992 resultados para Statistical Computation


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Statistical downscaling (SD) methods have become a popular, low-cost and accessible means of bridging the gap between the coarse spatial resolution at which climate models output climate scenarios and the finer spatial scale at which impact modellers require these scenarios, with various different SD techniques used for a wide range of applications across the world. This paper compares the Generator for Point Climate Change (GPCC) model and the Statistical DownScaling Model (SDSM)—two contrasting SD methods—in terms of their ability to generate precipitation series under non-stationary conditions across ten contrasting global climates. The mean, maximum and a selection of distribution statistics as well as the cumulative frequencies of dry and wet spells for four different temporal resolutions were compared between the models and the observed series for a validation period. Results indicate that both methods can generate daily precipitation series that generally closely mirror observed series for a wide range of non-stationary climates. However, GPCC tends to overestimate higher precipitation amounts, whilst SDSM tends to underestimate these. This infers that GPCC is more likely to overestimate the effects of precipitation on a given impact sector, whilst SDSM is likely to underestimate the effects. GPCC performs better than SDSM in reproducing wet and dry day frequency, which is a key advantage for many impact sectors. Overall, the mixed performance of the two methods illustrates the importance of users performing a thorough validation in order to determine the influence of simulated precipitation on their chosen impact sector.

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Repeated recolonization of freshwater environments following Pleistocene glaciations has played a major role in the evolution and adaptation of anadromous taxa. Located at the western fringe of Europe, Ireland and Britain were likely recolonized rapidly by anadromous fishes from the North Atlantic following the last glacial maximum (LGM). While the presence of unique mitochondrial haplotypes in Ireland suggests that a cryptic northern refugium may have played a role in recolonization, no explicit test of this hypothesis has been conducted. The three-spined stickleback is native and ubiquitous to aquatic ecosystems throughout Ireland, making it an excellent model species with which to examine the biogeographical history of anadromous fishes in the region. We used mitochondrial and microsatellite markers to examine the presence of divergent evolutionary lineages and to assess broad-scale patterns of geographical clustering among postglacially isolated populations. Our results confirm that Ireland is a region of secondary contact for divergent mitochondrial lineages and that endemic haplotypes occur in populations in Central and Southern Ireland. To test whether a putative Irish lineage arose from a cryptic Irish refugium, we used approximate Bayesian computation (ABC). However, we found no support for this hypothesis. Instead, the Irish lineage likely diverged from the European lineage as a result of postglacial isolation of freshwater populations by rising sea levels. These findings emphasize the need to rigorously test biogeographical hypothesis and contribute further evidence that postglacial processes may have shaped genetic diversity in temperate fauna.

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Identifying processes that shape species geographical ranges is a prerequisite for understanding environmental change. Currently, species distribution modelling methods do not offer credible statistical tests of the relative influence of climate factors and typically ignore other processes (e.g. biotic interactions and dispersal limitation). We use a hierarchical model fitted with Markov Chain Monte Carlo to combine ecologically plausible niche structures using regression splines to describe unimodal but potentially skewed response terms. We apply spatially explicit error terms that account for (and may help identify) missing variables. Using three example distributions of European bird species, we map model results to show sensitivity to change in each covariate. We show that the overall strength of climatic association differs between species and that each species has considerable spatial variation in both the strength of the climatic association and the sensitivity to climate change. Our methods are widely applicable to many species distribution modelling problems and enable accurate assessment of the statistical importance of biotic and abiotic influences on distributions.

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BACKGROUND:
Statistical numeracy, necessary for making informed medical decisions, is reduced among older adults who make more decisions about their medical care and treatment than at any other stage of life. Objective numeracy scales are a source of anxiety among patients, heightened among older adults.
OBJECTIVE:
We investigate the subjective numeracy scale as an alternative tool for measuring statistical numeracy with older adult samples.
METHODS:
Numeracy was assessed using objective measures for 526 adults ranging in age from 18 to 93 years, and all participants provided subjective numeracy ratings.
RESULTS:
Subjective numeracy correlated highly with objective measurements among oldest adults (70+ years; r = 0.51, 95% CI 0.32, 0.66), and for younger age groups. Subjective numeracy explained 33.2% of age differences in objective numeracy.
CONCLUSION:
The subjective numeracy scale provides an effective tool for assessing statistical numeracy for broad age ranges and circumvents problems associated with objective numeracy measures.

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The properties of Ellerman bombs (EBs), small-scale brightenings in the Hα line wings, have proved difficult to establish because their size is close to the spatial resolution of even the most advanced telescopes. Here, we aim to infer the size and lifetime of EBs using high-resolution data of an emerging active region collected using the Interferometric BIdimensional Spectrometer (IBIS) and Rapid Oscillations of the Solar Atmosphere (ROSA) instruments as well as the Helioseismic and Magnetic Imager (HMI) onboard the Solar Dynamics Observatory (SDO). We develop an algorithm to track EBs through their evolution, finding that EBs can often be much smaller (around 0.3″) and shorter-lived (less than one minute) than previous estimates. A correlation between G-band magnetic bright points and EBs is also found. Combining SDO/HMI and G-band data gives a good proxy of the polarity for the vertical magnetic field. It is found that EBs often occur both over regions of opposite polarity flux and strong unipolar fields, possibly hinting at magnetic reconnection as a driver of these events.The energetics of EB events is found to follow a power-law distribution in the range of a nanoflare (1022-25 ergs).

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It is an exciting era for molecular computation because molecular logic gates are being pushed in new directions. The use of sulfur rather than the commonplace nitrogen as the key receptor atom in metal ion sensors is one of these directions; plant cells coming within the jurisdiction of fluorescent molecular thermometers is another, combining photochromism with voltammetry for molecular electronics is yet another. Two-input logic gates benefit from old ideas such as rectifying bilayer electrodes, cyclodextrin-enhanced room-temperature phosphorescence, steric hindrance, the polymerase chain reaction, charge transfer absorption of donor–acceptor complexes and lectin–glycocluster interactions. Furthermore, the concept of photo-uncaging enables rational ways of concatenating logic gates. Computational concepts are also applied to potential cancer theranostics and to the selective monitoring of neurotransmitters in situ. Higher numbers of inputs are also accommodated with the concept of functional integration of gates, where complex input–output patterns are sought out and analysed. Molecular emulation of computational components such as demultiplexers and parity generators/checkers are achieved in related ways. Complexity of another order is tackled with molecular edge detection routines.

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Motivated by the need for designing efficient and robust fully-distributed computation in highly dynamic networks such as Peer-to-Peer (P2P) networks, we study distributed protocols for constructing and maintaining dynamic network topologies with good expansion properties. Our goal is to maintain a sparse (bounded degree) expander topology despite heavy {\em churn} (i.e., nodes joining and leaving the network continuously over time). We assume that the churn is controlled by an adversary that has complete knowledge and control of what nodes join and leave and at what time and has unlimited computational power, but is oblivious to the random choices made by the algorithm. Our main contribution is a randomized distributed protocol that guarantees with high probability the maintenance of a {\em constant} degree graph with {\em high expansion} even under {\em continuous high adversarial} churn. Our protocol can tolerate a churn rate of up to $O(n/\poly\log(n))$ per round (where $n$ is the stable network size). Our protocol is efficient, lightweight, and scalable, and it incurs only $O(\poly\log(n))$ overhead for topology maintenance: only polylogarithmic (in $n$) bits needs to be processed and sent by each node per round and any node's computation cost per round is also polylogarithmic. The given protocol is a fundamental ingredient that is needed for the design of efficient fully-distributed algorithms for solving fundamental distributed computing problems such as agreement, leader election, search, and storage in highly dynamic P2P networks and enables fast and scalable algorithms for these problems that can tolerate a large amount of churn.

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Molecular logic-based computation continues to throw up new applications in sensing and switching, the newest of which is the edge detection of objects. The scope of this phenomenon is mapped out by the use of structure-activity relationships, where several structures of the molecules and of the objects are examined. The different angles and curvatures of the objects are followed with good-fidelity in the visualized edges, even when the objects are in reverse video.

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In this paper, we study the achievable ergodic sum-rate of multiuser multiple-input multiple-output downlink systems in Rician fading channels. We first derive a lower bound on the average signal-to-leakage-and-noise ratio by using the Mullen’s inequality, and then use it to analyze the effect of channel mean information on the achievable ergodic sum-rate. A novel statistical-eigenmode space-division multiple-access (SESDMA) downlink transmission scheme is then proposed. For this scheme, we derive an exact analytical closed-form expression for the achievable ergodic rate and present tractable tight upper and lower bounds. Based on our analysis, we gain valuable insights into the system parameters, such as the number of transmit antennas, the signal-to-noise ratio (SNR) and Rician K-factor on the system sum-rate. Results show that the sum-rate converges to a saturation value in the high SNR regime and tends to a lower limit for the low Rician K-factor case. In addition, we compare the achievable ergodic sum-rate between SE-SDMA and zeroforcing beamforming with perfect channel state information at the base station. Our results reveal that the rate gap tends to zero in the high Rician K-factor regime. Finally, numerical results are presented to validate our analysis.