We report herein a novel atropoenantioselective redox‐neutral amination of biaryl compounds triggered by a cascade of borrowing hydrogen and dynamic kinetic resolution under the cooperative catalysis ...of a chiral iridium complex and an achiral Brønsted acid. This protocol features broad substrate scope and good functional‐group tolerance, and allows the rapid assembly of axially chiral biaryl compounds in good to high yields and with high to excellent enantioselectivity.
Selective when it comes to borrowing: Biaryl compounds with an o‐hydroxy group and an o‐hydroxymethyl group underwent redox‐neutral amination through a cascade of borrowing hydrogen and dynamic kinetic resolution under the cooperative catalysis of a chiral iridium complex and an achiral Brønsted acid (see scheme). This method enabled the rapid synthesis of a range of axially chiral biaryl compounds in good yields with high enantioselectivity.
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RNA-guided genome editing （RGE） using the Streptococcus pyogenes CRISPR-Cas9 system （Jinek et al., 2012; Cong et al., 2013; Mall et al., 2013b） is emerging as a simple and highly ...efficient tool for genome editing in many organisms. The Cas9 nuclease can be programmed by dual or single guide RNA （gRNA） to cut target DNA at specific sites,
Abstract
Accurate flight trajectory prediction is a crucial and challenging task in air traffic control, especially for maneuver operations. Modern data-driven methods are typically formulated as a ...time series forecasting task and fail to retain high accuracy. Meantime, as the primary modeling method for time series forecasting, frequency-domain analysis is underutilized in the flight trajectory prediction task. In this work, an innovative wavelet transform-based framework is proposed to perform time-frequency analysis of flight patterns to support trajectory forecasting. An encoder-decoder neural architecture is developed to estimate wavelet components, focusing on the effective modeling of global flight trends and local motion details. A real-world dataset is constructed to validate the proposed approach, and the experimental results demonstrate that the proposed framework exhibits higher accuracy than other comparative baselines, obtaining improved prediction performance in terms of four measurements, especially in the climb and descent phase with maneuver control. Most importantly, the time-frequency analysis is confirmed to be effective to achieve the flight trajectory prediction task.
We present a thin and elastic tactile sensor glove for teaching dexterous manipulation tasks to robots through human demonstration. The entire glove, including the sensor cells, base layer, and ...electrical connections, is made from soft and stretchable silicone rubber, adapting to deformations under bending and contact while preserving human dexterity. We develop a glove design with five fingers and a palm sensor, revise material formulations for reduced thickness, faster processing and lower cost, adapt manufacturing processes for reduced layer thickness, and design readout electronics for improved sensitivity and battery operation. We further address integration with a multi-camera system and motion reconstruction, wireless communication, and data processing to obtain multimodal reconstructions of human manipulation skills.
This paper surveys the developments of the last 20 years in the field of central pattern generator (CPG) inspired locomotion control, with particular emphasis on the fast emerging robotics-related ...applications. Functioning as a biological neural network, CPGs can be considered as a group of coupled neurons that generate rhythmic signals without sensory feedback; however, sensory feedback is needed to shape the CPG signals. The basic idea in engineering endeavors is to replicate this intrinsic, computationally efficient, distributed control mechanism for multiple articulated joints, or multi-DOF control cases. In terms of various abstraction levels, existing CPG control models and their extensions are reviewed with a focus on the relative advantages and disadvantages of the models, including ease of design and implementation. The main issues arising from design, optimization, and implementation of the CPG-based control as well as possible alternatives are further discussed, with an attempt to shed more light on locomotion control-oriented theories and applications. The design challenges and trends associated with the further advancement of this area are also summarized.
Azulene‐Embedded [n]Helicenes (n=5, 6 and 7) Duan, Chao; Zhang, Jianwei; Xiang, Junjun ...
Angewandte Chemie International Edition,
April 25, 2022, Letnik:
61, Številka:
18
Journal Article
Recenzirano
Azulene is a non‐benzenoid aromatic building block with unique chemical structure and physicochemical properties. By using the “bottom‐up” synthetic strategy, we synthesized three azulene‐embedded ...nhelicenes (nAzHs, n=5, 6 and 7), in which one terminal azulene subunit was fused with n‐2 benzene rings. P‐ and M‐enantiomers were observed in the packing diagrams of 5‐, and 6AzHs. However, P‐ and M‐7AzHs could be isolated by recrystallization of the racemic mixture. These nAzHs were endowed with new properties through the azulene moiety such as low‐lying first electric state (S1), small optical energy gap and anti‐Kasha emission. 6‐, and 7AzHs exhibit strong chiroptical responses with high absorption dissymmetry factor (gabs) maxima of about 0.02, which is among the highest |gabs| values of helicenes in the visible range. These azulene‐embedded nhelicenes contribute to the non‐benzenoid helicene library and allow the structure–property relationships to be better understood.
A straightforward “bottom‐up” approach has been used to synthesize azulene‐embedded pristine nhelicenes (n=5, 6 and 7) that show low‐lying first electric states, small optical energy gaps, and anti‐Kasha emissions. These azulene‐embedded nhelicenes contribute to the non‐benzenoid helicene library and allow structure–property relationships to be better understood.
Photographs taken under harsh ambient lighting can suffer from a number of image quality degradation phenomena due to insufficient exposure. These include reduced brightness, loss of transfer ...information, noise, and color distortion. In order to solve the above problems, researchers have proposed many deep learning-based methods to improve the illumination of images. However, most existing methods face the problem of difficulty in obtaining paired training data. In this context, a zero-reference image enhancement network for low light conditions is proposed in this paper. First, the improved Encoder-Decoder structure is used to extract image features to generate feature maps and generate the parameter matrix of the enhancement factor from the feature maps. Then, the enhancement curve is constructed using the parameter matrix. The image is iteratively enhanced using the enhancement curve and the enhancement parameters. Second, the unsupervised algorithm needs to design an image non-reference loss function in training. Four non-reference loss functions are introduced to train the parameter estimation network. Experiments on several datasets with only low-light images show that the proposed network has improved performance compared with other methods in NIQE, PIQE, and BRISQUE non-reference evaluation index, and ablation experiments are carried out for key parts, which proves the effectiveness of this method. At the same time, the performance data of the method on PC devices and mobile devices are investigated, and the experimental analysis is given. This proves the feasibility of the method in this paper in practical application.
Grasping force control is important for multi-fingered robotic hands to stabilize the grasped object. Humans are able to adjust their grasping force and react quickly to instabilities through tactile ...sensing. However, grasping force control through tactile sensing with robotic hands is still relatively unexplored. In this paper, we make use of tactile sensing for multi-fingered robot hands to adjust the grasping force to stabilize unknown objects without prior knowledge of their shape or physical properties. In particular, an online detection module based on Deep Neural Network (DNN) is designed to detect contact events and object material simultaneously from tactile data. In addition, a force estimation method based on Gaussian Mixture Model (GMM) is proposed to compute the contact information (i.e., contact force and contact location) from tactile data. According to the results of tactile sensing, an object stabilization controller is then employed for a robotic hand to adjust the contact configuration for object stabilization. The spatio-temporal property of tactile data is exploited during tactile sensing. Finally, the effectiveness of the proposed framework is evaluated in a real-world experiment with a five-fingered Shadow Dexterous Hand equipped with BioTac sensors.
In this study, we report the fabrication of nitrogen rich activated nanosized carbon with hierarchical micro/mesoporous and ultrahigh specific surface area by template-free and one-step ...carbonization-activation method, which greatly simplified the process and avoided the waste of reagents. Chitin nanoparticles were prepared by a mechanical induced sol-gel transition process in NaOH/Urea solvent and a subsequent carbonization utilizing NaOH for activation and urea for N doping, resulting in activated carbon (ACNC-800) with extraordinary specific surface area (2631 m2/g) and high nitrogen content (7.1%). Further characterization and electrochemical tests demonstrate high electrochemical performance of the activated nanocarbon. Under the current density of 0.5 A/g, the specific capacitance of the three-electrode system is 245 F/g and that of the two-electrode system is 227 F/g. The assembled capacitors exhibit superior rate performance and good cycle stability (98% capacitance retention after 10000 charge-discharge cycles). This work introduces a simple and efficient strategy to prepare N-doped carbon with hierarchical porosity applied to high performance supercapacitors.
To have a more comprehensive understanding of the water ecological security status of the Yellow River Basin, this paper constructs a water ecological security evaluation index system founded on the ...Pressure-State-Response (PSR) model. The indicators are selected by considering factors such as meteorological conditions, population, economy, water resources, water environment, water ecology, land ecology, ecological service functions, pollution control, and capital investment. Then, the "single index quantification-multiple indices syntheses-poly-criteria integration (SMI-P) method was used to determine the water ecological security index (WESI) of 62 cities in the Yellow River Basin, to classify the safety levels, and combined with the spatial autocorrelation analysis to study the regional characteristics. The results prove that: (a) The overall water ecological security of the Yellow River Basin is relatively poor. Half of the 62 cities have reached the second-level warning level, and most of them are concentrated in the upper and middle reaches of the basin. (b) Wetland area is a long-term key factor in the construction of water ecological safety, and the greening rate of built-up areas has an increasing impact on water ecological safety. (c) The overall water ecological security index shows a slow upward trend, with the annual average growth rate was 0.59%. (d) The water ecological security of 62 cities in the Yellow River Basin shows significant spatial autocorrelation. The findings can offer a practical basis for the water ecological management to promote the high-quality development of the Yellow River Basin.
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