On the Optimality of Finite Constellations from Algebraic Lattices

A construction technique of finite point constellations in n-dimensional spaces from ideals in rings of algebraic integers is described. An algorithm is presented to find constellations with minimum average energy from a given lattice. For comparison, a numerical table of lattice constellations and group codes is computed for spaces of dimension two, three, and four. © 2001.

Relaxation Labeling with Learning Automata

Relaxation labeling processes are a class of mechanisms that solve the problem of assigning labels to objects in a manner that is consistent with respect to some domain-specific constraints. We reformulate this using the model of a team of learning automata interacting with an environment or a high-level critic that gives noisy responses as to the consistency of a tentative labeling selected by the automata. This results in an iterative linear algorithm that is itself probabilistic. Using an explicit definition of consistency we give a complete analysis of this probabilistic relaxation process using weak convergence results for stochastic algorithms. Our model can accommodate a range of uncertainties in the compatibility functions. We prove a local convergence result and show that the point of convergence depends both on the initial labeling and the constraints. The algorithm is implementable in a highly parallel fashion.

Development of functionalized terbium fluorescent nanoparticles for antibody labeling and time-resolved fluoroimmunoassay application

Silica-based functionalized terbium fluorescent nanoparticles were prepared, characterized and developed as a fluorescence probe for antibody labeling and time-resolved fluoroimmunoassay. The nanoparticles were prepared in a water-in-oil (W/O) microemulsion containing a strongly fluorescent Tb3+ chelate. N,N.N-1,N-1-12,6-bis(3'-aminomethyl-1'-pyrazolyl)phenylpyridine] tetrakis(acetate)-Tb3+ (BPTA-Tb3+), Triton X-100, octanol, and cyclohexane by controlling copolymerization of tetraethyl orthosilicate (TEOS) and 3-[2-(2- aminoethylamino)-ethylamino]propyl-trimethoxysilane (AEPS) with ammonia water. The characterizations by transmission electron microscopy and fluorometric quantum methods show that the nanoparticles are spherical and uniform in size, 45 +/- 3 nm in diameter, strongly fluorescent with fluorescence yield of 10% and a long fluorescence lifetime of 2.0 ms. The amino groups directly introduced to the nanoparticle's surface by using AEPS in the preparation made the surface modification and bioconjugation of the nanoparticles easier. The nanoparticle-labeled anti-human alpha-fetoprotein antibody was prepared and used for time-resolved fluoroimmunoassay of (x-fetoprotein (AFP) in human serum samples. The assay response is linear from 0.10 ng ml(-1) to about 100 ng ml(-1) with the detection limit of 0.10 ng ml(-1). The coefficient variations (CVs) of the method are less than 9.0%. and the recoveries are in the range of 84-98% for human serum sample measurements. (C) 2004 Elsevier B.V. All rights reserved.

Determination of amines using 2-(11H-benzo[a]carbazol-11-yl) ethyl chloroformate (BCEC-Cl) as labeling reagent by HPLC with fluorescence detection and identification with APCI/MS

A pre-column derivatization method for the sensitive determination of amines using a labeling reagent 2-(11H-benzo[a]-carbazol-11-yl) ethyl chloroformate (BCEC-Cl) followed by high-performance, liquid chromatography with fluorescence detection has been developed. Identification of derivatives was carried out by LC/APCI/MS in positive-ion mode. The chromophore of 1,2-benzo-3,4-dihydrocarbazole-9-ethyl chloroformate (BCEOC-Cl) reagent was replaced by 2-(11H-benzo[a]-carbazol-11-yl) ethyl functional group, which resulted in a sensitive fluorescence derivatizing reagent BCEC-Cl. BCEC-Cl could easily and quickly label amines. Derivatives were stable enough to be efficiently analyzed by HPLC and showed an intense protonated molecular ion corresponding m/z [M+ H](+) under APCI/MS in positive-ion mode. The collision-induced dissociation of the protonated molecular ion formed characteristic fragment ions at m/z 261.8 and m/z 243.8 corresponding to the cleavages of CH2O-CO and CH2-OCO bonds. Studies on derivatization demonstrated excellent derivative yields over the pH 9.0-10.0. Maximal yields close to 100% were observed with three- to four-fold molar reagent excess. In addition, the detection responses for BCEC-derivatives were compared to those obtained using 1,2-benzo-3,4-dihydrocarbazole-9-ethyl chloroformate (BCEOC-Cl) and 9-fluorenyl methylchloroformate, (FMOC-Cl) as labeling reagents. The ratios I-BCEC/I-BCEOC = 1.94-2.17 and I-BCEC/I-FMOC = 1.04-2.19 for fluorescent (FL) responses (here, I was relative fluorescence intensity). Separation of the derivatized amines had been optimized on reversed-phase Eclipse XDB-C-8 column. Detection limits calculated from 0.50 pmol injection, at a signal-to-noise ratio of 3, were 1.77-14.4 fmol. The relative standard deviations for within-day determination (n = 11) were 1.84-2.89% for the tested amines. The mean intra- and inter-assay precision for all amines levels were < 3.64% and 2.52%, respectively. The mean recoveries ranged from 96.6% to 107.1% with their standard deviations in the range of 0.8-2.7. Excellent linear responses were observed with coefficients of > 0.9996. (C) 2006 Elsevier B.V. All rights reserved.

Supramolecular approaches to organized luminescent nanostructures for sensing, labeling and imaging applications

The common thread of this thesis is the will of investigating properties and behavior of assemblies. Groups of objects display peculiar properties, which can be very far from the simple sum of respective components’ properties. This is truer, the smaller is inter-objects distance, i.e. the higher is their density, and the smaller is the container size. “Confinement” is in fact a key concept in many topics explored and here reported. It can be conceived as a spatial limitation, that yet gives origin to unexpected processes and phenomena based on inter-objects communication. Such phenomena eventually result in “non-linear properties”, responsible for the low predictability of large assemblies. Chapter 1 provides two insights on surface chemistry, namely (i) on a supramolecular assembly based on orthogonal forces, and (ii) on selective and sensitive fluorescent sensing in thin polymeric film. In chapters 2 to 4 confinement of molecules plays a major role. Most of the work focuses on FRET within core-shell nanoparticles, investigated both through a simulation model and through experiments. Exciting results of great applicative interest are drawn, such as a method of tuning emission wavelength at constant excitation, and a way of overcoming self-quenching processes by setting up a competitive deactivation channel. We envisage applications of these materials as labels for multiplexing analysis, and in all fields of fluorescence imaging, where brightness coupled with biocompatibility and water solubility is required. Adducts of nanoparticles and molecular photoswitches are investigated in the context of superresolution techniques for fluorescence microscopy. In chapter 5 a method is proposed to prepare a library of functionalized Pluronic F127, which gives access to a twofold “smart” nanomaterial, namely both (i)luminescent and (ii)surface-functionalized SCSSNPs. Focus shifts in chapter 6 to confinement effects in an upper size scale. Moving from nanometers to micrometers, we investigate the interplay between microparticles flowing in microchannels where a constriction affects at very long ranges structure and dynamics of the colloidal paste.

Labeling the human skeleton with 41Ca to assess changes in bone calcium metabolism

Bone research is limited by the methods available for detecting changes in bone metabolism. While dual X-ray absorptiometry is rather insensitive, biochemical markers are subject to significant intra-individual variation. In the study presented here, we evaluated the isotopic labeling of bone using 41Ca, a long-lived radiotracer, as an alternative approach. After successful labeling of the skeleton, changes in the systematics of urinary 41Ca excretion are expected to directly reflect changes in bone Ca metabolism. A minute amount of 41Ca (100 nCi) was administered orally to 22 postmenopausal women. Kinetics of tracer excretion were assessed by monitoring changes in urinary 41Ca/40Ca isotope ratios up to 700 days post-dosing using accelerator mass spectrometry and resonance ionization mass spectrometry. Isotopic labeling of the skeleton was evaluated by two different approaches: (i) urinary 41Ca data were fitted to an established function consisting of an exponential term and a power law term for each individual; (ii) 41Ca data were analyzed by population pharmacokinetic (NONMEM) analysis to identify a compartmental model that describes urinary 41Ca tracer kinetics. A linear three-compartment model with a central compartment and two sequential peripheral compartments was found to best fit the 41Ca data. Fits based on the use of the combined exponential/power law function describing urinary tracer excretion showed substantially higher deviations between predicted and measured values than fits based on the compartmental modeling approach. By establishing the urinary 41Ca excretion pattern using data points up to day 500 and extrapolating these curves up to day 700, it was found that the calculated 41Ca/40Ca isotope ratios in urine were significantly lower than the observed 41Ca/40Ca isotope ratios for both techniques. Compartmental analysis can overcome this limitation. By identifying relative changes in transfer rates between compartments in response to an intervention, inaccuracies in the underlying model cancel out. Changes in tracer distribution between compartments were modeled based on identified kinetic parameters. While changes in bone formation and resorption can, in principle, be assessed by monitoring urinary 41Ca excretion over the first few weeks post-dosing, assessment of an intervention effect is more reliable approximately 150 days post-dosing when excreted tracer originates mainly from bone.

Differential fluorescence labeling of cysteinyl clusters uncovers high tissue levels of thionein

The isolation of thionein (T) from tissues has not been reported heretofore. T contains 20 cysteinyl residues that react with 7-fluorobenz-2-oxa-1,3-diazole-4-sulfonamide to form fluorescent adducts. In metallothionein (MT) the cysteinyl residues, which are bound to zinc, do not react. However, they do react in the presence of a chelating agent such as EDTA. The resultant difference in chemical reactivity provides a means to measure T in the absence of EDTA, (MT + T) in its presence, and, of course, MT by difference. The 7-fluorobenz-2-oxa-1,3-diazole-4-sulfonamide derivative of T can be isolated from tissue homogenates by HPLC and quantified fluorimetrically with a detection limit in the femtomolar range and a linear response over 3 orders of magnitude. Analysis of liver, kidney, and brain of rats reveals almost as much T as MT. Moreover, in contrast to earlier views, MT in tissue extracts appears to be less stable than T. The existence of T in tissues under normal physiological conditions has important implications for its function both in zinc metabolism and the redox balance of the cell.

Labeling large scale social media data using budget-driven One-class SVM classification

The social media classification problems draw more and more attention in the past few years. With the rapid development of Internet and the popularity of computers, there is astronomical amount of information in the social network (social media platforms). The datasets are generally large scale and are often corrupted by noise. The presence of noise in training set has strong impact on the performance of supervised learning (classification) techniques. A budget-driven One-class SVM approach is presented in this thesis that is suitable for large scale social media data classification. Our approach is based on an existing online One-class SVM learning algorithm, referred as STOCS (Self-Tuning One-Class SVM) algorithm. To justify our choice, we first analyze the noise-resilient ability of STOCS using synthetic data. The experiments suggest that STOCS is more robust against label noise than several other existing approaches. Next, to handle big data classification problem for social media data, we introduce several budget driven features, which allow the algorithm to be trained within limited time and under limited memory requirement. Besides, the resulting algorithm can be easily adapted to changes in dynamic data with minimal computational cost. Compared with two state-of-the-art approaches, Lib-Linear and kNN, our approach is shown to be competitive with lower requirements of memory and time.

Components of learning and assessment in linear algebra

Linear algebra provides theory and technology that are the cornerstones of a range of cutting edge mathematical applications, from designing computer games to complex industrial problems, as well as more traditional applications in statistics and mathematical modelling. Once past introductions to matrices and vectors, the challenges of balancing theory, applications and computational work across mathematical and statistical topics and problems are considerable, particularly given the diversity of abilities and interests in typical cohorts. This paper considers two such cohorts in a second level linear algebra course in different years. The course objectives and materials were almost the same, but some changes were made in the assessment package. In addition to considering effects of these changes, the links with achievement in first year courses are analysed, together with achievement in a following computational mathematics course. Some results that may initially appear surprising provide insight into the components of student learning in linear algebra.