Search results for: multivariate statistical analysis

Authors: Iman Farasat, Howard M. Salis

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The CRISPR/Cas9 system has revolutionized genome engineering by enabling site-directed and high-throughput genome editing, genome insertion, and gene knockdowns in several species, including bacteria, yeast, flies, worms, and human cell lines. This technology has the potential to enable human gene therapy to treat genetic diseases and cancer at the molecular level; however, the current CRISPR/Cas9 system suffers from seemingly sporadic off-target genome mutagenesis that prevents its use in gene therapy. A comprehensive mechanistic model that explains how the CRISPR/Cas9 functions would enable the rational design of the guide-RNAs responsible for target site selection while minimizing unexpected genome mutagenesis. Here, we present the first quantitative model of the CRISPR/Cas9 genome mutagenesis system that predicts how guide-RNA sequences (crRNAs) control target site selection and cleavage activity. We used statistical thermodynamics and law of mass action to develop a five-step biophysical model of cas9 cleavage, and examined it in vivo and in vitro. To predict a crRNA's binding specificities and cleavage rates, we then compiled a nearest neighbor (NN) energy model that accounts for all possible base pairings and mismatches between the crRNA and the possible genomic DNA sites. These calculations correctly predicted crRNA specificity across 5518 sites. Our analysis reveals that cas9 activity and specificity are anti-correlated, and, the trade-off between them is the determining factor in performing an RNA-mediated cleavage with minimal off-targets. To find an optimal solution, we first created a scheme of safe-design criteria for Cas9 target selection by systematic analysis of available high throughput measurements. We then used our biophysical model to determine the optimal Cas9 expression levels and timing that maximizes on-target cleavage and minimizes off-target activity. We successfully applied this approach in bacterial and mammalian cell lines to reduce off-target activity to near background mutagenesis level while maintaining high on-target cleavage rate.

Keywords: biophysical model, CRISPR, Cas9, genome editing

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Authors: Hyeondal Jeong, Yoonjung Baek

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This research examines the effects of positive psychological capital (or PsyCap) on employee’s outcomes (satisfaction, commitment, organizational citizenship behavior, innovation behavior and individual creativity). This study conducted a meta-analysis of articles published in the Republic of Korea. As a result, positive psychological capital has a positive effect on the behavior of employees. Heterogeneity was identified among the studies included in the analysis and the context factors were analyzed; the study proposes contextual factors such as team tenure. The moderating effect of team tenure was not statistically significant. The implications were discussed based on the analysis results.

Keywords: positive psychological capital , satisfaction, commitment, OCB, creativity, meta-analysis

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Authors: Ashit Syngle, Inderjit Verma, Pawan Krishan

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Objective: Endothelial progenitor cells (EPCs) have reparative potential in overcoming the endothelial dysfunction and reducing cardiovascular risk. EPC depletion has been demonstrated in the setting of established atherosclerotic diseases. With this background, we evaluated whether reduced EPCs population are associated with endothelial dysfunction, subclinical atherosclerosis and inflammatory markers in ankylosing spondylitis (AS) patients without any known traditional cardiovascular risk factor in AS patients. Methods: Levels of circulating EPCs (CD34+/CD133+), brachial artery flow-mediated dilatation, carotid intima-media thickness (CIMT) and inflammatory markers i.e erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), tissue necrosis factor (TNF)–α, interleukin (IL)-6, IL-1 were assessed in 30 AS patients (mean age33.41 ± 10.25; 11 female and 19 male) who fulfilled the modified New York diagnostic criteria with 25 healthy volunteers (mean age 29.36± 8.64; 9 female and 16 male) matched for age and sex. Results: EPCs (CD34+/CD133+) cells were significantly (0.020 ± 0.001% versus 0.040 ± 0.010%, p<0.001) reduced in patients with AS compared to healthy controls. Endothelial function (7.35 ± 2.54 versus 10.27 ±1.73, p=0.002), CIMT (0.63 ± 0.01 versus 0.35 ± 0.02, p < 0.001) and inflammatory markers were also significantly (p < 0.01) altered as compared to healthy controls. Specifically, CD34+CD133+cells were inversely multivariate correlated with CRP and TNF-α and endothelial dysfunction was positively correlated with reduced number of EPC. Conclusion: Depletion of EPCs population is an independent predictor of endothelial dysfunction and early atherosclerosis in AS patients and may provide additional information beyond conventional risk factors and inflammatory markers.

Keywords: endothelial progenitor cells, atherosclerosis, ankylosing spondylitis, cardiovascular

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Authors: Aizzat Md. Nasurdin, Noor Hazlina Ahmad, Cheng Ling Tan

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This study aims to examine the role of career advancement and job security as predictors of employee commitment to their organization. Data was collected from 580 frontline employees attached to two departments of 29 luxury hotels in Peninsular Malaysia. Statistical results using Partial Least Squares technique provided support for the proposed hypotheses. In view of the findings, theoretical and practical implications are discussed.

Keywords: organizational commitment, career advancement, job security, frontline employees, luxury hotels, Malaysia

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Authors: Marina Lazar Chandy, N. Kannan, Rajendra Patil, Vinod Mathew, Ajmal Mohamed, P. K. Sreeja, Renju Jose

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Introduction- Arecoline, a major constituent of arecanut has shown to have some effect on liver. The use of arecanut is found to be the most common etiological factor for the development of Oral Submucous fibrosis (O.S.M.F). The effect of arecanut usage on liver in patients with O.S.M.F needs to be assessed. Lipids play a role in structural maintenance of cell. Alterations of lipid profile were noted in cancer patients. O.S.M.F being a precancerous lesion can have some effect on the level of lipids in the body. Objectives: This study was done to assess the alterations in liver enzymes (Serum Glutamic Pyruvic Transaminase(S.G.P.T ,Serum Glutamic Oxaloacetic Transaminase(S.G.O.T)) and lipid metabolism (High Density Lipoprotien(H.D.L) and Apo Lipoprotien A1 (Apo A1)) in patients with O.S.M.F. Methods-130 patients were taken for the study,100 patients with O.S.M.F and 30 as control group without O.S.M.F. Fasting blood sugar levels were taken, centrifuged and analyzed for S.G.P.T,S.G.O.T, H.D.L and Apo A1 using semi automated spectrophotometer. Results: After statistical analysis, it was concluded that there is an elevation of levels of S.G.P.T, S.G.O.T, and decreased levels of H.D.L, Apo A1 for O.S.M.F group when compared with control group. With increased grade of O.S.M.F. and duration of habit, S.G.P.T. & S.G.O.T. increased whereas, H.D.L. & Apo A1 decreased. All the values were statistically significant at p<0.01.

Keywords: apolipoprotien A1, high density lipoprotien, oral submucous fibrosis, serum glutamic oxaloacetic transaminase

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Authors: Iveta Řepková

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The aim of this paper is to estimate the efficiency of the Slovak commercial banks employing the Data Envelopment Analysis (DEA) window analysis approach during the period 2003-2012. The research is based on unbalanced panel data of the Slovak commercial banks. Undesirable output was included into analysis of banking efficiency. It was found that most efficient banks were Postovabanka, UniCredit Bank and Istrobanka in CCR model and the most efficient banks were Slovenskasporitelna, Istrobanka and UniCredit Bank in BCC model. On contrary, the lowest efficient banks were found Privatbanka and CitiBank. We found that the largest banks in the Slovak banking market were lower efficient than medium-size and small banks. Results of the paper is that during the period 2003-2008 the average efficiency was increasing and then during the period 2010-2011 the average efficiency decreased as a result of financial crisis.

Keywords: data envelopment analysis, efficiency, Slovak banking sector, window analysis

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Authors: Ligia Florio, João Mauricio Castaldelli-Maia

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Background: Food addiction (FA) emerged in the 1990s as a possible contributor to the increasing prevalence of obesity and overweight, in conjunction with changing food environments and mental health conditions. However, FA is not yet listed as one of the disorders in the DSM-5 and/or the ICD-11. Although there are controversies and debates in the literature about the classification and construct of FA, the most common approach to access it is the use of a research tool - the Yale Food Addiction Scale (YFAS) - which approximates the concept of FA to the concept diagnosis of dependence on psychoactive substances. There is a need to explore the dimensional phenotypes accessed by YFAS in different population groups for a better understanding and scientific support of FA diagnoses. Methods: The primary objective of this project was to investigate the construct validity of the FA concept by mYFAS 2.0 in individuals who underwent bariatric surgery (n = 100) at the Hospital Estadual Mário Covas since 2011. Statistical analyzes were conducted using the STATA software. In this sense, structural or factor validity was the type of construct validity investigated using exploratory factor analysis (EFA) and item response theory (IRT) techniques. Results: EFA showed that the one-dimensional model was the most parsimonious. The IRT showed that all criteria contributed to the latent structure, presenting discrimination values greater than 0.5, with most presenting values greater than 2. Conclusion: This study reinforces a FA dimension in patients who underwent bariatric surgery. Within this dimension, we identified the most severe and discriminating criteria for the diagnosis of FA.

Keywords: obesity, food addiction, bariatric surgery, regain

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Authors: Dolly Gadhiya, Jayvadan Patel, Mihir Raval

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Lercanidipine hydrochloride is a calcium channel blockers used for treating angina pectoris and hypertension. Lercanidipine is a BCS Class II drug having poor aqueous solubility. Absolute bioavailability of Lercanidipine is very low and the main reason ascribed for this is poor aqueous solubility of the drug. Design and formulatation of nanocrystals by media milling method was main focus of this study. In this present study preliminary optimization was carried out with one factor at a time (OFAT) approach. For this different parameters like size of milling beads, amount of zirconium beads, types of stabilizer, concentrations of stabilizer, concentrations of drug, stirring speeds and milling time were optimized on the basis of particle size, polydispersity index and zeta potential. From the OFAT model different levels for above parameters selected for Plackett - Burman Design (PBD). Plackett-Burman design having 13 runs involving 6 independent variables was carried out at higher and lower level. Based on statistical analysis of PBD it was found that concentration of stabilizer, concentration of drug and stirring speed have significant impact on particle size, PDI, zeta potential value and saturation solubility. These experimental designs for preparation of nanocrystals were applied successfully which shows increase in aqueous solubility and dissolution rate of Lercanidipine hydrochloride.

Keywords: Lercanidipine hydrochloride, nanocrystals, OFAT, Plackett Burman

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Authors: Maria E. V. Amarante, Carolina L. Cerdeira, Julia V. Cortes, Fiorita G. L. Mundim

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Basal cell carcinoma (BCC) is the most prevalent type of skin cancer in humans. It arises from the basal cells of the epidermis and cutaneous appendages. The role of sunlight exposure as a risk factor for BCC is very well defined due to its power to influence genetic mutations, in addition to having a suppressor effect on the skin immune system. Despite showing low metastasis and mortality rates, the tumor is locally infiltrative, aggressive, and destructive. Considering the high prevalence rate of this carcinoma and the importance of early detection, a retrospective study was carried out in order to correlate the clinical data available on BBC, characterize it epidemiologically, and thus enable effective prevention measures for the population. Data on the period from January 2015 to December 2019 were collected from the medical records of patients registered at one pathology service located in the southeast region of Brazil, known as SVO, which delivers skin biopsy results. The study was aimed at correlating the variables, sex, age, and subtypes found. Data analysis was performed using the chi-square test at a nominal significance level of 5% in order to verify the independence between the variables of interest. Fisher's exact test was applied in cases where the absolute frequency in the cells of the contingency table was less than or equal to five. The statistical analysis was performed using the R® software. Ninety-three basal cell carcinoma were analyzed, and its frequency in the 31-to 45-year-old age group was 5.8 times higher in men than in women, whereas, from 46 to 59 years, the frequency was found 2.4 times higher in women than in men. Between the ages of 46 to 59 years, it should be noted that the sclerodermiform subtype appears more than the solid one, with a difference of 7.26 percentage points. Reversely, the solid form appears more frequently in individuals aged 60 years or more, with a difference of 8.57 percentage points. Among women, the frequency of the solid subtype was 9.93 percentage points higher than the sclerodermiform frequency. In males, the same percentage difference is observed, but sclerodermiform is the most prevalent subtype. It is concluded in this study that, in general, there is a predominance of basal cell carcinoma in females and in individuals aged 60 years and over, which demonstrates the tendency of this tumor. However, when rarely found in younger individuals, the male gender prevailed. The most prevalent subtype was the solid one. It is worth mentioning that the sclerodermiform subtype, which is more aggressive, was seen more frequently in males and in the 46-to 59-year-old range.

Keywords: basal cell carcinoma, epidemiology, sclerodermiform basal cell carcinoma, skin cancer, solar radiation, solid basal cell carcinoma

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Authors: L. Srikanth, D. Neelima Satyam

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The transmission line towers are one of the important life line structures in the distribution of power from the source to the various places for several purposes. The predominant external loads which act on these towers are wind and earthquake loads. In this present study tower is analyzed using Indian Standards IS: 875:1987 (Wind Load), IS: 802:1995 (Structural Steel), IS:1893:2002 (Earthquake) and dynamic analysis of tower has been performed considering ground motion of 2001 Bhuj Earthquake (India). The dynamic analysis was performed considering a tower system consisting two towers spaced 800m apart and 35m height each. This analysis has been performed using numerical time stepping finite difference method which is central difference method were employed by a developed MATLAB program to get the normalized ground motion parameters includes acceleration, frequency, velocity which are important in designing the tower. The tower is analyzed using response spectrum analysis.

Keywords: response spectra, dynamic analysis, central difference method, transmission tower

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Authors: Usama Shahid, Muhammad Zunnurain Hussain

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This research paper presents a comprehensive analysis of a sentiment analysis approach that employs valence and arousal as its foundational pillars, in comparison to traditional techniques. Sentiment analysis is an indispensable task in natural language processing that involves the extraction of opinions and emotions from textual data. The valence and arousal dimensions, representing the intensity and positivity/negativity of emotions, respectively, enable the creation of four quadrants, each representing a specific emotional state. The study seeks to determine the impact of utilizing these quadrants to identify distinct emotional states on the accuracy and efficiency of sentiment analysis, in comparison to traditional techniques. The results reveal that the valence and arousal-based approach outperforms other approaches, particularly in identifying nuanced emotions that may be missed by conventional methods. The study's findings are crucial for applications such as social media monitoring and market research, where the accurate classification of emotions and opinions is paramount. Overall, this research highlights the potential of using valence and arousal as a framework for sentiment analysis and offers invaluable insights into the benefits of incorporating specific types of emotions into the analysis. These findings have significant implications for researchers and practitioners in the field of natural language processing, as they provide a basis for the development of more accurate and effective sentiment analysis tools.

Keywords: sentiment analysis, valence and arousal, emotional states, natural language processing, machine learning, text analysis, sentiment classification, opinion mining

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Authors: Svenja Pieritz, Jakab Pilaszanovich

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Collaborative Problem Solving (CPS) is recognized as being one of the most important skills of the 21st century with having a potential impact on education, job selection, and collaborative systems design. Therefore, CPS has been adopted in several standardized tests, including the Programme for International Student Assessment (PISA) in 2015. A significant challenge of evaluating CPS is the underlying interplay of cognitive and social skills, which requires a more holistic assessment. However, the majority of the existing tests are using a questionnaire-based assessment, which oversimplifies this interplay and undermines ecological validity. Two major difficulties were identified: Firstly, the creation of a controllable, real-time environment allowing natural behaviors and communication between at least two people. Secondly, the development of an appropriate method to collect and synthesize both cognitive and social metrics of collaboration. This paper proposes a more holistic and automated approach to the assessment of CPS. To address these two difficulties, a multiplayer problem-solving game called Sea of Light was developed: An environment allowing students to deploy a variety of measurable collaborative strategies. This controlled environment enables researchers to monitor behavior through the analysis of game actions and chat. The according solution for the statistical model is a combined approach of Natural Language Processing (NLP) and Bayesian network analysis. Social exchanges via the in-game chat are analyzed through NLP and fed into the Bayesian network along with other game actions. This Bayesian network synthesizes evidence to track and update different subdimensions of CPS. Major findings focus on the correlations between the evidences collected through in- game actions, the participants’ chat features and the CPS self- evaluation metrics. These results give an indication of which game mechanics can best describe CPS evaluation. Overall, Sea of Light gives test administrators control over different problem-solving scenarios and difficulties while keeping the student engaged. It enables a more complete assessment based on complex, socio-cognitive information on actions and communication. This tool permits further investigations of the effects of group constellations and personality in collaborative problem-solving.

Keywords: bayesian network, collaborative problem solving, game-based assessment, natural language processing

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Authors: H. Z. Ulukan, E. Demircioğlu, M. Erol Genevois

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The scope of this paper and the aim of proposed model were to apply monetary Input –Output (I-O) analysis to point out the importance of reusing know-how and other requirements in order to reduce the production costs in a manufacturing process for a laptop computer. I-O approach using the monetary input-output model is employed to demonstrate the impacts of different factors in a manufacturing process. A sensitivity analysis showing the correlation between these different factors is also presented. It is expected that the recommended model would have an advantageous effect in the cost minimization process.

Keywords: input-output analysis, monetary input-output model, manufacturing process, laptop computer

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Authors: Friday Godwin Okibe, Elaoyi David Paul, Oladayo Thomas Ojekunle

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In this study, Nitrogen and Phosphorous co-doped Zinc Oxide (NPZ) was prepared through a solvent-free reaction. The NPZ was characterized by Scanning Electron Microscopy (SEM) and Fourier Transform Infrared (FTIR) spectroscopy. The photocatalytic activity of the catalyst was investigated by monitoring the degradation of para-nitrophenol (PNP) under visible light irradiation and the process was optimized using factorial design of experiment. The factors investigated were initial concentration of para-nitrophenol, catalyst loading, pH and irradiation time. The characterization results revealed a successful doping of ZnO by nitrogen and phosphorus and an improvement in the surface morphology of the catalyst. The photo-catalyst exhibited improved photocatalytic activity under visible light by 73.8%. The statistical analysis of the optimization result showed that the model terms were significant at 95% confidence level. Interactions plots revealed that irradiation time was the most significant factor affecting the degradation process. The cube plots of the interactions of the variables showed that an optimum degradation efficiency of 66.9% was achieved at 10mg/L initial PNP concentration, 0.5g catalyst loading, pH 7 and 150 minutes irradiation time.

Keywords: nitrogen and phosphorous co-doped Zno, p-nitrophenol, photocatalytic degradation, optimization, factorial design of experimental

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Authors: Jingjie Li, Wenjie Hu

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Phraseological units in academic English texts have been a central focus in recent corpus linguistic research. A wide variety of phraseological units have been explored, including collocations, chunks, lexical bundles, patterns, semantic sequences, etc. This paper describes a special category of clause-level phraseological units, namely, Characteristic Sentence Stems (CSSs), with a view to describing their defining criteria and extraction method. CSSs are contiguous lexico-grammatical sequences which contain a subject-predicate structure and which are frame expressions characteristic of academic writing. The extraction of CSSs consists of six steps: Part-of-speech tagging, n-gram segmentation, structure identification, significance of occurrence calculation, text range calculation, and overlapping sequence reduction. Significance of occurrence calculation is the crux of this study. It includes the computing of both the internal association and the boundary independence of a CSS and tests the occurring significance of the CSS from both inside and outside perspectives. A new normalization algorithm is also introduced into the calculation of LocalMaxs for reducing overlapping sequences. It is argued that many sentence stems are so recurrent in academic texts that the most typical of them have become the habitual ways of making meaning in academic writing. Therefore, studies of CSSs could have potential implications and reference value for academic discourse analysis, English for Academic Purposes (EAP) teaching and writing.

Keywords: characteristic sentence stem, extraction method, phraseological unit, the statistical measure

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Authors: Wanvipa Thongborisute, Punyaphat Sirithanabadeekul, Pichit Suvanprakorn, Anan Jiraviroon

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Background: Acne vulgaris is one of the most common dermatologic problems, and can have a significant psychological and physical effect on patients. Propionibacterium acnes' roles in acne vulgaris involve the activation of toll-like receptor 4 (TLR4), and toll-like receptor 2 (TLR2) pathways. By activating these pathways, inflammatory events of acne lesions, comedogenesis and sebaceous lipogenesis can occur. Currently, there are several topical agents commonly use in treating acne vulgaris that are known to have an effect on TLRs, such as retinoic acid and adapalene, but these drugs still have some irritating effects. At present, there is an alarming increase in rate of bacterial resistance due to irrational used of antibiotics both orally and topically. For this reason, acne treatments should contain bioactive molecules targeting at the site of action for the most effective therapeutic effect with the least side effects. Sparganium stoloniferumis a Chinese aquatic herb containing a compound called Sparstolonin B (SsnB), which has been reported to selectively blocks Toll-like receptor 2 (TLR2) and Toll-like receptor 4 (TLR4)-mediated inflammatory signals. Therefore, this topical TLR2 and TLR4 antagonist, in a form of Sparganium stoloniferum-derived compound containing SsnB, should give a benefit in reducing inflammation of acne vulgaris lesions and providing an alternative treatments for patients with this condition. Materials and Methods: The objectives of this randomized double blinded split faced placebo controlled trial is to study the safety and efficacy of the Sparganium stoloniferum-derived compound. 32 volunteered patients with mild to moderate degree of acne vulgaris according to global acne grading system were included in the study. After being informed and consented the subjects were given 2 topical treatments for acne vulgaris, one being topical 2.40% Sparganium stoloniferum extraction (containing Sparstolonin B) and the other, placebo. The subjects were asked to apply each treatment to either half of the face daily morning and night by randomization for 8 weeks, and come in for a weekly follow up. For each visit, the patients went through a procedure of lesion counting, including comedones, papules, nodules, pustules, and cystic lesions. Results: During 8 weeks of experimentation, the result shows a reduction in total lesions number between the placebo and the treatment side show statistical significance starting at week 4, where the 95% confidence interval begin to no longer overlap, and shows a trend of continuing to be further apart. The decrease in the amount of total lesions between week 0 and week 8 of the placebo side shows no statistical significant at P value >0.05. While the decrease in the amount of total lesions of acne vulgaris of the treatment side comparing between week 0 and week 8 shows statistical significant at P value <0.001. Conclusion: The data demonstrates that 2.40% Sparganium stoloniferum extraction (containing Sparstolonin B) is more effective in treating acne vulgaris comparing to topical placebo in treating acne vulgaris, by showing significant reduction in the total numbers of acne lesions. Therefore, this topical Sparganium stoloniferum extraction could become a potential alternative treatment for acne vulgaris.

Keywords: acne vulgaris, sparganium stoloniferum, sparstolonin B, toll-like receptor 2, toll-like receptor 4

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Authors: Araceli Martínez Ortiz

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An educational research effort is analyzed using systems theory to document the power of collective impact when addressing multiple factors contributing towards the retention of students majoring in science, technology, engineering and mathematics (STEM) academic programs. This research promotes understanding on how networked communities may work effectively toward a shared vision and mutually aligned activities that result in sustained, large scale change. The actions of a team of researchers in their third year of collaboration are presented to describe a model that positively aligns work efforts resulting in greater total gains. The goals of the multiple programs managed by the funded program team are to: 1) expand the number of students who choose to study a STEM field of study; 2) promote student collaborative learning; 3) support faculty understanding of the funds of knowledge of diverse students and 4) establish innovative and robust STEM education research that will lead to the development of nationally replicable, scalable models for broadening participation in STEM. The impacts of this research effort are measured through quantitative statistical analysis of the changes in second-year STEM undergraduate student retention rates and representation rates of women, Hispanics and African American STEM majors.

Keywords: collaborative impact, diversity, student retention, systems theory, STEM education

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Authors: Mohammad Muntasir Maruf, Muhammad Zillur Rahman Khan, Nasim Jahan, Md. Waziul Alam Chowdhury, Satparkash, Md. Nozrul Islam

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Background: Substance use disorders have become a major public health problem in Bangladesh. Objectives: The present study was designed to assess the pattern of substance use and factors related to it among the hospitalized patients. Methods: This was a cross-sectional study. All the patients who were admitted in a private drug de-addiction clinic in the capital city (Dhaka) of Bangladesh during 1 July-31 December, 2013 and diagnosed as a case of substance use disorder by applying Structured Clinical Interview for DSM- Clinician Version were enrolled in the study. Data were collected through face to face interview by a semi-structured questionnaire and the information was complemented by the case-notes. Study subjects were 105 in number. Data analysis was performed using Statistical Package for Social Sciences (SPSS). Results: Most (90.5%) of the respondents were male. The mean age of the respondents was 28.8 (± 8.0) years. Majority (91.4%) were poly-substance users. Most (27.6%) respondents used 3 types of substances. Smoking or inhalation was the route used by most (90.5%) respondents. More than three-fourth (81%) of the respondents used nicotine. Among the other substances, majority (79%) used opiates group, followed by cannabinoids group (55.2%) and alcohol (41%). Curiosity, peer pressure and to have enjoyment or fun were identified as the common reasons for initiating substance use. Conclusions: A high proportion of poly-substance use was found. The study findings would help in management and prevention strategy of substance use in Bangladesh.

Keywords: Bangladesh, de-addiction clinic, poly-substance users, substance use disorder

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Authors: Amine Ganibardi, Cherif Arab Ali

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This paper addresses the data cleaning issue as a part of web usage data preprocessing within the scope of Web Usage Mining. Weblog data recorded by web servers within log files reflect usage activity, i.e., End-users’ clicks and underlying user-agents’ hits. As Web Usage Mining is interested in End-users’ behavior, user-agents’ hits are referred to as noise to be cleaned-off before mining. Filtering hits from clicks is not trivial for two reasons, i.e., a server records requests interlaced in sequential order regardless of their source or type, website resources may be set up as requestable interchangeably by end-users and user-agents. The current methods are content-centric based on filtering heuristics of relevant/irrelevant items in terms of some cleaning attributes, i.e., website’s resources filetype extensions, website’s resources pointed by hyperlinks/URIs, http methods, user-agents, etc. These methods need exhaustive extra-weblog data and prior knowledge on the relevant and/or irrelevant items to be assumed as clicks or hits within the filtering heuristics. Such methods are not appropriate for dynamic/responsive Web for three reasons, i.e., resources may be set up to as clickable by end-users regardless of their type, website’s resources are indexed by frame names without filetype extensions, web contents are generated and cancelled differently from an end-user to another. In order to overcome these constraints, a clustering-based cleaning method centered on the logging structure is proposed. This method focuses on the statistical properties of the logging structure at the requested and referring resources attributes levels. It is insensitive to logging content and does not need extra-weblog data. The used statistical property takes on the structure of the generated logging feature by webpage requests in terms of clicks and hits. Since a webpage consists of its single URI and several components, these feature results in a single click to multiple hits ratio in terms of the requested and referring resources. Thus, the clustering-based method is meant to identify two clusters based on the application of the appropriate distance to the frequency matrix of the requested and referring resources levels. As the ratio clicks to hits is single to multiple, the clicks’ cluster is the smallest one in requests number. Hierarchical Agglomerative Clustering based on a pairwise distance (Gower) and average linkage has been applied to four logfiles of dynamic/responsive websites whose click to hits ratio range from 1/2 to 1/15. The optimal clustering set on the basis of average linkage and maximum inter-cluster inertia results always in two clusters. The evaluation of the smallest cluster referred to as clicks cluster under the terms of confusion matrix indicators results in 97% of true positive rate. The content-centric cleaning methods, i.e., conventional and advanced cleaning, resulted in a lower rate 91%. Thus, the proposed clustering-based cleaning outperforms the content-centric methods within dynamic and responsive web design without the need of any extra-weblog. Such an improvement in cleaning quality is likely to refine dependent analysis.

Keywords: clustering approach, data cleaning, data preprocessing, weblog data, web usage data

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Authors: Yin-Yee Leong, Jack C. Yue, Hsin-Chung Wang

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Human longevity has been experiencing its largest increase since the end of World War II, and modeling the mortality rates is therefore often the focus of many studies. Among all mortality models, the Lee–Carter model is the most popular approach since it is fairly easy to use and has good accuracy in predicting mortality rates (e.g., for Japan and the USA). However, empirical studies from several countries have shown that the age parameters of the Lee–Carter model are not constant in time. Many modifications of the Lee–Carter model have been proposed to deal with this problem, including adding an extra cohort effect and adding another period effect. In this study, we propose a spatial modification and use clusters to explain why the age parameters of the Lee–Carter model are not constant. In spatial analysis, clusters are areas with unusually high or low mortality rates than their neighbors, where the “location” of mortality rates is measured by age and time, that is, a 2-dimensional coordinate. We use a popular cluster detection method—Spatial scan statistics, a local statistical test based on the likelihood ratio test to evaluate where there are locations with mortality rates that cannot be described well by the Lee–Carter model. We first use computer simulation to demonstrate that the cluster effect is a possible source causing the problem of the age parameters not being constant. Next, we show that adding the cluster effect can solve the non-constant problem. We also apply the proposed approach to mortality data from Japan, France, the USA, and Taiwan. The empirical results show that our approach has better-fitting results and smaller mean absolute percentage errors than the Lee–Carter model.

Keywords: mortality improvement, Lee–Carter model, spatial statistics, cluster detection

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Authors: Hanan H. ALQahtani, Karen Jones

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Catching a ball during sitting is a functional exercise commonly used in rehabilitation to enhance trunk muscle activity. To progress this exercise, physiotherapists incorporate a Swiss ball or change seat height. However, no study has assessed the effect of different seating surfaces on trunk muscle activity while catching a ball. Objective: To investigate the effect of catching a ball during sitting on a Swiss ball, a low seat and a high seat on trunk muscle activity. Method: A repeated-measures, counterbalanced design was used. A total of 26 healthy participants (15 female and 11 male) performed three repetitions of catching a ball on each seating surface. Using surface electromyography (sEMG), the activity of the bilateral transversus abdominis/internal oblique (TrA/IO), rectus abdominis (RA), erector spinae (ES) and lumbar multifidus (MF) was recorded. Trunk muscle activity was normalized using maximum voluntary isometric contraction and analyzed. Statistical significance was set at p ≤ .05. Results: No significant differences were observed in the activity of RA, TrA/IO, ES or MF between a low seat and a Swiss ball. However, the activity of the right and left ES on a low seat was significantly greater than on a high seat (p = .017 and p = .017, respectively). Conversely, the activity of the right and left RA on a high seat was significantly greater than on a low seat (p = .007 and p = .004, respectively). Conclusion: This study suggests that replacing a low seat with a Swiss ball while catching a ball is insufficient to increase trunk muscle activity, whereas changing the seat height could induce different trunk muscle activities. However, research conducted on patients is needed before translating these results into clinical settings.

Keywords: catching, electromyography, seating, trunk

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Authors: Frank Fan

Abstract:

PharmD (Doctor of Pharmacy) education has confronted an increasing challenge — curricular overload, a phenomenon resulting from the expansion of curricular requirements, as PharmD education strives to produce graduates who are practice-ready. The aftermath of the global pandemic has amplified the need for healthcare professionals, leading to a growing trend of assigning more responsibilities to them to address the global healthcare shortage. For instance, the pharmacist’s role has expanded to include not only compounding and distributing medication but also providing clinical services, including minor ailments management, patient counselling and vaccination. Consequently, PharmD programs have responded by continually expanding their curricula adding more requirements. While these changes aim to enhance the education and training of future professionals, they have also led to unintended consequences, including curricular overload, student burnout, and a potential decrease in program quality. To address the issue and ensure program quality, there is a growing need for evidence-based curriculum reforms. My research seeks to integrate Cognitive Load Theory, emerging machine learning algorithms within artificial intelligence (AI), and statistical approaches to develop a quantitative framework for optimizing curriculum design within the PharmD program at the University of Toronto, the largest PharmD program within Canada, to provide quantification and measurement of issues that currently are only discussed in terms of anecdote rather than data. This research will serve as a guide for curriculum planners, administrators, and educators, aiding in the comprehension of how the pharmacy degree program compares to others within and beyond the field of pharmacy. It will also shed light on opportunities to reduce the curricular load while maintaining its quality and rigor. Given that pharmacists constitute the third-largest healthcare workforce, their education shares similarities and challenges with other health education programs. Therefore, my evidence-based, data-driven curriculum analysis framework holds significant potential for training programs in other healthcare professions, including medicine, nursing, and physiotherapy.

Keywords: curriculum, curriculum analysis, health professions education, reflective writing, machine learning

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Authors: Mojtaba Aghajari, Alireza Aghasi

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The first challenge which the current research faced has been the identification or determination of the level of knowledge in Isfahan public transportation corporation, and the second challenge has been the recognition and choice of a proper approach for the instructional system design. Responding these two challenges will present an appropriate model of instructional system design. In order to respond the first challenge or question, Nonaka and Takeuchi KM model has been utilized due to its universality among the 26 models proposed so far. The statistical population of this research included 2200 people, among which 200 persons were chosen as the sample of the research by the use of Morgan’s method. The data gathering has been carried out by the means of a questionnaire based on Nonaka and Takeuchi KM model, analysis of which has been done by SPSS program. The output of this questionnaire, yielding the point of 1.96 (out of 5 points), revealed that the general condition of Isfahan public transportation corporation is weak concerning its being knowledge-centered. After placing this output on Jonassen’s continuum, it was revealed that the appropriate approach for instructional system design is the system (or behavioral) approach. Accordingly, different steps of the general model of ADDIE, which covers all of the ISO10015 standards, were adopted in the act of designing. Such process in Isfahan public transportation corporation was designed and divided into three main steps, including: instructional designing and planning, instructional course planning, determination of the evaluation and the effectiveness of the instructional courses.

Keywords: instructional system design, system approach, knowledge management, employees

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Authors: Simone Leonardi, Luca Ardito

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Micro-influencers are effective elements in the marketing strategies of companies and institutions because of their capability to create an hyper-engaged audience around a specific topic of interest. In recent years, many scientific approaches and commercial tools have handled the task of detecting this type of social media users. These strategies adopt solutions ranging from rule based machine learning models to deep neural networks and graph analysis on text, images, and account information. This work compares the existing solutions and proposes an ensemble method to generalize them with different input data and social media platforms. The deployed solution combines deep learning models on unstructured data with statistical machine learning models on structured data. We retrieve both social media accounts information and multimedia posts on Twitter and Instagram. These data are mapped into feature vectors for an eXtreme Gradient Boosting (XGBoost) classifier. Sixty different topics have been analyzed to build a rule based gold standard dataset and to compare the performances of our approach against baseline classifiers. We prove the effectiveness of our work by comparing the accuracy, precision, recall, and f1 score of our model with different configurations and architectures. We obtained an accuracy of 0.91 with our best performing model.

Keywords: deep learning, gradient boosting, image processing, micro-influencers, NLP, social media

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Authors: Keiwoma Mark Yila, Mathew Lamrana Siaffa Gboku, Mohamed Sahr Lebbie, Lamin Ibrahim Kamara

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Rainfall and temperature are the important variables which are often used to trace climate variability and change. A perception study and analysis of climatic data were conducted to assess the changes in rainfall and temperature and their impact on crop production in Moyamba district, Sierra Leone. For the perception study, 400 farmers were randomly selected from farmer-based organizations (FBOs) in 4 chiefdoms, and 30 agricultural extension workers (AWEs) in the Moyamba district were purposely selected as respondents. Descriptive statistics and Kendall’s test of concordance was used to analyze the data collected from the farmers and AEWs. Data for the analysis of variability and trends of rainfall and temperature from 1991 to 2020 were obtained from the Sierra Leone Meteorological Agency and Njala University and grouped into monthly, seasonal and annual time series. Regression analysis was used to determine the statistical values and trend lines for the seasonal and annual time series data. The Mann-Kendall test and Sen’s Slope Estimator were used to analyze the trends' significance and magnitude, respectively. The results of both studies show evidence of climate change in the Moyamba district. A substantial number of farmers and AEWs perceived a decrease in the annual rainfall amount, length of the rainy season, a late start and end of the rainy season, an increase in the temperature during the day and night, and a shortened harmattan period over the last 30 years. Analysis of the meteorological data shows evidence of variability in the seasonal and annual distribution of rainfall and temperature, a decreasing and non-significant trend in the rainy season and annual rainfall, and an increasing and significant trend in seasonal and annual temperature from 1991 to 2020. However, the observed changes in rainfall and temperature by the farmers and AEWs partially agree with the results of the analyzed meteorological data. The majority of the farmers perceived that; adverse weather conditions have negatively affected crop production in the district. Droughts, high temperatures, and irregular rainfall are the three major adverse weather events that farmers perceived to have contributed to a substantial loss in the yields of the major crops cultivated in the district. In response to the negative effects of adverse weather events, a substantial number of farmers take no action due to their lack of knowledge and technical or financial capacity to implement climate-sensitive agricultural (CSA) practices. Even though few farmers are practising some CSA practices in their farms, there is an urgent need to build the capacity of farmers and AEWs to adapt to and mitigate the negative impacts of climate change. The most priority support needed by farmers is the provision of climate-resilient crop varieties, whilst the AEWs need training on CSA practices.

Keywords: climate change, crop productivity, farmer’s perception, rainfall, temperature, Sierra Leone

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Authors: M. Jalali Azizpour

Abstract:

In this paper, the effect of WC-12Co particle Temperature in HVOF thermal spraying process on the coating thickness has been studied. The statistical results show that the spray distance and oxygen-to-fuel ratio are more effective factors on particle characterization and thickness of HVOF thermal spraying coatings. Spray Watch diagnostic system, scanning electron microscopy (SEM), X-ray diffraction and thickness measuring system were used for this purpose.

Keywords: HVOF, temperature thickness, velocity, WC-12Co

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Authors: N. A. Ismail, Abdul Arif, Sharul Hafiz, Lu S. J., Tham W. S., Wong S. K.

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This paper investigates the visulization of Malaysia universities websites. Twenty (20) public universities websites in Malaysia has been chosen as samples to explore and visualize the link relationship between their academic websites using social network analysis methods such as inlink, degree, weight, betweenness and modularity class. All of the connection and relation demonstrate the power to influence, comprehensive strength and also the variety of subject types that are present in universities. The experimental results also show that University Malaysia Sabah (UMS) is the biggest back links provider.

Keywords: academic websites, link analysis, social network analysis, experimental result

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Authors: Riaan Kleyn

Abstract:

Mass wine production companies across the globe are provided with grapes from winegrowers that predominantly utilize mechanical harvesting machines to harvest wine grapes. Mechanical harvesting accelerates the rate at which grapes are harvested, allowing grapes to be delivered faster to meet the demands of wine cellars. The disadvantage of the mechanical harvesting method is the inclusion of material-other-than-grapes (MOG) in the harvested wine grape loads arriving at the cellar which degrades the quality of wine that can be produced. Currently, wine cellars do not have a method to determine the amount of MOG present within wine grape loads. This paper seeks to find an optimal computer vision method capable of detecting the amount of MOG within a wine grape load. A MOG detection method will encourage winegrowers to deliver MOG-free wine grape loads to avoid penalties which will indirectly enhance the quality of the wine to be produced. Traditional image segmentation methods were compared to deep learning segmentation methods based on images of wine grape loads that were captured at a wine cellar. The Mask R-CNN model with a ResNet-50 convolutional neural network backbone emerged as the optimal method for this study to determine the amount of MOG in an image of a wine grape load. Furthermore, a statistical analysis was conducted to determine how the MOG on the surface of a grape load relates to the mass of MOG within the corresponding grape load.

Keywords: computer vision, wine grapes, machine learning, machine harvested grapes

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Authors: Augustine Ndudi Egere, Shehu Adamu, Esther Ishaya Solomon

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As internet accessibility and smartphones continue to increase in Nigeria, Africa’s most populous country, social media platforms have become ubiquitous, causing students of 18-25 age brackets to spend more time on social media. The research investigated the impact of prolonged social media use on the physical health of students, with a specific focus on computer vision syndrome, hand pain, headaches and mental status. The study adopted a mixed-methods approach combining quantitative surveys to gather statistical data on usage patterns and symptoms, along with qualitative interviews into the experiences and perceptions of medical practitioners concerning cases under study within the geopolitical region. The result was analyzed using Regression analysis. It was observed that there is a significant correlation between social media usage by the students in the study age bracket concerning computer vision syndrome, hand pain, headache and general mental status. The research concluded by providing valuable insights into potential interventions and strategies to mitigate the adverse effects of excessive social media use on student well-being and recommends, among others, that educational institutions, parents, and students themselves collaborate to implement strategies aimed at promoting responsible and balanced use of social media.

Keywords: social media, student health, computer vision syndrome, hand pain, headaches, mental staus

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Authors: Mevlüt Burak Dalmış, Kemal Yaman

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In this study, flutter characteristics of cantilever rectangular plate structure under incompressible flow regime are investigated by comparing the results of commercial flutter analysis program ZAERO^© with wind tunnel tests conducted in Ankara Wind Tunnel (ART). A rectangular polycarbonate (PC) plate, 5x125x1000 mm in dimensions, is used for both numerical and experimental investigations. Analysis and test results are very compatible with each other. A comparison between two different solution methods (g and k-method) of ZAERO^© is also done. It is seen that, k-method gives closer result than the other one. However, g-method results are on conservative side and it is better to use conservative results namely g-method results. Even if the modal analysis results are used for the flutter analysis for this simple structure, a modal test should be conducted in order to validate the modal analysis results to have accurate flutter analysis results for more complicated structures.

Keywords: flutter, plate, subsonic flow, wind tunnel

Procedia PDF Downloads 515