Search results for: variable shrinkage

Authors: Michael C. Barbecho, Romeo B. Morcilla

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This study focused on the development of a solar powered front wheel drive electric trike for personal use and short distance travel, utilizing solar power and a variable speed transmission to adapt in places where varying road grades and unavailability of plug-in charging stations are of great problems. The actual performance of the vehicle was measured in terms of duration of charging using solar power, distance travel and battery power duration, top speed developed at full power, and load capacity. This project followed the research and development process which involved planning, designing, construction, and testing. Solar charging tests revealed that the vehicle requires 6 to 8 hours sunlight exposure to fully charge the batteries. At full charge, the vehicle can travel 35 km utilizing battery power down to 42%. Vehicle showed top speed of 25 kph at 0 to 3% road grade carrying a maximum load of 122 kg. The maximum climbing grade was 23% with the vehicle carrying a maximum load of 122 kg. Technically the project was feasible and can be a potential model for possible conversion of traditional Philippine made “pedicabs” and gasoline engine powered tricycle into modern electric vehicles. Moreover, it has several technical features and advantages over a commercialized electric vehicle such as the use solar charging system and variable speed power transmission and front drive power train for adaptability in any road gradient.

Keywords: electric vehicle, solar vehicles, front drive, solar, solar power

Procedia PDF Downloads 548

Authors: Milica Karadžić, Lidija Jevrić, Sanja Podunavac-Kuzmanović, Strahinja Kovačević, Anamarija Mandić, Aleksandar Oklješa, Andrea Nikolić, Marija Sakač, Katarina Penov Gaši

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Using chemometric approach, the relationships between the chromatographic lipophilicity and in silico molecular descriptors for twenty-nine selected steroid derivatives were studied. The chromatographic lipophilicity was predicted using artificial neural networks (ANNs) method. The most important in silico molecular descriptors were selected applying stepwise selection (SS) paired with partial least squares (PLS) method. Molecular descriptors with satisfactory variable importance in projection (VIP) values were selected for ANN modeling. The usefulness of generated models was confirmed by detailed statistical validation. High agreement between experimental and predicted values indicated that obtained models have good quality and high predictive ability. Global sensitivity analysis (GSA) confirmed the importance of each molecular descriptor used as an input variable. High-quality networks indicate a strong non-linear relationship between chromatographic lipophilicity and used in silico molecular descriptors. Applying selected molecular descriptors and generated ANNs the good prediction of chromatographic lipophilicity of the studied steroid derivatives can be obtained. This article is based upon work from COST Actions (CM1306 and CA15222), supported by COST (European Cooperation and Science and Technology).

Keywords: artificial neural networks, chemometrics, global sensitivity analysis, liquid chromatography, steroids

Procedia PDF Downloads 318

Authors: Rachid Mosbah, Aziez Chettoum, Zouhir Djerrou, Alberto Mantovani

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Selective serotonin reuptake inhibitors (SSRI) are a class of molecules used in treating depression, anxiety, and mood disorders. Paroxetine (PRT) is one of the mostly prescribed antidepressant which has attracted great attention regarding its side effects in recent years. This study was planned to assess the adverse effects of PRT on the biochemical parameters and reproductive system. Fourteen male Wistar rats were randomly allocated into two groups (7 rats or each): control and treated with PRT at dose of 5mg/kg.bw for two weeks. At the end of the experiment, blood was collected from retro orbital plexus for measuring the biochemical parameters, whereas the reproductive organs were removed for measuring semen quality and the histological investigations. Results showed that PRT induced significant changes in some biochemical parameters and alteration of semen quality including sperm count, spermatids number and sperm viability, motility, and abnormalities. The histopathological examinations of testis and epididymis revealed an alteration of spermatogenesis, cellular disorganization and vacuolization, enlargement of interstitial space, shrinkage and degenerative changes in the epithelium of seminiferous and epididymal tubules with few to nil numbers of spermatozoa in their lumen. In conclusion, PRT treatment caused changes in some biochemical parameters and sperm profile as well as histopathologic effects of reproductive organs.

Keywords: antidepressant, biochemical parameters, reproductive function, paroxetine

Procedia PDF Downloads 106

Authors: Emmanuel Chinagorom Nwadike, Joseph Tagbo Nwabanne, Matthew Ndubuisi Abonyi, Onyemazu Andrew Azaka

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This research focused on the modeling of the convective drying of aerial yam using finite element methods. The thermo-gravimetric analyzer was used to determine the thermal stability of the sample. An aerial yam sample of size 30 x 20 x 4 mm was cut with a mold designed for the purpose and dried in a convective dryer set at 4m/s fan speed and temperatures of 68.58 and 60.56°C. The volume shrinkage of the resultant dried sample was determined by immersing the sample in a toluene solution. The finite element analysis was done with PDE tools in Matlab 2015. Seven kinetic models were employed to model the drying process. The result obtained revealed three regions in the thermogravimetric analysis (TGA) profile of aerial yam. The maximum thermal degradation rates of the sample occurred at 432.7°C. The effective thermal diffusivity of the sample increased as the temperature increased from 60.56°C to 68.58°C. The finite element prediction of moisture content of aerial yam at an air temperature of 68.58°C and 60.56°C shows R² of 0.9663 and 0.9155, respectively. There was a good agreement between the finite element predicted moisture content and the measured moisture content, which is indicative of a highly reliable finite element model developed. The result also shows that the best kinetic model for the aerial yam under the given drying conditions was the Logarithmic model with a correlation coefficient of 0.9991.

Keywords: aerial yam, finite element, convective, effective, diffusivity

Procedia PDF Downloads 127

Authors: Maha Zouaoui Khalifa, Hakim Ben Othman, Hussaney Khaled

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Prior empirical studies have investigated the economic consequences of accounting conservatism by examining its impact on the cost of equity capital (COEC). However, findings are not conclusive. We assume that inconsistent results of such association may be attributed to the regression models used in data analysis. To address this issue, we re-examine the effect of different dimension of accounting conservatism: unconditional conservatism (U_CONS) and conditional conservatism (C_CONS) on the COEC for a sample of listed firms from Middle Eastern and North Africa (MENA) countries, applying quantile regression (QR) approach developed by Koenker and Basset (1978). While classical ordinary least square (OLS) method is widely used in empirical accounting research, however it may produce inefficient and bias estimates in the case of departures from normality or long tail error distribution. QR method is more powerful than OLS to handle this kind of problem. It allows the coefficient on the independent variables to shift across the distribution of the dependent variable whereas OLS method only estimates the conditional mean effects of a response variable. We find as predicted that U_CONS has a significant positive effect on the COEC however, C_CONS has a negative impact. Findings suggest also that the effect of the two dimensions of accounting conservatism differs considerably across COEC quantiles. Comparing results from QR method with those of OLS, this study throws more lights on the association between accounting conservatism and COEC.

Keywords: unconditional conservatism, conditional conservatism, cost of equity capital, OLS, quantile regression, emerging markets, MENA countries

Procedia PDF Downloads 333

Authors: Saba Gachpaz, Hamid Reza Heidari

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The sharp increase in population growth leads to more pressure on agricultural areas to satisfy the food supply. To achieve this, more resources should be consumed and, besides other environmental concerns, highlight sustainable agricultural development. Land-use management is a crucial factor in obtaining optimum productivity. Machine learning is a widely used technique in the agricultural sector, from yield prediction to customer behavior. This method focuses on learning and provides patterns and correlations from our data set. In this study, nine physical control factors, namely, soil classification, electrical conductivity, normalized difference water index (NDWI), groundwater level, elevation, annual precipitation, pH of water, annual mean temperature, and slope in the alluvial plain in Khuzestan (an agricultural hotspot in Iran) are used to decide the best agricultural land use for both rainfed and irrigated agriculture for ten different crops. For this purpose, each variable was imported into Arc GIS, and a raster layer was obtained. In the next level, by using training samples, all layers were imported into the python environment. A random forest model was applied, and the weight of each variable was specified. In the final step, results were visualized using a digital elevation model, and the importance of all factors for each one of the crops was obtained. Our results show that despite 62% of the study area being allocated to agricultural purposes, only 42.9% of these areas can be defined as a suitable class for cultivation purposes.

Keywords: land suitability, machine learning, random forest, sustainable agriculture

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Authors: Ashwini Shripatwar, Mayur Biyani, Nikhil Rao, Rajendra Bodake, Sachin Sane

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This paper documents the correlation of valve cover sealing, cracking, and warpage Finite Element Modelling with observations on engine test development. The valve cover is a component mounted on engine head with a gasket which provides sealing against oil which flows around camshaft, valves, rockers, and other overhead components. Material nonlinearity and contact nonlinearity characteristics are taken into consideration because the valve cover is made of a composite material having temperature dependent elastic-plastic properties and because the gasket load-deformation curve is also nonlinear. The leakage is observed between the valve cover and the engine head due to the insufficient contact pressure. The crack is observed on the valve cover due to force application at a region with insufficient stiffness and with elevated temperature. The valve cover shrinkage is observed during the disassembly process on hot exhaust side bolt holes after the engine has been running. In this paper, an analytical approach is developed to correlate a Finite Element Model with the observed failures and to address the design issues associated with the failure modes in question by making design changes in the model.

Keywords: cracking issue, gasket sealing analysis, nonlinearity of contact and material, valve cover

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Authors: Yahya Al-Gabri

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This study aimed to identify the availability degree of transformational leadership dimensions among heads of scientific departments in the Education Faculty at King Saud University. It also aimed to identify the degree of opinions divergence of the study sample on the availability degree of transformational leadership dimensions among the department heads according to the variable of scientific rank. The researcher used the descriptive approach. The study sample consisted of (34) members of education faculty which chosen randomly. To collect the data, the researcher developed a questionnaire consisting of (47) items distributed on four areas after ensuring validity and reliability. Results showed that the degree of practicing the dimensions of transformational leadership by the heads of scientific departments was medium and the mean was (3.21). The dimension of Individualized consideration came first and had a high degree of availability with a mean of (3.31) and the dimension of idealized influence came secondly and had a medium degree (near of high) of availability with a mean of (3.25), also and the dimension of inspirational motivation came thirdly and had a medium degree of availability with a mean of (3.16), whereas the dimension of intellectual stimulation came finally and had a medium degree of availability with a mean of (3.13). The study also showed that there are no statistically significant differences at the level of significance (0.05) in the availability degree of transformational leadership dimensions among the heads of scientific departments at the Faculty of Education according to the scientific rank variable. Finally, the researcher made a number of recommendations and suggestions.

Keywords: transformational leadership, heads of scientific departments, individualized consideration, idealized influence, inspirational motivation, intellectual stimulation

Procedia PDF Downloads 131

Authors: Khalifa Maha, Ben Othman Hakim, Khaled Hussainey

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Prior empirical studies have investigated the economic consequences of accounting conservatism by examining its impact on the cost of equity capital (COEC). However, findings are not conclusive. We assume that inconsistent results of such association may be attributed to the regression models used in data analysis. To address this issue, we re-examine the effect of different dimension of accounting conservatism: unconditional conservatism (U_CONS) and conditional conservatism (C_CONS) on the COEC for a sample of listed firms from Middle Eastern and North Africa (MENA) countries, applying quantile regression (QR) approach developed by Koenker and Basset (1978). While classical ordinary least square (OLS) method is widely used in empirical accounting research, however it may produce inefficient and bias estimates in the case of departures from normality or long tail error distribution. QR method is more powerful than OLS to handle this kind of problem. It allows the coefficient on the independent variables to shift across the distribution of the dependent variable whereas OLS method only estimates the conditional mean effects of a response variable. We find as predicted that U_CONS has a significant positive effect on the COEC however, C_CONS has a negative impact. Findings suggest also that the effect of the two dimensions of accounting conservatism differs considerably across COEC quantiles. Comparing results from QR method with those of OLS, this study throws more lights on the association between accounting conservatism and COEC.

Keywords: unconditional conservatism, conditional conservatism, cost of equity capital, OLS, quantile regression, emerging markets, MENA countries

Procedia PDF Downloads 343

Authors: Nitza Davidovitch, Yael Yossel-Eisenbach

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The purpose of the study was to inquire whether there was a change in the shaping of undergraduate students’ digitally-oriented study pattern in the pre-Covid (2016-2017) versus post-Covid period (2022-2023), as affected by three factors: social background characteristics, high school, and academic background characteristics. These two-time points were cauterized by dramatic changes in teaching and learning at institutions of higher education. The data were collected via cross-sectional surveys at two-time points, in the 2016-2017 academic school year (N=443) and in the 2022-2023 school year (N=326). The questionnaire was distributed on social media and it includes questions on demographic background characteristics, previous studies in high school and present academic studies, and questions on learning and reading habits. Method of analysis: A. Statistical descriptive analysis, B. Mean comparison tests were conducted to analyze the variations in the mean score for the digitally-oriented learning pattern variable at two-time points (pre- and post-Covid) in relation to each of the independent variables. C. Analysis of variance was performed to test the main effects and the interactions. D. Applying linear regression, the research aimed to examine the combined effect of the independent variables on shaping students' digitally-oriented learning habits. The analysis includes four models. In all four models, the dependent variable is students’ perception of digitally oriented learning. The first model included social background variables; the second model included scholastic background as well. In the third model, the academic background variables were added, and the fourth model includes all the independent variables together with the variable of period (pre- and post-COVID). E. Factor analysis confirms using the principal component method with varimax rotation; the variables were constructed by a weighted mean of all the relevant statements merged to form a single variable denoting a shared content world. The research findings indicate a significant rise in students’ perceptions of digitally-oriented learning in the post-COVID period. From a gender perspective, the impact of COVID on shaping a digital learning pattern was much more significant for female students. The socioeconomic status perspective is eliminated when controlling for the period, and the student’s job is affected - more than all other variables. It may be assumed that the student’s work pattern mediates effects related to the convenience offered by digital learning regarding distance and time. The significant effect of scholastic background on shaping students’ digital learning patterns remained stable, even when controlling for all explanatory variables. The advantage that universities had over colleges in shaping a digital learning pattern in the pre-COVID period dissipated. Therefore, it can be said that after COVID, there was a change in how colleges shape students’ digital learning patterns in such a way that no institutional differences are evident with regard to shaping the digital learning pattern. The study shows that period has a significant independent effect on shaping students’ digital learning patterns when controlling for the explanatory variables.

Keywords: learning pattern, COVID, socioeconomic status, digital learning

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Authors: Takuma Yamamoto

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Present study investigated the relationship between elementary school children’s prosocial behavior in classroom and satisfaction with school life (approval and victimization from other children) with considering from the perspective of classroom social goal structures (prosocial and compliance goal structures). Participants were 755 elementary school children (393 boys, 362 girls, mean range= 10-12, 5th grader and 6th grader) who were living in Chugoku District, Japan. They filled up questionnaire which was consisted of Murakami, Nishimura and Sakurai’s (2016) prosocial behavior toward friend scale, Kawamura and Tagami’s (1997) satisfaction in classroom scale and Ohtani, Okada, Nakaya and Ito’s (2016) classroom social goal structures scale. Regression lines that satisfaction in classroom is dependent variable and prosocial behavior is independent variable for each class were drawn. There were two types of classroom which children’s prosocial behavior correlated with satisfaction positively and did not. Then one-way MANOVA was conducted to further describe two types of classroom which prosocial behavior increased satisfaction in classroom (type 1) and prosocial behavior decreased satisfaction (type 2). MANOVA for Prosocial goal structure was significant, type 1 > type 2. There were two key findings from this study. First, MANOVA for prosocial goal structure was significant. Second, high score of prosocial goal structure was not necessary condition for the classroom type which children’s prosocial behavior correlated with satisfaction. The implications from these key findings were: (1) in the low prosocial goal structure classroom, children will not behave prosocially because of their negative expectation for the effect of prosocial behavior, (2) this study can be a contribution for classroom management that teachers need to consider about the negative possibilities of prosocial behavior when they try to increase the amount of children’s positive behavior.

Keywords: elementary school children, classroom social goal structure, satisfaction with school life, prosocial behavior

Procedia PDF Downloads 222

Authors: Rachida Ouysse

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This paper proposes a constrained principal components (CnPC) estimator for efficient estimation of large-dimensional factor models when errors are cross sectionally correlated and the number of cross-sections (N) may be larger than the number of observations (T). Although principal components (PC) method is consistent for any path of the panel dimensions, it is inefficient as the errors are treated to be homoskedastic and uncorrelated. The new CnPC exploits the assumption of bounded cross-sectional dependence, which defines Chamberlain and Rothschild’s (1983) approximate factor structure, as an explicit constraint and solves a constrained PC problem. The CnPC method is computationally equivalent to the PC method applied to a regularized form of the data covariance matrix. Unlike maximum likelihood type methods, the CnPC method does not require inverting a large covariance matrix and thus is valid for panels with N ≥ T. The paper derives a convergence rate and an asymptotic normality result for the CnPC estimators of the common factors. We provide feasible estimators and show in a simulation study that they are more accurate than the PC estimator, especially for panels with N larger than T, and the generalized PC type estimators, especially for panels with N almost as large as T.

Keywords: high dimensionality, unknown factors, principal components, cross-sectional correlation, shrinkage regression, regularization, pseudo-out-of-sample forecasting

Procedia PDF Downloads 129

Authors: Esther M. Folarin, Evans Osabuohien, Ademola Onabote

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Agriculture constitutes an important part of development and poverty mitigation in lower-middle-income countries, like Nigeria. The level of agricultural productivity in the Nigerian economy in line with the level of demand necessary to meet the desired expectation of the Nigerian populace is threatening to meeting the standard of the United Nations (UN) Sustainable Development Goals (SDGs); This includes the SDG-2 (achieve food security through agricultural productivity). The overall objective of the study is to reveal the performance of the interaction variable in the model among other factors that help in the achievement of greater Nigerian agricultural productivity. The study makes use of Wave 4 (2018/2019) of the Living Standard Measurement Studies, Integrated Survey on Agriculture (LSMS-ISA). Qualitative analysis of the information was also used to provide complimentary answers to the quantitative analysis done in the study. The study employed human capital theory and Grossman’s theory of health Demand in explaining the relationships that exist between the variables within the model of the study. The study engages the Instrumental Variable Regression technique in achieving the broad objectives among other techniques for the other specific objectives. The estimation results show that there exists a positive relationship between female healthcare and the level of female agricultural productivity in Nigeria. In conclusion, the study emphasises the need for more provision and empowerment for greater female access to healthcare and educational attainment levels that aids higher female agricultural productivity and consequently an improvement in the total agricultural productivity of the Nigerian economy.

Keywords: agricultural productivity, education, female, healthcare, investment

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Authors: Mezhoud Samy, Toumi Youcef, Boukendekdji Otmane

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Nowadays, industrial by-products and waste are increasing along with public needs increase. The engineering sector has turned to sustainable development by emphasizing the aspects of environmental and life cycle assessment as an important objective. Among this waste, the remains of the red bricks (DBR) may be an alternative worth checking out, given their availability and abundance at the construction sites. In this context, this work aims to valorize DBR in the concrete road (BR). The incorporation of DBR is carried out by the substitution of the granular fractions of mixtures from noble quarry materials. The experimental plan aims to determine the physico-mechanical performance and environmental performance of manufactured BRs from DBR with a cement content (6.5%) and compared with a control BR without DBR. The studied characteristics are proctor, resistance to compression, resistance to flexural tensile at 7 and 28 days, modulus of elasticity, and total shrinkage. The results of this experimental study showed that the characteristics of recycled aggregates (DBR) are lower than those of natural aggregates but remain acceptable with respect to regulations. Results demonstrate the mechanical performance of BR made from less DBR than the control BR without DBR but remains appreciable and encourage their jobs in the road sector. Recycled aggregates can constitute an interesting economic and ecological alternative but require elementary precautions before any use.

Keywords: life cycle assessment, brick waste, road concrete, performance

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Authors: Levent Dumenci, Laura A. Siminoff

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Health literacy has been shown to predict a variety of health outcomes. Reliable identification of persons with limited cancer health literacy (LCHL) has been proved questionable with existing instruments using an arbitrary cut point along a continuum. The CHLT-6, however, uses a latent mixture modeling approach to identify persons with LCHL. The purpose of this study was to estimate two-week and six-month stability of identifying persons with LCHL using the CHLT-6 with a discrete latent variable approach as the underlying measurement structure. Using a test-retest design, the CHLT-6 was administered to cancer patients with two-week (N=98) and six-month (N=51) intervals. The two-week and six-month latent test-retest agreements were 89% and 88%, respectively. The chance-corrected latent agreements estimated from Dumenci’s latent kappa were 0.62 (95% CI: 0.41 – 0.82) and .47 (95% CI: 0.14 – 0.80) for the two-week and six-month intervals, respectively. High levels of latent test-retest agreement between limited and adequate categories of cancer health literacy construct, coupled with moderate to good levels of change-corrected latent agreements indicated that the CHLT-6 classification of limited versus adequate cancer health literacy is relatively stable over time. In conclusion, the measurement structure underlying the instrument allows for estimating classification errors circumventing limitations due to arbitrary approaches adopted by all other instruments. The CHLT-6 can be used to identify persons with LCHL in oncology clinics and intervention studies to accurately estimate treatment effectiveness.

Keywords: limited cancer health literacy, the CHLT-6, discrete latent variable modeling, latent agreement

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Authors: Vinod B. Suryawanshi, Ajit D. Kelkar

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Glass fiber reinforced composites materials, due their unique properties such as high mechanical strength to weight ratio, corrosion resistance, and impact resistance have huge potential as structural materials in automotive, construction and transportation applications. However, these properties often come at higher cost owing to complex design methods, difficult manufacturing processes and raw material cost. In this paper, a cost effective design and manufacturing approach for a composite cantilever beam structure is presented. A constant stress (variable cross section) beam concept has been used to design and optimize the shape of composite cantilever beam and thus obtain the reduction in material used. The variable cross section beam was fabricated from the glass epoxy prepregs using cost effective out of autoclave process. The drop ply technique has been successfully used to obtain the variation in the cross section along the span of the beam. In order to test the beam and validate the design, the beam was subjected to different end loads. Strain gauges were mounted along the length of the beam to obtain strains in the beam at different sections and loads. The strain values were used to calculate the flexural strength and bending stresses in the beam. The stresses obtained through strain measurements from the experiment were found to be uniform along the span of the beam, and thus validates the design. Finally, the finite element model for the constant stress beam was developed using commercial finite element simulation software. It was observed that the simulation results agreed very well with the experimental results.

Keywords: beams, composites, constant cross-section, structures

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Authors: Monika Szymańska-Czerwińska, Agnieszka Jodełko, Krzysztof Niemczuk

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Q fever (coxiellosis) is an infectious disease of animals and humans causes by C. burnetii and widely distributed throughout the world. Cattle and small ruminants are commonly known as shedders of C. burnetii. The aims of this study were the evaluation of seroprevalence and shedding of C. burnetii in cattle. Genotypes of the pathogen present in the tested specimens were also identified using MLVA (Multiple Locus Variable-Number Tandem Repeat Analysis) and MST (multispacer sequence typing) methods. Sampling was conducted in different regions of Poland in 2018-2021. In total, 2180 bovine serum samples from 801 cattle herds were tested by ELISA (enzyme-linked immunosorbent assay). 489 specimens from 157 cattle herds such as: individual milk samples (n=407), bulk tank milk (n=58), vaginal swabs (n=20), placenta (n=3) and feces (n=1) were subjected to C. burnetii specific qPCR. The qPCR (IS1111 transposon-like repetitive region) was performed using Adiavet COX RealTime PCR kit. Genotypic characterization of the strains was conducted utilizing MLVA and MST methods. MLVA was performed using 6 variable loci. The overall herd-level seroprevalence of C. burnetii infection was 36.74% (801/2180). Shedders were detected in 29.3% (46/157) cattle herds in all tested regions. ST 61 sequence type was identified in 10 out of 18 genotyped strains. Interestingly one strain represents sequence type which has never been recorded previously. MLVA method identified three previously known genotypes: most common was J but also I and BE were recognized. Moreover, a one genotype has never been described previously. Seroprevalence and shedding of C. burnetii in cattle is common and strains are genetically diverse.

Keywords: Coxiella burnetii, cattle, MST, MLVA, Q fever

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Authors: Mamadou Dione, Eric Matzner-lober, Philippe Alexandre

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The Energy Transition Act defined by the French State has precise implications on Renewable Energies, in particular on its remuneration mechanism. Until then, a purchase obligation contract permitted the sale of wind-generated electricity at a fixed rate. Tomorrow, it will be necessary to sell this electricity on the Market (at variable rates) before obtaining additional compensation intended to reduce the risk. This sale on the market requires to announce in advance (about 48 hours before) the production that will be delivered on the network, so to be able to predict (in the short term) this production. The fundamental problem remains the variability of the Wind accentuated by the geographical situation. The objective of the project is to provide, every day, short-term forecasts (48-hour horizon) of wind production using weather data. The predictions of the GFS model and those of the ECMWF model are used as explanatory variables. The variable to be predicted is the production of a wind farm. We do two approaches: a direct approach that predicts wind generation directly from weather data, and an integrated approach that estimâtes wind from weather data and converts it into wind power by power curves. We used machine learning techniques to predict this production. The models tested are random forests, CART + Bagging, CART + Boosting, SVM (Support Vector Machine). The application is made on a wind farm of 22MW (11 wind turbines) of the Compagnie du Vent (that became Engie Green France). Our results are very conclusive compared to the literature.

Keywords: forecast aggregation, machine learning, spatio-temporal dynamics modeling, wind power forcast

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Authors: Martins Onyekwelu Onuorah, Jnr Dahiru Usman

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Introduction: In the realm of public health, the threat posed by Monkeypox continues to elicit concern, prompting rigorous studies to understand its dynamics and devise effective containment strategies. Particularly significant is its recurrence in variable populations, such as the observed outbreak in Nigeria in 2022. In light of this, our study undertakes a meticulous analysis, employing a data-driven approach to explore, validate, and propose optimized intervention strategies tailored to the distinct dynamics of Monkeypox within varying demographic structures. Utilizing a deterministic mathematical model, we delved into the intricate dynamics of Monkeypox, with a particular focus on a variable population context. Our qualitative analysis provided insights into the disease-free equilibrium, revealing its stability when R0 is less than one and discounting the possibility of backward bifurcation, as substantiated by the presence of a single stable endemic equilibrium. The model was rigorously validated using real-time data from the Nigerian 2022 recorded cases for Epi weeks 1 – 52. Transitioning from qualitative to quantitative, we augmented our deterministic model with optimal control, introducing three time-dependent interventions to scrutinize their efficacy and influence on the epidemic's trajectory. Numerical simulations unveiled a pronounced impact of the interventions, offering a data-supported blueprint for informed decision-making in containing the disease. A comprehensive cost-effectiveness analysis employing the Infection Averted Ratio (IAR), Average Cost-Effectiveness Ratio (ACER), and Incremental Cost-Effectiveness Ratio (ICER) facilitated a balanced evaluation of the interventions’ economic and health impacts. In essence, our study epitomizes a holistic approach to understanding and mitigating Monkeypox, intertwining rigorous mathematical modeling, empirical validation, and economic evaluation. The insights derived not only bolster our comprehension of Monkeypox's intricate dynamics but also unveil optimized, cost-effective interventions. This integration of methodologies and findings underscores a pivotal stride towards aligning public health imperatives with economic sustainability, marking a significant contribution to global efforts in combating infectious diseases.

Keywords: monkeypox, equilibrium states, stability, bifurcation, optimal control, cost-effectiveness

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Authors: Aid Abdelkrim

Abstract:

A method of fatigue damage accumulation based upon application of energy parameters of the fatigue process is proposed in the paper. Using this model is simple, it has no parameter to be determined, it requires only the knowledge of the curve W–N (W: strain energy density N: number of cycles at failure) determined from the experimental Wöhler curve. To examine the performance of nonlinear models proposed in the estimation of fatigue damage and fatigue life of components under random loading, a batch of specimens made of 6082 T 6 aluminium alloy has been studied and some of the results are reported in the present paper. The paper describes an algorithm and suggests a fatigue cumulative damage model, especially when random loading is considered. This work contains the results of uni-axial random load fatigue tests with different mean and amplitude values performed on 6082T6 aluminium alloy specimens. The proposed model has been formulated to take into account the damage evolution at different load levels and it allows the effect of the loading sequence to be included by means of a recurrence formula derived for multilevel loading, considering complex load sequences. It is concluded that a ‘damaged stress interaction damage rule’ proposed here allows a better fatigue damage prediction than the widely used Palmgren–Miner rule, and a formula derived in random fatigue could be used to predict the fatigue damage and fatigue lifetime very easily. The results obtained by the model are compared with the experimental results and those calculated by the most fatigue damage model used in fatigue (Miner’s model). The comparison shows that the proposed model, presents a good estimation of the experimental results. Moreover, the error is minimized in comparison to the Miner’s model.

Keywords: damage accumulation, energy model, damage indicator, variable loading, random loading

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Authors: Hari Krishna Ayyappa, Reenu Singh

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Rising population and restricted land for development has led towards the growth of vertical buildings and small complexes. It provides many possibilities to change the shape and size of internal space in addition to the social impacts on the commercial spaces. With the increased volatility of necessities of people, the need for mental and physical comfort has continuously increased. . Living in a small space musts minimalist and space- saving cabinetwork results to sustain mortal good. This paper attempts to explore the Influence of Using Minimalist Furniture on the Efficiency of the commercial Space interiors by means of the variable resulting from preceding studies based on literature. A literature review was conducted on research articles to understand the contributing variables in a well designed small commercial spaces. A questionnaire survey was conducted to understand the layout of small commercial spaces with respect to Environmental impact, material, Design elements, Modern approach, Layered lightings, and colours. The problem of small spaces can be resolved by some ways; it's still needed for cabinetwork to develop to be more innovative to accommodate small living spaces. Since cabinetwork is a necessity and not luxury, everybody is in need of it. The spatial factors affecting overall satisfaction at a detailed position were bandied. The variable helped in proposing design ideation and mock ups to explore improved interiors. This paper concludes that most of the principles of the minimalist approach have been overlooked at, which had an impact on the space efficiency in commercial spaces like storage rooms, office area, retail stores, restaurants, and other spaces where business is conducted.

Keywords: materials, modern approach, space efficiency, tall commercial buildings

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Authors: Patel Darshan Shaileshkumar, M. G. Vanza

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Black cotton soil is problematic soil for any construction work. Black cotton soil contains montmorillonite in its structure. Due to this mineral, black cotton soil will attain maximum swelling and shrinkage. Due to these volume changes, it is necessary to stabilize black cotton soil before the construction of the road. For soil stabilization use of pozzolanic waste is found to be a good solution by some researchers. The palm kernel shell ash (PKSA) is a pozzolanic material that can be used for soil stabilization. Basically, PKSA is a waste material, and it is available at a cheap cost. Palm kernel shell is a waste material generated in palm oil mills. Then palm kernel shell is used in industries instead of coal for power generation. After the burning of a palm kernel shell, ash is formed; the ash is called palm kernel shell ash (PKSA). The PKSA contains a free lime content that will react chemically with the silicate and aluminate of black cotton soil and forms a C-S-H and C-A-H gel which will bines soil particles together and reduce the plasticity of the soil. In this study, the PKSA is added to the soil. It was found that with the addition of PKSA content in the soil, the liquid limit of the soil is decreased, the plastic limit of the soil is increased, and the plasticity of the soil is decreased. The group index value of the soil is evaluated, and it was found that with the addition of PKSA GI value of the soil is decreased, which indicates the strength of the soil is improved.

Keywords: palm kernel shell ash, black cotton soil, liquid limit, group index, plastic limit, plasticity index

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Authors: Mohammad Hossein Bayati Chaleshtari, Hadi Khoramishad

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Minimizing the stress concentration around triangular cutout in infinite perforated plates subjected to a uniform heat flux induces thermal stresses is an important consideration in engineering design. Furthermore, understanding the effective parameters on stress concentration and proper selection of these parameters enables the designer to achieve a reliable design. In the analysis of thermal stress, the effective parameters on stress distribution around cutout include fiber angle, flux angle, bluntness and rotation angle of the cutout for orthotropic materials. This paper was tried to examine effect of these parameters on thermal stress analysis of infinite perforated plates with central triangular cutout. In order to achieve the least amount of thermal stress around a triangular cutout using a novel swarm intelligence optimization technique called dragonfly optimizer that inspired by the life method and hunting behavior of dragonfly in nature. In this study, using the two-dimensional thermoelastic theory and based on the Likhnitskiiʼ complex variable technique, the stress analysis of orthotropic infinite plate with a circular cutout under a uniform heat flux was developed to the plate containing a quasi-triangular cutout in thermal steady state condition. To achieve this goal, a conformal mapping function was used to map an infinite plate containing a quasi- triangular cutout into the outside of a unit circle. The plate is under uniform heat flux at infinity and Neumann boundary conditions and thermal-insulated condition at the edge of the cutout were considered.

Keywords: infinite perforated plate, complex variable method, thermal stress, optimization method

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Authors: Adewale Oladapo, C. A. Afolami

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The study analyzed the effect of micro credit access on poverty reduction among small scale women entrepreneurs in Ondo state, Nigeria. Primary data were collected in a cross-sectional survey of 100 randomly selected woman entrepreneurs. These were drawn in multistage sampling process covering four local government areas (LGAS). Data collected include socio economics characteristics of respondents, access to micro credit, sources of micro credit, and constraints faced by the entrepreneur in sourcing for micro credit. Data were analyzed using descriptive statistics, Foster, Greer and Thorbecke (FGT) index of poverty measure, Gini coefficients and probit regression analysis. The study found that respondents sampled for the survey were within the age range of 31-40 years with mean age 38.6%. Mostly (56.0%) of the respondents were educated to the tune of primary school. Majority (87.0%) of the respondents were married with fairly large household size of (4-5). The poverty index analysis revealed that most (67%) of the sample respondents were poor. The result of the Probit regression analyzed showed that income was a significant variable in micro credit access, while the result of the Gini coefficient revealed a very high income inequality among the respondents. The study concluded that most of the respondents were poor and return on investment (income) was an important variable that increased the chance of respondents in sourcing for micro-credit loan and recommended that income realized by entrepreneur should be properly documented to facilitate loan accessibility.

Keywords: entrepreneurs, income, micro-credit, poverty

Procedia PDF Downloads 107

Authors: Yohannes Bisa Biramo

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This study examined the meditational role of surface acting and deep acting on the relationship between calling orientation and work engagement of teachers in secondary schools of Wolaita Zone, Wolaita, Ethiopia. A predictive non-experimental correlational design was performed among 300 secondary school teachers. Stratified random sampling followed by a systematic random sampling technique was used as the basis for selecting samples from the target population. To analyze the data, Structural Equation Modeling (SEM) was used to test the association between the independent variables and the dependent variables. Furthermore, the goodness of fit of the study variables was tested using SEM to see and explain the path influence of the independent variable on the dependent variable. Confirmatory factor analysis (CFA) was conducted to test the validity of the scales in the study and to assess the measurement model fit indices. The analysis result revealed that calling was significantly and positively correlated with surface acting, deep acting and work engagement. Similarly, surface acting was significantly and positively correlated with deep acting and work engagement. And also, deep acting was significantly and positively correlated with work engagement. With respect to mediation analysis, the result revealed that surface acting mediated the relationship between calling and work engagement and also deep acting mediated the relationship between calling and work engagement. Besides, by using the model of the present study, the school leaders and practitioners can identify a core area to be considered in recruiting and letting teachers teach, in giving induction training for newly employed teachers and in performance appraisal.

Keywords: calling, surface acting, deep acting, work engagement, mediation, teachers

Procedia PDF Downloads 57

Authors: S. I. Usenko, V. N. Golubeva, I. A. Konopkina, I. V. Astakhova, O. V. Vakhnina, A. A. Korableva, A. A. Kalinina, K. B. Zhogova

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Gold can be determined in natural objects and manufactured articles of different origin. The up-to-date status of research and problems of high gold level determination in alloys and manufactured articles are described in detail in the literature. No less important is the task of this metal determination in minerals, process products and waste pieces. The latters, as objects of gold content chemical analysis, are most hard-to-study for two reasons: Because of high requirements to accuracy of analysis results and because of difference in chemical and phase composition. As a rule, such objects are characterized by compound, variable and very often unknown matrix composition that leads to unpredictable and uncontrolled effect on accuracy and other analytical characteristics of analysis technique. In this paper, the methods for the determination of gold are described, using flame atomic-absorption spectrophotometry and gravimetric analysis technique. The techniques are aimed at gold determination in a solution for gold etching (KJ+J2), in the technological mixture formed after cleaning stainless steel members of vacuum-deposit installation with concentrated nitric and hydrochloric acids as well as in gold-containing powder resulted from liquid wastes reprocessing. Optimal conditions for sample preparation and analysis of liquid and solid waste specimens of compound and variable matrix composition were chosen. The boundaries of relative resultant error were determined for the methods within the range of gold mass concentration from 0.1 to 30g/dm3 in the specimens of liquid wastes and mass fractions from 3 to 80% in the specimens of solid wastes.

Keywords: microelectronics waste pieces, gold, sample preparation, atomic-absorption spectrophotometry, gravimetric analysis technique

Procedia PDF Downloads 180

Authors: Restituto I. Rodelas

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The higher education has adopted the outcomes-based education from K-12. In this approach, the teacher uses any teaching and learning strategies that enable the students to achieve the learning outcomes. The students may be required to exert more effort and figure things out on their own. Hence, outcomes-based students are assumed to be more responsible and more capable of applying the knowledge learned. Another approach that the higher education in the Philippines is starting to adopt from other countries is blended learning. This combination of classroom and fully online instruction and learning is expected to be more effective. Participating in the online sessions, however, is entirely up to the students. Thus, the effect of blended learning on the performance of students in Statistics may be mediated by outcomes-based education. If there is a significant positive mediating effect, then blended learning can be optimized by integrating outcomes-based education. In this study, the sample will consist of four blended learning Statistics classes at Jose Rizal University in the second semester of AY 2015–2016. Two of these classes will be assigned randomly to the experimental group that will be handled using outcomes-based education. The two classes in the control group will be handled using the traditional lecture approach. Prior to the discussion of the first topic, a pre-test will be administered. The same test will be given as posttest after the last topic is covered. In order to establish equality of the groups’ initial knowledge, single factor ANOVA of the pretest scores will be performed. Single factor ANOVA of the posttest-pretest score differences will also be conducted to compare the performance of the experimental and control groups. When a significant difference is obtained in any of these ANOVAs, post hoc analysis will be done using Tukey's honestly significant difference test (HSD). Mediating effect will be evaluated using correlation and regression analyses. The groups’ initial knowledge are equal when the result of pretest scores ANOVA is not significant. If the result of score differences ANOVA is significant and the post hoc test indicates that the classes in the experimental group have significantly different scores from those in the control group, then outcomes-based education has a positive effect. Let blended learning be the independent variable (IV), outcomes-based education be the mediating variable (MV), and score difference be the dependent variable (DV). There is mediating effect when the following requirements are satisfied: significant correlation of IV to DV, significant correlation of IV to MV, significant relationship of MV to DV when both IV and MV are predictors in a regression model, and the absolute value of the coefficient of IV as sole predictor is larger than that when both IV and MV are predictors. With a positive mediating effect of outcomes-base education on the effect of blended learning on student performance, it will be recommended to integrate outcomes-based education into blended learning. This will yield the best learning results.

Keywords: outcome-based teaching, blended learning, face-to-face, student-centered

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Authors: Mohammad Sadegh Allahyari, Sorush Marzban

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The main aim of this study was to investigate the factors affecting farmers' attitude of the Shanderman District in Masal (Guilan Province in the north of Iran), towards the concepts of multifunctional agriculture. The statistical population consisted of all 4908 in Shanderman.The sample of the present study consisted of 209 subjects who were selected from the total population using the Bartlett et al. Table. Questionnaire as the main tool of data collection was divided in two parts. The first part of questionnaire consisted of farmers' profiles regarding individual, technical-agronomic, economic and social characteristics. The second part included items to identify the farmers’ attitudes regarding different aspects of multifunctional agriculture. The validity of the questionnaire was assessed by professors and experts. Cronbach's alpha was used to determine the reliability (α= 0.844), which is considered an acceptable reliability value. Overall, the average scores of attitudes towards multifunctional agriculture show a positive tendency towards multifunctional agriculture, considering farmers' attitudes of the Shanderman district (SD = 0.53, M = 3.81). Results also highlight a significant difference between farmers' income source levels (F = 0.049) and agricultural literature review (F = 0.022) toward farmers' attitudes considering multifunctional agriculture (p < 0.05). Pearson correlations also indicated that there is a positive relationship between positive attitudes and family size (r = 0.154), farmers' experience (r = 0.246), size of land under cultivation (r = 0.186), income (r = 0.227), and social contribution activities (r = 0.224). The results of multiple regression analyses showed that the variation in the dependent variable depended on the farmers' experience in agricultural activities and their social contribution activities. This means that the variables included in the regression analysis are estimated to explain 12 percent of the variation in the dependent variable.

Keywords: multifunctional agriculture, attitude, effective factor, sustainable agriculture

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Authors: Monjurul Hasan, Golam Kibria, Abdus Salam

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Pervious concrete is a form of lightweight porous concrete, obtained by eliminating the fine aggregate from the normal concrete mix. The advantages of this type of concrete are lower density, lower cost due to lower cement content, lower thermal conductivity, relatively low drying shrinkage, no segregation and capillary movement of water. In this paper an investigation is made on the mechanical response of the pervious concrete at zero fine level (zero fine concrete) made with local brick aggregate. Effect of aggregate size variation on the strength, void ratio and permeability of the zero fine concrete is studied. Finally, a comparison is also presented between the stone aggregate made pervious concrete and brick aggregate made pervious concrete. In total 75 concrete cylinder were tested for compressive strength, 15 cylinder were tested for void ratio and 15 cylinder were tested for permeability test. Mix proportion (cement: Coarse aggregate) was kept fixed at 1:6 (by weights), where water cement ratio was valued 0.35 for preparing the sample specimens. The brick aggregate size varied among 25mm, 19mm, 12mm. It has been found that the compressive strength decreased with the increment of aggregate size but permeability increases and concrete made with 19mm maximum aggregate size yields the optimum value. No significant differences on the strength and permeability test are observed between the brick aggregate made zero fine concrete and stone aggregate made zero fine concrete.

Keywords: pervious concrete, brick aggregate concrete, zero fine concrete, permeability, porosity

Procedia PDF Downloads 523

Authors: Bhavna Malik

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The study is build on a theoretical framework that links characteristics of job, key attitudes and intention to leave, why faculty may be disengaging from institutional service. The literature indicates that job characteristics, key attitudes and intention to leave are very important for effective organizational functioning. In general, the literature showed that some job characteristics might be the antecedents of job satisfaction and the aggregate variable job scope was positively associated with organizational commitment, and these key attitudes predicted intention to leave negatively. The present study attempted to propose a new integrative model of the relationships among job characteristics, key attitudes, and intention to leave. The main purpose of the present study is to examine the effects of job characteristics on intention to leave. While examining the role of job characteristics, the mediating roles of key attitudes were taken into account in order to better understand how job characteristics affect the exhibition of intention to leave. The secondary purpose is to investigate the effects of job characteristics on key attitudes, and the effects of key attitudes on intention to leave. Job characteristics of remuneration, resource for professional activities, career opportunities were positively associated with the work attitude of job satisfaction. The aggregate job scope was positively associated with the work attitude of organizational commitment although no single job characteristic was significantly associated with organizational commitment. Commitment, however, did not significantly affect time spent on institutional service. Two job characteristics—time spent on research and time spent on teaching—were negatively associated with this behavior. In general, the literature showed that some job characteristics might be the antecedents of job satisfaction and the aggregate variable job scope was positively associated with organizational commitment, and these key attiudes predicted intention to leave negatively. In turn, job satisfaction and organizational commitment were negatively associated with the intention to leave. In addition to these, organizational commitment was negatively associated with the intention to leave. However, no significant direct association was found between job characteristics and intention to leave.

Keywords: Job Characteristics Model, job satisfaction, organizational commitment, intention to leave

Procedia PDF Downloads 466