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Recent progress in information technologies provides sellers with detailed knowledge about consumers' preferences, approaching perfect price discrimination in the limit. We construct a model where consumers with less strategic sophistication than the seller's pricing algorithm face a trade-off when buying. They choose between a direct, transaction cost-free sales channel and a privacy-protecting, but costly, anonymous channel. We show that the anonymous channel is used even in the absence of an explicit taste for privacy if consumers are not too strategically sophisticated. This provides a micro-foundation for consumers' privacy choices. Some consumers benefit but others suffer from their anonymization.

Hybrid sequences comprising a peptide with several Cys residues and an aromatic foldamer helix with several chloroacetamide functions at its surface were synthesized. Such products may in principle form numerous macromulticyclic thioether products by intramolecularly combining all Cys residues and all chloroacetamide functions. However, we show that the reactive sites on the structurally defined helix can be placed at such locations that the peptide selectively stitches itself to form a series of different macrocycles within mostly one preferred product. Reactions were monitored by HPLC and products with two, three or four macrocycles were identified using LC-MS and NMR. The series of selective macrocyclizations define a sort of reaction trail where reaction sites otherwise identical are involved successively because of their precise positioning in space. The trails can be predicted to a large extent based on structural considerations and the assumption that smaller macrocycles form faster.

Chemical science 12(33), 11004-11012 (2021). doi:10.1039/D1SC03640H, Macrocyclic peptides are an important class of bioactive substances. When inserting an aromatic foldamer segment in a macrocyclic peptide, the strong folding propensity of the former may influence the conformation and alter the properties of the latter. Such an insertion is relevant because some foldamer���peptide hybrids have recently been shown to be tolerated by the ribosome, prior to forming macrocycles, and can thus be produced using an in vitro translation system. We have investigated the interplay of peptide and foldamer conformations in such hybrid macrocycles. We show that foldamer helical folding always prevails and stands as a viable means to stretch, i.e. unfold, peptides in a solvent dependent manner. Conversely, the peptide systematically has a reciprocal influence and gives rise to strong foldamer helix handedness bias as well as foldamer helix stabilisation. The hybrid macrocycles also show resistance towards proteolytic degradation., Published by RSC, Cambridge

A helical aromatic foldamer was identified that undergoes tRNA acylation by a flexizyme and ribosomal peptide initiation with yields sufficiently high to perform an mRNA display selection of macrocyclic foldamer-peptide hybrids. A hybrid macrocyle binder to the C-lobe of the E6AP HECT domain was selected that showed highly converged peptide residues. A crystal structure and molecular dynamics simulations revealed that both the peptide and foldamer are helical in an intriguing reciprocal stapling fashion. The strong residue convergence could be rationalized based on their involvement in specific interactions. The foldamer stabilizes the peptide helix through stapling and through contacts with key residues. It appears to also contribute to protein binding by direct protein interactions. The results altogether highlight possible benefits in inserting an aromatic foldamer into a peptide macrocycle for the purpose of protein recognition.

We develop a dynamic resource extraction game that mimics the global multi-generation planning problem for climate change and fossil fuel extraction. We implement the game under different conditions in the laboratory. Compared to a ‘libertarian’ baseline condition, we find that policy interventions that provide a costly commitment device or reduce climate threshold uncertainty reduce resource extraction. We also study two conditions to assess the underlying social preferences and the viability of ecological dictatorship. Our results suggest that climate-change policies that focus on investments that lock the economy into carbon-free energy sources provide an important commitment device in the intertemporal cooperation problem.

Sequence-defined cationic lipo-oligomers are potent siRNA carriers, forming stable lipo-polyplexes based on both electrostatic and hydrophobic interactions and, after endocytosis and endosomal protonation, facilitating the delivery of siRNA into the cytosol. After completion of the nucleic acid delivery process, carriers should be readily biodegradable to ensure minimum accumulation of amphiphilic molecules that are harmful to lysosomes and other intracellular organelles. Endolysosomal enzymes may degrade a surplus of carrier molecules left over in lysosomes and thereby facilitate the generation and rapid excretion of cleavage products. By solid-phase supported synthesis, a library of sequence-defined lipo-oligomers was generated containing artificial and natural amino acids comprising precise enzymatic cleavage sites. Incorporating either short cleavable l-arginine sequences (RR), noncleavable d-arginine linkers (rr), or varieties of both tailored the degradability of lipo-oligomers, as demonstrated upon incubation with the endolysosomal protease cathepsin B. Cleavage products were identified by MALDI-TOF mass spectrometry. The effect of improved intracellular degradation on cell tolerability was studied by transfecting Huh7-eGFPLuc and DU145-eGFPLuc cells. Positioning of enzymatic cleavage sites between a lipophilic diacyl domain and an ionizable oligocationic siRNA binding unit enabled efficient enzymatic degradation of the carrier and reduced the lytic potential under lysosomal conditions. Highly degradable carriers containing at least one l-arginine dipeptide linker significantly improved the viability of transfected cells without hampering gene silencing activity. Therefore, the precise integration of enzymatic cleavage sites in lipo-oligomers is a promising strategy toward biocompatible nucleic acid carriers.

Creating reliable and robust quality control systems that identify process errors while having a low number of false rejects is a considerable challenge in the automated manufacturing industry. Especially in the pharmaceutical industry, where a product's quality has to be ensured at all costs, a large amount of false rejects is acceptable to guarantee the integrity of all released products. As standard quality control systems mainly perform a binary classification, most of them do not provide insights about the reason behind rejections. As a result, the underlying reason for the rejects, such as degradation in equipment or wrong settings in process parameters, often goes unnoticed. Yet, these systems are based on conservative approaches that incorporate the uncertainties related to the measurement system and process variation such as batch-to-batch variations and assembly tolerances. In this contribution, a new data-driven quality control system is suggested. The system is based on well-established machine learning methods that differentiate multiple types of errors in the assembly processes of medical products. Trained on process data, the system's functionality is demonstrated in a pre-study and two real industrial use cases. Moreover, application-specific differences are discussed. It is shown that for the two use cases and a limited number of batches the system not only detects 100% of all defective products but also limits the number of false rejects to an acceptable amount. In all of the application examples, the system has the potential to be executed as a soft real-time system that allows integration into industrial processes. Moreover, it is shown that the algorithm can present the extracted knowledge in various forms understandable for humans, allowing for more informed decision making.

Part 3: Sustainability and Reconfigurability of Manufacturing Systems; International audience; Current trends such as mass customization necessitate an agile and transformable production. In this context, robotic technologies are seen as a key enabler. But, to date, industrial robots lack the flexibility to easily adapt to changing needs. Therefore, a modular skill-based software framework aiming for free configurability is presented here. A generic task control allows varying incoming tasks to be processed, based on the actual skills of the robot. In this way, the flexible composition of a robot’s skills can be achieved, according to the actual situation.

We develop a dynamic resource extraction game that mimics the global multi-generation planning problem for climate change and fossil fuel extraction. We implement the game under different conditions in the laboratory. Compared to a ‘libertarian’ baseline condition, we find that policy interventions that provide a costly commitment device or reduce climate threshold uncertainty reduce resource extraction. We also study two conditions to assess the underlying social preferences and the viability of ecological dictatorship. Our results suggest that climate-change policies that focus on investments that lock the economy into carbon-free energy sources provide an important commitment device in the intertemporal cooperation problem.