Brain dynamics sustaining rapid rule extraction from speech

Language acquisition is a complex process that requires the synergic involvement of different cognitive functions, which include extracting and storing the words of the language and their embedded rules for progressive acquisition of grammatical information. As has been shown in other fields that study learning processes, synchronization mechanisms between neuronal assemblies might have a key role during language learning. In particular, studying these dynamics may help uncover whether different oscillatory patterns sustain more item-based learning of words and rule-based learning from speech input. Therefore, we tracked the modulation of oscillatory neural activity during the initial exposure to an artificial language, which contained embedded rules. We analyzed both spectral power variations, as a measure of local neuronal ensemble synchronization, as well as phase coherence patterns, as an index of the long-range coordination of these local groups of neurons. Synchronized activity in the gamma band (2040 Hz), previously reported to be related to the engagement of selective attention, showed a clear dissociation of local power and phase coherence between distant regions. In this frequency range, local synchrony characterized the subjects who were focused on word identification and was accompanied by increased coherence in the theta band (48 Hz). Only those subjects who were able to learn the embedded rules showed increased gamma band phase coherence between frontal, temporal, and parietal regions.

Sensor Fusion of Proprioception, Force and Vision in Estimation and Robot

Sensor-based robot control allows manipulation in dynamic environments with uncertainties. Vision is a versatile low-cost sensory modality, but low sample rate, high sensor delay and uncertain measurements limit its usability, especially in strongly dynamic environments. Force is a complementary sensory modality allowing accurate measurements of local object shape when a tooltip is in contact with the object. In multimodal sensor fusion, several sensors measuring different modalities are combined to give a more accurate estimate of the environment. As force and vision are fundamentally different sensory modalities not sharing a common representation, combining the information from these sensors is not straightforward. In this thesis, methods for fusing proprioception, force and vision together are proposed. Making assumptions of object shape and modeling the uncertainties of the sensors, the measurements can be fused together in an extended Kalman filter. The fusion of force and visual measurements makes it possible to estimate the pose of a moving target with an end-effector mounted moving camera at high rate and accuracy. The proposed approach takes the latency of the vision system into account explicitly, to provide high sample rate estimates. The estimates also allow a smooth transition from vision-based motion control to force control. The velocity of the end-effector can be controlled by estimating the distance to the target by vision and determining the velocity profile giving rapid approach and minimal force overshoot. Experiments with a 5-degree-of-freedom parallel hydraulic manipulator and a 6-degree-of-freedom serial manipulator show that integration of several sensor modalities can increase the accuracy of the measurements significantly.

Development of a simple, rapid and validated spectrophotometric method for nitazoxanide in pharmaceutical formulations and comparison with HPLC

A rapid, economical, reproducible, and simple direct spectrophotometric method was developed and validated for the assay of nitazoxanide in pharmaceutical formulations. Nitazoxanide concentration was estimated in water at 345 nm and pH 4.5. The method was suitable and validated for specificity, linearity, precision, and accuracy. There was no interference of the excipients in the determination of the active pharmaceutical ingredient. The proposed method was successfully applied in the determination of nitazoxanide in coated tablets and in powders for oral suspension. This method was compared to a previously developed and validated method for liquid chromatography to the same drug. There was no significative difference between these methods for nitazoxanide quantitation.

Use of pyrosequencing to identify streptococci and to detect mutations causing antimicrobial resistance

Rapid identification and resistance determination of pathogens in clinical specimens is vital for accurate treatment and monitoring of infectious diseases. Antimicrobial drug resistance is increasing globally and healthcare settings are facing this cost-intensive and even life-threatening problem. The incidence of resistant pathogens in Finland has remained relatively steady and manageable at least for the time being. DNA sequencing is the gold standard method for genotyping, mutation analysis, and identification of bacteria. Due to significant cost decrease in recent years, this technique is available to many research and clinical laboratories. Pyrosequencing technique, a rapid real-time DNA sequencing method especially suitable for analyzing fairly short stretches of DNA, was used in this study. Due to its robustness and versatility, pyrosequencing was applied in this study for identification of streptococci and detection of certain mutations causing antimicrobial resistance in different bacteria. Certain streptococcal species such as S. pneumoniae and S. pyogenes are significantly important clinical pathogens. S. pneumoniae causes e.g. pneumonia and otitis media and is one of the most important community-acquired pathogens. S. pyogenes, also known as group A streptococcus, causes e.g. angina and erysipelas. In contrast, the socalled alpha-haemolytic streptococci, such as S. mitis and S. oralis, belong to the normal microbiota, which are regarded to be non-pathogenic and are nearly impossible to identify by phenotypic methods. In this thesis, a pyrosequencing method was developed for identification of streptococcal species based on the 16S rRNA sequences. Almost all streptococcal species could be differentiated from one another by the developed method, including S. pneumoniae from its close relatives S. mitis and S. oralis . New resistance genes and their variants are constantly discovered and reported. In this study, new methods for detecting certain mutations causing macrolide resistance or extended spectrum beta-lactamase (ESBL) phenotype were developed. These resistance detection approaches are not only suitable for surveillance of mechanisms causing antimicrobial resistance but also for routine analysis of clinical samples particularly in epidemic settings. In conclusion, pyrosequencing was found to be an accurate, versatile, cost-effective, and rapid DNA sequencing method that is especially suitable for mutation analysis of short DNA fragments and identification of certain bacteria.

Preparation and purification of Flavobacterium heparinum chondroitinases AC and B by hydrophobic interaction chromatography

Flavobacterium heparinum is a soil bacterium that produces several mucopolysaccharidases such as heparinase, heparitinases I and II, and chondroitinases AC, B, C and ABC. The purpose of the present study was to optimize the preparation of F. heparinum chondroitinases, which are very useful tools for the identification and structural characterization of chondroitin and dermatan sulfates. We observed that during the routine procedure for cell disruption (ultrasound, 100 kHz, 5 min) some of the chondroitinase B activity was lost. Using milder conditions (2 min), most of the chondroitinase B and AC protein was solubilized and the enzyme activities were preserved. Tryptic soy broth without glucose was the best culture medium both for bacterial growth and enzyme induction. Chondroitinases AC and B were separated from each other and also from glucuronidases and sulfatases by hydrophobic interaction chromatography on HP Phenyl-Sepharose. A rapid method for screening of the column fractions was also developed based on the metachromatic shift of the color of dimethylmethylene blue.

The radio frequency identification technology in the supply chain management: a case of a big logistics company

Nowadays global business trends force the adoption of innovative ICTs into the supply chain management (SCM). Particularly, the RFID technology is on high demand among SCM professionals due to its business advantages such as improving of accuracy and veloc-ity of SCM processes which lead to decrease of operational costs. Nevertheless, a question of the RFID technology impact on the efficiency of warehouse processes in the SCM re-mains open. The goal of the present study is to experiment the possibility of improvement order picking velocity in a warehouse of a big logistics company with the use of the RFID technology. In order to achieve this goal the following objectives have been developed: 1) Defining the scope of the RFID technology applications in the SCM; 2) Justification of the RFID technology impact on the SCM processes; 3) Defining a place of the warehouse order picking process in the SCM; 4) Identification and systematization of existing meth-ods of order picking velocity improvement; 5) Choosing of the study object and gathering of the empirical data about number of orders, number of hours spent per each order line daily during 5 months; 6) Processing and analysis of the empirical data; 7) Conclusion about the impact of the RFID technology on the speed of order picking process. As a result of the research it has been found that the speed of the order picking processes has not been changed as time has gone after the RFID adoption. It has been concluded that in order to achieve a positive effect in the speed of order picking process with the use of the RFID technology it is necessary to simultaneously implement changes in logistics and organizational management in 3PL logistics companies. Practical recommendations have been forwarded to the management of the company for further investigation and procedure.

The Nature of Object of Perception and Its Role in the Knowledge Concerning the External World

Questions concerning perception are as old as the field of philosophy itself. Using the first-person perspective as a starting point and philosophical documents, the study examines the relationship between knowledge and perception. The problem is that of how one knows what one immediately perceives. The everyday belief that an object of perception is known to be a material object on grounds of perception is demonstrated as unreliable. It is possible that directly perceived sensible particulars are mind-internal images, shapes, sounds, touches, tastes and smells. According to the appearance/reality distinction, the world of perception is the apparent realm, not the real external world. However, the distinction does not necessarily refute the existence of the external world. We have a causal connection with the external world via mind-internal particulars, and therefore we have indirect knowledge about the external world through perceptual experience. The research especially concerns the reasons for George Berkeley’s claim that material things are mind-dependent ideas that really are perceived. The necessity of a perceiver’s own qualities for perceptual experience, such as mind, consciousness, and the brain, supports the causal theory of perception. Finally, it is asked why mind-internal entities are present when perceiving an object. Perception would not directly discern material objects without the presupposition of extra entities located between a perceiver and the external world. Nevertheless, the results show that perception is not sufficient to know what a perceptual object is, and that the existence of appearances is necessary to know that the external world is being perceived. However, the impossibility of matter does not follow from Berkeley’s theory. The main result of the research is that singular knowledge claims about the external world never refer directly and immediately to the objects of the external world. A perceiver’s own qualities affect how perceptual objects appear in a perceptual situation.

Exploring female graduate students' multifaceted and intersecting roles and identities in a complex educational milieu /

This qualitative phenomenological investigation explored six female Master of Education students' critical understandings of their identity and role negotiations, and their perceptions of environmental conditions that facilitated or impeded their identity explorations and negotiations within the institution. The interweaving of Feminist and Women's Development theories enabled the data to be examined under different, yet complementary, lenses. The data collection strategies included: four to five in-depth semistructured interviews, three take-home activities (involving identity mapping, object and metaphor identification, and strategy development), and the compilation of extensive interview notes as well as researcher reflections. The combination of a constant comparative method and a voice-centered method were used in tandem to analyze the data. Together they uncovered five emergent themes: (a) intricate understandings of key terms; (b) life-long learning and transformative pathways; (c) gender issues; (d) challenges, tensions, and possibilities; as well as (e) personal, professional, and educational implications. The findings underscored the possibility for both a singular static identity and dynamic multifaceted identities to exist in tandem, and the emergence of natural or logical identity intersections, as well as disjointed or colliding identity intersections. Ultimately, it is the continuous negotiation of internal and external spheres that contributes to the complexity and multidimensionality of graduate students' identities.

Identification, Weak Instruments and Statistical Inference in Econometrics

We discuss statistical inference problems associated with identification and testability in econometrics, and we emphasize the common nature of the two issues. After reviewing the relevant statistical notions, we consider in turn inference in nonparametric models and recent developments on weakly identified models (or weak instruments). We point out that many hypotheses, for which test procedures are commonly proposed, are not testable at all, while some frequently used econometric methods are fundamentally inappropriate for the models considered. Such situations lead to ill-defined statistical problems and are often associated with a misguided use of asymptotic distributional results. Concerning nonparametric hypotheses, we discuss three basic problems for which such difficulties occur: (1) testing a mean (or a moment) under (too) weak distributional assumptions; (2) inference under heteroskedasticity of unknown form; (3) inference in dynamic models with an unlimited number of parameters. Concerning weakly identified models, we stress that valid inference should be based on proper pivotal functions —a condition not satisfied by standard Wald-type methods based on standard errors — and we discuss recent developments in this field, mainly from the viewpoint of building valid tests and confidence sets. The techniques discussed include alternative proposed statistics, bounds, projection, split-sampling, conditioning, Monte Carlo tests. The possibility of deriving a finite-sample distributional theory, robustness to the presence of weak instruments, and robustness to the specification of a model for endogenous explanatory variables are stressed as important criteria assessing alternative procedures.

Identification et localisation des préoccupations fonctionnelles dans un code légataire Java

Traditionnellement, les applications orientées objets légataires intègrent différents aspects fonctionnels. Ces aspects peuvent être dispersés partout dans le code. Il existe différents types d’aspects : • des aspects qui représentent des fonctionnalités métiers ; • des aspects qui répondent à des exigences non fonctionnelles ou à d’autres considérations de conception comme la robustesse, la distribution, la sécurité, etc. Généralement, le code qui représente ces aspects chevauche plusieurs hiérarchies de classes. Plusieurs chercheurs se sont intéressés à la problématique de la modularisation de ces aspects dans le code : programmation orientée sujets, programmation orientée aspects et programmation orientée vues. Toutes ces méthodes proposent des techniques et des outils pour concevoir des applications orientées objets sous forme de composition de fragments de code qui répondent à différents aspects. La séparation des aspects dans le code a des avantages au niveau de la réutilisation et de la maintenance. Ainsi, il est important d’identifier et de localiser ces aspects dans du code légataire orienté objets. Nous nous intéressons particulièrement aux aspects fonctionnels. En supposant que le code qui répond à un aspect fonctionnel ou fonctionnalité exhibe une certaine cohésion fonctionnelle (dépendances entre les éléments), nous proposons d’identifier de telles fonctionnalités à partir du code. L’idée est d’identifier, en l’absence des paradigmes de la programmation par aspects, les techniques qui permettent l’implémentation des différents aspects fonctionnels dans un code objet. Notre approche consiste à : • identifier les techniques utilisées par les développeurs pour intégrer une fonctionnalité en l’absence des techniques orientées aspects • caractériser l’empreinte de ces techniques sur le code • et développer des outils pour identifier ces empreintes. Ainsi, nous présentons deux approches pour l’identification des fonctionnalités existantes dans du code orienté objets. La première identifie différents patrons de conception qui permettent l’intégration de ces fonctionnalités dans le code. La deuxième utilise l’analyse formelle de concepts pour identifier les fonctionnalités récurrentes dans le code. Nous expérimentons nos deux approches sur des systèmes libres orientés objets pour identifier les différentes fonctionnalités dans le code. Les résultats obtenus montrent l’efficacité de nos approches pour identifier les différentes fonctionnalités dans du code légataire orienté objets et permettent de suggérer des cas de refactorisation.

OFFLINE AND ONLINE SOLID PHASE EXTRACTION/PRECONCENTRATION OF INORGANICS

Solid phase extraction (SPE) is a powerful technique for preconcentration/removal or separation of trace and ultra trace amounts of toxic and nutrient elements. SPE effectively simplifies the labour intensive sample preparation, increase its reliability and eliminate the clean up step by using more selective extraction procedures. The synthesis of sorbents with a simplified procedure and diminution of the risks of errors shows the interest in the areas of environmental monitoring, geochemical exploration, food, agricultural, pharmaceutical, biochemical industry and high purity metal designing, etc. There is no universal SPE method because the sample pretreatment depends strongly on the analytical demand. But there is always an increasing demand for more sensitive, selective, rapid and reliable analytical procedures. Among the various materials, chelate modified naphthalene, activated carbon and chelate functionalized highly cross linked polymers are most important. In the biological and environmental field, large numbers of samples are to be analysed within a short span of time. Hence, online flow injection methods are preferred as they allow extraction, separation, identification and quantification of many numbers of analytes. The flow injection online preconcentration flame AAS procedure developed allows the determination of as low as 0.1 µg/l of nickel in soil and cobalt in human hair samples. The developed procedure is precise and rapid and allows the analysis of 30 samples per hour with a loading time of 60 s. The online FI manifold used in the present study permits high sampling, loading rates and thus resulting in higher preconcentration/enrichment factors of -725 and 600 for cobalt and nickel respectively with a 1 min preconcentration time compared to conventional FAAS signal. These enrichment factors are far superior to hitherto developed on line preconcentration procedures for inorganics. The instrumentation adopted in the present study allows much simpler equipment and low maintenance costs compared to costlier ICP-AES or ICP-MS instruments.

Development and Evaluation of Blind Identification Techniques for Nonlinear Systems

Identification and Control of Non‐linear dynamical systems are challenging problems to the control engineers.The topic is equally relevant in communication,weather prediction ,bio medical systems and even in social systems,where nonlinearity is an integral part of the system behavior.Most of the real world systems are nonlinear in nature and wide applications are there for nonlinear system identification/modeling.The basic approach in analyzing the nonlinear systems is to build a model from known behavior manifest in the form of system output.The problem of modeling boils down to computing a suitably parameterized model,representing the process.The parameters of the model are adjusted to optimize a performanace function,based on error between the given process output and identified process/model output.While the linear system identification is well established with many classical approaches,most of those methods cannot be directly applied for nonlinear system identification.The problem becomes more complex if the system is completely unknown but only the output time series is available.Blind recognition problem is the direct consequence of such a situation.The thesis concentrates on such problems.Capability of Artificial Neural Networks to approximate many nonlinear input-output maps makes it predominantly suitable for building a function for the identification of nonlinear systems,where only the time series is available.The literature is rich with a variety of algorithms to train the Neural Network model.A comprehensive study of the computation of the model parameters,using the different algorithms and the comparison among them to choose the best technique is still a demanding requirement from practical system designers,which is not available in a concise form in the literature.The thesis is thus an attempt to develop and evaluate some of the well known algorithms and propose some new techniques,in the context of Blind recognition of nonlinear systems.It also attempts to establish the relative merits and demerits of the different approaches.comprehensiveness is achieved in utilizing the benefits of well known evaluation techniques from statistics. The study concludes by providing the results of implementation of the currently available and modified versions and newly introduced techniques for nonlinear blind system modeling followed by a comparison of their performance.It is expected that,such comprehensive study and the comparison process can be of great relevance in many fields including chemical,electrical,biological,financial and weather data analysis.Further the results reported would be of immense help for practical system designers and analysts in selecting the most appropriate method based on the goodness of the model for the particular context.

Computational Models of Object Recognition in Cortex: A Review

Understanding how biological visual systems perform object recognition is one of the ultimate goals in computational neuroscience. Among the biological models of recognition the main distinctions are between feedforward and feedback and between object-centered and view-centered. From a computational viewpoint the different recognition tasks - for instance categorization and identification - are very similar, representing different trade-offs between specificity and invariance. Thus the different tasks do not strictly require different classes of models. The focus of the review is on feedforward, view-based models that are supported by psychophysical and physiological data.

Identification, characterization and antigenicity of the Plasmodium vivax rhoptry neck protein 1 (PvRON1)

Background: Plasmodium vivax malaria remains a major health problem in tropical and sub-tropical regions worldwide. Several rhoptry proteins which are important for interaction with and/or invasion of red blood cells, such as PfRONs, Pf92, Pf38, Pf12 and Pf34, have been described during the last few years and are being considered as potential anti-malarial vaccine candidates. This study describes the identification and characterization of the P. vivax rhoptry neck protein 1 (PvRON1) and examine its antigenicity in natural P. vivax infections. Methods: The PvRON1 encoding gene, which is homologous to that encoding the P. falciparum apical sushi protein (ASP) according to the plasmoDB database, was selected as our study target. The pvron1 gene transcription was evaluated by RT-PCR using RNA obtained from the P. vivax VCG-1 strain. Two peptides derived from the deduced P. vivax Sal-I PvRON1 sequence were synthesized and inoculated in rabbits for obtaining anti-PvRON1 antibodies which were used to confirm the protein expression in VCG-1 strain schizonts along with its association with detergent-resistant microdomains (DRMs) by Western blot, and its localization by immunofluorescence assays. The antigenicity of the PvRON1 protein was assessed using human sera from individuals previously exposed to P. vivax malaria by ELISA. Results: In the P. vivax VCG-1 strain, RON1 is a 764 amino acid-long protein. In silico analysis has revealed that PvRON1 shares essential characteristics with different antigens involved in invasion, such as the presence of a secretory signal, a GPI-anchor sequence and a putative sushi domain. The PvRON1 protein is expressed in parasite's schizont stage, localized in rhoptry necks and it is associated with DRMs. Recombinant protein recognition by human sera indicates that this antigen can trigger an immune response during a natural infection with P. vivax. Conclusions: This study shows the identification and characterization of the P. vivax rhoptry neck protein 1 in the VCG-1 strain. Taking into account that PvRON1 shares several important characteristics with other Plasmodium antigens that play a functional role during RBC invasion and, as shown here, it is antigenic, it could be considered as a good vaccine candidate. Further studies aimed at assessing its immunogenicity and protection-inducing ability in the Aotus monkey model are thus recommended.

Mapping and controlling molecular processes: The application of control theory and system identification algorithms to ASOPS and other fast pulse spectroscopies

Asynchronous Optical Sampling (ASOPS) [1,2] and frequency comb spectrometry [3] based on dual Ti:saphire resonators operated in a master/slave mode have the potential to improve signal to noise ratio in THz transient and IR sperctrometry. The multimode Brownian oscillator time-domain response function described by state-space models is a mathematically robust framework that can be used to describe the dispersive phenomena governed by Lorentzian, Debye and Drude responses. In addition, the optical properties of an arbitrary medium can be expressed as a linear combination of simple multimode Brownian oscillator functions. The suitability of a range of signal processing schemes adopted from the Systems Identification and Control Theory community for further processing the recorded THz transients in the time or frequency domain will be outlined [4,5]. Since a femtosecond duration pulse is capable of persistent excitation of the medium within which it propagates, such approach is perfectly justifiable. Several de-noising routines based on system identification will be shown. Furthermore, specifically developed apodization structures will be discussed. These are necessary because due to dispersion issues, the time-domain background and sample interferograms are non-symmetrical [6-8]. These procedures can lead to a more precise estimation of the complex insertion loss function. The algorithms are applicable to femtosecond spectroscopies across the EM spectrum. Finally, a methodology for femtosecond pulse shaping using genetic algorithms aiming to map and control molecular relaxation processes will be mentioned.