Search results for: multivariate statistical analysis

Authors: Kadir Gök

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In this study, a vacuum system was developed for orthopedic drilling processes, and the most efficient processing parameters were determined using statistical analysis of temperature rise. A reverse engineering technique was used to obtain a 3D model of the chip vacuum system, and the obtained point cloud data was transferred to Solidworks software in STL format. An experimental design method was performed by selecting different parameters and their levels, such as RPM, feed rate, and drill bit diameter, to determine the most efficient processing parameters in temperature rise using ANOVA. Additionally, the bone chip-vacuum device was developed and performed successfully to collect the whole chips and fragments in the bone drilling experimental tests, and the chip-collecting device was found to be useful in removing overheating from the drilling zone. The effects of processing parameters on the temperature levels during the chip-vacuuming were determined, and it was found that bone chips and fractures can be used as autograft and allograft for tissue engineering. Overall, this study provides significant insights into the development of a vacuum system for orthopedic drilling processes and the use of bone chips and fractures in tissue engineering applications.

Keywords: vacuum system, orthopedic drilling, temperature rise, bone chips

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Authors: Sheena Christabel Pravin, M. Palanivelan

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Speech disfluencies are common in spontaneous speech. The primary purpose of this study was to distinguish linguistic disfluencies from stuttering disfluencies in bilingual Tamil–English (TE) speaking children. The secondary purpose was to determine whether their disfluencies are mediated by native language dominance and/or on an early onset of developmental stuttering at childhood. A detailed study was carried out to identify the prosodic and acoustic features that uniquely represent the disfluent regions of speech. This paper focuses on statistical modeling of repetitions, prolongations, pauses and interjections in the speech corpus encompassing bilingual spontaneous utterances from school going children – English and Tamil. Two classifiers including Hidden Markov Models (HMM) and the Multilayer Perceptron (MLP), which is a class of feed-forward artificial neural network, were compared in the classification of disfluencies. The results of the classifiers document the patterns of disfluency in spontaneous speech samples of school-aged children to distinguish between Children Who Stutter (CWS) and Children with Language Impairment CLI). The ability of the models in classifying the disfluencies was measured in terms of F-measure, Recall, and Precision.

Keywords: bi-lingual, children who stutter, children with language impairment, hidden markov models, multi-layer perceptron, linguistic disfluencies, stuttering disfluencies

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Authors: Manasvi Pinnaka, Brianna Chrisman

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Cystic fibrosis patients often develop lung infections that range anywhere in severity from mild to life-threatening due to the presence of thick and sticky mucus that fills their airways. Since many of these infections are chronic, they not only affect a patient’s ability to breathe but also increase the chances of mortality by respiratory failure. With a publicly available dataset of DNA sequences from bacterial species in the lung microbiome of cystic fibrosis patients, the correlations between different microbial species in the lung and the extent of deterioration of lung function were investigated. 16S sequencing technologies were used to determine the microbiome composition of the samples in the dataset. For the statistical analyses, referencing helped distinguish between taxonomies, and the proportions of certain taxa relative to another were determined. It was found that the Fusobacterium, Actinomyces, and Leptotrichia microbial types all had a positive correlation with the FEV1 score, indicating the potential displacement of these species by pathogens as the disease progresses. However, the dominant pathogens themselves, including Pseudomonas aeruginosa and Staphylococcus aureus, did not have statistically significant negative correlations with the FEV1 score as described by past literature. Examining the lung microbiology of cystic fibrosis patients can help with the prediction of the current condition of lung function, with the potential to guide doctors when designing personalized treatment plans for patients.

Keywords: bacterial infections, cystic fibrosis, lung microbiome, 16S sequencing

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Authors: Wang Yichen, Haruka Yamashita

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In recent years, in the field of sports, decision making such as member in the game and strategy of the game based on then analysis of the accumulated sports data are widely attempted. In fact, in the NBA basketball league where the world's highest level players gather, to win the games, teams analyze the data using various statistical techniques. However, it is difficult to analyze the game data for each play such as the ball tracking or motion of the players in the game, because the situation of the game changes rapidly, and the structure of the data should be complicated. Therefore, it is considered that the analysis method for real time game play data is proposed. In this research, we propose an analytical model for "determining the optimal lineup composition" using the real time play data, which is considered to be difficult for all coaches. In this study, because replacing the entire lineup is too complicated, and the actual question for the replacement of players is "whether or not the lineup should be changed", and “whether or not Small Ball lineup is adopted”. Therefore, we propose an analytical model for the optimal player selection problem based on Small Ball lineups. In basketball, we can accumulate scoring data for each play, which indicates a player's contribution to the game, and the scoring data can be considered as a time series data. In order to compare the importance of players in different situations and lineups, we combine RNN (Recurrent Neural Network) model, which can analyze time series data, and NN (Neural Network) model, which can analyze the situation on the field, to build the prediction model of score. This model is capable to identify the current optimal lineup for different situations. In this research, we collected all the data of accumulated data of NBA from 2019-2020. Then we apply the method to the actual basketball play data to verify the reliability of the proposed model.

Keywords: recurrent neural network, players lineup, basketball data, decision making model

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Authors: Farid Khosravikia, Patricia Clayton

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The main objective of this work is to evaluate the advantages and disadvantages of various machine learning techniques in two key steps of seismic hazard and risk assessment of different types of structures. The first step is the development of ground-motion models, which are used for forecasting ground-motion intensity measures (IM) given source characteristics, source-to-site distance, and local site condition for future events. IMs such as peak ground acceleration and velocity (PGA and PGV, respectively) as well as 5% damped elastic pseudospectral accelerations at different periods (PSA), are indicators of the strength of shaking at the ground surface. Typically, linear regression-based models, with pre-defined equations and coefficients, are used in ground motion prediction. However, due to the restrictions of the linear regression methods, such models may not capture more complex nonlinear behaviors that exist in the data. Thus, this study comparatively investigates potential benefits from employing other machine learning techniques as statistical method in ground motion prediction such as Artificial Neural Network, Random Forest, and Support Vector Machine. The results indicate the algorithms satisfy some physically sound characteristics such as magnitude scaling distance dependency without requiring pre-defined equations or coefficients. Moreover, it is shown that, when sufficient data is available, all the alternative algorithms tend to provide more accurate estimates compared to the conventional linear regression-based method, and particularly, Random Forest outperforms the other algorithms. However, the conventional method is a better tool when limited data is available. Second, it is investigated how machine learning techniques could be beneficial for developing probabilistic seismic demand models (PSDMs), which provide the relationship between the structural demand responses (e.g., component deformations, accelerations, internal forces, etc.) and the ground motion IMs. In the risk framework, such models are used to develop fragility curves estimating exceeding probability of damage for pre-defined limit states, and therefore, control the reliability of the predictions in the risk assessment. In this study, machine learning algorithms like artificial neural network, random forest, and support vector machine are adopted and trained on the demand parameters to derive PSDMs for them. It is observed that such models can provide more accurate estimates of prediction in relatively shorter about of time compared to conventional methods. Moreover, they can be used for sensitivity analysis of fragility curves with respect to many modeling parameters without necessarily requiring more intense numerical response-history analysis.

Keywords: artificial neural network, machine learning, random forest, seismic risk analysis, seismic hazard analysis, support vector machine

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Authors: Mehari Teshome, Lara Agostini, Anna Nosella

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The current knowledge-based economy extends intellectual property rights (IPRs) legal research themes into a more strategic and organizational perspectives. From the diverse types of IPRs, patents are the strongest and well-known form of legal protection that influences commercial success and market value. Indeed, from our pilot survey, we understood that firms are less likely to manage their patents and actively used it as a tool for achieving competitive advantage rather they invest resource and efforts for patent application. To this regard, the literature also confirms that insights into how firms manage their patents from a holistic, strategic perspective, and how the portfolio value of patents can be optimized are scarce. Though patent management is an important business tool and there exist few scales to measure some dimensions of patent management, at the best of our knowledge, no systematic attempt has been made to develop a valid and comprehensive measure of it. Considering this theoretical and practical point of view, the aim of this article is twofold: to develop a framework for patent management encompassing all relevant dimensions with their respective constructs and measurement items, and to validate the measurement using survey data from practitioners. Methodology: We used six-step methodological approach (i.e., specify the domain of construct, item generation, scale purification, internal consistency assessment, scale validation, and replication). Accordingly, we carried out a systematic review of 182 articles on patent management, from ISI Web of Science. For each article, we mapped relevant constructs, their definition, and associated features, as well as items used to measure these constructs, when provided. This theoretical analysis was complemented by interviews with experts in patent management to get feedbacks that are more practical on how patent management is carried out in firms. Afterwards, we carried out a questionnaire survey to purify our scales and statistical validation. Findings: The analysis allowed us to design a framework for patent management, identifying its core dimensions (i.e., generation, portfolio-management, exploitation and enforcement, intelligence) and support dimensions (i.e., strategy and organization). Moreover, we identified the relevant activities for each dimension, as well as the most suitable items to measure them. For example, the core dimension generation includes constructs as: state-of-the-art analysis, freedom-to-operate analysis, patent watching, securing freedom-to-operate, patent potential and patent-geographical-scope. Originality and the Study Contribution: This study represents a first step towards the development of sound scales to measure patent management with an overarching approach, thus laying the basis for developing a recognized landmark within the research area of patent management. Practical Implications: The new scale can be used to assess the level of sophistication of the patent management of a company and compare it with other firms in the industry to evaluate their ability to manage the different activities involved in patent management. In addition, the framework resulting from this analysis can be used as a guide that supports managers to improve patent management in firms.

Keywords: patent, management, scale, development, intellectual property rights (IPRs)

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Authors: Elizabeth Adebomi Akinlotan, Olukemi Odukoya

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INTRODUCTION: Physical Activity is defined as activity that involves bodily movement which is done as a part of daily activity in the form of working, playing, active transportation such as walking and also as a form of recreational activity. Physical inactivity has been identified as the fourth leading risk factor for global mortality and morbidity causing an estimated 3.2 million deaths globally and 5.5% of total deaths and it remains a pressing public health issue. There is a shift in the major causes of death from communicable to non-communicable diseases in many developed countries and this is fast becoming the case in developing countries. Physical activity is an important determinant of health and has been associated with lower mortality rates as it reduces the risk of developing chronic diseases such as diabetes mellitus, hypertension, stroke, cancer and osteoporosis. It improves musculoskeletal health, controls weight and reduces symptoms of depression. AIM: The aim is to study the knowledge, attitude and practices of physical activity among adults in Alimosho local government area. METHODOLOGY: This was a descriptive cross sectional survey designed to study the knowledge, attitude and practice of physical activity among adults in Alimosho Local Government Area. The study population were 250 adults aged 18-65 who were residents of the area of more than 6 months duration and had no chronic disease condition or physical disability. A multistage sampling method was used to select the respondents and data was collected using interviewer administered questionnaires. The data was analyzed with the use of EPI-info 2007 statistical software. Chi Square was thereafter used to test the association between selected variables. The level of statistical significance was set at 5% (p<0.05). RESULTS: In general, majority (61.6%) of the respondents had a good knowledge of what physical activity entails, 34.0% had fair knowledge and 4.4% had poor knowledge. There was a favorable attitude towards physical activity among the respondents with 82.4% having an overall positive attitude. Below a third of the respondents (26.4%) reported having a high physical activity (METS > 3001) while 40.0% had moderate (601-3000 METS) levels of activity and 33.6% were inactive (<600METS). There is statistical significance between the gender of the respondent and the levels of physical activity (p=0.0007); 75.2% males reached the minimum recommendations while 24.8% were inactive and 55.0% females reached the minimum recommendations while 45.0% were inactive. Results also showed that of 95 respondents who were satisfied with their levels of physical activity, 33.7% were insufficiently active while 66.3% were either minimally active or highly active and of 110 who were unsatisfied with their levels of physical activity, 72.0% were above the minimum recommendations while 38.0% were insufficiently active. CONCLUSION: In contrast to the high level of knowledge and favorable attitude towards physical activity, there was a lower level of practice of high or moderate physical activities. It is recommended that more awareness should be created on the recommended levels of physical activity especially for the vigorous intensity and moderate intensity physical activity.

Keywords: METS, physical activity, physical inactivity, public health

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Authors: Mehdi Rahimi-Nasrabadi, Seied Mahdi Pourmortazavi

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Taguchi robust design as a statistical method was applied for optimization of the process parameters in order to tunable, simple and fast synthesis of europium (III) tungstate nanoparticles. Europium (III) tungstate nanoparticles were synthesized by a chemical precipitation reaction involving direct addition of europium ion aqueous solution to the tungstate reagent solved in aqueous media. Effects of some synthesis procedure variables i.e., europium and tungstate concentrations, flow rate of cation reagent addition, and temperature of reaction reactor on the particle size of europium (III) tungstate nanoparticles were studied experimentally in order to tune particle size of europium (III) tungstate. Analysis of variance shows the importance of controlling tungstate concentration, cation feeding flow rate and temperature for preparation of europium (III) tungstate nanoparticles by the proposed chemical precipitation reaction. Finally, europium (III) tungstate nanoparticles were synthesized at the optimum conditions of the proposed method and the morphology and chemical composition of the prepared nano-material were characterized by means of X-Ray diffraction, scanning electron microscopy, transmission electron microscopy, FT-IR spectroscopy, and fluorescence.

Keywords: europium (III) tungstate, nano-material, particle size control, procedure optimization

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Authors: Rasha Waheeb, Bjorn Andersen, Rafa Shakir

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Purpose The purpose of this study is to avoid delays that occur in emergency reconstruction projects especially in post disaster circumstances whether if they were natural or manmade due to their particular national and humanitarian importance. We presented a theoretical and practical concepts for projects management in the field of construction industry that deal with a range of global and local trails. This study aimed to identify the factors of effective delay in construction projects in Iraq that affect the time and the specific quality cost, and find the best solutions to address delays and solve the problem by setting parameters to restore balance in this study. 30 projects were selected in different areas of construction were selected as a sample for this study. Design/methodology/approach This study discusses the reconstruction strategies and delay in time and cost caused by different delay factors in some selected projects in Iraq (Baghdad as a case study).A case study approach was adopted, with thirty construction projects selected from the Baghdad region, of different types and sizes. Project participants from the case projects provided data about the projects through a data collection instrument distributed through a survey. Mixed approach and methods were applied in this study. Mathematical data analysis was used to construct models to predict delay in time and cost of projects before they started. The artificial neural networks analysis was selected as a mathematical approach. These models were mainly to help decision makers in construction project to find solutions to these delays before they cause any inefficiency in the project being implemented and to strike the obstacles thoroughly to develop this industry in Iraq. This approach was practiced using the data collected through survey and questionnaire data collection as information form. Findings The most important delay factors identified leading to schedule overruns were contractor failure, redesigning of designs/plans and change orders, security issues, selection of low-price bids, weather factors, and owner failures. Some of these are quite in line with findings from similar studies in other countries/regions, but some are unique to the Iraqi project sample, such as security issues and low-price bid selection. Originality/value we selected ANN’s analysis first because ANN’s was rarely used in project management , and never been used in Iraq to finding solutions for problems in construction industry. Also, this methodology can be used in complicated problems when there is no interpretation or solution for a problem. In some cases statistical analysis was conducted and in some cases the problem is not following a linear equation or there was a weak correlation, thus we suggested using the ANN’s because it is used for nonlinear problems to find the relationship between input and output data and that was really supportive.

Keywords: construction projects, delay factors, emergency reconstruction, innovation ANN, post disasters, project management

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Authors: Peter J. Fusco, Dave M. Mathew, Chris Mathew, Kenneth H. Levy, Kathryn S. Varghese, Stephanie Salazar-Restrepo, Serena M. Mathew, Sofia Khaja, Eamon Vega, Mia Polizzi, Alyssa Mullane, Adham Ahmed

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Background: Laparoscopic (LS) removal of neuroblastomas in children has been reported to offer favorable outcomes compared to the conventional open thoracotomy (OT) procedure. Critical perioperative measures such as blood loss, operative time, length of stay, and time to postoperative chemotherapy have all supported laparoscopic use rather than its more invasive counterpart. Herein, a pairwise meta-analysis was performed comparing perioperative outcomes between LS and OT in thoracoabdominal neuroblastoma cases. Methods: A comprehensive literature search was performed on PubMed, Ovid EMBASE, and Scopus databases to identify studies comparing the outcomes of pediatric patients with thoracoabdominal neuroblastomas undergoing resection via OT or LS. After deduplication, 4,227 studies were identified and subjected to initial title screening with exclusion and inclusion criteria to ensure relevance. When studies contained overlapping cohorts, only the larger series were included. Primary outcomes include estimated blood loss (EBL), hospital length of stay (LOS), and mortality, while secondary outcomes were tumor recurrence, post-operative complications, and operation length. The “meta” and “metafor” packages were used in R, version 4.0.2, to pool risk ratios (RR) or standardized mean differences (SMD) in addition to their 95% confidence intervals in the random effects model via the Mantel-Haenszel method. Heterogeneity between studies was assessed using the I² test, while publication bias was assessed via funnel plot. Results: The pooled analysis included 209 patients from 5 studies (141 OT, 68 LS). Of the included studies, 2 originated from the United States, 1 from Toronto, 1 from China, and 1was from a Japanese center. Mean age between study cohorts ranged from 2.4 to 5.3 years old, with female patients occupying between 30.8% to 50% of the study populations. No statistically significant difference was found between the two groups for LOS (SMD -1.02; p=0.083), mortality (RR 0.30; p=0.251), recurrence(RR 0.31; p=0.162), post-operative complications (RR 0.73; p=0.732), or operation length (SMD -0.07; p=0.648). Of note, LS appeared to be protective in the analysis for EBL, although it did not reach statistical significance (SMD -0.4174; p= 0.051). Conclusion: Despite promising literature assessing LS removal of pediatric neuroblastomas, results showed it was non-superior to OT for any explored perioperative outcomes. Given the limited comparative data on the subject, it is evident that randomized trials are necessary to further the efficacy of the conclusions reached.

Keywords: laparoscopy, neuroblastoma, thoracoabdominal, thoracotomy

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Authors: Daniela Magalhaes, Jorge Pedro, Pedro Souteiro, Joao S. Neves, Sofia Castro-Oliveira, Vanessa Guerreiro, Rita Bettencourt- Silva, Maria M. Costa, Ana Varela, Joana Queiros, Paula Freitas, Davide Carvalho

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Introduction: Obesity is an independent risk factor for renal dysfunction. Our aims were: (1) evaluate the impact of bariatric surgery (BS) on renal function; (2) clarify the factors determining the postoperative evolution of the glomerular filtration rate (GFR); (3) access the occurrence of oxalate-mediated renal complications. Methods: We investigated a cohort of 1448 obese patients who underwent bariatric surgery. Those with basal GFR (GFR0) < 30mL/min or without information about the GFR 2-year post-surgery (GFR2) were excluded. Results: We included 725 patients, of whom 647 (89.2%) women, with 41 (IQR 34-51) years, a median weight of 112.4 (IQR 103.0-125.0) kg and a median BMI of 43.4 (IQR 40.6-46.9) kg/m2. Of these, 459 (63.3%) performed gastric bypass (RYGB), 144 (19.9%) placed an adjustable gastric band (AGB) and 122 (16.8%) underwent vertical gastrectomy (VG). At 2-year post-surgery, excess weight loss (EWL) was 60.1 (IQR 43.7-72.4) %. There was a significant improve of metabolic and inflammatory status, as well as a significant decrease in the proportion of patients with diabetes, arterial hypertension and dyslipidemia (p < 0.0001). At baseline, 38 (5.2%) of subjects had hyperfiltration with a GFR0 ≥ 125mL/min/1.73m2, 492 (67.9%) had a GFR0 90-124 mL/min/1.73m2, 178 (24.6%) had a GFR0 60-89 mL/min/1.73m2, and 17 (2.3%) had a GFR0 < 60 mL/min/1.73m2. GFR decreased in 63.2% of patients with hyperfiltration (ΔGFR=-2.5±7.6), and increased in 96.6% (ΔGFR=22.2±12.0) and 82.4% (ΔGFR=24.3±30.0) of the subjects with GFR0 60-89 and < 60 mL/min/1.73m2, respectively ( p < 0.0001). This trend was maintained when adjustment was made for the type of surgery performed. Of 321 patients, 10 (3.3%) had a urinary albumin excretion (UAE) > 300 mg/dL (A3), 44 (14.6%) had a UAE 30-300 mg/dL (A2) and 247 (82.1%) has a UAE < 30 mg/dL (A1). Albuminuria decreased after surgery and at 2-year follow-up only 1 (0.3%) patient had A3, 17 (5.6%) had A2 and 283 (94%) had A1 (p < 0,0001). In multivariate analysis, the variables independently associated with ΔGFR were BMI (positively) and fasting plasma glucose (negatively). During the 2-year follow-up, only 57 of the 725 patients had transient urinary excretion of calcium oxalate crystals. None has records of oxalate-mediated renal complications at our center. Conclusions: The evolution of GFR after BS seems to depend on the initial renal function, as it decreases in subjects with hyperfiltration, but tends to increase in those with renal dysfunction. Our results suggest that BS is associated with improvement of renal outcomes, without significant increase of renal complications. So, apart the clear benefits in metabolic and inflammatory status, maybe obese adults with nondialysis-dependent CKD should be referred for bariatric surgery evaluation.

Keywords: albuminuria, bariatric surgery, glomerular filtration rate, renal function

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Authors: Soyon Kim, Edward Kim

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In order to retrieve information from the massive stream of songs in the music industry, music search by title, lyrics, artist, mood, and genre has become more important. Despite the subjectivity and controversy over the definition of music genres across different nations and cultures, automatic genre classification systems that facilitate the process of music categorization have been developed. Manual genre selection by music producers is being provided as statistical data for designing automatic genre classification systems. In this paper, an automatic music genre classification system utilizing non-negative matrix factorization (NMF) is proposed. Short-term characteristics of the music signal can be captured based on the timbre features such as mel-frequency cepstral coefficient (MFCC), decorrelated filter bank (DFB), octave-based spectral contrast (OSC), and octave band sum (OBS). Long-term time-varying characteristics of the music signal can be summarized with (1) the statistical features such as mean, variance, minimum, and maximum of the timbre features and (2) the modulation spectrum features such as spectral flatness measure, spectral crest measure, spectral peak, spectral valley, and spectral contrast of the timbre features. Not only these conventional basic long-term feature vectors, but also NMF based feature vectors are proposed to be used together for genre classification. In the training stage, NMF basis vectors were extracted for each genre class. The NMF features were calculated in the log spectral magnitude domain (NMF-LSM) as well as in the basic feature vector domain (NMF-BFV). For NMF-LSM, an entire full band spectrum was used. However, for NMF-BFV, only low band spectrum was used since high frequency modulation spectrum of the basic feature vectors did not contain important information for genre classification. In the test stage, using the set of pre-trained NMF basis vectors, the genre classification system extracted the NMF weighting values of each genre as the NMF feature vectors. A support vector machine (SVM) was used as a classifier. The GTZAN multi-genre music database was used for training and testing. It is composed of 10 genres and 100 songs for each genre. To increase the reliability of the experiments, 10-fold cross validation was used. For a given input song, an extracted NMF-LSM feature vector was composed of 10 weighting values that corresponded to the classification probabilities for 10 genres. An NMF-BFV feature vector also had a dimensionality of 10. Combined with the basic long-term features such as statistical features and modulation spectrum features, the NMF features provided the increased accuracy with a slight increase in feature dimensionality. The conventional basic features by themselves yielded 84.0% accuracy, but the basic features with NMF-LSM and NMF-BFV provided 85.1% and 84.2% accuracy, respectively. The basic features required dimensionality of 460, but NMF-LSM and NMF-BFV required dimensionalities of 10 and 10, respectively. Combining the basic features, NMF-LSM and NMF-BFV together with the SVM with a radial basis function (RBF) kernel produced the significantly higher classification accuracy of 88.3% with a feature dimensionality of 480.

Keywords: mel-frequency cepstral coefficient (MFCC), music genre classification, non-negative matrix factorization (NMF), support vector machine (SVM)

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Authors: Peter Mc Coll, Alberto Caro, Chiara Gandolfo, Montserrat Labbe, Francisca Schnaidt, Michela Palazzi

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Self-esteem and emotional intelligence are variables that are related to people's nutritional status. Self-esteem may be at low levels in people living with obesity, while emotional intelligence can play an important role in the way people living with obesity cope. The objective of the study was to measure the association between self-esteem and emotional intelligence to nutritional status in adolescent population. Methodology: A cross-sectional study was carried out with 179 adolescent schoolchildren between 13 and 19 years old from a public school. The objective was to evaluate nutritional status; weight and height were measured by calculating the body mass index and Z score. Self-esteem was evaluated using the Coopersmith Self-esteem Inventory adapted by Brinkmann and Segure. Emotional intelligence was measured using the Emotional Quotient Inventory: short, by Bar On, adapted questionnaire, translated into Spanish by López Zafra. For statistical analysis: Pearson's Chi-square test, Pearson's correlation, and odd ratio calculation were used, with a p value at a significance level < 5%. Results: The study group was composed of 71% female and 29% male. The nutritional status was distributed as eutrophic 41.9%, overweight 20.1%, and obesity 21.1%. In relation to self-esteem, 44.1% presented low and very low levels, without differences by gender. Emotional intelligence was distributed: low 3.4%, medium 81%, and high 13.4% -no differences according to gender. The association between nutritional status (overweight and obesity) with low and very low self-esteem, an odds ratio of 2.5 (95% CI 1.12 – 5.59) was obtained with a p-value = 0.02. The correlation analysis between the intrapersonal sub-dimension emotional intelligence scores and the Z score of nutritional status presented a negative correlation of r = - 0.209 with a p-value < 0.005. The correlation between emotional intelligence subdimension stress management with Z score presented a positive correlation of r = 0.0161 with a p-value < 0.05. In conclusion, the group of adolescents studied had a high prevalence of overweight and obesity, a high prevalence of low self-esteem, and a high prevalence of average emotional intelligence. Overweight and obese adolescents were 2.5 times more likely to have low self-esteem. As overweight and obesity increase, self-esteem decreases, and the ability to manage stress increases.

Keywords: self-esteem, emotional intelligence, obesity, adolescent, nutritional status

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Authors: Pornnapat Berndt

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The purpose of this research is to study the tourism routes in Bangnoi Floating Market, Bangkhontee District, Samut Songkhram province, Thailand in order to create type and form of interpretation to promote cultural tourism based on local community and visitor requirement. To accomplish the goals and objectives, qualitative research will be applied. The research instruments used are observation, questionnaires, basic interviews, in-depth interviews, focus group, interviewed of key local informants including site visitors. The study also uses both primary data and secondary data. A Statistical Package for Social Sciences (SPSS) was used to analyze the data. Descriptive and inferential statistics such as tables, percentage, mean and standard deviation were used for data analysis and summary. From research result, it is revealed that the local community requirement on types of interpretation conforms to visitors require which need guide post, guide book, etc. with up to date and informally content to present Bangnoi Floating Market which got the most demand score (3.78) considered as most wanted demand.

Keywords: interpretation, cultural tourism, tourism route, local community, stakeholders participated

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Authors: Haolin Li, Eric Bair, Jane Monaco, Quefeng Li

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The temporomandibular disorder (TMD) is a series of musculoskeletal disorders ranging from jaw pain to chronic debilitating pain, and the risk factors for the onset and maintenance of TMD are still unclear. Prior researches have shown that the potential risk factors for chronic TMD are related to psychosocial factors, autonomic functions, and pain sensitivity. Using data from the Orofacial Pain: Prospective Evaluation and Risk Assessment (OPPERA) study’s baseline case-control study, we examine whether the risk factors identified by prior researches are still statistically significant after taking all of the risk measures into account in one single model, and we also compare the relative influences of the risk factors in three different perspectives (psychosocial factors, autonomic functions, and pain sensitivity) on the chronic TMD. The statistical analysis is conducted by using ridge logistic regression and bootstrapping, in which the performance of the algorithms has been assessed using extensive simulation studies. The results support most of the findings of prior researches that there are many psychosocial and pain sensitivity measures that have significant associations with chronic TMD. However, it is surprising that most of the risk factors of autonomic functions have not presented significant associations with chronic TMD, as described by a prior research.

Keywords: autonomic function, OPPERA study, pain sensitivity, psychosocial measures, temporomandibular disorder

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Authors: Oluronke Odunjo

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The world is becoming increasingly urbanized and Nigeria is not left out. One of the indicators of human developments is housing and as such, water is needed by households for survival. This Paper assesses sources of water being used by residents in the newly urbanized areas of Ogbomoso, Southwest, Nigeria. Multistage sampling technique was used and Oke-Adunin Community was purposively selected for the study as it has large concentration of staff and students of Ladoke Akintola University of Technology. The area was captured with Google earth and two hundred and twenty two inhabited houses were found. Questionnaire was the instrument for data collection which was administered using total enumeration technique. Data obtained however, were analyzed with descriptive and inferential statistical analyses. Findings revealed that most of the respondents were male, while 36.03% house owners were between the ages of 46 and 55 years. Sources of water used by residents include well (56.94%), water vendors (17.77%), rain (15.29%) and borehole (3.72%). Distance travelled by house owners to sources of water was as high as 5.06 metres, resulting into stress (30.00 %), depression (25.00%) and aggressiveness (18.75%). Result of correlation analysis between the sources of water of respondents and disease prevalence showed that both rain water and water vendor had very strong positive correlation with typhoid, diarrhea and dysentery, while well water only had positive correlation with dysentery. Recommendations were therefore, proffered towards solving the problems associated with water in the area.

Keywords: newly urbanized area, Ogbomoso, sources of water, residents

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Authors: Marta Fernandez Cabrera

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The period of economic boom generated by the housing bubble created a climate of social indifference to the problem of corruption. This resulted in the persecution and conviction for these criminal offenses being low. After the economic recession, social awareness about the problem of corruption has increased. This has led to the Spanish citizenship requiring the public authorities to try to end the problem in the most effective way possible. In order to respond to the continuous social demands that require an exemplary punishment, the legislator has made changes in crimes against the public administration in the Spanish Criminal Code. However, from the point of view of criminal law, the social change has not served to modify only the law, but also the jurisprudence. After the recession, judges are punishing more severely these conducts than in the past. Before the crisis, it was usual for criminal judges to divert relevant behavior to other areas of the legal system such as administrative law and acquit in the criminal field. Criminal judges have considered that administrative law already has mechanisms that can effectively deal with this type of behavior in order to respect the principle of subsidiarity or ultima ratio. It has also been usual for criminal judges to acquit civil servants due to the absence of requirements unrelated to the applicable offense. For example, they have required an economic damage to the public administration when the offense in the criminal code does not require it. Nevertheless, for some years, these arguments have either partially disappeared or considerably transformed. Since 2010, a jurisprudential stream has been consolidated that aims to provide a more severe response to corruption than it had received until now. This change of opinion, together with greater prosecution of these behaviors by judges and prosecutors, has led to a significant increase in the number of individuals convicted of corruption crimes. This paper has two objectives. The first one is to show that even though judges apply the law impartially, they are flexible to social changes. The second one is to identify the erroneous arguments the courts have used up until now. To carry out the present paper, it has been done a detailed analysis of the judgments of the supreme court before and after the year 2010. Therefore, the jurisprudential analysis is complemented with the statistical data on corruption available.

Keywords: corruption, public administration, social perception, ultima ratio principle

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Authors: Hela Ayeb Mrabtini, Ghazi Bellakhal, Jamel Chahed

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The presence of the dispersed phase in gas-liquid bubbly flow considerably alters the liquid turbulence. The bubbles induce turbulent fluctuations that enhance the global liquid turbulence level and alter the mechanisms of turbulence. RANS modeling of uniformly sheared flows on an isolated sphere centered in a control volume is performed using first and second order turbulence closures. The sphere is placed in the production-dissipation equilibrium zone where the liquid velocity is set equal to the relative velocity of the bubbles. The void fraction is determined by the ratio between the sphere volume and the control volume. The analysis of the turbulence statistics on the control volume provides numerical results that are interpreted with regard to the effect of the bubbles wakes on the turbulence structure in uniformly sheared bubbly flow. We assumed for this purpose that at low void fraction where there is no hydrodynamic interaction between the bubbles, the single-phase flow simulation on an isolated sphere is representative on statistical average of a sphere network. The numerical simulations were firstly validated against the experimental data of bubbly homogeneous turbulence with constant shear and then extended to produce numerical results for a wide range of shear rates from 0 to 10 s^-1. These results are compared with our turbulence closure proposed for gas-liquid bubbly flows. In this closure, the turbulent stress tensor in the liquid is split into a turbulent dissipative part produced by the gradient of the mean velocity which also contains the turbulence generated in the bubble wakes and a pseudo-turbulent non-dissipative part induced by the bubbles displacements. Each part is determined by a specific transport equation. The simulations of uniformly sheared flows on an isolated sphere reproduce the mechanisms related to the turbulent part, and the numerical results are in perfect accordance with the modeling of the transport equation of the turbulent part. The reduction of second order turbulence closure provides a description of the modification of turbulence structure by the bubbles presence using a dimensionless number expressed in terms of two-time scales characterizing the turbulence induced by the shear and that induced by bubbles displacements. The numerical simulations carried out in the framework of a comprehensive analysis reproduce particularly the attenuation of the turbulent friction showed in the experimental results of bubbly homogeneous turbulence subjected to a constant shear.

Keywords: gas-liquid bubbly flows, homogeneous turbulence, turbulence closure, uniform shear

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Authors: B. Mavhuru, N. S. Nethengwe

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Human activities on land degradation have triggered several environmental problems especially in rural areas that are underdeveloped. The main aim of this study is to analyze the contribution of different land uses to gully development and sediment load on the Nzhelele River Valley in the Limpopo Province. Data was collected using different methods such as observation, field data techniques and experiments. Satellite digital images, topographic maps, aerial photographs and the sediment load static model also assisted in determining how land use affects gully development and sediment load. For data analysis, the researcher used the following methods: Analysis of Variance (ANOVA), descriptive statistics, Pearson correlation coefficient and statistical correlation methods. The results of the research illustrate that high land use activities create negative changes especially in areas that are highly fragile and vulnerable. Distinct impact on land use change was observed within settlement area (9.6 %) within a period of 5 years. High correlation between soil organic matter and soil moisture (R=0.96) was observed. Furthermore, a significant variation (p ≤ 0.6) between the soil organic matter and soil moisture was also observed. A very significant variation (p ≤ 0.003) was observed in bulk density and extreme significant variations (p ≤ 0.0001) were observed in organic matter and soil particle size. The sand mining and agricultural activities has contributed significantly to the amount of sediment load in the Nzhelele River. A high significant amount of total suspended sediment (55.3 %) and bed load (53.8 %) was observed within the agricultural area. The connection which associates the development of gullies to various land use activities determines the amount of sediment load. These results are consistent with other previous research and suggest that land use activities are likely to exacerbate the development of gullies and sediment load in the Nzhelele River Valley.

Keywords: drainage basin, geomorphological processes, gully development, land degradation, riparian land use and sediment load

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Authors: Abdullah Al Mamoon, Ataur Rahman

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Due to climate change, future rainfall will change at many locations on earth; however, the spatial and temporal patterns of this change are not easy to predict. One approach of predicting such future changes is to examine the trends in the historical rainfall data at a given region and use the identified trends to make future prediction. For this, a statistical trend test is commonly applied to the historical data. This paper examines the trends of daily extreme rainfall events from 30 rain gauges located in the State of Qatar. Rainfall data covering from 1962 to 2011 were used in the analysis. A combination of four non-parametric and parametric tests was applied to identify trends at 10%, 5%, and 1% significance levels. These tests are Mann-Kendall (MK), Spearman’s Rho (SR), Linear Regression (LR) and CUSUM tests. These tests showed both positive and negative trends throughout the country. Only eight stations showed positive (upward) trend, which were however not statistically significant. In contrast, significant negative (downward) trends were found at the 5% and 10% levels of significance in six stations. The MK, SR and LR tests exhibited very similar results. This finding has important implications in the derivation/upgrade of design rainfall for Qatar, which will affect design and operation of future urban drainage infrastructure in Qatar.

Keywords: trends, extreme rainfall, daily rainfall, Mann-Kendall test, climate change, Qatar

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Authors: Riona Dighe

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

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

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Authors: Walid A. Alkeridy, Arwa Aljasser, Khalid Mohammed Alayed, Saad Alsaad, Amani S. Alqahtani, Claire Ann Lim, Sultan H. Alamri, Doaa Zainhom Mekkawy, Mohammed Al-Sofiani

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Introduction: The history of publicly funded Home Health Care (HHC) service in Saudi Arabia dates back to 1991. The first HC program was launched to provide palliative home care services for patients with terminal cancer. Thereafter, more programs launched across Saudi Arabia most remarkably was launching the national program for HHC by the Ministry Of Health (MOH) in 2008. The national HHC MOH program is mainly providing long-term care home care services for over 40,000 Saudi citizens. The scope of the HHC service program provided by the Saudi MOH is quite diverse, ranging from basic nursing care to specialized care programs, e.g., home peritoneal dialysis, home ventilation, home infusion therapy, etc. Objectives: The primary aim of our study is to report the prevalence of chronic conditions among Saudi people receiving long-term HHC services. Secondary aims include identifying the predictors of mortality among individuals receiving long-term HHC services and studying the association between frailty and poor health outcomes among HHC users. Methods: We conducted a retrospective and cross-sectional data collection from participants receiving HHC services at King Saud University Medical City, Riyadh, Saudi Arabia. Data were collected from electronic health records (EHR), patient charts, and interviewing caregivers from the year 2019 to 2022. We assessed functional performance by Katz's activity of daily living and the Bristol Activity of Daily Living Scale (BADLS). A trained health care provider assessed frailty using the Clinical Frailty Scale (CFS). Mortality was assessed by reviewing the death certificates if patients were hospitalized through discharge status ascertainment from EHR. Results: The mean age for deceased individuals in HHC was 78.3 years. Over twenty percent of individuals receiving HHC services were readmitted to the hospital. The following variables were statistically significant between deceased and alive individuals receiving HHC services; clinical frailty scale, the total number of comorbid conditions, and functional performance based on the KATZ activity of daily living scale and the BADLS. We found that the strongest predictors for mortality were pressure ulcers which had an odds ratio of 3.75 and p-value of < 0.0001, and the clinical frailty scale, which had an odds ratio of 1.69 and p-value of 0.002, using multivariate regression analysis. In conclusion, our study found that pressure ulcers and frailty are the strongest predictors of mortality for individuals receiving home health care services. Moreover, we found a high rate of annual readmission for individuals enrolled in HHC, which requires further analysis to understand the possible contributing factors for the increased rate of hospital readmission and develop strategies to address them. Future studies should focus on designing quality improvement projects aimed at improving the quality of life for individuals receiving HHC services, especially those who have pressure ulcers at the end of life.

Keywords: homecare, Saudi, prevalence, chronic

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Authors: Ozan Kahraman, Hao Feng

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Several models such as Weibull, Modified Gompertz, Biphasic linear, and Log-logistic models have been proposed in order to describe non-linear inactivation kinetics and used to fit non-linear inactivation data of several microorganisms for inactivation by heat, high pressure processing or pulsed electric field. First-order kinetic parameters (D-values and z-values) have often been used in order to identify microbial inactivation by non-thermal processing methods such as ultrasound. Most ultrasonic inactivation studies employed first-order kinetic parameters (D-values and z-values) in order to describe the reduction on microbial survival count. This study was conducted to analyze the E. coli O157:H7 inactivation data by using five microbial survival models (First-order, Weibull, Modified Gompertz, Biphasic linear and Log-logistic). First-order, Weibull, Modified Gompertz, Biphasic linear and Log-logistic kinetic models were used for fitting inactivation curves of Escherichia coli O157:H7. The residual sum of squares and the total sum of squares criteria were used to evaluate the models. The statistical indices of the kinetic models were used to fit inactivation data for E. coli O157:H7 by MTS at three temperatures (40, 50, and 60 0C) and three pressures (100, 200, and 300 kPa). Based on the statistical indices and visual observations, the Weibull and Biphasic models were best fitting of the data for MTS treatment as shown by high R2 values. The non-linear kinetic models, including the Modified Gompertz, First-order, and Log-logistic models did not provide any better fit to data from MTS compared the Weibull and Biphasic models. It was observed that the data found in this study did not follow the first-order kinetics. It is possibly because of the cells which are sensitive to ultrasound treatment were inactivated first, resulting in a fast inactivation period, while those resistant to ultrasound were killed slowly. The Weibull and biphasic models were found as more flexible in order to determine the survival curves of E. coli O157:H7 treated by MTS on apple-carrot juice.

Keywords: Weibull, Biphasic, MTS, kinetic models, E.coli O157:H7

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Authors: P. Wlodarczak, J. Soar, M. Ally

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The dramatic rise in the use of Social Media (SM) platforms such as Facebook and Twitter provide access to an unprecedented amount of user data. Users may post reviews on products and services they bought, write about their interests, share ideas or give their opinions and views on political issues. There is a growing interest in the analysis of SM data from organisations for detecting new trends, obtaining user opinions on their products and services or finding out about their online reputations. A recent research trend in SM analysis is making predictions based on sentiment analysis of SM. Often indicators of historic SM data are represented as time series and correlated with a variety of real world phenomena like the outcome of elections, the development of financial indicators, box office revenue and disease outbreaks. This paper examines the current state of research in the area of SM mining and predictive analysis and gives an overview of the analysis methods using opinion mining and machine learning techniques.

Keywords: social media, text mining, knowledge discovery, predictive analysis, machine learning

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Authors: Zahid Ullah, Atlas Khan

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In today's data-driven world, the role of mathematics in bridging the gap between theory and applications is becoming increasingly vital. This abstract highlights the significance of mathematics as a powerful tool for analyzing, interpreting, and extracting meaningful insights from vast amounts of data. By integrating mathematical principles with real-world applications, researchers can unlock the full potential of data-driven decision-making processes. This abstract delves into the various ways mathematics acts as a bridge connecting theoretical frameworks to practical applications. It explores the utilization of mathematical models, algorithms, and statistical techniques to uncover hidden patterns, trends, and correlations within complex datasets. Furthermore, it investigates the role of mathematics in enhancing predictive modeling, optimization, and risk assessment methodologies for improved decision-making in diverse fields such as finance, healthcare, engineering, and social sciences. The abstract also emphasizes the need for interdisciplinary collaboration between mathematicians, statisticians, computer scientists, and domain experts to tackle the challenges posed by the data-driven landscape. By fostering synergies between these disciplines, novel approaches can be developed to address complex problems and make data-driven insights accessible and actionable. Moreover, this abstract underscores the importance of robust mathematical foundations for ensuring the reliability and validity of data analysis. Rigorous mathematical frameworks not only provide a solid basis for understanding and interpreting results but also contribute to the development of innovative methodologies and techniques. In summary, this abstract advocates for the pivotal role of mathematics in bridging theory and applications in a data-driven world. By harnessing mathematical principles, researchers can unlock the transformative potential of data analysis, paving the way for evidence-based decision-making, optimized processes, and innovative solutions to the challenges of our rapidly evolving society.

Keywords: mathematics, bridging theory and applications, data-driven world, mathematical models

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Authors: James Patrick A. Diaz, Raul E. Ramboyong

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Background: Hypertensive response during maximal exercise test provides important information on the level of blood pressure control and evaluation of treatment. Method: A single center retrospective descriptive study was conducted among 117 young (aged 20 to 40) and middle age (aged 40 to 65) hypertensive patients, who underwent treadmill stress test. Currently on maintenance frontline medication either monotherapy (Angiotensin-converting enzyme inhibitor/Angiotensin receptor blocker [ACEi/ARB], Calcium channel blocker [CCB], Diuretic - Hydrochlorthiazide [HCTZ]) or combination therapy (ARB+CCB, ARB+HCTZ), who attained a maximal exercise on treadmill stress test (TMST) with hypertensive response (systolic blood pressure: male >210 mm Hg, female >190 mm Hg, diastolic blood pressure >100 mmHg, or increase of >10 mm Hg at any time during the test), on Bruce and Modified Bruce protocol. Exaggerated blood pressure response during exercise (systolic [SBP] and diastolic [DBP]), peak exercise blood pressure (SBP and DBP), recovery period (SBP and DBP) and test for ischemia and their antihypertensive medication/s were investigated. Analysis of variance and chi-square test were used for statistical analysis. Results: Hypertensive responses on maximal exercise test were seen mostly among female population (P < 0.000) and middle age (P < 0.000) patients. Exaggerated diastolic blood pressure responses were significantly lower in patients who were taking CCB (P < 0.004). A longer recovery period that showed a delayed decline in SBP was observed in patients taking ARB+HCTZ (P < 0.036). There were no significant differences in the level of exaggerated systolic blood pressure response and during peak exercise (both systolic and diastolic) in patients using either monotherapy or combination antihypertensives. Conclusion: Calcium channel blockers provided lower exaggerated diastolic BP response during maximal exercise test in hypertensive middle age patients. Patients on combination therapy using ARB+HCTZ exhibited a longer recovery period of systolic blood pressure.

Keywords: antihypertensive, exercise test, hypertension, hyperytensive response

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Authors: Iyad A. A. Abusahloub

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This research aimed to measure the level of perception and application of Integrated Talent Management according to IBM standards, by the upper and middle categories in Palestinian government institutions in Gaza, using a descriptive-analytical method. Using a questionnaire based on the standards of the IBM Institute for Business Value, the researcher added a second section to measure the perception of integrated talent management, the sample was 248 managers. The SPSS package was used for statistical analysis. The results showed that government institutions in Gaza apply Integrated Talent Management according to IBM standards at a medium degree did not exceed 59.8%, there is weakness in the perception of integrated talent management at the level of 53.6%, and there is a strong correlation between (Integrated Talent Management) and (the perception of the integrated talent management) amounted to 92.9%, and 88.9% of the change in the perception of the integrated talent management is by (motivate and develop, deploy and manage, connect and enable, and transform and sustain) talents, and 11.1% is by other factors. Conclusion: This study concluded that the integrated talent management model presented by IBM with its six dimensions is an effective model to reach your awareness and understanding of talent management, especially that it must rely on at least four basic dimensions out of the six dimensions: 1- Stimulating and developing talent. 2- Organizing and managing talent. 3- Connecting with talent and empowering it. 4- Succession and sustainability of talent. Therefore, this study recommends the adoption of the integrated talent management model provided by IBM to any organization across the world, regardless of its specialization or size, to reach talent sustainability.

Keywords: HR, talent, talent management, IBM

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Authors: Majid A. AlSayari

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The study reported here investigated social cognitive theory (SCT) in the context of Vocational Rehab (VR) for people with disabilities. The prime purpose was to increase knowledge of VR phenomena and make recommendations for improving VR services. The sample consisted of 242 persons with Spinal Cord Injuries (SCI) who completed questionnaires. A further 32 participants were Trainers. Analysis of questionnaire data was carried out using factor analysis, multiple regression analysis, and thematic analysis. The analysis suggested that, in motivational terms, and consistent with research carried out in other academic contexts, self-efficacy was the best predictor of VR performance. The author concludes that that VR self-efficacy predicted VR training performance.

Keywords: people with physical disabilities, social cognitive theory, self-efficacy, vocational training

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Authors: Ikumapayi Catherine Mayowa

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The well-being of humans on a construction site is critical; abundant manpower had been lost through accidents which kill or make workers physically unfit to carry out construction activities, these, in turn, have multiple effects on the whole economy. Thus, it is necessary to put all safety items and regulations in place before construction activities can commence. This study was carried out in the Ondo state of Nigeria to investigate and analyze the state of health and safety of construction workers in the state. The study was done using first-hand observations, 50 construction project sites were visited in ten major towns of Ondo state, questionnaires were distributed, and the results were analyzed. The result shows that construction workers are being exposed to many construction site hazards due to lack of inadequate safety programs and lack of appropriate safety equipment for workers on site. From the data gotten from each site visited and the statistical analysis, it can be concluded that occurrences of an accident on construction sites depend significantly on the available safety facilities on the sites. The result of the regression statistics shows that the dependence of the frequency of occurrence of an accident on the availability of safety items on the site is 0.0362 which is less than 0.05 maximum significant level allowed. Therefore, a vital way of sustaining our building strategy is given a detail attention to the provision of adequate health and safety items on construction sites which will reduce the occurrence of accident, loss of manpower and death of skilled workers.

Keywords: construction sites, health, safety, welfare

Procedia PDF Downloads 321

Authors: Fatin H. Mohamad, Jia H. Wong, Muhammad Bilal, Abdul A. Mohamed Yusoff, Jafri M. Abdullah, Jingli Zhang

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Kv1.4 is a Shaker-related member of voltage-gated potassium channel which can be associated with cardiac action potential but can also be found in Schaffer collateral and dentate gyrus. It has two inactivation mechanisms; the fast N-type and slow C-type. Kv1.4 produces rapid current inactivation. This A type potential of Kv1.4 makes it as a target in antiepileptic drugs (AEDs) selection. In this study, 4-hydroxybenzoic acid, which can be naturally found in bamboo shoots, were tested on its enhancement effect on potassium current of Kv1.4 channel expressed in Xenopus laevis oocytes using the two-microelectrode voltage clamp method. Current obtained were recorded and analyzed with pClamp software whereas statistical analysis were done by student t-test. The ratio of final / peak amplitude is an index of the activity of the Kv1.4 channel. The less the ratio, the greater the function of Kv1.4. The decrease of ratio of which by 1µM 4-hydroxybenzoic acid (n= 7), compared with 0.1% DMSO (vehicle), was mean= 47.62%, SE= 13.76%, P= 0.026 (statistically significant). It indicated more opening of Kv1.4 channels under 4-hydroxybenzoic acid. In conclusion, 4-hydroxybenzoic acid can enhance the function of Kv1.4 potassium channels, which is regarded as one of the mechanisms of antiepileptic treatment.

Keywords: antiepileptic, Kv1.4 potassium channel, two-microelectrode voltage clamp, Xenopus laevis oocytes, 4-hydroxybenzoic acid

Procedia PDF Downloads 357