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T1ρ relaxation imaging is a quantitative imaging technique that has been used to assess cartilage integrity, liver fibrosis, tumors, cardiac infarction, and Alzheimer's disease. T1, T2, and T1ρ relaxation time constants have each demonstrated different degrees of sensitivity to several markers of fibrosis and inflammation, allowing for a potential multi‐parametric approach to tissue quantification. Traditional magnetic resonance fingerprinting (MRF) has been shown to provide quick, quantitative mapping of T1 and T2 relaxation time constants. In this study, T1ρ relaxation is added to the MRF framework using spin lock preparations. An MRF sequence involving an RF‐spoiled sequence with TR, flip angle, T1ρ, and T2 preparation variation is described. The sequence is then calibrated against conventional T1, T2, and T1ρ relaxation mapping techniques in agar phantoms and the abdomens of four healthy volunteers. Strong intraclass correlation coefficients (ICC > 0.9) were found between conventional and MRF sequences in phantoms and also in healthy volunteers (ICC > 0.8). The highest ICC correlation values were seen in T1, followed by T1ρ and then T2. In this study, T1ρ relaxation has been incorporated into the MRF framework by using spin lock preparations, while still fitting for T1 and T2 relaxation time constants. The acquisition of these parameters within a single breath hold in the abdomen alleviates the issues of movement between breath holds in conventional techniques. [ABSTRACT FROM AUTHOR]

Introduction: Time‐resolved three‐dimensional phase contrast MRI (4D flow) of aortic blood flow requires acceleration to reduce scan time. Two established techniques for highly accelerated 4D flow MRI are k‐t principal component analysis (k‐t PCA) and compressed sensing (CS), which employ either regular or random k‐space undersampling. The goal of this study was to gain insights into the quantitative differences between k‐t PCA‐ and CS‐derived aortic blood flow, especially for high temporal resolution CS 4D flow MRI. Methods: The scan protocol consisted of both k‐t PCA and CS accelerated 4D flow MRI, as well as a 2D flow reference scan through the ascending aorta acquired in 15 subjects. 4D flow scans were accelerated with factor R = 8. For CS accelerated scans, we used a pseudo‐spiral Cartesian sampling scheme, which could additionally be reconstructed at higher temporal resolution, resulting in R = 13. 4D flow data were compared with the 2D flow scan in terms of flow, peak flow and stroke volume. A 3D peak systolic voxel‐wise velocity and wall shear stress (WSS) comparison between k‐t PCA and CS 4D flow was also performed. Results: The mean difference in flow/peak flow/stroke volume between the 2D flow scan and the 4D flow CS with R = 8 and R = 13 was 4.2%/9.1%/3.0% and 5.3%/7.1%/1.9%, respectively, whereas for k‐t PCA with R = 8 the difference was 9.7%/25.8%/10.4%. In the voxel‐by‐voxel 4D flow comparison we found 13.6% and 3.5% lower velocity and WSS values of k‐t PCA compared with CS with R = 8, and 15.9% and 5.5% lower velocity and WSS values of k‐t PCA compared with CS with R = 13. Conclusion: Pseudo‐spiral accelerated 4D flow acquisitions in combination with CS reconstruction provides a flexible choice of temporal resolution. We showed that our proposed strategy achieves better agreement in flow values with 2D reference scans compared with using k‐t PCA accelerated acquisitions. [ABSTRACT FROM AUTHOR]

The present study aims to evaluate the effect of archaeological structures in the preservation and recovery of bird remains, in particular by considering the overall shape, open or enclosed, of the structure. Indeed, hollow structures, sometimes of an enclosed shape that may be constructed in masonry, are supposed to have a protective effect on the fragile bones of birds. This is evaluated by considering different variables, such as the ratio of bird remains compared to those of the main domestic mammals used as meat suppliers, the number of bird taxa, or the identification rates for different types of archaeological structures. In a second step, once the impact of the type of structure is evaluated, the same variables are examined according to the social status, to verify their relevance to document this aspect. It transpires that the bird to mammal remains ratio is strongly influenced by the type of structure, as it is higher in enclosed structures. However, some open structures also deliver high bird ratios, in particular at high status sites. In contrast, the bird identification rate is lower in enclosed structures, but this is probably related to the recovery method. Finally, the number of taxa seems more affected by the social status of the consumers responsible for the accumulation of an archaeological assemblage than by the kind of archaeological structure the faunal assemblage was discarded into. This has implications for sampling strategies since open structures, when sieved, sometimes yield high bird to mammal ratios as well as a high number of bird taxa. Therefore, more systematic sieving of large samples of sediment should be applied not only to enclosed structures but also to open contexts such as refuse layers or floors, especially in sites of (potentially) high social status. [ABSTRACT FROM AUTHOR]

The snowpack is important for water resources, tourism, ecology, and the global energy budget. Over the past century, we have gone from point measurements of snow water equivalent (SWE) to estimate spring and summer runoff volumes, to remote sensing of various snowpack properties at continuously finer spatial and temporal resolutions, to various complexities of snowpack and hydrological modeling, to the current fusion of field data with remote sensing and modeling, all to improve our estimates of the snowpack and the subsequent runoff. However, we are still limited by the uncertainty induced by scaling from point field measurements to the area represented by remote sensing and modeling. This paper uses several examples of fine-resolution sampling to issue a call to snow hydrologists and other earth scientists to collect more data, or at least to thoroughly evaluate their sampling strategy for collecting ground-truth measurements. Recommendations are provided for different approaches to have more representative sampling, when at all possible, to collect at least a few more samples or data points.

The task of optimal sampling for the statistical simulation of a discrete random field is addressed from the perspective of minimizing the posterior uncertainty of non-sensed positions given the information of the sensed positions. In particular, information theoretic measures are adopted to formalize the problem of optimal sampling design for field characterization, where concepts such as information of the measurements, average posterior uncertainty, and the resolvability of the field are introduced. The use of the entropy and related information measures are justified by connecting the task of simulation with a source coding problem, where it is well known that entropy offers a fundamental performance limit. On the application, a one-dimensional Markov chain model is explored where the statistics of the random object are known, and then the more relevant case of multiple-point simulations of channelized facies fields is studied, adopting in this case a training image to infer the statistics of a non-parametric model. In both contexts, the superiority of information-driven sampling strategies is proved in different settings and conditions, with respect to random or regular sampling. [ABSTRACT FROM AUTHOR]

Abstract Plastic pollution is a global problem since 2016 when its production reached 322 million tonnes, excluding fibers. Daily discharges of microplastics (MPs, defined as <5 mm in size) are estimated in the range of 50,000 up to 15 million particles, whereas no information on nanoplastic (NP, <100 nm) release is available yet. Different processes further degraded these materials producing more MPs and NPs. This review attempts to fill the void of information on the state-of-art analysis of MPs and NPs (recently identified as emerging contaminants) and provides a critical overview on modern instrumentation, newly developed workflows, and promising techniques for their characterization (Raman and FT-IR spectroscopies and microscopies, pyrolysis and thermal desorption gas chromatography, imaging techniques, etc.). Available analytical methods, validation as well as applications with cells have been taken into account. MP and NP sampling, identification, and characterization are discussed. Finally, recent applications to establish their occurrence in freshwater ecosystems and the effectiveness of the proposed remediation technologies are considered. Highlights • Current sampling strategies for micro- and nanoplastics (MPs and NPs) in the environment are summarized. • Progress on isolation, characterization, and determination of MPs and NPs is reviewed. • Applications focused on MP and MP occurrence in fresh water and remediation systems are presented. • Future trends in the field of MP and NP characterization and determination are discussed. [ABSTRACT FROM AUTHOR]

Abstract Pesticide misuse incidents in residential indoor areas are typically associated with misapplications that are inconsistent with the label directions of the product. Surface wipe sampling and analysis procedures are relied upon to evaluate the extent of indoor contamination and the remediation efforts successfully. In general, surface wipe sampling procedures are widely varied, which can complicate the comparison of the results and data interpretation. Wipe sampling parameters were studied for the insecticides malathion and carbaryl. The parameters evaluated include wipe media, wetting solvents, composite sampling, surface concentration, and the influence of differing product formulations. Porous and nonporous surfaces tested include vinyl tile, plywood and painted drywall (porous/permeable) and stainless steel and glass (nonporous/impermeable). Specific wipe materials included pre-packaged sterile-cotton gauze, pre-cleaned cotton twill, cotton balls, and a pre-packaged, pre-wetted wipe. Commercially available insecticide formulations were tested, and the results were compared to surfaces fortified with neat analytes to determine surface recovery results (efficiency). A sampling procedure to measure pesticide residues was developed, and variables associated with the sampling methods were evaluated to clarify how estimations of surface residues are impacted. Malathion recoveries were 73–86% for twill and pre-wetted, pre-packaged isopropanol wipes on nonporous materials. Malathion formulations ranged from 78 to 124% for pre-wetted, pre-packaged isopropanol wipes and cotton gauze wipes on nonporous materials. Carbaryl and carbaryl formulation recoveries were 82–115% and 77–110%, respectively, on nonporous surfaces for all tested wipe materials. While not every wipe sampling variable could be tested, the collected information from this study may be useful and applied to sampling plans for classes of chemicals with similar physicochemical properties. Graphical abstract Unlabelled Image Highlights • Pesticide contamination poses health exposure risks to responders and public. • Results are hard to compare and interpret if multiple sampling procedures are used. • Wipe media and wipe wetting solvents affect recovery results. • High concentrations and technical formulations did not affect wipe recovery results. • Composite sampling improves recoveries for less compatible solvents and wipe media. [ABSTRACT FROM AUTHOR]

Botrytis cinerea causes botrytis bunch rot (BBR) disease in wine grapes. Small-scale labour-intensive visual disease assessments may not adequately represent an entire vineyard but larger assessments add cost without necessarily improving accuracy or financial returns. BBR-severity data were collected on three dates from two sites and spatially interpolated. Balanced acceptance sampling (BAS) and simple random sampling (SRS) were compared using sample sizes of 2 to 200 vines. Assessment times were calculated for both walking (rows ignored) and driving (rows impassable) and costs compared with assessment error and effects on crop value. Overall, BAS performed better than SRS. Driving was faster than walking except when sample distribution necessitated travelling down every row regardless of sample size. Annual crop losses of up to NZ$2578 per hectare could result from short assessment times and subsequent inaccurate estimates of BBR severity. Spatial interpolation was shown to be a useful and promising technique for studying BBR sampling strategies in vineyard blocks. Travel was not a substantial component of assessment time. An 80-minutelong assessment could substantially reduce economic losses because of errors in BBR assessments. [ABSTRACT FROM AUTHOR]

In solving expensive multi-objective optimization problems, surrogate models have been widely investigated. The existing multi-objective algorithms adopting surrogate models can be classified into two categories: surrogate-assisted evolutionary algorithms (SAEAs) and surrogate-based optimization algorithms (SBAs). However, their efficiency and convergence remain considerably inadequate. In this work, we propose a trust-region-like algorithm for dealing with expensive multi-objective problems, where only a small number of expensive objective function evaluations are allowed. The optimization process of the proposed algorithm mainly includes two stages. The first stage is the surrogate-assisted stage, in which a promising population with the consideration of convergence and diversity is obtained by reference vector-guided evolutionary algorithms (RVEA). The promising population is considered the preliminary trust-region. Moreover, a new adaptive sampling selection criterion switching between two different sampling strategies is used to further narrow the trust-region. The second stage is the surrogate-based stage, wherein the selection of the most promising individuals is carried out from the ultimate trust-region using the pseudo hypervolume-based expected improvement matrix (PEIM) criterion. Comparison results on the benchmark functions demonstrate that the proposed algorithm is competitive with five state-of-art algorithms in a limited computational budget. Finally, the proposed algorithm is used in the design optimization of a variable stiffness composite cylinder. • RVEA-PEIM fuses the basic idea of trust-regions to multi-objective optimization. • An adaptive sampling selection criterion is proposed to narrow the trust-region. • Different state-of-the-art multi-objective algorithms are tested and compared. [ABSTRACT FROM AUTHOR]

Once the research question and the research design have been finalised, it is important to select the appropriate sample for the study. The method by which the researcher selects the sample is the 'Sampling Method'. There are essentially two types of sampling methods: 1) probability sampling – based on chance events (such as random numbers, flipping a coin etc.); and 2) non-probability sampling – based on researcher's choice, population that accessible & available. Some of the non-probability sampling methods are: purposive sampling, convenience sampling, or quota sampling. Random sampling method (such as simple random sample or stratified random sample) is a form of probability sampling. It is important to understand the different sampling methods used in clinical studies and mention this method clearly in the manuscript. The researcher should not misrepresent the sampling method in the manuscript (such as using the term 'random sample' when the researcher has used convenience sample). The sampling method will depend on the research question. For instance, the researcher may want to understand an issue in greater detail for one particular population rather than worry about the 'generalizability' of these results. In such a scenario, the researcher may want to use 'purposive sampling' for the study.

The definition of “arable weeds” remains contentious. Although much attention has been devoted to specialized, segetal weeds, many taxa found in arable fields also commonly occur in other habitats. The extent to which adjacent habitats are favorable to the weed flora and act as potential sources of colonizers in arable fields remains unclear. In addition, weeds form assemblages with large spatiotemporal variability, so that many taxa in weed flora are rarely observed in plot-based surveys. We thus addressed the following questions: How often do weeds occur in other habitats than arable fields? How does including field edges extend the taxonomic and ecological diversity of weeds? How does the weed flora vary across surveys at different spatial and temporal scales? We built a comprehensive dataset of weed taxa in France by compiling weed flora, lists of specialized segetal weeds, and plot-based surveys in agricultural fields, with different spatial and temporal coverages. We informed life forms, biogeographical origins and conservation status of these weeds. We also defined a broader dataset of plants occupying open habitats in France and assessed habitat specialization of weeds and of other plant species absent from arable fields. Our results show that many arable weeds are frequently recorded in both arable fields and non-cultivated open habitats and are, on average, more generalist than species absent from arable fields. Surveys encompassing field edges included species also occurring in mesic grasslands and nitrophilous fringes, suggesting spill-over from surrounding habitats. A total of 71.5% of the French weed flora was not captured in plot-based surveys at regional and national scales, and many rare and declining taxa were of Mediterranean origin. This result underlines the importance of implementing conservation measures for specialist plant species that are particularly reliant on arable fields as a habitat, while also pointing out biotic homogenization of agricultural landscapes as a factor in the declining plant diversity of farmed landscapes. Our dataset provides a reference species pool for France, with associated ecological and biogeographical information.

Abstract In this paper the authors describe the limnological approaches, the sampling methodology, and strategy adopted in the study of the Xingu River in the area of influence of future Belo Monte Power Plant. The river ecosystems are characterized by unidirectional current, highly variable in time depending on the climatic situation the drainage pattern an hydrological cycle. Continuous vertical mixing with currents and turbulence, are characteristic of these ecosystems. All these basic mechanisms were taken into consideration in the sampling strategy and field work carried out in the Xingu River Basin, upstream and downstream the future Belo Monte Power Plant Units.

Marine natural products are a rich source of novel and biologically active compounds. The number of identified marine natural compounds has grown 20% over the last five years from 2009 to 2013. Several challenges, including sample collection and structure elucidation, have limited the development of this research field. Nonetheless, new approaches, such as sampling strategies for organisms from extreme ocean environments, nanoscale NMR and computational chemistry for structural determination, are now available to overcome the barriers. In this review, we highlight the experimental technology innovations in the field of marine natural products, which in our view will lead to the development of many new drugs in the future.

The use of quantitative imaging biomarkers in the imaging of various disease states, including cancer and neurodegenerative disease, has increased in recent years. T1, T2, and T2* relaxation time constants have been shown to be affected by tissue structure or contrast infusion. Acquiring these biomarkers simultaneously in a multi‐parametric acquisition could provide more robust detection of tissue changes in various disease states including neurodegeneration and cancer. Traditional magnetic resonance fingerprinting (MRF) has been shown to provide quick, quantitative mapping of T1 and T2 relaxation time constants. In this study, T2* relaxation is added to the MRF framework using variable echo times (TE). To demonstrate the feasibility of the method and compare incremental and golden angle spiral rotations, simulated phantom data was fit using the proposed method. Additionally, T1/T2/T2*/δf MRF as well as conventional T1, T2, and T2* acquisitions were acquired in agar phantoms and the brains of three healthy volunteers. Golden angle spiral rotation was found to reduce inaccuracy resulting from off resonance effects. Strong correlations were found between conventional and MRF values in the T1, T2, and T2* relaxation time constants of the agar phantoms and healthy volunteers. In this study, T2* relaxation has been incorporated into the MRF framework by using variable echo times, while still fitting for T1 and T2 relaxation time constants. In addition to fitting these relaxation time constants, a novel method for fitting and correcting off resonance effects has been developed. [ABSTRACT FROM AUTHOR]

The estimation of stormwater pollutant concentrations is a primary requirement of integrated urban water management. In order to determine effective sampling strategies for estimating pollutant concentrations, data from extensive field measurements at seven different catchments was used. At all sites, 1-min resolution continuous flow measurements, as well as flow-weighted samples, were taken and analysed for total suspend solids (TSS), total nitrogen (TN) and Escherichia coli ( E. coli ). For each of these parameters, the data was used to calculate the Event Mean Concentrations (EMCs) for each event. The measured Site Mean Concentrations (SMCs) were taken as the volume-weighted average of these EMCs for each parameter, at each site. 17 different sampling strategies, including random and fixed strategies were tested to estimate SMCs, which were compared with the measured SMCs. The ratios of estimated/measured SMCs were further analysed to determine the most effective sampling strategies. Results indicate that the random sampling strategies were the most promising method in reproducing SMCs for TSS and TN, while some fixed sampling strategies were better for estimating the SMC of E. coli . The differences in taking one, two or three random samples were small (up to 20% for TSS, and 10% for TN and E. coli ), indicating that there is little benefit in investing in collection of more than one sample per event if attempting to estimate the SMC through monitoring of multiple events. It was estimated that an average of 27 events across the studied catchments are needed for characterising SMCs of TSS with a 90% confidence interval (CI) width of 1.0, followed by E.coli (average 12 events) and TN (average 11 events). The coefficient of variation of pollutant concentrations was linearly and significantly correlated to the 90% confidence interval ratio of the estimated/measured SMCs (R 2 = 0.49; P < 0.01) as well as the number of events required to achieve certain accuracy, and hence could be a promising surrogate for determining the sampling frequency needed to accurately estimate SMCs of pollutants. [ABSTRACT FROM AUTHOR]

Full scale aerodynamic wind tunnel testing, numerical simulation of high dimensional (full-order) aerodynamic models or flight testing are some of the fundamental but complex steps in the various design phases of recent civil transport aircrafts. Current aircraft aerodynamic designs have increase in complexity (multidisciplinary, multi-objective or multi-fidelity) and need to address the challenges posed by the nonlinearity of the objective functions and constraints, uncertainty quantification in aerodynamic problems or the restrained computational budgets. With the aim to reduce the computational burden and generate low-cost but accurate models that mimic those full order models at different values of the design variables, Recent progresses have witnessed the introduction, in real-time and many-query analyses, of surrogate-based approaches as rapid and cheaper to simulate models. In this paper, a comprehensive and state-of-the art survey on common surrogate modeling techniques and surrogate-based optimization methods is given, with an emphasis on models selection and validation, dimensionality reduction, sensitivity analyses, constraints handling or infill and stopping criteria. Benefits, drawbacks and comparative discussions in applying those methods are described. Furthermore, the paper familiarizes the readers with surrogate models that have been successfully applied to the general field of fluid dynamics, but not yet in the aerospace industry. Additionally, the review revisits the most popular sampling strategies used in conducting physical and simulation-based experiments in aircraft aerodynamic design. Attractive or smart designs infrequently used in the field and discussions on advanced sampling methodologies are presented, to give a glance on the various efficient possibilities to a priori sample the parameter space. Closing remarks foster on future perspectives, challenges and shortcomings associated with the use of surrogate models by aircraft industrial aerodynamicists, despite their increased interest among the research communities. [ABSTRACT FROM AUTHOR]

Studies on the quantities and distribution of soil organic carbon stocks (SOC-S) can help to fill the knowledge gaps in estimating the amount of carbon stored in soils. However, one of the problems of soil organic carbon (SOC) is the high variability in space and time. Over the years, many researchers have studied the soil mainly in two different ways: by pedogenic horizons in entire soil profiles (ESP) or by soil control sections (SCS) with different thicknesses along the profile, and this causes uncertainty in SOC and SOC-S evaluation and assessment. This study analyzed the differences in the SOC-S in northeastern Sardinia (Italy) in Cambisols, following two soil sampling approaches, ESP by pedogenic horizons and SCS (25 cm thick) on these selected land uses: tilled vineyards, no-till grassed vineyards, and former vineyards naturally re-vegetated after abandonment. Average data on total SOC-S (T-SOC-S) estimations were 61.5 Mg ha − 1 and 67.3 Mg ha − 1 for ESP and SCS respectively, indicating significantly higher estimates of T-SOC-S when sampling by SCS. Consequently, the ESP approach is recommended to evaluate and certify SOC-S, while SCS may be preferred for monitoring and soil management interpretation purposes. [ABSTRACT FROM AUTHOR]

Purpose: Data sampling strategies in large-scale life-cycle assessments (LCAs) are often developed informally based on a combination of sector expertise, common sense, resource restrictions, and politics. The assessment of the representativeness of the acquired sample is then assessed ex post in a qualitative fashion or using a semi-quantitative approach based on pedigree matrices. The purpose of this paper is twofold: provide a structured framework for both designing a representative sample for these types of studies as well as for assessing the representativeness of the sample one was able to obtain. Methods: For sample design, we propose the use of proportionate stratified sampling after defining the strata through the identification of those population characteristics that are able to introduce a relevant bias to average specific environmental burdens of the product system under study. For assessment of the final representativeness of the acquired sample, we propose a metric based on the weighted average deviation between population and sample based on the identified strata for technological and geographical representativeness and another metric for temporal representativeness that is based on a weighting scale applied to the years that data was collected from. Results and discussion: The proposed approach is pragmatic and practical and helps to improve representativeness compared to simple random sampling. The general principles can inform the discussions about how many and which sites to sample even if detailed data on the composition of the population is missing. Its key strength is that it is not a one-size-fits-all methodology, but that it can and needs to be adapted to the product system under study, which in return requires the transparent documentation of all rationales and value choices along the way. Conclusions: The proposed approach provides practitioners with a flexible framework to plan data collection in a way that increases representativeness compared to simple random sampling. The representativeness can be quantified and discussed using a defined scale that is based on quantitative measures rather than based on qualitative descriptions or pedigrees. If the underlying rationales and value choices are transparently documented and justified, the framework can help to improve how representativeness of primary data is addressed in large-scale LCAs. [ABSTRACT FROM AUTHOR]

The study of sex trafficking, prostitution, sex work, and sexual exploitation is associated with many methodological issues and challenges. Researchers’ study designs must consider the many safety issues related to this vulnerable and hidden population. Community advisory boards and key stakeholder involvement are essential to study design to increase safety of participants, usefulness of study aims, and meaningfulness of conclusions. Nonrandomized sampling strategies are most often utilized when studying exploited women and girls, which have the capacity to provide rich data and require complex sampling and recruitment methods. This article reviews the current methodological issues when studying this marginalized population as well as strategies to address challenges while working with the community in order to bring about social change. The authors also discuss their own experiences in collaborating with community organizations to conduct research in this field. [ABSTRACT FROM AUTHOR]

Identifying intestinal microbiota is arguably an important task that is performed to determine the pathogenesis of inflammatory bowel diseases (IBD); thus, it is crucial to collect and analyze intestinally-associated microbiota. Analyzing a single niche to categorize individuals does not enable researchers to comprehensively study the spatial variations of the microbiota. Therefore, characterizing the spatial community structures of the inflammatory bowel disease microbiome is critical for advancing our understanding of the inflammatory landscape of IBD. However, at present there is no universally accepted consensus regarding the use of specific sampling strategies in different biogeographic locations. In this review, we discuss the spatial distribution when screening sample collections in IBD microbiota research. Here, we propose a novel model, a three-dimensional spatial community structure, which encompasses the x-, y-, and z-axis distributions; it can be used in some sampling sites, such as feces, colonoscopic biopsy, the mucus gel layer, and oral cavity. On the basis of this spatial model, this article also summarizes various sampling and processing strategies prior to and after DNA extraction and recommends guidelines for practical application in future research. [ABSTRACT FROM AUTHOR]

Presently, Theobroma cacao L. (cacao) in Cuba is mainly cultivated in the eastern region where plantations comprise a mixture of clonal varieties, hybrids, progeny of Trinidad Selected Hybrids, and traditional-also known as ancient-cacao. The ancient genetic resources, probably the plants most closely related to the original introductions, are endangered by their progressive replacement by modern clones. To promote the conservation and utilization of these genetic resources, a representative sample of 537 traditional Cuban cacao plants was used to develop a core collection. Core collections based on 15 simple sequence repeat (SSR) markers were generated using five different sampling algorithms: random sampling, simulated annealing, stepwise clustering with random sampling, the M strategy, and maximum genetic diversity. The five core collections were designed to capture 95 % of the SSR alleles in the complete collection. The genetic, morphological, and geographical diversity of each core collection was compared with that of the entire collection. The entire collection contained 139 alleles, including 104 rare ones, with the 95 % allelic coverage threshold achieved with 133 alleles. The core collection generated by the maximum genetic diversity algorithm had the lowest number of accessions (185), the highest mean genetic distance (0.486), the lowest morphological character redundancy, and the highest diversity as assessed by the mean Shannon-Weaver diversity index (0.757). This core collection can thus serve as the basis of future improvement programs based on local genetic resources. [ABSTRACT FROM AUTHOR]

Establishing a core collection that represents the genetic diversity of the entire collection with a minimum loss of its original diversity and minimal redundancies is an important problem for gene bank curators and crop breeders. In this paper, we assess the representativeness of the original genetic diversity in core collections consisting of one-tenth of the entire collection obtained according to 23 sampling strategies. The study was performed using the Polish orchardgrass Dactylis glomerata L. germplasm collection as a model. The representativeness of the core collections was validated by the difference of means (MD%) and difference of mean squared Euclidean distance (d‒D%) for the studied traits in the core subsets and the entire collection. In this way, we compared the efficiency of a simple random and 22 (20 cluster-based and 2 direct cluster-based) stratified sampling strategies. Each cluster-based stratified sampling strategy is a combination of 2 clusterings, 5 allocations and 2 methods of sampling in a group. We used the accession genotypic predicted values for 8 quantitative traits tested in field trials. A sampling strategy is considered more effective for establishing core collections if the means of the traits in a core are maintained at the same level as the means in the entire collection (i.e., the mean of MD% in the simulated samples is close to zero) and, simultaneously, when the overall variation in a core collection is greater than in the entire collection (i.e., the mean of d‒D% in the simulated samples is greater than that obtained for the simple random sampling strategy). Both cluster analyses (unweighted pair group method with arithmetic mean UPGMA and Ward) were similarly useful in constructing those sampling strategies capable of establishing representative core collections. Among the allocation methods that are relatively most useful for constructing efficient samplings were proportional and D2 (including variation). Within the Ward clusters, the random sampling was better than the cluster-based sampling, but not within the UPGMA clusters.

Background Depending on tree and site characteristics crown biomass accounts for a significant portion of the total aboveground biomass in the tree. Crown biomass estimation is useful for different purposes including evaluating the economic feasibility of crown utilization for energy production or forest products, fuel load assessments and fire management strategies, and wildfire modeling. However, crown biomass is difficult to predict because of the variability within and among species and sites. Thus the allometric equations used for predicting crown biomass should be based on data collected with precise and unbiased sampling strategies. In this study, we evaluate the performance different sampling strategies to estimate crown biomass and to evaluate the effect of sample size in estimating crown biomass. Methods Using data collected from 20 destructively sampled trees, we evaluated 11 different sampling strategies using six evaluation statistics: bias, relative bias, root mean square error (RMSE), relative RMSE, amount of biomass sampled, and relative biomass sampled. We also evaluated the performance of the selected sampling strategies when different numbers of branches (3, 6, 9, and 12) are selected from each tree. Tree specific log linear model with branch diameter and branch length as covariates was used to obtain individual branch biomass. Results Compared to all other methods stratified sampling with probability proportional to size estimation technique produced better results when three or six branches per tree were sampled. However, the systematic sampling with ratio estimation technique was the best when at least nine branches per tree were sampled. Under the stratified sampling strategy, selecting unequal number of branches per stratum produced approximately similar results to simple random sampling, but it further decreased RMSE when information on branch diameter is used in the design and estimation phases. Conclusions Use of auxiliary information in design or estimation phase reduces the RMSE produced by a sampling strategy. However, this is attained by having to sample larger amount of biomass. Based on our finding we would recommend sampling nine branches per tree to be reasonably efficient and limit the amount of fieldwork.

Free-form surfaces are widely used in engineering applications. These surfaces are complex and without rotational symmetry, and for this reason they are inspected using the coordinate measuring machines equipped with contact sensor require a suitable sampling strategy. Sampling algorithms are one of the most important factors of error creation in the accuracy of substitute geometry. In coordinate measuring machines, the sampling strategy involves the estimation of the number of sample points (sample size) and identification of their positions (how distribution) on the surface. Thus sample points should be distributed on the surface using sampling strategies that are appropriate for the surface. Often it is difficult to establish such pieces of information (number and the way of distributing the points on the surface) owing to the complex nature of free-form surfaces. In the present work for first time, new adaptive sampling strategy by particle swarm optimization algorithm (PSO) for sampling from free-form surface is proposed. The proposed strategy was compared with two conventional strategies and the deviation between substitute geometry and CAD model is extracted. The simulation results showed that in the proposed method the deviation between substitute geometry and CAD model is less than conventional methods by 2 to 3 times (depending on the number of points). Therefore high efficiency of the proposed method over other methods is concluded. [ABSTRACT FROM AUTHOR]

Once the research question and the research design have been finalised, it is important to select the appropriate sample for the study. The method by which the researcher selects the sample is the 'Sampling Method'. There are essentially two types of sampling methods: 1) probability sampling - based on chance events (such as random numbers, flipping a coin etc.); and 2) non-probability sampling - based on researcher's choice, population that accessible & available. Some of the non-probability sampling methods are: purposive sampling, convenience sampling, or quota sampling. Random sampling method (such as simple random sample or stratified random sample) is a form of probability sampling. It is important to understand the different sampling methods used in clinical studies and mention this method clearly in the manuscript. The researcher should not misrepresent the sampling method in the manuscript (such as using the term 'random sample' when the researcher has used convenience sample). The sampling method will depend on the research question. For instance, the researcher may want to understand an issue in greater detail for one particular population rather than worry about the 'generalizability' of these results. In such a scenario, the researcher may want to use 'purposive sampling' for the study. [ABSTRACT FROM AUTHOR]

We consider two stochastic variants of the Share-a-Ride problem: one with stochastic travel times and one with stochastic delivery locations. Both variants are formulated as a two-stage stochastic programming model with recourse. The objective is to maximize the expected profit of serving a set of passengers and parcels using a set of homogeneous vehicles. Our solution methodology integrates an adaptive large neighborhood search heuristic and three sampling strategies for the scenario generation (fixed sample size sampling, sample average approximation, and sequential sampling procedure). A computational study is carried out to compare the proposed approaches. The results show that the convergence rate depends on the source of stochasticity in the problem: stochastic delivery locations converge faster than stochastic travel times according to the numerical test. The sample average approximation and the sequential sampling procedure show a similar performance. The performance of the fixed sample size sampling is better compared to the other two approaches. The results suggest that the stochastic information is valuable in real-life and can dramatically improve the performance of a taxi sharing system, compared to deterministic solutions. [ABSTRACT FROM AUTHOR]

Objective: The aim of the study is to compare detection frequency of periodontal pathogens in patients with aggressive/severe chronic periodontitis using pooled plaque samples from the deepest pockets per quadrant/per sextant. Methods: In 100 patients with aggressive/chronic periodontitis, subgingival plaque was sampled from the deepest pockets per quadrant (MT4) and per sextant (MT6). Plaque samples were taken using two sterile paper points simultaneously. One paper point from each pocket was pooled with the three other paper points of the pockets (MT4). Subsequently, the remaining four paper points were pooled with two paper points from the deepest pockets from the two remaining sextants (MT6). The content of each vial was analyzed with nucleic-acid based methods for Aggregatibacter actinomycetemcomitans, Tannerella forsythia, Porphyromonas gingivalis, Treponema denticola, Prevotella intermedia, Parvimonas micra, Fusobacterium nucleatum, Campylobacter rectus, Eubacterium nodatum, Eikenella corrodens, and Capnocytophaga sp. Results: The detection frequency of A. actinomycetemcomitans (MT4/MT6) at 22/24 %, T. forsythia at 93/96 %, P. gingivalis at 78/79 %, T. denticola at 88/90 %, P. intermedia at 40/46 %, P. micra at 75/79 %, F. nucleatum at both 99 %, C. rectus at 84/89 %, E. nodatum at 62/65 %, E. corrodens at 80/87 %, and Capnocytophaga sp. at 49/58 % was higher with MT6 than with MT4. None of these differences were statistically significant. Conclusion: The detection frequency of the investigated periopathogens was statistically insignificant higher with the sampling method MT6 compared with MT4. Clinical relevance: In daily dental practice, the plaque sampling of the deepest pockets per quadrant seems to be sufficient. [ABSTRACT FROM AUTHOR]

The resolution of rapid evolutionary radiations or “bushes” in the tree of life has been one of the most difficult and interesting problems in phylogenetics. The avian order Galliformes appears to have undergone several rapid radiations that have limited the resolution of prior studies and obscured the position of taxa important both agriculturally and as model systems (chicken, turkey, Japanese quail). Here we present analyses of a multi-locus data matrix comprising over 15,000 sites, primarily from nuclear introns but also including three mitochondrial regions, from 46 galliform taxa with all gene regions sampled for all taxa. The increased sampling of unlinked nuclear genes provided strong bootstrap support for all but a small number of relationships. Coalescent-based methods to combine individual gene trees and analyses of datasets that are independent of published data indicated that this well-supported topology is likely to reflect the galliform species tree. The inclusion or exclusion of mitochondrial data had a limited impact upon analyses upon analyses using either concatenated data or multispecies coalescent methods. Some of the key phylogenetic findings include support for a second major clade within the core phasianids that includes the chicken and Japanese quail and clarification of the phylogenetic relationships of turkey. Jackknifed datasets suggested that there is an advantage to sampling many independent regions across the genome rather than obtaining long sequences for a small number of loci, possibly reflecting the differences among gene trees that differ due to incomplete lineage sorting. Despite the novel insights we obtained using this increased sampling of gene regions, some nodes remain unresolved, likely due to periods of rapid diversification. Resolving these remaining groups will likely require sequencing a very large number of gene regions, but our analyses now appear to support a robust backbone for this order.

High Nature Value ( HNV) farmland is increasingly important within Europe and effective sampling strategies that collect invertebrates in agricultural wet grassland are vital to gauge the biodiversity in these pockets of high species richness., One group of potential bioindicators of HNV farmland particularly suited to wet grasslands are the marsh or snail-killing flies (Diptera: Sciomyzidae). Their relatively sedentary adult habit and terrestrial - aquatic habitats make them ideal for fine-grain resolution of biodiversity within farms., In this short communication, we demonstrate that using Malaise trapping, emergence trapping and sweep-netting in isolation can result in incomplete species lists in addition to which we relate capture efficacies of the methods employed with reference to previous studies and the biology of the species concerned., Furthermore, we demonstrate that sweep-net captures are more effective at crepuscular periods (dawn and dusk) than during the middle of the day. [ABSTRACT FROM AUTHOR]

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Sample locations for large river studies affect the representativeness of data, and thus can alter decisions made regarding river conditions and the need for interventions to improve water quality. The present study evaluated three water-quality sampling programs for Total Dissolved Solid (TDS) assessment in the Monongahela River from 2008 to 2012. The sampling plans cover the same 145 km of river but differ in frequency, sample location and type (e.g., river water sample vs drinking water plant intake sample). Differences resulting from temporal and spatial variability in sampling lead to different conclusions regarding water quality in the river (including regulatory listing decisions), especially when low flow leads to concentrations at or near the water quality criteria (500 mg/L TDS). Drinking water samples exceeded the criteria 82 out of 650 samples (12.6%), while river water samples exceeded the criteria 47 out of 464 samples (10.1%). Different water sample types could provide different pictures of water quality in the river and lead to different regulatory listing decisions. [ABSTRACT FROM AUTHOR]