Friction Stir Welding of Low-Carbon AISI 1006 Steel: Room and High-Temperature Mechanical Properties

Friction stir welding (FSW) is an ecologically benign solid-state joining process. In this work, FSW of low-carbon AISI 1006 steel was carried out to study the microstructure and mechanical properties of the resulting joints at both room temperature (RT) and 200 °C. In the parameter space investigated here, a rotational tool speed and translation feed combination of 1200 rpm and 60 mm/min produced a defect-free weld with balanced mechanical properties and a superior Vickers microhardness profile compared to all other conditions and to base metal (BM). At faster translation feeds (100 and 150 mm/min), wormhole defects were observed in the weld microstructure and were attributed to higher strain rate experienced by the weld zone. Under tensile loading, welded material exhibited yield strength that was up to 86 and 91% of the BM at RT and 200 °C, respectively. On the other hand, tensile strength of welded material was nearly similar to that of the base metal at both RT and 200 °C. However, at both temperatures the tensile ductility of the welded joints was observed to be significantly lower than the BM. Annealing of the 1200 rpm and 60 mm/min FSW specimen resulted in tensile strength of 102% compared to base material and 47% increase in the strain at failure compared to the as-welded specimen. The Charpy impact values revealed up to 62 and 53% increase in the specific impact energy for the 1200 rpm and 60 mm/min welded joints as compared with the BM.     

Deployment of real-time systems in the cloud environment

Interest in real-time systems has grown considerably over recent years, primarily due to significant increase in the use of smart technologies and latency-sensitive applications such as cloud gaming, audio/video streaming, and smart homes. Significant work has been done on resource mapping in the cloud environment, and a number of promising results have been established accordingly where the focus is mainly on resource provisioning. However, the applicability of cloud computing services for real-time systems generated from smart systems is still in its infancy and remains unexplored, relatively. To address this gap, we propose a model for the smart systems that periodically offload computational workload to the cloud environment where virtual machines are allocated according to rate-monotonic scheduling policy to ensure requests are processed within the associated deadlines. Deadlines of tasks have been relaxed to improve server utilization as well as maintain a level of confidence in the timing constrains. Experimental results are discussed to highlight the applicability of static priority assignment for the workload in the context of virtual machines allocation.

     

Project Scheduling Using Fuzzy Set Concepts

Probabilistic methods are being used increasingly in construction engineering. However, when a parameter is expressed in linguistic rather than mathematical terms, classical probability theory fails to incorporate the information. The linguistic variables can be translated into mathematical measures using fuzzy set and system theory. A construction management problem, i.e., estimation of the duration of an activity, is solved using this theory. In order to implement the proposed technique, various membership functions need to be estimated using judgment or with the assistance of experts. The proposed technique is not sensitive to small variations in the membership values. This is a very desirable property. However, the method is sensitive to the choice of the fuzzy relations. The uncertainty in the fuzzy relations can be modeled along with other sources of uncertainty. The mean and variance of the parameters involved in the problem under consideration are estimated here using a new method. The method maximizes the product of the sum of the membership associations for a certain frequency of occurrence and the corresponding frequency of occurrence. One of the main advantages of the proposed technique is that it can be easily implemented in existing computer programs for project scheduling.     

Alpha-Synuclein: The Spark That Flames Dopaminergic Neurons,In Vitro and In Vivo Evidence

Mitochondria, α-syn fibrils and the endo-lysosomal system are key players in the pathophysiology of Parkinson’s disease. The toxicity of α-syn is amplified by cell-to-cell transmission and aggregation of endogenous species in newly invaded neurons. Toxicity of α-syn PFF was investigated using primary cultures of dopaminergic neurons or on aged mice after infusion in the SNpc and combined with mild inhibition of GBA. In primary dopaminergic neurons, application of α-syn PFF induced a progressive cytotoxicity associated with mitochondrial dysfunction, oxidative stress, and accumulation of lysosomes suggesting that exogenous α-syn reached the lysosome (from the endosome). Counteracting the α-syn endocytosis with a clathrin inhibitor, dopaminergic neuron degeneration was prevented. In vivo, α-syn PFF induced progressive neurodegeneration of dopaminergic neurons associated with motor deficits. Histology revealed progressive aggregation of α-syn and microglial activation and accounted for the seeding role of α-syn, injection of which acted as a spark suggesting a triggering of cell-to-cell toxicity. We showed for the first time that a localized SNpc α-syn administration combined with a slight lysosomal deficiency and aging triggered a progressive lesion. The cellular and animal models described could help in the understanding of the human disease and might contribute to the development of new therapies.     

Estimation and optimization based ill-posed inverse restoration using fuzzy logic

Intelligent systems ranging from neural network, evolutionary computations and swarm intelligence to fuzzy systems are extensively exploited by researchers to solve variety of problems. In this paper focus is on deblurring that is considered as an inverse problem. It becomes ill-posed when noise contaminates the blurry image. Hence the problem is very sensitive to small perturbation in data. Conventionally, smoothness constraints are considered as a remedy to cater the sensitivity of the problem. In this paper, fuzzy rule based regularization parameter estimation is proposed with quadratic functional smoothness constraint. For deblurring image in the presence of noise, a constrained least square error function is minimized by the steepest descent algorithm. Visual results and quantitative measurements show the efficiency and robustness of the proposed technique compared to the state of the art and recently proposed methods.     

Performance characteristics of an elliptic hydrostatic bearing and comparative analysis based on Stokes’ conditions

The Stokesian motion of viscous fluid lubricants in a class of externally pressurized hydrostatic bearings due to a pressure source has been studied by complex potential theory and conformal mapping. The outer boundary of the bearing is a (2:1) ellipse, and the inner boundary is a concentric circle. The complex potential function that satisfies the boundary conditions of the bearing has been constructed by reducing the flow inside an annulus. Applying the Riemann’s mapping theorem and using Jacobian elliptic functions, the exact mapping transformation could be found. A two-dimensional pressure distribution has been determined analytically and is presented in graphical form. An approximate evaluation of the total thrust is also calculated. This research is done through the selected configuration of the “elliptic-circle” domain. The deduced results are compared with the results of the preceding investigations, and conformity is found excellent.     

Thin film flow of the water‐based carbon nanotubes hybrid nanofluid under the magnetic effects

In this article, the effects of magnetic field versus the thin liquid film water‐based ferrum oxide (Fe₃O₄) and carbon nanotubes (CNTs) nanofluids have been studied through stretching cylinder. The iron oxide and CNTs (single‐wall [SWCNTs] or multi‐wall [MWCNTs]) have been used as nanoparticles in carrier fluid water (H₂O). To the flow field, magnetic effects are applied vertically. The modeled system of partial differential equations are transformed to nonlinear ordinary differential equations by selecting variables. The analytic solution has been obtained through homotopy analysis method. The obtained results are further compared with the numerical ND‐solve method. The embedded constraints impacts are focused on pressure distribution, velocity profile, heat transfer, Nusselt number, and Skin friction through graphical illustration and tables. The dispersion of Fe₃O₄ and CNTs in base fluid significantly enhanced the mechanism of heat transfer. Moreover, from the results, it has been observed that the MWCNTs have a greater impact on heat transfer, velocity, and pressure profile.     

Effects of osmotic pretreatment and frying conditions on quality and storage stability of vacuum-fried pumpkin chips

The effects of osmotic (OP), ultrasound-assisted osmotic pretreatment (UAOP) and frying conditions on quality and storage stability of vacuum fried pumpkin chips were investigated. The pumpkin samples were pretreated in maltodextrin solution and subsequently fried at different temperatures (90–110 °C) and time periods (10–30 min). The results demonstrated that the moisture content, water activity, lightness, yellowness and carotenoid content of the fried chips decreased, while oil content, hardness and a* (dark brown colour) value increased with increasing frying temperature and time. UAOP reduced about 16.0% of oil absorption and enhanced approximately 70% of carotenoid retention in the fried chips. UAOP samples were also more stable during storage than the untreated ones, indicated by lower degradation kinetics constants of key quality parameters. The proposed pretreatment could be an effective method for food industries to develop vacuum fried pumpkin chips with improved quality and stability.     

Genotyping of the kappa‐casein and beta‐lactoglobulin genes in Anatolian water buffalo by PCR‐RFLP

The objective of this study was to identify allele and genotype frequencies of the κ‐CN and β‐LG genes in Anatolian water buffalo. A total of 126 water buffalos from Turkey were genotyped using the PCR‐RFLP method. For gene κ‐CN, only B allele and BB genotype were observed. And for gene β‐LG, two types of alleles (A and B) and three types of genotypes were observed. The genotype frequencies of AA, AB and BB of β‐LG in Anatolian water buffalo were 0.254, 0.698 and 0.048, respectively. Surprisingly, the frequency of allele A was higher than that of allele B in contrast to world buffalo breeds.     

Production of waste tyre oil and experimental investigation on combustion,engine performance and exhaust emissions

In this study, waste tyre was pyrolyzed at different conditions such as temperature, heating rate and inert purging gas (N₂) flow rate. Pyrolysis parameters were optimized. Optimum parameters were determined. The main objective of this study was to investigate combustion, performance and emissions of diesel and waste tyre oil fuel blend. Experimental investigation was performed in a single cylinder, direct injection, air cooled diesel engine at maximum engine torque speed of 2200 rpm and four different engine load including 3.75, 7.5, 11.25 and 15 Nm. The effects of waste tyre oil on combustion characteristics such as cylinder pressure, heat release rate, ignition delay (ID), combustion duration, engine performance were investigated. In-cylinder pressure and heat release rate increased with waste tyre oil fuel blend (W10) with the increase of engine load. In addition, ID was shortened with the increase of engine load for test fuels but it increased with the addition of waste tyre oil. Lower imep values were obtained because of the lower calorific value of waste tyre oil fuels. Maximum thermal efficiencies were determined as 28.27% and %25.12 with diesel and W10 respectively at 11.25 Nm engine load. When test results were examined, it was seen that waste tyre oil highly affected combustion characteristics, performance and emissions.