In order to predict the corrosion depth of a district heating pipeline, it is necessary to analyze various corrosion factors. In this study, the relationship between corrosion factors such as pH, ...dissolved oxygen, and operating time and corrosion depth was investigated using the Box-Behnken method within the response surface methodology. To accelerate the corrosion process, galvanostatic tests were conducted in synthetic district heating water. Subsequently, a multiple regression analysis was performed using the measured corrosion depth to derive a formula for predicting the corrosion depth as a function of the corrosion factors. As a result, the following regression formula was derived for predicting the corrosion depth: "corrosion depth (μm) = -133 + 17.1 pH + 0.00072 DO + 125.2 Time - 7.95 pH × Time + 0.002921 DO × Time".
Delamination is one of the detrimental defects in laminated composite materials that often arose due to manufacturing defects or in-service loadings (e.g., low/high velocity impacts). Most of the ...contemporary research efforts are dedicated to high-frequency guided wave and mode shape-based methods for the assessment (i.e., detection, quantification, localization) of delamination. This paper presents a deep learning framework for structural vibration-based assessment of delamination in smart composite laminates. A number of small-sized (4.5% of total area) inner and edge delaminations are simulated using an electromechanically coupled model of the piezo-bonded laminated composite. Healthy and delaminated structures are stimulated with random loads and the corresponding transient responses are transformed into spectrograms using optimal values of window size, overlapping rate, window type, and fast Fourier transform (FFT) resolution. A convolutional neural network (CNN) is designed to automatically extract discriminative features from the vibration-based spectrograms and use those to distinguish the intact and delaminated cases of the smart composite laminate. The proposed architecture of the convolutional neural network showed a training accuracy of 99.9%, validation accuracy of 97.1%, and test accuracy of 94.5% on an unseen data set. The testing confusion chart of the pre-trained convolutional neural network revealed interesting results regarding the severity and detectability for the in-plane and through the thickness scenarios of delamination.
This paper addresses ground target tracking (GTT) for airborne radar. Digital terrain elevation data (DTED) are widely used for GTT as prior information under the premise that ground targets are ...constrained on terrain. Existing works fuse DTED to a tracking filter in a way that adopts only the assumption that the position of the target is constrained on the terrain. However, by kinematics, it is natural that the velocity of the moving ground target is constrained as well. Furthermore, DTED provides neither continuous nor accurate measurement of terrain elevation. To overcome such limitations, we propose a novel soft terrain constraint and a constraint-aided particle filter. To resolve the difficulties in applying the DTED to the GTT, first, we reconstruct the ground-truth terrain elevation using a Gaussian process and treat DTED as a noisy observation of it. Then, terrain constraint is formulated as joint soft constraints of position and velocity. Finally, we derive a Soft Terrain Constrained Particle Filter (STC-PF) that propagates particles while approximately satisfying the terrain constraint in the prediction step. In the numerical simulations, STC-PF outperforms the Smoothly Constrained Kalman Filter (SCKF) in terms of tracking performance because SCKF can only incorporate hard constraints.
This paper proposes a binary linear programming formulation for multiple target assignment of a radar network and demonstrates its applicability to obtain optimal solutions using an off-the-shelf ...mixed-integer linear programming solver. The goal of radar resource scheduling in this paper is to assign the maximum number of targets by handing over targets between networked radar systems to overcome physical limitations such as the detection range and simultaneous tracking capability of each radar. To achieve this, time windows are generated considering the relation between each radar and target considering incoming target information. Numerical experiments using a local-scale simulation were performed to verify the functionality of the formulation and a sensitivity analysis was conducted to identify the trend of the results with respect to several parameters. Additional experiments performed for a large-scale (battlefield) scenario confirmed that the proposed formulation is valid and applicable for hundreds of targets and corresponding radar network systems composed of five distributed radars. The performance of the scheduling solutions using the proposed formulation was better than that of the general greedy algorithm as a heuristic approach in terms of objective value as well as the number of handovers.
Various studies have been conducted to better understand the long-term corrosion mechanism for steels in a soil environment. Here, electrochemical acceleration methods present the most efficient way ...to simulate long-term corrosion. Among the various methods, galvanostatic testing allows for accelerating the surface corrosion reactions through controlling the impressed anodic current density. However, a large deviation from the equilibrium state can induce different corrosion mechanisms to those in actual service. Therefore, applying a suitable anodic current density is important for shortening the test times and maintaining the stable dissolution of steel. In this paper, to calibrate the anodic current density, galvanostatic tests were performed at four different levels of anodic current density and time to accelerate a one-year corrosion reaction of pipeline steel. To validate the appropriate anodic current density, analysis of the potential vs. time curves, thermodynamic analysis, and analysis of the specimen's cross-sections and products were conducted using a validation algorithm. The results indicated that 0.96 mA/cm
was the optimal impressed anodic current density in terms of a suitable polarized potential, uniform corrosion, and a valid corrosion product among the evaluated conditions.
This paper addresses the problem of target-directed exploration (TDE) in initially unknown and large-scale indoor environments. In such scenarios, the inference on an unknown space can improve the ...search performance under the assumption that the context of a particular space (i.e., the functional category of the space) is correlated with the existence of a target. The space inference is promising in that there is a strong statistical correlation between the semantic categories of indoor spaces and their adjacency because the spaces are designed to reflect universal human preferences. In this point of view, we propose a novel TDE scheme leveraging the semantic-spatial relations of an indoor floorplan dataset. Whereas existing works dealing with the data-driven space inferences consider only the one-to-one relation statistics of the spaces or utilize heuristic counting-based matching algorithms without building a trainable latent model, we propose the pattern cognitive Multivariate Bernoulli Distribution-based Graphical Space Inference Model (MBD-GSIM). MBD-GSIM efficiently captures the core contexts of the discrete semantic-spatial relations to predict an unknown space by using the latent Multivariate Bernoulli Distribution model. We also suggest utilizing the MBD-GSIM in a cost-utility based frontier exploration scheme for TDE problems. The proposed scheme is constructed in the Robot Operating System (ROS); its efficiency is investigated in the Gazebo simulation environment.
Dynamic contrast‐enhanced magnetic resonance imaging (DCE‐MRI) is a promising tool for evaluating tumor vascularity, as it can provide vasculature‐derived, functional, and quantitative parameters. To ...implement DCE‐MRI parameters as biomarkers for monitoring the effect of antiangiogenic or vascular‐disrupting treatment, two crucial elements of surrogate endpoint, ie, validation and qualification, should be satisfied. Although early studies have shown the accuracy and reliability of DCE‐MRI parameters for evaluating treatment‐driven vascular alterations, there have been an increasing number of studies demonstrating the limitations of DCE‐MRI parameters as surrogate endpoints. Therefore, in order to improve the application of DCE‐MRI parameters in drug development, it is necessary to establish a standardized evaluation method and to determine the correct therapeutics‐oriented meaning of individual DCE‐MRI parameter. In this regard, this article describes the biophysical background and data acquisition/analysis techniques of DCE‐MRI while focusing on the validation and qualification issues. Specifically, the causes of disagreement and confusion encountered in the preclinical and clinical trials using DCE‐MRI are presented in detail. Finally, considering these limitations, we present potential strategies to optimize implementation of DCE‐MRI. J. Magn. Reson. Imaging 2016;44:251–264.
Cell-based therapy has been reported to repair or restore damaged salivary gland (SG) tissue after irradiation. This study was aimed at determining whether systemic administration of human ...adipose-derived mesenchymal stem cells (hAdMSCs) can ameliorate radiation-induced SG damage.
hAdMSCs (1 × 10(6)) were administered through a tail vein of C3H mice immediately after local irradiation, and then this infusion was repeated once a week for 3 consecutive weeks. At 12 weeks after irradiation, functional evaluations were conducted by measuring salivary flow rates (SFRs) and salivation lag times, and histopathologic and immunofluorescence histochemistry studies were performed to assay microstructural changes, apoptosis, and proliferation indices. The engraftment and in vivo differentiation of infused hAdMSCs were also investigated, and the transdifferentiation of hAdMSCs into amylase-producing SG epithelial cells (SGCs) was observed in vitro using a co-culture system.
The systemic administration of hAdMSCs exhibited improved SFRs at 12 weeks after irradiation. hAdMSC-transplanted SGs showed fewer damaged and atrophied acinar cells and higher mucin and amylase production levels than untreated irradiated SGs. Immunofluorescence TUNEL assays revealed fewer apoptotic cells in the hAdMSC group than in the untreated group. Infused hAdMSCs were detected in transplanted SGs at 4 weeks after irradiation and some cells were found to have differentiated into SGCs. In vitro, a low number of co-cultured hAdMSCs (13%-18%) were observed to transdifferentiate into SGCs.
The findings of this study indicate that hAdMSCs have the potential to protect against irradiation-induced cell loss and to transdifferentiate into SGCs, and suggest that hAdMSC administration should be viewed as a candidate therapy for the treatment of radiation-induced SG damage.
Sodium metal chloride batteries have become a substantial focus area in the research on prospective alternatives for battery energy storage systems (BESSs) since they are more stable than lithium ion ...batteries. This study demonstrates the effects of the cathode microstructure on the electrochemical properties of sodium metal chloride cells. The cathode powder is manufactured in the form of granules composed of a metal active material and NaCl, and the ionic conductivity is attained by filling the interiors of the granules with a second electrolyte (NaAlCl4). Thus, the microstructure of the cathode powder had to be optimized to ensure that the second electrolyte effectively penetrated the cathode granules. The microstructure was modified by selecting the NaCl size and density of the cathode granules, and the resulting Na/(Ni,Fe)Cl2 cell showed a high capacity of 224 mAh g−1 at the 100th cycle owing to microstructural improvements. These findings demonstrate that control of the cathode microstructure is essential when cathode powders are used to manufacture sodium metal chloride batteries.
Proper placental development in early pregnancy ensures a positive outcome later on. The developmental relationship between the placenta and embryonic organs, such as the heart, is crucial for a ...normal pregnancy. However, the mechanism through which the placenta influences the development of embryonic organs remains unclear. Trophoblasts fuse to form multinucleated syncytiotrophoblasts (SynT), which primarily make up the placental materno-fetal interface. We discovered that endogenous progesterone immunomodulatory binding factor 1 (PIBF1) is vital for trophoblast differentiation and fusion into SynT in humans and mice. PIBF1 facilitates communication between SynT and adjacent vascular cells, promoting vascular network development in the primary placenta. This process affected the early development of the embryonic cardiovascular system in mice. Moreover, in vitro experiments showed that PIBF1 promotes the development of cardiovascular characteristics in heart organoids. Our findings show how SynTs organize the barrier and imply their possible roles in supporting embryogenesis, including cardiovascular development. SynT-derived factors and SynT within the placenta may play critical roles in ensuring proper organogenesis of other organs in the embryo.
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