Search results for: propensity score matching
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2574

Search results for: propensity score matching

564 The Risk of Post-stroke Pneumonia and Its One-Year Disability in Taiwan

Authors: Hui-Chi Huang, Su-Ju Yang, Ching-Wei Lin, Jui-Yao Tsai, Liang-Yiang

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Background: Evidence exists that pneumonia is a frequently encountered complication after stroke which is associated with a higher rate of mortality and increased long-term disability Purpose: To determine the predictors associated with the risk of one-year disability in acute stroke. Methods: Data for this longitudinal follow-up study were extracted from a tertiary referral medical center’s stroke registry database in Northern Taipei. Eligible patients with acute stroke admitted to the hospital and completed a one-year follow up were recruited for analysis. Favorable outcome was defined as a modified Rankin Scale score ≤ 2. SAS version 9.2 was used for the multivariable regression analyses to examine the factors correlated with the one-year disability in stroke patients. Results: From January 2012 to December 2013, a total of 1373 (mean age: 70.49±15.4 years, 913(66.5%) males) consecutively administered acute stroke patients were recruited. Overall, the rate of one-year disability was 37.20%(404/1086) in those without post-stroke pneumonia. It increased to 82.93 %(238/287) in patients developed post-stroke pneumonia. Factors associated with increased risk of disability were age ≧ 75(OR= 4.845, p<.0001), female /gender (OR=1.568, p =.0062), previous stroke (OR= 1.868, p = <. 0001) ,dementia (OR= 2.872, p =.0047), ventilator use (OR= 4.653, p <. 0001),age ≧ 75 /pneumonia (OR=1.236, p <. 0001) , ICU admission (OR=3.314, p <.0001) , nasogastric tube insertion (OR= 4.28, p <.0001), speech therapy (OR= 1.79, p =.0142), urinary tract infection (OR= 1.865, p =.0018), estimated glomerular filtration rate (eGFR > 60 )(OR= 0.525, p= .0029), Admission NIHSS >11 (OR= 2.101, p = .0099), Length of hospitalization > 30(d) (OR= 5.182, p <.0001). Conclusion: Older age, severe neurological deficit, complications, rehabilitation intervention, length of hospitalization >30(d), and cognitive impairment were significantly associated with Post-stroke functional impairment, especially those with post-stroke pneumonia. These findings could open new avenues in the management of stroke patients.

Keywords: stroke, risk, pneumonia, disability

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563 The Effectiveness of Sleep Behavioral Interventions during the Third Trimester of Pregnancy on Sleep Quality and Postpartum Depression in a Randomized Clinical Controlled Trial

Authors: Somaye Ghafarpour, Kamran Yazdanbakhsh, Mohamad Reza Zarbakhsh, Simin Hosseinian, Samira Ghafarpour

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Unsatisfactory sleep quality is one of the most common complications of pregnancy, which can predispose mothers to postpartum depression, requiring implementing effective psychological interventions to prevent and modify behaviors accentuating sleep problems. This study was a randomized clinical controlled trial with a pre-test/post-test design aiming to investigate the effectiveness of sleep behavioral interventions during the third trimester of pregnancy on sleep quality and postpartum depression. A total of 50 pregnant mothers in the 26-30 weeks of pregnancy suffering from sleep problems (based on the score obtained from the Pittsburgh Sleep Questionnaire) were randomized into two groups (control and intervention, n= 25 per group). The data were collected using interviews, the Pittsburgh Sleep Quality Index (PSQI), and the Edinburgh Postnatal Depression Scale (EPDS) were used. The participants in the intervention group received eight 60-minute sessions of combinational training for behavioral therapy techniques. At the end of the intervention and four weeks after delivery, sleep quality and postpartum depression were evaluated. Considering that the Kolmogorov Smirnov test confirmed the normal distribution of the data, the independent t-test and analysis of covariance were used to analyze the data, showing that the behavioral interventions were effective on the overall sleep quality after delivery (p=0.001); however, no statistically significant effects were observed on postpartum depression, the sub-scales of sleep disorders, and daily functioning (p>0.05). Considering the potential effectiveness of behavioral interventions in improving sleep quality and alleviating insomnia symptoms, it is recommended to implement such measures as an effective intervention to prevent or treat these problems during prenatal and postnatal periods.

Keywords: behavioral interventions, sleep quality, postpartum depression, pregnancy, delivery

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562 Geographic Information System Based Development Potentiality Assessment for Rural Villages: Case Study in Fuliang County, Jingdezhen

Authors: Sishen Wang

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Chinese rural industry development is the major task currently during rapid urbanization. Development of potentiality assessment, evaluate the overall suitability of each village for further industrial development, could offer reference for policy makers, especially considering the limited data available in Chinese rural regions. The study focuses on 157 official villages in Fuliang County and evaluates their development potentiality by their topography, transportation condition, population, income of villagers, infrastructure and environmental conditions. Land cover changes for Fuliang county and surrounding areas of each village is also investigated for reference. The final development potentiality of each village was calculated by adding different weighted scores of different categories. Besides, inverse distance weighting (IDW) images for both final score of development potentiality and each factor were made and compared to help to understand the final result. The study found that village in the southern and northern regions have higher development potentiality than villages in the eastern and western regions, mainly because of higher income of villagers, good accessibilities and a large amount of population size. In addition, the Fuliang county was divided into five regions based on final result and policy reference for the development of each region were put forward individually. In addition, three suggestions were made for better local development potentiality: Firstly, the transportation accessibility needs to be improved in the northern regions by building more public transit system there. Secondly, the environmental conditions and infrastructure conditions in the eastern region of the county need some improvement. Thirdly, some encouragement and job opportunities should beset up in the western regions to attract labor force to move in and settle down.

Keywords: development potentiality, Fuliang GIS-Based, GIS, official village

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561 Revised Risk Priority Number in Failure Mode and Effects Analysis Model from the Perspective of Healthcare System

Authors: Fatemeh Rezaei, Mohammad H. Yarmohammadian, Masoud Ferdosi, Abbas Haghshnas

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Background: Failure Modes and Effect Analysis is now having known as the main methods of risk assessment and the accreditation requirements for many organizations. The Risk Priority Number (RPN) approach is generally preferred, especially for its easiness of use. Indeed it does not require statistical data, but it is based on subjective evaluations given by the experts about the Occurrence (O i), the Severity (Si) and the Detectability (D i) of each cause of failure. Methods: This study is a quantitative – qualitative research. In terms of qualitative dimension, method of focus groups with inductive approach is used. To evaluate the results of the qualitative study, quantitative assessment was conducted to calculate RPN score. Results; We have studied patient’s journey process in surgery ward and the most important phase of the process determined Transport of the patient from the holding area to the operating room. Failures of the phase with the highest priority determined by defining inclusion criteria included severity (clinical effect, claim consequence, waste of time and financial loss), occurrence (time- unit occurrence and degree of exposure to risk) and preventability (degree of preventability and defensive barriers) and quantifying risks priority criteria in the context of RPN index. Ability of improved RPN reassess by root cause (RCA) analysis showed some variations. Conclusions: Finally, It could be concluded that understandable criteria should have been developed according to personnel specialized language and communication field. Therefore, participation of both technical and clinical groups is necessary to modify and apply these models.

Keywords: failure mode, effects analysis, risk priority number(RPN), health system, risk assessment

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560 Phenotypic Characterisation of Bapedi Sheep Breed

Authors: Fhulufhelo Ramukhithi, Kgothatso Masethe, Tlou Chokoe, Ayanda Maqhashu, Julius Sebei, Tshililo Raphulu, Joseph Mugwabana

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Phenotypic characterisation ensures that the physical appearance of an animal is well documented. The information provided by this phenotypic characterisation study is important for planning management and the use of animal genetic resources. The aim of this study was to characterise the phenotypic characteristics of Bapedi sheep. Bapedi sheep are at risk of extinction like most of the indigenous breeds. As a result, a total of 196 Bapedi ewes and 35 rams were used. Phenotypic-qualitative characteristics were evaluated through visual appraisal. Phenotypic-quantitative characteristics such as body parts measurements were obtained using a flexible tape (cm), while body weight were obtained by using a weighing scale (kg). Bapedi rams (97 %) had higher satisfactory body condition when compared to ewes (75 %). A higher proportion of Bapedi sheep that did not have ticks observed (ewes = 87 % and rams = 91 %). Brown and white colour combination (head x body) was dominating in Bapedi sheep (80 % ewes and 91 % rams). Bapedi ewes did not have any horns; however, 3 % of rams had them. Bapedi sheep had a higher proportion of brown eyes, moderate neck, stiff sideways ears and normal front legs. Bapedi rams had a higher proportion of well-balanced and good attached testicles. Bapedi ewes had average (45 %), small (40 %) and big udders (15 %). Bapedi rams had a significantly higher body weight, height, depth, hearth girth circumference, rump width, hind leg width and length compared to ewes. However, both Bapedi rams and ewes had similar age, body condition score, tail length, length below hock and knee. In conclusion, Bapedi sheep had a higher satisfactory body condition and brown and white colour combination. Some of Bapedi rams’ quantitative characteristics were higher compared to ewes.

Keywords: extinction, indigenous, phenotypic, smallstock

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559 Sentiment Analysis of Fake Health News Using Naive Bayes Classification Models

Authors: Danielle Shackley, Yetunde Folajimi

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As more people turn to the internet seeking health-related information, there is more risk of finding false, inaccurate, or dangerous information. Sentiment analysis is a natural language processing technique that assigns polarity scores to text, ranging from positive, neutral, and negative. In this research, we evaluate the weight of a sentiment analysis feature added to fake health news classification models. The dataset consists of existing reliably labeled health article headlines that were supplemented with health information collected about COVID-19 from social media sources. We started with data preprocessing and tested out various vectorization methods such as Count and TFIDF vectorization. We implemented 3 Naive Bayes classifier models, including Bernoulli, Multinomial, and Complement. To test the weight of the sentiment analysis feature on the dataset, we created benchmark Naive Bayes classification models without sentiment analysis, and those same models were reproduced, and the feature was added. We evaluated using the precision and accuracy scores. The Bernoulli initial model performed with 90% precision and 75.2% accuracy, while the model supplemented with sentiment labels performed with 90.4% precision and stayed constant at 75.2% accuracy. Our results show that the addition of sentiment analysis did not improve model precision by a wide margin; while there was no evidence of improvement in accuracy, we had a 1.9% improvement margin of the precision score with the Complement model. Future expansion of this work could include replicating the experiment process and substituting the Naive Bayes for a deep learning neural network model.

Keywords: sentiment analysis, Naive Bayes model, natural language processing, topic analysis, fake health news classification model

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558 Autoimmune Diseases Associated with Primary Biliary Cirrhosis: A Retrospective Study of 51 Patients

Authors: Soumaya Mrabet, Imen Akkari, Amira Atig, Elhem Ben Jazia

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Introduction: Primary biliary cirrhosis (PBC) is a cholestatic cholangitis of unknown etiology. It is frequently associated with autoimmune diseases, which explains their systematic screening. The aim of our study was to determine the prevalence and the type of autoimmune disorders associated with PBC and to assess their impact on the prognosis of the disease. Material and methods: It is a retrospective study over a period of 16 years (2000-2015) including all patients followed for PBC. In all these patients we have systematically researched: dysthyroidism (thyroid balance, antithyroid autoantibodies), type 1 diabetes, dry syndrome (ophthalmologic examination, Schirmer test and lip biopsy in case of Presence of suggestive clinical signs), celiac disease(celiac disease serology and duodenal biopsies) and dermatological involvement (clinical examination). Results: Fifty-one patients (50 women and one men) followed for PBC were collected. The Mean age was 54 years (37-77 years). Among these patients, 30 patients(58.8%) had at least one autoimmune disease associated with PBC. The discovery of these autoimmune diseases preceded the diagnosis of PBC in 8 cases (26.6%) and was concomitant, through systematic screening, in the remaining cases. Autoimmune hepatitis was found in 12 patients (40%), defining thus an overlap syndrome. Other diseases were Hashimoto's thyroiditis (n = 10), dry syndrome (n = 7), Gougerot Sjogren syndrome (n=6), celiac disease (n = 3), insulin-dependent diabetes (n = 1), scleroderma (n = 1), rheumatoid arthritis (n = 1), Biermer Anemia (n=1) and Systemic erythematosus lupus (n=1). The two groups of patients with PBC with or without associated autoimmune disorders were comparable for bilirubin levels, Child-Pugh score, and response to treatment. Conclusion: In our series, the prevalence of autoimmune diseases in PBC was 58.8%. These diseases were dominated by autoimmune hepatitis and Hashimoto's thyroiditis. Even if their association does not seem to alter the prognosis, screening should be systematic in order to institute an early and adequate management.

Keywords: autoimmune diseases, autoimmune hepatitis, primary biliary cirrhosis, prognosis

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557 A Radiomics Approach to Predict the Evolution of Prostate Imaging Reporting and Data System Score 3/5 Prostate Areas in Multiparametric Magnetic Resonance

Authors: Natascha C. D'Amico, Enzo Grossi, Giovanni Valbusa, Ala Malasevschi, Gianpiero Cardone, Sergio Papa

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Purpose: To characterize, through a radiomic approach, the nature of areas classified PI-RADS (Prostate Imaging Reporting and Data System) 3/5, recognized in multiparametric prostate magnetic resonance with T2-weighted (T2w), diffusion and perfusion sequences with paramagnetic contrast. Methods and Materials: 24 cases undergoing multiparametric prostate MR and biopsy were admitted to this pilot study. Clinical outcome of the PI-RADS 3/5 was found through biopsy, finding 8 malignant tumours. The analysed images were acquired with a Philips achieva 1.5T machine with a CE- T2-weighted sequence in the axial plane. Semi-automatic tumour segmentation was carried out on MR images using 3DSlicer image analysis software. 45 shape-based, intensity-based and texture-based features were extracted and represented the input for preprocessing. An evolutionary algorithm (a TWIST system based on KNN algorithm) was used to subdivide the dataset into training and testing set and select features yielding the maximal amount of information. After this pre-processing 20 input variables were selected and different machine learning systems were used to develop a predictive model based on a training testing crossover procedure. Results: The best machine learning system (three-layers feed-forward neural network) obtained a global accuracy of 90% ( 80 % sensitivity and 100% specificity ) with a ROC of 0.82. Conclusion: Machine learning systems coupled with radiomics show a promising potential in distinguishing benign from malign tumours in PI-RADS 3/5 areas.

Keywords: machine learning, MR prostate, PI-Rads 3, radiomics

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556 Assessment of Nurses’ Knowledge of the Glasgow Coma Scale in a Saudi Tertiary Care Hospital: A Cross-Sectional Study

Authors: Roaa Al Sharif, Salsabil Abo Al-Azayem, Nimah Alsomali, Wjoud Alsaeed, Nawal Alshammari, Abdulaziz Alwatban, Yaseen Alrabae, Razan Orfali, Faisal Alqarni, Ahmad Alrasheedi

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from various countries have revealed that nurses possess only a basic understanding of the GCS. Regarding this matter, limited knowledge is available about the situation in Saudi Arabia. Overall, the available research suggests that there is room for improvement in the knowledge of the GCS among nurses in Saudi Arabia. Further training and education programs may be beneficial in enhancing nurses' understanding and application of the GCS in clinical practice. Objective: To determine the level of knowledge and competence in assessing the GCS among staff nurses and to identify factors that might influence their knowledge at King Fahd Medical City in Riyadh, Saudi Arabia. Methods: A descriptive, cross-sectional survey involving 199 KFMC staff nurses was conducted. Nurses were provided with a structured questionnaire, and data were collected and analyzed using SPSS version 16, employing descriptive statistics and Chi-square tests. Results: The majority, 81.4% of nurses, had an average level of knowledge in assessing the Glasgow Coma Scale (GCS). The mean score for measuring the level of knowledge among staff nurses in GCS assessment was 8.8 ± 1.826. Overall, 13.6% of respondents demonstrated good knowledge of the GCS, scoring between 11 and 15 points, while only 5% of nurses exhibited poor knowledge of the GCS assessment. There was a significant correlation between knowledge and nurses' departments (χ2(2) = 19.184, p < 0.001). χ2(2) = 19.184," representing a Chi-square statistic with 2 degrees of freedom used to test the association between categorical variables in the data analysis. Conclusion: The findings indicate that knowledge of GCS assessment among staff nurses in a single center in Saudi Arabia is moderate. Therefore, there is a need for continuous education programs to enhance their competence in using this assessment.

Keywords: Glasgow Coma Scale, brain injury, nurses’ knowledge assessment, continuous education programs

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555 Debriefing Practices and Models: An Integrative Review

Authors: Judson P. LaGrone

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Simulation-based education in curricula was once a luxurious component of nursing programs but now serves as a vital element of an individual’s learning experience. A debriefing occurs after the simulation scenario or clinical experience is completed to allow the instructor(s) or trained professional(s) to act as a debriefer to guide a reflection with a purpose of acknowledging, assessing, and synthesizing the thought process, decision-making process, and actions/behaviors performed during the scenario or clinical experience. Debriefing is a vital component of the simulation process and educational experience to allow the learner(s) to progressively build upon past experiences and current scenarios within a safe and welcoming environment with a guided dialog to enhance future practice. The aim of this integrative review was to assess current practices of debriefing models in simulation-based education for health care professionals and students. The following databases were utilized for the search: CINAHL Plus, Cochrane Database of Systemic Reviews, EBSCO (ERIC), PsycINFO (Ovid), and Google Scholar. The advanced search option was useful to narrow down the search of articles (full text, Boolean operators, English language, peer-reviewed, published in the past five years). Key terms included debrief, debriefing, debriefing model, debriefing intervention, psychological debriefing, simulation, simulation-based education, simulation pedagogy, health care professional, nursing student, and learning process. Included studies focus on debriefing after clinical scenarios of nursing students, medical students, and interprofessional teams conducted between 2015 and 2020. Common themes were identified after the analysis of articles matching the search criteria. Several debriefing models are addressed in the literature with similarities of effectiveness for participants in clinical simulation-based pedagogy. Themes identified included (a) importance of debriefing in simulation-based pedagogy, (b) environment for which debriefing takes place is an important consideration, (c) individuals who should conduct the debrief, (d) length of debrief, and (e) methodology of the debrief. Debriefing models supported by theoretical frameworks and facilitated by trained staff are vital for a successful debriefing experience. Models differed from self-debriefing, facilitator-led debriefing, video-assisted debriefing, rapid cycle deliberate practice, and reflective debriefing. A reoccurring finding was centered around the emphasis of continued research for systematic tool development and analysis of the validity and effectiveness of current debriefing practices. There is a lack of consistency of debriefing models among nursing curriculum with an increasing rate of ill-prepared faculty to facilitate the debriefing phase of the simulation.

Keywords: debriefing model, debriefing intervention, health care professional, simulation-based education

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554 ABET Accreditation Process for Engineering and Technology Programs: Detailed Process Flow from Criteria 1 to Criteria 8

Authors: Amit Kumar, Rajdeep Chakrabarty, Ganesh Gupta

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This paper illustrates the detailed accreditation process of Accreditation Board of Engineering and Technology (ABET) for accrediting engineering and Technology programs. ABET is a non-governmental agency that accredits engineering and technology, applied and natural sciences, and computing sciences programs. ABET was founded on 10th May 1932 and was founded by Institute of Electrical and Electronics Engineering. International industries accept ABET accredited institutes having the highest standards in their academic programs. In this accreditation, there are eight criteria in general; criterion 1 describes the student outcome evaluations, criteria 2 measures the program's educational objectives, criteria 3 is the student outcome calculated from the marks obtained by students, criteria 4 establishes continuous improvement, criteria 5 focus on curriculum of the institute, criteria 6 is about faculties of this institute, criteria 7 measures the facilities provided by the institute and finally, criteria 8 focus on institutional support towards staff of the institute. In this paper, we focused on the calculative part of each criterion with equations and suitable examples, the files and documentation required for each criterion, and the total workflow of the process. The references and the values used to illustrate the calculations are all taken from the samples provided at ABET's official website. In the final section, we also discuss the criterion-wise score weightage followed by evaluation with timeframe and deadlines.

Keywords: Engineering Accreditation Committee, Computing Accreditation Committee, performance indicator, Program Educational Objective, ABET Criterion 1 to 7, IEEE, National Board of Accreditation, MOOCS, Board of Studies, stakeholders, course objective, program outcome, articulation, attainment, CO-PO mapping, CO-PO-SO mapping, PDCA cycle, degree certificates, course files, course catalogue

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553 Freshwater Pinch Analysis for Optimal Design of the Photovoltaic Powered-Pumping System

Authors: Iman Janghorban Esfahani

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Due to the increased use of irrigation in agriculture, the importance and need for highly reliable water pumping systems have significantly increased. The pumping of the groundwater is essential to provide water for both drip and furrow irrigation to increase the agricultural yield, especially in arid regions that suffer from scarcities of surface water. The most common irrigation pumping systems (IPS) consume conventional energies through the use of electric motors and generators or connecting to the electricity grid. Due to the shortage and transportation difficulties of fossil fuels, and unreliable access to the electricity grid, especially in the rural areas, and the adverse environmental impacts of fossil fuel usage, such as greenhouse gas (GHG) emissions, the need for renewable energy sources such as photovoltaic systems (PVS) as an alternative way of powering irrigation pumping systems is urgent. Integration of the photovoltaic systems with irrigation pumping systems as the Photovoltaic Powered-Irrigation Pumping System (PVP-IPS) can avoid fossil fuel dependency and the subsequent greenhouse gas emissions, as well as ultimately lower energy costs and improve efficiency, which made PVP-IPS systems as an environmentally and economically efficient solution for agriculture irrigation in every region. The greatest problem faced by integration of PVP with IPS systems is matching the intermittence of the energy supply with the dynamic water demand. The best solution to overcome the intermittence is to incorporate a storage system into the PVP-IPS to provide water-on-demand as a highly reliable stand-alone irrigation pumping system. The water storage tank (WST) is the most common storage device for PVP-IPS systems. In the integrated PVP-IPS with a water storage tank (PVP-IPS-WST), a water storage tank stores the water pumped by the IPS in excess of the water demand and then delivers it when demands are high. The Freshwater pinch analysis (FWaPA) as an alternative to mathematical modeling was used by other researchers for retrofitting the off-grid battery less photovoltaic-powered reverse osmosis system. However, the Freshwater pinch analysis has not been used to integrate the photovoltaic systems with irrigation pumping system with water storage tanks. In this study, FWaPA graphical and numerical tools were used for retrofitting an existing PVP-IPS system located in Salahadin, Republic of Iraq. The plant includes a 5 kW submersible water pump and 7.5 kW solar PV system. The Freshwater Composite Curve as the graphical tool and Freashwater Storage Cascade Table as the numerical tool were constructed to determine the minimum required outsourced water during operation, optimal amount of delivered electricity to the water pump, and optimal size of the water storage tank for one-year operation data. The results of implementing the FWaPA on the case study show that the PVP-IPS system with a WST as the reliable system can reduce outsourced water by 95.41% compare to the PVP-IPS system without storage tank.

Keywords: irrigation, photovoltaic, pinch analysis, pumping, solar energy

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552 Immature Palm Tree Detection Using Morphological Filter for Palm Counting with High Resolution Satellite Image

Authors: Nur Nadhirah Rusyda Rosnan, Nursuhaili Najwa Masrol, Nurul Fatiha MD Nor, Mohammad Zafrullah Mohammad Salim, Sim Choon Cheak

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Accurate inventories of oil palm planted areas are crucial for plantation management as this would impact the overall economy and production of oil. One of the technological advancements in the oil palm industry is semi-automated palm counting, which is replacing conventional manual palm counting via digitizing aerial imagery. Most of the semi-automated palm counting method that has been developed was limited to mature palms due to their ideal canopy size represented by satellite image. Therefore, immature palms were often left out since the size of the canopy is barely visible from satellite images. In this paper, an approach using a morphological filter and high-resolution satellite image is proposed to detect immature palm trees. This approach makes it possible to count the number of immature oil palm trees. The method begins with an erosion filter with an appropriate window size of 3m onto the high-resolution satellite image. The eroded image was further segmented using watershed segmentation to delineate immature palm tree regions. Then, local minimum detection was used because it is hypothesized that immature oil palm trees are located at the local minimum within an oil palm field setting in a grayscale image. The detection points generated from the local minimum are displaced to the center of the immature oil palm region and thinned. Only one detection point is left that represents a tree. The performance of the proposed method was evaluated on three subsets with slopes ranging from 0 to 20° and different planting designs, i.e., straight and terrace. The proposed method was able to achieve up to more than 90% accuracy when compared with the ground truth, with an overall F-measure score of up to 0.91.

Keywords: immature palm count, oil palm, precision agriculture, remote sensing

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551 Understanding Inhibitory Mechanism of the Selective Inhibitors of Cdk5/p25 Complex by Molecular Modeling Studies

Authors: Amir Zeb, Shailima Rampogu, Minky Son, Ayoung Baek, Sang H. Yoon, Keun W. Lee

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Neurotoxic insults activate calpain, which in turn produces truncated p25 from p35. p25 forms hyperactivated Cdk5/p25 complex, and thereby induces severe neuropathological aberrations including hyperphosphorylated tau, neuroinflammation, apoptosis, and neuronal death. Inhibition of Cdk5/p25 complex alleviates aberrant phosphorylation of tau to mitigate AD pathology. PHA-793887 and Roscovitine have been investigated as selective inhibitors of Cdk5/p25 with IC50 values 5nM and 160nM, respectively, but their mechanistic studies remain unknown. Herein, computational simulations have explored the binding mode and interaction mechanism of PHA-793887 and Roscovitine with Cdk5/p25. Docking results suggested that PHA-793887 and Rsocovitine have occupied the ATP-binding site of Cdk5 and obtained highest docking (GOLD) score of 66.54 and 84.03, respectively. Furthermore, molecular dynamics (MD) simulation demonstrated that PHA-793887 and Roscovitine established stable RMSD of 1.09 Å and 1.48 Å with Cdk5/p25, respectively. Profiling of polar interactions suggested that each inhibitor formed hydrogen bonds (H-bond) with catalytic residues of Cdk5 and could remain stable throughout the molecular dynamics simulation. Additionally, binding free energy calculation by molecular mechanics/Poisson–Boltzmann surface area (MM/PBSA) suggested that PHA-793887 and Roscovitine had lowest binding free energies of -150.05 kJ/mol and -113.14 kJ/mol, respectively with Cdk5/p25. Free energy decomposition demonstrated that polar energy by H-bond between the Glu81 of Cdk5 and PHA-793887 is the essential factor to make PHA-793887 highly selective towards Cdk5/p25. Overall, this study provided substantial evidences to explore mechanistic interactions of the selective inhibitors of Cdk5/p25 and could be used as fundamental considerations in the development of structure-based selective inhibitors of Cdk5/p25.

Keywords: Cdk5/p25 inhibition, molecular modeling of Cdk5/p25, PHA-793887 and roscovitine, selective inhibition of Cdk5/p25

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550 Developing a Video Game (Historia’s Nightmare) and Finding Out if We Can Use It to Raise Social Awareness and Improve Learning

Authors: Hasibul Kabir, Samin Shahriar Tokey, Md. Tofazzal Hossain

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One of the most necessary things in the present time is raising social awareness about global warming and climate change among the people. Though many types of mediums and techniques have been used to teach people about this global phenomenon, there are still more effective ways to reach people with useful information about global warming. As many traditional methods to teach people about global warming and climate change did not work well, video games were overdue. To learn how effective a video game can be in this regard, we developed a Video game, "Historia's Nightmare," that teaches people about Global warming and climate change. The game was designed to entertain people and give them an idea about the reasons and consequences of global warming and climate change while not being like traditional educational games. The game threw a mini quiz consisting of two MCQs based on the information shown in the game, where a gamer had to pass the quiz to reach the next level. We published the game on different platforms to let all types of people play and complete our experiment effectively. The game continuously communicated with our server to send data about gamers' performance. We observed the data, including the participants' performance, time spent, quiz score, and the in-game feedback on a regular basis, and finally came to a verdict. In our experiment, we have found that most participants positively accepted the game and learned something new. The participants who spent more on our game performed better in both quiz and the game. Our experiment's result demonstrates that video games can be a great way to teach people something, particularly to raise social awareness about global warming and climate change. It also demonstrates that the game can be a significant element in education and learning improvement.

Keywords: video game, global warming, social awareness, climate change, education, feedback

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549 Machine Learning Techniques for COVID-19 Detection: A Comparative Analysis

Authors: Abeer A. Aljohani

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COVID-19 virus spread has been one of the extreme pandemics across the globe. It is also referred to as coronavirus, which is a contagious disease that continuously mutates into numerous variants. Currently, the B.1.1.529 variant labeled as omicron is detected in South Africa. The huge spread of COVID-19 disease has affected several lives and has surged exceptional pressure on the healthcare systems worldwide. Also, everyday life and the global economy have been at stake. This research aims to predict COVID-19 disease in its initial stage to reduce the death count. Machine learning (ML) is nowadays used in almost every area. Numerous COVID-19 cases have produced a huge burden on the hospitals as well as health workers. To reduce this burden, this paper predicts COVID-19 disease is based on the symptoms and medical history of the patient. This research presents a unique architecture for COVID-19 detection using ML techniques integrated with feature dimensionality reduction. This paper uses a standard UCI dataset for predicting COVID-19 disease. This dataset comprises symptoms of 5434 patients. This paper also compares several supervised ML techniques to the presented architecture. The architecture has also utilized 10-fold cross validation process for generalization and the principal component analysis (PCA) technique for feature reduction. Standard parameters are used to evaluate the proposed architecture including F1-Score, precision, accuracy, recall, receiver operating characteristic (ROC), and area under curve (AUC). The results depict that decision tree, random forest, and neural networks outperform all other state-of-the-art ML techniques. This achieved result can help effectively in identifying COVID-19 infection cases.

Keywords: supervised machine learning, COVID-19 prediction, healthcare analytics, random forest, neural network

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548 The Inherent Flaw in the NBA Playoff Structure

Authors: Larry Turkish

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Introduction: The NBA is an example of mediocrity and this will be evident in the following paper. The study examines and evaluates the characteristics of the NBA champions. As divisions and playoff teams increase, there is an increase in the probability that the champion originates from the mediocre category. Since it’s inception in 1947, the league has been mediocre and continues to this day. Why does a professional league allow any team with a less than 50% winning percentage into the playoffs? As long as the finances flow into the league, owners will not change the current algorithm. The objective of this paper is to determine if the regular season has meaning in finding an NBA champion. Statistical Analysis: The data originates from the NBA website. The following variables are part of the statistical analysis: Rank, the rank of a team relative to other teams in the league based on the regular season win-loss record; Winning Percentage of a team based on the regular season; Divisions, the number of divisions within the league and Playoff Teams, the number of playoff teams relative to a particular season. The following statistical applications are applied to the data: Pearson Product-Moment Correlation, Analysis of Variance, Factor and Regression analysis. Conclusion: The results indicate that the divisional structure and number of playoff teams results in a negative effect on the winning percentage of playoff teams. It also prevents teams with higher winning percentages from accessing the playoffs. Recommendations: 1. Teams that have a winning percentage greater than 1 standard deviation from the mean from the regular season will have access to playoffs. (Eliminates mediocre teams.) 2. Eliminate Divisions (Eliminates weaker teams from access to playoffs.) 3. Eliminate Conferences (Eliminates weaker teams from access to the playoffs.) 4. Have a balanced regular season schedule, (Reduces the number of regular season games, creates equilibrium, reduces bias) that will reduce the need for load management.

Keywords: alignment, mediocrity, regression, z-score

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547 A Machine Learning-Based Model to Screen Antituberculosis Compound Targeted against LprG Lipoprotein of Mycobacterium tuberculosis

Authors: Syed Asif Hassan, Syed Atif Hassan

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Multidrug-resistant Tuberculosis (MDR-TB) is an infection caused by the resistant strains of Mycobacterium tuberculosis that do not respond either to isoniazid or rifampicin, which are the most important anti-TB drugs. The increase in the occurrence of a drug-resistance strain of MTB calls for an intensive search of novel target-based therapeutics. In this context LprG (Rv1411c) a lipoprotein from MTB plays a pivotal role in the immune evasion of Mtb leading to survival and propagation of the bacterium within the host cell. Therefore, a machine learning method will be developed for generating a computational model that could predict for a potential anti LprG activity of the novel antituberculosis compound. The present study will utilize dataset from PubChem database maintained by National Center for Biotechnology Information (NCBI). The dataset involves compounds screened against MTB were categorized as active and inactive based upon PubChem activity score. PowerMV, a molecular descriptor generator, and visualization tool will be used to generate the 2D molecular descriptors for the actives and inactive compounds present in the dataset. The 2D molecular descriptors generated from PowerMV will be used as features. We feed these features into three different classifiers, namely, random forest, a deep neural network, and a recurring neural network, to build separate predictive models and choosing the best performing model based on the accuracy of predicting novel antituberculosis compound with an anti LprG activity. Additionally, the efficacy of predicted active compounds will be screened using SMARTS filter to choose molecule with drug-like features.

Keywords: antituberculosis drug, classifier, machine learning, molecular descriptors, prediction

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546 The Influence of Concrete Pictorial Abstract Teaching Approach on Students' Concepts Understanding and Retention in Mathematics in Rwandan Lower Secondary Schools

Authors: Emmanuel Iyamuremye, Irenee Ndayambaje

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This study investigated the influence of Concrete Pictorial Abstract (CPA) teaching approach on mathematics achievement based on a sample of eighth-grade students (N = 10,345) from the Rwandan Lower Secondary School quasi-experimental study with pre-test and post-test control group of 2019 (RLSQES19). Key aspects studied included mathematics concept understanding and mathematics concept retention and how these are influenced by teacher's teaching approach. Specifically, the study aimed to a.) investigate students' concept understanding and concept retention in mathematics when exposed to CPA approach and to those exposed to non-CPA approach before and after the intervention, and b.) ascertain the significant difference between the performance of the students exposed to CPA approach and those exposed to non-CPA approach in terms of post-test scores and retention test scores. Two groups (control and experimental) undergone pre-test, post-test, and retention test. The assignment of control and experimental group among senior two classes from 10 schools was done randomly. The materials used to determine the performance of the students is a teacher-made test. Descriptive statistics and ANCOVA were used for the analysis of the study. For determining the improvement in concept understanding of mathematics, Hakes methods of calculating gain were used to analyze the pre-test and post test score. The level of performance of the two groups in the pre-test is below average level. During the post-test and retention test, the performance of students in non-CPA group is on average level, and students in CPA group are on above average level. Hakes methods of calculating gain revealed higher significant performance in the post-test and retention test of CPA group of students than non-CPA group of students.

Keywords: concept understanding, concept retention, performance, teaching approach

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545 Comparative Study Between Two Different Techniques for Postoperative Analgesia in Cesarean Section Delivery

Authors: Nermeen Elbeltagy, Sara Hassan, Tamer Hosny, Mostafa Abdelaziz

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Introduction: Adequate postoperative analgesia after caesarean section (CS) is crucial as it impacts the distinct surgical recovery needs of the parturient. Over recent years, there has been increased interest in regional nerve block techniques with promising results on efficacy. These techniques reduce the need for additional analgesia, thereby lowering the incidence of drug-related side effects. As postoperative pain after cesarean is mainly due to abdominal incision, the transverses abdomenis plane ( TAP ) block is a relatively new abdominal nerve block with excellent efficacy after different abdominal surgeries, including cesarean section. Objective: The main objective is to compare ultrasound-guided TAP block provided by the anesthesiologist with TAP provided by the surgeon through a caesarean incision regarding the duration of postoperative analgesia, intensity of analgesia, timing of mobilization, and easiness of the procedure. Method: Ninety pregnant females at term who were scheduled for delivery by elective cesarean section were randomly distributed into two groups. The first group (45) received spinal anesthesia and postoperative ultrasound guided TAP block using 20ml on each side of 0.25% bupivacaine which was provided by the anesthesiologist. The second group (45) received spinal anesthesia plus a TAP block using 20ml on each side of 0.25% bupivacaine, which was provided by the surgeon through the cesarean incision. Visual Analogue Scale (VAS) was used for the comparison between the two groups. Results: VAS score after four hours was higher among the TAP block group provided by the surgeon through the surgical incision than the postoperative analgesic profile using ultrasound-guided TAP block provided by the anesthesiologist (P=0.011). On the contrary, there was no statistical difference in the patient’s dose of analgesia after four hours of the TAP block (P=0.228). Conclusion: TAP block provided through the surgical incision is safe and enhances early patient’s mobilization.

Keywords: TAP block, CS, VAS, analgesia

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544 Identification of Promiscuous Epitopes for Cellular Immune Responses in the Major Antigenic Protein Rv3873 Encoded by Region of Difference 1 of Mycobacterium tuberculosis

Authors: Abu Salim Mustafa

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Rv3873 is a relatively large size protein (371 amino acids in length) and its gene is located in the immunodominant genomic region of difference (RD)1 that is present in the genome of Mycobacterium tuberculosis but deleted from the genomes of all the vaccine strains of Bacillus Calmette Guerin (BCG) and most other mycobacteria. However, when tested for cellular immune responses using peripheral blood mononuclear cells from tuberculosis patients and BCG-vaccinated healthy subjects, this protein was found to be a major stimulator of cell mediated immune responses in both groups of subjects. In order to further identify the sequence of immunodominant epitopes and explore their Human Leukocyte Antigen (HLA)-restriction for epitope recognition, 24 peptides (25-mers overlapping with the neighboring peptides by 10 residues) covering the sequence of Rv3873 were synthesized chemically using fluorenylmethyloxycarbonyl chemistry and tested in cell mediated immune responses. The results of these experiments helped in the identification of an immunodominant peptide P9 that was recognized by people expressing varying HLA-DR types. Furthermore, it was also predicted to be a promiscuous binder with multiple epitopes for binding to HLA-DR, HLA-DP and HLA-DQ alleles of HLA-class II molecules that present antigens to T helper cells, and to HLA-class I molecules that present antigens to T cytotoxic cells. In addition, the evaluation of peptide P9 using an immunogenicity predictor server yielded a high score (0.94), which indicated a greater probability of this peptide to elicit a protective cellular immune response. In conclusion, P9, a peptide with multiple epitopes and ability to bind several HLA class I and class II molecules for presentation to cells of the cellular immune response, may be useful as a peptide-based vaccine against tuberculosis.

Keywords: mycobacterium tuberculosis, PPE68, peptides, vaccine

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543 Diagnosing Depression during Pregnancy-Identifying Risk Factors of Prenatal Depression in Polish Women

Authors: Olga Plaza, Katarzyna Kosinska-Kaczynska, Stepan Feduniw, Dominika Pazdzior, Kinga Zebrowska, Katarzyna Kwiatkowska

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Introduction: The main causes of depression among pregnant women remain unclear. However, it is clear that pregnancy carries a higher risk of depression occurrence. Left untreated, prenatal depression can be a cause of serious both maternal and neonatal complications. Aim of the study: The aim of the study was to define potential risk factors of prenatal depression and to assess the frequency of its occurrence among pregnant women. Material and Methods: A prospective cross-sectional study was performed among 346 women. The self- composed questionnaire consisting of 46 questions, was distributed via the Internet between November 2017 and March 2018. The questionnaire contained the Edinburgh Postnatal Depression Scale (EPDS), in which the results of 13 and more points (out of 30) suggested possible prenatal depression. Statistical analysis was performed with Chi2 Pearson. P value < 0.05 was considered significant. Results: 37.57% (n=130) of women had a score of 13 or more points. Women with depressive symptoms (DS) reported lack of support from the partner (46.9% vs. 16.2%; p < 0.001) as well as other family members (40.8% vs. 14.4%; p < 0.001), current pregnancy being unplanned (21.5% vs. 12.5%; p=0.014) and low socio-economic status (10% vs. 0.9%; p < 0.001). Both early and advanced maternal age seemed to play a role in occurrence of DS: in women aged 17-24 40.8% declared symptoms (vs 28.7%; p < 0.01), in mothers aged ≥37 6.2% did (vs 0.5%; p < 0.001). Smoking during pregnancy was also more frequent among patients with DS (31.5% vs. 18.1%; p=0.004). Previous diagnosis of depression or other mood disorders significantly increased a chance of DS occurrence (respectively- 17.7% vs. 4.6%; p < 0.001 and 49.2% vs. 25%; p<0.001). Parental diagnosis of mood disorders and other mental disorders was also more frequent in this group of patients (respectively- 24.6% vs. 15.7%; p= 0.026 and 26.4% vs. 9.7%; p < 0.001). Only 23.8% of women with DS sought help from healthcare professionals, with 21.5% receiving pharmacological treatment. Conclusions: Pregnant women often report having DS. Evaluation of risk factors of DS and possible prenatal depression is essential in proper screening for depression among pregnant women.

Keywords: obstetrics, polish women, prenatal care, prenatal depression, risk factors

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542 National Scope Study on Resilience of Nursing Teams During the COVID-19 Pandemic: Brazilian Experience

Authors: Elucir Gir, Laelson Rochelle Milanês Sousa, Pedro Henrique Tertuliano Leoni, Carla Aparecida Arena Ventura, Ana Cristina de Oliveira e Silva, Renata Karina Reis

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Context and significance: Resilience is a protective agent for the physical and mental well-being of nursing professionals. Team members are constantly subjected to high levels of work stress that can negatively impact care performance and users of health services. Stress levels have been exacerbated with the COVID-19 pandemic. Objective: The aim of this study was to analyze the resilience of nursing professionals in Brazil during the COVID-19 pandemic. Method: Cross-sectional study with a quantitative approach carried out with professionals from nursing teams from all regions of Brazil. Data collection took place in the first year of the pandemic between October and December 2020. Data were obtained through an online questionnaire posted on social networks. The information collected included the sociodemographic characterization of the nursing professionals and the Brief Resilient Coping Scale was applied. Student's t-test for independent samples and analysis of variance (ANOVA) were used to compare resilience scores with sociodemographic variables. Results: 8,792 nursing professionals participated in the study, 5,767 (65.6%) were nurses, 7,437 (84.6%) were female and 2,643 (30.1%) were from the Northeast region of Brazil, 5,124 (58.8% ) had low levels of resilience. The results showed a statistically significant difference between the resilience score and the variables: professional category (p<0.001); sex (p = 0.003); age range (p<0.001); region of Brazil (p<0.001); marital status (p=0.029) and providing assistance in a field hospital (p<0.001). Conclusion: Participants in this study had, in general, low levels of resilience. There is an urgent need for actions aimed at promoting the psychological health of nursing professionals inserted in pandemic contexts. Descriptors: Psychological Resilience; Nursing professionals; COVID-19; SARSCoV-2.

Keywords: psychological resilience, nursing professionals, COVID-19, SARS-CoV-2

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541 Compliance of Systematic Reviews in Ophthalmology with the PRISMA Statement

Authors: Seon-Young Lee, Harkiran Sagoo, Reem Farwana, Katharine Whitehurst, Alex Fowler, Riaz Agha

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Background/Aims: Systematic reviews and meta-analysis are becoming increasingly important way of summarizing research evidence. Researches in ophthalmology may represent further challenges, due to their potential complexity in study design. The aim of our study was to determine the reporting quality of systematic reviews and meta-analysis in ophthalmology with the PRISMA statement, by assessing the articles published between 2010 and 2015 from five major journals with the highest impact factor. Methods: MEDLINE and EMBASE were used to search systematic reviews published between January 2010 and December 2015, in 5 major ophthalmology journals: Progress in Retinal and Eye Research, Ophthalmology, Archives of Ophthalmology, American Journal of Ophthalmology, Journal of the American Optometric Association. Screening, identification, and scoring of articles were performed independently by two teams, followed by statistical analysis including the median, range, and 95% CIs. Results: 115 articles were involved. The median PRISMA score was 15 of 27 items (56%), with a range of 5-26 (19-96%) and 95% CI 13.9-16.1 (51-60%). Compliance was highest in items related to the description of rationale (item 3,100%) and inclusion of a structured summary in the abstract (item 2, 90%), while poorest in indication of review protocol and registration (item 5, 9%), specification of risk of bias affecting the cumulative evidence (item 15, 24%) and description of clear objectives in introduction (item 4, 26%). Conclusion: The reporting quality of systematic reviews and meta-analysis in ophthalmology need significant improvement. While the use of PRISMA criteria as a guideline before journal submission is recommended, additional research identifying potential barriers may be required to improve the compliance to the PRISMA guidelines.

Keywords: systematic reviews, meta-analysis, research methodology, reporting quality, PRISMA, ophthalmology

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540 The Role of the Corporate Social Responsibility in Poverty Reduction

Authors: M. Verde, G. Falzarano

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The paper examines the connection between corporate social responsibility (CSR), capability approach and poverty reduction; in particular, the local employment development (LED) by way of CSR initiatives. The joint action of LED/CSR results in a win-win situation, not only for the enterprises but also for all the stakeholders involved; in this regard, subsidiarity and coordination between national and regional/local authorities are central to a socially-oriented market economy. In the first section, the CSR is analysed on the basis of its social function in the fight against poverty, as a 'capabilities deprivation'. In the central part, the attention is focused on the relationship between CSR and LED; ergo, on the role of the enterprises in fostering capabilities development (the employment). Besides, all the potential solutions are presented, stressing the possible combinations, in the last part. The benchmark is the enterprise as an economic and a social institution: the business should not be combined with profit merely, paying more attention to its sustainable impact and social contribution. In which way could it be possible? The answer is the CSR. The impact of CSR on poverty reduction is still little explored. The companies help to reduce poverty through economic contribution, human rights and social inclusion; hence, the business becomes an 'agent of development' in order to fight against 'inequality'. The starting point is the pyramid of social responsibility, where ethic and philanthropic responsibilities involve programmes and actions aimed at personal development of the individuals, improving human standard of living in all forms, including poverty, when people do not have a choice between different 'life options', ranging from level of education to employment. At this point, CSR comes into play and works on two dimensions: poverty reduction and poverty prevention, by means of a series of initiatives: first of all, job creation and precarious work reduction. Empowerment of the local actors, financial support and combination of top down and bottom up initiatives are some of CSR areas of activity. Several positive effects occur on individual levels of educations, access to capital, individual health status, empowerment of youth and woman, access to social networks and it was observed that these effects depend on the type of CSR strategy. Indeed, CSR programmes should take into account fundamental criteria, such as the transparency, the information about benefits, a coordination unit among institutions and more clear guidelines. In this way, the advantages to the corporate reputation and to the community translate into a better job matching on the labour market, inter alia. It is important to underline that the success depends on the specific measures of the areas in question, by adapting them to the local needs, in light of general principles and index; therefore, the concrete commitment of the all stakeholders involved is decisive in order to achieve the goals. The enterprise would represent a concrete contribution for the pursuit of sustainable development and for the dissemination of a social and well being awareness.

Keywords: capability approach, local employment development, poverty, social inclusion

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539 Determinants of Quality of Life and Mental Health in Medical Students During Two Years Observation

Authors: Szymon Szemik, Małgorzata Kowalska

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Objective: Medical students experience numerous demands during the education process, determining their quality of life (QoL) and health status. POLLEK (POLski LEKarz, eng. Polish Physician) study aims to identify and evaluate the quality of life, mental health status, and ever-recognized chronic diseases by simultaneously assessing their determinants in Polish medical students during long-term observation. Material and Methods: The POLLEK is the follow-up cohort study conducted among medical students at the Medical University of Silesia in Katowice. Students were followed during two observation periods: in their first year of studies, the academic year 2021/2022 (T1), and in their second year, the academic year 2022/2023 (T2). Results: The total number of participants in the first year of observation (T1) was 427 while in the second year (T2) was 335. Obtained results confirmed that the QoL score significantly decreased in their second year of studies mainly in the somatic and psychological domains. Moreover, we observed a significant increase in self-declared scoring of somatic symptoms year by year (from M=4.75 at T1 to M=8.06 at T2, p<0.001) in the GHQ-28 questionnaire survey. The determinants of QoL domains common to T1 and T2 remained self-declared health status, frequency of physical activity, and current financial situation. In the first year of evaluation, 56 students (13.10%) were overweight or obese, and 52 (15.8%) in the second. Regardless of the academic year, the increased risk of being overweight or obese was significantly associated with dissatisfaction with personal health, financial deficiencies, and a diet abundant in meat consumption. Conclusions: The QoL in medical students and selected determinants of their health status deteriorated during the observation period. Our findings suggest that medical schools should actively promote the activity needed to achieve a balance between schoolwork and the personal life of medical students from the beginning of university study.

Keywords: quality of life, mental health, medical students, follow-up study

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538 Factors Related to Oncology Ward Nurses’ Job Stress Adaptation Needs in Southern Taiwan Regional Hospital

Authors: Minhui Chiu

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According to relevant studies, clinical nurses have high work pressure and relatively high job adaptation needs. The nurses who work in oncology wards have more adaptation needs when they face repeating hospitalization patients. The aims of this study were to investigate the job stress adaptation and related factors of nurses in oncology wards and to understand the predictors of job stress adaptation needs. Convenience sampling was used in this study. The nurses in the oncology specialist ward of a regional teaching hospital in southern Taiwan were selected as the research objects. A cross-sectional survey was conducted using a structured questionnaire, random sampling, and the questionnaires were filled out by the participating nurses. A total of 68 people were tested, and 65 valid questionnaires (95.6%). One basic data questionnaire and nurses’ job stress adaptation needs questionnaire were used. The data was archived with Microsoft Excel, and statistical analysis was performed with JMP12.0. The results showed that the average age was 28.8 (±6.7) years old, most of them were women, 62 (95.38%), and the average clinical experience in the hospital was 5.7 years (±5.9), and 62 (95.38%) were university graduates. 39 people (60.0%) had no work experience. 39 people (60.0%) liked nursing work very much, and 23 people (35.3%) just “liked”. 47 (72.3%) people were supported to be oncology nurses by their families. The nurses' job stress adaptation needs were 119.75 points (±17.24). The t-test and variance analysis of the impact of nurses' job pressure adaptation needs were carried out. The results showed that the score of college graduates was 121.10 (±16.39), which was significantly higher than that of master graduates 96.67 (±22.81), and the degree of liking for nursing work also reached a Significant difference. These two variables are important predictors of job adaptation needs, and the R Square is 24.15%. Conclusion: Increasing the love of clinical nurses in nursing and encouraging university graduation to have positive effects on job pressure adaptation needs and can be used as a reference for the management of human resources hospitals for oncology nurses.

Keywords: oncology nurse, job stress, job stress adaptation needs, manpower

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537 Detecting Indigenous Languages: A System for Maya Text Profiling and Machine Learning Classification Techniques

Authors: Alejandro Molina-Villegas, Silvia Fernández-Sabido, Eduardo Mendoza-Vargas, Fátima Miranda-Pestaña

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The automatic detection of indigenous languages ​​in digital texts is essential to promote their inclusion in digital media. Underrepresented languages, such as Maya, are often excluded from language detection tools like Google’s language-detection library, LANGDETECT. This study addresses these limitations by developing a hybrid language detection solution that accurately distinguishes Maya (YUA) from Spanish (ES). Two strategies are employed: the first focuses on creating a profile for the Maya language within the LANGDETECT library, while the second involves training a Naive Bayes classification model with two categories, YUA and ES. The process includes comprehensive data preprocessing steps, such as cleaning, normalization, tokenization, and n-gram counting, applied to text samples collected from various sources, including articles from La Jornada Maya, a major newspaper in Mexico and the only media outlet that includes a Maya section. After the training phase, a portion of the data is used to create the YUA profile within LANGDETECT, which achieves an accuracy rate above 95% in identifying the Maya language during testing. Additionally, the Naive Bayes classifier, trained and tested on the same database, achieves an accuracy close to 98% in distinguishing between Maya and Spanish, with further validation through F1 score, recall, and logarithmic scoring, without signs of overfitting. This strategy, which combines the LANGDETECT profile with a Naive Bayes model, highlights an adaptable framework that can be extended to other underrepresented languages in future research. This fills a gap in Natural Language Processing and supports the preservation and revitalization of these languages.

Keywords: indigenous languages, language detection, Maya language, Naive Bayes classifier, natural language processing, low-resource languages

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536 Clinical Prediction Rules for Using Open Kinetic Chain Exercise in Treatment of Knee Osteoarthritis

Authors: Mohamed Aly, Aliaa Rehan Youssef, Emad Sawerees, Mounir Guirgis

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Relevance: Osteoarthritis (OA) is the most common degenerative disease seen in all populations. It causes disability and substantial socioeconomic burden. Evidence supports that exercise are the most effective conservative treatment for patients with OA. Therapists experience and clinical judgment play major role in exercise prescription and scientific evidence for this regard is lacking. The development of clinical prediction rules to identify patients who are most likely benefit from exercise may help solving this dilemma. Purpose: This study investigated whether body mass index and functional ability at baseline can predict patients’ response to a selected exercise program. Approach: Fifty-six patients, aged 35 to 65 years, completed an exercise program consisting of open kinetic chain strengthening and passive stretching exercises. The program was given for 3 sessions per week, 45 minutes per session, for 6 weeks Evaluation: At baseline and post treatment, pain severity was assessed using the numerical pain rating scale, whereas functional ability was being assessed by step test (ST), time up and go test (TUG) and 50 feet time walk test (50 FTW). After completing the program, global rate of change (GROC) score of greater than 4 was used to categorize patients as successful and non-successful. Thirty-eight patients (68%) had successful response to the intervention. Logistic regression showed that BMI and 50 FTW test were the only significant predictors. Based on the results, patients with BMI less than 34.71 kg/m2 and 50 FTW test less than 25.64 sec are 68% to 89% more likely to benefit from the exercise program. Conclusions: Clinicians should consider the described strengthening and flexibility exercise program for patents with BMI less than 34.7 Kg/m2 and 50 FTW faster than 25.6 seconds. The validity of these predictors should be investigated for other exercise.

Keywords: clinical prediction rule, knee osteoarthritis, physical therapy exercises, validity

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535 Applying Biosensors’ Electromyography Signals through an Artificial Neural Network to Control a Small Unmanned Aerial Vehicle

Authors: Mylena McCoggle, Shyra Wilson, Andrea Rivera, Rocio Alba-Flores

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This work introduces the use of EMGs (electromyography) from muscle sensors to develop an Artificial Neural Network (ANN) for pattern recognition to control a small unmanned aerial vehicle. The objective of this endeavor exhibits interfacing drone applications beyond manual control directly. MyoWare Muscle sensor contains three EMG electrodes (dual and single type) used to collect signals from the posterior (extensor) and anterior (flexor) forearm and the bicep. Collection of raw voltages from each sensor were connected to an Arduino Uno and a data processing algorithm was developed with the purpose of interpreting the voltage signals given when performing flexing, resting, and motion of the arm. Each sensor collected eight values over a two-second period for the duration of one minute, per assessment. During each two-second interval, the movements were alternating between a resting reference class and an active motion class, resulting in controlling the motion of the drone with left and right movements. This paper further investigated adding up to three sensors to differentiate between hand gestures to control the principal motions of the drone (left, right, up, and land). The hand gestures chosen to execute these movements were: a resting position, a thumbs up, a hand swipe right motion, and a flexing position. The MATLAB software was utilized to collect, process, and analyze the signals from the sensors. The protocol (machine learning tool) was used to classify the hand gestures. To generate the input vector to the ANN, the mean, root means squared, and standard deviation was processed for every two-second interval of the hand gestures. The neuromuscular information was then trained using an artificial neural network with one hidden layer of 10 neurons to categorize the four targets, one for each hand gesture. Once the machine learning training was completed, the resulting network interpreted the processed inputs and returned the probabilities of each class. Based on the resultant probability of the application process, once an output was greater or equal to 80% of matching a specific target class, the drone would perform the motion expected. Afterward, each movement was sent from the computer to the drone through a Wi-Fi network connection. These procedures have been successfully tested and integrated into trial flights, where the drone has responded successfully in real-time to predefined command inputs with the machine learning algorithm through the MyoWare sensor interface. The full paper will describe in detail the database of the hand gestures, the details of the ANN architecture, and confusion matrices results.

Keywords: artificial neural network, biosensors, electromyography, machine learning, MyoWare muscle sensors, Arduino

Procedia PDF Downloads 174