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Abstract Display has been evolving its role as a conventional optical output device into an user interactive input and output device by harnessing various sensors and taking full advantage of its user interaction friendly nature. To demonstrate this phenomenon, here we report a full organic photodiode embedded organic light-emitting diode display as multiple objects sensing platform which identifies the user’s physiological data based on the obtained photoplethysmography signal and also detects a fingerprint for an authentication concurrently in a single device. This paper introduces the technical breakthroughs to solve the complex technical challenges due to the crosstalks induced within the shared common layers during the full integration of the two conflicting devices and also the method made possible for the multiple objects sensing with the measurement results. Consequently, we believe it could prove a progression of display to a fully bidirectional innovative smart user interactive device and also could take a role as a sophisticated future display beyond organic light-emitting diode display.

Abstract Introduction Regdanvimab, a monoclonal antibody pharmaceutical, is the first Korean drug approved for treating coronavirus disease 2019 (COVID-19). We analyzed the therapeutic efficacy of regdanvimab in patients with the COVID-19 delta variant infection. Methods We retrospectively reviewed the electronic medical records of patients hospitalized at two Korean tertiary COVID-19 hospitals with COVID-19 delta variant infection between May 26, 2021, and January 30, 2022. To analyze the therapeutic efficacy of regdanvimab, the patients were divided into regdanvimab and non-regdanvimab groups and were 1:1 propensity-score (PS)-matched on age, severity at admission, and COVID-19 vaccination history. Results Of 492 patients, 262 (53.3%) and 230 (46.7%) were in the regdanvimab and non-regdanvimab groups, respectively. After PS matching the groups on age, severity at admission, and COVID-19 vaccination history, each group comprised 189 patients. The 30-day hospital mortality rates (0.0% vs. 1.6%, p = 0.030), proportions of patients with exacerbated conditions to severe/critical/died (9.5% vs. 16.4%, p = 0.047), proportions who received oxygen therapy because of pneumonia exacerbation (7.4% vs. 16.4%, p = 0.007), and proportions with a daily National Early Warning Score ≥ 5 from hospital day 2 were significantly lower in the regdanvimab group. Conclusions We showed that regdanvimab reduced the exacerbation rates of conditions and mortality in patients with the COVID-19 delta variant infection. Thus, it is recommended to streamline the drug approval system during epidemics of new variant viruses to improve the availability and usage of therapeutics for patients. To facilitate this, relevant institutional support is required.

Identifying features significantly influencing the target outcome is crucial for understanding complex relationships, reducing computational costs, and improving model generalization in high-dimensional data. While powerful for discovering intricate relationships, deep learning-based feature selection methods often overlook inherent group structures in data, such as gene pathways or categorical variables. Consequently, these methods may fail to select informative features within the relevant groups, potentially leading to the selection of less informative features and ultimately, lower model performance. To address this challenge, we propose a novel deep learning-based feature selection method that achieves both intra-group and inter-group sparsity. By introducing a penalty term that encourages group sparsity, our method effectively selects informative groups of features, thereby improving model performance. We validate our approach through experiments on synthetic and real-world datasets with predefined group structures. Our method achieved a $2.5~\sim ~8.2$ % reduction in prediction RMSE and a $0.3~\sim ~1.9$ % improvement in prediction accuracy compared to existing methods. Furthermore, our approach demonstrated a 50% increase in the selection of biologically relevant features, enhancing model interpretability and alignment with relevant scientific literature. These results confirm the effectiveness of our method in leveraging group structures to improve both performance and interpretability.

Objective We aimed to improve the performance of sleep prediction algorithms by increasing the data amount, adding variables reflecting psychological state, and adjusting the data length.Materials and Methods We used ActiGraph GT3X+® and Galaxy Watch Active2™ to collect physical activity and light exposure data. We collected heart rate variability (HRV) data with the Galaxy Watch. We evaluated the performance of sleep prediction algorithms based on different data sources (wearable devices only, sleep diary only, or both), data lengths (1, 2, or 3 days), and analysis methods. We defined the target outcome, ‘good sleep’, as ≥90% sleep efficiency.Results Among 278 participants who denied having sleep disturbance, we used data including 2136 total days and nights from 230 participants. The performance of the sleep prediction algorithms improved with an increased amount of data and added HRV data. The model with the best performance was the extreme gradient boosting model; XGBoost, using both sources combined data with HRV, and 2-day data (accuracy=.85, area under the curve =.80).Conclusions The results show that the performance of the sleep prediction models improved by increasing the data amount and adding HRV data. Further studies targeting insomnia patients and applied researches on non-pharmacological insomnia treatment are needed.

Abstract On the recent report of a field-induced first order transition in the superconducting state of CeRh2As2, which is a possible indication of a parity-switching transition of the superconductor, the microscopic physics is still under investigation. However, if two competing paring channels of opposite parities do exist, a particle-particle collective mode referred to as the Bardasis-Schrieffer (BS) mode should generically exist below the pair-breaking continuum. The BS mode of the CeRh2As2 superconductor can couple to the light, as it arises from a pairing channel with the parity opposite to that of the superconducting condensate. Here, by using a generic model Hamiltonian we carry out a qualitative investigation on the excitation energy of the BS mode with respect to the out-of-plane magnetic fields and its contribution to the optical conductivity. Our findings indicate that the distinct coupling between the BS mode and the light can serve as evidence for the competing odd-parity channels of CeRh2As2 and other locally non-centrosymmetric superconductors.

Traumatic brain injury (TBI) is a biomechanical problem where the initiating event is dynamic loading (blunt, inertial, blast) to the head. To understand the relationship between the mechanical parameters of the injury and the deformation patterns in the brain, we have previously developed a surrogate head (SH) model capable of measuring spatial and temporal deformation in a surrogate brain under blunt impact. The objective of this work was to examine how material properties and anatomical features affect the motion of the brain and the development of injurious deformations. The SH head model was modified to study six variables independently under blunt impact: surrogate brain stiffness, surrogate skull stiffness, inclusion of cerebrospinal fluid (CSF), head/skull size, inclusion of vasculature, and neck stiffness. Each experimental SH was either crown or frontally impacted at 1.3 m/s (3 mph) using a drop tower system. Surrogate brain material, the Hybrid III neck stiffness, and skull stiffness were measured and compared to published properties. Results show that the most significant variables affecting changes in brain deformation are skull stiffness, inclusion of CSF and surrogate brain stiffness. Interestingly, neck stiffness and SH size significantly affected the strain rate only suggesting these parameters are less important in blunt trauma. While the inclusion of vasculature locally created strain concentrations at the interface of the artery and brain, overall deformation was reduced.

Summary: Co-occurrence of multiple myeloma and acute myelogenous leukemia is rare, with both malignancies often tracing back to multipotent hematopoietic stem cells. Cytogenetic techniques are the established baseline for diagnosis and characterization of complex hematological malignancies. In this study, we develop a workflow called Hema-seq to delineate clonal changes across various hematopoietic lineages through the integration of whole-genome sequencing, copy-number variations, cell morphology, and cytogenetic aberrations. In Hema-seq, cells are selected from Wright-stained slides and fluorescent probe-stained slides for sequencing. This technique therefore enables direct linking of whole-genome sequences to cytogenetic profiles. Through this method, we mapped sequential clonal alterations within the hematopoietic lineage, identifying critical shifts leading to myeloma and acute myeloid leukemia (AML) cell formations. By synthesizing data from each cell lineage, we provided insights into the hematopoietic tree’s clonal evolution. Overall, this study highlights Hema-seq’s capability in deciphering genomic heterogeneity in complex hematological malignancies, which can enable better diagnosis and treatment strategies. Motivation: Hematological malignancies, with their intricate molecular landscapes, present significant challenges in the diagnostic and therapeutic realms. The co-existence of neoplastic and normal cells within these malignancies further adds to this complexity. Traditional cytogenetic methods, while invaluable, cannot resolve the full spectrum of genomic aberrations, especially in rare simultaneous occurrences. We therefore sought to bring the greater degree of genomic resolution afforded by whole-genome sequencing to samples that have been processed and preserved through cytogenetic methods and to link sequencing profiles to selected cell populations for higher-resolution clonal reconstruction and analysis. Such an approach not only holds promise in unveiling the mysteries of clonal evolution but also in guiding tailored therapeutic strategies for enhanced patient outcomes. In short, our work with “Hema-seq” is driven by the motivation to bridge existing gaps and offer a panoramic view of the genomic intricacies within hematopoietic lineage cells.

Background: The extra-capsular spread (ECS) of lymph node metastasis (LNM) is a hallmark of aggressive primary tumor phenotype in head and neck cancer (HNC); however, the factors influencing ECS are poorly understood. Patients and Methods: This was a retrospective study, including 190 cases of oral tongue cancer (OTC), 148 cases of oropharyngeal cancer (OPC) (118 HPV-positive and 30 HPV-negative), and 100 cases of hypopharyngeal cancer (HPC). Tumor dimension, tumor biological variables (lymphovascular/perineural invasion and histologic grade), and LNM variables (LNM number and size) were analyzed according to the presence of ECS using multivariable logistic regression and receiver operating characteristic (ROC) curve analyses. Results: LNM variables were significant factors for ECS in all subsites of HNC (p < 0.05), except HPV-positive OPC. In OTC, tumor dimensional variables were significantly related to ECS (p < 0.01). Meanwhile, in OPC and HPC, neither the primary tumor dimension nor the T status were significant factors for ECS occurrence. The predictability of ECS by ROC curve using multiple variables was 0.819 [95% confidence interval: 0.759–0.878] in OTC, 0.687 [0.559–0.815] in HPV-positive OPC, 0.823 [0.642–1.000] in HPV-negative OPC, and 0.907 [0.841–0.973] in HPC. Conclusion: LNM variables were correlated with ECS occurrence for most HNC subsites, and site-dependent primary tumor characteristics might contribute differentially to the ECS development of LNM in HNC.

Abstract Background Reemergent local outbreaks of classical swine fever (CSF) occurred simultaneously in multiple pig farms on CSF‐free Jeju Island, South Korea, in 2014 because of inadvertent injection of a commercial CSF (LOM) vaccine into pregnant sows. The LOM virus has since spread across the island and has become endemic in Jeju herds, raising concern about possible reversion to the virulence of the LOM vaccine. We previously isolated LOM‐derived field CSF virus (CSFV) strains with unique insertion‐deletion (INDEL) mutations in the 3′‐untranslated region (UTR), designated LOM‐derived Jeju 3′‐UTR INDEL variants, from CSF‐recurrent swine farms on Jeju Island in 2019. Methods The present study conducted animal experiments to investigate whether a 2019 emergent LOM 3′‐UTR INDEL variant, KNU‐1905, has reverted to a pathogenic form in conventional pigs (n = 10). Results Experimental animal infection showed that pigs inoculated with the commercial LOM vaccine strain developed no adverse effects compared to the sham‐infected pigs. However, KNU‐1905 displayed pathogenic characteristics in pigs, including clinical symptoms (e.g., lethargy, conjunctivitis, nasal discharge, and diarrhoea), weight loss, and gross lesions. Moreover, viremia, virus shedding in faeces and nasal fluids, and viral loads in various tissues of all the KNU‐1905‐infected pigs were highly significant, in contrast to those of the LOM‐infected group in which CSFV RNA was detected only in the serum, nasal, and tonsil samples of one identical pig. Conclusions Overall, the LOM‐derived field isolate with molecular variations induced clinical adverse events in pigs, which commonly shed considerable amounts of CSFV. This study provides evidence that the genetic evolution of the LOM‐derived CSFV circulating on Jeju Island might have allowed the LOM vaccine to recover its primary prototype and that these variants might have induced chronic or persistent infection in pigs that can shed CSFV in field farms leading to a risk of transmission among pigs or farms in this former CSF‐free region.

Abstract Active Surveillance (AS) for prostate cancer is a management option that continually monitors early disease and considers intervention if progression occurs. A robust method to incorporate “live” updates of progression risk during follow-up has hitherto been lacking. To address this, we developed a deep learning-based individualised longitudinal survival model using Dynamic-DeepHit-Lite (DDHL) that learns data-driven distribution of time-to-event outcomes. Further refining outputs, we used a reinforcement learning approach (Actor-Critic) for temporal predictive clustering (AC-TPC) to discover groups with similar time-to-event outcomes to support clinical utility. We applied these methods to data from 585 men on AS with longitudinal and comprehensive follow-up (median 4.4 years). Time-dependent C-indices and Brier scores were calculated and compared to Cox regression and landmarking methods. Both Cox and DDHL models including only baseline variables showed comparable C-indices but the DDHL model performance improved with additional follow-up data. With 3 years of data collection and 3 years follow-up the DDHL model had a C-index of 0.79 (±0.11) compared to 0.70 (±0.15) for landmarking Cox and 0.67 (±0.09) for baseline Cox only. Model calibration was good across all models tested. The AC-TPC method further discovered 4 distinct outcome-related temporal clusters with distinct progression trajectories. Those in the lowest risk cluster had negligible progression risk while those in the highest cluster had a 50% risk of progression by 5 years. In summary, we report a novel machine learning approach to inform personalised follow-up during active surveillance which improves predictive power with increasing data input over time.

Various invasive fungal infections can occur in immunocompromised hosts, and an acute invasive fungal infection (AIFI) can be fatal. Because of its high mortality rate, AIFI must be quickly diagnosed and treated, such as anti-fungal agents or surgical debridement. In an immunocompromised host, nasal herpes simplex infection, usually caused by herpes simplex virus (HSV) type-1, can have various clinical manifestations, some of which can mimic AIFI. However, the management of acute viral infection differs significantly from invasive fungal infections of the nose. A fast and accurate differential diagnosis is mandatory because a delay in the disease-specific treatment of acute invasive infections can lead to mortality. This report describes two immunocompromised patients with mucosal and skin lesions around the nose. We provide clinical clues when mucosal lesions of the nasal cavity and skin lesions around the nose develop in immunocompromised hosts.

BackgroundImmune-evading severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants are emerging continuously. The clinical effectiveness of monoclonal antibody agents that exhibit decreased in vitro activity against SARS-CoV-2 variants needs to be elucidated.MethodsA nationwide, multicenter, retrospective cohort study was designed to evaluate the effectiveness of regdanvimab, an anti-SARS-CoV-2 monoclonal antibody agent. Regdanvimab was prescribed in South Korea before and after the emergence of the delta variant, against which the in vitro activity of regdanvimab was decreased but present. Mild to moderate coronavirus 2019 (COVID-19) patients with risk factors for disease progression who were admitted within seven days of symptom onset were screened in four designated hospitals between December 2020 and September 2021. The primary outcomes, O2 requirements and progression to severe disease within 21 days of admission, were compared between the regdanvimab and supportive care groups, with a subgroup analysis of delta variant–confirmed patients.ResultsA total of 2,214 mild to moderate COVID-19 patients were included, of whom 1,095 (49.5%) received regdanvimab treatment. In the analysis of the total cohort, significantly fewer patients in the regdanvimab group than the supportive care group required O2 support (18.4% vs. 27.1%, P < 0.001) and progressed to severe disease (4.0% vs. 8.0%, P < 0.001). In the multivariable analysis, regdanvimab was significantly associated with a decreased risk for O2 support (HR 0.677, 95% CI 0.561–0.816) and progression to severe disease (HR 0.489, 95% CI 0.337–0.709). Among the 939 delta-confirmed patients, O2 support (21.5% vs. 23.5%, P = 0.526) and progression to severe disease (4.2% vs. 7.3%, P = 0.055) did not differ significantly between the regdanvimab and supportive care groups. In the multivariable analyses, regdanvimab treatment was not significantly associated with a decreased risk for O2 support (HR 0.963, 95% CI 0.697–1.329) or progression to severe disease (HR 0.665, 95% CI 0.349–1.268) in delta-confirmed group.ConclusionsRegdanvimab treatment effectively reduced progression to severe disease in the overall study population, but did not show significant effectiveness in the delta-confirmed patients. The effectiveness of dose increment of monoclonal antibody agents should be evaluated for variant strains exhibiting reduced susceptibility.

This study explores the potential of titanium disulfide (TiS2) as an active material for aqueous calcium-ion batteries (CIBs). We investigate the electrochemical redox reactions of calcium ions within TiS2 and assess its suitability for use in aqueous CIBs. Additionally, we examine the impact of varying electrolyte concentrations, ranging from 1.0 to 8.0 mol dm−3, on TiS2 electrode reactions. Our findings reveal that TiS2 exhibits distinct charge–discharge behaviors in various aqueous calcium-ion electrolytes. Notably, at higher electrolyte concentrations, TiS2 effectively suppresses the hydrogen generation reaction caused by water decomposition. In situ X-ray diffraction analysis confirms the intercalation of Ca2+ ions between the TiS2 layers during charging, which is a groundbreaking discovery, signifying TiS2’s applicability in aqueous CIBs. X-ray photoelectron spectroscopy analysis further supports the formation of a solid electrolyte interphase (SEI) on the TiS2 electrode surface, contributing to the suppression of electrolyte decomposition reactions. Furthermore, we investigate the influence of anions in the electrolyte on charge–discharge behavior. Our findings suggest that the choice of anion coordinated with Ca2+ ions affects the SEI formation and cycling performance. Understanding the role of anions in SEI formation is crucial for optimizing aqueous CIBs. In conclusion, this research underscores TiS2’s potential as an active material for aqueous calcium-ion batteries and emphasizes the importance of the electrolyte composition in influencing SEI formation and battery performance, contributing to sustainable and efficient energy storage technologies.

Pedestrians are more likely to be seriously injured in vehicle collisions. In fact, multiple collisions between vehicles and pedestrians occur on residential roads that lack street-to-sidewalk dividers and have numerous blind spots. Traditional traffic safety features and equipment, such as speed bumps and traffic signs, are not always sufficient to prevent pedestrian accidents on such residential roads. Therefore, we suggest a collision risk warning service for residential roads as a solution to this issue. We use CCTVs with computer vision techniques and radar to accurately detect objects in real-time and to trace their trajectories. In addition, we employ a time-to-collision-based method to identify dangerous situations. The service warns drivers and pedestrians about hazardous situations using a light-emitting diode sign board. We applied our service to three different roads on a university campus in Seoul, Korea, and then conducted a user survey to evaluate the service. In summary, more than 90% of respondents stated that the service was necessary for these specific locations, and 76.9% noted that the service significantly contributed to traffic safety on the campus. This implies that the proposed service improved traffic safety and can be applied to various locations on residential roads.

Intermetallic γ-TiAl alloy has excellent properties at high temperatures and is thus attracting attention as a substitute for nickel-based superalloy parts for turbine engines. However, γ-TiAl alloy is reported to be a difficult material to be machined due to its low ductility at room temperature, tensile strength, and thermal conductivity. In this study, a system capable of measuring thrust force (Tf) and torque (Tc) during the drilling process was constructed, and drilling processability according to the heat treated microstructure of γ-TiAl alloy was compared. As a result, it was confirmed that the thrust and torque of the γ-TiAl alloy having a microstructure in which the grains were refined by the heat treatment process was relatively low and rapidly stabilized, which is advantageous for drilling.

A wider array of color gamut and higher luminance are increasingly offered by displays to provide users with immersive content. However, in the latest displays available, it is difficult to predict image brightness because the extensively used color appearance model is made based on a color patch whose color appearance is not the same as that of an image on the display. Therefore, in this study, a method of predicting image brightness on a display depending on its color gamut by quantifying the Helmholtz–Kohlrausch (H–K) effect is proposed. A method for accurately measuring image luminance is also presented. To verify the performance of the proposed model, a brightness matching experiment is performed under two different color gamut sizes. The experimental results confirm that the image appears brighter with the increase in color gamut due to the H–K effect, demonstrating that the proposed prediction model exhibits desirable performance. The proposed brightness prediction model, which includes the image experience in the color range, delivers better image quality to users.

The technology proposed in this study aims to improve the performance characteristics and coefficient of performance (COP) of a geothermal system by fundamentally preventing underground water discharge and maintaining a constant temperature of the underground heat exchanger composed of bleed discharge water that utilizes two balancing wells using cross-mixing methods. The results of measurements using this technique show that the change in operation from a regular SCW-type heat exchange system to a well-intersected heat exchange system not only improves the COP of geothermal heating and cooling systems, but also ensures a stable supply of geothermal sources. This result is useful for essentially eliminating the ultimately wasted bleed water.

Background: There remains a lack of accurate and validated outcome-prediction models in total knee arthroplasty (TKA). While machine learning (ML) is a powerful predictive tool, determining the proper algorithm to apply across diverse data sets is challenging. AutoPrognosis (AP) is a novel method that uses automated ML framework to incorporate the best performing stages of prognostic modeling into a single well-calibrated algorithm. We aimed to compare various ML methods to AP in predictive performance of complications after TKA. Methods: Thirty-eight preoperative patient demographics and clinical features from all primary TKAs performed at California-licensed hospitals between 2015 and 2017 were evaluated as predictors of major complications after TKA. Traditional logistic regression (LR), various other ML methods (XGBoost, Gradient Boosting, AdaBoost, and Random Forest), and AP were used for model building to determine discriminative power (area under receiver operating curve), calibration (Brier score), and feature importance. Results: Between 2015 and 2017, there were a total of 156,750 TKAs with 1109 (0.7%) total major complications. AP had the highest discriminative performance with area under receiver operating curve 0.679 compared with LR, XGBoost, Gradient Boosting, AdaBoost, and Random Forest (0.617, 0.601, 0.662, 0.657, and 0.545, respectively). AP (Brier score 0.007) had similar calibration as the other ML methods (0.006, 0.006, 0.022, 0.007, and 0.008, respectively). The variables that are most important for AP differ from those that are most important for LR. Conclusion: Compared to conventional ML algorithms, AP has superior discriminative ability with similar calibration and suggests nonlinear relationships between variables in outcomes of TKA.

Internships are widely viewed as “door openers” to opportunity, yet students without ample financial, social, and institutional supports are often excluded from these experiences. This exclusion is especially problematic for Latinx students attending Hispanic-Serving Institutions, for whom an internship could be transformative. In this article, we elaborate upon Núñez’s (2014) multilevel model of intersectionality to highlight how agents’ perceptions, social categories, embodied practices, and broader contextual forces interrelate to shape Latinx students’ access to internship opportunities at a university in the border region of Texas. Using inductive thematic, correlational, and social-network analysis techniques to analyze survey (n = 192) and focus group (n = 12) data, we find that gender, academic major, socioeconomic status, and race intersect with organizational (e.g., insufficient information) and contextual (e.g., labor markets) factors to shape students’ access and perceptions. We provide recommendations for disrupting systemic inequalities in internship access and culturally appropriate programming and ideas for future research.

Background The demand and incidence of anatomic total shoulder arthroplasty (aTSA) procedures is projected to increase substantially over the next decade. There is a paucity of accurate risk prediction models which would be of great utility in minimizing morbidity and costs associated with major post-operative complications. Machine learning is a powerful predictive modeling tool and has become increasingly popular, especially in orthopedics. We aimed to build a ML model for prediction of major complications and readmission following primary aTSA. Methods A large California administrative database was retrospectively reviewed for all adults undergoing primary aTSA between 2015 to 2017. The primary outcome was any major complication or readmission following aTSA. A wide scope of standard ML benchmarks, including Logistic regression (LR), XGBoost, Gradient boosting, AdaBoost and Random Forest were employed to determine their power to predict outcomes. Additionally, important patient features to the prediction models were indentified. Results There were a total of 10,302 aTSAs with 598 (5.8%) having at least one major post-operative complication or readmission. XGBoost had the highest discriminative power (area under receiver operating curve AUROC of 0.689) of the 5 ML benchmarks with an area under precision recall curve AURPC of 0.207. History of implant complication, severe chronic kidney disease, teaching hospital status, coronary artery disease and male sex were the most important features for the performance of XGBoost. In addition, XGBoost identified teaching hospital status and male sex as markedly more important predictors of outcomes compared to LR models. Conclusion We report a well calibrated XGBoost ML algorithm for predicting major complications and 30-day readmission following aTSA. History of prior implant complication was the most important patient feature for XGBoost performance, a novel patient feature that surgeons should consider when counseling patients.

In this study, we investigated media reports and literacy research in four nations--China, Morocco, the Republic of (South) Korea, and the United States--about the relationship between adolescents' literacy and use of digital media, or digital literacy. We present short "snapshots" of adolescents' digital literacy in each country and then compare these to findings in a report about adolescent literacy and uses of digital media published by the Program for International Student Assessment (PISA). Our analysis indicates significant variation across countries in both literate traditions and adolescents' access to digital media, and notes that these interact to create unique conditions for adolescents' digital literacy in each country, even as, across the four nations, adolescents' capacity to innovate and solve problems with digital access seems constant. In conclusion, we are cautious about making global claims about the state of adolescents' literacy worldwide but point to important findings about how the use of the internet in schools seems to have a positive impact on reading performance and offer some implications for classroom practice.

A major focus of innovation in higher education today is to improve faculty teaching, especially their focus on students' career readiness and acquisition of workplace-relevant communication and teamwork competencies (i.e., transferable skills). Some contend that such instruction is best achieved through hiring faculty with prior work experience in industry, where the "culture" is preferable to academia where practical skills and career guidance are undervalued. However, little research exists on the topic and in this study we draw on person-centered views of culture to conceptualize industry experience as a form of cultural knowledge (i.e., cultural scripts) that can travel with a person (or not) over time and space. Using a mixed methods design where we gathered survey (n = 1,140) and interview (n = 89) data from STEMM faculty, we used thematic and HLM techniques to explore the relationships among industry experience, various situational factors, and transferable skills instruction. Results show that while most had industry experience (76.2%), transferable skills are rarely emphasized, a variety of individual (e.g., race) and institutional (e.g., discipline) factors are associated with transferable skills instruction, and that industry experience provides both generalized and specific cultural scripts for career- and skills-oriented teaching. We conclude that instead of promoting skills-focused instructional innovations via hiring policies that assume the value of one institutional culture over another, it is more useful and respectful (to faculty) to teach industry-based cultural knowledge via faculty development programming in a way similar to work-integrated learning (WIL) and communication in the disciplines (CID) initiatives.

Early detection of pharyngocutaneous fistula (PCF) after total laryngectomy (TL) could prevent severe complications such as major vessel rupture. We aimed to develop prediction models for detecting PCF in the early postoperative period. We retrospectively analyzed patients (N = 263) who received TL between 2004 and 2021. We collected clinical data for fever (>38.0 °C) and blood tests (WBC, CRP, albumin, Hb, neutrophils, lymphocytes) on postoperative days (POD) 3 and 7, and fistulography on POD 7. Clinical data were compared between fistula and no fistula groups, and significant factors were selected using machine learning. Using these clinical factors, we developed improved prediction models for PCF detection. Fistula occurred in 86 (32.7%) patients. Fever was significantly (p < 0.001) more common in the fistula group, and ratios (POD 7 to 3) of WBC, CRP, neutrophils, and neutrophils-to-lymphocytes (NLR) were significantly higher (all p ≤ 0.001) in the fistula group than in the no fistula group. Leakage on fistulography was more common in the fistula group (38.2%) than in the no fistula group (3.0%). The area under curve (AUC) of fistulography alone was 0.68, but predictive models using a combination of fistulography, WBC at POD 7, and neutrophil ratio (POD 7/POD 3) showed better diagnostic performance (AUC of 0.83). Our predictive models may detect PCF early and accurately, which could reduce fatal complications following PCF.

Abstract Most individuals undergo traumatic stresses at some points in their life, but only a small proportion develop stress-related disorders such as anxiety diseases and posttraumatic stress disorder (PTSD). Although stress susceptibility is one determinant of mental disorders, the underlying mechanisms and functional implication remain unclear yet. We found that an increased amount of freezing that animals exhibited in the intertrial interval (ITI) of a stress-enhanced fear learning paradigm, predicts ensuing PTSD-like symptoms whereas resilient mice show ITI freezing comparable to that of unstressed mice. To examine the behavioral features, we developed a systematic analytical approach for ITI freezing and stress susceptibility. Thus, we provide a behavioral parameter for prognosis to stress susceptibility of individuals in the development of PTSD-like symptoms as well as a new mathematical means to scrutinize freezing behavior.

Category: Ankle Arthritis; Ankle Introduction/Purpose: Ankle arthrodesis and total ankle replacement are the most commonly performed procedures for surgical management of ankle arthritis. Arthrodesis provides effective pain relief but the rate of complications after arthrodesis is higher as it is more commonly performed in patients with comorbidities that preclude ankle replacement. Accurately risk- stratifying patients who undergo ankle arthrodesis would be of great utility, given the significant cost and morbidity associated with developing major perioperative complications. There is a paucity of accurate prediction models that can be used to pre- operatively risk-stratify patients for ankle arthrodesis. We aim to develop a machine learning (ML) algorithm for prediction of major perioperative complication after ankle arthrodesis as well as compare its performance against traditional predictive models based on logistic regression. Methods: This is a retrospective cohort study of adult patients who underwent ankle arthrodesis at any non-federal California hospital between 2015 and 2017. The primary outcome was readmission within 30 days or major perioperative complication - venous thromboembolism within 30 days, myocardial infarction within 7 days, pneumonia within 7 days, systemic infection within 7 days, surgical site bleeding within 90 days, and wound complications within 90 days. We build ML and logistic regression models that span different classes of modeling approaches: XGBoost, AdaBoost, Gradient Boosting, and Random Forest. Discrimination and calibration were assessed using area under the receiver operating characteristic curve (AUROC) and Brier score, respectively. We utilize a partial dependence function to measure the importance of an individual feature by assessing the average effect in predicted risks when its value is altered. We rank the contribution of the included variables to the prediction of adverse outcomes. Results: A total of 1,084 patients met inclusion criteria for this study. There were 131 major complications or readmission (12.1%). The optimized XGBoost algorithm demonstrates higher discrimination (AUROC: 0.707 + 0.052) compared to LR (0.691 + 0.055). The receiver operating characteristic curves for the XGBoost and logistic regression models are visualized in Figure 1. XGBoost also outperforms the three other ML models. This model was well calibrated (Brier score: 0.103 + 0.001). The variables most important for the XGBoost model include diabetes, chronic kidney disease, implant complication, and major fracture. Five of the ten most important features for XGBoost were markedly less important for the traditional logistic regression model: male sex, prior hip fracture, cardiorespiratory failure, acute renal failure, and dialysis status. Conclusion: We report a ML algorithm for prediction of major perioperative complications after ankle arthrodesis. The optimized XGBoost model is well-calibrated and demonstrates superior risk prediction to logistic regression. This tool may identify and address potentially modifiable risk factors, helping to accurately risk-stratify patients and decrease likelihood of major complications. Notably, the predictors most important for XGBoost are different from those for logistic regression. This suggests that the superior discriminative capability of ML methods stems from their ability to capture complex non-linear relationships between variables that logistic regression is unable to detect.

Designing high-resolution displays based on colloidal quantum dots remains a challenge. Here, the authors demonstrate a photo-patterning method to develop CdSe-based core-shell quantum dots patterns of red, green and blue colours with diameters ranging from 7 to 20 nm and resolution of 1400 pixels per inch.

Background Reverse total shoulder arthroplasty (rTSA) offers tremendous promise for the treatment of complex pathologies beyond the scope of anatomic total shoulder arthroplasty but is associated with a higher rate of major postoperative complications. We aimed to design and validate a machine learning (ML) model to predict major postoperative complications or readmission following rTSA. Methods We retrospectively reviewed California's Office of Statewide Health Planning and Development database for patients who underwent rTSA between 2015 and 2017. We implemented logistic regression (LR), extreme gradient boosting (XGBoost), gradient boosting machines, adaptive boosting, and random forest classifiers in Python and trained these models using 64 binary, continuous, and discrete variables to predict the occurrence of at least one major postoperative complication or readmission following primary rTSA. Models were validated using the standard metrics of area under the receiver operating characteristic (AUROC) curve, area under the precision–recall curve (AUPRC), and Brier scores. The key factors for the top-performing model were determined. Results Of 2799 rTSAs performed during the study period, 152 patients (5%) had at least 1 major postoperative complication or 30-day readmission. XGBoost had the highest AUROC and AUPRC of 0.681 and 0.129, respectively. The key predictive features in this model were patients with a history of implant complications, protein-calorie malnutrition, and a higher number of comorbidities. Conclusion Our study reports an ML model for the prediction of major complications or 30-day readmission following rTSA. XGBoost outperformed traditional LR models and also identified key predictive features of complications and readmission.

For the past three decades, the porcine epidemic diarrhea virus (PEDV) has remained an enormous threat to the South Korean swine industry. The scarcity of an effective method for manipulating viral genomes has impeded research progress in PEDV biology and vaccinology. Here, we report the development of reverse genetics systems using two novel infectious full-length cDNA clones of a Korean highly pathogenic-G2b strain, KNU-141112, and its live attenuated vaccine strain, S DEL5/ORF3, in a bacterial artificial chromosome (BAC) under the control of a eukaryotic promoter. Direct transfection of cells with each recombinant BAC clone induced cytopathic effects and produced infectious progeny. The reconstituted viruses, icKNU-141112 and icS DEL5/ORF3, harboring genetic markers, displayed phenotypic and genotypic properties identical to their respective parental viruses. Using the DNA-launched KNU-141112 infectious cDNA clone as a backbone, two types of recombinant viruses were generated. First, we edited the open reading frame 3 (ORF3) gene, as cell-adapted strains lose full-length ORF3, and replaced this region with an enhanced green fluorescent protein (EGFP) gene to generate icPEDV-EGFP. This mutant virus presented parental virus-like growth kinetics and stably retained robust EGFP expression, indicating that ORF3 is dispensable for PEDV replication in cell culture and is a tolerant location for exogeneous gene acceptance. However, the plaque size and syncytia phenotypes of ORF3-null icPEDV-EGFP were larger than those of icKNU-141112 but similar to ORF3-null icS DEL5/ORF3, suggesting a potential role of ORF3 in PEDV cytopathology. Second, we substituted the spike (S) gene with a heterologous S protein, designated S51, from a variant of interest (VOI), which was the most genetically and phylogenetically distant from KNU-141112. The infectious recombinant VOI, named icPEDV-S51, could be recovered, and the rescued virus showed indistinguishable growth characteristics compared to icKNU-141112. Virus cross-neutralization and structural analyses revealed antigenic differences in S between icKNU-141112 and icPEDV-S51, suggesting that genetic and conformational changes mapped within the neutralizing epitopes of S51 could impair the neutralization capacity and cause considerable immune evasion. Collectively, while the established molecular clones afford convenient, versatile platforms for PEDV genome manipulation, allowing for corroborating the molecular basis of viral replication and pathogenesis, they also provide key infrastructural frameworks for developing new vaccines and coronaviral vectors.

Chronic obstructive pulmonary disease (COPD) is mainly caused by cigarette smoking and characterized by chronic inflammation in vulnerable individuals. However, it is unknown how genetic factors may shape chronic inflammation in COPD. To understand how hedgehog interacting protein, encoded by HHIP gene identified in the genome-wide association study in COPD, plays a role in inflammation, we utilized Hhip+/– mice that present persistent inflammation and emphysema upon aging similar to that observed in human COPD. By performing single-cell RNA sequencing of the whole lung from mice at different ages, we found that Hhip+/– mice developed a cytotoxic immune response with a specific increase in killer cell lectin-like receptor G1–positive CD8+ T cells with upregulated Ifnγ expression recapitulating human COPD. Hhip expression was restricted to a lung fibroblast subpopulation that had increased interaction with CD8+ T lymphocytes in Hhip+/– compared with Hhip+/+ during aging. Hhip-expressing lung fibroblasts had upregulated IL-18 pathway genes in Hhip+/– lung fibroblasts, which was sufficient to drive increased levels of IFN-γ in CD8+ T cells ex vivo. Our finding provides insight into how a common genetic variation contributes to the amplified lymphocytic inflammation in COPD.

The characteristics of the interface between Ni-rich cathode materials and carbonate-based electrolytes are crucial for stability in charge-discharge cycles. In this study, we used tris(trimethylsilyl)phosphite (TMSPi) as an additive for film formation and investigated the properties of the layer formed on a LiNi0.6Co0.2Mn0.2O2 (NCM622) thin-film electrode. This layer can act as a barrier to mitigate the underlying attack at the oxygen sites of the layered Ni-rich structure. Moreover, this layer mainly consists of Li-rich organic components, leading to a decreased activation energy with a rapid Li-ion transfer process.

Colloidal semiconductor nanocrystals, referred to as quantum dots (QDs), have unique and superb photophysical properties, promising a variety of applications ranging from optoelectronics and energy harvesting to agriculture. The last decade witnessed a tremendous advance in QDs and their successful debut in displays, and now, QDs are equipped with environmental benignity to expand their territory to everyday life. From this perspective, the current research status and future perspective of environmentally benign QDs as building blocks for light-generating and light-harvesting applications are provided. Also provided is an overview of the progress made in the chemistry (colloidal synthesis, surface chemistry, and heterostructuring) and in their photophysical and electrical properties from the viewpoint of their use in light-emitting or light-harvesting applications. Grounded on the current status of heavy-metal-free QDs compared with cutting-edge technologies, the perspective of environmentally benign QDs for practical use and future research directions is discussed.

Electrical annealing (EA) is one of the post treatments to enhance the electrical performances of organic devices. To date, the improvements using EA have only been reported for the solution-processed devices because its mechanism has been known as the alignments of ionic impurities or polymer chains. In this paper, we applied EA to thermally evaporated organic diodes which not have ionic impurities or polymer chains. After EA, the turn-on voltage of the diode was reduced, and the forward-bias current of the diode was increased without changing the reverse-bias current, resulting in an improvement of the cutoff frequency of the rectifier. In addition, we proposed a new mechanism to explain why the EA can be applied to the thermally evaporated organic devices. Based on time-of-flight secondary ion mass spectrometry and impedance spectra, we suggest that this improvement is due to the creation of a MoO3:pentacene mixed layer, leading to ease of charge injection. We believe that our finding will be helpful to understand change at the organic/metal interfaces and useful to apply a wide range of organic devices such as organic photovoltaics, organic light-emitting diodes, and organic thin-film transistors.

This work investigates the electrochemical intercalation of Ca2+ ions into TiS2 in organic electrolytes at room temperature and demonstrates that successful intercalation/de-intercalation can be achieved using a 0.1 M solution of Ca(CF3SO3)2 in propylene carbonate (PC) as an electrolyte. Additionally, further performance (charge/discharge capacity, reversibility, and hysteresis) enhancement is observed when a 0.1 M solution of Ca(CF3SO3)2 in a 1:10 (mol/mol) mixture of PC and dimethyl carbonate (DMC) is employed, which is ascribed to the modulation of the solvation environment of Ca2+ ions by the use of the relatively low-polar DMC. Finally, the structural changes in TiS2 caused by Ca2+ intercalation/de-intercalation during charge/discharge are probed by in situ X-ray diffraction analysis. Keywords: Calcium-ion batteries, TiS2 electrode, Organic electrolyte, In situ X-ray diffraction analysis

Despite the increasing number of foreign seafarers working in the Korean shipping industry and the growing concern for psycho-emotional stress due to discrimination in the maritime sector, few studies have focused on the working environment of foreign seafarers on South Korean vessels. This study aimed to determine whether foreign seafarers perceived discrimination in the Korean shipping industry and if so, the types of discrimination they faced and how they responded to this challenge. A survey was conducted to assess foreign seafarers’ experiences of discrimination, understanding of their own human rights, and level of satisfaction in working with Korean seafarers as well as identifying positive factors. The main positive findings included the kindness of colleagues, and excellent welfare facilities and benefits; whilst the most frequently reported negative factors related to language barriers and food types. These findings can be used to identify and share best practices and help determine priority areas for action. However, as the number of participants was small due to difficulties in contacting foreign seafarers during COVID-19 restrictions, further research is necessary to understand and improve the working environment of foreign seafarers on South Korean vessels.

Maritime Autonomous Surface Ships (MASS), an emerging area of digital advancement in shipping and shipbuilding industries, presents a different legal paradigm from that of existing ships. Existing maritime-related industries, including shipping, shipbuilding, and logistics, based on large hardware called ships, are rapidly changing into highly autonomous software-centered structures. This study is focused on analyzing the legal issues in preparation for MASS’ commercial operations in the future by applying comparative methods centered on the Republic of Korea and the United Kingdom. The study’s results contribute to the criteria for the manufacturing responsibility of autonomous ship-embedded software and a desirable legal policy improvement plan. Various legal issues and macro legal policy directions related to software product liability were identified. The study also presents concrete implementation strategies to achieve an ideological harmony and a balance between equitable damage relief and the advancement of related technologies to ensure maritime safety in the maritime industry. Based on the issues identified and their legal policy alternatives, it is hoped that the institutional ideal of product liability, which promotes technological advancement and protects consumer rights, is realized in the software domain as well.

The goal of this study was to measure the mechanical properties of porcine brain tissue and determine if they were dependent on anatomical region or direction. Multistep stress relaxation indentations with a cylindrical probe were performed at 10, 20, and 30% nominal strain on multiple regions in the sagittal, horizontal, and coronal planes. Linear and nonlinear (using the quasilinear theory of viscoelasticity [QLV]) constitutive formulations were applied to extract parameters to capture the mechanical behavior of brain tissue. The linear viscoelastic analytic approach provided the best fit to the experimental data of the models tested. Within each directional plane there were region-dependent differences. The cerebellum was the softest region within each loading direction. Although the majority of the regions were isotropic, the cerebellum white matter and thalamus were anisotropic. The characterization of these mechanical properties can be used to inform finite element models of the pig brain to help predict a more biofidelic response in animal models of traumatic brain injury. Statement of Significance: Finite element models been developed to predict brain tissue response to traumatic brain injury (TBI) to advance protective and preventative strategies. In order to improve the accuracy of these computational models, appropriate mechanical experimentation is required to identify brain viscoelasticity, heterogeneity, and anisotropy. Our custom indentation design allows for high spatial resolution to characterize mechanical properties based on anatomical region and loading direction. Due to the challenges in procuring human brain tissue, porcine brain models are a suitable substitute to study TBI based on its structural similarities to that of human brains. This study will further illuminate the complexity of brain tissue mechanics in response to injury loading.

The reaction kinetics of electrochemical lithiation/delithiation in a composite consisting of black phosphorus and cup-stacked carbon nanotube (BP-CSCNT) were investigated. Two semicircles were observed in Nyquist plots at the high and low frequency regions, which were attributed to the resistance of lithium-ion transport through the surface film and the resistance of the alloying/dealloying reaction (charge-transfer resistance), respectively. The activation energy using the charge transfer reaction was evaluated from the temperature-dependence of the interfacial conductivity. Even with the use of ethylene carbonate-based and propylene carbonate electrolytes, the activation energy was calculated to be 25–26 kJ mol−1, which is much smaller than that obtained with graphite electrodes and cathode materials. These results indicate that the ionic charge transfer process in BP-CSCNT composite electrodes is not coupled with the desolvation process and suggest that the charge transfer in BP-CSCNT is exceptionally fast compared to that in other insertion materials.

Abstract Background Porcine reproductive and respiratory syndrome virus (PRRSV) causes devastating disease characterized by reproductive failure and respiratory problems in the swine industry. To understand the recent prevalence and genetic diversity of field PRRSVs in the Republic of Korea, open reading frames (ORFs) 5 and 7 of PRRSV field isolates from 631 PRRS-affected swine farms nationwide in 2013–2016 were analyzed along with 200 Korean field viruses isolated in 2003–2010, and 113 foreign field and vaccine strains. Results Korean swine farms were widely infected with PRRSVs of a single type (38.4 and 37.4% for Type 1 and Type 2 PRRSV, respectively) or both types (24.2%) with up to approximately 83% nucleotide sequence similarity to prototype PRRSVs (Lelystad or VR2332). Phylogenetic analysis based on the ORF5 nucleotide sequence revealed that Korean Type 1 field isolates were classified as subgroups A, B, and C under subtype 1, while Korean Type 2 field isolates were classified as lineages 1 and 5 as well as three Korean lineages (kor A, B, and C) with the highest infection prevalence in subgroup A (50.5%) and lineage 5 (15.3%) for Type 1 and Type 2 PRRSV, respectively, among ORF5-positive farms. In particular, the lineages kor B and C were identified as novel lineages in this study, and lineage kor B comprised only the field viruses isolated from Gyeongnam Province in 2014–2015, establishing regionally unique genetic characteristics. It has also recently been confirmed that commercialized vaccine-like viruses (subgroup C) of Type 1 PRRSV and NADC30-like viruses of Type 2 PRRSV (lineage 1) are spreading rapidly in Korean swine farms. The Korean field viruses were also expected to be antigenically variable as shown in the high diversity of neutralizing epitopes and N-glycosylation sites. Conclusions This up-to-date information regarding recent field PRRSVs should be taken into consideration when creating strategies for the application of PRRS control measures, including vaccination in the field.

Porcine epidemic diarrhea virus (PEDV) has negatively affected the welfare of animals and their productivity in South Korea for three decades. A shortage of effective control measures has led to the virus becoming endemic in domestic pig populations. This study aimed to describe how our intervention measures were implemented for PEDV elimination in an enzootically infected farm. We operated a risk assessment model of PEDV recurrence to obtain information about the virus itself, herd immunity, virus circulation, and biosecurity at the farm. Next, we conducted a four-pillar-based two-track strategy to heighten sow immunity and eradicate the virus, with longitudinal monitoring of immunity and virus circulation, involving strict biosecurity, prime-boost pre-farrow L/K/K immunization, all-in-all-out and disinfection practices in farrowing houses, and disinfection and gilt management in wean-to-finish barns. In particular, we observed a high prevalence and long-term survival of PEDV in slurries, posing a critical challenge to PED eradication and highlighting the necessity for consecutive testing of barn slurry samples and for the management of infected manure to control PEDV. Genetic analysis of PEDVs in this farm indicated that genetic drift continued in the spike gene, with a substitution rate of 1.683 × 10−4 substitutions/site/year. Our study underlines the need for active monitoring and surveillance of PEDV in herds and their environments, along with the coordinated means, to eliminate the virus and maintain a negative herd. The tools described in this study will serve as a framework for regional and national PED eradication programs.

Organic solar cells (OSCs) are an attractive technique for next-generation renewable energy. However, the intrinsically unstable nature of the organic compounds involved is delaying their commercialization. Therefore, it is essential to improve the lifetime of OSCs significantly. Here, we investigated the effect of the hydrophobic cyclized transparent optical polymer (CYTOP) as a solution-processable encapsulation layer based on shelf lifetime measurement, current–voltage characteristics, and impedance spectroscopy. We found that CYTOP utilization greatly enhanced OSCs’ shelf lifetime, maintaining 96% of initial performance when unencapsulated devices decreased to 82%. Furthermore, based on the dark current characteristics, ideality factor (n), and Cole–Cole plots, the CYTOP encapsulation is revealed to effectively inhibit unfavorable changes of parasitic resistive components and trap-assisted recombination. These findings provide an inclusive perspective on the shelf lifetime issue and commercialization of the OSCs.

To increase the quality of recycling, a new demolition technique is required that can work in parallel with existing crushing methods, which use large equipment with high crushing efficiency. Moreover, the efficient collection of the remains from the fractional dismantling method needs to be considered based on its procedure, and the technology for partial dismantling that is efficient in remodeling, maintenance, and reinforcement has to be developed. In this study, the temperature-increasing characteristics of rebars inside ferroconcrete with respect to their arrangement was investigated by partial rapid heating through high-frequency induction heating. Based on this, the chemical and physical vulnerability characteristics of ferroconcrete due to the thermal conduction generated on the rebar surface and the cracks caused by the thermal expansion pressure of the rebar were verified. In addition, the objective of this study was to verify the applicability of the technology by specifying the vulnerability range of ferroconcrete based on the heating range with adequate consumption of energy.

Weldments inevitably shrink during cooling from the melt pool. Residual stresses then occur owing to surrounding constraints. Tensile residual stresses in weldments cause various problems, such as deformation and reduction of fatigue strength. Low-temperature transformation (LTT) welding consumables can reduce the tensile residual stress through volume expansion, which accompanies a phase transformation from austenite to martensite. In this study, the relationship between residual stress and net strain was examined, mainly by controlling the martensite start (Ms) temperature, and the result was related to the weld’s microstructure. The Ms temperature and the expansion accompanying the phase transformation were analyzed by the dilatometric method. A hole drilling test was carried out to measure the residual stress in the weldments. The highest compressive stress was observed in the most expanded weldment at room temperature, and a linear relationship between the net strain and residual stress was derived. This linear relationship was analyzed with a microstructural approach.

The use of high-tension bars to strengthen flexural members is gaining increasing interest. However, the applicability of current standards to such bars is uncertain, because there may not be a definite yield strength and it may be unclear whether the tensile or compressive failure mode dominates. Determining the balanced–destruction steel ratio is particularly difficult. We measure the bending behaviour of flexural members containing high-tension bars with different yield strengths and tensile steel ratios. We conclude that the maximum-steel-ratio regulation and nominal -strength equation in the current standard remain applicable.

To improve recycling quality, it is necessary to develop a demolition technology that can be combined with existing crushing methods that employ large shredding-efficient equipment. The efficient collection of bones in a segmentation dismantling method must be considered according to the procedure. Furthermore, there is a need for the development of partial dismantling technologies that enable efficient remodeling, maintenance, and reinforcement. In this study, we experimentally investigated the temperature-rise characteristics of reinforced concrete through partial rapid heating during high-frequency induced heating. Accordingly, the chemical and physical vulnerability characteristics of the reinforced concrete were verified by studying the thermal conduction on the surface of the rebars and the cracks caused by the thermal expansion pressure of the rebars. Furthermore, we aimed to verify the applicability of the proposed technology by specifying the vulnerability range of the reinforced concrete based on the heating range, as well as the appropriate energy consumption. We investigated the temperature rise and temperature distribution characteristics of the rebar surfaces based on diameter, length, bar placement conditions, heating distance, heating coil location, and output, using reinforced steel of grade SD345. Maximum powers of 5, 6, and 10 kW, and inductive heating were used to achieve satisfactory results.

Standing column well (SCW) geothermal heat exchanger permits a bleeding discharge of less than 20% in the event of a maximum load, which is an inappropriate method of using underground water. In this study, the existing operational method of two adjacent SCW geothermal heat exchangers, each with a single well, was modified. This technology aims to improve the coefficient of performance (COP) of the geothermal system by fundamentally preventing underground water discharge and maintaining a constant temperature of the underground heat exchanger. To curb the bleed water discharge, two balancing wells of cross-mixing methods were employed. The result of the cooling and heating operations with the existing SCW heat exchange system and the balancing well cross-combined heat exchange system showed that the measured COP increases by 23% and 12% during the cooling and heating operations, respectively. When operating with a balanced well cross-mixed heat exchange system, the initial temperature of the underground was constant with a small standard deviation of 0.08–0.12 °C.

Exhaust gases from ships and automobiles have a significant impact on people and the environment. As a result, diesel engines used in land and marine vehicles are gradually being restricted, and low-carbon engines are under development. This study considers marine diesel oil (MDO) that is used in ships to meet the emission regulations required by the International Maritime Organization. This investigation explores the method and application technology for the reduction of nitrogen oxides (NOx) and particulate matter using emulsified fuel and mass-produced dimethyl ether (DME) fuel, which are analyzed. When comparing emulsified fuel and DME fuel to MDO, which is a ship oil, NOx are reduced by 20–45% and the particulate matter is reduced by 60–97%. When emulsified fuel containing moisture is used, the combustion chamber temperature is lowered due to the optimal expansion by moisture contained in the fuel. The particulate matter is also reduced. When DME fuel is used, it reduces the particulate matter by more than 97% in comparison with the existing MDO fuel and the emulsified fuel. The conditions are believed to be suitable for combustion and they can be satisfied by supplying oxygen during post-combustion.

As concerns regarding environmental pollution, energy security and future oil supply continue to grow, communities around the world are looking for non-petroleum-based alternative fuels along with advanced energy technologies (e.g., fuel cells) to increase energy use efficiency. Compared with the main alternative fuel candidates (e.g., methane, methanol, ethanol and Fischer–Tropsch fuels), dimethyl ether (DME) seems to have a significant potential to solve the aforementioned problems and can be used as a clean, high-efficiency compressed ignition fuel with reduced nitrogen oxide, sulphur oxide and particulate matter (PM) emissions. In this study, the results of experiments using a ship engine and numerical analysis were verified using AVL BOOST software. Based on these verifications, nitrogen oxide and PM reduction characteristics were numerically analysed by controlling the diameter and spraying time of the fuel nozzle, which is the fuel injection system of a marine engine. When DME fuel was used, nitrogen oxide and PM emissions were reduced by 40% and 90%, respectively, compared with marine diesel oil fuel. To prove the viability of DME as an alternative fuel, combustion and exhaust characteristics were analysed in accordance with injection timing and the variation of nozzle hole.

In this study, a mobile measuring device was developed and a thermal response test that applied a standing column well-type heat exchanger was conducted to obtain design parameters from field measurements. The main purpose of this study was to investigate the effects of thermal conductivity and geothermal resistance on site, including the flow and effects of natural convection of groundwater in boreholes. We compared, analyzed, and investigated the effective thermal conductivity of a borehole heat exchanger system and the effective thermal conductivity that was not applied when bleeding single-well standing column wells (SCWs), which is called an open-type standing column well geothermal heat exchanger system. We also investigated the heat transfer characteristics during the bleeding of two-well type SCWs, where water is injected from one clearing hole to the returning hole depending on the bleeding rate. Artificial recharging was used to inject the change of thermal conductivity from the bleeding rate of a geothermal heat exchanger into another SCW type. From the comparison results of the thermal conductivity of the multi-well and single-well underground heat exchangers, four times higher efficiency than the single-well was obtained. The reason for this is considered to be energy utilization utilizing groundwater energy.

The need for high-throughput screening has led to the miniaturization of the reaction volume of the chamber in bioassays. As the reactor gets smaller, surface tension dominates the gravitational or inertial force, and mixing efficiency decreases in small-scale reactions. Because passive mixing by simple diffusion in tens of microliter-scale volumes takes a long time, active mixing is needed. Here, we report an efficient micromixing method using magnetically rotating microparticles with patterned magnetization induced by magnetic nanoparticle chains. Because the microparticles have magnetization patterning due to fabrication with magnetic nanoparticle chains, the microparticles can rotate along the external rotating magnetic field, causing micromixing. We validated the reaction efficiency by comparing this micromixing method with other mixing methods such as simple diffusion and the use of a rocking shaker at various working volumes. This method has the potential to be widely utilized in suspension assay technology as an efficient mixing strategy.

The characteristics of black carbon and nitrogen oxide reduction versus the water content of emulsion fuel were studied by numerical methods, and a method of reducing fuel consumption was achieved by adjusting the turbocharger compression ratio. The results of the combustion period characteristics, versus the three types of emulsion fuel and the turbocharger compression ratios, shows that the combustion period is shortened in the order of CR00 > CR01 > CR02 > CR03, according to the compression ratio of the turbocharger. As the fuel water content increases, the combustion period is shortened in the order of EMDO16 < EMDO13 < EMDO10. The nitrogen oxide and black carbon reduction was because the combustion period increased, with increasing compression ratio, while the combustion period was shortened, with increasing moisture content of emulsion fuel. This also caused is an increase in the combustion pressure and a shortening of the combustion period, due to the expansion of the volume, in turn due to the micro-explosion of water. This may be due to the shortening of the post combustion period and the reduction of black carbon emissions. In addition, combustion was accelerated in the order—CR00 > CR01> CR02> CR03. By optimizing the water content of the emulsion fuel and turbocharger compression ratio, while considering the exhaust emission and combustion state, reduction of the fuel consumption rate and output improvement are shown.