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The application of a doubly Type-Ⅱ censoring scheme, where observations are censored at both the left and right ends, is often used in various fields including social science, psychology, and economics. However, the observed sample size under this censoring scheme may not be large enough to apply a likelihood-based approach due to the occurrence of censoring at both ends. To effectively respond to this difficulty, we propose a pivotal-based approach within a doubly Type-Ⅱ censoring framework, focusing on two key aspects: Estimation for parameters of interest and prediction for missing or censored samples. The proposed approach offers two prominent advantages, compared to the likelihood-based approach. First, this approach leads to exact confidence intervals for unknown parameters. Second, it addresses prediction problems in a closed-form manner, ensuring computational efficiency. Moreover, novel algorithms using a pseudorandom sequence, which are introduced to implement the proposed approach, have remarkable scalability. The superiority and applicability of the proposed approach are substantiated in Monte Carlo simulations and real-world case analysis through a comparison with the likelihood-based approach.

In many applications, modeling based on a normal kernel is preferred because not only does the normal kernel belong to the family of stable distributions, but also it is easy to satisfy the stationary condition in the stochastic process. However, the characteristic of the data, such as count or proportion, is a major obstacle to complete modeling based on a normal distribution. To solve a limited boundary or non-normal distribution problem, we provided a novel transformation method and proposed a nonparametric Bayesian approach based on a normal kernel of the transformed variable. In particular, the provided transformation transforms any probability space into a real space and is free from the constraints of the previous transformation, such as skewness, presence of power, and bounded domains. Another advantage was that it was possible to use the Dirichlet process mixture model with full conditional posterior distributions for all parameters, leading to a fast convergence rate in the Markov chain Monte Carlo. The proposed methodology was illustrated with simulated datasets and two real datasets with non-normal distribution problems. In addition, to demonstrate the superiority of the proposed methodology, the comparison with the transformed Bernstein polynomial model was made in the real data analysis.

This paper proposes an inference approach based on a pivotal quantity under the adaptive progressive Type-II censoring scheme. To exemplify the proposed methodology, an extensively employed distribution, a Pareto distribution, is utilized. This distribution has limitations in estimating confidence intervals for unknown parameters from classical methods such as the maximum likelihood and bootstrap methods. For example, in the maximum likelihood method, the asymptotic variance-covariance matrix does not always exist. In addition, both classical methods can yield confidence intervals that do not satisfy nominal levels when a sample size is not large enough. Our approach resolves these limitations by allowing us to construct exact intervals for unknown parameters with computational simplicity. Aside from this, the proposed approach leads to closed-form estimators with properties such as unbiasedness and consistency. To verify the validity of the proposed methodology, two approaches, a Monte Carlo simulation and a real-world data analysis, are conducted. The simulation testifies to the superior performance of the proposed methodology as compared to the maximum likelihood method, and the real-world data analysis examines the applicability and scalability of the proposed methodology.

Currently, more than 30% of the fine dust generated in the Seoul metropolitan area is a pollutant emitted from automobiles such as diesel vehicles, and air pollution caused by this is becoming increasingly serious. In addition, the importance of electric vehicle distribution is increasing due to the strengthening of international environmental regulations on automobile exhaust gas and increasing the possibility of depletion of petroleum resources. This manuscript proposes a method for selecting an optimal electric vehicle charging station location in expanding charging facilities to activate electric vehicle distribution. For the sake of illustration, directions will be provided on how to select the best location for electric vehicle charging stations using data from Seoul, which has the best access. As the features, the number of living population and work force people and the number of guest facilities, which are determined to affect demand for quick charging, are considered. The missing values of the observed data are imputed based on the kriging technique from spatial correlation, and by segmenting the data through clustering, a representative technique of unsupervised learning, the characteristics of each cluster are examined and the characteristics of the clusters are identified. In addition, machine learning techniques such as the elastic net, random forest, support vector machine, and extreme gradient boosting are applied to examine the influence of the features used in predicting classes of data. In clustering analysis, the optimal number of clusters was determined to be 3 based on the heuristic and information-theoretic methods, and all the machine learning techniques considered showed that the number of work force population is the most important feature in predicting classes of data. All things considered from our results, it is reasonable to install quick electric vehicle charging stations in the places with the highest concentration of work force population and guest facility.

This paper provides an estimation method for an unknown parameter by extending weighted least-squared and pivot-based methods to the Gompertz distribution with the shape and scale parameters under the progressive Type-II censoring scheme, which induces a consistent estimator and an unbiased estimator of the scale parameter. In addition, a way to deal with a nuisance parameter is provided in the pivot-based approach. For evaluation and comparison, the Monte Carlo simulations are conducted, and real data are analyzed.

This paper proposes a new approach based on the regression framework employing a pivotal quantity to estimate unknown parameters of a Weibull distribution under the progressive Type-II censoring scheme, which provides a closed form solution for the shape parameter, unlike its maximum likelihood estimator counterpart. To resolve serious rounding errors for the exact mean and variance of the pivotal quantity, two different types of Taylor series expansion are applied, and the resulting performance is enhanced in terms of the mean square error and bias obtained through the Monte Carlo simulation. Finally, an actual application example, including a simple goodness-of-fit analysis of the actual test data based on the pivotal quantity, proves the feasibility and applicability of the proposed approach.

This paper derives the entropy of a generalized half-logistic distribution based on Type-II censored samples, obtains some entropy estimators by using Bayes estimators of an unknown parameter in the generalized half-logistic distribution based on Type-II censored samples and compares these estimators in terms of the mean squared error and the bias through Monte Carlo simulations.

The maximum likelihood method is the most widely used estimation method. On the other hand, it can produce substantial bias, and an approximate confidence interval based on the maximum likelihood estimator cannot be valid when the sample size is small. Because the sizes of the record values are considerably smaller than the original sequence observed in the majority of cases, a method appropriate for this situation is required for precise inference. This paper provides the exact confidence intervals for unknown parameters and exact predictive intervals for the future upper record values by providing some pivotal quantities in the two-parameter Rayleigh distribution based on the upper record values. Finally, the validity of the proposed inference methods was examined from Monte Carlo simulations and real data.

The body color state is an important determinant of the value of golden severum (Heros efasciatus)—a popular ornamental fish. The use of dietary supplements to improve the color development and health of this species is unexplored. Herein, the effects of marigold extract (MG) and carophyll red (CR) are examined on the growth, body color development, antioxidant properties, and innate immunity in golden severum. Fish were maintained under controlled water quality conditions (pH, temperature, and dissolved oxygen) and fed six experimental diets containing either 0% MG and CR, 1% MG, 2% MG, 5% MG, 0.5% CR, or 2% CR for five weeks. Both MG and CR significantly decreased lipid peroxide levels in hepatic tissues. In contrast, only MG enhanced the activities of reactive oxygen species (ROS)-scavenging enzymes (superoxide dismutase and catalase). Although MG and CR decreased the respiratory burst activity of splenic leukocytes, other innate immune parameters remained unchanged. Additionally, MG and CR stimulated body color development patterns in golden severum that reflect their unique coloring principles. The ROS-scavenging abilities of MG and CR appear to be related to their antioxidant activity. Hence, MG and CR at the optimal levels of 1.0% and 0.5%, respectively, can improve the body color of golden severum and protect against oxidative stress.

We developed an electro-mechanical actuator for use as a steering device for railway vehicles. The specifications for a 50 kN-class electro-mechanical actuator capable of steering control for a sharp of a railway radius curve of up to 250 m, and with Direct Drive motor (DD motor) specifications, were derived as a power source to drive it. The DD motor and an electric mechanical steering actuator equipped with it were designed and a prototype was manufactured. As a result of testing laboratory tests on motor and actuator prototypes, all performance requirements were satisfied. We conducted a field test on the actuator prototype by installing it on a railway vehicle to verify the steering angle performance. The steering action of the actuator worked well when running in curved sections, and the steering angles measured for each curve were in line with the target steering angles. The mean error between the target steering angle and the measured steering angle was only 3.4%, indicating that the wheel steering action of the developed steering system was working very well. Therefore, the developed electro-mechanical actuator is expected to be fully utilized as a steering device for railway vehicles by meeting all the performance requirements of the steering system.

Underwater optical images face various limitations that degrade the image quality compared with optical images taken in our atmosphere. Attenuation according to the wavelength of light and reflection by very small floating objects cause low contrast, blurry clarity, and color degradation in underwater images. We constructed an image data of the Korean sea and enhanced it by learning the characteristics of underwater images using the deep learning techniques of CycleGAN (cycle-consistent adversarial network), UGAN (underwater GAN), FUnIE-GAN (fast underwater image enhancement GAN). In addition, the underwater optical image was enhanced using the image processing technique of Image Fusion. For a quantitative performance comparison, UIQM (underwater image quality measure), which evaluates the performance of the enhancement in terms of colorfulness, sharpness, and contrast, and UCIQE (underwater color image quality evaluation), which evaluates the performance in terms of chroma, luminance, and saturation were calculated. For 100 underwater images taken in Korean seas, the average UIQMs of CycleGAN, UGAN, and FUnIE-GAN were 3.91, 3.42, and 2.66, respectively, and the average UCIQEs were measured to be 29.9, 26.77, and 22.88, respectively. The average UIQM and UCIQE of Image Fusion were 3.63 and 23.59, respectively. CycleGAN and UGAN qualitatively and quantitatively improved the image quality in various underwater environments, and FUnIE-GAN had performance differences depending on the underwater environment. Image Fusion showed good performance in terms of color correction and sharpness enhancement. It is expected that this method can be used for monitoring underwater works and the autonomous operation of unmanned vehicles by improving the visibility of underwater situations more accurately.

Abstract Interleukin-7 (IL-7) is a cytokine known for its importance in T cell development and survival. How IL-7 shapes CD8 T cell responses during an acute viral infection is less understood. We had previously shown that IL-7 signaling deficient mice have reduced accumulation of influenza-specific CD8 T cells following influenza infection. We sought to determine whether IL-7 affects early CD8 T cell expansion in the mediastinal lymph node and effector function in the lungs. Using IL-7Rα signaling deficient mice, we show that IL-7 is required for a normal sized mediastinal lymph node and the early clonal expansion of influenza-specific CD8 T cells therein. We show that IL-7 plays a cell-intrinsic role in the accumulation of NP366–374 and PA224–233-specific CD8 T cells in the lymph node. We also found that IL-7 shapes terminal differentiation, degranulation and cytokine production to a greater extent in PA224–233-specific than NP366–374-specific CD8 T cells. We further demonstrate that IL-7 is induced in the lung tissue by viral infection and we characterize multiple cellular sources that contribute to IL-7 production. Our findings on IL-7 and its effects on lower respiratory diseases will be important for expanding the utility of therapeutics that are currently available.

Abstract Developing an effective and efficient recycling process for marine debris (MD) is one of the most urgent issues to maintain environmental sustainability on Earth. However, restricted storage capacities and secondary pollution (e.g., microbial adhesion, putrefaction) limit the proper MD recycling. Here, we proposed a complete eco-friendly low-temperature MD pulverizing system that utilizes excessive liquefied natural gas (LNG) cold energy (LCE) in an LNG propulsion ship to improve the efficiency and effectiveness of MD recycling. The prototype design of the low-temperature pulverization (LTP) system showed that consumable refrigerant (liquid nitrogen) up to 2831 kg per hour could be substituted. Furthermore, with a 20% ship output, 1250 kg of MD could be treated with 363 kg of additional refrigerant. In addition, LTP systems utilizing LCE could increase the storage capacity by more than 10 times compared to bulk MD while minimizing the required energy consumption. To determine the feasibility of LTP for MD recycling, four types of plastics obtained from actual MD from a coastal area in Busan, Korea were classified and tested.

Renal epithelioid angiomyolipoma (EAML) is a rare variant of angiomyolipoma (AML), with a prominent epithelioid component. EAML usually presents as a large heterogeneous soft tissue lesion with intratumoral hemorrhage and variable necrosis or cystic changes. We present a case of multiloculated cystic renal EAML mimicking renal cell carcinoma in a 64-year-old female. Intracystic massive hemorrhage, hyperattenuating wall and septa on an unenhanced study, and enlarged intratumoral vessels can be helpful imaging features for distinguishing renal EAML from renal cell carcinoma.

Abstract This study was conducted to examine the physiological activity of Ulva ohnoi, some of which may be used for food or natural products but could disturbing coastal ecosystems due to large scale green-tide, to check values of U. ohnoi oil through experimental results. U. ohnoi oil was extracted from bulk of Ulva biomass to confirm its antioxidant and antibacterial activity, and the efficacy of U. ohnoi oil in the state of inflammation was confirmed through animal experiments. To confirm the anti-inflammatory effect, a mouse model induced with DSS was used. As a result of measuring NO using plasma after induction of inflammation, the amount of NO produced in the U. ohnoi oil group was decreased compared to the control group. Expression of inflammatory cytokines TNF-α, IL-6, and IL-1β was decreased compared to the control group. As a result of observing H&E staining, lower crypt loss and inflammatory cell infiltration were found in the U. ohnoi oil group compared to the control group. Consequently, U. ohnoi oil appears to have great anti-inflammatory properties.

Current industrial practices and approaches are simplified and do not describe the actual behavior of plated elements of offshore topside structures for safety design due to fires. Therefore, it is better to make up for the defective methods with integrated fire safety design methods based on fire resistance characteristics such as residual strength capacity. This study numerically investigates the residual strength of steel stiffened panels exposed to hydrocarbon jet fire. A series of nonlinear finite element analyses (FEAs) were carried out with varying probabilistic selected exposures in terms of the jet fire location, side, area, and duration. These were used to assess the effects of exposed fire on the residual strength of a steel stiffened panel on a ship-shaped offshore structure. A probabilistic approach with a feasible fire location was used to determine credible fire scenarios in association with thermal structural responses. Heat transfer analysis was performed to obtain the steel temperature, and then the residual strength was obtained for the credible fire scenarios under compressive axial loading using nonlinear FEA code. The results were used to derive closed-form expressions to predict the residual strength of steel stiffened panels with various exposure to jet fire characteristics. The results could be used to assess the sustainability of structures at risk of exposure to fire accidents in offshore installations.

Objectives: To investigate the effects of a smartphone‐based oral and whole‐body exercise programme on oral function in older adults. Methods: Individuals aged 65 years or above were randomized into three groups (non‐app use, app use and control group), and a combined oral and whole‐body exercise programme was conducted for 5 weeks. Oral muscle strength, saliva flow rate, Oral Health Impact Profile‐14 (OHIP‐14), and Geriatric Oral Health Assessment Index (GOHAI) were measured before and after the intervention. The changes in each group were analysed at the end of the programme using paired sample t‐tests, and the differences among the groups were analysed using the chi‐square test, Fisher's exact test and ANOVA. Results: The anterior tongue strength increased by 2.80 kPa after the intervention in the non‐app use group; however, the change was not statistically significant. In the app use group, the anterior tongue strength significantly increased by 4.48 kPa. The saliva flow rate increased by 0.54 and 0.71 g/min in the non‐app and app use groups, respectively, after the intervention (p < 0.05), and the change was greater in the app use group than in the other groups (p < 0.01). There were no significant changes in the posterior tongue strength, cheek strength, OHIP‐14 or GOHAI scores over the course of the study. Conclusions: A smartphone‐based combined oral and whole‐body exercise programme can improve anterior tongue strength and saliva flow rate in older participants. The programme, however, did not result in significant changes in posterior tongue strength, cheek strength and perceived oral health. [ABSTRACT FROM AUTHOR]

Introduction: Acute coronary syndrome (ACS) is one of the leading causes of death from cardiovascular diseases worldwide, with ST-segment elevation myocardial infarction (STEMI) representing a severe form of ACS that exhibits high prevalence and mortality rates. This study proposes a new method for accurately diagnosing STEMI and categorizing the infarction area in detail, based on 12-lead electrocardiogram (ECG) data using a deep learning-based artificial intelligence (AI) algorithm. Methods: Utilizing an ECG database consisting of 888 myocardial infarction (MI) patients, this study enhanced the generalization ability of the AI model through five-fold cross-validation. The developed ST-segment elevation (STE) detector accurately identified STE across all 12 leads, which is a crucial indicator for the clinical ECG diagnosis of STEMI. This detector was employed in the AI model to differentiate between STEMI and non-ST-segment elevation myocardial infarction (NSTEMI). Results: In the process of distinguishing between STEMI and NSTEMI, the average area under the receiver operating characteristic curve (AUROC) was 0.939, and the area under the precision-recall curve (AUPRC) was 0.977, demonstrating significant results. Furthermore, this detector exhibited the ability to accurately differentiate between various infarction territories in the ECG, including anterior myocardial infarction (AMI), inferior myocardial infarction (IMI), lateral myocardial infarction (LMI), and suspected left main disease. Discussion: These results suggest that integrating clinical domains into AI technology for ECG diagnosis can play a crucial role in the rapid treatment and improved prognosis of STEMI patients. This study provides an innovative approach for the diagnosis of cardiovascular diseases and contributes to enhancing the practical applicability of AI-based diagnostic tools in clinical settings. [ABSTRACT FROM AUTHOR]

Immunoglobulin G4 (IgG4)-related disease is a systemic disease characterized by dense lymphoplasmacytic infiltrates with abundant IgG4-positive plasma cells and fibroblast proliferation. The retroperitoneal involvement of IgG4-related disease usually appears as a soft-tissue mass covering the abdominal aorta or entrapping the ureters, resulting in hydronephrosis. Here, we present a case of IgG4-related disease with retroperitoneal involvement in a 75-yearold woman with an unusual manifestation. A preoperative computed tomography (CT) scan revealed an irregular infiltrative retroperitoneal mass invading the normal anatomic barriers, raising the suspicion of malignancy or inflammation. Contrast-enhanced CT revealed a homogeneous progressive enhancement of the mass.

Mineral wool is an insulation material commonly used in passive fire protection (PFP) systems on offshore installations. Insulation materials have only been considered functional materials for thermal analysis in the conventional offshore PFP system design method. Hence, the structural performance of insulation has yet to be considered in the design of PFP systems. However, the structural elements of offshore PFP systems are often designed with excessive dimensions to satisfy structural requirements under external loads such as wind, fire and explosive pressure. To verify the structural contribution of insulation material, it was considered a structural material in this study. A series of material tensile tests was undertaken with two types of mineral wool at room temperature and at elevated temperatures for fire conditions. The mechanical properties were then verified with modified methods, and a database was constructed for application in a series of nonlinear structural and thermal finite-element analyses of an offshore bulkhead-type PFP system. Numerical analyses were performed with a conventional model without insulation and with a new suggested model with insulation. These analyses showed the structural contribution of the insulation in the structural behaviour of the PFP panel. The results suggest the need to consider the structural strength of the insulation material in PFP systems during the structural design step for offshore installations.

This paper presents a 2-D analysis of synchronous reluctance motors (SynRMs) considering the end-plate effect. In an electric machine with a laminated steel core, an end-plate is often attached to the rotor core to support the structural robustness of the machine. End-plates occasionally comprise carbon-steel, which changes the magnetic behavior of the electric machine. Thus, an electric machine that utilizes the 3-D finite element analysis (FEA) should be designed to consider the comprehensive magnetic flux path. However, the application of 3-D FEA for the whole design process is computationally expensive. Therefore, we proposed a 2-D FEA-based design strategy that can consider the additional magnetic path of the end-plate for SynRMs. The proposed analysis method was developed based on the magnetic equivalent circuit analysis and $d$ - and $q$ -axis flux linkage calculation. The effectiveness of the proposed method was verified by presenting the actual design case of a SynRM and via an experimental study.

Abstract Background Hepatitis B is known to cause several forms of liver diseases including chronic hepatitis B (CHB), and hepatocellular carcinoma. Previous genome-wide association study of CHB risk has demonstrated that rs12614 of complement factor B (CFB) was significantly associated with CHB risk. In this study, fine-mapping study of previously reported GWAS single nucleotide polymorphism (SNP; CFB rs12614) was performed to validate genetic effect of rs12614 on CHB susceptibility and identify possible additional causal variants around rs12614 in a Korean population. This association study was conducted in order to identify genetic effects of CFB single nucleotide polymorphisms (SNPs) and to identify additional independent CHB susceptible causal markers within a Korean population. Methods A total of 10 CFB genetic polymorphisms were selected and genotyped in 1716 study subjects comprised of 955 CHB patients and 761 population controls. Results A non-synonymous variant, rs12614 (Arg32Trp) in exon2 of CFB, had significant associations with risk of CHB (odds ratio = 0.43, P = 5.91 × 10− 10). Additional linkage disequilibrium and conditional analysis confirmed that rs12614 had independent genetic effect on CHB susceptibility with previously identified CHB markers. The genetic risk scores (GRSs) were calculated and the CHB patients had higher GRSs than the population controls. Moreover, OR was found to increase significantly with cumulative GRS. Conclusions rs12614 showed significant genetic effect on CHB risk within the Korean population. As such rs12614 may be used as a possible causal genetic variant for CHB susceptibility.

A track-type underwater construction robot (URI-R) was developed by the Korea Institute of Ocean Science & Technology. Because URI-R uses tracks to move on the seabed, insufficient ground strength may hinder its movement. For smooth operation of URI-R on the seabed, it is important to determine the geotechnical properties of the seabed.To determine these properties, standard penetration test (SPT), cone penetration test (CPT), and sampling are used on land. However, these tests cannot be applied on the seabed due to a high cost owing to the vessel, crane, sampler, and analysis time. To overcome these problems, a free fall cone penetration tester (FFCPT) is being developed.The FFCPT is a device that acquires the geotechnical properties during impact/penetration/finish phases by free fall in water. Depth information is crucial during soil data acquisition. As the FFCPT cannot measure the penetration depth directly, it is estimated indirectly using acceleration. The estimated penetration depth was verified by results of real tests conducted on land.

The Integrated Offshore Standard Specification (IOSS) involves Korean shipyards, classification societies, research institutes, the Korean industrial society, engineering companies, and oil companies with the objective of reducing costs and risks without compromising safety in international offshore engineering procurement construction (EPC) projects using new standardized bulk components and qualification procedures. The activities of the IOSS include the analysis of the existing rules and regulations to achieve the best standardization, which is reflected in the best practices, and minimize the variables in regulations and rules. In addition, a standard inventory of shapes and dimensions, referred to as specifications, is proposed in the IOSS. In this paper, the aluminum tertiary standardization part (IOSS S102-1/2 S104: Specification for Structural Tertiary Design) is presented with the details of the procedures, background reviews, and cost-benefit analyses of the design and verification methods for standard designs in the IOSS standardization items. Based on the cost-benefit analysis, the application of standardized aluminum tertiary items to offshore projects has significant advantages in terms of maintenance and repair compared to the carbon steel tertiary items utilized in current industrial practices.

This paper investigates the effects of types and aging of asphalt binder on healing performance of asphalt mixture modified with steel wool fibers (SWF) using induction heating method. Asphalt binders PG58-22, PG64-22 and PG76-22, widely used in Korea, were applied in this study. The rolling thin film oven (RTFO) and pressure ageing vessel (PAV) tests were conducted to simulate the aging process of asphalt binder. The healing performance of mixtures was evaluated by the crack-heal process, which included semi-circular bending and induction heating tests. The cooking oil waste was used as a rejuvenator in order to refresh the aged binder and its healing performance was also examined. The results indicated that the performance grade (PG) of asphalt binder slightly affected the healing performance of mixtures due to the difference of binder viscosity. In addition, the healing level of asphalt mixture was reduced significantly by aged asphalt binder. Finally, it was found that using cooking oil waste as a rejuvenator for the aged asphalt mixture can improve its healing performance. Keywords: Asphalt mixture, Induction heating, Steel wool fibers, Healing, Aging, Cooking oil waste

A computational model of drug dissolution in the human stomach is developed to investigate the interaction between gastric flow and orally administrated drug in the form of a solid tablet. The stomach model is derived from the anatomical imaging data and the motion and dissolution of the drug in the stomach are modeled via fluid-structure interaction combined with mass transport simulations. The effects of gastric motility and the associated fluid dynamics on the dissolution characteristics are investigated. Two different pill densities are considered to study the effects of the gastric flow as well as the gravitational force on the motion of the pill. The average mass transfer coefficient and the spatial distributions of the dissolved drug concentration are analyzed in detail. The results show that the retropulsive jet and recirculating flow in the antrum generated by the antral contraction wave play an important role in the motion of the pill as well as the transport and mixing of the dissolved drug concentration. It is also found that the gastric flow can increase the dissolution mass flux, especially when there is substantial relative motion between the gastric flow and the pill.

Haman, Gunbuk, and Daejang deposits are neighboring vein-type hydrothermal Cu deposits located in the SE part of the Korean Peninsula. These three deposits are formed by magmatic-hydrothermal activity associated with a series of Cretaceous granodioritic intrusions of the Jindong Granitoids, which have created a series of veins and alterations in a hornfelsed shale formation. The copper deposits have common veining and alteration features: 1) a pervasive chlorite-epidote alteration, cut by 2) Cu-Pb-Zn-bearing quartz veins with a tourmaline-biotite alteration, and 3) the latest barren calcite veins. Chalcopyrite, pyrite, and pyrrhotite are common ore minerals in the three deposits. Whereas magnetite is a dominant mineral in the Haman and Gunbuk deposits, no magnetite is present, but sphalerite and galena are abundant in the Daejang deposit. Ore-bearing quartz veins have three types of fluid inclusions: 1) liquid-rich, 2) vapor-rich, and 3) brine inclusions. Hydrothermal temperatures obtained from the brine inclusion assemblages are about 340–600, 250–500, and 320–460°C in the Haman, Gunbuk, and Daejang deposits, respectively. The maximum temperatures (from 460 to 600°C) recorded in the fluid inclusions of the three deposits are higher than those of the Cu ore precipitating temperature of typical porphyry-like deposits (from 300 to 400°C). Raman spectroscopy of vapor inclusions showed the presence of CO2 and CH4 in the three deposits, which indicates relatively reduced hydrothermal conditions as compared with typical porphyry deposits. The Rb/Sr ratios and Cs concentrations of brine inclusions suggest that the Daejang deposit was formed by a later and more fractionated magma than the Haman and Gunbuk deposits, and the Daejang deposit has lower Fe/Mn ratios in brine inclusions than the Haman and Gunbuk deposits, which indicates contrasting redox conditions in hydrothermal fluids possibly caused by an interaction with a hosting shale formation. In brines, concentrations of base metals do not change significantly with temperature, which suggests that significant ore mineralization precipitation is unlikely below current exposure levels, especially at the Haman deposit. Ore and alteration mineral petrography and fluid inclusions suggest that the Haman deposit was formed near the top of the deep intrusion center, whereas the Gunbuk deposit was formed at a shallower intrusion periphery. The Daejang deposit was formed later at a shallow depth by relatively fractionated magma.

The clinical manifestations of diabetic kidney disease (DKD) are more heterogeneous than those previously reported, and these observations mandate the need for the recruitment of patients with biopsy-proven DKD in biomarker research. In this study, using the public gene expression omnibus (GEO) repository, we aimed to identify urinary mRNA biomarkers that can predict histological severity and disease progression in patients with DKD in whom the diagnosis and histologic grade has been confirmed by kidney biopsy. We identified 30 DKD-specific mRNA candidates based on the analysis of the GEO datasets. Among these, there were significant alterations in the urinary levels of 17 mRNAs in patients with DKD, compared with healthy controls. Four urinary mRNAs—LYZ, C3, FKBP5, and G6PC—reflected tubulointerstitial inflammation and fibrosis in kidney biopsy and could predict rapid progression to end-stage kidney disease independently of the baseline eGFR (tertile 1 vs. tertile 3; adjusted hazard ratio of 9.68 and 95% confidence interval of 2.85–32.87, p < 0.001). In conclusion, we demonstrated that urinary mRNA signatures have a potential to indicate the pathologic status and predict adverse renal outcomes in patients with DKD.

Patients who receive transcatheter aortic valve replacement are at risk for leaflet thrombosis-related complications, and can benefit from continuous, longitudinal monitoring of the prosthesis. Conventional angiography modalities are expensive, hospital-centric and either invasive or employ potentially nephrotoxic contrast agents, which preclude their routine use. Heart sounds have been long recognized to contain valuable information about individual valve function, but the skill of auscultation is in decline due to its heavy reliance on the physician’s proficiency leading to poor diagnostic repeatability. This subjectivity in diagnosis can be alleviated using machine learning techniques for anomaly detection. We present a computational and data-driven proof-of-concept analysis of a novel, auscultation-based technique for monitoring aortic valve, which is practical, non-invasive, and non-toxic. However, the underlying mechanisms leading to physiological and pathological heart sounds are not well-understood, which hinders development of such a technique. We first address this by performing direct numerical simulations of the complex interactions between turbulent blood flow in a canonical ascending aorta model and dynamic valve motion in 29 cases with healthy and stenotic valves. Using the turbulent pressure fluctuations on the aorta lumen boundary, we model the propagation of heart sounds, as elastic waves, through the patient’s thorax. The heart sound may be recorded on the epidermal surface using a stethoscope/phonocardiograph. This approach allows us to correlate instantaneous hemodynamic phenomena and valve motion with the acoustic response. From this dataset we extract “acoustic signatures” of healthy and stenotic valves based on principal components of the recorded sound. These signatures are used to train a linear discriminant classifier by maximizing correlation between recorded heart sounds and valve status. We demonstrate that this classifier is capable of accurate prospective detection of anomalous valve function and that the principal component-based signatures capture prominent audible features of heart sounds, which have been historically used by physicians for diagnosis. Further development of such technology can enable inexpensive, safe and patient-centric at-home monitoring, and can extend beyond transcatheter valves to surgical as well as native valves.

The rapid proliferation of oil/gas drilling and wind turbine installations with jack-up rig-formed structures increases structural safety requirements, due to the greater risks of operational collisions during use of these structures. Therefore, current industrial practices and regulations have tended to increase the required accidental collision design loads (impact energies) for jack-up rigs. However, the existing simplified design approach tends to be limited to the design and prediction of local members due to the difficulty in applying the increased uniform impact energy to a brace member without regard for the member’s position. It is therefore necessary to define accidental load estimation in terms of a reasonable collision scenario and its application to the structural response analysis. We found by a collision probabilistic approach that the kinetic energy ranged from a minimum of 9 MJ to a maximum 1049 MJ. Only 6% of these values are less than the 35 MJ recommendation of DNV-GL (2013). This study assumed and applied a representative design load of 196.2 MN for an impact load of 20,000 tons. Based on this design load, the detailed design of a leg structure was numerically verified via an FE analysis comprising three categories: linear analysis, buckling analysis and progressive collapse analysis. Based on the numerical results from this analysis, it was possible to predict the collapse mode and position of each member in relation to the collision load. This study provided a collision strength assessment between attendant vessels and a jack-up rig based on probabilistic collision scenarios and nonlinear structural analysis. The numerical results of this study also afforded reasonable evaluation criteria and specific evaluation procedures.

Ga-doped ZnO (GZO)-graded layer, facilitating electron extraction from electron transport layer, was integrated on the surface of transparent indium tin oxide (ITO) cathode by using graded sputtering technique to improve the performance of planar n-i-p perovskite solar cells (PSCs). The thickness of graded GZO layer was controlled to optimize GZO–indium tin oxide (ITO) combined electrode for planar n-i-p PSCs. At optimized graded thickness of 15 nm, the GZO–ITO combined electrode showed an optical transmittance of 95%, a resistivity of 2.3 × 10−4 Ohm cm, a sheet resistance of 15.6 Ohm/square, and work function of 4.23 eV, which is well matched with the 4.0-eV lowest unoccupied molecular orbital of [6,6]-phenyl-C61-butyric acid methyl ester. Owing to enhanced extraction of electron by the graded GZO, the n-i-p PSC with GZO–ITO combined electrode showed higher power conversion efficiency (PCE) of 9.67% than the PCE (5.25%) of PSC with only ITO electrode without GZO-graded layer. In addition, the GZO integrated-ITO electrode acts as transparent electrode and electron extraction layer simultaneously due to graded mixing of the GZO at the surface region of ITO electrode.

Transcatheter arterial chemoembolization (TACE) improves the survival rate in patients with hepatocellular carcinoma (HCC). Despite the low probability, iatrogenic hepatic arterial dissections during interventional procedure are rarely created by the technical difficulties. Direct trauma from the guidewire, the tip of the catheter, or the jet of contrast injection can contribute to iatrogenic hepatic arterial dissections. We report one case of a female who had HCC necrosis caused by iatrogenic hepatic arterial dissection during TACE. Ischemia resulting from iatrogenic hepatic arterial dissection during TACE was smilar to the result of transarterial embolization for HCC on our case. To our knowledge, none of the similar cases was reported in previously published literatures.

Welding often results in welding distortion during the assembly process. The welding distortion of thin-plate structures such as the living quarters of ships and offshore installations is a more significant problem than in the case of thick-plate structures. Pre-stressing/heating and fairing, which are additional works to mitigate and control welding distortion, are inevitable, and the construction planning is accordingly delayed. In order to prevent welding distortion and minimize the additional work during the assembly process, increasing the plate thickness and/or the number of stiffeners may be a simple solution, but it may give rise to problems related to cost and weight. In this study, the welding distortion control effect of the type of stiffeners on the door openings of various living quarter structures was investigated using an experimental method and a finite element method. The results showed the feasibility of mitigating and controlling the welding distortion, and the optimum selection of the type of stiffeners was confirmed.

Diamond is a highly attractive ultrawide bandgap semiconductor for next-generation high-power switching devices and RF devices for its superior physical and electrical properties. However, the lack of effective n-type dopants in diamond has limited the material to only unipolar p-type device applications. Heterostructure bipolar devices that use better n-type semiconductors together with p-type diamond is an approach to get high performance devices. In this work, p–n–p AlGaAs/GaAs/diamond heterojunction bipolar transistors (HBTs) are proposed and fabricated using a grafting technique. The double-heterojunction is formed by transferring an AlGaAs(p-type)/GaAs(n-type) membrane onto single-crystalline p-type doped diamond with an electron affinity of 0.32 eV. The epitaxial AlGaAs/GaAs emitter-base p–n junction shows an ideality factor of 1.09 with an Ion/Ioff of 1.53 × 107 at ± 1.5 V. The grafted GaAs/diamond n–p junction shows an ideality factor of 3.67 with an Ion/Ioff of 3.74 × 1010 at ± 5.2 V. Due to the valence-band energy barrier of 0.3 eV between the GaAs base and the diamond collector, the measured current gain for the HBT is slightly below unity. Simulations show that by reducing the electron affinity value of the p-type diamond, the base-collector energy barrier height can be correspondingly reduced, and high current gain can be expected.

Abstract A charge transport layer based on transition metal‐oxides prepared by an anhydrous sol–gel method normally requires high‐temperature annealing to achieve the desired quality. Although annealing is not a difficult process in the laboratory, it is definitely not a simple process in mass production, such as roll‐to‐roll, because of the inevitable long cooling step that follows. Therefore, the development of an annealing‐free solution‐processable metal‐oxide is essential for the large‐scale commercialization. In this work, a room‐temperature processable annealing‐free “aqueous” MoOx solution is developed and applied in non‐fullerene PBDB‐T‐2F:Y6 solar cells. By adjusting the concentration of water in the sol–gel route, an annealing‐free MoOx with excellent electrical properties is successfully developed. The PBDB‐T‐2F:Y6 solar cell with the general MoOx prepared by the anhydrous sol–gel method shows a low efficiency of 7.7% without annealing. If this anhydrous MoOx is annealed at 200 °C, the efficiency is recovered to 17.1%, which is a normal value typically observed in conventional structure PBDB‐T‐2F:Y6 solar cells. However, without any annealing process, the solar cell with aqueous MoOx exhibits comparable performance of 17.0%. In addition, the solar cell with annealing‐free aqueous MoOx exhibits better performance and stability without high‐temperature annealing compared to the solar cells with PEDOT:PSS.

Due to their ability to provide efficient mixing at small scales, confined impinging jet mixers (CIJMs) are employed widely in nanoparticle assembly processes such as flash nanoprecipitation and flash nanocomplexation, which require rapid mixing. In this mixing device, two jets from opposite directions impinge directly on each other forming a thin shear layer that breaks down rapidly into small flow structures. This enables effective mixing of the species transported by each jet by drastically reducing the diffusion distance. In the present study, the mixing performance of a commonly used cylindrical CIJM is examined by direct numerical simulations. Analysis of the simulation results indicates that the interaction of the shear layer with the inner walls of the CIJM is critical in inducing a range of instabilities in the impinging jet flow. By examining flow structures, statistical quantities, and metrics, we have characterized and quantified the mixing quality of a binary mixture in the CIJM. Product uniformity in processes such as precipitation and complexation is expected to depend on the residence time of the constituents, and this quantity is also calculated and compared for the cases with different jet Reynolds numbers. The jet Reynolds numbers of Re = 200, 600, and 1000 are considered, and the simulation results show that the CIJM achieves very good mixing for the Re = 600 and Re = 1000 cases. It is also found that the Re = 600 case performs slightly better than the other cases in terms of uniformity of the residence time. These quantitative analyses offer useful insights into the mechanism of nanoparticle size control and uniformity afforded by the unique flow physics and mixing characteristics in the CIJMs.