Search results for: improvement score

Authors: Ana Munguia, Gerardo Ortiz, Guadalupe Gonzalez, Fiacro Jimenez

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Parkinson's disease (PD) is a neurodegenerative disorder that causes motor and cognitive symptoms. The first-choice treatment for these patients is pharmacological, but this generates several side effects. Because of that new treatments were introduced such as Repetitive Transcranial Magnetic Stimulation (rTMS) in order to improve the life quality of the patients. Several studies suggest significant changes in motor symptoms. However, there is a great diversity in the number of pulses, amplitude, frequency and stimulation targets, which results in inconsistent data. In addition, these studies do not have an analysis of the neuropsychological effects of the treatment. The main purpose of this study is to evaluate the impact of rTMS on the cognitive performance of 6 patients with H&Y III and IV (45-65 years, 3 men and 3 women). An initial neuropsychological and neurological evaluation was performed. Patients were randomized into two groups; in the first phase one received rTMS in the supplementary motor area, the other group in the dorsolateral prefrontal cortex contralateral to the most affected hemibody. In the second phase, each group received the stimulation in the area that he had not been stimulated previously. Reassessments were carried out at the beginning, at the end of each phase and a follow-up was carried out 6 months after the conclusion of the stimulation. In these preliminary results, it is reported that there's no statistically significant difference before and after receiving rTMS in the neuropsychological test scores of the patients, which suggests that the cognitive performance of patients is not detrimental. There are even tendencies towards an improvement in executive functioning after the treatment. What added to motor improvement, showed positive effects in the activities of the patients' daily life. In a later and more detailed analysis, will be evaluated the effects in each of the patients separately in relation to the functionality of the patients in their daily lives.

Keywords: Parkinson's disease, rTMS, cognitive, treatment

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Authors: Afrah Saad Mohsen Al-Mahfadi

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In rural areas of developing countries, participation of all stakeholders in water supply projects is an important step towards further development. As most of the beneficiaries are women, it is important that they should be involved to achieve successful and sustainable water supply projects. Women are responsible for the management of water both inside and outside home, and often spend more than six-hours a day fetching drinking water from distant water sources. The problem is that rural women play a role of little importance in the water supply projects’ phases in rural Yemen. Therefore, this research aimed at analyzing the different reasons of their lack of participation in projects and in what way a full participation -if achieved- could contribute to sustainable water supply projects in the rural mountainous areas in Yemen. Four water supply projects were selected as a case study in Al-Della'a Alaala sub-district in the Al-Mahweet governorate, two of them were implemented by the Social Fund and Development (SFD), while others were implemented by the General Authority for Rural Water Supply Projects (GARWSSP). Furthermore, the successful Al-Galba project, which is located in Badan district in Ibb governorate, was selected for comparison. The rural women's active participation in water projects have potential consequences including continuity and maintenance improvement, equipment security, and improvement in the overall health and education status of these areas. The majority of respondents taking part in GARWSSP projects estimated that there is no reason to involve women in the project activities. In the comparison project - in which a woman worked as a supervisor and implemented the project – all respondents indicated that the participation of women is vital for sustainability. Therefore, the results of this research are intended to stimulate rural women's participation in the mountainous areas of Yemen.

Keywords: assessment, rural woman, sustainability, water management

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Authors: Esam Roshdy, Saleh AlRashdi, Turki Alharbi, Rawan Eskandarani, Zurina Cabilo

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Introduction/ background: Consultation in the Emergency Department constitute a major part of the work flow every day. Any delay in the consultation process have a major impact on the length of stay and patient disposition and thus affect the total waiting time of patients in the ED. King Fahad medical City in Riyadh City, Saudi Arabia is considered a major Tertiary hospital where there is high flow of patients of different categories visiting the ED. The importance of decreasing consultation time and decision for final disposition of patients was recognized and interpreted in this project to find ways to improve the patient flow in the department and thus the total patient disposition and outcome. Aim / Objectives: 1. To monitor the time of consultation for patients in the Emergency department and its impact on the length of stay of patients in the ED. 2. To detect and assess the problems that lead to long consultation times in the ED, and reach a targeted time of 2 hours for final disposition of patients, according to recognized international and our institutional consultation policy, to reach the final goal of decreasing total length of stay and thus improve the patient flow in the ED. Methods: Data was collected retrospectively for a 92 charts of consultations done in the ED over 2 month’s period. The data was analyzed to get the median of Total Consultation Time. A survey was conducted among all ED staff to determine the level of knowledge about the total consultation time and the compliance to the institutional policy target of 2 hours. A second Data sample of 168 chart was collected after awareness campaign and education of all ED staff about the importance of reaching the target consultation time and compliance to the institutional policy. Results: We have found that there is room for improvement in our overall consultation time. This was found to be more frequent with certain specialties. Our surveys have showed that many ED staff are not familiar or not compliant with our consultation policy which was not clear for everyone. Post-intervention data have showed that awareness of the importance to decrease the total consultation time and compliance alone to the targeted goal have had a huge impact on overall improvement and decreasing the time of final decision and disposition of the patient and the overall patient length of stay in the ED. Conclusion: Working on improving Consultation time in the Emergency Department is a major factor in improving overall length of stay and patient flow. This improvement helps in the overall patient disposition and satisfaction. Plan: As a continuation of our project we are planning to focus on the conflict of admission cases where more than one specialty is involved in the care of patients. We are planning to collect data on the time it takes to resolve and reach final disposition of those patients, and its impact on the length of stay and our department flow and the overall patient outcome and satisfaction.

Keywords: consultation time, impact, length of stay, in the ED

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Authors: Rangika Perera, Shyamani Hettiarachchi, Fran Hagstrom

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

Keywords: Dyslexia, knowledge, teaching skills, training program

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Authors: K. C. M. Wong, C. P. Y. Cheng, K. Y. Chan, G. S. C. Fung, T. F. O. Lau, K. F. C. Leung, J. P. C. Fok

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Hospital Authority (HA) is the statutory body to manage all public hospitals in Hong Kong. Occupational Care Medicine Service (OMCS) is an in-house multi-disciplinary team responsible for injury management in HA. Hospital administrative services (AS) provides essential support in hospital daily operation to facilitate the provision of quality healthcare services. An occupational health enhancement program in Tai Po Hospital (TPH) domestic service supporting unit (DSSU) was piloted in 2013 with satisfactory outcome, the keys to success were staff engagement and management support. Riding on the success, the program was rolled out to another 5 AS departments of Alice Ho Miu Ling Nethersole Hospital (AHNH) and TPH in 2015. This paper highlights the indispensable components of disability management and occupational health enhancement program in hospital settings. Objectives: 1) Facilitate workplace to support staff with health affecting work problem, 2) Enhance staff’s occupational health. Methodology: Hospital Occupational Safety and Health (OSH) team and AS departments (catering, linen services, and DSSU) of AHNH and TPH worked closely with OMCS. Focus group meetings and worksite visits were conducted with frontline staff engagement. OSH hazards were identified with corresponding OSH improvement measures introduced, e.g., invention of high dusting device to minimize working at height; tailor-made linen cart to minimize back bending at work, etc. Specific MHO trainings were offered to each AS department. A disability management workshop was provided to supervisors in order to enhance their knowledge and skills in return-to-work (RTW) facilitation. Based on injured staff's health condition, OMCS would provide work recommendation, and RTW plan was formulated with engagement of staff and their supervisors. Genuine communication among stakeholders with expectation management paved the way for realistic goals setting and success in our program. Outcome: After implementation of the program, a significant drop of 26% in musculoskeletal disorders related sickness absence day was noted in 2016 as compared to the average of 2013-2015. The improvement was postulated by innovative OSH improvement measures, teamwork, staff engagement and management support. Staff and supervisors’ feedback were very encouraging that 90% respondents rated very satisfactory in program evaluation. This program exemplified good work sharing among departments to support staff in need.

Keywords: disability management, occupational health, return to work, occupational medicine

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Authors: Yu-Chi Liao, Nai-Wen Guo, Chun‑Hung Lee, Yung-Chin Lu, Cheng-Hung Ko

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Objective: The incidence of behavioral addictions, especially substance use disorders (SUDs), is gradually be taken seriously with various physical health problems. Mindfulness-based relapse prevention (MBRP) is a treatment option for promoting long-term health behavior change in recent years. MBRP is a structured protocol that integrates formal meditation practices with the cognitive-behavioral approach of relapse prevention treatment by teaching participants not to engage in reappraisal or savoring techniques. However, considering SUDs as a complex brain disease, questionnaires and symptom evaluation are not sufficient to evaluate the effect of MBRP. Neurophysiological biomarkers such as quantitative electroencephalogram (QEEG) may improve accurately represent the curative effects. This study attempted to find out the neurophysiological indicator of MBRP in various severity SUD involuntary clients. Participants and Methods: Thirteen participants (all males) completed 8-week mindfulness-based treatment provided by trained, licensed clinical psychologists. The behavioral data were from the Severity of Dependence Scale (SDS) and Negative Mood Regulation Scale (NMR) before and afterMBRP treatment. The QEEG data were simultaneously recorded with executive attention tasks, called comprehensive nonverbal attention test(CNAT). The two-way repeated-measures (treatment * severity) ANOVA and independent t-test were used for statistical analysis. Results: Thirteen participants regrouped into high substance dependence (HS) and low substance dependence (LS) by SDS cut-off. The HS group showed more SDS total score and lower gamma wave in the Go/No Go task of CNAT at pretest. Both groups showed the main effect that they had a lower frontal theta/beta ratio (TBR) during the simple reaction time task of CNAT. The main effect showed that the delay errors of CNAT were lower after MBRP. There was no other difference in CNAT between groups. However, after MBRP, compared to LS, the HS group have resonant progress in improving SDS and NMR scores. The neurophysiological index, the frontal TBR of the HS during the Go/No Go task of CNATdecreased than that of the LS group. Otherwise, the LS group’s gamma wave was a significant reduction on the Go/No Go task of CNAT. Conclusion: The QEEG data supports the MBRP can restore the prefrontal function of involuntary addicts and lower their errors in executive attention tasks. However, the improvement of MBRPfor the addict with high addiction severity is significantly more than that with low severity, including QEEG’s indicators and negative emotion regulation. Future directions include investigating the reasons for differences in efficacy among different severity of the addiction.

Keywords: mindfulness, involuntary clients, QEEG, emotion regulation

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Authors: Lyndsee Baumann-Birkbeck, Sohil A. Khan, Shailendra Anoopkumar-Dukie, Gary D. Grant

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Technology-enhanced education tools are being rapidly integrated into health programs globally. These tools provide an interactive platform for students and can be used to deliver topics in various modes including games and simulations. Simulations are of particular interest to healthcare education, where they are employed to enhance clinical knowledge and help to bridge the gap between theory and practice. Simulations will often assess competencies for practical tasks, yet limited research examines the effects of simulation on student perceptions of their learning. The aim of this study was to determine the effects of an interactive virtual patient simulation for pharmacology education and clinical practice on student knowledge, skills and confidence. Ethics approval for the study was obtained from Griffith University Research Ethics Committee (PHM/11/14/HREC). The simulation was intended to replicate the pharmacy environment and patient interaction. The content was designed to enhance knowledge of proton-pump inhibitor pharmacology, role in therapeutics and safe supply to patients. The tool was deployed into a third-year clinical pharmacology and therapeutics course. A number of core practice areas were examined including the competency domains of questioning, counselling, referral and product provision. Baseline measures of student self-reported knowledge, skills and confidence were taken prior to the simulation using a specifically designed questionnaire. A more extensive questionnaire was deployed following the virtual patient simulation, which also included measures of student engagement with the activity. A quiz assessing student factual and conceptual knowledge of proton-pump inhibitor pharmacology and related counselling information was also included in both questionnaires. Sixty-one students (response rate >95%) from two cohorts (2014 and 2015) participated in the study. Chi-square analyses were performed and data analysed using Fishers exact test. Results demonstrate that student knowledge, skills and confidence within the competency domains of questioning, counselling, referral and product provision, show improvement following the implementation of the virtual patient simulation. Statistically significant (p<0.05) improvement occurred in ten of the possible twelve self-reported measurement areas. Greatest magnitude of improvement occurred in the area of counselling (student confidence p<0.0001). Student confidence in all domains (questioning, counselling, referral and product provision) showed a marked increase. Student performance in the quiz also improved, demonstrating a 10% improvement overall for pharmacology knowledge and clinical practice following the simulation. Overall, 85% of students reported the simulation to be engaging and 93% of students felt the virtual patient simulation enhanced learning. The data suggests that the interactive virtual patient simulation developed for clinical pharmacology and therapeutics education enhanced students knowledge, skill and confidence, with respect to the competency domains of questioning, counselling, referral and product provision. These self-reported measures appear to translate to learning outcomes, as demonstrated by the improved student performance in the quiz assessment item. Future research of education using virtual simulation should seek to incorporate modern quantitative measures of student learning and engagement, such as eye tracking.

Keywords: clinical simulation, education, pharmacology, simulation, virtual learning

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Authors: Ljubica Milanović Glavan

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Because of the increasing business pressures, companies must be adaptable and flexible in order to withstand them. Inadequate business processes and low level of business process orientation, that in its core accentuates business processes as opposed to business functions and focuses on process performance and customer satisfaction, hider the ability to adapt to changing environment. It has been shown in previous studies that the companies which have reached higher business process maturity level consistently outperform those that have not reached them. The aim of this paper is to provide a basic understanding of business process orientation concept and business process maturity model. Besides that the paper presents the state of business process orientation in Croatia that has been captured with a study conducted in 2013. Based on the results some practical implications and guidelines for managers are given.

Keywords: business process orientation, business process maturity, Croatia, maturity score

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Authors: Nisar Ahmad, Xuyi, Ali Akbar

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As healthcare systems worldwide strive for improvement, the integration of advanced health information systems (HIS) has emerged as a pivotal strategy. This study aims to investigate the critical role of leadership in the implementation and enhancement of HIS in Chinese hospitals and how such leadership can drive improvements in patient outcomes and overall healthcare satisfaction. We propose a comprehensive study to be conducted across various hospitals in China, targeting healthcare professionals as the primary population. The research will leverage established theories of transformational leadership and technology acceptance to underpin the analysis. In our approach, data will be meticulously gathered through surveys and interviews, focusing on the experiences and perceptions of healthcare professionals regarding HIS implementation and its impact on patient care. The study will utilize SPSS and SmartPLS software for robust data analysis, ensuring precise and comprehensive insights into the correlation between leadership effectiveness and HIS success. We hypothesize that strong, visionary leadership is essential for the successful adoption and optimization of HIS, leading to enhanced patient outcomes and increased satisfaction with healthcare services. By applying advanced statistical methods, we aim to identify key leadership traits and practices that significantly contribute to these improvements. Our research will provide actionable insights for policymakers and healthcare administrators in China, offering evidence-based recommendations to foster leadership that champions HIS and drives continuous improvement in healthcare delivery. This study will contribute to the global discourse on health information systems, emphasizing the future role of leadership in transforming healthcare environments and outcomes.

Keywords: health information systems, leadership, patient outcomes, healthcare satisfaction

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Authors: Dhyaalddin Bahaalddin Noori Zangana

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This study involves the behavior of reinforced sand under a square footing. A series of bearing capacity tests were performed on a small-scale laboratory model, which filled with a poorly-graded homogenous bed of sand, which was placed in a medium dense state using sand raining technique. The sand was reinforced with 40 mm wide household aluminum foil strips. The main studied parameters was to consider the effect of reinforcing strip length, with various linear density of reinforcement, number of reinforcement layers and depth of top layer of reinforcement below the footing, on load-settlement behavior, bearing capacity ratio and settlement reduction factor. The relation of load-settlement generally showed similar trend in all the tests. Failure was defined as settlement equal to 10% of the footing width. The recommended optimum reinforcing strip length, linear density of reinforcement, number of reinforcement layers and depth of top layer of reinforcing strips that give the maximum bearing capacity improvement and minimum settlement reduction factor were presented and discussed. Different bearing capacity ration versus length of the reinforcing strips and settlement reduction factor versus length of the reinforcing strips relations at failure were showed improvement of bearing capacity ratio by a factor of 3.82 and reduction of settlement reduction factor by a factor of 0.813. The optimum length of reinforcement was found to be 7.5 times the footing width.

Keywords: square footing, relative density, linear density of reinforcement, bearing capacity ratio, load-settlement behaviour

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Authors: Ricardo Chaves, Carlos Vasconcelos

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Candidates to join the Naval Academy have to take a set of physical tests, which is crucial for a high level of physical fitness. Thus, the planning of physical exercises for candidates to the Naval School must take into account the improvement of their physical fitness. The aim of this study was to investigate the impact of a 6-month exercise program to improve the physical fitness of an individual who will apply for the Naval Academy. This was a non-experimental pre-post-evaluation study. The patient was male, had 18 years old, and a body mass index of 21.1 kg.m². The patient participated in a 6-month aerobic and strength exercise program (3 sessions per week, 75 minutes duration each session). Physical fitness tests were performed according to the physical fitness requirements for entry into the Naval academy (muscle strength [maximum number of lifts and maximum number of sit-ups for 1 minute]; aerobic fitness [2.4 km run and 200 m swimming test]) before (baseline) and after the exercise intervention (6 months). Regarding muscle strength, in the abdominal test, the improvements between the pre-test (39 abdominals.) and post-test (61 abdominals) were 56.4%. For elevations, there was an increase in its number by 150% between the pre-test (4 elevations) and post-test (10 elevations). With regard to aerobic fitness, in the 2.4 km race, there was an evolution of 32.0% between the pre-test (16.46 min.) and the post-test (12.42 min.). For the 200-meter swimming test, there was a negative variation of 2% between the pre-test (2.25 min.) and post-test (2.28 min). A 6-month aerobic and strength exercise program leads to a positive evolution in the muscular strength of the patient. Regarding aerobic fitness, opposite results were found, with a positive evolution in the 2.4 km running test and a negative evolution in the swimming test. In future exercise programs for the improvement of the physical fitness of candidates for the Naval Academy, more emphasis has to be done on specific swimming training.

Keywords: case study, exercise program, Naval Academy, physical fitness

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Authors: Jingjue Bao, Ye Li, Yujie Qi

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The explosive growth of ride-hailing has reshaped residents' travel behavior and plays a crucial role in urban mobility within the built environment. Contributing to the research of the spatial variation of ride-hailing demand and its relationship to the built environment and socioeconomic factors, this study utilizes multi-source data from Haikou, China, to construct a Multi-scale Geographically Weighted Regression model (MGWR), considering spatial scale heterogeneity. The regression results showed that MGWR model was demonstrated superior interpretability and reliability with an improvement of 3.4% on R2 and from 4853 to 4787 on AIC, compared with Geographically Weighted Regression model (GWR). Furthermore, to precisely identify the surrounding environment of sampling point, DeepLabv3+ model is employed to segment street-level images. Features extracted from these images are incorporated as variables in the regression model, further enhancing its rationality and accuracy by 7.78% improvement on R2 compared with the MGWR model only considered region-level variables. By integrating multi-scale geospatial data and utilizing advanced computer vision techniques, this study provides a comprehensive understanding of the spatial dynamics between ride-hailing demand and the urban built environment. The insights gained from this research are expected to contribute significantly to urban transportation planning and policy making, as well as ride-hailing platforms, facilitating the development of more efficient and effective mobility solutions in modern cities.

Keywords: travel behavior, ride-hailing, spatial relationship, built environment, street-level image

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Authors: Omar Alsetoohy, Mohamed Ezzat, Mahmoud Abou Kamar

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The success of a restaurant or hotel depends very much on the quality and quantity of its human resources. Thus, establishing a competitive edge through human assets requires careful attention to the practices that best leverage these assets. Usually, hotel or restaurant employees recognize customer defection as an unfavorable or unpleasant occurrence associated with failure. These failures could be in handling, communication, learning, or encouragement. Besides, employees could be afraid of blame from their colleagues and managers, which prevents them from freely discussing these mistakes with them. Such behaviors, in turn, would push employees to withdraw from the workplace. However, we have a good knowledge of the leadership outcomes, but less is known about how and why these effects occur. Accordingly, mindful leaders usually analyze the causes and underlying mechanisms of failures for work improvement. However, despite the excessive literature in the field of leadership and employee behaviors, to date, no research studies had investigated the impact of a failure-tolerant restaurant culture on the employees’ withdrawal behaviors considering the moderating role of psychological empowerment and mindful leadership. Thus, this study seeks to investigate the impact of a failure-tolerant culture on the employees’ withdrawal behaviors in fast-food restaurants in Egypt considering the moderating effects of employee empowerment and mindful leaders. This study may contribute to the existing literature by filling the gap between failure-tolerant cultures and employee withdrawal behaviors in the hospitality literature. The study may also identify the best practices for restaurant operators and managers to deal with employees' failures as an improvement tool for their performance.

Keywords: failure-tolerant culture, employees’ withdrawal behaviors psychological empowerment, mindful leadership, restaurants

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Authors: Hieu Nguyen

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Performance management is the concern of any organizations in the context of increasing demand and fierce competition between education institution. This paper draws together the performance management concepts and focuses specifically to Balance Scorecard in the context of education. The study employs semi-structured in-depth interview to explore the measurement items for each of the sub-objectives in the four perspectives. Each of the perspectives’ explored measurement items will then be discussed the role and influence of them towards the perspective and how to improve the measurements to have improved performance management. Finally, the measurements will be put together as a suggested balanced scorecard framework in the case of International University.

Keywords: performance management, education institution, balance scorecard, measurement items, four perspectives, international univeristy

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Authors: Despoina Mouratidis, Katia Lida Kermanidis

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Machine translation (MT) is a very important task in Natural Language Processing (NLP). MT evaluation is crucial in MT development, as it constitutes the means to assess the success of an MT system, and also helps improve its performance. Several methods have been proposed for the evaluation of (MT) systems. Some of the most popular ones in automatic MT evaluation are score-based, such as the BLEU score, and others are based on lexical similarity or syntactic similarity between the MT outputs and the reference involving higher-level information like part of speech tagging (POS). This paper presents a language-independent machine learning framework for classifying pairwise translations. This framework uses vector representations of two machine-produced translations, one from a statistical machine translation model (SMT) and one from a neural machine translation model (NMT). The vector representations consist of automatically extracted word embeddings and string-like language-independent features. These vector representations used as an input to a multi-layer neural network (NN) that models the similarity between each MT output and the reference, as well as between the two MT outputs. To evaluate the proposed approach, a professional translation and a "ground-truth" annotation are used. The parallel corpora used are English-Greek (EN-GR) and English-Italian (EN-IT), in the educational domain and of informal genres (video lecture subtitles, course forum text, etc.) that are difficult to be reliably translated. They have tested three basic deep learning (DL) architectures to this schema: (i) fully-connected dense, (ii) Convolutional Neural Network (CNN), and (iii) Long Short-Term Memory (LSTM). Experiments show that all tested architectures achieved better results when compared against those of some of the well-known basic approaches, such as Random Forest (RF) and Support Vector Machine (SVM). Better accuracy results are obtained when LSTM layers are used in our schema. In terms of a balance between the results, better accuracy results are obtained when dense layers are used. The reason for this is that the model correctly classifies more sentences of the minority class (SMT). For a more integrated analysis of the accuracy results, a qualitative linguistic analysis is carried out. In this context, problems have been identified about some figures of speech, as the metaphors, or about certain linguistic phenomena, such as per etymology: paronyms. It is quite interesting to find out why all the classifiers led to worse accuracy results in Italian as compared to Greek, taking into account that the linguistic features employed are language independent.

Keywords: machine learning, machine translation evaluation, neural network architecture, pairwise classification

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Authors: Supatchalee Sirichokworrakit

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Fishbone of Nile tilapia (Tilapia nilotica), waste from the frozen Nile tilapia fillet factory, is one of calcium sources. In order to increase fish bone powder value, this study aimed to investigate the effect of tilapia bone flour (TBF) addition (5, 10, 15% by flour weight) on cooking quality, texture and sensory attributes of noodles. The results indicated that tensile strength, color value (a*) and water absorption of noodles significantly decreased (p≤0.05) as the levels of TBF increased from 0-15%. While cooking loss, cooking time and color values (L* and b*) of noodles significantly increased (p≤0.05). Sensory evaluation indicated that noodles with 5% TBF received the highest overall acceptability score.

Keywords: tilapia bone flour, noodles, cooking quality, calcium

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Authors: Panaya Sudta, Wanchalerm Patanacharoenwong, Prachya Bumrungkun

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As With the evolution of smart grids, ensuring the reliability and efficiency of electrical systems in smart cities has become crucial. This paper proposes a distinct approach that combines advanced machine learning techniques to accurately predict electrical failures and address voltage reliability issues. This approach aims to improve the accuracy and efficiency of reliability evaluations in smart cities. The aim of this research is to develop a comprehensive predictive model that accurately predicts electrical failures and voltage reliability in smart cities. This model integrates RFM analysis, K-means clustering, and LSTM networks to achieve this objective. The research utilizes RFM analysis, traditionally used in customer value assessment, to categorize and analyze electrical components based on their failure recency, frequency, and monetary impact. K-means clustering is employed to segment electrical components into distinct groups with similar characteristics and failure patterns. LSTM networks are used to capture the temporal dependencies and patterns in customer data. This integration of RFM, K-means, and LSTM results in a robust predictive tool for electrical failures and voltage reliability. The proposed model has been tested and validated on diverse electrical utility datasets. The results show a significant improvement in prediction accuracy and reliability compared to traditional methods, achieving an accuracy of 92.78% and an F1-score of 0.83. This research contributes to the proactive maintenance and optimization of electrical infrastructures in smart cities. It also enhances overall energy management and sustainability. The integration of advanced machine learning techniques in the predictive model demonstrates the potential for transforming the landscape of electrical system management within smart cities. The research utilizes diverse electrical utility datasets to develop and validate the predictive model. RFM analysis, K-means clustering, and LSTM networks are applied to these datasets to analyze and predict electrical failures and voltage reliability. The research addresses the question of how accurately electrical failures and voltage reliability can be predicted in smart cities. It also investigates the effectiveness of integrating RFM analysis, K-means clustering, and LSTM networks in achieving this goal. The proposed approach presents a distinct, efficient, and effective solution for predicting and mitigating electrical failures and voltage issues in smart cities. It significantly improves prediction accuracy and reliability compared to traditional methods. This advancement contributes to the proactive maintenance and optimization of electrical infrastructures, overall energy management, and sustainability in smart cities.

Keywords: electrical state prediction, smart grids, data-driven method, long short-term memory, RFM, k-means, machine learning

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Authors: Alan Ruiz-Padilla, Brando Villalobos-Villalobos, Yeniley Ruiz-Noa, Claudia Mendoza-Macías, Claudia Palafox-Sánchez, Miguel Marín-Rosales, Álvaro Cruz, Rubén Rangel-Salazar

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Introduction: In patients with rheumatoid arthritis, resistance or poor response to disease modifying antirheumatic drugs (DMARD) may be a reflection of the increase in g-P. The expression of g-P may be important in mediating the effluence of DMARD from the cell. In addition, P-glycoprotein is involved in the transport of cytokines, IL-1, IL-2 and IL-4, from normal lymphocytes activated to the surrounding extracellular matrix, thus influencing the activity of RA. The involvement of P-glycoprotein in the transmembrane transport of cytokines can serve as a modulator of the efficacy of DMARD. It was shown that a number of lymphocytes with glycoprotein P activity is increased in patients with RA; therefore, P-glycoprotein expression could be related to the activity of RA and could be a predictor of poor response to therapy. Objective: To evaluate in RA patients, if the G2677T/A MDR1 polymorphisms is associated with differences in the rate of therapeutic response to disease-modifying antirheumatic agents in patients with rheumatoid arthritis. Material and Methods: A prospective cohort study was conducted. Fifty seven patients with RA were included. They had an active disease according to DAS-28 (score >3.2). We excluded patients receiving biological agents. All the patients were followed during 6 months in order to identify the rate of therapeutic response according to the American College of Rheumatology (ACR) criteria. At the baseline peripheral blood samples were taken in order to identify the G2677T/A MDR1 polymorphisms using PCR- Specific allele. The fragment was identified by electrophoresis in polyacrylamide gels stained with ethidium bromide. For statistical analysis, the genotypic and allelic frequencies of MDR1 gene polymorphism between responders and non-responders were determined. Chi-square tests as well as, relative risks with 95% confidence intervals (95%CI) were computed to identify differences in the risk for achieving therapeutic response. Results: RA patients had a mean age of 47.33 ± 12.52 years, 87.7% were women with a mean for DAS-28 score of 6.45 ± 1.12. At the 6 months, the rate of therapeutic response was 68.7 %. The observed genotype frequencies were: for G/G 40%, T/T 32%, A/A 19%, G/T 7% and for A/A genotype 2%. Patients with G allele developed at 6 months of treatment, higher rate for therapeutic response assessed by ACR20 compared to patients with others alleles (p=0.039). Conclusions: Patients with G allele of the - G2677T/A MDR1 polymorphisms had a higher rate of therapeutic response at 6 months with DMARD. These preliminary data support the requirement for a deep evaluation of these and other genotypes as factors that may influence the therapeutic response in RA.

Keywords: pharmacogenetics, MDR1, P-glycoprotein, therapeutic response, rheumatoid arthritis

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Authors: Cecile Laval, Harriet Lowe

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Processing Instruction is a psycholinguistic pedagogical approach drawing insights from the Input Processing Model which establishes the initial innate strategies used by second language learners to connect form and meaning of linguistic features. With the ever-growing use of technology in Second Language Acquisition research, the present study uses eye-tracking to measure the effectiveness of Processing Instruction in the acquisition of French and its effects on learner’s cognitive strategies. The experiment was designed using a TOBII Pro-TX300 eye-tracker to measure participants’ default strategies when processing French linguistic input and any cognitive changes after receiving Processing Instruction treatment. Participants were drawn from lower intermediate adult learners of French at the University of Greenwich and randomly assigned to two groups. The study used a pre-test/post-test methodology. The pre-tests (one per linguistic item) were administered via the eye-tracker to both groups one week prior to instructional treatment. One group received full Processing Instruction treatment (explicit information on the grammatical item and on the processing strategies, and structured input activities) on the primary target linguistic feature (French past tense imperfective aspect). The second group received Processing Instruction treatment except the explicit information on the processing strategies. Three immediate post-tests on the three grammatical structures under investigation (French past tense imperfective aspect, French Subjunctive used for the expression of doubt, and the French causative construction with Faire) were administered with the eye-tracker. The eye-tracking data showed the positive change in learners’ processing of the French target features after instruction with improvement in the interpretation of the three linguistic features under investigation. 100% of participants in both groups made a statistically significant improvement (p=0.001) in the interpretation of the primary target feature (French past tense imperfective aspect) after treatment. 62.5% of participants made an improvement in the secondary target item (French Subjunctive used for the expression of doubt) and 37.5% of participants made an improvement in the cumulative target feature (French causative construction with Faire). Statistically there was no significant difference between the pre-test and post-test scores in the cumulative target feature; however, the variance approximately tripled between the pre-test and the post-test (3.9 pre-test and 9.6 post-test). This suggests that the treatment does not affect participants homogenously and implies a role for individual differences in the transfer-of-training effect of Processing Instruction. The use of eye-tracking provides an opportunity for the study of unconscious processing decisions made during moment-by-moment comprehension. The visual data from the eye-tracking demonstrates changes in participants’ processing strategies. Gaze plots from pre- and post-tests display participants fixation points changing from focusing on content words to focusing on the verb ending. This change in processing strategies can be clearly seen in the interpretation of sentences in both primary and secondary target features. This paper will present the research methodology, design and results of the experimental study using eye-tracking to investigate the primary effects and transfer-of-training effects of Processing Instruction. It will then provide evidence of the cognitive benefits of Processing Instruction in Second Language Acquisition and offer suggestion in second language teaching of grammar.

Keywords: eye-tracking, language teaching, processing instruction, second language acquisition

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Authors: Ricardo Avila, Gabriel Lopes, Vania Vidal, Jose Macedo

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This proposal aims for semantic enrichment between glossaries using the Simple Knowledge Organization System (SKOS) vocabulary to discover synonyms, hyponyms and hyperonyms semiautomatically, in Brazilian Portuguese, generating new semantic relationships based on WordNet. To evaluate the quality of this proposed model, experiments were performed by the use of two sets containing new relations, being one generated automatically and the other manually mapped by the domain expert. The applied evaluation metrics were precision, recall, f-score, and confidence interval. The results obtained demonstrate that the applied method in the field of Oil Production and Extraction (E&P) is effective, which suggests that it can be used to improve the quality of terminological mappings. The procedure, although adding complexity in its elaboration, can be reproduced in others domains.

Keywords: ontology matching, mapping enrichment, semantic web, linked data, SKOS

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Authors: Pricillia Priska Sianita

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An aesthetic facial profile is one of the goals in Orthodontics treatment. However, this is not easily achieved, especially in patients with Class II Division 1 malocclusion who have the clinical characteristics of convex profile and significant skeletal discrepancy due to mandibular growth deficiency. Malocclusion with skeletal problems require proper treatment timing for growth stimulation, and it must be done in early age and in need of good cooperation from the patient. If this is not done and the patient has passed the growth period, the ideal treatment is orthognathic surgery which is more complicated and more painful. The growth stimulation of skeletal malocclusion requires a careful cephalometric evaluation ranging from diagnosis to determine the parts that require stimulation to post-treatment evaluation to see the success achieved through changes in the measurement of the skeletal parameters shown in the cephalometric analysis. This case report aims to describe skeletal changes cephalometrically that were achieved through orthodontic treatment in growing period. Material and method: Lateral Cephalograms, pre-treatment, and post-treatment of cases of Class II Division 1 malocclusion is selected from a collection of cephalometric radiographic in a private clinic. The Cephalogram is then traced and measured for the skeletal parameters. The result is noted as skeletal condition data of pre-treatment and post-treatment. Furthermore, superimposition is done to see the changes achieved. The results show that growth stimulation through orthodontic treatment can solve the skeletal problem of Class II Division 1 malocclusion and the skeletal changes that occur can be verified through cephalometric analysis. The skeletal changes have an impact on the improvement of patient's facial profile. To sum up, the treatment timing on a skeletal malocclusion is very important to obtain satisfactory results for the improvement of the aesthetic facial profile, and skeletal changes can be verified through cephalometric evaluation of pre- and post-treatment.

Keywords: cephalometric evaluation, class II division 1 malocclusion, growth stimulation, skeletal changes, skeletal problems

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Authors: Temitope O. Tokosi, Visvanathan Naicker

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Patient health records contain sensitive information for which an electronic patient record (EPR) system can safely secure and transmit amongst clinicians for use in improving health delivery. Clinician’s use of the behaviour of these systems is under scrutiny to assess their attributes towards health technology. South Africa (SA) clinicians responded to a pilot study survey to assess their understanding of EPR, what attributes are important towards technology use and more importantly streamlining the survey for a larger study. Descriptive statistics using mean scores was used because of the small sample size of 11 clinicians who completed the survey. Nine (9) constructs comprising 62 items were used and a Cronbach alpha score of 0.883 was obtained. Limitations and discussions conclude the study.

Keywords: EPR, clinicians, pilot study, South Africa

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Authors: Stephen McCarthy, Joanne Gray, Esther Carr, Gerard Danjoux, Paul Baker, Rhiannon Hackett

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Background: The Go Well Health (GWH) platform is a web-based programme that allows patients to access personalised care plans and resources, aimed at prehabilitation prior to surgery. The online digital platform delivers essential patient education and support for patients prior to undergoing total hip replacements (THR) and total knee replacements (TKR). This study evaluated the impact of an online digital platform (ODP) in terms of functional health outcomes, health related quality of life and hospital length of stay following surgery. Methods: A retrospective cohort study comparing a cohort of patients who used the online digital platform (ODP) to deliver patient education and support (PES) prior to undergoing THR and TKR surgery relative to a cohort of patients who did not access the ODP and received usual care. Routinely collected Patient Reported Outcome Measures (PROMs) data was obtained on 2,406 patients who underwent a knee replacement (n=1,160) or a hip replacement (n=1,246) between 2018 and 2019 in a single surgical centre in the United Kingdom. The Oxford Hip and Knee Score and the European Quality of Life Five-Dimensional tool (EQ5D-5L) was obtained both pre-and post-surgery (at 6 months) along with hospital LOS. Linear regression was used to compare the estimate the impact of GWH on both health outcomes and negative binomial regressions were used to impact on LOS. All analyses adjusted for age, sex, Charlson Comorbidity Score and either pre-operative Oxford Hip/Knee scores or pre-operative EQ-5D scores. Fractional polynomials were used to represent potential non-linear relationships between the factors included in the regression model. Findings: For patients who underwent a knee replacement, GWH had a statistically significant impact on Oxford Knee Scores and EQ5D-5L utility post-surgery (p=0.039 and p=0.002 respectively). GWH did not have a statistically significant impact on the hospital length of stay. For those patients who underwent a hip replacement, GWH had a statistically significant impact on Oxford Hip Scores and EQ5D-5L utility post (p=0.000 and p=0.009 respectively). GWH also had a statistically significant reduction in the hospital length of stay (p=0.000). Conclusion: Health Outcomes were higher for patients who used the GWH platform and underwent THR and TKR relative to those who received usual care prior to surgery. Patients who underwent a hip replacement and used GWH also had a reduced hospital LOS. These findings are important for health policy and or decision makers as they suggest that prehabilitation via an ODP can maximise health outcomes for patients following surgery whilst potentially making efficiency savings with reductions in LOS.

Keywords: digital prehabilitation, online digital platform, orthopaedics, surgery

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Authors: Pei Yi Lin

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Objective: The objective of this study is to use machine learning methods to build an early prediction classifier model for acute delirium to improve the quality of medical care for intensive care patients. Background: Delirium is a common acute and sudden disturbance of consciousness in critically ill patients. After the occurrence, it is easy to prolong the length of hospital stay and increase medical costs and mortality. In 2021, the incidence of delirium in the intensive care unit of internal medicine was as high as 59.78%, which indirectly prolonged the average length of hospital stay by 8.28 days, and the mortality rate is about 2.22% in the past three years. Therefore, it is expected to build a delirium prediction classifier through big data analysis and machine learning methods to detect delirium early. Method: This study is a retrospective study, using the artificial intelligence big data database to extract the characteristic factors related to delirium in intensive care unit patients and let the machine learn. The study included patients aged over 20 years old who were admitted to the intensive care unit between May 1, 2022, and December 31, 2022, excluding GCS assessment <4 points, admission to ICU for less than 24 hours, and CAM-ICU evaluation. The CAMICU delirium assessment results every 8 hours within 30 days of hospitalization are regarded as an event, and the cumulative data from ICU admission to the prediction time point are extracted to predict the possibility of delirium occurring in the next 8 hours, and collect a total of 63,754 research case data, extract 12 feature selections to train the model, including age, sex, average ICU stay hours, visual and auditory abnormalities, RASS assessment score, APACHE-II Score score, number of invasive catheters indwelling, restraint and sedative and hypnotic drugs. Through feature data cleaning, processing and KNN interpolation method supplementation, a total of 54595 research case events were extracted to provide machine learning model analysis, using the research events from May 01 to November 30, 2022, as the model training data, 80% of which is the training set for model training, and 20% for the internal verification of the verification set, and then from December 01 to December 2022 The CU research event on the 31st is an external verification set data, and finally the model inference and performance evaluation are performed, and then the model has trained again by adjusting the model parameters. Results: In this study, XG Boost, Random Forest, Logistic Regression, and Decision Tree were used to analyze and compare four machine learning models. The average accuracy rate of internal verification was highest in Random Forest (AUC=0.86), and the average accuracy rate of external verification was in Random Forest and XG Boost was the highest, AUC was 0.86, and the average accuracy of cross-validation was the highest in Random Forest (ACC=0.77). Conclusion: Clinically, medical staff usually conduct CAM-ICU assessments at the bedside of critically ill patients in clinical practice, but there is a lack of machine learning classification methods to assist ICU patients in real-time assessment, resulting in the inability to provide more objective and continuous monitoring data to assist Clinical staff can more accurately identify and predict the occurrence of delirium in patients. It is hoped that the development and construction of predictive models through machine learning can predict delirium early and immediately, make clinical decisions at the best time, and cooperate with PADIS delirium care measures to provide individualized non-drug interventional care measures to maintain patient safety, and then Improve the quality of care.

Keywords: critically ill patients, machine learning methods, delirium prediction, classifier model

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Authors: Thi Huong Vu, Vijay Jayasena, Zhongxiang Fang, Gary Dykes

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Carob kibble has recently received attention due to the presence of high level of polyphenol antioxidants. The capacity of microorganisms to improve antioxidant activities and total phenolics in carob kibble was investigated in the study. Two types of microorganisms including lactic acid bacteria Lactobacillus plantarum (L. plantarum) and yeast Saccharomyces cerevisiae (S. cerevisiae) were used in single and in their combination as starters. The total phenolic content was determined by the Folin–Ciocalteu method. Antioxidant activities were assessed scavenging capacity using 2,2-diphenyl-1-picrylhydrazyl (DPPH) and 2,2′-azinobis-(3-ethylbenzothiazoline-6-sulfonic acid (ABTS). The study found that S. cerevisiae alone considerably improved 55% total phenolics content at 15 h, while L. plantarum caused in a loss of 20% through the process. Antioxidant capacity of the yeast-fermented samples significantly increased by 43 % and 10 % in ABTS and DPPH assays, respectively. However, reduction of 13 % and 32 % inhibition were recorded in the carob treated with L. plantarum. In the combination of S. cerevisiae and L. plantarum (1:1), both total phenolic content and antioxidant activity of carob kibble were a similar trend as these of S. cerevisiae single, but a lower improvement. The antioxidant power of the extracts was linearly correlated to their total phenolic contents (R=0.75). The results suggested that S. cerevisiae alone was the better for enhancement of both total phenolic content and antioxidant activity in carob kibble using submerged fermentation. The efficiency of fermentation reached the highest at 15h. Thus submerged fermentation with S. cerevisiae offers a tool with simple and cost effective to further increase the bioactive potential of carob kibble, which is in use for food, cosmetic and pharmaceutical industries.

Keywords: antioxidant activity, carob kibble, lactobacillus plantarum, saccharomyces cerevisiae, total phenolics

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Authors: F. Ruiz-Navarro, M. Matzner, G. Kobinia

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Background: Cerebral palsy (CP) encompasses the largest group of childhood movement disorders, the patterns and severity varies widely. Today, the management focuses only on a rehabilitation therapy that tries to secure the functions remained and prevents complications. However the treatments are not aimed to cure the disease. Stem cells (SCs) transplant via intrathecal is a new approach to the disease. Method: Our aim was to performed a pilot study under the condition of unproven treatment on clinical practice to assessed the safety and efficacy of Neuron Point-of-care Stem cell Therapy (N-POCST), an ambulatory procedure of autologous bone marrow derived SCs (BM-SCs) harvested from the posterior superior iliac crest undergo an on-site cell separation for intrathecal infusion via lumbar puncture. Results: 82 patients were treated in a period of 28 months, with a follow-up after 6 months. They had a mean age of 6,2 years old and male predominance (65,9%). Our preliminary results show that: A. No patient had any major side effects, B. Only 20% presented mild headache due to LP, C. 53% of the patients had an improvement in spasticity, D. 61% improved the coordination abilities, 23% improved the motor function, 15% improved the speech, 23% reduced the number of convulsive events with the same doses or less doses of anti-convulsive medication and 94% of the patients report a subjective general improvement. Conclusions: These results support previous worldwide publications that described the safety and effectiveness of autologous BM-SCs transplant for patients wit CP.

Keywords: autologous transplant, cerebral palsy, point of care, childhood movement disorders

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Authors: Pellecchia M. T., Savarese G., Carpinelli L., Calabrese M.

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Introduction: Parkinson's disease (PD) is characterized by a progressive loss of autonomy which undoubtedly has a significant impact on the quality of life of caregivers, and parents are the main informal caregivers. Caring for a person with PD is associated with an increased risk of psychiatric morbidity and persistent anxiety-depressive distress. The aim of the study is to investigate the burden on caregivers of patients with PD, through the use of multidimensional scales and to identify their personological and environmental determinants. Methods: The study has been approved by the Ethic Committee of the University of Salerno and informed consent for participation to the study was obtained from patients and their caregivers. The study was conducted at the Neurology Department of the A.O.U. "San Giovanni di Dio and Ruggi D’Aragona" of Salerno between September 2020 and May 2021. Materials: The questionnaires used were: a) Caregiver Burden Inventory - CBI a questionnaire of 24 items that allow identifying five sub-categories of burden (objective, psychological, physical, social, emotional); b) Depression Anxiety Stress Scales Short Version - DASS-21 questionnaire consisting of 21 items and valid in examining three distinct but interrelated areas (depression, anxiety and stress); c) Family Strain Questionnaire Short Form - FSQ-SF is a questionnaire of 30 items grouped in areas of increasing psychological risk (OK, R, SR, U); d) Zarit Caregiver Burden Inventory - ZBI, consisting of 22 items based on the analysis of two main factors: personal stress and pressure related to his role; e) Life Satisfaction, a single item that aims to evaluate the degree of life satisfaction in a global way using a 0-100 Likert scale. Findings: N ° 29 caregivers (M age = 55.14, SD = 9.859; 69% F) participated in the study. 20.6% of the sample had severe and severe burden (CBI score = M = 26.31; SD = 22.43) and 13.8% of participants had moderate to severe burden (ZBI). The FSQ-SF highlighted a minority of caregivers who need psychological support, in some cases urgent (Area SR and Area U). The DASS-21 results show a prevalence of stress-related symptoms (M = 10.90, SD = 10.712) compared to anxiety (M = 7.52, SD = 10.752) and depression (M = 8, SD = 10.876). There are significant correlations between some specific variables and mean test scores: retired caregivers report higher ZBI scores (p = 0.423) and lower Life Satisfaction levels (p = -0.460) than working caregivers; years of schooling show a negative linear correlation with the ZBI score (p = -0.491). The T-Test indicates that caregivers of patients with cognitive impairment are at greater risk than those of patients without cognitive impairment. Conclusions: It knows the factors that affect the burden the most would allow for early recognition of risky situations and caregivers who would need adequate support.

Keywords: anxious-depressive axis, caregivers’ burden, Parkinson’ disease, psychological risks

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Authors: Esha Thakkar, Ina Liu, Kalynn Hosea, Shana Katz, Katie Marks, Sarah Hall, Cat Liu, Suzanne Harris

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Purpose: Inequities in mental healthcare accessibility are cited as an international public health concern by the World Health Organization (WHO) and National Alliance on Mental Illness (NAMI). These disparities are further exacerbated in racial and ethnic minority groups and are especially concerning in health professional training settings such as Doctor of Pharmacy (PharmD) programs and postgraduate residency training where mental illness rates are high. The purpose of the study was to determine baseline access to culturally sensitive mental healthcare and how to improve such access and communication for racially and ethnically minoritized pharmacy students and residents at one school of pharmacy and a partnering academic medical center in the United States. Methods: This IRB-exempt study included 60-minute focus groups conducted in person or online from November 2021 to February 2022. Eligible participants included PharmD students in their first (P1), second (P2), third (P3), or fourth year (P4) or pharmacy residents completing a postgraduate year 1 (PGY1) or PGY2 who identify as Black, Indigenous, or Person of Color (BIPOC). There were four core theme questions asked during the focus groups to lead the discussion, specifically on the core themes of personal barriers, identities, areas that are working well, and areas for improvement. Participant responses were transcribed and analyzed using an open coding system with two individual reviews, followed by collaborative and intentional discussion and, as needed, an external audit of the coding by a third research team member to reach a consensus on themes. Results: This study enrolled 26 participants, with eight P1, five P2, seven P3, two P4, and four resident participants. Within the four core themes of barriers, identities, areas working well, and areas for improvement, emerging subthemes included: lack of time, access to resources, and stigma under barriers; lack of representation, cultural and family stigma, and gender identities for identity barriers; supportive faculty, sense of community and culture supporting paid time off for areas going well; and wellness days, reduced workload and diversity of the workforce in areas of improvement. Subthemes sometimes varied within a core theme depending on the participant year. Conclusions: There is a gap in the literature in addressing barriers and disparities in mental health access for pharmacy trainees who identify as BIPOC. We identified key findings in regards to barriers, identities, areas going well and areas for improvement that can inform the School and the Residency Program in two priority initiatives of well-being and diversity equity and inclusion in creating actionable recommendations for trainees, program directors, and employers of our institutions, and also has the potential to provide insight for other organizations about the structures influencing access to culturally sensitive care in BIPOC trainees. These findings can inform organizations on how to continue building on communication with those who identify as BIPOC and improve access to care.

Keywords: mental health, disparities, minorities, wellbeing, identity, communication, barriers

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Authors: Parisa Mansour

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Introduction: Early diagnosis of coronavirus disease (COVID-19) is extremely important to isolate and treat patients in time, thus preventing the spread of the disease, improving prognosis and reducing mortality. High-resolution computed tomography (HRCT) chest imaging and artificial intelligence (AI)-based analysis of HRCT chest images can play a central role in the treatment of patients with COVID-19. Objective: To investigate different chest HRCT findings in different stages of COVID-19 pneumonia and to evaluate the potential role of artificial intelligence in the quantitative assessment of lung parenchymal involvement in COVID-19 pneumonia. Materials and Methods: This retrospective observational study was conducted between May 1, 2020 and August 13, 2020. The study included 2169 patients with COVID-19 who underwent chest HRCT. HRCT images showed the presence and distribution of lesions such as: ground glass opacity (GGO), compaction, and any special patterns such as septal thickening, inverted halo, mark, etc. HRCT findings of the breast at different stages of the disease (early: andlt) 5 days, intermediate: 6-10 days and late stage: >10 days). A CT severity score (CTSS) was calculated based on the extent of lung involvement on HRCT, which was then correlated with clinical disease severity. Use of artificial intelligence; Analysis of CT pneumonia and quot; An algorithm was used to quantify the extent of pulmonary involvement by calculating the percentage of pulmonary opacity (PO) and gross opacity (PHO). Depending on the type of variables, statistically significant tests such as chi-square, analysis of variance (ANOVA) and post hoc tests were applied when appropriate. Results: Radiological findings were observed in HRCT chest in 1438 patients. A typical pattern of COVID-19 pneumonia, i.e., bilateral peripheral GGO with or without consolidation, was observed in 846 patients. About 294 asymptomatic patients were radiologically positive. Chest HRCT in the early stages of the disease mostly showed GGO. The late stage was indicated by such features as retinal enlargement, thickening and the presence of fibrous bands. Approximately 91.3% of cases with a CTSS = 7 were asymptomatic or clinically mild, while 81.2% of cases with a score = 15 were clinically severe. Mean PO and PHO (30.1 ± 28.0 and 8.4 ± 10.4, respectively) were significantly higher in the clinically severe categories. Conclusion: Because COVID-19 pneumonia progresses rapidly, radiologists and physicians should become familiar with typical TC chest findings to treat patients early, ultimately improving prognosis and reducing mortality. Artificial intelligence can be a valuable tool in treating patients with COVID-19.

Keywords: chest, HRCT, covid-19, artificial intelligence, chest HRCT

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Authors: Angela U. Makolo

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Protein-coding and Non-coding regions determine the biology of a sequenced transcriptome. Research advances have shown that Non-coding regions are important in disease progression and clinical diagnosis. Existing bioinformatics tools have been targeted towards Protein-coding regions alone. Therefore, there are challenges associated with gaining biological insights from transcriptome sequence data. These tools are also limited to computationally intensive sequence alignment, which is inadequate and less accurate to identify both Protein-coding and Non-coding regions. Alignment-free techniques can overcome the limitation of identifying both regions. Therefore, this study was designed to develop an efficient sequence alignment-free model for identifying both Protein-coding and Non-coding regions in sequenced transcriptomes. Feature grouping and randomization procedures were applied to the input transcriptomes (37,503 data points). Successive iterations were carried out to compute the gradient vector that converged the developed Protein-coding and Non-coding Region Identifier (PNRI) model to the approximate coefficient vector. The logistic regression algorithm was used with a sigmoid activation function. A parameter vector was estimated for every sample in 37,503 data points in a bid to reduce the generalization error and cost. Maximum Likelihood Estimation (MLE) was used for parameter estimation by taking the log-likelihood of six features and combining them into a summation function. Dynamic thresholding was used to classify the Protein-coding and Non-coding regions, and the Receiver Operating Characteristic (ROC) curve was determined. The generalization performance of PNRI was determined in terms of F1 score, accuracy, sensitivity, and specificity. The average generalization performance of PNRI was determined using a benchmark of multi-species organisms. The generalization error for identifying Protein-coding and Non-coding regions decreased from 0.514 to 0.508 and to 0.378, respectively, after three iterations. The cost (difference between the predicted and the actual outcome) also decreased from 1.446 to 0.842 and to 0.718, respectively, for the first, second and third iterations. The iterations terminated at the 390th epoch, having an error of 0.036 and a cost of 0.316. The computed elements of the parameter vector that maximized the objective function were 0.043, 0.519, 0.715, 0.878, 1.157, and 2.575. The PNRI gave an ROC of 0.97, indicating an improved predictive ability. The PNRI identified both Protein-coding and Non-coding regions with an F1 score of 0.970, accuracy (0.969), sensitivity (0.966), and specificity of 0.973. Using 13 non-human multi-species model organisms, the average generalization performance of the traditional method was 74.4%, while that of the developed model was 85.2%, thereby making the developed model better in the identification of Protein-coding and Non-coding regions in transcriptomes. The developed Protein-coding and Non-coding region identifier model efficiently identified the Protein-coding and Non-coding transcriptomic regions. It could be used in genome annotation and in the analysis of transcriptomes.

Keywords: sequence alignment-free model, dynamic thresholding classification, input randomization, genome annotation

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