Search results for: continuous glucose monitoring

Authors: Sayed Isahaq Hossain, K. T. Chang, Moustapha Ndour

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Inference of the phreatic line through earth dams is of paramount importance because it could be directly associated with piping phenomena which may lead to the dam failure. Normally in the field, the instrumentations such as ‘diver’ and ‘standpipe’ are to be used to identify the seepage conditions which only provide point data with a fair amount of interpolation or assumption. Here in this paper, we employed high-resolution fiber optic cable sensors (FOCS) based on Raman Scattering in order to obtain a very accurate phreatic line and seepage profile. Unlike the above-mention devices which pinpoint the water level location, this kind of Distributed Fiber Optics Sensing gives us more reliable information due to its inherent characteristics of continuous measurement.

Keywords: standpipe, diver, FOCS, monitoring, Raman scattering

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Authors: Yong-Su Jo, Seung-Min Yang, Seok Hong Min, Tae Kwon Ha

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The synthesis of nickel nanoparticles by the reduction of nickel chloride with hydrazine in an aqueous solution. The effect of hydrazine concentration on batch-processed particle characteristics was investigated using Field Emission Scanning Electron Microscopy (FESEM). Both average particle size and geometric standard deviation (GSD) were decreasing with increasing hydrazine concentration. The continuous synthesis of nickel nanoparticles by microemulsion method was also studied using FESEM and X-ray Diffraction (XRD). The average size and geometric standard deviation of continuous-processed particles were 87.4 nm and 1.16, respectively. X-ray diffraction revealed continuous-processed particles were pure nickel crystalline with a face-centered cubic (fcc) structure.

Keywords: nanoparticle, hydrazine reduction, continuous process, microemulsion method

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Authors: Pranav Gulati, Isha Sharma

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Hypertension and hypotension are known to have repercussions on the health of an individual, with hypertension contributing to an increased probability of risk to cardiovascular diseases and hypotension resulting in syncope. This prompts the development of a non-invasive, non-intrusive, continuous and cuff-less blood pressure monitoring system to detect blood pressure variations and to identify individuals with acute and chronic heart ailments, but due to the unavailability of such devices for practical daily use, it becomes difficult to screen and subsequently regulate blood pressure. The complexities which hamper the steady monitoring of blood pressure comprises of the variations in physical characteristics from individual to individual and the postural differences at the site of monitoring. We propose to develop a continuous, comprehensive cardio-analysis tool, based on reflective photoplethysmography (PPG). The proposed device, in the form of an eyewear captures the PPG signal and estimates the systolic and diastolic blood pressure using a sensor positioned near the temporal artery. This system relies on regression models which are based on extraction of key points from a pair of PPG wavelets. The proposed system provides an edge over the existing wearables considering that it allows for uniform contact and pressure with the temporal site, in addition to minimal disturbance by movement. Additionally, the feature extraction algorithms enhance the integrity and quality of the extracted features by reducing unreliable data sets. We tested the system with 12 subjects of which 6 served as the training dataset. For this, we measured the blood pressure using a cuff based BP monitor (Omron HEM-8712) and at the same time recorded the PPG signal from our cardio-analysis tool. The complete test was conducted by using the cuff based blood pressure monitor on the left arm while the PPG signal was acquired from the temporal site on the left side of the head. This acquisition served as the training input for the regression model on the selected features. The other 6 subjects were used to validate the model by conducting the same test on them. Results show that the developed prototype can robustly acquire the PPG signal and can therefore be used to reliably predict blood pressure levels.

Keywords: blood pressure, photoplethysmograph, eyewear, physiological monitoring

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Authors: Bitewulign Mekonnen

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Context: This scientific paper focuses on the use of near-infrared (NIR) spectroscopy to determine glucose concentration in aqueous solutions accurately and rapidly. The study compares six different machine learning methods for predicting glucose concentration and also explores the development of a deep learning model for classifying NIR spectra. The objective is to optimize the detection model and improve the accuracy of glucose prediction. This research is important because it provides a comprehensive analysis of various machine-learning techniques for estimating aqueous glucose concentrations. Research Aim: The aim of this study is to compare and evaluate different machine-learning methods for predicting glucose concentration from NIR spectra. Additionally, the study aims to develop and assess a deep-learning model for classifying NIR spectra. Methodology: The research methodology involves the use of machine learning and deep learning techniques. Six machine learning regression models, including support vector machine regression, partial least squares regression, extra tree regression, random forest regression, extreme gradient boosting, and principal component analysis-neural network, are employed to predict glucose concentration. The NIR spectra data is randomly divided into train and test sets, and the process is repeated ten times to increase generalization ability. In addition, a convolutional neural network is developed for classifying NIR spectra. Findings: The study reveals that the SVMR, ETR, and PCA-NN models exhibit excellent performance in predicting glucose concentration, with correlation coefficients (R) > 0.99 and determination coefficients (R²)> 0.985. The deep learning model achieves high macro-averaging scores for precision, recall, and F1-measure. These findings demonstrate the effectiveness of machine learning and deep learning methods in optimizing the detection model and improving glucose prediction accuracy. Theoretical Importance: This research contributes to the field by providing a comprehensive analysis of various machine-learning techniques for estimating glucose concentrations from NIR spectra. It also explores the use of deep learning for the classification of indistinguishable NIR spectra. The findings highlight the potential of machine learning and deep learning in enhancing the prediction accuracy of glucose-relevant features. Data Collection and Analysis Procedures: The NIR spectra and corresponding references for glucose concentration are measured in increments of 20 mg/dl. The data is randomly divided into train and test sets, and the models are evaluated using regression analysis and classification metrics. The performance of each model is assessed based on correlation coefficients, determination coefficients, precision, recall, and F1-measure. Question Addressed: The study addresses the question of whether machine learning and deep learning methods can optimize the detection model and improve the accuracy of glucose prediction from NIR spectra. Conclusion: The research demonstrates that machine learning and deep learning methods can effectively predict glucose concentration from NIR spectra. The SVMR, ETR, and PCA-NN models exhibit superior performance, while the deep learning model achieves high classification scores. These findings suggest that machine learning and deep learning techniques can be used to improve the prediction accuracy of glucose-relevant features. Further research is needed to explore their clinical utility in analyzing complex matrices, such as blood glucose levels.

Keywords: machine learning, signal processing, near-infrared spectroscopy, support vector machine, neural network

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Authors: Sina Aghili, Ali Arasteh Nodeh

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Tamarisk usage as a new group of lignocelluloses material to produce fermentable sugars in bio-ethanol process was studied. The overall aim of this work was to establish the optimum condition for acid hydrolysis of this new material and a mathematical model predicting glucose release as a function of operation variable. Sulfuric acid concentration in the range of 20 to 60%(w/w), process temperature between 60 to 95oC, hydrolysis time from 120 to 240 min and solid content 5,10,15%(w/w) were used as hydrolysis conditions. HPLC was used to analysis of the product. This analysis indicated that glucose was the main fermentable sugar and was increased with time, temperature and solid content and acid concentration was a parabola influence in glucose production.The process was modeled by a quadratic equation. Curve study and model were found that 42% acid concentration, 15 % solid content and 90oC were in optimum condition.

Keywords: fermentable sugar, saccharification, wood, hydrolysis

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Authors: Abdesselam Babouri, Ahcène Lemzadmi, M Rahmane, B. Belhadi, N. Abouchi

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Medical monitoring aims at monitoring and remotely controlling the vital physiological parameters of the patient. The physiological sensors provide repetitive measurements of these parameters in the form of electrical signals that vary continuously over time. Various measures allow informing us about the health of the person's physiological data (weight, blood pressure, heart rate or specific to a disease), environmental conditions (temperature, humidity, light, noise level) and displacement and movements (physical efforts and the completion of major daily living activities). The collected data will allow monitoring the patient’s condition and alerting in case of modification. They are also used in the diagnosis and decision making on medical treatment and the health of the patient. This work presents the implementation of a monitoring system to be used for the control of physiological parameters.

Keywords: clinical monitoring, physiological parameters, biomedical sensors, personal health

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Authors: Christian Fercher, Jiaul Islam, Simon R. Corrie

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Fluorescence-based immunodiagnostics are an emerging field in biosensor development and exhibit several advantages over traditional detection methods. While various affinity biosensors have been developed to generate a fluorescence signal upon sensing varying concentrations of analytes, reagentless, reversible, and continuous monitoring of complex biological samples remains challenging. Here, we aimed to genetically engineer biosensors based on single-chain antibody fragments (scFv) that are site-specifically labeled with environmentally sensitive fluorescent unnatural amino acids (UAA). A rational design approach resulted in quantifiable analyte-dependent changes in peak fluorescence emission wavelength and enabled antigen detection in vitro. Incorporation of a polarity indicator within the topological neighborhood of the antigen-binding interface generated a titratable wavelength blueshift with nanomolar detection limits. In order to ensure continuous analyte monitoring, scFv candidates with fast binding and dissociation kinetics were selected from a genetic library employing a high-throughput phage display and affinity screening approach. Initial rankings were further refined towards rapid dissociation kinetics using bio-layer interferometry (BLI) and surface plasmon resonance (SPR). The most promising candidates were expressed, purified to homogeneity, and tested for their potential to detect biomarkers in a continuous microfluidic-based assay. Variations of dissociation kinetics within an order of magnitude were achieved without compromising the specificity of the antibody fragments. This approach is generally applicable to numerous antibody/antigen combinations and currently awaits integration in a wide range of assay platforms for one-step protein quantification.

Keywords: antibody engineering, biosensor, phage display, unnatural amino acids

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Authors: Y. Kim, H. Lee, M. Park, B. Lee

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Planning is understood as the determination of what has to be performed, how, in which sequence, when, what resources are needed, and their cost within the organization before execution. In most construction project, it is evident that the inherent nature of planning is dynamic, and initial planning is subject to be changed due to various uncertain conditions of construction project. Planners take a continuous revision process during the course of a project and until the very end of project. However, current practice lacks reliable, systematic tool for setting variance thresholds to determine when and what corrective actions to be taken. Rather it is heavily dependent on the level of experience and knowledge of the planner. Thus, this paper introduces a machine learning approach to evaluate project control threshold reliability incorporating project-specific data and presents a method to automate the process. The results have shown that the model improves the efficiency and accuracy of the monitoring process as an early warning.

Keywords: machine learning, project control, project progress monitoring, schedule

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Authors: Jean-Francois Rajotte, Martin Sotir, Frank Gouineau

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The installation and management of traffic monitoring devices can be costly from both a financial and resource point of view. It is therefore important to take advantage of in-place infrastructures to extract the most information. Here we show how low-quality urban road traffic images from cameras already available in many cities (such as Montreal, Vancouver, and Toronto) can be used to estimate traffic flow. To this end, we use a pre-trained neural network, developed for object detection, to count vehicles within images. We then compare the results with human annotations gathered through crowdsourcing campaigns. We use this comparison to assess performance and calibrate the neural network annotations. As a use case, we consider six months of continuous monitoring over hundreds of cameras installed in the city of Montreal. We compare the results with city-provided manual traffic counting performed in similar conditions at the same location. The good performance of our system allows us to consider applications which can monitor the traffic conditions in near real-time, making the counting usable for traffic-related services. Furthermore, the resulting annotations pave the way for building a historical vehicle counting dataset to be used for analysing the impact of road traffic on many city-related issues, such as urban planning, security, and pollution.

Keywords: traffic monitoring, deep learning, image annotation, vehicles, roads, artificial intelligence, real-time systems

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Authors: Vethathirri Ramanujam Srinivasan, S. M. Shiva Nagendra

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Air quality management in urban areas is a serious concern in both developed and developing countries. In this regard, more number of air quality monitoring stations are planned to mitigate air pollution in urban areas. In India, Central Pollution Control Board has set up 574 air quality monitoring stations across the country and proposed to set up another 500 stations in the next few years. The number of monitoring stations for each city has been decided based on population data. The setting up of ambient air quality monitoring stations and their operation and maintenance are highly expensive. Therefore, there is a need to optimize monitoring networks for air quality management. The present paper discusses the various methods such as Indian Standards (IS) method, US EPA method and European Union (EU) method to arrive at the minimum number of air quality monitoring stations. In addition, optimization of rain-gauge method and Inverse Distance Weighted (IDW) method using Geographical Information System (GIS) are also explored in the present work for the design of air quality network in Chennai city. In summary, additionally 18 stations are required for Chennai city, and the potential monitoring locations with their corresponding land use patterns are ranked and identified from the 1km x 1km sized grids.

Keywords: air quality monitoring network, inverse distance weighted method, population based method, spatial variation

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Authors: Jonas P. Reges, Jessyca A. Bessa, Auzuir R. Alexandria

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The research came up with the need of monitoring them of temperature and relative moisture in past work that enveloped the study of a greenhouse located in the Research and Extension Unit(UEPE). This research brought several unknowns that were resolved from bibliographical research. Based on the studies performed were found some monitoring methods, including the serial communication between the arduino and matlab which showed a great option due to the low cost. The project was conducted in two stages, the first, an algorithm was developed to the Arduino and Matlab, and second, the circuits were assembled and performed the monitoring tests the following variables: moisture, temperature, and distance. During testing it was possible to momentarily observe the change in the levels of monitored variables. The project showed satisfactory results, such as: real-time verification of the change of state variables, the low cost of acquisition of the prototype, possibility of easy change of programming for the execution of monitoring of other variables. Therefore, the project showed the possibility of monitoring through software and hardware that have easy programming and can be used in several areas. However, it is observed also the possibility of improving the project from a remote monitoring via Bluetooth or web server and through the control of monitored variables.

Keywords: automation, monitoring, programming, arduino, matlab

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Authors: Sagar R. Patil, Dinesh R. Gawade, Sudhir N. Divekar

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One of the medical devices we found when we visit a hospital care unit such device is ‘patient monitoring system’. This device (patient monitoring system) informs doctors and nurses about the patient’s physiological signals. However, this device (patient monitoring system) does not have a remote monitoring capability, which is necessitates constant onsite attendance by support personnel (doctors and nurses). Thus, we have developed a Remote Wireless Patient Monitoring System using some biomedical sensors and Android OS, which is a portable patient monitoring. This device(Remote Wireless Patient Monitoring System) monitors the biomedical signals of patients in real time and sends them to remote stations (doctors and nurse’s android Smartphone and web) for display and with alerts when necessary. Wireless Patient Monitoring System different from conventional device (Patient Monitoring system) in two aspects: First its wireless communication capability allows physiological signals to be monitored remotely and second, it is portable so patients can move while there biomedical signals are being monitor. Wireless Patient Monitoring is also notable because of its implementation. We are integrated four sensors such as pulse oximeter (SPO2), thermometer, respiration, blood pressure (BP), heart rate and electrocardiogram (ECG) in this device (Wireless Patient Monitoring System) and Monitoring and communication applications are implemented on the Android OS using threads, which facilitate the stable and timely manipulation of signals and the appropriate sharing of resources. The biomedical data will be display on android smart phone as well as on web Using web server and database system we can share these physiological signals with remote place medical personnel’s or with any where in the world medical personnel’s. We verified that the multitasking implementation used in the system was suitable for patient monitoring and for other Healthcare applications.

Keywords: patient monitoring, wireless patient monitoring, bio-medical signals, physiological signals, embedded system, Android OS, healthcare, pulse oximeter (SPO2), thermometer, respiration, blood pressure (BP), heart rate, electrocardiogram (ECG)

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Authors: Song Zhang, Hui Wang, Johannes Henrich Schleifenbaum

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Due to the increasing demand for quality assurance and reliability for additive manufacturing, the development of an advanced in-situ monitoring system is required to monitor the process anomalies as input for further process control. Optical-based monitoring systems, such as CMOS cameras and NIR cameras, are proved as effective ways to monitor the geometrical distortion and exceptional thermal distribution. Therefore, many studies and applications are focusing on the availability of the optical-based monitoring system for detecting varied types of defects. However, the capability of the monitoring setup is not quantified. In this study, a quantification model to evaluate the capability of the monitoring setups for the LPBF machine based on acquired monitoring data of a designed test artifact is presented, while the design of the relevant test artifacts is discussed. The monitoring setup is evaluated based on its hardware properties, location of the integration, and light condition. Methodology of data processing to quantify the capacity for each aspect is discussed. The minimal capability of the detectable size of the monitoring set up in the application is estimated by quantifying its resolution and accuracy. The quantification model is validated using a CCD camera-based monitoring system for LPBF machines in the laboratory with different setups. The result shows the model to quantify the monitoring system's performance, which makes the evaluation of monitoring systems with the same concept but different setups possible for the LPBF process and provides the direction to improve the setups.

Keywords: data processing, in-situ monitoring, LPBF process, optical system, quantization model, test artifact

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Authors: Gabriela-Andreea Despescu, Mădălina Mavrodin, Gheorghe Lăzăroiu, S. Nacu, R. Băstinaş

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The Monitoring of Surface Water Bodies (Rivers) from Tisa Catchment Area - Maramureş County in 2014. This study is focused on the monitoring and evaluation of river’s water bodies from Maramureş County, using the methodology associated with the EU Water Framework Directive 60/2000. Thus, in the first part are defined the theoretical terms of monitoring activities related to the water bodies’ quality and the specific features of those we can find in the studied area. There are presented the water bodies’ features, quality indicators and the monitoring frequencies for the rivers situated in the Tisa catchment area. The results have shown the actual ecological and chemical state of those water bodies, in relation with the standard values mentioned through the Water Framework Directive.

Keywords: monitoring, surveillance, water bodies, quality

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Authors: Ounassa Adjroud

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Potassium dichromate (K2Cr2O7) is one of the most toxic elements to which man can be exposed at work or in the environment. The purpose of the current work is to compare the effect of K2Cr2O7 using variations in the dose, route of administration and duration of exposure in male and female Wistar albino rats with a special focus on biochemical parameters. K2Cr2O7 was subcutaneously administered alone (10, 50 and 100 mg/kg body weight) to female Wistar albino rats. Male rats received in their drinking water K2Cr2O7 30 mg/L/day) for 20 consecutive days. The Biochemical parameters were evaluated on days 3, 6 and 21 after subcutaneous (sc.) treatment in female rats and on days 10 and 20 after oral administration in male rats. The subcutaneous (s.c.) administration of 25 mg/kg of K2Cr2O7 to Wistar albino rats induced a slight change in plasma glucose levels during the experiment period. On the contrary, a significant decrease in plasma glucose levels was observed with 50 mg/kg mainly on days 3 (-26%) and 21 (-48%) after treatment compared to controls females rats. On the other hand, the higher dose provoked a significant increase in plasma glucose concentrations on days 6 (+31%) and 21 (+60%). similarly, the lower dose of chromium had no effect on the plasma urea levels. Conversely, a significant increase (122%) in this parameter was obtained during the first three days after treatment. In addition, a significant decrease in plasma glucose levels was observed with 50 mg/kg mainly on days 3 (-26%) and 21 (-48%) after treatment. On the other hand, the higher dose provoked a significant increase in plasma glucose concentrations on days 6 (+31%) and 21 (+60%). similarly, the lower dose of chromium had no effect on the plasma urea levels. Conversely, a significant increase in this parameter (122%) was obtained during the first three days after treatment. In addition, administration of 100 mg/kg of K2Cr2O7 by s.c markedly augmented the levels of plasma urea on days 3 (62%) and 6 (121%). Administration of 30 mg/L/day of K2Cr2O7 in the drinking water induced a significant augmentation in both of plasma glucose (27%) and urea (126%) during the first ten days of treatment. These results suggested that K2Cr2O7 administered subcutaneously or in the drinking water may induce harmful effects on biochemical parameters.

Keywords: glucose, potassium dichromate, Wistar albino rat, urea

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Authors: Guenther Schuh, Christina Koenig, Nico Schoen, Markus Wellensiek

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Identification and selection of appropriate product and manufacturing technologies are key factors for competitiveness and market success of technology-based companies. Therefore many companies perform technology intelligence (TI) activities to ensure the identification of evolving technologies at the right time. Technology monitoring is one of the three base activities of TI, besides scanning and scouting. As the technological progress is accelerating, more and more technologies are being developed. Against the background of limited resources it is therefore necessary to focus TI activities. In this paper, we propose a concept for defining appropriate search fields for technology monitoring. This limitation of search space leads to more concentrated monitoring activities. The concept will be introduced and demonstrated through an anonymized case study conducted within an industry project at the Fraunhofer Institute for Production Technology. The described concept provides a customized monitoring approach, which is suitable for use in technology-oriented companies especially those that have not yet defined an explicit technology strategy. It is shown in this paper that the definition of search fields and search tasks are suitable methods to define topics of interest and thus to direct monitoring activities. Current as well as planned product, production and material technologies as well as existing skills, capabilities and resources form the basis of the described derivation of relevant search areas. To further improve the concept of technology monitoring the proposed concept should be extended during future research e.g. by the definition of relevant monitoring parameters.

Keywords: monitoring radar, search field, technology intelligence, technology monitoring

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Authors: Shyh-Ming Chern, Hung-Chi Tu

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One way to utilize biomass is to thermochemically convert it into gases and chemicals. For conversion of biomass, glucose is a particularly popular model compound for cellulose, or more generally for biomass. The present study takes a different approach by employing lactic acid as the model compound for cellulose. Since lactic acid and glucose have identical elemental composition, they are expected to produce similar results as they go through the conversion process. In the current study, lactic acid was thermochemically converted to assess its reactivity and reaction mechanism in subcritical and supercritical water, by using a 16-ml autoclave reactor. The major operating parameters investigated include: The reaction temperature, from 673 to 873 K, the reaction pressure, 10 and 25 MPa, the dosage of oxidizing agent, 0 and 0.5 chemical oxygen demand, and the concentration of lactic acid in the feed, 0.5 and 1.0 M. Gaseous products from the conversion were generally found to be comparable to those derived from the conversion of glucose.

Keywords: lactic acid, subcritical water, supercritical water, thermochemical conversion

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Authors: Lan Nguyen, Kien Le Tan, Bao Nguyen Pham Gia

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Due to the high cost, specialized dynamic measurement devices for industrial lands are difficult for many colleges to equip for hands-on teaching. This study connects a dynamic measurement sensor and receiver utilizing an inexpensive Raspberry Pi 4 board, some 24-bit ADC circuits, a geophone vibration sensor, and embedded Python open-source programming. Gather and analyze signals for dynamic measuring, ground vibration monitoring, and structure vibration monitoring. The system may wirelessly communicate data to the computer and is set up as a communication node network, enabling real-time monitoring of background vibrations at various locations. The device can be utilized for a variety of dynamic measurement and monitoring tasks, including monitoring earthquake vibrations, ground vibrations from construction operations, traffic, and vibrations of building structures.

Keywords: sensors, FFT, signal processing, real-time data monitoring, ground propagation wave, python, raspberry Pi 4

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Authors: Kornanong Yuenyongchaiwat, Duangnate Pepatsitipong, Panthip Sangprasert

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High blood pressure and diabetes have been suggested as being non-communicable disease (NCDs), and there is one of the components of the definition of metabolic syndrome. Therefore, the purpose of this study was to evaluate the effect of a 12-week pedometer based community walking intervention on change in resting blood pressure and blood glucose in participants with overweight in the community setting. Method: Participants were recruited both males and females who had a sedentary lifestyle aged 35-59 years (mean aged 49.67 years). A longitudinal quasi-experimental study was designed with 35 overweight participants who had body mass index ≥ 25 kg/m2. These volunteers were assigned to the 12-week pedometer-based walking program (an accumulated at least 10,000 steps a day). Blood pressure and blood glucose were measured initially before and after 12-week intervention. Results: Systolic blood pressure and heart rate were significantly lower in 30 individuals who had accumulated 10,000 steps d-1 in the intervention group at 12 week follow-up (-13.74 mmHg and 5.3 bpm, respectively). In addition, reduction in blood glucose (-14.89 mmol) in the intervention participants was statistically significant (p < .001). A regression analysis indicated that reductions in systolic blood pressure were significantly related to the increase in steps per day. Conclusion: The accumulation of least 10,000 steps d-1 resulted in decreased resting systolic blood pressure and blood glucose in overweight participants. This has also shown that an increase in physical activity in overweight participants with sedentary lifestyle by accumulating at least 10,000 steps a day can reduce the risk of cardiovascular disease (e.g., hypertension and diabetes).

Keywords: blood glucose, blood pressure, diabetes, hypertension, physical activity, walking

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Authors: Jungho Moon, Lae-Jeong Park

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This paper introduces a signal monitoring program developed with a view to helping electrical engineering students get familiar with sensors with digital output. Because the output of digital sensors cannot be simply monitored by a measuring instrument such as an oscilloscope, students tend to have a hard time dealing with digital sensors. The monitoring program runs on a PC and communicates with an MCU that reads the output of digital sensors via an asynchronous communication interface. Receiving the sensor data from the MCU, the monitoring program shows time and/or frequency domain plots of the data in real time. In addition, the monitoring program provides a serial terminal that enables the user to exchange text information with the MCU while the received data is plotted. The user can easily observe the output of digital sensors and configure the digital sensors in real time, which helps students who do not have enough experiences with digital sensors. Though the monitoring program was programmed in the Matlab programming language, it runs without the Matlab since it was compiled as a standalone executable.

Keywords: digital sensor, MATLAB, MCU, signal monitoring program

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Authors: Faizul Azly Abd Dzubir, Muhammad F. Othman

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Conventional structural health monitoring approach for mechanical equipment uses inspection data from Non-Destructive Testing (NDT) during plant shut down window and fitness for service evaluation to estimate the integrity of the equipment that is prone to crack damage. Yet, this forecast is fraught with uncertainty because it is often based on assumptions of future operational parameters, and the prediction is not continuous or online. Advanced Diagnostic and Prognostic Technology (ADaPT) uses Acoustic Emission (AE) technology and a stochastic prognostic model to provide real-time monitoring and prediction of mechanical defects or cracks. The forecast can help the plant authority handle their cracked equipment before it ruptures, causing an unscheduled shutdown of the facility. The ADaPT employs process historical data trending, finite element analysis, fitness for service, and probabilistic statistical analysis to develop a prediction model for crack initiation and growth due to mechanical damage. The prediction model is combined with live equipment operating data for real-time prediction of the remaining life span owing to fracture. ADaPT was devised at a hot combined feed exchanger (HCFE) that had suffered creep crack damage. The ADaPT tool predicts the initiation of a crack at the top weldment area by April 2019. During the shutdown window in April 2019, a crack was discovered and repaired. Furthermore, ADaPT successfully advised the plant owner to run at full capacity and improve output by up to 7% by April 2019. ADaPT was also used on a coke drum that had extensive fatigue cracking. The initial cracks are declared safe with ADaPT, with remaining crack lifetimes extended another five (5) months, just in time for another planned facility downtime to execute repair. The prediction model, when combined with plant information data, allows plant operators to continuously monitor crack propagation caused by mechanical damage for improved maintenance planning and to avoid costly shutdowns to repair immediately.

Keywords: mechanical damage, cracks, continuous monitoring tool, remaining life, acoustic emission, prognostic model

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Authors: Girish M. Bhatia

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Most of the important structures in refinery complex are RCC Structures for which in-depth structural monitoring and inspection is required for incessant service. Reinforced concrete structures can be under threat from a combination of insidious challenges due to environmental conditions, including temperature and humidity that lead to accelerated deterioration mechanisms like carbonation, as well as marine exposure, above and below ground structures can experience ingress from aggressive ground waters carrying chlorides and sulphates leading to unexpected deterioration that threaten the integrity of a vital structural asset. By application of health monitoring techniques like corrosion monitoring with help of sensor probes, visual inspection of high rise structures with help of drones, it is possible to establish an early warning at the onset of these destructive processes.

Keywords: concrete structures, corrosion sensors, drones, health monitoring

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Authors: Alok Raghav, Jamal Ahmad

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Background: Serum albumin glycation and advanced glycation end products (AGE) formation correlates in diabetes and its associated complications. Extensive modified human serum albumin is used to study the biochemical, electrochemical and functional properties in hyperglycemic environment with relevance to diabetes. We evaluate Spectroscopic, side chain modifications, amino acid analysis, biochemical and functional group properties in four glucose modified samples. Methods: A series four human serum albumin samples modified with glucose was characterized in terms of amino acid analysis, spectroscopic properties and side chain modifications. The diagnostic technique employed incorporates UV Spectroscopy, Fluorescence Spectroscopy, biochemical assays for side chain modifications, amino acid estimations. Conclusion: Glucose modified human serum albumin confers AGE formation causes biochemical and functional property that depend on the reactivity of glucose and its concentration used for in-vitro glycation. A biochemical and functional characterization of modified albumin in-vitro produced AGE product that will be useful to interpret the complications and pathophysiological significance in diabetes.

Keywords: glycation, diabetes, human serum albumin, biochemical and electrochemical characterization

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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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Authors: Carolina Gouveia, José Vieira, Pedro Pinho

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The cardiopulmonary signal monitoring, without the usage of contact electrodes or any type of in-body sensors, has several applications such as sleeping monitoring and continuous monitoring of vital signals in bedridden patients. This system has also applications in the vehicular environment to monitor the driver, in order to avoid any possible accident in case of cardiac failure. Thus, the bio-radar system proposed in this paper, can measure vital signals accurately by using the Doppler effect principle that relates the received signal properties with the distance change between the radar antennas and the person’s chest-wall. Once the bio-radar aim is to monitor subjects in real-time and during long periods of time, it is impossible to guarantee the patient immobilization, hence their random motion will interfere in the acquired signals. In this paper, a mathematical model of the bio-radar is presented, as well as its simulation in MATLAB. The used algorithm for breath rate extraction is explained and a method for DC offsets removal based in a motion detection system is proposed. Furthermore, experimental tests were conducted with a view to prove that the unavoidable random motion can be used to estimate the DC offsets accurately and thus remove them successfully.

Keywords: bio-signals, DC component, Doppler effect, ellipse fitting, radar, SDR

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Authors: Victor A. Okenyi, Kehinde A. Alawode

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Corrosion of reinforcement in concrete structures remains a durability issue in structural engineering with the increasing cost of repair and maintenance. The mechanism and factors influencing reinforcement corrosion in concrete with various electrochemical monitoring techniques including non-destructive, destructive techniques and the roles of sensors have been reviewed with the aim of determining the monitoring technique that proved most effective in determining corrosion parameters and more practicable for the assessment of concrete durability. Electrochemical impedance spectroscopy (EIS) and linear polarization resistance (LPR) techniques showed great performance in evaluating corrosion kinetics and corrosion rate, respectively, while the gravimetric weight loss (GWL) technique provided accurate measurements. However, no single monitoring technique showed to be the ultimate technique, and this calls for more research work in the development of more dynamic monitoring tools capable of considering all possible corrosion factors in the corrosion monitoring process.

Keywords: corrosion, concrete structures, durability, non-destructive technique, sensor

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Authors: Kh. Dehkordi, R. Sharifi Gholam, S. Arshadi

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Objective: Oxidative stress is produced under diabetic conditions and possibly causes various forms of tissue damage inpatients with diabetes. Antioxidants defend against the harmful effect of free radicals, which are associated with heart disease, cancer, arthritis, aging and many other diseases1). Antioxidants are very stable molecules capable of neutralizing free radicals by donating an electron to them.The aim of this study was to examine the effect of swimming training, fenugreek seed extract and glibenclamide on plasma glucose and cardiac antioxidants activity in diabetic rats. Design: For this purpose, fifty male wistar rats were divided into five groups, two groups of control rats (diabetic control [DC] and healthy control [HC]), one group of endurance swimming training (EST), one group of fenugreek seed extract highdose (F1, 1.74 g/kg b.w), one group of fenugreek seed extract middle dose (F2, 0.87 g/kg b.w), one group of glibenclamide (G, 0.5 mg/kg b.w). Materials and Methods: Diabetes induced by streptozotocine (STZ), data was analyzed using the one-way ANOVA followed by a Tukey test. Significance level was 0.05. Results: All of the groups' exception of HC showed significant decrease in body weight (P < 0.05), but the diabetic control and swimming training group exhibited a more decrease. All of the groups have shown a significant decrease in plasma glucose than DC group (P < 0.05) but this reduction was more in G group than DC no HC group. S, G and HC groups have shown significant increase in cardiac antioxidant than DC group (P < 0.05) but there wasn't significant difference in other groups (P > 0.05). Conclusion: The present results indicate that regular swimming training lead to decrease in plasma glucose and enhanced cardiac antioxidants in diabetic rats.

Keywords: swimming, glucose, cardiac, antioxidants

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Authors: P. Gayathri, G. P. Jeyanthi

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The bark of Polyalthia longifolia is used in ayurvedic system of medicine for the manangement of various ailments including diabetes mellitus. The bark of P. longifolia extracts was extracted using various polar and non-polar solvents and tested for inhibition of alpha-amylase and alpha-glucosidase among which the ethanolic extracts were found to be more potent. The ethanolic extracts of the bark were tested for the in vitro inhibition of alpha-amylase using starch as substrate and alpha-glucosidase using p-nitro phenyl alpha-D-gluco pyranoside as substrate to establish its in vitro antidiabetic effect. The mechanism of inhibition was determined by Dixon plot and Cornish-Bowden plot. The cytotoxic effect of the extract was tested on L6 and Vero cell-lines. The extract was partially purified by TLC. The individual effect of the ethanolic extract, TLC fractions and its combinatorial effect with insulin and glibenclamide on glucose uptake by rat hemi-diaphragm were studied.Results revealed that the ethanolic extracts of Polyalthia longifolia bark exhibited competitive inhibition of alpha-amylase and alpha-glucosidase. The extracts were also found not to be cytotoxic at the highest dose of 1 mg/mL. Glucose uptake study revealed that the extract alone and when combined with insulin, decreased the glucose uptake when compared to insulin control, however the purified TLC fractions exhibited significantly higher (p<0.05) glucose uptake by the rat hemi-diaphragm when compared to insulin. The study shows various possible mechanism of in vitro antidiabetic effect of the P. longifolia bark.

Keywords: alpha-amylase, alpha-glucosidase, dixon, cornish-bowden, L6 , Vero cell-lines, glucose uptake, polyalthia longifolia bark, ethanolic extract, TLC fractions

Procedia PDF Downloads 447

Authors: Natan C. G. Silva, Carlos A. C. Girao Neto, Marcele M. S. Vasconcelos, Luciana R. B. Goncalves, Maria Valderez P. Rocha

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Galactooligosaccharides (GOS) are sugars with prebiotic function that can be synthesized chemically or enzymatically, and this last one can be promoted by the action of β-galactosidases. In addition to favoring the transgalactosylation reaction to form GOS, these enzymes can also catalyze the hydrolysis of lactose. A highly studied type of GOS is lactulose because it presents therapeutic properties and is a health promoter. Among the different raw materials that can be used to produce lactulose, whey stands out as the main by-product of cheese manufacturing, and its discarded is harmful to the environment due to the residual lactose present. Therefore, its use is a promising alternative to solve this environmental problem. Thus, lactose from whey is hydrolyzed into glucose and galactose by β-galactosidases. However, in order to favor the transgalactosylation reaction, the medium must contain fructose, due this sugar reacts with galactose to produce lactulose. Then, the glucose-isomerase enzyme can be used for this purpose, since it promotes the isomerization of glucose into fructose. In this scenario, the aim of the present work was first to develop β-galactosidase biocatalysts of Kluyveromyces lactis and to apply it in the integrated reactions of hydrolysis, isomerization (with the glucose-isomerase from Streptomyces murinus) and transgalactosylation reaction, using whey as a substrate. The immobilization of β-galactosidase in chitosan previously functionalized with 0.8% glutaraldehyde was evaluated using different enzymatic loads (2, 5, 7, 10, and 12 mg/g). Subsequently, the hydrolysis and transgalactosylation reactions were studied and conducted at 50°C, 120 RPM for 20 minutes. In parallel, the isomerization of glucose into fructose was evaluated under conditions of 70°C, 750 RPM for 90 min. After, the integration of the three processes for the production of lactulose was investigated. Among the evaluated loads, 7 mg/g was chosen because the best activity of the derivative (44.3 U/g) was obtained, being this parameter determinant for the reaction stages. The other parameters of immobilization yield (87.58%) and recovered activity (46.47%) were also satisfactory compared to the other conditions. Regarding the integrated process, 94.96% of lactose was converted, achieving 37.56 g/L and 37.97 g/L of glucose and galactose, respectively. In the isomerization step, conversion of 38.40% of glucose was observed, obtaining a concentration of 12.47 g/L fructose. In the transgalactosylation reaction was produced 13.15 g/L lactulose after 5 min. However, in the integrated process, there was no formation of lactulose, but it was produced other GOS at the same time. The high galactose concentration in the medium probably favored the reaction of synthesis of these other GOS. Therefore, the integrated process proved feasible for possible production of prebiotics. In addition, this process can be economically viable due to the use of an industrial residue as a substrate, but it is necessary a more detailed investigation of the transgalactosilation reaction.

Keywords: beta-galactosidase, glucose-isomerase, galactooligosaccharides, lactulose, whey

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Authors: Saddam Husain Dhobi, Bikrant Karki

Abstract:

The main objective of this paper is save money, balance ecosystem of the terrestrial organism, control global warming, and enhancing the storage capacity of the battery with requiring weight and thinness by using Cyanobacteria in the battery. To fulfill this purpose of paper we can use different methods: Analysis, Biological, Chemistry, theoretical and Physics with some engineering design. Using this different method, we can produce the special type of battery that has the long life, high storage capacity, and clean environment, save money so on and by using the byproduct of Cyanobacteria i.e. glucose. Cyanobacteria are a special type of bacteria that produces different types of extracellular glucoses and oxygen with the help of little sunlight, water, and carbon dioxide and can survive in freshwater, marine and in the land as well. In this process, O₂ is more in the comparison to plant due to rapid growth rate of Cyanobacteria. The required materials are easily available in this process to produce glucose with the help of Cyanobacteria. Since CO₂, is greenhouse gas that causes the global warming? We can utilize this gas and save our ecological balance and the byproduct (glucose) C₆H₁₂O₆ can be utilized for raw material for the battery where as O₂ escape is utilized by living organism. The glucose produce by Cyanobateria goes on Krebs's Cycle or Citric Acid Cycle, in which glucose is complete, oxidizes and all the available energy from glucose molecule has been release in the form of electron and proton as energy. If we use a suitable anodes and cathodes, we can capture these electrons and protons to produce require electricity current with the help of byproduct of Cyanobacteria. According to "Virginia Tech Bio-battery" and "Sony" 13 enzymes and the air is used to produce nearly 24 electrons from a single glucose unit. In this output power of 0.8 mW/cm, current density of 6 mA/cm, and energy storage density of 596 Ah/kg. This last figure is impressive, at roughly 10 times the energy density of the lithium-ion batteries in your mobile devices. When we use Cyanobacteria in battery, we are able to reduce Carbon dioxide, Stop global warming, and enhancing the storage capacity of battery more than 10 times that of lithium battery, saving money, balancing ecology. In this way, we can produce energy from the Cyanobacteria and use it in battery for different benefits. In addition, due to the mass, size and easy cultivation, they are better to maintain the size of battery. Hence, we can use Cyanobacteria for the battery having suitable size, enhancing the storing capacity of battery, helping the environment, portability and so on.

Keywords: anode, byproduct, cathode, cyanobacteri, glucose, storage capacity

Procedia PDF Downloads 316