Search results for: toxicity monitoring

Authors: Yuxiang Pan, Yong Qiu, Chenlei Gu, Ping Wang

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In the past decade, three-dimensional (3D) tumor cell models have attracted increasing interest in the field of drug screening due to their great advantages in simulating more accurately the heterogeneous tumor behavior in vivo. Drug sensitivity testing based on 3D tumor cell models can provide more reliable in vivo efficacy prediction. The gold standard fluorescence staining is hard to achieve the real-time and label-free monitoring of the viability of 3D tumor cell models. In this study, micro-groove impedance sensor (MGIS) was specially developed for dynamic and non-invasive monitoring of 3D cell viability. 3D tumor cells were trapped in the micro-grooves with opposite gold electrodes for the in-situ impedance measurement. The change of live cell number would cause inversely proportional change to the impedance magnitude of the entire cell/matrigel to construct and reflect the proliferation and apoptosis of 3D cells. It was confirmed that 3D cell viability detected by the MGIS platform is highly consistent with the standard live/dead staining. Furthermore, the accuracy of MGIS platform was demonstrated quantitatively using 3D lung cancer model and sophisticated drug sensitivity testing. In addition, the parameters of micro-groove impedance chip processing and measurement experiments were optimized in details. The results demonstrated that the MGIS and 3D cell-based biosensor and would be a promising platform to improve the efficiency and accuracy of cell-based anti-cancer drug screening in vitro.

Keywords: micro-groove impedance sensor, 3D cell-based biosensors, 3D cell viability, micro-electromechanical systems

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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

Procedia PDF Downloads 71

Authors: Sang Hun Park, Moung Young Lee, Su Min Yu, Hyun Sang Jo, Ji Hyeon Kim, Chul Gyu Song

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A near-infrared light source used as a light source in the fluorescence imaging system is suitable for use in real-time during the operation since it has no interference in surgical vision. However, fluorescence images do not have depth information. In this paper, we configured the device with the research on molecular imaging systems for monitoring thrombus imaging using fluorescence and photoacoustic. Fluorescence imaging was performed using a phantom experiment in order to search the exact location, and the Photoacoustic image was in order to detect the depth. Fluorescence image obtained when evaluated through current phantom experiments when the concentration of the contrast agent is 25μg / ml, it was confirmed that it looked sharper. The phantom experiment is has shown the possibility with the fluorescence image and photoacoustic image using an indocyanine green contrast agent. For early diagnosis of cardiovascular diseases, more active research with the fusion of different molecular imaging devices is required.

Keywords: fluorescence, photoacoustic, indocyanine green, carotid artery

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Authors: Heramb Somthankar, Anujoy Chakraborty

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This paper presents a classification study on yield prediction in semiconductor production using machine learning approaches. A complicated semiconductor production process is generally monitored continuously by signals acquired from sensors and measurement sites. A monitoring system contains a variety of signals, all of which contain useful information, irrelevant information, and noise. In the case of each signal being considered a feature, "Feature Selection" is used to find the most relevant signals. The open-source UCI SECOM Dataset provides 1567 such samples, out of which 104 fail in quality assurance. Feature extraction and selection are performed on the dataset, and useful signals were considered for further study. Afterward, common machine learning algorithms were employed to predict whether the signal yields pass or fail. The most relevant algorithm is selected for prediction based on the accuracy and loss of the ML model.

Keywords: deep learning, feature extraction, feature selection, machine learning classification algorithms, semiconductor production monitoring, signal processing, time-series analysis

Procedia PDF Downloads 102

Authors: K. Sangeeth, P. Rekha, P. Preeja, P. Divya, R. Arya, R. Maneesha

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Wireless sensor networks (WSN) are small or tiny devices that consists of different sensors to sense physical parameters like air pressure, temperature, vibrations, movement etc., process these data and sends it to the central data center to take decisions. The WSN domain, has wide range of applications such as monitoring and detecting natural hazards like landslides, forest fire, avalanche, flood monitoring and also in healthcare applications. With such different applications, it is being taught in undergraduate/post graduate level in many universities under department of computer science. But the cost and infrastructure required to purchase WSN nodes for having the students getting hands on expertise on these devices is expensive. This paper gives overview about the remote triggered lab that consists of more than 100 WSN nodes that helps the students to remotely login from anywhere in the world using the World Wide Web, configure the nodes and learn the WSN concepts in intuitive way. It proposes new way called over the air programming (OTAP) and its internals that program the 100 nodes simultaneously and view the results without the nodes being physical connected to the computer system, thereby allowing for sparse deployment.

Keywords: WSN, over the air programming, virtual lab, AT45DB

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Authors: Seungmin Shin, Jin-Baek Kim

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Hematite (α-Fe2O3) has very good semiconducting properties with a band gap of 2.1 eV and is antiferromagnetic. Due to its electrochemical stability, low toxicity, wide abundance, and low-cost, hematite, it is a particularly attractive material for photoelectrochemical cells. Additionally, hematite has also found applications in gas sensing, field emission, heterogeneous catalysis, and lithium-ion battery electrodes. Here, we discovered a new universal top-down method for the synthesis of one-dimensional hematite nanowire arrays. Various shapes and lengths of hematite nanowire have been easily fabricated over large areas by sequential processes. The obtained hematite nanowire arrays are promising candidates as photoanodes in photoelectrochemical solar cells.

Keywords: hematite, lithography, nanowire, top-down process

Procedia PDF Downloads 245

Authors: Michael D. Vinod, Hadi Khabbaz

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Construction of infrastructure above or adjacent to landfills is becoming more common to capitalize on the limited space available within urban areas. However, development above landfills is a challenging task due to large voids, the presence of organic matter, heterogeneous nature of waste and ambiguity surrounding landfill settlement prediction. Prior to construction of infrastructure above landfills, ground improvement techniques are being employed to improve the geotechnical properties of landfill material. Although the ground improvement techniques have little impact on long term biodegradation and creep related landfill settlement, they have shown some notable short term success with a variety of techniques, including methods for verifying the level of effectiveness of ground improvement techniques. This paper provides geotechnical and landfill engineers a guideline for selection of landfill ground improvement techniques and their suitability to project-specific sites. Ground improvement methods assessed and compared in this paper include concrete injected columns (CIC), dynamic compaction, rapid impact compaction (RIC), preloading, high energy impact compaction (HEIC), vibro compaction, vibro replacement, chemical stabilization and the inclusion of geosynthetics such as geocells. For each ground improvement technique a summary of the existing theory, benefits, limitations, suitable modern ground improvement monitoring methods, the applicability of ground improvement techniques for landfills and supporting case studies are provided. The authors highlight the importance of implementing cost-effective monitoring techniques to allow observation and necessary remediation of the subsidence effects associated with long term landfill settlement. These ground improvement techniques are primarily for the purpose of construction above closed landfills to cater for transport infrastructure loading.

Keywords: closed landfills, ground improvement, monitoring, settlement, transport infrastructure

Procedia PDF Downloads 214

Authors: Hongquan Zhang

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Inspired by endogenous protein motors, researchers have constructed various synthetic DNA motors based on the specificity and predictability of Watson-Crick base pairing. However, the application of DNA motors to signal amplification and biosensing is limited because of low mobility and difficulty in real-time monitoring of the walking process. The objective of our work was to construct a new type of DNA motor termed target-triggered DNA motors that can walk for hundreds of steps in response to a single target binding event. To improve the mobility and processivity of DNA motors, we used gold nanoparticles (AuNPs) as scaffolds to build high-density, three-dimensional tracks. Hundreds of track strands are conjugated to a single AuNP. To enable DNA motors to respond to specific protein and nucleic acid targets, we adapted the binding-induced DNA assembly into the design of the target-triggered DNA motors. In response to the binding of specific target molecules, DNA motors are activated to autonomously walk along AuNP, which is powered by a nicking endonuclease or DNAzyme-catalyzed cleavage of track strands. Each moving step restores the fluorescence of a dye molecule, enabling monitoring of the operation of DNA motors in real time. The motors can translate a single binding event into the generation of hundreds of oligonucleotides from a single nanoparticle. The motors have been applied to amplify the detection of proteins and nucleic acids in test tubes and live cells. The motors were able to detect low pM concentrations of specific protein and nucleic acid targets in homogeneous solutions without the need for separation. Target-triggered DNA motors are significant for broadening applications of DNA motors to molecular sensing, cell imagining, molecular interaction monitoring, and controlled delivery and release of therapeutics.

Keywords: biosensing, DNA motors, gold nanoparticles, signal amplification

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Authors: Ilme Faridatul, Bo Wu

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Bangladesh is often called as a motherland of rivers. It contains about 700 rivers among all these the Padma River is one of the largest rivers of Bangladesh. The change of river bank and erosion has become a common environmental natural hazard in Bangladesh. The river banks are under intense pressure from natural processes such as erosion and accretion as well as anthropogenic processes such as urban growth and pollution. The Padma River is flowing along ten districts of Bangladesh among all these Faridpur district is most vulnerable to river bank erosion. The severity of the river erosion is so high that each year a thousand of populations become homeless and lose their agricultural lands. Though the Faridpur district is most vulnerable to river bank erosion no specific research has been conducted to identify the changing pattern of river bank along this district. The outcome of the research may serve as guidance to prepare river bank monitoring program and management. This research has utilized integrated techniques of remote sensing and geographic information system to monitor the changes from 1995 to 2015 at Faridpur district. To discriminate the land water interface Modified Normalized Difference Water Index (MNDWI) algorithm is applied and on screen digitization approach is used over MNDWI images of 1995, 2002 and 2015 for river bank line extraction. The extent of changes in the river bank along Faridpur district is estimated through overlaying the digitized maps of all three years. The river bank lines are highlighted to infer the erosion and accretion and the changes are calculated. The result shows that the middle of the river is gaining land through sedimentation and the both side river bank is shifting causing severe erosion that consequently resulting the loss of farmland and homestead. Over the study period from 1995 to 2015 it witnessed huge erosion and accretion that played an active role in the changes of the river bank.

Keywords: river bank, erosion and accretion, change monitoring, remote sensing

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Authors: M. Sundaram, H. R. Sanath Kumar, A. Ramprakash

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Energy saving is a key sustainability focus area for the Indian telecom industry today. This is especially true in rural India where energy consumption contributes to 70 % of the total network operating cost. In urban areas, the energy cost for network operation ranges between 15-30 %. This expenditure on energy as a result of the lack of grid power availability highlights a potential barrier to telecom industry growth. As a result of this, telecom tower companies switch to diesel generators, making them the second largest consumer of diesel in India, consuming over 2.5 billion litres per annum. The growing cost of energy due to increasing diesel prices and concerns over rising greenhouse emissions have caused these companies to look at other renewable energy options. Even the TRAI (Telecom Regulation Authority of India) has issued a number of guidelines to implement Renewable Energy Technologies (RETs) in the telecom towers as part of its ‘Implementation of Green Technologies in Telecom Sector’ initiative. Our proposal suggests the implementation of a Programmable Logic Controller (PLC) based ‘optimisation controller’ that can not only efficiently utilize the energy from RETs but also help to conserve the power used in the telecom towers. When there are multiple RETs available to supply energy, this controller will pick the optimum amount of energy from each RET based on the availability and feasibility at that point of time, reducing the dependence on diesel generators. For effective maintenance of the towers, we are planing to implement a SCADA based monitoring system along with the ‘optimization controller’.

Keywords: operation costs, consumption of fuel and carbon footprint, implementation of a programmable logic controller (PLC) based ‘optimisation controller’, efficient SCADA based monitoring system

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Authors: Faiza Marrium, Masood Rabbani, Ali Ahmad Sheikh, Muhammad Yasin Tipu Javed Muhammad, Sohail Raza

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More than 75% diseases spreading in the past 10 years in human population globally are linked to veterinary sector. Veterinary diagnostic labs are the powerful ally for diagnosis, prevention and monitoring of animal diseases in any country. In order to avoid detrimental effects of errors in disease diagnostic and biorisk management, there is a dire need to establish quality control system. In current study, 3 private and 6 public sectors veterinary diagnostic labs were selected for survey. A questionnaire survey in biorisk management guidelines of CWA 15793 was designed to find quality control breaches in lab design, personal, equipment and consumable, quality control measures adopted in lab, waste management, environmental monitoring and customer care. The data was analyzed through frequency distribution statistically by using (SPSS) version 18.0. A non-significant difference was found in all parameters of lab design, personal, equipment and consumable, quality control measures adopted in lab, waste management, environmental monitoring and customer care with an average percentage of 46.6, 57.77, 52.7, 55.5, 54.44, 48.88 and 60, respectively. A non-significant difference among all nine labs were found, with highest average compliance percentage of all parameters are lab 2 (78.13), Lab 3 (70.56), Lab 5 (57.51), Lab 6 (56.37), Lab 4 (55.02), Lab 9 (49.58), Lab 7 (47.76), Lab 1 (41.01) and Lab 8 (36.09). This study shows that in Lahore district veterinary diagnostic labs are not giving proper attention to quality of their system and there is no significant difference between setups of private and public sector laboratories. These results show that most of parameters are between 50 and 80 percent, which needs some work and improvement as per WHO criteria.

Keywords: veterinary lab, quality management system, accreditation, regulatory body, disease identification

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Authors: Harkishen Singh, Gavin Mangeni

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This project aims at building an efficient and automatic power monitoring SCADA system, which is capable of monitoring the electrical parameters of high voltage powered devices in real time for example RMS voltage and current, frequency, energy consumed, power factor etc. The system uses RS-485 serial communication interface to transfer data over longer distances. Embedded C programming is the platform used to develop two hardware modules namely: RTU and Master Station modules, which both use the CC2540 BLE 4.0 microcontroller configured in slave / master mode. The Si8900 galvanic ally isolated microchip is used to perform ADC externally. The hardware communicates via UART port and sends data to the user PC using the USB port. Labview software is used to design a user interface to display current state of the power loads being monitored as well as logs data to excel spreadsheet file. An understanding of the Si8900’s auto baud rate process is key to successful implementation of this project.

Keywords: SCADA, RS485, CC2540, labview, Si8900

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Authors: Arafat A. A. Shabaneh

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Harsh environments demand a developed detection of an optical communication system to ensure a high level of security and safety. Fiber Bragg gratings (FBG) are emerging sensing instruments that respond to variations in strain and temperature via varying wavelengths. In this paper, cascaded uniform FBG as a strain sensor for 6 km length at 1550 nm wavelength with 30 oC is designed with analyzing of dynamic strain and wavelength shifts. FBG is placed in a small segment of optical fiber, which reflects light of a specific wavelength and passes the remaining wavelengths. This makes a periodic alteration in the refractive index within the fiber core. The alteration in the modal index of fiber produced due to strain consequences in a Bragg wavelength. When the developed sensor exposure to a strain of cascaded uniform FBG by 0.01, the wavelength is shifted to 0.0000144383 μm. The sensing accuracy of the developed sensor is 0.0012. Simulation results show reliable and effective strain monitoring sensors for remote sensing applications.

Keywords: Cascaded fiber Bragg gratings, Strain sensor, Remote sensing, Wavelength shift

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Authors: Rolivhuwa Bishop Ramagoma1*, Lynn Cairncross1, , Saartjie Roux1

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According to the world health organisation, colon cancer is among the most common cancers diagnosed in both men and women. Specifically, it is the second leading cause of cancer related deaths accounting for over 860 000 deaths worldwide in 2018. Currently, chemotherapy has become an essential component of most cancer treatments. Despite progress in cancer drug development over the previous years, traditional chemotherapeutic drugs still have low selectivity for targeting tumour tissues and are frequently constrained by dose-limiting toxicity. The creation of nanoscale delivery vehicles capable of directly directing treatment into cancer cells has recently caught the interest of researchers. Herein, the development of peptide-functionalized polyethylene glycol gold nanoparticles (Peptide-PEG-AuNPs) as a cellular probe and delivery agent is described, with the higher aim to develop a specific diagnostic prototype and assess their specificity not only against cell lines but primary human cells as well. Gold nanoparticles (AuNPs) were synthesized and stabilized through chemical conjugation. The synthesized AuNPs were characterized, stability in physiological solutions was assessed, their cytotoxicity against colon carcinoma and non-carcinoma skin fibroblasts was also studied. Furthermore, genetic effect through real-time polymerase chain reaction (RT-PCR), localization and uptake, peptide specificity were also determined. In this study, different peptide-AuNPs were found to have preferential toxicity at higher concentrations, as revealed by cell viability assays, however, all AuNPs presented immaculate stability for over 3 months following the method of synthesis. The final obtained peptide-PEG-AuNP conjugates showed good biocompatibility in the presence of high ionic solutions and biological media and good cellular uptake. Formulation of colon cancer specific targeting peptide was successful, additionally, the genes/pathways affected by the treatments were determined through RT-PCR. Primary cells study is still on going with promising results thus far.

Keywords: nanotechnology, cancer, diagnosis, therapeutics, gold nanoparticles.

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Authors: Tanu Sharma, Bikramjit Singh Bajwa, Inderpreet Kaur

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Monitoring of groundwater in Tarn-Taran, Bathinda, Faridkot and Mansa districts of Punjab state, India is essential where this freshwater resource is being over-exploited causing quality deterioration, groundwater depletion and posing serious threats to residents. The present integrated study was done to appraise quality and suitability of groundwater for drinking/irrigation purposes, hydro-geochemical characteristics, source identification and associated health risks. In the present study, groundwater of various districts of Punjab state was found to be heavily contaminated with As followed by U, thus posing high cancerous risks to local residents via ingestion, along with minor contamination of Fe, Mn, Pb and F−. Most health concerns in the study region were due to the elevated concentrations of arsenic in groundwater with average values of 130 µg L-1, 176 µg L-1, 272 µg L-1 and 651 µg L-1 in Tarn-Taran, Bathinda, Faridkot and Mansa districts, respectively, which is quite high as compared to the safe limit as recommended by BIS i.e. 10 µg L-1. In Tarn-Taran, Bathinda, Faridkot and Mansa districts, average uranium contents were found to be 37 µg L-1, 88 µg L-1, 61 µg L-1 and 104 µg L-1, with 51 %, 74 %, 61 % and 71 % samples, respectively, being above the WHO limit of 30 µg L-1 in groundwater. Further, the quality indices showed that groundwater of study region is suited for irrigation but not appropriate for drinking purposes. Hydro-geochemical studies revealed that most of the collected groundwater samples belonged to Ca2+ - Mg2+ - HCO3- type showing dominance of MgCO3 type which indicates the presence of temporary hardness in groundwater. Rock-water reactions and reverse ion exchange were the predominant factors for controlling hydro-geochemistry in the study region. Dissolution of silicate minerals caused the dominance of Na+ ions in the aquifers of study region. Multivariate statistics revealed that along with geogenic sources, contribution of anthropogenic activities such as injudicious application of agrochemicals and domestic waste discharge was also very significant. The results obtained abolished the myth that uranium is only root cause for large number of cancer patients in study region as arsenic and mercury were also present in groundwater at levels that were of health concern to groundwater.

Keywords: uranium, trace elements, multivariate data analysis, risk assessment

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Authors: Shanker Kalakotla, Krishna Mohan Gottumukkala

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Diabetes is a metabolic disorder characterized by hyperglycemia, carbohydrates, altered lipids and proteins metabolism. In recent research nanotechnology is a blazing field for the researchers; latterly there has been prodigious excitement in the nanomedicine and nano pharmacological area for the study of silver nanoparticles synthesis using natural products. Biological methods have been used to synthesize silver nanoparticles in presence of medicinally active antidiabetic plants, and this intention made us assess the biologically synthesized silver nanoparticles from the seed extract of Psoralea corylfolia using 1 mM silver nitrate solution. The synthesized herbal mediated silver nanoparticles (HMSNP’s) then subjected to various characterization techniques such as XRD, SEM, EDX, TEM, DLS, UV and FT-IR respectively. In current study, the silver nanoparticles tested for in-vitro anti-diabetic activity and possible toxic effects in healthy female albino mice by following OECD guidelines-425. Herbal mediated silver nanoparticles were successfully obtained from bioreduction of silver nitrate using Psoralea corylifolia plant extract. Silver nanoparticles have been appropriately characterized and confirmed using different types of equipment viz., UV-vis spectroscopy, XRD, FTIR, DLS, SEM and EDX analysis. From the behavioral observations of the study, the female albino mice did not show sedation, respiratory arrest, and convulsions. Test compounds did not cause any mortality at the dose level tested (i.e., 2000 mg/kg body weight) doses till the end of 14 days of observation and were considered safe. It may be concluded that LD50 of the HMSNPs was 2000mg/kg body weight. Since LD50 of the HMSNPs was 2000mg/kg body weight, so the preferred dose range for HMSNPs falls between the levels of 200 and 400 mg/kg. Further In-vivo pharmacological models and biochemical investigations will clearly elucidate the mechanism of action and will be helpful in projecting the currently synthesized silver nanoparticles as a therapeutic target in treating chronic ailments.

Keywords: herbal mediated silver nanoparticles, HMSNPs, toxicity of silver nanoparticles, PTP1B in-vitro anti-diabetic assay female albino mice, 425 OECD guidelines

Procedia PDF Downloads 268

Authors: Huan-Chieh Chiu, Hung-Shuo Wu, Chien-Hao Wang, Yu-Cheng Yang, Ching-Ya Tseng, Joe-Air Jiang

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Power failure resulting from tower collapse due to violent seismic events might bring enormous and inestimable losses. The Chi-Chi earthquake, for example, strongly struck Taiwan and caused huge damage to the power system on September 21, 1999. Nearly 10% of extra high voltage (EHV) transmission towers were damaged in the earthquake. Therefore, seismic hazards of EHV transmission towers should be monitored and evaluated. The ultimate goal of this study is to establish a damage level assessment model for EHV transmission towers. The data of earthquakes provided by Taiwan Central Weather Bureau serve as a reference and then lay the foundation for earthquake simulations and analyses afterward. Some parameters related to the damage level of each point of an EHV tower are simulated and analyzed by the data from monitoring stations once an earthquake occurs. Through the Fourier transform, the seismic wave is then analyzed and transformed into different wave frequencies, and the data would be shown through a response spectrum. With this method, the seismic frequency which damages EHV towers the most is clearly identified. An estimation model is built to determine the damage level caused by a future seismic event. Finally, instead of relying on visual observation done by inspectors, the proposed model can provide a power company with the damage information of a transmission tower. Using the model, manpower required by visual observation can be reduced, and the accuracy of the damage level estimation can be substantially improved. Such a model is greatly useful for health and construction monitoring because of the advantages of long-term evaluation of structural characteristics and long-term damage detection.

Keywords: damage level monitoring, drift ratio, fragility curve, smart grid, transmission tower

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Authors: Mahdokht Sadeghvishkaei, Azizah Abdul-Hamid, Amin Ismail, Nazamid Saari

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Hypertension is a common and serious chronic health problem and known as the most important risk factor for development of many diseases such as stroke. Since angiotensin I-converting enzyme (ACE) is the key enzyme involved in blood pressure, one of the well accepted mechanisms to control hypertension is through ACE inhibition. The ACE inhibitory effect of Actinopyga lecanora (stone fish) proteolysate in vitro had been reported. Hence, this study aimed to evaluate the ACE inhibitory potential of Actinopyga lecanora proteolysate in vivo in normotensive rats. Therefore the ACE inhibitory capability of the proteolysate to prevent increasing systolic blood pressure, after inducing hypertension by angiotensin I was examined. The pre-fed rats with the proteolysates at various doses (200, 400, 800 mg/kg body weight) revealed the significant (p ≤ 0.05) suppression effect compared with control groups. Furthermore, different doses of the proteolysate (200, 400, 800 mg/kg body weight) were examined to find its optimum effective dose. Results depicted that 800 mg proteolysate/kg body weight significantly reduced systolic blood pressure without negative effect on normal blood pressure (p ≤ 0.05). Furthermore, Sub-acute toxicity study based on OECD guideline demonstrated the safety of the proteolysate in vivo. The present study indicated that the proteolysate at a dose of 1000 mg/kg daily for 14 days did not cause toxicity signs such as death, changes in activity, or piloerection. Since there are no significant differences between treated groups and control groups, hematological and biochemical analysis confirmed safety of the proteolysate (p > 0.05). In addition, there were no significant differences between organs weights of the treated groups and the control groups. Morphologically, neither histopathological changes, nor gross abnormalities were observed. However, the proteolysate caused significant decrease in body weight in relation to the control groups (p ≤ 0.05) probably due to appetite stimulation by the proteolysate, leading to decreased food consumption in sub-acute group. It is concluded that the proteolysate generated from Actinopyga lecanora possess a significant anti-hypertensive effect and would be potentially used as natural alternative of ACE inhibitors.

Keywords: ACE inhibition, Actinopyga lecanora, anti-hypertensive activity, bioactive peptides, normotensive rats

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Authors: Sergio Celaschi, Henrique Canavarro de Alencar, Claaudecir Biazoli

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Effluent quality is of the highest priority for compliance with the permit limits of environmental protection agencies and ensures the protection of their local water system. Of the pollutants monitored, the biochemical oxygen demand (BOD) posed one of the greatest challenges. This work presents a solution for wastewater treatment plants - WWTP’s ability to react to different situations and meet treatment goals. Delayed BOD5 results from the lab take 7 to 8 analysis days, hindered the WWTP’s ability to react to different situations and meet treatment goals. Reducing BOD turnaround time from days to hours is our quest. Such a solution is based on a system of two BOD bioreactors associated with Digital Twin (DT) and Machine Learning (ML) methodologies via an Internet of Things (IoT) platform to monitor and control a WWTP to support decision making. DT is a virtual and dynamic replica of a production process. DT requires the ability to collect and store real-time sensor data related to the operating environment. Furthermore, it integrates and organizes the data on a digital platform and applies analytical models allowing a deeper understanding of the real process to catch sooner anomalies. In our system of continuous time monitoring of the BOD suppressed by the effluent treatment process, the DT algorithm for analyzing the data uses ML on a chemical kinetic parameterized model. The continuous BOD monitoring system, capable of providing results in a fraction of the time required by BOD5 analysis, is composed of two thermally isolated batch bioreactors. Each bioreactor contains input/output access to wastewater sample (influent and effluent), hydraulic conduction tubes, pumps, and valves for batch sample and dilution water, air supply for dissolved oxygen (DO) saturation, cooler/heater for sample thermal stability, optical ODO sensor based on fluorescence quenching, pH, ORP, temperature, and atmospheric pressure sensors, local PLC/CPU for TCP/IP data transmission interface. The dynamic BOD system monitoring range covers 2 mg/L < BOD < 2,000 mg/L. In addition to the BOD monitoring system, there are many other operational WWTP sensors. The CPU data is transmitted/received to/from the digital platform, which in turn performs analyses at periodic intervals, aiming to feed the learning process. BOD bulletins and their credibility intervals are made available in 12-hour intervals to web users. The chemical kinetics ML algorithm is composed of a coupled system of four first-order ordinary differential equations for the molar masses of DO, organic material present in the sample, biomass, and products (CO₂ and H₂O) of the reaction. This system is solved numerically linked to its initial conditions: DO (saturated) and initial products of the kinetic oxidation process; CO₂ = H₂0 = 0. The initial values for organic matter and biomass are estimated by the method of minimization of the mean square deviations. A real case of continuous monitoring of BOD wastewater effluent quality is being conducted by deploying an IoT application on a large wastewater purification system located in S. Paulo, Brazil.

Keywords: effluent treatment, biochemical oxygen demand, continuous monitoring, IoT, machine learning

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Authors: Reda A. Elkhyat, Mahmoud Nasr, Amel A. Tammam, Mohamed A. Ghazy

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Pharmaceuticals and personal care products (PPCPs) are a unique group of emerging contaminants continuously introduced into the aquatic ecosystem at concentrations capable of inducing adverse effects on humans and aquatic organisms, even at trace levels ranging from ppt to ppm. Amongst the common pharmaceutical emerging pollutants detected in several aquatic environments, acetaminophen has been recognized for its high toxicity. Once released into the aquatic environment, acetaminophen could be degraded by the microbial community and adsorption/ uptake by the plants. Although many studies have investigated the hazard risks of acetaminophen pollutants on aquatic animals, the number of studies demonstrating its removal efficiency and effects on the aquatic plant still needs to be expanded. In this context, this study aims to apply the aquatic plant-based phytoremediation system to eliminate this emerging contaminant from domestic wastewater. The phytoremediation experiment was performed in a hydroponic system containing Eichhornia crassipes and operated under the natural environment at 25°C to 30°C. This system was subjected to synthetic domestic wastewater with the maximum initial chemical oxygen demand (COD) of 390 mg/L and three different acetaminophen concentrations of 25, 50, and 200 mg/L. After 17 d of operation, the phytoremediation system achieved removal efficiencies of about 100% and 85.6±4.2% for acetaminophen and COD, respectively.Moreover, the Eichhornia crassipes could withstand the toxicity associated with increasing the acetaminophen concentrations from 25 to 200 mg/L. This high treatment performance could be assigned to the well-adaptation of the water hyacinth to the phytoremediation factors. Moreover, it has been proposed that this phytoremediation system could be largely supported by phytodegradation and plant uptaking mechanisms; however, detecting the generated intermediates, metabolites, and degradation products are still under investigation. Applying this free-floating plant in wastewater treatment and reducing emerging contaminants would meet the targets of SDGs 3, 6, and. 14. The cost-benefit analysis was performed for the phytoremediation system. The phytoremediation system is financially viable as the net profit was 2921 US $/ y with a payback period of nine years.

Keywords: domestic wastewater, emerging pollutants, hydrophyte Eichhornia crassipes, paracetamol removal efficiency, sustainable development goals (SDGs)

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Authors: Leila Jafari, Viliam Makis, G. B. Akram Khaleghei

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In this paper, we present a maintenance model of a two-unit series system with economic dependence. Unit#1, which is considered to be more expensive and more important, is subject to condition monitoring (CM) at equidistant, discrete time epochs and unit#2, which is not subject to CM, has a general lifetime distribution. The multivariate observation vectors obtained through condition monitoring carry partial information about the hidden state of unit#1, which can be in a healthy or a warning state while operating. Only the failure state is assumed to be observable for both units. The objective is to find an optimal opportunistic maintenance policy minimizing the long-run expected average cost per unit time. The problem is formulated and solved in the partially observable semi-Markov decision process framework. An effective computational algorithm for finding the optimal policy and the minimum average cost is developed and illustrated by a numerical example.

Keywords: condition-based maintenance, semi-Markov decision process, multivariate Bayesian control chart, partially observable system, two-unit system

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Authors: Dingding Chen, Kazuo Arakawa, Masakazu Uchino, Changheng Xu

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Vacuum assisted resin transfer moulding (VARTM) is a promising manufacture process for making large and complex fiber reinforced composite structures. However, the complexity of the flow of the resin in the infusion stage usually leads to nonuniform property distribution of the produced composite part. In order to control the flow of the resin, the situation of flow should be mastered. For the safety of the usage of the produced composite in practice, the understanding of the property distribution is essential. In this paper, we did some trials on monitoring the resin infusion stage and evaluation for the fiber volume fraction distribution of the VARTM produced composite using the digital image correlation methods. The results show that 3D-DIC is valid on monitoring the resin infusion stage and it is possible to use 2D-DIC to estimate the distribution of the fiber volume fraction on a FRP plate.

Keywords: digital image correlation, VARTM, FRP, fiber volume fraction

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Authors: Sanjay Adhikesaven

Abstract:

Workplace accidents are a critical problem that causes many deaths, injuries, and financial losses. Climate change has a severe impact on industrial workers, partially caused by global warming. To reduce such casualties, it is important to proactively find unsafe environments where injuries could occur by detecting the use of personal protective equipment (PPE) and identifying unsafe activities. Thus, we propose an industrial workplace alerting and monitoring platform to detect PPE use and classify unsafe activity in group settings involving multiple humans and objects over a long period of time. Our proposed method is the first to analyze prolonged actions involving multiple people or objects. It benefits from combining pose estimation with PPE detection in one platform. Additionally, we propose the first open-source annotated data set with video data from industrial workplaces annotated with the action classifications and detected PPE. The proposed system can be implemented within the surveillance cameras already present in industrial settings, making it a practical and effective solution.

Keywords: computer vision, deep learning, workplace safety, automation

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Authors: Zahzouh Zoubir

Abstract:

The widespread adoption of photovoltaic panel systems for global electricity generation is a prominent trend. Algeria, demonstrating steadfast commitment to strategic development and innovative projects for harnessing solar energy, emerges as a pioneering force in the field. Heat and radiation, being fundamental factors in any solar system, are currently subject to comprehensive studies aiming to discern their genuine impact on crucial elements within photovoltaic systems. This endeavor is particularly pertinent given that solar module performance is exclusively assessed under meticulously defined Standard Test Conditions (STC). Nevertheless, when deployed outdoors, solar modules exhibit efficiencies distinct from those observed under STC due to the influence of diverse environmental factors. This discrepancy introduces ambiguity in performance determination, especially when surpassing test conditions. This article centers on the performance monitoring of an Algerian photovoltaic project, specifically the Oued El Keberite power (OKP) plant boasting a 15 megawatt capacity, situated in the town of Souk Ahras in eastern Algeria. The study elucidates the behavior of a subfield within this facility throughout the year, encompassing various conditions beyond the STC framework. To ensure the optimal efficiency of solar panels, this study integrates crucial factors, drawing on an authentic technical sheet from the measurement station of the OKP photovoltaic plant. Numerical modeling and simulation of a sub-field of the photovoltaic station were conducted using MATLAB Simulink. The findings underscore how radiation intensity and temperature, whether low or high, impact the short-circuit current, open-circuit voltage; fill factor, and overall efficiency of the photovoltaic system.

Keywords: performance monitoring, photovoltaic system, numerical modeling, radiation intensity

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Authors: Wenhao Li, Shijun Guo

Abstract:

Carbon fibre reinforced composites are progressively replacing metal structures in modern civil aircraft. This is because composite materials have large potential of weight saving compared with metal. However, the achievement to date of weight saving in composite structure is far less than the theoretical potential due to many uncertainties in structural integrity and safety concern. Unlike the conventional metallic structure, composite components are bonded together along the joints where structural integrity is a major concern. To ensure the safety, metal fasteners are used to reinforce the composite bonded joints. One of the solutions for a significant weight saving of composite structure is to develop an effective technology of on-board Structural Health Monitoring (SHM) System. By monitoring the real-life stress status of composite structures during service, the safety margin set in the structure design can be reduced with confidence. It provides a means of safeguard to minimize the need for programmed inspections and allow for maintenance to be need-driven, rather than usage-driven. The aim of this paper is to develop smart composite joint. The key technology is a multifunctional thermoplastic composite fastener (MTCF). The MTCF will replace some of the existing metallic fasteners in the most concerned locations distributed over the aircraft composite structures to reinforce the joints and form an on-board SHM network system. Each of the MTCFs will work as a unit of the AU and AE technology. The proposed MTCF technology has been patented and developed by Prof. Guo in Cranfield University, UK in the past a few years. The manufactured MTCF has been successfully employed in the composite SLJ (Single-Lap Joint). In terms of the structure integrity, the hybrid SLJ reinforced by MTCF achieves 19.1% improvement in the ultimate failure strength in comparison to the bonded SLJ. By increasing the diameter or rearranging the lay-up sequence of MTCF, the hybrid SLJ reinforced by MTCF is able to achieve the equivalent ultimate strength as that reinforced by titanium fastener. The predicted ultimate strength in simulation is in good agreement with the test results. In terms of the structural health monitoring, a signal from the MTCF was measured well before the load of mechanical failure. This signal provides a warning of initial crack in the joint which could not be detected by the strain gauge until the final failure.

Keywords: composite single-lap joint, crack propagation, multifunctional composite fastener, structural health monitoring

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Authors: Ebere Christian Ugochukwu, Okafor Josephine, Oyawoye Tomisin

Abstract:

The occurrence of multidrug resistance patterns that have been developed by bacteria has made it difficult to properly treat infections using standard clinical medications. Hence, the use of herbs as an alternative source of therapy is considered cheap and easily accessible to locals. This research explored the antimicrobial effects of aqueous and ethanolic extracts obtained from Chrysophyllum albidum (commonly called ‘Agbalumo’ in southwest Nigeria and ‘Udara’ in the eastern and southern parts of Nigeria) plant parts (leaves, roots and seeds) against bacteria isolated from urinary catheter tips. The following isolates were obtained; Pseudomonas aeruginosa, Staphylococcus aureus, Escherichia coli, Proteus mirabilis, and Klebsiella aerogenes. The agar well diffusion method was used. The average percentages of antimicrobial resistance of the isolates to gentamycin were 45.5% for P. aeruginosa, 42.1% for E. coli, 46.9% for K. aerogenes, and ˃90% for other isolates. Qualitative phytochemical screening of the plant parts extracts was done using chemical test for the screening and identification of bioactive chemical constituents. The ethanolic extract mixtures (leaf, root and seed) had the greatest effect on all the isolates, with inhibition zones (IZs) ranging from 8-26 mm and MICs ranging from <16-32 mg/ml. The Potencies of the C. albidum extracts based on the IZ and MIC values were greater in the extract mixtures, followed by those in the roots. Phytochemical screening revealed that all the extracts contained phenol except for the seeds while tannins were present in all the extracts except the leaves. The activity of the ethanolic extracts of each part at high and low concentrations was greater than that of the aqueous extracts at the same concentrations (p<0.05). The acute toxicity results showed that the LD50 of the extracts was ˃5000 mg/body weight, indicating no toxicity. The antibacterial activities of the extract mixtures and roots on the isolates confirmed the use of C. albidum in folk medicine for the treatment of CAUTIs, hence indicating its antibacterial potential for use in novel antibiotic production.

Keywords: antimicrobials, susceptibility, minimum inhibitory concentration, extracts

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Authors: Asmir Gogic, Aljo Mujcic, Sandra Ibric, Nermin Suljanovic

Abstract:

Ubiquity of natural disasters during last few decades have risen serious questions towards the prediction of such events and human safety. Every disaster regardless its proportion has a precursor which is manifested as a disruption of some environmental parameter such as temperature, humidity, pressure, vibrations and etc. In order to anticipate and monitor those changes, in this paper we propose an overall system for disaster prediction and monitoring, based on wireless sensor network (WSN). Furthermore, we introduce a modified and simplified WSN routing protocol built on the top of the trickle routing algorithm. Routing algorithm was deployed using the bluetooth low energy protocol in order to achieve low power consumption. Performance of the WSN network was analyzed using a real life system implementation. Estimates of the WSN parameters such as battery life time, network size and packet delay are determined. Based on the performance of the WSN network, proposed system can be utilized for disaster monitoring and prediction due to its low power profile and mesh routing feature.

Keywords: bluetooth low energy, disaster prediction, mesh routing protocols, wireless sensor networks

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Authors: Koichi Kurita

Abstract:

In this study, an effective non-contact technique for the detection of human physical activity is proposed. The technique is based on detecting the electrostatic induction current generated by the walking motion under non-contact and non-attached conditions. A theoretical model for the electrostatic induction current generated because of a change in the electric potential of the human body is proposed. By comparing the obtained electrostatic induction current with the theoretical model, it becomes obvious that this model effectively explains the behavior of the waveform of the electrostatic induction current. The normal walking motions are recorded using a portable sensor measurement located in a passageway　of office building. The obtained results show that detailed information regarding physical activity such as a walking cycle can be estimated using our proposed technique. This suggests that the proposed technique which is based on the detection of the walking signal, can be successfully applied to the detection of human walking motion in a secured building.

Keywords: human walking motion, access control, electrostatic induction, alarm monitoring

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Authors: Javier A. Dominguez Caballero, Graeme A. Manson, Matthew B. Marshall

Abstract:

Cutting tools with ceramic inserts are often used in the process of machining many types of superalloy, mainly due to their high strength and thermal resistance. Nevertheless, during the cutting process, the plastic flow wear generated in these inserts enhances and propagates cracks due to high temperature and high mechanical stress. This leads to a very variable failure of the cutting tool. This article explores the relationship between the continuous wear that ceramic SiAlON (solid solutions based on the Si3N4 structure) inserts experience during a high-speed machining process and the evolution of sparks created during the same process. These sparks were analysed through pictures of the cutting process recorded using an SLR camera. Features relating to the intensity and area of the cutting sparks were extracted from the individual pictures using image processing techniques. These features were then related to the ceramic insert’s crater wear area.

Keywords: ceramic cutting tools, high speed machining, image processing, tool condition monitoring, tool wear

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Authors: Spoorthi Sripad

Abstract:

Rapid advancements in LiDAR (Light Detection and Ranging) technology, coupled with the synergy of remote sensing, have revolutionized Earth observation methodologies. This paper delves into the transformative impact of integrated LiDAR and remote sensing systems. Focusing on miniaturization, cost reduction, and improved resolution, the study explores the evolving landscape of terrestrial and aquatic environmental monitoring. The integration of multi-wavelength and dual-mode LiDAR systems, alongside collaborative efforts with other remote sensing technologies, presents a comprehensive approach. The paper highlights the pivotal role of LiDAR in environmental assessment, urban planning, and infrastructure development. As the amalgamation of LiDAR and remote sensing reshapes Earth observation, this research anticipates a paradigm shift in our understanding of dynamic planetary processes.

Keywords: LiDAR, remote sensing, earth observation, advancements, integration, environmental monitoring, multi-wavelength, dual-mode, technology, urban planning, infrastructure, resolution, miniaturization

Procedia PDF Downloads 72