Synthesis and Evaluation of Novel Photocatalysts for Photocatalytic Reactions

This study focuses on the design of low-dimensional (LD) photocatalysts for water oxidation in oxygen evolution reaction (OER). Through skillful approaches, such as morphological control, interface construction, defect or vacancy engineering, we developed a series of LD hybrids and examined their photo- and photoelectrochemical performances in OER. Attribute to the stable LD structure and synergistic effect of the components, the heterojunction or hierarchical materials showed enhanced charge separation, transportation, water oxidation kinetics and quantum efficiency

Seasonal behaviour of tidal damping and residual water level slope in the Yangtze River estuary: identifying the critical position and river discharge for maximum tidal damping

As a tide propagates into the estuary, river discharge affects tidal damping, primarily via a friction term, attenuating tidal motion by increasing the quadratic velocity in the numerator, while reducing the effective friction by increasing the water depth in the denominator. For the first time, we demonstrate a third effect of river discharge that may lead to the weakening of the channel convergence (i.e. landward reduction of channel width and/or depth). In this study, monthly averaged tidal water levels (2003–2014) at six gauging stations along the Yangtze River estuary are used to understand the seasonal behaviour of tidal damping and residual water level slope. Observations show that there is a critical value of river discharge, beyond which the tidal damping is reduced with increasing river discharge. This phenomenon is clearly observed in the upstream part of the Yangtze River estuary (between the Maanshan and Wuhu reaches), which suggests an important cumulative effect of residual water level on tide–river dynamics. To understand the underlying mechanism, an analytical model has been used to quantify the seasonal behaviour of tide–river dynamics and the corresponding residual water level slope under various external forcing conditions. It is shown that a critical position along the estuary.info:eu-repo/semantics/publishedVersio

Demonstration of three‐dimensional indoor visible light positioning with multiple photodiodes and reinforcement learning

To provide high‐quality location‐based services in the era of the Internet of Things, visible light positioning (VLP) is considered a promising technology for indoor positioning. In this paper, we study a multi‐photodiodes (multi‐PDs) three‐dimensional (3D) indoor VLP system enhanced by reinforcement learning (RL), which can realize accurate positioning in the 3D space without any off-line training. The basic 3D positioning model is introduced, where without height information of the receiver, the initial height value is first estimated by exploring its relationship with the received signal strength (RSS), and then, the coordinates of the other two dimensions (i.e., X and Y in the horizontal plane) are calculated via trilateration based on the RSS. Two different RL processes, namely RL1 and RL2, are devised to form two methods that further improve horizontal and vertical positioning accuracy, respectively. A combination of RL1 and RL2 as the third proposed method enhances the overall 3D positioning accuracy. The positioning performance of the four presented 3D positioning methods, including the basic model without RL (i.e., Benchmark) and three RL based methods that run on top of the basic model, is evaluated experimentally. Experimental results verify that obviously higher 3D positioning accuracy is achieved by implementing any proposed RL based methods compared with the benchmark. The best performance is obtained when using the third RL based method that runs RL2 and RL1 sequentially. For the testbed that emulates a typical office environment with a height difference between the receiver and the transmitter ranging from 140 cm to 200 cm, an average 3D positioning error of 2.6 cm is reached by the best RL method, demonstrating at least 20% improvement compared to the basic model without performing RL

Iterative point-wise reinforcement learning for highly accurate indoor visible light positioning

Iterative point-wise reinforcement learning (IPWRL) is proposed for highly accurate indoor visible light positioning (VLP). By properly updating the height information in an iterative fashion, the IPWRL not only effectively mitigates the impact of non-deterministic noise but also exhibits excellent tolerance to deterministic errors caused by the inaccurate a priori height information. The principle of the IPWRL is explained, and the performance of the IPWRL is experimentally evaluated in a received signal strength (RSS) based VLP system and compared with other positioning algorithms, including the conventional RSS algorithm, the k-nearest neighbors (KNN) algorithm and the PWRL algorithm where iterations exclude. Unlike the supervised machine learning method, e.g., the KNN, whose performance is highly dependent on the training process, the proposed IPWRL does not require training and demonstrates robust positioning performance for the entire tested area. Experimental results also show that when a large height information mismatch occurs, the IPWRL is able to first correct the height information and then offers robust positioning results with a rather low positioning error, while the positioning errors caused by the other algorithms are significantly higher

Effects of tidal-forcing variations on tidal properties along a narrow convergent estuary

A 1D analytical framework is implemented in a narrow convergent estuary that is 78 km in length (the Guadiana, Southern Iberia) to evaluate the tidal dynamics along the channel, including the effects of neap-spring amplitude variations at the mouth. The close match between the observations (damping from the mouth to ∼ 30 km, shoaling upstream) and outputs from semi-closed channel solutions indicates that the M2 tide is reflected at the estuary head. The model is used to determine the contribution of reflection to the dynamics of the propagating wave. This contribution is mainly confined to the upper one third of the estuary. The relatively constant mean wave height along the channel (< 10% variations) partly results from reflection effects that also modify significantly the wave celerity and the phase difference between tidal velocity and elevation (contradicting the definition of an “ideal” estuary). Furthermore, from the mouth to ∼ 50 km, the variable friction experienced by the incident wave at neap and spring tides produces wave shoaling and damping, respectively. As a result, the wave celerity is largest at neap tide along this lower reach, although the mean water level is highest in spring. Overall, the presented analytical framework is useful for describing the main tidal properties along estuaries considering various forcings (amplitude, period) at the estuary mouth and the proposed method could be applicable to other estuaries with small tidal amplitude to depth ratio and negligible river discharge.info:eu-repo/semantics/publishedVersio

Interplay between Lefty and Nodal signaling is essential for the organizer and axial formation in amphioxus embryos

Abstract(#br)The organizer is an essential signaling center required for axial formation during vertebrate embryonic development. In the basal chordate amphioxus, the dorsal blastopore lip of the gastrula has been proposed to be homologous to the vertebrate organizer. Lefty is one of the first genes to be expressed in the organizer. The present results show that Lefty overexpression abolishes the organizer; the embryos were severely ventralized and posteriorized, and failed to develop anterior and dorsal structures. In Lefty knockouts the organizer is enlarged, and anterior and dorsal structures are expanded. Different from Lefty morphants in vertebrates, amphioxus Lefty mutants also exhibited left-right defects. Inhibition of Nodal with SB505124 partially rescued the effects of Lefty loss-of-function on morphology. In addition, while SB505124 treatment blocked Lefty expression in the cleavage stages of amphioxus embryos, activation of Nodal signaling with Activin protein induced ectopic Lefty expression at these stages. These results show that the interplay between Lefty and Nodal signaling plays an essential role in the specification of the amphioxus organizer and axes

Confined FeNi alloy nanoparticles in carbon nanotubes for photothermal oxidative dehydrogenation of ethane by carbon dioxide

Oxidative dehydrogenation of ethane with CO2 (ODEC) is an attractive reaction for reduction of carbon footprints and ethene production. In this work, we present photothermal catalysis on confined bimetal catalysts for ODEC. Carbon nanotubes confined non-noble bimetal alloy (i.e., CoNi@CNTs and FeNi@CNTs) catalysts were prepared and FeNi@CNTs showed effective performance in photothermal catalytic ODEC to ethene. Experiments and simulations reveal that UV and visible lights (420 – 490 nm) are responsible for ODEC and non-oxidative dehydrogenation of ethane, respectively, to ethene. Additionally, ODEC to ethene is preferred to C-C cracking to methane on FeNi@CNTs in light ( \u3e 490 nm)-induced thermocatalysis. The photothermal effect turns more significant when introduced into thermocatalytic ODEC (500 °C), with ethene generation at one order of magnitude. This work advances new mechanism of photo-mediated catalysis and sheds light on utilization of full-spectrum solar energy and non-noble metallic catalysts for ethene production and CO2 recycling at moderate conditions

NTU4DRadLM: 4D Radar-centric Multi-Modal Dataset for Localization and Mapping

Simultaneous Localization and Mapping (SLAM) is moving towards a robust perception age. However, LiDAR- and visual- SLAM may easily fail in adverse conditions (rain, snow, smoke and fog, etc.). In comparison, SLAM based on 4D Radar, thermal camera and IMU can work robustly. But only a few literature can be found. A major reason is the lack of related datasets, which seriously hinders the research. Even though some datasets are proposed based on 4D radar in past four years, they are mainly designed for object detection, rather than SLAM. Furthermore, they normally do not include thermal camera. Therefore, in this paper, NTU4DRadLM is presented to meet this requirement. The main characteristics are: 1) It is the only dataset that simultaneously includes all 6 sensors: 4D radar, thermal camera, IMU, 3D LiDAR, visual camera and RTK GPS. 2) Specifically designed for SLAM tasks, which provides fine-tuned ground truth odometry and intentionally formulated loop closures. 3) Considered both low-speed robot platform and fast-speed unmanned vehicle platform. 4) Covered structured, unstructured and semi-structured environments. 5) Considered both middle- and large- scale outdoor environments, i.e., the 6 trajectories range from 246m to 6.95km. 6) Comprehensively evaluated three types of SLAM algorithms. Totally, the dataset is around 17.6km, 85mins, 50GB and it will be accessible from this link: https://github.com/junzhang2016/NTU4DRadLMComment: 2023 IEEE International Intelligent Transportation Systems Conference (ITSC 2023