Particle breakage in gap-graded soil

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The influence of particle shape and mineralogy on the particle strength, breakage and compressibility

It is widely accepted that both particle shape and mineralogy could have a great effect on the particle strength. However, due to the complexity of nature grains, it is difficult to distinguish the influence of particle shape from mineralogy. This paper shows measurements of the particle shape and mineralogy of carbonate sand, completely decomposed granite, Leighton Buzzard sand and pumice sand. The particle shape of carbonate sand and completely decomposed granite is similar, but the mineral of carbonate sand is carbon dioxide while the mineral of completely decomposed granite is mica and feldspar. It is found that the single particle strength of completely decomposed granite is higher than that of carbonate sand, and the particle breakage caused by one-dimensional compressing tests of completely decomposed granite is higher than that of carbonate sand. The mineralogy of both completely decomposed granite and Leighton Buzzard sand are quartz, but completely decomposed granite is more heterogeneous, result in the single particle strength of completely decomposed granite is much lower than that of Leighton Buzzard sand. It is also found the particle breakage from the one-dimensional compression test for completely decomposed is larger than Leighton Buzzard sand. It should be noted that carbonate sand is stronger than completely decomposed granite after quantitatively analysis the particle shape, particle breakage and compressibility behavior although carbonate sand has extremely irregular shape such as a branch shape, and also several pores. On the other hand, although Leighton Buzzard sand, completely decomposed granite and also pumice sand to some extent have composition of silica, the crystal of those three is completely different, result in the strength or compressibility are quite different. It seems that particle shape is not a major factor to affect strength or compressibility, but the mineralogy could be a major factor

Adaptive Localisation for Unmanned Surface Vehicles Using IMU-Interacting Multiple Model

Unscented Kalman Filter (UKF) remains to be a prevalent multi-sensor fusion method in many practices, including navigational tracking for Unmanned Surface Vehicles (USVs). This paper suggests that results from UKF fusion is unsatisfactory for USVs’ relatively smooth path due to UKF’s lack of versatility. Hence, it is proposed here that by replacing the UKF with Interacting Multiple Model (IMM), estimation results will better represent USV’s movement. Furthermore, this paper proposes slight modification to the IMM in order to heighten the algorithm’s confidence in switching modes. By exploiting angular velocity information from Inertial Measurement Unit (IMU), an independent mode probability can be obtained which is then injected into the IMM. Computer simulations based on maritime operations were done to show that the proposed IMU-based IMM is able to react faster to mode changes, giving more reliable outcomes

Early life adversity induced third ventricular enlargement in young adult male patients suffered from major depressive disorder: a study of brain morphology

Background: Early life adversity (ELA) is not uncommon in major depressive disorder (MDD) patients. Childhood trauma has been reported more frequently in adult MDD patients relative to healthy controls. Recent researches have demonstrated that ELA could result in changes in brain morphology which might be an aetiological factor of MDD development.Materials and methods: We recruited 40 young adult patients suffered from MDD and made computed tomography scan. Subjects were divided in two groups: MDD patients with ELA experience (E+D) vs. MDD patients without ELAexperience (E–D) according to Chinese version-Childhood Trauma Questionnaire (CTQ). 17-item Hamilton Depression (HAMD) Scale and Neuropsychiatric Inventory (NPI) were also examined. Student’s t-test was used to compare the HAMD scores, NPI scores, CTQ subcomponents scores, third ventricular (TV) width and volume of patients from E+D and E–D groups.Results: Findings demonstrated that ELA might result in TV enlargement; furthermore, there was a correlation between physical neglect and TV volume.Conclusions: These findings supported the hypothesis that ELA could induce changes of structure around the TV, which might undermine the aetiology of MDD

An Equivalent Circuit Model for Predicting the Core Loss in a Claw-Pole Permanent Magnet Motor with Soft Magnetic Composite Core

© 1965-2012 IEEE. Soft magnetic composite (SMC) materials and SMC electromagnetic devices have attracted strong research interest in the past decades. However, SMC devices have large core loss that needs to be put into consideration even at the design stage. Effective and accurate prediction of the core loss becomes crucial for the design and optimization of high-performance motors with these materials. Equivalent circuit model is a widely used method for machine analysis, due to the advantages in the fast calculation with a clear physical mechanism. This paper presents an equivalent circuit model to predict the core loss of a claw-pole permanent magnet motor with SMC stator core. All the parameters including the equivalent core-loss resistance in the equivalent circuit model are identified based on the finite-element method to achieve high accuracy, and the effectiveness of the parameters identification methods is experimentally verified. The proposed equivalent circuit model can predict the core loss and motor's performance efficiently both under no-load and loading conditions

Multiplex cytokine analysis of dermal interstitial blister fluid defines local disease mechanisms in systemic sclerosis.

Clinical diversity in systemic sclerosis (SSc) reflects multifaceted pathogenesis and the effect of key growth factors or cytokines operating within a disease-specific microenvironment. Dermal interstitial fluid sampling offers the potential to examine local mechanisms and identify proteins expressed within lesional tissue. We used multiplex cytokine analysis to profile the inflammatory and immune activity in the lesions of SSc patients

Deep Learning networks with p-norm loss layers for spatial resolution enhancement of 3D medical images

Thurnhofer-Hemsi K., López-Rubio E., Roé-Vellvé N., Molina-Cabello M.A. (2019) Deep Learning Networks with p-norm Loss Layers for Spatial Resolution Enhancement of 3D Medical Images. In: Ferrández Vicente J., Álvarez-Sánchez J., de la Paz López F., Toledo Moreo J., Adeli H. (eds) From Bioinspired Systems and Biomedical Applications to Machine Learning. IWINAC 2019. Lecture Notes in Computer Science, vol 11487. Springer, ChamNowadays, obtaining high-quality magnetic resonance (MR) images is a complex problem due to several acquisition factors, but is crucial in order to perform good diagnostics. The enhancement of the resolution is a typical procedure applied after the image generation. State-of-the-art works gather a large variety of methods for super-resolution (SR), among which deep learning has become very popular during the last years. Most of the SR deep-learning methods are based on the min- imization of the residuals by the use of Euclidean loss layers. In this paper, we propose an SR model based on the use of a p-norm loss layer to improve the learning process and obtain a better high-resolution (HR) image. This method was implemented using a three-dimensional convolutional neural network (CNN), and tested for several norms in order to determine the most robust t. The proposed methodology was trained and tested with sets of MR structural T1-weighted images and showed better outcomes quantitatively, in terms of Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM), and the restored and the calculated residual images showed better CNN outputs.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Applying local cooccurring patterns for object detection from aerial images

Developing a spatial searching tool to enhance the search car pabilities of large spatial repositories for Geographical Information System (GIS) update has attracted more and more attention. Typically, objects to be detected are represented by many local features or local parts. Testing images are processed by extracting local features which are then matched with the object's model image. Most existing work that uses local features assumes that each of the local features is independent to each other. However, in many cases, this is not true. In this paper, a method of applying the local cooccurring patterns to disclose the cooccurring relationships between local features for object detection is presented. Features including colour features and edge-based shape features of the interested object are collected. To reveal the cooccurring patterns among multiple local features, a colour cooccurrence histogram is constructed and used to search objects of interest from target images. The method is demonstrated in detecting swimming pools from aerial images. Our experimental results show the feasibility of using this method for effectively reducing the labour work in finding man-made objects of interest from aerial images. © Springer-Verlag Berlin Heidelberg 2007

Tunability and Robustness of Dirac Points of Photonic Nanostructures

We study the tunability and robustness of photonic Dirac points (DPs) in plasmonic nanostructures. The tunability of the DP is demonstrated in graphene-based photonic superlattices by adjusting the graphene permittivity via the optical Kerr effect or electrical doping. The robustness of DPs is demonstrated in plasmonic lattices by showing that even very high levels of disorder are unable to localize the modes located near the DP. The robustness of the DP also manifests itself in the fact that the inversely-proportional dependence of the transmission on the lattice length near the DP remains unchanged under strong disorder