Search results for: modified Jones model

Authors: Teja Koduru

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Untreated Lyme disease can lead to neurological, cardiac, and dermatological complications. Rapid diagnosis of the erythema migrans (EM) rash, a characteristic symptom of Lyme disease is therefore crucial to early diagnosis and treatment. In this study, we aim to utilize deep learning frameworks including Tensorflow and Keras to create deep convolutional neural networks (DCNN) to detect images of acute Lyme Disease from images of erythema migrans. This study uses a custom database of erythema migrans images of varying quality to train a DCNN capable of classifying images of EM rashes vs. non-EM rashes. Images from publicly available sources were mined to create an initial database. Machine-based removal of duplicate images was then performed, followed by a thorough examination of all images by a clinician. The resulting database was combined with images of confounding rashes and regular skin, resulting in a total of 683 images. This database was then used to create a DCNN with an accuracy of 93% when classifying images of rashes as EM vs. non EM. Finally, this model was converted into a web and mobile application to allow for rapid diagnosis of EM rashes by both patients and clinicians. This tool could be used for patient prescreening prior to treatment and lead to a lower mortality rate from Lyme disease.

Keywords: Lyme, untreated Lyme, erythema migrans rash, EM rash

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Authors: Renu Sharma, D. C. Saxena, Tanuja Srivastava

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Mechanical properties of ready-to-eat extrudates are perceived by the consumers as one of the quality criteria. Texture quality of any product has a strong influence on the sensory evaluation as well as on the acceptability of the product. The main texture characteristics influencing the product acceptability are crispness, elasticity, hardness and softness. In the present work, the authors investigated one of the most important textural characteristics of extrudates i.e. hardness. A five-level, four-factor central composite rotatable design was employed to investigate the effect of temperature, screw speed, feed moisture content and feed composition mainly rice bran content and their interactions, on the mechanical hardness of extrudates. Among these, feed moisture was found to be a prominent factor affecting the product hardness. It was found that with the increase of feed moisture content, the rice bran proportion leads to increase in hardness of extrudates whereas the increase of temperature leads to decrease of hardness of product. A good agreement between the predicted (26.49 N) and actual value (28.73N) of the response confirms the validation of response surface methodology (RSM)-model.

Keywords: deoiled rice bran, extrusion, rheological properties, RSM

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Authors: Wen-Tsung Ho, Ku-Kuang Chang, Hsin-Yuan Chang

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In this study, we consider an economic lot-size batch-shipment scheduling problem (ELBSP) with extended basic period (EBP) and power-of-two (PoT) policies. In this problem, the supplier using a single facility to manufacture multiple products and equally sized batches are then delivered by the supplier to buyers over an infinite planning horizon. Further, the extended basic period (EBP) and power-of-two (PoT) policy are utilized. Relaxing the production schedule converts the ELBSP to an economic lot-size batch-shipment problem (ELBP) with EBP and PoT policies, and a nonlinear integer programming model of the ELBP is constructed. Using the replenishment cycle division and recursive tightening methods, optimal solutions are then solved separately for each product. The sum of these optimal solutions is the lower bound of the ELBSP. A proposed heuristic method with polynomial complexity is then applied to figure out the near-optimal solutions of the ELBSP. Numerical example is presented to confirm the efficacy of the proposed method.

Keywords: economic lot-size scheduling problem, extended basic period, replenishment cycle division, recursive tightening, power-of-two

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Authors: Ankit Kumar, Balram Dubey

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This study proposes a three dimensional prey-predator model with additional food, provided to predator individuals, including gestation delay in predators and delay in supplying the additional food to predators. It is assumed that the interaction between prey and predator is followed by Holling type-II functional response. We discussed the steady states and their local and global asymptotic behavior for the non-delayed system. Hopf-bifurcation phenomenon with respect to different parameters has also been studied. We obtained a range of predator’s tendency factor on provided additional food, in which the periodic solutions occur in the system. We have shown that oscillations can be controlled from the system by increasing the tendency factor. Moreover, the existence of periodic solutions via Hopf-bifurcation is shown with respect to both the delays. Our analysis shows that both delays play an important role in governing the dynamics of the system. It changes the stability behavior into instability behavior. The direction and stability of Hopf-bifurcation are also investigated through the normal form theory and the center manifold theorem. Lastly, some numerical simulations and graphical illustrations have been carried out to validate our analytical findings.

Keywords: additional food, gestation delay, Hopf-bifurcation, prey-predator

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Authors: Chieh-Chun Chang, Cheng-Ting Shih, Yan-Lin Liu, Shu-Jun Chang, Jay Wu

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With the widespread use of digital mammography (DM), radiation dose evaluation of breasts has become important. X-ray spectra are one of the key factors that influence the absorbed dose of glandular tissue. In this study, we estimated the X-ray spectrum of DM using the expectation maximization (EM) algorithm with the transmission measurement data. The interpolating polynomial model proposed by Boone was applied to generate the initial guess of the DM spectrum with the target/filter combination of Mo/Mo and the tube voltage of 26 kVp. The Monte Carlo N-particle code (MCNP5) was used to tally the transmission data through aluminum sheets of 0.2 to 3 mm. The X-ray spectrum was reconstructed by using the EM algorithm iteratively. The influence of the initial guess for EM reconstruction was evaluated. The percentage error of the average energy between the reference spectrum inputted for Monte Carlo simulation and the spectrum estimated by the EM algorithm was -0.14%. The normalized root mean square error (NRMSE) and the normalized root max square error (NRMaSE) between both spectra were 0.6% and 2.3%, respectively. We conclude that the EM algorithm with transmission measurement data is a convenient and useful tool for estimating x-ray spectra for DM in clinical practice.

Keywords: digital mammography, expectation maximization algorithm, X-Ray spectrum, X-Ray

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Authors: Valentina Narvaez Gaitan, Laura Valentina Rodriguez Leguizamon, Ruben Dario Hernandez B.

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This work describes a physiological signal emulation system that uses electromyography (EMG) signals obtained from muscle sensors in the first instance. These signals are used to extract their characteristics to model and emulate specific arm movements. The main objective of this effort is to develop a new biomedical software system capable of generating physiological signals through the use of embedded systems by establishing the characteristics of the acquired signals. The acquisition system used was Biosignals, which contains two EMG electrodes used to acquire signals from the forearm muscles placed on the extensor and flexor muscles. Processing algorithms were implemented to classify the signals generated by the arm muscles when performing specific movements such as wrist flexion extension, palmar grip, and wrist pronation-supination. Matlab software was used to condition and preprocess the signals for subsequent classification. Subsequently, the mathematical modeling of each signal is performed to be generated by the embedded system, with a validation of the accuracy of the obtained signal using the percentage of cross-correlation, obtaining a precision of 96%. The equations are then discretized to be emulated in the embedded system, obtaining a system capable of generating physiological signals according to the characteristics of medical analysis.

Keywords: classification, electromyography, embedded system, emulation, physiological signals

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Authors: Trupti Meher, Harihar Sahoo

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Premature menopause refers to the occurrence of menopause before the age of 40 years. Women who experience premature menopause either due to biological or induced reasons have a longer duration of exposure to severe symptoms and adverse health consequences when compared to those who undergo menopause at a later age, despite the fact that premature menopause has a profound effect on the health of women. This study attempted to determine the prevalence and predictors of premature menopause among women aged 25-39 years, using data from the National Family Health Survey (NFHS-4) conducted during 2015–16 in India. Descriptive statistics and multinomial logistic regression were used to carry out the result. The results revealed that the prevalence of premature menopause in India was 3.7 percent. Out of which, 2.1 percent of women had experienced natural premature menopause, whereas 1.7 percent had premature surgical menopause. The prevalence of premature menopause was highest in the southern region of India. Further, results of the multivariate model indicated that rural women, women with higher parity, early age at childbearing and women with smoking habits were at a greater risk of premature menopause. A sizeable proportion of women in India are attaining menopause prematurely. Unless due attention is given to this matter, it will emerge as a major problem in India in the future. The study also emphasized the need for further research to enhance knowledge on the problems of premature menopausal women in different socio-cultural settings in India.

Keywords: India, natural menopause, premature menopause, surgical menopause

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Authors: Hamid Ahmadi, Neda Azari Dodaran

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This paper aims to study the structural behavior of tubular KT-joints subjected to axial loading at fire induced elevated temperatures. At first, a finite element (FE) model was developed and validated against the data available from experimental tests. Then, a set of 810 FE analyses were performed to study the influence of temperature and dimensionless geometrical parameters (β, γ, θ, and τ) on the ultimate strength and initial stiffness. The joints were analyzed under two types of axial loading and five different temperatures (20 ºC, 200 ºC, 400 ºC, 550 ºC, and 700 ºC). Results show that the ultimate strength and initial stiffness of KT-joints decrease considerably by increasing the temperature. In the joints having bigger values of the β, the temperature elevation leads to less reduction in ultimate strength; while in the joints with bigger values of the γ, the temperature elevation results in more reduction in ultimate strength. The influence of the θ on the ultimate strength is independent from the temperature. To our knowledge, there is no design formula available for determining the ultimate strength of KT-joints at elevated temperatures. Hence, after parametric study, two equations were developed through nonlinear regression, for calculating the ultimate strength of KT-joints at elevated temperatures.

Keywords: axial loads, fire condition, parametric formula, static strength, tubular KT-joint

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Authors: Joseph M. Rich, Vinay A. Duddalwar, Assad A. Oberai

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Prostate adenocarcinoma is the most common cancer in males, with osseous metastases as the commonest site of metastatic prostate carcinoma (mPC). Treatment monitoring is based on the evaluation and characterization of lesions on multiple imaging studies, including Computed Tomography (CT). Monitoring of the osseous disease burden, including follow-up of lesions and identification and characterization of new lesions, is a laborious task for radiologists. Deep learning algorithms are increasingly used to perform tasks such as identification and segmentation for osseous metastatic disease and provide accurate information regarding metastatic burden. Here, nnUNet was used to produce a model which can segment CT scan images of prostate adenocarcinoma vertebral bone metastatic lesions. nnUNet is an open-source Python package that adds optimizations to deep learning-based UNet architecture but has not been extensively combined with transfer learning techniques due to the absence of a readily available functionality of this method. The IRB-approved study data set includes imaging studies from patients with mPC who were enrolled in clinical trials at the University of Southern California (USC) Health Science Campus and Los Angeles County (LAC)/USC medical center. Manual segmentation of metastatic lesions was completed by an expert radiologist Dr. Vinay Duddalwar (20+ years in radiology and oncologic imaging), to serve as ground truths for the automated segmentation. Despite nnUNet’s success on some medical segmentation tasks, it only produced an average Dice Similarity Coefficient (DSC) of 0.31 on the USC dataset. DSC results fell in a bimodal distribution, with most scores falling either over 0.66 (reasonably accurate) or at 0 (no lesion detected). Applying more aggressive data augmentation techniques dropped the DSC to 0.15, and reducing the number of epochs reduced the DSC to below 0.1. Datasets have been identified for transfer learning, which involve balancing between size and similarity of the dataset. Identified datasets include the Pancreas data from the Medical Segmentation Decathlon, Pelvic Reference Data, and CT volumes with multiple organ segmentations (CT-ORG). Some of the challenges of producing an accurate model from the USC dataset include small dataset size (115 images), 2D data (as nnUNet generally performs better on 3D data), and the limited amount of public data capturing annotated CT images of bone lesions. Optimizations and improvements will be made by applying transfer learning and generative methods, including incorporating generative adversarial networks and diffusion models in order to augment the dataset. Performance with different libraries, including MONAI and custom architectures with Pytorch, will be compared. In the future, molecular correlations will be tracked with radiologic features for the purpose of multimodal composite biomarker identification. Once validated, these models will be incorporated into evaluation workflows to optimize radiologist evaluation. Our work demonstrates the challenges of applying automated image segmentation to small medical datasets and lays a foundation for techniques to improve performance. As machine learning models become increasingly incorporated into the workflow of radiologists, these findings will help improve the speed and accuracy of vertebral metastatic lesions detection.

Keywords: deep learning, image segmentation, medicine, nnUNet, prostate carcinoma, radiomics

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Authors: Rezwana Rahman

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Various simulations have been conducted to understand the particle's macroscopic behavior in the solid-gas multiphase flow in rotating drums in the past. In these studies, the particle-wall no-slip boundary condition was usually adopted. However, the non-slip boundary condition is rarely encountered in real systems. A little effort has been made to investigate the particle behavior at slip boundary conditions. The paper represents a study of the gas-solid flow in a horizontal rotating drum at a slip boundary wall condition. Two different sizes of particles with the same density have been considered. The Eulerian–Eulerian multiphase model with the kinetic theory of granular flow was used in the simulations. The granular pressure at the rolling flow regime with specularity coefficient 1 was examined and compared with that obtained based on the no-slip boundary condition. The results reveal that the profiles of granular pressure distribution on the transverse plane of the drum are similar for both boundary conditions. But, overall, compared with those for the no-slip boundary condition, the values of granular pressure for specularity coefficient 1 are larger for the larger particle and smaller for the smaller particle.

Keywords: boundary condition, eulerian–eulerian, multiphase, specularity coefficient, transverse plane

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Authors: Hakan Ozturk, Aydin Demir, Kemal Edip, Marta Stojmanovska, Julijana Bojadjieva

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There are many factors that affect the behavior of reinforced concrete beams. These can be listed as concrete compressive and reinforcement yield strength, amount of tension, compression and confinement bars, and strain hardening of reinforcement. In the study, support condition of short beams is selected statically indeterminate to first degree. Experimental and numerical analysis are carried for reinforcement concrete (RC) short beams. Dimensions of cross sections are selected as 250mm width and 500 mm height. The length of RC short beams is designed as 2250 mm and these values are constant in all beams. After verifying accurately finite element model, a numerical parametric study is performed with varied diameter of tension reinforcement. Effect of change in diameter is investigated on behavior of RC short beams. As a result of the study, ductility ratios and failure modes are determined, and load-displacement graphs are obtained in order to understand the behavior of short beams. It is deduced that diameter of tension reinforcement plays very important role on the behavior of RC short beams in terms of ductility and brittleness.

Keywords: short beam, reinforced concrete, finite element analysis, longitudinal reinforcement

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Authors: Farah Kanani

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Blue Tide Environmental is a company focused on developing a network of used motor oil recycling facilities across the U.S. They initiated the redesign of its recycling plant in Texas, and aimed to establish an updated carbon footprint of re-refined used motor oils compared to an equivalent product derived from virgin stock that is not re-refined. The aim was to quantify emissions savings of a circular alternative to conventional end-of-life combustion of used motor oil (UMO). To do so, they mandated an ISO-compliant carbon footprint, utilizing complex models requiring geographical and temporal accuracy to accommodate the U.S. refinery market. The quantification of linear and circular flows, proxies for fuel substitution and system expansion for multi-product outputs were all critical methodological choices and were tested through sensitivity analyses. The re-refined system consisted of continuous recycling of UMO and thus, end-of-life is considered non-existent. The unique perspective to this topic will be from a life cycle i.e. holistic one and essentially demonstrate using this example of how a cradle-to-cradle model can be used to quantify a comparative carbon footprint. The intended audience is lubricant manufacturers as the consumers, motor oil industry professionals and other industry members interested in performing a cradle-to-cradle modeling.

Keywords: circularity, used motor oil, re-refining, systems expansion

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Authors: Spandan Sahu, Amiya Kumar Pati, Kishanjit Kumar Khatua

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River is our main source of water which is a form of open channel flow and the flow in open channel provides with many complex phenomenon of sciences that needs to be tackled such as the critical flow conditions, boundary shear stress and depth averaged velocity. During floods, part of a river is carried by the simple main channel and rest is carried by flood plains. For such compound asymmetric channels, the flow structure becomes complicated due to momentum exchange between main channel and adjoining flood plains. Distribution of boundary shear in subsections provides us with the concept of momentum transfer between the interface of main channel and the flood plains. Experimentally, to get better data with accurate results are very complex because of the complexity of the problem. Hence, CES software has been used to tackle the complex processes to determine the shear stresses at different sections of an open channel having asymmetric flood plains on both sides of the main channel and the results is compared with the symmetric flood plains for various geometrical shapes and flow conditions. Error analysis is also performed to know the degree of accuracy of the model implemented.

Keywords: depth average velocity, non prismatic compound channel, relative flow depth, velocity distribution

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Authors: Tam Nguyen

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Self-leadership is strongly tied to the ability to be resilient in the face of adversity. This study aims to demonstrate how a strategy based on a culturally relevant "bamboo metaphor" enables Asian students to cross cultural boundaries and to engage in online discussions to unlock their self-leadership potential. Asian students are influenced to varying degrees by the Confucian heritage culture, which educates students to respect authority, maintain harmony, and avoid public confrontations. This has a significant impact on the cultural readiness of Asian students to express their development as self-leaders. In this research project, researchers as mentors individually assist students, cultivate cognitive progress, encourage and personally ask students to join a process of mentorship program. This study analyzes and interprets the data from a large online seminar in Ho Chi Minh City, Vietnam, where students were trained in self-leadership skills. Focus-group interviews were implemented among 90 students in the program. Findings reveal the emotional needs of Asian students and suggest a cognitive model for developing students' self-awareness, self-confidence, and self-efficacy. The research results are anticipated to be applicable to a broader Asian population with a comparable cultural environment to Vietnam.

Keywords: self-leadership, bamboo resilience, cognitive modeling, Asian culture

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Authors: Sirilak Areerachakul

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Water quality has initiated serious management efforts in many countries. Artificial Neural Network (ANN) models are developed as forecasting tools in predicting water quality trend based on historical data. This study endeavors to automatically classify water quality. The water quality classes are evaluated using 6 factor indices. These factors are pH value (pH), Dissolved Oxygen (DO), Biochemical Oxygen Demand (BOD), Nitrate Nitrogen (NO3N), Ammonia Nitrogen (NH3N) and Total Coliform (T-Coliform). The methodology involves applying data mining techniques using multilayer perceptron (MLP) neural network models. The data consisted of 11 sites of Saen Saep canal in Bangkok, Thailand. The data is obtained from the Department of Drainage and Sewerage Bangkok Metropolitan Administration during 2007-2011. The results of multilayer perceptron neural network exhibit a high accuracy multilayer perception rate at 94.23% in classifying the water quality of Saen Saep canal in Bangkok. Subsequently, this encouraging result could be combined with GIS data improves the classification accuracy significantly.

Keywords: artificial neural network, geographic information system, water quality, computer science

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Authors: Mateusz Mokrogulski, Piotr Śliwka

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The aim of this paper is the identification of periods of excessive credit growth in the Polish banking sector in years 2007-2014 using different methodologies. Due to the lack of precise guidance in CRD IV regarding methods of calculating the credit gap and related deviations from the long-term trends, a few filtering methods are applied, e.g. Hodrick-Prescott and Baxter-King. The solutions based on the switching model are also proposed. The next step represent computations of both the credit gap, and the counter cyclical capital buffer (CCB) rates on a quarterly basis. The calculations are carried out for the entire banking sector in Poland, as well as for its components (commercial and co-operative banks), and different types of loans. The calculations show vividly that in the analysed period there were the times of excessive credit growth. However, the results are different for the above mentioned sub-sectors. Of paramount importance here are mortgage loans, where the outcomes are distorted by high exchange rate fluctuations. The research on the CCB is now going to gain popularity as the buffer will soon become one of the tools of the macro prudential policy under CRD IV. Although the presented method is focused on the Polish banking sector, it can also be applied to other member states. Especially to the Central and Eastern European countries, that are usually characterized by smaller banking sectors compared to EU-15.

Keywords: countercyclical capital buffer, CRD IV, filtering methods, mortgage loans

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Authors: Offer E. Edelstein, Iris Vered, Orly Sarid

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Background: Physical activity (PA) is considered as a major factor in bone density preservation and fracture prevention. Yet, gaps in understanding exist regarding how ethnocultural backgrounds might shape attitudes, intentions, and actual PA participation. Based on the theory of planned behavior (TPB) for predicting PA, the aims of the current study were: i) to compare attitudes, subjective norms, perceived control, intentions and knowledge, across two ethnocultural groups; ii) to evaluate the fit of the model across two ethnocultural groups of women: Israeli-born Jews and Ethiopian immigrants. Methods: Two hundred women (one hundred from each group), aged > 65, completed valid and reliable questionnaires assessing knowledge, TPB components, and actual PA. Results: The level of knowledge on osteoporosis was relatively low in both groups. Intention to participate in PA was the only variable that directly predicted actual PA. Intention to participate in PA served as a mediator among attitudes, subjective norms, perceived control, and actual PA. The TPB components mediated the link between knowledge and intention to participate in PA. Conclusion: It is important to understand and augment interventions that enhance PA, in the community, and with sensitivity concerning each ethnocultural group.

Keywords: attitudes, ethnocultural groups, knowledge, physical activity

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Authors: Firoz Alam Faroque, Ankur Neog

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Earthquake causes significant loss of lives and severe damage to infrastructure. Base isolator is one of the most suitable solutions to make a building earthquake resistant. Base isolation consists of installing an isolator along with the steel plates covered with pads of strong material like steel, rubber, etc. In our study, we have used lead rubber bearing (LRB). The basic idea of seismic isolation is based on the reduction of the earthquake-induced inertia forces by shifting the fundamental period of the structure out of dangerous resonance range, and concentration of the deformation and energy dissipation demands at the isolation and energy dissipation systems, which are designed for this purpose. In this paper, RC frame buildings have been modeled and analyzed by response spectrum method using ETABS software. The LRB used in the model is designed as per uniform building code (UBC) 97. It is found that time period for the base isolated structures are higher than that of the fixed base structure and the value of base shear significantly reduces in the case of base-isolated buildings. It has also been found that buildings with vertical irregularities give better performance as compared to building with plan irregularities using base isolators.

Keywords: base isolation, base shear, irregularities in buildings, lead rubber bearing (LRB)

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Authors: J. Julius Adebayo

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The objective of this paper is to assess the agro-climatic condition of Ibadan in the rain forest ecological zone of Nigeria, using rainfall pattern and temperature between 1978-2018. Data on rainfall and temperature in Ibadan, Oyo State for a period of 40 years were obtained from Meteorological Section of Forestry Research Institute of Nigeria, Ibadan and Oyo State Meteorology Centre. Time series analysis was employed to analyze the data. The trend revealed that rainfall is decreasing slowly and temperature is averagely increasing year after year. The model for rainfall and temperature are Yₜ = 1454.11-8*t and Yₜ = 31.5995 + 2.54 E-02*t respectively, where t is the time. On this basis, a forecast of 20 years (2019-2038) was generated, and the results showed a further downward trend on rainfall and upward trend in temperature, this indicates persistence rainfall shortage and very hot weather for agricultural practices in the southwest rain forest ecological zone. Suggestions on possible solutions to avert climate change crisis and also promote climate-smart agriculture for sustainable food and nutrition security were also discussed.

Keywords: climate change, rainfall pattern, temperature, time series analysis, food and nutrition security

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Authors: Daniel C. Bonzo

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Practical considerations lead to the use of unit of analysis within subjects, e.g., bleeding episodes or treatment-related adverse events, in rare disease settings. This is coupled with data augmentation techniques such as extrapolation to enlarge the subject base. In general, one can think about extrapolation of data as extending information and conclusions from one estimand to another estimand. This approach induces hierarchichal clustered data with varying cluster sizes. Extrapolation of clinical trial data is being accepted increasingly by regulatory agencies as a means of generating data in diverse situations during drug development process. Under certain circumstances, data can be extrapolated to a different population, a different but related indication, and different but similar product. We consider here the problem of estimation (point and interval) using a mixed-models approach under an extrapolation. It is proposed that estimators (point and interval) be constructed using weighting schemes for the clusters, e.g., equally weighted and with weights proportional to cluster size. Simulated data generated under varying scenarios are then used to evaluate the performance of this approach. In conclusion, the evaluation result showed that the approach is a useful means for improving statistical inference in rare disease settings and thus aids not only signal detection but risk-benefit evaluation as well.

Keywords: clustered data, estimand, extrapolation, mixed model

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Authors: Saleh Alzahrani, Halim Boussabaine

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The majority of Public Private Partnership (PPP) are developed based on the rationale that the design, construction, operation, and financing of a public project is to be awarded to a private party within a single contractual framework. PPP project risks normally include the development and construction of a new asset as well as its operation for decades. Undoubtedly the most serious consequences of risks during the construction period are price and time overruns. These events are amongst the most broadly used scenarios in value for money analysis risks. The sources of risk change over the life cycle of a PPP project. In traditional procurement, the public sector normally has to cover all price distress from these risks. At least there is plenty evidence to suggest that price distress is a norm in some of the projects that are delivered under traditional procurement. This paper will find the impact of construction risk factors into actual construction price into PPP projects. The paper will present a brief literature review on PPP risk pricing strategies, and then using system dynamics (SD) to analyses of the risks associated with the estimated project price. Based on the finding from these analyses a risk pricing association model is presented and discussed. The paper concludes with thoughts for future research.

Keywords: Public Private Partnership (PPP), Risk, Risk Pricing, System Dynamics (SD), construction price

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Authors: Fatma Ismailia, Malek Saihi

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This research provides an explanation of exchange incentives on the Tunis stock market from a behavioural point of view. The elucidation of the anomalies of excessive volume of transactions and that of excessive volatility cannot be done without the recourse to the psychological aspects of investors. The excessive confidence has been given the predominant role for the explanation of these phenomena. Indeed, when investors store increments, they become more confident about the precision of their private information and their exchange activities then become more aggressive on the subsequent periods. These overconfident investors carry out the intensive exchanges leading to an increase of securities volatility. The objective of this research is to identify whether the trading volume and the excessive volatility of securities observed on the Tunisian stock market come from the excessive exchange of overconfident investors. We use a sample of daily observations over the period January 1999 - October 2007 and we relied on various econometric tests including the VAR model. Our results provide evidence on the importance to consider the bias of overconfidence in the analysis of Tunis stock exchange specificities. The results reveal that the excess of confidence has a major impact on the trading volume while using daily temporal intervals.

Keywords: overconfidence, trading volume, efficiency, rationality, anomalies, behavioural finance, cognitive biases

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Authors: Godwin A. Otogo, Sansanee Wangvoralak, Graham J. Pierce, Lee C. Hastie, Beth Scott

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The squid Loligo forbesii is suspected to be an important species in marine food webs, as it can strongly impact its prey and be impacted upon by predation, competition, fishing and/or climate variability. To quantify these impacts in the food web, the measurement of its trophic position and ecological role within well-studied ecosystems is essential. An Ecopath model was balanced and run for the Moray Firth ecosystem and was used to investigate the significance of this squid’s trophic roles. The network analysis routine included in Ecopath with Ecosim (EwE) was used to estimate trophic interaction, system indicators (health condition and developmental stage) and food web features. Results indicated that within the Moray Firth squid occupy a top trophic position in the food web and also a major prey item for many other species. Results from Omnivory Index (OI) showed that squid is a generalized feeder transferring energy across wide trophic levels and is more important as a predator than that as a prey in the Moray Firth ecosystem. The results highlight the importance of taking squid into account in the management of Europe’s living marine resources.

Keywords: Squid, Loligo forbesii, Ecopath, Moray Firth, Trophic level

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Authors: Zaouche Mohammed, Amini Mohammed, Foughali Khaled, Hamissi Aicha, Aktouf Mohand Arezki, Boureghda Ilyes

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In this paper, we present a piloting law based on the adaptive differentiators via high order sliding mode controller, by using an aircraft in virtual simulated environment. To deal with the design of an autopilot controller, we propose a framework based on Software in the Loop (SIL) methodology and we use Microsoft^TM Flight Simulator (FS-2004) as the environment for plane simulation. The aircraft dynamic model is nonlinear, Multi-Input Multi-Output (MIMO) and tightly coupled. The nonlinearity resides in the dynamic equations and also in the aerodynamic coefficients' variability. In our case, two (02) aircrafts are used in the flight tests, the Zlin-142 and MQ-1 Predator. For both aircrafts and in a very low altitude flight, we send the piloting control inputs to the aircraft which has stalled due to a command disconnection. Then, we present the aircraft’s dynamic behavior analysis while reestablishing the command transmission. Finally, a comparative study between the two aircraft’s dynamic behaviors is presented.

Keywords: adaptive differentiators, second order sliding modes, dynamic adaptation of the gains, microsoft flight simulator, Zlin-142, MQ-1 predator

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Authors: E. Esra Kasapbaşı, Büşra Yıldırım

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Weak oxidizing radicals, such as alkyl peroxyl derivatives, react with carotenoids through hydrogen atom transfer to form neutral carotenoid radicals. Using the DFT method, it has been observed that s-cis-β-carotene is more stable than all-transforms. In the context of this study, an attempt is made to explain the reaction mechanism of the isomers of β-carotene, which exhibits antioxidant properties, with n-pentyl peroxide, one of the alkyl peroxyl molecules, using the Density Functional Theory (DFT) method. The cis and transforms of β-carotene are used in the study to determine which form is more reactive. For this purpose, Natural Bond Orbital (NBO) charges of all optimized structures are calculated, and electron transfer is determined by examining electron transitions between Highest Occupied Molecular Orbital (HOMO) and Lowest Unoccupied Molecular Orbital (LUMO). Additionally, the radical character and reaction mechanism of β-carotene in a radical environment are attempted to be explained based on the calculations. The theoretical inclination of whether β-carotene in cis or transforms is more active in reaction is also discussed. All these calculations are performed in the gas phase using the Integral Equation Formalism Polarizable Continuum Model IEFPCM method with dichloromethane as the solvent.

Keywords: β-carotene, n-pentyl peroxyl radical, DFT, TD-DFT

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Authors: Srijoni Banerjee

Abstract:

Sequences of some of the candidate genes (e.g., CPE, CDKAL1, GCKR, HSD11B1, IGF2BP2, IRS1, LPIN1, PKLR, TNF, PPARG) implicated in some of the complex disease, e.g. Type II diabetes in man has been compared with other species to investigate phylogenetic affinity. Based on mRNA sequence of these genes of 7 to 8 species, using bioinformatics tools Mega 5, Bioedit, Clustal W, distance matrix was obtained. Phylogenetic trees were obtained by NJ and UPGMA clustering methods. The results of the phylogenetic analyses show that of the species compared: Xenopus l., Danio r., Macaca m., Homo sapiens s., Rattus n., Mus m. and Gallus g., Bos taurus, both NJ and UPGMA clustering show close affinity between clustering of Homo sapiens s. (Man) with Rattus n. (Rat), Mus m. species for the candidate genes, except in case of Lipin1 gene. The results support the functional similarity of these genes in physiological and biochemical process involving man and mouse/rat. Therefore, in understanding the complex etiology and treatment of the complex disease mouse/rate model is the best laboratory choice for experimentation.

Keywords: phylogeny, candidate gene of type-2 diabetes, CPE, CDKAL1, GCKR, HSD11B1, IGF2BP2, IRS1, LPIN1, PKLR, TNF, PPARG

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Authors: Jeanetta Darno

Abstract:

This paper explores the realm of organizational development through the lens of Edgar Schein's seminal work on culture and change. Specifically, the paper will focus on the strategic implementation of Employee Resource Groups (ERGs) as powerful interventions for catalyzing culture change within modern workplaces. Edgar Schein's foundational theories on organizational culture and his renowned model of culture work will serve as the theoretical framework to guide the exploration of how ERGs can be harnessed as transformative tools in organizational development initiatives. Through a review of literature combined with content analysis, this paper will explore how ERGs align with Schein's principles, contribute to development, and drive positive cultural shifts toward inclusion and equity. The paper aims to provide practical insights for organizational leaders, HR practitioners, and change agents looking to integrate ERGs effectively into their culture change efforts, thereby advancing the field of organizational development informed by Schein's influential framework. The objective of the paper is to investigate and understand the intersection between Employee Resource Groups (ERGs) and Edgar Schein's Culture Work within the context of organizational development.

Keywords: inclusive leadership, culture, equity, employee resource groups, organization development

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Authors: Chia-Chun Wu, Ying-Yao Cheng

Abstract:

The purpose of this study was developing the 'short-form BASIC scale' psychotic tendencies subscale so as to provide a more efficient, economical and effective way to assess the mental health of recruits. 1749 students from Naval Recruit Training Center participated in this study. The multidimensional constructs of psychotic tendencies subscale include four dimensions: schizophrenic tendencies, manic tendencies, depression tendencies, and suicidal ideation. We cut down the 36-item psychotic tendencies subscale to 25 items by using multidimension Rasch techniques. They were applied to assess model-data fit and to provide the validity evidence of the short form BASIC scale of psychotic tendencies subscale. The person separation reliabilities of the measures from four dimensions were .70, .67, .74 and .57, respectively. In addition, there is a notable correlation between the length version and short version of schizophrenic tendencies (scaled .89), manic tendencies (.96), depression tendencies (.97) and suicidal ideation (.97). The results have indicated that the development of the study of short-form scale sufficient to replace the original scale. Therefore, it is suggested that short-form basic scale is used to assess the mental health with participants being more willing to answer questions to ensure the validation of assessments.

Keywords: BASIC scale, military, Rasch analysis, short-form scale

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Authors: Shreedevi Moharana, Subashisa Dutta

Abstract:

The present study focuses on the estimation of crop biophysical parameters like crop chlorophyll, nitrogen and water stress at plot scale in the crop fields. To achieve these, we have used high-resolution satellite LISS IV imagery. A new methodology has proposed in this research work, the spectral shape function of paddy crop is employed to get the significant wavelengths sensitive to paddy crop parameters. From the shape functions, regression index models were established for the critical wavelength with minimum and maximum wavelengths of multi-spectrum high-resolution LISS IV data. Moreover, the functional relationships were utilized to develop the index models. From these index models crop, biophysical parameters were estimated and mapped from LISS IV imagery at plot scale in crop field level. The result showed that the nitrogen content of the paddy crop varied from 2-8%, chlorophyll from 1.5-9% and water content variation observed from 40-90% respectively. It was observed that the variability in rice agriculture system in India was purely a function of field topography.

Keywords: crop parameters, index model, LISS IV imagery, plot scale, shape function

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Authors: Fu-Chien Hung, Chi‐Wen Liang

Abstract:

Background: People who suffer from chronic fatigue syndrome (CFS) frequently complain about continuous tiredness, weakness or lack of strength, but without apparent organic etiology. The prevalence rate of the CFS is nearly from 3% to 20%, yet more than 80% go undiagnosed or misdiagnosed as depression. The biopsychosocial model has suggested the associations among the CFS, depressive syndrome, and stress. This study aimed to investigate the difference between individuals with the CFS and with the depressive syndrome on psychophysiological responses under stress. Method: There were 23 participants in the CFS group, 14 participants in the depression group, and 23 participants in the healthy control group. All of the participants first completed the measures of demographic data, CFS-related symptoms, daily life functioning, and depressive symptoms. The participants were then asked to perform a stressful cognitive task. The participants’ psychophysiological responses including the HR, BVP and SC were measured during the task. These indexes were used to assess the reactivity and recovery rates of the automatic nervous system. Results: The stress reactivity of the CFS and depression groups was not different from that of the healthy control group. However, the stress recovery rate of the CFS group was worse than that of the healthy control group. Conclusion: The results from this study suggest that the CFS is a syndrome which can be independent from the depressive syndrome, although the depressive syndrome may include fatigue syndrome.

Keywords: chronic fatigue syndrome, depression, stress response, misdiagnosis

Procedia PDF Downloads 457