gesttools: General Purpose G-Estimation in R

In this paper we present gesttools, a series of general purpose, user friendly functions with which to perform g-estimation of structural nested mean models (SNMMs) for time-varying exposures and outcomes in R. The package implements the g-estimation methods found in Vansteelandt and Sjolander (2016) and Dukes and Vansteelandt (2018), and is capable of analysing both end of study and time-varying outcome data that are either binary or continuous, or exposure variables that are either binary, continuous, or categorical. It also allows for the fitting of SNMMs with time-varying causal effects, effect modification by other variables, or both, as well as support for censored data using inverse weighting. We outline the theory underpinning these methods, as well as describing the SNMMs that can be fitted by the software. The package is demonstrated using simulated, and real-world inspired datasets

Performance Evaluation of Bluetooth Low Energy Communication

Bluetooth Low Energy (BLE), also known as Bluetooth Smart is the new power efficient version of Bluetooth. With the massive increase in the use of IoT devices, their compatibility and suitability for use with BLE, it has become an important protocol for communication. The performance of the protocol in terms of throughput, however, remains untested. Several parameters like connection interval, packet size per connection interval, data length extension and others constitute the implementation of the BLE protocol on a device. These parameters directly or indirectly effect the throughput of devices communicating over BLE. In this paper, we evaluated BLE performance by performing experiments to calculate throughput with varying values of connection interval and MTU size of application payload. We provide experimental values of throughput and compare it with the theoretically expected results and discuss the pattern and aberration found

The impact of COVID-19 on anxiety and wellbeing for families of individuals with Special Education Needs and Disabilities in the UK

COVID-19 has affected people across the world. However, it has been suggested that individuals with Special Education Needs and Disabilities (SEND) and their families might have been particularly impacted by the first national lockdown in the UK. In contrast to previous studies, the current study examined wellbeing and anxiety at different time points and included a control group matched for family situation. Parents of 402 individuals with SEND reported on their own anxiety and wellbeing as well as that of their son/daughter at three time points (before COVID-19, when COVID-19 pandemic started, and during the national lockdown). In addition, data from 186 typically developing (TD) siblings was obtained. Repeated measures ANOVAs and regression analyses showed that, although both individuals with SEND and their TD siblings showed increased anxiety across the three time points, levels of anxiety were not predicted by age, gender or health. Instead, levels of anxiety in the SEND group, but not the TD siblings, were predicted by awareness about COVID-19, diagnosis of an existing anxiety disorder as well as parental anxiety. In addition, whilst TD individuals were reported to increasingly worry about social related issues as well as family related issues, those with SEND were reported to worry about issues related to school closures. These findings show that COVID-19 impacts the wellbeing of those with SEND differently to that of their TD siblings and that school closures have a particular effect on this group. Further implications for policy impact and interventions are discussed

Reviews and syntheses: Soil responses to manipulated precipitation changes – an assessment of meta-analyses

In the face of ongoing and projected climatic changes, precipitation manipulation experiments (PMEs) have produced a wealth of data about the effects of precipitation changes on soils. In response, researchers have undertaken a number of synthetic efforts. Several meta-analyses have been conducted, each revealing new aspects of soil responses to precipitation changes. Here, we conducted a comparative analysis of the findings of 16 meta-analyses focused on the effects of precipitation changes on 42 soil response variables, covering a wide range of soil processes. We examine responses of individual variables as well as more integrative responses of carbon and nitrogen cycles. We find strong agreement among meta-analyses that belowground carbon and nitrogen cycling accelerate under increased precipitation and slow under decreased precipitation, while bacterial and fungal communities are relatively resistant to decreased precipitation. Much attention has been paid to fluxes and pools in carbon, nitrogen, and phosphorus cycles, such as gas emissions, soil carbon, soil phosphorus, extractable nitrogen ions, and biomass. The rates of processes underlying these variables (e.g., mineralization, fixation, and (de)nitrification) are less frequently covered in meta-analytic studies, with the major exception of respiration rates. Shifting scientific attention to these less broadly evaluated processes would deepen the current understanding of the effects of precipitation changes on soil and provide new insights. By jointly evaluating meta-analyses focused on a wide range of variables, we provide here a holistic view of soil responses to changes in precipitation

Surface oxides, carbides, and impurities on RF superconducting Nb and Nb3Sn: A comprehensive analysis

Surface structures on radio-frequency (RF) superconductors are crucially important in determining their interaction with the RF field. Here we investigate the surface compositions, structural profiles, and valence distributions of oxides, carbides, and impurities on niobium (Nb) and niobium-tin (Nb3Sn) in situ under different processing conditions. We establish the underlying mechanisms of vacuum baking and nitrogen processing in Nb and demonstrate that carbide formation induced during high-temperature baking, regardless of gas environment, determines subsequent oxide formation upon air exposure or low-temperature baking, leading to modifications of the electron population profile. Our findings support the combined contribution of surface oxides and second-phase formation to the outcome of ultra-high vacuum baking (oxygen processing) and nitrogen processing. Also, we observe that vapor-diffused Nb3Sn contains thick metastable oxides, while electrochemically synthesized Nb3Sn only has a thin oxide layer. Our findings reveal fundamental mechanisms of baking and processing Nb and Nb3Sn surface structures for high-performance superconducting RF and quantum application

Principled Selection of Baseline Covariates to Account for Censoring in Randomized Trials with a Survival Endpoint

The analysis of randomized trials with time-to-event endpoints is nearly always plagued by the problem of censoring. As the censoring mechanism is usually unknown, analyses typically employ the assumption of non-informative censoring. While this assumption usually becomes more plausible as more baseline covariates are being adjusted for, such adjustment also raises concerns. Pre-specification of which covariates will be adjusted for (and how) is difficult, thus prompting the use of data-driven variable selection procedures, which may impede valid inferences to be drawn. The adjustment for covariates moreover adds concerns about model misspecification, and the fact that each change in adjustment set, also changes the censoring assumption and the treatment effect estimand. In this paper, we discuss these concerns and propose a simple variable selection strategy that aims to produce a valid test of the null in large samples. The proposal can be implemented using off-the-shelf software for (penalized) Cox regression, and is empirically found to work well in simulation studies and real data analyses

Reconstruction of the spin state

System of 1/2 spin particles is observed repeatedly using Stern-Gerlach apparatuses with rotated orientations. Synthesis of such non-commuting observables is analyzed using maximum likelihood estimation as an example of quantum state reconstruction. Repeated incompatible observations represent a new generalized measurement. This idealized scheme will serve for analysis of future experiments in neutron and quantum optics.Comment: 4 pages, 1 figur