Search results for: Tool Integration

Authors: Mohammad Shahid Jamil

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In this study we have investigated students’ learning and satisfaction in one of the course offered in the Foundation Program at Qatar University. We implied innovative teaching methodology that emphasizes on enhancing students’ thinking skills, decision making, and problem solving skills. Some interesting results were found which can be used to further improve the teaching methodology. To make sure the full use of technology in Foundation Program at Qatar University has started implementing new ways of teaching Math course by using Blackboard as an innovative interactive tool to support standard teaching such as Discussion board, Virtual class, and Study plan in My Math Lab “MML”. In MML Study Plan is designed in such a way that the student can improve their skills wherever they face difficulties with in their Homework, Quiz or Test. Discussion board and Virtual Class are collaborative learning tools encourages students to engage outside of class time. These tools are useful to share students’ knowledge and learning experiences, promote independent and active learning and they helps students to improve their critical thinking skills through the learning process.

Keywords: blackboard, discussion board, critical thinking, active learning, independent learning, problem solving

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Authors: Bibiana Hlebova

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The Slovak Republic is a democratic and plural society consisting of people differing in language and culture, and its citizens should already be well prepared for the coexistence of multiple nations, nationalities or ethnic groups. Reflection on culture, art and literature of the Roma minority has taken on a new dimension in Slovakia in the past two decades when it comes to social, cultural and arts integration of this ethnic group with the plural society. Non-Roma view Roma as a specific ethnic group with their own culture, language, customs and traditions, social norms and coexistence that has retained archetypal qualities of Roma identity (romipen) in their real lives as well as in the literary world. Roma characters in works of art are specific and distinguishable from other literary characters simply by being Roma, that is, of a different origin and social status, they represent a different way of life, a distinctive hierarchy of values. The portrayal of Roma and the life of Roma ethnic group in the most dominant genre of Roma literature for children and youth, a Roma fairy tale (paramisi), can work as a suitable means to learn about, accept and tolerate the otherness of Roma in the conditions of school inclusion of students coming from the Roma ethnic group, and to support their identification with their own ethnic group and its cultural traditions. The paper aims to point out not only the specific nature of Roma identity (romipen) through the selected Roma fairy tale (paramisa) – Children of the Sun, but also the diversity of its uses in the educational process within primary education of pupils at elementary schools, advocating the philosophy of inclusive education. Through the suggestions of multi-cultural, emotional, and language and communication education of pupils through the work with the selected Roma fairy tale (paramisa), the author is exploring ways to overcome the issues stemming from the coexistence of Roma and Non-Roma pupils, which are burdened with prejudice, intolerance, aggression and racism on both sides, in the education process.

Keywords: inclusive education, otherness, Roma, Roma fairy tale, Roma identity

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Authors: Marianna Ciaccia, Gennaro Agrimi, Isabella Pisano, Maurizio Bettiga, Silvia Rapacioli, Giulia Mensa, Monica Marzagalli

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Objective: Untargeted metabolomic analysis of extracellular metabolites is a powerful approach that focuses on comprehensively profiling in the extracellular space. In this study, we applied extracellular metabolomic analysis to investigate the metabolism of two probiotic microorganisms with health benefits that extend far beyond the digestive tract and the immune system. Methods: Analytical techniques employed in extracellular metabolomic analysis encompass various technologies, including mass spectrometry (MS), which enables the identification of metabolites present in the fermentation media, as well as the comparison of metabolic profiles under different experimental conditions. Multivariate statistical analysis techniques like principal component analysis (PCA) or partial least squares-discriminant analysis (PLS-DA) play a crucial role in uncovering metabolic signatures and understanding the dynamics of metabolic networks. Results: Different types of supernatants from fermentation processes, such as dairy-free, not dairy-free media and media with no cells or pasteurized, were subjected to metabolite profiling, which contained a complex mixture of metabolites, including substrates, intermediates, and end-products. This profiling provided insights into the metabolic activity of the microorganisms. The integration of advanced software tools has facilitated the identification and characterization of metabolites in different fermentation conditions and microorganism strains. Conclusions: In conclusion, untargeted extracellular metabolomic analysis, combined with software tools, allowed the study of the metabolites consumed and produced during the fermentation processes of probiotic microorganisms. Ongoing advancements in data analysis methods will further enhance the application of extracellular metabolomic analysis in fermentation research, leading to improved bioproduction and the advancement of sustainable manufacturing processes.

Keywords: biotechnology, metabolomics, lactic bacteria, probiotics, postbiotics

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Authors: S. Chami, J. Chauvin, T. Demarest, Stan Ng, M. Straus, W. Jahner

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Biometrics tools such as fingerprint and iris are widely used in industry to protect critical assets. However, their vulnerability and lack of robustness raise several worries about the protection of highly critical assets. Biometrics based on Electrocardiographic (ECG) signals is a robust identification tool. However, most of the state-of-the-art techniques have worked on clinical signals, which are of high quality and less noisy, extracted from wearable devices like a smartwatch. In this paper, we are presenting a complete machine learning pipeline that identifies people using ECG extracted from an off-person device. An off-person device is a wearable device that is not used in a medical context such as a smartwatch. In addition, one of the main challenges of ECG biometrics is the variability of the ECG of different persons and different situations. To solve this issue, we proposed two different approaches: per person classifier, and one-for-all classifier. The first approach suggests making binary classifier to distinguish one person from others. The second approach suggests a multi-classifier that distinguishes the selected set of individuals from non-selected individuals (others). The preliminary results, the binary classifier obtained a performance 90% in terms of accuracy within a balanced data. The second approach has reported a log loss of 0.05 as a multi-class score.

Keywords: biometrics, electrocardiographic, machine learning, signals processing

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Authors: Soo Hyung Park, Seong Beom Kim, Wontae Lee, Jin Chul Joo, Jungmin Lee, Jongsoo Choi

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A newly-developed electromagnetically vibrated solid-phase microextraction (SPME) device for extracting nonpolar organic compounds from aqueous matrices was evaluated in terms of sorption equilibrium time, precision, and detection level relative to three other more conventional extraction techniques involving SPME, viz., static, magnetic stirring, and fiber insertion/retraction. Electromagnetic vibration at 300~420 cycles/s was found to be the most efficient extraction technique in terms of reducing sorption equilibrium time and enhancing both precision and linearity. The increased efficiency for electromagnetic vibration was attributed to a greater reduction in the thickness of the stagnant-water layer that facilitated more rapid mass transport from the aqueous matrix to the SPME fiber. Electromagnetic vibration less than 500 cycles/s also did not detrimentally impact the sustainability of the extracting performance of the SPME fiber. Therefore, electromagnetically vibrated SPME may be a more powerful tool for rapid sampling and solvent-free sample preparation relative to other more conventional extraction techniques used with SPME.

Keywords: electromagnetic vibration, organic compounds, precision, solid-phase microextraction (SPME), sorption equilibrium time

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Authors: Ntaganda J.M., Maniraguha J.D., Mukeshimana S., Harelimana D, Bizimungu T., Ruataganda E.

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This paper presents the design of Graphic User Interface (GUI) in Matlab as interaction tool between human and machine. The designed GUI can be used by medical doctors and other experts particularly the physiologists. Matlab packages and estimated parameters of the mathematical model of cardiovascular-respiratory system developed in Rwandan context are used in GUI. The ordinary differential equations (ODE’s) govern a mathematical model in designing GUI in Matlab and a window that sets model estimated parameters and the measured parameters by any user. For healthy subject, these measured parameters include heart rate, systolic blood and diastolic blood pressure, partial pressure of oxygen in arterial blood, partial pressure of carbon dioxide in arterial blood, concentration of bound and dissolved oxygen in the mixed venous blood entering the lungs, and concentration of bound and dissolved carbon dioxide in the mixed venous blood entering the lungs. The results of numerical test give a consistent appearance as empirically known results.

Keywords: Graphic User Interface, mathematical model, cardiovascur-respiratory system, walking physical activity, blood pressure, oxygen

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Authors: Zakheleni P. Dube, Phatu W. Mashela

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The Curve-fitting Allelochemical Response Data (CARD) model had been adopted as a valuable tool in enhancing the understanding of the efficacy of cucurbitacin-containing phytonematicides on the suppression of nematodes. In most cases, for registration purposes, the active ingredients should be in purified form. Evidence in other phytonematicides suggested that purified active ingredients were less effective in suppression of nematodes. The objective of this study was to use CARD model to compare the overall sensitivities of Meloidogyne incognita J2 hatch, mobility and mortality to Nemarioc-AL phytonematicides, cucurbitacin A, Nemafric-BL phytonematicide and cucurbitacin B. Meloidogyne incognita eggs and J2 were exposed to 0.00, 0.50, 1.00, 1.50, 2.00, 2.50, 3.00, 3.50, 4.00, 4.50 and 5.00% of each phytonematicide, whereas in purified form the concentrations were 0.00, 0.25, 0.50, 0.75, 1.00, 1.25, 1.50, 1.75, 2.00, 2.25 and 2.50 μg.mL⁻¹. The exposure period to each concentration was 24-, 48- and 72-h. The overall sensitivities of J2 hatch to Nemarioc-AL phytonematicide, cucurbitacin A, Nemafric-BL phytonematicide and cucurbitacin B were 1, 30, 5 and 2 units, respectively, whereas J2 mobiltity were 3, 17, 3 and 6 units, respectively. For J2 mortality overall sensitivities to Nemarioc-AL phytonematicide, cucurbitacin A, Nemafric-BL phytonematicide and cucurbitacin B were 2, 4, 1 and 4 units, respectively. In conclusion, the two crude extracts, Nemarioc-AL and Nemafric-BL phytonematicides were generally more potent to M. incognita compared to their pure active ingredients. The crude plant extract preparation is easy, and they could be an ideal tactic for the management of nematodes in resource poor farming communities.

Keywords: Botanicals, cucumin, leptodermin, plant extracts, triterpenoids

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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: Royia Soliman, Salma ElAnsary, Akram Amin Abdellatif, Florian Holzapfel

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Model-Based Safety Analysis (MBSA) is an approach in which the system and safety engineers share a common system model created using a model-based development process. The model can also be extended by the failure modes of the system components. There are two famous approaches for the addition of fault behaviors to system models. The first one is to enclose the failure into the system design directly. The second approach is to develop a fault model separately from the system model, thus combining both independent models for safety analysis. This paper introduces a hybrid approach of MBSA. The approach tries to use informal abstracted models to investigate failure behaviors. The approach will combine various concepts such as directed graph traversal, event lists and Constraint Satisfaction Problems (CSP). The approach is implemented using an Object Oriented programming language. The components are abstracted to its failure logic and relationships of connected components. The implemented approach is tested on various flight control systems, including electrical and multi-domain examples. The various tests are analyzed, and a comparison to different approaches is represented.

Keywords: flight control systems, model based safety analysis, safety assessment analysis, system modelling

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Authors: Dalin Si, Azizan Aziz, Bertrand Lasternas

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To encourage building owners to purchase electricity at the wholesale market and reduce building peak demand, this study aims to develop models that predict day-ahead hourly electricity consumption and demand using artificial neural network (ANN) and support vector machine (SVM). All prediction models are built in Python, with tool Scikit-learn and Pybrain. The input data for both consumption and demand prediction are time stamp, outdoor dry bulb temperature, relative humidity, air handling unit (AHU), supply air temperature and solar radiation. Solar radiation, which is unavailable a day-ahead, is predicted at first, and then this estimation is used as an input to predict consumption and demand. Models to predict consumption and demand are trained in both SVM and ANN, and depend on cooling or heating, weekdays or weekends. The results show that ANN is the better option for both consumption and demand prediction. It can achieve 15.50% to 20.03% coefficient of variance of root mean square error (CVRMSE) for consumption prediction and 22.89% to 32.42% CVRMSE for demand prediction, respectively. To conclude, the presented models have potential to help building owners to purchase electricity at the wholesale market, but they are not robust when used in demand response control.

Keywords: building energy prediction, data mining, demand response, electricity market

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Authors: Felix Olajide Ibikunle

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Introductory Statement: Sustainable participation of teenagers in sport requires deliberate and concerted plan and managerial policy rooted in the “philosophy of catch them young”. At risk, teenagers need proper integration into societal aspiration: This direction will go a long way to streamline them into the security breach and attractive nuisance free lifestyles. Basic Methodology: The population consists of children within 13-19 years old. A proportionate sampling size technique of 60% was adopted to select seven zones out of 11 geo-political zones in the Ibadan metropolis. Qualitative information and interview were used to collect needed information. Majority of the teenagers were out of school, street hawkers, motor pack, touts, and unserious vocation apprentices. These groups have the potentials of security breaches in the metropolis and beyond. Five hundred and thirty-four (534) respondents were used for the study. They were drawn from Ojoo, Akingbile, and Moniya axis = 72, Agbowo, Ajibode, and Apete axis = 74; Akobo, Basorun, and Idi-ape axis 79; Wofun, Monatan, and Iyana-Church axis = 78; Molete, Oke-ado and Oke-Bola axis = 75; Beere, Odinjo, Elekuro axis = 77; Eleyele, Ologuneru, and Alesinloye axis = 79. Major Findings: Multiple regression was used to analyze the independent variables and percentage. The respondents average age was 15.6 years old, and with 100% male. The instrument(questionnaire) used yielded; sport preference (r = 0.72); intervention (r = 0.68) and the sustainable participation (r = 0.70).The relative contributions of sport preference on participation of at risk teenagers was (F-ratio = 1.067); Intervention contribution of sport on participation of at risk teenagers = produced (F-ratio of 12.095) was significant while sustainable participation of at risk teenager produced (F-ratio = 1.062) was significant. Closing Statement: The respondents’ sport preference stimulated their participation in sport. The intervention exposed at risk-teenagers to coaching, which activated their interest and participation in sport. While sustainable participation contributed positively to evolve at risk teenagers participation in their preferred sport.

Keywords: sport, preference, intervention, teenagers, sustainable, participation and risk teenagers

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Authors: Shashank Kumar, Mansi Chandra, Ujjawal Singh, Parth Gupta, Rishi Ram, Arnab Sarkar

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Milk is one of the basic and primary sources of food and energy as we start consuming milk from birth. Hence, milk quality and purity and checking the concentration of its constituents become necessary steps. Considering the importance of the purity of milk for human health, the following study has been carried out to simultaneously detect and quantify the different adulterants like urea and starch in milk with the help of a paper-based microfluidic device integrated with a smartphone. The detection of the concentration of urea and starch is based on the principle of colorimetry. In contrast, the fluid flow in the device is based on the capillary action of porous media. The microfluidic channel proposed in the study is equipped with a specialized detection zone, and it employs a colorimetric indicator undergoing a visible color change when the milk gets in touch or reacts with a set of reagents which confirms the presence of different adulterants in the milk. In our proposed work, we have used iodine to detect the percentage of starch in the milk, whereas, in the case of urea, we have used the p-DMAB. A direct correlation has been found between the color change intensity and the concentration of adulterants. A calibration curve was constructed to find color intensity and subsequent starch and urea concentration. The device has low-cost production and easy disposability, which make it highly suitable for widespread adoption, especially in resource-constrained settings. Moreover, a smartphone application has been developed to detect, capture, and analyze the change in color intensity due to the presence of adulterants in the milk. The low-cost nature of the smartphone-integrated paper-based sensor, coupled with its integration with smartphones, makes it an attractive solution for widespread use. They are affordable, simple to use, and do not require specialized training, making them ideal tools for regulatory bodies and concerned consumers.

Keywords: paper based microfluidic device, milk adulteration, urea detection, starch detection, smartphone application

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Authors: A. Fettahoglu

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Theory of viscoelasticity is used by many researchers to represent behavior of many materials such as pavements on roads or bridges. Several researches used analytical methods and rheology to predict the material behaviors of simple models. Today, more complex engineering structures are analyzed using Finite Element Method, in which material behavior is embedded by means of three dimensional viscoelastic material laws. As a result, structures of unordinary geometry and domain like pavements of bridges can be analyzed by means of Finite Element Method and three dimensional viscoelastic equations. In the scope of this study, rheological models embedded in ANSYS, namely, generalized Maxwell elements and Prony series, which are two methods used by ANSYS to represent viscoelastic material behavior, are presented explicitly. Subsequently, a practical problem, which has an analytical solution given in literature, is used to verify the applicability of viscoelasticity tool embedded in ANSYS. Finally, amount of error in the results of ANSYS is compared with the analytical results to indicate the influence of used method and time step size.

Keywords: generalized Maxwell model, finite element method, prony series, time step size, viscoelasticity

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Authors: Jean-Jacques Randrianarimanana, Nassim Sebaibi, Mohamed Boutouil

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In order to solve problems associated with stormwater runoff in urban areas and their effects on natural and artificial water bodies, the integration of new technical solutions to the rainwater drainage becomes even more essential. Permeable pavement systems are one of the most widely used techniques. This paper presents a laboratory analysis of stormwater runoff hydraulic and pollutant removal performance of permeable pavement system using pervious pavements based on seashell products. The laboratory prototype is a square column of 25 cm of side and consists of the surface in pervious concrete, a bedding of 3 cm in height, a geotextile and a subbase layer of 50 cm in height. A series of constant simulated rain events using semi-synthetic runoff which varied in intensity and duration were carried out. The initial vertical saturated hydraulic conductivity of the entire pervious pavement system was 0.25 cm/s (148 L/m²/min). The hydraulic functioning was influenced by both the inlet flow rate value and the test duration. The total water losses including evaporation ranged between 9% to 20% for all hydraulic experiments. The temporal and vertical variability of the pollutant removal efficiency (PRE) of the system were studied for total suspended solids (TSS). The results showed that the PRE along the vertical profile was influenced by the size of the suspended solids, and the pervious paver has the highest capacity to trap pollutant than the other porous layers of the permeable pavement system after the geotextile. The TSS removal efficiency was about 80% for the entire system. The first-flush effect of TSS was observed, but it appeared only at the beginning (2 to 6 min) of the experiments. It has been shown that the PPS can capture first-flush. The project in which this study is integrated aims to contribute to both the valorization of shellfish waste and the sustainable management of rainwater.

Keywords: hydraulic, pervious concrete, pollutant removal efficiency, seashell by-products, stormwater runoff

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Authors: I. Chebbi, L. Boudaya, L. Neifar

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The bogue, Boops boops is an economically important fishery resource and commonly captured in the Mediterranean, and its diversity in parasites has been used as a tool to differentiate between stocks along with Tunisia since it is widely acceptable in fisheries management. In this study, a total of 90 fish are investigated from three localities off Tunisia, including Kelibia, Mahdia, and Zarzis. Fifteen species of parasites totaling 1270 individuals were harvested from B. boops, whereas ten parasites were used as biological tags. Based on Mahalanobis distance, each parasite species shows a great importance in the discrimination between groups. Tetraphyllidea larvae are the most influential parasites in determining the position of samples belonging to Kelibia. Monogenean species and Hysterothylacium sp. are the most important species for determining the position of samples from Mahdia. Specimens from Zarzis are characterized by the absence of the four Monogenean species and the Tetraphyllidea larvae. Parasites allocate B. boops population correctly to their origin communities with an accuracy of 83.3%. These results were corroborated by the discriminant analyses, highlighted the presence of three stocks, and improved that the parasitological method can be considered as a reliable key to provide imperative information for discriminating among B. boops stocks in Tunisian waters.

Keywords: biological marker, Boops boops, parasite, population structure

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Authors: Nahid Ehsani, Amir Hossein Rezvanfar

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The main objective of this study is to investigate psychological and socio-cultural factors effective on the tendency of the villagers to use e-banking services. The current paper is an applied study considering its objectives. The main data gathering tool in the current study is a made questionnaire which is designed and executed based on the conceptual background of the subject matter and the objectives and hypotheses of the study. The statistical population of this study includes all the customers of rural branches of Agricultural Bank in Ilam Province (N=82885). Among these 120 participants were chosen through sample size determination formula and they were studied using stratified random sampling method. In the analytical statistics level the results obtained from calculating Spearman’s Correlative Coefficient showed that socio-cultural and psychological factors had a significant impact of the extent of the tendency of the villagers to use e-banking services of the Agricultural Bank at the 99% level. Furthermore, stepwise multiple regression analysis showed that both sets of psychological factors as well as socio-economic factors were able to explain 50 percent of the variance of the independent variable; namely the tendency of villagers to use e-banking services.

Keywords: e-banking, agricultural bank, tendency, socio-economic factors, psychological factors

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Authors: Elias Akoury

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Nuclear Magnetic Resonance (NMR) spectroscopy is an indispensable technique used in structure determination of small and macromolecules to study their physical properties, elucidation of characteristic interactions, dynamics and thermodynamic processes. Quantum mechanics defines the theoretical description of NMR spectroscopy and treatment of the dynamics of nuclear spin systems. The phenomenon of residual dipolar coupling (RDCs) has become a routine tool for accurate structure determination by providing global orientation information of magnetic dipole-dipole interaction vectors within a common reference frame. This offers accessibility of distance-independent angular information and insights to local relaxation. The measurement of RDCs requires an anisotropic orientation medium for the molecules to partially align along the magnetic field. This can be achieved by introduction of liquid crystals or attaching a paramagnetic center. Although anisotropic paramagnetic tags continue to mark achievements in the biomolecular NMR of large proteins, its application in small organic molecules remains unspread. Here, we propose a strategy for the synthesis of a lanthanide tag and the measurement of RDCs in organic molecules using paramagnetic lanthanide complexes.

Keywords: lanthanide tags, NMR spectroscopy, residual dipolar coupling, quantum mechanics of spin dynamics

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Authors: Saeed M. Alshahrani

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This research integrated blockchain technology to reform medical records management in healthcare informatics. It was aimed at resolving the limitations of centralized systems by establishing a secure, decentralized, and user-centric platform. The system was architected with a sophisticated three-tiered structure, integrating advanced cryptographic methodologies, consensus algorithms, and the Fast Healthcare Interoperability Resources (HL7 FHIR) standard to ensure data security, transaction validity, and semantic interoperability. The research has profound implications for healthcare delivery, patient care, legal compliance, operational efficiency, and academic advancements in blockchain technology and healthcare IT sectors. The methodology adapted in this research comprises of Preliminary Feasibility Study, Literature Review, Design and Development, Cryptographic Algorithm Integration, Modeling the data and testing the system. The research employed a permissioned blockchain with a Practical Byzantine Fault Tolerance (PBFT) consensus algorithm and Ethereum-based smart contracts. It integrated advanced cryptographic algorithms, role-based access control, multi-factor authentication, and RESTful APIs to ensure security, regulate access, authenticate user identities, and facilitate seamless data exchange between the blockchain and legacy healthcare systems. The research contributed to the development of a secure, interoperable, and decentralized system for managing medical records, addressing the limitations of the centralized systems that were in place. Future work will delve into optimizing the system further, exploring additional blockchain use cases in healthcare, and expanding the adoption of the system globally, contributing to the evolution of global healthcare practices and policies.

Keywords: healthcare informatics, blockchain, medical records management, decentralized architecture, data security, cryptographic algorithms

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Authors: Vasiliki Stratidou

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Modern simulation mobile games have the potential to enhance students’ interest, motivation and creativity. Research conducted on the effectiveness of digital games for educational purposes has shown that such games are also ideal at providing an appropriate environment for language learning. The paper examines the issue of simulation mobile games in regard to the potential positive impacts on L2 vocabulary learning. Sixteen intermediate level students, aged 10-14, participated in the experimental study for four weeks. The participants were divided into experimental (8 participants) and control group (8 participants). The experimental group was planned to learn some new vocabulary words via digital games while the control group used a reading passage to learn the same vocabulary words. The study investigated the effect of mobile games as well as the traditional learning methods on Greek EFL learners’ vocabulary learning in a pre-test, an immediate post-test, and a two-week delayed retention test. A teacher’s diary and learners’ interviews were also used as tools to estimate the effectiveness of the implementation. The findings indicated that the experimental group outperformed the control group in acquiring new words through mobile games. Therefore, digital games proved to be an effective tool in learning English vocabulary.

Keywords: control group, digital games, experimental group, second language vocabulary learning, simulation games

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Authors: Neeraj Kumar Mishra, In Su Kim

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The isoindoline, indazole and indole heterocycles are ubiquitous structural motif found in heterocyclic compounds as they exhibit biological and medicinal applications. For example, isoindoline motif is present in molecules that act as endothelin-A receptor antagonists and dipeptidyl peptidase inhibitors. Moreover, isoindoline derivatives are very crucial constituents in the field of materials science as attractive candidates for organic light-emitting devices. However, compounds containing the indazole motif are known to exhibit to a variety of biological activities, such as estrogen receptor, HIV protease inhibition and anti-tumor activity. The prevalence of indazoles and indoles has led to the development of many useful methods for their preparation. Thus, isoindoline, indazole and indole heterocycles can be new candidates for the next generation of pharmaceuticals. Therefore, the development of highly efficient strategies for the formation of these heterocyclic architectures is an area of great interest in organic synthesis. The past years, transition-metal-catalyzed C−H activation followed by annulation reaction has been frequently used as a powerful tool to construct various heterocycles. Herein, we describe our recent achievements about the transition-metal-catalyzed tandem cyclization reactions of N-benzyltriflamides, 1,2-disubstituted arylhydrazines, acetanilides, etc. via C−H bond activation to access the corresponding bioactive heterocylic scaffolds.

Keywords: biologically active, C-H activation, heterocyclic compounds, transition-metal catalysts

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Authors: Abdulrahman Aljabri, Essam R. I. Mahmoud, Hamad Almohamedi, Zhengyi Jiang

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Cold rolled thin strip has received intensive attention through technological and theoretical progress in the rolling process, as well as researchers have focused on its control during rolling as an essential parameter for producing thinner strip with good shape and profile. An advanced approach has been proposed to analysis the thin strip profile in cold rolling of pair roll crossing and shifting mill using Finite Element Analysis (FEA) with an ALE technique. The ALE (Arbitrary Lagrangian-Eulerian) techniques to enable more flexibility of the ALE technique in the adjustment of the finite element mesh, which provides a significant tool for simulating the thin strip under realistic rolling process constraint and provide accurate model results. The FEA can provide theoretical basis for the 3D model of controlling the strip shape and profile in thin strip rolling, and deliver an optimal rolling process parameter, and suggest corrective changes during cold rolling of thin strip.

Keywords: pair roll crossing, work roll shifting, strip shape and profile, finite element modeling

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Authors: Ahmed Hamzi, Bryan Norman

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Having scribes help document patient records in electronic health record systems can improve hospitalists’ productivity. But hospitals need to determine the optimum number of scribes to hire to maximize scribe cost effectiveness. Scribe attendance uncertainty due to planned and unplanned absences is a primary challenge. This paper presents simulation and analytical models to determine the optimum number of scribes for a hospital to hire. Scribe staffing practices vary from one context to another; different staffing scenarios are considered where having extra attending scribes provides or does not provide additional value and utilizing on-call scribes to fill in for potentially absent scribes. These staffing scenarios are assessed for different scribe revenue ratios (ratio of the value of the scribe relative to scribe costs) ranging from 100% to 300%. The optimum solution depends on the absenteeism rate, revenue ratio, and desired service level. The analytical model obtains solutions easier and faster than the simulation model, but the simulation model is more accurate. Therefore, the analytical model’s solutions are compared with the simulation model’s solutions regarding both the number of scribes hired and cost-effectiveness. Additionally, an Excel tool has been developed to facilitate decision-makers in easily obtaining solutions using the analytical model.

Keywords: hospitalists, workload, optimization cost, economic analysis

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Authors: Hagen Stosnach

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The analytical demands on modern instruments for element analysis in food samples include the analysis of major, trace and ultra-trace essential elements as well as potentially toxic trace elements. In this study total reflection, X-ray fluorescence analysis (TXRF) is presented as an analytical technique, which meets the requirements, defined by the Association of Official Agricultural Chemists (AOAC) regarding the limit of quantification, repeatability, reproducibility and recovery for most of the target elements. The advantages of TXRF are the small sample mass required, the broad linear range from µg/kg up to wt.-% values, no consumption of gases or cooling water, and the flexible and easy sample preparation. Liquid samples like alcoholic or non-alcoholic beverages can be analyzed without any preparation. For solid food samples, the most common sample pre-treatment methods are mineralization, direct deposition of the sample onto the reflector without/with minimal treatment, mainly as solid suspensions or after extraction. The main disadvantages are due to the possible peaks overlapping, which may lower the accuracy of quantitative analysis and the limit in the element identification. This analytical technique will be presented by several application examples, covering a broad range of liquid and solid food types.

Keywords: essential elements, toxic metals, XRF, spectroscopy

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Authors: Samuel Nii Tackie, Oyebade K. Oyedotun, Ebenezer O. Olaniyi, Adnan Khashman

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Artificial neural networks have been used in different fields of artificial intelligence, and more specifically in machine learning. Although, other machine learning options are feasible in most situations, but the ease with which neural networks lend themselves to different problems which include pattern recognition, image compression, classification, computer vision, regression etc. has earned it a remarkable place in the machine learning field. This research exploits neural networks as a data mining tool in predicting the number of times a student repeats a course, considering some attributes relating to the course itself, the teacher, and the particular student. Neural networks were used in this work to map the relationship between some attributes related to students’ course assessment and the number of times a student will possibly repeat a course before he passes. It is the hope that the possibility to predict students’ performance from such complex relationships can help facilitate the fine-tuning of academic systems and policies implemented in learning environments. To validate the power of neural networks in data mining, Turkish students’ performance database has been used; feedforward and radial basis function networks were trained for this task; and the performances obtained from these networks evaluated in consideration of achieved recognition rates and training time.

Keywords: artificial neural network, data mining, classification, students’ evaluation

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Authors: Sarra Haouala, Issam Doghri

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In this work, a multiscale computational strategy is proposed for the analysis of structures, which are described at a refined level both in space and in time. The proposal is applied to two-phase viscoelastic-viscoplastic (VE-VP) reinforced thermoplastics subjected to large numbers of cycles. The main aim is to predict the effective long time response while reducing the computational cost considerably. The proposed computational framework is a combination of the mean-field space homogenization based on the generalized incrementally affine formulation for VE-VP composites, and the asymptotic time homogenization approach for coupled isotropic VE-VP homogeneous solids under large numbers of cycles. The time homogenization method is based on the definition of micro and macro-chronological time scales, and on asymptotic expansions of the unknown variables. First, the original anisotropic VE-VP initial-boundary value problem of the composite material is decomposed into coupled micro-chronological (fast time scale) and macro-chronological (slow time-scale) problems. The former is purely VE, and solved once for each macro time step, whereas the latter problem is nonlinear and solved iteratively using fully implicit time integration. Second, mean-field space homogenization is used for both micro and macro-chronological problems to determine the micro and macro-chronological effective behavior of the composite material. The response of the matrix material is VE-VP with J2 flow theory assuming small strains. The formulation exploits the return-mapping algorithm for the J2 model, with its two steps: viscoelastic predictor and plastic corrections. The proposal is implemented for an extended Mori-Tanaka scheme, and verified against finite element simulations of representative volume elements, for a number of polymer composite materials subjected to large numbers of cycles.

Keywords: asymptotic expansions, cyclic loadings, inclusion-reinforced thermoplastics, mean-field homogenization, time homogenization

Procedia PDF Downloads 348

Authors: Allaeddine Athmani, Abdelhacine Gouasmia, Tiago Ferreira, Romeu Vicente

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The seismic risk mitigation from the perspective of the old buildings stock is truly essential in Algerian urban areas, particularly those located in seismic prone regions, such as Annaba city, and which the old buildings present high levels of degradation associated with no seismic strengthening and/or rehabilitation concerns. In this sense, the present paper approaches the issue of the seismic vulnerability assessment of old masonry building stocks through the adaptation of a simplified methodology developed for a European context area similar to that of Annaba city, Algeria. Therefore, this method is used for the first level of seismic vulnerability assessment of the masonry buildings stock of the old city center of Annaba. This methodology is based on a vulnerability index that is suitable for the evaluation of damage and for the creation of large-scale loss scenarios. Over 380 buildings were evaluated in accordance with the referred methodology and the results obtained were then integrated into a Geographical Information System (GIS) tool. Such results can be used by the Annaba city council for supporting management decisions, based on a global view of the site under analysis, which led to more accurate and faster decisions for the risk mitigation strategies and rehabilitation plans.

Keywords: Damage scenarios, masonry buildings, old city center, seismic vulnerability, vulnerability index

Procedia PDF Downloads 432

Authors: Ruchika Yadav

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Street vendors are the integral component of urban economies of the world. They are the distributors of affordable goods and services and provide convenient and accessible retail options to the customers and form a vital part of the social and economic life of a city. A street vendor as an occupation existed for hundreds of years and considered to be as a cornerstone of many cities. In this paper, our objective is to analyze the socio-economic profile of street vendors, identification of their problems and to suggest remedial measures for the betterment based on the observation and suggestions of the street vendors. To conduct this study, primary data has been collected with the help of field survey and direct questionnaire to the respondents in Aligarh City which contains all the information relevant to social and economic conditions. The overall analysis of this study reveals street vendors are the backward sections of the society possess medium to the low-level standard of living due to illiteracy; their working environment and social security issues are not addressed properly. They are unaware of many of the governmental schemes launched for poverty alleviation and their poor accessibility in basic amenities leads to the backward socio-economic status in the society. The results found in this study can be very useful and helping tool for the policymakers to know the socio-economic conditions of the street vendors in detail.

Keywords: abject poverty, socio-economic conditions, street vendors, vulnerability

Procedia PDF Downloads 118

Authors: Ahmad Ali Shahid, Mukhtar Ahmed

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The demand for long staple fiber having better strength and length is increasing with the introduction of modern spinning and weaving industry in Pakistan. Work on gene discovery from developing cotton fibers has helped to identify dozens of genes that take part in cotton fiber development and several genes have been characterized for their role in fiber development. Sucrose synthase (SuS) is a key enzyme in the metabolism of sucrose in a plant cell, in cotton fiber it catalyzes a reversible reaction, but preferentially converts sucrose and UDP into fructose and UDP-glucose. UDP-glucose (UDPG) is a nucleotide sugar act as a donor for glucose residue in many glycosylation reactions and is essential for the cytosolic formation of sucrose and involved in the synthesis of cell wall cellulose. The study was focused on successful Agrobacterium-mediated stable transformation of SuS gene in pCAMBIA 1301 into cotton under a CaMV35S promoter. Integration and expression of the gene were confirmed by PCR, GUS assay, and real-time PCR. Young leaves of SuS overexpressing lines showed increased total soluble sugars and plant biomass as compared to non-transgenic control plants. Cellulose contents from fiber were significantly increased. SEM analysis revealed that fibers from transgenic cotton were highly spiral and fiber twist number increased per unit length when compared with control. Morphological data from field plants showed that transgenic plants performed better in field conditions. Incorporation of genes related to cotton fiber length and quality can provide new avenues for fiber improvement. The utilization of this technology would provide an efficient import substitution and sustained production of long-staple fiber in Pakistan to fulfill the industrial requirements.

Keywords: agrobacterium-mediated transformation, cotton fiber, sucrose synthase gene, staple length

Procedia PDF Downloads 216

Authors: Asna Anchalan, Anjana Bhagyanathan

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Urban green space plays an important role in providing health (physical and mental well-being), economic, and environmental benefits for urban residents and neighborhoods. Ensuring equitable distribution of urban green space is vital to ensure equal access to these benefits. This study is developing a methodology for assessing spatial equity of urban green spaces in the Indian context. Through a systematic literature review, the research trends, parameters, data, and tools being used are identified. After 2020, the research in this domain is increasing rapidly, where COVID-19 acted as a catalyst. Indian documents use various terminologies, definitions, and classifications of urban green spaces. The terminology, definition, and classification for this study are done after reviewing several Indian documents, master plans, and research papers. Parameters identified for assessing spatial equity are availability, proximity, accessibility, and socio-economic disparity. Criteria for evaluating each parameter were identified from diverse research papers. There is a research gap identified as a comprehensive approach encompassing all four parameters. The outcome of this study led to the development of a methodology that addresses the gaps, providing a practical tool applicable across diverse Indian cities.

Keywords: urban green space, spatial equity, accessibility, proximity, methodology

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Authors: Yvonne Dedzo

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Social media has become a powerful tool in bridging the distance between individuals regardless of their location. It has become a convenient platform for public discussion and, consequently, generated the phenomenon of citizen journalists who have become both proactive and reactive participants in the dissemination of news, information and other epochal and historical events. This phenomenon has fueled the growth of niche authorities who deliver exceptional democratically consequential information online. This study, therefore, investigates how some selected niche authorities maintain their status on social media. Using the selective processes theory, the study further interrogates the information shared by niche authorities and further analyses the extent to which a public interest-altruistic motive or personal interest-self-serving motive drives their agenda of new sharing and usage. Through cyber-ethnography and, qualitative content analysis and semi-structured interviews, data was gathered and analysed from the posts of two purposely selected niche authorities on Facebook and Twitter. The findings indicate that niche authorities maintain their status by being consistent, prompt, informative, resourceful and interactive in their postings on the social media platform. The study also discovered that even though niche authorities are motivated by both public interest-altruism and interest-self-serving, the latter had a higher of motivation than the former.

Keywords: social medida, citizen journalist, niche authorities, selective processes theory

Procedia PDF Downloads 46