42 research outputs found
Association of junk food consumption with overweight-obesity among preclinical medical students of Shahid Beheshti University of Medical Sciences
Background: The consumption of high energy and low nutritional content foods, which are known as junk foods, is considered as one of the main causes of obesity particularly in adolescents. The aim of this study was to determine the association of junk food consumption with overweight-obesity among preclinical medical students of Shahid Beheshti University of Medical Sciences (SBMU).
Methods: In this cross-sectional study, preclinical students of SBMU were recruited by simple randomized sampling. Study participants included 18-23 years old male and female. Demographic and socio-economic data were collected by a questionnaire. Information relating to the consumption of junk foods was provided by a 24-items self-administered semi-quantitative food frequency questioner (F.F.Q). The relationship between the consumption of fast food and overweight-obesity (O.O) was analyzed using IBM SPSS Statistics for Windows, Version 21.0. through binary logistic regression method.
Results: A total of 186 students participated in this study. Overweight-obese students (BMI 25) accounted for 63 (34%) of the total participants. A total of 58 (31.1%) students consumed fast foods more than 1.52 serving/week. Students who were at the highest tertile of fast food consumption, had a higher chance of O.O (OR=2.42, 95% CI=1.17-4.99, P=0.01) in comparison with those in the lowest tertile (OR=2.21, 95% CI=1.01-4.84, P=0.04). After adjustment for age and socioeconomic factors, this chance was increased (OR=3.824, 95% CI=1.66-8.811, P=0.002); but, after adjusting lifestyle variables (physical activity) this relationship was not significant anymore (OR=2.247, 95% CI=0.998-5.058, P=0.05).
Conclusion: The findings of this study represent a positive association between fast-food consumption and O.O in medical students
Human Arm simulation for interactive constrained environment design
During the conceptual and prototype design stage of an industrial product, it
is crucial to take assembly/disassembly and maintenance operations in advance.
A well-designed system should enable relatively easy access of operating
manipulators in the constrained environment and reduce musculoskeletal disorder
risks for those manual handling operations. Trajectory planning comes up as an
important issue for those assembly and maintenance operations under a
constrained environment, since it determines the accessibility and the other
ergonomics issues, such as muscle effort and its related fatigue. In this
paper, a customer-oriented interactive approach is proposed to partially solve
ergonomic related issues encountered during the design stage under a
constrained system for the operator's convenience. Based on a single objective
optimization method, trajectory planning for different operators could be
generated automatically. Meanwhile, a motion capture based method assists the
operator to guide the trajectory planning interactively when either a local
minimum is encountered within the single objective optimization or the operator
prefers guiding the virtual human manually. Besides that, a physical engine is
integrated into this approach to provide physically realistic simulation in
real time manner, so that collision free path and related dynamic information
could be computed to determine further muscle fatigue and accessibility of a
product designComment: International Journal on Interactive Design and Manufacturing
(IJIDeM) (2012) 1-12. arXiv admin note: substantial text overlap with
arXiv:1012.432
Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019
Background: In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries. Methods: GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw values of the posterior distribution. Findings: Global health has steadily improved over the past 30 years as measured by age-standardised DALY rates. After taking into account population growth and ageing, the absolute number of DALYs has remained stable. Since 2010, the pace of decline in global age-standardised DALY rates has accelerated in age groups younger than 50 years compared with the 1990–2010 time period, with the greatest annualised rate of decline occurring in the 0–9-year age group. Six infectious diseases were among the top ten causes of DALYs in children younger than 10 years in 2019: lower respiratory infections (ranked second), diarrhoeal diseases (third), malaria (fifth), meningitis (sixth), whooping cough (ninth), and sexually transmitted infections (which, in this age group, is fully accounted for by congenital syphilis; ranked tenth). In adolescents aged 10–24 years, three injury causes were among the top causes of DALYs: road injuries (ranked first), self-harm (third), and interpersonal violence (fifth). Five of the causes that were in the top ten for ages 10–24 years were also in the top ten in the 25–49-year age group: road injuries (ranked first), HIV/AIDS (second), low back pain (fourth), headache disorders (fifth), and depressive disorders (sixth). In 2019, ischaemic heart disease and stroke were the top-ranked causes of DALYs in both the 50–74-year and 75-years-and-older age groups. Since 1990, there has been a marked shift towards a greater proportion of burden due to YLDs from non-communicable diseases and injuries. In 2019, there were 11 countries where non-communicable disease and injury YLDs constituted more than half of all disease burden. Decreases in age-standardised DALY rates have accelerated over the past decade in countries at the lower end of the SDI range, while improvements have started to stagnate or even reverse in countries with higher SDI. Interpretation: As disability becomes an increasingly large component of disease burden and a larger component of health expenditure, greater research and developm nt investment is needed to identify new, more effective intervention strategies. With a rapidly ageing global population, the demands on health services to deal with disabling outcomes, which increase with age, will require policy makers to anticipate these changes. The mix of universal and more geographically specific influences on health reinforces the need for regular reporting on population health in detail and by underlying cause to help decision makers to identify success stories of disease control to emulate, as well as opportunities to improve. Funding: Bill & Melinda Gates Foundation. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licens
Hybrid adaptive battery parameter estimation approach for equivalent circuit model toolbox
This article presents a software tool for estimating the equivalent circuit model (ECM) of lithium-ion batteries using battery voltage and current datasets based on dynamic and static RC loop curve fitting techniques. This tool calculates the state of charge (SOC) of a battery and clusters experimental data based on the SOC. This provides the possibility of determining the equivalent circuit of the battery. Also, by leveraging the unique structure of the equivalent circuit, the method of estimating the effectiveness of this tool is integrated. The supplementary idea of this article is based on the calculation of the best method of estimating the equivalent circuit based on the hybrid adaptive battery parameter estimation (HABPE) based on model architecture and fitting it accordingly. By comparing the data from the extracted model with the experimental data of the battery, an accuracy of 82–87 % has been achieved, depending on the type of battery model. This method provides an easy and accurate approach to obtaining battery parameters and constructing its equivalent circuit for future applications
A single-period analysis of a two-echelon inventory system with dependent supply uncertainty
Disruptions and random supplies have been important sources of uncertainty that should be considered in the design and control of supply chains. There have been many real world examples in which a single catastrophic event has simultaneously degraded the capabilities of several suppliers leading to considerable erosion of profits and goodwill for a company. However, the literature on analytical models that account for the dependence nature of disruptions and its impact on supply chain performance is sparse. In this paper, we consider an m-manufacturer, 1-retailer, newsvendor inventory system with stochastically dependent manufacturing capacities, caused by random disruptions that may simultaneously inflict damages to the capacities of the manufacturers. We develop the structural/analytical properties of key performance measures and optimal inventory policies for the multi-source and assembly inventory systems. We show that stochastic dependence in disruptions can have opposite effects on system performance in the multi-source and assembly systems. While risk diversification is preferred in the multi-source system, risk concentration is preferred in the assembly system. Our results also suggest that, if the retailer ignores the effect of dependent disruptions, then in the multi-source structure, it would underestimate the cost, overestimate the fill rate, and order more units than the optimum; however, in the assembly structure, the opposite would happen. We perform a comprehensive numerical study to validate our analytical results and generate useful managerial and operational insights for effective risk management of supply chains in the presence of dependent supply uncertainty.Dependent supply disruptions Multi-source and assembly structures Supermodular and orthant dependence orders Copula Optimal inventory policy Performance bounds
Does motivational interviewing improve the weight management process in adolescents? Protocol for a systematic review and meta-analysis
Abstract Background Data on the effects of motivational interviewing (MI) on modifying unhealthy lifestyles and promoting weight status during childhood is controversial. Adolescents are more prone to assume higher personal responsibilities for behavioral changes. This study aims to investigate whether MI will improve weight management process in adolescents. Methods/design A systematic review will be conducted on clinical trials, assessing the effect of MI on weight management processes in adolescents, aged 10 to 19 years. The primary objective is to assess the efficacy of MI in controlling weight-related measures in overweight and obese adolescents. Secondary objectives are assessing the efficacy of MI on obesity-related behaviors and cognitive abilities considering heterogeneity in outcomes of primary studies in different MI settings. Main data sources include MEDLINE/PubMed, Scopus, Embase, Web of Science, Cochrane, and PsycINFO from 1980 to May, 2018, with no language restrictions. Study selection, data extraction, and risk of bias assessment will be performed by two independent reviewers. A meta-analysis will be conducted on relevant outcomes. Data will be analyzed for outcome of interest using the 95% confidence interval (CI) of an estimate for dichotomous outcomes and mean differences (MDs) for continious outcomes. Cochrane’s Q statistic and the I 2 statistic will be performed to evaluate the heterogeneity. Subgroup analysis and suitable analytical strategies will be conducted to identify the potential sources of heterogeneity. As we expect a high heterogeneity in our included studies, pooled risk ratios (RRs) and 95% CI will be calculated to estimate the overall effect sizes, using meta-regression models or finite mixture modeling through conducting random effect methods. GRADE system will be used to evaluate the certainty of evidence. We will also use subgroup analysis and the GRADE system to investigate the effect of methodological quality of primary studies on results of meta-analysis. Funnel plots and egger and beggs test and plot will be implemented to assess publication bias. Discussion The results of this systematic review will provide more insights regarding the effect of MI on weight management in adolescents and will be useful for future research and health promotion programs in this age group. Systematic review registration PROSPERO 2017:CRD42017069813
BIOSTRATIGRAPHY AND REGIONAL ASPECTS OF THE TARBUR FORMATION (MAASTRICHTIAN) IN CENTRAL ZAGROS, SOUTHWEST IRAN
The aim of this study is to investigate the biostratigraphy and regional stratigraphy of the Maastrichtian deposits (Tarbur Formation) in the high outreaches of the Zagros Mountains in Chahar Mahal and Bakhtiyari Province, southwest Iran. The thickness of the investigated sequences is about 600 m in Tang-e-Vanak, 156 m inTang-e-Zendan,and 111 m in Kuh-e-Dozdaran sections. Shale and marls of the Gurpi Fm. (Campanian) mark the lower lithostratigraphic limit of the Tarbur Fm. in Kuh-e-Dozdaran section, whereas its upper limit is disconformably distinguished by the dolomitic Jahrom Fm. (Eocene). The Tarbur Fm. in Tang-e-Vanak andTang-e-Zendansections overlies the clastic Amiran Fm. (Maastrichtian) and is truncated with a sharp disconformity by the white dolomites of Shahbazan Fm. (Eocene). Biostratigraphically, the Tarbur Fm. is characterized by a Loftusia-Omphalocyclus assemblage zone, indicating a Maastrichtian age. Within this biozone, three regional subbiozones are proposed. They are: the Loftusia arabica range subzone , the Loftusia persica interval subzone , and the Loftusia baykali interval subzone . Based on the foraminiferal content, the age of the Tarbur Fm. in Kuh-e-Dozdaran section is assigned to the lower-middle parts of the Maastrichtian. Likewise, the Tarbur Fm. in Tang-e-Vanak and theTang-e-Zendansections is Maastrichtian in age, possibly extending locally into the Paleocene.The identification of the biostratigraphic limits of the Tarbur Fm. in the studied areas assists the reconstruction of the sedimentary basin in the Late Cretaceous.
Technology selection and sizing of on-board energy recovery system to reduce fuel consumption of diesel-electric mine haul trucks
Installing an energy recovery system (ERS) on a mining haul truck has the potential to save a significant amount of fuel by recovering energy while descending into the pit and reinjecting this energy to reduce fuel usage for acceleration and ascent out of the pit. This chapter presents an initial investigation into the technical and economic feasibility of such an ERS for diesel-electric drive mine haul trucks. A simulation model incorporating the haul route, the truck and drive system characteristics, and the ERS is employed to evaluate the changes to fuel used and impact on payload for an ERS of a specific technology and size on a given pit depth, from which cost savings and fuel savings per tonne of material moved are inferred. Lithium-ion batteries and electrolytic double-layer capacitors were found to be generally infeasible due to, respectively, poor charging rate and cycle life, and low energy density. Both lithium-ion capacitors and electromechanical flywheels promise fuel efficiency improvements of greater than 10% for a large range of pit depths. Electromechanical flywheels are judged the most cost-effective option, with an expected payback period of less than 1.2\ua0years