Search results for: motor fault diagnosis
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3294

Search results for: motor fault diagnosis

1044 Copy Effect Myopic Anisometropia in a Pair of Monozygotic Twins: A Case Report

Authors: Fatma Sümer

Abstract:

Introduction: This case report aims to report myopic anisometropia with copy-image in monozygotic twins. Methods: In February 2021, a 6-year-old identical twin was seen, who was referred to us with the diagnosis of amblyopia in their left eye from an external center. Both twins had a full ophthalmic examination, which included visual acuity testing, ocular motility testing, cycloplegic refraction, and fundus examination. Results: On examination, “copy image” myopic anisometropia was discovered. Twin 1 had anisometropia with myopic astigmatism in the left eye. His cycloplegic refraction was +1.00 (-0.75x 75) in the right eye and -8.0 (-1.50x175) in the left eye. Similarly, twin 2 had anisometropia with myopic astigmatism in the left eye. His cycloplegic refraction was -7.75 (-1.50x180) in the left eye and +1.25 (-0.75x90 ) in the right eye. The best-corrected visual acuity was 20/60 in the amblyopic eyes and 20/20 in the unaffected eyes. There was no ocular deviation. In either patient, a slit-lamp microscopic examination revealed no abnormalities in the anterior parts of either eye. Fundoscopic examination revealed no abnormalities. No abnormal ocular movements were demonstrated. Conclusion: As far as we have reviewed in the literature, previous studies with twins were mostly concerned with mirror-effect myopic anisometropia and myopic anisometropia, whereas ipsilateral amblyopia and anisometropia were not reported in monozygotic twins. This case underscores the possible genetic basis of myopic anisometropia.

Keywords: amblyopia, anisometropia, myopia, twins

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1043 Development of a Novel Score for Early Detection of Hepatocellular Carcinoma in Patients with Hepatitis C Virus

Authors: Hatem A. El-Mezayen, Hossam Darwesh

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Background/Aim: Hepatocellular carcinoma (HCC) is often diagnosed at advanced stage where effective therapies are lacking. Identification of new scoring system is needed to discriminate HCC patients from those with chronic liver disease. Based on the link between vascular endothelial growth factor (VEGF) and HCC progression, we aimed to develop a novel score based on combination of VEGF and routine laboratory tests for early prediction of HCC. Methods: VEGF was assayed for HCC group (123), liver cirrhosis group (210) and control group (50) by Enzyme Linked Immunosorbent Assay (ELISA). Data from all groups were retrospectively analyzed including α feto protein (AFP), international normalized ratio (INR), albumin and platelet count, transaminases, and age. Areas under ROC curve were used to develop the score. Results: A novel index named hepatocellular carcinoma-vascular endothelial growth factor score (HCC-VEGF score)=1.26 (numerical constant) + 0.05 ×AFP (U L-1)+0.038 × VEGF(ng ml-1)+0.004× INR –1.02 × Albumin (g l-1)–0.002 × Platelet count × 109 l-1 was developed. HCC-VEGF score produce area under ROC curve of 0.98 for discriminating HCC patients from liver cirrhosis with sensitivity of 91% and specificity of 82% at cut-off 4.4 (ie less than 4.4 considered cirrhosis and greater than 4.4 considered HCC). Conclusion: Hepatocellular carcinoma-VEGF score could replace AFP in HCC screening and follow up of cirrhotic patients.

Keywords: Hepatocellular carcinoma, cirrhosis, HCV, diagnosis, tumor markers

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1042 Efficacy of Phonological Awareness Intervention for People with Language Impairment

Authors: I. Wardana Ketut, I. Suparwa Nyoman

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This study investigated the form and characteristic of speech sound produced by three Balinese subjects who have recovered from aphasia as well as intervened their language impairment on side of linguistic and neuronal aspects of views. The failure of judging the speech sound was caused by impairment of motor cortex that indicated there were lesions in left hemispheric language zone. Sound articulation phenomena were in the forms of phonemes deletion, replacement or assimilation in individual words and meaning building for anomic aphasia. Therefore, the Balinese sound patterns were stimulated by showing pictures to the subjects and recorded to recognize what individual consonants or vowels they unclearly produced and to find out how the sound disorder occurred. The physiology of sound production by subject’s speech organs could not only show the accuracy of articulation but also any level of severity the lesion they suffered from. The subjects’ speech sounds were investigated, classified and analyzed to know how poor the lingual units were and observed to clarify weaknesses of sound characters occurred either for place or manner of articulation. Many fricative and stopped consonants were replaced by glottal or palatal sounds because the cranial nerve, such as facial, trigeminal, and hypoglossal underwent impairment after the stroke. The phonological intervention was applied through a technique called phonemic articulation drill and the examination was conducted to know any change has been obtained. The finding informed that some weak articulation turned into clearer sound and simple meaning of language has been conveyed. The hierarchy of functional parts of brain played important role of language formulation and processing. From this finding, it can be clearly emphasized that this study supports the role of right hemisphere in recovery from aphasia is associated with functional brain reorganization.

Keywords: aphasia, intervention, phonology, stroke

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1041 Study on the Incidence of Chikungunya Infection in Swat Region

Authors: Nasib Zaman, Maneesha Kour, Muhammad Rizwan, Fazal Akbar

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Abstract: Chikungunya fever is a re-emerging rapidly spreading mosquito-borne disease cause by Aedes albopictus and Aedes aegypti mosquito vectors. Currently, it is affecting millions of people globally. Objective: This study's main objective was to find the incidence of chikungunya fever in the Swat region and the factors associated with the spread of this infection. Method: This study was carried out in different areas of Swat. Blood samples and data were collected from selected patients, and a questionnaire was filled for each patient. 3-5ml of the specimen was taken from the patient's vein and serum, or plasma was separated by centrifugation. Chikungunya tests were performed for IgG and IgM antibodies. The data was analyzed by SPSS and Graph Paid Prism 5. Results: A total of 169 patients were included in this study, out of which 103 (60.9%) having age less than 30 years were positive for chikungunya infection and 66 (39.1%) having more than 30 years were negative for this infection. Only 1 (0.6%) were positive for both IgG and IgM antibody. About 15 (8.9%) patients have diagnosed with positive IgG antibodies, and 25 (26.6%) patients were positive for IgM positive antibodies. The infection rate was significantly higher in males compared to females 71 (59.6%) vs. 14 (38%) P value=0.088, OR=1.7. Conclusion: This study concludes clinical knowledge and awareness that are necessary for a diagnosis of chikungunya infection properly. Therefore it is important to educate people for the eradication of this infection. Recommendation: This study also recommends investigating the other risk factors associated with this infection.

Keywords: Chikungunya, risk factor, Incidence, antibodies, mosquito

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1040 Design, Modeling, Fabrication, and Testing of a Scaled down Hybrid Rocket Engine

Authors: Pawthawala Nancy Manish, Syed Alay Hashim

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A hybrid rocket is a rocket engine which uses propellants in two different states of matter- one is in solid and the other either gas or liquid. A hybrid rocket exhibit advantages over both liquid rockets and solid rockets especially in terms of simplicity, stop-start-restart capabilities, safety and cost. This paper deals the design and development of a hybrid rocket having paraffin wax as solid fuel and liquid oxygen as oxidizer. Due to variation of pressure in combustion chamber there is significantly change in mass flow rate, burning rate and uneven regression along the length of the grain. This project describes the working model of a hybrid propellant rocket motor. We have designed a hybrid rocket thrust chamber based on the predetermined combustion chamber pressure and the properties of hybrid propellant. This project is all ready in working condition with normal oxygen injector. Now we have planned to modify the injector design to improve the combustion property. We will use spray type injector for injecting the oxidizer. This idea will increase the performance followed by the regression rate of the solid fuel. By employing mass conservation law, oxygen mass flux, oxidizer/fuel ratio and regression rate the thrust coefficient can be obtained for our current design. CATIA V5 R20 is our design software for the complete setup. This project is fully based on experimental evaluation and the collection of combustion and flow parameters. The thrust chamber is made of stainless steel and the duration of test is around 15-20 seconds (Maximum). These experiments indicates that paraffin based fuel provides the opportunity to satisfy a broad range of mission requirements for the next generation of the hybrid rocket system.

Keywords: burning rate, liquid oxygen, mass flow rate, paraffin wax and sugar

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1039 A Generative Pretrained Transformer-Based Question-Answer Chatbot and Phantom-Less Quantitative Computed Tomography Bone Mineral Density Measurement System for Osteoporosis

Authors: Mian Huang, Chi Ma, Junyu Lin, William Lu

Abstract:

Introduction: Bone health attracts more attention recently and an intelligent question and answer (QA) chatbot for osteoporosis is helpful for science popularization. With Generative Pretrained Transformer (GPT) technology developing, we build an osteoporosis corpus dataset and then fine-tune LLaMA, a famous open-source GPT foundation large language model(LLM), on our self-constructed osteoporosis corpus. Evaluated by clinical orthopedic experts, our fine-tuned model outperforms vanilla LLaMA on osteoporosis QA task in Chinese. Three-dimensional quantitative computed tomography (QCT) measured bone mineral density (BMD) is considered as more accurate than DXA for BMD measurement in recent years. We develop an automatic Phantom-less QCT(PL-QCT) that is more efficient for BMD measurement since no need of an external phantom for calibration. Combined with LLM on osteoporosis, our PL-QCT provides efficient and accurate BMD measurement for our chatbot users. Material and Methods: We build an osteoporosis corpus containing about 30,000 Chinese literatures whose titles are related to osteoporosis. The whole process is done automatically, including crawling literatures in .pdf format, localizing text/figure/table region by layout segmentation algorithm and recognizing text by OCR algorithm. We train our model by continuous pre-training with Low-rank Adaptation (LoRA, rank=10) technology to adapt LLaMA-7B model to osteoporosis domain, whose basic principle is to mask the next word in the text and make the model predict that word. The loss function is defined as cross-entropy between the predicted and ground-truth word. Experiment is implemented on single NVIDIA A800 GPU for 15 days. Our automatic PL-QCT BMD measurement adopt AI-associated region-of-interest (ROI) generation algorithm for localizing vertebrae-parallel cylinder in cancellous bone. Due to no phantom for BMD calibration, we calculate ROI BMD by CT-BMD of personal muscle and fat. Results & Discussion: Clinical orthopaedic experts are invited to design 5 osteoporosis questions in Chinese, evaluating performance of vanilla LLaMA and our fine-tuned model. Our model outperforms LLaMA on over 80% of these questions, understanding ‘Expert Consensus on Osteoporosis’, ‘QCT for osteoporosis diagnosis’ and ‘Effect of age on osteoporosis’. Detailed results are shown in appendix. Future work may be done by training a larger LLM on the whole orthopaedics with more high-quality domain data, or a multi-modal GPT combining and understanding X-ray and medical text for orthopaedic computer-aided-diagnosis. However, GPT model gives unexpected outputs sometimes, such as repetitive text or seemingly normal but wrong answer (called ‘hallucination’). Even though GPT give correct answers, it cannot be considered as valid clinical diagnoses instead of clinical doctors. The PL-QCT BMD system provided by Bone’s QCT(Bone’s Technology(Shenzhen) Limited) achieves 0.1448mg/cm2(spine) and 0.0002 mg/cm2(hip) mean absolute error(MAE) and linear correlation coefficient R2=0.9970(spine) and R2=0.9991(hip)(compared to QCT-Pro(Mindways)) on 155 patients in three-center clinical trial in Guangzhou, China. Conclusion: This study builds a Chinese osteoporosis corpus and develops a fine-tuned and domain-adapted LLM as well as a PL-QCT BMD measurement system. Our fine-tuned GPT model shows better capability than LLaMA model on most testing questions on osteoporosis. Combined with our PL-QCT BMD system, we are looking forward to providing science popularization and early morning screening for potential osteoporotic patients.

Keywords: GPT, phantom-less QCT, large language model, osteoporosis

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1038 PET Image Resolution Enhancement

Authors: Krzysztof Malczewski

Abstract:

PET is widely applied scanning procedure in medical imaging based research. It delivers measurements of functioning in distinct areas of the human brain while the patient is comfortable, conscious and alert. This article presents the new compression sensing based super-resolution algorithm for improving the image resolution in clinical Positron Emission Tomography (PET) scanners. The issue of motion artifacts is well known in Positron Emission Tomography (PET) studies as its side effect. The PET images are being acquired over a limited period of time. As the patients cannot hold breath during the PET data gathering, spatial blurring and motion artefacts are the usual result. These may lead to wrong diagnosis. It is shown that the presented approach improves PET spatial resolution in cases when Compressed Sensing (CS) sequences are used. Compressed Sensing (CS) aims at signal and images reconstructing from significantly fewer measurements than were traditionally thought necessary. The application of CS to PET has the potential for significant scan time reductions, with visible benefits for patients and health care economics. In this study the goal is to combine super-resolution image enhancement algorithm with CS framework to achieve high resolution PET output. Both methods emphasize on maximizing image sparsity on known sparse transform domain and minimizing fidelity.

Keywords: PET, super-resolution, image reconstruction, pattern recognition

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1037 Nephroblastoma at Universitas Academic Hospital Complex in the Last 20 Years

Authors: I. Iroka, L. Mgidlana, J. Willoughby, S. Dhlamini, P. Nxumalo, S. Sefadi, A. Mthembu, E. Gerber, E. Brits

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Introduction: Nephroblastoma is a common paediatric tumor with good survival rates when diagnosed and treated early. Method: This retrospective study aimed to describe the patients with nephroblastoma seen at Universitas Academic Hospital Complex between the years 2000 and 2020. Results: In the study period, there were 207 patients identified. The patient profile had slightly more male than female patients; the median age was under four years of age. The study found a median delay of one month between symptom onset and diagnosis; a common cause was a delay in seeking care. Patients diagnosed and treated more than a month after symptoms started had poorer survival rates. There was a higher rate of Stage IV disease compared to similar studies in South Africa. Good preoperative histology and no relapse had good survival rates.. Patients from Lesotho had longer delays and presented with more severe diseases than the South African cohort. Conclusion: Early identification and treatment lead to better outcomes. Health-seeking behaviour, misdiagnosis, and referral delays might contribute to the long delays. A targeted study for patients from Lesotho is recommended.

Keywords: nephroblastoma, South Africa, Lesotho, developing country

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1036 Diagnostic Performance of Tumor Associated Trypsin Inhibitor in Early Detection of Hepatocellular Carcinoma in Patients with Hepatitis C Virus

Authors: Aml M. El-Sharkawy, Hossam M. Darwesh

Abstract:

Abstract— Background/Aim: Hepatocellular carcinoma (HCC) is often diagnosed at advanced stage where effective therapies are lacking. Identification of new scoring system is needed to discriminate HCC patients from those with chronic liver disease. Based on the link between tumor associated trypsin inhibitor (TATI) and HCC progression, we aimed to develop a novel score based on combination of TATI and routine laboratory tests for early prediction of HCC. Methods: TATI was assayed for HCC group (123), liver cirrhosis group (210) and control group (50) by Enzyme Linked Immunosorbent Assay (ELISA). Data from all groups were retrospectively analyzed including α feto protein (AFP), international normalized ratio (INR), albumin and platelet count, transaminases, and age. Areas under ROC curve were used to develop the score. Results: A novel index named hepatocellular carcinoma-vascular endothelial growth factor score (HCC-TATI score) = 3.1 (numerical constant) + 0.09 ×AFP (U L-1) + 0.067 × TATI (ng ml-1) + 0.16 × INR – 1.17 × Albumin (g l-1) – 0.032 × Platelet count × 109 l-1 was developed. HCC-TATI score produce area under ROC curve of 0.98 for discriminating HCC patients from liver cirrhosis with sensitivity of 91% and specificity of 82% at cut-off 6.5 (ie less than 6.5 considered cirrhosis and greater than 4.4 considered HCC). Conclusion: Hepatocellular carcinoma-TATI score could replace AFP in HCC screening and follow up of cirrhotic patients.

Keywords: Hepatocellular carcinoma, cirrhosis, HCV, diagnosis, TATI

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1035 Comparison of Breast Surface Doses for Full-Field Digital Mammography and Digital Breast Tomosynthesis Using Breast Phantoms

Authors: Chia-Hui Chen, Chien-Kuo Wang

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Background: Full field digital mammography (FFDM) is widely used in diagnosis of breast cancer. Digital breast tomosynthesis (DBT) has recently been introduced into the clinic and is being used for screening for breast cancer in the general population. Hence, the radiation dose delivered to the patients involved in an imaging protocol is of utmost concern. Aim: To compare the surface radiation dose (ESD) of digital breast tomosynthesis (DBT) and full-field digital mammography (FFDM) by using breast phantoms. Method: We analyzed the average entrance surface dose (ESD) of FFDM and DBT by using breast phantoms. Optically Stimulated luminescent Dosimeters (OSLD) were placed in a tissue-equivalent Breast phantom at difference sites of interest. Absorbed dose measurements were obtained after digital breast tomosynthesis (DBT) and full-field digital mammography (FFDM) exposures. Results: An automatic exposure control (AEC) is proposed for surface dose measurement during DBT and FFDM. The mean ESD values for DBT and FFDM were 6.37 mGy and 3.51mGy, respectively. Using of OSLD measured for surface dose during DBT and FFDM. There were 19.87 mGy and 11.36 mGy, respectively. The surface exposure dose of DBT could possibly be increased by two times with FFDM. Conclusion: The radiation dose from DBT was higher than that of FFDM and the difference in dose between AEC and OSLD measurements at phantom surface.

Keywords: full-field digital mammography, digital breast tomosynthesis, optically stimulated luminescent dosimeters, surface dose

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1034 An Analytical Formulation of Pure Shear Boundary Condition for Assessing the Response of Some Typical Sites in Mumbai

Authors: Raj Banerjee, Aniruddha Sengupta

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An earthquake event, associated with a typical fault rupture, initiates at the source, propagates through a rock or soil medium and finally daylights at a surface which might be a populous city. The detrimental effects of an earthquake are often quantified in terms of the responses of superstructures resting on the soil. Hence, there is a need for the estimation of amplification of the bedrock motions due to the influence of local site conditions. In the present study, field borehole log data of Mangalwadi and Walkeswar sites in Mumbai city are considered. The data consists of variation of SPT N-value with the depth of soil. A correlation between shear wave velocity (Vₛ) and SPT N value for various soil profiles of Mumbai city has been developed using various existing correlations which is used further for site response analysis. MATLAB program is developed for studying the ground response analysis by performing two dimensional linear and equivalent linear analysis for some of the typical Mumbai soil sites using pure shear (Multi Point Constraint) boundary condition. The model is validated in linear elastic and equivalent linear domain using the popular commercial program, DEEPSOIL. Three actual earthquake motions are selected based on their frequency contents and durations and scaled to a PGA of 0.16g for the present ground response analyses. The results are presented in terms of peak acceleration time history with depth, peak shear strain time history with depth, Fourier amplitude versus frequency, response spectrum at the surface etc. The peak ground acceleration amplification factors are found to be about 2.374, 3.239 and 2.4245 for Mangalwadi site and 3.42, 3.39, 3.83 for Walkeswar site using 1979 Imperial Valley Earthquake, 1989 Loma Gilroy Earthquake and 1987 Whitter Narrows Earthquake, respectively. In the absence of any site-specific response spectrum for the chosen sites in Mumbai, the generated spectrum at the surface may be utilized for the design of any superstructure at these locations.

Keywords: deepsoil, ground response analysis, multi point constraint, response spectrum

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1033 Influence of HbA1c on Nitric Oxide Level in Patients with Type 2 Diabetes Mellitus

Authors: Dara Kutsyk, Olga Bondarenko, Mariya Sorochka

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In 21-century type 2 diabetes (T2D) has become a global health and social problem in the whole world. The goal of treatment for patients with T2D is to prevent complications of diabetes - macrovascular diseases (heart disease, stroke, and peripheral vascular disease) and microvascular diseases (retinopathy, neuropathy and nephropathy). Nitric oxide (NO) plays an important role in maintaining vascular homeostasis. Loss of NO function is one of the earliest indicators of disease and its progression especially in patients with T2D. Aim: To compare NO level between patients with well and bad controlled glycemia in T2D. Methods: The study included 32 patients with T2D. The diagnosis of T2D was confirmed due to International Diabetes Federation (IDF) criteria 2015. Patients were divided into two groups: with well controlled glycaemia (HbA1c < 7%) and bad controlled glycaemia (HbA1c > 7%). The control group consists of 15 healthy subjects. Results: NO level in patients with T2D is significantly higher (27,2 ±3,1 µmol), compared to controls (18,86±0,9 µmol; p < 0,001). A significant difference in NO level was found between patients with bad controlled glycaemia (25,9±2,2 µmol) and well controlled glycaemia (28,7 ± 3,0 µmol; p<0,01). The study showed a moderate negative correlation between NO level and HbA1c (-0,399; р< 0,05). Conclusions: Production of NO is impaired in patients with T2D, especially with badly controlled glycaemia. With the increase in HbAc serum NO decreases. This can be the main target for prevention vascular complication in T2D.

Keywords: type 2 diabetes, glycated hemoglobin, nitric oxide, Diabetes mellitus

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1032 Quality of Life of Patients on Oral Antiplatelet Therapy in Outpatient Cardiac Department Dr. Hasan Sadikin Central General Hospital Bandung

Authors: Andhiani Sharfina Arnellya, Mochammad Indra Permana, Dika Pramita Destiani, Ellin Febrina

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Health Research Data, Ministry of Health of Indonesia in 2007, showed coronary heart disease (CHD) or coronary artery disease (CAD) was the third leading cause of death in Indonesia after hypertension and stroke with 7.2% incidence rate. Antiplatelet is one of the important therapy in management of patients with CHD. In addition to therapeutic effect on patients, quality of life is one aspect of another assessment to see the success of antiplatelet therapy. The purpose of this study was to determine the quality of life of patients on oral antiplatelet therapy in outpatient cardiac department Dr. Hasan Sadikin central general hospital, Bandung, Indonesia. This research is a cross sectional by collecting data through quality of life questionnaire of patients which performed prospectively as primary data and secondary data from medical record of patients. The results of this study showed that 54.3% of patients had a good quality of life, 45% had a moderate quality of life, and 0.7% had a poor quality of life. There are no significant differences in quality of life-based on age, gender, diagnosis, and duration of drug use.

Keywords: antiplatelet, quality of life, coronary artery disease, coronary heart disease

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1031 An Implementation of Fuzzy Logic Technique for Prediction of the Power Transformer Faults

Authors: Omar M. Elmabrouk., Roaa Y. Taha., Najat M. Ebrahim, Sabbreen A. Mohammed

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Power transformers are the most crucial part of power electrical system, distribution and transmission grid. This part is maintained using predictive or condition-based maintenance approach. The diagnosis of power transformer condition is performed based on Dissolved Gas Analysis (DGA). There are five main methods utilized for analyzing these gases. These methods are International Electrotechnical Commission (IEC) gas ratio, Key Gas, Roger gas ratio, Doernenburg, and Duval Triangle. Moreover, due to the importance of the transformers, there is a need for an accurate technique to diagnose and hence predict the transformer condition. The main objective of this technique is to avoid the transformer faults and hence to maintain the power electrical system, distribution and transmission grid. In this paper, the DGA was utilized based on the data collected from the transformer records available in the General Electricity Company of Libya (GECOL) which is located in Benghazi-Libya. The Fuzzy Logic (FL) technique was implemented as a diagnostic approach based on IEC gas ratio method. The FL technique gave better results and approved to be used as an accurate prediction technique for power transformer faults. Also, this technique is approved to be a quite interesting for the readers and the concern researchers in the area of FL mathematics and power transformer.

Keywords: dissolved gas-in-oil analysis, fuzzy logic, power transformer, prediction

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1030 Urinary Neutrophil Gelatinase Associated Lipocalin as Diagnostic Biomarkers for Lupus Nephritis

Authors: Lorena GóMez Escorcia, Gustavo Aroca MartíNez, Jose Luiz Villarreal, Elkin Navarro Quiroz

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Lupus nephritis (LN) is a high-cost disease, occurring in about half of patients with Systemic Lupus Erythematosus (SLE). Renal biopsy constitutes the only protocol that, to date, allows a correct diagnosis of the level of renal involvement in these patients. However, this procedure can have various adverse effects such as kidney bleeding, muscle bleeding, infection, pain, among others. Therefore, the development of new diagnostic alternatives is required. The neutrophil gelatinase-associated lipocalin (NGAL) has been emerging as a novel biomarker of acute kidney injury. The aim of this study was to assess urinary NGAL levels as a marker for disease activity in patients with lupus nephritis. For this work included 50 systemic lupus erythematosus (SLE) patients, 50 with active lupus nephritis (LN), and 50 without autoimmune and renal disease as controls. TNGAL in urine samples was measured by enzyme-linked immunosorbent assay (ELISA). The results revealed that patients with kidney damage had an elevated urinary NGAL as compared to patients with lupus without kidney damage and controls (p <0.005), and the mean of uNGAL was (28.72 ± 4.53), (19.51 ± 4.72), (8.91 ± 3.37) respectively. Measurement of urinary NGAL levels showed a very good diagnostic performance for discriminating patients with Lupus nephritis from SLE without renal damage and of control individuals.

Keywords: lupus nephritis, biomarker, NGAL, urine samples

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1029 Sexual Risk Behaviours among Patients Living with HIV/AIDS in Douala in 2012

Authors: Etienne Sugewe

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Purpose: The establishment of a positive HIV serologic status of an individual could have been an inhibitory factor to prevent risk behaviours in people living with HIV/AIDS. We conducted a cross-sectional study in order to assess the prevalence and predictors of risk behaviors among HIV-positive people in Douala-Cameroon. Methods: We used pre-checked questionnaires to systematically collect data from four HIV treatment centers in Douala. This was done to some of them during the distribution of drugs and to others during their classical rendezvous between the months of May and July 2012. The Chi-Square and Student t-test were used for cross tabulation of variables; multiple regression analysis was performed to identify predictors of risky sexual behaviours. Results: Of the 330 persons interviewed, sixty percent were reported to have had sexual intercourse after the diagnosis of HIV. We obtained 37% HIV-positive partners, and 63% had HIV- negative partners or partners with unknown status. Among our patients, 45% of the subjects with regular partners reported to have had anal or vaginal sex. Those whose score on the knowledge about HIV/AIDS was < 50% and where 90% of them were less susceptible to the condom during intercourse (p: 0.01). About 74% of patients on ARV were less susceptible to the use of condoms during sexual intercourse (p: 0.03). Conclusion: Risk sexual behaviours among people living with HIV/AIDS are common and potentially expose their partners. For HIV-positive partners, these habits pose a real risk of suprainfection by other strains of HIV. The need to increase awareness and education among people living with HIV is therefore highly recommended.

Keywords: HIV/AIDS, behaviours, HIV positive, Douala, 2012

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1028 PsyVBot: Chatbot for Accurate Depression Diagnosis using Long Short-Term Memory and NLP

Authors: Thaveesha Dheerasekera, Dileeka Sandamali Alwis

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The escalating prevalence of mental health issues, such as depression and suicidal ideation, is a matter of significant global concern. It is plausible that a variety of factors, such as life events, social isolation, and preexisting physiological or psychological health conditions, could instigate or exacerbate these conditions. Traditional approaches to diagnosing depression entail a considerable amount of time and necessitate the involvement of adept practitioners. This underscores the necessity for automated systems capable of promptly detecting and diagnosing symptoms of depression. The PsyVBot system employs sophisticated natural language processing and machine learning methodologies, including the use of the NLTK toolkit for dataset preprocessing and the utilization of a Long Short-Term Memory (LSTM) model. The PsyVBot exhibits a remarkable ability to diagnose depression with a 94% accuracy rate through the analysis of user input. Consequently, this resource proves to be efficacious for individuals, particularly those enrolled in academic institutions, who may encounter challenges pertaining to their psychological well-being. The PsyVBot employs a Long Short-Term Memory (LSTM) model that comprises a total of three layers, namely an embedding layer, an LSTM layer, and a dense layer. The stratification of these layers facilitates a precise examination of linguistic patterns that are associated with the condition of depression. The PsyVBot has the capability to accurately assess an individual's level of depression through the identification of linguistic and contextual cues. The task is achieved via a rigorous training regimen, which is executed by utilizing a dataset comprising information sourced from the subreddit r/SuicideWatch. The diverse data present in the dataset ensures precise and delicate identification of symptoms linked with depression, thereby guaranteeing accuracy. PsyVBot not only possesses diagnostic capabilities but also enhances the user experience through the utilization of audio outputs. This feature enables users to engage in more captivating and interactive interactions. The PsyVBot platform offers individuals the opportunity to conveniently diagnose mental health challenges through a confidential and user-friendly interface. Regarding the advancement of PsyVBot, maintaining user confidentiality and upholding ethical principles are of paramount significance. It is imperative to note that diligent efforts are undertaken to adhere to ethical standards, thereby safeguarding the confidentiality of user information and ensuring its security. Moreover, the chatbot fosters a conducive atmosphere that is supportive and compassionate, thereby promoting psychological welfare. In brief, PsyVBot is an automated conversational agent that utilizes an LSTM model to assess the level of depression in accordance with the input provided by the user. The demonstrated accuracy rate of 94% serves as a promising indication of the potential efficacy of employing natural language processing and machine learning techniques in tackling challenges associated with mental health. The reliability of PsyVBot is further improved by the fact that it makes use of the Reddit dataset and incorporates Natural Language Toolkit (NLTK) for preprocessing. PsyVBot represents a pioneering and user-centric solution that furnishes an easily accessible and confidential medium for seeking assistance. The present platform is offered as a modality to tackle the pervasive issue of depression and the contemplation of suicide.

Keywords: chatbot, depression diagnosis, LSTM model, natural language process

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1027 Analytical-Behavioral Intervention for Women with Fibromyalgia: Evaluation of Effectiveness Clinical Significance and Reliable Change

Authors: Luziane De Fatima Kirchner, Maria De Jesus Dutra Dos Reis, Francine Nathalie Ferraresi Rodrigues Queluz

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This study evaluated the effect of two components of analytic-behavioral intervention (1-management of conditions of the physical environment, 2-management of the interpersonal relationship) of women with fibromyalgia (FM), besides Clinical Significance and Reliable Change at the end of the intervention. Self-report instruments were used to evaluate stress, anxiety, depression, social skills and disability due to pain and Cortisol Awakening Response (CAR). Four women with a medical diagnosis of FM (mean age 52.7; sd = 6.65), participated of the following procedures: initial evaluation, 10 sessions of component 1, intermediate evaluation, 10 sessions of component 2, and final evaluation. The 20 sessions were effective, with positive changes in the scores of all the self-report instruments, highlighting the results of the stress symptoms that had improvement in the intermediate evaluation. There was, however, no change in the cortisol response on awakening. The Clinical Significance or Reliable Change observed, according to the scores of the stress, anxiety, depression and social skills instruments, corroborated the reports of the participants in the session and the objectives of the treatment. Implications for future studies are discussed, above all, the importance in conducting evaluations with the use of direct measures together with self-report measures.

Keywords: behavioral intervention, clinical significance, fibromyalgia, reliable change

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1026 Historic Urban Landscape Approach, a Methodology to Elaborate Sustainable Development Plans through Culture and Heritage: The Case Study of Valverde de Burguillos (Spain)

Authors: Julia Rey Perez, Victoria Dominguez Ruiz

Abstract:

The phenomenon of depopulation puts the authorities at risk of abandoning a number of rural-urban areas of significant cultural value, affecting their architecture and intangible cultural heritage. The purpose of this research is to present a methodology created according to the UNESCO Recommendation on the Historic Urban Landscape (HUL), which through the identification of cultural values and attributes, leads to ´Strategic Plans´ build upon the culture and heritage. This methodology is based on the analysis of the town from three perspectives: 1) from the public administration, 2) from the discipline of architecture, and 3) from citizen perception. In order to be able to work on the development of a diagnosis from three very different approaches, collaborative cartographies have been used as working tools. The methodology discussed was applied in Valverde de Burguillos, in Spain, leading to the construction of an inclusive ‘Strategic Plan’ that integrates the management of the town within the overall territorial development plan. The importance of incorporating culture and heritage as a conductor for sustainable urban development through the HUL approach has allowed the local authorities to assume these new tools for heritage conservation, acknowledging community participation as the main element for the ´Strategic Plan” elaboration.

Keywords: rural heritage, citizen participation, inclusiveness, urban governance, UNESCO

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1025 Diagnostics of Subclinical Mastitis in Dairy Cows

Authors: G. Tanbayeva, Z. Myrzabekov, O. Tagayev, B. Barakhov, M. Tokayeva

Abstract:

Mastitis is widely spread among dairy cows bringing large economic damage resulting in decreased milk yield, deterioration of the milk quality, gastrointestinal tract disorders among young animals, culling of breeding stock, and expenses for sick animal treatment. Up-to-date and accurate diagnostics of subclinical (latent) mastitis in dairy cows has huge practical and economical significance. The aim of the research was to develop a new optimal alternative rapid method for the diagnosis of subclinical mastitis in cows. The study was performed in the laboratory of the Hygiene and Sanitation of Kazakh National Agrarian University. The first stage was to evaluate the different percentages of “Promastit” preparation. It showed that the best diagnostics capacity had 10% dilution. The second stage was to compare “Promastit” with some of the domestic and foreign analogues “Somatic-Test” (Denmark), “MastTest” (Russia), “Mastidin” (Ukraine), “Diagmast” (Kazakhstan). The observation was carried out on 520 dairy cows with subclinical mastitis on farms of Almaty region of Kazakhstan. The effectiveness was checked by milk sedimentation test. Our research tends to show that the diagnostic test "Promastitis" revealed subclinical mastitis in 193 out of 520 lactating cows (37.1% of those examined). At the same time, in the case of using other diagnostic tests, the given index was as follows: 35.5% (mastidin), 34.4% (masttest-AF), 33.8% (somatic-test Ecotest), 30.7% (diagmast).

Keywords: dairy cows, diagnostics, subclinical mastitis, test Promastit

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1024 Simultaneous Analysis of 25 Trace Elements in Micro Volume of Human Serum by Inductively Coupled Plasma–Mass Spectrometry

Authors: Azmawati Mohammed Nawi, Siok-Fong Chin, Shamsul Azhar Shah, Rahman Jamal

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In recent years, trace elements have gained importance as biomarkers in many chronic diseases. Unfortunately, the requirement for sample volume increases according to the extent of investigation for diagnosis or elucidating the mechanism of the disease. Here, we describe the method development and validation for simultaneous determination of 25 trace elements (lithium (Li), beryllium (Be), magnesium (Mg), aluminium (Al), vanadium (V), chromium (Cr), manganese (Mn), iron (Fe), cobalt (Co), nickel (Ni), copper (Cu), zinc (Zn), gallium (Ga), arsenic (As), selenium (Se), rubidium (Rb), strontium (Sr), silver (Ag), cadmium (Cd), caesium (Cs), barium (Ba), mercury (Hg), thallium (Tl), lead (Pb), uranium (U)) using just 20 µL of human serum. Serum samples were digested with nitric acid and hydrochloric acid (ratio 1:1, v/v) and analysed using inductively coupled plasma–mass spectrometry (ICP-MS). Seronorm®, a human-derived serum control material was used as quality control samples. The intra-day and inter-day precisions were consistently < 15% for all elements. The validated method was later applied to 30 human serum samples to evaluate its suitability. In conclusion, we have successfully developed and validated a precise and accurate analytical method for determining 25 trace elements requiring very low volume of human serum.

Keywords: acid digestion, ICP-MS, trace element, serum

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1023 Use of Nutritional Screening Tools in Cancer-Associated Malnutrition

Authors: Meryem Saban Guler, Saniye Bilici

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Malnutrition is a problem that significantly affects patients with cancer throughout the course of their illness, and it may be present from the moment of diagnosis until the end of treatment. We searched electronic databases using key terms such as ‘malnutrition in cancer patients’ or ‘nutritional status in cancer’ or ‘nutritional screening tools’ etc. Decline in nutritional status and continuing weight loss are associated with an increase in number and severity of complications, impaired quality of life and decreased survival rate. Nutrition is an important factor in the treatment and progression of cancer. Cancer patients are particularly susceptible to nutritional depletion due to the combined effects of the malignant disease and its treatment. With increasing incidence of cancer, identification and management of nutritional deficiencies are needed. Early identification of malnutrition, is substantial to minimize or prevent undesirable outcomes throughout clinical course. In determining the nutritional status; food consumption status, anthropometric methods, laboratory tests, clinical symptoms, psychosocial data are used. First-line strategies must include routine screening and identification of inpatients or outpatients at nutritional risk with the use of a simple and standardized screening tool. There is agreement among international nutrition organizations and accredited health care organizations that routine nutritional screening should be a standard procedure for every patient admitted to a hospital. There are f management of all cancer patients therefore routine nutritional screening with validated tools can identify cancer patients at risk.

Keywords: cancer, malnutrition, nutrition, nutritional screening

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1022 Review on Implementation of Artificial Intelligence and Machine Learning for Controlling Traffic and Avoiding Accidents

Authors: Neha Singh, Shristi Singh

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Accidents involving motor vehicles are more likely to cause serious injuries and fatalities. It also has a host of other perpetual issues, such as the regular loss of life and goods in accidents. To solve these issues, appropriate measures must be implemented, such as establishing an autonomous incident detection system that makes use of machine learning and artificial intelligence. In order to reduce traffic accidents, this article examines the overview of artificial intelligence and machine learning in autonomous event detection systems. The paper explores the major issues, prospective solutions, and use of artificial intelligence and machine learning in road transportation systems for minimising traffic accidents. There is a lot of discussion on additional, fresh, and developing approaches that less frequent accidents in the transportation industry. The study structured the following subtopics specifically: traffic management using machine learning and artificial intelligence and an incident detector with these two technologies. The internet of vehicles and vehicle ad hoc networks, as well as the use of wireless communication technologies like 5G wireless networks and the use of machine learning and artificial intelligence for the planning of road transportation systems, are elaborated. In addition, safety is the primary concern of road transportation. Route optimization, cargo volume forecasting, predictive fleet maintenance, real-time vehicle tracking, and traffic management, according to the review's key conclusions, are essential for ensuring the safety of road transportation networks. In addition to highlighting research trends, unanswered problems, and key research conclusions, the study also discusses the difficulties in applying artificial intelligence to road transport systems. Planning and managing the road transportation system might use the work as a resource.

Keywords: artificial intelligence, machine learning, incident detector, road transport systems, traffic management, automatic incident detection, deep learning

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1021 An Exploration of the Pancreatic Cancer miRNome during the Progression of the Disease

Authors: Barsha Saha, Shouvik Chakravarty, Sukanta Ray, Kshaunish Das, Nidhan K. Biswas, Srikanta Goswami

Abstract:

Pancreatic Ductal Adenocarcinoma is a well-recognised cause of cancer death with a five-year survival rate of about 9%, and its incidence in India has been found to be increased manifold in recent years. Due to delayed detection, this highly metastatic disease has a poor prognosis. Several molecular alterations happen during the progression of the disease from pre-cancerous conditions, and many such alterations could be investigated for their biomarker potential. MicroRNAs have been shown to be prognostic for PDAC patients in a variety of studies. We hereby used NGS technologies to evaluate the role of small RNA changes during pancreatic cancer development from chronic pancreatitis. Plasma samples were collected from pancreatic cancer patients (n=16), chronic pancreatitis patients (n=8), and also from normal individuals (n=16). Pancreatic tumour tissue (n=5) and adjacent normal tissue samples (n=5) were also collected. Sequencing of small RNAs was carried out after small RNAs were isolated from plasma samples and tissue samples. We find that certain microRNAs are highly deregulated in pancreatic cancer patients in comparison to normal samples. A combinatorial analysis of plasma and tissue microRNAs and subsequent exploration of their targets and altered molecular pathways could not only identify potential biomarkers for disease diagnosis but also help to understand the underlying mechanism.

Keywords: small RNA sequencing, pancreatic cancer, biomarkers, tissue sample

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1020 Multi-Layer Perceptron and Radial Basis Function Neural Network Models for Classification of Diabetic Retinopathy Disease Using Video-Oculography Signals

Authors: Ceren Kaya, Okan Erkaymaz, Orhan Ayar, Mahmut Özer

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Diabetes Mellitus (Diabetes) is a disease based on insulin hormone disorders and causes high blood glucose. Clinical findings determine that diabetes can be diagnosed by electrophysiological signals obtained from the vital organs. 'Diabetic Retinopathy' is one of the most common eye diseases resulting on diabetes and it is the leading cause of vision loss due to structural alteration of the retinal layer vessels. In this study, features of horizontal and vertical Video-Oculography (VOG) signals have been used to classify non-proliferative and proliferative diabetic retinopathy disease. Twenty-five features are acquired by using discrete wavelet transform with VOG signals which are taken from 21 subjects. Two models, based on multi-layer perceptron and radial basis function, are recommended in the diagnosis of Diabetic Retinopathy. The proposed models also can detect level of the disease. We show comparative classification performance of the proposed models. Our results show that proposed the RBF model (100%) results in better classification performance than the MLP model (94%).

Keywords: diabetic retinopathy, discrete wavelet transform, multi-layer perceptron, radial basis function, video-oculography (VOG)

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1019 A Theoretical Modelling and Simulation of a Surface Plasmon Resonance Biosensor for the Detection of Glucose Concentration in Blood and Urine

Authors: Natasha Mandal, Rakesh Singh Moirangthem

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The present work reports a theoretical model to develop a plasmonic biosensor for the detection of glucose concentrations in human blood and urine as the abnormality of glucose label is the major cause of diabetes which becomes a life-threatening disease worldwide. This study is based on the surface plasmon resonance (SPR) sensor applications which is a well-established, highly sensitive, label-free, rapid optical sensing tool. Here we have introduced a sandwich assay of two dielectric spacer layers of MgF2 and BaTiO3which gives better performance compared to commonly used SiO2 and TiO2 dielectric spacers due to their low dielectric loss and higher refractive index. The sensitivity of our proposed sensor was found as 3242 nm/RIU approximately, with an excellent linear response of 0.958, which is higher than the conventional single-layer Au SPR sensor. Further, the sensitivity enhancement is also optimized by coating a few layers of two-dimensional (2D) nanomaterials (e.g., Graphene, h-BN, MXene, MoS2, WS2, etc.) on the sensor chip. Hence, our proposed SPR sensor has the potential for the detection of glucose concentration in blood and urine with enhanced sensitivity and high affinity and could be utilized as a reliable platform for the optical biosensing application in the field of medical diagnosis.

Keywords: biosensor, surface plasmon resonance, dielectric spacer, 2D nanomaterials

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1018 A Machine Learning Framework Based on Biometric Measurements for Automatic Fetal Head Anomalies Diagnosis in Ultrasound Images

Authors: Hanene Sahli, Aymen Mouelhi, Marwa Hajji, Amine Ben Slama, Mounir Sayadi, Farhat Fnaiech, Radhwane Rachdi

Abstract:

Fetal abnormality is still a public health problem of interest to both mother and baby. Head defect is one of the most high-risk fetal deformities. Fetal head categorization is a sensitive task that needs a massive attention from neurological experts. In this sense, biometrical measurements can be extracted by gynecologist doctors and compared with ground truth charts to identify normal or abnormal growth. The fetal head biometric measurements such as Biparietal Diameter (BPD), Occipito-Frontal Diameter (OFD) and Head Circumference (HC) needs to be monitored, and expert should carry out its manual delineations. This work proposes a new approach to automatically compute BPD, OFD and HC based on morphological characteristics extracted from head shape. Hence, the studied data selected at the same Gestational Age (GA) from the fetal Ultrasound images (US) are classified into two categories: Normal and abnormal. The abnormal subjects include hydrocephalus, microcephaly and dolichocephaly anomalies. By the use of a support vector machines (SVM) method, this study achieved high classification for automated detection of anomalies. The proposed method is promising although it doesn't need expert interventions.

Keywords: biometric measurements, fetal head malformations, machine learning methods, US images

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1017 Using Short Narrative Film to Drive Healthcare Policy: A Case Study

Authors: T. L. Granzyk, S. Scarborough, J. DeCosmo

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The use of health-related or medical narratives has gained increasing anecdotal and research-based support as a successful device for changing health behavior and outcomes. These narratives, in the form of oral storytelling, short films, and educational documentaries, for example, are most effective when including empathetic characters that transport viewers into the story and command both their attention and emotional response. This case study outlines how and why one large health system created a short narrative film for their internal Sepsis Awareness campaign, which told the dramatic story of a patient recovering from a missed sepsis diagnosis, leaving her a quad-amputee. Results include positive global anecdotal response to the film from healthcare professionals and patients, as well as use of the film to support legislation, ultimately passed in favor of the formation of Sepsis Awareness Workgroups in Maryland. Authors conclude that narrative films can be used successfully to initiate healthcare legislation and to increase internal and external awareness of health-related areas in need of greater improvement and support. As such, healthcare leaders and stakeholders would benefit from learning how to intentionally create, cultivate, and curate narratives from within their own health systems that elicit an empathetic response.

Keywords: healthcare policy, healthcare narratives, sepsis awareness, short films

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1016 Model for Calculating Traffic Mass and Deceleration Delays Based on Traffic Field Theory

Authors: Liu Canqi, Zeng Junsheng

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This study identifies two typical bottlenecks that occur when a vehicle cannot change lanes: car following and car stopping. The ideas of traffic field and traffic mass are presented in this work. When there are other vehicles in front of the target vehicle within a particular distance, a force is created that affects the target vehicle's driving speed. The characteristics of the driver and the vehicle collectively determine the traffic mass; the driving speed of the vehicle and external variables have no bearing on this. From a physical level, this study examines the vehicle's bottleneck when following a car, identifies the outside factors that have an impact on how it drives, takes into account that the vehicle will transform kinetic energy into potential energy during deceleration, and builds a calculation model for traffic mass. The energy-time conversion coefficient is created from an economic standpoint utilizing the social average wage level and the average cost of motor fuel. Vissim simulation program measures the vehicle's deceleration distance and delays under the Wiedemann car-following model. The difference between the measured value of deceleration delay acquired by simulation and the theoretical value calculated by the model is compared using the conversion calculation model of traffic mass and deceleration delay. The experimental data demonstrate that the model is reliable since the error rate between the theoretical calculation value of the deceleration delay obtained by the model and the measured value of simulation results is less than 10%. The article's conclusion is that the traffic field has an impact on moving cars on the road and that physical and socioeconomic factors should be taken into account while studying vehicle-following behavior. The deceleration delay value of a vehicle's driving and traffic mass have a socioeconomic relationship that can be utilized to calculate the energy-time conversion coefficient when dealing with the bottleneck of cars stopping and starting.

Keywords: traffic field, social economics, traffic mass, bottleneck, deceleration delay

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1015 Myosin-Driven Movement of Nanoparticles – An Approach to High-Speed Tracking

Authors: Sneha Kumari, Ravi Krishnan Elangovan

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This abstract describes the development of a high-speed tracking method by modification in motor components for nanoparticle attachment. Myosin motors are nano-sized protein machines powering movement that defines life. These miniature molecular devices serve as engines utilizing chemical energy stored in ATP to produce useful mechanical energy in the form of a few nanometre displacement events leading to force generation that is required for cargo transport, cell division, cell locomotion, translated to macroscopic movements like running etc. With the advent of in vitro motility assay (IVMA), detailed functional studies of the actomyosin system could be performed. The major challenge with the currently available IVMA for tracking actin filaments is a resolution limitation of ± 50nm. To overcome this, we are trying to develop Single Molecule IVMA in which nanoparticle (GNP/QD) will be attached along or on the barbed end of actin filaments using CapZ protein and visualization by a compact TIRF module called ‘cTIRF’. The waveguide-based illumination by cTIRF offers a unique separation of excitation and collection optics, enabling imaging by scattering without emission filters. So, this technology is well equipped to perform tracking with high precision in temporal resolution of 2ms with significantly improved SNR by 100-fold as compared to conventional TIRF. Also, the nanoparticles (QD/GNP) attached to actin filament act as a point source of light coffering ease in filament tracking compared to conventional manual tracking. Moreover, the attachment of cargo (QD/GNP) to the thin filament paves the way for various nano-technological applications through their transportation to different predetermined locations on the chip

Keywords: actin, cargo, IVMA, myosin motors and single-molecule system

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