Abstract: Background Breast cancer (BC) is the most common cancer in women in the developed world. In order to find developing cancers in an early stage, BC screening is commonly used. In Flanders, screening is performed in and outside an organized breast cancer screening program (BCSP). However, the determinants of BC screening coverage for both screening strategies are yet unknown. Objective To assess the determinants of BC screening coverage in Flanders. Methods Reimbursement data were used to attribute a screening status to each woman in the target population for the years 2008-2016. Yearly coverage data were categorized as screening inside or outside BCSP or no screening. Data were clustered by municipality level. A generalized linear equation model was used to assess the determinants of screening type. Results Over all years and municipalities, the median screening coverage rate inside and outside BCSP was 48.40% (IQR: 41.50-54.40%) and 14.10% (IQR: 9.80-19.80%) respectively. A higher coverage rate outside BSCP was statistically significantly (P < 0.001) associated with more crowded households (OR: 3.797, 95% CI: 3.199-4.508), younger age, higher population densities (OR: 2.528, 95% CI: 2.455-2.606), a lower proportion of unemployed job seekers (OR: 0.641, 95% CI: 0.624-0.658) and lower use of dental care (OR: 0.969, 95% CI: 0.967-0.972). Conclusion Coverage rate of BC screening is not optimal in Flanders. Women with low SES that are characterized by younger age, living in a high population density area, living in crowded households, or having low dental care are less likely to be screened for BC in Flanders. If screened, they are more likely to be screened outside the BCSP.

Abstract: Coupling photosensitizers (PSs) with plasmonic nanoparticles increases the photocatalytic activity of PSs as the localized surface plasmon resonance (LSPR) of plasmonic nanoparticles leads to extreme concentration of light in their vicinity known as the near-field enhancement effect. To realize this in a colloidal phase, efficient conjugation of the PS molecules with the plasmonic nanoparticle surface is critical. In this work, we demonstrate the coupling of phthalocyanine (Pc) molecules with gold nanoparticles (AuNPs) in the colloidal phase via click chemistry. This conjugated Pc-AuNPs colloidal system is shown to enhance the photocatalytic singlet oxygen (1O2) production over non-conjugated Pcs and hence improve the photoelectrochemical detection of phenols. The plasmonic enhancement of the 1O2 generation by Pcs was clearly elucidated by complementary experimental and computational classical electromagnetic models. The dependence of plasmonic enhancement on the spectral position of the excitation laser wavelength and the absorbance of the Pc molecules with respect to the wavelength specific near-field enhancement is clearly demonstrated. A high similar to 8 times enhancement is obtained with green laser (532 nm) at the LSPR due to the maximum near-field enhancement at the resonance wavelength. Zinc phthalocyanine is covalently linked to plasmonic AuNPs via click chemistry to investigate the synergistic effect that boosts the overall activity toward the detection of HQ under visible light illumination. The 1O2 quantum yield of ZnPc improved significantly after conjugating with AuNPs, resulting in enhanced photoelectrochemical activity. image

Abstract: Assemblies of closely separated gold nanoparticles exhibit a strong collective plasmonic response due to coupling of the plasmon modes of the individual nanostructures. In the context of self-assembly of nanoparticles, close-packed two-dimensional (2D) clusters of spherical nanoparticles present an important composite system that promises numerous applications. The present study probes the collective plasmonic characteristics and resulting photothermal behavior of close-packed 2D Au nanoparticle clusters to delineate the effects of the cluster size, interparticle distance, and particle size. Smaller nanoparticles (20 and 40 nm in diameter) that exhibit low individual scattering and high absorption were considered for their relevance to photothermal applications. In contrast to typical literature studies, the present study compares the optical response of clusters of different sizes ranging from a single nanoparticle up to large assemblies of 61 nanoparticles. Increasing the cluster size induces significant changes to the spectral position and optophysical characteristics. Based on the model outcome, an optimal cluster size for maximum absorption per nanoparticle is also determined for enhanced photothermal effects. The effect of the particle size and interparticle distance is investigated to elucidate the nature of interaction in terms of near-field and far-field coupling. The photothermal effect resulting from absorption is compared for different cluster sizes and interparticle distances considering a homogeneous water medium. A strong dependence of the steady-state temperature of the nanoparticles on the cluster size, particle position in the cluster, incident light polarization, and interparticle distance provides new physical insight into the local temperature control of plasmonic nanostructures.

Abstract: In this study, the microbial community characteristics in continuous lab-scale anaerobic reactors were correlated to reactor functionality using the microbial resource management (MRM) approach. Two molecular techniques, denaturing gradient gel electrophoresis (DGGE) and terminal-restriction fragment length polymorphism (T-RFLP), were applied to analyze the bacterial and archaeal communities, and the results obtained have been compared. Clustering analyses showed a similar discrimination of samples with DGGE and T-RFLP data, with a clear separation between the meso- and thermophilic communities. Both techniques indicate that bacterial and mesophilic communities were richer and more even than archaeal and thermophilic communities, respectively. Remarkably, the community composition was highly dynamic for both Bacteria and Archaea, with a rate of change between 30% and 75% per 18 days, also in stable performing periods. A hypothesis to explain the latter in the context of the converging metabolism in anaerobic processes is proposed. Finally, a more even and diverse bacterial community was found to be statistically representative for a well-functioning reactor as evidenced by a low Ripley index and high biogas production.

Abstract: We present a large dataset containing simulated core-loss electron energy loss spectroscopy (EELS) spectra with the elemental content as ground-truth labels. Additionally we present some neural networks trained on this data for element identification.  The simulated dataset contains zero padded core-loss spectra from 0 to 3072 eV, which represents 107 core-loss edges through all 80 elements from Be up to Bi. The core-loss edges are calculated from the generalised oscillator strength (GOS) database presented by Zhang et al.[1] Generic fine structures using lifetime broadened peaks are used to imitate fine structure due to solid-state effects in experimental spectra. Generic low-loss regions are used to imitate the effect of multiple scattering. Each spectrum contains at least one edge of a given query element and possibly additional edges depending on samples drawn from The Materials Project [2]. The dataset contains for each of the 80 elements: 7000 training spectra, 1500 test spectra, 600 validation spectra and 100 spectra representing only the query element. This results in a total 736 000 labeled spectra. Code on how to  – read the simulated data – transform HDF5 format to TFRecord format – train and evaluate neural networks using the simulated data – use the trained networks for automated element identification is available on GitHub at arnoannys/EELS_ID A full report on the simulation of the dataset and the training and evaluation of the neural networks can be found at:                    Annys, A., Jannis, D. & Verbeeck, J. Deep learning for automated materials characterisation in core-loss electron energy loss spectroscopy. Sci Rep 13, 13724 (2023). https://doi.org/10.1038/s41598-023-40943-7 [1] Zezhong Zhang, Ivan Lobato, Daen Jannis, Johan Verbeeck, Sandra Van Aert, & Peter Nellist. (2023). Generalised oscillator strength for core-shell electron excitation by fast electrons based on Dirac solutions (1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7729585 [2] Anubhav Jain, Shyue Ping Ong, Geoffroy Hautier, Wei Chen, William Davidson Richards, Stephen Dacek, Shreyas Cholia, Dan Gunter, David Skinner, Gerbrand Ceder, Kristin A. Persson; Commentary: The Materials Project: A materials genome approach to accelerating materials innovation. APL Mater 1 July 2013; 1 (1): 011002. [https://doi.org/10.1063/1.4812323](https://doi.org/10.1063/1.4812323)

Abstract: The hot working of 5xxx series alloys with Mg ≥3.5 wt% is a concern due to the precipitation of β (Al3Mg2) phase at grain boundaries favoring Inter Granular Corrosion (IGC). The mechanical and corrosion properties of a new 5028-H116 Al-Mg-Sc alloy under various β precipitates distribution is analyzed by imposing different cooling rates from the hot forming temperature (i.e. 325 °C). The mechanical properties are maintained regardless of the heat treatment. However, the different nucleation sites and volume fractions of β precipitates for different cooling rates critically affect IGC. Controlled furnace cooling after the 325 °C heat treatment is ideal in 5028-H116 alloy to reduce susceptibility to IGC after sensitization.

Abstract: To gain full control over the growth of carbon nanotubes (CNTs) using plasma-enhanced chemical vapor deposition (PECVD), a thorough understanding of the underlying plasma-catalyst mechanisms is required. Oxygen-containing species are often used as or added to the growth precursor gas, but these species also yield various radicals and ions, which may simultaneously etch the CNT during the growth. At present, the effect of these reactive species on the growth onset has not yet been thoroughly investigated. We here report on the etching mechanism of incipient CNT structures from OH and O radicals as derived from combined (reactive) molecular dynamics (MD) and force-bias Monte Carlo (tfMC) simulations. Our results indicate that the oxygen-containing radicals initiate a dissociation process. In particular, we show how the oxygen species weaken the interaction between the CNT and the nanocluster. As a result of this weakened interaction, the CNT closes off and dissociates from the cluster in the form of a fullerene. Beyond the specific systems studied in this work, these results are generically important in the context of PECVD-based growth of CNTs using oxygen-containing precursors.

Abstract: Porous limestone and mortar are able to absorb large quantities of water. This phenomenon will accelerate the deterioration of the material. In such cases, the material might be treated with a hydrophobic product, which creates a superficial layer that hampers the penetration of water. In order to decide if such a treatment should be applied or not, the water absorbing behaviour of the material should be measured. With the same measuring technique the efficiency of the hydrophobic barrier can be evaluated. Moreover, it allows the monitoring of such barriers as a function of time. At the same time, the water absorption of porous stone material is an indication of the degree of deterioration and its sensitivity to future deterioration. Up to now, two different measuring techniques exist, but one can only be used in laboratory and the other, which can be operated in laboratory as well as in situ, is not always reliable for in situ analyses. This article proposes an alternative method: the contact sponge method. This recently developed method was tested on non-treated porous stone materials in a laboratory environment in order to evaluate its performance in comparison with the two existing methods.