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The rheological and adhesive properties of bis‐urea functionalized low‐molecular‐weight polyisobutylenes (PIBUT) are investigated. The polymers, which can interact through supramolecular hydrogen bonds, can self‐organize over times of the order of days at room temperature. This organized structure has been identified by small angle X‐ray scattering (SAXS) and its rheological properties indicate the behaviour of a soft viscoelastic gel. The ordered structure can be disrupted by temperature and shear so that at 80 °C, the material behaves as a highly viscoelastic fluid and no SAXS peak is observed. When cooled back at room temperature, the PIBUT retrieves its ordered structure and gel properties after 20 h of annealing. This very slow molecular dynamics gives PIBUT a highly dissipative nature upon deformation, which combined with strongly interacting moieties results in very interesting adhesive properties both on steel surfaces but more importantly on typical low adhesion surfaces such as silicone. A strategy based on the controlled incorporation of supramolecular bonds in a covalently crosslinked network appears promising for the development of a new generation of highly interacting and dissipative soft adhesives.  相似文献   
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Today, the Wireless Sensor Networks (WSNs) are increasingly used in many applications, and in parallel the scientific researches to improve the features of such networks are accelerated. As the nodes are small components that suffer from very limited energy resources, several researches carried out at the MAC layer in order to minimize energy costs. The techniques based on periodic active/passive mode are energy efficient, but the node can not adapt the behavior of the transceiver according to the network traffic. Our approach aims to reduce the latency without increasing energy consumption. We propose to manage the radio in a dynamic way according to ON/OFF Markov model. The passage from passive to active mode is set according to the transition probability from OFF to ON state. Based on this probability, we give the period that the transceiver can stay in sleep mode. Through simulation we show that the proposed technique outperforms the well known MAC protocol for WSN.  相似文献   
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In the present paper, a three-dimensional numerical model has been built using ANSYS code to analyze the static and fatigue behavior of a welded design based on four rectangular profiles under damped loads for automotive application. The fatigue of the proposed design is generally influenced by a number of factors. The aim of this study is to investigate the effect of the load level, the stress ratio, the mean stress theory, the geometry size, the weld bead height, the temperature of the weld bead on the durability (P1), and the maximum of von Mises stress (P2) at the critical areas in the welded structure. As well as the length and the stiffness of the spring have been furtherly investigated. For this purpose, the application of the Taguchi method with computational simulation was performed for the target to determine the optimum operating parameters conditions. The results indicated that the optimum levels yielding a higher performance for P1 and P2 were (L1, L2, L2, L3, L1, L1, L3, and L3) and (L2, L3, L3, L3, L3, L3, L3, and L2), respectively. Thus, it revealed that the weld temperature was the predominant parameter influencing P1 and the mean stress theory factor was the most significant parameter influencing P2. This study led to defining a regression equation relating the output parameters with the selected factors. Consequently, the percentage error between regression equation calculations and computational outputs of fatigue life and maximum von Mises stress corresponding to the most optimal combinations obtained from Taguchi calculations was 0.92% and 0.63%, respectively. In fact, several parameters have been employed in this durability assessment to characterize the behavior of welded rectangular profiles prototype to predict the overall behavior of the suspension system of the automotive.  相似文献   
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Multiple sclerosis (MS) is an autoimmune disease affecting the central nervous system associated with chronic inflammation, demyelination, and axonal damage. MS is a highly heterogeneous disease that leads to discrepancies regarding the clinical appearance, progression, and therapy response of patients. Therefore, there is a strong unmet need for clinically relevant biomarkers capable of recapitulating the features of the disease. Experimental autoimmune encephalomyelitis (EAE) is a valuable model for studying the pathophysiology of MS as it recapitulates the main hallmarks of the disease: inflammation, blood-brain barrier (BBB) disruption, gliosis, myelin damage, and repair mechanisms. In this study, we used the EAE-PLP animal model and established a molecular RNA signature for each phase of the disease (onset, peak, remission). We compared variances of expression of known biomarkers by RT-qPCR in the brain and spinal cord of sham and EAE animals monitoring each of the five hallmarks of the disease. Using magnetic cell isolation technology, we isolated microglia and oligodendrocytes of mice of each category, and we compared the RNA expression variations. We identify genes deregulated during a restricted time frame, and we provide insight into the timing and interrelationships of pathological disease processes at the organ and cell levels.  相似文献   
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