3D Micro-PIXE at atmospheric pressure: A new tool for the investigation of art and archaeological objects

The paper describes a novel experiment characterized by the development of a confocal geometry in an external Micro-PIXE set-up. The position of X-ray optics in front of the X-ray detector and its proper alignment with respect to the proton micro-beam focus provided the possibility of carrying out 3D Micro-PIXE analysis. As a first application, depth intensity profiles of the major elements that compose the patina layer of a quaternary bronze alloy were measured. A simulation approach of the 3D Micro-PIXE data deduced elemental concentration profiles in rather good agreement with corresponding results obtained by electron probe micro-analysis from a cross-sectioned patina sample. With its non-destructive and depth-resolving properties, as well as its feasibility in atmospheric pressure, 3D Micro-PIXE seems especially suited for investigations in the field of cultural heritage.     

A Study of Surface Deformation during Wire‐Rod Rolling of High Speed Steels using Experimental and Computational Techniques

The evolution of surface defects during shape rolling of high‐speed steel billets is studied using longitudinal surface defects prepared by machining and welding. The reduction of the defects during rolling in a production mill is compared to the total area reduction of the billets. Samples are collected after pass 4, 6, 8, 14, 19 and the final pass, 28, representing the finished 5.5mm wire. By inspecting the cross sections, the rotation of the billets from pass to pass is evaluated. Results from FE simulations on solid billets are compared to the experimental results. Generally, simulations predict less reduction than observed experimentally. In most cases cracks reduce most effectively followed by carbon steel welds and stainless steel welds.     

Cathodic reduction of acids in dimethylformamide on platinum

A linear correlation was shown to exist between the acidity and the cyclic voltammetric half-potential of the reduction of acids in DMF for carboxylic and N-acids in the pK_a range of 6-16. Chlorophenols are reduced at slightly lower potentials giving a separate parallel line. Applying the obtained equation and employing the same method to literature data in DMSO, the pK_a values for conjugate aids of DMF and DMSO can be calculated, showing DMSO·H⁺ to be more acidic (pK_a = 2.9) than DMF·H⁺ (pK_a = 5.7). The analysis of cyclovoltammetric data demonstrated that a CE mechanism operates in the reduction of strong acids, including the conjugate acid of DMF. Weaker acids are reduced by direct discharge or a mixed mechanism.     

Predictive value of biological markers in etiopathogenesis of juvenile diabetes--reviewing the role of insulin antibodies

The lack of complete concordance for diseases in monozygotic twins prevents application of genetic markers for a thorough identification of the subjects who will develop the type I diabetes. Furthermore, the impact of the environmental factors precipitating beta cells destruction in genetically sensitive subjects has not been completely enlightened yet. The identification of high risk markers for the development of diabetes is aimed at detection of the early immune response activation markers. Islet cell antibodies are the most valuable markers, whose presence can be discovered even up to 7-8 years prior to the onset of symptoms. They are found in 50-80% of the newly discovered insulin-dependent diabetics. Their prevalence in the general population is 0.5-2%. These are commonly concomitant with insulin antibodies, found in 20-40% of the newly discovered diabetics, as reported in the literature. In our circumstances it was possible to determine the insulin antibodies only. We have concluded that they appear in 13.6% of children with a newly discovered diabetes, presenting a significant marker for predicting the course of the disease.     

An approach to automatic display layout using combinatorial optimization algorithms

The introduction of automatic display layout (ADL), i.e. the automatic placing and sizing of windows in a window-oriented graphical user interface, is a major contribution towards an improved user interface. Our approach to ADL is to treat this problem as a combinatorial optimization problem. In this article we describe the concepts we used for implementing an experimental system which controls the computer screen contents and its layout. We give two examples of different standard applications into which we included ADL successfully, namely hypertext for a window layout problem and graph-browser for a hierarchical graph layout problem within a particular window. The results show that automatic (and tool independent) display layout will be possible in the near future even in an interactive environment.     

Context relevance assessment and exploitation in mobile recommender systems

In order to generate relevant recommendations, a context-aware recommender system (CARS) not only makes use of user preferences, but also exploits information about the specific contextual situation in which the recommended item will be consumed. For instance, when recommending a holiday destination, a CARS could take into account whether the trip will happen in summer or winter. It is unclear, however, which contextual factors are important and to which degree they influence user ratings. A large amount of data and complex context-aware predictive models must be exploited to understand these relationships. In this paper, we take a new approach for assessing and modeling the relationship between contextual factors and item ratings. Rather than using the traditional approach to data collection, where recommendations are rated with respect to real situations as participants go about their lives as normal, we simulate contextual situations to more easily capture data regarding how the context influences user ratings. To this end, we have designed a methodology whereby users are asked to judge whether a contextual factor (e.g., season) influences the rating given a certain contextual condition (e.g., season is summer). Based on the analyses of these data, we built a context-aware mobile recommender system that utilizes the contextual factors shown to be important. In a subsequent user evaluation, this system was preferred to a similar variant that did not exploit contextual information.     

Improving sub-pixel accuracy for long range stereo

Dense stereo algorithms are able to estimate disparities at all pixels including untextured regions. Typically these disparities are evaluated at integer disparity steps. A subsequent sub-pixel interpolation often fails to propagate smoothness constraints on a sub-pixel level.We propose to increase the sub-pixel accuracy in low-textured regions in four possible ways: First, we present an analysis that shows the benefit of evaluating the disparity space at fractional disparities. Second, we introduce a new disparity smoothing algorithm that preserves depth discontinuities and enforces smoothness on a sub-pixel level. Third, we present a novel stereo constraint (gravitational constraint) that assumes sorted disparity values in vertical direction and guides global algorithms to reduce false matches, especially in low-textured regions. Finally, we show how image sequence analysis improves stereo accuracy without explicitly performing tracking. Our goal in this work is to obtain an accurate 3D reconstruction. Large-scale 3D reconstruction will benefit heavily from these sub-pixel refinements.Results based on semi-global matching, obtained with the above mentioned algorithmic extensions are shown for the Middlebury stereo ground truth data sets. The presented improvements, called ImproveSubPix, turn out to be one of the top-performing algorithms when evaluating the set on a sub-pixel level while being computationally efficient. Additional results are presented for urban scenes. The four improvements are independent of the underlying type of stereo algorithm.     

Refining Genotypes and Phenotypes in KCNA2-Related Neurological Disorders

Pathogenic variants in KCNA2, encoding for the voltage-gated potassium channel K_v1.2, have been identified as the cause for an evolving spectrum of neurological disorders. Affected individuals show early-onset developmental and epileptic encephalopathy, intellectual disability, and movement disorders resulting from cerebellar dysfunction. In addition, individuals with a milder course of epilepsy, complicated hereditary spastic paraplegia, and episodic ataxia have been reported. By analyzing phenotypic, functional, and genetic data from published reports and novel cases, we refine and further delineate phenotypic as well as functional subgroups of KCNA2-associated disorders. Carriers of variants, leading to complex and mixed channel dysfunction that are associated with a gain- and loss-of-potassium conductance, more often show early developmental abnormalities and an earlier onset of epilepsy compared to individuals with variants resulting in loss- or gain-of-function. We describe seven additional individuals harboring three known and the novel KCNA2 variants p.(Pro407Ala) and p.(Tyr417Cys). The location of variants reported here highlights the importance of the proline(405)–valine(406)–proline(407) (PVP) motif in transmembrane domain S6 as a mutational hotspot. A novel case of self-limited infantile seizures suggests a continuous clinical spectrum of KCNA2-related disorders. Our study provides further insights into the clinical spectrum, genotype–phenotype correlation, variability, and predicted functional impact of KCNA2 variants.     

Structure-Activity Relationships of Benzamides and Isoindolines Designed as SARS-CoV Protease Inhibitors Effective against SARS-CoV-2

Inhibition of coronavirus (CoV)-encoded papain-like cysteine proteases (PL^pro) represents an attractive strategy to treat infections by these important human pathogens. Herein we report on structure-activity relationships (SAR) of the noncovalent active-site directed inhibitor (R)-5-amino-2-methyl-N-(1-(naphthalen-1-yl)ethyl) benzamide ( 2 b ), which is known to bind into the S3 and S4 pockets of the SARS-CoV PL^pro. Moreover, we report the discovery of isoindolines as a new class of potent PL^pro inhibitors. The studies also provide a deeper understanding of the binding modes of this inhibitor class. Importantly, the inhibitors were also confirmed to inhibit SARS-CoV-2 replication in cell culture suggesting that, due to the high structural similarities of the target proteases, inhibitors identified against SARS-CoV PL^pro are valuable starting points for the development of new pan-coronaviral inhibitors.     

Continuous size fractionation of magnetic nanoparticles by using simulated moving bed chromatography

The size fractionation of magnetic nanoparticles is a technical problem, which until today can only be solved with great effort. Nevertheless, there is an important demand for nanoparticles with sharp size distributions, for example for medical technology or sensor technology. Using magnetic chromatography, we show a promising method for fractionation of magnetic nanoparticles with respect to their size and/or magnetic properties. This was achieved by passing magnetic nanoparticles through a packed bed of fine steel spheres with which they interact magnetically because single domain ferro-/ferrimagnetic nanoparticles show a spontaneous magnetization. Since the strength of this interaction is related to particle size, the principle is suitable for size fractionation. This concept was transferred into a continuous process in this work using a so-called simulated moving bed chromatography. Applying a suspension of magnetic nanoparticles within a size range from 20 to 120 nm, the process showed a separation sharpness of up to 0.52 with recovery rates of 100%. The continuous feed stream of magnetic nanoparticles could be fractionated with a space-time-yield of up to 5 mg/(L∙min). Due to the easy scalability of continuous chromatography, the process is a promising approach for the efficient fractionation of industrially relevant amounts of magnetic nanoparticles.