Comparison of two rapid automated analysis tools for large FTIR microplastic datasets

AbstractOne of the biggest issues in microplastic (MP, plastic items  &lt;5 mm) research is the lack of standardisation and harmonisation in all fields, reaching from sampling methodology to sample purification, analytical methods and data analysis. This hampers comparability as well as reproducibility among studies. Concerning chemical analysis of MPs, Fourier-transform infrared (FTIR) spectroscocopy is one of the most powerful tools. Here, focal plane array (FPA) based micro-FTIR (µFTIR) imaging allows for rapid measurement and identification without manual preselection of putative MP and therefore enables large sample throughputs with high spatial resolution. The resulting huge datasets necessitate automated algorithms for data analysis in a reasonable time frame. Although solutions are available, little is known about the comparability or the level of reliability of their output. For the first time, within our study, we compare two well-established and frequently applied data analysis algorithms in regard to results in abundance, polymer composition and size distributions of MP (11–500 µm) derived from selected environmental water samples: (a) the siMPle analysis tool (systematic identification of MicroPlastics in the environment) in combination with MPAPP (MicroPlastic Automated Particle/fibre analysis Pipeline) and (b) the BPF (Bayreuth Particle Finder). The results of our comparison show an overall good accordance but also indicate discrepancies concerning certain polymer types/clusters as well as the smallest MP size classes. Our study further demonstrates that a detailed comparison of MP algorithms is an essential prerequisite for a better comparability of MP data.</jats:p

Generation of macro- and microplastic databases by high-throughput FTIR analysis with microplate readers

FTIR spectral identification is today’s gold standard analytical procedure for plastic pollution material characterization. High-throughput FTIR techniques have been advanced for small microplastics (10–500 µm) but less so for large microplastics (500–5 mm) and macroplastics (> 5 mm). These larger plastics are typically analyzed using ATR, which is highly manual and can sometimes destroy particles of interest. Furthermore, spectral libraries are often inadequate due to the limited variety of reference materials and spectral collection modes, resulting from expensive spectral data collection. We advance a new high-throughput technique to remedy these problems using FTIR microplate readers for measuring large particles (> 500 µm). We created a new reference database of over 6000 spectra for transmission, ATR, and reflection spectral collection modes with over 600 plastic, organic, and mineral reference materials relevant to plastic pollution research. We also streamline future analysis in microplate readers by creating a new particle holder for transmission measurements using off-the-shelf parts and fabricating a nonplastic 96-well microplate for storing particles. We determined that particles should be presented to microplate readers as thin as possible due to thick particles causing poor-quality spectra and identifications. We validated the new database using Open Specy and demonstrated that additional transmission and reflection spectra reference data were needed in spectral libraries

Identifying microplastics in North Sea waters - A matter of extraction and detection

In times of a rising plastic production the occurrence of microplastics (< 5 mm in size) in the marine environment has been identified as an emerging topic of global concern. Microplastics are omnipresent in our environment, hardly degradable and are easily ingested by a wide range of organisms throughout all trophic levels. However, the extent of this microplastic pollution as well as the resulting impacts on the marine environment remains largely unknown. Therefore, standardized and reliable methods to securely detect microplastics are urgently needed. The conclusive identification requires a successful extraction from different, complex environmental matrices. Thus we developed a highly promising procedure to successfully analyze also small microplastics (11-500 µm) isolated from surface water samples. This procedure includes the usage of an enzymatic-oxidative purification in newly developed semi-enclosed filtration units (microplastic reactors). This is followed by a state-of-the-art analysis via micro Fourier transform infrared (µFTIR) spectroscopy. The aim of this work is to contribute to the field of microplastic research by applying innovative analysis techniques as well as generating solid and comparable data. These provide information on quantities, polymer and size composition as well as spatial distribution of microplastics in North Sea surface waters. First results show that microplastics are present in the North Sea exhibiting a variety of polymer types, dominated by rubbers and polyethylene. Concerning the size, the vast majority of the detected microplastic particles is less than 75 µm in length

Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis

Search for heavy resonances decaying to two Higgs bosons in final states containing four b quarks

A search is presented for narrow heavy resonances X decaying into pairs of Higgs bosons (H) in proton-proton collisions collected by the CMS experiment at the LHC at root s = 8 TeV. The data correspond to an integrated luminosity of 19.7 fb(-1). The search considers HH resonances with masses between 1 and 3 TeV, having final states of two b quark pairs. Each Higgs boson is produced with large momentum, and the hadronization products of the pair of b quarks can usually be reconstructed as single large jets. The background from multijet and t (t) over bar events is significantly reduced by applying requirements related to the flavor of the jet, its mass, and its substructure. The signal would be identified as a peak on top of the dijet invariant mass spectrum of the remaining background events. No evidence is observed for such a signal. Upper limits obtained at 95 confidence level for the product of the production cross section and branching fraction sigma(gg -> X) B(X -> HH -> b (b) over barb (b) over bar) range from 10 to 1.5 fb for the mass of X from 1.15 to 2.0 TeV, significantly extending previous searches. For a warped extra dimension theory with amass scale Lambda(R) = 1 TeV, the data exclude radion scalar masses between 1.15 and 1.55 TeV

Search for supersymmetry in events with one lepton and multiple jets in proton-proton collisions at root s=13 TeV

Peer reviewe

Measurement of the top quark mass using charged particles in pp collisions at root s=8 TeV

Peer reviewe

Search for anomalous couplings in boosted WW/WZ -> l nu q(q)over-bar production in proton-proton collisions at root s=8TeV

Peer reviewe

Microplastic Occurence in North Sea Surface Waters - Analyzed using Fourier Transform Infrared Spectroscopy

The global plastic production is increasing steadily, and so the amount of synthetic material reaching our marine environment does. In recent years, more and more studies focused on the occurrence of microplastics, i.e. synthetic organic polymers with a size < 5 mm. These pollutants are omnipresent and hardly degradable, leading to an accumulation in the environment. They are easily ingested by a wide range of animals throughout the food web, and may act as a vector for persistent organic pollutants (POPs). For a valid evaluation of microplastic pollution in marine ecosystems appropriate assessment strategies are crucial. By now, no standardized sampling and analysis techniques are available, which would be urgently needed in order to generate solid and comparable data bases. In many studies, microplastics are identified and quantified solely through visual examination, although this approach is highly subjective and may lead to misidentification. In this work, state-of-the-art methods were used for the identification and quantification of microplastics in seven North Sea neuston samples. The samples were split into two size fractions, on which two different methodological approaches were applied. Microplastics > 500 μm were extracted using a stereomicroscope, followed by polymer identification via Attenuated Total Reflection based Fourier Transform Infrared spectroscopy (FTIR-ATR). For the size fraction 500 μm and from 16.1 – 393.1 m−3 (1.3 × 106 – 4.3 × 107 km−2) in the size fraction < 500 μm. With regard to the size distribution small-sized particles clearly dominated in both fractions. In total, 17 different synthetic polymers were detected in the studied neuston samples with comparably high abundances of polyethylene, polypropylene, varnish and rubber, possibly stemming from land-based sources or shipping activities