Response and resilience of Spartina alterniflora to sudden dieback

We measured an array of biophysical and spectral variables to evaluate the response and recovery of Spartina alterniflora to a sudden dieback event in spring and summer 2004 within a low marsh in coastal Virginia, USA. S. alterniflora is a foundation species, whose loss decreases ecosystem services and potentiates ecosystem state change. Long-term records of the potential environmental drivers of dieback such as precipitation and tidal inundation did not evidence any particular anomalies, although Hurricane Isabel in fall 2003 may have been related to dieback. Transects were established across the interface between the dieback area and apparently healthy areas of marsh. Plant condition was classified based on ground cover within transects as dieback, intermediate and healthy. Numerous characteristics of S. alterniflora culms within each condition class were assessed including biomass, morphology and spectral attributes associated with photosynthetic pigments. Plants demonstrated evidence of stress in 2004 and 2005 beyond areas of obvious dieback and resilience at a multi-year scale. Resilience of the plants was evident in recovery of ground cover and biomass largely within 3 y, although a small remnant of dieback persisted for 8 y. Culms surviving within the dieback and areas of intermediate impact had modified morphological traits and spectral response that reflected stress. These morphometric and spectral differences among plant cover condition classes serve as guidelines for monitoring of dieback initiation, effects and subsequent recovery. Although a number of environmental and biotic parameters were assessed relative to causation, the reason for this particular dieback remains largely unknown, however

'Designer atoms' for quantum metrology

Entanglement is recognized as a key resource for quantum computation and quantum cryptography. For quantum metrology, the use of entangled states has been discussed and demonstrated as a means of improving the signal-to-noise ratio. In addition, entangled states have been used in experiments for efficient quantum state detection and for the measurement of scattering lengths. In quantum information processing, manipulation of individual quantum bits allows for the tailored design of specific states that are insensitive to the detrimental influences of an environment. Such 'decoherence-free subspaces' protect quantum information and yield significantly enhanced coherence times. Here we use a decoherence-free subspace with specifically designed entangled states to demonstrate precision spectroscopy of a pair of trapped Ca+ ions; we obtain the electric quadrupole moment, which is of use for frequency standard applications. We find that entangled states are not only useful for enhancing the signal-to-noise ratio in frequency measurements - a suitably designed pair of atoms also allows clock measurements in the presence of strong technical noise. Our technique makes explicit use of non-locality as an entanglement property and provides an approach for 'designed' quantum metrology

Probabilistic abstract interpretation: From trace semantics to DTMC’s and linear regression

In order to perform probabilistic program analysis we need to consider probabilistic languages or languages with a probabilistic semantics, as well as a corresponding framework for the analysis which is able to accommodate probabilistic properties and properties of probabilistic computations. To this purpose we investigate the relationship between three different types of probabilistic semantics for a core imperative language, namely Kozen’s Fixpoint Semantics, our Linear Operator Semantics and probabilistic versions of Maximal Trace Semantics. We also discuss the relationship between Probabilistic Abstract Interpretation (PAI) and statistical or linear regression analysis. While classical Abstract Interpretation, based on Galois connection, allows only for worst-case analyses, the use of the Moore-Penrose pseudo inverse in PAI opens the possibility of exploiting statistical and noisy observations in order to analyse and identify various system properties

Left to Their Own Devices: Breakdowns in United States Medical Device Premarket Review

Using examples from recent FDA regulatory proceedings, Jonas Hines and colleagues critique the medical device premarket review and identify eight weaknesses in the process that should be remedied

Proximity curves for potential-based clustering

YesThe concept of proximity curve and a new algorithm are proposed for obtaining clusters in a finite set of data points in the finite dimensional Euclidean space. Each point is endowed with a potential constructed by means of a multi-dimensional Cauchy density, contributing to an overall anisotropic potential function. Guided by the steepest descent algorithm, the data points are successively visited and removed one by one, and at each stage the overall potential is updated and the magnitude of its local gradient is calculated. The result is a finite sequence of tuples, the proximity curve, whose pattern is analysed to give rise to a deterministic clustering. The finite set of all such proximity curves in conjunction with a simulation study of their distribution results in a probabilistic clustering represented by a distribution on the set of dendrograms. A two-dimensional synthetic data set is used to illustrate the proposed potential-based clustering idea. It is shown that the results achieved are plausible since both the ‘geographic distribution’ of data points as well as the ‘topographic features’ imposed by the potential function are well reflected in the suggested clustering. Experiments using the Iris data set are conducted for validation purposes on classification and clustering benchmark data. The results are consistent with the proposed theoretical framework and data properties, and open new approaches and applications to consider data processing from different perspectives and interpret data attributes contribution to patterns

Genetic noise control via protein oligomerization

Gene expression in a cell entails random reaction events occurring over disparate time scales. Thus, molecular noise that often results in phenotypic and population-dynamic consequences sets a fundamental limit to biochemical signaling. While there have been numerous studies correlating the architecture of cellular reaction networks with noise tolerance, only a limited effort has been made to understand the dynamic role of protein-protein interactions. Here we have developed a fully stochastic model for the positive feedback control of a single gene, as well as a pair of genes (toggle switch), integrating quantitative results from previous in vivo and in vitro studies. We find that the overall noise-level is reduced and the frequency content of the noise is dramatically shifted to the physiologically irrelevant high-frequency regime in the presence of protein dimerization. This is independent of the choice of monomer or dimer as transcription factor and persists throughout the multiple model topologies considered. For the toggle switch, we additionally find that the presence of a protein dimer, either homodimer or heterodimer, may significantly reduce its random switching rate. Hence, the dimer promotes the robust function of bistable switches by preventing the uninduced (induced) state from randomly being induced (uninduced). The specific binding between regulatory proteins provides a buffer that may prevent the propagation of fluctuations in genetic activity. The capacity of the buffer is a non-monotonic function of association-dissociation rates. Since the protein oligomerization per se does not require extra protein components to be expressed, it provides a basis for the rapid control of intrinsic or extrinsic noise

An Exploratory Study of Primary Care Physician Decision Making Regarding Total Joint Arthroplasty

BACKGROUND: For patients to experience the benefits of total joint arthroplasty (TJA), primary care physicians (PCPs) ought to know when to refer a patient for TJA and/or optimize nonsurgical treatment options for osteoarthritis (OA). OBJECTIVE: To evaluate the ability of physicians to make clinical treatment decisions. DESIGN AND PARTICIPANTS: A survey, using ten clinical vignettes, of PCPs in Indiana. MEASUREMENTS: A test score (range 0 to 10) was computed based on the number of correct answers consistent with published explicit appropriateness criteria for TJA. We also collected demographic characteristics and physicians’ perceived success rate of TJA in terms of pain relief and functional improvement. RESULTS: There were 149 PCPs (response rate = 61%) who participated. The mean test score was 6.5 ± 1.5. Only 17% correctly identified the published success rate of TJA (i.e., ≥90%). In multivariate analysis, the only physician-related variables associated with test score were ethnicity, board status, and perceived success rate of TJA. Physicians who were white (P = .001), board-certified (P = .04), and perceived a higher success rate of TJA (P = .004) had higher test scores. CONCLUSIONS: PCP knowledge with respect to guideline-concordant care for OA could be improved, specifically in deciding when to consider TJA versus optimizing nonsurgical options. Moreover, the perception of the success rate of TJA may influence a clinician’s decision making

Understanding the chronology and occupation dynamics of oversized pit houses in the southern Brazilian highlands

A long held view about the occupation of southern proto-Je pit house villages of the southern Brazilian highlands is that these sites represent cycles of long-term abandonment and reoccupation. However, this assumption is based on an insufficient number of radiocarbon dates for individual pit houses. To address this problem, we conducted a programme of comprehensive AMS radiocarbon dating and Bayesian modelling at the deeply stratified oversized pit Houe 1, Baggio 1 site (Cal. A.D. 1395-1650), Campo Belo do Sul, Santa Catarina, Brazil. The straigraphy of House 1 revealed an unparalleled sequence of twelve well preserved floors evidencing a major change in occupation dynamics including five completely burnt collapsed roofs. The results of the radiocarbon dating allowed us to understand for the first time the occupation dynamics of an oversized pit house in the southern Brazilian highlands. The Bayesian model demonstrates that House 1 was occupied for over two centuries with no evidence of major periods of abandonment, calling into question previous models of long-term abandonment. In addition, the House 1 sequence allowed us to tie transformations in ceramic style and lithic technology to an absolute chronology. Finally, we can provide new evidence that the emergence of oversized domestic structures is a relatively recent phenomenon among the southern proto-Je. As monumental pit houses start to be bulit, small pit houses continue to be inhabited, evidencing emerging disparities in domestic architecture after AD 1000. Our research shows the importance of programmes of intensive dating of individual structures to understand occupation dynamcis and site permanence, and challenges long held assumptions that the southern Brazilian highlands were home to marginal cultures in the context of lowland South America

Stochastic Gravity: Theory and Applications

Whereas semiclassical gravity is based on the semiclassical Einstein equation with sources given by the expectation value of the stress-energy tensor of quantum fields, stochastic semiclassical gravity is based on the Einstein-Langevin equation, which has in addition sources due to the noise kernel.In the first part, we describe the fundamentals of this new theory via two approaches: the axiomatic and the functional. In the second part, we describe three applications of stochastic gravity theory. First, we consider metric perturbations in a Minkowski spacetime: we compute the two-point correlation functions for the linearized Einstein tensor and for the metric perturbations. Second, we discuss structure formation from the stochastic gravity viewpoint. Third, we discuss the backreaction of Hawking radiation in the gravitational background of a quasi-static black hole.Comment: 75 pages, no figures, submitted to Living Reviews in Relativit

Stochastic Gravity: Theory and Applications

Whereas semiclassical gravity is based on the semiclassical Einstein equation with sources given by the expectation value of the stress-energy tensor of quantum fields, stochastic semiclassical gravity is based on the Einstein-Langevin equation, which has in addition sources due to the noise kernel. In the first part, we describe the fundamentals of this new theory via two approaches: the axiomatic and the functional. In the second part, we describe three applications of stochastic gravity theory. First, we consider metric perturbations in a Minkowski spacetime, compute the two-point correlation functions of these perturbations and prove that Minkowski spacetime is a stable solution of semiclassical gravity. Second, we discuss structure formation from the stochastic gravity viewpoint. Third, we discuss the backreaction of Hawking radiation in the gravitational background of a black hole and describe the metric fluctuations near the event horizon of an evaporating black holeComment: 100 pages, no figures; an update of the 2003 review in Living Reviews in Relativity gr-qc/0307032 ; it includes new sections on the Validity of Semiclassical Gravity, the Stability of Minkowski Spacetime, and the Metric Fluctuations of an Evaporating Black Hol