Advanced undergraduate experiments in vacuum physics and mass spectrometry

A comprehensive high‐vacuum system has been set up and operated in an advanced undergraduate laboratory for students majoring in physics and microelectronics. The aim of the experiment is to provide the students with both practical experience and basic theoretical understanding of the production and measurement of low pressures. The students measure the pumping speed of a rotary forepump and of an oil diffusion pump, as a function of pressure, using procedures adopted by the AVS. A hot‐cathode ionization gauge and a thermocouple gauge are calibrated against a McLeod (absolute) manometer for several gases. The compositions of ambient air, of an isotopic mixture of neon, and of the residual gases in an oil‐diffusion‐pumped system are determined with the aid of a mass spectrometer. The influence of a liquid‐nitrogen‐cooled surface is assessed. Helium leak detection is demonstrated, and the response and sensitivity of the mass spectrometer as a leak detector are evaluated

Soil analysis using visible and near infrared spectroscopy

Visible-near infrared diffuse reflectance (vis-NIR) spectroscopy is a fast, non-destructive technique well suited for analyses of some of the essential constituents of the soil. These constituents, mainly clay minerals, organic matter and soil water strongly affect conditions for plant growth and influence plant nutrition. Here we describe the process by which vis–NIR spectroscopy can be used to collect soil spectra in the laboratory. Because it is an indirect technique, the succeeding model calibrations and validations that are necessary to obtain reliable predictions about the soil properties of interest, are also described in the chapter

Sampling soil organic carbon to detect change over time

This research describes a generic monitoring design that could be widely applied to detect temporal changes in soil organic carbon stocks (SOC) across a carbon estimation area (CEA) with no prior knowledge of the spatial or temporal variance of SOC within the CEA. The report includes information on: Bases for designing SOC stock sampling for detecting change Monitoring SOC change to verify the effects of land use or management practicesStatistical rationale for monitoring SOC changeQuality measure and constraints for monitoring SOC changeDesign-based optimisation of sample sizesModel-based optimisation of sample sizesHypothesis testingStatistical model for monitoring SOC changeUsing available data and its variability to guide initial sampling designUncertainty in outcomes of monitoring designsSummary and conclusions

Visible and near infrared spectroscopy in soil science

This chapter provides a review on the state of soil visible–near infrared (vis–NIR) spectroscopy. Our intention is for the review to serve as a source of up-to date information on the past and current role of vis–NIR spectroscopy in soil science. It should also provide critical discussion on issues surrounding the use of vis–NIR for soil analysis and on future directions. To this end, we describe the fundamentals of visible and infrared diffuse reflectance spectroscopy and spectroscopic multivariate calibrations. A review of the past and current role of vis–NIR spectroscopy in soil analysis is provided, focusing on important soil attributes such as soil organic matter (SOM), minerals, texture, nutrients, water, pH, and heavy metals. We then discuss the performance and generalization capacity of vis–NIR calibrations, with particular attention on sample pre-tratments, co-variations in data sets, and mathematical data preprocessing. Field analyses and strategies for the practical use of vis–NIR are considered. We conclude that the technique is useful to measure soil water and mineral composition and to derive robust calibrations for SOM and clay content. Many studies show that we also can predict properties such as pH and nutrients, although their robustness may be questioned. For future work we recommend that research should focus on: (i) moving forward with more theoretical calibrations, (ii) better understanding of the complexity of soil and the physical basis for soil reflection, and (iii) applications and the use of spectra for soil mapping and monitoring, and for making inferences about soils quality, fertility and function. To do this, research in soil spectroscopy needs to be more collaborative and strategic. The development of the Global Soil Spectral Library might be a step in the right direction

Meta-analysis of rare events: the challenge of combining the lack of information

For both count and incidence rate data, it is complicated to provide reliable inference of a treatment effect when the number of observed events is too low. Therefore, the idea of regrouping several studies to increase the amount of available information seems particularly appealing in such settings. Unfortunately, standard meta-analysis methods break down with rare events. This thesis aimed at studying the challenge of combining the lack of information. Throughout four articles, we assessed, via simulations, the performance of several alternative meta-analysis methods that better accommodate rare events. Not only did we consider existing methods, but we also designed innovative methods for both count and incidence rate data. Based on the results obtained in these different papers, we were able to draw several recommendations for applied researchers. With count data, and under the assumption of a homogeneous treatment effect, the Mantel-Haenszel method can be used safely, no matter the scarcity level considered. A newly designed pseudo-likelihood approach performed as well as the Mantel-Haenszel method and allowed a gain of precision when the meta-analysis included studies with missing treatment arms. Moreover, unlike Mantel-Haenszel, this pseudo-likelihood approach could be extended to settings with treatment effect heterogeneity and was shown to provide good estimates of the mean treatment effect and informative prediction intervals, even in extremely rare event settings. As for the meta-analysis of incidence rate data, we found that accounting for over-dispersion using a negative-binomial model allowed for improvements in the performance of the classical Poisson model, even in the presence of studies reporting zero event and/or only one treatment arm