The Design and Implementation of a SD Card File System

SD card (Secure Digital Memory Card) is widely used in portable storage medium. Currently, latest researches on SD card, are mainly SD card controller based on FPGA (Field Programmable Gate Array). Most of them are relying on API interface (Application Programming Interface), AHB bus (Advanced High performance Bus), etc. They are dedicated to the realization of ultra high speed communication between SD card and upper systems. Studies about SD card controller, really play a vital role in the field of high speed cameras and other sub-areas of expertise. This design of FPGA-based file systems and SD2.0 IP (Intellectual Property core) does not only exhibit a nice transmission rate, but also achieve the systematic management of files, while retaining a strong portability and practicality. The file system design and implementation on a SD card covers the main three IP innovation points. First, the combination and integration of file system and SD card controller, makes the overall system highly integrated and practical. The popular SD2.0 protocol is implemented for communication channels. Pure digital logic design based on VHDL (Very-High-Speed Integrated Circuit Hardware Description Language), integrates the SD card controller in hardware layer and the FAT32 file system for the entire system. Secondly, the document management system mechanism makes document processing more convenient and easy. Especially for small files in batch processing, it can ease the pressure of upper system to frequently access and process them, thereby enhancing the overall efficiency of systems. Finally, digital design ensures the superior performance. For transmission security, CRC (Cyclic Redundancy Check) algorithm is for data transmission protection. Design of each module is platform-independent of macro cells, and keeps a better portability. Custom integrated instructions and interfaces may facilitate easily to use. Finally, the actual test went through multi-platform method, Xilinx and Altera FPGA developing platforms. The timing simulation and debugging of each module was covered. Finally, Test results show that the designed FPGA-based file system IP on SD card can support SD card, TF card and Micro SD with 2.0 protocols, and the successful implementation of systematic management for stored files, and supports SD bus mode. Data read and write rates in Kingston class10 card is approximately 24.27MB/s and 16.94MB/s.

Anomaly Detection in Noisy Images

Finding rare events in multidimensional data is an important detection problem that has applications in many fields, such as risk estimation in insurance industry, finance, flood prediction, medical diagnosis, quality assurance, security, or safety in transportation. The occurrence of such anomalies is so infrequent that there is usually not enough training data to learn an accurate statistical model of the anomaly class. In some cases, such events may have never been observed, so the only information that is available is a set of normal samples and an assumed pairwise similarity function. Such metric may only be known up to a certain number of unspecified parameters, which would either need to be learned from training data, or fixed by a domain expert. Sometimes, the anomalous condition may be formulated algebraically, such as a measure exceeding a predefined threshold, but nuisance variables may complicate the estimation of such a measure. Change detection methods used in time series analysis are not easily extendable to the multidimensional case, where discontinuities are not localized to a single point. On the other hand, in higher dimensions, data exhibits more complex interdependencies, and there is redundancy that could be exploited to adaptively model the normal data. In the first part of this dissertation, we review the theoretical framework for anomaly detection in images and previous anomaly detection work done in the context of crack detection and detection of anomalous components in railway tracks. In the second part, we propose new anomaly detection algorithms. The fact that curvilinear discontinuities in images are sparse with respect to the frame of shearlets, allows us to pose this anomaly detection problem as basis pursuit optimization. Therefore, we pose the problem of detecting curvilinear anomalies in noisy textured images as a blind source separation problem under sparsity constraints, and propose an iterative shrinkage algorithm to solve it. Taking advantage of the parallel nature of this algorithm, we describe how this method can be accelerated using graphical processing units (GPU). Then, we propose a new method for finding defective components on railway tracks using cameras mounted on a train. We describe how to extract features and use a combination of classifiers to solve this problem. Then, we scale anomaly detection to bigger datasets with complex interdependencies. We show that the anomaly detection problem naturally fits in the multitask learning framework. The first task consists of learning a compact representation of the good samples, while the second task consists of learning the anomaly detector. Using deep convolutional neural networks, we show that it is possible to train a deep model with a limited number of anomalous examples. In sequential detection problems, the presence of time-variant nuisance parameters affect the detection performance. In the last part of this dissertation, we present a method for adaptively estimating the threshold of sequential detectors using Extreme Value Theory on a Bayesian framework. Finally, conclusions on the results obtained are provided, followed by a discussion of possible future work.

The mosaic of habitats of the Seine estuary: Insights from food-web modelling and network analysis

Ecological network analysis was applied in the Seine estuary ecosystem, northern France, integrating ecological data from the years 1996 to 2002. The Ecopath with Ecosim (EwE) approach was used to model the trophic flows in 6 spatial compartments leading to 6 distinct EwE models: the navigation channel and the two channel flanks in the estuary proper, and 3 marine habitats in the eastern Seine Bay. Each model included 12 consumer groups, 2 primary producers, and one detritus group. Ecological network analysis was performed, including a set of indices, keystoneness, and trophic spectrum analysis to describe the contribution of the 6 habitats to the Seine estuary ecosystem functioning. Results showed that the two habitats with a functioning most related to a stressed state were the northern and central navigation channels, where building works and constant maritime traffic are considered major anthropogenic stressors. The strong top-down control highlighted in the other 4 habitats was not present in the central channel, showing instead (i) a change in keystone roles in the ecosystem towards sediment-based, lower trophic levels, and (ii) a higher system omnivory. The southern channel evidenced the highest system activity (total system throughput), the higher trophic specialisation (low system omnivory), and the lowest indication of stress (low cycling and relative redundancy). Marine habitats showed higher fish biomass proportions and higher transfer efficiencies per trophic levels than the estuarine habitats, with a transition area between the two that presented intermediate ecosystem structure. The modelling of separate habitats permitted disclosing each one's response to the different pressures, based on their a priori knowledge. Network indices, although non-monotonously, responded to these differences and seem a promising operational tool to define the ecological status of transitional water ecosystems.

Low-power high-performance SAR ADC design with digital calibration techniques

This dissertation presents the design of three high-performance successive-approximation-register (SAR) analog-to-digital converters (ADCs) using distinct digital background calibration techniques under the framework of a generalized code-domain linear equalizer. These digital calibration techniques effectively and efficiently remove the static mismatch errors in the analog-to-digital (A/D) conversion. They enable aggressive scaling of the capacitive digital-to-analog converter (DAC), which also serves as sampling capacitor, to the kT/C limit. As a result, outstanding conversion linearity, high signal-to-noise ratio (SNR), high conversion speed, robustness, superb energy efficiency, and minimal chip-area are accomplished simultaneously. The first design is a 12-bit 22.5/45-MS/s SAR ADC in 0.13-μm CMOS process. It employs a perturbation-based calibration based on the superposition property of linear systems to digitally correct the capacitor mismatch error in the weighted DAC. With 3.0-mW power dissipation at a 1.2-V power supply and a 22.5-MS/s sample rate, it achieves a 71.1-dB signal-to-noise-plus-distortion ratio (SNDR), and a 94.6-dB spurious free dynamic range (SFDR). At Nyquist frequency, the conversion figure of merit (FoM) is 50.8 fJ/conversion step, the best FoM up to date (2010) for 12-bit ADCs. The SAR ADC core occupies 0.06 mm2, while the estimated area the calibration circuits is 0.03 mm2. The second proposed digital calibration technique is a bit-wise-correlation-based digital calibration. It utilizes the statistical independence of an injected pseudo-random signal and the input signal to correct the DAC mismatch in SAR ADCs. This idea is experimentally verified in a 12-bit 37-MS/s SAR ADC fabricated in 65-nm CMOS implemented by Pingli Huang. This prototype chip achieves a 70.23-dB peak SNDR and an 81.02-dB peak SFDR, while occupying 0.12-mm2 silicon area and dissipating 9.14 mW from a 1.2-V supply with the synthesized digital calibration circuits included. The third work is an 8-bit, 600-MS/s, 10-way time-interleaved SAR ADC array fabricated in 0.13-μm CMOS process. This work employs an adaptive digital equalization approach to calibrate both intra-channel nonlinearities and inter-channel mismatch errors. The prototype chip achieves 47.4-dB SNDR, 63.6-dB SFDR, less than 0.30-LSB differential nonlinearity (DNL), and less than 0.23-LSB integral nonlinearity (INL). The ADC array occupies an active area of 1.35 mm2 and dissipates 30.3 mW, including synthesized digital calibration circuits and an on-chip dual-loop delay-locked loop (DLL) for clock generation and synchronization.

Two novel COLVI long chains in zebrafish that are essential for muscle development

Collagen VI (COLVI), a protein ubiquitously expressed in connective tissues, is crucial for structural integrity, cellular adhesion, migration and survival. Six different genes are recognized in mammalians, encoding six COLVI-chains that assemble as two ‘short’ (α1, α2) and one ‘long’ chain (theoretically any one of α3–6). In humans, defects in the most widely expressed heterotrimer (α123), due to mutations in the COL6A1-3 genes, cause a heterogeneous group of neuromuscular disorders, collectively termed COLVI-related muscle disorders. Little is known about the function(s) of the recently described α4-6 chains and no mutations have been detected yet. In this study, we characterized two novel COLVI long chains in zebrafish that are most homologous to the mammalian α4 chain; therefore, we named the corresponding genes col6a4a and col6a4b. These orthologues represent ancestors of the mammalian Col6a4-6 genes. By in situ hybridization and RT-qPCR, we unveiled a distinctive expression kinetics for col6a4b, compared with the other col6a genes. Using morpholino antisense oligonucleotides targeting col6a4a, col6a4b and col6a2, we modelled partial and complete COLVI deficiency, respectively. All morphant embryos presented altered muscle structure and impaired motility. While apoptosis was not drastically increased, autophagy induction was defective in all morphants. Furthermore, motoneuron axon growth was abnormal in these morphants. Importantly, some phenotypical differences emerged between col6a4a and col6a4b morphants, suggesting only partial functional redundancy. Overall, our results further confirm the importance of COLVI in zebrafish muscle development and may provide important clues for potential human phenotypes associated with deficiency of the recently described COLVI-chains.

Local Field Potentials in the Gustatory Cortex Carry Taste Information

It has been recently shownthat localfield potentials (LFPs)fromthe auditory and visual cortices carry information about sensory stimuli, but whether this is a universal property of sensory cortices remains to be determined. Moreover, little is known about the temporal dynamics of sensory information contained in LFPs following stimulus onset. Here we investigated the time course of the amount of stimulus information in LFPs and spikes from the gustatory cortex of awake rats subjected to tastants and water delivery on the tongue. We found that the phase and amplitude of multiple LFP frequencies carry information about stimuli, which have specific time courses after stimulus delivery. The information carried by LFP phase and amplitude was independent within frequency bands, since the joint information exhibited neither synergy nor redundancy. Tastant information in LFPs was also independent and had a different time course from the information carried by spikes. These findings support the hypothesis that the brain uses different frequency channels to dynamically code for multiple features of a stimulus.

Genome-scale analysis of the non-cultivable Treponema pallidum reveals extensive within-patient genetic variation

Insights into the genomic adaptive traits of Treponema pallidum, the causative bacterium of syphilis, have long been hampered due to the absence of in vitro culture models and the constraints associated with its propagation in rabbits. Here, we have bypassed the culture bottleneck by means of a targeted strategy never applied to uncultivable bacterial human pathogens to directly capture whole-genome T. pallidum data in the context of human infection. This strategy has unveiled a scenario of discreet T. pallidum interstrain single-nucleotide-polymorphism-based microevolution, contrasting with a rampant within-patient genetic heterogeneity mainly targeting multiple phase-variable loci and a major antigen-coding gene (tprK). TprK demonstrated remarkable variability and redundancy, intra- and interpatient, suggesting ongoing parallel adaptive diversification during human infection. Some bacterial functions (for example, flagella- and chemotaxis-associated) were systematically targeted by both inter- and intrastrain single nucleotide polymorphisms, as well as by ongoing within-patient phase variation events. Finally, patient-derived genomes possess mutations targeting a penicillin-binding protein coding gene (mrcA) that had never been reported, unveiling it as a candidate target to investigate the impact on the susceptibility to penicillin. Our findings decode the major genetic mechanisms by which T. pallidum promotes immune evasion and survival, and demonstrate the exceptional power of characterizing evolving pathogen subpopulations during human infection.

The Warwick-Edinburgh Mental Well-Being Scale

Background There is increasing international interest in the concept of mental well-being and its contribution to all aspects of human life. Demand for instruments to monitor mental well-being at a population level and evaluate mental health promotion initiatives is growing. This article describes the development and validation of a new scale, comprised only of positively worded items relating to different aspects of positive mental health: the Warwick-Edinburgh Mental Well-Being Scale (WEMWBS). Methods WEMWBS was developed by an expert panel drawing on current academic literature, qualitative research with focus groups, and psychometric testing of an existing scale. It was validated on a student and representative population sample. Content validity was assessed by reviewing the frequency of complete responses and the distribution of responses to each item. Confirmatory factor analysis was used to test the hypothesis that the scale measured a single construct. Internal consistency was assessed using Cronbach’s alpha. Criterion validity was explored in terms of correlations between WEMWBS and other scales and by testing whether the scale discriminated between population groups in line with pre-specified hypotheses. Test-retest reliability was assessed at one week using intra-class correlation coefficients. Susceptibility to bias was measured using the Balanced Inventory of Desired Responding. Results WEMWBS showed good content validity. Confirmatory factor analysis supported the single factor hypothesis. A Cronbach’s alpha score of 0.89 (student sample) and 0.91 (population sample) suggests some item redundancy in the scale. WEMWBS showed high correlations with other mental health and well-being scales and lower correlations with scales measuring overall health. Its distribution was near normal and the scale did not show ceiling effects in a population sample. It discriminated between population groups in a way that is largely consistent with the results of other population surveys. Test–retest reliability at one week was high (0.83). Social desirability bias was lower or similar to that of other comparable scales. Conclusions WEMWBS is a measure of mental well-being focusing entirely on positive aspects of mental health. As a short and psychometrically robust scale, with no ceiling effects in a population sample, it offers promise as a tool for monitoring mental well-being at a population level. Whilst WEMWBS should appeal to those evaluating mental health promotion initiatives, it is important that the scale’s sensitivity to change is established before it is recommended in this context.

The Kinome of Pacific Oyster Crassostrea gigas, Its Expression during Development and in Response to Environmental Factors

Oysters play an important role in estuarine and coastal marine habitats, where the majority of humans live. In these ecosystems, environmental degradation is substantial, and oysters must cope with highly dynamic and stressful environmental constraints during their lives in the intertidal zone. The availability of the genome sequence of the Pacific oyster Crassostrea gigas represents a unique opportunity for a comprehensive assessment of the signal transduction pathways that the species has developed to deal with this unique habitat. We performed an in silico analysis to identify, annotate and classify protein kinases in C. gigas, according to their kinase domain taxonomy classification, and compared with kinome already described in other animal species. The C. gigas kinome consists of 371 protein kinases, making it closely related to the sea urchin kinome, which has 353 protein kinases. The absence of gene redundancy in some groups of the C. gigas kinome may simplify functional studies of protein kinases. Through data mining of transcriptomes in C. gigas, we identified part of the kinome which may be central during development and may play a role in response to various environmental factors. Overall, this work contributes to a better understanding of key sensing pathways that may be central for adaptation to a highly dynamic marine environment.

Motion compensation with minimal residue dispersion matching criteria

Dissertação (mestrado)—Universidade de Brasília, Faculdade de Tecnoloigia, 2016.

Roślinność wodna, błotna i bagienna północnej części Dolnych Łużyc

Wydział Biologii

Chronic Polyaromatic Hydrocarbon (PAH) Contamination Is a Marginal Driver for Community Diversity and Prokaryotic Predicted Functioning in Coastal Sediments

Benthic microorganisms are key players in the recycling of organic matter and recalcitrant compounds such as polyaromatic hydrocarbons (PAHs) in coastal sediments. Despite their ecological importance, the response of microbial communities to chronic PAH pollution, one of the major threats to coastal ecosystems, has received very little attention. In one of the largest surveys performed so far on coastal sediments, the diversity and composition of microbial communities inhabiting both chronically contaminated and non-contaminated coastal sediments were investigated using high-throughput sequencing on the 18S and 16S rRNA genes. Prokaryotic alpha-diversity showed significant association with salinity, temperature, and organic carbon content. The effect of particle size distribution was strong on eukaryotic diversity. Similarly to alpha-diversity, beta-diversity patterns were strongly influenced by the environmental filter, while PAHs had no influence on the prokaryotic community structure and a weak impact on the eukaryotic community structure at the continental scale. However, at the regional scale, PAHs became the main driver shaping the structure of bacterial and eukaryotic communities. These patterns were not found for PICRUSt predicted prokaryotic functions, thus indicating some degree of functional redundancy. Eukaryotes presented a greater potential for their use as PAH contamination biomarkers, owing to their stronger response at both regional and continental scales.

Food-Web Complexity in Guaymas Basin Hydrothermal Vents and Cold Seeps

In the Guaymas Basin, the presence of cold seeps and hydrothermal vents in close proximity, similar sedimentary settings and comparable depths offers a unique opportunity to assess and compare the functioning of these deep-sea chemosynthetic ecosystems. The food webs of five seep and four vent assemblages were studied using stable carbon and nitrogen isotope analyses. Although the two ecosystems shared similar potential basal sources, their food webs differed: seeps relied predominantly on methanotrophy and thiotrophy via the Calvin-Benson-Bassham (CBB) cycle and vents on petroleum-derived organic matter and thiotrophy via the CBB and reductive tricarboxylic acid (rTCA) cycles. In contrast to symbiotic species, the heterotrophic fauna exhibited high trophic flexibility among assemblages, suggesting weak trophic links to the metabolic diversity of chemosynthetic primary producers. At both ecosystems, food webs did not appear to be organised through predator-prey links but rather through weak trophic relationships among co-occurring species. Examples of trophic or spatial niche differentiation highlighted the importance of species-sorting processes within chemosynthetic ecosystems. Variability in food web structure, addressed through Bayesian metrics, revealed consistent trends across ecosystems. Food-web complexity significantly decreased with increasing methane concentrations, a common proxy for the intensity of seep and vent fluid fluxes. Although high fluid-fluxes have the potential to enhance primary productivity, they generate environmental constraints that may limit microbial diversity, colonisation of consumers and the structuring role of competitive interactions, leading to an overall reduction of food-web complexity and an increase in trophic redundancy. Heterogeneity provided by foundation species was identified as an additional structuring factor. According to their biological activities, foundation species may have the potential to partly release the competitive pressure within communities of low fluid-flux habitats. Finally, ecosystem functioning in vents and seeps was highly similar despite environmental differences (e.g. physico-chemistry, dominant basal sources) suggesting that ecological niches are not specifically linked to the nature of fluids. This comparison of seep and vent functioning in the Guaymas basin thus provides further supports to the hypothesis of continuity among deep-sea chemosynthetic ecosystems.

Kinematics and Local Motion Planning for Quasi-static Whole-body Mobile Manipulation

This thesis studies mobile robotic manipulators, where one or more robot manipulator arms are integrated with a mobile robotic base. The base could be a wheeled or tracked vehicle, or it might be a multi-limbed locomotor. As robots are increasingly deployed in complex and unstructured environments, the need for mobile manipulation increases. Mobile robotic assistants have the potential to revolutionize human lives in a large variety of settings including home, industrial and outdoor environments.

Mobile Manipulation is the use or study of such mobile robots as they interact with physical objects in their environment. As compared to fixed base manipulators, mobile manipulators can take advantage of the base mechanism’s added degrees of freedom in the task planning and execution process. But their use also poses new problems in the analysis and control of base system stability, and the planning of coordinated base and arm motions. For mobile manipulators to be successfully and efficiently used, a thorough understanding of their kinematics, stability, and capabilities is required. Moreover, because mobile manipulators typically possess a large number of actuators, new and efficient methods to coordinate their large numbers of degrees of freedom are needed to make them practically deployable. This thesis develops new kinematic and stability analyses of mobile manipulation, and new algorithms to efficiently plan their motions.

I first develop detailed and novel descriptions of the kinematics governing the operation of multi- limbed legged robots working in the presence of gravity, and whose limbs may also be simultaneously used for manipulation. The fundamental stance constraint that arises from simple assumptions about friction and the ground contact and feasible motions is derived. Thereafter, a local relationship between joint motions and motions of the robot abdomen and reaching limbs is developed. Baseeon these relationships, one can define and analyze local kinematic qualities including limberness, wrench resistance and local dexterity. While previous researchers have noted the similarity between multi- fingered grasping and quasi-static manipulation, this thesis makes explicit connections between these two problems.

The kinematic expressions form the basis for a local motion planning problem that that determines the joint motions to achieve several simultaneous objectives while maintaining stance stability in the presence of gravity. This problem is translated into a convex quadratic program entitled the balanced priority solution, whose existence and uniqueness properties are developed. This problem is related in spirit to the classical redundancy resoxlution and task-priority approaches. With some simple modifications, this local planning and optimization problem can be extended to handle a large variety of goals and constraints that arise in mobile-manipulation. This local planning problem applies readily to other mobile bases including wheeled and articulated bases. This thesis describes the use of the local planning techniques to generate global plans, as well as for use within a feedback loop. The work in this thesis is motivated in part by many practical tasks involving the Surrogate and RoboSimian robots at NASA/JPL, and a large number of examples involving the two robots, both real and simulated, are provided.

Finally, this thesis provides an analysis of simultaneous force and motion control for multi- limbed legged robots. Starting with a classical linear stiffness relationship, an analysis of this problem for multiple point contacts is described. The local velocity planning problem is extended to include generation of forces, as well as to maintain stability using force-feedback. This thesis also provides a concise, novel definition of static stability, and proves some conditions under which it is satisfied.

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.