Abstract: Tuberculosis (TB) is considered as a major disease that affects daily activities and impairs health-related quality of life (HRQoL). The impact of TB on HRQoL can affect treatment outcome and may lead to treatment defaulting. Therefore, this study aims to evaluate the HRQoL of TB treatment lost to follow-up during and after treatment in Yemen. For this aim, this prospective study enrolled a total of 399 TB lost to follow-up patients between January 2011 and December 2015. By applying HRQoL criteria, only 136 fill the survey during treatment. Moreover, 96 were traced and fill out the HRQoL survey. All eight HRQol domains were categorized into the physical component score (PCS) and mental component score (MCS), which were calculated using QM scoring software. Results show that all lost to follow-up TB patients reported a score less than 47 for all eight domains, except general health (67.3) during their treatment period. Low scores of 27.9 and 29.8 were reported for emotional role limitation (RE) and mental health (MH), respectively. Moreover, the mental component score (MCS) was found to be only 28.9. The trace lost follow-up shows a significant improvement in all eight domains and a mental component score of 43.1. The low scores of 27.9 and 29.8 for role emotion and mental health, respectively, in addition to the MCS score of 28.9, show that severe emotional condition and reflect the higher depression during treatment period that can result to lost to follow-up. The low MH, RE, and MCS can be used as a clue for predicting future TB treatment lost to follow-up.
Abstract: Heat pipe is characterised as superconductor of heat because of its excellent heat removal ability. The operation of several engineering system results in generation of heat. This may cause several overheating problems and lead to failure of the systems. To overcome this problem and to achieve desired rate of heat dissipation, there is need to study the performance of heat pipe with annular fins under free convection at different inclinations. This study demonstrates the effect of different mass flow rate of hot fluid into evaporator section on the condenser side heat transfer coefficient with annular fins under natural convection at different inclinations. In this study annular fins are used for the experimental work having dimensions of length of fin, thickness of fin and spacing of fin as 10 mm, 1 mm and 6 mm, respectively. The main aim of present study is to discover at what inclination angles the maximum heat transfer coefficient shall be achieved. The heat transfer coefficient on the external surface of heat pipe condenser section is determined by experimental method and then predicted by empirical correlations. The results obtained from experimental and Churchill and Chu relation for laminar are in fair agreement with not more than 22% deviation. It is elucidated the maximum heat transfer coefficient of 31.2 W/(m2-K) at 25˚ tilt angle and minimal condenser heat transfer coefficient of 26.4 W/(m2-K) is seen at 45˚ tilt angle and 200 ml/min mass flow rate. Inclination angle also affects the thermal performance of heat pipe. Beyond 25o inclination, heat transport rate starts to decrease.
Abstract: The lateral stiffness of buildings is one of the most important properties which define resistance to displacements under lateral loads. Moreover, it has a great impact on the natural period of the structures. Different stiffness’s values can ultimately affect the behavior of the structure under the seismic load and the lateral forces that will be applied to it. In this study the effect of cracking is studied on 2D shell thin cantilever shear wall by using ETABS. Multi linear elastic analysis is conducted with the ACI stiffness modifiers for each analysis step. The results showed that the cracks affect the value of the drift especially at the top of the high rise buildings and this will change the lateral stiffness and so change the fundamental period of the structures which lead to change in the applied shear force that comes from the earthquake. Finally, this study emphasizes that the finite element method can be considered as a good tool to predict the tensile stresses in the elements.
Abstract: In China, the changes that men experience in the perinatal period are not well researched. Men are also at risk of maladaptation to parenthood. The aim of this research is to review current studies regarding changes that Chinese men experience during transitioning to parenthood. 5 databases were employed to search relevant papers. The search found 128 articles. Based on the inclusion and exclusion criteria, 35 articles were included in this integrative review. Results showed the changes that Chinese fathers experienced during the transition to parenthood can be divided into two aspects: family relationships and mental problems. During transition to parenthood, fathers usually experienced an increase in their disappointment with marital conflict resolution and decreased sexual intimacy with their partner. Mental health declined, with fathers often feeling depressed and/or anxious during this time. Some men were diagnosed with clinical depression. The predictors of these changes included three domains: personal background (age and income), family background (gender of infant, relationship status and unplanned child) and cultural background (‘doing the month’, Confucianism, policy, social support).
Abstract: European eels (Anguilla anguilla) belong to Anguilliformes order and Anguillidae family. They are generally classified as warm-water fish. Eels have a great commercial value in Europe and Asian countries. Eels can reach high weights, although their commercial size is relatively low in some countries. The capture of larger eels would facilitate the recovery of the species, as well as having a greater number of either glass eels or elvers for aquaculture. In the last years, the demand and the price of eels have increased significantly. However, European eel is considered critically endangered by the International Union for the Conservation of Nature (IUCN) Red List. The biochemical composition of fishes is an important aspect of quality and affects the nutritional value and consumption quality of fish. In addition, knowing this composition can help predict an individual’s condition for their recovery. Fish is known to be important source of protein rich in essential amino acids. However, there is very little information about changes in amino acids composition of European eels with increase in size. The aim of this study was to evaluate the effect of two different weight categories on the amino acids content in muscle tissue of wild European eels. European eels were caught in River Ulla (Galicia, NW Spain), during winter. The eels were slaughtered in ice water immersion. Then, they were purchased and transferred to the laboratory. The eels were subdivided into two groups, according to the weight. The samples were kept frozen (-20 °C) until their analysis. Frozen eels were defrosted and the white muscle between the head and the anal hole. was extracted, in order to obtain amino acids composition. Thirty eels for each group were used. Liquid chromatography was used for separation and quantification of amino a cids. The results conclude that the eels are rich in glutamic acid, leucine, lysine, threonine, valine, isoleucine and phenylalanine. The analysis showed that there are significant differences (p < 0.05) among the eels with different sizes. Histidine, threonine, lysine, hydroxyproline, serine, glycine, arginine, alanine and proline were higher in small eels. European eels muscle presents between 45 and 46% of essential amino acids in the total amino acids. European eels have a well-balanced and high quality protein source in the respect of E/NE ratio. However, eels with higher weight showed a better ratio of essential and non-essential amino acid.
Abstract: The author conducted post-test analysis with the RELAP5/MOD3.3 code for an experiment using the ROSA/LSTF (rig of safety assessment/large-scale test facility) that simulated a 1% cold leg small-break loss-of-coolant accident under the failure of scram in a pressurized water reactor. The LSTF test assumed total failure of high-pressure injection system of emergency core cooling system. In the LSTF test, natural circulation contributed to maintain core cooling effect for a relatively long time until core uncovery occurred. The post-test analysis result confirmed inadequate prediction of the primary coolant distribution. The author created the phenomena identification and ranking table (PIRT) for each component. The author investigated the influences of uncertain parameters determined by the PIRT on the cladding surface temperature at a certain time during core uncovery within the defined uncertain ranges.
Abstract: In the paper the results of welding of car’s air-conditioning elements are presented. These systems based on, mainly, the environmental unfriendly refrigerants. Thus, the producers of cars will have to stop using traditional refrigerant and to change it to carbon dioxide (R744). This refrigerant is environmental friendly. However, it should be noted that the air condition system working with R744 refrigerant operates at high temperature (up to 150 °C) and high pressure (up to 130 bar). These two parameters are much higher than for other refrigerants. Thus new materials, design as well as joining technologies are strongly needed for these systems. AISI 304 and 316L steels as well as aluminium alloys 5xxx are ranked among the prospective materials. As a joining process laser welding, plasma welding, electron beam welding as well as high rotary friction welding can be applied. In the study, the metallographic examination based on light microscopy as well as SEM was applied to estimate the quality of welded joints. The analysis of welding was supported by numerical modelling based on Sysweld software. The results indicated that using laser, plasma and electron beam welding, it is possible to obtain proper quality of welds in stainless steel. Moreover, high rotary friction welding allows to guarantee the metallic continuity in the aluminium welded area. The metallographic examination revealed that the grain growth in the heat affected zone (HAZ) in laser and electron beam welded joints were not observed. It is due to low heat input and short welding time. The grain growth and subgrains can be observed at room temperature when the solidification mode is austenitic. This caused low microstructural changes during solidification. The columnar grain structure was found in the weld metal. Meanwhile, the equiaxed grains were detected in the interface. The numerical modelling of laser welding process allowed to estimate the temperature profile in the welded joint as well as predicts the dimensions of welds. The agreement between FEM analysis and experimental data was achieved.
Abstract: Unidentified Flying Objects (UFOs) have been an interesting topic for most enthusiasts and hence people all over the United States report such findings online at the National UFO Report Center (NUFORC). Some of these reports are a hoax and among those that seem legitimate, our task is not to establish that these events confirm that they indeed are events related to flying objects from aliens in outer space. Rather, we intend to identify if the report was a hoax as was identified by the UFO database team with their existing curation criterion. However, the database provides a wealth of information that can be exploited to provide various analyses and insights such as social reporting, identifying real-time spatial events and much more. We perform analysis to localize these time-series geospatial events and correlate with known real-time events. This paper does not confirm any legitimacy of alien activity, but rather attempts to gather information from likely legitimate reports of UFOs by studying the online reports. These events happen in geospatial clusters and also are time-based. We look at cluster density and data visualization to search the space of various cluster realizations to decide best probable clusters that provide us information about the proximity of such activity. A random forest classifier is also presented that is used to identify true events and hoax events, using the best possible features available such as region, week, time-period and duration. Lastly, we show the performance of the scheme on various days and correlate with real-time events where one of the UFO reports strongly correlates to a missile test conducted in the United States.
Abstract: A major challenge in medical studies, especially those that are longitudinal, is the problem of missing measurements which hinders the effective application of many machine learning algorithms. Furthermore, recent Alzheimer's Disease studies have focused on the delineation of Early Mild Cognitive Impairment (EMCI) and Late Mild Cognitive Impairment (LMCI) from cognitively normal controls (CN) which is essential for developing effective and early treatment methods. To address the aforementioned challenges, this paper explores the potential of using the eXtreme Gradient Boosting (XGBoost) algorithm in handling missing values in multiclass classification. We seek a generalized classification scheme where all prodromal stages of the disease are considered simultaneously in the classification and decision-making processes. Given the large number of subjects (1631) included in this study and in the presence of almost 28% missing values, we investigated the performance of XGBoost on the classification of the four classes of AD, NC, EMCI, and LMCI. Using 10-fold cross validation technique, XGBoost is shown to outperform other state-of-the-art classification algorithms by 3% in terms of accuracy and F-score. Our model achieved an accuracy of 80.52%, a precision of 80.62% and recall of 80.51%, supporting the more natural and promising multiclass classification.
Abstract: Due to aging populations, the need for seamless palliative care provision is of central interest for western societies. An essential aspect of palliative care delivery is the quality of collaboration amongst palliative care providers. Therefore, the current research is based on Bainbridge’s conceptual framework, which provides an outline for the evaluation of palliative care provision. This study is the first one to investigate the predictive validity of spatial distribution on the quantity of interaction amongst various palliative care providers. Furthermore, based on the familiarity principle, we examine whether the extent of collaboration influences the perceived quality of collaboration among palliative care providers in urban versus rural areas of Switzerland. Based on a population-representative survey of Swiss palliative care providers, the results of the current study show that professionals in densely populated areas report higher absolute numbers of interactions and are more satisfied with their collaborative practice. This indicates that palliative care providers who work in urban areas are better embedded into networks than their counterparts in more rural areas. The findings are especially important, considering that efficient collaboration is a prerequisite to achieve satisfactory patient outcomes. Conclusively, measures should be taken to foster collaboration in weakly interconnected palliative care networks.
Abstract: In this paper, experiments were conducted to investigate the heat transfer of Copper Oxide-Heat Transfer Oil (CuO-HTO) nanofluid laminar flow in vertical smooth and microfin tubes as the surface temperature is constant. The effect of adding the nanoparticle to base fluid and Richardson number on the heat transfer enhancement is investigated as Richardson number increases from 0.1 to 0.7. The experimental results demonstrate that the combined forced-natural convection heat transfer rate may be improved significantly with an increment of mass nanoparticle concentration from 0% to 1.5%. In this experiment, a correlation is also proposed to predict the mixed convection heat transfer rate of CuO-HTO nanofluid flow. The maximum deviation of both correlations is less than 14%. Moreover, a correlation is presented to estimate the Nusselt number inside vertical smooth and microfin tubes as Rayleigh number is between 2´105 and 6.8´106 with the maximum deviation of 12%.
Abstract: Electricity markets throughout the world have
undergone substantial changes. Accurate, reliable, clear and
comprehensible modeling and forecasting of different variables
(loads and prices in the first instance) have achieved increasing
importance. In this paper, we describe the actual state of the
art focusing on reg-SARMA methods, which have proven to be
flexible enough to accommodate the electricity price/load behavior
satisfactory. More specifically, we will discuss: 1) The dichotomy
between point and interval forecasts; 2) The difficult choice between
stochastic (e.g. climatic variation) and non-deterministic predictors
(e.g. calendar variables); 3) The confrontation between modelling
a single aggregate time series or creating separated and potentially
different models of sub-series. The noteworthy point that we would
like to make it emerge is that prices and loads require different
approaches that appear irreconcilable even though must be made
reconcilable for the interests and activities of energy companies.
Abstract: Vitamin D deficiency and overweight are common in women suffering from polycystic ovary syndrome (PCOS). Weight gain in PCOS is an important factor for the development of menstrual dysfunction and signs of hyperandrogenism and alopecia. Features of PCOS such as oligomenorrhea can be predicted by anthropometric measurements as body mass index (BMI). Therefore, the aim of this trial was to study the effect of 50,000 IU/week of vitamin D₃ supplementation on the body composition and on the anthropometric measurements of overweight women with PCOS and to examine the impact of this effect on ovaries ultrasonography and menstrual cycle regularity. The study design was a prospective randomized, double-blinded placebo-controlled clinical trial conducted on 60 overweight Jordanian women aged (18-49) years with PCOS and vitamin D deficiency. The study participants were divided into two groups; vitamin D group (n = 30) who were assigned to receive 50,000 IU/week of vitamin D₃ and placebo group (n = 30) who were assigned to receive placebo tablets orally for 90 days. The anthropometric measurements and body composition were measured at baseline and after treatment for the PCOS and vitamin D deficient women. Also, assessment of the participants’ picture of ovaries by ultrasound and menstrual cycle regulatory were performed before and after treatment. Results showed that there were no significant (p > 0.05) differences between the placebo and vitamin D group basal 25(OH)D levels, body composition and anthropometric parameters. After treatment, vitamin D group serum levels of 25(OH)D increased (12.5 ± 0.61 to 50.2 ± 2.04 ng/mL, (p < 0.001), and decreased (50.2 ± 2.04 to 48.2 ± 2.03 ng/mL, p < 0.001) after 14 days of vitamin D₃ treatment cessation. There were no significant changes in the placebo group. In the vitamin D group, there were significant (p < 0.001) decreases in body weight, BMI, waist, and hip circumferences and fat mass. In addition, there were significant increases (p < 0.05) in fat free mass and total body water. These improvements in both anthropometric and body composition as well as in 25(OH)D concentrations, resulted in significant improvements in the picture of PCOS women ovaries ultrasonography and in menstrual cycle regularity, where nearly most of them (93%) had regular cycles after vitamin D₃ supplementation. In the placebo group, there were only significant decreases (p < 0.05) in waist and hip circumferences. It can be concluded that vitamin D supplementation improving serum 25(OH)D levels and PCOS prognosis by reducing body weight of overweight PCOS women and regulating their menstrual cycle.
Abstract: Time dependent settlement due to loading on soft saturated soils produces many problems such as high consolidation settlements and low consolidation rates. Also, long term consolidation settlement of soft soil underlying the embankment leads to unpredicted settlements and cracks on soil surface. Preloading method is an effective improvement method to solve this problem. Using vertical drains in preloading method is an effective method for improving soft soils. Applying deep soil mixing method on soft soils is another effective method for improving soft soils. There are little studies on using two methods of preloading and deep soil mixing simultaneously. In this paper, the concurrent effect of preloading with deep soil mixing by vertical drains is investigated through a finite element code, Plaxis2D. The influence of parameters such as deep soil mixing columns spacing, existence of vertical drains and distance between them, on settlement and stability factor of safety of embankment embedded on soft soil is investigated in this research.
Abstract: Machine Learning and Data Mining are the two important tools for extracting useful information and knowledge from large datasets. In machine learning, classification is a wildly used technique to predict qualitative variables and is generally preferred over regression from an operational point of view. Due to the enormous increase in air pollution in various countries especially China, Air Quality Classification has become one of the most important topics in air quality research and modelling. This study aims at introducing a hybrid classification model based on information theory and Support Vector Machine (SVM) using the air quality data of four cities in China namely Beijing, Guangzhou, Shanghai and Tianjin from Jan 1, 2014 to April 30, 2016. China's Ministry of Environmental Protection has classified the daily air quality into 6 levels namely Serious Pollution, Severe Pollution, Moderate Pollution, Light Pollution, Good and Excellent based on their respective Air Quality Index (AQI) values. Using the information theory, information gain (IG) is calculated and feature selection is done for both categorical features and continuous numeric features. Then SVM Machine Learning algorithm is implemented on the selected features with cross-validation. The final evaluation reveals that the IG and SVM hybrid model performs better than SVM (alone), Artificial Neural Network (ANN) and K-Nearest Neighbours (KNN) models in terms of accuracy as well as complexity.
Abstract: High cost of fossil fuels and intensifying installations of alternate energy generation sources are intimidating main challenges in power systems. Making accurate load forecasting an important and challenging task for optimal energy planning and management at both distribution and generation side. There are many techniques to forecast load but each technique comes with its own limitation and requires data to accurately predict the forecast load. Artificial Neural Network (ANN) is one such technique to efficiently forecast the load. Comparison between two different ranges of input datasets has been applied to dynamic ANN technique using MATLAB Neural Network Toolbox. It has been observed that selection of input data on training of a network has significant effects on forecasted results. Day-wise input data forecasted the load accurately as compared to year-wise input data. The forecasted load is then distributed among the six generators by using the linear programming to get the optimal point of generation. The algorithm is then verified by comparing the results of each generator with their respective generation limits.
Abstract: This paper presents a prediction performance of
feedforward Multilayer Perceptron (MLP) and Echo State Networks
(ESN) trained with extended Kalman filter. Feedforward neural
networks and ESN are powerful neural networks which can track and
predict nonlinear signals. However, their tracking performance
depends on the specific signals or data sets, having the risk of
instability accompanied by large error. In this study we explore this
process by applying different network size and leaking rate for
prediction of nonlinear or chaotic signals in MLP neural networks.
Major problems of ESN training such as the problem of initialization
of the network and improvement in the prediction performance are
tackled. The influence of coefficient of activation function in the
hidden layer and other key parameters are investigated by simulation
results. Extended Kalman filter is employed in order to improve the
sequential and regulation learning rate of the feedforward neural
networks. This training approach has vital features in the training of
the network when signals have chaotic or non-stationary sequential
pattern. Minimization of the variance in each step of the computation
and hence smoothing of tracking were obtained by examining the
results, indicating satisfactory tracking characteristics for certain
conditions. In addition, simulation results confirmed satisfactory
performance of both of the two neural networks with modified
parameterization in tracking of the nonlinear signals.
Abstract: It is well known that the real estate price depends on a lot of factors. Each house current value is dependent on the location, room number, transportation, living convenience, year and surrounding environments. Although, there are different experienced models for housing agent to estimate the price, it is a case by case study without overall dynamic variation investigation. However, many economic parameters may more or less influence the real estate price variation. Here, the influences of most macroeconomic parameters on real estate price are investigated individually based on least-square scheme and grey correlation strategy. Then those parameters are classified into leading indices, simultaneous indices and laggard indices. In addition, the leading time period is evaluated based on least square method. The important leading and simultaneous indices can be used to establish an artificial intelligent neural network model for real estate price variation prediction. The real estate price variation of Taipei, Taiwan during 2005 ~ 2017 are chosen for this research data analysis and validation. The results show that the proposed method has reasonable prediction function for real estate business reference.
Abstract: Controlling the flow of fluids is a challenging problem
that arises in many fields. Burgers’ equation is a fundamental
equation for several flow phenomena such as traffic, shock waves,
and turbulence. The optimal feedback control method, so-called
model predictive control, has been proposed for Burgers’ equation.
However, the model predictive control method is inapplicable to
systems whose all state variables are not exactly known. In practical
point of view, it is unusual that all the state variables of systems are
exactly known, because the state variables of systems are measured
through output sensors and limited parts of them can be only
available. In fact, it is usual that flow velocities of fluid systems
cannot be measured for all spatial domains. Hence, any practical
feedback controller for fluid systems must incorporate some type of
state estimator. To apply the model predictive control to the fluid
systems described by Burgers’ equation, it is needed to establish
a state estimation method for Burgers’ equation with limited
measurable state variables. To this purpose, we apply unscented
Kalman filter for estimating the state variables of fluid systems
described by Burgers’ equation. The objective of this study is to
establish a state estimation method based on unscented Kalman filter
for Burgers’ equation. The effectiveness of the proposed method is
verified by numerical simulations.
Abstract: The globalization of football especially among youth over the decade is uprising. Nigeria youth displaying football jerseys at every opportunity is an acceptance of football globalization. The Love for English Premier League (EPL) football jersey is very strong among Nigeria fans. Football club jerseys of the EPL are a common sports product among fans in Nigeria. This study investigates the contribution of football club jerseys towards EPL fans’ loyalty in Nigeria. Descriptive survey research design was used for the study. The population consists of EPL fans in Nigeria. Simple random sampling technique (fish bowl without replacement) was used to select two states from the six geo-political zones. Purposive sampling technique was used to pick eight viewing centres while accidental sampling technique was used to pick five vendor stands from each State. An average of 250 respondents was selected from each state. A total of 3,200 respondents participated in the research. Two research instruments were used. A self-developed structured questionnaire on Football Jersey Scale (FJS): The instrument consists of 10 items. Fans Loyalty Scale (FLS): The instrument was modified from the psychological commitment to team (PCT) scale, and consists of 20 items. The Cronbach’s Alpha reliability coefficient of 0.72 and 0.75 was obtained, respectively. The hypothesis was tested at 0.05 significant levels. Data were analysed using frequency, percentages count, pie chart and multiple regressions. The result showed that the b-value of football club jersey is 0.148 also the standard regression coefficient (Beta) is 0.089. The t = 4.759 is statistically significant at p = 0.000. This signified a relative contribution of football club jersey on EPL fans loyalty in Nigeria. Club jersey, which is the most outstanding identifier of every club, was found to significantly predict loyalty. The jersey on the body of the fan has become the site for a declaration of loyalty which becomes available for social interaction and negotiation. The Nigerian local league clubs in an attempt to keep Nigerian fans loyal must borrow a leaf from their European counterparts.