Search results for: progress monitoring

Authors: George N. Zaimes, Valasia Iakovoglou, Paschalis Koutalakis, Konstantinos Ioannou, Ioannis Kosmadakis, Panagiotis Tsardaklis, Theodoros Laopoulos

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The advancements in technology allow the development of a new system that can continuously measure surface soil erosion. Continuous soil erosion measurements are required in order to comprehend the erosional processes and propose effective and efficient conservation measures to mitigate surface erosion. Mitigating soil erosion, especially in Mediterranean countries such as Greece, is essential in order to maintain environmental and agricultural sustainability. In this paper, we present the Automated Soil Erosion Monitoring System (ASEMS) that measures surface soil erosion along with other factors that impact erosional process. Specifically, this system measures ground level changes (surface soil erosion), rainfall, air temperature, soil temperature and soil moisture. Another important innovation is that the data will be collected by remote communication. In addition, stakeholder’s awareness is a key factor to help reduce any environmental problem. The different dissemination activities that were utilized are described. The overall outcomes were the development of an innovative system that can measure erosion very accurately. These data from the system help study the process of erosion and find the best possible methods to reduce erosion. The dissemination activities enhance the stakeholder's and public's awareness on surface soil erosion problems and will lead to the adoption of more effective soil erosion conservation practices in Greece.

Keywords: soil management, climate change, new technologies, conservation practices

Procedia PDF Downloads 338

Authors: Anand K. Patel

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Background: Patients with COPD have decreased pulmonary functions, which in turn reflect on their day-to-day activities. Objectives: To assess the correlation between functional vital capacity (FVC) and forced expiratory volume in one second (FEV1) with 6 minutes walk test (6MWT). To correlate the Borg rating for perceived exertion scale (Borg scale) and Modified medical research council (MMRC) dyspnea scale with the 6MWT, FVC and FEV1. Method: In this prospective study total 72 patients with COPD diagnosed by the GOLD guidelines were enrolled after taking written consent. They were first asked to rate physical exertion on the Borg scale as well as the modified medical research council dyspnea scale and then were subjected to perform pre and post bronchodilator spirometry followed by 6 minute walk test. The findings were correlated by calculating the Pearson coefficient for each set and obtaining the p-values, with a p < 0.05 being clinically significant. Result: There was a significant correlation between spirometry and 6MWT suggesting that patients with lower measurements were unable to walk for longer distances. However, FVC had the stronger correlation than FEV1. MMRC scale had a stronger correlation with 6MWT as compared to the Borg scale. Conclusion: The study suggests that 6MWT is a better test for monitoring the patients of COPD. In spirometry, FVC should be used in monitoring patients with COPD, instead of FEV1. MMRC scale shows a stronger correlation than the Borg scale, and we should use it more often.

Keywords: spirometry, 6 minute walk test, MMRC, Borg scale

Procedia PDF Downloads 193

Authors: Yeliz Ekinci, Raife Merve Ön

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Nowadays, technological progress is one of the most important components of economic growth and the efficiency of R&D activities is particularly essential for countries. This study is an attempt to analyze the R&D efficiencies of EU countries. The indicators related to R&D efficiencies should be determined in advance in order to use DEA. For this reason a list of input and output indicators are derived from the literature review. Considering the data availability, a final list is given for the numerical analysis for future research.

Keywords: data envelopment analysis, economic growth, EU countries, R&D efficiency

Procedia PDF Downloads 535

Authors: Altab Hossain, Shakerul Islam, Golamur R. Khan, Abu Zafar M. Salahuddin

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An effective identification of breakdowns is of premier importance for the safe and reliable operation of Nuclear Power Plants (NPP) and its associated facilities. A great number of monitoring and diagnosis methodologies are applied and used worldwide in areas such as industry, automobiles, hospitals, and power plant to detect and reduce human disasters. The potential consequences of several hazardous activities may harm the society using nuclear and its associated facilities. Hence, one of the most popular and effective methods to ensure safety and monitor the entire nuclear facility and imply risk-free operation without human interference during the hazardous situation is using a robot. Therefore, in this study, an advanced autonomous robot has been designed and developed that can monitor several parameters in the NPP to ensure the safety and do some risky job in case of nuclear disaster. The robot consisted of autonomous track following unit, data processing and transmitting unit can follow a straight line and take turn as the bank greater than 90 degrees. The developed robot can analyze various parameters such as temperature, altitude, radiation, obstacle, humidity, detecting fire, measuring distance, ultrasonic scan and taking the heat of any particular object. It has an ability to broadcast live stream and can record the document to its own server memory. There is a separate control unit constructed with a baseboard which processes the recorded data and a transmitter which transmits the processed data. To make the robot user-friendly, the code is developed such a way that a user can control any of robotic arm as per types of work. To control at any place and without the track, there is an advanced code has been developed to take manual overwrite. Through this process, administrator who has logged in permission to Dynamic Host Client Protocol (DHCP) can make the handover of the control of the robot. In this process, this robot is provided maximum nuclear security from being hacked. Not only NPP, this robot can be used to maximize the real-time monitoring system of any nuclear facility as well as nuclear material transportation and decomposition system.

Keywords: nuclear power plant, radiation, dynamic host client protocol, nuclear security

Procedia PDF Downloads 206

Authors: Fidelia A. Orji, Julita Vassileva

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This research aims to develop machine learning models for students' academic performance and study strategy prediction, which could be generalized to all courses in higher education. Key learning attributes (intrinsic, extrinsic, autonomy, relatedness, competence, and self-esteem) used in building the models are chosen based on prior studies, which revealed that the attributes are essential in students’ learning process. Previous studies revealed the individual effects of each of these attributes on students’ learning progress. However, few studies have investigated the combined effect of the attributes in predicting student study strategy and academic performance to reduce the dropout rate. To bridge this gap, we used Scikit-learn in python to build five machine learning models (Decision Tree, K-Nearest Neighbour, Random Forest, Linear/Logistic Regression, and Support Vector Machine) for both regression and classification tasks to perform our analysis. The models were trained, evaluated, and tested for accuracy using 924 university dentistry students' data collected by Chilean authors through quantitative research design. A comparative analysis of the models revealed that the tree-based models such as the random forest (with prediction accuracy of 94.9%) and decision tree show the best results compared to the linear, support vector, and k-nearest neighbours. The models built in this research can be used in predicting student performance and study strategy so that appropriate interventions could be implemented to improve student learning progress. Thus, incorporating strategies that could improve diverse student learning attributes in the design of online educational systems may increase the likelihood of students continuing with their learning tasks as required. Moreover, the results show that the attributes could be modelled together and used to adapt/personalize the learning process.

Keywords: classification models, learning strategy, predictive modeling, regression models, student academic performance, student motivation, supervised machine learning

Procedia PDF Downloads 125

Authors: M. Ahmadi, M. Kafil, H. Ebrahimi

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Nowadays, induction motors have a significant role in industries. Condition monitoring (CM) of this equipment has gained a remarkable importance during recent years due to huge production losses, substantial imposed costs and increases in vulnerability, risk, and uncertainty levels. Motor current signature analysis (MCSA) is one of the most important techniques in CM. This method can be used for rotor broken bars detection. Signal processing methods such as Fast Fourier transformation (FFT), Wavelet transformation and Empirical Mode Decomposition (EMD) are used for analyzing MCSA output data. In this study, these signal processing methods are used for broken bar problem detection of Mobarakeh steel company induction motors. Based on wavelet transformation method, an index for fault detection, CF, is introduced which is the variation of maximum to the mean of wavelet transformation coefficients. We find that, in the broken bar condition, the amount of CF factor is greater than the healthy condition. Based on EMD method, the energy of intrinsic mode functions (IMF) is calculated and finds that when motor bars become broken the energy of IMFs increases.

Keywords: broken bar, condition monitoring, diagnostics, empirical mode decomposition, fourier transform, wavelet transform

Procedia PDF Downloads 147

Authors: Yuguang Wang, Chuanjun Wang

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At present, many coastal areas around the world suffer from seawater intrusion. Seawater intrusion is the superimposed result of two factors which are nature and human social economical activities in particular area. In recent years, due to excessive exploitation of groundwater, the seawater intrusion phenomenon aggravate in coastal zone of the Bohai and Huanghai seas in our country. Moreover, with sea-level rising, the original hydrodynamic equilibrium between saltwater and freshwater has been damaged to a certain extent, and it will further aggravate seawater intrusion in the land plains. In addition, overexploitation of groundwater declined groundwater level and increase saltwater intrusion in coastal areas. Therefore, in view of the sensitivity and vulnerability of the impact of sea-level rise in the future, the risk of sea-level rise in coastal zone should be considered, reasonable exploitation, utilization and management of coastal zone’s groundwater should be formulated. The response mechanism of sea-level rise should be studied to prevent and reduce the harm of seawater intrusion, which has important theoretical and realistic significances. In this paper, through the long-term monitoring of groundwater level and conductibility in the transition region of seawater intrusion for the sand coast area, realtimely master the situation of seawater intrusion. Combined with the seasonal exploitation station of groundwater and sea level variation, early alert the seawater intrusion to prevent and reduce the harm of seawater intrusion.

Keywords: groundwater level, sea level, seawater intrusion, sand coast

Procedia PDF Downloads 463

Authors: Esra Yuksel, Dilek Duman, Levent Yeniay, Sezgin Ulukaya

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Sentinel lymph node biopsy (SLNB) is a minimal invasive technique with lower morbidity in axillary staging of breast cancer. Isosulfan blue stain is frequently used in SLNB and regarded as safe. The present case report aimed to report severe decrement in SpO2 following isosulfan blue administration, as well as skin and urine signs and inconsistency with clinical picture in a 67-year-old ,77 kg, ASA II female case that underwent SLNB under general anesthesia. Ten minutes after subcutaneous administration of 10 ml 1% isosulfan blue by the surgeons into the patient, who were hemodynamically stable, SpO2 first reduced to 87% from 99%, and then to 75% in minutes despite 100% oxygen support. Meanwhile, blood pressure and EtCO2 monitoring was unremarkable. After specifying that anesthesia device worked normally, airway pressure did not increase and the endotracheal tube has been placed accurately, the blood sample was taken from the patient for arterial gas analysis. A severe increase was thought in MetHb concentration since SpO2 persisted to be 75% although the concentration of inspired oxygen was 100%, and solution of 2500 mg ascorbic acid in 500 ml 5% Dextrose was given to the patient via intravenous route until the results of arterial blood gas were obtained. However, arterial blood gas results were as follows: pH: 7.54, PaCO2: 23.3 mmHg, PaO2: 281 mmHg, SaO2: %99, and MetHb: %2.7. Biochemical analysis revealed a blood MetHb concentration of 2%.However, since arterial blood gas parameters were good, hemodynamics of the patient was stable and methemoglobin concentration was not so high, the patient was extubated after surgery when she was relaxed, cooperated and had adequate respiration. Despite the absence of respiratory or neurological distress, SpO2 value was increased only up to 85% within 2 hours with 5 L/min oxygen support via face mask in the surgery room as the patient was extubated. At that time, the skin of particularly the upper part of her body has turned into blue, more remarkable on the face. The color of plasma of the blood taken from the patient for biochemical analysis was blue. The color of urine coming throughout the urinary catheter placed in intensive care unit was also blue. Twelve hours after 5 L/min. oxygen inhalation via a mask, the SpO2 reached to 90%. During monitoring in intensive care unit on the postoperative 1st day, facial color and urine color of the patient was still blue, SpO2 was 92%, and arterial blood gas levels were as follows: pH: 7.44, PaO2: 76.1 mmHg, PaCO2: 38.2 mmHg, SaO2: 99%, and MetHb 1%. During monitoring in clinic on the postoperative 2nd day, SpO2 was 95% without oxygen support and her facial and urine color turned into normal. The patient was discharged on the 3rd day without any problem.In conclusion, SLNB is a less invasive alternative to axillary dissection. However, false pulse oximeter reading due to pigment interference is a rare complication of this procedure. Arterial blood gas analysis should be used to confirm any fall in SpO2 reading during monitoring.

Keywords: isosulfan blue, pulse oximetry, SLNB, methemoglobinemia

Procedia PDF Downloads 313

Authors: A. Casale, J. Alessi, C. N. Bianchi, G. Bozzini, M. Brunoldi, V. Cappanera, P. Corvisiero, G. Fanciulli, D. Grosso, N. Magnoli, A. Mandich, C. Melchiorre, C. Morri, P. Povero, N. Stasi, M. Taiuti, G. Viano, M. Wurtz

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This work describes a real-time algorithm for detecting, tracking and classifying single motorboats, developed using the acoustic data recorded by a hydrophone array within the framework of EU LIFE + project ARION (LIFE09NAT/IT/000190). The project aims to improve the conservation status of bottlenose dolphins through a real-time simultaneous monitoring of their population and surface ship traffic. A Passive Acoustic Monitoring (PAM) system is installed on two autonomous permanent marine buoys, located close to the boundaries of the Marine Protected Area (MPA) of Portofino (Ligurian Sea- Italy). Detecting surface ships is also a necessity in many other sensible areas, such as wind farms, oil platforms, and harbours. A PAM system could be an effective alternative to the usual monitoring systems, as radar or active sonar, for localizing unauthorized ship presence or illegal activities, with the advantage of not revealing its presence. Each ARION buoy consists of a particular type of structure, named meda elastica (elastic beacon) composed of a main pole, about 30-meter length, emerging for 7 meters, anchored to a mooring of 30 tons at 90 m depth by an anti-twist steel wire. Each buoy is equipped with a floating element and a hydrophone tetrahedron array, whose raw data are send via a Wi-Fi bridge to a ground station where real-time analysis is performed. Bottlenose dolphin detection algorithm and ship monitoring algorithm are operating in parallel and in real time. Three modules were developed and commissioned for ship monitoring. The first is the detection algorithm, based on Time Difference Of Arrival (TDOA) measurements, i.e., the evaluation of angular direction of the target respect to each buoy and the triangulation for obtaining the target position. The second is the tracking algorithm, based on a Kalman filter, i.e., the estimate of the real course and speed of the target through a predictor filter. At last, the classification algorithm is based on the DEMON method, i.e., the extraction of the acoustic signature of single vessels. The following results were obtained; the detection algorithm succeeded in evaluating the bearing angle with respect to each buoy and the position of the target, with an uncertainty of 2 degrees and a maximum range of 2.5 km. The tracking algorithm succeeded in reconstructing the real vessel courses and estimating the speed with an accuracy of 20% respect to the Automatic Identification System (AIS) signals. The classification algorithm succeeded in isolating the acoustic signature of single vessels, demonstrating its temporal stability and the consistency of both buoys results. As reference, the results were compared with the Hilbert transform of single channel signals. The algorithm for tracking multiple targets is ready to be developed, thanks to the modularity of the single ship algorithm: the classification module will enumerate and identify all targets present in the study area; for each of them, the detection module and the tracking module will be applied to monitor their course.

Keywords: acoustic-noise, bottlenose-dolphin, hydrophone, motorboat

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Authors: Gabrielle Peck, Ryan Hayes

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This research presents the design and creation of a drone gas analyser, aimed at addressing the need for independent data collection and analysis of gas emissions during large-scale fires, particularly wasteland fires. The analyser drone, comprising a lightweight gas analysis system attached to a remote-controlled drone, enables the real-time assessment of smoke toxicity and the monitoring of gases released into the atmosphere during such incidents. The key components of the analyser unit included two gas line inlets connected to glass wool filters, a pump with regulated flow controlled by a mass flow controller, and electrochemical cells for detecting nitrogen oxides, hydrogen cyanide, and oxygen levels. Additionally, a non-dispersive infrared (NDIR) analyser is employed to monitor carbon monoxide (CO), carbon dioxide (CO₂), and hydrocarbon concentrations. Thermocouples can be attached to the analyser to monitor temperature, as well as McCaffrey probes combined with pressure transducers to monitor air velocity and wind direction. These additions allow for monitoring of the large fire and can be used for predictions of fire spread. The innovative system not only provides crucial data for assessing smoke toxicity but also contributes to fire prediction and management. The remote-controlled drone's mobility allows for safe and efficient data collection in proximity to the fire source, reducing the need for human exposure to hazardous conditions. The data obtained from the gas analyser unit facilitates informed decision-making by emergency responders, aiding in the protection of both human health and the environment. This abstract highlights the successful development of a drone gas analyser, illustrating its potential for enhancing smoke toxicity analysis and fire prediction capabilities. The integration of this technology into fire management strategies offers a promising solution for addressing the challenges associated with wildfires and other large-scale fire incidents. The project's methodology and results contribute to the growing body of knowledge in the field of environmental monitoring and safety, emphasizing the practical utility of drones for critical applications.

Keywords: fire prediction, drone, smoke toxicity, analyser, fire management

Procedia PDF Downloads 85

Authors: Mandeep Kataria, Ritu Narula, Navneet Kaur

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Asparagine is vital amino acid which is required for the development of brain and it regulates the equilibrium of central nervous system. Asparagine is the chief amino acid that forms acrylamide in baked food by reacting with reducing sugars at high temperature ( Millard Reaction i.e. amino acids and sugars give new flavors at high temperature). It can also be a parameter of freshness in fruit juices because on storage of juices at 37°C caused an 87% loss in the total free amino acids and major decrease was recorded in asparagine contents. With this significance of monitoring asparagine, in the present work a biosensor for determining asparagine in fruit juices is developed. For the construction of biosensor L-asparaginase enzyme (0.5 IU) was co-immobilized with phenol red on TEOS chitosan sol-gel plastic disc and fixed on the fiber optic tip. Tip was immersed in a cell having 5ml of substrate and absorption was noted at response time of 5 min with 10-1 - 10-10 M concentrations of asparagine at 538 nm. L-asparaginase was extracted and from Solanum nigrum Asparagine biosensor was applied fruit juices on the monitoring asparagine contents. L-asparagine concentration found to be present in fruit juices like Guava Juice, Apple Juice, Mango Juice, Litchi juice, Strawberry juice, Pineapple juice Lemon juice, and Orange juice. Hence the developed biosensor has commercial aspects in quality insurance of fruit juices.

Keywords: fiber optic biosensor, chitosan, teos, l-asparaginase

Procedia PDF Downloads 285

Authors: Ugur Fidan, Naim Karasekreter

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Healthy and clean water should not contain disease-causing micro-organisms and toxic chemicals and must contain the necessary minerals in a balanced manner. Today, water resources have a limited and strategic importance, necessitating the management of water reserves. Water tanks meet the water needs of people and should be regularly chlorinated to prevent waterborne diseases. For this purpose, automatic chlorination systems placed in water tanks for killing bacteria. However, the regular operation of automatic chlorination systems depends on refilling the chlorine tank when it is empty. For this reason, there is a need for a stock control system, in which chlorine levels are regularly monitored and supplied. It has become imperative to take urgent measures against epidemics caused by the fact that most of our country is not aware of the end of chlorine. The aim of this work is to rehabilitate existing water tanks and to provide a method for a modern water storage system in which chlorination is digitally monitored by turning the newly established water tanks into a closed system. A sensor network structure using GSM/GPRS communication infrastructure has been developed in the study. The system consists of two basic units: hardware and software. The hardware includes a chlorine level sensor, an RFID interlock system for authorized personnel entry into water tank, a motion sensor for animals and other elements, and a camera system to ensure process safety. It transmits the data from the hardware sensors to the host server software via the TCP/IP protocol. The main server software processes the incoming data through the security algorithm and informs the relevant unit responsible (Security forces, Chlorine supply unit, Public health, Local Administrator) by e-mail and SMS. Since the software is developed base on the web, authorized personnel are also able to monitor drinking water tank and report data on the internet. When the findings and user feedback obtained as a result of the study are evaluated, it is shown that closed drinking water tanks are built with GRP type material, and continuous monitoring in digital environment is vital for sustainable health water supply for people.

Keywords: wireless sensor networks (WSN), monitoring, chlorine, water tank, security

Procedia PDF Downloads 156

Authors: Lorenza Abbracciavento, Valerio De Biagi

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Infrastructures are key elements to ensure the operational functionality of the transport system. The collapse of a single bridge or, equivalently, a tunnel can leads an entire motorway to be considered completely inaccessible. As a consequence, the paralysis of the communications network determines several important drawbacks for the community. Recent chronicle events have demonstrated that ensuring the functional continuity of the strategic infrastructures during and after a catastrophic event makes a significant difference in terms of life and economical losses. Moreover, it has been observed that RC structures located in mountain environments show a worst state of conservation compared to the same typology and aging structures located in temperate climates. Because of its morphology, in fact, the mountain environment is particularly exposed to severe collapse and deterioration phenomena, generally: natural hazards, e.g. rock falls, and meteorological hazards, e.g. freeze-thaw cycles or heavy snows. For these reasons, deep investigation on the characteristics of these processes becomes of fundamental importance to provide smart and sustainable solutions and make the infrastructure system more resilient. In this paper, the design of a monitoring system in mountainous environments is presented and analyzed in its parts. The method not only takes into account the peculiar climatic conditions, but it is integrated and interacts with the environment surrounding.

Keywords: structural health monitoring, resilience of bridges, mountain infrastructures, infrastructural network, maintenance

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Authors: Teklay Gebrecherkos, Mahmud Abdulkadir

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Abstract: The emergence and subsequent rapid worldwide spread of the COVID-19 pandemic have posed a global crisis, with a tremendously increasing burden of infection, morbidity, and mortality risks. Recent studies have suggested that severe cases of COVID-19 are characterized by massive biochemical, hematological, and inflammatory alterations whose synergistic effect is estimated to progress to multiple organ damage and failure. In this regard, biochemical monitoring of COVID-19 patients, based on comprehensive laboratory assessments and findings, is expected to play a crucial role in effective clinical management and improving the survival rates of patients. However, biochemical markers that can be informative of COVID-19 patient risk stratification and predictor of clinical outcomes are currently scarcely available. The study aims to investigate the profiles of common biochemical markers and their influence on the severity of the COVID-19 infection in Tigray, Ethiopia. Methods: A laboratory-based cross-sectional study was conducted from July to August 2020 at Quiha College of Engineering, Mekelle University COVID-19 isolation and treatment center. Sociodemographic and clinical data were collected using a structured questionnaire. Whole blood was collected from each study participant, and serum samples were separated after being delivered to the laboratory. Hematological biomarkers were analyzed using FACS count, while organ tests and serum electrolytes were analyzed using ion-selective electrode methods using a Cobas-6000 series machine. Data was analyzed using SPSS Vs 20. Results: A total of 120 SARS-CoV-2 patients were enrolled during the study. The participants ranged between 18 and 91 years, with a mean age of 52 (±108.8). The majority (40%) of participants were between the ages of 60 and above. Patients with multiple comorbidities developed severe COVID-19, though not statistically significant (p=0.34). Mann-Whitney U test analysis showed that biochemical tests such as neuropile count (p=0.003), AST levels (p=0.050), serum creatinine (p=0.000), and serum sodium (p=0.015) were significantly correlated with severe COVID-19 disease as compared to non-severe disease. Conclusion: The severity of COVID-19 was associated with higher age, organ tests AST and creatinine, serum Na+, and elevated total neutrophile count. Thus, further study needs to be conducted to evaluate the alterations of biochemical biomarkers and their impact on COVID-19.

Keywords: COVID-19, biomarkers, mortality, Tigray, Ethiopia

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Authors: Aoxue Yang, Weili Tian, Yonghe Wu, Haikun Liu

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Brain tumor stem cells (BTSCs) are resistant to therapy and give rise to recurrent tumors. These rare and elusive cells are likely to disseminate during cancer progression, and some may enter dormancy, remaining viable but not increasing. The identification of dormant BTSCs is thus necessary to design effective therapies for glioblastoma (GBM) patients. Little progress has been made in therapeutic treatment of glioblastoma in the last decade despite rapid progress in molecular understanding of brain tumors1. Here we show that the stress hormone glucocorticoid is essential for the maintenance of brain tumor stem cells (BTSCs), which are resistant to conventional therapy. The glucocorticoid receptor (GR) regulates metabolic plasticity and chemoresistance of the dormant BTSC via controlling expression of GPD1 (glycerol-3-phosphate dehydrogenase 1), which is an essential regulator of lipid metabolism in BTSCs. Genomic, lipidomic and cellular analysis confirm that GR/GPD1 regulation is essential for BTSCs metabolic plasticity and survival. We further demonstrate that the GR agonist dexamethasone (DEXA), which is commonly used to control edema in glioblastoma, abolishes the effect of chemotherapy drug temozolomide (TMZ) by upregulating GPD1 and thus promoting tumor cell dormancy in vivo, this provides a mechanistic explanation and thus settle the long-standing debate of usage of steroid in brain tumor patient edema control. Pharmacological inhibition of GR/GPD1 pathway disrupts metabolic plasticity of BTSCs and prolong animal survival, which is superior to standard chemotherapy. Patient case study shows that GR antagonist mifepristone blocks tumor progression and leads to symptomatic improvement. This study identifies an important mechanism regulating cancer stem cell dormancy and provides a new opportunity for glioblastoma treatment.

Keywords: cancer stem cell, dormancy, glioblastoma, glycerol-3-phosphate dehydrogenase 1, glucocorticoid receptor, dexamethasone, RNA-sequencing, phosphoglycerides.

Procedia PDF Downloads 80

Authors: Boris Kolev, Matt Kokan, Mohammad Deriszadeh, Farshid Bateni

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Due to the increasing demand for real estate and the need for efficient land utilization in Greater Vancouver, developers have been increasingly considering the construction of high-rise structures with multiple below-grade parking. The temporary excavations required to allow for the construction of underground levels have recently reached up to 40 meters in depth. One of the challenges with deep excavations is the prediction of wall displacements and ground settlements due to their effect on the integrity of City utilities, infrastructure, and adjacent buildings. A large database of survey monitoring data has been collected for deep excavations in various soil conditions and shoring systems. The majority of the data collected is for tie-back anchors and shotcrete lagging systems. The data were categorized, analyzed and the results were evaluated to find a relationship between the most dominant parameters controlling the displacement, such as depth of excavation, soil properties, and the tie-back anchor loading and arrangement. For a select number of deep excavations, finite element modeling was considered for analyses. The lateral displacements from the simulation results were compared to the recorded survey monitoring data. The study concludes with a discussion and comparison of the available empirical and numerical modeling methodologies for evaluating lateral displacements in deep excavations.

Keywords: deep excavations, lateral displacements, numerical modeling, shoring walls, tieback anchors

Procedia PDF Downloads 179

Authors: Yuli Hou, Jianping Sun, Mengdan Gao, Hui Liu, Ling Qin, Ang Li, Dongfu Li, Yonghong Zhang, Yan Zhao

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Background and Aims: Interferon-induced transmembrane protein 3 (IFITM3) is a component of ISG (Interferon-Stimulated Gene) family. IFITM3 has been recognized as a key signal molecule regulating cell growth in some tumors. However, the function of IFITM3 rs12252-CC genotype in the hepatocellular carcinoma (HCC) remains unknown to author’s best knowledge. A cohort study was employed to clarify the relationship between IFITM3 rs12252-CC genotype and HCC progression, and cellular experiments were used to investigate the correlation of function of IFITM3 and the progress of HCC. Methods: 336 candidates were enrolled in study, including 156 with HBV related HCC and 180 with chronic Hepatitis B infections or liver cirrhosis. Polymerase chain reaction (PCR) was employed to determine the gene polymorphism of IFITM3. The functions of IFITM3 were detected in PLC/PRF/5 cell with different treated:LV-IFITM3 transfected with lentivirus to knockdown the expression of IFITM3 and LV-NC transfected with empty lentivirus as negative control. The IFITM3 expression, proliferation and migration were detected by Quantitative reverse transcription polymerase chain reaction (qRT-PCR), QuantiGene Plex 2.0 assay, western blotting, immunohistochemistry, Cell Counting Kit(CCK)-8 and wound healing respectively. Six samples (three infected with empty lentiviral as control; three infected with LV-IFITM3 vector lentiviral as experimental group ) of PLC/PRF/5 were sequenced at BGI (Beijing Genomics Institute, Shenzhen,China) using RNA-seq technology to identify the IFITM3-related signaling pathways and chose PI3K/AKT pathway as related signaling to verify. Results: The patients with HCC had a significantly higher proportion of IFITM3 rs12252-CC compared with the patients with chronic HBV infection or liver cirrhosis. The distribution of CC genotype in HCC patients with low differentiation was significantly higher than that in those with high differentiation. Patients with CC genotype found with bigger tumor size, higher percentage of vascular thrombosis, higher distribution of low differentiation and higher 5-year relapse rate than those with CT/TT genotypes. The expression of IFITM3 was higher in HCC tissues than adjacent normal tissues, and the level of IFITM3 was higher in HCC tissues with low differentiation and metastatic than high/medium differentiation and without metastatic. Higher RNA level of IFITM3 was found in CC genotype than TT genotype. In PLC/PRF/5 cell with knockdown, the ability of cell proliferation and migration was inhibited. Analysis RNA sequencing and verification of RT-PCR found out the phosphatidylinositol 3-kinase/protein kinase B/mammalian target of rapamycin(PI3K/AKT/mTOR) pathway was associated with knockdown IFITM3.With the inhibition of IFITM3, the expression of PI3K/AKT/mTOR signaling pathway was blocked and the expression of vimentin was decreased. Conclusions: IFITM3 rs12252-CC with the higher expression plays a vital role in the progress of HCC by regulating HCC cell proliferation and migration. These effects are associated with PI3K/AKT/mTOR signaling pathway.

Keywords: IFITM3, interferon-induced transmembrane protein 3, HCC, hepatocellular carcinoma, PI3K/ AKT/mTOR, phosphatidylinositol 3-kinase/protein kinase B/mammalian target of rapamycin

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Authors: Emmanuel O. Ezim, Idowu A. Olayinka, Michael Oladunjoye, Izuchukwu I. Obiadi

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Monitoring of reservoir properties prior to well placements and production is a requirement for optimisation and efficient oil and gas production. This is usually done using well log analyses and 3-D seismic, which are often prone to errors. However, 4-D (Time-lapse) seismic, incorporating numerous 3-D seismic surveys of the same field with the same acquisition parameters, which portrays the transient changes in the reservoir due to production effects over time, could be utilised because it generates better resolution. There is, however dearth of information on the applicability of this approach in the Niger Delta. This study was therefore designed to apply 4-D seismic, well-log and geologic data in monitoring of reservoirs in the EK field of the Niger Delta. It aimed at locating bypassed accumulations and ensuring effective reservoir management. The Field (EK) covers an area of about 1200km2 belonging to the early (18ma) Miocene. Data covering two 4-D vintages acquired over a fifteen-year interval were obtained from oil companies operating in the field. The data were analysed to determine the seismic structures, horizons, Well-to-Seismic Tie (WST), and wavelets. Well, logs and production history data from fifteen selected wells were also collected from the Oil companies. Formation evaluation, petrophysical analysis and inversion alongside geological data were undertaken using Petrel, Shell-nDi, Techlog and Jason Software. Well-to-seismic tie, formation evaluation and saturation monitoring using petrophysical and geological data and software were used to find bypassed hydrocarbon prospects. The seismic vintages were interpreted, and the amounts of change in the reservoir were defined by the differences in Acoustic Impedance (AI) inversions of the base and the monitor seismic. AI rock properties were estimated from all the seismic amplitudes using controlled sparse-spike inversion. The estimated rock properties were used to produce AI maps. The structural analysis showed the dominance of NW-SE trending rollover collapsed-crest anticlines in EK with hydrocarbons trapped northwards. There were good ties in wells EK 27, 39. Analysed wavelets revealed consistent amplitude and phase for the WST; hence, a good match between the inverted impedance and the good data. Evidence of large pay thickness, ranging from 2875ms (11420 TVDSS-ft) to about 2965ms, were found around EK 39 well with good yield properties. The comparison between the base of the AI and the current monitor and the generated AI maps revealed zones of untapped hydrocarbons as well as assisted in determining fluids movement. The inverted sections through EK 27, 39 (within 3101 m - 3695 m), indicated depletion in the reservoirs. The extent of the present non-uniform gas-oil contact and oil-water contact movements were from 3554 to 3575 m. The 4-D seismic approach led to better reservoir characterization, well development and the location of deeper and bypassed hydrocarbon reservoirs.

Keywords: reservoir monitoring, 4-D seismic, well placements, petrophysical analysis, Niger delta basin

Procedia PDF Downloads 113

Authors: Kyu Jin Kim, Byung Kwan Oh, Hyo Seon Park

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The seismic responses-based structural health monitoring system has been performed to reduce seismic damage. The inter-story drift ratio which is the major index of the seismic capacity assessment is employed for estimating the seismic damage of buildings. Meanwhile, seismic response analysis to estimate the structural responses of building demands significantly high computational cost due to increasing number of high-rise and large buildings. To estimate the inter-story drift ratio of buildings from the earthquake efficiently, this paper suggests the estimation method of inter-story drift for buildings using an artificial neural network (ANN). In the method, the radial basis function neural network (RBFNN) is integrated with optimization algorithm to optimize the variable through evolutionary learning that refers to evolutionary radial basis function neural network (ERBFNN). The estimation method estimates the inter-story drift without seismic response analysis when the new earthquakes are subjected to buildings. The effectiveness of the estimation method is verified through a simulation using multi-degree of freedom system.

Keywords: structural health monitoring, inter-story drift ratio, artificial neural network, radial basis function neural network, genetic algorithm

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Authors: Branislav Timotijevic, Yves Petremand, Markus Luetzelschwab, Dara Bayat, Laurent Aebi

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Optical miniaturized sensors with remote readout are required devices for the monitoring in harsh electromagnetic environments. As an example, in turbo and hydro generators, excessively high vibrations of the end-windings can lead to dramatic damages, imposing very high, additional service costs. A significant change of the generator temperature can also be an indicator of the system failure. Continuous monitoring of vibrations, temperature, humidity, and gases is therefore mandatory. The high electromagnetic fields in the generators impose the use of non-conductive devices in order to prevent electromagnetic interferences and to electrically isolate the sensing element to the electronic readout. Metal-free sensors are good candidates for such systems since they are immune to very strong electromagnetic fields and given the fact that they are non-conductive. We have realized miniature optical accelerometer and temperature sensors for a remote sensing of the harsh environments using the common, inexpensive silicon Micro Electro-Mechanical System (MEMS) platform. Both devices show highly linear response. The accelerometer has a deviation within 1% from the linear fit when tested in a range 0 – 40 g. The temperature sensor can provide the measurement accuracy better than 1 °C in a range 20 – 150 °C. The design of other type of sensors for the environments with high electromagnetic interferences has also been discussed.

Keywords: optical MEMS, temperature sensor, accelerometer, remote sensing, harsh environment

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Authors: Pranav Mohan Parki, C. Mallika Parveen, Tahseen Ahmad Khan, Mihika Shivkumar

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Additive manufacturing (AM) is one of the several manufacturing processes in use today. AM comprises of techniques such as ‘Selective Laser Sintering’ and ‘Selective Laser Melting’ etc. along with other equipment and materials has been developed way back in 1980s, although major use of these methods has risen during the last decade. AM seems to be the most efficient way when compared to the traditional machining procedures. Still many problems continue to hinder its progress to becoming the most widely used of all. This paper contributes to the better understanding of AM and also aims at providing viable solutions to these problems, which may further help in enabling AM to become the most flaw free production method.

Keywords: additive manufacturing (AM), 3D printing, prototype, laser sintering

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Authors: Yamamah Abdulrazaq, Lahieb A. Abrahim, Samuel E. Davies, Iain Shewring

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An electric water heater (EWH) is a powerful appliance that uses electricity in residential, commercial, and industrial settings, and the ability to control them properly will result in cost savings and the prevention of blackouts on the national grid. This article discusses the usage of timers in EWH control strategies for demand-side management (DSM). Up to the authors' knowledge, there is no systematic mapping review focusing on the utilisation of EWH control strategies in DSM has yet been conducted. Consequently, the purpose of this research is to identify and examine main papers exploring EWH procedures in DSM by quantifying and categorising information with regard to publication year and source, kind of methods, and source of data for monitoring control techniques. In order to answer the research questions, a total of 31 publications published between 1999 and 2023 were selected depending on specific inclusion and exclusion criteria. The data indicate that direct load control (DLC) has been somewhat more prevalent than indirect load control (ILC). Additionally, the mixing method is much lower than the other techniques, and the proportion of Real-time data (RTD) to non-real-time data (NRTD) is about equal.

Keywords: demand side management, direct load control, electric water heater, indirect load control, non real-time data, real-time data

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Authors: Yude Wu

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Mongolia, grappling with significant socio-economic challenges, faces pressing issues of inequality and poverty, as evidenced by a high Gini coefficient and the highest poverty rate among the top 20 largest Asian countries. Despite government efforts, Mongolia's poverty rate experienced only a slight reduction from 29.6 percent in 2016 to 27.8 percent in 2020. PEER countries, such as South Africa, Botswana, Kazakhstan, and Peru, share characteristics with Mongolia, including reliance on the mining industry and classification as lower middle-income countries. Successful transitions of these countries to upper middle-income status between 1994 and the 2010s provide valuable insights. Drawing on secondary analyses of existing research and PEER country profiles, the study evaluates past policies, identifies gaps in current approaches, and proposes recommendations to combat poverty sustainably. The hypothesis includes a reliance on the mining industry and a transition from lower to upper middle-income status. Policies from these countries, such as the GEAR policy in South Africa and economic diversification in Botswana, offer insights into Mongolia's development. This essay aims to illuminate the multidimensional nature of underdevelopment in Mongolia through a secondary analysis of existing research and PEER country profiles, evaluating past policies, identifying gaps in current approaches, and providing recommendations for sustainable progress. Drawing inspiration from PEER countries, Mongolia can implement policies such as economic diversification to reduce vulnerability and create stable job opportunities. Emphasis on infrastructure, human capital, and strategic partnerships for Foreign Direct Investment (FDI) aligns with successful strategies implemented by PEER countries, providing a roadmap for Mongolia's development objectives.

Keywords: inequality, PEER countries, comparative analysis, nomadic animal husbandry, sustainable growth

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Authors: Judith Mwakalonge, Geophrey Mbatta, Saidi Siuhi, Gurcan Comert, Cuthbert Ruseruka

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Transportation agencies worldwide continuously monitor their roads' conditions to minimize road maintenance costs and maintain public safety and rideability quality. Existing methods for carrying out road condition surveys involve manual observations of roads using standard survey forms done by qualified road condition surveyors or engineers either on foot or by vehicle. Automated road condition survey vehicles exist; however, they are very expensive since they require special vehicles equipped with sensors for data collection together with data processing and computing devices. The manual methods are expensive, time-consuming, infrequent, and can hardly provide real-time information for road conditions. This study contributes to this arena by utilizing built-in vehicle technologies, drones, and deep learning to automate road condition surveys while using low-cost technology. A single model is trained to capture flexible pavement distresses (Potholes, Rutting, Cracking, and raveling), thereby providing a more cost-effective and efficient road condition monitoring approach that can also provide real-time road conditions. Additionally, data fusion is employed to enhance the road condition assessment with data from vehicles and drones.

Keywords: road conditions, built-in vehicle technology, deep learning, drones

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Authors: Chen-Ya Juan

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Problem-Based Learning uses vague questions to guide student thinking and enhance their self-learning and collaboration. Most teachers implement PBL in a physical classroom, where teachers can monitor and evaluate students’ learning progress and guide them to search resources for answers. However, the prevalence of the Covid-19 in the world had changed from physical teaching to distance teaching. This instruction used many cases and applied Problem-Based Learning combined on the distance teaching via the internet for college students. This study involved an experimental group with PBL and a control group without PBL. The teacher divided all students in PBL class into eight groups, and 7~8 students in each group. The teacher assigned different cases for each group of the PBL class. Three stages of instruction were developed, including background knowledge of Learning, case analysis, and solving problems for each case. This study used a quantitative research method, a two-sample t-test, to find a significant difference in groups with PBL and without PBL. Findings indicated that PBL incased the average score of special education knowledge. The average score was improved by 20.46% in the PBL group and 15.4% without PBL. Results didn’t show significant differences (0.589>0.05) in special education professional knowledge. However, the feedback of the PBL students implied learning more about the application, problem-solving skills, and critical thinking. PBL students were more likely to apply professional knowledge on the actual case, find questions, resources, and answers. Most of them understood the importance of collaboration, working as a team, and communicating with other team members. The suggestions of this study included that (a) different web-based teaching instruments influenced student’s Learning; (b) it is difficult to monitor online PBL progress; (c) online PBL should be implemented flexible and multi-oriented; (d) although PBL did not show a significant difference on the group with PBL and without PBL, it did increase student’s problem-solving skills and critical thinking.

Keywords: problem-based learning, college students, distance learning, case analysis, problem-solving

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Authors: Kirill Filianin, Satu-Pia Reinikainen, Tuomo Sainio

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Frequent measurements of product steam quality create a data overload that becomes more and more difficult to handle. In the current study, plant history data with multiple variables was successfully treated by principal component analysis to detect abnormal process behavior, particularly, in copper solvent extraction. The multivariate model is based on the concentration levels of main process metals recorded by the industrial on-stream x-ray fluorescence analyzer. After mean-centering and normalization of concentration data set, two-dimensional multivariate model under principal component analysis algorithm was constructed. Normal operating conditions were defined through control limits that were assigned to squared score values on x-axis and to residual values on y-axis. 80 percent of the data set were taken as the training set and the multivariate model was tested with the remaining 20 percent of data. Model testing showed successful application of control limits to detect abnormal behavior of copper solvent extraction process as early warnings. Compared to the conventional techniques of analyzing one variable at a time, the proposed model allows to detect on-line a process failure using information from all process variables simultaneously. Complex industrial equipment combined with advanced mathematical tools may be used for on-line monitoring both of process streams’ composition and final product quality. Defining normal operating conditions of the process supports reliable decision making in a process control room. Thus, industrial x-ray fluorescence analyzers equipped with integrated data processing toolbox allows more flexibility in copper plant operation. The additional multivariate process control and monitoring procedures are recommended to apply separately for the major components and for the impurities. Principal component analysis may be utilized not only in control of major elements’ content in process streams, but also for continuous monitoring of plant feed. The proposed approach has a potential in on-line instrumentation providing fast, robust and cheap application with automation abilities.

Keywords: abnormal process behavior, failure detection, principal component analysis, solvent extraction

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Authors: R. Farhoud, G. Hermand, S. Delepine-lesoille

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Future underground facility of French radioactive waste disposal, named Cigeo, is designed to store intermediate and high level - long-lived French radioactive waste. Intermediate level waste cells are tunnel-like, about 400m length and 65 m² section, equipped with several concrete layers, which can be grouted in situ or composed of tunnel elements pre-grouted. The operating space into cells, to allow putting or removing waste containers, should be monitored for several decades without any maintenance. To provide the required information, design was performed and tested in situ in Andra’s underground laboratory (URL) at 500m under the surface. Based on distributed optic fiber sensors (OFS) and backscattered Brillouin for strain and Raman for temperature interrogation technics, the design consists of 2 loops of OFS, at 2 different radiuses, around the monitored section (Orthoradiale strains) and longitudinally. Strains measured by distributed OFS cables were compared to classical vibrating wire extensometers (VWE) and platinum probes (Pt). The OFS cables were composed of 2 cables sensitive to strains and temperatures and one only for temperatures. All cables were connected, between sensitive part and instruments, to hybrid cables to reduce cost. The connection has been made according to 2 technics: splicing fibers in situ after installation or preparing each fiber with a connector and only plugging them together in situ. Another challenge was installing OFS cables along a tunnel mad in several parts, without interruption along several parts. First success consists of the survival rate of sensors after installation and quality of measurements. Indeed, 100% of OFS cables, intended for long-term monitoring, survived installation. Few new configurations were tested with relative success. Measurements obtained were very promising. Indeed, after 3 years of data, no difference was observed between cables and connection methods of OFS and strains fit well with VWE and Pt placed at the same location. Data, from Brillouin instrument sensitive to strains and temperatures, were compensated with data provided by Raman instrument only sensitive to temperature and into a separated fiber. These results provide confidence in the next steps of the qualification processes which consists of testing several data treatment approach for direct analyses.

Keywords: monitoring, fiber optic, sensor, data treatment

Procedia PDF Downloads 124

Authors: Ibrahim Tiryakioglu, Mehmet Ali Ugur, Caglar Ozkaymak

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The development of GNSS technology has led to increasingly widespread and successful applications of GNSS surveys for monitoring crustal movements. However, multi-period GPS survey solutions have not been applied in monitoring vertical surface deformation. This study uses long-term GNSS time series that are required to determine vertical deformations. In recent years, the surface deformations that are parallel and semi-parallel to Bolvadin fault have occurred in Western Anatolia. These surface deformations have continued to occur in Bolvadin settlement area that is located mostly on alluvium ground. Due to these surface deformations, a number of cracks in the buildings located in the residential areas and breaks in underground water and sewage systems have been observed. In order to determine the amount of vertical surface deformations, two continuous GNSS stations have been established in the region. The stations have been operating since 2015 and 2017, respectively. In this study, GNSS observations from the mentioned two GNSS stations were processed with GAMIT/GLOBK (GNSS Analysis Massachusetts Institute of Technology/GLOBal Kalman) program package to create a coordinate time series. With the time series analyses, the GNSS stations’ behavior models (linear, periodical, etc.), the causes of these behaviors, and mathematical models were determined. The study results from the time series analysis of these two 2 GNSS stations shows approximately 50-80 mm/yr vertical movement.

Keywords: Bolvadin fault, GAMIT, GNSS time series, surface deformations

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Authors: Ahmed Ait Hou

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The wing leading edge and nose cone of the space shuttle are fabricated from a reinforced carbon/carbon material. This material attains its durability from a diffusion coating of silicon carbide (SiC) and a glass sealant. During re-entry into the atmosphere, this material is subject to an oxidizing high-temperature environment. The use of thermochemical calculations resulting at the HSC CHEMISTRY software and its database allows us to interpret the phenomena of oxidation and chloridation observed on the wing leading edge and nose cone of the space shuttle during its mission in space. First study is the monitoring of the oxidation reaction of SiC. It has been demonstrated that thermal oxidation of the SiC gives the two compounds SiO₂(s) and CO(g). In the extreme conditions of very low oxygen partial pressures and high temperatures, there is a reaction between SiC and SiO₂, leading to SiO(g) and CO(g). We had represented the phase stability diagram of Si-C-O system calculated by the use of the HSC Chemistry at 1300°C. The principal characteristic of this diagram of predominance is the line of SiC + SiO₂ coexistence. Second study is the monitoring of the chloridation reaction of SiC. The other problem encountered in addition to oxidation is the phenomenon of chloridation due to the presence of NaCl. Indeed, after many missions, the leading edge wing surfaces have exhibited small pinholes. We have used the HSC Chemistry database to analyze these various reactions. Our calculations concorde with the phenomena we announced in research work resulting in NASA LEWIS Research center.

Keywords: thermochchemicals calculations, HSC software, oxidation and chloridation, wings in space

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Authors: Gurjeet Singh, Rabindra K. Panda

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Soil moisture is a key hydrologic state variable and is intrinsically linked to the Earth's water, climate and carbon cycles. On ecological point of view, the soil moisture is a fundamental natural resource providing the transpirable water for plants. Soil moisture varies both temporally and spatially due to spatiotemporal variation in rainfall, vegetation cover, soil properties and topography. Satellite derived soil moisture provides spatio-temporal extensive data. However, the spatial resolution of a typical satellite (L-band radiometry) is of the order of tens of kilometers, which is not good enough for developing efficient agricultural water management schemes at the field scale. In the present study, the soil moisture from radiometer data has been disaggregated using blending approach to achieve higher resolution soil moisture data. The radiometer estimates of soil moisture at a 40 km resolution have been disaggregated to 10 km, 5 km and 1 km resolutions. The disaggregated soil moisture was compared with the observed data, consisting of continuous sensor based soil moisture profile measurements, at three monitoring sites and extensive spatial near-surface soil moisture measurements, concurrent with satellite monitoring in the 500 km2 study watershed in the Eastern India. The estimated soil moisture status at different spatial scales can help in developing efficient agricultural water management schemes to increase the crop production and water use efficiency.

Keywords: disaggregation, eastern India, radiometers, soil moisture, water use efficiency

Procedia PDF Downloads 273