156 resultados para Narrow Polydispersity
Resumo:
Data are presented from the EISCAT CP-3-E experiment which show the presence of non-thermal plasma over a range of latitudes. The O+ ion-velocity distribution function is almost toroidal when the electric field reaches values of 125 mV m−1. The ion temperature derived from such data assuming a Maxwellian distribution function will overestimate the true ion temperature when the observing angle is large with respect to the magnetic field, and underestimate the temperature when the aspect angle is small. When the expressions for the distribution function are extended to include mixed ion composition, an improvement is sometimes found in fitting the observed data, and estimates of the composition can be made. Such an analysis suggests that N2+ can occasionally form a significant part of the total ion density in a narrow height region centred at 275 km.
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Recent radar studies of field-perpendicular flows in the auroral ionosphere, in conjunction with observations of the interplanetary medium immediately upstream of the Earth's bow shock, have revealed direct control of dayside convection by the Bz component of the interplanetary magnetic field (IMF). The ionospheric flows begin to respond to both northward and southward turnings of the IMF impinging upon the magnetopause after a delay of only a few minutes in the early afternoon sector, rising to about 15 minutes nearer dawn and dusk. In both the polar cap and the auroral oval, the subsequent rise and decay times are of order 5–10 minutes. We conclude there is very little convection “flywheel” effect in the dayside polar ionosphere and that only newly-opened flux tubes impart significant momentum to the ionosphere, in a relatively narrow region immediately poleward of the cusp. These findings concerning the effects of quasi-steady reconnection have important implications for any ionospheric signatures of transient reconnection which should be considerably shorter-lived than thought hitherto. In order to demonstrate the difficulty of uniquely identifying a Flux Transfer Event (FTE) in ground-based magnetometer data, we present observations of an impulsive signature, identical with that expected for an FTE if data from only one station is studied, following an observed magnetopause compression when the IMF was purely northward. We also report new radar observations of a viscous-like interaction, consistent with an origin on the flanks of the magnetotail and contributing an estimated 15–30kV to the total cross-cap potential during quiet periods.
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In the last decade, the growth of local, site-specific weather forecasts delivered by mobile phone or website represents arguably the fastest change in forecast consumption since the beginning of Television weather forecasts 60 years ago. In this study, a street-interception survey of 274 members of the public a clear first preference for narrow weather forecasts above traditional broad weather forecasts is shown for the first time, with a clear bias towards this preference for users under 40. The impact of this change on the understanding of forecast probability and intensity information is explored. While the correct interpretation of the statement ‘There is a 30% chance of rain tomorrow’ is still low in the cohort, in common with previous studies, a clear impact of age and educational attainment on understanding is shown, with those under 40 and educated to degree level or above more likely to correctly interpret it. The interpretation of rainfall intensity descriptors (‘Light’, ‘Moderate’, ‘Heavy’) by the cohort is shown to be significantly different to official and expert assessment of the same descriptors and to have large variance amongst the cohort. However, despite these key uncertainties, members of the cohort generally seem to make appropriate decisions about rainfall forecasts. There is some evidence that the decisions made are different depending on the communication format used, and the cohort expressed a clear preference for tabular over graphical weather forecast presentation.
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A model based on graph isomorphisms is used to formalize software evolution. Step by step we narrow the search space by an informed selection of the attributes based on the current state-of-the-art in software engineering and generate a seed solution. We then traverse the resulting space using graph isomorphisms and other set operations over the vertex sets. The new solutions will preserve the desired attributes. The goal of defining an isomorphism based search mechanism is to construct predictors of evolution that can facilitate the automation of ’software factory’ paradigm. The model allows for automation via software tools implementing the concepts.
Resumo:
When considering adaptation measures and global climate mitigation goals, stakeholders need regional-scale climate projections, including the range of plausible warming rates. To assist these stakeholders, it is important to understand whether some locations may see disproportionately high or low warming from additional forcing above targets such as 2 K (ref. 1). There is a need to narrow uncertainty2 in this nonlinear warming, which requires understanding how climate changes as forcings increase from medium to high levels. However, quantifying and understanding regional nonlinear processes is challenging. Here we show that regional-scale warming can be strongly superlinear to successive CO2 doublings, using five different climate models. Ensemble-mean warming is superlinear over most land locations. Further, the inter-model spread tends to be amplified at higher forcing levels, as nonlinearities grow—especially when considering changes per kelvin of global warming. Regional nonlinearities in surface warming arise from nonlinearities in global-mean radiative balance, the Atlantic meridional overturning circulation, surface snow/ice cover and evapotranspiration. For robust adaptation and mitigation advice, therefore, potentially avoidable climate change (the difference between business-as-usual and mitigation scenarios) and unavoidable climate change (change under strong mitigation scenarios) may need different analysis methods.
Resumo:
A model based on graph isomorphisms is used to formalize software evolution. Step by step we narrow the search space by an informed selection of the attributes based on the current state-of-the-art in software engineering and generate a seed solution. We then traverse the resulting space using graph isomorphisms and other set operations over the vertex sets. The new solutions will preserve the desired attributes. The goal of defining an isomorphism based search mechanism is to construct predictors of evolution that can facilitate the automation of ’software factory’ paradigm. The model allows for automation via software tools implementing the concepts.
Resumo:
Background Autism Spectrum Conditions (ASC) are neurodevelopmental conditions characterized by difficulties in communication and social interaction, alongside unusually repetitive behaviours and narrow interests. Asperger Syndrome (AS) is one subgroup of ASC and differs from classic autism in that in AS there is no language or general cognitive delay. Genetic, epigenetic and environmental factors are implicated in ASC and genes involved in neural connectivity and neurodevelopment are good candidates for studying the susceptibility to ASC. The aryl-hydrocarbon receptor nuclear translocator 2 (ARNT2) gene encodes a transcription factor involved in neurodevelopmental processes, neuronal connectivity and cellular responses to hypoxia. A mutation in this gene has been identified in individuals with ASC and single nucleotide polymorphisms (SNPs) have been nominally associated with AS and autistic traits in previous studies. Methods In this study, we tested 34 SNPs in ARNT2 for association with AS in 118 cases and 412 controls of Caucasian origin. P values were adjusted for multiple comparisons, and linkage disequilibrium (LD) among the SNPs analysed was calculated in our sample. Finally, SNP annotation allowed functional and structural analyses of the genetic variants in ARNT2. We tested the replicability of our result using the genome-wide association studies (GWAS) database of the Psychiatric Genomics Consortium (PGC). Results We report statistically significant association of rs17225178 with AS. This SNP modifies transcription factor binding sites and regions that regulate the chromatin state in neural cell lines. It is also included in a LD block in our sample, alongside other genetic variants that alter chromatin regulatory regions in neural cells. Conclusions These findings demonstrate that rs17225178 in the ARNT2 gene is associated with AS and support previous studies that pointed out an involvement of this gene in the predisposition to ASC.
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This paper provides a review of the last five years of policymaking in the area of health and safety law; this includes multiple reviews, legislative reform, and the reframing of rhetoric around the issue. It characterises this as a process of social construction of a new ‘universe of meaning’ around health and safety regulation, which provides a basis for a particular, narrow, neoliberal conception of regulation and responsibility to permeate the mainstream. Deliberative and public-facing policymaking processes have been utilised as a key element of this process.
Resumo:
Background Atypical self-processing is an emerging theme in autism research, suggested by lower self-reference effect in memory, and atypical neural responses to visual self-representations. Most research on physical self-processing in autism uses visual stimuli. However, the self is a multimodal construct, and therefore, it is essential to test self-recognition in other sensory modalities as well. Self-recognition in the auditory modality remains relatively unexplored and has not been tested in relation to autism and related traits. This study investigates self-recognition in auditory and visual domain in the general population and tests if it is associated with autistic traits. Methods Thirty-nine neurotypical adults participated in a two-part study. In the first session, individual participant’s voice was recorded and face was photographed and morphed respectively with voices and faces from unfamiliar identities. In the second session, participants performed a ‘self-identification’ task, classifying each morph as ‘self’ voice (or face) or an ‘other’ voice (or face). All participants also completed the Autism Spectrum Quotient (AQ). For each sensory modality, slope of the self-recognition curve was used as individual self-recognition metric. These two self-recognition metrics were tested for association between each other, and with autistic traits. Results Fifty percent ‘self’ response was reached for a higher percentage of self in the auditory domain compared to the visual domain (t = 3.142; P < 0.01). No significant correlation was noted between self-recognition bias across sensory modalities (τ = −0.165, P = 0.204). Higher recognition bias for self-voice was observed in individuals higher in autistic traits (τ AQ = 0.301, P = 0.008). No such correlation was observed between recognition bias for self-face and autistic traits (τ AQ = −0.020, P = 0.438). Conclusions Our data shows that recognition bias for physical self-representation is not related across sensory modalities. Further, individuals with higher autistic traits were better able to discriminate self from other voices, but this relation was not observed with self-face. A narrow self-other overlap in the auditory domain seen in individuals with high autistic traits could arise due to enhanced perceptual processing of auditory stimuli often observed in individuals with autism.
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A combination of structural, physical and computational techniques including powder X-ray and neutron diffraction, SQUID magnetometry, electrical and thermal transport measurements, DFT calculations and 119Sn Mössbauer and X-ray photoelec-tron spectroscopies has been applied to Co3Sn2-xInxS2 (0 ≤ x ≤ 2) in an effort to understand the relationship between metal-atom ordering and physical properties as the Fermi level is systematically varied. Whilst solid solution behavior is found throughout the composition region, powder neutron diffraction reveals that indium preferentially occupies an inter-layer site over an alternative kagome-like intra-layer site. DFT calculations indicate that this ordering, which leads to a lowering of energy, is related to the dif-fering bonding properties of tin and indium. Spectroscopic data suggest that throughout the composition range 0 ≤ x ≤ 2, all ele-ments adopt oxidation states that are significantly reduced from expectations based on formal charges. Chemical substitution ena-bles the electrical transport properties to be controlled through tuning of the Fermi level within a region of the density of states, which comprises narrow bands of predominantly Co d-character. This leads to a compositionally-induced double metal-to-semiconductor-to-metal transition. The marked increase in the Seebeck coefficient as the semiconducting region is approached leads to a substantial improvement in the thermoelectric figure of merit, ZT, which exhibits a maximum of ZT = 0.32 at 673 K. At 425 K, the figure of merit for phases in the region 0.8 ≤ x ≤ 0.85 is amongst the highest reported for sulphide phases, suggesting these materials may have applications in low-grade waste heat recovery.
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This paper reports the first derived thermo-optical properties for vacuum deposited infrared thin films embedded in multilayers. These properties were extracted from the temperature-dependence of manufactured narrow bandpass filters across the 4-17 µm mid-infrared wavelength region. Using a repository of spaceflight multi-cavity bandpass filters, the thermo-optical expansion coefficients of PbTe and ZnSe were determined across an elevated temperature range 20-160 ºC. Embedded ZnSe films showed thermo-optical properties similar to reported bulk values, whilst the embedded PbTe films of lower optical density, deviate from reference literature sources. Detailed knowledge of derived coefficients is essential to the multilayer design of temperature-invariant narrow bandpass filters for use in non-cooled infrared detection systems. We further present manufacture of the first reported temperature-invariant multi-cavity narrow bandpass filter utilizing PbS chalcogenide layer material.
Resumo:
The incorporation of numerical weather predictions (NWP) into a flood warning system can increase forecast lead times from a few hours to a few days. A single NWP forecast from a single forecast centre, however, is insufficient as it involves considerable non-predictable uncertainties and can lead to a high number of false or missed warnings. Weather forecasts using multiple NWPs from various weather centres implemented on catchment hydrology can provide significantly improved early flood warning. The availability of global ensemble weather prediction systems through the ‘THORPEX Interactive Grand Global Ensemble’ (TIGGE) offers a new opportunity for the development of state-of-the-art early flood forecasting systems. This paper presents a case study using the TIGGE database for flood warning on a meso-scale catchment (4062 km2) located in the Midlands region of England. For the first time, a research attempt is made to set up a coupled atmospheric-hydrologic-hydraulic cascade system driven by the TIGGE ensemble forecasts. A probabilistic discharge and flood inundation forecast is provided as the end product to study the potential benefits of using the TIGGE database. The study shows that precipitation input uncertainties dominate and propagate through the cascade chain. The current NWPs fall short of representing the spatial precipitation variability on such a comparatively small catchment, which indicates need to improve NWPs resolution and/or disaggregating techniques to narrow down the spatial gap between meteorology and hydrology. The spread of discharge forecasts varies from centre to centre, but it is generally large and implies a significant level of uncertainties. Nevertheless, the results show the TIGGE database is a promising tool to forecast flood inundation, comparable with that driven by raingauge observation.
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This paper investigates the feasibility of using approximate Bayesian computation (ABC) to calibrate and evaluate complex individual-based models (IBMs). As ABC evolves, various versions are emerging, but here we only explore the most accessible version, rejection-ABC. Rejection-ABC involves running models a large number of times, with parameters drawn randomly from their prior distributions, and then retaining the simulations closest to the observations. Although well-established in some fields, whether ABC will work with ecological IBMs is still uncertain. Rejection-ABC was applied to an existing 14-parameter earthworm energy budget IBM for which the available data consist of body mass growth and cocoon production in four experiments. ABC was able to narrow the posterior distributions of seven parameters, estimating credible intervals for each. ABC’s accepted values produced slightly better fits than literature values do. The accuracy of the analysis was assessed using cross-validation and coverage, currently the best available tests. Of the seven unnarrowed parameters, ABC revealed that three were correlated with other parameters, while the remaining four were found to be not estimable given the data available. It is often desirable to compare models to see whether all component modules are necessary. Here we used ABC model selection to compare the full model with a simplified version which removed the earthworm’s movement and much of the energy budget. We are able to show that inclusion of the energy budget is necessary for a good fit to the data. We show how our methodology can inform future modelling cycles, and briefly discuss how more advanced versions of ABC may be applicable to IBMs. We conclude that ABC has the potential to represent uncertainty in model structure, parameters and predictions, and to embed the often complex process of optimizing an IBM’s structure and parameters within an established statistical framework, thereby making the process more transparent and objective.
Resumo:
Direct effects of soil or its constituents on human health are through its ingestion, inhalation or absorption. The soil contains many infectious organisms that may enter the human body through these pathways, but it also provides organisms on which our earliest antibiotics are based. Indirect effects of soil arise from the quantity and quality of food that humans consume. Trace elements can have both beneficial and toxic effects on humans, especially where the range for optimal intake is narrow. We focus on four trace elements (iodine, iron, selenium and zinc) whose deficiencies have substantial effects on human health. As the world’s population increases issues of food security become more pressing, as does the need to sustain soil fertility and minimize its degradation. Lack of adequate food and food of poor nutritional quality lead to differing degrees of under-nutrition, which in turn causes ill health. Soil and land are finite resources and agricultural land is under severe competition from other uses. Relationships between soil and health are often difficult to extricate because of the many confounding factors present. Nevertheless, recent scientific understanding of soil processes and factors that affect human health are enabling greater insight into the effects of soil on our health. Multidisciplinary research that includes soil science, agronomy, agricultural sustainability, toxicology, epidemiology and the medical sciences will facilitate the discovery of new antibiotics, a greater understanding of how materials added to soil used for food production affect health and deciphering of the complex relationships between soil and human health.
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Observations have been obtained within an intense (precipitation rates > 50 mm h−1 ) narrow cold-frontal rainband (NCFR) embedded within a broader region of stratiform precipitation. In situ data were obtained from an aircraft which flew near a steerable dual-polarisation Doppler radar. The observations were obtained to characterise the microphysical properties of cold frontal clouds, with an emphasis on ice and precipitation formation and development. Primary ice nucleation near cloud top (−55◦ C) appeared to be enhanced by convective features. However, ice multiplication led to the largest ice particle number concentrations being observed at relatively high temperatures (> −10◦ C). The multiplication process (most likely rime splintering) occurs when stratiform precipitation interacts with supercooled water generated in the NCFR. Graupel was notably absent in the data obtained. Ice multiplication processes are known to have a strong impact in glaciating isolated convective clouds, but have rarely been studied within larger organised convective systems such as NCFRs. Secondary ice particles will impact on precipitation formation and cloud dynamics due to their relatively small size and high number density. Further modelling studies are required to quantify the effects of rime splintering on precipitation and dynamics in frontal rainbands. Available parametrizations used to diagnose the particle size distributions do not account for the influence of ice multiplication. This deficiency in parametrizations is likely to be important in some cases for modelling the evolution of cloud systems and the precipitation formation. Ice multiplication has significant impact on artefact removal from in situ particle imaging probes.