Blade-Tip Vortex Noise Mitigation Traded-Off against Aerodynamic Design for Propellers of Future Electric Aircraft

We study noise generation at the blade tips of propellers designed for future electric aircraft propulsion and, furthermore, analyze the interrelationship between noise mitigation and aerodynamics improvement in terms of propeller geometric designs. Classical propellers with three or six blades and a conceptual propeller with three joined dual-blades are compared to understand the effects of blade tip vortices on the noise generation and aerodynamics. The dual blade of the conceptual propeller is constructed by joining the tips of two sub-blades. These propellers are designed to operate under the same freestream flow conditions and similar electric power consumption. The Improved Delayed Detached Eddy Simulation (IDDES) is adopted for the flow simulation to identify high-resolution time-dependent noise sources around the blade tips. The acoustic computations use a time-domain method based on the convective Ffowcs Williams–Hawkings (FW-H) equation. The thrust of the 3-blade conceptual propeller is\ua04%\ua0larger than the 3-blade classical propeller and\ua08%\ua0more than the 6-blade one, given that they have similar efficiencies. Blade tip vortices are found emitting broadband noise. Since the classical and conceptual 3-blade propellers have different geometries, especially at the blade tips, they introduce deviations in the vortex development. However, the differences are small regarding the broadband noise generation. As compared to the 6-blade classical propeller, both 3-blade propellers produce much larger noise. The reason is that the increased number of blades leads to the reduced strength of tip vortices. The findings indicate that the noise mitigation through the modification of the blade design and number can be traded-off by the changed aerodynamic performance

PAI-Diffusion: Constructing and Serving a Family of Open Chinese Diffusion Models for Text-to-image Synthesis on the Cloud

Text-to-image synthesis for the Chinese language poses unique challenges due to its large vocabulary size, and intricate character relationships. While existing diffusion models have shown promise in generating images from textual descriptions, they often neglect domain-specific contexts and lack robustness in handling the Chinese language. This paper introduces PAI-Diffusion, a comprehensive framework that addresses these limitations. PAI-Diffusion incorporates both general and domain-specific Chinese diffusion models, enabling the generation of contextually relevant images. It explores the potential of using LoRA and ControlNet for fine-grained image style transfer and image editing, empowering users with enhanced control over image generation. Moreover, PAI-Diffusion seamlessly integrates with Alibaba Cloud's Machine Learning Platform for AI, providing accessible and scalable solutions. All the Chinese diffusion model checkpoints, LoRAs, and ControlNets, including domain-specific ones, are publicly available. A user-friendly Chinese WebUI and the diffusers-api elastic inference toolkit, also open-sourced, further facilitate the easy deployment of PAI-Diffusion models in various environments, making it a valuable resource for Chinese text-to-image synthesis

Standardized Volume Power Density Boost in Frequency-Up Converted Contact-Separation Mode Triboelectric Nanogenerators

The influence of a mechanical structure’s volume increment on the volume power density (VPD) of triboelectric nanogenerators (TENGs) is often neglected when considering surface charge density and surface power density. This paper aims to address this gap by introducing a standardized VPD metric for a more comprehensive evaluation of TENG performance. The study specifically focuses on 2 frequency-up mechanisms, namely, the integration of planetary gears (PG-TENG) and the implementation of a double-cantilever structure (DC-TENG), to investigate their impact on VPD. The study reveals that the PG-TENG achieves the highest volume average power density, measuring at 0.92 W/m3. This value surpasses the DC-TENG by 1.26 times and the counterpart TENG by a magnitude of 69.9 times. Additionally, the PG-TENG demonstrates superior average power output. These findings introduce a new approach for enhancing TENGs by incorporating frequency-up mechanisms, and highlight the importance of VPD as a key performance metric for evaluating TENGs

Safety and feasibility of robotic-assisted thoracic surgery after neoadjuvant chemoimmunotherapy in non-small cell lung cancer

ObjectivesThis study aimed to evaluate the safety and feasibility of robotic-assisted thoracic surgery (RATS) after neoadjuvant chemoimmunotherapy in NSCLC.MethodsWe retrospectively collected data for NSCLC patients who received thoracic surgery after neoadjuvant chemoimmunotherapy from May 2020 to August 2022. Surgery details, pathological response, and perioperative outcome were compared between video-assisted thoracic surgery (VATS) group and RATS group. Inverse probability of treatment weighting (IPTW) was used to equal the baseline characteristics.ResultsA total of 220 patients were divided into 78 VATS patients and 142 RATS patients. There was no 90-day mortality in either group. RATS patients demonstrated better results in conversion rate to thoracotomy (VATS vs. RATS: 28.2% vs. 7.5%, P < 0.001), number of lymph node stations harvested (5.63 ± 1.75 vs. 8.09 ± 5.73, P < 0.001), number of lymph nodes harvested (13.49 ± 9.325 vs. 20.35 ± 10.322, P < 0.001), yield pathologic-N (yp-N) assessment (yp-N0, 88.5% vs. 67.6%; yp-N1, 7.6% vs. 12.6%; yp-N2, 3.8% vs. 19.7%; P < 0.001), and visual analog scale pain score after surgery (4.41 ± 0.93 vs. 3.77 ± 1.21, P=0.002). However, there were no significant differences in pathological response evaluation for neoadjuvant chemoimmunotherapy (P = 0.493) and complication rate (P = 0.803). After IPTW-adjustment, these results remained constant.ConclusionsRATS reduced the risk of conversion to thoracotomy, provided a better yp-N stage evaluation, and improved pain score; this suggests that RATS is safe and feasible for NSCLC patients after neoadjuvant chemoimmunotherapy

Learning Knowledge-Enhanced Contextual Language Representations for Domain Natural Language Understanding

Knowledge-Enhanced Pre-trained Language Models (KEPLMs) improve the performance of various downstream NLP tasks by injecting knowledge facts from large-scale Knowledge Graphs (KGs). However, existing methods for pre-training KEPLMs with relational triples are difficult to be adapted to close domains due to the lack of sufficient domain graph semantics. In this paper, we propose a Knowledge-enhanced lANGuAge Representation learning framework for various clOsed dOmains (KANGAROO) via capturing the implicit graph structure among the entities. Specifically, since the entity coverage rates of closed-domain KGs can be relatively low and may exhibit the global sparsity phenomenon for knowledge injection, we consider not only the shallow relational representations of triples but also the hyperbolic embeddings of deep hierarchical entity-class structures for effective knowledge fusion.Moreover, as two closed-domain entities under the same entity-class often have locally dense neighbor subgraphs counted by max point biconnected component, we further propose a data augmentation strategy based on contrastive learning over subgraphs to construct hard negative samples of higher quality. It makes the underlying KELPMs better distinguish the semantics of these neighboring entities to further complement the global semantic sparsity. In the experiments, we evaluate KANGAROO over various knowledge-aware and general NLP tasks in both full and few-shot learning settings, outperforming various KEPLM training paradigms performance in closed-domains significantly.Comment: emnlp 202

A critical review of resistance and oxidation mechanisms of Sb-oxidizing bacteria for the bioremediation of Sb(Ⅲ) pollution

Antimony (Sb) is a priority pollutant in many countries and regions due to its chronic toxicity and potential carcinogenicity. Elevated concentrations of Sb in the environmental originating from mining and other anthropogenic sources are of particular global concern, so the prevention and control of the source of pollution and environment remediation are urgent. It is widely accepted that indigenous microbes play an important role in Sb speciation, mobility, bioavailability, and fate in the natural environment. Especially, antimony-oxidizing bacteria can promote the release of antimony from ore deposits to the wider environment. However, it can also oxidize the more toxic antimonite [Sb(III)] to the less-toxic antimonate [Sb(V)], which is considered as a potentially environmentally friendly and efficient remediation technology for Sb pollution. Therefore, understanding its biological oxidation mechanism has great practical significance to protect environment and human health. This paper reviews studies of the isolation, identification, diversity, Sb(III) resistance mechanisms, Sb(III) oxidation characteristics and mechanism and potential application of Sb-oxidizing bacteria. The aim is to provide a theoretical basis and reference for the diversity and metabolic mechanism of Sb-oxidizing bacteria, the prevention and control of Sb pollution sources, and the application of environment treatment for Sb pollution

You Do (Not) Belong Here: Detecting DPI Evasion Attacks with Context Learning

As Deep Packet Inspection (DPI) middleboxes become increasingly popular, a spectrum of adversarial attacks have emerged with the goal of evading such middleboxes. Many of these attacks exploit discrepancies between the middlebox network protocol implementations, and the more rigorous/complete versions implemented at end hosts. These evasion attacks largely involve subtle manipulations of packets to cause different behaviours at DPI and end hosts, to cloak malicious network traffic that is otherwise detectable. With recent automated discovery, it has become prohibitively challenging to manually curate rules for detecting these manipulations. In this work, we propose CLAP, the first fully-automated, unsupervised ML solution to accurately detect and localize DPI evasion attacks. By learning what we call the packet context, which essentially captures inter-relationships across both (1) different packets in a connection; and (2) different header fields within each packet, from benign traffic traces only, CLAP can detect and pinpoint packets that violate the benign packet contexts (which are the ones that are specially crafted for evasion purposes). Our evaluations with 73 state-of-the-art DPI evasion attacks show that CLAP achieves an Area Under the Receiver Operating Characteristic Curve (AUC-ROC) of 0.963, an Equal Error Rate (EER) of only 0.061 in detection, and an accuracy of 94.6% in localization. These results suggest that CLAP can be a promising tool for thwarting DPI evasion attacks.Comment: 12 pages, 12 figures; accepted to ACM CoNEXT 202

Effects of a small planktivore (Pseudorasbora parva: Cyprinidae) on eutrophication of a shallow eutrophic lake in central China

An enclosure experiment was performed in Lake Yuehu, central China, to assess the effects of a gradient of Pseudorasbora parva biomass on eutrophication state parameters, from May 15 to June 14, 2004. Experimental enclosures were placed into the lake and four treatments were conducted: Control (no fish), low fish (16.5 g m(-3)), medium fish (55 g m(-3)), and high fish (110 g m(-3)). The experimental fish were an average total length of 78 +/- 7 mm (mean +/- standard deviation) and an average weight of 5.5 +/- 1.5 g (mean +/- standard deviation). In general, fish increased Secchi disk transparency (SD) and reduced chlorophyll a and total phytoplankton cells, especially in the medium and high fish treatments. No significant effect of fish on total nitrogen (TN) and total phosphorus (TP) was observed. Relatively higher SD, and lower TN and TP were observed in the medium fish treatment as compared to other fish treatments. Effects of fish biomass on chlorophyll a and total phytoplankton cells were not significantly different between the medium and the high fish treatments. Based on the observed eutrophication parameters and fish mortality, the current experiments suggest that maintaining a 55 g m(-3) biomass of P. parva may be helpful for controlling eutrophic state in the studied lake. Further studies are needed to extrapolate the current results to the whole-lake management decisions

Epidemic characteristics, high-risk townships and space-time clusters of human brucellosis in Shanxi Province of China, 2005–2014

BACKGROUND: Brucellosis, one of the world's most important zoonosis, has been re-emerging in China. Shanxi Province, located in northern China, where husbandry development has been accelerated in recent years, has a rather high incidence of human brucellosis but drew little attention from the researchers. This study aimed to describe the changing epidemiology of human brucellosis in Shanxi Province from 2005 to 2014 and explore high-risk towns and space-time clusters for elucidating the necessity of decentralizing disease control resource to township level in epidemic regions, particularly in hotspot areas.METHODS: We extracted data from the Chinese National Notifiable Infectious Disease Reporting System to describe the incidence and spatiotemporal distribution of human brucellosis in Shanxi Province. Geographic information system was used to identify townships at high risk for the disease. Space-Time Scan Statistic was applied to detect the space-time clusters of human brucellosis during the past decade.RESULTS: From 2005 to 2014, a total of 50,002 cases of human brucellosis were recorded in Shanxi, with a male-to-female ratio of 3.9:1. The reported incidence rate increased dramatically from 7.0/100,000 in 2005 to 23.5/100,000 in 2014, with an average annual increase of 14.5%. There were still 33.8% cases delaying diagnosis in 2014. The proportion of the affected towns increased from 31.5% in 2005 to 82.5% in 2014. High-risk towns spread from the north to the center and then south of Shanxi Province, which were basins and adjacent highlands suitable for livestock cultivation. During the past decade, there were 55 space-time clusters of human brucellosis detected in high risk towns; the clusters could happen in any season. Some clusters' location maintained stable over time.CONCLUSIONS: During the last decade, Shanxi province's human brucellosis epidemic had been aggravated and high-risk areas concentrated in some towns located in basins and adjacent highlands. Space-time clusters existed and some located steadily over time. Quite a few cases still missed timely diagnosis. Greater resources should be allocated and decentralized to mitigate the momentum of rise and improve the accessibility of prompt diagnosis treatment in the high-risk townships