Search results for: squared prediction risk

Authors: Mohammad Alkhatatbeh, Nehad Ayoub, Nizar Mhaidat, Nesreen Saadeh, Lisa Lincz

Abstract:

CD36 is involved in the development of atherosclerosis by enhancing macrophage endocytosis of oxidized-low density lipoproteins and foam cell formation. Soluble CD36 (sCD36) was found to be elevated in type 2 diabetic patients and was supposed to act as a marker of insulin resistance and atherosclerosis. In young subjects, sCD36 was associated with cardiovascular risk factors including obesity and hypertriglyceridemia. This study was conducted to further investigate the relationship between plasma sCD36 and cardiovascular risk factors among middle-aged patients with metabolic syndrome (MetS) and healthy controls. SCD36 concentrations were determined by enzyme-linked immunosorbent assays (ELISA) for 41 patients with MetS and 36 healthy controls. Data for other variables were obtained from patients' medical records. SCD36 concentrations were relatively low compared to most other studies and were not significantly different between the MetS group and controls (P-value=0.17). SCD36 was also not correlated with age, body mass index, glucose, lipid profile, serum electrolytes and blood counts. SCD36 was not significantly different between subjects with obesity, hyperglycemia, dyslipidemia, hypertension or cardiovascular disease and those without these abnormalities (P-value > 0.05). The inconsistency between results reported in this study and other studies may be unique to the study population or be a result of the lack of a reliable standardized method for determining absolute sCD36 concentrations. However, further investigations are required to assess CD36 tissue expression in the study population and to assess the accuracy of various commercially available sCD36 ELISA kits. Thus, the availability of a standardized simple sCD36 ELISA that could be performed in any basic laboratory would be more favorable to the specialized flow cytometry methods that detect CD36+ microparticles if it was to be used as a biomarker.

Keywords: metabolic syndrome, CD36, cardiovascular risk, obesity, type 2 diabetes mellitus

Procedia PDF Downloads 267

Authors: Mustapha Kamel Mihoubi, Essadik Kerkar, Abdelhamid Hebbouche

Abstract:

According to the randomness of most of the factors affecting the stability of a gravity dam, probability theory is generally used to TESTING the risk of failure and there is a confusing logical transition from the state of stability failed state, so the stability failure process is considered as a probable event. The control of risk of product failures is of capital importance for the control from a cross analysis of the gravity of the consequences and effects of the probability of occurrence of identified major accidents and can incur a significant risk to the concrete dam structures. Probabilistic risk analysis models are used to provide a better understanding the reliability and structural failure of the works, including when calculating stability of large structures to a major risk in the event of an accident or breakdown. This work is interested in the study of the probability of failure of concrete dams through the application of the reliability analysis methods including the methods used in engineering. It is in our case of the use of level II methods via the study limit state. Hence, the probability of product failures is estimated by analytical methods of the type FORM (First Order Reliability Method), SORM (Second Order Reliability Method). By way of comparison, a second level III method was used which generates a full analysis of the problem and involving an integration of the probability density function of, random variables are extended to the field of security by using of the method of Mont-Carlo simulations. Taking into account the change in stress following load combinations: normal, exceptional and extreme the acting on the dam, calculation results obtained have provided acceptable failure probability values which largely corroborate the theory, in fact, the probability of failure tends to increase with increasing load intensities thus causing a significant decrease in strength, especially in the presence of combinations of unique and extreme loads. Shear forces then induce a shift threatens the reliability of the structure by intolerable values of the probability of product failures. Especially, in case THE increase of uplift in a hypothetical default of the drainage system.

Keywords: dam, failure, limit state, monte-carlo, reliability, probability, sliding, Taylor

Procedia PDF Downloads 318

Authors: Fatemeh Abdollahi, Munn-Sann Lye, Jamshid Yazdani Charati, Mehran Zarghami

Abstract:

Both obesity and intimate partner violence (IPV) are growing health threats. This study aimed to assess the prevalence and risk factors of both IPV and obesity and their association. In this cross-sectional study, 530 women aged 16-65 years attending Mazandaran primary health centers were recruited through the stratified random sampling method (2019-2020). Data were collected using the modified World Health Organization Domestic Violence questionnaire, Perceived Stress Scale, and socio-demographic, obstetric, and anthropometric questionnaires. The data were analyzed using descriptive statistics, the chi-square test, and multiple logistic regression. The prevalence of overweight, obesity and psychological, physical, and sexual IPV were 47.6%, 26.7%, 70.4%, 17.9%, and 6.4%, respectively. Increasing women’s educational level and exposure to violence during their lifespan increased the odds of any type of IPV while living in a nuclear family reduced it. In groups of women who were subjected to any type of IPV and only psychological IPV, experiencing violence during the lifespan was significant in predicting obesity. The alarming prevalence of IPV and obesity-overweight in this study points to the need for collaborative socio-political and health intervention. The link between experiencing violence during lifespan and obesity in some subgroups of women highlights the detrimental consequences of chronic violence and the urgent need for effective preventive programs.

Keywords: intimate partner violence, body mass index, obesity, risk factor, women

Procedia PDF Downloads 102

Authors: Parvin Mirmiran, Zahra Bahadoran, Sahar Mirzae, Fereidoun Azizi

Abstract:

Background and aim: Lifestyle factors, especially dietary intakes play an important role in metabolism of lipids and lipoproteins. In this study, we assessed the association between dietary factors and 3-year changes of serum triglycerides (TG), HDL-C and the atherogenic index of plasma among Iranian adults. This longitudinal study was conducted on 1938 subjects, aged 19-70 years, who participated in the Tehran Lipid and Glucose Study. Demographics, anthropometrics and biochemical measurements including serum TG were assessed at baseline (2006-2008) and after a 3-year follow-up (2009-2011). Dietary data were collected by using a 168-food item, validated semi-quantitative food frequency questionnaire at baseline. The risk of hypertriglyceridemia in the quartiles of dietary factors was evaluated using logistic regression models with adjustment for age, gender, body mass index, smoking, physical activity and energy intakes. Results: Mean age of the participants at baseline was 41.0±13.0 y. Mean TG and HDL-C at baseline was 143±86 and 42.2±10.0 mg/dl, respectively. Three-year change of serum TG were inversely related energy intake from phytochemical rich foods, whole grains, and legumes (P<0.05). Higher intakes compared to lower ones of dietary fiber and phytochemical-rich foods had similar impact on decreased risk of hyper-triglyceridemia (OR=0.58, 95% CI=0.34-1.00). Higher- compared to lower-dietary sodium to potassium ratios (Na/K ratio) increased the risk of hypertriglyceridemia by 63% (OR=0.1.63, 95% CI= 0.34-1.00). Conclusion: Findings showed that higher intakes of fiber and phytochemical rich foods especially whole grain and legumes could have protective effects against lipid disorders; in contrast higher sodium to potassium ratio had undesirable effect on triglycerides.

Keywords: lipid disorders, hypertriglyceridemia, diet, food science

Procedia PDF Downloads 468

Authors: Ivonne N. Pérez-Sánchez. María L. Rascón- Gasca, Angélica Riveros-Rosas, Rebeca Robles García

Abstract:

Introduction: Primary caregivers of cancer patients have health problems related to their lack of time, stress, and fiscal strain. Their health problems could affect their patients’ health and also increase the expenses in public health. Aim: To describe self-care and risk behaviors in a sample of Mexican primary caregiver and the relation of these behaviors with emotional distress (caregiver burden, anxiety and depression symptoms), coping and sociodemographic variables. Method: Participated in this study 173 caregivers of a third level reference medical facility (age: M=49.4, SD=13.5) females 78%, males 22%, 57.5% were caregivers of patients with terminal cancer (CPTC), and 40.5% were caregivers of patients on oncology treatment (CPOT). Results: The 75.7% of caregivers reported to have had health problem in last six months as well as several symptoms which were related to emotional distress, these symptoms were more frequently between CPTC and female caregivers. A half (47.3%) of sample reported have had difficulties in caring their health; these difficulties were related to emotional distress and lower coping, more affected caregivers were who attend male patients and CPTC. The 76.8% of caregivers had health problems in last six months, but 26.5% of them waited to search medical care until they were very sick, and 11% didn't do it. Also, more than a half of sample (56.1%) admitted to have risk behaviors as drink alcohol, smoke or overeating for feeling well, these caregivers showed high emotional distress and lower coping. About caregivers healthy behaviors, 80% of them had a hobby; 27.2% do exercise usually and between 12% to 60% did medical checkups (glucose tests, blood pressure and cholesterol tests, eye exams and watched their weight), these caregivers had lower emotional distress and high coping, some variables related health behaviors were: care only one patient or a female patient and be a CPOT, social support, high educational level and experience as a caregiver in past. The half of caregivers were worrying to develop cancer in the future; this idea was 2.5 times more frequent in caregiver with problems to care their health. Conclusions: The results showed a big proportion of caregivers with medical problems. High emotional distress and low coping were related to physical symptoms, risk behaviors, and low self-care; poor self-care was frequently even in caregiver who have chronic illness.

Keywords: cancer, primary caregiver, risk behaviors, self-care

Procedia PDF Downloads 404

Authors: Mahmoud Hassanin, Amita Gupta

Abstract:

Background: During current practice, Thiopentone is not cost-effectively added to resources wastage, risk of drug error with antibiotics, short shelf life, infection risk, and risk of delay while preparing during category one cesarean section. There is no significant difference or preference to the other alternative as per current use. Aims and Objectives: Patient safety, Cost-effective use of trust resources, problem awareness, Consider improvising on the current practice. Methods: In conjunction with the local department survey results, many studies support the change. Results: More than 50%(15 from 29) are already using Propofol, more than 75% of the participant are willing to shift to Propofol if it becomes standard, and the cost analysis also revealed that Thiopentone 10 X500=£60 Propofol 10X200= £5.20, Cost of Thiopentone/year =£2190. Approximately GA in a year =35-40 could cost approximately £20 Propofol, given it is a well-established practice. We could save not only money, but it will be environmentally friendly also to avoid adding any carbon footprints. Recommendation: Thiopentone is rarely used as an induction agent for the category one Caesarean section in our obstetric emergency theatres. Most obstetric anesthetists are using Propofol. Keep both Propofol and thiopentone(powder not withdrawn) in the cat one cesarean section emergency drugs tray ready until the department completely changes the practice protocol. A further retrospective study is required to compare the outcomes for these induction agents through the local database.

Keywords: thiopentone, propofol, category 1 caesarean, induction agents

Procedia PDF Downloads 143

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

Abstract:

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

Procedia PDF Downloads 175

Authors: Maryam Vaezjalali, Foad Davoodbeglou, Mehrnaz Mesdaghi, Hossein Goudarzi, Fariba Shojaei, Hourieh Aram

Abstract:

Introduction: Hepatitis B virus (HBV) infection causes chronic infection in human population, with high mortality. Some people are more susceptible to this infection. One of the high risk communities is mentally retarded children, who are institutionalized. Special conditions in these centers predispose children for HBV infection and transmission to healthy people. In this study our objective was to determine the prevalence of HBV infection among institutionalized mentally retarded children and study its associated risk factors. Materials and methods: In this study, 250 mentally retarded children (younger than 14 years old) were included. They were living in 5 nursing institutions, located in different parts of Tehran. HBsAg was measured in the sera of these patients by ELISA method. Results: Among 250 children, 20 children (8%) were HBsAg positive. HBV infection in girls was more than boys (11% to 5.6%). Among the types of mental retardation, children with cerebral palsy had the highest positive result for HBsAg. The most HBV infection (28.5%) was seen in children with longest duration of being institutionalized (10 to 11 years). Vaccinated children were more HBsAg positive (8.7%) than non-vaccinated children (5.3%). However, no significant relationship was observed between any of these factors and HBsAg positivity. Conclusion: Despite improvement of people’s health condition and implementation of HBV vaccination, the prevalence of HBV infection is high in institutionalized mentally retarded children, which highlights the need for active measures to reduce this infection among this high risk population.

Keywords: hepatitis B virus, HBV vaccine, intellectually disabled children, mentally retarded

Procedia PDF Downloads 482

Authors: S. B. D. Samarasinghe, Malini Herath

Abstract:

Participatory planning is a very important process for decision making and choosing the best alternative options for community welfare, development of the society and its interactions among community and professionals. People’s involvement is considered as the key guidance in participatory planning. Presently, Participatory planning is being used in many fields. It's not only limited to planning but also to disaster management, poverty, housing, etc. In the past, Disaster management practice was a top-down approach, but it raised many issues as it was converted to a bottom-up approach. There are several approaches that can aid disaster management. Community-Based Disaster Risk Management (CBDRM) is a very successful participatory approach to risk management that is often successfully applied by other disaster-prone countries. In the local context, CBDRM has been applied to prevent Diseases as well as to prevent disasters such as landslides, tsunamis and floods. From three years before, Sri Lanka has initiated the CBDRM approach to minimize landslide vulnerability. Hence, this study mainly focuses on the impact of CBDRM approaches on landslide hazards. Also to identify their successes and failures from both implementing parties and community. This research is carried out based on a qualitative method combined with a descriptive research approach. A successful framework was prepared via a literature review. Case studies were selected considering landslide CBDRM programs which were implemented by Disaster Management Center and National Building Research Organization in Badulla. Their processes were evaluated. Data collection is done through interviews and informal discussions. Then their ideas were quantified by using the Relative Effectiveness index. The resulting numerical value was used to rank the program effectiveness and their success, failures and impacting factors. Results show that there are several failures among implementing parties and the community. Overcoming those factors can make way for better conduction of future CBDRM programs.

Keywords: community-based disaster risk management, disaster management, preparedness, landslide

Procedia PDF Downloads 147

Authors: Navid Kaboudi, Ali Shayanfar

Abstract:

Introduction: Feeding infants with safe milk from the beginning of their life is an important issue. Drugs which are used by mothers can affect the composition of milk in a way that is not only unsuitable, but also toxic for infants. Consuming permeable drugs during that sensitive period by mother could lead to serious side effects to the infant. Due to the ethical restrictions of drug testing on humans, especially women, during their lactation period, computational approaches based on structural parameters could be useful. The aim of this study is to develop mechanistic models to predict the M/P ratio of drugs during breastfeeding period based on their structural descriptors. Methods: Two hundred and nine different chemicals with their M/P ratio were used in this study. All drugs were categorized into two groups based on their M/P value as Malone classification: 1: Drugs with M/P>1, which are considered as high risk 2: Drugs with M/P>1, which are considered as low risk Thirty eight chemical descriptors were calculated by ACD/labs 6.00 and Data warrior software in order to assess the penetration during breastfeeding period. Later on, four specific models based on the number of hydrogen bond acceptors, polar surface area, total surface area, and number of acidic oxygen were established for the prediction. The mentioned descriptors can predict the penetration with an acceptable accuracy. For the remaining compounds (N= 147, 158, 160, and 174 for models 1 to 4, respectively) of each model binary regression with SPSS 21 was done in order to give us a model to predict the penetration ratio of compounds. Only structural descriptors with p-value<0.1 remained in the final model. Results and discussion: Four different models based on the number of hydrogen bond acceptors, polar surface area, and total surface area were obtained in order to predict the penetration of drugs into human milk during breastfeeding period About 3-4% of milk consists of lipids, and the amount of lipid after parturition increases. Lipid soluble drugs diffuse alongside with fats from plasma to mammary glands. lipophilicity plays a vital role in predicting the penetration class of drugs during lactation period. It was shown in the logistic regression models that compounds with number of hydrogen bond acceptors, PSA and TSA above 5, 90 and 25 respectively, are less permeable to milk because they are less soluble in the amount of fats in milk. The pH of milk is acidic and due to that, basic compounds tend to be concentrated in milk than plasma while acidic compounds may consist lower concentrations in milk than plasma. Conclusion: In this study, we developed four regression-based models to predict the penetration class of drugs during the lactation period. The obtained models can lead to a higher speed in drug development process, saving energy, and costs. Milk/plasma ratio assessment of drugs requires multiple steps of animal testing, which has its own ethical issues. QSAR modeling could help scientist to reduce the amount of animal testing, and our models are also eligible to do that.

Keywords: logistic regression, breastfeeding, descriptors, penetration

Procedia PDF Downloads 72

Authors: Benedictus Asriparusa, Lathifah Al Hakimi, Aulia Husada

Abstract:

A large amount of energy is being wasted by the release of natural gas associated with the oil industry. This release interrupts the environment particularly atmosphere layer condition globally which contributes to global warming impact. This research presents an overview of the methods employed by researchers in PT. Chevron Pacific Indonesia in the Minas area to determine a new prediction method of measuring and reducing gas flaring and its emission. The method emphasizes advanced research which involved analytical studies, numerical studies, modeling, and computer simulations, amongst other techniques. A flaring system is the controlled burning of natural gas in the course of routine oil and gas production operations. This burning occurs at the end of a flare stack or boom. The combustion process releases emissions of greenhouse gases such as NO2, CO2, SO2, etc. This condition will affect the chemical composition of air and environment around the boundary layer mainly during transition season. Transition season in Indonesia is absolutely very difficult condition to predict its pattern caused by the difference of two air mass conditions. This paper research focused on transition season in 2013. A simulation to create the new pattern of the pollutants distribution is needed. This paper has outlines trends in gas flaring modeling and current developments to predict the dominant variables in the pollutants distribution. A Fluent model is used to simulate the distribution of pollutants gas coming out of the stack, whereas WRF model output is used to overcome the limitations of the analysis of meteorological data and atmospheric conditions in the study area. Based on the running model, the most influence factor was wind speed. The goal of the simulation is to predict the new pattern based on the time of fastest wind and slowest wind occurs for pollutants distribution. According to the simulation results, it can be seen that the fastest wind (last of March) moves pollutants in a horizontal direction and the slowest wind (middle of May) moves pollutants vertically. Besides, the design of flare stack in compliance according to EPA Oil and Gas Facility Stack Parameters likely shows pollutants concentration remains on the under threshold NAAQS (National Ambient Air Quality Standards).

Keywords: flare motion, new prediction, pollutants distribution, transition season, WRF model

Procedia PDF Downloads 556

Authors: Mesias Alfeus, Kirsty Fitzhenry, Alessia Lederer

Abstract:

The present paper provides empirical studies to estimate defaultable bonds in the South African financial market. The main goal is to estimate the unobservable factors affecting bond yields for South African major banks. The maximum likelihood approach is adopted for the estimation methodology. Extended Kalman filtering techniques are employed in order to tackle the situation that the factors cannot be observed directly. Multi-dimensional Cox-Ingersoll-Ross (CIR)-type factor models are considered. Results show that default risk increased sharply in the South African financial market during COVID-19 and the CIR model with jumps exhibits a better performance.

Keywords: default intensity, unobservable state variables, CIR, α-CIR, extended kalman filtering

Procedia PDF Downloads 111

Authors: Seyed Fakhroddin Hejazi, Mohammad Saleh Sadeghi, Leili Iranirad

Abstract:

Silent myocardial infarction is defined as the appearance of pathological Q waves in the electrocardiogram, without objective signs of myocardial infarction and any minimal or atypical symptoms. Although this condition has been known for a long time, but little is known about its phenomenon and the mechanisms of it remain unclear. Its coincidence with stroke is also still controversial. This case report introduces a middle-aged man with silent myocardial infarction presented with homonymous hemianopia, which except stage 1 hypertension, had no other major cardiovascular risk factors including diabetes mellitus, hypercholesterolemia, family history of cardiac diseases and smoking. In conclusion, this case report indicated that existence of only one cardiovascular risk factor would lead to the development of MI or stroke.

Keywords: silent myocardial infarction, homonymous hemianopia, stroke, hypertension

Procedia PDF Downloads 288

Authors: Tatiana G. Smirnova, Stan G. Benjamin

Abstract:

Rapid Update Cycle (RUC) land surface model (LSM) was a land-surface component in several generations of operational weather prediction models at the National Center for Environment Prediction (NCEP) at the National Oceanic and Atmospheric Administration (NOAA). It was designed for short-range weather predictions with an emphasis on severe weather and originally was intentionally simple to avoid uncertainties from poorly known parameters. Nevertheless, the RUC LSM, when coupled with the hourly-assimilating atmospheric model, can produce a realistic evolution of time-varying soil moisture and temperature, as well as the evolution of snow cover on the ground surface. This result is possible only if the soil/vegetation/snow component of the coupled weather prediction model has sufficient skill to avoid long-term drift. RUC LSM was first implemented in the operational NCEP Rapid Update Cycle (RUC) weather model in 1998 and later in the Weather Research Forecasting Model (WRF)-based Rapid Refresh (RAP) and High-resolution Rapid Refresh (HRRR). Being available to the international WRF community, it was implemented in operational weather models in Austria, New Zealand, and Switzerland. Based on the feedback from the US weather service offices and the international WRF community and also based on our own validation, RUC LSM has matured over the years. Also, a sea-ice module was added to RUC LSM for surface predictions over the Arctic sea-ice. Other modifications include refinements to the snow model and a more accurate specification of albedo, roughness length, and other surface properties. At present, RUC LSM is being tested in the regional application of the Unified Forecast System (UFS). The next generation UFS-based regional Rapid Refresh FV3 Standalone (RRFS) model will replace operational RAP and HRRR at NCEP. Over time, RUC LSM participated in several international model intercomparison projects to verify its skill using observed atmospheric forcing. The ESM-SnowMIP was the last of these experiments focused on the verification of snow models for open and forested regions. The simulations were performed for ten sites located in different climatic zones of the world forced with observed atmospheric conditions. While most of the 26 participating models have more sophisticated snow parameterizations than in RUC, RUC LSM got a high ranking in simulations of both snow water equivalent and surface temperature. However, ESM-SnowMIP experiment also revealed some issues in the RUC snow model, which will be addressed in this paper. One of them is the treatment of grid cells partially covered with snow. RUC snow module computes energy and moisture budgets of snow-covered and snow-free areas separately by aggregating the solutions at the end of each time step. Such treatment elevates the importance of computing in the model snow cover fraction. Improvements to the original simplistic threshold-based approach have been implemented and tested both offline and in the coupled weather model. The detailed description of changes to the snow cover fraction and other modifications to RUC soil and snow parameterizations will be described in this paper.

Keywords: land-surface models, weather prediction, hydrology, boundary-layer processes

Procedia PDF Downloads 88

Authors: Sara ElElimy, Samir Moustafa

Abstract:

Mobile network operators start to face many challenges in the digital era, especially with high demands from customers. Since mobile network operators are considered a source of big data, traditional techniques are not effective with new era of big data, Internet of things (IoT) and 5G; as a result, handling effectively different big datasets becomes a vital task for operators with the continuous growth of data and moving from long term evolution (LTE) to 5G. So, there is an urgent need for effective Big data analytics to predict future demands, traffic, and network performance to full fill the requirements of the fifth generation of mobile network technology. In this paper, we introduce data science techniques using machine learning and deep learning algorithms: the autoregressive integrated moving average (ARIMA), Bayesian-based curve fitting, and recurrent neural network (RNN) are employed for a data-driven application to mobile network operators. The main framework included in models are identification parameters of each model, estimation, prediction, and final data-driven application of this prediction from business and network performance applications. These models are applied to Telecom Italia Big Data challenge call detail records (CDRs) datasets. The performance of these models is found out using a specific well-known evaluation criteria shows that ARIMA (machine learning-based model) is more accurate as a predictive model in such a dataset than the RNN (deep learning model).

Keywords: big data analytics, machine learning, CDRs, 5G

Procedia PDF Downloads 139

Authors: Namekong Fokeng Armand

Abstract:

Background: Zoonoses are nowadays a serious public health problem in both developing and developed countries. They contribute to increase the economic burden. In case of emergence, rural populations are the most affected, hence the need to investigate risk practices in rural households of Penka-Michel (West Cameroon). Methods: This cross-sectional study was conducted from October to November 2021 among 200 heads of households living in the Penka-Michel health district (West Cameroon). It was done using a pre-tested and validated questionnaire, allowing to obtain socio-demographic, economic data, and data on zoonotic risk practices. Results: The participants [women (56%), men (44%)] worked mainly in the informal private sector (53%) and practiced agriculture secondarily (90%). Their highest level of education, for the most part, was a secondary school (50%); the average household size was 06 persons with a monthly income > 36270 FCFA (72%). 74% of household heads thought that animals can transmit diseases, and 17% had heard about zoonotic diseases through the media (65%). Rats caught in households (60%) were consumed there (74%), as was bush meat (61%) or dog meat (18%). For family food (90%), animals were slaughtered within the household (97%), rarely preceded by a veterinary inspection (6%). 87% of households practiced traditional rites with animal blood, 65% shared the same habitat as their animals, 41% did not systematically wash their hands after handling animals. More than 50% of households owned one or more dogs, usually strays (41%) and 48% of which were vaccinated (rabies). Many households had at least one: poultry (98%); pig (50%); dog (57%), cat (52%). 25% of households slaughtered sick animals for consumption, and 27% ate dead animals. Conclusion: This study identified numerous zoonotic risk practices in households in the Penka-Michel health district (West Cameroon). Concerted, multisectoral communication / awareness-raising actions are needed to break with these practices.

Keywords: zoonoses, risky practices, rural households, penka-michel, cameroon

Procedia PDF Downloads 171

Authors: Alia Ali, Azeem Taj, Muhammed Joher Amin, Farrukh Iqbal, Zafar Iqbal

Abstract:

Background: Hypertension is commonly found in patients with Diabetic Kidney Disease (DKD). Microalbuminuria is the first clinical sign of involvement of kidneys in patients with type 2 diabetes. Uncontrolled hypertension induces a higher risk of cardiovascular events, including death, increasing proteinuria and progression to kidney disease. Objectives: To determine the correlation between microalbuminuria and hypertension and their association with other risk factors in type 2 diabetic patients. Methods: One hundred and thirteen type 2 diabetic patients were screened for microalbuminuria and raised blood pressure, attending the diabetic clinic of Shaikh Zayed Hospital, Lahore, Pakistan. The study was conducted from November 2012 to June 2013. Results: Patients were divided into two groups. Group 1, those with normoalbuminuria (n=63) and Group 2, those having microalbuminuria (n=50). Group 2 patients showed higher blood pressure values as compared to Group 1. The results were statistically significant and showed poor glycemic control as a contributing risk factor. Conclusion: The study concluded that there is high frequency of hypertension among type 2 diabetics but still much higher among those having microalbuminuria. So, early recognition of renal dysfunction through detection of microalbuminuria and to start treatment without any delay will confer future protection from end-stage renal disease as well as hypertension and its complications in type 2 diabetic patients.

Keywords: hypertension, microalbuminuria, diabetic kidney disease, type 2 Diabetes mellitus

Procedia PDF Downloads 397

Authors: Thewodros K. Geberemariam

Abstract:

The rapid physical expansion of urbanization coupled with aging infrastructure presents a unique decision and management challenges for many big city municipalities. Cities must therefore upgrade and maintain the existing aging urban drainage infrastructure systems to keep up with the demands. Given the overall contribution of assets to municipal revenue and the importance of infrastructure to the success of a livable city, many municipalities are currently looking for a robust and smart urban drainage infrastructure asset management solution that combines management, financial, engineering and technical practices. This robust decision-making shall rely on sound, complete, current and relevant data that enables asset valuation, impairment testing, lifecycle modeling, and forecasting across the multiple asset portfolios. On this paper, predictive computational intelligence (CI) and multi-class machine learning (ML) coupled with online, offline, and historical record data that are collected from an array of multi-parameter sensors are used for the extraction of different operational and non-conforming patterns hidden in structured and unstructured data to determine and produce actionable insight on the current and future states of the network. This paper aims to improve the strategic decision-making process by identifying all possible alternatives; evaluate the risk of each alternative, and choose the alternative most likely to attain the required goal in a cost-effective manner using historical and near real-time urban drainage infrastructure data for urban drainage infrastructures assets that have previously not benefited from computational intelligence and machine learning advancements.

Keywords: computational intelligence, machine learning, urban drainage infrastructure, machine learning, classification, prediction, asset management space

Procedia PDF Downloads 152

Authors: B. Marasović, S. Pivac, S. V. Vukasović

Abstract:

Constructing a portfolio of investments is one of the most significant financial decisions facing individuals and institutions. In accordance with the modern portfolio theory maximization of return at minimal risk should be the investment goal of any successful investor. In addition, the costs incurred when setting up a new portfolio or rebalancing an existing portfolio must be included in any realistic analysis. In this paper rebalancing an investment portfolio in the presence of transaction costs on the Croatian capital market is analyzed. The model applied in the paper is an extension of the standard portfolio mean-variance optimization model in which transaction costs are incurred to rebalance an investment portfolio. This model allows different costs for different securities, and different costs for buying and selling. In order to find efficient portfolio, using this model, first, the solution of quadratic programming problem of similar size to the Markowitz model, and then the solution of a linear programming problem have to be found. Furthermore, in the paper the impact of transaction costs on the efficient frontier is investigated. Moreover, it is shown that global minimum variance portfolio on the efficient frontier always has the same level of the risk regardless of the amount of transaction costs. Although efficient frontier position depends of both transaction costs amount and initial portfolio it can be concluded that extreme right portfolio on the efficient frontier always contains only one stock with the highest expected return and the highest risk.

Keywords: Croatian capital market, Markowitz model, fractional quadratic programming, portfolio optimization, transaction costs

Procedia PDF Downloads 385

Authors: Aarthi Mariappan, Janani Selvaraj, P. B. Harathi, M. Prashanthi Devi

Abstract:

Anthropogenic modification of the urban environment has largely increased in the recent years in order to sustain the growing human population. Intense industrial activity, permanent and high traffic on the roads, a developed subterranean infrastructure network, land use patterns are just some specific characteristics. Every day, the urban environment is polluted by more or less toxic emissions, organic or metals wastes discharged from specific activities such as industrial, commercial, municipal. When these eventually deposit into the soil, the physical and chemical properties of the surrounding soil is changed, transforming it into a human exposure indicator. Metals are non-degradable and occur cumulative in soil due to regular deposits are a result of permanent human activity. Due to this, metals are a contaminant factor for soil when persistent over a long period of time and a possible danger for inhabitant’s health on prolonged exposure. Metals accumulated in contaminated soil may be transferred to humans directly, by inhaling the dust raised from top soil, or by ingesting, or by dermal contact and indirectly, through plants and animals grown on contaminated soil and used for food. Some metals, like Cu, Mn, Zn, are beneficial for human’s health and represent a danger only if their concentration is above permissible levels, but other metals, like Pb, As, Cd, Hg, are toxic even at trace level causing gastrointestinal and lung cancers. In urban areas, metals can be emitted from a wide variety of sources like industrial, residential, commercial activities. Our study interrogates the spatial distribution of heavy metals in soil in relation to their permissible levels and their association with the health risk to the urban population in Coimbatore, India. Coimbatore region is a high cancer risk zone and case records of gastro intestinal and respiratory cancer patients were collected from hospitals and geocoded in ArcGIS10.1. The data of patients pertaining to the urban limits were retained and checked for their diseases history based on their diagnosis and treatment. A disease map of cancer was prepared to show the disease distribution. It has been observed that in our study area Cr, Pb, As, Fe and Mg exceeded their permissible levels in the soil. Using spatial overlay analysis a relationship between environmental exposure to these potentially toxic elements in soil and cancer distribution in Coimbatore district was established to show areas of cancer risk. Through this, our study throws light on the impact of prolonged exposure to soil contamination in soil in the urban zones, thereby exploring the possibility to detect cancer risk zones and to create awareness among the exposed groups on cancer risk.

Keywords: soil contamination, cancer risk, spatial analysis, India

Procedia PDF Downloads 403

Authors: Ankit Sinha, Soham Banerjee, Pratik Chattopadhyay

Abstract:

Automated product recognition in retail stores is an important real-world application in the domain of Computer Vision and Pattern Recognition. In this paper, we consider the problem of automatically identifying the classes of the products placed on racks in retail stores from an image of the rack and information about the query/product images. We improve upon the existing approaches in terms of effectiveness and memory requirement by developing a two-stage object detection and recognition pipeline comprising of a Faster-RCNN-based object localizer that detects the object regions in the rack image and a ResNet-18-based image encoder that classifies the detected regions into the appropriate classes. Each of the models is fine-tuned using appropriate data sets for better prediction and data augmentation is performed on each query image to prepare an extensive gallery set for fine-tuning the ResNet-18-based product recognition model. This encoder is trained using a triplet loss function following the strategy of online-hard-negative-mining for improved prediction. The proposed models are lightweight and can be connected in an end-to-end manner during deployment to automatically identify each product object placed in a rack image. Extensive experiments using Grozi-32k and GP-180 data sets verify the effectiveness of the proposed model.

Keywords: retail stores, faster-RCNN, object localization, ResNet-18, triplet loss, data augmentation, product recognition

Procedia PDF Downloads 157

Authors: Myoungsoon You, Heejung Son

Abstract:

During a pandemic, hospital workers should protect not only their vulnerable patients but also themselves from the consequences of rapidly spreading infection. However, the evidence on the psychological impact of an outbreak on hospital workers is limited. In this study, we aim to assess hospital workers’ psychological well-being and function at the workplace after an outbreak, by focusing on ‘psychological resilience’. Specifically, the effects of risk appraisal, emotional experience, and coping ability on resilience indicated by the likelihood of post-traumatic syndrome disorder and willingness to work were investigated. Such role and position of each factor were analyzed using a path model, and the result was compared between the healthcare worker and non-healthcare worker groups. In the investigation, 280 hospital workers who experienced the 2015 Middle East Respiratory Syndrome outbreak in South Korea have participated. The result presented, in both groups, the role of the appraisal of risk and coping ability appeared consistent with a previous research, that was, the former interrupted resilience while the latter facilitated it. In addition, the role of emotional experience was highlighted as, in both groups, emotional disruption not only directly associated with low resilience but mediated the effect of perceived risk on resilience. The differences between the groups were also identified, which were, the role of emotional experience and coping ability was more prominent in the non-HCW group in explaining resilience. From the results, implications on how to support hospital personnel during an outbreak in a way to facilitate their resilience after the outbreak were drawn.

Keywords: hospital workers, emotions, infectious disease outbreak, psychological resilience

Procedia PDF Downloads 245

Authors: Zhaoan Wang

Abstract:

Research in predictive maintenance modeling has improved in the recent years to predict failures and needed maintenance with high accuracy, saving cost and improving manufacturing efficiency. However, classic prediction models provide little valuable insight towards the most important features contributing to the failure. By analyzing and quantifying feature importance in predictive maintenance models, cost saving can be optimized based on business goals. First, multiple classifiers are evaluated with cross-validation to predict the multi-class of failures. Second, predictive performance with features provided by different feature selection algorithms are further analyzed. Third, features selected by different algorithms are ranked and combined based on their predictive power. Finally, linear explainer SHAP (SHapley Additive exPlanations) is applied to interpret classifier behavior and provide further insight towards the specific roles of features in both local predictions and global model behavior. The results of the experiments suggest that certain features play dominant roles in predictive models while others have significantly less impact on the overall performance. Moreover, for multi-class prediction of machine failures, the most important features vary with type of machine failures. The results may lead to improved productivity and cost saving by prioritizing sensor deployment, data collection, and data processing of more important features over less importance features.

Keywords: automated supply chain, intelligent manufacturing, predictive maintenance machine learning, feature engineering, model interpretation

Procedia PDF Downloads 133

Authors: Milica Karadzic, Lidija Jevric, Sanja Podunavac-Kuzmanovic, Strahinja Kovacevic, Anamarija Mandic, Katarina Penov Gasi, Marija Sakac, Aleksandar Okljesa, Andrea Nikolic

Abstract:

The present paper deals with chromatographic lipophilicity prediction of newly synthesized steroid derivatives. The prediction was achieved using in silico generated molecular descriptors and quantitative structure-retention relationship (QSRR) methodology with the artificial neural networks (ANN) approach. Chromatographic lipophilicity of the investigated compounds was expressed as retention factor value logk. For QSRR modeling, a feedforward back-propagation ANN with gradient descent learning algorithm was applied. Using the novel sum of ranking differences (SRD) method generated ANN models were ranked. The aim was to distinguish the most consistent QSRR model that can be found, and similarity or dissimilarity between the models that could be noticed. In this study, SRD was performed with average values of retention factor value logk as reference values. An excellent correlation between experimentally observed retention factor value logk and values predicted by the ANN was obtained with a correlation coefficient higher than 0.9890. Statistical results show that the established ANN models can be applied for required purpose. This article is based upon work from COST Action (TD1305), supported by COST (European Cooperation in Science and Technology).

Keywords: artificial neural networks, liquid chromatography, molecular descriptors, steroids, sum of ranking differences

Procedia PDF Downloads 319

Authors: Maria C. Proença, Maria T. Rebelo, Maria J. Alves, Sofia Cunha

Abstract:

Vector-borne diseases are transmitted to humans by mosquitos, sandflies, bugs, ticks, and other vectors. Some are re-transmitted between vectors, if the infected human has a new contact when his levels of infection are high. The vector is infected for lifetime and can transmit infectious diseases not only between humans but also from animals to humans. Some vector borne diseases are very disabling and globally account for more than one million deaths worldwide. The mosquitoes from the complex Culex pipiens sl. are the most abundant in Portugal, and we dispose in this moment of a data set from the surveillance program that has been carried on since 2006 across the country. All mosquitos’ species are included, but the large coverage of Culex pipiens sl. and its importance for public health make this vector an interesting candidate to assess risk of disease amplification. This work focus on ports and airports identified as key areas of high density of vectors. Mosquitoes being ectothermic organisms, the main factor for vector survival and pathogen development is temperature. Minima and maxima local air temperatures for each area of interest are averaged by month from data gathered on a daily basis at the national network of meteorological stations, and interpolated in a geographic information system (GIS). The range of temperatures ideal for several pathogens are known and this work shows how to use it with the meteorological data in each port and airport facility, to focus an efficient implementation of countermeasures and reduce simultaneously risk transmission and mitigation costs. The results show an increased alert with decreasing latitude, which corresponds to higher minimum and maximum temperatures and a lower amplitude range of the daily temperature.

Keywords: human health, risk assessment, risk management, vector-borne diseases

Procedia PDF Downloads 419

Authors: Maria Reichenber Arcilla

Abstract:

Objective: To determine the risk factors for maternal and neonatal complications associated with operative vaginal deliveries. Methods: A retrospective chart review of 435 patients who underwent operative vaginal deliveries was done. Patient profiles – age, parity, AOG, duration of labor – and outcomes – birthweight, maternal and neonatal complications - were tabulated and multivariable analysis and logistic regression were performed using SPSS® Statistics Base. Results and Conclusion: There was no significant difference in the incidence of maternal and neonatal complications between those that underwent vacuum and forceps extraction. Among the variables analysed, parity and duration of labor reached statistical significance. The odds of maternal complications were 3 times higher among nulliparous patients. Neonatal complications were seen in those whose labor lasted more than 9 hours.

Keywords: operative vaginal deliveries, maternal, neonatal, morbidity

Procedia PDF Downloads 406

Authors: Andreas Helwig, John Bell, Wangmo

Abstract:

Hybrid energy storage systems (HESS) are gaining popularity for grid energy storage (ESS) driven by the increasingly dynamic nature of energy demands, requiring both high energy and high power density. Particularly the ability of energy storage systems via inverters to respond to increasing fluctuation in energy demands, the combination of lithium Iron Phosphate (LFP) battery and supercapacitor (SC) is a particular example of complex electro-chemical devices that may provide benefit to each other for pulse width modulated DC to AC inverter application. This is due to SC’s ability to respond to instantaneous, high-current demands and batteries' long-term energy delivery. However, there is a knowledge gap on the current sharing mechanism within a HESS supplying a load powered by high-frequency pulse-width modulation (PWM) switching to understand the mechanism of aging in such HESS. This paper investigates the prediction of current utilizing various equivalent circuits for SC to investigate sharing between battery and SC in MATLAB/Simulink simulation environment. The findings predict a significant reduction of battery current when the battery is used in a hybrid combination with a supercapacitor as compared to a battery-only model. The impact of PWM inverter carrier switching frequency on current requirements was analyzed between 500Hz and 31kHz. While no clear trend emerged, models predicted optimal frequencies for minimized current needs.

Keywords: hybrid energy storage, carrier frequency, PWM switching, equivalent circuit models

Procedia PDF Downloads 26

Authors: Getachew Demesa Bexa

Abstract:

Building resilience to withstand extreme weather events through reduction and mitigation measures towards predicted disasters with appropriate contingency plans complemented by timely and effective emergency response demands committed and integrated/coordinated efforts. The 2006 flood disaster that claimed more than 200 people in Dire Dawa town shifted the paradigm from reactive to proactive engagement among government, NGOs and communities to contain future disasters through resilience building. Dire Dawa CMDRR Association is a model community organization that demonstrated the basic minimum and turning adversity into opportunity by mobilizing vulnerable community members. Meanwhile the birth of African Centre for Disaster Risk Management is a milestone in changing the image of the country and beyond in resilience building while linking relief and development.

Keywords: Dire Dawa, disaster, resilience, risk management

Procedia PDF Downloads 387

Authors: Orkide Donma, Mustafa M. Donma

Abstract:

Basal metabolic rate (BMR) is widely used and an accepted measure of energy expenditure. Its principal determinant is body mass. However, this parameter is also correlated with a variety of other factors. The objective of this study is to measure BMR and compare it with the values obtained from predictive equations in adults classified according to their body mass index (BMI) values. 276 adults were included into the scope of this study. Their age, height and weight values were recorded. Five groups were designed based on their BMI values. First group (n = 85) was composed of individuals with BMI values varying between 18.5 and 24.9 kg/m². Those with BMI values varying from 25.0 to 29.9 kg/m² constituted Group 2 (n = 90). Individuals with 30.0-34.9 kg/m², 35.0-39.9 kg/m², > 40.0 kg/m² were included in Group 3 (n = 53), 4 (n = 28) and 5 (n = 20), respectively. The most commonly used equations to be compared with the measured BMR values were selected. For this purpose, the values were calculated by the use of four equations to predict BMR values, by name, introduced by Food and Agriculture Organization (FAO)/World Health Organization (WHO)/United Nations University (UNU), Harris and Benedict, Owen and Mifflin. Descriptive statistics, ANOVA, post-Hoc Tukey and Pearson’s correlation tests were performed by a statistical program designed for Windows (SPSS, version 16.0). p values smaller than 0.05 were accepted as statistically significant. Mean ± SD of groups 1, 2, 3, 4 and 5 for measured BMR in kcal were 1440.3 ± 210.0, 1618.8 ± 268.6, 1741.1 ± 345.2, 1853.1 ± 351.2 and 2028.0 ± 412.1, respectively. Upon evaluation of the comparison of means among groups, differences were highly significant between Group 1 and each of the remaining four groups. The values were increasing from Group 2 to Group 5. However, differences between Group 2 and Group 3, Group 3 and Group 4, Group 4 and Group 5 were not statistically significant. These insignificances were lost in predictive equations proposed by Harris and Benedict, FAO/WHO/UNU and Owen. For Mifflin, the insignificance was limited only to Group 4 and Group 5. Upon evaluation of the correlations of measured BMR and the estimated values computed from prediction equations, the lowest correlations between measured BMR and estimated BMR values were observed among the individuals within normal BMI range. The highest correlations were detected in individuals with BMI values varying between 30.0 and 34.9 kg/m². Correlations between measured BMR values and BMR values calculated by FAO/WHO/UNU as well as Owen were the same and the highest. In all groups, the highest correlations were observed between BMR values calculated from Mifflin and Harris and Benedict equations using age as an additional parameter. In conclusion, the unique resemblance of the FAO/WHO/UNU and Owen equations were pointed out. However, mean values obtained from FAO/WHO/UNU were much closer to the measured BMR values. Besides, the highest correlations were found between BMR calculated from FAO/WHO/UNU and measured BMR. These findings suggested that FAO/WHO/UNU was the most reliable equation, which may be used in conditions when the measured BMR values are not available.

Keywords: adult, basal metabolic rate, fao/who/unu, obesity, prediction equations

Procedia PDF Downloads 133

Authors: Muhammad Yasir Tarar

Abstract:

Background: Intraarticular steroid injections are an effective option in alleviating the symptoms of conditions like osteoarthritis, rheumatoid arthritis, crystal arthropathy, and rotator cuff tendinopathy. Most of these injections are conducted in the elderly who are on polypharmacy, including anticoagulants at times. Up to 6% of patients aged 80-84 years have been reported to be taking Warfarin. The literature availability on safety quotient for patients undergoing intraarticular injections on Warfarin is scarce. It has remained debatable over the years which approach is safe for these patients. Continuing warfarin has a theoretical bleeding risk, and stopping it can lead to even severe life-threatening thromboembolic events in high-risk patients. Objectives: To evaluate the risk of bleeding complications in patients on warfarin undergoing intraarticular injections or arthrocentesis. Study Design & Methods: A literature search of MEDLINE (1946 to present), EMBASE (1974 to present), and Cochrane CENTRAL (1988 to present) databases were conducted using any combination of the keywords, Injection, Knee, Shoulder, Joint, Intraarticular, arthrocentesis, Warfarin, and Anticoagulation in November 2020 for articles published in any language with no publication year limit. The study inclusion criteria included reporting on the rate of bleeding complications following injection of the knee or shoulder in patients on warfarin treatment. Randomized control trials and prospective and retrospective study designs were included. An electronic standardized Performa for data extraction was made. The Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) the methodology was used. The articles were appraised using the methodological index for nonrandomized studies. The Cochrane Risk of Bias Tool used to assess the risk of bias in included RCTs and the MINORS tool for assessment of bias in observational studies. Results: The search of databases resulted in a total of 852 articles. Relevant articles as per the inclusion criteria were shortlisted, 7 articles deemed suitable to be include. A total of 1033 joints sample size was undertaken with specified knee and shoulder joints of a total of 820. Only 6 joints had bleeding complications, 5 early bleeding at the time of injection or aspiration, and one late bleeding complication with INR of 5, additionally, 2 patients complained of bruising, 3 of pain, and 1 managed for infection. Conclusions: The results of the metanalysis show that it is relatively safe to perform intraarticular injections in patients on Warfarin regardless of the INR range.

Keywords: arthrocentesis, warfarin, bleeding, injection

Procedia PDF Downloads 77