Search results for: PREDICT score

Authors: Hazratullah Khattak, Abdul Waheed Mughal, Inamullah Khattak

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This study is envisaged as vital contribution as it intends to develop norms for the Sit and Reach Test in the Local Environment of Khyber Pakhtunkhwa Pakistan, for the age group between 12-14 years which will be used to measure the flexibility level of early adolescents (12-14 years). Sit and Reach test was applied on 2000 volunteers, 400 subjects from each selected district (Five (5) Districts, Peshawar, Nowshera, Karak, Dera Ismail Khan and Swat (20% percent of the total 25 districts) using convenient sampling technique. The population for this study is comprised of all the early adolescents aging 12-14 years (Age Mean 13 + 0.63, Height 154 + 046, Weight 46 + 7.17, BMI 19 + 1.45) representing various public and private sectors educational institutions of the Khyber Pakhtunkhwa. As for as the norms developed for Sit and Reach test, the score below 6.8 inches comes in the category of poor, 6.9 to 9.6 inches (below Average), 9.7 to 10.8 inches (Average), 10.9 to 13 inches (Above average) and above 13 inches score is considered as Excellent.

Keywords: fitness, flexibility, norms, sit and reach

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Authors: Amr Sadek, Abdelrahaman Al-Qahtany, Turkey Salem Al-Qahtany

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In this study, a backpropagation artificial neural network (ANN) model has been used to predict the cooling and heating capacities of air conditioners (AC) under different conditions. Sufficiently large measurement results were obtained from the national energy-efficiency laboratories in Saudi Arabia and were used for the learning process of the ANN model. The parameters affecting the performance of the AC, including temperature, humidity level, specific heat enthalpy indoors and outdoors, and the air volume flow rate of indoor units, have been considered. These parameters were used as inputs for the ANN model, while the cooling and heating capacity values were set as the targets. A backpropagation ANN model with two hidden layers and one output layer could successfully correlate the input parameters with the targets. The characteristics of the ANN model including the input-processing, transfer, neurons-distance, topology, and training functions have been discussed. The performance of the ANN model was monitored over the training epochs and assessed using the mean squared error function. The model was then used to predict the performance of the AC under conditions that were not included in the measurement results. The optimum performance of the AC was also predicted under the different environmental conditions in Saudi Arabia. The uncertainty of the ANN model predictions has been evaluated taking into account the randomness of the data and lack of learning.

Keywords: artificial neural network, uncertainty of model predictions, efficiency of air conditioners, cooling and heating capacities

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Authors: Zeinab Amini Moghaddam, Alireza Dehkhodania

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Nowadays, organizations have found a high status in the cultural and social structures of societies. The purpose of current study is to investigate the relationship between organizational climate with job burnout as well as job satisfaction. The research method is descriptive and correlational. The population of the study includes all employees in Tehran Electric Company, which equals 1984 people in 2018. The sampling was performed in the form of a consensus, and all employees were regarded as samples. The data gathering tools consist of three questionnaires of Smith’s Job Satisfaction Questionnaire, Halpin and Craft's Occupational climate, and Maslach and Jackson's Job burnout. The results showed that there was a direct and positive relationship between organizational climate and job burnout, as well as job satisfaction. The organizational climate variable could successfully predict job satisfaction. It was also able to predict job burnout.

Keywords: organizational climate, job burnout, job satisfaction, descriptive, correlational

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Authors: Zahra Karimian, Effat Merghati Khoei, Raziyeh Maasoumi

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Background: Women's sexual well-being is center of focus in the field of sexology. Study of sexual behavior and investigating its predictors is important in women's health promotion. Objectives: This study aimed to explore the components of sexual behaviors and their possible associations with the women's demographic. Methods: A National Sexual Behavior Assessment Questionnaire was administered to 500 women ages 15 to 45 who referred to the public health centers seeking for health care services. The associations with demographic were examined. Results: From all participant, 31.8% of women obtain high score in the sexual capacity 21.2% in sexual motivation and 0.2% in sexual function. In sexual script component, 86.2% of women were holding traditional beliefs toward sexual behaviors; the majority (91.5%) of women believed in mutual and relational sexuality, 83.4% believed in androcentricity (male-dominated sexuality). Pearson correlation test showed significant positive correlations between sexual capacity, motivation, function and sexual script (p < 0.05). Regression model showed that sexual capacity is associated with women's education, age of her spouse. Sexual function and sexual motivation were significantly associated with the age of subjects' spouses. Conclusion: In this study, lower score was found in sexual performance while women were scored higher in the sexual capacity and motivation. We argue that these lower score in sexual performance more likely is due to the level of participants' religiosity and formation of their sexuality through an androcentric culture. Women's level of education and the spouse age appear to be predicting factors in the scores the subjects gained. We suggest that gender-specific and culturally sensitive sexuality education should be focus of women's health programs in Iran.

Keywords: sexual behaviors, women, health, Iran

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Authors: Johnson Opoku-Asante, Emmanuel Bobobee, Joseph Akowuah, Eric Amoah Asante

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In recent years, the issue of postharvest losses has become a serious concern in Sub-Saharan Africa. Postharvest technology development and adaptation need urgent attention, particularly for small and medium-scale rice farmers in Africa. However, to better develop any postharvest technology, knowledge of the mechanical properties of different varieties of paddy rice is vital. There is also the issue of the development of new rice cultivars. The objectives of this research are to (1) determine the mechanical properties of the selected paddy rice varieties at varying moisture content. (2) conduct a comparative analysis of the mechanical properties of selected rice paddy for different variety-moisture content interactions. (3) determine the significant statistical differences between the mean values of the various variety-moisture content interactions The mechanical properties of AGRA rice, CRI-Amankwatia, CRI-Enapa and CRI-Dartey, four local varieties developed by Crop Research Institute of Ghana are compared at 11.5%, 13.0% and 16.5% dry basis moisture content. The mechanical properties measured are Sphericity, Aspect ratio, Grain mass, 1000 Grain mass, Bulk Density, True Density, Porosity and Angle of Repose. Samples were collected from the Kwadaso Agric College of the CRI in Kumasi. The samples were threshed manually and winnowed before conducting the experiment. The moisture content was determined on a dry basis using the Moistex Screw-Type Digital Grain Moisture Meter. Other equipment used for data collection were venire calipers and Citizen electronic scale. A 4×3 factorial arrangement was used in a completely randomized design in three replications. Tukey's HSD comparisons test was conducted during data analysis to compare all possible pairwise combinations of the various varieties’ moisture content interaction. From the results, it was concluded that Sphericity recorded 0.391 mm³ to 0.377 mm³ for CRI-Dartey at 16.5% and CRI-Enapa at 13.5%, respectively, whereas Aspect Ratio recorded 0.298 mm³ to 0.269 mm³ for CRI-Dartey at 16.5% and CRI-Enapa at 13.5% respectively. For grain mass, AGRA rice at 13.0% also recorded 0.0312 g as the highest score and CRI-Enapa at 13.0% obtained 0.0237 as the lowest score. For the GM1000, it was observed that it ranges from 29.33 g for CRI-Amankwatia at 16.5% moisture content to 22.54 g for CRI-Enapa at 16.5% interactions. Bulk Density ranged from 654.0 kg/m³ to 422.9 kg/m³ for CRI-Amankwatia at 16.5% and CRI-Enapa at 11.5% as the highest and lowest recordings, respectively. It was also observed that the true Density ranges from 1685.8 kg/m3 for AGRA rice at 13.0% moisture content to 1352.5 kg/m³ for CRI-Enapa at 16.5% interactions. In the case of porosity, CRI-Enapa at 11.5% received the highest score of 70.83% and CRI-Amankwatia at 16.5 received the lowest score of 55.88%. Finally, in the case of Angle of Repose, CRI-Amankwatia at 16.5% recorded the highest score of 47.3o and CRI-Enapa at 11.5% recorded the least score of 34.27o. In all cases, the difference in mean value was less than the LSD. This indicates that there were no significant statistical differences between their mean values, indicating that technologies developed and adapted for one variety can equally be used for all the other varieties.

Keywords: angle of repose, aspect ratio, bulk density, porosity, sphericity, mechanical properties

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Authors: Donghee Noh, Seonhyeong Kim, Junhwan Choi, Heegon Kim, Sooho Jung, Keunho Park

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In this paper, we describe an image post-processing method to enhance the performance of the parcel segmentation method using deep learning-based aerial images conducted in previous studies. The study results were evaluated using a confusion matrix, IoU, Precision, Recall, and F1-Score. In the case of the confusion matrix, it was observed that the false positive value, which is the result of misclassification, was greatly reduced as a result of image post-processing. The average IoU was 0.9688 in the image post-processing, which is higher than the deep learning result of 0.8362, and the F1-Score was also 0.9822 in the image post-processing, which was higher than the deep learning result of 0.8850. As a result of the experiment, it was found that the proposed technique positively complements the deep learning results in segmenting the parcel of interest.

Keywords: aerial image, image process, machine vision, open field smart farm, segmentation

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Authors: A. Ibovi Mouondayi, S. Zaher, R. Assadi, K. Erraoui, S. Sboul, J. Daoudim, S. Bousselham, K. Nassar, S. Janani

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INTRODUCTION: Neuropathic pain (NP) caused by damage to the somatosensory nervous system has a significant impact on quality of life and is associated with a high economic burden on the individual and society. The treatment of neuropathic pain consists of the use of a wide range of therapeutic agents, including gabapentin, which is used in the treatment of neuropathic pain. OBJECTIF: The objective of this study was to evaluate the efficacy and tolerance of gabapentin in the treatment of neuropathic pain. MATERIAL AND METHOD: This is a monocentric, cross-sectional, descriptive, retrospective study conducted in our department over a period of 19 months from October 2020 to April 2022. The missing parameters were collected during phone calls of the patients concerned. The diagnostic tool adopted was the DN4 questionnaire in the dialectal Arabic version. The impact of NP was assessed by the visual analog scale (VAS) on pain, sleep, and function. The impact of PN on mood was assessed by the "Hospital anxiety, and depression scale HAD" score in the validated Arabic version. The exclusion criteria were patients followed up for depression and other psychiatric pathologies. RESULTS: A total of 67 patients' data were collected. The average age was 64 years (+/- 15 years), with extremes ranging from 26 years to 94 years. 58 women and 9 men with an M/F sex ratio of 0.15. Cervical radiculopathy was found in 21% of this population, and lumbosacral radiculopathy in 61%. Gabapentin was introduced in doses ranging from 300 to 1800 mg per day with an average dose of 864 mg (+/- 346) per day for an average duration of 12.6 months. Before treatment, 93% of patients had a non-restorative sleep quality (VAS>3). 54% of patients had a pain VAS greater than 5. The function was normal in only 9% of patients. The mean anxiety score was 3.25 (standard deviation: 2.70), and the mean HAD depression score was 3.79 (standard deviation: 1.79). After treatment, all patients had improved the quality of their sleep (p<0.0001). A significant difference was noted in pain VAS, function, as well as anxiety and depression, and HAD score. Gabapentin was stopped for side effects (dizziness and drowsiness) and/or unsatisfactory response. CONCLUSION: Our data demonstrate a favorable effect of gabapentin on the management of neuropathic pain with a significant difference before and after treatment on the quality of life of patients associated with an acceptable tolerance profile.

Keywords: neuropathic pain, chronic pain, treatment, gabapentin

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Authors: Josip Karuc, Marjeta Mišigoj-Duraković, Goran Marković, Vedran Hadžić, Michael J. Duncan, Hrvoje Podnar, Maroje Sorić

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As a part of the CRO-PALS longitudinal study, this investigation aimed to examine the association between different levels of physical activity (PA) and movement quality in 16-years old school children. The total number of participants in this research was 725. Movement quality was assessed via the Functional Movement Screen (FMSTM), and the PA level was estimated using the School Health Action, Planning, and Evaluation System (SHAPES) questionnaire. In addition, body fat and socioeconomic status (SES) were assessed. In order to investigate the association between total FMS score and different levels of PA, multilevel modeling was employed for boys (n=359) and girls (n=366) separately. All models were adjusted for age, body fat, and SES. Among boys, MVPA, MPA, and VPA were not significant predictors of the total FMS score (β=0.000, p=0.78; β=-0.002, p=0.455; β=0.004, p=0.158, respectively). On the contrary, among girls, VPA and MVPA showed significant effects on the total FMS score (β=0.011, p=0.001, β=0.005, p=0.006, respectively). The findings of this research provide evidence that the intensity of PA is a minor but relevant factor in describing the association between PA and movement quality in adolescent girls but not in boys. This means that the PA level does not guarantee optimal functional movement patterns. Therefore, practicing functional movement patterns in an isolated manner and at moderate to vigorous intensity could be beneficial in order to reduce the risk of injury incidence and potential orthopedic abnormalities in later life. This work was supported by the Croatian Science Foundation, grant no: IP-2016-06-9926 and grant no: DOK-2018-01-2328.

Keywords: functional movement screen, fundamental movement patterns, movement quality, pediatric

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Authors: Angela T. H. Kwan, Saman Arfaie, Joseph Therriault, Zahra Azizi, Firoza Z. Lussier, Cecile Tissot, Mira Chamoun, Gleb Bezgin, Stijn Servaes, Jenna Stevenon, Nesrine Rahmouni, Vanessa Pallen, Serge Gauthier, Pedro Rosa-Neto

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Alzheimer’s disease (AD) can be detected in living people using in vivo biomarkers of amyloid-β (Aβ) and tau, even in the absence of cognitive impairment during the preclinical phase. [¹⁸F]-MK-6420 is a high affinity positron emission tomography (PET) tracer that quantifies tau neurofibrillary tangles, but its ability to predict cognitive changes associated with early AD symptoms, such as memory decline, is unclear. Here, we assess the prognostic accuracy of baseline [18F]-MK-6420 tau PET for predicting longitudinal memory decline in asymptomatic elderly individuals. In a longitudinal observational study, we evaluated a cohort of cognitively normal elderly participants (n = 111) from the Translational Biomarkers in Aging and Dementia (TRIAD) study (data collected between October 2017 and July 2020, with a follow-up period of 12 months). All participants underwent tau PET with [¹⁸F]-MK-6420 and Aβ PET with [¹⁸F]-AZD-4694. The exclusion criteria included the presence of head trauma, stroke, or other neurological disorders. There were 111 eligible participants who were chosen based on the availability of Aβ PET, tau PET, magnetic resonance imaging (MRI), and APOEε4 genotyping. Among these participants, the mean (SD) age was 70.1 (8.6) years; 20 (18%) were tau PET positive, and 71 of 111 (63.9%) were women. A significant association between baseline Braak I-II [¹⁸F]-MK-6240 SUVR positivity and change in composite memory score was observed at the 12-month follow-up, after correcting for age, sex, and years of education (Logical Memory and RAVLT, standardized beta = -0.52 (-0.82-0.21), p < 0.001, for dichotomized tau PET and -1.22 (-1.84-(-0.61)), p < 0.0001, for continuous tau PET). Moderate cognitive decline was observed for A+T+ over the follow-up period, whereas no significant change was observed for A-T+, A+T-, and A-T-, though it should be noted that the A-T+ group was small.Our results indicate that baseline tau neurofibrillary tangle pathology is associated with longitudinal changes in memory function, supporting the use of [¹⁸F]-MK-6420 PET to predict the likelihood of asymptomatic elderly individuals experiencing future memory decline. Overall, [¹⁸F]-MK-6420 PET is a promising tool for predicting memory decline in older adults without cognitive impairment at baseline. This is of critical relevance as the field is shifting towards a biological model of AD defined by the aggregation of pathologic tau. Therefore, early detection of tau pathology using [¹⁸F]-MK-6420 PET provides us with the hope that living patients with AD may be diagnosed during the preclinical phase before it is too late.

Keywords: alzheimer’s disease, braak I-II, in vivo biomarkers, memory, PET, tau

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Authors: Magdalena Bury-Kaminska, Aneta Szudy-Szczyrek, Aleksandra Nowaczynska, Olga Jankowska-Lecka, Marek Hus, Klaudia Kot

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Introduction: The aim of the research was to determine the changes in cognitive functioning in patients with plasma cell myeloma by comparing patients’ state before the treatment and during chemotherapy as well as to determine the biological factors that can be used to predict patients’ cognitive state. Methods: The patients underwent the research procedure twice: before chemotherapy and after 4-6 treatment cycles. A psychological test and measurement of the following biological variables were carried out: TNF-α (tumor necrosis factor), IL-6 (interleukin 6), IL-10 (interleukin 10), BDNF (brain-derived neurotrophic factor). The following research methods were implemented: the Montreal Cognitive Assessment (MoCA), Battery of Tests for Assessing Cognitive Functions PU1, experimental and clinical trials based on the Choynowski’s Memory Scale, Stroop Color-Word Interference Test (SCWT), depression measurement questionnaire. Results: The analysis of the research showed better cognitive functions of patients during chemotherapy in comparison to the phase before it. Moreover, neurotrophin BDNF allows to predict the level of selected cognitive functions (semantic fluency and execution control) already at the diagnosis stage. After 4-6 cycles, it is also possible to draw conclusions concerning the extent of working memory based on the level of BDNF. Cytokine TNF-α allows us to predict the level of letter fluency during anti-cancer treatment. Conclusions: It is possible to presume that BDNF has a protective influence on patients’ cognitive functions and working memory and that cytokine TNF-α co-occurs with a diminished execution control and better material grouping in terms of phonological fluency. Acknowledgment: This work was funded by the National Science Center in Poland [grant no. 2017/27/N/HS6/02057.

Keywords: chemobrain, cognitive impairment, non−central nervous system cancers, hematologic diseases

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Authors: Christos Lampropoulos, Maria Konsta, Ifigenia Apostolou, Vicky Dradaki, Tamta Sirbilatze, Irini Dri, Christina Kordali, Vaggelis Lambas, Kostas Argyros, Georgios Mavras

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Objectives: Mediterranean diet has been associated with lower incidence of cardiovascular disease and cancer. The purpose of our study was to examine the hypothesis that Mediterranean diet may protect against mortality and reduce admission duration in elderly, hospitalized patients. Methods: Sample population included 150 patients (78 men, 72 women, mean age 80±8.2). The following data were taken into account in analysis: anthropometric and laboratory data, dietary habits (MedDiet score), patients’ nutritional status [Mini Nutritional Assessment (MNA) score], physical activity (International Physical Activity Questionnaires, IPAQ), smoking status, cause and duration of current admission, medical history (co-morbidities, previous admissions). Primary endpoints were mortality (from admission until 6 months afterwards) and duration of admission, compared to national guidelines for closed consolidated medical expenses. Logistic regression and linear regression analysis were performed in order to identify independent predictors for mortality and admission duration difference respectively. Results: According to MNA, nutrition was normal in 54/150 (36%) of patients, 46/150 (30.7%) of them were at risk of malnutrition and the rest 50/150 (33.3%) were malnourished. After performing multivariate logistic regression analysis we found that the odds of death decreased 30% per each unit increase of MedDiet score (OR=0.7, 95% CI:0.6-0.8, p < 0.0001). Patients with cancer-related admission were 37.7 times more likely to die, compared to those with infection (OR=37.7, 95% CI:4.4-325, p=0.001). According to multivariate linear regression analysis, admission duration was inversely related to Mediterranean diet, since it is decreased 0.18 days on average for each unit increase of MedDiet score (b:-0.18, 95% CI:-0.33 - -0.035, p=0.02). Additionally, the duration of current admission increased on average 0.83 days for each previous hospital admission (b:0.83, 95% CI:0.5-1.16, p<0.0001). The admission duration of patients with cancer was on average 4.5 days higher than the patients who admitted due to infection (b:4.5, 95% CI:0.9-8, p=0.015). Conclusion: Mediterranean diet adequately protects elderly, hospitalized patients against mortality and reduces the duration of hospitalization.

Keywords: Mediterranean diet, malnutrition, nutritional status, prognostic factors for mortality

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Authors: Mohamed Hamada Abdelkader Fayed

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Background: To evaluate the diagnostic accuracy of (ADD-RS) with D-dimer as a screening test to exclude AAS. Methods: We conducted research for the studies examining the diagnostic accuracy of (ADD- RS)+ D-dimer to exclude the diagnosis of AAS, We searched MEDLINE, Embase, and Cochrane of Trials up to 31 December 2020. Results: We identified 3 studies using (ADD-RS) with D-dimer as a diagnostic tool for AAS, involving 3261 patients were AAS was diagnosed in 559(17.14%) patients. Overall results showed that the pooled sensitivities were 97.6 (95% CI 0.95.6, 99.6) at (ADD-RS)≤1(low risk group) with D-dimer and 97.4(95% CI 0.95.4,, 99.4) at (ADD-RS)>1(High risk group) with D-dimer., the failure rate was 0.48% at low risk group and 4.3% at high risk group respectively. Conclusions: (ADD-RS) with D-dimer was a useful screening test with high sensitivity to exclude Acute Aortic Syndrome.

Keywords: aortic dissection detection risk score, D-dimer, acute aortic syndrome, diagnostic accuracy

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Authors: Adandé Belarmain Fandohan

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Climate change has become a major concern globally, particularly in rural communities that have to find rapid coping solutions. Several vulnerability assessment approaches have been developed in the last decades. This comes along with a higher risk for different methods to result in different conclusions, thereby making comparisons difficult and decision-making non-consistent across areas. The effect of methods and computational approaches on estimates of people’s vulnerability was assessed using data collected from the Gambia. Twenty-four indicators reflecting vulnerability components: (exposure, sensitivity, and adaptive capacity) were selected for this purpose. Data were collected through household surveys and key informant interviews. One hundred and fifteen respondents were surveyed across six communities and two administrative districts. Results were compared over three computational approaches: the maximum value transformation normalization, the z-score transformation normalization, and simple averaging. Regardless of the approaches used, communities that have high exposure to climate change and extreme events were the most vulnerable. Furthermore, the vulnerability was strongly related to the socio-economic characteristics of farmers. The survey evidenced variability in vulnerability among communities and administrative districts. Comparing output across approaches, overall, people in the study area were found to be highly vulnerable using the simple average and maximum value transformation, whereas they were only moderately vulnerable using the z-score transformation approach. It is suggested that assessment approach-induced discrepancies be accounted for in international debates to harmonize/standardize assessment approaches to the end of making outputs comparable across regions. This will also likely increase the relevance of decision-making for adaptation policies.

Keywords: maximum value transformation, simple averaging, vulnerability assessment, West Africa, z-score transformation

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Authors: M. D. D. Chathurangi, M. G. K. Nayanathara, K. M. H. M. M. Gunapala, G. M. R. G. Dayananda, Kavinga Yapa Abeywardena, Deemantha Siriwardana

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Due to the growing popularity of social media platforms at present, there are various concerns, mostly cyberbullying, spam, bot accounts, and the spread of incorrect information. To develop a risk score calculation system as a thorough method for deciphering and exposing unethical social media profiles, this research explores the most suitable algorithms to our best knowledge in detecting the mentioned concerns. Various multiple models, such as Naïve Bayes, CNN, KNN, Stochastic Gradient Descent, Gradient Boosting Classifier, etc., were examined, and the best results were taken into the development of the risk score system. For cyberbullying, the Logistic Regression algorithm achieved an accuracy of 84.9%, while the spam-detecting MLP model gained 98.02% accuracy. The bot accounts identifying the Random Forest algorithm obtained 91.06% accuracy, and 84% accuracy was acquired for fake news detection using SVM.

Keywords: cyberbullying, spam behavior, bot accounts, fake news, machine learning

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Authors: Muhammet Baldan, Emel Timuçin

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Generally, absorption and bioavailability increase if solubility increases; therefore, it is crucial to predict them in drug discovery applications. Molecular descriptors and Molecular properties are traditionally used for the prediction of water solubility. There are various key descriptors that are used for this purpose, namely Drogan Descriptors, Morgan Descriptors, Maccs keys, etc., and each has different prediction capabilities with differentiating successes between different data sets. Another source for the prediction of solubility is structural features; they are commonly used for the prediction of solubility. However, there are little to no studies that combine three or more properties or descriptors for prediction to produce a more powerful prediction model. Unlike available models, we used a combination of those features in a random forest machine learning model for improved solubility prediction to better predict and, therefore, contribute to drug discovery systems.

Keywords: solubility, random forest, molecular descriptors, maccs keys

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Authors: Shedy Maharani Nariswari, Prima Agustia Nova, I. Made Kariasa

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Background. Heart Failure (HF) is a chronic and progressive condition associated with significant morbidity, mortality, health care expenditures, and a high readmission rate over the years. Self‐care is essential to manage chronic heart failure in the long term, and it is related to better outcomes and can enhance the quality of life. Objective. The aims of this study were to describe the relationship between self-care behavior and quality of life among heart failure patients in East Jakarta, Indonesia. Methods. This study used a correlational-descriptive design with a cross-sectional study, the sampling method used purposive sampling method. Self-care was measured using Self-care Heart Failure Index version 6.2, and quality of life was measured using The Minnesota Living with Heart Failure. Pearson correlation and Spearman-rho correlations are used to analyze the data. Results. We recruited 103 patients with HF in both outpatient and inpatient ward: mean age 59.26 ± 11.643 years, 63.1% male. Patients with higher levels of education were associated with higher self-care maintenance (p= 0.007). The patient's average quality of life is quite high, with a score of 72,07 ± 16,89. There were a significant relationship among self-care maintenance (r=0,305, p=0,001), self-care management (r=0,330, p=0,001), and self-care confidence (r=0,335, p=0,001) towards the quality of life. Most participants have inadequate self-care maintenance, self-care management, and self-care confidence (score < 70), while the score of quality of life is categorized as poor. Conclusion. The self-care behaviors were limited among patients living with HF in Indonesia yet was associated with better quality of life. It is necessary to promote health related to knowledge and adherence to self-care behavior so that it can improve the quality of life of heart failure patients. This study can be used as a reference to promote self-care among patients with heart failure, it can help to enhance their quality of life.

Keywords: heart failure, self-care maintenance, self-care management, self-care confidence, quality of life

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Authors: Antoni Wibowo, Harry Pujianto, Dewi Retno Sari Saputro

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The stock market can provide huge profits in a relatively short time in financial sector; however, it also has a high risk for investors and traders if they are not careful to look the factors that affect the stock market. Therefore, they should give attention to the dynamic fluctuations and movements of the stock market to optimize profits from their investment. In this paper, we present a nonlinear autoregressive exogenous model (NARX) to predict the movements of stock market; especially, the movements of the closing price index. As case study, we consider to predict the movement of the closing price in Indonesia composite index (IHSG) and choose the best structures of NARX for IHSG’s prediction.

Keywords: NARX (Nonlinear Autoregressive Exogenous Model), prediction, stock market, time series

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Authors: Yuki Irie, Shota Ogawa, Hitomi Kosugi, Hiromitsu Shinozaki

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Background: Dropout from higher educational institutions is a major problem both for students and institutions, and poor mental health is one of the risk factors. Medical college students are at higher risk of poor mental health than general students because of their hard academic schedules. On the other hand, food insecurity has negative impacts on mental health. The healthcare college of the project site is located heavily snowy area. The students without own vehicles may be at higher risk of food insecurity, especially in the winter season. Therefore, they have many risks to mental health. The aim of the study is to clarify the relationship between mental health and its risk factors to promote students’ mental well-being. Method: A cross-sectional design was used to investigate the relationship between mental health status and lifestyle, including diet and food security among the students (n=421, 147 male, 274 females; 20.7 ± 2.8 years old). Participants were required to answer 3 questionnaires which consisted of diet, lifestyle, food security, and mental health. The survey was conducted during the snowy season from Dec. 2022 to Jan. 2023. Results: Mean mental score was 6.7±4.6 (max. score 27, a higher score means worse mental health). Significant risk factors in mental health were breakfast habit (p=0.02), subjective dietary habit (p=0.00), subjective health (p=0.00), exercise habit (p=0.02), food insecurity in the winter season (p=0.01), and vitamin A intakes (p=0.03). Conclusions: Nutrients intakes are not associated with mental health except vitamin A; however, some other lifestyle factors are significantly associated with mental health. Nutrition doesn’t lead to poor mental health directly; however, the promotion of a healthy lifestyle and improved food security in winter may be effective in better mental health.

Keywords: mental health, winter, lifestyle, students

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Authors: Vinod K. Singh, S. G. Chung

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The degree of structuration of Busan clays at the mouth of Nakdong River mouth was highly influenced by the depositional environment, i.e., flow of the river stream, marine regression, and transgression during the sedimentation process. As a result, the geotechnical properties also varies along the depth with change in degree of structuration. Thus, the in-situ tests such as cone penetration test (CPT) could not be used to predict various geotechnical properties properly by using the conventional empirical methods. In this paper, the shear wave velocity (Vs) was measured from the field using the seismic dilatometer. The Vs was also measured in the laboratory from high quality undisturbed and remolded samples using bender element method to evaluate the degree of structuration. The degree of structuration was quantitatively defined by the modulus ratio of undisturbed to remolded soil samples which is found well correlated with the normalized void ratio (e0/eL) where eL is the void ratio at the liquid limit. It is revealed that the empirical method based on laboratory results incorporating e0/eL can predict Vs from the field more accurately. Thereafter, the CPT based empirical method was developed to estimate the shear wave velocity taking the effect of structuration in the consideration. The developed method was found to predict shear wave velocity reasonably for Busan clays.

Keywords: level of structuration, normalized modulus, normalized void ratio, shear wave velocity, site characterization

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Authors: Zhuang Guo

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In the field of GaN-based resonant tunneling diodes (RTDs) simulations, the traditional Tsu-Esaki formalism failed to predict the values of peak currents and peak voltages in the simulated current-voltage(J-V) characteristics. The main reason is that due to the strong internal polarization fields, two-dimensional electron gas(2DEG) accumulates at emitters, resulting in 2D-2D resonant tunneling currents, which become the dominant parts of the total J-V characteristics. By comparison, based on the 3D-2D resonant tunneling mechanism, the traditional Tsu-Esaki formalism cannot predict the J-V characteristics correctly. To overcome this shortcoming, we develop a new analytical model for the 2D-2D resonant tunneling currents generated in GaN-based RTDs. Compared with Tsu-Esaki formalism, the new model has made the following modifications: Firstly, considering the Heisenberg uncertainty, the new model corrects the expression of the density of states around the 2DEG eigenenergy levels at emitters so that it could predict the half width at half-maximum(HWHM) of resonant tunneling currents; Secondly, taking into account the effect of bias on wave vectors on the collectors, the new model modifies the expression of the transmission coefficients which could help to get the values of peak currents closer to the experiment data compared with Tsu-Esaki formalism. The new analytical model successfully predicts the J-V characteristics of GaN-based RTDs, and it also reveals more detailed mechanisms of resonant tunneling happened in GaN-based RTDs, which helps to design and fabricate high-performance GaN RTDs.

Keywords: GaN-based resonant tunneling diodes, tsu-esaki formalism, 2D-2D resonant tunneling, heisenberg uncertainty

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Authors: Rachel S. E. Lim, Winnie L. C. Tan

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Visual literacy is about making meaning through the interaction of images, words, and sounds. Graphic communication students typically develop visual literacy through critique and production of studio-based projects for their portfolios. However, the abrupt switch to online learning during the COVID-19 pandemic has made it necessary to consider new strategies of visualization and planning to scaffold teaching and learning. This study, therefore, investigated how MIRO, a cloud-based visual collaboration platform, could be used to develop the visual literacy confidence of 30 diploma in graphic communication students attending a graphic design course at a Singapore arts institution. Due to COVID-19, the course was taught fully online throughout a 16-week semester. Guided by Kolb’s Experiential Learning Cycle, the two lecturers developed students’ engagement with visual literacy concepts through different activities that facilitated concrete experiences, reflective observation, abstract conceptualization, and active experimentation. Throughout the semester, students create, collaborate, and centralize communication in MIRO with infinite canvas, smart frameworks, a robust set of widgets (i.e., sticky notes, freeform pen, shapes, arrows, smart drawing, emoticons, etc.), and powerful platform capabilities that enable asynchronous and synchronous feedback and interaction. Students then drew upon these multimodal experiences to brainstorm, research, and develop their motion design project. A survey was used to examine students’ perceptions of engagement (E), confidence (C), learning strategies (LS). Using multiple regression, it¬ was found that the use of MIRO helped students develop confidence (C) with visual literacy, which predicted performance score (PS) that was measured against their application of visual literacy to the creation of their motion design project. While students’ learning strategies (LS) with MIRO did not directly predict confidence (C) or performance score (PS), it fostered positive perceptions of engagement (E) which in turn predicted confidence (C). Content analysis of students’ open-ended survey responses about their learning strategies (LS) showed that MIRO provides organization and structure in documenting learning progress, in tandem with establishing standards and expectations as a preparatory ground for generating feedback. With the clarity and sequence of the mentioned conditions set in place, these prerequisites then lead to the next level of personal action for self-reflection, self-directed learning, and time management. The study results show that the affordances of MIRO can develop visual literacy and make up for the potential pitfalls of student isolation, communication, and engagement during online learning. The context of how MIRO could be used by lecturers to orientate students for learning in visual literacy and studio-based projects for future development are discussed.

Keywords: design education, graphic communication, online learning, visual literacy

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Authors: Paul Dallyn, Ashraf El-Hamalawi, Alessandro Palmeri, Bob Knight

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In order to better understand the long term implications of the grout wear failure mode in large-diameter plain-sided grouted connections, a numerical model has been developed and calibrated that can take advantage of existing operational plant data to predict the wear accumulation for the actual load conditions experienced over a given period, thus limiting the need for expensive monitoring systems. This model has been derived and calibrated based on site structural condition monitoring (SCM) data and supervisory control and data acquisition systems (SCADA) data for two operational wind turbine generator substructures afflicted with this challenge, along with experimentally derived wear rates.

Keywords: grouted connection, numerical model, offshore structure, wear, wind energy

Procedia PDF Downloads 432

Authors: O. Davies, K. Veravalli, P. Panwalkar, M. Tofighi, P. Butterick, B. Healy, A. Mofidi

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Vancomycin resistant enterococcus infection is a condition that usually impacts ICUs, transplant, dialysis, and cancer units, often as a nosocomial infection. After an outbreak in the acute trauma and orthopaedic unit in Morriston hospital, we aimed to access the conditions that predispose VRE infections in our unit. Thirteen cases of VRE infection and five cases of VRE colonisations were identified in patients who were treated for orthopaedic care between 1/1/2020 and 1/11/2021. Cases were reviewed to identify predisposing factors, specifically looking at age, presenting condition and treatment, presence of infection and antibiotic care, active haemo-oncological condition, long term renal dialysis, previous hospitalisation, VRE predisposition, and clearance (PREVENT) scores, and outcome of care. The presenting condition, treatment, presence of postoperative infection, VRE scores, age was compared between colonised and the infected cohort. VRE type in both colonised and infection group was Enterococcus Faecium in all but one patient. The colonised group had the same age (T=0.6 P>0.05) and sex (2=0.115, p=0.74), presenting condition and treatment which consisted of peri-femoral fixation or arthroplasty in all patients. The infected group had one case of myelodysplasia and four cases of chronic renal failure requiring dialysis. All of the infected patient had sustained an infected complication of their fracture fixation or arthroplasty requiring reoperation and antibiotics. The infected group had an average VRE predisposition score of 8.5 versus the score of 3 in the colonised group (F=36, p<0.001). PREVENT score was 7 in the infected group and 2 in the colonised group(F=153, p<0.001). Six patients(55%) succumbed to their infection, and one VRE infection resulted in limb loss. In the orthopaedic cohort, VRE infection is a nosocomial condition that has peri-femoral predilection and is seen in association with immunosuppression or renal failure. The VRE infection cohort has been treated for infective complication of original surgery weeks prior to VRE infection. Based on our findings, we advise avoidance of infective complications, change of practice in use of antibiotics and use radical surgery and surveillance for VRE infections beyond infective precautions. PREVENT score shows that the infected group are unlikely to clear their VRE in the future but not the colonised group.

Keywords: surgical site infection, enterococcus, orthopaedic surgery, vancomycin resistance

Procedia PDF Downloads 120

Authors: Melody Yin

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Concussions impact a large amount of adolescents; they make up as much as half of the diagnosed concussions in America. This research proposes a hybrid machine learning model based on the combination of human/knowledge-based domains and computer-generated feature rankings to improve the accuracy of diagnosing sports related concussion (SRC). Using a data set of symptoms collected on the sideline post-SRC events, the symptom selection criteria method has been developed by using Google AutoML's important score function to identify the top 10 symptom features. In addition, symptom domains have been introduced as another parameter, categorizing the symptoms into physical, cognitive, sleep, and emotional domains. The hybrid machine learning model has been trained with a combination of the top 10 symptoms and 4 domains. From the results, the hybrid model was the best performer for symptom resolution time prediction in 2 and 4-week thresholds. This research is a proof of concept study in the use of domains along with machine learning in order to improve concussion prediction accuracy. It is also possible that the use of domains can make the model more efficient due to reduced training time. This research examines the use of a hybrid method in predicting sports-related concussion. This achievement is based on data preprocessing, using a hybrid method to select criteria to achieve high performance.

Keywords: hybrid model, machine learning, sports related concussion, symptom resolution time

Procedia PDF Downloads 150

Authors: Chariya Laohavich, Viboon Bunsrangsuk

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Objective: Bronchoscopy is a common outpatient procedure. The authors compared the patient anxiety level before and after received video-assisted procedural information. Method: One hundred and twenty patients who never received bronchoscopy and scheduled for elective bronchoscopy at outpatient Bronchosope unit at Ramathibodi Hospital, Mahidol University were randomized into control and intervention group. Video-assisted procedural information was given in intervention group. Pre and post procedural anxiety score were recorded and compared between two groups. Paired T-test was used for statistical analysis. Result: There was statistically significant decrease (p < 0.001) for anxiety score in patients who received video assisted procedural information compare with control group. Conclusion: Video-assisted procedural information should be given to patient who will have bronchoscopy to reduce anxiety.

Keywords: anxiety, bronchoscopy, video compact disc (VCD)

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Authors: Petros Roussos

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The present study focused on students' statistical reasoning related to Null Hypothesis Statistical Testing and p-values. Its objective was to test the hypothesis that neither the place (classroom, at a distance, online) nor the medium that actually supports the learning (ICT, internet, books) has an effect on understanding of statistical concepts. In addition, it was expected that students' attitudes towards statistics would not predict understanding of statistical concepts. The sample consisted of 385 undergraduate and postgraduate students from six state and private universities (five in Greece and one in Cyprus). Students were administered two questionnaires: a) the Greek version of the Survey of Attitudes Toward Statistics, and b) a short instrument which measures students' understanding of statistical significance and p-values. Results suggest that attitudes towards statistics do not predict students' understanding of statistical concepts, whereas the medium did not have an effect.

Keywords: attitudes towards statistics, blended learning, e-learning, statistical reasoning

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Authors: Ainura Tursunalieva, Irene Hudson

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Continuous improvement of both the quality and safety of health care is an important goal in Australia and internationally. The intensive care unit (ICU) receives patients with a wide variety of and severity of illnesses. Accurately identifying patients at risk of developing complications or dying is crucial to increasing healthcare efficiency. Thus, it is essential for clinicians and researchers to have a robust framework capable of evaluating the risk profile of a patient. ICU scoring systems provide such a framework. The Acute Physiology and Chronic Health Evaluation III and the Simplified Acute Physiology Score II are ICU scoring systems frequently used for assessing the severity of acute illness. These scoring systems collect multiple risk factors for each patient including physiological measurements then render the assessment outcomes of individual risk factors into a single numerical value. A higher score is related to a more severe patient condition. Furthermore, the Mortality Probability Model II uses logistic regression based on independent risk factors to predict a patient’s probability of mortality. An important overlooked limitation of SAPS II and MPM II is that they do not, to date, include interaction terms between a patient’s vital signs. This is a prominent oversight as it is likely there is an interplay among vital signs. The co-existence of certain conditions may pose a greater health risk than when these conditions exist independently. One barrier to including such interaction terms in predictive models is the dimensionality issue as it becomes difficult to use variable selection. We propose an innovative scoring system which takes into account a dependence structure among patient’s vital signs, such as systolic and diastolic blood pressures, heart rate, pulse interval, and peripheral oxygen saturation. Copulas will capture the dependence among normally distributed and skewed variables as some of the vital sign distributions are skewed. The estimated dependence parameter will then be incorporated into the traditional scoring systems to adjust the points allocated for the individual vital sign measurements. The same dependence parameter will also be used to create an alternative copula-based model for predicting a patient’s probability of mortality. The new copula-based approach will accommodate not only a patient’s trajectories of vital signs but also the joint dependence probabilities among the vital signs. We hypothesise that this approach will produce more stable assessments and lead to more time efficient and accurate predictions. We will use two data sets: (1) 250 ICU patients admitted once to the Chui Regional Hospital (Kyrgyzstan) and (2) 37 ICU patients’ agitation-sedation profiles collected by the Hunter Medical Research Institute (Australia). Both the traditional scoring approach and our copula-based approach will be evaluated using the Brier score to indicate overall model performance, the concordance (or c) statistic to indicate the discriminative ability (or area under the receiver operating characteristic (ROC) curve), and goodness-of-fit statistics for calibration. We will also report discrimination and calibration values and establish visualization of the copulas and high dimensional regions of risk interrelating two or three vital signs in so-called higher dimensional ROCs.

Keywords: copula, intensive unit scoring system, ROC curves, vital sign dependence

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Authors: Mohsen Varzande

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Translators’ professional and academic characteristics may directly influence their translation quality. The present study aimed at investigating whether translators’ degree in translation and years of professional experience predict their translation quality. Following a causal-comparative study, a sample of one hundred professional translators was selected using purposive sampling method. The participants were divided into two groups each containing individuals with and without a degree in translation, respectively. The participants were asked to translate a paragraph to assess their translation quality. For data analysis, appropriate statistical procedures including correlation and regression were used. Results showed that both degree in translation and years of professional experience significantly predict translation quality. Also, the interaction of translators’ years of professional experience and degree in translation significantly affect their translation quality. An implication could be that besides providing translators with academic knowledge and theories, practical training in translation is necessary as a prerequisite for a competent translator.

Keywords: translation, degree in translation, translation quality, professional experience

Procedia PDF Downloads 406

Authors: Weerakarj Dokchan

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The purposes of this research are to find out the factors for developing trainers in the auto part manufacturing factories (AMF) in Amata Nakon Industrial Estate Cholburi. Population in this study included 148 operators to complete the questionnaires and 10 trainers to provide the information on the interview. The research statistics consisted of percentage, mean, standard deviation and step-wise multiple linear regression analysis.The analysis of the training model revealed that: The research result showed that the development factors of trainers in AMF consisted of 3 main factors and 8 sub-factors: 1) knowledge competency consisting of 4 sub-factors; arrangement of critical thinking, organizational loyalty, working experience of the trainers, analysis of behavior, and work and organization loyalty which could predict the success of the trainers at 55.60%. 2) Skill competency consisted of 4 sub-factors, arrangement of critical thinking, organizational loyalty and analysis of behavior and work and the development of emotional quotient. These 4 sub-factors could predict the success of the trainers in skill aspect 55.90%. 3) The attitude competency consisted of 4 sub-factors, arrangement of critical thinking, intention of trainee computer competency and teaching psychology. In conclusion, these 4 sub-factors could predict the success of the trainers in attitude aspect 58.50%.

Keywords: the development factors, trainers development, trainer competencies, auto part manufacturing factory (AMF), AmataNakon Industrial Estate Cholburi

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Authors: Raghuveer Kaur, Kartikay Sharma, Ashu Khanna

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Earnings management has been present from times immemorial. The recent downfall of giant enterprises like Enron, Satyam and WorldCom has brought a lot of focus on the study and detection of earnings management. The present study is an attempt to study earnings management in one of the fastest emerging economy - India. The study makes an attempt to understand earnings management in different sectors of the economy. The paper first tests a hypothesis to check whether different sectors of India are engaged in earnings management or not. In the later section the paper aims to study the level of earnings management in 6 popular sectors of India: IT&BPO, Retail, Telecom, Biotech, Hotels and coffee. To measure earnings management two popular techniques of detecting earnings management has been employed: Modified Jones Model and Beniesh M Score. A total of 332 companies were studied. Publicly available data from Capitaline database has been used. The paper also classifies the top and bottom five performers on the basis of sales turnover in each sector and identifies whether they manage their earnings or not.

Keywords: earnings management, India, modified Jones model, Beneish M score

Procedia PDF Downloads 494