Smart Edge Computing for 5 g/6 g Satellite IOT for Reducing Inter Transmission Delay

Mobile Networks and Applications - 5G/6G communication are first generation high speed wireless communication network which integrates the aerial data, terrestrial data and maritime data via...     

Effect of Boronizing on Operating Stability of Steel AISI 304L under Erosion Impact of Hard Particles

Metal Science and Heat Treatment - The effect of solid boronizing at 950°C for 2 and 4 h on the phase composition, microstructure, hardness and abrasive wear of steel AISI 304L is studied...     

Masking the Peroxidase-Like Activity of the Molybdenum Disulfide Nanozyme Enables Label-Free Lipase Detection

Two-dimensional MoS₂ nanoparticles (2D-nps) exhibit artificial enzyme properties that can be regulated at bio-nanointerfaces. We discovered that protein lipase is able to tune the peroxidase-like activity of MoS₂ 2D-nps, offering low-nanomolar, label-free detection and identification in samples with unknown identity. The inhibition of the peroxidase-like activity of the MoS₂ 2D-nps was demonstrated to be concentration dependent, and as low as 5 nm lipase was detected with this approach. The results were compared with those obtained with several other proteins that did not display any significant interference with the nanozyme behavior of the MoS₂ 2D-nps. This unique response of lipase was characterized and exploited for the successful identification of lipase in six unknown samples by using qualitative visual inspection and a quantitative statistical analysis method. The developed methodology in this approach is noteworthy for many aspects; MoS₂ 2D-nps are neither labeled with a signaling moiety nor modified with any ligands for signal readout. Only the intrinsic nanozyme activity of the MoS₂ 2D-nps is exploited for this detection approach. No analytical equipment is necessary for the visual detection of lipase. The synthesis of the water-soluble MoS₂ 2D-nps is low costing and can be performed in bulk scale. Exploring the properties of 2D-nps and their interactions with biological materials reveals highly interesting yet instrumental features that offer the development of novel bioanalytical approaches.     

THE FLOW PRODUCED IN PARTICLE-SUSPENSION BY AN INFINITE ROTATING DISK:SERIES SOLUTION

To the flow produced in particle-suspension by a rotating disk of infinite extent,the asymptotic behavior at infinity is analyzed.A corresponding series solution is presented.It isshown that this approach yields widely valid solutions of high accuracy for all the cases in whichthat suction or weak injection at the disk surface exists.For the cases that strong injection or par-ticle-free band exists,the series method fails.     

半导体长波长异质结构材料光压谱测试探讨

本文介绍了ＩｎＰ、ＩｎＧａＡｓ、ＩｎＧａＰ、ＩｎＧａＡｓＰ等的光压港（ＰＶＳ）。并把ＩｎＧａＡｓＰ（在特定组份下）的ＰＶＳ与ＦＦＴ—ＰＬ谱进行了比较；分析和讨论了ＰＶＳ测试的局限性和复杂性；指出了对多层异质结构材料，只有把器件结构、外延工艺、ＥＣＶ测试等结合起来，才可能正确地理解ＰＶＳ给出的测试结果。     

Heat-integration retrofit study of a petroleum refinery

The operation of a petroleum refinery at TÜPRA . Tütünçiftlik was assessed using the pinch-design method. By making use of heat integration in the heat-exchange network, appreciable amounts of energy can be saved as a result of a capital investment having a pay-back period of about 6·5 months.     

黑釉铁锈花产品的试制

本文论述了黑釉铁锈花产品的坯釉料组成及制作工艺．井对黑釉铁锈花产品的起源、形成机理进行了探讨分析。     

Data stream classification with novel class detection: a review,comparison and challenges

Knowledge and Information Systems - Developing effective and efficient data stream classifiers is challenging for the machine learning community because of the dynamic nature of data streams. As a...     

A novel approach to predict shear strength of tilted angle connectors using artificial intelligence techniques

Shear connectors play a prominent role in the design of steel-concrete composite systems. The behavior of shear connectors is generally determined through conducting push-out tests. However, these tests are costly and require plenty of time. As an alternative approach, soft computing (SC) can be used to eliminate the need for conducting push-out tests. This study aims to investigate the application of artificial intelligence (AI) techniques, as sub-branches of SC methods, in the behavior prediction of an innovative type of C-shaped shear connectors, called Tilted Angle Connectors. For this purpose, several push-out tests are conducted on these connectors and the required data for the AI models are collected. Then, an adaptive neuro-fuzzy inference system (ANFIS) is developed to identify the most influencing parameters on the shear strength of the tilted angle connectors. Totally, six different models are created based on the ANFIS results. Finally, AI techniques such as an artificial neural network (ANN), an extreme learning machine (ELM), and another ANFIS are employed to predict the shear strength of the connectors in each of the six models. The results of the paper show that slip is the most influential factor in the shear strength of tilted connectors and after that, the inclination angle is the most effective one. Moreover, it is deducted that considering only four parameters in the predictive models is enough to have a very accurate prediction. It is also demonstrated that ELM needs less time and it can reach slightly better performance indices than those of ANN and ANFIS.