Search results for: teaching and learning effectiveness
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 11453

Search results for: teaching and learning effectiveness

4673 Tip60 Histone Acetyltransferase Activators as Neuroepigenetic Therapeutic Modulators for Alzheimer’s Disease

Authors: Akanksha Bhatnagar, Sandhya Kortegare, Felice Elefant

Abstract:

Context: Alzheimer's disease (AD) is a neurodegenerative disorder that is characterized by progressive cognitive decline and memory loss. The cause of AD is not fully understood, but it is thought to be caused by a combination of genetic, environmental, and lifestyle factors. One of the hallmarks of AD is the loss of neurons in the hippocampus, a brain region that is important for memory and learning. This loss of neurons is thought to be caused by a decrease in histone acetylation, which is a process that regulates gene expression. Research Aim: The research aim of the study was to develop mall molecule compounds that can enhance the activity of Tip60, a histone acetyltransferase that is important for memory and learning. Methodology/Analysis: The researchers used in silico structural modeling and a pharmacophore-based virtual screening approach to design and synthesize small molecule compounds strongly predicted to target and enhance Tip60’s HAT activity. The compounds were then tested in vitro and in vivo to assess their ability to enhance Tip60 activity and rescue cognitive deficits in AD models. Findings: The researchers found that several of the compounds were able to enhance Tip60 activity and rescue cognitive deficits in AD models. The compounds were also developed to cross the blood-brain barrier, which is an important factor for the development of potential AD therapeutics. Theoretical Importance: The findings of this study suggest that Tip60 HAT activators have the potential to be developed as therapeutic agents for AD. The compounds are specific to Tip60, which suggests that they may have fewer side effects than other HDAC inhibitors. Additionally, the compounds are able to cross the blood-brain barrier, which is a major hurdle for the development of AD therapeutics. Data Collection: The study collected data from a variety of sources, including in vitro assays and animal models. The in vitro assays assessed the ability of compounds to enhance Tip60 activity using histone acetyltransferase (HAT) enzyme assays and chromatin immunoprecipitation assays. Animal models were used to assess the ability of the compounds to rescue cognitive deficits in AD models using a variety of behavioral tests, including locomotor ability, sensory learning, and recognition tasks. The human clinical trials will be used to assess the safety and efficacy of the compounds in humans. Questions: The question addressed by this study was whether Tip60 HAT activators could be developed as therapeutic agents for AD. Conclusions: The findings of this study suggest that Tip60 HAT activators have the potential to be developed as therapeutic agents for AD. The compounds are specific to Tip60, which suggests that they may have fewer side effects than other HDAC inhibitors. Additionally, the compounds are able to cross the blood-brain barrier, which is a major hurdle for the development of AD therapeutics. Further research is needed to confirm the safety and efficacy of these compounds in humans.

Keywords: Alzheimer's disease, cognition, neuroepigenetics, drug discovery

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4672 An Algorithm for Determining the Arrival Behavior of a Secondary User to a Base Station in Cognitive Radio Networks

Authors: Danilo López, Edwin Rivas, Leyla López

Abstract:

This paper presents the development of an algorithm that predicts the arrival of a secondary user (SU) to a base station (BS) in a cognitive network based on infrastructure, requesting a Best Effort (BE) or Real Time (RT) type of service with a determined bandwidth (BW) implementing neural networks. The algorithm dynamically uses a neural network construction technique using the geometric pyramid topology and trains a Multilayer Perceptron Neural Networks (MLPNN) based on the historical arrival of an SU to estimate future applications. This will allow efficiently managing the information in the BS, since it precedes the arrival of the SUs in the stage of selection of the best channel in CRN. As a result, the software application determines the probability of arrival at a future time point and calculates the performance metrics to measure the effectiveness of the predictions made.

Keywords: cognitive radio, base station, best effort, MLPNN, prediction, real time

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4671 Whale Optimization Algorithm for Optimal Reactive Power Dispatch Solution Under Various Contingency Conditions

Authors: Medani Khaled Ben Oualid

Abstract:

Most of researchers solved and analyzed the ORPD problem in the normal conditions. However, network collapses appear in contingency conditions. In this paper, ORPD under several contingencies is presented using the proposed method WOA. To ensure viability of the power system in contingency conditions, several critical cases are simulated in order to prevent and prepare the power system to face such situations. The results obtained are carried out in IEEE 30 bus test system for the solution of ORPD problem in which control of bus voltages, tap position of transformers and reactive power sources are involved. Moreover, another method, namely, Particle Swarm Optimization with Time Varying Acceleration Coefficient (PSO-TVAC) has been compared with the proposed technique. Simulation results indicate that the proposed WOA gives remarkable solution in terms of effectiveness in case of outages.

Keywords: optimal reactive power dispatch, metaheuristic techniques, whale optimization algorithm, real power loss minimization, contingency conditions

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4670 Incorporating Information Gain in Regular Expressions Based Classifiers

Authors: Rosa L. Figueroa, Christopher A. Flores, Qing Zeng-Treitler

Abstract:

A regular expression consists of sequence characters which allow describing a text path. Usually, in clinical research, regular expressions are manually created by programmers together with domain experts. Lately, there have been several efforts to investigate how to generate them automatically. This article presents a text classification algorithm based on regexes. The algorithm named REX was designed, and then, implemented as a simplified method to create regexes to classify Spanish text automatically. In order to classify ambiguous cases, such as, when multiple labels are assigned to a testing example, REX includes an information gain method Two sets of data were used to evaluate the algorithm’s effectiveness in clinical text classification tasks. The results indicate that the regular expression based classifier proposed in this work performs statically better regarding accuracy and F-measure than Support Vector Machine and Naïve Bayes for both datasets.

Keywords: information gain, regular expressions, smith-waterman algorithm, text classification

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4669 Model-Based Control for Piezoelectric-Actuated Systems Using Inverse Prandtl-Ishlinskii Model and Particle Swarm Optimization

Authors: Jin-Wei Liang, Hung-Yi Chen, Lung Lin

Abstract:

In this paper feedforward controller is designed to eliminate nonlinear hysteresis behaviors of a piezoelectric stack actuator (PSA) driven system. The control design is based on inverse Prandtl-Ishlinskii (P-I) hysteresis model identified using particle swarm optimization (PSO) technique. Based on the identified P-I model, both the inverse P-I hysteresis model and feedforward controller can be determined. Experimental results obtained using the inverse P-I feedforward control are compared with their counterparts using hysteresis estimates obtained from the identified Bouc-Wen model. Effectiveness of the proposed feedforward control scheme is demonstrated. To improve control performance feedback compensation using traditional PID scheme is adopted to integrate with the feedforward controller.

Keywords: the Bouc-Wen hysteresis model, particle swarm optimization, Prandtl-Ishlinskii model, automation engineering

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4668 Factors Affecting Attitude of Community Pharmacists Towards Locally Manufactured Pharmaceutical Products in Addisababa: A Cross-sectional Study

Authors: Gelila Tamyalew, Asres Abitie

Abstract:

Community Pharmacists (CPs) have a significant part in consumer choice in the rational use of LMPPs. The opinion of pharmacists regarding branded and generic medications can offer a perception of the potential obstacles that might have to be overcome to advance generic medicine utilization. Many factors affect CPs' attitudes negatively toward LMPPs. Therefore, the current study assessed factors that can affect CPs' attitudes toward LMPPs. In the regression analysis of variables, three variables were associated with CPs' attitudes toward LMPPs. These are; maximum educational status, professional status, and year of experience in community pharmacy practice. Moreover, lack of belief in LMPPs, substitution agreement with the prescriber, cost-effectiveness of LMPPs, and consumer preference/demand were the most influencing reasons for the selection of LMPPs. In conclusion, the attitude of CPs seems suboptimal that requires an intervention to optimize LMPP utilization.

Keywords: locally manufactured pharmaceutical products, attitude, community pharmacist, Ethiopia

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4667 An Approach to Autonomous Drones Using Deep Reinforcement Learning and Object Detection

Authors: K. R. Roopesh Bharatwaj, Avinash Maharana, Favour Tobi Aborisade, Roger Young

Abstract:

Presently, there are few cases of complete automation of drones and its allied intelligence capabilities. In essence, the potential of the drone has not yet been fully utilized. This paper presents feasible methods to build an intelligent drone with smart capabilities such as self-driving, and obstacle avoidance. It does this through advanced Reinforcement Learning Techniques and performs object detection using latest advanced algorithms, which are capable of processing light weight models with fast training in real time instances. For the scope of this paper, after researching on the various algorithms and comparing them, we finally implemented the Deep-Q-Networks (DQN) algorithm in the AirSim Simulator. In future works, we plan to implement further advanced self-driving and object detection algorithms, we also plan to implement voice-based speech recognition for the entire drone operation which would provide an option of speech communication between users (People) and the drone in the time of unavoidable circumstances. Thus, making drones an interactive intelligent Robotic Voice Enabled Service Assistant. This proposed drone has a wide scope of usability and is applicable in scenarios such as Disaster management, Air Transport of essentials, Agriculture, Manufacturing, Monitoring people movements in public area, and Defense. Also discussed, is the entire drone communication based on the satellite broadband Internet technology for faster computation and seamless communication service for uninterrupted network during disasters and remote location operations. This paper will explain the feasible algorithms required to go about achieving this goal and is more of a reference paper for future researchers going down this path.

Keywords: convolution neural network, natural language processing, obstacle avoidance, satellite broadband technology, self-driving

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4666 Effectiveness of Imagery Compared with Exercise Training on Hip Abductor Strength and EMG Production in Healthy Adults

Authors: Majid Manawer Alenezi, Gavin Lawrence, Hans-Peter Kubis

Abstract:

Imagery training could be an important treatment for muscle function improvements in patients who are facing limitations in exercise training by pain or other adverse symptoms. However, recent studies are mostly limited to small muscle groups and are often contradictory. Moreover, a possible bilateral transfer effect of imagery training has not been examined. We, therefore, investigated the effectiveness of unilateral imagery training in comparison with exercise training on hip abductor muscle strength and EMG. Additionally, both limbs were assessed to investigate bilateral transfer effects. Healthy individuals took part in an imagery or exercise training intervention for two weeks and were assesses pre and post training. Participants (n=30), after randomization into an imagery and an exercise group, trained 5 times a week under supervision with additional self-performed training on the weekends. The training consisted of performing, or to imagine, 5 maximal isometric hip abductor contractions (= one set), repeating the set 7 times. All measurements and trainings were performed laying on the side on a dynamometer table. The imagery script combined kinesthetic and visual imagery with internal perspective for producing imagined maximal hip abduction contractions. The exercise group performed the same number of tasks but performing the maximal hip abductor contractions. Maximal hip abduction strength and EMG amplitudes were measured of right and left limbs pre- and post-training period. Additionally, handgrip strength and right shoulder abduction (Strength and EMG) were measured. Using mixed model ANOVA (strength measures) and Wilcoxen-tests (EMGs), data revealed a significant increase in hip abductor strength production in the imagery group on the trained right limb (~6%). However, this was not reported for the exercise group. Additionally, the left hip abduction strength (not used for training) did not show a main effect in strength, however, there was a significant interaction of group and time revealing that the strength increased in the imagery group while it remained constant in the exercise group. EMG recordings supported the strength findings showing significant elevation of EMG amplitudes after imagery training on right and left side, while the exercise training group did not show any changes. Moreover, measures of handgrip strength and shoulder abduction showed no effects over time and no interactions in both groups. Experiments showed that imagery training is a suitable method for effectively increasing functional parameters of larger limb muscles (strength and EMG) which were enhanced on both sides (trained and untrained) confirming a bilateral transfer effect. Indeed, exercise training did not reveal any increases in the parameters above omitting functional improvements. The healthy individuals tested might not easily achieve benefits from exercise training within the time tested. However, it is evident that imagery training is effective in increasing the central motor command towards the muscles and that the effect seems to be segmental (no increase in handgrip strength and shoulder abduction parameters) and affects both sides (trained and untrained). In conclusion, imagery training was effective in functional improvements in limb muscles and produced a bilateral transfer on strength and EMG measures.

Keywords: imagery, exercise, physiotherapy, motor imagery

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4665 A Longitudinal Case Study of Greek as a Second Language

Authors: M. Vassou, A. Karasimos

Abstract:

A primary concern in the field of Second Language Acquisition (SLA) research is to determine the innate mechanisms of second language learning and acquisition through the systematic study of a learner's interlanguage. Errors emerge while a learner attempts to communicate using the target-language and can be seen either as the observable linguistic product of the latent cognitive and language process of mental representations or as an indispensable learning mechanism. Therefore, the study of the learner’s erroneous forms may depict the various strategies and mechanisms that take place during the language acquisition process resulting in deviations from the target-language norms and difficulties in communication. Mapping the erroneous utterances of a late adult learner in the process of acquiring Greek as a second language constitutes one of the main aims of this study. For our research purposes, we created an error-tagged learner corpus composed of the participant’s written texts produced throughout a period of a 4- year instructed language acquisition. Error analysis and interlanguage theory constitute the methodological and theoretical framework, respectively. The research questions pertain to the learner's most frequent errors per linguistic category and per year as well as his choices concerning the Greek Article System. According to the quantitative analysis of the data, the most frequent errors are observed in the categories of the stress system and syntax, whereas a significant fluctuation and/or gradual reduction throughout the 4 years of instructed acquisition indicate the emergence of developmental stages. The findings with regard to the article usage bespeak fossilization of erroneous structures in certain contexts. In general, our results point towards the existence and further development of an established learner’s (inter-) language system governed not only by mother- tongue and target-language influences but also by the learner’s assumptions and set of rules as the result of a complex cognitive process. It is expected that this study will contribute not only to the knowledge in the field of Greek as a second language and SLA generally, but it will also provide an insight into the cognitive mechanisms and strategies developed by multilingual learners of late adulthood.

Keywords: Greek as a second language, error analysis, interlanguage, late adult learner

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4664 The Relationship between Brand Recall and Brand Attitude in Advergame

Authors: Azaze-Azizi Abdul Adis, Hyung Jun Kim, Mohamad Rizwan Abdul Majid, Zaiton Osman, Izyanti Awang Razli

Abstract:

The increase of online advertising, specifically advergame has become a popular method of strengthening consumer brand recognition by inserting attractive characters and enhancing entertainment value. There have been several remarkable studies on spokes-characters in advertising effectiveness. However, few studies have examined the link between character presence and consumers' brand recall and attitude in advergame. Moreover, how the entertainment value of an advergame influences brand recall and brand attitude and the mediating role of brand recall in influencing character presence and entertainment on brand attitude are still lacking in the advergaming literature. An online survey was conducted with 366 Malaysian gamers. Using structural equation modeling, the results showed that character presence had no influence but entertainment value had a positive influence on brand recall and brand attitude. This study confirmed the role of brand recall as a mediator of the effect of between entertainment and brand attitude in advergame.

Keywords: character presence, entertainment, brand recall, brand attitude, advergame

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4663 Plasma Actuator Application to Control Surfaces of a Model Aircraft

Authors: Yuta Moriyama, Etsuo Morishita

Abstract:

Plasma actuator is very effective to recover stall flows over an upper airfoil surface. We first manufacture the actuator, test the stability of the device by trial and error basis and find the conditions for steady operations. We visualize the flow around an airfoil in the smoke tunnel and observe the stall recovery. The plasma actuator is stationary device and has no moving parts, and it might be an ideal device to control a model aircraft. We can use the actuator not only as a stall recovery device but also as a spoiler. We put the actuator near the leading edge of an elevator of a model aircraft as a spoiler, and measure the aerodynamic forces by a three-component balance. We observe the effect of the plasma actuator on the aerodynamic forces and the device effectiveness changes depending on the angle of attack whether it is positive or negative. We also visualize the flow caused by the plasma actuator by a desk-top Schlieren photography which is otherwise very difficult in a low-speed wind tunnel experiment.

Keywords: aerodynamics, plasma actuator, model aircraft, wind tunnel

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4662 Psychodiagnostic Tool Development for Measurement of Social Responsibility in Ukrainian Organizations

Authors: Olena Kovalchuk

Abstract:

How to define the understanding of social responsibility issues by Ukrainian companies is a contravention question. Thus, one of the practical uses of social responsibility is a diagnostic tool development for educational, business or scientific purposes. So the purpose of this research is to develop a tool for measurement of social responsibility in organization. Methodology: A 21-item questionnaire “Organization Social Responsibility Scale” was developed. This tool was adapted for the Ukrainian sample and based on the questionnaire “Perceived Role of Ethics and Social Responsibility” which connects ethical and socially responsible behavior to different aspects of the organizational effectiveness. After surveying the respondents, the factor analysis was made by the method of main compounds with orthogonal rotation VARIMAX. On the basis of the obtained results the 21-item questionnaire was developed (Cronbach’s alpha – 0,768; Inter-Item Correlations – 0,34). Participants: 121 managers at all levels of Ukrainian organizations (57 males; 65 females) took part in the research. Results: Factor analysis showed five ethical dilemmas concerning the social responsibility and profit compatibility in Ukrainian organizations. Below we made an attempt to interpret them: — Social responsibility vs profit. Corporate social responsibility can be a way to reduce operational costs. A firm’s first priority is employees’ morale. Being ethical and socially responsible is the priority of the organization. The most loaded question is "Corporate social responsibility can reduce operational costs". Significant effect of this factor is 0.768. — Profit vs social responsibility. Efficiency is much more important to a firm than ethics or social responsibility. Making the profit is the most important concern for a firm. The dominant question is "Efficiency is much more important to a firm than whether or not the firm is seen as ethical or socially responsible". Significant effect of this factor is 0.793. — A balanced combination of social responsibility and profit. Organization with social responsibility policy is more attractive for its stakeholders. The most loaded question is "Social responsibility and profitability can be compatible". Significant effect of this factor is 0.802. — Role of Social Responsibility in the successful organizational performance. Understanding the value of social responsibility and business ethics. Well-being and welfare of the society. The dominant question is "Good ethics is often good business". Significant effect of this factor is 0.727. — Global vision of social responsibility. Issues related to global social responsibility and sustainability. Innovative approaches to poverty reduction. Awareness of climate change problems. Global vision for successful business. The dominant question is "The overall effectiveness of a business can be determined to a great extent by the degree to which it is ethical and socially responsible". Significant effect of this factor is 0.842. The theoretical contribution. The perspective of the study is to develop a tool for measurement social responsibility in organizations and to test questionnaire’s adequacy for social and cultural context. Practical implications. The research results can be applied for designing a training programme for business school students to form their global vision for successful business as well as the ability to solve ethical dilemmas in managerial practice. Researchers interested in social responsibility issues are welcome to join the project.

Keywords: corporate social responsibility, Cronbach’s alpha, ethical behaviour, psychodiagnostic tool

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4661 An Approach on Intelligent Tolerancing of Car Body Parts Based on Historical Measurement Data

Authors: Kai Warsoenke, Maik Mackiewicz

Abstract:

To achieve a high quality of assembled car body structures, tolerancing is used to ensure a geometric accuracy of the single car body parts. There are two main techniques to determine the required tolerances. The first is tolerance analysis which describes the influence of individually tolerated input values on a required target value. Second is tolerance synthesis to determine the location of individual tolerances to achieve a target value. Both techniques are based on classical statistical methods, which assume certain probability distributions. To ensure competitiveness in both saturated and dynamic markets, production processes in vehicle manufacturing must be flexible and efficient. The dimensional specifications selected for the individual body components and the resulting assemblies have a major influence of the quality of the process. For example, in the manufacturing of forming tools as operating equipment or in the higher level of car body assembly. As part of the metrological process monitoring, manufactured individual parts and assemblies are recorded and the measurement results are stored in databases. They serve as information for the temporary adjustment of the production processes and are interpreted by experts in order to derive suitable adjustments measures. In the production of forming tools, this means that time-consuming and costly changes of the tool surface have to be made, while in the body shop, uncertainties that are difficult to control result in cost-intensive rework. The stored measurement results are not used to intelligently design tolerances in future processes or to support temporary decisions based on real-world geometric data. They offer potential to extend the tolerancing methods through data analysis and machine learning models. The purpose of this paper is to examine real-world measurement data from individual car body components, as well as assemblies, in order to develop an approach for using the data in short-term actions and future projects. For this reason, the measurement data will be analyzed descriptively in the first step in order to characterize their behavior and to determine possible correlations. In the following, a database is created that is suitable for developing machine learning models. The objective is to create an intelligent way to determine the position and number of measurement points as well as the local tolerance range. For this a number of different model types are compared and evaluated. The models with the best result are used to optimize equally distributed measuring points on unknown car body part geometries and to assign tolerance ranges to them. The current results of this investigation are still in progress. However, there are areas of the car body parts which behave more sensitively compared to the overall part and indicate that intelligent tolerancing is useful here in order to design and control preceding and succeeding processes more efficiently.

Keywords: automotive production, machine learning, process optimization, smart tolerancing

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4660 Usability Evaluation of a Mobile Application to Enhance the Use of Smartphone, by Visually Impaired Users in Indonesia

Authors: Johanna Renny Octavia, Kamila Okta Saarah

Abstract:

Smartphone nowadays is widely used by many people all over the world. However, people with vision impairment may experience difficulties that interfere with the proper usage of the smartphone. In Indonesia, the population of visually impaired is about 13 million people (estimated 285 million people worldwide). There are a number of mobile applications developed to enhance the use of smartphone by visually impaired. This paper discusses the usability evaluation of a mobile application, namely Ray Vision, designed to help visually impaired in using smartphone. A series of usability testing with a number of Indonesian visually impaired revealed 28 usability problems in the mobile application that led to 14 design recommendations. The redesigned application was then re-evaluated through another usability testing series. The results showed that all five usability criteria assessed were increased (usefulness by 13%, effectiveness by 27%, efficiency by 27%, satisfaction by 23%, and learnability by 12%). The System Usability Score (SUS) was also increased by 14.92%.

Keywords: mobile application, smartphone, usability evaluation, vision impaired

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4659 A New Tactical Optimization Model for Bioenergy Supply Chain

Authors: Birome Holo Ba, Christian Prins, Caroline Prodhon

Abstract:

Optimization is an important aspect of logistics management. It can reduce significantly logistics costs and also be a good tool for decision support. In this paper, we address a planning problem specific to biomass supply chain. We propose a new mixed integer linear programming (MILP) model dealing with different feed stock production operations such as harvesting, packing, storage, pre-processing and transportation, with the objective of minimizing the total logistic cost of the system on a regional basis. It determines the optimal number of harvesting machine, the fleet size of trucks for transportation and the amount of each type of biomass harvested, stored and pre-processed in each period to satisfy demands of refineries in each period. We illustrate the effectiveness of the proposal model with a numerical example, a case study in Aube (France department), which gives preliminary and interesting, results on a small test case.

Keywords: biomass logistics, supply chain, modelling, optimization, bioenergy, biofuels

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4658 Application of MALDI-MS to Differentiate SARS-CoV-2 and Non-SARS-CoV-2 Symptomatic Infections in the Early and Late Phases of the Pandemic

Authors: Dmitriy Babenko, Sergey Yegorov, Ilya Korshukov, Aidana Sultanbekova, Valentina Barkhanskaya, Tatiana Bashirova, Yerzhan Zhunusov, Yevgeniya Li, Viktoriya Parakhina, Svetlana Kolesnichenko, Yeldar Baiken, Aruzhan Pralieva, Zhibek Zhumadilova, Matthew S. Miller, Gonzalo H. Hortelano, Anar Turmuhambetova, Antonella E. Chesca, Irina Kadyrova

Abstract:

Introduction: The rapidly evolving COVID-19 pandemic, along with the re-emergence of pathogens causing acute respiratory infections (ARI), has necessitated the development of novel diagnostic tools to differentiate various causes of ARI. MALDI-MS, due to its wide usage and affordability, has been proposed as a potential instrument for diagnosing SARS-CoV-2 versus non-SARS-CoV-2 ARI. The aim of this study was to investigate the potential of MALDI-MS in conjunction with a machine learning model to accurately distinguish between symptomatic infections caused by SARS-CoV-2 and non-SARS-CoV-2 during both the early and later phases of the pandemic. Furthermore, this study aimed to analyze mass spectrometry (MS) data obtained from nasal swabs of healthy individuals. Methods: We gathered mass spectra from 252 samples, comprising 108 SARS-CoV-2-positive samples obtained in 2020 (Covid 2020), 7 SARS-CoV- 2-positive samples obtained in 2023 (Covid 2023), 71 samples from symptomatic individuals without SARS-CoV-2 (Control non-Covid ARVI), and 66 samples from healthy individuals (Control healthy). All the samples were subjected to RT-PCR testing. For data analysis, we employed the caret R package to train and test seven machine-learning algorithms: C5.0, KNN, NB, RF, SVM-L, SVM-R, and XGBoost. We conducted a training process using a five-fold (outer) nested repeated (five times) ten-fold (inner) cross-validation with a randomized stratified splitting approach. Results: In this study, we utilized the Covid 2020 dataset as a case group and the non-Covid ARVI dataset as a control group to train and test various machine learning (ML) models. Among these models, XGBoost and SVM-R demonstrated the highest performance, with accuracy values of 0.97 [0.93, 0.97] and 0.95 [0.95; 0.97], specificity values of 0.86 [0.71; 0.93] and 0.86 [0.79; 0.87], and sensitivity values of 0.984 [0.984; 1.000] and 1.000 [0.968; 1.000], respectively. When examining the Covid 2023 dataset, the Naive Bayes model achieved the highest classification accuracy of 43%, while XGBoost and SVM-R achieved accuracies of 14%. For the healthy control dataset, the accuracy of the models ranged from 0.27 [0.24; 0.32] for k-nearest neighbors to 0.44 [0.41; 0.45] for the Support Vector Machine with a radial basis function kernel. Conclusion: Therefore, ML models trained on MALDI MS of nasopharyngeal swabs obtained from patients with Covid during the initial phase of the pandemic, as well as symptomatic non-Covid individuals, showed excellent classification performance, which aligns with the results of previous studies. However, when applied to swabs from healthy individuals and a limited sample of patients with Covid in the late phase of the pandemic, ML models exhibited lower classification accuracy.

Keywords: SARS-CoV-2, MALDI-TOF MS, ML models, nasopharyngeal swabs, classification

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4657 Alumina Generated by Electrocoagulation as Adsorbent for the Elimination of the Iron from Drilling Water

Authors: Aimad Oulebsir, Toufik Chaabane, Venkataraman Sivasankar, André Darchen, Titus A. M. Msagati

Abstract:

Currently, the presence of pharmaceutical substances in the environment is an emerging pollution leading to the disruption of ecosystems. Indeed, water loaded with pharmaceutical residues is an issue that has raised the attention of researchers. The aim of this study was to monitor the effectiveness of the alumina electro-generated by the adsorption process the iron of well water for the production of drugs. The Fe2+ was removed from wastewater by adsorption in a batch cell. Performance results of iron removal by alumina electro-generated revealed that the efficiency of the carrier in the method of electro-generated adsorption. The overall Fe2+ of the synthetically solutions and simulated effluent removal efficiencies reached 75% and 65%, respectively. The application of models and isothermal adsorption kinetics complement the results obtained experimentally. Desorption of iron was investigated using a solution of 0.1M NaOH. Regeneration of the tests shows that the adsorbent maintains its capacity after five adsorption/desorption cycles.

Keywords: electrocoagulation, aluminum electrode, electrogenerated alumina, iron, adsorption/desorption

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4656 Assessing Secondary School Curricula in the light of Developing Quality of Life Standards of High School Students

Authors: Othman Ali Alghtani, Yahya Abdul-Ekhalq Ali, Abdullah Abdul-Ekhalq Ali, Ahmed Al Sadiq Abdul Majeed, Najwa Attian Al-Mohammadi, Obead Mozel Alharbi, Sabri Mohamed Ismail, Omar Ibrahim Asiri

Abstract:

This study assessed the curricula of secondary schools given requirements to enhance the quality of life of students. The components of quality of life were described to build a list of standards and indicators. A questionnaire assessing the dimensions of mental (cognitive and emotional), physical, digital, and social health, and environmental awareness was prepared. A descriptive-analytical approach was used on a sample of 258 teachers and educational supervisors in Tabuk. The results indicated shortcomings in the secondary school curricula regarding developing standards and indicators of components of quality of life. Results also indicated that secondary school curricula incorporated few practices to improve student’s quality of life. No significant differences were found regarding the core subject, job, gender, and years of experience.

Keywords: assessing curricula, teacher practices, quality of life, teaching practices

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4655 Enhancing Teacher Retention and Professional Satisfaction: An Analysis of Salaries, Policies, and Educational Frameworks

Authors: Melissa Beck Wells

Abstract:

This study examines the complex factors affecting teacher retention across states, focusing on the roles of salaries, educational policies, and professional development. Despite efforts to reduce teacher turnover, it remains a significant challenge, impacting the quality of education and student outcomes. Analysis of data from the National Education Association, the ‘Raise the Bar’ initiative, and the Education Commission of the States reveals a minimal negative correlation between teacher salaries and retention, indicating that salary alone does not determine retention. Additionally, thematic analysis of educational policies and development programs highlights effective strategies for addressing retention challenges. The research emphasizes the need for holistic support systems, including mentorship and professional growth opportunities, to improve retention. These findings urge policymakers and educational leaders to develop comprehensive strategies to maintain a qualified teaching workforce and enhance educational quality and equity nationwide.

Keywords: teacher retention, salary levels, educational policies, professional development, teacher turnover

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4654 A Practical Methodology for Evaluating Water, Sanitation and Hygiene Education and Training Programs

Authors: Brittany E. Coff, Tommy K. K. Ngai, Laura A. S. MacDonald

Abstract:

Many organizations in the Water, Sanitation and Hygiene (WASH) sector provide education and training in order to increase the effectiveness of their WASH interventions. A key challenge for these organizations is measuring how well their education and training activities contribute to WASH improvements. It is crucial for implementers to understand the returns of their education and training activities so that they can improve and make better progress toward the desired outcomes. This paper presents information on CAWST’s development and piloting of the evaluation methodology. The Centre for Affordable Water and Sanitation Technology (CAWST) has developed a methodology for evaluating education and training activities, so that organizations can understand the effectiveness of their WASH activities and improve accordingly. CAWST developed this methodology through a series of research partnerships, followed by staged field pilots in Nepal, Peru, Ethiopia and Haiti. During the research partnerships, CAWST collaborated with universities in the UK and Canada to: review a range of available evaluation frameworks, investigate existing practices for evaluating education activities, and develop a draft methodology for evaluating education programs. The draft methodology was then piloted in three separate studies to evaluate CAWST’s, and CAWST’s partner’s, WASH education programs. Each of the pilot studies evaluated education programs in different locations, with different objectives, and at different times within the project cycles. The evaluations in Nepal and Peru were conducted in 2013 and investigated the outcomes and impacts of CAWST’s WASH education services in those countries over the past 5-10 years. In 2014, the methodology was applied to complete a rigorous evaluation of a 3-day WASH Awareness training program in Ethiopia, one year after the training had occurred. In 2015, the methodology was applied in Haiti to complete a rapid assessment of a Community Health Promotion program, which informed the development of an improved training program. After each pilot evaluation, the methodology was reviewed and improvements were made. A key concept within the methodology is that in order for training activities to lead to improved WASH practices at the community level, it is not enough for participants to acquire new knowledge and skills; they must also apply the new skills and influence the behavior of others following the training. The steps of the methodology include: development of a Theory of Change for the education program, application of the Kirkpatrick model to develop indicators, development of data collection tools, data collection, data analysis and interpretation, and use of the findings for improvement. The methodology was applied in different ways for each pilot and was found to be practical to apply and adapt to meet the needs of each case. It was useful in gathering specific information on the outcomes of the education and training activities, and in developing recommendations for program improvement. Based on the results of the pilot studies, CAWST is developing a set of support materials to enable other WASH implementers to apply the methodology. By using this methodology, more WASH organizations will be able to understand the outcomes and impacts of their training activities, leading to higher quality education programs and improved WASH outcomes.

Keywords: education and training, capacity building, evaluation, water and sanitation

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4653 Copula Markov Switching Multifractal Models for Forecasting Value-at-Risk

Authors: Giriraj Achari, Malay Bhattacharyya

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In this paper, the effectiveness of Copula Markov Switching Multifractal (MSM) models at forecasting Value-at-Risk of a two-stock portfolio is studied. The innovations are allowed to be drawn from distributions that can capture skewness and leptokurtosis, which are well documented empirical characteristics observed in financial returns. The candidate distributions considered for this purpose are Johnson-SU, Pearson Type-IV and α-Stable distributions. The two univariate marginal distributions are combined using the Student-t copula. The estimation of all parameters is performed by Maximum Likelihood Estimation. Finally, the models are compared in terms of accurate Value-at-Risk (VaR) forecasts using tests of unconditional coverage and independence. It is found that Copula-MSM-models with leptokurtic innovation distributions perform slightly better than Copula-MSM model with Normal innovations. Copula-MSM models, in general, produce better VaR forecasts as compared to traditional methods like Historical Simulation method, Variance-Covariance approach and Copula-Generalized Autoregressive Conditional Heteroscedasticity (Copula-GARCH) models.

Keywords: Copula, Markov Switching, multifractal, value-at-risk

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4652 Management of Organizational Behavior Utilizing Human Resources

Authors: Habab Ahmed Hassan Abuzeid

Abstract:

Organizations are social systems. If one wishes to work in them or to manage them, it is necessary to understand how they operate. Organizations combine science and people–technology and humanity. Unless we have qualified people to design and implement, techniques alone will not produce desirable results. Human behavior in organizations is rather unpredictable. It is unpredictable because it arises from people’s deep-seated needs and value systems. However, it can be partially understood in terms of the framework of behavioral science, management and other disciplines. There is no idealistic solution to organizational problems. All that can be done is to increase our understanding and skills so that human relations at work can be enhanced. In this paper, we consider management of organization behavior utilizing human resources. Study the elements of organization behavior, the effectiveness of mechanism to enhance staff relationships. Many approaches could be applied for healthy organizational environment, it’s highlighted more details in this paper. Organization behavior can raise the employees’ engagement, loyalty and commitment; to accomplish the goal.

Keywords: environment, engagement, human resources, organization behavior

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4651 A Review of the Long Term Effects of In-Service Training Towards Inclusive Education

Authors: Meenakshi Srivastava, Anke A. De Boer, Sip Jan Pij

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Teacher’s preparedness towards special educational needs (SEN) of the students in regular schools is an important factor in making education inclusive as a goal to provide education for all. The current study measured the long term effects of an in-service teacher training programme which focused on the inclusion of students with a range of SEN. The programme was on three particular aspects: teachers’ attitudes, their knowledge about SEN and knowledge about teaching methods. A refresher course was also organized for participants of the initial training programme. The long term effects were examined by teachers using a self-report questionnaire (n = 38). The wider effects of the initial training were recorded by interviewing school principals (n = 4). Repeated measures of ANOVA revealed significant effects: more positive attitudes and increased knowledge about SEN among teachers who took the refresher course (n = 18) compared to those who had not (n = 19). Principals also found a more positive attitude, sensitivity and increased awareness about SEN among the participants.

Keywords: inclusion, students with special educational needs, teacher training, follow-up, attitudes change

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4650 Reading and Writing Memories in Artificial and Human Reasoning

Authors: Ian O'Loughlin

Abstract:

Memory networks aim to integrate some of the recent successes in machine learning with a dynamic memory base that can be updated and deployed in artificial reasoning tasks. These models involve training networks to identify, update, and operate over stored elements in a large memory array in order, for example, to ably perform question and answer tasks parsing real-world and simulated discourses. This family of approaches still faces numerous challenges: the performance of these network models in simulated domains remains considerably better than in open, real-world domains, wide-context cues remain elusive in parsing words and sentences, and even moderately complex sentence structures remain problematic. This innovation, employing an array of stored and updatable ‘memory’ elements over which the system operates as it parses text input and develops responses to questions, is a compelling one for at least two reasons: first, it addresses one of the difficulties that standard machine learning techniques face, by providing a way to store a large bank of facts, offering a way forward for the kinds of long-term reasoning that, for example, recurrent neural networks trained on a corpus have difficulty performing. Second, the addition of a stored long-term memory component in artificial reasoning seems psychologically plausible; human reasoning appears replete with invocations of long-term memory, and the stored but dynamic elements in the arrays of memory networks are deeply reminiscent of the way that human memory is readily and often characterized. However, this apparent psychological plausibility is belied by a recent turn in the study of human memory in cognitive science. In recent years, the very notion that there is a stored element which enables remembering, however dynamic or reconstructive it may be, has come under deep suspicion. In the wake of constructive memory studies, amnesia and impairment studies, and studies of implicit memory—as well as following considerations from the cognitive neuroscience of memory and conceptual analyses from the philosophy of mind and cognitive science—researchers are now rejecting storage and retrieval, even in principle, and instead seeking and developing models of human memory wherein plasticity and dynamics are the rule rather than the exception. In these models, storage is entirely avoided by modeling memory using a recurrent neural network designed to fit a preconceived energy function that attains zero values only for desired memory patterns, so that these patterns are the sole stable equilibrium points in the attractor network. So although the array of long-term memory elements in memory networks seem psychologically appropriate for reasoning systems, they may actually be incurring difficulties that are theoretically analogous to those that older, storage-based models of human memory have demonstrated. The kind of emergent stability found in the attractor network models more closely fits our best understanding of human long-term memory than do the memory network arrays, despite appearances to the contrary.

Keywords: artificial reasoning, human memory, machine learning, neural networks

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4649 Ultrasonographic Manifestation of Periventricular Leukomalacia in Preterm Neonates at Teaching Hospital Peradeniya, Sri Lanka

Authors: P. P. Chandrasekera, P. B. Hewavithana, S. Rosairo, M. H. M. N. Herath, D. M. R. D. Mirihella

Abstract:

Periventricular Leukomalacia (PVL) is a White Matter Injury (WMI) of preterm neonatal brain. Objectives of the study were to assess the neuro-developmental outcome at one year of age and to determine a good protocol of cranial ultrasonography to detect PVL. Two hundred and sixty four preterm neonates were included in the study. Series of cranial ultrasound scans were done by using a dedicated neonatal head probe 4-10 MHz of Logic e portable ultrasound scanner. Clinical history of seizures, abnormal head growth (hydrocephalus or microcephaly) and developmental milestones were assessed and neurological examinations were done until one year of age. Among live neonates, 57% who had cystic PVL (Grades2 and 3) manifested as cerebral palsy. In conclusion cystic PVL has permanent neurological disabilities like cerebral palsy. Good protocol of real time cranial ultrasonography to detect PVL is to perform scans at least once a week until one month and at term (40 weeks of gestation).

Keywords: cerebral palsy, cranial ultrasonography, Periventricular Leukomalacia, preterm neonates

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4648 India’s Emigration Act: Its Emergence and Changes

Authors: Sudhaveni Naresh

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Emigration is not a new phenomenon in India but globalization has reinforced it. India has been a source of emigrants for many countries for a long period. Over 25 million Indian diaspora is spread across the world. Historically, during the British rule indenture labour from India was sent to other colonies. To regulate indentured emigration and to provide a mechanism for emigration, the British India government enacted Emigration Act, 1922. After independence, a majority of unskilled and semi-skilled labour emigrated to Gulf and South-East Asia, whereas white-collar workers preferred North America, Europe and Australia. They are contributing to both the economies in origin and destination. Due to increasing quantum of emigration, the Ministry of Labour enacted Emigration Act, 1983, which deals with the emigration of Indian workers for overseas employment on contractual basis, seeks to safeguard emigrants’ interest and ensures their welfare. The paper explains the reason behind enacting Emigration Act, 1983, and the changes in the form of an Emigration (Amendment) Rules, 2009. This paper examines the current status, effectiveness of the Act and rules.

Keywords: economic growth, emigrants, Emigration Act 1983, remittance

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4647 Mapping New Technologies for Sustainability along the Fashion Supply Chain

Authors: Hilde Heim

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The textile industry is known for its swift adoption of innovations in fashion technology (Fash-Tech). The industry is also known for its harmful effects on the environment. Opportunely, Fash-Tech is expected to facilitate the turn towards more sustainable practice. However, although several technologies have the potential for advancing sustainable practice, many industry players, whether large or small, are confused and misinformed about Fash-Tech adoption, application, and impact. Through a visual poster presentation, this project aims to map global fashion innovations along the supply chain from fibre production to waste management, thus providing a clearer picture of numbers, scale, and adoption. While the project aims to identify Fash-Tech effectiveness in reaching sustainability goals, it also identifies areas of congestion as well as insufficiency in the accessibility of Fash-Tech. This project intends to help inform future decisions in business, investment, and policy for the advancement of sustainable practice.

Keywords: fashion technology, sustainability, supply chain, enterprise management

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4646 Fulfillment of Models of Prenatal Care in Adolescents from Mexico and Chile

Authors: Alejandra Sierra, Gloria Valadez, Adriana Dávalos, Mirliana Ramírez

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For years, the Pan American Health Organization/World Health Organization and other organizations have made efforts to the improve access and the quality of prenatal care as part of comprehensive programs for maternal and neonatal health, the standards of care have been renewed in order to migrate from a medical perspective to a holistic perspective. However, despite the efforts currently antenatal care models have not been verified by a scientific evaluation in order to determine their effectiveness. The teenage pregnancy is considered as a very important phenomenon since it has been strongly associated with inequalities, poverty and the lack of gender quality; therefore it is important to analyze the antenatal care that’s been given, including not only the clinical intervention but also the activities surrounding the advertising and the health education. In this study, the objective was to describe if the previously established activities (on the prenatal care models) are being performed in the care of pregnant teenagers attending prenatal care in health institutions in two cities in México and Chile during 2013. Methods: Observational and descriptive study, of a transversal cohort. 170 pregnant women (13-19 years) were included in prenatal care in two health institutions (100 women from León-Mexico and 70 from Chile-Coquimbo). Data collection: direct survey, perinatal clinical record card which was used as checklists: WHO antenatal care model WHO-2003, Official Mexican Standard NOM-007-SSA2-1993 and Personalized Service Manual on Reproductive Process- Chile Crece Contigo; for data analysis descriptive statistics were used. The project was approved by the relevant ethics committees. Results: Regarding the fulfillment of interventions focused on physical, gynecological exam, immunizations, monitoring signs and biochemical parameters in both groups was met by more than 84%; the activities of guidance and counseling pregnant teenagers in Leon compliance rates were below 50%, on the other hand, although pregnant women in Coquimbo had a higher percentage of compliance, no one reached 100%. The topics that less was oriented were: family planning, signs and symptoms of complications and labor. Conclusions: Although the coverage of the interventions indicated in the prenatal care models was high, there were still shortcomings in the fulfillment of activities to orientation, education and health promotion. Deficiencies in adherence to prenatal care guidelines could be due to different circumstances such as lack of registration or incomplete filling of medical records, lack of medical supplies or health personnel, absences of people at prenatal check-up appointments, among many others. Therefore, studies are required to evaluate the quality of prenatal care and the effectiveness of existing models, considering the role of the different actors (pregnant women, professionals and health institutions) involved in the functionality and quality of prenatal care models, in order to create strategies to design or improve the application of a complete process of promotion and prevention of maternal and child health as well as sexual and reproductive health in general.

Keywords: adolescent health, health systems, maternal health, primary health care

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4645 Competitor Analysis to Quantify the Benefits and for Different Use of Transport Infrastructure

Authors: Dimitrios J. Dimitriou, Maria F. Sartzetaki

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Different transportation modes have key operational advantages and disadvantages, providing a variety of different transport options to users and passengers. This paper reviews key variables for the competition between air transport and other transport modes. The aim of this paper is to review the competition between air transport and other transport modes, providing results in terms of perceived cost for the users, for destinations high competitiveness for all transport modes. The competitor analysis variables include the cost and time outputs for each transport option, highlighting the level of competitiveness on high demanded Origin-Destination corridors. The case study presents the output of a such analysis for the OD corridor in Greece that connects the Capital city (Athens) with the second largest city (Thessaloniki) and the different transport modes have been considered (air, train, road). Conventional wisdom is to present an easy to handle tool for planners, managers and decision makers towards pricing policy effectiveness and demand attractiveness, appropriate to use for other similar cases.

Keywords: competitor analysis, transport economics, transport generalized cost, quantitative modelling

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4644 Advantages of Fuzzy Control Application in Fast and Sensitive Technological Processes

Authors: Radim Farana, Bogdan Walek, Michal Janosek, Jaroslav Zacek

Abstract:

This paper presents the advantages of fuzzy control use in technological processes control. The paper presents a real application of the Linguistic Fuzzy-Logic Control, developed at the University of Ostrava for the control of physical models in the Intelligent Systems Laboratory. The paper presents an example of a sensitive non-linear model, such as a magnetic levitation model and obtained results which show how modern information technologies can help to solve actual technical problems. A special method based on the LFLC controller with partial components is presented in this paper followed by the method of automatic context change, which is very helpful to achieve more accurate control results. The main advantage of the used system is its robustness in changing conditions demonstrated by comparing with conventional PID controller. This technology and real models are also used as a background for problem-oriented teaching, realized at the department for master students and their collaborative as well as individual final projects.

Keywords: control, fuzzy logic, sensitive system, technological proves

Procedia PDF Downloads 459