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The effects of an ultrasonic surface rolling process (USRP) on the localized corrosion behavior of 7B50-T7751 aluminum alloy in a sodium chloride + hydrogen peroxide solution were investigated through microstructural observation, immersion testing, and electrochemical measurements. The results revealed that this alloy is prone to pitting. However, the localized corrosion resistance can be significantly improved via both one-pass USRP and 12-pass USRP treatment. Furthermore, in the test solution, the thickness and the acceptor density of the passivation film were affected by the USRP treatment. The improved corrosion resistance of one-pass USRP-treated samples resulted mainly from the introduced compressive residual stress. However, this stress played a secondary role in the considerable enhancement observed for the corrosion resistance of the 12-pass USRP-treated samples. This enhancement is attributed primarily to the nanocrystalline surface and homogeneous surface microstructure induced by the multiple-pass USRP treatment.Composed of multi-strand parallel high-strength wires or steel strands, the stayed cables have been widely used recently in stayed bridges or suspension bridges owing to their light weight and high bearing capacity, especially the steel strands. Meanwhile, chloride-induced corrosion of steel strands is one of the most considerable factors for the durability of the stayed cable exposed to marine environments. The fatigue caused by both cyclic loading and corrosion can affect the life of the steel strands. Besides, the current studies related to the effects of the aforementioned two impact factors on the life of the steel strands either considered the fatigue only, or took the two impact factors into account separately. The coupling effects of fatigue and corrosion on the life of the steel strands are required to be further explored and discussed. Consequently, it is essential to create a model to predict the life of the steel strands with the coupling effects taken into consideration. In this paper, an indoor -width ratios, length-depth ratios, and depth-to-width ratios of the pits was obtained to determine the stress concentration factor based on the multi-dimensional linear regression method. The fatigue notch factor of components can be deduced by the stress concentration factor, and the life of the steel strands can be deduced by both of them. The findings are expected to be useful in realistically predicting the durability of wire structures.Alzheimer's disease (AD) is a complex and chronic neurodegenerative disorder that involves a progressive and severe decline in cognition and memory. During the last few decades a considerable amount of research has been done in order to better understand tau-pathology, inflammatory activity and neuronal synapse loss in AD, all of them contributing to cognitive decline. Early hippocampal network dysfunction is one of the main factors associated with cognitive decline in AD. Much has been published about amyloid-beta1-42 (Aβ1-42)-mediated excitotoxicity in AD. However, increasing evidence demonstrates that the remodeling of the inhibitory gamma-aminobutyric acid (GABAergic) system contributes to the excitatory/inhibitory (E/I) disruption in the AD hippocampus, but the underlying mechanisms are not well understood. In the present study, we show that hippocampal injection of Aβ1-42 is sufficient to induce cognitive deficits 7 days post-injection. We demonstrate using in vitro whole-cell patch-clamping an increased inhibitory GABAergic tonic conductance mediated by extrasynaptic type A GABA receptors (GABAARs), recorded in the CA1 region of the mouse hippocampus following Aβ1-42 micro injection. Such alterations in GABA neurotransmission and/or inhibitory GABAARs could have a significant impact on both hippocampal structure and function, causing E/I balance disruption and potentially contributing to cognitive deficits in AD.The Internet of Things (IoT) domain presents a wide spectrum of technologies for building IoT applications. The requirements are varying from one application to another granting uniqueness to each IoT system. Each application demands custom implementations to achieve efficient, secure and cost-effective environments. They pose a set of properties that cannot be addressed by a single-based protocol IoT network. Such properties are achievable by designing a heterogeneous IoT system, which integrates diverse IoT protocols and provides a network management solution to efficiently manage the system components. This paper proposes an IoT message-based communication model applied atop the IoT protocols in order to achieve functional scalability and network management transparency agnostic to the employed communication protocol. The paper evaluates the proposed communication model and proves its functional scalability in a heterogeneous IoT system. The experimental assessment compares the payload size of the proposed system with respect to the LwM2M standard, a protocol designed specifically for IoT applications. In addition, the paper discusses the energy consumption introduced by the proposed model as well as the options available to reduce such impact.A bottom-up material modeling based on a nonlocal crystal plasticity model requires information of a large set of physical and phenomenological parameters. Because of the many material parameters, it is inherently difficult to determine the nonlocal crystal plasticity parameters. Therefore, a robust method is proposed to parameterize the nonlocal crystal plasticity model of a body-centered cubic (BCC) material by combining a nanoindentation test and inverse analysis. Nanoindentation tests returned the load-displacement curve and surface imprint of the considered sample. The inverse analysis is developed based on trust-region-reflective algorithm, which is the most robust optimization algorithm for the considered non-convex problem. this website The discrepancy function is defined to minimize both the load-displacement curves and the surface topologies of the considered material under applying varied indentation forces obtained from numerical models and experimental output. The numerical model results based on the identified material properties show good agreement with the experimental output.

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