Low-cost photoreactors for highly photon/energy-efficient solar-driven synthesis

Solar-driven photocatalytic processes are an emerging field that inspires hopes and dreams of a sustainable future on planet Earth. Using carbon dioxide and water as feedstocks, photocatalytic processes could deliver the energy and carbon feedstock for the future world economy. However, until today, low achieved photocatalytic efficiencies and high costs of photoreaction technology are hurdles for photocatalytic processes at scale. Within this contribution, a low-cost, milli-to-micro structured, and panel-like photoreactor concept, which is suitable for small-scale decentral and large-scale solar farm applications, is introduced. The key feature is a high achieved photocatalytic efficiency at a low design complexity and system cost. The optical modeling and analysis reveal achievable limits and prevalent loss mechanisms cumulating in a concise design guideline for the proposed photoreactors. The guideline comprehensibly establishes a connection between design parameters and performance metrics at a universal level, thereby providing a basis for adaptation and further development in the field of solar-driven photosynthesis

SSL-WM: A Black-Box Watermarking Approach for Encoders Pre-trained by Self-supervised Learning

Recent years have witnessed significant success in Self-Supervised Learning (SSL), which facilitates various downstream tasks. However, attackers may steal such SSL models and commercialize them for profit, making it crucial to protect their Intellectual Property (IP). Most existing IP protection solutions are designed for supervised learning models and cannot be used directly since they require that the models' downstream tasks and target labels be known and available during watermark embedding, which is not always possible in the domain of SSL. To address such a problem especially when downstream tasks are diverse and unknown during watermark embedding, we propose a novel black-box watermarking solution, named SSL-WM, for protecting the ownership of SSL models. SSL-WM maps watermarked inputs by the watermarked encoders into an invariant representation space, which causes any downstream classifiers to produce expected behavior, thus allowing the detection of embedded watermarks. We evaluate SSL-WM on numerous tasks, such as Computer Vision (CV) and Natural Language Processing (NLP), using different SSL models, including contrastive-based and generative-based. Experimental results demonstrate that SSL-WM can effectively verify the ownership of stolen SSL models in various downstream tasks. Furthermore, SSL-WM is robust against model fine-tuning and pruning attacks. Lastly, SSL-WM can also evade detection from evaluated watermark detection approaches, demonstrating its promising application in protecting the IP of SSL models

A Strong Maneuvering Target-Tracking Filtering Based on Intelligent Algorithm

In this paper, a variable-structure multimodel (VSMM) filtering algorithm based on the long short-term memory (LSTM) regression-deep Q network (L-DQN) is proposed to accurately track strong maneuvering targets. The algorithm can map the selection of the model set to the selection of the action label and realize the purpose of a deep reinforcement-learning agent to replace the model switching in the traditional VSMM algorithm by reasonably designing a reward function, state space, and network structure. At the same time, the algorithm introduces a LSTM algorithm, which can compensate the error of tracking results based on model history information. The simulation results show that compared with the traditional VSMM algorithm, the proposed algorithm can quickly capture the maneuvering of the target, the response time is short, the calculation accuracy is significantly improved, and the range of adaptation is wider. Precise tracking of maneuvering targets was achieved

Numerical Simulation and Field Test of the Interaction between Existing Station and Enclosure in Open Excavation and Adding Stories Construction

When constructing open excavation and adding stories on the upper part of an existing station structure, the new foundation pit contacts with the existing station at zero distance; subsequently, the construction has a greater impact than that of other close constructions. To explore the cross-impact of new and existing structures on open excavation and story-adding above the existing station, in this study, through numerical simulation and field measurement, we analyze the deformation law of the existing station and foundation pit retaining structure in the excavation and story-adding construction above the existing station. The following conclusions are obtained. The excavation of the upper foundation pit leads to the overall uplift of the existing station, and the sidewall exhibits an internal extrusion trend, which is caused by an increase in the horizontal load on the station caused by the unloading of the vault and expansion of the formation plastic zone. Affected by the existing station structure, some foundation pit retaining structures are end-suspended piles; the bottoms of the end-suspended pile slips are evident. This study offers control measures for the primary support connection between the pile bottom and initial retention and protection of the existing station, deep hole grouting reinforcement of the stratum behind the pile, and reserving earth berm at the pit bottom to reduce the deformation of the end-suspended pile. The research results can provide a reference for constructing the added story of a subway transfer station

Structure-Based Drug Design of Small Molecule Peptide Deformylase Inhibitors to Treat Cancer

Human peptide deformylase (HsPDF) is an important target for anticancer drug discovery. In view of the limited HsPDF, inhibitors were reported, and high-throughput virtual screening (HTVS) studies based on HsPDF for developing new PDF inhibitors remain to be reported. We reported here on diverse small molecule inhibitors with excellent anticancer activities designed based on HTVS and molecular docking studies using the crystal structure of HsPDF. The compound M7594_0037 exhibited potent anticancer activities against HeLa, A549 and MCF-7 cell lines with IC50s of 35.26, 29.63 and 24.63 μM, respectively. Molecular docking studies suggested that M7594_0037 and its three derivatives could interact with HsPDF by several conserved hydrogen bonds. Moreover, the pharmacokinetic and toxicity properties of M7594_0037 and its derivatives were predicted using the OSIRIS property explorer. Thus, M7594_0037 and its derivatives might represent a promising scaffold for the further development of novel anticancer drugs