Sources, pathways, and abatement strategies of macroplastic pollution: an interdisciplinary approach for the southern North Sea

The issue of marine plastic pollution has been extensively studied by various scientific disciplines in recent decades due to its global threat. However, owing to its complexity, it requires an interdisciplinary approach to develop effective management strategies. The multidisciplinary scientific approach presented here focuses on understanding the sources and pathways of macroplastic litter and developing abatement strategies in the southern North Sea region. Over 2.5 years, more than 63,400 biodegradable wooden drifters were deployed with the help of citizen science to study the sources, pathways, and accumulation areas of floating marine litter. Rivers act as sinks of most of the floating marine litter released within their waterways. Short-term field experiments were also conducted to analyse the hydrodynamic and atmospheric processes that govern the transport of floating litter particles at the sea surface. Numerical models were used to examine the transport of virtual litter particles in the entire North Sea and in coastal regions. It was found that there are no permanent accumulation areas in the North Sea, and the Skagerrak and fronts can increase the residence times of floating marine litter and favour sinking. Field surveys revealed that the majority of litter objects originate from fisheries and consumer waste. To develop effective abatement strategies, the key stakeholder landscape was analysed on a regional level. The interdisciplinary approach developed in this study highlights the importance of synergizing scientific resources from multiple disciplines for a better understanding of marine plastic pollution and the development of effective management strategies

Sample Size Estimation for Detection of Splicing Events in Transcriptome Sequencing Data

Merging data from multiple samples is required to detect low expressed transcripts or splicing events that might be present only in a subset of samples. However, the exact number of required replicates enabling the detection of such rare events often remains a mystery but can be approached through probability theory. Here, we describe a probabilistic model, relating the number of observed events in a batch of samples with observation probabilities. Therein, samples appear as a heterogeneous collection of events, which are observed with some probability. The model is evaluated in a batch of 54 transcriptomes of human dermal fibroblast samples. The majority of putative splice-sites (alignment gap-sites) are detected in (almost) all samples or only sporadically, resulting in an U-shaped pattern for observation probabilities. The probabilistic model systematically underestimates event numbers due to a bias resulting from finite sampling. However, using an additional assumption, the probabilistic model can predict observed event numbers within a <10% deviation from the median. Single samples contain a considerable amount of uniquely observed putative splicing events (mean 7122 in alignments from TopHat alignments and 86,215 in alignments from STAR). We conclude that the probabilistic model provides an adequate description for observation of gap-sites in transcriptome data. Thus, the calculation of required sample sizes can be done by application of a simple binomial model to sporadically observed random events. Due to the large number of uniquely observed putative splice-sites and the known stochastic noise in the splicing machinery, it appears advisable to include observation of rare splicing events into analysis objectives. Therefore, it is beneficial to take scores for the validation of gap-sites into account

Validation of Splicing Events in Transcriptome Sequencing Data

Genomic alignments of sequenced cellular messenger RNA contain gapped alignments which are interpreted as consequence of intron removal. The resulting gap-sites, genomic locations of alignment gaps, are landmarks representing potential splice-sites. As alignment algorithms report gap-sites with a considerable false discovery rate, validations are required. We describe two quality scores, gap quality score (gqs) and weighted gap information score (wgis), developed for validation of putative splicing events: While gqs solely relies on alignment data wgis additionally considers information from the genomic sequence. FASTQ files obtained from 54 human dermal fibroblast samples were aligned against the human genome (GRCh38) using TopHat and STAR aligner. Statistical properties of gap-sites validated by gqs and wgis were evaluated by their sequence similarity to known exon-intron borders. Within the 54 samples, TopHat identifies 1,000,380 and STAR reports 6,487,577 gap-sites. Due to the lack of strand information, however, the percentage of identified GT-AG gap-sites is rather low. While gap-sites from TopHat contain ≈89% GT-AG, gap-sites from STAR only contain ≈42% GT-AG dinucleotide pairs in merged data from 54 fibroblast samples. Validation with gqs yields 156,251 gap-sites from TopHat alignments and 166,294 from STAR alignments. Validation with wgis yields 770,327 gap-sites from TopHat alignments and 1,065,596 from STAR alignments. Both alignment algorithms, TopHat and STAR, report gap-sites with considerable false discovery rate, which can drastically be reduced by validation with gqs and wgis

Parameters influencing the numerical calculation of the structural intensity

The structural intensity (STI) characterizes the energy flow in solid structures between an energy source and an energy sink. In numerical simulations the structural intensity can be calculated from internal forces and moments multiplied with vibrational velocities and angular velocities. These quantities can be computed by means of modal superposition. The accuracy of this method and thus the calculation of the STI strongly depends on the number of mode shapes considered in the harmonic simulation. The error of the STI related to the number of mode shapes considered in the calculation is studied by means of a convergence analysis,. For a good accuracy of the STI over a wide frequency range, several thousand mode shapes must be taken into account. The STI can be used to calculate the input or dissipated power of certain areas of the structure. This can be done by a numerical integration along a cyclic integral. In this paper, the influence of the distance between the integration path and the source (excitation point) or the sink on the calculation of the input or dissipated power is shown. An optimal distance for the integration path can be found that results in a minimal error