Statistical analysis of multichannel scalp field data

High density spatial and temporal sampling of EEG data enhances the quality of results of electrophysiological experiments. Because EEG sources typically produce widespread electric fields (see Chapter 3) and operate at frequencies well below the sampling rate, increasing the number of electrodes and time samples will not necessarily increase the number of observed processes, but mainly increase the accuracy of the representation of these processes. This is namely the case when inverse solutions are computed. As a consequence, increasing the sampling in space and time increases the redundancy of the data (in space, because electrodes are correlated due to volume conduction, and time, because neighboring time points are correlated), while the degrees of freedom of the data change only little. This has to be taken into account when statistical inferences are to be made from the data. However, in many ERP studies, the intrinsic correlation structure of the data has been disregarded. Often, some electrodes or groups of electrodes are a priori selected as the analysis entity and considered as repeated (within subject) measures that are analyzed using standard univariate statistics. The increased spatial resolution obtained with more electrodes is thus poorly represented by the resulting statistics. In addition, the assumptions made (e.g. in terms of what constitutes a repeated measure) are not supported by what we know about the properties of EEG data. From the point of view of physics (see Chapter 3), the natural “atomic” analysis entity of EEG and ERP data is the scalp electric field

A method to incorporate the effect of taxonomic uncertainty on multivariate analyses of ecological data

Researchers in ecology commonly use multivariate analyses (e.g. redundancy analysis, canonical correspondence analysis, Mantel correlation, multivariate analysis of variance) to interpret patterns in biological data and relate these patterns to environmental predictors. There has been, however, little recognition of the errors associated with biological data and the influence that these may have on predictions derived from ecological hypotheses. We present a permutational method that assesses the effects of taxonomic uncertainty on the multivariate analyses typically used in the analysis of ecological data. The procedure is based on iterative randomizations that randomly re-assign non identified species in each site to any of the other species found in the remaining sites. After each re-assignment of species identities, the multivariate method at stake is run and a parameter of interest is calculated. Consequently, one can estimate a range of plausible values for the parameter of interest under different scenarios of re-assigned species identities. We demonstrate the use of our approach in the calculation of two parameters with an example involving tropical tree species from western Amazonia: 1) the Mantel correlation between compositional similarity and environmental distances between pairs of sites, and; 2) the variance explained by environmental predictors in redundancy analysis (RDA). We also investigated the effects of increasing taxonomic uncertainty (i.e. number of unidentified species), and the taxonomic resolution at which morphospecies are determined (genus-resolution, family-resolution, or fully undetermined species) on the uncertainty range of these parameters. To achieve this, we performed simulations on a tree dataset from southern Mexico by randomly selecting a portion of the species contained in the dataset and classifying them as unidentified at each level of decreasing taxonomic resolution. An analysis of covariance showed that both taxonomic uncertainty and resolution significantly influence the uncertainty range of the resulting parameters. Increasing taxonomic uncertainty expands our uncertainty of the parameters estimated both in the Mantel test and RDA. The effects of increasing taxonomic resolution, however, are not as evident. The method presented in this study improves the traditional approaches to study compositional change in ecological communities by accounting for some of the uncertainty inherent to biological data. We hope that this approach can be routinely used to estimate any parameter of interest obtained from compositional data tables when faced with taxonomic uncertainty.

Genetic redundancy among durum wheat accessions as assessed with SSRs and endosperm proteins

Reducing duplication in ex-situ collections is complicated and requires good quality genetic markers. This study was conducted to assess the value of endosperm proteins and SSRs for validation of potential duplicates and monitoring intra-accession variability. Fifty durum wheat (Triticum turgidum ssp. durum) accessions grouped in 23 potential duplicates, and previously characterised for 30 agro-morphological traits, were analysed for gliadin and high molecular weight glutenin (HMWG) subunit alleles, total protein, and 24 SSRs, covering a wide genome area. Similarity and dissimilarity matrices were generated based on protein and SSRs alleles. For heterogeneous accessions at gliadins the percent pattern homology (PH) between gliadin patterns and the Nei’s coefficient of genetic identity (I) were computed. Eighteen duplicates identical for proteins showed none or less than 3 unshared SSRs alleles. For heterogeneous accessions PH and I values lower than 80 identified clearly off-types with more than 3 SSRs unshared. Only those biotypes differing in no more than one protein-coding locus were confirmed with SSRs. A good concordance among proteins, morphological traits, and SSR were detected. However, the discrepancy in similarity detected in some cases showed that it is advisable to evaluate redundancy through distinct approaches. The analysis in proteins together with SSRs data are very useful to identify duplicates, biotypes, close related genotypes, and contaminations

Ovulation efficiency is reduced in mice that lack plasminogen activator gene function: functional redundancy among physiological plasminogen activators.

Several lines of indirect evidence suggest that plasminogen activation plays a crucial role in degradation of the follicular wall during ovulation. However, single-deficient mice lacking tissue-type plasminogen activator (tPA), urokinase-type plasminogen activator (uPA), or PA inhibitor type 1(PAI-1) gene function were recently found to have normal reproduction, although mice with a combined deficiency of tPA and uPA were significantly less fertile. To investigate whether the reduced fertility of mice lacking PA gene function is due to a reduced ovulation mechanism, we have determined the ovulation efficiency in 25-day-old mice during gonadotropin-induced ovulation. Our results reveal that ovulation efficiency is normal in mice with a single deficiency of tPA or uPA but reduced by 26% in mice lacking both physiological PAs. This result suggests that plasminogen activation plays a role in ovulatory response, although neither tPA nor uPA individually or in combination is obligatory for ovulation. The loss of an individual PA seems to be functionally complemented by the remaining PA but this compensation does not appear to involve any compensatory up-regulation. Our data imply that a functionally redundant mechanism for plasmin formation operates during gonadotropin-induced ovulation and that PAs together with other proteases generate the proteolytic activity required for follicular wall degradation.

Efficient Mitigation of Data and Control Flow Errors in Microprocessors

The use of microprocessor-based systems is gaining importance in application domains where safety is a must. For this reason, there is a growing concern about the mitigation of SEU and SET effects. This paper presents a new hybrid technique aimed to protect both the data and the control-flow of embedded applications running on microprocessors. On one hand, the approach is based on software redundancy techniques for correcting errors produced in the data. On the other hand, control-flow errors can be detected by reusing the on-chip debug interface, existing in most modern microprocessors. Experimental results show an important increase in the system reliability even superior to two orders of magnitude, in terms of mitigation of both SEUs and SETs. Furthermore, the overheads incurred by our technique can be perfectly assumable in low-cost systems.

Reducing task’s redundancy – the strategy of Faculty of Pharmacy Library to centralize all scientific research

Introduction – Based on a previous project of University of Lisbon (UL) – a Bibliometric Benchmarking Analysis of University of Lisbon, for the period of 2000-2009 – a database was created to support research information (ULSR). However this system was not integrated with other existing systems at University, as the UL Libraries Integrated System (SIBUL) and the Repository of University of Lisbon (Repositório.UL). Since libraries were called to be part of the process, the Faculty of Pharmacy Library’ team felt that it was very important to get all systems connected or, at least, to use that data in the library systems. Objectives – The main goals were to centralize all the scientific research produced at Faculty of Pharmacy, made it available to the entire Faculty, involve researchers and library team, capitalize and reinforce team work with the integration of several distinct projects and reducing tasks’ redundancy. Methods – Our basis was the imported data collection from the ISI Web of Science (WoS), for the period of 2000-2009, into ULSR. All the researchers and indexed publications at WoS, were identified. A first validation to identify all the researchers and their affiliation (university, faculty, department and unit) was done. The final validation was done by each researcher. In a second round, concerning the same period, all Pharmacy Faculty researchers identified their published scientific work in other databases/resources (NOT WoS). To our strategy, it was important to get all the references and essential/critical to relate them with the correspondent digital objects. To each researcher previously identified, was requested to register all their references of the ‘NOT WoS’ published works, at ULSR. At the same time, they should submit all PDF files (for both WoS and NOT WoS works) in a personal area of the Web server. This effort enabled us to do a more reliable validation and prepare the data and metadata to be imported to Repository and to Library Catalogue. Results – 558 documents related with 122 researchers, were added into ULSR. 1378 bibliographic records (WoS + NOT WoS) were converted into UNIMARC and Dublin Core formats. All records were integrated in the catalogue and repository. Conclusions – Although different strategies could be adopted, according to each library team, we intend to share this experience and give some tips of what could be done and how Faculty of Pharmacy created and implemented her strategy.

Watermarking biomedical time series data

This thesis addresses the problem of information hiding in low dimensional digital data focussing on issues of privacy and security in Electronic Patient Health Records (EPHRs). The thesis proposes a new security protocol based on data hiding techniques for EPHRs. This thesis contends that embedding of sensitive patient information inside the EPHR is the most appropriate solution currently available to resolve the issues of security in EPHRs. Watermarking techniques are applied to one-dimensional time series data such as the electroencephalogram (EEG) to show that they add a level of confidence (in terms of privacy and security) in an individual’s diverse bio-profile (the digital fingerprint of an individual’s medical history), ensure belief that the data being analysed does indeed belong to the correct person, and also that it is not being accessed by unauthorised personnel. Embedding information inside single channel biomedical time series data is more difficult than the standard application for images due to the reduced redundancy. A data hiding approach which has an in built capability to protect against illegal data snooping is developed. The capability of this secure method is enhanced by embedding not just a single message but multiple messages into an example one-dimensional EEG signal. Embedding multiple messages of similar characteristics, for example identities of clinicians accessing the medical record helps in creating a log of access while embedding multiple messages of dissimilar characteristics into an EPHR enhances confidence in the use of the EPHR. The novel method of embedding multiple messages of both similar and dissimilar characteristics into a single channel EEG demonstrated in this thesis shows how this embedding of data boosts the implementation and use of the EPHR securely.

Data partitioning and replication management in distributed geographic information system (GIS) database

This research presents several components encompassing the scope of the objective of Data Partitioning and Replication Management in Distributed GIS Database. Modern Geographic Information Systems (GIS) databases are often large and complicated. Therefore data partitioning and replication management problems need to be addresses in development of an efficient and scalable solution. ^ Part of the research is to study the patterns of geographical raster data processing and to propose the algorithms to improve availability of such data. These algorithms and approaches are targeting granularity of geographic data objects as well as data partitioning in geographic databases to achieve high data availability and Quality of Service(QoS) considering distributed data delivery and processing. To achieve this goal a dynamic, real-time approach for mosaicking digital images of different temporal and spatial characteristics into tiles is proposed. This dynamic approach reuses digital images upon demand and generates mosaicked tiles only for the required region according to user's requirements such as resolution, temporal range, and target bands to reduce redundancy in storage and to utilize available computing and storage resources more efficiently. ^ Another part of the research pursued methods for efficient acquiring of GIS data from external heterogeneous databases and Web services as well as end-user GIS data delivery enhancements, automation and 3D virtual reality presentation. ^ There are vast numbers of computing, network, and storage resources idling or not fully utilized available on the Internet. Proposed "Crawling Distributed Operating System "(CDOS) approach employs such resources and creates benefits for the hosts that lend their CPU, network, and storage resources to be used in GIS database context. ^ The results of this dissertation demonstrate effective ways to develop a highly scalable GIS database. The approach developed in this dissertation has resulted in creation of TerraFly GIS database that is used by US government, researchers, and general public to facilitate Web access to remotely-sensed imagery and GIS vector information. ^

Infants' selective attention to faces and prosody of speech: The roles of intersensory redundancy and exploratory time

One of the overarching questions in the field of infant perceptual and cognitive development concerns how selective attention is organized during early development to facilitate learning. The following study examined how infants' selective attention to properties of social events (i.e., prosody of speech and facial identity) changes in real time as a function of intersensory redundancy (redundant audiovisual, nonredundant unimodal visual) and exploratory time. Intersensory redundancy refers to the spatially coordinated and temporally synchronous occurrence of information across multiple senses. Real time macro- and micro-structural change in infants' scanning patterns of dynamic faces was also examined. ^ According to the Intersensory Redundancy Hypothesis, information presented redundantly and in temporal synchrony across two or more senses recruits infants' selective attention and facilitates perceptual learning of highly salient amodal properties (properties that can be perceived across several sensory modalities such as the prosody of speech) at the expense of less salient modality specific properties. Conversely, information presented to only one sense facilitates infants' learning of modality specific properties (properties that are specific to a particular sensory modality such as facial features) at the expense of amodal properties (Bahrick & Lickliter, 2000, 2002). ^ Infants' selective attention and discrimination of prosody of speech and facial configuration was assessed in a modified visual paired comparison paradigm. In redundant audiovisual stimulation, it was predicted infants would show discrimination of prosody of speech in the early phases of exploration and facial configuration in the later phases of exploration. Conversely, in nonredundant unimodal visual stimulation, it was predicted infants would show discrimination of facial identity in the early phases of exploration and prosody of speech in the later phases of exploration. Results provided support for the first prediction and indicated that following redundant audiovisual exposure, infants showed discrimination of prosody of speech earlier in processing time than discrimination of facial identity. Data from the nonredundant unimodal visual condition provided partial support for the second prediction and indicated that infants showed discrimination of facial identity, but not prosody of speech. The dissertation study contributes to the understanding of the nature of infants' selective attention and processing of social events across exploratory time.^

Condition assessment of timber utility poles based on a hierarchical data fusion model

This paper proposes a novel hierarchical data fusion technique for the non-destructive testing (NDT) and condition assessment of timber utility poles. The new method analyzes stress wave data from multisensor and multiexcitation guided wave testing using a hierarchical data fusion model consisting of feature extraction, data compression, pattern recognition, and decision fusion algorithms. The researchers validate the proposed technique using guided wave tests of a sample of in situ timber poles. The actual health states of these poles are known from autopsies conducted after the testing, forming a ground-truth for supervised classification. In the proposed method, a data fusion level extracts the main features from the sampled stress wave signals using power spectrum density (PSD) estimation, wavelet packet transform (WPT), and empirical mode decomposition (EMD). These features are then compiled to a feature vector via real-number encoding and sent to the next level for further processing. Principal component analysis (PCA) is also adopted for feature compression and to minimize information redundancy and noise interference. In the feature fusion level, two classifiers based on support vector machine (SVM) are applied to sensor separated data of the two excitation types and the pole condition is identified. In the decision making fusion level, the Dempster–Shafer (D-S) evidence theory is employed to integrate the results from the individual sensors obtaining a final decision. The results of the in situ timber pole testing show that the proposed hierarchical data fusion model was able to distinguish between healthy and faulty poles, demonstrating the effectiveness of the new method.