Search results for: clinical survey data simulation

Authors: Mirzashahi Babak, Mansouri Pejman, Najafi Arvin, Farzan Mahmoud

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Introduction: There are several surgical treatment choices for cervical spondylotic myelopathy (CSM). The aim of this study is to evaluate clinical outcomes and surgical complications in patients with cervical disk degeneration (CDD) undergoing either anterior cervical discectomy with or without fusion or cervical laminectomy and fusion. Methods: This prospective case series study included 45 consecutive patients with cervical spondylotic myelopathy between January 2010 and November 2014. There were 28 males and 17 females, with a mean age of 47 (range 37-68) years. The mean clinical follow-up was 14 months (range 3-24 months). The Neck Disability Index (NDI), visual analog scale (VAS) neck and arm pain, Short Form-36 (SF-36) were used as the functional outcome measurements. All of the complications in our patients were recorded. Results: In our study group, 26 patients underwent only one or two level anterior cervical discectomy. Ten patients underwent anterior cervical discectomy and fusion (ACDF) and nine cases underwent posterior laminectomy and fusion. We have found a statistically significant improvement between mean preoperative (29, range 19-43) and postoperative (7, range 0-12) NDI scores following surgery (P < 0.05). Also, there was a statistically significant difference between pre and post-operative VAS and SF-36 score (p < 0.05). There was a 7% overall complication rate (n = 3). The only complication in our patients was surgical site cellulitis which has been managed with oral antibiotic therapy. Conclusion: Both anterior cervical discectomy with or without fusion or posterior laminectomy and fusion are safe and efficacious treatment options for the management of CSM. The clinical outcomes seem to be fairly reproducible.

Keywords: cervical, myelopathy, discectomy, fusion, laminectomy

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Authors: Sun Hyoung Park

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A total of 151 children admitted to a secondary hospital in Gyeongnam, South Korea, with respiratory infection caused by M. pneumoniae from January to November 2024 participated in this study. Of the 151 patients, 52% were boys, and the median age was 13.2 years (interquartile range: 7.8 – 15.6 years). The average duration of fever before hospitalization was 4.7 days ((interquartile range: 3.5 - 6.4 days). M. pneumoniae infection was confirmed through ELISA with a more than 4-fold increase in M. pneumoniae antibody values compared to the 5-day interval. Antibiotic resistance was measured by whether clinical improvement occurred after taking macrolide (roxithromycin) for 3 days. Of the 39 patients showing antibiotic resistance, 37 patients were administered doxycycline for 14 days, and 2 patients developed vomiting and rashes after taking doxycycline, so the medication was changed to levofloxacin. The antibiotic-resistance group presented significantly longer febrile days compared to the no-resistance group (P = 0.006). The number of febrile days after macrolide treatment was also longer in antibiotic antibiotic-resistance group than in no resistance group (P = 0.058). Patients who received doxycycline early, within 3 days, improved faster than those who received it later (P=0.008). This study aims to analyze the clinical characteristics and antibiotic resistance of Mycoplasma pneumoniae pneumonia (MP) patients in Gyeongnam, Korea, providing valuable information for the management of patients with MP. Macrolide antibiotic resistance is gradually increasing, and it was found that switching to doxycycline or levofloxacin within 3 days of taking macrolide was helpful for clinical improvement.

Keywords: mycoplasma pneumoniae, macrolide, antibiotic resistance, macrolide resistance

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Authors: Teja Joshi

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Laterality has shown to play a role in performance as well as injuries especially in unilateral sports disciplines. Uniquely, Artistic Gymnastics involves combination of unilateral, bilateral and complex multi-planer elements as well as gymnastics specific rotational preference. Therefore, this study was conducted to explore if any such preferences are associated with number of injuries in artistic gymnasts. To explore the association between lateral preferences, rotational preferences and injuries incidence in artistic gymnastics. Artistic gymnasts above 16 years of age, were invited to participate in an online survey. The survey included consent, lateral preference inventory, injury data collection according to anatomical locations and rotational preference for selected gymnastics elements performed on the floor exercise. SPSS version 24 was used to analyse Non-parametric data using Kruskal-Wallis (K- independent test) test. Multiple regression was performed to identify the predictor for injuries and their side in gymnasts. Total number of injuries per gymnast was associated with handedness (p value-0.049) and no significant association was noted for footdness (p value-0.207), eyedness (p value-0.491) and eardness (p value-0.798). Additionally, rotational preferences did not influence number of injuries (p value-0.521). In multiple regression, eyedness was identified as a predicting factor to determine the number of injuries. Rotational preferences were neither determined as a national strategy nor a product of lateral preference. Dominant hand had higher number of injuries in artistic gymnasts. Rotational preference is independent of laterality, number of injuries and nationality.

Keywords: sports injury, rotational preference, gymnastics, handedness

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Authors: Shiyun Liu

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Radiant heating systems work fundamentally differently from air systems by taking advantage of both radiant and convective heat transfer to remove space heating load. There are rare studies on differences of heating systems between all-air system and radiant floor system. This paper uses the method of simulation based on state-space to calculate the indoor temperature and wall temperature of each system and shows how the dynamic heat transfer in rooms conditioned by a radiant system is different from an air system. Then this paper analyses the changes of indoor temperature of these two systems, finding out the differences between all-air heating system and radiant floor heating system to help the designer choose a more suitable heating system.

Keywords: radiant floor, all-air system, thermal comfort, simulation, heating system

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Authors: Samia Rabet, Rachida Chemini, Gerhard Schäfer, Farid Aiouache

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The textile industry generates large quantities of wastewater, which poses significant environmental problems due to its complex composition and high levels of pollutants loaded principally with heavy metals, large amounts of COD, and dye. Separation treatment methods are often known for their effectiveness in removing contaminants whereas membrane separation techniques are a promising process for the treatment of textile effluent due to their versatility, efficiency, and low energy requirements. This study focuses on the modeling and simulation of membrane separation technologies with a cross-flow filtration process for textile effluent treatment. It aims to explore the application of mathematical models and computational simulations using ASPEN Plus Software in the prediction of a complex and real effluent separation. The results demonstrate the effectiveness of modeling and simulation techniques in predicting pollutant removal efficiencies with a global deviation percentage of 1.83% between experimental and simulated results; membrane fouling behavior, and overall process performance (hydraulic resistance, membrane porosity) were also estimated and indicating that the membrane losses 10% of its efficiency after 40 min of working.

Keywords: membrane separation, ultrafiltration, textile effluent, modeling, simulation

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Authors: Ajai Singh

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Simulation of hydrological processes at the watershed outlet through modelling approach is essential for proper planning and implementation of appropriate soil conservation measures in Damodar Barakar catchment, Hazaribagh, India where soil erosion is a dominant problem. This study quantifies the parametric uncertainty involved in simulation of stream flow using Soil and Water Assessment Tool (SWAT), a watershed scale model and Radial Basis Neural Network (RBNN), an artificial neural network model. Both the models were calibrated and validated based on measured stream flow and quantification of the uncertainty in SWAT model output was assessed using ‘‘Sequential Uncertainty Fitting Algorithm’’ (SUFI-2). Though both the model predicted satisfactorily, but RBNN model performed better than SWAT with R2 and NSE values of 0.92 and 0.92 during training, and 0.71 and 0.70 during validation period, respectively. Comparison of the results of the two models also indicates a wider prediction interval for the results of the SWAT model. The values of P-factor related to each model shows that the percentage of observed stream flow values bracketed by the 95PPU in the RBNN model as 91% is higher than the P-factor in SWAT as 87%. In other words the RBNN model estimates the stream flow values more accurately and with less uncertainty. It could be stated that RBNN model based on simple input could be used for estimation of monthly stream flow, missing data, and testing the accuracy and performance of other models.

Keywords: SWAT, RBNN, SUFI 2, bootstrap technique, stream flow, simulation

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Authors: Asaf Toker

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Matricelf developed a technology that enables the production of autologous engineered tissue composed of matrix and cells derived from patients Omentum biopsy. The platform showed remarkable pre-clinical results for several medical conditions. The company recently licensed the technology that enabled scientist at Tel Aviv university that 3D printed a human heart from human cells and matrix for the first time in human history. The company plans to conduct its first human clinical trial for Acute Spinal Cord Injury (SCI) early in 2023.

Keywords: tissue engineering, regenerative medicine, spinal Cord Injury, autologous implants, iPSC

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Authors: Alyaa Farouk Abdelfattah Ibrahim, Samah Mohamed, Huda Jrady, Mashail Alrashidi, Alaa Mohammad, Fatimah Alotaibi, Maram Almutiri

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Participation in volunteering was associated with better mental and physical health, self-esteem, and life satisfaction. The main motivator for students in particular is the chance to gain work-related experiences, improve skills, and build on qualifications that may help them achieve their educational goals and further their careers. This study aimed to assess the effect of summer training volunteering practices in healthcare on self-confidence of nursing students in Riyadh. In a crossectional study design, 150 nursing students at King Saud bin Abdul-Aziz University for health sciences in Riyadh were included in the study. Bio-socio-demographic, self-confidence, patients’ care and skills questionnaires were used for data collection. Results: Participants’ age ranged between 20 and 26 years. The majority were from the educational level seven (80%). 40.7 % of them reported volunteering in summer training programs; 70.37% of them volunteered at least once and for a duration of at least one month. Nursing students from level 6 were less likely to have self-confidence in their patients’ care skills than those in level 7. Students who volunteered were more likely to be more interested in becoming social, professional, and independent healthcare workers. There was no difference regarding experience in clinical skills and education by volunteering status. Clinical skills improved by a level of education in this group. Conclusion: Professional self-confidence and clinical performance are related in this group of nursing students. Monitoring, arranging, and encouraging volunteering activities for nursing students are important to help them broaden their interests, their self-confidence in their capabilities, and advancement in their chosen profession. Mostly, volunteering enhanced knowledge in patient safety and quality of care and attempts to secure volunteering opportunities should be a priority on the nursing education agenda.

Keywords: volunteering, health care volunteering, nursing students, summer training

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

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

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

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Authors: Jinyan Li, Simon Fong, Raymond Wong, Mohammed Sabah, Fiaidhi Jinan

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Clinical data analysis and forecasting have make great contributions to disease control, prevention and detection. However, such data usually suffer from highly unbalanced samples in class distributions. In this paper, we target at the binary imbalanced dataset, where the positive samples take up only the minority. We investigate two different meta-heuristic algorithms, particle swarm optimization and bat-inspired algorithm, and combine both of them with the synthetic minority over-sampling technique (SMOTE) for processing the datasets. One approach is to process the full dataset as a whole. The other is to split up the dataset and adaptively process it one segment at a time. The experimental results reveal that while the performance improvements obtained by the former methods are not scalable to larger data scales, the later one, which we call Adaptive Swarm Balancing Algorithms, leads to significant efficiency and effectiveness improvements on large datasets. We also find it more consistent with the practice of the typical large imbalanced medical datasets. We further use the meta-heuristic algorithms to optimize two key parameters of SMOTE. Leading to more credible performances of the classifier, and shortening the running time compared with the brute-force method.

Keywords: Imbalanced dataset, meta-heuristic algorithm, SMOTE, big data

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Authors: Grace Omowunmi Soyebi

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A computerized medical record system is a collection of medical information about a person that is stored on a computer. One principal problem of most hospitals in rural areas is using the file management system for keeping records. A lot of time is wasted when a patient visits the hospital, probably in an emergency, and the nurse or attendant has to search through voluminous files before the patient's file can be retrieved; this may cause an unexpected to happen to the patient. This data mining application is to be designed using a structured system analysis and design method which will help in a well-articulated analysis of the existing file management system, feasibility study, and proper documentation of the design and implementation of a computerized medical record system. This computerized system will replace the file management system and help to quickly retrieve a patient's record with increased data security, access clinical records for decision-making, and reduce the time range at which a patient gets attended to.

Keywords: programming, data, software development, innovation

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Authors: Faisal Kalota

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Big Data and analytics have gained a huge momentum in recent years. Big Data feeds into the field of Learning Analytics (LA) that may allow academic institutions to better understand the learners’ needs and proactively address them. Hence, it is important to have an understanding of Big Data and its applications. The purpose of this descriptive paper is to provide an overview of Big Data, the technologies used in Big Data, and some of the applications of Big Data in education. Additionally, it discusses some of the concerns related to Big Data and current research trends. While Big Data can provide big benefits, it is important that institutions understand their own needs, infrastructure, resources, and limitation before jumping on the Big Data bandwagon.

Keywords: big data, learning analytics, analytics, big data in education, Hadoop

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Authors: Constantin Ott, Dietmar Drummer

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The direct encapsulation of electronic components is an effective way of protecting components against external influences. In addition to achieving a sufficient protective effect, there are two other big challenges for satisfying the increasing demand for encapsulated circuit boards. The encapsulation process should be both suitable for mass production and offer a low component load. Injection molding is a method with good suitability for large series production but also with typically high component stress. In this article, two aims were pursued: first, the development of a calculation model that allows an estimation of the occurring forces based on process variables and material parameters. Second, the evaluation of a new approach for stress reduction by means of thermoplastic foam injection molding. For this purpose, simulation-based process data was generated with the Moldflow simulation tool. Based on this, component stresses were calculated with the calculation model. At the same time, this paper provided a model for estimating the forces occurring during overmolding and derived a solution method for reducing these forces. The suitability of this approach was clearly demonstrated and a significant reduction in shear forces during overmolding was achieved. It was possible to demonstrate a process development that makes it possible to meet the two main requirements of direct encapsulation in addition to a high protective effect.

Keywords: encapsulation, stress reduction, foam-injection-molding, simulation

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Authors: Tess Hartland, Moitree Banerjee, Sue Churchill, Antonina Pereira, Ian Tyndall, Ruth Lowry

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Background: Sexual health services and policies for middle-aged and older adults are underdeveloped, while global sexually transmitted infections in this age group are on the rise. The Interreg cross-Europe Sexual Health In Over 45s (SHIFT) project aims to increase participation in sexual health services and improve sexual health and wellbeing in people aged over 45, with an additional focus on disadvantaged groups. Methods: A two-pronged mixed-methodology is being used to develop a model for good service provision in sexual health for over 45s. (1) Following PRISMA-ScR guidelines, a scoping review is being conducted, using the databases PsychINFO, Web of Science, ERIC and PubMed. A key search strategy using terms around sexual health, good practice, over 45s and disadvantaged groups. The initial search for literature yielded 7914 results. (2) Surveys (n=1000) based on the Theory of Planned Behaviour are being administered across the UK, Belgium and Netherlands to explore current sexual health knowledge, awareness and attitudes. Expected results: It is expected that sexual health needs and potential gaps in service provision will be identified in order to inform good practice for sexual health services for the target population. Results of the scoping review are being analysed, while focus group and survey data is being gathered. Preliminary analysis of the survey data highlights barriers to access such as limited risk awareness and stigma. All data analysis will be completed by the time of the conference. Discussion: Findings will inform the development of a model to improve sexual health and wellbeing for among over 45s, a population which is often missed in sexual health policy improvement.

Keywords: adult health, disease prevention, health promotion, over 45s, sexual health

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Authors: Eric Lai, Sarah Lorger, David Eisinger, Richard Waugh

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Introduction: Percutaneous embolization of varicoceles has shown similar outcomes to surgery. However, there are advantages of radiological intervention as patients are not exposed to general anaesthesia, experience a quicker recovery and face a lower risk of major complications. Radiological interventions are also preferable after a failed surgical approach. We evaluate clinical outcomes of percutaneous embolization at a tertiary hospital in Sydney, Australia. Methods: Retrospective case series without a control group from a single site (Royal Prince Alfred Hospital, Sydney, Australia). A data search was performed on the interventional radiology database with the word “varicocele” between February 2017 and March 2022. 62 patients were identified. Each patient file was reviewed and included in the study if they met the inclusion criteria. Results: A total of 56 patients were included. 6 patients were excluded as they did not receive intervention after the initial diagnostic venography. Technical success was 100%. Complications were seen in 3 patients (5.3%). The complications included post-procedural pain and fever, venous perforation with no clinical adverse outcome, and a mild allergic reaction to contrast. Recurrence occurred in 3 patients (5.6%), all of whom received a successful second procedure. DISCUSSION: This study demonstrates comparable rates of technical success, complication rate and recurrence to other studies in the literature. When compared to surgical outcomes, the results were also similar. The main limitation is multiple patients lack long-term follow-up beyond 1 year, resulting in potential underestimation of the recurrence rate. Conclusion: Percutaneous embolization of varicocele is a safe alternative to surgical intervention.

Keywords: varicocele, interventional radiology, urology, radiology

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Authors: Umair Ahmed, Muhammad Bin Irfan

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This study focuses on designing and optimization of an alkaline water electrolyser for the production of green hydrogen. The aim is to enhance the durability and efficiency of this technology while simultaneously reducing the cost associated with the production of green hydrogen. The experimental results obtained from the alkaline water electrolyser are compared with simulated results using Aspen Plus software, allowing a comprehensive analysis and evaluation. To achieve the aforementioned goals, several design and operational parameters are investigated. The electrode material, electrolyte concentration, and operating conditions are carefully selected to maximize the efficiency and durability of the electrolyser. Additionally, cost-effective materials and manufacturing techniques are explored to decrease the overall production cost of green hydrogen. The experimental setup includes a carefully designed alkaline water electrolyser, where various performance parameters (such as hydrogen production rate, current density, and voltage) are measured. These experimental results are then compared with simulated data obtained using Aspen Plus software. The simulation model is developed based on fundamental principles and validated against the experimental data. The comparison between experimental and simulated results provides valuable insight into the performance of an alkaline water electrolyser. It helps to identify the areas where improvements can be made, both in terms of design and operation, to enhance the durability and efficiency of the system. Furthermore, the simulation results allow cost analysis providing an estimate of the overall production cost of green hydrogen. This study aims to develop a comprehensive understanding of alkaline water electrolysis technology. The findings of this research can contribute to the development of more efficient and durable electrolyser technology while reducing the cost associated with this technology. Ultimately, these advancements can pave the way for a more sustainable and economically viable hydrogen economy.

Keywords: sustainable development, green energy, green hydrogen, electrolysis technology

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Authors: Efrat Neter, Esther Brainin, Orna Baron-Epel

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Background: Connecting end-users to newly developed ICT technologies and channeling patients to new products requires an assessment of compatibility. End user’s assessment is conveyed in the concept of eHealth literacy. The study examined the association between perceived and performed eHealth literacy (EHL) in a heterogeneous age sample in Israel. Methods: Participants included 100 Israeli adults (mean age 43,SD 13.9) who were first phone interviewed and then tested on a computer simulation of health-related Internet tasks. Performed, perceived and evaluated EHL were assessed. Levels of successful completion of tasks represented EHL performance and evaluated EHL included observed motivation, confidence, and amount of help provided. Results: The skills of accessing, understanding, appraising, applying, and generating new information had a decreasing successful completion rate with increase in complexity of the task. Generating new information, though highly correlated with all other skills, was least correlated with the other skills. Perceived and performed EHL were correlated (r=.40, P=.001), while facets of performance (i.e, digital literacy and EHL) were highly correlated (r=.89, P<.001). Participants low and high in performed EHL were significantly different: low performers were older, had attained less education, used the Internet for less time and perceived themselves as less healthy. They also encountered more difficulties, required more assistance, were less confident in their conduct and exhibited less motivation than high performers. Conclusions: The association in this age-hetrogenous ample was larger than in previous age-homogenous samples. The moderate association between perceived and performed EHL indicates that the two are associated yet distinct, the latter requiring separate assessment. Features of future rapid performed EHL tools are discussed.

Keywords: eHealth, health literacy, performance, simulation

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Authors: Cleto J. Sauer Jr., Rita C. Sauer, Chaider G. Andrade, Dóris F. Rabelo

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Some patients with COVID-19 disease and difficult airway characteristics undergo to endotracheal intubation (ETI) procedure. The tracheal introducer, known as the bougie guide, can aid ETI in patients with difficult airway pattern. Realistic simulation (RS) is a methodology utilized for healthcare professionals training. To improve skills in using the bougie guide of physicians from Recôncavo da Bahia region in Brazil, during COVID-19 outbreak, RS training was carried out. Simulated scenario included the Nasco Lifeform realistic simulator for ETI and a bougie guide introducer. Training was a capacitation program organized by the Health Department of Bahia State. Objective: To report effects in participants´ self-confidence perception for using bougie guide after a RS based training. Methods: Descriptive study, secondary data extracted from questionnaires. Priority workplace and previous knowledge about bougie were reported on a preparticipation formulary. Participants also completed pre- and post-training qualitative self-assessment (10-point Likert scale) regarding to self-confidence in using bougie guide. Distribution analysis for qualitative data was performed with Wilcoxon Signed Rank Test, and self-confidence increase analysis in frequency contingency tables with Fisher's exact test. Results: From May to June 2020 a total of 36 physicians participated of training, 25 (69%) from primary care setting, 32 (89%) with no previous knowledge about the bougie guide utilization. For those who had previous knowledge about bougie pre-training self-confidence median was 6,5, and 2 for participants who had not. In overall there was an increase in self-confidence median for bougie utilization. Median (variation) before and after training was 2.5 (1-7) vs. 8 (4-10) (p <0.0001). Among those who had no previous knowledge about bougie (n = 32) an increase in self-confidence greater than 3 points for bougie utilization was reported by 31 vs. 1 participants (p = 0.71). Conclusions: Most of participants had no previous knowledge about using the bougie guide. RS training contributed to self-confidence increase for using bougie for ETI procedure. RS methodology can contribute for training in using the bougie guide for ETI procedure during COVID-19 outbreak.

Keywords: bougie, confidence, COVID-19, endotracheal intubation, realistic simulation

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Authors: Khalil Aryanfar, Shahrzad Sanjari, Pariya Gholipor, Elmira Hafez

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The present study aimed to investigate and compare the characteristics of entrepreneurship among students in senior secondary schools in the academic year 2008-2009 in Tabriz city. Research employed survey method respectively. The study population consisted of all students in the senior branch of theoretical, technical, professional and vocational (1033 patients) were included. Sample size of 493 was calculated according to Morgan table. Sampling method was random cluster and stratified sampling. Data collected by researcher made questionnaire based on the theory of MC clleland (1963) and Brvkhavs (1980). These tools would indicators be for achievement, Independence, disposition, creativity, risk-taking, self-control, tolerance for ambiguity, team work approach in the future. To determine the psychometric properties of the questionnaire, content validity of the survey was approved by relevant experts. In addition, to estimate the internal consistency of Cronbach's alpha coefficient was calculated for 84% of total inventory. Collected data Using mean, standard deviation and were analyzed by ANOVA. The results showed that there is a significant difference between students' entrepreneurial potential fields of theoretical, technical, professional and vocational level (0/01).

Keywords: entrepreneurship, achievement motivation, risk taking, creativity, self-control, independence, tolerance of ambiguity, foresight

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Authors: Srikanth Pandurangi, Basheer Mohammed, Nezar Al Sayegh

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In order to meet the increasing demand for housing care for Kuwaiti citizens, the government authorities in Kuwait are undertaking a series of projects in the form of new large cities, outside the current urban area. Al Mutlaa City located to the north-west of the Kuwait Metropolitan Area is one such project out of the 15 planned new cities. The city accommodates a wide variety of residential developments, employment opportunities, commercial, recreational, health care and institutional uses. This paper examines the application of comprehensive transportation demand modeling works undertaken in VISUM platform to understand the future intracity and intercity travel distribution patterns in Kuwait. The scope of models developed varied in levels of detail: strategic model update, sub-area models representing future demand of Al Mutlaa City, sub-area models built to estimate the demand in the residential neighborhoods of the city. This paper aims at offering model update framework that facilitates easy integration between sub-area models and strategic national models for unified traffic forecasts. This paper presents the transportation demand modeling results utilized in informing the planning of multi-modal transportation system for Al Mutlaa City. This paper also presents the household survey data collection efforts undertaken using GPS devices (first time in Kuwait) and notebook computer based digital survey forms for interviewing representative sample of citizens and residents. The survey results formed the basis of estimating trip generation rates and trip distribution coefficients used in the strategic base year model calibration and validation process.

Keywords: innovative methods in transportation data collection, integrated public transportation system, traffic forecasts, transportation modeling, travel behavior

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Authors: Mateusz Paszko, Konrad Pietrykowski, Krzysztof Skiba

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Due to low-altitude and relatively low flight speed, today’s combat assets like missile weapons equipped with infrared guidance systems are one of the most important threats to the helicopters performing combat missions. Especially meaningful in helicopter aviation is infrared emission by exhaust gases, regressed to the surroundings. Due to high temperature, exhaust gases are a major factor in detectability of a helicopter performing air combat operations. This study presents the results of simulating the flow of the mixture of exhaust and air in the flow duct of an injective exhaust cooler, adapted to cooperate with the PZL 10W turbine engine. The simulation was performed using a numerical model and the ANSYS Fluent software. Simulation computations were conducted for set flight conditions of the PZL W-3 Falcon helicopter. The conclusions resulting from the conducted numerical computations should allow for optimisation of the flow duct geometry in the cooler, in order to achieve the greatest possible temperature reduction of exhaust exiting into the surroundings. It is expected that the obtained results should be useful for further works related to the development of the final version of exhaust cooler for the PZL W-3 Falcon helicopter.

Keywords: exhaust cooler, helicopter, numerical simulation, stealth

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Authors: Zhichao Song, Swanand Vaidya

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Nowadays, most portable (e.g., smartphones) and wearable (e.g., smartwatches and earphones) consumer hardware are designed to be dustproof following IP5 or IP6 ratings to ensure the product is able to handle potentially dusty outdoor environments. On the other hand, the design guideline is relatively vague for indoor devices (e.g., smart displays and speakers). While it is generally believed that the indoor environment is much less dusty, in certain circumstances, dust ingression is still able to cause functional failures, such as microphone frequency response shift and camera black spot, or cosmetic dissatisfaction, mainly the dust build up in visible pockets and gaps which is hard to clean. In this paper, we developed a simulation methodology to analyze dust settlement and ingression into known ports of a device. A closed system is initialized with dust particles whose sizes follow Weibull distribution based on data collected in a user study, and dust particle movement was approximated as a settlement in stationary fluid, which is governed by Stokes’ law. Following this method, we simulated dust ingression into MEMS microphone through the acoustic port and protective mesh. Various design and environmental parameters are evaluated including mesh pore size, acoustic port depth-to-diameter ratio, mass density of dust material and inclined angle of microphone port. Although the dependencies of dust resistance on these parameters are all monotonic, smaller mesh pore size, larger acoustic depth-to-opening ratio and more inclined microphone placement (towards horizontal direction) are preferred for dust resistance; these preferences may represent certain trade-offs in audio performance and compromise in industrial design. The simulation results suggest the quantitative ranges of these parameters, with more pronounced effects in the improvement of dust resistance. Based on the simulation results, we proposed several design guidelines that intend to achieve an overall balanced design from audio performance, dust resistance, and flexibility in industrial design.

Keywords: dust settlement, numerical simulation, microphone design, Weibull distribution, Stoke's equation

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Authors: Skyler Kim

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An early diagnosis of leukemia has always been a challenge to doctors and hematologists. On a worldwide basis, it was reported that there were approximately 350,000 new cases in 2012, and diagnosing leukemia was time-consuming and inefficient because of an endemic shortage of flow cytometry equipment in current clinical practice. As the number of medical diagnosis tools increased and a large volume of high-quality data was produced, there was an urgent need for more advanced data analysis methods. One of these methods was the AI approach. This approach has become a major trend in recent years, and several research groups have been working on developing these diagnostic models. However, designing and implementing a leukemia diagnostic system in real clinical environments based on a deep learning approach with larger sets remains complex. Leukemia is a major hematological malignancy that results in mortality and morbidity throughout different ages. We decided to select acute lymphocytic leukemia to develop our diagnostic system since acute lymphocytic leukemia is the most common type of leukemia, accounting for 74% of all children diagnosed with leukemia. The results from this development work can be applied to all other types of leukemia. To develop our model, the Kaggle dataset was used, which consists of 15135 total images, 8491 of these are images of abnormal cells, and 5398 images are normal. In this paper, we design and implement a leukemia diagnostic system in a real clinical environment based on deep learning approaches with larger sets. The proposed diagnostic system has the function of detecting and classifying leukemia. Different from other AI approaches, we explore hybrid architectures to improve the current performance. First, we developed two independent convolutional neural network models: VGG19 and ResNet50. Then, using both VGG19 and ResNet50, we developed a hybrid deep learning architecture employing transfer learning techniques to extract features from each input image. In our approach, fusing the features from specific abstraction layers can be deemed as auxiliary features and lead to further improvement of the classification accuracy. In this approach, features extracted from the lower levels are combined into higher dimension feature maps to help improve the discriminative capability of intermediate features and also overcome the problem of network gradient vanishing or exploding. By comparing VGG19 and ResNet50 and the proposed hybrid model, we concluded that the hybrid model had a significant advantage in accuracy. The detailed results of each model’s performance and their pros and cons will be presented in the conference.

Keywords: acute lymphoblastic leukemia, hybrid model, leukemia diagnostic system, machine learning

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Authors: Sadman Durlov, Aditya Ganesh-Ram, Hamidreza Hekmatjou, Md Najmus Salehin, Nora Shayesteh Ameri

Abstract:

In the field of additive manufacturing, tungsten stands out for its exceptional resistance to high temperatures, making it an ideal candidate for use in extreme conditions. However, its inherent brittleness and vulnerability to thermal cracking pose significant challenges to its manufacturability. This study explores the microstructural evolution of tungsten processed through layer-wise rolling in laser powder bed fusion additive manufacturing, utilizing a comprehensive approach that combines advanced simulation techniques with empirical research. We aim to uncover the complex processes of plastic deformation and microstructural transformations, with a particular focus on the dynamics of grain size, boundary evolution, and phase distribution. Our methodology employs a combination of simulation and experimental data, allowing for a detailed comparison that elucidates the key mechanisms influencing microstructural alterations during the rolling process. This approach facilitates a deeper understanding of the material's behavior under additive manufacturing conditions, specifically in terms of deformation and recrystallization. The insights derived from this research not only deepen our theoretical knowledge but also provide actionable strategies for refining manufacturing parameters to improve the tungsten components' mechanical properties and functional performance. By integrating simulation with practical experimentation, this study significantly enhances the field of materials science, offering a robust framework for the development of durable materials suited for challenging operational environments. Our findings pave the way for optimizing additive manufacturing techniques and expanding the use of tungsten across various demanding sectors.

Keywords: additive manufacturing, layer wise rolling, refractory materials, in-situ microstructure modifications

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Authors: Shirin Ghatrehsamani

Abstract:

Higher efficiency and lower environmental impact are the consequence of using advanced technology in farming. They also help to decrease yield variability by diminishing weather variability impact, optimizing nutrient and pest management as well as reducing competition from weeds. A better understanding of the pros and cons of applying technology and finding the main reason for preventing the utilization of the technology has a significant impact on developing technology adoption among farmers and producers in the digital agriculture era. The results from two surveys carried out in 2019 and 2021 were used to investigate whether the crop types had an impact on the willingness to utilize technology on the farms. The main focus of the questionnaire was on utilizing precision agriculture (PA) technologies among farmers in some parts of the united states. Collected data was analyzed to determine the practical application of various technologies. The survey results showed more similarities in the main reason not to use PA between the two crop types, but the present application of using technology in specialty crops is generally five times larger than in row crops. GPS receiver applications were reported similar for both types of crops. Lack of knowledge and high cost of data handling were cited as the main problems. The most significant difference was among using variable rate technology, which was 43% for specialty crops while was reported 0% for row crops. Pest scouting and mapping were commonly used for specialty crops, while they were rarely applied for row crops. Survey respondents found yield mapping, soil sampling map, and irrigation scheduling were more valuable for specialty crops than row crops in management decisions. About 50% of the respondents would like to share the PA data in both types of crops. Almost 50 % of respondents got their PA information from retailers in both categories, and as the second source, using extension agents were more common in specialty crops than row crops.

Keywords: precision agriculture, smart farming, digital agriculture, technology adoption

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Authors: Adilah Abdul Ghapor, Yong Zulina Zubairi, Rahmatullah Imon

Abstract:

Missing value problem is common in statistics and has been of interest for years. This article considers two modern techniques in handling missing data for linear functional relationship model (LFRM) namely the Expectation-Maximization (EM) algorithm and Expectation-Maximization with Bootstrapping (EMB) algorithm using three performance indicators; namely the mean absolute error (MAE), root mean square error (RMSE) and estimated biased (EB). In this study, we applied the methods of imputing missing values in the LFRM. Results of the simulation study suggest that EMB algorithm performs much better than EM algorithm in both models. We also illustrate the applicability of the approach in a real data set.

Keywords: expectation-maximization, expectation-maximization with bootstrapping, linear functional relationship model, performance indicators

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Authors: Ubaka Chukwuemeka Michael, Ukwe Chinwe Victoria

Abstract:

Background: The use of antipsychotic monotherapy remains the standard for schizophrenic disorders so also a prescription switch from older typical to newer atypical classes of antipsychotics on the basis of better efficacy and tolerability. However, surveys on the quality of antipsychotic drug use and substitution in developing countries are very scarce. This study was intended to evaluate quality and factors that drive the prescription and substitution of antipsychotic drugs among schizophrenic patients visiting a regional psychiatric hospital. Methods: Case files of patients visiting a federal government funded Neuropsychiatric Hospital between July 2012 and July 2014 were systematically retrieved. Patient demographic characteristics, clinical details and drug management data were collected and subjected to descriptive and inferential data analysis to determine quality and predictors of utilization. Results: Of the 600 case files used, there were more male patients (55.3%) with an overall mean age of 33.7±14.4 years. Typical antipsychotic agents accounted for over 85% of prescriptions, with majority of the patients receiving more than 2 drugs in at least a visit (80.9%). Fluphenazine (25.2%) and Haloperidol (18.8%) were mostly given as antipsychotics for treatment initiation while Olazenpine (23.0%) and Benzhexol (18.3%) were the most currently prescribed antipsychotics. Nearly half (42%, 252/600) of these patients were switched from one class to another, with 34.5% (207/600) of them switched from typical to atypical drug classes. No demographic or clinical factors influenced drug substitutions but a younger age and being married influenced being prescribed a polypharmacy regimen (more than 2 drugs) and an injectable antipsychotic agent. Conclusion: The prevalence of antipsychotic polypharmacy and use of typical agents among these patients was high. However, only age and marital status affected the quality of antipsychotic prescriptions among these patients.

Keywords: antipsychotics, drug substitution, pharmacoepidemiology, polypharmacy

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Authors: Sophia Shi

Abstract:

Acute kidney injury (AKI) is the sudden onset of kidney damage in which the kidneys cannot filter waste from the blood, requiring emergency hospitalization. AKI patient mortality rate is high in the ICU and is virtually impossible for doctors to predict because it is so unexpected. Currently, there is no hybrid model predicting AKI that takes advantage of two types of data. De-identified patient data from the MIMIC-III database and de-identified kidney images and corresponding patient records from the Beijing Hospital of the Ministry of Health were collected. Using data features including serum creatinine among others, two numeric models using MIMIC and Beijing Hospital data were built, and with the hospital ultrasounds, an image-only model was built. Convolutional neural networks (CNN) were used, VGG and Resnet for numeric data and Resnet for image data, and they were combined into a hybrid model by concatenating feature maps of both types of models to create a new input. This input enters another CNN block and then two fully connected layers, ending in a binary output after running through Softmax and additional code. The hybrid model successfully predicted AKI and the highest AUROC of the model was 0.953, achieving an accuracy of 90% and F1-score of 0.91. This model can be implemented into urgent clinical settings such as the ICU and aid doctors by assessing the risk of AKI shortly after the patient’s admission to the ICU, so that doctors can take preventative measures and diminish mortality risks and severe kidney damage.

Keywords: Acute kidney injury, Convolutional neural network, Hybrid deep learning, Patient record data, ResNet, Ultrasound kidney images, VGG

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Authors: Sai Hung Cheung, Zhe Shao

Abstract:

It is of our great interest to quantify the risk to structural dynamic systems due to earthquake-induced tsunamis in view of recent earthquake-induced tsunamis in Padang, 2004 and Tohoku, 2011 which brought huge losses of lives and properties. Despite continuous advancement in computational simulation of the tsunami and wave-structure interaction modeling, it still remains computationally challenging to evaluate the reliability of a structural dynamic system when uncertainties related to the system and its modeling are taken into account. The failure of the structure in a tsunami-wave-structural system is defined as any response quantities of the system exceeding specified thresholds during the time when the structure is subjected to dynamic wave impact due to earthquake-induced tsunamis. In this paper, an approach based on a novel integration of a recently proposed moving least squares response surface approach for stochastic sampling and the Subset Simulation algorithm is proposed. The effectiveness of the proposed approach is discussed by comparing its results with those obtained from the Subset Simulation algorithm without using the response surface approach.

Keywords: response surface, stochastic simulation, structural reliability tsunami, risk

Procedia PDF Downloads 681

Authors: Bo Yan, Amy Y. M. Chow

Abstract:

Bereavement is recognized as a universal challenging experience. It is important to gather research evidence on protective factors in bereavement. Hope is considered as one of the protective factors in previous coping studies. The present study aims to add knowledge by investigating hope at the first month after death to predict psychological symptoms altogether including complicated grief (CG), anxiety, and depressive symptoms at the seventh month. The data were collected via one-on-one interview survey in a longitudinal project with Hong Kong hospice users (sample size 105). Most participants were at their middle age (49-year-old on average), female (72%), with no religious affiliation (58%). Bayesian Structural Equation Modeling (BSEM) analysis was conducted on the longitudinal dataset. The BSEM findings show that hope at the first month of bereavement negatively predicts both CG and anxiety symptoms at the seventh month but not for depressive symptoms. Age and gender are controlled in the model. The overall model fit is good. The current study findings suggest assessing hope at the first month of bereavement. Hope at the first month after the loss is identified as an excellent predictor for complicated grief and anxiety symptoms at the seventh month. The result from this sample is clear, so it encourages cross-cultural research on replicated modeling and development of further clinical application. Particularly, practical consideration for early intervention to increase the level of hope has the potential to reduce the psychological symptoms and thus to improve the bereaved persons’ wellbeing in the long run.

Keywords: anxiety, complicated grief, depressive symptoms, hope, structural equational modeling

Procedia PDF Downloads 208