Search results for: score analysis Z

Authors: R. Abdeldjebar, B. Labbaci, L. Missoum, B. Moudden, M. Djermane

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The basic components of a composite material made him very sensitive to damage, which requires techniques for detecting damage reliable and efficient. This work focuses on the detection of damage by vibration analysis, whose main objective is to exploit the dynamic response of a structure to detect understand the damage. The experimental results are compared with those predicted by numerical models to confirm the effectiveness of the approach.

Keywords: experimental, composite, vibration analysis, damage

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Authors: O. Abdelkhalek, A. Naimi, M. Rami, M. N. Tandjaoui, A. Kechich

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This paper deals with the active and reactive power flow analysis inside the unified power quality conditioner (UPQC) during several cases. The UPQC is a combination of shunt and series active power filter (APF). It is one of the best solutions towards the mitigation of voltage sags and swells problems on distribution network. This analysis can provide the helpful information to well understanding the interaction between the series filter, the shunt filter, the DC bus link and electrical network. The mathematical analysis is based on active and reactive power flow through the shunt and series active power filter. Wherein series APF can absorb or deliver the active power to mitigate a swell or sage voltage where in the both cases it absorbs a small reactive power quantity whereas the shunt active power absorbs or releases the active power for stabilizing the storage capacitor’s voltage as well as the power factor correction. The voltage sag and voltage swell are usually interpreted through the DC bus voltage curves. These two phenomena are introduced in this paper with a new interpretation based on the active and reactive power flow analysis inside the UPQC. For simplifying this study, a linear load is supposed in this digital simulation. The simulation results are carried out to confirm the analysis done.

Keywords: UPQC, Power flow analysis, shunt filter, series filter.

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Authors: Chaitanya Kanakamedala, Hansa Pradhan, Carter Gilbert

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Social media platforms, such as Twitter, are excellent datasets for understanding human interactions and sentiments. This report explores social dynamics among US Congressional members through a network analysis applied to a dataset of tweets spanning 2008 to 2017 from the ’US Congressional Tweets Dataset’. In this report, we preform network analysis where connections between users (edges) are established based on a similarity threshold: two tweets are connected if the tweets they post are similar. By utilizing the Natural Language Toolkit (NLTK) and NetworkX, we quantified tweet similarity and constructed a graph comprising various interconnected components. Each component represents a cluster of users with closely aligned content. We then preform sentiment analysis on each cluster to explore the prevalent emotions and opinions within these groups. Our findings reveal that despite the initial expectation of distinct ideological divisions typically aligning with party lines, the analysis exposed a high degree of topical convergence across tweets from different political affiliations. The analysis preformed in this report not only highlights the potential of social media as a tool for political communication but also suggests a complex layer of interaction that transcends traditional partisan boundaries, reflecting a complicated landscape of politics in the digital age.

Keywords: natural language processing, sentiment analysis, centrality analysis, topic modeling

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Authors: P. Renjitha, P. Hari Prakash

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Auditory neuropathy spectrum disorder (ANSD) is an auditory disorder with normal cochlear outer hair cell function and disrupted auditory nerve function. It results in unique clinical characteristic with absent auditory brainstem response (ABR), absent acoustic reflex and the presence of otoacoustic emissions (OAE) and cochlear microphonics. The lesion site could be at cochlear inner hair cells, the synapse between the inner hair cells and type I auditory nerve fibers, and/or the auditory nerve itself. But the literatures on synchrony at higher auditory system are sporadic and are less understood. It might be interesting to see if there is a recovery of neural synchrony at higher auditory centers. Also, does the level at which the auditory system recovers with adequate synchrony to the extent of observable evoke response potentials (ERPs) can predict speech perception? In the current study, eight ANSD participants and healthy controls underwent detailed audiological assessment including ABR, auditory middle latency response (AMLR), and auditory late latency response (ALLR). AMLR was recorded for clicks and ALLR was evoked using 500Hz and 2 kHz tone bursts. Analysis revealed that the participant could be categorized into three groups. Group I (2/8) where ALLR was present only for 2kHz tone burst. Group II (4/8), where AMLR was absent and ALLR was seen for both the stimuli. Group III (2/8) consisted individuals with identifiable AMLR and ALLR for all the stimuli. The highest speech identification sore observed in ANSD group was 30% and hence considered having poor speech perception. Overall test result indicates that the site of neural synchrony recovery could be varying across individuals with ANSD. Some individuals show recovery of neural synchrony at the thalamocortical level while others show the same only at the cortical level. Within ALLR itself there could be variation across stimuli again could be related to neural synchrony. Nevertheless, none of these patterns could possible explain the speech perception ability of the individuals. Hence, it could be concluded that neural synchrony as measured by evoked potentials could not be a good clinical predictor speech perception.

Keywords: auditory late latency response, auditory middle latency response, auditory neuropathy spectrum disorder, correlation with speech identification score

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Authors: Rahul Arora, S. S. Dhami

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This paper implements the design structure of industrial robot along with the different transmission components like gear assembly and analysis of complete industrial robot. In this paper, it gives the overview on the most efficient types of modeling and different analysis results that can be obtained for an industrial robot. The investigation is executed in regards to two classifications i.e. the deformation and the stress tests. SolidWorks is utilized to design and review the 3D drawing plan while ANSYS Workbench is utilized to execute the FEA on an industrial robot and the designed component. The CAD evaluation was conducted on a disentangled model of an industrial robot. The study includes design and drafting its transmission system. In CAE study static, modal and dynamic analysis are presented. Every one of the outcomes is divided in regard with the impact of the static and dynamic analysis on the situating exactness of the robot. It gives critical data with respect to parts of the industrial robot that are inclined to harm under higher high force applications. Therefore, the mechanical structure under different operating conditions can help in optimizing the manipulator geometry and in selecting the right material for the same. The FEA analysis is conducted for four different materials on the same industrial robot and gear assembly.

Keywords: CAD, CAE, FEA, robot, static, dynamic, modal, gear assembly

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Authors: Vishal Bhatnagar

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The objective of this study is to compare the efficacy of epidural analgesia of two amide local anesthetics, ropivacaine and levobupivacaine, with fentanyl for postoperative analgesia in major abdominal surgery CRS+HIPEC. Cytoreductive surgery and hyperthermic intraperitoneal chemotherapy (CRS+HIPEC) are done for primary peritoneal malignancies or peritoneal spread of malignant neoplasm. CRS and HIPEC are considered one of the most painful surgery among all major abdominal surgeries. Poorly managed postoperative pain elevates stress, increases anxiety, causes prolonged Hospital stay, increases opioid requirement and side effects, increases the cost of treatment and psychological effects on patient and family. It affects the quality of life of patients. The epidural technique provides better postoperative analgesia, earlier recovery of bowel function, fewer side effects, higher patient satisfaction, and an improvement in life quality in the postoperative days after abdominal surgery than other analgesic techniques.

Keywords: HIPEC, postoperative analgesia, cytoreductive surgery, VAS score, rescue analgesia

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Authors: Namrata Mishra

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Health of a person plays a vital role in the collective health of his community and hence the well-being of the society as a whole. But, in today’s fast paced technology driven world, health issues are increasingly being associated with human behaviors – their lifestyle. Social networks have tremendous impact on the health behavior of individuals. Many researchers have used social network analysis to understand human behavior that implicates their social and economic environments. It would be interesting to use a similar analysis to understand human behaviors that have health implications. This paper focuses on concepts of those behavioural analyses that have health implications using social networks analysis and provides possible algorithmic approaches. The results of these approaches can be used by the governing authorities for rolling out health plans, benefits and take preventive measures, while the pharmaceutical companies can target specific markets, helping health insurance companies to better model their insurance plans.

Keywords: breadth first search, directed graph, health behaviors, social network analysis

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Authors: Lidija R. Jevrić, Sanja O. Podunavac-Kuzmanović, Strahinja Z. Kovačević

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This study considers the selection of the most suitable in silico molecular descriptors that could be used for s-triazine pesticides characterization. Suitable descriptors among topological, geometrical and physicochemical are used for quantitative structure-retention relationships (QSRR) model establishment. Established models were obtained using linear regression (LR) and multiple linear regression (MLR) analysis. In this paper, MLR models were established avoiding multicollinearity among the selected molecular descriptors. Statistical quality of established models was evaluated by standard and cross-validation statistical parameters. For detection of similarity or dissimilarity among investigated s-triazine pesticides and their classification, principal component analysis (PCA) and hierarchical cluster analysis (HCA) were used and gave similar grouping. This study is financially supported by COST action TD1305.

Keywords: chemometrics, classification analysis, molecular descriptors, pesticides, regression analysis

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Authors: Princes Ann E. Prieto, Denise F. Alpuerto, John Rafael C. Unlayao, Neil Concibido, Monet Concepcion Maguyon-Detras

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Failure Mode and Effects Analysis (FMEA) has been used in the virtual Process Hazard Analysis (PHA) of the Acetone production process through the dehydrogenation of isopropyl alcohol, for which very limited process risk assessment has been published. In this study, the potential failure modes, effects, and possible causes of selected major equipment in the process were identified. During the virtual FMEA mock sessions, the risks in the process were evaluated and recommendations to reduce and/or mitigate the process risks were formulated. The risk was estimated using the calculated risk priority number (RPN) and was classified into four (4) levels according to their effects on acetone production. Results of this study were also used to rank the criticality of equipment in the process based on the calculated criticality rating (CR). Bow tie diagrams were also created for the critical hazard scenarios identified in the study.

Keywords: chemical process safety, failure mode and effects analysis (FMEA), process hazard analysis (PHA), process safety management (PSM)

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Authors: L. Rakesh, T. Y. Heblekar

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This study entails the development and optimization of a mathematical model for a floating drum biogas reactor from first principles using thermal and empirical considerations. The model was derived on the basis of mass conservation, lumped mass heat transfer formulations and empirical biogas formation laws. The treatment leads to a system of coupled nonlinear ordinary differential equations whose solution mapped four-time independent controllable parameters to five output variables which adequately serve to describe the reactor performance. These equations were solved numerically using fourth order Runge-Kutta method for a range of input parameter values. Using the data so obtained an Artificial Neural Network with a single hidden layer was trained using Levenberg-Marquardt Damped Least Squares (DLS) algorithm. This network was then fine-tuned for optimal mapping by varying hidden layer size. This fast forward model was then employed as a health score generator in the Bacterial Foraging Optimization code. The optimal operating state of the simplified Biogas reactor was thus obtained.

Keywords: biogas, floating drum reactor, neural network model, optimization

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Authors: H. S. Niroshani, W. M. Ediri Arachchi, R. Tudugala, U. J. M. A. L. Jayasinghe, U. M. U. J. Jayasekara, P. B. Hewavithana

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Mammography is used as a screening tool for early diagnosis of breast cancer. It is also useful in refining the diagnosis of breast cancer either by assessment or work up after a suspicious area in the breast has been detected. In order to detect breast cancer accurately and at the earliest possible stage, the image must have an optimum contrast to reveal mass densities and spiculated fibrous structures radiating from them. In addition, the spatial resolution must be adequate to reveal the suffusion of micro calcifications and their shape. The above factors can be optimized by implementing an effective QA programme to enhance the accurate diagnosis of mammographic imaging. Therefore, the radiographer’s knowledge on QA is greatly instrumental in routine mammographic practice. The aim of this study was to assess the radiographer’s knowledge on Quality Assurance and Quality Control programmes in relation to mammographic procedures. A cross-sectional study was carried out among all radiographers working in each mammography setting in Sri Lanka. Pre-tested, anonymous self-administered questionnaires were circulated among the study population and duly filled questionnaires returned within a period of three months were taken into the account. The data on demographical information, knowledge on QA programme and associated QC tests, overall knowledge on QA and QC programmes were obtained. Data analysis was performed using IBM SPSS statistical software (version 20.0). The total response rate was 59.6% and the average knowledge score was 54.15±11.29 SD out of 100. Knowledge was compared on the basis of education level, special training of mammography, and the years of working experience in a mammographic setting of the individuals. Out of 31 subjects, 64.5% (n=20) were graduate radiographers and 35.5% (n=11) were diploma holders while 83.9% (n=26) of radiographers have been specially trained for mammography and 16.1% (n=5) have not been attended for any special training for mammography. It is also noted that 58.1% (n=18) of individuals possessed their experience of less than one year and rest 41.9% (n=13) of them were greater than that. Further, the results found that there is a significant difference (P < 0.05) in the knowledge of QA and overall knowledge on QA and QC programme in the categories of education level and working experience. Also, results imply that there was a significant difference (P < 0.05) in the knowledge of QC test among the groups of trained and non-trained radiographers. This study reveals that education level, working experience and the training obtained particularly in the field of mammography have a significant impact on their knowledge on QA and QC in mammography.

Keywords: knowledge, mammography, quality assurance, quality control

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Authors: Lene Granzau Juel-Jacobsen

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The problem of beautification is an obvious concern of photography, claiming reference to reality, but it also lies at the very heart of social theory. As we become accustomed to sophisticated visualizations of statistical data in pace with the development of software programs, we should not only be inclined to ask new types of research questions, but we also need to confront social theories based on such visualization techniques with new types of questions. Correspondence Analysis, GIS analysis, Social Network Analysis, and Perceptual Maps are current examples of visualization techniques popular within the social sciences and neighboring disciplines. This article discusses correspondence analysis, arguing that the graphic plot of correspondence analysis is to be interpreted much similarly to a photograph. It refers no more evidently or univocally to reality than a photograph, representing social life no more truthfully than a photograph documents. Pierre Bourdieu’s theoretical corpus, especially his theory of fields, relies heavily on correspondence analysis. While much attention has been directed towards critiquing the somewhat vague conceptualization of habitus, limited focus has been placed on the equally problematic concepts of social space and field. Based on a re-reading of the Distinction, the article argues that the concepts rely on ‘a small graphic lie’ very similar to a photograph. Like any other piece of art, as Bourdieu himself recognized, the graphic display is a politically and morally loaded representation technique. However, the correspondence analysis does not necessarily serve the purpose he intended. In fact, it tends towards the pitfalls he strove to overcome.

Keywords: datavisualization, correspondance analysis, bourdieu, Field, visual representation

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Authors: C. V. Pietreanu, S. E. Zaharia, C. Dinu

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The present research is built on three major pillars, commencing by making some considerations on accident investigation methods and pointing out both defining aspects and differences between linear and non-linear analysis. The traditional linear focus on accident analysis describes accidents as a sequence of events, while the latest systemic models outline interdependencies between different factors and define the processes evolution related to a specific (normal) situation. Linear and non-linear accident analysis methods have specific limitations, so the second point of interest is mirrored by the aim to discover the drawbacks of systemic models which becomes a starting point for developing new directions to identify risks or data closer to the cause of incidents/accidents. Since communication represents a critical issue in the interaction of human factor and has been proved to be the answer of the problems made by possible breakdowns in different communication procedures, from this focus point, on the third pylon a new error-modeling instrument suitable for risk assessment/accident analysis will be elaborated.

Keywords: accident analysis, multi-factorial error modeling, risk, systemic methods

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Authors: Wilawan Kanhachon, Yodchai Boonprakob, Uraiwon Chatchawan, Junichiro Yamauchi

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Introduction: Paslop is a traditional dance from Laos, which is popular in Laos and northeastern of Thailand. This unique type of Paslop dancing is to control body movement with the song. While dancing to the beat, dancers should contract their abdomen and back muscle all the time. Paslop may be a good alternative to improve strengthening, balance and flexibility. Objective: To investigate the effects of Paslop dance exercise on core strength, balance, and flexibility. Methods: Seven healthy participants (age, 20.57±1.13 yrs; height, 162.29±6.16 cm; body mass, 58.14±7.03 kg; mean± S.D.) were volunteered to perform the 45-minute Paslop dance exercise in three times a week for 8 weeks. Before, during and after the exercise period, core strength, balance and flexibility were measured with the pressure biofeedback unit (PBU), one-leg stance test (OLST), and sit and reach test (SAR), respectively. Result: PBU score for core strength increased from 2.12 mmHg in baseline to 6.34 mmHg at the 4th week and 10.10 mmHg at the 8th week after the Paslop dance training, while OLST and SAR did not change. Conclusion: The study demonstrates that 8-week Paslop dancing exercise can improve the core strength.

Keywords: balance, core strength, flexibility, Paslop

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

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

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

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Authors: Moammar Dayoub

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The study aimed to know the reality of farmers and determine the extent of adoption of the recommendations of the fertilizer and the difficulties and problems they face. The study was conducted on a random sample of farmers consist of 95 farmers who had analysed their field soil in scientific research centres in agricultural southern region through the form specially prepared for this purpose, the results showed that the rate of adoption of the fertilizer recommendations whole amounted to an average of 36.9% in the southern region, The degree of adoption was 34.7% in the region. The results showed that 41% of farmers did not implement the recommendations because of the non-convenient analysis, and 34% due to neglect, and 15% due to the weather and an environment, while 10% of them for lack of manure in the suitable time. The study also revealed that Independent factors affecting the continuing adoption of soil analysis are: farms experience, sampling method in farmer’s schools, irrigated area, and personal knowledge of farmers in analysing the soil. Also, show that the application of fertilizer recommendations led to increased production by 15-20%, this analysis emphasizes the importance of soil analysis and adherence to the recommendations of the research centres.

Keywords: adoption, recommendations of the fertilizer, soil analysis, southern region

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Authors: Ashi Gautam, Isha Shukla, Akhil Seghal

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Biosensors are analytical devices that use a biological sensing element to detect and measure a specific chemical substance or biomolecule in a sample. These devices are widely used in various fields, including medical diagnostics, environmental monitoring, and food analysis, due to their high specificity, sensitivity, and selectivity. In this research paper, a machine learning model is proposed for predicting the suitability of skin care products based on biosensor readings. The proposed model takes in features extracted from biosensor readings, such as biomarker concentration, skin hydration level, inflammation presence, sensitivity, and free radicals, and outputs the most appropriate skin care product for an individual. This model is trained on a dataset of biosensor readings and corresponding skin care product information. The model's performance is evaluated using several metrics, including accuracy, precision, recall, and F1 score. The aim of this research is to develop a personalised skin care product recommendation system using biosensor data. By leveraging the power of machine learning, the proposed model can accurately predict the most suitable skin care product for an individual based on their biosensor readings. This is particularly useful in the skin care industry, where personalised recommendations can lead to better outcomes for consumers. The developed model is based on supervised learning, which means that it is trained on a labeled dataset of biosensor readings and corresponding skin care product information. The model uses these labeled data to learn patterns and relationships between the biosensor readings and skin care products. Once trained, the model can predict the most suitable skin care product for an individual based on their biosensor readings. The results of this study show that the proposed machine learning model can accurately predict the most appropriate skin care product for an individual based on their biosensor readings. The evaluation metrics used in this study demonstrate the effectiveness of the model in predicting skin care products. This model has significant potential for practical use in the skin care industry for personalised skin care product recommendations. The proposed machine learning model for predicting the suitability of skin care products based on biosensor readings is a promising development in the skin care industry. The model's ability to accurately predict the most appropriate skin care product for an individual based on their biosensor readings can lead to better outcomes for consumers. Further research can be done to improve the model's accuracy and effectiveness.

Keywords: biosensors, data model, machine learning, skin care

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Authors: Seung Cho Yang, Jae Sung Lee, Se Hee Park

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This study suggests the analysis method to predict the damages of tunnel concrete caused by fires. The result obtained from the analyses of concrete temperatures at a fire in a tunnel using ABAQUS was compared with the test result. After the reliability of the analysis method was verified, the temperatures of a tunnel at a real fire and those of concrete during the fire were estimated to predict fire damages. The temperatures inside the tunnel were estimated by FDS, a CFD model. It was deduced that the fire performance of tunnel lining and the fire damages of the structure at an actual fire could be estimated by the analysis method.

Keywords: fire resistance, heat transfer, numerical analysis, tunnel fire

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Authors: Sonia Butalia, Huong Luu, Alexis Guigue, Karen J. B. Martins, Khanh Vu, Scott W. Klarenbach

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Obesity is associated with significant personal impacts on health and has a substantial economic burden on payers due to increased healthcare use. A contemporary estimate of the healthcare costs associated with obesity at the population level are lacking. This evidence may provide further rationale for weight management strategies. Methods: Adults who underwent a medical procedure between 2012 and 2019 in Alberta, Canada were categorized into the investigational cohort (had body mass index [BMI]-defined class 2 or 3 obesity based on a procedure-associated code) and the control cohort (did not have the BMI procedure-associated code); those who had bariatric surgery were excluded. Characteristics were presented and healthcare costs ($CDN) determined over a 1-year observation period (2019/2020). Logistic regression and a generalized linear model with log link and gamma distribution were used to assess total healthcare costs (comprised of hospitalizations, emergency department visits, ambulatory care visits, physician visits, and outpatient prescription drugs); potential confounders included age, sex, region of residence, and whether the medical procedure was performed within 6-months before the observation period in the partial adjustment, and also the type of procedure performed, socioeconomic status, Charlson Comorbidity Index (CCI), and seven obesity-related health conditions in the full adjustment. Cost ratios and estimated cost differences with 95% confidence intervals (CI) were reported; incremental cost differences within the adjusted models represent referent cases. Results: The investigational cohort (n=220,190) was older (mean age: 53 standard deviation [SD]±17 vs 50 SD±17 years), had more females (71% vs 57%), lived in rural areas to a greater extent (20% vs 14%), experienced a higher overall burden of disease (CCI: 0.6 SD±1.3 vs 0.3 SD±0.9), and were less socioeconomically well-off (material/social deprivation was lower [14%/14%] in the most well-off quintile vs 20%/19%) compared with controls (n=1,955,548). Unadjusted total healthcare costs were estimated to be 1.77-times (95% CI: 1.76, 1.78) higher in the investigational versus control cohort; each healthcare resource contributed to the higher cost ratio. After adjusting for potential confounders, the total healthcare cost ratio decreased, but remained higher in the investigational versus control cohort (partial adjustment: 1.57 [95% CI: 1.57, 1.58]; full adjustment: 1.21 [95% CI: 1.20, 1.21]); each healthcare resource contributed to the higher cost ratio. Among urban-dwelling 50-year old females who previously had non-operative procedures, no procedures performed within 6-months before the observation period, a social deprivation index score of 3, a CCI score of 0.32, and no history of select obesity-related health conditions, the predicted cost difference between those living with and without obesity was $386 (95% CI: $376, $397). Conclusions: If these findings hold for the Canadian population, one would expect an estimated additional $3.0 billion per year in healthcare costs nationally related to BMI-defined obesity (based on an adult obesity rate of 26% and an estimated annual incremental cost of $386 [21%]); incremental costs are higher when obesity-related health conditions are not adjusted for. Results of this study provide additional rationale for investment in interventions that are effective in preventing and treating obesity and its complications.

Keywords: administrative data, body mass index-defined obesity, healthcare cost, real world evidence

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Authors: Karolína Vozková, Matěj Kuc

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This paper analyzes recent trends in cost efficiency of European cooperative banks using efficient frontier analysis. Our methodology is based on stochastic frontier analysis which is run on a set of 649 European cooperative banks using data between 2006 and 2015. Our results show that average inefficiency of European cooperative banks is increasing since 2008, smaller cooperative banks are significantly more efficient than the bigger ones over the whole time period and that share of net fee and commission income to total income surprisingly seems to have no impact on bank cost efficiency.

Keywords: cooperative banks, cost efficiency, efficient frontier analysis, stochastic frontier analysis, net fee and commission income

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Authors: May Abdelghani

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The present work is devoted to the study of the microstructural anisotropy in mechanical cyclic behavior of the 2017AA aluminum alloy which is widely used in the aerospace industry. The main purpose of the study is to investigate the microstructural origins of this anisotropy already confirmed in our previous work in 2017AA aluminum alloy. To do this, we have used the microstructural analysis resources such as Scanning Electron Microscope (SEM) to see the differences between breaks from different directions of cyclic loading. Another resource of investigation was used in this study is that the EBSD method, which allows us to obtain a mapping of the crystallographic texture of our material. According to the obtained results in the microscopic analysis, we are able to identify the origins of the anisotropic behavior at the macroscopic scale.

Keywords: fatigue damage, cyclic behavior, anisotropy, microstructural analysis

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Authors: M. Sarai Atab, A. Smallbone, A. P. Roskilly

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A thermodynamic study is performed on the Reverse Osmosis (RO) desalination process for brackish water. The detailed RO model of thermodynamics properties with and without an energy recovery device was built in Simulink/MATLAB and validated against reported measurement data. The efficiency of desalination plants can be estimated by both the first and second laws of thermodynamics. While the first law focuses on the quantity of energy, the second law analysis (i.e. exergy analysis) introduces quality. This paper used the Main Outfall Drain in Iraq as a case study to conduct energy and exergy analysis of RO process. The result shows that it is feasible to use energy recovery method for reverse osmosis with salinity less than 15000 ppm as the exergy efficiency increases twice. Moreover, this analysis shows that the highest exergy destruction occurs in the rejected water and lowest occurs in the permeate flow rate accounting 37% for 4.3% respectively.

Keywords: brackish water, exergy, irrigation, reverse osmosis (RO)

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Authors: Liwen Hou

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The booming mobile business has been penetrating the taxi industry worldwide with P2P (peer to peer) taxi services, as an emerging business model, transforming the industry. Parallel with other mobile businesses, member recommendations and online reviews are believed to be very effective with regard to acquiring new users for P2P taxi services. Based on an empirical dataset of the taxi industry in China, this study aims to reveal which factors influence users’ recommendations and review-writing behaviors. Differing from the existing literature, this paper takes the taxi driver’s perspective into consideration and hence selects a group of variables related to the drivers. We built two models to reflect the factors that influence the number of recommendations and reviews posted on the platform (i.e., the app). Our models show that all factors, except the driver’s score, significantly influence the recommendation behavior. Likewise, only one factor, passengers’ bad reviews, is insignificant in generating more drivers’ reviews. In the conclusion, we summarize the findings and limitations of the research.

Keywords: online recommendation, P2P taxi service, review-writing, word of mouth

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Authors: Phutthiwat Waiyawuththanapoom, Pimploi Tirastittam, Manop Tirastittam

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Thailand is the agriculture country which mainly exports the agriculture product to the other countries in so many ways which are fresh vegetable, chilled vegetable or frozen vegetable. The gross export for Thailand’s vegetable is 30-40 billion baht per year, and the growth rate is about 15-20 percent per year. Ginger is one of the main vegetable product that Thailand export to Japan because Thailand’s Ginger has a good quality and be able to supply Japan’s demand with a reasonable price. This research paper is aimed to study the factors which affect the efficiency of the supply chain process of Thailand’s ginger to Japan. There are 5 factors which related to the exporting Thailand’s ginger to Japan which are quality, price, equipment and supply standard, custom process and distribution pattern. The result of the research showed that the factor which reached the 'very good' significant level is quality of Thailand’s ginger with the score of 4.86. The other 5 factors are in the 'good' significant level. So the most important factor for Thai ginger farmer to concern is the quality of the product.

Keywords: critical success factor, export, ginger, supply chain

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Authors: Hai Chien Pham, Thi Phuong Anh Vo, Chansik Park

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Risks management in construction projects is important to ensure the positive feasibility of the projects in which financial risks are most concerned while construction projects always run on a credit basis. Credit risks, therefore, require unique and technical tools to be well managed. Underwriting technique in credit risks, in its most basic sense, refers to the process of evaluating the risks and the potential exposure of losses. Risks analysis and underwriting are applied as a must in banks and financial institutions who are supporters for constructions projects when required. Recently, construction organizations, especially contractors, have recognized the significant increasing of credit risks which caused negative impacts to project performance and profit of construction firms. Despite the successful application of underwriting in banks and financial institutions for many years, there are few contractors who are applying this technique to analyze and mitigate the credit risks of their potential owners before signing contracts with them for delivering their performed services. Thus, contractors have taken credit risks during project implementation which might be not materialized due to the bankruptcy and/or protracted default made by their owners. With this regard, this study proposes a model using the underwriting technique for contractors to analyze and assess credit risks of their owners before making final decisions for the potential construction contracts. Contractor’s underwriters are able to analyze and evaluate the subjects such as owner, country, sector, payment terms, financial figures and their related concerns of the credit limit requests in details based on reliable information sources, and then input into the proposed model to have the Overall Assessment Score (OAS). The OAS is as a benchmark for the decision makers to grant the proper limits for the project. The proposed underwriting model is validated by 30 subjects in Asia Pacific region within 5 years to achieve their OAS, and then compare output OAS with their own practical performance in order to evaluate the potential of underwriting model for analyzing and assessing credit risks. The results revealed that the underwriting would be a powerful method to assist contractors in making precise decisions. The contribution of this research is to allow the contractors firstly to develop their own credit risk management model for proactively preventing the credit risks of construction projects and continuously improve and enhance the performance of this function during project implementation.

Keywords: underwriting technique, credit risk, risk management, construction project

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Authors: Shishen Xie, Yingda L. Xie

Abstract:

Tuberculosis (TB) is a potentially serious infectious disease that remains a health concern. The Interferon Gamma Release Assay (IGRA) is a blood test to find out if an individual is tuberculous positive or negative. This study applies statistical analysis to the clinical data of interferon-gamma levels of seventy-three subjects who diagnosed pulmonary TB in an anti-tuberculous treatment. Data analysis is performed to determine if there is a significant decline in interferon-gamma levels for the subjects during a period of six months, and to infer if the anti-tuberculous treatment is effective.

Keywords: data analysis, interferon gamma release assay, statistical methods, tuberculosis infection

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Authors: Asmaa M. Hussein, Amr Wassal, Ahmed Farouk Al-Sadek, A. F. Abd El-Rahman

Abstract:

In this study, a multivariate analysis of potato spectroscopic data was presented to detect the presence of brown rot disease or not. Near-Infrared (NIR) spectroscopy (1,350-2,500 nm) combined with multivariate analysis was used as a rapid, non-destructive technique for the detection of brown rot disease in potatoes. Spectral measurements were performed in 565 samples, which were chosen randomly at the infection place in the potato slice. In this study, 254 infected and 311 uninfected (brown rot-free) samples were analyzed using different advanced statistical analysis techniques. The discrimination performance of different multivariate analysis techniques, including classification, pre-processing, and dimension reduction, were compared. Applying a random forest algorithm classifier with different pre-processing techniques to raw spectra had the best performance as the total classification accuracy of 98.7% was achieved in discriminating infected potatoes from control.

Keywords: Brown rot disease, NIR spectroscopy, potato, random forest

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Authors: Liya Shan, Qing Liao, Qinyue Hu, Shantao Jiang, Tao Wang

Abstract:

In this paper, a Quality of Experience (QoE)-driven cross-layer resource allocation scheme for high traffic service over Open Wireless Network (OWN) downlink is proposed, and the related problem about the users in the whole cell including the users in overlap region of different cells has been solved.A method, in which assess models of the BestEffort service and the no-reference assess algorithm for video service are adopted, to calculate the Mean Opinion Score (MOS) value for high traffic service has been introduced. The cross-layer architecture considers the parameters in application layer, media access control layer and physical layer jointly. Based on this architecture and the MOS value, the Binary Constrained Particle Swarm Optimization (B_CPSO) algorithm is used to solve the cross-layer resource allocation problem. In addition,simulationresults show that the proposed scheme significantly outperforms other schemes in terms of maximizing average users’ MOS value for the whole system as well as maintaining fairness among users.

Keywords: high traffic service, cross-layer resource allocation, QoE, B_CPSO, OWN

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Authors: Fadwa Alhalaiqa, Othman Alfuqaha, Anas H. Khalifeh, Mahmoud Alsaraireh, Rami Masa’Deh, Natija S Manaa

Abstract:

Background: Post-traumatic stress disorders (PTSD) usually occur after traumatic occurrences that exceed the range of common human experience. This study aimed to test the psychometric properties of PCL-5 checklist for the 20 PTSD symptoms from DSM-5 among Lebanese population and to identify the prevalence of PTSD. Methods: A cross sectional survey of PCL5 among 950 Lebanese using the online survey platform by Google form was conducted. Snowball recruitment was used to identify participants for the survey. STROBE guideline was used in reporting the current study. Results: Face content, construct, discriminant, and convergent validity had been accomplished of PCL-5. The reliability by Cronbach alpha, composite, and average variance extracted were set superior. We found also that more than half of the participants (55.6%) scored 33 or above, which is the cutoff score for a likely diagnosis of PTSD. Conclusion: The current study provides further support for the Arabic version PCL-5 validity and reliability among non-Western populations. This support using this tool in the screening of PTSD.

Keywords: post traumatic stress disorder, psychometric properties, stress, adult population

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Authors: Georges Jabbour

Abstract:

Background and aims: This two-year follow-up study explores the long-term sustainability of physical activity (PA) levels in young people with type 1 diabetes, focusing on the relationship between PA, hypoglycemia, and behavioral scores. The literature highlights the importance of PA and its health benefits, as well as the barriers to engaging in PA practices. Studies have shown that individuals with high levels of vigorous physical activity have higher fear of hypoglycemia (FOH) scores and more hypoglycemia episodes. Considering that hypoglycemia episodes are a major barrier to physical activity, and many studies reported a negative association between PA and high FOH scores, it cannot be guaranteed that those experiencing hypoglycemia over a long period will remain active. Building on that, the present work assesses whether high PA levels, despite elevated hypoglycemia risk, can be maintained over time. The study tracks PA levels at one and two years, correlating them with hypoglycemia instances and Fear of Hypoglycemia (FOH) scores. Materials and methods: A self-administered questionnaire was completed by 61 youth with T1D, and their PA was assessed. Hypoglycemia episodes, fear of hypoglycemia scores and HbA1C levels were collected. All assessments were realized at baseline (visit 0: V0), one year (V1) and two years later (V2). For the purpose of the present work, we explore the relationships between PA levels, hypoglycemia episodes, and FOH scores at each time point. We used multiple linear regression to model the mean outcomes for each exposure of interest. Results: Findings indicate no changes in total moderate to vigorous PA (MVPA) and VPA levels among visits, and HbA1c (%) was negatively correlated with the total amount of VPA per day in minutes (β= -0.44; p=0.01, β= -0.37; p=0.04, and β= -0.66; p=0.01 for V0, V1, and V2, respectively). Our linear regression model reported a significant negative correlation between VPA and FOH across the visits (β=-0.59, p=0.01; β= -0.44, p=0.01; and β= -0.34, p=0.03 for V0, V1, and V2, respectively), and HbA1c (%) was influenced by both the number of hypoglycemic episodes and FOH score at V2 (β=0.48; p=0.02 and β=0.38; p=0.03, respectively). Conclusion: The sustainability of PA levels and HbA1c (%) in young individuals with type 1 diabetes is influenced by various factors, including fear of hypoglycemia. Understanding these complex interactions is essential for developing effective interventions to promote sustained PA levels in this population. Our results underline the necessity of a multi-strategic approach to promoting active lifestyles among diabetic youths. This approach should synergize PA enhancement with vigilant glucose monitoring and effective FOH management.

Keywords: physical activity, hypoglycemia, fear of hypoglycemia, youth

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