Search results for: Adult dataset

Authors: Li Zhou, Yanmei Fang

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With current technology, images and videos can be obtained more easily than ever. It is so easy to manipulate these digital multimedia information when obtained, and that the content or source of the image and video could be easily tampered. In this paper, we propose to identify the image and video frame by the texture-based approach, e.g. Markov Transition Probability (MTP), which is in space domain, DCT domain and DWT domain, respectively. In the experiment, image and video frame database is constructed, and is used to train and test the classifier Support Vector Machine (SVM). Experiment results show that the texture-based approach has good performance. In order to verify the experiment result, and testify the universality and robustness of algorithm, we build a random testing dataset, the random testing result is in keeping with above experiment.

Keywords: multimedia forensics, video frame, LBP, MTP, SVM

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Authors: Yufen Qin

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Text sentiment transfer is an important branch of text style transfer. The goal is to generate text with another sentiment attribute based on a text with a specific sentiment attribute while maintaining the content and semantic information unrelated to sentiment unchanged in the process. There are currently two main challenges in this field: no parallel corpus and text attribute entanglement. In response to the above problems, this paper proposed a novel solution: Mask-Prompt-Rerank. Use the method of masking the sentiment words and then using prompt regeneration to transfer the sentence sentiment. Experiments on two sentiment benchmark datasets and one formality transfer benchmark dataset show that this approach makes the performance of small pre-trained language models comparable to that of the most advanced large models, while consuming two orders of magnitude less computing and memory.

Keywords: language model, natural language processing, prompt, text sentiment transfer

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Authors: Ali Kirkbas

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R peaks in an electrocardiogram (ECG) are signs of cardiac activity in individuals that reveal valuable information about cardiac abnormalities, which can lead to mortalities in some cases. This paper examines the problem of detecting R-peaks in ECG signals, which is a two-class pattern classification problem in fact. To handle this problem with a reliable high accuracy, we propose to use the common vector approach which is a successful machine learning algorithm. The dataset used in the proposed method is obtained from MIT-BIH, which is publicly available. The results are compared with the other popular methods under the performance metrics. The obtained results show that the proposed method shows good performance than that of the other. methods compared in the meaning of diagnosis accuracy and simplicity which can be operated on wearable devices.

Keywords: ECG, R-peak classification, common vector approach, machine learning

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Authors: Sohil I. Alqazlan

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Introduction and Objectives: There is limited research focusing on young adults with intellectual disabilities (ID) and their experiences after finishing compulsory education, especially in the Middle Eastern/Arab countries. This paper aims to further understand the lives of young adults with ID in Riyadh [the capital city of Saudi Arabia], particularly as they go on to access Post-Secondary Education [PSE]. As part of this study, it is important to understand the roles of high schools in Riyadh in terms of preparing their students for post-school life. To achieve this, the researcher has asked Saudi Arabia’s Ministry of Education to provide student transition plans (TPs) for post-school opportunities. However, and unfortunately, high schools in Riyadh do not use transition plans for their students. Therefore, the researcher has requested individual education plans (IEPs) for students with ID in their final year at high school to find the type of support the students had regarding both their long- and short-term goals that might help them access PSE or the labour market. Methods: The researcher analysed 10 IEPs of students in their final year at high school. To achieve the aim of the study, the researcher compared these IEPs with expectations set out in the official IEP framework of the MoE in Saudi Arabia, such as collaboration on the IEP sample and the focus on adult life. By analysing the students’ IEPs in terms of various goals, this study attempts to highlight skills that might offer students more independence after finishing compulsory education and going on to PSE. Results: Unfortunately, communication between IEP team members proved persistently absent in the sample. This was clear from the fact that none of the team members, apart from the SEN teachers, had signed any of the IEPs. Thus, none of the daily or weekly goals outlined were sent to parents to review at home. As a result of this, there were no goals in the IEPs that clearly referred to PSE. However, some long-term goals were set which might help those with ID become more independent in their adult life. For example, in the IEPs, which dealt with computer skills, the student had goals related to using Microsoft Word. Finally, just one goal of these IEPs set an important independent skill for the young adults with ID: “the student will learn how to use public transportation”. Conclusions: From analysing the ten IEPs, it was clear that SEN teachers in Riyadh schools were working without any help from other professionals. The students with ID, as well as their families, were not consulted on their views on important goals. Therefore, more work needs to be done with the students regarding their transition to PSE, perhaps by building partnerships between high schools and potential PSE institutions. Finally, more PSE programmes and a higher level of employer awareness could help create a bridge for students transferring from high school to PSE. Schools could also focus their IEP goals towards specific PSE programmes the student might attend, which could increase their chances of success.

Keywords: high school, post-secondary education, PSE, students with intellectual disabilities

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Authors: Ammar Boudaka, Maryam Al-Suleimani, Hajar BaOmar, Intisar Al-Lawati, Fahad Zadjali

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Background: Hypertension is increasingly becoming a matter of medical and public health importance. The maintenance of normal blood pressure requires a balance between cardiac output and total peripheral resistance. The endothelium, through the release of vasodilating factors, plays an important role in the control of total peripheral resistance and hence blood pressure homeostasis. Transient Receptor Potential Vanilloid type 4 (TRPV4) is a mechanosensitive non-selective cation channel that is expressed on the endothelium and contributes to endothelium-mediated vasodilation. So far, no data are available about the morphological and functional status of this channel in hypertensive cases. Objectives: This study aimed to investigate whether there is any difference in the morphological and functional features of TRPV4 in the mesenteric artery of normotensive and hypertensive rats. Methods: Functional feature of TRPV4 in four experimental animal groups: young and adult Wistar-Kyoto rats (WKY-Y and WKY-A), young and adult spontaneously hypertensive rats (SHR-Y and SHR-A), was studied by adding 5 µM 4αPDD (TRPV4 agonist) to mesenteric arteries mounted in a four-chamber wire myograph and pre-contracted with 4 µM phenylephrine. The 4αPDD-induced response was investigated in the presence and absence of 1 µM HC067047 (TRPV4 antagonist), 100 µM L-NAME (nitric oxide synthase inhibitor), and endothelium. The morphological distribution of TRPV4 in the wall of rat mesenteric arteries was investigated by immunostaining. Real-time PCR was used in order to investigate mRNA expression level of TRPV4 in the mesenteric arteries of the four groups. The collected data were expressed as mean ± S.E.M. with n equal to the number of animals used (one vessel was taken from each rat). To determine the level of significance, statistical comparisons were performed using the student’s t-test and considered to be significantly different at p<0.05. Results: 4αPDD induced a relaxation response in the mesenteric arterial preparations (WKY-Y: 85.98% ± 4.18; n = 5) that was markedly inhibited by HC067047 (18.30% ± 2.86; n= 5; p<0.05), endothelium removal (19.93% ± 1.50; n = 5; p<0.05) and L-NAME (28.18% ± 3.09; n = 5; p<0.05). The 4αPDD-induced relaxation was significantly lower in SHR-Y compared to WKY-Y (SHR-Y: 70.96% ± 3.65; n = 6, WKY-Y: 85.98% ± 4.18; n = 5-6, p<0.05. Moreover, the 4αPDD-induced response was significantly lower in WKY-A than WKY-Y (WKY-A: 75.58 ± 1.30; n = 5, WKY-Y: 85.98% ± 4.18; n = 5, p<0.05). Immunostaining study showed immunofluorescent signal confined to the endothelial layer of the mesenteric arteries. The expression of TRPV4 mRNA in SHR-Y was significantly lower than in WKY-Y (SHR-Y; 0.67RU ± 0.34; n = 4, WKY-Y: 2.34RU ± 0.15; n = 4, p<0.05). Furthermore, TRPV4 mRNA expression in WKY-A was lower than its expression in WKY-Y (WKY-A: 0.62RU ± 0.37; n = 4, WKY-Y: 2.34RU ± 0.15; n = 4, p<0.05). Conclusion: Stimulation of TRPV4, which is expressed on the endothelium of rat mesenteric artery, triggers an endothelium-mediated relaxation response that markedly decreases with hypertension and growing up changes due to downregulation of TRPV4 expression.

Keywords: hypertension, endothelium, mesenteric artery, TRPV4

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Authors: Kamalpreet Kaur, Renu Dhir

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Climate prediction is an essential component of climate research, which helps evaluate possible effects on economies, communities, and ecosystems. Climate prediction involves short-term weather prediction, seasonal prediction, and long-term climate change prediction. Climate prediction can use the information gathered from satellites, ground-based stations, and ocean buoys, among other sources. The paper's four architectures, such as ResNet50, VGG19, Inception-v3, and Xception, have been combined using an ensemble approach for overall performance and robustness. An ensemble of different models makes a prediction, and the majority vote determines the final prediction. The various architectures such as ResNet50, VGG19, Inception-v3, and Xception efficiently classify the dataset RSI-CB256, which contains satellite images into cloudy and non-cloudy. The generated ensembled S-E model (Sar-ensembled model) provides an accuracy of 99.25%.

Keywords: climate, satellite images, prediction, classification

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Authors: Arpit Patil, Atharav Bhagwat, Rajas Bhope, Pramod Bide

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This research integrates IoT and ML to predict heart failure risks, utilizing the Framingham dataset. IoT devices gather real-time physiological data, focusing on heart rate dynamics, while ML, specifically Random Forest, predicts heart failure. Rigorous feature selection enhances accuracy, achieving over 90% prediction rate. This amalgamation marks a transformative step in proactive healthcare, highlighting early detection's critical role in cardiovascular risk mitigation. Challenges persist, necessitating continual refinement for improved predictive capabilities.

Keywords: cardiovascular diseases, internet of things, machine learning, cardiac risk assessment, heart failure prediction, early detection, cardio data analysis

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Authors: Tzu-Ching Weng, Hsin-Yi Chi

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This study examines the effect of family succession on the cost of bank loans and non-price contractual terms. We use a unique dataset from China and find that lending banks are likely to charge high-interest rates and offer tight contractual terms, such as loan maturity and collateral requirement, for family succession firms. These findings indicate that information and default risks may arise after subsequent family successions. We also find that family succession firms can reduce the cost of bank loans by hiring top-tier auditors to enhance financial reporting credibility. This finding suggests that professional and high-quality auditors can provide extremely valuable services to family succession firms.

Keywords: family succession, cost of bank loans, loan contract terms, top-tier auditor

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Authors: Kathia Melbouci, Sylvie Naudet Collette, Vincent Gay-Bellile, Omar Ait-Aider, Michel Dhome

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In this paper, we handle the problem of real time localization and mapping in indoor environment assisted by a partial prior 3D model, using an RGBD sensor. The proposed solution relies on a feature-based RGBD SLAM algorithm to localize the camera and update the 3D map of the scene. To improve the accuracy and the robustness of the localization, we propose to combine in a local bundle adjustment process, geometric information provided by a prior coarse 3D model of the scene (e.g. generated from the 2D floor plan of the building) along with RGBD data from a Kinect camera. The proposed approach is evaluated on a public benchmark dataset as well as on real scene acquired by a Kinect sensor.

Keywords: SLAM, global localization, 3D sensor, bundle adjustment, 3D model

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Authors: Jawharah Alasmari

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In inflectional morphology of verb, tense and aspect indicate action’s time either past/present or future and their period whether completed or not. The usage and meaning of tense and aspect differ in Arabic and English, therefore is no simple one -to- one mapping from an Arabic verb inflected form an appropriate English translation depends on a range of features, including immediate and wider context of use. The Quranic Arabic Corpus includes seven alternative expertly crafted English translations of each Arabic verses, which provides a test dataset for the study of appropriate Arabic to English translations of verb tense and aspect. We applied Corpus Linguistics Methods in a theoretical study of exemplary verbs, to elicit candidate verbal contexts which influence the choice of English inflection for each verse.

Keywords: Corpus linguistics methods, Arabic verb, tense and aspect, English translations

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Authors: Caihong Sun, Xizi Zhang

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Rating prediction is an important problem for recommender systems. The task is to predict the rating for an item that a user would give. Most of the existing algorithms for the task ignore the effect of negative ratings rated by users on items, but the negative ratings have a significant impact on users’ purchasing decisions in practice. In this paper, we present a rating prediction algorithm based on factorization machines that consider the effect of negative ratings inspired by Loss Aversion theory. The aim of this paper is to develop a concave and a convex negative disgust function to evaluate the negative ratings respectively. Experiments are conducted on MovieLens dataset. The experimental results demonstrate the effectiveness of the proposed methods by comparing with other four the state-of-the-art approaches. The negative ratings showed much importance in the accuracy of ratings predictions.

Keywords: factorization machines, feature engineering, negative ratings, recommendation systems

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Authors: Prikhil Agrawal, N. Priyanka

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With the increase of millions of users on Internet day by day, it is very essential to maintain highly reliable and secured data communication between various corporations. Although there are various traditional security imparting techniques such as antivirus software, password protection, data encryption, biometrics and firewall etc. But still network security has become the main issue in various leading companies. So IDSs have become an essential component in terms of security, as it can detect various network attacks and respond quickly to such occurrences. IDSs are used to detect unauthorized access to a computer system. This paper describes various intrusion detection techniques using GA approach. The intrusion detection problem has become a challenging task due to the conception of miscellaneous computer networks under various vulnerabilities. Thus the damage caused to various organizations by malicious intrusions can be mitigated and even be deterred by using this powerful tool.

Keywords: genetic algorithm (GA), intrusion detection system (IDS), dataset, network security

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Authors: Ghada Hasabo, Mahmoud Saber Elbasiouny, Mervat Abdelsalam, Sherin Ghaleb, Niveen Eldessouky

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In the near future, nanotechnology is envisaged for large scale use. Hence health and safety issues of nanoparticles should be promptly addressed. In the present study the acute hepatoxicity assessment due to high single oral dose of nano iron and micro iron particles were studied. The normal daily activities, biochemical alterations, blood coagulation, histopathological changes in Wister rats were the aspect of the toxicological assessment.This work found that significant alterations in biochemical enzymes (serum iron level, liver enzymes, albumin, and bilirubin levels), blood coagulation (PT, PC, INR), and histopathological changes occurred more prominently in the nano iron particle treated group.

Keywords: nanobiotechnology, nanosystems, nanomaterials, nanotechnology

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Authors: Fernando Duarte

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The work aims to evaluate the use of classical image processing methodologies towards skin tone classification in dermatological images. The skin tone is an important attribute when considering several factor for skin cancer diagnosis. Currently, there is a lack of clear methodologies to classify the skin tone based only on the dermatological image. In this work, a recent released dataset with the label for skin tone was used as reference for the evaluation of classical methodologies for segmentation and adjustment of color space for classification of skin tone in dermatological images. It was noticed that even though the classical methodologies can work fine for segmentation and color adjustment, classifying the skin tone without proper control of the aquisition of the sample images ended being very unreliable.

Keywords: segmentation, classification, color space, skin tone, Fitzpatrick

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Authors: Dhivyalakshmi Gnanasekaran, Sonali Adole Prasante, Raveendranath Veeramamani, H. Y. Suma

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A rare case of intestinal malrotation with midline descending colon and right sided sigmoid colon was observed in an adult male cadaver aged around 55 years during routine dissection. The descending colon began from the splenic flexure and gradually descended downwards to occupy the midline position and turned to the right side to be continued as sigmoid colon at the level of the fifth lumbar vertebra. In the right iliac fossa some part of loop of sigmoid colon displaced into the right lumbar region before entering into the true pelvis to continue as rectum. This anomalous descending and sigmoid colon was supplied by varying branching pattern of inferior mesenteric artery. It is extremely important to consider this embryological anomaly before any interventional diagnostic procedures like colonoscopy and to enhance the safety of colonic surgery.

Keywords: sigmoid colon, descending colon, hindgut, malrotation

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Authors: Xochilt Ramirez-Garcia, Mario Garcia-Valdez

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Contextual recommendations are implemented in Recommender Systems to improve user satisfaction, recommender system makes accurate and suitable recommendations for a particular situation reaching personalized recommendations. The context provides information relevant to the Recommender System and is used as a filter for selection of relevant items for the user. This paper presents a Context-aware Recommender System, which uses techniques based on Collaborative Filtering and Content-Based, as well as fuzzy rules, to recommend items inside the context. The dataset used to test the system is Trip Advisor. The accuracy in the recommendations was evaluated with the Mean Absolute Error.

Keywords: algorithms, collaborative filtering, intelligent systems, fuzzy logic, recommender systems

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Authors: Sofia Stoica

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In this paper, we use historical data to predict the stock price of a tech company. To this end, we use a dataset consisting of the stock prices in the past five years of ten major tech companies – Adobe, Amazon, Apple, Facebook, Google, Microsoft, Netflix, Oracle, Salesforce, and Tesla. We experimented with a variety of models– a linear regressor model, K nearest Neighbors (KNN), a sequential neural network – and algorithms - Multiplicative Weight Update, and AdaBoost. We found that the sequential neural network performed the best, with a testing error of 0.18%. Interestingly, the linear model performed the second best with a testing error of 0.73%. These results show that using historical data is enough to obtain high accuracies, and a simple algorithm like linear regression has a performance similar to more sophisticated models while taking less time and resources to implement.

Keywords: finance, machine learning, opening price, stock market

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Authors: Shamsa Al Sharji, Athar Al Jabri, Haitham Al Dughaishi, Mirfat Al Barwani, Raja Al Rawahi, Raiya Al Rajhi, Shurooq Al Ruqaishi, Thamreen Al Zadjali, Iman Al Humaidi

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Background: External Ventricular Drains (EVDs) are critical in managing traumatic brain injuries and hydrocephalus by controlling intracranial pressure, but they carry a high risk of infection. Infection rates vary globally, ranging from 5% to 45%, leading to increased morbidity, prolonged hospital stays, and higher healthcare costs. Nursing protocols play a pivotal role in reducing these infection rates. This study investigates the impact of a structured nursing protocol on EVD-associated infections in adult neurosurgery patients at the Directorate General of Khoula Hospital, Oman, from January to September 2024. Methods: A cluster-randomized trial was conducted across neurosurgery wards and the ICU. The intervention group followed a comprehensive nursing protocol, including strict sterile insertion, standardized dressing changes, infection control training, and regular clinical audits. The control group received standard care. The primary outcome was the incidence of EVD-associated infections, with secondary outcomes including protocol compliance, infection severity, recovery times, length of stay, and 30-day mortality. Statistical analysis was conducted using Chi-square tests, paired t-tests, and logistic regression to assess the differences between groups. Results: The study involved 75 patients, with an overall infection rate of 13.3%. The intervention group showed a reduced infection rate of 8.9% compared to 20% in the control group. Compliance rates for key nursing actions were high, with 89.7% for hand hygiene and 86.2% for wound dressing. The relative risk of infection was 0.44 in the intervention group, reflecting a 55.6% reduction. Logistic regression identified obesity as a significant predictor of EVD infections. Although mortality rates were slightly higher in the intervention group, the number needed to treat (NNT) of 9 suggests that the nursing protocol may improve survival outcomes. Conclusion: This study demonstrates that structured nursing protocols can reduce EVD-related infections and improve patient outcomes in neurosurgery. While the findings are promising, further research with larger sample sizes is needed to confirm these results and optimize infection control strategies in neurosurgical care.

Keywords: EVD, CSF, nursing protocol, EVD infection

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Authors: J. K. Alhassan, B. Attah, S. Misra

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Human beings have the ability to make logical decisions. Although human decision - making is often optimal, it is insufficient when huge amount of data is to be classified. medical dataset is a vital ingredient used in predicting patients health condition. In other to have the best prediction, there calls for most suitable machine learning algorithms. This work compared the performance of Artificial Neural Network (ANN) and Decision Tree Algorithms (DTA) as regards to some performance metrics using diabetes data. The evaluations was done using weka software and found out that DTA performed better than ANN. Multilayer Perceptron (MLP) and Radial Basis Function (RBF) were the two algorithms used for ANN, while RegTree and LADTree algorithms were the DTA models used. The Root Mean Squared Error (RMSE) of MLP is 0.3913,that of RBF is 0.3625, that of RepTree is 0.3174 and that of LADTree is 0.3206 respectively.

Keywords: artificial neural network, classification, decision tree algorithms, diabetes mellitus

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Authors: Bambi Ward

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Children of Holocaust survivors have been described as inheriting their parents’ trauma as a result of ‘vicarious memory’. The term refers to a process whereby second generation Holocaust survivors subconsciously remember aspects of Holocaust trauma, despite not having directly experienced it. This can occur even when there has been a conspiracy of silence in which survivors chose not to discuss the Holocaust with their children. There are still people born in various parts of the world such as Poland, Hungary, other parts of Europe, USA, Canada and Australia, who have only learnt of their Jewish roots as adults. This discovery may occur during a parent’s deathbed confession, or when an adult child is sorting through the personal belongings of a deceased family member. Some Holocaust survivors chose to deny their Jewish heritage and raise their children as Christians. Reasons for this decision include the trauma experienced during the Holocaust for simply being Jewish, the existence of anti-Semitism, and the desire to protect one’s self and one’s family. Although there has been considerable literature written about the transgenerational impact of trauma on children of Holocaust survivors, there has been little scholarly investigation into the effects of a hidden Jewish identity on these children. This paper presents a case study of an adult child of Hungarian Holocaust survivors who was raised as a Christian. At the age of eight she was told about her family’s Jewish background, but her parents insisted that she keep this a secret, even if asked directly. She honoured their request until she turned forty. By that time she had started the challenging process of reclaiming her Jewish identity. The paper outlines the tension between family loyalty and individual freedom, and discusses the role that art and art therapy played in assisting the subject of the case study to reclaim her Jewish identity and commence writing a memoir about her spiritual journey. The main methodology used in this case study is creative practice-led research. Particular attention is paid to the utilisation of an autoethnographic approach. The autoethnographic tools used include reflective journals of the subject of the case study. These journals reflect on the subject’s collection of autobiographical data relating to her family history, and include memories, drawings, products of art therapy, diaries, letters, photographs, home movies, objects, and oral history interviews with her mother. The case study illustrates how art and art therapy benefitted a second generation Holocaust survivor who was brought up having to suppress her Jewish identity. The process allowed her to express subconscious thoughts and feelings about her identity and free herself from the burden of the long term secret she had been carrying. The process described may also be of assistance to other traumatised people who have been trying to break the silence and who are seeking to express themselves in a positive and healing way.

Keywords: art, hidden identity, holocaust, silence

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Authors: Jingjing Ye, Cijun Fan, Yan Dong

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The development of financial sector plays an important role in shaping industrial structure. However, evidence on the micro-level channels through which this relation manifest remains relatively sparse, particularly for developing countries. In this paper, we compile an industry-by-city dataset based on manufacturing firms and registered banks in 287 Chinese cities from 1998 to 2008. Based on a difference-in-difference approach, we find the highly concentrated banking sector decreases the competitiveness of firms in each manufacturing industry. There are two main reasons: i) bank accessibility successfully fosters firm expansion within each industry, however, only for sufficiently large enterprises; ii) state-owned enterprises are favored by the banking industry in China. The results are robust after considering alternative concentration and external finance dependence measures.

Keywords: bank concentration, China, difference-in-difference, industry structure

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Authors: Kathrina Aseanne Acapulco-Gomez, Shayne Julieane Morales, Tzar Francis Verame

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Mean platelet volume (MPV) is the most accurate measure of the size of platelets and is routinely measured by most automated hematological analyzers. Several studies have shown associations between MPV and cardiovascular risks and outcomes. Although its measurement may provide useful data, MPV remains to be a diagnostic tool that is yet to be included in routine clinical decision making. The aim of this systematic review and meta-analysis is to determine summary estimates of the diagnostic accuracy of mean platelet volume for the diagnosis of myocardial infarction among adult patients with angina and/or its equivalents in terms of sensitivity, specificity, diagnostic odds ratio, and likelihood ratios, and to determine the difference of the mean MPV values between those with MI and those in the non-MI controls. The primary search was done through search in electronic databases PubMed, Cochrane Review CENTRAL, HERDIN (Health Research and Development Information Network), Google Scholar, Philippine Journal of Pathology, and Philippine College of Physicians Philippine Journal of Internal Medicine. The reference list of original reports was also searched. Cross-sectional, cohort, and case-control articles studying the diagnostic performance of mean platelet volume in the diagnosis of acute myocardial infarction in adult patients were included in the study. Studies were included if: (1) CBC was taken upon presentation to the ER or upon admission (within 24 hours of symptom onset); (2) myocardial infarction was diagnosed with serum markers, ECG, or according to accepted guidelines by the Cardiology societies (American Heart Association (AHA), American College of Cardiology (ACC), European Society of Cardiology (ESC); and, (3) if outcomes were measured as significant difference AND/OR sensitivity and specificity. The authors independently screened for inclusion of all the identified potential studies as a result of the search. Eligible studies were appraised using well-defined criteria. Any disagreement between the reviewers was resolved through discussion and consensus. The overall mean MPV value of those with MI (9.702 fl; 95% CI 9.07 – 10.33) was higher than in those of the non-MI control group (8.85 fl; 95% CI 8.23 – 9.46). Interpretation of the calculated t-value of 2.0827 showed that there was a significant difference in the mean MPV values of those with MI and those of the non-MI controls. The summary sensitivity (Se) and specificity (Sp) for MPV were 0.66 (95% CI; 0.59 - 0.73) and 0.60 (95% CI; 0.43 – 0.75), respectively. The pooled diagnostic odds ratio (DOR) was 2.92 (95% CI; 1.90 – 4.50). The positive likelihood ratio of MPV in the diagnosis of myocardial infarction was 1.65 (95% CI; 1.20 – 22.27), and the negative likelihood ratio was 0.56 (95% CI; 0.50 – 0.64). The intended role for MPV in the diagnostic pathway of myocardial infarction would perhaps be best as a triage tool. With a DOR of 2.92, MPV values can discriminate between those who have MI and those without. For a patient with angina presenting with elevated MPV values, it is 1.65 times more likely that he has MI. Thus, it is implied that the decision to treat a patient with angina or its equivalents as a case of MI could be supported by an elevated MPV value.

Keywords: mean platelet volume, MPV, myocardial infarction, angina, chest pain

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Authors: Nitin Shravan, Sudarsun Santhiappan, B. Sivaselvan

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Subsection identification, in the context of Electronic Health Records (EHRs), is identifying the important sections for down-stream tasks like auto-coding. In this work, we classify the text present in EHRs according to their information, using machine learning and deep learning techniques. We initially describe briefly about the problem and formulate it as a text classification problem. Then, we discuss upon the methods from the literature. We try two approaches - traditional feature extraction based machine learning methods and deep learning methods. Through experiments on a private dataset, we establish that the deep learning methods perform better than the feature extraction based Machine Learning Models.

Keywords: deep learning, machine learning, semantic clinical classification, subsection identification, text classification

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Authors: Helen J. Spray, Karina J. Linnell

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Local-global bias in adulthood is strongly dependent on environmental factors and a global bias is not the universal characteristic of adult perception it was once thought to be: whilst Western adults typically demonstrate a global bias, Namibian adults living in traditional villages possess a strong local bias. Furthermore, environmental effects on local-global bias have been shown to be highly gender-specific; whereas urbanisation promoted a global bias in urbanised Namibian women but not men, education promoted a global bias in urbanised Namibian men but not women. Adult populations, however, provide only a snapshot of the gene-environment interactions which shape perceptual bias. Yet, to date, there has been little work on the development of local-global bias across environmental settings. In the current study, local-global bias was assessed using a similarity-matching task with Navon figures in children aged between 4 and 15 years from across three populations: traditional Namibians, urban Namibians, and urban British. For the two Namibian groups, measures of urbanisation and education were obtained. Data were subjected to both between-group and within-group analyses. Between-group analyses compared developmental trajectories across population and gender. These analyses revealed a global bias from even as early as 4 in the British sample, and showed that the developmental onset of a global bias is not fixed. Urbanised Namibian children ultimately developed a global bias that was indistinguishable from British children; however, a global bias did not emerge until much later in development. For all populations, the greatest developmental effects were observed directly following the onset of formal education. No overall gender effects were observed; however, there was a significant gender by age interaction which was difficult to reconcile with existing biological-level accounts of gender differences in the development of local-global bias. Within-group analyses compared the effects of urbanisation and education on local-global bias for traditional and urban Namibian boys and girls separately. For both traditional and urban boys, education mediated all effects of age and urbanisation; however, this was not the case for girls. Traditional Namibian girls retained a local bias regardless of age, education, or urbanisation, and in urbanised girls, the development of a global bias was not attributable to any one factor specifically. These results are broadly consistent with aforementioned findings that education promoted a global bias in urbanised Namibian men but not women. The development of local-global bias does not follow a fixed trajectory but is subject to environmental control. Understanding how variability in the development of local-global bias might arise, particularly in the context of gender, may have far-reaching implications. For example, a number of educationally important cognitive functions (e.g., spatial ability) are known to show consistent gender differences in childhood and local-global bias may mediate some of these effects. With education becoming an increasingly prevalent force across much of the developing world it will be important to understand the processes that underpin its effects and their implications.

Keywords: cross-cultural, development, education, gender, local-global bias, perception, urbanisation, urbanization

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Authors: Padma Chutoo, Elena Kulinskaya, Ilyas Bakbergenuly, Nicholas Steel, Dmitri Pchejetski

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Stroke is associated with a significant risk of morbidity and mortality. There is scarcity of research on the long-term survival after first-ever ischaemic stroke (IS) events in England with regards to effects of different medical therapies and comorbidities. The objective of this study was to model the all-cause mortality after an IS diagnosis in the adult population of England. Using a retrospective case-control design, we extracted the electronic medical records of patients born prior to or in year 1960 in England with a first-ever ischaemic stroke diagnosis from January 1986 to January 2017 within the Health and Improvement Network (THIN) database. Participants with a history of ischaemic stroke were matched to 3 controls by sex and age at diagnosis and general practice. The primary outcome was the all-cause mortality. The hazards of the all-cause mortality were estimated using a Weibull-Cox survival model which included both scale and shape effects and a shared random effect of general practice. The model included sex, birth cohort, socio-economic status, comorbidities and medical therapies. 20,250 patients with a history of IS (cases) and 55,519 controls were followed up to 30 years. From 2008 to 2015, the one-year all-cause mortality for the IS patients declined with an absolute change of -0.5%. Preventive treatments to cases increased considerably over time. These included prescriptions of statins and antihypertensives. However, prescriptions for antiplatelet drugs decreased in the routine general practice since 2010. The survival model revealed a survival benefit of antiplatelet treatment to stroke survivors with hazard ratio (HR) of 0.92 (0.90 – 0.94). IS diagnosis had significant interactions with gender and age at entry and hypertension diagnosis. IS diagnosis was associated with high risk of all-cause mortality with HR= 3.39 (3.05-3.72) for cases compared to controls. Hypertension was associated with poor survival with HR = 4.79 (4.49 - 5.09) for hypertensive cases relative to non-hypertensive controls, though the detrimental effect of hypertension has not reached significance for hypertensive controls, HR = 1.19(0.82-1.56). This study of English primary care data showed that between 2008 and 2015, the rates of prescriptions of stroke preventive treatments increased, and a short-term all-cause mortality after IS stroke declined. However, stroke resulted in poor long-term survival. Hypertension, a modifiable risk factor, was found to be associated with poor survival outcomes in IS patients. Antiplatelet drugs were found to be protective to survival. Better efforts are required to reduce the burden of stroke through health service development and primary prevention.

Keywords: general practice, hazard ratio, health improvement network (THIN), ischaemic stroke, multiple imputation, Weibull-Cox model.

Procedia PDF Downloads 186

Authors: Sh. Minapoor, S. Ajeli

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Non-crimp three-dimensional (3D) orthogonal carbon fabrics are one of the useful textiles reinforcements in composites. In this paper, flexural and bending properties of a carbon non-crimp 3D orthogonal woven reinforcement are experimentally investigated. The present study is focused on the understanding and measurement of the main bending parameters including flexural stress, strain, and modulus. For this purpose, the three-point bending test method is used and the load-displacement curves are analyzed. The influence of some weave's parameters such as yarn type, geometry of structure, and fiber volume fraction on bending behavior of non-crimp 3D orthogonal carbon fabric is investigated. The obtained results also represent a dataset for the simulation of flexural behavior of non-crimp 3D orthogonal weave carbon composite reinforcement.

Keywords: non-crimp 3D orthogonal weave, carbon composite reinforcement, flexural behavior, three-point bending

Procedia PDF Downloads 298

Authors: Kilari Nikhil, Ankur Tibrewal, Srinivas Kruthiventi S. S.

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Conventional speaker identification systems often fall short of capturing the diverse variations present in speech data due to fixed-scale architectures. In this research, we propose a CNN-based architecture, USENet, designed to overcome these limitations. Leveraging two key techniques, our approach achieves superior performance on the VoxCeleb 1 Dataset without any pre-training. Firstly, we adopt a U-net-inspired design to extract features at multiple scales, empowering our model to capture speech characteristics effectively. Secondly, we introduce the squeeze and excitation block to enhance spatial feature learning. The proposed architecture showcases significant advancements in speaker identification, outperforming existing methods, and holds promise for future research in this domain.

Keywords: multi-scale feature extraction, squeeze and excitation, VoxCeleb1 speaker identification, mel-spectrograms, USENet

Procedia PDF Downloads 74

Authors: Hřebíčková Sylva, Grasgruber Pavel, Ondráček Jan, Cacek Jan, Kalina Tomáš

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The aim of this study was to describe typical changes in several parameters of body composition – the amount of skeletal muscle mass (SMM), % body fat (BF) and body mass index (BMI) - in selected age categories (30+ years) of men and women in the Czech Republic, depending on the degree of sports activity. Study (n = 823, M = 343, F = 480) monitored differences in BF, SM and BMI in five age groups (from 30-39 years to 70+ years). Physically inactive individuals have (p < 0.05) higher % BF in comparison with physically active individuals (29.5 ± 0.59 vs. 27 ± 0.38%), higher BMI (27.3 ± 0.32 vs. 26.1 ± 0.20 kg/m2), but lower SM (39.0 ± 0.33 vs. 40.4 ± 0.21%). The results indicate that with an increasing age, there is a trend towards increasing values of BMI and % BF, and decreasing values of SMM.

Keywords: body composition, body fat, physical activity, skeletal muscle

Procedia PDF Downloads 316

Authors: Marina Fuertes

Abstract:

Introduction: In everyday life experiences, children are solicited to cooperate with others. Often they perform cooperative tasks with their parents (e.g., setting the table for dinner) or in school. These tasks are very significant since children may learn to turn taking in interactions, to participate as well to accept others participation, to trust, to respect, to negotiate, to self-regulate their emotions, etc. Indeed, cooperative tasks contribute to children social, motor, cognitive and linguistic development. Therefore, it is important to study what learning, social and affective experiences are provided to children during these tasks. In this study, we included parents and preschool educators. Parents and educators are both significant: educative, interactive and affective figures. Rarely parents and educators behavior have been compared in studies about cooperative tasks. Parents and educators have different but complementary styles of interaction and communication. Aims: Therefore, this study aims to compare parents and educators' (of both genders) interactive behavior (cooperativity, empathy, ability to challenge the child, reciprocity, elaboration) during a play/individualized situation involving a cooperative task. Moreover, to compare parents and educators' behavior with girls and boys. Method: A quasi-experimental study with 45 dyads educators-children and 45 dyads with parents and their children. In this study, participated children between 3 and 5 years old and with age appropriate development. Adults and children were videotaped using a variety of materials (e.g., pencils, wood, wool) and tools (e.g., scissors, hammer) to produce together something of their choice during 20-minutes. Each dyad (one adult and one child) was observed and videotaped independently. Adults and children agreed and consented to participate. Experimental conditions were suitable, pleasant and age appropriated. Results: Findings indicate that parents and teachers offer different learning experiences. Teachers were more likely to challenged children to explore new concepts and to accept children ideas. In turn, parents gave more support to children actions and were more likely to use their own example to teach children. Multiple regression analysis indicates that parent versus educator status predicts their behavior. Gender of both children and adults affected the results. Adults acted differently with girls and boys (e.g., adults worked more cooperatively with girls than boys). Male participants supported more girls participation rather than boys while female adults allowed boys to make more decisions than girls. Discussion: Taking our results and past studies, we learn that different qualitative interactions and learning experiences are offered by parents, educators according to parents and children gender. Thus, the same child needs to learn different cooperative strategies according to their interactive patterns and specific context. Yet, cooperative play and individualized activities with children generate learning opportunities and benefits children participation and involvement.

Keywords: early childhood education, parenting, gender, cooperative tasks, adult-child interaction

Procedia PDF Downloads 325

Authors: Jaiden X. Schraut

Abstract:

Medical Imaging Segmentation of Chest X-rays is used for the purpose of identification and differentiation of lung cancer, pneumonia, COVID-19, and similar respiratory diseases. Widespread application of computer-supported perception methods into the diagnostic pipeline has been demonstrated to increase prognostic accuracy and aid doctors in efficiently treating patients. Modern models attempt the task of segmentation and classification separately and improve diagnostic efficiency; however, to further enhance this process, this paper proposes a multi-output network that follows a U-Net architecture for image segmentation output and features an additional CNN module for auxiliary classification output. The proposed model achieves a final Jaccard Index of .9634 for image segmentation and a final accuracy of .9600 for classification on the COVID-19 radiography database.

Keywords: chest X-ray, deep learning, image segmentation, image classification

Procedia PDF Downloads 144