Search results for: brain training

Authors: Viktoriia Burkina, Vladimir Zlabek, Galia Zamaratskaia

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Cytochromes P450 (CYP) are important family of enzymes in Phase I metabolism. Environmental pollutants often act as inducers of the gene expression and activities CYP1A1 and CYP3A-like isoforms in fish. The activities are generally measured in the fish liver or gills, and less is known about tissue distribution of expression. In present study, the CYP1A1 and CYP3A-like activities were measured in rainbow trout liver, gill, intestine, heart, brain and gonads. The activities of CYP1A1 and CYP3A-like proteins were estimated as the rates of 7-ethoxyresorufin-O-deethylation (EROD) and benzyloxy-4-trifluoromethylcoumarin-O-debenzyloxylation (BFCOD), respectively. The CYP1A1 and CYP3A-like activities were detectable in all investigated fish tissues, with the highest activity in hepatic tissue followed by heart > brain > gill > intestine > gonads. To confirm the presence of CYP1A1 in different tissues, EROD activity was measured in presence of the selective inhibitors ellipticine (CYP1A1), ketoconazole (CYP3A), 8-methoxypsoralen (human CYP2A) and diallyl sulphide (CYP2E1). It was found that ellipticine, ketoconazole and 8-methoxypsoralen inhibited hepatic EROD activity by 88-98%. Ellipticine inhibited gill, intestine, and gonad EROD activity by 50%. In conclusion, EROD and BFCOD activities were detected in rainbow trout liver, gill, intestine, heart, brain and gonads. Further studies are needed to fully identify all CYP450 isoforms responsible for these activities. Acknowledgement: The study was financially supported by the Ministry of Education, Youth and Sports of the Czech Republic - projects „CENAKVA “(No. CZ.1.05/2.1.00/01.0024), “CENAKVA Center Development “(No. CZ.1.05/2.1.00/19.0380), “CENAKVA II “(No. LO1205 under the NPU I program), and "Development of USB - International mobility (No. CZ.02.2.69/0.0/0.0/16_027/0008364).

Keywords: BFCOD, EROD, fish, phase I metabolism, selective inhibitors

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Authors: Parker Murray, Marci Johnson, Tyson S. Burnham, Alina K. Fong, Mark D. Allen, Bruce McIff

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Purpose: Pathological dysregulation of Neurovascular Coupling (NVC) caused by mild traumatic brain injury (mTBI) is the predominant source of chronic post-concussion syndrome (PCS) symptomology. fNCI has the ability to localize dysregulation in NVC by measuring blood-oxygen-level-dependent (BOLD) signaling during the performance of fMRI-adapted neuropsychological evaluations. With fNCI, 57 brain areas consistently affected by concussion were identified as PCS neural markers, which were validated on large samples of concussion patients and healthy controls. These neuromarkers provide the basis for a computation of PCS severity which is referred to as the Severity Index Score (SIS). The SIS has proven valuable in making pre-treatment decisions, monitoring treatment efficiency, and assessing long-term stability of outcomes. Methods and Materials: After being scanned while performing various cognitive tasks, 476 concussed patients received an SIS score based on the neural dysregulation of the 57 previously identified brain regions. These scans provide an objective measurement of attentional, subcortical, visual processing, language processing, and executive functioning abilities, which were used as biomarkers for post-concussive neural dysregulation. Initial SIS scores were used to develop individualized therapy incorporating cognitive, occupational, and neuromuscular modalities. These scores were also used to establish pre-treatment benchmarks and measure post-treatment improvement. Results: Changes in SIS were calculated in percent change from pre- to post-treatment. Patients showed a mean improvement of 76.5 percent (σ= 23.3), and 75.7 percent of patients showed at least 60 percent improvement. Longitudinal reassessment of 24 of the patients, measured an average of 7.6 months post-treatment, shows that SIS improvement is maintained and improved, with an average of 90.6 percent improvement from their original scan. Conclusions: fNCI provides a reliable measurement of NVC allowing for identification of concussion pathology. Additionally, fNCI derived SIS scores direct tailored therapy to restore NVC, subsequently resolving chronic PCS resulting from mTBI.

Keywords: concussion, functional magnetic resonance imaging (fMRI), neurovascular coupling (NVC), post-concussion syndrome (PCS)

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Authors: Abdeta Bayissa Mekessa

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The purpose of this study was to examine the effects of plyometric exercises on agility, power, and speed and improvement of U-17 female sprinters in the case of the Burayu Athletics project. The true experimental research design was employed for conducting this study. The total populations of the study were 14 U-17 female sprinters from Burayu athletics project. The populations were small in numbers; therefore, the researcher took all as a sample by using comprehensive sampling techniques. These subjects were classified into the Experimental group (N=7) and the Control group (N=7) by using simple random sampling techniques. The Experimental group participated in plyometric training for 8 weeks, 3 days per week and 60 minutes duration per day in addition to their regular training. But, the control groups were following their only regular training program. The variables selected for the purpose of this study were agility, power and speed. The tests were the Illinois agility test, standing long jump test, and 30m sprint test, respectively. Both groups were tested before (pre-test) and after (post-test) 8 weeks of plyometric training. For data analysis, the researcher used SPSS version 26.0 software. The collected data was analyzed using a paired sample t-test to observe the difference between the pre-test and post-test results of the plyometric exercises of the study. The significant level of p<0.05 was considered. The result of the study shows that after 8 weeks of plyometric training, significant improvements were found in Agility (MD=0.45, p<0.05), power (MD=-1.157, P<0.05) and speed (MD=0.37, P<0.05) for experimental group subjects. On the other hand, there was no significant change (P>0.05) in those variables in the control groups. Finally, the findings of the study showed that eight (8) weeks of plyometric exercises had a positive effect on agility, power and speed improvement of female sprinters. Therefore, Athletics coaches and athletes are highly recommended to include plyometric exercise in their training program.

Keywords: ploymetric exercise, speed power, aglity, female sprinter

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Authors: Esshili Awatef, Manitz Marie-Pierre, Eßlinger Manuela, Gerhardt Alexandra, Plümper Jennifer, Wachholz Simone, Friebe Astrid, Juckel Georg

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Maternal immune activation (MIA) resulting from maternal viral infection during pregnancy is a known risk factor for schizophrenia. The neural mechanisms by which maternal infections increase the risk for schizophrenia remain unknown, although the prevailing hypothesis argues that an activation of the maternal immune system induces changes in the maternal-fetal environment that might interact with fetal brain development. It may lead to an activation of fetal microglia inducing long-lasting functional changes of these cells. Based on post-mortem analysis showing an increased number of activated microglial cells in patients with schizophrenia, it can be hypothesized that these cells contribute to disease pathogenesis and may actively be involved in gray matter loss observed in such patients. In the present study, we hypothesize that prenatal treatment with the inflammatory agent Poly(I:C) during embryogenesis at contributes to microglial activation in the offspring, which may, therefore, represent a contributing factor to the pathogenesis of schizophrenia and underlines the need for new pharmacological treatment options. Pregnant rats were treated with intraperitoneal injections a single dose of Poly(I:C) or saline on gestation day 17. Brains of control and Poly(I:C) offspring, were removed and into 20-μm-thick coronal sections were cut by using a Cryostat. Brain slices were fixed and immunostained with ba1 antibody. Subsequently, Iba1-immunoreactivity was detected using a secondary antibody, goat anti-rabbit. The sections were viewed and photographed under microscope. The immunohistochemical analysis revealed increases in microglia cell number in the prefrontal cortex, in offspring of poly(I:C) treated-rats as compared to the controls injected with NaCl. However, no significant differences were observed in microglia activation in the cerebellum among the groups. Prenatal immune challenge with Poly(I:C) was able to induce long-lasting changes in the offspring brains. This lead to a higher activation of microglia cells in the prefrontal cortex, a brain region critical for many higher brain functions, including working memory and cognitive flexibility. which might be implicated in possible changes in cortical neuropil architecture in schizophrenia. Further studies will be needed to clarify the association between microglial cells activation and schizophrenia-related behavioral alterations.

Keywords: Microglia, neuroinflammation, PolyI:C, schizophrenia

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Authors: Kennedy Zinn, Chris Anderson

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Chronic Covid syndrome (CCS) is a condition in which individuals who test positive for Covid-19 experience persistent symptoms after recovering from the virus. CCS affects every organ system, including the central nervous system. Neurological “long-haul” symptoms last from a few weeks to several months and include brain fog, chronic fatigue, dyspnea, mood dysregulation, and headaches. Data suggest that 10-30% of individuals testing positive for Covid-19 develop CCS. Current literature indicates a decreased quality of life in persistent symptoms. CCS is a pervasive and pernicious COVID-19 sequelae. More research is needed to understand risk factors, impact, and possible interventions. Research frequently cites cytokine storming as noteworthy etiology in CCS. Cytokine storming is a malfunctional immune response and facilitates multidimensional interconnected physiological responses. The most prominent responses include abnormal blood flow, hypoxia/hypoxemia, inflammation, and endothelial damage. Neurological impairments and pathogenesis in CCS parallel that of traumatic brain injury (TBI). Both exhibit impairments in memory, cognition, mood, sustained attention, and chronic fatigue. Evidence suggests abnormal blood flow, inflammation, and hypoxemia as shared causal factors. Cytokine storming is also typical in mTBI. The shared characteristics in symptoms and etiology suggest potential parallel routes of investigation that allow for better understanding of CCS. Research on the effect of altitude in mTBI varies. Literature finds decreased rates of concussions at higher altitudes. Other studies suggest that at a higher altitude, pre-existing mTBI symptoms are exacerbated. This may mean that in CCS, the geographical location where individuals live and the location where individuals experienced acute Covid-19 symptoms may influence the severity and risk of developing CCS. It also suggests that clinics which treat mTBI patients could also provide benefits for those with CCS. This study aims to examine the relationships between altitude and CCS as a risk factor and investigate the longevity and severity of symptoms in different altitudes. Existing patient data from a concussion clinic using fMRI scans and self-reported symptoms will be used for approximately 30 individuals with CCS symptoms. The association between acclimated altitude and CCS severity will be analyzed. Patients will be classified into low, medium, and high altitude groups and compared for differences on fMRI severity scores and self-reported measures. It is anticipated that individuals living in lower altitudes are at higher risk of developing more severe neuropsychological symptoms in CCS. It is also anticipated that a treatment approach for mTBI will also be beneficial to those with CCS.

Keywords: altitude, chronic covid syndrome, concussion, covid brain, EPIC treatment, fMRI, traumatic brain injury

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Authors: Monika Benedek

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This paper intends to present a pilot study of blended ear-training course at a Finnish university. The course ran for ten weeks and included both traditional (offline) group lessons for 90 minutes each week and an online learning platform. Twelve students majored in musicology and music education participated in the course. The aims of pilot research were to develop a new blended ear-training course at university level, to determine the ideal amount of workload in each part of the blended instruction (offline and online) and to develop the course material. The course material was selected from the Classical period in order to develop students’ aural skills together with their stylistic knowledge. Students were asked to provide written feedback of the course content and learning approaches of face-to-face group lessons and online learning platform each week during the course. Therefore, the teaching material is continuously planned for each week. This qualitative data collection and weekly analysis of data are on progress. However, based on the teacher-researcher’s experiences and the students’ feedback already collected, it could be seen that the blended instruction would be an ideal teaching strategy for ear-trainging at the music programmes of universities to develop students’ aural skills and stylistic knowledge. It is also presumed that such blended instruction with less workload would already improve university students’ aural skills and related musicianship skills. The preliminary findings of research also indicated that students generally found those ear-training tasks the most useful to learn online that combined listening, singing, singing and playing an instrument. This paper intends to summarise the final results of the pilot study.

Keywords: blended-learning, ear-training, higher music education, online-learning, pilot study

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Authors: Maryam Alimardani, Kazuo Hiraki

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This study presents a framework for development of a new generation of therapy robots that can interact with users by monitoring their physiological and mental states. Here, we focused on one of the controversial methods of therapy, hypnotherapy. Hypnosis has shown to be useful in treatment of many clinical conditions. But, even for healthy people, it can be used as an effective technique for relaxation or enhancement of memory and concentration. Our aim is to develop a robot that collects information about user’s mental and physical states using electroencephalogram (EEG) and electromyography (EMG) signals and performs costeffective hypnosis at the comfort of user’s house. The presented framework consists of three main steps: (1) Find the EEG-correlates of mind state before, during, and after hypnosis and establish a cognitive model for state changes, (2) Develop a system that can track the changes in EEG and EMG activities in real time and determines if the user is ready for suggestion, and (3) Implement our system in a humanoid robot that will talk and conduct hypnosis on users based on their mental states. This paper presents a pilot study in regard to the first stage, detection of EEG and EMG features during hypnosis.

Keywords: hypnosis, EEG, robotherapy, brain-computer interface (BCI)

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Authors: Rangika Perera, Shyamani Hettiarachchi, Fran Hagstrom

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Dyslexia is the most common reading reading-related difficulty among the school school-aged population and currently, 5-10% are showing the features of dyslexia in Sri Lanka. As there is an insufficient number of speech and language pathologists in the country and few speech and language pathologists working in government mainstream school settings, these children who are at risk of dyslexia are not receiving enough quality early intervention services to develop their reading skills. As teachers are the key professionals who are directly working with these children, using them as the primary facilitators to improve their reading skills will be the most effective approach. This study aimed to identify the efficacy of a two and half a day of intensive training provided to fifteen mainstream government school teachers of grade two classes. The goal of the training was to enhance their knowledge of dyslexia and provide full classroom skills training that could be used to support the development of the students’ reading competencies. A closed closed-ended multiple choice questionnaire was given to these teachers pre and -post-training to measure teachers’ knowledge of dyslexia, the areas in which these children needed additional support, and the best strategies to facilitate reading competencies. The data revealed that the teachers’ knowledge in all areas was significantly poorer prior to the training and that there was a clear improvement in all areas after the training. The gain in target areas of teaching skills selected to improve the reading skills of children was evaluated through peer feedback. Teachers were assigned to three groups and expected to model how they were going to introduce the skills in recommended areas using researcher developed, validated and reliability reliability-tested materials and the strategies which were introduced during the training within the given tasks. Peers and the primary investigator rated teachers’ performances and gave feedback on organizational skills, presentation skills of materials, clarity of instruction, and appropriateness of vocabulary. After modifying their skills according to the feedback the teachers received, they were expected to modify and represent the same tasks to the group the following day. Their skills were re-evaluated by the peers and primary investigator using the same rubrics to measure the improvement. The findings revealed a significant improvement in their teaching skills development. The data analysis of both knowledge and skills gains of the teachers was carried out using quantitative descriptive data analysis. The overall findings of the study yielded promising results that support intensive training as a method for improving teachers’ knowledge and teaching skill development for use with children in a whole class intervention setting who are at risk of dyslexia.

Keywords: Dyslexia, knowledge, teaching skills, training program

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Authors: Abdulhakim Ali Mosleh Alzubidy

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The study's aim was to establish a proposed training program for kindergarten teachers according to their modern professional demands so that they could effectively teach children through movement education and play. The sample, which consisted of (46) teachers and administrators selected at random from the Ibb governorate, represented the study population of kindergarten teachers and administrators. The researcher developed three survey forms as a tool for data collection, and the forms were used with the research sample. The researcher used the descriptive method due to its applicability and the nature of the study, and he also used the appropriate statistical treatment of the data, which is to extract the percentage and the percentage of agreement. The study came to the following conclusions: ● The proposed program is of great importance in preparing the kindergarten teacher in an appropriate manner that keeps pace with modern developments in this field. ● The field of movement education is a necessity for the kindergarten teacher, through which she will be able to prepare the child physically and kinetically and teach him effectively the principles of reading, writing, and numerical and arithmetic concepts.

Keywords: training program, professional needs, kindergarten, kindergarten teacher

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Authors: Verd Shomrom, Gilat Trabelsi

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The goal of the study was to examine the effects of Computerized Cognitive Training (CCT) with and without cognitive mediation on Executive Function (EF) (planning and self- regulation) and on psychological resiliency among adolescents with Attention Deficits Hyperactive Disorder (ADHD) with or without Learning Disabilities (LD). Adolescents diagnosed with Attention Deficit Disorder and / or Learning Disabilities have multidimensional impairments that result from neurological damage. This work explored the possibility of influencing cognitive aspects in the field of Executive Functions (specifically: patterns of planning and self-regulation) among adolescents with a diagnosis of Attention Deficit Disorder and / or Learning Disabilities who study for a 10-12 grades. 46 adolescents with ADHD and/or with LD were randomly applied to experimental and control groups. All the participants were tested (BRC- research version, Resiliency quaternaries) before and after the intervention: mediated/ non-mediated Computerized Cognitive Training (MINDRI). The results indicated significant effects of cognitive modification in the experimental group, between pre and post Phases, in comparison to control group, especially in self- regulation (BRC- research version, Resiliency quaternaries), and on process analysis of Computerized Cognitive Training (MINDRI). The main conclusion was that even short- term mediation synchronized with CCT could greatly enhance the performance of executive functions demands. Theoretical implications for the positive effects of MLE in combination with CCT indicate the ability for cognitive change. The practical implication is the awareness and understanding of efficient intervention processes to enhance EF, learning awareness, resiliency and self-esteem of adolescents in their academic and daily routine.

Keywords: attention deficits hyperactive disorder, computerized cognitive training, executive function, mediated learning experience, learning disabilities

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Authors: Mohamad R. Moshtagh, Ahmad Bagheri

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Accurate fault detection in rotating machinery is of utmost importance to ensure optimal performance and prevent costly downtime in industrial applications. This study presents a robust fault detection system based on vibration data collected from rotating gears under various operating conditions. The considered scenarios include: (1) both gears being healthy, (2) one healthy gear and one faulty gear, and (3) introducing an imbalanced condition to a healthy gear. Vibration data was acquired using a Hentek 1008 device and stored in a CSV file. Python code implemented in the Spider environment was used for data preprocessing and analysis. Winner features were extracted using the Wiener feature selection method. These features were then employed in multiple machine learning algorithms, including Convolutional Neural Networks (CNN), Multilayer Perceptron (MLP), K-Nearest Neighbors (KNN), and Random Forest, to evaluate their performance in detecting and classifying faults in both the training and validation datasets. The comparative analysis of the methods revealed the superior performance of the Wiener-CNN approach. The Wiener-CNN method achieved a remarkable accuracy of 100% for both the two-class (healthy gear and faulty gear) and three-class (healthy gear, faulty gear, and imbalanced) scenarios in the training and validation datasets. In contrast, the other methods exhibited varying levels of accuracy. The Wiener-MLP method attained 100% accuracy for the two-class training dataset and 100% for the validation dataset. For the three-class scenario, the Wiener-MLP method demonstrated 100% accuracy in the training dataset and 95.3% accuracy in the validation dataset. The Wiener-KNN method yielded 96.3% accuracy for the two-class training dataset and 94.5% for the validation dataset. In the three-class scenario, it achieved 85.3% accuracy in the training dataset and 77.2% in the validation dataset. The Wiener-Random Forest method achieved 100% accuracy for the two-class training dataset and 85% for the validation dataset, while in the three-class training dataset, it attained 100% accuracy and 90.8% accuracy for the validation dataset. The exceptional accuracy demonstrated by the Wiener-CNN method underscores its effectiveness in accurately identifying and classifying fault conditions in rotating machinery. The proposed fault detection system utilizes vibration data analysis and advanced machine learning techniques to improve operational reliability and productivity. By adopting the Wiener-CNN method, industrial systems can benefit from enhanced fault detection capabilities, facilitating proactive maintenance and reducing equipment downtime.

Keywords: fault detection, gearbox, machine learning, wiener method

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Authors: Lorena Caires Moreira, Marcos Kauffman

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This paper outlines the results of experimental research on deploying an emerging augmented reality (AR) system for real-time task assistance of highly customized and high-risk manual operations. The focus is on operators’ training capabilities and the aim is to test if such technologies can support achieving higher levels of knowledge retention and accuracy of task execution to improve health and safety (H and S) levels. The proposed solution is tested and validated using a real-world case study of electric vehicles’ battery module assembly. The experimental results revealed that the proposed AR method improved the training practices by increasing the knowledge retention levels from 40% to 84% and improved the accuracy of task execution from 20% to 71%, compared to the traditional paper-based method. The results of this research can be used as a demonstration of how emerging technologies are advancing the choice of manual, hybrid, or fully automated processes by promoting the connected worker (Industry 5.0) and supporting manufacturing in becoming more resilient in times of constant market changes.

Keywords: augmented reality, extended reality, connected worker, XR-assisted operator, manual assembly, industry 5.0, smart training, battery assembly

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Authors: Abdulatif Abdulsalam Mohamed Shaban

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This paper states that the art of Procedure Entry Array (PEA) plan with a focus on control system applications. This paper begins with an impression of PEA technology development, followed by an arrangement of design technologies, and the use of programmable description languages and system-level design tools. They allow a practical approach based on a unique model for complete engineering electronics systems. There are three main design rules are implemented in the system. These are algorithm based fine-tuning, modularity, and the control act and the architectural constraints. An overview of contributions and limits of PEAs is also given, followed by a short survey of PEA-based gifted controllers for recent engineering systems. Finally, two complete and timely case studies are presented to illustrate the benefits of a PEA implementation when using the proposed system modelling and devise attitude. These consist of the direct control for training motor drives and the control of a diesel-driven stand-alone generator with the help of logical design.

Keywords: control (DC), engineering electronics systems, training motor drives, procedure entry array

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Authors: Chien-kuo Chang, Bo-wei Wu, Yi-yun Tang, Min-chiu Wu

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This paper proposes a power equipment diagnosis system based on partial discharge (PD), which is characterized by increasing the readability of experimental data and the convenience of operation. This system integrates a variety of analysis programs of different data formats and different programming languages and then establishes a set of interfaces that can follow and expand the structure, which is also helpful for subsequent maintenance and innovation. This study shows a case of using the developed Convolutional Neural Networks (CNN) to integrate with this system, using the designed model architecture to simplify the complex training process. It is expected that the simplified training process can be used to establish an adaptive deep learning experimental structure. By selecting different test data for repeated training, the accuracy of the identification system can be enhanced. On this platform, the measurement status and partial discharge pattern of each equipment can be checked in real time, and the function of real-time identification can be set, and various training models can be used to carry out real-time partial discharge insulation defect identification and insulation state diagnosis. When the electric power equipment entering the dangerous period, replace equipment early to avoid unexpected electrical accidents.

Keywords: partial discharge, convolutional neural network, partial discharge analysis platform, adaptive deep learning

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Authors: Lucy Tsado

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As cybercrime and cyberattacks continue to increase, the need to respond will follow suit. When cybercrimes occur, the duty to respond sometimes falls on law enforcement. However, criminal justice students are not taught concepts in cybersecurity and digital forensics. There is, therefore, an urgent need for many more institutions to begin teaching cybersecurity and related courses to social science students especially criminal justice students. However, many faculty in universities, colleges, and high schools are not equipped to teach these courses or do not have the knowledge and resources to teach important concepts in cybersecurity or digital forensics to criminal justice students. This research intends to develop curricula and training programs to equip faculty with the skills to meet this need. There is a current call to involve non-technical fields to fill the cybersecurity skills gap, according to experts. There is a general belief among non-technical fields that cybersecurity education is only attainable within computer science and technologically oriented fields. As seen from current calls, this is not entirely the case. Transitioning into the field is possible through curriculum development, training, certifications, internships and apprenticeships, and competitions. There is a need to identify how a cybersecurity eco-system can be created at a university to encourage/start programs that will lead to an interest in cybersecurity education as well as attract potential students. A short-term strategy can address this problem through curricula development, while a long-term strategy will address developing training faculty to teach cybersecurity and digital forensics. Therefore this research project addresses this overall problem in two parts, through curricula development for the criminal justice discipline; and training of faculty in criminal justice to teaching the important concepts of cybersecurity and digital forensics.

Keywords: cybersecurity education, criminal justice, curricula development, nontechnical cybersecurity, cybersecurity, digital forensics

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Authors: Magdy Abouzeid, Nancy Abouzeid, Afaf Salem

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Background: The elite child athletes are one who has superior athletic talent. Monofin (a single surface swim fin) swimming already proved to be the most efficient method of swimming for human being. This is a novel descriptive study examining myocardial function indices in prepubertal monofin children. The aim of the present study was to determine the influence of long-term monofin training (LTMT), 36 weeks, 6 times per week, 90 min per unit on Myocardial function adaptation in elite child monofin athletes. Methods: 14 elite monofin children aged 11.95 years (± 1.09 yr) took part for (LTMT). All subjects underwent two-dimension, M-mode, and Doppler echocardiography before and after training to evaluate cardiac dimensions and function; septal and posterior wall thickness. Statistical methods of SPSS, means ± SD and paired t test, % of improvement were used. Findings: There was significant difference (p<0.01) and % improvement for all echocardiography parameter after (LTMT). Inter ventricular septal thickness in diastole and in systole increased by 27.9 % and 42.75 %. Left ventricular end systolic dimension and diastole increased by 16.81 % and 42.7 % respectively. Posterior wall thickness in systole very highly increased by 283.3 % and in diastole increased by 51.78 %. Left ventricular mass in diastole and in systole increased by 44.8 % and 40.1 % respectively. Stroke volume (SV) and resting heart rate (HR) significant changed (sv) 25 %, (HR) 14.7 %. Interpretation: the unique swim fin tool and create propulsion and overcome resistance. Further researches are needed to determine the effects of monofin training on right ventricular in child athletes.

Keywords: prepubertal, monofin training, heart athlete's, elite child athlete, echocardiography

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Authors: Siddarth Kannan

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Objectives: Deep Brain Stimulation (DBS) and Motor Cortex stimulation (MCS) are innovative interventions in order to treat various neuropathic pain disorders such as post-stroke pain. While each treatment has a varying degree of success in managing pain, comparative analysis has not yet been performed, and the success rates of these techniques using validated, objective pain scores have not been synthesised. The aim of this study was to compare the effect of pain relief offered by MCS and DBS on patients with post-stroke pain and to assess if either of these procedures offered better results. Methods: A systematic review and meta-analysis were conducted in accordance with PRISMA guidelines (PROSPEROID CRD42021277542). Three databases were searched, and articles published from 2000 to June 2023 were included (last search date 25 June 2023). Meta-analysis was performed using random effects models. We evaluated the performance of DBS or MCS by assessing studies that reported pain relief using the Visual Analogue Scale (VAS). Data analysis of descriptive statistics was performed using SPSS (Version 27; IBM; Armonk; NY; USA). R statistics (Rstudio Version 4.0.1) was used to perform meta-analysis. Results: Of the 478 articles identified, 27 were included in the analysis (232 patients- 117 DBS & 115 MCS). The pooled number of patients who improved after DBS was 0.68 (95% CI, 0.57-0.77, I2=36%). The pooled number of patients who improved after MCS was 0.72 (95% CI, 0.62-0.80, I2=59%). Further sensitivity analysis was done to include only studies with a minimum of 5 patients in order to assess if there was any impact on the overall results. Nine studies each for DBS and MCS met these criteria. There seemed to be no significant difference in results. Conclusions: The use of surgical interventions such as DBS and MCS is an upcoming field for the treatment of post-stroke pain, with limited studies exploring and comparing these two techniques. While our study shows that MCS might be a slightly better treatment option, further research would need to be done in order to determine the appropriate surgical intervention for post-stroke pain.

Keywords: post-stroke pain, deep brain stimulation, motor cortex stimulation, pain relief

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Authors: Adebayo Emmanuel Layi

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Library and Information Science Education is about six (6) decades old in Nigeria. The first Library School was established in 1962 at the University of Ibadan, and since then, several institutions have been running the programme under various certifications, providing the manpower needs of professionals for libraries. As at June 2023, Nigeria has close to a thousand (1000) tertiary institutions and all needing the services of librarians. Apart from the tertiary institutions, several libraries exit in various establishments, both government, private and non-governmental organisations. These has underscored the enormous need for trained librarians for the libraries in these places. The Nexus between LIS Education training and Practice is like a puzzle of egg and chick, which one came first and against this background, this paper examined the roles of the colonial masters in educational development in Africa and vis-à-vis the influence of great library educators such as Melvil Dewey and other educators and the journey through Nigeria institutions. Despite the sound footing of LIS Education, Noise which seems to be a major obstacle on the practice as well as mending the broken link were all examined in the paper. Strategies and the way forward for overall development are suggested.

Keywords: nexus, education, training, synergy

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Authors: Anastasiya Paltarzhitskaya

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Subjective time plays an important role in consciousness processes and self-awareness at the moment. The concept of intrinsic neural timescales (INT) explains the difference in perceiving various time intervals. The capacity to experience the present builds on the fundamental properties of temporal cognition. The challenge that both philosophy and neuroscience try to answer is how the brain differentiates the present from the past and future. In our work, we analyze papers which describe mechanisms involved in the perception of ‘present’ and ‘non-present’, i.e., future and past moments. Taking into account that we perceive time intervals even during rest or relaxation, we suppose that the default-mode network activity can code time features, including the present moment. We can compare some results of time perceptual studies, where brain activity was shown in states with different flows of time, including resting states and during “mental time travel”. According to the concept of mental traveling, we employ a range of scenarios which demand episodic memory. However, some papers show that the hippocampal region does not activate during time traveling. It is a controversial result that is further complicated by the phenomenological aspect that includes a holistic set of information about the individual’s past and future.

Keywords: temporal consciousness, time perception, memory, present

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Authors: Angelika Lau

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One aspect totally underrepresented regarding the effectiveness of gamification in education is gameful experience. To examine the extent to which gameful experience has been considered empirically, a systematic review was conducted. By doing so, comprehensive state-of-the-art research of gameful experience in higher education and organizational training is provided. This way, the actual gameful efficiency of gamification applications is disclosed and summarized. The review indicates that gamification provides positive effects, however, emphasizing the need for further research in this regard.

Keywords: game experience, gameful experience, game-like experience, gamification

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Authors: E. K. Soyele

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This study is on capacity building and motivation as determinants of productivity among library personnel in colleges of education in South West, Nigeria. This study made use of a descriptive research design of survey type. A total enumeration sampling technique was used for the selected sample. The research sample consisted of 40 library personnel. The instrument used for the study was a structured questionnaire divided into four parts. Statistics data analysis used were descriptive statistics with frequencies, percentages, and regression statistics analysis. Findings from this study revealed that capacity building and motivation have positive impact on library personnel productivity with their percentages greater than 50% acceptance level. A test of null hypotheses at P < 0.05 significant level was tested to see the significance between capacity building and productivity, which was positive at P < 0.05 significant level. This implies that capacity building and motivation significantly determine productivity among library personnel in selected college libraries in Nigeria. The study concluded that there is need for institutions to equip their library personnel via training programmes, in-service, digital training, ICT training, seminars, and conferences, etc. Incentives should be provided to motivate personnel for high productivity. The study, therefore, recommends that government, institutions and library management should fund college libraries adequately so as to enhance capacity building, staff commitment and training for further education

Keywords: capacity building, library personnel, motivation, productivity

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Authors: Leif Inge Tjelta, Gerd Lise Nordbotten, Cathrine Nyhus Hagum, Merete Hagen Helland

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Overweight and obesity can lead to numerous health problems, and inactive people are more often overweight and obese compared to physically active people. Even a moderate weight loss can improve cardiovascular and endocrine disease risk factors. The aim of the study was to examine to what extent overweight and obese adults starting up with two weekly intensive running sessions had an increase in aerobic capacity, reduction in BMI and waist circumference and changes in body composition after 33 weeks of training. An additional aim was to see if there were differences between participants who, in addition to training, also received lifestyle modification education, including practical cooking (nutritional guidance and training group (NTG =32)) compared to those who were not given any nutritional guidance (training group (TG=40)). 72 participants (49 women), mean age of 46.1 ( ± 10.4) were included. Inclusion Criteria: Previous untrained and inactive adults in all age groups, BMI ≥ 25, desire to become fitter and reduce their BMI. The two weekly supervised training sessions consisted of 10 min warm up followed by 20 to 21 min effective interval running where the participants’ heart rate were between 82 and 92% of hearth rate maximum. The sessions were completed with ten minutes whole body strength training. Measures of BMI, waist circumference (WC) and 3000m running time were performed at the start of the project (T1), after 15 weeks (T2) and at the end of the project (T3). Measurements of fat percentage, muscle mass, and visceral fat were performed at T1 and T3. Twelve participants (9 women) from both groups, who all scored around average on the 3000 m pre-test, were chosen to do a VO₂max test at T1 and T3. The NTG were given ten theoretical sessions (80 minutes each) and eight practical cooking sessions (140 minutes each). There was a significant reduction in bout groups for WC and BMI from T1 to T2. There was not found any further reduction from T2 to T3. Although not significant, NTG reduced their WC more than TG. For both groups, the percentage reduction in WC was similar to the reduction in BMI. There was a decrease in fat percentage in both groups from pre-test to post-test, whereas, for muscle mass, a small, but insignificant increase was observed for both groups. There was a decrease in 3000m running time for both groups from T1 to T2 as well as from T2 to T3. The difference between T2 and T3 was not statistically significant. The 12 participants who tested VO₂max had an increase of 2.86 ( ± 3.84) mlkg⁻¹ min⁻¹ in VO₂max and 3:02 min (± 2:01 min) reduction in running time over 3000 m from T1 until T3. There was a strong, negative correlation between the two variables. The study shows that two intensive running session in 33 weeks can increase aerobic fitness and reduce BMI, WC and fat percent in inactive adults. Cost guidance in addition to training will give additional effect.

Keywords: interval training, nutritional guidance, fitness, BMI

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Authors: Bernabeo R. Alberto

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With the tremendous improvements in the processing power of computers, the possibilities of artificial intelligence will increasingly be used in aviation and make autonomous flights, preventive maintenance, ATM (Air Traffic Management) optimization, pilots, cabin crew, ground staff, and airport staff training possible in a cost-saving, less time-consuming and less polluting way. Through the use of artificial intelligence, we foresee an interviewing scenario where the interviewee will interact with the artificial intelligence tool to contextualize the character and the necessary information in a way that aligns reasonably with the character and the scenario. We are creating simulated scenarios connected with either an aviation incident or accident to enhance also the training of future accident/incident investigators integrating artificial intelligence and augmented reality tools. The project's goal is to improve the learning and teaching scenario through academic and professional expertise in aviation and in the artificial intelligence field. Thus, we intend to contribute to the needed high innovation capacity, skills, and training development and management of artificial intelligence, supported by appropriate regulations and attention to ethical problems.

Keywords: artificial intelligence, aviation accident, aviation incident, risk, safety

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Authors: Skiker Kaoutar, Mounir Maouene

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Neuroimaging studies have shown that animal and tool concepts rely on distinct networks of brain areas. Animal concepts depend predominantly on temporal areas while tool concepts rely on fronto-temporo-parietal areas. However, the origin of this neurofunctional distinction for processing animal and tool concepts remains still unclear. Here, we address this question from a network perspective suggesting that the neural distinction between animals and tools might reflect the differences in their structural semantic networks. We build semantic networks for animal and tool concepts derived from McRae and colleagues’s behavioral study conducted on a large number of participants. These two networks are thus analyzed through a large number of graph theoretical measures for small-worldness: centrality, clustering coefficient, average shortest path length, as well as resistance to random and targeted attacks. The results indicate that both animal and tool networks have small-world properties. More importantly, the animal network is more vulnerable to targeted attacks compared to the tool network a result that correlates with brain lesions studies.

Keywords: animals, tools, network, semantics, small-worls, resilience to damage

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Authors: Ilham Akbar Rahman, Aflah Dhea Bariz Yasta, Iin Fadhilah Utami Tamasse, Devina Juanita

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Meningioma is adult brain tumors originating from the meninges covering the brain and spinal cord. The females have approximately twice higher 2:1 than male in the incidence of meningioma. This study aimed to analyze the histopathological grading and clinical aspect in predicting the prognosis of meningioma patients. An observational study with cross sectional design was used on 53 meningioma patients treated at Dr. Wahidin Sudirohusodo hospital in 2016. The data then were analyzed using SPSS 20.0. Of 53 patients, mostly 41 (77,4%) were female and 12 (22,6%) were male. The distribution of histopathology patients showed the meningothelial meningioma of 18 (43,9%) as the most type found. Fibroplastic meningioma were 8 (19,5%), while atypical meningioma and psammomatous meningioma were 6 (14,6%) each. The rest were malignant meningioma and angiomatous meningioma which found in respectively 2 (4,9%) and 1 (2,4%). Our result found significant finding that mostly male were fibroblastic meningioma (50%), however meningothelial meningioma were found in the majority of female (54,8%) and also seizure comprised only in higher grade meningioma. On the outcome of meningioma patient treated operatively, histopathological grade remained insignificant (p > 0,05). This study can be used as prognostic value of meningioma patients based on gender, histopathological grade, and clinical manifestation. Overall, the outcome of the meningioma’s patients is good and promising as long as it is well managed.

Keywords: meningioma, prognostic value, histopathological grading, clinical manifestation

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Authors: Christoph Linse, Thomas Martinetz

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Recent findings have shown that Neural Networks generalize also in over-parametrized regimes with zero training error. This is surprising, since it is completely against traditional machine learning wisdom. In our empirical study we fortify these findings in the domain of fine-grained image classification. We show that very large Convolutional Neural Networks with millions of weights do learn with only a handful of training samples and without image augmentation, explicit regularization or pretraining. We train the architectures ResNet018, ResNet101 and VGG19 on subsets of the difficult benchmark datasets Caltech101, CUB_200_2011, FGVCAircraft, Flowers102 and StanfordCars with 100 classes and more, perform a comprehensive comparative study and draw implications for the practical application of CNNs. Finally, we show that VGG19 with 140 million weights learns to distinguish airplanes and motorbikes with up to 95% accuracy using only 20 training samples per class.

Keywords: convolutional neural networks, fine-grained image classification, generalization, image recognition, over-parameterized, small data sets

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Authors: Norman Sinnigen, Igor Izyurov, Marina Krylova, Hamidreza Jamalabadi, Sarah Alizadeh, Martin Walter

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Background: EEG is a non-invasive brain activity recording technique with a high temporal resolution that allows the use of real-time applications, such as neurofeedback. However, EEG data are susceptible to electrooculographic (EOG) and electromyography (EMG) artifacts (i.e., jaw clenching, teeth squeezing and forehead movements). Due to their non-stationary nature, these artifacts greatly obscure the information and power spectrum of EEG signals. Many EEG artifact correction methods are too time-consuming when applied to low-density EEG and have been focusing on offline processing or handling one single type of EEG artifact. A software-only real-time method for correcting multiple types of EEG artifacts of high-density EEG remains a significant challenge. Methods: We demonstrate an improved approach for automatic real-time EEG artifact correction of EOG and EMG artifacts. The method was tested on three healthy subjects using 64 EEG channels (Brain Products GmbH) and a sampling rate of 1,000 Hz. Captured EEG signals were imported in MATLAB with the lab streaming layer interface allowing buffering of EEG data. EMG artifacts were detected by channel variance and adaptive thresholding and corrected by using channel interpolation. Real-time independent component analysis (ICA) was applied for correcting EOG artifacts. Results: Our results demonstrate that the algorithm effectively reduces EMG artifacts, such as jaw clenching, teeth squeezing and forehead movements, and EOG artifacts (horizontal and vertical eye movements) of high-density EEG while preserving brain neuronal activity information. The average computation time of EOG and EMG artifact correction for 80 s (80,000 data points) 64-channel data is 300 – 700 ms depending on the convergence of ICA and the type and intensity of the artifact. Conclusion: An automatic EEG artifact correction algorithm based on channel variance, adaptive thresholding, and ICA improves high-density EEG recordings contaminated with EOG and EMG artifacts in real-time.

Keywords: EEG, muscle artifacts, ocular artifacts, real-time artifact correction, real-time ICA

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Authors: Benjamin D Reese Jr

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Implicit bias is understood as unconscious attitudes, stereotypes, or associations that can influence the cognitions, actions, decisions, and interactions of an individual without intentional control. These unconscious attitudes or stereotypes are often targeted toward specific groups of people based on their gender, race, age, perceived sexual orientation or other social categories. Since the late 1980s, there has been a proliferation of research that hypothesizes that the operation of implicit bias is the result of the brain needing to process millions of bits of information every second. Hence, one’s prior individual learning history provides ‘shortcuts’. As soon as one see someone of a certain race, one have immediate associations based on their past learning, and one might make assumptions about their competence, skill, or danger. These assumptions are outside of conscious awareness. In recent years, an alternative conceptualization has been proposed. The ‘bias of crowds’ theory hypothesizes that a given context or situation influences the degree of accessibility of particular biases. For example, in certain geographic communities in the United States, there is a long-standing and deeply ingrained history of structures, policies, and practices that contribute to racial inequities and bias toward African Americans. Hence, negative biases among groups of people towards African Americans are more accessible in such contexts or communities. This theory does not focus on individual brain functioning or cognitive ‘shortcuts.’ Therefore, attempts to modify individual perceptions or learning might have negligible impact on those embedded environmental systems or policies that are within certain contexts or communities. From the ‘bias of crowds’ perspective, high levels of racial bias in a community can be reduced by making fundamental changes in structures, policies, and practices to create a more equitable context or community rather than focusing on training or education aimed at reducing an individual’s biases. The current paper acknowledges and supports the foundational role of long-standing structures, policies, and practices that maintain racial inequities, as well as inequities related to other social categories, and highlights the critical need to continue organizational, community, and national efforts to eliminate those inequities. It also makes a case for providing individual leaders with a deep understanding of the dynamics of how implicit biases impact cognitions, actions, decisions, and interactions so that those leaders might more effectively develop structural changes in the processes and systems under their purview. This approach incorporates both the importance of an individual’s learning history as well as the important variables within the ‘bias of crowds’ theory. The paper also offers a model for leadership education, as well as examples of structural changes leaders might consider.

Keywords: implicit bias, unconscious bias, bias, inequities

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Authors: Rachnavy Pornthep, Khaothin Thawichai

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The purpose of this paper was to investigate the effects of rowing ergometer exercise on older persons health. The subjects were divided into two groups. Group 1 was control group (10 male and 10 female) Group 2 was experimental group (10 male and 10 female). The time for study was 12 week. Group 1 engage in normal daily activities Group 2 Training with rowing machine for 20 minutes three days a week. The average age of the experimental group was 73.7 years old, mean weight 55.4 kg, height 154.8 cm in the control group, mean age was 74.95 years, mean weight 48.6 kg, mean height 153.85 cm. Physical fitness test composted of body size, flexibility, Strength, muscle endurance and cardiovascular endurance. The comparison between the experimental and control groups before training showed that body weight, body mass index and waist to hip ratio were significantly different. The flexibility, strength, cardiovascular endurance was not significantly different. The comparison between the control group and the experimental group after training showed that body weight, body mass index and cardiovascular endurance were significantly different. The ratio of waist to hips, flexibility and muscular strength were not significantly different. Comparison of physical fitness before training and after training of the control group showed that body weight, flexibility (Sit and reach) and muscular strength (30 – Second chair stand) were significantly different. Body mass index, waist to hip ratio, muscles flexible (Shoulder girdle flexibility), muscle strength (30 – Second arm curl) and the cardiovascular endurance were not significantly difference. Comparison of physical fitness before training and after training the experimental group showed that waist to hip ratio, flexibility (sit and reach) muscle strength (30 – Second chair stand), cardiovascular endurance (Standing leg raises - up to 2 minutes) were significantly different. The Body mass index and the flexibility (Shoulder girdle flexibility) no significantly difference. The study found that exercising with rowing machine can improve the physical fitness of the elderly, especially the cardiovascular endurance, corresponding with the past research on the effects of exercise in the elderly with different exercise such as cycling, treadmill, walking on the elliptical machine. Therefore, we can conclude that exercise by using rowing machine can improve cardiovascular system and flexibility in the elderly.

Keywords: effect, rowing, exercise, elderly

Procedia PDF Downloads 495

Authors: Abdul Rashid Ahmadi, Samiullah Paracha, Hamidullah Sokout, Mohammad Hanif Gharana

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Conventional educational practices, do not offer all the required skills for teachers to successfully survive in today’s workplace. Due to poor professional training, a big gap exists across the curriculum plan and the teacher practices in the classroom. As such, raising the quality of teaching through ICT-enabled training and professional development of teachers should be an urgent priority. ‘Mobile Learning’, in that vein, is an increasingly growing field of educational research and practice across schools and work places. In this paper, we propose a novel Mobile learning system that allows the users to learn through an intelligent mobile learning in cooperatively every-time and every-where. The system will reduce the training cost and increase consistency, efficiency, and data reliability. To establish that our system will display neither functional nor performance failure, the evaluation strategy is based on formal observation of users interacting with system followed by questionnaires and structured interviews.

Keywords: computer assisted learning, intelligent tutoring system, learner centered design, mobile mediated learning and teacher education

Procedia PDF Downloads 292