Nanostarch Reinforced with Chitosan/Poly (vinyl pyrrolidone) Blend for In Vitro Wound Healing Application

Nanostarch, which is inexpensive and environmentally abundant, has been used as filler to prepare biocompatible films. The bio-nanocomposites were synthesized by solution casting method. TEM analysis proves that the average particle size of the nanostarch is in the range of 20–40?nm. Thermal stability and cell viability of CS/PVP matrix were best enhanced at 1% of nanostarch loading. The antibacterial activity exhibited by CPS bio-nanocomposite against Staphylococcus aureus and Pseudomonas aeruginosa and synergistic effects of CPS such as barrier properties, swelling properties, and better blood compatibility make it a suitable material for in vitro wound healing application.     

A multi-class classification MCLP model with particle swarm optimization for network intrusion detection

The critical data we share through computer network gets stolen by unethical means. This unethical way of accessing one’s data without proper authentication becomes intrusion. To solve this issue, in this paper we propose a new network intrusion detection method, Multi-Class Classification Multiple Criteria Linear Programming (MCC-MCLP) model. MCLP is a mathematical classification technique that is used widely to solve real-time data mining problems. So far, the literature discusses only about binary classification MCLP. But in this paper we propose a Multi-Class Classification MCLP model. We use PSO for fine-tuning the parameters of MCC-MCLP. KDD CUP 99 data set is used for performance evaluation of the proposed method. Our MCC-MCLP method classifies the data better and helps in fine-tuning the parameters with the help of PSO. The results clearly show that the proposed model performs better in terms of detection rate, false alarm rate and accuracy.     

Computation of Current Distributions using FEMLAB

An efficient method for the computation of current density and surface concentration distributions in electrochemical processes is analyzed using the commercial mathematical software FEMLAB. To illustrate the utility of the software, the procedure is applied to some realistic problems encountered in electrochemical engineering, such as current distribution in a continuous moving electrode, parallel plate electrode, hull cell, curvilinear hull cell, thin layer galvanic cell, through‐hole plating, and a recessed disc electrode. The model equations of the above cases are considered and their implementations into the software, FEMLAB, are analyzed. The technique is attractive because it involves a systematic way of coupling equations to perform case studies.     

Multi-view Scene Flow Estimation: A View Centered Variational Approach

We present a novel method for recovering the 3D structure and scene flow from calibrated multi-view sequences. We propose a 3D point cloud parametrization of the 3D structure and scene flow that allows us to directly estimate the desired unknowns. A unified global energy functional is proposed to incorporate the information from the available sequences and simultaneously recover both depth and scene flow. The functional enforces multi-view geometric consistency and imposes brightness constancy and piecewise smoothness assumptions directly on the 3D unknowns. It inherently handles the challenges of discontinuities, occlusions, and large displacements. The main contribution of this work is the fusion of a 3D representation and an advanced variational framework that directly uses the available multi-view information. This formulation allows us to advantageously bind the 3D unknowns in time and space. Different from optical flow and disparity, the proposed method results in a nonlinear mapping between the images’ coordinates, thus giving rise to additional challenges in the optimization process. Our experiments on real and synthetic data demonstrate that the proposed method successfully recovers the 3D structure and scene flow despite the complicated nonconvex optimization problem.     

Design and Synthesis of Imidazo[2,1‐b]thiazole–Chalcone Conjugates: Microtubule‐Destabilizing Agents

A series of chalcone conjugates featuring the imidazo[2,1‐b]thiazole scaffold was designed, synthesized, and evaluated for their cytotoxic activity against five human cancer cell lines (MCF‐7, A549, HeLa, DU‐145 and HT‐29). These new hybrid molecules have shown promising cytotoxic activity with IC₅₀ values ranging from 0.64 to 30.9 μM . Among them, (E)‐3‐(6‐(4‐fluorophenyl)‐2,3‐bis(4‐methoxyphenyl)imidazo[2,1‐b]thiazol‐5‐yl)‐1‐(pyridin‐2‐yl)prop‐2‐en‐1‐one ( 11 x ) showed potent antiproliferative activity with IC₅₀ values ranging from 0.64 to 1.44 μM in all tested cell lines. To investigate the mechanism of action, the detailed biological aspects of this promising conjugate ( 11 x ) were carried out on the A549 lung cancer cell line. The tubulin polymerization assay and immunofluoresence analysis results suggest that this conjugate effectively inhibits microtubule assembly in A549 cells. Flow cytometric analysis revealed that this conjugate induces cell‐cycle arrest in the G2/M phase and leads to apoptotic cell death. This was further confirmed by Hoechst staining, activation of caspase‐3, DNA fragmentation analysis, and Annexin V–FITC assay. Moreover, molecular docking studies indicated that this conjugate ( 11 x) interacts and binds efficiently with the tubulin protein.     

BOT Viability Model for Large-Scale Infrastructure Projects

The key to a successful implementation of a build-operate-transfer (BOT) infrastructure project is in-depth analysis of all aspects related to economic, environmental, social, political, legal, and financial feasibility of the project. For these reasons, the analysis of the project feasibility decision needs a technique to include the qualitative decision factors that have a strong impact on the project. This paper aims to introduce a decomposed evaluation model developed to assess the most common significant decision factors that strongly affect the feasibility of BOT projects. The paper describes the viability decision factors that were identified and screened with the assistance of a group of industry experts. This analysis yielded 21 significant factors that would have a certain impact on the feasibility of any BOT project. These factors were classified into three relative categories forming the structure of the suggested project viability model. This model presents a new approach, based on the analytical hierarchy process technique, to evaluate the relationships between decision factors related to project feasibility determination. The new approach has been validated by information obtained from three case studies of BOT projects. The proposed approach to project feasibility evaluation aims to increase the decision maker’s ability to determine the factors contributing the most to the viability to the BOT project at hand.