Ligand design for molecule-based magnetic and/or conducting materials

Work in the area of molecule-based magnetic and/or conducting materials is presented in two projects. The first project describes the use of 4,4’-bipyridine as a scaffold for the preparation of a new family of tetracarboxamide ligands. Four new ligands I-III have been prepared and characterized and the coordination chemistry of these ligands is presented. This project was then extended to exploit 4,4’-bipyridine as a covalent linker between two N3O2 macrocyles. In this respect, three dimeric macrocycles have been prepared IV-VI. Substitution of the labile axial ligands of the Co(II) complex IV by [Fe(CN)6]4- afforded the self-assembly of the 1-D polymeric chain {[Co(N3O2)H2O]2Fe(CN)6}n•3H2O that has been structurally and magnetically characterized. Magnetic studies on the Fe(II) complexes V and VI indicate that they undergo incomplete spin crossover transitions in the solid state. Strategies for the preparation of chiral spin crossover N3O2 macrocycles are discussed and the synthesis of the novel chiral Fe(II) macrocyclic complex VII is reported. Magnetic susceptibility and Mössbauer studies reveal that this complex undergoes a gradual spin crossover in the solid state with no thermal hysteresis. Variable temperature X-ray diffraction studies on single crystals of VII reveal interesting structural changes in the coordination geometry of the macrocycle accompanying its SCO transition. The second project reports the synthesis and characterization of a new family of tetrathiafulvalene derivatives VIII – XII, where a heterocyclic chelating ligand is appended to a TTF donor via an imine linker. The coordination chemistries of these ligands with M(hfac)2.H2O (M( = Co, Ni, Mn, Cu) have been explored and the structural and magnetic properties of these complexes are described.

Heuristics for the Critical Node Detection Problem in Large Complex Networks

Complex networks have recently attracted a significant amount of research attention due to their ability to model real world phenomena. One important problem often encountered is to limit diffusive processes spread over the network, for example mitigating pandemic disease or computer virus spread. A number of problem formulations have been proposed that aim to solve such problems based on desired network characteristics, such as maintaining the largest network component after node removal. The recently formulated critical node detection problem aims to remove a small subset of vertices from the network such that the residual network has minimum pairwise connectivity. Unfortunately, the problem is NP-hard and also the number of constraints is cubic in number of vertices, making very large scale problems impossible to solve with traditional mathematical programming techniques. Even many approximation algorithm strategies such as dynamic programming, evolutionary algorithms, etc. all are unusable for networks that contain thousands to millions of vertices. A computationally efficient and simple approach is required in such circumstances, but none currently exist. In this thesis, such an algorithm is proposed. The methodology is based on a depth-first search traversal of the network, and a specially designed ranking function that considers information local to each vertex. Due to the variety of network structures, a number of characteristics must be taken into consideration and combined into a single rank that measures the utility of removing each vertex. Since removing a vertex in sequential fashion impacts the network structure, an efficient post-processing algorithm is also proposed to quickly re-rank vertices. Experiments on a range of common complex network models with varying number of vertices are considered, in addition to real world networks. The proposed algorithm, DFSH, is shown to be highly competitive and often outperforms existing strategies such as Google PageRank for minimizing pairwise connectivity.

Potential Urinary miRNA Biomarker Candidates for the Accurate Detection of Prostate Cancer among Benign Prostatic Hyperplasia Patients

MicroRNAs (miRNAs) are a class of short (similar to 22nt), single stranded RNA molecules that function as post-transcriptional regulators of gene expression. MiRNAs can regulate a variety of important biological pathways, including: cellular proliferation, differentiation and apoptosis. Profiling of miRNA expression patterns was shown to be more useful than the equivalent mRNA profiles for characterizing poorly differentiated tumours. As such, miRNA expression "signatures" are expected to offer serious potential for diagnosing and prognosing cancers of any provenance. The aim of this study was to investigate the potential of using deregulation of urinary miRNAs in order to detect Prostate Cancer (PCa) among Benign Prostatic Hyperplasia (BPH). To identify the miRNA signatures specific for PCa, miRNA expression profiling of 8 PCa patients, 12 BPH patients and 10 healthy males was carried out using whole genome expression profiling. Differential expression of two individual miRNAs between healthy males and BPH patients was detected and found to possibly target genes related to PCa development and progression. The sensitivity and specificity of miR-1825 for detecting PCa among BPH individuals was found to be 60% and 69%, respectively. Whereas, the sensitivity and specificity of miR-484 were 80% and 19%, respectively. Additionally, the sensitivity and specificity for miR-1825/484 in tandem were 45% and 75%, respectively. The proposed PCa miRNA signatures may therefore be of great value for the accurate diagnosis of PCa and BPH. This exploratory study has identified several possible targets that merit further investigation towards the development and validation of diagnostically useful, non-invasive, urine-based tests that might not only help diagnose PCa but also possibly help differentiate it from BPH.

FPGA-based object detection using classification circuits

Dans l'apprentissage machine, la classification est le processus d’assigner une nouvelle observation à une certaine catégorie. Les classifieurs qui mettent en œuvre des algorithmes de classification ont été largement étudié au cours des dernières décennies. Les classifieurs traditionnels sont basés sur des algorithmes tels que le SVM et les réseaux de neurones, et sont généralement exécutés par des logiciels sur CPUs qui fait que le système souffre d’un manque de performance et d’une forte consommation d'énergie. Bien que les GPUs puissent être utilisés pour accélérer le calcul de certains classifieurs, leur grande consommation de puissance empêche la technologie d'être mise en œuvre sur des appareils portables tels que les systèmes embarqués. Pour rendre le système de classification plus léger, les classifieurs devraient être capable de fonctionner sur un système matériel plus compact au lieu d'un groupe de CPUs ou GPUs, et les classifieurs eux-mêmes devraient être optimisés pour ce matériel. Dans ce mémoire, nous explorons la mise en œuvre d'un classifieur novateur sur une plate-forme matérielle à base de FPGA. Le classifieur, conçu par Alain Tapp (Université de Montréal), est basé sur une grande quantité de tables de recherche qui forment des circuits arborescents qui effectuent les tâches de classification. Le FPGA semble être un élément fait sur mesure pour mettre en œuvre ce classifieur avec ses riches ressources de tables de recherche et l'architecture à parallélisme élevé. Notre travail montre que les FPGAs peuvent implémenter plusieurs classifieurs et faire les classification sur des images haute définition à une vitesse très élevée.

Anisotropy in elastic properties of lithium sodium sulphate hexahydrate single crystal—An ultrasonic study

The double sulfate family (ABSO4), where A and B are alkali metal cations, is the object of great interest owing to the complexity and richness of its sequence of phase transition induced by temperature variation. A new sulfate salt characterized by the presence of water molecule in the unit cell with the chemical formula, Li2Na3(SO4)2⋅6H2O (LSSW), was obtained. The ultrasonic velocity measurement was done with pulse echo overlap technique [PEO]. All the six second order elastic stiffness constants, C11 = C22, C33, C44 = C55, C12, C14 and C13 = C23 are reported for the first time. The anisotropy in the elastic properties of the crystal are well explained by the pictorial representation of the polar plots of phase velocity, slowness, Young’s modulus and linear compressibility in a–b and a–c planes.

Use of mirage effect for the detection of phase transitions in liquid crystals

he phenomenon of single beam mirage effect, otherwise known as photothermal deflection (PTD) effect using a He–Ne laser beam has been employed to detect phase transitions in some liquid crystals. It has been observed that anomalous changes in amplitude occur in the PTD signal level near the transition temperature. The experimental details and the results of measurements made in liquid crystals E8, M21 and M24 are given in this paper.

Photoacoustic detection of two photon absorption in formaldehyde using pulsed dye laser

Absorption spectra of formaldehyde molecule in the gas phase have been recorded using photoacoustic (PA) technique with pulsed dye laser at various power levels. The spectral profiles at higher power levels are found to be different from that obtained at lower laser powers. Two photon absorption (TPA) is found to be responsible for the photoacoustic signal at higher laser power while the absorption at lower laser power level is attributed to one photon absorption (OPA) process. Probable assignments for the different transitions are given in this paper.

Design and development of an LED based fiber optic evanescent wave sensor for simultaneous detection of chromium and nitrite traces in water

The design and development of a cost-effective, simple, sensitive and portable LED based fiber optic evanescent wave sensor for simultaneously detecting trace amounts of chromium and nitrite in water are presented. In order to obtain the desired performance, the middle portions of two multimode plastic clad silica fibers are unclad and are used as the sensing elements in the two arms of the sensor. Each of the sensor arms is sourced by separate super bright green LEDs, which are modulated in a time-sharing manner and a single photo detector is employed for detecting these light signals. The performance and characteristics of this system clearly establish the usefulness of the technique for detecting very low concentrations of the dissolved contaminants.

Fault Tolerant Error Coding and Detection using Reversible Gates

In recent years, reversible logic has emerged as one of the most important approaches for power optimization with its application in low power CMOS, quantum computing and nanotechnology. Low power circuits implemented using reversible logic that provides single error correction – double error detection (SEC-DED) is proposed in this paper. The design is done using a new 4 x 4 reversible gate called ‘HCG’ for implementing hamming error coding and detection circuits. A parity preserving HCG (PPHCG) that preserves the input parity at the output bits is used for achieving fault tolerance for the hamming error coding and detection circuits.

Asymptotic model for shape resonance control of diatomics by intense non-resonant light: universality in the single-channel approximation

Non-resonant light interacting with diatomics via the polarizability anisotropy couples different rotational states and may lead to strong hybridization of the motion. The modification of shape resonances and low-energy scattering states due to this interaction can be fully captured by an asymptotic model, based on the long-range properties of the scattering (Crubellier et al 2015 New J. Phys. 17 045020). Remarkably, the properties of the field-dressed shape resonances in this asymptotic multi-channel description are found to be approximately linear in the field intensity up to fairly large intensity. This suggests a perturbative single-channel approach to be sufficient to study the control of such resonances by the non-resonant field. The multi-channel results furthermore indicate the dependence on field intensity to present, at least approximately, universal characteristics. Here we combine the nodal line technique to solve the asymptotic Schrödinger equation with perturbation theory. Comparing our single channel results to those obtained with the full interaction potential, we find nodal lines depending only on the field-free scattering length of the diatom to yield an approximate but universal description of the field-dressed molecule, confirming universal behavior.

Rotation Invariant Real-time Face Detection and Recognition System

In this report, a face recognition system that is capable of detecting and recognizing frontal and rotated faces was developed. Two face recognition methods focusing on the aspect of pose invariance are presented and evaluated - the whole face approach and the component-based approach. The main challenge of this project is to develop a system that is able to identify faces under different viewing angles in realtime. The development of such a system will enhance the capability and robustness of current face recognition technology. The whole-face approach recognizes faces by classifying a single feature vector consisting of the gray values of the whole face image. The component-based approach first locates the facial components and extracts them. These components are normalized and combined into a single feature vector for classification. The Support Vector Machine (SVM) is used as the classifier for both approaches. Extensive tests with respect to the robustness against pose changes are performed on a database that includes faces rotated up to about 40 degrees in depth. The component-based approach clearly outperforms the whole-face approach on all tests. Although this approach isproven to be more reliable, it is still too slow for real-time applications. That is the reason why a real-time face recognition system using the whole-face approach is implemented to recognize people in color video sequences.

Face Detection in Still Gray Images

We present a trainable system for detecting frontal and near-frontal views of faces in still gray images using Support Vector Machines (SVMs). We first consider the problem of detecting the whole face pattern by a single SVM classifer. In this context we compare different types of image features, present and evaluate a new method for reducing the number of features and discuss practical issues concerning the parameterization of SVMs and the selection of training data. The second part of the paper describes a component-based method for face detection consisting of a two-level hierarchy of SVM classifers. On the first level, component classifers independently detect components of a face, such as the eyes, the nose, and the mouth. On the second level, a single classifer checks if the geometrical configuration of the detected components in the image matches a geometrical model of a face.

Contextual Priming for Object Detection

There is general consensus that context can be a rich source of information about an object's identity, location and scale. In fact, the structure of many real-world scenes is governed by strong configurational rules akin to those that apply to a single object. Here we introduce a simple probabilistic framework for modeling the relationship between context and object properties based on the correlation between the statistics of low-level features across the entire scene and the objects that it contains. The resulting scheme serves as an effective procedure for object priming, context driven focus of attention and automatic scale-selection on real-world scenes.

Prevalencia de obesidad y factores de riesgo cardiovascular en estudiantes de ciencias de la salud - universidad del Quindío - 2013

ANTECEDENTES: En Colombia, reportes del año 2010 de la Encuesta Nacional de la Situación en Nutrición ENSIN 2010(2), muestran uno de cada dos colombianos, presentan un índice de masa corporal mayor al esperado (3) METODO: El presente estudio de corte transversal, determino la prevalencia de obesidad y otros factores de riesgo cardiovascular en una población de estudiantes de Ciencias de la Salud de una Universidad regional en el primer periodo académico del año 2013. El tamaño de muestra fue n=113 sujetos que corresponden 60,5% a la carrera de medicina y 39,95% a enfermería. Con el fin de conocer su comportamiento con respecto a hábitos y estilos de vida específicos como el consumo de alcohol, el consumo de tabaco y el sedentarismo, así como su asociación a eventos inflamatorios relacionados con la fisiopatología de los procesos de salud asociados al peso, por medio de instrumentos de medición clínica, antropométrica y sérica, determino un modelo estadístico propicio para entender el comportamiento de la obesidad y la enfermedad Cardiovascular RESULTADOS: La prevalencia estimada de sobrepeso y obesidad por Índice de Masa Corporal (IMC), fue del 27,7% (IC 95%: 19.9%,37.2%); por el perímetro abdominal (OBPABD) se encontró una prevalencia estimada del 27,4% (IC 95%: 19,9% – 36,4%), y la prevalencia con el Índice Cintura Cadera (OBICC) fue de 3,5% (IC 95%:1,3% – 9,3%). CONCLUSIONES: La presencia de hábitos no saludables y la presencia de sobrepeso y obesidad se considera que es necesario en primera instancia una valoración general de estado nutricional de los universitarios de las diferentes facultados y plantear estrategias preventivas ya que la literatura documenta los efectos de los hábitos no saludables sino además documenta los efectos de la prevención de la misma ya que en si se ha encontrado asociación para enfermedades cardiovasculares. Se propone que para obtener mayor información del comportamiento de los factores de riesgo cardiovasculares se deberían realizar estudios retrospectivos en el que intervengan las demás carreras de la universidad y poder evaluar la totalidad de población universitaria

Single and multiple addition to C60. A computational chemistry study

Des del seu descobriment, a la molècula C60 se li coneixen una varietat de derivats segons el tipus de funcionalització amb propietats fisicoquímiques específiques de gran interès científic. Una sel·lecció de derivats corresponents a addicions simple o múltiple al C60 s'ha considerat en aquest treball d'investigació. L'estudi a nivell de química computacional de diversos tipus d'addició al C60 s'han portat a terme per tal de poder donar resposta a aspectes que experimentalment no s'entenen o són poc clars. Els sistemes estudiats en referència a l'addició simple al C60 han estat en primer lloc els monoiminoful·lerens, C60NR, (de les dues vies proposades per la seva síntesi, anàlisis cinètic i termodinàmic han ajudat a explicar els mecanismes de formació i justificar l'addició a enllaços tipus [5,6]), i en segon lloc els metanoful·lerens i els hidroful·lerens substituits, C60CHR i C60HR, (raons geomètriques, electròniques, energètiques i magnètiques justifiquen el diferent caràcter àcid ente ambdós derivats tenint en compte una sèrie de substituents R amb diferent caràcter electrònic donor/acceptor). Els fluoroful·lerens, C60Fn, i els epoxid ful·lerens, C60On, (anàlisi sistemàtic dels seus patrons d'addició en base a poder justificar la força que els governa han aportat dades complementàries a les poques que existeixen experimentalment al respecte).