Search results for: clinical prediction rule

Authors: Joselito Medina-Marin, Maria G. Serna-Diaz, Juan C. Seck-Tuoh-Mora, Norberto Hernandez-Romero, Irving Barragán-Vite

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Wind speed forecasting is an important issue for planning wind power generation facilities. The accuracy in the wind speed prediction allows a good performance of wind turbines for electricity generation. A model based on artificial neural networks is presented in this work. A dataset with atmospheric information about air temperature, atmospheric pressure, wind direction, and wind speed in Pachuca, Hidalgo, México, was used to train the artificial neural network. The data was downloaded from the web page of the National Meteorological Service of the Mexican government. The records were gathered for three months, with time intervals of ten minutes. This dataset was used to develop an iterative algorithm to create 1,110 ANNs, with different configurations, starting from one to three hidden layers and every hidden layer with a number of neurons from 1 to 10. Each ANN was trained with the Levenberg-Marquardt backpropagation algorithm, which is used to learn the relationship between input and output values. The model with the best performance contains three hidden layers and 9, 6, and 5 neurons, respectively; and the coefficient of determination obtained was r²=0.9414, and the Root Mean Squared Error is 1.0559. In summary, the ANN approach is suitable to predict the wind speed in Pachuca City because the r² value denotes a good fitting of gathered records, and the obtained ANN model can be used in the planning of wind power generation grids.

Keywords: wind power generation, artificial neural networks, wind speed, coefficient of determination

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Authors: Prof. Ammal Mokhtar Metwally, Samia M. Sami, Nihad A. Ibrahim, Fatma A. Shaaban, Iman I. Salama

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Objectives: Reducing neonatal mortality by 2030 is still a challenging goal in developing countries. low birth weight (LBW) is a significant contributor to this, especially where weighing newborns is not possible routinely. The present study aimed to determine a simple, easy, reliable anthropometric measure(s) that can predict LBW) and neonatal mortality. Methods: A prospective cohort study of 570 babies born in districts of El Menia governorate, Egypt (where most deliveries occurred at home) was examined at birth. Newborn weight, length, head, chest, mid-arm, and thigh circumferences were measured. Follow up of the examined neonates took place during their first four weeks of life to report any mortalities. The most predictable anthropometric measures were determined using the statistical package of SPSS, and multiple Logistic regression analysis was performed.: Results: Head and chest circumferences with cut-off points < 33 cm and ≤ 31.5 cm, respectively, were the significant predictors for LBW. They carried the best combination of having the highest sensitivity (89.8 % & 86.4 %) and least false negative predictive value (1.4 % & 1.7 %). Chest circumference with a cut-off point ≤ 31.5 cm was the significant predictor for neonatal mortality with 83.3 % sensitivity and 0.43 % false negative predictive value. Conclusion: Using chest circumference with a cut-off point ≤ 31.5 cm is recommended as a single simple anthropometric measurement for the prediction of both LBW and neonatal mortality. The predicted measure could act as a substitute for weighting newborns in communities where scales to weigh them are not routinely available.

Keywords: low birth weight, neonatal mortality, anthropometric measures, practical screening

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Authors: Mary Farrell, Maria Soubra, Sandra Vega, Dorothy Kakraba, Joanne Fontanilla, Moira Kendra, Danielle Tonzola, Stephanie Chiu

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Pneumonia is the most common infectious cause of hospitalizations in the United States, with more than one million admissions annually and costs of $10 billion every year, making it the 8th leading cause of death. Aspiration pneumonia is an aggressive type of pneumonia that results from inhalation of oropharyngeal secretions and/or gastric contents and is preventable. The authors hypothesized that an evidence-based aspiration pneumonia clinical care pathway could reduce 30-day hospital readmissions and mortality rates, while improving the overall care of patients. We conducted a retrospective chart review on 979 patients discharged with aspiration pneumonia from January 2021 to December 2022 at Overlook Medical Center. The authors identified patients who were coded with aspiration pneumonia and/or stable sepsis. Secondarily, we identified 30-day readmission rates for aspiration pneumonia from a SNF. The Aspiration Pneumonia Clinical Care Pathway starts in the emergency department (ED) with the initiation of antimicrobials within 4 hours of admission and early recognition of aspiration. Once this is identified, a swallow test is initiated by the bedside nurse, and if the patient demonstrates dysphagia, they are maintained on strict nothing by mouth (NPO) followed by a speech and language pathologist (SLP) referral for an appropriate modified diet recommendation. Aspiration prevention techniques included the avoidance of straws, 45-degree positioning, no talking during meals, taking small bites, placement of the aspiration wrist band, and consuming meals out of the bed in a chair. Nursing education was conducted with a newly created online learning module about aspiration pneumonia. The authors identified 979 patients, with an average age of 73.5 years old, who were diagnosed with aspiration pneumonia on the index hospitalization. These patients were reviewed for a 30-day readmission for aspiration pneumonia or stable sepsis, and mortality rates from January 2021 to December 2022 at Overlook Medical Center (OMC). The 30-day readmission rates were significantly lower in the cohort that received the clinical care pathway (35.0% vs. 27.5%, p = 0.011). When evaluating the mortality rates in the pre and post intervention cohort the authors discovered the mortality rates were lower in the post intervention cohort (23.7% vs 22.4%, p = 0.61) Mortality among non-white (self-reported as non-white) patients were lower in the post intervention cohort (34.4% vs. 21.0% , p = 0.05). Patients who reported as a current smoker/vaper in the pre and post cohorts had increased mortality rates (5.9% vs 22%). There was a decrease in mortality for the male population but an increase in mortality for women in the pre and post cohorts (19% vs. 25%). The authors attributed this increase in mortality in the post intervention cohort to more active smokers, more former smokers, and more being admitted from a SNF. This research identified that implementation of an Aspiration Pneumonia Clinical Care Pathway showed a statistically significant decrease in readmission rates and mortality rates in non-whites. The 30-day readmission rates were lower in the cohort that received the clinical care pathway (35.0% vs. 27.5%, p = 0.011).

Keywords: aspiration pneumonia, mortality, quality improvement, 30-day pneumonia readmissions

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Authors: Hyunjoo Choi, Jeonghun Nam, Chae Seung Lim

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Acoustomicrofluidics has gained much attention due to the advantages, such as noninvasiveness and easy integration with other miniaturized systems, for clinical and biological applications. However, a limitation of acoustomicrofluidics is the complicated and costly fabrication process of electrodes. In this study, we propose a low-cost and lithography-free device using Lamb wave for blood analysis. Using a Lamb wave, calcium ion-removed blood plasma and coagulation reagents can be rapidly mixed for blood coagulation test. Due to the coagulation process, the viscosity of the sample increases and the viscosity change can be monitored by internal acoustic streaming of microparticles suspended in the sample droplet. When the acoustic streaming of particles stops by the viscosity increase is defined as the coagulation time. With the addition of calcium ion at 0-25 mM, the coagulation time was measured and compared with the conventional index for blood coagulation analysis, prothrombin time, which showed highly correlated with the correlation coefficient as 0.94. Therefore, our simple and cost-effective Lamb wave-based blood analysis device has the powerful potential to be utilized in clinical settings.

Keywords: acoustomicrofluidics, blood analysis, coagulation, lamb wave

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Authors: Mahboobe Daneshvar

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Introduction: Clinical studies on the effect of systemic conditions on periodontal diseases have shown that some systemic deficiencies may provide grounds for the onset of periodontal diseases. One of these systemic problems is osteoporosis, which may be a risk factor for the onset and exacerbation of periodontitis. This study tends to evaluate periodontal indices in osteoporotic menopausal women and compare them with healthy controls. Materials and Methods: In this case-control study, participants included 45-75-year-old menopausal women referred to rheumatology wards of the Khatamolanbia Clinic and Shahid Sadoughi Hospital in Yazd; Their bone density was determined by DEXA-scan and by imaging the femoral-lumbar bone. Thirty patients with osteoporosis and 30 subjects with normal BMD were selected. Then, informed consent was obtained for participation in the study. During the clinical examinations, tooth loss (TL), plaque index (PI), gingival recession, pocket probing depth (PPD), clinical attachment loss (CAL), and tooth mobility (TM) were measured to evaluate the periodontal status. These clinical examinations were performed to determine the periodontal status by catheter, mirror and probe. Results: During the evaluation, there was no significant difference in PPD, PI, TM, gingival recession, and CAL between case and control groups (P-value>0.05); that is, osteoporosis has no effect on the above factors. These periodontal factors are almost the same in both healthy and patient groups. In the case of missing teeth, the following results were obtained: the mean of missing teeth was 22.173% of the total teeth in the case group and 18.583% of the total teeth in the control group. In the study of the missing teeth in the case and control groups, there was a significant relationship between case and control groups (P-value = 0.025). Conclusion: In fact, since periodontal disease is multifactorial and microbial plaque is the main cause, osteoporosis is considered a predisposing factor in exacerbation or persistence of periodontal disease. In patients with osteoporosis, usually pathological fractures, hormonal changes, and aging lead to reduced physical activity and affect oral health, which leads to the manifestation of periodontal disease. But this disease increases tooth loss by changing the shape and structure of bone trabeculae and weakening them. Osteoporosis does not seem to be a deterministic factor in the incidence of periodontal disease, since it affects bone quality rather than bone quantity.

Keywords: plaque index, Osteoporosis, tooth mobility, periodontal packet

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Authors: Marzieh Yassin, Masoud Rashed, Soheil Mansour Sohani, Reza Salehi

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Background: Hip arthroplasty is one of the surgical methods to improve symptoms in patients with hip osteoarthritis. The use of electroacupuncture and TENS reduces pain, increases range of motion and improves performance. Methods: In this clinical trial study, 30 patients after hip arthroplasty were randomly divided into two groups: electroacupuncture (n=16) with exercise therapy and TENS with exercise therapy (n=14). Severity of pain, quality of life, range of motion, edema and function were evaluated in two groups before and after the interventions. Interventions of 10 sessions (three sessions per week) were conducted for two groups. The significance level in all tests was below 0.05. Results: The results showed that both groups improved all of the symptoms after the intervention (p≤0.05), although there was no statistically significant difference between the two groups in terms of effectiveness (p≥0.05). Conclusion: The results showed that both methods improve symptoms in patients after surgery. According to this study, electroacupuncture is suggested as a new method effective for the treatment of people with post-Total Hip Arthroplasty.

Keywords: electroacupuncture, physical performance, total hip arthroplasty, TENS

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Authors: RuiJin Zhang, HengJiang Cai, JinSong Gui

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It takes Patinopecten yessoensis larvae more than 20 days from spawning to settlement. Due to the natural environmental factors such as current, Patinopecten yessoensis larvae are transported to a distance more than hundreds of kilometers, leading to a high instability of their spatial and temporal distribution and great difficulties in the natural spat collection. Therefore predicting the distribution is of great significance to improve the operating efficiency of the collecting. Hydrodynamic model of Northern China Yellow Sea was established and the motions equations of physical oceanography and verified by the tidal harmonic constants and the measured data velocities of Dalian Bay. According to the passivity drift characteristics of the larvae, combined with the hydrodynamic model and the particle tracking model, the spatial and temporal distribution prediction model was established and the spatial and temporal distribution of the larvae under the influence of flow and wind were simulated. It can be concluded from the model results: ocean currents have greatest impacts on the passive drift path and diffusion of Patinopecten yessoensis larvae; the impact of wind is also important, which changed the direction and speed of the drift. Patinopecten yessoensis larvae were generated in the sea along Zhangzi Island and Guanglu-Dachangshan Island, but after two months, with the impact of wind and currents, the larvae appeared in the west of Dalian and the southern of Lvshun, and even in Bohai Bay. The model results are consistent with the relevant literature on qualitative analysis, and this conclusion explains where the larvae come from in the perspective of numerical simulation.

Keywords: numerical simulation, Patinopecten yessoensis larvae, predicting model, spatial and temporal distribution

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Authors: A. Nicknam, N. Eftekhari, A. Mazarei, M. Ganjvar

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This article presents an alternative collapse capacity intensity measure in the three elements form which is influenced by the spectral ordinates at periods longer than that of the first mode period at near and far source sites. A parameter, denoted by β, is defined by which the spectral ordinate effects, up to the effective period (2T_1), on the intensity measure are taken into account. The methodology permits to meet the hazard-levelled target extreme event in the probabilistic and deterministic forms. A MATLAB code is developed involving OpenSees to calculate the collapse capacities of the 8 archetype RC structures having 2 to 20 stories for regression process. The incremental dynamic analysis (IDA) method is used to calculate the structure’s collapse values accounting for the element stiffness and strength deterioration. The general near field set presented by FEMA is used in a series of performing nonlinear analyses. 8 linear relationships are developed for the 8structutres leading to the correlation coefficient up to 0.93. A collapse capacity near field prediction equation is developed taking into account the results of regression processes obtained from the 8 structures. The proposed prediction equation is validated against a set of actual near field records leading to a good agreement. Implementation of the proposed equation to the four archetype RC structures demonstrated different collapse capacities at near field site compared to those of FEMA. The reasons of differences are believed to be due to accounting for the spectral shape effects.

Keywords: collapse capacity, fragility analysis, spectral shape effects, IDA method

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Authors: Mahkameh Asadi, Habibollah Dadgar

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The precise definition margin of high and low-grade glioma is crucial for choosing best treatment approach after surgery and radio-chemotherapy. The aim of the current study was to assess the O-(2-18F-fluoroethyl)-L-tyrosine (18F-FET) positron emission tomography (PET)/computed tomography (CT) in patients with low (LGG) and high grade glioma (HGG). We retrospectively analyzed 18F-FET PET/CT of 10 patients (age: 33 ± 12 years) with suspicious for recurrent LGG and HGG. The final decision of recurrence was made by magnetic resonance imaging (MRI) and registered clinical data. While response to radio-chemotherapy by MRI is often complex and sophisticated due to the edema, necrosis, and inflammation, emerging amino acid PET leading to better interpretations with more specifically differentiate true tumor boundaries from equivocal lesions. Therefore, integrating amino acid PET in the management of glioma to complement MRI will significantly improve early therapy response assessment, treatment planning, and clinical trial design.

Keywords: positron emission tomography, amino acid positron emission tomography, magnetic resonance imaging, low and high grade glioma

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Authors: Brogan Guest, Amy Donaldson-Perrott

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The Master’s of Physician Associate Studies (MPAS) programme at St George’s, University of London (SGUL), is an intensive two-year course that trains students to become physician associates (PAs). PAs are generalized healthcare providers who work in primary and secondary care across the UK. PA programmes face the difficult task of preparing students to become safe medical providers in two short years. Our goal is to teach students to develop clinical reasoning early on in their studies and historically, this has been done predominantly though problem-based learning (PBL). We have had an increase concern about student engagement in PBL and difficulty recruiting facilitators to maintain the low student to facilitator ratio required in PBL. To address this issue, we created ‘Clinical Application of Anatomy and Physiology (CAAP)’. These peer-led, interactive, problem-based, small group sessions were designed to facilitate students’ clinical reasoning skills. The sessions were designed using the concept of Team-Based Learning (TBL). Students were divided into small groups and each completed a pre-session quiz consisting of difficult questions devised to assess students’ application of medical knowledge. The quiz was completed in small groups and they were not permitted access of external resources. After the quiz, students worked through a series of openended, clinical tasks using all available resources. They worked at their own pace and the session was peer-led, rather than facilitator-driven. For a group of 35 students, there were two facilitators who observed the sessions. The sessions utilised an infinite space whiteboard software. Each group member was encouraged to actively participate and work together to complete the 15-20 tasks. The session ran for 2 hours and concluded with a post-session quiz, identical to the pre-session quiz. We obtained subjective feedback from students on their experience with CAAP and evaluated the objective benefit of the sessions through the quiz results. Qualitative feedback from students was generally positive with students feeling the sessions increased engagement, clinical understanding, and confidence. They found the small group aspect beneficial and the technology easy to use and intuitive. They also liked the benefit of building a resource for their future revision, something unique to CAAP compared to PBL, which out students participate in weekly. Preliminary quiz results showed improvement from pre- and post- session; however, further statistical analysis will occur once all sessions are complete (final session to run December 2022) to determine significance. As a post-graduate healthcare professional programme, we have a strong focus on self-directed learning. Whilst PBL has been a mainstay in our curriculum since its inception, there are limitations and concerns about its future in view of student engagement and facilitator availability. Whilst CAAP is not TBL, it draws on the benefits of peer-led, small group work with pre- and post- team-based quizzes. The pilot of these sessions has shown that students are engaged by CAAP, and they can make significant progress in clinical reasoning in a short amount of time. This can be achieved with a high student to facilitator ratio.

Keywords: problem based learning, team based learning, active learning, peer-to-peer teaching, engagement

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Authors: Geng Xiangren, Liu Lei, Gui Ye-Wei, Tang Wei, Wang An-ling

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The malfunction of thermal protection system (TPS) caused by aerodynamic heating is a latent trouble to aircraft structure safety. Accurately predicting the structure temperature field is quite important for the TPS design of hypersonic vehicle. Since Thornton’s work in 1988, the coupled method of aerodynamic heating and heat transfer has developed rapidly. However, little attention has been paid to the influence of structural deformation on aerodynamic heating and structural temperature field. In the flight, especially the long-endurance flight, the structural deformation, caused by the aerodynamic heating and temperature rise, has a direct impact on the aerodynamic heating and structural temperature field. Thus, the coupled interaction cannot be neglected. In this paper, based on the method of static aero-thermo-elasticity, considering the influence of aero-thermo-elasticity deformation, the aerodynamic heating and heat transfer coupled results of hypersonic vehicle wing model were calculated. The results show that, for the low-curvature region, such as fuselage or center-section wing, structure deformation has little effect on temperature field. However, for the stagnation region with high curvature, the coupled effect is not negligible. Thus, it is quite important for the structure temperature prediction to take into account the effect of elastic deformation. This work has laid a solid foundation for improving the prediction accuracy of the temperature distribution of aircraft structures and the evaluation capacity of structural performance.

Keywords: aerothermoelasticity, elastic deformation, structural temperature, multi-field coupling

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Authors: Nadish Anand, Richard D. Gould

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A simplistic model is introduced for determining the thermal characteristics of a Low-rise Residential (LRR) building and then predicts the energy usage by its Heating Ventilation & Air Conditioning (HVAC) system according to changes in weather conditions which are reflected in the Ambient Temperature (Outside Air Temperature). The LRR buildings are treated as a simple lump for solving the heat transfer problem and the model is derived using the lumped capacitance model of transient conduction heat transfer from bodies. Since most contemporary HVAC systems have a thermostat control which will have an offset temperature and user defined set point temperatures which define when the HVAC system will switch on and off. The aim is to predict without any error the Body Temperature (i.e. the Inside Air Temperature) which will estimate the switching on and off of the HVAC system. To validate the mathematical model derived from lumped capacitance we have used EnergyPlus simulation engine, which simulates Buildings with considerable accuracy. We have predicted through the low order model the Inside Air Temperature of a single house kept in three different climate zones (Detroit, Raleigh & Austin) and different orientations for summer and winter seasons. The prediction error from the model for the same day as that of model parameter calculation has showed an error of < 10% in winter for almost all the orientations and climate zones. Whereas the prediction error is only <10% for all the orientations in the summer season for climate zone at higher latitudes (Raleigh & Detroit). Possible factors responsible for the large variations are also noted in the work, paving way for future research.

Keywords: building energy, energy consumption, energy+, HVAC, low order model, lumped capacitance

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Authors: Said Alshukri, Mazhar Hussain Malik

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Green hydrogen is hydrogen produced using renewable energy sources. In the last few years, Oman aimed to reduce its dependency on fossil fuels. Recently, the hydrogen economy has become a global trend, and many countries have started to investigate the feasibility of implementing this sector. Oman created an alliance to establish the policy and rules for this sector. With motivation coming from both global and local interest in green hydrogen, this paper investigates the potential of producing hydrogen from wind and solar energies in three different locations in Oman, namely Duqm, Salalah, and Sohar. By using machine learning-based software “WEKA” and local metrological data, the project was designed to figure out which location has the highest wind and solar energy potential. First, various supervised models were tested to obtain their prediction accuracy, and it was found that the Random Forest (RF) model has the best prediction performance. The RF model was applied to 2021 metrological data for each location, and the results indicated that Duqm has the highest wind and solar energy potential. The system of one wind turbine in Duqm can produce 8335 MWh/year, which could be utilized in the water electrolysis process to produce 88847 kg of hydrogen mass, while a solar system consisting of 2820 solar cells is estimated to produce 1666.223 MWh/ year which is capable of producing 177591 kg of hydrogen mass.

Keywords: green hydrogen, machine learning, wind and solar energies, WEKA, supervised models, random forest

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Authors: Bui Phuong Linh, Yuki Sakakibara, Ryuto Tanaka, Elizabeth H. Pigney, Taishi Hashiguchi

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Non-alcoholic steatohepatitis (NASH) is a chronic liver disease, often associated with type II diabetes, which sometimes progresses to more serious conditions such as liver fibrosis and hepatocellular carcinoma (HCC). NASH has become an important health problem worldwide, buttherapeutic agents for NASH have not yet been approved, and animal models with high clinical correlation are required. TheSTAM™ mouse shows the same pathological progression as human NASH patients and has been widely used for both drug efficacy and basic research, such as lipid profiling and gut microbiota research. In this study, we analyzed the RNA-seq data of STAM™mice at each pathological stage (steatosis, steatohepatitis, liver fibrosis, and HCC) and examined the clinical correlation at the genetic level. NASH was induced in male mice by a single subcutaneous injection of 200 µg streptozotocin solution 2 days after birth and feeding with high fat dietafter 4 weeks of age. The mice were sacrificed and livers collected at 6, 8, 10, 12, 16, and 20 weeks of age. For liver samples, the left lateral lobe was snap frozen in liquid nitrogen and stored at -80˚C for RNA-seq analysis. Total RNA of the cells was isolated using RNeasy mini kit. The gene expression of the canonical pathways in NASH progression from steatosis to hepatocellular carcinoma were analyzed, such as immune system process, oxidation-reduction process, lipid metabolic process. Moreover, since it has been reported that genetic traits are involved in the development of NASH-HCC, we next analyzed the genetic mutations in the STAM™mice. The number of individuals showing mutations in Mtorinvolved in Insulin signaling increases as the disease progresses, especially in the liver cancer phase. These results indicated a clinical correlation of gene profiles in the STAM™mouse.

Keywords: steatosis, non-alcoholic steatohepatitis, fibrosis, hepatocellular carcinoma, RNA-seq

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Authors: Darren J. Ellis

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This paper investigates the key industry-level consequences and future prospects for the global airline industry of the requirement for airlines to have a home base. This industry context results in geographical location playing a central role in determining how and where international airlines can operate, and the extent to which their international networks can develop. Data from a five stage mixed-methods Delphi study into the global airline industry’s likely future trajectory conducted in 2013 and 2014 are utilized to better understand the likelihood and consequences of home base requirements changing in future. Expert views and forecasts were collected to gauge core industry trends over a ten year timeframe. Attempts to change or bypass this industry requirement have not been successful to date outside of the European single air market. Europe remains the only prominent exception to the general rule in this regard. Most of the industry is founded on air space sovereignty, the nationality rule, and the bilateral system of traffic rights. Europe’s exceptionalism has seen it evolve into a single air market with characteristics similar to a nation-state, rather than to become a force for wider industry change and regional multilateralism. Europe has indeed become a key actor in global aviation, but Europe seems to now be part of the industry’s status quo, not a vehicle for substantially wider multilateralism around the world. The findings from this research indicate that the bilateral system is not viewed by most study experts as disappearing or substantially weakening in the foreseeable future. However, regional multilateralism was also viewed as progressively taking hold in the industry in future, demonstrating that for most industry experts the two are not seen as mutually exclusive but rather as being able to co-exist with each other. This reality ensures that geographical location will continue to play an important role in the global airline industry in future and that, home base requirements will not disappear any time soon either. Even moves in some aviation jurisdictions to dilute nationality requirements for airlines, and instead replace ownership and control restrictions with principal place of business tests, do not ultimately free airlines from their home base. Likewise, an expansion of what constitutes home base to include a regional grouping of countries – again, a currently uncommon reality in global aviation – does not fundamentally weaken the continued relevance of geographical location to the global industry’s future growth and development realities and prospects.

Keywords: airline industry, air space sovereignty, geographical location, home base

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Authors: Shazia Anwer Bukhari, Madiha Javeed Ghani, Muhammad Ibrahim Rajoka

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Objective: Biochemical, environmental, physical and genetic factors have a strong effect on the development of coronary disease (CAD). Plasma homocysteine (Hcy) level and DNA damage play a pivotal role in its development and progression. The aim of this study was to investigate the predictive strength of an oxidative stress, clinical biomarkers and total antioxidant status (TAS) in CAD patients to find the correlation of homocysteine, TOS and oxidative DNA damage with other clinical parameters. Methods: Sixty confirmed patients with CAD and 60 healthy individuals as control were included in this study. Different clinical and laboratory parameters were studied in blood samples obtained from patients and control subjects using commercially available biochemical kits and statistical software Results: As compared to healthy individuals, CAD patients had significantly higher concentrations of indices of oxidative stress: homocysteine (P=0.0001), total oxidative stress (TOS) (P=0.0001), serum cholesterol (P=0.04), low density lipoprotein cholesterol (LDL) (P=0.01), high density lipoprotein-cholesterol (HDL) (P=0.0001), and malondialdehyde (MDA) (P=0.001) than those of healthy individuals. Plasma homocysteine level and oxidative DNA damage were positively correlated with cholesterol, triglycerides, systolic blood pressure, urea, total protein and albumin (P values= 0.05). Both Hcy and oxidative DNA damage were negatively correlated with TAS and proteins. Conclusion: Coronary artery disease patients had a significant increase in homocysteine level and DNA damage due to increased oxidative stress. In conclusion, our study shows a significantly increase in lipid peroxidation, TOS, homocysteine and DNA damage in the erythrocytes of patients with CAD. A significant decrease level of HDL-C and TAS was observed only in CAD patients. Therefore these biomarkers may be useful diagnosis of patients with CAD and play an important role in the pathogenesis of CAD.

Keywords: antioxidants, coronary artery disease, DNA damage, homocysteine, oxidative stress, malondialdehyde, 8-Hydroxy-2’deoxyguanosine

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Authors: Vanessa Roulet, Marc Turini, Juliane Hey, Stéphanie Bord-Romeu, Emilie Bonzom, Mahmoud Badawi, Mohammed-Amine Chakir, Valérie Simon, Vanessa Viotti, Jérémie Gautier, Françoise Le Boulaire, Catherine Coignard, Claire Vincent, Sandrine Greaume, Isabelle Voisin

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Background: Beckman Coulter, Inc. has recently developed fully automated assays for the detection of HBsAg on a new immunoassay platform. The objective of this European multicenter study was to evaluate the performance of the ACCESS HBsAg and ACCESS HBsAg Confirmatory assays† on the recently CE-marked DxI 9000 ACCESS Immunoassay Analyzer. Methods: The clinical specificity of the ACCESS HBsAg and HBsAg Confirmatory assays was determined using HBsAg-negative samples from blood donors and hospitalized patients. The clinical sensitivity was determined using presumed HBsAg-positive samples. Sample HBsAg status was determined using a CE-marked HBsAg assay (Abbott ARCHITECT HBsAg Qualitative II, Roche Elecsys HBsAg II, or Abbott PRISM HBsAg assay) and a CE-marked HBsAg confirmatory assay (Abbott ARCHITECT HBsAg Qualitative II Confirmatory or Abbott PRISM HBsAg Confirmatory assay) according to manufacturer package inserts and pre-determined testing algorithms. False initial reactive rate was determined on fresh hospitalized patient samples. The sensitivity for the early detection of HBV infection was assessed internally on thirty (30) seroconversion panels. Results: Clinical specificity was 99.95% (95% CI, 99.86 – 99.99%) on 6047 blood donors and 99.71% (95%CI, 99.15 – 99.94%) on 1023 hospitalized patient samples. A total of six (6) samples were found false positive with the ACCESS HBsAg assay. None were confirmed for the presence of HBsAg with the ACCESS HBsAg Confirmatory assay. Clinical sensitivity on 455 HBsAg-positive samples was 100.00% (95% CI, 99.19 – 100.00%) for the ACCESS HBsAg assay alone and for the ACCESS HBsAg Confirmatory assay. The false initial reactive rate on 821 fresh hospitalized patient samples was 0.24% (95% CI, 0.03 – 0.87%). Results obtained on 30 seroconversion panels demonstrated that the ACCESS HBsAg assay had equivalent sensitivity performances compared to the Abbott ARCHITECT HBsAg Qualitative II assay with an average bleed difference since first reactive bleed of 0.13. All bleeds found reactive in ACCESS HBsAg assay were confirmed in ACCESS HBsAg Confirmatory assay. Conclusion: The newly developed ACCESS HBsAg and ACCESS HBsAg Confirmatory assays from Beckman Coulter have demonstrated high clinical sensitivity and specificity, equivalent to currently marketed HBsAg assays, as well as a low false initial reactive rate. †Pending achievement of CE compliance; not yet available for in vitro diagnostic use. 2023-11317 Beckman Coulter and the Beckman Coulter product and service marks mentioned herein are trademarks or registered trademarks of Beckman Coulter, Inc. in the United States and other countries. All other trademarks are the property of their respective owners.

Keywords: dxi 9000 access immunoassay analyzer, hbsag, hbv, hepatitis b surface antigen, hepatitis b virus, immunoassay

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Authors: R. O. Osaseri, A. R. Usiobaifo

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The power transformer which is responsible for the voltage transformation is of great relevance in the power system and oil-immerse transformer is widely used all over the world. A prompt and proper maintenance of the transformer is of utmost importance. The dissolved gasses content in power transformer, oil is of enormous importance in detecting incipient fault of the transformer. There is a need for accurate prediction of the incipient fault in transformer oil in order to facilitate the prompt maintenance and reducing the cost and error minimization. Study on fault prediction and diagnostic has been the center of many researchers and many previous works have been reported on the use of artificial intelligence to predict incipient failure of transformer faults. In this study machine learning technique was employed by using gradient decent algorithms and Support Vector Machine (SVM) in predicting incipient fault diagnosis of transformer. The method focuses on creating a system that improves its performance on previous result and historical data. The system design approach is basically in two phases; training and testing phase. The gradient decent algorithm is trained with a training dataset while the learned algorithm is applied to a set of new data. This two dataset is used to prove the accuracy of the proposed model. In this study a transformer fault diagnostic model based on Support Vector Machine (SVM) and gradient decent algorithms has been presented with a satisfactory diagnostic capability with high percentage in predicting incipient failure of transformer faults than existing diagnostic methods.

Keywords: diagnostic model, gradient decent, machine learning, support vector machine (SVM), transformer fault

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Authors: Rakan Alajmi, Rahaf Alnazzawi, Yara Aljefri, Abdullah Alafif, Ali Alraddadi, Awadh Alamri

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Background: The distribution of physicians in different specialties across Saudi Arabia is determined by the career choices of medical students. Dermatology residency program is one of the highly competitive programs here in Saudi Arabia. Assessing and understanding the factors perceived to be attractive in choosing dermatology will aid the directors of the specialty programs to plan for a more balanced workforce distribution to better suit the needs of the specialties. Aim: The aim of our study is to determine and assess the factors perceived to be significantly attractive when choosing dermatology as a future specialty. Methods: The study is a cross-sectional study conducted in King Saud bin Abdulaziz University for Health Sciences, Jeddah, Saudi Arabia. A validated questionnaire was sent electronically to clinical year medical students. In addition to the questionnaire, gender, grade point average, preferred specialty, and other socio-demographic data were assessed. Results: A total of 121 clinical years medical students completed the questionnaire, 8 (6.6%) preferred dermatology as a specialty. 76 (62.8%) of the participants score a grade point average of more than 4.5 and 83 students (68.6%) chose their specialty during clinical years. The appeal of being a dermatologist (P= 0.047), the portrayal of different specialities in the media (P= 0.005), and the likelihood that dermatologists can influence patients’ lives (P=0.010) were shown to be significantly attractive factors. Conclusion: There are many factors that are affecting students’ choices when choosing a medical specialty. The appeal of being a dermatologist, the portrayal of different specialities in the media, and the likelihood that dermatologists can influence patients’ lives were shown to be significantly attractive factors when choosing dermatology as a future specialty. Recognizing medical students’ specialty perception will lead them to a proper specialty tailored to their needs.

Keywords: dermatology, career choice, medical specialties, student's perception

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Authors: Saba Gachpaz, Hamid Reza Heidari

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The sharp increase in population growth leads to more pressure on agricultural areas to satisfy the food supply. To achieve this, more resources should be consumed and, besides other environmental concerns, highlight sustainable agricultural development. Land-use management is a crucial factor in obtaining optimum productivity. Machine learning is a widely used technique in the agricultural sector, from yield prediction to customer behavior. This method focuses on learning and provides patterns and correlations from our data set. In this study, nine physical control factors, namely, soil classification, electrical conductivity, normalized difference water index (NDWI), groundwater level, elevation, annual precipitation, pH of water, annual mean temperature, and slope in the alluvial plain in Khuzestan (an agricultural hotspot in Iran) are used to decide the best agricultural land use for both rainfed and irrigated agriculture for ten different crops. For this purpose, each variable was imported into Arc GIS, and a raster layer was obtained. In the next level, by using training samples, all layers were imported into the python environment. A random forest model was applied, and the weight of each variable was specified. In the final step, results were visualized using a digital elevation model, and the importance of all factors for each one of the crops was obtained. Our results show that despite 62% of the study area being allocated to agricultural purposes, only 42.9% of these areas can be defined as a suitable class for cultivation purposes.

Keywords: land suitability, machine learning, random forest, sustainable agriculture

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Authors: D. Zhang, H. Y. Du, G. W. Li, J. Zeng, D. W. Zuo, Y. P. You

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For the difficult issues of process selection, case-based reasoning technology is applied to computer aided process planning system for cold form tapping of internal threads on the basis of similarity in the process. A model is established based on the analysis of process planning. Case representation and similarity computing method are given. Confidence degree is used to evaluate the case. Rule-based reuse strategy is presented. The scheme is illustrated and verified by practical application. The case shows the design results with the proposed method are effective.

Keywords: case-based reasoning, internal thread, cold extrusion, process planning

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Authors: Ahmed Alghurabi, Mysara Mohyaldinn, Shiferaw Jufar, Obai Younis, Abdullah Abduljabbar

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Erosion modeling equations were typically acquired from regulated experimental trials for solid particles entrained in single-phase or multi-phase flows. Evidently, those equations were later employed to predict the erosion damage caused by the continuous impacts of solid particles entrained in streamflow. It is also well-known that the particle impact angle and velocity do not change drastically in gas-sand flow erosion prediction; hence an accurate prediction of erosion can be projected. On the contrary, high-density fluid flows, such as water flow, through complex geometries, such as sand screens, greatly affect the sand particles’ trajectories/tracks and consequently impact the erosion rate predictions. Particle tracking models and erosion equations are frequently applied simultaneously as a method to improve erosion visualization and estimation. In the present work, computational fluid dynamic (CFD)-based erosion modeling was performed using a commercially available software; ANSYS Fluent. The continuous phase (water flow) behavior was simulated using the realizable K-epsilon model, and the secondary phase (solid particles), having a 5% flow concentration, was tracked with the help of the discrete phase model (DPM). To accomplish a successful erosion modeling, three erosion equations from the literature were utilized and introduced to the ANSYS Fluent software to predict the screen wire-slot velocity surge and estimate the maximum erosion rates on the screen surface. Results of turbulent kinetic energy, turbulence intensity, dissipation rate, the total pressure on the screen, screen wall shear stress, and flow velocity vectors were presented and discussed. Moreover, the particle tracks and path-lines were also demonstrated based on their residence time, velocity magnitude, and flow turbulence. On one hand, results from the utilized erosion equations have shown similarities in screen erosion patterns, locations, and DPM concentrations. On the other hand, the model equations estimated slightly different values of maximum erosion rates of the wire-wrapped screen. This is solely based on the fact that the utilized erosion equations were developed with some assumptions that are controlled by the experimental lab conditions.

Keywords: CFD simulation, erosion rate prediction, material loss due to erosion, water-sand flow

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Authors: Silvia Arrate, Waldo Salud, Eloy París

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The wear of cutting tools is one of the most decisive elements when planning tunneling works, programming the maintenance stops and saving the optimum stock of spare parts during the evolution of the excavation. Being able to predict the behavior of cutting tools can give a very competitive advantage in terms of costs and excavation performance, optimized to the needs of the TBM itself. The incredible evolution of data science in recent years gives the option to implement it at the time of analyzing the key and most critical parameters related to machinery with the purpose of knowing how the cutting head is performing in front of the excavated ground. Taking this as a case study, Metro Line 3 of Guadalajara in Mexico will develop the feasibility of using Specific Energy versus data science applied over parameters of Torque, Penetration, and Contact Force, among others, to predict the behavior and status of cutting tools. The results obtained through both techniques are analyzed and verified in the function of the wear and the field situations observed in the excavation in order to determine its effectiveness regarding its predictive capacity. In conclusion, the possibilities and improvements offered by the application of digital tools and the programming of calculation algorithms for the analysis of wear of cutting head elements compared to purely empirical methods allow early detection of possible damage to cutting tools, which is reflected in optimization of excavation performance and a significant improvement in costs and deadlines.

Keywords: cutting tools, data science, prediction, TBM, wear

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Authors: Evangelia Kotrotsiou, Mairy Gouva, Theodosios Paralikas, Maria Fiaka, Styliani Kotrotsiou, Maria Malliarou

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The purpose of this research is to investigate the way nurses perceive the care provided in comparison to the way patients perceive it, taking into account existing literature. As far as the sample of research is concerned, it has come from the population of nurses working in the General Hospital of Thessaloniki, St. Paul and the patients of its surgical clinic. In the present study, the sample consists of 100 nurses and 88 patients. The questionnaire used was the Caring Nurse-Patient Interactions Scale: 23-Item Version, created by Cossette et al. (2006). In the case of both patients and nurses, a high score was observed in relational care in the case of the frequency of nursing care in daily practice, as well as the satisfaction of providing nursing care. Overall, patients rated higher clinical care in the case of the frequency of nursing care in daily practice, as well as the satisfaction of the clinical care they were given. On the other hand, nurses rated higher comfort care in the case of the frequency of nursing care in everyday practice, as well as relational care in the area of the importance of nursing care in everyday practice.

Keywords: nursing care, patient needs, patient satisfaction, care giving

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Authors: Sophia Liang Zhou

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For investors, businesses, consumers, and governments, an accurate assessment of future housing prices is crucial to critical decisions in resource allocation, policy formation, and investment strategies. Previous studies are contradictory about macroeconomic determinants of housing price and largely focused on one or two areas using point prediction. This study aims to develop data-driven models to accurately predict future housing market trends in different markets. This work studied five different metropolitan areas representing different market trends and compared three-time lagging situations: no lag, 6-month lag, and 12-month lag. Linear regression (LR), random forest (RF), and artificial neural network (ANN) were employed to model the real estate price using datasets with S&P/Case-Shiller home price index and 12 demographic and macroeconomic features, such as gross domestic product (GDP), resident population, personal income, etc. in five metropolitan areas: Boston, Dallas, New York, Chicago, and San Francisco. The data from March 2005 to December 2018 were collected from the Federal Reserve Bank, FBI, and Freddie Mac. In the original data, some factors are monthly, some quarterly, and some yearly. Thus, two methods to compensate missing values, backfill or interpolation, were compared. The models were evaluated by accuracy, mean absolute error, and root mean square error. The LR and ANN models outperformed the RF model due to RF’s inherent limitations. Both ANN and LR methods generated predictive models with high accuracy ( > 95%). It was found that personal income, GDP, population, and measures of debt consistently appeared as the most important factors. It also showed that technique to compensate missing values in the dataset and implementation of time lag can have a significant influence on the model performance and require further investigation. The best performing models varied for each area, but the backfilled 12-month lag LR models and the interpolated no lag ANN models showed the best stable performance overall, with accuracies > 95% for each city. This study reveals the influence of input variables in different markets. It also provides evidence to support future studies to identify the optimal time lag and data imputing methods for establishing accurate predictive models.

Keywords: linear regression, random forest, artificial neural network, real estate price prediction

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Authors: Priscilla Akua Agyapong

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Background: In a country of nearly 34 million people, Ghana suffers from rapidly growing pediatric CHD cases and not enough pediatric specialists to attend to the burgeoning needs of these children. Most of the cases are either missed or diagnosed late, resulting in increased mortality. According to the National Cardiothoracic Centre, 1 in every 100,000 births in Ghana has CHD; however, there is limited data on the clinical presentation and its management, one of the many reasons I decided to do this case study coupled with the loss my 2 month old niece to multiple Ventricular Septal Defect 3 years ago due late diagnoses. Method: A retrospective cohort study was performed at the child health clinic of one of Ghana’s public tertiary Institutions using data from their electronic health record (EHR) from February 2021 to April 2022. All suspected or provisionally diagnosed cases were included in the analysis. Results: Records of over 3000 children were reviewed with an approximate male to female ratio of 1:1.53 cases diagnosed during the period of study, most of whom were less than 5 years of age. 25 cases had complete clinical records, with acyanotic septal defects being the most diagnosed. 62.5% of the cases were ventricular septal defects, followed by Patent Ductus Arteriosus (23%) and Atrial Septal Defects (4.5%). Tetralogy of Fallot was the most predominant and complex cyanotic CHD with 10%. Conclusion: The indeterminate coronary anatomy of infants makes it difficult to use only echocardiography and other conventional clinical methods in screening for CHDs. There are rising modernizations and new innovative ways that can be employed in Ghana for early detection, hence preventing the delay of a potential surgical repair. It is, therefore, imperative to create the needed awareness about these “SILENT CRISES” and help save the Ghanaian child’s life.

Keywords: congenital heart defect(CHD), ventricular septal defect(VSD), atrial septal defect(ASD), patent ductus arteriosus(PDA)

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Authors: S. M. Satyam, K. L. Bairy, R. Pirasanthan, R. L. Vaishnav

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Zincovit tablets have been used as nutritional food supplement over a prolonged period of time. The aim of the present study was to investigate the cardio-protective effect of combined formulation of grape seed extract and Zincovit tablets (40, 80 and 160 mg/kg) using a Langendorff model of ischemia-reperfusion in Wistar rats. Following 21 days of pre-treatment, combined formulation of grape seed extract and Zincovit tablets significantly attenuated ischemia-reperfusion induced cardiac injury in terms of increased coronary flow rate (p < 0.01), decreased creatine kinase activity in coronary effluent (p < 0.05), decreased MDA (p < 0.001), 4-HNE (p < 0.001) and increased protein thiol content (p < 0.01) in comparison with the untreated (control) group. This study opens an avenue to clinical studies to demonstrate the validity of this paradigm as a nutritional food supplement, which could improve the clinical outcome of patients subjected to percutaneous angioplasty.

Keywords: grape seed extract, myocardial ischemia-reperfusion injury, oxidative stress, Zincovit tablets

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Authors: Ghadeer Mohammad Said El-Sheikh, Samer Mohamad Shalhoob

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Medical equipment operation state is a valid reflection of health care organizations' performance, where such equipment highly contributes to the quality of healthcare services on several levels in which quality improvement has become an intrinsic part of the discourse and activities of health care services. In healthcare organizations, clinical and biomedical engineering departments play an essential role in maintaining the safety and efficiency of such equipment. One of the most challenging topics when it comes to such sophisticated equipment is the lifespan of medical equipment, where many factors will impact such characteristics of medical equipment through its life cycle. So far, many attempts have been made in order to address this issue where most of the approaches are kind of arbitrary approaches and one of the criticisms of existing approaches trying to estimate and understand the lifetime of a medical equipment lies under the inquiry of what are the environmental factors that can play into such a critical characteristic of a medical equipment. In an attempt to address this shortcoming, the purpose of our study rises where in addition to the standard technical factors taken into consideration through the decision-making process by a clinical engineer in case of medical equipment failure, the dimension of environmental factors shall be added. The investigations, researches and studies applied for the purpose of supporting the decision making process by a clinical engineers and assessing the lifespan of healthcare equipment’s in the Lebanese society was highly dependent on the identification of technical criteria’s that impacts the lifespan of a medical equipment where the affecting environmental factors didn’t receive the proper attention. The objective of our study is based on the need for introducing a new well-designed plan for evaluating medical equipment depending on two dimensions. According to this approach, the equipment that should be replaced or repaired will be classified based on a systematic method taking into account two essential criteria; the standard identified technical criteria and the added environmental criteria.

Keywords: technical, environmental, healthcare, characteristic of medical equipment

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Authors: Ahmed Z. Mazen, Nejat Rahmanian, Iqbal Mujtaba, Ali Hassanpour

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In oil and gas well drilling, the drill bit is an important part of the Bottom Hole Assembly (BHA), which is installed and designed to drill and produce a hole by several mechanisms. The efficiency of the bit depends on many drilling parameters such as weight on bit, rotary speed, and mud properties. When the bit is pulled out of the hole, the evaluation of the bit damage must be recorded very carefully to guide engineers in order to select the bits for further planned wells. Having a worn bit for hole drilling may cause severe damage to bit leading to cutter or cone losses in the bottom of hole, where a fishing job will have to take place, and all of these will increase the operating cost. The main factor to reduce the cost of drilling operation is to maximize the rate of penetration by analyzing real-time data to predict the drill bit wear while drilling. There are numerous models in the literature for prediction of the rate of penetration based on drilling parameters, mostly based on empirical approaches. One of the most commonly used approaches is Bourgoyne and Young model, where the rate of penetration can be estimated by the drilling parameters as well as a wear index using an empirical correlation, provided all the constants and coefficients are accurately determined. This paper introduces a new methodology to estimate the eight coefficients for Bourgoyne and Young model using the gPROMS parameters estimation GPE (Version 4.2.0). Real data collected form similar formations (12 ¼’ sections) in two different fields in Libya are used to estimate the coefficients. The estimated coefficients are then used in the equations and applied to nearby wells in the same field to predict the bit wear.

Keywords: Bourgoyne and Young model, bit wear, gPROMS, rate of penetration

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Authors: Mari A. Virtanen, Elina Haavisto, Eeva Liikanen, Maria Kääriäinen

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Rapid technological development and digitalization has affected also on higher education. During last twenty years multiple of electronic and mobile learning (e-learning, m-learning) platforms have been developed and have become prevalent in many universities and in the all fields of education. Ubiquitous learning (u-learning) is not that widely known or used. Ubiquitous learning environments (ULE) are the new era of computer-assisted learning. They are based on ubiquitous technology and computing that fuses the learner seamlessly into learning process by using sensing technology as tags, badges or barcodes and smart devices like smartphones and tablets. ULE combines real-life learning situations into virtual aspects and can be flexible used in anytime and anyplace. The aim of this study was to assess the effects of ubiquitous 360 o learning environment on higher education students’ clinical histotechnology competence. A quasi-experimental study design was used. 57 students in biomedical laboratory science degree program was assigned voluntarily to experiment (n=29) and to control group (n=28). Experimental group studied via ubiquitous 360o learning environment and control group via traditional web-based learning environment (WLE) in a 8-week educational intervention. Ubiquitous 360o learning environment (ULE) combined authentic learning environment (histotechnology laboratory), digital environment (virtual laboratory), virtual microscope, multimedia learning content, interactive communication tools, electronic library and quick response barcodes placed into authentic laboratory. Web-based learning environment contained equal content and components with the exception of the use of mobile device, interactive communication tools and quick response barcodes. Competence of clinical histotechnology was assessed by using knowledge test and self-report developed for this study. Data was collected electronically before and after clinical histotechnology course and analysed by using descriptive statistics. Differences among groups were identified by using Wilcoxon test and differences between groups by using Mann-Whitney U-test. Statistically significant differences among groups were identified in both groups (p<0.001). Competence scores in post-test were higher in both groups, than in pre-test. Differences between groups were very small and not statistically significant. In this study the learning environment have developed based on 360o technology and successfully implemented into higher education context. And students’ competence increases when ubiquitous learning environment were used. In the future, ULE can be used as a learning management system for any learning situation in health sciences. More studies are needed to show differences between ULE and WLE.

Keywords: competence, higher education, histotechnology, ubiquitous learning, u-learning, 360o

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