Search results for: lattice parameters

Authors: Ratnakumar V. Kappagantula, Gordon D. Ingram, Hari B. Vuthaluru

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This paper analyzes a three reactor chemical looping process for hydrogen production from natural gas, allowing for carbon dioxide capture through chemical looping technology. An oxygen carrier is circulated to separate carbon dioxide, to reduce steam for hydrogen production and to supply oxygen for combustion. In this study, the emphasis is placed on the steam conversion in the steam reactor by investigating the hydrogen efficiencies of the complete system at steam conversions of 15.8% and 50%. An Aspen Plus model was developed for a Three Reactor Chemical Looping process to study the effects of operational parameters on hydrogen production is investigated. Maximum hydrogen production was observed under stoichiometric conditions. Different conversions in the steam reactor, which was modelled as a Gibbs reactor, were found when Gibbs-identified products and user identified products were chosen. Simulations were performed for different oxygen carriers, which consist of an active metal oxide on an inert support material. For the same metal oxide mass flowrate, the fuel reactor temperature decreased for different support materials in the order: aluminum oxide (Al2O3) > magnesium aluminate (MgAl2O4) > zirconia (ZrO2). To achieve the same fuel reactor temperature for the same oxide mass flow rate, the inert mass fraction was found to be 0.825 for ZrO2, 0.7 for MgAl2O4 and 0.6 for Al2O3. The effect of poisoning of the oxygen carrier was also analyzed. With 3000 ppm sulfur-based impurities in the feed gas, the hydrogen product energy rate of the process were found to decrease by 0.4%.

Keywords: aspen plus, chemical looping combustion, inert support balls, oxygen carrier

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Authors: F. Clara Fang, Hernan Castaneda

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The Connecticut Department of Transportation (ConnDOT) has constructed four roundabouts in the State of Connecticut within the past ten years. VISSIM traffic simulation software was utilized to analyze these roundabouts during their design phase. The queue length and level of service observed in the field appear to be better than predicted by the VISSIM model. The objectives of this project are to: identify VISSIM input variables most critical to accurate modeling; recommend VISSIM calibration factors; and, provide other recommendations for roundabout traffic operations modeling. Traffic data were collected at these roundabouts using Miovision Technologies. Cameras were set up to capture vehicle circulating activity and entry behavior for two weekdays. A large sample size of filed data was analyzed to achieve accurate and statistically significant results. The data extracted from the videos include: vehicle circulating speed; critical gap estimated by Maximum Likelihood Method; peak hour volume; follow-up headway; travel time; and, vehicle queue length. A VISSIM simulation of existing roundabouts was built to compare both queue length and travel time predicted from simulation with measured in the field. The research investigated a variety of simulation parameters as calibration factors for describing driver behaviors at roundabouts. Among them, critical gap is the most effective calibration variable in roundabout simulation. It has a significant impact to queue length, particularly when the volume is higher. The results will improve the design of future roundabouts in Connecticut and provide decision makers with insights on the relationship between various choices and future performance.

Keywords: driver critical gap, roundabout analysis, simulation, VISSIM modeling

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Authors: Santosh Kumar Yadav, Shobha Keswani, Nishat Quddus, Sohrab Ahmad Khan, Zuheb Ahmad Shiddiqui, Varsha Chorsiya

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Introduction: Early onset diabetes is more aggressive than the late onset diabetes. Diabetic individual has a greater spectrum of life period to suffer from its damage, complications, and long-term disability. This study aimed at assessing knee joint muscle performance under various durations of diabetes. Method and Materials: A total of 30 diabetic subjects (18 male and 12 females) without diabetic neuropathy were included for the study. They were divided into three groups with 5 years, 10 years and 15 years of duration of disease each. Muscle performance was evaluated through strength and flexibility. Peak torque for quadriceps muscle was measured using isokinetic dynamometer. Flexibility for quadriceps and hamstring muscles were measured through Ducan’s Elys test and 90/90 test. Results: The result showed significant difference in muscle strength (p<0.05), flexibility (p≤0.05) between groups. Discussion: Optimal muscle strength and flexibility are vital for musculoskeletal health and functional independence. Conclusion: The reduced muscle performance and functional impairment in nonneuropathic diabetic patients suggest that other mechanism besides neuropathy that contribute to altered biomechanics. These findings of this study project early management of these altered parameters through disease-specific physical therapy and assessment-based intervention. Clinical Relevance: Managing disability is more costly than managing disease. Prompt and timely identification and management strategy can dramatically reduce the cost of care for diabetic patients.

Keywords: muscle flexibility, muscle performance, muscle torque, type 2 diabetes

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Authors: Mediha B. Sılaydın Aydın, Emine D. Kahraman

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One of the important impacts of climate change is the sea level rise. Turkey is a peninsula, so the coastal areas of the country are threatened by the problem of sea level rise. Therefore, the urbanized coastal areas are highly vulnerable to climate change. At the aim of enhancing spatial resilience of urbanized areas, this question arises: What should be the priority intervention subject in the urban planning process for a given city. To answer this question, by focusing on the problem of sea level rise, this study aims to determine spatial vulnerability typologies and levels of Turkey coastal cities based on morphological, physical and social characteristics. As a method, spatial vulnerability of coastal cities is determined by two steps as level and type. Firstly, physical structure, morphological structure and social structure were examined in determining spatial vulnerability levels. By determining these levels, most vulnerable areas were revealed as a priority in adaptation studies. Secondly, all parameters are also used to determine spatial typologies. Typologies are determined for coastal cities in order to use as a base for urban planning studies. Adaptation to climate change is crucial for developing countries like Turkey so, this methodology and created typologies could be a guide for urban planners as spatial directors and an example for other developing countries in the context of adaptation to climate change. The results demonstrate that the urban settlements located on the coasts of the Marmara Sea, the Aegean Sea and the Mediterranean respectively, are more vulnerable than the cities located on the Black Sea’s coasts to sea level rise.

Keywords: climate change, coastal cities, vulnerability, urban land use planning

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Authors: Brindha Senthil Kumar, Payel Chakraborty, Senthil Kumar Nachimuthu, Arindam Maitra, Prem Nath

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Gastric cancer is predominantly caused by demographic and diet factors as compared to other cancer types. The aim of the study is to predict Early Gastric Cancer (ECG) from diet and lifestyle factors using supervised machine learning algorithms. For this study, 160 healthy individual and 80 cases were selected who had been followed for 3 years (2016-2019), at Civil Hospital, Aizawl, Mizoram. A dataset containing 11 features that are core risk factors for the gastric cancer were extracted. Supervised machine algorithms: Logistic Regression, Naive Bayes, Support Vector Machine (SVM), Multilayer perceptron, and Random Forest were used to analyze the dataset using Python Jupyter Notebook Version 3. The obtained classified results had been evaluated using metrics parameters: minimum_false_positives, brier_score, accuracy, precision, recall, F1_score, and Receiver Operating Characteristics (ROC) curve. Data analysis results showed Naive Bayes - 88, 0.11; Random Forest - 83, 0.16; SVM - 77, 0.22; Logistic Regression - 75, 0.25 and Multilayer perceptron - 72, 0.27 with respect to accuracy and brier_score in percent. Naive Bayes algorithm out performs with very low false positive rates as well as brier_score and good accuracy. Naive Bayes algorithm classification results in predicting ECG showed very satisfactory results using only diet cum lifestyle factors which will be very helpful for the physicians to educate the patients and public, thereby mortality of gastric cancer can be reduced/avoided with this knowledge mining work.

Keywords: Early Gastric cancer, Machine Learning, Diet, Lifestyle Characteristics

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Authors: Abeer Hashem, Khalid F. Almutairi, Ulkar Ibrahimova, Elsayed Fathi Abdallah

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Salinity poses a significant challenge to wheat production, necessitating the exploration of strategies to mitigate its adverse effects. The present investigation aims to study the impact of arbuscular mycorrhizal fungi (AMF) application to improve plant tolerance in terms of growth, carbohydrate, photosynthetic characteristics, and antioxidant enzyme activities under salt stress conditions. So, a randomized complete block design with five replications was employed comprising various treatments of AMF application under salinity stress (200mM), and control samples were used for each treatment. The obtained results demonstrated significantly that AMF used in this study showed beneficial impacts in all parameters used as sensitive monitor for relation of plant-salt microbe interaction. The root colonization by AMF showed the highest plant growth criteria, relative water content, soluble sugar, starch, and total non-structural carbohydrates under both control and salinity stress conditions. Moreover, the application of AMF-treated plants showed the highest soluble protein concentration and activity in leaves and antioxidant enzymes (catalase, superoxide dismutase, guaiacol peroxidase). These findings highlight the potential impact of AMF application as a biologically based strategy to manage the mitigation of salt stress on wheat, which increases the availability of many salt marsh habitats for sustainable agriculture of such strategy crops.

Keywords: arbuscular mycorrhizal fungi, salt stress, plant growth criteria, soluble protein, antioxidant enzymes, wheat plant

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Authors: Buchh Aqsa, Inayat Umar

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Background- Clonidine, α 2 agonist, possesses several properties to make it valuable adjuvant for spinal anesthesia. The study was aimed to evaluate the clinical effects of oral clonidine premedication for laparoscopic gynecological procedures under subarachnoid block. Patients and method- Sixtyfour adult female patients of ASA physical status I and II, aged 25 to 45 years and scheduled for laparoscopic gynecological procedures under the subarachnoid block, were randomized into two comparable equal groups of 32 patients each to received either oral clonidine, 100 µg (Group I) or placebo (Group II), 90 minutes before the procedure. Subarachnoid block was established with of 3.5 ml of 0.5% hyperbaric bupivacaine in all patients. Onset and duration of sensory and motor block, maximum cephalad level, and the regression time to reach S1 sensory level were assessed as primary end points. Sedation, hemodynamic variability, and respiratory depression or any other side effects were evaluated as secondary outcomes. Results- The demographic profile was comparable. The intraoperative hemodynamic parameters showed significant differences between groups. Oral clonidine was accelerated the onset time of sensory and motor blockade and extended the duration of sensory block (216.4 ± 23.3 min versus 165 ± 37.2 min, P <0.05). The duration of motor block showed no significant difference. The sedation score was more than 2 in the clonidine group as compared to the control group. Conclusion- Oral clonidine premedication has extended the duration of sensory analgesia with arousable sedation. It also prevented the post spinal shivering of the subarachnoid block.

Keywords: oral clonidine, subarachnoid block, sensory analgesia, laparoscopic gynaecological

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Authors: Soufiane Fal, Abderahim Aasfar, Ali Ouhssain, Hasnae Choukri, Abelaziz Smouni, Hicham El Arroussi

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Heavy metals contamination is a major environmental concern around the world. It has a harmful impact on plant productivity and poses a serious risk to humans and animals health. In the present study, the effect of Microalgae Crude Extract (MCE) on tomato growth and nutrients uptake exposed to 2 mM Pb2+ and Cd2+ was investigated. In results, 2 mM Pb2+ and Cd2+ showed a significant reduction of tomatobiomass and perturbation in nutrients absorption. Moreover, MCE application in tomato plant exposed to Pb2+ and Cd2+ showed a significant enhancement of biomass compared to tomato plants under Pb2+ and Cd2+. On the other hand, MCE application favoured heavy metals accumulation in root and inhibited their translocation to shoot as phytostabilisation mechanism. Tomato plants showed biochemical responses to Pb2+ and Cd2+ stress with elevation of scavenging enzymes and molecules such as POD, CAT, SOD, Proline, and polyphenols, etc. In addition, the treatment by MCE showed a significant reduction level of the majority of these parameters. Furthermore, the metabolomic analysis revealed a significant change in important metabolites. Pb2+ and Cd2+ showed decrease in SFA and increase of UFA, VLFA, alkanes, alkenes, sterols, which known accumulated as tolerance and resistance mechanism to heavy metal (H.M) stress. However, MCE treatment showed the inverse of these response to return tomato plants to normal state and enhanced tolerance and resistance to heavy metal stress. In the present study, we emphasized that MCE can alleviate H.M stress, enhance tomato plant growth nutrients absorption and improve biochemical responses.

Keywords: microalgae crude extract, heavy metal stress, nutrient uptake, metabolomic analysis, solanum lycopersicum (Tomato), phytostabilisation

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Authors: Morlu Stevens, Bareki Batlokwa

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The use of treated wastewater is widely employed to compensate for the scarcity of safe and uncontaminated freshwater. However, the existence of toxic heavy metal ions in the wastewater pose a health hazard to animals and the environment, hence, the importance for an effective technique to tackle the challenge. A multi-templated ion imprinted sorbent (Fe,Ni,Cu-IIP) for the simultaneous removal of heavy metal ions from waste water was synthesised employing molecular imprinting technology (MIT) via thermal free radical bulk polymerization technique. Methacrylic acid (MAA) was employed as the functional monomer, and ethylene glycol dimethylacrylate (EGDMA) as cross-linking agent, azobisisobutyronitrile (AIBN) as the initiator, Fe, Ni, Cu ions as template ions, and 1,10-phenanthroline as the complexing agent. The template ions were exhaustively washed off the synthesized polymer by solvent extraction in several washing steps, while periodically increasing solvent (HCl) concentration from 1.0 M to 10.0 M. The physical and chemical properties of the sorbents were investigated using Fourier Transform Infrared Spectroscopy (FT-IR), X-ray Diffraction (XRD) and Atomic Force Microscopy (AFM) were employed. Optimization of operational parameters such as time, pH and sorbent dosage to evaluate the effectiveness of sorbents were investigated and found to be 15 min, 7.5 and 666.7 mg/L respectively. Selectivity of ion-imprinted polymers and competitive sorption studies between the template and similar ions were carried out and showed good selectivity towards the targeted metal ion by removing 90% - 98% of the templated ions as compared to 58% - 62% of similar ions. The sorbents were further applied for the selective removal of Fe, Ni and Cu from real wastewater samples and recoveries of 92.14 ± 0.16% - 106.09 ± 0.17% and linearities of R2 = 0.9993 - R2 = 0.9997 were achieved.

Keywords: ion imprinting, ion imprinted polymers, heavy metals, wastewater

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Authors: Nedal N. Marei, Nashaat Nassar

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Many treatment techniques have been used to remove the soluble pollutants from wastewater as; dyes and metal ions which could be found in rich amount in the used water of the textile and tanneries industry. The effluents from these industries are complex, containing a wide variety of dyes and other contaminants, such as dispersants, acids, bases, salts, detergents, humectants, oxidants, and others. These techniques can be divided into physical, chemical, and biological methods. Adsorption has been developed as an efficient method for the removal of heavy metals from contaminated water and soil. It is now recognized as an effective method for the removal of both organic and inorganic pollutants from wastewaters. Nanosize materials are new functional materials, which offer high surface area and have come up as effective adsorbents. Nano alumina is one of the most important ceramic materials widely used as an electrical insulator, presenting exceptionally high resistance to chemical agents, as well as giving excellent performance as a catalyst for many chemical reactions, in microelectronic, membrane applications, and water and wastewater treatment. In this study, methylene blue (MB) dye has been used as model dye of textile wastewater in order to synthesize a synthetic MB wastewater. NiO nanoparticles were added in small percentage in the sand packed bed adsorption columns to remove the MB from the synthetic textile wastewater. Moreover, different parameters have been evaluated; flow of the synthetic wastewater, pH, height of the bed, percentage of the NiO to the sand in the packed material. Different mathematical models where employed to find the proper model which describe the experimental data and help to analyze the mechanism of the MB adsorption. This study will provide good understanding of the dyes adsorption using metal oxide nanoparticles in the classical sand bed.

Keywords: adsorption, column, nanoparticles, methylene

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Authors: Arjun G. Koppad

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The study was conducted in Joida taluk of Uttara Kannada district, Karnataka, India, to assess the land use land cover (LULC) and forest aboveground biomass using L band SAR data. The study area covered has dense, moderately dense, and sparse forests. The sampled area was 0.01 percent of the forest area with 30 sampling plots which were selected randomly. The point center quadrate (PCQ) method was used to select the tree and collected the tree growth parameters viz., tree height, diameter at breast height (DBH), and diameter at the tree base. The tree crown density was measured with a densitometer. Each sample plot biomass was estimated using the standard formula. In this study, the LULC classification was done using Freeman-Durden, Yamaghuchi and Pauli polarimetric decompositions. It was observed that the Freeman-Durden decomposition showed better LULC classification with an accuracy of 88 percent. An attempt was made to estimate the aboveground biomass using SAR backscatter. The ALOS-2 PALSAR-2 L-band data (HH, HV, VV &VH) fully polarimetric quad-pol SAR data was used. SAR backscatter-based regression model was implemented to retrieve forest aboveground biomass of the study area. Cross-polarization (HV) has shown a good correlation with forest above-ground biomass. The Multi Linear Regression analysis was done to estimate aboveground biomass of the natural forest areas of the Joida taluk. The different polarizations (HH &HV, VV &HH, HV & VH, VV&VH) combination of HH and HV polarization shows a good correlation with field and predicted biomass. The RMSE and value for HH & HV and HH & VV were 78 t/ha and 0.861, 81 t/ha and 0.853, respectively. Hence the model can be recommended for estimating AGB for the dense, moderately dense, and sparse forest.

Keywords: forest, biomass, LULC, back scatter, SAR, regression

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Authors: Mohamed Ahmed Fouad

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Background: Stroke is the most leading cause to functional disability and gait problems. Objectives: The purpose of this study was to determine the effect of rhythmic auditory stimulation combined with treadmill training on selected gait kinematics in stroke patients. Methods: Thirty male stroke patients participated in this study. The patients were assigned randomly into two equal groups, (study and control). Patients in the study group received treadmill training combined with rhythmic auditory stimulation in addition to selected physical therapy program for hemiparetic patients. Patients in the control group received treadmill training in addition to the same selected physical therapy program including strengthening, stretching, weight bearing, balance exercises and gait training. Biodex gait trainer 2 TM was used to assess selected gait kinematics (step length, step cycle, walking speed, time on each foot and ambulation index) before and after six weeks training period (end of treatment) for both groups. Results: There was a statistically significant increase in walking speed, step cycle, step length, percent of the time on each foot and ambulation index in both groups post-treatment. The improvement in gait parameters post-treatment was significantly higher in the study group compared to the control. Conclusion: Rhythmic auditory stimulation combined with treadmill training is effective in improving selected gait kinematics in stroke patients when added to the selected physical therapy program.

Keywords: stroke, rhythmic auditory stimulation, treadmill training, gait kinematics

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Authors: Olalekan Sunday Alabi, Titus Adeyemi Alonge, Olumuyiwa Idowu Ojo

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Agricultural land suitability analysis and mapping play an imperative role for sustainable utilization of scarce physical land resources. The objective of this study was to prepare spatial database of physical land resources for irrigated agriculture and to assess land suitability for irrigation and developing suitable area map of the study area. The study was conducted at Kampe-Omi irrigation scheme located at Yagba West Local Government Area of Kogi State, Nigeria. Temperature and rainfall data of the study area were collected for 10 consecutive years (2005-2014). Geographic Information System (GIS) techniques were used to develop irrigation land suitability map of the study area. Attribute parameters such as the slope, soil properties, topography of the study area were used for the analysis. The available data were arranged, proximity analysis of Arc-GIS was made, and this resulted into five mapping units. The final agricultural land suitability map of the study area was derived after overlay analysis. Based on soil composition, slope, soil properties and topography, it was concluded that; Kampe-Omi has rich sandy loam soil, which is viable for agricultural purpose, the soil composition is made up of 60% sand and 40% loam. The land-use pattern map of Kampe-Omi has vegetal area and water-bodies covering 55.6% and 19.3% of the total assessed area respectively. The landform of Kampe-Omi is made up of 41.2% lowlands, 37.5% normal lands and 21.3% highlands. Kampe-Omi is adequately suitable for agricultural purpose while an extra of 20.2% of the area is highly suitable for agricultural purpose making 72.6% while 18.7% of the area is slightly suitable.

Keywords: remote sensing, GIS, Kampe–Omi, land suitability, mapping

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Authors: Azam Fazelpour, Saeed R. Dehghani, Vlastimil Masek, Yuri S. Muzychka

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The study uses an image analysis technique employing thermal imaging to measure the percentage of areas with various temperatures on a freezing surface. An image segmentation method using threshold values is applied to a sequence of image recording the freezing process. The phenomenon is transient and temperatures vary fast to reach the freezing point and complete the freezing process. Freezing salt water is subjected to the salt rejection that makes the freezing point dynamic and dependent on the salinity at the phase interface. For a specific area of freezing, nucleation starts from one side and end to another side, which causes a dynamic and transient temperature in that area. Thermal cameras are able to reveal a difference in temperature due to their sensitivity to infrared radiance. Using Experimental setup, a video is recorded by a thermal camera to monitor radiance and temperatures during the freezing process. Image processing techniques are applied to all frames to detect and classify temperatures on the surface. Image processing segmentation method is used to find contours with same temperatures on the icing surface. Each segment is obtained using the temperature range appeared in the image and correspond pixel values in the image. Using the contours extracted from image and camera parameters, stratified areas with different temperatures are calculated. To observe temperature contours on the icing surface using the thermal camera, the salt water sample is dropped on a cold surface with the temperature of -20°C. A thermal video is recorded for 2 minutes to observe the temperature field. Examining the results obtained by the method and the experimental observations verifies the accuracy and applicability of the method.

Keywords: ice contour boundary, image processing, image segmentation, salt ice, thermal image

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Authors: Steven Arcidiacono, Robert Stote, Erin Anderson, Molly Richards

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There are numerous standard test methods for antimicrobial textiles that measure activity against specific microorganisms. However, many times these results do not translate to the performance of treated textiles when worn by individuals. Standard test methods apply a single target organism grown under optimal conditions to a textile, then recover the organism to quantitate and determine activity; this does not reflect the actual performance environment that consists of polymicrobial communities in less than optimal conditions or interaction of the textile with the skin substrate. Here we propose the development of in vitro skin model method to bridge the gap between lab testing and wear studies. The model will consist of a defined polymicrobial community of 5-7 commensal microbes simulating the skin microbiome, seeded onto a solid tissue platform to represent the skin. The protocol would entail adding a non-commensal test organism of interest to the defined community and applying a textile sample to the solid substrate. Following incubation, the textile would be removed and the organisms recovered, which would then be quantitated to determine antimicrobial activity. Important parameters to consider include identification and assembly of the defined polymicrobial community, growth conditions to allow the establishment of a stable community, and choice of skin surrogate. This model could answer the following questions: 1) is the treated textile effective against the target organism? 2) How is the defined community affected? And 3) does the textile cause unwanted effects toward the skin simulant? The proposed model would determine activity under conditions comparable to the intended application and provide expanded knowledge relative to current test methods.

Keywords: antimicrobial textiles, defined polymicrobial community, in vitro skin model, skin microbiome

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Authors: Aneesh Joshi, Sagil James

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Cold Spray (CS) process is deposition of solid particles over a substrate above a certain critical impact velocity. Unlike thermal spray processes, CS process does not melt the particles thus retaining their original physical and chemical properties. These characteristics make CS process ideal for various engineering applications involving metals, polymers, ceramics and composites. The bonding mechanism involved in CS process is extremely complex considering the dynamic nature of the process. Though CS process offers great promise for several engineering applications, the realization of its full potential is limited by the lack of understanding of the complex mechanisms involved in this process and the effect of critical process parameters on the deposition efficiency. The goal of this research is to understand the complex nanoscale mechanisms involved in CS process. The study uses Molecular Dynamics (MD) simulation technique to understand the material deposition phenomenon during the CS process. Impact of a single crystalline copper nanoparticle on copper substrate is modelled under varying process conditions. The quantitative results of the impacts at different velocities, impact angle and size of the particles are evaluated using flattening ratio, von Mises stress distribution and local shear strain. The study finds that the flattening ratio and hence the quality of deposition was highest for an impact velocity of 700 m/s, particle size of 20 Å and an impact angle of 90°. The stress and strain analysis revealed regions of shear instabilities in the periphery of impact and also revealed plastic deformation of the particles after the impact. The results of this study can be used to augment our existing knowledge in the field of CS processes.

Keywords: cold spray process, molecular dynamics simulation, nanoparticles, particle impact

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Authors: Ling Xu, Giuseppe Loprencipe, Antonio D'Andrea

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Asphalt pavement with recycled and sustainable materials has become the most commonly adopted strategy for road construction, including reclaimed asphalt pavement (RAP) and crumb rubber (CR) from waste tires. However, the adhesion and cohesion characteristics of rubberized reclaimed asphalt pavement were still ambiguous, resulting in deteriorated adhesion behavior and life performance. This research investigated the effect of bonding characteristics on rutting resistance and moisture susceptibility of rubberized reclaimed asphalt pavement in terms of two RAP sources with different oxidation levels and two tire rubber with different particle sizes. Firstly, the binder bond strength (BBS) test and bonding failure distinguishment were conducted to analyze the surface behaviors of binder-aggregate interaction. Then, the compatibility and penetration grade of rubberized RAP binder were evaluated by rotational viscosity test and penetration test, respectively. Hamburg wheel track (HWT) test with high-temperature viscoelastic deformation analysis was adopted, which illustrated the rutting resistance. Additionally, a water boiling test was employed to evaluate the moisture susceptibility of the mixture and the texture features were characterized with the statistical parameters of image colors. Finally, the colloid structure model of rubberized RAP binder with surface interaction was proposed, and statistical analysis was established to release the correlation among various indexes. This study concluded that the gel-phase colloid structure and molecular diffusion of the free light fraction would affect the surface interpretation with aggregate, determining the bonding characteristic of rubberized RAP asphalt.

Keywords: bonding characteristics, reclaimed asphalt pavement, rubberized asphalt, sustainable material

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Authors: M. R. Kamandar, J. Massah

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The information of the impact cutting behavior of plants stalk plays an important role in the design and fabrication of plants cutting equipment. It is difficult to investigate a theoretical method for defining cutting properties of plants stalks because the cutting process is complex. Thus, it is necessary to set up an experimental approach to determine cutting parameters for a single stalk. To measure the shear force, shear energy and shear strength of plant stalk, a special impact cutting tester was fabricated. It was similar to an Izod impact cutting tester for metals but a cutting blade and data acquisition system were attached to the end of pendulum's arm. The apparatus was included four strain gages and a digital indicator to show the real-time cutting force of plant stalk. To measure the shear force and also testing the apparatus, two plants’ stalks, like buxus and privet, were selected. The samples (buxus and privet stalks) were cut under impact cutting process at four loading rates 1, 2, 3 and 4 m.s^-1 and three internodes fifth, tenth and fifteenth by the apparatus. At buxus cutting analysis: the minimum value of cutting energy was obtained at fifth internode and loading rate 4 m.s^-1 and the maximum value of shear energy was obtained at fifteenth internode and loading rate 1 m.s^-1. At privet cutting analysis: the minimum value of shear consumption energy was obtained at fifth internode and loading rate: 4 m.s^-1 and the maximum value of shear energy was obtained at fifteenth internode and loading rate: 1 m.s^-1. The statistical analysis at both plants showed that the increase of impact cutting speed would decrease the shear consumption energy and shear strength. In two scenarios, the results showed that with increase the cutting speed, shear force would decrease.

Keywords: Buxus, Privet, impact cutting, shear energy

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Authors: Sara Sallam, Mohamed Taqi, Naoual Belouaggadia

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Solar thermal power plants using parabolic trough collectors (PTC) are currently a powerful technology for generating electricity. Most of these solar power plants use thermal oils as heat transfer fluid. The latter is heated in the solar field and transfers the heat absorbed in an oil-water heat exchanger for the production of steam driving the turbines of the power plant. Currently, we are seeking to develop PTCs with direct steam generation (DSG). This process consists of circulating water under pressure in the receiver tube to generate steam directly into the solar loop. This makes it possible to reduce the investment and maintenance costs of the PTCs (the oil-water exchangers are removed) and to avoid the environmental risks associated with the use of thermal oils. The pressure drops in these systems are an important parameter to ensure their proper operation. The determination of these losses is complex because of the presence of the two phases, and most often we limit ourselves to describing them by models using empirical correlations. A comparison of these models with experimental data was performed. Our calculations focused on the evolution of the pressure of the liquid-vapor mixture along the receiver tube of a PTC-DSG for pressure values and inlet flow rates ranging respectively from 3 to 10 MPa, and from 0.4 to 0.6 kg/s. The comparison of the numerical results with experience allows us to demonstrate the validity of some models according to the pressures and the flow rates of entry in the PTC-DSG receiver tube. The analysis of these two parameters’ effects on the evolution of the pressure along the receiving tub, shows that the increase of the inlet pressure and the decrease of the flow rate lead to minimal pressure losses.

Keywords: direct steam generation, parabolic trough collectors, Ppressure drop, empirical models

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Authors: Adela Penesova, Zofia Radikova, Boris Bajer, Andrea Havranova, Miroslav Vlcek

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Background: The aim of our study was to compare the effect of intensified lifestyle intervention on insulin resistance (HOMA-IR), alanine aminotransferase (ALT), aspartate aminotransferase (AST), and Fibroblast growth factor (FGF) 21 after 8 weeks of lifestyle intervention. Methods: A group of 43 obese patients (13M/30F; 43.0±12.4 years; BMI (body mass index) 31.2±6.3 kg/m2 participated in a weight loss interventional program (NCT02325804) following an 8-week hypocaloric diet (-30% energy expenditure) and physical activity 150 minutes/week. Insulin sensitivity was evaluated according to the homeostasis model assessment of insulin resistance (HOMA-IR) and insulin sensitivity indices according to Matsuda and Cederholm were calculated (ISImat and ISIced). Plasma ALT, AST, Fetuin-A, FGF 21, and physical fitness were measured. Results: The average reduction of body weight was 6.8±4.9 kg (0-15 kg; p=0.0006), accompanied with a significant reduction of body fat amount of fat mass (p=0.03), and waist circumference (p=0.02). Insulin sensitivity has been improved (IR HOMA 2.71±3.90 vs 1.24±0.83; p=0.01; ISIMat 6.64±4.38 vs 8.93±5.36 p ≤ 0.001). Total, LDL cholesterol, and triglycerides decreased (p=0.05, p=0.04, p=0.04, respectively). Physical fitness significantly improved after intervention (as measure VO2 max (maximal oxygen uptake) (p ≤ 0.001). ALT decreased significantly (0.44±0.26 vs post 0.33±0.18 ukat/l, p=0.004); however, AST not (pre 0.40±0.15 vs 0.35±0.09 ukat/l, p=0.07). Hepatokine Fetuin-A significantly decreased after intervention (43.1±10.8 vs 32.6±8.6 ng/ml, p < 0.001); however, FGF 21 levels tended to decrease (146±152 vs 132±164 pg/ml, p=0.07). Conclusion: 8-weeks of diet and physical activity intervention program in obese otherwise healthy subjects led to an improvement of insulin resistance parameters and liver marker profiles, as well as increased physical fitness. This study was supported by grants APVV 15-0228; VEGA 2/0161/16.

Keywords: obesity, diet, exercice, insulin sensitivity

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Authors: Flavio Cannavo

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Continuous evaluation of the status of potentially hazardous volcanos plays a key role for civil protection purposes. The importance of monitoring volcanic activity, especially for energetic paroxysms that usually come with tephra emissions, is crucial not only for exposures to the local population but also for airline traffic. Presently, real-time surveillance of most volcanoes worldwide is essentially delegated to one or more human experts in volcanology, who interpret data coming from different kind of monitoring networks. Unfavorably, the high nonlinearity of the complex and coupled volcanic dynamics leads to a large variety of different volcanic behaviors. Moreover, continuously measured parameters (e.g. seismic, deformation, infrasonic and geochemical signals) are often not able to fully explain the ongoing phenomenon, thus making the fast volcano state assessment a very puzzling task for the personnel on duty at the control rooms. With the aim of aiding the personnel on duty in volcano surveillance, here we introduce a system based on an ensemble of data-driven classifiers to infer automatically the ongoing volcano status from all the available different kind of measurements. The system consists of a heterogeneous set of independent classifiers, each one built with its own data and algorithm. Each classifier gives an output about the volcanic status. The ensemble technique allows weighting the single classifier output to combine all the classifications into a single status that maximizes the performance. We tested the model on the Mt. Etna (Italy) case study by considering a long record of multivariate data from 2011 to 2015 and cross-validated it. Results indicate that the proposed model is effective and of great power for decision-making purposes.

Keywords: Bayesian networks, expert system, mount Etna, volcano monitoring

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Authors: R. Unnikrishnan, K. Shankar

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In the case of high-speed fighter aircrafts, seat ejection is designed mainly for the safety of the pilot in case of an emergency. Strong windblast due to the high velocity of flight is one main difficulty in clearing the tail of the aircraft. Excessive G-forces generated, immobilizes the pilot from escape. In most of the cases, seats are ejected out of the aircrafts by explosives or by rocket motors attached to the bottom of the seat. Ejection forces are primarily in the vertical direction with the objective of attaining the maximum possible velocity in a specified period of time. The safe ejection parameters are studied to estimate the critical time of ejection for various geometries and velocities of flight. An equivalent analytical 2-dimensional biomechanical model of the human spine has been modelled consisting of vertebrae and intervertebral discs with a lumped mass approach. The 24 vertebrae, which consists of the cervical, thoracic and lumbar regions, in addition to the head mass and the pelvis has been designed as 26 rigid structures and the intervertebral discs are assumed as 25 flexible joint structures. The rigid structures are modelled as mass elements and the flexible joints as spring and damper elements. Here, the motions are restricted only in the mid-sagittal plane to form a 26 degree of freedom system. The equations of motions are derived for translational movement of the spinal column. An ejection force with a linearly increasing acceleration profile is applied as vertical base excitation on to the pelvis. The dynamic vibrational response of each vertebra in time-domain is estimated.

Keywords: biomechanical model, lumped mass, seat ejection, vibrational response

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Authors: Lucile Soudani, Hervé Illy, Rémi Bouchié

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Mould growth in living environments has been widely reported for decades all throughout the world. A higher level of moisture in housings can lead to building degradation, chemical component emissions from construction materials as well as enhancing mould growth within the envelope elements or on the internal surfaces. Moreover, a significant number of studies have highlighted the link between mould presence and the prevalence of respiratory diseases. In recent years, the proportion of biobased materials used in construction has been increasing, as seen as an effective lever to reduce the environmental impact of the building sector. Besides, bio-based materials are also hygroscopic materials: when in contact with the wet air of a surrounding environment, their porous structures enable a better capture of water molecules, thus providing a more suitable background for mould growth. Many studies have been conducted to develop reliable models to be able to predict mould appearance, growth, and decay over many building materials and external exposures. Some of them require information about temperature and/or relative humidity, exposure times, material sensitivities, etc. Nevertheless, several studies have highlighted a large disparity between predictions and actual mould growth in experimental settings as well as in occupied buildings. The difficulty of considering the influence of all parameters appears to be the most challenging issue. As many complex phenomena take place simultaneously, a preliminary study has been carried out to evaluate the feasibility to sadopt a reliability approach rather than a deterministic approach. Both epistemic and random uncertainties were identified specifically for the prediction of mould appearance and growth. Several studies published in the literature were selected and analysed, from the agri-food or automotive sectors, as the deployed methodology appeared promising.

Keywords: bio-based materials, mould growth, numerical prediction, reliability approach

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Authors: G. Hafner

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A method developed at the University of Stuttgart will be presented: ‘Analysis, Evaluation and Optimization of Food Management’. A major focus is represented by quantification of food losses and food waste as well as their classification and evaluation regarding a system optimization through waste prevention. For quantification and accounting of food, food losses and food waste along the food chain, a clear definition of core terms is required at the beginning. This includes their methodological classification and demarcation within sectors of the food value chain. The food chain is divided into agriculture, industry and crafts, trade and consumption (at home and out of home). For adjustment of core terms, the authors have cooperated with relevant stakeholders in Germany for achieving the goal of holistic and agreed definitions for the whole food chain. This includes modeling of sub systems within the food value chain, definition of terms, differentiation between food losses and food wastage as well as methodological approaches. ‘Food Losses’ and ‘Food Wastes’ are assigned to individual sectors of the food chain including a description of the respective methods. The method for analyzing, evaluation and optimization of food management systems consist of the following parts: Part I: Terms and Definitions. Part II: System Modeling. Part III: Procedure for Data Collection and Accounting Part. IV: Methodological Approaches for Classification and Evaluation of Results. Part V: Evaluation Parameters and Benchmarks. Part VI: Measures for Optimization. Part VII: Monitoring of Success The method will be demonstrated at the example of an invesigation of food losses and food wastage in the Federal State of Bavaria including an extrapolation of respective results to quantify food wastage in Germany.

Keywords: food losses, food waste, resource management, waste management, system analysis, waste minimization, resource efficiency

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Authors: R. N. Karthik Babu, R. Sarvesh, A. Rajendra Prasad, G. Swaminathan

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M42 is a molybdenum-series high-speed alloy steel widely used because of its better hot-hardness and wear resistance. These steels are conventionally heat treated in a salt bath furnace with up to three stages of preheating with predetermined soaking and holding periods. Such methods often involve long periods of processing with a large amount of energy consumed. In this study, the M42 steel samples were heat-treated by rapidly heating the specimens to the austenising temperature of 1260 °C and cooled conventionally by quenching in a neutral salt bath at a temperature of 550 °C with the aid of a hybrid microwave furnace. As metals reflect microwaves, they cannot directly be heated up when placed in a microwave furnace. The technology used herein requires the specimens to be placed in a crucible lined with SiC which is a good absorber of microwaves and the SiC lining heats the metal through radiation which facilitates the volumetric heating of the metal. A sample of similar dimensions was heat treated conventionally and cooled in the same manner. Conventional tempering process was then carried out on both these samples and analysed for various parameters such as micro-hardness, processing time, etc. Microstructure analysis and scanning electron microscopy was also carried out. The objective of the study being that similar or better properties, with substantial time and energy saving and cost cutting are achievable by rapid heat treatment through hybrid microwave furnaces. It is observed that the heat treatment is done with substantial time and energy savings, and also with minute improvement in mechanical properties of the tool steel heat treated.

Keywords: rapid heating, heat treatment, metal processing, microwave heating

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Authors: Luísa P. Cruz-Lopes, Hugo Costa e Silva, Idalina Domingos, José Ferreira, Luís Teixeira de Lemos, Bruno Esteves

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The liquefaction process of cork based tree barks has led to an increase of interest due to its potential innovation in the lumber and wood industries. In this particular study the bark of Quercus cerris (Turkish oak) is used due to its appreciable amount of cork tissue, although of inferior quality when compared to the cork provided by other Quercus trees. This study aims to optimize alkaline catalysis liquefaction conditions, regarding several parameters. To better comprehend the possible chemical characteristics of the bark of Quercus cerris, a complete chemical analysis was performed. The liquefaction process was performed in a double-jacket reactor heated with oil, using glycerol and a mixture of glycerol/ethylene glycol as solvents, potassium hydroxide as a catalyst, and varying the temperature, liquefaction time and granulometry. Due to low liquefaction efficiency resulting from the first experimental procedures a study was made regarding different washing techniques after the filtration process using methanol and methanol/water. The chemical analysis stated that the bark of Quercus cerris is mostly composed by suberin (ca. 30%) and lignin (ca. 24%) as well as insolvent hemicelluloses in hot water (ca. 23%). On the liquefaction stage, the results that led to higher yields were: using a mixture of methanol/ethylene glycol as reagents and a time and temperature of 120 minutes and 200 ºC, respectively. It is concluded that using a granulometry of <80 mesh leads to better results, even if this parameter barely influences the liquefaction efficiency. Regarding the filtration stage, washing the residue with methanol and then distilled water leads to a considerable increase on final liquefaction percentages, which proves that this procedure is effective at liquefying suberin content and lignocellulose fraction.

Keywords: liquefaction, Quercus cerris, polyalcohol liquefaction, temperature

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Authors: Anjali Suresh

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Kerala is well known for its unique settlement pattern; comprising the most part, a continuous spread of habitation. The notable urbanization trend in Kerala is urban spread rather than concentration which points out the increasing urbanization of peripheral areas of existing urban centers. This has thrown a challenge for the authorities to cater the needs of the urban population like to provide affordable housing and infrastructure facilities to sustain their livelihood; which is a matter of concern that needs policy attention in fixing the optimum FSI value. Based on recent reports (Post Disaster Need Analysis –PDNA) from the UN, addressing the unsafe situation of the carpet FAR/FSI practice in the state showcasing the varying geological & climatic conditions should also be the matter of concern. The FSI (Floor space index- the ratio of the built-up space on a plot to the area of the plot) value is certainly one of the key regulation factors in checking the land utilization for the varying occupancies desired for the overall development of a state with limitation in land availability when compared to its neighbors. The pattern of urbanization, physical conditions, topography, etc., varies within the state and can change remarkably over time which identifies that the practicing FSI norms in Kerala does not fulfils the intended function. Thus the FSI regulation is expected to change dynamically from location to location. So for determining the optimum value of FSI /FAR of a region in the state of Kerala, the government agencies should consider the optimum land utilization for the growing urbanization. On the other hand, shall keep in check the overutilization of the same in par with environmental and geographic nature. Therefore the study identifies parameters that should be considered for assigning FSI within the Kerala context, and through expert surveys; opinions arrive at a methodology for assigning an optimum FSI value of a region in the state of Kerala.

Keywords: floor space index, urbanization, density, civic pressure, optimization

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Authors: Alicia Regodon Puyalto, Alfonso Garcia-Santos

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This article presents a method to analyze the use of indoor spaces based on data analytics obtained from inbuilt digital devices. The study uses the data generated by the in-place devices, such as smart locks, Wi-Fi routers, and electrical sensors, to gain additional insights on space occupancy, user behaviour, and comfort. Those devices, originally installed to facilitate remote operations, report data through the internet that the research uses to analyze information on human real-time use of spaces. Using an in-place Internet of Things (IoT) network enables a faster, more affordable, seamless, and scalable solution to analyze building interior spaces without incorporating external data collection systems such as sensors. The methodology is applied to a real case study of coliving, a residential building of 3000m², 7 floors, and 80 users in the centre of Madrid. The case study applies the method to classify IoT devices, assess, clean, and analyze collected data based on the analysis framework. The information is collected remotely, through the different platforms devices' platforms; the first step is to curate the data, understand what insights can be provided from each device according to the objectives of the study, this generates an analysis framework to be escalated for future building assessment even beyond the residential sector. The method will adjust the parameters to be analyzed tailored to the dataset available in the IoT of each building. The research demonstrates how human-centered data analytics can improve the future spatial design of indoor spaces.

Keywords: in-place devices, IoT, human-centred data-analytics, spatial design

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Authors: Vladimir A. Vinnikov

Abstract:

The paper proposes a model of an inhomogeneous rock mass with initially random distribution of microcracks on mineral grain boundaries. It describes the behavior of cracks in a medium under the effect of thermal field, the medium heated instantaneously to a predetermined temperature. Crack growth occurs according to the concept of fracture mechanics provided that the stress intensity factor K exceeds the critical value of Kc. The modeling of thermally induced acoustic emission memory effects is based on the assumption that every event of crack nucleation or crack growth caused by heating is accompanied by a single acoustic emission event. Parameters of the thermally induced acoustic emission memory effect produced by cyclic heating and cooling (with the temperature amplitude increasing from cycle to cycle) were calculated for several rock texture types (massive, banded, and disseminated). The study substantiates the adaptation of the proposed model to humidity interference with the thermally induced acoustic emission memory effect. The influence of humidity on the thermally induced acoustic emission memory effect in quasi-homogeneous and banded rocks is estimated. It is shown that such modeling allows the structure and texture of rocks to be taken into account and the influence of interference factors on the distinctness of the thermally induced acoustic emission memory effect to be estimated. The numerical modeling can be used to obtain information about the thermal impacts on rocks in the past and determine the degree of rock disturbance by means of non-destructive testing.

Keywords: degree of rock disturbance, non-destructive testing, thermally induced acoustic emission memory effects, structure and texture of rocks

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Authors: Sukriti Sabharwal, Sonali Bhattar, Shikhar Saxena

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Introduction: COVID-19 molecular diagnostic laboratory is the cornerstone of the COVID-19 disease diagnosis as the patient’s treatment and management protocol depend on the molecular results. For this purpose, it is extremely important that the laboratory conducting these results adheres to the quality management processes to increase the accuracy and validity of the reports generated. We started our own molecular diagnostic setup at the onset of the pandemic. Therefore, we conducted this study to generate our quality management data to help us in improving on our weak points. Materials and Methods: A total of 14561 samples were evaluated by the retrospective observational method. The quality variables analysed were classified into pre-analytical, analytical, and post-analytical variables, and the results were presented in percentages. Results: Among the pre-analytical variables, sample leaking was the most common cause of the rejection of samples (134/14561, 0.92%), followed by non-generation of SRF ID (76/14561, 0.52%) and non-compliance to triple packaging (44/14561, 0.3%). The other pre-analytical aspects assessed were incomplete patient identification (17/14561, 0.11%), insufficient quantity of samples (12/14561, 0.08%), missing forms/samples (7/14561, 0.04%), samples in the wrong vials/empty VTM tubes (5/14561, 0.03%) and LIMS entry not done (2/14561, 0.01%). We are unable to obtain internal quality control in 0.37% of samples (55/14561). We also experienced two incidences of cross-contamination among the samples resulting in false-positive results. Among the post-analytical factors, a total of 0.07% of samples (11/14561) could not be dispatched within the stipulated time frame. Conclusion: Adherence to quality control processes is foremost for the smooth running of any diagnostic laboratory, especially the ones involved in critical reporting. Not only do the indicators help in keeping in check the laboratory parameters but they also allow comparison with other laboratories.

Keywords: laboratory quality management, COVID-19, molecular diagnostics, healthcare

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