Search results for: learning goal orientation

Authors: Penn P. Wu, Jeannie Jo

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Blockchain technology has rapidly gained popularity in industry. This paper attempts to assist academia to answer four questions. First, should community colleges begin offering education to nurture blockchain-literate students for the job market? Second, what are the appropriate topical areas to cover? Third, should it be an individual course? And forth, should it be a technical or management course? This paper starts with identifying the knowledge domains of blockchain technology and the topical areas each domain has, and continues with placing them in appropriate academic territories (Computer Sciences vs. Business) and subjects (programming, management, marketing, and laws), and then develops an evaluation model to determine the appropriate topical area for community colleges to teach. The evaluation is based on seven factors: maturity of technology, impacts on management, real-world applications, subject classification, knowledge prerequisites, textbook readiness, and recommended pedagogies. The evaluation results point to an interesting direction that offering an introductory course is an ideal option to guide students through the learning journey of what blockchain is and how it applies to business. Such an introductory course does not need to engage students in the discussions of mathematics and sciences that make blockchain technologies possible. While it is inevitable to brief technical topics to help students build a solid knowledge foundation of blockchain technologies, community colleges should avoid offering students a course centered on the discussion of developing blockchain applications.

Keywords: blockchain, pedagogies, blockchain technologies, blockchain course, blockchain pedagogies

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Authors: Ganesh B. Shinde, Vijaya B. Musande

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Cotton crop identification based on the timely information has significant advantage to the different implications of food, economic and environment. Due to the significant advantages, the accurate detection of cotton crop regions using supervised learning procedure is challenging problem in remote sensing. Here, classifiers on the direct image are played a major role but the results are not much satisfactorily. In order to further improve the effectiveness, variety of vegetation indices are proposed in the literature. But, recently, the major challenge is to find the better vegetation indices for the cotton crop identification through the proposed methodology. Accordingly, fuzzy c-means clustering is combined with neural network algorithm, trained by Levenberg-Marquardt for cotton crop classification. To experiment the proposed method, five LISS-III satellite images was taken and the experimentation was done with six vegetation indices such as Simple Ratio, Normalized Difference Vegetation Index, Enhanced Vegetation Index, Green Atmospherically Resistant Vegetation Index, Wide-Dynamic Range Vegetation Index, Green Chlorophyll Index. Along with these indices, Green Leaf Area Index is also considered for investigation. From the research outcome, Green Atmospherically Resistant Vegetation Index outperformed with all other indices by reaching the average accuracy value of 95.21%.

Keywords: Fuzzy C-Means clustering (FCM), neural network, Levenberg-Marquardt (LM) algorithm, vegetation indices

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Authors: Amelia Frickey, Timothy (TJ) Sheridan, Angelica Rossi, Bahar Aliakbarian

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The growth of large food supply chains demanded improved end-to-end traceability of food products, which has led to companies being increasingly interested in using smart technologies such as Radio Frequency Identification (RFID)-enabled packaging to track items. As technology is being widely used, there are several technological or economic issues that should be overcome to facilitate the adoption of this track-and-trace technology. One of the technological challenges of RFID technology is its sensitivity to different environmental form factors, including packaging materials and the content of the packaging. Although researchers have assessed the performance loss due to the proximity of water and aqueous solutions, there is still the need to further investigate the impacts of food products on the reading range of RFID tags. However, to the best of our knowledge, there are not enough studies to determine the correlation between RFID tag performance and food beverages properties. The goal of this project was to investigate the effect of the solution properties (pH and conductivity) and different packaging materials filled with food-like water-based solutions on the performance of an RFID tag. Three commercially available ultra high-frequency RFID tags were placed on three different bottles and filled with different concentrations of water-based solutions, including sodium chloride, citric acid, sucrose, and ethanol. Transparent glass, Polyethylneterephtalate (PET), and Tetrapak® were used as the packaging materials commonly used in the beverage industries. Tag readability (Theoretical Read Range, TRR) and sensitivity (Power on Tag Forward, PoF) were determined using an anechoic chamber. First, the best place to attach the tag for each packaging material was investigated using empty and water-filled bottles. Then, the bottles were filled with the food-like solutions and tested with the three different tags and the PoF and TRR at the fixed frequency of 915MHz. In parallel, the pH and conductivity of solutions were measured. The best-performing tag was then selected to test the bottles filled with wine, orange, and apple juice. Despite various solutions altering the performance of each tag, the change in tag performance had no correlation with the pH or conductivity of the solution. Additionally, packaging material played a significant role in tag performance. Each tag tested performed optimally under different conditions. This study is the first part of comprehensive research to determine the regression model for the prediction of tag performance behavior based on the packaging material and the content. More investigations, including more tags and food products, are needed to be able to develop a robust regression model. The results of this study can be used by RFID tag manufacturers to design suitable tags for specific products with similar properties.

Keywords: smart food packaging, supply chain management, food waste, radio frequency identification

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Authors: Julie Chuah Suan Choo

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Due to the continuous change in workforce and the demands of the global workplace, many employers had lamented that the majority of university graduates were not prepared in the key areas of employment such as critical thinking, writing, self-direction and global knowledge which are most needed for the purposes of promotion. Further, critical thinking skills are deemed as integral parts of transformational pedagogy which aims at having a more informed society. To add to this, literature teaching has recently been advocated for enhancing students’ critical thinking and reasoning. Thus this study explored the effects of incorporating a few strategies in teaching literature, namely a Shakespeare play, into a course design to enhance these skills. An experiment involving a pretest and posttest using the California Critical Thinking Skills Test (CCTST) were administered on 80 first-year students enrolled in the Bachelor of Arts programme who were randomly assigned into the control group and experimental group. For the next 12 weeks, the experimental group was given intervention which included guided in-class discussion with Socratic questioning skills, learning log to detect their weaknesses in logical reasoning; presentations and quizzes. The results of CCTST which included paired T-test using SPSS version 22 indicated significant differences between the two groups. Findings have significant implications on the course design as well as pedagogical practice in using literature to enhance students’ critical thinking skills.

Keywords: literature teaching, critical thinking, California critical thinking skills test (CCTST), course design

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Authors: Bin Liu

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MicroRNAs (miRNAs) are small non-coding RNA molecules, functioning in transcriptional and post-transcriptional regulation of gene expression. The discrimination of the real pre-miRNAs from the false ones (such as hairpin sequences with similar stem-loops) is necessary for the understanding of miRNAs’ role in the control of cell life and death. Since both their small size and sequence specificity, it cannot be based on sequence information alone but requires structure information about the miRNA precursor to get satisfactory performance. Kmers are convenient and widely used features for modeling the properties of miRNAs and other biological sequences. However, Kmers suffer from the inherent limitation that if the parameter K is increased to incorporate long range effects, some certain Kmer will appear rarely or even not appear, as a consequence, most Kmers absent and a few present once. Thus, the statistical learning approaches using Kmers as features become susceptible to noisy data once K becomes large. In this study, we proposed a Gapped k-mer approach to overcome the disadvantages of Kmers, and applied this method to the field of miRNA prediction. Combined with the structure status composition, a classifier called imiRNA-GSSC was proposed. We show that compared to the original imiRNA-kmer and alternative approaches. Trained on human miRNA precursors, this predictor can achieve an accuracy of 82.34 for predicting 4022 pre-miRNA precursors from eleven species.

Keywords: gapped k-mer, imiRNA-GSSC, microRNA precursor, support vector machine

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Authors: Shahla Ali

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In the context of promoting green infrastructure development, new opportunities are emerging to re-examine sustainable development practices. This paper presents an initial exploration of the development of community-investor dispute prevention and facilitation mechanisms in the context of the Belt and Road Initiative (BRI) spanning Asia, Africa, and Europe. Given the widescale impact of China’s multi-jurisdictional development initiative, learning how to coordinate with local communities is vital to realizing inclusive and sustainable growth. In the 20 years since the development of the first multilateral community-investor dispute resolution mechanism developed by the International Finance Centre/World Bank, much has been learned about public facilitation, community engagement, and dispute prevention during the early stages of major infrastructure development programs. This paper will explore initial findings as they relate to initiatives underway along the BRI within the Asian Infrastructure Investment Bank and the Asian Development Bank. Given the borderless nature of sustainability concerns, insights from diverse regions are critical to deepening insights into best practices. Drawing on a case-based methodology, this paper will explore the achievements, challenges, and lessons learned in community-investor dispute prevention and resolution for major infrastructure projects in the greater China region.

Keywords: law and development, dispute prevention, sustainable development, mitigation

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Authors: Margarida Porfírio Tomás, Paula Pereira, José Manuel Palma Oliveira

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The decline in employment rates across sectors like industry and construction is exacerbated by an aging workforce. This has far-reaching implications for the economy, including skills gaps, labour shortages, productivity challenges due to physical limitations, and workplace safety concerns. To sustain the workforce and pension systems, technology plays a pivotal role. Robots provide valuable support to human workers, and effective human-robot interaction is essential. FORTIS, a Horizon project, aims to address these challenges by creating a comprehensive Human-Robot Interaction (HRI) solution. This solution focuses on multi-modal communication and multi-aspect interaction, with a primary goal of maintaining a human-centric approach. By meeting the needs of both human workers and robots, FORTIS aims to facilitate efficient and safe collaboration. The project encompasses three key activities: 1) A Human-Centric Approach involving data collection, annotation, understanding human behavioural cognition, and contextual human-robot information exchange. 2) A Robotic-Centric Focus addressing the unique requirements of robots during the perception and evaluation of human behaviour. 3) Ensuring Human-Robot Trustworthiness through measures such as human-robot digital twins, safety protocols, and resource allocation. Factor Social, a project partner, will analyse psycho-physiological signals that influence human factors, particularly in hazardous working conditions. The analysis will be conducted using a combination of case studies, structured interviews, questionnaires, and a comprehensive literature review. However, the adoption of novel technologies, particularly those involving human-robot interaction, often faces hurdles related to acceptance. To address this challenge, FORTIS will draw upon insights from Social Sciences and Humanities (SSH), including risk perception and technology acceptance models. Throughout its lifecycle, FORTIS will uphold a human-centric approach, leveraging SSH methodologies to inform the design and development of solutions. This project received funding from European Union’s Horizon 2020/Horizon Europe research and innovation program under grant agreement No 101135707 (FORTIS).

Keywords: skills gaps, productivity challenges, workplace safety, human-robot interaction, human-centric approach, social sciences and humanities, risk perception

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Authors: Xiaolin Zeng, Lei Cheng, Zhirong Li, Xueping Liu

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Aiming at the problem of low accuracy and susceptibility to cultural relic diseases in the generation of high-resolution archaeology drawings by current image generation algorithms, an archaeology drawings generation algorithm based on a conditional generative adversarial network is proposed. An attention mechanism is added into the high-resolution image generation network as the backbone network, which enhances the line feature extraction capability and improves the accuracy of line drawing generation. A dual-branch parallel architecture consisting of two backbone networks is implemented, where the semantic translation branch extracts semantic features from orthophotographs of cultural relics, and the gradient screening branch extracts effective gradient features. Finally, the fusion fine-tuning module combines these two types of features to achieve the generation of high-quality and high-resolution archaeology drawings. Experimental results on the self-constructed archaeology drawings dataset of grotto temple statues show that the proposed algorithm outperforms current mainstream image generation algorithms in terms of pixel accuracy (PA), structural similarity (SSIM), and peak signal-to-noise ratio (PSNR) and can be used to assist in drawing archaeology drawings.

Keywords: archaeology drawings, digital heritage, image generation, deep learning

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Authors: Mohammed Khalil Ur Rahman, Mohammed Alsharon, Arshad Muktar, Zahid Shaik

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Any ailment can go into terminal stages, cancer being one such disease which is many times detected in latent stages. Cancer is often characterized by constitutional symptoms which are agonizing in nature which disturbs patients and their family as well. In order to relieve such intolerable symptoms treatment modality employed is known to be ‘Palliative Care’. The goal of palliative care is to enhance patient’s quality of life by relieving or rather reducing the distressing symptoms of patients such as pain, nausea/ vomiting, anorexia/loss of appetite, excessive salivation, mouth ulcers, weight loss, constipation, oral thrush, emaciation etc. which are due to the effect of disease or due to the undergoing treatment such as chemotherapy, radiation etc. Ayurveda and Unani as well as other traditional medicines is getting more and more international attention in recent years and Ayurveda and Unani holistic perspective of the disease, it seems that there are many herbs and herbomineral preparation which can be employed in the treatment of malignancy and also in palliative care. Though many of them have yet to be scientifically proved as anti-cancerous but there is definitely a positive lead that some of these medications relieve the agonising symptoms thereby making life of the patient easy. Health is viewed in Islam in a holistic way. One of the names of the Quran is al-shifa' meaning ‘that which heals’ or ‘the restorer of health’ to refer to spiritual, intellectual, psychological, and physical health. The general aim of medical science, according to Islam, is to secure and adopt suitable measures which, with Allah’s permission, help to preserve or restore the health of the human body. Islam motivates the Physician to view the patient as one organism. The patient has physical, social, psychological, and spiritual dimensions that must be considered in synthesis with an integrated, holistic approach. Aims & Objectives: - To suggest herbs which are mentioned in Ayurveda Unani with potential palliative activity in case of Cancer patients. - Most of tibb nabawi [Prophetic Medicine] is preventive medicine and must have been divinely inspired. - Spiritual Aspects of Healing: Prayer, dua, recitation of the Quran - Remembrance of Allah play a central role.Materials & Method: Literary review of the herbs supported with experiential evidence will be discussed. Discussion: On the basis of collected data subject will be discussed in length. Conclusion: Will be presented in paper.

Keywords: palliative care, holistic, Ayurvedic and Unani traditional system of medicine, Quran, hadith

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Authors: Zhang Shuqi, Liu Dan

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For the problems in intelligent network anomaly traffic detection models, such as low detection accuracy caused by the lack of training samples, poor effect with small sample attack detection, a classification model enhancement method, F-ACGAN(Flow Auxiliary Classifier Generative Adversarial Network) which introduces generative adversarial network and adversarial training, is proposed to solve these problems. Generating adversarial data with category labels could enhance the training effect and improve classification accuracy and model robustness. FACGAN consists of three steps: feature preprocess, which includes data type conversion, dimensionality reduction and normalization, etc.; A generative adversarial network model with feature learning ability is designed, and the sample generation effect of the model is improved through adversarial iterations between generator and discriminator. The adversarial disturbance factor of the gradient direction of the classification model is added to improve the diversity and antagonism of generated data and to promote the model to learn from adversarial classification features. The experiment of constructing a classification model with the UNSW-NB15 dataset shows that with the enhancement of FACGAN on the basic model, the classification accuracy has improved by 8.09%, and the score of F1 has improved by 6.94%.

Keywords: data imbalance, GAN, ACGAN, anomaly detection, adversarial training, data augmentation

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Authors: Smah Almotiri

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One of the most common fields of natural language processing (NLP) is sentimental analysis. The inferred feeling in the text can be successfully mined for various events using sentiment analysis. Twitter is viewed as a reliable data point for sentimental analytics studies since people are using social media to receive and exchange different types of data on a broad scale during the COVID-19 epidemic. The processing of such data may aid in making critical decisions on how to keep the situation under control. The aim of this research is to look at how sentimental states differed in a single geographic region during the lockdown at two different times.1162 tweets were analyzed related to the COVID-19 pandemic lockdown using keywords hashtags (lockdown, COVID-19) for the first sample tweets were from March 23, 2020, until April 23, 2020, and the second sample for the following year was from March 1, 2020, until April 4, 2020. Natural language processing (NLP), which is a form of Artificial intelligence, was used for this research to calculate the sentiment value of all of the tweets by using AFINN Lexicon sentiment analysis method. The findings revealed that the sentimental condition in both different times during the region's lockdown was positive in the samples of this study, which are unique to the specific geographical area of New Zealand. This research suggests applying machine learning sentimental methods such as Crystal Feel and extending the size of the sample tweet by using multiple tweets over a longer period of time.

Keywords: sentiment analysis, Twitter analysis, lockdown, Covid-19, AFINN, NodeJS

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Authors: Heba Salama, Barry Gibson, Jennifer Burr

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Introduction: It is often argued that better oral health leads to better wellbeing, and the goal of dental care is to improve wellbeing. Notwithstanding, to our best knowledge, there is a lack of evidence to support the relationship between oral health and wellbeing. Aim: The scoping review aims to examine current definitions of health and wellbeing as well as map the evidence to examine the relationship between oral health and wellbeing. Methods: The scoping review followed the Preferred Reporting Items for Systematic Reviews Extension for Scoping Review (PRISMA-ScR). A two-phase search strategy was followed because of the unmanageable number of hits returned. The first phase was to identify how well-being was conceptualised in oral health literacy, and the second phase was to search for extracted keywords. The extracted keywords were searched in four databases: PubMed, CINAHL, PsycINFO, and Web of Science. To limit the number of studies to a manageable amount, the search was limited to the open-access studies that have been published in the last five years (from 2018 to 2022). Results: Only eight studies (0.1%) of the 5455 results met the review inclusion criteria. Most of the included studies defined wellbeing based on the hedonic theory. And the Satisfaction with Life Scale is the most used. Although the research results are inconsistent, it has generally been shown that there is a weak or no association between oral health and wellbeing. Interpretation: The review revealed a very important point about how oral health literature uses loose definitions that have significant implications for empirical research. That results in misleading evidence-based conclusions. According to the review results, improving oral health is not a key factor in improving wellbeing. It appears that investing in oral health care to improve wellbeing is not a top priority to tell policymakers about. This does not imply that there should be no investment in oral health care to improve oral health. That could have an indirect link to wellbeing by eliminating the potential oral health-related barriers to quality of life that could represent the foundation of wellbeing. Limitation: Only the most recent five years (2018–2022), peer-reviewed English-language literature, and four electronic databases were included in the search. These restrictions were put in place to keep the volume of literature at a manageable level. This suggests that some significant studies might have been omitted. Furthermore, the study used a definition of wellbeing that is currently being evolved and might not everyone agrees with it. Conclusion: Whilst it is a ubiquitous argument that oral health is related to wellbeing, and this seems logical, there is little empirical evidence to support this claim. This question, therefore, requires much more detailed consideration. Funding: This project was funded by the Ministry of Higher Education and Scientific Research in Libya and Tripoli University.

Keywords: oral health, wellbeing, satisfaction, emotion, quality of life, oral health related quality of life

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Authors: Loukou Amoin Marie Djedri

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Financing is important for all terrorists – from the largest organizations in control of territories, to the smallest groups – not only for spreading fear through attacks, but also to finance the expansion of terrorist dogmas. These organizations pose serious threats to the international community. The disruption of terrorist financing aims to create a hostile environment for the growth of terrorism and to limit considerably the terrorist groups capacities. The World Bank (WB), together with the International Monetary Fund (IMF), decided to include in their scope the Fight against the money laundering and the financing of terrorism, in order to assist Member States in protecting their internal financial system from terrorism use and abuse and reinforcing their legal system. To do so, they have adopted the Anti-Money Laundering /Combating Financing of Terrorism (AML/CFT) standards that have been set up by the Financial Action Task Force. This set of standards, recognized as the international standards for anti-money laundering and combating the financing of terrorism, has to be implemented by States Members in order to strengthen their judicial system and relevant national institutions. However, we noted that, to date, some States Members still have significant AML/CFT deficiencies, which can constitute serious threats not only to the country’s economic stability but also for the global financial system. In addition, studies stressed out that repressive measures are more implemented by countries than preventive measures, which could be an important weakness in a state security system. Furthermore, we noticed that the AML/CFT standards evolve slowly, while techniques used by terrorist networks keep developing. The goal of the study is to show how to enhance the AML/CFT global compliance through the work of the IMF and the WB, to help member states to consolidate their financial system. To encourage and ensure the effectiveness of these standards, a methodology for assessing the compliance with the AML/CFT standards has been created to follow up the concrete implementation of these standards and to provide accurate technical assistance to countries in need. A risk-based approach has also been adopted as a key component of the implementation of the AML/CFT Standards, with the aim of strengthening the efficiency of the standards. Instead, we noted that the assessment is not efficient in the process of enhancing AML/CFT measures because it seems to lack of adaptation to the country situation. In other words, internal and external factors are not enough taken into account in a country assessment program. The purpose of this paper is to analyze the AML/CFT regime in the fight against the financing of terrorism and to find lasting solutions to achieve the global AML/CFT compliance. The work of all the organizations involved in this combat is imperative to protect the financial network and to lead to the disintegration of terrorist groups in the future.

Keywords: AML/CFT standards, financing of terrorism, international financial institutions, risk-based approach

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Authors: Azza El-Medany, Jamila El-Medany

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Residential and agricultural pesticide use is widespread in the world. Their extensive and indiscriminative use, in addition with their ability to interact with biological systems other than their primary targets constitute a health hazards to both humans and animals. The toxic effects of pesticides include alterations in metabolism; there is a lack of knowledge that organophosphates can cause pancreatic toxicity. The primary goal of this work is to study the effects of chronic exposure to Diazinon an organophosphate used in agriculture on pancreatic tissues and evaluate the ameliorating effect of Mesna as antioxidant on the toxicity of Diazinon on pancreatic tissues.40 adult male rats, their weight ranged between 300-350 g. The rats were classified into three groups; control (10 rats) was received corn oil at a dose of 1 0 mg/kg/day by gavage once a day for 2 months. Diazinon (15 rats) was received Diazinon at a dose of 10 mg/kg/day dissolved in corn oil by gavage once a day for 2 months. Treated group (15 rats), were received Mesna 180mg/kg once a week by gavage 15 minutes before administration of Diazinon for 2 months. At the end of the experiment, animals were anesthetized, blood samples were taken by cardiac puncture for glucose and insulin assays and pancreas was removed and divided into 3 portions; first portion for histopathological study; second portion for ultrastructural study; third portion for biochemical study using Elisa Kits including determination of malondialdehyde (MDA), tumor necrosis factor α (TNF-α), myeloperoxidase activity (MPO), interleukin 1β (IL-1β). A significant increase in the levels of MDA, TNF-α, MPO activity, IL-1β, serum glucose levels in the toxicated group with Diazinon were observed, while a significant reduction was noticed in GSH in serum insulin levels. After treatment with Mesna a significant reduction was observed in the previously mentioned parameters except that there was a significant rise in GSH in insulin levels. Histopathological and ultra-structural studies showed destruction in pancreatic tissues and β cells were the most affected cells among the injured islets as compared with the control group. The current study try to spot light about the effects of chronic exposure to pesticides on vital organs as pancreas also the role of oxidative stress that may be induced by them in evoking their toxicity. This study shows the role of antioxidant drugs in ameliorating or preventing the toxicity. This appears to be a promising approach that may be considered as a complementary treatment of pesticide toxicity.

Keywords: Diazinon, reduced glutathione, myeloperoxidase activity, tumor necrosis factor α, Mesna

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Authors: Songul Cinaroglu

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Background: Random Forest is an efficient, multi-class machine learning method using for classification, regression and other tasks. This method is operating by constructing each tree using different bootstrap sample of the data. Determining the number of trees in random forests is an open question in the literature for studies about improving classification performance of random forests. Aim: The aim of this study is to analyze whether there is an optimal number of trees in Random Forests and how performance of Random Forests differ according to increase in number of trees using sample health data sets in R programme. Method: In this study we analyzed the performance of Random Forests as the number of trees grows and doubling the number of trees at every iteration using “random forest” package in R programme. For determining minimum and optimal number of trees we performed Mc Nemar test and Area Under ROC Curve respectively. Results: At the end of the analysis it was found that as the number of trees grows, it does not always means that the performance of the forest is better than forests which have fever trees. In other words larger number of trees only increases computational costs but not increases performance results. Conclusion: Despite general practice in using random forests is to generate large number of trees for having high performance results, this study shows that increasing number of trees doesn’t always improves performance. Future studies can compare different kinds of data sets and different performance measures to test whether Random Forest performance results change as number of trees increase or not.

Keywords: classification methods, decision trees, number of trees, random forest

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Authors: Hussein Alahmer, Amr Ahmed

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Liver cancer is one of the common diseases that cause the death. Early detection is important to diagnose and reduce the incidence of death. Improvements in medical imaging and image processing techniques have significantly enhanced interpretation of medical images. Computer-Aided Diagnosis (CAD) systems based on these techniques play a vital role in the early detection of liver disease and hence reduce liver cancer death rate.  This paper presents an automated CAD system consists of three stages; firstly, automatic liver segmentation and lesion’s detection. Secondly, extracting features. Finally, classifying liver lesions into benign and malignant by using the novel contrasting feature-difference approach. Several types of intensity, texture features are extracted from both; the lesion area and its surrounding normal liver tissue. The difference between the features of both areas is then used as the new lesion descriptors. Machine learning classifiers are then trained on the new descriptors to automatically classify liver lesions into benign or malignant. The experimental results show promising improvements. Moreover, the proposed approach can overcome the problems of varying ranges of intensity and textures between patients, demographics, and imaging devices and settings.

Keywords: CAD system, difference of feature, fuzzy c means, lesion detection, liver segmentation

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Authors: Siddharth Sarma, Ayush Majumdar, Nidhi Sabu, Mufaddal Jiruwaala, Shilpa Paygude

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Digital Elevation Models (DEMs) are digital representations of the Earth’s topography, which include information about the elevation, slope, aspect, and other terrain attributes. DEMs play a crucial role in various applications, including terrain analysis, urban planning, and environmental modeling. In this paper, TerraEnhance is proposed, a distinct approach for high-resolution DEM generation using Generative Adversarial Networks (GANs) combined with Real-ESRGANs. By learning from a dataset of low-resolution DEMs, the GANs are trained to upscale the data by 10 times, resulting in significantly enhanced DEMs with improved resolution and finer details. The integration of Real-ESRGANs further enhances visual quality, leading to more accurate representations of the terrain. A post-processing layer is introduced, employing high-pass filtering to refine the generated DEMs, preserving important details while reducing noise and artifacts. The results demonstrate that TerraEnhance outperforms existing methods, producing high-fidelity DEMs with intricate terrain features and exceptional accuracy. These advancements make TerraEnhance suitable for various applications, such as terrain analysis and precise environmental modeling.

Keywords: DEM, ESRGAN, image upscaling, super resolution, computer vision

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Authors: Shizra Waris, Bilal Shoaib, Munib Ahmad

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Background; The using of clinical decision support systems (CDSSs) may recover unceasing disease organization, which requires regular visits to multiple health professionals, treatment monitoring, disease control, and patient behavior modification. The objective of this survey is to determine if these CDSSs improve the processes of unceasing care including diagnosis, treatment, and monitoring of diseases. Though artificial intelligence is not a new idea it has been widely documented as a new technology in computer science. Numerous areas such as education business, medical and developed have made use of artificial intelligence Methods: The survey covers articles extracted from relevant databases. It uses search terms related to information technology and viral hepatitis which are published between 2000 and 2016. Results: Overall, 80% of studies asserted the profit provided by information technology (IT); 75% of learning asserted the benefits concerned with medical domain;25% of studies do not clearly define the added benefits due IT. The CDSS current state requires many improvements to hold up the management of liver diseases such as HCV, liver fibrosis, and cirrhosis. Conclusion: We concluded that the planned model gives earlier and more correct calculation of hepatitis B and it works as promising tool for calculating of custom hepatitis B from the clinical laboratory data.

Keywords: detection, hapataties, observation, disesese

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Authors: Huicong Jia, Donghua Pan

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As a key component of disaster reduction management, disaster emergency relief and reconstruction is an important process. Based on disaster system theory, this study analyzed the Jiangsu tornado from the formation mechanism of disasters, through to the economic losses, loss of life, and social infrastructure losses along the tornado disaster chain. The study then assessed the emergency relief and reconstruction efforts, based on an analytic hierarchy process method. The results were as follows: (1) An unstable weather system was the root cause of the tornado. The potentially hazardous local environment, acting in concert with the terrain and the river network, was able to gather energy from the unstable atmosphere. The wind belt passed through a densely populated district, with vulnerable infrastructure and other hazard-prone elements, which led to an accumulative disaster situation and the triggering of a catastrophe. (2) The tornado was accompanied by a hailstorm, which is an important triggering factor for a tornado catastrophe chain reaction. (3) The evaluation index (EI) of the emergency relief and reconstruction effect for the ‘‘6.23’’ tornado disaster in Yancheng was 91.5. Compared to other relief work in areas affected by disasters of the same magnitude, there was a more successful response than has previously been experienced. The results provide new insights for studies of disaster systems and the recovery measures in response to tornado catastrophe in China.

Keywords: China, disaster system, emergency relief, tornado catastrophe

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Authors: Weiming Hu, Xu Li, Xiaonan Li, Zhong Xu, Li Yuan, Xuan Dong

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Maneuver decision-making plays a critical role in high-performance intelligent driving. This paper proposes a risk assessment-based decision-making network (RADMN) to address the problem of driving strategy for the commercial vehicle. RADMN integrates two networks, aiming at identifying the risk degree of collision and rollover and providing decisions to ensure the effectiveness and reliability of driving strategy. In the risk assessment module, risk degrees of the backward collision, forward collision and rollover are quantified for hazard recognition. In the decision module, a deep reinforcement learning based on multi-objective optimization (DRL-MOO) algorithm is designed, which comprehensively considers the risk degree and motion states of each traffic participant. To evaluate the performance of the proposed framework, Prescan/Simulink joint simulation was conducted in highway scenarios. Experimental results validate the effectiveness and reliability of the proposed RADMN. The output driving strategy can guarantee the safety and provide key technical support for the realization of autonomous driving of commercial vehicles.

Keywords: decision-making strategy, risk assessment, multi-objective optimization, commercial vehicle

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Authors: Aklima Jesmin, Ubaidur Rob, M. Ashrafur Rahman

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Rohingya population of Arakan state in Myanmar are one the most persecuted ethnic minorities in this 21st century. According to the Universal Declaration of Human Rights (UDHR), all human beings are born free, equal in dignity and rights. However, these populations are systematically excluded from this universal proclamation of human rights as they are Rohingya, which signify ‘other’. Based on the accessible and available literatures about Rohingya issue, this study firstly found there are chronological pattern of human rights violations against the ethnic Rohingya which follows the pathology of the Holocaust in this 21st century of human civilization. These violations have been possible due to modern technology, bureaucracy which has been performed through authorization, routinization and dehumanization; not only in formal institutions but in the society as a whole. This kind of apparently never-ending situation poses any author with the problem of available many scientific articles. The most important sources are, therefore the international daily newspapers, social media and official webpage of the non-state actors for nitty-gritty day to day update. Although it challenges the validity and objectivity of the information, but to address the critical ongoing human rights violations against Rohingya population can become a base for further work on this issue. One of the aspects of this paper is to accommodate all the social movements since August 2017 to date. The findings of this paper is that even though it seemed only human rights violations occurred against Rohingya historically but, simultaneously the process of social movements had also started, can be traced more after the military campaign in 2017. Therefore, the Rohingya crisis can be conceptualized within one ‘campaign’ movement for justice, not as episodic events, especially within the Political Process Model than any other social movement theories. This model identifies that the role of international political movements as well as the role of non-state actors are more powerful than any other episodes of violence conducted against Rohinyga in reframing issue, blaming and shaming to Myanmar government and creating the strategic opportunities for social changes. The lack of empowerment of the affected Rohingya population has been found as the loop to utilize this strategic opportunity. Their lack of empowerment can also affect their capacity to reframe their rights and to manage the campaign for their justice. Therefore, this should be placed at the heart of the international policy agenda within the broader socio-political movement for the justice of Rohingya population. Without ensuring human rights of Rohingya population, achieving the promise of the united nation’s sustainable development goals - no one would be excluded – will be impossible.

Keywords: civilization, holocaust, human rights violation, military campaign, political process model, Rohingya population, sustainable development goal, social justice, social movement, strategic opportunity

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Authors: Ruwan Gunawardane

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This paper attempts to emphasize the benefits of conducting an intensive course in English for university entrants. In the Sri Lankan university context, an intensive course in English is usually conducted amidst various obstacles. In the 1970s and 1980s, undergraduates had intensive programmes in English for two to three months. Towards the end of the 1990s, a programme called General English Language Training (GELT) was conducted for the new students, and it was done outside universities before they entered their respective universities. Later it was not conducted, and that also resulted in students’ poor performance in English at university. However, having understood its importance, an eight week long intensive course in English was conducted for the new intake of the Faculty of Science, University of Ruhuna. As the findings show, the students heavily benefited from the programme. More importantly, they had the opportunity to refresh their knowledge of English gained at school and private institutions while gaining new knowledge. Another advantage was that they had plenty of time to enjoy learning English since the learners had adequate opportunities to carry out communicative tasks and the course was not exam-oriented, which reduced their fear of making mistakes in English considerably. The data was collected through an open-ended questionnaire given to 60 students, and their oral feedback was also taken into consideration. In addition, a focus group interview with 6 teachers was also conducted to get an idea about their experience and perception. The data were qualitatively analyzed. The findings suggest that an intensive programme in English undoubtedly lays a good foundation for the students’ academic career at university.

Keywords: intensive course, English, teachers, undergraduates, experience, perception

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Authors: Olga Maksakova

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A work with unconscious patients after acute brain damages besides special knowledge and practical skills of all the participants requires a very specific organization. A lot of said about team approach in neurorehabilitation, usually as for outpatient mode. Rehabilitologists deal with fixed patient problems or deficits (motion, speech, cognitive or emotional disorder). Team-building means superficial paradigm of management psychology. Linear mode of teamwork fits casual relationships there. Cases with deep altered states of consciousness (vegetative states, coma, and confusion) require non-linear mode of teamwork: recovery of consciousness might not be the goal due to phenomenon uncertainty. Rehabilitation team as Semi-open Complex System includes the patient as a part. Patient's response pattern becomes formed not only with brain deficits but questions-stimuli, context, and inquiring person. Teamwork is sourcing of phenomenology knowledge of patient's processes as Third-person approach is replaced with Second- and after First-person approaches. Here is a chance for real-time change. Patient’s contacts with his own body and outward things create a basement for restoration of consciousness. The most important condition is systematic feedbacks to any minimal movement or vegetative signal of the patient. Up to now, recovery work with the most severe contingent is carried out in the mode of passive physical interventions, while an effective rehabilitation team should include specially trained psychologists and psychotherapists. It is they who are able to create a network of feedbacks with the patient and inter-professional ones building up the team. Characteristics of ‘Team-Patient’ system (TPS) are energy, entropy, and complexity. Impairment of consciousness as the absence of linear contact appears together with a loss of essential functions (low energy), vegetative-visceral fits (excessive energy and low order), motor agitation (excessive energy and excessive order), etc. Techniques of teamwork are different in these cases for resulting optimization of the system condition. Directed regulation of the system complexity is one of the recovery tools. Different signs of awareness appear as a result of system self-organization. Joint meetings are an important part of teamwork. Regular or event-related discussions form the language of inter-professional communication, as well as the patient's shared mental model. Analysis of complex communication process in TPS may be useful for creation of the general theory of consciousness.

Keywords: rehabilitation team, urgent rehabilitation, severe brain damage, consciousness disorders, complex system theory

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Authors: Mahfoodh Saleh Al Sabbagh, Venkoba Rao

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There is plenty of research, both in academic and consultancy circles, about the importance and benefits of employee engagement and customer engagement and how it gives organization an opportunity to reduce variability and improve performance. Customer engagement is directly related to the engagement level of the organization's employees. It is therefore important to measure both. This research drawing from the work of Human Sigma by Fleming and Asplund, attempts to assess engagement level of customer and employees - the human systems of business - in an educational setup. Student is important to an educational institute and is a customer to be served efficiently and effectively. Considering student as customer and faculty as employees serving them, in–depth interviews were conducted to analyze the relationship between faculty and student engagement in two leading colleges in Oman, one from private sector and another from public sector. The study relied mainly on secondary data sources to understand the concept of engagement. However, the search of secondary sources was extensive to compensate the limited primary data. The results indicate that high faculty engagement is likely to lead to high student engagement. Engaged students were excited about learning, loved the feeling of they being cared as a person by their faculty and advocated the organization to other. The interaction truly represents an opportunity to build emotional connection to the organization. This study could be of interest to organizations interest in building and maintaining engagement with employees and customers.

Keywords: customer engagement, consumer psychology, strategy, educational institutes

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Authors: Ming-Dong Wang, Abigail F. Ruby, Michelle E. Ross

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Methylphenidate is a first-line treatment drug for attention deficit hyperactivity disorder (ADHD), a common mental health disorder in children and adolescents. Over the last several decades, the rate of children and adolescents using ADHD medication has been increasing in many countries. A recent study found that the prevalence of ADHD medication use among children aged 3-18 years increased in 13 different world regions between 2001 and 2015, where the absolute increase ranged from 0.02 to 0.26% per year. The goal of this study was to examine the use of methylphenidate in Canadian children and its associated adverse reactions. Methylphenidate use information among young Canadians aged 0-14 years was extracted from IQVIA data on prescriptions dispensed by pharmacies between April 2014 and June 2020. The adverse reaction information associated with methylphenidate use was extracted from the Canada Vigilance database for the same time period. Methylphenidate use trends were analyzed based on sex, age group (0-4 years, 5-9 years, and 10-14 years), and geographical location (province). The common classes of adverse reactions associated with methylphenidate use were sorted, and the relative risks associated with methylphenidate use as compared with two second-line amphetamine medications for ADHD were estimated. This study revealed that among Canadians aged 0-14 years, every 100 people used about 25 prescriptions (or 23,000 mg) of methylphenidate per year during the study period, and the use increased with time. Boys used almost three times more methylphenidate than girls. The amount of drug used was inversely associated with age: Canadians aged 10-14 years used nearly three times as many drugs compared to those aged 5-9 years. Seasonal methylphenidate use patterns were apparent among young Canadians, but the seasonal trends differed among the three age groups. Methylphenidate use varied from region to region, and the highest methylphenidate use was observed in Quebec, where the use of methylphenidate was at least double that of any other province. During the study period, Health Canada received 304 adverse reaction reports associated with the use of methylphenidate for Canadians aged 0-14 years. The number of adverse reaction reports received for boys was 3.5 times higher than that for girls. The three most common adverse reaction classes were psychiatric disorders, nervous system disorders and injury, poisoning procedural complications. The number one commonly reported adverse reaction for boys was aggression (11.2%), while for girls, it was a tremor (9.6%). The safety profile in terms of adverse reaction classes associated with methylphenidate use was similar to that of the selected control products. Methylphenidate is a commonly used pharmaceutical product in young Canadians, particularly in the province of Quebec. Boys used approximately three times more of this product as compared to girls. Future investigation is needed to determine what factors are associated with the observed geographic variations in Canada.

Keywords: adverse reaction risk, methylphenidate, prescription trend, use variation

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Authors: Martina Katalin Szabó, István Üveges

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In this paper, the usage of negative emotive words is examined on the basis of a large Hungarian twitter-database via NLP methods. The data is analysed from a gender point of view, as well as changes in language usage over time. The term negative emotive word refers to those words that, on their own, without context, have semantic content that can be associated with negative emotion, but in particular cases, they may function as intensifiers (e.g. rohadt jó ’damn good’) or a sentiment expression with positive polarity despite their negative prior polarity (e.g. brutális, ahogy ez a férfi rajzol ’it’s awesome (lit. brutal) how this guy draws’. Based on the findings of several authors, the same phenomenon can be found in other languages, so it is probably a language-independent feature. For the recent analysis, 67783 tweets were collected: 37818 tweets (19580 tweets written by females and 18238 tweets written by males) in 2016 and 48344 (18379 tweets written by females and 29965 tweets written by males) in 2021. The goal of the research was to make up two datasets comparable from the viewpoint of semantic changes, as well as from gender specificities. An exhaustive lexicon of Hungarian negative emotive intensifiers was also compiled (containing 214 words). After basic preprocessing steps, tweets were processed by ‘magyarlanc’, a toolkit is written in JAVA for the linguistic processing of Hungarian texts. Then, the frequency and collocation features of all these words in our corpus were automatically analyzed (via the analysis of parts-of-speech and sentiment values of the co-occurring words). Finally, the results of all four subcorpora were compared. Here some of the main outcomes of our analyses are provided: There are almost four times fewer cases in the male corpus compared to the female corpus when the negative emotive intensifier modified a negative polarity word in the tweet (e.g., damn bad). At the same time, male authors used these intensifiers more frequently, modifying a positive polarity or a neutral word (e.g., damn good and damn big). Results also pointed out that, in contrast to female authors, male authors used these words much more frequently as a positive polarity word as well (e.g., brutális, ahogy ez a férfi rajzol ’it’s awesome (lit. brutal) how this guy draws’). We also observed that male authors use significantly fewer types of emotive intensifiers than female authors, and the frequency proportion of the words is more balanced in the female corpus. As for changes in language usage over time, some notable differences in the frequency and collocation features of the words examined were identified: some of the words collocate with more positive words in the 2nd subcorpora than in the 1st, which points to the semantic change of these words over time.

Keywords: gender differences, negative emotive words, semantic changes over time, twitter

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Authors: Ehsan Ahmed Yahia

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Introduction: The nursing role in nutrition screening and assessing hospitalized patients is important. Malnutrition is a common and costly problem, particularly among hospitalized patients, and can have an adverse effect on the healing process. The study's goal is to assess the prevalence of malnutrition among adult hospitalized orthopedic patients and to detect the barriers to the nutrition screening process. Aim of the study: This study aimed to (a) assess the prevalence of malnutrition in hospitalized orthopedic patients and (b) evaluate the relationship between malnutrition and selected clinical outcomes. Material and Methods: This prospective field study was conducted for three months between 03/2022 and 06/2022 in the selected orthopedic departments in a teaching hospital affiliated withCairo University, Egypt. with a total number of one hundred twenty (120) patients. Patients' assessment included checking for malnutrition using the Nutritional Risk Screening Questionnaire. Patients at risk for malnourishment were defined as NRS score ≥ 3. Clinical outcomes under consideration included 1) length of hospitalization, 2) mobilization after surgery and conservative treatment, and 3) rate of adverse events. Results: This study found that malnutrition is a significant problem among patients hospitalized in an orthopedic ward. The prevalence of malnutrition was the highest in patients with lumbar spine and pelvis fractures, followed by the proximal femur and proximal humerus fractures. Patients at risk for malnutrition had significantly prolonged hospitalization, delayed postoperative mobilization, and increased incidence of adverse events.27.8% of the study sample were at risk for malnutrition. The highest prevalence of malnourishment was found in Septic Surgery with 32%, followed by Traumatology with 19.6% and Arthroplasty with 15.3%. A higher prevalence of malnutrition was detected among patients with typical fractures, such as lumbar spine and pelvis (46.7%), proximal femur (34.4%), and proximal humeral (23.7%) fractures. Additionally, patients at risk for malnutrition showed prolonged hospitalization (14.7 ± 11.1 vs. 21.2 ± 11.7 days), delayed postoperative mobilization (2.3 ± 2.9 vs. 4.1 ± 4.9 days), and delayed to mobilize after conservative treatment (1.1 ± 2.7 vs. 1.8 ± 1.9 days). A significant statistical correlation of NRS with individual parameters (Spearman's rank correlation, p < 0.05) was observed. The rate of adverse incidents in patients at risk for malnutrition was significantly higher than that of patients with a regular nutritional status (37.2% vs. 21.1%, p < 0.001). Conclusions: Our results indicate that the prevalence of malnutrition in surgical patients is significant. The nutritional status of patients with typical fractures is especially at risk. Prolonged hospitalization, delayed postoperative mobilization, and delayed mobilization after conservative treatment is significantly associated with malnutrition. In addition, the incidence of adverse events in patients at risk for malnutrition is significantly higher.

Keywords: malnutrition, nutritional risk screening, surgery, nursing, orthopedic nurse

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Authors: Abhijeet Ostawal, Parmjit Lall

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The run times for a large strategic model that we were managing had become too long leading to delays in project delivery, increased costs and loss in productivity. Software developers are continuously working towards developing more efficient tools by changing their algorithms and processes. The issue faced by our team was how do you apply the latest technologies on validated existing models which are based on much older versions of software that do not have the latest software capabilities. The multi-model transport model that we had could only be run in sequential assignment order. Recent upgrades to the software now allowed the assignment to be run in parallel, a concept called parallelization. Parallelization is a Python script working only within the latest version of the software. A full model transfer to the latest version was not possible due to time, budget and the potential changes in trip assignment. This article is to show the method to adapt and update the Python script in such a way that it can be used in older software versions by calling the latest version and then recalling the old version for assignment model without affecting the results. Through a process of trial-and-error run time savings of up to 30-40% have been achieved. Assignment results were maintained within the older version and through this learning process we’ve applied this methodology to other even older versions of the software resulting in huge time savings, more productivity and efficiency for both client and consultant.

Keywords: model run time, demand model, parallelisation, python scripting

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Authors: D. M. Lewis, L. Frisby, U. Stead

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Objective: Many patients are receiving invasive treatments in acute care or are dying in hospital without having had comprehensive goals of care conversations. Some of these treatments may not align with the patient’s wishes, may be futile, and may cause unnecessary suffering. While many staff may recognize the benefits of engaging patients and families in Serious Illness Conversations (a goal of care framework developed by Ariadne Labs in Boston), few staff feel confident and/or competent in having these conversations in acute care. Another barrier to having these conversations may be due to a lack of incorporation in the current workflow. An educational exercise, titled the Two Question Challenge, was initiated on four medical units across two Vancouver Coastal Health (VCH) hospitals in attempt to engage the entire interdisciplinary team in asking patients and families questions around goals of care and to improve the documentation of these expressed wishes and preferences. Methods: Four acute care units across two separate hospitals participated in the Two Question Challenge. On each unit, over the course of two eight-hour shifts, all members of the interdisciplinary team were asked to select at least two questions from a selection of nine goals of care questions. They were asked to pose these questions of a patient or family member throughout their shift and then asked to document their conversations in a centralized Advance Care Planning/Goals of Care discussion record in the patient’s chart. A visual representation of conversation outcomes was created to demonstrate to staff and patients the breadth of conversations that took place throughout the challenge. Staff and patients were interviewed about their experiences throughout the challenge. Two palliative approach leads remained present on the units throughout the challenge to support, guide, or role model these conversations. Results: Across four acute care medical units, 47 interdisciplinary staff participated in the Two Question Challenge, including nursing, allied health, and a physician. A total of 88 questions were asked of patients, or their families around goals of care and 50 newly documented goals of care conversations were charted. Two code statuses were changed as a result of the conversations. Patients voiced an appreciation for these conversations and staff were able to successfully incorporate these questions into their daily care. Conclusion: The Two Question Challenge proved to be an effective way of having teams explore the goals of care of patients and families in an acute care setting. Staff felt that they gained confidence and competence. Both staff and patients found these conversations to be meaningful and impactful and felt they were notably different from their usual interactions. Documentation of these conversations in a centralized location that is easily accessible to all care providers increased significantly. Application of the Two Question Challenge in non-medical units or other care settings, such as long-term care facilities or community health units, should be explored in the future.

Keywords: advance care planning, goals of care, interdisciplinary, palliative approach, serious illness conversations

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Authors: Freja Rydahl Rasmussen, Naja Villadsen, Stig Koust

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Air purifiers have become widely implemented in a wide range of settings, including households, schools, institutions, and hospitals, as they tackle the pressing issue of indoor air pollution. With their ability to enhance indoor air quality and create healthier environments, air purifiers are particularly vital when ventilation options are limited. These devices incorporate a diverse array of technologies, including HEPA filters, active carbon filters, UV-C light, photocatalytic oxidation, and ionizers, each designed to combat specific pollutants and improve air quality within enclosed spaces. However, the safety of air purifiers has not been investigated thoroughly, and many questions still arise when applying them. Certain air purification technologies, such as UV-C light or ionization, can unintentionally generate undesirable byproducts that can negatively affect indoor air quality and health. It is well-established that these technologies can inadvertently generate nanoparticles or convert common gaseous compounds into harmful ones, thus exacerbating air pollution. However, the formation of byproducts can vary across products, necessitating further investigation. There is a particular concern about the formation of the carcinogenic substance formaldehyde from common gases like acetone. Many air purifiers use mechanical filtration to remove particles, dust, and pollen from the air. Filters need to be replaced periodically for optimal efficiency, resulting in an additional cost for end-users. Currently, there are no guidelines for filter lifespan, and replacement recommendations solely rely on manufacturers. A market screening revealed that manufacturers' recommended lifespans vary greatly (from 1 month to 10 years), and there is a need for general recommendations to guide consumers. Activated carbon filters are used to adsorb various types of chemicals that can pose health risks or cause unwanted odors. These filters have a certain capacity before becoming saturated. If not replaced in a timely manner, the adsorbed substances are likely to be released from the filter through off-gassing or losing adsorption efficiency. The goal of this study is to investigate the lifespan of filters as well as investigate the potentially harmful effects of air purifiers. Understanding the lifespan of filters used in air purifiers and the potential formation of harmful byproducts is essential for ensuring their optimal performance, guiding consumers in their purchasing decisions, and establishing industry standards for safer and more effective air purification solutions. At this time, a selection of air purifiers has been chosen, and test methods have been established. In the following 3 months, the tests will be conducted, and the results will be ready for presentation later.

Keywords: air purifiers, activated carbon filters, byproducts, clean air, indoor air quality

Procedia PDF Downloads 75