Search results for: functional gradient material

Authors: Belgherbi Aicha, Hadjidj Ismahen, Bessaid Abdelhafid

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The phase of segmentation is an important step in the processing and interpretation of medical images. In this paper, we focus on the segmentation of liver and spleen from the abdomen computed tomography (CT) images. The importance of our study comes from the fact that the segmentation of ROI from CT images is usually a difficult task. This difficulty is the gray’s level of which is similar to the other organ also the ROI are connected to the ribs, heart, kidneys, etc. Our proposed method is based on the anatomical information and mathematical morphology tools used in the image processing field. At first, we try to remove the surrounding and connected organs and tissues by applying morphological filters. This first step makes the extraction of interest regions easier. The second step consists of improving the quality of the image gradient. In this step, we propose a method for improving the image gradient to reduce these deficiencies by applying the spatial filters followed by the morphological filters. Thereafter we proceed to the segmentation of the liver, spleen. To validate the segmentation technique proposed, we have tested it on several images. Our segmentation approach is evaluated by comparing our results with the manual segmentation performed by an expert. The experimental results are described in the last part of this work.The system has been evaluated by computing the sensitivity and specificity between the semi-automatically segmented (liver and spleen) contour and the manually contour traced by radiological experts.

Keywords: CT images, liver and spleen segmentation, anisotropic diffusion filter, morphological filters, watershed algorithm

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Authors: E. T. Carvalho Filho, J. T. N. Medeiros, L. G. Martinez

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Residual stresses are self equilibrating in a rigid body that acts on the microstructure of the material without application of an external load. They are elastic stresses and can be induced by mechanical, thermal and chemical processes causing a deformation gradient in the crystal lattice favoring premature failure in mechanicals components. The search for measurements with good reliability has been of great importance for the manufacturing industries. Several methods are able to quantify these stresses according to physical principles and the response of the mechanical behavior of the material. The diffraction X-ray technique is one of the most sensitive techniques for small variations of the crystalline lattice since the X-ray beam interacts with the interplanar distance. Being very sensitive technique is also susceptible to variations in measurements requiring a study of the factors that influence the final result of the measurement. Instrumental, operational factors, form deviations of the samples and geometry of analyzes are some variables that need to be considered and analyzed in order for the true measurement. The aim of this work is to analyze the sources of errors inherent to the residual stress measurement process by X-ray diffraction technique making an interlaboratory comparison to verify the reproducibility of the measurements. In this work, two specimens were machined, differing from each other by the surface finishing: grinding and polishing. Additionally, iron powder with particle size less than 45 µm was selected in order to be a reference (as recommended by ASTM E915 standard) for the tests. To verify the deviations caused by the equipment, those specimens were positioned and with the same analysis condition, seven measurements were carried out at 11Ψ tilts. To verify sample positioning errors, seven measurements were performed by positioning the sample at each measurement. To check geometry errors, measurements were repeated for the geometry and Bragg Brentano parallel beams. In order to verify the reproducibility of the method, the measurements were performed in two different laboratories and equipments. The results were statistically worked out and the quantification of the errors.

Keywords: residual stress, x-ray diffraction, repeatability, reproducibility, error analysis

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Authors: Mohammad Asadpour, Maryam Sadeghi, Mahmoud Jafari

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The transformation of carbon dioxide into fuels and commodity chemicals is considered one of the most attractive methods to meet energy demands and reduce atmospheric CO₂ levels. Cobalt complexes have previously shown high faradaic efficiency in the reduction of CO₂ to CO. In this study, a nanostructure, referred to as a porphyrin-like buckyball, is simulated and analyzed for its electrical properties. The investigation aims to understand the unique characteristics of this material and its potential applications in electronic devices. Through computational simulations and analysis, the electrocatalytic reduction of CO₂ to CO by Cobalt-porphyrin-like buckyball is explored. The findings of this study offer valuable insights into the electrocatalytic properties of this predicted structure, paving the way for further research and development in the field of nanotechnology.

Keywords: porphyrin-like buckyball, DFT, nanomaterials, CO₂ to CO

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Authors: U. L. Fulco, E. L. Albuquerque, José X. Lima Neto, L. R. Da Silva

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The binding of the nonsteroidal anti-inflammatory drug ibuprofen (IBU) to human serum albumin (HSA) is investigated using density functional theory (DFT) calculations within a fragmentation strategy. Crystallographic data for the IBU–HSA supramolecular complex shows that the ligand is confined to a large cavity at the subdomain IIIA and at the interface between the subdomains IIA and IIB, whose binding sites are FA3/FA4 and FA6, respectively. The interaction energy between the IBU molecule and each amino acid residue of these HSA binding pockets was calculated using the Molecular Fractionation with Conjugate Caps (MFCC) approach employing a dispersion corrected exchange–correlation functional. Our investigation shows that the total interaction energy of IBU bound to HSA at binding sites of the fatty acids FA3/FA4 (FA6) converges only for a pocket radius of at least 8.5 °A, mainly due to the action of residues Arg410, Lys414 and Ser489 (Lys351, Ser480 and Leu481) and residues in nonhydrophobic domains, namely Ile388, Phe395, Phe403, Leu407, Leu430, Val433, and Leu453 (Phe206, Ala210, Ala213, and Leu327), which is unusual. Our simulations are valuable for a better understanding of the binding mechanism of IBU to albumin and can lead to the rational design and the development of novel IBU-derived drugs with improved potency.

Keywords: ibuprofen, human serum albumin, density functional theory, binding energies

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Authors: Mohammadreza Biabani, Mohammad Azadfallah

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A facile and robust strategy is required to fabricate films with high special optical properties for application in the field of anti-counterfeit marking. Nanocellulose, derived from bioresources, is a renewable material with broad application prospects. In this paper, a method for grafting the eco-friendly Berberine cationic dye on cellulose nanofiber is proposed. A functional modification was carried out by in-situ polymerization along with a grafting approach with acrylic acid(AA) in order to develop cationic dyeability of the cellulose nanofiber (CNF). The Berberine grafting on nanocellulose was significantly influenced by the reaction time and temperature during the dyeing process. The dyed CNF-films exhibited appropriate characteristics like appearance, color strength, and fastness for anti-counterfeiting application.

Keywords: Cellulose nanofiber, Berberine, Grafting, anti-counterfeiting, film

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Authors: Farideh Tabatabei-Yazdi, Fereshteh Falah, Alireza Vasiee

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Nowadays, production of functional foods has become very essential. Inulin is one of the most functional hydrocolloid compounds used in such products. In the present study, the production of a synbiotic yogurt containing 1, 2.5, and 5% (w/v) inulin has been investigated. The yogurt was fermented with Lactobacillus brevis PML1 derived from Tarkhineh, an Iranian cereal-dairy fermented food. Furthermore, the physicochemical properties, antioxidant activity, sensory attributes, and microbial viability properties were investigated on the 0th, 7th, and 14th days of storage after fermentation. The viable cells of L. brevis PML1 reached 108 CFU/g, and the product resisted to simulated digestive juices. Moreover, the synbiotic yogurt impressively increased the production of antimicrobial compounds and had the most profound antimicrobial effect on S. typhimurium. The physiochemical properties were in the normal range, and the fat content of the synbiotic yogurt was reduced remarkably. The antioxidant capacity of the fermented yogurt was significantly increased (p<0:05), which was equal to those of DPPH (69:18±1:00%) and BHA (89:16±2:00%). The viability of L. brevis PML1 was increased during storage. Sensory analysis showed that there were significant differences in terms of the impressive parameters between the samples and the control (p<0:05). Addition of 2.5% inulin not only improved the physical properties but also retained the viability of the probiotic after 14 days of storage, in addition to the viability of L. brevis with a viability count above 6 log CFU/g in the yogurt. Therefore, a novel synbiotic product containing L. brevis PML1, which can exert the desired properties, can be used as a suitable carrier for the delivery of the probiotic strain, exerting its beneficial health effects.

Keywords: functional food, lactobacillus brevis, symbiotic yogurt, physiochemical properties

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Authors: Jatupon Em-Udom, Nirand Pisutha-Arnond

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The phase-field-crystal, PFC, approach is a density-functional-type material model with an atomic resolution on a diffusive timescale. Spatially, the model incorporates periodic nature of crystal lattices and can naturally exhibit elasticity, plasticity and crystal defects such as grain boundaries and dislocations. Temporally, the model operates on a diffusive timescale which bypasses the need to resolve prohibitively small atomic-vibration time steps. The PFC model has been used to study many material phenomena such as grain growth, elastic and plastic deformations and solid-solid phase transformations. In this study, the pressure-controlled dynamic equation for the PFC model was developed to simulate a single-component system under externally applied pressure; these coupled equations are important for studies of deformable systems such as those under constant pressure. The formulation is based on the non-equilibrium thermodynamics and the thermodynamics of crystalline solids. To obtain the equations, the entropy variation around the equilibrium point was derived. Then the resulting driving forces and flux around the equilibrium were obtained and rewritten as conventional thermodynamic quantities. These dynamics equations are different from the recently-proposed equations; the equations in this study should provide more rigorous descriptions of the system dynamics under externally applied pressure.

Keywords: driving forces and flux, evolution equation, non equilibrium thermodynamics, Onsager’s reciprocal relation, phase field crystal model, thermodynamics of single-component solid

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Authors: B. SahaRoy, T. Medhi, S. C. Saha

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To understand the friction stir welding process, it is very important to know the nature of the material flow in and around the tool. The process is a combination of both thermal as well as mechanical work i.e it is a coupled thermo-mechanical process. Numerical simulations are very much essential in order to obtain a complete knowledge of the process as well as the physics underlying it. In the present work a model based approach is adopted in order to study material flow. A thermo-mechanical based CFD model is developed using a Finite Element package, Comsol Multiphysics. The fluid flow analysis is done. The model simultaneously predicts shear strain fields, shear strain rates and shear stress over the entire workpiece for the given conditions. The flow fields generated by the streamline plot give an idea of the material flow. The variation of dynamic viscosity, velocity field and shear strain fields with various welding parameters is studied. Finally the result obtained from the above mentioned conditions is discussed elaborately and concluded.

Keywords: AA6061-T6, CFD modelling, friction stir welding, material flow

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Authors: Wilhelmina van den Berg

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Through intentionally developing the Register Continuum and the Functional Model of Language in the secondary history classroom, teachers can effectively build a teaching and learning cycle geared towards literacy improvement and EAL differentiation. Developing an understanding of and engaging students in the field, tenor, and tone of written and spoken language, allows students to build the foundation for greater academic achievement due to integrated literacy skills in the history classroom. Building a variety of scaffolds during lessons within these models means students can improve their academic language and communication skills.

Keywords: academic language, EAL, functional model of language, international baccalaureate, literacy skills

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Authors: Lifar M. S., Tereshchenko A. A., Bulgakov A. N., Guda S. A., Guda A. A., Soldatov A. V.

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Metal nanoparticles are widely used as heterogeneous catalysts to activate adsorbed molecules and reduce the energy barrier of the reaction. Reaction product yield depends on the interplay between elementary processes - adsorption, activation, reaction, and desorption. These processes, in turn, depend on the inlet feed concentrations, temperature, and pressure. At stationary conditions, the active surface sites may be poisoned by reaction byproducts or blocked by thermodynamically adsorbed gaseous reagents. Thus, the yield of reaction products can significantly drop. On the contrary, the dynamic control accounts for the changes in the surface properties and adjusts reaction parameters accordingly. Therefore dynamic control may be more efficient than stationary control. In this work, a reinforcement learning algorithm has been applied to control the simulation of CO oxidation on a catalyst. The policy gradient algorithm is learned to maximize the CO₂ production rate based on the CO and O₂ flows at a given time step. Nonstationary solutions were found for the regime with surface deactivation. The maximal product yield was achieved for periodic variations of the gas flows, ensuring a balance between available adsorption sites and the concentration of activated intermediates. This methodology opens a perspective for the optimization of catalytic reactions under nonstationary conditions.

Keywords: artificial intelligence, catalyst, co oxidation, reinforcement learning, dynamic control

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Authors: Natural Frequency Analysis of a Porous Functionally Graded Shaft System

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The vibration characteristics of a functionally graded (FG) rotor model having porosities and micro-voids is investigated using three-dimensional finite element analysis. The FG shaft is mounted with a steel disc located at the midspan. The shaft ends are supported on isotropic bearings. The FG material is composed of a metallic (stainless-steel) and ceramic phase (zirconium oxide) as its constituent phases. The layer wise material property variation is governed by power law. Material property equations are developed for the porosity modelling. Python code is developed to assign the material properties to each layer including the effect of porosities. ANSYS commercial software is used to extract the natural frequencies and whirl frequencies for the FG shaft system. The obtained results show the influence of porosity volume fraction and power-law index, on the vibration characteristics of the ceramic-based FG shaft system.

Keywords: Finite element method, Functionally graded material, Porosity volume fraction, Power law

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Authors: Y. R. Adullayev, О. О. Karimzada

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Analytical expressions for inductances, current, ampere-turns, excitation winding, maximum width, coordinates of the levitation screen (LS) are derived for the calculation of electromagnetic devices based on tracking systems with levitation elements (TS with LS). Taking into account the expression of the complex magnetic resistance of the screen, the dependence of the screen width on the heating temperature of the physical and technical characteristics of the screen material and the relationship of the geometric dimensions of the magnetic circuit is established. Analytic expressions for a number of functional dependencies characterizing complex parameter relationships in explicit form are obtained and analyzed.

Keywords: tracking systems, levitation screens, electromagnetic levitation, excitation windings, magnetic cores, defining converter, receiving converter, electromagnetic force, electrical and magnetic resistance

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Authors: Debajyoti Bose

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Chitosan has received much attention as a functional biopolymer for diverse applications, especially in pharmaceutics and medicine. Chitosan is a positively charged natural biodegradable and biocompatible polymer. It is a linear polysaccharide consisting of β-1,4 linked monomers of glucosamine and N-acetylglucosamine. Chitosan can be mainly obtained from fungal sources during large fermentation process. In this study,three different fungal strains Aspergillus niger NCIM 1045, Aspergillus oryzae NCIM 645 and Mucor indicus MTCC 3318 were used for the production of chitosan. The growth mediums were optimized for maximum fungal production. The produced chitosan was characterized by determining degree of deacetylation. Chitosan possesses one reactive amino at the C-2 position of the glucosamine residue, and these amines confer important functional properties to chitosan which can be exploited for biofabrication to generate various chemically modified derivatives and explore their potential for pharmaceutical field. Chitosan nanoparticles were prepared by ionic cross-linking with tripolyphosphate (TPP). The major effect on encapsulation and release of protein (e.g. enzyme diastase) in chitosan-TPP nanoparticles was investigated in order to control the loading and release efficiency. It was noted that the chitosan loading and releasing efficiency as a nanocapsule, obtained from different fungal sources was almost near to initial enzyme activity(12026 U/ml) with a negligible loss. This signify, chitosan can be used as a polymeric drug as well as active component or protein carrier material in dosage by design due to its appealing properties such as biocompatibility, biodegradability, low toxicity and relatively low production cost from abundant natural sources. Based upon these initial experiments, studies were also carried out on modification of chitosan based nanocapsules incorporated with physiologically important enzymes and nutraceuticals for target delivery.

Keywords: fungi, chitosan, enzyme, nanocapsule

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Authors: Amal Shehata

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Low back pain related to disc prolapse is localized in the lumbar area and it may be radiated to the lower extremities, starting from neurons near or around the spinal canal. Most of the population may be affected with disc prolapse within their lifetime and leads to lost productivity, disability and loss of function. The study purpose was to examine the effect of rehabilitative nursing program on pain intensity and functional status among patients with discectomy. Design: Aquasi experimental design was utilized. Setting: The study was carried out at neurosurgery department and out patient's clinic of Menoufia University and Teaching hospitals at Menoufia governorate, Egypt. Instrument of the study: Five Instruments were used for data collection: Structured interviewing questionnaire, Functional assessment instrument, Observational check list, Numeric rating Scale and Oswestry low back pain disability questionnaire. Results: There was an improvement in mean total knowledge score about disease process, discectomy and rehabilitation program in study group (25.32%) than control group (7.32%). There was highly statistically significant improvement in lumbar flexibility among study group (80%) than control group (30%) after rehabilitation program than before. Also there was a decrease in pain score in study group (58% no pain) than control group (28% no pain) after rehabilitation program. There was an improvement in total disability score of study group (zero %) regarding effect of pain on the activity of daily living after rehabilitation program than control group (16%). Conclusion: Application of rehabilitative nursing program for patient with discectomy had proven a positive effect in relation to knowledge score, pain reduction, activity of daily living and functional abilities. Recommendation: A continuous rehabilitative nursing program should be carried out for all patients immediately after discectomy surgery on regular basis. Also A colored illustrated booklet about rehabilitation program should be available and distributed for all patients before surgery.

Keywords: discectomy, rehabilitative nursing program, pain intensity, functional status

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Authors: Bo-Bin Xiaoa, Chia-Yi Liua

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In the task of searching for anomalous radiation sources, personnel holding radiation detectors to search for radiation sources may be exposed to unnecessary radiation risk, and automated search using machines becomes a required project. The research uses various sophisticated algorithms, which are double Q learning, dueling network, and NoisyNet, of deep reinforcement learning to search for radiation sources. The simulation environment, which is a 10*10 grid and one shielding wall setting in it, improves the development of the AI model by training 1 million episodes. In each episode of training, the radiation source position, the radiation source intensity, agent position, shielding wall position, and shielding wall length are all set randomly. The three algorithms are applied to run AI model training in four environments where the training shielding wall is a full-shielding wall, a lead wall, a concrete wall, and a lead wall or a concrete wall appearing randomly. The 12 best performance AI models are selected by observing the reward value during the training period and are evaluated by comparing these AI models with the gradient search algorithm. The results show that the performance of the AI model, no matter which one algorithm, is far better than the gradient search algorithm. In addition, the simulation environment becomes more complex, the AI model which applied Double DQN combined Dueling and NosiyNet algorithm performs better.

Keywords: double Q learning, dueling network, NoisyNet, source searching

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Authors: Cao Bin, Yuan Yi, Wang Qiang, Amor Abdelkader, Ali Reza Kamali, Diogo Montalvão

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The study of the electrodynamic behavior of non-ferrous particles in time-varying magnetic fields is a promising area of research with wide applications, including recycling of non-ferrous metals, mechanical transmission, and space debris. The key technology for recovering non-ferrous metals is eddy current separation (ECS), which utilizes the eddy current force and torque to separate non-ferrous metals. ECS has several advantages, such as low energy consumption, large processing capacity, and no secondary pollution, making it suitable for processing various mixtures like electronic scrap, auto shredder residue, aluminum scrap, and incineration bottom ash. Improving the separation efficiency of mixtures with different particle sizes in ECS can create significant social and economic benefits. Our previous study investigated the influence of particle size on separation efficiency by combining numerical simulations and separation experiments. Pearson correlation analysis found a strong correlation between the eddy current force in simulations and the repulsion distance in experiments, which confirmed the effectiveness of our simulation model. The interaction effects between particle size and material type, rotational speed, and magnetic pole arrangement were examined. It offer valuable insights for the design and optimization of eddy current separators. The underlying mechanism behind the effect of particle size on separation efficiency was discovered by analyzing eddy current and field gradient. The results showed that the magnitude and distribution heterogeneity of eddy current and magnetic field gradient increased with particle size in eddy current separation. Based on this, we further found that increasing the curvature of magnetic field lines within particles could also increase the eddy current force, providing a optimized method to improving the separation efficiency of fine particles. By combining the results of the studies, a more systematic and comprehensive set of optimization guidelines can be proposed for mixtures with different particle size ranges. The separation efficiency of fine particles could be improved by increasing the rotational speed, curvature of magnetic field lines, and electrical conductivity/density of materials, as well as utilizing the eddy current torque. When designing an ECS, the particle size range of the target mixture should be investigated in advance, and the suitable parameters for separating the mixture can be fixed accordingly. In summary, these results can guide the design and optimization of ECS, and also expand the application areas for ECS.

Keywords: eddy current separation, particle size, numerical simulation, metal recovery

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Authors: Mayandi Ramanathan

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Gas turbine blades see the most aggressive thermal stress conditions within the engine, due to Turbine Entry Temperatures in the range of 1500 to 1600°C, but in synchronization with other functional components, they must readily deliver efficient performance, whilst incurring minimal overhaul and repair costs during its service life up to 5 million flying miles. The blades rotate at very high rotation rates and remove significant amount of thermal power from the gas stream. At high temperatures the major component failure mechanism is creep. During its service over time under high temperatures and loads, the blade will deform, lengthen and rupture. High strength and stiffness in the longitudinal direction up to elevated service temperatures are certainly the most needed properties of turbine blades. The proposed advanced Ti alloy material needs a process that provides strategic orientation of metallic ordering, uniformity in composition and high metallic strength. 25% Ta/(Al+Ta) ratio ensures TaAl3 phase formation, where as 51% Al/(Al+Ti) ratio ensures formation of α-Ti3Al and γ-TiAl mixed phases fand the three phase combination ensures minimal Al excess (~1.4% Al excess), unlike Ti-47Al-2Cr-2Nb which has significant excess Al (~5% Al excess) that could affect the service life of turbine blades. This presentation will involve the summary of additive manufacturing and heat treatment process conditions to fabricate turbine blade with Ti-43Al matrix alloyed with optimized amount of refractory Ta metal. Summary of thermo-mechanical test results such as high temperature tensile strength, creep strain rate, thermal expansion coefficient and fracture toughness will be presented. Improvement in service temperature of the turbine blades and corrosion resistance dependence on coercivity of the alloy material will be reported. Phase compositions will be quantified, and a summary of its correlation with creep strain rate will be presented.

Keywords: gas turbine, aerospace, specific strength, creep, high temperature materials, alloys, phase optimization

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Authors: Pedro G. Morouço

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One utmost challenge in Tissue Engineering is the production of 3D constructs capable of mimicking the functional hierarchy of native tissues. This is well stated for osteochondral tissue due to the complex mechanical functional unit based on the junction of articular cartilage and bone. Thus, the aim of the present study was to develop a new additive manufacturing system coupling micro-extrusion with hydrogels printing. An integrated system was developed with 2 main features: (i) the printing of up to three distinct hydrogels; (ii) in coordination with the printing of a thermoplastic structural support. The hydrogel printing module was projected with a ‘revolver-like’ system, where the hydrogel selection was made by a rotating mechanism. The hydrogel deposition was then controlled by pressured air input. The use of specific components approved for medical use was incorporated in the material dispensing system (Nordson EDF Optimum® fluid dispensing system). The thermoplastic extrusion modulus enabled the control of required extrusion temperature through electric resistances in the polymer reservoir and the extrusion system. After testing and upgrades, a hydrogel modulus with 3 syringes (3cm3 capacity each), with a pressure range of 0-2.5bar, a rotational speed of 0-5rpm, and working with needles from 200-800µm was obtained. This modulus was successfully coupled to the extrusion system that presented a temperature up to 300˚C, a pressure range of 0-12bar, and working with nozzles from 200-500µm. The applied motor could provide a velocity range 0-2000mm/min. Although, there are distinct printing requirements for hydrogels and polymers, the novel system could develop hybrid scaffolds, combining the 2 moduli. The morphological analysis showed high reliability (n=5) between the theoretical and obtained filament and pore size (350µm and 300µm vs. 342±4µm and 302±3µm, p>0.05, respectively) of the polymer; and multi-material 3D constructs were successfully obtained. Human tissues present very distinct and complex structures regarding their mechanical properties, organization, composition and dimensions. For osteochondral regenerative medicine, a multiphasic scaffold is required as subchondral bone and overlying cartilage must regenerate at the same time. Thus, a scaffold with 3 layers (bone, intermediate and cartilage parts) can be a promising approach. The developed system may give a suitable solution to construct those hybrid scaffolds with enhanced properties. The present novel system is a step-forward regarding osteochondral tissue engineering due to its ability to generate layered mechanically stable implants through the double-printing of hydrogels with thermoplastics.

Keywords: 3D bioprinting, bone regeneration, cartilage regeneration, regenerative medicine, tissue engineering

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Authors: Syed M. Rizvi, Yiqing Meng, Simon Iwnicki

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With an increased demand in the land cargo industry, it is predicted that the freight trade will rise to a record $1.1 trillion in revenue and volume in the following years to come. This increase is mainly driven by the e-commerce model ever so popular in the consumer market. Many innovative ideas have stemmed from this demand and change in lifestyle likes of which include e-bike cargo and drones. Rural and urban areas are facing air quality challenges to keep pollution levels in city centre to a minimum. For this purpose, this paper presents the design and implementation of a non-linear PID control system, employing a micro-controller and low cost sensing technique, for controlling an electrical motor based cargo vehicle with various loads, to follow a leading vehicle (bike). Within using this system, the cargo vehicle will have no load influence on the bike rider on different gradient conditions, such as hill climbing. The system is being integrated with a microcontroller to continuously measure several parameters such as relative displacement between bike and the cargo vehicle and gradient of the road, and process these measurements to create a portable controller capable of controlling the performance of electrical vehicle without the need of a PC. As a result, in the case of carrying 180kg of parcel weight, the cargo vehicle can maintain a reasonable spacing over a short length of sensor travel between the bike and itself.

Keywords: cargo, e-bike, microcontroller, embedded system, nonlinear pid, self-adaptive, inertial measurement unit (IMU)

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Authors: Isik Cetintav, Cenk Misirli, Yilmaz Can, Damla Gunel

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This work investigates experimental and numerical analysis of open die forging of multimetallic materials. Multimetallic material production has recently become an interesting research field. The mechanical properties of the materials to be used for the formation of multimetallic materials and the mechanical properties of the multimetallic materials produced will be compared and the material flows of the use of different lubricants will be examined. Furthermore, in this work, the mechanical properties of multimetallic metallic materials produced using different materials will be examined by using different lubricants. The advantages and disadvantages of different lubricants will be approached with the bi-metallic material to be produced. Cylindrical specimens consisting of two different materials were used in the experiments. Specimens were prepared as aluminum sleeve and copper core and upset at different reduction. This metal combination present a material model of which chemical composition is different. ABAQUS software was used for the simulations. Simulation and experimental results have also shown reasonable agreement.

Keywords: multimetallic, forging, experimental, numerical

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Authors: K. Pandey

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The present study is a functional analysis of the relationship between castes which indicates the dynamics of the caste structure in the rural setting. The researcher has tried to show both the cooperation and competition on important ceremonial and social occasions. The real India exists in the villages, so we need to know about their solidarity and also what the village life is and has been shaping into. We need to emphasize a microcosmic study of Indian rural life. Furthermore, caste integration is an acute problem country faces today. To resolve this we are required to know the dynamics of behavior of the people of different castes and for the study of the caste dynamics a study of caste relations are needed. The present study is an attempt in this direction.

Keywords: hierarchial groups, jajmani system, functional dependence, commensalities

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Authors: Muhtasim Shafi Kader, Fizar Ahmed, Annesha Acharjee

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Machine learning and data mining are crucial in health care, as well as medical information and detection. Machine learning approaches are now being utilized to improve awareness of a variety of critical health issues, including diabetes detection, neuron cell tumor diagnosis, COVID 19 identification, and so on. Parkinson’s disease is basically a disease for our senior citizens in Bangladesh. Parkinson's Disease indications often seem progressive and get worst with time. People got affected trouble walking and communicating with the condition advances. Patients can also have psychological and social vagaries, nap problems, hopelessness, reminiscence loss, and weariness. Parkinson's disease can happen in both men and women. Though men are affected by the illness at a proportion that is around partial of them are women. In this research, we have to get out the accurate ML algorithm to find out the disease with a predictable dataset and the model of the following machine learning classifiers. Therefore, nine ML classifiers are secondhand to portion study to use machine learning approaches like as follows, Naive Bayes, Adaptive Boosting, Bagging Classifier, Decision Tree Classifier, Random Forest classifier, XBG Classifier, K Nearest Neighbor Classifier, Support Vector Machine Classifier, and Gradient Boosting Classifier are used.

Keywords: naive bayes, adaptive boosting, bagging classifier, decision tree classifier, random forest classifier, XBG classifier, k nearest neighbor classifier, support vector classifier, gradient boosting classifier

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Authors: Kasra Ghaemi, Syeda Tasnim, Shohel Mahmud

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One of the main issues affecting the quality and shelf life of food products is temperature fluctuation during transportation and storage. Packaging plays an important role in protecting food from environmental conditions, especially thermal variations. In this study, the performance of using microencapsulated Phase Change Material (PCM) as a promising thermal buffer layer in smart food packaging is investigated. The considered insulation layer is evaluated for different thicknesses and the absorbed heat from the environment. The results are presented in terms of the melting time of PCM or provided thermal protection period.

Keywords: food packaging, phase change material, thermal buffer, protection time

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Authors: Benny Alexander, Ikhlashia N. Fadhilah, Muhammad R. Pasha, Michelle Julia, Anne Z. Syahrial

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Brake shoe is a component that serves to reduce speed or stop the train's speed by utilizing the friction force. Generally, the material used as a brake shoe is cast iron, where cast iron itself is a heavy, expensive, and easily worn material. Aluminum matrix composites are one of candidates for the cast iron replacement material as the basic material for brake shoe. The matrix in the composite used is Aluminum AC4B. Reinforcement used in aluminum matrix composites is nano-alumina, where the use of nano-alumina of 0.25%, 0.3%, 0.35%, 0.4%, and 0.5% volume fraction will be tested. The sample is made using the stir casting method; then, it will be tested mechanically. The use of nano-alumina as a reinforcement will increase the strength of the matrix. SEM (scanning electron microscopy) testing is used to test the distribution of reinforcing particles due to stirring. Therefore, the addition of nano-alumina will improve AC4B aluminum matrix composites.

Keywords: aluminium matrix composites, brake shoe application, stir casting, nano-alumina

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Authors: Muhammad Rizwan Tariq, Muhammad Issa Khan, Zulfiqar Ahmad, Muhammad Adnan Nasir, Muhammad Sameem Javed, Sheraz Ahmed

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Functional foods may be a good tool that can be simply utilized in reducing community health expenses. Regular consumption of rabbit meat can offer patrons with bioactive components because the manipulation in rabbit feed is much successful to raise the levels of conjugated linoleic acid, ecosapentaenoic acid, decosahexaenoic acid, polyunsaturated fatty acids, selenium, tocopherol etc. and to reduce the ω-3/ω-6 ratio which is performing a major role in curing of cardiovascular and several other diseases. In comparison to the meats of other species, rabbit meat has higher amounts of protein with essential amino acids, especially in the muscles and low cholesterol contents that also have elevated digestibility. The present study was carried out to develop the functional rabbit meat by modifying feed ingredient of rabbit diet. Thirty-day old rabbits were fed with feeds containing 2 % and 4 % oat. The feeding trial was carried out for eight weeks. Rabbits were divided into three different groups and reared for the period of two months. T0 rabbits were considered control group while T1 rabbits were reared on 4% oat, and T2 were on 2% oat in the feed. At the end of the 8 weeks, the rabbits were slaughtered. Results presented in this study concluded that 4 % oat seed supplementation enhanced n-3 PUFA in meat. It was observed that oat seed supplementation also reduced fat percentage in the meat. Utilization of oat in the feed of rabbits significantly affected the pH, protein, fat, textural and concentration of polyunsaturated fatty acids. A study trial was conducted in order to examine the impact of functional meat on the blood lipid profile of human subjects. They were given rabbit meat in comparison to the chicken meat for the period of one month. The cholesterol, triglycerides and low density lipoprotein were found to be lower in blood serum of human subject group treated with 4 % oat meat.

Keywords: functional food, functional rabbit meat, meat quality, rabbit

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Authors: Hakim Derradji, Abdelkader Yahi, Abdelmalek Sabrou, Nacer Tabet

Abstract:

Introduction: Cystic lesions located in the sellar and suprasellar region cause a diagnostic and therapeutic problem, given their location and their impact on neighboring structures. The patient's symptomatology varies from a simple headache to serious visual and endocrine disorders, involving the functional prognosis, sometimes even the vital prognosis. Surgery in this region remains a therapeutic challenge, and several surgical techniques have been described and used. Material and Methods: We treated 15 patients during the period from 2015 to 2022, whose clinical, biological, radiological, and therapeutic characteristics will be presented in detail in this work, and in whom the surgical technique differs from one case to another. Conclusion: We will discuss in this work the different techniques used to treat these lesions and the different objectives to be achieved for each case, as well as the complications and our conduct to be taken per and post-operative.

Keywords: cystic lesions, adenomas, sellar and suprasellar region, neuroendoscopy

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Authors: Jonathan Sohn

Abstract:

Deep neural networks (DNNs) have shown state-of-the-art performance for many applications, including computer vision, natural language processing, and speech recognition. Recently, adversarial attacks have been studied in the context of deep neural networks, which aim to alter the results of deep neural networks by modifying the inputs slightly. For example, an adversarial attack on a DNN used for object detection can cause the DNN to miss certain objects. As a result, the reliability of DNNs is undermined by their lack of robustness against adversarial attacks, raising concerns about their use in safety-critical applications such as autonomous driving. In this paper, we focus on studying the adversarial attacks and defenses on DNNs for image classification. There are two types of adversarial attacks studied which are fast gradient sign method (FGSM) attack and projected gradient descent (PGD) attack. A DNN forms decision boundaries that separate the input images into different categories. The adversarial attack slightly alters the image to move over the decision boundary, causing the DNN to misclassify the image. FGSM attack obtains the gradient with respect to the image and updates the image once based on the gradients to cross the decision boundary. PGD attack, instead of taking one big step, repeatedly modifies the input image with multiple small steps. There is also another type of attack called the target attack. This adversarial attack is designed to make the machine classify an image to a class chosen by the attacker. We can defend against adversarial attacks by incorporating adversarial examples in training. Specifically, instead of training the neural network with clean examples, we can explicitly let the neural network learn from the adversarial examples. In our experiments, the digit recognition accuracy on the MNIST dataset drops from 97.81% to 39.50% and 34.01% when the DNN is attacked by FGSM and PGD attacks, respectively. If we utilize FGSM training as a defense method, the classification accuracy greatly improves from 39.50% to 92.31% for FGSM attacks and from 34.01% to 75.63% for PGD attacks. To further improve the classification accuracy under adversarial attacks, we can also use a stronger PGD training method. PGD training improves the accuracy by 2.7% under FGSM attacks and 18.4% under PGD attacks over FGSM training. It is worth mentioning that both FGSM and PGD training do not affect the accuracy of clean images. In summary, we find that PGD attacks can greatly degrade the performance of DNNs, and PGD training is a very effective way to defend against such attacks. PGD attacks and defence are overall significantly more effective than FGSM methods.

Keywords: deep neural network, adversarial attack, adversarial defense, adversarial machine learning

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Authors: Liu Li, Kim Seng Lee, Li Lu

Abstract:

The high-energy-density Li-rich layered materials are promising cathode materials for the next-generation high-performance lithium-ion batteries. The relatively low rate capability is one of the major problems that limit their practical application. In this work, Li-rich layered Li1.2Mn0.54Ni0.13Co0.13O2 cathode material synthesized by coprecipitation method is further modified by F doping or surface treatment to enhance its cycling stability as well as rate capability.

Keywords: Li-ion battery, Li-rich layered cathode material, phase transformation, cycling stability, rate capacility

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Authors: Joseph Wolff, Jeffrey Eilbott

Abstract:

Autism Spectrum Disorders (ASD) are a spectrum of social disorders characterized by deficits in social communication, verbal ability, and interaction that can vary in severity. In recent years, researchers have used magnetic resonance imaging (MRI) to help detect how neural patterns in individuals with ASD differ from those of neurotypical (NT) controls for classification purposes. This study analyzed the classification of ASD within males and females using functional MRI data. Functional connectivity (FC) correlations among brain regions were used as feature inputs for machine learning algorithms. Analysis was performed on 558 cases from the Autism Brain Imaging Data Exchange (ABIDE) I dataset. When trained specifically on females, the algorithm underperformed in classifying the ASD subset of our testing population. Although the subject size was relatively smaller in the female group, the manual matching of both male and female training groups helps explain the algorithm’s bias, indicating the altered sex abnormalities in functional brain networks compared to typically developing peers. These results highlight the importance of taking sex into account when considering how generalizations of findings on males with ASD apply to females.

Keywords: autism spectrum disorder, machine learning, neuroimaging, sex differences

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Authors: Mohammad Khazaei, Reza Rostami, Hassan Gharayagh Zandi, Ruhollah Basatnia, Mahboubeh Ghayour Najafabadi

Abstract:

Introduction: This study delves into the influence of diverse interventions on brain functional connectivity among young male basketball players. Given the significance of understanding how interventions affect cognitive functions in athletes, particularly in the context of basketball, this research contributes to the growing body of knowledge in sports neuroscience. Methods: Three distinct groups were selected for comprehensive investigation: the Motivational Interview Group, Placebo Consumption Group, and Ritalin Consumption Group. The study involved assessing brain functional connectivity using various frequency bands (Delta, Theta, Alpha, Beta1, Beta2, Gamma, and Total Band) before and after the interventions. The participants were subjected to specific interventions corresponding to their assigned groups. Results: The findings revealed substantial differences in brain functional connectivity across the studied groups. The Motivational Interview Group exhibited optimal outcomes in PLI (Total Band) connectivity. The Placebo Consumption Group demonstrated a marked impact on PLV (Alpha) connectivity, and the Ritalin Consumption Group experienced a considerable enhancement in imCoh (Total Band) connectivity. Discussion: The observed variations in brain functional connectivity underscore the nuanced effects of different interventions on young male basketball players. The enhanced connectivity in specific frequency bands suggests potential cognitive and performance improvements. Notably, the Motivational Interview and Placebo Consumption groups displayed unique patterns, emphasizing the multifaceted nature of interventions. These findings contribute to the understanding of tailored interventions for optimizing cognitive functions in young male basketball players. Conclusion: This study provides valuable insights into the intricate relationship between interventions and brain functional connectivity in young male basketball players. Further research with expanded sample sizes and more sophisticated statistical analyses is recommended to corroborate and expand upon these initial findings. The implications of this study extend to the broader field of sports neuroscience, aiding in the development of targeted interventions for athletes in various disciplines.

Keywords: electroencephalography, Ritalin, Placebo effect, motivational interview

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