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The in situ imaging of the cutting process exhibits outstanding advantages in reconstructing the precise and visual thermoplastic deformation fields. The physical and geometric characteristics of deformation fields provide a deeper understanding of the cutting processes. In this paper, a mechanism-image hybrid analysis method is proposed to acquire the characteristics of the serrated chip deformation in the orthogonal cutting of TA15 titanium alloy based on in situ imaging. The established hybrid analysis method combines the shear-plane theory with the streamline method and image segmentation method, which realizes the identification of pixel coordinates of the main shear plane (MSP) and the primary shear zone (PSZ) and then the extraction of the physical and geometric variables from the digital image correlation (DIC) full-field measurements. Consequently, the variations of equivalent strain rate, strain, temperature, and the geometric characterizations of MSP and PSZ during an individual serration formation of TA15 titanium alloy were quantitatively investigated. It was found that the physical and geometric variables reached stability in the final stage of serration evolution and were averaged as the DIC-based equivalent characterizations to analyze the impact of cutting depth and tool rake angle. Meanwhile, the DIC-based equivalent characterizations were compared with the results obtained by the classical analytical models to illustrate the advantages of the DIC-based analysis. The findings also support that the established hybrid analysis method holds the potential to characterize the serrated chip formation of other materials and improve the models of PSZ. [ABSTRACT FROM AUTHOR]

The carbon emissions trading market and direct power purchases by large consumers are two promising directions of power system development. To trace the carbon emission flow in the power grid, the theory of carbon emission flow is improved by allocating power loss to the load side. Based on the improved carbon emission flow theory, an optimal dispatch model is proposed to optimize the cost of both large consumers and the power grid, which will benefit from the carbon emissions trading market. Moreover, to better simulate reality, the direct purchase of power by large consumers is also considered in this paper. The OPF (optimal power flow) method is applied to solve the problem. To evaluate our proposed optimal dispatch strategy, an IEEE 30-bus system is used to test the performance. The effects of the price of carbon emissions and the price of electricity from normal generators and low-carbon generators with regards to the optimal dispatch are analyzed. The simulation results indicate that the proposed strategy can significantly reduce both the operation cost of the power grid and the power utilization cost of large consumers. [ABSTRACT FROM AUTHOR]

In power systems, although the inertia energy in power sources can partly cover power unbalances caused by load disturbance or renewable energy fluctuation, it is still hard to maintain the frequency deviation within acceptable ranges. However, with the vehicle-to-grid (V2G) technique, electric vehicles (EVs) can act as mobile energy storage units, which could be a solution for load frequency control (LFC) in an isolated grid. In this paper, a LFC model of an isolated micro-grid with EVs, distributed generations and their constraints is developed. In addition, a controller based on multivariable generalized predictive control (MGPC) theory is proposed for LFC in the isolated micro-grid, where EVs and diesel generator (DG) are coordinated to achieve a satisfied performance on load frequency. A benchmark isolated micro-grid with EVs, DG, and wind farm is modeled in the Matlab/Simulink environment to demonstrate the effectiveness of the proposed method. Simulation results demonstrate that with MGPC, the energy stored in EVs can be managed intelligently according to LFC requirement. This improves the system frequency stability with complex operation situations including the random renewable energy resource and the continuous load disturbances. [ABSTRACT FROM AUTHOR]

Background: Amyloid-β (Aβ) 42 has been implicated as the initiating molecule in the pathogenesis of Alzheimer's disease (AD); thus, therapeutic strategies that target Aβ42 are of great interest. γ-Secretase modulators (GSMs) are small molecules that selectively decrease Aβ42. We have previously reported that many acidic steroids are GSMs with potencies ranging in the low to mid micromolar concentration with 5β-cholanic acid being the most potent steroid identified GSM with half maximal effective concentration (EC50) of 5.7 µM. Results: We find that the endogenous cholesterol metabolite, 3β-hydroxy-5-cholestenoic acid (CA), is a steroid GSM with enhanced potency (EC50 of 250 nM) relative to 5β-cholanic acid. CA i) is found in human plasma at ~100-300 nM concentrations ii) has the typical acidic GSM signature of decreasing Aβ42 and increasing Aβ38 levels iii) is active in in vitro γ-secretase assay iv) is made in the brain. To test if CA acts as an endogenous GSM, we used Cyp27a1 knockout (Cyp27a1-/-) and Cyp7b1 knockout (Cyp7b1-/-) mice to investigate if manipulation of cholesterol metabolism pathways relevant to CA formation would affect brain Aβ42 levels. Our data show that Cyp27a1-/- had increased brain Aβ42, whereas Cyp7b1-/- mice had decreased brain Aβ42 levels; however, peripheral dosing of up to 100 mg/kg CA did not affect brain Aβ levels. Structure-activity relationship (SAR) studies with multiple known and novel CA analogs studies failed to reveal CA analogs with increased potency. Conclusion: These data suggest that CA may act as an endogenous GSM within the brain. Although it is conceptually attractive to try and increase the levels of CA in the brain for prevention of AD, our data suggest that this will not be easily accomplished. [ABSTRACT FROM AUTHOR]