Paleoenvironments and Geochemical Signals from the Late Barremian to the Middle Aptian in a Tethyan Marginal Basin, Northeast Spain: Implications for Carbon Sequestration in Restricted Basins

The hallmark of oceanic anoxic event 1a (OAE1a) (early Aptian ~125 Ma) corresponds to worldwide deposition of black shales with total organic carbon (TOC) content > 2% and a d13C positive excursion up to ~5‰. OAE1a has been related to large igneous province volcanism and dissociation of methane hydrates during the Lower Cretaceous. However, the occurrence of atypical, coeval and diachronous organic-rich deposits associated with OAE1a, which are also characterized by positive spikes of the d13C in epicontinental to restricted marine environments of the Tethys Ocean, indicates localized responses decoupled from complex global forcing factors. The present research is a high-resolution, multiproxy approach to assess the paleoenvironmental conditions that led to enhanced carbon sequestration from the late Barremian to the middle Aptian in a restricted, Tethyan marginal basin prior to and during OAE1a. I studied the lower 240 m of the El Pui section, Organyà Basin, Spanish Pyrenees. The basin developed as the result of extensional tectonism linked to the opening of the Atlantic Ocean. At the field scale the section consists of a sequence of alternating beds of cm – m-scale, medium-gray to grayish-black limestones and marlstones with TOC up to ~4%. The results indicate that the lowest 85 m of the section, from latest Barremian –earliest Aptian, characterize a deepening phase of the basin concomitant with sustained riverine flux and intensified primary productivity. These changes induced a shift in the sedimentation pattern and decreased the oxygen levels in the water column through organic matter respiration and limited ventilation of the basin. The upper 155 m comprising the earliest – late-early Aptian document the occurrence of OAE1a and its associated geochemical signatures (TOC up to 3% and a positive shift in d13C of ~5‰). However, a low enrichment of redox-sensitive trace elements indicates that the basin did not achieve anoxic conditions. The results also suggest that a shallower-phase of the basin, coeval with platform progradation, may have increased ventilation of the basin at the same time that heightened sedimentation rates and additional input of organic matter from terrestrial sources increased the burial and preservation rate of TOC in the sediment.

Harnessing bacterial signals for suppression of biofilm formation in the nosocomial fungal pathogen Aspergillus fumigatus

Faced with the continued emergence of antibiotic resistance to all known classes of antibiotics, a paradigm shift in approaches toward antifungal therapeutics is required. Well characterized in a broad spectrum of bacterial and fungal pathogens, biofilms are a key factor in limiting the effectiveness of conventional antibiotics. Therefore, therapeutics such as small molecules that prevent or disrupt biofilm formation would render pathogens susceptible to clearance by existing drugs. This is the first report describing the effect of the Pseudomonas aeruginosa alkylhydroxyquinolone interkingdom signal molecules 2-heptyl-3-hydroxy-4-quinolone and 2-heptyl-4-quinolone on biofilm formation in the important fungal pathogen Aspergillus fumigatus. Decoration of the anthranilate ring on the quinolone framework resulted in significant changes in the capacity of these chemical messages to suppress biofilm formation. Addition of methoxy or methyl groups at the C5–C7 positions led to retention of anti-biofilm activity, in some cases dependent on the alkyl chain length at position C2. In contrast, halogenation at either the C3 or C6 positions led to loss of activity, with one notable exception. Microscopic staining provided key insights into the structural impact of the parent and modified molecules, identifying lead compounds for further development.

Singularity and multifractal characterization of signals with wavelets. Application to clay soil images

In the field of multiscale analysis of signals, including images, the wavelet transform is one of the most attractive and powerful tool due to its ability to focus on signals structures at different scales. Wavelet Transform at different scales is successfully applied to image characterization (which can be applied to a watermarking scheme) and multiscale singularity detection and processing. In this work we show further research of computation of multifractals properties such as the multifractal spectrum (D(alpha)) applied to dye stained images of natural terrain. This can be useful for statically describing preferential flow path geometry.

Applications of perceptual sparse representation (Spikegram) for copyright protection of audio signals

Chaque année, le piratage mondial de la musique coûte plusieurs milliards de dollars en pertes économiques, pertes d’emplois et pertes de gains des travailleurs ainsi que la perte de millions de dollars en recettes fiscales. La plupart du piratage de la musique est dû à la croissance rapide et à la facilité des technologies actuelles pour la copie, le partage, la manipulation et la distribution de données musicales [Domingo, 2015], [Siwek, 2007]. Le tatouage des signaux sonores a été proposé pour protéger les droit des auteurs et pour permettre la localisation des instants où le signal sonore a été falsifié. Dans cette thèse, nous proposons d’utiliser la représentation parcimonieuse bio-inspirée par graphe de décharges (spikegramme), pour concevoir une nouvelle méthode permettant la localisation de la falsification dans les signaux sonores. Aussi, une nouvelle méthode de protection du droit d’auteur. Finalement, une nouvelle attaque perceptuelle, en utilisant le spikegramme, pour attaquer des systèmes de tatouage sonore. Nous proposons tout d’abord une technique de localisation des falsifications (‘tampering’) des signaux sonores. Pour cela nous combinons une méthode à spectre étendu modifié (‘modified spread spectrum’, MSS) avec une représentation parcimonieuse. Nous utilisons une technique de poursuite perceptive adaptée (perceptual marching pursuit, PMP [Hossein Najaf-Zadeh, 2008]) pour générer une représentation parcimonieuse (spikegramme) du signal sonore d’entrée qui est invariante au décalage temporel [E. C. Smith, 2006] et qui prend en compte les phénomènes de masquage tels qu’ils sont observés en audition. Un code d’authentification est inséré à l’intérieur des coefficients de la représentation en spikegramme. Puis ceux-ci sont combinés aux seuils de masquage. Le signal tatoué est resynthétisé à partir des coefficients modifiés, et le signal ainsi obtenu est transmis au décodeur. Au décodeur, pour identifier un segment falsifié du signal sonore, les codes d’authentification de tous les segments intacts sont analysés. Si les codes ne peuvent être détectés correctement, on sait qu’alors le segment aura été falsifié. Nous proposons de tatouer selon le principe à spectre étendu (appelé MSS) afin d’obtenir une grande capacité en nombre de bits de tatouage introduits. Dans les situations où il y a désynchronisation entre le codeur et le décodeur, notre méthode permet quand même de détecter des pièces falsifiées. Par rapport à l’état de l’art, notre approche a le taux d’erreur le plus bas pour ce qui est de détecter les pièces falsifiées. Nous avons utilisé le test de l’opinion moyenne (‘MOS’) pour mesurer la qualité des systèmes tatoués. Nous évaluons la méthode de tatouage semi-fragile par le taux d’erreur (nombre de bits erronés divisé par tous les bits soumis) suite à plusieurs attaques. Les résultats confirment la supériorité de notre approche pour la localisation des pièces falsifiées dans les signaux sonores tout en préservant la qualité des signaux. Ensuite nous proposons une nouvelle technique pour la protection des signaux sonores. Cette technique est basée sur la représentation par spikegrammes des signaux sonores et utilise deux dictionnaires (TDA pour Two-Dictionary Approach). Le spikegramme est utilisé pour coder le signal hôte en utilisant un dictionnaire de filtres gammatones. Pour le tatouage, nous utilisons deux dictionnaires différents qui sont sélectionnés en fonction du bit d’entrée à tatouer et du contenu du signal. Notre approche trouve les gammatones appropriés (appelés noyaux de tatouage) sur la base de la valeur du bit à tatouer, et incorpore les bits de tatouage dans la phase des gammatones du tatouage. De plus, il est montré que la TDA est libre d’erreur dans le cas d’aucune situation d’attaque. Il est démontré que la décorrélation des noyaux de tatouage permet la conception d’une méthode de tatouage sonore très robuste. Les expériences ont montré la meilleure robustesse pour la méthode proposée lorsque le signal tatoué est corrompu par une compression MP3 à 32 kbits par seconde avec une charge utile de 56.5 bps par rapport à plusieurs techniques récentes. De plus nous avons étudié la robustesse du tatouage lorsque les nouveaux codec USAC (Unified Audion and Speech Coding) à 24kbps sont utilisés. La charge utile est alors comprise entre 5 et 15 bps. Finalement, nous utilisons les spikegrammes pour proposer trois nouvelles méthodes d’attaques. Nous les comparons aux méthodes récentes d’attaques telles que 32 kbps MP3 et 24 kbps USAC. Ces attaques comprennent l’attaque par PMP, l’attaque par bruit inaudible et l’attaque de remplacement parcimonieuse. Dans le cas de l’attaque par PMP, le signal de tatouage est représenté et resynthétisé avec un spikegramme. Dans le cas de l’attaque par bruit inaudible, celui-ci est généré et ajouté aux coefficients du spikegramme. Dans le cas de l’attaque de remplacement parcimonieuse, dans chaque segment du signal, les caractéristiques spectro-temporelles du signal (les décharges temporelles ;‘time spikes’) se trouvent en utilisant le spikegramme et les spikes temporelles et similaires sont remplacés par une autre. Pour comparer l’efficacité des attaques proposées, nous les comparons au décodeur du tatouage à spectre étendu. Il est démontré que l’attaque par remplacement parcimonieux réduit la corrélation normalisée du décodeur de spectre étendu avec un plus grand facteur par rapport à la situation où le décodeur de spectre étendu est attaqué par la transformation MP3 (32 kbps) et 24 kbps USAC.

Mathematical methods to analyze and interpret calcium signals of astrocytes

Astrocytes are the most numerous glial cell type in the mammalian brain and permeate the entire CNS interacting with neurons, vasculature, and other glial cells. Astrocytes display intracellular calcium signals that encode information about local synaptic function, distributed network activity, and high-level cognitive functions. Several studies have investigated the calcium dynamics of astrocytes in sensory areas and have shown that these cells can encode sensory stimuli. Nevertheless, only recently the neuro-scientific community has focused its attention on the role and functions of astrocytes in associative areas such as the hippocampus. In our first study, we used the information theory formalism to show that astrocytes in the CA1 area of the hippocampus recorded with 2-photon fluorescence microscopy during spatial navigation encode spatial information that is complementary and synergistic to information encoded by nearby "place cell" neurons. In our second study, we investigated various computational aspects of applying the information theory formalism to astrocytic calcium data. For this reason, we generated realistic simulations of calcium signals in astrocytes to determine optimal hyperparameters and procedures of information measures and applied them to real astrocytic calcium imaging data. Calcium signals of astrocytes are characterized by complex spatiotemporal dynamics occurring in subcellular parcels of the astrocytic domain which makes studying these cells in 2-photon calcium imaging recordings difficult. However, current analytical tools which identify the astrocytic subcellular regions are time consuming and extensively rely on user-defined parameters. Here, we present Rapid Astrocytic calcium Spatio-Temporal Analysis (RASTA), a novel machine learning algorithm for spatiotemporal semantic segmentation of 2-photon calcium imaging recordings of astrocytes which operates without human intervention. We found that RASTA provided fast and accurate identification of astrocytic cell somata, processes, and cellular domains, extracting calcium signals from identified regions of interest across individual cells and populations of hundreds of astrocytes recorded in awake mice.

Deploying and processing neural representations of signals

Neural representations (NR) have emerged in the last few years as a powerful tool to represent signals from several domains, such as images, 3D shapes, or audio. Indeed, deep neural networks have been shown capable of approximating continuous functions that describe a given signal with theoretical infinite resolution. This finding allows obtaining representations whose memory footprint is fixed and decoupled from the resolution at which the underlying signal can be sampled, something that is not possible with traditional discrete representations, e.g., grids of pixels for images or voxels for 3D shapes. During the last two years, many techniques have been proposed to improve the capability of NR to approximate high-frequency details and to make the optimization procedures required to obtain NR less demanding both in terms of time and data requirements, motivating many researchers to deploy NR as the main form of data representation for complex pipelines. Following this line of research, we first show that NR can approximate precisely Unsigned Distance Functions, providing an effective way to represent garments that feature open 3D surfaces and unknown topology. Then, we present a pipeline to obtain in a few minutes a compact Neural Twin® for a given object, by exploiting the recent advances in modeling neural radiance fields. Furthermore, we move a step in the direction of adopting NR as a standalone representation, by considering the possibility of performing downstream tasks by processing directly the NR weights. We first show that deep neural networks can be compressed into compact latent codes. Then, we show how this technique can be exploited to perform deep learning on implicit neural representations (INR) of 3D shapes, by only looking at the weights of the networks.

Motor Unit Spike Trains Recontruction from sEMG Signals for Gesture Classification on a Low-Power Processing Platform

Hand gesture recognition based on surface electromyography (sEMG) signals is a promising approach for the development of intuitive human-machine interfaces (HMIs) in domains such as robotics and prosthetics. The sEMG signal arises from the muscles' electrical activity, and can thus be used to recognize hand gestures. The decoding from sEMG signals to actual control signals is non-trivial; typically, control systems map sEMG patterns into a set of gestures using machine learning, failing to incorporate any physiological insight. This master thesis aims at developing a bio-inspired hand gesture recognition system based on neuromuscular spike extraction rather than on simple pattern recognition. The system relies on a decomposition algorithm based on independent component analysis (ICA) that decomposes the sEMG signal into its constituent motor unit spike trains, which are then forwarded to a machine learning classifier. Since ICA does not guarantee a consistent motor unit ordering across different sessions, 3 approaches are proposed: 2 ordering criteria based on firing rate and negative entropy, and a re-calibration approach that allows the decomposition model to retain information about previous sessions. Using a multilayer perceptron (MLP), the latter approach results in an accuracy up to 99.4% in a 1-subject, 1-degree of freedom scenario. Afterwards, the decomposition and classification pipeline for inference is parallelized and profiled on the PULP platform, achieving a latency < 50 ms and an energy consumption < 1 mJ. Both the classification models tested (a support vector machine and a lightweight MLP) yielded an accuracy > 92% in a 1-subject, 5-classes (4 gestures and rest) scenario. These results prove that the proposed system is suitable for real-time execution on embedded platforms and also capable of matching the accuracy of state-of-the-art approaches, while also giving some physiological insight on the neuromuscular spikes underlying the sEMG.

Acquisition of Vibration Signals for Predictive Maintenance: a Practical Case

As predictive maintenance becomes more and more relevant in industrial environment, the possible range of applications for this maintenance strategy grows. The progresses in components technology and their reduction in price, together with the late years' advances in machine learning and in computational power, are making the implementation of predictive maintenance possible in plants where it would have previously been unreasonably costly. This is leading major pharmaceutical industries to explore the possibility of the application of condition monitoring systems on progressively less and less critical equipment. The focus of this thesis is on the implementation of a system to gather vibrational data from the motors installed in a pre-existing machine using off-the-shelf components. The final goal for the system is to provide the necessary vibration data, in the form of frequency spectra, to a machine learning system developed by IMA Digital, which will be leveraging such data to predict possible upcoming faults and to give the final client all the information necessary to plan maintenance activity according to the estimated machine condition.

Hypothalamic Inflammation And The Central Nervous System Control Of Energy Homeostasis.

The control of energy homeostasis relies on robust neuronal circuits that regulate food intake and energy expenditure. Although the physiology of these circuits is well understood, the molecular and cellular response of this program to chronic diseases is still largely unclear. Hypothalamic inflammation has emerged as a major driver of energy homeostasis dysfunction in both obesity and anorexia. Importantly, this inflammation disrupts the action of metabolic signals promoting anabolism or supporting catabolism. In this review, we address the evidence that favors hypothalamic inflammation as a factor that resets energy homeostasis in pathological states.

Interplay Between Cell Growth And Cell Cycle In Plants.

The growth of organs and whole plants depends on both cell growth and cell-cycle progression, but the interaction between both processes is poorly understood. In plants, the balance between growth and cell-cycle progression requires coordinated regulation of four different processes: macromolecular synthesis (cytoplasmic growth), turgor-driven cell-wall extension, mitotic cycle, and endocycle. Potential feedbacks between these processes include a cell-size checkpoint operating before DNA synthesis and a link between DNA contents and maximum cell size. In addition, key intercellular signals and growth regulatory genes appear to target at the same time cell-cycle and cell-growth functions. For example, auxin, gibberellin, and brassinosteroid all have parallel links to cell-cycle progression (through S-phase Cyclin D-CDK and the anaphase-promoting complex) and cell-wall functions (through cell-wall extensibility or microtubule dynamics). Another intercellular signal mediated by microtubule dynamics is the mechanical stress caused by growth of interconnected cells. Superimposed on developmental controls, sugar signalling through the TOR pathway has recently emerged as a central control point linking cytoplasmic growth, cell-cycle and cell-wall functions. Recent progress in quantitative imaging and computational modelling will facilitate analysis of the multiple interconnections between plant cell growth and cell cycle and ultimately will be required for the predictive manipulation of plant growth.

[the Perception Of Behavior Related To Mindfulness And The Brazilian Version Of The Freiburg Mindfulness Inventory].

Mindfulness is a practice and a form of consciousness which has been the basis for innovative interventions in care and health promotion. This study presents mindfulness, describes and discusses the process of cultural adaptation of The Freiburg Mindfulness Inventory (FMI) to Brazilian Portuguese. From the original version of this pioneering instrument for assessing mindfulness two translations and two back-translations were made. These were evaluated by a committee of 14 experts (Buddhists, linguists, health professionals), who helped to create two versions for the first pre-test, based on which suggestions were made by a sample of 41 people of the population through interviews. Considering the difficulties in understanding the concepts that are unfamiliar to the Brazilian culture, a new version was prepared with additional explanations, which underwent a further evaluation of the experts and a second pre-test with 72 people. This process aimed at addressing the limitations and challenges of evaluating mindfulness in a country of western culture through a self-report instrument based on Buddhist psychology. With appropriate levels of clarity and equivalence with the original instrument, the Freiburg Mindfulness Inventory adapted for Brazil is presented.

High-resolution Transcript Profiling Of The Atypical Biotrophic Interaction Between Theobroma Cacao And The Fungal Pathogen Moniliophthora Perniciosa.

Witches' broom disease (WBD), caused by the hemibiotrophic fungus Moniliophthora perniciosa, is one of the most devastating diseases of Theobroma cacao, the chocolate tree. In contrast to other hemibiotrophic interactions, the WBD biotrophic stage lasts for months and is responsible for the most distinctive symptoms of the disease, which comprise drastic morphological changes in the infected shoots. Here, we used the dual RNA-seq approach to simultaneously assess the transcriptomes of cacao and M. perniciosa during their peculiar biotrophic interaction. Infection with M. perniciosa triggers massive metabolic reprogramming in the diseased tissues. Although apparently vigorous, the infected shoots are energetically expensive structures characterized by the induction of ineffective defense responses and by a clear carbon deprivation signature. Remarkably, the infection culminates in the establishment of a senescence process in the host, which signals the end of the WBD biotrophic stage. We analyzed the pathogen's transcriptome in unprecedented detail and thereby characterized the fungal nutritional and infection strategies during WBD and identified putative virulence effectors. Interestingly, M. perniciosa biotrophic mycelia develop as long-term parasites that orchestrate changes in plant metabolism to increase the availability of soluble nutrients before plant death. Collectively, our results provide unique insight into an intriguing tropical disease and advance our understanding of the development of (hemi)biotrophic plant-pathogen interactions.

Microsatellite In Aeschynomene Falcata (leguminosae): Diversity, Cross-amplification, And Chromosome Localization.

Aeschynomene falcata is an important forage species; however, because of low seed production, it is underutilized as forage species. Aeschynomene is a polyphyletic genus with a challenging taxonomic position. Two subgenera have been proposed, and it is suggested that Aeschynomene can be split in 2 genera. Thus, new markers, such as microsatellite sequences, are desirable for improving breeding programs for A. falcata. Based on transferability and in situ localization, these microsatellite sequences can be applied as chromosome markers in the genus Aeschynomene and closely related genera. Here, we report the first microsatellite library developed for this genus; 11 microsatellites were characterized, with observed and expected heterozygosities ranging from 0.0000 to 0.7143 and from 0.1287 to 0.8360, respectively. Polymorphic information content varied from 0.1167 to 0.7786. The departure from Hardy-Weinberg equilibrium may have resulted from frequent autogamy, which is characteristic of A. falcata. Of the 11 microsatellites, 9 loci were cross-amplified in A. brevipes and A. paniculata and 7 in Dalbergia nigra and Machaerium vestitum. Five of these 7 cross-amplified microsatellites were applied as probes during the in situ hybridization assay and 2 showed clear signals on A. falcata chromosomes, ensuring their viability as chromosome markers.

Structural And Biomechanical Changes In The Achilles Tendon After Chronic Treatment With Statins.

Cases of tendinopathy and tendon ruptures have been reported as side effects associated with statin therapy. This work assessed possible changes in the structural and biomechanical properties of the tendons after chronic treatment with statins. Wistar rats were divided into the following groups: treated with atorvastatin (A-20 and A-80), simvastatin (S-20 and S-80) and the group that received no treatment (C). The doses of statins were calculated using allometric scaling, based on the doses of 80 mg/day and 20 mg/day recommended for humans. The morphological aspect of the tendons in A-20, S-20 and S-80 presented signals consistent with degeneration. Both the groups A-80 and S-80 showed a less pronounced metachromasia in the compression region of the tendons. Measurements of birefringence showed that A-20, A-80 and S-80 groups had a lower degree of organization of the collagen fibers. In all of the groups treated with statins, the thickness of the epitenon was thinner when compared to the C group. In the biomechanical tests the tendons of the groups A-20, A-80 and S-20 were less resistant to rupture. Therefore, statins affected the organization of the collagen fibers and decreased the biomechanical strength of the tendons, making them more predisposed to ruptures.

Exercise Increases Pancreatic β-cell Viability In A Model Of Type 1 Diabetes Through Il-6 Signaling.

Type 1 diabetes (T1D) is provoked by an autoimmune assault against pancreatic β cells. Exercise training enhances β-cell mass in T1D. Here, we investigated how exercise signals β cells in T1D condition. For this, we used several approaches. Wild-type and IL-6 knockout (KO) C57BL/6 mice were exercised. Afterward, islets from control and trained mice were exposed to inflammatory cytokines (IL-1β plus IFN-γ). Islets from control mice and β-cell lines (INS-1E and MIN6) were incubated with serum from control or trained mice or medium obtained from 5-aminoimidazole-4 carboxamide1-β-d-ribofuranoside (AICAR)-treated C2C12 skeletal muscle cells. Subsequently, islets and β cells were exposed to IL-1β plus IFN-γ. Proteins were assessed by immunoblotting, apoptosis was determined by DNA-binding dye propidium iodide fluorescence, and NO(•) was estimated by nitrite. Exercise reduced 25, 75, and 50% of the IL-1β plus IFN-γ-induced iNOS, nitrite, and cleaved caspase-3 content, respectively, in pancreatic islets. Serum from trained mice and medium from AICAR-treated C2C12 cells reduced β-cell death, induced by IL-1β plus IFN-γ treatment, in 15 and 38%, respectively. This effect was lost in samples treated with IL-6 inhibitor or with serum from exercised IL-6 KO mice. In conclusion, muscle contraction signals β-cell survival in T1D through IL-6.-Paula, F. M. M., Leite, N. C., Vanzela, E. C., Kurauti, M. A., Freitas-Dias, R., Carneiro, E. M., Boschero, A. C., and Zoppi, C. C. Exercise increases pancreatic β-cell viability in a model of type 1 diabetes through IL-6 signaling.