Rae1/YacP, a new endoribonuclease involved in ribosome-dependent mRNA decay in Bacillus subtilis

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Chemical Shift-Dependent Interaction Maps in Molecular Solids

Structure determinationof molecular solids through NMR crystallographyrelies on the generation of a comprehensive set of candidate crystalstructures and on the comparison of chemical shifts computed for thosecandidates with experimental values. Exploring t ...

AMER CHEMICAL SOC2023

Efficient and sensitive profiling of RNA–protein interactions using TLC-CLIP

Didier Trono, Julien Léonard Duc, Christina Ernst

RNA-binding proteins are instrumental for post-transcriptional gene regulation, controlling all aspects throughout the lifecycle of RNA molecules. However, transcriptome-wide methods to profile RNA-protein interactions in vivo remain technically challengin ...

2023

Controlling the crystal structure of succinic acid via microfluidic spray-drying

Esther Amstad, Aysu Ceren Okur

Many properties of materials, including their dissolution kinetics, hardness, and optical appearance, depend on their structure. Unfortunately, it is often difficult to control the structure of low molecular weight organic compounds that have a high propen ...

ROYAL SOC CHEMISTRY2023

Melting pseudosymmetry and thermal expansion in 3-benzoylpropionic acid

Tomasz Poreba

The thermal behavior of 3-benzoylpropionic acid (BPA) was investigated using single-crystal and synchrotron powder X-diffraction, as well as differential scanning calorimetry analysis. The study revealed the existence of two subtly distinct structures of B ...

ROYAL SOC CHEMISTRY2023

Direct Observation of the Phase Transition in C60 Fullerene

Chengcheng Yan

In the third study, the order-disorder phase transition of single-crystal C60 is studied using time-resolved electron microscopy. Solid C60 undergoes a first-order phase transition upon heating to 260 K. This is a structural transition from the low-tempera ...

EPFL Infoscience2023

When do Minimax-fair Learning and Empirical Risk Minimization Coincide?

Volkan Cevher

Minimax-fair machine learning minimizes the error for the worst-off group. However, empirical evidence suggests that when sophisticated models are trained with standard empirical risk minimization (ERM), they often have the same performance on the worst-of ...

2023

Learning Transformations To Reduce the Geometric Shift in Object Detection

Mathieu Salzmann, Martin Pierre Engilberge, Vidit Vidit

The performance of modern object detectors drops when the test distribution differs from the training one. Most of the methods that address this focus on object appearance changes caused by, e.g., different illumination conditions, or gaps between syntheti ...

Ieee Computer Soc2023

Pressure-freezing of dodecane: exploring the crystal structures, formation kinetics and phase diagrams for colossal barocaloric effects in n-alkanes

Tomasz Poreba

Barocaloric (BC) materials provide cheaper and more energy efficient alternatives to traditional refrigerants. Some liquid alkanes were recently shown to exhibit a colossal BC effect, matching the entropy changes in commercial vapour-liquid refrigerants. D ...

Royal Soc Chemistry2023

Predicting party switching through machine learning and open data

Silvestro Micera, Emanuele Rossi

Parliament dynamics might seem erratic at times. Predicting future voting patterns could support policy design based on the simulation of voting scenarios. The availability of open data on legislative activities and machine learning tools might enable such ...

CELL PRESS2023

NMR Crystallography in the Big Data Era: New Methods and Applications Powered by Machine Learning

Manuel Cordova

Structure determination of materials is key to understanding their physical properties. While single-crystal X-ray diffraction is the gold standard for structures displaying long-range order, many materials of interest are polycrystalline and/or disordered ...

EPFL2023

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Pressure-freezing of dodecane: exploring the crystal structures, formation kinetics and phase diagrams for colossal barocaloric effects in n-alkanes

Tomasz Poreba

Royal Soc Chemistry2023

Predicting party switching through machine learning and open data

Silvestro Micera, Emanuele Rossi

CELL PRESS2023

NMR Crystallography in the Big Data Era: New Methods and Applications Powered by Machine Learning

Manuel Cordova

EPFL2023