Search results for: manual attendance

Authors: K. Mokatse, O. M. Barei, K. Gabanakgosi, P. Matlhabaphiri

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The mining of pit slopes is often associated with some level of deviation from design recommendations, and this may translate to associated changes in the stability of the excavated pit slopes. Therefore slope angle design reconciliations are essential for assessing and monitoring compliance of excavated pit slopes to accepted slope designs. These associated changes in slope stability may be reflected by changes in the calculated factors of safety and/or probabilities of failure. Reconciliations of as-mined and slope design profiles are conducted periodically to assess the implications of these deviations on pit slope stability. Currently, the slope design reconciliation process being implemented in Jwaneng Mine involves the measurement of as-mined and design slope angles along vertical sections cut along the established geotechnical design section lines on the GEOVIA GEMS™ software. Bench retentions are calculated as a percentage of the available catchment area, less over-mined and under-mined areas, to that of the designed catchment area. This process has proven to be both tedious and requires a lot of manual effort and time to execute. Consequently, a new semi-automated mine-to-design reconciliation approach that utilizes laser scanning and GIS-based tools is being proposed at Jwaneng Mine. This method involves high-resolution scanning of targeted bench walls, subsequent creation of 3D surfaces from point cloud data and the derivation of slope toe lines and crest lines on the Maptek I-Site Studio software. The toe lines and crest lines are then exported to the ArcGIS software where distance offsets between the design and actual bench toe lines and crest lines are calculated. Retained bench catchment capacity is measured as distances between the toe lines and crest lines on the same bench elevations. The assessment of the performance of the inter-ramp and overall slopes entails the measurement of excavated and design slope angles along vertical sections on the ArcGIS software. Excavated and design toe-to-toe or crest-to-crest slope angles are measured for inter-ramp stack slope reconciliations. Crest-to-toe slope angles are also measured for overall slope angle design reconciliations. The proposed approach allows for a more automated, accurate, quick and easier workflow for carrying out slope angle design reconciliations. This process has proved highly effective and timeous in the assessment of slope performance in Jwaneng Mine. This paper presents a newly proposed process for assessing compliance to slope angle designs for Jwaneng Mine.

Keywords: slope angle designs, slope design recommendations, slope performance, slope stability

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Authors: Zheng Yuxun

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This review critically assesses the advancements and prospective developments in defect detection methodologies within the semiconductor industry, an essential domain that significantly affects the operational efficiency and reliability of electronic components. As semiconductor devices continue to decrease in size and increase in complexity, the precision and efficacy of defect detection strategies become increasingly critical. Tracing the evolution from traditional manual inspections to the adoption of advanced technologies employing automated vision systems, artificial intelligence (AI), and machine learning (ML), the paper highlights the significance of precise defect detection in semiconductor manufacturing by discussing various defect types, such as crystallographic errors, surface anomalies, and chemical impurities, which profoundly influence the functionality and durability of semiconductor devices, underscoring the necessity for their precise identification. The narrative transitions to the technological evolution in defect detection, depicting a shift from rudimentary methods like optical microscopy and basic electronic tests to more sophisticated techniques including electron microscopy, X-ray imaging, and infrared spectroscopy. The incorporation of AI and ML marks a pivotal advancement towards more adaptive, accurate, and expedited defect detection mechanisms. The paper addresses current challenges, particularly the constraints imposed by the diminutive scale of contemporary semiconductor devices, the elevated costs associated with advanced imaging technologies, and the demand for rapid processing that aligns with mass production standards. A critical gap is identified between the capabilities of existing technologies and the industry's requirements, especially concerning scalability and processing velocities. Future research directions are proposed to bridge these gaps, suggesting enhancements in the computational efficiency of AI algorithms, the development of novel materials to improve imaging contrast in defect detection, and the seamless integration of these systems into semiconductor production lines. By offering a synthesis of existing technologies and forecasting upcoming trends, this review aims to foster the dialogue and development of more effective defect detection methods, thereby facilitating the production of more dependable and robust semiconductor devices. This thorough analysis not only elucidates the current technological landscape but also paves the way for forthcoming innovations in semiconductor defect detection.

Keywords: semiconductor defect detection, artificial intelligence in semiconductor manufacturing, machine learning applications, technological evolution in defect analysis

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Authors: N. D'Amico, E. Grossi, B. Colombo, F. Rigiroli, M. Buscema, D. Fazzini, G. Cornalba, S. Papa

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Purpose: To characterize, through a radiomic approach, the nature of nodules considered non-specific by expert radiologists, recognized in magnetic resonance mammography (MRm) with T1-weighted (T1w) sequences with paramagnetic contrast. Material and Methods: 47 cases out of 1200 undergoing MRm, in which the MRm assessment gave uncertain classification (non-specific nodules), were admitted to the study. The clinical outcome of the non-specific nodules was later found through follow-up or further exams (biopsy), finding 35 benign and 12 malignant. All MR Images were acquired at 1.5T, a first basal T1w sequence and then four T1w acquisitions after the paramagnetic contrast injection. After a manual segmentation of the lesions, done by a radiologist, and the extraction of 150 radiomic features (30 features per 5 subsequent times) a machine learning (ML) approach was used. An evolutionary algorithm (TWIST system based on KNN algorithm) was used to subdivide the dataset into training and validation test and to select features yielding the maximal amount of information. After this pre-processing, different machine learning systems were applied to develop a predictive model based on a training-testing crossover procedure. 10 cases with a benign nodule (follow-up older than 5 years) and 18 with an evident malignant tumor (clear malignant histological exam) were added to the dataset in order to allow the ML system to better learn from data. Results: NaiveBayes algorithm working on 79 features selected by a TWIST system, resulted to be the best performing ML system with a sensitivity of 96% and a specificity of 78% and a global accuracy of 87% (average values of two training-testing procedures ab-ba). The results showed that in the subset of 47 non-specific nodules, the algorithm predicted the outcome of 45 nodules which an expert radiologist could not identify. Conclusion: In this pilot study we identified a radiomic approach allowing ML systems to perform well in the diagnosis of a non-specific nodule at MR mammography. This algorithm could be a great support for the early diagnosis of malignant breast tumor, in the event the radiologist is not able to identify the kind of lesion and reduces the necessity for long follow-up. Clinical Relevance: This machine learning algorithm could be essential to support the radiologist in early diagnosis of non-specific nodules, in order to avoid strenuous follow-up and painful biopsy for the patient.

Keywords: breast, machine learning, MRI, radiomics

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Authors: Manjinder Singh, Jasvinder Singh

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Existing theories of Titanic/Liberty ship, Sydney bridge accidents and practical experience generated an interest in developing weldments those has high toughness under sub-zero temperature conditions. The purpose was to protect the joint from undergoing DBT (Ductile to brittle transition), when ambient temperature reach sub-zero levels. Metallurgical improvement such as low carbonization or addition of deoxidization elements like Mn and Si was effective to prevent fracture in weldments (crack) at low temperature. In the present research, an attempt has been made to investigate the reason behind ductile to brittle transition of mild steel weldments when subjected to sub-zero temperatures and method of its mitigation. Nickel is added to weldments using manual metal arc welding (MMAW) preventing the DBT, but progressive reduction in charpy impact values as temperature is lowered. The variation in toughness with respect to nickel content being added to the weld pool is analyzed quantitatively to evaluate the rise in toughness value with increasing nickel amount. The impact performance of welded specimens was evaluated by Charpy V-notch impact tests at various temperatures (20 °C, 0 °C, -20 °C, -40 °C, -60 °C). Notch is made in the weldments, as notch sensitive failure is particularly likely to occur at zones of high stress concentration caused by a notch. Then the effect of nickel to weldments is investigated at various temperatures was studied by mechanical and metallurgical tests. It was noted that a large gain in impact toughness could be achieved by adding nickel content. The highest yield strength (462J) in combination with good impact toughness (over 220J at – 60 °C) was achieved with an alloying content of 16 wt. %nickel. Based on metallurgical behavior it was concluded that the weld metals solidify as austenite with increase in nickel. The microstructure was characterized using optical and high resolution SEM (scanning electron microscopy). At inter-dendritic regions mainly martensite was found. In dendrite core regions of the low carbon weld metals a mixture of upper bainite, lower bainite and a novel constituent coalesced bainite formed. Coalesced bainite was characterized by large bainitic ferrite grains with cementite precipitates and is believed to form when the bainite and martensite start temperatures are close to each other. Mechanical properties could be rationalized in terms of micro structural constituents as a function of nickel content.

Keywords: MMAW, Toughness, DBT, Notch, SEM, Coalesced bainite

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Authors: Kuniaki Kudo, Raviraj Solanki, Kaushal Patel, Yash Virani

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This research mainly concerns optimizing UI test automation for large-scale web applications. The test target application is the HHAexchange homecare management WEB application that seamlessly connects providers, state Medicaid programs, managed care organizations (MCOs), and caregivers through one platform with large-scale functionalities. This study focuses on user interface automation testing for the WEB application. The quality assurance team must execute many manual users interface test cases in the development process to confirm no regression bugs. The team automated 346 test cases; the UI automation test execution time was over 17 hours. The business requirement was reducing the execution time to release high-quality products quickly, and the quality assurance automation team modernized the test automation framework to optimize the execution time. The base of the WEB UI automation test environment is Selenium, and the test code is written in Python. Adopting a compilation language to write test code leads to an inefficient flow when introducing scalability into a traditional test automation environment. In order to efficiently introduce scalability into Test Automation, a scripting language was adopted. The scalability implementation is mainly implemented with AWS's serverless technology, an elastic container service. The definition of scalability here is the ability to automatically set up computers to test automation and increase or decrease the number of computers running those tests. This means the scalable mechanism can help test cases run parallelly. Then test execution time is dramatically decreased. Also, introducing scalable test automation is for more than just reducing test execution time. There is a possibility that some challenging bugs are detected by introducing scalable test automation, such as race conditions, Etc. since test cases can be executed at same timing. If API and Unit tests are implemented, the test strategies can be adopted more efficiently for this scalability testing. However, in WEB applications, as a practical matter, API and Unit testing cannot cover 100% functional testing since they do not reach front-end codes. This study applied a scalable UI automation testing strategy to the large-scale homecare management system. It confirmed the optimization of the test case execution time and the detection of a challenging bug. This study first describes the detailed architecture of the scalable test automation environment, then describes the actual performance reduction time and an example of challenging issue detection.

Keywords: aws, elastic container service, scalability, serverless, ui automation test

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Authors: P. Vindin, R. Cordier, N. J. Wilson, H. Lee

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Engagement in community-based activities such as education, employment, and social relationships can improve the quality of life for individuals with Autism Spectrum Disorder (ASD). Community mobility is vital to attaining independence for individuals with ASD. Learning to drive and gaining a driver’s license is a critical link to community mobility; however, for individuals with ASD acquiring safe driving skills can be a challenging process. Issues related to anxiety, executive function, and social communication may affect driving behaviours. Driving training and education aimed at addressing barriers faced by learner drivers with ASD can help them improve their driving performance. A multi-site randomized controlled trial (RCT) was conducted to evaluate the effectiveness of an autism-specific driving training intervention for improving the on-road driving performance of learner drivers with ASD. The intervention was delivered via a training manual and interactive website consisting of five modules covering varying driving environments starting with a focus on off-road preparations and progressing through basic to complex driving skill mastery. Seventy-two learner drivers with ASD aged 16 to 35 were randomized using a blinded group allocation procedure into either the intervention or control group. The intervention group received 10 driving lessons with the instructors trained in the use of an autism-specific driving training protocol, whereas the control group received 10 driving lessons as usual. Learner drivers completed a pre- and post-observation drive using a standardized driving route to measure driving performance using the Driving Performance Checklist (DPC). They also completed anxiety, executive function, and social responsiveness measures. The findings showed that there were significant improvements in driving performance for both the intervention (d = 1.02) and the control group (d = 1.15). However, the differences were not significant between groups (p = 0.614) or study sites (p = 0.842). None of the potential moderator variables (anxiety, cognition, social responsiveness, and driving instructor experience) influenced driving performance. This study is an important step toward improving community mobility for individuals with ASD showing that an autism-specific driving training intervention can improve the driving performance of leaner drivers with ASD. It also highlighted the complexity of conducting a multi-site design even when sites were matched according to geography and traffic conditions. Driving instructors also need more and clearer information on how to communicate with learner drivers with restricted verbal expression.

Keywords: autism spectrum disorder, community mobility, driving training, transportation

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Authors: Cory B. Portner, Julie A. Grauert, Lisa M. Stromme, Shelby D. Anderson, Franji H. Mayes

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Introduction: WASHINGTON state in the Pacific Northwest of the United States is internationally known for its technology industry, fisheries, agriculture, and vistas. On January 21, 2020, Washington state also became known as the first state with a confirmed COVID-19 case in the United States, thrusting the state into the international spotlight as the world came to grips with the global threat of this disease presented. Tourism is Washington state’s fourth-largest industry. Tourism to the state generates over 1.8 billion dollars (USD) in local and state tax revenue and employs over 180,000 people. Communicating with residents, stakeholders, and visitors on the status of disease activity, prevention measures, and response updates was vital to stopping the pandemic and increasing compliance and awareness. Significance: In order to communicate vital public health updates, guidance implementation, and safety measures to the public, the Washington State Department of Health established routine live virtual media briefings to reach audiences via social media, internet television, and broadcast television. Through close partnership with regional broadcast news stations and the state public affairs news network, the Washington State Department of Health hosted 95 media briefings from January 2020 through September 2022 and continues to regularly host live virtual media briefings to accommodate the needs of the public and media. Methods: Our methods quickly evolved from hosting briefings in the cement closet of a military base to being able to produce and stream the briefings live from any home-office location. The content was tailored to the hot topic of the day and to the reporter's questions and needs. Virtual media briefings hosted through inexpensive or free platforms online are extremely cost-effective: the only mandatory components are WiFi, a laptop, and a monitor. There is no longer a need for a fancy studio or expensive production software to achieve the goal of communicating credible, reliable information promptly. With minimal investment and a small learning curve, facilitators and panelists are able to host highly produced and engaging media availabilities from their living rooms. Results: The briefings quickly developed a reputation as the best source for local and national journalists to get the latest and most factually accurate information about the pandemic. In the height of the COVID-19 response, 135 unique media outlets logged on to participate in the briefing. The briefings typically featured 4-5 panelists, with as many as 9 experts in attendance to provide information and respond to media questions. Preparation was always a priority: Public Affairs staff for the Washington State Department of Health produced over 170 presenter remarks, including guidance on talking points for 63 expert guest panelists. Implication For Practice: Information is today’s most valuable currency. The ability to disseminate correct information urgently and on a wide scale is the most effective tool in crisis communication. Due to our role as the first state with a confirmed COVID-19 case, we were forced to develop the most accurate and effective way to get life-saving information to the public. The cost-effective, web-based methods we developed can be applied in any crisis to educate and protect communities under threat, ultimately saving lives from a laptop.

Keywords: crisis communications, public relations, media management, news media

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Authors: Brooke Sweeney, David White, Felix Amparano, Nick A. Clark, Amy R. Beck, Mathew Lindquist, Lora Edwards, Julie Vandal, Jennifer Lisondra, Katie Cox, Renee Arensberg, Allen Cummins, Jazmine Cedeno, Jason D. Fraser, Kelsey Dean, Helena H. Laroche, Cristina Fernandez

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Background: National organizations call for standardized pre-surgical requirements and education to optimize postoperative outcomes. Since 2017 our surgery program has used defined protocols and educational curricula pre- and post-surgery. In response to patient outcomes, our educational content was refined to include quizzes to assess patient knowledge and surgical preparedness. We aim to optimize adolescent pre-bariatric surgery preparedness by improving overall aggregate pre-surgical assessment performance from 68% to 80% within 12 months. Methods: A multidisciplinary improvement team was developed within the weight management clinic (WMC) of our tertiary care, free-standing children’s hospital. A manual has been utilized since 2017, with limitations in consistent delivery and patient uptake of information. The curriculum has been improved to include quizzes administered during WMC visits prior to bariatric surgery. The initial outcome measure is the pre-surgical quiz score of adolescents preparing for bariatric surgery. Process measure was the number of questions answered correctly to test the questions. Baseline performance was determined by a patient assessment survey of pre-surgical preparedness at patient visits. Plan-Do-Study-Act cycles (PDSA) included: 1) creation and implementation of a refined curriculum, 2) development of 5 new quizzes based upon learning objectives, and 3) improving provider-lead teaching and quiz administration within clinic workflow. Run charts assessed impact over time. Results: A total of 346 quiz questions were administered to 34 adolescents. The outcome measure improved from a baseline mean of 68% to 86% following PDSA 2 cycles, and it was sustained. Conclusion/Implication: Patient/family comprehension of surgical preparedness improved with standardized education via team member-led teaching and assessment using quizzes during pre-surgical clinic visits. The next steps include launching redesigned teaching materials with modules correlated to quizzes and assessment of comprehension and outcomes post-surgically.

Keywords: bariatric surgery, adolescent, clinic, pre-bariatric training

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Authors: Victoria Eugenia Garnacho-Garnacho, Elena Sonsoles Rodriguez-Lopez, Raquel Delgado-Delgado, Alvaro Otero-Campos, Jesus Guodemar-Perez, Angelo Michelle Vagali, Juan Pablo Hervas-Perez

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Asthma is a heterogeneous disease which has always had a drug treatment. Osteopathic treatment that we propose is aimed, seen through a dorsal manipulation (Dog Technic D1-D4) and a technique for diaphragm (Longitudinal Stroke) forced expiratory flow in spirometry changes there are in particular that there is an increase in the volumes of the Peak Flow and Post intervention and effort and that the application of these two techniques together is more powerful if we applied only a Longitudinal (Stroke). Also rating if this type of treatment will have repercussions on breathlessness, a very common symptom in asthma. And finally to investigate if provided vertebra pain decreased after a manipulation. Methods—Participants were recruited between students and professors of the University, aged 18-65, patients (n = 18) were assigned randomly to one of the two groups, group 1 (longitudinal Stroke and manipulation dorsal Dog Technic) and group 2 (diaphragmatic technique, Longitudinal Stroke). The statistical analysis is characterized by the comparison of the main indicator of obstruction of via area PEF (peak expiratory flow) in various situations through the peak flow meter Datospir Peak-10. The measurements were carried out in four phases: at rest, after the stress test, after the treatment, after treatment and the stress test. After each stress test was evaluated, through the Borg scale, the level of Dyspnea on each patient, regardless of the group. In Group 1 in addition to these parameters was calculated using an algometer spinous pain before and after the manipulation. All data were taken at the minute. Results—12 Group 1 (Dog Technic and Longitudinal Stroke) patients responded positively to treatment, there was an increase of 5.1% and 6.1% of the post-treatment PEF and post-treatment, and effort. The results of the scale of Borg by which we measure the level of Dyspnea were positive, a 54.95%, patients noted an improvement in breathing. In addition was confirmed through the means of both groups group 1 in which two techniques were applied was 34.05% more effective than group 2 in which applied only a. After handling pain fell by 38% of the cases. Conclusions—The impact of the technique of Dog-Technic for D1-D4 and the Longitudinal Stroke technique for diaphragm in the volumes of peak expiratory flow (PEF) in asthmatic patients were positive, there was a change of the PEF Post intervention and post-treatment, and effort and showed the most effective group in which only a technique was applied. Furthermore this type of treatment decreased facilitated vertebrae pain and was efficient in the improvement of Dyspnea and the general well-being of the patient.

Keywords: ANS, asthma, manipulation, manual therapy, osteopathic

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Authors: Shu Jiuan Chen, Shu Fen Wu, I. Ling Tsai, Chia Yu Chen, Yen Lin Liu, Chen-Fuh Lam

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Background: Increased emotional stress in workplace and depressed job satisfaction may significantly affect the turnover intention and career life of personnel. However, very limited studies have reported the factors influencing the turnover intention of the surgical team members in the operating rooms, where extraordinary stress is normally exit in this isolated medical care unit. Therefore, this study aimed to determine the environmental and personal characteristic factors that might be associated with job satisfaction and turnover intention in the non-physician staff who work in the operating rooms. Methods: This was a cross-sectional, descriptive study performed in a metropolitan teaching hospital in southern Taiwan between May 2017 to July 2017. A structured self-administered questionnaire, modified from the Practice Environment Scale of the Nursing Work Index (PES-NWI), Occupational Stress Indicator-2 (OSI-2) and Maslach Burnout Inventory (MBI) manual was collected from the operating room nurses, nurse anesthetists, surgeon assistants, orderly and other non-physician staff. Numerical and categorical data were analyzed using unpaired t-test and Chi-square test, as appropriate (SPSS, version 20.0). Results: A total of 167 effective questionnaires were collected from 200 eligible, non-physician personnel who worked in the operating room (response rate 83.5%). The overall satisfaction of all responders was 45.64 ± 7.17. In comparison to those who had more than 4-year working experience in the operating rooms, the junior staff ( ≤ 4-year experience) reported to have significantly higher satisfaction in workplace environment and job contentment, as well as lower intention to quit (t = 6.325, P =0.000). Among the different specialties of surgical team members, nurse anesthetists were associated with significantly lower levels of job satisfaction (P=0.043) and intention to stay (x² = 8.127, P < 0.05). Multivariate regression analysis demonstrates job title, seniority, working shifts and job satisfaction are the significant independent predicting factors for quit jobs. Conclusion: The results of this study highlight that increased work seniorities ( > 4-year working experience) are associated with significantly lower job satisfaction, and they are also more likely to leave their current job. Increased workload in supervising the juniors without appropriate job compensation (such as promotions in job title and work shifts) may precipitate their intention to quit. Since the senior staffs are usually the leaders and core members in the operating rooms, the retention of this fundamental manpower is essential to ensure the safety and efficacy of surgical interventions in the operating rooms.

Keywords: surgical team, job satisfaction, resignation intention, operating room

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Authors: Jafar S. Noori, Jan Romano-deGea, Maria Dimaki, John Mortensen, Winnie E. Svendsen

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Pesticides have been intensively used in agriculture to control weeds, insects, fungi, and pest. One of the most commonly used pesticides is glyphosate. Glyphosate has the ability to attach to the soil colloids and degraded by the soil microorganisms. As glyphosate led to the appearance of resistant species, the pesticide was used more intensively. As a consequence of the heavy use of glyphosate, residues of this compound are increasingly observed in food and water. Recent studies reported a direct link between glyphosate and chronic effects such as teratogenic, tumorigenic and hepatorenal effects although the exposure was below the lowest regulatory limit. Today, pesticides are detected in water by complicated and costly manual procedures conducted by highly skilled personnel. It can take up to several days to get an answer regarding the pesticide content in water. An alternative to this demanding procedure is offered by electrochemical measuring techniques. Electrochemistry is an emerging technology that has the potential of identifying and quantifying several compounds in few minutes. It is currently not possible to detect glyphosate directly in water samples, and intensive research is underway to enable direct selective and quantitative detection of glyphosate in water. This study focuses on developing and modifying a sensor chip that has the ability to selectively measure glyphosate and minimize the signal interference from other compounds. The sensor is a silicon-based chip that is fabricated in a cleanroom facility with dimensions of 10×20 mm. The chip is comprised of a three-electrode configuration. The deposited electrodes consist of a 20 nm layer chromium and 200 nm gold. The working electrode is 4 mm in diameter. The working electrodes are modified by creating molecularly imprinted polymers (MIP) using electrodeposition technique that allows the chip to selectively measure glyphosate at low concentrations. The modification included using gold nanoparticles with a diameter of 10 nm functionalized with 4-aminothiophenol. This configuration allows the nanoparticles to bind to the working electrode surface and create the template for the glyphosate. The chip was modified using electrodeposition technique. An initial potential for the identification of glyphosate was estimated to be around -0.2 V. The developed sensor was used on 6 different concentrations and it was able to detect glyphosate down to 0.5 mgL⁻¹. This value is below the accepted pesticide limit of 0.7 mgL⁻¹ set by the US regulation. The current focus is to optimize the functionalizing procedure in order to achieve glyphosate detection at the EU regulatory limit of 0.1 µgL⁻¹. To the best of our knowledge, this is the first attempt to modify miniaturized sensor electrodes with functionalized nanoparticles for glyphosate detection.

Keywords: pesticides, glyphosate, rapid, detection, modified, sensor

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Authors: Atucungwiire Rwebiita

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Introduction: In Uganda, provision of adolescent sexual reproductive health and rights (SRHR) services for key population is still hindered by negative attitudes, stigma and discrimination (S&D) at both the community and facility levels. To address this barrier, Integrated Community Based Initiatives (ICOBI) with support from SIDA is currently implementing a quality improvement (QI) innovative approach for strengthening the capacity of key population (KP) peer leaders and health workers to deliver friendly SRHR services without S&D. Methods: Our innovative approach involves continuous mentorship and coaching of 8 QI teams at 8 health facilities and their catchment areas. Each of the 8 teams (comprised of 5 health workers and 5 KP peer leaders) are facilitated twice a month by two QI Mentors in a 2-hour mentorship session over a period of 4 months. The QI mentors were provided a 2-weeks training on QI approaches for reducing S&D against young key populations in the delivery of SRHR Services. The mentorship sessions are guided by a manual where teams base to analyse root causes of S&D and develop key performance indicators (KPIs) in the 1st and 2nd second sessions respectively. The teams then develop action plans in the 3rd session and review implementation progress on KPIs at the end of subsequent sessions. The KPIs capture information on the attitude of health workers and peer leaders and the general service delivery setting as well as clients’ experience. A dashboard is developed to routinely track the KPIs for S&D across all the supported health facilities and catchment areas. After 4 months, QI teams share documented QI best practices and tested change packages on S&D in a learning and exchange session involving all the teams. Findings: The implementation of this approach is showing positive results. So far, QI teams have already identified the root causes of S&D against key populations including: poor information among health workers, fear of a perceived risk of infection, perceived links between HIV and disreputable behaviour. Others are perceptions that HIV & STIs are divine punishment, sex work and homosexuality are against religion and cultural values. They have also noted the perception that MSM are mentally sick and a danger to everyone. Eight QI teams have developed action plans to address the root causes of S&D. Conclusion: This approach is promising, offers a novel and scalable means to implement stigma-reduction interventions in facility and community settings.

Keywords: key populations, sexual reproductive health and rights, stigma and discrimination , quality improvement approach

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Authors: Gabriel Fernando Talero Rojas, Vladimir Silva Leal, Camilo Bayona-Roa, Juan Pava, Mauricio Lopez Gomez

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The substitution of conventional aviation fuels with biomass-derived alternative fuels is an emerging field of study in the aviation transport, mainly due to its energy consumption, the contribution to the global Greenhouse Gas - GHG emissions and the fossil fuel price fluctuations. Nevertheless, several challenges remain as the biofuel production cost and its degradative effect over the fuel systems that alter the operating safety. Moreover, experimentation on full-scale aeronautic turbines are expensive and complex, leading to most of the research to the testing of small-size turbojets with a major absence of information regarding the effects in the energy performance and the emissions. The main purpose of the current study is to present the results of experimentation in a full-scale military turbojet engine J69-T-25A (presented in Fig. 1) with 640 kW of power rating and using blends of Jet A1 with oil palm biodiesel. The main findings are related to the thrust specific fuel consumption – TSFC, the engine global efficiency – η, the air/fuel ratio – AFR and the volume fractions of O2, CO2, CO, and HC. Two fuels are used in the present study: a commercial Jet A1 and a Colombian palm oil biodiesel. The experimental plan is conducted using the biodiesel volume contents - w_BD from 0 % (B0) to 50 % (B50). The engine operating regimes are set to Idle, Cruise, and Take-off conditions. The turbojet engine J69 is used by the Colombian Air Force and it is installed in a testing bench with the instrumentation that corresponds to the technical manual of the engine. The increment of w_BD from 0 % to 50 % reduces the η near 3,3 % and the thrust force in a 26,6 % at Idle regime. These variations are related to the reduction of the 〖HHV〗_ad of the fuel blend. The evolved CO and HC tend to be reduced in all the operating conditions when increasing w_BD. Furthermore, a reduction of the atomization angle is presented in Fig. 2, indicating a poor atomization in the fuel nozzle injectors when using a higher biodiesel content as the viscosity of fuel blend increases. An evolution of cloudiness is also observed during the shutdown procedure as presented in Fig. 3a, particularly after 20 % of biodiesel content in the fuel blend. This promotes the contamination of some components of the combustion chamber of the J69 engine with soot and unburned matter (Fig. 3). Thus, the substitution of biodiesel content above 20 % is not recommended in order to avoid a significant decrease of η and the thrust force. A more detail examination of the mechanical wearing of the main components of the engine is advised in further studies.

Keywords: aviation, air to fuel ratio, biodiesel, energy performance, fuel atomization, gas turbine

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Authors: Tianqi Wu, Min Wang

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Research investigating language acquisition from a constructionist perspective has demonstrated that language is learned as constructions at various linguistic levels, which is related to factors of frequency, semantic prototypicality, and form-meaning contingency. However, previous research on construction learning tended to focus on clause-level constructions such as verb argument constructions but few attempts were made to study morpheme-level constructions such as the progressive construction, which is regarded as a source of acquisition problems for English learners from diverse L1 backgrounds, especially for those whose L1 do not have an equivalent construction such as German and Chinese. To trace the developmental trajectory of Chinese EFL learners’ use of the progressive with respect to verb frequency, verb-progressive contingency, and verbal prototypicality and generality, a learner corpus consisting of three sub-corpora representing three different English proficiency levels was extracted from the Chinese Learners of English Corpora (CLEC). As the reference point, a native speakers’ corpus extracted from the Louvain Corpus of Native English Essays was also established. All the texts were annotated with C7 tagset by part-of-speech tagging software. After annotation all valid progressive hits were retrieved with AntConc 3.4.3 followed by a manual check. Frequency-related data showed that from the lowest to the highest proficiency level, (1) the type token ratio increased steadily from 23.5% to 35.6%, getting closer to 36.4% in the native speakers’ corpus, indicating a wider use of verbs in the progressive; (2) the normalized entropy value rose from 0.776 to 0.876, working towards the target score of 0.886 in native speakers’ corpus, revealing that upper-intermediate learners exhibited a more even distribution and more productive use of verbs in the progressive; (3) activity verbs (i.e., verbs with prototypical progressive meanings like running and singing) dropped from 59% to 34% but non-prototypical verbs such as state verbs (e.g., being and living) and achievement verbs (e.g., dying and finishing) were increasingly used in the progressive. Apart from raw frequency analyses, collostructional analyses were conducted to quantify verb-progressive contingency and to determine what verbs were distinctively associated with the progressive construction. Results were in line with raw frequency findings, which showed that contingency between the progressive and non-prototypical verbs represented by light verbs (e.g., going, doing, making, and coming) increased as English proficiency proceeded. These findings altogether suggested that beginning Chinese EFL learners were less productive in using the progressive construction: they were constrained by a small set of verbs which had concrete and typical progressive meanings (e.g., the activity verbs). But with English proficiency increasing, their use of the progressive began to spread to marginal members such as the light verbs.

Keywords: Construction learning, Corpus-based, Progressives, Prototype

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Authors: Jeremy Jenrette, Z. Y. C. Liu, Pranav Chimote, Edward Fox, Trevor Hastie, Francesco Ferretti

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Suitable shark conservation depends on well-informed population assessments. Direct methods such as scientific surveys and fisheries monitoring are adequate for defining population statuses, but species-specific indices of abundance and distribution coming from these sources are rare for most shark species. We can rapidly fill these information gaps by boosting media-based remote monitoring efforts with machine learning and automation. We created a database of shark images by sourcing 24,546 images covering 219 species of sharks from the web application spark pulse and the social network Instagram. We used object detection to extract shark features and inflate this database to 53,345 images. We packaged object-detection and image classification models into a Shark Detector bundle. We developed the Shark Detector to recognize and classify sharks from videos and images using transfer learning and convolutional neural networks (CNNs). We applied these models to common data-generation approaches of sharks: boosting training datasets, processing baited remote camera footage and online videos, and data-mining Instagram. We examined the accuracy of each model and tested genus and species prediction correctness as a result of training data quantity. The Shark Detector located sharks in baited remote footage and YouTube videos with an average accuracy of 89\%, and classified located subjects to the species level with 69\% accuracy (n =\ eight species). The Shark Detector sorted heterogeneous datasets of images sourced from Instagram with 91\% accuracy and classified species with 70\% accuracy (n =\ 17 species). Data-mining Instagram can inflate training datasets and increase the Shark Detector’s accuracy as well as facilitate archiving of historical and novel shark observations. Base accuracy of genus prediction was 68\% across 25 genera. The average base accuracy of species prediction within each genus class was 85\%. The Shark Detector can classify 45 species. All data-generation methods were processed without manual interaction. As media-based remote monitoring strives to dominate methods for observing sharks in nature, we developed an open-source Shark Detector to facilitate common identification applications. Prediction accuracy of the software pipeline increases as more images are added to the training dataset. We provide public access to the software on our GitHub page.

Keywords: classification, data mining, Instagram, remote monitoring, sharks

Procedia PDF Downloads 121

Authors: Jun Won Kim

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Objective: Theta-phase gamma-amplitude coupling (TGC) was used as a novel evidence-based tool to reflect the dysfunctional cortico-thalamic interaction in patients with schizophrenia. However, to our best knowledge, no studies have reported the diagnostic utility of the TGC in the resting-state electroencephalographic (EEG) of neuroleptic-naive patients with schizophrenia compared to healthy controls. Thus, the purpose of this EEG study was to understand the underlying mechanisms in patients with schizophrenia by comparing the TGC at rest between two groups and to evaluate the diagnostic utility of TGC. Method: The subjects included 90 patients with schizophrenia and 90 healthy controls. All patients were diagnosed with schizophrenia according to the criteria of Diagnostic and Statistical Manual of Mental Disorders, 4th edition (DSM-IV) by two independent psychiatrists using semi-structured clinical interviews. Because patients were either drug-naïve (first episode) or had not been taking psychoactive drugs for one month before the study, we could exclude the influence of medications. Five frequency bands were defined for spectral analyses: delta (1–4 Hz), theta (4–8 Hz), slow alpha (8–10 Hz), fast alpha (10–13.5 Hz), beta (13.5–30 Hz), and gamma (30-80 Hz). The spectral power of the EEG data was calculated with fast Fourier Transformation using the 'spectrogram.m' function of the signal processing toolbox in Matlab. An analysis of covariance (ANCOVA) was performed to compare the TGC results between the groups, which were adjusted using a Bonferroni correction (P < 0.05/19 = 0.0026). Receiver operator characteristic (ROC) analysis was conducted to examine the discriminating ability of the TGC data for schizophrenia diagnosis. Results: The patients with schizophrenia showed a significant increase in the resting-state TGC at all electrodes. The delta, theta, slow alpha, fast alpha, and beta powers showed low accuracies of 62.2%, 58.4%, 56.9%, 60.9%, and 59.0%, respectively, in discriminating the patients with schizophrenia from the healthy controls. The ROC analysis performed on the TGC data generated the most accurate result among the EEG measures, displaying an overall classification accuracy of 92.5%. Conclusion: As TGC includes phase, which contains information about neuronal interactions from the EEG recording, TGC is expected to be useful for understanding the mechanisms the dysfunctional cortico-thalamic interaction in patients with schizophrenia. The resting-state TGC value was increased in the patients with schizophrenia compared to that in the healthy controls and had a higher discriminating ability than the other parameters. These findings may be related to the compensatory hyper-arousal patterns of the dysfunctional default-mode network (DMN) in schizophrenia. Further research exploring the association between TGC and medical or psychiatric conditions that may confound EEG signals will help clarify the potential utility of TGC.

Keywords: quantitative electroencephalography (QEEG), theta-phase gamma-amplitude coupling (TGC), schizophrenia, diagnostic utility

Procedia PDF Downloads 143

Authors: Xiao Wang, Qinge Zhang

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Background: This randomized, open-label study examined the therapeutic effects of computerized cognitive training (CCT) combined with selective serotonin reuptake inhibitors (SSRIs) on cognitive impairment among patients with late-life depression (LLD). Method: Study data were collected from May 5, 2021, to April 21, 2023. Outpatients who met diagnostic criteria for major depressive disorder according to the fifth revision of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) criteria (i.e., a total score on the 17-item Hamilton Depression Rating Scale (HAMD-17) ≥ 18 and a total score on the Montreal Cognitive Assessment scale (MOCA) <26) were randomly assigned to receive up to 12 weeks of CCT and SSRIs treatment (n=57) or SSRIs and Control treatment (n=61). The primary outcome was the change in Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-Cog) scores from baseline to week 12 between the two groups. The secondary outcomes included changes in the HAMD-17 score, Hamilton Anxiety Scale (HAMA) score and Neuropsychiatric Inventory (NPI) score. Mixed model repeated measures (MMRM) analysis was performed on modified intention-to-treat (mITT) and completer populations. Results: The full analysis set (FAS) included 118 patients (CCT and SSRIs group, n=57; SSRIs and Control group, n =61). Over the 12-week study period, the reduction in the ADAS-cog total score was significant (P < 0.001) in both groups, while MMRM analysis revealed a significantly greater reduction in cognitive function (ADAS-cog total scores) from baseline to posttreatment in the CCT and SSRIs group than in the SSRI and Control group [(F (1,115) =13.65, least-squares mean difference [95% CI]: −2.77 [−3.73, −1.81], p<0.001)]. There were significantly greater improvements in depression symptoms (measured by the HAMD-17) in the CCT and SSRIs group than in the control group [MMRM, estimated mean difference (SE) between groups −3.59 [−5.02, −2.15], p < 0.001]. The least-squares mean changes in the HAMA scores and NPI scores between baseline and week 8 were greater in the CCT and SSRIs group than in the control group (all P < 0.05). There was no significant difference between groups on response rates and remission rates by using the last-observation-carried-forward (LOCF) method (all P > 0.05). The most frequent adverse events (AEs) in both groups were dry mouth, somnolence, and constipation. There was no significant difference in the incidence of adverse events between the two groups. Conclusions: CCT combined with SSRIs was efficacious and well tolerated in LLD patients with cognitive impairment.

Keywords: late-life depression, cognitive function, computerized cognitive training, SSRIs

Procedia PDF Downloads 50

Authors: I. Ling Tsai, Shu Fen Wu, Chen-Fuh Lam, Chia Yu Chen, Shu Jiuan Chen, Yen Lin Liu

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Purpose: Following the conduction of the National Health Insurance (NHI) system in Taiwan since 1995, the demand for anesthesia services continues to increase in the operating rooms and other medical units. It has been well recognized that increased work stress not only affects the clinical performance of the medical staff, long-term work load may also result in occupational burnout. Our study aimed to determine the influence of working environment, work stress and job satisfaction on the occupational burnout in nurse anesthetists. The ultimate goal of this research project is to develop a strategy in establishing a friendly, less stressful workplace for the nurse anesthetists to enhance their job satisfaction, thereby reducing occupational burnout and increasing the career life for nurse anesthetists. Methods: This was a cross-sectional, descriptive study performed in a metropolitan teaching hospital in southern Taiwan between May 2017 to July 2017. A structured self-administered questionnaire, modified from the Practice Environment Scale of the Nursing Work Index (PES-NWI), Occupational Stress Indicator 2 (OSI-2) and Maslach Burnout Inventory (MBI) manual was collected from the nurse anesthetists. The relationships between two numeric datasets were analyzed by the Pearson correlation test (SPSS 20.0). Results: A total of 66 completed questionnaires were collected from 75 nurses (response rate 88%). The average scores for the working environment, job satisfaction, and work stress were 69.6%, 61.5%, and 63.9%, respectively. The three perspectives used to assess the occupational burnout, namely emotional exhaustion, depersonalization and sense of personal accomplishment were 26.3, 13.0 and 24.5, suggesting the presence of moderate to high degrees of burnout in our nurse anesthetists. The presence of occupational burnout was closely correlated with the unsatisfactory working environment (r=-0.385, P=0.001) and reduced job satisfaction (r=-0.430, P=0.000). Junior nurse anesthetists (<1-year clinical experience) reported having higher satisfaction in working environment than the seniors (5 to 10-year clinical experience) (P=0.02). Although the average scores for work stress, job satisfaction, and occupational burnout were lower in junior nurses, the differences were not statistically different. The linear regression model, the working environment was the independent factor that predicted occupational burnout in nurse anesthetists up to 19.8%. Conclusions: High occupational burnout is more likely to develop in senior nurse anesthetists who experienced the dissatisfied working environment, work stress and lower job satisfaction. In addition to the regulation of clinical duties, the increased workload in the supervision of the junior nurse anesthetists may result in emotional stress and burnout in senior nurse anesthetists. Therefore, appropriate adjustment of clinical and teaching loading in the senior nurse anesthetists could be helpful to improve the occupational burnout and enhance the retention rate.

Keywords: nurse anesthetists, working environment, work stress, job satisfaction, occupational burnout

Procedia PDF Downloads 278

Authors: Rose Antony, Vivekanand B. Khanapuri, Karuna Jain

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Online groceries have transformed the way the supply chains are managed. These are facing numerous challenges in terms of product wastages, low margins, long breakeven to achieve and low market penetration to mention a few. The e-grocery chains need to overcome these challenges in order to survive the competition. The purpose of this paper is to carry out a structural analysis of the enablers in e-grocery chains by applying Interpretive Structural Modeling (ISM) and MICMAC analysis in the Indian context. The research design is descriptive-explanatory in nature. The enablers have been identified from the literature and through semi-structured interviews conducted among the managers having relevant experience in e-grocery supply chains. The experts have been contacted through professional/social networks by adopting a purposive snowball sampling technique. The interviews have been transcribed, and manual coding is carried using open and axial coding method. The key enablers are categorized into themes, and the contextual relationship between these and the performance measures is sought from the Industry veterans. Using ISM, the hierarchical model of the enablers is developed and MICMAC analysis identifies the driver and dependence powers. Based on the driver-dependence power the enablers are categorized into four clusters namely independent, autonomous, dependent and linkage. The analysis found that information technology (IT) and manpower training acts as key enablers towards reducing the lead time and enhancing the online service quality. Many of the enablers fall under the linkage cluster viz., frequent software updating, branding, the number of delivery boys, order processing, benchmarking, product freshness and customized applications for different stakeholders, depicting these as critical in online food/grocery supply chains. Considering the perishability nature of the product being handled, the impact of the enablers on the product quality is also identified. Hence, study aids as a tool to identify and prioritize the vital enablers in the e-grocery supply chain. The work is perhaps unique, which identifies the complex relationships among the supply chain enablers in fresh food for e-groceries and linking them to the performance measures. It contributes to the knowledge of supply chain management in general and e-retailing in particular. The approach focus on the fresh food supply chains in the Indian context and hence will be applicable in developing economies context, where supply chains are evolving.

Keywords: interpretive structural modelling (ISM), India, online grocery, retail operations, supply chain management

Procedia PDF Downloads 203

Authors: Weeradej Cheewapattananuwong, Keeree Srivichian, Godchamon Somchai, Wasin Phusanong, Nontawat Yoddamnern

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Natural rubber used for traffic devices in Thailand has been developed and researched for several years. When compared with Dry Rubber Content (DRC), the quality of Rib Smoked Sheet (RSS) is better. However, the cost of admixtures, especially CaCO₃ and sulphur, is higher than the cost of RSS itself. In this research, Flexible Guideposts and Rubber Fender Barriers (RFB) are taken into consideration. In case of flexible guideposts, the materials used are both RSS and DRC60%, but for RFB, only RSS is used due to the controlled performance tests. The objective of flexible guideposts and RFB is to decrease a number of accidents, fatal rates, and serious injuries. Functions of both devices are to save road users and vehicles as well as to absorb impact forces from vehicles so as to decrease of serious road accidents. This leads to the mitigation methods to remedy the injury of motorists, form severity to moderate one. The solution is to find the best practice of traffic devices using natural rubber under the engineering concepts. In addition, the performances of materials, such as tensile strength and durability, are calculated for the modulus of elasticity and properties. In the laboratory, the simulation of crashes, finite element of materials, LRFD, and concrete technology methods are taken into account. After calculation, the trials' compositions of materials are mixed and tested in the laboratory. The tensile test, compressive test, and weathering or durability test are followed and based on ASTM. Furthermore, the Cycle-Repetition Test of Flexible Guideposts will be taken into consideration. The final decision is to fabricate all materials and have a real test section in the field. In RFB test, there will be 13 crash tests, 7 Pickup Truck tests, and 6 Motorcycle Tests. The test of vehicular crashes happens for the first time in Thailand, applying the trial and error methods; for example, the road crash test under the standard of NCHRP-TL3 (100 kph) is changed to the MASH 2016. This is owing to the fact that MASH 2016 is better than NCHRP in terms of speed, types, and weight of vehicles and the angle of crash. In the processes of MASH, Test Level 6 (TL-6), which is composed of 2,270 kg Pickup Truck, 100 kph, and 25 degree of crash-angle is selected. The final test for real crash will be done, and the whole system will be evaluated again in Korea. The researchers hope that the number of road accidents will decrease, and Thailand will be no more in the top tenth ranking of road accidents in the world.

Keywords: LRFD, load and resistance factor design, ASTM, american society for testing and materials, NCHRP, national cooperation highway research program, MASH, manual for assessing safety hardware

Procedia PDF Downloads 128

Authors: Eun-Jeong Jang

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Inequality has been considered as a core issue in public policy. Korea is categorized into one of the countries in the high level of inequality, which matters to not only current but also future generations. The relationship between individuals' origin and destination has an implication of intergenerational inequality. The previous work on this was mostly conducted at macro level using panel data to our knowledge. However, in this level, there is no room to track down what happened during the time between origin and destination. Individuals' origin is represented by their parents' socio-economic status, and in the same way, destination is translated into their own socio-economic status. The first research question is that how origin is related to the destination. Certainly, destination is highly affected by origin. In this view, people's destination is already set to be more or less than a reproduction of previous generations. However, educational achievement is widely believed as an independent factor from the origin. From this point of view, there is a possibility to change the path given by parents by educational attainment. Hence, the second research question would be that how education is related to destination and also, which factor is more influential to destination between origin and education. Also, the focus lies in the mediation of education between origin and destination, which would be the third research question. Socio-economic status in this study is referring to class as a sociological term, as well as wealth including labor and capital income, as an economic term. The combination of class and wealth would be expected to give more accurate picture about the hierarchy in a society. In some cases of non-manual and professional occupations, even though they are categorized into relatively high class, their income is much lower than those who in the same class. Moreover, it is one way to overcome the limitation of the retrospective view during survey. Education is measured as an absolute term, the years of schooling, and also as a relative term, the rank of school. Moreover, all respondents were asked the effort scaled by time intensity, self-motivation, before and during the course of their college based on a standard questionnaire academic achieved model provides. This research is based on a survey at an individual level. The target for sampling is an individual who has a job, regardless of gender, including income-earners and self-employed people and aged between thirties and forties because this age group is considered to reach the stage of job stability. In most cases, the researcher met respondents person to person visiting their work place or home and had a chance to interview some of them. One hundred forty individual data collected from May to August in 2017. It will be analyzed by multiple regression (Q1, Q2) and structural equation modeling (Q3).

Keywords: class, destination, educational achievement, effort, income, origin, socio-economic status, South Korea

Procedia PDF Downloads 273

Authors: Junior Akunzi

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In the matter of patient treatment planning quality assurance in 3D conformational therapy (3D-CRT) and volumetric arc therapy (VMAT or RapidArc), the independent monitor unit verification calculation (MUVC) is an indispensable part of the process. Concerning 3D-CRT treatment planning, the MUVC can be performed manually applying the standard ESTRO formalism. However, due to the complex shape and the amount of beams in advanced treatment planning technic such as RapidArc, the manual independent MUVC is inadequate. Therefore, commercially available software such as RadCalc can be used to perform the MUVC in complex treatment planning been. Indeed, RadCalc (version 6.3 LifeLine Inc.) uses a simplified Clarkson algorithm to compute the dose contribution for individual RapidArc fields to the isocenter. The purpose of this project is the validation of RadCalc in 3D-CRT and RapidArc for treatment planning dosimetry quality assurance at Antoine Lacassagne center (Nice, France). Firstly, the interfaces between RadCalc and our treatment planning systems (TPS) Isogray (version 4.2) and Eclipse (version13.6) were checked for data transfer accuracy. Secondly, we created test plans in both Isogray and Eclipse featuring open fields, wedges fields, and irregular MLC fields. These test plans were transferred from TPSs according to the radiotherapy protocol of DICOM RT to RadCalc and the linac via Mosaiq (version 2.5). Measurements were performed in water phantom using a PTW cylindrical semiflex ionisation chamber (0.3 cm³, 31010) and compared with the TPSs and RadCalc calculation. Finally, 30 3D-CRT plans and 40 RapidArc plans created with patients CT scan were recalculated using the CT scan of a solid PMMA water equivalent phantom for 3D-CRT and the Octavius II phantom (PTW) CT scan for RapidArc. Next, we measure the doses delivered into these phantoms for each plan with a 0.3 cm³ PTW 31010 cylindrical semiflex ionisation chamber (3D-CRT) and 0.015 cm³ PTW PinPoint ionisation chamber (Rapidarc). For our test plans, good agreements were found between calculation (RadCalc and TPSs) and measurement (mean: 1.3%; standard deviation: ± 0.8%). Regarding the patient plans, the measured doses were compared to the calculation in RadCalc and in our TPSs. Moreover, RadCalc calculations were compared to Isogray and Eclispse ones. Agreements better than (2.8%; ± 1.2%) were found between RadCalc and TPSs. As for the comparison between calculation and measurement the agreement for all of our plans was better than (2.3%; ± 1.1%). The independent MU verification calculation software RadCal has been validated for clinical use and for both 3D-CRT and RapidArc techniques. The perspective of this project includes the validation of RadCal for the Tomotherapy machine installed at centre Antoine Lacassagne.

Keywords: 3D conformational radiotherapy, intensity modulated radiotherapy, monitor unit calculation, dosimetry quality assurance

Procedia PDF Downloads 216

Authors: Ilyas Khan. Liliane Pintelon, Harry Martin, Michael Shömig

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The increasing costs of healthcare on one hand, and the rise in aging population and associated chronic disease, on the other hand, are putting increasing burden on the current health care system in many Western countries. For instance, chronic kidney disease (CKD) is a common disease and in Europe, the cost of renal replacement therapy (RRT) is very significant to the total health care cost. However, the recent advancement in healthcare technology, provide the opportunity to treat patients at home in their own comfort. It is evident that home healthcare offers numerous advantages apparently, low costs and high patients’ quality of life. Despite these advantages, the intake of home hemodialysis (HHD) therapy is still low in particular in Germany. Many factors are accounted for the low number of HHD intake. However, this paper is focusing on patients’ safety-related factors of current HHD practices in Germany. The aim of this paper is to analyze the current HHD practices in Germany and to identify risks related factors if any exist. A case study has been conducted in a dialysis center which consists of four dialysis centers in the south of Germany. In total, these dialysis centers have 350 chronic dialysis patients, of which, four patients are on HHD. The centers have 126 staff which includes six nephrologists and 120 other staff i.e. nurses and administration. The results of the study revealed several risk-related factors. Most importantly, these centers do not offer allied health services at the pre-dialysis stage, the HHD training did not have an established curriculum; however, they have just recently developed the first version. Only a soft copy of the machine manual is offered to patients. Surprisingly, the management was not aware of any standard available for home assessment and installation. The home assessment is done by a third party (i.e. the machines and equipment provider) and they may not consider the hygienic quality of the patient’s home. The type of machine provided to patients at home is similar to the one in the center. The model may not be suitable at home because of its size and complexity. Even though portable hemodialysis machines, which are specially designed for home use, are available in the market such as the NxStage series. Besides the type of machine, no assistance is offered for space management at home in particular for placing the machine. Moreover, the centers do not offer remote assistance to patients and their carer at home. However, telephonic assistance is available. Furthermore, no alternative is offered if a carer is not available. In addition, the centers are lacking medical staff including nephrologists and renal nurses.

Keywords: home hemodialysis, home hemodialysis practices, patients’ related risks in the current home hemodialysis practices, patient safety in home hemodialysis

Procedia PDF Downloads 119

Authors: Enes Huylu, Sude Erkin, Nur A. Özdemir, Hatice K. Güney, Cemre S. Atılgan, Hüseyin Y. Altıntaş, Aysemin Top, Muammer Yılman, Özak Durmuş

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Remanufacturing (reman) applications allow manufacturers to contribute to the circular economy and help to introduce products with almost the same quality, environment-friendly, and lower cost. The objective of this study is to present that the carbon footprint of automotive spare parts used in vehicles could be reduced by reman applications based on Life Cycle Analysis which was framed with ISO 14040 principles. In that case, it was aimed to investigate reman applications for 21 parts in total. So far, research and calculations have been completed for the alternator, turbocharger, starter motor, compressor, manual transmission, auto transmission, and DPF (diesel particulate filter) parts, respectively. Since the aim of Ford Motor Company and Ford OTOSAN is to achieve net zero based on Science-Based Targets (SBT) and the Green Deal that the European Union sets out to make it climate neutral by 2050, the effects of reman applications are researched. In this case, firstly, remanufacturing articles available in the literature were searched based on the yearly high volume of spare parts sold. Paper review results related to their material composition and emissions released during incoming production and remanufacturing phases, the base part has been selected to take it as a reference. Then, the data of the selected base part from the research are used to make an approximate estimation of the carbon footprint reduction of the relevant part used in Ford OTOSAN. The estimation model is based on the weight, and material composition of the referenced paper reman activity. As a result of this study, it was seen that remanufacturing applications are feasible to apply technically and environmentally since it has significant effects on reducing the emissions released during the production phase of the vehicle components. For this reason, the research and calculations of the total number of targeted products in yearly volume have been completed to a large extent. Thus, based on the targeted parts whose research has been completed, in line with the net zero targets of Ford Motor Company and Ford OTOSAN by 2050, if remanufacturing applications are preferred instead of recent production methods, it is possible to reduce a significant amount of the associated greenhouse gas (GHG) emissions of spare parts used in vehicles. Besides, it is observed that remanufacturing helps to reduce the waste stream and causes less pollution than making products from raw materials by reusing the automotive components.

Keywords: greenhouse gas emissions, net zero targets, remanufacturing, spare parts, sustainability

Procedia PDF Downloads 81

Authors: Ravshan A. Ibadov, Sardor Kh. Ibragimov

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Objective. The aim of the study was to optimize the protocol of cardiopulmonary resuscitation (CPR) after cardiovascular surgical interventions. Methods. The experience of CPR conducted on patients after cardiovascular surgical interventions in the Department of Intensive Care and Resuscitation (DIR) of the Republican Specialized Scientific-Practical Medical Center of Surgery named after Academician V. Vakhidov is presented. The key to the new approach is the rapid elimination of reversible causes of cardiac arrest, followed by either defibrillation or electrical cardioversion (depending on the situation) before external heart compression, which may damage sternotomy. Careful use of adrenaline is emphasized due to the potential recurrence of hypertension, and timely resternotomy (within 5 minutes) is performed to ensure optimal cerebral perfusion through direct massage. Out of 32 patients, cardiac arrest in the form of asystole was observed in 16 (50%), with hypoxemia as the cause, while the remaining 16 (50%) experienced ventricular fibrillation caused by arrhythmogenic reactions. The age of the patients ranged from 6 to 60 years. All patients were evaluated before the operation using the ASA and EuroSCORE scales, falling into the moderate-risk group (3-5 points). CPR was conducted for cardiac activity restoration according to the American Heart Association and European Resuscitation Council guidelines (Ley SJ. Standards for Resuscitation After Cardiac Surgery. Critical Care Nurse. 2015;35(2):30-38). The duration of CPR ranged from 8 to 50 minutes. The ARASNE II scale was used to assess the severity of patients' conditions after CPR, and the Glasgow Coma Scale was employed to evaluate patients' consciousness after the restoration of cardiac activity and sedation withdrawal. Results. In all patients, immediate chest compressions of the necessary depth (4-5 cm) at a frequency of 100-120 compressions per minute were initiated upon detection of cardiac arrest. Regardless of the type of cardiac arrest, defibrillation with a manual defibrillator was performed 3-5 minutes later, and adrenaline was administered in doses ranging from 100 to 300 mcg. Persistent ventricular fibrillation was also treated with antiarrhythmic therapy (amiodarone, lidocaine). If necessary, infusion of inotropes and vasopressors was used, and for the prevention of brain edema and the restoration of adequate neurostatus within 1-3 days, sedation, a magnesium-lidocaine mixture, mechanical intranasal cooling of the brain stem, and neuroprotective drugs were employed. A coordinated effort by the resuscitation team and proper role allocation within the team were essential for effective cardiopulmonary resuscitation (CPR). All these measures contributed to the improvement of CPR outcomes. Conclusion. Successful CPR following cardiac surgical interventions involves interdisciplinary collaboration. The application of an optimized CPR standard leads to a reduction in mortality rates and favorable neurological outcomes.

Keywords: cardiac surgery, cardiac arrest, resuscitation, critically ill patients

Procedia PDF Downloads 53

Authors: Tunde Ope-Davies

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Transmediality and platformization as online content-sharing protocols have continued to accentuate the growing impact of the unprecedented digital revolution across the world. The rapid transformation across all sectors as a result of this revolution has continued to spotlight the increasing importance of new media technologies in redefining and reshaping the rhythm and dynamics of our private and public discursive practices. Equally, social and political activities are being impacted daily through the creation and transmission of political discourse content through multi-channel platforms such as mobile telephone communication, social media networks and the internet. It has been observed that digital platforms have become central to the production, processing, and distribution of multimodal social data and cultural content. The platformization paradigm thus underpins our understanding of how digital platforms enhance the production and heterogenous distribution of media and cultural content through these platforms and how this process facilitates socioeconomic and political activities. The use of multiple digital platforms to share and transmit political discourse material synchronously and asynchronously has gained some exciting momentum in the last few years. Nigeria’s 2023 general elections amplified the usage of social media and other online platforms as tools for electioneering campaigns, socio-political mobilizations and civic engagement. The study, therefore, focuses on transmedia and platformed political discourse as a new strategy to promote political candidates and their manifesto in order to mobilize support and woo voters. This innovative transmedia digital discourse model involves a constellation of online texts and images transmitted through different online platforms almost simultaneously. The data for the study was extracted from the 2023 general elections campaigns in Nigeria between January- March 2023 through media monitoring, manual download and the use of software to harvest the online electioneering campaign material. I adopted a discursive-analytic qualitative technique with toolkits drawn from a computer-mediated multimodal discourse paradigm. The study maps the progressive development of digital political discourse in this young democracy. The findings also demonstrate the inevitable transformation of modern democratic practice through platform-dependent and transmedia political discourse. Political actors and media practitioners now deploy layers of social media network platforms to convey messages and mobilize supporters in order to aggregate and maximize the impact of their media campaign projects and audience reach.

Keywords: social media, digital humanities, political discourse, platformized discourse, multimodal discourse

Procedia PDF Downloads 83

Authors: M. Bahari Mehrabani, Hua-Peng Chen

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Management and maintenance of coastal defence structures during the expected life cycle have become a real challenge for decision makers and engineers. Accurate evaluation of the current condition and future performance of flood defence structures is essential for effective practical maintenance strategies on the basis of available field inspection data. Moreover, as coastal defence structures age, it becomes more challenging to implement maintenance and management plans to avoid structural failure. Therefore, condition inspection data are essential for assessing damage and forecasting deterioration of ageing flood defence structures in order to keep the structures in an acceptable condition. The inspection data for flood defence structures are often collected using discrete visual condition rating schemes. In order to evaluate future condition of the structure, a probabilistic deterioration model needs to be utilised. However, existing deterioration models may not provide a reliable prediction of performance deterioration for a long period due to uncertainties. To tackle the limitation, a time-dependent condition-based model associated with a transition probability needs to be developed on the basis of condition grade scheme for flood defences. This paper presents a probabilistic method for predicting future performance deterioration of coastal flood defence structures based on condition grading inspection data and deterioration curves estimated by expert judgement. In condition-based deterioration modelling, the main task is to estimate transition probability matrices. The deterioration process of the structure related to the transition states is modelled according to Markov chain process, and a reliability-based approach is used to estimate the probability of structural failure. Visual inspection data according to the United Kingdom Condition Assessment Manual are used to obtain the initial condition grade curve of the coastal flood defences. The initial curves then modified in order to develop transition probabilities through non-linear regression based optimisation algorithms. The Monte Carlo simulations are then used to evaluate the future performance of the structure on the basis of the estimated transition probabilities. Finally, a case study is given to demonstrate the applicability of the proposed method under no-maintenance and medium-maintenance scenarios. Results show that the proposed method can provide an effective predictive model for various situations in terms of available condition grading data. The proposed model also provides useful information on time-dependent probability of failure in coastal flood defences.

Keywords: condition grading, flood defense, performance assessment, stochastic deterioration modelling

Procedia PDF Downloads 233

Authors: U. Pruthviraj, Praveen Kumar R. A. K. Athul, K. V. Gangadharan, S. Rao Shrikantha

Abstract:

An open source based autonomous unmanned marine surface vehicle (UMSV) is developed for some of the marine applications such as pollution control, environmental monitoring and thermal imaging. A double rotomoulded hull boat is deployed which is rugged, tough, quick to deploy and moves faster. It is suitable for environmental monitoring, and it is designed for easy maintenance. A 2HP electric outboard marine motor is used which is powered by a lithium-ion battery and can also be charged from a solar charger. All connections are completely waterproof to IP67 ratings. In full throttle speed, the marine motor is capable of up to 7 kmph. The motor is integrated with an open source based controller using cortex M4F for adjusting the direction of the motor. This UMSV can be operated by three modes: semi-autonomous, manual and fully automated. One of the channels of a 2.4GHz radio link 8 channel transmitter is used for toggling between different modes of the USMV. In this electric outboard marine motor an on board GPS system has been fitted to find the range and GPS positioning. The entire system can be assembled in the field in less than 10 minutes. A Flir Lepton thermal camera core, is integrated with a 64-bit quad-core Linux based open source processor, facilitating real-time capturing of thermal images and the results are stored in a micro SD card which is a data storage device for the system. The thermal camera is interfaced to an open source processor through SPI protocol. These thermal images are used for finding oil spills and to look for people who are drowning at low visibility during the night time. A Real Time clock (RTC) module is attached with the battery to provide the date and time of thermal images captured. For the live video feed, a 900MHz long range video transmitter and receiver is setup by which from a higher power output a longer range of 40miles has been achieved. A Multi-parameter probe is used to measure the following parameters: conductivity, salinity, resistivity, density, dissolved oxygen content, ORP (Oxidation-Reduction Potential), pH level, temperature, water level and pressure (absolute).The maximum pressure it can withstand 160 psi, up to 100m. This work represents a field demonstration of an open source based autonomous navigation system for a marine surface vehicle.

Keywords: open source, autonomous navigation, environmental monitoring, UMSV, outboard motor, multi-parameter probe

Procedia PDF Downloads 241

Authors: Jiangbo Li, Wenqian Huang

Abstract:

Early detection of fungal infection in citrus fruit is one of the major problems in the postharvest commercialization process. The automatic and nondestructive detection of infected fruits is still a challenge for the citrus industry. At present, the visual inspection of rotten citrus fruits is commonly performed by workers through the ultraviolet induction fluorescence technology or manual sorting in citrus packinghouses to remove fruit subject with fungal infection. However, the former entails a number of problems because exposing people to this kind of lighting is potentially hazardous to human health, and the latter is very inefficient. Orange is used as a research object. This study would focus on this problem and proposed an effective method based on Vis-NIR hyperspectral imaging in the wavelength range of 400-1000 nm with a spectroscopic resolution of 2.8 nm. In this work, three normalization approaches are applied prior to analysis to reduce the effect of sample curvature on spectral profiles, and it is found that mean normalization was the most effective pretreatment for decreasing spectral variability due to curvature. Then, principal component analysis (PCA) was applied to a dataset composing of average spectra from decayed and normal tissue to reduce the dimensionality of data and observe the ability of Vis-NIR hyper-spectra to discriminate data from two classes. In this case, it was observed that normal and decayed spectra were separable along the resultant first principal component (PC1) axis. Subsequently, five wavelengths (band) centered at 577, 702, 751, 808, and 923 nm were selected as the characteristic wavelengths by analyzing the loadings of PC1. A multispectral combination image was generated based on five selected characteristic wavelength images. Based on the obtained multispectral combination image, the intensity slicing pseudocolor image processing method is used to generate a 2-D visual classification image that would enhance the contrast between normal and decayed tissue. Finally, an image segmentation algorithm for detection of decayed fruit was developed based on the pseudocolor image coupled with a simple thresholding method. For the investigated 238 independent set samples including infected fruits infected by Penicillium digitatum and normal fruits, the total success rate is 100% and 97.5%, respectively, and, the proposed algorithm also used to identify the orange infected by penicillium italicum with a 100% identification accuracy, indicating that the proposed multispectral algorithm here is an effective method and it is potential to be applied in citrus industry.

Keywords: citrus fruit, early rotten, fungal infection, hyperspectral imaging

Procedia PDF Downloads 299

Authors: Tsega Asresa, Getahun Tigistu, Melaku Bayih

Abstract:

Computer vision is a subfield of artificial intelligence that allows computers and systems to extract meaning from digital images and video. It is used in a wide range of fields of study, including self-driving cars, video surveillance, medical diagnosis, manufacturing, law, agriculture, quality control, health care, facial recognition, and military applications. Aromatic medicinal plants are botanical raw materials used in cosmetics, medicines, health foods, essential oils, decoration, cleaning, and other natural health products for therapeutic and Aromatic culinary purposes. These plants and their products not only serve as a valuable source of income for farmers and entrepreneurs but also going to export for valuable foreign currency exchange. In Ethiopia, there is a lack of technologies for the classification and identification of Aromatic medicinal plant parts and disease type cured by aromatic medicinal plants. Farmers, industry personnel, academicians, and pharmacists find it difficult to identify plant parts and disease types cured by plants before ingredient extraction in the laboratory. Manual plant identification is a time-consuming, labor-intensive, and lengthy process. To alleviate these challenges, few studies have been conducted in the area to address these issues. One way to overcome these problems is to develop a deep learning model for efficient identification of Aromatic medicinal plant parts with their corresponding disease type. The objective of the proposed study is to identify the aromatic medicinal plant parts and their disease type classification using computer vision technology. Therefore, this research initiated a model for the classification of aromatic medicinal plant parts and their disease type by exploring computer vision technology. Morphological characteristics are still the most important tools for the identification of plants. Leaves are the most widely used parts of plants besides roots, flowers, fruits, and latex. For this study, the researcher used RGB leaf images with a size of 128x128 x3. In this study, the researchers trained five cutting-edge models: convolutional neural network, Inception V3, Residual Neural Network, Mobile Network, and Visual Geometry Group. Those models were chosen after a comprehensive review of the best-performing models. The 80/20 percentage split is used to evaluate the model, and classification metrics are used to compare models. The pre-trained Inception V3 model outperforms well, with training and validation accuracy of 99.8% and 98.7%, respectively.

Keywords: aromatic medicinal plant, computer vision, convolutional neural network, deep learning, plant classification, residual neural network

Procedia PDF Downloads 186