Search results for: random deviation

Authors: Shoukat Ali, Amjad Hussain, Latif-ur-Rehman, Sehrish Inam

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Radiotherapy plays an important role in the management of cancer patients. Approximately 50% of the cancer patients receive radiotherapy at one point or another during the course of treatment. The entire radiotherapy treatment of curative intent is divided into different phases, depending on the histology of the tumor. The established protocols are useful in deciding the total dose, fraction size, and numbers of phases. The objective of this study was to evaluate the dosimetric differences between the conventional treatment protocols and the three-dimensional conformal simultaneously integrated boost (SIB) plans for three different tumors sites (i.e. bladder, breast, and brain). A total of 30 patients with brain, breast and bladder cancers were selected in this retrospective study. All the patients were CT simulated initially. The primary physician contoured PTV1 and PTV2 in the axial slices. The conventional doses prescribed for brain and breast is 60Gy/30 fractions, and 64.8Gy/36 fractions for bladder treatment. For the SIB plans biological effective doses (BED) were calculated for 25 fractions. The two conventional (Phase I and Phase II) and a single SIB plan for each patient were generated on Eclipse™ treatment planning system. Treatment plans were compared and analyzed for coverage index, conformity index, homogeneity index, dose gradient and organs at risk doses.In both plans 95% of PTV volume received a minimum of 95% of the prescribe dose. Dose deviation in the optic chiasm was found to be less than 0.5%. There is no significant difference in lung V20 and heart V30 in the breast plans. In the rectum plans V75%, V50% and V25% were found to be less than 1.2% different. Deviation in the tumor coverage, conformity and homogeneity indices were found to be less than 1%. SIB plans with three dimensional conformal radiotherapy technique reduce the overall treatment time without compromising the target coverage and without increasing dose to the organs at risk. The higher dose per fraction may increase the late effects to some extent. Further studies are required to evaluate the late effects with the intention of standardizing the SIB technique for practical implementation.

Keywords: coverage index, conformity index, dose gradient, homogeneity index, simultaneously integrated boost

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Authors: Xin Chen

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It has been widely observed that marine food webs have significantly larger predator–prey body-size ratios compared with their terrestrial counterparts. A number of hypotheses have been proposed to account for such difference on the basis of primary productivity, trophic structure, biophysics, bioenergetics, habitat features, energy efficiency, etc. In this study, an alternative explanation is suggested based on the difference in the spatial dimensions of foraging arenas: terrestrial animals primarily forage in two dimensional arenas, while marine animals mostly forage in three dimensional arenas. Using 2-dimensional and 3-dimensional random walk simulations, it is shown that marine predators with 3-dimensional foraging would normally have a greater foraging efficiency than terrestrial predators with 2-dimensional foraging. Marine prey with 3-dimensional dispersion usually has greater swarms or aggregations than terrestrial prey with 2-dimensional dispersion, which again favours a greater predator foraging efficiency in marine animals. As an analytical tool, a Lotka-Volterra based adaptive dynamical model is developed with the predator-prey ratio embedded as an adaptive variable. The model predicts that high predator foraging efficiency and high prey conversion rate will dynamically lead to the evolution of a greater predator-prey ratio. Therefore, marine food webs with 3-dimensional foraging space, which generally have higher predator foraging efficiency, will evolve a greater predator-prey ratio than terrestrial food webs.

Keywords: predator-prey, body size, lotka-volterra, random walk, foraging efficiency

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Authors: Abdul Qadir Jangda, Khadija Mariam, Usman Ahmed, Sharib Ahmed

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The Gafchromic EBT3 film has the characteristic of high spatial resolution, weak energy dependence and near tissue equivalence which makes them viable to be used for in-vivo dosimetry in External Beam and Brachytherapy applications. The aim of this study is to assess the smallest film dimension that may be feasible for the use in in-vivo dosimetry. To evaluate the viability, the film sizes from 3 x 3 mm to 20 x 20 mm were calibrated with 6 MV Photon and 6 MeV electron beams. The Gafchromic EBT3 (Lot no. A05151201, Make: ISP) film was cut into five different sizes in order to establish the relationship between absorbed dose vs. film dimensions. The film dimension were 3 x 3, 5 x 5, 10 x 10, 15 x 15, and 20 x 20 mm. The films were irradiated on Varian Clinac® 2100C linear accelerator for dose range from 0 to 1000 cGy using PTW solid water phantom. The irradiation was performed as per clinical absolute dose rate calibratin setup, i.e. 100 cm SAD, 5.0 cm depth and field size of 10x10 cm2 and 100 cm SSD, 1.4 cm depth and 15x15 cm2 applicator for photon and electron respectively. The irradiated films were scanned with the landscape orientation and a post development time of 48 hours (minimum). Film scanning accomplished using Epson Expression 10000 XL Flatbed Scanner and quantitative analysis carried out with ImageJ freeware software. Results show that the dose variation with different film dimension ranging from 3 x 3 mm to 20 x 20 mm is very minimal with a maximum standard deviation of 0.0058 in Optical Density for a dose level of 3000 cGy and the the standard deviation increases with the increase in dose level. So the precaution must be taken while using the small dimension films for higher doses. Analysis shows that there is insignificant variation in the absorbed dose with a change in film dimension of EBT3 film. Study concludes that the film dimension upto 3 x 3 mm can safely be used up to a dose level of 3000 cGy without the need of recalibration for particular dimension in use for dosimetric application. However, for higher dose levels, one may need to calibrate the films for a particular dimension in use for higher accuracy. It was also noticed that the crystalline structure of the film got damage at the edges while cutting the film, which can contribute to the wrong dose if the region of interest includes the damage area of the film

Keywords: external beam radiotherapy, film calibration, film dosimetery, in-vivo dosimetery

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Authors: Novita Linda Akbar, Elmeida Effendy, Mustafa M. Amin

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Background: The most common of psychotic disorders is schizophrenia. Vitamin D is made from sunlight, and in the skin from UVB radiation from sunlight. If people with Vitamin D deficiency is common severe mental illness such as schizophrenia.Schizophrenia is a chronic mental illness characterised by positive symptoms and negatives symptoms, such as hallucinations and delusions, flat affect and lack of motivation we can found. In patients with Schizophrenia maybe have several environmental risk factors for schizophrenia, such as season of birth, latitude, and climate has been linked to vitamin D deficiency. There is also relationship between the risk of schizophrenia and latitude, and with an increased incidence rate of schizophrenia seen at a higher latitude. Methods: This study was an analytical study, conducted in BLUD RS Jiwa Propinsi Sumatera Utara and RSUD Deli Serdang, the period in May 2016 and ended in June 2016 with a sample of the study 60 sample (20 patients live in the Highland and Lowland, 20 healthy controls). Inclusion criteria were schizophrenic patients both men and women, aged between 18 to 60 years old, acute phase no agitation or abstinence antipsychotic drugs for two weeks, live in the Highland and Lowland, and willing to participate this study. Exclusion criteria were history of other psychotic disorders, comorbidities with other common medical condition, a history of substance abuse. Sample inspection for serum vitamin D using ELFA method. Statistical analysis using numeric comparative T-independent test. Results: The results showed that average levels of vitamin D for a group of subjects living in areas of high land was 227.6 ng / mL with a standard deviation of 86.78 ng / mL, the lowest levels of vitamin D is 138 ng / mL and the highest 482 ng / mL. In the group of subjects who settled in the low lands seem mean vitamin D levels higher than the mountainous area with an average 237.8 ng / mL with a standard deviation of 100.16 ng / mL. Vitamin D levels are lowest and the highest 138-585 ng / mL. Conclusion and Suggestion: The results of the analysis using the Mann Whitney test showed that there were no significant differences between the mean for the levels of vitamin D based on residence subject with a value of p = 0.652.

Keywords: latitude, schizophrenia, Vitamin D, Sumatera Utara

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Authors: Roghieh A. Biroon, Zoleikha Abdollahi

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The recent growth of renewables, e.g., solar panels, batteries, and electric vehicles (EVs) in residential and small commercial sectors, has potential impacts on the stability and operation of power grids. Considering approximately 50 percent share of the residential and the commercial sectors in the electricity demand market, the significance of these impacts, and the necessity of addressing them are more highlighted. Utilities and power system operators should manage the renewable electricity sources integration with power systems in such a way to extract the most possible advantages for the power systems. The most common effect of high penetration level of the renewables is the reverse power flow in the distribution feeders when the customers generate more power than their needs. The reverse power flow causes voltage rise and thermal issues in the power grids. To overcome the voltage rise issues in the distribution system, several techniques have been proposed including reducing transformers short circuit resistance and feeder impedance, installing autotransformers/voltage regulators along the line, absorbing the reactive power by distributed generators (DGs), and limiting the PV and battery sizes. In this study, we consider a medium-scale battery energy storage to manage the power energy and address the aforementioned issues on voltage deviation and power loss increase. We propose an optimization algorithm to find the optimum size and location for the battery. The optimization for the battery location and size is so that the battery maintains the feeder voltage deviation and power loss at a certain desired level. Moreover, the proposed optimization algorithm controls the charging/discharging profile of the battery to absorb the negative power flow from residential and commercial customers in the feeder during the peak time and sell the power back to the system during the off-peak time. The proposed battery regulates the voltage problem in the distribution system while it also can play frequency regulation role in islanded microgrids. This battery can be regulated and controlled by the utilities or a third-party ancillary service provider for the utilities to reduce the power system loss and regulate the distribution feeder voltage and frequency in standard level.

Keywords: ancillary services, battery, distribution system and optimization

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Authors: S. Ziaran, M. Musil, M. Cekan, O. Chlebo

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The paper analyzes the response of buildings and industrially structures on seismic waves (low frequency mechanical vibration) generated by blasting operations. The principles of seismic analysis can be applied for different kinds of excitation such as: earthquakes, wind, explosions, random excitation from local transportation, periodic excitation from large rotating and/or machines with reciprocating motion, metal forming processes such as forging, shearing and stamping, chemical reactions, construction and earth moving work, and other strong deterministic and random energy sources caused by human activities. The article deals with the response of seismic, low frequency, mechanical vibrations generated by nearby blasting operations on a residential home. The goal was to determine the fundamental natural frequencies of the measured structure; therefore it is important to determine the resonant frequencies to design a suitable modal damping. The article also analyzes the package of seismic waves generated by blasting (Primary waves – P-waves and Secondary waves S-waves) and investigated the transfer regions. For the detection of seismic waves resulting from an explosion, the Fast Fourier Transform (FFT) and modal analysis, in the frequency domain, is used and the signal was acquired and analyzed also in the time domain. In the conclusions the measured results of seismic waves caused by blasting in a nearby quarry and its effect on a nearby structure (house) is analyzed. The response on the house, including the fundamental natural frequency and possible fatigue damage is also assessed.

Keywords: building structure, seismic waves, spectral analysis, structural response

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Authors: Manal Suleiman, George Abu-Aqil, Uraib Sharaha, Klaris Riesenberg, Itshak Lapidot, Ahmad Salman, Mahmoud Huleihel

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Klebsiella pneumoniae is one of the most aggressive multidrug-resistant bacteria associated with human infections resulting in high mortality and morbidity. Thus, for an effective treatment, it is important to diagnose both the species of infecting bacteria and their susceptibility to antibiotics. Current used methods for diagnosing the bacterial susceptibility to antibiotics are time-consuming (about 24h following the first culture). Thus, there is a clear need for rapid methods to determine the bacterial susceptibility to antibiotics. Infrared spectroscopy is a well-known method that is known as sensitive and simple which is able to detect minor biomolecular changes in biological samples associated with developing abnormalities. The main goal of this study is to evaluate the potential of infrared spectroscopy in tandem with Random Forest and XGBoost machine learning algorithms to diagnose the susceptibility of Klebsiella pneumoniae to antibiotics within approximately 20 minutes following the first culture. In this study, 1190 Klebsiella pneumoniae isolates were obtained from different patients with urinary tract infections. The isolates were measured by the infrared spectrometer, and the spectra were analyzed by machine learning algorithms Random Forest and XGBoost to determine their susceptibility regarding nine specific antibiotics. Our results confirm that it was possible to classify the isolates into sensitive and resistant to specific antibiotics with a success rate range of 80%-85% for the different tested antibiotics. These results prove the promising potential of infrared spectroscopy as a powerful diagnostic method for determining the Klebsiella pneumoniae susceptibility to antibiotics.

Keywords: urinary tract infection (UTI), Klebsiella pneumoniae, bacterial susceptibility, infrared spectroscopy, machine learning

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Authors: Yasuyo Makido, Vivek Shandas, David J. Sailor, M. Salim Ferwati

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Mitigating extreme urban heat is challenging in a desert climate such as Doha, Qatar, since outdoor daytime temperature area often too high for the human body to tolerate. Recent studies demonstrate that cities in arid and semiarid areas can exhibit ‘urban cool islands’ - urban areas that are cooler than the surrounding desert. However, the variation of temperatures as a result of the time of day and factors leading to temperature change remain at the question. To address these questions, we examined the spatial and temporal variation of air temperature in Doha, Qatar by conducting multiple vehicle-base local temperature observations. We also employed three statistical approaches to model surface temperatures using relevant predictors: (1) Ordinary Least Squares, (2) Regression Tree Analysis and (3) Random Forest for three time periods. Although the most important determinant factors varied by day and time, distance to the coast was the significant determinant at midday. A 70%/30% holdout method was used to create a testing dataset to validate the results through Pearson’s correlation coefficient. The Pearson’s analysis suggests that the Random Forest model more accurately predicts the surface temperatures than the other methods. We conclude with recommendations about the types of development patterns that show the greatest potential for reducing extreme heat in air climates.

Keywords: desert cities, tree-structure regression model, urban cool Island, vehicle temperature traverse

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Authors: Carla Idely Palencia-Aguilar

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Artificial wetlands play an important role at Guasca Municipality in Colombia, not only because they are used for the agroindustry, but also because more than 45 species were found, some of which are endemic and migratory birds. Remote sensing was used to determine the changes in the area occupied by water of artificial wetlands by means of Aster and Modis images for different time periods. Evapotranspiration was also determined by three methods: Surface Energy Balance System-Su (SEBS) algorithm, Surface Energy Balance- Bastiaanssen (SEBAL) algorithm, and Potential Evapotranspiration- FAO. Empirical equations were also developed to determine the relationship between Normalized Difference Vegetation Index (NDVI) versus net radiation, ambient temperature and rain with an obtained R2 of 0.83. Groundwater level fluctuations on a daily basis were studied as well. Data from a piezometer placed next to the wetland were fitted with rain changes (with two weather stations located at the proximities of the wetlands) by means of multiple regression and time series analysis, the R2 from the calculated and measured values resulted was higher than 0.98. Information from nearby weather stations provided information for ordinary kriging as well as the results for the Digital Elevation Model (DEM) developed by using PCI software. Standard models (exponential, spherical, circular, gaussian, linear) to describe spatial variation were tested. Ordinary Cokriging between height and rain variables were also tested, to determine if the accuracy of the interpolation would increase. The results showed no significant differences giving the fact that the mean result of the spherical function for the rain samples after ordinary kriging was 58.06 and a standard deviation of 18.06. The cokriging using for the variable rain, a spherical function; for height variable, the power function and for the cross variable (rain and height), the spherical function had a mean of 57.58 and a standard deviation of 18.36. Threatens of eutrophication were also studied, given the unconsciousness of neighbours and government deficiency. Water quality was determined over the years; different parameters were studied to determine the chemical characteristics of water. In addition, 600 pesticides were studied by gas and liquid chromatography. Results showed that coliforms, nitrogen, phosphorous and prochloraz were the most significant contaminants.

Keywords: DEM, evapotranspiration, geostatistics, NDVI

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Authors: Hu Ding, Kai Liu, Guoan Tang

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The Chinese Loess Plateau suffers from serious gully erosion induced by natural and human causes. Gully features detection including gully-affected area and its two dimension parameters (length, width, area et al.), is a significant task not only for researchers but also for policy-makers. This study aims at gully-affected area detection in three catchments of Chinese Loess Plateau, which were selected in Changwu, Ansai, and Suide by using unmanned aerial vehicle (UAV). The methodology includes a sequence of UAV data generation, image segmentation, feature calculation and selection, and random forest classification. Two experiments were conducted to investigate the influences of segmentation strategy and feature selection. Results showed that vertical and horizontal root-mean-square errors were below 0.5 and 0.2 m, respectively, which were ideal for the Loess Plateau region. The segmentation strategy adopted in this paper, which considers the topographic information, and optimal parameter combination can improve the segmentation results. Besides, the overall extraction accuracy in Changwu, Ansai, and Suide achieved was 84.62%, 86.46%, and 93.06%, respectively, which indicated that the proposed method for detecting gully-affected area is more objective and effective than traditional methods. This study demonstrated that UAV can bridge the gap between field measurement and satellite-based remote sensing, obtaining a balance in resolution and efficiency for catchment-scale gully erosion research.

Keywords: unmanned aerial vehicle (UAV), object-analysis image analysis, gully erosion, gully-affected area, Loess Plateau, random forest

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Authors: Faiza Babur Khan, Sohail Asghar

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With an emergence of distributed environment, cloud computing is proving to be the most stimulating computing paradigm shift in computer technology, resulting in spectacular expansion in IT industry. Many companies have augmented their technical infrastructure by adopting cloud resource sharing architecture. Cloud computing has opened doors to unlimited opportunities from application to platform availability, expandable storage and provision of computing environment. However, from a security viewpoint, an added risk level is introduced from clouds, weakening the protection mechanisms, and hardening the availability of privacy, data security and on demand service. Issues of trust, confidentiality, and integrity are elevated due to multitenant resource sharing architecture of cloud. Trust or reliability of cloud refers to its capability of providing the needed services precisely and unfailingly. Confidentiality is the ability of the architecture to ensure authorization of the relevant party to access its private data. It also guarantees integrity to protect the data from being fabricated by an unauthorized user. So in order to assure provision of secured cloud, a roadmap or model is obligatory to analyze a security problem, design mitigation strategies, and evaluate solutions. The aim of the paper is twofold; first to enlighten the factors which make cloud security critical along with alleviation strategies and secondly to propose an intrusion detection model that identifies the attackers in a preventive way using machine learning Random Forest classifier with an accuracy of 99.8%. This model uses less number of features. A comparison with other classifiers is also presented.

Keywords: cloud security, threats, machine learning, random forest, classification

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Authors: Alanoud Moraya Aldalan, Abdulaziz Almaleh

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A crucial component of maintaining a customer-oriented business as in the telecom industry is understanding the reasons and factors that lead to customer churn. Competition between telecom companies has greatly increased in recent years. It has become more important to understand customers’ needs in this strong market of telecom industries, especially for those who are looking to turn over their service providers. So, predictive churn is now a mandatory requirement for retaining those customers. Machine learning can be utilized to accomplish this. Churn Prediction has become a very important topic in terms of machine learning classification in the telecommunications industry. Understanding the factors of customer churn and how they behave is very important to building an effective churn prediction model. This paper aims to predict churn and identify factors of customers’ churn based on their past service usage history. Aiming at this objective, the study makes use of feature selection, normalization, and feature engineering. Then, this study compared the performance of four different machine learning algorithms on the Orange dataset: Logistic Regression, Random Forest, Decision Tree, and Gradient Boosting. Evaluation of the performance was conducted by using the F1 score and ROC-AUC. Comparing the results of this study with existing models has proven to produce better results. The results showed the Gradients Boosting with feature selection technique outperformed in this study by achieving a 99% F1-score and 99% AUC, and all other experiments achieved good results as well.

Keywords: machine learning, gradient boosting, logistic regression, churn, random forest, decision tree, ROC, AUC, F1-score

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Authors: Mariia Timofeeva, Andrew Ooi, Eric K. W. Poon, Peter Barlis

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Atherosclerotic plaque build-up, commonly known as stenosis, limits blood flow and hence oxygen and nutrient supplies to the heart muscle. Thus, assessment of its severity is of great interest to health professionals. Numerical simulation of the fractional flow reserve (FFR) has proved to be well correlated with invasively measured FFR used for physiological assessment of the severity of coronary stenosis in arteries. Atherosclerosis may impact the diseased artery in several locations causing serial stenoses, which is a complicated subset of coronary artery disease that requires careful treatment planning. However, hemodynamic of the serial sequential stenoses in coronary arteries has not been extensively studied. The hemodynamics of the serial stenoses is complex because the stenoses in the series interact and affect the flow through each other. To address this, serial stenoses in a 3.4 mm left anterior descending (LAD) artery are examined in this study. Two diameter stenoses (DS) are considered, 30 and 50 percent of the reference diameter. Serial stenoses configurations are divided into three groups based on the order of the stenoses in the series, spacing between them, and deviation of the stenoses’ symmetry (eccentricity). A patient-specific pulsatile waveform is used in the simulations. Blood flow within the stenotic artery is assumed to be laminar, Newtonian, and incompressible. Results for the FFR are reported. Based on the simulation results, it can be deduced that the larger drop in pressure (smaller value of the FFR) is expected when the percentage of the second stenosis in the series is bigger. Varying the distance between the stenoses affects the location of the maximum drop in the pressure, while the minimal FFR in the artery remains unchanged. Eccentric serial stenoses are characterized by a noticeably larger decrease in pressure through the stenoses and by the development of the chaotic flow downstream of the stenoses. The largest drop in the pressure (about 4% difference compared to the axisymmetric case) is obtained for the serial stenoses, where both the stenoses are highly eccentric with the centerlines deflected to the different sides of the LAD. In conclusion, varying configuration of the sequential serial stenoses results in a different distribution of FFR through the LAD. Results presented in this study provide insight into the clinical assessment of the severity of the coronary serial stenoses, which is proved to depend on the relative position of the stenoses and the deviation of the stenoses’ symmetry.

Keywords: computational fluid dynamics, coronary artery, fractional flow reserve, serial stenoses

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Authors: Ounis Hadj Mohamed, Ounis Abdelhafid

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In order to illustrate the effect of damping on the response of a base-isolated building, a parametric study is led, taking into account the progressive variation of the damping ratio (10% to 30%) under different types of seismic excitations (near and far field). A time history analysis is used to determine the response of the structure in terms of relative displacement and understory drift at various levels of the building. Thus, the results show that the efficiency of the isolator increases with the assumed damping ratio, provided that this latter is less or equal to 20%. Beyond this value, the isolator becomes less convenient. Furthermore, a strong deviation of energy capacity by the LRB (Lead Rubber Bearing) system is recorded.

Keywords: damping, base isolation, LRB, seismic excitation, hysteresis

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Authors: Xiangtuo Chen, Paul-Henry Cournéde

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Crop yield prediction is a paramount issue in agriculture. The main idea of this paper is to find out efficient way to predict the yield of corn based meteorological records. The prediction models used in this paper can be classified into model-driven approaches and data-driven approaches, according to the different modeling methodologies. The model-driven approaches are based on crop mechanistic modeling. They describe crop growth in interaction with their environment as dynamical systems. But the calibration process of the dynamic system comes up with much difficulty, because it turns out to be a multidimensional non-convex optimization problem. An original contribution of this paper is to propose a statistical methodology, Multi-Scenarios Parameters Estimation (MSPE), for the parametrization of potentially complex mechanistic models from a new type of datasets (climatic data, final yield in many situations). It is tested with CORNFLO, a crop model for maize growth. On the other hand, the data-driven approach for yield prediction is free of the complex biophysical process. But it has some strict requirements about the dataset. A second contribution of the paper is the comparison of these model-driven methods with classical data-driven methods. For this purpose, we consider two classes of regression methods, methods derived from linear regression (Ridge and Lasso Regression, Principal Components Regression or Partial Least Squares Regression) and machine learning methods (Random Forest, k-Nearest Neighbor, Artificial Neural Network and SVM regression). The dataset consists of 720 records of corn yield at county scale provided by the United States Department of Agriculture (USDA) and the associated climatic data. A 5-folds cross-validation process and two accuracy metrics: root mean square error of prediction(RMSEP), mean absolute error of prediction(MAEP) were used to evaluate the crop prediction capacity. The results show that among the data-driven approaches, Random Forest is the most robust and generally achieves the best prediction error (MAEP 4.27%). It also outperforms our model-driven approach (MAEP 6.11%). However, the method to calibrate the mechanistic model from dataset easy to access offers several side-perspectives. The mechanistic model can potentially help to underline the stresses suffered by the crop or to identify the biological parameters of interest for breeding purposes. For this reason, an interesting perspective is to combine these two types of approaches.

Keywords: crop yield prediction, crop model, sensitivity analysis, paramater estimation, particle swarm optimization, random forest

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Authors: Sudhir Kumar Singh, Debashish Chakravarty

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Slope stability analysis is an important aspect in the field of geotechnical engineering. It is also important from safety, and economic point of view as any slope failure leads to loss of valuable lives and damage to property worth millions. This paper aims at mitigating the risk of slope failure by studying the effect of different joint sets on the stability of mine pit slopes under the influence of various external factors, namely degree of saturation, rainfall intensity, and seismic coefficients. Supervised machine learning approach has been utilized for making accurate and reliable predictions regarding the stability of slopes based on the value of Factor of Safety. Numerous cases have been studied for analyzing the stability of slopes using the popular Finite Element Method, and the data thus obtained has been used as training data for the supervised machine learning models. The input data has been trained on different supervised machine learning models, namely Random Forest, Decision Tree, Support vector Machine, and XGBoost. Distinct test data that is not present in training data has been used for measuring the performance and accuracy of different models. Although all models have performed well on the test dataset but Random Forest stands out from others due to its high accuracy of greater than 95%, thus helping us by providing a valuable tool at our disposition which is neither computationally expensive nor time consuming and in good accordance with the numerical analysis result.

Keywords: finite element method, geotechnical engineering, machine learning, slope stability

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Authors: Mohsen Bahrami, Banafsheh Nikmehr, Yueqiang Song, Anuradha Koduru, Ayse K. Vuruskan, Hongkun Lu, Tamer M. Yalcinkaya

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In recent years, we have witnessed an explosion of studies aimed at using a combination of artificial intelligence (AI) and time-lapse imaging data on embryos to improve IVF outcomes. However, despite promising results, no study has used a matched cohort of transferred embryos which only differ in pregnancy outcome, i.e., embryos from a single clinic which are similar in parameters, such as: morphokinetic condition, patient age, and overall clinic and lab performance. Here, we used time-lapse data on embryos with known pregnancy outcomes to see if the rich spatiotemporal information embedded in this data would allow the prediction of the pregnancy outcome regardless of such critical parameters. Methodology—We did a retrospective analysis of time-lapse data from our IVF clinic utilizing Embryoscope 100% of the time for embryo culture to blastocyst stage with known clinical outcomes, including live birth vs nonpregnant (embryos with spontaneous abortion outcomes were excluded). We used time-lapse data from 200 elective single transfer embryos randomly selected from January 2019 to June 2021. Our sample included 100 embryos in each group with no significant difference in patient age (P=0.9550) and morphokinetic scores (P=0.4032). Data from all patients were combined to make a 4th order tensor, and feature extraction were subsequently carried out by a tensor decomposition methodology. The features were then used in a machine learning classifier to classify the two groups. Major Findings—The performance of the model was evaluated using 100 random subsampling cross validation (train (80%) - test (20%)). The prediction accuracy, averaged across 100 permutations, exceeded 80%. We also did a random grouping analysis, in which labels (live birth, nonpregnant) were randomly assigned to embryos, which yielded 50% accuracy. Conclusion—The high accuracy in the main analysis and the low accuracy in random grouping analysis suggest a consistent spatiotemporal pattern which is associated with pregnancy outcomes, regardless of patient age and embryo morphokinetic condition, and beyond already known parameters, such as: early cleavage or early blastulation. Despite small samples size, this ongoing analysis is the first to show the potential of AI methods in capturing the complex morphokinetic changes embedded in embryo time-lapse data, which contribute to successful pregnancy outcomes, regardless of already known parameters. The results on a larger sample size with complementary analysis on prediction of other key outcomes, such as: euploidy and aneuploidy of embryos will be presented at the meeting.

Keywords: IVF, embryo, machine learning, time-lapse imaging data

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Authors: Emine Şahin, Murat Soner Balcıoğlu

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The aim of this study was to determine the growth hormone (bGH) gene polymorphism in the Holstein cattle growing around Antalya in Turkey. In order to determine the bGH-AluI polymorphism, polymerase chain reaction - restriction fragment length polymorphism (PCR-RFLP) method was performed. A 891 bp fragment of bGH was amplified and two types of alleles C and D for bGH were observed. In this study, the frequencies of C and D alleles were 0.8438 and 0.1562, respectively. The genotype frequencies for CC, CD and DD were 0.787, 0.191 and 0.022, respectively. According to the results of the chi-square test, a significant deviation from the Hardy-Weinberg equilibrium was not determined for the bGH locus in the population.

Keywords: Growth Hormone Gene, Holstein , Polymorphism, RFLP

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Authors: Hossam N. Alhawatmeh, Areen I. Albustanji

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Hemodialysis negatively affects physical and psychological health. Pain, poor sleep quality, and low self-esteem are highly prevalent among patients with end-stage renal disease (ESRD) who receive hemodialysis, significantly increasing mortality and morbidity of those patients. Mind-body interventions (MBI), such as mindfulness meditation, have been recently gaining popularity that improved pain, sleep quality, and self-esteem in different populations. However, to our best knowledge, its effects on these health problems in patients receiving hemodialysis have not been studied in Jordan. Thus, the purpose of the study was to examine the effect of mindfulness meditation on pain, sleep quality, and self-esteem in patients with ESR receiving hemodialysis in Jordan. An experimental repeated-measures, randomized, parallel control design was conducted on (n =60) end-stage renal disease patients undergoing hemodialysis between March and June 2023 in the dialysis center at a public hospital in Jordan. Participants were randomly assigned to the experimental (n =30) and control groups (n =30) using a simple random assignment method. The experimental group practiced mindfulness meditation for 30 minutes three times per week for five weeks during their hemodialysis treatments. The control group's patients continued to receive hemodialysis treatment as usual for five weeks during hemodialysis sessions. The study variables for both groups were measured at baseline (Time 0), two weeks after intervention (Time 1), and at the end of intervention (Time 3). The numerical rating scale (NRS), the Rosenberg Self-Esteem Scale (RSES-M), and the Pittsburgh Sleep Quality Index (PSQI) were used to measure pain, self-esteem, and sleep quality, respectively. SPSS version 25 was used to analyze the study data. The sample was described by frequency, mean, and standard deviation as an appropriate. The repeated measures analysis of variance (ANOVA) tests were run to test the study hypotheses. The results of repeated measures ANOVA (within-subject) revealed that mindfulness meditation significantly decrease pain by the end of the intervention in the experimental group. Additionally, mindfulness meditation improved sleep quality and self-esteem in the experimental group, and these improvements occurred significantly after two weeks of the intervention and at the end of the intervention. The results of repeated measures ANOVA (within and between-subject) revealed that the experimental group, compared to the control group, experienced lower levels of pain and higher levels of sleep quality and self-esteem over time. In conclusion, the results provided substantial evidence supporting the positive impacts of mindfulness meditation on pain, sleep quality, and self-esteem in patients with ESRD undergoing hemodialysis. These results highlight the potential of mindfulness meditation as an adjunctive therapy in the comprehensive care of this patient population. Incorporating mindfulness meditation into the treatment plan for patients receiving hemodialysis may contribute to improved well-being and overall quality of life.

Keywords: hemodialysis, pain, sleep quality, self-esteem, mindfulness

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Authors: Mohammed Asiri, Saleh Alsuwayt, Mohammed Bin Mugren, Abdulmalik Almufarrih, Tariq Alotaibi, Saad Almodameg

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Background: End-stage renal disease is a major public health concern with high incidence and mortality rate. Most of ESRD patients are on hemodialysis therapy which is a long-term treatment that disturbs patients’ lifestyle. As a result, he will be susceptible to develop psychiatric disorders like anxiety that may direct him to non-compliance on physician instructions and hemodialysis therapy. Although there are studies conducted on psychiatric issues in hemodialysis patients, but few studies focused on the effect of anxiety disorder and the patient’s compliance. Hence, we are interested in determining the prevalence of anxiety disorder among hemodialysis patients in Saudi Arabia, as well as in defining the correlation between anxiety disorder and compliance on physician instructions and hemodialysis therapy. We hypothesize that our study will show a higher prevalence of anxiety in hemodialysis patients than in general population. Also, we expect the anxiety to have a negative impact on their compliance. Methodology: We used a cross-sectional study design carried out at dialysis unit of four major hospitals in Riyadh, KSA. We interviewed 235 End Stage Renal Disease male and female patients who are on hemodialysis. We divided the patients into two categories according to their compliance. we used modified general questionnaire to get their demographic data, then we used a psychometric response scale called visual analog scale (VAS) to assess patient’s compliance to hemodialysis and physician’s instructions. Also, we used the Arabic validated version of the hospital anxiety and depression scale (HAD scale) used mainly for anxiety assessment. Results: The overall response rate was 54%. Respondents included 147 (62.6%) males and 88 (37.4%) females. The prevalence of anxiety among hemodialysis patients is 13.3%. According to visual analog scale, we found that 189 compliant patients and 45 non-compliant patients. For HAD scale, the mean ± standard deviation of the total score for females was (4.44 ± 4.7) and it’s higher than males which was 2.65 ± 3.08 (P-value= 0.002). The mean ± standard deviation of HAD score in the non-compliant group was (5.88  4.88) and it was higher than the compliant group (2.7  3.32) (P-value= 0.004). Among non-complaint group, 33.3% of anxious patients were males and 66.6% were females. There was a negative correlation between HAD score of anxiety and visual analog scale (R= - 0.285). Conclusion: We conclude that there is a high prevalence of anxiety among patients with End Stage Renal Disease that was higher in females with association of non-compliance to physician’s instructions and hemodialysis therapy.

Keywords: anxiety, end-stage renal disease, renal failure, anxiety disorder

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Authors: Esther O. Adebitan, Florence Oyelade

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The Millennium Development Goals (MDGs) was initiated by the UN member nations’ aspiration for the betterment of human life. It is expressed in a set of numerical ‎and time-bound targets. In more recent time, the aspiration is shifting away from just the achievement to the sustainability of achieved MDGs beyond the 2015 target. The main objective of this study was assessing how much the hotel industry within the Nigerian Federal Capital Territory (FCT) as a member of the global community is involved in the achievement of sustainable MDGs within the FCT. The study had two population groups consisting of 160 hotels and the communities where these are located. Stratified random sampling technique was adopted in selecting 60 hotels based on large, medium ‎and small hotels categorisation, while simple random sampling technique was used to elicit information from 30 residents of three of the hotels host communities. The study was guided by tree research questions and two hypotheses aimed to ascertain if hotels see the need to be involved in, and have policies in pursuit of achieving sustained MDGs, and to determine public opinion regarding hotels contribution towards the achievement of the MDGs in their communities. A 22 item questionnaire was designed ‎and administered to hotel managers while 11 item questionnaire was designed ‎and administered to hotels’ host communities. Frequency distribution and percentage as well as Chi-square were used to analyse data. Results showed no significant involvement of the hotel industry in achieving sustained MDGs in the FCT and that there was disconnect between the hotels and their immediate communities. The study recommended that hotels should, as part of their Corporate Social Responsibility pick at least one of the goals to work on in order to be involved in the attainment of enduring Millennium Development Goals.

Keywords: MDGs, hotels, FCT, host communities, corporate social responsibility

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Authors: Baleeqs, O. Adegoke, Adeola, O. Aburime

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Juvenile delinquency is fast becoming one of the largest problems facing many societies due to many different factors ranging from parental factors to bullying at schools all which had led to different theoretical notions by different scholars. Delinquency is an illegal or immoral behaviour, especially by the young person who behaves in a way that is illegal or that society does not approve of. The purpose of the study was to investigate causes and effects of delinquent behaviours among adolescent in juvenile home in Osun State. A descriptive survey research type was employed. The random sampling technique was used to select 100 adolescents in Juvenile home in Osun State. Questionnaires were developed and given to them. The data collected from this study were analyzed using frequency counts and percentage for the demographic data in section A, while the two research hypotheses postulated for this study were tested using t-test statistics at the significance level of 0.05. Findings revealed that the greatest school effects of delinquent behaviours among adolescent in juvenile home in Osun by respondents were their aggressive behaviours. Findings revealed that there was a significant difference in the causes and effects of delinquent behaviours among adolescent in juvenile home in Osun State. It was also revealed that there was no significant difference in the causes and effects of delinquent behaviours among secondary school students in Osun based on gender. These recommendations were made in order to address the findings of this study: More number of teachers should be appointed in the observation home so that it will be possible to provide teaching to the different age group of delinquents. Developing the infrastructure facilities of short stay homes and observation home is a top priority. Proper counseling session’s interval is highly essential for these juveniles.

Keywords: behaviour, delinquency, juvenile, random sampling, statistical techniques, survey

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Authors: Sule Pallavi, Shah Priyank, Thavkar Amit, Mehta Suyog, Rohira Poonam

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Minoxidil is used topically to help hair growth in the treatment of male androgenetic alopecia. The objective of this study is to compare irritation potential of three conventional formulation of minoxidil 5% topical solution of in human patch test. The study was a single centre, double blind, non-randomized controlled study in 56 healthy adult Indian subjects. Occlusive patch test for 24 hours was performed with three formulation of minoxidil 5% topical solution. Products tested included aqueous based minoxidil 5% (AnasureTM 5%, Sun Pharma, India – Brand A), alcohol based minoxidil 5% (Brand B) and aqueous based minoxidil 5% (Brand C). Isotonic saline 0.9% and 1% w/w sodium lauryl sulphate were included as negative control and positive control respectively. Patches were applied and removed after 24hours. The skin reaction was assessed and clinically scored 24 hours after the removal of the patches under constant artificial daylight source using Draize scale (0-4 points scale for erythema/wrinkles/dryness and for oedema). A combined mean score up to 2.0/8.0 indicates a product is “non-irritant” and score between 2.0/8.0 and 4.0/8.0 indicates “mildly irritant” and score above 4.0/8.0 indicates “irritant”. Follow-up was scheduled after one week to confirm recovery for any reaction. The procedure of the patch test followed the principles outlined by Bureau of Indian standards (BIS) (IS 4011:2018; Methods of Test for safety evaluation of Cosmetics-3rd revision). Fifty six subjects with mean age 30.9 years (27 males and 29 females) participated in the study. The combined mean score (± standard deviation) were: 0.13 ± 0.33 (Brand A), 0.39 ± 0.49 (Brand B), 0.22 ± 0.41 (Brand C), 2.91 ± 0.79 (Positive control) and 0.02 ± 0.13 (Negative control). The mean score of Brand A (Sun Pharma product) was significantly lower than Brand B (p=0.001) and was comparable with Brand C (p=0.21). The combined mean erythema score (± standard deviation) were: 0.09 ± 0.29 (Brand A), 0.27 ± 0.5 (Brand B), 0.18 ± 0.39 (Brand C), 2.02 ± 0.49 (Positive control) and 0.0 ± 0.0 (Negative control). The mean erythema score of Brand A was significantly lower than Brand B (p=0.01) and was comparable with Brand C (p=0.16). Any reaction observed at 24hours after patch removal subsided in a week. All the three topical formulation of minoxidil 5% were non-irritant. Brand A of 5% minoxidil (Sun Pharma) was found to be least irritant than Brand B and Brand C based on the combined mean score and mean erythema score in the human patch test as per the BIS, IS 4011;2018.

Keywords: erythema, irritation, minoxidil, patch test

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Authors: Khanh To Duc, Monica Chiogna, Gianfranco Adimari

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With three diagnostic categories, assessment of the performance of diagnostic tests is achieved by the analysis of the receiver operating characteristic (ROC) surface, which generalizes the ROC curve for binary diagnostic outcomes. The volume under the ROC surface (VUS) is a summary index usually employed for measuring the overall diagnostic accuracy. When the true disease status can be exactly assessed by means of a gold standard (GS) test, unbiased nonparametric estimators of the ROC surface and VUS are easily obtained. In practice, unfortunately, disease status verification via the GS test could be unavailable for all study subjects, due to the expensiveness or invasiveness of the GS test. Thus, often only a subset of patients undergoes disease verification. Statistical evaluations of diagnostic accuracy based only on data from subjects with verified disease status are typically biased. This bias is known as verification bias. Here, we consider the problem of correcting for verification bias when continuous diagnostic tests for three-class disease status are considered. We assume that selection for disease verification does not depend on disease status, given test results and other observed covariates, i.e., we assume that the true disease status, when missing, is missing at random. Under this assumption, we discuss several solutions for ROC surface analysis based on imputation and re-weighting methods. In particular, verification bias-corrected estimators of the ROC surface and of VUS are proposed, namely, full imputation, mean score imputation, inverse probability weighting and semiparametric efficient estimators. Consistency and asymptotic normality of the proposed estimators are established, and their finite sample behavior is investigated by means of Monte Carlo simulation studies. Two illustrations using real datasets are also given.

Keywords: imputation, missing at random, inverse probability weighting, ROC surface analysis

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Authors: Davie G. Dave, Prisca H. Mugabe, Tonderai Mutibvu

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Globally, HWCs are on the rise. Such is the case with urban areas in Zimbabwe, yet little has been documented about it. This study was done to provide insights into the occurrence of human-wildlife conflicts in urban areas. The study was carried out in Harare, Bindura, Masvingo, Beitbridge, and Chiredzi to determine the cause, nature, extent, and frequency of occurrence of HWC, to determine the key wildlife species involved in conflicts and management practices done to combat wildlife conflicts in these areas. Several sampling techniques encompassing multi-stage sampling, stratified random, purposive, and simple random sampling were employed for placing residential areas into three strata according to population density, selecting residential areas, and selecting actual participants. Data were collected through a semi-structured questionnaire and key informant interviews. The results revealed that property destruction and crop damage were the most prevalent conflicts. Of the 15 animals that were cited, snakes, baboons, and monkeys were associated with the most conflicts. The occurrence of HWCs was mainly attributed to the increase in both animal and human populations. To curtail these HWCs, the local people mainly used non-lethal methods, whilst lethal methods were used by authorities for some of the reported cases. The majority of the conflicts were seasonal and less severe. There were growing concerns by respondents on the issues of wildlife conflicts, especially in those areas that had primates, such as Warren Park in Harare and Limpopo View in Beitbridge. There are HWCs hotspots in urban areas, and to ameliorate this, suggestions are that there is a need for a multi-action approach that includes general awareness campaigns on HWCs and land use planning that involves the creation of green spaces to ease wildlife management.

Keywords: human-wildlife conflicts, mitigation measures, residential areas, types of conflicts, urban areas

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Authors: Sogol Zarafshan

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The present study aimed to identify important factors affecting the effectiveness of quality control circles in a hospital, as well as rank them using a combination of fuzzy VIKOR and Grey Relational Analysis (GRA). The study population consisted of five academic members and five experts in the field of nursing working in a hospital, who were selected using a purposive sampling method. Also, a sample of 107 nurses was selected through a simple random sampling method using their employee codes and the random-number table. The required data were collected using a researcher-made questionnaire which consisted of 12 factors. The validity of this questionnaire was confirmed through giving the opinions of experts and academic members who participated in the present study, as well as performing confirmatory factor analysis. Its reliability also was verified (α=0.796). The collected data were analyzed using SPSS 22.0 and LISREL 8.8, as well as VIKOR–GRA and IPA methods. The results of ranking the factors affecting the effectiveness of quality control circles showed that the highest and lowest ranks were related to ‘Managers’ and supervisors’ support’ and ‘Group leadership’. Also, the highest hospital performance was for factors such as ‘Clear goals and objectives’ and ‘Group cohesiveness and homogeneity’, and the lowest for ‘Reward system’ and ‘Feedback system’, respectively. The results showed that although ‘Training the members’, ‘Using the right tools’ and ‘Reward system’ were factors that were of great importance, the organization’s performance for these factors was poor. Therefore, these factors should be paid more attention by the studied hospital managers and should be improved as soon as possible.

Keywords: Quality control circles, Fuzzy VIKOR, Grey Relational Analysis, Importance–Performance Analysis

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Authors: Swati Bhasin, Ali Ahmed, Valence Xavier, Ben Liu

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Aims: Diarrhea is a problem that is a frequent clinic referral to the gastroenterology and surgical team from the General practitioner. To establish a diagnosis, these patients undergo colonoscopy. The current practice at our district general hospital is to perform random left and right colonic biopsies. National guidelines issued by the British Society of Gastroenterology advise all patients presenting with chronic diarrhea should have an Ileoscopy as an indicator for colonoscopy completion. Our primary aim was to check if Terminal ileum (TI) biopsy is required to establish a diagnosis of inflammatory bowel disease (IBD). Methods: Data was collected retrospectively from November 2018 to November 2019. The target population were patients who underwent colonoscopies for diarrhea. Demographic data, endoscopic and histology findings of TI were assessed and analyzed. Results: 140 patients with a mean age of 57 years (19-84) underwent a colonoscopy (M: F; 1:2.3). 92 patients had random colonic biopsies taken and based on the histological results of these, 15 patients (16%) were diagnosed with IBD. The TI was successfully intubated in 40 patients, of which 32 patients had colonic biopsies taken as well. 8 patients did not have a colonic biopsy taken. Macroscopic abnormality in the TI was detected in 5 patients, all of whom were biopsied. Based on histological results of the biopsy, 3 patients (12%) were diagnosed with IBD. These 3 patients (100%) also had colonic biopsies taken simultaneously and showed inflammation. None of the patients had a diagnosis of IBD confirmed on TI intubation alone (where colonic biopsies were not done). None of the patients has a diagnosis of IBD confirmed on TI intubation alone (where colonic biopsies were negative). Conclusion: TI intubation is a highly-skilled, time-consuming procedure with a higher risk of perforation, which as per our study, has little additional diagnostic value in finding IBD for symptoms of diarrhea if colonic biopsies are taken. We propose that diarrhea is a colonic symptom; therefore, colonic biopsies are positive for inflammation if the diarrhea is secondary to IBD. We conclude that all of the IBDs can be diagnosed simply with colonic biopsies.

Keywords: biopsy, colon, IBD, terminal ileum

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Authors: Prapoj Na Bangchang

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This research aimed to study the satisfaction of university students on the Suan Sunandha Rajabhat University television station. The sample were 250 undergraduate students from Year 1 to Year 4. The tool used to collect data was a questionnaire. Statistics used in data analysis were percentage, mean and standard deviation. The results showed that student satisfaction on the University's television station location received high score, followed by the number of devices, and the content presented received the lowest score. Most students want the content of the programs to be improved especially entertainment content, followed by sports content.

Keywords: student satisfaction, university TV channel, media, broadcasting

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Authors: Habte Tadesse Likassa, Bacha Edosa

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Customer’s satisfaction was very important thing that is required for the existence of banks to be more productive and success in any organization and business area. The main goal of the study is assessing and identifying factors that influence customer’s satisfaction in West Shoa Zone of Commercial Bank of Ethiopia (Holeta, Ginchi, Ambo, Gedo and Bako). Stratified random sampling procedure was used in the study and by using simple random sampling (lottery method) 520 customers were drawn from the target population. By using Probability Proportional Size Techniques sample size for each branch of banks were allocated. Both descriptive and inferential statistics methods were used in the study. A binary logistic regression model was fitted to see the significance of factors affecting customer’s satisfaction in this study. SPSS statistical package was used for data analysis. The result of the study reveals that the overall level of customer’s satisfaction in the study area is low (38.85%) as compared those who were not satisfied (61.15%). The result of study showed that all most all factors included in the study were significantly associated with customer’s satisfaction. Therefore, it can be concluded that based on the comparison of branches on their customers satisfaction by using odd ratio customers who were using Ambo and Bako are less satisfied as compared to customers who were in Holeta branch. Additionally, customers who were in Ginchi and Gedo were more satisfied than that of customers who were in Holeta. Since the level of customers satisfaction was low in the study area, it is more advisable and recommended for concerned body works cooperatively more in maximizing satisfaction of their customers.

Keywords: customers, satisfaction, binary logistic, complain handling process, waiting time

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Authors: Yohannes Bisa Biramo

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

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

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