Stereochemical enrichment of a racemic mixture by deracemization must overcome unfavorable entropic effects as well as the principle of microscopic reversibility; recently, photochemical reaction pathways unveiled by the energetic input of light have led to innovations toward this end, most often by ablation of a stereogenic C(sp)-H bond. We report a photochemically driven deracemization protocol in which a single chiral catalyst effects two mechanistically different steps, C-C bond cleavage and C-C bond formation, to achieve multiplicative enhancement of stereoinduction, which leads to high levels of stereoselectivity. Ligand-to-metal charge transfer excitation of a titanium catalyst coordinated by a chiral phosphoric acid or bisoxazoline efficiently enriches racemic alcohols that feature adjacent and fully substituted stereogenic centers to enantiomeric ratios up to 99:1. Mechanistic investigations support a pathway of sequential radical-mediated bond scission and bond formation through a common prochiral intermediate and reveal that, although the overall stereoenrichment is high, the selectivity in each individual step is moderate.
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BioData Min
December 2024
School of Computing, Queen's University, 557 Goodwin Hall, 21-25 Union St, Kingston, K7L 2N8, Ontario, Canada.
Background: Epistasis, the phenomenon where the effect of one gene (or variant) is masked or modified by one or more other genes, significantly contributes to the phenotypic variance of complex traits. Traditionally, epistasis has been modeled using the Cartesian epistatic model, a multiplicative approach based on standard statistical regression. However, a recent study investigating epistasis in obesity-related traits has identified potential limitations of the Cartesian epistatic model, revealing that it likely only detects a fraction of the genetic interactions occurring in natural systems.
View Article and Find Full Text PDFSci Rep
December 2024
School of Construction Machinery, Shandong Jiaotong University, Jinan, 250023, China.
Injection molded parts are increasingly utilized across various industries due to their cost-effectiveness, lightweight nature, and durability. However, traditional defect detection methods for these parts often rely on manual visual inspection, which is inefficient, expensive, and prone to errors. To enhance the accuracy of defect detection in injection molded parts, a new method called MRB-YOLO, based on the YOLOv8 model, has been proposed.
View Article and Find Full Text PDFFront Plant Sci
December 2024
College of Agronomy, College of Mechanical and Electronic Engineering, Shandong Agricultural University, Taian, Shandong, China.
In order to achieve precise discrimination of leaf diseases in the Maize/Soybean intercropping system, i.e. leaf spot disease, rust disease, mixed leaf diseases, this study utilized hyperspectral imaging and deep learning algorithms for the classification of diseased leaves of maize and soybean.
View Article and Find Full Text PDFPhys Rev E
November 2024
Department of Physics, Humboldt Universität zu Berlin, Newtonstr 15, 12489 Berlin, Germany.
The Kuramoto model has provided deep insights into synchronization phenomena and remains an important paradigm to study the dynamics of coupled oscillators. Yet, despite its success, the asynchronous regime in the Kuramoto model has received limited attention. Here, we adapt and enhance the mean-field approach originally proposed by Stiller and Radons [Phys.
View Article and Find Full Text PDFSensors (Basel)
December 2024
College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China.
Simultaneous localization and mapping (SLAM) faces significant challenges due to high computational costs, low accuracy, and instability, which are particularly problematic because SLAM systems often operate in real-time environments where timely and precise state estimation is crucial. High computational costs can lead to delays, low accuracy can result in incorrect mapping and localization, and instability can make the entire system unreliable, especially in dynamic or complex environments. As the state-space dimension increases, the filtering error of the standard cubature Kalman filter (CKF) grows, leading to difficulties in multiplicative noise propagation and instability in state estimation results.
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