Browse Articles

Environmental influence and species occurrence of yellowjacket drones in an invaded area

Organocatalytic Activation of Alkynes Enabled Remote Control of Atroposelectivity via Vinylidene <i>para</i>-Quinone Methides

Cortical arealization of interneurons defines shared and distinct molecular programs in developing human and macaque brains

Establishment and internal validation of a model to predict the efficacy of Adalimumab in Crohn’s disease

Illuminating the impact of N-terminal acetylation: from protein to physiology

Research on the impact of land use and land cover changes on local meteorological conditions and surface ozone in the north China plain from 2001 to 2020

Silicate-Confined Hydrogen on Nanoscale Zerovalent Iron for Efficient Defluorination Reactions

Two-layer homolog network approach for PFAS nontarget screening and retrospective data mining

Abstract The rapid increase of novel per- and polyfluoroalkyl substances (PFAS) raises concerns, while their identification remains challenging. Here, we develop a two-layer homolog network approach for PFAS nontarget screening using mass spectrometry. The first layer constructs networks between homologs, with evaluation showing that it filters 94% of false candidates. The second layer builds a network between classes to expedite the identification of PFAS. We detected 94 PFAS in twelve waterproof products and two related industrial sludges, including 36 novel PFAS not previously reported in any sample. A local dataset is constructed for retrospective analysis by re-analyzing our previous samples, revealing fifteen novel PFAS in samples collected in 2005. The retrieval of the public database MassIVE uncovers novel PFAS in samples from seven countries. Here, we reveal the historic and global presence of novel PFAS, providing guidance for the management and policy-making concerning persistent chemicals.

Elucidating the role of pyrimidine metabolism in prostate cancer and its therapeutic implications

Structure of transmembrane AMPA receptor regulatory protein subunit γ2

Abnormality detection in nailfold capillary images using deep learning with EfficientNet and cascade transfer learning

Structural basis of phosphate export by human XPR1

Unloading damage evolution and rockburst risk assessment of Xuefengshan No.1 tunnel by combining multiple approaches

Training data diversity enhances the basecalling of novel RNA modification-induced nanopore sequencing readouts

Auditory decision-making deficits after permanent noise-induced hearing loss

Nord Stream methane leaks spread across 14% of Baltic waters

Abstract A suspected 443-486 kt of methane escaped from the Nord Stream pipelines in September 2022 at four explosion sites across three pipelines. Much of this methane rapidly escaped to the atmosphere, while an unknown amount was dissolved. We use sustained high-resolution observations of methane concentrations from autonomous gliders and an instrumented ship of opportunity to reveal the timing and spread of dissolved methane across different Baltic regions and marine protected areas. Estimates of methane spread and concentrations are essential to understand the ecosystem response, and for establishing accurate priors for atmospheric outgassing and transport models. A numerical model, initialized by engineering estimates and our observations, enables us to constrain the mass of locally dissolved Nord Stream methane (9.5-14.7 kt). We show that dissolved methane decreased rapidly through outgassing, however initial concentrations were so high that 14% of the Baltic Sea still experienced concentrations 5 times greater than average natural levels.

A novel breath pattern model and analysis to minimize patient discomfort in medical ventilators

Cyclodehydrogenation of molecular nanographene precursors catalyzed by atomic hydrogen

Abstract Atomically precise synthesis of graphene nanostructures on semiconductors and insulators has been a formidable challenge. In particular, the metallic substrates needed to catalyze cyclodehydrogenative planarization reactions limit subsequent applications that exploit the electronic and/or magnetic structure of graphene derivatives. Here, we introduce a protocol in which an on-surface reaction is initiated and carried out regardless of the substrate type. We demonstrate that, counterintuitively, atomic hydrogen can play the role of a catalyst in the cyclodehydrogenative planarization reaction. The high efficiency of the method is demonstrated by the nanographene synthesis on metallic Au, semiconducting TiO2, Ge:H, as well as on inert and insulating Si/SiO2 and thin NaCl layers. The hydrogen-catalyzed cyclodehydrogenation reaction reported here leads towards the integration of graphene derivatives in optoelectronic devices as well as developing the field of on-surface synthesis by means of catalytic transformations. It also inspires merging of atomically shaped graphene-based nanostructures with low-dimensional inorganic units into functional devices.

Investigating nonlinear dynamic properties of an inertial sensor with rotational velocity-dependent rigidity

A comprehensive assessment of current methods for measuring metacognition

Abstract One of the most important aspects of research on metacognition is the measurement of metacognitive ability. However, the properties of existing measures of metacognition have been mostly assumed rather than empirically established. Here I perform a comprehensive empirical assessment of 17 measures of metacognition. First, I develop a method of determining the validity and precision of a measure of metacognition and find that all 17 measures are valid and most show similar levels of precision. Second, I examine how measures of metacognition depend on task performance, response bias, and metacognitive bias, finding only weak dependences on response and metacognitive bias but many strong dependencies on task performance. Third, I find that all measures have very high split-half reliabilities, but most have poor test-retest reliabilities. This comprehensive assessment paints a complex picture: no measure of metacognition is perfect and different measures may be preferable in different experimental contexts.