Search results for: mortality prediction

Authors: Omar Hussein El Ayadi, EmadY. El-Mansouri, Mohamed B. Dozan

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Production oil process require specific details i.e. oil composition. Generally, types of oil or differentiation between reservoir fluids depend specifically on composition. The main purpose of this study is to correlate and predict the Libyan oil (reservoir fluid and residual) composition utilizing tri-angle-coordinate plots discovered and tasked with Excel. The reservoir fluid data (61 old + 47 new), the residual oil data (33 new) collected from most of Libyan reservoirs were correlated with each others. Moreover, find a relation between stock tank molecular weight and stock tank oil gravity (oAPI), the molecular weight oh (C7+) versus residual oil gravity (oAPI). The average value of every oil composition was estimated including non-hydrocarbon (H2S, CO2, and N2). Nevertheless, the isomers (i-…) and normal (n-…) structure of (C4) and (C5) were also obtained. The summary of the conclusion is; utilizing excel Microsoft office to draw triangle coordinates to find two unknown component if only one is known. However, it is recommended to use the obtained oil composition plots and equations for any oil composition dependents i.e. optimum separator pressure.

Keywords: PVT, phase behavior, petroleum, chemical engineering

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Authors: Sasitharan Ambicapathy, J. Vignesh, P. Sivaraj, Godfrey Derek Sams, K. Sabarinath, V. R. Sanal Kumar

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The external flow simulation of a flying car at take off phase is a daunting task owing to the fact that the prediction of the transient unsteady flow features during its deployment phase is very complex. In this paper 3D numerical simulations of external flow of Ferrari F430 proposed flying car with different NACA 9618 rectangular wings have been carried. Additionally, the aerodynamics characteristics have been generated for optimizing its geometry for achieving the minimum take off velocity with better overall performance in both road and air. The three-dimensional standard k-omega turbulence model has been used for capturing the intrinsic flow physics during the take off phase. In the numerical study, a fully implicit finite volume scheme of the compressible, Reynolds-Averaged, Navier-Stokes equations is employed. Through the detailed parametric analytical studies we have conjectured that Ferrari F430 flying car facilitated with high wings having three different deployment histories during the take off phase is the best choice for accomplishing its better performance for the commercial applications.

Keywords: aerodynamics of flying car, air taxi, negative lift, roadable airplane

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Authors: Vinti Davar

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India is one among the many countries where child malnutrition is severe and also a major underlying cause of child mortality. The Mid Day Meal (MDM) program was launched to improve the nutritional status of children, attendance, and retention in schools. It was based on one meal provided to the children, who are attending elementary school (primary school). The objective of present study was to evaluate the impact of mid-day meal on the nutritional status of primary school children in Haryana, India. The present work was carried out on 1200 children between 6-11years of age, studying in primary schools in Haryana, India. Out of these 960 students as, the experimental group was selected from schools where mid-day meal is supplied by the government, and 240 students as control group where mid-day meal is not supplied. The mean height, weight, and BMI of children of both the groups were found to be significantly low as compared to NCHS standards. Stunting was found in 56.40% MDMB (Mid-day meal beneficiaries) and 62.50 % NMDMC (non- mid-day meal children).The weight of almost all subjects were low according to age indicating thinness. Anemia was more prevalent in MDMB as compared to NMDMC may be because school meals did not include vegetables. The consumption of energy, proteins, fat, calcium, iron, vitamins was significantly low (P ≤ .01) in both groups especially in girls of NMDM. The consumption of various food groups except vegetables was better in MDMB compared to NMDMC. It is concluded that with certain improvements, mid-meal can be beneficial in meeting everyday requirements of school going children.

Keywords: foods, meals, nutritional status, school going children

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Authors: Lan Nguyen, Lam Cao Van

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Thuan Phuoc is a suspension bridge built in Danang city, Vietnam. Because this bridge locates near the estuary, its structure has degraded rapidly. Many cracks have currently occurred on most of the concrete piers of the curved approach spans. This paper aims to present the results of diagnostic analysis of causes for cracks as well as some calculations for strengthening piers by carbon fiber reinforced polymer (CFRP). Besides, it describes how to use concrete nonlinear analysis software ATENA to diagnostically analyze cracks, strengthening designs. Basing on the results of studying the map of distributing crack on Thuan Phuoc bridge’s concrete piers is analyzed by the software ATENA is suitable for the real conditions and CFRP would be the best solution to strengthen piers in a sound and fast way.

Keywords: ATENA, bridge pier strengthening, carbon fiber reinforced polymer (CFRP), crack prediction analysis

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Authors: Samah Laalej, Abdelfattah Bouatem

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In the field of wind turbine blades, it is complicated to evaluate the aerodynamic performances through experimental measurements as it requires a lot of computing time and resources. Therefore, in this paper, a hybrid BEM-CFD numerical technique is developed to predict power and aerodynamic forces acting on the blades. Computational fluid dynamics (CFD) simulation was conducted to calculate the drag and lift forces through Ansys software using the K-w model. Then an enhanced BEM code was created to predict the power outputs generated by the wind turbine using the aerodynamic properties extracted from the CFD approach. The numerical approach was compared and validated with experimental data. The power curves calculated from this hybrid method were in good agreement with experimental measurements for all velocity ranges.

Keywords: blade element momentum, aerodynamic forces, wind turbine blades, computational fluid dynamics approach

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Authors: Esra Bora, Alper Omeroglu, Zeynep Pelin Polat, Oguzhan Kara, Fatih Akdogan, Sema Ucak Basat

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Hyponatremia is one of the most encountered electrolyte imbalance among all medical fields. It has a wide range of symptoms as well as complications from fatigue to loss of consciousness. Although a lot of factors can cause low sodium levels in serum, combining specific medications can lead to severe hyponatremia in a rapid onset which can cause high mortality and morbidity. The objective of this case report was to underline that prescribing specific medications disregarding their side effects can cause this common electrolyte imbalance but in a more severe manner. In this case report, we present a 46-year-old male patient with a serum sodium level of 104 mEq/L who consumed hydrochlorothiazide for hypertension and was under treatment with selective serotonin reuptake inhibitors (SSRIs) for major depression. The patient had tonic-clonic seizures at the second hour of the treatment and intubation was needed due to loss of consciousness and hypoxia. After proper replacement of sodium with hypertonic solutions in intensive care unit for nine days, extubation indicated. Even in healthy young males, hyponatremia due to two separately prescribed medications can lead life-threatening hyponatremia. Physicians should be aware of the side effects of diuretics, especially hydrochlorothiazides and SSRIs and their combinations.

Keywords: diuretics, hydrochlorothiazide, hyponatremia, SSRI

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Authors: Mohamed Hamed Mohamed Ahmed Alameer

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Population studies, essentially deals with the size, growth, and distribution of the population in a given area. Size, growth, and distribution are determined by three major factors, which are fertility mortality, and migration. Of these factors, fertility- as a number of live births a woman has actually had- is a potent socio-demographic force in vital process of population growth. So, fertility is a major component of population growth. It is one of the main determinants of population growth and has crucial role in population dynamic, because it measures the rate at which a population increased. In fact the levels of fertility are vary widely among nations, countries, geographic regions, ethnic, socio- economic groups, and religious groups. Fertility differential by religion have been empirically documented in a large numbers of countries. For instance, many researchers in developing and developed countries investigated the differential of fertility among Muslims and Non- Muslims. Most of them have found that fertility of Muslims is higher than fertility of non Muslims. And Muslims have a tendency for large families comparing to non- Muslims population. On the basis of this; Islam by it itself could play an important role in shaping attitudes and values of fertility, such as: sustainability of human kind, developmental reasons, religious Motivations, socioeconomic Motivations, and Psychological Motivation. Therefore, this paper investigates socio-economic values of fertility in Islam and compare it to Malthusian and neo Malthusian functionalists and conflict perspectives.

Keywords: islam, fertility, socioeconomic values, social sciences

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Authors: A. Kamel Abd Elaziz Mohamed, B. Sameh Kamal el Maraghi

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Introduction: Adaptive support ventilation (ASV) is an improved closed-loop ventilation mode that provides both pressure-controlled ventilation and PSV according to the patient’s needs. Aim of the work: To compare the short-term effects of Adaptive support ventilation (ASV), with conventional Pressure support ventilation (PSV) in weaning of intubated COPD patients. Patients and methods: Fifty patients admitted in the intensive care with acute exacerbation of COPD and needing intubation were included in the study. All patients were initially ventilated with control/assist control mode, in a stepwise manner and were receiving standard medical therapy. Patients were randomized into two groups to receive either ASV or PSV. Results: Out of fifty patients included in the study forty one patients in both studied groups were weaned successfully according to their ABG data and weaning indices. APACHE II score showed no significant difference in both groups. There were statistically significant differences between the groups in term of, duration of mechanical ventilation, weaning hours and length of ICU stay being shorter in (group 1) weaned by ASV. Re-intubation and mortality rate were higher in (group 11) weaned by conventional PSV, however the differences were not significant. Conclusion: ASV can provide automated weaning and achieve shorter weaning time for COPD patients hence leading to reduction in the total duration of MV, length of stay, and hospital costs.

Keywords: COPD patients, ASV, PSV, mechanical ventilation (MV)

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Authors: Ngozi Claribelle Nwogu, Mohammed Nasir Kajama, Oyoh Kechinyere, Edward Gobina

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Atmospheric carbon dioxide emissions are considered as the greatest environmental challenge the world is facing today. The challenges to control the emissions include the recovery of CO2 from flue gas. This concern has been improved due to recent advances in materials process engineering resulting in the development of inorganic gas separation membranes with excellent thermal and mechanical stability required for most gas separations. This paper therefore evaluates the performance of a highly selective inorganic membrane for CO2 recovery applications. Analysis of results obtained is in agreement with experimental literature data. Further results show the prediction performance of the membranes for gas separation and the future direction of research. The materials selection and the membrane preparation techniques are discussed. Method of improving the interface defects in the membrane and its effect on the separation performance has also been reviewed and in addition advances to totally exploit the potential usage of this innovative membrane.

Keywords: carbon dioxide, gas separation, inorganic ceramic membrane, permselectivity

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Authors: Sadia Ilyas, Hyunjung Kim, Rajiv R. Srivastava

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Current work has attempted to establish the linkages between circular bio-economy and recycling of copper and gold from urban mine by applying microbial activities instead of the smelter and chemical technologies. Thereafter, based on the potential of microbial approaches and research hypothesis, the structural model has been tested for a significance level of 99%, which is supported by the corresponding standardization co-efficient values. A prediction model applied to determine the recycling impact on circular bio-economy indicates to re-circulate 51,833 tons of copper and 58 tons of gold by 2030 for the production of virgin metals/raw-materials, while recycling rate of the accumulated e-waste remains to be 20%. This restoration volume of copper and gold through the microbial activities corresponds to mitigate 174 million kg CO₂ emissions and 24 million m³ water consumption if compared with the primary production activities. The study potentially opens a new window for environmentally-friendly biotechnological recycling of e-waste urban mine under the umbrella concept of circular bio-economy.

Keywords: urban mining, biobleaching, circular bio-economy, environmental impact

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Authors: Rassoli Aisa, Abrishami Movahhed Arezu, Faturaee Nasser, Seddighi Amir Saeed, Shafigh Mohammad

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Cardiovascular diseases are one of the most common causes of mortality in developed countries. Coronary artery abnormalities and carotid artery stenosis, also known as silent death, are among these diseases. One of the treatment methods for these diseases is to create a deviatory pathway to conduct blood into the heart through a bypass surgery. The saphenous vein is usually used in this surgery to create the deviatory pathway. Unfortunately, a re-surgery will be necessary after some years due to ignoring the disagreement of mechanical properties of graft tissue and/or applied prostheses with those of host tissue. The objective of the present study is to clarify the viscoelastic behavior of human saphenous tissue. The stress relaxation tests in circumferential and longitudinal direction were done in this vein by exerting 20% and 50% strains. Considering the stress relaxation curves obtained from stress relaxation tests and the coefficients of the standard solid model, it was demonstrated that the saphenous vein has a non-linear viscoelastic behavior. Thereafter, the fitting with Fung’s quasilinear viscoelastic (QLV) model was performed based on stress relaxation time curves. Finally, the coefficients of Fung’s QLV model, which models the behavior of saphenous tissue very well, were presented.

Keywords: Viscoelastic behavior, stress relaxation test, uniaxial tensile test, Fung’s quasilinear viscoelastic (QLV) model, strain rate

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Authors: J. K. Kavitha, D. Manjula, U. Kanimozhi

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Mining frequent and high utility item sets have gained much significance in the recent years. When the data arrives sporadically, incremental and interactive rule mining and utility mining approaches can be adopted to handle user’s dynamic environmental needs and avoid redundancies, using previous data structures, and mining results. The dependence on recommendation systems has exponentially risen since the advent of search engines. This paper proposes a model for building a recommendation system that suggests frequent and high utility item sets over dynamic datasets for a cluster based location prediction strategy to predict user’s trajectories using the Efficient Incremental Rule Mining (EIRM) algorithm and the Fast Update Utility Pattern Tree (FUUP) algorithm. Through comprehensive evaluations by experiments, this scheme has shown to deliver excellent performance.

Keywords: data sets, recommendation system, utility item sets, frequent item sets mining

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Authors: Lu Si, Jie Yu, Shasha Li, Jun Ma, Lei Luo, Qingbo Wu, Yongqi Ma, Zhengji Liu

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Instance selection (IS) technique is used to reduce the data size to improve the performance of data mining methods. Recently, to process very large data set, several proposed methods divide the training set into some disjoint subsets and apply IS algorithms independently to each subset. In this paper, we analyze the limitation of these methods and give our viewpoint about how to divide and conquer in IS procedure. Then, based on fast condensed nearest neighbor (FCNN) rule, we propose a large data sets instance selection method with MapReduce framework. Besides ensuring the prediction accuracy and reduction rate, it has two desirable properties: First, it reduces the work load in the aggregation node; Second and most important, it produces the same result with the sequential version, which other parallel methods cannot achieve. We evaluate the performance of FCNN-MR on one small data set and two large data sets. The experimental results show that it is effective and practical.

Keywords: instance selection, data reduction, MapReduce, kNN

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Authors: Abhimanyu Kumar, Chirag Gupta

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This work presents a comprehensive study on the employment of Model Predictive Control (MPC) for a three-phase voltage-source inverter to regulate the output voltage efficiently. The inverter is modeled via the Clarke Transformation, considering a scenario where the load is unknown. An LC filter model is developed, demonstrating its efficacy in Total Harmonic Distortion (THD) reduction. The system, when implemented with fault-tolerant multilevel inverter topologies, ensures reliable operation even under fault conditions, a requirement that is paramount with the increasing dependence on renewable energy sources. The research also integrates a Fuzzy Logic based fault tolerance system which identifies and manages faults, ensuring consistent inverter performance. The efficacy of the proposed methodology is substantiated through rigorous simulations and comparative results, shedding light on the voltage prediction efficiency and the robustness of the model even under fault conditions.

Keywords: total harmonic distortion, fuzzy logic, renewable energy sources, MLI

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Authors: Osama Shakeel

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The objective of the paper is to study the clinic-pathological factors, survival analyses, recurrence rate, metastatic rate, risk factors and the management of cutaneous malignant melanoma at Shaukat Khanum Memorial Cancer Hospital and Research Center. Methodology: From 2014 to 2017, all patients with a diagnosis of cutaneous malignant melanoma (CMM) were included in the study. Demographic variables were collected. Short and long term oncological outcomes were recorded. All data were entered and analyzed in SPSS version 21. Results: A total of 28 patients were included in the study. Median age was 46.5 +/-15.9 years. There were 16 male and 12 female patients. The family history of melanoma was present in 7.1% (n=2) of the patients. All patients had a mean survival of 13.43+/- 9.09 months. Lower limb was the commonest site among all which constitutes 46.4%(n=13). On histopathological analyses, ulceration was seen in 53.6% (n=15) patients. Unclassified tumor type was present in 75%(n=21) of the patients followed by nodular 21.4% (n=6) and superficial spreading 3.5%(n=1). Clark level IV was the commonest presentation constituting 46.4%(n=13). Metastases were seen in 50%(n=14) of the patients. Local recurrence was observed in 60.7%(n=17). 64.3%(n=18) lived after one year of treatment. Conclusion: CMM is a fatal disease. Although its disease of fair skin individuals, however, the incidence of CMM is also rising in this part of the world. Management includes early diagnoses and prompt management. However, mortality associated with this disease is still not favorable.

Keywords: malignant cancer of skin, cutaneous malignant melanoma, skin cancer, survival analyses

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Authors: Aadityaa Singla

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The big five personality traits are as follows: openness, conscientiousness, extraversion, agreeableness, and neuroticism. In order to get an insight into their personality, many flocks to these categories, which each have different meanings/characteristics. This information is important not only to individuals but also to career professionals and psychologists who can use this information for candidate assessment or job recruitment. The links between AI and psychology have been well studied in cognitive science, but it is still a rather novel development. It is possible for various AI classification models to accurately predict a personality question via ten input questions. This would contrast with the hundred questions that normal humans have to answer to gain a complete picture of their five personality traits. In order to approach this problem, various AI classification models were used on a dataset to predict what a user may answer. From there, the model's prediction was compared to its actual response. Normally, there are five answer choices (a 20% chance of correct guess), and the models exceed that value to different degrees, proving their significance. By utilizing an MLP classifier, decision tree, linear model, and K-nearest neighbors, they were able to obtain a test accuracy of 86.643, 54.625, 47.875, and 52.125, respectively. These approaches display that there is potential in the future for more nuanced predictions to be made regarding personality.

Keywords: machine learning, personally, big five personality traits, cognitive science

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Authors: Nyussupova Gulnara, Kenespayeva Laura, Kelinbayeva Roza, Aubakirova Gaukhar, Zhumagulov Chingiz, Aidarkhanova Gaukhar

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The article analyzes the development of demographic processes in four regions of the Western region of the Republic of Kazakhstan (Aktobe, Atyrau, West Kazakhstan, and Mangystau) for the period from 2000 to 2022. This study uses theoretical and methodological analysis of scientific literature, methods of comparative, statistical analysis, GIS methods, grouping and systematization, index method and structural analysis. The research identified regional characteristics, development trends, and disproportions in the population of the studied areas within the framework of sustainable demographic development. The population dynamics, the age-sex structure of the population, life expectancy, natural movement of the population, including maternal and infant mortality, are considered as important indicators of the region’s sustainability. The features of migration processes in the Western region of Kazakhstan and the factors that determine them are identified. Conclusions are drawn about the level of sustainable development of the population of the studied region based on demographic processes. The results obtained will provide scientific, methodological and information support in the sectors of economics and science, including the preparation of socio-economic development programs and the development of scientific research using GIS.

Keywords: sustainable development, demographic processes, Western Region, Republic of Kazakhstan, population structure, natural population movement, migration

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Authors: Çiğdem Bakır, Mecit Yüzkat

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With the increasing emphasis on water quality worldwide, the search for and expanding the market for new and intelligent monitoring systems has increased. The current method is the laboratory process, where samples are taken from bodies of water, and tests are carried out in laboratories. This method is time-consuming, a waste of manpower, and uneconomical. To solve this problem, we used machine learning methods to detect water pollution in our study. We created decision trees with the Orange3 software we used in our study and tried to determine all the factors that cause water pollution. An automatic prediction model based on water quality was developed by taking many model inputs such as water temperature, pH, transparency, conductivity, dissolved oxygen, and ammonia nitrogen with machine learning methods. The proposed approach consists of three stages: preprocessing of the data used, feature detection, and classification. We tried to determine the success of our study with different accuracy metrics and the results. We presented it comparatively. In addition, we achieved approximately 98% success with the decision tree.

Keywords: decision tree, water quality, water pollution, machine learning

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Authors: Abdul Hakim Chikho

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A simple method of calculating satisfactory of the effect of instability on the distribution of in-plane bending moments in unbraced semi-rigidly multistory steel framed structures is presented in this paper. This method, which is a modified form of the current amplified sway method of BS5950: part1:2000, uses an approximate load factor at elastic instability in each storey of a frame which in turn dependent up on the axial loads acting in the columns. The calculated factors are then used to represent the geometrical deformations due to the presence of axial loads, acting in that storey. Only a first order elastic analysis is required to accomplish the calculation. Comparison of the prediction of the proposed method and the current BS5950 amplified sway method with an accurate second order elastic computation shows that the proposed method leads to predictions which are markedly more accurate than the current approach of BS5950.

Keywords: improved amplified sway method, steel frames, semi-rigid connections, secondary effects

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Authors: Bhavita S. Dave, Jaimin Vaidya, Chandresh H. Solanki, Atul K.

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To measure the permeability of a soil specimen, one of the basic assumptions of Darcy's law is that the soil sample should be saturated. Unlike saturated soils, the permeability of unsaturated soils cannot be found using conventional methods as it does not follow Darcy's law. Many empirical models, such as the Van Genuchten Model and Fredlund-Xing Model were suggested to predict permeability value for unsaturated soil. Such models use data from the soil-freezing characteristic curve to find fitting parameters for frozen unsaturated soils. In this study, soil specimens were subjected to 0, 1, 3, and 5 freezing-thawing (F-T) cycles for different degrees of saturation to have a wide range of suction, and its soil freezing characteristic curves were formulated for all F-T cycles. Changes in fitting parameters and relative permeability with subsequent F-T cycles are presented in this paper for both models.

Keywords: frozen unsaturated soil, Fredlund Xing model, soil-freezing characteristic curve, Van Genuchten model

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Authors: Bronwen Wade

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Over the last half-century, child welfare systems have increasingly relied on quantitative risk assessment tools, such as actuarial or predictive risk tools. These tools are developed by performing statistical analysis of how attributes captured in administrative data are related to future child maltreatment. Some scholars argue that attributes in administrative data can serve as proxies for race and that quantitative risk assessment tools reify racial bias in decision-making. Others argue that these tools provide more “objective” and “scientific” guides for decision-making instead of subjective social worker judgment. This study performs a systematic review of the literature on the impact of quantitative risk assessment tools on racial disproportionality; it examines methodological biases in work on this topic, summarizes key findings, and provides suggestions for further work. A search of CINAHL, PsychInfo, Proquest Social Science Premium Collection, and the ProQuest Dissertations and Theses Collection was performed. Academic and grey literature were included. The review includes studies that use quasi-experimental methods and development, validation, or re-validation studies of quantitative risk assessment tools. PROBAST (Prediction model Risk of Bias Assessment Tool) and CHARMS (CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies) were used to assess the risk of bias and guide data extraction for risk development, validation, or re-validation studies. ROBINS-I (Risk of Bias in Non-Randomized Studies of Interventions) was used to assess for bias and guide data extraction for the quasi-experimental studies identified. Due to heterogeneity among papers, a meta-analysis was not feasible, and a narrative synthesis was conducted. 11 papers met the eligibility criteria, and each has an overall high risk of bias based on the PROBAST and ROBINS-I assessments. This is deeply concerning, as major policy decisions have been made based on a limited number of studies with a high risk of bias. The findings on racial disproportionality have been mixed and depend on the tool and approach used. Authors use various definitions for racial equity, fairness, or disproportionality. These concepts of statistical fairness are connected to theories about the reason for racial disproportionality in child welfare or social definitions of fairness that are usually not stated explicitly. Most findings from these studies are unreliable, given the high degree of bias. However, some of the less biased measures within studies suggest that quantitative risk assessment tools may worsen racial disproportionality, depending on how disproportionality is mathematically defined. Authors vary widely in their approach to defining and addressing racial disproportionality within studies, making it difficult to generalize findings or approaches across studies. This review demonstrates the power of authors to shape policy or discourse around racial justice based on their choice of statistical methods; it also demonstrates the need for improved rigor and transparency in studies of quantitative risk assessment tools. Finally, this review raises concerns about the impact that these tools have on child welfare systems and racial disproportionality.

Keywords: actuarial risk, child welfare, predictive risk, racial disproportionality

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Authors: O. Behar, A. Khellaf, K. Mohammedi, S. Ait Kaci

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Up to now, most validation studies have been based on the MBE and RMSE, and therefore, focused only on long and short terms performance to test and classify solar radiation models. This traditional analysis does not take into account the quality of modeling and linearity. In our analysis we have tested 22 solar radiation models that are capable to provide instantaneous direct and global radiation at any given location Worldwide. We introduce a new indicator, which we named Global Accuracy Indicator (GAI) to examine the linear relationship between the measured and predicted values and the quality of modeling in addition to long and short terms performance. Note that the quality of model has been represented by the T-Statistical test, the model linearity has been given by the correlation coefficient and the long and short term performance have been respectively known by the MBE and RMSE. An important founding of this research is that the use GAI allows avoiding default validation when using traditional methodology that might results in erroneous prediction of solar power conversion systems performances.

Keywords: solar radiation model, parametric model, performance analysis, Global Accuracy Indicator (GAI)

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Authors: Anders S. Kristensen, Dewan Ahsan, Saqib Mehmood, Shakeel Ahmed

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Traffic accidents are a result of the convergence of hazards, malfunctioning of vehicles and human negligence that have adverse economic and health impacts and effects. Unfortunately, avoiding them completely is very difficult, but with quick response to rescue and first aid, the mortality rate of inflicted persons can be reduced significantly. Smart and innovative technologies can play a pivotal role to respond faster to traffic crash emergencies comparing conventional means of transportation. For instance, Rescue Emergency Drone (RED) can provide faster and real-time crash site risk assessment to emergency medical services, thereby helping them to quickly and accurately assess a situation, dispatch the right equipment and assist bystanders to treat inflicted person properly. To conduct a research in this regard, the case of a traffic roundabout that is prone to frequent traffic accidents on the outskirts of Esbjerg, a town located on western coast of Denmark is hypothetically considered. Along with manual calculations, Emergency Disaster Management Simulation (EDMSIM) has been used to verify the response time of RED from a fire station of the town to the presumed crash site. The results of the study demonstrate the robustness of RED into emergency services to help save lives. 

Keywords: automated external defibrillator, medical emergency, response time, unmanned aerial system

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Authors: Mohamed Hafid, Marcel Lacroix

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This study presents an inverse analysis for predicting the thermal conductivities and the heat flux of a high-temperature metallurgical reactor simultaneously. Once these thermal parameters are predicted, the time-varying thickness of the protective phase-change bank that covers the inside surface of the brick walls of a metallurgical reactor can be calculated. The enthalpy method is used to solve the melting/solidification process of the protective bank. The inverse model rests on the Levenberg-Marquardt Method (LMM) combined with the Broyden method (BM). A statistical analysis for the thermal parameter estimation is carried out. The effect of the position of the temperature sensors, total number of measurements and measurement noise on the accuracy of inverse predictions is investigated. Recommendations are made concerning the location of temperature sensors.

Keywords: inverse heat transfer, phase change, metallurgical reactor, Levenberg–Marquardt method, Broyden method, bank thickness

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Authors: Ardalan Tofighi Soleimandarabi

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Artificial intelligence has revolutionized the concrete construction industry and improved processes by increasing efficiency, accuracy, and sustainability. This article examines the applications of artificial intelligence in predicting the compressive strength of concrete, optimizing mixing plans, and improving structural health monitoring systems. Artificial intelligence-based models, such as artificial neural networks (ANN) and combined machine learning techniques, have shown better performance than traditional methods in predicting concrete properties. In addition, artificial intelligence systems have made it possible to improve quality control and real-time monitoring of structures, which helps in preventive maintenance and increases the life of infrastructure. Also, the use of artificial intelligence plays an effective role in sustainable construction by optimizing material consumption and reducing waste. Although the implementation of artificial intelligence is associated with challenges such as high initial costs and the need for specialized training, it will create a smarter, more sustainable, and more affordable future for concrete structures.

Keywords: artificial intelligence, concrete construction, compressive strength prediction, structural health monitoring, stability

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Authors: S. Mousavian, A. Abedianpour, A. Khanmohammadi, S. Hematian, Gh. Eidi Veisi

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Ionic liquids are finding a wide range of applications from reaction media to separations and materials processing. In these applications, Vapor–Liquid equilibrium (VLE) is the most important one. VLE for six systems at 353 K and activity coefficients at infinite dilution 〖(γ〗_i^∞) for various solutes (alkanes, alkenes, cycloalkanes, cycloalkenes, aromatics, alcohols, ketones, esters, ethers, and water) in the ionic liquids (1-ethyl-3-methylimidazolium bis (trifluoromethylsulfonyl)imide [EMIM][BTI], 1-hexyl-3-methyl imidazolium bis (trifluoromethylsulfonyl) imide [HMIM][BTI], 1-octyl-3-methylimidazolium bis(trifluoromethylsulfonyl) imide [OMIM][BTI], and 1-butyl-1-methylpyrrolidinium bis (trifluoromethylsulfonyl) imide [BMPYR][BTI]) have been used to train neural networks in the temperature range from (303 to 333) K. Densities of the ionic liquids, Hildebrant constant of substances, and temperature were selected as input of neural networks. The networks with different hidden layers were examined. Networks with seven neurons in one hidden layer have minimum error and good agreement with experimental data.

Keywords: ionic liquid, neural networks, VLE, dilute solution

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Authors: Adnan Sahin, Ufuk Uylas, Ercument Pasaoglu, Tarik Caga, Enver Ihtiyar, Serdar Erkasap, Ersin Ates, Fatih Yasar

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Background: In this study, it was evaluated the demographic features, etiological factors and the management of acute pancreatitis. Methods: 106 patient hospitalized due to acute pancreatitis were retrospectively examined from 1 January 2015 to 31 December 2015 in Department of General Surgery of ESOGUMF. The data of gender, signs and symptoms, etiological factors, WBC, AST, ALT, Amilase, USG and CT findings treatment options ERCP, and complications, mortality rate were analysed. Results: The mean age of patients were 58.8 (53 men and 53 women). The causes of acute pancreatitis were as follows: gallbladder stone was 89, hyperlipidemia was 5 and idiopathic were 16 patients. Severe pancreatitis was developed in 16 patients in the biliary pancreatitis group and ERCP was performed. Cholecystectomy was performed to all biliary pancreatitis group patients after acute pancreatitis subside. The mean hospital stay period was 9.33 (2-37) day. Discussion and conclusion: Severe acute pancreatitis is a mortal disease. The most common etiological cause of acute pancreatitis is biliary origin. The first line treatment modality of acute pancreatitis is medical. Cholecystectomy should be planned to the all-biliary caused acute pancreatitis patients after the attack subside. ERCP is a useful treatment modality in the case of clinical worsening and suspicion of acute cholangitis. ERCP procedure used 16 patients in our series and these patients have a good morbidity and mean hospital period is lower than the others. We suppose that ERCP procedure should be planned selectively and conservatively.

Keywords: acute pancreatitis, ERCP, morbidity, treatment

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Authors: Fatema Salman, Ridha Hammam, Fatima Khairallah, Fatima Aradi, Nafeesa Abdulla, Mohammed Alsafar

Abstract:

Purpose: This study aims at measuring the extent of nurses’ knowledge and attitudes toward the use of physical restraints in different hospital wards at Salmaniya Medical Complex (SMC). Background: The habitual use of physical restraint is a widespread practice among nurses working in the clinical settings. Restraints inflict many deleterious consequences on patients physically and psychologically which in turn increases their morbidity and mortality risk and jeopardizes care quality. Nurses’ knowledge and attitudes toward physical restraints are crucial determinants of the persistence of this practice. Literature review: the evidence of lack of knowledge among nurses regarding the use of physical restraints is overwhelming in various clinical settings, especially in two main areas which are the negative consequences and the available alternatives to physical restraints. Studies explored nurses’ attitudes toward physical restraints yielded inconsistent findings. Equally comparable, some studies found that nurses hold positive attitudes toward the use of physical restraints while some others reported just the opposite. Methods: Self-administered knowledge and attitudes scales to 106 nurses working in the SMC. Findings: nurses hold the moderate level of knowledge about restraints (M=58%) with weak negative attitudes (M = -20%) toward using it. Significant moderately-strong negative correlation (r= -0.57, r2= 0.32, p= 0.000) was uncovered between nurses knowledge and their attitudes which provided an empirical explanation of this phenomenon (use of physical restraints). Recommendations: Induction of awareness program that especially focuses on the negative consequences and encourages the use of alternatives is an evident need. This effort necessarily should be adjoined with policy and procedure adjustments.

Keywords: attitudes, knowledge, nurses, restraints

Procedia PDF Downloads 323

Authors: José Leandro Melgar Néris, Claudinéia Brazil, Luciane Teresa Salvi, Isabel Cristina Damin

Abstract:

The impact the climate change is not recent, the main variable in the hydrological cycle is the sequence and shortage of a drought, which has a significant impact on the socioeconomic, agricultural and environmental spheres. This study aims to characterize and quantify, based on precipitation climatic projections, the rainy and dry events in the region of the Uruguay River Basin, through the Standardized Precipitation Index (SPI). The database is the image that is part of the Intercomparison of Model Models, Phase 5 (CMIP5), which provides condition prediction models, organized according to the Representative Routes of Concentration (CPR). Compared to the normal set of climates in the Uruguay River Watershed through precipitation projections, seasonal precipitation increases for all proposed scenarios, with a low climate trend. From the data of this research, the idea is that this article can be used to support research and the responsible bodies can use it as a subsidy for mitigation measures in other hydrographic basins.

Keywords: climate change, climatic model, dry events, precipitation projections

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Authors: Gangmin Li, Fan Yang

Abstract:

Personalized recommendation is crucial for any recommendation system. One of the techniques for personalized recommendation is to identify the intention. Traditional user intention identification uses the user’s selection when facing multiple items. This modeling relies primarily on historical behaviour data resulting in challenges such as the cold start, unintended choice, and failure to capture intention when items are new. Motivated by recent advancements in Large Language Models (LLMs) like ChatGPT, we present an approach for user intention identification by embracing LLMs with Chain-of-Thought (CoT) prompting. We use the initial user profile as input to LLMs and design a collection of prompts to align the LLM's response through various recommendation tasks encompassing rating prediction, search and browse history, user clarification, etc. Our tests on real-world datasets demonstrate the improvements in recommendation by explicit user intention identification and, with that intention, merged into a user model.

Keywords: personalized recommendation, generative user modelling, user intention identification, large language models, chain-of-thought prompting

Procedia PDF Downloads 62