Quantum phase transition in the one-dimensional period-two and uniform compass model

Quantum phase transition in the one-dimensional period-two and uniform quantum compass model are studied by using the pseudo-spin transformation method and the trace map method. The exact solutions are presented, the fidelity, the nearest-neighbor pseudo-spin entanglement, spin and pseudo-spin correlation functions are then calculated. At the critical point, the fidelity and its susceptibility change substantially, the gap of pseudo-spin concurrence is observed, which scales as $1/N$ (N is system size). The spin correlation functions show smooth behavior around the critical point. In the period-two chain, the pseudo-spin correlation functions exhibit a oscillating behavior, which is absent in the unform chain. The divergent correlation length at the critical point is demonstrated in the general trend for both cases.Comment: 5 pages, 6 figure

CaSiO3 microstructure modulating the in vitro and in vivo bioactivity of poly(lactide-co-glycolide) microspheres

Poly (lactide-co-glycolide) (PLGA) microspheres have been used for regenerative medicine due to their ability for drug delivery and generally good biocompatibility, but they lack adequate bioactivity for bone repair application. CaSiO3 (CS) has been proposed as a new class of material suitable for bone tissue repair due to its excellent bioactivity. In this study, we set out to incorporate CS into PLGA microspheres to investigate how the phase structure (amorphous and crystal) of CS influences the in vitro and in vivo bioactivity of the composite microspheres, with a view to the application for bone regeneration. X-ray diffraction (XRD), N2 adsorption-desorption analysis and scanning electron microscopy (SEM) were used to analyze the phase structure, surface area/pore volume, and microstructure of amorphous CS (aCS) and crystal CS (cCS), as well as their composite microspheres. The in vitro bioactivity of aCS and cCS – PLGA microspheres was evaluated by investigating their apatite-mineralization ability in simulated body fluids (SBF) and the viability of human bone mesenchymal stem cells (BMSCs). The in vivo bioactivity was investigated by measuring their de novo bone-formation ability. The results showed that the incorporation of both aCS and cCS enhanced the in vitro and in vivo bioactivity of PLGA microspheres. cCS/PLGA microspheres improved better in vitro BMSC viability and de novo bone-formation ability in vivo, compared to aCS/PLGA microspheres. Our study indicates that controlling the phase structure of CS is a promising method to modulate the bioactivity of polymer microsphere system for potential bone tissue regeneration

Promoting cold-start items in recommender systems

As one of major challenges, cold-start problem plagues nearly all recommender systems. In particular, new items will be overlooked, impeding the development of new products online. Given limited resources, how to utilize the knowledge of recommender systems and design efficient marketing strategy for new items is extremely important. In this paper, we convert this ticklish issue into a clear mathematical problem based on a bipartite network representation. Under the most widely used algorithm in real e-commerce recommender systems, so-called the item-based collaborative filtering, we show that to simply push new items to active users is not a good strategy. To our surprise, experiments on real recommender systems indicate that to connect new items with some less active users will statistically yield better performance, namely these new items will have more chance to appear in other users' recommendation lists. Further analysis suggests that the disassortative nature of recommender systems contributes to such observation. In a word, getting in-depth understanding on recommender systems could pave the way for the owners to popularize their cold-start products with low costs.Comment: 6 pages, 6 figure

Behavior-Based Modeling and Its Application to Email Analysis

The Email Mining Toolkit (EMT) is a data mining system that computes behavior profiles or models of user email accounts. These models may be used for a multitude of tasks including forensic analyses and detection tasks of value to law enforcement and intelligence agencies, as well for as other typical tasks such as virus and spam detection. To demonstrate the power of the methods, we focus on the application of these models to detect the early onset of a viral propagation without "content-base" (or signature-based) analysis in common use in virus scanners. We present several experiments using real email from 15 users with injected simulated viral emails and describe how the combination of different behavior models improves overall detection rates. The performance results vary depending upon parameter settings, approaching 99% true positive (TP) (percentage of viral emails caught) in general cases and with 0.38% false positive (FP) (percentage of emails with attachments that are mislabeled as viral). The models used for this study are based upon volume and velocity statistics of a user's email rate and an analysis of the user's (social) cliques revealed in the person's email behavior. We show by way of simulation that virus propagations are detectable since viruses may emit emails at rates different than human behavior suggests is normal, and email is directed to groups of recipients in ways that violate the users' typical communications with their social groups

Analysis of interspecies adherence of oral bacteria using a membrane binding assay coupled with polymerase chain reaction-denaturing gradient gel electrophoresis profiling.

Information on co-adherence of different oral bacterial species is important for understanding interspecies interactions within oral microbial community. Current knowledge on this topic is heavily based on pariwise coaggregation of known, cultivable species. In this study, we employed a membrane binding assay coupled with polymerase chain reaction-denaturing gradient gel electrophoresis (PCR-DGGE) to systematically analyze the co-adherence profiles of oral bacterial species, and achieved a more profound knowledge beyond pairwise coaggregation. Two oral bacterial species were selected to serve as "bait": Fusobacterium nucleatum (F. nucleatum) whose ability to adhere to a multitude of oral bacterial species has been extensively studied for pairwise interactions and Streptococcus mutans (S. mutans) whose interacting partners are largely unknown. To enable screening of interacting partner species within bacterial mixtures, cells of the "bait" oral bacterium were immobilized on nitrocellulose membranes which were washed and blocked to prevent unspecific binding. The "prey" bacterial mixtures (including known species or natural saliva samples) were added, unbound cells were washed off after the incubation period and the remaining cells were eluted using 0.2 mol x L(-1) glycine. Genomic DNA was extracted, subjected to 16S rRNA PCR amplification and separation of the resulting PCR products by DGGE. Selected bands were recovered from the gel, sequenced and identified via Nucleotide BLAST searches against different databases. While few bacterial species bound to S. mutans, consistent with previous findings F. nucleatum adhered to a variety of bacterial species including uncultivable and uncharacterized ones. This new approach can more effectively analyze the co-adherence profiles of oral bacteria, and could facilitate the systematic study of interbacterial binding of oral microbial species

Behavior Profiling of Email

This paper describes the forensic and intelligence analysis capabilities of the Email Mining Toolkit (EMT) under development at the Columbia Intrusion Detection (IDS) Lab. EMT provides the means of loading, parsing and analyzing email logs, including content, in a wide range of formats. Many tools and techniques have been available from the fields of Information Retrieval (IR) and Natural Language Processing (NLP) for analyzing documents of various sorts, including emails. EMT, however, extends these kinds of analyses with an entirely new set of analyses that model "user behavior." EMT thus models the behavior of individual user email accounts, or groups of accounts, including the "social cliques" revealed by a user's email behavior

A genome-wide transcriptome profiling reveals the early molecular events during callus initiation in Arabidopsis multiple organs

AbstractInduction of a pluripotent cell mass termed callus is the first step in an in vitro plant regeneration system, which is required for subsequent regeneration of new organs or whole plants. However, the early molecular mechanism underlying callus initiation is largely elusive. Here, we analyzed the dynamic transcriptome profiling of callus initiation in Arabidopsis aerial and root explants and identified 1342 differentially expressed genes in both explants after incubation on callus-inducing medium. Detailed categorization revealed that the differentially expressed genes were mainly related to hormone homeostasis and signaling, transcriptional and post transcriptional regulations, protein phosphorelay cascades and DNA- or chromatin-modification. Further characterization showed that overexpression of two transcription factors, HB52 or CRF3, resulted in the callus formation in transgenic plants without exogenous auxin. Therefore, our comprehensive analyses provide some insight into the early molecular regulations during callus initiation and are useful for further identification of the regulators governing callus formation