Search results for: chronic training

Authors: Lateefat Amao, Misagh Faezipour

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Implementing electronic health records (EHR) in healthcare is a pivotal transition aimed at digitizing and optimizing patient health information management. The expectations associated with this transition are high, even towards other health information systems (HIS) and health technology. This multifaceted process involves careful planning and execution to improve the quality and efficiency of patient care, especially as healthcare technology is a sensitive niche. Key considerations include a thorough needs assessment, judicious vendor selection, robust infrastructure development, and training and adaptation of healthcare professionals. Comprehensive training programs, data migration from legacy systems and models, interoperability, as well as security and regulatory compliance are imperative for healthcare staff to navigate EHR systems adeptly. The purpose of this work is to offer a comprehensive review of the literature on EHR implementation. It explores the impact of this health technology on health practices, highlights challenges and barriers to its successful utility, and offers practical strategies that can impact its success in healthcare. This paper provides a thorough review of studies on the adoption of EHRs, emphasizing the wide range of experiences and results connected to EHR use in the medical field, especially across different types of healthcare organizations.

Keywords: healthcare, electronic health records, EHR implementation, patient care, interoperability

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Authors: Bianca W. O. Silva, Adriana C. M. Andrade, Gustavo C. M. Lucena, Virna M. S. Lima

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Introduction: Basic life support (BLS) involves the immediate recognition of cardiopulmonary arrest. Each year, 359.400 and 275.000 individuals with cardiac arrest are attended in emergency departments in USA and Europe. Brazilian data shows that 200.000 cardiac arrests occur every year, and half of them out of the hospital. Medical schools around the world teach BLS in the first years of the course, but studies show that there is a decline of the knowledge as the years go by, affecting the chain of survival. The objective was to analyze the knowledge of medical students about BLS and the retention of this learning throughout the course. Methods: This study included 150 students who were at the second and third year of a medical school in Salvador, Bahia, Brazil. The instrument of data collection was a structured questionnaire composed of 20 questions based on the 2015 American Heart Association guideline. The Pearson Chi-square test was used in order to study the association between previous training, sex and semester with the degree of knowledge of the students. The Kruskal-Wallis test was used to evaluate the different yields obtained between the various semesters. The number of correct answers was described by average and quartiles. Results: Regarding the degree of knowledge, 19.6% of the female students reached the optimal classification, a better outcome than the achieved by the male participants. Of those with previous training, 33.33% were classified as good and optimal, none of the students reached the optimal classification and only 2.2% of them were classified as bad (those who did not have 52.6% of correct answers). The analysis of the degree of knowledge related to each semester revealed that the 5th semester had the highest outcome: 30.5%. However, the acquaintance presented by the semesters was generally unsatisfactory, since 50% of the students, or more, demonstrated knowledge levels classified as bad or regular. When confronting the different semesters and the achieved scores, the value of p was 0.831. Conclusion: It is important to focus on the training of medical professionals that are capable of facing emergency situations, improving the systematization of care, and thereby increasing the victims' possibility of survival.

Keywords: basic life support, cardiopulmonary ressucitacion, education, medical students

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Authors: Liaquat Ali, Khurshid Natasha

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Low resource countries are not usually equipped with the organizational tools to implement health care for chronic diseases, and thus, providing effective diabetes care in such countries is a challenging task. Diabetic Association of Bangladesh (BADAS in Bengali acronym) has created a stimulating example to meet this challenge. Starting its journey in 1956 with 39 patients in a small tin shed clinic BADAS, and its affiliated associations now operate 90 hospitals and health centres all over the country. Together, these facilities provide integrated health care to about 1.5 million registered diabetic patients which constitute about 20% of the estimated diabetic population in the country. BADAS has also become a pioneer in health manpower generation in Bangladesh. Along with its affiliates, it now runs 3 Medical Colleges (to generate graduate physicians), 2 Nursing Institutes, and 2 Postgraduate Institutes which conduct 25 postgraduate courses (under the University of Dhaka) in various basic, clinical and public health disciplines. BADAS gives great emphasis on research, which encompasses basic, clinical as well as public health areas. BADAS is an ideal example of public-private partnership in health as most of its infrastructure has been created through government support but it is almost self-reliant in managing its revenue budget which approached approximately 40 million US dollar during 2010. BADAS raises resources by providing high-quality services to the people, both diabetic and non-diabetic. At the same time, BADAS has developed a cross financing model, to support diabetic patients in general and poor diabetic patients (identified through a social welfare network) in particular, through redistribution of the resources. Along with financial sustainability BADAS ensure organizational sustainability through a process of decentralization, community ownership, and democratic management. Presently a large scale pilot project (named as a Health Care Development Project or HCDP) is under implementation under BADAS umbrella with an objective to transform the diabetes care model to a health care model in general. It is expected to create further evidence on providing sustainable (with social safety net) health care delivery for diabetes, and other chronic illnesses as an integral part of general health care delivery in a resource constrained setting.

Keywords: Bangladesh, self sustain, health care, constrain

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Authors: Hervice Roméo Fogno Fotsoa, Germaine Djuidje Kenmoe, Claude Vidal Aloyem Kazé

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One of the main applications of machine learning is the prediction of time series. But a more accurate prediction requires a more optimal model of machine learning. Several optimization techniques have been developed, but without considering the input variables disposition of the system. Thus, this work aims to present a new machine learning architecture optimization technique based on their optimal input variables disposition. The validations are done on the prediction of wind time series, using data collected in Cameroon. The number of possible dispositions with four input variables is determined, i.e., twenty-four. Each of the dispositions is used to perform the prediction, with the main criteria being the training and prediction performances. The results obtained from a static architecture and a dynamic architecture of neural networks have shown that these performances are a function of the input variable's disposition, and this is in a different way from the architectures. This analysis revealed that it is necessary to take into account the input variable's disposition for the development of a more optimal neural network model. Thus, a new neural network training algorithm is proposed by introducing the search for the optimal input variables disposition in the traditional back-propagation algorithm. The results of the application of this new optimization approach on the two single neural network architectures are compared with the previously obtained results step by step. Moreover, this proposed approach is validated in a collaborative optimization method with a single objective optimization technique, i.e., genetic algorithm back-propagation neural networks. From these comparisons, it is concluded that each proposed model outperforms its traditional model in terms of training and prediction performance of time series. Thus the proposed optimization approach can be useful in improving the accuracy of time series forecasts. This proves that the proposed optimization approach can be useful in improving the accuracy of time series prediction based on machine learning.

Keywords: input variable disposition, machine learning, optimization, performance, time series prediction

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Authors: Paula Andrea Segura Delgado, Martha Helena Ramírez-Bahena

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Research on how the brain learns has a transcendental application in the educational context. It is crucial for teacher training to understand the nature of brain changes and their direct influence on learning processes. This communication is based on a literature review focused on neuroscience, neuroeducation, and the impact of digital technology on the human brain. Information was gathered from both English and Spanish language sources, using online journals, books and reports. The general objective was to analyze the role of neuroscience knowledge in enriching our understanding of the learning process. In fact, the authors have focused on the impact of digital technology on the human brain as well as its influence in the field of education..Neuroscience knowledge can contribute significantly to improving the training of educators and therefore educational practices. Education as an instrument of change and school as an agent of socialization, it is necessary to understand what it aims to transform: the human brain. Understanding the functioning of the human brain has important repercussions on education: this elucidates cognitive skills, psychological processes and elements that influence the learning process (memory, executive functions, emotions and the circadian cycle); helps identify psychological and neurological deficits that can impede learning processes (dyslexia, autism, hyperactivity); It allows creating environments that promote brain development and contribute to the advancement of brain capabilities in alignment with the stages of neurobiological development. The digital age presents diverse opportunities to every social environment. The frequent use of digital technology (DT) has had a significant and abrupt impact on both the cognitive abilities and physico-chemical properties of the brain, significantly influencing educational processes. Hence, educational community, with the insights from advances in neuroscience, aspire to identify the positive and negative effects of digital technology on the human brain. This knowledge helps ensure the alignment of teacher training and practices with these findings. The knowledge of neuroscience enables teachers to develop teaching methods that are aligned with the way the brain works. For example, neuroscience research has shown that digital technology is having a significant impact on the human brain (addition, anxiety, high levels of dopamine, circadian cycle disorder, decrease in attention, memory, concentration, problems with their social relationships). Therefore, it is important to understand the nature of these changes, their impact on the learning process, and how educators should effectively adapt their approaches based on these brain's changes.

Keywords: digital technology, learn process, neuroscience knowledge, neuroeducation, training proffesors

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Authors: A. Qayed Al-Emadi, C. Schwabenland, Q. Wei, B. Czarnecka

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In 2009, the new HRM policy was implemented in Qatar for public sector organisations. The purpose of this research is to examine how Qatar’s 2009 HRM policy was significant in influencing employee retention in public organisations. The conducted study utilised quantitative methodology to analyse the data on employees’ perceptions of such HRM practices as performance çanagement, rewards and promotion, training and development associated with the HRM policy in public organisations in comparison to semi-private organisations. Employees of seven public and semi-private organisations filled in the questionnaire based on the 5-point likert scale to present quantitative results. The data was analysed with the correlation and multiple regression statistical analyses. It was found that Performance Management had the relationship with Employee Retention, and Rewards and Promotion influenced Job Satisfaction in public organisations. The relationship between Job Satisfaction and Employee Retention was also observed. However, no significant differences were observed in the role of HRM practices in public and semi-private organisations.

Keywords: performance management, rewards and promotion, training and development, job satisfaction, employee retention, SHRM, configurational perspective

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Authors: Tamara Thompson

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This presentation will address the vocality of American soprano Sibyl Sanderson (1865–1903) in Massenet’s Manon and Esclarmonde as discernible from documentary sources such as vocal treatises, annotated scores, and correspondence. These sources will then be compared and contrasted with Sanderson’s reception in French press. Sanderson sang Manon in 1888, which Massenet revised for her. She then created the role of Esclarmonde for the 1889 l'Exposition Universelle in Paris. The soprano appeared as the Byzantine Empress more than 100 times in the nine months following the premiere, which secured her fame and an international operatic career frought with controversy and criticism as well as adulation. Before her débuts as Manon and Esclarmonde, Sanderson received musical training in California and Paris from multiple teachers with varied and opposing methods. There will be an exploration of the ways in which the disparate pedagogic influences such as those taught by Giovanni Sbriglia and Jean de Reszké may have guided Sanderson’s vocal strategies, and possibly caused or promoted the severe vocal pathologies she battled in subsequent years. In addition, there is interrogation of the vocal writing and revisions made to the titular roles for Sanderson in order to assess how these factors may have affected her technique and vocal health.

Keywords: French, nineteenth-century, opera, pedagogy, vocality

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Authors: Andrea Zielke-Nadkarni

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Pain management is a question of quality of life and an indicator for nursing quality. Chronic pain which is predominant in oncology and palliative nursing situations is perceived today as a multifactorial, individual emotional experience with specific characteristics including the sociocultural dimension when dealing with migrant patients. This dimension of chronic pain is of major importance in professional nursing of migrant patients in hospices or palliative care units. Objectives of the study are: 1. To find out more about the sociocultural views on pain and nursing care, on customs and nursing practices connected with pain of both Turkish Muslim and German Christian women, 2. To improve individual and family oriented nursing practice with view to sociocultural needs of patients in severe pain in palliative care. In a qualitative-explorative comparative study 4 groups of women, Turkish Muslims immigrants (4 from the first generation, 5 from the second generation) and German Christian women of two generations (5 of each age group) of the same age groups as the Turkish women and with similar educational backgrounds were interviewed (semistructured ethnographic interviews using Spradley, 1979) on their perceptions and experiences of pain and nursing care within their families. For both target groups the presentation will demonstrate the following results in detail: Utterance of pain as well as “private” and “public” pain vary within different societies and cultures. Permitted forms of pain utterance are learned in childhood and determine attitudes and expectations in adulthood. Language, especially when metaphors and symbols are used, plays a major role for misunderstandings. The sociocultural context of illness may include specific beliefs that are important to the patients and yet seem more than far-fetched from a biomedical perspective. Pain can be an influential factor in family relationships where respect or hierarchies do not allow the direct utterance of individual needs. Specific resources are often, although not exclusively, linked to religious convictions and are significantly helpful in reducing pain. The discussion will evaluate the results of the study with view to the relevant literature and present nursing interventions and instruments beyond medication that are helpful when dealing with patients from various socio-cultural backgrounds in painful end-oflife situations.

Keywords: pain management, migrants, sociocultural context, palliative care

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Authors: Aliya Grig, Konstantin Sokolov, Igor Shatalin

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The report describes the methodology for collecting data and building an ML model for determining the personality psychotype using profiling and personality traits methods based on several short messages of a user communicating on an arbitrary topic with a chitchat bot. In the course of the experiments, the minimum amount of text was revealed to confidently determine aspects of personality. Model accuracy - 85%. Users' language of communication is English. AI for a personalized communication with a user based on his mood, personality, and current emotional state. Features investigated during the research: personalized communication; providing empathy; adaptation to a user; predictive analytics. In the report, we describe the processes that captures both structured and unstructured data pertaining to a user in large quantities and diverse forms. This data is then effectively processed through ML tools to construct a knowledge graph and draw inferences regarding users of text messages in a comprehensive manner. Specifically, the system analyzes users' behavioral patterns and predicts future scenarios based on this analysis. As a result of the experiments, we provide for further research on training AI models to be empathetic, creating personalized communication for a user

Keywords: AI, empathetic, chatbot, AI models

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Authors: Najim Akorede Babalola

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Adult Education is a multi and interdisciplinary in nature that cut across different fields of study which includes education, social sciences, engineering even information technologies that dominate the contemporary world among others. In the past, Adult Education has been used as an instrument of civilization by teaching people how to read and write as well as earning a better living. The present world has witnessed a transition from industrial age to information age which is also known as knowledge society needs Adult Education for knowledge acquisition and update of existing knowledge. An individual needs Adult Education in either of its various forms (on-the-job-training, in-service training, extramural classes, vocational education, continuing education among others) in order to develop towards the information society trends; this is because Adult Education is a process of transforming an individual through acquisition of relevant skills and knowledge for personal as well as societal development. Evidence abounds in the literature that Adult Education has not only assisted people in the medieval period but still assisting people in this modern society in changing and transforming their lives for a better living. This study, therefore, raised a salient question that with different ideas and innovations brought by the contemporary world, is Adult Education relevant? It is on this basis that this study intends to examine the relevance of Adult Education in the past and present in order to determine its future relevance.

Keywords: adult education, multi and inter-disciplinary, knowledge society, skill acquisition

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Authors: Nathaniel Deboever, Malcolm Breeze, Adrian Sheen

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Basic surgical and suturing techniques are a fundamental requirement for all doctors. In order to gain confidence and competence, doctors in training need to obtain sufficient teaching and just as importantly: practice. Young doctors with an apt level of expertise on these simple surgical skills, which are often used in the Emergency Department, can help alleviate some pressure during a busy evening. Unfortunately, learning these skills can be quite difficult during medical school or even during junior doctor years. The aim of this project was to adequately train medical students attending University of Sydney’s Nepean Clinical School through a series of workshops highlighting practical skills, with hopes to further extend this program to junior doctors in the hospital. The sessions instructed basic skills via tutorials, demonstrations, and lastly, the sessions cemented these proficiencies with practical sessions. During such an endeavor, it is fundamental to employ models that appropriately resemble what students will encounter in the clinical setting. The sustainability of workshops is similarly important to the continuity of such a program. To address both these challenges, the authors have developed models including suturing platforms, knot tying, and vessel ligation stations, as well as a shave and punch biopsy models and ophthalmologic foreign body device. The unique aspect of this work is that we utilized hands-on teaching sessions, to address a gap in doctors-in-training and junior doctor curriculum. Presented to you through this poster are our approaches to creating models that do not employ animal products and therefore do not necessitate particular facilities or discarding requirements. Covering numerous skills that would be beneficial to all young doctors, these models are easily replicable and affordable. This exciting work allows for countless sessions at low cost, providing enough practice for students to perform these skills confidently as it has been shown through attendee questionnaires.

Keywords: medical education, surgical models, surgical simulation, surgical skills education

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Authors: Basma Hassabo, Sarah Ahmed, Aisha Hameed

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Aims and Objectives: To determine the incidence of maternal mortality amongst pregnant women with sickle cell disease (SCD) in the United Kingdom and to determine exact cause of death in these women. Background: SCD is caused by the ‘sickle’ gene and is characterized by episodes of severe bone pain and other complications like acute chest syndrome, chronic pulmonary hypertension, stroke, retinopathy, chronic renal failure, hepato-splenic crises, avascular bone necrosis, sepsis and leg ulcers. SCD is a continual cause of maternal mortality and fetal complications, and it comprises 1.5% of all Direct and Indirect deaths in the UK. Sepsis following premature rupture of membranes with ascending infection, post-partum infection and pre-labour overwhelming septic shock is one of its leading causes of death. Over the last fifty years of maternal mortality reports in UK, between 1 to 4 pregnant women died in each triennium. Material and Method: This is a retrospective study that involves pregnant women who died from SCD complications in the UK between 1952-2012. Data were collected from the UK Confidential Enquiries into Maternal Death and its causes between 1952–2012. Prior to 1985, exact cause of death in this cohort was not recorded. Results: 33 deaths reported between 1964 and 1984. 17 deaths were reported due to sickle cell disease between 1985 and 2012. Five women in this group died of sickle cell crisis, one woman had liver sequestration crisis, two women died of venous thromboembolism, two had myocardial fibrosis and three died of sepsis. Remaining women died of amniotic fluid embolism, SUDEP, myocardial ischemia and intracranial haemorrhage. Conclusion: The leading causes of death in sickle cell sick pregnant women are sickle cell crises, sepsis, venous thrombosis and thromboembolism. Prenatal care for women with SCD should be managed by a multidisciplinary team that includes an obstetrician, nutritionist, primary care physician, and haematologist. In every sick Sickle Cell woman Sickle Cell crises should be on the top of the list of differential diagnosis. Aggressive treatment of complications with low threshold to commence broad-spectrum antibiotics and LMWH contribute to better outcomes.

Keywords: incidence, maternal mortality, sickle cell disease (SCD), uk

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Authors: Dacheng Li, Bo Huang, Qinjin Han, Ming Li

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Remotely sensed imagery with the high spatial and temporal characteristics, which it is hard to acquire under the current land observation satellites, has been considered as a key factor for monitoring environmental changes over both global and local scales. On a basis of the limited high spatial-resolution observations, challenged studies called spatiotemporal fusion have been developed for generating high spatiotemporal images through employing other auxiliary low spatial-resolution data while with high-frequency observations. However, a majority of spatiotemporal fusion approaches yield to satisfactory assumption, empirical but unstable parameters, low accuracy or inefficient performance. Although the spatiotemporal fusion methodology via sparse representation theory has advantage in capturing reflectance changes, stability and execution efficiency (even more efficient when overcomplete dictionaries have been pre-trained), the retrieval of high-accuracy dictionary and its response to fusion results are still pending issues. In this paper, we employ additional image pairs (here each image-pair includes a Landsat Operational Land Imager and a Moderate Resolution Imaging Spectroradiometer acquisitions covering the partial area of Baotou, China) only into the coupled dictionary training process based on K-SVD (K-means Singular Value Decomposition) algorithm, and attempt to improve the fusion results of two existing sparse representation based fusion models (respectively utilizing one and two available image-pair). The results show that more eligible image pairs are probably related to a more accurate overcomplete dictionary, which generally indicates a better image representation, and is then contribute to an effective fusion performance in case that the added image-pair has similar seasonal aspects and image spatial structure features to the original image-pair. It is, therefore, reasonable to construct multi-dictionary training pattern for generating a series of high spatial resolution images based on limited acquisitions.

Keywords: spatiotemporal fusion, sparse representation, K-SVD algorithm, dictionary learning

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Authors: Shujun Xie, Shirong Zhang, Shenglin Ma

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Background: Chronic inflammation might lead to many malignancies, and inadequate resolution could play a crucial role in tumor invasion, progression, and metastases. A randomised, double-blind, placebo-controlled trial shows that IL-1β inhibition with canakinumab could reduce incident lung cancer and lung cancer mortality in patients with atherosclerosis. The process and secretion of proinflammatory cytokine IL-1β are controlled by the inflammasome. Here we showed the correlation of the innate immune system and afatinib, a tyrosine kinase inhibitor targeting epidermal growth factor receptor (EGFR) in non-small cell lung cancer. Methods: Murine Bone marrow derived macrophages (BMDMs), peritoneal macrophages (PMs) and THP-1 were used to check the effect of afatinib on the activation of NLRP3 inflammasome. The assembly of NLRP3 inflammasome was check by co-immunoprecipitation of NLRP3 and apoptosis-associated speck-like protein containing CARD (ASC), disuccinimidyl suberate (DSS)-cross link of ASC. Lipopolysaccharide (LPS)-induced sepsis and Alum-induced peritonitis were conducted to confirm that afatinib could inhibit the activation of NLRP3 in vivo. Peripheral blood mononuclear cells (PBMCs) from non-small cell lung cancer (NSCLC) patients before or after taking afatinib were used to check that afatinib inhibits inflammation in NSCLC therapy. Results: Our data showed that afatinib could inhibit the secretion of IL-1β in a dose-dependent manner in macrophage. Moreover, afatinib could inhibit the maturation of IL-1β and caspase-1 without affecting the precursors of IL-1β and caspase-1. Next, we found that afatinib could block the assembly of NLRP3 inflammasome and the ASC speck by blocking the interaction of the sensor protein NLRP3 and the adaptor protein ASC. We also found that afatinib was able to alleviate the LPS-induced sepsis in vivo. Conclusion: Our study found that afatinib could inhibit the activation of NLRP3 inflammasome in macrophage, providing new evidence that afatinib could target the innate immune system to control chronic inflammation. These investigations will provide significant experimental evidence in afatinib as therapeutic drug for non-small cell lung cancer or other tumors and NLRP3-related diseases and will explore new targets for afatinib.

Keywords: inflammasome, afatinib, inflammation, tyrosine kinase inhibitor

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Authors: Mohd Faridz Ahmad, Amirul Hakim Hasbullah

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Electrical Muscle Stimulation (EMS) has been introduced to the world in the 19th and 20th centuries and has globally gained increasing attention on its usefulness. EMS is known as the application of electrical current transcutaneous to muscles through electrodes to induce involuntary contractions that can lead to the increment of muscle mass and strength. This study can be used as an alternative to help people especially those living a sedentary lifestyle to improve their muscle activity without having to go through a heavy workout session. Therefore, this study intended to investigate the effectiveness of EMS training in 5 weeks interventions towards male body composition. It was a quasi-experimental design, held at the Impulse Studio Bangsar, which examined the effects of EMS training towards skeletal muscle mass among the subjects. Fifteen subjects (n = 15) were selected to assist in this study. The demographic data showed that, the average age of the subjects was 43.07 years old ± 9.90, height (173.4 cm ± 9.09) and weight was (85.79 kg ± 18.07). Results showed that there was a significant difference on the skeletal muscle mass (p = 0.01 < 0.05), upper body (p = 0.01 < 0.05) and lower body (p = 0.00 < 0.05). Therefore, the null hypothesis has been rejected in this study. As a conclusion, the application of EMS towards body composition can increase the muscle size and strength. This method has been proven to be able to improve athlete strength and thus, may be implemented in the sports science area of knowledge.

Keywords: body composition, EMS, skeletal muscle mass, strength

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Authors: Cyrus Addy, Venkata Sriram Siddhardh Nadendla, Kwame Awuah-Offei

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Surface robots in modern underground mine rescue operations suffer from several limitations in enabling a prompt self-rescue. Therefore, the possibility of designing and deploying in-mine robots to expedite miner self-rescue can have a transformative impact on miner safety. These in-mine robots for miner self-rescue can be envisioned to carry out diverse tasks such as object detection, autonomous navigation, and payload delivery. Specifically, this paper investigates the challenges in the design of object detection algorithms for in-mine robots using thermal images, especially to detect people in real-time. A total of 125 thermal images were collected in the Missouri S&T Experimental Mine with the help of student volunteers using the FLIR TG 297 infrared camera, which were pre-processed into training and validation datasets with 100 and 25 images, respectively. Three state-of-the-art, pre-trained real-time object detection models, namely YOLOv5, YOLO-FIRI, and YOLOv8, were considered and re-trained using transfer learning techniques on the training dataset. On the validation dataset, the re-trained YOLOv8 outperforms the re-trained versions of both YOLOv5, and YOLO-FIRI.

Keywords: miner self-rescue, object detection, underground mine, YOLO

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Authors: Leonard Tiong, Sonit Singh, Kevin Ho Shon, Sarah Lewis

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Investigation into the use of artificial intelligence in radiology continues to develop at a rapid rate. During the coronavirus pandemic, the combination of an exponential increase in chest x-rays and unpredictable staff shortages resulted in a huge strain on the department's workload. There is a World Health Organisation estimate that two-thirds of the global population does not have access to diagnostic radiology. Therefore, there could be demand for a program that could detect acute changes in imaging compatible with infection to assist with screening. We generated a conventional neural network and tested its efficacy in recognizing changes compatible with coronavirus infection. Following ethics approval, a deidentified set of 77 normal and 77 abnormal chest x-rays in patients with confirmed coronavirus infection were used to generate an algorithm that could train, validate and then test itself. DICOM and PNG image formats were selected due to their lossless file format. The model was trained with 100 images (50 positive, 50 negative), validated against 28 samples (14 positive, 14 negative), and tested against 26 samples (13 positive, 13 negative). The initial training of the model involved training a conventional neural network in what constituted a normal study and changes on the x-rays compatible with coronavirus infection. The weightings were then modified, and the model was executed again. The training samples were in batch sizes of 8 and underwent 25 epochs of training. The results trended towards an 85.71% true positive/true negative detection rate and an area under the curve trending towards 0.95, indicating approximately 95% accuracy in detecting changes on chest X-rays compatible with coronavirus infection. Study limitations include access to only a small dataset and no specificity in the diagnosis. Following a discussion with our programmer, there are areas where modifications in the weighting of the algorithm can be made in order to improve the detection rates. Given the high detection rate of the program, and the potential ease of implementation, this would be effective in assisting staff that is not trained in radiology in detecting otherwise subtle changes that might not be appreciated on imaging. Limitations include the lack of a differential diagnosis and application of the appropriate clinical history, although this may be less of a problem in day-to-day clinical practice. It is nonetheless our belief that implementing this program and widening its scope to detecting multiple pathologies such as lung masses will greatly assist both the radiology department and our colleagues in increasing workflow and detection rate.

Keywords: artificial intelligence, COVID, neural network, machine learning

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Authors: Chayanika Hazarika Bordoloi

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This paper is an attempt to work on a highly inflectional language called Assamese. This is also one of the national languages of India and very little has been achieved in terms of computational research. Building a language processing tool for a natural language is not very smooth as the standard and language representation change at various levels. This paper presents inflectional suffixes of Assamese verbs and how the statistical tools, along with linguistic features, can improve the tagging accuracy. Conditional random fields (CRF tool) was used to automatically tag and train the text data; however, accuracy was improved after linguistic featured were fed into the training data. Assamese is a highly inflectional language; hence, it is challenging to standardizing its morphology. Inflectional suffixes are used as a feature of the text data. In order to analyze the inflections of Assamese word forms, a list of suffixes is prepared. This list comprises suffixes, comprising of all possible suffixes that various categories can take is prepared. Assamese words can be classified into inflected classes (noun, pronoun, adjective and verb) and un-inflected classes (adverb and particle). The corpus used for this morphological analysis has huge tokens. The corpus is a mixed corpus and it has given satisfactory accuracy. The accuracy rate of the tagger has gradually improved with the modified training data.

Keywords: CRF, morphology, tagging, tagset

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Authors: Peiming Li

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This paper presents an innovative blockchain-based approach to enhance the reliability and efficiency of federated learning systems. By integrating a decentralized oracle consensus mechanism into the federated learning framework, we address key challenges of data and model integrity. Our approach utilizes a network of redundant oracles, functioning as independent validators within an epoch-based training system in the federated learning model. In federated learning, data is decentralized, residing on various participants' devices. This scenario often leads to concerns about data integrity and model quality. Our solution employs blockchain technology to establish a transparent and tamper-proof environment, ensuring secure data sharing and aggregation. The decentralized oracles, a concept borrowed from blockchain systems, act as unbiased validators. They assess the contributions of each participant using a Hidden Markov Model (HMM), which is crucial for evaluating the consistency of participant inputs and safeguarding against model poisoning and malicious activities. Our methodology's distinct feature is its epoch-based training. An epoch here refers to a specific training phase where data is updated and assessed for quality and relevance. The redundant oracles work in concert to validate data updates during these epochs, enhancing the system's resilience to security threats and data corruption. The effectiveness of this system was tested using the Mnist dataset, a standard in machine learning for benchmarking. Results demonstrate that our blockchain-oriented federated learning approach significantly boosts system resilience, addressing the common challenges of federated environments. This paper aims to make these advanced concepts accessible, even to those with a limited background in blockchain or federated learning. We provide a foundational understanding of how blockchain technology can revolutionize data integrity in decentralized systems and explain the role of oracles in maintaining model accuracy and reliability.

Keywords: federated learning system, block chain, decentralized oracles, hidden markov model

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Authors: E. Verduci, I. Aguglia, A. Filocamo, I. Macrì, R. Scala, A. Vinci

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One of the first indicator of autism spectrum disorder (ASD) is a decreasing tendency or failure to respond to name (RTN) call. Despite RTN is important for social and language developmentand it’s a common target for early interventions for children with ASD, research on specific treatments is insufficient and does not consider the importance of the discrimination between the own name and other names. The purpose of the current study was to replicate an assessment and treatment model proposed by Conine et al. (2020) to teach children with ASD to respond to their own name and to not respond to other names (RTO). The model includes three different phases (baseline/screening, treatment, and generalization), and itgradually introduces the different treatment components, starting with the most naturalistic ones (such as social interaction) and adding more intrusive components (such as tangible reinforcements, prompt and fading procedures) if necessary. The participants of this study were three children with ASD diagnosis: D. (5 years old) with a low frequency of RTN, M. (7 years old) with a RTN unstable and no ability of discrimination between his name and other names, S. (3 years old) with a strong RTN but a constant response to other names. Moreover, the treatment for D. and M. consisted of social and tangible reinforcements (treatment T1), for S. the purpose of the treatment was to teach the discrimination between his name and the others. For all participants, results suggest the efficacy of the model to acquire the ability to selectively respond to the own name and the generalization of the behavior with other people and settings.

Keywords: response to name, autism spectrum disorder, progressive training, ABA

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Authors: Kohkan Shamsi

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Background: MRI and PET are now extensively utilized in Alzheimer's disease (AD) trials for patient eligibility, efficacy assessment, and safety evaluations but including imaging in AD trials impacts site selection process, patient recruitment, and patient retention. Methods: PET/MRI are performed at baseline and at multiple follow-up timepoints. This requires prospective site imaging qualification, evaluation of phantom data, training and continuous monitoring of machines for acquisition of standardized and consistent data. This also requires prospective patient/caregiver training as patients must go to multiple facilities for imaging examinations. We will share our experience form one of the largest AD programs. Lesson learned: Many neurological diseases have a similar presentation as AD or could confound the assessment of drug therapy. The inclusion of wrong patients has ethical and legal issues, and data could be excluded from the analysis. Centralized eligibility evaluation read process will be discussed. Amyloid related imaging abnormalities (ARIA) were observed in amyloid-β trials. FDA recommended regular monitoring of ARIA. Our experience in ARIA evaluations in large phase III study at > 350 sites will be presented. Efficacy evaluation: MRI is utilized to evaluate various volumes of the brain. FDG PET or amyloid PET agents has been used in AD trials. We will share our experience about site and central independent reads. Imaging logistic issues that need to be handled in the planning phase will also be discussed as it can impact patient compliance thereby increasing missing data and affecting study results. Conclusion: imaging must be prospectively planned to include standardizing imaging methodologies, site selection process and selecting assessment criteria. Training should be transparently conducted and documented. Prospective patient/caregiver awareness of imaging requirement is essential for patient compliance and reduction in missing imaging data.

Keywords: Alzheimer's disease, ARIA, MRI, PET, patient recruitment, retention

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Authors: Samar Mousa, Ryan Kerstein, Mohanad Adam

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Regional anaesthesia has been associated with favourable outcomes in patients undergoing a wide range of surgeries. Beneficial effects have been demonstrated in terms of postoperative respiratory and cardiovascular endpoints, 7-day survival, time to ambulation and hospital discharge, and postoperative analgesia. Our project aimed at assessing the regional anaesthesia practice in the plastic surgery department of Buckinghamshire trust and finding out ways to improve the service in collaboration with the anaesthesia team. It is a retrospective study associated with a questionnaire filled out by plastic surgeons and anaesthetists to get the full picture behind the numbers. The study period was between 1/3/2022 and 23/5/2022 (12 weeks). The operative notes of all patients who had an operation under plastic surgery, whether emergency or elective, were reviewed. The criteria of suitable candidates for the regional block were put by the consultant anaesthetists as follows: age above 16, single surgical site (arm, forearm, leg, foot), no drug allergy, no pre-existing neuropathy, no bleeding disorders, not on ant-coagulation, no infection to the site of the block. For 12 weeks, 1061 operations were performed by plastic surgeons. Local cases were excluded leaving 319 cases. Of the 319, 102 patients were suitable candidates for regional block after applying the previously mentioned criteria. However, only seven patients had their operations under the regional block, and the rest had general anaesthesia that could have been easily avoided. An online questionnaire was filled out by both plastic surgeons and anaesthetists of different training levels to find out the reasons behind the obvious preference for general over regional anaesthesia, even if this was against the patients’ interest. The questionnaire included the following points: training level, time taken to give GA or RA, factors that influence the decision, percentage of RA candidates that had GA, reasons behind this percentage, recommendations. Forty-four clinicians filled out the questionnaire, among which were 23 plastic surgeons and 21 anaesthetists. As regards the training level, there were 21 consultants, 4 associate specialists, 9 registrars, and 10 senior house officers. The actual percentage of patients who were good candidates for RA but had GA instead is 93%. The replies estimated this percentage as between 10-30%. 29% of the respondents thought that this percentage is because of surgeons’ preference to have GA rather than RA for their operations without medical support for the decision. 37% of the replies thought that anaesthetists prefer giving GA even if the patient is a suitable candidate for RA. 22.6% of the replies thought that patients refused to have RA, and 11.3% had other causes. The recommendations were in 5 main accesses, which are protocols and pathways for regional blocks, more training opportunities for anaesthetists on regional blocks, providing a separate block room in the hospital, better communication between surgeons and anaesthetists, patient education about the benefits of regional blocks.

Keywords: regional anaesthesia, regional block, plastic surgery, general anaesthesia

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Authors: Mahera Abdulrahman

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Objective: Healthcare transformation from traditional to modern in the country recently prompted the need to address career choices, accreditation perception and satisfaction among medical residents. However, a concerted nationwide study to understand and address burnout in the medical residency program has not been conducted in the UAE and the region. Methods: A nationwide, multicenter, cross-sectional study was designed to evaluate professional burnout and depression among medical residents in order to address the gap. Results: Our results indicate that 75.5% (216/286) of UAE medical residents had moderate to high emotional exhaustion, 84% (249/298) had high depersonalization, and 74% (216/291) had a low sense of personal accomplishment. In aggregate, 70% (212/302) of medical residents were considered to be experiencing at least one symptom of burnout based on a high emotional exhaustion score or a high depersonalization score. Depression ranging from 6-22%, depending on the specialty was also striking given the fact the Arab culture lays high emphasis on family bonding. Interestingly 83% (40/48) of medical residents who had high scores for depression also reported burnout. Conclusion: Our data indicate that burnout and depression among medical residents is epidemic. There is an immediate need to address burnout through effective interventions at both the individual and institutional levels. It is imperative to reconfigure the approach to medical training for the well-being of the next generation of physicians in the Arab world.

Keywords: mental health, Gulf, Arab, residency training, burnout, depression

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Authors: Sílvia tuyà Viñas, Bruno Fernández-Valdés, Carla Pérez-Chirinos, Monica Morral-Yepes, Lucas del Campo Montoliu, Gerard Moras Feliu

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Some researchers stated that whole body vibration (WBV) generates postural destabilization, although there is no extensive research. Therefore, the aim of this study was to analyze movement variability when performing a half-squat with a different type of ballasts and rhythms with (V) and without (NV) WBV in male athletes using entropy. Twelve experienced in strength training males (age: 21.24  2.35 years, height: 176.83  5.80 cm, body mass: 70.63  8.58 kg) performed a half-squat with weighted vest (WV), dumbbells (D), and a bar with the weights suspended with elastic bands (B), in V and NV at 40 bpm and 60 bpm. Subjects performed one set of twelve repetitions of each situation, composed by the combination of the three factors. The movement variability was analyzed by calculating the Sample Entropy (SampEn) of the total acceleration signal recorded at the waist. In V, significant differences were found between D and WV (p<0.001; ES: 2.87 at 40 bpm; p<0.001; ES: 3.17 at 60 bpm) and between the B and WV at both rhythms (p<0.001; ES: 3.12 at 40 bpm; p<0.001; ES: 2.93 at 60 bpm) and a higher SampEn was obtained at 40 bpm with all ballasts (p<0.001; ES of WV: 1.22; ES of D: 4.49; ES of B: 4.03). No significant differences were found in NV. WBV is a disturbing and destabilizing stimulus. Strength and conditioning coaches should choose the combination of ballast and rhythm of execution according to the level and objectives of each athlete.

Keywords: accelerometry, destabilization, entropy, movement variability, resistance training

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Authors: Valerie Isaak

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Background: This study explores the effectiveness of refresher training sessions of an intervention program at reducing the employees’ risk of injury due to patient violence in a forensic psychiatric hospital. Methods: The original safety intervention program that consisted of a 3 days’ workshop was conducted in the maximum-security ward of a psychiatric hospital in Israel. Ever since the original intervention, annual refreshers were conducted, highlighting one of the safety elements covered in the original intervention. The study examines the effect of the intervention program along with the refreshers over a period of 10 years in four wards. Results: Analysis of the data demonstrates that beyond the initial reduction following the original intervention, refreshers seem to have an additional positive long-term effect, reducing both the number of violent incidents and the number of actual employee injuries in a forensic psychiatric hospital. Conclusions: We conclude that such an intervention program followed by refresher training would promote employees’ wellbeing. A healthy work environment is part of management’s commitment to improving employee wellbeing at the workplace.

Keywords: wellbeing, violence at work, intervention program refreshers, public sector mental healthcare

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Authors: Victoria L. Chester, Usha Kuruganti

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The forest industry is a major economic sector of Canada and also one of the most dangerous industries for workers. The use of mechanized mobile forestry harvesting machines has successfully reduced the incidence of injuries in forest workers related to manual labor. However, these machines have also created additional concerns, including a high machine operation learning curve, increased the length of the workday, repetitive strain injury, cognitive load, physical and mental fatigue, and increased postural loads due to sitting in a confined space. It is critical to obtain objective performance data for employers to develop appropriate work practices for this industry, however ergonomic field studies of this industry are lacking mainly due to the difficulties in obtaining comprehensive data while operators are cutting trees in the woods. The purpose of this study was to establish a measurement and experimental protocol to examine the effects of worker skill level and movement training speed (joystick crane speed) on harvesting performance using a forestry simulator. A custom wrist angle measurement device was developed as part of the study to monitor Euler angles during operation of the simulator. The device of the system consisted of two accelerometers, a Bluetooth module, three 3V coin cells, a microcontroller, a voltage regulator and an application software. Harvesting performance and crane data was provided by the simulator software and included tree to frame collisions, crane to tree collisions, boom tip distance, number of trees cut, etc. A pilot study of 3 operators with various skill levels was tested to identify factors that distinguish highly skilled operators from novice or intermediate operators. Dependent variables such as reaction time, math skill, past work experience, training movement speed (e.g. joystick control speeds), harvesting experience level, muscle activity, and wrist biomechanics were measured and analyzed. A 10-channel wireless surface EMG system was used to monitor the amplitude and mean frequency of 10 upper extremity muscles during pre and postperformance on the forestry harvest stimulator. The results of the pilot study showed inconsistent changes in median frequency pre-and postoperation, but there was the increase in the activity of the flexor carpi radialis, anterior deltoid and upper trapezius of both arms. The wrist sensor results indicated that wrist supination and pronation occurred more than flexion and extension with radial-ulnar rotation demonstrating the least movement. Overall, wrist angular motion increased as the crane speed increased from slow to fast. Further data collection is needed and will help industry partners determine those factors that separate skill levels of operators, identify optimal training speeds, and determine the length of training required to bring new operators to an efficient skill level effectively. In addition to effective and employment training programs, results of this work will be used for selective employee recruitment strategies to improve employee retention after training. Further, improved training procedures and knowledge of the physical and mental demands on workers will lead to highly trained and efficient personnel, reduced risk of injury, and optimal work protocols.

Keywords: EMG, forestry, human factors, wrist biomechanics

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Authors: Carlos Vera, Tetyana Baydyk, Ernst Kussul, Graciela Velasco, Miguel Aparicio

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This article describes the Random Subspace Neural Classifier (RSC) for the recognition of meteors in the night sky. We used images of meteors entering the atmosphere at night between 8:00 p.m.-5: 00 a.m. The objective of this project is to classify meteor and star images (with stars as the image background). The monitoring of the sky and the classification of meteors are made for future applications by scientists. The image database was collected from different websites. We worked with RGB-type images with dimensions of 220x220 pixels stored in the BitMap Protocol (BMP) format. Subsequent window scanning and processing were carried out for each image. The scan window where the characteristics were extracted had the size of 20x20 pixels with a scanning step size of 10 pixels. Brightness, contrast and contour orientation histograms were used as inputs for the RSC. The RSC worked with two classes and classified into: 1) with meteors and 2) without meteors. Different tests were carried out by varying the number of training cycles and the number of images for training and recognition. The percentage error for the neural classifier was calculated. The results show a good RSC classifier response with 89% correct recognition. The results of these experiments are presented and discussed.

Keywords: contour orientation histogram, meteors, night sky, RSC neural classifier, stars

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Authors: Charalambos C. Cleanthous, Ryan Sain, Tabitha Black, Stephen Vera, Suzanne Milton

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A concern when administering questionnaires is whether the participant is providing information that is accurate. The results may be invalid because the person is trying to present oneself in an unrealistic positive manner referred to as ‘faking good’, or in an unrealistic negative manner known as ‘faking bad’. The Balanced Inventory of Desirable Responding (BIDR) was used to assess commercial pilots’ responses on the two subscales of the BIDR: impression management (IM) and self-deceptive enhancement (SDE) that result in high or low scores. Thus, the BIDR produces four valid profiles: IM low and SDE low, IM high and SDE low, IM low and SDE high, and IM high and SDE high. The various profiles were used to compare the respondents’ answers to crew resource management (CRM) items developed from the USA Federal Aviation Administration’s (FAA) guidelines for CRM composition and training. Of particular interest were the results on the IM subscale. The comparisons between those scoring high (lying or faking) versus those low on the IM suggest that there were significant differences regarding their views of the various dimensions of CRM. One of the more disconcerting conclusions is that the high IM scores suggest that the pilots were trying to impress rather than honestly answer the questions regarding their CRM training and practice.

Keywords: USA commercial pilots, crew resource management, faking, social desirability

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Authors: Hancy Issac, Gerben Keijzers, Ian Yang, Clint Moloney, Jackie Lea, Melissa Taylor

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Introduction: Chronic obstructive pulmonary disease guideline non-adherence is associated with a reduction in health-related quality of life in patients (HRQoL). Improving guideline adherence has the potential to mitigate fragmented care thereby sustaining pulmonary function, preventing acute exacerbations, reducing economic health burdens, and enhancing HRQoL. The development of an electronic proforma stemming from expert consensus, including digital guideline resources and direct interdisciplinary referrals is hypothesised to improve guideline adherence and patient outcomes for emergency department (ED) patients with COPD. Aim: The aim of this study was to develop consensus among ED and respiratory staff for the correct composition of a COPD electronic proforma that aids in guideline adherence and management in the ED. Methods: This study adopted a mixed-method design to develop the most important indicators of care in the ED. The study involved three phases: (1) a systematic literature review and qualitative interdisciplinary staff interviews to assess barriers and solutions for guideline adherence and qualitative interdisciplinary staff interviews, (2) a modified Delphi panel to select interventions for the proforma, and (3) a consensus process through three rounds of scoring through a quantitative survey (ED and Respiratory consensus) and qualitative thematic analysis on each indicator. Results: The electronic proforma achieved acceptable and good internal consistency through all iterations from national emergency department and respiratory department interdisciplinary experts. Cronbach’s alpha score for internal consistency (α) in iteration 1 emergency department cohort (EDC) (α = 0.80 [CI = 0.89%]), respiratory department cohort (RDC) (α = 0.95 [CI = 0.98%]). Iteration 2 reported EDC (α = 0.85 [CI = 0.97%]) and RDC (α = 0.86 [CI = 0.97%]). Iteration 3 revealed EDC (α = 0.73 [CI = 0.91%]) and RDC (α = 0.86 [CI = 0.95%]), respectively. Conclusion: Electronic proformas have the potential to facilitate direct referrals from the ED leading to reduced hospital admissions, reduced length of hospital stays, holistic care, improved health care and quality of life and improved interdisciplinary guideline adherence.

Keywords: COPD, electronic proforma, modified delphi study, interdisciplinary, guideline adherence, COPD-X plan

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Authors: Ahmet Erdoğan, Şahin Kesici, Mustafa Baloğlu

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Information technologies have lead to changes in the areas of communication, learning, and teaching. Besides offering many opportunities to the learners, these technologies have changed the teaching methods and beliefs of teachers. What the Technological Pedagogical Content Knowledge (TPACK) means to the teachers is considerably important to integrate technology successfully into teaching processes. It is necessary to understand how to plan and apply teacher training programs in order to balance students’ pedagogical and technological knowledge. Because of many inefficient teacher training programs, teachers have difficulties in relating technology, pedagogy and content knowledge each other. While providing an efficient training supported with technology, understanding the three main components (technology, pedagogy and content knowledge) and their relationship are very crucial. The purpose of this study is to determine whether motivational beliefs and self-regulated learning strategies are significant predictors of mathematics teacher candidates' TPACK perceptions. A hundred seventy five Turkish mathematics teachers candidates responded to the Motivated Strategies for Learning Questionnaire (MSLQ) and the Technological Pedagogical And Content Knowledge (TPACK) Scale. Of the group, 129 (73.7%) were women and 46 (26.3%) were men. Participants' ages ranged from 20 to 31 years with a mean of 23.04 years (SD = 2.001). In this study, a multiple linear regression analysis was used. In multiple linear regression analysis, the relationship between the predictor variables, mathematics teacher candidates' motivational beliefs, and self-regulated learning strategies, and the dependent variable, TPACK perceptions, were tested. It was determined that self-efficacy for learning and performance and intrinsic goal orientation are significant predictors of mathematics teacher candidates' TPACK perceptions. Additionally, mathematics teacher candidates' critical thinking, metacognitive self-regulation, organisation, time and study environment management, and help-seeking were found to be significant predictors for their TPACK perceptions.

Keywords: candidate mathematics teachers, motivational beliefs, self-regulated learning strategies, technological and pedagogical knowledge, content knowledge

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