UNIFIED METHOD OF ADAPTIVE-ROBUST REDUCTION OF UNCERTAINTIES IN THE ELIMINATION OF BLIND SPOTS AND RANGING OF AIR OBJECTS IN PULSE-DOPPLER RADARS

A unified method of disclosing blind ranges, reducing or eliminating measurement ambiguity has been proposed and investigated, which allows, within the framework of a typical long-range detection session of an air object by a pulse-Doppler radar, to reduce time costs, expand information content, and unify algorithmic support of a detection session. At the heart of: unified adaptive-robust procedures for controlling radiation parameters (guaranteeing the observability of an object) and processing ambiguous quasi-measurements of range (in absence of detection) and real measurement (in initial detection).

New tools for automated cryo-EM single-particle analysis in RELION-4.0

We describe new tools for the processing of electron cryo-microscopy (cryo-EM) images in the fourth major release of the RELION software. In particular, we introduce VDAM, a Variable-metric gradient Descent algorithm with Adaptive Moments estimation, for image refinement; a convolutional neural network for unsupervised selection of 2D classes; and a flexible framework for the design and execution of multiple jobs in pre-defined workflows. In addition, we present a stand-alone utility called MDCatch that links the execution of jobs within this framework with metadata gathering during microscope data acquisition. The new tools are aimed at providing fast and robust procedures for unsupervised cryo-EM structure determination, with potential applications for on-the-fly processing and the development of flexible, high-throughput structure determination pipelines. We illustrate their potential on twelve publicly available cryo-EM data sets.

New tools for automated cryo-EM single-particle analysis in RELION-4.0

We describe new tools for the processing of electron cryo-microscopy (cryo-EM) images in the fourth major release of the RELION software. In particular, we introduce VDAM, a Variable-metric gradient Descent algorithm with Adaptive Moments estimation, for image refinement; a convolutional neural network for unsupervised selection of 2D classes; and a flexible framework for the design and execution of multiple jobs in pre-defined workflows. In addition, we present a stand-alone utility called MDCatch that links the execution of jobs within this framework with metadata gathering during microscope data acquisition. The new tools are aimed at providing fast and robust procedures for unsupervised cryo-EM structure determination, with potential applications for on-the-fly processing and the development of flexible, high-throughput structure determination pipelines. We illustrate their potential on twelve publicly available cryo-EM data sets.

Lithium heparin interference in the Abbott enzymatic creatinine assay: the significance of under-filled tubes

Background Spuriously high results using the Abbott Architect enzymatic creatinine assay were noted to be particularly associated with very small sample volumes. This led us to query the effect of under-filling lithium heparin tubes on the measured enzymatic creatinine result. Methods Blood was provided by 5 laboratory personnel and then decanted into 5 x1.2 mL Sarstedt S-Monovette tubes, giving final blood volumes of 200, 400, 600, 800 and 1200 μL. Plasma was analysed using Abbott Architect Jaffe, enzymatic creatinine, Beckman Coulter (AU500) enzymatic creatinine and Roche (Cobas c702) enzymatic creatinine assays. Saline was also added to Sarstedt 1.2 mL and Teklab 2 mL tubes and analysed using the Abbott Jaffe and enzymatic creatinine methods. Results Increasing degrees of under-fill were associated with greater over-estimation of creatinine using the Abbott enzymatic assay, but no difference was noted using Jaffe methodology on the same platform or enzymatic assays provided by Roche or Beckman. On average, creatinine was 40.6% (+27.7 μmol/L) higher when only 200 μL of blood was present in the tube. Small volumes of saline added to lithium heparin tubes measured significant creatinine concentrations using the Abbott enzymatic method. Conclusions Lithium heparin directly interferes in the Abbott Architect enzymatic creatinine assay. Under-filling lithium heparin tubes can lead to clinically significant over-estimation of creatinine results by this assay. Users of this assay should be aware of the potential for spurious results in small sample volumes collected into lithium heparin tubes and implement robust procedures for identifying and reporting results on these samples.

On the Viability of Video Imaging in Leak Rate Quantification: A Theoretical Error Analysis

Optical gas imaging through multispectral cameras is a promising technique for mitigation of methane emissions through localization and quantification of emissions sources. While more advanced cameras developed in recent years have led to lower uncertainties in measuring gas concentrations, a systematic analysis of the uncertainties associated with leak rate estimation have been overlooked. We present a systematic categorization of the involved uncertainties with a focus on a theoretical analysis of projection uncertainties that are inherent to this technique. The projection uncertainties are then quantified using Large Eddy Simulation experiments of a point source release into the atmosphere. Our results show that while projection uncertainties are typically about 5% of the emission rate, low acquisition times and observation of the gas plume at small distances from the emission source (<10 m) can amount to errors of about 20%. Further, we found that acquisition times on the order of tens of seconds are sufficient to significantly reduce (>50%) the projection uncertainties. These findings suggest robust procedures on how to reduce projection uncertainties, however, a balance between other sources of uncertainty due to operational conditions and the employed instrumentation are required to outline more practical guidelines.

An Occupant-Centric Theory of Building Control Systems and Their User Interfaces

This paper presents an occupant-centric theory of buildings’ indoor-environmental control systems and their user interfaces. Buildings typically can have multiple devices and systems to maintain indoor-environmental conditions within certain ranges in order to meet occupants’ health and comfort requirements. Therefore, it is important to understand what those ranges are exactly, who defines them, and for whom. Health and comfort sciences offer some broad directions concerning desirable indoor conditions. These are typically formulated in various codes, standards, and guidelines in terms of target values or the set points of control variables. However, preferable conditions may differ at different times and for different individuals. Another question concerns the agency responsible for maintaining the preferred conditions. In some settings, conditions may be centrally controlled via the buildings’ automation systems, whereas in other settings, occupants might have the possibility to control their immediate surroundings. Given these qualifications, the objective of the present inquiry can be stated more precisely. We outline a human-ecologically inspired theory pertaining to the occupants’ perception of and interaction with a building’s indoor-environmental control systems and their user interfaces. Specifically, we explore the operationalization potential of the proposed theory as a compact assessment protocol for the evaluation of buildings’ responsiveness to occupants’ preferences. Initial experiences with the derivative protocol are promising. Nonetheless, in order to be fully applicable in practice, certain challenges must be addressed. These specifically include the need for more robust procedures toward the translation of occupants’ subjective judgments into quantitative evaluation scales.

Utility of Verification Testing to Confirm Attainment of Maximal Oxygen Uptake in Unhealthy Participants: A Perspective Review

Maximal oxygen uptake (VO2max) is strongly associated with endurance performance as well as health risk. Despite the fact that VO2max has been measured in exercise physiology for over a century, robust procedures to ensure that VO2max is attained at the end of graded exercise testing (GXT) do not exist. This shortcoming led to development of an additional bout referred to as a verification test (VER) completed after incremental exercise or on the following day. Workloads used during VER can be either submaximal or supramaximal depending on the population tested. Identifying a true VO2max value in unhealthy individuals at risk for or having chronic disease seems to be more paramount than in healthy and active persons, who face much lower risk of premature morbidity and mortality. This review summarized existing findings from 19 studies including 783 individuals regarding efficacy of VER in unhealthy individuals to determine its efficacy and feasibility in eliciting a ‘true’ VO2max in this sample. Results demonstrated that VER is a safe and suitable approach to confirm attainment of VO2max in unhealthy adults and children, as in most studies VER-derived VO2max is similar of that obtained in GXT. However, many individuals reveal higher VO2max in response to VER and protocols used across studies vary, which merits additional work identifying if an optimal VER protocol exists to elicit ‘true’ VO2max in this particular population.

Robust Procedures for Estimating and Testing in the Framework of Divergence Measures

The approach for estimating and testing based on divergence measures has become, in the last 30 years, a very popular technique not only in the field of statistics, but also in other areas, such as machine learning, pattern recognition, etc [...]

Comparison of three robust impedance estimators for the MT method

The initial magnetotelluric (MT) response function estimator is based on the least-square theory; it can be severely disturbed by the cultural noise. The different robust procedures have been developed and improve the performance of response function estimation dramatically. It is hard to say which method is better or not. In a specific situation, a different approach has different performance. Therefore, it is important to know the different property of them. Between the robust procedures, the robust M-estimator gives a small weight to reject the outlier based on the residual between the output (electric filed) of the least-squares estimator and the observed data. M-estimator can reduce the influence of unusual data in the electric field (outliers) but are not sensitive to exceptional input (magnetic field) data, which are termed leverage points. The bounded influence (BI) estimator combines the standard robust M-estimator with leverage weighting based on the hat matrix diagonal element's statistics, a standard statistical measure of leverage point. Chave (2004) also creates an open-source code, Bounded Influence Remote Reference Processing (BIRRP), and it is widely used in the MT community. But the leverage point corresponds to the large variation of the magnetic field. It may be an energetic signal or active noise. The performance of the M-estimator and the BI-estimator was dramatically different in the two situations. On the other hand, the repeat median algorithm can protect against unusual data (outlier and leverage point) maximum. We researched the difference property of bound influence (BI-estimator), maximum likelihood (M-estimator), and repeat median (RM-estimator) signal site MT respond function estimator. Three independent code (BIRRP code, robust M-estimator code, and RM-estimator code) are used to compare them. At last, two typical field data are used, making the difference between the bound influence estimator and robust M-estimator transparent. We found that when the leverage point is the energetic signal, the M-estimator will perform better than the BI-estimator. When the leverage point is the active noise, the BI-estimator will work much better than the M-estimator. Finally, we also investigated the ability of the three estimators at a single site.