Search

Artificial intelligence (AI) technologies such as image recognition, classification, and generative AI are constantly evolving rapidly. Many of these techniques operate in high-performance computing environments because they use complex architectural models and millions of parameters to improve inference and prediction performance. In recent years, there has been a growing demand for AI applications in the defense domain, and considerable research has been conducted. In tactical environments, images are used for various functions, such as creating an operational overlay and analyzing information, and AI can be leveraged for these functions. However, tactical mobile edge devices have insufficient computing resources, which limits their ability to simultaneously perform various applications such as service-proven command and control, intelligence analysis, and fire operations, as well as applications using existing AI models. Therefore, a robust bare-bone convolutional neural network (CNN) model that can support reliable services on tactical mobile edge devices was proposed. The proposed model uses only four convolutional layers, has a performance equivalent to or better than that of existing CNN models, and has a stable and sufficient performance potential to perform multiple applications simultaneously. For experimental validation of the proposed model, a military symbol inferencer using self-collected handwritten military symbol images was implemented. This inferencer has an average accuracy of 95.42% when used alone, with CPU utilization reduced by up to 31.3% and inference time reduced by up to 47.2%. When running multiple applications in parallel, CPU utilization was reduced by up to 23.7% and inference time by up to 55.9%.

Abstract Specimen-induced aberration has been a major factor limiting the imaging depth of single-molecule localization microscopy (SMLM). Here, we report the application of label-free wavefront sensing adaptive optics to SMLM for deep-tissue super-resolution imaging. The proposed system measures complex tissue aberrations from intrinsic reflectance rather than fluorescence emission and physically corrects the wavefront distortion more than three-fold stronger than the previous limit. This enables us to resolve sub-diffraction morphologies of cilia and oligodendrocytes in whole zebrafish as well as dendritic spines in thick mouse brain tissues at the depth of up to 102 μm with localization number enhancement by up to 37 times and localization precision comparable to aberration-free samples. The proposed approach can expand the application range of SMLM to whole zebrafish that cause the loss of localization number owing to severe tissue aberrations.

Since the leakage of sodium in an SFR (sodium-cooled fast reactor) causes an explosion upon reaction with air and water, sodium leakages represent an important safety issue. In this study, a novel technique for improving the reliability of sodium leakage detection applying DDVR (dynamic data validation and reconciliation) is proposed and verified to resolve this technical issue. DDVR is an approach that aims to improve the accuracy of a target system in a dynamic state by minimizing random errors, such as from the uncertainty of instruments and the surrounding environment, and by eliminating gross errors, such as instrument failure, miscalibration, or aging, using the spatial redundancy of measurements in a physical model and the reliability information of the instruments. DDVR also makes it possible to estimate the state of unmeasured points. To validate this approach for supporting sodium leakage detection, this study applies experimental data from a sodium leakage detection experiment performed by the Korea Atomic Energy Research Institute. The validation results show that the reliability of sodium leakage detection is improved by cooperation between DDVR and hardware measurements. Based on these findings, technology integrating software and hardware approaches is suggested to improve the reliability of sodium leakage detection by presenting the expected true state of the system.

Abstract Optical imaging has been essential for scientific observations to date, however its biomedical applications has been restricted due to its poor penetration through tissues. In living tissue, signal attenuation and limited imaging depth caused by the wave distortion occur because of scattering and absorption of light by various molecules including hemoglobin, pigments, and water. To overcome this, methodologies have been proposed in the various fields, which can be mainly categorized into two stategies: developing new imaging probes and optical techniques. For example, imaging probes with long wavelength like NIR-II region are advantageous in tissue penetration. Bioluminescence and chemiluminescence can generate light without excitation, minimizing background signals. Afterglow imaging also has high a signal-to-background ratio because excitation light is off during imaging. Methodologies of adaptive optics (AO) and studies of complex media have been established and have produced various techniques such as direct wavefront sensing to rapidly measure and correct the wave distortion and indirect wavefront sensing involving modal and zonal methods to correct complex aberrations. Matrix-based approaches have been used to correct the high-order optical modes by numerical post-processing without any hardware feedback. These newly developed imaging probes and optical techniques enable successful optical imaging through deep tissue. In this review, we discuss recent advances for multi-scale optical imaging within deep tissue, which can provide reseachers multi-disciplinary understanding and broad perspectives in diverse fields including biophotonics for the purpose of translational medicine and convergence science. Graphical Abstract Methodologies for multi-scale optical imaging within deep tissues are discussed in diverse fields including biophotonics for the purpose of translational medicine and convergence science. Recent imaging probes have tried deep tissue imaging by NIR-II imaging, bioluminescence, chemiluminescence, and afterglow imaging. Optical techniques including direct/indirect and coherence-gated wavefront sensing also can increase imaging depth.

Monolayer transition metal dichalcogenides, due to a lack of inversion symmetry and strong spin orbit coupling, exhibit a number of unique features applicable to optical devices. Here, the authors use polarised microphotoluminescence to demonstrate optical pumping of the valley degree of freedom for charge-tunable MoS2 monolayers, the optical features of which they attribute to its unusual band structure.

Background and Objectives: The fruit of Schisandra chinensis (Turcz.) Baill. is widely used medicinally to treat coughs, asthma, exhaustion, eczema, and pruritus in Northeast Asian countries, including Korea, China, and Japan. This study was designed to investigate the effects of S. chinensis on dermatitis in mice with calcipotriol (MC-903)-induced atopic dermatitis (AD), and its effects on skin barrier dysfunction was also investigated. Materials and Methods: The inhibitory effects of an ethanolic extract of S. chinensis (EESC) on skin lesions, water content, water-holding capacity (WHC), histopathological abnormalities, and inflammatory cytokine and chemokine levels were evaluated in mice with AD induced by MC903. Results: Topical EESC ameliorated skin lesions, reduced skin water content, and increased MC903-induced WHC. EESC also prevented MC-903-induced histopathological abnormalities such as epidermal disruption, hyperkeratosis, spongiotic changes, and immune cell infiltration in inflamed tissue. Moreover, topical EESC reduced MC-903-induced levels of pro-inflammatory cytokines and chemokines, such as tumor necrosis factor (TNF)-α, interleukin (IL)-1β, IL-4, IL-6, IL-8, monocyte chemotactic protein (MCP)-1, and thymic stromal lymphopoietin (TSLP). Furthermore, unlike dexamethasone, EESC did not reduce the spleen/body weight ratio. Conclusions: These results suggest that S. chinensis can be used as an alternative to external corticosteroids and that its anti-inflammatory and skin barrier dysfunction-restoring effects are related to the downregulation of pro-inflammatory cytokines and chemokines, such as TNF-α, IL-4, IL-6, IL-8, and TSLP.

As the frequency of extreme weather events rises, the resilience of power systems is becoming increasingly important. This paper proposes a proactive microgrid management strategy for enhancing the resilience of microgrids (MGs) based on nested Mixed Integer Linear Programming problems with chance constraints. In the proposed method, MGs operate in a special operating mode referred to as the “preparation mode” to protect the vital load and maximize resource operation efficiency when an external grid outage warning is issued. The preparation mode problem is formulated to reflect both the normal and emergency mode operation conditions. The on-event phase-operation problem under emergency-mode operation conditions is nested within the pre-scheduling problem under normal-mode operation conditions in the preparation mode. Further, according to their importance, loads are divided into critical and non-critical ones in the problems. The former is represented by a chance constraint, and the latter is represented by the expected cost of load shedding in the cost function. The numerical examples demonstrate that the proposed preparation mode enables the MG to guarantee a high chance that the critical load will survive and to lower the cost of the non-critical load shedding with a minor increase in resource operation costs.

In this study, the drying shrinkage cracking characteristics of concrete containing 30% fly ash were investigated for various dune sand (DS) replacements and unit water contents. In the results of compressive strength, the mixture with a DS-to-fine aggregate (DS/FA) ratio of 10% showed the highest value, which was 17.6% higher than the lowest value. However, in the results of restrained drying shrinkage cracking, the mixtures with a DS/FA ratio of 20% showed the highest crack resistance, which was 24% higher than the lowest crack resistance. Therefore, it is necessary to consider DS replacement according to the required performance of concrete. The restraint effect factors of the aggregates were analyzed based on the relationship between the volume change of each aggregate and the change in the net time to cracking. The restraint effect factor of crushed sand was 0.71–0.98 and that of DS was 0.56–0.90 when that of the coarse aggregate (CA) was 1.