Abstract: Quantitative PCR (qPCR) is broadly used as the gold standard to quantify microbial community fractions in environmental microbiology and biotechnology. Benchmarking efforts to ensure the comparability of qPCR data for environmental bioprocesses are still scarce. Also, for partial nitritation/anammox (PN/A) systems systematic investigations are still missing, rendering meta-analysis of reported trends and generic insights potentially precarious. We report a baseline investigation of the variability of qPCR-based analyses for microbial communities applied to PN/A systems. Round-robin testing was performed for three PN/A biomass samples in six laboratories, using the respective in-house DNA extraction and qPCR protocols. The concentration of extracted DNA was significantly different between labs, ranged between 2.7 and 328 ng mg−1 wet biomass. The variability among the qPCR abundance data of different labs was very high (1−7 log fold) but differed for different target microbial guilds. DNA extraction caused maximum variation (3–7 log fold), followed by the primers (1–3 log fold). These insights will guide environmental scientists and engineers as well as treatment plant operators in the interpretation of qPCR data.

Abstract: Air pollution caused by particulate matter (PM) is a well-known health issue in urban environments. Urban green infrastructure offers opportunities as a nature-based solution to urban PM pollution. Green walls have advantages over other types of urban green infrastructure, since they can be applied to the enormous available wall area in cities and since they do not interfere with the prevailing ventilation resulting in elevated PM levels. However, this has raised questions about the effectiveness of GW in removing PM and this could explain the limited applicability of green walls to tackle PM pollution. Nevertheless, it is suggested that green walls have a significant unexploited potential and this review article aims to address current knowledge gaps and to propose future research requirements for the implementation of green walls to mitigate urban PM pollution. An in-depth analysis is given of the mechanisms behind PM deposition and the influence of vegetation properties on this process, as well as the practices followed to model PM dispersion and deposition. It was suggested that particle deposition on green walls depends on the green wall species, pollution level, and the residence time of PM in a street (canyon). Rainfall plays an important role in the PM pathway, although it is not a necessary requirement to sustain PM deposition on plant leaves. There are still some discrepancies in the literature about the ideal plant characteristics for PM deposition in terms of the macro- and microstructures that require further investigation, especially in comparison with tree and shrub species. In addition, extensively validated models are required to accurately calculate the impact of green walls on air flow and the PM concentration on site.

Abstract: Colloidal nanoparticles (NPs) including nanowires and nanosheets made by chemical methods involve many organic ligands. When the structure of NPs is investigated via transmission electron microscopy (TEM), the organic ligands act as a source for e-beam induced deposition and this causes substantial build-up of carbon layers in the investigated areas, which is typically referred to as “contamination” in the eld of electron mi- croscopy. This contamination is often more severe for scanning TEM, a technique that is based on a focused electron beam and hence higher electron dose rate. In this paper, we report a simple and effective method to clean drop-cast TEM grids that contain NPs with ligands. Using a combination of activated carbon and ethanol, this method effectively reduces the amount of ligands on TEM grids, and therefore greatly improves the quality of electron microscopy images and subsequent analytical measurements. This ef cient and facile method can be helpful during electron microscopy investigation of different kinds of nanomaterials that suffer from ligand- induced contamination.

Abstract: In computed tomography, the reconstruction is typically obtained on a voxel grid. In this work, however, we propose a mesh-based reconstruction method. For tomographic problems, 3D meshes have mostly been studied to simulate data acquisition, but not for reconstruction, for which a 3D mesh means the inverse process of estimating shapes from projections. In this paper, we propose a differentiable forward model for 3D meshes that bridge the gap between the forward model for 3D surfaces and optimization. We view the forward projection as a rendering process, and make it differentiable by extending recent work in differentiable rendering. We use the proposed forward model to reconstruct 3D shapes directly from projections. Experimental results for single-object problems show that the proposed method outperforms traditional voxel-based methods on noisy simulated data. We also apply the proposed method on electron tomography images of nanoparticles to demonstrate the applicability of the method on real data.

Abstract: This current review focuses on contributions to amphetamine-type substances (ATS) analysis. This type of synthetic illicit drugs has been increasingly present worldwide reaching 5% of the market on illicit drugs in 2019. The increment of their production in many clandestine laboratories and easy distribution among society are two of the main concerns towards the battle against synthetic drugs. Therefore, the first part of this review details the classification and mechanism of action of ATS in the human body. Second, the pharmacological and toxicological effects of ATS on human health are described to motivate the need of early detection of ATS. Subsequently, the most used laboratory-based and portable methods are presented and critically discussed along the review. Finally, a careful discussion on the advantages and disadvantages of portable techniques employed on the field are addressed as potential tools for on-site ATS detection by law enforcement officers.

Abstract: A multiscale modeling and simulation approach, including first-principles calculations, ab initio molecular dynamics simulations, and a tight binding approach, is employed to study band flattening of the electronic band structure of oxidized monolayer graphene. The width offlat bands can be tuned by strain, the external electric field, and the density of functional groups and their distribution. A transition to a conducting state is found for monolayer graphene with impurities when it is subjected to an electric field of similar to 1.0 V/angstrom. Several parallel impurity-induced flat bands appear in the low-energy spectrum of monolayer graphene when the number of epoxy groups is changed. The width of the flat band decreases with an increase in tensile strain but is independent of the electric field strength. Here an alternative and easy route for obtaining band flattening in thermodynamically stable functionalized monolayer graphene is introduced. Our work discloses a new avenue for research on band flattening in monolayer graphene.

Abstract: The illicit consumption of heroin is an increasing concern in our society. For this reason, rapid analytical methods to seize heroin samples in the field are of paramount importance to hinder drug trafficking, and thus prevent the availability of heroin in the drug market. The present work reports on the enriched electrochemical fingerprint of heroin, allowing its selective detection in street samples, based on the use of electrochemical pretreated screen printed electrodes (p-SPE). The voltammetric identification is built on two oxidation peaks of both heroin and its degradation product 6-monoacetylmorphine (6-MAM), generated in alkaline conditions. Interestingly, an anodic pretreatment of the screen printed electrodes (SPE) shifts the peak potential of paracetamol (the most encountered cutting agent in heroin seizures), allowing the detection of 6-MAM peak, overlapping with the paracetamol signal in the case of untreated SPE. Subsequently, the characterization of the p-SPE with scanning electron microscopy, cyclic voltammetry, electrochemical impedance spectroscopy, Raman and Fourier transform infrared (FTIR) spectroscopy is provided to demonstrate local changes on the surface of the electrode. From an analytical perspective, p-SPE provide higher sensitivity (0.019 μA μM-1), excellent reproducibility (6-MAM, RSD = 2.85%, and heroin RSD = 0.91%, n = 5) and lower limits of detection (LOD) (5.2 μM) in comparison to untreated SPE. The proposed protocol which integrates a tailor-made script is interrogated against common cutting agents, and finally, validated with the screening of 14 street samples, also analyzed by standard methods. Besides, a comparison with portable spectroscopic techniques on the confiscated samples shows the better performance of the electrochemical strategy. Overall, this sensing approach offers promising results for the rapid on-site profiling of suspicious heroin samples, also in the presence of paracetamol.

Abstract: Bridging the gap between complex signal data output and clear interpretation by non-expert end-users is a major challenge many scientists face when converting their scientific technology into a real-life application. Currently, pattern recognition algorithms are the most frequently encountered signal data interpretation algorithms to close this gap, not in the least because of their straight-forward implementation via convenient software packages. Paradoxically, just because their implementation is so straight-forward, it becomes cumbersome to integrate the expert's domain-specific knowledge. In this work, a novel signal data interpretation approach is presented that uses this domain-specific knowledge as its fundament, thereby fully exploiting the unique expertise of the scientist. The new approach applies data preprocessing in an innovative way that transcends its usual purpose and is easy to translate into a software application. Multiple case studies illustrate the straight-forward application of the novel approach. Ultimately, the approach is highly suited for integration in various (bio)analytical applications that require interpretation of signal data.

Abstract: This publication introduces the audiovisual geometry database with Gielis transformations as initial records for a prototype of the database. A concise overview is given of the rationale behind the database and studying wave phenomena with Gielis transformations. First results on a form of timbral polyphony observed in Gielis curves and future work are briefly discussed.

Abstract: The richness, diversity, connection, depth and pleasure of studying symmetry continue to open doors. Here we report a connection between Coxeter's Apeirogon and the geometry associated with pictorial space, parabolic rotation and dual numbers.

Abstract: Growing global plastic production combined with poor waste collection has led to increasing amounts of plastic debris being found in oceans, rivers and on shores. The goal of this study is to provide an overview on currently available technological solutions to tackle marine plastic litter and to assess their potential use in developing countries. To compile an inventory of technological solutions, a dedicated online platform was developed. A total of 51 out of initially 75 submitted solutions along the plastics value chain were assessed by independent experts. Collection systems represent more than half of the shortlisted solutions. A quarter include processing and treatment technologies, either as a stand-alone solution (30%) or, more commonly, in combination with a first litter capturing step. Ten percent offer digital solutions. The rest focuses on integrated waste management solutions. For each stage in the source-to-sea spectrum-land, rivers, sea-two illustrative examples are described in detail. This study concludes that the most cost-effective type of solution tackles land-based sources of marine litter and combines technology with people-oriented practices, runs on own energy sources, connects throughout the plastics value chain with a convincing valorization plan for captured debris, and involves all relevant stakeholders.

Abstract: In this work, the carbon (C) and silicon (Si) doping and codoping effects on beta-arsenene (As) monolayer structural, electronic, and magnetic properties have been comprehensively investigated using first-principles calculations. The studied two-dimensional (2D) materials exhibit good stability. Pristine beta-As single layer is an indirect gap semiconductor with a band gap of 1.867(2.441) eV as determined by PBE(HSE06) functional. Due to the difference in atomic size and electronic interactions, C and Si substitution induces a significant local structural distortion. Depending upon dopant concentration and doping sites, feature-rich electronic properties including non-magnetic semiconductor, magnetic semiconductor and half-metallicity may be obtained, which result from p-p interactions. High spin-polarization at the Fermi level vicinity and significant magnetism suggest As:1C, As:2C, As:1Si, As:2Si, and As:CSi systems as prospective spintronic 2D materials. While, the C-C, Si-Si, and C-Si dimer doping decreases electronic band gap, making the layer more suitable for applications in optoelectronic devices. Results presented herein may suggest an efficient approach to create novel multi-functional 2D materials from beta-As monolayer.

Abstract: This study presents novel sulfolane based non-aqueous CO2 capture solvents, as an alternative solution for capturing CO2 from industrial processes. In order to select the most promising amine system, five different amines were tested by monitoring CO2 absorption and desorption processes using the time-base Attenuated Total Reflectance-Fourier Transform Infrared (ATR-FTIR) spectroscopy. During absorption experiments, we observed the formation of Monomethyl Carbonate (MMC) in diisopropylamine (DIPA) and 2-amino-2-methyl-1-propanol (AMP) systems, while carbamate was observed as the main product for the other three amine systems tested. In regeneration experiments, the MMC could be desorbed relatively easily from the amine solution at a mild temperature.

Abstract: We present a first-principles computational study of cation–Se 3 (112) grain boundaries in CuGaSe. We discuss the structure of these grain boundaries, as well as the effect of native defects and Na impurities on their electronic properties. The formation energies show that the defects will tend to form preferentially at the grain boundaries, rather than in the grain interiors. We find that in Ga-rich growth conditions Cu vacancies as well as Ga at Cu and Cu at Ga antisites are mainly responsible for having the equilibrium Fermi level pinned toward the middle of the gap, resulting in carrier depletion. The Na at Cu impurity in its +1 charge state contributes to this. In Ga-poor growth conditions, on the other hand, the formation energies of Cu vacancies and Ga at Cu antisites are comparatively too high for any significant influence on carrier density or on the equilibrium Fermi level position. Thus, under these conditions, the Cu at Ga antisites give rise to a -type grain boundary. Also, their formation energy is lower than the formation energy of Na at Cu impurities. Thus, the latter will fail to act as a hole barrier preventing recombination at the grain boundary, in contrast to what occurs in CuInSe grain boundaries. We also discuss the effect of the defects on the electronic properties of bulk CuGaSe, which we assume reflect the properties of the grain interiors.