Recently, many companies have introduced automated defect detection methods for defect-free PCB manufacturing. In particular, deep learning-based image understanding methods are very widely used. In ...this study, we present an analysis of training deep learning models to perform PCB defect detection stably. To this end, we first summarize the characteristics of industrial images, such as PCB images. Then, the factors that can cause changes (contamination and quality degradation) to the image data in the industrial field are analyzed. Subsequently, we organize defect detection methods that can be applied according to the situation and purpose of PCB defect detection. In addition, we review the characteristics of each method in detail. Our experimental results demonstrated the impact of various degradation factors, such as defect detection methods, data quality, and image contamination. Based on our overview of PCB defect detection and experiment results, we present knowledge and guidelines for correct PCB defect detection.
Issues in the circuitry, integration, and material properties of the two‐dimensional (2D) and three‐dimensional (3D) crossbar array (CBA)‐type resistance switching memories are described. Two ...important quantitative guidelines for the memory integration are provided with respect to the required numbers of signal wires and sneak current paths. The advantage of 3D CBAs over 2D CBAs (i.e., the decrease in effect memory cell size) can be exploited only under certain limited conditions due to the increased area and layout complexity of the periphery circuits. The sneak current problem can be mitigated by the adoption of different voltage application schemes and various selection devices. These have critical correlations, however, and depend on the involved types of resistance switching memory. The problem is quantitatively dealt with using the generalized equation for the overall resistance of the parasitic current paths. Atomic layer deposition is discussed in detail as the most feasible fabrication process of 3D CBAs because it can provide the device with the necessary conformality and atomic‐level accuracy in thickness control. Other subsidiary issues related to the line resistance, maximum available current, and fabrication technologies are also reviewed. Finally, a summary and outlook on various other applications of 3D CBAs are provided.
Three‐dimensional resistive switching cross‐bar array memories are highly desirable future memory devices for data centric computation. Issues in the circuitry, integration, and material properties of the two‐ and three‐dimensional crossbar array memories are dealt with in a quantitative manner. The impressive progress in theoretical understanding and fabrication of these devices achieved during the past decade is summarized, and an outlook on possible applications is further provided.
The development of a resistance switching (RS) memory cell that contains rectification functionality in itself, highly reproducible RS performance, and electroforming‐free characteristics is an ...impending task for the development of resistance switching random access memory. In this work, a two‐layered dielectric structure consisting of HfO2 and Ta2O5 layers, which are in contact with the TiN and Pt electrode, is presented for achieving these tasks simultaneously in one sample configuration. The HfO2 layer works as the resistance switching layer by trapping or detrapping of electronic carriers, whereas the Ta2O5 layer remains intact during the whole switching cycle, which provides the rectification. With the optimized structure and operation conditions for the given materials, excellent RS uniformity, electroforming‐free, and self‐rectifying functionality could be simultaneously achieved from the Pt/Ta2O5/HfO2/TiN structure.
A feasible method is reported for achieving a highly uniform, electroforming‐free, and self‐rectifying RS memory cell with a two‐layered dielectric structure. HfO2 works as the resistance switching layer by trapping and detrapping the deep 1.0 eV trap sites, whereas Ta2O5 layer remains intact during the switching and forms a high Schottky barrier with a high‐work‐function Pt to constitute the rectifying functionality.
Limiting the location where electron injection occurs at the cathode interface to a narrower region is the key factor for achieving a highly improved RS performance, which can be achieved by ...including Ru Nanodots. The development of a memory cell structure truly at the nanoscale with such a limiting factor for the electric‐field distribution can solve the non‐uniformity issue of future ReRAM.
Various array types of 1‐diode and 1‐resistor stacked crossbar array (1D1R CA) devices composed of a Schottky diode (SD) (Pt/TiO2/Ti/Pt) and a resistive switching (RS) memory cell (Pt/TiO2/Pt) are ...fabricated and their performances are investigated. The unit cell of the 1D1R CA device shows high RS resistance ratio (≈103 at 1.5 V) between low and high resistance state (LRS and HRS), and high rectification ratio (≈105) between LRS and reverse‐state SD. It also shows a short RS time of <50 ns for SET (resistance transition from HRS to LRS), and ≈600 ns for RESET (resistance transition from LRS to HRS), as well as stable RS endurance and data retention characteristics. It is experimentally confirmed that the selected unit cell in HRS (logically the “off” state) is stably readable when it is surrounded by unselected LRS (logically the “on” state) cells, in an array of up to 32 × 32 cells. The SD, as a highly non‐linear resistor, appropriately controls the conducting path formation during the switching and protects the memory element from the noise during retention.
1 diode 1 resistor (1D1R) resistive memory devices with the crossbar array configuration composed of a stacked Schottky diode (Pt/TiO2/Ti/Pt) and unipolar resistive (URS) memory (Pt/TiO2/Pt) elements are fabricated, and their fluent functionality is proven. Atomic force microscopy is used to image one memory cell and scanning electron microscopy is used to study the 32 × 32 memory array.
Edge-cloud computing is an emerging approach in which tasks are offloaded from mobile devices to edge or cloud servers. However, Task offloading may result in increased energy consumption and delays, ...and the decision to offload the task is dependent on various factors such as time-varying radio channels, available computation resources, and the location of devices. As edge-cloud computing is a dynamic and resource-constrained environment, making optimal offloading decisions is a challenging task. This paper aims to optimize offloading and resource allocation to minimize delay and meet computation and communication needs in edge-cloud computing. The problem of optimizing task offloading in the edge-cloud computing environment is a multi-objective problem, for which we employ deep reinforcement learning to find the optimal solution. To accomplish this, we formulate the problem as a Markov decision process and use a Double Deep Q-Network (DDQN) algorithm. Our DDQN-edge-cloud (DDQNEC) scheme dynamically makes offloading decisions by analyzing resource utilization, task constraints, and the current status of the edge-cloud network. Simulation results demonstrate that DDQNEC outperforms heuristic approaches in terms of resource utilization, task offloading, and task rejection.
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•2D NiNDC MOF with large surface area was used as a novel template precursor.•NIBS was utilized for the first time on the MOF OER electrocatalyst.•Accerlating potential of the ion ...beam determined the ratio of three N sites.•The roles of 3 N sites (pyridinic, pyrrolic, graphitic N) were elucidated.•The best OER performances were observed at the optimized N ratio.
Modification of metal–organic frameworks (MOFs) is recently under the spotlight due to their versatile properties and potential applications in electrochemical catalysis. Here, we successfully demonstrate nitrogen doping into the MOF electrocatalyst without noble metals using a facile, tunable ion beam sputtering (IBS) process for the first time and evaluate the role of the incorporated heteroatom. Two-dimensional Ni-naphthalene-2,6-dicarboxylic acid MOF (NiNDC) with large surface area was subjected to nitrogen IBS (NIBS) and exhibited significantly improved performance for oxygen evolution reaction (OER) with a low overpotential of 222 mV at 10 mA cm−2; a Tafel slope of 88 mV dec-1; and over 120 h of stability at 100 mA cm−2. The relationship between the nitrogen functionalities and catalytic activity was elucidated by spectroscopic analysis and electrochemical measurements, i.e., (i) pyridinic N as an electron-withdrawing group that directly enhances the reaction kinetics, (ii) pyrrolic N to stabilize the catalyst and (iii) graphitic N to enhance the electrical conductivity. We found that the electrocatalytic performance was affected by the ratio of the three nitrogen species, which was controllable by the accelerating potential (AP) of NIBS. This study provides insights into the influence of the chemical state of MOF surfaces on catalytic reactions and presents a novel method for effective nitrogen doping.
Pretreatment of samples is one of the most important steps in analytical methods for efficient and accurate results. Typically, an extraction method used for lipid analysis with mass spectrometry is ...accompanied by complex liquid–liquid extraction. We have devised a simple, rapid, and efficient lipid extraction method using superabsorbent polymers (SAPs) and developed a high-throughput lipid extraction platform based on a microfluidic system. Since SAPs can rapidly absorb an aqueous solution from a raw sample and convert it into the gel, the lipid extraction process can be remarkably simplified. The hydrophobic lipid components were captured into the fibrous SAP gel and then solubilized and eluted directly into the organic solvent without significant interference by this polymer. The small-scale lipid extraction process minimizes the liquid handling and unnecessary centrifugation steps, thereby enabling the implementation of a SAP-integrated microfluidic lipid extraction platform. The SAP method successfully induced reproducible extraction and high recovery rates (95–100%) compared to the conventional Folch method in several lipid classes. We also demonstrated the feasibility of the SAP method for the analysis of lipids in complex biological samples, such as the brain and liver, as well as Escherichia coli. This small-scale SAP method and its microfluidic platform will open up new possibilities in high-throughput lipidomic research for diagnosing diseases because this new technique saves time, labor, and cost.
The elucidation of the biological roles of individual active compounds in terms of their in vivo bio-distribution and bioactivity could provide crucial information to understand how natural compounds ...work together as treatments for diseases.
We examined the functional roles of Byakangelicin (Byn) to improve the brain accumulation of active compounds, e.g., umbelliferone (Umb), curcumin (Cur), and doxorubicin (Dox), and consequently to enhance their biological activities.
Active compounds were administered intravenously to mice, with or without Byn, after which organs were isolated and visualized for their ex vivo fluorescence imaging to determine the bio-distribution of each active compound in vivo. For the in vivo bioactivity, Cur, either with or without Byn, was administered to a lipopolysaccharide (LPS)-induced neuro-inflammation model for 5 days, and its anti-inflammatory effects were examined by ELISA using a brain homogenate and serum.
We successfully demonstrated that the levels of active compounds (Umb, Cur, and Dox) in the brain, lung, and pancreas were greatly elevated by the addition of Byn via direct ex vivo fluorescence monitoring. In addition, sufficient accumulation of the active compound, Cur, greatly reduced LPS-induced neuro-inflammation in vivo.
Byn could serve as a modulator to allow improved brain accumulation of diverse active compounds (Umb, Cur, and Dox) and enhanced therapeutic effects.
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Previously, we found that the water extract of Artermisia scoparia Waldst. & Kit suppressed the cytokine production of lipopolysaccharide (LPS)-stimulated macrophages and alleviated ...carrageenan-induced acute inflammation in mice. Artemisia contains various sesquiterpene lactones and most of them exert immunomodulatory activity.
In the present study, we investigated the immunomodulatory effect of estafiatin (EST), a sesquiterpene lactone derived from A. scoparia, on LPS-induced inflammation in macrophages and mouse sepsis model.
Murine bone marrow-derived macrophages (BMDMs) and THP-1 cells, a human monocytic leukemia cell line, were pretreated with different doses of EST for 2 h, followed by LPS treatment. The gene and protein expression of pro-inflammatory cytokines interleukin (IL)-6, tumor necrosis factor (TNF)-α, and inducible nitric oxide synthase (iNOS) were measured by quantitative real-time polymerase chain reaction (qPCR) and Western blot analysis. The activation of nuclear factor kappa B (NF-κB) and mitogen-activated protein kinases (MAPKs) was also evaluated at the level of phosphorylation. The effect of EST on inflammatory cytokine production, lung histopathology, and survival rate was assessed in an LPS-induced mice model of septic shock. The effect of EST on the production of cytokines in LPS-stimulated peritoneal macrophages was evaluated by in vitro and ex vivo experiments and protective effect of EST on cecal ligation and puncture (CLP) mice was also assessed.
The LPS-induced expression of IL-6, TNF-α, and iNOS was suppressed at the mRNA and protein levels in BMDMs and THP-1 cells, respectively, by pretreatment with EST. The half-maximal inhibitory concentration (IC50) of EST on IL-6 and TNF-α production were determined as 3.2 μM and 3.1 μM in BMDMs, 3 μM and 3.4 μM in THP1 cells, respectively. In addition, pretreatment with EST significantly reduced the LPS-induced phosphorylation p65, p38, JNK, and ERK in both cell types. In the LPS-induced mice model of septic shock, serum levels of IL-6, TNF-α, IL-1β, CXCL1, and CXCL2 were lower in EST-treated mice than in the control animals. Histopathology analysis revealed that EST treatment ameliorated LPS-induced lung damage. Moreover, while 1 of 7 control mice given lethal dose of LPS survived, 3 of 7 EST-treated (1.25 mg/kg) mice and 5 of 7 EST-treated (2.5 mg/kg) mice were survived. Pretreatment of EST dose-dependently suppressed the LPS-induced production of IL-6, TNF-α and CXCL1 in peritoneal macrophages. In CLP-induced mice sepsis model, while all 6 control mice was dead at 48 h, 1 of 6 EST-treated (1.25 mg/kg) mice and 3 of 6 EST-treated (2.5 mg/kg) mice survived for 96 h.
These results demonstrated that EST exerts anti-inflammatory effects on LPS-stimulated macrophages and protects mice from sepsis. Our study suggests that EST could be developed as a new therapeutic agent for sepsis and various inflammatory diseases.
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