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We report the site-selective acetylation of partially protected monosaccharides using immobilized oligopeptide catalysts, which are readily accessible via solid-phase peptide synthesis. The catalysts are able to invert the intrinsic selectivity, which was determined using N-methylimidazole, for a variety of pyranosides. We demonstrate that the catalysts are stable for multiple reaction cycles and can be easily reused after separation from the reaction solution. The catalysts can also be used in flow without loss of reactivity and selectivity.

When demands exceed capacities, suppliers allocate available supply to customers based on customer importance and advance demand information. The accuracy of advance demand information interacts with the length of customer order lead times and influences overall customer service levels. In this paper, we analyse industrial contract portfolios with customer-specific terms in order to derive insights for contract portfolio management and the design of demand fulfilment processes. For this purpose, we develop a framework for analysis of contract portfolios capturing the dynamics of industrial planning processes. The framework is applied to portfolios from the semiconductor sector. Our numerical analysis shows that, in order to improve service levels, demand fulfilment processes and contract portfolio management must especially take into account the length of order lead times and the accuracy of advance demand information. Even though suppliers often prefer long order lead times, our analysis shows that demand fulfilment performance is not primarily determined by the absolute length of the order lead times but by the presence of a negative correlation with the accuracy of advance demand information in the entire contract portfolio. Consequently, these factors require increased attention in the management of contract portfolios and in the negotiation of individual contracts.

We present a novel concept for the in situ control of site-selectivity of catalytic acetylations of partially protected sugars using light as external stimulus and oligopeptide catalysts equipped with an azobenzene moiety. The isomerizable azobenzene-peptide backbone defines the size and shape of the catalytic pocket, while the π-methyl-l-histidine (Pmh) moiety transfers the electrophile. Photoisomerization of the

Herein, we report the oligopeptide-catalyzed site-selective acylation of partially protected monosaccharides. We identified catalysts that invert site-selectivity compared to N-methylimidazole, whi...

BACKGROUND: Recent advances in sequencing have facilitated large-scale analyses of the metagenomic composition of different samples, including the environmental microbiome of air, water, and soil, as well as the microbiome of living humans and other animals. Analyses of the microbiome of ancient human samples may provide insights into human health and disease, as well as pathogen evolution, but the field is still in its very early stages and considered highly challenging. - RESULTS: The metagenomic and pathogen content of Egyptian mummified individuals from different time periods was investigated via genetic analysis of the microbial composition of various tissues. The analysis of the dental calculus’ microbiome identified Red Complex bacteria, which are correlated with periodontal diseases. From bone and soft tissue, genomes of two ancient pathogens, a 2200-year-old Mycobacterium leprae strain and a 2000-year-old human hepatitis B virus, were successfully reconstructed. - CONCLUSIONS: The results show the reliability of metagenomic studies on Egyptian mummified individuals and the potential to use them as a source for the extraction of ancient pathogen DNA. Background Results - Sample information and dating - General metagenomic assessment - Mycobacterium leprae (individual Abusir1630) - Hepatitis B virus (individual Abusir1543) - Oral microbiome assessment Discussion Conclusions Methods - Sample extraction and radiocarbon dating - Sample extraction and library preparation - Metagenomic screening - Authentication of ancient DNA - Content of endogenous DNA (SourceTracker2) - Data processing of sample Abusir1630b (M. leprae) -- Read processing, mapping, and variant calling -- SNP typing -- Anthropological analysis -- Phylogeny -- Beast analysis -- Temporal signal - Data processing individual Abusir1543 (hepatitis B virus) -- Read processing, mapping, and variant calling -- Phylogeny -- Recombination analysis -- Beast analysis -- Temporal signal

Why should a person be liable for circumstances that are beyond his control? The work by Alexander Seitz focuses on this question. Starting from an introduction to the concept of chance and the dogmatic foundations of the principle of fault, he analyses the provisions of this form of liability in the German Civil Code. This analysis reveals the diversity of this form of liability. The author examines the dogmatic differences between the liability for Acts of God and the liability for random damages in the context of the principles of causality and fault. Furthermore, the author assesses the effectiveness of the establishment of a liability for Acts of God as an instrument of the legislator to control behaviour.

This paper presents an extension of Nitsche’s method to finite deformation thermomechanical contact problems including friction. The mechanical contact constraints, i.e. non-penetration and Coulomb’s law of friction, are introduced into the weak form using a stabilizing consistent penalty term. The required penalty parameter is estimated with local generalized eigenvalue problems, based on which an additional harmonic weighting of the boundary traction is introduced. A special focus is put on the enforcement of the thermal constraints at the contact interface, namely heat conduction and frictional heating. Two numerical methods to introduce these effects are presented, a substitution method as well as a Nitsche-type approach. Numerical experiments range from two-dimensional frictionless thermo-elastic problems demonstrating optimal convergence rates to three-dimensional thermo-elasto-plastic problems including friction.

The focus of this contribution is the numerical treatment of interface-coupled problems concerned with the interaction of impermeable or permeable elastic bodies 1 and the surrounding fluid including the contact interaction of deformable bodies. The presented formulation is based on the approach for fluid-structural-contact interaction in [1] , and consistently takes into account fluid-filled poroelastic bodies including the conditions of solid-poroelastic contact, poroelastic-poroelastic contact, and viscous flow poroelasticity interaction. The interface conditions in normal and tangential orientation to formulate this type of coupled problem, based on the fundamental balances of mass and linear momentum, the no-slip condition, the Beavers Joseph condition, and the conditions for frictionless contact on the respective interfaces, are discussed. A continuous transition of the different types of tangential conditions is enabled by application of the general Navier condition with varying slip length. The fluid stress in the zone of closed contact, which is essential for the lift-off behavior of contacting bodies, is obtained by an extension approach augmented by the porous fluid state to ensure continuity and physical accuracy. To account for topological changes of the fluid domain, the numerical approach utilizes non-interface fitted computational meshes for the fluid domain enabled by the Cut Finite Element Method. All interface conditions are incorporated in a weak sense by Nitsche-based approaches. Different numerical examples analyze the proper contacting and lift-off behavior for contact between the different pairs of impermeable and permeable bodies and demonstrate the robustness for more challenging configurations, which include topological changes of the fluid domain, large contacting areas, and 3D configurations.

Alzheimer's disease (AD) involves changes in both lipid and RNA metabolism, but it remained unknown if these differences associate with AD's cognition and/or post-mortem neuropathology indices. Here, we report RNA-sequencing evidence of inter-related associations between lipid processing, cognition level, and AD neuropathology. In two unrelated cohorts, we identified pathway-enriched facilitation of lipid processing and alternative splicing genes, including the neuronal-enriched NOVA1 and hnRNPA1. Specifically, this association emerged in temporal lobe tissue samples from donors where postmortem evidence demonstrated AD neuropathology, but who presented normal cognition proximate to death. The observed changes further associated with modified ATP synthesis and mitochondrial transcripts, indicating metabolic relevance; accordingly, mass-spectrometry-derived lipidomic profiles distinguished between individuals with and without cognitive impairment prior to death. In spite of the limited group sizes, tissues from persons with both cognitive impairment and AD pathology showed elevation in several drug-targeted genes of other brain, vascular and autoimmune disorders, accompanied by pathology-related increases in distinct lipid processing transcripts, and in the RNA metabolism genes hnRNPH2, TARDBP, CLP1 and EWSR1. To further detect 3′-polyadenylation variants, we employed multiple cDNA primer pairs. This identified variants that showed limited differences in scope and length between the tested cohorts, yet enabled superior clustering of demented and non-demented AD brains versus controls compared to total mRNA expression values. Our findings indicate inter-related cognition-associated differences in AD's lipid processing, alternative splicing and 3′-polyadenylation, calling for pursuing the underlying psychological and therapeutics implications., Highlights • RNA transcripts differ between brains from Alzheimer's patients with or without dementia. • In non-demented patients with pathology, brain neurons show facilitated RNA and lipid processing. • Cognition-related differences included brain, vascular and autoimmune disease-related genes. • Polyadenylation changes classify patients better than transcript expression levels.

High demand uncertainties, long production lead times, and short product life cycles cause high risks for supply chain planning in the semiconductor industry. These affect all industries producing goods containing semiconductors. We present a robust supply chain planning framework for revenue management that consists of stable and flexible solutions for demand steering and dynamic pricing, extending current industry practice in several aspects. We introduce the concept of availabilities and capabilities, as well as various planning processes and process enablers. Based on our framework, we also highlight directions for future research.

Transformations of 2-formylbenzoic acid provide direct access to a series of heterocyclic organic compounds such as phthalides and isoindolinones. Here, we use (+)-cinchonine as a catalyst in conjunction with nonafluoro-tert-butanol as a hydrogen-bond donor to afford enantiomerically enriched acylated 3-hydroxyphthalides with up to 99% yield and 90% ee through dynamic kinetic resolution. Moreover, various 3-alkoxyphthalides as well as 2-alkyl-3-hydroxy-1-isoindolinones were synthesized from 2-formylbenzoic acid.

We propose a data-driven allocation planning approach, which is designed for use in advanced planning systems as they are widely used in industrial environments. The approach exploits increasingly available data on individual customers and products by allocating supply on a highly granular level at high planning frequencies. It counteracts rationing gaming by customers, which we assume to be the reason for demand forecast biases. We create an incentive for truthful forecasting by not only allocating supply based on customer profitability but also based on forecast bias. In the long term, this approach gives access to a profit potential and an on-time service level increase. In the short term, however, setting such an incentive does not only have a positive impact on service levels but also leads to a decline in profits. Our methodology quantifies this trade off providing decision support for determining the extent to which the forecast bias should affect the allocation. In a numerical study based on the semiconductor industry, we demonstrate that the approach has a large long-term profit potential while having limited effect on short-term profits for significant service level incentives. The analysis further shows that the allocation efficiency increases with the granularity level and the predictive quality of the available data.