Search results for: knowledge management incentives

Authors: Zaw Z Aung

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Background: High-risk groups for hepatitis B infection (HBV) are people who injected drugs (PWID), men who have sex with men (MSM), people living with HIV (PLHIV) and persons with hepatitis C (HCV), etc. HBV/HCV coinfected patients are at increased risk of cirrhosis, hepatic decompensation and hepatocellular carcinoma. To the best of author’s knowledge, there is currently no data for hepatitis B vaccine utilization in HCV positive patients and their antibody response. Methodology: From February 2018 to May 2018, consented participants at or above 18 years who came to the clinic in Mandalay were tested with the anti-HCV rapid test. Those who tested HCV positive (n=168) were further tested with hepatitis B profile and asked about their previous hepatitis B vaccination history and risk factors. Results: Out of 168 HCV positive participants, three were excluded for active HBV infections. The remaining 165 were categorized into previously vaccinated 64% (n=106) and unvaccinated 36% (n=59) There were three characteristics groups- PWID monoinfected (n=77), General Population (GP) monoinfected (n=22) and HIV/HCV coinfected participants (n=66). Unvaccinated participants were highest in HIV/HCV, with 68%(n=45) followed by GP (23%, n=5) and PWID (12%, n=9). Among previously vaccinated participants, the highest percentage was PWID (88%, n=68), the second highest was GP (77%, n=17) and lowest in HIV/HCV patients (32%, n=21). 63 participants completed third doses of vaccination (PWID=36, GP=13, HIV/HCV=14). 53% of participants who completed 3 dose of hepatitis B were non-responders (n=34): HIV/HCV (86%, n=12), PWID (44%, n=16), and GP (46%, n=6) Conclusion: Even in the presence of effective and safe hepatitis B vaccine, uptake is low among high risk groups especially PLHIV that needs to be improved. Integration or collaboration of hepatitis B vaccination program, HIV/AIDS and hepatitis C treatment centers is desirable. About half of vaccinated participants were non-responders so that optimal doses, schedule and follow-up testing need to be addressed carefully for those groups.

Keywords: Hepatitis B vaccine, Hepatitis C, HIV, Myanmar

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Authors: Yi-Ling Lin, Lu-Ming Tseng

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Customer sexual harassment is recognized as a serious problem in the personal selling industry. At a personal level, customer sexual harassment could have very negative impacts on the salespeople's physical and mental health. At the organizational level, customer sexual harassment is destructive in terms of organizational reputation. Therefore, this research takes Taiwan's life insurance salesperson as the research sample and explores the impacts of customer power and perceived behavioral control on the life insurance salespeople's whistleblowing intentions to report quid pro quo and hostile work environment types of customer sexual harassment. This study then investigates how personal factors (such as gender difference) may relate to the intentions. Questionnaires are often used as a data collection instrument in studies on workplace sexual harassment. This study collects data through questionnaire surveys, and the research sample of this research is the full-time life insurance salespeople in Taiwan. The hypotheses are examined by using PLS regression approach. The main results show that the types of customer sexual harassment, customer power, and gender are related to the whistleblowing intentions. To our best knowledge, this is the first empirical study to test the relationships among customer reward power, customer coercive power, perceived behavioral control, and the salespeople's whistleblowing intentions toward customer sexual harassment. The findings may provide some implications for the researchers and official authorities.

Keywords: customer sexual harassment, life insurance salespeople, perceived behavioral control, PLS regression

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Authors: Chih-I. Tsai, Yu-Chien. Lin

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Through experiences of clinical practices, it is discovered that locations on the body at a level of four fingerbreadth above and below the joints are the points at which muscles connect to tendons, and since the muscles and tendons possess opposite characteristics, muscles are full of blood but lack qi, while tendons are full of qi but lack blood, these points on our body become easily blocked. It is proposed that through doing acupuncture or creating localized pressure to the areas four fingerbreadths above and below our joints, with an elastic bandage, we could help the energy, also known as qi, to flow smoothly in our body and further improve our health. Based on the Four Fingers Theory, we understand that human height is 22 four fingerbreadths. In addition, qi and blood travel through 24 meridians, 50 times each day, and they flow through 6 cun with every human breath. We can also understand the average number of human heartbeats is 75 times per minute. And the function of qi-blood circulation system in Traditional Chinese Medicine is the same as the blood circulation in Western Medical Science. Informed by Four Fingers Theory, this study further examined its applications in acupuncture practices. The research question is how Four Fingers Theory proves what has been mentioned in Nei Jing that there are 66 acupoints under a human’s elbow and knee. In responding to the research question, there are 66 acupoints under a human’s elbow and knee. Four Fingers Theory facilitated the creation of the acupuncture naming and teaching system. It is expected to serve as an approachable and effective way to deliver knowledge of acupuncture to the public worldwide.

Keywords: four fingers theory, meridians circulation, 66 acupoints under human elbow and knee, acupuncture

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Authors: Christina Knorr

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Analysis of the evacuation of occupants of a building plays a significant role in Fire Safety Engineering. One of the tools used for the analysis is the concept of the Required Safe Egress Time (RSET). It is generally accepted that RSET is measured from the time the fire ignites until the time that all occupants have evacuated to a safe location. Instructions on how RSET is determined can be found in both the International Fire Engineering Guidelines and, more recently, in the Australian Fire Engineering Guidelines. The guidelines also specify measures that could be applied to reduce the RSET and hence improve the performance of fire-safety measures of a building. Further, it is suggested that the delay period can be reduced through “training programs.” This study examined the overall level of fire-safety awareness among occupants of residential apartment buildings in Australia and investigated the possible effects of fire-safety training on the delay period and, hence, the RSET. A questionnaire, interviews, and an experiment were conducted to collect data about people’s fire-safety knowledge, people’s behaviour and nature, and the duration of activities people are likely to undertake in the event of a fire. The study led to an investigation into the delay and response time approximations and the development of a new equation to incorporate the impact of training into the RSET calculations for the general use of the fire engineering community. Regardless of the RSET, it can be concluded that fire-safety education and training for residents of apartment buildings have a direct impact on improving their behaviour and firefighting equipment usage in a fire incident.

Keywords: fire safety engineering, fire safety training, occupant evacuation behaviour, required safe egress time

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Authors: Mohammed Alhammad

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The movement towards the inclusion of students with special educational needs (SEN) in mainstream schools has become widely accepted practice in many countries. However in Saudi Arabia, this is not happening. Instead the practice for students with learning difficulties (LD) is to study in special classrooms in mainstream schools and they are not included with their peers, except at break times and morning assembly, and on school trips. There are a number of barriers that face implementing inclusion for students with LD in mainstream classrooms: one such barrier is the training of teachers. The training, either pre- or in-service, that teachers receive is seen as playing an important role in leading to the successful implementation of inclusion. The aim of this presentation is to explore how pre-service training and in-service training are acting as barriers for implementing inclusion of students with LD in mainstream primary schools in Saudi Arabia from the perspective of teachers. The qualitative research approach was used to explore this barrier. Twenty-four teachers (general education teachers, special education teachers) were interviewed using semi-structured interview and a number of documents were used as method of data collection. The result showed teachers felt that not much attention was paid to inclusion in pre-services training for general education teachers and special education teachers in Saudi Arabia. In addition, pre-service training for general education teachers does not normally including modules on special education. Regarding the in-service training, no courses at all about inclusion are provided for teachers. Furthermore, training courses in special education are few. As result, the knowledge and skills required to implemented inclusion successfully.

Keywords: inclusion, learning difficulties, Saudi Arabia, training

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Authors: Zikra Faiz, Zaheer Asghar, Nisar Abid

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Information and Communication Technologies (ICTs) includes computers, the Internet, and electronic delivery systems such as televisions, radios, multimedia, and overhead projectors etc. In the modern world, ICTs is considered as an essential element of the teaching-learning process. The study was aimed to discover the usage of ICTs in Special Education Institutions for Visually Impaired students, Lahore, Pakistan. Objectives of the study were to explore the problems faced by teachers while using ICT in the classroom. The study was phenomenology in nature; a qualitative survey method was used through a semi-structured interview protocol developed by the researchers. The sample comprised of eighty faculty members selected through a purposive sampling technique. Data were analyzed through thematic analysis technique with the help of open coding. The study findings revealed that multimedia, projectors, computers, laptops and LEDs are used in special education institutes to enhance the teaching-learning process. Teachers believed that ICTs could enhance the knowledge of visually impaired students and every student should use these technologies in the classroom. It was concluded that multimedia, projectors and laptops are used in classroom by teachers and students. ICTs can promote effectively through the training of teachers and students. It was suggested that the government should take steps to enhance ICTs in teacher training and other institutions by pre-service and in-service training of teachers.

Keywords: information and communication technologies, in-services teachers, special education institutions

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Authors: D. Venu, N. V. Koteswara Rao

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Space – time adaptive processing (STAP) is an effective tool for detecting a moving target in spaceborne or airborne radar systems. Since airborne passive radar systems utilize broadcast, navigation and excellent communication signals to perform various surveillance tasks and also has attracted significant interest from the distinct past, therefore the need of the hour is to have cost effective systems as compared to conventional active radar systems. Moreover, requirements of small number of secondary samples for effective clutter suppression in bi-static passive radar offer abundant illuminator resources for passive surveillance radar systems. This paper presents a framework for incorporating knowledge sources directly in the space-time beam former of airborne adaptive radars. STAP algorithm for clutter mitigation for passive bi-static radar has better quantitation of the reduction in sample size thereby amalgamating the earlier data bank with existing radar data sets. Also, we proposed a novel method to estimate the clutter matrix and perform STAP for efficient clutter suppression based on small sample size. Furthermore, the effectiveness of the proposed algorithm is verified using MATLAB simulations in order to validate STAP algorithm for passive bi-static radar. In conclusion, this study highlights the importance for various applications which augments traditional active radars using cost-effective measures.

Keywords: bistatic radar, clutter, covariance matrix passive radar, STAP

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Authors: Pedro Rubio

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Antonio Romero y Andía, was one of the most active and interesting figures in 19th century Spanish music. He was not only an exceptional clarinetist, he was also a publisher, a brilliant oboist, a music critic, and he revitalized Madrid’s musical scene by promoting orchestras and a national opera. In 1849, Romero was appointed Professor of Clarinet at the Conservatory of Madrid. Shortly after, Romero introduced to Spain the Boehm-System clarinet recently appeared in France. However, when initial interest in that system waned, he conceived his own system in 1853. The clarinet was manufactured in Paris by Lefêvre, who registered its first patent in 1862. In 1867 a second version was patented, and a year earlier, in 1866, the Romero clarinet was adopted as an official instrument for teaching the clarinet at the Conservatory of Madrid. The Romero-System clarinet mechanism has incorporated numerous additional devices and several extra keys, its skillful combination in a single instrument represents not only one of the pinnacles in the manufacture of musical instruments of the 19th century, but also an authentic synthesis of knowledge and practice in an era in which woodwind instruments were shaped as we know them today. Through the description and analysis of the data related to the aforementioned historical period, this lecture will try to show a crucial time in the history of all woodwind instruments, a period of technological effervescence in which the Romero-System clarinet emerged. The different stages of conception of the clarinet will be described, as well as its manufacturing and marketing process. Romero played with his clarinet system over twenty-five years. The research has identified the repertoire associated with this instrument whose conclusions will be presented in its case in the Congress.

Keywords: Antonio Romero, clarinet, keywork, 19th century

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Authors: Yasaman Mohammadi

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Executive functions are a critical component of goal-directed behavior, encompassing a diverse set of cognitive processes such as working memory, cognitive flexibility, and inhibitory control. These functions are known to decline with age, but the precise mechanisms underlying this decline remain unclear. This paper provides an in-depth review of recent research investigating age-related changes in executive functions, drawing on insights from neuroimaging, genetics, and cognitive neuroscience. Through an interdisciplinary approach, this paper offers a nuanced understanding of the complex interplay between neural mechanisms, genetic factors, and cognitive processes that contribute to executive function decline in aging. Here, we investigate how different neuroimaging methods, like functional magnetic resonance imaging (fMRI) and positron emission tomography (PET), have helped scientists better understand the brain bases for age-related declines in executive function. Additionally, we discuss the role of genetic factors in mediating individual differences in executive functions across the lifespan, as well as the potential for cognitive interventions to mitigate age-related decline. Overall, this paper presents a comprehensive and integrative view of the current state of knowledge regarding age-related changes in executive functions. It underscores the need for continued interdisciplinary research to fully understand the complex and dynamic nature of executive function decline in aging, with the ultimate goal of developing effective interventions to promote healthy cognitive aging.

Keywords: executive functions, aging, neuroimaging, cognitive neuroscience, working memory, cognitive training

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Authors: Emad Al-Abdallat, Faris G. Bakri, Azmi Mahafza, Rayyan Al Ali, Nidaa Ababneh, Ahmed Idhair

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Background: Morgues are high-risk areas for the spread of infection from the cadavers to the staff during the postmortem examination. Infection can spread from corpses to workers by the airborne route, by direct contact, or from needle and sharp object injuries. Objective: Knowledge about the prevalence of these infections among autopsies is prudent to appreciate any risk of transmission and to further enforce safety measures. Method: A total of 242 autopsies were tested. Age ranged from 3 days to 94 years (median 75.5 years, mean 45.3 (21.9 ± SD)). There were 172 (71%) males. Results: The cause of death was considered natural in 137 (56.6%) cases, accidental in 89 (36.8%), homicidal in 9 (3.7%), suicidal in 4 (1.7%), and unknown in 3 (1.2%). Hepatitis B surface antigen was positive in 5 (2.1%) cases. Hepatitis C virus antibody was detected in 5 (2.1%) cases and the hepatitis C virus polymerase chain reaction was positive in 2 of them (0.8%). HIV antibody was not detected in any of the cases. Conclusions: Autopsies can be associated with exposure to blood borne viruses. Autopsies performed during the study period were tested for hepatitis B surface antigen, hepatitis C virus antibody, and human immunodeficiency virus antibody. Positive tests were subsequently confirmed by polymerase chain reaction. There is low prevalence of infections with these viruses in our autopsy cases. However, the risk of transmission remains a threat. Healthcare workers in the forensic departments should adhere to standard precautions.

Keywords: autopsy, hepatitis B virus, hepatitis C virus, human immunodeficiency virus, Jordan

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Authors: Beatriz González-rodrigo, Diego Hidalgo-leiva, Omar Flores, Claudia Germoso, Maribel Jiménez-martínez, Laura Navas-sánchez, Belén Orta, Nicola Tarque, Orlando Hernández- Rubio, Miguel Marchamalo, Juan Gregorio Rejas, Belén Benito-oterino

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Cities facing seismic hazard necessitate detailed risk assessments for effective urban planning and vulnerability identification, ensuring the safety and sustainability of urban infrastructure. Comprehensive studies involving seismic hazard, vulnerability, and exposure evaluations are pivotal for estimating potential losses and guiding proactive measures against seismic events. However, broad-scale traditional risk studies limit consideration of specific local threats and identify vulnerable housing within a structural typology. Achieving precise results at neighbourhood levels demands higher resolution seismic hazard exposure, and vulnerability studies. This research aims to bolster sustainability and safety against seismic disasters in three Central American and Caribbean capitals. It integrates geospatial techniques and artificial intelligence into seismic risk studies, proposing cost-effective methods for exposure data collection and damage prediction. The methodology relies on prior seismic threat studies in pilot zones, utilizing existing exposure and vulnerability data in the region. Emphasizing detailed building attributes enables the consideration of behaviour modifiers affecting seismic response. The approach aims to generate detailed risk scenarios, facilitating prioritization of preventive actions pre-, during, and post-seismic events, enhancing decision-making certainty. Detailed risk scenarios necessitate substantial investment in fieldwork, training, research, and methodology development. Regional cooperation becomes crucial given similar seismic threats, urban planning, and construction systems among involved countries. The outcomes hold significance for emergency planning and national and regional construction regulations. The success of this methodology depends on cooperation, investment, and innovative approaches, offering insights and lessons applicable to regions facing moderate seismic threats with vulnerable constructions. Thus, this framework aims to fortify resilience in seismic-prone areas and serves as a reference for global urban planning and disaster management strategies. In conclusion, this research proposes a comprehensive framework for seismic risk assessment in high-risk urban areas, emphasizing detailed studies at finer resolutions for precise vulnerability evaluations. The approach integrates regional cooperation, geospatial technologies, and adaptive fragility curve adjustments to enhance risk assessment accuracy, guiding effective mitigation strategies and emergency management plans.

Keywords: assessment, behaviour modifiers, emergency management, mitigation strategies, resilience, vulnerability

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Authors: Vhuhwavho Gadisi, Rebecca Alowo, German Nkhonjera

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This article sets out to detail an investigation of groundwater management in the Juksei Catchment of South Africa through spatial mapping of key hydrological relationships, interactions, and parameters in catchments. The Department of Water Affairs (DWA) noted gaps in the implementation of the South African National Water Act 1998: article 16, including the lack of appropriate models for dealing with water quantity parameters. For this reason, this research conducted a drastic GIS-based groundwater assessment to improve groundwater monitoring system in the Juksei River basin catchment of South Africa. The methodology employed was a mixed-methods approach/design that involved the use of DRASTIC analysis, questionnaire, literature review and observations to gather information on how to help people who use the Juskei River. GIS (geographical information system) mapping was carried out using a three-parameter DRASTIC (Depth to water, Recharge, Aquifer media, Soil media, Topography, Impact of the vadose zone, Hydraulic conductivity) vulnerability methodology. In addition, the developed vulnerability map was subjected to sensitivity analysis as a validation method. This approach included single-parameter sensitivity, sensitivity to map deletion, and correlation analysis of DRASTIC parameters. The findings were that approximately 5.7% (45km2) of the area in the northern part of the Juksei watershed is highly vulnerable. Approximately 53.6% (428.8 km^2) of the basin is also at high risk of groundwater contamination. This area is mainly located in the central, north-eastern, and western areas of the sub-basin. The medium and low vulnerability classes cover approximately 18.1% (144.8 km2) and 21.7% (168 km2) of the Jukskei River, respectively. The shallow groundwater of the Jukskei River belongs to a very vulnerable area. Sensitivity analysis indicated that water depth, water recharge, aquifer environment, soil, and topography were the main factors contributing to the vulnerability assessment. The conclusion is that the final vulnerability map indicates that the Juksei catchment is highly susceptible to pollution, and therefore, protective measures are needed for sustainable management of groundwater resources in the study area.

Keywords: contamination, DRASTIC, groundwater, vulnerability, model

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Authors: Nia McRae, Robert Wright, Ghalib Bello

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Introduction: Postpartum depression is a prevalent mood disorder that is detrimental to the mental and physical health of mothers and their newborns. Lead (Pb) is a toxic metal that is associated with hormonal imbalance and mental impairments. The hormone changes that accompany pregnancy and childbirth may be exacerbated by Pb and increase new mothers’ susceptibility to postpartum depression. To the best of the author’s knowledge, this is the only study that investigates the association between prenatal Pb exposure and postpartum depression. Identifying risk factors can contribute to improved prevention and treatment strategies for postpartum depression. Methods: Data was derived from the Programming Research in Obesity, Growth, Environment and Social Stress (PROGRESS) study which is an ongoing longitudinal birth cohort. Postpartum depression was identified by a score of 13 or above on the 10-Item Edinburg Postnatal Depression Scale (EPDS) 6-months and 12-months postpartum. Pb was measured in the blood (BPb) in the second and third trimester and in the tibia and patella 1-month postpartum. Quantile regression models were used to assess the relationship between BPb and postpartum depression. Results: BPb in the second trimester was negatively associated with the 80th percentile of depression 6-months postpartum (β: -0.26; 95% CI: -0.51, -0.01). No significant association was found between BPb in the third trimester and depression 6-months postpartum. BPb in the third trimester exhibited an inverse relationship with the 60th percentile (β: -0.23; 95% CI: -0.41, -0.06), 70th percentile (β: -0.31; 95% CI: -0.52, -0.10), and 90th percentile of depression 12-months postpartum (β: -0.36; 95% CI: -0.69, -0.03). There was no significant association between BPb in the second trimester and depression 12-months postpartum. Bone Pb concentrations were not significantly associated with postpartum depression. Conclusion: The negative association between BPb and postpartum depression may support research which demonstrates lead is a nontherapeutic stimulant. Further research is needed to verify these results and identify effect modifiers.

Keywords: depression, lead, postpartum, prenatal

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Authors: Dhiraj Biswas, Chaitali Ray

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A modified refined higher order zigzag theory has been developed in this paper in order to compute the accurate interlaminar stresses within hybrid laminates. Warping has significant effect on the mechanical behaviour of the laminates. To the best of author(s)’ knowledge the stress analysis of hybrid laminates is not reported in the published literature. The present paper aims to develop a new C0 continuous element based on the refined higher order zigzag theories considering warping effect in the formulation of hybrid laminates. The eight noded isoparametric plate bending element is used for the flexural analysis of laminated composite plates to study the performance of the proposed model. The transverse shear stresses are computed by using the differential equations of stress equilibrium in a simplified manner. A computer code has been developed using MATLAB software package. Several numerical examples are solved to assess the performance of the present finite element model based on the proposed higher order zigzag theory by comparing the present results with three-dimensional elasticity solutions. The present formulation is validated by comparing the results obtained from the relevant literature. An extensive parametric study has been carried out on the hybrid laminates with varying percentage of materials and angle of orientation of fibre content.

Keywords: hybrid laminate, Interlaminar stress, refined higher order zigzag theory, warping effect

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Authors: Felipe A. Guth, Shane Ward, Kevin McDonnell

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The assessment of disease levels in crop fields is an important and time-consuming task that generally relies on expert knowledge of trained individuals. Image classification in agriculture problems historically has been based on classical machine learning strategies that make use of hand-engineered features in the top of a classification algorithm. This approach tends to not produce results with high accuracy and generalization to the classes classified by the system when the nature of the elements has a significant variability. The advent of deep convolutional neural networks has revolutionized the field of machine learning, especially in computer vision tasks. These networks have great resourcefulness of learning and have been applied successfully to image classification and object detection tasks in the last years. The objective of this work was to propose a new method based on deep learning convolutional neural networks towards the task of disease level monitoring. Common RGB images of winter wheat were obtained during a growing season. Five categories of disease levels presence were produced, in collaboration with agronomists, for the algorithm classification. Disease level tasks performed by experts provided ground truth data for the disease score of the same winter wheat plots were RGB images were acquired. The system had an overall accuracy of 84% on the discrimination of the disease level classes.

Keywords: crop disease assessment, deep learning, precision agriculture, residual neural networks

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Authors: Hala Alshamlan, Ghada Badr, Yousef Alohali

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Cancer is one of the dreadful diseases, which causes considerable death rate in humans. DNA microarray-based gene expression profiling has been emerged as an efficient technique for cancer classification, as well as for diagnosis, prognosis, and treatment purposes. In recent years, a DNA microarray technique has gained more attraction in both scientific and in industrial fields. It is important to determine the informative genes that cause cancer to improve early cancer diagnosis and to give effective chemotherapy treatment. In order to gain deep insight into the cancer classification problem, it is necessary to take a closer look at the proposed gene selection methods. We believe that they should be an integral preprocessing step for cancer classification. Furthermore, finding an accurate gene selection method is a very significant issue in a cancer classification area because it reduces the dimensionality of microarray dataset and selects informative genes. In this paper, we classify and review the state-of-art gene selection methods. We proceed by evaluating the performance of each gene selection approach based on their classification accuracy and number of informative genes. In our evaluation, we will use four benchmark microarray datasets for the cancer diagnosis (leukemia, colon, lung, and prostate). In addition, we compare the performance of gene selection method to investigate the effective gene selection method that has the ability to identify a small set of marker genes, and ensure high cancer classification accuracy. To the best of our knowledge, this is the first attempt to compare gene selection approaches for cancer classification using microarray gene expression profile.

Keywords: gene selection, feature selection, cancer classification, microarray, gene expression profile

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Authors: Mihail Nagea, Olivera Lupescu, Elena Taina Avramescu, Cristina Patru

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Classical education of orthopedic surgeons involves lectures, self study, workshops and cadaver dissections, and sometimes supervised practical training within surgery, which quite seldom gives the young surgeons the feeling of being unable to apply what they have learned especially in surgical practice. The purpose of this paper is to present a different approach from the classical one, which enhances the practical skills of the orthopedic trainees and prepare them for future practice. The paper presents the content of the research project 2015-1-RO01-KA202-015230, ERASMUS+ VET ‘Collaborative learning for enhancing practical skills for patient-focused interventions in gait rehabilitation after orthopedic surgery’ which, using e learning as a basic tool , delivers to the trainees not only courses, but especially practical information through videos and case scenarios including gait analysis in order to build patient focused therapeutic plans, adapted to the characteristics of each patient. The outcome of this project is to enhance the practical skills in orthopedic surgery and the results are evaluated following the answers to the questionnaires, but especially the reactions within the case scenarios. The participants will thus follow the idea that any mistake within solving the cases might represent a failure of treating a real patient. This modern approach, besides using interactivity to evaluate the theoretical and practical knowledge of the trainee, increases the sense of responsibility, as well as the ability to react properly in real cases.

Keywords: interdisciplinary approach, gait analysis, orthopedic surgery, vocational training

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Authors: Davies Obaromi, Qin Yongsong, James Ndege, Azeez Adeboye, Akinwumi Odeyemi

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The basic model usually used in disease mapping, is the Besag, York and Mollie (BYM) model and which combines the spatially structured and spatially unstructured priors as random effects. Bayesian Conditional Autoregressive (CAR) model is a disease mapping method that is commonly used for smoothening the relative risk of any disease as used in the Besag, York and Mollie (BYM) model. This model (CAR), which is also usually assigned as a prior to one of the spatial random effects in the BYM model, successfully uses information from adjacent sites to improve estimates for individual sites. To our knowledge, there are some unrealistic or counter-intuitive consequences on the posterior covariance matrix of the CAR prior for the spatial random effects. In the conventional BYM (Besag, York and Mollie) model, the spatially structured and the unstructured random components cannot be seen independently, and which challenges the prior definitions for the hyperparameters of the two random effects. Therefore, the main objective of this study is to construct and utilize an extended Bayesian spatial CAR model for studying tuberculosis patterns in the Eastern Cape Province of South Africa, and then compare for flexibility with some existing CAR models. The results of the study revealed the flexibility and robustness of this alternative extended CAR to the commonly used CAR models by comparison, using the deviance information criteria. The extended Bayesian spatial CAR model is proved to be a useful and robust tool for disease modeling and as a prior for the structured spatial random effects because of the inclusion of an extra hyperparameter.

Keywords: Besag2, CAR models, disease mapping, INLA, spatial models

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Authors: Viktoriia Malinovska, Iryna Kuklina, Katerina Grabicova, Milos Buric, Pavel Kozak

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Personal care products, including organic UV filters, are considered emerging contaminants and their toxic effects have been a concern for the last decades. Sunscreen compounds continually enter the surface waters via sewage water treatment due to incomplete removal and during human recreational and laundry activities. Despite the environmental occurrence of organic UV filters in the freshwater environment, little is known about their impacts on aquatic biota. In this study, environmentally relevant concentrations of 5-Benzoyl-4-hydroxy-2-methoxybenzenesulfonic acid (BP-4, 2.5 µg/L) and 2-Phenylbenzimidazole-5-sulfonic acid (PBSA, 3 µg/L) were used to evaluate the cardiac and locomotor responses of signal crayfish Pacifastacus leniusculus during a short time period. The effects of these compounds were evident in experimental animals. Specimens exposed to both tested compounds exhibited significantly bigger changes in distance moved and time movement than controls. Significant differences in changes in mean heart rate were detected in both PBSA and BP-4 experimental groups compared to control groups. Such behavioral and physiological alterations demonstrate the ecological effects of selected sunscreen compounds during a short time period. Since the evidence of the impacts of sunscreen compounds is scarce, the knowledge of how organic UV filters influence aquatic organisms is of key importance for future research.

Keywords: aquatic pollutants, behavior, freshwaters, heart rate, invertebrate

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Authors: Matthew Kostawich, Mohammed Elmorsy, Mohamed Sayed Sifat, Shoukry Shams, Mahmoud Elsaadany

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6G communication systems represent the nominal future extension of current wireless technology, where its impact is extended to touch upon all human activities, including medical, security, and entertainment applications. As a result, human needs are allocated among the highest priority aspects of the system design and requirements. 6G communications is expected to replace all the current video conferencing with interactive virtual reality meetings involving high data-rate transmission merged with massive distributed computing resources. In addition, the current expansion of IoT applications must be mitigated with significant network changes to provide a reasonable Quality of Service (QoS). This directly implies a high demand for Human-Computer Interaction (HCI) through mobile computing modules in future wireless communication systems. This article proposes the utilization of a Printed Ridge Gap Waveguide (PRGW) to host the wearable nodes. To the best of our knowledge, we propose for the first time a physical layer analysis within the context of a complete architecture. A thorough study is provided on the impact of the distortion of the guiding structure on the overall system performance. The proposed structure shows small latency and small losses, highlighting its compatibility with future applications.

Keywords: ridge gap waveguide, edge computing module, 6G, multimedia IoT applications

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Authors: Dragana Gnjatovic

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Assessment is a burning topic in education policy and practice due to measurement-driven neoliberal agendas of quality and standardisation of assessment practice through high stakes standardised testing systems that are now influencing early childhood education. This paper presents a collaborative, arts-informed action research project which places children at the centre of their learning, with assessment as an integral part of play-based learning processes. It aims to challenge traditional approaches to assessment that are often teacher-led and decontextualised from the processes of learning through exploring approaches where children's voices are central, and their creative arts expressions are used to assess learning and development. The theoretical framework draws on Vygotsky's sociocultural theory and Freire's critical pedagogy, which indicate the importance of socially constructed reality where knowledge is the result of collaboration between children and adults. This reality perceives children as competent agents of their own learning processes. An interpretive-constructivist and critical-transformative paradigm underpin collaborative action research in a three to five-year-old setting, where creative methods like storytelling, play, drama, drawing are used to assess children's learning. As data collection and analysis are still in process, this paper will present the methodology and some data vignettes, with the aim of stimulating discussion about innovation in assessment and contribution of the collaborative enquiry in the field of Early Childhood Education and Care.

Keywords: assessment for learning, creative methodologies, collaborative action research, early childhood education and care

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Authors: E. Kempen, M. J. Labuschagne, M. P. Jama

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There is evidence that experiential learning is truly influential and favored by the millennial generation. However, little is known about the role and attributes an educator has to adopt during the experiential learning cycle, especially when applied in optometry education. This study aimed to identify the roles and attributes of an optometry educator during the different modes of the experiential learning cycle. Methods: A qualitative case study design was used. Data was collected using an open-ended questionnaire survey, following the application of nine different teaching-learning methods based on the experimental learning cycle. The total sample population of 68 undergraduate students from the Department of Optometry at the University of the Free State, South Africa were invited to participate. Focus group interviews (n=15) added additional data that contributed to the interpretation and confirmation of the data obtained from the questionnaire surveys. Results: The perceptions and experiences of the students identified a variety of roles and attributes as well as recommendations on the effective adoption of these roles and attributes. These roles and attributes included being knowledgeable, creating an interest, providing guidance, being approachable, building confidence, implementing ground rules, leading by example, and acting as a mediator. Conclusion: The findings suggest that the actions of an educator have the most substantial impact on students’ perception of a learning experience. Not only are the recommendations based on the views of a millennial generation, but the implementation of the personalized recommendations may also transform a learning environment. This may lead an optometry student to a deeper understanding of knowledge.

Keywords: experiences and perceptions, experiential learning, millennial generation, recommendation for optometry education

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Authors: Anny Lucrece Nlend Nkott, Ludovic Temple

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The appearance in 2012 of the CRISPR-CaS9 genome editing technique marks a turning point in the field of genetics. This technique would make it possible to create new varieties quickly and cheaply. Although some consider CRISPR-CaS9 to be revolutionary, others consider it a potential societal threat. To document the controversy, we explain the socioeconomic conditions under which this technique could be accepted for the creation of a rainfed rice variety in Madagascar. The methodological framework is based on 38 individual and semistructured interviews, a multistakeholder forum with 27 participants, and a survey of 148 rice producers. Results reveal that the acceptability of genome editing requires (i) strengthening the seed system through the operationalization of regulatory structures and the upgrading of stakeholders' knowledge of genetically modified organisms, (ii) assessing the effects of the edited variety on biodiversity and soil nitrogen dynamics, and (iii) strengthening the technical and human capacities of the biosafety body. Structural mechanisms for regulating the seed system are necessary to ensure safe experimentation of genome editing techniques. Organizational innovation also appears to be necessary. The study documents how collective learning between communities of scientists and nonscientists is a component of systemic processes of varietal innovation. This study was carried out with the financial support of the GENERICE project (Generation and Deployment of Genome-Edited, Nitrogen-use-Efficient Rice Varieties), funded by the Agropolis Foundation.

Keywords: CRISPR-CaS9, varietal innovation, seed system, innovation system

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Authors: Ali Kazemi

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Those within the volatile and interconnected international economic markets, appropriately predicting market trends, hold substantial fees for traders and financial establishments. Traditional device mastering strategies have made full-size strides in forecasting marketplace movements; however, monetary data's complicated and networked nature calls for extra sophisticated processes. This observation offers a groundbreaking method for monetary marketplace prediction that leverages the synergistic capability of Graph Convolutional Networks (GCNs) and Long Short-Term Memory (LSTM) networks. Our suggested algorithm is meticulously designed to forecast the traits of inventory market indices and cryptocurrency costs, utilizing a comprehensive dataset spanning from January 1, 2015, to December 31, 2023. This era, marked by sizable volatility and transformation in financial markets, affords a solid basis for schooling and checking out our predictive version. Our algorithm integrates diverse facts to construct a dynamic economic graph that correctly reflects market intricacies. We meticulously collect opening, closing, and high and low costs daily for key inventory marketplace indices (e.g., S&P 500, NASDAQ) and widespread cryptocurrencies (e.g., Bitcoin, Ethereum), ensuring a holistic view of marketplace traits. Daily trading volumes are also incorporated to seize marketplace pastime and liquidity, providing critical insights into the market's shopping for and selling dynamics. Furthermore, recognizing the profound influence of the monetary surroundings on financial markets, we integrate critical macroeconomic signs with hobby fees, inflation rates, GDP increase, and unemployment costs into our model. Our GCN algorithm is adept at learning the relational patterns amongst specific financial devices represented as nodes in a comprehensive market graph. Edges in this graph encapsulate the relationships based totally on co-movement styles and sentiment correlations, enabling our version to grasp the complicated community of influences governing marketplace moves. Complementing this, our LSTM algorithm is trained on sequences of the spatial-temporal illustration discovered through the GCN, enriched with historic fee and extent records. This lets the LSTM seize and expect temporal marketplace developments accurately. Inside the complete assessment of our GCN-LSTM algorithm across the inventory marketplace and cryptocurrency datasets, the version confirmed advanced predictive accuracy and profitability compared to conventional and opportunity machine learning to know benchmarks. Specifically, the model performed a Mean Absolute Error (MAE) of 0.85%, indicating high precision in predicting day-by-day charge movements. The RMSE was recorded at 1.2%, underscoring the model's effectiveness in minimizing tremendous prediction mistakes, which is vital in volatile markets. Furthermore, when assessing the model's predictive performance on directional market movements, it achieved an accuracy rate of 78%, significantly outperforming the benchmark models, averaging an accuracy of 65%. This high degree of accuracy is instrumental for techniques that predict the course of price moves. This study showcases the efficacy of mixing graph-based totally and sequential deep learning knowledge in economic marketplace prediction and highlights the fee of a comprehensive, records-pushed evaluation framework. Our findings promise to revolutionize investment techniques and hazard management practices, offering investors and economic analysts a powerful device to navigate the complexities of cutting-edge economic markets.

Keywords: financial market prediction, graph convolutional networks (GCNs), long short-term memory (LSTM), cryptocurrency forecasting

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Authors: Peng Liu

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Deep Q networks (DQNs) represent a significant advancement in reinforcement learning, utilizing neural networks to approximate the optimal Q-value for guiding sequential decision processes. This paper presents a comprehensive introduction to reinforcement learning principles, delves into the mechanics of DQNs, and explores its application in portfolio optimization. By evaluating the performance of DQNs against traditional benchmark portfolios, we demonstrate its potential to enhance investment strategies. Our results underscore the advantages of DQNs in dynamically adjusting asset allocations, offering a robust portfolio management framework.

Keywords: deep reinforcement learning, deep Q networks, portfolio optimization, multi-period optimization

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Authors: Kalsoom Sumra

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The increasing concern of public sector reforms brings new challenges to public service ethics in developing countries not only at central level but also at local level. This paper aims to identify perceptions on public service ethics of public officials and examines more generally the understanding of public servants in Pakistan towards public service ethics in local public organizations. The study uses an independently administered structured questionnaire to collect data to know the extent of the recognition of public service ethics in local organizations. A total of 150 completed questionnaires are analyzed received from public servants working at the local level in Pakistan. The analysis explores how traditional, social patterns and cultural ethics can provide us with a rounded picture of the main antecedents, moderators of public service ethics in Pakistan. Moreover, the findings of this study contribute in association of public service ethics which are crucial in ongoing political and administrative culture of Pakistan, the most crucial core for public organizational ethical climate. This study also has numerous implications for local public administration and it highlights the importance of expanding research agenda on public service ethics in developing settings with challenging institutional contexts with imperfect training and operating environments. This study may well be particularly important for practice of public service ethics in developing countries in public administration. To the best of author’s knowledge, this study is the first of its kind to provide an initial step in practical implications to emphasize relevant public service ethics in public administration in developing transparent and accountable organization.

Keywords: public service ethics, accountability and transparency, public service reforms, public administration, organizational ethical climate

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Authors: Yawei Liang

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Threat from cruise missiles is among the most dangerous considerations to a warship in the modern era: anti-ship cruise missiles are fast, accurate, and extremely destructive. In this paper, the goal was to use an object-orientated environment to program a simulation to model a scenario in which a lone frigate is attacked by a wave of missiles fired at given intervals. The parameters of the simulation are modified to examine the relationships between different variables in the situation, and an analysis is performed on various aspects of the defending ship’s equipment. Finally, the results are presented, along with a brief discussion.

Keywords: discrete event simulation, Monte Carlo simulation, naval resource management, weapon-target allocation/assignment

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Authors: Rebekah Volgin, Jane Shakespeare-Finch, Ian Shochet

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Commercial sexual exploitation (CSE) and sex trafficking affect between 5000-7000 girls and women in Nepal each year and can have devastating physical and psychological consequences. Much research has documented these effects, however, there is no published longitudinal research that focuses on whether healing and growth outcomes are possible for survivors of CSE and sex trafficking. The narratives of 27 girls and women (13-22 years) were taken at two-time points during participation in a six-week group psychoeducation and art therapy program which was delivered across three NGO’s in Kathmandu, Nepal. These narratives form part of a larger ethnographic project. Thematic analysis of the data was undertaken. Themes emerging from time point 1 were: psychological distress in the form of anxiety and grief over loss of family, psychosomatic symptoms, empathy and compassion, and posttraumatic growth (PTG) in the form of new possibilities, relating to others and personal strength. Posttraumatic growth refers to positive changes in the aftermath of trauma. The themes emerging from time point 2, were: empathy and compassion and PTG (cognitive restructuring, new possibilities, relating to others and personal strength). Alongside the distress that these participants experienced, they also experienced positive outcomes such as empathy and compassion and psychological growth. Future research would advance knowledge by further examining the process of PTG in this population, if the changes observed were lasting, and if so, ways in which PTG can be facilitated or promoted.

Keywords: commercial sexual exploitation, human trafficking, posttraumatic growth, sexual trauma

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Authors: Bakari Mohammed

Abstract:

Sports performance and achievements have been the avenue through which great nations of the world exhibit their supremacy over others through sports development strategy. Effective sports development, therefore, requires variables like sports policy, sports funding, sports programme, sports facilities and sponsorship. The extent to what these variables are met shall no doubt affects the effectiveness of any sports development. Two distinguishing features of the Nigerian sports system are its central organization and its employment for specific socio-political objectives, it is against this backdrop that this paper will x-ray the politicization of sports which parallels sports development in the enhanced role of sports and in contrast with developed nations system and management.

Keywords: sport development, sport policy, personnel, program, facilities, funding, sponsorship

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Authors: Emilienne Lardy, Eric Ballot, Mariam Lafkihi

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Efficient urban logistics requires a comprehensive understanding of traffic dynamics, particularly as it pertains to kinetic parameters influencing energy consumption and trip duration estimations. While real-time traffic information is increasingly accessible, current high-precision forecasting services embedded in route planning often function as opaque 'black boxes' for users. These services, typically relying on AI-processed counting data, fall short in accommodating open design parameters essential for management studies, notably within Supply Chain Management. This work revisits the modelling of traffic conditions in the context of city logistics, emphasizing its significance from the user’s point of view, with two focuses. Firstly, the focus is not on the vehicle flow but on the vehicles themselves and the impact of the traffic conditions on their driving behaviour. This means opening the range of studied indicators beyond vehicle speed, to describe extensively the kinetic and dynamic aspects of the driving behaviour. To achieve this, we leverage the Art. Kinema parameters are designed to characterize driving cycles. Secondly, this study examines how the driving context (i.e., exogenous factors to the traffic flow) determines the mentioned driving behaviour. Specifically, we explore how accurately the kinetic behaviour of a vehicle can be predicted based on a limited set of exogenous factors, such as time, day, road type, orientation, slope, and weather conditions. To answer this question, statistical analysis was conducted on real-world driving data, which includes high-frequency measurements of vehicle speed. A Factor Analysis and a Generalized Linear Model have been established to link kinetic parameters with independent categorical contextual variables. The results include an assessment of the adjustment quality and the robustness of the models, as well as an overview of the model’s outputs.

Keywords: factor analysis, generalised linear model, real world driving data, traffic congestion, urban logistics, vehicle kinematics

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