Feasibility and Diagnostic Accuracy of Saliva-Based SARS-CoV-2 Screening in Educational Settings and Children Aged <12 Years

Children have been disproportionately affected during the COVID-19 pandemic. We aimed to assess a saliva-based algorithm for SARS-CoV-2 testing to be used in schools and childcare institutions under pandemic conditions. A weekly SARS-CoV-2 sentinel study in primary schools, kindergartens, and childcare facilities was conducted over a 12-week-period. In a sub-study covering 7 weeks, 1895 paired oropharyngeal and saliva samples were processed for SARS-CoV-2 rRT-PCR testing in both asymptomatic children (n = 1243) and staff (n = 652). Forty-nine additional concurrent swab and saliva samples were collected from SARS-CoV-2 infected patients (patient cohort). The Salivette® system was used for saliva collection and assessed for feasibility and diagnostic performance. For children, a mean of 1.18 mL saliva could be obtained. Based on results from both cohorts, the Salivette® testing algorithm demonstrated the specificity of 100% (95% CI 99.7–100) and sensitivity of 94.9% (95% CI 81.4–99.1) with oropharyngeal swabs as reference. Agreement between sampling systems was 100% for moderate to high viral load situations (defined as Ct-values <33 from oropharyngeal swabs). Comparative analysis of Ct-values derived from saliva vs. oropharyngeal swabs demonstrated a significant difference (mean 4.23; 95% CI 2.48–6.00). In conclusion, the Salivette® system proved to be an easy-to-use, safe and feasible saliva collection method and a more pleasant alternative to oropharyngeal swabs for SARS-CoV-2 testing in children aged 3 years and above.

Microplastic concentrations, characteristics, and fluxes in water bodies of the Tollense catchment, Germany, with regard to different sampling systems

The widespread presence of microplastics in multiple environmental compartments has largely been demonstrated. Assessing the ecological risk that microplastics pose is, at the present stage, hindered due to methodical differences. Moreover, different methods hamper meaningful comparisons between studies and data on microplastics <300 μm is scarce. Therefore, we focused on microplastics >20 μm in freshwater and sampling-related aspects in this concern. Sampling was conducted between 2018 and 2020 in the Tollense catchment in northeastern Germany and was carried out by in situ pump filtration. Two different sampling systems (cutoff sizes 20 μm and 63 μm) were applied to filter water volumes of 0.075–1.836 m3. Retained particles were analyzed by a combination of Nile red staining and micro-Raman spectroscopy. Thereby, we found microplastic concentrations between 123 and 1728 particles m−3 using the 63-μm cut-off size and between 1357 and 2146 particles m−3 using the 20-μm cut-off size. Local hydrodynamics (discharge and flow velocity) and land cover are likely influencing the observed microplastic concentrations and fluxes. The variability between both sampling systems cannot fully be explained by the different mesh sizes used. We argue that differentiation between a theoretical cut-off size (finest mesh) and a factual cut-off size (reliable quantification) can help to understand sampling related differences between studies.

Use of Discrete Element Modelling to Evaluate the Parameters of the Sampling Theory in the Feed Grade Sampler of a Sulphide Gold Plant

Cross-stream cutters are widely used in the mining and resources industry to obtain representative samples of particulate flows. Discrete element modelling (DEM) and analysis can be used to investigate influences of operational parameters, sampler design and material physical properties in the generation of the Increment Extraction Error (IEE), which when present, results in a frequently biased, non-representative sample. The study investigates the practicality of the rules and recommendations proposed by Dr. Pierre Gy that were developed and established as principles for the correct extraction of samples in industrial sampling equipment. Results validate Pierre Gy’s sampling theory using DEM in a cross-stream cutter of a sulphide gold plant. Importantly, the outcomes indicate that careful consideration must be given to physical ore properties and, consequently, that sampling systems should be developed specifically to each application.

Design of Miniaturized Sensors for a Mission-Oriented UAV Application: A New Pathway for Early Warning

In recent decades, the increasing threats associated with Chemical and Radiological (CR) agents prompted the development of new tools to detect and collect samples without putting in danger first responders inside contaminated areas. A particularly promising branch of these technological developments relates to the integration of different detectors and sampling systems with Unmanned Aerial Vehicles (UAV). The adoption of this equipment may bring significant benefits for both military and civilian implementations. For instance, instrumented UAVs could be used in support of specialist military teams such as Sampling and Identification of Biological, Chemical and Radiological Agents (SIBCRA) team, tasked to perform sampling in contaminated areas, detecting the presence of CR substances in field and then confirming, collecting and evaluating the effective threats. Furthermore, instrumented UAVs may find dual-use application in the civil world in support of emergency teams during industrial accidents and in the monitoring activities of critical infrastructures. Small size drones equipped with different instruments for detection and collection of samples may enable, indeed, several applications, becoming a tool versatile and easy to use in different fields, and even featuring equipment normally utilized in manual operation. The authors hereby present the design of miniaturized sensors for a mission-oriented UAV application and the preliminary results from an experimental campaign performed in 2020.

Analytical protocols for Phobos regolith samples returned by the Martian Moons eXploration (MMX) mission

Japan Aerospace Exploration Agency (JAXA) will launch a spacecraft in 2024 for a sample return mission from Phobos (Martian Moons eXploration: MMX). Touchdown operations are planned to be performed twice at different landing sites on the Phobos surface to collect > 10 g of the Phobos surface materials with coring and pneumatic sampling systems on board. The Sample Analysis Working Team (SAWT) of MMX is now designing analytical protocols of the returned Phobos samples to shed light on the origin of the Martian moons as well as the evolution of the Mars–moon system. Observations of petrology and mineralogy, and measurements of bulk chemical compositions and stable isotopic ratios of, e.g., O, Cr, Ti, and Zn can provide crucial information about the origin of Phobos. If Phobos is a captured asteroid composed of primitive chondritic materials, as inferred from its reflectance spectra, geochemical data including the nature of organic matter as well as bulk H and N isotopic compositions characterize the volatile materials in the samples and constrain the type of the captured asteroid. Cosmogenic and solar wind components, most pronounced in noble gas isotopic compositions, can reveal surface processes on Phobos. Long- and short-lived radionuclide chronometry such as 53Mn–53Cr and 87Rb–87Sr systematics can date pivotal events like impacts, thermal metamorphism, and aqueous alteration on Phobos. It should be noted that the Phobos regolith is expected to contain a small amount of materials delivered from Mars, which may be physically and chemically different from any Martian meteorites in our collection and thus are particularly precious. The analysis plan will be designed to detect such Martian materials, if any, from the returned samples dominated by the endogenous Phobos materials in curation procedures at JAXA before they are processed for further analyses.

Monitoring airborne inoculum for improved plant disease management. A review

Global demand for pesticide-free food products is increasing rapidly. Crops of all types are, however, under constant threat from various plant pathogens. To achieve adequate control with minimal pesticide use, close monitoring is imperative. Many plant pathogens spread through the air, so the atmosphere is composed of a wide variety of plant pathogenic and non-plant pathogenic organisms, in particular in agricultural environments. Aerobiology is the science that studies airborne microorganisms and their distribution, especially as agents of infection. Although this discipline has existed for decades, the development of new molecular technologies is contributing to an increase in the use of aerobiological data for several purposes, from day-to-day monitoring to improving our understanding of pathosystems. Although the importance of knowing the size and composition of plant pathogen populations present in the air is recognized, technical constraints hinder the development of agricultural aerobiology. Here we review the application of spore sampling systems in agriculture and discuss the main considerations underlying the implementation of airborne inoculum monitoring. The results of this literature review confirm that the use of aerobiological data to study the escape of inoculum from a source and its role in the development of diseases is well mastered, but point at a lack of knowledge to proceed with the deployment of these systems at the landscape scale. Thus, we conclude that airborne inoculum surveillance networks are still in their early stages and although more and more initiatives are emerging, research must be conducted primarily to integrate evolving technologies and improve the access, analysis, interpretation and sharing of data. These tools are needed to estimate short- and medium-term risks, identify the most appropriate control measures with the lowest environmental risk, develop indicators to document the effects of climate change, and monitor the evolution of new genotypes at multiple scales.

The Issues of the Air-Fuel Ratio in Exhaust Emissions Tests Carried Out on a Chassis Dynamometer

Vehicle exhaust emission tests use exhaust sampling systems that dilute the exhaust gas with ambient air. The dilution factor DF is calculated assuming that the combustion is complete, and that the engine is operated at a stoichiometric air-fuel ratio (AFR). These assumptions are not always met. This is especially true for diesel engines. This article discusses the tests to find out what the average lambda (λ) over the ARTEMIS, WLTC and NEDC driving cycles is and how this affects the result of the emission measurements. Measurements were carried out on a chassis dynamometer equipped with a standard emission measurement system used during the homologation. The λ was calculated using the Brettschneider equation. The dilution ratio DR was also determined by measuring the CO2 concentration in the raw exhaust gas. The CO2-tracer method used for this was modified. The median of the λ for a CI vehicle was 1.23–3.31, which makes the relative percentage difference between the DF and DR (DDF) in the range of 28–167%. For a SI vehicle homologated under the WLTP procedure, the median of the λ for the WLTC and ARTEMIS cycles was close to one and DDF for most cycles does not exceed 10%. In order to reduce the influence of the error of DF determination on the result of the emission measurement, it is recommended to use exhaust gas sampling systems that allow to determine the actual dilution ratio or to use the lowest possible dilution. The PAS-CVS system seems to be the most promising.

SPECIES DISTRIBUTION MODELING IN FOREST PLANNING OF ANNUAL PRODUCTION UNITS IN THE SOUTHWEST AMAZONIA

ABSTRACT The generally limited resources for forest management and the growing need of forest production regulation requires the optimization of planning approaches for the spatialization of annual production units (APU). An APU planning methodology for forest species of high wood value (Amburana acreana (Ducke) ACSm., Apuleia leiocarpa (Vogel) JF Macbr. and Castilla ulei Warb.) in management area was proposed, using prediction of potential distribution of these species with data from the occurrence of a census forest inventory. It was used sample inventory data simulated in three sampling systems (random, conglomerate systematic, and systematic) and sample intensities (0.5% and 0.8%). As predictive variables, it was used the altitude, vertical distance to the nearest drain, individual bands of the TM sensor on board the Landsat 5, and vegetation index by normalized difference. Eighteen models were obtained, six per species. The test area under the curve (AUC) of the models ranged from 0.517 to 0.804. For all species, the best predictive model was considered the conglomerate system with a sample intensity of 0.8%. Altitude was the predictor variable that most contributed to the models. The AUC values for the Amburana acreana models were significantly different from Apuleia leiocarpa and Castilla ulei (p = 0.0138). For species of lower density, it is recommended greater sampling intensity and sampling systems that provide better spatialization of occurrence records. The use of data from sampling forest inventories in different sampling systems is capable of predicting environmental suitability for forest species and helps to define APUs. Thus, it is possible to strenghten the exploration strategies and management planning of management areas and to contribute to the perpetuation of the activity in the unequal forests of the Amazon region.