Ultrafast Raman loss spectroscopy: a new approach to vibrational structure determination

The rapid data acquisition, natural fluorescence rejection and experimental ease are the advantages of the ultra-fast Raman loss scattering (URLS) which makes it a unique and valuable molecular structure-determining technique. URLS is an analogue of stimulated Raman scattering (SRS) but far more sensitive than SRS. It involves the interaction of two laser sources, viz. a picosecond (ps) pulse and white light, with the sample leading to the generation of loss signal on the higher energy (blue) side with respect to the wavelength of the ps pulse, unlike the gain signal observed on the red side in SRS. These loss signals are at least 1.5 times more intense than the SRS signals. Also, the very prerequisite of the experimental protocol for signal detection to be on the higher energy side by design eliminates the interference from fluorescence, which always appears on the red side. Unlike coherent anti-Stokes Raman scattering, URLS signals are not precluded by non-resonant background under resonance condition and also being a self-phase matched process, it is experimentally easier.

Digital elevation model error in terrain analysis

Digital elevation models (DEMs) have been an important topic in geography and surveying sciences for decades due to their geomorphological importance as the reference surface for gravita-tion-driven material flow, as well as the wide range of uses and applications. When DEM is used in terrain analysis, for example in automatic drainage basin delineation, errors of the model collect in the analysis results. Investigation of this phenomenon is known as error propagation analysis, which has a direct influence on the decision-making process based on interpretations and applications of terrain analysis. Additionally, it may have an indirect influence on data acquisition and the DEM generation. The focus of the thesis was on the fine toposcale DEMs, which are typically represented in a 5-50m grid and used in the application scale 1:10 000-1:50 000. The thesis presents a three-step framework for investigating error propagation in DEM-based terrain analysis. The framework includes methods for visualising the morphological gross errors of DEMs, exploring the statistical and spatial characteristics of the DEM error, making analytical and simulation-based error propagation analysis and interpreting the error propagation analysis results. The DEM error model was built using geostatistical methods. The results show that appropriate and exhaustive reporting of various aspects of fine toposcale DEM error is a complex task. This is due to the high number of outliers in the error distribution and morphological gross errors, which are detectable with presented visualisation methods. In ad-dition, the use of global characterisation of DEM error is a gross generalisation of reality due to the small extent of the areas in which the decision of stationarity is not violated. This was shown using exhaustive high-quality reference DEM based on airborne laser scanning and local semivariogram analysis. The error propagation analysis revealed that, as expected, an increase in the DEM vertical error will increase the error in surface derivatives. However, contrary to expectations, the spatial au-tocorrelation of the model appears to have varying effects on the error propagation analysis depend-ing on the application. The use of a spatially uncorrelated DEM error model has been considered as a 'worst-case scenario', but this opinion is now challenged because none of the DEM derivatives investigated in the study had maximum variation with spatially uncorrelated random error. Sig-nificant performance improvement was achieved in simulation-based error propagation analysis by applying process convolution in generating realisations of the DEM error model. In addition, typology of uncertainty in drainage basin delineations is presented.

Statistical analysis of spectral data: A methodology for designing an intelligent monitoring system for the diabetic foot

Early detection of (pre-)signs of ulceration on a diabetic foot is valuable for clinical practice. Hyperspectral imaging is a promising technique for detection and classification of such (pre-)signs. However, the number of the spectral bands should be limited to avoid overfitting, which is critical for pixel classification with hyperspectral image data. The goal was to design a detector/classifier based on spectral imaging (SI) with a small number of optical bandpass filters. The performance and stability of the design were also investigated. The selection of the bandpass filters boils down to a feature selection problem. A dataset was built, containing reflectance spectra of 227 skin spots from 64 patients, measured with a spectrometer. Each skin spot was annotated manually by clinicians as "healthy" or a specific (pre-)sign of ulceration. Statistical analysis on the data set showed the number of required filters is between 3 and 7, depending on additional constraints on the filter set. The stability analysis revealed that shot noise was the most critical factor affecting the classification performance. It indicated that this impact could be avoided in future SI systems with a camera sensor whose saturation level is higher than 106, or by postimage processing.

Malaria burden and costs of intensified control in Bhutan, 2006-2014: A situational analysis

- Introduction Malaria cases have dwindled in Bhutan with aim of malaria elimination by 2016. The aims of this study are to determine the trends and burden of malaria, the costs of intensified control activities, the main donors of the control activities and the costs of different preventive measures in the pre-elimination phase (2006-2014). - Methods A descriptive analysis of malaria surveillance data from 2006-2014 was carried out, using data from the Vector-borne Disease Control Programme (VDCP), Bhutan. Malaria morbidity and mortality among local Bhutanese and foreign nationals were analysed. The cost of different control and preventive measures, and estimation of the average numbers of long-lasting insecticidal nests (LLINs) per person were calculated. - Findings There were 5,491 confirmed malaria cases from 2006 to 2014. By 2013, there was an average of one LLIN for every 1·51 individuals. The Global Fund was the main international donor accounting for > 80% of the total funds. The cost of procuring LLINs accounted for > 90% of the total cost of prevention measures. - Interpretation The malaria burden reduced significantly over the study period with high coverage of LLINs in Bhutan. This foreseeable challenges that require national attention to maintain malaria-free status after elimination are importation of malaria, particularly from India; continued protection of the population in endemic districts through complete coverage with LLINs and IRS; and exploration of local funding modalities post elimination in the event there is a reduction in international funding.

Formal security analysis of the DNP3-secure authentication protocol

This thesis evaluates the security of Supervisory Control and Data Acquisition (SCADA) systems, which are one of the key foundations of many critical infrastructures. Specifically, it examines one of the standardised SCADA protocols called the Distributed Network Protocol Version 3, which attempts to provide a security mechanism to ensure that messages transmitted between devices, are adequately secured from rogue applications. To achieve this, the thesis applies formal methods from theoretical computer science to formally analyse the correctness of the protocol.

Singular value decomposition based computationally efficient algorithm for rapid dynamic near-infrared diffuse optical tomography

Purpose: A computationally efficient algorithm (linear iterative type) based on singular value decomposition (SVD) of the Jacobian has been developed that can be used in rapid dynamic near-infrared (NIR) diffuse optical tomography. Methods: Numerical and experimental studies have been conducted to prove the computational efficacy of this SVD-based algorithm over conventional optical image reconstruction algorithms. Results: These studies indicate that the performance of linear iterative algorithms in terms of contrast recovery (quantitation of optical images) is better compared to nonlinear iterative (conventional) algorithms, provided the initial guess is close to the actual solution. The nonlinear algorithms can provide better quality images compared to the linear iterative type algorithms. Moreover, the analytical and numerical equivalence of the SVD-based algorithm to linear iterative algorithms was also established as a part of this work. It is also demonstrated that the SVD-based image reconstruction typically requires O(NN2) operations per iteration, as contrasted with linear and nonlinear iterative methods that, respectively, requir O(NN3) and O(NN6) operations, with ``NN'' being the number of unknown parameters in the optical image reconstruction procedure. Conclusions: This SVD-based computationally efficient algorithm can make the integration of image reconstruction procedure with the data acquisition feasible, in turn making the rapid dynamic NIR tomography viable in the clinic to continuously monitor hemodynamic changes in the tissue pathophysiology.

Application of artificial intelligence for the assessment of the status of power transformers

The Dissolved Gas Analysis (DGA) a non destructive test procedure, has been in vogue for a long time now, for assessing the status of power and related transformers in service. An early indication of likely internal faults that may exist in Transformers has been seen to be revealed, to a reasonable degree of accuracy by the DGA. The data acquisition and subsequent analysis needs an expert in the concerned area to accurately assess the condition of the equipment. Since the presence of the expert is not always guaranteed, it is incumbent on the part of the power utilities to requisition a well planned and reliable artificial expert system to replace, at least in part, an expert. This paper presents the application of Ordered Ant Mner (OAM) classifier for the prediction of involved fault. Secondly, the paper also attempts to estimate the remaining life of the power transformer as an extension to the elapsed life estimation method suggested in the literature.

Disallowed Ramachandran Conformations of Amino Acid Residues in Protein Structures

An analysis of the nature and distribution of disallowed Ramachandran conformations of amino acid residues observed in high resolution protein crystal structures has been carried out. A data set consisting of 110 high resolution, non-homologous, protein crystal structures from the Brookhaven Protein Data Bank was examined. The data set consisted of a total of 18,708 non-Gly residues, which were characterized on the basis of their backbone dihedral angles (φ, ψ). Residues falling outside the defined “broad allowed limits” on the Ramachandran map were chosen and the reportedB-factor value of the α-carbon atom was used to further select well defined disallowed conformations. The conformations of the selected 66 disallowed residues clustered in distinct regions of the Ramachandran map indicating that specific φ, ψ angle distortions are preferred under compulsions imposed by local constraints. The distribution of various amino acid residues in the disallowed residue data set showed a predominance of small polar/charged residues, with bulky hydrophobic residues being infrequent. As a further check, for all the 66 cases non-hydrogen van der Waals short contacts in the protein structures were evaluated and compared with the ideal “Ala-dipeptide” constructed using disallowed dihedral angle (φ, ψ) values. The analysis reveals that short contacts are eliminated in most cases by local distortions of bond angles. An analysis of the conformation of the identified disallowed residues in related protein structures reveals instances of conservation of unusual stereochemistry.

Machine recognition of online handwritten Devanagari characters

In this paper, we describe a system for the automatic recognition of isolated handwritten Devanagari characters obtained by linearizing consonant conjuncts. Owing to the large number of characters and resulting demands on data acquisition, we use structural recognition techniques to reduce some characters to others. The residual characters are then classified using the subspace method. Finally the results of structural recognition and feature-based matching are mapped to give final output. The proposed system Ifs evaluated for the writer dependent scenario.

Evolution of the Neckeraceae (Bryophyta): resolving the backbone phylogeny

Earlier phylogenetic studies, including species belonging to the Neckeraceae, have indicated that this pleurocarpous moss family shares a strongly supported sister group relationship with the Lembophyllaceae, but the family delimitation of the former needs adjustment. To test the monophyly of the Neckeraceae, as well as to redefine the family circumscription and to pinpoint its phylogenetic position in a larger context, a phylogenetic study based on molecular data was carried out. Sequence data were compiled, combining data from all three genomes: nuclear ITS1 and 2, plastid trnS-rps4-trnT-trnL-trnF and rpl16, and mitochondrial nad5 intron. The Neckeraceae have sometimes been divided into the two families, Neckeraceae and Thamnobryaceae, a division rejected here. Both parsimony and Bayesian analyses of molecular data revealed that the family concept of the Neckeraceae needs several further adjustments, such as the exclusion of some individual species and smaller genera as well as the inclusion of the Leptodontaceae. Within the family three well-supported clades (A, B and C) can be distinguished. Members of clade A are mainly non-Asiatic and nontropical. Most species have a weak costa and immersed capsules with reduced peristomes (mainly Neckera spp.) and the teeth at the leaf margins are usually unicellular. Clade B members are also mainly non-Asiatic. They are typically fairly robust, distinctly stipilate, having a single, at least relatively strong costa, long setae (capsules exserted), and the peristomes are well developed or only somewhat reduced. Members of clade C are essentially Asiatic and tropical. The species of this clade usually have a strong costa and a long seta, the seta often being mammillose in its upper part. The peristome types in this clade are mixed, since both reduced and unreduced types are found. Several neckeraceous genera that were recognised on a morphological basis are polyphyletic (e.g. Neckera, Homalia, Thamnobryum, Porotrichum). Ancestral state reconstructions revealed that currently used diagnostic traits, such as the leaf asymmetry and costa strength are highly homoplastic. Similarly, the reconstructions revealed that the 'reduced' sporophyte features have evolved independently in each of the three clades.

A Method for Comparing Scholarly Journals as Service Providers to Authors

When authors of scholarly articles decide where to submit their manuscripts for peer review and eventual publication, they often base their choice of journals on very incomplete information abouthow well the journals serve the authors’ purposes of informing about their research and advancing their academic careers. The purpose of this study was to develop and test a new method for benchmarking scientific journals, providing more information to prospective authors. The method estimates a number of journal parameters, including readership, scientific prestige, time from submission to publication, acceptance rate and service provided by the journal during the review and publication process. Data directly obtainable from the web, data that can be calculated from such data, data obtained from publishers and editors, and data obtained using surveys with authors are used in the method, which has been tested on three different sets of journals, each from a different discipline. We found a number of problems with the different data acquisition methods, which limit the extent to which the method can be used. Publishers and editors are reluctant to disclose important information they have at hand (i.e. journal circulation, web downloads, acceptance rate). The calculation of some important parameters (for instance average time from submission to publication, regional spread of authorship) can be done but requires quite a lot of work. It can be difficult to get reasonable response rates to surveys with authors. All in all we believe that the method we propose, taking a “service to authors” perspective as a basis for benchmarking scientific journals, is useful and can provide information that is valuable to prospective authors in selected scientific disciplines.

A pulsed field gradient spin echo NMR spectrometer for diffusion coefficient measurements

A pulsed field gradient spin echo NMR spectrometer has been assembled by interfacing a programmable pulse generator and a data acquisition system designed and fabricated in our laboratory with other imported units. Calibration results of the magnetic field gradients are presented.

Photoemission study of the high-Tc superconductor Bi1.8Pb0.4Sr2Ca2.2Cu3O10

Ultraviolet and X-ray photoemission spectroscopic (UPS and XPS) studies to characterize the electronic structure of bismuth cuprate superconductor with nominal composition of Bi1.8Pb0.4Sr2Ca2.2Cu3O10 have been carried out. The data clearly shows the metallic emission at the Fermi level (EF). The shoulder (-1.2 eV) near the EF is attributed to the Cu-O derived states. Cu satellite structures observed both in the UPS and XPS show the strongly correlated nature of the Cu 3d electrons. Core level shifts indicate that 3+ and 4+ are the main oxidation of Bi and Pb, respectively. The Pb core lines show two components indicating their inequivalent sites. Core level O 1s spectrum is deconvoluted to show the presence of structurally non-equivalent oxygen sites.

Resistivity imaging of a reconfigurable phantom with circular inhomogeneities in 2D-electrical impedance tomography

Resistivity imaging of a reconfigurable phantom with circular inhomogeneities is studied with a simple instrumentation and data acquisition system for Electrical Impedance Tomography. The reconfigurable phantom is developed with stainless steel electrodes and a sinusoidal current of constant amplitude is injected to the phantom boundary using opposite current injection protocol. Nylon and polypropylene cylinders with different cross sectional areas are kept inside the phantom and the boundary potential data are collected. The instrumentation and the data acquisition system with a DIP switch-based multiplexer board are used to inject a constant current of desired amplitude and frequency. Voltage data for the first eight current patterns (128 voltage data) are found to be sufficient to reconstruct the inhomogeneities and hence the acquisition time is reduced. Resistivity images are reconstructed from the boundary data for different inhomogeneity positions using EIDORS-2D. The results show that the shape and resistivity of the inhomogeneity as well as the background resistivity are successfully reconstructed from the potential data for single or double inhomogeneity phantoms. The resistivity images obtained from the single and double inhomogeneity phantom clearly indicate the inhomogeneity as the high resistive material. Contrast to noise ratio (CNR) and contrast recovery (CR) of the reconstructed images are found high for the inhomogeneities near all the electrodes arbitrarily chosen for the entire study. (C) 2010 Elsevier Ltd. All rights reserved.

A Real-time clustering system for spatio-temporal signals from network of neurons

Over past few years, the studies of cultured neuronal networks have opened up avenues for understanding the ion channels, receptor molecules, and synaptic plasticity that may form the basis of learning and memory. The hippocampal neurons from rats are dissociated and cultured on a surface containing a grid of 64 electrodes. The signals from these 64 electrodes are acquired using a fast data acquisition system MED64 (Alpha MED Sciences, Japan) at a sampling rate of 20 K samples with a precision of 16-bits per sample. A few minutes of acquired data runs in to a few hundreds of Mega Bytes. The data processing for the neural analysis is highly compute-intensive because the volume of data is huge. The major processing requirements are noise removal, pattern recovery, pattern matching, clustering and so on. In order to interface a neuronal colony to a physical world, these computations need to be performed in real-time. A single processor such as a desk top computer may not be adequate to meet this computational requirements. Parallel computing is a method used to satisfy the real-time computational requirements of a neuronal system that interacts with an external world while increasing the flexibility and scalability of the application. In this work, we developed a parallel neuronal system using a multi-node Digital Signal processing system. With 8 processors, the system is able to compute and map incoming signals segmented over a period of 200 ms in to an action in a trained cluster system in real time.