On reduction complexity of Heegaard splittings

AbstractLet ∪F W be a Heegaard splitting of a closed, connected, orientable 3-manifold M with genus n. We introduce a reduction complexity, δ, for the Heegaard splitting, and conclude that: 1.(1) δ ⩾ max{2, n} if and only if V ∪F W is reducible;2.(2) δ ⩾ 2 if and only if V ∪F W is weakly reducible,3.(3) δ > n if and only if M has exactly δ − n connected sum factors which are homeomorphic to S1 × S2

Methodology for Optimal Sizing of Hybrid Power System Usingparticle Swarm Optimization and Dynamic Programming

AbstractA methodology for optimal sizing of hybrid battery-ultracapacitor power system (HPS) is presented. The purpose of the proposed methodology is to locate the optimal voltage levelfor HPS used in a plug-in hybrid electric vehicle (PHEV). A combined optimization framework for a HPS is proposed and the optimization problem is solved in a bi-level manner. The framework contains two nested optimization loops. The outer loop evaluates the selected parameters throughparticle swarm optimization (PSO) algorithm, while the inner loop generates the optimal control strategy and calculates the costs through dynamic programming (DP) algorithm. The Chinese Typical City Bus Drive Cycle (CTCBDC) has beenused to verify and evaluate the performance of the proposed methodology. The optimization result shows that higher voltage degree usually means better performance and the battery tends to provide a constant power for the HPS. It is noted that the constant powercloses to the high efficiency district of the battery and DC/DC convertor. After that the optimal result is further analyzed undervarious optimization goals andbattery charge/discharge current constrains

Gene co-expression network analysis identifies BRCC3 as a key regulator in osteogenic differentiation of osteoblasts through a β-catenin signaling dependent pathway

Objective(s): The prognosis of osteoporosis is very poor, and it is very important to identify a biomarker for prevention of osteoporosis. In this study, we aimed to identify candidate markers in osteoporosis and to investigate the role of candidate markers in osteogenic differentiation. Materials and Methods: Using Weighted Gene Co-Expression Network analysis, we identified three hub genes might associate with osteoporosis. The mRNA expression of hub genes in osteoblasts from osteoporosis patients or healthy donor was detected by qRT-PCR. Using siRNA and overexpression, we investigated the role of hub gene BRCC3 in osteogenic differentiation by alkaline phosphatase staining and Alizarin red staining. Moreover, the role of β-catenin signaling in the osteogenic differentiation was detected by using β-catenin signaling inhibitor XAV939.Results: We identified three hub genes that might associate with osteoporosis including BRCC3, UBE2N, and UBE2K. UBE2N mRNA and UBE2K mRNA were not changed in osteoblasts isolated from osteoporosis patients, compared with healthy donors, whereas BRCC3 mRNA was significantly increased. Depletion of BRCC3 promoted the activation of alkaline phosphatase and formation of calcified nodules in osteoblasts isolated from osteoporosis patients and up-regulated β-catenin expression. XAV939 reversed the BRCC3 siRNA-induced osteogenic differentiation. Additionally, inhibited osteogenic differentiation was also observed after BACC3 overexpression, and this was accompanied by decreased β-catenin expression.Conclusion: BRCC3 is an important regulator for osteogenic differentiation of osteoblasts through β-catenin signaling, and it might be a promising target for osteoporosis treatment

The Ubiquitin/Proteasome System Mediates Entry and Endosomal Trafficking of Kaposi's Sarcoma-Associated Herpesvirus in Endothelial Cells

Ubiquitination, a post-translational modification, mediates diverse cellular functions including endocytic transport of molecules. Kaposi's sarcoma-associated herpesvirus (KSHV), an enveloped herpesvirus, enters endothelial cells primarily through clathrin-mediated endocytosis. Whether ubiquitination and proteasome activity regulates KSHV entry and endocytosis remains unknown. We showed that inhibition of proteasome activity reduced KSHV entry into endothelial cells and intracellular trafficking to nuclei, thus preventing KSHV infection of the cells. Three-dimensional (3-D) analyses revealed accumulation of KSHV particles in a cytoplasmic compartment identified as EEA1+ endosomal vesicles upon proteasome inhibition. KSHV particles are colocalized with ubiquitin-binding proteins epsin and eps15. Furthermore, ubiquitination mediates internalization of both KSHV and one of its receptors integrin β1. KSHV particles are colocalized with activated forms of the E3 ligase c-Cbl. Knock-down of c-Cbl or inhibition of its phosphorylation reduced viral entry and intracellular trafficking, resulting in decreased KSHV infectivity. These results demonstrate that ubiquitination mediates internalization of both KSHV and one of its cognate receptors integrin β1, and identify c-Cbl as a potential E3 ligase that facilitates this process

A Combined Cooperative Braking Model with a Predictive Control Strategy in an Electric Vehicle

Cooperative braking with regenerative braking and mechanical braking plays an important role in electric vehicles for energy-saving control. Based on the parallel and the series cooperative braking models, a combined model with a predictive control strategy to get a better cooperative braking performance is presented. The balance problem between the maximum regenerative energy recovery efficiency and the optimum braking stability is solved through an off-line process optimization stream with the collaborative optimization algorithm (CO). To carry out the process optimization stream, the optimal Latin hypercube design (Opt LHD) is presented to discrete the continuous design space. To solve the poor real-time problem of the optimization, a high-precision predictive model based on the off-line optimization data of the combined model is built, and a predictive control strategy is proposed and verified through simulation. The simulation results demonstrate that the predictive control strategy and the combined model are reasonable and effective

MicroRNA-34a Promotes EMT and Liver Fibrosis in Primary Biliary Cholangitis by Regulating TGF-β1/smad Pathway

Background and Aims. Primary biliary cholangitis (PBC) is an autoimmune cholestatic liver disease. We found microRNA-34a (miR-34a), as the downstream gene of p53, was overexpressed in some of fibrogenic diseases. In this study, we sought to explore whether miR-34a plays a role in the fibrosis of PBC. Methods. The peripheral blood of PBC patients and controls was collected to analyze the level of miR-34a. Human intrahepatic biliary epithelial cells (HIBEC) were cultured. The expression of miR-34a was regulated by miR-34a mimics and inhibitor. The biomarkers of epithelium-mesenchymal transition (EMT), fibrogenesis, inflammation, and transforming growth factor- (TGF-) β1/smad pathway were analyzed. Results. We found that miR-34a was overexpressed in the peripheral blood in PBC patients. In vitro, overexpressed miR-34a increased the EMT and fibrogenesis activity of HIBEC. Transforming growth factor-beta type 1 receptor (TβR1), TGF-β1, and p-smad2/3 were upregulated by miR-34a. Inflammatory factors such as IL-6 and IL-17 were also upregulated. Finally, we showed that miR-34a promoted EMT and liver fibrosis in PBC by targeting the TGF-β1/smad pathway antagonist transforming growth factor-beta-induced factor homeobox 2 (TGIF2). Conclusions. Our findings show that miR-34a plays an important role in the EMT and fibrosis of PBC through the TGF-β1/smad pathway by targeting TGIF2. This study suggests that miR-34a may be a new marker of fibrogenesis in PBC. Inhibition of miR-34a may be a promising strategy in treating PBC and improving the prognosis of the disease

Application Study on the Dynamic Programming Algorithm for Energy Management of Plug-in Hybrid Electric Vehicles

To explore the problems associated with applying dynamic programming (DP) in the energy management strategies of plug-in hybrid electric vehicles (PHEVs), a plug-in hybrid bus powertrain is introduced and its dynamic control model is constructed. The numerical issues, including the discretization resolution of the relevant variables and the boundary issue of their feasible regions, were considered when implementing DP to solve the optimal control problem of PHEVs. The tradeoff between the optimization accuracy when using the DP algorithm and the computational burden was systematically investigated. As a result of overcoming the numerical issues, the DP-based approach has the potential to improve the fuel-savings potential of PHEVs. The results from comparing the DP-based strategy and the traditional control strategy indicate that there is an approximately 20% improvement in fuel economy