Preparation and Properties of 1, 3, 5, 7-Tetranitro-1, 3, 5, 7-Tetrazocane-based Nanocomposites

A new insensitive explosive based on octahydro-1, 3, 5, 7-tetranitro-1, 3, 5, 7-tetrazocine (HMX) was prepared by spray drying using Viton A as a binder. The HMX sample without binder (HMX-1) was obtained by the same spray drying process also. The samples were characterised by Scanning Electron Microscope, and X-ray diffraction. The Differential Scanning Calorimetry and the impact sensitivity of HMX-1 and nanocomposites were also being tested. The nanocomposite morphology was found to be microspherical (1 μm to 7 μm diameter) and composed of many tiny particles, 100 nm to 200 nm in size. The crystal type of HMX-1 and HMX/Viton A agrees with raw HMX. The activation energy of raw HMX, HMX-1 and HMX/Viton A is 523.16 kJ mol-1, 435.74 kJ mol-1 and 482.72 kJ mol-1, respectively. The self-ignition temperatures of raw HMX, HMX-1 and HMX/Viton A is 279.01 °C, 277.63 °C, and 279.34 °C, respectively. The impact sensitivity order of samples is HMX/Viton A < HMX-1 < raw HMX from low to high.Defence Science Journal, Vol. 65, No. 2, March 2015, pp.131-134, DOI:http://dx.doi.org/10.14429/dsj.65.784

A Dataset And Benchmark Of Underwater Object Detection For Robot Picking

Underwater object detection for robot picking has attracted a lot of interest. However, it is still an unsolved problem due to several challenges. We take steps towards making it more realistic by addressing the following challenges. Firstly, the currently available datasets basically lack the test set annotations, causing researchers must compare their method with other SOTAs on a self-divided test set (from the training set). Training other methods lead to an increase in workload and different researchers divide different datasets, resulting there is no unified benchmark to compare the performance of different algorithms. Secondly, these datasets also have other shortcomings, e.g., too many similar images or incomplete labels. Towards these challenges we introduce a dataset, Detecting Underwater Objects (DUO), and a corresponding benchmark, based on the collection and re-annotation of all relevant datasets. DUO contains a collection of diverse underwater images with more rational annotations. The corresponding benchmark provides indicators of both efficiency and accuracy of SOTAs (under the MMDtection framework) for academic research and industrial applications, where JETSON AGX XAVIER is used to assess detector speed to simulate the robot-embedded environment

A New Dataset, Poisson GAN and AquaNet for Underwater Object Grabbing

To boost the object grabbing capability of underwater robots for open-sea farming, we propose a new dataset (UDD) consisting of three categories (seacucumber, seaurchin, and scallop) with 2,227 images. To the best of our knowledge, it is the first 4K HD dataset collected in a real open-sea farm. We also propose a novel Poisson-blending Generative Adversarial Network (Poisson GAN) and an efficient object detection network (AquaNet) to address two common issues within related datasets: the class-imbalance problem and the problem of mass small object, respectively. Specifically, Poisson GAN combines Poisson blending into its generator and employs a new loss called Dual Restriction loss (DR loss), which supervises both implicit space features and image-level features during training to generate more realistic images. By utilizing Poisson GAN, objects of minority class like seacucumber or scallop could be added into an image naturally and annotated automatically, which could increase the loss of minority classes during training detectors to eliminate the class-imbalance problem; AquaNet is a high-efficiency detector to address the problem of detecting mass small objects from cloudy underwater pictures. Within it, we design two efficient components: a depth-wise-convolution-based Multi-scale Contextual Features Fusion (MFF) block and a Multi-scale Blursampling (MBP) module to reduce the parameters of the network to 1.3 million. Both two components could provide multi-scale features of small objects under a short backbone configuration without any loss of accuracy. In addition, we construct a large-scale augmented dataset (AUDD) and a pre-training dataset via Poisson GAN from UDD. Extensive experiments show the effectiveness of the proposed Poisson GAN, AquaNet, UDD, AUDD, and pre-training dataset.Comment: 14 pages, 10 figure

EEG-based approach for recognizing human social emotion perception

Social emotion perception plays an important role in our daily social interactions and is involved in the treatments for mental disorders. Hyper-scanning technique enables to measure brain activities simultaneously from two or more persons, which was employed in this study to explore social emotion perception. We analyzed the recorded electroencephalogram (EEG) to explore emotion perception in terms of event related potential (ERP) and phase synchronization, and classified emotion categories based on convolutional neural network (CNN). The results showed that (1) ERP was significantly different among four emotion categories (i.e., anger, disgust, neutral, and happy), but there was no significant difference for ERP in the comparison of rating orders (the order of rating actions of the paired participants); (2) the intra-brain phase lag index (PLI) was higher than the inter-brain PLI but its number of connections exhibiting significant difference was less in all typical frequency bands (from delta to gamma); (3) the emotion classification accuracy of inter-PLI-Conv outperformed that of intra-PLI-Conv for all cases of using each frequency band (five frequency bands totally). In particular, the classification accuracies averaged across all participants in the alpha band were 65.55% and 50.77% (much higher than the chance level) for the inter-PLI-Conv and intra-PLI-Conv, respectively. According to our results, the emotion category of happiness can be classified with a higher performance compared to the other categories

Hydrodynamic analysis of a heave-hinge wave energy converter combined with a floating breakwater

Research interest in breakwater design has increased recently due to the impetus to develop marine renewable energy systems, as breakwaters can be retrofitted to harness wave energy at the same time as attenuating it. This study investigates a novel system of attaching a hinge baffle under a floating breakwater. The floating breakwater itself acts as a heaving wave energy converter, and meanwhile the hinge rotation provides a second mechanism for wave energy harnessing. A computational model with multi-body dynamics was established to study this system, and a series of simulations were conducted in various wave conditions. Both wave attenuation performance and energy conversion ratio were studied, using an interdisciplinary approach considering both coastal engineering and renewable energy. In particular, the performance of the proposed system is compared with contemporary floating breakwater designs to demonstrate its advantage. Overall, a useful simulation framework with multi-body dynamics is presented and the simulation results provide valuable insights into the design of combined wave energy and breakwater systems

Hydrodynamic analysis of a heave-hinge wave energy converter combined with a floating breakwater

Research interest in breakwater design has increased recently due to the impetus to develop marine renewable energy systems, as breakwaters can be retrofitted to harness wave energy at the same time as attenuating it. This study investigates a novel system of attaching a hinge baffle under a floating breakwater. The floating breakwater itself acts as a heaving wave energy converter, and meanwhile the hinge rotation provides a second mechanism for wave energy harnessing. A computational model with multi-body dynamics was established to study this system, and a series of simulations were conducted in various wave conditions. Both wave attenuation performance and energy conversion ratio were studied, using an interdisciplinary approach considering both coastal engineering and renewable energy. In particular, the performance of the proposed system is compared with contemporary floating breakwater designs to demonstrate its advantage. Overall, a useful simulation framework with multi-body dynamics is presented and the simulation results provide valuable insights into the design of combined wave energy and breakwater systems

Preparation and characterization of a novel triple composite scaffold containing silk fibroin, chitosan, extracellular matrix and the mechanism of Akt/FoxO signaling pathway in colonic cancer cells cultured in 3D

This work examined the physical and chemical properties and biocompatibility in vivo and in vitro of a unique triple composite scaffold incorporating silk fibroin, chitosan, and extracellular matrix. The materials were blended, cross-linked, and freeze-dried to create a composite scaffold of silk fibroin/chitosan/colon extracellular matrix (SF/CTS/CEM) with varying CEM contents. The SF/CTS/CEM (1:1:1) scaffold demonstrated the preferable shape, outstanding porosity, favorable connectivity, good moisture absorption, and acceptable and controlled swelling and degradation properties. Additionally, HCT-116 cells cultivated with SF/CTS/CEM (1:1:1) showed excellent proliferation capacity, cell malignancy, and delayed apoptosis, according to the in vitro cytocompatibility examination. We also examined the PI3K/PDK1/Akt/FoxO signaling pathway and discovered that cell culture using a SF/CTS/CEM (1:1:1) scaffold may prevent cell death by phosphorylating Akt and suppressing FoxO expression. Our findings demonstrate the potential of the SF/CTS/CEM (1:1:1) scaffold as an experimental model for colonic cancer cell culture and for replicating the three-dimensional in vivo cell growth environment

Nonlinear Simulation of Wave Train Impact on a Vertical Seawall

A 2D nonlinear numerical wave flume is developed to investigate the wave train impact on a vertical seawall. Fully nonlinear kinematic and dynamic boundary conditions are satisfied on the instantaneous free surface. Cases of single-, double- and multi-crest wave trains are discussed. For single-crest wave train cases, the present nonlinear results are compared with the solution of the Serre-Green-Naghdi (SGN) model, showing good agreement. For double-crest wave train cases, the SGN model underestimates the maximum wave run-up along the vertical seawall. Compared with the linear results, the nonlinearity for double-crest cases can lead to an evident increase of the wave run-up and high-frequency free-surface oscillations. Through a fast Fourier analysis, evident nonlinear characteristics of the time series of the wave run-up and wave load during the wave impact process are confirmed. For multi-crest wave train cases, irregular wave run-ups can be observed. In some cases, the wave run-up along the vertical seawall can reach about 6 times that of the incident wave, which should be considered carefully in a practical design

The Effects of Exogenous Benzoic Acid on the Physicochemical Properties, Enzyme Activities and Microbial Community Structures of <i>Perilla frutescens</i> Inter-Root Soil

This study analyzed the effects of benzoic acid (BA) on the physicochemical properties and microbial community structure of perilla rhizosphere soil. The analysis was based on high-throughput sequencing technology and physiological and biochemical detection. The results showed that with the increase in BA concentration, soil pH significantly decreased, while the contents of total nitrogen (TN), alkaline nitrogen (AN), available phosphorus (AP), and available potassium (AK) significantly increased. The activities of soil conversion enzymes urease and phosphatase significantly increased, but the activities of catalase and peroxidase significantly decreased. This indicates that BA can increase soil enzyme activity and improve nutrient conversion; the addition of BA significantly altered the composition and diversity of soil bacterial and fungal communities. The relative abundance of beneficial bacteria such as Gemmatimonas, Pseudolabrys, and Bradyrhizobium decreased significantly, while the relative abundance of harmful fungi such as Pseudogymnoascus, Pseudoeurotium, and Talaromyces increased significantly. Correlation analysis shows that AP, AN, and TN are the main physicochemical factors affecting the structure of soil microbial communities. This study elucidates the effects of BA on the physicochemical properties and microbial community structure of perilla soil, and preliminarily reveals the mechanism of its allelopathic effect on the growth of perilla