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The anisotropic creep response in both the XY and XZ planes of Ti–6Al–4V ELI manufactured by powder bed fusion (PBF) was examined under nanoindentation creep loading at room temperature, ranging from nm to μm scales. The stress exponent values of 4.06–4.30, rationalised through threshold stress, indicate that the creep behaviour is primarily dominated by dislocation gliding. Creep displacement results show that the anisotropic creep behaviour in the XY and XZ planes of the as-built, and heat treatment enhances the creep resistance of the XZ plane, while there is no significant difference in creep displacement between the as-built and heat-treated XY planes. Due to the higher dislocation density and compressive residual stress in the XY plane compared to the XZ plane, the creep resistance is higher in the XY plane for the as-built. It is highlighted that compressive residual stress is more relieved in the XY plane than in the XZ plane through heat treatment. The heat treatment results in improved creep resistance due to the formation of the Widmanstätten structure and β precipitates, which can impede dislocation movement under creep loading. The combination of residual stress and microstructural effects leads to anisotropic creep behaviour, suggesting that the anisotropy is inherited from the additive manufacturing process at micron scales.

Abstract Electric heaters based on functional materials and innovative designs have been developed for various applications. In this paper, we propose a soft dielectric heater (SDH) using polyvinyl chloride-gel (PVC-gel) as the dielectric heater and hydrogel as stretchable electrodes. Under an AC voltage, the leakage current in the PVC-gel leads to continuous injection and discharge of charges, causing the polarized plasticizers and flexible PVC chains to vibrate and collide, thereby generating heat through dielectric heating. Furthermore, the SDH generates a uniform temperature distribution even under strains up to 400%. Besides, high transmittance over 86% across the visible range renders it suitable for wearable or skin-mountable heaters from an esthetic viewpoint. Its capacitor-like structure achieves a scalable design, enabling extension from a singular cell to a row/column addressable and pixelated array of heaters. The 5 × 5 SDH array can deliver varied thermal information and sensations while maintaining performance even when stretched.

Background Diacylglycerol O-acyltransferase 2 (DGAT2) synthesizes triacylglycerol (TG) from diacylglycerol; therefore, DGAT2 is considered as a therapeutic target for steatosis. However, the consequence of inhibiting DGAT2 is not fully investigated due to side effects including lethality and lipotoxicity. In this article, we observed the role of DGAT2 in hepatocarcinoma. Methods The role of DGAT2 is analyzed via loss-of-function assay. DGAT2 knockdown (KD) and inhibitor treatment on HepG2 cell line was analyzed. Cumulative analysis of cell metabolism with bioinformatic data were assessed, and further compared with different cohorts of liver cancer patients and non-alcoholic fatty liver disease (NAFLD) patients to elucidate how DGAT2 is regulating cancer metabolism. Results Mitochondrial function is suppressed in DGAT2 KD HepG2 cell along with the decreased lipid droplets. In the aspect of the cancer, DGAT2 KD upregulates cell proliferation. Analyzing transcriptome of NAFLD and hepatocellular carcinoma (HCC) patients highlights negatively correlating expression patterns of 73 lipid-associated genes including DGAT2. Cancer patients with the lower DGAT2 expression face lower survival rate. DGAT2 KD cell and patients’ transcriptome show downregulation in estrogen- related receptor alpha (ESRRA) via integrated system for motif activity response analysis (ISMARA), with increased dimerization with corepressor prospero homeobox 1 (PROX1). Conclusion DGAT2 sustains the stability of mitochondria in hepatoma via suppressing ESRRA-PROX1 transcriptional network and hinders HCC from shifting towards glycolytic metabolism, which lowers cell proliferation.

This study investigates the microstructure and mechanical properties of wear-resistant hardfacing structures fabricated on an AISI 1045 carbon steel substrate using a specially designed Fe–Cr based powder for directed energy deposition (DED). Electron backscatter diffraction (EBSD) analysis reveals that the texture predominantly consists of cube rotated {001} and cube {001} textures, in addition to weaker Brass {112} texture components. These textures contribute to the random orientations of martensitic grains and facilitate the tracing of austenite reconstruction. Notably, the as-printed samples exhibited superior yield strength (999.4 ± 86.3 MPa) and ductility (9.6 ± 2.6%) along the build direction (BD), compared to conventional samples, which demonstrated a tensile strength of 790 MPa and ductility of 2%. This improvement is primarily attributed to the hardening effects associated with a low volume fraction of retained austenite and the precipitation of Cr carbides. Comprehensive mechanical response, nanoindentation hardness profile across the interface, and microstructural analyses were conducted to confirm the feasibility of using a Fe-based hardfacing alloy for DED. The findings underscore the outstanding balance of strength and ductility exhibited by as-printed hardfacing alloy, further enhanced by its high printability, highlighting its potential in producing wear-resistant structures for repair applications.

Abstract Serine is a key contributor to the generation of one-carbon units for DNA synthesis during cellular proliferation. In addition, it plays a crucial role in the production of antioxidants that prevent abnormal proliferation and stress in cancer cells. In recent studies, the relationship between cancer metabolism and the serine biosynthesis pathway has been highlighted. In this context, 3-phosphoglycerate dehydrogenase (PHGDH) is notable as a key enzyme that functions as the primary rate-limiting enzyme in the serine biosynthesis pathway, facilitating the conversion of 3-phosphoglycerate to 3-phosphohydroxypyruvate. Elevated PHGDH activity in diverse cancer cells is mediated through genetic amplification, posttranslational modification, increased transcription, and allosteric regulation. Ultimately, these characteristics allow PHGDH to not only influence the growth and progression of cancer but also play an important role in metastasis and drug resistance. Consequently, PHGDH has emerged as a crucial focal point in cancer research. In this review, the structural aspects of PHGDH and its involvement in one-carbon metabolism are investigated, and PHGDH is proposed as a potential therapeutic target in diverse cancers. By elucidating how PHGDH expression promotes cancer growth, the goal of this review is to provide insight into innovative treatment strategies. This paper aims to reveal how PHGDH inhibitors can overcome resistance mechanisms, contributing to the development of effective cancer treatments.

Currently generated nitrogen oxides (NOx) and unburned ammonia (NH3) can be converted into nitrogen and moisture that are harmless to the human body and environment using selective catalytic reduction (SCR). The concentrations of NOx and unburned NH3 emitted from the ammonia combustion engines are significantly higher than those emitted by engines using existing hydrocarbon fuels. In this study, ammonia, a representative carbon-free fuel, was used in spark ignition engines for existing passenger vehicles to identify the trends in exhaust gases emitted from engines and conduct experiments on after-treatment strategies to reduce NOx and unburned NH3. The addition of oxygen significantly maximized the conversion efficiency of the SCR after-treatment system by changing the concentration of both NOx and NH3 in the exhaust gas.

Abstract Triple-negative breast cancer (TNBC) is an aggressive breast cancer subtype with inferior outcomes owing to its low treatment response and high invasiveness. Based on abundant cancer-associated fibroblasts (CAFs) and frequent mutation of breast cancer-associated 1 (BRCA1) in TNBC, the characteristics of CAFs in TNBC patients with BRCA1 mutation compared to wild-type were investigated using single-cell analysis. Intriguingly, we observed that characteristics of inflammatory CAFs (iCAFs) were enriched in patients with BRCA1 mutation compared to the wild-type. iCAFs in patients with BRCA1 mutation exhibited outgoing signals to endothelial cells (ECs) clusters, including chemokine (C-X-C motif) ligand (CXCL) and vascular endothelial growth factor (VEGF). During CXCL signaling, the atypical chemokine receptor 1 (ACKR1) mainly interacts with CXCL family members in tumor endothelial cells (TECs). ACKR1-high TECs also showed high expression levels of angiogenesis-related genes, such as ANGPT2, MMP1, and SELE, which might lead to EC migration. Furthermore, iCAFs showed VEGF signals for FLT1 and KDR in TECs, which showed high co-expression with tip cell marker genes, including ZEB1 and MAFF, involved in sprouting angiogenesis. Moreover, BRCA1 mutation patients with relatively abundant iCAFs and tip cell gene expression exhibited a limited response to neoadjuvant chemotherapy, including cisplatin and bevacizumab. Importantly, our study observed the intricate link between iCAFs-mediated angiogenesis and chemoresistance in TNBC with BRCA1 mutation.

PURPOSE This study aimed to develop a Handball Academy Korea Physical Fitness Test Battery for youth handball athletes considering their characteristics using the Delphi/AHP method. METHODS After reviewing previous studies, an expert meeting was held to draft a battery. To select physical fitness variables, 17 experts with more than 10 years of research or coaching experience in related fields were invited. The contact validity of each variable was verified using the 1st and 2nd Delphi surveys. A decision-making method based on the analytic hierarchy process (AHP) was used to assign weights to each factor in the final physical fitness battery, which was selected based on the results of the Delphi survey. RESULTS Ten physical fitness factors, namely, length (CVR=1.00), weight (CVR=0.67), muscle strength (CVR=0.67), muscular endurance (CVR=0.83), cardiorespiratory fitness (CVR=0.83), flexibility (CVR=0.67), power (CVR=1.00), agility (CVR=1.00), speed (CVR=0.80), coordination (CVR=1.00), were determined. As test variables for physical fitness, height (CVR=0.83), arm span (CVR=0.67), lean body mass (CVR=0.64), handgrip strength (CVR=0.83), push-up (CVR=0.67), 20 m shuttle run (CVR=1.00), sit-and-reach (CVR=0.83), standing long jump (CVR=0.76), countermovement jump (CVR=0.67), ball speed (CVR=0.67), rollercoaster run (CVR=0.83), visual reaction (CVR=0.83), 20 m sprint (CVR=0.83), and ball handling (CVR=0.67) were found to be valid. Weight was calculated according to the relative importance of the determined variables. CONCLUSIONS The present findings indicate that the Handball Academy Korea Physical Fitness Test Battery can be used to evaluate the physical fitness of youth handball athletes and select potential players.

Abstract Anaplastic thyroid cancer (ATC) is one of the most aggressive tumors with an extremely poor prognosis. Based on the several biological features related to glutamine metabolism in ATC, we hypothesized glutaminolysis inhibition induces cell death in ATC cells. However, glutamine metabolism inhibition triggered cell growth arrest independent of cell death in ATC, suggesting that other signaling pathways avoid glutamine metabolism inhibition-induced stress exist. To investigate the functional mechanism against glutamine metabolism inhibition, we conducted mRNA and ATAC-Sequencing data analysis and found that glutamine deprivation increased ATF4-mediated one-carbon metabolism. When we inhibited PHGDH, the first rate-limiting enzyme for one-carbon metabolism, cell growth arrest was promoted upon glutamine metabolism inhibition by accumulating intracellular ROS. We next observed that the co-inhibition of glutamine and one-carbon metabolism could augment the anticancer effects of drugs used in patients with ATC. Finally, single-cell RNA sequencing analysis revealed that one-carbon metabolism was strengthened through the evolutionary process from PTC to ATC. Collectively, our data demonstrate that one-carbon metabolism has a potential role of modulation of cell fate in metabolic stress and can be a therapeutic target for enhancing antitumor effects in ATC.

We present extensions of the colorful Helly theorem for d-collapsible and d-Leray complexes, providing a common generalization to the matroidal versions of the theorem due to Kalai and Meshulam, the ‘very colorful’ Helly theorem introduced by Arocha, Bárány, Bracho, Fabila and Montejano and the ‘semi-intersecting’ colorful Helly theorem proved by Montejano and Karasev.

This paper presents a teleoperation system of robot grasping for undefined objects based on a real-time EEG (Electroencephalography) measurement and shared autonomy. When grasping an undefined object in an unstructured environment, real-time human decision is necessary since fully autonomous grasping may not handle uncertain situations. The proposed system allows involvement of a wide range of human decisions throughout the entire grasping procedure, including 3D movement of the gripper, selecting proper grasping posture, and adjusting the amount of grip force. These multiple decision-making procedures of the human operator have been implemented with six flickering blocks for steady-state visually evoked potentials (SSVEP) by dividing the grasping task into predefined substeps. Each substep consists of approaching the object, selecting posture and grip force, grasping, transporting to the desired position, and releasing. The graphical user interface (GUI) displays the current substep and simple symbols beside each flickering block for quick understanding. The tele-grasping of various objects by using real-time human decisions of selecting among four possible postures and three levels of grip force has been demonstrated. This system can be adapted to other sequential EEG-controlled teleoperation tasks that require complex human decisions.

Abstract The demand for anomaly detection, which involves the identification of abnormal samples, has continued to increase in various domains. In particular, with increases in the data volume of medical imaging, the demand for automated screening systems has also risen. Consequently, in actual clinical practice, radiologists can focus only on diagnosing patients with abnormal findings. In this study, we propose an unsupervised anomaly detection method for posteroanterior chest X-rays (CXR) using multiresolution patch-based self-supervised learning. The core aspect of our approach is to leverage patch images of different sizes for training and testing to recognize diverse anomalies characterized by unknown shapes and scales. In addition, self-supervised contrastive learning is applied to learn the generalized and robust features of the patches. The performance of the proposed method is evaluated using posteroanterior CXR images from a public dataset for training and testing. The results show that the proposed method is superior to state-of-the-art anomaly detection methods. In addition, unlike single-resolution patch-based methods, the proposed method consistently exhibits a good overall performance regardless of the evaluation criteria used for comparison, thus demonstrating the effectiveness of using multiresolution patch-based features. Overall, the results of this study validate the effectiveness of multiresolution patch-based self-supervised learning for detecting anomalies in CXR images.

The authors use resonant wireless power transfer to remotely trap and release nanoparticles in solution and detect their presence as a shift in impedance in real-time. This is accomplished using the extreme field confinement of a nanogap capacitor.

This study investigated defect formation and strain distribution in high-Mg-content Al-Mg alloys during normal rolling and cross-rolling processes. The finite element analysis (FEA) revealed the presence of wave defects and strain localization-induced zipper cracks in normal cold rolling, which were confirmed by the experimental results. The concentration of shear strain played a significant role in crack formation and propagation. However, the influence of wave defects was minimal in the cross-rolling process, which exhibited a relatively uniform strain distribution. Nonetheless, strain concentration at the edge and center regions led to the formation of zipper cracks and edge cracks, with more pronounced propagation observed in the experiments compared to FEA predictions. Furthermore, texture evolution was found to be a crucial factor affecting crack propagation, particularly with the development of the Goss texture component, which was observed via electron backscattered diffraction analysis at bending points. The Goss texture hindered crack propagation, while the Brass texture allowed cracks to pass through. This phenomenon was consistent with both FEA and experimental observations. To mitigate edge crack formation and propagation, potential strategies involve promoting the formation of the Goss texture at the edge through alloy and process conditions, as well as implementing intermediate annealing to alleviate stress accumulation. These measures can enhance the overall quality and reliability of Al-Mg alloys during cross-rolling processes. In summary, understanding the mechanisms of defect formation and strain distribution in Al-Mg alloys during rolling processes is crucial for optimizing their mechanical properties. The findings of this study provide insights into the challenges associated with wave defects, strain localization, and crack propagation. Future research and optimization efforts should focus on implementing strategies to minimize defects and improve the overall quality of Al-Mg alloys in industrial applications.

Abstract We examined the feasibility of explainable computer-aided detection of cardiomegaly in routine clinical practice using segmentation-based methods. Overall, 793 retrospectively acquired posterior–anterior (PA) chest X-ray images (CXRs) of 793 patients were used to train deep learning (DL) models for lung and heart segmentation. The training dataset included PA CXRs from two public datasets and in-house PA CXRs. Two fully automated segmentation-based methods using state-of-the-art DL models for lung and heart segmentation were developed. The diagnostic performance was assessed and the reliability of the automatic cardiothoracic ratio (CTR) calculation was determined using the mean absolute error and paired t-test. The effects of thoracic pathological conditions on performance were assessed using subgroup analysis. One thousand PA CXRs of 1000 patients (480 men, 520 women; mean age 63 ± 23 years) were included. The CTR values derived from the DL models and diagnostic performance exhibited excellent agreement with reference standards for the whole test dataset. Performance of segmentation-based methods differed based on thoracic conditions. When tested using CXRs with lesions obscuring heart borders, the performance was lower than that for other thoracic pathological findings. Thus, segmentation-based methods using DL could detect cardiomegaly; however, the feasibility of computer-aided detection of cardiomegaly without human intervention was limited.

Accurate identification of the shape and position of organs and abnormal objects (e.g., tumors) in medical images plays an important role in surgical planning as well as in the diagnosis and prognosis of diseases. However, this is difficult to achieve from two-dimensional medical images as these images present inaccurate and ambiguous organ boundaries. Further, traditional image processing-based boundary detection methods such as the Canny edge detector and Sobel operator exhibit poor boundary detection performance for images with substantial noise. Recently, the use of deep learning has resulted in improvements in semantic segmentation in medical images. In this paper, we propose a generic boundary-aware loss function to facilitate the effective discernment of the boundaries of organs and abnormal objects in medical images. Specifically, the proposed loss function introduces a boundary area and assigns higher weights to the loss of pixels located in the boundary area than to those in the non-boundary areas, thereby promoting effective learning in the boundary area. The results of experiments conducted using public medical datasets comprising colon polyp, skin lesion, and chest X-ray data indicate that the standard loss functions, such as cross-entropy loss and Dice loss, combined with the proposed boundary-aware loss function, achieve comparable or better performance than those without the boundary-aware loss function.

Background: Ulcerative colitis (UC) is a commonly encountered large intestine disease in the contemporary world that terminates into colorectal cancer; therefore, the timely treatment of UC is of major concern. Panax ginseng Meyer is an extensively consumed herbal commodity in South East Asian countries, especially Korea. It exhibits a wide range of biologically beneficial qualities for almost head-to-toe ailments in the body. Epimedium koreanum Nakai (EKN) is also a widely used traditional Korean herbal medicine used for treating infertility, rheumatism, and cardiovascular diseases. Materials and methods: Separately the anti-inflammatory activities of both red ginseng extracts (RGEs) and EKNs had been demonstrated in the past in various inflammatory models; however, we sought to unravel the anti-inflammatory activities of the combination of these two extracts in dextran sulfate sodium (DSS)-induced ulcerative colitis in mice model because the allopathic remedies for UC involve more side effects than benefits. Results: Our results have shown that the combination of RGE + EKN synergistically alleviated the macroscopic lesions in DSS-induced colitic mice such as colon shortening, hematochezia, and weight loss. Moreover, it restored the histopathological lesions in mice and decreased the levels of pro-inflammatory mediators and cytokines through the repression of nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) and nucleotide-binding domain (NOD)-like receptor protein 3 (NLRP-3) expression. In vitro, this combination also reduced the magnitude of nitric acid (NO), pro-inflammatory mediators and cytokine through NF-κB and mitogen-activated protein kinase (MAPK) pathways in RAW 264.7 mouse macrophage cells. Conclusion: In the light of these findings, we can endorse this combination extract as a functional food for the prophylactic as well as therapeutic treatment of UC in humans together with allopathic remedies.

Cardiovascular diseases prevail among modern societies and underdeveloped countries, and a high mortality rate has also been reported by the World Health Organization affecting millions of people worldwide. Hyperactive platelets are the major culprits in thrombotic disorders. A group of drugs is available to deal with such platelet-related disorders; however, sometimes, side effects and complications caused by these drugs outweigh their benefits. Ginseng and its nutraceuticals have been reported to reduce the impact of thrombotic conditions and improve cardiovascular health by antiplatelet mechanisms. This review provides (1) a comprehensive insight into the available pharmacological options from ginseng and ginsenosides (saponin and nonsaponin fractions) for platelet-originated cardiovascular disorders; (2) a discussion on the impact of specific functional groups on the modulation of platelet functions and how structural modifications among ginsenosides affect platelet activation, which may further provide a basis for drug design, optimization, and the development of ginsenoside scaffolds as pharmacological antiplatelet agents; (3) an insight into the synergistic effects of ginsenosides on platelet functions; and (4) a perspective on future research and the development of ginseng and ginsenosides as super nutraceuticals. Keywords: Antiplatelet, Ginsenosides, Nutraceutical, Structural modification, Synergism

We present a permanent magnet–based spherical wheel motor that can be used in omnidirectional mobility applications. The proposed motor consists of a ball‐shaped rotor with a magnetic dipole and a hemispherical shell with circumferential air‐core coils attached to the outer surface acting as a stator. Based on the rotational symmetry of the rotor poles and stator coils, we are able to model the rotor poles and stator coils as dipoles. A simple physical model constructed based on a torque model enables fast numerical simulations of motor dynamics. Based on these numerical simulations, we test various control schemes that enable constant‐speed rotation along arbitrary axes with small rotational attitude error. Torque analysis reveals that the back electromotive force induced in the coils can be used to construct a control scheme that achieves the desired results. Numerical simulations of trajectories confirm that even without explicit methods for correcting the rotational attitude error, it is possible to drive the motor with a low attitude error (

We propose a substrate with high thermal conductivity, manufactured by the low‐temperature co‐fired ceramic (LTCC) multilayer circuit process technology, as a new DC/DC converter platform for power electronics applications. We compare the reliability and power conversion efficiency of a converter using the LTCC substrate with the one using a conventional printed circuit board (PCB) substrate, to demonstrate the superior characteristics of the LTCC substrates. The power conversion efficiencies of the LTCC‐ and PCB‐based synchronous buck converters are 95.5% and 94.5%, respectively, while those of nonsynchronous buck converters are 92.5% and 91.3%, respectively, at an output power of 100 W. To verify the reliability of the LTCC‐based converter, two types of tests were conducted. Storage temperature tests were conducted at −20 °C and 85 °C for 100 h each. The variation in efficiency after the tests was less than 0.3%. A working temperature test was conducted for 60 min, and the temperature of the converter was saturated at 58.2 °C without a decrease in efficiency. These results demonstrate the applicability of LTCC as a substrate for power conversion systems.

In conventional wear simulation, the geometry must be updated for succeeding iterations to predict the accumulated wear. However, repeating this procedure up to the desired iteration is rather time consuming. Thus, a wear simulation process capable of reasonable quantitative wear prediction in reduced computational time is needed. This study aimed to develop an efficient wear simulation method to predict quantitative wear reasonably in reduced computational time without updating the geometry for succeeding iterations. The wear resistance of a stamping tool was quantitatively evaluated for different punch shapes (R3.0 and R5.5) and coating conditions (physical vapor deposition of CrN and AlTiCrN coatings) by using a progressive die set. To capture the nonlinear wear behavior with respect to strokes, a nonlinear equation from a modified form of Archard’s wear model was proposed. By utilizing the scale factor representing the changes in wear properties with respect to wear depth as input, the simulation can predict the behavior of rapidly increasing wear depth with respect to strokes after failure initiation. Furthermore, the proposed simulation method is efficient in terms of computational time because it does not need to perform geometry updates.

Abstract Genetically engineered mouse models are commonly preferred for studying the human disease due to genetic and pathophysiological similarities between mice and humans. In particular, Cre-loxP system is widely used as an integral experimental tool for generating the conditional. This system has enabled researchers to investigate genes of interest in a tissue/cell (spatial control) and/or time (temporal control) specific manner. A various tissue-specific Cre-driver mouse lines have been generated to date, and new Cre lines are still being developed. This review provides a brief overview of Cre-loxP system and a few commonly used promoters for expression of tissue-specific Cre recombinase. Also, we finally introduce some available links to the Web sites that provides detailed information about Cre mouse lines including their characterization.

Herein, a novel soft actuator design is presented that simultaneously enables a high‐output force at a low operating voltage and an adjustable large normal displacement. The electrohydraulic actuator powered by induced interfacial charge (EPIC) uses the amplified electrostatic force when the surface charge‐inducing phenomenon of the polyvinyl chloride (PVC) gel and the geometrical gradient of the actuator are combined to reinforce the zipping motion of the liquid layer. This actuator produces a more than 50‐fold higher blocking force than conventional dielectric liquid‐coupled electrostatic actuators at 2 kV. This implies the possibility of expanding the applicability of soft actuators to high‐power transducers. This actuator is modeled as parallel capacitors by considering the interfacial‐induced charge; the ratio of the dielectric constant of the polymer film to that of the dielectric liquid is analyzed as the principal design criterion for optimizing the performance characteristics. The actuator prototype exerts a force as high as 16 times its body weight (25.5 g) and exhibits a large normal displacement of more than 20% of its height (8.5 mm). Furthermore, four actuators can lift a weight of 1.25 kg and one actuator can be used as a large‐aperture (diameter: 30 mm) varifocal lens (374% focal length variation).

In comparison to conventional human-driven vehicles (HVs), connected and automated vehicles (CAVs) provide benefits (e.g., reducing travel time and improving safety). However, before the period of fully CAVs appears, there will be a situation in which both HVs and CAVs are present, and the traffic flow pattern may differ from that of a single class (e.g., HV or CAV). In this study, we developed a multi-class traffic assignment problem (TAP) for a transportation network that explicitly considered mixed modes (e.g., HV and CAV). As a link’s travel time is dependent on the degree of mixed flows, each mode required an asymmetric interaction cost function. For TAP, the multi-class user equilibrium (UE) model was used for the route choice model. A route-based variational inequality (VI) formulation was used to represent the multi-class TAP and solve it using the gradient projection (GP) algorithm. It has been demonstrated that the GP algorithm is an effective route-based solution for solving the single-class user equilibrium (UE) problem. However, it has rarely been applied to solving asymmetric UE problems. In this study, the single-class GP algorithm was extended to solve the multi-class TAP. The numerical results indicated the model’s efficacy in capturing the features of the proposed TAP utilizing a set of simple networks and real transportation networks. Additionally, it demonstrated the computational effectiveness of the GP algorithm in solving the multi-class TAP.

This paper investigates the reduction of springback by an electrically single-pulsed current for an ultra-high-strength martensitic steel sheet, MART1470 1.2t. In order to evaluate the springback reduction by the electric current, V-bending tests were performed with various parameter-sets (current density and pulse duration). The amount of springback reduction was then calculated from the measured bent-angle of tested specimens. Experimental results show the springback is reduced with the increase in the current density, the pulse duration, and the electric energy density. In order to clarify thermal and athermal portions in the effect of electric current on the springback reduction, two ratios of force and isothermal flow stress were calculated based on bending theory. From the comparison of the ratios, it is noted that the athermal portion mainly contributes to the force relaxation, so the springback amount decreases. The athermal portion significantly increases as the electric energy density increases. Microstructures and micro-Vickers hardness were observed to confirm the applicability of the single-pulsed current to forming processes in practice. The springback reduction can be achieved up to 37.5% without severe changes in material properties when the electric energy density increases up to 281.3 mJ/mm3. Achievable reduction is 85.4% for the electric energy density of 500 mJ/mm3, but properties remarkably change.

Thyroid cancer (TC) includes tumors of follicular cells; it ranges from well differentiated TC (WDTC) with generally favorable prognosis to clinically aggressive poorly differentiated TC (PDTC) and undifferentiated TC (UTC). Papillary thyroid cancer (PTC) is a WDTC and the most common type of thyroid cancer that comprises almost 70–80% of all TC. PTC can present as a solid, cystic, or uneven mass that originates from normal thyroid tissue. Prognosis of PTC is excellent, with an overall 10-year survival rate >90%. However, more than 30% of patients with PTC advance to recurrence or metastasis despite anti-cancer therapy; consequently, systemic therapy is limited, which necessitates expansion of improved clinical approaches. We strived to elucidate genetic distinctions due to patient-derived anti-cancer drug-sensitive or -resistant PTC, which can support in progress novel therapies. Patients with histologically proven PTC were evaluated. PTC cells were gained from drug-sensitive and -resistant patients and were compared using mRNA-Seq. We aimed to assess the in vitro and in vivo synergistic anti-cancer effects of a novel combination therapy in patient-derived refractory PTC. This combination therapy acts synergistically to promote tumor suppression compared with either agent alone. Therefore, genetically altered combination therapy might be a novel therapeutic approach for refractory PTC.

Recently, deep learning has been employed in medical image analysis for several clinical imaging methods, such as X-ray, computed tomography, magnetic resonance imaging, and pathological tissue imaging, and excellent performance has been reported. With the development of these methods, deep learning technologies have rapidly evolved in the healthcare industry related to hair loss. Hair density measurement (HDM) is a process used for detecting the severity of hair loss by counting the number of hairs present in the occipital donor region for transplantation. HDM is a typical object detection and classification problem that could benefit from deep learning. This study analyzed the accuracy of HDM by applying deep learning technology for object detection and reports the feasibility of automating HDM. The dataset for training and evaluation comprised 4492 enlarged hair scalp RGB images obtained from male hair-loss patients and the corresponding annotation data that contained the location information of the hair follicles present in the image and follicle-type information according to the number of hairs. EfficientDet, YOLOv4, and DetectoRS were used as object detection algorithms for performance comparison. The experimental results indicated that YOLOv4 had the best performance, with a mean average precision of 58.67.

Background: Ginseng (Panax ginseng) is a widely used traditional herbal supplement that possesses various health-enhancing efficacies. Various ginseng products are available in market, especially in the Korean peninsula, in the form of drinks, tablets, and capsules. The different ginseng types include the traditional red ginseng extract (RGE), white ginseng, and black red ginseng extract (BRGE). Their fermented and enzyme-treated products are also available. Different treatment regimens alter the bioavailability of certain compounds present in the respective ginseng extracts. Therefore, in this study, we aimed to compare the antioxidant and immune-stimulating activities of RGE, BRGE, and fermented red ginseng extract (FRGE). Methods: We used an acetaminophen-induced oxidative stress model for investigating the reduction of oxidative stress by RGE, BRGE, and FRGE in Sprague Dawley rats. A cyclophosphamide-induced immunosuppression model was used to evaluate the immune-stimulating activities of these ginseng extracts in BALB/c mice. Results: Our results showed that most prominently, RGE (in almost all experiments) exhibited excellent antioxidant effects via increasing superoxide dismutase, catalase, and glutathione peroxidase activities in the liver and decreasing serum 8-hydroxy-2′-deoxyguanosine, aspartate aminotransferase, and lactate dehydrogenase levels compared with the groups treated with FRGE and BRGE. Moreover, RGE significantly increased the number of white blood cells, especially T and B lymphocytes, and antibody-forming cells in the spleen and thymus, and it also activated a number of immune cell subtypes. Conclusion: Taken together, these results indicate that RGE is the best supplement for consumption in everyday life for overall health-enhancing properties. Keywords: Antioxidant, Black red ginseng extract, Fermented red ginseng extract, Immune stimulation, Red ginseng extract

We propose a multilayered‐substrate‐based power semiconductor discrete device package for a low switching loss and high heat dissipation. To verify the proposed package, cost‐effective, low‐temperature co‐fired ceramic, multilayered substrates are used. A bare die is attached to an embedded cavity of the multilayered substrate. Because the height of the pad on the top plane of the die and the signal line on the substrate are the same, the length of the bond wires can be shortened. A large number of thermal vias with a high thermal conductivity are embedded in the multilayered substrate to increase the heat dissipation rate of the package. The packaged silicon carbide Schottky barrier diode satisfies the reliability testing of a high‐temperature storage life and temperature humidity bias. At 175 °C, the forward current is 7 A at a forward voltage of 1.13 V, and the reverse leakage current is below 100 μA up to a reverse voltage of 980 V. The measured maximum reverse current (IRM), reverse recovery time (Trr), and reverse recovery charge (Qrr) are 2.4 A, 16.6 ns, and 19.92 nC, respectively, at a reverse voltage of 300 V and di/dt equal to 300 A/μs.

Malware family classification is grouping malware samples that have the same or similar characteristics into the same family. It plays a crucial role in understanding notable malicious patterns and recovering from malware infections. Although many machine learning approaches have been devised for this problem, there are still several open questions including, “Which features, classifiers, and evaluation metrics are better for malware familial classification”? In this paper, we propose a machine learning approach to Android malware family classification using built-in and custom permissions. Each Android app must declare proper permissions to access restricted resources or to perform restricted actions. Permission declaration is an efficient and obfuscation-resilient feature for malware analysis. We developed a malware family classification technique using permissions and conducted extensive experiments with several classifiers on a well-known dataset, DREBIN. We then evaluated the classifiers in terms of four metrics: macrolevel F1-score, accuracy, balanced accuracy (BAC), and the Matthews correlation coefficient (MCC). BAC and the MCC are known to be appropriate for evaluating imbalanced data classification. Our experimental results showed that: (i) custom permissions had a positive impact on classification performance; (ii) even when the same classifier and the same feature information were used, there was a difference up to 3.67% between accuracy and BAC; (iii) LightGBM and AdaBoost performed better than other classifiers we considered.

Faults represent important analytical targets for the identification of perceptual ground motions and associated seismic hazards. In particular, during oil production, important data such as the path and flow rate of fluid flows can be obtained from information on fault location and their connectivity. Seismic attributes are conventional methods used for fault detection, whereby information obtained from seismic data are analyzed using various property processing methods. The analyzed data eventually provide information on fault properties and imaging of fault surfaces. In this study, we propose an efficient workflow for fault detection and extraction of requisite information to construct a fault surface model using 3D seismic cubes. This workflow not only improves the ability to detect faults but also distinguishes the edges of a fault more clearly, even with the application of fewer attributes compared to conventional workflows. Thus, the computing time of attribute processing is reduced, and fault surface cubes are generated more rapidly. In addition, the reduction in input variables reduces the effect of the interpreter’s subjective intervention on the results. Furthermore, the clustering method can be applied to the azimuth and dip of the fault to be extracted from the complexly intertwined fault faces and subsequently imaged. The application of the proposed workflow to field data obtained from the Vincentian oil field in Australia resulted in a significant reduction in noise compared to conventional methods. It also led to clearer and continuous edge detection and extraction.

Accurate identification of the boundaries of organs or abnormal objects (e.g., tumors) in medical images is important in surgical planning and in the diagnosis and prognosis of diseases. In this study, we propose a deep learning-based method to segment lung areas in chest X-rays. The novel aspect of the proposed method is the self-attention module, where the outputs of the channel and spatial attention modules are combined to generate attention maps, with each highlighting those regions of feature maps that correspond to “what” and “where” to attend in the learning process, respectively. Thereafter, the attention maps are multiplied element-wise with the input feature map, and the intermediate results are added to the input feature map again for residual learning. Using X-ray images collected from public datasets for training and evaluation, we applied the proposed attention modules to U-Net for segmentation of lung areas and conducted experiments while changing the locations of the attention modules in the baseline network. The experimental results showed that our method achieved comparable or better performance than the existing medical image segmentation networks in terms of Dice score when the proposed attention modules were placed in lower layers of both the contracting and expanding paths of U-Net.

Traditionally, sarcopenia has defined as amount of absolute muscle mass adjusted by height in the elderly people. However, relative muscle mass adjusted by weight has been used extensively in most non-alcoholic fatty liver disease (NAFLD) studies. Here, we attempted to investigate the pitfall of adjusted muscle mass by weight to evaluate association between sarcopenia and NAFLD. Adult subjects (n = 1343) who underwent a health check-up were finally included for analysis. The weight-adjusted skeletal muscle mass index (wSMI) and height-adjusted SMI (hSMI) calculated by dividing the total appendicular skeletal muscle (ASM) by weight or the square of height, respectively. Prevalence of sarcopenia defined by wSMI in the NAFLD group was significantly higher than in the control group (1.3% vs. 8.8%, p < 0.001). However, there was no difference in the prevalence of sarcopenia defined by hSMI between the control and NAFLD groups (2.0% vs. 0.8%, p = 0.055). Since body weight was the most potent independent risk factor for NAFLD in multivariable logistic regression analysis, abnormal rates (

A simple, sensitive, and rapid UHPLC-MS/MS method was developed for the simultaneous determination of veratraldehyde and its metabolite veratric acid in rat plasma. Cinnamaldehyde was used as an internal standard (IS) and the one-step protein precipitation method with 0.2% formic acid in acetonitrile (mobile phase B) was used for the sample extraction. Reversed C18 column (YMC-Triart C18 column, 50 mm × 2.0 mm, 1.9 µm) was used for chromatographic separation and was maintained at 30 °C. The total run time was 4.5 min and the electrospray ionization in positive mode was used with the transition m/z 167.07 → 139.00 for veratraldehyde, m/z 183.07 → 139.00 for veratric acid, and m/z 133.00 → 55.00 for IS. The developed method exhibited good linearity (r2 ≥ 0.9977), and the lower limits of quantification ranged from 3 to 10 ng/mL for the two analytes. Intra-day precision and accuracy parameters met the criteria (within ±15%) during the validation. The bioanalytical method was applied for the determination of veratraldehyde and veratric acid in rat plasma after oral and percutaneous administration of 300 and 600 mg/kg veratraldehyde. Using the analytical methods established in this study, we can confirm the absorption and metabolism of veratraldehyde in rats for various routes.

A surge of interest in microneedle (MN) vaccines as a novel vaccination system has emerged. Before the clinical application of MN vaccine, an assessment of potential biological risks to skin and quality control of MN must be performed. Therefore, the present study aims to evaluate the physicochemical properties of MN and to evaluate the histological changes and inflammatory cell infiltrations after the application of MN with hepatitis B surface antigen (HBsAg). During in vitro and in vivo release testing, HBsAg MN released over 70% of HBsAg at 30 min. During the pyrogen test of HBsAg MN in rabbit, no rabbit showed an individual rise in temperature of 0.5 °C or more. MN with HBsAg produced the moderate immunization in mice. MN application did not alter the thickness of dermal and epidermal layers in mice. In addition, the topical applications of MN and MN for hepatitis B vaccine did not acutely induce the inflammation, allergic reaction, dermal toxicity and skin irritation. Thus, the MN system for the delivery of HBsAg could be the promising technology in the hepatitis B vaccination.

Glucagon-like peptide-1 (GLP-1) is a well-known incretin hormone secreted from enteroendocrinal L cells in response to nutrients, such as glucose and dietary fat, and controls glycemic homeostasis. However, the detailed intracellular mechanisms of how L cells control GLP-1 secretion in response to nutrients still remain unclear. Here, we report that bone morphogenetic protein (BMP) signaling pathway plays a pivotal role to control GLP-1 secretion in response to nutrient replenishment in well-established mouse enteroendocrinal L cells (GLUTag cells). Nutrient starvation dramatically reduced cellular respiration and GLP-1 secretion in GLUTag cells. Transcriptome analysis revealed that nutrient starvation remarkably reduced gene expressions involved in BMP signaling pathway, whereas nutrient replenishment rescued BMP signaling to potentiate GLP-1 secretion. Transient knockdown of inhibitor of DNA binding (ID)1, a well-known target gene of BMP signaling, remarkably reduced GLP-1 secretion. Consistently, LDN193189, an inhibitor of BMP signaling, markedly reduced GLP-1 secretion in L cells. In contrast, BMP4 treatment activated BMP signaling pathway and potentiated GLP-1 secretion in response to nutrient replenishment. Altogether, we demonstrated that BMP signaling pathway is a novel molecular mechanism to control GLP-1 secretion in response to cellular nutrient status. Selective activation of BMP signaling would be a potent therapeutic strategy to stimulate GLP-1 secretion in order to restore glycemic homeostasis.

Recently, Achyranthis radix extract has been studied as a therapeutic agent for dry eye disease that occurs from fine dust. The aim of this study was the development of Achyranthis radix extract-loaded eye drop formulations using lubricants, generally used for artificial tear eye drops. Ecdysterone was used as a marker compound for Achyranthis radix extract and 1% Achyranthis radix extract solution contained 14.37 ± 0.04 μg/mL of ecdysterone. Before formulation studies, a new method was performed to evaluate pigmentation, which might be caused by eye drops of herbal extract. A comparative study of the water retention ability of each formulation and ability to prevent the death of conjunctival epithelial cells in dry conditions was conducted. Moreover, treatment of Achyranthis radix extract (USL) eye drop formulation exhibited a significant inhibitory effect on inflammation in a concentration-dependent manner. The long-term and accelerated stability tests showed that lubricants could contribute to the stability of herbal extracts in solution. In conclusion, hyaluronic acid showed a good effect on the development of eye drop formulation using Achyranthis radix extracts for treating dry eye disease.

Diabetes mellitus (DM) has become a major health problem in most countries of the world. DM causes many complications, including hyperglycemia, diabetic ketoacidosis, and death. In Asia, mulberry has been used widely in the treatment of DM. Combination of drugs with herbal medicine may reduce the unwanted side effects caused by drugs. In this study, the influence of extended mulberry leaves extract (MLE) intake on metformin (Met) was evaluated in terms of pharmacokinetics and pharmacodynamics in DM-induced rats. Three week-treatment of MLE alone produced the anti-hyperglycemic effect (around 24%) if compared to the control. Interestingly, Met administration after MLE treatment for 3 weeks enhanced about 49% of the anti-hyperglycemic effect of Met. In addition, the extended intake of MLE potentiated the anti-hyperglycemic effect of Met on various concentrations. This potentiated anti-hyperglycemic effect of Met appears to be due to the pharmacokinetic change of Met. In this study, 3 week-treatment of MLE reduced the elimination of Met in DM-induced rats. In addition, MLE reduced the human organic cation transporter 2 (hOCT2) activity in a concentration-dependent manner. Thus, these findings suggest that MLE lowered the elimination of Met via inhibiting the hOCT2.

Omega-3 fatty acid plays a role in protecting cells in the human body, maintaining the structure of the cell, and helping smooth metabolism. Also, it inhibits the formation of blood clotting and is effective in enhancing the formation of bone. However, the instability due to fatty acid oxidation and a fishy smell are the reasons it is avoided by people. In this study, we tried to obtain the omega-3 powder through spray-drying method using a variety of binders and surfactants for improving the limit of omega-3 fatty acid. First of all, an olive oil was used instead of omega-3 for optimization of the preparation of spray-dried omega-3 powder. Through the screening of binders and surfactants, γ-cyclodextrin and hydrogenated lecithin were chosen as a binder and a surfactant, respectively. Omega-3-loaded spray-dried powder was obtained, eventually. The morphology of omega-3-loaded spray-dried powder was spherical of 310 nm and the DHA amount was 98%. This study suggested that the transformation of omega-3 fatty acid into solid state by spray-drying using a binder and a surfactant was successively performed.

In this paper, we shed light on the dynamic characteristics of rational group behaviors and the relationship between monetary policy and economic units in the financial market by using an agent-based model (ABM), the Hurst exponent, and the Shannon entropy. First, an agent-based model is used to analyze the characteristics of the group behaviors at different levels of irrationality. Second, the Hurst exponent is applied to analyze the characteristics of the trend-following irrationality group. Third, the Shannon entropy is used to analyze the randomness and unpredictability of group behavior. We show that in a system that focuses on macro-monetary policy, steep fluctuations occur, meaning that the medium-level irrationality group has the highest Hurst exponent and Shannon entropy among all of the groups. However, in a system that focuses on micro-monetary policy, all group behaviors follow a stable trend, and the medium irrationality group thus remains stable, too. Likewise, in a system that focuses on both micro- and macro-monetary policies, all groups tend to be stable. Consequently, we find that group behavior varies across economic units at each irrationality level for micro- and macro-monetary policy in the financial market. Together, these findings offer key insights into monetary policy.