839 resultados para spontaneous generation


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Human ICT implants, such as RFID implants, cochlear implants, cardiac pacemakers, Deep Brain Stimulation, bionic limbs connected to the nervous system, and networked cognitive prostheses, are becoming increasingly complex. With ever-growing data processing functionalities in these implants, privacy and security become vital concerns. Electronic attacks on human ICT implants can cause significant harm, both to implant subjects and to their environment. This paper explores the vulnerabilities which human implants pose to crime victimisation in light of recent technological developments, and analyses how the law can deal with emerging challenges of what may well become the next generation of cybercrime: attacks targeted at technology implanted in the human body. After a state-of-the-art description of relevant types of human implants and a discussion how these implants challenge existing perceptions of the human body, we describe how various modes of attacks, such as sniffing, hacking, data interference, and denial of service, can be committed against implants. Subsequently, we analyse how these attacks can be assessed under current substantive and procedural criminal law, drawing on examples from UK and Dutch law. The possibilities and limitations of cybercrime provisions (eg, unlawful access, system interference) and bodily integrity provisions (eg, battery, assault, causing bodily harm) to deal with human-implant attacks are analysed. Based on this assessment, the paper concludes that attacks on human implants are not only a new generation in the evolution of cybercrime, but also raise fundamental questions on how criminal law conceives of attacks. Traditional distinctions between physical and non-physical modes of attack, between human bodies and things, between exterior and interior of the body need to be re-interpreted in light of developments in human implants. As the human body and technology become increasingly intertwined, cybercrime legislation and body-integrity crime legislation will also become intertwined, posing a new puzzle that legislators and practitioners will sooner or later have to solve.

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The MATLAB model is contained within the compressed folders (versions are available as .zip and .tgz). This model uses MERRA reanalysis data (>34 years available) to estimate the hourly aggregated wind power generation for a predefined (fixed) distribution of wind farms. A ready made example is included for the wind farm distribution of Great Britain, April 2014 ("CF.dat"). This consists of an hourly time series of GB-total capacity factor spanning the period 1980-2013 inclusive. Given the global nature of reanalysis data, the model can be applied to any specified distribution of wind farms in any region of the world. Users are, however, strongly advised to bear in mind the limitations of reanalysis data when using this model/data. This is discussed in our paper: Cannon, Brayshaw, Methven, Coker, Lenaghan. "Using reanalysis data to quantify extreme wind power generation statistics: a 33 year case study in Great Britain". Submitted to Renewable Energy in March, 2014. Additional information about the model is contained in the model code itself, in the accompanying ReadMe file, and on our website: http://www.met.reading.ac.uk/~energymet/data/Cannon2014/

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MAGIC populations represent one of a new generation of crop genetic mapping resources combining high genetic recombination and diversity. We describe the creation and validation of an eight-parent MAGIC population consisting of 1091 F7 lines of winter-sown wheat (Triticum aestivum L.). Analyses based on genotypes from a 90,000-single nucleotide polymorphism (SNP) array find the population to be well-suited as a platform for fine-mapping quantitative trait loci (QTL) and gene isolation. Patterns of linkage disequilibrium (LD) show the population to be highly recombined; genetic marker diversity among the founders was 74% of that captured in a larger set of 64 wheat varieties, and 54% of SNPs segregating among the 64 lines also segregated among the eight founder lines. In contrast, a commonly used reference bi-parental population had only 54% of the diversity of the 64 varieties with 27% of SNPs segregating. We demonstrate the potential of this MAGIC resource by identifying a highly diagnostic marker for the morphological character "awn presence/absence" and independently validate it in an association-mapping panel. These analyses show this large, diverse, and highly recombined MAGIC population to be a powerful resource for the genetic dissection of target traits in wheat, and it is well-placed to efficiently exploit ongoing advances in phenomics and genomics. Genetic marker and trait data, together with instructions for access to seed, are available at http://www.niab.com/MAGIC/.

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We utilize energy budget diagnostics from the Coupled Model Intercomparison Project phase 5 (CMIP5) to evaluate the models' climate forcing since preindustrial times employing an established regression technique. The climate forcing evaluated this way, termed the adjusted forcing (AF), includes a rapid adjustment term associated with cloud changes and other tropospheric and land-surface changes. We estimate a 2010 total anthropogenic and natural AF from CMIP5 models of 1.9 ± 0.9 W m−2 (5–95% range). The projected AF of the Representative Concentration Pathway simulations are lower than their expected radiative forcing (RF) in 2095 but agree well with efficacy weighted forcings from integrated assessment models. The smaller AF, compared to RF, is likely due to cloud adjustment. Multimodel time series of temperature change and AF from 1850 to 2100 have large intermodel spreads throughout the period. The intermodel spread of temperature change is principally driven by forcing differences in the present day and climate feedback differences in 2095, although forcing differences are still important for model spread at 2095. We find no significant relationship between the equilibrium climate sensitivity (ECS) of a model and its 2003 AF, in contrast to that found in older models where higher ECS models generally had less forcing. Given the large present-day model spread, there is no indication of any tendency by modelling groups to adjust their aerosol forcing in order to produce observed trends. Instead, some CMIP5 models have a relatively large positive forcing and overestimate the observed temperature change.

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With a rapidly increasing fraction of electricity generation being sourced from wind, extreme wind power generation events such as prolonged periods of low (or high) generation and ramps in generation, are a growing concern for the efficient and secure operation of national power systems. As extreme events occur infrequently, long and reliable meteorological records are required to accurately estimate their characteristics. Recent publications have begun to investigate the use of global meteorological “reanalysis” data sets for power system applications, many of which focus on long-term average statistics such as monthly-mean generation. Here we demonstrate that reanalysis data can also be used to estimate the frequency of relatively short-lived extreme events (including ramping on sub-daily time scales). Verification against 328 surface observation stations across the United Kingdom suggests that near-surface wind variability over spatiotemporal scales greater than around 300 km and 6 h can be faithfully reproduced using reanalysis, with no need for costly dynamical downscaling. A case study is presented in which a state-of-the-art, 33 year reanalysis data set (MERRA, from NASA-GMAO), is used to construct an hourly time series of nationally-aggregated wind power generation in Great Britain (GB), assuming a fixed, modern distribution of wind farms. The resultant generation estimates are highly correlated with recorded data from National Grid in the recent period, both for instantaneous hourly values and for variability over time intervals greater than around 6 h. This 33 year time series is then used to quantify the frequency with which different extreme GB-wide wind power generation events occur, as well as their seasonal and inter-annual variability. Several novel insights into the nature of extreme wind power generation events are described, including (i) that the number of prolonged low or high generation events is well approximated by a Poission-like random process, and (ii) whilst in general there is large seasonal variability, the magnitude of the most extreme ramps is similar in both summer and winter. An up-to-date version of the GB case study data as well as the underlying model are freely available for download from our website: http://www.met.reading.ac.uk/~energymet/data/Cannon2014/.

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Using data from the EISCAT (European Incoherent Scatter) VHF and CUTLASS (Co-operative UK Twin- Located Auroral Sounding System) HF radars, we study the formation of ionospheric polar cap patches and their relationship to the magnetopause reconnection pulses identified in the companion paper by Lockwood et al. (2005). It is shown that the poleward-moving, high-concentration plasma patches observed in the ionosphere by EISCAT on 23 November 1999, as reported by Davies et al. (2002), were often associated with corresponding reconnection rate pulses. However, not all such pulses generated a patch and only within a limited MLT range (11:00–12:00 MLT) did a patch result from a reconnection pulse. Three proposed mechanisms for the production of patches, and of the concentration minima that separate them, are analysed and evaluated: (1) concentration enhancement within the patches by cusp/cleft precipitation; (2) plasma depletion in the minima between the patches by fast plasma flows; and (3) intermittent injection of photoionisation-enhanced plasma into the polar cap. We devise a test to distinguish between the effects of these mechanisms. Some of the events repeat too frequently to apply the test. Others have sufficiently long repeat periods and mechanism (3) is shown to be the only explanation of three of the longer-lived patches seen on this day. However, effect (2) also appears to contribute to some events. We conclude that plasma concentration gradients on the edges of the larger patches arise mainly from local time variations in the subauroral plasma, via the mechanism proposed by Lockwood et al. (2000).

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Land cover plays a key role in global to regional monitoring and modeling because it affects and is being affected by climate change and thus became one of the essential variables for climate change studies. National and international organizations require timely and accurate land cover information for reporting and management actions. The North American Land Change Monitoring System (NALCMS) is an international cooperation of organizations and entities of Canada, the United States, and Mexico to map land cover change of North America's changing environment. This paper presents the methodology to derive the land cover map of Mexico for the year 2005 which was integrated in the NALCMS continental map. Based on a time series of 250 m Moderate Resolution Imaging Spectroradiometer (MODIS) data and an extensive sample data base the complexity of the Mexican landscape required a specific approach to reflect land cover heterogeneity. To estimate the proportion of each land cover class for every pixel several decision tree classifications were combined to obtain class membership maps which were finally converted to a discrete map accompanied by a confidence estimate. The map yielded an overall accuracy of 82.5% (Kappa of 0.79) for pixels with at least 50% map confidence (71.3% of the data). An additional assessment with 780 randomly stratified samples and primary and alternative calls in the reference data to account for ambiguity indicated 83.4% overall accuracy (Kappa of 0.80). A high agreement of 83.6% for all pixels and 92.6% for pixels with a map confidence of more than 50% was found for the comparison between the land cover maps of 2005 and 2006. Further wall-to-wall comparisons to related land cover maps resulted in 56.6% agreement with the MODIS land cover product and a congruence of 49.5 with Globcover.

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India is increasingly investing in renewable technology to meet rising energy demands, with hydropower and other renewables comprising one-third of current installed capacity. Installed wind-power is projected to increase 5-fold by 2035 (to nearly 100GW) under the International Energy Agency’s New Policies scenario. However, renewable electricity generation is dependent upon the prevailing meteorology, which is strongly influenced by monsoon variability. Prosperity and widespread electrification are increasing the demand for air conditioning, especially during the warm summer. This study uses multi-decadal observations and meteorological reanalysis data to assess the impact of intraseasonal monsoon variability on the balance of electricity supply from wind-power and temperature-related demand in India. Active monsoon phases are characterised by vigorous convection and heavy rainfall over central India. This results in lower temperatures giving lower cooling energy demand, while strong westerly winds yield high wind-power output. In contrast, monsoon breaks are characterised by suppressed precipitation, with higher temperatures and hence greater demand for cooling, and lower wind-power output across much of India. The opposing relationship between wind-power supply and cooling demand during active phases (low demand, high supply) and breaks (high demand, low supply) suggests that monsoon variability will tend to exacerbate fluctuations in the so-called demand-net-wind (i.e., electrical demand that must be supplied from non-wind sources). This study may have important implications for the design of power systems and for investment decisions in conventional schedulable generation facilities (such as coal and gas) that are used to maintain the supply/demand balance. In particular, if it is assumed (as is common) that the generated wind-power operates as a price-taker (i.e., wind farm operators always wish to sell their power, irrespective of price) then investors in conventional facilities will face additional weather-volatility through the monsoonal impact on the length and frequency of production periods (i.e. their load-duration curves).

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Schwann cells (SCs) are the supporting cells of the peripheral nervous system and originate from the neural crest. They play a unique role in the regeneration of injured peripheral nerves and have themselves a highly unstable phenotype as demonstrated by their unexpectedly broad differentiation potential. Thus, SCs can be considered as dormant, multipotent neural crest-derived progenitors or stem cells. Upon injury they de-differentiate via cellular reprogramming, re-enter the cell cycle and participate in the regeneration of the nerve. Here we describe a protocol for efficient generation of neurospheres from intact adult rat and murine sciatic nerve without the need of experimental in vivo pre-degeneration of the nerve prior to Schwann cell isolation. After isolation and removal of the connective tissue, the nerves are initially plated on poly-D-lysine coated cell culture plates followed by migration of the cells up to 80% confluence and a subsequent switch to serum-free medium leading to formation of multipotent neurospheres. In this context, migration of SCs from the isolated nerve, followed by serum-free cultivation of isolated SCs as neurospheres mimics the injury and reprograms fully differentiated SCs into a multipotent, neural crest-derived stem cell phenotype. This protocol allows reproducible generation of multipotent Schwann cell-derived neurospheres from sciatic nerve through cellular reprogramming by culture, potentially marking a starting point for future detailed investigations of the de-differentiation process.

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Neural crest-derived stem cells (NCSCs) from the embryonic peripheral nervous system (PNS) can be reprogrammed in neurosphere (NS) culture to rNCSCs that produce central nervous system (CNS) progeny, including myelinating oligodendrocytes. Using global gene expression analysis we now demonstrate that rNCSCs completely lose their previous PNS characteristics and acquire the identity of neural stem cells derived from embryonic spinal cord. Reprogramming proceeds rapidly and results in a homogenous population of Olig2-, Sox3-, and Lex-positive CNS stem cells. Low-level expression of pluripotency inducing genes Oct4, Nanog, and Klf4 argues against a transient pluripotent state during reprogramming. The acquisition of CNS properties is prevented in the presence of BMP4 (BMP NCSCs) as shown by marker gene expression and the potential to produce PNS neurons and glia. In addition, genes characteristic for mesenchymal and perivascular progenitors are expressed, which suggests that BMP NCSCs are directed toward a pericyte progenitor/mesenchymal stem cell (MSC) fate. Adult NCSCs from mouse palate, an easily accessible source of adult NCSCs, display strikingly similar properties. They do not generate cells with CNS characteristics but lose the neural crest markers Sox10 and p75 and produce MSC-like cells. These findings show that embryonic NCSCs acquire a full CNS identity in NS culture. In contrast, MSC-like cells are generated from BMP NCSCs and pNCSCs, which reveals that postmigratory NCSCs are a source for MSC-like cells up to the adult stage.

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Understanding the interplay between intrinsic molecular chirality and chirality of the bonding footprint is crucial in exploiting enantioselectivity at surfaces. As such, achiral glycine and chiral alanine are the most obvious candidates if one is to study this interplay on different surfaces. Here, we have investigated the adsorption of glycine on Cu{311} using reflection-absorption infrared spectroscopy, low-energy electron diffraction, temperature-programmed desorption and first-principles density-functional theory. This combination of techniques has allowed us to accurately identify the molecular conformations present under different conditions, and discuss the overlayer structure in the context of the possible bonding footprints. We have observed coverage-dependent local symmetry breaking, with three-point bonded glycinate moieties forming an achiral arrangement at low coverages, and chirality developing with the presence of two-point bonded moieties at high coverages. Comparison with previous work on the self-assembly of simple amino acids on Cu{311} and the structurally-similar Cu{110} surface has allowed us to rationalise the different conditions necessary for the formation of ordered chiral overlayers.

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Dynamic soundtracking presents various practical and aesthetic challenges to composers working with games. This paper presents an implementation of a system addressing some of these challenges with an affectively-driven music generation algorithm based on a second order Markov-model. The system can respond in real-time to emotional trajectories derived from 2-dimensions of affect on the circumplex model (arousal and valence), which are mapped to five musical parameters. A transition matrix is employed to vary the generated output in continuous response to the affective state intended by the gameplay.

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Wind generation's contribution to supporting peak electricity demand is one of the key questions in wind integration studies. Differently from conventional units, the available outputs of different wind farms cannot be approximated as being statistically independent, and hence near-zero wind output is possible across an entire power system. This paper will review the risk model structures currently used to assess wind's capacity value, along with discussion of the resulting data requirements. A central theme is the benefits from performing statistical estimation of the joint distribution for demand and available wind capacity, focusing attention on uncertainties due to limited histories of wind and demand data; examination of Great Britain data from the last 25 years shows that the data requirements are greater than generally thought. A discussion is therefore presented into how analysis of the types of weather system which have historically driven extreme electricity demands can help to deliver robust insights into wind's contribution to supporting demand, even in the face of such data limitations. The role of the form of the probability distribution for available conventional capacity in driving wind capacity credit results is also discussed.