Complete genome sequence of Limnobacter thiooxidans CS-K2T, isolated from freshwater lake sediments in Bavaria, Germany.

Limnobacter thiooxidans CS-K2T is a Gram-negative bacterium first isolated from the sediment of the littoral zone of a freshwater lake in Germany. We here present the complete annotated genome sequence of this thiosulfate-oxidizing bacterium, spanning 3.54 Mb and encoding 3,192 protein-coding sequences.

Fast-Decoding Algorithm for Electrode Processes at Electrified Interfaces by Mean-Field Kinetic Model and Bayesian Data Assimilation: An Active-Data-Mining Approach for the Efficient Search and Discovery of Electrocatalysts.

The microscopic origins of the activity and selectivity of electrocatalysts has been a long-lasting enigma since the 19th century. By applying an active-data-mining approach, employing a mean-field kinetic model and a statistical approach of Bayesian data assimilation, we demonstrate here a fast decoding to extract key properties in the kinetics of complicated electrode processes from current-potential profiles in experimental and literary data. As the proof-of-concept, kinetic parameters on the four-electron oxygen reduction reaction in the 0.1 M HClO4 solution (ORR: O2 + 4e- + 4H+ → 2H2O) of various platinum-based single-crystal electrocatalysts are extracted from our own experiments and third-party literature to investigate the microscopic electrode processes. Furthermore, data assimilation of the mean-field ORR model and experimental data is performed based on Bayesian inference for the inductive estimation of kinetic parameters, which sheds light on the dynamic behavior of kinetic parameters with respect to overpotential. This work shows that a fast-decoding algorithm based on a mean-field kinetic model and Bayesian data assimilation is a promising data-driven approach to extract key microscopic features of complicated electrode processes and therefore will be an important method toward building up advanced human-machine collaborations for the efficient search and discovery of high-performance electrochemical materials.

Hemodynamic Risk Factors for the Development of Carotid Stenosis in Patients with Unilateral Carotid Stenosis.

BACKGROUND: It is difficult to predict the development of carotid stenosis by means of the known risk factors. Using a computational fluid dynamics analysis, we examined the hemodynamic risks for carotid stenosis, focusing on wall shear stress (WSS) disturbances. METHODS: In 59 patients with unilateral carotid stenosis, the plaque was removed from the original three-dimensional computed tomography angiographic images, and the vessel shape before stenosis was artificially reproduced. A multivariate regression analysis was performed to determine the associations between the degree of area stenosis and hemodynamic and morphologic factors after adjustment for 6 known risk factors. RESULTS: Metrics for WSS disturbances were higher at and distal to a bifurcation in the carotid arteries after plaque removal compared with the normal carotid arteries, and metrics for WSS magnitudes were lower. In the plaque-removed arteries, the degree of stenosis was significantly negatively correlated with the ratio of stenotic to distal values of metrics for WSS disturbances and the diameter ratio of the external to common carotid artery, and positively correlated with the ratio of proximal to stenotic values of metrics for WSS magnitudes. CONCLUSIONS: Rapid increases in WSS from the common carotid artery toward the bifurcation, rapid decreases in WSS disturbance from the bifurcation toward the internal carotid artery, and lower diameter ratio of the external to common carotid artery are more likely than other risk factors to cause future severe stenosis. In patients with these hemodynamic risks, underlying diseases should be controlled more strictly, with imaging examinations at shorter intervals.

Non-classical nucleation in vapor-liquid-solid growth of monolayer WS2 revealed by in-situ monitoring chemical vapor deposition.

The very early nucleation stage of a transition metal dichalcogenide (TMD) was directly observed with in-situ monitoring of chemical vapor deposition and automated image analysis. Unique nucleation dynamics, such as very large critical nuclei and slow to rapid growth transitions, were observed during the vapor-liquid-solid (VLS) growth of monolayer tungsten disulfide (WS2). This can be explained by two-step nucleation, also known as non-classical nucleation, in which metastable clusters are formed through the aggregation of droplets. Subsequently, nucleation of solid WS2 takes place inside the metastable cluster. Furthermore, the detailed nucleation dynamics was systematically investigated from a thermodynamic point of view, revealing that the incubation time of metastable cluster formation follows the traditional time-temperature transformation diagram. Quantitative phase field simulation, combined with Bayesian inference, was conducted to extract quantitative information on the growth dynamics and crystal anisotropy from in-situ images. A clear transition in growth dynamics and crystal anisotropy between the slow and rapid growth phases was quantitatively verified. This observation supports the existence of two-step nucleation in the VLS growth of WS2. Such detailed understanding of TMD nucleation dynamics can be useful for achieving perfect structure control of TMDs.