Search results for: indirect costs overtime

Authors: Ravinder Singh, Pratima Syal

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Background: The rising prevalence and incidence of Acute Pancreatitis (AP) and its associated metabolic variables known as metabolic syndrome (MetS) are common medical conditions with catastrophic consequences and substantial treatment costs. The correlation between MetS and AP, as well as their impact on Health Related Quality of Life (HRQoL) is uncertain, and because there are so few published studies, further research is needed. As a result, we planned this study to determine the relationship between MetS components impact on HRQoL in AP patients. Patients and Methods: A prospective, observational study involving the recruitment of patients with AP with and without MetS was carried out in tertiary care hospital of North India. Patients were classified with AP if they were diagnosed with two or more components of the following criteria, abdominal pain, serum amylase and lipase levels two or more times normal, imaging trans-abdominal ultrasound, computed tomography, or magnetic resonance. The National Cholesterol Education Program–Adult Treatment Panel III (NCEP-ATP III) criterion was used to diagnose the MetS. The various socio-demographic variables were also taken into consideration for the calculation of statistical significance (P≤.05) in AP patients. Finally, the correlation between AP and MetS, along with their impact on HRQoL was assessed using Student's t test, Pearson Correlation Coefficient, and Short Form-36 (SF-36). Results: AP with MetS (n = 100) and AP without MetS (n = 100) patients were divided into two groups. Gender, Age, Educational Status, Tobacco use, Body Mass Index (B.M.I), and Waist Hip Ratio (W.H.R) were the socio-demographic parameters found to be statistically significant (P≤.05) in AP patients with MetS. Also, all the metabolic variables were also found to statistically significant (P≤.05) and found to be increased in patients with AP with MetS as compared to AP without MetS except HDL levels. Using the SF-36 form, a greater significant decline was observed in physical component summary (PCS) and mental component summary (MCS) in patients with AP with MetS as compared to patients without MetS (P≤.05). Furthermore, a negative association between all metabolic variables with the exception of HDL, and AP was found to be producing deterioration in PCS and MCS. Conclusion: The study demonstrated that patients with AP with MetS had a worse overall HRQOL than patients with AP without MetS due to number of socio-demographic and metabolic variables having direct correlation impacting physical and mental health of patients.

Keywords: metabolic disorers, QOL, cost effectiveness, pancreatitis

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Authors: S. Mani, M. Kafil, E. Asadi

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Condition Monitoring (CM) of electrical equipment has gained remarkable importance during the recent years; due to huge production losses, substantial imposed costs and increases in vulnerability, risk and uncertainty levels. Power cables feed numerous electrical equipment such as transformers, motors, and electric furnaces; thus their condition assessment is of a very great importance. This paper investigates electrical, structural and environmental failure sources, all of which influence cables' performances and limit their uptimes; and provides a comprehensive framework entailing practical CM guidelines for maintenance of cables in industries. The multilevel CM framework presented in this study covers performance indicative features of power cables; with a focus on both online and offline diagnosis and test scenarios, and covers short-term and long-term threats to the operation and longevity of power cables. The study, after concisely overviewing the concept of CM, thoroughly investigates five major areas of power quality, Insulation Quality features of partial discharges, tan delta and voltage withstand capabilities, together with sheath faults, shield currents and environmental features of temperature and humidity; and elaborates interconnections and mutual impacts between those areas; using mathematical formulation and practical guidelines. Detection, location, and severity identification methods for every threat or fault source are also elaborated. Finally, the comprehensive, practical guidelines presented in the study are presented for the specific case of Electric Arc Furnace (EAF) feeder MV power cables in Mobarakeh Steel Company (MSC), the largest steel company in MENA region, in Iran. Specific technical and industrial characteristics and limitations of a harsh industrial environment like MSC EAF feeder cable tunnels are imposed on the presented framework; making the suggested package more practical and tangible.

Keywords: condition monitoring, diagnostics, insulation, maintenance, partial discharge, power cables, power quality

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Authors: Christina Peristeri, Tobias Berg, Domenico Caridi, Paul Hutcheson, Robert Winstanley

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In recent years the demand for rapid innovations in the automotive industry has led to the need for accelerated simulation procedures while retaining a detailed representation of the simulated phenomena. The project’s aim is to create a fast transient workflow for external aerodynamic CFD simulations of road vehicles. The geometry used was the SAE Notchback Closed Cooling DrivAer model, and the simulation results were compared with data from wind tunnel tests. The meshes generated for this study were of two types. One was a mix of polyhedral cells near the surface and hexahedral cells away from the surface. The other was an octree hex mesh with a rapid method of fitting to the surface. Three different grid refinement levels were used for each mesh type, with the biggest total cell count for the octree mesh being close to 1 billion. A series of steady-state solutions were obtained on three different grid levels using a pseudo-transient coupled solver and a k-omega-based RANS turbulence model. A mesh-independent solution was found in all cases with a medium level of refinement with 200 million cells. Stress-Blended Eddy Simulation (SBES) was chosen for the transient simulations, which uses a shielding function to explicitly switch between RANS and LES mode. A converged pseudo-transient steady-state solution was used to initialize the transient SBES run that was set up with the SIMPLEC pressure-velocity coupling scheme to reach the fastest solution (on both CPU & GPU solvers). An important part of this project was the use of FLUENT’s Multi-GPU solver. Tesla A100 GPU has been shown to be 8x faster than an Intel 48-core Sky Lake CPU system, leading to significant simulation speed-up compared to the traditional CPU solver. The current study used 4 Tesla A100 GPUs and 192 CPU cores. The combination of rapid octree meshing and GPU computing shows significant promise in reducing time and hardware costs for industrial strength aerodynamic simulations.

Keywords: CFD, DrivAer, LES, Multi-GPU solver, octree mesh, RANS

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Authors: Tsung Chin Wu, Yu Chen Tsai, Rhay Hung Weng, Weir Sen Lin

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In recent years, nursing staff’s lower job satisfaction has led to higher turnover rates, and high turnover rates not only cause medical institution costs to increase but also the quality of medical care to decrease. From the perspective of internal marketing, institution staffs are internal customers, and institutions should focus and meet the needs of staff, so that staff will strive to meet the needs of external customers and provide them with the required care. However, few previous studies have investigated the impact of internal staff satisfaction on external customers. Therefore, this study aimed to conduct job satisfaction surveys on internal staff to investigate the relationship between job satisfaction and quality of medical care through statistical analysis of the study results. The related study results may serve as a reference for healthcare managers. This study was conducted using a questionnaire and the subjects were nursing staff from four hospitals. A total of 600 questionnaires were distributed and 577 valid questionnaires were returned with a response rate of 96.1%. After collecting the data, the reliability and validity of the study variables were confirmed by confirmatory factor analysis. The impact of internal marketing and job satisfaction on turnover intention of nursing staff was analyzed using descriptive analysis, one-way ANOVA, Pearson correlation analysis and multiple regression analysis. The study results showed that there was a significant difference between nursing staff’s job title and ‘professional participation’ and ‘shifts’. There was a significant difference between salary and ‘shifts’ and ‘turnover intention’, as well as between marriage and ‘remuneration’ and ‘turnover intention’. A significant difference was found between professional advancement and ‘professional growth’ and ‘type of leave’, as well as between division of service and ‘shifts’ and ‘turnover intention’. Pearson correlation analysis revealed a significant negative correlation between turnover intention and ‘internal marketing’, ‘interaction’, ‘professional participation’, ‘grasp of environment’, ‘remuneration’ and ‘shifts’, meaning that the higher the satisfaction, the lower the turnover intention. It is recommended that hospitals establish a comprehensive internal marketing mechanism to enhance staff satisfaction and in turn, reduce intention to resign, and the key to increasing job satisfaction is by establishing effective methods of internal communication.

Keywords: internal marketing, job satisfaction, turnover intention, nursing staff

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Authors: Jularat Chumnaul

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In forensic science, corpses from various homicides are different; there are both complete and incomplete, depending on causes of death or forms of homicide. For example, some corpses are cut into pieces, some are camouflaged by dumping into the river, some are buried, some are burned to destroy the evidence, and others. If the corpses are incomplete, it can lead to the difficulty of personally identifying because some tissues and bones are destroyed. To specify gender of the corpses from skeletal remains, the most precise method is DNA identification. However, this method is costly and takes longer so that other identification techniques are used instead. The first technique that is widely used is considering the features of bones. In general, an evidence from the corpses such as some pieces of bones, especially the skull and pelvis can be used to identify their gender. To use this technique, forensic scientists are required observation skills in order to classify the difference between male and female bones. Although this technique is uncomplicated, saving time and cost, and the forensic scientists can fairly accurately determine gender by using this technique (apparently an accuracy rate of 90% or more), the crucial disadvantage is there are only some positions of skeleton that can be used to specify gender such as supraorbital ridge, nuchal crest, temporal lobe, mandible, and chin. Therefore, the skeletal remains that will be used have to be complete. The other technique that is widely used for gender specifying in forensic science and archeology is skeletal measurements. The advantage of this method is it can be used in several positions in one piece of bones, and it can be used even if the bones are not complete. In this study, the classification and cluster analysis are applied to this technique, including the Kth Nearest Neighbor Classification, Classification Tree, Ward Linkage Cluster, K-mean Cluster, and Two Step Cluster. The data contains 507 particular individuals and 9 skeletal measurements (diameter measurements), and the performance of five methods are investigated by considering the apparent error rate (APER). The results from this study indicate that the Two Step Cluster and Kth Nearest Neighbor method seem to be suitable to specify gender from human skeletal remains because both yield small apparent error rate of 0.20% and 4.14%, respectively. On the other hand, the Classification Tree, Ward Linkage Cluster, and K-mean Cluster method are not appropriate since they yield large apparent error rate of 10.65%, 10.65%, and 16.37%, respectively. However, there are other ways to evaluate the performance of classification such as an estimate of the error rate using the holdout procedure or misclassification costs, and the difference methods can make the different conclusions.

Keywords: skeletal measurements, classification, cluster, apparent error rate

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Authors: Clinton Adas

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Antibiotic resistance has been identified by the World Health Organisation as a real possibility for the 21st Century. While many factors contribute to this, one of the more significant is industrial animal farming and its effect on the food chain and environment. Livestock consumes a significant portion of antibiotics sold globally, and these are used to make animals grow faster for profit purposes, to prevent illness caused by inhumane living conditions, and to treat disease when it breaks out. Many of these antibiotics provide little benefit to animals, and most are the same as those used by humans - including those deemed critical to human health that should therefore be used sparingly. Antibiotic resistance contributes to growing numbers of illnesses and death in humans, and the excess usage of these medications results in waste that enters the environment and is harmful to many ecological processes. This combination of antimicrobial resistance and environmental degradation furthermore harms the economic well-being and prospects of many. Using an interdisciplinary approach including medical, environmental, economic, and legal studies, the paper evaluates the dynamic between animal welfare and commerce and argues that while animal welfare is not of great concern to many, this approach is ultimately harming human welfare too. It is, however, proposed that both could be addressed under a One Health and Welfare approach, as we cannot continue to ignore the linkages between animals, the environment, and people. The evaluation of industrial animal farming is therefore considered through three aspects – the environmental impact, which is measured by pollution that causes environmental degradation; the human impact, which is measured by the rise of illnesses from pollution and antibiotics resistance; and the economic impact, which is measured through costs to the health care system and the financial implications of industrial farming on the economic well-being of many. These three aspects are considered in light of the Sustainable Development Goals that provide additional tangible metrics to evidence the negative impacts. While the research addresses the welfare of farmed animals, there is potential for these principles to be extrapolated into other contexts, including wildlife and habitat protection. It must be noted that while the question of animal rights in industrial animal farming is acknowledged and of importance, this is a separate matter that is not addressed here.

Keywords: animal and human welfare, industrial animal farming, one health and welfare, sustainable development goals

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Authors: Safak Isik, Ozalp Vayvay

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Strategic partnerships with suppliers play a vital role for the long-term value-based supply chain. This strategic collaboration keeps still being one of the top priority of many business organizations in order to create more additional value; benefiting mainly from supplier’s specialization, capacity and innovative power, securing supply and better managing costs and quality. However, many organizations encounter difficulties in initiating, developing and managing those partnerships and many attempts result in failures. One of the reasons for such failure is the incompatibility of members of this partnership or in other words wrong supplier selection which emphasize the significance of the selection process since it is the beginning stage. An effective selection process of strategic suppliers is critical to the success of the partnership. Although there are several research studies to select the suppliers in literature, only a few of them is related to strategic supplier selection for long-term partnership. The purpose of this study is to propose a conceptual model for the selection of strategic partnership suppliers. A two-stage approach has been used in proposed model incorporating first segmentation and second selection. In the first stage; considering the fact that not all suppliers are strategically equal and instead of a long list of potential suppliers, Kraljic’s purchasing portfolio matrix can be used for segmentation. This supplier segmentation is the process of categorizing suppliers based on a defined set of criteria in order to identify types of suppliers and determine potential suppliers for strategic partnership. In the second stage, from a pool of potential suppliers defined at first phase, a comprehensive evaluation and selection can be performed to finally define strategic suppliers considering various tangible and intangible criteria. Since a long-term relationship with strategic suppliers is anticipated, criteria should consider both current and future status of the supplier. Based on an extensive literature review; strategical, operational and organizational criteria have been determined and elaborated. The result of the selection can also be used to determine suppliers who are not ready for a partnership but to be developed for strategic partnership. Since the model is based on multiple criteria for both stages, it provides a framework for further utilization of Multi-Criteria Decision Making (MCDM) techniques. The model may also be applied to a wide range of industries and involve managerial features in business organizations.

Keywords: Kraljic’s matrix, purchasing portfolio, strategic supplier selection, supplier collaboration, supplier partnership, supplier segmentation

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Authors: Himanshu Sharma, Karthik Kumar, Harish Kumar

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The major problem in crop cultivation is the occurrence of multiple crop diseases. During the growth stage, timely identification of crop diseases is paramount to ensure the high yield of crops, lower production costs, and minimize pesticide usage. In most cases, crop diseases produce observable characteristics and symptoms. The Surveyors usually diagnose crop diseases when they walk through the fields. However, surveyor inspections tend to be biased and error-prone due to the nature of the monotonous task and the subjectivity of individuals. In addition, visual inspection of each leaf or plant is costly, time-consuming, and labour-intensive. Furthermore, the plant pathologists and experts who can often identify the disease within the plant according to their symptoms in early stages are not readily available in remote regions. Therefore, this study specifically addressed early detection of leaf scald, red rot, and eyespot types of diseases within sugarcane plants. The study proposes a computer vision-based approach using a convolutional neural network (CNN) for automatic identification of crop diseases. To facilitate this, firstly, images of sugarcane diseases were taken from google without modifying the scene, background, or controlling the illumination to build the training dataset. Then, the testing dataset was developed based on the real-time collected images from the sugarcane field from India. Then, the image dataset is pre-processed for feature extraction and selection. Finally, the CNN-based Visual Geometry Group (VGG) model was deployed on the training and testing dataset to classify the images into diseased and healthy sugarcane plants and measure the model's performance using various parameters, i.e., accuracy, sensitivity, specificity, and F1-score. The promising result of the proposed model lays the groundwork for the automatic early detection of sugarcane disease. The proposed research directly sustains an increase in crop yield.

Keywords: automatic classification, computer vision, convolutional neural network, image processing, sugarcane disease, visual geometry group

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Authors: Nepton Kiani

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Dental decay is one of the most common chronic diseases worldwide and imposes significant costs annually on people and healthcare systems. Addressing this issue is among the important programs of the World Health Organization in the field of oral and dental disease prevention and health promotion. In this context, oral and dental health in vulnerable groups, especially pregnant women, is of greater importance due to the health maintenance of the mother and fetus. The aim of this study is to investigate the DMFT index and various factors affecting it in order to identify different factors influencing the process of dental decay and to take an effective step in reducing the progression of this disease, control, and prevention. In this cross-sectional descriptive study, 120 pregnant women attending Nepton Policlinica clinic in Malaga, Spain, were evaluated for the DMFT index and oral and dental hygiene. In this regard, interviews, precise observations, and data collection were used. Subsequently, data analysis was performed using SPSS software and employing correlation tests, Kruskal-Wallis, and Mann-Whitney tests. The DMFT index for pregnant women in three age groups 22-26, 27- 31, and 32-36 years was respectively 2.8, 4.5, and 5.6. The results of logistic regression analysis showed that demographic variables (age, education, job, economic status) and the frequency of brushing and flossing lead to preventive behavior up to 49.58 percent (P<0.05). Generally, the results indicated that oral and dental care during pregnancy is poor. Only a small number of pregnant women regularly used toothbrush and dental floss or visited the dentist regularly. On the other hand, poor performance in adopting oral and dental care was more observed in pregnant women with lower economic and educational status. The present study showed that raising the level of awareness and education on oral and dental health in pregnant women is essential. In this field, it is necessary to focus on conducting educational-care courses at the level of healthcare centers for midwives, healthcare personnel, and at the community level for families, to prevent and perform dental treatments before the pregnancy period

Keywords: Malaga, oral and dental health, pregnant women, Spain

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Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

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Manufacturing companies are facing global competition and enormous cost pressure. The use of machine learning applications can help reduce production costs and create added value. Predictive quality enables the securing of product quality through data-supported predictions using machine learning models as a basis for decisions on test results. Furthermore, machine learning methods are able to process large amounts of data, deal with unfavourable row-column ratios and detect dependencies between the covariates and the given target as well as assess the multidimensional influence of all input variables on the target. Real production data are often subject to highly fluctuating boundary conditions and unbalanced data sets. Changes in production data manifest themselves in trends, systematic shifts, and seasonal effects. Thus, Machine learning applications require intensive pre-processing and feature selection. Data preprocessing includes rule-based data cleaning, the application of dimensionality reduction techniques, and the identification of comparable data subsets. Within the used real data set of Bosch hydraulic valves, the comparability of the same production conditions in the production of hydraulic valves within certain time periods can be identified by applying the concept drift method. Furthermore, a classification model is developed to evaluate the feature importance in different subsets within the identified time periods. By selecting comparable and stable features, the number of features used can be significantly reduced without a strong decrease in predictive power. The use of cross-process production data along the value chain of hydraulic valves is a promising approach to predict the quality characteristics of workpieces. In this research, the ada boosting classifier is used to predict the leakage of hydraulic valves based on geometric gauge blocks from machining, mating data from the assembly, and hydraulic measurement data from end-of-line testing. In addition, the most suitable methods are selected and accurate quality predictions are achieved.

Keywords: classification, achine learning, predictive quality, feature selection

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Authors: Zaki Abiza, Miguel Chavez, David M. Holman, Ruddy Brionnaud

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In this paper, the prediction of the aerodynamic behavior of the flow around a Finned Projectile will be validated using a Computational Fluid Dynamics (CFD) solution, XFlow, based on the Lattice-Boltzmann Method (LBM). XFlow is an innovative CFD software developed by Next Limit Dynamics. It is based on a state-of-the-art Lattice-Boltzmann Method which uses a proprietary particle-based kinetic solver and a LES turbulent model coupled with the generalized law of the wall (WMLES). The Lattice-Boltzmann method discretizes the continuous Boltzmann equation, a transport equation for the particle probability distribution function. From the Boltzmann transport equation, and by means of the Chapman-Enskog expansion, the compressible Navier-Stokes equations can be recovered. However to simulate compressible flows, this method has a Mach number limitation because of the lattice discretization. Thanks to this flexible particle-based approach the traditional meshing process is avoided, the discretization stage is strongly accelerated reducing engineering costs, and computations on complex geometries are affordable in a straightforward way. The projectile that will be used in this work is the Army-Navy Basic Finned Missile (ANF) with a caliber of 0.03 m. The analysis will consist in varying the Mach number from M=0.5 comparing the axial force coefficient, normal force slope coefficient and the pitch moment slope coefficient of the Finned Projectile obtained by XFlow with the experimental data. The slope coefficients will be obtained using finite difference techniques in the linear range of the polar curve. The aim of such an analysis is to find out the limiting Mach number value starting from which the effects of high fluid compressibility (related to transonic flow regime) lead the XFlow simulations to differ from the experimental results. This will allow identifying the critical Mach number which limits the validity of the isothermal formulation of XFlow and beyond which a fully compressible solver implementing a coupled momentum-energy equations would be required.

Keywords: CFD, computational fluid dynamics, drag, finned projectile, lattice-boltzmann method, LBM, lift, mach, pitch

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Authors: Henry Lau, Dilupa Nakandala, Li Zhao

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All along the length of the supply chain, fresh food firms face the challenge of managing both product quality, due to the perishable nature of the products, and product cost. This paper develops a method to assist logistics managers upstream in the fresh food supply chain in making cost optimized decisions regarding transportation, with the objective of minimizing the total cost while maintaining the quality of food products above acceptable levels. Considering the case of multiple fresh food products collected from multiple farms being transported to a warehouse or a retailer, this study develops a total cost model that includes various costs incurred during transportation. The practical application of the model is illustrated by using several computational intelligence approaches including Genetic Algorithms (GA), Fuzzy Genetic Algorithms (FGA) as well as an improved Simulated Annealing (SA) procedure applied with a repair mechanism for efficiency benchmarking. We demonstrate the practical viability of these approaches by using a simulation study based on pertinent data and evaluate the simulation outcomes. The application of the proposed total cost model was demonstrated using three approaches of GA, FGA and SA with a repair mechanism. All three approaches are adoptable; however, based on the performance evaluation, it was evident that the FGA is more likely to produce a better performance than the other two approaches of GA and SA. This study provides a pragmatic approach for supporting logistics and supply chain practitioners in fresh food industry in making important decisions on the arrangements and procedures related to the transportation of multiple fresh food products to a warehouse from multiple farms in a cost-effective way without compromising product quality. This study extends the literature on cold supply chain management by investigating cost and quality optimization in a multi-product scenario from farms to a retailer and, minimizing cost by managing the quality above expected quality levels at delivery. The scalability of the proposed generic function enables the application to alternative situations in practice such as different storage environments and transportation conditions.

Keywords: cost optimization, food supply chain, fuzzy sets, genetic algorithms, product quality, transportation

Procedia PDF Downloads 223

Authors: Haoyu Zhao, Qianshu Ma, Min Xie, Yunqi Huang, Yunjia Liu, Huan Song, Hongsheng Gui, Mingli Li, Qiang Wang

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Rationale: Bipolar disorder (BD) and major depressive disorder (MDD), as severe chronic illnesses that restrict patients’ psychosocial functioning and reduce their quality of life, are both categorized into mood disorders. Emerging evidence has suggested that the reliability of self-rated health (SRH) was wellvalidated and that the risk of various health outcomes, including mortality and health care costs, could be predicted by SRH. Compared with other lengthy multi-item patient-reported outcomes (PRO) measures, SRH was proven to have a comparable predictive ability to predict mortality and healthcare utilization. However, to our knowledge, no study has been conducted to assess the association between SRH and hospitalization among people with mental disorders. Therefore, our study aims to determine the association between SRH and subsequent all-cause hospitalizations in patients with BD and MDD. Methods: We conducted a prospective cohort study on people with BD or MDD in the UK from 2006 to 2010 using UK Biobank touchscreen questionnaire data and linked administrative health databases. The association between SRH and 2-year all-cause hospitalizations was assessed using proportional hazard regression after adjustment for sociodemographics, lifestyle behaviors, previous hospitalization use, the Elixhauser comorbidity index, and environmental factors. Results: A total of 29,966 participants were identified, experiencing 10,279 hospitalization events. Among the cohort, the average age was 55.88 (SD 8.01) years, 64.02% were female, and 3,029 (10.11%), 15,972 (53.30%), 8,313 (27.74%), and 2,652 (8.85%) reported excellent, good, fair, and poor SRH, respectively. Among patients reporting poor SRH, 54.19% had a hospitalization event within 2 years compared with 22.65% for those having excellent SRH. In the adjusted analysis, patients with good, fair, and poor SRH had 1.31 (95% CI 1.21-1.42), 1.82 (95% CI 1.68-1.98), and 2.45 (95% CI 2.22, 2.70) higher hazards of hospitalization, respectively, than those with excellent SRH. Conclusion: SRH was independently associated with subsequent all-cause hospitalizations in patients with BD or MDD. This large study facilitates rapid interpretation of SRH values and underscores the need for proactive SRH screening in this population, which might inform resource allocation and enhance high-risk population detection.

Keywords: severe mental illnesses, hospitalization, risk prediction, patient-reported outcomes

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Authors: Aneena Suresh, C. S. Sidharth

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Drug related problems (DRPs) are common in chronic kidney disease (CKD) patients and end stage patients undergoing hemodialysis. To treat the co-morbid conditions of the patients, more complex therapeutic regimen is required, and it leads to development of DRPs. So, this calls for frequent monitoring of the patients. Due to the busy work schedules, physicians are unable to deliver optimal care to these patients. Addition of a clinical pharmacist in the team will improve the standard of care offered to CKD patients by minimizing DRPs. In India, the role of clinical pharmacists in the improving the health outcomes in CKD patients is poorly recognized. Therefore, this study is conducted to put an insight on the role of clinical pharmacist in improving Drug Related Problems in patients with chronic kidney disease, thereby helping them to achieve desired therapeutic outcomes in the patients. A prospective interventional study was conducted for a year in a 620 bedded tertiary care hospital in India. Data was collected using an unstructured questionnaire, medication charts, etc. DRPs were categorized using Hepler and Strand classification. Relationships between the age, weight, GFR, average no of medication taken, average no of comorbidities, and average length of hospital days with the DRPs were identified using Mann Whitney U test. The study population primarily constituted of patients above the age of 50 years with a mean age of 59.91±13.59. Our study showed that 25% of the population presented with DRPs. On an average, CKD patients are prescribed at least 8 medications for the treatment in our study. This explains the high incidence of drug interactions in patients suffering from CKD (45.65%). The least common DRPs in our study were found to be sub therapeutic dose (2%) and adverse drug reactions (2%). Out of this, 60 % of the DRPs were addressed successfully. In our study, there is an association between the DRPs with the average number of medications prescribed, the average number of comorbidities, and the length of the hospital days with p value of 0.022, 0.004, and 0.000, respectively. In the current study, 86% of the proposed interventions were accepted, and 41 % were implemented by the physician, and only 14% were rejected. Hence, it is evident that clinical pharmacist interventions will contribute significantly to diminish the DRPs in CKD patients, thereby decreasing the economic burden of healthcare costs and improving patient’s quality of life.

Keywords: chronic kidney disease, clinical pharmacist, drug related problem, intervention

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Authors: Jennifer Cuellar, Angie L. Parada, Kevin N. S. Chacon, Sol M. Mejia

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The purification of bio-ethanol through distillation methods is an unresolved issue at the biofuel industry because of the ethanol-water azeotrope formation, which increases the steps of the purification process and subsequently increases the production costs. Therefore, understanding the mixture nature at the molecular level could provide new insights for improving the current methods and/or designing new and more efficient purification methods. For that reason, the present study focuses on the evaluation and analysis of (ethanol)₉-water heterodecamers, as the systems with the minimum molecular proportion that represents the azeotropic concentration (96 %m/m in ethanol). The computational modelling was carried out with B3LYP-D3/6-311++G(d,p) in Gaussian 09. Initial explorations of the potential energy surface were done through two methods: annealing simulated runs and molecular dynamics trajectories besides intuitive structures obtained from smaller (ethanol)n-water heteroclusters, n = 7, 8 and 9. The energetic order of the seven stable heterodecamers determines the most stable heterodecamer (Hdec-1) as a structure forming a bicyclic geometry with the O-H---O hydrogen bonds (HBs) where the water is a double proton donor molecule. Hdec-1 combines 1 water molecule and the same quantity of every ethanol conformer; this is, 3 trans, 3 gauche 1 and 3 gauche 2; its abundance is 89%, its decamerization energy is -80.4 kcal/mol, i.e. 13 kcal/mol most stable than the less stable heterodecamer. Besides, a way to understand why methanol does not form an azeotropic mixture with water, analogous systems ((ethanol)10, (methanol)10, and (methanol)9-water)) were optimized. Topologic analysis of the electron density reveals that Hec-1 forms 33 weak interactions in total: 11 O-H---O, 8 C-H---O, 2 C-H---C hydrogen bonds and 12 H---H interactions. The strength and abundance of the most unconventional interactions (H---H, C-H---O and C-H---O) seem to explain the preference of the ethanol for forming heteroclusters instead of clusters. Besides, O-H---O HBs present a significant covalent character according to topologic parameters as the Laplacian of electron density and the relationship between potential and kinetic energy densities evaluated at the bond critical points; obtaining negatives values and values between 1 and 2, for those two topological parameters, respectively.

Keywords: ADMP, DFT, ethanol-water azeotrope, Grimme dispersion correction, simulated annealing, weak interactions

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Authors: Brooklyn Rushton, Michelle Rutty, Natalie Knowles, Daniel Scott

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As people are increasingly on the search for extraordinary experiences and connections with nature, adventure tourism is experiencing significant growth and providing tourists with life-changing experiences. Unlike built attraction-based tourism, adventure tourism relies entirely on natural heritage, which leaves communities dependent on adventure tourism extremely vulnerable to environmental and climatic changes. A growing body of evidence suggests that global climate change will influence the future of adventure tourism and mountain outdoor recreation opportunities on a global scale. Across Canada, more specifically, climate change is broadly anticipated to present risks for winter-snow sports, while opportunities are anticipated to arise for green season activities. These broad seasonal shifts do not account for the indirect impacts of climate change on adventure tourism, such as the cost of adaptation or the increase of natural hazards and the associated likelihood of accidents. While some research has examined the impact of climate change on natural environments that adventure tourism relies on, a very small body of research has specifically focused on guides’ perspectives or included hard adventure tourism activities. The guiding industry is unique, as guides are trained through an elegant blend of art and science to make decisions based on experience, observation, and intuition. While quantitative research can monitor change in natural environments, guides local knowledge can provide eye-witness accounts and outline what environmental changes mean for the future sustainability of adventure tourism. This research will capture the extensive knowledge of mountain guides to better understand the implications of climate change for mountain adventure and potential adaptive responses for the adventure tourism industry. This study uses a structured online survey with open and close-ended questions that will be administered using Qualtrics (an online survey platform). This survey is disseminated to current members of the Association of Canadian Mountain Guides (ACMG). Participation in this study will be exclusive to members of the ACMG operating in the outdoor guiding streams. The 25 survey questions are organized into four sections: demographic and professional operation (9 questions), physical change (4 questions), climate change perception (6 questions), and climate change adaptation (6 questions). How mountain guides perceive and respond to climate change is important knowledge for the future of the expanding adventure tourism industry. Results from this study are expected to provide important information to mountain destinations on climate change vulnerability and adaptive capacity. Expected results of this study include guides insight into: (1) experience-safety relevant observed physical changes in guided regions (i.e. glacial coverage, permafrost coverage, precipitation, temperature, and slope instability) (2) changes in hazards within the guiding environment (i.e. avalanches, rockfall, icefall, forest fires, flooding, and extreme weather events), (3) existing and potential adaptation strategies, and (4) key information and other barriers for adaptation. By gaining insight from the knowledge of mountain guides, this research can help the tourism industry at large understand climate risk and create adaptation strategies to ensure the resiliency of the adventure tourism industry.

Keywords: adventure tourism, climate change, environmental change, mountain hazards

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Authors: Cangir Uyarlar, Eyup Eren Gultepe, Mustafa Kabu, Hacı Ahmet Celik

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This study aimed to evaluate the effects of orally Immunoglobulin (Ig) Y treatments to calves were fed with colostrum having insufficient antibodies before first suckling. A total of 28 Holstein calves were fed assigned into control and treatment groups. The calves were fed fresh colostrum from their respective mother for the first 4 days. The treatment group calves were orally administered IgLock (10 g/d/calf) immediately before the first colostrum feeding and IgLock was administered just one time in treatment group calves. Then, the calves were offered normal milk until weaning. After weaning, all calves kept same paddock and were fed same ration. Diarrhea and respiratoric diseases were recorded for one year. Blood was collected from all calves in the study on birth day (0 day) before vaccination and IgLock administration, then, collected for the following 2 days in all groups. Albumin (ALB), Total Protein (TP), Aspartate Aminotransferase (AST), Alanine Aminotrasferase (ALT), Gamma-Glutamyl Transferase (GGT), Serum Amyloid A (SAA), Haptoglobin (HPT) and Ig G analyses were performed on all samples. Although serum ALB, ALT, GGT and Ig G levels were not shown a time dependent-change within control group; serum TP, AST, HPT and SAA levels were significantly changed by the time within mentioned group. Serum TP level was steady at first 2 days, then, it was increased significantly at 3rd day. Also, serum AST level was significantly increased at 2nd day, then it was descended to first day levels again at 3rd day. Although serum HPT levels were shown a significant gradually decreasing within control group, serum SAA levels were decreased rapidly after first day and there were no significance differences between 2nd and 3rd day in SAA levels. Serum ALB, ALT, HPT and SAA levels were not shown a time dependent-change within treatmet group. After first day Serum TP, GGT, AST and Ig G levels were shown an significant increasing at 2nd day. Serum TP, GGT and Ig G levels were higher as compared to 1st day within treatment group at 3rd day. But, serum AST level was less significantly 3rd day as compared to 2nd day values. The total numbers of calves suffered from diarrhea were significantly less in treatment group as compared to control group (p < 0,05). The pneumonia reappear ratio in calves suffered the diseases is 33,3% in control group and 11,11% in treatment group. Total cost of diseases and additives was 2339,36 $ for control and 1276,4 $ for treatment. As a conclusion, the immunity enhancers like IgLock are important and cost-effective to boost up immunity status in the early age which would be having positive effects on calves were received colostrum included insufficient antibodies.

Keywords: dairy calves, Ig Y, pneumonia, scours

Procedia PDF Downloads 494

Authors: Fazıl Gökgöz, Fahrettin Filiz

Abstract:

Load forecasting has become crucial in recent years and become popular in forecasting area. Many different power forecasting models have been tried out for this purpose. Electricity load forecasting is necessary for energy policies, healthy and reliable grid systems. Effective power forecasting of renewable energy load leads the decision makers to minimize the costs of electric utilities and power plants. Forecasting tools are required that can be used to predict how much renewable energy can be utilized. The purpose of this study is to explore the effectiveness of LSTM-based neural networks for estimating renewable energy loads. In this study, we present models for predicting renewable energy loads based on deep neural networks, especially the Long Term Memory (LSTM) algorithms. Deep learning allows multiple layers of models to learn representation of data. LSTM algorithms are able to store information for long periods of time. Deep learning models have recently been used to forecast the renewable energy sources such as predicting wind and solar energy power. Historical load and weather information represent the most important variables for the inputs within the power forecasting models. The dataset contained power consumption measurements are gathered between January 2016 and December 2017 with one-hour resolution. Models use publicly available data from the Turkish Renewable Energy Resources Support Mechanism. Forecasting studies have been carried out with these data via deep neural networks approach including LSTM technique for Turkish electricity markets. 432 different models are created by changing layers cell count and dropout. The adaptive moment estimation (ADAM) algorithm is used for training as a gradient-based optimizer instead of SGD (stochastic gradient). ADAM performed better than SGD in terms of faster convergence and lower error rates. Models performance is compared according to MAE (Mean Absolute Error) and MSE (Mean Squared Error). Best five MAE results out of 432 tested models are 0.66, 0.74, 0.85 and 1.09. The forecasting performance of the proposed LSTM models gives successful results compared to literature searches.

Keywords: deep learning, long short term memory, energy, renewable energy load forecasting

Procedia PDF Downloads 266

Authors: M. Ali Mandegari, S. Farzad, , J. F. Görgens

Abstract:

Sugar is one of the main agricultural industries in South Africa and approximately livelihoods of one million South Africans are indirectly dependent on sugar industry which is economically struggling with some problems and should re-invent in order to ensure a long-term sustainability. Second generation biorefinery is defined as a process to use waste fibrous for the production of biofuel, chemicals animal food, and electricity. Bioethanol is by far the most widely used biofuel for transportation worldwide and many challenges in front of bioethanol production were solved. Biorefinery annexed to the existing sugar mill for production of bioethanol and electricity is proposed to sugar industry and is addressed in this study. Since flowsheet development is the key element of the bioethanol process, in this work, a biorefinery (bioethanol and electricity production) annexed to a typical South African sugar mill considering 65ton/h dry sugarcane bagasse and tops/trash as feedstock was simulated. Aspen PlusTM V8.6 was applied as simulator and realistic simulation development approach was followed to reflect the practical behaviour of the plant. Latest results of other researches considering pretreatment, hydrolysis, fermentation, enzyme production, bioethanol production and other supplementary units such as evaporation, water treatment, boiler, and steam/electricity generation units were adopted to establish a comprehensive biorefinery simulation. Steam explosion with SO2 was selected for pretreatment due to minimum inhibitor production and simultaneous saccharification and fermentation (SSF) configuration was adopted for enzymatic hydrolysis and fermentation of cellulose and hydrolyze. Bioethanol purification was simulated by two distillation columns with side stream and fuel grade bioethanol (99.5%) was achieved using molecular sieve in order to minimize the capital and operating costs. Also boiler and steam/power generation were completed using industrial design data. Results indicates that the annexed biorefinery can be self-energy sufficient when 35% of feedstock (tops/trash) bypass the biorefinery process and directly be loaded to the boiler to produce sufficient steam and power for sugar mill and biorefinery plant.

Keywords: biorefinery, self-energy sufficiency, tops/trash, bioethanol, electricity

Procedia PDF Downloads 538

Authors: Wighens Ngoie Ilunga, Pamela J. Welz, Olewaseun O. Oyekola, Daniel Ikhu-Omoregbe

Abstract:

Currently, most sludge from the wastewater treatment plants of edible oil factories is disposed to landfills, but landfill sites are finite and potential sources of environmental pollution. Production of biodiesel from wastewater sludge can contribute to energy production and waste minimization. However, conventional biodiesel production is energy and waste intensive. Generally, biodiesel is produced from the transesterification reaction of oils with alcohol (i.e., Methanol, ethanol) in the presence of a catalyst. Homogeneously catalysed transesterification is the conventional approach for large-scale production of biodiesel as reaction times are relatively short. Nevertheless, homogenous catalysis presents several challenges such as high probability of soap. The current study aimed to reuse wastewater sludge from the edible oil industry as a novel feedstock for both monounsaturated fats and bioethanol for the production of biodiesel. Preliminary results have shown that the fatty acid profile of the oilseed wastewater sludge is favourable for biodiesel production with 48% (w/w) monounsaturated fats and that the residue left after the extraction of fats from the sludge contains sufficient fermentable sugars after steam explosion followed by an enzymatic hydrolysis for the successful production of bioethanol [29% (w/w)] using a commercial strain of Saccharomyces cerevisiae. A novel nano-magnetic catalyst was synthesised from mineral processing alkaline tailings, mainly containing dolomite originating from cupriferous ores using a modified sol-gel. The catalyst elemental chemical compositions and structural properties were characterised by X-ray diffraction (XRD), scanning electron microscopy (SEM), Fourier transform infra-red (FTIR) and the BET for the surface area with 14.3 m²/g and 34.1 nm average pore diameter. The mass magnetization of the nano-magnetic catalyst was 170 emu/g. Both the catalytic properties and reusability of the catalyst were investigated. A maximum biodiesel yield of 78% was obtained, which dropped to 52% after the fourth transesterification reaction cycle. The proposed approach has the potential to reduce material costs, energy consumption and water usage associated with conventional biodiesel production technologies. It may also mitigate the impact of conventional biodiesel production on food and land security, while simultaneously reducing waste.

Keywords: biodiesel, bioethanol, edible oil wastewater sludge, nano-magnetism

Procedia PDF Downloads 145

Authors: Alexander Rych

Abstract:

Piql Preservation Services (“Piql”) is a turnkey solution designed for secure, migration-free long- term preservation of digital data. Piql sets an open standard for long- term preservation for the future. It consists of equipment and processes needed for writing and retrieving digital data. Exponentially growing amounts of data demand for logistically effective and cost effective processes. Digital storage media (hard disks, magnetic tape) exhibit limited lifetime. Repetitive data migration to overcome rapid obsolescence of hardware and software bears accelerated risk of data loss, data corruption or even manipulation and adds significant repetitive costs for hardware and software investments. Piql stores any kind of data in its digital as well as analog form securely for 500 years. The medium that provides this is a film reel. Using photosensitive film polyester base, a very stable material that is known for its immutability over hundreds of years, secure and cost-effective long- term preservation can be provided. The film reel itself is stored in a packaging capable of protecting the optical storage medium. These components have undergone extensive testing to ensure longevity of up to 500 years. In addition to its durability, film is a true WORM (write once- read many) medium. It therefore is resistant to editing or manipulation. Being able to store any form of data onto the film makes Piql a superior solution for long-term preservation. Paper documents, images, video or audio sequences – all of those file formats and documents can be preserved in its native file structure. In order to restore the encoded digital data, only a film scanner, a digital camera or any appropriate optical reading device will be needed in the future. Every film reel includes an index section describing the data saved on the film. It also contains a content section carrying meta-data, enabling users in the future to rebuild software in order to read and decode the digital information.

Keywords: digital data, long-term preservation, migration-free, photosensitive film

Procedia PDF Downloads 392

Authors: Eduardo Cabrera-Rode, Janet Rodriguez, Aimee Alvarez, Ragmila Echevarria, Antonio D. Reyes, Ileana Cubas-Duenas, Silvia E. Turcios, Oscar Diaz-Diaz

Abstract:

Obex is a nutritional supplement to help weight loss naturally. In addition, this supplement has a satiating effect that helps control the craving to eat between meals. The purpose of this study was to evaluate the effect of Obex in the metabolic syndrome (MS). This was an open label pilot study conducted in 30 patients with MS and ages between 29 and 60 years old. Participants received Obex, at a dose of one sachet before (30 to 45 minutes) the two main meals (lunch and dinner) daily (mean two sachets per day) for 3 months. The content of the sachets was dissolved in a glass of water or fruit juice. Obex ingredients: Açai (Euterpe oleracea Mart.) berry, inulin, Phaseolus vulgaris, Caralluma fimbriata, inositol, choline, arginine, ornitine, zinc sulfate, carnitine fumarate, methionine, calcium pantothenate, pyridoxine and folic acid. In addition to anthropometric measures and blood pressure, fasting plasma glucose, total cholesterol, triglycerides and HDL-cholesterol and insulin were determined. Insulin resistance was assessed by HOMA-IR index. Three indirect indexes were used to calculate insulin sensitivity [QUICKI index (Quantitative insulin sensitivity check index), Bennett index and Raynaud index]. Metabolic syndrome was defined according to the Joint Interim Statement (JIS) criteria. The JIS criteria require at least three of the following components: (1) abdominal obesity (waist circumference major or equal major or equal 94 cm for men or 80 cm for women), (2) triglycerides major or equal 1.7 mmol/L, (3) HDL cholesterol minor 1.03 mmol/L for men or minor 1.30 mmol/L for women, (4) systolic/diastolic blood pressure major or equal 130/85mmHg or use antihypertensive drugs, and (5) fasting plasma glucose major or equal 5.6 mmol/L or known treatment for diabetes. This study was approved by the Ethical and Research Committee of the National Institute of Endocrinology, Cuba and conducted according to the Declaration of Helsinki. Obex is registered as a food supplement in the National Institute of Nutrition and Food, Havana, Cuba. Written consent was obtained from all patients before the study. The clinical trial had been registered at ClinicalTrials.gov. After three months of treatment, 43.3% (13/30) of participants decreased the frequency of MS. Compared to baseline, Obex significantly reduced body weight, BMI, waist circumference, and waist/hip ratio and improved HDL-c (p<0.0001) and in addition to lowering blood pressure (p<0.05). After Obex intake, subjects also have shown a reduction in fasting plasma glucose (p<0.0001) and insulin sensitivity was enhanced (p=0.001). No adverse effects were seen in any of the participants during the study. In this pilot study, consumption of Obex decreased the prevalence of MS due to the improved selected components of the metabolic syndrome, indicating that further studies are warranted. Obex emerges as an effective and well tolerated treatment for preventing or delaying MS and therefore potential reduction of cardiovascular risk.

Keywords: nutritional supplement, metabolic syndrome, weight loss, insulin resistance

Procedia PDF Downloads 297

Authors: Miguel Angel Calvo Salve

Abstract:

Building enclosures and façades not only have an aesthetic component they must also ensure thermal comfort and improve the acoustics and air quality in buildings. The role of facades design, its assemblies, and construction are key in developing a greener future in architecture. This research and study focus on the design of a multi-leaves building envelope, with a self-supporting wall of granite slabs. The study will demonstrate the advantages of its use in compare with the hanging stone veneer in a vented cladding system. Using the Design of the School of Music and Theatre of the Atlantic Area in Spain as a case study where the multi-leaves enclosure system consists in a self-supported outer leaf of large granite slabs of 15cm. of thickness, a vent cavity with thermal isolation, a brick wall, and a series of internal layers. The methodology used were simulations and data collected in building. The advantages of the self-supporting wall of granite slabs in the outer leaf (15cm). compared with a hanging stone veneer in a vented cladding system can summarize the goals as follows: Using the stone in more natural way, by compression. The weight of the stone slabs goes directly to a strip-footing and don't overload the reinforced concrete structure of the building. The weight of the stone slabs provides an external aerial soundproofing, preventing the sound transmission to the structure. The thickness of the stone slabs is enough to provide the external waterproofing of the building envelope. The self-supporting system with minimum anchorages allows having a continuous and external thermal isolation without thermal bridges. The thickness of ashlars masonry provides a thermal inertia that balances the temperatures between day and night in the external thermal insulation layer. The absence of open joints gives the quality of a continuous envelope transmitting the sensations of the stone, the heaviness in the facade, the rhythm of the music and the sequence of the theatre. The main cost of stone due his bigger thickness is more than compensated with the reduction in assembly costs. Don´t need any substructure systems for hanging stone veneers.

Keywords: self-supporting wall, stone cladding systems, hanging veneer cladding systems, sustainability of facade systems

Procedia PDF Downloads 62

Authors: D. M. Cocârță, I. A. Istrate, C. Streche, D. M. Dumitru

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Soil contamination phenomena are a wide world issue that has received the important attention in the last decades. The main pollutants that have affected soils are especially those resulted from the oil extraction, transport and processing. This paper presents results obtained in the framework of a research project focused on the management of contaminated sites with petroleum products/ REMPET. One of the specific objectives of the REMPET project was to assess the electrochemical treatment (improved with polarity change respect to the typical approach) as a treatment option for the remediation of total petroleum hydrocarbons (TPHs) from contaminated soils. Petroleum hydrocarbon compounds attach to soil components and are difficult to remove and degrade. Electrochemical treatment is a physicochemical treatment that has gained acceptance as an alternative method, for the remediation of organic contaminated soils comparing with the traditional methods as bioremediation and chemical oxidation. This type of treatment need short time and have high removal efficiency, being usually applied in heterogeneous soils with low permeability. During the experimental tests, the following parameters were monitored: pH, redox potential, humidity, current intensity, energy consumption. The electrochemical method was applied in an experimental setup with the next dimensions: 450 mm x 150 mm x 150 mm (L x l x h). The setup length was devised in three electrochemical cells that were connected at two power supplies. The power supplies configuration was provided in such manner that each cell has a cathode and an anode without overlapping. The initial value of TPH concentration in soil was of 1420.28 mg/kg_dw. The remediation method has been applied for only 21 days, when it was already noticed an average removal efficiency of 31 %, with better results in the anode area respect to the cathode one (33% respect to 27%). The energy consumption registered after the development of the experiment was 10.6 kWh for exterior power supply and 16.1 kWh for the interior one. Taking into account that at national level, the most used methods for soil remediation are bioremediation (which needs too much time to be implemented and depends on many factors) and thermal desorption (which involves high costs in order to be implemented), the study of electrochemical treatment will give an alternative to these two methods (and their limitations).

Keywords: electrochemical remediation, pollution, total petroleum hydrocarbons, soil contamination

Procedia PDF Downloads 240

Authors: Peter Kutis, Vladimir Littva

Abstract:

Nowadays, it is necessary to ensure that this reduction in costs is not at the expense of the quality of health care and future medical success. In general, physiotherapy for total hip joint arthroplasty is considered to be a routine matter that deals mainly with mobility training, increased muscular strength, and basic day-to-day activities such as bed-to-chair transition, standing, and walking. Within the KEGA project no. 003KU-4-2021, we decided to investigate preoperative physiotherapy care in Slovakia and Austria in total hip arthroplasty patients to shortened overall recovery. Research Sample and Methods: The sample comprised 498 respondents –patients who were indicated to total hip arthroplasty on the territory of Slovakia and Austria. There were 130 women in Slovakia and 135 women in Austria. The numbers of men were 120 in Slovakia and 113 men in Austria. The age of respondents was between 40 and 85 years of age. As a method of our research, we chose a non-standardized questionnaire, which consisted of three parts. The first part for the initial examination of the patient contained the identification of the patient according to the assigned number and subsequently 19 questions conditioned by the physical examination and evaluation of the patients. The second part of our questionnaire was completed after the patient's hospitalization and contained 10 questions that were conditioned by the patient's examination. The last third part for the overall assessment of the patient's state of health consisted of 12 questions conditioned by the patient's examination. This part was performed at the last meeting with the patient at the end of the treatment. All data were statistically processed by SPSS 25. Results: All data were evaluated at a significance level of p = 0.05. From the comparison of patients who underwent preoperative preparation, we can clearly state that the total duration of treatment is significantly shorter. A t-test of two mean values with uneven variance was used to verify the validity of the assumption. The total duration of treatment in patients with preoperative preparation was on average 92,635 days and without preoperative preparation was on average 135,884 days (t-Stat = 44,52784, t Critical one-tail = 1,648187415, t Critical two-tail = 1,965157). Conclusion: The results obtained during the research show the importance of adequate preoperative physiotherapeutic preparation of the patient. The results of total hip joint arthroplasty studies showed a significant reduction in a hospital stay as well as shortened total treatment time.

Keywords: THA, physiotherapy, recovery, preoperative physiotherapy care

Procedia PDF Downloads 178

Authors: Natalia M. Acevedo, Luis M. Jimenez, Erick Lambis

Abstract:

Imperfections in the capital market are used to argue the relevance of the corporate risk management function. With corporate hedge, the value of the company is increased by reducing the volatility of the expected cash flow and making it possible to face a lower bankruptcy costs and financial difficulties, without sacrificing tax advantages for debt financing. With the propose to avoid exchange rate troubles over cash flows of Colombian exporting firms, this dissertation uses financial options, over exchange rate between Peso and Dollar, for realizing a financial hedge. In this study, a strategy of hedge is designed for an exporting company in Colombia with the objective of preventing fluctuations because, if the exchange rate down, the number of Colombian pesos that obtains the company by exports, is less than agreed. The exchange rate of Colombia is measured by the TRM (Representative Market Rate), representing the number of Colombian pesos for an American dollar. First, the TMR is modelled through the Geometric Brownian Motion, with this, the project price is simulated using Montecarlo simulations and finding the mean of TRM for three, six and twelve months. For financial hedging, currency options were used. The 6-month projection was covered with financial options on European-type currency with a strike price of $ 2,780.47 for each month; this value corresponds to the last value of the historical TRM. In the compensation of the options in each month, the price paid for the premium, calculated with the Black-Scholes method for currency options, was considered. Finally, with the modeling of prices and the Monte Carlo simulation, the effect of the exchange hedging with options on the exporting company was determined, this by means of the unit price estimate to which the dollars in the scenario without coverage were changed and scenario with coverage. After using the scenarios: is determinate that the TRM will have a bull trend and the exporting firm will be affected positively because they will get more pesos for each dollar. The results show that the financial options manage to reduce the exchange risk. The expected value with coverage is approximate to the expected value without coverage, but the 5% percentile with coverage is greater than without coverage. The foregoing indicates that in the worst scenarios the exporting companies will obtain better prices for the sale of the currencies if they cover.

Keywords: currency hedging, futures, geometric Brownian motion, options

Procedia PDF Downloads 130

Authors: John D. Sanderson

Abstract:

The popularity of American cinema worldwide has contributed to the development of sociolects related to specific film genres in other cultural contexts by means of screen translation, in many cases eluding norms of usage in the target language, a process whose result has come to be known as 'dubbese'. A consequence for the reception in countries where local audiovisual fiction consumption is far lower than American imported productions is that this linguistic construct is preferred, even though it differs from common everyday speech. The iconography of film genres such as science-fiction, western or sword-and-sandal films, for instance, generates linguistic expectations in international audiences who will accept more easily the sociolects assimilated by the continuous reception of American productions, even if the themes, locations, characters, etc., portrayed on screen may belong in origin to other cultures. And the non-normative language (e.g., calques, semantic loans) used in the preferred mode of linguistic transfer, whether it is translation for dubbing or subtitling, has diachronically evolved in many cases into a status of canonized sociolect, not only accepted but also required, by foreign audiences of American films. However, a remarkable step forward is taken when this typology of artificial linguistic constructs starts being used creatively by nationals of these target cultural contexts. In the case of Spain, the success of American sitcoms such as Friends in the 1990s led Spanish television scriptwriters to include in national productions lexical and syntactical indirect borrowings (Anglicisms not formally identifiable as such because they include elements from their own language) in order to target audiences of the former. However, this commercial strategy had already taken place decades earlier when Spain became a favored location for the shooting of foreign films in the early 1960s. The international popularity of the then newly developed sub-genre known as Spaghetti-Western encouraged Spanish investors to produce their own movies, and local scriptwriters made use of the dubbese developed nationally since the advent of sound in film instead of using normative language. As a result, direct Anglicisms, as well as lexical and syntactical borrowings made up the creative writing of these Spanish productions, which also became commercially successful. Interestingly enough, some of these films were even marketed in English-speaking countries as original westerns (some of the names of actors and directors were anglified to that purpose) dubbed into English. The analysis of these 'back translations' will also foreground some semantic distortions that arose in the process. In order to perform the research on these issues, a wide corpus of American films has been used, which chronologically range from Stagecoach (John Ford, 1939) to Django Unchained (Quentin Tarantino, 2012), together with a shorter corpus of Spanish films produced during the golden age of Spaghetti Westerns, from una tumba para el sheriff (Mario Caiano; in English lone and angry man, William Hawkins) to tu fosa será la exacta, amigo (Juan Bosch, 1972; in English my horse, my gun, your widow, John Wood). The methodology of analysis and the conclusions reached could be applied to other genres and other cultural contexts.

Keywords: dubbing, film genre, screen translation, sociolect

Procedia PDF Downloads 170

Authors: M. Ali Mandegari, S. Farzad, J. F. Görgens

Abstract:

Sugar is one of the main agricultural industries in South Africa and approximately livelihoods of one million South Africans are indirectly dependent on sugar industry which is economically struggling with some problems and should re-invent in order to ensure a long-term sustainability. Second generation bio-refinery is defined as a process to use waste fibrous for the production of bio-fuel, chemicals animal food, and electricity. Bio-ethanol is by far the most widely used bio-fuel for transportation worldwide and many challenges in front of bio-ethanol production were solved. Bio-refinery annexed to the existing sugar mill for production of bio-ethanol and electricity is proposed to sugar industry and is addressed in this study. Since flow-sheet development is the key element of the bio-ethanol process, in this work, a bio-refinery (bio-ethanol and electricity production) annexed to a typical South African sugar mill considering 65ton/h dry sugarcane bagasse and tops/trash as feedstock was simulated. Aspen PlusTM V8.6 was applied as simulator and realistic simulation development approach was followed to reflect the practical behavior of the plant. Latest results of other researches considering pretreatment, hydrolysis, fermentation, enzyme production, bio-ethanol production and other supplementary units such as evaporation, water treatment, boiler, and steam/electricity generation units were adopted to establish a comprehensive bio-refinery simulation. Steam explosion with SO2 was selected for pretreatment due to minimum inhibitor production and simultaneous saccharification and fermentation (SSF) configuration was adopted for enzymatic hydrolysis and fermentation of cellulose and hydrolyze. Bio-ethanol purification was simulated by two distillation columns with side stream and fuel grade bio-ethanol (99.5%) was achieved using molecular sieve in order to minimize the capital and operating costs. Also boiler and steam/power generation were completed using industrial design data. Results indicates 256.6 kg bio ethanol per ton of feedstock and 31 MW surplus power were attained from bio-refinery while the process consumes 3.5, 3.38, and 0.164 (GJ/ton per ton of feedstock) hot utility, cold utility and electricity respectively. Developed simulation is a threshold of variety analyses and developments for further studies.

Keywords: bio-refinery, bagasse, tops, trash, bio-ethanol, electricity

Procedia PDF Downloads 532

Authors: Chang Yu Chuan

Abstract:

Background and Aim: Pressure sore is not only the consequence of any gradual damage of the skin leading to tissue defects but also an important indicator of clinical care. If hospitalized patients develop pressure sores without proper care, it would result in delayed healing, wound infection, increase patient physical pain, prolonged hospital stay and even death, which would have a negative impact on the quality of care and also increase nursing manpower and medical costs. This project is aimed at decreasing the incidence of pressure sore in one ward of internal medicine. Our data showed 53 cases (0.61%) of pressure sore in 2015, which exceeded the average (0.5%) of Taiwan Clinical Performance Indicator (TCPI) for medical centers. The purpose of this project is to reduce the incidence rate of pressure sore in the ward. After data collection and analysis from January to December 2016, the reasons of developing pressure sore were found: 1. Lack of knowledge to prevent pressure among nursing staffs; 2. No relevant courses about preventing pressure ulcers and pressure wound care being held in this unit; 3. Low complete rate of pressure sore care education that family members should receive from nursing staffs; 4. Decompression equipment is not enough; 5. Lack of standard procedures for body-turning and positioning care. After team members brainstorming, several strategies were proposed, including holding in-service education, pressure sore care seed training, purchasing decompression mattress and memory pillows, designing more elements of health education tools, such as health education pamphlet, posters and multimedia films of body-turning and positioning demonstration, formulation and promotion of standard operating procedures. In this way, nursing staffs can understand the body-turning and positioning guidelines for pressure sore prevention and enhance the quality of care. After the implementation of this project, the pressure sore density significantly decreased from 0.61%(53 cases) to 0.45%(28 cases) in this ward. The project shows good results and good example for nurses working at the ward and helps to enhance quality of care.

Keywords: body-turning and positioning, incidence density, nursing, pressure sore

Procedia PDF Downloads 267

Authors: Knol Hester, Müller Swantje, Danchenko Natalya

Abstract:

Objective: Falls in older people cause an autonomy loss and result in an economic burden. LCare is an AI-based application to manage fall risks. The study's aim was to assess the effect of LCare use on patient outcomes in nursing homes in Germany. Methods: LCare identifies and monitors fall risks through a 3D-gait analysis and a digital questionnaire, resulting in tailored recommendations on fall prevention. A study was conducted with AOK Baden-Württemberg (01.09.2019- 31.05.2021) in 16 care facilities. Assessments at baseline and follow-up included: a fall risk score; falls (baseline: fall history in the past 12 months; follow-up: a fall record since the last analysis); fall-related injuries and hospitalizations; gait speed; fear of falling; psychological stress; nurses experience on app use. Results: 94 seniors were aged 65-99 years at the initial analysis (average 84±7 years); 566 mobility analyses were carried out in total. On average, the fall risk was reduced by 17.8 % as compared to the baseline (p<0.05). The risk of falling decreased across all subgroups, including a trend in dementia patients (p=0.06), constituting 43% of analyzed patients, and patients with walking aids (p<0.05), constituting 76% of analyzed patients. There was a trend (p<0.1) towards fewer falls and fall-related injuries and hospitalizations (baseline: 23 seniors who fell, 13 injury consequences, 9 hospitalizations; follow-up: 14 seniors who fell, 2 injury consequences, 0 hospitalizations). There was a 16% improvement in gait speed (p<0.05). Residents reported less fear of falling and psychological stress by 38% in both outcomes (p<0.05). 81% of nurses found LCare effective. Conclusions: In the presented study, the use of LCare app was associated with a reduction of fall risk among nursing home residents, improvement of health-related outcomes, and a trend toward reduction in injuries and hospitalizations. LCare may help to improve senior resident care and save healthcare costs.

Keywords: falls, digital healthcare, falls prevention, nursing homes, seniors, AI, digital assessment

Procedia PDF Downloads 131