Evolution of gas permeability for concrete materials under and after uni-axial loading

Under life-cycle service conditions, gas permeability which is usually employed to indicate the durability performance of concrete materials will be changed along with the evolution of microstructure under or after loading. This paper reports an extensive experimental research on the influence of loading condition on the evolution of gas permeability. A cyclic loading scheme under displacement control, which is employed to accelerate the evolution of its microstructure and model the loading condition under real service, is applied on cylinder specimens ϕ37u74mm dried to constant weight at 60°C. Both axial and lateral strains in the whole loading test are recorded by strain gauge to characterize the change of microstructure macroscopically. At the same time, gas permeability measurement is carried out by a well-designed tri-axial permeater at various loading levels in the planned loading history. The relationship between intrinsic gas permeability, Klinkenberg coefficient and residual strains discussed. It is found that intrinsic gas permeability will become great if the uniaxial loading level is beyond about 70% ultimate strength. Moreover, both the klinkenberg coefficient and intrinsic gas permeability are badly linked with elastic and plastic strains. However, the relationship between the Klinkenberg coefficient and intrinsic gas permeability can be approximated by a semi-empirical law, no matter under or after loading

A scalable and robust framework for agent-based heterogeneous database operation

How to operate database efficiently and unfailingly in agent-based heterogeneous data source environment is becoming a big problem. In this paper, we contribute a framework and develop a couple of agent-oriented matchmakers with logical ring organization structure to match task agents\u27 requests with middleware agents of databases. The middleware agent is a wrapper of a specific database and is run on the same server with the database management system. The matchmaker is of the features of proliferation and self-cancellation according to the sensory input from its environment. The ring-based coordination mechanism of matchmakers is designed. Two kinds of matchmakers, namely, host and duplicate, are designed for improving the scalability and robustness of agent-based system. The middleware agents are improved for satisfying the framework. We demonstrate the potentials of the framework by case study and present theoretical and empirical evidence that our approach is scalable and robust.<br /

Fatigue safety monitoring and assessment of short and medium span concrete girder bridges

Concrete bridge is widely used in highway infrastructure in China, especially in short and medium span bridges. Concrete bridges are prone to fatigue failure under the coupled actions of repeated vehicles loads, environment and material degradation. In recent years, the traffic volume and vehicle weights of highway bridges have been continuously increasing, so concrete bridge fatigue problem becomes more serious. This paper introduces advanced fatigue safety monitoring techniques and fatigue performance assessment methods for short and medium span concrete girder bridges. Weigh-in-motion (WIM) system was used to record the real traffic volume, and then the acquired load spectrum was applied on typical concrete bridges through Matlab to analyze the fatigue performance of different bridge types. From the analysis results, several typical short and medium span concrete girder bridges are selected to conduct long-term service monitoring. The cross section types include hollow slab girder, T-girder and short box girder, and the structure types contain simple supported bridge and continuous girder bridge. WIM technique, dynamic strain monitoring technique and acoustic emission technique are used to monitor the key details. Fatigue performance is assessed and analyzed based on monitoring data, considering traffic increase, overload and corrosion factors

A bio-inspired flapping wing rotor of variant frequency driven by ultrasonic motor

By combining the flapping and rotary motion, a bio-inspired flapping wing rotor (FWR) is a unique kinematics of motion. It can produce a significantly greater aerodynamic lift and efficiency than mimicking the insect wings in a vertical take-off and landing (VTOL). To produce the same lift, the FWR’s flapping frequency, twist angle, and self-propelling rotational speed is significantly smaller than the insect-like flapping wings and rotors. Like its opponents, however, the effect of variant flapping frequency (VFF) of a FWR, during a flapping cycle on its aerodynamic characteristics and efficiency, remains to be evaluated. A FWR model is built to carry out experimental work. To be able to vary the flapping frequency rapidly during a stroke, an ultrasonic motor (USM) is used to drive the FWR. Experiment and numerical simulation using computational fluid dynamics (CFD) are performed in a VFF range versus the usual constant flapping frequency (CFF) cases. The measured lifting forces agree very well with the CFD results. Flapping frequency in an up-stroke is smaller than a down-stroke, and the negative lift and inertia forces can be reduced significantly. The average lift of the FWR where the motion in VFF is greater than the CFF, in the same input motor power or equivalent flapping frequency. In other words, the required power for a VFF case to produce a specified lift is less than a CFF case. For this FWR model, the optimal installation angle of the wings for high lift and efficiency is found to be 30° and the Strouhal number of the VFF cases is between 0.3–0.36. View Full-Tex

HuMiTar: A sequence-based method for prediction of human microRNA targets

<p>Abstract</p> <p>Background</p> <p>MicroRNAs (miRs) are small noncoding RNAs that bind to complementary/partially complementary sites in the 3' untranslated regions of target genes to regulate protein production of the target transcript and to induce mRNA degradation or mRNA cleavage. The ability to perform accurate, high-throughput identification of physiologically active miR targets would enable functional characterization of individual miRs. Current target prediction methods include traditional approaches that are based on specific base-pairing rules in the miR's seed region and implementation of cross-species conservation of the target site, and machine learning (ML) methods that explore patterns that contrast true and false miR-mRNA duplexes. However, in the case of the traditional methods research shows that some seed region matches that are conserved are false positives and that some of the experimentally validated target sites are not conserved.</p> <p>Results</p> <p>We present HuMiTar, a computational method for identifying common targets of miRs, which is based on a scoring function that considers base-pairing for both seed and non-seed positions for human miR-mRNA duplexes. Our design shows that certain non-seed miR nucleotides, such as 14, 18, 13, 11, and 17, are characterized by a strong bias towards formation of Watson-Crick pairing. We contrasted HuMiTar with several representative competing methods on two sets of human miR targets and a set of ten glioblastoma oncogenes. Comparison with the two best performing traditional methods, PicTar and TargetScanS, and a representative ML method that considers the non-seed positions, NBmiRTar, shows that HuMiTar predictions include majority of the predictions of the other three methods. At the same time, the proposed method is also capable of finding more true positive targets as a trade-off for an increased number of predictions. Genome-wide predictions show that the proposed method is characterized by 1.99 signal-to-noise ratio and linear, with respect to the length of the mRNA sequence, computational complexity. The ROC analysis shows that HuMiTar obtains results comparable with PicTar, which are characterized by high true positive rates that are coupled with moderate values of false positive rates.</p> <p>Conclusion</p> <p>The proposed HuMiTar method constitutes a step towards providing an efficient model for studying translational gene regulation by miRs.</p

Comprehensive evaluation research of hybrid energy systems driven by renewable energy based on fuzzy multi-criteria decision-making

The worsening of climate conditions is closely related to the large amount of carbon dioxide produced by human use of fossil fuels. Under the guidance of the goal of “carbon peaking and carbon neutrality goals”, with the deepening of the structural reform of the energy supply side, the hybrid energy system coupled with renewable energy has become an important means to solve the energy problem. This paper focuses on the comprehensive evaluation of hybrid energy systems. A complete decision support system is constructed in this study. The system primarily consists of four components: 1) Twelve evaluation criteria from economic, environmental, technological, and socio-political perspectives; 2) A decision information collecting and processing method in uncertain environment combining triangular fuzzy numbers and hesitation fuzzy language term sets; 3) A comprehensive weighting method based on Lagrange optimization theory; 4) Solution ranking based on the fuzzy VIKOR method that considers the risk preferences of decision-makers. Through a case study, it was found that the four most important criteria are investment cost, comprehensive energy efficiency, dynamic payback period and energy supply reliability with weights of 7.21%, 7.17%, 7.17%, and 7.15% respectively. A1 is the scheme with the best comprehensive benefit. The selection of solutions may vary depending on the decision-maker’s risk preference. Through the aforementioned research, the decision framework enables the evaluation of the overall performance of the system and provides decision-making references for decision-makers in selecting solutions