplasty with 15.3%. A higher prevalence of malnutrition was detected among patients with typical fractures, such as lumbar spine and pelvis (46.7%), proximal femur (34.4%), and proximal humeral (23.7%) fractures. Additionally, patients at risk for malnutrition showed prolonged hospitalization (14.7 ± 11.1 vs. 21.2 ± 11.7 days), delayed postoperative mobilization (2.3 ± 2.9 vs. 4.1 ± 4.9 days), and delayed to mobilize after conservative treatment (1.1 ± 2.7 vs. 1.8 ± 1.9 days). A significant statistical correlation of NRS with individual parameters (Spearman's rank correlation, p < 0.05) was observed. The rate of adverse incidents in patients at risk for malnutrition was significantly higher than that of patients with a regular nutritional status (37.2% vs. 21.1%, p < 0.001). Conclusions: Our results indicate that the prevalence of malnutrition in surgical patients is significant. The nutritional status of patients with typical fractures is especially at risk. Prolonged hospitalization, delayed postoperative mobilization, and delayed mobilization after conservative treatment is significantly associated with malnutrition. In addition, the incidence of adverse events in patients at risk for malnutrition is significantly higher.

Keywords: malnutrition, nutritional risk screening, surgery, nursing, orthopedic nurse

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Authors: Ashvinie Thembiliyagoda, Kasun De Silva, Nimal Wijayaratna

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The lowering of the riverbed level as a result of water erosion is termed as scouring. This phenomenon remarkably undermines the potential stability of the bridge pier, causing a threat of failure or collapse. The formation of vortices in the vicinity of bridges due to the obstruction caused by river flow is the main reason behind this pursuit. Scouring is aggravated by factors including high flow rates, bridge pier geometry, sediment configuration etc. Tackling scour-related problems when they become severe is more costly and disruptive compared to implementing preventive measures based on predicted scour depths. This paper presents a comprehensive investigation of the development of a numerical model that could reproduce the scouring effect around bridge piers and estimate the scour depth. The numerical model was developed for one selected bridge in Sri Lanka, the Kelanisiri Bridge. HEC-RAS two-dimensional (2D) modeling approach was utilized for the development of the model and was calibrated and validated with field data. To further enhance the reliability of the model, a physical model was developed, allowing for additional validation. Results from the numerical model were compared with those obtained from the physical model, revealing a strong correlation between the two methods and confirming the numerical model's accuracy in predicting scour depths. The findings from this study underscore the ability of the HEC-RAS two-dimensional modeling approach for the estimation of scour depth around bridge piers. The developed model is able to estimate the scour depth under varying flow conditions, and its flexibility allows it to be adapted for application to other bridges with similar hydraulic and geomorphological conditions, providing a robust tool for widespread use in scour estimation. The developed two-dimensional model not only offers reliable predictions for the case study bridge but also holds significant potential for broader implementation, contributing to the improved design and maintenance of bridge structures in diverse environments.

Keywords: piers, scouring, HEC-RAS, physical model

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Authors: Marlon Gallo, Eduardo Miguel, Laura Oca, Eneko Gonzalez, Unai Iraola

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The heat generation of an energy storage system is an essential topic when designing a battery pack and its cooling system. Heat generation estimation is used together with thermal models to predict battery temperature in operation and adapt the design of the battery pack and the cooling system to these thermal needs guaranteeing its safety and correct operation. In the present work, a comparison between the use of a heat flux sensor (HFS) for indirect measurement of heat losses in a cell and the widely used and simplified version of Bernardi’s equation for estimation is presented. First, a Li-ion cell is thermally characterized with an HFS to measure the thermal parameters that are used in a first-order lumped thermal model. These parameters are the equivalent thermal capacity and the thermal equivalent resistance of a single Li-ion cell. Static (when no current is flowing through the cell) and dynamic (making current flow through the cell) tests are conducted in which HFS is used to measure heat between the cell and the ambient, so thermal capacity and resistances respectively can be calculated. An experimental platform records current, voltage, ambient temperature, surface temperature, and HFS output voltage. Second, an equivalent circuit model is built in a Matlab-Simulink environment. This allows the comparison between the generated heat predicted by Bernardi’s equation and the HFS measurements. Data post-processing is required to extrapolate the heat generation from the HFS measurements, as the sensor records the heat released to the ambient and not the one generated within the cell. Finally, the cell temperature evolution is estimated with the lumped thermal model (using both HFS and Bernardi’s equation total heat generation) and compared towards experimental temperature data (measured with a T-type thermocouple). At the end of this work, a critical review of the results obtained and the possible mismatch reasons are reported. The results show that indirectly measuring the heat generation with HFS gives a more precise estimation than Bernardi’s simplified equation. On the one hand, when using Bernardi’s simplified equation, estimated heat generation differs from cell temperature measurements during charges at high current rates. Additionally, for low capacity cells where a small change in capacity has a great influence on the terminal voltage, the estimated heat generation shows high dependency on the State of Charge (SoC) estimation, and therefore open circuit voltage calculation (as it is SoC dependent). On the other hand, with indirect measuring the heat generation with HFS, the resulting error is a maximum of 0.28ºC in the temperature prediction, in contrast with 1.38ºC with Bernardi’s simplified equation. This illustrates the limitations of Bernardi’s simplified equation for applications where precise heat monitoring is required. For higher current rates, Bernardi’s equation estimates more heat generation and consequently, a higher predicted temperature. Bernardi´s equation accounts for no losses after cutting the charging or discharging current. However, HFS measurement shows that after cutting the current the cell continues generating heat for some time, increasing the error of Bernardi´s equation.

Keywords: lithium-ion battery, heat flux sensor, heat generation, thermal characterization

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Authors: Muhammad Ali, Aamir Sohail, Umair Malik

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Research in entrepreneurship has gained much attention in current academic environment. Youngsters are taking interest to start their own business in spite of risk matter. The objective of the study is to explain how various personality traits (personal attitude, locus of control, instrumental readiness and perceived behavioral control) are affecting entrepreneurial intention of students. The theory of planned behavior supports out study which explains that personal attractiveness, social norms and feasibility are the main factors that affect intentions of an individual. The sample data of 120 is collected from graduating batch of three reputed universities of Islamabad through questionnaires. Our results support the hypothesis that personality traits positively influence the entrepreneurial intention. We conclude from the study that many graduating students are willing to start a new venture, but most of them are likely to do a job in their respective fields. Risk factor also exists in their minds because in our country most people are risk-averse and they do not want to lose their money in case of loss.

Keywords: entrepreneurship, instrumental readiness, locus of control, personal attitude

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Authors: Je Young Lee, Hee Sung Kim, Kwang Ho Choi, Joonhoo Lim, Sebum Chun, Hyung Keun Lee

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A purpose of this study is to develop efficient detection method for Global Navigation Satellite Systems (GNSS) applications based on adaptive estimation. Due to dependence of radio frequency signals, GNSS measurements are dominated by systematic errors in receiver’s operating environment. Thus, to utilize GNSS for aerospace or ground vehicles requiring high level of safety, unhealthy measurements should be considered seriously. For the reason, this paper proposes adaptive fault detection method to deal with unhealthy measurements in various harsh environments. By the proposed method, the test statistics for fault detection is generated by estimated measurement noise. Pseudorange and carrier-phase measurement noise are obtained at time propagations and measurement updates in process of Carrier-Smoothed Code (CSC) filtering, respectively. Performance of the proposed method was evaluated by field-collected GNSS measurements. To evaluate the fault detection capability, intentional faults were added to measurements. The experimental result shows that the proposed detection method is efficient in detecting unhealthy measurements and improves the accuracy of GNSS positioning under fault occurrence.

Keywords: adaptive estimation, fault detection, GNSS, residual

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Authors: Chia-Chun Wu, Yu-Hsien Sung

Abstract:

This study aims to examine the consistency between students’ predictions and their actual observations on the bullying prevalence rate among different types of high-risk victims, thereby clarifying the reliability of students’ reports on the identification of bullying. A total of 1,732 Taiwanese students (734 males and 998 females) participated in this study. A Rasch model was adopted for data analysis. The results showed that students with “personality or behavioral issues” are more likely to be bullied in schools, based on both students’ predictions and actual observations. Moreover, the results differed significantly between genders and between various educational levels in students’ predictions and their actual observations on the bullying prevalence rate of different types of high-risk victims. To summarize, this study not only suggests that students’ reports on the identification of bullying are accurate and could be a valuable reference in terms of recognizing a bullying incident, but it also argues that more attention should be paid to students’ gender and educational level when taking their perspectives into consideration when it comes to identifying bullying behaviors.

Keywords: school bullying, student, bullying recognition, high-risk victims

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Authors: Mengdan Guo, Zongmin Wang, Haibo Yang

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Drought is one of the most complex and destructive natural disasters, with a huge impact on both nature and society. In recent years, adverse climate conditions and uncontrolled human activities have exacerbated the occurrence of global droughts, among which socio-economic droughts are closely related to human survival. The study of socio-economic drought risk assessment is crucial for sustainable social development. Therefore, this study comprehensively considered the risk of disaster causing factors, the exposure level of the disaster-prone environment, and the vulnerability of the disaster bearing body to construct a socio-economic drought risk assessment model for Chuxiong Prefecture in Yunnan Province. Firstly, a threedimensional frequency analysis of intensity area duration drought was conducted, followed by a statistical analysis of the drought risk of the socio-economic system. Secondly, a grid analysis model was constructed to assess the exposure levels of different agents and study the effects of drought on regional crop growth, industrial economic growth, and human consumption thresholds. Thirdly, an agricultural vulnerability model for different irrigation levels was established by using the DSSAT crop model. Industrial economic vulnerability and domestic water vulnerability under the impact of drought were investigated by constructing a standardized socio-economic drought index and coupling water loss. Finally, the socio-economic drought risk was assessed by combining hazard, exposure, and vulnerability. The results show that the frequency of drought occurrence in Chuxiong Prefecture, Yunnan Province is relatively high, with high population and economic exposure concentrated in urban areas of various counties and districts, and high agricultural exposure concentrated in mountainous and rural areas. Irrigation can effectively reduce agricultural vulnerability in Chuxiong, and the yield loss rate under the 20mm winter irrigation scenario decreased by 10.7% compared to the rain fed scenario. From the perspective of comprehensive risk, the distribution of long-term socio-economic drought risk in Chuxiong Prefecture is relatively consistent, with the more severe areas mainly concentrated in Chuxiong City and Lufeng County, followed by counties such as Yao'an, Mouding and Yuanmou. Shuangbai County has the lowest socio-economic drought risk, which is basically consistent with the economic distribution trend of Chuxiong Prefecture. And in June, July, and August, the drought risk in Chuxiong Prefecture is generally high. These results can provide constructive suggestions for the allocation of water resources and the construction of water conservancy facilities in Chuxiong Prefecture, and provide scientific basis for more effective drought prevention and control. Future research is in the areas of data quality and availability, climate change impacts, human activity impacts, and countermeasures for a more comprehensive understanding and effective response to drought risk in Chuxiong Prefecture.

Keywords: DSSAT model, risk assessment, socio-economic drought, standardized socio-economic drought index

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Authors: Tolga Barisik, Ali Fuat Guneri, K. Dastan

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Major industrial facilities have a high potential for fire risk. In particular, the indices used for the detection of hidden fire are used very effectively in order to prevent the fire from becoming dangerous in the initial stage. These indices provide the opportunity to prevent or intervene early by determining the stage of the fire, the potential for hazard, and the type of the combustion agent with the percentage values of the ambient air components. In this system, artificial neural network will be modeled with the input data determined using the Levenberg-Marquardt algorithm, which is a multi-layer sensor (CAA) (teacher-learning) type, before modeling the modeling methods in the literature. The actual values produced by the indices will be compared with the outputs produced by the network. Using the neural network and the curves to be created from the resulting values, the feasibility of performance determination will be investigated.

Keywords: artifical neural networks, fire, Graham Index, levenberg-marquardt algoritm, oxygen decrease percentage index, risk assessment, Trickett Index

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Authors: Orathai Srithongtham, Ubonsri Thabuddha

Abstract:

The youth with HIV positive is not difference from the general youth in term of sexual needs. Sexual health is crucial the most to support the youth with HIV positive to be sexual well-being. This study aims to elucidate the sexual health on protection from STDs (Sexual Transmitted Diseases) and HIV transmission and to explain sexual risk behavior of the youth with HIV positive. The target group was the youth with HIV positive about 23 cases from two provinces in northeastern part of Thailand. Qualitative method was applied for collecting data by in-depth interview. Content analysis was use for data analysis. The youth with HIV positive was protection from STDs and HIV transmission by using the condom during sexual activity. The reason to deny the condom use were ashamed, condom is not a part of life, no have fit size, and the youth fear to stigmatized as a mental disorder and fear to stigmatized as going to fuck someone. The youth who trust with nurse in clinic was dare to request the condom by face. Sexual activity without condom use is sexual risk behavior. The major causes were couple trust and the sexual enjoyment first and sexual active competition with friend without condom use. The concern on HIV was the boyfriend or girlfriend not accepts the HIV positive people, worry about the HIV transmutation, and finally not compliance to ARV drug. The youth with HIV positive was lacking of the knowledge on sexual health on the issues of access to condom and the concern to keep on relationship with the boyfriend or girlfriend. This concern issues was led to the non-adherence of ARV drug and HIV distribution. To provide the sexual health service is more essential to the youth with HIV positive.

Keywords: sexual health, sexual risk behavior, youth, HIV

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Authors: Tin Thongthammachart, Wanida Jinsart

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Atmospheric particulate matter particles with a diameter less than 10 microns (PM₁₀) and less than 2.5 microns (PM₂.₅) have adverse health effect. The impact from PM was studied from both health and regulatory perspective. Ambient PM data was collected over ten years in Bangkok and vicinity areas of Thailand from 2007 to 2017. Statistical models were used to forecast PM concentrations from 2018 to 2020. Monitoring monthly data averaged concentration of PM₁₀ and PM₂.₅ were used as input to forecast the monthly average concentration of PM. The forecasting results were validated by root means square error (RMSE). The predicted results were used to determine hazard risk for the carcinogenic disease. The health risk values were interpolated with GIS with ordinary kriging technique to create hazard maps in Bangkok and vicinity area. GIS-based maps illustrated the variability of PM distribution and high-risk locations. These evaluated results could support national policy for the sake of human health.

Keywords: PM₁₀, PM₂.₅, statistical models, atmospheric particulate matter

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Authors: Reza Safdari, Goli Arji, Robab Abdolkhani Maryam zahmatkeshan

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Background and purpose: Cardiovascular diseases are among the most common diseases in all societies. The most important step in minimizing myocardial infarction and its complications is to minimize its risk factors. The amount of medical data is increasingly growing. Medical data mining has a great potential for transforming these data into information. Using data mining techniques to generate predictive models for identifying those at risk for reducing the effects of the disease is very helpful. The present study aimed to collect data related to risk factors of heart infarction from patients’ medical record and developed predicting models using data mining algorithm. Methods: The present work was an analytical study conducted on a database containing 350 records. Data were related to patients admitted to Shahid Rajaei specialized cardiovascular hospital, Iran, in 2011. Data were collected using a four-sectioned data collection form. Data analysis was performed using SPSS and Clementine version 12. Seven predictive algorithms and one algorithm-based model for predicting association rules were applied to the data. Accuracy, precision, sensitivity, specificity, as well as positive and negative predictive values were determined and the final model was obtained. Results: five parameters, including hypertension, DLP, tobacco smoking, diabetes, and A+ blood group, were the most critical risk factors of myocardial infarction. Among the models, the neural network model was found to have the highest sensitivity, indicating its ability to successfully diagnose the disease. Conclusion: Risk prediction models have great potentials in facilitating the management of a patient with a specific disease. Therefore, health interventions or change in their life style can be conducted based on these models for improving the health conditions of the individuals at risk.

Keywords: decision trees, neural network, myocardial infarction, Data Mining

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Authors: Nael Y. Zabel, Maged E. Georgy, Moheeb E. Ibrahim

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A knowledge-based expert system with the acronym RASPE is developed as an application tool to help decision makers in construction companies make informed decisions about managing risks in pipeline construction projects. Choosing to use expert systems from all available artificial intelligence techniques is due to the fact that an expert system is more suited to representing a domain’s knowledge and the reasoning behind domain-specific decisions. The knowledge-based expert system can capture the knowledge in the form of conditional rules which represent various project scenarios and potential risk mitigation/response actions. The built knowledge in RASPE is utilized through the underlying inference engine that allows the firing of rules relevant to a project scenario into consideration. This paper provides an overview of the knowledge acquisition process and goes about describing the knowledge structure which is divided up into four major modules. The paper shows one module in full detail for illustration purposes and concludes with insightful remarks.

Keywords: expert system, knowledge management, pipeline projects, risk mismanagement

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Authors: Yelin Zhao, Xinxiu Li, Martin Smelik, Oleg Sysoev, Firoj Mahmud, Dina Mansour Aly, Mikael Benson

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Background: Early diagnosis of pancreatic cancer is clinically challenging due to vague, or no symptoms, and lack of biomarkers. Polygenic risk score (PRS) scores may provide a valuable tool to assess increased or decreased risk of PC. This study aimed to develop such PRS by filtering genetic variants identified by GWAS using transcriptional programs identified by single-cell RNA sequencing (scRNA-seq). Methods: ScRNA-seq data from 24 pancreatic ductal adenocarcinoma (PDAC) tumor samples and 11 normal pancreases were analyzed to identify differentially expressed genes (DEGs) in in tumor and microenvironment cell types compared to healthy tissues. Pathway analysis showed that the DEGs were enriched for hundreds of significant pathways. These were clustered into 40 “programs” based on gene similarity, using the Jaccard index. Published genetic variants associated with PDAC were mapped to each program to generate program PRSs (pPRSs). These pPRSs, along with five previously published PRSs (PGS000083, PGS000725, PGS000663, PGS000159, and PGS002264), were evaluated in a European-origin population from the UK Biobank, consisting of 1,310 PDAC participants and 407,473 non-pancreatic cancer participants. Stepwise Cox regression analysis was performed to determine associations between pPRSs with the development of PC, with adjustments of sex and principal components of genetic ancestry. Results: The PDAC genetic variants were mapped to 23 programs and were used to generate pPRSs for these programs. Four distinct pPRSs (P1, P6, P11, and P16) and two published PRSs (PGS000663 and PGS002264) were significantly associated with an increased risk of developing PC. Among these, P6 exhibited the greatest hazard ratio (adjusted HR[95% CI] = 1.67[1.14-2.45], p = 0.008). In contrast, P10 and P4 were associated with lower risk of developing PC (adjusted HR[95% CI] = 0.58[0.42-0.81], p = 0.001, and adjusted HR[95% CI] = 0.75[0.59-0.96], p = 0.019). By comparison, two of the five published PRS exhibited an association with PDAC onset with HR (PGS000663: adjusted HR[95% CI] = 1.24[1.14-1.35], p < 0.001 and PGS002264: adjusted HR[95% CI] = 1.14[1.07-1.22], p < 0.001). Conclusion: Compared to published PRSs, scRNA-seq-based pPRSs may be used not only to assess increased but also decreased risk of PDAC.

Keywords: cox regression, pancreatic cancer, polygenic risk score, scRNA-seq, UK biobank

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