Exploiting small world property for network clustering

Graph partitioning is a traditional problem with many applications and a number of high-quality algorithms have been developed. Recently, demand for social network analysis arouses the new research interest on graph partitioning/clustering. Social networks differ from conventional graphs in that they exhibit some key properties like power-law and small-world property. Currently, these features are largely neglected in popular partitioning algorithms. In this paper, we present a novel framework which leverages the small-world property for finding clusters in social networks. The framework consists of several key features. Firstly, we define a total order, which combines the edge weight, the small-world weight, and the hub value, to better reflect the connection strength between two vertices. Secondly, we design a strategy using this ordered list, to greedily, yet effectively, refine existing partitioning algorithms for common objective functions. Thirdly, the proposed method is independent of the original approach, such that it could be integrated with any types of existing graph clustering algorithms. We conduct an extensive performance study on both real-life and synthetic datasets. The empirical results clearly demonstrate that our framework significantly improves the output of the state-of-the-art methods. Furthermore, we show that the proposed method returns clusters with both internal and external higher qualities.     

Sites for CO2 activation over amine-functionalized mesoporous Ti(Al)-SBA-15 catalysts

Activation of CO₂ and its utilization in the synthesis of chloropropene and styrene carbonates over functionalized, mesoporous SBA-15 solids, have been investigated. The surface basicity of SBA-15 was modified with nitrogen-based organic molecules of varying basicity viz., alkyl amines (–NH₂), adenine (Ade), imidazole (Im) and guanine (Gua). The surface of SBA-15 was also functionalized with Ti⁴⁺ and Al³⁺ species. The acid–base properties of these modified SBA-15 materials were investigated by temperature-programmed desorption (TPD) and diffuse-reflectance infrared Fourier transform (DRIFT) spectroscopy. NH₃ and pyridine were used as probe molecules for acid sites, while CO₂ was used to characterize the basic sites. CO₂ was activated at the basic amine sites forming surface carbamate species (IR peaks: 1609 and 1446 cm⁻¹). The latter reacted further with epoxides adsorbed on the acid sites forming cyclic carbonates. A correlation between the intensity of the IR peak at 1609 cm⁻¹ and cyclic carbonate yield has been observed. The cyclic carbonate yields were higher when both the acid and base functionalities were present on the surface. The Ti- and Al-SBA-15 functionalized with adenine exhibited the highest catalytic activity and selectivity. There is an optimal dependence (“volcanic plot”) of the yield of cyclic carbonates on the desorption temperature, T_max(CO₂) in the TPD experiments. These solid catalysts were structurally stable up to 473 K and could be recycled for repeated use. In addition to density, the strength and type of amine sites play a crucial role on CO₂ activation and utilization.     

Electrodeposition of nickel-cobalt-zinc alloys from a borate bath

The electrodeposition has been studied of nickel-cobalt-zinc alloys from a borate bath containing nickel sulphate (120–140 g dm^–3), cobalt sulphate (30–46 g dm^–3), zinc sulphate (144–168 g dm^–3), boric acid (30 g dm^–3) and ammonium chloride (2 g dm^–3). The operating conditions were: current density, 2.0–5.0 A dm^–2; temperature, 30–40°C and pH, 2.4 to 5.4. Light grey, semibright, stressed films have been obtained. However, the deposits consist partially of black powder when the concentration of the various components is increased. The brightness is found to increase with decreasing temperature and pH of the solution. The total cathode efficiency increases when the pH and temperature of the solution decrease, whereas at any particular pH and temperature it first decreases, reaches a minimum and then increases with increasing current density.     

Understanding the pathogenesis of endometriosis through proteomics: Recent advances and future prospects

Endometriosis is a complex gynecological disease, characterized by the presence and growth of endometrial tissue outside the uterus, resulting in pelvic pain and infertility. It occurs in 10% of women in their reproductive age. The viable endometrial cells enter the peritoneal cavity by retrograde menstruation, implant, and cause lesions ectopically; depending on their ability to survive, attach, grow, and invade. These “normal” endometrial cells turn “endometriotic” apparently because of inherent abnormalities present in them. Information on these molecular abnormalities is now being sought through proteomic approaches. Recent proteome-based comparisons between the eutopic endometrium from normal women and patients with endometriosis have revealed several proteins (many of which are shown to have a role in several cancers), of which a few have been validated as potential players in the etiology of endometriosis. After an initial in-flow of information from these proteome studies of eutopic endometrium, focus now needs to be expanded to the changes in the various protein PTMs and their upstream effectors present in these tissues. Early diagnosis of endometriosis through noninvasive means is the need of the hour as well—which would require the use of the presently existing immunoassays, along with the advancing MS-based proteomics. In this review, we aim to discuss these future thrust areas of human endometriosis proteomics and also present the proteomic advances made so far in understanding the molecular basis of endometriosis.     

Subsumption and indexing in constraint query languages with linear arithmetic constraints

Bottom-up evaluation of a program-query pair in a constraint query language (CQL) starts with the facts in the database and repeatedly applies the rules of the program, in iterations, to compute new facts, until we have reached a fixpoint. Checking if a fixpoint has been reached amounts to checking if any new facts were computed in an iteration. Such a check also enhances efficiency in that subsumed facts can be discarded, and not be used to make any further derivations in subsequent iterations, if we use Semi-naive evaluation. We show that the problem of subsumption in CQLs with linear arithmetic constraints is co-NP complete, and present a deterministic algorithm, based on the divide and conquer strategy, for this problem. We also identify polynomial-time sufficient conditions for subsumption and non-subsumption in CQLs with linear arithmetic constraints. We adapt indexing strategies from spatial databases for efficiently indexing facts in such a CQL: such indexing is crucial for performance in the presence of large databases. Based on a recent algorithm by C. Lassez and J.-L. Lassez for quantifier elimination, we present an incremental version of the algorithm to check for subsumption in CQLs with linear arithmetic constraints.This work was supported by a David and Lucile Packard Foundation Fellowship in Science and Engineering, a Presidential Young Investigator Award, with matching grants from the Digital Equipment Corporation, Tandem and Xerox, and NSF Grant No. IRI-9011563.     

Deformable template models for emission tomography

The reconstruction of emission tomography data is an ill-posed inverse problem and, as such, requires some form of regularization. Previous efforts to regularize the restoration process have incorporated rather general assumptions about the isotope distribution within a patient's body. A theoretical and algorithmic framework is presented in which the notion of a deformable template can be used to identify and quantify brain tumors in pediatric patients. Patient data and computer simulation experiments are presented which illustrate the performance of the deformable template approach to single photon emission computed tomography     

Autostereoscopic 3D pictures on optically rewritable electronic paper

In this article, we disclose a method to fabricate the three‐dimensional (3D) image on an optically rewritable (ORW) electronic paper (e‐paper) by deploying the lenticular lenses array on the top of the ORW e‐paper. Unlike other autostereoscopic 3D liquid crystal displays, our autostereoscopic 3D ORW e‐paper is actually a green technology, which is without electrode and voltage. No electricity is needed to maintain the 3D image on the ORW e‐paper. We can easily change a 3D image by erasing and rewriting with photoalignment technology.     

Model-based cross-layer monitoring and adaptation of multilayer systems

With the vision of "Internet as a computer", complex software-intensive systems running on the Internet, or the "Internetwares", can be also divided into multiple layers. Each layer has a different focus, implementation technique, and stakeholders. Monitoring and adaptation of such multilayer systems are challenging, because the mismatches and adaptations are interrelated across the layers. This interrelation makes it difficult to find out: 1) When a system change causes mismatches in one layer, how to identify all the cascaded mismatches on the other layers? 2) When an adaptation is performed at one layer, how to find out all the complementary adaptations required in other layers? This paper presents a model-based approach towards cross-layer monitoring and adaptation of multilayer systems. We provide standard meta-modelling languages for system experts to specify the concepts and constraints separately for each layer, as well as the relations among the concepts from different layers. Within each individual layer, we use run-time models to represent the system state specific to this layer, monitor the systems by evaluating model changes according to specified constraints, and support manual or semi-automated adaption by modifying the models. When a change happens in the run-time model for one layer, either caused by system changes or by the adaptation, we synchronize the models for other layers to identify cascaded mismatches and complementary adaptations across the layers. We illustrate the approach on a simulated crisis management system, and are using it on a number of ongoing projects.     

Region based QIM digital watermarking scheme for image database in DCT domain

This paper proposes a region based digital watermarking scheme to serve the purpose of copyright protection and integrity verification of image database using discrete cosine transform (DCT). The objective is achieved by embedding watermark into visually significant regions of the image(s) using quantization index modulation (QIM). The main contributions of this work are, (1) the use of quad tree decomposition for image segmentation to find visually significant regions, and (2) the use of image database as a single entity for watermarking, instead of watermarking on individual image, so that integrity of the database is checked. Simulation results validate the above claims. Simulation results also show that the proposed scheme is robust and secured against a wide range of attacks available in StirMark 4.0 package.     

Policy analysis for Administrative Role-Based Access Control

Role-Based Access Control (RBAC) is a widely used model for expressing access control policies. In large organizations, the RBAC policy may be collectively managed by many administrators. Administrative RBAC (ARBAC) models express the authority of administrators, thereby specifying how an organization’s RBAC policy may change. Changes by one administrator may interact in unintended ways with changes by other administrators. Consequently, the effect of an ARBAC policy is hard to understand by simple inspection. In this paper, we consider the problem of analyzing ARBAC policies. Specifically, we consider reachability properties (e.g., whether a user can eventually be assigned to a role by a group of administrators), availability properties (e.g., whether a user cannot be removed from a role by a group of administrators), containment properties (e.g., every member of one role is also a member of another role) satisfied by a policy, and information flow properties. We show that reachability analysis for ARBAC is PSPACE-complete. We also give algorithms and complexity results for reachability and related analysis problems for several categories of ARBAC policies, defined by simple restrictions on the policy language. Some of these results are based on the connection we establish between security policy analysis and planning problems in Artificial Intelligence.