Data broadcasting strategies for cognitive radio based AMI networks

Wireless Networks - Communication systems play an important role in smart grid (SG). Advanced Metering Infrastructure (AMI) is hybrid architecture in smart grid comprising of smart meters and...     

Simulating study on RHCRP protocol in utility tunnel WSN

Wireless Networks - Utility tunnel is one of the important infrastructures for the planning and building of smart city. It is of great significance to improve the efficiency of maintenance and...     

Microstructural evolution and defect formation in a powder metallurgy nickel-based superalloy processed by selective laser melting

In this study,the selective laser melting(SLM)technology has been employed to manufacture a nickelbased superalloy which was conventionally prepared through powder metallurgy(PM)route.The microstructural features and defects were systematically investigated both prior to and after heat treatment and compared with the PM counterpart.Both solidification cracking and liquation cracking were observed in the SLM specimen in which the grain misorientation and low melting point(γ+γ')eutectic played a vital role in their formation mechanism.Columnar grains oriented along building direction were ubiquitous,corresponding to strong<001>fiber texture.Solidification cell structures and melt pools are pervasive and noγ'precipitates were detected at about 10 nm scale before heat treatment.After supersolvus solution and two-step aging treatments,high volume fractionγ'precipitates emerged and their sizes and morphologies were comparable to those in PM alloy.<001>texture is relieved and columnar grains tend to become more equiaxed due to static recrystallization process and grain boundary migration events.Significant annealing twins formed in SLM alloy and are clarified as a consequence of recrystallization.Our results provide fundamental understandings for the SLM PM nickel-based superalloy both before and after heat treatment and demonstrate the potential to fabricate this group of alloys using SLM technology.     

Empirical Analysis of Agricultural Cultural Resources Value Evaluation under DEA Model

Agricultural culture is a productive activity about education and management. It aims at high efficiency and high quality, uses technology as its means, and takes nature as its carrier. Agricultural cultural resources are the product of the rapid development of modern economy. It promotes the development of the national economy and profoundly affects people's production and life. DEA model, also known as data envelope analysis method, is an algorithm that uses multiple data decision units for input and output training to obtain the final model. This article explains the concept and basic characteristics of agricultural culture. Through questionnaire surveys and expert interviews, we collected development data, screened human, material, and financial data, and calculated information on economic and social resources. On this basis, this paper establishes the evaluation index of agricultural culture based on DEA model. Then, through empirical analysis from a specific perspective, it can be concluded that increasing human, material and financial input can achieve economic and social benefits. Generally speaking, cultural investment can promote the development of the industry. The research results of this paper laid a theoretical foundation for the development of agricultural culture, and put forward a development model focusing on technology development, improving investment efficiency, and investing in material resources.     

MOOC Learner’s Final Grade Prediction Based on an Improved Random Forests Method

Massive Open Online Course (MOOC) has become a popular way of online learning used across the world by millions of people. Meanwhile, a vast amount of information has been collected from the MOOC learners and institutions. Based on the educational data, a lot of researches have been investigated for the prediction of the MOOC learner’s final grade. However, there are still two problems in this research field. The first problem is how to select the most proper features to improve the prediction accuracy, and the second problem is how to use or modify the data mining algorithms for a better analysis of the MOOC data. In order to solve these two problems, an improved random forests method is proposed in this paper. First, a hybrid indicator is defined to measure the importance of the features, and a rule is further established for the feature selection; then, a Clustering-Synthetic Minority Over-sampling Technique (SMOTE) is embedded into the traditional random forests algorithm to solve the class imbalance problem. In experiment part, we verify the performance of the proposed method by using the Canvas Network Person-Course (CNPC) dataset. Furthermore, four well-known prediction methods have been applied for comparison, where the superiority of our method has been proved.     

Nanoparticle Conjugation of Ginsenoside Rg3 Inhibits Hepatocellular Carcinoma Development and Metastasis

Hepatocellular carcinoma (HCC) is the third leading cause of cancer‐related death worldwide. The prognosis of HCC remains very poor; thus, an effective treatment remains urgent. Herein, a type of nanomedicine is developed by conjugating Fe@Fe₃O₄ nanoparticles with ginsenoside Rg3 (NpRg3), which achieves an excellent coupling effect. In the dimethylnitrosamine‐induced HCC model, NpRg3 application significantly prolongs the survival of HCC mice. Further research indicates that NpRg3 application significantly inhibits HCC development and eliminates HCC metastasis to the lung. Notably, NpRg3 application delays HCC‐induced ileocecal morphology and gut microbial alterations more than 12 weeks during HCC progression. NpRg3 administration elevates the abundance of Bacteroidetes and Verrucomicrobia, but decreases Firmicutes. Twenty‐nine predicted microbial gene functions are enriched, while seven gene functions are reduced after NpRg3 administration. Moreover, the metabolomics profile presents a significant progression during HCC development, but NpRg3 administration corrects tumor‐dominant metabolomics. NpRg3 administration decreases 3‐indolepropionic acid and urea, but elevates free fatty acids. Importantly, NpRg3 application remodels the unbalanced correlation networks between gut microbiota and metabolism during HCC therapy. In conclusion, nanoparticle conjugation of ginsenoside Rg3 inhibits HCC development and metastasis via the remodeling of unbalanced gut microbiota and metabolism in vivo, providing an antitumor therapy strategy.     

Atomic Modulation Triggering Improved Performance of MoO3 Nanobelts for Fiber‐Shaped Supercapacitors

Asymmetric supercapacitors (ASCs) are emerging as a new class of energy storage devices that could potentially meet the increasing power and energy demand for next‐generation portable and flexible electronics. Yet, the energy density of ASC is severely limited by the low capacitance of the anode side, which commonly uses the carbon‐based nanomaterials. Here, the demonstration of sulfur‐doped MoO_3?x nanobelts (denoted as S‐MoO_3?x) as the anode for high‐performance fiber‐shaped ASC are reported. The Mo sites in MoO₃ are intentionally modulated at the atomic level through sulfur doping, where sulfur could be introduced into the MoO₆ octahedron to intrinsically tune the covalency character of bonds around Mo sites and thus boost the charge storage kinetics of S‐MoO_3?x. Moreover, the oxygen defects are occurring along with sulfur‐doping in MoO₃, enabling efficient electron transport. As expected, the fiber‐shaped S‐MoO_3?x achieves outstanding capacitance with good rate capability and long cycling life. More impressively, the fiber‐shaped ASC based on S‐MoO_3?x anode delivers extremely high volumetric capacitance of 6.19 F cm^?3 at 0.5 mA cm^?1, which makes it promising as one of the most attractive candidates of anode materials for high‐performance fiber‐shaped ASCs.     

The Regulatory Functionality of Exosomes Derived from hUMSCs in 3D Culture for Alzheimer's Disease Therapy

Reducing amyloid‐β (Aβ) accumulation could be a potential therapeutic approach for Alzheimer's disease (AD). Particular functional biomolecules in exosomes vested by the microenvironment in which the original cells resided can be transferred to recipient cells to improve pathological conditions. However, there are few reports addressing whether exosomes derived from cells cultured on scaffolds with varying dimension can reduce Aβ deposition or ameliorate cognitive decline for AD therapy. Herein, both 3D graphene scaffold and 2D graphene film are used as the matrix for human umbilical cord mesenchymal stem cell culture, from which the supernatants are obtained to isolate exosomes. The levels of 195 kinds of miRNAs and proteins, including neprilysin, insulin‐degrading enzyme and heat shock protein 70, in 3D‐cultured exosomes (3D‐Exo) are dramatically different from those obtained from 2D culture. Hence, 3D‐Exo could up‐regulate the expression of α‐secretase and down‐regulate the β‐secretase to reduce Aβ production in both AD pathology cells and transgenic mice, through their special cargo. With rescuing Aβ pathology, 3D‐Exo exerts enhanced therapeutic effects on ameliorating the memory and cognitive deficits in AD mice. These findings provide a novel clinical application for scaffold materials and functional exosomes derived from stem cells.