Search results for: wells score

Authors: Cristy Stagnar, Nina Hubig, Diana Ivankovic

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The epigenome is a compelling candidate for mediating long-term responses to environmental effects modifying disease risk. The main goal of this research is to develop a machine learning-based DNA methylation score, which will be valuable in delineating the unique contribution of paternal epigenetic modifications to the germline impacting childhood health outcomes. It will also be a useful tool in validating self-reports of nonsmoking and in adjusting epigenome-wide DNA methylation association studies for this early-life exposure. Using secondary data from two population-based methylation profiling studies, our DNA methylation score is based on CpG DNA methylation measurements from cord blood gathered from children whose fathers smoked pre- and peri-conceptually. Each child’s mother and father fell into one of three class labels in the accompanying questionnaires -never smoker, former smoker, or current smoker. By applying different machine learning algorithms to the accessible resource for integrated epigenomic studies (ARIES) sub-study of the Avon longitudinal study of parents and children (ALSPAC) data set, which we used for training and testing of our model, the best-performing algorithm for classifying the father smoker and mother never smoker was selected based on Cohen’s κ. Error in the model was identified and optimized. The final DNA methylation score was further tested and validated in an independent data set. This resulted in a linear combination of methylation values of selected probes via a logistic link function that accurately classified each group and contributed the most towards classification. The result is a unique, robust DNA methylation score which combines information on DNA methylation and early life exposure of offspring to paternal smoking during pregnancy and which may be used to examine the paternal contribution to offspring health outcomes.

Keywords: epigenome, health outcomes, paternal preconception environmental exposures, supervised machine learning

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Authors: Jana Atteah, Wid Jan, Yara AlHibshi, Rahaf AlRougi

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Anyword is an AI copywriting tool that helps marketers create effective campaigns for specific audiences. It offers a wide range of templates for various platforms, brand voice guidelines, and valuable analytics insights. Anyword is used by top global companies and has been recognized as one of the "Fastest Growing Products" in the 2023 software awards. A recent study examined the utilization and impact of AI-powered writing tools, specifically focusing on the adoption of AI in writing pursuits and the use of the Anyword platform. The results indicate that a majority of respondents (52.17%) had not previously used Anyword, but those who had were generally satisfied with the platform. Notable productivity improvements were observed among 13% of the participants, while an additional 34.8% reported a slight increase in productivity. A majority (47.8%) maintained a neutral stance, suggesting that their productivity remained unaffected. Only a minimal percentage (4.3%) claimed that their productivity did not improve with the usage of Anyword AI. In terms of the quality of written content generated, the participants responded positively. Approximately 91% of participants gave Anyword AI a score of 5 or higher, with roughly 17% giving it a perfect score. A small percentage (approximately 9%) gave a low score between 0-2. The mode result was a score of 7, indicating a generally positive perception of the quality of content generated using Anyword AI. These findings suggest that AI can contribute to increased productivity and positively influence the quality of written content. Further research and exploration of AI tools in writing pursuits are warranted to fully understand their potential and limitations.

Keywords: artificial intelligence, marketing platforms, productivity, user interface

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Authors: Hatem A. El-Mezayen, Ahmed Abdelmajeed, Fatehya Metwally, Usama Elsaly, Salwa Atef

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Tumor metastasis involves the dissemination of malignant cells into the basement membrane and vascular system contributes to the circulating pool of these markers. In this context our aim has been focused on development of a non-invasive. Circulating tumor cells (CTCs) represent a unique liquid biopsy carrying comprehensive biological information of the primary tumor. Herein, we sought to develop a novel score based on the combination of the most significant CTCs biomarkers with and routine laboratory tests for accurate detection of metastatic breast cancer. Methods: Cytokeratin 18 (CK18), Cytokeratin 19 (CK19), and CA15.3 were assayed in metastatic breast cancer (MBC) patients (75), non-MBC patients (50) and healthy control (20). Results: Areas under receiving operating curve (AUCs) were calculated and used for construction on novel score. A novel score named MBC-CTCs = CA15.3 (U/L) × 0.08 + CK 18 % × 2.9 + CK19 × 3.1– 510. That function correctly classified 87% of metastatic breast cancer at cut-off value = 0.55. (i.e great than 0.55 indicates patients with metastatic breast cancer and less than 0.55 indicates patients with non-metastatic breast cancer). Conclusion: MBC-CTCs is a novel, non-invasive and simple can applied to discriminate patients with metastatic breast cancer.

Keywords: metastatic breast cancer, circulating tumor cells, cytokeratin, EpiCam

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Authors: Eva Kirzner

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Based on outcome studies published over the past two decades, in 2018, the ACC/AHA published new guidelines for the management of hypercholesterolemia that incorporate the use of coronary artery calcium (CAC) scanning as a decision tool for ascertaining which patients may benefit from statin therapy. This use is based on the recognition that the absence of calcium on CAC scanning (i.e., a CAC score of zero) usually signifies the absence of significant atherosclerotic deposits in the coronary arteries. Specifically, in patients with a high risk for atherosclerotic cardiovascular disease (ASCVD), initiation of statin therapy is generally recommended to decrease ASCVD risk. However, among patients with intermediate ASCVD risk, the need for statin therapy is less certain. However, there is a need for new outcome studies that provide evidence that the management of hypercholesterolemia based on these new ACC/AHA recommendations is safe for patients. Based on a Pub-Med and Google Scholar literature search, four relevant population-based or patient-based cohort studies that studied the relationship between CAC scanning, risk assessment or mortality, and statin therapy that were published between 2017 and 2021 were identified (see references). In each of these studies, patients were assessed for their baseline risk for atherosclerotic cardiovascular disease (ASCVD) using the Pooled Cohorts Equation (PCE), an ACC/AHA calculator for determining patient risk based on assessment of patient age, gender, ethnicity, and coronary artery disease risk factors. The combined findings of these four studies provided concordant evidence that a zero CAC score defines patients who remain at low clinical risk despite the non-use of statin therapy. Thus, these new studies confirm the use of CAC scanning as a safe tool for reducing the potential overuse of statin therapy among patients with zero CAC scores. Incorporating these new data suggest the following best practice: (1) ascertain ASCVD risk according to the PCE in all patients; (2) following an initial attempt trial to lower ASCVD risk with optimal diet among patients with elevated ASCVD risk, initiate statin therapy for patients who have a high ASCVD risk score; (3) if the ASCVD score is intermediate, refer patients for CAC scanning; and (4) and if the CAC score is zero among the intermediate risk ASCVD patients, statin therapy can be safely withheld despite the presence of an elevated serum cholesterol level.

Keywords: cholesterol, cardiovascular disease, statin therapy, coronary calcium

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Authors: Khalid Al Saleh, Najlaa AlSayed

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Background: Palliative care is changing from just ‘end of life care’ to care delivered earlier in the disease course. Metanalysis showed that Palliative Performance Scale (PPS) is associated with increased length of survival. The Palliative Care Center (PCC) in Kuwait is the only stand-alone center in Eastern Mediterranean Region with a capacity of 92 beds. We compared clinical characteristics between patients referred from the Specialized Cancer Center and general hospitals in Kuwait to PCC. Method: A cross Sectional survey was conducted since the opening of PCC in January 2011 to June 2013. Patients’ data on demographics, type of the cancer, PPS score and referring hospital were collected and analyzed. Results: Total number of the patients was 142. Mean age was 61.05±14.79 years, 66 patients (47.1%) were males and 74 (52.9%) were females. The most common cancers in males were lung (n=18, 27.3%) followed by head and neck cancers (n=8, 12.1%) and brain tumors (n=7, 10.6%) while in females, the most common cancers were breast cancer (n=12, 16.7%) followed by ovarian cancer (n=10, 13.9%) and Cancer Colon (n=8, 11.1%). Patients with PPS score 30% were 27.9% (n=39), 40% in 40.7% (n=57), and 50% in 17.1% (n=24) respectively. Patients referred from the Specialized Cancer Center had significantly higher portion of patients with PPS score > 30% (73.4%, n=94), compared to patients coming from general hospitals (33.3%, n=4), P value= 0.007. Conclusion: There is significant difference in PPS scores between patients referred from the Specialized Cancer Center compared to patients referred from general hospitals. We encourage that all cancer patients should be treated in Specialized Cancer Centers and earlier involvement of Palliative Care Centers to achieve better survival. Training workshops are needed for health care professionals working in general hospitals to raise awareness about earlier referral of patients to palliative care services.

Keywords: palliative care, kuwait, performance scale differences, pps score, specialized hospitals

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Authors: Manar Aslan, Ayse Yildiz

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The study was conducted descriptively to assess their hospital institutionalization of upper and mid-level managers of 18 hospitals affiliated to Public Hospitals Association. In its simplest form institutionalization is whatever the subject matter, is dominated by the rules of articulated and determined behavior in all kinds of business, interaction, and communication. Hospital service is a type of service carried out chained together. It should not be forgotten that this kind of services is carried out without barrier, and who and what to do with definite lines, hospital management is a process, and this process can be achieved through institutionalization. With the establishment of the Public Hospitals Unions in Turkey, all the state hospitals in the provinces have been gathered under this roof. One of the goals is to establish control mechanisms to ensure that hospitals reach pre-determined financial, medical, and administrative standards. In this way, the preparations for the institutionalization of units and hospital enterprises will be completed. The data of the study were collected by institutionalization management attitude scale (cronbach alpha: 0.98) of composed of 5 sub-dimensions and 52 questions in 18 hospitals’ managers (N=310) in the largest province in Turkey. The results of the study revealed that the total score taken by managers at the institutionalization scale was 200.80, and this was close to the maximum score. In addition, it was determined that the difference between the mean score of the scale and its sub-dimensions with the gender, the hospitals, and the management position.

Keywords: institutionalization, hospital, manager, evaluation

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Authors: Arezoo Fallahi

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Introduction: Exposure to second-hand smoke is an important global health problem and threatens the health of people, especially children and women. The aim of this study was to determine the effect of education based on the Health Belief Model on preventive behaviors of exposure to secondhand smoke in women. Materials and Methods: This experimental study was performed in 2023in Sanandaj, west of Iran. Seventy-four people were selected by simple random sampling and divided into an intervention group (37 people) and a control group (37 people). Data collection tools included demographic characteristics and a second-hand smoke exposure questionnaire based on the Health Beliefs Model. The training in the intervention group was conducted in three one-hour sessions in the comprehensive health service centers in the form of lectures, pamphlets, and group discussions. Data were analyzed using SPSS software version 21 and statistical tests such as correlation, paired t-test, and independent t-test. Results: The intervention and control groups were homogeneous before education. They were similar in terms of mean scores of the Health Belief Model. However, after an educational intervention, some of the scores increased, including the mean perceived sensitivity score (from 17.62±2.86 to 19.75±1.23), perceived severity score (28.40±4.45 to 31.64±2), perceived benefits score (27.27±4.89 to 31.94±2.17), practice score (32.64±4.68 to 36.91±2.32) perceived barriers from 26.62±5.16 to 31.29±3.34, guide for external action (from 17.70±3.99 to 22/89 ±1.67), guide for internal action from (16.59±2.95 to 1.03±18.75), and self-efficacy (from 19.83 ±3.99 to 23.37±1.43) (P <0.05). Conclusion: The educational intervention designed based on the Health Belief Model in women was effective in performing preventive behaviors against exposure to secondhand smoke.

Keywords: women, health behaviour, smoke, belive

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Authors: Atiwit Sinyoo, Sekh Thanprasertsuk, Sithiporn Agthong, Pasakorn Watanatada, Shaun Peter Qureshi, Saknan Bongsebandhu-Phubhakdi

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Background: Since the SARS-CoV-2 virus became extensively disseminated throughout the world, online learning has become one of the most hotly debated topics in educational reform. While some studies have already shown the advantage of online learning, there are still questions concerning how online learning affects students’ learning behavior and academic achievement when each student learns in a different way. Hence, we aimed to develop a guide for preclinical medical students to avoid drawbacks and get benefits from online learning that possibly a double-edged sword. Methods: We used a multiple-choice questionnaire to evaluate the learning behavior of second-year Thai medical students in the neuroscience course. All traditional face-to-face lecture classes were video-recorded and promptly posted to the online learning platform throughout this course. Students could pick and choose whatever classes they wanted to attend, and they may use online learning as often as they wished. Academic performance was evaluated as summative score, spot exam score and pre-post-test improvement. Results: More frequently students used online learning platform, the less they attended lecture classes (P = 0.035). High proactive online learners (High PO) who were irregular attendee (IrA) had significantly lower summative scores (P = 0.026), spot exam score (P = 0.012) and pre-post-test improvement (P = 0.036). In the meanwhile, conditional attendees (CoA) who only attended classes with attendance check had significantly higher summative score (P = 0.025) and spot exam score (P = 0.001) if they were in the High PO group. Conclusions: The benefit and drawbacks edges of using an online learning platform were demonstrated in our research. Based on this double-edged sword effect, we believe that online learning is a valuable learning strategy, but students must carefully plan their study schedule to gain the “benefit edge” meanwhile avoiding its “drawback edge”.

Keywords: academic performance, assessment, attendance, online learning, preclinical medical students

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Authors: Jing Hu, Dong Yang

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With the increasingly difficult development and operating environment of exploration, there are many new challenges and difficulties in developing and exploiting oil and gas resources. These include the ability to dynamically monitor wells and provide data and assurance for the completion and production of high-cost and complex wells. A key technology in providing these assurances and maximizing oilfield profitability is real-time permanent reservoir monitoring. The emergence of optical fiber sensing systems has gradually begun to replace traditional electronic systems. Traditional temperature sensors can only achieve single-point temperature monitoring, but fiber optic sensing systems based on the Bragg grating principle have a high level of reliability, accuracy, stability, and resolution, enabling cost-effective monitoring, which can be done in real-time, anytime, and without well intervention. Continuous data acquisition is performed along the entire wellbore. The integrated package with the downhole pressure gauge, packer, and surface system can also realize real-time dynamic monitoring of the pressure in some sections of the downhole, avoiding oil well intervention and eliminating the production delay and operational risks of conventional surveys. Real-time information obtained through permanent optical fibers can also provide critical reservoir monitoring data for production and recovery optimization.

Keywords: PDHM, optical fiber, coiled tubing, photoelectric composite cable, digital-oilfield

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Authors: Nitin Lahkar, Rishiraj Goswami

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“Oil Well Logging” or the practice of making a detailed record (a well log) of the geologic formations penetrated by a borehole is an important practice in the Oil and Gas industry. Although a lot of research has been undertaken in this field, some basic limitations still exist. One of the main arenas or venues where plethora of problems arises is in logistically challenged areas. Accessibility and availability of efficient manpower, resources and technology is very time consuming, restricted and often costly in these areas. So, in this regard, the main challenge is to decrease the Non Productive Time (NPT) involved in the conventional logging process. The thought for the solution to this problem has given rise to a revolutionary concept called the “Robotic Logging Technology”. Robotic logging technology promises the advent of successful logging in all kinds of wells and trajectories. It consists of a wireless logging tool controlled from the surface. This eliminates the need for the logging truck to be summoned which in turn saves precious rig time. The robotic logging tool here, is designed such that it can move inside the well by different proposed mechanisms and models listed in the full paper as TYPE A, TYPE B and TYPE C. These types are classified on the basis of their operational technology, movement and conditions/wells in which the tool is to be used. Thus, depending on subsurface conditions, energy sources available and convenience the TYPE of Robotic model will be selected. Advantages over Conventional Logging Techniques: Reduction in Non-Productive time, lesser energy requirements, very fast action as compared to all other forms of logging, can perform well in all kinds of well trajectories (vertical/horizontal/inclined).

Keywords: robotic logging technology, innovation, geology, geophysics

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Authors: Siyamak Sarafraz, Reza Esmaeil Pour, Saeed Jamshidi, Asghar Molaei Dehkordi

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Cutting transport is one of the major problems in directional and extended reach oil and gas wells. Lack of sufficient attention to this issue may bring some troubles such as casing running, stuck pipe, excessive torque and drag, hole pack off, bit wear, decreased the rate of penetration (ROP), increased equivalent circulation density (ECD) and logging. Since it is practically impossible to directly observe the behavior of deep wells, a test setup was designed to investigate cutting transport phenomena. This experimental work carried out to scrutiny behavior of the effective variables in cutting transport. The test setup contained a test section with 17 feet long that made of a 3.28 feet long transparent glass pipe with 3 inch diameter, a storage tank with 100 liters capacity, drill pipe rotation which made of stainless steel with 1.25 inches diameter, pump to circulate drilling fluid, valve to adjust flow rate, bit and a camera to record all events which then converted to RGB images via the Image Processing Toolbox. After preparation of test process, each test performed separately, and weights of the output particles were measured and compared with each other. Observation charts were plotted to assess the behavior of viscosity, flow rate and RPM in inclinations of 0°, 30°, 60° and 90°. RPM was explored with other variables such as flow rate and viscosity in different angles. Also, effect of different flow rate was investigated in directional conditions. To access the precise results, captured image were analyzed to find out bed thickening and particles behave in the annulus. The results of this experimental study demonstrate that drill string rotation helps particles to be suspension and reduce the particle deposition cutting movement increased significantly. By raising fluid velocity, laminar flow converted to turbulence flow in the annulus. Increases in flow rate in horizontal section by considering a lower range of viscosity is more effective and improved cuttings transport performance.

Keywords: cutting transport, directional drilling, flow rate, hole cleaning, pipe rotation

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Authors: Oktavian Prasetia Wardana, Martono Tri Utomo, Risa Etika, Kartika Darma Handayani, Dina Angelika, Wurry Ayuningtyas

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Background: Critically ill neonates are newborn babies with high-risk factors that potentially cause disability and/or death. Scoring systems for determining the severity of the disease have been widely developed as well as some designs for use in neonates. The SNAPPE-II method, which has been used as a mortality predictor scoring system in several referral centers, was found to be slow in assessing the outcome of critically ill neonates in the Neonatal Intensive Care Unit (NICU). Objective: To analyze the predictive value of MSNS on the outcome of critically ill neonates at the time of arrival up to 24 hours after being admitted to the NICU. Methods: A longitudinal observational analytic study based on medical record data was conducted from January to August 2022. Each sample was recorded from medical record data, including data on gestational age, mode of delivery, APGAR score at birth, resuscitation measures at birth, duration of resuscitation, post-resuscitation ventilation, physical examination at birth (including vital signs and any congenital abnormalities), the results of routine laboratory examinations, as well as the neonatal outcomes. Results: This study involved 105 critically ill neonates who were admitted to the NICU. The outcome of critically ill neonates was 50 (47.6%) neonates died, and 55 (52.4%) neonates lived. There were more males than females (61% vs. 39%). The mean gestational age of the subjects in this study was 33.8 ± 4.28 weeks, with the mean birth weight of the subjects being 1820.31 ± 33.18 g. The mean MSNS score of neonates with a deadly outcome was lower than that of the lived outcome. ROC curve with a cut point MSNS score <10.5 obtained an AUC of 93.5% (95% CI: 88.3-98.6) with a sensitivity value of 84% (95% CI: 80.5-94.9), specificity 80 % (CI 95%: 88.3-98.6), Positive Predictive Value (PPV) 79.2%, Negative Predictive Value (NPV) 84.6%, Risk Ratio (RR) 5.14 with Hosmer & Lemeshow test results p>0.05. Conclusion: The MSNS score has a good predictive value and good calibration of the outcomes of critically ill neonates admitted to the NICU.

Keywords: critically ill neonate, outcome, MSNS, NICU, predictive value

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Authors: Ying Jia Teoh

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The Canning Basin is located between the Kimberley and Pilbara Precambrian cratonic blocks. It is a large but relatively poorly explored Paleozoic basin in remote Western Australia. During the early Ordovician period, the Australian continent was located near the equator. Middle Ordovician age Nita and Goldwyer Formations in Canning Basin are therefore warm water carbonates. The Nita Formation carbonates are a regressive sequence which conformably overlies the Goldwyer Formation. It contains numerous progradational cycles of limestone, vuggy dolomitized carbonate beds and shale deposited in subtidal to supratidal environments. The Goldwyer Formation contains transgressive shale sequences and regressive carbonates deposited in shallow subtidal conditions. The shales contain oil-prone Gloeocapsormorpha prisca-bearing source rocks. Llanvirnian relative sea-level fluctuations were reconstructed by using Fischer plots methodology for three key wells (wells McLarty 1, Looma 1 and Robert 1) in Broome Platform and compared with INPEFA data. The Goldwyer lower shale (interval Or1000P) shows increasing relative sea-level and this matches with a transgressive systems tract. Goldwyer middle carbonate (interval Or2000) shows relative sea-level drop and this matches with a regressive systems tract. Goldwyer upper shale (interval Or2000P) shows relative sea-level drop and this matches with a transgressive systems tract. Nita Formation Leo Member (interval Or3000) shows a relative sea level drop and this matches with a regressive systems tract. The Nita Formation Cudalgarra Member (intervals Or3000P and Or4000) with transgressive systems tract then this is followed by a regressive systems tract. This pattern matches with the relative sea-level curves in wells McLarty 1 and Robert 1. The correlation is weak for parts of well Looma 1. This is probably influenced by the fact that the thickness of this section is quite small. As a conclusion, Fischer plots for the Llanvirnian Goldwyer and Nita Formations show good agreement with the third order global sea level cycles of Haq and others. Fischer plots are generally correlated well with trend and cyclicity determined by INPEFA curves and as a method of cross-checking INPEFA data and sea-level change.

Keywords: canning basin, Fischer plots, Llanvirnian, middle Ordovician, sea-level fluctuations, stratigraphy

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Authors: Veronica Sri Lestari, Sitti Nurani Sirajuddin, Kasmiyati Kasim

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The purpose of this research was to know the attitude of beef cattle farmers toward bio security practices. This research was conducted in Barru regency, South Sulawesi province, Indonesia, in 2014. Thirty beef cattle farmers were selected through random sampling. Primary and secondary data were collected through report, observation and deep interview by using questionnaire. Bio security practices consisted of 35 questions. Every answer of the question was scored based on three categories: score 1 (not important), score 2 (important) and 3 (very important). The results of this research showed that the attitude of beef cattle farmers toward bio security practices was categorized as important.

Keywords: attitude, beef cattle, biosecurity, farmers

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Authors: B. Mendonça, D. Sandwell

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The Metropolitan Region of Sao Paulo (MRSP) has suffered from serious water scarcity. Consequently, the most convenient solution has been building wells to extract groundwater from local aquifers. However, it requires constant vigilance to prevent over extraction and future events that can pose serious threat to the population, such as subsidence. Radar imaging techniques (InSAR) have allowed continuous investigation of such phenomena. The analysis of data in the present study consists of 23 SAR images dated from October 2007 to March 2011, obtained by the ALOS-1 spacecraft. Data processing was made with the software GMTSAR, by using the InSAR technique to create pairs of interferograms with ground displacement during different time spans. First results show a correlation between the location of 102 wells registered in 2009 and signals of ground displacement equal or lower than -90 millimeters (mm) in the region. The longest time span interferogram obtained dates from October 2007 to March 2010. As a result, from that interferogram, it was possible to detect the average velocity of displacement in millimeters per year (mm/y), and which areas strong signals have persisted in the MRSP. Four specific areas with signals of subsidence of 28 mm/y to 40 mm/y were chosen to investigate the phenomenon: Guarulhos (Sao Paulo International Airport), the Greater Sao Paulo, Itaquera and Sao Caetano do Sul. The coverage area of the signals was between 0.6 km and 1.65 km of length. All areas are located above a sedimentary type of aquifer. Itaquera and Sao Caetano do Sul showed signals varying from 28 mm/y to 32 mm/y. On the other hand, the places most likely to be suffering from stronger subsidence are the ones in the Greater Sao Paulo and Guarulhos, right beside the International Airport of Sao Paulo. The rate of displacement observed in both regions goes from 35 mm/y to 40 mm/y. Previous investigations of the water use at the International Airport highlight the risks of excessive water extraction that was being done through 9 deep wells. Therefore, it is affirmed that subsidence events are likely to occur and to cause serious damage in the area. This study could show a situation that has not been explored with proper importance in the city, given its social and economic consequences. Since the data were only available until 2011, the question that remains is if the situation still persists. It could be reaffirmed, however, a scenario of risk at the International Airport of Sao Paulo that needs further investigation.

Keywords: ground subsidence, Interferometric Satellite Aperture Radar (InSAR), metropolitan region of Sao Paulo, water extraction

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Authors: Fatma Abdel Moneim Al Tawil

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This study was undertaken to evaluate an educational program regarding scientific writing and presentation skills among university students. This interventional study used a one-group, pretest/posttest design and was conducted in Al Jouf University among four colleges in Saudi Arabia. Baseline students’ assessment was conducted for developing educational program. Interventional, one group, pretest/posttest study was designed to evaluate the effectiveness of the educational program. Three parts evaluation sheet with total scores of 30 was used for 113 students for the development of the program and 52 students for test pretest phase. Wilcoxon signed ranks showed statistically significant improvement in the combined overall program skills score from a median of 56.7 pre to a median of 86.7 post, (z = 6.231, p < 0.001). When compared to preprogram intervention, post interventions 51.9 % of students achieve excellent performance. While pre intervention no students (0.0 %) achieve this score. Regarding to scientific writing skills, Wilcoxon signed ranks showed statistically significant improvement in the score from a median of 60 pre to a median of 90 post, (z = 6.122, p < 0.001). None of students had excellent performance changed to 73.1%. Regarding to oral presentation skills, Wilcoxon signed ranks showed statistically significant improvement in the score from a median of 50 pre to a median of 80 post, (z = 6.153, p < 0.001). None of students had excellent performance changed to 48.1%. Such educational program needs to be incorporated into classroom delivery of the students’ curriculum. Scientific writing skills book needed to be developed to be recommended as a basic educational strategy for all university faculties.

Keywords: scientific writing, presentation skills, university students, educational program

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Authors: S. Lakel, F. Elhamra, M. Ibrir, K. Almi

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There is a growing interest in Zn1-xBexO (ZBO)/ZnO hetero structures and quantum wells since the band gap energy of Zn1-xBexO solid solutions can be turned over a very large range (3.37–10.6 eV) as a function of the Be composition. ZBO/ZnO has been utilized in ultraviolet light emission diodes and lasers, and may find applications as active elements of various other electronic and optoelectronic devices. Band gap engineering by Be substitution enables the facile preparation of barrier layers and quantum wells in device structures. In addition, ZnO and its ternary alloys, as piezoelectric semiconductors, have been used for high-frequency surface acoustic wave devices in wireless communication systems due to their high acoustic velocities and large electromechanical coupling. However, many important parameters such as elastic constants, bulk modulus, Young’s modulus and band-gap bowing. First-principles calculations of the structural, electrical and elastic properties of Zn1-xBexO as a function of the Be concentration x have been performed within density functional theory using norm-conserving pseudopotentials and local density approximation (LDA) for the exchange and correlation energy. The alloys’ lattice constants may deviate from the Vegard law. As Be concentration increases, the elastic constants, the bulk modulus and Young’s modulus of the alloys increase, the band gap increases with increasing Be concentration and Zn1-xBexO alloys have direct band. Our calculated results are in good agreement with experimental data and other theoretical calculations.

Keywords: DFT calculation, norm-conserving pseudopotentials, ZnBeO alloys, ZnO

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Authors: Qing Wu, Xuchun Ye, Qiuchen Wang, Kirsten Corazzini

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Objective: It’s increasing acknowledged that patient engagement in healthcare and health literacy both have positive impact on patient outcome. Health literacy emphasizes the ability of individuals to understand and apply health information and manage health. Patients' health literacy affected their willingness to participate in decision-making, but its impact on the behavior and willingness of patient engagement in healthcare is not clear, especially in China. Therefore, this study aimed to explore the correlation between the behavior and willingness of patient engagement and health literacy. Methods: A cross-sectional survey was employed using the behavior and willingness of patient engagement in healthcare questionnaire, Chinese version All Aspects of Health Literacy Scale (AAHLS). A convenient sample of 443 patients was recruited from 8 general hospitals in Shanghai, Jiangsu Province and Zhejiang Province, from September 2016 to January 2017. Results: The mean score for the willingness was (4.41±0.45), and the mean score for the patient engagement behavior was (4.17±0.49); the mean score for the patient's health literacy was (2.36±0.29)，the average score of its three dimensions- the functional literacy, the Communicative/interactive literacy and the Critical literacy, was (2.26±0.38), (2.28±0.42), and (2.61±0.43), respectively. Patients' health literacy was positively correlated with their willingness of engagement (r = 0.367, P < 0.01), and positively correlated with patient engagement behavior (r = 0.357, P < 0.01). All dimensions of health literacy were positively correlated with the behavior and willingness of patient engagement in healthcare; the dimension of Communicative/interactive literacy (r = 0.312, P < 0.01; r = 0.357, P < 0.01) and the Critical literacy (r = 0.357, P < 0.01; r = 0.357, P < 0.01) are more relevant to the behavior and willingness than the dimension of basic/functional literacy (r=0.150, P < 0.01; r = 0.150, P < 0.01). Conclusions: The behavior and willingness of patient engagement in healthcare are positively correlated with health literacy and its dimensions. In clinical work, medical staff should pay attention to patients’ health literacy, especially the situation that low literacy leads to low participation and provide health information to patients through health education or communication to improve their health literacy as well as guide them to actively and rationally participate in their own health care.

Keywords: patient engagement, health literacy, healthcare, correlation

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Authors: Raman Sharma, S. K. Jain

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Aims and Objectives: Fixation of the mesh during laparoscopic total extraperitoneal (TEP) repair of inguinal hernia is thought to be necessary to prevent recurrence. However, mesh fixation may increase surgical complications and postoperative pain. Our objective was to compare the outcomes of nonfixation with fixation of polypropylene mesh by metal tacks during TEP repair of inguinal hernia. Methods: Forty patients aged 18 to72 years with inguinal hernia were included who underwent laparoscopic TEP repair of inguinal hernia with (n=20) or without (n=20) fixation of the mesh. The outcomes were operative duration, postoperative pain score, cost, in-hospital stay, time to return to normal activity, and complications. Results: Patients in whom the mesh was not fixed had shorter mean operating time (p < 0.05). We found no difference between groups in the postoperative pain score, incidence of recurrence, in-hospital stay, time to return to normal activity and complications (P > 0.05). Moreover, a net cost savings was realized for each hernia repair performed without stapled mesh. Conclusions: TEP repair without mesh fixation resulted in the shorter operating time and lower operative cost with no difference between groups in the postoperative pain score, incidence of recurrence, in-hospital stay, time to return to normal activity and complications. All this contribute to make TEP repair without mesh fixation a better choice for repair of uncomplicated inguinal hernia, especially in developing nations with scarce resources.

Keywords: postoperative pain score, inguinal hernia, nonfixation of mesh, total extra peritoneal (TEP)

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Authors: Arezoo Fallahi

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Introduction: Exposure to second-hand smoke is an important global health problem and threatens the health of people, especially children and women. The aim of this study was to determine the effect of education based on the Health Belief Model on preventive behaviors of exposure to second-hand smoke in women. Materials and Methods: This experimental study was performed in 2022 in Sanandaj, west of Iran. Seventy-four people were selected by simple random sampling and divided into an intervention group (37 people) and a control group (37 people). Data collection tools included demographic characteristics and a second-hand smoke exposure questionnaire based on the Health Beliefs Model. The training in the intervention group was conducted in three one-hour sessions in the comprehensive health service centers in the form of lectures, pamphlets, and group discussions. Data were analyzed using SPSS software version 21 and statistical tests such as correlation, paired t-test, and independent t-test. Results: The intervention and control groups were homogeneous before education. They were similar in terms of mean scores of the Health Belief Model. However, after an educational intervention, some of the scores increased, including the mean perceived sensitivity score (from 17.62±2.86 to 19.75±1.23), perceived severity score (28.40±4.45 to 31.64±2), perceived benefits score (27.27±4.89 to 31.94±2.17), practice score (32.64±4.68 to 36.91±2.32) perceived barriers from 26.62±5.16 to 31.29±3.34, guide for external action (from 17.70±3.99 to 22/89 ±1.67), guide for internal action from (16.59±2.95 to 1.03±18.75), and self-efficacy (from 19.83 ±3.99 to 23.37±1.43) (P <0.05). Conclusion: The educational intervention designed based on the Health Belief Model in women was effective in performing preventive behaviors against exposure to second-hand smoke.

Keywords: education, women, exposure to secondhand smoke, health belief model

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Authors: Nopadol Burananat, Kedsara Tripaichayonsak

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This research aims to study the level of expectations and participation of personnel in implementing educational quality assurance of programs in Graduate School, Rajabhat Suan Sunandha University. The sample used in this study is 60 participants. The tool used for data collection is a questionnaire constructed by the researcher. The analysis is done by frequency, percentage, mean and standard deviation. It was found that the level of expectations personnel in Graduate School, Suan Sunandha Rajabhat University in implementing educational quality assurance is at high level. The category which received the most score is Action, followed by Check, Do and Plan, respectively. For the level of participation of personnel at program level of Graduate School, Suan Sunandha Rajabhat University in implementing educational quality assurance, the overall score is at high level. The category which received the most score is Action, followed by Do, Check and Plan, respectively.

Keywords: participation, implementation of educational quality assurance, educational quality assurance, expectations and participation

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Authors: Semachew M. Kassa, Africa M Geremew, Tezera F. Azmatch, Nandyala Darga Kumar

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Frequency ratio (FR) and analytical hierarchy process (AHP) methods are developed based on past landslide failure points to identify the landslide susceptibility mapping because landslides can seriously harm both the environment and society. However, it is still difficult to select the most efficient method and correctly identify the main driving factors for particular regions. In this study, we used fourteen landslide conditioning factors (LCFs) and five soft computing algorithms, including Random Forest (RF), Support Vector Machine (SVM), Logistic Regression (LR), Artificial Neural Network (ANN), and Naïve Bayes (NB), to predict the landslide susceptibility at 12.5 m spatial scale. The performance of the RF (F1-score: 0.88, AUC: 0.94), ANN (F1-score: 0.85, AUC: 0.92), and SVM (F1-score: 0.82, AUC: 0.86) methods was significantly better than the LR (F1-score: 0.75, AUC: 0.76) and NB (F1-score: 0.73, AUC: 0.75) method, according to the classification results based on inventory landslide points. The findings also showed that around 35% of the study region was made up of places with high and very high landslide risk (susceptibility greater than 0.5). The very high-risk locations were primarily found in the western and southeastern regions, and all five models showed good agreement and similar geographic distribution patterns in landslide susceptibility. The towns with the highest landslide risk include Amhara Saint Town's western part, the Northern part, and St. Gebreal Church villages, with mean susceptibility values greater than 0.5. However, rainfall, distance to road, and slope were typically among the top leading factors for most villages. The primary contributing factors to landslide vulnerability were slightly varied for the five models. Decision-makers and policy planners can use the information from our study to make informed decisions and establish policies. It also suggests that various places should take different safeguards to reduce or prevent serious damage from landslide events.

Keywords: artificial neural network, logistic regression, landslide susceptibility, naïve Bayes, random forest, support vector machine

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Authors: Sakshi Dhumale, Madhushree C., Amba Shetty

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The effect of station density on the geostatistical prediction of groundwater levels is of critical importance to ensure accurate and reliable predictions. Monitoring station density directly impacts the accuracy and reliability of geostatistical predictions by influencing the model's ability to capture localized variations and small-scale features in groundwater levels. This is particularly crucial in regions with complex hydrogeological conditions and significant spatial heterogeneity. Insufficient station density can result in larger prediction uncertainties, as the model may struggle to adequately represent the spatial variability and correlation patterns of the data. On the other hand, an optimal distribution of monitoring stations enables effective coverage of the study area and captures the spatial variability of groundwater levels more comprehensively. In this study, we investigate the effect of station density on the predictive performance of groundwater levels using the geostatistical technique of Ordinary Kriging. The research utilizes groundwater level data collected from 121 observation wells within the semi-arid Berambadi watershed, gathered over a six-year period (2010-2015) from the Indian Institute of Science (IISc), Bengaluru. The dataset is partitioned into seven subsets representing varying sampling densities, ranging from 15% (12 wells) to 100% (121 wells) of the total well network. The results obtained from different monitoring networks are compared against the existing groundwater monitoring network established by the Central Ground Water Board (CGWB). The findings of this study demonstrate that higher station densities significantly enhance the accuracy of geostatistical predictions for groundwater levels. The increased number of monitoring stations enables improved interpolation accuracy and captures finer-scale variations in groundwater levels. These results shed light on the relationship between station density and the geostatistical prediction of groundwater levels, emphasizing the importance of appropriate station densities to ensure accurate and reliable predictions. The insights gained from this study have practical implications for designing and optimizing monitoring networks, facilitating effective groundwater level assessments, and enabling sustainable management of groundwater resources.

Keywords: station density, geostatistical prediction, groundwater levels, monitoring networks, interpolation accuracy, spatial variability

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Authors: Dharmit Viroja, Prerakkumar Shah, Rajanikant Gajera, Ruchit Shah

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With present scenario of aging oil and gas fields with high water cuts, volatile oil prices and increasing greenhouse gas emission, the need for alleviating such issues has necessitated for oil and gas industry to make the maximum out of available assets, infrastructure and reserves in mother Earth. Study undertaken emphasizes on utilizing Geothermal Energy under specific reservoir conditions for Enhanced oil Recovery (EOR) to boost up production. Allied benefits of this process include mitigation of electricity problem in remote fields and controlled CO-emission. Utilization of this energy for EOR and increasing economic life of field could surely be rewarding. A new way to value oil lands would be considered if geothermal co-production is integrated in the field development program. Temperature profile of co-produced fluid across its journey is a pivotal issue which has been studied. Geo pressured reservoirs resulting from trapped brine under an impermeable bed is also a frontier for exploitation. Hot geothermal fluid is a by-product of large number of oil and gas wells, historically this hot water has been seen as an inconvenience; however, it can be looked at as a useful resource. The production of hot fluids from abandoned and co-production of hot fluids from producing wells has potential to prolong life of oil and gas fields. The study encompasses various factors which are required for use of this technology and application of this process across various phases of oil and gas value chain. Interdisciplinary approach in oil and gas value chain has shown potential for economic production of estimated oil and gas reserves.

Keywords: enhanced oil recovery, geo-pressured reservoirs, geothermal energy, oil and gas value chain

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Authors: Makram Ben Jeddou

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The ABC classification is widely used by managers for inventory control. The classical ABC classification is based on the Pareto principle and according to the criterion of the annual use value only. Single criterion classification is often insufficient for a closely inventory control. Multi-criteria inventory classification models have been proposed by researchers in order to take into account other important criteria. From these models, we will consider the ZF model in order to make a sensitive analysis on the composite score calculated for each item. In fact, this score based on a normalized average between a good and a bad optimized index can affect the ABC items classification. We will then focus on the weights assigned to each index and propose a classification compromise.

Keywords: ABC classification, multi criteria inventory classification models, ZF-model

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Authors: Zhidong Zhang

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This study established a mixed method model in assessing statistics learning with Bayesian network models. There are three variants in exploratory sequential designs. There are three linked steps in one of the designs: qualitative data collection and analysis, quantitative measure, instrument, intervention, and quantitative data collection analysis. The study used a scoring model of analysis of variance (ANOVA) as a content domain. The research study is to examine students’ learning in both semantic and performance aspects at fine grain level. The ANOVA score model, y = α+ βx1 + γx1+ ε, as a cognitive task to collect data during the student learning process. When the learning processes were decomposed into multiple steps in both semantic and performance aspects, a hierarchical Bayesian network was established. This is a theory-driven process. The hierarchical structure was gained based on qualitative cognitive analysis. The data from students’ ANOVA score model learning was used to give evidence to the hierarchical Bayesian network model from the evidential variables. Finally, the assessment results of students’ ANOVA score model learning were reported. Briefly, this was a mixed method research design applied to statistics learning assessment. The mixed methods designs expanded more possibilities for researchers to establish advanced quantitative models initially with a theory-driven qualitative mode.

Keywords: exploratory sequential design, ANOVA score model, Bayesian network model, mixed methods research design, cognitive analysis

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Authors: Urmi Khatri

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Capital asset pricing model (CAPM) draws a direct relationship between the risk and the expected rate of return. There was a criticism on the beta and the assumptions of CAPM, as they are not applicable in the real world. Fama French Three Factor Model and Fama French Five Factor Model have given different factors, which have an impact on the return of any asset like size, value, investment and profitability. This study proposes to see Capital Asset pricing Model through the lenses of the quality aspect. In the study, the six factors are studied. The Fama French Five Factor Model and addition of the quality dimension are studied. Here, Graham’s seven quality and quantity criteria are measured to determine the score of the sample firms. Thus, this study tries to check the model fit. The beta coefficient of the quality dimension and the R square value is seen to determine validity of the proposed model. The sample is drawn from the firms listed on Indian Stock Exchange (BSE). For the study, only nonfinancial firms are been selected. The time period of the study is from January 1999 to December 2019. Hence, the primary objective of the study is to check how robust the model becomes after giving the quality dimension to the capital asset pricing model in addition to the size, value, profitability and investment.

Keywords: asset pricing model, CAPM, Graham’s score, G-score, multifactor model, quality

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Authors: Riona Dighe

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This research attempts to identify an alternative approach to the measurement of Gross National Happiness (GNH). It uses artificial intelligence (AI), incorporating natural language processing (NLP) and sentiment analysis to measure GNH. We use ‘off the shelf’ NLP models responsible for the sentiment analysis of a sentence as a building block for this research. We constructed an algorithm using NLP models to derive a sentiment analysis score against sentences. This was then tested against a sample of 20 respondents to derive a sentiment analysis score. The scores generated resembled human responses. By utilising the MLP classifier, decision tree, linear model, and K-nearest neighbors, we were able to obtain a test accuracy of 89.97%, 54.63%, 52.13%, and 47.9%, respectively. This gave us the confidence to use the NLP models against sentences in websites to measure the GNH of a country.

Keywords: artificial intelligence, NLP, sentiment analysis, gross national happiness

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Authors: Khawla Saad Albalawi

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The aim of this research was to explore the effectiveness of the internet counseling in reducing social shyness among the university's students. The sample consisted of 40 students and was divided into two groups: an experimental group and a control group. The social shyness scale (SSS) was administered to both groups before applying the counseling to the experimental group (as a pre-test). After that, the internet counseling was applied to the experimental group. Next, the SSS was administered to both groups (as a post-test). Finally, the SSS was administered to the experimental group (as an iterative application). Results suggest that: 1. There is a significant difference between the two groups in the post-test in all dimensions and the total score of the (SSS) in favor of the experimental group in all cases. 2. There is a significant difference between the pre- and the post-test of the experimental group in all dimensions and the total score of the (SSS) in favor of the post-test in all cases. 3. There is no significant difference between the post-test and the iterative application of the experimental group in all dimensions and the total score of the (SSS). The above results were discussed in light of previous research. Recommendations and future researches were suggested.

Keywords: internet psychological clinics, social interaction disorders, shyness, Twitter, Facebook

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Authors: Tahmidul Islam

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Propensity Score Matching (PSM) technique has been widely used for estimating causal effect of treatment in observational studies. One major step of implementing PSM is estimating the propensity score (PS). Logistic regression model with additive linear terms of covariates is most used technique in many studies. Logistics regression model is also used with cubic splines for retaining flexibility in the model. However, choosing the functional form of the logistic regression model has been a question since the effectiveness of PSM depends on how accurately the PS been estimated. In many situations, the linearity assumption of linear logistic regression may not hold and non-linear relation between the logit and the covariates may be appropriate. One can estimate PS using machine learning techniques such as random forest, neural network etc for more accuracy in non-linear situation. In this study, an attempt has been made to compare the efficacy of Generalized Additive Model (GAM) in various linear and non-linear settings and compare its performance with usual logistic regression. GAM is a non-parametric technique where functional form of the covariates can be unspecified and a flexible regression model can be fitted. In this study various simple and complex models have been considered for treatment under several situations (small/large sample, low/high number of treatment units) and examined which method leads to more covariate balance in the matched dataset. It is found that logistic regression model is impressively robust against inclusion quadratic and interaction terms and reduces mean difference in treatment and control set equally efficiently as GAM does. GAM provided no significantly better covariate balance than logistic regression in both simple and complex models. The analysis also suggests that larger proportion of controls than treatment units leads to better balance for both of the methods.

Keywords: accuracy, covariate balances, generalized additive model, logistic regression, non-linearity, propensity score matching

Procedia PDF Downloads 339