Search results for: mixed effects models

Authors: Suvorov Vasyl, Filipchuk Viktor

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Developmental Dysplasia of the Hip (DDH) is a frequent pathology in pediatric orthopedist’s practice. Neglected or residual cases of DDH in walking patients are usually treated using pelvic osteotomies. Plastic changes take place in hinge points due to acetabulum reorientation during surgery. Classically described hinge points and a traditional division of pelvic osteotomies on reshaping and reorientation are currently debated. The purpose of this article was to evaluate biomechanical changes during the most commonly used pelvic osteotomies (Salter, Dega, Pemberton) for DDH treatment in pediatric patients. Methods: virtual pelvic models of 2- and 6-years old patients were created, material properties were assigned, pelvic osteotomies were simulated and biomechanical changes were evaluated using finite element analysis (FEA). Results: it was revealed that the patient's age has an impact on pelvic bones and cartilages density (in younger patients the pelvic elements are more pliable - p<0.05). Stress distribution after each of the abovementioned pelvic osteotomy was assessed in 2- and 6-years old patients’ pelvic models; hinge points were evaluated. The new term "restriction point" was introduced, which means a place where restriction of acetabular deformity correction occurs. Pelvic ligaments attachment points were mainly these restriction points. Conclusions: it was found out that there are no purely reshaping and reorientation pelvic osteotomies as previously believed; the pelvic ring acts as a unit in carrying out the applied load. Biomechanical overload of triradiate cartilage during Salter osteotomy in 2-years old patient and in 2- and 6-years old patients during Pemberton osteotomy was revealed; overload of the posterior cortical layer in the greater sciatic notch in 2-years old patient during Dega osteotomy was revealed. Level of Evidence – Level IV, prognostic.

Keywords: developmental dysplasia of the hip, pelvic osteotomy, finite element analysis, hinge point, biomechanics

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Authors: Babak Moradi, Hassan Zare-Maivan

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A greenhouse investigation has been conducted to study the effect of crude oil on morphology and protein content of Avicennia marina plant. Avicennia marina seeds were sown in different concentrations of the crude oil mixed soil (i.e., 2.5, 5, 7.5, and 10 w/w). Controls and replicates were also set up. Morphological traits were recorded 4 months after plantation. Avicennia marina seedlings could tolerate up to 10% (w/w). Results demonstrated that there was a reduction in plant shoot and root biomass with the increase of crude oil concentration. Plant height, total leaf number and length reduced significantly with increase of crude oil contamination. Investigation revealed that there is a great impact of crude oil contamination on protein content of the roots of the experimental plant. Protein content of roots grown in different concentrations of crude oil were more than those of the control plant. Further, results also showed that protein content was increased with increased concentration of crude oil.

Keywords: Avicennia marina, morphology, oil contamination, protein content

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Authors: Hadjer Sadoune, Liza Lamini, Scherazade Krim, Amel Djouadi, Rachida Rihani

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Deep neural networks are highly regarded for their accuracy in predicting intricate fermentation processes. Their ability to learn from a large amount of datasets through artificial intelligence makes them particularly effective models. The primary obstacle in improving the performance of these models is to carefully choose the suitable hyperparameters, including the neural network architecture (number of hidden layers and hidden units), activation function, optimizer, learning rate, and other relevant factors. This study predicts biogas production from real wastewater treatment plant data using a sophisticated approach: hybrid Bayesian optimization with a tree-structured Parzen estimator (BO-TPE) for an optimised deep neural network (DNN) model. The plant utilizes an Upflow Anaerobic Sludge Blanket (UASB) digester that treats industrial wastewater from soft drinks and breweries. The digester has a working volume of 1574 m3 and a total volume of 1914 m3. Its internal diameter and height were 19 and 7.14 m, respectively. The data preprocessing was conducted with meticulous attention to preserving data quality while avoiding data reduction. Three normalization techniques were applied to the pre-processed data (MinMaxScaler, RobustScaler and StandardScaler) and compared with the Non-Normalized data. The RobustScaler approach has strong predictive ability for estimating the volume of biogas produced. The highest predicted biogas volume was 2236.105 Nm³/d, with coefficient of determination (R2), mean absolute error (MAE), and root mean square error (RMSE) values of 0.712, 164.610, and 223.429, respectively.

Keywords: anaerobic digestion, biogas production, deep neural network, hybrid bo-tpe, hyperparameters tuning

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Authors: Niroshan K. Walgama Wellalage, Tieling Zhang, Richard Dwight

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State-based Markov deterioration models (SMDM) sometimes fail to find accurate transition probability matrix (TPM) values, and hence lead to invalid future condition prediction or incorrect average deterioration rates mainly due to drawbacks of existing nonlinear optimization-based algorithms and/or subjective function types used for regression analysis. Furthermore, a set of separate functions for each condition state with age cannot be directly derived by using Markov model for a given bridge element group, which however is of interest to industrial partners. This paper presents a new approach for generating Homogeneous SMDM model output, namely, the Modified Weibull approach, which consists of a set of appropriate functions to describe the percentage condition prediction of bridge elements in each state. These functions are combined with Bayesian approach and Metropolis Hasting Algorithm (MHA) based Markov Chain Monte Carlo (MCMC) simulation technique for quantifying the uncertainty in model parameter estimates. In this study, factors contributing to rail bridge deterioration were identified. The inspection data for 1,000 Australian railway bridges over 15 years were reviewed and filtered accordingly based on the real operational experience. Network level deterioration model for a typical bridge element group was developed using the proposed Modified Weibull approach. The condition state predictions obtained from this method were validated using statistical hypothesis tests with a test data set. Results show that the proposed model is able to not only predict the conditions in network-level accurately but also capture the model uncertainties with given confidence interval.

Keywords: bridge deterioration modelling, modified weibull approach, MCMC, metropolis-hasting algorithm, bayesian approach, Markov deterioration models

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Authors: Gabrielle Robertson, Matthew Downs, Joseph Dagher

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Iron deposition in the brain has been linked with a host of neurological disorders such as Alzheimer’s, Parkinson’s, and Multiple Sclerosis. While some treatment options exist, there are no objective measurement tools that allow for the monitoring of iron levels in the brain in vivo. An emerging Magnetic Resonance Imaging (MRI) method has been recently proposed to deduce iron concentration through quantitative measurement of magnetic susceptibility. This is a multi-step process that involves repeated modeling of physical processes via approximate numerical solutions. For example, the last two steps of this Quantitative Susceptibility Mapping (QSM) method involve I) mapping magnetic field into magnetic susceptibility and II) mapping magnetic susceptibility into iron concentration. Process I involves solving an ill-posed inverse problem by using regularization via injection of prior belief. The end result from Process II highly depends on the model used to describe the molecular content of each voxel (type of iron, water fraction, etc.) Due to these factors, the accuracy and repeatability of QSM have been an active area of research in the MRI and medical imaging community. This work aims to estimate iron concentration in the brain via a single step. A synthetic numerical model of the human head was created by automatically and manually segmenting the human head on a high-resolution grid (640x640x640, 0.4mm³) yielding detailed structures such as microvasculature and subcortical regions as well as bone, soft tissue, Cerebral Spinal Fluid, sinuses, arteries, and eyes. Each segmented region was then assigned tissue properties such as relaxation rates, proton density, electromagnetic tissue properties and iron concentration. These tissue property values were randomly selected from a Probability Distribution Function derived from a thorough literature review. In addition to having unique tissue property values, different synthetic head realizations also possess unique structural geometry created by morphing the boundary regions of different areas within normal physical constraints. This model of the human brain is then used to create synthetic MRI measurements. This is repeated thousands of times, for different head shapes, volume, tissue properties and noise realizations. Collectively, this constitutes a training-set that is similar to in vivo data, but larger than datasets available from clinical measurements. This 3D convolutional U-Net neural network architecture was used to train data-driven Deep Learning models to solve for iron concentrations from raw MRI measurements. The performance was then tested on both synthetic data not used in training as well as real in vivo data. Results showed that the model trained on synthetic MRI measurements is able to directly learn iron concentrations in areas of interest more effectively than other existing QSM reconstruction methods. For comparison, models trained on random geometric shapes (as proposed in the Deep QSM method) are less effective than models trained on realistic synthetic head models. Such an accurate method for the quantitative measurement of iron deposits in the brain would be of important value in clinical studies aiming to understand the role of iron in neurological disease.

Keywords: magnetic resonance imaging, MRI, iron deposition, machine learning, quantitative susceptibility mapping

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Authors: C. Chaiyaraksa, T. Khamko

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This study investigated the influence of limestone and sepiolite on heavy metals accumulation in the soil and soybean. The soil was synthesized to contaminate with zinc 150 mg/kg, copper 100 mg/kg, and cadmium 1 mg/kg. The contaminated soil was mixed with limestone and sepiolite at the ratio of 1:0, 0:1, 1:1, and 2:1. The amount of soil modifier added to soil was 0.2%, 0.4%, and 0.8%. The metals determination was performed on soil both before and after soybean planting and in the root, shoot, and seed of soybean after harvesting. The study was also on metal translocate from root to seed and on bioaccumulation factor. Using of limestone and sepiolite resulted in a reduction of metals accumulated in soybean. For soil containing a high concentration of copper, cadmium, and zinc, a mixture of limestone and sepiolite (1:1) was recommended to mix with soil with the amount of 0.2%. Zinc could translocate from root to seed more than copper, and cadmium. From studying the movement of metals from soil to accumulate in soybean, the result was that soybean could absorb the highest amount of cadmium, followed by zinc, and copper, respectively.

Keywords: heavy metals, limestone, sepiolite, soil, soybean

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Authors: Mustapha Kamel Mihoubi, Essadik Kerkar, Abdelhamid Hebbouche

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

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

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Authors: Hannah M. Russell

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‘The Attach Project’ (TAP), is an educational intervention aimed at improving educational and socio-emotional outcomes for children who are looked after. TAP is underpinned by Attachment Theory and is adapted from Dyadic Developmental Psychotherapy (DDP), which is a treatment for children and young people impacted by complex trauma and disorders of attachment. TAP has been implemented in primary schools in Northern Ireland throughout the 2018/19 academic year. During this time, a design and implementation study has been conducted to assess the promise of effectiveness for the future dissemination and ‘scaling-up’ of the programme for a larger, randomised control trial. TAP has been designed specifically for implementation in a school setting and is comprised of a whole school element and a more individualised Key Adult-Key Child pairing. This design and implementation study utilises a mixed-methods research design consisting of quantitative, qualitative, and observational measures with stakeholder input and involvement being considered an integral component. The use of quantitative measures, such as self-report questionnaires prior to and eight months following the implementation of TAP, enabled the analysis of the strengths and direction of relations between the various components of the programme, as well as the influence of implementation factors. The use of qualitative measures, incorporating semi-structured interviews and focus groups, enabled the assessment of implementation factors, identification of implementation barriers, and potential methods of addressing these issues. Observational measures facilitated the continual development and improvement of ‘TAP training’ for school staff. Preliminary findings have provided evidence of promise for the effectiveness of TAP and indicate the potential benefits of introducing this type of attachment-based intervention across other educational settings. This type of intervention could benefit not only children who are looked after but all children who may be impacted by complex trauma or disorders of attachment. Furthermore, findings from this study demonstrate that it is possible for children to form a secondary attachment relationship with a significant adult in school. However, various implementation factors which should be addressed were identified throughout the study, such as the necessity of protected time being introduced to facilitate the development of a positive Key Adult- Key Child relationship. Furthermore, additional ‘re-cap’ training is required in future dissemination of the programme, to maximise ‘attachment friendly practice’ in the whole staff team. Qualitative findings have also indicated that there is a general opinion across school staff that this type of Key Adult- Key Child pairing could be more effective if it was introduced as soon as children begin primary school. This research has provided ample evidence for the need to introduce relationally based interventions in schools, to help to ensure that children who are looked after, or who are impacted by complex trauma or disorders of attachment, can thrive in the school environment. In addition, this research has facilitated the identification of important implementation factors and barriers to implementation, which can be addressed prior to the ‘scaling-up’ of TAP for a robust, randomised controlled trial.

Keywords: attachment, complex trauma, educational interventions, implementation

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Authors: Isaac Kayode Ogunlade

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Data acquisition (DAQ) is the process by which physical phenomena from the real world are transformed into an electrical signal(s) that are measured and converted into a digital format for processing, analysis, and storage by a computer. The DAQ is designed using PIC18F4550 microcontroller, communicating with Personal Computer (PC) through USB (Universal Serial Bus). The research deployed initial knowledge of data acquisition system and embedded system to develop a weather data acquisition device using LM35 sensor to measure weather parameters and the use of Artificial Intelligence(Artificial Neural Network - ANN)and statistical approach(Autoregressive Integrated Moving Average – ARIMA) to predict precipitation (rainfall). The device is placed by a standard device in the Department of Meteorology, Federal University of Technology, Akure (FUTA) to know the performance evaluation of the device. Both devices (standard and designed) were subjected to 180 days with the same atmospheric condition for data mining (temperature, relative humidity, and pressure). The acquired data is trained in MATLAB R2012b environment using ANN, and ARIMAto predict precipitation (rainfall). Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Correction Square (R2), and Mean Percentage Error (MPE) was deplored as standardize evaluation to know the performance of the models in the prediction of precipitation. The results from the working of the developed device show that the device has an efficiency of 96% and is also compatible with Personal Computer (PC) and laptops. The simulation result for acquired data shows that ANN models precipitation (rainfall) prediction for two months (May and June 2017) revealed a disparity error of 1.59%; while ARIMA is 2.63%, respectively. The device will be useful in research, practical laboratories, and industrial environments.

Keywords: data acquisition system, design device, weather development, predict precipitation and (FUTA) standard device

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Authors: M. Karaman, H. Catalkaya

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Due to the complex nature of cyber attacks and their effects ranging from personal to governmental level, it becomes one of the priority tasks for operation planners to take into account the risks, influences and effects of cyber attacks. However it can also be embedded or integrated technically with electronic warfare planning, cyber operation planning is needed to have a sole and broadened perspective. This perspective embodies itself firstly in operational design and then military decision making process. In order to find out the ill-structured problems, understand or visualize the operational environment and frame the problem, operational design can help support cyber operation planners and commanders. After having a broadened and conceptual startup with cyber operational design, military decision making process will follow the principles of design into more concrete elements like reaching results after risk management and center of gravity analysis of our and the enemy. In this paper we tried to emphasize the importance of cyber operational design, cyber operation planning and its integration to military decision making problem. In this foggy, uncertain and unaccountable cyber security environment, it is inevitable to stay away from cyber attacks. Therefore, a cyber operational design should be formed with line of operations, decisive points and end states in cyber then a tactical military decision making process should be followed with cyber security focus in order to support the whole operation.

Keywords: cyber operational design, military decision making process (MDMP), operation planning, end state

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Authors: Florencio D. De Los Reyes, Magdaleno R. Vasquez Jr., Mark Daniel G. De Luna, Peerasak Paoprasert

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The effect of adding silica nanoparticles (SiNPs) obtained from rice husk, and phosphorus and nitrogen based compounds namely 9,10-dihydro-9-oxa-10-phosphaphenantrene-10-oxide (DOPO) and melamine, respectively, on the flammability of polystyrene (PS) was studied using response surface methodology (RSM). The flammability of PS was reduced as the limiting oxygen index (LOI) values increased when the flame retardant additives were added. DOPO exhibited the best retarding property increasing the LOI value of PS by 42.4%. A quadratic model for LOI was obtained from the RSM results, with percent loading of SiNPs, DOPO, and melamine, as independent variables. The observed increase in the LOI value as the percent loading of the flame retardant additives is increased, was attributed both to the main effects and synergistic effects of the parameters, as the LOI response of SiNPs is greatly enhanced by the addition of DOPO and melamine, as shown by the response surface plots. This indicates the potential of producing a cheaper, effective, and non-toxic multi-flame retardant system for the polymeric system via different flame retarding mechanisms.

Keywords: flame retardancy, polystyrene, response surface methodology, rice husk, silica nanoparticle

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Authors: Cecilia Sosa, Fernanda Figueroa, Leonardo Calzada

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Biosphere reserves (BR) are considered as the main strategy for biodiversity and ecosystems conservation. Mexican BR are mainly inhabited by rural communities who strongly depend on forests and their resources. Even though the dual objective of conservation and development has been sought in BR, land cover change is a common process in these areas, while most rural communities are highly marginalized, partly as a result of restrictions imposed by conservation to the access and use of resources. Achieving ecosystems conservation and social development face serious challenges. Factors such as financial support for development projects (public/private), environmental conditions, infrastructure and regional economic conditions might influence both land use change and wellbeing. Examining the temporal trends of conservation and development in BR is central for the evaluation of outcomes for these conservation strategies. In this study, we analyzed changes in primary vegetation cover (as a proxy for conservation) and the index of marginalization (as a proxy for development) in Mexican BR (2000-2015); we also explore the influence of various factors affecting these trends, such as conservation-development projects financial support (public or private), geographical distribution in ecoregions (as a proxy for shared environmental conditions) and in economic zones (as a proxy for regional economic conditions). We developed a spatial analysis at the municipal scale (2,458 municipalities nationwide) in ArcGIS, to obtain road densities, geographical distribution in ecoregions and economic zones, the financial support received, and the percent of municipality area under protection by protected areas and, particularly, by BR. Those municipalities with less than 25% of area under protection were regarded as part of the protected area. We obtained marginalization indexes for all municipalities and, using MODIS in Google Earth Engine, the number of pixels covered by primary vegetation. We used a linear mixed model in RStudio for the analysis. We found a positive correlation between the marginalization index and the percent of primary vegetation cover per year (r=0.49-0.5); i.e., municipalities with higher marginalization also show higher percent of primary vegetation cover. Also, those municipalities with higher area under protection have more development projects (r=0.46) and some environmental conditions were relevant for percent of vegetation cover. Time, economic zones and marginalization index were all important. Time was particularly, in 2005, when both marginalization and deforestation decreased. Road densities and financial support for conservation-development projects were irrelevant as factors in the general correlation. Marginalization is still being affected by the conservation strategies applied in BR, even though that this management category considers both conservation and development of local communities as its objectives. Our results suggest that roads densities and support for conservation-development projects have not been a factor of poverty alleviation. As better conservation is being attained in the most impoverished areas, we face the dilemma of how to improve wellbeing in rural communities under conservation, since current strategies have not been able to leave behind the conservation-development contraposition.

Keywords: deforestation, local development, marginalization, protected areas

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Authors: Carol Anne Hargreaves

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A key issue in stock investment is how to select representative features for stock selection. The objective of this paper is to firstly determine whether an automated stock investment system, using machine learning techniques, may be used to identify a portfolio of growth stocks that are highly likely to provide returns better than the stock market index. The second objective is to identify the technical features that best characterize whether a stock’s price is likely to go up and to identify the most important factors and their contribution to predicting the likelihood of the stock price going up. Unsupervised machine learning techniques, such as cluster analysis, were applied to the stock data to identify a cluster of stocks that was likely to go up in price – portfolio 1. Next, the principal component analysis technique was used to select stocks that were rated high on component one and component two – portfolio 2. Thirdly, a supervised machine learning technique, the logistic regression method, was used to select stocks with a high probability of their price going up – portfolio 3. The predictive models were validated with metrics such as, sensitivity (recall), specificity and overall accuracy for all models. All accuracy measures were above 70%. All portfolios outperformed the market by more than eight times. The top three stocks were selected for each of the three stock portfolios and traded in the market for one month. After one month the return for each stock portfolio was computed and compared with the stock market index returns. The returns for all three stock portfolios was 23.87% for the principal component analysis stock portfolio, 11.65% for the logistic regression portfolio and 8.88% for the K-means cluster portfolio while the stock market performance was 0.38%. This study confirms that an automated stock investment system using machine learning techniques can identify top performing stock portfolios that outperform the stock market.

Keywords: machine learning, stock market trading, logistic regression, cluster analysis, factor analysis, decision trees, neural networks, automated stock investment system

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Authors: Lindie Grebe

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This paper reports on a study that explored the strategizing practices of professional accountants in the mining industry, based on Jarratt and Stiles’ dominant strategizing practice models framework. Drawing on a strategy-as-practice perspective, the paper recognises qualified professional accountants in strategic management such as Chief Executive Officers, as strategy practitioners that perform their strategizing practices and praxis within a specific context. The main findings of this paper were produced through semi-structured individual interviews with accountants that perform strategy on a business level in the South African mining industry. Qualitative data were analysed through conversation analysis over two coding-cycles. Findings describe accountant strategists as practitioners who challenge the dominant business model when a disconnect seems to exist between international corporate level strategy and business level strategy in the South African mining industry. Accountant strategy practitioners described their dominant strategizing practice model as incremental change during strategic planning and as a lived experience during strategy implementation. Findings portrayed these strategists as taking initiative as strategy leaders in a dynamic and volatile environment to combine their accounting background with strategic management and challenge the dominant business model. Understanding how accountant strategists perform strategizing offers insight into the social practice of strategic management. This understanding contributes to the body of knowledge on strategizing in the South African mining industry. In addition, knowledge on the transformation of accountants as strategists could provide valuable practice relevant insights for accounting educators and the accounting profession alike.

Keywords: accountant strategists, dominant strategizing practice models framework, mining industry, strategy-as-practice

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Authors: Sulaiman Al-Hinai, Setyawan Widyarto

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The aim of this study is to identify the critically dominating factors on the delays of road constructions in the GCC countries and their effects on project delivery in Arab countries. Towards the achieved of the objectives the study used the empirical literature from the all relevant online sources and database as many as possible. The findings of this study have summarized and short listed of the success factors in the two categories such as internal and external factors have caused to be influenced to delay of road constructions in the Arab regions. However, in the category of internal factors, there are 63 factors short listed from seven group of factors which has revealed to effects on the delay of road constructions especially, the consultant related factors, the contractor related factors, designed related factors, client related factors, labor related factors, material related issues, equipment related issues respectively. Moreover, for external related factors are also considered to summarized especially natural disaster (flood, hurricanes and cyclone etc.), conflict, war, global financial crisis, compensation delay to affected property owner, price fluctuated, unexpected ground conditions (soil and high-water level), changing of government regulations and laws, delays in obtaining permission from municipality, loss of time by traffic control and restrictions at job site, problem with inhabitant of community, delays in providing service from utilities (water and electricity’s) and accident during constructions accordingly. The present study also concluded the effects of above factors which has delay road constructions through increasing of cost and overrun it, taken overtime, creating of disputes, going for lawsuits, finally happening of abandon of projects. Thus, the present study has given the following recommendations to overcome of above problems by increasing of detailed site investigations, ensure careful monitoring and regular meetings, effective site management, collaborative working and effective coordination’s, proper and comprehensive planning and scheduling and ensure full and intensive commitment from all parties accordingly.

Keywords: Arab GCC countries, critical success factors, road constructions delay, project management

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Authors: Patrascu Andrei Tudor

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One of the main problems in high energy physics is the fact that we do not have a complete understanding of the interaction between local and global effects in gauge theory. This has an increasing impact on our ability to access the non-perturbative regime of most of our theories. Our theories, while being based on gauge groups considered to be simple or semi-simple and connected, are expected to be described by their simple local linear approximation, namely the Lie algebras. However, higher homotopy properties resulting in gauge anomalies appear frequently in theories of physical interest. Our assumption that the groups we deal with are simple and simply connected is probably not suitable, and ways to go beyond such assumptions, particularly in gauge theories, where the Lie algebra linear approximation is prevalent, are not known. We approach this problem from two directions: on one side we are explaining the potential role of formal group laws in describing certain higher homotopical properties and interferences with local or perturbative effects, and on the other side, we employ a categorical approach leading to synthetic theory and a way of looking at gauge theories. The topos approach is based on a geometry where the fundamental logic is intuitionistic logic, and hence the ‘tertium non datur’ principle is abandoned. This has a remarkable impact on understanding conformal symmetry and its anomalies in string theory in various dimensions.

Keywords: Gauge theory, formal group laws, Topos theory, conformal symmetry

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Authors: Mohamad Shurair, Fares Almomani, Simon Judd, Rahul Bhosale, Anand Kumar, Ujjal Gosh

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This study evaluated the use of mixed indigenous microalgae (MIMA) as a treatment process for wastewaters and CO2 capturing technology at different temperatures. The study follows the growth rate of MIMA, removals of organic matter, removal of nutrients from synthetic wastewater and its effectiveness as CO2 capturing technology from flue gas. A noticeable difference between the growth patterns of MIMA was observed at different CO2 and different operational temperatures. MIMA showed the highest growth grate when injected with CO2 dosage of 10% and limited growth was observed for the systems injected with 5% and 15 % of CO2 at 30 ◦C. Ammonia and phosphorus removals for Spirulina were 69%, 75%, and 83%, and 20%, 45%, and 75% for the media injected with 0, 5 and 10% CO2. The results of this study show that simple and cost-effective microalgae-based wastewater treatment systems can be successfully employed at different temperatures as a successful CO2 capturing technology even with the small probability of inhibition at high temperatures

Keywords: greenhouse, climate change, CO2 capturing, green algae

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Authors: Paola Montenegro, Maria de los Angeles Balaguera Villa

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In February 2022 Colombia achieved a historic milestone in ensuring universal access to abortion rights with ruling C-055 of 2022 decriminalising abortion up to 24 weeks of gestation. In the context of this triumph and the expansion of telemedicine services in the wake of the COVID-19 pandemic, this research studied the acceptability of self-care abortion in young people (13 - 28 years) through a telemedicine service and also explored the primary needs that should be the focus of such care. The results shine light on a more comprehensive understanding of opportunities and challenges of teleabortion practices in a context that combines overall higher access to technology and low access to reliable information of safe abortion, stigma, and scarcity especially felt by transnational migrants, racialised people, trans men and non-binary people. Through a mixed methods approach, this study collected 5.736 responses to a virtual survey disseminated nationwide in Colombia and 47 in-person interviews (24 of them with people who were assigned female at birth and 21 with local key stakeholders in the abortion ecosystem). Quantitative data was analyzed using Stata SE Version 16.0 and qualitative analysis was completed through NVivo using thematic analysis. Key findings of the research suggest that self-care abortion is practice with growing acceptability among young people, but important adjustments must be made to meet quality of care expectations of users. Elements like quick responses from providers, lower costs, and accessible information were defined by users as decisive factors to choose over the abortion service provider. In general, the narratives in participants about quality care were centred on the promotion of autonomy and the provision of accompaniment and care practices, also perceived as transformative and currently absent of most health care services. The most staggering findings from the investigation are related to current barriers faced by young people in abortion contexts even when the legal barriers have: high rates of scepticism and distrust associated with pitfalls of telehealth and structural challenges associated with lacking communications infrastructure, among a few of them. Other important barriers to safe self-care abortion identified by participants surfaced like lack of privacy and confidentiality (especially in rural areas of the country), difficulties accessing reliable information, high costs of procedures and expenses related to travel costs or having to cease economic activities, waiting times, and stigma are among the primary barriers to abortion identified by participants. Especially in a scenario marked by unprecedented social, political and economic disruptions due to the COVID-19 pandemic, the commitment to design better care services that can be adapted to the identities, experiences, social contexts and possibilities of the user population is more necessary than ever. In this sense, the possibility of expanding access to services through telemedicine brings us closer to the opportunity to rethink the role of health care models in transforming the role of individuals and communities to make autonomous, safe and informed decisions about their own health and well-being.

Keywords: contraception, family planning, premarital fertility, unplanned pregnancy

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Authors: Muzaffer Topgul, Hasan Atac

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After the September 11 attacks, fight against terrorism has risen to higher levels in security concepts of the countries. The following reactions of some nation states have led to the formation of unstable areas in different parts of the World. Especially, in Iraq and Syria, the influences of radical groups have risen with the weakening of the central governments. Turkey (with the geographical proximity to the current crisis) has become a stop on the movement of people who were displaced because of terrorism. In the process, the policies of the Syrian regime resulted in a civil war which is still going on since 2011, and remain as an unresolved crisis. With the extension of the problem, changes occurred in foreign policies of the World Powers; moreover, the ongoing effects of the riots, conflicts of interests of foreign powers, conflicts in the region because of the activities of radical groups increased instability within the country. This case continues to affect the security of Turkey, particularly illegal immigration. It has exceeded the number of two million Syrians who took refuge in Turkey due to the civil war, while continuing uncertainty about the legal status of asylum seekers, besides the security problems of asylum-seekers themselves, there are problems in education, health and communication (language) as well. In this study, we will evaluate the term of immigration through the eyes of national and international law, place the disorganized and illegal immigration in security sphere, and define the elements/components of irregular migration within the changing security concept. Ultimately, this article will assess the effects of the Syrian refuges to Turkey’s short-term, mid-term, and long-term security in the light of the national and international data flows and solutions will be presented to the ongoing problem. While explaining the security problems the data and the donnees obtained from the nation and international corporations will be examined thorough the human security dimensions such as living conditions of the immigrants, the ratio of the genders, especially birth rate occasions, the education circumstances of the immigrant children, the effects of the illegal passing on the public order. In addition, the demographic change caused by the immigrants will be analyzed, the changing economical conditions where the immigrants mostly accumulate, and their participation in public life will be worked on and the economical obstacles sourcing due to irregular immigration will be clarified. By the entire datum gathered from the educational, cultural, social, economic, demographical extents, the regional factors affecting the migration and the role of irregular migration in Turkey’s future security will be revealed by implication to current knowledge sources.

Keywords: displaced people, human security, irregular migration, refugees

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Authors: Abdulaziz Alageel, Martino Luis, Shuya Zhong

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The main focus of this research study is on the challenges faced in decision-making in a supply chain network regarding the facility location while considering carbon emissions. The study aims (i) to locate facilities (i.e., distribution centeres) in a continuous space considering limitations of capacity and the costs associated with opening and (ii) to reduce the cost of carbon emissions by selecting the mode of transportation. The problem is formulated as mixed-integer linear programming. This study hybridised a greedy randomised adaptive search (GRASP) and variable neighborhood search (VNS) to deal with the problem. Well-known datasets from the literature (Brimberg et al. 2001) are used and adapted in order to assess the performance of the proposed method. The proposed hybrid method produces encouraging results based on computational analysis. The study also highlights some research avenues for future recommendations.

Keywords: supply chain, facility location, weber problem, sustainability

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Authors: Masese Chuma Benard, Martin Onsiro Ronald

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Businesses have been using cloud computing more frequently recently because they wish to take advantage of its advantages. However, employing cloud computing also introduces new security concerns, particularly with regard to data security, potential risks and weaknesses that could be exploited by attackers, and various tactics and strategies that could be used to lessen these risks. This study examines data security issues on cloud computing amongst sme’s in Nairobi county, Kenya. The study used the sample size of 48, the research approach was mixed methods, The findings show that data owner has no control over the cloud merchant's data management procedures, there is no way to ensure that data is handled legally. This implies that you will lose control over the data stored in the cloud. Data and information stored in the cloud may face a range of availability issues due to internet outages; this can represent a significant risk to data kept in shared clouds. Integrity, availability, and secrecy are all mentioned.

Keywords: data security, cloud computing, information, information security, small and medium-sized firms (SMEs)

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Authors: Lin Xie, Yang Wang

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An extensive body of research studies suggest that students, teachers, and supervisors can enhance the likelihood of reaching their goals by improving their communication skills. It is highly important to learn how and when to provide different kinds of feedback, e.g. anticipatory, corrective and positive) will gain better result and higher morale. The purpose of this mixed methods research is twofold: 1) To find out what factors affect effective communication among different stakeholders and how these factors affect student learning 2) What are the good practices for improving communication among different stakeholders and improve student achievement. This presentation first begins with an introduction to the recent research on Marshall’s Nonviolent Communication Techniques (NVC), including four important components: observations, feelings, needs, requests. These techniques can be effectively applied at all levels of communication. To develop an in-depth understanding of the relationship among different techniques within, this research collected, compared, and combined qualitative and quantitative data to better improve communication and support student learning.

Keywords: communication, education, language learning, goal achievement, academic success

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Authors: Prateek Bhattacharya

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The definition of 'control' in India is a rapidly evolving concept, owing to varying rights attached to varying securities. Shares with differential voting rights (DVRs) provide the holder with differential rights as to voting, as compared to ordinary equity shareholders of the company. Such DVRs can amount to both superior voting rights and inferior voting rights, where DVRs with superior voting rights amount to providing the holder with golden shares in the company. While DVRs are not a novel concept in India having been recognized since 2000, they were placed on a back burner by the Securities and Exchange Board of India (SEBI) in 2010 after issuance of DVRs with superior voting rights was restricted. In June 2019, the SEBI rekindled the ebbing fire of DVRs, keeping mind the fast-paced nature of the global economy, the government's faith that India’s ‘new age technology companies’ (i.e., Start-Ups) will lead the charge in achieving its goal of India becoming a $5 trillion dollar economy by 2024, and recognizing that the promoters of such Start-Ups seek to raise capital without losing control over their companies. DVRs with superior voting rights guarantee promoters with up to 74% shareholding in Start-Ups for a period of 5 years, meaning that the holder of such DVRs can exercise sole control and material influence over the company for that period. This manner of control has the potential of causing both pro-competitive and anti-competitive effects in the markets where these companies operate. On the one hand, DVRs will allow Start-Up promoters/founders to retain control of their companies and protect its business interests from foreign elements such as private/public investors – in a scenario where such investors have multiple investments in firms engaged in associated lines of business (whether on a horizontal or vertical level) and would seek to influence these firms to enter into potential anti-competitive arrangements with one another, DVRs will enable the promoters to thwart such scenarios. On the other hand, promoters/founders who themselves have multiple investments in Start-Ups, which are in associated lines of business run the risk of influencing these associated Start-Ups to engage in potentially anti-competitive arrangements in the name of profit maximisation. This paper shall be divided into three parts: Part I shall deal with the concept of ‘control’, as deliberated upon and decided by the SEBI and the Competition Commission of India (CCI) under both company/securities law and competition law; Part II shall review this definition of ‘control’ through the lens of DVRs, and Part III shall discuss the aforementioned potential pro-competitive and anti-competitive effects caused by the DVRs by examining the current Indian Start-Up scenario. The paper shall conclude by providing suggestions for the CCI to incorporate a clearer and more progressive concept of ‘control’.

Keywords: competition law, competitive effects, control, differential voting rights, DVRs, investor shareholding, merger control, start-ups

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Authors: Renato Morbidelli, Carla Saltalippi, Alessia Flammini, Tommaso Picciafuoco, Corrado Corradini

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A considerable part of rainfall data to be used in the hydrological practice is available in aggregated form within constant time intervals. This can produce undesirable effects, like the underestimate of the annual maximum rainfall depth, Hd, associated with a given duration, d, that is the basic quantity in the development of rainfall depth-duration-frequency relationships and in determining if climate change is producing effects on extreme event intensities and frequencies. The errors in the evaluation of Hd from data characterized by a coarse temporal aggregation, ta, and a procedure to reduce the non-homogeneity of the Hd series are here investigated. Our results indicate that: 1) in the worst conditions, for d=ta, the estimation of a single Hd value can be affected by an underestimation error up to 50%, while the average underestimation error for a series with at least 15-20 Hd values, is less than or equal to 16.7%; 2) the underestimation error values follow an exponential probability density function; 3) each very long time series of Hd contains many underestimated values; 4) relationships between the non-dimensional ratio ta/d and the average underestimate of Hd, derived from continuous rainfall data observed in many stations of Central Italy, may overcome this issue; 5) these equations should allow to improve the Hd estimates and the associated depth-duration-frequency curves at least in areas with similar climatic conditions.

Keywords: central Italy, extreme events, rainfall data, underestimation errors

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Authors: U.N. Emiri, E. Moroyei

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Mycoflora associated with the seed rot disease of Mucuna sloanei and their effects on nutrient and phytochemical composition of the seeds were investigated. The fungal pathogens implicated in the seed rot disease were Rhizopus stolonifer, Aspergillus flavus, Aspergillus niger, and Fusarium oxysporum. The fungal isolates were aseptically inoculated into healthy M. Sloanei seeds and incubated for 7 days at room temperature of 25 ± 30c. The results of the proximate and mineral analysis in mg/100g of fungal infected and non-infected (control) seeds that were carried out revealed that there was an increase in Moisture and Carbohydrate content of the fungal infected seeds relative to the non-infected seeds (control). However, there was a decrease in Ash, Fibre, Lipid, and Protein content of the fungal infected seeds relative to the non-infected (control). It was observed that moisture had increased from 10.50 ± 0.16 in the non-infected seeds to 17.60 ± 0.20 in the infected samples and Carbohydrate content had also increased from 49.6 ± 0.25 in the non-infected to 52.50 ± 0.29 in the infected seeds. The following parameters decreased in the infected than in the non-infected seeds. They include Ash 2.60 ± 0.12, Crude fibre 1.9 ± 0.08, Lipid 6.50 ± 0.16, and Protein content 18.50 ± 0.06. Similarly, Calcium 2.50 ± 0.12, Phosphorus 1.80 + 0.12 and Potassium 1.80 + 0.09 increased in the infected than in the non-infected seed, while iron 0.20 ± 0.05, Sodium 0.02 ± 0.01 and Magnesium 0.06 ± 0.02 decreased in the infected seeds. All phytochemical contents analyzed increased in the infected seeds viz Tannim 0.50 ± 0.12, Oxalate 1.60 ± 0.05, Hydrogen cyanide 1.82 ± 0.06, and Saponin 2.50+0.28. However, the nutrient compositions and Phytochemical between the infected and non-infected seeds are not significantly different (p > 0.05).

Keywords: Mycoflora, mucuna sloanei, seeds, phytochemical, nutrient composition

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Authors: Mary Konadu

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The rectal route for drug administration is becoming attractive to drug formulators because it can avoid hepatic first-pass effects, decrease gastrointestinal side effects and avoid undesirable effects of meals on drug absorption. Suppositories have been recognized as an alternative to the oral route in situations such as when the patient is comatose, unable to swallow, or when the drug produces nausea or vomiting. Effective drug delivery with appropriate pharmaceutical excipient is key in the production of clinically useful preparations. The high cost of available excipients coupled with other disadvantages have led to the exploration of potential excipients from natural sources. Allanblackia floribunda butter, a naturally occurring lipid, is used for medicinal, culinary, and cosmetic purposes. Different extraction methods (solvent (hexane) extraction, traditional/hot water extraction, and cold/screw press extraction) were employed to extract the oil. The different extracts of A. floribunda oil were analyzed for their physicochemical properties and mineral content. The oil was used as a base to formulate Paracetamol and Diclofenac suppositories. Quality control test were carried out on the formulated suppositories. The %age oil yield for hexane extract, hot water extract, and cold press extract were 50.40 ±0.00, 37.36±0.00, and 20.48±0.00, respectively. The acid value, saponification value, iodine value and free fatty acid were 1.159 ± 0.065, 208.51 ± 8.450, 49.877 ± 0.690 and 0.583 ± 0.032 respectively for hexane extract; 3.480 ± 0.055, 204.672±2.863, 49.04 ± 0.76 and 1.747 ± 0.028 respectively for hot water/traditional extract; 4.43 ± 0.055, 192.05±1.56, 49.96 ± 0.29 and 2.23 ± 0.03 respectively for cold press extract. Calcium, sodium, magnesium, potassium, and iron were minerals found to be present in the A. floribunda butter extracts. The uniformity of weight, hardness, disintegration time, and uniformity of content were found to be within the acceptable range. The melting point ranges for all the suppositories were found to be satisfactory. The cumulative drug release (%) of the suppositories at 45 minutes was 90.19±0.00 (Hot water extract), 93.75±0.00 (Cold Pres Extract), and 98.16±0.00 (Hexane Extract) for Paracetamol suppositories. Diclofenac sodium suppositories had a cumulative %age release of 81.60±0.00 (Hot water Extract), 95.33±0.00 (Cold Press Extract), and 99.20±0.00 (Hexane Extract). The physicochemical parameters obtained from this study shows that Allanblackia floribunda seed oil is edible and can be used as a suppository base. The suppository formulation was successful, and the quality control tests conformed to Pharmacopoeia standard.

Keywords: allanblackia foribunda, paracetamol, diclofenac, suppositories

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Authors: Luís Felipe da Cunha Mendonça

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Normally, rural roads do not have any type of coating, and when they have any coating, they have a high maintenance cost due to the characteristics of natural materials. The Steel Aggregate has specific technical characteristics, which considerably reduce the maintenance costs of rural roads with the execution of the Primary Coating. For use as a primary coating, it must be mixed with clay due to the physical-chemical properties of the material. The application is mainly in the Primary Coating of rural roads due to the cementitious property in the presence of water, offering greater resistance to wear caused by traffic and consequently a longer useful life of the coating. The Steel Aggregate executed on rural roads has reduced particulate emissions and offers normal traffic in any weather condition, as well as creating sustainability. Contribute to the quality of life of communities through improvements in the conditions of rural and urban unpaved roads. Leading to substantial savings in maintenance. Because the durability, if applied correctly, is about 3 years, but if annual monitoring is carried out, it can be extended for more than 5 years.

Keywords: steel slag, co-product, primary coating, steel aggregate

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Authors: Sami W. Tabsh

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The strength of reinforced concrete depends on the member dimensions and material properties. The properties of concrete and steel materials are not constant but random variables. The variability of concrete strength is due to batching errors, variations in mixing, cement quality uncertainties, differences in the degree of compaction and disparity in curing. Similarly, the variability of steel strength is attributed to the manufacturing process, rolling conditions, characteristics of base material, uncertainties in chemical composition, and the microstructure-property relationships. To account for such uncertainties, codes of practice for reinforced concrete design impose resistance factors to ensure structural reliability over the useful life of the structure. In this investigation, the effects of reductions in concrete and reinforcing steel strengths from the nominal values, beyond those accounted for in the structural design codes, on the structural reliability are assessed. The considered limit states are flexure, shear and axial compression based on the ACI 318-11 structural concrete building code. Structural safety is measured in terms of a reliability index. Probabilistic resistance and load models are compiled from the available literature. The study showed that there is a wide variation in the reliability index for reinforced concrete members designed for flexure, shear or axial compression, especially when the live-to-dead load ratio is low. Furthermore, variations in concrete strength have minor effect on the reliability of beams in flexure, moderate effect on the reliability of beams in shear, and sever effect on the reliability of columns in axial compression. On the other hand, changes in steel yield strength have great effect on the reliability of beams in flexure, moderate effect on the reliability of beams in shear, and mild effect on the reliability of columns in axial compression. Based on the outcome, it can be concluded that the reliability of beams is sensitive to changes in the yield strength of the steel reinforcement, whereas the reliability of columns is sensitive to variations in the concrete strength. Since the embedded target reliability in structural design codes results in lower structural safety in beams than in columns, large reductions in material strengths compromise the structural safety of beams much more than they affect columns.

Keywords: code, flexure, limit states, random variables, reinforced concrete, reliability, reliability index, shear, structural safety

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Authors: Ashish Dhamaniya, Satish Chandra

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Speed and traffic volume data are collected on different sections of four lane and six lane roads in three metropolitan cities in India. Speed data are analyzed to fit the statistical distribution to individual vehicle speed data and all vehicles speed data. It is noted that speed data of individual vehicle generally follows a normal distribution but speed data of all vehicle combined at a section of urban road may or may not follow the normal distribution depending upon the composition of traffic stream. A new term Speed Spread Ratio (SSR) is introduced in this paper which is the ratio of difference in 85^th and 50^th percentile speed to the difference in 50^th and 15^th percentile speed. If SSR is unity then speed data are truly normally distributed. It is noted that on six lane urban roads, speed data follow a normal distribution only when SSR is in the range of 0.86 – 1.11. The range of SSR is validated on four lane roads also.

Keywords: normal distribution, percentile speed, speed spread ratio, traffic volume

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Authors: D. Songpol, K. Taweesak, T. Sookyuen

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A social enterprise is an organization that operates commercial business as a source of income with the aim of addressing social and environmental issues. Though it is clear that this kind of organization will benefit society and environment but in practice, it is found that most of social enterprises’ goals cannot be achieved. The most success factors of social enterprises usually rely on individual characteristics of entrepreneurs, especially in educational business. This study aims to find out the magnitude of influence from the components of entrepreneur competencies to social enterprises in education. There are developmental models of research demonstrating that knowledge, skills and attributes affect the success of social enterprises in term of sustainability, social opportunities and innovation leadership. The 5-scale questionnaire was used to collect data from the social entrepreneurs in education who operates in the South East Asian region of 135 samples and then processed by the methods of structural equation models. The results show that the competency of entrepreneurs in attributes has the greatest impact on the success of social enterprises while the skills and knowledge have respectively impact on the social enterprises’ success as well. The reason why attributes of entrepreneurs have the greatest impact on social enterprise success is because, social enterprise is an organization that does not motivate or provide attractive financial incentives to the entrepreneur. Entrepreneurs, who succeed in developing their organizations, therefore need attribute factor higher than normal entrepreneurs, especially those in education sector that have somewhat few human resources to operate their businesses. More importantly, attribute’s traits such as entrepreneurial passion, self-efficacy, entrepreneurial identity and, innovativeness and perseverance will significantly affect the ideology and tolerance of the entrepreneurs once facing the problem in doing business. In conclusion, the education social enterprise would be successful depending on the performance of the entrepreneurs which derives from higher attributes competency.

Keywords: education, entrepreneur competencies, social enterprise, South East Asia

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