876 resultados para Measured signals


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Question: What are the correlations between the degree of drought stress and temperature, and the adoption of specific adaptive strategies by plants in the Mediterranean region? Location: 602 sites across the Mediterranean region. Method: We considered 12 plant morphological and phenological traits, and measured their abundance at the sites as trait scores obtained from pollen percentages. We conducted stepwise regression analyses of trait scores as a function of plant available moisture (α) and winter temperature (MTCO). Results: Patterns in the abundance for the plant traits we considered are clearly determined by α, MTCO or a combination of both. In addition, trends in leaf size, texture, thickness, pubescence and aromatic leaves and other plant level traits such as thorniness and aphylly, vary according to the life form (tree, shrub, forb), the leaf type (broad, needle) and phenology (evergreen, summer-green). Conclusions: Despite conducting this study based on pollen data we have identified ecologically plausible trends in the abundance of traits along climatic gradients. Plant traits other than the usual life form, leaf type and leaf phenology carry strong climatic signals. Generally, combinations of plant traits are more climatically diagnostic than individual traits. The qualitative and quantitative relationships between plant traits and climate parameters established here will help to provide an improved basis for modelling the impact of climate changes on vegetation and form a starting point for a global analysis of pollen-climate relationships

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Cyclamen colchicum has a mixed history in the hands of botanists. This paper examines the genetic identity of a group of wild Cyclamen populations from the Caucasus to discover whther they are Cyclamen colchicum, C. purpurascens or a mixture of the two. The collections supplemented by material collected at the type locality for C. colchicum, proved to be a single but variable genetic group of C. colchicum that was distinct from C. purpurascens.

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We have extensively analysed the interdependence between cloud optical depth, droplet effective radius, liquid water path (LWP) and geometric thickness for stratiform warm clouds using ground-based observations. In particular, this analysis uses cloud optical depths retrieved from untapped solar background signals that are previously unwanted and need to be removed in most lidar applications. Combining these new optical depth retrievals with radar and microwave observations at the Atmospheric Radiation Measurement (ARM) Climate Research Facility in Oklahoma during 2005–2007, we have found that LWP and geometric thickness increase and follow a power-law relationship with cloud optical depth regardless of the presence of drizzle; LWP and geometric thickness in drizzling clouds can be generally 20–40 % and at least 10 % higher than those in non-drizzling clouds, respectively. In contrast, droplet effective radius shows a negative correlation with optical depth in drizzling clouds and a positive correlation in non-drizzling clouds, where, for large optical depths, it asymptotes to 10 μm. This asymptotic behaviour in non-drizzling clouds is found in both the droplet effective radius and optical depth, making it possible to use simple thresholds of optical depth, droplet size, or a combination of these two variables for drizzle delineation. This paper demonstrates a new way to enhance ground-based cloud observations and drizzle delineations using existing lidar networks.

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This paper presents a novel approach to the automatic classification of very large data sets composed of terahertz pulse transient signals, highlighting their potential use in biochemical, biomedical, pharmaceutical and security applications. Two different types of THz spectra are considered in the classification process. Firstly a binary classification study of poly-A and poly-C ribonucleic acid samples is performed. This is then contrasted with a difficult multi-class classification problem of spectra from six different powder samples that although have fairly indistinguishable features in the optical spectrum, they also possess a few discernable spectral features in the terahertz part of the spectrum. Classification is performed using a complex-valued extreme learning machine algorithm that takes into account features in both the amplitude as well as the phase of the recorded spectra. Classification speed and accuracy are contrasted with that achieved using a support vector machine classifier. The study systematically compares the classifier performance achieved after adopting different Gaussian kernels when separating amplitude and phase signatures. The two signatures are presented as feature vectors for both training and testing purposes. The study confirms the utility of complex-valued extreme learning machine algorithms for classification of the very large data sets generated with current terahertz imaging spectrometers. The classifier can take into consideration heterogeneous layers within an object as would be required within a tomographic setting and is sufficiently robust to detect patterns hidden inside noisy terahertz data sets. The proposed study opens up the opportunity for the establishment of complex-valued extreme learning machine algorithms as new chemometric tools that will assist the wider proliferation of terahertz sensing technology for chemical sensing, quality control, security screening and clinic diagnosis. Furthermore, the proposed algorithm should also be very useful in other applications requiring the classification of very large datasets.

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New in-situ aircraft measurements of Saharan dust originating from Mali, Mauritania and Algeria taken during the Fennec 2011 aircraft campaign over a remote part of the Sahara Desert are presented. Size distributions extending to 300 μm are shown, representing measurements extending further into the coarse mode than previously published for airborne Saharan dust. A significant coarse mode was present in the size distribution measurements with effective diameter (deff) from 2.3 to 19.4 μm and coarse mode volume median diameter (dvc) from 5.8 to 45.3 μm. The mean size distribution had a larger relative proportion of coarse mode particles than previous aircraft measurements. The largest particles (with deff >12 μm, or dvc >25 μm) were only encountered within 1 km of the ground. Number concentration, mass loading and extinction coefficient showed inverse relationships to dust age since uplift. Dust particle size showed a weak exponential relationship to dust age. Two cases of freshly uplifted dust showed quite different characteristics of size distribution and number concentration. Single Scattering Albed (SSA) values at 550 nm calculated from the measured size distributions revealed high absorption ranging from 0.70 to 0.97 depending on the refractive index. SSA was found to be strongly related to deff. New instrumentation revealed that direct measurements, behind Rosemount inlets, overestimate SSA by up to 0.11 when deff is greater than 2 μm. This is caused by aircraft inlet inefficiencies and sampling losses. Previous measurements of SSA from aircraft measurements may also have been overestimates for this reason. Radiative transfer calculations indicate that the range of SSAs during Fennec 2011 can lead to underestimates in shortwave atmospheric heating rates by 2.0 to 3.0 times if the coarse mode is neglected. This will have an impact on Saharan atmospheric dynamics and circulation,which should be taken into account by numerical weather prediction and climate models.

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Measurements of the ionospheric E region during total solar eclipses in the period 1932-1999 have been used to investigate the fraction of Extreme Ultra Violet and soft X-ray radiation, phi, that is emitted from the limb corona and chromosphere. The relative apparent sizes of the Moon and the Sun are different for each eclipse, and techniques are presented which correct the measurements and, therefore, allow direct comparisons between different eclipses. The results show that the fraction of ionising radiation emitted by the limb corona has a clear solar cycle variation and that the underlying trend shows this fraction has been increasing since 1932. Data from the SOHO spacecraft are used to study the effects of short-term variability and it is shown that the observed long-term rise in phi has a negligible probability of being a chance occurrence.

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BACKGROUND: Brain inflammation has been recognized as a complex phenomenon with numerous related aspects. In addition to the very well-described neurodegenerative effect of inflammation, several studies suggest that inflammatory signals exert a potentially positive influence on neural stem cell proliferation, migration and differentiation. Tumor necrosis factor alpha (TNF-alpha) is one of the best-characterized mediators of inflammation. To date, conclusions about the action of TNF on neural stem or progenitor cells (NSCs, NPCs) have been conflicting. TNF seems to activate NSC proliferation and to inhibit their differentiation into NPCs. The purpose of the present study was to analyze the molecular signal transduction mechanisms induced by TNF and resulting in NSC proliferation. RESULTS: Here we describe for the first time the TNF-mediated signal transduction cascade in neural stem cells (NSCs) that results in increased proliferation. Moreover, we demonstrate IKK-alpha/beta-dependent proliferation and markedly up-regulated cyclin D1 expression after TNF treatment. The significant increase in proliferation in TNF-treated cells was indicated by increased neurosphere volume, increased bromodeoxyuridin (BrdU) incorporation and a higher total cell number. Furthermore, TNF strongly activated nuclear factor-kappa B (NF-kappaB) as measured by reporter gene assays and by an activity-specific antibody. Proliferation of control and TNF-treated NSCs was strongly inhibited by expression of the NF-kappaB super-repressor IkappaB-AA1. Pharmacological blockade of IkappaB ubiquitin ligase activity led to comparable decreases in NF-kappaB activity and proliferation. In addition, IKK-beta gene product knock-down via siRNA led to diminished NF-kappaB activity, attenuated cyclin D1 expression and finally decreased proliferation. In contrast, TGFbeta-activated kinase 1 (TAK-1) is partially dispensable for TNF-mediated and endogenous proliferation. Understanding stem cell proliferation is crucial for future regenerative and anti-tumor medicine. CONCLUSION: TNF-mediated activation of IKK-beta resulted in activation of NF-kappaB and was followed by up-regulation of the bona-fide target gene cyclin D1. Activation of the canonical NF-kappaB pathway resulted in strongly increased proliferation of NSCs.

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In multiple-input multiple-output (MIMO) radar systems, the transmitters emit orthogonal waveforms to increase the spatial resolution. New frequency hopping (FH) codes based on chaotic sequences are proposed. The chaotic sequences have the characteristics of good encryption, anti-jamming properties and anti-intercept capabilities. The main idea of chaotic FH is based on queuing theory. According to the sensitivity to initial condition, these sequences can achieve good Hamming auto-correlation while also preserving good average correlation. Simulation results show that the proposed FH signals can achieve lower autocorrelation side lobe level and peak cross-correlation level with the increasing of iterations. Compared to the LFM signals, this sequence has higher range-doppler resolution.

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Characterization of neural and hemodynamic biomarkers of epileptic activity that can be measured using noninvasive techniques is fundamental to the accurate identification of the epileptogenic zone (EZ) in the clinical setting. Recently, oscillations at gamma-band frequencies and above (N30 Hz) have been suggested to provide valuable localizing information of the EZ and track cortical activation associated with epileptogenic processes. Although a tight coupling between gamma-band activity and hemodynamic-based signals has been consistently demonstrated in non-pathological conditions, very little is known about whether such a relationship is maintained in epilepsy and the laminar etiology of these signals. Confirmation of this relationship may elucidate the underpinnings of perfusion-based signals in epilepsy and the potential value of localizing the EZ using hemodynamic correlates of pathological rhythms. Here, we use concurrent multi-depth electrophysiology and 2- dimensional optical imaging spectroscopy to examine the coupling between multi-band neural activity and cerebral blood volume (CBV) during recurrent acute focal neocortical seizures in the urethane-anesthetized rat. We show a powerful correlation between gamma-band power (25–90 Hz) and CBV across cortical laminae, in particular layer 5, and a close association between gamma measures and multi-unit activity (MUA). Our findings provide insights into the laminar electrophysiological basis of perfusion-based imaging signals in the epileptic state and may have implications for further research using non-invasive multi-modal techniques to localize epileptogenic tissue

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Objective. Functional near-infrared spectroscopy (fNIRS) is an emerging technique for the in vivo assessment of functional activity of the cerebral cortex as well as in the field of brain–computer interface (BCI) research. A common challenge for the utilization of fNIRS in these areas is a stable and reliable investigation of the spatio-temporal hemodynamic patterns. However, the recorded patterns may be influenced and superimposed by signals generated from physiological processes, resulting in an inaccurate estimation of the cortical activity. Up to now only a few studies have investigated these influences, and still less has been attempted to remove/reduce these influences. The present study aims to gain insights into the reduction of physiological rhythms in hemodynamic signals (oxygenated hemoglobin (oxy-Hb), deoxygenated hemoglobin (deoxy-Hb)). Approach. We introduce the use of three different signal processing approaches (spatial filtering, a common average reference (CAR) method; independent component analysis (ICA); and transfer function (TF) models) to reduce the influence of respiratory and blood pressure (BP) rhythms on the hemodynamic responses. Main results. All approaches produce large reductions in BP and respiration influences on the oxy-Hb signals and, therefore, improve the contrast-to-noise ratio (CNR). In contrast, for deoxy-Hb signals CAR and ICA did not improve the CNR. However, for the TF approach, a CNR-improvement in deoxy-Hb can also be found. Significance. The present study investigates the application of different signal processing approaches to reduce the influences of physiological rhythms on the hemodynamic responses. In addition to the identification of the best signal processing method, we also show the importance of noise reduction in fNIRS data.

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Subdermal magnetic implants originated as an art form in the world of body modification. To date an in depth scientific analysis of the benefits of this implant has yet to be established. This research explores the concept of sensory extension of the tactile sense utilising this form of implantation. This relatively simple procedure enables the tactile sense to respond to static and alternating magnetic fields. This is not to say that the underlying biology of the system has changed; i.e. the concept does not increase our tactile frequency response range or sensitivity to pressure, but now does invoke a perceptual response to a stimulus that is not innately available to humans. Within this research two social surveys have been conducted in order to ascertain one, the social acceptance of the general notion of human enhancement, and two the perceptual experiences of individuals with the magnetic implants themselves. In terms of acceptance to the notion of sensory improvement (via implantation) ~39% of the general population questioned responded positively with a further ~25% of the respondents answering with the indecisive response. Thus with careful dissemination a large proportion of individuals may adopt this technology much like this if it were to become available for consumers. Interestingly of the responses collected from the magnetic implants survey ~60% of the respondents actually underwent the implant for magnetic vision purposes. The main contribution of this research however comes from a series of psychophysical testing. In which 7 subjects with subdermal magnetic implants, were cross compared with 7 subjects that had similar magnets superficially attached to their dermis. The experimentation examined multiple psychometric thresholds of the candidates including intensity, frequency and temporal. Whilst relatively simple, the experimental setup for the perceptual experimentation conducted was novel in that custom hardware and protocols were created in order to determine the subjective thresholds of the individuals. Abstract iv The overall purpose of this research is to utilise this concept in high stress scenarios, such as driving or piloting; whereby alerts and warnings could be relayed to an operator without intruding upon their other (typically overloaded) exterior senses (i.e. the auditory and visual senses). Hence each of the thresholding experiments were designed with the intention of utilising the results in the design of signals for information transfer. The findings from the study show that the implanted group of subjects significantly outperformed the superficial group in the absolute intensity threshold experiment, i.e. the implanted group required significantly less force than the superficial group in order to perceive the stimulus. The results for the frequency difference threshold showed no significant difference in the two groups tested. Interestingly however at low frequencies, i.e. 20 and 50 Hz, the ability of the subjects tested to discriminate frequencies significantly increased with more complex waveforms i.e. square and sawtooth, when compared against the typically used sinewave. Furthermore a novel protocol for establishing the temporal gap detection threshold during a temporal numerosity study has been established in this thesis. This experiment measured the subjects’ capability to correctly determine the number of concatenated signals presented to them whilst the time between the signals, referred to as pulses, tended to zero. A significant finding was that when altering the length of, the frequency of, and the number of cycles of the pulses, the time between pulses for correct recognition altered. This finding will ultimately aid in the design of the tactile alerts for this method of information transfer. Preliminary development work for the use of this method of input to the body, in an automotive scenario, is also presented within this thesis in the form of a driving simulation. The overall goal of which is to present warning alerts to a driver, such as rear-to-end collision, or excessive speeds on roads, in order to prevent incidents and penalties from occurring. Discussion on the broader utility of this implant has been presented, reflecting on its potential use as a basis for vibrotactile, and sensory substitution, devices. This discussion furthers with postulations on its use as a human machine interface, as well as how a similar implant could be used within the ear as a hearing aid device.

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Although the adult brain contains neural stem cells (NSCs) that generate new neurons throughout life, these astrocyte-like populations are restricted to two discrete niches. Despite their terminally differentiated phenotype, adult parenchymal astrocytes can re-acquire NSC-like characteristics following injury, and as such, these 'reactive' astrocytes offer an alternative source of cells for central nervous system (CNS) repair following injury or disease. At present, the mechanisms that regulate the potential of different types of astrocytes are poorly understood. We used in vitro and ex vivo astrocytes to identify candidate pathways important for regulation of astrocyte potential. Using in vitro neural progenitor cell (NPC)-derived astrocytes, we found that exposure of more lineage-restricted astrocytes to either tumor necrosis factor alpha (TNF-α) (via nuclear factor-κB (NFκB)) or the bone morphogenetic protein (BMP) inhibitor, noggin, led to re-acquisition of NPC properties accompanied by transcriptomic and epigenetic changes consistent with a more neurogenic, NPC-like state. Comparative analyses of microarray data from in vitro-derived and ex vivo postnatal parenchymal astrocytes identified several common pathways and upstream regulators associated with inflammation (including transforming growth factor (TGF)-β1 and peroxisome proliferator-activated receptor gamma (PPARγ)) and cell cycle control (including TP53) as candidate regulators of astrocyte phenotype and potential. We propose that inflammatory signalling may control the normal, progressive restriction in potential of differentiating astrocytes as well as under reactive conditions and represent future targets for therapies to harness the latent neurogenic capacity of parenchymal astrocytes.

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Pasture-based ruminant production systems are common in certain areas of the world, but energy evaluation in grazing cattle is performed with equations developed, in their majority, with sheep or cattle fed total mixed rations. The aim of the current study was to develop predictions of metabolisable energy (ME) concentrations in fresh-cut grass offered to non-pregnant non-lactating cows at maintenance energy level, which may be more suitable for grazing cattle. Data were collected from three digestibility trials performed over consecutive grazing seasons. In order to cover a range of commercial conditions and data availability in pasture-based systems, thirty-eight equations for the prediction of energy concentrations and ratios were developed. An internal validation was performed for all equations and also for existing predictions of grass ME. Prediction error for ME using nutrient digestibility was lowest when gross energy (GE) or organic matter digestibilities were used as sole predictors, while the addition of grass nutrient contents reduced the difference between predicted and actual values, and explained more variation. Addition of N, GE and diethyl ether extract (EE) contents improved accuracy when digestible organic matter in DM was the primary predictor. When digestible energy was the primary explanatory variable, prediction error was relatively low, but addition of water-soluble carbohydrates, EE and acid-detergent fibre contents of grass decreased prediction error. Equations developed in the current study showed lower prediction errors when compared with those of existing equations, and may thus allow for an improved prediction of ME in practice, which is critical for the sustainability of pasture-based systems.