Synthesis of High Coercivity Cobalt Nanotubes with Acetate Precursors and Elucidation of the Mechanism of Growth

Cobalt nanotubes (CoNTs) with very high longitudinal coercivity were prepared by electrodeposition of cobalt acetate for the first time by using anodized alumina (AAO) template. They were then characterized with X-ray diffraction (XRD), a field emission scanning electron microscope (FESEM), and a transmission electron microscope (TEM). Formation of a highly ordered hexagonal cobalt phase is observed. Room temperature SQUID (superconducting quantum interference device) magnetometer measurements indicate that the easy axis of magnetization is parallel to the nanotube axis. These CoNTs exhibit very high longitudinal coercivity of ∼820 Oe. A very high intertubular interaction resulting from magnetostatic dipolar interaction between nanotubes is observed. Thick-walled nanotubes were also fabricated by using cobalt acetate tetrahydrate precursors. A plausible mechanism for the formation of CoNTs based on mobility assisted growth is proposed. The role of the hydration layer and the mobility of metal ions are elucidated in the case of the growth mechanism of one-dimensional geometry

Conduction mechanism in plasma polymerized aniline thin films

Electrical properties of ac plasma polymerized aniline thin films are investigated with a view of determining the dominant conduction mechanism. The current–voltage (I–V) characteristics in symmetric and asymmetric electrode configuration for polyaniline thin films in the thickness range from 1300 to 2000 A ° are investigated. From the studies on asymmetric electrode configuration, it is found that the dominant conduction mechanism in these films is of Schottky type

On the Growth Mechanism of Nickel and Cobalt Nanowires and Comparison of Their Magnetic Properties

Magnetic nanowires (NWs) are ideal materials for the fabrication of various multifunctional nanostructures which can be manipulated by an external magnetic fi eld. Highly crystalline and textured nanowires of nickel (Ni NWs) and cobalt (Co NWs) with high aspect ratio (~330) and high coercivity have been synthesized by electrodeposition using nickel sulphate hexahydrate (NiSO4·6H2O) and cobalt sulphate heptahydrate (CoSO4·7H2O) respectively on nanoporous alumina membranes. They exhibit a preferential growth along〈110〉. A general mobility assisted growth mechanism for the formation of Ni and Co NWs is proposed. The role of the hydration layer on the resulting one-dimensional geometry in the case of potentiostatic electrodeposition is verified. A very high interwire interaction resulting from magnetostatic dipolar interactions between the nanowires is observed. An unusual low-temperature magnetisation switching for fi eld parallel to the wire axis is evident from the peculiar high fi eld M(T) curve

Mechanism of ac conduction in nanostructured manganese zinc mixed ferrites

Mn1−xZnxFe2O4 nanoparticles (x = 0 to 1) were synthesized by the wet chemical co-precipitation technique. X-ray diffraction and transmission electron microscopy and high resolution transmission electron microscopy were effectively utilized to investigate the different structural parameters. The ac conductivity of nanosized Mn1−xZnxFe2O4 were investigated as a function of frequency, temperature and composition. The frequency dependence of ac conductivity is analysed by the power law σ(ω)ac = Bωn which is typical for charge transport by hopping or tunnelling processes. The temperature dependence of frequency exponent n was investigated to understand the conduction mechanism in different compositions. The conduction mechanisms are mainly based on polaron hopping conduction

On conduction mechanism in paramagnetic phase of Gd based manganites

Materials belonging to the family of manganites are technologically important since they exhibit colossal magneto resistance. A proper understanding of the transport properties is very vital in tailoring the properties. A heavy rare earth doped manganite like Gd0·7Sr0·3MnO3 is purported to be exhibiting unusual properties because of smaller ionic radius of Gd. Gd0·7Sr0·3MnO3 is prepared by a wet solid state reaction method. The conduction mechanism in such a compound has been elucidated by subjecting the material to low temperature d.c. conductivity measurement. It has been found that the low band width material follows a variable range hopping (VRH) model followed by a small polaron hopping (SPH) model. The results are presented here

The empirical study of the price mechanism in the Chinese housing market

In China, the history of the establishment of the private housing market is pretty short. Actually in less then two decades, the market has grown from almost the scratch to playing an important role in the economy. A great achievement! But many problems also exist. They need to be properly addressed and solved. Price problem---simply put, housing price is too high--- is one of them, and this paper is focused on it. Three basic questions are posed, i.e. (1) how to judge the housing affordability? (2) why the housing price is so high? (3) how to solve the housing price problem. The paper pays particular attention to answering the second question. Except the numerous news reports and surveys show that most of the ordinary city dwellers complained about the high housing price, the mathematical means, the four ratios, are applied to judge the housing affordability in Shanghai and Shenzhen. The results are very clear that the price problem is severe. So why? Something is wrong with the price mechanism. This research shows that mainly these five factors contribute to the price problem: the housing reform, the housing development model, the unbalanced housing market, the housing project financing and the poor governmental management. Finally the paper puts forward five suggestions to solve the housing price problem in first-hand private Chinese housing market. They include: the establishment of real estate information system, the creation of specific price management department, the government price regulation, the property tax and the legalization of "cushion money".

India’s Carbon Governance: The Clean Development Mechanism

Carbon Governance systems – institutional arrangements in place for mitigating greenhouse gas emissions – are different in emerging countries. Indeed, carbon is the same everywhere but Carbon Governance isn’t: in Brazil, the financial community is actively interested in carbon trading, but Chinese banks have hardly any interest in it; and while the Chinese government takes an active interest in providing capacity to project developers, the Brazilian authorities see their role uniquely as guarantors of environmental integrity of emissions reductions projects. In the case of India, carbon governance offers specific features of patterns and interactions mostly because India strongly developed the Clean Development Mechanism and its market. This article proposes a study to the research and understanding of how exactly carbon governance works in the Indian case, knowing that India is the second largest host of CDM projects.

Structural insights into the allosteric activation mechanism of cGMP-dependent protein kinase I

Cyclic GMP-dependent protein kinase (PKG) is a key transducer in the NO-cGMP signaling pathway. In this line, PKG has been considered an important drug target for treating hypertensive cardiovascular and pulmonary diseases. However, the investigation of PKG’s allosteric activation mechanism has been hampered by a lack of structural information. One of the fundamental questions on the cGMP-dependent activation of PKG is how the enzyme can distinguish cGMP over cAMP and selectively respond to cGMP. To ensure proper signaling, PKG must have developed unique features to ensure its activation upon the right activation signal. In this thesis, the cGMP-selective activation mechanism of PKG was studied through determining crystal structures of three truncated constructs of the regulatory domain [CNB-A (92-227), CNB-B (271-369), and CNB-A/B (92-351)] of PKG Iβ in the absence or presence of cyclic nucleotides. Herein, two individual CNB domain structures with biochemical data revealed that the C-terminal CNB domain (CNB-B) is responsible for cGMP selectivity, while the N-terminal CNB-domain (CNB-A) has a higher binding affinity for both cGMP and cAMP without showing any selectivity. Based on these crystal structures, mutagenesis studies were performed in which the critical residues for cyclic nucleotide selectivity and activation were identified. Furthermore, we discovered that the conformational changes of the C-terminal helix of the CNB-B that bridges between the regulatory and catalytic domains including the hydrophobic capping interaction are crucial for PKG activation. In addition, to observe the global conformation of the activated R-domain, I solved a co-crystal structure of the CNB-A/B with cGMP. Although a monomeric construct was crystallized, the structure displays a dimer. Strikingly, the CNB-A domain and its bound cGMP provide a key interface for this dimeric interaction. Using small angle X-ray scattering (SAXS), the existence of the cGMP-mediated dimeric interface within the CNB domains was confirmed. Furthermore, measuring cGMP-binding affinities (EC50) of the dimeric interface mutants as well as determining activation constants (Ka) revealed that the interface formation is important for PKG activation. To conclude, this thesis study provides a new mechanistic insight in PKG activation along with a newly found interface that can be targeted for designing PKG-specific activity modulators.

Natural Object Categorization

This thesis addresses the problem of categorizing natural objects. To provide a criteria for categorization we propose that the purpose of a categorization is to support the inference of unobserved properties of objects from the observed properties. Because no such set of categories can be constructed in an arbitrary world, we present the Principle of Natural Modes as a claim about the structure of the world. We first define an evaluation function that measures how well a set of categories supports the inference goals of the observer. Entropy measures for property uncertainty and category uncertainty are combined through a free parameter that reflects the goals of the observer. Natural categorizations are shown to be those that are stable with respect to this free parameter. The evaluation function is tested in the domain of leaves and is found to be sensitive to the structure of the natural categories corresponding to the different species. We next develop a categorization paradigm that utilizes the categorization evaluation function in recovering natural categories. A statistical hypothesis generation algorithm is presented that is shown to be an effective categorization procedure. Examples drawn from several natural domains are presented, including data known to be a difficult test case for numerical categorization techniques. We next extend the categorization paradigm such that multiple levels of natural categories are recovered; by means of recursively invoking the categorization procedure both the genera and species are recovered in a population of anaerobic bacteria. Finally, a method is presented for evaluating the utility of features in recovering natural categories. This method also provides a mechanism for determining which features are constrained by the different processes present in a multiple modal world.

A Theory of Quantitative Inference Applied to a Mechanical Design Compiler

This thesis presents the ideas underlying a computer program that takes as input a schematic of a mechanical or hydraulic power transmission system, plus specifications and a utility function, and returns catalog numbers from predefined catalogs for the optimal selection of components implementing the design. Unlike programs for designing single components or systems, the program provides the designer with a high level "language" in which to compose new designs. It then performs some of the detailed design process. The process of "compilation" is based on a formalization of quantitative inferences about hierarchically organized sets of artifacts and operating conditions. This allows the design compilation without the exhaustive enumeration of alternatives.

A Statistical Image-Based Shape Model for Visual Hull Reconstruction and 3D Structure Inference

We present a statistical image-based shape + structure model for Bayesian visual hull reconstruction and 3D structure inference. The 3D shape of a class of objects is represented by sets of contours from silhouette views simultaneously observed from multiple calibrated cameras. Bayesian reconstructions of new shapes are then estimated using a prior density constructed with a mixture model and probabilistic principal components analysis. We show how the use of a class-specific prior in a visual hull reconstruction can reduce the effect of segmentation errors from the silhouette extraction process. The proposed method is applied to a data set of pedestrian images, and improvements in the approximate 3D models under various noise conditions are shown. We further augment the shape model to incorporate structural features of interest; unknown structural parameters for a novel set of contours are then inferred via the Bayesian reconstruction process. Model matching and parameter inference are done entirely in the image domain and require no explicit 3D construction. Our shape model enables accurate estimation of structure despite segmentation errors or missing views in the input silhouettes, and works even with only a single input view. Using a data set of thousands of pedestrian images generated from a synthetic model, we can accurately infer the 3D locations of 19 joints on the body based on observed silhouette contours from real images.

Memory Usage Inference for Object-Oriented Programs

We present a type-based approach to statically derive symbolic closed-form formulae that characterize the bounds of heap memory usages of programs written in object-oriented languages. Given a program with size and alias annotations, our inference system will compute the amount of memory required by the methods to execute successfully as well as the amount of memory released when methods return. The obtained analysis results are useful for networked devices with limited computational resources as well as embedded software.

Inference of distributional parameters from compositional samples containing nondetects

Low concentrations of elements in geochemical analyses have the peculiarity of being compositional data and, for a given level of significance, are likely to be beyond the capabilities of laboratories to distinguish between minute concentrations and complete absence, thus preventing laboratories from reporting extremely low concentrations of the analyte. Instead, what is reported is the detection limit, which is the minimum concentration that conclusively differentiates between presence and absence of the element. A spatially distributed exhaustive sample is employed in this study to generate unbiased sub-samples, which are further censored to observe the effect that different detection limits and sample sizes have on the inference of population distributions starting from geochemical analyses having specimens below detection limit (nondetects). The isometric logratio transformation is used to convert the compositional data in the simplex to samples in real space, thus allowing the practitioner to properly borrow from the large source of statistical techniques valid only in real space. The bootstrap method is used to numerically investigate the reliability of inferring several distributional parameters employing different forms of imputation for the censored data. The case study illustrates that, in general, best results are obtained when imputations are made using the distribution best fitting the readings above detection limit and exposes the problems of other more widely used practices. When the sample is spatially correlated, it is necessary to combine the bootstrap with stochastic simulation