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Herein we report on the formation of the adduct salts [Xe(OTeF5)(pyF)][Al(OTeF5)4] (pyF = C5F5N, C5H3F2N) by abstraction of an –OTeF5 group from Xe(OTeF5)2 with the Lewis superacid Al(OTeF5)3 and subsequent adduct formation of the generated [XeOTeF5]+ cation with fluorinated pyridines. These salts represent the first xenonium cations with the weakly coordinating [Al(OTeF5)4]− anion. The strong oxidizing property of these compounds is further assessed. [ABSTRACT FROM AUTHOR]

Privacy-utility tradeoff remains as one of the fundamental issues of differentially private machine learning. This paper introduces a geometrically inspired kernel-based approach to mitigate the accuracy-loss issue in classification. In this approach, a representation of the affine hull of given data points is learned in Reproducing Kernel Hilbert Spaces (RKHS). This leads to a novel distance measure that hides privacy-sensitive information about individual data points and improves the privacy-utility tradeoff via significantly reducing the risk of membership inference attacks. The effectiveness of the approach is demonstrated through experiments on MNIST dataset, Freiburg groceries dataset, and a real biomedical dataset. It is verified that the approach remains computationally practical. The application of the approach to federated learning is considered and it is observed that the accuracy-loss due to data being distributed is either marginal or not significantly high. [ABSTRACT FROM AUTHOR]

The straightforward synthesis of polyamide-derived statistical copolymers with catechol, amine, amide and hydroxy residues via free radical polymerization is presented. In particular, catechol, amine and amide residues are present in natural mussel foot proteins, enabling strong underwater adhesion due to synergistic effects where cationic residues displace hydration and ion layers, followed by strong short-rang hydrogen bonding between the catechol or primary amides and SiO2 surfaces. The present study is aimed at investigating whether such synergistic effects also exist for statistical copolymer systems that lack the sequence-defined positioning of functional groups in mussel foot proteins. A series of copolymers is established and the adsorption in saline solutions on SiO2 is determined by quartz crystal microbalance measurements and ellipsometry. These studies confirm a synergy between cationic amine groups with catechol units and primary amide groups via an increased adsorptivity and increased polymer layer thicknesses. Therefore, the free radical polymerization of catechol, amine and amide monomers as shown here may lead to simplified mussel-inspired adhesives that can be prepared with the readily scalable methods required for large-scale applications. [ABSTRACT FROM AUTHOR]

In order to develop machine learning and deep learning models that take into account the guidelines and principles of trustworthy AI, a novel information theoretic approach is introduced in this article. A unified approach to privacy-preserving interpretable and transferable learning is considered for studying and optimizing the trade-offs between the privacy, interpretability, and transferability aspects of trustworthy AI. A variational membership-mapping Bayesian model is used for the analytical approximation of the defined information theoretic measures for privacy leakage, interpretability, and transferability. The approach consists of approximating the information theoretic measures by maximizing a lower-bound using variational optimization. The approach is demonstrated through numerous experiments on benchmark datasets and a real-world biomedical application concerned with the detection of mental stress in individuals using heart rate variability analysis. [ABSTRACT FROM AUTHOR]

Herein, we successfully fabricated porous nanocomposite membranes decorated with high loadings of nickel nanoparticles (25–45 wt %) by using chelating additives (sodium dodecyl sulfate (SDS) and Fumion) for the film casting cum phase separation approach. These additives decreased the nickel agglomeration and promoted the presentation of particles at the pore surface of the final membranes, leading to increased water permeances (450 to 1200–2400 L/m2 hbar) and porosities (56% to 70–78%) in comparison to a nanocomposite membrane made without additives. The hydrophobic ionomer Fumion, incorporated into the polyethersulfone matrix during solidification, further allowed us to tune the membrane hydrophobicity. We discovered that the same nickel nanoparticles exhibited a 5× increased H2 generation rate during the catalytic hydrogen formation from ammonia borane when presented in a membrane with a higher water contact angle (85° compared to 60°). We could attribute this improvement to the lower capillary pressure in more hydrophobic pores, which facilitates the release of H2 bubbles. The nanocomposite membranes were further employed as flow-through reactors for the catalytic hydrogenation of p-nitrophenol (p-NP) in the presence of ammonia borane. Membranes with an additive-directed nickel nanoparticle presentation at the pore surface demonstrated 6 to 7× higher p-NP turnover frequencies (TOFs). We also observed that the formation of hydrogen gas from ammonia borane results in a permeance decrease during the flow-through p-NP conversion. However, this effect was mitigated in more hydrophilic membranes with an anisotropic pore structure. [ABSTRACT FROM AUTHOR]

Magnetic gels and elastomers are promising candidates to construct reversibly excitable soft actuators, triggered from outside by magnetic fields. These magnetic fields induce or alter the magnetic interactions between discrete rigid particles embedded in a soft elastic polymeric matrix, leading to overall deformations. It is a major challenge in theory to correctly predict from the discrete particle configuration the type of deformation resulting for a finite-sized system. Considering an elastic sphere, we here present such an approach. The method is in principle exact, at least within the framework of linear elasticity theory and for large enough interparticle distances. Different particle arrangements are considered. We find, for instance, that regular simple cubic configurations show elongation of the sphere along the magnetization if oriented along a face or space diagonal of the cubic unit cell. Contrariwise, with the magnetization along the edge of the cubic unit cell, they contract. The opposite is true in this geometry for body- and face-centered configurations. Remarkably, for the latter configurations but the magnetization along a face or space diagonal of the unit cell, contraction was observed to revert to expansion with decreasing Poisson ratio of the elastic material. Randomized configurations were considered as well. They show a tendency of elongating the sphere along the magnetization, which is more pronounced for compressible systems. Our results can be tested against actual experiments for spherical samples. Moreover, our approach shall support the search of optimal particle distributions for a maximized effect of actuation. [ABSTRACT FROM AUTHOR]

Medical Assisted Reproduction proved its efficacy to treat the vast majority forms of infertility. One of the key procedures in this treatment is the selection and transfer of the embryo with the highest developmental potential. To assess this potential, clinical embryologists routinely work with static images (morphological assessment) or short video sequences (time-lapse annotation). Recently, Artificial Intelligence models were utilized to support the embryo selection procedure. Even though they have proven their great potential in different in vitro fertilization settings, there is still considerable room for improvement. To support the advancement of algorithms in this research field, we built a dataset consisting of static blastocyst images and additional annotations. As such, Gardner criteria annotations, depicting a morphological blastocyst rating scheme, and collected clinical parameters are provided. The presented dataset is intended to be used to train deep learning models on static morphological images to predict Gardner's criteria and clinical outcomes such as live birth. A benchmark of human expert's performance in annotating Gardner criteria is provided. [ABSTRACT FROM AUTHOR]

Although not labeled as such, the three research centers presented in this article have been performing translational computer science (TCS) for more than 20 years. SBA Research, Software Competence Center Hagenberg, and VRVis Zentrum fuer Virtual Reality und Visualisierung, all funded by the Austrian COMET Competence Centers for Excellent Technologies program, each selected one science–industry partnership to exemplify how they do TCS in their day-to-day work. We show how the COMET funding program provides a framework for establishing long-term research relationships with industry, thus facilitating TCS: research done by the COMET centers is directly put in the practical context of the industry partners, and successes and failures are immediately reported back. This constant feedback loop positively impacts the know-how at the involved companies, while allowing the computer scientists to continuously test, improve, and publish their research based on real-world scenarios. [ABSTRACT FROM AUTHOR]

We present an electrical mobility classifier for mass–mobility measurements of atmospheric ions. Size segregation coupled with mass spectrometric detection of naturally occurring ions in the atmosphere is challenging due to the low ion concentration. Conventional electrical mobility classifying devices were not yet coupled with mass spectrometry to resolve natural ion composition. This is due to either the insufficient transmission efficiency or design concepts being incompatible with this application, e.g. using high electric fields close to the inlets to push ions from high to low electric potential. Here, we introduce an axial ion mobility classifier, termed AMC, with the aim to achieve higher transmission efficiencies to segregate natural ions at reasonable sizing resolution. Similar to the recently introduced principle of the high-pass electrical mobility filter (HP-EMF) presented by Bezantakos et al. (2015) and Surawski et al. (2017), ions are classified via an electric field that is opposed to the gas flow direction carrying the ions. Compared to the HP-EMF concept, we make use of sheath flows to improve the size resolution in the sub-3 nm range. With our new design we achieve a sizing resolution of 7 Z/ΔZ with a transmission efficiency of about 70 %. [ABSTRACT FROM AUTHOR]

In the last decade, industry's demand for deep learning (DL) has increased due to its high performance in complex scenarios. Due to the DL method's complexity, experts and non-experts rely on blackbox software packages such as Tensorflow and Pytorch. The frameworks are constantly improving, and new versions are released frequently. As a natural process in software development, the released versions contain improvements/changes in the methods and their implementation. Moreover, versions may be bug-polluted, leading to the model performance decreasing or stopping the model from working. The aforementioned changes in implementation can lead to variance in obtained results. This work investigates the effect of implementation changes in different major releases of these frameworks on the model performance. We perform our study using a variety of standard datasets. Our study shows that users should consider that changing the framework version can affect the model performance. Moreover, they should consider the possibility of a bug-polluted version before starting to debug source code that had an excellent performance before a version change. This also shows the importance of using virtual environments, such as Docker, when delivering a software product to clients. [ABSTRACT FROM AUTHOR]

Dendrites receive the vast majority of a single neuron's inputs, and coordinate the transformation of these signals into neuronal output. Ex vivo and theoretical evidence has shown that dendrites possess powerful processing capabilities, yet little is known about how these mechanisms are engaged in the intact brain or how they influence circuit dynamics. New experimental and computational technologies have led to a surge in interest to unravel and harness their computational potential. This review highlights recent and emerging work that combines established and cutting-edge technologies to identify the role of dendrites in brain function. We discuss active dendritic mediation of sensory perception and learning in neocortical and hippocampal pyramidal neurons. Complementing these physiological findings, we present theoretical work that provides new insights into the underlying computations of single neurons and networks by using biologically plausible implementations of dendritic processes. Finally, we present a novel brain-computer interface task, which assays somatodendritic coupling to study the mechanisms of biological credit assignment. Together, these findings present exciting progress in understanding how dendrites are critical for in vivo learning and behavior, and highlight how subcellular processes can contribute to our understanding of both biological and artificial neural computation. [ABSTRACT FROM AUTHOR]

Macroscopic elastic core-shell systems can be generated as toy models to be deformed and haptically studied by hand. On the mesoscale, colloidal core-shell particles and microgels are fabricated and investigated by different types of microscopy. We analyse, using linear elasticity theory, the response of spherical core-shell systems under the influence of a line density of force that is oriented radially and acts along the equator of the outer surface. Interestingly, deformational coupling of the shell to the core can determine the resulting overall appearance in response to the forces. We address various combinations of radii, stiffness, and Poisson ratio of core and shell and illustrate the resulting deformations. Macroscopically, the situation could be realized by wrapping a cord around the equator of a macroscopic model system and pulling it tight. On the mesoscale, colloidal microgel particles symmetrically confined to the interface between two immiscible fluids are pulled radially outward by surface tension. [ABSTRACT FROM AUTHOR]

We present an electrical mobility classifier for mass-mobility measurements of atmospheric ions. Size segregation coupled with mass spectrometric detection of naturally occurring ions in the atmosphere is challenging due to the low ion concentration. Conventional electrical mobility classifying devices were not yet coupled with mass spectrometry to resolve natural ion composition. This is either due to the insufficient transmission efficiency, or design concepts are incompatible with this application e.g., using high electric fields close to the inlets to push ions from high to low electric potential. Here, we introduce an axial ion mobility classifier, termed AMC, with the aim to achieve higher transmission efficiencies to segregate natural ions at reasonable sizing resolution. Similar, to the recently introduced principle of the high-pass electrical mobility filter (HP-EMF) presented by Bezantakos et al., 2015, and Surawski et al., 2017, ions are classified via an electric field that is opposed to the gas flow direction carrying the ions. Compared to the HP-EMF concept, we make use of sheath flows to improve the size resolution in the sub 3 nm range. With our new design we achieve a sizing resolution of 7 with a transmission efficiency of about 70 %. [ABSTRACT FROM AUTHOR]

Service research emphasizes the relevance of consumers' participation in the cocreation of transformative outcomes like health and well-being. However, in complex services, consumers' limited operant resources and lacking resource integration efficiency hinder transformative value cocreation. Service research on mechanisms that facilitate well-being through efficient resource integration is sparse, but several disciplines elaborate cognitive interventions with that target. These interventions have been validated in various contexts. Nevertheless, concerns persist that they can hurt, rather than help, individual consumers. Overcoming such limitations requires an interdisciplinary effort. The present article outlines the new research area "transformative consumer interventions" (TCI) by integrating interventions theory, consumer psychology, and transformative service research in a health context. TCI provide theory-driven principles for the selection and design of interventions that facilitate operant resource integration in complex services. Additionally, we conceptualize consumer boosting, the first TCI-based intervention construct. Consumer boosts are efficient, context-specific, and personalized interventions that enhance individuals' operant resources. Consumer boosting provides a pathway to transformative cocreation and alleviates the risk of unintended consequences and value co-destruction. This research illustrates that the transformative service domain stands to benefit substantially from getting involved in the discussion on consumer interventions and offers a unique perspective for further conceptual elaboration. [ABSTRACT FROM AUTHOR]

We present first eddy covariance flux measurements with the PTR3-TOF-MS, a novel proton transfer time of flight reaction mass spectrometer. During 3 weeks in spring 2016, the instrument recorded 10 Hz data of biogenic volatile organic compounds above a boreal forest, on top of a measurement tower at the SMEAR (Station for Measuring Ecosystem –Atmosphere Relations) II station in Hyytiälä, Finland. Flux and concentration data of isoprene, monoterpenes, and sesquiterpenes were compared to the literature. Due to the improved instrument sensitivity and a customized wall-less inlet design, we could detect fluxes of semi-volatile and low-volatility organic compounds with less than single-digit picomol per square meter per second (pmolm-2s-1) values for the first time. These compounds include sesquiterpene oxidation products and diterpenes. Daytime diterpene fluxes were in the range of 0.05 to 0.15 pmolm-2s-1 , which amounts to about 0.25 % to 0.5 % of the daytime sesquiterpene flux above canopy. [ABSTRACT FROM AUTHOR]

Background: Neoadjuvant chemotherapy in patients with primary osteosarcoma improves survival rates, but it also causes side effects in various organs including bone. Low bone mineral density (BMD) can occur owing partly to chemotherapy or limited mobility. This can cause a higher risk of fractures compared with those who do not receive such treatment. Changes in BMD alone cannot explain the propensity of fractures. Studying microarchitectural changes of bone might help to understand the effect.Questions/purposes: (1) Do patients who were treated for osteosarcoma (more than 20 years previously) have low BMD? (2) Do these patients experience more fractures than controls who do not have osteosarcoma? (3) What differences in bone microarchitecture are present between patients treated for high-grade osteosarcoma and individuals who have never had osteosarcoma?Methods: We contacted 48 patients who were treated for osteosarcoma and who participated in an earlier study. These patients underwent multimodal treatment including chemotherapy more than 20 years ago. Of the original patient group, 60% (29 of 48) were missing, leaving 40% (19 of 48) available for inclusion in this study; all 19 agreed to participate. There were nine men and 10 women with a mean age of 46 ± 4 years and a mean time from surgery to examination of 28 ± 3 years. BMD was measured by dual-energy x-ray absorptiometry, and any fracture history was assessed using a questionnaire. Additionally, high-resolution peripheral quantitative CT was performed to compare the groups in terms of microarchitectural changes, such as cortical and trabecular area, cortical and trabecular thickness, cortical porosity, and endocortical perimeter. Participants in the control group were selected from a cohort consisting of a population-based random sample of 499 healthy adult women and men. Osteoporosis or low BMD was not an exclusion criterion for entering this study; however, the patients in the control group were selected based on a normal BMD (that is, T score > -1.0 at both the spine and hip). Also, the participants were matched based on age and sex. Differences between patients and controls were assessed using the Wilcoxon rank sum test for continuous variables and a chi-square test for categorical variables. A multiple regression analysis was performed. Model assumptions were checked using histograms and quantile-quantile plots of residuals.Results: Twelve of 19 patients who were treated for osteosarcoma had either osteopenia (eight patients) or osteoporosis (four patients). More patients with osteosarcoma reported sustaining fractures (11 of 19 patients) than did control patients (2 of 19 controls; p < 0.001). Among all microarchitectural parameters, only the endocortical perimeter was increased in patients compared with the control group (75 ± 15 mm versus 62 ± 18 mm; p = 0.04); we found no differences between the groups in terms of cortical and trabecular area, cortical and trabecular thickness, or cortical porosity.Conclusion: Although patients who were treated for osteosarcoma had osteopenic or osteoporotic BMD and a higher proportion of patients experienced fractures than did patients in the control group, we could not confirm differences in microarchitectural parameters using high-resolution peripheral quantitative CT. Therefore, it seems that bone geometry and microstructural parameters are not likely the cause of the increased proportion of fractures observed in our patients who were treated for osteosarcoma. Until we learn more about the bone changes associated with chemotherapy in patients with osteosarcoma, we recommend that patients undergo regular BMD testing, and we recommend that physicians consider osteoporosis treatment in patients with low BMD. These data might provide the impetus for future multicenter prospective studies examining the association between chemotherapy and bone microarchitecture.Level Of Evidence: Level III, therapeutic study. [ABSTRACT FROM AUTHOR]

For the first time, the direct synthesis of 1-methyl-phosphininium salts has been achieved by reacting aromatic λ3,σ2-phosphinines with the readily available dimethyl chloronium salt [(CH3)2Cl]+[Al(OTeF5)4]−. The remarkably high electrophilicity of the alkylation reagent in combination with the weakly coordinating pentafluoro-orthotelluratoaluminate anion offers excellent conditions for this one-step approach. Our simple and quantitative access to 1-methyl-phosphininium salts will pave the way to explore the chemistry of such reactive species in more detail. [ABSTRACT FROM AUTHOR]

Separating and labeling each nuclear instance (instance-aware segmentation) is the key challenge in nuclear image segmentation. Deep Convolutional Neural Networks have been demonstrated to solve nuclear image segmentation tasks across different imaging modalities, but a systematic comparison on complex immunofluorescence images has not been performed. Deep learning based segmentation requires annotated datasets for training, but annotated fluorescence nuclear image datasets are rare and of limited size and complexity. In this work, we evaluate and compare the segmentation effectiveness of multiple deep learning architectures (U-Net, U-Net ResNet, Cellpose, Mask R-CNN, KG instance segmentation) and two conventional algorithms (Iterative h-min based watershed, Attributed relational graphs) on complex fluorescence nuclear images of various types. We propose and evaluate a novel strategy to create artificial images to extend the training set. Results show that instance-aware segmentation architectures and Cellpose outperform the U-Net architectures and conventional methods on complex images in terms of F1 scores, while the U-Net architectures achieve overall higher mean Dice scores. Training with additional artificially generated images improves recall and F1 scores for complex images, thereby leading to top F1 scores for three out of five sample preparation types. Mask R-CNN trained on artificial images achieves the overall highest F1 score on complex images of similar conditions to the training set images while Cellpose achieves the overall highest F1 score on complex images of new imaging conditions. We provide quantitative results demonstrating that images annotated by under-graduates are sufficient for training instance-aware segmentation architectures to efficiently segment complex fluorescence nuclear images. [ABSTRACT FROM AUTHOR]

The so-called "raspberry" model refers to the hybrid lattice-Boltzmann (LB) and Langevin molecular dynamics schemes for simulating the dynamics of suspensions of colloidal particles, originally developed by Lobaskin and Dünweg [New J. Phys. 6, 54 (2004)], wherein discrete surface points are used to achieve fluid-particle coupling. In this paper, we present a follow up to our study of the effectiveness of the raspberry model in reproducing hydrodynamic interactions in the Stokes regime for spheres arranged in a simple-cubic crystal [Fischer et al., J. Chem. Phys. 143, 084107 (2015)]. Here, we consider the accuracy with which the raspberry model is able to reproduce such interactions for particles confined between two parallel plates. To this end, we compare our LB simulation results to established theoretical expressions and finite-element calculations. We show that there is a discrepancy between the translational and rotational mobilities when only surface coupling points are used, as also found in Part I of our joint publication. We demonstrate that adding internal coupling points to the raspberry can be used to correct said discrepancy in confining geometries as well. Finally, we show that the raspberry model accurately reproduces hydrodynamic interactions between a spherical colloid and planar walls up to roughly one LB lattice spacing. [ABSTRACT FROM AUTHOR]

The so-called "raspberry" model refers to the hybrid lattice-Boltzmann and Langevin molecular dynamics scheme for simulating the dynamics of suspensions of colloidal particles, originally developed by Lobaskin and Dünweg [New J. Phys. 6, 54 (2004)], wherein discrete surface points are used to achieve fluid-particle coupling. This technique has been used in many simulation studies on the behavior of colloids. However, there are fundamental questions with regards to the use of this model. In this paper, we examine the accuracy with which the raspberry method is able to reproduce Stokes-level hydrodynamic interactions when compared to analytic expressions for solid spheres in simple-cubic crystals. To this end, we consider the quality of numerical experiments that are traditionally used to establish these properties and we discuss their shortcomings. We show that there is a discrepancy between the translational and rotational mobility reproduced by the simple raspberry model and present a way to numerically remedy this problem by adding internal coupling points. Finally, we examine a non-convex shape, namely, a colloidal dumbbell, and show that the filled raspberry model replicates the desired hydrodynamic behavior in bulk for this more complicated shape. Our investigation is continued in de Graaf et al. [J. Chem. Phys. 143, 084108 (2015)], wherein we consider the raspberry model in the confining geometry of two parallel plates. [ABSTRACT FROM AUTHOR]

We present first eddy covariance flux measurements with the PTR3-TOF-MS, a novel proton-transfer-reaction mass-spectrometer. During three weeks in spring 2016 the instrument recorded 10 Hz data of biogenic volatile organic compounds above a boreal forest, on top of a measurement tower at the SMEAR II station in Hyytiälä, Finland. Flux and concentration data of isoprene, monoterpenes and sesquiterpenes were compared to the literature. Due to the improved instrument sensitivity and a customized "wall less" inlet design we could detect fluxes of semi-volatile and low volatile organic compounds with less than single digit picomol/m²/s values for the first time. These compounds include sesquiterpene oxidation products and diterpenes. Daytime diterpene fluxes were in the range of 0.05 to 0.15 picomol/m²/s, which amounts to about 0.25% to 0.5% of the daytime sesquiterpene flux above canopy. [ABSTRACT FROM AUTHOR]

Purpose: Swept Source Optical coherence tomography angiography (SS-OCTA) is a novel technique to visualize perfusion and vascular changes like ischemia in patients with diabetic retinopathy. The aim of this study was to compare non-perfusion areas on conventional fluorescein angiography (FA) with those on SS-OCTA using detailed manual annotation in patients with diabetic macular edema (DME) and to evaluate possible artifacts caused by DME on SS-OCTA. Methods: 27 eyes of 21 patients with DME were analyzed in this prospective, cross-sectional study; on all, standard ophthalmological examination, SS-OCTA and FA imaging were performed. Early-phase FA and SS-OCTA images were analyzed for capillary dropout and foveal avascular zone (FAZ) was measured on both modalities. Artifacts in SS-OCTA imaging caused by DME were marked and analyzed. Results: The mean age of the patients was 62.6 ± 11.5 years. On FA the mean size of the annotated non-perfusion areas was 0.14 ± 0.31 mm2 whereas the mean size in SS-OCTA was 0.04 ± 0.13 mm2; areas marked on FA were statistically significantly larger than on SS-OCTA (p<0.01). Mean size of FAZs was similar between FA and OCTA images. (p = 0.91). Seven eyes (25.9 percent) showed imaging artifacts due to DME in SS-OCTA. Conclusion: SS-OCTA is a valid tool to analyze capillary perfusion status of patients with DME, although areas of non-perfusion were measured smaller than in conventional FA. More non-perfusion areas were found on SS-OCTA images. FAZ measurements were similar using the two modalities. However, SS-OCTA is prone to artifacts and therefore requires reviewing of imaging results: up to 25 percent of the analyzed eyes showed artifacts on OCTA, which occurred in the areas of diabetic macular edema and did not correspond to capillary drop out. [ABSTRACT FROM AUTHOR]

Soft elastic composite materials can serve as actuators when they transform changes in external fields into mechanical deformation. Here, we theoretically address the corresponding deformational behavior in model systems of magnetic gels and elastomers exposed to external magnetic fields. In reality, such materials consist of magnetizable colloidal particles in a soft polymeric matrix. Since many practical realizations of such materials involve particulate inclusions of polydisperse size distributions, we concentrate on the effect that mixed particle sizes have on the overall deformational response. To perform a systematic study, our focus is on binary size distributions. We systematically vary the fraction of larger particles relative to smaller ones and characterize the resulting magnetostrictive behavior. The consequences for systems of various different spatial particle arrangements and different degrees of compressibility of the elastic matrix are evaluated. In parts, we observe a qualitative change in the overall response for selected systems of mixed particle sizes. Specifically, overall changes in volume and relative elongations or contractions in response to an induced magnetization can be reversed into the opposite types of behavior. Our results should apply to the characteristics of other soft elastic composite materials like electrorheological gels and elastomers when exposed to external electric fields as well. Overall, we hope to stimulate corresponding experimental realizations and the further investigation on the purposeful use of mixed particle sizes as a means to design tailored requested material behavior. [ABSTRACT FROM AUTHOR]

Nucleation of atmospheric vapours produces more than half of global cloud condensation nuclei and so has an important influence on climate. Recent studies show that monoterpene (C10H16) oxidation yields highly oxygenated products that can nucleate with or without sulfuric acid. Monoterpenes are emitted mainly by trees, frequently together with isoprene (C5H8), which has the highest global emission of all organic vapours. Previous studies have shown that isoprene suppresses new-particle formation from monoterpenes, but the cause of this suppression is under debate. Here, in experiments performed under atmospheric conditions in the CERN CLOUD chamber, we show that isoprene reduces the yield of highly oxygenated dimers with 19 or 20 carbon atoms – which drive particle nucleation and early growth – while increasing the production of dimers with 14 or 15 carbon atoms. The dimers (termed C20 and C15 , respectively) are produced by termination reactions between pairs of peroxy radicals (RO2⚫) arising from monoterpenes or isoprene. Compared with pure monoterpene conditions, isoprene reduces nucleation rates at 1.7 nm (depending on the isoprene / monoterpene ratio) and approximately halves particle growth rates between 1.3 and 3.2 nm. However, above 3.2 nm, C15 dimers contribute to secondary organic aerosol, and the growth rates are unaffected by isoprene. We further show that increased hydroxyl radical (OH⚫) reduces particle formation in our chemical system rather than enhances it as previously proposed, since it increases isoprene-derived RO2⚫ radicals that reduce C20 formation. RO2⚫ termination emerges as the critical step that determines the highly oxygenated organic molecule (HOM) distribution and the corresponding nucleation capability. Species that reduce the C20 yield, such as NO, HO2 and as we show isoprene, can thus effectively reduce biogenic nucleation and early growth. Therefore the formation rate of organic aerosol in a particular region of the atmosphere under study will vary according to the precise ambient conditions. [ABSTRACT FROM AUTHOR]

In Graeco-Roman times in the Lower-Egyptian Fayoum region, a painted portrait was traditionally placed over the face of a deceased individual. These mummy portraits show considerable inter-individual diversity. This suggests that those portraits were created separately for each individual. In the present study, we investigated a completely wrapped young infant mummy with a typical mummy portrait by whole body CT analysis. This was used to obtain physical information on the infant and provided the basis for a virtual face reconstruction in order to compare it to the mummy portrait. We identified the mummy as a 3–4 years old male infant that had been prepared according to the typical ancient Egyptian mummification rites. It most probably suffered from a right-sided pulmonary infection which may also be the cause of death. The reconstructed face showed considerable similarities to the portrait, confirming the portrait's specificity to this individual. However, there are some differences between portrait and face. The portrait seems to show a slightly older individual which may be due to artistic conventions of that period. [ABSTRACT FROM AUTHOR]

Fully-automated nuclear image segmentation is the prerequisite to ensure statistically significant, quantitative analyses of tissue preparations,applied in digital pathology or quantitative microscopy. The design of segmentation methods that work independently of the tissue type or preparation is complex, due to variations in nuclear morphology, staining intensity, cell density and nuclei aggregations. Machine learning-based segmentation methods can overcome these challenges, however high quality expert-annotated images are required for training. Currently, the limited number of annotated fluorescence image datasets publicly available do not cover a broad range of tissues and preparations. We present a comprehensive, annotated dataset including tightly aggregated nuclei of multiple tissues for the training of machine learning-based nuclear segmentation algorithms. The proposed dataset covers sample preparation methods frequently used in quantitative immunofluorescence microscopy. We demonstrate the heterogeneity of the dataset with respect to multiple parameters such as magnification, modality, signal-to-noise ratio and diagnosis. Based on a suggested split into training and test sets and additional single-nuclei expert annotations, machine learning-based image segmentation methods can be trained and evaluated. Measurement(s) nucleus • Annotation • Frozen Section • Neuroblastoma • Touch Prep Slide • Centrifuged Smear Slide • cells grown on slide • Ganglioneuroblastoma • Wilms Tumor • HaCaT cell Technology Type(s) Fluorescence Imaging • machine learning Factor Type(s) nucleus segmentation Sample Characteristic - Organism Homo sapiens Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12570854 [ABSTRACT FROM AUTHOR]

Highly oxygenated organic molecules (HOMs) contribute substantially to the formation and growth of atmospheric aerosol particles, which affect air quality, human health and Earth's climate. HOMs are formed by rapid, gas-phase autoxidation of volatile organic compounds (VOCs) such as α -pinene, the most abundant monoterpene in the atmosphere. Due to their abundance and low volatility, HOMs can play an important role in new-particle formation (NPF) and the early growth of atmospheric aerosols, even without any further assistance of other low-volatility compounds such as sulfuric acid. Both the autoxidation reaction forming HOMs and their NPF rates are expected to be strongly dependent on temperature. However, experimental data on both effects are limited. Dedicated experiments were performed at the CLOUD (Cosmics Leaving OUtdoor Droplets) chamber at CERN to address this question. In this study, we show that a decrease in temperature (from +25 to -50 ∘ C) results in a reduced HOM yield and reduced oxidation state of the products, whereas the NPF rates (J1.7nm) increase substantially. Measurements with two different chemical ionization mass spectrometers (using nitrate and protonated water as reagent ion, respectively) provide the molecular composition of the gaseous oxidation products, and a two-dimensional volatility basis set (2D VBS) model provides their volatility distribution. The HOM yield decreases with temperature from 6.2 % at 25 ∘ C to 0.7 % at -50 ∘ C. However, there is a strong reduction of the saturation vapor pressure of each oxidation state as the temperature is reduced. Overall, the reduction in volatility with temperature leads to an increase in the nucleation rates by up to 3 orders of magnitude at -50 ∘ C compared with 25 ∘ C. In addition, the enhancement of the nucleation rates by ions decreases with decreasing temperature, since the neutral molecular clusters have increased stability against evaporation. The resulting data quantify how the interplay between the temperature-dependent oxidation pathways and the associated vapor pressures affect biogenic NPF at the molecular level. Our measurements, therefore, improve our understanding of pure biogenic NPF for a wide range of tropospheric temperatures and precursor concentrations. [ABSTRACT FROM AUTHOR]

Background: The objective of this study was to analyze prognostic factors and risk stratification in patients with pulmonary arterial hypertension (PAH) and comorbidities.Methods: Patients with invasively diagnosed PAH were included in the analysis. Comorbidities were clinically diagnosed as proposed in the 6th World Symposium of pulmonary hypertension. Uni- and multivariate analysis were employed for identification of factors predicting survival and time to first clinical worsening (TTCW). Risk stratification was based on parameters from ESC/ERS-guidelines 2015.Results: In total 142 patients were enrolled in the study, 90 of them were diagnosed as PAH without and 52 with comorbidities. All patients received targeted PAH therapy and were followed for 3.3 ± 2.4 years. In PAH patients without comorbidities survival and TTCW were significantly associated with reduced 6-min walking distance (6MWD), elevated N-terminal pro brain natriuretic peptide (NT-proBNP), WHO-functional class (WHO-FC) and right atrial (RA) area. In the multivariate analysis, 6MWD was an independent predictor for survival (p = 0.002) and WHO-FC for TTCW (p = 0.001). In patients with PAH and comorbidities these parameters had no significant association with survival and TTCW. Average risk score was significantly associated with survival (p = 0.001) and TTCW (p = 0.013) in PAH but not in PAH with comorbidities (both p > 0.05; figure 1).Conclusion: Risk stratification based on ESC/ERS-guidelines could only be confirmed in patients without comorbidities, but not in patients with PAH and comorbidities. The data of this study suggest, that a different risk stratification needs to be applied to PAH patients with comorbidities. Further studies are needed to confirm these results.Trial Registration: Not applicable, retrospective registry. [ABSTRACT FROM AUTHOR]

Nucleation of atmospheric vapors produces more than half of global cloud condensation nuclei and so has an important influence on climate. Recent studies show that monoterpene (C10H16) oxidation yields highly-oxygenated products that can nucleate with or without sulfuric acid. Monoterpenes are emitted mainly by trees, frequently together with isoprene (C5H8), which has the highest global emission of all organic vapors. Previous studies have shown that isoprene suppresses new-particle formation from monoterpenes, but the cause of this suppression is under debate. Here, in experiments performed under atmospheric conditions in the CERN CLOUD chamber, we show that isoprene reduces the yield of highly-oxygenated dimers with 19 or 20 carbon atoms – which drive particle nucleation and early growth – while increasing the production of dimers with 14 or 15 carbon atoms. The dimers (termed C20 and C15, respectively) are produced by termination reactions between pairs of peroxy radicals (RO2·) arising from monoterpenes or isoprene. Compared with pure monoterpene conditions, isoprene reduces nucleation rates at 1.7 nm (depending on the isoprene/monoterpene ratio) and approximately halves particle growth rates between 1.3 and 3.2 nm. However, above 3.2 nm, C15 dimers contribute to secondary organic aerosol and the growth rates are unaffected by isoprene. We further show that increased hydroxyl radical (OH·) reduces particle formation in our chemical system rather than enhances it as previously proposed, since it increases isoprene derived RO2· radicals that reduce C20 formation. RO2· termination emerges as the critical step that determines the HOM distribution and the corresponding nucleation capability. Species that reduce the C20 yield, such as NO, HO2 and as we show isoprene, can thus effectively reduce biogenic nucleation and early growth. Therefore the formation rate of organic aerosol in a particular region of the atmosphere under study will vary according to the precise ambient conditions. [ABSTRACT FROM AUTHOR]

Highly-oxygenated organic molecules (HOMs) contribute substantially to the formation and growth of atmospheric aerosol particles, which affect air quality, human health and Earth's climate. HOMs are formed by rapid, gas-phase autoxidation of volatile organic compounds (VOCs) such as α-pinene, the most abundant monoterpene in the atmosphere. Due to their abundance and low volatility, HOMs can play an important role for new-particle formation (NPF) and the early growth of atmospheric aerosols, even without any further assistance of other low-volatility compounds such as sulfuric acid. Both the autoxidation reaction forming HOMs and their new-particle formation rates are expected to be strongly dependent on temperature. However, experimental data on both effects are limited. Dedicated experiments were performed at the CLOUD (Cosmics Leaving OUtdoor Droplets) chamber at CERN to address this question. In this study, we show that a decrease in temperature (from +25 to -50 °C) results in a reduced HOM yield and reduced oxidation state of the products, whereas the new-particle formation rates (J1.7 nm) increase substantially. Measurements with two different chemical ionization mass spectrometers (using nitrate and protonated water as reagent ion, respectively) provide the molecular composition of the gaseous oxidation products and a 2-dimensional volatility basis set model (2D-VBS) provides their volatility distribution. The HOM yield decreases with temperature from 6.2 % at 25 °C to 0.7 % at -50 °C. However, there is a strong reduction of the saturation vapor pressure of each oxidation state as the temperature is reduced. Overall, the reduction in volatility with temperature leads to an increase in the nucleation rates by up to three orders of magnitude at -50 °C compared with 25 °C. In addition, the enhancement of the nucleation rates by ions decreases with decreasing temperature, since the neutral molecular clusters have increased stability against evaporation. The resulting data quantify how the interplay between the temperature-dependent oxidation pathways and the associated vapor pressures affect biogenic new-particle formation at the molecular level. Our measurements therefore improve our understanding of pure biogenic new-particle formation for a wide range of tropospheric temperatures and precursor concentrations. [ABSTRACT FROM AUTHOR]

Here we present an alternative approach of an atmospheric pressure interface (APi) time-of-flight mass spectrometer for the study of atmospheric ions and cluster ions, the so-called ioniAPi-TOF. The novelty is the use of two hexapoles as ion guides within the APi. In our case, hexapoles can accept and transmit a broad mass range enabling the study of small precursor ions and heavy cluster ions at the same time. Weakly bound cluster ions can easily de-cluster during ion transfer depending on the voltages applied to the ion transfer optics. With the example system of H3O+(H2O)n=0-3 , we estimate that cluster ions with higher binding energies than 17 kcal mol -1 can be transferred through the APi without significant fragmentation, which is considerably lower than about 25 kcal mol -1 estimated from the literature for APi-TOFs with quadrupole ion guides. In contrast to the low-fragmenting ion transfer, the hexapoles can be set to a high-fragmenting declustering mode for collision-induced dissociation (CID) experiments as well. The ion transmission efficiency over a broad mass range was determined to be on the order of 1 %, which is comparable to existing instrumentation. From measurements under well-controlled conditions during the CLOUD experiment, we demonstrate the instrument's performance and present results from an inter-comparison with a quadrupole-based APi-TOF. [ABSTRACT FROM AUTHOR]

Salts of the weakly coordinating anions [Ga(OTeF5)4]− as well as [Ga(Et)(OTeF5)3]− and the neutral Ga2(Et)3(OTeF5)3 were synthesized and characterized by spectroscopic methods and single‐crystal X‐ray diffraction. Ga2(Et)3(OTeF5)3 was formed by treating GaEt3 with pentafluoroorthotelluric acid (HOTeF5) and reacted with PPh4Cl and CPh3Cl to [PPh4][Ga(Et)(OTeF5)3] and [CPh3][Ga(Et)(OTeF5)3]. In contrast, Ag[Ga(OTeF5)4] was prepared from AgOTeF5 and GaCl3 and was used as a versatile starting material for further reactions. Starting with Ag[Ga(OTeF5)4] the substrates [PPh4][Ga(OTeF5)4] and [CPh3][Ga(OTeF5)4] were formed from PPh4Cl and CPh3Cl. [ABSTRACT FROM AUTHOR]

Here we present an alternative approach of an Atmospheric-Pressure interface (APi) Time-Of-Flight mass spectrometer for the study of atmospheric ions and cluster ions, the so-called ioniAPi-TOF. The novelty is the use of two hexapoles as ion guides within the APi. As we will show, hexapoles can accept and transmit a broad mass range enabling the study of small precursor ions and heavy cluster ions at the same time. Weakly bound cluster ions can easily de-cluster during ion transfer depending on the voltages applied to the ion transfer optics. With the example system of H3O+(H2O)n=0-3, we estimate that cluster ions with higher binding energies than 17kcal/mol can be transferred through the APi without significant fragmentation, which is considerably lower than about 25kcal/mol estimated from the literature for APi-TOFs with quadrupole ion guides. In contrast to the low fragmenting ion transfer, the hexapoles can be set to a high fragmenting declustering mode for collision-induced dissociation (CID) experiments as well. The ion transmission efficiency over a broad mass range was determined to be in the order of 1%, which is comparable to existing instrumentation. From measurements under well-controlled conditions during the CLOUD experiment, we demonstrate the instrument's performance and present results from an inter-comparison with a quadrupole based APi-TOF. [ABSTRACT FROM AUTHOR]

Nucleation and growth of aerosol particles from atmospheric vapors constitutes a major source of global cloud condensation nuclei (CCN). The fraction of newly formed particles that reaches CCN sizes is highly sensitive to particle growth rates, especially for particle sizes <10 nm, where coagulation losses to larger aerosol particles are greatest. Recent results show that some oxidation products from biogenic volatile organic compounds are major contributors to particle formation and initial growth. However, whether oxidized organics contribute to particle growth over the broad span of tropospheric temperatures remains an open question, and quantitative mass balance for organic growth has yet to be demonstrated at any temperature. Here, in experiments performed under atmospheric conditions in the Cosmics Leaving Outdoor Droplets (CLOUD) chamber at the European Organization for Nuclear Research (CERN), we show that rapid growth of organic particles occurs over the range from -25 °C to 25 °C. The lower extent of autoxidation at reduced temperatures is compensated by the decreased volatility of all oxidized molecules. This is confirmed by particle-phase composition measurements, showing enhanced uptake of relatively less oxygenated products at cold temperatures. We can reproduce the measured growth rates using an aerosol growth model based entirely on the experimentally measured gas-phase spectra of oxidized organic molecules obtained from two complementary mass spectrometers. We show that the growth rates are sensitive to particle curvature, explaining widespread atmospheric observations that particle growth rates increase in the singledigit-nanometer size range. Our results demonstrate that organic vapors can contribute to particle growth over a wide range of tropospheric temperatures from molecular cluster sizes onward. [ABSTRACT FROM AUTHOR]

Summary The integration of visual stimuli and motor feedback is critical for successful visually guided navigation. These signals have been shown to shape neuronal activity in the primary visual cortex (V1), in an experience-dependent manner. Here, we examined whether visual, reward, and self-motion-related inputs are integrated in order to encode behaviorally relevant locations in V1 neurons. Using a behavioral task in a virtual environment, we monitored layer 2/3 neuronal activity as mice learned to locate a reward along a linear corridor. With learning, a subset of neurons became responsive to the expected reward location. Without a visual cue to the reward location, both behavioral and neuronal responses relied on self-motion-derived estimations. However, when visual cues were available, both neuronal and behavioral responses were driven by visual information. Therefore, a population of V1 neurons encode behaviorally relevant spatial locations, based on either visual cues or on self-motion feedback when visual cues are absent. Graphical Abstract Highlights • Most V1 L2/3 neurons show task-related activity after learning a rewarded task • A subset of neurons became responsive to an expected reward location • Without visual cues, behavioral and neuronal responses rely on self-motion signals • With visual cues, behavioral and neuronal responses rely on visual information Pakan et al. show that spatial locations that are relevant for a behavioral task are represented in the primary visual cortex. Both neuronal and behavioral responses to an expected reward location primarily rely on visual information. Without visual landmarks, both neuronal and behavioral responses are driven by self-motion derived information. [ABSTRACT FROM AUTHOR]

During nucleation studies from pure isoprene oxidation in the CLOUD chamber at the European Organization for Nuclear Research (CERN) we observed unexpected ion signals at m=zD137.133 (C10H+17) and m=zD81.070 (C6H+9) with the recently developed proton-transfer-reaction time-of-flight (PTR3-TOF) mass spectrometer instrument. The mass-to-charge ratios of these ion signals typically correspond to protonated monoterpenes and their main fragment. We identified two origins of these signals: first secondary association reactions of protonated isoprene with isoprene within the PTR3-TOF reaction chamber and secondly T4C2U cycloaddition (Diels-Alder) of isoprene inside the gas bottle which presumably forms the favored monoterpenes limonene and sylvestrene, as known from literature. Under our PTR3-TOF conditions used in 2016 an amount (relative to isoprene) of 2% is formed within the PTR3-TOF reaction chamber and 1% is already present in the gas bottle. The presence of unwanted cycloaddition products in the CLOUD chamber impacts the nucleation studies by creating ozonolysis products as the corresponding monoterpenes and is responsible for the majority of the observed highly oxygenated organic molecules (HOMs), which in turn leads to a significant overestimation of both the nucleation rate and the growth rate. In order to study new particle formation (NPF) from pure isoprene oxidation under relevant atmospheric conditions, it is important to improve and assure the quality and purity of the precursor isoprene. This was successfully achieved by cryogenically trapping lowervolatility compounds such as monoterpenes before isoprene was introduced into the CLOUD chamber. [ABSTRACT FROM AUTHOR]

Nowadays every provider of critical infrastructure is obliged to use alarm systems - mainly simple surveillance CCTV cameras - to increase security and safety of those objects. Yet such systems have proven ineffectual in preventing security disrupting situations, such as identity theft, as the most they can do is offer evidence to identify perpetrators of criminal acts once they have occurred. To use them for crime prevention, specially trained personnel need to monitor all screens constantly on the look-out for potentially dangerous activity - which is financially and time-consuming and prone to mistakes. This study aims at developing semi-automatic video surveillance technologies, which are able to detect events of changed behaviour of employees in relation to their standard behaviour - this means for example cases of identity theft, possible blackmail of a person, or safety disrupting cases - an employee might be sick or under influence of drugs what may lead to potentially dangerous acts. [ABSTRACT FROM AUTHOR]

Abstract: Hydrocarbons are emitted into the Earth's atmosphere in very large quantities by human and biogenic activities. Their atmospheric oxidation processes almost exclusively yield RO2 radicals as reactive intermediates whose atmospheric fate is not yet fully unraveled. Herein, we show that gas‐phase reactions of two RO2 radicals produce accretion products composed of the carbon backbone of both reactants. The rates for accretion product formation are very high for RO2 radicals bearing functional groups, competing with those of the corresponding reactions with NO and HO2. This pathway, which has not yet been considered in the modelling of atmospheric processes, can be important, or even dominant, for the fate of RO2 radicals in all areas of the atmosphere. Moreover, the vapor pressure of the formed accretion products can be remarkably low, characterizing them as an effective source for the secondary organic aerosol. [ABSTRACT FROM AUTHOR]

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Spatial learning requires estimates of location that may be obtained by path integration or from positional cues. Grid and other spatial firing patterns of neurons in the superficial medial entorhinal cortex (MEC) suggest roles in behavioral estimation of location. However, distinguishing the contributions of path integration and cue-based signals to spatial behaviors is challenging and the roles of identified MEC neurons are unclear. We use virtual reality to dissociate linear path integration from other strategies for behavioral estimation of location. We find that mice learn to path integrate using motor-related self-motion signals, with accuracy that decreases steeply as a function of distance. We show that inactivation of stellate cells in superficial MEC impairs spatial learning in virtual reality and in a real world object location recognition task. Our results quantify contributions of path integration to behavior and corroborate key predictions of models in which stellate cells contribute to location estimation. [ABSTRACT FROM AUTHOR]

During nucleation studies from pure isoprene oxidation in the CLOUD chamber at CERN we observed unexpected ion signals at m/z = 137.133 (C10H17+) and m/z = 81.070 (C6H9+) with the recently developed proton transfer reaction time-of-flight mass spectrometer (PTR3-TOF) instrument. The mass-to-charge ratios of these ion signals typically correspond to protonated monoterpenes and their main fragment. We identified two origins of these signals: First secondary association reactions of protonated isoprene with isoprene within the PTR3 reaction chamber and secondly [4+2] cycloaddition (Diels-Alder) of isoprene inside the gas bottle which presumably forms the favoured monoterpenes limonene and sylvestrene, as known from literature. Under our PTR3 conditions used in 2016 an amount (relative to isoprene) of 2 % is formed within the PTR3 reaction chamber and 1 % is already present in the gas bottle. The presence of unwanted cycloaddition products in the CLOUD chamber impacts the nucleation studies by creating ozonolysis products as corresponding monoterpenes, and is responsible for the majority of the observed highly oxygenated organic molecules (HOMs). In order to study NPF from pure isoprene oxidation under atmospheric relevant conditions, it is important to improve and assure the quality and purity of the precursor isoprene. This was successfully achieved by cryogenically trapping lower volatility compounds such as monoterpenes before isoprene was introduced into the CLOUD chamber. [ABSTRACT FROM AUTHOR]

It was recently shown by the CERN CLOUD experiment that biogenic highly oxygenated molecules (HOMs) form particles under atmospheric conditions in the absence of sulfuric acid, where ions enhance the nucleation rate by 1-2 orders of magnitude. The biogenic HOMs were produced from ozonolysis of α-pinene at 5 °C. Here we extend this study to compare the molecular composition of positive and negative HOM clusters measured with atmospheric pressure interface time-of-flight mass spectrometers (APi-TOFs), at three different temperatures (25, 5 and -25 °C). Most negative HOM clusters include a nitrate (NO-3 ) ion, and the spectra are similar to those seen in the nighttime boreal forest. On the other hand, most positive HOM clusters include an ammonium (NHC+ 4 ) ion, and the spectra are characterized by mass bands that differ in their molecular weight by ~20 C atoms, corresponding to HOM dimers. At lower temperatures the average oxygen to carbon (O : C) ratio of the HOM clusters decreases for both polarities, reflecting an overall reduction of HOM formation with decreasing temperature. This indicates a decrease in the rate of autoxidation with temperature due to a rather high activation energy as has previously been determined by quantum chemical calculations. Furthermore, at the lowest temperature (-25 °C), the presence of C30 clusters shows that HOM monomers start to contribute to the nucleation of positive clusters. These experimental findings are supported by quantum chemical calculations of the binding energies of representative neutral and charged clusters. [ABSTRACT FROM AUTHOR]