Search results for: teaching and learning effectiveness

Authors: Kritchakhris Na-Wattanaprasert

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The objective of this research is to design and develop a prototype of a key performance indicator system this is suitable for warehouse management in a case study and use requirement. In this study, we design a prototype of key performance indicator system (KPI) for warehouse case study of furniture business by methodology in step of identify scope of the research and study related papers, gather necessary data and users requirement, develop key performance indicator base on balance scorecard, design pro and database for key performance indicator, coding the program and set relationship of database and finally testing and debugging each module. This study use Balance Scorecard (BSC) for selecting and grouping key performance indicator. The system developed by using Microsoft SQL Server 2010 is used to create the system database. In regard to visual-programming language, Microsoft Visual C# 2010 is chosen as the graphic user interface development tool. This system consists of six main menus: menu login, menu main data, menu financial perspective, menu customer perspective, menu internal, and menu learning and growth perspective. Each menu consists of key performance indicator form. Each form contains a data import section, a data input section, a data searches – edit section, and a report section. The system generates outputs in 5 main reports, the KPI detail reports, KPI summary report, KPI graph report, benchmarking summary report and benchmarking graph report. The user will select the condition of the report and period time. As the system has been developed and tested, discovers that it is one of the ways to judging the extent to warehouse objectives had been achieved. Moreover, it encourages the warehouse functional proceed with more efficiency. In order to be useful propose for other industries, can adjust this system appropriately. To increase the usefulness of the key performance indicator system, the recommendations for further development are as follows: -The warehouse should review the target value and set the better suitable target periodically under the situation fluctuated in the future. -The warehouse should review the key performance indicators and set the better suitable key performance indicators periodically under the situation fluctuated in the future for increasing competitiveness and take advantage of new opportunities.

Keywords: key performance indicator, warehouse management, warehouse operation, logistics management

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Authors: Adel Khorramrouz, Monireh Ahmadi Bani, Ehsan Norouzi

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Background:-Due to the essential role of the foot in movement, foot disorders (FDs) have significant impacts on activity and quality of life. Many studies confirmed the association between FDs and demographic characteristics. On the other hand, recent advances in data collection and statistical analysis led to an increase in the volume of databases. Analysis of patient’s data through the decision tree can be used to explore the relationship between demographic characteristics and FDs. Significance of the study: This study aimed to investigate the relationship between demographic characteristics with common FDs. The second purpose is to better inform foot intervention, we classify FDs based on demographic variables. Methodologies: We analyzed 2323 subjects with pes-planus (PP), pes-cavus (PC), hallux-valgus (HV) and plantar-fasciitis (PF) who were referred to a foot therapy clinic between 2015 and 2021. Subjects had to fulfill the following inclusion criteria: (1) weight between 14 to 150 kilogram, (2) height between 30 to 220, (3) age between 3 to 100 years old, and (4) BMI between 12 to 35. Medical archives of 2323 subjects were recorded retrospectively and all the subjects examined by an experienced physician. Age and BMI were classified into five and four groups, respectively. 80% of the data were randomly selected as training data and 20% tested. We build a decision tree model to classify FDs using demographic characteristics. Findings: Results demonstrated 981 subjects from 2323 (41.9%) of people who were referred to the clinic with FDs were diagnosed as PP, 657 (28.2%) PC, 628 (27%) HV and 213 (9%) identified with PF. The results revealed that the prevalence of PP decreased in people over 18 years of age and in children over 7 years. In adults, the prevalence depends first on BMI and then on gender. About 10% of adults and 81% of children with low BMI have PP. There is no relationship between gender and PP. PC is more dependent on age and gender. In children under 7 years, the prevalence was twice in girls (10%) than boys (5%) and in adults over 18 years slightly higher in men (62% vs 57%). HV increased with age in women and decreased in men. Aging and obesity have increased the prevalence of PF. We conclude that the accuracy of our approach is sufficient for most research applications in FDs. Conclusion:-The increased prevalence of PP in children is probably due to the formation of the arch of the foot at this age. Increasing BMI by applying high pressure on the foot can increase the prevalence of this disorder in the foot. In PC, the Increasing prevalence of PC from women to men with age may be due to genetics and innate susceptibility of men to this disorder. HV is more common in adult women, which may be due to environmental reasons such as shoes, and the prevalence of PF in obese adult women may also be due to higher foot pressure and housekeeping activities.

Keywords: decision tree, demographic characteristics, foot disorders, machine learning

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Authors: Olivera Lupescu, Taina Elena Avramescu, Mihail Nagea, Alexandru Dimitriu

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Acetabular fractures represent a real challenge due to their impact upon the long term function of the hip joint, and due to the risk of intra- and peri-operative complications especially that they affect young, active people. That is why treating these fractures require certain skills which must be exercised, regarding the pre-operative planning, as well as the execution of surgery.The authors retrospectively analyse 38 cases with acetabular fractures operated using the posterior approach in our hospital between 01.01.2013- 01.01.2015 for which complete medical records ensure a follow-up of 24 months, in order to establish the main causes of potential errors and to underline the methods for preventing them. This target is included in the Erasmus + project ‘Collaborative learning for enhancing practical skills for patient-focused interventions in gait rehabilitation after orthopedic surgery COR-skills’. This paper analyses the pitfalls revealed by these cases, as well as the measures necessary to enhance the practical skills of the surgeons who perform acetabular surgery. Pre-op planning matched the intra and post-operative outcome in 88% of the analyzed points, from 72% at the beginning to 94% in the last case, meaning that experience is very important in treating this injury. The main problems detected for the posterior approach were: nervous complications - 3 cases, 1 of them a complete paralysis of the sciatic nerve, which recovered 6 months after surgery, and in other 2 cases intra-articular position of the screws was demonstrated by post-operative CT scans, so secondary screw removal was necessary in these cases. We analysed this incident, too, due to lack of information about the relationship between the screws and the joint secondary to this approach. Septic complications appeared in 3 cases, 2 superficial and 1 profound (requiring implant removal). The most important problems were the reduction of the fractures and the positioning of the screws so as not to interfere with the the articular space. In posterior acetabular fractures, pre-op complex planning is important in order to achieve maximum treatment efficacy with minimum of risk; an optimal training of the surgeons insisting on the main points of potential mistakes ensure the success of the procedure, as well as a favorable outcome for the patient.

Keywords: acetabular fractures, articular congruency, surgical skills, vocational training

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Authors: Madhura Yadav

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Urban redevelopment planning initiatives in developing countries have been largely criticised due to top-down planning approach and lack of involvement of the targeted beneficiaries which have led to a challenging situation which is contrary to the perceived needs of beneficiaries. Urban renewal projects improve the lives of people and meaningful participation of community plays a pivotal role. Public perceptions on satisfaction and participation have been given less priority in the investigation, which hinders effective planning and implementation of urban renewal projects. Moreover, challenges of community participation in urban renewal projects are less documented, particularly in relation to public participation and satisfaction. There is a need for new paradigm shift focusing on community participatory approach in urban renewal projects. The over 125-year-old Bhendi Bazar in Mumbai, India is the country’s first ever cluster redevelopment project, popularly known as Bhendi Bazaar redevelopment and it will be one of the largest projects for urban rejuvenation of one of Mumbai’s oldest and dying inner city areas. The project is led by the community trust, inputs were taken from various stakeholders, including residents, commercial tenants and expert consultants to shape the master plan and design of the project. The project started in 2016 but there is a significant delay in implementing the project. The study aimed at studying and assessing public perceptions on satisfaction and the relationship between community participation and community satisfaction in Bhendi Bazaar of Mumbai, India. Furthermore, the study will outline the challenges and problems of community participation in urban renewal projects and it suggests recommendations for the future. The qualitative and quantitative methods such as reconnaissance survey, key informant interviews, focus group discussions, walking interviews, a narrative inquiry is used for analysis of data. Preliminary findings revealed that all tenants are satisfied for the redevelopment of an area but the willingness of residential tenants to move in transit accommodation has made the projects successful and reductant of some residential and commercial tenants, regulatory provisions rising to face challenges in implementation. Experiences from the case study can help to understand dynamics behind public participation and government. At the same time, they serve as an inspiration and learning opportunity for future projects to ensure that they are sustainable not only from an economic standpoint but also, a social perspective.

Keywords: urban renewal, Bhendi Bazaar, community participation, satisfaction, social perspective

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Authors: Kai-Chieh Lin, Chih-Fu Wu, Hsiang Ling Hsu, Yung-Hsiang Tu, Chia-Chen Wu

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With the rapid development of computer technology, the design of computers and keyboards moves towards a trend of slimness. The change of mobile input devices directly influences users’ behavior. Although multi-touch applications allow entering texts through a virtual keyboard, the performance, feedback, and comfortableness of the technology is inferior to traditional keyboard, and while manufacturers launch mobile touch keyboards and projection keyboards, the performance has not been satisfying. Therefore, this study discussed the design factors of slim pressure-sensitive keyboards. The factors were evaluated with an objective (accuracy and speed) and a subjective evaluation (operability, recognition, feedback, and difficulty) depending on the shape (circle, rectangle, and L-shaped), thickness (flat, 3mm, and 6mm), and force (35±10g, 60±10g, and 85±10g) of the keyboard. Moreover, MANOVA and Taguchi methods (regarding signal-to-noise ratios) were conducted to find the optimal level of each design factor. The research participants, by their typing speed (30 words/ minute), were divided in two groups. Considering the multitude of variables and levels, the experiments were implemented using the fractional factorial design. A representative model of the research samples were established for input task testing. The findings of this study showed that participants with low typing speed primarily relied on vision to recognize the keys, and those with high typing speed relied on tactile feedback that was affected by the thickness and force of the keys. In the objective and subjective evaluation, a combination of keyboard design factors that might result in higher performance and satisfaction was identified (L-shaped, 3mm, and 60±10g) as the optimal combination. The learning curve was analyzed to make a comparison with a traditional standard keyboard to investigate the influence of user experience on keyboard operation. The research results indicated the optimal combination provided input performance to inferior to a standard keyboard. The results could serve as a reference for the development of related products in industry and for applying comprehensively to touch devices and input interfaces which are interacted with people.

Keywords: input performance, mobile device, slim keyboard, tactile feedback

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Authors: Ildiko Fekete-Kertesz, Jade Chaker, Sylvain Berthelot, Viktoria Feigl, Monika Molnar, Lidia Favier

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There has been growing concern about emerging micropollutants in recent years, because of the possible environmental and health risk posed by these substances, which are released into the environment as a consequence of anthropogenic activities. Among them pharmaceuticals are currently not considered under water quality regulations; however, their potential effect on the environment have become more frequent in recent years. Due to the fact that these compounds can be detected in natural water matrices, it can be concluded, that the currently applied water treatment processes are not efficient enough for their effective elimination. To date, advanced oxidation processes (AOPs) are considered as highly competitive water treatment technologies for the removal of those organic micropollutants not treatable by conventional techniques due to their high chemical stability and/or low biodegradability. AOPs such as (photo)chemical oxidation and heterogeneous photocatalysis have proven their potential in degrading harmful organic compounds from aqueous matrices. However, some of these technologies generate reaction by-products, which can even be more toxic to aquatic organisms than the parent compounds. Thus, target compound removal does not necessarily result in the removal of toxicity. Therefore, to evaluate process efficiency the determination of the toxicity and ecotoxicity of the reaction intermediates is crucial to estimate the environmental risk of such techniques. In this context, the present study investigates the effectiveness of TiO2 assisted photodegradation for the removal of emerging water contaminants. Two drugs named losartan (used in high blood pressure medication) and levetiracetam (used to treat epilepsy) were considered in this work. The photocatalytic reactions were carried out with a commercial catalyst usually employed in photocatalysis. Moreover, the toxicity of the by-products generated during the process was assessed with various ecotoxicological methods applying aquatic test organisms from different trophic levels. A series of experiments were performed to evaluate the toxicity of untreated and treated solutions applying the Aliivibrio fischeri bioluminescence inhibition test, the Tetrahymena pyriformis proliferation inhibition test, the Daphnia magna lethality and immobilization tests and the Lemna minor growth inhibition test. The applied ecotoxicological methodology indicated sensitively the toxic effects of the treated and untreated water samples, hence the applied test battery is suitable for the ecotoxicological characterization of TiO2 based photocatalytic water treatment technologies and the indication of the formation of toxic by-products from the parent chemical compounds. Obtained results clearly showed that the TiO2 assisted photodegradation was more efficient in the elimination of losartan than levetiracetam. It was also observed that the treated levetiracetam solutions had more severe effect on the applied test organisms. A possible explanation would be the production of levetiracetam by-products, which are more toxic than the parent compound. The increased toxicity and the risk of formation of toxic metabolites represent one possible limitation to the implementation of photocatalytic treatment using TiO2 for the removal of losartan and levetiracetam. Our results proved that, the battery of ecotoxicity tests used in this work can be a promising investigation tool for the environmental risk assessment of photocatalytic processes.

Keywords: aquatic micropollutants, ecotoxicology, nano titanium dioxide, photocatalysis, water treatment

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Authors: Tayyab Ahmad, Gerard Healey

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Sustainability in built environment sector is subject to many development constraints. Building projects are developed under different requirements of deliverables which makes each project unique. For an owner organization, i.e., a higher-education institution, involved in a significant building stock, it is important to prioritize some of the sustainability initiatives over the others in order to align the sustainable building development with organizational goals. The point-based green building rating tools i.e. Green Star, LEED, BREEAM are becoming increasingly popular and are well-acknowledged worldwide for verifying a sustainable development. It is imperative to synthesize a multi-criteria decision-making tool that can capitalize on the point-based methodology of rating systems while customizing the sustainable development of building projects according to the individual requirements and constraints of the client organization. A multi-criteria decision-making tool for the University of Melbourne is developed that builds on the action-learning and experience of implementing Green Buildings at the University of Melbourne. The tool evaluates the different sustainable building initiatives based on the framework of Green Star rating tool of Green Building Council of Australia. For each different sustainability initiative the decision-making tool makes an assessment based on at least five performance criteria including the ease with which a sustainability initiative can be achieved and the potential of a sustainability initiative to enhance project objectives, reduce life-cycle costs, enhance University’s reputation, and increase the confidence in quality construction. The use of a weighted aggregation mathematical model in the proposed tool can have a considerable role in the decision-making process of a Green Building project by indexing the Green Building initiatives in terms of organizational priorities. The index value of each initiative will be based on its alignment with some of the key performance criteria. The usefulness of the decision-making tool is validated by conducting structured interviews with some of the key stakeholders involved in the development of sustainable building projects at the University of Melbourne. The proposed tool is realized to help a client organization in deciding that within limited resources which sustainability initiatives and practices are more important to be pursued than others.

Keywords: higher education institution, multi-criteria decision-making tool, organizational values, prioritizing sustainability initiatives, weighted aggregation model

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Authors: Zeta Dooly, Aidan Duane

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The collaborative European funded research and development landscape provides prime environmental conditions for multi-disciplinary teams to learn and enhance their knowledge beyond the capability of training and learning within their own organisation cocoons. Whilst the emergence of the academic entrepreneur has changed the focus of educational institutions to that of quasi-businesses, the training and professional development of lecturers and academic staff are often not formalised to the same level as industry. This research focuses on industry and academic collaborative research funded by the European Commission. The impact of research is scalable if an optimum research network is created and managed effectively. This paper investigates network embeddedness, the nature of relationships, links, and nodes within a research network, and the enhancement of the network’s knowledge. The contribution of this paper extends our understanding of establishing and maintaining effective collaborative research networks. The effects of network embeddedness are recognized in the literature as pertinent to innovation and the economy. Network theory literature claims that networks are essential to innovative clusters such as Silicon valley and innovation in high tech industries. This research provides evidence to support the impact collaborative research has on the disparate individuals toward their innovative contributions to their organisations and their own professional development. This study adopts a qualitative approach and uncovers some of the challenges of multi-disciplinary research through case study insights. The contribution of this paper recommends the establishment of scaffolding to accommodate cooperation in research networks, role appointment, and addressing contextual complexities early to avoid problem cultivation. Furthermore, it suggests recommendations in relation to network formation, intra-network challenges in relation to open data, competition, friendships, and competency enhancement. The network capability is enhanced by the adoption of the relevant theories; network theory, open innovation, and social exchange, with the understanding that the network structure has an impact on innovation and social exchange in research networks. The research concludes that there is an opportunity to deepen our understanding of the impact of network reuse and network hoping that provides scaffolding for the network members to enhance and build upon their knowledge using a progressive approach.

Keywords: research networks, competency building, network theory, case study

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Authors: Alicia Yanadira Nava Fuentes, Ilse Cervantes Camacho, Amadeo José Argüelles Cruz, Ana María Balboa Verduzco

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Augmented reality promises being present in future driving, with its immersive technology let to show directions and maps to identify important places indicating with graphic elements when the car driver requires the information. On the other side, driving is considered a multitasking activity and, for some people, a complex activity where different situations commonly occur that require the immediate attention of the car driver to make decisions that contribute to avoid accidents; therefore, the main aim of the project is the instrumentation of a platform with biometric sensors that allows evaluating the performance in driving vehicles with the influence of augmented reality devices to detect the level of attention in drivers, since it is important to know the effect that it produces. In this study, the physiological sensors EPOC X (EEG), ECG06 PRO and EMG Myoware are joined in the driving test platform with a Logitech G29 steering wheel and the simulation software City Car Driving in which the level of traffic can be controlled, as well as the number of pedestrians that exist within the simulation obtaining a driver interaction in real mode and through a MSP430 microcontroller achieves the acquisition of data for storage. The sensors bring a continuous analog signal in time that needs signal conditioning, at this point, a signal amplifier is incorporated due to the acquired signals having a sensitive range of 1.25 mm/mV, also filtering that consists in eliminating the frequency bands of the signal in order to be interpretative and without noise to convert it from an analog signal into a digital signal to analyze the physiological signals of the drivers, these values are stored in a database. Based on this compilation, we work on the extraction of signal features and implement K-NN (k-nearest neighbor) classification methods and decision trees (unsupervised learning) that enable the study of data for the identification of patterns and determine by classification methods different effects of augmented reality on drivers. The expected results of this project include are a test platform instrumented with biometric sensors for data acquisition during driving and a database with the required variables to determine the effect caused by augmented reality on people in simulated driving.

Keywords: augmented reality, driving, physiological signals, test platform

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Authors: Lee Rui, Rajeev Ramachandran

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The approach to recurrent fevers in the paediatric or adolescent age group is not a straightforward one. Causes range from infectious diseases to rheumatological conditions to endocrinopathies, and are usually accompanied by weight loss rather than weight gain. We present an interesting case of a 16-year-old girl brought by her mother to the General Pediatrics Clinic for concerns of recurrent fever paired with significant weight gain over 1.5 years, with no identifiable cause found despite extensive work-up by specialists ranging from Rheumatologists to Oncologists. This case provides a learning opportunity on the approach to weight gain paired with persistent fevers in a paediatric population, one which is not commonly encountered and prompts further evaluation and consideration of less common diagnoses. In a span of 2 years, the girl’s weight had increased from 55 kg at 13 years old (75th centile) to 73.9 kg at 16 years old (>97th centile). About 1 year into her rapid weight gain, she started developing recurrent fevers of documented temperatures > 37.5 – 38.6 every 2-3 days, resulting in school absenteeism when she was sent home after temperature-taking in school found her to be febrile. The rapid onset of weight gain paired with unexplained fevers prompted the treating physician to consider the diagnosis of ROHHAD syndrome. Rapid onset obesity with hypoventilation, hypothalamic dysfunction and autonomic dysregulation (ROHHAD) syndrome is a rare disorder first described in 2007. It is characterized by dysfunction of the autonomic and endocrine system, characterized by hyperphagia and rapid-onset weight gain. This rapid weight gain is classically followed by hypothalamic manifestations with neuroendocrine deficiencies, hypo-ventilatory breathing abnormalities, and autonomic dysregulation. ROHHAD is challenging to diagnose with and diagnosis is made based mostly on clinical judgement. However if truly diagnosed, the condition is characterized by high morbidity and mortality rates. Early recognition of sleep disorders breathing and targeted therapeutic interventions helps limit morbidity and mortality associated with ROHHAD syndrome. This case poses an interesting diagnostic challenge and a diagnosis of ROHHAD has to be considered, given the serious complications that can come with disease progression while conditions such as Munchausen’s or drug fever remain as diagnoses of exclusion until we have exhausted all other possible conditions.

Keywords: pediatrics, endocrine, weight gain, recurrent fever, adolescent

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Authors: Uraib Sharaha, Ahmad Salman, Eladio Rodriguez-Diaz, Elad Shufan, Klaris Riesenberg, Irving J. Bigio, Mahmoud Huleihel

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Antimicrobial drugs have an important role in controlling illness associated with infectious diseases in animals and humans. However, the increasing resistance of bacteria to a broad spectrum of commonly used antibiotics has become a global health-care problem. Rapid determination of antimicrobial susceptibility of a clinical isolate is often crucial for the optimal antimicrobial therapy of infected patients and in many cases can save lives. The conventional methods for susceptibility testing like disk diffusion are time-consuming and other method including E-test, genotyping are relatively expensive. Fourier transform infrared (FTIR) microscopy is rapid, safe, and low cost method that was widely and successfully used in different studies for the identification of various biological samples including bacteria. The new modern infrared (IR) spectrometers with high spectral resolution enable measuring unprecedented biochemical information from cells at the molecular level. Moreover, the development of new bioinformatics analyses combined with IR spectroscopy becomes a powerful technique, which enables the detection of structural changes associated with resistivity. The main goal of this study is to evaluate the potential of the FTIR microscopy in tandem with machine learning algorithms for rapid and reliable identification of bacterial susceptibility to antibiotics in time span of few minutes. The bacterial samples, which were identified at the species level by MALDI-TOF and examined for their susceptibility by the routine assay (micro-diffusion discs), are obtained from the bacteriology laboratories in Soroka University Medical Center (SUMC). These samples were examined by FTIR microscopy and analyzed by advanced statistical methods. Our results, based on 550 E.coli samples, were promising and showed that by using infrared spectroscopic technique together with multivariate analysis, it is possible to classify the tested bacteria into sensitive and resistant with success rate higher than 85% for eight different antibiotics. Based on these preliminary results, it is worthwhile to continue developing the FTIR microscopy technique as a rapid and reliable method for identification antibiotic susceptibility.

Keywords: antibiotics, E. coli, FTIR, multivariate analysis, susceptibility

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Authors: Xiaoyu Sun

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In recent years, the rapid development of Artificial Intelligence (AI) has extensively promoted medicine, pharmaceutical, and other related fields. The medical research and development of artificial intelligence by scientific and commercial organizations are on the fast track. The ethics review is one of the critical procedures of registration to get the products approved and launched. However, the SOPs for ethics review is not enough to guide the healthy and rapid development of artificial intelligence in healthcare in China. Ethical Review Measures for Biomedical Research Involving Human Beings was enacted by the National Health Commission of the People's Republic of China (NHC) on December 1st, 2016. However, from a legislative design perspective, it was neither updated timely nor in line with the trends of AI international development. Therefore, it was great that NHC published a consultation paper on the updated version on March 16th, 2021. Based on the most updated laws and regulations in the States and EU, and in-depth-interviewed 11 subject matter experts in China, including lawmakers, regulators, and key members of ethics review committees, heads of Regulatory Affairs in SaMD industry, and data scientists, several suggestions were proposed on top of the updated version. Although the new version indicated that the Ethics Review Committees need to be created by National, Provincial and individual institute levels, the review authorities of different levels were not clarified. The suggestion is that the precise scope of review authorities for each level should be identified based on Risk Analysis and Management Model, such as the complicated leading technology, gene editing, should be reviewed by National Ethics Review Committees, it will be the job of individual institute Ethics Review Committees to review and approve the clinical study with less risk such as an innovative cream to treat acne. Furthermore, to standardize the research and development of artificial intelligence in healthcare in the age of AI, more clear guidance should be given to data security in the layers of data, algorithm, and application in the process of ethics review. In addition, transparency and responsibility, as two of six principles in the Rome Call for AI Ethics, could be further strengthened in the updated version. It is the shared goal among all countries to manage well and develop AI to benefit human beings. Learned from the other countries who have more learning and experience, China could be one of the most advanced countries in artificial intelligence in healthcare.

Keywords: biomedical research involving human beings, data security, ethics committees, ethical review, medical artificial intelligence

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Authors: Casey Keenan Joiner, Shayna Tayloe

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Classical voice training for the novice singer has long relied on the guidance and instruction of vocalise collections, such as those written and compiled by Marchesi, Lütgen, Vaccai, and Lamperti. These vocalise collections purport to encourage healthy vocal habits and instill technical longevity in both aspiring and established singers, though their scope has long been somewhat confined to the classical idiom. For pedagogues and students specializing in other vocal genres, such as musical theatre and CCM (contemporary commercial music,) low-impact and pertinent vocal training aids are in short supply, and much of the suggested literature derives from classical methodology. While the tenants of healthy vocal production remain ubiquitous, specific stylistic needs and technical emphases differ from genre to genre and may require a specified extension of vocal acuity. As musical theatre continues to grow in popularity at both the professional and collegiate levels, the need for specialized training grows as well. Pedagogical literature geared specifically towards musical theatre (MT) singing and vocal production, while relatively uncommon, is readily accessible to the contemporary educator. Practitioners such as Norman Spivey, Mary Saunders Barton, Claudia Friedlander, Wendy Leborgne, and Marci Rosenberg continue to publish relevant research in the field of musical theatre voice pedagogy and have successfully identified many common MT vocal faults, their subsequent diagnoses, and their eventual corrections. Where classical methodology would suggest specific vocalises or training exercises to maintain corrected vocal posture following successful fault diagnosis, musical theatre finds itself without a relevant body of work towards which to transition. By analyzing the existing vocalise literature by means of a specialized set of parameters, including but not limited to melodic variation, rhythmic complexity, vowel utilization, and technical targeting, we have composed a set of vocalises meant specifically to address the training and conditioning of adult musical theatre voices. These vocalises target many pedagogical tenants in the musical theatre genre, including but not limited to thyroarytenoid-dominant production, twang resonance, lateral vowel formation, and “belt-mix.” By implementing these vocalises in the musical theatre voice studio, pedagogues can efficiently communicate proper musical theatre vocal posture and kinesthetic connection to their students, regardless of age or level of experience. The composition of these vocalises serves MT pedagogues on both a technical level as well as a sociological one. MT is a relative newcomer on the collegiate stage and the academization of musical theatre methodologies has been a slow and arduous process. The conflation of classical and MT techniques and training methods has long plagued the world of voice pedagogy and teachers often find themselves in positions of “cross-training,” that is, teaching students of both genres in one combined voice studio. As MT continues to establish itself on academic platforms worldwide, genre-specific literature and focused studies are both rare and invaluable. To ensure that modern students receive exacting and definitive training in their chosen fields, it becomes increasingly necessary for genres such as musical theatre to boast specified literature and a collection of musical theatre-specific vocalises only aids in this effort. This collection of musical theatre vocalises is the first of its kind and provides genre-specific studios with a basis upon which to grow healthy, balanced voices built for the harsh conditions of the modern theatre stage.

Keywords: voice pedagogy, targeted methodology, musical theatre, singing

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Authors: Sheillah Hlamalani Mboweni, Lufuno Makhado

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Background: The increasing number of people who tested HIV positive and who demand antiretroviral therapy (ART) prompted the National Department of Health to adopt WHO recommendations of task shifting where Professional Nurses(PNs) initiate ART rather than doctors in the hospital. This resulted in the decentralization of services to primary health care(PHC), generating a need to capacitate PNs on NIMART. After years of training, the impact of NIMART was assessed where it was established that even though there was an increased number who accessed ART, the quality of care is of serious concern. The study aims to answer the following question: What are the challenges influencing NIMART implementation in primary health care. Objectives: This study explores challenges influencing NIMART training and implementation and makes recommendations to improve patient and HIV program outcomes. Methods: A qualitative explorative program evaluation research design. The study was conducted in the rural districts of North West province. Purposive sampling was used to sample PNs trained on NIMART. FGDs were used to collect data with 6-9 participants and data was analysed using ATLAS ti. Results: Five FGDs, n=28 PNs and three program managers were interviewed. The study results revealed two themes: inadequacy in NIMART training and the health care system challenges. Conclusion: The deficiency in NIMART training and health care system challenges is a public health concern as it compromises the quality of HIV management resulting in poor patients’ outcomes and retard the goal of ending the HIV epidemic. These should be dealt with decisively by all stakeholders. Recommendations: The national department of health should improve NIMART training and HIV management: standardization of NIMART training curriculum through the involvement of all relevant stakeholders skilled facilitators, the introduction of pre-service NIMART training in institutions of higher learning, support of PNs by district and program managers, plan on how to deal with the shortage of staff, negative attitude to ensure compliance to guidelines. There is a need to develop a conceptual framework that provides guidance and strengthens NIMART implementation in PHC facilities.

Keywords: antiretroviral therapy, nurse initiated management of retroviral therapy, primary health care, professional nurses

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Authors: Paola Causin, Andrea Aspri, Alessandro Benfenati

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Diffuse Optical Tomography (DOT) is an emergent medical imaging technique which employs NIR light to estimate the spatial distribution of optical coefficients in biological tissues for diagnostic purposes, in a noninvasive and non-ionizing manner. DOT reconstruction is a severely ill-conditioned problem due to prevalent scattering of light in the tissue. In this contribution, we present our research in adopting hybrid knowledgedriven/data-driven approaches which exploit the existence of well assessed physical models and build upon them neural networks integrating the availability of data. Namely, since in this context regularization procedures are mandatory to obtain a reasonable reconstruction [1], we explore the use of neural networks as tools to include prior information on the solution. 2. Materials and Methods The idea underlying our approach is to leverage neural networks to solve PDE-constrained inverse problems of the form 𝒒 ∗ = 𝒂𝒓𝒈 𝒎𝒊𝒏𝒒 𝐃(𝒚, 𝒚̃), (1) where D is a loss function which typically contains a discrepancy measure (or data fidelity) term plus other possible ad-hoc designed terms enforcing specific constraints. In the context of inverse problems like (1), one seeks the optimal set of physical parameters q, given the set of observations y. Moreover, 𝑦̃ is the computable approximation of y, which may be as well obtained from a neural network but also in a classic way via the resolution of a PDE with given input coefficients (forward problem, Fig.1 box ). Due to the severe ill conditioning of the reconstruction problem, we adopt a two-fold approach: i) we restrict the solutions (optical coefficients) to lie in a lower-dimensional subspace generated by auto-decoder type networks. This procedure forms priors of the solution (Fig.1 box ); ii) we use regularization procedures of type 𝒒̂ ∗ = 𝒂𝒓𝒈𝒎𝒊𝒏𝒒 𝐃(𝒚, 𝒚̃)+ 𝑹(𝒒), where 𝑹(𝒒) is a regularization functional depending on regularization parameters which can be fixed a-priori or learned via a neural network in a data-driven modality. To further improve the generalizability of the proposed framework, we also infuse physics knowledge via soft penalty constraints (Fig.1 box ) in the overall optimization procedure (Fig.1 box ). 3. Discussion and Conclusion DOT reconstruction is severely hindered by ill-conditioning. The combined use of data-driven and knowledgedriven elements is beneficial and allows to obtain improved results, especially with a restricted dataset and in presence of variable sources of noise.

Keywords: inverse problem in tomography, deep learning, diffuse optical tomography, regularization

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Authors: Kim Ji-Hyun, Jeon Hye-Seon, Kwon Oh-Yun, Park Eun-Young, Hwang Ui-Jae, Gwak Gyeong-Tae, Yoon Hyeo-Bin

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Stress urinary incontinence (SUI), a common women health problem, is an involuntary leakage of urine while sneezing, coughing, or physical exertion caused by insufficient strength of the pelvic floor and sphincter muscles. SUI also leads to decrease in quality of life and limits sexual activities. SUI is related to the increased bladder neck angle, bladder neck movement, funneling index, urethral width, and decreased urethral length. Various pelvic floor muscle electrical stimulation (ES) interventions have been applied to improve the symptoms of the people with SUI. ES activates afferent fibers of pudendal nerve and smoothly induces contractions of the pelvic floor muscles such as striated periurethral muscles and striated pelvic floor muscles. ES via intravaginal electrodes are the most frequently used types of the pelvic floor muscle ES for the female SUI. However, inserted electrode is uncomfortable and it increases the risks of infection. The purpose of this preliminary study was to determine if the 8-week transcutaneous pelvic floor ES would be effective to improve the symptoms and satisfaction of the females with SUI. Easy-K, specially designed ES equipment for the people with SUI, was used in this study. The oval shape stimulator can be placed on a toilet seat, and the surface has invaded electrode fit to contact with the entire vulva area while users are sitting on the stimulator. Five women with SUI were included in this experiment. Prior to the participation, subjects were instructed about procedures and precautions in using the ES. They have used the stimulator once a day for 20 minutes for each session at home. Outcome data was collected 3 times at the baseline, 4 weeks and 8 weeks after the intervention. Intravaginal sonography was used to measure the bladder neck angle, bladder neck movement, funneling index, thickness of an anterior rhabdosphincter and a posterior rhabdosphincter, urethral length, and urethral width. Leavator ani muscle (LAM) contraction strength was assessed by manual palpation according to the oxford scoring system. In addition, incontinence quality of life (IQOL) and female sexual function index (FSFI) questionnaires were used to obtain addition subjective information. Friedman test, a nonparametric statistical test, was used to determine the effectiveness of the ES. The Wilcoxon test was used for the post-hoc analysis and the significance level was set at .05. The bladder neck angle, funneling index and urethral width were significantly decreased after 8-weeks of intervention (p<.05). LAM contraction score, urethral length and anterior and posterior rhabdosphicter thickness were statistically increased by the intervention (p<.05). However, no significant change was found in the bladder neck movement. Although total score of the IQOL did not improve, the score of the ‘avoidance’ subscale of IQOL had significant improved (p<.05). FSFI had statistical difference in FSFI total score and ‘desire’ subscale (p<.05). In conclusion, 8-week use of a transcutaneous ES on peri-vulva area improved dynamic mechanical structures of the pelvic floor musculature as well as IQOL and conjugal relationship.

Keywords: electrical stimulation, Pelvic floor muscle, sonography, stress urinary incontinence, women health

Procedia PDF Downloads 135

Authors: Elissavet Feloni, Ioannis Kourtis, Konstantinos Kotsifakis, Evangelos Baltas

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Water inadequacy in small dry islands scattered in the Aegean Sea (Greece) is a major problem regarding Water Resources Management (WRM), especially during the summer period due to tourism. In the present work, various WRM schemes are designed and presented. The WRM schemes take into account current infrastructure and include Rainwater Harvesting tanks and Reverse Osmosis Desalination Units. The energy requirements are covered mainly by wind turbines and/or a seawater pumped storage system. Sizing is based on the available data for population and tourism per island, after taking into account a slight increase in the population (up to 1.5% per year), and it guarantees at least 80% reliability for the energy supply and 99.9% for potable water. Evaluation of scenarios is carried out from a financial perspective, after calculating the Life Cycle Cost (LCC) of each investment for a lifespan of 30 years. The wind-powered desalination plant was found to be the most cost-effective practice, from an economic point of view. Finally, in order to estimate the Climate Change (CC) impact, six different CC scenarios were investigated. The corresponding rate of on-grid versus off-grid energy required for ensuring the targeted reliability for the zero and each climatic scenario was investigated per island. The results revealed that under CC the grid-on energy required would increase and as a result, the reduction in wind turbines and seawater pumped storage systems’ reliability will be in the range of 4 to 44%. However, the range of this percentage change does not exceed 22% per island for all examined CC scenarios. Overall, CC is proposed to be incorporated into the design process for WRM-related projects. Acknowledgements: This research is co-financed by Greece and the European Union (European Social Fund - ESF) through the Operational Program «Human Resources Development, Education and Lifelong Learning 2014-2020» in the context of the project “Development of a combined rain harvesting and renewable energy-based system for covering domestic and agricultural water requirements in small dry Greek Islands” (MIS 5004775).

Keywords: small dry islands, water resources management, climate change, desalination, RES, seawater pumped storage system, rainwater harvesting

Procedia PDF Downloads 100

Authors: Paulo Roberto Vasconcellos-Silva

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The "Janeiro Roxo" (Purple January) campaign in Brazil aims to promote awareness of leprosy and its early symptoms. The COVID-19 pandemic has adversely affected institutional campaigns, mostly considering leprosy a neglected disease by the media. Google Trends (GT) is a tool that tracks user searches on Google, providing insights into the popularity of specific search terms. Our prior research has categorized online searches into two types: "Reactive searches," driven by transient campaign-related stimuli, and "Proactive searches," driven by personal interest in early symptoms and self-diagnosis. Using GT we studied: (i) the impact of "Janeiro Roxo" on public interest in leprosy (assessed through reactive searches) and its early symptoms (evaluated through proactive searches) over the past five years; (ii) changes in public interest during and after the COVID-19 pandemic; (iii) patterns in the dynamics of reactive and proactive searches Methods: We used GT's "Relative Search Volume" (RSV) to gauge public interest on a scale from 0 to 100. "HANSENÍASE" (HAN) was a proxy for reactive searches, and "HANSENÍASE SINTOMAS" (leprosy symptoms) (H.SIN) for proactive searches (interest in leprosy or in self-diagnosis). We analyzed 261 weeks of data from 2018 to 2023, using polynomial trend lines to model trends over this period. Analysis of Variance (ANOVA) was used to compare weekly RSV, monthly (MM) and annual means (AM). Results: Over a span of 261 weeks, there was consistently higher Relative Search Volume (RSV) for HAN compared to H.SIN. Both search terms exhibited their highest (MM) in January months during all periods. COVID-19 pandemic: a decline was observed during the pandemic years (2020-2021). There was a 24% decrease in RSV for HAN and a 32.5% decrease for H.SIN. Both HAN and H.SIN regained their pre-pandemic search levels in January 2022-2023. Breakpoints indicated abrupt changes - in the 26th week (February 2019), 55th and 213th weeks (September 2019 and 2022) related to September regional campaigns (interrupted in 2020-2021). Trend lines for HAN exhibited an upward curve between 33rd-45th week (April to June 2019), a pandemic-related downward trend between 120th-136th week (December 2020 to March 2021), and an upward trend between 220th-240th week (November 2022 to March 2023). Conclusion: The "Janeiro Roxo" campaign, along with other media-driven activities, exerts a notable influence on both reactive and proactive searches related to leprosy topics. Reactive searches, driven by campaign stimuli, significantly outnumber proactive searches. Despite the interruption of the campaign due to the pandemic, there was a subsequent resurgence in both types of searches. The recovery observed in reactive and proactive searches post-campaign interruption underscores the effectiveness of such initiatives, particularly at the national level. This suggests that regional campaigns aimed at leprosy awareness can be considered highly successful in stimulating proactive public engagement. The evaluation of internet-based campaign programs proves valuable not only for assessing their impact but also for identifying the needs of vulnerable regions. These programs can play a crucial role in integrating regions and highlighting their needs for assistance services in the context of leprosy awareness.

Keywords: health communication, leprosy, health campaigns, information seeking behavior, Google Trends, reactive searches, proactive searches, leprosy early identification

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Authors: Evan Lowhorn, Rocio Alba-Flores

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Traditional classification Convolutional Neural Networks (CNN) attempt to classify an image in its entirety. This becomes problematic when trying to perform classification with a drone’s camera in real-time due to unpredictable backgrounds. Object detectors with bounding boxes can be used to isolate individuals and other items, but the original backgrounds remain within these boxes. These basic detectors have been regularly used to determine what type of object an item is, such as “person” or “dog.” Recent advancement in computer vision, particularly with human imaging, is keypoint detection. Human keypoint detection goes beyond bounding boxes to fully isolate humans and plot points, or Regions of Interest (ROI), on their bodies within an image. ROIs can include shoulders, elbows, knees, heads, etc. These points can then be related to each other and used in deep learning methods such as pose estimation. For drone control based on human motions, poses, or signals using the onboard camera, it is important to have a simple method for pilot identification among multiple individuals while also giving the pilot fine control options for the drone. To achieve this, the OpenPose keypoint detection network was used with body and hand keypoint detection enabled. OpenPose supports the ability to combine multiple keypoint detection methods in real-time with a single network. Body keypoint detection allows simple poses to act as the pilot identifier. The hand keypoint detection with ROIs for each finger can then offer a greater variety of signal options for the pilot once identified. For this work, the individual must raise their non-control arm to be identified as the operator and send commands with the hand on their other arm. The drone ignores all other individuals in the onboard camera feed until the current operator lowers their non-control arm. When another individual wish to operate the drone, they simply raise their arm once the current operator relinquishes control, and then they can begin controlling the drone with their other hand. This is all performed mid-flight with no landing or script editing required. When using a desktop with a discrete NVIDIA GPU, the drone’s 2.4 GHz Wi-Fi connection combined with OpenPose restrictions to only body and hand allows this control method to perform as intended while maintaining the responsiveness required for practical use.

Keywords: computer vision, drone control, keypoint detection, openpose

Procedia PDF Downloads 167

Authors: Misuk Kim, Seokho Kang, Jehyuk Lee, Hyunchang Cho, Sungzoon Cho

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In semiconductor manufacturing, virtual metrology (VM) refers to methods to predict properties of a wafer based on machine parameters and sensor data of the production equipment, without performing the (costly) physical measurement of the wafer properties (Wikipedia). Additional benefits include avoidance of human bias and identification of important factors affecting the quality of the process which allow improving the process quality in the future. It is however rare to find VM applied to other areas of manufacturing. In this work, we propose to use VM to copper clad laminate (CCL) manufacturing. CCL is a core element of a printed circuit board (PCB) which is used in smartphones, tablets, digital cameras, and laptop computers. The manufacturing of CCL consists of three processes: Treating, lay-up, and pressing. Treating, the most important process among the three, puts resin on glass cloth, heat up in a drying oven, then produces prepreg for lay-up process. In this process, three important quality factors are inspected: Treated weight (T/W), Minimum Viscosity (M/V), and Gel Time (G/T). They are manually inspected, incurring heavy cost in terms of time and money, which makes it a good candidate for VM application. We developed prediction models of the three quality factors T/W, M/V, and G/T, respectively, with process variables, raw material, and environment variables. The actual process data was obtained from a CCL manufacturer. A variety of variable selection methods and learning algorithms were employed to find the best prediction model. We obtained prediction models of M/V and G/T with a high enough accuracy. They also provided us with information on “important” predictor variables, some of which the process engineers had been already aware and the rest of which they had not. They were quite excited to find new insights that the model revealed and set out to do further analysis on them to gain process control implications. T/W did not turn out to be possible to predict with a reasonable accuracy with given factors. The very fact indicates that the factors currently monitored may not affect T/W, thus an effort has to be made to find other factors which are not currently monitored in order to understand the process better and improve the quality of it. In conclusion, VM application to CCL’s treating process was quite successful. The newly built quality prediction model allowed one to reduce the cost associated with actual metrology as well as reveal some insights on the factors affecting the important quality factors and on the level of our less than perfect understanding of the treating process.

Keywords: copper clad laminate, predictive modeling, quality control, virtual metrology

Procedia PDF Downloads 340

Authors: Zan Chen, D. Kwok

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The SkillsFuture Singapore’s mission to develop a responsive and forward-looking Training and Adult Education (TAE) and workforce development system is undergirded by how successful TAE providers are in their business performance and strategies that strengthen their operational efficiency and processes. Therefore, understanding the factors that drive the business performance of TAE providers is critical to the success of SkillsFuture Singapore’s initiatives. This study aims to investigate how business strategy, work autonomy, work intensity and professional development support impact the business performance of private TAE providers. Specifically, the three research questions are: (1) Are there significant relationships between the above-mentioned four factors and TAE providers’ business performance?; (2) Are there significant differences on the four factors between low and high TAE providers’ business performance groups?; and (3) To what extent and in what manner do the four factors predict TAE providers’ business performance? This was part of the first national study on organizations and professionals working in the Training and Adult Education (TAE) sector. Data from 265 private TAE providers where respondents were Chief Executive Officers representatives from the Senior Management were analyzed. The results showed that business strategy (the extent that the organization leads the way in terms of developing new products and services; uses up-to-date learning technologies; customizes its products and services to the client’s needs), work autonomy (the extent that the staff personally have an influence on how hard they work; deciding what tasks they are to do; deciding how they are to do the tasks, and deciding the quality standards to which they work) and professional development support (both monetary and non-monetary support and incentives) had positive and significant relationships with business performance. However, no significant relationship is found between work intensity and business performance. A business strategy, work autonomy and professional development support were significantly higher in the high business performance group compared to the low-performance group among the TAE providers. Results of hierarchical regression analyses controlling for the size of the TAE providers showed significant impacts of business strategy, work autonomy and professional development support on TAE providers’ business performance. Overall, the model accounted for 27% of the variance in TAE providers’ business performance. This study provides policymakers with insights into improving existing policies, designing new initiatives and implementing targeting interventions to support TAE providers. The findings also have implications on how the TAE providers could better formulate their organizational strategies and business models. Finally, limitations of study, along with directions for future research will be discussed in the paper.

Keywords: adult education, business performance, business strategy, training, work autonomy

Procedia PDF Downloads 182

Authors: Johanna Lindstrom, Jacob Mickelsson

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Changes in the current media environment are transforming peoples’ everyday media consumption patterns all over the world. Digital media have become a natural, almost unavoidable, part of everyday lives of humans. While this has led to many positive consequences, there is also a growing concern for harmful effects. This paper contributes to knowledge about “the dark side” of media use by considering the topic of media addiction and subsequent coping strategies among young adults. The paper draws on a longitudinal media diary study conducted among young university students between the years 2013 and 2021. A total of 1029 diaries have been collected (approximately 100 each year), aiming at capturing the students’ everyday media behavior. In this paper, reflective narratives in the diaries have been analyzed, aiming at answering the following questions: Which of their own media behaviors do the students perceive as particularly destructive, addictive or problematic? How do they cope with such behaviors? Results from the study indicate a noticeable increase in reflections on addictive media behavior over the years. For example, compared to earlier years, the amount of such reflections significantly started to increase in the diaries in 2016 and 2017, and this trend has continued ever since. Furthermore, the nature of these reflections has changed, displaying a growing concern for one’s own excessive media use and general wellbeing. Media addiction seems particularly difficult to cope with as digital media is literally everywhere and media use in general is described as consistent and habitual, in terms of regularly repeated routines that are fragmented but performed continuously and often unintentionally throughout the day. Reflections on “the dark side” of everyday media consumption become particularly prominent in times of the Covid -19 pandemic. However, this trend was noticeable well before the pandemic started. The study also identifies a countertrend regarding reflections on how to deal and cope with problematic media behavioral patterns. This countertrend portrays a general development of increased awareness of factors that may trigger compulsive behavior and how to avoid or handle such trigger points. The countertrend is particularly evident in recent years, despite the ongoing pandemic and subsequent increases in time spent using media. Addictive media behavior may lead to severe consequences for students’ learning processes and general well-being. Increased awareness of this growing trend and coping strategies are needed on an individual as well as a broader educational level.

Keywords: coping strategies, media addiction, media behavior, well-being

Procedia PDF Downloads 183

Authors: Lindy Valdez, Daryl Parker

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Introduction: There has been much research on academic achievement in elementary schools. Most of the research has been on school leadership. While research has focused on the role of leadership on school improvement, little research has examined what variables the top elementary schools have in common. To undertake school improvement, it is important to understand what factors the best schools share. The purpose of this study was to examine data of the “Best Elementary Schools in California,” based on academic achievement as rated by three prominent websites and determine if these schools had any common factors which were different than the statewide averages. The variables examined included access to subject matter specialists (physical education, art, and music), librarians, after school programs, class size, socioeconomic status, and diversity. The participants consisted of the top public elementary schools in California based on the websites i)https://www.niche.com/k12/search/best-schools/, ii)https://www.finder.com/best-schools-california,and iii)https://www.schooldigger.com/go/CA/schoolrank.aspx. The data for subject matter specialists (physical education, art, and music), librarians, after school programs, class size, socioeconomic status, and diversity were collected from these top schools and compared to California statewide averages. Results indicate that top public elementary schools in California have a high number of subject matter specialists that teach physical education, art, and music. These positions are on the decline in the average public elementary school in California, but the top schools have abundant access to these specialists. The physical education specialist has the highest statistically significant difference between the nationwide average and the top schools—librarians, and after school programs are also most commonly high in top public elementary schools in California. The high presence of these programs may be aiding academic achievement in less visible ways. Class size is small, socio-economic status is high, and diversity is low among top public elementary schools in California when compared to the statewide average public elementary schools in California. The single largest area of discrepancy was between physical education specialists in a top school and their state and nationwide averages. The socioeconomic status of schools and parents may be an underlining factor affecting several other variables. This affluence could explain how these schools were able to have access to subject matter specialists, after-school activities, and, therefore, more opportunities for physical activity and greater learning opportunities affecting academic achievement.

Keywords: academic achievement, elementary education, factors, schools

Procedia PDF Downloads 113

Authors: Loreta Kaklauskiene, Arturas Kaklauskas

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The Integrated Human Resources and Work Environment Management (HOWE) System optimises employee productivity, improves the work environment, and, at the same time, meets the employer’s strategic goals. The HOWE system has been designed to ensure an organisation can successfully compete in the global market, thanks to the high performance of its employees. The HOWE system focuses on raising workforce productivity and improving work conditions to boost employee performance and motivation. The methods used in our research are linear correlation, INVAR multiple criteria analysis, digital twin, and affective computing. The HOWE system is based on two patents issued in Lithuania (LT 6866, LT 6841) and one European Patent application (No: EP 4 020 134 A1). Our research analyses ways to make human resource management more efficient and boost labour productivity by improving and adapting a personalised work environment. The efficiency of human capital and labour productivity can be increased by applying personalised workplace improvement systems that can optimise lighting colours and intensity, scents, data, information, knowledge, activities, media, games, videos, music, air pollution, humidity, temperature, vibrations, and other workplace aspects. HOWE generates and maintains a personalised workspace for an employee, taking into account the person’s affective, physiological and emotional (APSE) states. The purpose of this project was to create a HOWE for the customisation of quality control in smart workspaces taking into account the user’s APSE states in an integrated manner as a single unit. This customised management of quality control covers the levels of lighting and colour intensities, scents, media, information, activities, learning materials, games, music, videos, temperature, energy efficiency, the carbon footprint of a workspace, humidity, air pollution, vibrations and other aspects of smart spaces. The system is based on Digital Twins technology, seen as a logical extension of BIM.

Keywords: human resource management, health economics, work environment, organizational behaviour and employee productivity, prosperity in work, smart system

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Authors: Rema Vazhappilly, Tapas Das

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Oleic acid is a cis unsaturated fatty acid and is known to be a partially essential fatty acid due to its limited endogenous synthesis during pregnancy and lactation. Previous studies have demonstrated the role of oleic acid in neuronal differentiation and brain phospholipid synthesis. These evidences indicate a major role for oleic acid in learning and memory. Interestingly, oleic acid has been shown to enhance hippocampal long term potentiation (LTP), the physiological correlate of long term synaptic plasticity. However the effect of oleic acid on short term synaptic plasticity has not been investigated. Short term potentiation (STP) is the physiological correlate of short term synaptic plasticity which is the key underlying molecular mechanism of short term memory and neuronal information processing. STP in the hippocampal CA1 region has been known to require the activation of N-methyl-D-aspartate receptors (NMDARs). The NMDAR dependent hippocampal STP as a potential mechanism for short term memory has been a subject of intense interest for the past few years. Therefore in the present study the effect of oleic acid on NMDAR dependent hippocampal STP was determined in mouse hippocampal slices (in vitro) using Multi-electrode array system. STP was induced by weak tetanic Stimulation (one train of 100 Hz stimulations for 0.1s) of the Schaffer collaterals of CA1 region of the hippocampus in slices treated with different concentrations of oleic acid in presence or absence of NMDAR antagonist D-AP5 (30 µM) . Oleic acid at 20 (mean increase in fEPSP amplitude = ~135 % Vs. Control = 100%; P<0.001) and 30 µM (mean increase in fEPSP amplitude = ~ 280% Vs. Control = 100%); P<0.001) significantly enhanced the STP following weak tetanic stimulation. Lower oleic acid concentrations at 10 µM did not modify the hippocampal STP induced by weak tetanic stimulation. The hippocampal STP induced by weak tetanic stimulation was completely blocked by the NMDA receptor antagonist D-AP5 (30µM) in both oleic acid and control treated hippocampal slices. This lead to the conclusion that the hippocampal STP elicited by weak tetanic stimulation and enhanced by oleic acid was NMDAR dependent. Together these findings suggest that oleic acid may enhance the short term memory and neuronal information processing through the modulation of NMDAR dependent hippocampal short-term synaptic plasticity. In conclusion this study suggests the possible role of oleic acid to prevent the short term memory loss and impaired neuronal function throughout development.

Keywords: oleic acid, short-term potentiation, memory, field excitatory post synaptic potentials, NMDA receptor

Procedia PDF Downloads 315

Authors: Jun Wang, Chenglei Diao, Emanuele Pagone, Jialuo Ding, Stewart Williams

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As a crucial component in aircraft, landing gear systems are responsible for supporting the plane during parking, taxiing, takeoff, and landing. Given the need for high load-bearing capacity over extended periods, 300M ultra-high strength steel (UHSS) is often the material of choice for crafting these systems due to its exceptional strength, toughness, and fatigue resistance. In the quest for cost-effective and sustainable manufacturing solutions, Wire Arc Additive Manufacturing (WAAM) emerges as a promising alternative for fabricating 300M UHSS landing gears. This is due to its advantages in near-net-shape forming of large components, cost-efficiency, and reduced lead times. Cranfield University has conducted an extensive preliminary study on WAAM 300M UHSS, covering feature deposition, interface analysis, and post-heat treatment. Both Gas Metal Arc (GMA) and Plasma Transferred Arc (PTA)-based WAAM methods were explored, revealing their feasibility for defect-free manufacturing. However, as-deposited 300M features showed lower strength but higher ductility compared to their forged counterparts. Subsequent post-heat treatments were effective in normalising the microstructure and mechanical properties, meeting qualification standards. A 300M UHSS landing gear demonstrator was successfully created using PTA-based WAAM, showcasing the method's precision and cost-effectiveness. The demonstrator, measuring Ф200mm x 700mm, was completed in 16 hours, using 7 kg of material at a deposition rate of 1.3kg/hr. This resulted in a significant reduction in the Buy-to-Fly (BTF) ratio compared to traditional manufacturing methods, further validating WAAM's potential for this application. A "cradle-to-gate" environmental impact assessment, which considers the cumulative effects from raw material extraction to customer shipment, has revealed promising outcomes. Utilising Wire Arc Additive Manufacturing (WAAM) for landing gear components significantly reduces the need for raw material extraction and refinement compared to traditional subtractive methods. This, in turn, lessens the burden on subsequent manufacturing processes, including heat treatment, machining, and transportation. Our estimates indicate that the carbon footprint of the component could be halved when switching from traditional machining to WAAM. Similar reductions are observed in embodied energy consumption and other environmental impact indicators, such as emissions to air, water, and land. Additionally, WAAM offers the unique advantage of part repair by redepositing only the necessary material, a capability not available through conventional methods. Our research shows that WAAM-based repairs can drastically reduce environmental impact, even when accounting for additional transportation for repairs. Consequently, WAAM emerges as a pivotal technology for reducing environmental impact in manufacturing, aiding the industry in its crucial and ambitious journey towards Net Zero. This study paves the way for transformative benefits across the aerospace industry, as we integrate manufacturing into a hybrid solution that offers substantial savings and access to more sustainable technologies for critical component production.

Keywords: WAAM, aircraft landing gear, microstructure, mechanical performance, life cycle assessment

Procedia PDF Downloads 142

Authors: Adriana Muñoz-Talavera, Ana Rosa Rincón-Sánchez, Abraham Escobedo-Moratilla, María Cristina Islas-Carbajal, Miguel Ángel Gómez-Lim

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The highest rates of diabetes incidence and prevalence worldwide will increase the number of diabetic patients requiring insulin or insulin analogues. Then, current production systems would not be sufficient to meet the future market demands. Therefore, developing efficient expression systems for insulin and insulin analogues are needed. In addition, insulin analogues with better pharmacokinetics and pharmacodynamics properties and without mitogenic potential will be required. SCI-57 (single chain insulin-57) is an insulin analogue having 10 times greater affinity to the insulin receptor, higher resistance to thermal degradation than insulin, native mitogenicity and biological effect. Plants as expression platforms have been used to produce recombinant proteins because of their advantages such as cost-effectiveness, posttranslational modifications, absence of human pathogens and high quality. Immunoglobulin production with a yield of 50% has been achieved by transient expression in Nicotiana benthamiana (Nb). The aim of this study is to produce SCI-57 by transient expression in Nb. Methodology: DNA sequence encoding SCI-57 was cloned in pICH31070. This construction was introduced into Agrobacterium tumefaciens by electroporation. The resulting strain was used to infiltrate leaves of Nb. In order to isolate SCI-57, leaves from transformed plants were incubated 3 hours with the extraction buffer therefore filtrated to remove solid material. The resultant protein solution was subjected to anion exchange chromatography on an FPLC system and ultrafiltration to purify SCI-57. Detection of SCI-57 was made by electrophoresis pattern (SDS-PAGE). Protein band was digested with trypsin and the peptides were analyzed by Liquid chromatography tandem-mass spectrometry (LC-MS/MS). A purified protein sample (20µM) was analyzed by ESI-Q-TOF-MS to obtain the ionization pattern and the exact molecular weight determination. Chromatography pattern and impurities detection were performed using RP-HPLC using recombinant insulin as standard. The identity of the SCI-57 was confirmed by anti-insulin ELISA. The total soluble protein concentration was quantified by Bradford assay. Results: The expression cassette was verified by restriction mapping (5393 bp fragment). The SDS-PAGE of crude leaf extract (CLE) of transformed plants, revealed a protein of about 6.4 kDa, non-present in CLE of untransformed plants. The LC-MS/MS results displayed one peptide with a high score that matches SCI-57 amino acid sequence in the sample, confirming the identity of SCI-57. From the purified SCI-57 sample (PSCI-57) the most intense charge state was 1069 m/z (+6) on the displayed ionization pattern corresponding to the molecular weight of SCI-57 (6412.6554 Da). The RP-HPLC of the PSCI-57 shows the presence of a peak with similar retention time (rt) and UV spectroscopic profile to the insulin standard (SCI-57 rt=12.96 and insulin rt=12.70 min). The collected SCI-57 peak had ELISA signal. The total protein amount in CLE from transformed plants was higher compared to untransformed plants. Conclusions: Our results suggest the feasibility to produce insulin analogue SCI-57 by transient expression in Nicotiana benthamiana. Further work is being undertaken to evaluate the biological activity by glucose uptake by insulin-sensitive and insulin-resistant murine and human cultured adipocytes.

Keywords: insulin analogue, mass spectrometry, Nicotiana benthamiana, transient expression

Procedia PDF Downloads 331

Authors: Martín Pratto Burgos

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The Engineering School of the University of the Republic in Uruguay offers an Introductory Mathematical Course from the second semester of 2019. This course has been designed to assist students in preparing themselves for math courses that are essential for Engineering Degrees, namely Math1, Math2, and Math3 in this research. The research proposes to build a model that can accurately predict the student's activity and academic progress based on their performance in the three essential Mathematical courses. Additionally, there is a need for a model that can forecast the incidence of the Introductory Mathematical Course in the three essential courses approval during the first academic year. The techniques used are Principal Component Analysis and predictive modelling using the Generalised Linear Model. The dataset includes information from 5135 engineering students and 12 different characteristics based on activity and course performance. Two models are created for a type of data that follows a binomial distribution using the R programming language. Model 1 is based on a variable's p-value being less than 0.05, and Model 2 uses the stepAIC function to remove variables and get the lowest AIC score. After using Principal Component Analysis, the main components represented in the y-axis are the approval of the Introductory Mathematical Course, and the x-axis is the approval of Math1 and Math2 courses as well as student activity three years after taking the Introductory Mathematical Course. Model 2, which considered student’s activity, performed the best with an AUC of 0.81 and an accuracy of 84%. According to Model 2, the student's engagement in school activities will continue for three years after the approval of the Introductory Mathematical Course. This is because they have successfully completed the Math1 and Math2 courses. Passing the Math3 course does not have any effect on the student’s activity. Concerning academic progress, the best fit is Model 1. It has an AUC of 0.56 and an accuracy rate of 91%. The model says that if the student passes the three first-year courses, they will progress according to the timeline set by the curriculum. Both models show that the Introductory Mathematical Course does not directly affect the student’s activity and academic progress. The best model to explain the impact of the Introductory Mathematical Course on the three first-year courses was Model 1. It has an AUC of 0.76 and 98% accuracy. The model shows that if students pass the Introductory Mathematical Course, it will help them to pass Math1 and Math2 courses without affecting their performance on the Math3 course. Matching the three predictive models, if students pass Math1 and Math2 courses, they will stay active for three years after taking the Introductory Mathematical Course, and also, they will continue following the recommended engineering curriculum. Additionally, the Introductory Mathematical Course helps students to pass Math1 and Math2 when they start Engineering School. Models obtained in the research don't consider the time students took to pass the three Math courses, but they can successfully assess courses in the university curriculum.

Keywords: machine-learning, engineering, university, education, computational models

Procedia PDF Downloads 64

Authors: Alan Collins

Abstract:

This study explains how The People’s Tribunal empowered survivors of child abuse. It examines how People’s tribunals can be effective mean of empowerment; the challenges of empowerment – expectation v. reality; the findings and how they reflect other inquiry findings; and the importance of listening and learning from survivors. UKCSAPT “The People’s Tribunal” was established by survivors of child sex abuse and members of civil society to investigate historic cases of institutional sex abuse. The independent inquiry, led by a panel of four judges, listened to evidence spanning four decades from survivors and experts. A common theme throughout these accounts showed that a series of institutional failures prevented abuse from being reported; and that there are clear links between children being rendered vulnerable by these failures and predatory abuse on an organised scale. It made a series of recommendations including the establishment of a permanent and open forum for victims to share experiences and give evidence, better links between mental health services and police investigations, and training for police and judiciary professionals on the effects of undisclosed sexual abuse. The main findings of the UKCSAPT report were:-There are clear links between children rendered vulnerable by institutional failures and predatory abuse on an organised scale, even if these links often remain obscure. -UK governmental institutions have failed to provide survivors with meaningful opportunities for either healing or justice. -The vital mental health needs of survivors are not being met and this undermines both their psychological recovery and access to justice. -Police and other authorities often lack the training to understand the complex reasons for the inability of survivors to immediately disclose a history of abuse. -Without far-reaching changes in institutional culture and practices, the sexual abuse of children will continue to be a significant scourge in the UK. The report also outlined a series of recommendations for improving reporting and mental health provision, and access to justice for victims were made, including: -A permanent, government-funded popular tribunal should be established to enable survivors to come forward and tell their stories. -Survivors giving evidence should be assigned an advocate to assist their access to justice. -Mental health services should be linked to police investigations to help victims disclose abuse. -Victims who fear reprisals should be provided with a channel though which to give evidence anonymously.

Keywords: empowerment, survivors, sexual, abuse

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Authors: Christine Y. Yeh, Brian D. Piening, Sarah M. Totten, Kimberly Kukurba, Wenyu Zhou, Kevin P. F. Contrepois, Gucci J. Gu, Sharon Pitteri, Michael Snyder

Abstract:

Three million deaths worldwide are attributed to obesity. However, the biomolecular mechanisms that describe the link between adiposity and subsequent disease states are poorly understood. Insulin resistance characterizes approximately half of obese individuals and is a major cause of obesity-mediated diseases such as Type II diabetes, hypertension and other cardiovascular diseases. This study makes use of longitudinal quantitative and high-throughput multi-omics (genomics, epigenomics, transcriptomics, glycoproteomics etc.) methodologies on blood samples to develop multigenic and multi-analyte signatures associated with weight gain and insulin resistance. Participants of this study underwent a 30-day period of weight gain via excessive caloric intake followed by a 60-day period of restricted dieting and return to baseline weight. Blood samples were taken at three different time points per patient: baseline, peak-weight and post weight loss. Patients were characterized as either insulin resistant (IR) or insulin sensitive (IS) before having their samples processed via longitudinal multi-omic technologies. This comparative study revealed a wealth of biomolecular changes associated with weight gain after using methods in machine learning, clustering, network analysis etc. Pathways of interest included those involved in lipid remodeling, acute inflammatory response and glucose metabolism. Some of these biomolecules returned to baseline levels as the patient returned to normal weight whilst some remained elevated. IR patients exhibited key differences in inflammatory response regulation in comparison to IS patients at all time points. These signatures suggest differential metabolism and inflammatory pathways between IR and IS patients. Biomolecular differences associated with weight gain and insulin resistance were identified on various levels: in gene expression, epigenetic change, transcriptional regulation and glycosylation. This study was not only able to contribute to new biology that could be of use in preventing or predicting obesity-mediated diseases, but also matured novel biomedical informatics technologies to produce and process data on many comprehensive omics levels.

Keywords: insulin resistance, multi-omics, next generation sequencing, proteogenomics, type ii diabetes

Procedia PDF Downloads 414