Parameter identification of JONSWAP spectrum acquired by airborne LIDAR

International audienceIn this study, we developed the first linear Joint North Sea Wave Project (JONSWAP) spectrum (JS), which involves a transformation from the JS solution to the natural logarithmic scale. This transformation is convenient for defining the least squares function in terms of the scale and shape parameters. We identified these two wind-dependent parameters to better understand the wind effect on surface waves. Due to its efficiency and high-resolution, we employed the airborne Light Detection and Ranging (LIDAR) system for our measurements. Due to the lack of actual data, we simulated ocean waves in the MATLAB environment, which can be easily translated into industrial programming language. We utilized the Longuet-Higgin (LH) random-phase method to generate the time series of wave records and used the fast Fourier transform (FFT) technique to compute the power spectra density. After validating these procedures, we identified the JS parameters by minimizing the mean-square error of the target spectrum to that of the estimated spectrum obtained by FFT. We determined that the estimation error is relative to the amount of available wave record data. Finally, we found the inverse computation of wind factors (wind speed and wind fetch length) to be robust and sufficiently precise for wave forecasting

Open Set Dandelion Network for IoT Intrusion Detection

As IoT devices become widely, it is crucial to protect them from malicious intrusions. However, the data scarcity of IoT limits the applicability of traditional intrusion detection methods, which are highly data-dependent. To address this, in this paper we propose the Open-Set Dandelion Network (OSDN) based on unsupervised heterogeneous domain adaptation in an open-set manner. The OSDN model performs intrusion knowledge transfer from the knowledge-rich source network intrusion domain to facilitate more accurate intrusion detection for the data-scarce target IoT intrusion domain. Under the open-set setting, it can also detect newly-emerged target domain intrusions that are not observed in the source domain. To achieve this, the OSDN model forms the source domain into a dandelion-like feature space in which each intrusion category is compactly grouped and different intrusion categories are separated, i.e., simultaneously emphasising inter-category separability and intra-category compactness. The dandelion-based target membership mechanism then forms the target dandelion. Then, the dandelion angular separation mechanism achieves better inter-category separability, and the dandelion embedding alignment mechanism further aligns both dandelions in a finer manner. To promote intra-category compactness, the discriminating sampled dandelion mechanism is used. Assisted by the intrusion classifier trained using both known and generated unknown intrusion knowledge, a semantic dandelion correction mechanism emphasises easily-confused categories and guides better inter-category separability. Holistically, these mechanisms form the OSDN model that effectively performs intrusion knowledge transfer to benefit IoT intrusion detection. Comprehensive experiments on several intrusion datasets verify the effectiveness of the OSDN model, outperforming three state-of-the-art baseline methods by 16.9%.Comment: Accepted by ACM Transactions on Internet Technolog

Nanodispersed UV blockers in skin-friendly silica vesicles with superior UV-attenuating efficiency

Using a pig ear skin model, it is demonstrated that silica vesicles show higher skin safety compared to dense silica nanoparticles with similar sizes. A hydrophobic UV blocker is efficiently dispersed in silica vesicles in an amorphous state, leading to ultrahigh UV-attenuating efficiency and a sun protection factor of 100 in a sunscreen formulation

Rechargeable aluminum–selenium batteries with high capacity

Rechargeable aluminum (Al) batteries are emerging as a promising post lithium-ion battery technology. Herein, we demonstrate a conceptually new design of rechargeable aluminum-selenium (Al-Se) batteries by understanding the selenium chemistry and controlling the electrode reaction. The Al-Se battery consists of a composite cathode including selenium nanowires and mesoporous carbon (CMK-3) nanorods, an Al metal anode and chloroaluminate ionic liquid electrolyte. The working mechanism of the Al-Se battery is the reversible redox reaction of the SeCl/Se pair confined in the mesopores of CMK-3 nanorods. Al-Se batteries deliver a high reversible capacity of 178 mA h g (by Se mass), high discharge voltages (mainly above 1.5 V), and good cycling/rate performances

Chinese Expert Consensus on Critical Care Ultrasound Applications at COVID-19 Pandemic

The spread of new coronavirus (SARS-Cov-2) follows a different pattern than previous respiratory viruses, posing a serious public health risk worldwide. World Health Organization (WHO) named the disease as COVID-19 and declared it a pandemic. COVID-19 is characterized by highly contagious nature, rapid transmission, swift clinical course, profound worldwide impact, and high mortality among critically ill patients. Chest X-ray, computerized tomography (CT), and ultrasound are commonly used imaging modalities. Among them, ultrasound, due to its portability and non-invasiveness, can be easily moved to the bedside for examination at any time. In addition, with use of 4G or 5G networks, remote ultrasound consultation can also be performed, which allows ultrasound to be used in isolated medial areas. Besides, the contact surface of ultrasound probe with patients is small and easy to be disinfected. Therefore, ultrasound has gotten lots of positive feedbacks from the frontline healthcare workers, and it has played an indispensable role in the course of COVID-19 diagnosis and follow up

Advances in silica based nanoparticles for targeted cancer therapy

Targeted delivery of anticancer drug specifically to tumor site without damaging normal tissues has been the dream of all scientists fighting against cancer for decades. Recent breakthrough on nanotechnology based medicines has provided a possible tool to solve this puzzle. Among diverse nanomaterials that are under development and extensive study, silica based nanoparticles with vast advantages have attracted great attention. In this review, we concentrate on the recent progress using silica based nanoparticles, particularly mesoporous silica nanoparticles (MSNs), for targeted drug delivery applications. First, we discuss the passive targeting capability of silica based nanoparticles in relation to their physiochemical properties. Then, we focus on the recent advances of active targeting strategies involving tumor cell targeting, vascular targeting, nuclear targeting and multistage targeting, followed by an introduction to magnetic field directed targeting approach. We conclude with our personal perspectives on the remaining challenges and the possible future directions

ANALYSIS OF THE STRESS CHARACTERISTICS OF CFG PILE COMPOSITE FOUNDATION UNDER IRREGULARITY CONDITION

By the excitation load function corresponding to the irregularity management standard the vertical load of the train is simulated. Based on the finite difference software FLAC3D the three-dimensional dynamic coupling finite difference model of track-embankment-pile-soil composite foundation is established. Focuses on the analysis of the dynamic response characteristics of the embankment, pile and soil foundation caused by the change of foundation, pile and cushion elastic modulus and cushion thickness. Results show: by the excitation load, the centre pile dynamic stresses are maximum, piles dynamic stress away from the centre side pile decreases gradually. The dynamic response of the pile and soil caused by subgrade surface elastic modulus variation has a little effect with more obvious by the cushion effect. With the increase of elastic modulus and thickness of cushion, the dynamic interaction between pile and cushion is increased while the dynamic interaction between soil and cushion is weakened. Therefore, the bearing capacity of the pile is fully utilized. With the increase of the elastic modulus of the pile, the dynamic stress of pile top increases correspondingly, but the dynamic stress increases gradually, and the pile bears most of the load, thus effectively reduce the dynamic load of the foundation soil

ANALYSIS OF THE STRESS CHARACTERISTICS OF CFG PILE COMPOSITE FOUNDATION UNDER IRREGULARITY CONDITION

By the excitation load function corresponding to the irregularity management standard the vertical load of the train is simulated. Based on the finite difference software FLAC3D the three-dimensional dynamic coupling finite difference model of track-embankment-pile-soil composite foundation is established. Focuses on the analysis of the dynamic response characteristics of the embankment, pile and soil foundation caused by the change of foundation, pile and cushion elastic modulus and cushion thickness. Results show: by the excitation load, the centre pile dynamic stresses are maximum, piles dynamic stress away from the centre side pile decreases gradually. The dynamic response of the pile and soil caused by subgrade surface elastic modulus variation has a little effect with more obvious by the cushion effect. With the increase of elastic modulus and thickness of cushion, the dynamic interaction between pile and cushion is increased while the dynamic interaction between soil and cushion is weakened. Therefore, the bearing capacity of the pile is fully utilized. With the increase of the elastic modulus of the pile, the dynamic stress of pile top increases correspondingly, but the dynamic stress increases gradually, and the pile bears most of the load, thus effectively reduce the dynamic load of the foundation soil