Recommendations for representative sampling methodologies in ballast water: A case study from the land-based test.

Accurate assessment of ballast water's community composition and organism concentrations is crucial for effective management. Yet, the lack of standardized global sampling methods presents challenges to achieving this objective. Inconsistencies hinder data comparison across regions and vessels, impeding efficient ballast water treatment and discharge regulation. This study conducted land-based tests to establish suitable methodologies. For organisms ≥50 µm and ≥10 µm to <50 µm, the recommended max flow rate is 50 L/min; for <10 µm organisms, 25 L/min is advised to prevent cell damage. Sampling should cover substantial discharge durations. To ensure representation, ≥50 µm organisms require ≥1m3, while ≥10 µm to <50 µm and <10 µm organisms need 20 L. The ultimate aim is standardized methods for assessing ballast water across regions and vessel types, facilitating effective management to curb invasive species and protect aquatic ecosystems.

Efficiency of five samplers to trap suspended particulate matter and microplastic particles of different sizes.

Suspended particulate matter (SPM) plays a major role in nutrient cycles and for the transport of pollutants within local and transboundary water catchments. Obtaining representative SPM samples from rivers, lakes, inland and coastal waters is crucial for quantitative and qualitative chemical analyses to correctly describe the chemical status of a water body. However, a representative sampling of SPM over time is challenging due to the heterogeneity of SPM particles sizes, their non-uniform distribution in rivers, and a variety of sampling devices being in use. Therefore, we investigated the efficiencies of five different sampling devices commonly used in national and international monitoring programs to collect representative SPM samples. We tested three passive sedimentation-based samplers (SBSs: sedimentation box, SB; sedimentation tank, ST; Raetz Sampler, RS), and two active separation techniques (continuous flow centrifuge, CFC; vacuum filtration, VF) in an experimental laboratory setup using in-house SPM standard suspensions (mineral, organic, and microplastic particles) with defined particle sizes. The mass-based efficiencies of the three examined SBSs were 0-66% for the mineral and organic particles <75 µm, where the mean particle sizes of collected samples were always shifted to bigger sizes compared to the initial suspensions. The efficiencies of the three SBSs to collect microplastic particles <80 µm were <20% due to the lower densities of microplastic compared to organic and mineral particles. In contrast to the SBSs, VF and CFC units showed excellent efficiencies >86% for all tested materials, with similar particle size distributions of the sampled material compared to those of the inlet suspensions. In conclusion, SPM sampling efficiencies of sampling units have to be carefully considered and compared to the respective aims of the monitoring approaches, especially when statements are derived from quantitative results on SPM.

Shifted Excitation Raman Difference Spectroscopy Combined with Wide Area Illumination and Sample Rotation for Wood Species Classification.

Raman spectroscopy has found its way into a wide range of applications and is successfully applied for qualitative and quantitative studies. Despite significant technical progress over the last few decades, there are still some challenges that limit its more widespread usage. This paper presents a holistic approach to addressing simultaneously the problems of fluorescence interference, sample heterogeneity, and laser-induced sample heating. Long wavelength shifted excitation Raman difference spectroscopy (SERDS) at 830 nm excitation combined with wide-area illumination and sample rotation is presented as a suitable approach for the investigation of selected wood species. Wood as a natural specimen represents a well-suited model system for our study as it is fluorescent, heterogeneous, and susceptible to laser-induced modifications. Two different subacquisition times (50 and 100 ms) and two sample rotation speeds (12 and 60 r/min) were exemplarily assessed. Results demonstrate that SERDS can effectively separate the Raman spectroscopic fingerprints of the wood species balsa, beech, birch, hickory, and pine from intense fluorescence interference. Sample rotation in conjunction with 1 mm-diameter wide-area illumination was suitable to obtain representative SERDS spectra of the wood species within 4.6 s. Using partial least squares discriminant analysis, a classification accuracy of 99.4% for the five investigated wood species was realized. This study highlights the large potential of SERDS combined with wide-area illumination and sample rotation for the effective analysis of fluorescent, heterogeneous, and thermally sensitive specimens in a wide range of application areas.

PARNAS: Objectively Selecting the Most Representative Taxa on a Phylogeny.

The use of next-generation sequencing technology has enabled phylogenetic studies with hundreds of thousands of taxa. Such large-scale phylogenies have become a critical component in genomic epidemiology in pathogens such as SARS-CoV-2 and influenza A virus. However, detailed phenotypic characterization of pathogens or generating a computationally tractable dataset for detailed phylogenetic analyses requires objective subsampling of taxa. To address this need, we propose parnas, an objective and flexible algorithm to sample and select taxa that best represent observed diversity by solving a generalized k-medoids problem on a phylogenetic tree. parnas solves this problem efficiently and exactly by novel optimizations and adapting algorithms from operations research. For more nuanced selections, taxa can be weighted with metadata or genetic sequence parameters, and the pool of potential representatives can be user-constrained. Motivated by influenza A virus genomic surveillance and vaccine design, parnas can be applied to identify representative taxa that optimally cover the diversity in a phylogeny within a specified distance radius. We demonstrated that parnas is more efficient and flexible than existing approaches. To demonstrate its utility, we applied parnas to 1) quantify SARS-CoV-2 genetic diversity over time, 2) select representative influenza A virus in swine genes derived from over 5 years of genomic surveillance data, and 3) identify gaps in H3N2 human influenza A virus vaccine coverage. We suggest that our method, through the objective selection of representatives in a phylogeny, provides criteria for quantifying genetic diversity that has application in the the rational design of multivalent vaccines and genomic epidemiology. PARNAS is available at https://github.com/flu-crew/parnas.

The prevalence and mental health correlates of exposure to offensive behaviours at work in Hungary: results of a national representative survey.

BACKGROUND: Within the last decades, a substantial number of reports have established bullying behaviours as a severe risk to the health and safety of workers. However, in Hungary, the severity of this issue remains largely unknown. Therefore, the current study aimed to 1) determine the prevalence of offensive workplace behaviours in the Hungarian working population and 2) examine the relationship between exposure to these offensive behaviours and certain mental health indicators. METHODS: The cross-sectional analyses of the present study are based on a sample of 13,104 active workers being representative of the Hungarian working population according to gender, age, educational level, and 18 occupational sectors. The mid-length version of the Copenhagen Psychosocial Questionnaire II (COPSOQ II) was used to measure workplace offensive behaviours (bullying, sexual harassment, threats of violence, and physical violence) in the 12 months preceding the survey. Examined mental health correlates included depressive symptomatology (Beck Depression Inventory), functional somatic symptoms (PHQ-15), perceived stress (Perceived Stress Scale), and general well-being (WHO Well-being Index). RESULTS: Almost half (48.7%) of the sample reported exposure to some form of offensive behaviour; 37.6% of participants reported occasional-, while 11.1% reported weekly or daily exposure. More women than men were exposed to offensive workplace behaviours, and those targeted the most were individuals aged 18-29 and in companies employing 20-49 employees. Top managers reported the lowest amount of bullying, while unskilled labourers reported the most frequent exposure. A moderately strong relationship was discovered between exposure to workplace offensive behaviours and all indicators of mental health. CONCLUSION: Workplace bullying was revealed to be a significant public health concern according to this large, representative data set from Hungary. Strategies to reduce the occurrence and impact of these behaviours on employee health should be a priority for occupational health and safety interventions.

On the representability of soil water samples in space and time: Impact of heterogeneous solute transport pathways underneath a sandy field.

In Europe, millions of water samples have been collected from sampling points, especially in the saturated zone to assess the water quality among others to fulfil EU water quality directives. Often water samples are collected from sampling points installed in the subsurface without knowing what the water collected represents in space and time. As such, without detailed knowledge of hydrogeological settings and fluctuations in groundwater levels, it is not possible to assess whether water collected represents a hydraulic active sediment setting or an adjacent isolated sediment body. Collecting water from the latter will hence not reveal by analysis potential contamination in the hydraulic active setting. Based on a detailed three-dimensional sedimentary facies model interpreted from geological and geophysical data combined with groundwater level measurements, this study focuses on delineating the impact of changing solute transport pathways underneath a sandy field (2 ha) exposed to bromide and pesticide applications. Hence, the analyses utilize detections in water samples of bromide, pesticides, and/or their degradation products collected through 19 years at 25 sampling points. A special focus is on the relatively high concentration, long-termed leaching of four degradation products (1,2,4-triazole, CGA108906, PPU, and desethyl-terbuthylazine) through the field. The results show that even for sand, knowledge of the hydrogeological setting and in-situ fate knowledge is imperative to assess the representability of water being sampled from both the variably-saturated and saturated zone of the soil-sediment system. Especially, the sub-horizontal layered sediments with numerous facies shifts facilitate horizontal solute transport, and fluctuations in the groundwater table seem to be decisive for, which solute transport pathways are dominating. Such detailed insights are crucial for accurately assessing sources of contaminants, leaching risk of contaminants through the variably-saturated zone, and improving monitoring procedures in the protection of the water resources and hereby the water quality of the future.

Raman spectroscopy and NIR hyperspectral imaging for in-line estimation of fatty acid features in salmon fillets.

Raman spectroscopy was compared with near infrared (NIR) hyperspectral imaging for determination of fat composition (%EPA + DHA) in salmon fillets at short exposure times. Fillets were measured in movement for both methods. Salmon were acquired from several different farming locations in Norway with different feeding regimes, representing a realistic variation of salmon in the market. For Raman, we investigated three manual scanning strategies; i) line scan of loin, ii) line scan of belly and iii) sinusoidal scan of belly at exposure times of 2s and 4s. NIR images were acquired while the fillets moved on a conveyor belt at 40 cm/s, which corresponds to an acquisition time of 1s for a 40 cm long fillet. For NIR images, three different regions of interest (ROI) were investigated including the i) whole fillet, ii) belly segment, and iii) loin segment. For both Raman and NIR measurements, we investigated an untrimmed and trimmed version of the fillets, both relevant for industrial in-line evaluation. For the trimmed fillets, a fat rich deposition layer in the belly was removed. The %EPA + DHA models were validated by cross validation (N = 51) and using an independent test set (N = 20) which was acquired in a different season. Both Raman and NIR showed promising results and high performances in the cross validation, with R2CV = 0.96 for Raman at 2s exposure and R2CV = 0.97 for NIR. High performances were obtained also for the test set, but while Raman had low and stable biases for the test set, the biases were high and varied for the NIR measurements. Analysis of variance on the squared test set residuals showed that performance for Raman measurements were significantly higher than NIR at 1% significance level (p = 0.000013) when slope-and-bias errors were not corrected, but not significant when residuals were slope-and-bias corrected (p = 0.28). This indicated that NIR was more sensitive to matrix effects. For Raman, signal-to-noise ratio was the main limitation and there were indications that Raman was close to a critical sample exposure time at the 2s signal accumulation.

Active learning for data efficient semantic segmentation of canine bones in radiographs.

X-ray bone semantic segmentation is one crucial task in medical imaging. Due to deep learning's emergence, it was possible to build high-precision models. However, these models require a large quantity of annotated data. Furthermore, semantic segmentation requires pixel-wise labeling, thus being a highly time-consuming task. In the case of hip joints, there is still a need for increased anatomic knowledge due to the intrinsic nature of the femur and acetabulum. Active learning aims to maximize the model's performance with the least possible amount of data. In this work, we propose and compare the use of different queries, including uncertainty and diversity-based queries. Our results show that the proposed methods permit state-of-the-art performance using only 81.02% of the data, with O ( 1 ) time complexity.

Problematic gaming risk among European adolescents: a cross-national evaluation of individual and socio-economic factors.

BACKGROUND AND AIMS: Previous research has identified numerous risk and protective factors of adolescent problematic gaming (PG) at the individual and social levels; however, the influence of socio-economic indicators on PG is less known. This study aimed to measure the contribution of individual and socio-economic factors involved in PG risk among adolescents from 30 European countries. DESIGN: Multi-level logistic regression analysis of survey data from the 2019 European School Survey Project on Alcohol and Other Drugs (ESPAD) cross-sectional study using self-administered anonymous questionnaires. SETTING: Thirty European countries. PARTICIPANTS: A representative cohort of 15-16-year-old students (n = 88 998 students; males = 49.2%). MEASUREMENTS: The primary outcome measure was adolescents' (low and high) risk of PG. Individual key predictors included self-report assessments of socio-demographic characteristics, time spent gaming and family variables (parental regulation and monitoring, family support). Main country-level predictors comprised Gini coefficient for economic inequalities and benefits for families and children (% gross domestic product), retrieved from international public data sets and national thematic reports. The data analysis plan involved multi-level logistic regression. FINDINGS: Participants who reported stronger parental regulation [odds ratio (OR) = 0.81, 95% confidence interval (CI) = 0.79-0.83] and higher family support (OR = 0.93, 95% CI = 0.91-0.95) reported lower risk of PG. At the country-level, economic inequalities (OR = 1.05, 95% CI = 1.03-1.07) were positively associated with the risk of PG, while benefits for families and children (OR = 0.78, 95% CI = 0.70-0.89) were negatively correlated with the risk of PG. CONCLUSIONS: Supportive family environments, lower country-level economic inequalities and higher government expenditures on benefits for families and children appear to be associated with a lower risk of problematic gaming among European adolescents.

Feasibility of In-Line Raman Spectroscopy for Quality Assessment in Food Industry: How Fast Can We Go?

Raman spectroscopy is a viable tool within process analytical technologies due to recent technological advances. In this article, we evaluate the feasibility of Raman spectroscopy for in-line applications in the food industry by estimating the concentration of the fatty acids EPA + DHA in ground salmon samples (n = 63) and residual bone concentration in samples of mechanically recovered ground chicken (n = 66). The samples were measured under industry like conditions: They moved on a conveyor belt through a dark cabinet where they were scanned with a wide area illumination standoff Raman probe. Such a setup should be able to handle relevant industrial conveyor belt speeds, and it was studied how different speeds (i.e., exposure times) influenced the signal-to-noise ratio (SNR) of the Raman spectra as well as the corresponding model performance. For all samples we applied speeds that resulted in 1 s, 2 s, 4 s, and 10 s exposure times. Samples were scanned in both heterogenous and homogenous state. The slowest speed (10 s exposure) yielded prediction errors (RMSECV) of 0.41%EPA + DHA and 0.59% ash for the salmon and chicken data sets, respectively. The more in-line relevant exposure time of 1 s resulted in increased RMSECV values, 0.84% EPA + DHA and 0.84% ash, respectively. The increase in prediction error correlated closely with the decrease in SNR. Further improvements of model performance were possible through different noise reduction strategies. Model performance for homogenous and heterogenous samples was similar, suggesting that the presented Raman scanning approach has the potential to work well also on intact heterogenous foods. The estimation errors obtained at these high speeds are likely acceptable for industrial use, but successful strategies to increase SNR will be key for widespread in-line use in the food industry.

Computational fluid dynamics analysis of influence of different pipe structures on gas mixing uniformity / 中国辐射卫生

Objective Tostudy the influence of pipe structures on the mixing uniformity of airborne effluents from nuclear power plant chimneys. Methods We used the computational fluid dynamics (CFD) method to simulate the velocity distribution and gas mixing in long straight pipes (I type) with square section and circular section, 90° single-bend pipes (L type) with square section and circular section, and 90° double-bend pipes (S type and U type) with square section and circular section. Results For the long straight pipe, due to the lack of flow disturbance caused by structural changes, the mixing effect was not good; when the pipe section was circular, it might take mixing distance 20 times the hydraulic diameter to achieve the uniformity index required by the relevant standard; for the square pipe, the distance might be longer. In the single bend pipe with square section, the velocity uniformity was improved more greatly after the bend, and the tracer gas met the mixing uniformity at a shorter distance (11 times the hydraulic diameter), as compared with the single bend pipe with circular section. For the S-type double-bend pipe, the tracer gas appeared uniformly mixed after a distance 6 times the hydraulic diameter in the square pipe, and 7 times the hydraulic diameter in the circular pipe. For the U-type double-bend pipe, the gas in the square pipe also achieved uniform mixing ata shorter distance downstream, and the airflow showed greater disturbance when passing through the bend. Conclusion The CFD method can make an accurate prediction for the change patterns of gas mixing uniformity in pipes with different structures, and can partially replace physical experiments to study the factors affecting the mixing uniformity of airborne effluents from the chimney of nuclear power plants.

A multifunctional matching algorithm for sample design in agricultural plots.

Collection of accurate and representative data from agricultural fields is required for efficient crop management. Since growers have limited available resources, there is a need for advanced methods to select representative points within a field in order to best satisfy sampling or sensing objectives. The main purpose of this work was to develop a data-driven method for selecting locations across an agricultural field given observations of some covariates at every point in the field. These chosen locations should be representative of the distribution of the covariates in the entire population and represent the spatial variability in the field. They can then be used to sample an unknown target feature whose sampling is expensive and cannot be realistically done at the population scale. An algorithm for determining these optimal sampling locations, namely the multifunctional matching (MFM) criterion, was based on matching of moments (functionals) between sample and population. The selected functionals in this study were standard deviation, mean, and Kendall's tau. An additional algorithm defined the minimal number of observations that could represent the population according to a desired level of accuracy. The MFM was applied to datasets from two agricultural plots: a vineyard and a peach orchard. The data from the plots included measured values of slope, topographic wetness index, normalized difference vegetation index, and apparent soil electrical conductivity. The MFM algorithm selected the number of sampling points according to a representation accuracy of 90% and determined the optimal location of these points. The algorithm was validated against values of vine or tree water status measured as crop water stress index (CWSI). Algorithm performance was then compared to two other sampling methods: the conditioned Latin hypercube sampling (cLHS) model and a uniform random sample with spatial constraints. Comparison among sampling methods was based on measures of similarity between the target variable population distribution and the distribution of the selected sample. MFM represented CWSI distribution better than the cLHS and the uniform random sampling, and the selected locations showed smaller deviations from the mean and standard deviation of the entire population. The MFM functioned better in the vineyard, where spatial variability was larger than in the orchard. In both plots, the spatial pattern of the selected samples captured the spatial variability of CWSI. MFM can be adjusted and applied using other moments/functionals and may be adopted by other disciplines, particularly in cases where small sample sizes are desired.

How to take representative samples to quantify microplastic particles in soil?

The amount of plastic particles in terrestrial ecosystems is not well known, not only because it is difficult to extract and identify plastic particles from terrestrial samples, but also because it is challenging to take representative samples from soils or sediments. Here, we numerically simulated how to take representative terrestrial samples to quantify plastic particles, and we evaluated the accuracy (error) of reported plastic concentrations in the literature. Fields with randomly distributed plastic particles (uniform and clustered) were numerically generated and sampled to determine the representative elementary volume (REV) and the required number of samples to quantify plastic concentrations (10 to 106 particles/m2) with different relative errors (5%, 10%, 15%). The REV and the required number of samples decrease hyperbolically as the plastic concentration increases, indicating a strong non-linear relation. For instance, hundreds to thousands of soil cores (8-cm diameter) would be required to quantify plastics at low concentrations (102 particles/m2), while a few cores are sufficient at high plastic concentrations (105 particles/m2). For an accurate measurement of plastic concentrations, the total surface area of samples taken should approach or exceed the REV. We recommend to take replicated samples with each sample as large as possible (e.g., 1 m × 1 m) rather than multiple small cores, and then reduce the soil volume by the quartering method.

A Population-Specific Major Allele Reference Genome From The United Arab Emirates Population.

The ethnic composition of the population of a country contributes to the uniqueness of each national DNA sequencing project and, ideally, individual reference genomes are required to reduce the confounding nature of ethnic bias. This work represents a representative Whole Genome Sequencing effort of an understudied population. Specifically, high coverage consensus sequences from 120 whole genomes and 33 whole exomes were used to construct the first ever population specific major allele reference genome for the United Arab Emirates (UAE). When this was applied and compared to the archetype hg19 reference, assembly of local Emirati genomes was reduced by ∼19% (i.e., some 1 million fewer calls). In compiling the United Arab Emirates Reference Genome (UAERG), sets of annotated 23,038,090 short (novel: 1,790,171) and 137,713 structural (novel: 8,462) variants; their allele frequencies (AFs) and distribution across the genome were identified. Population-specific genetic characteristics including loss-of-function variants, admixture, and ancestral haplogroup distribution were identified and reported here. We also detect a strong correlation between F ST and admixture components in the UAE. This baseline study was conceived to establish a high-quality reference genome and a genetic variations resource to enable the development of regional population specific initiatives and thus inform the application of population studies and precision medicine in the UAE.

Improved Sample Selection and Preparation Methods for Sampling Plans Used to Facilitate Rapid and Reliable Estimation of Aflatoxin in Chicken Feed.

Aflatoxin B1 (AFB1), a toxic fungal metabolite associated with human and animal diseases, is a natural contaminant encountered in agricultural commodities, food and feed. Heterogeneity of AFB1 makes risk estimation a challenge. To overcome this, novel sample selection, preparation and extraction steps were designed for representative sampling of chicken feed. Accuracy, precision, limits of detection and quantification, linearity, robustness and ruggedness were used as performance criteria to validate this modification and Horwitz function for evaluating precision. A modified sampling protocol that ensured representativeness is documented, including sample selection, sampling tools, random procedures, minimum size of field-collected aggregate samples (primary sampling), procedures for mass reduction to 2 kg laboratory (secondary sampling), 25 g test portion (tertiary sampling) and 1.3 g analytical samples (quaternary sampling). The improved coning and quartering procedure described herein (for secondary and tertiary sampling) has acceptable precision, with a Horwitz ratio (HorRat = 0.3) suitable for splitting of 25 g feed aliquots from laboratory samples (tertiary sampling). The water slurring innovation (quaternary sampling) increased aflatoxin extraction efficiency to 95.1% through reduction of both bias (-4.95) and variability of recovery (1.2-1.4) and improved both intra-laboratory precision (HorRat = 1.2-1.5) and within-laboratory reproducibility (HorRat = 0.9-1.3). Optimal extraction conditions are documented. The improved procedure showed satisfactory performance, good field applicability and reduced sample analysis turnaround time.

Design and installation of ballast water sample ports: Current status and implications for assessing compliance with discharge standards.

To verify ships' compliance with ballast water regulations, samples may be collected and tested for viable organisms. This task is completed using a sample probe, which is placed in the ballast discharge pipe through a sample port (a flanged opening). To collect representative samples, the placement of the sample port and the size of the sample probe must be appropriate for the shipboard piping arrangement and ballast water flows. The placement of sample ports was evaluated on 72 ships to assess the current condition of ballast water sampling installations against available guidance. Few ships (15%) had sample ports fully aligned with International Organization for Standardization (ISO) standard 11711-1. While current configurations may present challenges in collecting representative samples, these installations likely occurred before the ISO standard was available. Future installations should be in accordance with the standard to facilitate representative sampling.

Assessment of Bulk Composition of Heterogeneous Food Matrices Using Raman Spectroscopy.

Raman spectroscopy (RS) has for decades been considered a promising tool for food analysis, but widespread adoption has been held back by, e.g., high instrument costs and sampling limitations regarding heterogeneous samples. The aim of the present study was to use wide area RS in conjunction with surface scanning to overcome the obstacle of heterogeneity. Four different food matrices were scanned (intact and homogenized pork and by-products from salmon and poultry processing) and the bulk chemical parameters such as fat and protein content were estimated using partial least squares regression (PLSR). The performance of PLSR models from RS was compared with near-infrared spectroscopy (NIRS). Good to excellent results were obtained with PLSR models from RS for estimation of fat content in all food matrices (coefficient of determination for cross-validation (R2CV) from 0.73 to 0.96 and root mean square error of cross-validation (RMSECV) from 0.43% to 2.06%). Poor to very good PLSR models were obtained for estimation of protein content in salmon and poultry by-product using RS (R2CV from 0.56 to 0.92 and RMSECV from 0.85% to 0.94%). The performance of RS was similar to NIRS for all analyses. This work demonstrates the applicability of RS to analyze bulk composition in heterogeneous food matrices and paves way for future applications of RS in routine food analyses.

Representative Sequencing: Unbiased Sampling of Solid Tumor Tissue.

Although thousands of solid tumors have been sequenced to date, a fundamental under-sampling bias is inherent in current methodologies. This is caused by a tissue sample input of fixed dimensions (e.g., 6 mm biopsy), which becomes grossly under-powered as tumor volume scales. Here, we demonstrate representative sequencing (Rep-Seq) as a new method to achieve unbiased tumor tissue sampling. Rep-Seq uses fixed residual tumor material, which is homogenized and subjected to next-generation sequencing. Analysis of intratumor tumor mutation burden (TMB) variability shows a high level of misclassification using current single-biopsy methods, with 20% of lung and 52% of bladder tumors having at least one biopsy with high TMB but low clonal TMB overall. Misclassification rates by contrast are reduced to 2% (lung) and 4% (bladder) when a more representative sampling methodology is used. Rep-Seq offers an improved sampling protocol for tumor profiling, with significant potential for improved clinical utility and more accurate deconvolution of clonal structure.

The surgeon's role on chemical investigations of the composition of urinary stones.

The chemical analysis of an urolith is often interpreted as "stone's composition". However, it must be taken into consideration, that in most cases, only a fragment of the stone has been sent to the laboratory. In some recurrent patients, stone compositions either vary considerably between episodes or the analytical result obtained from the stone fragment does not fit with the data of e.g. current 24 h-urinalysis or urinary pH-records. The question arises, whether this outcome may be the result of an improper stone sampling scheme. On a simple layered 2D-stone model composed of two mineral phases it is shown, how the choice of a stone fragment process may influence the result of "stone composition". Depending on the initial position of fragment within the whole stone, the respective calculated analyses can relevantly differ from the whole stone composition as well as strongly between two fragments. Even under the simplified conditions of a 2D-2-component-model "grown" under defined conditions, the differences between the analyses of the different specimens taken from a stone are in part remarkable. The more it can be argued that these differences increase if a real 3D-urolith is investigated. Further sampling biases may evolve and increase the problem of proper sampling:, e.g., if an urolith's more resistant parts remain intact while ESWL or laser-based stone fragmentation ("dusting"), the weak parts became fully disintegrated and removed from the body as fine-grained sludge-the stone's fine fraction is lost although its composition may carry important information on the stone's pathogenesis. Consequently, a "stone analysis" only obtained from the harder remains reveals an incomplete result, a fact that in principle limits its clinical interpretation. Choice of stone fragment is crucial. The extent of the uncertainty of an analysis resulting from potential selection biases should not be underestimated. Thus, sampling should be considered as an important part of the processes of quality assurance and management. Errors made at this early stage of diagnosis finding will affect the analytical result and thus influence the clarification of the underlying pathomechanism. This can lead to an improper metaphylactic strategy potentially causing recurrent stone formation which otherwise would have been prevented. A decision scheme for analysis of urinary stones removed using endoscopic methods is suggested.

Combination of a rotating tube sample divider and dynamic image analysis for continuous on-line determination of granule size distribution.

The granule size distribution is a critical quality attribute of granules. It has a great impact on further packaging or processing. Due to increasing interest in continuous manufacturing techniques, it is of high interest to develop an in-line or on-line tool to monitor the granule size distribution. However, development of an in-line measurement tool for granule size distribution was challenging since large throughput and inhomogeneous product stream are limiting factors for current particle size analyzers. In this study, continuous sampling was tested in conjunction to a continuous on-line method of size determination using dynamic image analysis. A rotating tube sample divider was used to split previously compacted material in representative samples at different ratios and the sample was directly conveyed to the particle size analyzer where the granule size distribution was determined. The method was tested for different granule sizes to determine limits of detection and its ability to detect these changes immediately, as this enables real-time monitoring of the process. This research is the base for development of control tools concerning the granule size distributions for continuous granulation processes.