Search results for: coated reinforcement

Authors: Abhishek Sraw, Amit Sobti, Yamini Pandey, R. K. Wanchoo, Amrit Pal Toor

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Monocrotophos (MCP) is a widely used pesticide in India, which belong to an extremely toxic organophosphorus family, is persistent in nature and its toxicity is widely reported in all environmental segments in the country. Advanced Oxidation Process (AOP) is a promising solution to the problem of water pollution. TiO₂ is being widely used as a photocatalyst because of its many advantages, but it has a large band gap, due to which it is modified using metal and nonmetal dopant to make it active under sunlight and visible light. The use of nanosized powdered catalysts makes the recovery process extremely complicated. Hence the aim is to use low cost, easily available, eco-friendly clay material in form of bead as the support for the immobilization of catalyst, to solve the problem of post-separation of suspended catalyst from treated water. A recirculation type photocatalytic reactor (RTPR), using ultraviolet light emitting source (blue black lamp) was designed which work effectively for both suspended catalysts and catalyst coated clay beads. The bare, TiO₂ and W-TiO₂ coated clay beads were characterized by scanning electron microscopy (SEM), electron dispersive spectroscopy (EDS) and N₂ adsorption–desorption measurements techniques (BET) for their structural, textural and electronic properties. The study involved variation of different parameters like light conditions, recirculation rate, light intensity and initial MCP concentration under UV and sunlight for the degradation of MCP. The degradation and mineralization studies of the insecticide solution were performed using UV-Visible spectrophotometer, and COD vario-photometer and GC-MS analysis respectively. The main focus of the work lies in checking the recyclability of the immobilized TiO₂ over clay beads in the developed RTPR up to 30 continuous cycles without reactivation of catalyst. The results demonstrated the economic feasibility of the utilization of developed RTPR for the efficient purification of pesticide polluted water. The prepared TiO₂ clay beads delivered 75.78% degradation of MCP under UV light with negligible catalyst loss. Application of W-TiO₂ coated clay beads filled RTPR for the degradation of MCP under sunlight, however, shows 32% higher degradation of MCP than the same system based on undoped TiO₂. The COD measurements of TiO₂ coated beads led to 73.75% COD reduction while W-TiO₂ resulted in 87.89% COD reduction. The GC-MS analysis confirms the efficient breakdown of complex MCP molecules into simpler hydrocarbons. This supports the promising application of clay beads as a support for the photocatalyst and proves its eco-friendly nature, excellent recyclability, catalyst holding capacity, and economic viability.

Keywords: immobilized clay beads, monocrotophos, recirculation type photocatalytic reactor, TiO₂

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Authors: Nusaiba Al-Nemrawi, Belal Al-Husein

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Methotrexate (MTX) is a stoichiometric inhibitor of dihydrofolate reductase, which is essential for DNA synthesis. MTX is a chemotherapeutic agent used for treating many types of cancer cells. However, cells’ resistant to MTX is very common and its pharmacokinetic behavior is highly problematic. of MTX within tumor cells, we propose encapsulation of antitumor drugs in nanoparticulated systems. Chitosan (CS) is a naturally occurring polymer that is biocompatibe, biodegradable, non-toxic, cationic and bioadhesive. CS nanoparticles (CS-NPs) have been used as drug carrier for targeted delivery. Titanium dioxide (TiO2), a natural mineral oxide, which is used in biomaterials due to its high stability and antimicrobial and anticorrosive properties. TiO2 showed a potential as a tumor suppressor. In this study a new formulation of MTX loaded in CS NPs (CS-MTX NPs) and coated with Titanium oxide (TiO2) was prepared. The mean particle size, zeta potential, polydispersity index were measured. The interaction between CS NPs and TiO2 NPs was confirmed using FTIR and XRD. CS-MTX NPs was studied in vitro using the tumor cell line MCF-7 (human breast cancer). The results showed that CS-MTX has a size around 169 nm and as they were coated with TiO2, the size ranged between and depending on the ratio of CS-MTX to TiO2 ratio used in the preparation. All NPs (uncoated and coated carried positive charges and were monodispersed. The entrapment efficacy was around 65%. Both FTIR and XRD proved that TiO2 interacted with CS-MTX NPs. The drug invitro release was controlled and sustained over days. Finally, the studied in vitro using the tumor cell line MCF-7 suggested that combining nanomaterials with anticancer drugs CS-MTX NPs may be more effective than free MTX for cancer treatment. In conclusion, the combination of CS-MTX NPs and TiO2 NPs showed excellent time-dependent in vitro antitumor behavior, therefore, can be employed as a promising anticancer agent to attain efficient results towards MCF-7 cells.

Keywords: Methotrexate, Titanium dioxide, Chitosan nanoparticles, cancer

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Authors: Migena Mana, Ahmed Khalid Syed, Abdul Malik, Nikhil Cherian

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In recent years, advancements in deep learning enabled researchers to tackle the problem of self-driving cars. Car companies use huge datasets to train their deep learning models to make autonomous cars a reality. However, this approach has certain drawbacks in that the state space of possible actions for a car is so huge that there cannot be a dataset for every possible road scenario. To overcome this problem, the concept of reinforcement learning (RL) is being investigated in this research. Since the problem of autonomous driving can be modeled in a simulation, it lends itself naturally to the domain of reinforcement learning. The advantage of this approach is that we can model different and complex road scenarios in a simulation without having to deploy in the real world. The autonomous agent can learn to drive by finding the optimal policy. This learned model can then be easily deployed in a real-world setting. In this project, we focus on three RL algorithms: Q-learning, Deep Deterministic Policy Gradient (DDPG), and Proximal Policy Optimization (PPO). To model the environment, we have used TORCS (The Open Racing Car Simulator), which provides us with a strong foundation to test our model. The inputs to the algorithms are the sensor data provided by the simulator such as velocity, distance from side pavement, etc. The outcome of this research project is a comparative analysis of these algorithms. Based on the comparison, the PPO algorithm gives the best results. When using PPO algorithm, the reward is greater, and the acceleration, steering angle and braking are more stable compared to the other algorithms, which means that the agent learns to drive in a better and more efficient way in this case. Additionally, we have come up with a dataset taken from the training of the agent with DDPG and PPO algorithms. It contains all the steps of the agent during one full training in the form: (all input values, acceleration, steering angle, break, loss, reward). This study can serve as a base for further complex road scenarios. Furthermore, it can be enlarged in the field of computer vision, using the images to find the best policy.

Keywords: autonomous driving, DDPG (deep deterministic policy gradient), PPO (proximal policy optimization), reinforcement learning

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Authors: Galo D. Soria, Jenny S. Casame, Eddy F. Pazmino

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In Ecuador, mining operations have significantly impacted water sources. Artisanal mining extensively relies in mercury amalgamation. Mercury is a neurotoxic substance even at low concentrations. The objective of this investigation is to exploit Hg-removal capacity of sulfur-limonene polysulfide (SLP), which is a low-cost polymer, in order to prepare granular media (sand) coated with SLP to be used in laboratory scale column-filtration systems. Preliminary results achieved 85% removal of Hg⁺⁺ from synthetic effluents using 20-cm length and 5-cm diameter columns at 119m/day average pore water velocity. During elution of the column, the SLP-coated sand indicated that Hg⁺⁺ is permanently fixed to the collector surface, in contrast, uncoated sand showed reversible retention in Hg⁺⁺ in the solid phase. Injection of 50 pore volumes decreased Hg⁺⁺ removal to 46%. Ongoing work has been focused in optimizing the synthesis of SLP and the polymer content in the porous media coating process to improve Hg⁺⁺ removal and extend the lifetime of the column-filter.

Keywords: column-filter, mercury, mining, polysulfide, water treatment

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Authors: T. Sakamoto, S. Kainuma

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Firstly, in order to examine the influence of the remaining amount of the rust on the coating film durability, the accelerated deterioration tests were carried out. In order to prepare test specimens, uncoated steel plates were corroded by the Salt Spray Test (SST) prior to the accelerated deterioration tests, and then the prepared test specimens were coated by epoxy resin and phthalic acid resin each of which has different gas-barrier performance. As the result, it was confirmed that the under-film corrosion occurred in the area and the adjacency to great quantities of salt exists in the rust, and did not occurred in the specimen which was applied the epoxy resin paint after the surface preparation by the power tool. Secondly, in order to clarify the influence of the corrosive factors on the coating film durability, outdoor exposure tests were conducted for one year on actual steel bridge located at a coastal area. The tests specimens consist of coated corroded plates and the uncoated steel plates, and they were installed on the different structural members of the bridge for one year. From the test results, the uncoated steel plates which were installed on the underside of the member are easily corrosive and had highly correlation with the amount of salt in the rust. On the other hand, the most corrosive under-film steel was the vertical surface of the web plate. Thus, it was confirmed that under-film corrosion rate was not match with corrosion rate of the uncoated steel. Consequently, it is estimated that the main factors of under-film corrosion are gas-barrier property of coating film and corrosive factors such as water vapor and temperature. The salt which significantly corrodes the uncoated steel plate is not directly related to the under-film corrosion.

Keywords: accelerated deterioration test, coating durability, environmental factor, under-film corrosion

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Authors: Mahboubeh Kabiri, Saba Aslani

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Among various approaches used for the treatment of cardiovascular diseases, the occlusion of the small-diameter vascular graft (SDVG) is still an unresolved problem which seeks further research to address them. Though autografts are now the gold standards to be replaced for blocked coronary arteries, they suffer from inadequate quality and quantity. On the other hand, the major problems of the tissue engineered grafts are thrombosis and intimal hyperplasia. Provision of a suitable spatiotemporal release pattern of anticoagulant agents such as heparin and aspirin can be a step forward to overcome such issues . Herein, we fabricated electrospun scaffolds from FDA (Food and Drug Administration) approved poly-L-lactic acid (PLLA) with aspirin loaded into the nanofibers. Also, we surface coated the scaffolds with Amniotic Membrane lysate as a source for natural elastic polymers and a mimic of endothelial basement membrane. The scaffolds were characterized thoroughly structurally and mechanically for their morphology, fiber orientation, tensile strength, hydrophilicity, cytotoxicity, aspirin release and cell attachment support. According to the scanning electron microscopy (SEM) images, the size of fibers ranged from 250 to 500 nm. The scaffolds showed appropriate tensile strength expected for vascular grafts. Cellular attachment, growth, and infiltration were proved using SEM and MTT (3-(4,5-Dimethylthiazol-2-Yl)-2,5-Diphenyltetrazolium Bromide) assay. Drug-loaded scaffolds showed a sustained release profile of aspirin in 7 days. An enhanced cytocompatibility was observed in AM-coated electrospun PLLA fibers compared to uncoated scaffolds. Our results together indicated that AM lysate coated ASA releasing scaffolds have promising potentials for development of a biocompatible SDVG.

Keywords: vascular tissue engineering, vascular grafts, anticoagulant agent, aspirin, amniotic membrane

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Authors: Hatem I. Mokhtar, Randa A. Abd-El-Salam, Ghada M. Hadad

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An improved nano-composite of self-doped polyaniline nanofibers and silica-coated magnetite nanoparticles were prepared and evaluated for suitability to magnetic dispersive micro solid-phase extraction. The work focused on optimization of the composite capacity to extract four fluoroquinolones (FQs) antibiotics, ciprofloxacin, enrofloxacin, danofloxacin, and difloxacin from water and improvement of composite stability towards acid and atmospheric degradation. Self-doped polyaniline nanofibers were prepared by oxidative co-polymerization of aniline with anthranilic acid. Magnetite nanopariticles were prepared by alkaline co-precipitation and coated with silica by silicate hydrolysis on magnetite nanoparticles surface at pH 6.5. The composite was formed by self-assembly by mixing self-doped polyaniline nanofibers with silica-coated magnetite nanoparticles dispersions in ethanol. The composite structure was confirmed by transmission electron microscopy (TEM). Self-doped polyaniline nanofibers and magnetite chemical structures were confirmed by FT-IR while silica coating of the magnetite was confirmed by Energy Dispersion X-ray Spectroscopy (EDS). Improved stability of the composite magnetic component was evidenced by resistance to degrade in 2N HCl solution. The adsorption capacity of self-doped polyaniline nanofibers based composite was higher than previously reported corresponding composite prepared from polyaniline nanofibers instead of self-doped polyaniline nanofibers. Adsorption-pH profile for the studied FQs on the prepared composite revealed that the best pH for adsorption was in range of 6.5 to 7. Best extraction recovery values were obtained at pH 7 using phosphate buffer. The best solvent for FQs desorption was found to be 0.1N HCl in methanol:water (8:2; v/v) mixture. 20 mL of Spiked water sample with studied FQs were preconcentrated using 4.8 mg of composite and resulting extracts were analysed by HPLC-UV method. The prepared composite represented a suitable adsorbent phase for magnetic dispersive micro-solid phase application.

Keywords: fluoroquinolones, magnetic dispersive micro extraction, nano-composite, self-doped polyaniline nanofibers

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Authors: A. Bouhaloufa, T. Kadri, S. Zouaoui, A. Belhacene

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To put more durable bridges, it is important to maintain existing structures, rather than investing in new structures. Instead of demolishing the old bridge and replace them with new, we must preserve and upgrade using better methods of diagnosis, auscultation and repair, the interest of this work is to increase the bearing capacity bridges damaged by additional prestressing, this type of reinforcement is growing continuously. In addition to excellent static strength, prestressing also has a very high resistance to fatigue, so it is suitable to solve the problem of failure of the bearing capacity of the bridges. This failure often comes to the development of overloads in quantity and quality, that is our daily traffic has increased and become very complicated, on the other hand its constituents are advanced in weight and speed and therefore almost all old bridges became unable to support the movement of the latter and remain disabled to all these problems. The main purpose of this work includes the following three aspects: - Determination of the main diseases and factors affecting the deterioration of bridges in Algeria, - Evaluation of the bearing capacity of bridges, - Proposal technical reinforcement to improve the bearing capacity of a degraded structure.

Keywords: bridges, repair, auscultation, diagnosis, pathology, additional prestressing

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Authors: Ki-Seok Kwon, Heung-Youl Kim

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This research evaluated fire resistances of high-strengthened reinforced concrete (RC) column, spiral wire rope which applied with 60, and 100MPa. The fire resistance test of RC column with loading condition was conducted following the ISO 834 (3 hours). This experiment set mixing of fiber (PP fiber, Steel fiber) and types of horizontal reinforcement as a variable of reinforcement method. The fire resistance test measured the main steel bar’s max and mean temperatures also the shrinkage and shrinking ratio of columns(500 X 500 X 3,000mm) with loadings. As a result, the specimen of 60MPa attained three hours fire resistance with only spiral wire rope. Also, the specimen of 100MPa must be reinforced with fibers and spiral wire rope to attain three hours fire resistance.

Keywords: reinforced concrete column, high strength concrete, wire rope, fire resistance test

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Authors: Metwally Abdel Aziz Ahmed, Ahmed Shaban Abdel Hay Gabr, Inas Mohamed Saleh

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The main objective of structural design is to ensure safety and functional performance requirements of a structural system for its target reliability levels. In this study, the reliability index for the reinforcement concrete slender columns with rectangular cross section is studied. The variable parameters studied include the loads, the concrete compressive strength, the steel yield strength, the dimensions of concrete cross-section, the reinforcement ratio, and the location of steel placement. Risk analysis program was used to perform the analytical study. The effect of load eccentricity on the reliability index of reinforced concrete slender column was studied and presented. The results of this study indicate that the good quality control improve the performance of slender reinforced columns through increasing the reliability index β.

Keywords: reliability, reinforced concrete, safety, slender column

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Authors: Güzi̇n Ti̇rkeş, Özge Teki̇n, Kerem Kurtuluş, Y. Yekta Yurtseven, Murat Baran

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A scanning electron microscope (SEM) is a type of electron microscope mainly used in nanoscience and nanotechnology areas. Automatic image recognition and classification are among the general areas of application concerning SEM. In line with these usages, the present paper proposes a deep learning algorithm that classifies SEM images into nine categories by means of an online application to simplify the process. The NFFA-EUROPE - 100% SEM data set, containing approximately 21,000 images, was used to train and test the algorithm at 80% and 20%, respectively. Validation was carried out using a separate data set obtained from the Middle East Technical University (METU) in Turkey. To increase the accuracy in the results, the Inception ResNet-V2 model was used in view of the Fine-Tuning approach. By using a confusion matrix, it was observed that the coated-surface category has a negative effect on the accuracy of the results since it contains other categories in the data set, thereby confusing the model when detecting category-specific patterns. For this reason, the coated-surface category was removed from the train data set, hence increasing accuracy by up to 96.5%.

Keywords: convolutional neural networks, deep learning, image classification, scanning electron microscope

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Authors: Vivian A. Galindo, Maria C. Galvis, Jaime R. Obando, Alvaro Guarin

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In Colombia, most of the roads of the national tertiary road network are unpaved roads with granular rolling surface. These are very important ways of guaranteeing the mobility of people, products, and inputs from the agricultural sector from the most remote areas to urban centers; however, it has not paid much attention to the search for alternatives to avoid the occurrence of deteriorations that occur shortly after its commissioning. In recent years, geosynthetics have been used satisfactorily to reinforce unpaved roads on soft soils, with geotextiles and geogrids being the most widely used. The interaction of the geogrid and the aggregate minimizes the lateral movement of the aggregate particles and increases the load capacity of the material, which leads to a better distribution of the vertical stresses, consequently reducing the vertical deformations in the subgrade. Taking into account the above, the research aimed at the mechanical behavior of the granular material, used in unpaved roads with and without the presence of geogrids, from the development of laboratory tests through the loaded wheel tester (LWT). For comparison purposes, the reinforced conditions and traffic conditions to which this type of material can be accessed in practice were simulated. In total four types of geogrids, were tested with granular material; this means that five test sets, the reinforced material and the non-reinforced control sample were evaluated. The results of the numbers of load cycles and depth rutting supported by each test body showed the influence of the properties of the reinforcement on the mechanical behavior of the assembly and the significant increases in the number of load cycles of the reinforced specimens in relation to those without reinforcement.

Keywords: geosynthetics, load wheel tester LWT, tertiary roads, unpaved road, vertical deformation

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Authors: Natália C. C. Lobato, Ângela M. Ferreira, Marcelo B. Mansur

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In solvent extraction operations, large sedimentation areas in the mixer-settler are required when the disengagement of the aqueous and the organic phases is slow and/or difficult. The use of a magnetic organic liquid (also known as ferrofluid), consisting of magnetite nanoparticles coated by oleic acid dispersed in the organic diluent, has proven successful to speed up phase disengagement. The method, however, has never been used industrially; therefore, the aim of this study is to raise its main limitations. Tests were carried out using a ferrofluid containing 30 g/l of magnetite dissolved in commercial aliphatic kerosene Exxsol D80. The efficiency of cobalt extraction ([Co] = 1 g/l) with 10% v/v Cyanex 272 (bis-2,4,4-trimethylpentyl phosphinic acid) at changing pH of the aqueous phase (2 to 7) was found unaffected in the conditions studied. However, the chemical resistance of the ferrofluid in contact with deionized water at changing acidity (from 10-7 to 2 mol/l) revealed that the nanoparticles are not resistant when contacted to aqueous solutions with a pH ≤ 2. Such result represents a serious limitation to the applicability of the method mainly to hydrometallurgical systems because solvent extraction operations are normally done in acid conditions, therefore more effective strategies to coat the particles are required.

Keywords: magnetic solvent extraction, oleic acid, magnetite nanoparticles, cyanex 272

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Authors: Masato Nishi, Tetsushi Kaburagi, Masashi Kurose, Tei Hirashima, Tetsusei Kurasiki

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The process of thermoforming a carbon fiber reinforced thermoplastic (CFRTP) has increased its presence in the automotive industry for its wide applicability to the mass production car. A non-isothermal forming for CFRTP can shorten its cycle time to less than 1 minute. In this paper, the textile reinforcement FE model which the authors proposed in a previous work is extended to the CFRTP model for non-isothermal forming simulation. The effect of thermoplastic is given by adding shell elements which consider thermal effect to the textile reinforcement model. By applying Reuss model to the stress calculation of thermoplastic, the proposed model can accurately predict in-plane shear behavior, which is the key deformation mode during forming, in the range of the process temperature. Using the proposed model, thermoforming simulation was conducted and the results are in good agreement with the experimental results.

Keywords: carbon fiber reinforced thermoplastic, finite element analysis, pre-impregnated textile composite, non-isothermal forming

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Authors: Nihal Murali, Kunal Gupta, Surekha Bhanot

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Training of artificial neural networks (ANNs) using reinforcement learning (RL) techniques is being widely discussed in the robot learning literature. The high model complexity of ANNs along with the model-free nature of RL algorithms provides a desirable combination for many robotics applications. There is a huge need for algorithms that generalize using raw sensory inputs, such as vision, without any hand-engineered features or domain heuristics. In this paper, the standard control problem of line following robot was used as a test-bed, and an ANN controller for the robot was trained on images from a live video feed using Q-learning. A virtual agent was first trained in simulation environment and then deployed onto a robot’s hardware. The robot successfully learns to traverse a wide range of curves and displays excellent generalization ability. Qualitative analysis of the evolution of policies, performance and weights of the network provide insights into the nature and convergence of the learning algorithm.

Keywords: artificial neural networks, q-learning, reinforcement learning, robot learning

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Authors: Sanjay Singh, Parameswara Rao Vuddanda

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The aim of the present study is study the factual benefit of nano size and surface coating of p-gp efflux inhibitor on enhancement of bioavailability of Berberine chloride (BBR); a p-gp substrate. In addition, 28 days sub acute oral toxicity study was also conducted to assess the toxicity of the formulation on chronic administration. BBR loaded polymeric nanoparticles (BBR-NP) were prepared by nanoprecipitation method. BBR NP were surface coated (BBR-SCNP) with the 1 % w/v of vitamin E TPGS. For bioavailability study, total five groups (n=6) of rat were treated as follows first; pure BBR, second; physical mixture of BBR, carrier and vitamin E TPGS, third; BBR-NP, fourth; BBR-SCNP and fifth; BBR and verapamil (widely used p-gp inhibitor). Blood was withdrawn at pre-set timing points in 24 hrs study and drug was quantified by HPLC method. In oral chronic toxicity study, total four groups (n=6) were treated as follows first (control); water, second; pure BBR, third; BBR surface coated nanoparticles and fourth; placebo BBR surface coated nanoparticles. Biochemical levels of liver (AST, ALP and ALT) and kidney (serum urea and creatinine) along with their histopathological studies were also examined (0-28 days). The AUC of BBR-SCNP was significantly 3.5 folds higher compared to all other groups. The AUC of BBR-NP was 3.23 and 1.52 folds higher compared to BBR solution and BBR with verapamil group, respectively. The physical mixture treated group showed slightly higher AUC than BBR solution treated group but significantly low compared to other groups. It indicates that encapsulation of BBR in nanosize form can circumvent P-gp efflux effect. BBR-NP showed pharmacokinetic parameters (Cmax and AUC) which are near to BBR-SCNP. However, the difference in values of T1/2 and clearance indicate that surface coating with vitamin E TPGS not only avoids the P-gp efflux at its absorption site (intestine) but also at organs which are responsible for metabolism and excretion (kidney and liver). It may be the reason for observed decrease in clearance of BBR-SCNP. No toxicity signs were observed either in biochemical or histopathological examination of liver and kidney during toxicity studies. The results indicate that administration of BBR in surface coated nanoformulation would be beneficial for enhancement of its bioavailability and longer retention in systemic circulation. Further, sub acute oral dose toxicity studies for 28 days such as evaluation of intestine, liver and kidney histopathology and biochemical estimations indicated that BBR-SCNP developed were safe for long use.

Keywords: bioavailability, berberine nanoparticles, p-gp efflux inhibitor, nanoprecipitation method

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Authors: Rafik Balti, Mohamed Ben Mansour, Abdellah Arhaliass, Anthony Masse

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Unfortunately, shrimps are highly perishable and they start deteriorating immediately after death owing to their high water content and nutritional components. Currently, there has been an increasing interest in bioactive edible films and coatings to preserve the freshness and quality of foods. In this study, active edible coatings from microalgal exopolysaccharides (EPS) enriched with different concentrations of Red Seaweed Extract (RSE) (0.5, 1 and 1.5 % (w/v)) were developed and their effects on the quality changes of white shrimp during refrigerated storage (4 ± 1 °C) were examined over a period of 8 days. The control and the coated shrimp samples were analyzed periodically for microbiological (total viable bacteria, psychrotrophic bacteria, and enterobacteriaceae counts), chemical (pH, TVB-N, TMA-N, PV, TBARS), textural and sensory characteristics. The results indicated that the coating with a mixture of EPS and RSE could significantly decrease the total volatile basic nitrogen (TVB-N), trimethylamine (TMA) and thiobarbituric acid reactive substances (TBARS) (p < 0.05). With storage, EPS coatings containing RSE at both levels (1 and 1.5 %) were more effective in inhibiting the microbial species studied, specially psychrotrophic bacteria. Also, EPS + RSE coated samples had lower polyphenol oxidase (PPO) activity and lipid oxidation (p < 0.05) toward the end of storage. Textural and color properties of coated shrimp were generally more acceptable. Sensory scores indicated no significant changes in all samples during storage. The obtained results indicate that the edible EPS coating solutions enriched with RSE have noticeable effects on the quality and shelf life of shrimps when compared to control group. Finally, the present work demonstrates the effectiveness of EPS enriched coatings, offering a promising alternative to preserve more better the quality characteristics and to extend the shelf life of shrimp during the refrigerated storage

Keywords: active coating, exopolysaccharides, red seaweed, refrigerated storage, white shrimp

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Authors: Szymon Rutkowski, Tomasz Korbak

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We present a reinforcement-learning-based method of training neural machine translation models without parallel corpora. The standard encoder-decoder approach to machine translation suffers from two problems we aim to address. First, it needs parallel corpora, which are scarce, especially for low-resource languages. Second, it lacks psychological plausibility of learning procedure: learning a foreign language is about learning to communicate useful information, not merely learning to transduce from one language’s 'encoding' to another. We instead pose the problem of learning to translate as learning a policy in a communication game between two agents: the translator and the classifier. The classifier is trained beforehand on a natural language inference task (determining the entailment relation between a premise and a hypothesis) in the target language. The translator produces a sequence of actions that correspond to generating translations of both the hypothesis and premise, which are then passed to the classifier. The translator is rewarded for classifier’s performance on determining entailment between sentences translated by the translator to disciple’s native language. Translator’s performance thus reflects its ability to communicate useful information to the classifier. In effect, we train a machine translation model without the need for parallel corpora altogether. While similar reinforcement learning formulations for zero-shot translation were proposed before, there is a number of improvements we introduce. While prior research aimed at grounding the translation task in the physical world by evaluating agents on an image captioning task, we found that using a linguistic task is more sample-efficient. Natural language inference (also known as recognizing textual entailment) captures semantic properties of sentence pairs that are poorly correlated with semantic similarity, thus enforcing basic understanding of the role played by compositionality. It has been shown that models trained recognizing textual entailment produce high-quality general-purpose sentence embeddings transferrable to other tasks. We use stanford natural language inference (SNLI) dataset as well as its analogous datasets for French (XNLI) and Polish (CDSCorpus). Textual entailment corpora can be obtained relatively easily for any language, which makes our approach more extensible to low-resource languages than traditional approaches based on parallel corpora. We evaluated a number of reinforcement learning algorithms (including policy gradients and actor-critic) to solve the problem of translator’s policy optimization and found that our attempts yield some promising improvements over previous approaches to reinforcement-learning based zero-shot machine translation.

Keywords: agent-based language learning, low-resource translation, natural language inference, neural machine translation, reinforcement learning

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Authors: Mohammad Reza Koushki Ardestani, Saeed Daneshmand, Mohammad Heydari Vini

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In the present study, AA7075/SiO2 composites have been fabricated via liquid metallurgy process. Using the degassing process, the wet ability of the molten aluminum alloys increased which improved the bonding between aluminum matrix and reinforcement (SiO2) particles. AA7075 alloy and SiO2 particles were taken as the base matrix and reinforcements, respectively. Then, contents of 2.5 and 5 wt. % of SiO2 subdivisions were added into the AA7075 matrix. To improve wettability and distribution, reinforcement particles were pre-heated to a temperature of 550°C for each composite sample. A uniform distribution of SiO2 particles was observed through the matrix alloy in the microstructural study. A hardened EN32 steel disc as the counter face was used to evaluate the wear rate pin-on-disc, a wear testing machine containing. The results showed that the wear rate of the AA/SiO2 composites was lesser than that of the monolithic AA7075 samples. Finally, The SEM worn surfaces of samples were investigated.

Keywords: Al7075, SiO₂, wear, composites, stir casting

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Authors: Parisa Ahmadi Oliaei, Seyed Abolhassan Naeini

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The knowledge of soil–reinforcement interaction parameters is particularly important in the design of reinforced soil structures. The pull-out test is one of the most widely used tests in this regard. The results of tensile tests may be very sensitive to boundary conditions, and more research is needed for a better understanding of the Pull-out response of reinforcement, so numerical analysis using the finite element method can be a useful tool for the understanding of the Pull-out response of soil-geogrid interaction. The main objective of the present study is to compare the numerical and experimental results of Pull- out a test on geogrid-reinforced sandy soils interactions. Plaxis 2D finite element software is used for simulation. In the present study, the pull-out test modeling has been done on sandy soil. The effect of geogrid hardness was also investigated by considering two different types of geogrids. The numerical results curve had a good agreement with the pull-out laboratory results.

Keywords: plaxis, pull-out test, sand, soil- geogrid interaction

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Authors: Ziying Wu, Danfeng Yan

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Multi-Access Edge Computing (MEC) is one of the key technologies of the future 5G network. By deploying edge computing centers at the edge of wireless access network, the computation tasks can be offloaded to edge servers rather than the remote cloud server to meet the requirements of 5G low-latency and high-reliability application scenarios. Meanwhile, with the development of IOV (Internet of Vehicles) technology, various delay-sensitive and compute-intensive in-vehicle applications continue to appear. Compared with traditional internet business, these computation tasks have higher processing priority and lower delay requirements. In this paper, we design a 5G-based Vehicle-Aware Multi-Access Edge Computing Network (VAMECN) and propose a joint optimization problem of minimizing total system cost. In view of the problem, a deep reinforcement learning-based joint computation offloading and task migration optimization (JCOTM) algorithm is proposed, considering the influences of multiple factors such as concurrent multiple computation tasks, system computing resources distribution, and network communication bandwidth. And, the mixed integer nonlinear programming problem is described as a Markov Decision Process. Experiments show that our proposed algorithm can effectively reduce task processing delay and equipment energy consumption, optimize computing offloading and resource allocation schemes, and improve system resource utilization, compared with other computing offloading policies.

Keywords: multi-access edge computing, computation offloading, 5th generation, vehicle-aware, deep reinforcement learning, deep q-network

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Authors: Harjot Singh Gill, Neelkanth Grover, Jwala Parshad Singla

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The main aim of this research work is to present the effect of coating on two different grades of grey cast iron using detonation spray method. Ni20Cr and Al2O3-13TiO2 powders were sprayed using detonation gun onto GI250 and GIHC substrates and the results as well as coating surface morphology of the coating is studied by XRD and SEM/EDAX analysis. The wear resistance of Ni20Cr and Al2O3-13TiO2 has been investigated on pin-on-disc tribometer using ASTM G99 standards. Cumulative wear rate and coefficient of friction (µ) were calculated under three normal load of 30N, 40N, 50N at constant sliding velocity of 1m/s. Worn out surfaces were analyzed by SEM/EDAX. The results show significant resistance to wear with Al2O3-13TiO2 coating as compared to Ni20Cr and bare substrates. SEM/EDAX analysis and cumulative wear loss bar charts clearly explain the wear behavior of coated as well as bare sample of GI250 and GIHC.

Keywords: detonation spray, grey cast iron, wear rate, coefficient of friction

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Authors: Renu Kumari, Jyotsna Dutta Majumdar

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In the present study, composite coating consisting of hydroxyapatite (HA) + 50 wt% TiO2 has been developed on Ti-6Al-4V substrate by plasma spray deposition technique. Followed by plasma spray deposition, detailed surface roughness and microstructural characterization were carried out by using optical profilometer and scanning electron microscopy (SEM), respectively. The composition and phase analysis were carried out by energy-dispersive X-ray spectroscopy analysis, and X-ray diffraction (XRD) technique, respectively. The bio-activity behavior of the uncoated and coated samples was also compared by dipping test in Hank’s solution. The average surface roughness of the coating was 10 µm (as compared to 0.5 µm of as-received Ti-6Al-4V substrate) with the presence of porosities. The microstructure of the coating was found to be continuous with the presence of solidified splats. A detailed XRD analysis shows phase transformation of TiO2 from anatase to rutile, decomposition of hydroxyapatite, and formation of CaTiO3 phase. Standard dipping test confirmed a faster kinetics of deposition of calcium phosphate in the coated HA+50% wt.% TiO2 surface as compared to the as-received substrate.

Keywords: titanium, plasma spraying, microstructure, bio-activity, TiO2, hydroxyapatite

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Authors: A. G. Pershina, P. S. Postnikov, M. E. Trusova, D. O. Burlakova, A. E. Sazonov

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Invention of magnetic-fluorescent nanocomposites is a rapidly developing area of research. The magnetic-fluorescent nanocomposite attractiveness is connected with the ability of simultaneous management and control of such nanocomposites by two independent methods based on different physical principles. These nanocomposites are applied for the solution of various essential scientific and experimental biomedical problems. The aim of this research is development of principle approach to nanobiohybrid structures with magnetic and fluorescent properties design. The surface of carbon-coated iron nanoparticles (Fe@C) were covalently modified by 4-carboxy benzenediazonium tosylate. Recombinant fluorescent protein TagGFP2 (Eurogen) was obtained in E. coli (Rosetta DE3) by standard laboratory techniques. Immobilization of TagGFP2 on the nanoparticles surface was provided by the carbodiimide activation. The amount of COOH-groups on the nanoparticle surface was estimated by elemental analysis (Elementar Vario Macro) and TGA-analysis (SDT Q600, TA Instruments. Obtained nanocomposites were analyzed by FTIR spectroscopy (Nicolet Thermo 5700) and fluorescence microscopy (AxioImager M1, Carl Zeiss). Amount of the protein immobilized on the modified nanoparticle surface was determined by fluorimetry (Cary Eclipse) and spectrophotometry (Unico 2800) with the help of preliminary obtained calibration plots. In the FTIR spectra of modified nanoparticles the adsorption band of –COOH group around 1700 cm-1 and bands in the region of 450-850 cm-1 caused by bending vibrations of benzene ring were observed. The calculated quantity of active groups on the surface was equal to 0,1 mmol/g of material. The carbodiimide activation of COOH-groups on nanoparticles surface results to covalent immobilization of TagGFP2 fluorescent protein (0.2 nmol/mg). The success of immobilization was proved by FTIR spectroscopy. Protein characteristic adsorption bands in the region of 1500-1600 cm-1 (amide I) were presented in the FTIR spectrum of nanocomposite. The fluorescence microscopy analysis shows that Fe@C-TagGFP2 nanocomposite possesses fluorescence properties. This fact confirms that TagGFP2 protein retains its conformation due to immobilization on nanoparticles surface. Magnetic-fluorescent nanocomposite was obtained as a result of unique design solution implementation – the fluorescent protein molecules were fixed to the surface of superparamagnetic carbon-coated iron nanoparticles using original diazonium salts.

Keywords: carbon-coated iron nanoparticles, diazonium salts, fluorescent protein, immobilization

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Authors: Alica Höpken, Hergen Pargmann

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The resource-efficient planning of the complex production planning processes in the meat industry and the reduction of food waste is a permanent challenge. The complexity of the production planning process occurs in every part of the supply chain, from agriculture to the end consumer. It arises from long and uncertain planning phases. Uncertainties such as stochastic yields, fluctuations in demand, and resource variability are part of this process. In the meat industry, waste mainly relates to incorrect storage, technical causes in production, or overproduction. The high amount of food waste along the complex supply chain in the meat industry could not be reduced by simple solutions until now. Therefore, resource-efficient production planning by conventional methods is currently only partially feasible. The realization of intelligent, automated production planning is basically possible through the application of machine learning algorithms, such as those of reinforcement learning. By applying the adapted design thinking method, machine learning methods (especially reinforcement learning algorithms) are used for the complex production planning process in the meat industry. This method represents a concretization to the application area. A resource-efficient production planning process is made available by adapting the design thinking method. In addition, the complex processes can be planned efficiently by using this method, since this standardized approach offers new possibilities in order to challenge the complexity and the high time consumption. It represents a tool to support the efficient production planning in the meat industry. This paper shows an elegant adaption of the design thinking method to apply the reinforcement learning method for a resource-efficient production planning process in the meat industry. Following, the steps that are necessary to introduce machine learning algorithms into the production planning of the food industry are determined. This is achieved based on a case study which is part of the research project ”REIF - Resource Efficient, Economic and Intelligent Food Chain” supported by the German Federal Ministry for Economic Affairs and Climate Action of Germany and the German Aerospace Center. Through this structured approach, significantly better planning results are achieved, which would be too complex or very time consuming using conventional methods.

Keywords: change management, design thinking method, machine learning, meat industry, reinforcement learning, resource-efficient production planning

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Authors: Vara Prasad Vemu

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The aim of the present work is to investigate the mechanical properties and water absorption capacity of carbon and basalt fibers mixed with matrix epoxy. At present, there is demand for nature friendly products. Basalt reinforced composites developed recently, and these mineral amorphous fibres are a valid alternative to carbon fibres for their lower cost and to glass fibres for their strength. The present paper describes briefly on basalt and carbon fibres (uni-directional) which are used as reinforcement materials for composites. The matrix epoxy (LY 556-HY 951) is taken into account to assess its influence on the evaluated parameters. In order to use reinforced composites for structural applications, it is necessary to perform a mechanical characterization. With this aim experiments like tensile strength, flexural strength, hardness and water absorption are performed. Later the mechanical properties obtained from experiments are compared with ANSYS software results.

Keywords: carbon fibre, basalt fibre, uni-directional, reinforcement, mechanical tests, water absorption test, ANSYS

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Authors: Rahul Paul, Kedar Nath Das

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The paradigm of Reinforcement Learning (RL) has become prominent in training intelligent agents to make decisions in environments that are both dynamic and uncertain. The primary objective of RL is to optimize the policy of an agent in order to maximize the cumulative reward it receives throughout a given period. Nevertheless, the process of optimization presents notable difficulties as a result of the inherent trade-off between exploration and exploitation, the presence of extensive state-action spaces, and the intricate nature of the dynamics involved. Evolutionary Optimization Methods (EOMs) have garnered considerable attention as a supplementary approach to tackle these challenges, providing distinct capabilities for optimizing RL policies and value functions. The ongoing advancement of research in both RL and EOMs presents an opportunity for significant advancements in autonomous decision-making systems. The convergence of these two fields has the potential to have a transformative impact on various domains of artificial intelligence (AI) applications. This article highlights the considerable influence of EOMs in enhancing the capabilities of RL. Taking advantage of evolutionary principles enables RL algorithms to effectively traverse extensive action spaces and discover optimal solutions within intricate environments. Moreover, this paper emphasizes the practical implementations of EOMs in the field of RL, specifically in areas such as robotic control, autonomous systems, inventory problems, and multi-agent scenarios. The article highlights the utilization of EOMs in facilitating RL agents to effectively adapt, evolve, and uncover proficient strategies for complex tasks that may pose challenges for conventional RL approaches.

Keywords: machine learning, reinforcement learning, loss function, optimization techniques, evolutionary optimization methods

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Authors: D. A. S. Gamage, B. F. A. Basnayake, W. A. J. M. De Costa

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Agriculture plays an important and strategic role in the performance of Sri Lankan national economy. Rice is the staple food of Sri Lankans thus; rice cultivation is the major agricultural activity of the country. In Sri Lanka, out of the total rice production, a considerable amount of rice straw and rice husk goes wasted. Hence, there is a great potential of production of quality compost and rice husk charcoal. The concept of making rice straw compost and rice husk charcoal is practicable in Sri Lanka, where more than 40% of the farmers are engaged in rice cultivation. The application of inorganic nitrogen fertilizer has become a burden to the country. Rice husk charcoal as a coating material to retain N fertilizer is a suitable solution to gradually release nitrogenous compounds. Objective of this study was to produce rice husk charcoal coated urea as a slow releasing fertilizer with rice straw compost and to compare the leaching losses of nitrogen, phosphorus and potassium using leaching columns. Leaching column studies were prepared using 1.2 m tall PVC pipes with a diameter of 15 cm and a sampling port was attached to the bottom end of the column-cap. Leachates (100 ml/leaching column) were obtained from two sets of (each set has four leaching columns) leaching columns. The sampling was done once a week for 3 month period. Rice husk charcoal coated urea can potentially be used as a slow releasing nitrogen fertilizer which reduces leaching losses of urea. It also helps reduce the phosphate and potassium leaching. The cyclic effect of phosphate release is an important finding which could be the central issue in defining microbial behavior in soils. The fluctuations of phosphate may have cyclic effects of 28 days. In addition, rice straw compost and rice husk charcoal coating is less costly and contribute to mitigate pollution of water bodies by inorganic fertilizers.

Keywords: leaching, mitigate, rice husk charcoal, slow releasing fertilizer

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Authors: Princess Stephanie P. Llanos, Rinlee Butch M. Cervera

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Lithium iron phosphate (LiFePO4) is a potential cathode material for lithium-ion batteries due to its promising characteristics. In this study, carbon-coated nanograined LiFePO4 is synthesized via wet chemistry method at a low temperature of 400 °C and investigated its performance as a cathode in Lithium battery. The X-ray diffraction pattern of the synthesized samples can be indexed to an orthorhombic LiFePO4 structure. Agglomerated particles that range from 200 nm to 300 nm are observed from scanning electron microscopy images. Transmission electron microscopy images confirm the crystalline structure of LiFePO4 and coating of amorphous carbon layer. Elemental mapping using Energy dispersive spectroscopy analysis revealed the homogeneous dispersion of Fe, P, O, and C elements. On the other hand, the electrochemical performances of the synthesized cathodes were investigated using cyclic voltammetry, galvanostatic charge/discharge tests with different C-rates, and cycling performances. Galvanostatic charge and discharge measurements revealed that the sample sintered at 400 °C for 3 hours with carbon coating demonstrated the highest capacity among the samples which reaches up to 160 mAhg⁻¹ at 0.1C rate.

Keywords: cathode, charge-discharge, electrochemical, lithium batteries

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Authors: M. Gangadharappa, M. Ravi Kumar, H. N. Reddappa

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The mechanical properties and morphological analysis of Al6061-Red mud particulate composites were investigated. The compositions of the composite include a matrix of Al6061 and the red mud particles of 53-75 micron size as reinforcement ranging from 0% to 12% at an interval of 2%. Stir casting technique was used to fabricate Al6061-Red mud composites. Density measurement, estimation of percentage porosity, tensile properties, fracture toughness, hardness value, impact energy, percentage elongation and percentage reduction in area. Further, the microstructures and SEM examinations were investigated to characterize the composites produced. The result shows that a uniform dispersion of the red mud particles along the grain boundaries of the Al6061 alloy. The tensile strength and hardness values increases with the addition of Red mud particles, but there is a slight decrease in the impact energy values, values of percentage elongation and percentage reduction in area as the reinforcement increases. From these results of investigation, we concluded that the red mud, an industrial waste can be used to enhance the properties of Al6061 alloy for engineering applications.

Keywords: Al6061, red mud, tensile strength, hardness and microstructures

Procedia PDF Downloads 567