Search results for: protein stability prediction

Authors: Jérémie Ochin

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Soccer analytics are built on two data sources: the frame-by-frame position of each player on the terrain and the sequences of events, such as ball drive, pass, cross, shot, throw-in... With more than 2000 ball-events per soccer game, their precise and exhaustive annotation, based on a monocular video stream such as a TV broadcast, remains a tedious and costly manual task. State-of-the-art methods for spatio-temporal action detection from a monocular video stream, often based on 3D convolutional neural networks, are close to reach levels of performances in mean Average Precision (mAP) compatibles with the automation of such task. Nevertheless, to meet their expectation of exhaustiveness in the context of data analytics, such methods must be applied in a regime of high recall – low precision, using low confidence score thresholds. This setting unavoidably leads to the detection of false positives that are the product of the well documented overconfidence behaviour of neural networks and, in this case, their limited access to contextual information and understanding of the game: their predictions are highly unstructured. Based on the assumption that professional soccer players’ behaviour, pose, positions and velocity are highly interrelated and locally driven by the player performing a ball-action, it is hypothesized that the addition of information regarding surrounding player’s appearance, positions and velocity in the prediction methods can improve their metrics. Several methods are compared to build a proper representation of the game surrounding a player, from handcrafted features of the local graph, based on domain knowledge, to the use of Graph Neural Networks trained in an end-to-end fashion with existing state-of-the-art 3D convolutional neural networks. It is shown that the inclusion of information regarding surrounding players helps reaching higher metrics.

Keywords: fine-grained action recognition, human action recognition, convolutional neural networks, graph neural networks, spatio-temporal action recognition

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Authors: W. J. Wang, D. F. Lin, L. Y. Chen, K. Y. Liu

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In this study, the ladle furnace slag was used as a mineral filler in asphalt concrete with electric arc furnace slag (EAF asphalt concrete) to investigate the effect on the engineering and thermal properties of asphalt cement mastics and EAF asphalt concrete, the lime was used as a comparison for mineral filler, and the usage percentage of mineral filler was set at 2%, 4%, 6%, and 8%. First of all, the engineering properties of the ladle furnace slag and lime were compared, and then the mineral filler was mixed with bitumen to form the asphalt cement mastics in order to analyze the influence of the ladle furnace slag on the properties of asphalt cement mastics, and lastly, the mineral filler was used in the EAF asphalt concrete to analyze its feasibility of using ladle furnace slag as a mineral filler. The study result shows that the ladle furnace slag and the lime have no obvious difference in their physical properties, and from the energy dispersive spectrometer (EDS) test results, we know that the lime and the ladle furnace slag have similar elemental composition, but the Ca found in the ladle furnace slag belongs to CaO, and the lime belongs to CaCO3, therefore the ladle furnace slag has the property of expansion. According to the test results, the viscosity of asphalt cement mastics will increase with the increase in the use of mineral filler. Since the ladle furnace slag has more CaO content, the viscosity of the asphalt cement mastics with ladle furnace slag will increase more than using lime as mineral filler in the asphalt cement mastics, and the use of ladle furnace slag only needs to be 2% in order to achieve the effect of anti-peeling which is 6% for lime. From the related test results of EAF asphalt concrete, it is known that the maximum stability value can be obtained when the use of mineral filler is about 5%. When the ladle furnace slag is used as the mineral filler, it can improve the stiffness, indirect tension strength, spalling resistance, and thermal insulation of EAF asphalt concrete, which also indicates that using the ladle furnace slag as the mineral filler of bitumen can help to improve the durability of the asphalt pavement.

Keywords: ladle furnace slag, mineral filler, asphalt cement mastics, EAF asphalt concrete

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Authors: Ambreen Aslam, Tahira Aziz Mughal, Skye R. Thomas-Hall, Peer M. Schenk

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Biodiesel is an alternative to petroleum-derived fuel mainly composed of fatty acid from oleaginous microalgae feedstock. Microalgae produced fatty acid methyl esters (FAMEs) as they can store high levels of lipids without competing for food productivity. After lipid extraction and esterification, fatty acid profile from algae feedstock possessed the abundance of fatty acids with carbon chain length specifically C16 and C18. The qualitative analysis of FAME was done by cultivating mix microalgae consortia under three different CO₂ concentrations (1%, 3%, and 5.5%) from a coal fired flue gas. FAME content (280.3 µg/mL) and productivity (18.69 µg/mL/D) was higher under 1% CO₂ (flue gas) as compare to other treatments. Whereas, Mixed C. (F) supplemented with 5.5% CO₂ (50% flue gas) had higher SFA (36.28%) and UFA (63.72%) which improve the oxidative stability of biodiesel. Subsequently, low Iodine value (136.3 gI₂/100g) and higher Cetane number (52) of Mixed C.+P (F) were found to be in accordance with European (EN 14214) standard under 5.5% CO₂ along with 50mM phosphate buffer. Experimental results revealed that sufficient phosphate reduced FAME productivity but significantly enhance biodiesel quality. This research aimed to develop an integrated approach of utilizing flue gas (as CO₂ source) for significant improvement in biodiesel quality under surplus phosphorus. CO₂ sequestration from industrial flue gas not only reduce greenhouse gases (GHG) emissions but also ensure sustainability and eco-friendliness of the biodiesel production process through microalgae.

Keywords: biodiesel analysis, carbon dioxide, coal fired flue gas, FAME productivity, fatty acid profile, fuel properties, lipid content, mixed culture microalgae

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Authors: O. A. Adebiyi, A. O. Oni, A. O. K. Adeshehinwa, I. O. Adejumo

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In forty nine (49) days, twenty four (24) growing pigs (Landrace x Large white) with an average weight of 17 ±2.1kg were allocated to four experimental treatments T1 (dry mash without probiotics), T2 (wet feed without probiotics), T3 (dry mash + Saccaromyces cereviseae probiotics) and T4 (wet feed + Saccaromyces cereviseae probiotics) which were replicated three times with two pigs per replicate in a completely randomised design. The basal feed (dry feed) was formulated to meet the nutritional requirement of the animal with crude protein of 18.00% and metabolisable energy of 2784.00kcal/kgME. Growth pattern, faecal microbial load and behavioural activities (eating, drinking, physical pen interaction and frequency of visiting the drinking troughs) were accessed. Pigs fed dry mash without probiotics (T1) had the highest daily feed intake among the experimental animals (1.10kg) while pigs on supplemented diets (T3 and T4) had an average daily feed intake of 0.95kg. However, the feed conversion ratio was significantly (p < 0.05) affected with pigs on T3 having least value of 6.26 compared those on T4 (wet feed + Saccaromyces cereviseae) with means of 7.41. Total organism counts varied significantly (p < 0.05) with pigs on T1, T2, T3 and T4 with mean values of 179.50 x106cfu; 132.00 x 106cfu; 32.00 x 106cfu and 64.50 x 106cfu respectively. Coliform count was also significantly (p < 0.05) different among the treatments with corresponding values of 117.50 x 106cfu; 49.00 x 106cfu, 8.00 x 106cfu for pigs in T1, T2 and T4 respectively. The faecal Saccaromyces cereviseae was significantly lower in pigs fed supplemented diets compared to their counterparts on unsupplemented diets. This could be due to the inability of yeast organisms to be voided easily through feaces. The pigs in T1 spent the most time eating (7.88%) while their counterparts on T3 spent the least time eating. The corresponding physical pen interaction times expressed in percentage of a day for pigs in T1, T2, T3 and T4 are 6.22%, 5.92%, 4.04% and 4.80% respectively. These behavioural responses exhibited by these pigs (T3) showed that little amount of dry feed supplemented with probiotics is needed for better performance. The water intake increases as a result of the dryness of the feed with consequent decrease in pen interaction and more time was spent resting than engaging in other possible vice-habit like fighting or tail biting. Pigs fed dry feed (T3) which was supplemented with Saccaromyces cereviseae probiotics had a better overall performance, least faecal microbial load than wet fed pigs either supplemented with Saccaromyces cereviseae or non-supplemented.

Keywords: behaviour, feed forms, feed utilization, growth, microbial

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Authors: Rajani Kant Rai, Jayakrishnan Athipet

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There have been several attempts to prepare polymers with antimicrobial properties by doping with various N-halamines. Hydantoins (Cyclic N-halamine) is of importance due to their stability rechargeable chloroamide function, broad-spectrum anti-microbial action and ability to prevent resistance to the organisms. Polymerizable hydantoins are synthesized by tethering vinyl moieties to 5,5,-dialkyl hydantoin sacrificing the imide hydrogen in the molecule thereby restricting the halogen capture only to the amide nitrogen that results in compromised antibacterial activity. In order to increase the activity of the antimicrobial polymer, we have developed a scheme to maximize the attachment of chlorine to the amide and the imide moieties of hydantoin. Vinyl hydantoin monomer, (Z)-5-(4-((3-methylbuta-1,3-dien-2-yl)oxy)benzylidene)imidazolidine-2,4-dione (MBBID) was synthesized and copolymerized with a commercially available monomer, methyl methacrylate, by free radical polymerization. The antimicrobial activity of hydantoin is strongly dependent on their surface area and hence their microbial activity increases when incorporated in microspheres or nanoparticles as compared to their bulk counterpart. In this regard, smooth and rough surface microsphere of the vinyl monomer (MBBID) with commercial monomer was synthesized. The oxidative chlorine content of the copolymer ranged from 1.5 to 2.45 %. Further, to demonstrate the water purification potential, the thin column was packed with smooth or rough microspheres and challenged with simulated contaminated water that exhibited 6 log kill (total kill) of the bacteria in 20 minutes of exposure with smooth (25 mg/ml) and rough microsphere (15.0 mg/ml).

Keywords: cyclic N-halamine, vinyl hydantoin monomer, rough surface microsphere, simulated contaminated water

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Authors: Luyin Liang

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Although sibling relationship has been viewed as one of the most important family relationships that significantly impacted on the quality of life of both adults with Intellectual Disability (AWID) and their brothers/sisters, very few research have been done to investigate this relationship in China. This study investigated Chinese siblings of AWID’s relational motivations in sibling relationship and their determining factors. Quantitative research method has been adopted and 284 samples were recruited in this study. Siblings of AWID’s two types of relational motivations, including obligatory motivations and discretionary motivations were examined. Their emotional closeness, senses of responsibility, experiences of ID stigma, and expectancy of self-reward in sibling relationship were measured by validated scales. Personal, and familial-social demographic characteristics were also investigated. Linear correlation test and standard multiple regression analysis were the major statistical methods that have been used to analyze the data. The findings of this study showed that all the measured factors, including siblings of AWID’s emotional closeness, their senses of responsibility, experiences of ID stigma, and self-reward expectations had significant relationships with their both types of motivations. However, when these factors were grouped together to measure each type of these motivations, the prediction results were varied. The order of factors that best predict siblings of AWID’s obligatory motivations was: their senses of responsibility, emotional closeness, experiences of ID stigma, and their expectancy of self-reward, whereas the order of these factors that best determine siblings of AWID’s discretionary motivations was: their self-reward expectations, experiences of ID stigma, senses of responsibility, and emotional closeness. Among different demographic characteristics, AWID’s disability condition, their siblings’ age, gender, marital status, number of children, both siblings’ living arrangements and family financial status were found to have significant impacts on siblings of AWID’s both types of motivations in sibling relationship. The results of this study could enhance social work practitioners’ understandings about the needs and challenges of siblings of AWID. Suggestions on advocacies for policy changes and services improvements for these siblings were discussed in this study.

Keywords: sibling relationship, intellectual disability, adults, China

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Authors: Philipp Stehle, Dragoljub Vrankovic, Montaha Anjass

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Due to its high availability and extremely high specific capacity, silicon (Si) is the most promising anode material for next generation lithium-ion batteries (LIBs). However, Si anodes are suffering from high volume changes during cycling causing unstable solid-electrolyte interface (SEI). One approach for mitigation of these effects is to embed Si particles into a carbon matrix to create silicon/carbon composites (Si/C). These typically show more stable electrochemical performance than bare silicon materials. Nevertheless, the same failure mechanisms mentioned earlier appear in a less pronounced form. In this work, we further improved the cycling performance of two commercially available Si/C materials by coating thin metal oxide films of different thicknesses on the powders via Atomic Layer Deposition (ALD). The coated powders were analyzed via ICP-OES and AFM measurements. Si/C-graphite anodes with automotive-relevant loadings (~3.5 mAh/cm2) were processed out of the materials and tested in half coin cells (HCCs) and full pouch cells (FPCs). During long-term cycling in FPCs, a significant improvement was observed for some of the ALD-coated materials. After 500 cycles, the capacity retention was already up to 10% higher compared to the pristine materials. Cycling of the FPCs continued until they reached a state of health (SOH) of 80%. By this point, up to the triple number of cycles were achieved by ALD-coated compared to pristine anodes. Post-mortem analysis via various methods was carried out to evaluate the differences in SEI formation and thicknesses.

Keywords: silicon anodes, li-ion batteries, atomic layer deposition, silicon-carbon composites, surface coatings

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Authors: Jonghyuk Yoon, Hyoungwoon Song, Youngbae Kim, Eunju Kim

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Recently, with the rapid growth of semiconductor industry, lots of interests have been focused on after treatment system that remove the polluted gas produced from semiconductor manufacturing process, and a wet scrubber is the one of the widely used system. When it comes to mechanism of removing the gas, the polluted gas is removed firstly by chemical reaction in a reactor part. After that, the polluted gas stream is brought into contact with the scrubbing liquid, by spraying it with the liquid. Effective design of the reactor part inside the wet scrubber is highly important since removal performance of the polluted gas in the reactor plays an important role in overall performance and stability. In the present study, a CFD (Computational Fluid Dynamics) analysis was performed to figure out the thermal and flow characteristics inside unit a reactor of wet scrubber. In order to verify the numerical result, temperature distribution of the numerical result at various monitoring points was compared to the experimental result. The average error rates (12~15%) between them was shown and the numerical result of temperature distribution was in good agreement with the experimental data. By using validated numerical method, the effect of the reactor geometry on heat transfer rate was also taken into consideration. Uniformity of temperature distribution was improved about 15%. Overall, the result of present study could be useful information to identify the fluid behavior and thermal performance for various scrubber systems. This project is supported by the ‘R&D Center for the reduction of Non-CO₂ Greenhouse gases (RE201706054)’ funded by the Korea Ministry of Environment (MOE) as the Global Top Environment R&D Program.

Keywords: semiconductor, polluted gas, CFD (Computational Fluid Dynamics), wet scrubber, reactor

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Authors: Syed Hammad Ali, Rijan Bhakta Kayastha, Danial Hashmi, Richard Armstrong, Ahuti Shrestha, Iram Bano, Javed Hassan

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This paper presents the results of a semi-distributed modified positive degree-day model (MPDDM) for estimating snow and ice melt contributions to discharge from the glacierized Hunza River basin, Pakistan. The model uses daily temperature data, daily precipitation data, and positive degree day factors for snow and ice melt. The model is calibrated for the period 1995-2001 and validated for 2002-2013, and demonstrates close agreements between observed and simulated discharge with Nash–Sutcliffe Efficiencies of 0.90 and 0.88, respectively. Furthermore, the Weather Research and Forecasting model projected temperature, and precipitation data from 2016-2050 are used for representative concentration pathways RCP4.5 and RCP8.5, and bias correction was done using a statistical approach for future discharge estimation. No drastic changes in future discharge are predicted for the emissions scenarios. The aggregate snow-ice melt contribution is 39% of total discharge in the period 1993-2013. Snow-ice melt contribution ranges from 35% to 63% during the high flow period (May to October), which constitutes 89% of annual discharge; in the low flow period (November to April) it ranges from 0.02% to 17%, which constitutes 11 % of the annual discharge. The snow-ice melt contribution to total discharge will increase gradually in the future and reach up to 45% in 2041-2050. From a sensitivity analysis, it is found that the combination of a 2°C temperature rise and 20% increase in precipitation shows a 10% increase in discharge. The study allows us to evaluate the impact of climate change in such basins and is also useful for the future prediction of discharge to define hydropower potential, inform other water resource management in the area, to understand future changes in snow-ice melt contribution to discharge, and offer a possible evaluation of future water quantity and availability.

Keywords: climate variability, future discharge projection, positive degree day, regional climate model, water resource management

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Authors: Georgios Koronis, Arlindo Silva

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This study seeks to understand the mechanical behavior of a natural fiber reinforced composite (epoxy/flax) in more depth, utilizing both experimental and numerical methods. It is attempted to identify relationships between the design parameters and the product performance, understand the effect of noise factors and reduce process variations. Optimization of the mechanical performance of manufactured goods has recently been implemented by numerous studies for green composites. However, these studies are limited and have explored in principal mass production processes. It is expected here to discover knowledge about composite’s manufacturing that can be used to design artifacts that are of low batch and tailored to niche markets. The goal is to reach greater consistency in the performance and further understand which factors play significant roles in obtaining the best mechanical performance. A prediction of response function (in various operating conditions) of the process is modeled by the DoE. Normally, a full factorial designed experiment is required and consists of all possible combinations of levels for all factors. An analytical assessment is possible though with just a fraction of the full factorial experiment. The outline of the research approach will comprise of evaluating the influence that these variables have and how they affect the composite mechanical behavior. The coupons will be fabricated by the vacuum infusion process defined by three process parameters: flow rate, injection point position and fiber treatment. Each process parameter is studied at 2-levels along with their interactions. Moreover, the tensile and flexural properties will be obtained through mechanical testing to discover the key process parameters. In this setting, an experimental phase will be followed in which a number of fabricated coupons will be tested to allow for a validation of the design of the experiment’s setup. Finally, the results are validated by performing the optimum set of in a final set of experiments as indicated by the DoE. It is expected that after a good agreement between the predicted and the verification experimental values, the optimal processing parameter of the biocomposite lamina will be effectively determined.

Keywords: design of experiments, flax fabrics, mechanical performance, natural fiber reinforced composites

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Authors: Pedro M. Velasco, Cecilia C. Alday, Oscar C. Avello, Ximena T. Faundez, Luis M. Velasco

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Anaerobic digestion (AD) plants of food waste (FW) produced by agro-industry, have been widely developed from last decade to nowadays, because of the advantages over aerobic active sludge systems. Despite several bioreactor configurations and operation modes have been successfully improved and implemented at industrial scale in a wide range of applications, effluent behavior, after AD, does not commonly meet requirements for direct disposal into the environment without further treatments. In addition, literature has rarely shown AD of food waste at psychrophilic range. This temperature range may be of interest for making AD plant operation easier and increasing the stability of digestion. In spite of literature shows several methods for post-treatment, such as the use of microalgae, these have not been cultivated on effluents from AD at psychrophilic range. Hence, with the aim of showing the potential use of AD of FW at the psychrophilic range (25ºC) and the viability of microalgae post-treatment, single batch reactors have been used for methane potential tests at laboratory scale. Afterwards, digestates, derived from this AD of FW sludge, were diluted with fresh water at different ratios (1:0, 1:1; 1:4) and used as culture media for photoautotrophic microalgae. Several parameters, such as pH, biogas production, and chemical oxygen demand, were measured periodically over several months. Results show that methane potential is 150 ml g-1 per volatile solid with up to 57.7 % of methane content. Moreover, microalgae has been successfully cultivated on all tested effluents and in case of 1:1 and 1:4 rates, the resulting effluents meet the quality levels required for irrigation water.

Keywords: anaerobic digestion, biogas, food waste, microalgae, psychrophilic range

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Authors: Manal Elsayed Elkheshin, Rasha Saleh Mansour, Mohamed Fawzy Mohamed Eldnasury, Mamdouh Elbadry Mohamed

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This research Aims to identify the main factors affecting the production and the fish consumption in Egypt, through the econometric estimation for various forms functions of fish production and fish consumption during the period (1991-2014), as the aim of this research to forecast the production and the fish consumption in Egypt until 2020, through determine the best standard methods using (ARIMA).This research also aims to the economic feasibility of the production of fish in aquaculture farms study; investment cost and represents the value of land, buildings, equipment and irrigation. Aquaculture requires three types of fish (Tilapia, carp fish, and mullet fish), and the total area of the farm, about an acre. The annual Fish production from this project about 3.5 tons. The annual investment costs of about 50500 pounds, Find conclude that the project can repay the cost of their investments after about 4 years and 5 months, and therefore recommend the implementation of the project, and internal rate of return reached (IRR) of about 22.1%, where it is clear that the rate of large internal rate of return, and achieves pound invested in this project annual return is estimated at 22.1 pounds, more than the opportunity cost, so we recommend the need to implement the project.Recommendations:1. Increasing the fish agriculture to decrease the gap of animal protein. 2.Increasing the number of mechanism fishing boats, and the provision of transport equipped to maintain the quality of fish production. 3.Encourage and attract the local and foreign investments, providing advice to the investor on the aquaculture field. 4. Action newsletters awareness of the importance of these projects where these projects resulted in a net profit after recovery in less than five years, IRR amounted to about 23%, which is much more than the opportunity cost of a bank interest rate is about 7%, helping to create work and graduates opportunities, and contribute to the reduction of imports of the fish, and improve the performance of the food trade balance.

Keywords: equation model, individual share, red meat, consumption, production, endogenous variable, exogenous variable, financial performance evaluates fish culture, feasibility study, fish production, aquaculture

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Authors: Francesca Lombardi, Francesca Rosaria Augello, Benedetta Cinque, Maria Grazia Cifone, Paola Palumbo

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Glioblastoma multiforme (GBM) is a high-grade primary brain tumor refractory to current forms of treatment. The survival benefits of patients with GBM remain unsatisfactory due to the intrinsic or acquired resistance to temozolomide (TMZ), an alkylating agent, used as the first-line chemotherapeutic drug to treat GBM patients. Its cytotoxic effect is visualized by the induction of O6-methylguanine (O6MeG) within DNA. Cyclooxygenase-2 (COX-2), an inflammation-associated enzyme, has been implicated in tumorigenesis and progression of GBM, its inhibition shows anticancer activities. In the present study, it was verified if the combination of a COX-2 selective inhibitor, NS398, with TMZ could counteract the TMZ resistance. In particular, the effect of NS398 mixed with TMZ was investigated in the GBM TMZ-resistant cell line, T98G. Cells were pretreated with NS398 (100µM, 24 hours) and then exposed to TMZ alone (200µM), NS398 alone, or both for 72 hours, after which cell growth rate and cycle phases, as well as apoptosis level, were evaluated. Coadministration of NS398 and TMZ caused a significant decrease in cell growth and a progressive increase of dead cells detected by trypan blue staining. Moreover, a significant level of apoptotic cell percentage and alteration of cell cycle phases were observed in T98G treated with TMZ-NS398 combination when compared to untreated cells or TMZ-treated cells. TMZ-resistant tumors, as GBM, express elevated levels of DNA repair enzyme O6-methylguanine-DNA methyltransferase (MGMT). The mixture drastically reduced MGMT expression in the TMZ-resistant cell line T98G, known to express high levels of MGMT basically. Moreover, while TMZ alone did not influence the COX-2 protein expression, the combination successfully reduced it. In conclusion, these results demonstrated that NS398 enhanced the efficacy of TMZ through cell number reduction, apoptosis induction, and decreased MGMT levels, suggesting the ability of drug combination to reduce the chemoresistance. This drug combination deserves attention and could be considered as a promising therapeutic strategy for GBM patients.

Keywords: COX-2, COX-2 inhibitor, glioblastoma, NS398, T98G, temozolomide

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Authors: Delgado-Meza M., Minor-Pérez H.

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Protease is the generic name of enzymes that hydrolyze proteins. These are classified in the subgroup EC3.4.11-99X of the classification enzymes. In food technology the proteolysis is used to modify functional and nutritional properties of food, and in some cases this proteolysis may cause food spoilage. In general, seafood and rainbow trout have accelerated decomposition process once it has done its capture, due to various factors such as the endogenous enzymatic activity that can result in loss of structure, shape and firmness, besides the release of amino acid precursors of biogenic amines. Some studies suggest the use of protease inhibitors from legume as biological regulators of proteolytic activity. The enzyme inhibitors are any substance that reduces the rate of a reaction catalyzed by an enzyme. The objective of this study was to evaluate the reduction of the proteolytic activity of enzymes in extracts of rainbow trout with protease inhibitors obtained from chickpea flour. Different proportions of rainbow trout enzyme extract (75%, 50% and 25%) and extract chickpea enzyme inhibitors were evaluated. Chickpea inhibitors were obtained by mixing 5 g of flour in 30 mL of pH 7.0 phosphate buffer. The sample was centrifuged at 8000 rpm for 10 min. The supernatant was stored at -15°C. Likewise, 20 g of rainbow trout were ground in 20 mL of phosphate buffer solution at pH 7.0 and the mixture was centrifuged at 5000 rpm for 20 min. The supernatant was used for the study. In each treatment was determined the specific enzymatic activity with the technique of Kunitz, using hemoglobin as substrate for the enzymes acid fraction and casein for basic enzymes. Also biuret protein was quantified for each treatment. The results showed for fraction of basic enzymes in the treatments evaluated, that were inhibition of endogenous enzymatic activity. Inhibition values compared to control were 51.05%, 56.59% and 59.29% when the proportions of endogenous enzymes extract rainbow trout were 75%, 50% and 25% and the remaining volume used was extract with inhibitors. Treatments with acid enzymes showed no reduction in enzyme activity. In conclusion chickpea flour reduced the endogenous enzymatic activity of rainbow trout, which may favor its application to increase the half-life of this food. The authors acknowledge the funding provided by the CONACYT for the project 131998.

Keywords: rainbouw trout, enzyme inhibitors, proteolysis, enzyme activity

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Authors: Arup Saha Chaudhuri

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Structural steel is a very ductile material with high strength carrying capacity, thus it is very useful to make earthquake resistant buildings. It is a homogeneous material also. The member section and the structural system can be made very efficient for economical design. As the steel is recyclable and reused, it is a green material. The embodied energy for the efficiently designed steel structure is less than the RC structure. For sustainable green building steel is the best material nowadays. Moreover, pre-engineered and pre-fabricated faster construction methodologies help the development work to complete within the stipulated time. In this paper, the usefulness of Eccentric Bracing Frame (EBF) in steel structure over Moment Resisting Frame (MRF) and Concentric Bracing Frame (CBF) is shown. Stability of the steel structures against horizontal forces especially in seismic condition is efficiently possible by Eccentric bracing systems with economic connection details. The EBF is pin–ended, but the beam-column joints are designed for pin ended or for full connectivity. The EBF has several desirable features for seismic resistance. In comparison with CBF system, EBF system can be designed for appropriate stiffness and drift control. The link beam is supposed to yield in shear or flexure before initiation of yielding or buckling of the bracing member in tension or compression. The behavior of a 2-D steel frame is observed under seismic loading condition in the present paper. Ductility and brittleness of the frames are compared with respect to time period of vibration and dynamic base shear. It is observed that the EBF system is better than MRF system comparing the time period of vibration and base shear participation.

Keywords: steel building, green and sustainable, earthquake resistant, EBF system

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Authors: Rong Sun, Laihong Shen

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La-based perovskite oxygen carriers, especially the doped-La(M)FeO₃, showed excellent performances during chemical looping processes. However, the mechanisms of the undoped and doped La(M)FeO₃ are not clear at present, making the mechanisms clear may help the development of chemical looping technologies. In this paper, the method based on the density function theory (DFT) was used to analysis the influence of Ca, Sr, and Ba doping of La on the electronic structure, while the CO oxidation mechanisms on the surface of LaFeO₃ and Ca-doped LaFeO₃ oxygen carriers were also analyzed. The results showed that the band gap was decreased by the doping of low valence. While the doping of low valence element Ca, Sr, and Ba at La site simultaneously resulted to the moving of the valence band toward high energy and made the valence band cross the Fermi energy level. This was resulted from the holes generated by divalent ion substitution. The holes can change the total magnetization from antiferromagnet to weakly ferromagnetism. The calculation results about the formation of oxygen vacancy showed that substitutions of Ca, Sr, and Ba caused a large drop in oxygen vacancy formation energy, indicating that the bulk oxygen transport was improved. Based on the optimized bulk of the undoped and Ca-doped LaFeO₃(010) surface, the CO adsorption was analyzed. The results indicated that the adsorption energy increased by divalent ion substitution, meaning that the adsorption stability decreased. The results can provide a certain theoretical basis for the development of perovskite oxides in chemical looping technologies.

Keywords: chemical looping technologies, lanthanum ferrate (LaFeO₃), divalent ion substitution, CO oxidation

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Authors: Mane Darbinyan, Lusine Hayrapetyan, Elen Matevosyan

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Artificial Intelligence in Education (AIED) has been created to help students get ready for the workforce, and over the past 25 years, it has grown significantly, offering a variety of technologies to support academic, institutional, and administrative services. However, this is still challenging, especially considering the labor market's rapid change. While choosing a career, people face various obstacles because they do not take into consideration their own preferences, which might lead to many other problems like shifting jobs, work stress, occupational infirmity, reduced productivity, and manual error. Besides preferences, people should properly evaluate their technical and non-technical skills, as well as their personalities. Professional counseling has become a difficult undertaking for counselors due to the wide range of career choices brought on by changing technological trends. It is necessary to close this gap by utilizing technology that makes sophisticated predictions about a person's career goals based on their personality. Hence, there is a need to create an automated model that would help in decision-making based on user inputs. Improving career guidance can be achieved by embedding machine learning into the career consulting ecosystem. There are various systems of career guidance that work based on the same logic, such as the classification of applicants, matching applications with appropriate departments or jobs, making predictions, and providing suitable recommendations. Methodologies like KNN, Neural Networks, K-means clustering, D-Tree, and many other advanced algorithms are applied in the fields of data and compute some data, which is helpful to predict the right careers. Besides helping users with their career choice, these systems provide numerous opportunities which are very useful while making this hard decision. They help the candidate to recognize where he/she specifically lacks sufficient skills so that the candidate can improve those skills. They are also capable to offer an e-learning platform, taking into account the user's lack of knowledge. Furthermore, users can be provided with details on a particular job, such as the abilities required to excel in that industry.

Keywords: career guidance system, machine learning, career prediction, predictive decision, data mining, technical and non-technical skills

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Authors: Samira K. Al-Nasser, Siamak Noroozi, Roya Haratian, Adrian Harvey

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A total knee replacement (TKR) is a surgical procedure necessary when there is severe pain and/or loss of function in the knee. Surgeons balance the load in the knee and the surrounding soft tissue by feeling the tension at different ranges of motion. This method can be unreliable and lead to early failure of the joint. The ideal kinematics and load distribution have been debated significantly based on previous biomechanical studies surrounding both TKRs and normal knees. Intraoperative sensors like VERASENSE and eLibra have provided a method for the quantification of the load indicating a balanced knee. A review of the literature written about intraoperative sensors and tension/stability of the knee was done. Studies currently debate the quantification of the load in medial and lateral compartments specifically. However, most research reported that following a TKR the medial compartment was loaded more heavily than the lateral compartment. In several cases, these results were shown to increase the success of the surgery because they mimic the normal kinematics of the knee. In conclusion, most research agrees that an intercompartmental load differential of between 10 and 20 pounds, where the medial load was higher than the lateral, and an absolute load of less than 70 pounds was ideal. However, further intraoperative sensor development could help improve the accuracy and understanding of the load distribution on the surgical outcomes in a TKR. A reduction in early revision surgeries for TKRs would provide an improved quality of life for patients and reduce the economic burden placed on both the National Health Service (NHS) and the patient.

Keywords: intraoperative sensors, joint load forces, kinematics, load balancing, and total knee replacement

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Authors: Rosa Figueroa, Christopher Flores

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Text categorization is the problem of assigning a new document to a set of predetermined categories, on the basis of a training set of free-text data that contains documents whose category membership is known. To train a classification model, it is necessary to extract characteristics in the form of tokens that facilitate the learning and classification process. In text categorization, the feature extraction process involves the use of word sequences also known as N-grams. In general, it is expected that documents belonging to the same category share similar features. The Smith-Waterman (SW) algorithm is a dynamic programming algorithm that performs a local sequence alignment in order to determine similar regions between two strings or protein sequences. This work explores the use of SW algorithm as an alternative to feature extraction in text categorization. The dataset used for this purpose, contains 2,610 annotated documents with the classes Obese/Non-Obese. This dataset was represented in a matrix form using the Bag of Word approach. The score selected to represent the occurrence of the tokens in each document was the term frequency-inverse document frequency (TF-IDF). In order to extract features for classification, four experiments were conducted: the first experiment used SW to extract features, the second one used unigrams (single word), the third one used bigrams (two word sequence) and the last experiment used a combination of unigrams and bigrams to extract features for classification. To test the effectiveness of the extracted feature set for the four experiments, a Support Vector Machine (SVM) classifier was tuned using 20% of the dataset. The remaining 80% of the dataset together with 5-Fold Cross Validation were used to evaluate and compare the performance of the four experiments of feature extraction. Results from the tuning process suggest that SW performs better than the N-gram based feature extraction. These results were confirmed by using the remaining 80% of the dataset, where SW performed the best (accuracy = 97.10%, weighted average F-measure = 97.07%). The second best was obtained by the combination of unigrams-bigrams (accuracy = 96.04, weighted average F-measure = 95.97) closely followed by the bigrams (accuracy = 94.56%, weighted average F-measure = 94.46%) and finally unigrams (accuracy = 92.96%, weighted average F-measure = 92.90%).

Keywords: comorbidities, machine learning, obesity, Smith-Waterman algorithm

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Authors: Michael Williams

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The ability to control a flowing well is of the utmost important. During the kill phase, heavy weight kill mud is circulated around the well. While increasing bottom hole pressure near wellbore formation, the damage is increased. The addition of high density spherical objects has the potential to minimise this near wellbore damage, increase bottom hole pressure and reduce operational time to kill the well. This operational time saving is seen in the rapid deployment of high density spherical objects instead of building high density drilling fluid. The research aims to model the well kill process using a Computational Fluid Dynamics software. A model has been created as a proof of concept to analyse the flow of micron sized spherical objects in the drilling fluid. Initial results show that this new methodology of spherical objects in drilling fluid agrees with traditional stream lines seen in non-particle flow. Additional models have been created to demonstrate that areas of higher flow rate around the bit can lead to increased probability of wash out of formations but do not affect the flow of micron sized spherical objects. Interestingly, areas that experience dimensional changes such as tool joints and various BHA components do not appear at this initial stage to experience increased velocity or create areas of turbulent flow, which could lead to further borehole stability. In conclusion, the initial models of this novel well control methodology have not demonstrated any adverse flow patterns, which would conclude that this model may be viable under field conditions.

Keywords: well control, fluid mechanics, safety, environment

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Authors: Mane Darbinyan, Lusine Hayrapetyan, Elen Matevosyan

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Artificial Intelligence in Education (AIED) has been created to help students get ready for the workforce, and over the past 25 years, it has grown significantly, offering a variety of technologies to support academic, institutional, and administrative services. However, this is still challenging, especially considering the labor market's rapid change. While choosing a career, people face various obstacles because they do not take into consideration their own preferences, which might lead to many other problems like shifting jobs, work stress, occupational infirmity, reduced productivity, and manual error. Besides preferences, people should evaluate properly their technical and non-technical skills, as well as their personalities. Professional counseling has become a difficult undertaking for counselors due to the wide range of career choices brought on by changing technological trends. It is necessary to close this gap by utilizing technology that makes sophisticated predictions about a person's career goals based on their personality. Hence, there is a need to create an automated model that would help in decision-making based on user inputs. Improving career guidance can be achieved by embedding machine learning into the career consulting ecosystem. There are various systems of career guidance that work based on the same logic, such as the classification of applicants, matching applications with appropriate departments or jobs, making predictions, and providing suitable recommendations. Methodologies like KNN, neural networks, K-means clustering, D-Tree, and many other advanced algorithms are applied in the fields of data and compute some data, which is helpful to predict the right careers. Besides helping users with their career choice, these systems provide numerous opportunities which are very useful while making this hard decision. They help the candidate to recognize where he/she specifically lacks sufficient skills so that the candidate can improve those skills. They are also capable of offering an e-learning platform, taking into account the user's lack of knowledge. Furthermore, users can be provided with details on a particular job, such as the abilities required to excel in that industry.

Keywords: career guidance system, machine learning, career prediction, predictive decision, data mining, technical and non-technical skills

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Authors: Berkan Ural, Arif Eser, Sinan Apaydin

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Medical image processing is generally become a challenging task nowadays. Indeed, processing of brain MRI images is one of the difficult parts of this area. This study proposes a hybrid well-defined approach which is consisted from tumor detection, extraction and analyzing steps. This approach is mainly consisted from a computer aided diagnostics system for identifying and detecting the tumor formation in any region of the brain and this system is commonly used for early prediction of brain tumor using advanced image processing and probabilistic neural network methods, respectively. For this approach, generally, some advanced noise removal functions, image processing methods such as automatic segmentation and morphological operations are used to detect the brain tumor boundaries and to obtain the important feature parameters of the tumor region. All stages of the approach are done specifically with using MATLAB software. Generally, for this approach, firstly tumor is successfully detected and the tumor area is contoured with a specific colored circle by the computer aided diagnostics program. Then, the tumor is segmented and some morphological processes are achieved to increase the visibility of the tumor area. Moreover, while this process continues, the tumor area and important shape based features are also calculated. Finally, with using the probabilistic neural network method and with using some advanced classification steps, tumor area and the type of the tumor are clearly obtained. Also, the future aim of this study is to detect the severity of lesions through classes of brain tumor which is achieved through advanced multi classification and neural network stages and creating a user friendly environment using GUI in MATLAB. In the experimental part of the study, generally, 100 images are used to train the diagnostics system and 100 out of sample images are also used to test and to check the whole results. The preliminary results demonstrate the high classification accuracy for the neural network structure. Finally, according to the results, this situation also motivates us to extend this framework to detect and localize the tumors in the other organs.

Keywords: image processing algorithms, magnetic resonance imaging, neural network, pattern recognition

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Authors: Yee-Seul So, Guiseppe Ianiri, Alex Idnurm, Yong-Sun Bahn

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Tor1 is a serine/threonine protein kinase that is widely conserved across eukaryotic species. Tor1 was first identified in Saccharomyces cerevisiae as a target of rapamycin (TOR). The TOR pathway has been implicated in regulating cellular responses to nutrients, proliferation, translation, transcription, autophagy, and ribosome biogenesis. Here we identified two homologues of S. cerevisiae Tor proteins, CNAG_06642 (Tor1) and CNAG_05220 (Tlk1, TOR-like kinase 1), in Cryptococcus neoformans causing a life-threatening fungal meningoencephalitis. Both Tor1 and Tlk1 have rapamycin-binding (RB) domains but Tlk1 has truncated RB form. To study the TOR-signaling pathway in the fungal pathogen, we attempt to construct the tor1Δ and tlk1Δ mutants and phenotypically analyze them. Although we failed to construct the tor1Δ mutant, we successfully construct the tlk1Δ mutant. The tlk1Δ mutant does not exhibit any discernable phenotypes, suggesting that Tlk1 is dispensable in C. neoformans. The essentiality of TOR1 is independently confirmed by constructing the TOR1 promoter replacement strain by using a copper transporter 4 (CTR4) promoter and the TOR1/tor1 heterozygous mutant in diploid C. neoformans strain background followed by sporulation analysis. To further analyze the function of Tor1, we construct TOR1 overexpression mutant using a constitutively active histone H3 in C. neoformans. We find that the Tor1 overexpression mutant is resistant to rapamycin but the tlk1Δ mutant does not exhibit any altered resistance to rapamycin, further confirming that Tor1, but not Tlk1, is critical for TOR signaling. Furthermore, we found that Tor1 is involved in response to diverse stresses, including genotoxic stress, oxidative stress, thermo-stress, antifungal drug treatment, and production of melanin. To identify any TOR-related transcription factors, we screened C. neoformans transcription factor library that we constructed in our previous study and identified several potential downstream factors of Tor1, including Atf1, Crg1 and Bzp3. In conclusion, the current study provides insight into the role of the TOR signaling pathway in human fungal pathogens as well as C. neoformans.

Keywords: fungal pathogen, serine/threonine kinase, target of rapamycin, transcription factor

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Authors: Shweta Singh, Sudaman Katti

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The most well-known sequence models make use of complex recurrent neural networks in an encoder-decoder configuration. The model used in this research makes use of a transformer, which is based purely on a self-attention mechanism, without relying on recurrence at all. More specifically, encoders and decoders which make use of self-attention and operate based on a memory, are used. In this research work, results for various 3D visual and non-visual reinforcement learning tasks designed in Unity software were obtained. Convolutional neural networks, more specifically, nature CNN architecture, are used for input processing in visual tasks, and comparison with standard long short-term memory (LSTM) architecture is performed for both visual tasks based on CNNs and non-visual tasks based on coordinate inputs. This research work combines the transformer architecture with the proximal policy optimization technique used popularly in reinforcement learning for stability and better policy updates while training, especially for continuous action spaces, which are used in this research work. Certain tasks in this paper are long horizon tasks that carry on for a longer duration and require extensive use of memory-based functionalities like storage of experiences and choosing appropriate actions based on recall. The transformer, which makes use of memory and self-attention mechanism in an encoder-decoder configuration proved to have better performance when compared to LSTM in terms of exploration and rewards achieved. Such memory based architectures can be used extensively in the field of cognitive robotics and reinforcement learning.

Keywords: convolutional neural networks, reinforcement learning, self-attention, transformers, unity

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Authors: Gyula I. Tóth, Shaho Abdalla

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Even though numerical simulations indeed have a significant precursory/supportive role in exploring the disordered phase displaying no long-range order in pattern formation models, studying the stability properties of this phase and determining the order of the ordered-disordered phase transition in these models necessitate an analytical description of the disordered phase. First, we will present the results of a comprehensive statistical analysis of a large number (1,000-10,000) of numerical simulations in the Swift-Hohenberg model, where the bulk disordered (or amorphous) phase is stable. We will show that the average free energy density (over configurations) converges, while the variance of the energy density vanishes with increasing system size in numerical simulations, which suggest that the disordered phase is a thermodynamic phase (i.e., its properties are independent of the configuration in the macroscopic limit). Furthermore, the structural analysis of this phase in the Fourier space suggests that the phase can be modeled by a colored isotropic Gaussian noise, where any instant of the noise describes a possible configuration. Based on these results, we developed the general mathematical framework of finding a pool of solutions to partial differential equations in the sense of continuous probability measure, which we will present briefly. Applying the general idea to the Swift-Hohenberg model we show, that the amorphous phase can be found, and its properties can be determined analytically. As the general mathematical framework is not restricted to continuum theories, we hope that the proposed methodology will open a new chapter in studying disordered phases.

Keywords: fundamental theory, mathematical physics, continuum models, analytical description

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Authors: Hamdy Khamis Korayem, Manal Yehia Tayel, Abeer Shawky El Hadedy, Emmanuel Kamal Aziz Saba, Shimaa Badr Abdelnaby Badr

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The aim of the current study was to demonstrate whether serum Interleukin-18 (IL-18) is increased in rheumatoid arthritis (RA) and its correlation with disease activity, functional disability and quality of life in RA patients. The study included 30 RA patients and 20 healthy normal control subjects. The RA patients were diagnosed according to the 2010 ACR/EULAR classification criteria for RA with the exclusion of those who had diabetes mellitus, endocrine disorders, associated rheumatologic diseases, viral hepatitis B or C and other diseases with increased serum IL-18 level. All patients were subjected to clinical evaluation of the musculoskeletal system. Disease activity was assessed by disease activity score 28 with 4 variables (DAS 28). Functional disability was assessed by health assessment questionnaire disability index (HAQ-DI). The quality of life was assessed by Short form-36 (SF-36) questionnaire. Radiological assessment of both hands and feet by Sharp/van der Heijde (SvH) scoring method. Laboratory parameters including erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), rheumatoid factor (RF) and anti-cyclic citrullinated peptide antibody (ACPA) were assessed in patients and serum level of IL-18 in both patients and control subjects. There was no statistically significant difference between patient and control group as regards age and sex. Among patients, 29 % were females and the age range was between 25 to 55 years. Extra-articular manifestations were presented in 56.7% of the patients. The mean of DAS 28 score was 5.73±1.46 and that of HAQ-DI was 1.22±0.72 while that of SF-36 was 40.03±13.96. The level of serum IL-18 was significantly higher in patients than in the control subjects (P= 0.030). Serum IL-18 was correlated with ACPA among the patient group. There were no statistically significant correlations between serum IL-18 and DAS28, HAQ-DI, SF-36, total SvH score and the other laboratory results. In conclusion, IL-18 is significantly higher in RA patient than in healthy control subjects and positively correlated with ACPA level. IL-18 is associated with extra-articular manifestations. However, it is not correlated with other laboratory parameters, disease activity, functional disability, quality of life nor radiological severity.

Keywords: disease activity score, Interleukin-18, quality of life assessment, rheumatoid arthritis

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Authors: Olaide O. Wahab, Lukman O. Olasunkanmi, Krishna K. Govender, Penny P. Govender

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The economic and environmental challenges associated with azo disperse dyes applications are due to poor aqueous solubility and low degradation tendency which stems from low chemical reactivity. Poor aqueous solubility property of this group of dyes necessitates the use of dispersing agents which increase operational costs and also release toxic chemical components into the environment, while their low degradation tendency is due to the high stability of the azo functional group (-N=N-) in their chemical structures. To address these problems, this study investigated theoretically the effects of some polar substituents on the aqueous solubility and reactivity properties of disperse yellow (DY) 119 dye with a view to theoretically develop new azo disperse dyes with improved solubility in water and higher degradation tendency in the environment using DMol³ computational code. All calculations were carried out using the Becke and Perdew version of Volsko-Wilk-Nusair (VWN-BP) level of density functional theory in conjunction with double numerical basis set containing polarization function (DNP). The aqueous solubility determination was achieved with conductor-like screening model for realistic solvation (COSMO-RS) in conjunction with known empirical solubility model, while the reactivity was predicted using frontier molecular orbital calculations. Most of the new derivatives studied showed evidence of higher aqueous solubility and degradation tendency compared to the parent dye. We conclude that these derivatives are promising alternative dyes for more economic and environmental benign dyeing practice and therefore recommend them for synthesis.

Keywords: aqueous solubility, azo disperse dye, degradation, disperse yellow 119, DMol³, reactivity

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Authors: Iwona Cieślik, Władysław Migdał, Kinga Topolska, Ewa Cieślik

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The consumption of fish is recommended as a means of preventing serious diseases, especially cardiovascular problems. Fish is known to be a valuable source of protein (rich in essential amino acids), unsaturated fatty acids, fat-soluble vitamins, macro- and microelements. However, it can also contain several contaminants (e.g. pesticides, heavy metals) that may pose considerable risks for humans. Among others, pesticide are of special concern. Their widespread use has resulted in the contamination of environmental compartments, including water. The occurrence of pesticides in the environment is a serious problem, due to their potential toxicity. Therefore, a systematic monitoring is needed. The aim of the study was to determine the organochlorine and organophosphate pesticide residues in fish muscle tissues of the pike (Esox lucius, L.) and the rainbow trout (Oncorhynchus mykkis, Walbaum) by a modified QuEChERS (Quick, Easy, Cheap, Effective, Rugged and Safe) method, using Gas Chromatography Quadrupole Mass Spectrometry (GC/Q-MS), working in selected-ion monitoring (SIM) mode. The analysis of α-HCH, β-HCH, lindane, diazinon, disulfoton, δ-HCH, methyl parathion, heptachlor, malathion, aldrin, parathion, heptachlor epoxide, γ-chlordane, endosulfan, α-chlordane, o,p'-DDE, dieldrin, endrin, 4,4'-DDD, ethion, endrin aldehyde, endosulfan sulfate, 4,4'-DDT, and metoxychlor was performed in the samples collected in the Carp Valley (Malopolska region, Poland). The age of the pike (n=6) was 3 years and its weight was 2-3 kg, while the age of the rainbow trout (n=6) was 0.5 year and its weight was 0.5-1.0 kg. Detectable pesticide (HCH isomers, endosulfan isomers, DDT and its metabolites as well as metoxychlor) residues were present in fish samples. However, all these compounds were below the limit of quantification (LOQ). The other examined pesticide residues were below the limit of detection (LOD). Therefore, the levels of contamination were - in all cases - below the default Maximum Residue Levels (MRLs), established by Regulation (EC) No 396/2005 of the European Parliament and of the Council. The monitoring of pesticide residues content in fish is required to minimize potential adverse effects on the environment and human exposure to these contaminants.

Keywords: contaminants, fish, pesticides residues, QuEChERS method

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Authors: U. Ali Rahoma, Nabil Esawy, Fawzia Ibrahim Moursy, A. H. Hassan, Samy A. Khalil, Ashraf S. Khamees

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The design of any solar energy conversion system requires the knowledge of solar radiation data obtained over a long period. Satellite data has been widely used to estimate solar energy where no ground observation of solar radiation is available, yet there are limitations on the temporal coverage of satellite data. Reanalysis is a “retrospective analysis” of the atmosphere parameters generated by assimilating observation data from various sources, including ground observation, satellites, ships, and aircraft observation with the output of NWP (Numerical Weather Prediction) models, to develop an exhaustive record of weather and climate parameters. The evaluation of the performance of reanalysis datasets (ERA-5) for North Africa against high-quality surface measured data was performed using statistical analysis. The estimation of global solar radiation (GSR) distribution over six different selected locations in North Africa during ten years from the period time 2011 to 2020. The root means square error (RMSE), mean bias error (MBE) and mean absolute error (MAE) of reanalysis data of solar radiation range from 0.079 to 0.222, 0.0145 to 0.198, and 0.055 to 0.178, respectively. The seasonal statistical analysis was performed to study seasonal variation of performance of datasets, which reveals the significant variation of errors in different seasons—the performance of the dataset changes by changing the temporal resolution of the data used for comparison. The monthly mean values of data show better performance, but the accuracy of data is compromised. The solar radiation data of ERA-5 is used for preliminary solar resource assessment and power estimation. The correlation coefficient (R2) varies from 0.93 to 99% for the different selected sites in North Africa in the present research. The goal of this research is to give a good representation for global solar radiation to help in solar energy application in all fields, and this can be done by using gridded data from European Centre for Medium-Range Weather Forecasts ECMWF and producing a new model to give a good result.

Keywords: solar energy, solar radiation, ERA-5, potential energy

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Authors: Ahsan R. Khokhar, Fizza Hassan

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Alkali-Silica Reaction (ASR) has been recognized as a potential cause of concrete degradation in the world since the 1940s. In Pakistan, mega hydropower structures like dams, weirs constructed from aggregates extracted from a local riverbed exhibited different levels of alkali-silica reactivity over an extended service period. The concrete expansion potential due to such aggregates has been categorized as slow-reactive. Apart from hydropower structures, ASR existence has been identified in the concrete structural elements of a Textile Mill building which used aggregates extracted from the nearby riverbed. The original structure of the Textile Mill was erected in the 80s with the addition of a textile ‘sizing and wrapping’ hall constructed in the 90s. In the years to follow, intensive spalling was observed in the structural members of the subject hall; enough to threat to the overall stability of the building. Limitations such as incomplete building data posed hurdles during the detailed structural investigation. The paper lists observations made while assessing the extent of damage and its effect on the building hall structure. Core testing and Petrographic tests were carried out as per the ASTM standards for strength degradation analysis followed by the identifying its root cause. Results confirmed significant structural strength reduction because of ASR which necessitated the formulation of an immediate re-strengthening solution. The paper also discusses the possible tracks of rehabilitative measures which are being adapted to stabilize the structure and seize further concrete expansion.

Keywords: Alkali-Silica Reaction (ASR), concrete strength degradation, damage assessment, damage evaluation

Procedia PDF Downloads 129