Search results for: squared prediction risk

Authors: Vijaya Nirmala Pangi, K. V. Subhramanyam, C. Vijay Lakshmi

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Background: The prevalence of Type 2 Diabetes Mellitus is increasing drastically at a vigorous rate all over the world population. Aim: The present study aims to determine the prevalence of type-2 diabetes mellitus in Paderu tribal area population of Visakhapatnam district, located in northeastern region of Andhra Pradesh. Methods: A random sampling method was followed in 1025 subjects including controls (n=25) and determined 75-g oral glucose tolerance test to assess the presence of type 2 diabetes mellitus. The effect of anthropometric factors like age, gender, literacy, socio economic status, and environmental risk factors such as body fat response, hypertension and psychophysical stress response were determined in the studied subjects. Results: 78 (7.8%) were diabetic. Type 2 Diabetes Mellitus was found to be comparable between the two genders. Prevalence of diabetes was observed to be high in illiterate, low economic status subjects. Body fat response was comparable between control and diabetic subjects. However hypertension, stress associated enzymes showed significant (p < 0.05) decrease in diabetic subjects compared to controls in both the genders. Conclusion: It appears that there is a rising pattern in the prevalence of diabetes mellitus in tribal area, Paderu, Andhra Pradesh, India compared to previous rural studies.

Keywords: anthropometric studies, hypertension, oral glucose tolerance test, stress enzymes, type-2 diabetes mellitus

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Authors: Mahesh K. Chudasama, Harit K. Raval

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3-roller conical bending process is widely used in the industries for manufacturing of conical sections and shells. It involves static as well dynamic bending stages. Analytical models for prediction of bending force during static as well as dynamic bending stage are available in the literature. In this paper, bending forces required for static bending stage and dynamic bending stages have been compared using the analytical models. It is concluded that force required for dynamic bending is very less as compared to the bending force required during the static bending stage.

Keywords: analytical modeling, cone frustum, dynamic bending, static bending

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Authors: Xiaojing Wang, Ann-Marie Ward, Tony Wall

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The problem of over-indebtedness has increased since deregulation of the banking industry in the 1980s, and now it has become a major problem for most countries in Europe, including Germany. Consumer debt issues have attracted not only the attention of academics but also government and debt counselling institutions. Overall, this research aims to contribute to the knowledge gap regarding the causes of consumer over-indebtedness in Germany and to develop predictive models for assessing consumer over-indebtedness risk at consumer level. The situation of consumer over-indebtedness is serious in Germany. The relatively high level of social welfare support in Germany suggests that consumer debt problems are caused by other factors, other than just over-spending and income volatility. Prior literature suggests that the overall stability of the economy and level of welfare support for individuals from the structural environment contributes to consumers’ debt problems. In terms of cultural influence, the conspicuous consumption theory in consumer behaviour suggests that consumers would spend more than their means to be seen as similar profiles to consumers in a higher socio-economic class. This results in consumers taking on more debt than they can afford, and eventually becoming over-indebted. Studies have also shown that financial literacy is negatively related to consumer over-indebtedness risk. Whilst prior literature has examined structural and cultural influences respectively, no study has taken a collective approach. To address this gap, a model is developed to investigate the association between consumer over-indebtedness and proxies for influences from the structural and cultural environment based on the above theories. The model also controls for consumer demographic characteristics identified as being of influence in prior literature, such as gender and age, and adverse shocks, such as divorce or bereavement in the household. Benefiting from SOEP regional data, this study is able to conduct quantitative empirical analysis to test both structural and cultural influences at a localised level. Using German Socio-Economic Panel (SOEP) study data from 2006 to 2016, this study finds that social benefits, financial literacy and the existence of conspicuous consumption all contribute to being over-indebted. Generally speaking, the risk of becoming over-indebted is high when consumers are in a low-welfare community, have little awareness of their own financial situation and always over-spend. In order to tackle the problem of over-indebtedness, countermeasures can be taken, for example, increasing consumers’ financial awareness, and the level of welfare support. By analysing causes of consumer over-indebtedness in Germany, this study also provides new insights on the nature and underlying causes of consumer debt issues in Europe.

Keywords: consumer, debt, financial literacy, socio-economic

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Authors: Shivani Thakur, Jasmin Dominguez Cervantes, Ahmed Zabiba, Fatima Zabiba, Sandhini Agarwal, Kamalpreet Kaur, Hussein Maatouk, Shae Chand, Omar Madriz, Tiffany Huang, Saloni Bansal

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The prevalence of lymphedema in women in rural communities highlights the importance of developing effective treatment and prevention methods. Subjects with secondary lymphedema in California’s Central Valley were surveyed at 6 surgical clinics to assess demographics and symptoms of lymphedema. Additionally, subjects on semaglutide treatment for obesity and/or T2DM were monitored for their diabetes management, weight loss progress, and lymphedema symptoms compared to subjects who were not treated with semaglutide. The subjects were followed for 12 months. Subjects who were treated with semaglutide completed pre-treatment questionnaires and follow-up post-treatment questionnaires at 3, 6, 9, 12 months, along with medical assessment. The untreated subjects completed similar questionnaires. The questionnaires investigated subjective feelings regarding lymphedema symptoms and management using a Likert-scale; quantitative leg measurements were collected, and blood work reviewed at these appointments. Paired difference t-tests, chi-squared tests, and independent sample t-tests were performed. 50 subjects, aged 18-75 years, completed the surveys evaluating secondary lymphedema: 90% female, 69% Hispanic, 45% Spanish speaking, 42% disabled, 57 % employed, 54% income range below 30 thousand dollars, and average BMI of 40. Both treatment and non-treatment groups noted the most common symptoms were leg swelling (x̄=3.2, ▁d= 1.3), leg pain (x̄=3.2, ▁d=1.6 ), loss of daily function (x̄=3, ▁d=1.4 ), and negative body image (x̄=4.4, ▁d=0.54). Subjects in the semaglutide treatment group >3 months of treatment compared to the untreated group demonstrated: 55% subject in the treated group had a 10% weight loss vs 3% in the untreated group (average BMI reduction by 11% vs untreated by 2.5%, p<0.05) and improved subjective feelings about their lymphedema symptoms: leg swelling (x̄=2.4, ▁d=0.45 vs x̄=3.2, ▁d=1.3, p<0.05), leg pain (x̄=2.2, ▁d=0.45 vs x̄= 3.2, ▁d= 1.6, p<0.05), and heaviness (x̄=2.2, ▁d=0.45 vs x̄=3, ▁d=1.56, p<0.05). Improvement in diabetes management was demonstrated by an average of 0.9 % decrease in A1C values compared to untreated 0.1 %, p<0.05. In comparison to untreated subjects, treatment subjects on semaglutide noted 6 cm decrease in the circumference of the leg, knee, calf, and ankle compared to 2 cm in untreated subjects, p<0.05. Semaglutide was shown to significantly improve weight loss, T2DM management, leg circumference, and secondary lymphedema functional, physical and psychosocial symptoms.

Keywords: diabetes, secondary lymphedema, semaglutide, obesity

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Authors: Khitam Ibrahem Shlash Mohammad

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Background: Postnatal depression is a focus of considerable research attention, but little is known about the pattern of stress across this period. Objective: to investigate the prevalence of stress after childbirth for Jordanian women and identify associated risk factors. Method: Design: A descriptive cross-sectional study. Participants were recruited six to eight weeks postpartum, provided personal, social and obstetric information, and completed the stress subscale of Depression Anxiety and Stress Scale (DASS-S), the Maternity Social Support Scale (MSSS), and Perceived Self-Efficacy Scale (PSES). Setting: maternal and child health care clinics in four health care centres in Maan city in Southern Jordan. Participants: Arabic speaking women (n = 324) between the ages of 18 and 45 years, six to eight weeks postpartum, primiparous or multiparous at low risk for obstetric complications. Data collection took place between October 2015 and January 2016. Ethical clearance was obtained prior to data collection. Results: The prevalence of postpartum stress among Jordanian women was 39.8 %. A regression analysis revealed that occupation, low social support, financial problems, difficult marital relationships, difficult relationship with family-in-law, giving birth to a female baby, difficult childbirth, and low self-efficacy were associated with postpartum stress. Conclusions and implications for practice: Jordanian women need support during pregnancy, during and after childbirth. Postpartum emotional support and assessment of symptoms of stress need to be incorporated into routine practice. The opportunity for open discussion along with increased awareness and clarification of common misconceptions about postpartum stress is necessary.

Keywords: prevalence, postpartum, stress, Jordanian women

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Authors: Brock Liden, Eric Janowitz

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Introduction: Diabetic peripheral neuropathy (DPN) affects 70% of individuals with diabetes1. DPN causes a loss of protective sensation, which can lead to tissue damage and diabetic foot ulcer (DFU) formation2. These ulcers can result in infections and lower-extremity amputations of toes, the entire foot, and the lower leg. Even after a DFU is healed, recurrence is common, with 49% of DFU patients developing another ulcer within a year and 68% within 5 years3. This case series examines the use of sensory insoles and newly available plantar data (pressure, temperature, step count, adherence) and remote patient monitoring in patients at risk of DFU. Methods: Participants were provided with custom-made sensory insoles to monitor plantar pressure, temperature, step count, and daily use and were provided with real-time cues for pressure offloading as they went about their daily activities. The sensory insoles were used to track subject compliance, ulceration, and response to feedback from real-time alerts. Patients were remotely monitored by a qualified healthcare professional and were contacted when areas of concern were seen and provided coaching on reducing risk factors and overall support to improve foot health. Results: Of the 40 participants provided with the sensory insole system, 4 presented with a DFU. Based on flags generated from the available plantar data, patients were contacted by the remote monitor to address potential concerns. A standard clinical escalation protocol detailed when and how concerns should be escalated to the provider by the remote monitor. Upon escalation to the provider, patients were brought into the clinic as needed, allowing for any issues to be addressed before more serious complications might arise. Conclusion: This case series explores the use of innovative sensory technology to collect plantar data (pressure, temperature, step count, and adherence) for DFU detection and early intervention. The results from this case series suggest the importance of sensory technology and remote patient monitoring in providing proactive, preventative care for patients at risk of DFU. This robust plantar data, with the addition of remote patient monitoring, allow for patients to be seen in the clinic when concerns arise, giving providers the opportunity to intervene early and prevent more serious complications, such as wounds, from occurring.

Keywords: diabetic foot ulcer, DFU prevention, digital therapeutics, remote patient monitoring

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Authors: Zelalem Markos Borko

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The quality of life of people with blindness is significantly influenced by the level of resilience they possess. A qualitative approach of the descriptive phenomenological design was employed to address basic study objectives. The researcher purposely selected three blind graduate students from Sidist Kilo Campus and conducted a semi-structured interview to gather data. Data were analyzed by using thematic coding techniques. The present study found that personal characteristics such as commitment, living hope, motivation, positive self-esteem, self-confidence, and communication have shaped resiliency for successful university students with visual disabilities. The finding showed that the school environment is the place in which blind students had developed/experienced social, psychological, and economical competency and hope for their academic and entire life success. Furthermore, the finding showed that blind students had experienced individual, family, school, and community-related risks in the success track. Therefore, governmental and non-governmental organizations should provide training for students with visual impairments that focus on the individual traits that shape resilience for academic success, such as commitment, living hope, motivation, positive self-esteem, self-confidence, and communication and also community-oriented training should be to break the social stigma and discriminations for the individuals with the visual impairment.

Keywords: blind students, risk and protective factors, lived experience, success

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Authors: Mireille Elhajj, Washington Ochieng, Deeph Chana

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The challenges of the rapid growth in the demand for transport has traditionally been seen within the context of the problems of congestion, air quality, climate change, safety, and affordability. However, there are increasing threats including those related to crime such as cyber-attacks that threaten the security of the transport of people and goods. To the best of the authors’ knowledge, this paper presents for the first time, a comprehensive framework for the assessment of the current and future security issues of multi-modal transport systems. The approach or method proposed is based on a structured framework starting with a detailed specification of the transport asset map (transport system architecture), followed by the identification of vulnerabilities. The asset map and vulnerabilities are used to identify the various approaches for exploitation of the vulnerabilities, leading to the creation of a set of threat scenarios. The threat scenarios are then transformed into risks and their categories, and include insights for their mitigation. The consideration of the mitigation space is holistic and includes the formulation of appropriate policies and tactics and/or technical interventions. The quality of the framework is ensured through a structured and logical process that identifies the stakeholders, reviews the relevant documents including policies and identifies gaps, incorporates targeted surveys to augment the reviews, and uses subject matter experts for validation. The approach to categorising security risks is an extension of the current methods that are typically employed. Specifically, the partitioning of risks into either physical or cyber categories is too limited for developing mitigation policies and tactics/interventions for transport systems where an interplay between physical and cyber processes is very often the norm. This interplay is rapidly taking on increasing significance for security as the emergence of cyber-physical technologies, are shaping the future of all transport modes. Examples include: Connected Autonomous Vehicles (CAVs) in road transport; the European Rail Traffic Management System (ERTMS) in rail transport; Automatic Identification System (AIS) in maritime transport; advanced Communications, Navigation and Surveillance (CNS) technologies in air transport; and the Internet of Things (IoT). The framework adopts a risk categorisation scheme that considers risks as falling within the following threat→impact relationships: Physical→Physical, Cyber→Cyber, Cyber→Physical, and Physical→Cyber). Thus the framework enables a more complete risk picture to be developed for today’s transport systems and, more importantly, is readily extendable to account for emerging trends in the sector that will define future transport systems. The framework facilitates the audit and retro-fitting of mitigations in current transport operations and the analysis of security management options for the next generation of Transport enabling strategic aspirations such as systems with security-by-design and co-design of safety and security to be achieved. An initial application of the framework to transport systems has shown that intra-modal consideration of security measures is sub-optimal and that a holistic and multi-modal approach that also addresses the intersections/transition points of such networks is required as their vulnerability is high. This is in-line with traveler-centric transport service provision, widely accepted as the future of mobility services. In summary, a risk-based framework is proposed for use by the stakeholders to comprehensively and holistically assess the security of transport systems. It requires a detailed understanding of the transport architecture to enable a detailed vulnerabilities analysis to be undertaken, creates threat scenarios and transforms them into risks which form the basis for the formulation of interventions.

Keywords: mitigations, risk, transport, security, vulnerabilities

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Authors: Eung-Seok Park, Tae-Chul Jeong, Hyun-Jong Park, Hyun-Woo Jun, Dong-Woo Kang, Ju Lee

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This presents a methodology to determine detail design directions of an 150kW-class IPMSM (interior permanent magnet synchronous motor) and its detail design. The basic design of the stator and rotor was conducted. After dividing the designed models into the best cases and the worst cases based on rotor shape parameters, Sensitivity analysis and 3D Voltage-Inductance Map (3D EL-Map) parameters were analyzed. Then, the design direction for the final model was predicted. Based on the prediction, the final model was extracted with Trend analysis. Lastly, the final model was validated with experiments.

Keywords: PMSM, optimal design, rotor design, voltage-inductance map

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Authors: Atchara Sankom, Warapa Mahakarnchanakul, Ronnarit Rittiron, Tanaboon Sajjaanantakul, Thammasak Thongket

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Vegetables are frequently contaminated with pesticides residues resulting in the most food safety concern among agricultural products. The objective of this work was to develop a method to detect the organophosphate (OP) pesticides residues in vegetables using Near Infrared (NIR) spectroscopy technique. Low concentration (ppm) of OP pesticides in vegetables were investigated. The experiment was divided into 2 sections. In the first section, Chinese kale spiked with different concentrations of chlorpyrifos pesticide residues (0.5-100 ppm) was chosen as the sample model to demonstrate the appropriate conditions of sample preparation, both for a solution or solid sample. The spiked samples were extracted with acetone. The sample extracts were applied as solution samples, while the solid samples were prepared by the dry-extract system for infrared (DESIR) technique. The DESIR technique was performed by embedding the solution sample on filter paper (GF/A) and then drying. The NIR spectra were measured with the transflectance mode over wavenumber regions of 12,500-4000 cm⁻¹. The QuEChERS method followed by gas chromatography-mass spectrometry (GC-MS) was performed as the standard method. The results from the first section showed that the DESIR technique with NIR spectroscopy demonstrated good accurate calibration result with R² of 0.93 and RMSEP of 8.23 ppm. However, in the case of solution samples, the prediction regarding the NIR-PLSR (partial least squares regression) equation showed poor performance (R² = 0.16 and RMSEP = 23.70 ppm). In the second section, the DESIR technique coupled with NIR spectroscopy was applied to the detection of OP pesticides in vegetables. Vegetables (Chinese kale, cabbage and hot chili) were spiked with OP pesticides (chlorpyrifos ethion and profenofos) at different concentrations ranging from 0.5 to 100 ppm. Solid samples were prepared (based on the DESIR technique), then samples were scanned by NIR spectrophotometer at ambient temperature (25+2°C). The NIR spectra were measured as in the first section. The NIR- PLSR showed the best calibration equation for detecting low concentrations of chlorpyrifos residues in vegetables (Chinese kale, cabbage and hot chili) according to the prediction set of R2 and RMSEP of 0.85-0.93 and 8.23-11.20 ppm, respectively. For ethion residues, the best calibration equation of NIR-PLSR showed good indexes of R² and RMSEP of 0.88-0.94 and 7.68-11.20 ppm, respectively. As well as the results for profenofos pesticide, the NIR-PLSR also showed the best calibration equation for detecting the profenofos residues in vegetables according to the good index of R² and RMSEP of 0.88-0.97 and 5.25-11.00 ppm, respectively. Moreover, the calibration equation developed in this work could rapidly predict the concentrations of OP pesticides residues (0.5-100 ppm) in vegetables, and there was no significant difference between NIR-predicted values and actual values (data from GC-MS) at a confidence interval of 95%. In this work, the proposed method using NIR spectroscopy involving the DESIR technique has proved to be an efficient method for the screening detection of OP pesticides residues at low concentrations, and thus increases the food safety potential of vegetables for domestic and export markets.

Keywords: NIR spectroscopy, organophosphate pesticide, vegetable, food safety

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Authors: Brock Buckingham, Zhe Lin, Wenxuan Guo

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Accurate elevation data is critical in deriving topographic attributes for the precision management of crop inputs, especially water and nutrients. Traditional ground-based elevation data acquisition is time consuming, labor intensive, and often inconvenient at the field scale. Various unmanned aerial systems (UAS) provide the capability of generating digital elevation data from high-resolution images. The objective of this study was to compare the performance of two UAS with different global positioning system (GPS) receivers in determining elevation at the field scale. A DJI Phantom 4 Pro and a DJI Phantom 4 RTK(real-time kinematic) were applied to acquire images at three heights, including 40m, 80m, and 120m above ground. Forty ground control panels were placed in the field, and their geographic coordinates were determined using an RTK GPS survey unit. For each image acquisition using a UAS at a particular height, two elevation datasets were generated using the Pix4D stitching software: a calibrated dataset using the surveyed coordinates of the ground control panels and an uncalibrated dataset without using the surveyed coordinates of the ground control panels. Elevation values for each panel derived from the elevation model of each dataset were compared to the corresponding coordinates of the ground control panels. The coefficient of the determination (R²) and the root mean squared error (RMSE) were used as evaluation metrics to assess the performance of each image acquisition scenario. RMSE values for the uncalibrated elevation dataset were 26.613 m, 31.141 m, and 25.135 m for images acquired at 120 m, 80 m, and 40 m, respectively, using the Phantom 4 Pro UAS. With calibration for the same UAS, the accuracies were significantly improved with RMSE values of 0.161 m, 0.165, and 0.030 m, respectively. The best results showed an RMSE of 0.032 m and an R² of 0.998 for calibrated dataset generated using the Phantom 4 RTK UAS at 40m height. The accuracy of elevation determination decreased as the flight height increased for both UAS, with RMSE values greater than 0.160 m for the datasets acquired at 80 m and 160 m. The results of this study show that calibration with ground control panels improves the accuracy of elevation determination, especially for the UAS with a regular GPS receiver. The Phantom 4 Pro provides accurate elevation data with substantial surveyed ground control panels for the 40 m dataset. The Phantom 4 Pro RTK UAS provides accurate elevation at 40 m without calibration for practical precision agriculture applications. This study provides valuable information on selecting appropriate UAS and flight heights in determining elevation for precision agriculture applications.

Keywords: unmanned aerial system, elevation, precision agriculture, real-time kinematic (RTK)

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Authors: Yu-Chuan Huang

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Introduction: There is a higher mortality rate for unplanned transfer to intensive care units. It also needs a longer length of stay and makes the intensive care unit beds cannot be effectively used. It affects the immediate medical treatment of critically ill patients, resulting in a drop in the quality of medical care. Purpose: The purpose of this study was using SOFA and APACHEII score to analyze the mortality rate of the cases transferred from ED to ICU. According to the score that should be provide an appropriate care as early as possible. Methods: This study was a descriptive experimental design. The sample size was estimated at 220 to reach a power of 0.8 for detecting a medium effect size of 0.30, with a 0.05 significance level, using G-power. Considering an estimated follow-up loss, the required sample size was estimated as 242 participants. Data were calculated by medical system of SOFA and APACHEII score that cases transferred from ED to ICU in 2016. Results: There were 233 participants meet the study. The medical records showed 33 participants’ mortality. Age and sex with QSOFA , SOFA and sex with APACHEII showed p>0.05. Age with APCHHII in ED and ICU showed r=0.150, 0,268 (p < 0.001**). The score with mortality risk showed: ED QSOFA is r=0.235 (p < 0.001**), exp(B)=1.685(p = 0.007); ICU SOFA 0.78 (p < 0.001**), exp(B)=1.205(p < 0.001). APACHII in ED and ICU showed r= 0.253, 0.286 (p < 0.001**), exp(B) = 1.041,1.073(p = 0.017,0.001). For SOFA, a cutoff score of above 15 points was identified as a predictor of the 95% mortality risk. Conclusions: The SOFA and APACHE II were calculated based on initial laboratory data in the Emergency Department, and during the first 24 hours of ICU admission. In conclusion, the SOFA and APACHII score is significantly associated with mortality and strongly predicting mortality. Early predictors of morbidity and mortality, which we can according the predicting score, and provide patients with a detail assessment and proper care, thereby reducing mortality and length of stay.

Keywords: SOFA, APACHEII, mortality, ICU

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Authors: Preeyarach Whisetkhan, Malai Taweechotipatr, Ulisa Pachekrepapol

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Elevated level of blood cholesterol or hypercholesterolemia may lead to atherosclerosis and poses a major risk for cardiovascular diseases. Probiotics play a crucial role in human health, and probiotic bacteria that possesses bile salt hydrolase (BSH) activity can be used to lower cholesterol level of the host. The aim of this study was to investigate whether lactic acid bacteria (LAB) isolated from traditional Thai fermented foods were able to exhibit bile salt hydrolase activity and their use in fermented milk. A total of 28 isolates were tested for BSH activity by plate method on MRS agar supplemented with 0.5% sodium salt of taurodeoxycholic acid and incubated at 37°C for 48 h under anaerobic condition. The results showed that FN1-1 and FN23-3 isolates possessed strong BSH activity. FN1-1 and FN23-3 isolates were then identified for phenotype, biochemical characteristics, and genotype (16S rRNA sequencing). FN1-1 isolate showed 99.92% similarity to Lactobacillus pentosus DSM 20314(T), while FN23-3 isolate showed 99.94% similarity to Enterococcus faecium CGMCC1.2136 (T). Lactobacillus pentosus FN1-1 and Enterococcus faecium FN23-3 were tolerant of pH 3-4 and 0.3 and 0.8% bile. Bacterial count and pH of milk fermented with Lactobacillus pentosus FN1-1 at 37°C and 43°C were investigated. The results revealed that Lactobacillus pentosus FN1-1 was able to grow in milk, which led to decrease in pH level. Fermentation at 37°C resulted in faster growth rate than at 43 °C. Lactobacillus pentosus FN1-1 was a candidate probiotic to be used in fermented milk products to reduce the risk of high-cholesterol diseases.

Keywords: probiotics, lactic acid bacteria, bile salt hydrolase, cholesterol

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Authors: Erwin L. Descallar

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Food safety is crucial in protecting the health of consumers, maintaining integrity in the entire food industry, and ensuring regulatory compliance. Food is a universal need for survival, and everyone is at risk of engaging in improper food handling, which increases vulnerability to foodborne illnesses. The level of knowledge or awareness and meat storage practices of students are behaviors influenced by various demographic factors. The Health Belief Model examines the relationship of such demographic factors towards the attitude, perception, and actions of individuals on perceived risk. This study aims to analyze and understand the correlation of said behaviors with course programs, prior food poisoning experience, and food handling of university students. The study employed randomized responses from 89 university students (n=89) under the College of Science at the Polytechnic University of the Philippines–Sta. Mesa (Manila). The results were subjected to measures of central tendency for score ranking and inferential statistics. The statistics were compared using Pearson ‘r’ Product Moment Correlation to determine the degree of relationship between the knowledge and practices on meat storage and safety. No statistically significant differences were found between the course program of students, food poisoning experiences, level of knowledge, and awareness regarding proper meat storage practices. However, increased frequency and involvement in meat handling have shown a positive correlation, indicating that there is a correlation between food handling and proper meat storage practices of university students.

Keywords: meat storage practices, food handling, food safety, meat science and technology

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Authors: Farah Amalina Mohamed Affandi, Redhwan Ahmad Al-Naggar, Seok Mui Wang, Thanikasalam Kathiresan

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Gestational choriocarcinoma is a condition in which there is an abnormal growth or a tumor inside the women’s uterus after conception. It is a type of gestational trophoblastic disease which is relatively rare and malignant. The current epidemiological data of this disease are inadequate. The purposes of this study are to examine the epidemiology of choriocarcinoma and their risk factors based on all available population-based and hospital-based data of the disease. In this study, we searched The MEDLINE and Cumulative Index to Nursing and Allied Health Literature (CINAHL) databases using the keywords ‘choriocarcinoma’, ‘gestational’, ‘gestational choriocarcinoma’ and ‘epidemiology’. We included only human studies published in English between 1995 and 2015 to ensure up to date evidence. Case studies, case reports, animal studies, letters to the editor, news, and review articles were excluded. Retrieved articles were screened in three phases. In the first phase, any articles that did not match the inclusion criteria based solely on titles were excluded. In the second phase, the abstracts of remaining articles were screened thoroughly; any articles that did not meet our inclusion criteria were excluded. In the final phase, full texts of the remaining articles were read and assessed to exclude articles that did not meet the inclusion criteria or any articles that fulfilled the exclusion criteria. Duplicates articles were also removed. Systematic reviews and meta-analysis were excluded. Extracted data were summarized in table and figures descriptively. The reference lists of included studies were thoroughly reviewed in search for other relevant studies. A total of ten studies met all the selection criteria. Nine were retrospective studies and one was cohort study. Total numbers of 4563 cases of choriocarcinoma were reviewed from several countries which are Korea, Japan, South Africa, USA, New Mexico, Finland, Turkey, China, Brazil and The Netherlands. Different studies included different range of age with their mean age of 28.5 to 30.0 years. All studies investigated on the disease’s incidence rate, only two studies examined on the risk factors or associations of the disease. Approximately 20% of the studies showed a reduction in the incidence of choriocarcinoma while the other 80% showed inconsistencies in rate. Associations of age, fertility age, occupations and socio-demographic with the status remains unclear. There is limited information on the epidemiological aspects of gestational choriocarcinoma. The observed results indicated there was a decrease in the incidence rate of gestational choriocarcinoma globally. These could be due to the reduction in the incidence of molar pregnancy and the efficacy of the treatment, mainly by chemotherapy.

Keywords: epidemiology, gestational choriocarcinoma, incidence, prevalence, risk factor

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Authors: Lia Mania, Ketevan Nanobashvili

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Background: The coronavirus disease COVID-19 has become the cause of a global health crisis during the current pandemic. This study aims to fill the paucity of epidemiological studies on the impact of COVID-19 on the oral health of pediatric populations. Methods: It was conducted an observational, cross-sectional study in Georgia, in Tbilisi (capital of Georgia), among 7 to 12-year-old PCR or rapid test-confirmed post-Covid populations in all districts of Tbilisi (10 districts in total). 332 beneficiaries who were infected with Covid within one year were included in the study. The population was selected in schools of Tbilisi according to the principle of cluster selection. A simple random selection took place in the selected clusters. According to this principle, an equal number of beneficiaries were selected in all districts of Tbilisi. By July 1, 2022, according to National Center for Disease Control and Public Health data (NCDC.Ge), the number of test-confirmed cases in the population aged 0-18 in Tbilisi was 115137 children (17.7% of all confirmed cases). The number of patients to be examined was determined by the sample size. Oral screening, microbiological examination of saliva, and administration of oral health questionnaires to guardians were performed. Statistical processing of data was done with SPSS-23. Risk factors were estimated by odds ratio and logistic regression with 95% confidence interval. Results: Statistically reliable differences between the averages of oral health indicators in asymptomatic and symptomatic covid-infected groups are: for caries intensity (DMF+def) t=4.468 and p=0.000, for modified gingival index (MGI) t=3.048, p=0.002, for simplified oral hygiene index (S-OHI) t=4.853; p=0.000. Symptomatic covid-infection has a reliable effect on the oral microbiome (Staphylococcus aureus, Candida albicans, Pseudomonas aeruginosa, Streptococcus pneumoniae, Staphylococcus epidermalis); (n=332; 77.3% vs n=332; 58.0%; OR=2.46, 95%CI: 1.318-4.617). According to the logistic regression, it was found that the severity of the covid infection has a significant effect on the frequency of pathogenic and conditionally pathogenic bacteria in the oral cavity B=0.903 AOR=2.467 (CL 1.318-4.617). Symptomatic covid-infection affects oral health indicators, regardless of the presence of other risk factors, such as parental employment status, tooth brushing behaviors, carbohydrate meal, fruit consumption. (p<0.05). Conclusion: Risk factors (parental employment status, tooth brushing behaviors, carbohydrate consumption) were associated with poorer oral health status in a post-Covid population of 7- to 12-year-old children. However, such a risk factor as symptomatic ongoing covid-infection affected the oral microbiome in terms of the abundant growth of pathogenic and conditionally pathogenic bacteria (Staphylococcus aureus, Candida albicans, Pseudomonas aeruginosa, Streptococcus pneumoniae, Staphylococcus epidermalis) and further worsened oral health indicators. Thus, a close association was established between symptomatic covid-infection and microbiome changes in the post-covid period; also - between the variables of oral health indicators and the symptomatic course of covid-infection.

Keywords: oral microbiome, COVID-19, population based research, oral health indicators

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Authors: Afaneen Anwer, Samara M. Kamil

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Load Forecast required prediction accuracy based on optimal operation and maintenance. A good accuracy is the basis of economic dispatch, unit commitment, and system reliability. A good load forecasting system fulfilled fast speed, automatic bad data detection, and ability to access the system automatically to get the needed data. In this paper, the formulation of the load forecasting is discussed and the solution is obtained by using artificial neural network method. A MATLAB environment has been used to solve the load forecasting schedule of Iraqi super grid network considering the daily load for three years. The obtained results showed a good accuracy in predicting the forecasted load.

Keywords: load forecasting, neural network, back-propagation algorithm, Iraqi power system

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Authors: Madhu Jain, Rakesh Kumar Meena

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This paper investigates a finite M/G/1 fault tolerant multi-component machining system. The system incorporates the features such as standby support, threshold recovery and imperfect coverage make the study closer to real time systems. The performance prediction of M/G/1 fault tolerant system is carried out using recursive approach by treating remaining service time as a supplementary variable. The numerical results are presented to illustrate the computational tractability of analytical results by taking three different service time distributions viz. exponential, 3-stage Erlang and deterministic. Moreover, the cost function is constructed to determine the optimal choice of system descriptors to upgrading the system.

Keywords: fault tolerant, machine repair, threshold recovery policy, imperfect coverage, supplementary variable technique

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Authors: Rajandeep Kaur, Rajeev Gupta

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Background: Chronic myeloid leukemia (CML) is the most common leukaemia in India. The annual incidence of chronic myeloid leukemia in India was originally reported to be 0.8 to 2.2 per 1,00,000 population. CML is a clonal disorder that is usually easily diagnosed because the leukemic cells of more than 95% of patients have a distinctive cytogenetic abnormality, the Philadelphia chromosome (Ph1). The approval of tyrosine kinase inhibitors (TKIs), which target BCR-ABL1 kinase activity, has significantly reduced the mortality rate associated with chronic myeloid leukemia (CML) and revolutionized treatment. Material and Methods: 80 diagnosed cases of CML were taken. Investigations were done. Bone marrow and molecular studies were also done and with EUTOS, patients were stratified into low and high-risk groups and then treatment with Imatinib was given to all patients and the molecular response was evaluated at 6 months and 12 months follow up with BCR-ABL by RT-PCR quantitative assay. Results: In the study population, out of 80 patients in the study population, 40 were females and 40 were males, with M: F is 1:1. Out of total 80 patients’ maximum patients (54) were in 31-60 years age group. Our study showed a most common symptom of presentation is abdominal discomfort followed by fever. Out of the total 80 patients, 25 (31.3%) patients had high EUTOS scores and 55 (68.8%) patients had low EUTOS scores. On 6 months follow up 36.3% of patients had Complete Molecular Response, 16.3% of patients had Major Molecular Response and 47.5% of patients had No Molecular Response but on 12 months follow up 71.3% of patients had Complete Molecular Response, 16.25% of patients had Major Molecular Response and 12.5% patients had No Molecular Response. Conclusion: In this study, we found a significant correlation between EUTOS score and Molecular response at 6 months and 12 months follow up after Imatinib therapy.

Keywords: chronic myeloid leukemia, European treatment and outcome study score, hematological response, molecular response, tyrosine kinase inhibitor

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Authors: Dipanshu Sur, Ratnabali Chakravorty

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Background: Polycystic ovary syndrome (PCOS) is the most common metabolic abnormality such as changes in lipid profile, diabetes, hypertension and metabolic syndrome occurring in young women of reproductive age. Low vitamin D levels were found to be associated with the development of obesity and insulin resistance in women with PCOS. Variants on vitamin D receptor (VDR) gene have also been related to metabolic comorbidities in general population. Aim: The aim of this case-control study was to investigate whether the VDR gene polymorphisms are associated with susceptibility to PCOS. Methods: Women with PCOS and a control group, all aged 16-40 years, were enrolled. Genotyping of VDR Fok-I (rs2228570), VDR Apa-I (rs7975232) as well as GC (rs2282679), DHCR7 (rs12785878) SNPs between groups were determined by using direct sequencing. Serum 25-hydroxyvitamin D [25(OH)] levels were measured by ELISA. Results: Mean serum 25(OH)D in the PCOS and control samples were 19.08±7 and 23.27±6.03 (p=0.048) which were significantly lower in PCOS patients compared with controls. CC genotype of the VDR Apa-I SNP was same frequent in PCOS (25.6%) and controls (25.6%) (OR: 0.9995; 95%CI: 0.528 to 1.8921; p= 0.9987). The CC genotype was also significantly associated with both lower E2 (p=0.031) and Androstenedione levels (p=0.062). We observed a significant association of GC polymorphism with 25(OH)D levels. PCOS women carrying the GG genotype (in GC genes) had significantly higher risk for vitamin D deficiency than women carrying the TT genotype. Conclusions: In conclusion, data from this study indicate that vitamin D levels are lower, and vitamin D deficiency more frequent, in PCOS than in controls. The present findings suggest that the Apa-I, Fok-I polymorphism of the VDR gene is associated with PCOS and seems to modulate ovarian steroid secretion. Further studies are needed to better clarify the biological mechanisms by which the polymorphism influences PCOS risk.

Keywords: vitamin D receptor, polymorphism, vitamin D, polycystic ovary syndrome

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Authors: Vignesh Ratnaraj, Jaewon Chang

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Background: Frailty is associated with poorer outcomes in cardiac surgery, but the heterogeneity in frailty assessment tools makes it difficult to ascertain its true impact in cardiac surgery. Slow gait speed is a simple, validated, and reliable marker of frailty. We performed a systematic review and meta-analysis to examine the effect of slow gait speed on postoperative cardiac surgical patients. Methods: PubMED, MEDLINE, and EMBASE databases were searched from January 2000 to August 2021 for studies comparing slow gait speed and “normal” gait speed. The primary outcome was in-hospital mortality. Secondary outcomes were composite mortality and major morbidity, AKI, stroke, deep sternal wound infection, prolonged ventilation, discharge to a healthcare facility, and ICU length of stay. Results: There were seven eligible studies with 36,697 patients. Slow gait speed was associated with an increased likelihood of in-hospital mortality (risk ratio [RR]: 2.32; 95% confidence interval [CI]: 1.87–2.87). Additionally, they were more likely to suffer from composite mortality and major morbidity (RR: 1.52; 95% CI: 1.38–1.66), AKI (RR: 2.81; 95% CI: 1.44–5.49), deep sternal wound infection (RR: 1.77; 95% CI: 1.59–1.98), prolonged ventilation >24 h (RR: 1.97; 95% CI: 1.48–2.63), reoperation (RR: 1.38; 95% CI: 1.05–1.82), institutional discharge (RR: 2.08; 95% CI: 1.61–2.69), and longer ICU length of stay (MD: 21.69; 95% CI: 17.32–26.05). Conclusion: Slow gait speed is associated with poorer outcomes in cardiac surgery. Frail patients are twofold more likely to die during hospital admission than non-frail counterparts and are at an increased risk of developing various perioperative complications.

Keywords: cardiac surgery, gait speed, recovery, frailty

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Authors: Woo-Young Jung, Minho Kwon

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Seismic design criteria based on performance of structures have recently been adopted by practicing engineers in response to destructive earthquakes. A simple but efficient structural-analysis tool capable of predicting both the strength and ductility is needed to analyze reinforced concrete (RC) structures under such event. A three-dimensional lattice model is developed in this study to analyze torsions in high-strength RC members. Optimization techniques for determining optimal variables in each lattice model are introduced. Pure torsion tests of RC members are performed to validate the proposed model. Correlation studies between the numerical and experimental results confirm that the proposed model is well capable of representing salient features of the experimental results.

Keywords: torsion, non-linear analysis, three-dimensional lattice, high-strength concrete

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Authors: N. Boutra, N. Ravot, J. Benoit, O. Picon

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Submarine power cables used for offshore wind farms electric energy distribution and transmission are subject to numerous threats. Some of the risks are associated with transport, installation and operating in harsh marine environment. This paper describes the feasibility of an electromagnetic low frequency sensing technique for submarine power cable failure prediction. The impact of a structural damage shape and material variability on the induced electric field is evaluated. The analysis is performed by modeling the cable using the finite element method, we use sensitivity analysis in order to identify the main damage characteristics affecting electric field variation. Lastly, we discuss the results obtained.

Keywords: electromagnetism, finite element method, sensitivity analysis, submarine power cables

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Authors: A. Medjnoun, R. Bahar

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The disorders caused by the shrinking-swelling phenomenon are prevalent in arid and semi-arid in the presence of swelling clay. This soil has the characteristic of changing state under the effect of water solicitation (wetting and drying). A set of geotechnical parameters is necessary for the characterization of this soil type, such as state parameters, physical and chemical parameters and mechanical parameters. Some of these tests are very long and some are very expensive, hence the use or methods of predictions. The complexity of this phenomenon and the difficulty of its characterization have prompted researchers to use several identification parameters in the prediction of swelling potential. This document is an analytical and statistical study of geotechnical parameters affecting the potential of swelling clays. This work is performing on a database obtained from investigations swelling Algerian soil. The obtained observations have helped us to understand the soil swelling structure and its behavior.

Keywords: analysis, estimated model, parameter identification, swelling of clay

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Authors: Temesgen Kassa Getahun, Gezahegn Mamo, Beksisa Urge

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A cross-sectional study was conducted from December 2019 to May 2020 with the aim of determining the seroprevalence of brucellosis in dairy cows and their owners in the central highland of Oromia, Ethiopia. A total of 352 blood samples from dairy cattle, 149 from animal owners, and 17 from farm workers were collected and initially screened using the Rose Bengal Plate test and confirmed by the Complement Fixation test. Overall seroprevalence was 0.6% (95% CI: 0.0016–0.0209) in bovines and 1.2% (95% CI: 0.0032–0.0427) in humans. Market-based stock replacement (OR=16.55, p=0.002), breeding by artificial insemination (OR=7.58, p=0.05), and parturition pen (OR = 11.511, p=0.027) were found to be significantly associated with the seropositivity for Brucella infection in dairy cattle. Human housing (OR=1.8, p=0.002), contact with an aborted fetus (OR=21.19, p=0.017), drinking raw milk from non-aborted (OR=24.99, p=0.012), aborted (OR=5.72, p=0.019) and retained fetal membrane (OR=4.22, p=0.029) cows had a significant influence on human brucellosis. A structured interview question was administered to 284 respondents. Accordingly, most respondents had no knowledge of brucellosis (93.3%), and in contrast, 90% of them consumed raw milk. In conclusion, the present seroprevalence study revealed that brucellosis was low among dairy cattle and exposed individuals in the study areas. However, since there were no control strategies implemented in the study areas, there is a potential risk of transmission of brucellosis in dairy cattle and the exposed human population in the study areas. Implementation of a test and slaughter strategy with compensation to farmers is recommended, while in the case of human brucellosis, continuous social training and implementing one health approach framework must be applied.

Keywords: abortion, bovine brucellosis, human brucellosis, risk factors, seroprevalence

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Authors: Y. Galerkin, K. Soldatova, A. Drozdov

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The 6th version of Universal modeling method for centrifugal compressor stage calculation is described. Identification of the new mathematical model was made. As a result of identification the uniform set of empirical coefficients is received. The efficiency definition error is 0,86 % at a design point. The efficiency definition error at five flow rate points (except a point of the maximum flow rate) is 1,22 %. Several variants of the stage with 3D impellers designed by 6th version program and quasi three-dimensional calculation programs were compared by their gas dynamic performances CFD (NUMECA FINE TURBO). Performance comparison demonstrated general principles of design validity and leads to some design recommendations.

Keywords: compressor design, loss model, performance prediction, test data, model stages, flow rate coefficient, work coefficient

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Authors: Shahram Jamali, Samira Hamed

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One of the open issues in Random Early Detection (RED) algorithm is how to set its parameters to reach high performance for the dynamic conditions of the network. Although original RED uses fixed values for its parameters, this paper follows a model-based approach to upgrade performance of the RED algorithm. It models the routers queue behavior by using the Markov model and uses this model to predict future conditions of the queue. This prediction helps the proposed algorithm to make some tunings over RED's parameters and provide efficiency and better performance. Widespread packet level simulations confirm that the proposed algorithm, called Markov-RED, outperforms RED and FARED in terms of queue stability, bottleneck utilization and dropped packets count.

Keywords: active queue management, RED, Markov model, random early detection algorithm

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Authors: Sofia Stoica

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In this paper, we use historical data to predict the stock price of a tech company. To this end, we use a dataset consisting of the stock prices in the past five years of ten major tech companies – Adobe, Amazon, Apple, Facebook, Google, Microsoft, Netflix, Oracle, Salesforce, and Tesla. We experimented with a variety of models– a linear regressor model, K nearest Neighbors (KNN), a sequential neural network – and algorithms - Multiplicative Weight Update, and AdaBoost. We found that the sequential neural network performed the best, with a testing error of 0.18%. Interestingly, the linear model performed the second best with a testing error of 0.73%. These results show that using historical data is enough to obtain high accuracies, and a simple algorithm like linear regression has a performance similar to more sophisticated models while taking less time and resources to implement.

Keywords: finance, machine learning, opening price, stock market

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Authors: Z. Bayat

Abstract:

A quantitative structure–property relationship (QSPR) study was performed to develop models those relate the structures of 65 Kovats retention index (RI) of adamantane derivatives. Molecular descriptors derived solely from 3D structures of the molecular compounds. The usefulness of the quantum chemical descriptors, calculated at the level of the DFT theories using 6-311+G** basis set for QSAR study of adamantane derivatives was examined. The use of descriptors calculated only from molecular structure eliminates the need to experimental determination of properties for use in the correlation and allows for the estimation of RI for molecules not yet synthesized. The prediction results are in good agreement with the experimental value. A multi-parametric equation containing maximum Four descriptors at B3LYP/6-31+G** method with good statistical qualities (R2train=0.913, Ftrain=97.67, R2test=0.770, Ftest=3.21, Q2LOO=0.895, R2adj=0.904, Q2LGO=0.844) was obtained by Multiple Linear Regression using stepwise method.

Keywords: DFT, adamantane, QSAR, Kovat

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Authors: Behzad Niknam, Kourosh Shahriar, Hassan Madani

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This paper demonstrates the applicability of Hybrid Neural Networks that combine with back propagation networks (BPN) and Genetic Algorithms (GAs) for predicting the flame length of tunnel fire A hybrid neural network model has been developed to predict the flame length of tunnel fire based parameters such as Fire Heat Release rate, air velocity, tunnel width, height and cross section area. The network has been trained with experimental data obtained from experimental work. The hybrid neural network model learned the relationship for predicting the flame length in just 3000 training epochs. After successful learning, the model predicted the flame length.

Keywords: tunnel fire, flame length, ANN, genetic algorithm

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