Search results for: interlaminar damage model

Authors: A. Khosravi, S. Ghadirian, J. S. McCartney

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Evaluation of the seismic-induced settlement of an unsaturated soil layer depends on several variables, among which the small strain shear modulus, Gmax, and soil’s state of stress have been demonstrated to be of particular significance. Recent interpretation of trends in Gmax revealed considerable effects of the degree of saturation and hydraulic hysteresis on the shear stiffness of soils in unsaturated states. Accordingly, the soil layer is expected to experience different settlement behaviors depending on the soil saturation and seasonal weathering conditions. In this study, a semi-empirical formulation was adapted to extend an existing Gmax model to infer hysteretic effects along different paths of the SWRC including scanning curves. The suitability of the proposed approach is validated against experimental results from a suction-controlled resonant column test and from data reported in literature. The model was observed to follow the experimental data along different paths of the SWRC, and showed a slight hysteresis in shear modulus along the scanning curves.

Keywords: hydraulic hysteresis, scanning path, small strain shear modulus, unsaturated soil

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Authors: K. Shiba, T. Kaburagi, Y. Kurihara

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With global aging, people who require care, such as people with dementia (PwD), are increasing within many developed countries. And PwDs may wander and unconsciously set foot outdoors, it may lead serious accidents, such as, traffic accidents. Here, round-the-clock monitoring by caregivers is necessary, which can be a burden for the caregivers. Therefore, an automatic wandering detection system is required when an elderly person wanders outdoors, in which case the detection system transmits a ‘moving’ followed by an ‘absence’ state. In this paper, we focus on the transition from the ‘resting’ to the ‘absence’ state, via the ‘moving’ state as one of the wandering transitions. To capture the transition of the three states, our method based on the hidden Markov model (HMM) is built. Using our method, the restraint where the ‘resting’ state and ‘absence’ state cannot be transmitted to each other is applied. To validate our method, we conducted the experiment with 10 subjects. Our results show that the method can classify three states with 0.92 accuracy.

Keywords: wander, microwave Doppler sensor, respiratory frequency band, the state transition, hidden Markov model (HMM).

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Authors: A. Jourani, C. Trevisiol, S. Bouvier

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The aim of this work is to study the coupled effect of microstructure and surface roughness on friction coefficient, wear resistance and wear mechanisms. Friction tests on 35NCD16 steel are performed under different normal loads (50-110 N) on a pin-on-plane configuration at cyclic sliding with abrasive silicon carbide grains ranging from 35 µm to 200 µm. To vary hardness and microstructure, the specimens are subjected to water quenching and tempering at various temperatures from 200°C to 600°C. The evolution of microstructures and wear mechanisms of worn surfaces are analyzed using scanning electron microscopy (SEM). For a given microstructure and hardness, the friction coefficient decreases with increasing of normal load and decreasing of the abrasive particle size. The wear rate increase with increasing of normal load and abrasive particle size. The results also reveal that there is a critical hardness Hcᵣᵢₜᵢcₐₗ around 430 Hv which maximizes the friction coefficient and wear rate. This corresponds to a microstructure transition from martensite laths to carbides and equiaxed grains, for a tempering around 400°C. Above Hcᵣᵢₜᵢcₐₗ the friction coefficient and the amount of material loss decrease with an increase of hardness and martensite volume fraction. This study also shows that the debris size and the space between the abrasive particles decrease with a reduction in the particle size. The coarsest abrasive grains lost their cutting edges, accompanied by particle damage and empty space due to the particle detachment from the resin matrix. The compact packing nature of finer abrasive papers implicates lower particle detachment and facilitates the clogging and the transition from abrasive to adhesive wear.

Keywords: martensite, microstructure, friction, wear, surface roughness

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Authors: Rebeca V. Tholen, Elaine Bundy

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Background: Liver transplantation (LT) is considered the only curative treatment for end-stage liver disease Background: Liver transplantation (LT) is considered the only curative treatment for end-stage liver disease (ESLD). The effects of alcoholism can cause irreversible liver damage, cirrhosis and subsequent liver failure. Alcohol relapse after transplant occurs in 20-50% of patients and increases the risk for recurrent cirrhosis, organ rejection, and graft failure. Alcohol relapse after transplant has been identified as a problem among liver transplant recipients at a large urban academic transplant center in the United States. Transplantation will reverse the complications of ESLD, but it does not treat underlying alcoholism or reduce the risk of relapse after transplant. The purpose of this quality improvement project is to implement and evaluate the effectiveness of a High-Risk Alcoholism Relapse (HRAR) Scale to screen and identify patients at high-risk for alcohol relapse after receiving an LT. Methods: The HRAR Scale is a predictive tool designed to determine the severity of alcoholism and risk of relapse after transplant. The scale consists of three variables identified as having the highest predictive power for early relapse including, daily number of drinks, history of previous inpatient treatment for alcoholism, and the number of years of heavy drinking. All adult liver transplant recipients at a large urban transplant center were screened with the HRAR Scale prior to hospital discharge. A zero to two ordinal score is ranked for each variable, and the total score ranges from zero to six. High-risk scores are between three to six. Results: Descriptive statistics revealed 25 patients were newly transplanted and discharged from the hospital during an 8-week period. 40% of patients (n=10) were identified as being high-risk for relapse and 60% low-risk (n=15). The daily number of drinks were determined by alcohol content (1 drink = 15g of ethanol) and number of drinks per day. 60% of patients reported drinking 9-17 drinks per day, and 40% reported ≤ 9 drinks. 50% of high-risk patients reported drinking ≥ 25 years, 40% for 11-25 years, and 10% ≤ 11 years. For number of inpatient treatments for alcoholism, 50% received inpatient treatment one time, 20% ≥ 1, and 30% reported never receiving inpatient treatment. Findings reveal the importance and value of a validated screening tool as a more efficient method than other screening methods alone. Integration of a structured clinical tool will help guide the drinking history portion of the psychosocial assessment. Targeted interventions can be implemented for all high-risk patients. Conclusions: Our findings validate the effectiveness of utilizing the HRAR scale to screen and identify patients who are a high-risk for alcohol relapse post-LT. Recommendations to help maintain post-transplant sobriety include starting a transplant support group within the organization for all high-risk patients. (ESLD). The effects of alcoholism can cause irreversible liver damage, cirrhosis and subsequent liver failure. Alcohol relapse after transplant occurs in 20-50% of patients, and increases the risk for recurrent cirrhosis, organ rejection, and graft failure. Alcohol relapse after transplant has been identified as a problem among liver transplant recipients at a large urban academic transplant center in the United States. Transplantation will reverse the complications of ESLD, but it does not treat underlying alcoholism or reduce the risk of relapse after transplant. The purpose of this quality improvement project is to implement and evaluate the effectiveness of a High-Risk Alcoholism Relapse (HRAR) Scale to screen and identify patients at high-risk for alcohol relapse after receiving a LT. Methods: The HRAR Scale is a predictive tool designed to determine severity of alcoholism and risk of relapse after transplant. The scale consists of three variables identified as having the highest predictive power for early relapse including, daily number of drinks, history of previous inpatient treatment for alcoholism, and the number of years of heavy drinking. All adult liver transplant recipients at a large urban transplant center were screened with the HRAR Scale prior to hospital discharge. A zero to two ordinal score is ranked for each variable, and the total score ranges from zero to six. High-risk scores are between three to six. Results: Descriptive statistics revealed 25 patients were newly transplanted and discharged from the hospital during an 8-week period. 40% of patients (n=10) were identified as being high-risk for relapse and 60% low-risk (n=15). The daily number of drinks were determined by alcohol content (1 drink = 15g of ethanol) and number of drinks per day. 60% of patients reported drinking 9-17 drinks per day, and 40% reported ≤ 9 drinks. 50% of high-risk patients reported drinking ≥ 25 years, 40% for 11-25 years, and 10% ≤ 11 years. For number of inpatient treatments for alcoholism, 50% received inpatient treatment one time, 20% ≥ 1, and 30% reported never receiving inpatient treatment. Findings reveal the importance and value of a validated screening tool as a more efficient method than other screening methods alone. Integration of a structured clinical tool will help guide the drinking history portion of the psychosocial assessment. Targeted interventions can be implemented for all high-risk patients. Conclusions: Our findings validate the effectiveness of utilizing the HRAR scale to screen and identify patients who are a high-risk for alcohol relapse post-LT. Recommendations to help maintain post-transplant sobriety include starting a transplant support group within the organization for all high-risk patients.

Keywords: alcoholism, liver transplant, quality improvement, substance abuse

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Authors: P. Brunne, K. Ciechowska, K. Gajc, K. Gawin, M. Gawin, M. Kania, J. Kindracki, Z. Kusznierewicz, D. Pączkowska, F. Perczyński, K. Pilarski, D. Rafało, E. Ryszawa, M. Sobiecki, I. Uwarowa

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Big amount of space debris constitutes nowadays a real thread for operating space crafts; therefore the main purpose of PW-Sat2’ team was to create a system that could help cleanse the Earth’s orbit after each small satellites’ mission. After 4 years of development, the motorless, low energy consumption and low weight system has been created. During series of tests, the system has shown high reliable efficiency. The PW-Sat2’s deorbit system is a square-shaped sail which covers an area of 4m². The sail surface is made of 6 μm aluminized Mylar film which is stretched across 4 diagonally placed arms, each consisting of two C-shaped flat springs and enveloped in Mylar sleeves. The sail is coiled using a special, custom designed folding stand that provides automation and repeatability of the sail unwinding tests and placed in a container with inner diameter of 85 mm. In the final configuration the deorbit system weights ca. 600 g and occupies 0.6U (in accordance with CubeSat standard). The sail’s releasing system requires minimal amount of power based on thermal knife that burns out the Dyneema wire, which holds the system before deployment. The Sail is being pushed out of the container within a safe distance (20 cm away) from the satellite. The energy for the deployment is completely assured by coiled C-shaped flat springs, which during the release, unfold the sail surface. To avoid dynamic effects on the satellite’s structure, there is the rotational link between the sail and satellite’s main body. To obtain complete knowledge about complex dynamics of the deployment, a number of experiments have been performed in varied environments. The numerical model of the dynamics of the Sail’s deployment has been built and is still under continuous development. Currently, the integration of the flight model and Deorbit Sail is performed. The launch is scheduled for February 2018. At the same time, in cooperation with United Nations Office for Outer Space Affairs, sail models and requested facilities are being prepared for the sail deployment experiment under micro-gravity and low pressure conditions at Bremen Drop Tower, Germany. Results of those tests will provide an ultimate and wide knowledge about deployment in space environment to which system will be exposed during its mission. Outcomes of the numerical model and tests will be compared afterwards and will help the team in building a reliable and correct model of a very complex phenomenon of deployment of 4 c-shaped flat springs with surface attached. The verified model could be used inter alia to investigate if the PW-Sat2’s sail is scalable and how far is it possible to go with enlarging when creating systems for bigger satellites.

Keywords: cubesat, deorbitation, sail, space, debris

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Authors: Yousef Bakhbakhi

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Crystallization with supercritical fluids (SCFs), as a developed technology to produce particles of micron and sub-micron size with narrow size distribution, has found appreciable importance as an environmentally friendly technology. Particle synthesis using SCFs can be achieved employing a number of special processes involving solvent and antisolvent mechanisms. In this study, the compressed antisolvent (PCA) process is utilized as a model to analyze the theoretical complexity of crystallization with supercritical fluids. The population balance approach has proven to be an effectual technique to simulate and predict the particle size and size distribution. The nucleation and growth mechanisms of the particles formation in the PCA process is investigated using the population balance equation, which describes the evolution of the particle through coalescence and breakup levels with time. The employed mathematical population balance model contains a set of the partial differential equation with algebraic constraints, which demands a rigorous numerical approach. The combined Collocation and Galerkin finite element method are proposed as a high-resolution technique to solve the dynamics of the PCA process.

Keywords: particle formation, particle size and size distribution, PCA, supercritical carbon dioxide

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Authors: Venkata Narayana Chejarla, Nafisa Parvez Shaik, Gopi Vara Prasad Marabathula, Deva Kumar Bejjam

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Yoga is an advanced, well-recognized method with roots in Indian philosophy. Yoga benefits both the body and the psyche. Yoga is a regular exercise that helps people relax and sleep better while also enhancing their balance, endurance, and concentration. Yoga can be learned in a variety of settings, including at home with the aid of books and the internet as well as in yoga studios with the guidance of an instructor. Self-learning does not teach the proper yoga poses, and doing them without the right instruction could result in significant injuries. We developed "Online Yoga Asana Trainer using Deep Learning" so that people could practice yoga without a teacher. Our project is developed using Tensorflow, Movenet, and Keras models. The system makes use of data from Kaggle that includes 25 different yoga poses. The first part of the process involves applying the movement model for extracting the 17 key points of the body from the dataset, and the next part involves preprocessing, which includes building a pose classification model using neural networks. The system scores a 98.3% accuracy rate. The system is developed to work with live videos.

Keywords: yoga, deep learning, movenet, tensorflow, keras, CNN

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Authors: Manish Pandey, Gurinderjit Kaur, Meenu Talwar, Sachin Chauhan, Jagbir Gill

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Health-care management systems are a unit of nice connection as a result of the supply a straightforward and fast management of all aspects relating to a patient, not essentially medical. What is more, there are unit additional and additional cases of pathologies during which diagnosing and treatment may be solely allotted by victimization medical imaging techniques. With associate ever-increasing prevalence, medical pictures area unit directly acquired in or regenerate into digital type, for his or her storage additionally as sequent retrieval and process. Data Mining is the process of extracting information from large data sets through using algorithms and Techniques drawn from the field of Statistics, Machine Learning and Data Base Management Systems. Forecasting may be a prediction of what's going to occur within the future, associated it's an unsure method. Owing to the uncertainty, the accuracy of a forecast is as vital because the outcome foretold by foretelling the freelance variables. A forecast management should be wont to establish if the accuracy of the forecast is within satisfactory limits. Fuzzy regression strategies have normally been wont to develop shopper preferences models that correlate the engineering characteristics with shopper preferences relating to a replacement product; the patron preference models offer a platform, wherever by product developers will decide the engineering characteristics so as to satisfy shopper preferences before developing the merchandise. Recent analysis shows that these fuzzy regression strategies area units normally will not to model client preferences. We tend to propose a Testing the strength of Exponential Regression Model over regression toward the mean Model.

Keywords: health-care management systems, fuzzy regression, data mining, forecasting, fuzzy membership function

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Authors: Teodrose Atnafu Abegaze, P. K. Sharma

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In this study, an attempt has been made to study the behavior of breakthrough curves in both layered and mixed heterogeneous soil by conducting experiments in long soil columns. Sodium chloride has been used as a conservative tracer in the experiment. Advective dispersive transport equations, including equilibrium sorption and first-order degradation coefficients, are used for solute transport through mobile-immobile porous media. In order to do the governing equation for solute transport, there are explicit and implicit schemes for our condition; we use an implicit scheme to numerically model the solute concentration. Results of experimental breakthrough curves indicate that the behavior of observed breakthrough curves is approximately similar in both cases of layered and mixed soil, while earlier arrival of solute concentration is obtained in the case of mixed soil. It means that the types of heterogeneity of the soil media affect the behavior of solute concentration. Finally, it is also shown that the asymptotic dispersion model simulates the experimental data better than the constant and linear distance-dependent dispersion models.

Keywords: numerical method, distance dependant dispersion, reactive transport, experiment

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Authors: M. Macchiaroli, V. Pellecchia, L. Dolores

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The water supply for production users (craft, commercial, industrial), understood as the set of water supply and wastewater collection services becomes an increasingly felt problem in a water scarcity regime. In fact, disputes are triggered between the different social parties for the fair and efficient use of water resources. Within this aspect, the problem arises of the different pricing of services between civil users and production users. Of particular interest is the question of defining the tariff classes depending on consumption levels. If for civil users, this theme is strongly permeated by social profiles (a topic dealt with by the author in a forthcoming research contribution) connected with the inalienability of the right to have water and with the reconciliation of the needs of the weakest groups of the population, for consumers in the production sector the logic adopted by the manager may be inspired by criteria of greater corporate rationality. This work illustrates the Italian regulatory framework and shows an optimization model of tariff classes in the production sector that reconciles the public objective of sustainable use of the resource and the needs of a production system in search of recovery after the depressing effects caused by COVID-19 pandemic.

Keywords: decision making, economic evaluation, urban water management, water tariff

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Authors: Milad Gholizadeh

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Asthma and chronic obstructive pulmonary disease (COPD) are very shared inflammatory diseases of the airlines. They togethercause airway tapering and are cumulative in occurrence throughout the world, imposing huge burdens on health care. It is currently recognized that some asthmatic inflammation is neutrophilic, controlled by the TH17 subset of helper T cells, and that some eosinophilic inflammation is controlled by type 2 innate lymphoid cells (ILC2 cells) temporary together with basophils. Patients who have plain asthma or are asthmatic patients who smoke with topographies of COPD-induced inflammation and might advantage from treatments targeting neutrophils, countingmacrolides, CXCR2 antagonists, phosphodiesterase 4 inhibitors, p38 mitogen-activating protein kinase inhibitors, and antibodies in contradiction of IL-1 and IL-17.Viral and bacterial infections, not only reason acute exacerbations of COPD, but also intensify and continue chronic inflammation in steady COPD through pathogen-associated molecular patterns. Present treatment plans are absorbed on titration of inhaled therapies such as long-acting bronchodilators, with cumulative interest in the usage of beleaguered biologic therapies meant at the underlying inflammatory devices. Educationssuggest that the mucosal IgA reply is abridged in COPD, and a lacking conveyance of IgA across the bronchial epithelium in COPD has been recognized, perhaps involving neutrophil proteinases, which may damage the Ig receptor mediating this transepithelialdirection-finding. Future instructions for investigation will emphasis elucidating the diverse inflammatory signatures foremost to asthma and chronic obstrucive, the development of reliable analytic standards and biomarkers of illness, and refining the clinical organization with an eye toward targeted therapies.

Keywords: imminology, asthma, COPD, CXCR2 antagonists

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Authors: Osman Mohamed

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Over the past two decades, the global interest in the rights of persons with disabilities (PWDs) has increased that resulted in the United Nations Convention on the Rights of Persons with Disabilities (UNCRPWDs). In this regard, the Gulf States have witnessed remarkable efforts towards strengthening the rights of persons with disabilities, including enactment of laws and establishment of specialized government councils for the Persons with Disabilities. This study aims to highlight the efforts of Shafallah Foundation in strengthening the rights of persons with disabilities as a model for the Gulf States. The researcher will conduct interviews with officials at Shafallah Foundation, some persons with disabilities who have benefited from the Foundation's programmes, officials from government agencies related to Persons with disabilities. The study is expected to reveal the role of Shafallah Foundation in implementing the UNCRPWDs through its programmes and activities as well as an overview of the situation of the rights of PWDs in the Gulf States. The study is important for stakeholders, decision-makers, policy-makers, academics, and the disability’s organizations.

Keywords: GCC, Gulf Cooperation Council, Shafallah Foundation, UNCRPWDs, United Nations Convention on the Rights of Persons with Disabilities, PWDs, persons with disabilities

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Authors: Wade Ghribi, Abdelmoty M. Ahmed, Ahmed Said Badawy, Belgacem Bouallegue

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In higher education institutions, the most pressing priority is to improve student performance and retention. Large volumes of student data are used in Educational Data Mining techniques to find new hidden information from students' learning behavior, particularly to uncover the early symptom of at-risk pupils. On the other hand, data with noise, outliers, and irrelevant information may provide incorrect conclusions. By identifying features of students' data that have the potential to improve performance prediction results, comparing and identifying the most appropriate ensemble learning technique after preprocessing the data, and optimizing the hyperparameters, this paper aims to develop a reliable students' performance prediction model for Higher Education Institutions. Data was gathered from two different systems: a student information system and an e-learning system for undergraduate students in the College of Computer Science of a Saudi Arabian State University. The cases of 4413 students were used in this article. The process includes data collection, data integration, data preprocessing (such as cleaning, normalization, and transformation), feature selection, pattern extraction, and, finally, model optimization and assessment. Random Forest, Bagging, Stacking, Majority Vote, and two types of Boosting techniques, AdaBoost and XGBoost, are ensemble learning approaches, whereas Decision Tree, Support Vector Machine, and Artificial Neural Network are supervised learning techniques. Hyperparameters for ensemble learning systems will be fine-tuned to provide enhanced performance and optimal output. The findings imply that combining features of students' behavior from e-learning and students' information systems using Majority Vote produced better outcomes than the other ensemble techniques.

Keywords: educational data mining, student performance prediction, e-learning, classification, ensemble learning, higher education

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Authors: Basiliyos Tilahun Betru, Charles Awono Onana, Bernabe Batchakui

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Recommender systems have become increasingly popular in recent years, and are utilized in numerous areas. Nowadays many web services provide several information for users and recommender systems have been developed as critical element of these web applications to predict choice of preference and provide significant recommendations. With the help of the advantage of deep learning in modeling different types of data and due to the dynamic change of user preference, building a deep model can better understand users demand and further improve quality of recommendation. In this paper, deep neural network models for recommender system are evaluated. Most of deep neural network models in recommender system focus on the classical collaborative filtering user-item setting. Deep learning models demonstrated high level features of complex data can be learned instead of using metadata which can significantly improve accuracy of recommendation. Even though deep learning poses a great impact in various areas, applying the model to a recommender system have not been fully exploited and still a lot of improvements can be done both in collaborative and content-based approach while considering different contextual factors.

Keywords: big data, decision making, deep learning, recommender system

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Authors: Charles Horace Ampong

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Non-linear models have been found to be useful in modeling the elasticity (measure of degree of responsiveness) of a dependent variable with respect to a set of independent variables ceteris paribus. This constant elasticity principle was applied to the dependent variable (Compressive Strength of Concrete in MPa) which was found to be non-linearly related to the independent variable (Water-Cement ratio in kg/m3) for given Ages of Concrete in days (3, 7, 28) at different levels of admixtures Superplasticizer (in kg/m3), Blast Furnace Slag (in kg/m3) and Fly Ash (in kg/m3). The levels of the admixtures were categorized as: S1=Some Plasticizer added & S0=No Plasticizer added; B1=some Blast Furnace Slag added & B0=No Blast Furnace Slag added; F1=Some Fly Ash added & F0=No Fly Ash added. The number of observations (samples) used for the research was one-hundred and thirty-two (132) in all. For Superplasticizer, it was found that Compressive Strength of Concrete was more elastic with regards to Water-Cement ratio at S1 level than at S0 level for the given ages of concrete 3, 7and 28 days. For Blast Furnace Slag, Compressive Strength with regards to Water-Cement ratio was more elastic at B0 level than at B1 level for concrete ages 3, 7 and 28 days. For Fly Ash, Compressive Strength with regards to Water-Cement ratio was more elastic at B0 level than at B1 level for Ages 3, 7 and 28 days. The research also tested for different combinations of the levels of Superplasticizer, Blast Furnace Slag and Fly Ash. It was found that Compressive Strength elasticity with regards to Water-Cement ratio was lowest (Elasticity=-1.746) with a combination of S0, B0 and F0 for concrete age of 3 days. This was followed by Elasticity of -1.611 with a combination of S0, B0 and F0 for a concrete of age 7 days. Next, the highest was an Elasticity of -1.414 with combination of S0, B0 and F0 for a concrete age of 28 days. Based on preceding outcomes, three (3) non-linear model equations for predicting the output elasticity of Compressive Strength of Concrete (in %) or the value of Compressive Strength of Concrete (in MPa) with regards to Water to Cement was formulated. The model equations were based on the three different ages of concrete namely 3, 7 and 28 days under investigation. The three models showed that higher elasticity translates into higher compressive strength. And the models revealed a trend of increasing concrete strength from 3 to 28 days for a given amount of water to cement ratio. Using the models, an increasing modulus of elasticity from 3 to 28 days was deduced.

Keywords: concrete, compressive strength, elasticity, water-cement

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Authors: Jan Van Uden

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The paper reviews classical agency-theory and its contributions to the analysis of complex business negotiations and gives an approach for the modification of the basic agency-model in order to examine the negotiation specific dimensions of agency-problems. By illustrating fundamental potentials for the modification of agency-theory in context of business negotiations the paper highlights recent empirical research that investigates agent-based negotiations and inter-team constellations. A general theoretical analysis of complex negotiation would be based on a two-level approach. First, the modification of the basic agency-model in order to illustrate the organizational context of business negotiations (i.e., multi-agent issues, common-agencies, multi-period models and the concept of bounded rationality). Second, the application of the modified agency-model on complex business negotiations to identify agency-problems and relating areas of risk in the negotiation process. The paper is placed on the first level of analysis – the modification. The method builds on the one hand on insights from behavior decision research (BRD) and on the other hand on findings from agency-theory as normative directives to the modification of the basic model. Through neoclassical assumptions concerning the fundamental aspects of agency-relationships in business negotiations (i.e., asymmetric information, self-interest, risk preferences and conflict of interests), agency-theory helps to draw solutions on stated worst-case-scenarios taken from the daily negotiation routine. As agency-theory is the only universal approach able to identify trade-offs between certain aspects of economic cooperation, insights obtained provide a deeper understanding of the forces that shape business negotiation complexity. The need for a modification of the basic model is illustrated by highlighting selected issues of business negotiations from agency-theory perspective: Negotiation Teams require a multi-agent approach under the condition that often decision-makers as superior-agents are part of the team. The diversity of competences and decision-making authority is a phenomenon that overrides the assumptions of classical agency-theory and varies greatly in context of certain forms of business negotiations. Further, the basic model is bound to dyadic relationships preceded by the delegation of decision-making authority and builds on a contractual created (vertical) hierarchy. As a result, horizontal dynamics within the negotiation team playing an important role for negotiation success are therefore not considered in the investigation of agency-problems. Also, the trade-off between short-term relationships within the negotiation sphere and the long-term relationships of the corporate sphere calls for a multi-period perspective taking into account the sphere-specific governance-mechanisms already established (i.e., reward and monitoring systems). Within the analysis, the implementation of bounded rationality is closely related to findings from BRD to assess the impact of negotiation behavior on underlying principal-agent-relationships. As empirical findings show, the disclosure and reservation of information to the agent affect his negotiation behavior as well as final negotiation outcomes. Last, in context of business negotiations, asymmetric information is often intended by decision-makers acting as superior-agents or principals which calls for a bilateral risk-approach to agency-relations.

Keywords: business negotiations, agency-theory, negotiation analysis, interteam negotiations

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Authors: Salma Baig, Bakrudeen Ali Ahmad, Ainnul Hamidah Syahadah Azizan, Hapipah Mohd Ali, Elham Rouhollahi, Mahmood Ameen Abdulla

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Free radical damage induced by reactive oxygen species (ROS) contributes to etiology of many chronic diseases, cancer being one of them. Recent studies have been successful in ROS targeted therapies via antioxidants using mouse models in cancer therapeutics. The present study was designed to scrutinize anticancer activity, antioxidant activity of 5 different extracts of Thymus serpyllum in MDA-MB-231, MCF-7, HepG2, HCT-116, PC3, and A549. Identification of the phytochemicals present in the most active extract of Thymus serpyllum was conducted using gas chromatography coupled with mass spectrophotometry and antioxidant activity was measured by using DPPH radical scavenging and FRAP assay. Anticancer impact of the extract in terms of IC50 was evaluated using MTT cell viability assay. Results revealed that the hexane extract showed the best anticancer activity in HepG2 (Liver Carcinoma Cell Line) with an IC50 value of 23 ± 0.14 µg/ml followed by 25 µg/ml in HCT-116 (Colon Cancer Cell Line), 30 µm/ml in MCF-7 (Breast Cancer Cell Line), 35 µg/ml in MDA-MB-231 (Breast Cancer Cell Line), 57 µg/ml in PC3 (Prostate Cancer Cell Line) and 60 µg/ml in A549 (Lung Carcinoma Cell Line). GC-MS profile of the hexane extract showed the presence of 31 compounds with carvacrol, thymol and thymoquione being the major compounds. Phenolics such as Vitamin E, terpinen-4-ol, borneol and phytol were also identified. Hence, here we present the first report on cytotoxicity of hexane extract of Thymus serpyllum extract in HepG2 cell line with a robust anticancer activity with an IC50 of 23 ± 0.14 µg/ml.

Keywords: Thymus serpyllum L., hexane extract, GC-MS profile, antioxidant activity, anticancer activity, HepG2 cell line

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Authors: Renalda El Samra, Elie Bou-Zeid, Hamza Kunhu Bangalath, Georgiy Stenchikov, Mutasem El Fadel

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The regional-scale impact of climate change over complex terrain was examined through high-resolution dynamic downscaling conducted using the Weather Research and Forecasting (WRF) model, with initial and boundary conditions from a High-Resolution Atmospheric Model (HiRAM). The analysis was conducted over the eastern Mediterranean, with a focus on the country of Lebanon, which is characterized by a challenging complex topography that magnifies the effect of orographic precipitation. Four year-long WRF simulations, selected based on HiRAM time series, were performed to generate future climate projections of extreme temperature and precipitation over the study area under the conditions of the Representative Concentration Pathway (RCP) 4.5. One past WRF simulation year, 2008, was selected as a baseline to capture dry extremes of the system. The results indicate that the study area might be exposed to a temperature increase between 1.0 and 3ºC in summer mean values by 2050, in comparison to 2008. For extreme years, the decrease in average annual precipitation may exceed 50% at certain locations in comparison to 2008.

Keywords: HiRAM, regional climate modeling, WRF, Representative Concentration Pathway (RCP)

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Authors: Frista Dearetha Marasabessy, Usep Suhud, Mohammad Rizan

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The study objective was to compare influencing factors on customer retention of two brands – SimPATI and IM3 – of telecommunication services owned by Telkomsel and Indosat, two giant mobile telecommunication providers in Indonesia. The authors applied predictor variables including perceived tariff, perceived quality, switching barriers, and customer satisfaction. These variables were used after reviewing literature in quantitative studies on consumer behaviour relating to telecommunication services. This study used indicators adopted and adapted from literature. The quantitative data were gathered in Jakarta, involving 205 subscribers of SimPATI and 202 subscribers of IM3. The authors selected respondents purposively. Data were analysed using both exploratory and confirmatory factor analyses. Two fitted models were developed confirming factors that were involved in customer retention as stated on the proposed model: perceived tariff, perceived quality, switching barriers, and customer satisfaction. However, parts of the hypotheses were rejected.

Keywords: customer retention, switching barriers, telecommunication providers, structural equation model, SimPATI, IM3, Indonesia

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Authors: Seyed Saeid Tabaee, Omid Bahar

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Nowadays, using energy dissipation devices has been commonly used in structures. A high rate of energy absorption during earthquakes is the benefit of using such devices, which results in damage reduction of structural elements specifically columns. The hysteretic damping capacity of energy dissipation devices is the key point that it may adversely complicate analysis and design of such structures. This effect may be generally represented by equivalent viscous damping. The equivalent viscous damping may be obtained from the expected hysteretic behavior under the design or maximum considered displacement of a structure. In this paper, the hysteretic damping coefficient of a steel moment resisting frame (MRF), which its performance is enhanced by a buckling restrained brace (BRB) system has been evaluated. Having the foresight of damping fraction between BRB and MRF is inevitable for seismic design procedures like Direct Displacement-Based Design (DDBD) method. This paper presents an approach to calculate the damping fraction for such systems by carrying out the dynamic nonlinear time history analysis (NTHA) under harmonic loading, which is tuned to the natural frequency of the system. Two steel moment frame structures, one equipped with BRB, and the other without BRB are simultaneously studied. The extensive analysis shows that proportion of each system damping fraction may be calculated by its shear story portion. In this way, the contribution of each BRB in the floors and their general contribution in the structural performance may be clearly recognized, in advance.

Keywords: buckling restrained brace, direct displacement based design, dual systems, hysteretic damping, moment resisting frames

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Authors: Emrah Ayhan, Puspa Saananta Irfani, Ömer Doğukan Şahin

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Public services, which are important for the order and continuity of social life, have begun to transform into electronic services (E-service) with the development of information and communication technologies in recent years. In particular, as a result of the widespread use of the internet and the increase in citizen demands, it has become necessary to provide public services electronically. In addition to facilitating traditional public services, new types of e-services strengthen the interaction, cooperation, accessibility, transparency, citizen participation (e-governance) and accountability between citizens and the state. In this context, the factors in the literature that are considered to influence the citizens’ satisfaction towards e-services will be examined through the example of student satisfaction with the e-services (Anasis, Mergen, E-mail, library, cafeteria and other transactions) offered by Anadolu University (Eskişehir, Türkiye) through university website and mobile application. The data for the analysis will be obtained from the survey research that will be used to measure user satisfaction with university e-services of 1,000 students studying at 9 different faculties and graduate schools of Anadolu University. These data will be analyzed with a unique methodology that uses the E-GovQual model and Importance Performance Analysis (IPA) methods together. The e-GovQual model serves as a framework for evaluating the quality of e-services, allowing a detailed understanding of students' perceptions. On the other hand, the IPA method will be used to determine the performance level of Anadolu University in the provision of e-services and to understand the areas that require improvement and student expectations. Strategic goals and suggestions will be made to decision-makers, students, and researchers in line with the findings obtained in the research. Thus, it is planned to contribute to e-governance and user satisfaction in educational institutions and to reveal practical implications for optimizing online platforms to better serve student needs.

Keywords: e-service, Anadolu university, student satisfaction, e-governance, e-govqual, importance performance analysis

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Authors: Sergo Esadze

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Seismic resistance norms require calculation of cantilevers on vertical components of the base seismic acceleration. Long span cantilevers, as a rule, must be calculated as a separate construction element. According to the architectural-planning solution, functional purposes and environmental condition of a designing buildings/structures, long span cantilever construction may be of very different types: both by main bearing element (beam, truss, slab), and by material (reinforced concrete, steel). A choice from these is always linked with bearing construction system of the building. Research of vertical seismic vibration of these constructions requires individual approach for each (which is not specified in the norms) in correlation with model of seismic load. The latest may be given both as deterministic load and as a random process. Loading model as a random process is more adequate to this problem. In presented paper, two types of long span (from 6m – up to 12m) reinforcement concrete cantilever beams have been considered: a) bearing elements of cantilevers, i.e., elements in which they fixed, have cross-sections with large sizes and cantilevers are made with haunch; b) cantilever beam with load-bearing rod element. Calculation models are suggested, separately for a) and b) types. They are presented as systems with finite quantity degree (concentrated masses) of freedom. Conditions for fixing ends are corresponding with its types. Vertical acceleration and vertical component of the angular acceleration affect masses. Model is based on assumption translator-rotational motion of the building in the vertical plane, caused by vertical seismic acceleration. Seismic accelerations are considered as random processes and presented by multiplication of the deterministic envelope function on stationary random process. Problem is solved within the framework of the correlation theory of random process. Solved numerical examples are given. The method is effective for solving the specific problems.

Keywords: cantilever, random process, seismic load, vertical acceleration

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Authors: Seyi Olalekan Olawuyi, Abbyssiania Mushunje

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The potential benefits of agricultural production to improve the welfare condition of smallholder farmers in developing countries is no more a news because it has been widely documented. Yet majority of these farming households suffer from shortfall in production output to meet both the consumption needs and market demand which adversely affects output market participation and by extension welfare condition. Therefore, this study investigated the impacts of output market participation on households’ welfare of cassava-based farmers in Oyo State, Nigeria. Multistage sampling technique was used to select 324 sample size used for this study. The findings from the data obtained and analyzed through composite score and crosstab analysis revealed that there is varying degree of output market participation among the farmers which also translate to the observed welfare profile differentials in the study area. The probit model analysis with respect to the selection equation identified gender of household head, household size, access to remittance, off-farm income and ownership of farmland as significant drivers of output market participation in the study area. Furthermore, the treatment effect model of the welfare equation and propensity score matching (PSM) technique were used as robust checks; and the findings attest to the fact that, complimentarily with other significant variables highlighted in this study, output market participation indeed has a significant impact on farming households’ welfare. As policy implication inferences, the study recommends female active inclusiveness and empowerment in farming activities, birth control strategies, secondary income smoothing activities and discouragement of land fragmentation habits, to boost productivity and output market participation, which by extension can significantly improve farming households’ welfare.

Keywords: Cassava market participation, households' welfare, propensity score matching, treatment effect model

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Authors: Kh. Dehkordi, R. Sharifi Gholam, S. Arshadi

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Objective: Oxidative stress is produced under diabetic conditions and possibly causes various forms of tissue damage inpatients with diabetes. Antioxidants defend against the harmful effect of free radicals, which are associated with heart disease, cancer, arthritis, aging and many other diseases1). Antioxidants are very stable molecules capable of neutralizing free radicals by donating an electron to them.The aim of this study was to examine the effect of swimming training, fenugreek seed extract and glibenclamide on plasma glucose and cardiac antioxidants activity in diabetic rats. Design: For this purpose, fifty male wistar rats were divided into five groups, two groups of control rats (diabetic control [DC] and healthy control [HC]), one group of endurance swimming training (EST), one group of fenugreek seed extract highdose (F1, 1.74 g/kg b.w), one group of fenugreek seed extract middle dose (F2, 0.87 g/kg b.w), one group of glibenclamide (G, 0.5 mg/kg b.w). Materials and Methods: Diabetes induced by streptozotocine (STZ), data was analyzed using the one-way ANOVA followed by a Tukey test. Significance level was 0.05. Results: All of the groups' exception of HC showed significant decrease in body weight (P < 0.05), but the diabetic control and swimming training group exhibited a more decrease. All of the groups have shown a significant decrease in plasma glucose than DC group (P < 0.05) but this reduction was more in G group than DC no HC group. S, G and HC groups have shown significant increase in cardiac antioxidant than DC group (P < 0.05) but there wasn't significant difference in other groups (P > 0.05). Conclusion: The present results indicate that regular swimming training lead to decrease in plasma glucose and enhanced cardiac antioxidants in diabetic rats.

Keywords: swimming, glucose, cardiac, antioxidants

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Authors: Anjali Uday, Yuting Wang, Andres Alfonso Pena Olare

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The Discrete Element Method is a promising approach to modeling microscopic behaviors of granular materials. The quality of the simulations however depends on the model parameters utilized. The present study focuses on calibration and validation of the discrete element parameters for Cuxhaven sand based on the experimental data from triaxial and oedometer tests. A sensitivity analysis was conducted during the sample preparation stage and the shear stage of the triaxial tests. The influence of parameters like rolling resistance, inter-particle friction coefficient, confining pressure and effective modulus were investigated on the void ratio of the sample generated. During the shear stage, the effect of parameters like inter-particle friction coefficient, effective modulus, rolling resistance friction coefficient and normal-to-shear stiffness ratio are examined. The calibration of the parameters is carried out such that the simulations reproduce the macro mechanical characteristics like dilation angle, peak stress, and stiffness. The above-mentioned calibrated parameters are then validated by simulating an oedometer test on the sand. The oedometer test results are in good agreement with experiments, which proves the suitability of the calibrated parameters. In the next step, the calibrated and validated model parameters are applied to forecast the micromechanical behavior including the evolution of contact force chains, buckling of columns of particles, observation of non-coaxiality, and sample inhomogeneity during a simple shear test. The evolution of contact force chains vividly shows the distribution, and alignment of strong contact forces. The changes in coordination number are in good agreement with the volumetric strain exhibited during the simple shear test. The vertical inhomogeneity of void ratios is documented throughout the shearing phase, which shows looser structures in the top and bottom layers. Buckling of columns is not observed due to the small rolling resistance coefficient adopted for simulations. The non-coaxiality of principal stress and strain rate is also well captured. Thus the micromechanical behaviors are well described using the calibrated and validated material parameters.

Keywords: discrete element model, parameter calibration, triaxial test, oedometer test, simple shear test

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Authors: Muñiz-Lino Marcos Agustín, Vazquez Borbolla Jessica, Licéaga-Escalera Carlos

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The ectomesenchymal tissues involved in tooth development and their remnants are the origin of different odontogenic lesions, including tumors and cysts of the jaws, with a wide range of clinical behaviors. Dentigerous cyst (DC) represents approximately 20% of all cases of odontogenic cysts, and it has been demonstrated that it can develop benign and malignant odontogenic tumors. DC is characterized by bone destruction of the area surrounding the crown of a tooth which has not erupted and it contain is liquid. The treatment of odontogenic tumors and cysts usually are partial or total removal of the jaw, causing important secondary co-morbidities. However, molecules implicated in DC pathogenesis as well in its development to odontogenic tumors remains unknown. A cellular model may be useful to study these molecules, but that model has not been established yet. Here, we reported the establishment of a cell culture derived from a dentigerous cyst. This cell line was named DeCy-1. In spite of its ectomesenchymal morphology, DeCy-1 cells express epithelial markers such as cytokeratins 5, 6, and 8. Furthermore, these cells express the ODAM protein, which is present in odontogenesis and in dental follicle, indicating that DeCy-1 cells derived from odontogenic epithelium. Analysis by electron microscopy of this cell line showed that it has a high vesicular activity, suggesting that DeCy-1 could secrete molecules that may be involved in DC pathogenesis. Thus, secreted proteins were analyzed by PAGE-SDS, where we observed approximately 11 bands. In addition, the capacity of these secretions to degrade proteins was analyzed by gelatin substrate zymography. A degradation band of about 62 kDa was found in these assays. Western blot assays suggested that the matrix metalloproteinase 2 (MMP-2) is responsible of this protease activity. Thus, our results indicate that the establishment of a cell line derived from DC is a useful in vitro model to study the biology of this odontogenic lesion and its participation in the development of odontogenic tumors.

Keywords: dentigerous cyst, MMP20, cancer, cell culture

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Authors: Yasaswi Palagummi, Sareh Rowlands

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Generalised Zero-Shot Learning, often known as GZSL, is an advanced variant of zero-shot learning in which the samples in the unseen category may be either seen or unseen. GZSL methods typically have a bias towards the seen classes because they learn a model to perform recognition for both the seen and unseen classes using data samples from the seen classes. This frequently leads to the misclassification of data from the unseen classes into the seen classes, making the task of GZSL more challenging. In this work of ours, to solve the GZSL problem, we propose an approach leveraging the Shifted Window based Self-Attention in the Swin Transformer (Swin-GZSL) to work in the inductive GSZL problem setting. We run experiments on three popular benchmark datasets: CUB, SUN, and AWA2, which are specifically used for ZSL and its other variants. The results show that our model based on Swin Transformer has achieved state-of-the-art harmonic mean for two datasets -AWA2 and SUN and near-state-of-the-art for the other dataset - CUB. More importantly, this technique has a linear computational complexity, which reduces training time significantly. We have also observed less bias than most of the existing GZSL models.

Keywords: generalised, zero-shot learning, inductive learning, shifted-window attention, Swin transformer, vision transformer

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Authors: Chyi Jaw

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Prior literature on innovation diffusion or acceptance has almost exclusively concentrated on consumers’ positive attitudes and behaviors for new products/services. Consumers’ negative attitudes or behaviors to innovations have received relatively little marketing attention, but it happens frequently in practice. This study discusses consumer psychological factors when they try to learn or use new technologies. According to recent research, technological innovation acceptance has been considered as a dynamic or mediated process. This research argues that consumers can experience inertia and emotions in the initial use of new technologies. However, given such consumer psychology, the argument can be made as to whether the inclusion of consumer inertia (routine seeking and cognitive rigidity) and emotions increases the predictive power of new technology acceptance model. As data from the empirical study find, the process is potentially consumer emotion changing (independent of performance benefits) because of technology complexity and consumer inertia, and impact innovative technology use significantly. Finally, the study presents the superior predictability of the hypothesized model, which let managers can better predict and influence the successful diffusion of complex technological innovations.

Keywords: cognitive rigidity, consumer emotions, new technology acceptance, routine seeking, technology complexity

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Authors: Jill Villarreal, Kristalyn Cooksey, Kai Lloyd, Daniel Ha

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Little research has been conducted to examine college students' reading attitudes, including students' perceptions of reading behaviors and reading abilities. This is problematic, as reading assigned course material is a critical component to an undergraduate student's academic success. For this study, flyers were electronically disseminated to instructors at 24 public and 10 private U.S. institutions in “Reading-Intensive Departments” including Psychology, Sociology, Education, Business, and Communications. We requested the online survey be completed as an in-class activity during the fall 2019 and spring 2020 semesters. All participants voluntarily completed the questionnaire anonymously. Of the participants, 280 self-identified their race as Black and 280 self-identified their race as White. Of the participants, 177 self-identified their gender as Male and 383 self-identified their Gender as Female. Participants ranged in age from 18-24. Factor analysis found four dimensions resulting from the questions regarding reading. The first we interpret as “Reading Proficiency”, accounted for 19% of the variability. The second dimension was “Reading Anxiety” (15%), the third was “Textbook Reading Ability” (9%), and the fourth was “Reading Enjoyment” (8%). Linear models on each of these dimensions revealed no effect of Age, Gender, Race, or Income on “Reading proficiency”. The linear model of “Reading Anxiety” showed a significant effect of race (p = 0.02), with higher anxiety in white students, as well as higher reading anxiety in female students (p < 0.001). The model of “Textbook Reading Ability” found a significant effect of race (p < 0.001), with higher textbook problems in white students. The model of “Reading Enjoyment” showed significant effects of race (p = 0.013) with more enjoyment for white students, gender (p = 0.001) with higher enjoyment for female students, and age (p = 0.033) with older students showing higher enjoyment. These findings suggest that gender, age, and race are important factors in many aspects of college students' reading attitudes. Further research will investigate possible causes for these differences. In addition, the effectiveness of college-level programs to reduce reading anxiety, promote the reading of textbooks, and foster a love of reading will be assessed.

Keywords: age, college, gender, race, reading

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Authors: Muhammad Faisal, Zai-Jin You, Muhammad Naeem

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Concerns about the environment, public health, and the economy are raised by the fact that the world produces around 6 trillion cigarettes annually. Arguably the most pervasive forms of environmental litter, this dangerous trash must be eliminated. The researchers wanted to get an idea of how much pollution is seeping out of cigarette butts in metropolitan areas by studying their distribution and concentration. In order to accomplish this goal, the cigarette butt pollution indicator was applied in 29 different areas. The locations were monitored monthly for a full calendar year. The conditions for conducting the investigation of the venues were the same on both weekends and during the weekdays. By averaging the metal leakage ratio in various climates and the average weight of cigarette butts, we were able to estimate the total amount of heavy metal leakage. The findings revealed that the annual average value of the index for the areas that were investigated ranged from 1.38 to 10.4. According to these numbers, just 27.5% of the areas had a low pollution rating, while 43.5% had a major pollution status or worse. Weekends witnessed the largest fall (31% on average) in all locations' indices, while spring and summer saw the largest increase (26% on average) compared to autumn and winter. It was calculated that the average amount of heavy metals such as Cr, Cu, Cd, Zn, and Pb that seep into the environment from discarded cigarette butts in commercial, residential, and park areas, respectively, is 0.25 µg/m2, 0.078 µg/m2, and 0.18 µg/m2. Butt from cigarettes is one of the most prevalent forms of litter in the area that was examined. This litter is the origin of a wide variety of contaminants, including heavy metals. This toxic garbage poses a significant risk to the city.

Keywords: heavy metal, hazardous waste, waste management, litter

Procedia PDF Downloads 63