Developing New Methodologies For Electro-Organic Chemistry

Electro-Organic Chemistry has great potential to be used extensively in chemical synthesis but remains relatively under-exploited. To help expand this promising field of research, this PhD project was centred around developing new electrochemical methodology for use in organic reactions, particularly through activation of iodide ions and organic iodide compounds. The first research part is related to iodide ions: a dual electrochemical oxidative process in synthesizing the dihydrobenzofuran motif with excellent efficiency has been developed. This allowed for the formation of zinc ions and molecular iodine from a carbon anode in one pot followed by a zinc catalysed iodocyclisation of phenol and alkene. Related mechanistic studies indicate an unusual pathway which explains the selectivity of the reaction without the often-problematic electrophilic aromatic iodination of the aryl ring. Further extension of this newly developed method to aniline has led to a novel aziridine intermediate which ultimately yielded a diaminated product. The second research part is related to the activation of organic iodide compounds. A newly developed electrochemical approach allows the generation of C-centered radicals for radical addition reaction and cyclisation. The yields and efficiency of the processes are superior in most cases to comparable conditions with tributyltin hydride. The use of air and electricity as the promotor combined with the aqueous reaction media make this a clean and ‘green’ alternative to these classic C–C bond forming processes. We have described the reaction mechanism in terms of electrogenerated reactive oxygen species which arises from the reduction of molecular oxygen in the aqueous phase. In addition, for easy and cheap access to this area and enable reactions that require for anhydrous conditions, we have successfully applied a supermarket purchased battery and UV light respectively as replacements of the roles of potentiostat equipment and oxygen in the methodology

Numerical simulation on the dynamic mechanical response and fracture mechanism of rocks containing a single hole

Caverns and tunnels are constantly exposed to dynamic loads, posing a potentially significant threat to the safety of rock structures. To facilitate the understanding of dynamic fracture around openings, a series of discrete element models were established to numerically examine the effect of hole shape on dynamic mechanical properties and crack evolution. The results indicate that the existence of a hole greatly reduces dynamic strength, and the reduction is closely related to hole shape. The strain variation of pre-holed specimens is more complicated and even larger than the value of intact specimens. Although crack initiation differs for varying hole shapes, the entire structural collapse of specimens is controlled by macro shear cracks along the diagonal direction of the specimen, which are effectively identified by velocity trend arrows and contact force distribution. Finally, comparative analysis between failure pattern of pre-holed specimens under static and dynamic loads were conducted

Neural Video Recovery for Cloud Gaming

Cloud gaming is a multi-billion dollar industry. A client in cloud gaming sends its movement to the game server on the Internet, which renders and transmits the resulting video back. In order to provide a good gaming experience, a latency below 80 ms is required. This means that video rendering, encoding, transmission, decoding, and display have to finish within that time frame, which is especially challenging to achieve due to server overload, network congestion, and losses. In this paper, we propose a new method for recovering lost or corrupted video frames in cloud gaming. Unlike traditional video frame recovery, our approach uses game states to significantly enhance recovery accuracy and utilizes partially decoded frames to recover lost portions. We develop a holistic system that consists of (i) efficiently extracting game states, (ii) modifying H.264 video decoder to generate a mask to indicate which portions of video frames need recovery, and (iii) designing a novel neural network to recover either complete or partial video frames. Our approach is extensively evaluated using iPhone 12 and laptop implementations, and we demonstrate the utility of game states in the game video recovery and the effectiveness of our overall design

Beyond Reward: Offline Preference-guided Policy Optimization

This study focuses on the topic of offline preference-based reinforcement learning (PbRL), a variant of conventional reinforcement learning that dispenses with the need for online interaction or specification of reward functions. Instead, the agent is provided with fixed offline trajectories and human preferences between pairs of trajectories to extract the dynamics and task information, respectively. Since the dynamics and task information are orthogonal, a naive approach would involve using preference-based reward learning followed by an off-the-shelf offline RL algorithm. However, this requires the separate learning of a scalar reward function, which is assumed to be an information bottleneck of the learning process. To address this issue, we propose the offline preference-guided policy optimization (OPPO) paradigm, which models offline trajectories and preferences in a one-step process, eliminating the need for separately learning a reward function. OPPO achieves this by introducing an offline hindsight information matching objective for optimizing a contextual policy and a preference modeling objective for finding the optimal context. OPPO further integrates a well-performing decision policy by optimizing the two objectives iteratively. Our empirical results demonstrate that OPPO effectively models offline preferences and outperforms prior competing baselines, including offline RL algorithms performed over either true or pseudo reward function specifications. Our code is available on the project website: https://sites.google.com/view/oppo-icml-2023

Numerical analysis of hard rock tunnel excavated by double shield TBM based on CWFS model

In order to study the mechanical response of a hard rock tunnel excavated by double shield tunnel boring machine (DS-TBM), a numerical method was introduced to simulate the TBM excavating process. The failure modes of surrounding rock mass described based on the cohesion weakening and frictional strengthening (CWFS) Mohr-Coulomb strain-softening criterion. The characteristics of stress field and plastic zone on the cross and longitudinal section of the tunnel were analyzed in detail, and the results were compared with those in the intrinsic condition (when TBM model is not activated). The simulation results indicate that the stress paths at the vault are relatively simple, and the stress concentration caused by excavation unloading is obviously reduced by lining and backfill grouting, while the sidewall is less disturbed by the excavation of TBM. The invert experiences three unloading processes, due to excavation, the contact between the rear shield and the bottom of surrounding rock, as well as backfill grouting at gap between the lining and the rock mass. The vault has a larger plastic zone than the invert, attributing to the geometrical difference between the cutter-head and the front shield, as well as the conicity of the front and rear shields. The area of plastic zones gradually increases along the tunnel route, but it becomes stable after the rear shield

Fatty acid 2-hydroxylation inhibits tumor growth and increases sensitivity to cisplatin in gastric cancer

Background: Most gastric cancers are diagnosed at an advanced or metastatic stage with poor prognosis and survival rate. Fatty acid 2-hydroxylase (FA2H) with high expression in stomach generates chiral (R)-2-hydroxy FAs ((R)-2-OHFAs) and regulates glucose utilization which is important for cell proliferation and invasiveness. We hypothesized that FA2H impacts gastric tumor growth and could represent a novel target to improve gastric cancer therapy. Methods: FA2H level in 117 human gastric tumors and its association with tumor growth, metastasis and overall survival were examined. Its roles and potential mechanisms in regulating tumor growth were studied by genetic and pharmacological manipulation of gastric cancer cells in vitro and in vivo. Findings: FA2H level was lower in gastric tumor tissues as compared to surrounding tissues and associated with clinicopathologic status of patients, which were confirmed by analyses of multiple published datasets. FA2H depletion decreased tumor chemosensitivity, partially due to inhibition of AMPK and activation of the mTOR/S6K1/Gli1 pathway. Conversely, FA2H overexpression or treatment with (R)-2-OHFAs had the opposite effects. In line with these in vitro observations, FA2H knockdown promoted tumor growth with increased level of tumor Gli1 in vivo. Moreover, (R)-2-OHFA treatment significantly decreased Gli1 level in gastric tumors and enhanced tumor chemosensitivity to cisplatin, while alleviating the chemotherapy-induced weight loss in mice. Interpretation: Our results demonstrate that FA2H plays an important role in regulating Hh signaling and gastric tumor growth and suggest that (R)-2-OHFAs could be effective as nontoxic wide-spectrum drugs to promote chemosensitivity. Fund: Grants of NSF, NIH, and PAPD. Keywords: Fatty acid 2-hydroxylation, Gastric cancer, Lipid metabolism, mTOR, Chemotherapy, Hedgehog pathwa

A Novel Method of Multitype Hybrid Rock Lithology Classification Based on Convolutional Neural Networks

Rock lithology recognition plays a fundamental role in geological survey research, mineral resource exploration, mining engineering, etc. However, the objectivity of researchers, rock variable natures, and tedious experimental processes make it difficult to ensure the accurate and effective identification of rock lithology. Additionally, multitype hybrid rock lithology identification is challenging, and few studies on this issue are available. In this paper, a novel multitype hybrid rock lithology detection method was proposed based on convolutional neural network (CNN), and neural network model compression technology was adopted to guarantee the model inference efficiency. Four fundamental single class rock datasets: sandstone, shale, monzogranite, and tuff were collected. At the same time, multitype hybrid rock lithologies datasets were obtained based on data augmentation method. The proposed model was then trained on multitype hybrid rock lithologies datasets. Besides, for comparison purposes, the other three algorithms, were trained and evaluated. Experimental results revealed that our method exhibited the best performance in terms of precision, recall, and efficiency compared with the other three algorithms. Furthermore, the inference time of the proposed model is twice as fast as the other three methods. It only needs 11 milliseconds for single image detection, making it possible to be applied to the industry by transforming the algorithm to an embedded hardware device or Android platform

Experimental Investigation on Crack Behavior and Stress Thresholds of Sandstone Containing a Square Inclusion under Uniaxial Compression

To study the effect of strength, stiffness and inclination angle of square inclusions on failure characteristics of rock, uniaxial compression tests were carried out on prismatic sandstone containing a square hole with different filling modes and hole angles using a servo-hydraulic loading system. Digital image correlation and acoustic emission techniques were jointly applied to analyze the damage and fracture process, and the crack stress thresholds were determined qualitatively and quantitatively by combining the stress–strain behavior. The results show that the mechanical properties and crack stress thresholds of pre-holed specimens increase with the increase of the strength and stiffness of inclusions, and are affected by the hole angle. Rock failure is mainly caused by secondary crack propagation and shear crack coalescence, eventually forming mixed tensile-shear failure. The crack behavior, especially the crack initiation position, is affected by the filling mode and the hole angle. Interface debonding tends to initiate at the vertical interface, while interface slipping tends to propagate along the inclined interface. Under identical loading conditions, the specimen with 45° hole is more susceptible to crack and damage than that with 0° hole. Notably, inclusions can inhibit the hole deformation and the fracture of rock matrix, especially the sidewall spalling of 0° hole