Magnetic-nanoparticle-doped carbogenic nanocomposite: an effective magnetic resonance/fluorescence multimodal imaging probe

A novel and facile approach is developed to synthesize a magnetic nanoparticle (iron oxide)-doped carbogenic nanocomposite (IO-CNC) for magnetic resonance (MR)/fluorescence imaging applications. IO-CNC is synthesized by thermal decomposition of organic precursors in the presence of Fe(3) O(4) nanoparticles with an average size of 6 nm. IO-CNC shows wavelength-tunable fluorescence properties with high quantum yield. Magnetic studies confirm the superparamagnetic nature of IO-CNC at room temperature. IO-CNC shows MR contrast behavior by affecting the proton relaxation phenomena. The measured longitudinal (r(1) ) and transverse (r(2) ) relaxivity values are 4.52 and 34.75 mM(-1) s(-1) , respectively. No apparent cytotoxicity is observed and the nanocomposite shows a biocompatible nature. In vivo MR studies show both T(1) and T(2) * contrast behavior of the nanocomposite. Fluorescence imaging indicates selective uptake of IO-CNC by macrophages in spleen.     

Genetic variants of beta-lactoglobulin gene and its association with milk composition traits in riverine buffalo

A study was carried out to determine genetic variants of beta-lactoglobulin gene and to explore associations between these and milk composition traits in riverine buffalo. Single strand conformation polymorphism was employed to detect the genetic variants of the gene. Two fragments of this gene i.e. 119 bp of exon I and 400 bp spanning exon IV and intron IV were included in the study. For 119 bp fragment, three alleles namely, A, B and C were observed in all the buffalo breeds whereas four alleles (A, B, C and D) were detected for 400 bp fragment. The frequency distribution of alleles was different in different breeds of buffaloes for both the fragments. For exon I fragment, the milk composition traits such as total SNF, protein, solid, fat and whey protein yield were found to be significantly (P<0.05) associated with genotypes in Murrah and Bhadawari buffalo whereas in Mehsana breed genotypes were significantly (P<0.05) co-related with total SNF, solid and fat yield. Genotypes of 400 bp fragment, only total fat yield in Mehsana buffalo was found to be significantly (P<0.05) associated with genotypes.     

Ensemble clustering using semidefinite programming with applications

In this paper, we study the ensemble clustering problem, where the input is in the form of multiple clustering solutions. The goal of ensemble clustering algorithms is to aggregate the solutions into one solution that maximizes the agreement in the input ensemble. We obtain several new results for this problem. Specifically, we show that the notion of agreement under such circumstances can be better captured using a 2D string encoding rather than a voting strategy, which is common among existing approaches. Our optimization proceeds by first constructing a non-linear objective function which is then transformed into a 0-1 Semidefinite program (SDP) using novel convexification techniques. This model can be subsequently relaxed to a polynomial time solvable SDP. In addition to the theoretical contributions, our experimental results on standard machine learning and synthetic datasets show that this approach leads to improvements not only in terms of the proposed agreement measure but also the existing agreement measures based on voting strategies. In addition, we identify several new application scenarios for this problem. These include combining multiple image segmentations and generating tissue maps from multiple-channel Diffusion Tensor brain images to identify the underlying structure of the brain.     

Up-Conversion in Perovskite Strontium Stannate Nanocrystal Whiskers

We report a simple, eco-friendly facile wet chemical route for the synthesis of pristine and rare–earth metal co-doped (Er/Yb, 10/90, 15/85, 20/80) nano-crystalline, strontium stannate (SrSnO₃) whiskers. It is n-type wide bandgap (~4.1 eV) orthorhombic perovskite semiconductor at room temperature, and reveals increase in band gap with the increase in Er/Yb content (from 4.10 to 4.23, 4.30 to 4.39 eV). The samples exhibited strong emission around 365 nm following band-edge excitation by the wavelength of 290 nm. Further, strong up-conversion emission was observed in visible range at the excitation of wavelength 980 nm. The resistivity values were found to decrease with increase in the dopants Er/Yb concentration due to enhancement of charge carriers.     

Optimal on–off control of refrigerated transport systems

This paper presents a hysteretic on–off control scheme with optimization algorithms for temperature regulation in refrigerated transport systems. A nonlinear dynamic refrigerated transport system model, which consists of a refrigeration unit and a cargo space, is developed. The model serves as an analytical tool for control design. An optimal on–off control strategy is developed based on the time domain analysis of the temperature oscillations. A cost function involving temperature variations from the set-point, energy consumption and average compressor on–off cycling frequency is introduced for minimization. Choices of weighting values in the cost function give the flexibility of the control approach to meet different requirements. Simulation examples are presented that demonstrate the ability and robustness of the proposed method in achieving tighter temperature regulation and higher system efficiency control in transport refrigeration systems. The simulations are augmented by experimental validation via a novel hardware-in-the-loop load emulation approach.     

Adaptive neural controller for cooperative multiple robot manipulator system manipulating a single rigid object

In this article, an adaptive neural controller is developed for cooperative multiple robot manipulator system carrying and manipulating a common rigid object. In coordinated manipulation of a single object using multiple robot manipulators simultaneous control of the object motion and the internal force exerted by manipulators on the object is required. Firstly, an integrated dynamic model of the manipulators and the object is derived in terms of object position and orientation as the states of the derived model. Based on this model, a controller is proposed that achieves required trajectory tracking of the object as well as tracking of the desired internal forces arising in the system. A feedforward neural network is employed to learn the unknown dynamics of robot manipulators and the object. It is shown that the neural network can cope with the unknown nonlinearities through the adaptive learning process and requires no preliminary offline learning. The adaptive learning algorithm is derived from Lyapunov stability analysis so that both error convergence and tracking stability are guaranteed in the closed loop system. Finally, simulation studies and analysis are carried out for two three-link planar manipulators moving a circular disc on specified trajectory.     

Liquid Biomarkers for Improved Diagnosis and Classification of CNS Tumors

Liquid biopsy, as a non-invasive technique for cancer diagnosis, has emerged as a major step forward in conquering tumors. Current practice in diagnosis of central nervous system (CNS) tumors involves invasive acquisition of tumor biopsy upon detection of tumor on neuroimaging. Liquid biopsy enables non-invasive, rapid, precise and, in particular, real-time cancer detection, prognosis and treatment monitoring, especially for CNS tumors. This approach can also uncover the heterogeneity of these tumors and will likely replace tissue biopsy in the future. Key components of liquid biopsy mainly include circulating tumor cells (CTC), circulating tumor nucleic acids (ctDNA, miRNA) and exosomes and samples can be obtained from the cerebrospinal fluid, plasma and serum of patients with CNS malignancies. This review covers current progress in application of liquid biopsies for diagnosis and monitoring of CNS malignancies.     

MEMs hydrodynamic bearings: Applications to and implications for machine failure prevention

Microdynamic systems have been studied for a number of years. Only limited work, however, has been completed on integrating microdynamic components into systems that satisfy mechanical tasks on macroscopic scales. In this paper, we describe microdynamic components needed to produce a surface which is actively deformable on local scales. In particular, we consider the design and demonstration of smart journal and thrust bearings capable of using embedded sensors and actuators to change dynamically the surface geometry. The ability actively to deform bearing surfaces allows for the design of bearings which are less prone to failure, the design of bearings with greater load-carrying abilities, and a fundamental study of the effect of surface geometries and fluid conditions on bearing performance, such as start-up and shut-down conditions. Some results of our new bearing designs are presented, focusing on numerical bearing models, sensor and actuator design and fabrication, and physical experimentation.     

Polypropylene/phosphazene nanotube nanocomposites: Thermal,mechanical, and flame retardation studies

In this study, flame retardant polypropylene (PP) nanocomposites with superior mechanical performance have been developed using amine-functionalized phosphazene nanotubes (APZS, 1–10 wt%) through melt-blending method. Polypropylene-graft-maleic anhydride was used as the compatibilizer to attain effective interaction between the nanofiller and the PP matrix. The characterization of amine-functionalized phosphazene nanotubes (APZS) using solid-state nuclear magnetic resonance (NMR), X-ray photoelectron spectroscopy, X-ray diffraction, fourier-transform infrared (FTIR), and transmission electron microscopy indicated successful amine functionalization, though structural changes were observed as compared to the unfunctionalized nanotubes. Owing to the covalent polymer-filler interfacial interactions and resulting in uniform filler dispersion, the nanocomposites exhibited significant enhancement in the tensile modulus up to 5 wt% APZS content (98% increment at 5 wt% content as compared to pure polymer). The addition of a small fraction of APZS (1 wt%) improved the impact strength of the nanocomposite by more than 180%. APZS acted as a weak nucleating agent for PP, thereby leading to enhanced degree of crystallinity (up to 5 wt% APZS content). The thermal stability of the nanocomposites was also enhanced with APZS content. The nanocomposites with 5 and 10 wt% APZS loading exhibited a V0 rating in UL-94 test, indicating that APZS introduced a robust flame retardancy behavior in the PP nanocomposites. The limiting oxygen index values also confirmed the findings from the UL-94 analysis. The developed nanocomposites exhibit high potential of use in a wide range of high temperature applications.