Probing the effects of heterocyclic functionality in [(Benzene) Ru(TsDPENR) Cl] catalysts for asymmetric transfer hydrogenation

A range of TsDPEN catalysts containing heterocyclic groups on the amine nitrogen atom were prepared and evaluated in the asymmetric transfer hydrogenation of ketones. Bidentate and tridentate ligands demonstrated a mutual exclusivity directly related to their function as catalysts. A broad series of ketones were reduced with these new catalysts, permitting the ready identification of an optimal catalyst for each substrate and revealing the subtle effects that changes to nearby donor groups can exhibit

Applications of N′-monofunctionalised TsDPEN derivatives in asymmetric catalysis

This review contains an account of recent developments in the applications of N′-monoalkylated or N′-mono(thio)acylated(N-sulfonyl)-1,2-diphenylethylene-1,2-diamine (TsDPEN) derivatives to asymmetric catalysis. The coverage features examples of applications of derivatives as ligands in organometallic complexes for use in asymmetric reduction and oxidation reactions. The use of TsDPEN derivatives as catalysts in a diverse range of C–C and C–S bond formation reactions is also described in detail

A diversity of recently reported methodology for asymmetric imine reduction

This review contains an account of recent developments in catalytic, asymmetric processes reported for the reduction of C=N bonds to amines, in which we have attempted to communicate the remarkable diversity of methods which have been reported in recent years, including organometallic and organocatalytic processes

Asymmetric transfer hydrogenation of unhindered and non-electron-rich 1-Aryl dihydroisoquinolines with high enantioselectivity

The use of arene/Ru/TsDPEN catalysts bearing a heterocyclic group on the TsDPEN in the asymmetric transfer hydrogenation (ATH) of dihydroisoquinolines (DHIQs) containing meta- or para-substituted aromatic groups at the 1-position results in the formation of products of high enantiomeric excess. Previously, only 1-(ortho-substituted)aryl DHIQs, or with an electron-rich fused ring gave products with high enantioselectivity; therefore, this approach solves a long-standing challenge for imine ATH

Meeting-Merging-Mission: A Multi-robot Coordinate Framework for Large-Scale Communication-Limited Exploration

This letter presents a complete framework Meeting-Merging-Mission for multi-robot exploration under communication restriction. Considering communication is limited in both bandwidth and range in the real world, we propose a lightweight environment presentation method and an efficient cooperative exploration strategy. For lower bandwidth, each robot utilizes specific polytopes to maintains free space and super frontier information (SFI) as the source for exploration decision-making. To reduce repeated exploration, we develop a mission-based protocol that drives robots to share collected information in stable rendezvous. We also design a complete path planning scheme for both centralized and decentralized cases. To validate that our framework is practical and generic, we present an extensive benchmark and deploy our system into multi-UGV and multi-UAV platforms

CREPES: Cooperative RElative Pose Estimation System

Mutual localization plays a crucial role in multi-robot cooperation. CREPES, a novel system that focuses on six degrees of freedom (DOF) relative pose estimation for multi-robot systems, is proposed in this paper. CREPES has a compact hardware design using active infrared (IR) LEDs, an IR fish-eye camera, an ultra-wideband (UWB) module and an inertial measurement unit (IMU). By leveraging IR light communication, the system solves data association between visual detection and UWB ranging. Ranging measurements from the UWB and directional information from the camera offer relative 3-DOF position estimation. Combining the mutual relative position with neighbors and the gravity constraints provided by IMUs, we can estimate the 6-DOF relative pose from a single frame of sensor measurements. In addition, we design an estimator based on the error-state Kalman filter (ESKF) to enhance system accuracy and robustness. When multiple neighbors are available, a Pose Graph Optimization (PGO) algorithm is applied to further improve system accuracy. We conduct enormous experiments to demonstrate CREPES' accuracy between robot pairs and a team of robots, as well as performance under challenging conditions

A flavour perspective of Tiepishihu (Dendrobium officinale) – an emerging food ingredient from popular traditional Chinese medicinal plants: a review

Many Dendrobium orchid stems are used in Traditional Chinese Medicine (TCM). The most popular and premium species is Dendrobium officinale, and its stem in TCM is called Tiepishihu. Tiepishihu has a sweet flavour and is an ingredient in Chinese tea and desserts. There is no comprehensive understanding of its flavour compounds. It is, therefore, essential to understand compounds responsible for its flavour, and how they are formed. This review assesses twelve diverse studies in Tiepishihu flavour (2013–2022). Thirty aroma compounds were compared – furfural and nonanal were identified as common compounds. Four of seven essential amino acids were taste-active, with lysine being the most potent. Pre-harvest factors such as environment impact specific aroma compounds. Post-harvest processing methods, including drying and grinding, can control Tiepishihu's flavour. Methodological consistency is a challenge, but controlling Tiepishihu's flavour could increase its commercial value as a food ingredient

Global research trends of the application of artificial intelligence in bladder cancer since the 21st century: a bibliometric analysis

IntroductionSince the significant breakthroughs in artificial intelligence (AI) algorithms, the application of AI in bladder cancer has rapidly expanded. AI can be used in all aspects of the bladder cancer field, including diagnosis, treatment and prognosis prediction. Nowadays, these technologies have an excellent medical auxiliary effect and are in explosive development, which has aroused the intense interest of researchers. This study will provide an in-depth analysis using bibliometric analysis to explore the trends in this field.MethodDocuments regarding the application of AI in bladder cancer from 2000 to 2022 were searched and extracted from the Web of Science Core Collection. These publications were analyzed by bibliometric analysis software (CiteSpace, Vosviewer) to visualize the relationship between countries/regions, institutions, journals, authors, references, keywords.ResultsWe analyzed a total of 2368 publications. Since 2016, the number of publications in the field of AI in bladder cancer has increased rapidly and reached a breathtaking annual growth rate of 43.98% in 2019. The U.S. has the largest research scale, the highest study level and the most significant financial support. The University of North Carolina is the institution with the highest level of research. EUROPEAN UROLOGY is the most influential journal with an impact factor of 24.267 and a total citation of 11,848. Wiklund P. has the highest number of publications, and Menon M. has the highest number of total citations. We also find hot research topics within the area through references and keywords analysis, which include two main parts: AI models for the diagnosis and prediction of bladder cancer and novel robotic-assisted surgery for bladder cancer radicalization and urinary diversion.ConclusionAI application in bladder cancer is widely studied worldwide and has shown an explosive growth trend since the 21st century. AI-based diagnostic and predictive models will be the next protagonists in this field. Meanwhile, the robot-assisted surgery is still a hot topic and it is worth exploring the application of AI in it. The advancement and application of algorithms will be a massive driving force in this field