Clinical manifestations and imaging and pathological features of giant cell angioblastoma: Report of four cases and literature review

Giant cell angioblastoma is a relatively rare vasogenic tumour. To date, studies on its clinical manifestations, imaging characteristics, pathological features, and prognosis are extremely limited and unknown, with only a few cases recorded. In this study, four cases of giant cell angioblastoma confirmed by pathological examination were reported to improve our understanding and deep exploration of the tumour spectrum. All cases in our study were male, including two adults and two boys. The lesions were located in the lower segment of the femur, medial condyle of the femur, knee joint, and popliteal fossa. Regarding the imaging characteristics, two patients with lesions in bone showed bone destruction, while the other two had lesions that invaded soft tissues, showing irregular, abnormal signal shadows and obvious enhancement. Histopathological analysis revealed that the nodular tumour tissue was mainly composed of oval and spindle cells, with varying numbers of osteoclast-like multinucleated giant cells, and the interstitial tissues were often filled with blood vessels of different sizes. The immunophenotype demonstrates that endothelial cells of small vessels in nodules expressed CD31, SMA, and ERG, while osteoclast-like multinucleated giant cells and histiocytes expressed CD68 and CD163, and the surrounding cells expressed SMA. All four patients were treated with surgical resection. One of them relapsed 1 month after surgery and received a second surgical resection. No distant metastasis or death occurred during the follow-up period. This study indicates that giant cell angioblastoma is a local invasive vascular tumour that can develop both in children and adults with skin, mucous membrane, soft tissue, and bone involvement. Imaging characteristics show bone destruction and irregular, abnormal signal shadows; in addition, obvious pathological morphological features can be observed. Currently, the treatment is mainly surgical resection, and interferons may be used as adjuvant chemotherapy

Reconstructing the global stress of marine structures based on Artificial-Intelligence-Generated content

This paper proposes an approach that utilizes Artificial-Intelligence-Generated Content (AIGC) to overcome the constraints of Structural Health Monitoring (SHM) devices in capturing global stress with limited sensors. Feature elements are selected based on correlation analysis among finite elements and used as stress-measured points. An Artificial Neural Network (ANN) is used to establish the relationship between the feature and correlation elements. The proposed method is applied to the connector structure of an offshore platform, and an optimal ANN is established to optimize its performance by considering factors such as the number of sensors, the neural network framework, and the convergence criteria. The generalization performance of the ANN is validated through a real-scale model test, with deviations below 10% and an average deviation of less than 4% in multiple conditions, verifying its accuracy. This technology represents a significant advancement, enhancing the practicality of the SHM technology from “point monitoring” to “field monitoring”

An Algorithm for Mining of Association Rules for the Information Communication Network Alarms Based on Swarm Intelligence

Due to the centralized management of information communication network, the network operator have to face these pressures, which come from the increasing network alarms and maintenance efficiency. The effective analysis on mining of the network alarm association rules is achieved by incorporating classic data association mining algorithm and swarm intelligence optimization algorithm. From the related concept of the information communication network, the paper analyzes the data characteristics and association logic of the network alarms. Besides, the alarm data are preprocessed and the main standardization information fields are screened. The APPSO algorithm is proposed on the basis of combining the evaluation method for support and confidence coefficient in the Apriori (AP) algorithm as well as the particle swarm optimization (PSO) algorithm. By establishing a sparse linked list, the algorithm is able to calculate the particle support thus further improving the performance of the APPSO algorithm. Based on the test for the network alarm data, it is discovered that rational setting of the particle swarm scale and number of iterations of the APPSO algorithm can be used to mine the vast majority and even all of the association rules and the mining efficiency is significantly improved, compared with Apriori algorithm

An Analytical Method for Coaxial Helicopter Ground Resonance

A time-frequency analytical method is presented to analyze physical mechanism of coaxial helicopter ground resonance. Eigenvalue calculation and numerical integration of disturbance equations of motions are used to obtain modal characters and time-domain response characters of coaxial helicopter ground resonance, and the interaction between rotors and body is revealed according to response of various DOFs. The analysis results show that regressive lag mode with upper rotor character is the most instability mode. In dynamic instability region, coaxial helicopter ground resonance is mainly due to energy transferred between periodic lag motion of upper rotor and body roll rotation. For this instability mode, energy transferred between periodic lag motion of lower rotor and body roll rotation is also existed, and it can enhance ground resonance instability of coaxial helicopter

An Analytical Method for Coaxial Helicopter Ground Resonance

A time-frequency analytical method is presented to analyze physical mechanism of coaxial helicopter ground resonance. Eigenvalue calculation and numerical integration of disturbance equations of motions are used to obtain modal characters and time-domain response characters of coaxial helicopter ground resonance, and the interaction between rotors and body is revealed according to response of various DOFs. The analysis results show that regressive lag mode with upper rotor character is the most instability mode. In dynamic instability region, coaxial helicopter ground resonance is mainly due to energy transferred between periodic lag motion of upper rotor and body roll rotation. For this instability mode, energy transferred between periodic lag motion of lower rotor and body roll rotation is also existed, and it can enhance ground resonance instability of coaxial helicopter

Preparation of hydrogen from metals and water without CO2 emissions

Considering the high calorific value and low-carbon characteristics of hydrogen energy, it will play an important role in replacing fossil energy sources. The production of hydrogen from renewable energy sources for electricity generation and electrolysis of water is an important process to obtain green hydrogen compared with classic low-carbon hydrogen production methods. However, the challenges in this process include the high cost of liquefied hydrogen and the difficulty of storing hydrogen on a large scale. In this paper, we propose a new route for hydrogen storage in metals, namely, electricity generation from renewable energy sources, electrolysis to obtain metals, and subsequent hydrogen production from metals and water. Metal monomers facilitate large-scale and long-term storage and transportation, and metals can be used as large-scale hydrogen storage carriers in the future. In this technical route, the reaction between metal and water for hydrogen production is an important link. In this paper, we systematically summarize th

Preparation of hydrogen from metals and water without CO2 emissions

Considering the high calorific value and low-carbon characteristics of hydrogen energy, it will play an important role in replacing fossil energy sources. The production of hydrogen from renewable energy sources for electricity generation and electrolysis of water is an important process to obtain green hydrogen compared with classic low-carbon hydrogen production methods. However, the challenges in this process include the high cost of liquefied hydrogen and the difficulty of storing hydrogen on a large scale. In this paper, we propose a new route for hydrogen storage in metals, namely, electricity generation from renewable energy sources, electrolysis to obtain metals, and subsequent hydrogen production from metals and water. Metal monomers facilitate large-scale and long-term storage and transportation, and metals can be used as large-scale hydrogen storage carriers in the future. In this technical route, the reaction between metal and water for hydrogen production is an important link. In this paper, we systematically summarize th

The effects of compaction and interleaving on through-thickness electrical resistance and in-plane mechanical properties for CFRP laminates

The electrical conductivity of carbon fibre reinforced polymer (CFRP) laminates has previously been shown to be significantly improved by using different electrically functionalized interleaves - Functional Interleave Technology (FIT), particularly in through-thickness direction. Here, the mechanism of FIT is explored via the influence of compaction and interleaving of nickel plated polyester non-woven veils (NPVs) on through-thickness electrical conductivity and in-plane mechanical properties for the CFRP laminates are investigated. The through-thickness electrical property is found to be dominated by the electrically conductive network elements (carbon fibres) and components (carbon fibre layers and NPV layers), which, in turn, is strongly affected by compaction. By using the highly conductive NPVs, the through-thickness resistivity for cured FIT laminates was consistently lowered from 9.3 Ω⋅m to 0.48 Ω m and 1.54 Ω⋅m to 0.016 Ω m for 56% and 64% carbon fibre volume fraction laminates, respectively. The conductive mechanism of FIT specimens follows the series-resistor model, providing the potential to predict the through-thickness electrical conductivity (TTEC) value by interleaving the desired number of NPV layers. Investigation of in-plane mechanical properties indicates the flexural properties and interlaminar shear strength (ILSS) are less affected by compaction. Meanwhile, a 20% reduction of ILSS for FIT laminates is detected because of the lower intra-ply shear resistance of NPV layers

Mixed-dimensional Heterojunction by 3D CdS Nanowire Arrays Bridged with 2D WSe2 for Ultrafast Photoelectric Gas Sensor

Heterojunctions are of essential importance for electronic sensors due to their unique properties at the junctions. However, a planar junction made of two-dimensional (2D) materials commonly suffers from slow response and irreversible recovery because of slow physisorption and desorption rates. Herein, we present a unique design of a mixed-dimensional heterojunction built from patterned growth of 3D n-type CdS nanowire arrays and p-type 2D WSe2 nanosheets for photoelectric gas sensor. This heterojunction sensor showed highly selective and reversible response to NO2 and NH3 with detection limits of 60 and 54 ppb, respectively, under UV illumination at room temperature. Notably, the sensor exhibited ultrafast response time of less than 1s to 1 ppm NO2 and NH3, which outperforms most previous reports on NO2 and NH3 detection at room temperature. The outstanding sensing performance are attributed to the tuning of the Schottky barrier at the CdS/WSe2 heterojunction through the gas adsorption/desorption under UV excitation. The hybrid junction structure proposed herein will pave the way to engineer new electronic devices from a broad selection of materials to achieve improved sensing performances at room temperature