Carbon nanotubes as anti-bacterial agents

Multidrug-resistant bacterial infections that have evolved via natural selection have increased alarmingly at a global level. Thus, there is a strong need for the development of novel antibiotics for the treatment of these infections. Functionalized carbon nanotubes through their unique properties hold great promise in the fight against multidrug-resistant bacterial infections. This new family of nanovectors for therapeutic delivery proved to be innovative and efficient for the transport and cellular translocation of therapeutic molecules. The current review examines the latest progress in the antibacterial activity of carbon nanotubes and their composites.     

A forensic method for efficient file extraction in HDFS based on three-level mapping

The large scale and distribution of cloud computing storage have become the major challenges in cloud forensics for file extraction. Current disk forensic methods do not adapt to cloud computing well and the forensic research on distributed file system is inadequate. To address the forensic problems, this paper uses the Hadoop distributed file system (HDFS) as a case study and proposes a forensic method for efficient file extraction based on three-level (3L) mapping. First, HDFS is analyzed from overall architecture to local file system. Second, the 3L mapping of an HDFS file from HDFS namespace to data blocks on local file system is established and a recovery method for deleted files based on 3L mapping is presented. Third, a multi-node Hadoop framework via Xen virtualization platform is set up to test the performance of the method. The results indicate that the proposed method could succeed in efficient location of large files stored across data nodes, make selective image of disk data and get high recovery rate of deleted files.     

Cobalt doped titanate nanotubes: Synthesis and properties

Cobalt oxide doped titanate nanotubes are synthesized with a simple hydrothermal treatment of mixed Co_3O_4 and TiO_2 powders. The formed tubular nanostructure, chemical composition,and the elemental distribution are analyzed using TEM, BET, FTIR, XRD, and XPS. The electrocatalytic activity towards oxygen evolution reactions and photodegradation against Rhodamine B are investigated. It has been found out that the oxygen evolutions starts at 0.8 V and reaches 0.98 mA ·cm~(–1) at 1.4 V vs. SCE. For photodegradation of Rhodamine B, the concentration decreased to 24% after 1 h irradiation using the sample with a mass percentage of 5% cobalt. The results demonstrate that the cobalt oxide doped titanate nanotubes are good candidates as electrocatalysts and photocatalytic materials.     

Secure pairing with wearable devices by using ambient sound and light

Wearable devices usually work together with smart phones. To ensure only legitimate smart phones can read the data, they must conduct pairing to establish a shared key. Traditional pairing methods require that the pairing devices have a keyboard or screen for user interaction. However, due to the size limitation, keyboards or screens are hard to be installed in the wearable devices. To solve this problem, we propose a novel pairing method by using ambient sound and light. In this new scheme, any pairing request from smart phone will trigger wearable device vibration. Only after users press the confirm key on the device can the pairing process continues. Then pairing devices collect ambient sound and light at the predetermined time and establish a shared key by using the Diffie-Hellman protocol. To protect against potential man-in-the-middle attacks in the key establishment process, an improved interlock protocol with sound and light comparison is conducted to authenticate the key. If both the sound and light collected by the pairing devices are similar enough, the key is accepted. Otherwise, it is rejected. Compared with current context based pairing methods, our scheme does not impose strict synchronization on devices to collect ambient context data. Moreover, our scheme need not collect and exchange contextual information for multiple times to resist offline brute force attacks. The experimental results and security analysis prove the effectiveness of our scheme.     

Tyrosine 842 in the activation loop is required for full transformation by the oncogenic mutant FLT3-ITD

The type III receptor tyrosine kinase FLT3 is frequently mutated in acute myeloid leukemia. Oncogenic FLT3 mutants display constitutive activity leading to aberrant cell proliferation and survival. Phosphorylation on several critical tyrosine residues is known to be essential for FLT3 signaling. Among these tyrosine residues, Y842 is located in the so-called activation loop. The position of this tyrosine residue is well conserved in all receptor tyrosine kinases. It has been reported that phosphorylation of the activation loop tyrosine is critical for catalytic activity for some but not all receptor tyrosine kinases. The role of Y842 residue in FLT3 signaling has not yet been studied. In this report, we show that Y842 is not important for FLT3 activation or ubiquitination but plays a critical role in regulating signaling downstream of the receptor as well as controlling receptor stability. We found that mutation of Y842 in the FLT3-ITD oncogenic mutant background reduced cell viability and increased apoptosis. Furthermore, the introduction of the Y842 mutation in the FLT3-ITD background led to a dramatic reduction in in vitro colony forming capacity. Additionally, mice injected with cells expressing FLT3-ITD/Y842F displayed a significant delay in tumor formation, compared to FLT3-ITD expressing cells. Microarray analysis comparing gene expression regulated by FLT3-ITD versus FLT3-ITD/Y842F demonstrated that mutation of Y842 causes suppression of anti-apoptotic genes. Furthermore, we showed that cells expressing FLT3-ITD/Y842F display impaired activity of the RAS/ERK pathway due to reduced interaction between FLT3 and SHP2 leading to reduced SHP2 activation. Thus, we suggest that Y842 is critical for FLT3-mediated RAS/ERK signaling and cellular transformation.     

Two Innovative Coalition Formation Models for Dynamic Task Allocation in Disaster Rescues

This paper addresses the problem of multi-objective coalition formation for task allocation. In disaster rescue, due to the dynamics of environments, heterogeneity and complexity of tasks as well as limited available agents, it is hard for the single-objective and single (task)-to-single (agent) task allocation approaches to handle task allocation in such circumstances. To this end, two multi-objective coalition formation for task allocation models are proposed for disaster rescues in this paper. First, through coalition formation, the proposed models enable agents to cooperatively perform complex tasks that cannot be completed by single agent. In addition, through adjusting the weights of multiple task allocation objectives, the proposed models can employ the linear programming to generate more adaptive task allocation plans, which can satisfy different task allocation requirements in disaster rescue. Finally, through employing the multi-stage task allocation mechanism of the dynamic programming, the proposed models can handle the dynamics of tasks and agents in disaster environments. Experimental results indicate that the proposed models have good performance on coalition formation for task allocation in disaster environments, which can generate suitable task allocation plans according to various objectives of task allocation.     

Data-Driven Leader-Follower Output Synchronization for Networked Non-Linear Multi-Agent Systems with Switching Topology and Time-Varying Delays

This paper studies the output synchronization problem for a class of networked non-linear multi-agent systems with switching topology and time-varying delays. To synchronize the outputs, a leader is introduced whose connectivity to the followers varies with time, and a novel data-driven consensus protocol based on model free adaptive control is proposed, where the reference input of each follower is designed to be the time-varying average of the neighboring agents’ outputs. Both the case when the leader is with a prescribed reference input and the case otherwise are considered. The proposed protocol allows for time-varying delays, switching topology, and does not use the agent structure or the dynamics information implicitly or explicitly. Sufficient conditions are derived to guarantee the closed-loop stability, and conditions for consensus convergence are obtained, where only a joint spanning tree is required. Numerical simulations and practical experiments are conducted to demonstrate the effectiveness of the proposed protocol.     

Contours and Tight Clusters

Nested clusters arise independently in graph partitioning and in the study of contours. We take a step toward unifying these two instances of nested clusters. We show that the graph theoretical tight clusters introduced by Dress, Steel, Moulton and Wu in 2010 are a special case of nested clusters associated to contours.     

An empirical investigation on the risk-return relationship of carbon future market

This paper examines the risk-return relationship for the carbon future market during Phases I, II and III of the European Union Emission Trading Scheme (EU ETS). The risk factors derived from the newly developed LSW model, are embedded into a GARCH framework. This new specification is compared with several GARCH-M type models analyzing the risk-return relationship in the carbon market. The results show that the new specification consistently achieves a good fit and possesses superior explanatory power for the European Union Allowance (EUA) data. Some policy suggestions regarding market efficiency are also provided.