Montecarlo simulation of the role of defects as the melting mechanism

We study in this paper the melting transition of a crystal of fcc structure with the Lennard-Jones potential, by using isobaric-isothermal Monte Carlo simulations. Local and collective updates are sequentially used to optimize the convergence. We show the important role played by defects in the melting mechanism in favor of modern melting theories.Comment: 6 page, 10 figures included. Corrected version to appear in Phys. Rev.

Sodium bicarbonate and high-intensity-cycling capacity: variability in responses

Purpose: The aim of this study was to determine whether gastrointestinal (GI) distress affects the ergogenicity of sodium bicarbonate and whether the degree of alkalaemia or other metabolic responses are different between individuals who improve exercise capacity and those who do not. Methods: Twenty-one males completed two cycling capacity tests at 110% of maximum power output. Participants were supplemented with 0.3 g∙kg-1BM of either placebo (maltodextrin) or sodium bicarbonate (SB). Blood pH, bicarbonate, base excess and lactate were determined at baseline, pre-exercise, immediately post-exercise and 5 minutes post-exercise. Results: SB supplementation did not significantly increase total work done (TWD) (P = 0.16, 46.8 ± 9.1 vs. 45.6 ± 8.4 kJ, d = 0.14), although magnitude based inferences suggested a 63% likelihood of a positive effect. When data were analysed without four participants who experienced GI discomfort, TWD (P = 0.01) was significantly improved with SB. Immediately post-exercise blood lactate was higher in SB for the individuals who improved but not for those who didn’t. There were also differences in the pre to post-exercise change in blood pH, bicarbonate and base excess between individuals who improved and individuals who did not. Conclusions: SB improved high intensity cycling capacity, but only with the exclusion of participants experiencing GI discomfort. Differences in blood responses suggest that sodium bicarbonate may not be beneficial to all individuals. Magnitude based inferences suggested that the exercise effects are unlikely to be negative; therefore individuals should determine whether they respond well to sodium bicarbonate supplementation prior to competition

Estimation of the Optimal Statistical Quality Control Sampling Time Intervals Using a Residual Risk Measure

Background: An open problem in clinical chemistry is the estimation of the optimal sampling time intervals for the application of statistical quality control (QC) procedures that are based on the measurement of control materials. This is a probabilistic risk assessment problem that requires reliability analysis of the analytical system, and the estimation of the risk caused by the measurement error. Methodology/Principal Findings: Assuming that the states of the analytical system are the reliability state, the maintenance state, the critical-failure modes and their combinations, we can define risk functions based on the mean time of the states, their measurement error and the medically acceptable measurement error. Consequently, a residual risk measure rr can be defined for each sampling time interval. The rr depends on the state probability vectors of the analytical system, the state transition probability matrices before and after each application of the QC procedure and the state mean time matrices. As optimal sampling time intervals can be defined those minimizing a QC related cost measure while the rr is acceptable. I developed an algorithm that estimates the rr for any QC sampling time interval of a QC procedure applied to analytical systems with an arbitrary number of critical-failure modes, assuming any failure time and measurement error probability density function for each mode. Furthermore, given the acceptable rr, it can estimate the optimal QC sampling time intervals

Estimation of hydraulic conductivity and its uncertainty from grain-size data using GLUE and artificial neural networks

peer reviewedaudience: researcher, professionalVarious approaches exist to relate saturated hydraulic conductivity (Ks) to grain-size data. Most methods use a single grain-size parameter and hence omit the information encompassed by the entire grain-size distribution. This study compares two data-driven modelling methods, i.e.multiple linear regression and artificial neural networks, that use the entire grain-size distribution data as input for Ks prediction. Besides the predictive capacity of the methods, the uncertainty associated with the model predictions is also evaluated, since such information is important for stochastic groundwater flow and contaminant transport modelling. Artificial neural networks (ANNs) are combined with a generalized likelihood uncertainty estimation (GLUE) approach to predict Ks from grain-size data. The resulting GLUE-ANN hydraulic conductivity predictions and associated uncertainty estimates are compared with those obtained from the multiple linear regression models by a leave-one-out cross-validation. The GLUE-ANN ensemble prediction proved to be slightly better than multiple linear regression. The prediction uncertainty, however, was reduced by half an order of magnitude on average, and decreased at most by an order of magnitude. This demonstrates that the proposed method outperforms classical data-driven modelling techniques. Moreover, a comparison with methods from literature demonstrates the importance of site specific calibration. The dataset used for this purpose originates mainly from unconsolidated sandy sediments of the Neogene aquifer, northern Belgium. The proposed predictive models are developed for 173 grain-size -Ks pairs. Finally, an application with the optimized models is presented for a borehole lacking Ks data

Accelerating Community College Graduation Rates: A Benefit–Cost Analysis

This article reports a benefit–cost evaluation of the Accelerated Study in Associate Programs (ASAP) of the City University of New York (CUNY). ASAP was designed to accelerate associate degree completion within 3 years of degree enrollment at CUNY’s community colleges. The program evaluation revealed that the completion rate for the examined cohort increased from 24.1% to 54.9%, and cost per graduate declined considerably (Levin & Garcia, 2012; Linderman & Kolenovic, 2012). The returns on investment to the taxpayer include the benefits from higher tax revenues and lower costs of spending on public health, criminal justice, and public assistance. For each dollar of investment in ASAP by taxpayers, the return was $3 to$4. For each additional graduate, the taxpayer gained an amount equal to a certificate of deposit with a value of $146,000 (net of the costs of the investment). Based on these estimated returns, a cohort of 1,000 students enrolled in ASAP would generate net fiscal benefits for the taxpayer of more than$46 million relative to enrolling in the conventional degree program. ASAP results demonstrate that an effective educational policy can generate returns to the taxpayer that vastly exceed the public investment required

The influence of institutional factors on corporate narratives: a thematic content analysis of Guinness

This paper provides a thematic content analysis of the Chairman’s Statement of Arthur Guinness & Son Ltd over time. The analysis traces the evolution of the content over four distinct periods using a coding scheme developed from extant research. The objective is to study whether the corporate narratives change in line with the institutional factors over time. To interpret the results, we draw on an institutional theory-based lens to offer potential explanations of some of the change and stability noted. Institutions can constrain behaviour, but they can also support and empower agents to bring about change. The results of the longitudinal content analysis reveals some variations over time, but in general the content is relatively stable. This may be explained by the organisation itself being an institution that is sufficiently institutionalised so that corporate reporting remained relatively stable. This suggests Guinness may be an example of a strong institution over time. "The final, definitive version of this paper has been published in Accounting History, 2020, 25(3), 425-447, published by SAGE Publishing. Available online: https://doi.org/10.1177/1032373219881811. DOI: 10.1177/1032373219881811. Please cite the published version.

Abstracts of the 2014 Brains, Minds, and Machines Summer School

A compilation of abstracts from the student projects of the 2014 Brains, Minds, and Machines Summer School, held at Woods Hole Marine Biological Lab, May 29 - June 12, 2014.This work was supported by the Center for Brains, Minds and Machines (CBMM), funded by NSF STC award CCF-1231216

Impacts of past abrupt land change on local biodiversity globally

Abrupt land change, such as deforestation or agricultural intensification, is a key driver of biodiversity change. Following abrupt land change, local biodiversity often continues to be influenced through biotic lag effects. However, current understanding of how terrestrial biodiversity is impacted by past abrupt land changes is incomplete. Here we show that abrupt land change in the past continues to influence present species assemblages globally. We combine geographically and taxonomically broad data on local biodiversity with quantitative estimates of abrupt land change detected within time series of satellite imagery from 1982 to 2015. Species richness and abundance were 4.2% and 2% lower, respectively, and assemblage composition was altered at sites with an abrupt land change compared to unchanged sites, although impacts differed among taxonomic groups. Biodiversity recovered to levels comparable to unchanged sites after >10 years. Ignoring delayed impacts of abrupt land changes likely results in incomplete assessments of biodiversity change

Benzoxazinoids in Root Exudates of Maize Attract Pseudomonas putida to the Rhizosphere

Benzoxazinoids, such as 2,4-dihydroxy-7-methoxy-2H-1,4-benzoxazin-3(4H)-one (DIMBOA), are secondary metabolites in grasses. In addition to their function in plant defence against pests and diseases above-ground, benzoxazinoids (BXs) have also been implicated in defence below-ground, where they can exert allelochemical or antimicrobial activities. We have studied the impact of BXs on the interaction between maize and Pseudomonas putida KT2440, a competitive coloniser of the maize rhizosphere with plant-beneficial traits. Chromatographic analyses revealed that DIMBOA is the main BX compound in root exudates of maize. In vitro analysis of DIMBOA stability indicated that KT2440 tolerance of DIMBOA is based on metabolism-dependent breakdown of this BX compound. Transcriptome analysis of DIMBOA-exposed P. putida identified increased transcription of genes controlling benzoate catabolism and chemotaxis. Chemotaxis assays confirmed motility of P. putida towards DIMBOA. Moreover, colonisation essays in soil with Green Fluorescent Protein (GFP)-expressing P. putida showed that DIMBOA-producing roots of wild-type maize attract significantly higher numbers of P. putida cells than roots of the DIMBOA-deficient bx1 mutant. Our results demonstrate a central role for DIMBOA as a below-ground semiochemical for recruitment of plant-beneficial rhizobacteria during the relatively young and vulnerable growth stages of maize