Search results for: rapid diagnosis
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4369

Search results for: rapid diagnosis

2239 Analytical Authentication of Butter Using Fourier Transform Infrared Spectroscopy Coupled with Chemometrics

Authors: M. Bodner, M. Scampicchio

Abstract:

Fourier Transform Infrared (FT-IR) spectroscopy coupled with chemometrics was used to distinguish between butter samples and non-butter samples. Further, quantification of the content of margarine in adulterated butter samples was investigated. Fingerprinting region (1400-800 cm–1) was used to develop unsupervised pattern recognition (Principal Component Analysis, PCA), supervised modeling (Soft Independent Modelling by Class Analogy, SIMCA), classification (Partial Least Squares Discriminant Analysis, PLS-DA) and regression (Partial Least Squares Regression, PLS-R) models. PCA of the fingerprinting region shows a clustering of the two sample types. All samples were classified in their rightful class by SIMCA approach; however, nine adulterated samples (between 1% and 30% w/w of margarine) were classified as belonging both at the butter class and at the non-butter one. In the two-class PLS-DA model’s (R2 = 0.73, RMSEP, Root Mean Square Error of Prediction = 0.26% w/w) sensitivity was 71.4% and Positive Predictive Value (PPV) 100%. Its threshold was calculated at 7% w/w of margarine in adulterated butter samples. Finally, PLS-R model (R2 = 0.84, RMSEP = 16.54%) was developed. PLS-DA was a suitable classification tool and PLS-R a proper quantification approach. Results demonstrate that FT-IR spectroscopy combined with PLS-R can be used as a rapid, simple and safe method to identify pure butter samples from adulterated ones and to determine the grade of adulteration of margarine in butter samples.

Keywords: adulterated butter, margarine, PCA, PLS-DA, PLS-R, SIMCA

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2238 Using Closed Frequent Itemsets for Hierarchical Document Clustering

Authors: Cheng-Jhe Lee, Chiun-Chieh Hsu

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Due to the rapid development of the Internet and the increased availability of digital documents, the excessive information on the Internet has led to information overflow problem. In order to solve these problems for effective information retrieval, document clustering in text mining becomes a popular research topic. Clustering is the unsupervised classification of data items into groups without the need of training data. Many conventional document clustering methods perform inefficiently for large document collections because they were originally designed for relational database. Therefore they are impractical in real-world document clustering and require special handling for high dimensionality and high volume. We propose the FIHC (Frequent Itemset-based Hierarchical Clustering) method, which is a hierarchical clustering method developed for document clustering, where the intuition of FIHC is that there exist some common words for each cluster. FIHC uses such words to cluster documents and builds hierarchical topic tree. In this paper, we combine FIHC algorithm with ontology to solve the semantic problem and mine the meaning behind the words in documents. Furthermore, we use the closed frequent itemsets instead of only use frequent itemsets, which increases efficiency and scalability. The experimental results show that our method is more accurate than those of well-known document clustering algorithms.

Keywords: FIHC, documents clustering, ontology, closed frequent itemset

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2237 Stressful Events and Serious Mood Disorders

Authors: Horesh Reinman Netta

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Objectives: To examine the relationship between stressful life events and recurrent major depressive disorders Methods: Three groups of 50 subjects were assessed. One group had a recurrent major depressive disorder with melancholic features; the second group met the criteria for borderline personality disorder, and the third consisted of healthy controls. The Structured Clinical Interview for AXIS I DSM-IV Disorders sand the Structured Clinical Interview for AXIS II DSM-IV Disorders were used for diagnosis. The Israel Psychiatric Epidemiology Research Interview (IPERI) Life Event Scale and the Coddington Life Events Schedule (CLES) were used to measure life events which were confirmed with a confirmatory semi-structured interview. The Beck Depression Inventory and the Satisfaction from Life scales were also administered. Results : The total number of loss-related events in childhood and in the year preceding the first episode was significantly higher in the affective disorder group than in the two control groups. Total number of LE, uncontrolled and independent events were also more common in the depressed patients in the year preceding the first episode. No category of SLE was differentiated among any of the three groups during any period of time following the first depressive episode. Conclusions: SLE play an important role in the onset of affective disorders. There appear to be specific kinds of SLE occurring in childhood and in the year preceding a first episode that have particular significance. SLE may have a lesser role in the maintenance of this illness.

Keywords: modd dosorders, recurrent depression, stress, life events

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2236 The Strategy of Urban Traditional Consumer Areas Adapting to Digital Logistics: A Case Study of Fengying Xili in Changsha

Authors: Mengjie Zhou

Abstract:

Under the rapid promotion of digital logistics, the old consumption space in cities is undergoing profound transformation and reconstruction. This article systematically analyzes the impact of digital logistics on existing consumer spaces in cities and how these spaces can adapt to and lead this change through distinct ‘spatial production’ models. The digital transformation of the logistics industry has significantly improved logistics efficiency and service quality while also putting forward new requirements for the form and function of consumer space. In this process, the old consumption space in cities not only faces the trend of material consumption transforming into spiritual consumption but also needs to face profound changes in consumer behavior patterns. Taking Fengying Xili in Changsha as an empirical case, this article explores in detail how it successfully transformed from a traditional consumption space to a modern cultural consumption space by introducing new business formats, optimizing spatial layout, and improving service quality while preserving its historical heritage. This case not only provides valuable practical experience for the transformation of old urban consumption spaces but also demonstrates the feasibility and potential of the new model of ‘spatial production’.

Keywords: digital logistics, urban consumption space, space production, urban renewal

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2235 Crow Search Algorithm-Based Task Offloading Strategies for Fog Computing Architectures

Authors: Aniket Ganvir, Ritarani Sahu, Suchismita Chinara

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The rapid digitization of various aspects of life is leading to the creation of smart IoT ecosystems, where interconnected devices generate significant amounts of valuable data. However, these IoT devices face constraints such as limited computational resources and bandwidth. Cloud computing emerges as a solution by offering ample resources for offloading tasks efficiently despite introducing latency issues, especially for time-sensitive applications like fog computing. Fog computing (FC) addresses latency concerns by bringing computation and storage closer to the network edge, minimizing data travel distance, and enhancing efficiency. Offloading tasks to fog nodes or the cloud can conserve energy and extend IoT device lifespan. The offloading process is intricate, with tasks categorized as full or partial, and its optimization presents an NP-hard problem. Traditional greedy search methods struggle to address the complexity of task offloading efficiently. To overcome this, the efficient crow search algorithm (ECSA) has been proposed as a meta-heuristic optimization algorithm. ECSA aims to effectively optimize computation offloading, providing solutions to this challenging problem.

Keywords: IoT, fog computing, task offloading, efficient crow search algorithm

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2234 The Impact of Alumina Cement on Properties of Portland Cement Slurries and Mortars

Authors: Krzysztof Zieliński, Dariusz Kierzek

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The addition of a small amount of alumina cement to Portland cement results in immediate setting, a rapid increase in the compressive strength and a clear increase of the adhesion to concrete substrate. This phenomenon is used, among others, for the production of liquid floor self-levelling compounds. Alumina cement is several times more expensive than Portland cement and is a component having a significant impact on prices of products manufactured with its use. For the production of liquid floor self-levelling compounds, low-alumina cement containing approximately 40% Al2O3 is normally used. The aim of the study was to determine the impact of Portland cement with the addition of alumina cement on the basic physical and mechanical properties of cement slurries and mortars. CEM I 42.5R and three types of alumina cement containing 40%, 50% and 70% of Al2O3 were used for the tests. Mixes containing 4%, 6%, 8%, 10% and 12% of different varieties of alumina cement were prepared; for which, the time of initial and final setting, compressive and flexural strength and adhesion to concrete substrate were determined. The analysis of the obtained test results showed that a similar immediate setting effect and clearly better adhesion strength can be obtained using the addition of 6% of high-alumina cement than 12% of low-alumina cement. As the prices of these cements are similar, this can give significant financial savings in the production of liquid floor self-levelling compounds.

Keywords: alumina cement, immediate setting, compression strength, adhesion to substrate

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2233 Clinical and Sleep Features in an Australian Population Diagnosed with Mild Cognitive Impairment

Authors: Sadie Khorramnia, Asha Bonney, Kate Galloway, Andrew Kyoong

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Sleep plays a pivotal role in the registration and consolidation of memory. Multiple observational studies have demonstrated that self-reported sleep duration and sleep quality are associated with cognitive performance. Montreal Cognitive Assessment questionnaire is a screening tool to assess mild cognitive (MCI) impairment with a 90% diagnostic sensitivity. In our current study, we used MOCA to identify MCI in patients who underwent sleep study in our sleep department. We then looked at the clinical risk factors and sleep-related parameters in subjects found to have mild cognitive impairment but without a diagnosis of sleep-disordered breathing. Clinical risk factors, including physician, diagnosed hypertension, diabetes, and depression and sleep-related parameters, measured during sleep study, including percentage time of each sleep stage, total sleep time, awakenings, sleep efficiency, apnoea hypopnoea index, and oxygen saturation, were evaluated. A total of 90 subjects who underwent sleep study between March 2019 and October 2019 were included. Currently, there is no pharmacotherapy available for MCI; therefore, identifying the risk factors and attempting to reverse or mitigate their effect is pivotal in slowing down the rate of cognitive deterioration. Further characterization of sleep parameters in this group of patients could open up opportunities for potentially beneficial interventions.

Keywords: apnoea hypopnea index, mild cognitive impairment, sleep architecture, sleep study

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2232 Health and Mental Health among College Students: Toward a Better Understanding of the Impact of Sexual Assault, Alcohol Use, and COVID-19

Authors: Noel Busch-Armendariz, Caitlin Sulley

Abstract:

Introduction: This study investigated the development of college experiences, COVID-19 pandemic experiences, alcohol use, and sexual violence. The longitudinal study includes 656 college students living in the same dormitory. Students' alcohol use and social network structure were investigated to better understand the relationship with sexual violence risk. Basic Methodologies: Over two years, students repeated five web-based surveys, including a pre-college survey and surveys during four consecutive semesters. Questions were added in the fourth wave to assess students’ experiences of the COVID-19 pandemic, administered from November-January 2021, including mental and behavioral health. Analyses include the impact of COVID on living arrangements, drinking behaviors, and daily life; experiences of COVID symptoms, testing, and diagnosis, responses to COVID such as social distancing, quarantining, not working, increased health care needs; experience of fear, worry, stigma, emotional well-being, loneliness, and mental health; experiences of financial loss, lack of basic supplies, receiving emotional and financial support, and comparison with academic disengagement. Concluding Statement: Findings and discussion will include strategies to strengthen mental and behavioral health programs and policies.

Keywords: COVID, mental health, substance abuse, college students, sexual misconducts

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2231 Achieving 13th Sustainable Development Goal: Urbanization and ICT Empowerment in Pursuit of Carbon Neutrality - Beyond Linear Thinking

Authors: Salim Khan

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The attainment of the carbon neutrality objective and Sustainable Development Goal 13 (SDG-13) target, which pertains to climate actions, received widespread attention in developing and emerging nations. Given the increasing pace of urbanization, technological advancements, and rapid growth, it is imperative to examine the linear and nonlinear effects of urbanization and economic growth and the linear impact of information and communication technology (ICT) on carbon emissions (CO2e). This study employs the Dynamic System GMM (DSGMM) and Panel Quantile Regression (PQR) methodologies to investigate the causal relationship between urbanization, ICT, economic growth, and their interplay on CO2e in 39 BRI countries from 2001 to 2020. The study's findings indicate that the impact of urbanization on CO2e exhibits linear and nonlinear patterns. The specific nonlinear impact of urbanization leads to a decrease in CO2e, hence facilitating the achievement of carbon neutrality and contributing to SDG-13. The study highlights the importance of ICT in achieving SDG-13 by reducing CO2e, emphasizing the need for informatization. Simultaneously, the findings support the Environmental Kuznets Curve (EKC) hypothesis and support the pollution haven theory. Finally, based on empirical findings, significant policy implications are suggested for achieving SGD 13 and carbon neutrality.

Keywords: urbanization, ICT, CO2 emission, EKC, pollution haven, BRI

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2230 From Electroencephalogram to Epileptic Seizures Detection by Using Artificial Neural Networks

Authors: Gaetano Zazzaro, Angelo Martone, Roberto V. Montaquila, Luigi Pavone

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Seizure is the main factor that affects the quality of life of epileptic patients. The diagnosis of epilepsy, and hence the identification of epileptogenic zone, is commonly made by using continuous Electroencephalogram (EEG) signal monitoring. Seizure identification on EEG signals is made manually by epileptologists and this process is usually very long and error prone. The aim of this paper is to describe an automated method able to detect seizures in EEG signals, using knowledge discovery in database process and data mining methods and algorithms, which can support physicians during the seizure detection process. Our detection method is based on Artificial Neural Network classifier, trained by applying the multilayer perceptron algorithm, and by using a software application, called Training Builder that has been developed for the massive extraction of features from EEG signals. This tool is able to cover all the data preparation steps ranging from signal processing to data analysis techniques, including the sliding window paradigm, the dimensionality reduction algorithms, information theory, and feature selection measures. The final model shows excellent performances, reaching an accuracy of over 99% during tests on data of a single patient retrieved from a publicly available EEG dataset.

Keywords: artificial neural network, data mining, electroencephalogram, epilepsy, feature extraction, seizure detection, signal processing

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2229 Comparison of the Effectiveness of Neisseria gonorrhea Crude Protein Injections with Intravenous, Intracutaneous, and Subcutaneous

Authors: Annisa Amalina, Lintang Sekar Sari, Khairunnisa Salsabila, Astya Gema Ramadhan, M. Fatkhi, Andani Eka Putra

Abstract:

Gonorrhea is one of the sexually transmitted diseases by genito-genital, oro-genital and anogenital. Gonorrhea disease will cause complications if not treated properly. The diagnostic tool that has been used nowadays is microscopic. Thus a rapid diagnostic tool for gonorrhea is required, using polyclonal antibodies. The purpose of this study was to determine the effectiveness of injections of intravenous, subcutaneous and intracutaneous crude protein gonorrhea. The research method used in this research is experimental explorative. This research was conducted in Molecular Microbiology Laboratory of Faculty of Medicine, Andalas University for 3 months from April to June 2017. This study used 3 groups of rabbit with intravenous, subcutaneous, and intracutaneous injections. Each group was treated on days 1, 7, 21, and 28 with crude protein injection. After that, the examination of antibody levels held by using ELISA, followed by the antibody comparative tests contained in all three groups. The results examined by One Way ANOVA test on SPSS 21 and showed that there is no significant difference between intravenous, subcutaneous, and intracutaneous use p=0.69 (p < 0.05). However, there is an increased level (0.047 to 1.171) in antibodies from day 1 to day 14. In addition, subcutaneous use is preferred because it has minimal side effects compared to intravenous and intracutaneous use.

Keywords: crude protein, Neisseria gonorrhea, polyclonal antibodies, subcutaneous

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2228 The Use of Building Energy Simulation Software in Case Studies: A Literature Review

Authors: Arman Ameen, Mathias Cehlin

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The use of Building Energy Simulation (BES) software has increased in the last two decades, parallel to the development of increased computing power and easy to use software applications. This type of software is primarily used to simulate the energy use and the indoor environment for a building. The rapid development of these types of software has raised their level of user-friendliness, better parameter input options and the increased possibility of analysis, both for a single building component or an entire building. This, in turn, has led to many researchers utilizing BES software in their research in various degrees. The aim of this paper is to carry out a literature review concerning the use of the BES software IDA Indoor Climate and Energy (IDA ICE) in the scientific community. The focus of this paper will be specifically the use of the software for whole building energy simulation, number and types of articles and publications dates, the area of application, types of parameters used, the location of the studied building, type of building, type of analysis and solution methodology. Another aspect that is examined, which is of great interest, is the method of validations regarding the simulation results. The results show that there is an upgoing trend in the use of IDA ICE and that researchers use the software in their research in various degrees depending on case and aim of their research. The satisfactory level of validation of the simulations carried out in these articles varies depending on the type of article and type of analysis.

Keywords: building simulation, IDA ICE, literature review, validation

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2227 Algorithm for Quantification of Pulmonary Fibrosis in Chest X-Ray Exams

Authors: Marcela de Oliveira, Guilherme Giacomini, Allan Felipe Fattori Alves, Ana Luiza Menegatti Pavan, Maria Eugenia Dela Rosa, Fernando Antonio Bacchim Neto, Diana Rodrigues de Pina

Abstract:

It is estimated that each year one death every 10 seconds (about 2 million deaths) in the world is attributed to tuberculosis (TB). Even after effective treatment, TB leaves sequelae such as, for example, pulmonary fibrosis, compromising the quality of life of patients. Evaluations of the aforementioned sequel are usually performed subjectively by radiology specialists. Subjective evaluation may indicate variations inter and intra observers. The examination of x-rays is the diagnostic imaging method most accomplished in the monitoring of patients diagnosed with TB and of least cost to the institution. The application of computational algorithms is of utmost importance to make a more objective quantification of pulmonary impairment in individuals with tuberculosis. The purpose of this research is the use of computer algorithms to quantify the pulmonary impairment pre and post-treatment of patients with pulmonary TB. The x-ray images of 10 patients with TB diagnosis confirmed by examination of sputum smears were studied. Initially the segmentation of the total lung area was performed (posteroanterior and lateral views) then targeted to the compromised region by pulmonary sequel. Through morphological operators and the application of signal noise tool, it was possible to determine the compromised lung volume. The largest difference found pre- and post-treatment was 85.85% and the smallest was 54.08%.

Keywords: algorithm, radiology, tuberculosis, x-rays exam

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2226 Exploring Urbanization-Induced Wetland Loss within the Greater Toronto Area from 2005 to 2015

Authors: Kaushika Vinotheeswaran

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The Greater Toronto Area (GTA), located in Ontario, Canada, is among the fastest-growing metropolitan areas in North America. Rapid urbanization within the GTA has led to increased imperviousness and surface runoff, contributing to wetland loss. Wetland cover and land cover data from the Southern Ontario Land Resource Information System were analyzed to characterize wetland loss to built-up areas and land conversions between 2005 and 2015, evaluating the extent of urbanization-induced wetland loss. Spatial analysis revealed a significant increase in the number of wetlands lost from 2005 to 2011 compared to the period from 2011 to 2015, with these losses attributed to increased urban expansions within the GTA. Non-wetland conversions, such as agricultural and impervious built-up uses to support urban expansions, played a significant role in wetland loss. Current approaches to wetland policy implementation and land-use planning strategies do not effectively identify or mitigate damage to wetlands in advance of development, resulting in significant wetland loss. Therefore, wetland conservation policies must be re-evaluated to address gaps in policy practice and focus on minimizing wetland loss.

Keywords: wetland loss, urbanization, impervious, pervious, wetland conservation

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2225 Laser Based Microfabrication of a Microheater Chip for Cell Culture

Authors: Daniel Nieto, Ramiro Couceiro

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Microfluidic chips have demonstrated their significant application potentials in microbiological processing and chemical reactions, with the goal of developing monolithic and compact chip-sized multifunctional systems. Heat generation and thermal control are critical in some of the biochemical processes. The paper presents a laser direct-write technique for rapid prototyping and manufacturing of microheater chips and its applicability for perfusion cell culture outside a cell incubator. The aim of the microheater is to take the role of conventional incubators for cell culture for facilitating microscopic observation or other online monitoring activities during cell culture and provides portability of cell culture operation. Microheaters (5 mm × 5 mm) have been successfully fabricated on soda-lime glass substrates covered with aluminum layer of thickness 120 nm. Experimental results show that the microheaters exhibit good performance in temperature rise and decay characteristics, with localized heating at targeted spatial domains. These microheaters were suitable for a maximum long-term operation temperature of 120ºC and validated for long-time operation at 37ºC. for 24 hours. Results demonstrated that the physiology of the cultured SW480 adenocarcinoma of the colon cell line on the developed microheater chip was consistent with that of an incubator.

Keywords: laser microfabrication, microheater, bioengineering, cell culture

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2224 A Review: Detection and Classification Defects on Banana and Apples by Computer Vision

Authors: Zahow Muoftah

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Traditional manual visual grading of fruits has been one of the agricultural industry’s major challenges due to its laborious nature as well as inconsistency in the inspection and classification process. The main requirements for computer vision and visual processing are some effective techniques for identifying defects and estimating defect areas. Automated defect detection using computer vision and machine learning has emerged as a promising area of research with a high and direct impact on the visual inspection domain. Grading, sorting, and disease detection are important factors in determining the quality of fruits after harvest. Many studies have used computer vision to evaluate the quality level of fruits during post-harvest. Many studies have used computer vision to evaluate the quality level of fruits during post-harvest. Many studies have been conducted to identify diseases and pests that affect the fruits of agricultural crops. However, most previous studies concentrated solely on the diagnosis of a lesion or disease. This study focused on a comprehensive study to identify pests and diseases of apple and banana fruits using detection and classification defects on Banana and Apples by Computer Vision. As a result, the current article includes research from these domains as well. Finally, various pattern recognition techniques for detecting apple and banana defects are discussed.

Keywords: computer vision, banana, apple, detection, classification

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2223 Automated Digital Mammogram Segmentation Using Dispersed Region Growing and Pectoral Muscle Sliding Window Algorithm

Authors: Ayush Shrivastava, Arpit Chaudhary, Devang Kulshreshtha, Vibhav Prakash Singh, Rajeev Srivastava

Abstract:

Early diagnosis of breast cancer can improve the survival rate by detecting cancer at an early stage. Breast region segmentation is an essential step in the analysis of digital mammograms. Accurate image segmentation leads to better detection of cancer. It aims at separating out Region of Interest (ROI) from rest of the image. The procedure begins with removal of labels, annotations and tags from the mammographic image using morphological opening method. Pectoral Muscle Sliding Window Algorithm (PMSWA) is used for removal of pectoral muscle from mammograms which is necessary as the intensity values of pectoral muscles are similar to that of ROI which makes it difficult to separate out. After removing the pectoral muscle, Dispersed Region Growing Algorithm (DRGA) is used for segmentation of mammogram which disperses seeds in different regions instead of a single bright region. To demonstrate the validity of our segmentation method, 322 mammographic images from Mammographic Image Analysis Society (MIAS) database are used. The dataset contains medio-lateral oblique (MLO) view of mammograms. Experimental results on MIAS dataset show the effectiveness of our proposed method.

Keywords: CAD, dispersed region growing algorithm (DRGA), image segmentation, mammography, pectoral muscle sliding window algorithm (PMSWA)

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2222 Jejunostomy and Protective Ileostomy in a Patient with Massive Necrotizing Enterocolitis: A Case Report

Authors: Rafael Ricieri, Rogerio Barros

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Objective: This study is to report a case of massive necrotizing enterocolitis in a six-month-old patient, requiring ileostomy and protective jejunostomy as a damage control measure in the first exploratory laparotomy surgery in massive enterocolitis without a previous diagnosis. Methods: This study is a case report of success in making and closing a protective jejunostomy. However, the low number of publications on this staged and risky measure of surgical resolution encouraged the team to study the indication and especially the correct time for closing the patient's protective jejunostomy. The main study instrument will be the six-month-old patient's medical record. Results: Based on the observation of the case described, it was observed that the time for the closure of the described procedure (protective jejunostomy) varies according to the level of compromise of the health status of your patient and of an individual of each person. Early closure, or failure to close, can lead to a favorable problem for the patient since several problems can result from this closure, such as new intestinal perforations, hydroelectrolyte disturbances. Despite the risk of new perforations, we suggest closing the protective jejunostomy around the 14th day of the procedure, thus keeping the patient on broad-spectrum antibiotic therapy and absolute fasting, thus reducing the chances of new intestinal perforations. Associated with the closure of the jejunostomy, a gastric tube for decompression is necessary, and care in an intensive care unit and electrolyte replacement is necessary to maintain the stability of the case.

Keywords: jejunostomy, ileostomy, enterocolitis, pediatric surgery, gastric surgery

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2221 Stress and Marital Satisfaction of Parents to Children Diagnosed with Autism

Authors: Oren Shtayermman

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The current investigation expended on research among parents caring for a child who is diagnosed with an autism spectrum disorder (ASD). An online web survey was used to collect data from 253 parents caring for a child with a diagnosis of ASD. Both parents reported on elevated levels of parental stress associated with caring for the child on the spectrum. In addition, lower levels of marital satisfaction were found in both parents. About 13% of the parents in the sample met the diagnostic criteria for Major Depressive Disorder and About 15% of the parents met the diagnostic criteria for Generalized Anxiety Disorder. Although the majority of the sample was females (94%) significant differences were found between males and females in relation to meeting the diagnostic criteria for Major Depressive Disorder and for Generalized Anxiety Disorder. Higher levels of stress were associated with higher number of Generalized Anxiety Disorder symptoms and higher number of Major Depressive Disorder symptoms. Findings from this study indicate how vulnerable parents and especially females are in relation to caring to a child diagnosed with ASD. Educational Objectives: At the conclusion of the paper, the readers should be able to: -Identify levels of stress and marital satisfaction among parents caring for a child diagnosed with autism spectrum disorder, -Recognize the impact of stress on the development of mental health issues, -Name the two most common mood and anxiety related disorders associated with caring for a child diagnosed with an autism spectrum disorder.

Keywords: autism, stress, parents, children

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2220 Morphosyntactic Abilities in Speakers with Broca’s Aphasia: A Preliminary Examination

Authors: Mile Vuković, Lana Jerkić Rajić

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Introduction: Broca's aphasia is a non-fluent type of aphasic syndrome, which is primarily manifested by impairment of language production. In connected speech, patients with this type of aphasia produce short sentences in which they often omit function words and morphemes or choose inadequate forms. Aim: This research was conducted to examine the morphosyntactic abilities of people with Broca's aphasia, comparing them with neurologically healthy subjects without a language disorder. Method: The sample included 15 patients with Broca's post-stroke aphasia, who had the relatively intact ability of auditory comprehension. The diagnosis of aphasia was based on the Boston Diagnostic Aphasia Examination. The control group comprised 16 neurologically healthy subjects without data on the presence of disorders in speech and language development. The patients' mother tongue was Serbian. The new Serbian Morphosyntactic Abilities Test (SMAT) was used. Descriptive (frequency, percentage, mean, SD, min, max) and inferential (Mann-Whitney U-test) statistics were used in data processing. Results: We noticed statistically significant differences between people with Broca's aphasia and neurotypical subjects on the SMAT (U = 1.500, z = -4.982, p = 0.000). The results showed that people with Broca's aphasia had achieved low scores on the SMAT, regardless of age (ρ = -0.045, p = 0.873) and time post onset (ρ = 0.330, p = 0.229). Conclusion: Preliminary results show that the SMAT has the potential to detect morphosyntactic deficits in Serbian speakers with Broca's aphasia.

Keywords: Broca’s aphasia, morphosyntactic abilities, agrammatism, Serbian language

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2219 Machine Learning for Classifying Risks of Death and Length of Stay of Patients in Intensive Unit Care Beds

Authors: Itamir de Morais Barroca Filho, Cephas A. S. Barreto, Ramon Malaquias, Cezar Miranda Paula de Souza, Arthur Costa Gorgônio, João C. Xavier-Júnior, Mateus Firmino, Fellipe Matheus Costa Barbosa

Abstract:

Information and Communication Technologies (ICT) in healthcare are crucial for efficiently delivering medical healthcare services to patients. These ICTs are also known as e-health and comprise technologies such as electronic record systems, telemedicine systems, and personalized devices for diagnosis. The focus of e-health is to improve the quality of health information, strengthen national health systems, and ensure accessible, high-quality health care for all. All the data gathered by these technologies make it possible to help clinical staff with automated decisions using machine learning. In this context, we collected patient data, such as heart rate, oxygen saturation (SpO2), blood pressure, respiration, and others. With this data, we were able to develop machine learning models for patients’ risk of death and estimate the length of stay in ICU beds. Thus, this paper presents the methodology for applying machine learning techniques to develop these models. As a result, although we implemented these models on an IoT healthcare platform, helping clinical staff in healthcare in an ICU, it is essential to create a robust clinical validation process and monitoring of the proposed models.

Keywords: ICT, e-health, machine learning, ICU, healthcare

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2218 Retrospective Study for Elective Medical Patients Evacuation of Different Diagnoses Requiring Different Approach in Oxygen Usage

Authors: Branimir Skoric

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Over the past two decades, number of international travels rose significantly in the United Kingdom and Worldwide in the shape of business travels and holiday travels as well. The fact that elderly people travel a lot, more than ever before increased the needs for medical evacuations (repatriations) back home if they fell ill abroad or had any kind of accident. This paper concerns medical evacuations of patients on the way back home to the United Kingdom (United Kingdom Residents) and their specific medical needs during short-haul or long-haul commercial scheduled flight and ground transportation to the final destination regardless whether it was hospital or usual place of residence. Particular medical need during medical evacuations is oxygen supply and it can be supplied via portable oxygen concentrator, pulse flow oxygenator or continuous free flow oxygenator depending on the main diagnosis and patient’s comorbidities. In this retrospective study, patients were divided into two groups. One group was consisted of patients suffering from cardio-respiratory diagnoses as primary illness. Another Group consisted of patients suffering from noncardiac illnesses who have other problems including any kind of physical injury. Needs for oxygen and type of supply were carefully considered in regards of duration of the flight, standard airline cabin pressure and results described in this retrospective study.

Keywords: commercial flight, elderly travellers, medical evacuations, oxygen

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2217 Application of Residual Correction Method on Hyperbolic Thermoelastic Response of Hollow Spherical Medium in Rapid Transient Heat Conduction

Authors: Po-Jen Su, Huann-Ming Chou

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In this article we uses the residual correction method to deal with transient thermoelastic problems with a hollow spherical region when the continuum medium possesses spherically isotropic thermoelastic properties. Based on linear thermoelastic theory, the equations of hyperbolic heat conduction and thermoelastic motion were combined to establish the thermoelastic dynamic model with consideration of the deformation acceleration effect and non-Fourier effect under the condition of transient thermal shock. The approximate solutions of temperature and displacement distributions are obtained using the residual correction method based on the maximum principle in combination with the finite difference method, making it easier and faster to obtain upper and lower approximations of exact solutions. The proposed method is found to be an effective numerical method with satisfactory accuracy. Moreover, the result shows that the effect of transient thermal shock induced by deformation acceleration is enhanced by non-Fourier heat conduction with increased peak stress. The influence on the stress increases with the thermal relaxation time.

Keywords: maximum principle, non-Fourier heat conduction, residual correction method, thermo-elastic response

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2216 Comparison of the Positive and Indeterminate Rates of QuantiFERON-TB Gold In-Tube and T-SPOT. TB According to Age-group

Authors: Kina Kim

Abstract:

Background: There are two types of interferon-gamma release assays (IGRAs) in use for the detection of latent tuberculosis infection (LTBI), QuantiFERON-TB Gold In-tube (QFT-GIT) and T-SPOT.TB. There are some reports that IGRA results are affected by the patient's age. This study aims to compare the results of both IGRA tests according to age groups. Methods: We reviewed 54,882 samples referred to an independent reference laboratory (Seegene Medical Foundation, Seoul, Korea) for the diagnosis of LTBI from January 1, 2021, to December 31, 2021. This retrospective study enrolled 955 patients tested using QFT-GIT and 53,927 patients tested using T-SPOT.TB. The results of both IGRAs were divided in three age groups (0-9, 10-17, and ≥18-year old). The positive rates and the indeterminate rates between QFT-GIT and T-SPOT.TB were compared. We also evaluated the differences in positive and indeterminate rates by age-group. Results: The positive rate of QFT-GIT was 20.1% (192/955) and that of T-SPOT.TB was 8.7% (4704/53927) in overall patients. The positive rates of QFT-GIT in individuals aged 0-9, 10-17, and over 18-year old were 15.4%, 13.3%, and 22.0%, respectively. The positive rates of T-SPOT.TB were 8.9%, 2.0% and 8.8%,in each agegroup, respectively.The overall prevalence of indeterminate results was 2.1% (20/955) of QFT-GIT and 0.5% (270/53927) of T-SPOT.TB. The indeterminate rates of QFT-GIT in individuals aged 0-9, 10-17, and over 18 years were 0.4%, 6.7%, and 2.6%, respectively. The indeterminate rate of T-SPOT.TB were 0.5%, 0.7% and 0.5%,in each age group, respectively. Conclusion: Our findings suggest that T-SPOT.TB has a lower rate of positive results in overall patients and a lower rate of indeterminate results than those of QFT-GIT. The highest positive rate was found in the over 18 years group for QFT-GIT, but the positive rates of T-SPOT.TB was not significantly different among groups by age. QFT-GIT showed variable and higher indeterminate rates according to age group, but T-SPOT.TB showed lower rates in all age groups(<1%).

Keywords: LTBI, IGRA, QFT-GIT, T-SPOT. TB

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2215 Parkinson’s Disease Detection Analysis through Machine Learning Approaches

Authors: Muhtasim Shafi Kader, Fizar Ahmed, Annesha Acharjee

Abstract:

Machine learning and data mining are crucial in health care, as well as medical information and detection. Machine learning approaches are now being utilized to improve awareness of a variety of critical health issues, including diabetes detection, neuron cell tumor diagnosis, COVID 19 identification, and so on. Parkinson’s disease is basically a disease for our senior citizens in Bangladesh. Parkinson's Disease indications often seem progressive and get worst with time. People got affected trouble walking and communicating with the condition advances. Patients can also have psychological and social vagaries, nap problems, hopelessness, reminiscence loss, and weariness. Parkinson's disease can happen in both men and women. Though men are affected by the illness at a proportion that is around partial of them are women. In this research, we have to get out the accurate ML algorithm to find out the disease with a predictable dataset and the model of the following machine learning classifiers. Therefore, nine ML classifiers are secondhand to portion study to use machine learning approaches like as follows, Naive Bayes, Adaptive Boosting, Bagging Classifier, Decision Tree Classifier, Random Forest classifier, XBG Classifier, K Nearest Neighbor Classifier, Support Vector Machine Classifier, and Gradient Boosting Classifier are used.

Keywords: naive bayes, adaptive boosting, bagging classifier, decision tree classifier, random forest classifier, XBG classifier, k nearest neighbor classifier, support vector classifier, gradient boosting classifier

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2214 Dynamics of the Landscape in the Different Colonization Models Implemented in the Legal Amazon

Authors: Valdir Moura, FranciléIa De Oliveira E. Silva, Erivelto Mercante, Ranieli Dos Anjos De Souza, Jerry Adriani Johann

Abstract:

Several colonization projects were implemented in the Brazilian Legal Amazon in the 1970s and 1980s. Among all of these colonization projects, the most prominent were those with the Fishbone and Topographic models. Within this scope, the projects of settlements known as Anari and Machadinho were created, which stood out because they are contiguous areas with different models and structure of occupation and colonization. The main objective of this work was to evaluate the dynamics of Land-Use and Land-Cover (LULC) in two different colonization models, implanted in the State of Rondonia in the 1980s. The Fishbone and Topographic models were implanted in the Anari and Machadinho settlements respectively. The understanding of these two forms of occupation will help in future colonization programs of the Brazilian Legal Amazon. These settlements are contiguous areas with different occupancy structures. A 32-year Landsat time series (1984-2016) was used to evaluate the rates and trends in the LULC process in the different colonization models. In the different occupation models analyzed, the results showed a rapid loss of primary and secondary forests (deforestation), mainly due to the dynamics of use, established by the Agriculture/Pasture (A/P) relation and, with heavy dependence due to road construction.

Keywords: land-cover, deforestation, rate fragments, remote sensing, secondary succession

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2213 Characterization of Filled HNBR Elastomers for Sealing Application in Cold Climate Areas

Authors: Anton G. Akulichev, Avinash Tiwari, Ben Alcock, Andreas Echtermeyer

Abstract:

Low temperatures are known to pose a major threat for polymers; many are prone to excessive stiffness or even brittleness. There is a technology gap between the properties of existing elastomeric sealing materials and the properties needed for service in extremely cold regions. Moreover, some aspects of low temperature behaviour of rubber are not thoroughly studied and understood. The paper presents results of laboratory testing of a conventional oilfield HNBR (hydrogenated nitrile butadiene rubber) elastomer at low climatic temperatures above and below its glass transition point, as well as the performance of some filled HNBR formulations. Particular emphasis in the experiments is put on rubber viscoelastic characteristics studied by Dynamic Mechanical Analysis (DMA) and quasi-static mechanical testing results at low temperatures. As demonstrated by the stress relaxation and DMA experiments the transition region near Tg of the studied compound has the most striking features, like rapid stress relaxation, as compared to the glassy and rubbery plateau. In addition the quasi-static experiments show that molecular movement below Tg is not completely frozen, but rather evident and manifested in a certain stress decay as well. The effect of temperature and filler additions on typical mechanical and other properties of the materials is also discussed.

Keywords: characterization, filled elastomers, HNBR, low temperature

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2212 Microbial Diversity Assessment in Household Point-of-Use Water Sources Using Spectroscopic Approach

Authors: Syahidah N. Zulkifli, Herlina A. Rahim, Nurul A. M. Subha

Abstract:

Sustaining water quality is critical in order to avoid any harmful health consequences for end-user consumers. The detection of microbial impurities at the household level is the foundation of water security. Water quality is now monitored only at water utilities or infrastructure, such as water treatment facilities or reservoirs. This research provides a first-hand scientific understanding of microbial composition presence in Malaysia’s household point-of-use (POUs) water supply influenced by seasonal fluctuations, standstill periods, and flow dynamics by using the NIR-Raman spectroscopic technique. According to the findings, 20% of water samples were contaminated by pathogenic bacteria, which are Legionella and Salmonella cells. A comparison of the spectra reveals significant signature peaks (420 cm⁻¹ to 1800 cm⁻¹), including species-specific bands. This demonstrates the importance of regularly monitoring POUs water quality to provide a safe and clean water supply to homeowners. Conventional Raman spectroscopy, up-to-date, is no longer suited for real-time monitoring. Therefore, this study introduced an alternative micro-spectrometer to give a rapid and sustainable way of monitoring POUs water quality. Assessing microbiological threats in water supply becomes more reliable and efficient by leveraging IoT protocol.

Keywords: microbial contaminants, water quality, water monitoring, Raman spectroscopy

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2211 Uncommon Presentation of Iscahemic Heart Disease with Sheehan’s Syndrome at Mid-Level Private Hospital of Bangladesh and Its Management- A Case Report

Authors: Nazmul Haque, Syeda Tasnuva Maria

Abstract:

Sheehan's Syndrome (SS), also known as postpartum hypopituitarism, is a rare but potentially serious condition resulting from ischemic necrosis of the pituitary gland, often occurring during or after childbirth. This syndrome is characterized by hypopituitarism, leading to deficiencies in various hormones produced by the pituitary gland. The primary cause is typically severe postpartum hemorrhage, leading to inadequate blood supply and subsequent necrosis of the pituitary tissue. This chronic hypopituitarism sometimes plays the role of premature atherosclerosis, which may lead to cardiovascular disease. This abstract provides a comprehensive overview of Sheehan's Syndrome with ischaemic heart disease, encompassing its pathophysiology, clinical manifestations, and current management strategies. The disorder presents a wide spectrum of symptoms, including chest pain, fatigue, amenorrhea, lactation failure, hypothyroidism, and adrenal insufficiency. Timely diagnosis is crucial, as delayed recognition can lead to complications and long-term health consequences. We herein report a patient complaining of chronic fatigue symptoms, aggressiveness, chest pain, and breathlessness with repeated LOC that were diagnosed with SS with IHD. The patient was treated with antiplatelet, antianginal, steroids, and hormone replacement with marked improvement in his overall condition.

Keywords: ischaemic heart disease, Sheehan's syndrome, post-partum haemorrhage, pituitary gland

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2210 Vision-Based Daily Routine Recognition for Healthcare with Transfer Learning

Authors: Bruce X. B. Yu, Yan Liu, Keith C. C. Chan

Abstract:

We propose to record Activities of Daily Living (ADLs) of elderly people using a vision-based system so as to provide better assistive and personalization technologies. Current ADL-related research is based on data collected with help from non-elderly subjects in laboratory environments and the activities performed are predetermined for the sole purpose of data collection. To obtain more realistic datasets for the application, we recorded ADLs for the elderly with data collected from real-world environment involving real elderly subjects. Motivated by the need to collect data for more effective research related to elderly care, we chose to collect data in the room of an elderly person. Specifically, we installed Kinect, a vision-based sensor on the ceiling, to capture the activities that the elderly subject performs in the morning every day. Based on the data, we identified 12 morning activities that the elderly person performs daily. To recognize these activities, we created a HARELCARE framework to investigate into the effectiveness of existing Human Activity Recognition (HAR) algorithms and propose the use of a transfer learning algorithm for HAR. We compared the performance, in terms of accuracy, and training progress. Although the collected dataset is relatively small, the proposed algorithm has a good potential to be applied to all daily routine activities for healthcare purposes such as evidence-based diagnosis and treatment.

Keywords: daily activity recognition, healthcare, IoT sensors, transfer learning

Procedia PDF Downloads 123