SCAE-Stacked Convolutional Autoencoder for Fault Diagnosis of a Hydraulic Piston Pump with Limited Data Samples.

Deep learning (DL) models require enormous amounts of data to produce reliable diagnosis results. The superiority of DL models over traditional machine learning (ML) methods in terms of feature extraction, feature dimension reduction, and diagnosis performance has been shown in various studies of fault diagnosis systems. However, data acquisition can sometimes be compromised by sensor issues, resulting in limited data samples. In this study, we propose a novel DL model based on a stacked convolutional autoencoder (SCAE) to address the challenge of limited data. The innovation of the SCAE model lies in its ability to enhance gradient information flow and extract richer hierarchical features, leading to superior diagnostic performance even with limited and noisy data samples. This article describes the development of a fault diagnosis method for a hydraulic piston pump using time-frequency visual pattern recognition. The proposed SCAE model has been evaluated on limited data samples of a hydraulic piston pump. The findings of the experiment demonstrate that the suggested approach can achieve excellent diagnostic performance with over 99.5% accuracy. Additionally, the SCAE model has outperformed traditional DL models such as deep neural networks (DNN), standard stacked sparse autoencoders (SSAE), and convolutional neural networks (CNN) in terms of diagnosis performance. Furthermore, the proposed model demonstrates robust performance under noisy data conditions, further highlighting its effectiveness and reliability.

Overexpression of Both Human Sodium Iodide Symporter (NIS) and BRG1-Bromodomain Synergistically Enhances Radioiodine Sensitivity by Stabilizing p53 through NPM1 Expression.

Improved therapeutic strategies are required to minimize side effects associated with radioiodine gene therapy to avoid unnecessary damage to normal cells and radiation-induced secondary malignancies. We previously reported that codon-optimized sodium iodide symporter (oNIS) enhances absorption of I-131 and that the brahma-associated gene 1 bromodomain (BRG1-BRD) causes inefficient DNA damage repair after high-energy X-ray therapy. To increase the therapeutic effect without applying excessive radiation, we considered the combination of oNIS and BRG1-BRD as gene therapy for the most effective radioiodine treatment. The antitumor effect of I-131 with oNIS or oNIS+BRD expression was examined by tumor xenograft models along with functional assays at the cellular level. The synergistic effect of both BRG1-BRD and oNIS gene overexpression resulted in more DNA double-strand breaks and led to reduced cell proliferation/survival rates after I-131 treatment, which was mediated by the p53/p21 pathway. We found increased p53, p21, and nucleophosmin 1 (NPM1) in oNIS- and BRD-expressing cells following I-131 treatment, even though the remaining levels of citrulline and protein arginine deiminase 4 (PAD4) were unchanged at the protein level.

Vibration-Based Loosening Detection of a Multi-Bolt Structure Using Machine Learning Algorithms.

Since artificial intelligence (AI) was introduced into engineering fields, it has made many breakthroughs. Machine learning (ML) algorithms have been very commonly used in structural health monitoring (SHM) systems in the last decade. In this study, a vibration-based early stage of bolt loosening detection and identification technique is proposed using ML algorithms, for a motor fastened with four bolts (M8 × 1.5) to a stationary support. First, several cases with fastened and loosened bolts were established, and the motor was operated in three different types of working condition (800 rpm, 1000 rpm, and 1200 rpm), in order to obtain enough vibration data. Second, for feature extraction of the dataset, the short-time Fourier transform (STFT) method was performed. Third, different types of classifier of ML were trained, and a new test dataset was applied to evaluate the performance of the classifiers. Finally, the classifier with the greatest accuracy was identified. The test results showed that the capability of the classifier was satisfactory for detecting bolt loosening and identifying which bolt or bolts started to lose their preload in each working condition. The identified classifier will be implemented for online monitoring of the early stage of bolt loosening of a multi-bolt structure in future works.

Glucose-Thymidine Ratio as a Metabolism Index Using 18F-FDG and 18F-FLT PET Uptake as a Potential Imaging Biomarker for Evaluating Immune Checkpoint Inhibitor Therapy.

Immune checkpoint inhibitors (ICIs) are widely used in cancer immunotherapy, requiring effective methods for response monitoring. This study evaluated changes in 18F-2-fluoro-2-deoxy-D-glucose (FDG) and 18F-fluorothymidine (FLT) uptake by tumors following ICI treatment as potential imaging biomarkers in mice. Tumor uptakes of 18F-FDG and 18F-FLT were measured and compared between the ICI treatment and control groups. A combined imaging index of glucose-thymidine uptake ratio (GTR) was defined and compared between groups. In the ICI treatment group, tumor growth was effectively inhibited, and higher proportions of immune cells were observed. In the early phase, 18F-FDG uptake was higher in the treatment group, whereas 18F-FLT uptake was not different. There was no difference in 18F-FDG uptake between the two groups in the late phase. However, 18F-FLT uptake of the control group was markedly increased compared with the ICI treatment group. GTR was consistently higher in the ICI treatment group in the early and late phases. After ICI treatment, changes in tumor cell proliferation were observed with 18F-FLT, whereas 18F-FDG showed altered metabolism in both tumor and immune cells. A combination of 18F-FLT and 18F-FDG PET, such as GTR, is expected to serve as a potentially effective imaging biomarker for monitoring ICI treatment.

Therapeutic efficacy of modified anti-miR21 in metastatic prostate cancer.

Despite improved therapeutic efficacy of the locked nucleic acid (LNA)- and peptide nucleic acid (PNA)-modified antisense microRNAs (anti-miRs), their wider application in clinical practice is still not thoroughly investigated. This study aimed to investigate the stability and therapeutic efficacy of the modified LNA- and PNA-type anti-miRs in a murine prostate cancer model under various treatment conditions. After verifying the anti-cancer potential of anti-miR21 by targeting tumor suppressor PTEN, the potential of the modified LNA- and PNA-type anti-miR21s was compared in vitro and in vivo. We found that PNA-type anti-miR21 showed better stability and therapeutic efficacy in the xenografted mouse tumor model than the LNA-type anti-miR21. Furthermore, PNA-type anti-miR21 treatment showed reduced tumor metastasis. This study may serve as a ground for exploring diverse choices in therapeutic oligonucleotide modification techniques to improve cancer treatment.

Order-of-Magnitude, Broadband-Enhanced Light Emission from Quantum Dots Assembled in Multiscale Phase-Separated Block Copolymers.

Achieving high emission efficiency in solid-state quantum dots (QDs) is an essential requirement for high-performance QD optoelectronics. However, most QD films suffer from insufficient excitation and light extraction efficiencies, along with nonradiative energy transfer between closely adjacent QDs. Herein, we suggest a highly effective strategy to enhance the photoluminescence (PL) of QD composite films through an assembly of QDs and poly(styrene-b-4-vinylpyridine)) (PS-b-P4VP) block copolymer (BCP). A BCP matrix casted under controlled humidity provides multiscale phase-separation features based on (1) submicrometer-scale spinodal decomposition between polymer-rich and water-rich phases and (2) sub-10 nm-scale microphase separation between polymer blocks. The BCP-QD composite containing bicontinuous random pores achieves significant enhancement of both light absorption and extraction efficiencies via effective random light scattering. Moreover, the microphase-separated morphology substantially reduces the Förster resonance energy transfer efficiency from 53% (pure QD film) to 22% (BCP-QD composite), collectively achieving an unprecedented 21-fold enhanced PL over a broad spectral range.

Identification of Lymphatic and Hematogenous Routes of Rapidly Labeled Radioactive and Fluorescent Exosomes through Highly Sensitive Multimodal Imaging.

There has been considerable interest in the clinical use of exosomes as delivery vehicles for treatments as well as for promising diagnostic biomarkers, but the physiological distribution of exosomes must be further elucidated to validate their efficacy and safety. Here, we aimed to develop novel methods to monitor exosome biodistribution in vivo using positron emission tomography (PET) and optical imaging. Exosomes were isolated from cultured mouse breast cancer cells and labeled for PET and optical imaging. In mice, radiolabeled and fluorescently labeled exosomes were injected both via lymphatic and hematogenous metastatic routes. PET and fluorescence images were obtained and quantified. Radioactivity and fluorescence intensity of ex vivo organs were measured. PET signals from exosomes in the lymphatic metastatic route were observed in the draining sentinel lymph nodes. Immunohistochemistry revealed greater exosome uptake in brachial and axillary versus inguinal lymph nodes. Following administration through the hematogenous metastasis pathway, accumulation of exosomes was clearly observed in the lungs, liver, and spleen. Exosomes from tumor cells were successfully labeled with 64Cu (or 68Ga) and fluorescence and were visualized via PET and optical imaging, suggesting that this simultaneous and rapid labeling method could provide valuable information for further exosome translational research and clinical applications.

Moderating effect of cognitive reserve on the association between grey matter atrophy and memory varies with age in older adults.

BACKGROUND: Educational attainment and verbal intelligence, which indirectly reflect an individual's cognitive reserve (CR), is suggested to buffer the effect of late-life brain degradation on cognitive performance outcome. We aimed to explore how the relationship between whole grey matter volume (GMV) and episodic memory function is altered by CR proxy as well as age in healthy older adults. METHODS: Elderly Verbal Learning Test (EVLT) and structural magnetic resonance imaging were administered to 110 community-residing older adults. Moderated moderation model tested whether the association between whole GMV and episodic memory was moderated by both CR and chronological age. RESULTS: The results showed that the moderating effect of CR on Immediate Recall, Short-delay Recall, and Recognition scores of EVLT differed across age groups. The elderly with higher CR showed steeper GMV effect on EVLT at the Age-Younger condition, while such moderating effect was reversed in the Age-Older condition, suggesting an alleviated brain atrophy effect in higher CR elderly. CONCLUSION: These findings suggest that although higher CR elderly may exhibit earlier GMV-related memory decline, the buffering effect of CR on the cognitive decline due to brain atrophy would become more evident in old-old elderly people who are likely to have accumulated more neuropathological changes. This study underscores chronological age as an important moderating factor in examining the moderating role of CR in late-life memory function.

Microstructure and Texture of P-Type Bi-Sb-Te Alloy by Using Gas-Atomization and Extrusion Processes.

Microstructure and texture of P-type 75%Sb2Te3-25%Bi2Te3 alloy fabricated by using gas-atomization and extrusion processes was investigated. The microstructure of the gas-atomized powders exhibited fine grains with needle shape. After hot extrusion, grain size was characterized by fine and equiaxed grains due to dynamic recrystallization by severe deformation. (0001) basal planes of the extruded specimens were preferentially orientated parallel to extrusion direction. As extrusion temperature, fraction of the basal planes was increased.

Changing Relationship between Unemployment and Mortality in South Korea.

Over the period from 1989 to 2012, total mortality in South Korea shifted from being weakly procyclical or unrelated to the economy to strongly countercyclical in the early 2000s. Cancers played a significant role in changing the direction of the effects of unemployment on mortality. The overall pattern of the effects of macroeconomic conditions on mortality in South Korea roughly follows the corresponding changes observed in the United States. We have provided evidence that the sudden change in the relationship between economic conditions and mortality was driven by diseases with higher and rapidly rising treatment costs. Copyright © 2016 John Wiley & Sons, Ltd.

Depth perception estimation of various stereoscopic displays.

In this paper, we investigate the relationship between depth perception and several disparity parameters in stereoscopic images. A number of subjective experiments were conducted using various 3D displays, which indicate that depth perception of stereoscopic images is proportional to depth difference and is inversely related to the camera distance. Based on this observation, we developed some formulas to quantify the degree of depth perception of stereoscopic images. The proposed method uses depth differences and the camera distance between the objects and the 3D camera. This method also produces improved depth perception estimation by using non-linear functions whose inputs include a depth difference and a camera distance. The results show that the proposed method provides noticeable improvements in terms of correlation and produces more accurate depth perception estimations of stereoscopic images.

Investigation and Prediction of Nano-Silver Line Quality upon Various Process Parameters in Inkjet Printing Process Based on an Experimental Method.

As an emerging additive manufacturing technology, inkjet printing has been increasingly applied in microelectronics field. However, due to the impacting and rebounding behaviors of conductive ink droplets impinging onto flat substrates, it is challenging to fabricate conductive lines with desired quality, such as suitable line width and line thickness, and matching resistance when it is used for interconnecting multifarious electronic components if there is not a proper configuration of operating parameters. To address this research gap, this article aims to investigate the effect of process parameters on the quality of conductive lines, including the platform temperature, printing speed, number of layers, and delay time (droplet interarrival time), are selected to conduct a full factorial experiment. First, the approximate parameter ranges for ensuring the continuity of conductive lines are determined. Second, this study analyzes the interactive effect among process parameters on line quality. Third, an artificial neural network (ANN) is constructed to predict the quality of printed lines. Results show that the line width does not increase with an increased number of layers, while the line thickness shows an increasing trend. The low resistance and high aspect ratio of printed line are achieved by printing 5 layers with the platform temperature of 70°C, the delay time of 12.2 ms, and the printing speed of 1139.39 mm/min. Moreover, the ANN model can be used to predict line width and line thickness with excellent performance, except for the resistance due to the irregular line edge. This study provides a useful guide for the selection of appropriate printing parameters to realize a diverse range of quality properties for 3D printed conductive lines in integrated circuits.

Performance Analysis of Time Series Deep Learning Models for Climate Prediction in Indoor Hydroponic Greenhouses at Different Time Intervals.

Indoor hydroponic greenhouses are becoming increasingly popular for sustainable food production. On the other hand, precise control of the climate conditions inside these greenhouses is crucial for the success of the crops. Time series deep learning models are adequate for climate predictions in indoor hydroponic greenhouses, but a comparative analysis of these models at different time intervals is needed. This study evaluated the performance of three commonly used deep learning models for climate prediction in an indoor hydroponic greenhouse: Deep Neural Network, Long-Short Term Memory (LSTM), and 1D Convolutional Neural Network. The performance of these models was compared at four time intervals (1, 5, 10, and 15 min) using a dataset collected over a week at one-minute intervals. The experimental results showed that all three models perform well in predicting the temperature, humidity, and CO2 concentration in a greenhouse. The performance of the models varied at different time intervals, with the LSTM model outperforming the other models at shorter time intervals. Increasing the time interval from 1 to 15 min adversely affected the performance of the models. This study provides insights into the effectiveness of time series deep learning models for climate predictions in indoor hydroponic greenhouses. The results highlight the importance of choosing the appropriate time interval for accurate predictions. These findings can guide the design of intelligent control systems for indoor hydroponic greenhouses and contribute to the advancement of sustainable food production.

Military Service and Economic Mobility: Evidence from the American Civil War.

How did geographic and occupational mobility after the Civil War differ between Union Army veterans and nonveterans? By 1880, Union veterans were more likely to migrate to a different state or region than nonveterans. The higher geographic mobility of veterans is likely attributable to their experience of traveling away from their hometowns while in service. Union veterans who held unskilled jobs prior to enlistment were more likely to move up to white-collar or farming jobs by 1880 than unskilled nonveterans. In contrast, unskilled veterans were less likely to become artisans than nonveterans. The differences in occupational mobility by veteran status might be explained by the effects of military experiences such as learning from comrades in the company.

The Feasibility of 64Cu-PSMA I&T PET for Prostate Cancer.

Background: The goal of this research was to investigate the feasibility of 64Cu labeling in prostate-specific membrane antigen imaging and therapy (PSMA I&T) for PSMA positron emission tomography (PET) imaging and biodistribution evaluation. Materials and Methods: PSMA I&T was labeled with 64Cu, and stability in human and mouse sera was evaluated. Prostate cancer cell lines were used for specific uptake assays (22RV1 for PSMA-positive, PC-3 for -negative). Both PC-3 and 22RV1 cells were transplanted into the left and right thighs in a mouse for PET/computed tomography (CT) imaging. Biodistribution was performed using 22RV1 tumor models. Results: Labeling yield (decay corrected) of 64Cu-PSMA I&T was more than 95% compared to the free 64Cu peak. The serum stability of 64Cu-PSMA I&T was maintained at more than 90% until 60 h. Regarding the specific binding of 64Cu-PSMA I&T was 7.5-fold higher to 22RV1 cells than PC-3 cells (p < 0.001). On PET/CT imaging, more specific 64Cu-PSMA I&T uptake was observed to 22RV1 tumors than to PC-3 tumors. In the PSMA blocking study using 2-phosphonomethoxypropyl adenine (2-PMPA), the 64Cu-PSMA I&T signal significantly decreased in the 22RV1 tumor region. In the biodistribution study, the kidney uptake was the highest among all organs at 2 h (52.6 ± 20.8%ID/g) but sharply decreased at 24 and 48 h. Also, the liver showed similar uptake over time (range, 10-12%ID/g). On the contrary, 64Cu-PSMA I&T uptake of the tumors increased with time and peaked at 48 h (5.6 ± 0.1%ID/g). Conclusions: PSMA I&T labeled with 64Cu showed the feasibility of the PSMA specific PET imaging through in vitro and in vivo studies. Furthermore, 64Cu-PSMA I&T might be considered as the candidate of future clinical trial.

Synergistic Optimization of the Thermoelectric and Mechanical Properties of Large-Size Homogeneous Bi0.5Sb1.5Te3 Bulk Samples via Carrier Engineering for Efficient Energy Harvesting.

Manufacturing an economically viable, efficient commercial thermoelectric (TE) module is essential for power generation and refrigeration. However, mediocre TE properties, lack of good mechanical stability of the material, and significant difficulties involved in the manufacturing of large-scale powder as well as bulk samples hinder the potential applications of the modules. Herein, an economically feasible single-step water atomization (WA) is employed to synthesize BST powder (2 kg) by Cu doping within a short time and consolidated into large-scale bulk samples (500 g) for the first time with a diameter of 50 mm and a thickness of about 40 mm using spark plasma sintering (SPS). The incorporation of Cu into BST greatly boosts the carrier concentration, leading to a significant increase in electrical conductivity, and inhibits the bipolar thermal conductivity by 73%. Synchronously, the lattice contribution (κL) is greatly reduced by the effective scattering of phonons by comprising fine-grain boundaries and point defects. Therefore, the peak ZT is shifted to the mid-temperature range and obtained a maximum of ∼1.31 at 425 K and a ZTave of 1.24 from 300 to 500 K for the BSTCu0.05 sample, which are considerably greater than those of the bare BST sample. Moreover, the maximum compressive mechanical strength of large-size samples manufactured by the WA-SPS process is measured as 102 MPa, which is significantly higher than commercial zone melting samples. The thermoelectric module assembled with WA-SPS-synthesized BSTCu0.05 and commercial n-type BTS material manifests an outstanding cooling performance (-19.4 °C), and a maximum output power of 6.91 W is generated at ΔT ∼ 200 K. These results prove that the BSTCux samples are eminently suitable for the fabrication of industrial thermoelectric modules.

Visualization of a novel human monoclonal antibody against Claudin-3 for targeting ovarian cancer.

INTRODUCTION: Claudin-3 (CLDN3), a tight junction protein, regulates cell-to-cell interactions in epithelial or endothelial cell sheets. During tumorigenesis, epithelial cells are transformed, and tumor cells proliferate through out-of-plane division, resulting in external exposure of CLDN3. Since alterations of CLDN3 expression are associated with cancer progression and higher CLDN3 expression is observed in most ovarian cancers, we tested the feasibility of using a CLDN3-specific antibody as a novel imaging tracer. MATERIALS AND METHODS: After reducing the CLDN3-specific antibodies to expose the -SH groups, click chemistry was used to conjugate the radioactive isotope 111In or the fluorescent protein FNR648. Human ovarian cancer OVCAR-3 and glioblastoma U87MG cells were used as CLDN3-positive and -negative cells. Flow cytometry was used to determine the CLDN3 IgG1 monoclonal antibody binding to both cell lines. OVCAR-3 cells were injected subcutaneously into mice to establish a xenograft model. 111In-labeled CLDN3 antibodies (370 kBq/50 µL) were administered intravenously into mice. After 24 h, organs, including tumors, were excised and measured with a γ-counter. Images were acquired with the IVIS optical imaging system and SPECT/CT. RESULTS: The labeling efficiency of NOTA-111In and antibody-NOTA-111In was 98.52% and 100%, respectively. FNR648-labeled CLDN3 antibody bound to the cell surface of OVCAR-3 and U87MG with 83.4% and 5.7% specificity, respectively. In OVCAR-3 tumor xenografted mice, CLDN3 IgG1 antibody showed a 2.5-fold higher tumor uptake (20.4 ± 7.4% ID/g) than human IgG1 (8.8 ± 2.6% ID/g) at 24 h post injection. The CLDN3 antibody fluorescence signal in the tumor peaked at 24 h post injection. CONCLUSION: We have successfully conjugated a radioisotope and a fluorescent protein with CLDN3-specific antibodies and verified the specific binding of labeled antibodies to OVCAR-3 tumors in a mouse model. Our data suggested that CLDN3-specific human monoclonal antibodies could be used as a useful theranostic tracer.

Auto-stereoscopic 3D displays with reduced crosstalk.

In this paper, we propose new auto-stereoscopic 3D displays that substantially reduce crosstalk. In general, it is difficult to eliminate crosstalk in auto-stereoscopic 3D displays. Ideally, the parallax barrier can eliminate crosstalk for a single viewer at the ideal position. However, due to variations in the viewing distance and the interpupillary distance, crosstalk is a problem in parallax barrier displays. In this paper, we propose 3-dimensional barriers, which can significantly reduce crosstalk.

Virtual surface characteristics of a tactile display using magneto-rheological fluids.

Virtual surface characteristics of tactile displays are investigated to characterize the feeling of human touch for a haptic interface application. In order to represent the tactile feeling, a prototype tactile display incorporating Magneto-Rheological (MR) fluid has been developed. Tactile display devices simulate the finger's skin to feel the sensations of contact such as compliance, friction, and topography of the surface. Thus, the tactile display can provide information on the surface of an organic tissue to the surgeon in virtual reality. In order to investigate the compliance feeling of a human finger's touch, normal force responses of a tactile display under various magnetic fields have been assessed. Also, shearing friction force responses of the tactile display are investigated to simulate the action of finger dragging on the surface. Moreover, different matrix arrays of magnetic poles are applied to form the virtual surface topography. From the results, different tactile feelings are observed according to the applied magnetic field strength as well as the arrays of magnetic poles combinations. This research presents a smart tactile display technology for virtual surfaces.

Targeted alpha immunotherapy of CD20-positive B-cell lymphoma model: dosimetry estimate of 225Ac-DOTA-rituximab using 64Cu-DOTA-rituximab.

OBJECTIVE: The aim of this study was to evaluate the radiation dosimetry of alpha-emitter 225Ac-DOTA-rituximab using Monte Carlo simulation of 64Cu-DOTA-rituximab. METHODS: CD20 expression was evaluated in lymphoma cell lines (Jurkat and Raji). DOTA-rituximab was conjugated and then chelated by 64Cu. Tumor xenograft models were established in BALB/c-nu mice. Animal PET/CT imaging was obtained after tail vein injection with and without a pre-dose of 2 mg of cold rituximab. Specific binding of tumors was evaluated by an organ distribution assay and autoradiography. CD20 expression in tumor tissues was evaluated by immunohistochemistry. The residence time was calculated using 64Cu-DOTA-rituximab PET/CT acquisition data using OLINDA/EXM software. 225Ac-DOTA-rituximab tumor dosimetry was performed using Monte Carlo simulation with 64Cu-DOTA-rituximab PET/CT images. RESULTS: Specific binding of Raji cells (CD20 positive) was 90 times that of Jurkat cells (CD20 negative) (p < 0.0001). Immunoreactivity was more than 75%. PET/CT imaging with 64Cu-DOTA-rituximab was specifically observed in tumors. The radioactivity of the tumor was much higher than that of other organs, and tumor uptake was related to CD20 expression. The predicted human dose for the administration of 64Cu-DOTA-rituximab was measured as the effective dose (1.07E-02 mSv/MBq). In the tumor region, equivalent doses of 225Ac-DOTA-rituximab (14 SvRBE5/MBq) were much higher (74-fold) than those of 64Cu-DOTA-rituximab (0.19 SvRBE5/MBq) (p < 0.01). CONCLUSION: Tumor dosimetry of 225Ac-DOTA-rituximab can be estimated via the Monte Carlo simulation of 64Cu-DOTA-rituximab. 225Ac-DOTA-rituximab can be employed for lymphoma as targeted alpha therapy.