Search results for: statistical arbitrage

Authors: I. Dangeard, S. Meineri, M. Dupré

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large body of research on energy consumption reveals that regular information on energy consumption produces a positive effect on behavior. The present research aims to test this feedback paradigm on waste management. A small-scale experiment on residual household waste was performed in a large french urban area, in partnership with local authorities, as part of the development of larger-scale project. A two-step door-to-door recruitment scheme led to 85 households answering a questionnaire. Among them, 54 accepted to participate in a study on waste (second step). Participants were then randomly assigned to one of the 3 experimental conditions : self-reported feedback on curbside waste, external feedback on waste weight based on information technologies, and no feedback for the control group. An additional control group was added, including households who were not requested to answer the questionnaire. Household residual waste was collected every week, and tags on curbside bins fed a database with waste weight of households. The feedback period lasted 14 weeks (february-may 2014). Quantitative data on waste weight were analysed, including these 14 weeks and the 7 previous weeks. Households were then contacted by phone in order to confirm the quantitative results. Regarding the recruitment questionnaire, results revealed high pro-environmental attitude on the NEP scale, high recycling behavior level and moderate level of source reduction behavior on the adapted 3R scale, but no statistical difference between the 3 experimental groups. Regarding the feedback manipulation paradigm, waste weight reveals important differences between households, but doesn't prove any statistical difference between the experimental conditions. Qualitative phone interviews confirm that recycling is a current practice among participants, whereas source reduction of waste is not, and mainly appears as a producer problem of packaging limitation. We conclude that triggering waste prevention behaviors among recycling households involves long-term feedback and should promote benchmarking, in order to clearly set waste reduction as an objective to be managed through feedback figures.

Keywords: eco-feedback, household waste, waste reduction, experimental research

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Authors: Desalegn Feyissa Desu

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Drug therapy problem is a significant challenge to provide high quality health care service for the patients. It is associated with morbidity, mortality, increased hospital stay, and reduced quality of life. Moreover, pediatric patients are quite susceptible to drug therapy problems. Thus this study aimed to assess drug therapy problem and its contributing factors among pediatric patients diagnosed with infectious disease admitted to pediatric ward of Jimma university medical center, from April 1 to June 30, 2018. Prospective observational study was conducted among pediatric patients with infectious disease admitted from April 01 to June 30, 2018. Drug therapy problems were identified by using Cipolle’s and strand’s drug related problem classification method. Patient’s written informed consent was obtained after explaining the purpose of the study. Patient’s specific data were collected using structured questionnaire. Data were entered into Epi data version 4.0.2 and then exported to statistical software package version 21.0 for analysis. To identify predictors of drug therapy problems occurrence, multiple stepwise backward logistic regression analysis was done. The 95% CI was used to show the accuracy of data analysis and statistical significance was considered at p-value < 0.05. A total of 304 pediatric patients were included in the study. Of these, 226(74.3%) patients had at least one drug therapy problem during their hospital stay. A total of 356 drug therapy problems were identified among two hundred twenty six patients. Non-compliance (28.65%) and dose too low (27.53%) were the most common type of drug related problems while disease comorbidity [AOR=3.39, 95% CI= (1.89-6.08)], Polypharmacy [AOR=3.16, 95% CI= (1.61-6.20)] and more than six days stay in hospital [AOR=3.37, 95% CI= (1.71-6.64) were independent predictors of drug therapy problem occurrence. Drug therapy problems were common in pediatric patients with infectious disease in the study area. Presence of comorbidity, polypharmacy and prolonged hospital stay were the predictors of drug therapy problem in study area. Therefore, to overcome the significant gaps in pediatric pharmaceutical care, clinical pharmacists, Pediatricians, and other health care professionals have to work in collaboration.

Keywords: drug therapy problem, pediatric, infectious disease, Ethiopia

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Authors: C. Soffritti, A. Fortini, E. Baroni, M. Merlin, G. L. Garagnani

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Aluminum alloys are widely used in many engineering applications due to their advantages such ashigh electrical and thermal conductivities, low density, high strength to weight ratio, and good corrosion resistance. However, their low hardness and poor tribological properties still limit their use in industrial fields requiring sliding contacts. Hard anodizing is one of the most common solution for overcoming issues concerning the insufficient friction resistance of aluminum alloys. In this work, the tribological behavior ofhard-anodized AW-4006 aluminum alloys in dry and lubricated conditions was evaluated. Three different hard-anodizing treatments were selected: a conventional one (HA) and two innovative golden hard-anodizing treatments (named G and GP, respectively), which involve the sealing of the porosity of anodic aluminum oxides (AAO) with silver ions at different temperatures. Before wear tests, all AAO layers were characterized by scanning electron microscopy (VPSEM/EDS), X-ray diffractometry, roughness (Ra and Rz), microhardness (HV0.01), nanoindentation, and scratch tests. Wear tests were carried out according to the ASTM G99-17 standard using a ball-on-disc tribometer. The tests were performed in triplicate under a 2 Hz constant frequency oscillatory motion, a maximum linear speed of 0.1 m/s, normal loads of 5, 10, and 15 N, and a sliding distance of 200 m. A 100Cr6 steel ball10 mm in diameter was used as counterpart material. All tests were conducted at room temperature, in dry and lubricated conditions. Considering the more recent regulations about the environmental hazard, four bio-lubricants were considered after assessing their chemical composition (in terms of Unsaturation Number, UN) and viscosity: olive, peanut, sunflower, and soybean oils. The friction coefficient was provided by the equipment. The wear rate of anodized surfaces was evaluated by measuring the cross-section area of the wear track with a non-contact 3D profilometer. Each area value, obtained as an average of four measurements of cross-section areas along the track, was used to determine the wear volume. The worn surfaces were analyzed by VPSEM/EDS. Finally, in agreement with DoE methodology, a statistical analysis was carried out to identify the most influencing factors on the friction coefficients and wear rates. In all conditions, results show that the friction coefficient increased with raising the normal load. Considering the wear tests in dry sliding conditions, irrespective of the type of anodizing treatments, metal transfer between the mating materials was observed over the anodic aluminum oxides. During sliding at higher loads, the detachment of the metallic film also caused the delamination of some regions of the wear track. For the wear tests in lubricated conditions, the natural oils with high percentages of oleic acid (i.e., olive and peanut oils) maintained high friction coefficients and low wear rates. Irrespective of the type of oil, smallmicrocraks were visible over the AAO layers. Based on the statistical analysis, the type of anodizing treatment and magnitude of applied load were the main factors of influence on the friction coefficient and wear rate values. Nevertheless, an interaction between bio-lubricants and load magnitude could occur during the tests.

Keywords: hard anodizing treatment, silver ions, bio-lubricants, sliding wear, statistical analysis

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Authors: Alketa Qafmolla, Mimoza Canga, Edit Xhajanka, Vergjini Mulo, Ramazan Isufi, Vito Antonio Malagnino

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COVID-19 is threatening the lives of people all over the world. A number of health problems, including oral health problems, have been linked to SARS-CoV-2 infection. Loss of taste is one of the initial symptoms presented by patients who have COVID-19. Purpose: The aim of the current study is to determine the prevalence of taste loss in young adults aged 18 to 26 who have contracted SARS-CoV-2. Materials and methods: This study is analytical cross-sectional research conducted in Albania from March 2023 to September 2023. Our research included a total of 157 students, of which 100 (63.7%) were female and 57 (36.3%) were male. They were divided into three age groups: 18-20, 21-23, and 24-26 years old. Students willingly agreed to participate in the current study and were assured that their participation would be kept anonymous. The study recorded no dropouts and was conducted in accordance with the Declaration of Helsinki. Statistical analysis was performed using IBM SPSS Statistics Version 23.0 on Microsoft Windows Linux, Chicago, IL, USA. The evaluation of data was done using analysis of variance (ANOVA), with a significance level set at P ≤ 0.05. Results: 113 (72%) of the participants reported loss of taste, while 44 (28%) did not experience any loss of taste. According to the study's data analysis, taste problems typically manifest over three days, with the lowest frequency occurring on the second day and the highest frequency occurring on the fifteenth. 68.7% of participants reported experiencing taste recovery after three weeks. The present study's findings demonstrated a substantial correlation between the duration of the individuals' COVID-19 infection and taste loss (P <0.0003). Based on the statistical analysis of the data, this study shows that there is no association between gender and loss of taste (P = 0.218). The participants reported having undergone the following treatments: prednisolone sodium phosphate (15 mg/5 mL daily), vitamin C (1000 mg), azithromycin (500 mg daily), oral vitamin D3 supplementation of 5000 IU daily, vitamin B12 (2.4 mcg daily), zinc 20 mg daily, Augmentin tablets (625 mg), and magnesium sulfate (4 g/100 mL). Conclusion: Within the limitations of this study conducted in Albania, it can be concluded that loss of taste was present in 72% of participants infected with COVID-19 and recovery was evident after three weeks.

Keywords: adult, Albania, COVID-19, cross-sectional study, loss of taste

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Authors: Raphael C. Zero, Thiago A. S. S. Rocha, Marita V. Cardozo, Caio C. C. Santos, Alisson D. S. Fechis, Antonio C. Shimano, FabríCio S. Oliveira

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Biomechanical analysis is an important factor in tissue studies. The objective of this study was to determine the feasibility of a new anatomical technique and quantify the changes in skin and the jejunum resistance of cats’ corpses throughout the process. Eight adult cat cadavers were used. For every kilogram of weight, 120ml of fixative solution (95% 96GL ethyl alcohol and 5% pure glycerin) was applied via the external common carotid artery. Next, the carcasses were placed in a container with 96 GL ethyl alcohol for 60 days. After fixing, all carcasses were preserved in a 30% sodium chloride solution for 60 days. Before fixation, control samples were collected from fresh cadavers and after fixation, three skin and jejunum fragments from each cadaver were tested monthly for strength and displacement until complete rupture in a universal testing machine. All results were analyzed by F-test (P <0.05). In the jejunum, the force required to rupture the fresh samples and the samples fixed in alcohol for 60 days was 31.27±19.14N and 29.25±11.69N, respectively. For the samples preserved in the sodium chloride solution for 30 and 60 days, the strength was 26.17±16.18N and 30.57±13.77N, respectively. In relation to the displacement required for the rupture of the samples, the values of fresh specimens and those fixed in alcohol for 60 days was 2.79±0.73mm and 2.80±1.13mm, respectively. For the samples preserved for 30 and 60 days with sodium chloride solution, the displacement was 2.53±1.03mm and 2.83±1.27mm, respectively. There was no statistical difference between the samples (P=0.68 with respect to strength, and P=0.75 with respect to displacement). In the skin, the force needed to rupture the fresh samples and the samples fixed for 60 days in alcohol was 223.86±131.5N and 211.86±137.53N respectively. For the samples preserved in sodium chloride solution for 30 and 60 days, the force was 227.73±129.06 and 224.78±143.83N, respectively. In relation to the displacement required for the rupture of the samples, the values of fresh specimens and those fixed in alcohol for 60 days were 3.67±1.03mm and 4.11±0.87mm, respectively. For the samples preserved for 30 and 60 days with sodium chloride solution, the displacement was 4.21±0.93mm and 3.93±0.71mm, respectively. There was no statistical difference between the samples (P=0.65 with respect to strength, and P=0.98 with respect to displacement). The resistance of the skin and intestines of the cat carcasses suffered little change when subjected to alcohol fixation and preservation in sodium chloride solution, each for 60 days, which is promising for use in surgery training. All experimental procedures were approved by the Municipal Legal Department (protocol 02.2014.000027-1). The project was funded by FAPESP (protocol 2015-08259-9).

Keywords: anatomy, conservation, fixation, small animal

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Authors: Jeena R. S., Sukesh Kumar A.

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Stroke is one of the major reasons of adult disability and morbidity in many of the developing countries like India. Early diagnosis of stroke is essential for timely prevention and cure. Various conventional statistical methods and computational intelligent models have been developed for predicting the risk and outcome of stroke. This research work focuses on a multilevel approach for predicting the occurrence of stroke based on various risk factors and invasive techniques like retinal imaging. This risk prediction model can aid in clinical decision making and help patients to have an improved and reliable risk prediction.

Keywords: prediction, retinal imaging, risk factors, stroke

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Authors: Ravinder Bahl, Jamini Sharma

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The paper demonstrates analysis of the cervical cancer based on a probabilistic model. It involves technique for classification and prediction by recognizing typical and diagnostically most important test features relating to cervical cancer. The main contributions of the research include predicting the probability of recurrences in no recurrence (first time detection) cases. The combination of the conventional statistical and machine learning tools is applied for the analysis. Experimental study with real data demonstrates the feasibility and potential of the proposed approach for the said cause.

Keywords: cervical cancer, recurrence, no recurrence, probabilistic, classification, prediction, machine learning

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Authors: Nurlan Smagulov, Aiman Konkabayeva, Akerke Sadykova, Arailym Serik

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Introduction. Adverse environmental factors do not immediately lead to pathological changes in the body. They can exert the growth of pre-pathology characterized by shifts in physiological, biochemical, immunological and other indicators of the body state. These disorders are unstable, reversible and indicative of body reactions. There is an opportunity to objectively judge the internal structure of the adaptive body reactions at the level of individual organs and systems. In order to obtain a stable response of the body to the chronic effects of unfavorable environmental factors of low intensity (compared to production environment factors), a time called the «lag time» is needed. The obtained results without considering this factor distort reality and, for the most part, cannot be a reliable statement of the main conclusions in any work. A technique is needed to reduce methodological errors and combine mathematical logic using statistical methods and a medical point of view, which ultimately will affect the obtained results and avoid a false correlation. Objective. Development of a methodology for assessing and predicting the environmental factors impact on the population health considering the «lag time.» Methods. Research objects: environmental and population morbidity indicators. The database on the environmental state was compiled from the monthly newsletters of Kazhydromet. Data on population morbidity were obtained from regional statistical yearbooks. When processing static data, a time interval (lag) was determined for each «argument-function» pair. That is the required interval, after which the harmful factor effect (argument) will fully manifest itself in the indicators of the organism's state (function). The lag value was determined by cross-correlation functions of arguments (environmental indicators) with functions (morbidity). Correlation coefficients (r) and their reliability (t), Fisher's criterion (F) and the influence share (R2) of the main factor (argument) per indicator (function) were calculated as a percentage. Results. The ecological situation of an industrially developed region has an impact on health indicators, but it has some nuances. Fundamentally opposite results were obtained in the mathematical data processing, considering the «lag time». Namely, an expressed correlation was revealed after two databases (ecology-morbidity) shifted. For example, the lag period was 4 years for dust concentration, general morbidity, and 3 years – for childhood morbidity. These periods accounted for the maximum values of the correlation coefficients and the largest percentage of the influencing factor. Similar results were observed in relation to the concentration of soot, dioxide, etc. The comprehensive statistical processing using multiple correlation-regression variance analysis confirms the correctness of the above statement. This method provided the integrated approach to predicting the degree of pollution of the main environmental components to identify the most dangerous combinations of concentrations of leading negative environmental factors. Conclusion. The method of assessing the «environment-public health» system (considering the «lag time») is qualitatively different from the traditional (without considering the «lag time»). The results significantly differ and are more amenable to a logical explanation of the obtained dependencies. The method allows presenting the quantitative and qualitative dependence in a different way within the «environment-public health» system.

Keywords: ecology, morbidity, population, lag time

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Authors: Rafika Bibi, Khaled Khaladi, Hind Mokran, Mohamed Salah Boukhechem

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A high performance liquid chromatographic method with ultraviolet detection at 264nm was developed and validate for quantitative determination and separation of cefazolin and cefotaxime in urine, the mobile phase consisted of acetonitrile and phosphate buffer pH4,2(15 :85) (v/v) pumped through ODB 250× 4,6 mm, 5um column at a flow rate of 1ml/min, loop of 20ul. In this condition, the validation of this technique showed that it is linear in a range of 0,01 to 10ug/ml with a good correlation coefficient ( R>0,9997), retention time of cefotaxime, cefazolin was 9.0, 10.1 respectively, the statistical evaluation of the method was examined by means of within day (n=6) and day to day (n=5) and was found to be satisfactory with high accuracy and precision.

Keywords: cefazolin, cefotaxime, HPLC, bioscience, biochemistry, pharmaceutical

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Authors: Djamila Benhaddouche, Abdelkader Benyettou

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In this paper, we used data mining to extract biomedical knowledge. In general, complex biomedical data collected in studies of populations are treated by statistical methods, although they are robust, they are not sufficient in themselves to harness the potential wealth of data. For that you used in step two learning algorithms: the Decision Trees and Support Vector Machine (SVM). These supervised classification methods are used to make the diagnosis of thyroid disease. In this context, we propose to promote the study and use of symbolic data mining techniques.

Keywords: biomedical data, learning, classifier, algorithms decision tree, knowledge extraction

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Authors: Alive Ntunja, Wilma ten Ham-Baloyi, June Teare, Oyedele Opeoluwa, Paula Melariri

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Sanitation workers are also known as “garbage workers” who play a significant role in the sanitation chain. For many generations sanitation workers’ level of knowledge regarding hygiene practices remains low due to a lack of educational programs on hygiene. As a result, they are widely exposed to hygiene-related diseases such as cholera, skin infections and various other diseases, increasing their risk of mortality to 40%. This review aimed to explore the global impact of educational programs on the hygiene knowledge and practices of sanitation workers. The systematic literature search was conducted for studies published between 2013 and 2023 using the following databases: MEDLINE (via EBSCOHost), PubMed, and Google Scholar to identify quantitative studies on the subject. Study quality was assessed using the Joanna Briggs Institute Critical Evaluation Instruments. Data extracted from the included articles was presented using a summary of findings table and presented graphically through charts and tables, employing both descriptive and inferential statistical methods. A one-way repeated measures ANOVA assessed the pooled effect of the intervention on mean scores across studies. Statistical analysis was performed using Microsoft Office 365 (2019 version), with significance set at p<0.05. The PRISMA flow diagram was used to present the article selection process. The systematic review included 15 eligible studies from a total of 2 777 articles. At least 60% (n=9) of the reviewed studies found educational program relating to hygiene to have a positive impact on sanitation workers’ hygiene knowledge and practices. The findings further showed that the stages (pre-post) of knowledge intervention used lead to statistically significant differences in mean score obtained [F (1,7) = 22.166, p = 0.002]. Likewise, it can be observed that the stages of practice intervention used lead to statistically significant differences in mean score obtained [F (1,7) = 21.857, p = 0.003]. However, most (n=7) studies indicated that, the efficacy of programs on hygiene knowledge and practices is indirectly influenced by educational background, age and work experience (predictor factors). Educational programs regarding hygiene have the potential to significantly improve sanitation workers knowledge and practices. Findings also suggest the implementation of active and intensive intervention programs, to improve sanitation workers hygiene knowledge and practices.

Keywords: educational programs, hygiene knowledge, practices, sanitation workers

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Authors: Diego Liberati

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Standard molecular modeling is traditionally done through Schroedinger equations via the help of powerful tools helping to manage them atom by atom, often needing High Performance Computing. Here, a full portfolio of new tools, conjugating statistical inference in the so called eXplainable Artificial Intelligence framework (in the form of Machine Learning of understandable rules) to the more traditional modeling and simulation control theory of mixed dynamic logic hybrid processes, is offered as quite a general purpose even if making an example to a popular chemical physics set of problems.

Keywords: understandable rules ML, k-means, PCA, PieceWise Affine Auto Regression with eXogenous input

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Authors: K. A. Adepoju, O. I. Shittu, A. U. Chukwu

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In this paper, a new four-parameter generalized version of the Fisher Snedecor distribution called Beta- F distribution is introduced. The comprehensive account of the statistical properties of the new distributions was considered. Formal expressions for the cumulative density function, moments, moment generating function and maximum likelihood estimation, as well as its Fisher information, were obtained. The flexibility of this distribution as well as its robustness using cancer remission time data was demonstrated. The new distribution can be used in most applications where the assumption underlying the use of other lifetime distributions is violated.

Keywords: fisher-snedecor distribution, beta-f distribution, outlier, maximum likelihood method

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Authors: Abdel Hadi Ebraheim

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This paper introduces a new extension of the Inverse Pareto distribution in the framework of Marshal-Olkin (1997) family of distributions. This model is capable of modeling various shapes of aging and failure data. The statistical properties of the new model are discussed. Several methods are used to estimate the parameters involved. Explicit expressions are derived for different types of moments of value in reliability analysis are obtained. Besides, the order statistics of samples from the new proposed model have been studied. Finally, the usefulness of the new model for modeling reliability data is illustrated using two real data sets with simulation study.

Keywords: pareto distribution, marshal-Olkin, reliability, hazard functions, moments, estimation

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Authors: Serdar Öge, Pinar Ertürk

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The main objective of this research is to describe the relationship between organizational climate and organizational citizenship behavior. In order to examine this relationship, a research is intended to be carried out in relevant institutions and organizations operating in the health sector in Turkey. It will be found whether there is a statistically significant relationship between organizational climate and organizational citizenship behavior through elated scientific research methods and statistical analysis. In addition, elationships between the dimensions of organizational climate and organizational citizenship behavior subscales will be questioned statistically.

Keywords: organizational climate, organizational citizenship, organizational citizenship behavior, climate

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Authors: Alexandru George Vaduva, Adriana Vlad, Bogdan Badea

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In this research, we conduct a Monte Carlo analysis on a two-dimensional χ2 test, which is used to determine the minimum distance required for independent sampling in the context of chaotic signals. We investigate the impact of transforming initial data sets from any probability distribution to new signals with a uniform distribution using the Spearman rank correlation on the χ2 test. This transformation removes the randomness of the data pairs, and as a result, the observed distribution of χ2 test values differs from the expected distribution. We propose a solution to this problem and evaluate it using another chaotic signal.

Keywords: chaotic signals, logistic map, Pearson’s test, Chi Square test, bivariate distribution, statistical independence

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Authors: Shafaq Rubab

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The primary reason for dropping out of school is associated with students’ lack of motivation in class, especially in mathematics. Digital game-based learning is an approach that is being actively explored; there are very few learning games based on proven instructional design models or frameworks due to which the effectiveness of the learning games suffers. The purpose of this research was twofold: first, developing an appropriate instructional design model and second, evaluating the impact of the instructional design model on students’ motivation. This research contributes significantly to the existing literature in terms of student motivation and the impact of instructional design model in digital game-based learning. The sample size for this study consists of two hundred out-of-school students between the age of 6 and 12 years. The research methodology used for this research was a quasi-experimental approach and data was analyzed by using the instructional material motivational survey questionnaire which is adapted from the Keller Arcs model. Control and experimental groups consisting of two hundred students were analyzed by utilizing instructional material motivational survey (IMMS), and comparison of result from both groups showed the difference in the level of motivation of the students. The result of the research showed that the motivational level of student in the experimental group who were taught by the game was higher than the student in control group (taught by conventional methodology). The mean score of the experimental group against all subscales (attention, relevance, confidence, and satisfaction) of IMMS survey was higher; however, no statistical significance was found between the motivational scores of control and experimental group. The positive impact of game-based learning on students’ level of motivation, as measured in this study, strengthens the case for the use of pedagogically sound instructional design models in the design of interactive learning applications. In addition, the present study suggests learning from interactive, immersive applications as an alternative solution for children, especially in Third World countries, who, for various reasons, do not attend school. The mean score of experimental group against all subscales of IMMS survey was higher; however, no statistical significance was found between motivational scores of control and experimental group.

Keywords: digital game-based learning, students’ motivation, and instructional designing, instructional material motivational survey

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Authors: Mehdi Homayouni, Karim Adinehvand, Bakhtiar Azadbakht

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In this study, we used Monte Carlo code (MCNP4C) that is a general method, for simulation, electron source and electric field, a disc source with 0.05 cm radius in direct of anode are used, radius of disc source show focal spot of X-ray tube that here is 0.05 cm. In this simulation, the anode is from tungsten with 18.9 g/cm3 density and angle of the anode is 18°. We simulated X-ray tube for 140 kv. For increasing of speed data acquisition, we use F5 tally. With determination the exact position of F5 tally in the program, outputs are acquired. In this spectrum the start point is about 0.02 Mev, the absorption edges are about 0.06 Mev and 0.07 Mev, and average energy is about 0.05 Mev.

Keywords: X-spectrum, simulation, Monte Carlo, tube

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Authors: David Krejci, Tony Schönherr, Quirin Koch, Valentin Hugonnaud, Lou Grimaud, Alexander Reissner, Bernhard Seifert

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In 2018 the NANO thruster became the first Field Emission Electric Propulsion (FEEP) system ever to be verified in space in an In-Orbit Demonstration mission conducted together with Fotec. Since then, 160 additional ENPULSION NANO propulsion systems have been deployed in orbit on 73 different spacecraft across multiple customers and missions. These missions included a variety of different satellite bus sizes ranging from 3U Cubesats to >100kg buses, and different orbits in Low Earth Orbit and Geostationary Earth orbit, providing an abundance of on orbit data for statistical analysis. This large-scale industrialization and flight heritage allows for a holistic way of gathering data from testing, integration and operational phases, deriving lessons learnt over a variety of different mission types, operator approaches, use cases and environments. Based on these lessons learnt a new generation of propulsion systems is developed, addressing key findings from the large NANO heritage and adding new capabilities, including increased resilience, thrust vector steering and increased power and thrust level. Some of these successor products have already been validated in orbit, including the MICRO R3 and the NANO AR3. While the MICRO R3 features increased power and thrust level, the NANO AR3 is a successor of the heritage NANO thruster with added thrust vectoring capability. 5 NANO AR3 have been launched to date on two different spacecraft. This work presents flight telemetry data of ENPULSION NANO systems and onorbit statistical data of the ENPULSION NANO as well as lessons learnt during onorbit operations, customer assembly, integration and testing support and ground test campaigns conducted at different facilities. We discuss how transfer of lessons learnt and operational improvement across independent missions across customers has been accomplished. Building on these learnings and exhaustive heritage, we present the design of the new generation of propulsion systems that increase the power and thrust level of FEEP systems to address larger spacecraft buses.

Keywords: FEEP, field emission electric propulsion, electric propulsion, flight heritage

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Authors: Navid Mirzaei Varzeghani, Mahmoud Saffarzadeh, Ali Naderan, Amirhossein Taheri

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Countries are progressing, and the world's busiest airports see year-on-year increases in travel demand. Passenger acceptability of an airport depends on the airport's appeals, which may include one of these routes between the city and the airport, as well as the facilities to reach them. One of the critical roles of transportation planners is to predict future transportation demand so that an integrated, multi-purpose system can be provided and diverse modes of transportation (rail, air, and land) can be delivered to a destination like an airport. In this study, 356 questionnaires were filled out in person over six days. First, the attraction of business and non-business trips was studied using data and a linear regression model. Lower travel costs, a range of ages more significant than 55, and other factors are essential for business trips. Non-business travelers, on the other hand, have prioritized using personal vehicles to get to the airport and ensuring convenient access to the airport. Business travelers are also less price-sensitive than non-business travelers regarding airport travel. Furthermore, carrying additional luggage (for example, more than one suitcase per person) undoubtedly decreases the attractiveness of public transit. Afterward, based on the manner and purpose of the trip, the locations with the highest trip generation to the airport were identified. The most famous district in Tehran was District 2, with 23 visits, while the most popular mode of transportation was an online taxi, with 12 trips from that location. Then, significant variables in separation and behavior of travel methods to access the airport were investigated for all systems. In this scenario, the most crucial factor is the time it takes to get to the airport, followed by the method's user-friendliness as a component of passenger preference. It has also been demonstrated that enhancing public transportation trip times reduces private transportation's market share, including taxicabs. Based on the responses of personal and semi-public vehicles, the desire of passengers to approach the airport via public transportation systems was explored to enhance present techniques and develop new strategies for providing the most efficient modes of transportation. Using the binary model, it was clear that business travelers and people who had already driven to the airport were the least likely to change.

Keywords: multimodal transportation, demand modeling, travel behavior, statistical models

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Authors: Mrinal Kanti Bhowmik, Shawli Bardhan Jr., Debotosh Bhattacharjee

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Human skin containing temperature value more than absolute zero, discharges infrared radiation related to the frequency of the body temperature. The difference in infrared radiation from the skin surface reflects the abnormality present in human body. Considering the difference, detection and forecasting the temperature variation of the skin surface is the main objective of using Medical Infrared Thermography(MIT) as a diagnostic tool for pain detection. Medical Infrared Thermography(MIT) is a non-invasive imaging technique that records and monitors the temperature flow in the body by receiving the infrared radiated from the skin and represent it through thermogram. The intensity of the thermogram measures the inflammation from the skin surface related to pain in human body. Analysis of thermograms provides automated anomaly detection associated with suspicious pain regions by following several image processing steps. The paper represents a rigorous study based survey related to the processing and analysis of thermograms based on the previous works published in the area of infrared thermal imaging for detecting inflammatory pain diseases like arthritis, spondylosis, shoulder impingement, etc. The study also explores the performance analysis of thermogram processing accompanied by thermogram acquisition protocols, thermography camera specification and the types of pain detected by thermography in summarized tabular format. The tabular format provides a clear structural vision of the past works. The major contribution of the paper introduces a new thermogram acquisition standard associated with inflammatory pain detection in human body to enhance the performance rate. The FLIR T650sc infrared camera with high sensitivity and resolution is adopted to increase the accuracy of thermogram acquisition and analysis. The survey of previous research work highlights that intensity distribution based comparison of comparable and symmetric region of interest and their statistical analysis assigns adequate result in case of identifying and detecting physiological disorder related to inflammatory diseases.

Keywords: acquisition protocol, inflammatory pain detection, medical infrared thermography (MIT), statistical analysis

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Authors: Jihan Abdulazeez Ahmed, Adnan Mohsin Abdulazeez Brifcani

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This paper suggests a new internal architecture of holon based on feature selection model using the combination of Bees Algorithm (BA) and Artificial Neural Network (ANN). BA is used to generate features while ANN is used as a classifier to evaluate the produced features. Proposed system is applied on the Wine data set, the statistical result proves that the proposed system is effective and has the ability to choose informative features with high accuracy.

Keywords: artificial neural network, bees algorithm, feature selection, Holon

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Authors: Magdalena Igras, Joanna Grzybowska, Mariusz Ziółko

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The study of emotions expressed in emergency phone call is presented, covering both statistical analysis of emotions configurations and an attempt to automatically classify emotions. An emergency call is a situation usually accompanied by intense, authentic emotions. They influence (and may inhibit) the communication between caller and responder. In order to support responders in their responsible and psychically exhaustive work, we studied when and in which combinations emotions appeared in calls. A corpus of 45 hours of conversations (about 3300 calls) from emergency call center was collected. Each recording was manually tagged with labels of emotions valence (positive, negative or neutral), type (sadness, tiredness, anxiety, surprise, stress, anger, fury, calm, relief, compassion, satisfaction, amusement, joy) and arousal (weak, typical, varying, high) on the basis of perceptual judgment of two annotators. As we concluded, basic emotions tend to appear in specific configurations depending on the overall situational context and attitude of speaker. After performing statistical analysis we distinguished four main types of emotional behavior of callers: worry/helplessness (sadness, tiredness, compassion), alarm (anxiety, intense stress), mistake or neutral request for information (calm, surprise, sometimes with amusement) and pretension/insisting (anger, fury). The frequency of profiles was respectively: 51%, 21%, 18% and 8% of recordings. A model of presenting the complex emotional profiles on the two-dimensional (tension-insecurity) plane was introduced. In the stage of acoustic analysis, a set of prosodic parameters, as well as Mel-Frequency Cepstral Coefficients (MFCC) were used. Using these parameters, complex emotional states were modeled with machine learning techniques including Gaussian mixture models, decision trees and discriminant analysis. Results of classification with several methods will be presented and compared with the state of the art results obtained for classification of basic emotions. Future work will include optimization of the algorithm to perform in real time in order to track changes of emotions during a conversation.

Keywords: acoustic analysis, complex emotions, emotion recognition, machine learning

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Authors: A. Brahma

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The drying of hydraulics materials is unavoidable and conducted to important spontaneous deformations. In this study, we show that it is possible to describe the drying shrinkage of the high-performance concrete by a simple expression. A multiple regression model was developed for the prediction of the drying shrinkage of the high-performance concrete. The assessment of the proposed model has been done by a set of statistical tests. The model developed takes in consideration the main parameters of confection and conservation. There was a very good agreement between drying shrinkage predicted by the multiple regression model and experimental results. The developed model adjusts easily to all hydraulic concrete types.

Keywords: hydraulic concretes, drying, shrinkage, prediction, modeling

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Authors: Mohammed R. Elkobaisi, Abdelsalam Maatuk

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The search engines are the large scale information retrieval tools from the Web that are currently freely available to all. This paper explains how to convert the raw resulted number of search engines into useful information. This represents a new method for data gathering comparing with traditional methods. When a query is submitted for a multiple numbers of keywords, this take a long time and effort, hence we develop a user interface program to automatic search by taking multi-keywords at the same time and leave this program to collect wanted data automatically. The collected raw data is processed using mathematical and statistical theories to eliminate unwanted data and converting it to usable data.

Keywords: search engines, information extraction, agent system

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Authors: Mohammad Arabi

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Business Process Reengineering (BPR) is a systematic approach to fundamentally redesign organizational processes to achieve significant improvements in organizational performance. At Fars Regional Electric Company, implementing BPR is deemed essential to increase productivity, reduce costs, and improve service quality. This article examines how BPR can help enhance the performance of Fars Regional Electric Company. The objective of this research is to evaluate and analyze the advancements in process modeling and reengineering at Fars Regional Electric Company and to provide solutions for improving the productivity and efficiency of organizational processes. This study aims to demonstrate how BPR can be used to improve organizational processes and enhance the overall performance of the company. This research employs both qualitative and quantitative research methods and includes interviews with senior managers and experts at Fars Regional Electric Company. The analytical tools include process modeling software such as Bizagi and ARIS, and statistical analysis software such as SPSS and Minitab. Data analysis was conducted using advanced statistical methods. The results indicate that the use of BPR techniques can lead to a significant reduction in process execution time and overall improvement in quality. Implementing BPR at Fars Regional Electric Company has led to increased productivity, reduced costs, and improved overall performance of the company. This study shows that with proper implementation of BPR and the use of modeling tools, the company can achieve significant improvements in its processes. Recommendations: (1) Continuous Training for Staff: Invest in continuous training of staff to enhance their skills and knowledge in BPR. (2) Use of Advanced Technologies: Utilize modeling and analysis software to improve processes. (3) Implementation of Effective Management Systems: Employ knowledge and information management systems to enhance organizational performance. (4) Continuous Monitoring and Review of Processes: Regularly review and revise processes to ensure ongoing improvements. This article highlights the importance of improving organizational processes at Fars Regional Electric Company and recommends that managers and decision-makers at the company seriously consider reengineering processes and utilizing modeling technologies to achieve developmental goals and continuous improvement.

Keywords: business process reengineering, electric company, Fars province, process modeling advancements

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Authors: Mustafa M. Donma, Orkide Donma

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Obesity and weight gain are associated with increased risk of developing cardiovascular diseases and the progression of liver fibrosis. Aspartate transaminase–to-platelet count ratio index (AST-to-PLT, APRI) and fibrosis-4 (FIB-4) were primarily considered as the formulas capable of differentiating hepatitis from cirrhosis. Recently, they have found clinical use as measures of liver fibrosis and cardiovascular risk. However, their status in children has not been evaluated in detail yet. The aim of this study is to determine APRI and FIB-4 status in obese (OB) children and compare them with values found in children with normal body mass index (N-BMI). A total of sixty-eight children examined in the outpatient clinics of the Pediatrics Department in Tekirdag Namik Kemal University Medical Faculty were included in the study. Two groups were constituted. In the first group, thirty-five children with N-BMI, whose age- and sex-dependent BMI indices vary between 15 and 85 percentiles, were evaluated. The second group comprised thirty-three OB children whose BMI percentile values were between 95 and 99. Anthropometric measurements and routine biochemical tests were performed. Using these parameters, values for the related indices, BMI, APRI, and FIB-4, were calculated. Appropriate statistical tests were used for the evaluation of the study data. The statistical significance degree was accepted as p<0.05. In the OB group, values found for APRI and FIB-4 were higher than those calculated for the N-BMI group. However, there was no statistically significant difference between the N-BMI and OB groups in terms of APRI and FIB-4. A similar pattern was detected for triglyceride (TRG) values. The correlation coefficient and degree of significance between APRI and FIB-4 were r=0.336 and p=0.065 in the N-BMI group. On the other hand, they were r=0.707 and p=0.001 in the OB group. Associations of these two indices with TRG have shown that this parameter was strongly correlated (p<0.001) both with APRI and FIB-4 in the OB group, whereas no correlation was calculated in children with N-BMI. Triglycerides are associated with an increased risk of fatty liver, which can progress to severe clinical problems such as steatohepatitis, which can lead to liver fibrosis. Triglycerides are also independent risk factors for cardiovascular disease. In conclusion, the lack of correlation between TRG and APRI as well as FIB-4 in children with N-BMI, along with the detection of strong correlations of TRG with these indices in OB children, was the indicator of the possible onset of the tendency towards the development of fatty liver in OB children. This finding also pointed out the potential risk for cardiovascular pathologies in OB children. The nature of the difference between APRI vs FIB-4 correlations in N-BMI and OB groups (no correlation versus high correlation), respectively, may be the indicator of the importance of involving age and alanine transaminase parameters in addition to AST and PLT in the formula designed for FIB-4.

Keywords: APRI, children, FIB-4, obesity, triglycerides

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Authors: Rubi Alvarez-Rodriguez

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Traditionally, eco-centric and anthropocentric forms of environmentalism have been seen as mutually exclusive. While eco-centrism focuses on global environmental issues, anthropocentrism is concerned with local ones. The objective of this paper is to characterize the relationship between eco-centric and anthropocentric attitudes across 43 countries. This study analysed secondary data from the 2005 World Values Survey, using a standard linear regression approach. It is shown that eco-centric and anthropocentric attitudes are not mutually exclusive and that the predominance of one over the other is best predicted by a country’s level of wealth.

Keywords: anthropocentrism, eco-centrism, pro-environmental attitudes, wealth

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Authors: Sisuwan Kaseamsawat, Sivapan Choo-In

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A study was conducted in May to July 2013 with the aim of determination of heavy metal concentration in orchard area. 60 samples were collected and analyzed for Cadmium (Cd), Copper (Cu), Lead (Pb), and Zinc (Zn) by Atomic Absorption Spectrophotometer (AAS). The heavy metal concentrations in sediment of orchards, that use chemical for Cd (1.13 ± 0.26 mg/l), Cu (8.00 ± 1.05 mg/l), Pb (13.16 ± 2.01) and Zn (37.41 ± 3.20 mg/l). The heavy metal concentrations in sediment of the orchards, that do not use chemical for Cd (1.28 ± 0.50 mg/l), Cu (7.60 ± 1.20 mg/l), Pb (29.87 ± 4.88) and Zn (21.79 ± 2.98 mg/l). Statistical analysis between heavy metal in sediment from the orchard, that use chemical and the orchard, that not use chemical were difference statistic significant of 0.5 level of significant for Cd and Pb while no statistically difference for Cu and Zn.

Keywords: heavy metal, orchard, pollution and monitoring, sediment

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Authors: Mustafa M. Donma, Orkide Donma

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A growing list of cancers might be influenced by obesity. Obesity is associated with an increased risk for the occurrence and development of some cancers. Inflammation can lead to cancer. It is one of the characteristic features of cancer and plays a critical role in cancer development. C-reactive protein (CRP) is under evaluation related to the new and simple prognostic factors in patients with metastatic renal cell cancer. Obesity can predict and promote systemic inflammation in healthy adults. BMI is correlated with hs-CRP. In this study, SII index and CRP values were evaluated in children with normal BMI and those within the range of different obesity grades to detect the tendency towards cancer in pediatric obesity. A total of one hundred and ninety-four children; thirty-five children with normal BMI, twenty overweight (OW), forty-seven obese (OB) and ninety-two morbid obese (MO) participated in the study. Age- and sex-matched groups were constituted using BMI-for age percentiles. Informed consent was obtained. Ethical Committee approval was taken. Weight, height, waist circumference (C), hip C, head C and neck C of the children were measured. The complete blood count test was performed. C-reactive protein analysis was performed. Statistical analyses were performed using SPSS. The degree for statistical significance was p≤0.05. SII index values were progressively increasing starting from normal weight (NW) to MO children. There is a statistically significant difference between NW and OB as well as MO children. No significant difference was observed between NW and OW children, however, a correlation was observed between NW and OW children. MO constitutes the only group, which exhibited a statistically significant correlation between SII index and CRP. Obesity-related bladder, kidney, cervical, liver, colorectal, endometrial cancers are still being investigated. Obesity, characterized as a chronic low-grade inflammation, is a crucial risk factor for colon cancer. Elevated childhood BMI values may be indicative of processes leading to cancer, initiated early in life. Prevention of childhood adiposity may decrease the cancer incidence in adults. To authors’ best knowledge, this study is the first to introduce SII index values during obesity of varying degrees of severity. It is suggested that this index seems to affect all stages of obesity with an increasing tendency and may point out the concomitant status of obesity and cancer starting from very early periods of life.

Keywords: children, C-reactive protein, systemic immune-inflammation index, obesity

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