The spatial sign covariance matrix and its application for robust correlation estimation

8 pages, 2 figures, to be published in the conference proceedings of 11th international conference "Computer Data Analysis & Modeling 2016"

Circadian rhythms in Neurospora crassa: Lipid deficiencies restore robust rhythmicity to null frequency and white-collar mutants

The conidiation rhythm in the fungus Neurospora crassa is a model system for investigating the genetics of circadian clocks. Null mutants at the frq (frequency) locus (frq9 and frq10) make no functional frq gene products and are arrhythmic under standard conditions. The white-collar strains (wc-1 and wc-2) are insensitive to most effects of light, and are also arrhythmic. All three genes are proposed to be central components of the circadian oscillator. We have been investigating two mutants, cel (chain-elongation) and chol-1 (choline-requirer), which are defective in lipid synthesis and affect the period and temperature compensation of the rhythm. We have constructed the double mutant strains chol-1 frq9, chol-1 frq10, chol-1 wc-1, chol-1 wc-2, cel frq9, cel frq10, and cel wc-2. We find that these double mutant strains are robustly rhythmic when assayed under lipid-deficient conditions, indicating that free-running rhythmicity does not require the frq, wc-1, or wc-2 gene products. The rhythms in the double mutant strains are similar to the cel and chol-1 parents, except that they are less sensitive to light. This suggests that the frq, wc-1, and wc-2 gene products may be components of a pathway that normally supplies input to a core oscillator to transduce light signals and sustain rhythmicity. This pathway can be bypassed when lipid metabolism is altered.

Robust gut-specific gene expression in transgenic Aedes aegypti mosquitoes

Genetic modification of the vectorial capacity of mosquito vectors of human disease requires promoters capable of driving gene expression with appropriate tissue and stage specificity. We report on the characterization in transgenic Aedes aegypti of two mosquito gut-specific promoters. A 1.4-kb DNA fragment adjacent to the 5′ end of the coding region of the Ae. aegypti carboxypeptidase (AeCP) gene and a corresponding 3.4-kb DNA fragment at the 5′ end of the Anopheles gambiae carboxypeptidase (AgCP) gene were linked to a firefly luciferase reporter gene and introduced into the Ae. aegypti germ line by using Hermes and mariner (Mos1) transposons. Six independent transgenic lines were obtained with the AeCP construct and one with the AgCP construct. Luciferase mRNA and protein were abundantly expressed in the guts of transgenic mosquitoes in four of the six AeCP lines and in the AgCP line. Expression of the reporter gene was gut-specific and reached peak levels at about 24 h post-blood ingestion. The AeCP and AgCP promoters can be used to drive the expression of genes that hinder parasite development in the mosquito gut.

Sequence verification of human creatine kinase (43 kDa) isozymes by high-resolution tandem mass spectrometry.

Amino acid sequencing by recombinant DNA technology, although dramatically useful, is subject to base reading errors, is indirect, and is insensitive to posttranslational processing. Mass spectrometry techniques can provide molecular weight data from even relatively large proteins for such cDNA sequences and can serve as a check of an enzyme's purity and sequence integrity. Multiply-charged ions from electrospray ionization can be dissociated to yield structural information by tandem mass spectrometry, providing a second method for gaining additional confidence in primary sequence confirmation. Here, accurate (+/- 1 Da) molecular weight and molecular ion dissociation information for human muscle and brain creatine kinases has been obtained by electrospray ionization coupled with Fourier-transform mass spectrometry to help distinguish which of several published amino acid sequences for both enzymes are correct. The results herein are consistent with one published sequence for each isozyme, and the heterogeneity indicated by isoelectric focusing due to 1-Da deamidation changes. This approach appears generally useful for detailed sequence verification of recombinant proteins.

Voice-processing technologies--their application in telecommunications.

As the telecommunications industry evolves over the next decade to provide the products and services that people will desire, several key technologies will become commonplace. Two of these, automatic speech recognition and text-to-speech synthesis, will provide users with more freedom on when, where, and how they access information. While these technologies are currently in their infancy, their capabilities are rapidly increasing and their deployment in today's telephone network is expanding. The economic impact of just one application, the automation of operator services, is well over $100 million per year. Yet there still are many technical challenges that must be resolved before these technologies can be deployed ubiquitously in products and services throughout the worldwide telephone network. These challenges include: (i) High level of accuracy. The technology must be perceived by the user as highly accurate, robust, and reliable. (ii) Easy to use. Speech is only one of several possible input/output modalities for conveying information between a human and a machine, much like a computer terminal or Touch-Tone pad on a telephone. It is not the final product. Therefore, speech technologies must be hidden from the user. That is, the burden of using the technology must be on the technology itself. (iii) Quick prototyping and development of new products and services. The technology must support the creation of new products and services based on speech in an efficient and timely fashion. In this paper I present a vision of the voice-processing industry with a focus on the areas with the broadest base of user penetration: speech recognition, text-to-speech synthesis, natural language processing, and speaker recognition technologies. The current and future applications of these technologies in the telecommunications industry will be examined in terms of their strengths, limitations, and the degree to which user needs have been or have yet to be met. Although noteworthy gains have been made in areas with potentially small user bases and in the more mature speech-coding technologies, these subjects are outside the scope of this paper.

Toward the ultimate synthesis/recognition system.

This paper predicts speech synthesis, speech recognition, and speaker recognition technology for the year 2001, and it describes the most important research problems to be solved in order to arrive at these ultimate synthesis and recognition systems. The problems for speech synthesis include natural and intelligible voice production, prosody control based on meaning, capability of controlling synthesized voice quality and choosing individual speaking style, multilingual and multidialectal synthesis, choice of application-oriented speaking styles, capability of adding emotion, and synthesis from concepts. The problems for speech recognition include robust recognition against speech variations, adaptation/normalization to variations due to environmental conditions and speakers, automatic knowledge acquisition for acoustic and linguistic modeling, spontaneous speech recognition, naturalness and ease of human-machine interaction, and recognition of emotion. The problems for speaker recognition are similar to those for speech recognition. The research topics related to all these techniques include the use of articulatory and perceptual constraints and evaluation methods for measuring the quality of technology and systems.

Robust fitting of Zernike polynomials to noisy point clouds defined over connected domains of arbitrary shape

A new method for fitting a series of Zernike polynomials to point clouds defined over connected domains of arbitrary shape defined within the unit circle is presented in this work. The method is based on the application of machine learning fitting techniques by constructing an extended training set in order to ensure the smooth variation of local curvature over the whole domain. Therefore this technique is best suited for fitting points corresponding to ophthalmic lenses surfaces, particularly progressive power ones, in non-regular domains. We have tested our method by fitting numerical and real surfaces reaching an accuracy of 1 micron in elevation and 0.1 D in local curvature in agreement with the customary tolerances in the ophthalmic manufacturing industry.

Influence analysis of robust Wald-type tests

We consider a robust version of the classical Wald test statistics for testing simple and composite null hypotheses for general parametric models. These test statistics are based on the minimum density power divergence estimators instead of the maximum likelihood estimators. An extensive study of their robustness properties is given though the influence functions as well as the chi-square inflation factors. It is theoretically established that the level and power of these robust tests are stable against outliers, whereas the classical Wald test breaks down. Some numerical examples confirm the validity of the theoretical results.

Robust linear semi-infinite programming duality under uncertainty

In this paper, we propose a duality theory for semi-infinite linear programming problems under uncertainty in the constraint functions, the objective function, or both, within the framework of robust optimization. We present robust duality by establishing strong duality between the robust counterpart of an uncertain semi-infinite linear program and the optimistic counterpart of its uncertain Lagrangian dual. We show that robust duality holds whenever a robust moment cone is closed and convex. We then establish that the closed-convex robust moment cone condition in the case of constraint-wise uncertainty is in fact necessary and sufficient for robust duality. In other words, the robust moment cone is closed and convex if and only if robust duality holds for every linear objective function of the program. In the case of uncertain problems with affinely parameterized data uncertainty, we establish that robust duality is easily satisfied under a Slater type constraint qualification. Consequently, we derive robust forms of the Farkas lemma for systems of uncertain semi-infinite linear inequalities.

A robust and fast method for 6DoF motion estimation from generalized 3D data

Nowadays, there is an increasing number of robotic applications that need to act in real three-dimensional (3D) scenarios. In this paper we present a new mobile robotics orientated 3D registration method that improves previous Iterative Closest Points based solutions both in speed and accuracy. As an initial step, we perform a low cost computational method to obtain descriptions for 3D scenes planar surfaces. Then, from these descriptions we apply a force system in order to compute accurately and efficiently a six degrees of freedom egomotion. We describe the basis of our approach and demonstrate its validity with several experiments using different kinds of 3D sensors and different 3D real environments.

Robust Solutions of MultiObjective Linear Semi-Infinite Programs under Constraint Data Uncertainty

The multiobjective optimization model studied in this paper deals with simultaneous minimization of finitely many linear functions subject to an arbitrary number of uncertain linear constraints. We first provide a radius of robust feasibility guaranteeing the feasibility of the robust counterpart under affine data parametrization. We then establish dual characterizations of robust solutions of our model that are immunized against data uncertainty by way of characterizing corresponding solutions of robust counterpart of the model. Consequently, we present robust duality theorems relating the value of the robust model with the corresponding value of its dual problem.

Synthesis of Robust Hierarchical Silica Monoliths by Surface-Mediated Solution/Precipitation Reactions over Different Scales: Designing Capillary Microreactors for Environmental Applications

A synthetic procedure to prepare novel materials (surface-mediated fillings) based on robust hierarchical monoliths is reported. The methodology includes the deposition of a (micro- or mesoporous) silica thin film on the support followed by growth of a porous monolithic SiO2 structure. It has been demonstrated that this synthesis is viable for supports of different chemical nature with different inner diameters without shrinkage of the silica filling. The formation mechanism of the surface-mediated fillings is based on a solution/precipitation process and the anchoring of the silica filling to the deposited thin film. The interaction between the two SiO2 structures (monolith and thin film) depends on the porosity of the thin film and yields composite materials with different mechanical stability. By this procedure, capillary microreactors have been prepared and have been proved to be highly active and selective in the total and preferential oxidation of carbon monoxide (TOxCO and PrOxCO).

1,2-Functionalized Imidazoles as Palladium Ligands: An Efficient and Robust Catalytic System for the Fluorine-Free Hiyama Reaction

A variety of hydroxy- and amino-functionalized imidazoles were prepared from 1-methyl- and 1-(diethoxymethyl)imidazole by means of isoprene-mediated lithiation followed by reaction with an electrophile. These compounds in combination with palladium acetate were screened as catalyst systems for the Hiyama reaction under fluorine-free conditions using microwave irradiation. The systematic study of the catalytic system showed 1-methyl-2-aminoalkylimidazole derivative L1 to be the best ligand, which was employed under solvent-free conditions with a 1:2 Pd/ligand ratio and TBAB (20 mol-%) as additive. The study has revealed an interaction between the Pd/ligand ratio and the amount of TBAB. The established catalytic system presented a certain degree of robustness, and it has been successfully employed in the coupling of a range of aryl bromides and chlorides with different aryl siloxanes. Furthermore, both reagents were employed in an equimolecular amount, without an excess of organosilane.

Robust solutions to multi-objective linear programs with uncertain data

In this paper we examine multi-objective linear programming problems in the face of data uncertainty both in the objective function and the constraints. First, we derive a formula for the radius of robust feasibility guaranteeing constraint feasibility for all possible scenarios within a specified uncertainty set under affine data parametrization. We then present numerically tractable optimality conditions for minmax robust weakly efficient solutions, i.e., the weakly efficient solutions of the robust counterpart. We also consider highly robust weakly efficient solutions, i.e., robust feasible solutions which are weakly efficient for any possible instance of the objective matrix within a specified uncertainty set, providing lower bounds for the radius of highly robust efficiency guaranteeing the existence of this type of solutions under affine and rank-1 objective data uncertainty. Finally, we provide numerically tractable optimality conditions for highly robust weakly efficient solutions.