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In cycling races, overtaking is a crucial maneuver that involves drafting behind and moving to the side of another cyclist. The flow interaction between the cyclists has a very significant impact on the aerodynamic performance. Previous experimental and numerical studies have shown the aerodynamic drag changes at certain relative positions between cyclists. This study aims at providing a comprehensive aerodynamic power contour along a complete overtaking path, detailing the power at different relative positions to develop efficient overtaking strategies. The aerodynamic results are obtained with numerical simulations, the accuracy of which is validated against wind tunnel experiments. Improved sampling and data-fitting approaches are employed to enhance previous findings. The results show that starting the overtaking maneuver closest to the leading cyclist and overtaking with a larger lateral separation is the most aerodynamically efficient strategy. These findings provide valuable insights into developing optimal overtaking strategies in competitive cycling races.

In this work, we conduct a numerical investigation of a hexacopter for urban air mobility, emphasizing the interactional effect between different components of the vehicle on the aerodynamic and aeroacoustic performance. The nearfield turbulent flow fields are resolved by delayed detached eddy simulations, and the acoustic waves at far-field observers are computed using an integral solution of the Ffowcs-Williams and Hawkings equation. The results show that the close placement of rotors can lead to remarkable thrust fluctuations and slightly reduce the average thrust. Consequently, the sound pressure level for the tonal components is considerably increased over a wide frequency range, especially at the observers in the upstream and downstream directions. The rotor–rotor interaction also results in a contracted wake geometry towards the vehicle centre and intensifies the dissipation of the vortices in the downstream wake. The presence of connecting arms can cause significant thrust fluctuations on the surfaces of both rotor blades and arms, which produces additional tonal noise at high-order harmonics of the blade passing frequency. In contrast, for current configuration, the existence of the fuselage only slightly reduces the total thrust and contributes little to noise generation. © 2023 Elsevier Ltd

Xiaoxiao Zhao,1 Hanjun Zhao,1 Runzhen Chen,1 Jiannan Li,1 Jinying Zhou,1 Nan Li,1 Shaodi Yan,2 Chen Liu,1 Peng Zhou,1 Yi Chen,1 Li Song,1 Hongbing Yan2 1Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Peking Union Medical College & Chinese Academy of Medical Sciences, BeiJing, People’s Republic of China; 2Department of Cardiology, Fuwai Hospital Chinese Academy of Medical Sciences, ShenZhen, People’s Republic of ChinaCorrespondence: Hanjun Zhao, Department of Cardiology, Fuwai Hospital, Chinese Academy of Medical Sciences, No. 167, Beijing, 100037, People’s Republic of China, Tel +86-15210020808, Email 15210020808@163.com Hongbing Yan, Fuwai Hospital, Chinese Academy of Medical Sciences, 12 Langshan Road, Shenzhen, 518000, People’s Republic of China, Tel +86-1301339287, Email hbyanfuwai2018@163.comBackground and Aim: An elevated triglyceride-glucose (TyG) level is associated with increased risk of mortality in patients with CAD. Trimethylamine N-oxide (TMAO) has mechanistic links to atherosclerotic coronary artery disease (CAD) pathogenesis and is correlated with adverse outcomes. However, the incremental prognostic value of TMAO and TyG in the cohort of optical coherence tomography (OCT)-defined high-risk ST-segment elevation myocardial infarction (STEMI) patients is unknown.Methods: We studied 274 consecutive aged ≥ 18 years patients with evidence of STEMI and detected on pre-intervention OCT imaging of culprit lesions between March 2017 and March 2019.Outcomes: There were 22 (22.68%), 27 (27.84%), 26 (26.80%), and 22 (22.68%) patients in groups A-D, respectively. The baseline characteristics according to the level of TMAO and TyG showed that patients with higher level in both indicators were more likely to have higher triglycerides (p < 0.001), fasting glucose (p < 0.001) and higher incidence of diabetes (p = 0.008). The group with TMAO > median and TyG ≤ median was associated with higher rates of MA

In this study, flow structures and their evolution over a track cyclist were investigated through wind tunnel tests. In supplement to the experiment, high-fidelity numerical simulations were also conducted to demonstrate the origins of global flow structures. In wind tunnel tests, a full-scale track cyclist mannequin was built based on the three-dimensional scanning of an elite track cyclist in a riding position of a sprint event, and a Cobra probe was used to measure the wake structures. The results show that the preeminent flow structures around the track cyclist mannequin are the streamwise vortices originating from different body parts. The evolution of these vortices involves strong vortex interactions and performs differently on each side, resulting in a dominant streamwise vortex merged behind the right thigh, which is associated with aerodynamic drag productions. In particular, leg position affects the lateral displacement between the elbow vortex and upper thigh, which is the reason for the distinct flow behaviors on each side. This study helps to better understand the flow around a track cyclist, facilitating the development of drag-saving strategies in the future.

Constructing well-defined heterostructure interfaces in catalysts is an efficient strategy to break the so-called scaling relationships and to accelerate the reactions involving multiple intermediates. Here a cluster-cluster heterostructure catalyst composed of crystalline ruthenium cluster and amorphous chromium oxide cluster is designed to realize high-performance alkaline hydrogen electrocatalysis. The strongly coupled cluster-cluster heterostructure interface induces a unique interfacial interpenetration effect, which simultaneously optimizes the adsorption of intermediates on each cluster. The resulting catalyst exhibits impressive catalytic activities for the hydrogen oxidation reaction (exchange current density of 2.8 A mg-1Ru) and the hydrogen evolution reaction (mass activity of 23.0 A mg(-1)Ru at the overpotential of 100 mV) in alkaline media. The hydroxide exchange membrane fuel cell delivers a mass activity of 22.4 A mg(-1)Ru at 0.65 V and outstanding durability with no voltage loss over 105 h operation at 500 mA cm(-2). The present work demonstrates the superiority of cluster-cluster heterostructure interface towards the development of advanced catalysts.

While various models and computational tools have been proposed for structure and property analysis of molecules, generating molecules that conform to all desired structures and properties remains a challenge. Here, we introduce a multi-constraint molecular generation large language model, TSMMG, which, akin to a student, incorporates knowledge from various small models and tools, namely, the 'teachers'. To train TSMMG, we construct a large set of text-molecule pairs by extracting molecular knowledge from these 'teachers', enabling it to generate novel molecules that conform to the descriptions through various text prompts. We experimentally show that TSMMG remarkably performs in generating molecules meeting complex, natural language-described property requirements across two-, three-, and four-constraint tasks, with an average molecular validity of over 99% and success ratio of 88.08%, 65.27%, and 61.44%, respectively. The model also exhibits adaptability through zero-shot testing, creating molecules that satisfy combinations of properties that have not been encountered. It can comprehend text inputs with various language styles, extending beyond the confines of outlined prompts, as confirmed through empirical validation. Additionally, the knowledge distillation feature of TSMMG contributes to the continuous enhancement of small models, while the innovative approach to dataset construction effectively addresses the issues of data scarcity and quality, which positions TSMMG as a promising tool in the domains of drug discovery and materials science. Code is available at https://github.com/HHW-zhou/TSMMG., Comment: 25 pages, 4 figures

Bagging operations, common in packaging and assisted living applications, are challenging due to a bag's complex deformable properties. To address this, we develop a robotic system for automated bagging tasks using an adaptive structure-of-interest (SOI) manipulation approach. Our method relies on real-time visual feedback to dynamically adjust manipulation without requiring prior knowledge of bag materials or dynamics. We present a robust pipeline featuring state estimation for SOIs using Gaussian Mixture Models (GMM), SOI generation via optimization-based bagging techniques, SOI motion planning with Constrained Bidirectional Rapidly-exploring Random Trees (CBiRRT), and dual-arm manipulation coordinated by Model Predictive Control (MPC). Experiments demonstrate the system's ability to achieve precise, stable bagging of various objects using adaptive coordination of the manipulators. The proposed framework advances the capability of dual-arm robots to perform more sophisticated automation of common tasks involving interactions with deformable objects.

Interactive perception enables robots to manipulate the environment and objects to bring them into states that benefit the perception process. Deformable objects pose challenges to this due to significant manipulation difficulty and occlusion in vision-based perception. In this work, we address such a problem with a setup involving both an active camera and an object manipulator. Our approach is based on a sequential decision-making framework and explicitly considers the motion regularity and structure in coupling the camera and manipulator. We contribute a method for constructing and computing a subspace, called Dynamic Active Vision Space (DAVS), for effectively utilizing the regularity in motion exploration. The effectiveness of the framework and approach are validated in both a simulation and a real dual-arm robot setup. Our results confirm the necessity of an active camera and coordinative motion in interactive perception for deformable objects., Comment: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible

Ducted propellers present broad applicability in urban air mobility vehicles due to their enhanced operational safety, improved aerodynamic performance, and potential to mitigate noise emissions. This study proposes a numerical approach for designing adequate duct geometries, focusing on the duct's lip profile, expansion ratio, and tip clearance, aiming to provide valuable design guidance for ducted propellers. The simulations are validated through experimental data, showing reasonable agreement in terms of thrust generation and far-field noise. The mean flow and generated thrust are characterized with a parametric study using steady simulations, while delayed detached eddy simulations are employed to capture transient flow characteristics and investigate noise generation. The noise levels were computed using the integral solution of the Ffowcs-Williams and Hawkings equation. The lip geometry impacts the flow distribution and generated thrust, modifying the tonal noise. Furthermore, slightly divergent ducts can increase the total thrust by minimizing flow separation on the duct wall while increasing the suction on the duct lip. The primary noise sources are identified at the propeller's leading edge and tip. The results reveal that divergent ducts effectively reduce tonal noise at all observer angles but increase broadband noise, attributed to the noise sources at the leading edge of the propeller and the interaction with the duct lip. Additionally, reducing the tip clearance from 2 to 1 mm enhances the total thrust by more than 20% without causing extra noise generation.

Trailing edge serration is an effective method to reduce broadband noise generation by an airfoil. However, the noise reduction performance can be significantly reduced when there is flow misalignment at the serration. This experimental study investigates the impact of a shift in the serration position downstream of the airfoil trailing edge on the noise reduction performance, referred to in this paper as serration extension. Experiments were performed on a 100-mm-chord NACA 0012 wing model with sawtooth trailing edge serrations. The serration performance was studied at 0° and 7° flap-down configurations at various angles of attack. The serrations with three different extension lengths of 5, 10, and 15 mm were tested and compared with the baseline case without extension. The emitted noise was measured with a phased microphone array. The results show a significant reduction in broadband high-frequency noise by extension under loading conditions. Particle image velocimetry measurements of root flow along the wall-normal plane reveal diminished crossflow across the serration after extension. Furthermore, the extensions cause an up-to-25% increase in the maximum lift coefficient and improved or unaltered lift-to-drag ratios.

The previous study has shown that the longitudinal groove fabric can reduce drag forces on a circular cylinder by forcing a drag crisis (Zheng et al. 2021). In this study, the effects of the longitudinal groove fabric are investigated on a full-scale track cycling mannequin. The force measurement results show that the longitudinal groove fabric on the upper arms can achieve a maximum drag reduction of about 7% at a flow speed of 17 m/s, and its control effects depend on flow speeds. Large-scale particle image velocimetry measurements further show that the drag reductions on the upper arm are characterized by diminished streamwise velocity deficits. The control effects also vary on different spanwise locations of the arm, where the flow behaves distinctively. The measurements also reveal the distinct flow dynamics at different heights, i.e., wake interactions and swirling motions, showing the complexity of reducing drag forces from a track cyclist.

Low-altitude flights of unmanned aircraft systems (UASs), such as drones, can cause substantial noise pollution in urban areas. This study aims to tackle the crucial issue of noise in UAS flight planning and analyze the feasibility of implementing low-noise urban flights at a micro level. We employ a virtual flight simulator to accurately model the UAS noise impact in realistic flights and optimize the flight path via a heuristic algorithm accordingly. The flight noise assessment incorporates a sound source modeling technique for practical UAS models and an efficient Gaussian beam tracing method for outdoor noise propagation in realistic environments. Case studies for flight simulations are conducted in a representative resident community and metropolitan area to evaluate the noise impact resulting from different flight paths. By comparing our approach with benchmark shortest-distance paths, we validate its effectiveness in significantly reducing en-route noise exposure, encompassing both instantaneous and continuous noise levels. This method holds great potential for contributing to the planning and management of urban air transport systems. It effectively mitigates noise impact, promoting quieter and more environmentally friendly UAS operations and sustainable urban transportation.

In windsurfing, the sail is the primary source of propulsive force. Due to the unique shape and structure, the aerodynamic performance of a windsurfing sail is not well understood. This study aims to investigate the aerodynamic performance of a windsurfing sail under various angles of attack and sail heights using steady Reynolds-averaged Navier–Stokes simulations. The simulations were validated with wind tunnel measurements. The study finds that the local maximum lift coefficient and stall angle are different at different sections along the sail height. Further investigations on the pressure distributions and sectional flow fields indicate that the different sectional lift coefficients and stall are significantly influenced by the geometric profiles and orientations of the luff pocket. The sectional geometric profile consists of a reduced camber near the sail tip, which is prone to flow separation. Thus, flow separation first occurred at the sail tip with increasing angle of attack, then extended towards the sail foot. During flow separation, a recirculation region was found on the suction side of the sail, leading to a reduction in lift and increase in drag. The findings of this study provide insights into the aerodynamic forces and flow characteristics of windsurfing sails, which can be applied to improve sail design and performance.

Videos captured from multiple viewpoints can help in perceiving the 3D structure of the world and benefit computer vision tasks such as action recognition, tracking, etc. In this paper, we present a method for self-supervised learning from synchronized multi-view videos. We use a cross-view reconstruction task to inject geometry information in the model. Our approach is based on the masked autoencoder (MAE) framework. In addition to the same-view decoder, we introduce a separate cross-view decoder which leverages cross-attention mechanism to reconstruct a target viewpoint video using a video from source viewpoint, to help representations robust to viewpoint changes. For videos, static regions can be reconstructed trivially which hinders learning meaningful representations. To tackle this, we introduce a motion-weighted reconstruction loss which improves temporal modeling. We report state-of-the-art results on the NTU-60, NTU-120 and ETRI datasets, as well as in the transfer learning setting on NUCLA, PKU-MMD-II and ROCOG-v2 datasets, demonstrating the robustness of our approach. Code will be made available.

The manipulation of deformable objects by robotic systems presents a significant challenge due to their complex and infinite-dimensional configuration spaces. This paper introduces a novel approach to Deformable Object Manipulation (DOM) by emphasizing the identification and manipulation of Structures of Interest (SOIs) in deformable fabric bags. We propose a bimanual manipulation framework that leverages a Graph Neural Network (GNN)-based latent dynamics model to succinctly represent and predict the behavior of these SOIs. Our approach involves constructing a graph representation from partial point cloud data of the object and learning the latent dynamics model that effectively captures the essential deformations of the fabric bag within a reduced computational space. By integrating this latent dynamics model with Model Predictive Control (MPC), we empower robotic manipulators to perform precise and stable manipulation tasks focused on the SOIs. We have validated our framework through various empirical experiments demonstrating its efficacy in bimanual manipulation of fabric bags. Our contributions not only address the complexities inherent in DOM but also provide new perspectives and methodologies for enhancing robotic interactions with deformable objects by concentrating on their critical structural elements. Experimental videos can be obtained from https://sites.google.com/view/bagbot.

Matrix multiplication (MatMul) typically dominates the overall computational cost of large language models (LLMs). This cost only grows as LLMs scale to larger embedding dimensions and context lengths. In this work, we show that MatMul operations can be completely eliminated from LLMs while maintaining strong performance at billion-parameter scales. Our experiments show that our proposed MatMul-free models achieve performance on-par with state-of-the-art Transformers that require far more memory during inference at a scale up to at least 2.7B parameters. We investigate the scaling laws and find that the performance gap between our MatMul-free models and full precision Transformers narrows as the model size increases. We also provide a GPU-efficient implementation of this model which reduces memory usage by up to 61% over an unoptimized baseline during training. By utilizing an optimized kernel during inference, our model's memory consumption can be reduced by more than 10x compared to unoptimized models. To properly quantify the efficiency of our architecture, we build a custom hardware solution on an FPGA which exploits lightweight operations beyond what GPUs are capable of. We processed billion-parameter scale models at 13W beyond human readable throughput, moving LLMs closer to brain-like efficiency. This work not only shows how far LLMs can be stripped back while still performing effectively, but also points at the types of operations future accelerators should be optimized for in processing the next generation of lightweight LLMs. Our code implementation is available at \url{https://github.com/ridgerchu/matmulfreellm}.

Style transfer aims to render an image with the artistic features of a style image, while maintaining the original structure. Various methods have been put forward for this task, but some challenges still exist. For instance, it is difficult for CNN-based methods to handle global information and long-range dependencies between input images, for which transformer-based methods have been proposed. Although transformers can better model the relationship between content and style images, they require high-cost hardware and time-consuming inference. To address these issues, we design a novel transformer model that includes only the encoder, thus significantly reducing the computational cost. In addition, we also find that existing style transfer methods may lead to images under-stylied or missing content. In order to achieve better stylization, we design a content feature extractor and a style feature extractor, based on which pure content and style images can be fed to the transformer. Finally, we propose a novel network termed Puff-Net, i.e., pure content and style feature fusion network. Through qualitative and quantitative experiments, we demonstrate the advantages of our model compared to state-of-the-art ones in the literature., Comment: 11 pages, 11 figures, to be published in IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2024)

We present Eagle (RWKV-5) and Finch (RWKV-6), sequence models improving upon the RWKV (RWKV-4) architecture. Our architectural design advancements include multi-headed matrix-valued states and a dynamic recurrence mechanism that improve expressivity while maintaining the inference efficiency characteristics of RNNs. We introduce a new multilingual corpus with 1.12 trillion tokens and a fast tokenizer based on greedy matching for enhanced multilinguality. We trained four Eagle models, ranging from 0.46 to 7.5 billion parameters, and two Finch models with 1.6 and 3.1 billion parameters and find that they achieve competitive performance across a wide variety of benchmarks. We release all our models on HuggingFace under the Apache 2.0 license. Models at: https://huggingface.co/RWKV Training code at: https://github.com/RWKV/RWKV-LM Inference code at: https://github.com/RWKV/ChatRWKV Time-parallel training code at: https://github.com/RWKV/RWKV-infctx-trainer

Images suffer from heavy spatial redundancy because pixels in neighboring regions are spatially correlated. Existing approaches strive to overcome this limitation by reducing less meaningful image regions. However, current leading methods rely on supervisory signals. They may compel models to preserve content that aligns with labeled categories and discard content belonging to unlabeled categories. This categorical inductive bias makes these methods less effective in real-world scenarios. To address this issue, we propose a self-supervised framework for image redundancy reduction called Learning to Rank Patches (LTRP). We observe that image reconstruction of masked image modeling models is sensitive to the removal of visible patches when the masking ratio is high (e.g., 90\%). Building upon it, we implement LTRP via two steps: inferring the semantic density score of each patch by quantifying variation between reconstructions with and without this patch, and learning to rank the patches with the pseudo score. The entire process is self-supervised, thus getting out of the dilemma of categorical inductive bias. We design extensive experiments on different datasets and tasks. The results demonstrate that LTRP outperforms both supervised and other self-supervised methods due to the fair assessment of image content., Comment: Accepted by CVPR 2024

In the field of transportation, it is of paramount importance to address and mitigate illegal actions committed by both motor and non-motor vehicles. Among those actions, wrong-way cycling (i.e., riding a bicycle or e-bike in the opposite direction of the designated traffic flow) poses significant risks to both cyclists and other road users. To this end, this paper formulates a problem of detecting wrong-way cycling ratios in CCTV videos. Specifically, we propose a sparse sampling method called WWC-Predictor to efficiently solve this problem, addressing the inefficiencies of direct tracking methods. Our approach leverages both detection-based information, which utilizes the information from bounding boxes, and orientation-based information, which provides insights into the image itself, to enhance instantaneous information capture capability. On our proposed benchmark dataset consisting of 35 minutes of video sequences and minute-level annotation, our method achieves an average error rate of a mere 1.475% while taking only 19.12% GPU time of straightforward tracking methods under the same detection model. This remarkable performance demonstrates the effectiveness of our approach in identifying and predicting instances of wrong-way cycling.

This dissertation is dedicated to using Memristive Spiking Neural Networks (MSNNs) for deep learning tasks such as image classification, visual associative memory tasks such as pattern recognition, and auditory cortex processing tasks such as sound localization (SL). The image classification model consists entirely of memristive neurons and memristive synapses utilizing deep learning plausible supervised learning rules. The pattern recognition fully MSNNs consists of memristive neurons and memristive synapses harnessing biologically plausible unsupervised learning rules. SL MSNNs emulate biological brain functionality with volatile memristive synapses.By developing a minimal circuit element memristive neuron -- Memristive Integrate-and-Fire (MIF) neuron -- with commercially accessible memristors, we are able to demonstrate large-scale fully MSNNs and apply the supervised Backpropagation Through Time (BPTT) algorithm to train networks, achieving state-of-the-art accuracy for several datasets. In addition, using a memristive unsupervised learning rule based on a continuously evolving alpha function membrane potential, we are also able to train large-scale fully MSNNs with Spiking-Time-Dependent Plasticity (STDP) and achieve high accuracies. Moreover, a volatile memristor is used for mimicking Short-Term Depression (STD) synapses such that we can simulate SL networks and pinpoint the direction of the sound coming from.The major contributions reported in this proposal include: • Development of the MIF neuron SPICE-level model; • Validation of the SPICE-level MIF neuron model to a Python-based simulation of large-scale MSNNs; • Simulation of a small-scale neuron network consisting of a presynaptic, a memristive synapse, and a postsynaptic MIF neuron to generate the STDP learning window; • Abstraction of memristive STDP with alpha functions; • Simulation of a large-scale, fully MSNN consisting of MIF neurons and memristive synapses for unsupervised learning in Python; • D

Xiaoxiao Zhao,1,&ast; Li Song,1,&ast; Jiannan Li,1 Jinying Zhou,1 Nan Li,1 Shaodi Yan,2 Runzhen Chen,1 Ying Wang,1 Chen Liu,1 Peng Zhou,1 Zhaoxue Sheng,1 Yi Chen,1 Hanjun Zhao,1 Hongbing Yan2 1Department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing, People’s Republic of China; 2Fuwai Hospital Chinese Academy of Medical Sciences, Shenzhen, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Hongbing Yan, Fuwai Hospital, Chinese Academy of Medical Sciences, 12 Langshan Road, Shenzhen, 518000, People’s Republic of China, Tel +86-13701339287, Email hbyanfuwai2018@163.com Hanjun Zhao, Department of Cardiology, Fuwai Hospital, Chinese Academy of Medical Sciences, No. 167, Beijing, 100037, People’s Republic of China, Tel +86-15210020808, Email 15210020808@163.comBackground and Aims: This study aimed to determine whether convertase subtilisin/kexin type 9 (PCSK9)-associated cardiovascular risk is modulated by triglyceride-glucose (TyG) in ST-segment elevation myocardial infarction (STEMI) patients with primary percutaneous coronary disease (PCI).Methods: A total of 1541 patients with STEMI (aged ≥ 18 years) undergoing primary PCI were consecutively enrolled between March 2017 and March 2019.Outcomes: When stratifying the overall population according to TyG indices less than or greater than the median (TyG median = 9.07) as well as according to quartiles of PCSK9 levels, higher TyG index levels were significantly associated with all-cause mortality only when TyG levels were 9.07 or higher (ie, relative to quartile 1 [Q1], the adjusted HR for all-cause mortality was 3.20 [95% CI, 0.54– 18.80] for Q2, p = 0.199; 7.89 [95% CI, 1.56– 40.89] for Q3, p = 0.013; and 5.61 [95% CI, 1.04– 30.30] for Q4, p = 0.045. During a median follow-up period of 1.96 years, the HR for all-cause mortality was higher in th

Cuiling Li, Peng Zhou, Yuanqin Liu, Lei Zhang Department of Neurosurgery, Shandong Medicine and Health Key Laboratory of Neurosurgery, The First Affiliated Hospital of Shandong First Medical University and Shandong Provincial Qianfoshan Hospital, Jinan, People’s Republic of ChinaCorrespondence: Lei Zhang, Department of Neurosurgery, Shandong Medicine and Health Key Laboratory of Neurosurgery, The First Affiliated Hospital of Shandong First Medical University and Shandong Provincial Qianfoshan Hospital, 16766 Jingshi Road, Lixia District, Jinan, People’s Republic of China, Email zhanglei134@163.comAbstract: Post-neurosurgical infection is a common complication of neurosurgery, and serious infection can threaten the life of patients. In recent years, the increase in multidrug-resistant bacteria, especially carbapenem-resistant Enterobacteriaceae (CRE), has proved fatal to patients. Although there are a few cases of CRE meningitis and few clinical trials have been carried out, it has attracted increasing attention with the increasing probability of its occurrence, especially considering that there are few successful cases. An increasing number of studies are also looking for the risk factors and clinical symptoms of CRE intracranial infection. In terms of treatment, some new antibiotics are gradually being used in the clinic, but due to the complicated drug-resistant mechanism of CRE and the obstruction of the blood‒brain barrier (BBB), the therapeutic effect is still very poor. In addition, obstructive hydrocephalus and brain abscess caused by CRE meningitis are still important causes of patient death and are also difficult to treat.Keywords: CRE, ventriculitis and meningitis, polymyxin, ceftazidime-avibactam, cefiderocol

Shixiao Li,1 Peng Zhou,2 Lihong Yang,1 Tianbin Tang,1 Jiajia Qin,1 Jiao Qian,1 Shen Bo,1 Sufei Yu1 1Department of Clinical Microbiology Laboratory, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Taizhou, Zhejiang, People’s Republic of China; 2Department of Pharmacy, The Third Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, Zhejiang, People’s Republic of ChinaCorrespondence: Sufei Yu, Email ysf5236791@163.comObjective: Severe pneumonia is a common infectious disease with high morbidity and mortality. Early etiological diagnosis is crucial for improving the prognosis. The aim of this study is to evaluate the clinical value of sampling time of mNGS in patients with severe pneumonia.Methods: This retrospective study enrolled 105 patients with severe pneumonia. mNGS was performed on bronchoalveolar lavage fluid (BALF). Patients were divided into the sampling time ≤ 72h vs sampling time > 72h groups and survivors vs non-survivors groups according to their sampling time and prognosis. Clinical characteristics, the adjustment of antibiotics and clinical prognostic value were evaluated.Results: Our study showed that, early sampling of mNGS can significantly shorten the mechanical ventilation time (p = 0.007) and hospitalization time (p = 0.004). In the non-survivors group, CURB-65, SOFA, and APACHE II scores were higher. Age (OR: 1.051, 95% CI: 1.004– 1.100, p = 0.034), chronic respiratory diseases (OR: 4.639, 95% CI: 1.260– 17.082, p = 0.021), immunosuppression (OR: 5.008, 95% CI: 1.617– 15.510, p = 0.005) and SOFA score on the day of mNGS sampling (OR: 1.492, 95% CI: 1.212– 1.837, p < 0.001) were independent risk factors of in-hospital mortality. The most common pathogens were Klebsiella pneumoniae and Human gammaherpesvirus 4. The proportion of appropriate and targeted antibiotics adjusted was significantly higher than that in the sampling time > 72h group, and the proportion of antifungal and

This research investigates the aerodynamic forces and moments acting on a windsurfing sail during steady sailing. We performed wind tunnel experiments on a scaled-down sail model to measure the aerodynamic forces and moments at varying angles of attack and rig-back (swept-back). The study found that increasing the rig-back angle resulted in lower lift, drag, rolling moment coefficients and lift-to-drag ratio. Using kinematic considerations, the aerodynamic data was transformed into key performance parameters, including driving force, side force, and rolling moment. The study emphasis on the sail's aerodynamic rolling moment by taking into account a maximum righting moment threshold from the sailor. This threshold can restrict the maximum achievable driving force from the sail, and is particularly important at high apparent wind speeds. The study suggests that higher rig-back angles can be beneficial when the maximum driving force is restricted by the moment threshold. In these conditions, the reduction in sail rolling moment from a higher rig-back angle can offset the potential reduction in lift-to-drag ratio. This finding provides valuable insights into the optimal techniques for improving windsurfing performance under steady sailing conditions. This study contributes to the understanding of the underlying physical principles governing windsurfing and provides a basis for further research in this area.

Non-volatile reconfigurable devices have the potential to improve integration levels and lower power consumption in next-generation electronics. Two-dimensional semiconductors are promising materials for making non-volatile reconfigurable devices due to their atomic thinness and strong gate control, but it is challenging to create varied reconfigurable functions with a simple device configuration. Here we show that an effective-gate-voltage-programmed graded-doping strategy can be used to create a single-gate two-dimensional molybdenum ditelluride device with multiple reconfigurable functions. The device can be programmed to function as a polarity-switchable diode, memory, in-memory Boolean logic gates and artificial synapses with homosynaptic plasticity and heterosynaptic plasticity. As a diode, the device exhibits a rectification ratio of up to 104; as an artificial heterosynapse, it shows heterosynaptic metaplasticity with a modulatory power consumption that can be reduced to 7.3 fW. An effective-gate-voltage-programmed graded-doping method can be used to reconfigure a single-gate molybdenum ditelluride device to different states, including a polarity-switchable diode, memory, Boolean logic and artificial synapse.

Xin Zhao,1,&ast; Pingyuan Ge,1,&ast; Shaohua Lei,1 Siqi Guo,1 Peng Zhou,1 Li Zhao,1 Yiyu Qi,1 Xiaotong Wei,2 Weizhen Wu,2 Ningjing Wang,2 Rui Guo,3 Nianyun Yang,1 Qingqing Xiao,1 Qichun Zhang,1,2 Huaxu Zhu1 1Department of Traditional Chinese Medicine Processing and Preparation, Nanjing University of Chinese Medicine, Nanjing, Jiangsu, People’s Republic of China; 2Jiangsu Key Laboratory for Pharmacology and Safety Evaluation of Chinese Materia Medica, School of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, People’s Republic of China; 3School of Medicine and Holistic Integrative Medicine, Nanjing University of Chinese Medicine, Nanjing, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Qichun Zhang; Huaxu Zhu, Email zhangqichun@njucm.edu.cn; zhuhx@njucm.edu.cnIntroduction: Neuroinflammation is one of the major pathogeneses in Alzheimer’s disease (AD) and mainly involves abnormal inflammatory activation of microglia by multiple pathological stimuli. The treatment of AD remains a major challenge due to the multifactorial characterization of AD and the inefficient ability of therapeutic drugs to permeate through the blood‒brain barrier (BBB). Accordingly, drug combination treatment and drug carrier delivery have become important therapeutic tools for the treatment of multifactorial diseases, especially AD.Methods: Inflammatory cytokine levels in microglia, including NO, TNF-α, IL-1β, IL-4, and IL-10, were detected. The Morris water maze and object location task were used to investigate the learning and memory functions of APP/PS1 mice in different treatment groups. The number of neurons and plasticity of synapses were evaluated by immunofluorescence double labelling. Additionally, the ratio of β-amyloid plaques and the number of activated microglia were evaluated by immunofluorescence staining. The concentrations of β-amyloid plaques and inflammatory factors in the hippocampus were determin

Zequn Zhuang,1,&ast; Peng Zhou,1,&ast; Jing Wang,2 Xiaojing Lu,1 Yigang Chen1– 3 1Department of General Surgery, the Affiliated Wuxi No.2 People’s Hospital of Nanjing Medical University, Wuxi, People’s Republic of China; 2Jiangnan University Medical Center, Wuxi, People’s Republic of China; 3Wuxi Clinical College, Nantong University, Wuxi, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Yigang Chen, Department of General Surgery, the Affiliated Wuxi No.2 People’s Hospital of Nanjing Medical University, Wuxi, People’s Republic of China, Email 9862023226@jiangnan.edu.cnAbstract: Presently, obesity has emerged as a significant global public health concern due to its escalating prevalence and incidence rates. The gut microbiota, being a crucial environmental factor, has emerged as a key player in the etiology of obesity. Nevertheless, the intricate and specific interactions between obesity and gut microbiota, along with the underlying mechanisms, remain incompletely understood. This review comprehensively summarizes the gut microbiota characteristics in obesity, the mechanisms by which it induces obesity, and explores targeted therapies centered on gut microbiota restoration.Keywords: gut microbiota, obesity, dysbiosis, metabolism

Ducted propellers show large applicability in urban air mobility applications due to their operational safety, increased aerodynamic performance and noise reduction potential. In this work, we study the effect of the duct's lip design on the aerodynamics and aeroacoustics of ducted propellers in hover with numerical simulations, which are validated with experiments. Steady numerical simulations were conducted first to efficiently evaluate the impact of the lip design on the aerodynamic performance. The results show how the design of the lip affects the uniformity of the incoming flow to the propeller and the pressure distribution on the duct. Based on these results, an improved lip geometry is proposed, whose noise generation is investigated with delayed detached eddy simulations and the noise radiation to the far field is computed using the integral solution of the Ffowcs-Williams and Hawkings equation. The experimental results show reasonable agreement regarding thrust generation and far-field noise. The spectrum and directivity of the aerodynamic noise are compared, and the primary noise sources are identified in the leading edge and tip of the propeller.

A unique challenge of the urban air mobility noise assessment is the configuration-dependent acoustic signature of different designs, of which the installed noise sources must be considered. This work presents a computational aeroacoustics study of a four-rotor urban air mobility vehicle, focusing on near-field propagation considering the installation effects of different vehicle components. The aerodynamic noise sources are computed using the delayed detached eddy simulations, in which the interactional aerodynamics of the rotating propulsion sources and the airframe are addressed. The acoustic propagation effects are calculated by solving Pierce’s equation using the computed mean flow fields and the surface noise sources. The proposed approach is expected to capture the noise scattering from the rotor supports and the fuselage, which cannot be simulated by conventional computational fluid dynamics. The near-field results are then extrapolated to the far field and compared with those from the Ffowcs-Williams and Hawkings acoustic-analogy-based solver. This research provides an integrated aerodynamic and acoustic effects evaluation which should benefit low-noise vehicle design.

While various aerodynamic noise generation mechanisms and characteristics have been extensively studied for drone research, the noise features during the descending flight state have not been well addressed. In this work, we investigate the aerodynamics and aeroacoustics of a two-bladed drone rotor operating in descent using both experimental and numerical approaches. First, we measure the rotor thrust and torque in an anechoic wind tunnel at various rotational speeds and descent rates. The results reveal a significant loss of mean thrust and strong thrust fluctuations with the increase of descent rates due to the formation of highly unsteady vortex rings. The measured acoustic spectra show multiple humps occurring at the blade passing frequency and its harmonics. Next, we perform numerical simulations based on the delayed detached eddy simulations to gain more understanding of the noise generation mechanisms. The computed integrated aerodynamic forces and acoustic spectra agree well with the experimental results. We present nearfield flow structures that demonstrate the gradual formation process of the vortex ring and the complex turbulent wake structures. Notably, the computed aeroacoustic characteristics exhibit a similar tendency with respect to the descent rate to the experimental results. Moreover, the simulation results suggest that the additional noise has a radiation directivity in the axial direction perpendicular to the rotation plane. Finally, we conduct a noise source analysis on the blade surface based on the simulation results, revealing that the strong leading-edge sources are likely related to the blade-wake interaction process during descending flight. © 2023 American Physical Society.

H2O2-fueled micromotors are state-of-the-art mobile microreactors in environmental remediation. In this work, a magnetic FeOx@MnO2@SiO2 micromotor with multi-functions is designed and demonstrated its catalytic performance in H2O2/peroxymonosulfate (PMS) activation for simultaneously sustained motion and organic degradation. Moreover, this work reveals the correlations between catalytic efficiency and motion behavior/mechanism. The inner magnetic FeOx nanoellipsoids primarily trigger radical species (OH and O2−) to attack organics via Fenton-like reactions. The coated MnO2 layers on FeOx surface are responsible for decomposing H2O2 into O2 bubbles to provide a propelling torque in the solution and generating SO4− and OH for organic degradation. The outer SiO2 microcapsules with a hollow head and tail result in an asymmetrical Janus structure for the motion, driven by O2 bubbles ejecting from the inner cavity via the opening tail. Intriguingly, PMS adjusts the local environment to control over-violent O2 formation from H2O2 decomposition by occupying the Mn sites via inter-sphere interactions and enhances organic removal due to the strengthened contacts and Fenton-like reactions between inner FeOx and peroxides within the microreactor. The findings will advance the design of functional micromotors and the knowledge of micromotor-based remediation with controlled motion and high-efficiency oxidation using multiple peroxides.

The last-mile delivery based on drones can cause severe noise pollution. For each individual vehicle, the noise emission feature is dependent on the operation modes, and the perceived noise levels at given observers vary with the flights. The environmental noise impact is further complicated if there are multiple vehicles to achieve the given tasks. In this work, we propose an optimization method for drone scheduling in a vehicle routing problem to reduce the en-route sound exposure of drones. A three-step hybrid method is employed, including cluster construction, cluster adjustment, and route establishment. The customers at different positions are firstly classified into clusters according to their relative positions. The clusters are then modified according to the noise characteristics and assigned to different drones to conduct delivery tasks. Finally, the visiting sequence is optimized for each drone according to the noise exposure level. The core task of flight path optimization is the efficient estimation of the drone noise distribution in the community environment using an established virtual flight noise simulation platform. The computed sound distributions are employed to determine the cost function for optimization. In this work, the strategy is applied to the delivery tasks in a representative urban community. Results show that this approach can effectively reduce the accumulated noise exposure for mass delivery tasks. This study provides a promising approach for low-noise multi-drone operation management in future green smart cities. © 2023 Proceedings of the International Congress on Sound and Vibration. All rights reserved.

The interaction between two contra-rotating co-axial propellers leads to variations in noise strength during the rotation and presents challenges for traditional acoustic measurement methods. In this work, we propose using a wavelet-based beamforming method to study the transient noise generation characteristics of the contra-rotating co-axial propellers. Compared to the conventional beamforming method, the wavelet-based beamforming method can address unsteady and high-speed moving noise sources in the time-frequency domain. A representative set-up is considered herein. The acoustic imaging results show that the transient noise sources increase after the overlap of the propellers and are dominant on the aft propeller, particularly at high frequencies and low rotating speeds. At relatively high rotating speeds, the results show that the contra-rotating propellers noise can be generated at the trailing edge near the hub of the propellers. Overall, the wavelet-based beamforming method deepens the physical understanding of transient aerodynamic and aeroacoustic processes, and could find applications in the design of low-noise contra-rotating propellers.

The aerodynamic and aeroacoustic characteristics of ducted propellers are studied with numerical simulations to investigate the effect of modifying the duct's expansion ratio. Steady simulations were conducted to efficiently obtain the mean flow field and the generated thrust. The results show that the downstream wake is sensitive to the duct's geometry. Slightly divergent ducts are found to maximize the total thrust, minimizing flow separation on the inner wall and reducing the wake speed while increasing the suction on the lip of the duct. The near-field transient flow field was obtained through delayed detached eddy simulations to analyze the noise characteristics. Far-field noise predictions were obtained with integral solutions of the Ffowcs-Williams and Hawkings (FW-H) equation. The spectra and directivity of the aerodynamic noise are compared for relevant cases. The present results reveal that divergent ducts can reduce the level of tonal noise at all observer angles, but they increase broadband noise. Consequently, diffusing ducts offer superior aerodynamic performance while also reducing tonal noise at the cost of higher broadband noise. The differences between the divergent ducts are limited, as the wake speed does not change significantly due to flow separation. The main noise generation is identified to be located on the propeller tip and leading edge. The results of this study deepen the understanding of the influence of the duct's geometrical design on the aerodynamic and aeroacoustic performance of ducted propellers. © 2023 Proceedings of the International Congress on Sound and Vibration. All rights reserved.

Human rotavirus (HRV) is the causative agent of severe dehydrating diarrhea in children under the age of five, resulting in up to 215,000 deaths each year. These deaths almost exclusively occur in low- and middle-income countries where vaccine efficacy is the lowest due to chronic malnutrition, gut dysbiosis, and concurrent enteric viral infection. Parenteral vaccines for HRV are particularly attractive as they avoid many of the concerns associated with currently used live oral vaccines. In this study, a two-dose intramuscular (IM) regimen of the trivalent, nanoparticle-based, nonreplicating HRV vaccine (trivalent S60-VP8*), utilizing the shell (S) domain of the capsid of norovirus as an HRV VP8* antigen display platform, was evaluated for immunogenicity and protective efficacy against P[6] and P[8] HRV using gnotobiotic pig models. A prime–boost strategy using one dose of the oral Rotarix® vaccine, followed by one dose of the IM trivalent nanoparticle vaccine was also evaluated. Both regimens were highly immunogenic in inducing serum virus neutralizing, IgG, and IgA antibodies. The two vaccine regimens failed to confer significant protection against diarrhea; however, the prime–boost regimen significantly shortened the duration of virus shedding in pigs challenged orally with the virulent Wa (G1P[8]) HRV and significantly shortened the mean duration of virus shedding, mean peak titer, and area under the curve of virus shedding after challenge with Arg (G4P[6]) HRV. Prime–boost-vaccinated pigs challenged with P[8] HRV had significantly higher P[8]-specific IgG antibody-secreting cells (ASCs) in the spleen post-challenge. Prime–boost-vaccinated pigs challenged with P[6] HRV had significantly higher numbers of P[6]- and P[8]-specific IgG ASCs in the ileum, as well as significantly higher numbers of P[8]-specific IgA ASCs in the spleen post-challenge. These results suggest the promise of and warrant further investigatio

Industrial and disinfection wastewater typically contains high levels of organic pollutants and residue hydrogen peroxide, which have caused environmental concerns. In this work, dual-asymmetric MnO2@polymer microreactors are synthesized via pollutant polymerization for self-driven and controlled H2O2 decomposition. A hollow and asymmetric MnO2 nanotube is derived from MnO2 nanorods by selective acid etching and then coated by a polymeric layer from an aqueous phenolic pollutant via catalytic peroxymonosulfate (PMS)-induced polymerization. The evolution of particle-like polymers is controlled by solution pH, molar ratios of PMS/phenol, and reaction duration. The polymer-covered MnO2 tubing-structured micromotors presented a controlled motion velocity, due to the reverse torque driven by the O2 bubbles from H2O2 decomposition in the inner tunnels. In addition, the partially coated polymeric layer can regulate the exposure and population of Mn active sites to control the H2O2 decomposition rate, thus avoiding violent motions and massive heat caused by vigorous H2O2 decomposition. The microreactors can maintain the function of mobility in an ultra-low H2O2 environment ( < 0.31 wt.%). This work provides a new strategy for the transformation of micropollutants to functional polymer-based microreactors for safe and controlled hydrogen peroxide decomposition for environmental remediation.

Human rotavirus (HRV) is a leading cause of viral gastroenteritis in children across the globe. The virus has long been established as a pathogen of the gastrointestinal tract, targeting small intestine epithelial cells and leading to diarrhea, nausea, and vomiting. Recently, this classical infection pathway was challenged by the findings that murine strains of rotavirus can infect the salivary glands of pups and dams and transmit via saliva from pups to dams during suckling. Here, we aimed to determine if HRV was also capable of infecting salivary glands and spreading in saliva using a gnotobiotic (Gn) pig model of HRV infection and disease. Gn pigs were orally inoculated with various strains of HRV, and virus shedding was monitored for several days post-inoculation. HRV was shed nasally and in feces in all inoculated pigs. Infectious HRV was detected in the saliva of four piglets. Structural and non-structural HRV proteins, as well as the HRV genome, were detected in the intestinal and facial tissues of inoculated pigs. The pigs developed high IgM antibody responses in serum and small intestinal contents at 10 days post-inoculation. Additionally, inoculated pigs had HRV-specific IgM antibody-secreting cells present in the ileum, tonsils, and facial lymphoid tissues. Taken together, these findings indicate that HRV can replicate in salivary tissues and prime immune responses in both intestinal and facial lymphoid tissues of Gn pigs.

Through anechoic wind tunnel tests, this study comprehensively investigates the noise and drag reductions on a circular cylinder with dimples. Dimples built on a surface pattern fabric cover the cylinder surface as one of the passive flow control methods. The force, noise, and flow field measurements are performed at diameter-based Reynolds numbers ranging from 3 x 10( 4) to 1.3 x 10 (5), covering the sub-critical, critical, and supercritical regimes. The force and noise measurement results show that dimple fabric simultaneously reduces noise and drag in the critical regime. The changes in flow structures were characterized by the Time-resolved Particle Image Velocimetry (TR-PIV) measurements. Based on the vortex sound theory, the flow analysis shows that the dominant sound sources are found to be concentrated near the cylinder surface, which is caused by the unsteady vortex motions near the separation locations during the process of vortex shedding. The cross-correlation between the synchronized TR-PIV and microphone measurements further supports the conclusions. Moreover, the cylinder noise reductions controlled by the dimples are directly associated with the reduced sound sources in the critical and supercritical regimes, corresponding to the reduced strength of the vortex shedding.

This study experimentally investigates the potential of using surface pattern fabrics for the cylinder noise and drag control in different Reynolds number ranges. The aerodynamic and aeroacoustic effects were evaluated through the noise and force measurements in an anechoic wind tunnel. It was observed that the noise and drag reductions take place simultaneously but in different Reynolds number ranges, corresponding to the cylinder flow in different flow regimes, e.g., sub-critical, critical, and supercritical flow regimes. Microphone arc array measurements reveal that the suppression of the Aeolian tone in the critical regime is the major cause of noise reductions, and the noise directivity gradually loses dipole features in the critical and supercritical flow regimes, which is probably related to the reduced lift fluctuation coefficient and the spanwise segment of the sound sources. Further hotwire wake survey revealed significant changes in flow dynamics, which explain the variations of noise and drag in different flow regimes. We have shown for the first time that fabric with different surface patterns can effectively reduce cylinder drag and noise in different Reynolds number ranges. Since the Reynolds number is a key factor that determines the flow state in practical engineering applications, e.g., cycling aerodynamics, this study suggests that optimal drag and noise reductions can be realized by employing the combinations of different surface pattern fabrics to account for the Reynolds number effects.

In this work, the noise impact of delivery drones in an urban community is assessed based on a flight simulation and noise assessment platform. The tonal and broadband noise components are considered using analytical and semi-analytical prediction methods. The noise propagation in the urban environment is computed using an efficient Gaussian beam tracing method. The influence of flight speeds, payloads and ground vegetation on noise reception at different observation locations are investigated. The instantaneous sound level can be higher if the drone is operated at a relatively higher speed. However, the overall sound exposure might be lower because of the shorter flight time. Similarly, the drone with a heavier payload could be louder, but in the meanwhile, fewer flight times are required. The platform provides an economical approach to understanding the effect of those competing influential factors, which are essential for the following low-noise flight path planning.

Artificial lights can cause critical microbial biodeterioration of heritage monuments by promoting the outbreak of phototrophic microbiomes when they are used for touristic viewing. Here, with the ultimate aim of providing innovative solutions for the conservation and visiting of such monuments, we conducted a pioneering two-year in situ manipulative experiment to evaluate the impacts of different artificial light wavelengths (i.e., blue, green and red lights compared to white light) on the phototrophic microbiome of a millennial Chinese imperial mausoleum. Our results show that artificial light can shape the ecophysiological features of the phototrophic bacteriome in this monument and reduce its potential for further biodeterioration. In general, Cyanobacteria dominated (42.0% of the total relative abundance) the phototrophic bacteriome of this cultural relic; however, they were also very sensitive to the choice of artificial light. Compared to white light, monochromatic light, especially green light, reduced Cyanobacteria abundances (18.6%) by decreasing photosynthetic pigment abundances (42.9%); decreased the abundances of heterotrophic species belonging to Proteobacteria (4.5%) and the proportion of genes (6.1%) associated with carbon (i.e., carbon fixation), nitrogen (i.e., denitrification), and sulfur (i.e., dissimilatory sulfate reduction) cycling; and further decreased organic acid (10.1–14.1%) production of the phototrophic bacteriome, which is known to be involved in biodeterioration. Taken together, our findings constitute a major advancement in understanding how light wavelengths influence the phototrophic microbiome in cultural relics, and we found that artificial lights with certain wavelengths (e.g., green light) can help long-term conservation while allowing tourism activities

Yi-Jin Wu,1– 3,* Sa-Sa Zhang,1,* Qin Yin,1 Ming Lei,2 Qi-Hai Wang,4 Wen-Gang Chen,1 Ting-Ting Luo,1 Peng Zhou,5 Cong-Lan Ji4,6 1Department of Pharmacy, The Second Affiliated Hospital of Wannan Medical College, Wuhu, 241000, People’s Republic of China; 2Xin’an Medical Research Center, The First Affiliated Hospital of Wannan Medical College, Wuhu, 241000, People’s Republic of China; 3Vascular Diseases Research Center of Wannan Medical College, Wuhu, 241000, People’s Republic of China; 4School of Pharmacy, Anhui College of Traditional Chinese Medicine, Wuhu, Anhui, 241000, People’s Republic of China; 5School of Integrated Chinese and Western Medicine, Anhui University of Chinese Medicine, Hefei, 230000, People’s Republic of China; 6Research Center of Integration of Traditional Chinese and Western Medicine, Wannan Medical College, Wuhu, 241000, People’s Republic of China*These authors contributed equally to this workCorrespondence: Peng Zhou; Cong-Lan Ji, Email zhoupeng@ahtcm.edu.cn; 37709103@qq.comBackground: α-Mangostin (MG) showed the potentials in alleviating experimental arthritis, inhibiting inflammatory polarization of macrophages/monocytes, and regulating peroxisome proliferators-activated receptor γ (PPAR-γ) and silent information regulator 1 (SIRT1) signals. The aim of this study was to analyze the correlations among the above-mentioned properties.Methods: Antigen-induced arthritis (AIA) was established in mouse, which was treated with MG in combination with SIRT1/PPAR-γ inhibitors to clarify the role of the two signals in the anti-arthritic actions. Pathological changes were systematically investigated. Phenotypes of cells were investigated by flow cytometry. Expression and co-localization of SIRT1 and PPAR-γ proteins in joint tissues were observed by the immunofluorescence method. Finally, clinical implications from the synchronou

The aeroacoustic characteristics of flying vehicles with pitch-fixed rotors differ from traditional helicopters with pitch-controlled rotor blades. Accurate predictions of rotor noise are still challenging because many uncertainty factors and unsteadinesses exist. This work investigates the aeroacoustic effects of rotational speed deviation, rotation speed fluctuation, blade vibration and blade geometric asymmetry. The analysis is based on the efficient computation of rotor noise under different working conditions. The mean aerodynamic variables are computed using the blade element moment theory, while small-amplitude fluctuations are introduced to account for the unsteadiness and uncertainty factors. It is shown that periodic rotation speed fluctuations and blade vibrations can produce significant extra tones. By contrast, if the fluctuations and vibrations are random, the noise level in a wide frequency range is increased. The intriguing result reminds us of the need to revisit the rotor broadband noise sources commonly attributed to turbulent flows. The influences are observer angle dependent, and the extra noise production is more significant in the upstream and downstream directions. The asymmetric blade geometry can cause extra tonal noise at the harmonics of the blade shaft frequency. The noise features of dual rotors are also investigated. Usually, the noise is sensitive to the initial phase difference and rotation directions due to the interference effect. However, the noise features are vastly altered if there are slight differences in the rotation speeds. Although the influences of some factors on rotor noise were already known, the present study provides a more comprehensive analysis of the problem. The results also highlight the need to consider these practical factors for accurate noise prediction of multi-rotor flying vehicles. © The Author(s), 2023. Published by Cambridge University Press.