Search results for: least square estimation (LSE)

Authors: Sushma Ghildyal, Sanjay Kumar Singh

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The present study was undertaken with the purpose to understand the relationship of lifestyle and Socio-Economic status with child obesity among 1000 boys aged from 16 to 18 years of Varanasi District of Uttar Pradesh State in India. The study was conducted in both urban and rural area of the District. Ten schools i.e. five from urban area and five from rural area were selected by using purposive sampling. Healthy boys of class 10th, 11th and 12th were taken as subjects for the study. Prior consent was obtained from school authority. Anthropometric measurements were taken from each subject. Anthropometric measurements were Standing Height, Weight, Biceps skin folds, Triceps skin folds, Sub-scapular skin folds and Supra-iliac skin folds taken by Lange’s skin fold caliper. Lifestyle and Socio-Economic Status were obtained by questionnaires. In order to assess the BMI, Body fat %, Lifestyle and Socio-Economic Status; descriptive analyses were done. To find out the significant association of obesity with lifestyle and Socio-Economic Status Chi-square test was used. To find out significant difference between obesity of Urban and Rural children t-test was applied. Level of significance was set at 0.05 level. The conclusions drawn were: (1) The result showed that in urban area Varanasi District of Uttar Pradesh 0.6% children were in very high level adaptive lifestyle, 6.2% were in high level adaptive lifestyle, 25.4% above average level adaptive lifestyle, 47.8% moderately adaptive lifestyle, 3.6% and 0.4% low and very low level adaptive lifestyle. (2) In rural area Varanasi District of Uttar Pradesh 0.00% children were in very high level adaptive lifestyle, 9.4% were in high level adaptive lifestyle, 24.8% average level adaptive lifestyle, 47.0% moderately adaptive lifestyle, 15.2% below average and 3.0% very low level adaptive lifestyle.(3) In urban area 12.8% were in upper class Socio-Economic Status, 56.6% in upper middle class Socio-Economic Status, 30.2% in middle class Socio-Economic Status and 0.2% in lower middle class Socio-Economic Status. (4) In rural area 1.4% were in upper class Socio-Economic Status, 15.2% in upper middle class Socio-Economic Status, 51.6% in middle class Socio-Economic Status and 0.8% in lower middle class Socio-Economic Status. (5) In urban area 21.2% children of 16-18 years were obese. (6) In rural area 0.2% children of 16-18 years were obese. (7) In overall Varanasi District of Uttar Pradesh 10.7% children of 16-18 years were obese. (8) There was no significant relationship of obesity with Lifestyle of urban area children of 16-18 years. (9) There was significant relationship of obesity with Socio-Economic Status of urban area children of 16-18 years (10) There was no significant relationship of obesity with Lifestyle of rural area children of 16-18 years of Varanasi District Uttar Pradesh. (11) There was significant relationship of obesity with Socio-Economic Status of rural area children of 16-18 years. (12) Results showed significant difference between urban and rural area children of 16-18 years in respect to obesity of Varanasi District of Uttar Pradesh.

Keywords: lifestyle, obesity, rural area, socio-economic status, urban area

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Authors: Moustafa Osman Mohammed

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Construction industry, as one of the main contributor in depletion of natural resources, influences climate change. This paper discusses incremental and evolutionary development of the proposed models for optimization of a life-cycle analysis to explicit strategy for evaluation systems. The main categories are virtually irresistible for introducing uncertainties, uptake composite structure model (CSM) as environmental management systems (EMSs) in a practice science of evaluation small and medium-sized enterprises (SMEs). The model simplified complex systems to reflect nature systems’ input, output and outcomes mode influence “framework measures” and give a maximum likelihood estimation of how elements are simulated over the composite structure. The traditional knowledge of modeling is based on physical dynamic and static patterns regarding parameters influence environment. It unified methods to demonstrate how construction systems ecology interrelated from management prospective in procedure reflects the effect of the effects of engineering systems to ecology as ultimately unified technologies in extensive range beyond constructions impact so as, - energy systems. Sustainability broadens socioeconomic parameters to practice science that meets recovery performance, engineering reflects the generic control of protective systems. When the environmental model employed properly, management decision process in governments or corporations could address policy for accomplishment strategic plans precisely. The management and engineering limitation focuses on autocatalytic control as a close cellular system to naturally balance anthropogenic insertions or aggregation structure systems to pound equilibrium as steady stable conditions. Thereby, construction systems ecology incorporates engineering and management scheme, as a midpoint stage between biotic and abiotic components to predict constructions impact. The later outcomes’ theory of environmental obligation suggests either a procedures of method or technique that is achieved in sustainability impact of construction system ecology (SICSE), as a relative mitigation measure of deviation control, ultimately.

Keywords: sustainability, environmental impact assessment, environemtal management, construction ecology

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Authors: Edwin Calderon-Mendoza, Patrick Schweitzer, Serge Weber

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Series arc faults appear frequently and unpredictably in low voltage distribution systems. Many methods have been developed to detect this type of faults and commercial protection systems such AFCI (arc fault circuit interrupter) have been used successfully in electrical networks to prevent damage and catastrophic incidents like fires. However, these devices do not allow series arc faults to be located on the line in operating mode. This paper presents a location algorithm for series arc fault in a low-voltage indoor power line in an AC 230 V-50Hz home network. The method is validated through simulations using the MATLAB software. The fault location method uses electrical parameters (resistance, inductance, capacitance, and conductance) of a 49 m indoor power line. The mathematical model of a series arc fault is based on the analysis of the V-I characteristics of the arc and consists basically of two antiparallel diodes and DC voltage sources. In a first step, the arc fault model is inserted at some different positions across the line which is modeled using lumped parameters. At both ends of the line, currents and voltages are recorded for each arc fault generation at different distances. In the second step, a fault map trace is created by using signature coefficients obtained from Kirchhoff equations which allow a virtual decoupling of the line’s mutual capacitance. Each signature coefficient obtained from the subtraction of estimated currents is calculated taking into account the Discrete Fast Fourier Transform of currents and voltages and also the fault distance value. These parameters are then substituted into Kirchhoff equations. In a third step, the same procedure described previously to calculate signature coefficients is employed but this time by considering hypothetical fault distances where the fault can appear. In this step the fault distance is unknown. The iterative calculus from Kirchhoff equations considering stepped variations of the fault distance entails the obtaining of a curve with a linear trend. Finally, the fault distance location is estimated at the intersection of two curves obtained in steps 2 and 3. The series arc fault model is validated by comparing current registered from simulation with real recorded currents. The model of the complete circuit is obtained for a 49m line with a resistive load. Also, 11 different arc fault positions are considered for the map trace generation. By carrying out the complete simulation, the performance of the method and the perspectives of the work will be presented.

Keywords: indoor power line, fault location, fault map trace, series arc fault

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Authors: Marta Nawrocka

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In each of the legal proceedings, in which expert evidence is carried out, a major concern is the assessment of the evidential value of expert reports. Judicial institutions, while making decisions, rely heavily on the expert reports, because they usually do not possess 'special knowledge' from a certain fields of science which makes it impossible for them to verify the results presented in the processes. In handwriting studies, the standards of analysis are developed. They unify procedures used by experts in comparing signs and in constructing expert reports. However, the methods used by experts are usually of a qualitative nature. They rely on the application of knowledge and experience of expert and in effect give significant range of margin in the assessment. Moreover, the standards used by experts are still not very precise and the process of reaching the conclusions is poorly understood. The above-mentioned circumstances indicate that expert opinions in the field of handwriting analysis, for many reasons, may not be sufficiently reliable. It is assumed that this state of affairs has its source in a very low level of intersubjectivity of measuring scales and analysis procedures, which consist elements of this kind of analysis. Intersubjectivity is a feature of cognition which (in relation to methods) indicates the degree of consistency of results that different people receive using the same method. The higher the level of intersubjectivity is, the more reliable and credible the method can be considered. The aim of the conducted research was to determine the degree of intersubjectivity of the methods used by the experts from the scope of handwriting analysis. 30 experts took part in the study and each of them received two signatures, with varying degrees of readability, for analysis. Their task was to distinguish graphic characteristics in the signature, estimate the evidential value of the found characteristics and estimate the evidential value of the signature. The obtained results were compared with each other using the Alpha Krippendorff’s statistic, which numerically determines the degree of compatibility of the results (assessments) that different people receive under the same conditions using the same method. The estimation of the degree of compatibility of the experts' results for each of these tasks allowed to determine the degree of intersubjectivity of the studied method. The study showed that during the analysis, the experts identified different signature characteristics and attributed different evidential value to them. In this scope, intersubjectivity turned out to be low. In addition, it turned out that experts in various ways called and described the same characteristics, and the language used was often inconsistent and imprecise. Thus, significant differences have been noted on the basis of language and applied nomenclature. On the other hand, experts attributed a similar evidential value to the entire signature (set of characteristics), which indicates that in this range, they were relatively consistent.

Keywords: forensic sciences experts, handwriting analysis, inter-rater reliability, reliability of methods

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Authors: Daniel Osorio, Andreas Klenk, Stefan Weihe, Andreas Kopp, Frank Rödiger

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Future power plants currently face high design requirements due to worsening climate change and environmental restrictions, which demand high operational flexibility, superior thermal performance, minimal emissions, and higher cyclic capability. The aim of the paper is, therefore, to investigate the creep and thermo-mechanical material behavior of improved materials experimentally and welded joints at component scale under near-to-service operating conditions, which are promising for application in highly efficient and flexible future power plants. These materials promise an increase in flexibility and a reduction in manufacturing costs by providing enhanced creep strength and, therefore, the possibility for wall thickness reduction. At the temperature range between 550°C and 625°C, the investigation focuses on the in-phase thermo-mechanical fatigue behavior of dissimilar welded joints of conventional materials (ferritic and martensitic material T24 and T92) to nickel-based alloys (A617B and HR6W) by means of membrane test panels. The temperature and external load are varied in phase during the test, while the internal pressure remains constant. At the temperature range between 650°C and 750°C, it focuses on the creep behavior under multiaxial stress loading of similar and dissimilar welded joints of high temperature resistant nickel-based alloys (A740H, A617B, and HR6W) by means of a thick-walled-component test. In this case, the temperature, the external axial load, and the internal pressure remain constant during testing. Numerical simulations are used for the estimation of the axial component load in order to induce a meaningful damage evolution without causing a total component failure. Metallographic investigations after testing will provide support for understanding the damage mechanism and the influence of the thermo-mechanical load and multiaxiality on the microstructure change and on the creep and TMF- strength.

Keywords: creep, creep-fatigue, component behaviour, weld joints, high temperature material behaviour, nickel-alloys, high temperature resistant steels

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Authors: K. Rawojć, J. Miszczyk, A. Możdżeń, A. Panek, J. Swakoń, M. Rydygier

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Due to the mitotic delay, poor mitotic index and disappearance of lymphocytes from peripheral blood circulation, assessing the DNA damage after high dose exposure is less effective. Conventional chromosome aberration analysis or cytokinesis-blocked micronucleus assay do not provide an accurate dose estimation or radiosensitivity prediction in doses higher than 6.0 Gy. For this reason, there is a need to establish reliable methods allowing analysis of biological effects after exposure in high dose range i.e., during particle radiotherapy. Lately, Premature Chromosome Condensation (PCC) has become an important method in high dose biodosimetry and a promising treatment modality to cancer patients. The aim of the study was to evaluate the usefulness of drug-induced PCC scoring procedure in an experimental mode, where 100 G2/M cells were analyzed in different dose ranges. To test the consistency of obtained results, scoring was performed by 3 independent persons in the same mode and following identical scoring criteria. Whole-body exposure was simulated in an in vitro experiment by irradiating whole blood collected from healthy donors with 60 MeV protons and 250 keV X-rays, in the range of 4.0 – 20.0 Gy. Drug-induced PCC assay was performed on human peripheral blood lymphocytes (HPBL) isolated after in vitro exposure. Cells were cultured for 48 hours with PHA. Then to achieve premature condensation, calyculin A was added. After Giemsa staining, chromosome spreads were photographed and manually analyzed by scorers. The dose-effect curves were derived by counting the excess chromosome fragments. The results indicated adequate dose estimates for the whole-body exposure scenario in the high dose range for both studied types of radiation. Moreover, compared results revealed no significant differences between scores, which has an important meaning in reducing the analysis time. These investigations were conducted as a part of an extended examination of 60 MeV protons from AIC-144 isochronous cyclotron, at the Institute of Nuclear Physics in Kraków, Poland (IFJ PAN) by cytogenetic and molecular methods and were partially supported by grant DEC-2013/09/D/NZ7/00324 from the National Science Centre, Poland.

Keywords: cell response to radiation exposure, drug induced premature chromosome condensation, premature chromosome condensation procedure, proton therapy

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Authors: Nivedhitha Venkatakrishnan

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Walking down busy temple streets in India is an experience in lifetime. Especially the temple streets are one of the most energetic places not only because of the divinity but also because of the streets itself which provides place for people to relax, meet, shop, linger, just walk around these activities create a set of experience which results in memories that lasts longer. Thinking of any temple street in India the image that comes to anyone’s mind are the elegantly sculpted Gopurams (Gateway) that depicts the craftsmanship and the history of the place, people taking a holy dip in the water, the aroma of the agarbathi’s, flowers with the divine Vedic chants and the sound of the temple bell flock of pigeons flying from the niches of the Gopuram with the sun in the backdrop. It gives a feeling of impulse energy that brings in life to these streets. Any temple street with even any one factor missing would look dead. This will be amiss in the essence in the scene of one’s experiences. These Temple Streets traditionally cater not only for religious purpose but to a wide range of activities. A vibrant street that facilitates such activities are preferred by the public any day. The research seeks to understand and find out the definition of Vibrancy in Indian Context. What is Vibrancy? What brings in the feeling of Vibrancy/Liveliness/Energy? Is it the Built structure and the city? Or is it the people? Or is it the Activity? Or is it Built structure – city – People – Activity put together brings the sense of Vibrancy to a place? How to define Vibrancy? Is it measurable? For which a case of Car Street Udupi, Karnataka is taken. The research is carried out in two stages. ‘Stage One’ makes use of ethnographic fieldwork as a basic method, complimented by structured field observations using a behavioral mapping procedure of the streets. Stage Two’ utilizes surveys that collected. This stage seeks to understand what design characteristics and furniture arrangements are associated with stationary, social and gathering activities of people by each cultural group and all groups collectively. The main conclusion from this research is that retail activities remain the main concern of people in cultural streets. Management and higher-level planning of retail activities on the streets could encourage and motivate possible Shops to enrich the trade variety of the street that provides a means for social and cultural diversity. In addition to business activities, spatial design characteristics are found to have an influence on people’s behavior and activity. The findings of this research suggest that retail and business activities, together with the design and skillful management of the public areas, could support a wider range of static and social activities among people of various ethnic backgrounds.

Keywords: activity, liveliness, temple street, vibrancy

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Authors: Luthfia A. Eka, Bertri M. Masita, G. Indah Lestari, Rizka. Ryanindya, Anindita D. Nur, Asih. Setiarini

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The preferred habit nowadays is to watch television or listen to the radio rather than reading a newspaper or magazine. The low interest in reading is the reason to the Indonesian government passed a regulation to foster interest in reading early in schoolchildren through literacy programs. Literacy programs are held for the first 10 - 15 minutes before classes begin and children are asked to read books other than textbooks such as storybooks or magazines. In addition, elementary school children have a tendency to buy less healthy snacks around the school and do not know the nutrition fact from the food purchased. Whereas snacks contribute greatly in the fulfillment of energy and nutrients of children every day. The purpose of this study was to increase reading interest as well as knowledge of nutrition and health for elementary school students. This study used quantitative method with experimental study design for four months with twice intervention per week and deepened by qualitative method in the form of interview. The participants were 130 students consisting of 3rd and 4th graders in selected elementary school in Depok City. The Interventions given using KUCERIA (Child Storybook) which were storybooks with pictures consisting of 12 series about nutrition and health given at school literacy hours. There were five questions given by using the crossword method to find out the students' understanding of the story content in each series. To maximize the understanding and absorption of information, two students were asked to retell the story in front of the class and one student to fill the crossword on the board for each series. In addition, interviews were conducted by asking questions about students' interest in reading books. Intervention involved not only students but also teachers and parents in order to optimize students' reading habits. Analysis showed > 80% of student could answer 3 of 5 questions correctly in each series, which showed they had an interest in what they read. Research data on nutrition and health knowledge were analyzed using Wilcoxon and Chi-Square Test to see the relationship. However, only 46% of students completed 12 series and the rest lost to follow up due to school schedule incompatibility with the program. The results showed that there was a significant increase of knowledge (p = 0.000) between before intervention with 66,53 score and after intervention with 81,47 score. Retention of knowledge was conducted one month after the last intervention was administered and the analysis result showed no significant decrease of knowledge (p = 0,000) from 79,17 score to 75,48 score. There is also no relationship between sex and class with knowledge. Hence, an increased interest in reading of elementary school students and nutritional knowledge interventions using KUCERIA was proved successful. These interventions may be replicated in other schools or learning communities.

Keywords: literation, reading interest, nutrition knowledge, school children

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Authors: Parisa Mansour

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Introduction: Early diagnosis of coronavirus disease (COVID-19) is extremely important to isolate and treat patients in time, thus preventing the spread of the disease, improving prognosis and reducing mortality. High-resolution computed tomography (HRCT) chest imaging and artificial intelligence (AI)-based analysis of HRCT chest images can play a central role in the treatment of patients with COVID-19. Objective: To investigate different chest HRCT findings in different stages of COVID-19 pneumonia and to evaluate the potential role of artificial intelligence in the quantitative assessment of lung parenchymal involvement in COVID-19 pneumonia. Materials and Methods: This retrospective observational study was conducted between May 1, 2020 and August 13, 2020. The study included 2169 patients with COVID-19 who underwent chest HRCT. HRCT images showed the presence and distribution of lesions such as: ground glass opacity (GGO), compaction, and any special patterns such as septal thickening, inverted halo, mark, etc. HRCT findings of the breast at different stages of the disease (early: andlt) 5 days, intermediate: 6-10 days and late stage: >10 days). A CT severity score (CTSS) was calculated based on the extent of lung involvement on HRCT, which was then correlated with clinical disease severity. Use of artificial intelligence; Analysis of CT pneumonia and quot; An algorithm was used to quantify the extent of pulmonary involvement by calculating the percentage of pulmonary opacity (PO) and gross opacity (PHO). Depending on the type of variables, statistically significant tests such as chi-square, analysis of variance (ANOVA) and post hoc tests were applied when appropriate. Results: Radiological findings were observed in HRCT chest in 1438 patients. A typical pattern of COVID-19 pneumonia, i.e., bilateral peripheral GGO with or without consolidation, was observed in 846 patients. About 294 asymptomatic patients were radiologically positive. Chest HRCT in the early stages of the disease mostly showed GGO. The late stage was indicated by such features as retinal enlargement, thickening and the presence of fibrous bands. Approximately 91.3% of cases with a CTSS = 7 were asymptomatic or clinically mild, while 81.2% of cases with a score = 15 were clinically severe. Mean PO and PHO (30.1 ± 28.0 and 8.4 ± 10.4, respectively) were significantly higher in the clinically severe categories. Conclusion: Because COVID-19 pneumonia progresses rapidly, radiologists and physicians should become familiar with typical TC chest findings to treat patients early, ultimately improving prognosis and reducing mortality. Artificial intelligence can be a valuable tool in treating patients with COVID-19.

Keywords: chest, HRCT, covid-19, artificial intelligence, chest HRCT

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Authors: Gaurav Gupta, Jitendra Mahakud

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This study focuses on the significance of internal financing constraints on the determination of corporate fixed investments in the case of Indian manufacturing companies. Financing constraints companies which have less internal fund or retained earnings face more transaction and borrowing costs due to imperfections in the capital market. The period of study is 1999-2000 to 2013-2014 and we consider 618 manufacturing companies for which the continuous data is available throughout the study period. The data is collected from PROWESS data base maintained by Centre for Monitoring Indian Economy Pvt. Ltd. Panel data methods like fixed effect and random effect methods are used for the analysis. The Likelihood Ratio test, Lagrange Multiplier test, and Hausman test results conclude the suitability of the fixed effect model for the estimation. The cash flow and liquidity of the company have been used as the proxies for the internal financial constraints. In accordance with various theories of corporate investments, we consider other firm specific variable like firm age, firm size, profitability, sales and leverage as the control variables in the model. From the econometric analysis, we find internal cash flow and liquidity have the significant and positive impact on the corporate investments. The variables like cost of capital, sales growth and growth opportunities are found to be significantly determining the corporate investments in India, which is consistent with the neoclassical, accelerator and Tobin’s q theory of corporate investment. To check the robustness of results, we divided the sample on the basis of cash flow and liquidity. Firms having cash flow greater than zero are put under one group, and firms with cash flow less than zero are put under another group. Also, the firms are divided on the basis of liquidity following the same approach. We find that the results are robust to both types of companies having positive and negative cash flow and liquidity. The results for other variables are also in the same line as we find for the whole sample. These findings confirm that internal financing constraints play a significant role for determination of corporate investment in India. The findings of this study have the implications for the corporate managers to focus on the projects having higher expected cash inflows to avoid the financing constraints. Apart from that, they should also maintain adequate liquidity to minimize the external financing costs.

Keywords: cash flow, corporate investment, financing constraints, panel data method

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Authors: Mahsa Houshdar, Seyed Mehdi Samimi Ardestani , ُSeyed Saeed Sadr

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Introduction: Online Medicare is a method in which parts of a medical process - whether its diagnostics, monitoring or the treatment itself will be done by using online services. This system has been operated in one boy’s high school, one girl’s high school and one high school in deprived aria. Method: At the first step the students registered for using the system. It was not mandatory and not free. They participated in estimating depression scale, anxiety scale and clinical interview by online medical care system. During this estimation, we could find the existence and severity of depression and anxiety in each one of the participants, also we could find the consequent needs of each one, such as supportive therapy in mild depression or anxiety, need to visited by psychologist in moderate cases, need to visited by psychiatrist in moderate-severe cases, need to visited by psychiatrist and psychologist in severe cases and need to perform medical lab examination tests. The lab examination tests were performed on persons specified by the system. The lab examinations were included: serum level of vitamin D, serum level of vitamin B12, serum level of calcium, fasting blood sugar, HbA1c, thyroid function tests and CBC. All of the students were solely treated by vitamins or minerals therapy and/ or treatment of medical problem (such as hypothyroidism). After a few months, we came back to high schools and estimated the existence and severity of depression and anxiety in treated students. With comparing these results, the affectability of the system could be prof. Results: Totally, we operate this project in 1077 participants in 243 of participant, the lab examination test were performed. In girls high schools: the existence and severity of depression significantly deceased (P value= 0.018<0.05 & P value 0.004< 0.05), but results about anxiety was not significant. In boys high schools: the existence and severity of depression significantly decreased (P value= 0.023<0.05 & P value = 0.004< 0.05 & P value= 0.049< 0.05). In boys high schools: the existence and severity of anxiety significantly decreased (P value= 0.041<0.05 & P value = 0.046< 0.05 &) but in one high school results about anxiety was not significant. In high school in deprived area the students did not have any problem paying for participating in the project, but they could not pay for medical lab examination tests. Thus, operation of the system was not possible in deprived area without a sponsor. Conclusion: This online medical system was successful in creating medical and psychiatric profile without attending physician. It was successful in decreasing depression without using antidepressants, but it was partially successful in decreasing anxiety.

Keywords: depression, diabetes, online medicare, vitamin D deficiency

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Authors: M. Turmanauli, T. Todua, O. Gvaberidze, R. Javakhadze, N. Chkhaidze, N. Khatiashvili

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Background: Mining process has the significant influence on human health and quality of life. In recent years the events in Georgia were reflected on the industry working process, especially minimal requirements of labor safety, hygiene standards of workplace and the regime of work and rest are not observed. This situation is often caused by the lack of responsibility, awareness, and knowledge both of workers and employers. The control of working conditions and its protection has been worsened in many of industries. Materials and Methods: For evaluation of the current situation the prospective epidemiological study by face to face interview method was conducted at Georgian “Manganese Zestafoni Ferroalloy Plant” in 2011-2013. 65.7% of employees (1428 bulletin) were surveyed and the incidence rates of temporary disability days were studied. Results: The average length of a temporary disability single accident was studied taking into consideration as sex groups as well as the whole cohort. According to the classes of harmfulness the following results were received: Class 2.0-10.3%; 3.1-12.4%; 3.2-35.1%; 3.3-12.1%; 3.4-17.6%; 4.0-12.5%. Among the employees 47.5% and 83.1% were tobacco and alcohol consumers respectively. According to the age groups and years of work on the base of previous experience ≥50 ages and ≥21 years of work data prevalence respectively. The obtained data revealed increased morbidity rate according to age and years of work. It was found that the bone and articulate system and connective tissue diseases, aggravation of chronic respiratory diseases, ischemic heart diseases, hypertension and cerebral blood discirculation were the leading among the other diseases. High prevalence of morbidity observed in the workplace with not satisfactory labor conditions from the hygienic point of view. Conclusion: According to received data the causes of morbidity are the followings: unsafety labor conditions; incomplete of preventive medical examinations (preliminary and periodic); lack of access to appropriate health care services; derangement of gathering, recording, and analysis of morbidity data. This epidemiological study was conducted at the JSC “Manganese Ferro Alloy Plant” according to State program “ Prevention of Occupational Diseases” (Program code is 35 03 02 05).

Keywords: occupational health, mining process, morbidity level, cerebral blood discirculation

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Authors: Gadinga Walter Forje, Martin Ngankam Tchamba, Nyong Princely Awazi, Barnabas Neba Nfornka

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Ecotourism is viewed as a double edge sword for the enhancement of conservation and local livelihood within a protected landscape. The Campo Ma’an National Park (CMNP) adopted ecotourism in its management plan as a strategic axis for better management of the park. The growing importance of ecotourism as a strategy for the sustainable management of CMNP and its environs requires adequate information to bolster the sector. This study was carried out between November 2018 and September 2021, with the main objective to contribute to the sustainable management of the CMNP through suggestions for enhancing the capacity of ecotourism in and around the park. More specifically, the study aimed at; 1) Analyse the governance of ecotourism in the CMNP and its surrounding; 2) Assessing the impact of ecotourism on local livelihood around the CMNP; 3) Evaluating the contribution of ecotourism to biodiversity conservation in and around the CMNP; 4) Evaluate the determinants of ecotourism possibilities in achieving sustainable livelihood and biodiversity conservation in and around the CMNP. Data were collected from both primary and secondary sources. Primary data were obtained from household surveys (N=124), focus group discussions (N=8), and key informant interviews (N=16). Data collected were coded and imputed into SPSS (version 19.0) software and Microsoft Excel spreadsheet for both quantitative and qualitative analysis. Findings from the Chi-square test revealed overall poor ecotourism governance in and around the CMNP, with benefit sharing (X2 = 122.774, p <0.01) and conflict management (X2 = 90.839, p<0.01) viewed to be very poor. For the majority of the local population sampled, 65% think ecotourism does not contribute to local livelihood around CMNP. The main factors influencing the impact of ecotourism around the CMNP on the local population’s livelihood were gender (logistic regression (β) = 1.218; p = 0.000); and level of education (logistic regression (β) = 0.442; p = 0.000). Furthermore, 55.6% of the local population investigated believed ecotourism activities do not contribute to the biodiversity conservation of CMNP. Spearman correlation between socio-economic variables and ecotourism impact on biodiversity conservation indicated relationships with gender (r = 0.200, p = 0.032), main occupation (r = 0.300 p = 0.012), time spent in the community (r = 0.287 p = 0.017), and number of children (r =-0.286 p = 0.018). Variables affecting ecotourism impact on biodiversity conservation were age (logistic regression (β) = -0.683; p = 0.037) and gender (logistic regression (β) = 0.917; p = 0.045). This study recommends the development of ecotourism-friendly policies that can accelerate Public Private Partnership for the sustainable management of the CMNP as a commitment toward good governance. It also recommends the development of gender-sensitive ecotourism packages, with fair opportunities for rural women and more parity in benefit sharing to improve livelihood and contribute more to biodiversity conservation in and around the Park.

Keywords: biodiversity conservation, Campo Ma’an national park, ecotourism, ecotourism governance, rural livelihoods, protected area management

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Authors: Nina Ponikvar, Katja Zajc Kejžar

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While the positive impacts of heritage on a broad societal spectrum have long been recognized and measured, the economic effects of the heritage sector are often less visible and frequently underestimated. At macro level, economic effects are usually studied based on one of the two mainstream approach, i.e. either the multiplier approach or the value chain approach. Consequently, there is limited comparability of the empirical results due to the use of different methodological approach in the literature. Furthermore, it is also not clear on which criteria the used approach was selected. Our aim is to bring the attention to the difference in the scope of effects that are encompassed by the two most frequent methodological approaches to valuation of economic effects of cultural heritage on macroeconomic level, i.e. the multiplier approach and the value chain approach. We show that while the multiplier approach provides a systematic, theory-based view of economic impacts but requires more data and analysis, the value chain approach has less solid theoretical foundations and depends on the availability of appropriate data to identify the contribution of cultural heritage to other sectors. We conclude that the multiplier approach underestimates the economic impact of cultural heritage, mainly due to the narrow definition of cultural heritage in the statistical classification and the inability to identify part of the contribution of cultural heritage that is hidden in other sectors. Yet it is not possible to clearly determine whether the value chain method overestimates or underestimates the actual economic impact of cultural heritage since there is a risk that the direct effects are overestimated and double counted, but not all indirect and induced effects are considered. Accordingly, these two approaches are not substitutes but rather complementary. Consequently, a direct comparison of the estimated impacts is not possible and should not be done due to the different scope. To illustrate the difference of the impact assessment of the cultural heritage, we apply both approaches to the case of Slovenia in the 2015-2022 period and measure the economic impact of cultural heritage sector in terms of turnover, gross value added and employment. The empirical results clearly show that the estimation of the economic impact of a sector using the multiplier approach is more conservative, while the estimates based on value added capture a much broader range of impacts. According to the multiplier approach, each euro in cultural heritage sector generates an additional 0.14 euros in indirect effects and an additional 0.44 euros in induced effects. Based on the value-added approach, the indirect economic effect of the “narrow” heritage sectors is amplified by the impact of cultural heritage activities on other sectors. Accordingly, every euro of sales and every euro of gross value added in the cultural heritage sector generates approximately 6 euros of sales and 4 to 5 euros of value added in other sectors. In addition, each employee in the cultural heritage sector is linked to 4 to 5 jobs in other sectors.

Keywords: economic value of cultural heritage, multiplier approach, value chain approach, indirect effects, slovenia

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Authors: Soheila Sadeghi

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Construction projects are complex and often subject to significant cost overruns due to the multifaceted nature of the activities involved. Accurate cost estimation is crucial for effective budget planning and resource allocation. Traditional methods for predicting overruns often rely on expert judgment or analysis of historical data, which can be time-consuming, subjective, and may fail to consider important factors. However, with the increasing availability of data from construction projects, machine learning techniques can be leveraged to improve the accuracy of overrun predictions. This study applied machine learning algorithms to enhance the prediction of cost overruns in a case study of a construction project. The methodology involved the development and evaluation of two machine learning models: Random Forest and Neural Networks. Random Forest can handle high-dimensional data, capture complex relationships, and provide feature importance estimates. Neural Networks, particularly Deep Neural Networks (DNNs), are capable of automatically learning and modeling complex, non-linear relationships between input features and the target variable. These models can adapt to new data, reduce human bias, and uncover hidden patterns in the dataset. The findings of this study demonstrate that both Random Forest and Neural Networks can significantly improve the accuracy of cost overrun predictions compared to traditional methods. The Random Forest model also identified key cost drivers and risk factors, such as changes in the scope of work and delays in material delivery, which can inform better project risk management. However, the study acknowledges several limitations. First, the findings are based on a single construction project, which may limit the generalizability of the results to other projects or contexts. Second, the dataset, although comprehensive, may not capture all relevant factors influencing cost overruns, such as external economic conditions or political factors. Third, the study focuses primarily on cost overruns, while schedule overruns are not explicitly addressed. Future research should explore the application of machine learning techniques to a broader range of projects, incorporate additional data sources, and investigate the prediction of both cost and schedule overruns simultaneously.

Keywords: cost prediction, machine learning, project management, random forest, neural networks

Procedia PDF Downloads 36

Authors: Oshma Chakoory, Sophie Comtet-Marre, Pierre Peyret

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Metagenomic classifiers are widely used for the taxonomic profiling of metagenomic data and estimation of taxa relative abundance. Small subunit rRNA genes are nowadays a gold standard for the phylogenetic resolution of complex microbial communities, although the power of this marker comes down to its use as full-length. We benchmarked the performance and accuracy of rRNA-specialized versus general-purpose read mappers, reference-targeted assemblers and taxonomic classifiers. We then built a pipeline called RiboTaxa to generate a highly sensitive and specific metataxonomic approach. Using metagenomics data, RiboTaxa gave the best results compared to other tools (Kraken2, Centrifuge (1), METAXA2 (2), PhyloFlash (3)) with precise taxonomic identification and relative abundance description, giving no false positive detection. Using real datasets from various environments (ocean, soil, human gut) and from different approaches (metagenomics and gene capture by hybridization), RiboTaxa revealed microbial novelties not seen by current bioinformatics analysis opening new biological perspectives in human and environmental health. In a study focused on corals’ health involving 20 metagenomic samples (4), an affiliation of prokaryotes was limited to the family level with Endozoicomonadaceae characterising healthy octocoral tissue. RiboTaxa highlighted 2 species of uncultured Endozoicomonas which were dominant in the healthy tissue. Both species belonged to a genus not yet described, opening new research perspectives on corals’ health. Applied to metagenomics data from a study on human gut and extreme longevity (5), RiboTaxa detected the presence of an uncultured archaeon in semi-supercentenarians (aged 105 to 109 years) highlighting an archaeal genus, not yet described, and 3 uncultured species belonging to the Enorma genus that could be species of interest participating in the longevity process. RiboTaxa is user-friendly, rapid, allowing microbiota structure description from any environment and the results can be easily interpreted. This software is freely available at https://github.com/oschakoory/RiboTaxa under the GNU Affero General Public License 3.0.

Keywords: metagenomics profiling, microbial diversity, SSU rRNA genes, full-length phylogenetic marker

Procedia PDF Downloads 110

Authors: Janne Engblom, Elias Oikarinen

Abstract:

A panel dataset is one that follows a given sample of individuals over time, and thus provides multiple observations on each individual in the sample. Panel data models include a variety of fixed and random effects models which form a wide range of linear models. A special case of panel data models are dynamic in nature. A complication regarding a dynamic panel data model that includes the lagged dependent variable is endogeneity bias of estimates. Several approaches have been developed to account for this problem. In this paper, the panel models were estimated using the Arellano-Bover/Blundell-Bond Generalized method of moments (GMM) estimator which is an extension of the Arellano-Bond model where past values and different transformations of past values of the potentially problematic independent variable are used as instruments together with other instrumental variables. The Arellano–Bover/Blundell–Bond estimator augments Arellano–Bond by making an additional assumption that first differences of instrument variables are uncorrelated with the fixed effects. This allows the introduction of more instruments and can dramatically improve efficiency. It builds a system of two equations—the original equation and the transformed one—and is also known as system GMM. In this study, Finnish housing price dynamics were examined empirically by using the Arellano–Bover/Blundell–Bond estimation technique together with ordinary OLS. The aim of the analysis was to provide a comparison between conventional fixed-effects panel data models and dynamic panel data models. The Arellano–Bover/Blundell–Bond estimator is suitable for this analysis for a number of reasons: It is a general estimator designed for situations with 1) a linear functional relationship; 2) one left-hand-side variable that is dynamic, depending on its own past realizations; 3) independent variables that are not strictly exogenous, meaning they are correlated with past and possibly current realizations of the error; 4) fixed individual effects; and 5) heteroskedasticity and autocorrelation within individuals but not across them. Based on data of 14 Finnish cities over 1988-2012 differences of short-run housing price dynamics estimates were considerable when different models and instrumenting were used. Especially, the use of different instrumental variables caused variation of model estimates together with their statistical significance. This was particularly clear when comparing estimates of OLS with different dynamic panel data models. Estimates provided by dynamic panel data models were more in line with theory of housing price dynamics.

Keywords: dynamic model, fixed effects, panel data, price dynamics

Procedia PDF Downloads 1480

Authors: Soheila Sadeghi

Abstract:

Construction projects are complex and often subject to significant cost overruns due to the multifaceted nature of the activities involved. Accurate cost estimation is crucial for effective budget planning and resource allocation. Traditional methods for predicting overruns often rely on expert judgment or analysis of historical data, which can be time-consuming, subjective, and may fail to consider important factors. However, with the increasing availability of data from construction projects, machine learning techniques can be leveraged to improve the accuracy of overrun predictions. This study applied machine learning algorithms to enhance the prediction of cost overruns in a case study of a construction project. The methodology involved the development and evaluation of two machine learning models: Random Forest and Neural Networks. Random Forest can handle high-dimensional data, capture complex relationships, and provide feature importance estimates. Neural Networks, particularly Deep Neural Networks (DNNs), are capable of automatically learning and modeling complex, non-linear relationships between input features and the target variable. These models can adapt to new data, reduce human bias, and uncover hidden patterns in the dataset. The findings of this study demonstrate that both Random Forest and Neural Networks can significantly improve the accuracy of cost overrun predictions compared to traditional methods. The Random Forest model also identified key cost drivers and risk factors, such as changes in the scope of work and delays in material delivery, which can inform better project risk management. However, the study acknowledges several limitations. First, the findings are based on a single construction project, which may limit the generalizability of the results to other projects or contexts. Second, the dataset, although comprehensive, may not capture all relevant factors influencing cost overruns, such as external economic conditions or political factors. Third, the study focuses primarily on cost overruns, while schedule overruns are not explicitly addressed. Future research should explore the application of machine learning techniques to a broader range of projects, incorporate additional data sources, and investigate the prediction of both cost and schedule overruns simultaneously.

Keywords: resource allocation, machine learning, optimization, data-driven decision-making, project management

Procedia PDF Downloads 28

Authors: Peter C. St. John, Michael F. Crowley, Yannick J. Bomble

Abstract:

Production of chemicals from engineered organisms in a batch culture typically involves a trade-off between productivity, yield, and titer. However, strategies for strain design typically involve designing mutations to achieve the highest yield possible while maintaining growth viability. Such approaches tend to follow the principle of designing static networks with minimum metabolic functionality to achieve desired yields. While these methods are computationally tractable, optimum productivity is likely achieved by a dynamic strategy, in which intracellular fluxes change their distribution over time. One can use multi-stage fermentations to increase either productivity or yield. Such strategies would range from simple manipulations (aerobic growth phase, anaerobic production phase), to more complex genetic toggle switches. Additionally, some computational methods can also be developed to aid in optimizing two-stage fermentation systems. One can assume an initial control strategy (i.e., a single reaction target) in maximizing productivity - but it is unclear how close this productivity would come to a global optimum. The calculation of maximum theoretical yield in metabolic engineering can help guide strain and pathway selection for static strain design efforts. Here, we present a method for the calculation of a maximum theoretical productivity of a batch culture system. This method follows the traditional assumptions of dynamic flux balance analysis: that internal metabolite fluxes are governed by a pseudo-steady state and external metabolite fluxes are represented by dynamic system including Michealis-Menten or hill-type regulation. The productivity optimization is achieved via dynamic programming, and accounts explicitly for an arbitrary number of fermentation stages and flux variable changes. We have applied our method to succinate production in two common microbial hosts: E. coli and A. succinogenes. The method can be further extended to calculate the complete productivity versus yield Pareto surface. Our results demonstrate that nearly optimal yields and productivities can indeed be achieved with only two discrete flux stages.

Keywords: A. succinogenes, E. coli, metabolic engineering, metabolite fluxes, multi-stage fermentations, succinate

Procedia PDF Downloads 207

Authors: Jaspreet Kaur, Parminder Nain, Vipin Saini, Sumitra Dahiya

Abstract:

Elaeocarpus sphaericus has been traditionally used in the Indian traditional medicine system for the treatment of stress, anxiety, depression, palpitation, epilepsy, migraine and lack of concentration. The study was investigated to evaluate the neurological potential such as anxiolytic, muscle relaxant and sedative activity of methanolic extract of Elaeocarpus sphaericus stem bark (MEESSB) in mice. Preliminary phytochemical screening and acute oral toxicity of MEESSB was carried out by using standard methods. The anxiety was induced by employing Elevated Plus-Maze (EPM), Light and Dark Test (LDT), Open Field Test (OFT) and Social Interaction test (SIT). The motor coordination and sedative effect was also observed by using actophotometer, rota-rod apparatus and ketamine-induced sleeping time, respectively. Animals were treated with different doses of MEESSB (i.e.100, 200, 400 and 800 mg/kg orally) and diazepam (2 mg/kg i.p) for 21 days. Brain neurotransmitters like dopamine, serotonin and nor-epinephrine level were estimated by validated methods. Preliminary phytochemical analysis of the extract revealed the presence of tannins, phytosterols, steroids and alkaloids. In the acute toxicity studies, MEESSB was found to be non-toxic and with no mortality. In anxiolytic studies, the different doses of MEESSB showed a significant (p<0.05) effect on EPM and LDT. In OFT and SIT, a significant (p<0.05) increase in ambulation, rearing and social interaction time was observed. In the case of motor coordination activity, the MEESSB does not cause any significant effect on the latency to fall off from the rotarod bar as compared to the control group. Moreover, no significant effects on ketamine-induced sleep latency and total sleeping time induced by ketamine were observed. Results of neurotransmitter estimation revealed the increased concentration of dopamine, whereas the level of serotonin and nor-epinephrine was found to be decreased in the mice brain, with MEESSB at dose 800 mg/kg only. The study has validated the folkloric use of the plant as an anxiolytic in Indian traditional medicine while also suggesting potential usefulness in the treatment of stress and anxiety without causing sedation.

Keywords: anxiolytic, behavior experiments, brain neurotransmitters, elaeocarpus sphaericus

Procedia PDF Downloads 172

Authors: O. E. Akinyemi, P. O. Alege, O. O. Ajayi, L. A. Amaghionyediwe, A. A. Ogundipe

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Nigeria as an oil-producing developing country in Africa is one of the many countries that had been subsidizing consumption of fossil fuel. Despite the numerous advantage of this policy ranging from increased energy access, fostering economic and industrial development, protecting the poor households from oil price shocks, political considerations, among others; they have been found to impose economic cost, wasteful, inefficient, create price distortions discourage investment in the energy sector and contribute to environmental pollution. These negative consequences coupled with the fact that the policy had not been very successful at achieving some of its stated objectives, led to a number of organisations and countries such as the Group of 7 (G7), World Bank, International Monetary Fund (IMF), International Energy Agency (IEA), Organisation for Economic Co-operation and Development (OECD), among others call for global effort towards reforming fossil fuel subsidies. This call became necessary in view of seeking ways to harmonise certain existing policies which may by design hamper current effort at tackling environmental concerns such as climate change. This is in addition to driving a green growth strategy and low carbon development in achieving sustainable development. The energy sector is identified to play a vital role. This study thus investigates the prospects of using fuel subsidy reform as a viable tool in driving an economy that de-emphasizes carbon growth in Nigeria. The method used is the Johansen and Engle-Granger two-step Co-integration procedure in order to investigate the existence or otherwise of a long-run equilibrium relationship for the period 1971 to 2011. Its theoretical framework is rooted in the Environmental Kuznet Curve (EKC) hypothesis. In developing three case scenarios (case of subsidy payment, no subsidy payment and effective subsidy), findings from the study supported evidence of a long run sustainable equilibrium model. Also, estimation results reflected that the first and the second scenario do not significantly influence the indicator of environmental quality. The implication of this is that in reforming fuel subsidy to drive environmental quality for an economy like Nigeria, strong and effective regulatory framework (measure that was interacted with fuel subsidy to yield effective subsidy) is essential.

Keywords: environmental quality, fuel subsidy, green growth, low carbon growth strategy

Procedia PDF Downloads 317

Authors: Nwamaka Patricia Ibeme, Musa Zakari

Abstract:

E-learning is made more effective because; it is enable student to students to easily interact, share, and collaborate across time and space with the help of e-governance platform. Zoom and the Microsoft classroom team can invite students from all around the world to join a conversation on a certain subject simultaneously. E-governance may be able to work on problem solving skills, as well as brainstorming and developing ideas. As a result of the shared experiences and knowledge, students are able to express themselves and reflect on their own learning." For students, e-governance facilities provide greater opportunity for students to build critical (higher order) thinking abilities through constructive learning methods. Students' critical thinking abilities may improve with more time spent in an online classroom. Students' inventiveness can be enhanced through the use of computer-based instruction. Discover multimedia tools and produce products in the styles that are easily available through games, Compact Disks, and television. The use of e-learning has increased both teaching and learning quality by combining student autonomy, capacity, and creativity over time in developed countries." Teachers are catalysts for the integration of technology through Information and Communication Technology, and e-learning supports teaching by simplifying access to course content." Creating an Information and Communication Technology class will be much easier if educational institutions provide teachers with the assistance, equipment, and resources they need. The study adopted survey research design. The populations of the study are Students and staff. The study adopted a simple random sampling technique to select a representative population. Both primary and secondary method of data collection was used to obtain the data. A chi-square statistical technique was used to analyze. Finding from the study revealed that e-learning has increase accesses to universities educational by public servants in Nigeria. Public servants in Nigeria have utilized e-learning and Online Distance Learning (ODL) programme to into various degree programmes. Finding also shows that E-learning plays an important role in teaching because it is oriented toward the use of information and communication technologies that have become a part of the everyday life and day-to-day business. E-learning contributes to traditional teaching methods and provides many advantages to society and citizens. The study recommends that the e-learning tools and internet facilities should be upgrade to foster any network challenges in the online facilitation and lecture delivery system.

Keywords: E-governance, E-learning, online distance learning, university education public servants, Nigeria

Procedia PDF Downloads 65

Authors: V. I. Kozyavkin, L. F. Shestopalova, T. B. Voloshyn

Abstract:

Introduction: Rehabilitation of children with Autism is the issue of the day in psychiatry and neurology. It is attributed to constantly increasing quantity of autistic children - Autistic Spectrum Disorders (ASD) Existing rehabilitation approaches in treatment of children with Autism improve their medico- social and social- psychological adjustment. Experience of treatment for different kinds of Autistic disorders in International Clinic of Rehabilitation (ICR) reveals the necessity of complex intensive approach for healing this malady and wider implementation of a Kozyavkin method for treatment of children with ASD. Methods: 19 children aged from 3 to 14 years were examined. They were diagnosed ‘Autism’ (F84.0) with comorbid neurological pathology (from pyramidal insufficiency to para- and tetraplegia). All patients underwent rehabilitation in ICR during two weeks, where INRS approach was used. INRS included methods like biomechanical correction of the spine, massage, physical therapy, joint mobilization, wax-paraffin applications. They were supplemented by art- therapy, ergotherapy, rhythmical group exercises, computer game therapy, team Olympic games and other methods for improvement of motivation and social integration of the child. Estimation of efficacy was conducted using parent’s questioning and done twice- on the onset of INRS rehabilitation course and two weeks afterward. For efficacy assessment of rehabilitation of autistic children in ICR standardized tool was used, namely Autism Treatment Evaluation Checklist (ATEC). This scale was selected because any rehabilitation approaches for the child with Autism can be assessed using it. Results: Before the onset of INRS treatment mean score according to ATEC scale was 64,75±9,23, it reveals occurrence in examined children severe communication, speech, socialization and behavioral impairments. After the end of the rehabilitation course, the mean score was 56,5±6,7, what indicates positive dynamics in comparison to the onset of rehabilitation. Generally, improvement of psychoemotional state occurred in 90% of cases. Most significant changes occurred in the scope of speech (16,5 before and 14,5 after the treatment), socialization (15.1 before and 12,5 after) and behavior (20,1 before and 17.4 after). Conclusion: As a result of INRS rehabilitation course reduction of autistic symptoms was noted. Particularly improvements in speech were observed (children began to spell out new syllables, words), there was some decrease in signs of destructiveness, quality of contact with the surrounding people improved, new skills of self-service appeared. The prospect of the study is further, according to evidence- based medicine standards, deeper examination of INRS and assessment of its usefulness in treatment for Autism and ASD.

Keywords: intensive neurophysiological rehabilitation system (INRS), international clinic od rehabilitation, ASD, rehabilitation

Procedia PDF Downloads 166

Authors: D. Signore, M. Ferraiuolo, P. Caramuta, O. Petrella, C. Toscano

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The Digital Image Correlation (DIC) is a newly developed optical technique that is spreading in all engineering sectors because it allows the non-destructive estimation of the entire surface deformation without any contact with the component under analysis. These characteristics make the DIC very appealing in all the cases the global deformation state is to be known without using strain gages, which are the most used measuring device. The DIC is applicable to any material subjected to distortion caused by either thermal or mechanical load, allowing to obtain high-definition mapping of displacements and deformations. That is why in the civil and the transportation industry, DIC is very useful for studying the behavior of metallic materials as well as of composite materials. DIC is also used in the medical field for the characterization of the local strain field of the vascular tissues surface subjected to uniaxial tensile loading. DIC can be carried out in the two dimension mode (2D DIC) if a single camera is used or in a three dimension mode (3D DIC) if two cameras are involved. Each point of the test surface framed by the cameras can be associated with a specific pixel of the image, and the coordinates of each point are calculated knowing the relative distance between the two cameras together with their orientation. In both arrangements, when a component is subjected to a load, several images related to different deformation states can be are acquired through the cameras. A specific software analyzes the images via the mutual correlation between the reference image (obtained without any applied load) and those acquired during the deformation giving the relative displacements. In this paper, a metrological characterization of the digital image correlation is performed on aluminum and composite targets both in static and dynamic loading conditions by comparison between DIC and strain gauges measures. In the static test, interesting results have been obtained thanks to an excellent agreement between the two measuring techniques. In addition, the deformation detected by the DIC is compliant with the result of a FEM simulation. In the dynamic test, the DIC was able to follow with a good accuracy the periodic deformation of the specimen giving results coherent with the ones given by FEM simulation. In both situations, it was seen that the DIC measurement accuracy depends on several parameters such as the optical focusing, the parameters chosen to perform the mutual correlation between the images and, finally, the reference points on image to be analyzed. In the future, the influence of these parameters will be studied, and a method to increase the accuracy of the measurements will be developed in accordance with the requirements of the industries especially of the aerospace one.

Keywords: accuracy, deformation, image correlation, mechanical analysis

Procedia PDF Downloads 304

Authors: Weikang Gong, Chunhua Li

Abstract:

Dynamics plays an essential role in function exertion of proteins. Elastic network model (ENM), a harmonic potential-based and cost-effective computational method, is a valuable and efficient tool for characterizing the intrinsic dynamical properties encoded in biomacromolecule structures and has been widely used to detect the large-amplitude collective motions of proteins. Gaussian network model (GNM) and anisotropic network model (ANM) are the two often-used ENM models. In recent years, many ENM variants have been proposed. Here, we propose a small but effective modification (denoted as modified mENM) to the multiscale ENM (mENM) where fitting weights of Kirchhoff/Hessian matrixes with the least square method (LSM) is modified since it neglects the details of pairwise interactions. Then we perform its comparisons with the original mENM, traditional ENM, and parameter-free ENM (pfENM) on reproducing dynamical properties for the six representative proteins whose molecular dynamics (MD) trajectories are available in http://mmb.pcb.ub.es/MoDEL/. In the results, for B-factor prediction, mENM achieves the best performance among the four ENM models. Additionally, it is noted that with the weights of the multiscale Kirchhoff/Hessian matrixes modified, interestingly, the modified mGNM/mANM still has a much better performance than the corresponding traditional ENM and pfENM models. As to dynamical cross-correlation map (DCCM) calculation, taking the data obtained from MD trajectories as the standard, mENM performs the worst while the results produced by the modified mENM and pfENM models are close to those from MD trajectories with the latter a little better than the former. Generally, ANMs perform better than the corresponding GNMs except for the mENM. Thus, pfANM and the modified mANM, especially the former, have an excellent performance in dynamical cross-correlation calculation. Compared with GNMs (except for mGNM), the corresponding ANMs can capture quite a number of positive correlations for the residue pairs nearly largest distances apart, which is maybe due to the anisotropy consideration in ANMs. Furtherly, encouragingly the modified mANM displays the best performance in capturing the functional motional modes, followed by pfANM and traditional ANM models, while mANM fails in all the cases. This suggests that the consideration of long-range interactions is critical for ANM models to produce protein functional motions. Based on the analyses, the modified mENM is a promising method in capturing multiple dynamical characteristics encoded in protein structures. This work is helpful for strengthening the understanding of the elastic network model and provides a valuable guide for researchers to utilize the model to explore protein dynamics.

Keywords: elastic network model, ENM, multiscale ENM, molecular dynamics, parameter-free ENM, protein structure

Procedia PDF Downloads 114

Authors: Zohre Shahhosseini, Mehdi Pourasghar, AliReza Khalilian, Fariba Salehi

Abstract:

Objective: The prevalence of anxiety during pregnancy, particularly in developing countries, and its adverse effects on mother and baby, can make pregnancy unpleasant for pregnant women. The effect of anxiety during pregnancy on birth outcomes and children can be a justification for screening of anxious pregnant women in periodic pregnancy care and helping them. In this study, researchers have investigated effects and comparison of group counseling (Cognitive therapy) and interactive lectures on anxiety during pregnancy of primiparas. Methods: The population studied in this semi-experimental trail was nulliparous pregnant women with backgrounds in health care centers in Sari city .They were studied during a period of 3 months from early March to end May 2016. Sample size in this study was 91 patients, who were randomly assigned to three groups: group counseling, interactive lecture, and control group. Demographic questionnaire and Speilberger State –Trait Anxiety Inventory (SPAI) was completed for all three groups after obtaining letter of consent and completing the initial checklist. Then interventions included 4 sessions for group counseling and 4 sessions for interactive lecture which were implemented in two sessions a week. 4 weeks after interventions, Speilberger State – Trait Anxiety Inventory (SPAI), completed by both group counseling and interactive lectures groups again. In control group, the second questionnaire was also completed 4 weeks after completing the initial questionnaire. Data analysis was performed using spss software version 18. At first, the Kalmogorov-Smiranov test was carried out and then chi square tests, Independent t-test, paired t-test, ANOVA test, and Dunnett's post hoc test were applied. Results: Findings show that group counseling and interactive lecture with reducing state and trait anxiety in significant level of P=0/000 contribute to reduction of anxiety in nulliparous pregnant mothers. However, in this study, group counseling was more effective than an interactive lecture in reducing participants' anxiety, but this difference was not significant (P≥0/05). Conclusions: According to the results of this study, it is suggested that by screening of psychological - mental problems of pregnant women in periodic care during pregnancy be considered by revised prenatal care plans and creation of counseling and training units at health centers. Besides owing to the fact that both interactive lecture and group counseling method were effective in reducing anxiety, these methods should be used proportionate to situations and facilities.

Keywords: anxiety, group counseling, cognitive therapy, interactive lecture, nulliparous

Procedia PDF Downloads 290

Authors: Atheer Al-Nuaimi, Harry Evdorides

Abstract:

Every day many people die or get disabled or injured on roads around the world, which necessitates more specific treatments for transportation safety issues. International road assessment program (iRAP) model is one of the comprehensive road safety models which accounting for many factors that affect road safety in a cost-effective way in low and middle income countries. In iRAP model road safety has been divided into five star ratings from 1 star (the lowest level) to 5 star (the highest level). These star ratings are based on star rating score which is calculated by iRAP methodology depending on road attributes, traffic volumes and operating speeds. The outcome of iRAP methodology are the treatments that can be used to improve road safety and reduce fatalities and serious injuries (FSI) numbers. These countermeasures can be used separately as a single countermeasure or mix as multiple countermeasures for a location. There is general agreement that the adequacy of a countermeasure is liable to consistent losses when it is utilized as a part of mix with different countermeasures. That is, accident diminishment appraisals of individual countermeasures cannot be easily added together. The iRAP model philosophy makes utilization of a multiple countermeasure adjustment factors to predict diminishments in the effectiveness of road safety countermeasures when more than one countermeasure is chosen. A multiple countermeasure correction factors are figured for every 100-meter segment and for every accident type. However, restrictions of this methodology incorporate a presumable over-estimation in the predicted crash reduction. This study aims to adjust this correction factor by developing new models to calculate the effect of using multiple countermeasures on the number of fatalities for a location or an entire road. Regression models have been used to establish relationships between crash frequencies and the factors that affect their rates. Multiple linear regression, negative binomial regression, and Poisson regression techniques were used to develop models that can address the effectiveness of using multiple countermeasures. Analyses are conducted using The R Project for Statistical Computing showed that a model developed by negative binomial regression technique could give more reliable results of the predicted number of fatalities after the implementation of road safety multiple countermeasures than the results from iRAP model. The results also showed that the negative binomial regression approach gives more precise results in comparison with multiple linear and Poisson regression techniques because of the overdispersion and standard error issues.

Keywords: international road assessment program, negative binomial, road multiple countermeasures, road safety

Procedia PDF Downloads 233

Authors: Staņislavs Gendelis, Andris Jakovičs, Jānis Ratnieks, Aigars Laizāns, Dāvids Vardanjans

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Dehumidification of biogas at the biomass plants is very important to provide the energy efficient burning of biomethane at the outlet. A few methods are widely used to reduce the water content in biogas, e.g. chiller/heat exchanger based cooling, usage of different adsorbents like PSA, or the combination of such approaches. A quite different method of biogas dehumidification is offered and analyzed in this paper. The main idea is to direct the flow of biogas from the plant around it downwards; thus, creating additional insulation layer. As the temperature in gas shell layer around the plant will decrease from ~ 38°C to 20°C in the summer or even to 0°C in the winter, condensation of water vapor occurs. The water from the bottom of the gas shell can be collected and drain away. In addition, another upward shell layer is created after the condensate drainage place on the outer side to further reducing heat losses. Thus, counterflow biogas heat exchanger is created around the biogas plant. This research work deals with the numerical modelling of biogas flow, taking into account heat exchange and condensation on cold surfaces. Different kinds of boundary conditions (air and ground temperatures in summer/winter) and various physical properties of constructions (insulation between layers, wall thickness) are included in the model to make it more general and useful for different biogas flow conditions. The complexity of this problem is fact, that the temperatures in both channels are conjugated in case of low thermal resistance between layers. MATLAB programming language is used for multiphysical model development, numerical calculations and result visualization. Experimental installation of a biogas plant’s vertical wall with an additional 2 layers of polycarbonate sheets with the controlled gas flow was set up to verify the modelling results. Gas flow at inlet/outlet, temperatures between the layers and humidity were controlled and measured during a number of experiments. Good correlation with modelling results for vertical wall section allows using of developed numerical model for an estimation of parameters for the whole biogas dehumidification system. Numerical modelling of biogas counterflow heat exchanger system placed on the plant’s wall for various cases allows optimizing of thickness for gas layers and insulation layer to ensure necessary dehumidification of the gas under different climatic conditions. Modelling of system’s defined configuration with known conditions helps to predict the temperature and humidity content of the biogas at the outlet.

Keywords: biogas dehumidification, numerical modelling, condensation, biogas plant experimental model

Procedia PDF Downloads 543

Authors: Arosha Rashmi De Silva, Ananda Chandrasekara

Abstract:

This study seeks to comprehensively examine the influence of fast-food consumption and physical activity levels on the body weight of young employees within the private sector of Sri Lanka. The escalating popularity of fast food has raised concerns about its nutritional content and associated health ramifications. To investigate this phenomenon, a cohort of 100 individuals aged between 25 and 45, employed in Sri Lanka's private sector, participated in this research. These participants provided socio-demographic data through a standardized questionnaire, enabling the characterization of their backgrounds. Additionally, participants disclosed their frequency of fast-food consumption and engagement in physical activities, utilizing validated assessment tools. The collected data was meticulously compiled into an Excel spreadsheet and subjected to rigorous statistical analysis. Descriptive statistics, such as percentages and proportions, were employed to delineate the body weight status of the participants. Employing chi-square tests, our study identified significant associations between fast-food consumption, levels of physical activity, and body weight categories. Furthermore, through binary logistic regression analysis, potential risk factors contributing to overweight and obesity within the young employee cohort were elucidated. Our findings revealed a disconcerting trend, with 6% of participants classified as underweight, 32% within the normal weight range, and a substantial 62% categorized as overweight or obese. These outcomes underscore the alarming prevalence of overweight and obesity among young private-sector employees, particularly within the bustling urban landscape of Colombo, Sri Lanka. The data strongly imply a robust correlation between fast-food consumption, sedentary behaviors, and higher body weight categories, reflective of the evolving lifestyle patterns associated with the nation's economic growth. This study emphasizes the urgent need for effective interventions to counter the detrimental effects of fast-food consumption. The implementation of awareness campaigns elucidating the adverse health consequences of fast food, coupled with comprehensive nutritional education, can empower individuals to make informed dietary choices. Workplace interventions, including the provision of healthier meal alternatives and the facilitation of physical activity opportunities, are essential in fostering a healthier workforce and mitigating the escalating burden of overweight and obesity in Sri Lanka

Keywords: fast food consumption, obese, overweight, physical activity level

Procedia PDF Downloads 41

Authors: S. M. Mabandla, P. Loveday, C. Gomes, D. T. Maiga, T. T. Phadi

Abstract:

Lead zirconate titanate (PZT) piezoelectric ceramics are widely used in ultrasonic applications due to their ability to effectively convert electrical energy into mechanical vibrations and vice versa. This paper presents a study on the behaviour of various combinations of pairs of PZT piezoelectric ceramic materials positioned adjacent to each other with an intermediate gap submerged in water, where one piezoelectric ceramic material is excited by a cyclic electric field with constant frequency and amplitude displacement. The transmitted ultrasonic sound propagates through the medium and is received by the PZT ceramic at the other end, the ultrasonic sound signal amplitude displacement experiences attenuation during propagation due to acoustic impedance. The investigation focuses on understanding the causes of extremely high amplitude displacement attenuation that have been observed in various combinations of piezoelectric ceramic pairs that are submerged in water arranged in a manner stipulated earlier. by examining various combinations of pairs of these piezoelectric ceramics, their physical, electrical, and acoustic properties, and behaviour and attributing them to the observed significant signal attenuation. The experimental setup involves exciting one piezoelectric ceramic material at one end with a burst square cyclic electric field signal of constant frequency, which generates a burst of ultrasonic sound that propagates through the water medium to the adjacent piezoelectric ceramic at the other end. Mechanical vibrations of a PZT piezoelectric ceramic are measured using a double-beam laser Doppler vibrometer to mimic the incident ultrasonic waves generated and received ultrasonic waves on the other end due to mechanical vibrations of a PZT. The measured ultrasonic sound wave signals are continuously compared to the applied cyclic electric field at both ends. The impedance matching networks are continuously tuned at both ends to eliminate electromechanical impedance mismatch to improve ultrasonic transmission and reception. The study delves into various physical, electrical, and acoustic properties of the PZT piezoelectric ceramics, such as the electromechanical coupling factor, acoustic coupling, and elasticity, among others. These properties are analyzed to identify potential factors contributing to the unusually high acoustic impedance in the water medium between the ceramics. Additionally, impedance-matching networks are investigated at both ends to offset the high signal attenuation and improve overall system performance. The findings will be reported in this paper.

Keywords: acoustic impedance, impedance mismatch, piezoelectric ceramics, ultrasonic sound

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