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524 result(s) for "Zhang, Han-jun"
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Acetaminophen attenuates lipopolysaccharide-induced cognitive impairment through antioxidant activity
Background Considerable evidence has shown that neuroinflammation and oxidative stress play an important role in the pathophysiology of postoperative cognitive dysfunction (POCD) and other progressive neurodegenerative disorders. Increasing evidence suggests that acetaminophen (APAP) has unappreciated antioxidant and anti-inflammatory properties. However, the impact of APAP on the cognitive sequelae of inflammatory and oxidative stress is unknown. The objective of this study is to explore whether APAP could have neuroprotective effects on lipopolysaccharide (LPS)-induced cognitive impairment in mice. Methods A mouse model of LPS-induced cognitive impairment was established to evaluate the neuroprotective effects of APAP against LPS-induced cognitive impairment. Adult C57BL/6 mice were treated with APAP half an hour prior to intracerebroventricular microinjection of LPS and every day thereafter, until the end of the study period. The Morris water maze was used to assess cognitive function from postinjection days 1 to 3. Animal behavioural tests as well as pathological and biochemical assays were performed to evaluate LPS-induced hippocampal damage and the neuroprotective effect of APAP. Results Mice treated with LPS exhibited impaired performance in the Morris water maze without changing spontaneous locomotor activity, which was ameliorated by treatment with APAP. APAP suppressed the accumulation of pro-inflammatory cytokines and microglial activation induced by LPS in the hippocampus. In addition, APAP increased SOD activity, reduced MDA levels, modulated glycogen synthase kinase 3β (GSK3β) activity and elevated brain-derived neurotrophic factor (BDNF) expression in the hippocampus. Moreover, APAP significantly decreased the Bax/Bcl-2 ratio and neuron apoptosis in the hippocampus of LPS-treated mice. Conclusions Our results suggest that APAP may possess a neuroprotective effect against LPS-induced cognitive impairment and inflammatory and oxidative stress via mechanisms involving its antioxidant and anti-inflammatory properties, as well as its ability to inhibit the mitochondrial permeability transition (MPT) pore and the subsequent apoptotic pathway.
Asymptotic Inference in the Random Coefficient Autoregressive Model with Time-functional Variance Noises
This paper considers the random coefficient autoregressive model with time-functional variance noises, hereafter the RCA-TFV model. We first establish the consistency and asymptotic normality of the conditional least squares estimator for the constant coefficient. The semiparametric least squares estimator for the variance of the random coefficient and the nonparametric estimator for the variance function are constructed, and their asymptotic results are reported. A simulation study is presented along with an analysis of real data to assess the performance of our method in finite samples.
Markov branching processes with killing and resurrection
In this paper, we consider Markov branching processes with killing and resurrection. We first show that the Markov branching process with killing and stable resurrection is just the Feller minimum process which is honest and thus unique. We then further show that this honest Feller minimum process is not only positive recurrent but also strongly ergodic. The generating function of the important stationary distribution is explicitly expressed. For the interest of comparison and completeness, the results of the Markov branching processes with killing and instantaneous resurrection are also briefly stated. A new result regarding strong ergodicity of this difficult case is presented. The birth and death process with killing and resurrection together with another example is also analyzed.
Ergodicity of a class of nonlinear time series models in random environment domain
In this paper, we study the problem of a variety of nonlinear time series model Xn+1 = TZn+1(X(n), …, X(n − Zn+1), en+1(Zn+1)) in which Zn is a Markov chain with finite state space, and for every state i of the Markov chain, en(i) is a sequence of independent and identically distributed random variables. Also, the limit behavior of the sequence Xn defined by the above model is investigated. Some new novel results on the underlying models are presented.
Effects of Fuel Supply Advance Angles on Performance of Engine Fueled with Butanol Diesel
The experiments of the fuel economy performance and emission characteristics of diesel engine fueled with butanol diesel were performed on a dual-cylinder direct injection diesel engine at different fuel supply advance angles. The results showed that whether the fuel supply advance angle is too large or too small, it will increase the fuel consumption. As the fuel supply advance angle is 20°CA, the brake specific fuel consumption is the best of the butanol diesel engine. When the supply advance angle becomes larger, the smoke and CO emissions can be reduced on the medium and high loads, but NOX emissions are significantly increased on a variety of load conditions. The engine will obtain the lowest HC emissions, as the fuel supply advance angle is 20°CA.
Controlled Manipulation of Intermediate State in a Type-I Superconductor
The intermediate state of type-I superconductors presents a classic paradigm of modulated pattern formation, arising from the competition between short-range attractive and long-range repulsive vortex-vortex interactions. However, direct visualization and, more importantly, active control over the topology and dynamics of these flux structures have remained significant challenges, limiting our ability to manipulate them for fundamental studies and potential applications. Here, using low-temperature magnetic force microscopy, we achieve direct imaging and controllable manipulation of the flux structures in a high-purity tantalum single crystal. We systematically track the evolution of flux morphology - from tubes to stripes - during flux penetration and expulsion, revealing a pronounced topological hysteresis originating from the geometric barrier. Furthermore, we demonstrate precise local control by using the magnetic tip to drag and merge individual flux tubes and to reconfigure entire stripe domains. Under global alternating current (AC) excitation, we discover a reversible stripe-grid-stripe transition, a dynamic reorganization driven by current-induced flux penetration and pinning effects. The corresponding phase diagram shows that the threshold current decreases with magnetic field but increases with AC frequency. Our work establishes a pathway for active flux manipulation in type-I superconductors, revealing rich dynamics and paving the way for flux-based superconducting devices.
The Influence of a Drilled Hole on the Deformation Characteristics and Burst Proneness of Coal Samples
Borehole drilling in a coal seam is an efficient way to relieve ground stress and prevent coal burst. The deformational behavior and failure mechanism of a Φ50mm×L100mm coal sample with a 2–4 mm diameter drilling hole were studied under standard burst proneness laboratory testing. The results show that with the increase in borehole diameter, the uniaxial compressive strength (RC), impact energy index (KE), and elastic energy index (WET) decrease, and the dynamic failure time (DT) is prolonged. The overall burst proneness of the seam changes from strong to weak for a 4 mm hole sample. A high speed camera and acoustic emission (AE) monitor were used to study the deformation procedure and failure mode of the samples. It is found that cracks are propagated around the drilled hole at the initial stage of the loading, and the AE event and energy are weakened around the peak load. This suggests that the hole may significantly reduce the brittleness of the sample. The numerical method is employed to provide further insights on the internal deformation characteristics; the effect of hole sizes with diameters of 2–10 mm is also discussed. This paper provides quantified analysis methodology, monitoring technology, and borehole optimization for pressure relief drilling and burst proneness reduction in high coal burst-prone seams.
Nonlinear inelastic electron scattering revealed by plasmon-enhanced electron energy-loss spectroscopy
Electron energy-loss spectroscopy uses inelastically scattered electrons to provide information about a material’s chemical composition. It is now shown that localized plasmonic excitations can lead to nonlinear scattering, significantly enhancing the signals arising from inelastic electrons. Electron energy-loss spectroscopy is a powerful tool for identifying the chemical composition of materials 1 , 2 , 3 , 4 , 5 . It relies mostly on the measurement of inelastic electrons, which carry specific atomic or molecular information. Inelastic electron scattering, however, has a very low intensity, often orders of magnitude weaker than that of elastically scattered electrons. Here, we report the observation of enhanced inelastic electron scattering from silver nanostructures, the intensity of which can reach up to 60% of its elastic counterpart. A home-made scanning probe electron energy-loss spectrometer 6 was used to produce highly localized plasmonic excitations, significantly enhancing the strength of the local electric field of silver nanostructures. The intensity of inelastic electron scattering was found to increase nonlinearly with respect to the electric field generated by the tip–sample bias, providing direct evidence of nonlinear electron scattering processes.
Achieving high throughput and TCP Reno fairness in delay-based TCP over large networks
The transport control protocol (TCP) has been widely used in wired and wireless Intemet applications such as FTP, email and HTTP. Numerous congestion avoidance algorithms have been proposed to improve the performance of TCP in various scenarios, especially for high speed and wireless networks. Although different algorithms may achieve different performance improvements under different network conditions, designing a congestion algorithm that can perform well across a wide spectrum of network conditions remains a great challenge. Delay-based TCP has a potential to overcome above challenges. However, the unfairness problem of delay-based TCP with TCP Reno blocks widely the deployment of delay-based TCP over wide area networks. In this paper, we proposed a novel delay-based congestion control algorithm, named FAST-FIT, which could perform gracefully in both ultra high speed networks and wide area networks, as well as keep graceful faimess with widely deployed TCP Reno hosts. FAST-FIT uses queuing delay as a primary input for controlling TCP congestion window. Packet loss is used as a secondary signal to adaptively adjust parameters of primary control process. Theoretical analysis and experimental results show that the performance of the algorithm is significantly improved as compared to other state-of-the-art algorithms, while maintaining good faimess.