Search results for: multivariate linear regression

Authors: Siqing Guan, Fumiyo Oshima, Eiji Shimizu, Nozomi Tomita, Toru Takahashi, Hiroaki Kumano

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Risk factors for social anxiety in autism spectrum conditions involve executive attention, emotion regulation, and thought regulation as processes of cognitive dysregulation. Social camouflaging behaviors as strategies used to mask and/or compensate for autism characteristics during social interactions in autism spectrum conditions have also been emphasized. However, the role of cognitive dysregulation and social camouflaging related to social anxiety in autism spectrum conditions has not been clarified. Whether these factors are specific to social anxiety in autism spectrum conditions or common to social anxiety independent of autism spectrum conditions needs to be clarified. Here, we explored risk factors specific to social anxiety in autism spectrum conditions and general risk factors for social anxiety independent of autism spectrum conditions. From the Japanese participants in early adulthood (age=18~39) of the online survey in Japan, those who exceeded the Japanese version Autism-Spectrum Quotient cutoff (33 points or more )were divided into the autism spectrum conditions group (ASC; N=255, mean age=32.08, SD age=5.16)and those who did not exceed the cutoff were divided into the non-autism spectrum conditions group (Non-ASC; N=255, mean age=31.70, SD age=5.09). Using the Japanese versions of the Social Phobia Scale, the Social Interaction Anxiety Scale, and the Short Fear of Negative Evaluation Scale, a composite score for social anxiety was calculated using a method of principal. We also measured emotional control difficulties using the Difficulties in Emotion Regulation Scale, executive attention using the Effortful Control Scale for Adults, rumination using the Rumination-Reflection Questionnaire, and worry using the Penn State Worry Questionnaire. This study was passed through the review of the Ethics Committee. No conflicts of interest. Multiple regression analysis with forced entry method was used to predict social anxiety in the ASC and non-ASC groups separately, based on executive attention, emotion dysregulation, worry, rumination, and social camouflage. In the ASC group, emotion dysregulation (β=.277, p<.001), worry (β=.162, p<.05), assimilation (β=.308, p<.001) and masking (β=.275, p<.001) were significant predictors of social anxiety (F (7,247) = 45.791, p <.001, R2=.565). In the non-ASC groups,emotion dysregulation (β=.171, p<.05), worry (β=.344，p <.001), assimilation (β=.366,p <.001) and executive attention (β=-.132,p <.05) were significant predictors of social anxiety (F (7,207) =47.333, p <.001, R2=.615).The findings suggest that masking was shown to be a risk factor for social anxiety specific to autism spectrum conditions, while emotion dysregulation, worry, and assimilation were shown to be common risk factors for social anxiety, regardless of autism spectrum conditions. In addition, executive attention is a risk factor for social anxiety without autism spectrum conditions.

Keywords: autism spectrum, cognitive control, social anxiety, social camouflaging

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Authors: S. Behnia, S. Fathizadeh, A. Akhshani

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In the recent decades, DNA has increasingly interested in the potential technological applications that not directly related to the coding for functional proteins that is the expressed in form of genetic information. One of the most interesting applications of DNA is related to the construction of nanostructures of high complexity, design of functional nanostructures in nanoelectronical devices, nanosensors and nanocercuits. In this field, DNA is of fundamental interest to the development of DNA-based molecular technologies, as it possesses ideal structural and molecular recognition properties for use in self-assembling nanodevices with a definite molecular architecture. Also, the robust, one-dimensional flexible structure of DNA can be used to design electronic devices, serving as a wire, transistor switch, or rectifier depending on its electronic properties. In order to understand the mechanism of the charge transport along DNA sequences, numerous studies have been carried out. In this regard, conductivity properties of DNA molecule could be investigated in a simple, but chemically specific approach that is intimately related to the Su-Schrieffer-Heeger (SSH) model. In SSH model, the non-diagonal matrix element dependence on intersite displacements is considered. In this approach, the coupling between the charge and lattice deformation is along the helix. This model is a tight-binding linear nanoscale chain established to describe conductivity phenomena in doped polyethylene. It is based on the assumption of a classical harmonic interaction between sites, which is linearly coupled to a tight-binding Hamiltonian. In this work, the Hamiltonian and corresponding motion equations are nonlinear and have high sensitivity to initial conditions. Then, we have tried to move toward the nonlinear dynamics and phase space analysis. Nonlinear dynamics and chaos theory, regardless of any approximation, could open new horizons to understand the conductivity mechanism in DNA. For a detailed study, we have tried to study the current flowing in DNA and investigated the characteristic I-V diagram. As a result, It is shown that there are the (quasi-) ohmic areas in I-V diagram. On the other hand, the regions with a negative differential resistance (NDR) are detectable in diagram.

Keywords: DNA conductivity, Landauer resistance, negative dierential resistance, Chaos theory, mean Lyapunov exponent

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Authors: M. Paraipan, V. M. Javadova, S. I. Tyutyunnikov

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The concept of energy amplifier or accelerator driven system (ADS) involves the use of a particle accelerator coupled with a nuclear reactor. The accelerated particle beam generates a supplementary source of neutrons, which allows the subcritical functioning of the reactor, and consequently a safe exploitation. The harder neutron spectrum realized ensures a better incineration of the actinides. The almost generalized opinion is that the optimal beam for ADS is represented by protons with energy around 1 GeV (gigaelectronvolt). In the present work, a systematic analysis of the energy gain for proton beams with energy from 0.5 to 3 GeV and ion beams from deuteron to neon with energies between 0.25 and 2 AGeV is performed. The target is an assembly of metallic U-Pu-Zr fuel rods in a bath of lead-bismuth eutectic coolant. The rods length is 150 cm. A beryllium converter with length 110 cm is used in order to maximize the energy released in the target. The case of a linear accelerator is considered, with a beam intensity of 1.25‧10¹⁶ p/s, and a total accelerator efficiency of 0.18 for proton beam. These values are planned to be achieved in the European Spallation Source project. The energy gain G is calculated as the ratio between the energy released in the target to the energy spent to accelerate the beam. The energy released is obtained through simulation with the code Geant4. The energy spent is calculating by scaling from the data about the accelerator efficiency for the reference particle (proton). The analysis concerns the G values, the net power produce, the accelerator length, and the period between refueling. The optimal energy for proton is 1.5 GeV. At this energy, G reaches a plateau around a value of 8 and a net power production of 120 MW (megawatt). Starting with alpha, ion beams have a higher G than 1.5 GeV protons. A beam of 0.25 AGeV(gigaelectronvolt per nucleon) ⁷Li realizes the same net power production as 1.5 GeV protons, has a G of 15, and needs an accelerator length 2.6 times lower than for protons, representing the best solution for ADS. Beams of ¹⁶O or ²⁰Ne with energy 0.75 AGeV, accelerated in an accelerator with the same length as 1.5 GeV protons produce approximately 900 MW net power, with a gain of 23-25. The study of the evolution of the isotopes composition during irradiation shows that the increase in power production diminishes the period between refueling. For a net power produced of 120 MW, the target can be irradiated approximately 5000 days without refueling, but only 600 days when the net power reaches 1 GW (gigawatt).

Keywords: accelerator driven system, ion beam, electrical power, energy gain

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Authors: Asrat Agalu Abejew

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Background: Antimicrobial resistance (AMR) is a silent tsunami and one of the top global threats to health care and public health. It is one of the common agendas globally and in Ethiopia. Emerging AMR will be a double burden to Ethiopia, which is facing a series of problems from infectious disease morbidity and mortality. In Ethiopia, although there are attempts to document AMR in healthcare institutions, comprehensive and all-inclusive analysis is still lacking. Thus, this study is aimed to determine trends in AMR from 2016-2021. Methods: A retrospective analysis of secondary data recorded in the Amhara Public Health Institute (APHI) from 2016 to 2021 G.C was conducted. Blood, Urine, Stool, Swabs, Discharge, body effusions, and other Microbiological specimens were collected from each study participants, and Bacteria identification and Resistance tests were done using the standard microbiologic procedure. Data was extracted from excel in August 2022, Trends in AMR were analyzed, and the results were described. In addition, the chi-square (X2) test and binary logistic regression were used, and a P. value < 0.05 was used to determine a significant association. Results: During 6 years period, there were 25143 culture and susceptibility tests. Overall, 265 (46.2%) bacteria were resistant to 2-4 antibiotics, 253 (44.2%) to 5-7 antibiotics, and 56 (9.7%) to >=8 antibiotics. The gram-negative bacteria were 166 (43.9%), 155 (41.5%), and 55 (14.6%) resistant to 2-4, 5-7, and ≥8 antibiotics, respectively, whereas 99(50.8%), 96(49.2% and 1 (0.5%) of gram-positive bacteria were resistant to 2-4, 5-7 and ≥8 antibiotics respectively. K. pneumonia 3783 (15.67%) and E. coli 3199 (13.25%) were the most commonly isolated bacteria, and the overall prevalence of AMR was 2605 (59.9%), where K. pneumonia 743 (80.24%), E. cloacae 196 (74.81%), A. baumannii 213 (66.56%) being the most common resistant bacteria for antibiotics tested. Except for a slight decline during 2020 (6469 (25.4%)), the overall trend of AMR is rising from year to year, with a peak in 2019 (8480 (33.7%)) and in 2021 (7508 (29.9%). If left un-intervened, the trend in AMR will increase by 78% of variation from the study period, as explained by the differences in years (R2=0.7799). Ampicillin, Augmentin, ciprofloxacin, cotrimoxazole, tetracycline, and Tobramycin were almost resistant to common bacteria they were tested. Conclusion: AMR is linearly increasing during the last 6 years. If left as it is without appropriate intervention after 15 years (2030 E.C), AMR will increase by 338.7%. A growing number of multi-drug resistant bacteria is an alarm to awake policymakers and those who do have the concern to intervene before it is too late. This calls for a periodic, integrated, and continuous system to determine the prevalence of AMR in commonly used antibiotics.

Keywords: AMR, trend, pattern, MDR

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Authors: C. Hernandez-Garcia, P. Adderley, D. Bullard, J. Grames, M. A. Mamun, G. Palacios-Serrano, M. Poelker, M. Stutzman, R. Suleiman, Y. Wang, , S. Zhang

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High-energy nuclear physics experiments performed at the Jefferson Lab (JLab) Continuous Electron Beam Accelerator Facility require a beam of spin-polarized ps-long electron bunches. The electron beam is generated when a circularly polarized laser beam illuminates a GaAs semiconductor photocathode biased at hundreds of kV dc inside an ultra-high vacuum chamber. The photocathode is mounted on highly polished stainless steel electrodes electrically isolated by means of a conical-shape ceramic insulator that extends into the vacuum chamber, serving as the cathode electrode support structure. The assembly is known as a dc photogun, which has to simultaneously meet the following criteria: high voltage to manage space charge forces within the electron bunch, ultra-high vacuum conditions to preserve the photocathode quantum efficiency, no field emission to prevent gas load when field emitted electrons impact the vacuum chamber, and finally no voltage breakdown for robust operation. Over the past decade, JLab has tested and implemented the use of inverted geometry ceramic insulators connected to commercial high voltage cables to operate a photogun at 200kV dc with a 10 cm long insulator, and a larger version at 300kV dc with 20 cm long insulator. Plans to develop a third photogun operating at 400kV dc to meet the stringent requirements of the proposed International Linear Collider are underway at JLab, utilizing even larger inverted insulators. This contribution describes approaches that have been successful in solving challenging problems related to breakdown and field emission, such as triple-point junction screening electrodes, mechanical polishing to achieve mirror-like surface finish and high voltage conditioning procedures with Kr gas to extinguish field emission.

Keywords: electron guns, high voltage techniques, insulators, vacuum insulation

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Authors: Zeynep Altinkaya, Ugur Dal, Figen Dag, Dilan D. Koyuncu, Merve Turkegun

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Obesity is defined as abnormal fat-tissue accumulation as a result of imbalance between energy intake and expenditure. Since 50-70% daily energy expenditure of sedantary individuals is consumed as resting energy expenditure (REE), it takes an important place in the evaluation of new methods for obesity treatment. Also, it is known that walking is a prevalent activity in the prevention of obesity. The primary purpose of this study is to evaluate and compare the resting and walking energy expenditures of individuals with different body mass index (BMI). In this research, 4 groups are formed as underweight (BMI < 18,5 kg/m2), normal (BMI=18,5-24,9 kg/m2), overweight (BMI=25-29,9 kg/m2), and obese (BMI ≥ 30) according to BMI of individuals. 64 healthy young adults (8 man and 8 woman per group, age 18-30 years) with no known gait disabilities were recruited in this study. The body compositions of all participants were measured via bioelectric empedance analysis method. The energy expenditure of individuals was measured with indirect calorimeter method as inspired and expired gas samples are collected breath-by-breath through a special facemask. The preferred walking speed (PWS) of each subject was determined by using infrared sensors placed in 2nd and 12th meters of 14 m walkway. The REE was measured for 15 min while subjects were lying, and walking energy expenditure was measured during subjects walk in their PWS on treadmill. The gross REE was significantly higher in obese subjects compared to underweight and normal subjects (p < 0,0001). When REE was normalized to body weight, it was higher in underweight and normal groups than overweight and obese groups (p < 0,0001). However, when REE was normalized to fat-free mass, it did not differ significantly between groups. The gross walking energy expenditure in PWS was higher in obese and overweight groups than underweight and normal groups (p < 0,0001). The regression coefficient between gross walking energy expenditure and body weight was significiant among normal and obese groups (p < 0.05). It accounted for 70,5% of gross walking energy expenditure in normal group, and 57,9% of gross walking energy expenditure in obese group. It is known that obese individuals have more metabolically inactive fat-tissue compared to other groups. While excess fat-tissue increases total body weight, it does not contribute much to REE. Therefore, REE results normalized to body weight could lead to misleading results. In order to eliminate fat-mass effect on REE of obese individuals, REE normalized to fat-free mass should be used to acquire more accurate results. On the other hand, the fat-mass increasement raises energy requirement while walking to retain the body balance. Thus, gross walking energy expenditure should be taken into consideration for the evaluating energy expenditure of walking.

Keywords: body composition, obesity, resting energy expenditure, walking energy expenditure

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Authors: Samul Sahile Kebede

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Back ground: -Immune hemolytic anemia commonly affects human immune deficiency, infected individuals. Among anemic HIV patients in Africa, the burden of IHA due to autoantibody was ranged from 2.34 to 3.06 due to the drug was 43.4%. IHA due to autoimmune is potentially a fatal complication of HIV, which accompanies the greatest percent from acquired hemolytic anemia. Objective: -The main aim of this study was to determine the magnitude and associated factors of immune hemolytic anemia among human immuno deficiency virus infected adults at the university of Gondar comprehensive specialized hospital north west Ethiopia from March to April 2021. Methods: - An institution-based cross-sectional study was conducted on 358 human immunodeficiency virus-infected adults selected by systematic random sampling at the University of Gondar comprehensive specialized hospital from March to April 2021. Data for socio-demography, dietary and clinical data were collected by structured pretested questionnaire. Five ml of venous blood was drawn from each participant and analyzed by Unicel DHX 800 hematology analyzer, blood film examination, and antihuman globulin test were performed to the diagnosis of immune hemolytic anemia. Data was entered into Epidata version 4.6 and analyzed by STATA version 14. Descriptive statistics were computed and firth penalized logistic regression was used to identify predictors. P value less than 0.005 interpreted as significant. Result; - The overall prevalence of immune hemolytic anemia was 2.8 % (10 of 358 participants). Of these, 5 were males, and 7 were in the 31 to 50 year age group. Among individuals with immune hemolytic anemia, 40 % mild and 60 % moderate anemia. The factors that showed association were family history of anemia (AOR 8.30 at 95% CI 1.56, 44.12), not eating meat (AOR 7.39 at 95% CI 1.25, 45.0), and high viral load 6.94 at 95% CI (1.13, 42.6). Conclusion and recommendation; Immune hemolytic anemia is less frequent condition in human immunodeficiency virus infected adults, and moderate anemia was common in this population. The prevalence was increased with a high viral load, a family history of anemia, and not eating meat. In these patients, early detection and treatment of immune hemolytic anemia is necessary.

Keywords: anemia, hemolytic, immune, auto immune, HIV/AIDS

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Authors: Elcin Timur Cakmak, Ayse Oguzlar

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This study presents the results of the tweets sent by Twitter users on social media about the Russia-Ukraine war by bigram and trigram methods. On February 24, 2022, Russian President Vladimir Putin declared a military operation against Ukraine, and all eyes were turned to this war. Many people living in Russia and Ukraine reacted to this war and protested and also expressed their deep concern about this war as they felt the safety of their families and their futures were at stake. Most people, especially those living in Russia and Ukraine, express their views on the war in different ways. The most popular way to do this is through social media. Many people prefer to convey their feelings using Twitter, one of the most frequently used social media tools. Since the beginning of the war, it is seen that there have been thousands of tweets about the war from many countries of the world on Twitter. These tweets accumulated in data sources are extracted using various codes for analysis through Twitter API and analysed by Python programming language. The aim of the study is to find the word sequences in these tweets by the n-gram method, which is known for its widespread use in computational linguistics and natural language processing. The tweet language used in the study is English. The data set consists of the data obtained from Twitter between February 24, 2022, and April 24, 2022. The tweets obtained from Twitter using the #ukraine, #russia, #war, #putin, #zelensky hashtags together were captured as raw data, and the remaining tweets were included in the analysis stage after they were cleaned through the preprocessing stage. In the data analysis part, the sentiments are found to present what people send as a message about the war on Twitter. Regarding this, negative messages make up the majority of all the tweets as a ratio of %63,6. Furthermore, the most frequently used bigram and trigram word groups are found. Regarding the results, the most frequently used word groups are “he, is”, “I, do”, “I, am” for bigrams. Also, the most frequently used word groups are “I, do, not”, “I, am, not”, “I, can, not” for trigrams. In the machine learning phase, the accuracy of classifications is measured by Classification and Regression Trees (CART) and Naïve Bayes (NB) algorithms. The algorithms are used separately for bigrams and trigrams. We gained the highest accuracy and F-measure values by the NB algorithm and the highest precision and recall values by the CART algorithm for bigrams. On the other hand, the highest values for accuracy, precision, and F-measure values are achieved by the CART algorithm, and the highest value for the recall is gained by NB for trigrams.

Keywords: classification algorithms, machine learning, sentiment analysis, Twitter

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Authors: Jun Sun, Tsz Tin Yu, Maryam Mirabediny, Matthew Lee, Adele Jones, Denis M. O’Carroll, Michael J. Manefield, Björn Åkermark, Biswanath Das, Naresh Kumar

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Reductive defluorination has emerged as a sustainable approach to clean water from Per and polyfluoroalkyl substances (PFASs), also known as forever organic containments. For last few decades, nano zero valent metals (nZVMs) have been intensively applied in the reductive remediation of groundwater contaminated with chlorinated organic compounds due to its low redox potential, easy application, and low production cost. However, there is inadequate information on the effective reductive defluorination of linear or branched PFAS using nZVMs as reductants because of the lack of suitable catalysts. CoII-5,10,15,20-Tetraphenyl-21H,23H-porphyrin (CoTPP) has been recently reported for effective catalyzing reductive defluorination of branched (br-) perfluorooctane sulfonate (PFOS) by using TiIII citrate as reductant. However, the low water solubility of CoTPP limited its applicability. Here, we explored a series of structurally related soluble cobalt porphyrin catalysts based on our previously reported best performing CoTPP. All soluble porphyrins [[meso-tetra(4-carboxyphenyl)porphyrinato]cobalt(III)]Cl·₇H₂O (CoTCPP), [[meso-tetra(4-sulfonatophenyl) porphyrinato]cobalt(III)]·9H2O (CoTPPS), and [[meso-tetra(4-N-methylpyridyl) porphyrinato]cobalt(II)](I)₄·₄H₂O (CoTMpyP) displayed better defluorination efficiencies than CoTPP. Especially, CoTMpyP presented the best defluorination efficiency for br-PFOS (94 %), branched perfluorooctanoic acid (PFOA) (89 %), and 3,7-Perfluorodecanoic acid (PFDA) (60 %) after 1 day at 70 0C. CoTMpyP-nZn0 system showed 88-164 times higher defluorination rate than VB12-nZn0 system in terms of all investigated br-PFASs. The CoTMpyP-nZn0 also performed effectively at room temperature, demonstrating the potential prospect for in-situ reductive systems. Based on the analysis of the intermediate products, the calculated bond dissociation energies (BDEs) and possible first interaction between CoTMpyP and PFAS, degradation pathways of 3,7-PFDA and 6-PFOS are proposed.

Keywords: cationic, soluble porphyrin, cobalt, vitamin b12, pfas, reductive defluorination

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Authors: Janne Engblom, Elias Oikarinen

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The understanding of housing price dynamics is of importance to a great number of agents: to portfolio investors, banks, real estate brokers and construction companies as well as to policy makers and households. A panel dataset is one that follows a given sample of individuals over time, and thus provides multiple observations on each individual in the sample. Panel data models include a variety of fixed and random effects models which form a wide range of linear models. A special case of panel data models is dynamic in nature. A complication regarding a dynamic panel data model that includes the lagged dependent variable is endogeneity bias of estimates. Several approaches have been developed to account for this problem. In this paper, the panel models were estimated using the Common Correlated Effects estimator (CCE) of dynamic panel data which also accounts for cross-sectional dependence which is caused by common structures of the economy. In presence of cross-sectional dependence standard OLS gives biased estimates. In this study, U.S housing price dynamics were examined empirically using the dynamic CCE estimator with first-difference of housing price as the dependent and first-differences of per capita income, interest rate, housing stock and lagged price together with deviation of housing prices from their long-run equilibrium level as independents. These deviations were also estimated from the data. The aim of the analysis was to provide estimates with comparisons of estimates between 1980-1999 and 2000-2012. Based on data of 50 U.S cities over 1980-2012 differences of short-run housing price dynamics estimates were mostly significant when two time periods were compared. Significance tests of differences were provided by the model containing interaction terms of independents and time dummy variable. Residual analysis showed very low cross-sectional correlation of the model residuals compared with the standard OLS approach. This means a good fit of CCE estimator model. Estimates of the dynamic panel data model were in line with the theory of housing price dynamics. Results also suggest that dynamics of a housing market is evolving over time.

Keywords: dynamic model, panel data, cross-sectional dependence, interaction model

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Authors: Krisztina Bohacs, Klaudia Markus

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To author’s best knowledge we are in absence of studies on cognitive program evaluation and we are certainly short of programs that prove to have high effect sizes with strong retention results. The purpose of our study was to investigate the effectiveness of a comprehensive cognitive training program, namely BrainRx. This cognitive rehabilitation program target and remediate seven core cognitive skills and related systems of sub-skills through repeated engagement in game-like mental procedures delivered one-on-one by a clinician, supplemented by digital training. A larger sample of children with learning disability were given pretest and post-test cognitive assessments. The experimental group completed a twenty-week cognitive training program in a BrainRx center. A matched control group received another twenty-week intervention with Feuerstein’s Instrumental Enrichment programs. A second matched control group did not receive training. As for pre- and post-test, we used a general intelligence test to assess IQ and a computer-based test battery for assessing cognition across the lifespan. Multiple regression analyses indicated that the experimental BrainRx treatment group had statistically significant higher outcomes in attention, working memory, processing speed, logic and reasoning, auditory processing, visual processing and long-term memory compared to the non-treatment control group with very large effect sizes. With the exception of logic and reasoning, the BrainRx treatment group realized significantly greater gains in six of the above given seven cognitive measures compared to the Feuerstein control group. Our one-year retention measures showed that all the cognitive training gains were above ninety percent with the greatest retention skills in visual processing, auditory processing, logic, and reasoning. The BrainRx program may be an effective tool to establish long-term cognitive changes in case of students with learning disabilities. Recommendations are made for treatment centers and special education institutions on the cognitive training of students with special needs. The importance of our study is that targeted, systematic, progressively loaded and intensive brain training approach may significantly change learning disabilities.

Keywords: cognitive rehabilitation training, cognitive skills, learning disability, permanent structural cognitive changes

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Authors: Lihyo Sung

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Background: Children and teens in Korea experience extreme levels of academic stress. To perform better on the college entrance exam and gain admission to Korea’s most prestigious universities, they devote a significant portion of their early lives to studying. Because of their excessive preparation for entrance exams, students have become accustomed to passive and involuntary engagement. Any student starting university, however, faces new challenges that require more active involvement and self-regulated practice. As a way to tackle this issue, the study focuses on investigating the mediating effects of positive psychological capital on the relationship between self-leadership and career maturity among Korean university students. Objectives and Hypotheses: The long term goal of this study is to offer insights that promote the use of positive psychological interventions in the development and adaptation of career maturity. The current objective is to assess the role of positive psychological capital as a mediator between self-leadership and career maturity among Korean university students. Based on previous research, the hypotheses are: (a) self-leadership will be positively associated with indices of career maturity, and (b) positive psychological capital will partially or fully mediate the relationship between self-leadership and career maturity. Sample Characteristics and Sample Size: Participants in the current study consisted of undergraduate students enrolled in various courses at 5 large universities in Korea. A total of 181 students participated in the study. Methodology: A quantitative research design was adopted to test the hypotheses proposed in the current study. By using a cross-sectional approach to research, a self-administered questionnaire was used to collect data on indices of positive psychological capital, self-leadership, and career maturity. The data were analyzed by means of Cronbach's alpha, Pierson correlation test, multiple regression, path analysis, and SPSS for Windows version 22.0 using descriptive statistics. Results: Findings showed that positive psychological capital fully mediated the relationship between self-leadership and career maturity. Self-leadership significantly impacted positive psychological capital and career maturity, respectively. Scientific Contribution: The results of the current study provided useful insights into the role of psychological strengths such as positive psychological capital in improving self-leadership and career maturity. Institutions can assist in increasing positive psychological capital through the creation of positive experiences for undergraduate students, such as opportunities for coaching and mentoring.

Keywords: career maturity, mediating role, positive psychological capital, self-leadership

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Authors: Kevin Brochard, Herve Le Sourne, Guillaume Barras

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The design of a submarine’s hull is crucial for its operability and crew’s safety, but also complex. Indeed, engineers need to balance lightness, acoustic discretion and resistance to both immersion pressure and environmental attacks. Submarine explosions represent a first-rate threat for the integrity of the hull, whose behavior needs to be properly analyzed. The presented work is focused on the development of a simplified analytical method to study the structural response of a deeply immersed cylinder submitted to an underwater explosion. This method aims to provide engineers a quick estimation of the resulting damage, allowing them to simulate a large number of explosion scenarios. The present research relies on the so-called plastic string on plastic foundation model. A two-dimensional boundary value problem for a cylindrical shell is converted to an equivalent one-dimensional problem of a plastic string resting on a non-linear plastic foundation. For this purpose, equivalence parameters are defined and evaluated by making assumptions on the shape of the displacement and velocity field in the cross-sectional plane of the cylinder. Closed-form solutions for the deformation and velocity profile of the shell are obtained for explosive loading, and compare well with numerical and experimental results. However, the plastic-string model has not yet been adapted for a cylinder in immersion subjected to an explosive loading. In fact, the effects of fluid-structure interaction have to be taken into account. Moreover, when an underwater explosion occurs, several pressure waves are emitted by the gas bubble pulsations, called secondary waves. The corresponding loads, which may produce significant damages to the cylinder, must also be accounted for. The analytical developments carried out to solve the above problem of a shock wave impacting a cylinder, considering fluid-structure interaction will be presented for an unstiffened cylinder. The resulting deformations are compared to experimental and numerical results for different shock factors and different standoff distances.

Keywords: immersed cylinder, rigid plastic material, shock loading, underwater explosion

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Authors: Hassan Qandil

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Using a statistical algorithm incorporated in MATLAB, four types of non-imaging Fresnel lenses are designed; spot-flat, linear-flat, dome-shaped and semi-cylindrical-shaped. The optimization employs a statistical ray-tracing methodology of the incident light, mainly considering effects of chromatic aberration, varying focal lengths, solar inclination and azimuth angles, lens and receiver apertures, and the optimum number of prism grooves. While adopting an equal-groove-width assumption of the Poly-methyl-methacrylate (PMMA) prisms, the main target is to maximize the ray intensity on the receiver’s aperture and therefore achieving higher values of heat flux. The algorithm outputs prism angles and 2D sketches. 3D drawings are then generated via AutoCAD and linked to COMSOL Multiphysics software to simulate the lenses under solar ray conditions, which provides optical and thermal analysis at both the lens’ and the receiver’s apertures while setting conditions as per the Dallas-TX weather data. Once the lenses’ characterization is finalized, receivers are designed based on its optimized aperture size. Several cavity shapes; including triangular, arc-shaped and trapezoidal, are tested while coupled with a variety of receiver materials, working fluids, heat transfer mechanisms, and enclosure designs. A vacuum-reflective enclosure is also simulated for an enhanced thermal absorption efficiency. Each receiver type is simulated via COMSOL while coupled with the optimized lens. A lab-scale prototype for the optimum lens-receiver configuration is then fabricated for experimental evaluation. Application-based testing is also performed for the selected configuration, including that of a photovoltaic-thermal cogeneration system and solar furnace system. Finally, some future research work is pointed out, including the coupling of the collector-receiver system with an end-user power generator, and the use of a multi-layered genetic algorithm for comparative studies.

Keywords: COMSOL, concentrator, energy, fresnel, optics, renewable, solar

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Authors: R. Dimitri Halley

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The research within Jungian Psychology presented here is on the wave state of Self. What has been discovered via shared dreaming, independently correlating dreams across dreamers, is beyond the Self stage into the deepest layer or the wave state Self: the very quantum ocean, the Self archetype is embedded in. A quantum wave or rhyming of meaning constituting synergy across several dreamers was discovered in dreams and in extensively shared dream work with small groups at a post therapy stage. Within the format of shared dreaming, we find synergy patterns beyond what Jung called the Self archetype. Jung led us up to the phase of Individuation and delivered the baton to Von Franz to work out the next synchronistic stage, here proposed as the finding of the quantum patterns making up the wave state of Self. These enfolded synchronistic patterns have been found in group format of shared dreaming of individuals approximating individuation, and the unfolding of it is carried by belief and faith. The reason for this format and operating system is because beyond therapy and of living reality, we find no science – no thinking or even awareness in the therapeutic sense – but rather a state of mental processing resembling more like that of spiritual attitude. Thinking as such is linear and cannot contain the deepest layer of Self, the quantum core of the human being. It is self reflection which is the container for the process at the wave state of Self. Observation locks us in an outside-in reactive flow from a first-person perspective and hence toward the surface we see to believe, whereas here, the direction of focus shifts to inside out/intrinsic. The operating system or language at the wave level of Self is thus belief and synchronicity. Belief has up to now been almost the sole province of organized religions but was viewed by Jung as an inherent property in the process of Individuation. The shared dreaming stage of the synchronistic patterns forms a larger story constituting a deep connectivity unfolding around individual Selves. Dreams of independent dreamers form larger patterns that come together as puzzles forming a larger story, and in this sense, this group work level builds on Jung as a post individuation collective stage. Shared dream correlations will be presented, illustrating a larger story in terms of trails of shared synchronicity.

Keywords: belief, shared dreaming, synchronistic patterns, wave state of self

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Authors: Shankha Sanyal, Archi Banerjee, Sayan Biswas, Sourya Sengupta, Sayan Nag, Ranjan Sengupta, Dipak Ghosh

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The term ‘gestalt’ has been widely used in the field of psychology which defined the perception of human mind to group any object not in part but as a 'unified' whole. Music, in general, is polyphonic - i.e. a combination of a number of pure tones (frequencies) mixed together in a manner that sounds harmonious. The study of human brain response due to different frequency groups of the acoustic signal can give us an excellent insight regarding the neural and functional architecture of brain functions. Hence, the study of music cognition using neuro-biosensors is becoming a rapidly emerging field of research. In this work, we have tried to analyze the effect of different frequency bands of music on the various frequency rhythms of human brain obtained from EEG data. Four widely popular Rabindrasangeet clips were subjected to Wavelet Transform method for extracting five resonant frequency bands from the original music signal. These frequency bands were initially analyzed with Detrended/Adaptive Fractal analysis (DFA/AFA) methods. A listening test was conducted on a pool of 100 respondents to assess the frequency band in which the music becomes non-recognizable. Next, these resonant frequency bands were presented to 20 subjects as auditory stimulus and EEG signals recorded simultaneously in 19 different locations of the brain. The recorded EEG signals were noise cleaned and subjected again to DFA/AFA technique on the alpha, theta and gamma frequency range. Thus, we obtained the scaling exponents from the two methods in alpha, theta and gamma EEG rhythms corresponding to different frequency bands of music. From the analysis of music signal, it is seen that loss of recognition is proportional to the loss of long range correlation in the signal. From the EEG signal analysis, we obtain frequency specific arousal based response in different lobes of brain as well as in specific EEG bands corresponding to musical stimuli. In this way, we look to identify a specific frequency band beyond which the music becomes non-recognizable and below which in spite of the absence of other bands the music is perceivable to the audience. This revelation can be of immense importance when it comes to the field of cognitive music therapy and researchers of creativity.

Keywords: AFA, DFA, EEG, gestalt in music, Hurst exponent

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Authors: O. Ojeda Mena, Y. Cressault, P. Teulet, J. P. Gonnet, D. F. N. Santos, MD. Cunha, M. S. Benilov

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The assumption of plasma in local thermal equilibrium (LTE) is commonly used to perform electric arc simulations for industrial applications. This assumption allows to model the arc using a set of magneto-hydromagnetic equations that can be solved with a computational fluid dynamic code. However, the LTE description is only valid in the arc column, whereas in the regions close to the electrodes the plasma deviates from the LTE state. The importance of these near-electrode regions is non-trivial since they define the energy and current transfer between the arc and the electrodes. Therefore, any accurate modelling of the arc must include a good description of the arc-electrode phenomena. Due to the modelling complexity and computational cost of solving the near-electrode layers, a simplified description of the arc-electrode interaction was developed in a previous work to study a steady high-pressure arc discharge, where the near-electrode regions are introduced at the interface between arc and electrode as boundary conditions. The present work proposes a similar approach to simulate the arc ignition in a free-burning arc configuration following an LTE description of the plasma. To obtain the transient evolution of the arc characteristics, appropriate boundary conditions for both the near-cathode and the near-anode regions are used based on recent publications. The arc-cathode interaction is modeled using a non-linear surface heating approach considering the secondary electron emission. On the other hand, the interaction between the arc and the anode is taken into account by means of the heating voltage approach. From the numerical modelling, three main stages can be identified during the arc ignition. Initially, a glow discharge is observed, where the cold non-thermionic cathode is uniformly heated at its surface and the near-cathode voltage drop is in the order of a few hundred volts. Next, a spot with high temperature is formed at the cathode tip followed by a sudden decrease of the near-cathode voltage drop, marking the glow-to-arc discharge transition. During this stage, the LTE plasma also presents an important increase of the temperature in the region adjacent to the hot spot. Finally, the near-cathode voltage drop stabilizes at a few volts and both the electrode and plasma temperatures reach the steady solution. The results after some seconds are similar to those presented for thermionic cathodes.

Keywords: arc-electrode interaction, thermal plasmas, electric arc simulation, cold electrodes

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Authors: Tasnuba Binte Jamal, Khan Mahmud Amanat

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Carbon Fiber-Reinforced Polymer (CFRP) composite materials have proven to have valuable properties and suitability to be used in the construction of new buildings and in upgrading the existing ones due to its effectiveness, ease of implementation and many more. In the present study, a numerical finite element investigation has been conducted using ANSYS 18.1 to study the behavior of square HSS AISC sections under eccentric compressive loading strengthened with CFRP materials. A three-dimensional finite element model for square HSS section using shell element was developed. Application of CFRP strengthening was incorporated in the finite element model by adding an additional layer of shell elements. Both material and geometric nonlinearities were incorporated in the model. The developed finite element model was applied to simulate experimental studies done by past researchers and it was found that good agreement exists between the current analysis and past experimental results, which established the acceptability and validity of the developed finite element model to carry out further investigation. Study was then focused on some selected non-compact AISC square HSS columns and the effects of number of CFRP layers, amount of eccentricities and cross-sectional geometry on the strength gain of those columns were observed. Load was applied at a distance equal to the column dimension and twice that of column dimension. It was observed that CFRP strengthening is comparatively effective for smaller eccentricities. For medium sized sections, strengthening tends to be effective at smaller eccentricities as well. For relatively large AISC square HSS columns, with increasing number of CFRP layers (from 1 to 3 layers) the gain in strength is approximately 1 to 38% to that of unstrengthened section for smaller eccentricities and slenderness ratio ranging from 27 to 54. For medium sized square HSS sections, effectiveness of CFRP strengthening increases approximately by about 12 to 162%. The findings of the present study provide a better understanding of the behavior of HSS sections strengthened with CFRP subjected to eccentric compressive load.

Keywords: CFRP strengthening, eccentricity, finite element model, square hollow section

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Authors: Amr Mohamadien, Ali Imanpour, Sylvester Agbo, Nader Yoosef-Ghodsi, Samer Adeeb

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The fracture toughness resistance curve (e.g., J-R curve and crack tip opening displacement (CTOD) or δ-R curve) is important in facilitating strain-based design and integrity assessment of oil and gas pipelines. This paper aims to present laboratory experimental data to characterize the fracture behavior of pipeline steel. The influential parameters associated with the fracture of API 5L X52 pipeline steel, including different initial crack sizes, were experimentally investigated for a single notch edge bend (SENB). A total of 9 small-scale specimens with different crack length to specimen depth ratios were conducted and tested using single edge notch bending (SENB). ASTM E1820 and BS7448 provide testing procedures to construct the fracture resistance curve (Load-CTOD, CTOD-R, or J-R) from test results. However, these procedures are limited by standard specimens’ dimensions, displacement gauges, and calibration curves. To overcome these limitations, this paper presents the use of small-scale specimens and a 3D-digital image correlation (DIC) system to extract the parameters required for fracture toughness estimation. Fracture resistance curve parameters in terms of crack mouth open displacement (CMOD), crack tip opening displacement (CTOD), and crack growth length (∆a) were carried out from test results by utilizing the DIC system, and an improved regression fitting resistance function (CTOD Vs. crack growth), or (J-integral Vs. crack growth) that is dependent on a variety of initial crack sizes was constructed and presented. The obtained results were compared to the available results of the classical physical measurement techniques, and acceptable matchings were observed. Moreover, a case study was implemented to estimate the maximum strain value that initiates the stable crack growth. This might be of interest to developing more accurate strain-based damage models. The results of laboratory testing in this study offer a valuable database to develop and validate damage models that are able to predict crack propagation of pipeline steel, accounting for the influential parameters associated with fracture toughness.

Keywords: fracture toughness, crack propagation in pipeline steels, CTOD-R, strain-based damage model

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Authors: Jagdish Prasad Sahoo

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The increase in active earth pressure during the event of an earthquake results sliding, overturning and tilting of earth retaining structures. In order to improve upon the stability of structures, the soil mass is often reinforced with various types of reinforcements such as metal strips, geotextiles, and geogrids etc. The stresses generated in the soil mass are transferred to the reinforcements through the interface friction between the earth and the reinforcement, which in turn reduces the lateral earth pressure on the retaining walls. Hence, the evaluation of earth pressure in the presence of seismic forces with an inclusion of reinforcements is important for the design retaining walls in the seismically active zones. In the present analysis, the effect of reinforcing horizontal layers of reinforcements in the form of sheets (Geotextiles and Geogrids) in sand used as backfill, on reducing the active earth pressure due to earthquake body forces has been studied. For carrying out the analysis, pseudo-static approach has been adopted by employing upper bound theorem of limit analysis in combination with finite elements and linear optimization. The computations have been performed with and out reinforcements for different internal friction angle of sand varying from 30 ° to 45 °. The effectiveness of the reinforcement in reducing the active earth pressure on the retaining walls is examined in terms of active earth pressure coefficient for presenting the solutions in a non-dimensional form. The active earth pressure coefficient is expressed as functions of internal friction angle of sand, interface friction angle between sand and reinforcement, soil-wall interface roughness conditions, and coefficient of horizontal seismic acceleration. It has been found that (i) there always exists a certain optimum depth of the reinforcement layers corresponding to which the value of active earth pressure coefficient becomes always the minimum, and (ii) the active earth pressure coefficient decreases significantly with an increase in length of reinforcements only up to a certain length beyond which a further increase in length hardly causes any reduction in the values active earth pressure. The optimum depth of the reinforcement layers and the required length of reinforcements corresponding to the optimum depth of reinforcements have been established. The numerical results developed in this analysis are expected to be useful for purpose of design of retaining walls.

Keywords: active, finite elements, limit analysis, presudo-static, reinforcement

Procedia PDF Downloads 357

Authors: Mohammad Reza Esmaili

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One of the most important parts of the restoration process of a power network is the synchronizing of its subsystems. In this situation, the biggest concern of the system operators will be the reduction of the standing phase angle (SPA) between the endpoints of the two islands. In this regard, the system operators perform various actions and maneuvers so that the synchronization operation of the subsystems is successfully carried out and the system finally reaches acceptable stability. The most common of these actions include load control, generation control and, in some cases, changing the network topology. Although these maneuvers are simple and common, due to the weak network and extreme load changes, the restoration will be associated with low speed. One of the best ways to control the SPA is to use FACTS devices. By applying a soft control signal, these tools can reduce the SPA between two subsystems with more speed and accuracy, and the synchronization process can be done in less time. Meanwhile, the unified power controller (UPFC), a series-parallel compensator device with the change of transmission line power and proper adjustment of the phase angle, will be the proposed option in order to realize the subject of this research. Therefore, with the optimal placement of UPFC in a power system, in addition to improving the normal conditions of the system, it is expected to be effective in reducing the SPA during power system restoration. Therefore, the presented paper provides an optimal structure to coordinate the three problems of improving the division of subsystems, reducing the SPA and optimal power flow with the aim of determining the optimal location of UPFC and optimal subsystems. The proposed objective functions in this paper include maximizing the quality of the subsystems, reducing the SPA at the endpoints of the subsystems, and reducing the losses of the power system. Since there will be a possibility of creating contradictions in the simultaneous optimization of the proposed objective functions, the structure of the proposed optimization problem is introduced as a non-linear multi-objective problem, and the Pareto optimization method is used to solve it. The innovative technique proposed to implement the optimization process of the mentioned problem is an optimization algorithm called the water cycle (WCA). To evaluate the proposed method, the IEEE 39 bus power system will be used.

Keywords: UPFC, SPA, water cycle algorithm, multi-objective problem, pareto

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Authors: Azziz Assoumani, Francois Lestremau, Celine Ferret, Benedicte Lepot, Morgane Salomon, Helene Budzinski, Marie-Helene Devier, Pierre Labadie, Karyn Le Menach, Patrick Pardon, Laure Wiest, Emmanuelle Vulliet, Pierre-Francois Staub

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Seven French wastewater treatment plants (WWTP) were monitored for 53 contaminants of emerging concern within a nation-wide monitoring campaign in surface waters, which took place in 2018. The overall objective of the 2018 campaign was to provide the exercise of prioritization of emerging substances, which is being carried out in 2021, with monitoring data. This exercise should make it possible to update the list of relevant substances to be monitored (SPAS) as part of future water framework directive monitoring programmes, which will be implemented in the next water body management cycle (2022). One sampling campaign was performed in October 2018 in the seven WWTP, where affluent and sludge samples were collected. Surface water samples were collected in September 2018 at three to five sites upstream and downstream the point of effluent discharge of each WWTP. The contaminants (36 biocides and 17 surfactants, selected by the Prioritization Experts Committee) were determined in the seven WWTP effluent and sludge samples and in surface water samples by liquid or gas chromatography coupled with tandem mass spectrometry, depending on the contaminant. Nine surfactants and three biocides were quantified at least in one WWTP effluent sample. Linear alkylbenzene sulfonic acids (LAS) and fipronil were quantified in all samples; the LAS were quantified at the highest median concentrations. Twelve surfactants and 13 biocides were quantified in at least one sludge sample. The LAS and didecyldimethylammonium were quantified in all samples and at the highest median concentrations. Higher concentration levels of the substances quantified in WWTP effluent samples were observed in the surface water samples collected downstream the effluents discharge points, compared with the samples collected upstream, suggesting a contribution of the WWTP effluents in the contamination of surface waters.

Keywords: contaminants of emerging concern, effluent, monitoring, river water, sludge

Procedia PDF Downloads 141

Authors: Zaki Abiza, Miguel Chavez, David M. Holman, Ruddy Brionnaud

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In this paper, the prediction of the aerodynamic behavior of the flow around a Finned Projectile will be validated using a Computational Fluid Dynamics (CFD) solution, XFlow, based on the Lattice-Boltzmann Method (LBM). XFlow is an innovative CFD software developed by Next Limit Dynamics. It is based on a state-of-the-art Lattice-Boltzmann Method which uses a proprietary particle-based kinetic solver and a LES turbulent model coupled with the generalized law of the wall (WMLES). The Lattice-Boltzmann method discretizes the continuous Boltzmann equation, a transport equation for the particle probability distribution function. From the Boltzmann transport equation, and by means of the Chapman-Enskog expansion, the compressible Navier-Stokes equations can be recovered. However to simulate compressible flows, this method has a Mach number limitation because of the lattice discretization. Thanks to this flexible particle-based approach the traditional meshing process is avoided, the discretization stage is strongly accelerated reducing engineering costs, and computations on complex geometries are affordable in a straightforward way. The projectile that will be used in this work is the Army-Navy Basic Finned Missile (ANF) with a caliber of 0.03 m. The analysis will consist in varying the Mach number from M=0.5 comparing the axial force coefficient, normal force slope coefficient and the pitch moment slope coefficient of the Finned Projectile obtained by XFlow with the experimental data. The slope coefficients will be obtained using finite difference techniques in the linear range of the polar curve. The aim of such an analysis is to find out the limiting Mach number value starting from which the effects of high fluid compressibility (related to transonic flow regime) lead the XFlow simulations to differ from the experimental results. This will allow identifying the critical Mach number which limits the validity of the isothermal formulation of XFlow and beyond which a fully compressible solver implementing a coupled momentum-energy equations would be required.

Keywords: CFD, computational fluid dynamics, drag, finned projectile, lattice-boltzmann method, LBM, lift, mach, pitch

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Authors: Nimet Yildirim Tirgil, Ahmed Busnaina, April Z. Gu

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Environmental waters are monitored worldwide to protect people from infectious diseases primarily caused by enteric pathogens. All long, Escherichia coli (E. coli) is a good indicator for potential enteric pathogens in waters. Thus, a rapid and simple detection method for E. coli is very important to predict the pathogen contamination. In this study, to the best of our knowledge, as the first time we developed a rapid, direct and reusable SWCNTs (single walled carbon nanotubes) based biosensor system for sensitive and selective E. coli detection in water samples. We use a novel and newly developed flexible biosensor device which was fabricated by high-rate nanoscale offset printing process using directed assembly and transfer of SWCNTs. By simple directed assembly and non-covalent functionalization, aptamer (biorecognition element that specifically distinguish the E. coli O157:H7 strain from other pathogens) based SWCNTs biosensor system was designed and was further evaluated for environmental applications with simple and cost-effective steps. The two gold electrode terminals and SWCNTs-bridge between them allow continuous resistance response monitoring for the E. coli detection. The detection procedure is based on competitive mode detection. A known concentration of aptamer and E. coli cells were mixed and after a certain time filtered. The rest of free aptamers injected to the system. With hybridization of the free aptamers and their SWCNTs surface immobilized probe DNA (complementary-DNA for E. coli aptamer), we can monitor the resistance difference which is proportional to the amount of the E. coli. Thus, we can detect the E. coli without injecting it directly onto the sensing surface, and we could protect the electrode surface from the aggregation of target bacteria or other pollutants that may come from real wastewater samples. After optimization experiments, the linear detection range was determined from 2 cfu/ml to 10⁵ cfu/ml with higher than 0.98 R² value. The system was regenerated successfully with 5 % SDS solution over 100 times without any significant deterioration of the sensor performance. The developed system had high specificity towards E. coli (less than 20 % signal with other pathogens), and it could be applied to real water samples with 86 to 101 % recovery and 3 to 18 % cv values (n=3).

Keywords: aptamer, E. coli, environmental detection, nanobiosensor, SWCTs

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Authors: Sungeun Hyun, Sooin Lee, Gyewan Moon

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Work-Family Conflict has been an active research area for the past decades. Work-Family Conflict harms individuals and organizations, it is ultimately expected to bring the cost of losses to the company in the long run. WFC has mainly focused on effects of organizational effectiveness and job attitude such as Job Satisfaction, Organizational Commitment, and Turnover Intention variables. This study is different from consequence variable with previous research. For this purpose, we selected the positive job attitude 'Work Engagement' as a consequence of WFC. This research has its primary research purpose in identifying the negative effects of the Work-Family Conflict, and started out from the recognition of the problem that the research on the direct relationship on the influence of the WFC on Work Engagement is lacking. Based on the COR(Conservation of resource theory) and JD-R(Job Demand- Resource model), the empirical study model to examine the negative effects of WFC with Emotional Exhaustion as the link between WFC and Work Engagement was suggested and validated. Also, it was analyzed how much Positive Psychological Capital may buffer the negative effects arising from WFC within this relationship, and the Mediated Moderation model controlling the indirect effect influencing the Work Engagement by the Positive Psychological Capital mediated by the WFC and Emotional Exhaustion was verified. Data was collected by using questionnaires distributed to 500 employees engaged manufacturing, services, finance, IT industry, education services, and other sectors, of which 389 were used in the statistical analysis. The data are analyzed by statistical package, SPSS 21.0, SPSS macro and AMOS 21.0. The hierarchical regression analysis, SPSS PROCESS macro and Bootstrapping method for hypothesis testing were conducted. Results showed that all hypotheses are supported. First, WFC showed a negative effect on Work Engagement. Specifically, WIF appeared to be on more negative effects than FIW. Second, Emotional exhaustion found to mediate the relationship between WFC and Work Engagement. Third, Positive Psychological Capital showed to moderate the relationship between WFC and Emotional Exhaustion. Fourth, the effect of mediated moderation through the integration verification, Positive Psychological Capital demonstrated to buffer the relationship among WFC, Emotional Exhastion, and Work Engagement. Also, WIF showed a more negative effects than FIW through verification of all hypotheses. Finally, we discussed the theoretical and practical implications on research and management of the WFC, and proposed limitations and future research directions of research.

Keywords: emotional exhaustion, positive psychological capital, work engagement, work-family conflict

Procedia PDF Downloads 216

Authors: Olawale S. Fatoba, Stephen A. Akinlabi, Esther T. Akinlabi, Rezvan Gharehbaghi

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The performance of material surface under wear and corrosion environments cannot be fulfilled by the conventional surface modifications and coatings. Therefore, different industrial sectors need an alternative technique for enhanced surface properties. Titanium and its alloys possess poor tribological properties which limit their use in certain industries. This paper focuses on the effect of hybrid coatings Al-Cu-Fe on a grade five titanium alloy using laser metal deposition (LMD) process. Icosahedral Al-Cu-Fe as quasicrystals is a relatively new class of materials which exhibit unusual atomic structure and useful physical and chemical properties. A 3kW continuous wave ytterbium laser system (YLS) attached to a KUKA robot which controls the movement of the cladding process was utilized for the fabrication of the coatings. The titanium cladded surfaces were investigated for its hardness, corrosion and tribological behaviour at different laser processing conditions. The samples were cut to corrosion coupons, and immersed into 3.65% NaCl solution at 28oC using Electrochemical Impedance Spectroscopy (EIS) and Linear Polarization (LP) techniques. The cross-sectional view of the samples was analysed. It was found that the geometrical properties of the deposits such as width, height and the Heat Affected Zone (HAZ) of each sample remarkably increased with increasing laser power due to the laser-material interaction. It was observed that there are higher number of aluminum and titanium presented in the formation of the composite. The indentation testing reveals that for both scanning speed of 0.8 m/min and 1m/min, the mean hardness value decreases with increasing laser power. The low coefficient of friction, excellent wear resistance and high microhardness were attributed to the formation of hard intermetallic compounds (TiCu, Ti2Cu, Ti3Al, Al3Ti) produced through the in situ metallurgical reactions during the LMD process. The load-bearing capability of the substrate was improved due to the excellent wear resistance of the coatings. The cladded layer showed a uniform crack free surface due to optimized laser process parameters which led to the refinement of the coatings.

Keywords: Al-Cu-Fe coating, corrosion, intermetallics, laser metal deposition, Ti-6Al-4V alloy, wear resistance

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Authors: Rosa Tsegaye Aga, Xuan Jiang, Pavel Vazquez Faci, Siqing Liu, Simon Rayner, Endalkachew Alemu, Markos Abebe

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Tuberculosis (TB) is a major cause of disease globally. In most cases, TB is treatable and curable, but only with the proper treatment. There is a time when drug-resistant TB occurs when bacteria become resistant to the drugs that are used to treat TB. Current strategies to identify drug-resistant TB bacteria are laboratory-based, and it takes a longer time to identify the drug-resistant bacteria and treat the patient accordingly. But machine learning (ML) and data science approaches can offer new approaches to the problem. In this study, we propose to develop an ML-based model to predict the antibiotic resistance phenotypes of TB isolates in minutes and give the right treatment to the patient immediately. The study has been using the whole genome sequence (WGS) of TB isolates as training data that have been extracted from the NCBI repository and contain different countries’ samples to build the ML models. The reason that different countries’ samples have been included is to generalize the large group of TB isolates from different regions in the world. This supports the model to train different behaviors of the TB bacteria and makes the model robust. The model training has been considering three pieces of information that have been extracted from the WGS data to train the model. These are all variants that have been found within the candidate genes (F1), predetermined resistance-associated variants (F2), and only resistance-associated gene information for the particular drug. Two major datasets have been constructed using these three information. F1 and F2 information have been considered as two independent datasets, and the third information is used as a class to label the two datasets. Five machine learning algorithms have been considered to train the model. These are Support Vector Machine (SVM), Random forest (RF), Logistic regression (LR), Gradient Boosting, and Ada boost algorithms. The models have been trained on the datasets F1, F2, and F1F2 that is the F1 and the F2 dataset merged. Additionally, an ensemble approach has been used to train the model. The ensemble approach has been considered to run F1 and F2 datasets on gradient boosting algorithm and use the output as one dataset that is called F1F2 ensemble dataset and train a model using this dataset on the five algorithms. As the experiment shows, the ensemble approach model that has been trained on the Gradient Boosting algorithm outperformed the rest of the models. In conclusion, this study suggests the ensemble approach, that is, the RF + Gradient boosting model, to predict the antibiotic resistance phenotypes of TB isolates by outperforming the rest of the models.

Keywords: machine learning, MTB, WGS, drug resistant TB

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Authors: Shelley Harrington

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As a result of increasingly dynamic business environments, the creation and fostering of dynamic capabilities, [those capabilities that enable sustained competitive success despite of dynamism through the awareness and reconfiguration of internal and external competencies], supported by organisational learning [a dynamic capability] has gained increased and prevalent momentum in the research arena. Presenting findings funded by the Economic Social Research Council, this paper investigates the extent to which Senior Management Team (SMT) personality (at the trait and facet level) is associated with the creation of dynamic managerial capabilities at the team level, and effective organisational learning/knowledge sharing within the firm. In doing so, this research highlights the importance of micro-foundations in organisational psychology and specifically dynamic capabilities, a field which to date has largely ignored the importance of psychology in understanding these important and necessary capabilities. Using a direct measure of personality (NEO PI-3) at the trait and facet level across 32 high technology and finance firms in the UK, their CEOs (N=32) and their complete SMTs [N=212], a new measure of dynamic managerial capabilities at the team level was created and statistically validated for use within the work. A quantitative methodology was employed with regression and gap analysis being used to show the empirical foundations of personality being positioned as a micro-foundation of dynamic capabilities. The results of this study found that personality homogeneity within the SMT was required to strengthen the dynamic managerial capabilities of sensing, seizing and transforming, something which was required to reflect strong organisational learning at middle management level [N=533]. In particular, it was found that the greater the difference [t-score gaps] between the personality profiles of a Chief Executive Officer (CEO) and their complete, collective SMT, the lower the resulting self-reported nature of dynamic managerial capabilities. For example; the larger the difference between a CEOs level of dutifulness, a facet contributing to the definition of conscientiousness, and their SMT’s level of dutifulness, the lower the reported level of transforming, a capability fundamental to strategic change in a dynamic business environment. This in turn directly questions recent trends, particularly in upper echelons research highlighting the need for heterogeneity within teams. In doing so, it successfully positions personality as a micro-foundation of dynamic capabilities, thus contributing to recent discussions from within the strategic management field calling for the need to empirically explore dynamic capabilities at such a level.

Keywords: dynamic managerial capabilities, senior management teams, personality, dynamism

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Authors: A. Lianah, B. Peter Sopade, C. Krisantini

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Walikadep/Tetrastigma glabratum (Blume) Planch is a traditional herb that has been used by people of Blumah village; it is believed to have a stimulant effect and ailments for many illnesses. Our survey demonstrated that the people of Blumah village has exploited walikadep from Protected Forest of Mount Prau. More than 10% of 448 households at Blumah village have used walikadep as traditional herb or jamu. Part of the walikadep plants used is the liquid extract of the stem. The population of walikadep is getting scarce and it is rarely found now. The objectives of this study are to examine the stimulant effect of walikadep, to measure growth and exploitation rate of walikadep, and to find ways to effectively propagate the plants, as well as identifying the impact on the environment through field experiments and explorative survey. Stimulant effect was tested using open-field and hole-board test. Data were collected through field observation and experiment, and data were analysed using lab test and Anova. Rate of exploitation and plant growth was measured using Regression analysis; comparison of plant growth in-situ and ex-situ used descriptive analysis. The environmental impact was measured by population structure vegetation analysis method by Shannon Weinner. The study revealed that the walikadep exudates did not have a stimulant effect. Exploitation of walikadep and the long time required to reach harvestable size resulted in the scarcity of the plant in the natural habitat. Plant growth was faster in-situ than ex-situ; and fast growth was obtained from middle part cuttings treated with vermicompost. Biodiversity index after exploitation was higher than before exploitation, possibly due to the toxic and allellopathic effect (phenolics) of the plant. Based on these findings, further research is needed to examine the toxic effects of the leave and stem extract of walikadep and their allelopathic effects. We recommend that people of Blumah village to stop using walikadep as the stimulant. The local people, village government in the regional and central levels, and perhutani should do an integrated efforts to conserve walikadep through Pengamanan Terpadu Konservasi Walikadep Lestari (PTKWL) program, so this population of this plant in the natural habitat can be maintained.

Keywords: utilization, medical plants, traditional, Tetastigma glabratum

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Authors: Renato Morbidelli, Carla Saltalippi, Alessia Flammini, Marco Cifrodelli, Corrado Corradini

Abstract:

The trend of magnitude and frequency of extreme rainfalls seems to be different depending on the investigated area of the world. In this work, the impact of climate change on extreme rainfalls in Umbria, an inland region of central Italy, is examined using data recorded during the period 1921-2015 by 10 representative rain gauge stations. The study area is characterized by a complex orography, with altitude ranging from 200 to more than 2000 m asl. The climate is very different from zone to zone, with mean annual rainfall ranging from 650 to 1450 mm and mean annual air temperature from 3.3 to 14.2°C. Over the past 15 years, this region has been affected by four significant droughts as well as by six dangerous flood events, all with very large impact in economic terms. A least-squares linear trend analysis of annual maximums over 60 time series selected considering 6 different durations (1 h, 3 h, 6 h, 12 h, 24 h, 48 h) showed about 50% of positive and 50% of negative cases. For the same time series the non-parametrical Mann-Kendall test with a significance level 0.05 evidenced only 3% of cases characterized by a negative trend and no positive case. Further investigations have also demonstrated that the variance and covariance of each time series can be considered almost stationary. Therefore, the analysis on the magnitude of extreme rainfalls supplies the indication that an evident trend in the change of values in the Umbria region does not exist. However, also the frequency of rainfall events, with particularly high rainfall depths values, occurred during a fixed period has also to be considered. For all selected stations the 2-day rainfall events that exceed 50 mm were counted for each year, starting from the first monitored year to the end of 2015. Also, this analysis did not show predominant trends. Specifically, for all selected rain gauge stations the annual number of 2-day rainfall events that exceed the threshold value (50 mm) was slowly decreasing in time, while the annual cumulated rainfall depths corresponding to the same events evidenced trends that were not statistically significant. Overall, by using a wide available dataset and adopting simple methods, the influence of climate change on the heavy rainfalls in the Umbria region is not detected.

Keywords: climate changes, rainfall extremes, rainfall magnitude and frequency, central Italy

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