The data treatment dependent variability of U-Pb zircon ages obtained using mono-collector, sector field, laser ablation ICP-MS

U-Pb dating of zircons by laser ablation inductively coupled plasma mass spectrometry (LA-ICPMS) is a widely used analytical technique in Earth Sciences. For U-Pb ages below 1 billion years (1 Ga), Pb-206/U-238 dates are usually used, showing the least bias by external parameters such as the presence of initial lead and its isotopic composition in the analysed mineral. Precision and accuracy of the Pb/U ratio are thus of highest importance in LA-ICPMS geochronology. We consider the evaluation of the statistical distribution of the sweep intensities based on goodness-of-fit tests in order to find a model probability distribution fitting the data to apply an appropriate formulation for the standard deviation. We then discuss three main methods to calculate the Pb/U intensity ratio and its uncertainty in the LA-ICPMS: (1) ratio-of-the-mean intensities method, (2) mean-of-the-intensity-ratios method and (3) intercept method. These methods apply different functions to the same raw intensity vs. time data to calculate the mean Pb/U intensity ratio. Thus, the calculated intensity ratio and its uncertainty depend on the method applied. We demonstrate that the accuracy and, conditionally, the precision of the ratio-of-the-mean intensities method are invariant to the intensity fluctuations and averaging related to the dwell time selection and off-line data transformation (averaging of several sweeps); we present a statistical approach how to calculate the uncertainty of this method for transient signals. We also show that the accuracy of methods (2) and (3) is influenced by the intensity fluctuations and averaging, and the extent of this influence can amount to tens of percentage points; we show that the uncertainty of these methods also depends on how the signal is averaged. Each of the above methods imposes requirements to the instrumentation. The ratio-of-the-mean intensities method is sufficiently accurate provided the laser induced fractionation between the beginning and the end of the signal is kept low and linear. We show, based on a comprehensive series of analyses with different ablation pit sizes, energy densities and repetition rates for a 193 nm ns-ablation system that such a fractionation behaviour requires using a low ablation speed (low energy density and low repetition rate). Overall, we conclude that the ratio-of-the-mean intensities method combined with low sampling rates is the most mathematically accurate among the existing data treatment methods for U-Pb zircon dating by sensitive sector field ICPMS.

Exchange rate predictability

The main goal of this article is to provide an answer to the question: "Does anything forecast exchange rates, and if so, which variables?". It is well known thatexchange rate fluctuations are very difficult to predict using economic models, andthat a random walk forecasts exchange rates better than any economic model (theMeese and Rogoff puzzle). However, the recent literature has identified a series of fundamentals/methodologies that claim to have resolved the puzzle. This article providesa critical review of the recent literature on exchange rate forecasting and illustratesthe new methodologies and fundamentals that have been recently proposed in an up-to-date, thorough empirical analysis. Overall, our analysis of the literature and thedata suggests that the answer to the question: "Are exchange rates predictable?" is,"It depends" -on the choice of predictor, forecast horizon, sample period, model, andforecast evaluation method. Predictability is most apparent when one or more of thefollowing hold: the predictors are Taylor rule or net foreign assets, the model is linear, and a small number of parameters are estimated. The toughest benchmark is therandom walk without drift.

Changes in the use of broad-spectrum antibiotics after cefepime shortage: a time series analysis.

The original cefepime product was withdrawn from the Swiss market in January 2007, and replaced by a generic 10 months later. The goals of the study were to assess the impact of this cefepime shortage on the use and costs of alternative broad-spectrum antibiotics, on antibiotic policy, and on resistance of Pseudomonas aeruginosa towards carbapenems, ceftazidime and piperacillin-tazobactam. A generalized regression-based interrupted time series model assessed how much the shortage changed the monthly use and costs of cefepime and of selected alternative broad-spectrum antibiotics (ceftazidime, imipenem-cilastatin, meropenem, piperacillin-tazobactam) in 15 Swiss acute care hospitals from January 2005 to December 2008. Resistance of P. aeruginosa was compared before and after the cefepime shortage. There was a statistically significant increase in the consumption of piperacillin-tazobactam in hospitals with definitive interruption of cefepime supply, and of meropenem in hospitals with transient interruption of cefepime supply. Consumption of each alternative antibiotic tended to increase during the cefepime shortage and to decrease when the cefepime generic was released. These shifts were associated with significantly higher overall costs. There was no significant change in hospitals with uninterrupted cefepime supply. The alternative antibiotics for which an increase in consumption showed the strongest association with a progression of resistance were the carbapenems. The use of alternative antibiotics after cefepime withdrawal was associated with a significant increase in piperacillin-tazobactam and meropenem use and in overall costs, and with a decrease in susceptibility of P. aeruginosa in hospitals. This warrants caution with regard to shortages and withdrawals of antibiotics.

On the tractability of the piecewise-linear approximation for general discrete-choice network revenue management

The choice network revenue management (RM) model incorporates customer purchase behavioras customers purchasing products with certain probabilities that are a function of the offeredassortment of products, and is the appropriate model for airline and hotel network revenuemanagement, dynamic sales of bundles, and dynamic assortment optimization. The underlyingstochastic dynamic program is intractable and even its certainty-equivalence approximation, inthe form of a linear program called Choice Deterministic Linear Program (CDLP) is difficultto solve in most cases. The separation problem for CDLP is NP-complete for MNL with justtwo segments when their consideration sets overlap; the affine approximation of the dynamicprogram is NP-complete for even a single-segment MNL. This is in contrast to the independentclass(perfect-segmentation) case where even the piecewise-linear approximation has been shownto be tractable. In this paper we investigate the piecewise-linear approximation for network RMunder a general discrete-choice model of demand. We show that the gap between the CDLP andthe piecewise-linear bounds is within a factor of at most 2. We then show that the piecewiselinearapproximation is polynomially-time solvable for a fixed consideration set size, bringing itinto the realm of tractability for small consideration sets; small consideration sets are a reasonablemodeling tradeoff in many practical applications. Our solution relies on showing that forany discrete-choice model the separation problem for the linear program of the piecewise-linearapproximation can be solved exactly by a Lagrangian relaxation. We give modeling extensionsand show by numerical experiments the improvements from using piecewise-linear approximationfunctions.

Current Population Reports Series P-26, Federal-State cooperative program for population estimates, July 1974

T his report presents population estimates for July 1, 1972 and provisional estimates for July 1, 1973, for counties and metropolitan areas prepared under the auspices of the Federal State Cooperative Program for Local Population Estimates. The objective of this program. is the development and publication of State - prepared estimates of the population of counties using uniform procedures largely standardized for data input and methodology. The methods used have been mutually agreed upon by the individual States and the Bureau of the Census on the basis of a test of methods against the 1970 census. For a more detailed description of the program.

Current Population Reports Series P-26, Federal-State cooperative program for population estimates, September 1975

This report presents population estimates for July 1, 1973 and provisional estimates for July 1, for counties and metropolitan areas prepared under the auspices of the Federal State Cooperative Program for Local Population Estimates. The objective of this program. is the development and publication of State - prepared estimates of the population of counties using uniform procedures largely standardized for data input and methodology. The methods used have been mutually agreed upon by the individual States and the Bureau of the Census on the basis of a test of methods against the 1970 census. For a more detailed description of the program.

SAT Modulo Linear Arithmetic for Solving Polynomial

Polynomial constraint solving plays a prominent role in several areas of hardware and software analysis and verification, e.g., termination proving, program invariant generation and hybrid system verification, to name a few. In this paper we propose a new method for solving non-linear constraints based on encoding the problem into an SMT problem considering only linear arithmetic. Unlike other existing methods, our method focuses on proving satisfiability of the constraints rather than on proving unsatisfiability, which is more relevant in several applications as we illustrate with several examples. Nevertheless, we also present new techniques based on the analysis of unsatisfiable cores that allow one to efficiently prove unsatisfiability too for a broad class of problems. The power of our approach is demonstrated by means of extensive experiments comparing our prototype with state-of-the-art tools on benchmarks taken both from the academic and the industrial world.

Characteristics of highly frequent users of a Swiss academic emergency department: a retrospective consecutive case series.

OBJECTIVES: The aim of this study was to describe the demographic, social and medical characteristics, and healthcare use of highly frequent users of a university hospital emergency department (ED) in Switzerland. METHODS: A retrospective consecutive case series was performed. We included all highly frequent users, defined as patients attending the ED 12 times or more within a calendar year (1 January 2009 to 31 December 2009). We collected their characteristics and calculated a score of accumulation of risk factors of vulnerability. RESULTS: Highly frequent users comprised 0.1% of ED patients, and they accounted for 0.8% of all ED attendances (23 patients, 425 attendances). Of all highly frequent users, 87% had a primary care practitioner, 82.6% were unemployed, 73.9% were socially isolated, and 60.9% had a mental health or substance use primary diagnosis. One-third had attempted suicide during study period, all of them being women. They were often admitted (24.0% of attendances), and only 8.7% were uninsured. On average, they cumulated 3.3 different risk factors of vulnerability (SD 1.4). CONCLUSION: Highly frequent users of a Swiss academic ED are a highly vulnerable population. They are in poor health and accumulate several risk factors of being even in poorer health. The small number of patients and their high level of insurance coverage make it particularly feasible to design a specific intervention to approach their needs, in close collaboration with their primary care practitioner. Elaboration of the intervention should focus on social reinsertion and risk-reduction strategies with regard to substance use, hospital admissions and suicide.

Maximum likelihood Linear Programming Data Fusion for Speaker Recognition

Biometric system performance can be improved by means of data fusion. Several kinds of information can be fused in order to obtain a more accurate classification (identification or verification) of an input sample. In this paper we present a method for computing the weights in a weighted sum fusion for score combinations, by means of a likelihood model. The maximum likelihood estimation is set as a linear programming problem. The scores are derived from a GMM classifier working on a different feature extractor. Our experimental results assesed the robustness of the system in front a changes on time (different sessions) and robustness in front a change of microphone. The improvements obtained were significantly better (error bars of two standard deviations) than a uniform weighted sum or a uniform weighted product or the best single classifier. The proposed method scales computationaly with the number of scores to be fussioned as the simplex method for linear programming.

A non-linear VAD for noisy environments

This paper deals with non-linear transformations for improving the performance of an entropy-based voice activity detector (VAD). The idea to use a non-linear transformation has already been applied in the field of speech linear prediction, or linear predictive coding (LPC), based on source separation techniques, where a score function is added to classical equations in order to take into account the true distribution of the signal. We explore the possibility of estimating the entropy of frames after calculating its score function, instead of using original frames. We observe that if the signal is clean, the estimated entropy is essentially the same; if the signal is noisy, however, the frames transformed using the score function may give entropy that is different in voiced frames as compared to nonvoiced ones. Experimental evidence is given to show that this fact enables voice activity detection under high noise, where the simple entropy method fails.

A Canonical Genetic Algorithm for Blind Inversion of Linear Channels

It is well known the relationship between source separation and blind deconvolution: If a filtered version of an unknown i.i.d. signal is observed, temporal independence between samples can be used to retrieve the original signal, in the same manner as spatial independence is used for source separation. In this paper we propose the use of a Genetic Algorithm (GA) to blindly invert linear channels. The use of GA is justified in the case of small number of samples, where other gradient-like methods fails because of poor estimation of statistics.

What treatment for periprosthetic shoulder infection? Results from a multicentre retrospective series.

PURPOSE: Controversy still exists as to the best surgical treatment for periprosthetic shoulder infections. The aim of this multi-institutional study was to review a continuous retrospective series of patients treated in four European centres and to assess the respective eradication rate of various treatment approaches. METHODS: Forty-four patients were available for this retrospective follow-up evaluation. Functional and clinical evaluation of treatment for infection was performed using the Constant-Murley score, visual analogue scale and patient satisfaction Neer score. Erythrocyte sedimentation rate, serum leucocyte count and C-reactive protein were measured and shoulder X-ray examination performed prior to surgery and at the latest follow-up. RESULTS: At a mean follow-up of 41 months (range 24-98), 42 of 44 patients (95.5%) showed no signs of infection recurrence/persistence. Comparable eradication rates were observed after resection arthroplasty (100%; 6/6), two-stage revision (17/17) or permanent antibiotic-loaded spacer implant (93.3%; 14/15). No patient was treated by one-stage revision. On average, both functional and pain scores improved significantly; the worst joint function was observed after resection arthroplasty. CONCLUSIONS: This retrospective analysis conducted on the largest published series of patients to date shows comparable infection eradication rates after two-stage revision, resection arthroplasty or permanent spacer implant for the treatment of septic shoulder prosthesis.

La subtitulación amateur: la subtitulación amateur de series online: el caso de Lost

Debido a su gran repercusión y rápido ritmo de expansión, resulta obvio que la subtitulación amateur se configura como uno de los fenómenos más interesantes y novedosos de los estudios teóricos y prácticos de la investigación traductológica. Por este motivo, el objetivo principal del presente trabajo es el de conocer y estudiar más en profundidad dicho fenómeno, así como analizar la calidad de estos subtítulos con relación a los profesionales a través de un análisis comparativo de materiales reales de la serie norteamericana Lost. Por otro lado, y a la vista de las conclusiones, también se reflexiona acerca del estado actual de la subtitulación interlingüística, así como de la viabilidad de llevar a cabo una modernización de la disciplina mediante el establecimiento, renovación y diversificación de nuevas y existentes modalidades, junto con las repercusiones académicas, sociológicas y profesionales que ello acarrearía.

Pinpointing Suspect Triplicate Unconfined Compressive Strength Values in a Series of Soil-Additive Strength Determinations, HR-1, Progress Report, 1961

In recent years, various types of organic and inorganic materials have been investigated for use as soil stabilizing agents in the construction of highways and airports. Since the properties and environmental conditions of soils vary so greatly from place to place, a stabilizing agent that is suitable for one type of soil may not be satisfactory for another. As a result, it is often desirable to evaluate several stabilizing agents under varying treatment conditions before deciding on a specific one to be used with a given soil. In addition many research programs have been initiated which investigate the effects of these stabilizing agents upon soils.

A non-linear Bayesian approach for upscaling local-scale hydraulic conductivity measurements based on local- and regional-scale geophysical data

Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending the corresponding approaches to the regional scale represents a major, and as-of-yet largely unresolved, challenge. To address this problem, we have developed an upscaling procedure based on a Bayesian sequential simulation approach. This method is then applied to the stochastic integration of low-resolution, regional-scale electrical resistivity tomography (ERT) data in combination with high-resolution, local-scale downhole measurements of the hydraulic and electrical conductivities. Finally, the overall viability of this upscaling approach is tested and verified by performing and comparing flow and transport simulation through the original and the upscaled hydraulic conductivity fields. Our results indicate that the proposed procedure does indeed allow for obtaining remarkably faithful estimates of the regional-scale hydraulic conductivity structure and correspondingly reliable predictions of the transport characteristics over relatively long distances.