Exposure assessment and analysis for biological agents

Given the increasing concern about microplastics (MPs) and nanoplastics (NPs) in the atmosphere, numerous studies have been conducted on their presence and impacts. This review explores the occurrence, sources, physicochemical characteristics, and the sampling and analytical methods of MPs and NPs in ambient air. MPs are primarily found in the form of fibers and fragments, with sizes generally exceeding several micrometers, and have been detected in various environments, including urban, industrial, coastal, and remote areas. Currently, there are no standardized methods for sampling and analyzing MPs and NPs in the atmosphere. Existing studies predominantly employ passive sampling methods to collect depositable microplastics and active sampling methods for suspended MPs. In the laboratory, most samples are treated with H2O2 and then separated by density before being analyzed using microscopy and spectroscopic techniques such as FT-IR and Raman. However, the current sampling and analytical methods have proven insufficient for detecting the presence of NPs in the air. Therefore, there is a need to develop new sampling and analytical methods to determine them in the atmospheric environment.

The surrogate model-based sampling method has been an active area of research due to its evident efficiency over direct sampling method. The fusion of the adaptive kriging (AK) model with the adaptive radial-based importance sampling (ARBIS) method is developed as an improvement of the AK model combined with Monte Carlo simulation (MCS) method especially for estimating the small failure probabilities. In the AK–ARBIS method, the number of candidate samples in each updating process of the kriging model is reduced through partitioning the whole MCS sample domain into different subdomains and removing the samples inside the last subdomain from the participating candidate sampling pool, which can avoid the time-consuming matrix operation involved in kriging predictions in order to find the best training sample in each updating step. In the existing AK–ARBIS method, kriging model stops updating according to the learning function-based stopping criterion, which cannot directly reflect the error of the estimated failure probability. In this regard, this paper proposes the error-based stopping criterion (ESC) enhanced AK–ARBIS method, where the processes of finding the optimal hypersphere and accurately identifying the sign of candidate samples are decoupled in order to successfully embed the ESC. In addition to embedding the ESC into the AK–ARBIS method, two target-oriented candidate sampling reduction strategies are investigated, respectively, to improve the efficiency of finding the optimal hypersphere and accurately identifying the sign of the participating candidate samples. Based on the candidate sampling pool reduction strategies and ESC, both the computational time and the required number of calls to the real limit state function are reduced over the existing AK–ARBIS method. Three case studies are analyzed to demonstrate the accuracy and efficiency of the proposed enhanced AK–ARBIS method, especially for estimating the small failure probabilities.

This paper aims to quantify data uncertainties in marine microplastic measurements, including spatiotemporal sampling error and sample volume estimation error, identify impacts of varying mesh sizes, sampling and analysis methods, and evaluate consistency in multiple microplastic observation datasets. Twenty-seven datasets on surface marine microplastics with particle size >100 µm in the Baltic Sea are compiled. Results show that the trawl datasets have a spatiotemporal sampling error of 25% for microlitter concentration, 36% for microplastic fiber concentrations and 40-56% for microplastic particle concentration. By taking surface currents and wave-induced Stokes drift into account, the sample volume of the trawl measurements is corrected, leading to a mean microplastic concentration correction of 12%. The differences of microplastic concentration between datasets with varying mesh sizes from 100 – 500 µm are not statistically significant. Analysis methods, however, can lead to significant differences in microplastic datasets. The dataset consistency is further examined among the three dataset categories using trawl, pump and bulk sampling techniques. It is found that an individual dataset is often self-consistent. Most of the datasets within one monitoring category are more consistent than those from different categories. More than 70% of the datasets within individual categories are consistent, which have mean microplastic concentration significantly smaller than the rest of the datasets. Significant inconsistencies are identified between different data categories. Six out of eight highest relative standard deviations are found in the pump and bulk datasets. The median value of the mean microplastic concentration from the 10 pump datasets is about 4.5 times as much as that of the 14 trawl datasets, both for fiber and non-fiber particles. Significant differences are also identified on microplastic fiber fraction in different dataset categories. Two thirds of the 13 bulk and pump datasets have a microplastic fiber fraction >85% while the 14 trawl datasets show much lower microplastic fiber fractions between 45-70%. In addition, the particle collection efficiency, potential leakage of particles with irregular shapes, clogging, the false zero samples and related lower limit of the detectable microplastic concentration for given sampling methods and water environment, are also discussed.

To get representative soil samples, a sampling method was verified for crop fields in the vicinity of abandoned mine sites. Application of appropriate sampling or analytical methods is very important as it affects the costs, time, and accuracy of the refined investigation of soil contamination. Two-time sampling for each crop field was conducted to verify the reproducibility of a zigzag method for soil sampling. The soil analysis using a portable X-ray fluorescence (pXRF) device was conducted to measure concentrations of metal species in soils, and its results were compared to the extracted concentrations by the Korean Standard Test (KST) for soils. As a result, the determination coefficient (R (2)) of linear regression analysis for data obtained by ex situ precise measurement or in situ field screening using pXRF was closely related with the ratio of the extracted concentration by KST to interference-free detection limits (IFDL) of pXRF (designated as KST/IFDL). As the specific metal species had a higher ratio of KST/IFDL, its R (2) was even higher in the field screening tests. However, the slopes of linear regression analysis for most metal species extracted by aqua-regia were close to 1.0 so that extracted concentrations by aqua-regia were similar to the analytical values obtained by pXRF, whereas extraction using a weak acid (0.1 M HCl) had different slopes for soils contaminated with different ranges of concentrations of metal species. Especially Zn showed not only high ratios of KST/IFDL because of aqua regia extraction, but also high determination coefficients. Because of its simple, rapid, and accurate capacities for metal analysis, the pXRF analysis showed high applicability in ex situ precise measurements or in situ field screening of metal analysis. In terms of applicability for regulation, especially in situ pXRF field screening with the zigzag method could be effectively applied to achieve an economical survey by determining hot spots or non-contaminated areas if aqua-regia was applied as the extracting agent in the KST for soils.

The subject of this research in the method of finding proof of theoretical hypotheses based on their content. It demonstrated that historically this method emerged in geometry, and thus is called geometric (by origin) method of analysis and synthesis. Then it was shifted to mechanics by Galileo, and later to other sciences, never obtaining the status of the universal method for confirming theoretical hypotheses. The author conducts gnoseological analysis of this method. First, gnoseological analysis of the three initial forms is carried out on the basis of the three elementary geometric theorems. Then description is given to qualitative transformations that followed its transfer to other sciences. The author discusses the correlation of this method with the classical method of analysis and synthesis, as well as with experimental and hypothetical-deductive method. The main conclusion consists in the thesis that in accordance with its gnoseological status, the method of geometric (by origin) analysis and synthesis is on the same level as the classical method of analysis and synthesis, as well as experimental and hypothetical-deductive method. The author’s special contribution lies in substantiation of the thesis that with the development of science, this method of geometric origin was generalized to the method of finding proof of any theoretical hypotheses. Determination of qualitative changes that occurred in terms of its transfer from geometry to special sciences has an important methodological meaning. The author notes the role of idealization in the process of shifting into theoretical description of researched objects the results of practical actions with them.

The usefulness of microbiological standards for frozen foods is now a controversy in the trade and scientific literature. Most reviewers have given arguments both for and against, and have concluded that they should be applied with great caution. Such standards have the advantage of putting questions of safety on a convenient numerical basis. Canadian workers have reported that promulgation of standards has invariably raised the hygienic level of the products controlled. Bacteriological standards have often been associated with the question of safety to the consumer. Everyone recognizes that food poisoning bacteria are a potential danger in any food. But many have argued that the history of food poisoning outbreaks from frozen foods is excellent and that there is no need for standards; on the other hand, proponents of standards have pointed to the incomplete investigation and reporting of outbreaks, and have argued that there may be more outbreaks than we realize. They have pointed to laboratory studies that have shown grossly mishandled precooked frozen foods to be truly dangerous. Some have proposed that pathogens should be absent from foods; but others have questioned that a microbiological standard can accomplish this end. Some pathogens, such as Salmonella or Staphylococcus have been shown to be so ubiquitous that their presence in some commercial foods is unavoidable. Also, sampling and analytical methods have been described as inadequate to guarantee that pathogens present will be detected. Some have argued that control at the source is a better way-through inspections of the plant operation, by enforcement of handling codes, or by processing procedures such as pasteurization, which would be more certain to result in a pathogen-free food.A most important part of any of the proposed standards is a "total count" of viable aerobic bacteria. English workers have found that foods causing poisoning outbreaks usually had total viable counts above 10 million per gram. On the other hand, these same workers found Salmonella on meats with very low total viable count. The assumption by many that low total count indicates safety has been shown to be not always true. Furthermore, high counts of nonpathogenic organisms, such as psychrophilic saprophytes would have no public health significance. The relation between bacterial level and quality is open to less controversy. Some authorities have pointed to bacterial level as a measure of sanitation, adequacy of refrigeration, or speed of handling. Others have indicated that to determine which of these factors caused a high count would be impossible with only a total count on the product as a guide. Some investigators have said a high count affects flavor adversely before actual spoilage is evident, and this may be a factor in competition on today's market. It is well established that initial bacterial level will affect the shelf-life of a chilled product. Methods of analysis are more nearly adequate for counts than for pathogens, but they need improvement, and should be clearly specified as part of any bacteriological standard. Foods with high count could sometimes be brought into compliance merely by storing them for a sufficient period frozen, or by heating them slightly. This has been cited by some authors as a disadvantage of bacteriological standards. The enterococci and the coliform group (except Escherichia coli) have been shown to be ubiquitous and therefore should not be used alone to indicate fecal contamination. Although E. coli has greater significance, its source should be determined each time it is found. Various reviewers have expressed the need for caution in the application of standards. The principal precautionary arguments we have found are as follows:1) A single set of microbiological standards should not be applied to foods as a miscellaneous group, such as "frozen foods" or "precooked foods."2) Microbiological standards should be applied first to the more hazardous types of foods on an individual basis, after sufficient data are accumulated on expected bacterial levels, with consideration of variations in composition, processing procedures, and time of frozen storage.3) When standards are chosen, there should be a definite relation between the standard and the hazard against which it is meant to protect the public.4) Methods of sampling and analysis should be carefully studied for reliability and reproducibility among laboratories, and chosen methods should be specified in detail as part of the standard.5) Tolerances should be included in the standard to account for inaccuracies of sampling and analysis.6) At first, the standard should be applied on a tentative basis to allow for voluntary compliance before becoming a strictly enforced regulation.7) Microbiological standards will be expensive to enforce.8) If standards are unwisely chosen they will not stand in courts of law.

We describe sampling methods and provide software to accurately and efficiently estimate snag and tree densities at desired scales to meet a variety of research and management objectives. The methods optimize sampling effort by choosing a plot size appropriate for the specified forest conditions and sampling goals. Plot selection and data analyses are supported by SnagPRO, a software program designed specifically to serve our sampling methods. We present two sampling methods to estimate density and associated characteristics of snags and trees. The first method requires sampling until a desired precision is obtained for a density estimate. The second method compares estimated densities with target densities, such as target snag densities specified under a land management plan. Our methods of snag and tree sampling are compatible with recently developed methods of log sampling, thereby improving efficiencies by enabling the simultaneous collection of all three habitat components—snags, large trees, and logs—to meet research or management objectives for a variety of resource disciplines, including wildlife, silviculture, fuels, and soils. Recently developed methods of log sampling also use SnagPRO for data collection and analysis. Our methods and software are particularly relevant to forest management, given that nearly all federal land use plans require monitoring of snag and tree densities in relation to management direction for wildlife. Staffing and budgets available to estimate snag and tree densities, however, are extremely limited, and thus require efficient methods to achieve acceptable accuracy. Our methods are an efficient approach for estimating snag and tree densities, particularly when combined with use of the supporting SnagPRO software.

Novel environmental air and water mycobacteria sampling and analytical methods are needed to circumvent difficulties associated with the use of culture-based methodologies. To implement this objective, a commercial, clinical, genus DNA amplification method utilizing the polymerase chain reaction (PCR) was interfaced with novel air sampling strategies in the laboratory. Two types of air samplers, a three-piece plastic, disposable filter cassette and an eight-stage micro-orifice uniform deposit impactor (MOUDI), were used in these studies. In both samplers, 37-mm polytetrafluoroethylene (PTFE) filters were used. Use of the MOUDI sampler permitted the capture of airborne mycobacteria in discrete size ranges, an important parameter for relating the airborne mycobacteria cells to potential respirable particles (aerodynamic diameter <10 microm) capable of causing health effects. Analysis of the samples was rapid, requiring only 1-1.5 days, as no microbial culturing or DNA purification was required. This approach was then used to detect suspected mycobacteria contamination associated with pools at a large public facility. PCR was also used to analyze various water samples from these pools. Again, no culturing or sample purification was required. Water samples taken from all ultraviolet light/hydrogen peroxide-treated whirlpools tested positive for the presence of mycobacteria. No mycobacteria were detected in the chlorine-treated pools and the water main supply facility. All air samples collected in the proximity of the indoor whirlpools and the associated changing rooms were strongly positive for airborne mycobacteria. The airborne mycobacteria particles were predominantly collected on MOUDI stages 1-6 representing an aerodynamic size range of 0.5 to 9.9 microm. In conclusion, using this approach permits the rapid detection of mycobacteria contamination as well as the routine monitoring of suspected pools. The approach circumvents problems associated with culture-based methods such as fungal overgrowth on agar plates, and the presence of nonculturable or difficult to culture mycobacteria strains.

The response surface method (RSM) is a powerful approach for carrying out reliability analysis for complicate engineering with implicit limit state functions. The quality of a response surface mainly depends on the choice of response surface function and the selection of sample points. To investigate the influence of the types of response surface functions and to reduce the computation efforts, two new sampling methods and a hybrid RSM are proposed. In the hybrid RSM, four types of response surface functions and three sampling methods are involved, and each Response surface function can be connected to each sampling method. The four response surface functions are quadratic polynomial without cross terms (PN1), quadratic polynomial with cross terms, radial basic function network (RBFN) and support vector machine (SVM). The three RSMs using the traditional sampling method, the new iterative sampling method and the new experiment design method are RSM1, RSM2 and RSM3, respectively. The accuracy and efficiency of different RSMs are illustrated through three examples. When an iterative method is used for locating sample points, the PN1-based RSM2 is proposed for its accuracy and efficiency. And when an experiment design method is used for locating sample points, the RBFN- or SVM-based RSM3 is suggested because the RBFN or SVM is suitable for global fitting.

The problem of sampling constrained continuous distributions has frequently appeared in many machine/statistical learning models. Many Markov Chain Monte Carlo (MCMC) sampling methods have been adapted to handle different types of constraints on random variables. Among these methods, Hamilton Monte Carlo (HMC) and the related approaches have shown significant advantages in terms of computational efficiency compared with other counterparts. In this article, we first review HMC and some extended sampling methods, and then we concretely explain three constrained HMC‐based sampling methods, reflection, reformulation, and spherical HMC. For illustration, we apply these methods to solve three well‐known constrained sampling problems, truncated multivariate normal distributions, Bayesian regularized regression, and nonparametric density estimation. In this review, we also connect constrained sampling with another similar problem in the statistical design of experiments with constrained design space.This article is categorized under: Applications of Computational Statistics &gt; Computational Mathematics Statistical and Graphical Methods of Data Analysis &gt; Bayesian Methods and Theory Statistical and Graphical Methods of Data Analysis &gt; Markov Chain Monte Carlo (MCMC) Statistical and Graphical Methods of Data Analysis &gt; Sampling

Substances that are airborne and toxic by inhalation are usually evaluated by sampling and analysis of the relative or absolute concentration of the substance in air. First it is necessary to state the reason for evaluation: determining the sources of emissions in work processes; determining the quantity of emissions to the environment; determining compliance with regulations and guidelines; determining the exposure distribution for affected persons; determining the effect of process modification on exposure; and determining risk of disease. Once the desired outcome has been clearly stated it is possible to consider a strategy for sampling that involves sample number, distribution and timing. The sampling strategy also affects the selection of sampling and analysis methods, including requirements of selectivity, sensitivity and accuracy. Methods may be prescriptive, and following such methods strictly may be a requirement under regulation or for accreditation. Conversely, today's technology allows many options and variations that may not have been available in the past. Changing requirements, such as changes to concentration limit values, require a degree of flexibility. This chapter describes the theory and technology for sampling aerosols in general and beryllium aerosols in particular, with sufficient background and discussion to allow the user to select with confidence from the available options the tools and techniques most applicable to the desired outcome. It must be kept in mind that an air sample is only ever an estimate of exposure with an uncertainty that is associated with the methodology both of the strategy and the procedure.

The purpose of this study is to investigate the influence of financial leverage, liquidity, asset growth, size on the beta stock in manufacturing companies in Indonesia Stock Exchange. The sample in this study is manufacturing companies listed in Indonesia Stock Exchange during the 5 periods (2008-2012). Total samples are 58 companies. The sample selection is done by using the method of stratified random sampling. The multiple linear regression analysis was used to test the hypothesis.This research found that asset growth has significant effect on systematic risk, while variable financial leverage, liquidity, sizedid not have significant effect on systematic risk. The purpose of this study is to investigate the influence of financial leverage, liquidity, asset growth, sizeon the beta stock in manufacturing companies in Indonesia Stock Exchange. The sample in this study is manufacturing companies listed in Indonesia Stock Exchange during the 5 periods (2008-2012). Total samples are 58 companies. The sample selection is done by using the method of stratified random sampling. The multiple linear regression analysis was used to test the hypothesis.This research found that asset growth has significant effect on systematic risk, while variable financial leverage, liquidity, sizedid not have significant effect on systematic risk.

The draft ASTM Standard, "Standard Practice for Bulk Sample Collection and Swab Sample Collection of Visible Powders Suspected of Being Biological Agents from Nonporous Surfaces," was validated in a collaborative study consisting of 6 teams comprised of Civil Support personnel and First Responders, 2 levels of Bacillus anthracis Sterne and Bacillus thuringiensis Kurstaki spores, and 7 nonporous surfaces. The sample collection standard includes collection of the bulk sample (Method A) using a dry swab to push the sample onto a collection card and collection of residual sample (Method B) using an onsite test kit followed by a wet swab intended for additional onsite testing. Method A is to be performed prior to Method B in order to preserve unadulterated sample as potential criminal evidence. While statistical differences were observed between surfaces, between teams, and the interaction of surfaces and teams for the various sample types collected, these differences are due to the very low variability of the data and a much more narrow distribution than an ideal normal distribution, rather than to any practical differences. The data demonstrate that from both the 1.0 and 0.01 g powder samples, high levels of spores (mean >10(6) CFU) are recovered from the 7 surfaces by both the dry swab used in bulk sample collection (Method A) and the wet swab (Method B) sampling of the residual powder after bulk sample collection. Thus, after bulk sample collection, there is a high level of residual spores remaining for onsite biological testing and both Methods A and B should be performed in the field.

Limits of our knowledge, part 2: Selected frontiers in marine organic biogeochemistry

Food losses due to crop infections caused by different pathogens such as bacteria, viruses and fungi are persistent issues in agriculture for centuries across the globe. The timely detection and appropriate identification of casual agents associated with diseases of crop plants or seeds are considered to be the most important issue in formulating the management strategies. Seed health testing to detect seed-borne pathogens is an important step in the management of crop diseases. Specificity, sensitivity, speed, simplicity, cost-effectiveness and reliability are the main requirements for the selection of seed health test methods. Examples of frequently used seed assays include visual examination, selective media, seedling grow-out and serological assays which, while appropriate for some pathogens, often display inadequate levels of sensitivity, specificity and accuracy. Polymerase chain reaction (PCR) has emerged as a tool for the detection of microorganisms from diverse environments. Thus far, it is clear that nucleic acid-based detection protocols exhibit higher level of sensitivity than conventional methods. Unfortunately, PCR-based seed tests require the extraction of PCR-quality DNA from target pathogens in backgrounds of saprophytic organisms and inhibitory seed-derived compounds. The inability to efficiently extract PCR-quality DNA from seeds has restricted the acceptance and application of PCR for the detection of seed-borne pathogens. To overcome these limitations, several modified PCR protocols have been developed including selective target colony enrichment followed by PCR (Bio-PCR). These techniques seek to selectively concentrate or increase target organism populations to enhance detection and have been successfully applied for detecting fungi in seed. Ultimately, improved protocols based upon PCR, ELISA, etc. will be available for the detection of all seed-borne pathogens and may supersede conventional detection methods. This chapter provides a comprehensive overview of conventional and modern tools used for the early detection and identification of seed-borne fungal pathogens.