Search results for: generalized propensity score

Authors: Chengbin Wang, Li Lu, Luodan Suo, Qinghai Wang, Fan Yang, Xu Wang, Mona Marin

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Background: Two-dose varicella vaccination has been recommended in Beijing since November 2012. We investigated a varicella outbreak in a highly vaccinated elementary school population to examine transmission patterns and risk factors for vaccine failure. Methods: A varicella case was defined as an acute generalized maculopapulovesicular rash without other apparent cause in a student attending the school from March 28 to May 17, 2015. Breakthrough varicella was defined as varicella >42 days after last vaccine dose. Vaccination information was collected from immunization records. Information on prior disease and clinical presentation was collected via survey of students’ parents. Results: Of the 1056 school students, 1028 (97.3%) reported no varicella history, of whom 364 (35.4%) had received 1-dose and 650 (63.2%) had received 2-dose varicella vaccine, for 98.6% school-wide vaccination coverage with ≥ 1 dose before the outbreak. A total of 20 cases were identified for an overall attack rate of 1.9%. The index case was in a 2-dose vaccinated student who was not isolated. The majority of cases were breakthrough (19/20, 95%) with attack rates of 7.1% (1/14), 1.6% (6/364) and 2.0% (13/650) among unvaccinated, 1-dose, and 2-dose students, respectively. Most cases had < 50 lesions (18/20, 90%). No difference was found between 1-dose and 2-dose breakthrough cases in disease severity or sociodemographic factors. Conclusion: Moderate 2-dose varicella vaccine coverage was insufficient to prevent a varicella outbreak. Two-dose breakthrough varicella is still contagious. High 2-dose varicella vaccine coverage and timely isolation of ill persons might be needed for varicella outbreak control in the 2-dose era.

Keywords: varicella, outbreak, breakthrough varicella, vaccination

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Authors: Komon Paisal

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The purposes of this research were (1) to create a learning activity for constructivism, (2) study the Mathematical Analysis courses learning achievement, and (3) study students’ attitude toward the learning activity for constructivism. The samples in this study were divided into 2 parts including 3 Mathematical Analysis courses instructors of Suan Sunandha Rajabhat University who provided basic information and attended the seminar and 17 Mathematical Analysis courses students who were studying in the academic and engaging in the learning activity for constructivism. The research instruments were lesson plans constructivism, subjective Mathematical Analysis courses achievement test with reliability index of 0.8119, and an attitude test concerning the students’ attitude toward the Mathematical Analysis courses learning activity for constructivism. The result of the research show that the efficiency of the Mathematical Analysis courses learning activity for constructivism is 73.05/72.16, which is more than expected criteria of 70/70. The research additionally find that the average score of learning achievement of students who engaged in the learning activities for constructivism are equal to 70% and the students’ attitude toward the learning activity for constructivism are at the medium level.

Keywords: constructivism, learning management, mathematics analysis courses, learning activity

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Authors: Abdullah M. Alzahrani

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The karyotypes of Khalas (KH), Sukkary (SK), Sheeshi (SS), Shibeebi (SB) and Sillije (SJ) date palm cultivars were investigated. Data showed no variation in chromosome number, 2n = 36, 34 autosomes in addition to XX in females and XY in males. Mean autosomes length ranged from 3.85-9.93 μm and 3.71-2.73 μm for X and Y chromosomes, respectively. The formula of female date palm karyotype was 8m + 4sm +2st + 4t, and submedian Y chromosome. Relative chromosome length ranged from 3.3- 9.38 μm. SS cultivar showed high asymmetry levels by scoring low values of Syi (45.51), TF (42.8) and high values for A1 (0.53), A (0.41) and AI (0.29). Syi developed an inverse relation with A1 and A while A exhibited a direct correlation with A1. Cultivars SK, SB and SJ score medium values of Syi, A1, AI and A. KH cultivar exhibited high symmetry by scoring highest values of Syi (53.68), TF (51.81) and lowest values of A1 (0.44), A (0.34) and AI (0.18). Higher DI value was obtained in SB cultivar (1.34) followed by SJ (1.15) and low DI scores of 0.99, 0.86 and 0.71 were detected in KH, SS and SK, respectively. Stebbins classification assorted SS as 3B and the other cultivars as 2B, insuring the evolution and asymmetry of SS compared to the other karyotypes. Scatter diagram of Syi-A1 couple has the advantage of revealing high degree of sensitivity to present karyotype interrelationships, followed by AI-A and CVCL-CVCI couples.

Keywords: Karyotype, date palm, Khalas, Sukkary, Sheeshi

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Authors: Nadia Obaed, Lexi Frankel, Amalia Ardeljan, Denis Nigel, Anniki Witter, Omar Rashid

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Breast cancer is the most common cancer among women, with a lifetime risk of one in eight of all women in the United States. Although breast cancer is prevalent throughout the world, the uneven distribution in incidence and mortality rates is shaped by the variation in population structure, environment, genetics and known lifestyle risk factors. Furthermore, the bacterial profile in healthy and cancerous breast tissue differs with a higher relative abundance of bacteria capable of causing DNA damage in breast cancer patients. Previous bacterial infections may change the composition of the microbiome and partially account for the environmental factors promoting breast cancer. One study found that higher amounts of Staphylococcus, Bacillus, and Enterobacteriaceae, of which Escherichia coli (E. coli) is a part, were present in breast tumor tissue. Based on E. coli’s ability to damage DNA, it is hypothesized that there is an increased risk of breast cancer associated with previous E. coli infection. Therefore, the purpose of this study was to evaluate the correlation between E. coli infection and the incidence of breast cancer. Holy Cross Health, Fort Lauderdale, provided access to the Health Insurance Portability and Accountability (HIPAA) compliant national database for the purpose of academic research. International Classification of Disease 9th and 10th Codes (ICD-9, ICD-10) was then used to conduct a retrospective analysis using data from January 2010 to December 2019. All breast cancer diagnoses and all patients infected versus not infected with E. coli that underwent typical E. coli treatment were investigated. The obtained data were matched for age, Charlson Comorbidity Score (CCI score), and antibiotic treatment. Standard statistical methods were applied to determine statistical significance and an odds ratio was used to estimate the relative risk. A total of 81286 patients were identified and analyzed from the initial query and then reduced to 31894 antibiotic-specific treated patients in both the infected and control group, respectively. The incidence of breast cancer was 2.51% and present in 2043 patients in the E. coli group compared to 5.996% and present in 4874 patients in the control group. The incidence of breast cancer was 3.84% and present in 1223 patients in the treated E. coli group compared to 6.38% and present in 2034 patients in the treated control group. The decreased incidence of breast cancer in the E. coli and treated E. coli groups was statistically significant with a p-value of 2.2x10-16 and 2.264x10-16, respectively. The odds ratio in the E. coli and treated E. coli groups was 0.784 and 0.787 with a 95% confidence interval, respectively (0.756-0.813; 0.743-0.833). The current study shows a statistically significant decrease in breast cancer incidence in association with previous Escherichia coli infection. Researching the relationship between single bacterial species is important as only up to 10% of breast cancer risk is attributable to genetics, while the contribution of environmental factors including previous infections potentially accounts for a majority of the preventable risk. Further evaluation is recommended to assess the potential and mechanism of E. coli in decreasing the risk of breast cancer.

Keywords: breast cancer, escherichia coli, incidence, infection, microbiome, risk

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Authors: Anh Dao Vu, Bill Ryan

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The Vietnamese government struggles to grapple with the problem of rampant corruption, one of the most challenging difficulties the country faces. According to Transparency International’s Corruption Perceptions Index (CPI) 2014, Vietnam ranks 119 out of 175 countries. The CPI gives Vietnam a score of 31 on a scale from 0 to 100, where 0 indicates ‘highly corrupt’ and 100 represents ‘very clean’. Corruption eats into the national GDP of Vietnam, causing a loss of 3% to 4% of GDP per annum. In general, the Vietnamese people’s trust in their government to wage an effective fight against corruption, especially in the public sector, has been greatly eroded in recent years. Some substantial public demonstrations persuaded the government to implement strong anti-corruption measures. However, so far those measures have not been particularly successful. One of the main reasons for this shortcoming is that neither the Communist Party of Vietnam nor the government has demonstrated sufficiently strong ‘political will’ in fighting corruption. There remains a large gap between rhetoric and reality. This paper will examine the reasons why insufficient ‘political will’ is displayed in the ostensible fight against public sector corruption, and how certain anti-corruption strategies will both strengthen levels of political commitment to the fight against corruption while enhancing the effectiveness of that essential national endeavor.

Keywords: corruption, political will, Vietnam, anti-corruption

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Authors: Yang Zhang, Jian He

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Heart disease is one of the leading causes of death in the world, and coronary heart disease (CHD) is one of the major heart diseases. Electrocardiogram (ECG) is widely used in the detection of heart diseases, but the traditional manual method for CHD prediction by analyzing ECG requires lots of professional knowledge for doctors. This paper introduces sliding window and continuous wavelet transform (CWT) to transform ECG signals into images, and then ResNet and Bi-LSTM are introduced to build the ECG feature extraction network (namely ECGNet). At last, an auxiliary system for coronary heart disease prediction was developed based on modified ResNet18 and Bi-LSTM, and the public ECG dataset of CHD from MIMIC-3 was used to train and test the system. The experimental results show that the accuracy of the method is 83%, and the F1-score is 83%. Compared with the available methods for CHD prediction based on ECG, such as kNN, decision tree, VGGNet, etc., this method not only improves the prediction accuracy but also could avoid the degradation phenomenon of the deep learning network.

Keywords: Bi-LSTM, CHD, ECG, ResNet, sliding window

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Authors: T. Ito, K. Kawaguchi, R. Ohta

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The purpose of this study is to provide a guideline to assist globally-minded companies in developing task-based English-language programs for their employees. After conducting an online self-assessment questionnaire comprised of 45 job-related tasks, we analyzed responses received from 3,000 Japanese company employees and developed a checklist that considered three areas: (i) the percentage of those who need to accomplish English-language tasks in their workplace (need for English), (ii) a five-point self-assessment score (task performance level), and (iii) the impact of previous task experience on perceived performance (experience factor). The 45 tasks were graded according to five proficiency levels. Our results helped us to create a core guideline that may assist companies in two ways: first, in helping determine which tasks employees with a certain English proficiency should be able to satisfactorily carry out, and secondly, to quickly prioritize which business-related English skills they would need in future English language programs.

Keywords: business settings, can-do statements, English language training programs, self-assessment, task experience

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Authors: Ammal Mokhtar Metwally, Amal Elsaied, Ghada A. Abdel-Latef, Ebtissam M. Salah El-Din, Hanaa R. M. Attia

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The link between various diet therapies and autism is controversial and limited. Nutritional interventions aim to increase antioxidant levels suggesting a positive effect on the improvement of autism severity. In this study, the effectiveness of a 90-day Dates fruits consumption fruits (a non-pharmacological and risk-free option) on alleviating autism severity symptoms in individuals with ASD was investigated. The study examined also whether the baseline or improvements of some of the clinical and laboratory characteristics of the subjects affected their response to dates fruits intake on the severity of ASD symptoms. Methodology: This study involved a randomized controlled, double-blind 3-month dates fruits intake. 131 Egyptian children aged 3-12 years with confirmed ASD were enrolled in the study. cases were randomized in one of the three groups as follows; 1st regimen: Group I on 3 dates’ fruits/day (47 cases), 2nd regimen: Group II on 5 dates’ fruits/day (42 cases), and 3rd regimen: group III; nondates group (42 cases). ASD severity was assessed using both the Diagnostic and statistical manual of mental disorders, 5th ed. (DSM-V) criteria and the Childhood Autism Rating Scale (CARS) analysis. The following measures were assessed before and after the regimens: blood levels of three oxidative markers; Malondialdehyde (MDA), glutathione peroxidase (GPX1), and superoxide dismutase (SOD), nutritional, dietary assessment & anthropometric measurements Results: A significant reduction in the mean score of autism was detected based on CARS scores for those on dates’ regimens compared to those on non-dates (p < 0.01). Participants on 5 dates’ fruits/day for three months showed the highest improvement for autism severity based on both CARS and DSM5 compared to those in 3 dates’ fruits/day and non-dates groups. Responders to dates fruits intake as reflected on the Improvement of autism severity based on CARS diagnosis was detected among 78.7 % and 62.9 % based on CARS and DSM5 diagnosis, respectively. Responders had significant improvement in BMI z score and in the ratio levels of both MDA/SOD and MDA/GPX. Conclusion: The positive results of this study suggest that palm dates fruits could be recommended for children with ASD as adjuvant therapy on a daily regular basis to achieve consistent improvement of autism symptoms Objective: Investigate the effectiveness of a 90-day Dates fruits consumption fruits on alleviating autism severity symptoms in individuals with ASD and explore the clinical and laboratory characteristics of the subjects affected their response to dates fruits intake. Methodology: The study was a randomized controlled, double-blind for 3-month. 131 autistic Egyptian children aged 3-12 years were enrolled in one of the three groups; 1st: on 3 dates’ fruits/day (47 cases), 2nd: Group II on 5 dates’ fruits/day (42 cases), and 3rd: group III; nondates group (42 cases). Conclusion: The positive results of this study suggest that palm dates fruit (a non-pharmacological and risk-free option) could be recommended for children with ASD as adjuvant therapy on a daily regular basis to achieve consistent improvement of autism symptoms.

Keywords: autism spectrum disorders, palm dates fruits, CARS, DSM5, oxidative markers

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Authors: R. B. Knudsen, O. T. Rasmussen, R. A. Alphinas

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The reason for conducting this research is to develop an algorithm that is capable of classifying news articles from the automobile industry, according to the competitive actions that they entail, with the use of Text Mining (TM) methods. It is needed to test how to properly preprocess the data for this research by preparing pipelines which fits each algorithm the best. The pipelines are tested along with nine different classification algorithms in the realm of regression, support vector machines, and neural networks. Preliminary testing for identifying the optimal pipelines and algorithms resulted in the selection of two algorithms with two different pipelines. The two algorithms are Logistic Regression (LR) and Artificial Neural Network (ANN). These algorithms are optimized further, where several parameters of each algorithm are tested. The best result is achieved with the ANN. The final model yields an accuracy of 0.79, a precision of 0.80, a recall of 0.78, and an F1 score of 0.76. By removing three of the classes that created noise, the final algorithm is capable of reaching an accuracy of 94%.

Keywords: Artificial Neural network, Competitive dynamics, Logistic Regression, Text classification, Text mining

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Authors: Jong Hoon Kim, Hyun-Soo Lee, Moonseo Park, Min Jeong, Inbeom Lee

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Pre-construction is essential in achieving the success of a construction project. Due to the early involvement of project participants in the construction phase, project managers are able to plan ahead and solve issues well in advance leading to the success of the project and the satisfaction of the client. This research utilizes quantitative data derived from construction management projects in order to identify the relationship between pre-construction, construction schedule, and client satisfaction. A total of 65 construction projects and 93 clients were investigated for this research in an attempt to identify (a) the relationship between pre-construction and schedule reduction, and (b) pre-construction and client loyalty. Based on the quantitative analysis, this research was able to establish a negative correlation based on 65 construction projects between pre-construction and project schedule existed. This finding represents that the more pre-construction is performed for a certain project, the overall construction schedule decreased. Then, to determine the relationship between pre-construction and client satisfaction, Net Promoter Score (NPS) of 93 clients from the 65 projects was utilized. Pre-construction and NPS was further analyzed and a positive correlation was found between the two. This infers that clients tend to be more satisfied with projects with higher ratio of pre-construction than those projects with less pre-construction.

Keywords: client loyalty, NPS, pre-construction, schedule reduction

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Authors: Sifriyani Sifriyani, I Nyoman Budiantara, Sri Haryatmi, Gunardi Gunardi

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East Java Province has a first rank as a province that has the most counties and cities in Indonesia and has the largest population. In 2015, the population reached 38.847.561 million, this figure showed a very high population growth. High population growth is feared to lead to increase the levels of unemployment. In this study, the researchers mapped and modeled the unemployment rate with 6 variables that were supposed to influence. Modeling was done by nonparametric geographically weighted regression methods with truncated spline approach. This method was chosen because spline method is a flexible method, these models tend to look for its own estimation. In this modeling, there were point knots, the point that showed the changes of data. The selection of the optimum point knots was done by selecting the most minimun value of Generalized Cross Validation (GCV). Based on the research, 6 variables were declared to affect the level of unemployment in eastern Java. They were the percentage of population that is educated above high school, the rate of economic growth, the population density, the investment ratio of total labor force, the regional minimum wage and the ratio of the number of big industry and medium scale industry from the work force. The nonparametric geographically weighted regression models with truncated spline approach had a coefficient of determination 98.95% and the value of MSE equal to 0.0047.

Keywords: East Java, nonparametric geographically weighted regression, spatial, spline approach, unemployed rate

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Authors: Chad Goldsworthy, B. Rajeswari Matam

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The use of deep learning for species identification in camera trap images has revolutionised our ability to study, conserve and monitor species in a highly efficient and unobtrusive manner, with state-of-the-art models achieving accuracies surpassing the accuracy of manual human classification. The high imbalance of camera trap datasets, however, results in poor accuracies for minority (rare or endangered) species due to their relative insignificance to the overall model accuracy. This paper investigates the use of Focal Loss, in comparison to the traditional Cross Entropy Loss function, to improve the identification of minority species in the “255 Bird Species” dataset from Kaggle. The results show that, although Focal Loss slightly decreased the accuracy of the majority species, it was able to increase the F1-score by 0.06 and improve the identification of the bottom two, five and ten (minority) species by 37.5%, 15.7% and 10.8%, respectively, as well as resulting in an improved overall accuracy of 2.96%.

Keywords: convolutional neural networks, data imbalance, deep learning, focal loss, species classification, wildlife conservation

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Authors: Sujit Kumar Pradhan, Anil Kumar, Vijay Kumar

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The testing process of the software during the software development time is a crucial step as it makes the software more efficient and dependable. To estimate software’s reliability through the mean value function, many software reliability growth models (SRGMs) were developed under the assumption that operating and testing environments are the same. Practically, it is not true because when the software works in a natural field environment, the reliability of the software differs. This article discussed an SRGM comprising change-point and imperfect debugging in a simulated testing environment. Later on, we extended it in a multi-release direction. Initially, the software was released to the market with few features. According to the market’s demand, the software company upgraded the current version by adding new features as time passed. Therefore, we have proposed a generalized multi-release SRGM where change-point and imperfect debugging concepts have been addressed in a simulated testing environment. The failure-increasing rate concept has been adopted to determine the change point for each software release. Based on nine goodness-of-fit criteria, the proposed model is validated on two real datasets. The results demonstrate that the proposed model fits the datasets better. We have also discussed the optimal release time of the software through a cost model by assuming that the testing and debugging costs are time-dependent.

Keywords: software reliability growth models, non-homogeneous Poisson process, multi-release software, mean value function, change-point, environmental factors

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Authors: Pratibha, Jyoti Kori

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Particles in industry, harvesting, coal mines, etc. may not necessarily be spherical in shape. In general, it is difficult to find perfectly spherical particle. The prediction of movement and deposition of non spherical particle in distinct airway generation is much more difficult as compared to spherical particles. Moreover, there is extensive inflexibility in deposition between ducts of a particular generation and inside every alveolar duct since particle concentrations can be much bigger than the mean acinar concentration. Consequently, a large number of particles fail to be exhaled during expiration. This study presents a mathematical model for the movement and deposition of those non-spherical particles by using particle aspect ratio and shape factor. We analyse the pulsatile behavior underneath sinusoidal wall oscillation due to periodic breathing condition through a non-Darcian porous medium or inside pulmonary region. Since the fluid is viscous and Newtonian, the generalized Navier-Stokes equation in two-dimensional coordinate system (r, z) is used with boundary-layer theory. Results are obtained for various values of Reynolds number, Womersley number, Forchsheimer number, particle aspect ratio and shape factor. Numerical computation is done by using finite difference scheme for very fine mesh in MATLAB. It is found that the overall air velocity is significantly increased by changes in aerodynamic diameter, aspect ratio, alveoli size, Reynolds number and the pulse rate; while velocity is decreased by increasing Forchheimer number.

Keywords: deposition, interstitial lung diseases, non-Darcian medium, numerical simulation, shape factor

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Authors: Ayesha S. Rahman, Khaled Haddad, Ataur Rahman

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At-site flood frequency analysis is used to estimate flood quantiles when at-site record length is reasonably long. In Australia, FLIKE software has been introduced for at-site flood frequency analysis. The advantage of FLIKE is that, for a given application, the user can compare a number of most commonly adopted probability distributions and parameter estimation methods relatively quickly using a windows interface. The new version of FLIKE has been incorporated with the multiple Grubbs and Beck test which can identify multiple numbers of potentially influential low flows. This paper presents a case study considering six catchments in eastern Australia which compares two outlier identification tests (original Grubbs and Beck test and multiple Grubbs and Beck test) and two commonly applied probability distributions (Generalized Extreme Value (GEV) and Log Pearson type 3 (LP3)) using FLIKE software. It has been found that the multiple Grubbs and Beck test when used with LP3 distribution provides more accurate flood quantile estimates than when LP3 distribution is used with the original Grubbs and Beck test. Between these two methods, the differences in flood quantile estimates have been found to be up to 61% for the six study catchments. It has also been found that GEV distribution (with L moments) and LP3 distribution with the multiple Grubbs and Beck test provide quite similar results in most of the cases; however, a difference up to 38% has been noted for flood quantiles for annual exceedance probability (AEP) of 1 in 100 for one catchment. These findings need to be confirmed with a greater number of stations across other Australian states.

Keywords: floods, FLIKE, probability distributions, flood frequency, outlier

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Authors: David Tran, Sina Gallo, Jenny Lin

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The present study investigated two adolescent populations between the ages of 10-14 years of age from two different studies: a dietary assessment validation study conducted at the Georgia 4-H Rock Eagle summer camp (Eatonton, Georgia) and a middle-school diet study at an Alabama middle school (Birmingham, Alabama). Energy intake and meal consumption were recorded via either direct observation of camp lunch or weighing and photography of school lunch trays. Child weight and height were measured to calculate Body Mass Index (BMI) and compared to CDC growth charts to assess percentile or Z-score. Results showed that those participants categorized with higher BMI had a statistically significant and positive correlation with energy intake (kcal). Future research should increase the sample size and include a broader subject size which includes those of a younger childhood population, to assess the effect of age.

Keywords: BMI, adolescent, direct observation, dietary intake

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Authors: Hassan Younis

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Purpose: The objective of this study is to review influential papers in the sustainability and supply chain studies domain, leveraging insights from this review to develop a structured framework for academics and researchers. This framework aims to assist scholars in identifying the most impactful publications for their scholarly pursuits. Subsequently, the study will apply and trial the developed framework on selected scholarly articles within the sustainability and supply chain studies domain to evaluate its efficacy, practicality, and reliability. Design/Methodology/Approach: Utilizing the "Publish or Perish" tool, a search was conducted to locate papers incorporating "sustainability" and "supply chain" in their titles. After rigorous filtering steps, a panel of university professors identified five crucial criteria for evaluating research robustness: average yearly citation counts (25%), scholarly contribution (25%), alignment of findings with objectives (15%), methodological rigor (20%), and journal impact factor (15%). These five evaluation criteria are abbreviated as “ACMAJ" framework. Each paper then received a tiered score (1-3) for each criterion, normalized within its category, and summed using weighted averages to calculate a Final Normalized Score (FNS). This systematic approach allows for objective comparison and ranking of the research based on its impact, novelty, rigor, and publication venue. Findings: The study's findings highlight the lack of structured frameworks for assessing influential sustainability research in supply chain management, which often results in a dependence on citation counts. A complete model that incorporates five essential criteria has been suggested as a response. By conducting a methodical trial on specific academic articles in the field of sustainability and supply chain studies, the model demonstrated its effectiveness as a tool for identifying and selecting influential research papers that warrant additional attention. This work aims to fill a significant deficiency in existing techniques by providing a more comprehensive approach to identifying and ranking influential papers in the field. Practical Implications: The developed framework helps scholars identify the most influential sustainability and supply chain publications. Its validation serves the academic community by offering a credible tool and helping researchers, students, and practitioners find and choose influential papers. This approach aids field literature reviews and study suggestions. Analysis of major trends and topics deepens our grasp of this critical study area's changing terrain. Originality/Value: The framework stands as a unique contribution to academia, offering scholars an important and new tool to identify and validate influential publications. Its distinctive capacity to efficiently guide scholars, learners, and professionals in selecting noteworthy publications, coupled with the examination of key patterns and themes, adds depth to our understanding of the evolving landscape in this critical field of study.

Keywords: supply chain management, sustainability, framework, model

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Authors: Hongxia Wang, Yanjie Wang, Xiuqin Wang, Linlin Mo, Shuangshuang Niu

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Special Education Resource Center (SERC) is the localized product in the development of inclusive education in People’s Republic of China, which provides professional support and service for the students with special education needs(SEN) and their parents, teachers as well as inclusive schools. The study investigated 155 administrators, resource teachers and inclusive education teachers from primary and secondary schools in Beijing. The results indicate that: (1) The surveyed teachers put highest expectation of SERC on specialized guidance and teacher training , instead of research and administration function; (2) Each dimension of professional support needs gets higher scores, in which individual guidance gets highest score, followed by instruction guidance, psychological counseling, proposing suggestions, informational support and teacher training; (3) locality and training experience of surveyed teachers significantly influence their expectations and support needs of SERC.

Keywords: special education resource center (SERC) , functional expectation, professional support needs, support system

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Authors: Sham Kidane, Fitsum Gaim, Ibrahim Abdella, Sirak Asmerom, Yoel Ghebrihiwot, Simon Mulugeta, Natnael Ambassager

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The lack of annotated datasets is a bottleneck to the progress of NLP in low-resourced languages. The work presented here consists of large-scale annotated datasets and models for the named entity recognition (NER) system for the Tigrinya language. Our manually constructed corpus comprises over 340K words tagged for NER, with over 118K of the tokens also having parts-of-speech (POS) tags, annotated with 12 distinct classes of entities, represented using several types of tagging schemes. We conducted extensive experiments covering convolutional neural networks and transformer models; the highest performance achieved is 88.8% weighted F1-score. These results are especially noteworthy given the unique challenges posed by Tigrinya’s distinct grammatical structure and complex word morphologies. The system can be an essential building block for the advancement of NLP systems in Tigrinya and other related low-resourced languages and serve as a bridge for cross-referencing against higher-resourced languages.

Keywords: Tigrinya NER corpus, TiBERT, TiRoBERTa, BiLSTM-CRF

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Authors: Soroush Hooshyar, Mohamadali Masoudian, Natalie Germann

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Many soft materials such as polymer solutions can develop localized bands with different shear rates, which are known as shear bands. Using the generalized bracket approach of nonequilibrium thermodynamics, we recently developed a new two-fluid model to study shear banding for semi-dilute polymer solutions. The two-fluid approach is an appropriate means for describing diffusion processes such as Fickian diffusion and stress-induced migration. In this approach, it is assumed that the local gradients in concentration and, if accounted for, also stress generate a nontrivial velocity difference between the components. Since the differential velocity is treated as a state variable in our model, the implementation of the boundary conditions arising from the derivative diffusive terms is straightforward. Our model is a good candidate for benchmark simulations because of its simplicity. We analyzed its behavior in cylindrical Couette flow, a rectilinear channel flow, and a 4:1 planar contraction flow. The latter problem was solved using the OpenFOAM finite volume package and the impact of shear banding on the lip and salient vortices was investigated. For the other smooth geometries, we employed a standard Chebyshev pseudospectral collocation method. The results showed that the steady-state solution is unique with respect to initial conditions, deformation history, and the value of the diffusivity constant. However, smaller the value of the diffusivity constant is, the more time it takes to reach the steady state.

Keywords: nonequilibrium thermodynamics, planar contraction, polymer solutions, shear banding, two-fluid approach

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Authors: Syed Toqueer Akhter, Muhammad Awais

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Pakistan is a country which is gifted by naturally abundant resources these resources are a pioneer towards a prospect and developed country. Pakistan is the fourth largest exporter of the textile in the world and with the passage of time the competitiveness of these exports is subject to a decline. With a lot of International players in the textile world like China, Bangladesh, India, and Sri Lanka, Pakistan needs to put up a lot of effort to compete with these countries. This research paper would determine the impact of Foreign Direct Investment upon technological diffusion and that how significantly it may be affecting on export performance of the country. It would also demonstrate that with the increase in Foreign Direct Investment, technological diffusion, strong property rights, and using different policy tools, export competitiveness of the country could be improved. The research has been carried out using time series data from 1995 to 2013 and the results have been estimated by using competing Econometrics modes such as Robust regression and Generalized least squares so that to consolidate the impact of the Foreign Investments and Technological diffusion upon export competitiveness comprehensively. Distributed Lag model has also been used to encompass the lagged effect of policy tools variables used by the government. Model estimates entail that 'FDI' and 'Technological Diffusion' do have a significant impact on the competitiveness of the exports of Pakistan. It may also be inferred that competitiveness of Textile Sector requires integrated policy framework, primarily including the reduction in interest rates, providing subsides, and manufacturing of value added products.

Keywords: high technology export, robust regression, patents, technological diffusion, export competitiveness

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Authors: Horia Păunescu

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Purpose: The study aimed to assess the depressant or antidepressant effects of several Nonsteroidal Anti-Inflammatory Drugs (NSAIDs) in mice: the selective cyclooxygenase-2 (COX-2) inhibitor meloxicam, and the non-selective COX-1 and COX-2 inhibitors lornoxicam, sodium metamizole, and ketorolac. The current literature data regarding such effects of these agents are scarce. Materials and methods: The study was carried out on NMRI mice weighing 20-35 g, kept in a standard laboratory environment. The study was approved by the Ethics Committee of the University of Medicine and Pharmacy „Carol Davila”, Bucharest. The study agents were injected intraperitoneally, 10 mL/kg body weight (bw) 1 hour before the assessment of the locomotor activity by cage testing (n=10 mice/ group) and 2 hours before the forced swimming tests (n=15). The study agents were dissolved in normal saline (meloxicam, sodium metamizole), ethanol 11.8% v/v in normal saline (ketorolac), or water (lornoxicam), respectively. Negative and positive control agents were also given (amitryptilline in the forced swimming test). The cage floor used in the locomotor activity assessment was divided into 20 equal 10 cm squares. The forced swimming test involved partial immersion of the mice in cylinders (15/9cm height/diameter) filled with water (10 cm depth at 28C), where they were left for 6 minutes. The cage endpoint used in the locomotor activity assessment was the number of treaded squares. Four endpoints were used in the forced swimming test (immobility latency for the entire 6 minutes, and immobility, swimming, and climbing scores for the final 4 minutes of the swimming session), recorded by an observer that was "blinded" to the experimental design. The statistical analysis used the Levene test for variance homogeneity, ANOVA and post-hoc analysis as appropriate, Tukey or Tamhane tests.Results: No statistically significant increase or decrease in the number of treaded squares was seen in the locomotor activity assessment of any mice group. In the forced swimming test, amitryptilline showed an antidepressant effect in each experiment, at the 10 mg/kg bw dosage. Sodium metamizole was depressant at 100 mg/kg bw (increased the immobility score, p=0.049, Tamhane test), but not in lower dosages as well (25 and 50 mg/kg bw). Ketorolac showed an antidepressant effect at the intermediate dosage of 5 mg/kg bw, but not so in the dosages of 2.5 and 10 mg/kg bw, respectively (increased the swimming score, p=0.012, Tamhane test). Meloxicam and lornoxicam did not alter the forced swimming endpoints at any dosage level. Discussion: 1) Certain NSAIDs caused changes in the forced swimming patterns without interfering with locomotion. 2) Sodium metamizole showed a depressant effect, whereas ketorolac proved antidepressant. Conclusion: NSAID-induced mood changes are not class effects of these agents and apparently are independent of the type of inhibited cyclooxygenase (COX-1 or COX-2). Disclosure: This paper was co-financed from the European Social Fund, through the Sectorial Operational Programme Human Resources Development 2007-2013, project number POSDRU /159 /1.5 /S /138907 "Excellence in scientific interdisciplinary research, doctoral and postdoctoral, in the economic, social and medical fields -EXCELIS", coordinator The Bucharest University of Economic Studies.

Keywords: antidepressant, depressant, forced swim, NSAIDs

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Authors: Anisa Suraya Ab Razak, Izza Hayat

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Introduction: The diagnosis and management of severe hyponatremia in neuropsychiatric patients present a significant challenge to physicians. Several factors contribute, including diagnostic shadowing and attributing abnormal behavior to intellectual disability or psychiatric conditions. Hyponatraemia is the commonest electrolyte abnormality in the inpatient population, ranging from mild/asymptomatic, moderate to severe levels with life-threatening symptoms such as seizures, coma and death. There are several documented fatal case reports in the literature of severe hyponatremia secondary to psychogenic polydipsia, often diagnosed only in autopsy. This paper presents a case study of acute severe hyponatremia in a neuropsychiatric patient with early diagnosis and admission to intensive care. Case study: A 21-year old Caucasian male with known epilepsy and learning disability was admitted from residential living with generalized tonic-clonic self-terminating seizures after refusing medications for several weeks. Evidence of superficial head injury was detected on physical examination. His laboratory data demonstrated mild hyponatremia (125 mmol/L). Computed tomography imaging of his brain demonstrated no acute bleed or space-occupying lesion. He exhibited abnormal behavior - restlessness, drinking water from bathroom taps, inability to engage, paranoia, and hypersexuality. No collateral history was available to establish his baseline behavior. He was loaded with intravenous sodium valproate and leveritircaetam. Three hours later, he developed vomiting and a generalized tonic-clonic seizure lasting forty seconds. He remained drowsy for several hours and regained minimal recovery of consciousness. A repeat set of blood tests demonstrated profound hyponatremia (117 mmol/L). Outcomes: He was referred to intensive care for peripheral intravenous infusion of 2.7% sodium chloride solution with two-hourly laboratory monitoring of sodium concentration. Laboratory monitoring identified dangerously rapid correction of serum sodium concentration, and hypertonic saline was switched to a 5% dextrose solution to reduce the risk of acute large-volume fluid shifts from the cerebral intracellular compartment to the extracellular compartment. He underwent urethral catheterization and produced 8 liters of urine over 24 hours. Serum sodium concentration remained stable after 24 hours of correction fluids. His GCS recovered to baseline after 48 hours with improvement in behavior -he engaged with healthcare professionals, understood the importance of taking medications, admitted to illicit drug use and drinking massive amounts of water. He was transferred from high-dependency care to ward level and was initiated on multiple trials of anti-epileptics before achieving seizure-free days two weeks after resolution of acute hyponatremia. Conclusion: Psychogenic polydipsia is often found in young patients with intellectual disability or psychiatric disorders. Patients drink large volumes of water daily ranging from ten to forty liters, resulting in acute severe hyponatremia with mortality rates as high as 20%. Poor outcomes are due to challenges faced by physicians in making an early diagnosis and treating acute hyponatremia safely. A low index of suspicion of water intoxication is required in this population, including patients with known epilepsy. Monitoring urine output proved to be clinically effective in aiding diagnosis. Early referral and admission to intensive care should be considered for safe correction of sodium concentration while minimizing risk of fatal complications e.g. central pontine myelinolysis.

Keywords: epilepsy, psychogenic polydipsia, seizure, severe hyponatremia

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Authors: Abdelmounaim Lahrech, Hajar Bousfiha

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This paper examines equity market integration between Morocco and France and its consequent implications on international portfolio diversification. In the absence of stock market linkages, Morocco can act as a diversification destination to European investors, allowing higher returns at a comparable level of risk in developed markets. In contrast, this attractiveness is limited if both financial markets show significant linkage. The research empirically measures financial market’s integration in by capturing the conditional correlation between the two markets using the Generalized Autoregressive Conditionally Heteroscedastic (GARCH) model. Then, the research uses the Dynamic Conditional Correlation (DCC) model of Engle (2002) to track the correlations. The research findings show that there is no important increase over the years in the correlation between the Moroccan and the French equity markets, even though France is considered Morocco’s first trading partner. Failing to prove evidence of the stock index linkage between the two countries, the volatility series of each market were assumed to change over time separately. Yet, the study reveals that despite the important historical and economic linkages between Morocco and France, there is no evidence that equity markets follow. The small correlations and their stationarity over time show that over the 10 years studied, correlations were fluctuating around a stable mean with no significant change at their level. Different explanations can be attributed to the absence of market linkage between the two equity markets.

Keywords: equity market linkage, DCC GARCH, international portfolio diversification, Morocco, France

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Authors: Phumelele Kubheka, Pius Owolawi, Gbolahan Aiyetoro

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Twitter is one of the most popular social media platforms where users can share their opinions on different subjects. As of 2010, The Twitter platform generates more than 12 Terabytes of data daily, ~ 4.3 petabytes in a single year. For this reason, Twitter is a great source for big mining data. Many industries such as Telecommunication companies can leverage the availability of Twitter data to better understand their markets and make an appropriate business decision. This study performs topic modeling on Twitter data using Latent Dirichlet Allocation (LDA). The obtained results are benchmarked with another topic modeling technique, Latent Semantic Indexing (LSI). The study aims to retrieve topics on a Twitter dataset containing user tweets on South African Telcos. Results from this study show that LSI is much faster than LDA. However, LDA yields better results with higher topic coherence by 8% for the best-performing model represented in Table 1. A higher topic coherence score indicates better performance of the model.

Keywords: big data, latent Dirichlet allocation, latent semantic indexing, telco, topic modeling, twitter

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Authors: Souhir Chelly, Chahida Harizi, Aicha Hechaichi, Sihem Aissaoui, Leila Ben Ayed, Maha Bergaoui, Mohamed Kouni Chahed

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Introduction: The International Classification of Primary Care (ICPC) is part of the morbidity classification system. It had 17 chapters, and each is coded by an alphanumeric code: the letter corresponds to the chapter, the number to a paragraph in the chapter. The objective of this study is to show the utility of this classification in the coding of the reasons for demand for care in Primary health care (PHC), its advantages and limits. Methods: This is a cross-sectional descriptive study conducted in 4 PHC in Ariana district. Data on the demand for care during 2 days in the same week were collected. The coding of the information was done according to the CISP. The data was entered and analyzed by the EPI Info 7 software. Results: A total of 523 demands for care were investigated. The patients who came for the consultation are predominantly female (62.72%). Most of the consultants are young with an average age of 35 ± 26 years. In the ICPC, there are 7 rubrics: 'infections' is the most common reason with 49.9%, 'other diagnoses' with 40.2%, 'symptoms and complaints' with 5.5%, 'trauma' with 2.1%, 'procedures' with 2.1% and 'neoplasm' with 0.3%. The main advantage of the ICPC is the fact of being a standardized tool. It is very suitable for classification of the reasons for demand for care in PHC according to their specificity, capacity to be used in a computerized medical file of the PHC. Its current limitations are related to the difficulty of classification of some reasons for demand for care. Conclusion: The ICPC has been developed to provide healthcare with a coding reference that takes into account their specificity. The CIM is in its 10th revision; it would gain from revision to revision to be more efficient to be generalized and used by the teams of PHC.

Keywords: international classification of primary care, medical file, primary health care, Tunisia

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Authors: Mohd Zamri Osman, Mohd Aizaini Maarof, Mohd Foad Rohani

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Human skin detection recognized as the primary step in most of the applications such as face detection, illicit image filtering, hand recognition and video surveillance. The performance of any skin detection applications greatly relies on the two components: feature extraction and classification method. Skin color is the most vital information used for skin detection purpose. However, color feature alone sometimes could not handle images with having same color distribution with skin color. A color feature of pixel-based does not eliminate the skin-like color due to the intensity of skin and skin-like color fall under the same distribution. Hence, the statistical color analysis will be exploited such mean and standard deviation as an additional feature to increase the reliability of skin detector. In this paper, we studied the effectiveness of statistical color feature for human skin detection. Furthermore, the paper analyzed the integrated color and texture using eight classifiers with three color spaces of RGB, YCbCr, and HSV. The experimental results show that the integrating statistical feature using Random Forest classifier achieved a significant performance with an F1-score 0.969.

Keywords: color space, neural network, random forest, skin detection, statistical feature

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Authors: Sezin Ekşioğlu

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Multilabel classification has a huge importance for several applications, it is also a challenging research topic. It is a kind of supervised learning that contains binary targets. The distance between multilabel and binary classification is having more than one class in multilabel classification problems. Features can belong to one class or many classes. There exists a wide range of applications for multi label prediction such as image labeling, text categorization, gene functionality. Even though features are classified in many classes, they may not always be properly classified. There are many ensemble methods for the classification. However, most of the researchers have been concerned about better multilabel methods. Especially little ones focus on both efficiency of classifiers and pairwise relationships at the same time in order to implement better multilabel classification. In this paper, we worked on modified ensemble methods by getting benefit from k-Nearest Neighbors and neural network structure to address issues within a beneficial way and to get better impacts from the multilabel classification. Publicly available datasets (yeast, emotion, scene and birds) are performed to demonstrate the developed algorithm efficiency and the technique is measured by accuracy, F1 score and hamming loss metrics. Our algorithm boosts benchmarks for each datasets with different metrics.

Keywords: multilabel, classification, neural network, KNN

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Authors: Haohao Wang

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Technology, multimedia in Open Educational Resources, can contribute positively to student performance in an online instructional environment. Student performance data of past four years were obtained from an online course entitled Applied Calculus (MA139). This paper examined the data to determine whether multimedia (independent variable) had any impact on student performance (dependent variable) in online math learning, and how students felt about the value of the technology. Two groups of student data were analyzed, group 1 (control) from the online applied calculus course that did not use multimedia instructional materials, and group 2 (treatment) of the same online applied calculus course that used multimedia instructional materials. For the MA139 class, results indicate a statistically significant difference (p = .001) between the two groups, where group 1 had a final score mean of 56.36 (out of 100), group 2 of 70.68. Additionally, student testimonials were discussed in which students shared their experience in learning applied calculus online with multimedia instructional materials.

Keywords: online learning, open educational resources, multimedia, technology

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Authors: Alok Bapatla, Pamela Lutting, Mariastella Serrano

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Background: Irritable Bowel Syndrome (IBS) is a functional gastrointestinal disorder characterized by abdominal pain associated with altered bowel habits in the absence of an underlying organic cause. Although the exact etiology of IBS is not fully understood, one of the leading theories postulates a pathology within the Brain-Gut Axis that leads to an overall increase in gastrointestinal sensitivity and pejorative changes in gastrointestinal motility. Research and clinical practice have shown that Gut Directed Hypnotherapy (GDH) has a beneficial clinical role in improving Mind-Gut control and thereby comorbid conditions such as anxiety, abdominal pain, constipation, and diarrhea. Aims: This study presents a 17-year old male with underlying anxiety and a one-year history of IBS-Constipation Predominant Subtype (IBS-C), who has demonstrated impressive improvement of symptoms following GDH treatment following refractory trials with medications including bisacodyl, senna, docusate, magnesium citrate, lubiprostone, linaclotide. Method: The patient was referred to a licensed clinical psychologist specializing in clinical hypnosis and cognitive-behavioral therapy (CBT), who implemented “The Standardized Hypnosis Protocol for IBS” developed by Dr. Olafur S. Palsson, Psy.D at the University of North Carolina at Chapel Hill. The hypnotherapy protocol consisted of a total of seven weekly 45-minute sessions supplemented with a 20-minute audio recording to be listened to once daily. Outcome variables included the GAD-7, PHQ-9 and DCI-2, as well as self-ratings (ranging 0-10) for pain (intensity and frequency), emotional distress about IBS symptoms, and overall emotional distress. All variables were measured at intake prior to administration of the hypnosis protocol and at the conclusion of the hypnosis treatment. A retrospective IBS Questionnaire (IBS Severity Scoring System) was also completed at the conclusion of the GDH treatment for pre-and post-test ratings of clinical symptoms. Results: The patient showed improvement in all outcome variables and self-ratings, including abdominal pain intensity, frequency of abdominal pain episodes, emotional distress relating to gut issues, depression, and anxiety. The IBS Questionnaire showed a significant improvement from a severity score of 400 (defined as severe) prior to GDH intervention compared to 55 (defined as complete resolution) at four months after the last session. IBS Questionnaire subset questions that showed a significant score improvement included abdominal pain intensity, days of pain experienced per 10 days, satisfaction with bowel habits, and overall interference of life affected by IBS symptoms. Conclusion: This case supports the existing research literature that GDH has a significantly beneficial role in improving symptoms in patients with IBS. Emphasis is placed on the numerical results of the IBS Questionnaire scoring, which reflects a patient who initially suffered from severe IBS with failed response to multiple medications, who subsequently showed full and sustained resolution

Keywords: pediatrics, constipation, irritable bowel syndrome, hypnotherapy, gut-directed hypnosis

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