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The musculoskeletal system, which is vital for movement, support, and protection, can be impaired by disorders such as osteoporosis, osteoarthritis, and muscular dystrophy. This review focuses on the advances in tissue engineering and regenerative medicine, specifically aimed at alleviating these disorders. It explores the roles of cell therapy, particularly Mesenchymal Stem Cells (MSCs) and Adipose-Derived Stem Cells (ADSCs), biomaterials, and biomolecules/external stimulations in fostering bone and muscle regeneration. The current research underscores the potential of MSCs and ADSCs despite the persistent challenges of cell scarcity, inconsistent outcomes, and safety concerns. Moreover, integrating exogenous materials such as scaffolds and external stimuli like electrical stimulation and growth factors shows promise in enhancing musculoskeletal regeneration. This review emphasizes the need for comprehensive studies and adopting innovative techniques together to refine and advance these multi-therapeutic strategies, ultimately benefiting patients with musculoskeletal disorders.

Abstract Background Recent advances in Vision Transformer (ViT)-based deep learning have significantly improved the accuracy of lung disease prediction from chest X-ray images. However, limited research exists on comparing the effectiveness of different optimizers for lung disease prediction within ViT models. This study aims to systematically evaluate and compare the performance of various optimization methods for ViT-based models in predicting lung diseases from chest X-ray images. Methods This study utilized a chest X-ray image dataset comprising 19,003 images containing both normal cases and six lung diseases: COVID-19, Viral Pneumonia, Bacterial Pneumonia, Middle East Respiratory Syndrome (MERS), Severe Acute Respiratory Syndrome (SARS), and Tuberculosis. Each ViT model (ViT, FastViT, and CrossViT) was individually trained with each optimization method (Adam, AdamW, NAdam, RAdam, SGDW, and Momentum) to assess their performance in lung disease prediction. Results When tested with ViT on the dataset with balanced-sample sized classes, RAdam demonstrated superior accuracy compared to other optimizers, achieving 95.87%. In the dataset with imbalanced sample size, FastViT with NAdam achieved the best performance with an accuracy of 97.63%. Conclusions We provide comprehensive optimization strategies for developing ViT-based model architectures, which can enhance the performance of these models for lung disease prediction from chest X-ray images.

Latilactobacillus curvatus CACC879 originated from swine feces in Korea, and its probiotic properties have been analyzed. The complete genome of strain CACC879 contained one chromosome 1,398,247 bp in length and three circular plasmids, namely, pCACC879-1 (591,981 bp), pCACC879-2 (14,542 base pairs [bp]), and pCACC879-3 (45,393 bp). The complete genome encodes a total of 2,077 genes, including 25 rRNA genes and 90 tRNA genes. In addition, probiotic stability- genes acid/bile related to salts tolerance, the biosynthesis of cobalamin (vitamin B12), riboflavin (vitamin B2), and CRISPR/Cas9 were found in the whole genomes. Remarkably, L. curvatus CACC879 contained the antioxidant-related (peroxiredoxin) and bacteriocin-related genes (lysM and blpA). Overall, these results demonstrate that L. curvatus CACC879 is a functional probiotic candidate for animal industry applications.

Abstract Silybum marianum (L.) Gaertn., commonly known as milk thistle, is a medicinal plant belonging to the Asteraceae family. This plant has been recognized for its medicinal properties for over 2,000 years. However, the genome of this plant remains largely undiscovered, having no reference genome at a chromosomal level. Here, we assembled the chromosome-level genome of S. marianum, allowing for the annotation of 53,552 genes and the identification of transposable elements comprising 58% of the genome. The genome assembly from this study showed 99.1% completeness as determined by BUSCO assessment, while the previous assembly (ASM154182v1) showed 36.7%. Functional annotation of the predicted genes showed 50,329 genes (94% of total genes) with known protein functions in public databases. Comparative genome analysis among Asteraceae plants revealed a striking conservation of collinearity between S. marianum and C. cardunculus. The genomic information generated from this study will be a valuable resource for milk thistle breeding and for use by the larger research community.

Purpose This study aimed to examine the association between social support, postpartum depression (PPD), anxiety and perceived stress among women within 12 months of childbirth in South Korea. Methods A cross-sectional, web-based survey was conducted from 21 to 30 September 2022 and included women within 12 months of childbirth in Chungnam Province, South Korea. A total of 1486 participants were included. Multiple linear regression models were used to evaluate the association between social support and mental health. Results In total, 40.0% of the participants had mild to moderate PPD; 12.0%, anxiety symptoms; and 8.2%, perceived severe stress. Social support (from family and significant others) is significantly associated with PPD, anxiety and perceived severe stress. Current maternal health problems, unplanned pregnancy and low household income were risk factors for PPD, anxiety and perceived stress. The increase in the time elapsed after childbirth showed a positive association with PPD and perceived severe stress. Conclusions Our findings provide insights to identify at-risk mothers and emphasize the importance of social support in families, early screening and continuous monitoring for postpartum women to prevent PPD, anxiety and stress.

Ion migration is a plausible origin of material instability and photocurrent hysteresis in perovskite solar cells. Here, authors characterize photo-induced ion migration in perovskites by in situ laser illumination inside scanning electron microscope and observe long-range migration of halide ions.

Lactobacillus amylovorus CACC736 was originated from swine feces in Korea. The complete genome sequences of the strain contained one circular chromosome (2,057,809 base pair [bp]) with 38.2% guanine-cytosine (GC) content and two circular plasmids, namely, pCACC736-1 and pCACC736-2. The predicted protein-coding genes, which are encoding the clustered regularly interspaced short palindromic repeats (CRISPR)-associated proteins, biosynthesis of bacteriocin (helveticin J), and the related proteins of the bile, acid tolerance. Notably, the genes related to vitamin B-group biosynthesis (riboflavin and cobalamin) were also found in L. amylovorus CACC736. Collectively, the complete genome sequence of the L. amylovorus CACC736 will aid in the development of functional probiotics in the animal industry.

The bulk-heterojunction (BHJ) system that uses a π-conjugated polymer as an electron donor, and a fullerene derivative as an electron acceptor, is widely used in organic solar cells (OSCs) to facilitate efficient charge separation and extraction. However, the conventional BHJ system still suffers from unwanted phase segregation caused by the existence of significant differences in surface energy between the two BHJ components and the charge extraction layer during film formation. In the present work, we demonstrate a sophisticated control of fast film-growth kinetics that can be used to achieve a uniform distribution of donor and acceptor materials in the BHJ layer of OSCs without undesirable phase separation. Our approach involves depositing the BHJ solution onto a spinning substrate, thus inducing rapid evaporation of the solvent during BHJ film formation. The fast-growth process prevents the fullerene derivative from migrating toward the charge extraction layer, thereby enabling a homogeneous distribution of the fullerene derivative within the BHJ film. The OSCs based on the fast-growth BHJ thin film are found to exhibit substantial increases in JSC, fill factor, and a PCE up to 11.27 mA/cm2, 66%, and 4.68%, respectively; this last value represents a remarkable 17% increase in PCE compared to that of conventional OSCs.

Introduction: The prevalence of Type 2 diabetes mellitus (T2DM) is rising worldwide. Patients frequently struggle with controlling their diabetes and need the assistance of caregivers for effective self-management because managing diabetes requires a variety of strategies, including diet, glucose monitoring, and exercise. This study aimed to examine the effect of caregiver involvement in T2DM education within a community on patients’ diabetes care outcomes. Methods: Based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, a systematic review of all published studies from the earliest record to May 2022 that reported adult caregivers of T2DM patients who participated in educational interventions concerning diabetes management and that reported one or more outcomes of the interventions were conducted. Four databases were used, including PubMed, Cochrane Library, EMBASE, and CINAHL. The meta-analysis focused on glycated hemoglobin (HbA1c) levels among randomized controlled trials (RCTs), with additional attention to lipid levels. Review Manager 5.4 was used to perform this meta-analysis. Results: A total of 17 out of 683 studies were synthesized. Involvement of caregivers in T2DM education is shown to reduce body mass index and HbA1c. This involvement also improves patients’ knowledge, physical activity, and self-efficacy, but the effect on medication adherence varies. A meta-analysis of six RCT studies shows that caregiver involvement in T2DM education reduced pooled HbA1c levels by 0.83 (95% Confidence interval: −1.27–−0.38) compared to involvement (p = 0.0003). Meta-analysis of three types of lipids (low-density lipoprotein, total cholesterol, and high-density lipoprotein) showed no strong evidence that caregiver participation in diabetes education improved lipid levels. Conclusions: Caregivers play key roles in diabetes management and can contribute to improving patient HbA1c levels. Future research should focus on enhancing caregiver participation in T2DM education.

The recovery of contextual meanings on a machine code is required by a wide range of binary analysis applications, such as bug discovery, malware analysis, and code clone detection. To accomplish this, advancements on binary code analysis borrow the techniques from natural language processing to automatically infer the underlying semantics of a binary, rather than replying on manual analysis. One of crucial pipelines in this process is instruction normalization, which helps to reduce the number of tokens and to avoid an out-of-vocabulary (OOV) problem. However, existing approaches often substitutes the operand(s) of an instruction with a common token (e. g., callee target $\rightarrow $ FOO), inevitably resulting in the loss of important information. In this paper, we introduce well-balanced instruction normalization (WIN), a novel approach that retains rich code information while minimizing the downsides of code normalization. With large swaths of binary code, our finding shows that the instruction distribution follows Zipf’s Law like a natural language, a function conveys contextually meaningful information, and the same instruction at different positions may require diverse code representations. To show the effectiveness of WIN, we present DEEP SEMANTIC that harnesses the BERT architecture with two training phases: pre-training for generic assembly code representation, and fine-tuning for building a model tailored to a specialized task. We define a downstream task of binary code similarity detection, which requires underlying code semantics. Our experimental results show that our binary similarity model with WIN outperforms two state-of-the-art binary similarity tools, DeepBinDiff and SAFE, with an average improvement of 49.8% and 15.8%, respectively.

Abstract Background Early intervention is essential for improving the prognosis in patients with first-episode schizophrenia (FES). The Mental Health Act limits involuntary hospitalization in South Korea to cases where an individual exhibits both a mental disorder and a potential for harming themselves or others, which could result in a delay in the required treatment in FES. We investigated the effect of delay in the first psychiatric hospitalization on clinical outcomes in FES. Methods The South Korean Health Insurance Review Agency database (2012–2019) was used. We identified 15,994 patients with FES who had a record of at least one psychiatric hospitalization within 1 year from their diagnosis. A multivariate linear regression model and a generalized linear model with a gamma distribution and log link were used to examine associations between the duration from the diagnosis to the first psychiatric admission and clinical outcomes as well as direct medical costs after 2 and 5 years. Results Within both the 2-year and the 5-year period, longer durations from the diagnosis to the first psychiatric admission were associated with an increase in the number of psychiatric hospitalizations (2-y: B = 0.003, p = 0.003, 5-y: B = 0.007, p = 0.001) and an increase in direct medical costs (total: 2-y: B = 0.005, p

Background: Surveillance of healthcare-associated infection (HAI) is the basis of infection prevention programs. However, manual review of medical records is a labor-intensive and time-consuming process. We evaluated the diagnostic performance of automated surveillance of HAI using electronic screening algorithms. Methods: Between April and June 2022, we conducted surveillance of HAI manually and automatically using electronic screening algorithm on 75 units (general medical and surgical wards and ICUs) in a 2,700-bed, tertiary-care hospital in South Korea. Algorithms for surveillance of HAI were developed accordance with NHSN surveillance definitions (Fig. 1). Catheter-associated urinary tract infections (CAUTIs) were automatically detected when eligible pathogen and fever (>38°C) were matched within infection window period. Other specific types of infection were automatically classified based on laboratory results that met NHSN criteria. After the algorithm showed possible cases that met laboratory-confirmed bloodstream infection (LCBI) criteria, we excluded secondary BSIs using the automatic surveillance algorithm. We analyzed sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for the automated surveillance system compared to manual surveillance. Results: An algorithm for detecting CAUTI showed 98.7% sensitivity (78 of 79), 100.0% specificity (2,443 of 2,443), 100.0% PPV (78 of 78), and 100.0% NPV (2,443 of 2,444). For CLABSI, the algorithm had 97.3% sensitivity (214 of 220), 98.3% specificity (5,759 of 5,861), 67.7% PPV (214 of 316), and 99.9% NPV (5,759 of 5,765). In total, 102 cases of possible CLABSI were identified by the algorithm, and 76 (74.5%) were eventually diagnosed as secondary BSIs. Also, by chart review, 20 BSIs (19.6%) were present on arrival in ER (ER-POA). In 4 cases (3.9%), an original pathogen reoccurred in a repeated infection timeframe (RIT), and 2 cases (2%) were mucosal barrier injury-LCBI (MBI-LCBI). When we additionally performed manual surveillance for intra-abdominal infection secondary BSI, ER-POA, and assigning pathogen to original BSI in RIT, PPV increased to 87.7% (214 of 244). Conclusions: Algorithm for automated surveillance of CAUTI had good performance; however, automated surveillance of CLABSI was suboptimal. More elaborate screening algorithm for diagnosis CLABSI is needed, and further studies are needed to determine whether an automated surveillance system can reduce workload for surveillance of HAI.

Abstract Background Construction workers working in physically and mentally challenging environments experience high levels of occupational fatigue, which is the primary cause of industrial accidents and illnesses. Therefore, it is very important to measure fatigue in real time to manage the safety and health of construction workers. This study presents a novel approach for simultaneously measuring the subjective and objective fatigue of construction workers using ecological momentary assessment (EMA) and smartwatches. Due to the complexity and diversity of construction site environments, it is necessary to examine whether data collection using smartwatches is suitable in actual construction sites. This study aims to examine the feasibility of the integrated fatigue measurement method. Methods This study comprised two phases: (1) development of an integrated fatigue measurement system for construction workers, and (2) a validation study to evaluate the method’s feasibility based on sensor data acquisition, EMA compliance, and feedback from construction workers in the field (N = 80). Three days of biometric data were collected through sensors embedded in the smartwatches for objective fatigue measurement, including heart rate, accelerometer, and gyroscope data. Two types of self-reported data regarding each worker’s fatigue were collected through a researcher-developed EMA application. The acceptability and usability of this system were examined based on the researchers’ observations and unstructured interviews. Results Based on the standardized self-report questionnaire scores, participants were classified into high (n = 35, 43.75%) and low (n = 45, 56.25%) fatigue groups for comparison. The quantitative outcomes did not show a statistically significant difference between the two fatigue groups. Both groups experienced positive emotions and were able to recognize their health condition at the time of self-reporting, but stated that responding to this measurement system could be burdensome. Conclusions This feasibility study provides a unique understanding of the applications of EMA and smartwatches for safety management in the construction workforce. The developed measurement system shows potential for monitoring fatigue based on the real-time collection of relevant data. It is expected that by expanding this integrated system through further research and onsite application, the health and safety of construction workers can be improved.

During weaning, piglets experience various stressor events that disrupt their gut microbiota and immune balance, decrease growth parameters, and increase mortality rates. In this study, we assessed the efficacy of Pediococcus pentosaceus CACC616 as a probiotic supplement. We characterized this strain and evaluated its effect on improving growth performance, modulating gut microbiota composition, and reducing noxious odor components in weaned piglets compared to a non-supplementary diet (control). During the 26-day period, 40 crossbred weaned piglets were randomly assigned to pens with 20 animals each in two groups: control and treatment groups with CACC616. On day 26, the treatment group exhibited a lower feed conversion ratio (FCR) and a significant alteration in gut microbial composition, correlating with improved growth parameters and gut health (p < 0.05). The treatment group also exhibited significantly reduced digestibility- and intestinal-environment-related noxious odor components (p < 0.05). The CACC616 strain effectively reduced pathogenic genera numbers, including Campylobacter, Mogibacterium, Escherichia–Shigella, and Desulfovibrio spp., with the treatment group exhibiting lower fecal calprotectin levels than the control group (p < 0.05). Overall, this study revealed that the functional probiotic CACC616 contributes to enhanced FCR and effectively modulates weaned piglets’ inflammation and intestinal microbiota.

Constructing optical image time series for cropland monitoring requires a cloud removal method that accurately restores cloud regions and eliminates discontinuity around cloud boundaries. This paper describes a two-stage hybrid machine learning-based cloud removal method that combines Gaussian process regression (GPR)-based predictions with image blending for seamless optical image reconstruction. GPR is employed in the first stage to generate initial prediction results by quantifying temporal relationships between multi-temporal images. GPR predictive uncertainty is particularly combined with prediction values to utilize uncertainty-weighted predictions as the input for the next stage. In the second stage, Poisson blending is applied to eliminate discontinuity in GPR-based predictions. The benefits of this method are illustrated through cloud removal experiments using Sentinel-2 images with synthetic cloud masks over two cropland sites. The proposed method was able to maintain the structural features and quality of the underlying reflectance in cloud regions and outperformed two existing hybrid cloud removal methods for all spectral bands. Furthermore, it demonstrated the best performance in predicting several vegetation indices in cloud regions. These experimental results indicate the benefits of the proposed cloud removal method for reconstructing cloud-contaminated optical imagery.

Container-based deep learning has emerged as a cutting-edge trend in modern AI applications. Containers have several merits compared to traditional virtual machine platforms in terms of resource utilization and mobility. Nevertheless, containers still pose challenges in executing deep learning workloads efficiently with respect to resource usage and performance. In particular, multi-tenant environments are vulnerable to the performance of container-based deep learning due to conflicts of resource usage. To quantify the container effect in deep learning, this article captures various event traces related to deep learning performance using containers and compares them with those captured on a host machine without containers. By analyzing the system calls invoked and various performance metrics, we quantify the effect of containers in terms of resource consumption and interference. We also explore the effects of executing multiple containers to highlight the issues that arise in multi-tenant environments. Our observations show that containerization can be a viable solution for deep learning workloads, but it is important to manage resources carefully to avoid excessive contention and interference, especially for storage write-back operations. We also suggest a preliminary solution to avoid the performance bottlenecks of page-faults and storage write-backs by introducing an intermediate non-volatile flushing layer, which improves I/O latency by 82% on average.

Multi-task learning (MTL) improves learning efficiency compared to the single-task counterpart in that it performs multiple tasks at the same time. Due to the nature, it can achieve generalized performance as well as alleviate overfitting. However, it does not efficiently perform resource-aware inference from a single trained architecture. To address the issue, we aim to build a learning framework that minimizes the cost to infer tasks under different memory budgets. To this end, we propose a multi-path network with a self-auxiliary learning strategy. The multi-path structure contains task-specific paths in a backbone network, where a lower-level path predicts earlier with a smaller number of parameters. To alleviate the performance degradation from earlier predictions, a self-auxiliary learning strategy is presented. The self-auxiliary tasks convey task-specific knowledge to the main tasks to compensate for the performance leak. We evaluate the proposed method on an extensive set of multi-task learning scenarios, including multiple tasks learning, hierarchical learning, and curriculum learning. The proposed method outperforms existing multi-task learning competitors for most scenarios about by a margin of 1% ~ 2% accuracy on average while consuming 30% ~ 60% smaller computational cost.

Background: Since January 2022, the Omicron variant has become the dominant strain in South Korea, and COVID-19 cases among hospitalized patients and their guardians or caregivers have increased. We evaluated the usefulness of universal periodic screening for SARS-CoV-2 in patients and resident caregivers in a South Korean tertiary care hospital. Methods: We evaluated the reason for testing in COVID-19 confirmed patients and resident caregivers during their hospitalization from March 3 to 31, 2022. The rate of positive PCR universal testing in hospital (or residency) (HD) on days 3 and 7 in asymptomatic patients and caregivers were evaluated. The test for SARS-CoV-2 was done by RT-PCR. Results: During the study period, 677 patients were diagnosed with COVID-19. The reasons for testing were the symptoms (226 (33%)), pre-admission test (183 (27%)), exposure to COVID-19 (124 (18%)), universal testing on HD 3 (94 (14%)), and that on HD 7 (34 (5%)). Caregivers (n = 340) were tested during their residency due to exposure to COVID-19 cases, 103 (30%); universal testing on HD 3, 90 (26%); symptom development, 46 (14%); pre-stay, 39 (11%); and universal testing on HD 7, 29 (9%). The positive test rates of inpatients and caregivers on HD 3 and HD 7 were as follows: 1.4% (93/6553) and 2.1% (55/2646) in inpatients, and 1.3% (79/5989) and 1.7% (35/2106) in caregivers, respectively. Conclusions: Universal testing, regardless of symptom or epidemiologic link, is useful for detecting pre-symptomatic and asymptomatic COVID-19 cases among hospitalized patients and caregivers and preventing a nosocomial outbreak during the Omicron era.

Abstract A high‐performance energy storage device plays an important role in controlling carbon emissions. The emerging additive manufacturing techniques bring a great revolution of electrode fabrication process and promote the performance of energy storage devices through the advanced electrode architecture design. In this paper, recent studies on the three‐dimensional (3D)‐printed electrode with advanced architecture have been mainly reviewed, including interdigitated structure, through‐thickness aligned structure, hierarchical porous structure and fiber and fibric structure of electrodes, and expectations for the development of novel advanced electrode architecture generated and optimized by computational simulation and machine learning. The strategy of advanced electrode architecture design and fabrication enabled by the 3D printing technique represents a promising direction toward future energy storage devices with high electrochemical and mechanical performance.

Kevin Ziyang Chng et al. develop a microfluidic platform using a fluorescence quenching approach to assess transient changes in oxygen release rate of single red blood cells. They observe that biologically older red blood cells have a faster O2 release rate than younger cells and that storage of blood enhances this release rate.

Abstract Many eusocial insects, including ants, show complex colony structures, distributions, and reproductive strategies. In the ant Vollenhovia emeryi Wheeler (Hymenoptera: Myrmicinae), queens and males are produced clonally, while sterile workers arise sexually, unlike other ant species and Hymenopteran insects in general. Furthermore, there is a wing length polymorphism in the queen caste. Despite its evolutionary remarkable traits, little is known about the population structure of this ant species, which may provide insight into its unique reproductive mode and polymorphic traits. We performed in‐depth analyses of ant populations from Korea, Japan, and North America using three mitochondrial genes (COI, COII, and Cytb). The long‐winged (L) morph is predominant in Korean populations, and the short‐winged (S) morph is very rare. Interestingly, all L morphs were infected with Wolbachia, while all Korean S morphs lacked Wolbachia, demonstrating a association between a symbiont and a phenotypic trait. A phylogenetic analysis revealed that the S morph is derived from the L morph. We propose that the S morph is associated with potential resistance to Wolbachia infection and that Wolbachia infection does not influence clonal reproduction (as is the case in other ant species).

An external stimulus, event, or environment that stresses an individual is called a stressor. Many mental stress detection studies have been focused on the discrimination of the mental state with and without the experimental stressor. However, the mental state in the absence of experimental stressors may not represent accurately the nonstress (baseline) state because people inherently experience considerable stress in their daily lives. Therefore, we assumed that stress detection could be improved more accurately by considering the daily stress. In this study, functional near-infrared spectroscopy (fNIRS) was measured in 41 healthy participants to quantify their prefrontal cortical oxygenation during performing a cognitive task as an experimental stressor, considering individual daily stress level based on the self-report. We then extracted six signal features, including the slope, mean, standard deviation, peak, skewness, and kurtosis of the oxygenated hemoglobin concentration. Using various feature combinations and time windows, we successfully managed to classify daily stress (high/low) and the mental state (task/rest) with support vector machine classifiers. Specifically, individual daily stress level can be easily discriminated with signal features from fNIRS. Moreover, mental state classification performance improved significantly when the daily stress level was handled separately. The findings of this study show the feasibility of the fNIRS-based daily stress classification and can be used in the future to design a robust mental stress management system for the assessment of daily stress in individuals.

Continuous crop monitoring often requires a time-series set of satellite images. Since satellite images have a trade-off in spatial and temporal resolution, spatiotemporal image fusion (STIF) has been applied to construct time-series images at a consistent scale. With the increased availability of high spatial resolution images, it is necessary to develop a new STIF model that can effectively reflect the properties of high spatial resolution satellite images for small-scale crop field monitoring. This paper proposes an advanced STIF model using a single image pair, called high spatial resolution image fusion using object-based weighting (HIFOW), for blending high spatial resolution satellite images. The four-step weighted-function approach of HIFOW includes (1) temporal relationship modeling, (2) object extraction using image segmentation, (3) weighting based on object information, and (4) residual correction to quantify temporal variability between the base and prediction dates and also represent both spectral patterns at the prediction date and spatial details of fine-scale images. The specific procedures tailored for blending fine-scale images are the extraction of object-based change and structural information and their application to weight determination. The potential of HIFOW was evaluated from the experiments on agricultural sites using Sentinel-2 and RapidEye images. HIFOW was compared with three existing STIF models, including the spatial and temporal adaptive reflectance fusion model (STARFM), flexible spatiotemporal data fusion (FSDAF), and Fit-FC. Experimental results revealed that the HIFOW prediction could restore detailed spatial patterns within crop fields and clear crop boundaries with less spectral distortion, which was not represented in the prediction results of the other three models. Consequently, HIFOW achieved the best prediction performance in terms of accuracy and structural similarity for all the spectral bands. Other than the reflectance prediction, HIFOW also yielded superior prediction performance for blending normalized difference vegetation index images. These findings indicate that HIFOW could be a potential solution for constructing high spatial resolution time-series images in small-scale croplands.

This study investigated the usage of conversational artificial intelligence (CAI) to support learners in foreign language classrooms. It employed Google Assistant and focused on the interactions between the teacher, learners, and CAI, as well as the teacher's collaboration with CAI. Using social network and content analyses of two 50-minute language classes and group interviews, this study revealed that the teacher and CAI played a significant role during classroom interactions. The teacher employed various talk moves to facilitate interactions between the students and CAI. There were several instances of collaboration between the teacher and CAI during classroom facilitation. This study highlights the implications of the collaboration between human teachers and CAI in classrooms for teaching foreign languages and suggests avenues for future research.

Non-typhoidal Salmonella (NTS) is one of the primary causes of foodborne gastroenteritis; occasionally, it causes invasive infection in humans. Because of its broad host range, covering diverse livestock species, foods of animal origin pose a critical threat of NTS contamination. However, there is currently no licensed vaccine against NTS infection. FruR, also known as Cra (catabolite repressor/activator), was initially identified as the transcriptional repressor of the fructose (fru) operon, and then found to activate or repress the transcription of many different genes associated with carbon and energy metabolism. In view of its role as a global regulator, we constructed a live attenuated vaccine candidate, ΔfruR, and evaluated its prophylactic effect against NTS infection in mice. A Salmonella Typhimurium mutant strain lacking fruR was defective in survival inside macrophages and exhibited attenuated virulence in infected mice. Immunization with the ΔfruR mutant stimulated the production of antibodies, including the IgG, IgM, and IgG subclasses, and afforded a protection of 100% to mice against the challenge of lethal infection with a virulent Salmonella strain. The prophylactic effect obtained after ΔfruR immunization was also validated by the absence of signs of hepatosplenomegaly, as these mice had comparable liver and spleen weights in comparison with healthy mice. These results suggest that the ΔfruR mutant strain can be further exploited as a promising vaccine candidate against Salmonella lethal infection.

Non-typhoidal Salmonella (NTS) causes gastrointestinal infection, which is commonly self-limiting in healthy humans but may lead to invasive infection at extraintestinal sites, leading to bacteremia and focal systemic infections in the immunocompromised. However, a prophylactic vaccine against invasive NTS has not yet been developed. In this work, we explored the potential of a ΔyjeK mutant strain as a live attenuated vaccine against invasive NTS infection. YjeK in combination with YjeA is required for the post-translational modification of elongation factor P (EF-P), which is critical for bacterial protein synthesis. Therefore, malfunction of YjeK and YjeA-mediated EF-P activation might extensively influence protein expression during Salmonella infection. Salmonella lacking YjeK showed substantial alterations in bacterial motility, antibiotics resistance, and virulence. Interestingly, deletion of the yjeK gene increased the expression levels of Salmonella pathogenicity island (SPI)-1 genes but decreased the transcription levels of SPI-2 genes, thereby influencing bacterial invasion and survival abilities in contact with host cells. In a mouse model, the ΔyjeK mutant strain alleviated the levels of splenomegaly and bacterial burdens in the spleen and liver in comparison with the wild-type strain. However, mice immunized with the ΔyjeK mutant displayed increased Th1- and Th2-mediated immune responses at 28 days post-infection, promoting cytokines and antibodies production. Notably, the Th2-associated antibody response was highly induced by administration of the ΔyjeK mutant strain. Consequently, vaccination with the ΔyjeK mutant strain protected 100% of the mice against challenge with lethal invasive Salmonella and significantly relieved bacterial burdens in the organs. Collectively, these results suggest that the ΔyjeK mutant strain can be exploited as a promising live attenuated NTS vaccine.

Human–animal interaction (HAI) has been observed to effectively reduce stress and induce positive emotions owing to the process of directly petting and interacting with animals. Interaction with virtual animals has recently emerged as an alternative due to the limitations in general physical interactions, both due to the COVID-19 pandemic and, more generally, due to the difficulties involved in providing adequate care for animals. This study proposes mixed reality (MR)-based human–animal interaction content along with presenting the experimental verification of its effect on the reduction of mental stress. A mental arithmetic task was employed to induce acute mental stress, which was followed by either MR content, in which a participant interacted with virtual animals via gestures and voice commands, or a slide show of animal images. During the experiment, an electrocardiogram (ECG) was continuously recorded with a patch-type, wireless ECG sensor on the chest of the subject, and their psychological state was evaluated with the help of questionnaires after each task. The findings of the study demonstrate that the MR-based interaction with virtual animals significantly reduces mental stress and induces positive emotions. We expect that this study could provide a basis for the widespread use of MR-based content in the field of mental health.

Cancer: secreted proteins associated with fat-induced tumor growth By exposing liver cancer cells to oleate, an unsaturated fatty acid, researchers have discovered a group of secreted proteins that may help explain why fatty acids increase proliferative capacity in tumors. Soyeon Park from Pohang University of Science and Technology in South Korea and coworkers treated liver cancer cells with oleate and then measured all the proteins released from the cells. Comparison with untreated cells revealed 145 proteins secreted at elevated levels—most of which were involved in metabolism, stress responses and other proliferation-related processes—and another 192 proteins secreted at reduced levels. The researchers ran additional biochemical analyses on six secreted proteins to validate the changes following exposure to oleate. The authors suggest that these validated proteins could now serve as biomarkers of tumor aggressiveness or as future drug targets.

In this study, we have sequenced and annotated the complete mitochondrial genome of Ricania shantungensis (Hemiptera: Ricaniidae) for the first time. The circular mitogenome of R. shantungensis was 15,789 bp, including 13 protein-coding genes, two ribosomal RNA genes, 22 transfer RNAs, and a single control region of 1,363 bp. Its AT ratio was 74.6%. According to the phylogenetic tree, R. shantungensis was clustered with the genus Ricania.

Interactions between membrane proteins are poorly understood despite their importance in cell signaling and drug development. Here, we present a co-immunoimmobilization assay (Co-II) enabling the direct observation of membrane protein interactions in single living cells that overcomes the limitations of currently prevalent proximity-based indirect methods. Using Co-II, we investigated the transient homodimerizations of epidermal growth factor receptor (EGFR) and beta-2 adrenergic receptor (β2-AR) in living cells, revealing the differential regulation of these receptors' dimerizations by molecular conformations and microenvironment in a plasma membrane. Co-II should provide a simple, rapid, and robust platform for visualizing both weak and strong protein interactions in the plasma membrane of living cells.

Recently, as computer vision and image processing technologies have rapidly advanced in the artificial intelligence (AI) field, deep learning technologies have been applied in the field of urban and regional study through transfer learning. In the tourism field, studies are emerging to analyze the tourists’ urban image by identifying the visual content of photos. However, previous studies have limitations in properly reflecting unique landscape, cultural characteristics, and traditional elements of the region that are prominent in tourism. With the purpose of going beyond these limitations of previous studies, we crawled 168,216 Flickr photos, created 75 scenes and 13 categories as a tourist’ photo classification by analyzing the characteristics of photos posted by tourists and developed a deep learning model by continuously re-training the Inception-v3 model. The final model shows high accuracy of 85.77% for the Top 1 and 95.69% for the Top 5. The final model was applied to the entire dataset to analyze the regions of attraction and the tourists’ urban image in Seoul. We found that tourists feel attracted to Seoul where the modern features such as skyscrapers and uniquely designed architectures and traditional features such as palaces and cultural elements are mixed together in the city. This work demonstrates a tourist photo classification suitable for local characteristics and the process of re-training a deep learning model to effectively classify a large volume of tourists’ photos.

The aim of this study was to evaluate the biocompatibility of calcium silicate-based sealers (CeraSeal and EndoSeal TCS) and epoxy resin-based sealer (AH-Plus) in terms of cell viability, inflammatory response, expression of mesenchymal phenotype, osteogenic potential, cell attachment, and morphology, of human periodontal ligament stem cells (hPDLSCs). hPDLSCs were acquired from the premolars (n = 4) of four subjects, whose ages extended from 16 to 24 years of age. Flow cytometry analysis showed stemness of hPDLSCs was maintained in all materials. In cell viability test, AH-Plus showed the lowest cell viability, and CeraSeal showed significantly higher cell viability than others. In ELISA test, AH-Plus showed higher expression of IL-6 and IL-8 than calcium silicate-based sealers. In an osteogenic potential test, AH-Plus showed a lower expression level than other material; however, EndoSeal TCS showed a better expression level than others. All experiments were repeated at least three times per cell line. Scanning electronic microscopy studies showed low degree of cell proliferation on AH-Plus, and high degree of cell proliferation on calcium silicate-based sealers. In this study, calcium silicate-based sealers appear to be more biocompatible and less cytotoxic than epoxy-resin based sealers.

In this article, a strategy for the fabrication of color-tuned titanium using a torch was developed. The torch was used to manufacture a layer of titanium dioxide on titanium substrates. The reaction time and requirements were reduced compared to the anodization process. Various colors appeared depending on the time of torch heating, and this torched-titanium substrate was treated with octadecyltriethoxylsilane (ODTS) to gain superhydrophobic properties for self-cleaning. Scanning Electron Microscope (SEM), Raman spectroscopy, and Atomic Force Microscope (AFM) were used for surface analysis. Besides, the mechanical and ODTS stability of the surface were evaluated through a cross-cut adhesion tape test and water contact angle measurement, proving that the torch is a suitable fabrication process for multifunctional color-tuned titanium.

This paper proposes a technique to estimate the distance between an object and a rolling shutter camera using a single image. The implementation of this technique uses the principle of the rolling shutter effect (RSE), a distortion within the rolling-shutter-type camera. The proposed technique has a mathematical strength compared to other single photo-based distance estimation methods that do not consider the geometric arrangement. The relationship between the distance and RSE angle was derived using the camera parameters (focal length, shutter speed, image size, etc.). Mathematical equations were derived for three different scenarios. The mathematical model was verified through experiments using a Nikon D750 and Nikkor 50 mm lens mounted on a car with varying speeds, object distances, and camera parameters. The results show that the mathematical model provides an accurate distance estimation of an object. The distance estimation error using the RSE due to the change in speed remained stable at approximately 10 cm. However, when the distance between the object and camera was more than 10 m, the estimated distance was sensitive to the RSE and the error increased dramatically.

As the performance of supervised classification using convolutional neural networks (CNNs) are affected significantly by training patches, it is necessary to analyze the effects of the information content of training patches in patch-based classification. The objective of this study is to quantitatively investigate the effects of class purity of a training patch on performance of crop classification. Here, class purity that refers to a degree of compositional homogeneity of classes within a training patch is considered as a primary factor for the quantification of information conveyed by training patches. New quantitative indices for class homogeneity and variations of local class homogeneity over the study area are presented to characterize the spatial homogeneity of the study area. Crop classification using 2D-CNN was conducted in two regions (Anbandegi in Korea and Illinois in United States) with distinctive spatial distributions of crops and class homogeneity over the area to highlight the effect of class purity of a training patch. In the Anbandegi region with high class homogeneity, superior classification accuracy was obtained when using large size training patches with high class purity (7.1%p improvement in overall accuracy over classification with the smallest patch size and the lowest class purity). Training patches with high class purity could yield a better identification of homogenous crop parcels. In contrast, using small size training patches with low class purity yielded the highest classification accuracy in the Illinois region with low class homogeneity (19.8%p improvement in overall accuracy over classification with the largest patch size and the highest class purity). Training patches with low class purity could provide useful information for the identification of diverse crop parcels. The results indicate that training samples in patch-based classification should be selected based on the class purity that reflects the local class homogeneity of the study area.

Akt kinases are key signaling components in proliferation-competent and post-mitotic cells. Here, we sought to create a conditionally-inducible form of active Akt for both in vitro and in vivo applications. We fused a ligand-responsive Destabilizing Domain (DD) derived from E. coli dihydrofolate reductase to a constitutively active mutant form of Akt1, Akt(E40K). Prior work indicated that such fusion proteins may be stabilized and induced by a ligand, the antibiotic Trimethoprim (TMP). We observed dose-dependent, reversible induction of both total and phosphorylated/active DD-Akt(E40K) by TMP across several cellular backgrounds in culture, including neurons. Phosphorylation of FoxO4, an Akt substrate, was significantly elevated after DD-Akt(E40K) induction, indicating the induced protein was functionally active. The induced Akt(E40K) protected cells from apoptosis evoked by serum deprivation and was neuroprotective in two cellular models of Parkinson's disease (6-OHDA and MPP+ exposure). There was no significant protection without induction. We also evaluated Akt(E40K) induction by TMP in mouse substantia nigra and striatum after neuronal delivery via an AAV1 adeno-associated viral vector. While there was significant induction in striatum, there was no apparent induction in substantia nigra. To explore the possible basis for this difference, we examined DD-Akt(E40K) induction in cultured ventral midbrain neurons. Both dopaminergic and non-dopaminergic neurons in the cultures showed DD-Akt(E40K) induction after TMP treatment. However, basal DD-Akt(E40K) expression was 3-fold higher for dopaminergic neurons, resulting in a significantly lower induction by TMP in this population. Such findings suggest that dopaminergic neurons may be relatively inefficient in protein degradation, a property that could relate to their lack of apparent DD-Akt(E40K) induction in vivo and to their selective vulnerability in Parkinson's disease. In summary, we generated an inducible, biologically active form of Akt. The degree of inducibility appears to reflect cellular context that will inform the most appropriate applications for this and related reagents.

Resveratrol has gained widespread scientific attention due to its ability to significantly extend the lifespan of yeast. However, research on the efficacy of resveratrol on lifespan extension has yielded mixed results in animal studies, making resveratrol a contentious subject. In our previous work, we reported that transgenic resveratrol rice DJ526 showed unusual health benefits beyond expectations. In this work, we established a callus culture of resveratrol rice DJ526, which contains 180 times more resveratrol than the grain, and found that resveratrol rice callus significantly extended the median lifespan of Drosophila melanogaster by up to 50% compared to the control. The resveratrol rice callus also ameliorated age-dependent symptoms, including locomotive deterioration, body weight gain, eye degeneration, and neurodegeneration of D. melanogaster with age progression. Considering that resveratrol is the most preferred antiaging compound due to its superior safety and proven mechanism against many serious adult diseases, the outstanding efficacy of resveratrol on the longevity of wild-type animals could cast a light on the development of antiaging therapeutic agents.

Pericardial adipose tissue (PAT) is associated with adverse cardiometabolic risk factors and cardiovascular disease (CVD). However, the relative implications of PAT, abdominal visceral and subcutaneous adipose tissue on vascular inflammation have not been explored.We compared the association of PAT, abdominal visceral fat area (VFA), and subcutaneous fat area (SFA) with vascular inflammation, represented as the target-to-background ratio (TBR), the blood-normalized standardized uptake value measured using 18F-Fluorodeoxyglucose Positron Emission Tomography (18FDG-PET) in 93 men and women without diabetes or CVD. Age- and sex-adjusted correlation analysis showed that PAT, VFA, and SFA were positively associated with most cardiometabolic risk factors, including systolic blood pressure, LDL-cholesterol, triglycerides, glucose, insulin resistance and high sensitive C-reactive proteins (hsCRP), whereas they were negatively associated with HDL-cholesterol. In particular, the maximum TBR (maxTBR) values were positively correlated with PAT and VFA (r = 0.48 and r = 0.45, respectively; both P

Hydroxyapatite (HAp)/chitosan composites were prepared by a coprecipitation method, dropping a mixture of chitosan solution and phosphoric acid solution into a calcium hydroxide solution. Using the HAp/chitosan composites prepared, HAp/chitosan hybrid fibers with various HAp contents were prepared by a wet spinning method. X-ray diffraction and scanning electron microscopy analyses revealed that HAp particles were coated onto the surface of the fiber, and the surface roughness increased with increasing the HAp contents in the fiber. In order to evaluate the heavy metal removal characteristics of the HAp/chitosan hybrid fiber, adsorption tests were conducted and the results were compared with those of bare chitosan fibers. The results showed better performance in heavy metal ion removal for the HAp/chitosan hybrid fiber than the chitosan fiber. As the HAp content in the hybrid fiber increased, the removal efficiency of heavy metal ions also increased due to the increase of the specific surface area of the HAp/chitosan hybrid fiber. Adsorption kinetic and isotherm tests revealed that Pb2+ and Cd2+ adsorption to the hybrid fiber follows pseudo-second-order kinetic and Langmuir-type adsorption, respectively.

This qualitative research explored American Caucasian parents’ experience with transnational-transracial adoption. Guided by social constructivism and phenomenology, the goal of this study was to understand how parents perceive and interpret their experience when adopting a child transracially, specifically from China and Korea. Data from in-depth interviews with 17 parents revealed the essence of their experience as embedded in family relations distinctive at various stages of the adoption process. Prior to adoption, transracial adoptive parents possessed well-established ideas about the family and parenthood, which enhanced their commitment and sense of ownership throughout the adoption process. While meeting the child and developing a relationship, parents experienced a complicated mixture of emotions, including tension, anxiety, guilt, and grief. The results also offer further insight into the perspective of American Caucasian parents regarding the cultural socialization of their children. The lack of knowledge and resources regarding the adopted child’s birth culture influenced the parents, often resulting in feelings of helplessness.

In a species with a large distribution relative to its dispersal capacity, geographic variation in traits may be explained by gene flow, selection, or the combined effects of both. Studies of genetic diversity using neutral molecular markers show that patterns of isolation by distance (IBD) or barrier effect may be evident for geographic variation at the molecular level in amphibian species. However, selective factors such as habitat, predator, or interspecific interactions may be critical for geographic variation in sexual traits. We studied geographic variation in advertisement calls in the tree frog Hyla japonica to understand patterns of variation in these traits across Korea and provide clues about the underlying forces for variation.We recorded calls of H. japonica in three breeding seasons from 17 localities including localities in remote Jeju Island. Call characters analyzed were note repetition rate (NRR), note duration (ND), and dominant frequency (DF), along with snout-to-vent length.The findings of a barrier effect on DF and a longitudinal variation in NRR seemed to suggest that an open sea between the mainland and Jeju Island and mountain ranges dominated by the north-south Taebaek Mountains were related to geographic variation in call characters. Furthermore, there was a pattern of IBD in mitochondrial DNA sequences. However, no comparable pattern of IBD was found between geographic distance and call characters. We also failed to detect any effects of habitat or interspecific interaction on call characters.Geographic variations in call characters as well as mitochondrial DNA sequences were largely stratified by geographic factors such as distance and barriers in Korean populations of H. japonica. Although we did not detect effects of habitat or interspecific interaction, some other selective factors such as sexual selection might still be operating on call characters in conjunction with restricted gene flow.