De-anonymyzing scale-free social networks by using spectrum partitioning method

Social network data is widely shared, forwarded and published to third parties, which led to the risks of privacy disclosure. Even thought the network provider always perturbs the data before publishing it, attackers can still recover anonymous data according to the collected auxiliary information. In this paper, we transform the problem of de-anonymization into node matching problem in graph, and the de-anonymization method can reduce the number of nodes to be matched at each time. In addition, we use spectrum partitioning method to divide the social graph into disjoint subgraphs, and it can effectively be applied to large-scale social networks and executed in parallel by using multiple processors. Through the analysis of the influence of power-law distribution on de-anonymization, we synthetically consider the structural and personal information of users which made the feature information of the user more practical

Clustering-Based Energy-Efficient Broadcast Tree in Wireless Networks

The characteristics of wireless networks present formidable challenges to the study of broadcasting problem. A crucial issue in wireless networks is the energy consumption, because of the nonlinear attenuation properties of radio signals. Another crucial issue is the trade-off between reaching more nodes in a single hop by using higher power versus reaching fewer nodes in that single hop by using lower power. Given a wireless network with a specified source node that broadcasts messages to all other nodes in the network, the minimum energy broadcast (MEB) problem is NP-hard. In this paper, we propose a hybrid approach CBEEB(clustering-based energy-efficient broadcast) for the MEB problem based on clustering. Theoretical analysis indicates the efficiency and effectiveness of CBEEB. Simulation results show that CBEEB has better performance compared with the existing heuristic approaches

The role of glycogen synthase kinase 3 beta in neurodegenerative diseases

Neurodegenerative diseases (NDDs) pose an increasingly prevalent threat to the well-being and survival of elderly individuals worldwide. NDDs include Alzheimer’s disease (AD), Parkinson’s disease (PD), Huntington’s disease (HD), amyotrophic lateral sclerosis (ALS), and so on. They are characterized by progressive loss or dysfunction of neurons in the central or peripheral nervous system and share several cellular and molecular mechanisms, including protein aggregation, mitochondrial dysfunction, gene mutations, and chronic neuroinflammation. Glycogen synthase kinase-3 beta (GSK-3β) is a serine/threonine kinase that is believed to play a pivotal role in the pathogenesis of NDDs. Here we summarize the structure and physiological functions of GSK3β and explore its involvement in NDDs. We also discussed its potential as a therapeutic target

Online Modelling and Calculation for Operating Temperature of Silicon-Based PV Modules Based on BP-ANN

The operating temperature of silicon-based solar modules has a significant effect on the electrical performance and power generation efficiency of photovoltaic (PV) modules. It is an important parameter for PV system modeling, performance evaluation, and maximum power point tracking. The analysis shows that the results of physics-based methods always change with seasons and weather conditions. It is difficult to measure all the needed variables to build the physics-based model for the calculation of operating temperature. Due to the above problem, the paper proposes an online method to calculate operating temperature, which adopts the back propagation artificial neural network (BP-ANN) algorithm. The comparative analysis is carried out using data from the empirical test platform, and the results show that both the BP-ANN and the support vector machine (SVM) method can reach good accuracy when the dataset length was over six months. The SVM method is not suitable for the temperature modeling because its computing time is too long. To improve the performance, wind speed should be taken as one of the models’ input if possible. The proposed method is effective to calculate the operating temperature of silicon-based solar modules online, which is a low-cost soft-sensing solution

Human Streptococcus suis Outbreak, Sichuan, China

Streptococcus suis outbreak was associated with exposure to sick or dead pigs

Streptococcus suis Sequence Type 7 Outbreak, Sichuan, China

An outbreak of Streptococcus suis serotype 2 emerged in the summer of 2005 in Sichuan Province, and sporadic infections occurred in 4 additional provinces of China. In total, 99 S. suis strains were isolated and analyzed in this study: 88 isolates from human patients and 11 from diseased pigs. We defined 98 of 99 isolates as pulse type I by using pulsed-field gel electrophoresis analysis of SmaI-digested chromosomal DNA. Furthermore, multilocus sequence typing classified 97 of 98 members of the pulse type I in the same sequence type (ST), ST-7. Isolates of ST-7 were more toxic to peripheral blood mononuclear cells than ST-1 strains. S. suis ST-7, the causative agent, was a single-locus variant of ST-1 with increased virulence. These findings strongly suggest that ST-7 is an emerging, highly virulent S. suis clone that caused the largest S. suis outbreak ever described

Fabrication of protein-coated titanium dioxide nanoparticles for cellular uptake fluorescence imaging and treatment of colorectal cancer

Titanium dioxide (TiO _2 ) coated with different proteins has exhibited exceptional bio-compatibility, leading to various biomedical engineering applications. With the use of green and chemical reduction methods, we fabricated Titanium dioxide nanoparticles that were protein-coated. Bovine serum albumin (BSA), lysozyme proteins, zein, and collagen have been used to coat titanium dioxide-aryl nanoparticles of the form TiO _2 -NPs. However, in both cases, no catalysts or other stabilizing agents were used. These images of TiO _2 -NPs fabricated using the green method show high crystallinity. It is a malignant colorectal tumour with dysfunctional cellular processes that cause colorectal cancer cells. It is hoped that studies employing SW1417 cells would give mechanistic ideas on the specifics of the amplification in cancers. This was done by flow cytometry utilizing and laser confocal fluorescence microscopy (LCFM) on the SW1417 colorectal cell line. Of the protein-coated Titanium dioxide nanoparticles fabricated green methods, BSA@TiO _2 -NPs were the most readily absorbed. Of all TiO _2 -NPs, lysozyme@TiO _2 -NPs fabricated by the chemical reduction technique were the most effectively internalized by SW1417 cells out of TiO _2 -NPs types. However, TiO _2 -NPs fabricated by the green methodology were coated with zein and lysozyme and tiny. A hydrophobic covering is also on the two nanoparticles. There is a possibility that the variation in hydrophobicity and charge affected the internalization process. Colorectal diagnostic and therapeutic compounds might be synthesized from those coated nanoparticles that were effectively internalized

Multi-leader election in dynamic sensor networks

Abstract The leader election problem is one of the fundamental problems in distributed computing. Different from most of the existing results studying the multi-leader election in static networks or one leader election in dynamic networks, in this paper, we focus on the multi-leader election in dynamic sensor networks where nodes are deployed randomly. A centralized simple leader election algorithm (VLE), a distributed leader election algorithm (NMDLE), and a multi-leader election algorithm (PSMLE) are proposed so as to elect multi-leaders for the purpose of saving energy and prolonging the network lifetime, respectively. Specifically, the proposed algorithms aim at using less leaders to control the whole network, which is controlled by at least k opt leaders, here k opt denotes the optimal number of network partitions. Then we analyze the impacts of the sleep scheme of nodes and node moving on energy consumption and establish a theoretical model for energy cost. Finally, we provide extensive simulation results valuating the correctness of theoretical analysis

Chitin Biodegradation by Lytic Polysaccharide Monooxygenases from Streptomyces coelicolor In Vitro and In Vivo

Lytic polysaccharide monooxygenases (LPMOs) have the potential to improve recalcitrant polysaccharide hydrolysis by the oxidizing cleavage of glycosidic bond. Streptomyces species are major chitin decomposers in soil ecological environments and encode multiple lpmo genes. In this study, we demonstrated that transcription of the lpmo gene, Sclpmo10G, in the Streptomyces coelicolor A3(2) (ScA3(2)) strain is strongly induced by chitin. The ScLPMO10G protein was further expressed in Escherichia coli and characterized in vitro. The ScLPMO10G protein showed oxidation activity towards chitin. Chitinase synergy experiments demonstrated that the addition of ScLPMO10G resulted in a substantial in vitro increase in the reducing sugar levels. Moreover, in vivo the LPMO-overexpressing strain ScΔLPMO10G(+) showed stronger chitin-degrading ability than the wild-type, leading to a 2.97-fold increase in reducing sugar level following chitin degradation. The total chitinase activity of ScΔLPMO10G(+) was 1.5-fold higher than that of ScA3(2). In summary, ScLPMO10G may play a role in chitin biodegradation in S. coelicolor, which could have potential applications in biorefineries