Development of radical initiator based on o-imino-isourea capable of photo/thermal polymerization

Using o-imino isourea, three photo- and thermal dual-responsive radical initiators dicyheDCC, CyheDCC, and BnDCC were systematically developed and synthesized. By adding an aromatic ring to the free radical initiators, the ultraviolet-visible absorption was redshifted, and the absorption coefficient was increased. Compared with other initiators, BnphDCC exhibited an exceptional photoinitiation rate under photo-differential scanning calorimetry (DSC) and a high absorption coefficient (ε = 15 420 M-1 cm-1). Therefore, it is an appropriate potential photoinitiator. DicyheDCC, which was composed of a cyclic hydrocarbon, exhibited rapid thermal initiation (Tpeak = 82 °C) during thermal DSC, making it a valuable thermal radical initiator. Because of the low stiffness of the N-O link in radical initiators, density functional theory predicts that the aliphatic ring has a significantly lower enthalpy than the aromatic ring. Moreover, in this study, CyhephDCC and BnphDCC, as dual-responsive radical initiators, indicated the potential for a photo- and heat dual-curing system through the universal free-radical polymerization of acrylates. These significant discoveries may be useful for developing efficient and diversified polymer network systems that require synergistic photo- and thermal effects.

CNN-Based Facial Expression Recognition with Simultaneous Consideration of Inter-Class and Intra-Class Variations

Facial expression recognition is crucial for understanding human emotions and nonverbal communication. With the growing prevalence of facial recognition technology and its various applications, accurate and efficient facial expression recognition has become a significant research area. However, most previous methods have focused on designing unique deep-learning architectures while overlooking the loss function. This study presents a new loss function that allows simultaneous consideration of inter- and intra-class variations to be applied to CNN architecture for facial expression recognition. More concretely, this loss function reduces the intra-class variations by minimizing the distances between the deep features and their corresponding class centers. It also increases the inter-class variations by maximizing the distances between deep features and their non-corresponding class centers, and the distances between different class centers. Numerical results from several benchmark facial expression databases, such as Cohn-Kanade Plus, Oulu-Casia, MMI, and FER2013, are provided to prove the capability of the proposed loss function compared with existing ones.

Personal exposure of PM2.5 and metabolic syndrome markers of pregnant women in South Korea: APPO study

We examined the association between exposure to PM2.5, focused on individual exposure level, and metabolic dysfunction during pregnancy. APPO study (Air Pollution on Pregnancy Outcome) was a prospective, multicenter, observational cohort study conducted from January 2021 to March 2023. Individual PM2.5 concentrations were calculated using a time-weighted average model. Metabolic dysfunction during pregnancy was assessed based on a modified definition of metabolic syndrome and its components, accounting for pregnancy-specific criteria. Exposure to PM2.5 during pregnancy was associated with worsened metabolic parameters especially glucose metabolism. In comparison to participants exposed to the low PM2.5 group, those exposed to high PM2.5 levels exhibited increased odds of gestational diabetes mellitus (GDM) after adjusting for confounding variables in different adjusted models. Specifically, in model 1, the adjusted odds ratio (aOR) was 3.117 with a 95% confidence interval (CI) of 1.234-7.870; in model 2, the aOR was 3.855 with a 95% CI of 1.255-11.844; in model 3, the aOR was 3.404 with a 95% CI of 1.206-9.607; and in model 4, the aOR was 2.741 with a 95% CI of 0.712-10.547. Exposure to higher levels of PM2.5 during pregnancy was associated with a tendency to worsen metabolic dysfunction markers specifically in glucose homeostasis. Further research is needed to investigate the mechanisms underlying the effects of ambient PM2.5 on metabolic dysfunction during pregnancy.

Assessing Stress and Anxiety in Firefighters During the Coronavirus Disease-2019 Pandemic: A Comparative Adaptation of the Stress and Anxiety in the Viral Epidemic-9 Items and Stress and Anxiety in the Viral Epidemics-6 Items Scales

OBJECTIVE

This study assessed the reliability and validity of the Stress and Anxiety to Viral Epidemics-9 items (SAVE-9) and Stress and Anxiety to Viral Epidemics-6 items (SAVE-6) scales for measuring viral anxiety among firefighters during the coronavirus disease-2019 pandemic.

METHODS

An online survey was conducted among 304 firefighters assigned in Gyeonggi-do. The SAVE-9 scale, initially developed for healthcare workers, was adapted for firefighters. We compared it with the SAVE-6 scale designed for the general population among the firefighters sample. The confirmatory factor analysis (CFA) was conducted to explore the factor structure of both scales. Internal consistency reliability was checked using Cronbach's alpha and McDonald's omega. Convergent validity was assessed in accordance with the Patient Health Questionnaire-9 and Generalized Anxiety Disorder-7 scales.

RESULTS

The SAVE-9 scale demonstrated a Cronbach alpha of 0.880, while the SAVE-6 scale yielded an alpha of 0.874. CFA indicated good model fits for both SAVE-9 and SAVE-6 scales among firefighters sample. The SAVE-9 and SAVE-6 comparably measures viral anxiety of firefighters.

CONCLUSION

Both of the SAVE-9 and SAVE-6 scales are reliable and valid instruments for assessing viral anxiety among firefighters during the pandemic.

The Influence of Styrene Content in Solution Styrene Butadiene Rubber on Silica-Filled Tire Tread Compounds

In tire tread applications, achieving enhanced abrasion resistance, wet grip, and rolling resistance is crucial for optimizing overall performance. To realize improvements in these attributes for silica-filled tire tread compounds, it becomes imperative to improve the dispersity of silica filler by investigating the effect of each component in the tire tread compound. In this work, we study the effect of styrene content within solution styrene butadiene rubber (SSBR) on the properties of tire tread compounds. A higher styrene segment within SSBR contributes to increased silica dispersion and crosslink density. Thus, tire tread compounds featuring SSBR with increased styrene content not only improve physical and mechanical properties, but also enhance major characteristics tailored for tire tread applications. These findings provide valuable insights into advancing the reinforced performance of tire tread compounds through the strategic utilization of SSBR enriched in styrene content.

Improving Depression Severity Prediction from Passive Sensing: Symptom-Profiling Approach

Depression is a significant mental health issue that profoundly impacts people's lives. Diagnosing depression often involves interviews with mental health professionals and surveys, which can become cumbersome when administered continuously. Digital phenotyping offers an innovative approach for detecting and monitoring depression without requiring active user involvement. This study contributes to the detection of depression severity and depressive symptoms using mobile devices. Our proposed approach aims to distinguish between different patterns of depression and improve prediction accuracy. We conducted an experiment involving 381 participants over a period of at least three months, during which we collected comprehensive passive sensor data and Patient Health Questionnaire (PHQ-9) self-reports. To enhance the accuracy of predicting depression severity levels (classified as none/mild, moderate, or severe), we introduce a novel approach called symptom profiling. The symptom profile vector represents nine depressive symptoms and indicates both the probability of each symptom being present and its significance for an individual. We evaluated the effectiveness of the symptom-profiling method by comparing the F1 score achieved using sensor data features as inputs to machine learning models with the F1 score obtained using the symptom profile vectors as inputs. Our findings demonstrate that symptom profiling improves the F1 score by up to 0.09, with an average improvement of 0.05, resulting in a depression severity prediction with an F1 score as high as 0.86.

Effect of Particulate Matter 2.5 on Fetal Growth in Male and Preterm Infants through Oxidative Stress

Particulate matter 2.5 (PM2.5) levels are associated with adverse pregnancy outcomes. In this retrospective cohort study, we examined whether the concentration of indoor PM2.5 affected pregnancy outcomes. Additionally, we evaluated biomarkers of pregnancy-related complications caused by fine dust. We collected clinical information and data based on residential addresses from the Air Korea database to assess PM2.5 exposure levels. As a multicenter prospective cohort study, we measured the indoor PM2.5 concentration and inflammatory and oxidative stress markers. The PM2.5 concentration of the low-birth-weight (LBW) delivery group was 27.21 μg/m3, which was significantly higher than that of the normal-birth-weight (NBW) group (26.23 μg/m3) (p = 0.02). When the newborns were divided by sex, the PM2.5 concentration of the LBW group was 27.89 μg/m3 in male infants, which was significantly higher than that of the NBW group (26.26 μg/m3) (p = 0.01). In the prospective study, 8-hydroxy-2-deoxyguanosine significantly increased in the high-concentration group (113.55 ng/mL, compared with 92.20 ng/mL in the low-concentration group); in the high-concentration group, the rates of preterm birth (PTB) and small size for gestational age significantly increased (p < 0.01, p = 0.01). This study showed an association between PM2.5, oxidative stress, and fetal growth, with the PTB group being more vulnerable.

Enhancing Performance of Ultraviolet C Photodetectors Through Single-Domain Epitaxy of Monoclinic β-Ga2 O3 Films and Tailored Anti-Reflection Coating

Implementing high-performance ultraviolet C photodetectors (UVC PDs) based on β-Ga2 O3 films is challenging owing to the anisotropic crystal symmetry between the epitaxial films and substrates. In this study, highly enhanced state-of-the-art photoelectrical performance is achieved using single-domain epitaxy of monoclinic β-Ga2 O3 films on a hexagonal sapphire substrate. Unlike 3D β-Ga2 O3 films with twin domains, 2D β-Ga2 O3 films exhibit a single domain with a smooth surface and low concentration of point defects, which enable efficient charge separation by suppressing boundary-induced recombination. Furthermore, a tailored anti-reflection coating (ARC) is adopted as a light-absorbing medium to improve charge generation. The tailored nanostructure, which features a gradient refractive index, not only substantially reduces the reflection, but also suppresses the surface leakage current as a passivation layer. This study provides fundamental insights into the single-domain epitaxy of β-Ga2 O3 films and the application of ARC for the development of high-performance UVC PDs.

Polyether-based waterborne synergists: effect of polymer topologies on pigment dispersion

Control of polymer topologies is essential to determine their unique physical properties and potential applications. The polymer topologies can have a critical effect on pigment dispersion owing to their unique architectures; however, studies using polymer topologies on pigment dispersion in aqueous systems are scarce. Thus, this study proposes various topologies of polyether-based waterborne synergists, such as linear, hyperbranched, and branched cyclic structures. Specifically, we applied branched types of polyglycidols (PGs) as a synergist to provide polymer topology-dependent dispersibility for the surface-modification of Red 170 particles through adsorption and steric hindrance. The topology-controlled PG synergists (PGSs) were successfully prepared by post-polymerization modification with phthalimide and benzoyl groups. Particularly, the branched types of PGSs, branched cyclic PGS (bc-PGS), and hyperbranched PGS (hb-PGS) exhibited improved dispersibility through adsorption on top of the pigment, interaction between dispersant (BYK 190) and pigment, and steric effect. Surprisingly, hb-PGS conferred the Red 170 pigment particles with superior storage stability than that of bc-PGS despite their similar structural features. This study suggests the widespread potential application of PGSs as waterborne synergists for various dispersion applications.

Largely deformable torsional soft morphing actuator created by twisted shape memory alloy wire and its application to a soft morphing wing

We present a new type of torsional soft morphing actuator designed and fabricated by twisted shape memory alloy (SMA) wires embedded in polydimethylsiloxane matrix. The design and fabrication process of the proposed soft morphing actuator are presented with investigations of its working mechanism. Actuation performance was evaluated with respect to the temporal response, the maximum torsional deformation under an applied electric current, and various design parameters including the twist direction, wire diameter, helical pitch of the SMA wire, and the actuator's thickness and length. We demonstrate potential applications of the proposed soft morphing actuator as a soft morphing wing and airfoil. The proposed actuator will aid in the development of soft actuators, soft robotics, and other relevant scientific and engineering applications.

Fine conductive line printing of high viscosity CuO ink using near field electrospinning (NFES)

Modern printed electronics applications require patterning of fine conductive lines of sufficient thickness. However, the two requirements for pattern width and thickness are a trade-off. To print fine pattern at a micrometer size, the nozzle diameter must be approximately the size of the pattern width, so only low-viscosity inks are used. As a result, the pattern is likely to be very thin and multiple overlapping printing is required for sufficient conductance. In order to use high viscosity ink for fine patterning, near field electrospinning (NFES) is attracting attention because it can print very thin and thick patterns using large nozzles (high-viscosity ink). Until now, silver paste ink has been used for microconductive patterning using electrospinning. However, Ag nanoparticle (NP) inks are expensive. In this study, we report the use of a relatively inexpensive CuO NP ink for electrospinning-based printing. For implementation, the material preparation, printing and post-processing process are discussed. For post-processing, a continuous wave (CW) green laser with a 532 nm wavelength was used to reduce the CuO to Cu and sinter the nanoparticles. After sintering, the 50 μm width and 1.48 μm thick Cu conductive line exhibited a resistivity of 5.46 μΩ·cm, which is 3.25 times of the bulk resistivity of Cu.

Analysis of Mechanical Properties and Structural Analysis According to the Multi-Layered Structure of Polyethylene-Based Self-Reinforced Composites

In this research, a self-reinforced composite material was manufactured using a single polyethylene material, and this self-reinforced composite material has excellent recyclability and is environmentally friendly compared to composite materials composed of other types of material, such as glass fiber reinforced composites (GFRP) and carbon fiber reinforced composites (CFRP). In this research, the manufactured self-reinforced composite material consists of an outer layer and an inner layer. To manufacture the outer layer, low density polyethylene (LDPE) films were laminated on high density polyethylene (HDPE) fabrics and knitted fabrics, and composite materials were prepared at various temperatures using hot stamping. A 3D printing process was utilized to manufacture the inner layer. After designing a structure with a cross-sectional shape of a triangle, circle, or hexagon, the inner layer structure was manufactured by 3D printing high-density polyethylene material. As an adhesive film for bonding the outer layer and the inner layer, a polyethylene-based self-reinforced composite material was prepared using a low-density polyethylene material. Input data for simulation of self-reinforced composite materials were obtained through tensile property analysis using a universal testing machine (UTM, Shimadzu, Kyoto, Japan), and the physical property values derived as output data and actual experimental values were obtained. As a result of the comparison, the error rate between simulation data and experimental data was 5.4% when the shape of the inner layer of self-reinforced composite material was a hexagon, 3.6% when it was a circle, and 7.8% when a triangular shape showed the highest value. Simulation in a virtual space can reduce the time and cost required for actual research and can be important data for producing high-quality products.

Practical Approach for Determining Material Parameters When Predicting Austenite Grain Growth under Isothermal Heat Treatment

An investigation of austenite grain growth (AGG) during the isothermal heat treatment of low-alloy steel is conducted. The goal is to uncover the effect of time, temperature, and initial grain size on SA508-III steel grain growth. Understanding this relationship enables the optimization of the time and temperature of the heat treatment to achieve the desired grain size in the studied steel. A modified Arrhenius model is used to model austenite grain size (AGS) growth distributions. With this model, it is possible to predict how grain size will change depending on heat treatment conditions. Then, the generalized reduced gradient (GRG) optimization method is employed under adiabatic conditions to characterize the model's parameters, providing a more precise solution than traditional methods. With optimal model parameters, predicted AGS agree well with measured values. The model shows that AGS increases faster as temperature and time increase. Similarly, grain size grows directly in proportion to the initial grain size. The optimized parameters are then applied to a practical case study with a similar specimen size and material properties, demonstrating that our approach can efficiently and accurately predict AGS growth via GRG optimization.

Injectable biocompatible nanocomposites of Prussian blue nanoparticles and bacterial cellulose as a safe and effective photothermal cancer therapy

Photothermal therapy (PTT) is a novel cancer treatment using a photoabsorber to cause hyperthermia to kill tumors by laser irradiation. Prussian blue nanoparticles (PB NPs) are considered as next-generation photothermal agents due to the facile synthesis and excellent absorption of near-infrared light. Although PB NPs demonstrate remarkable PTT capabilities, their clinical application is limited due to their systemic toxicity. Bacterial cellulose (BC) has been applied to various bio-applications based on its unique properties and biocompatibility. Herein, we design composites with PB NPs and BC as an injectable, highly biocompatible PTT agent (IBC-PB composites). Injectable bacterial cellulose (IBC) is produced through the trituration of BC, with PB NPs synthesized on the IBC surface to prepare IBC-PB composites. IBC-PB composites show in vitro and in vivo photothermal therapeutic effects similar to those of PB NPs but with significantly greater biocompatibility. Specifically, in vitro therapeutic index of IBC-PB composites is 26.5-fold higher than that of PB NPs. Furthermore, unlike PB NPs, IBC-PB composites exhibit no overt toxicity in mice as assessed by blood biochemical analysis and histological images. Hence, it is worth pursuing further research and development of IBC-PB composites as they hold promise as safe and efficacious PTT agents for clinical application.

Sustainable Strategies for Synthesizing Lignin-Incorporated Bio-Based Waterborne Polyurethane with Tunable Characteristics

In this study, we introduce a novel approach for synthesizing lignin-incorporated castor-oil-based cationic waterborne polyurethane (CWPU-LX), diverging significantly from conventional waterborne polyurethane dispersion synthesis methods. Our innovative method efficiently reduces the required solvent quantity for CWPU-LX synthesis to approximately 50% of that employed in traditional WBPU experimental procedures. By incorporating lignin into the polyurethane matrix using this efficient and reduced-solvent method, CWPU-LX demonstrates enhanced properties, rendering it a promising material for diverse applications. Dynamic interactions between lignin and polyurethane molecules contribute to improved mechanical properties, enhanced thermal stability, and increased solvent resistance. Dynamic interactions between lignin and polyurethane molecules contribute to improved tensile strength, up to 250% compared to CWPU samples. Furthermore, the inclusion of lignin enhanced thermal stability, showcasing a 4.6% increase in thermal decomposition temperature compared to conventional samples and increased solvent resistance to ethanol. Moreover, CWPU-LX exhibits desirable characteristics such as protection against ultraviolet light and antibacterial properties. These unique properties can be attributed to the presence of the polyphenolic group and the three-dimensional structure of lignin, further highlighting the versatility and potential of this material in various application domains. The integration of lignin, a renewable and abundant resource, into CWPU-LX exemplifies the commitment to environmentally conscious practices and underscores the significance of greener materials in achieving a more sustainable future.

Steerable and Agile Light-Fueled Rolling Locomotors by Curvature-Engineered Torsional Torque

On-demand photo-steerable amphibious rolling motions are generated by the structural engineering of monolithic soft locomotors. Photo-morphogenesis of azobenzene-functionalized liquid crystal polymer networks (azo-LCNs) is designed from spiral ribbon to helicoid helices, employing a 270° super-twisted nematic molecular geometry with aspect ratio variations of azo-LCN strips. Unlike the intermittent and biased rolling of spiral ribbon azo-LCNs with center-of-mass shifting, the axial torsional torque of helicoid azo-LCNs enables continuous and straight rolling at high rotation rates (≈720 rpm). Furthermore, center-tapered helicoid structures with wide edges are introduced for effectively accelerating photo-motilities while maintaining directional controllability. Irrespective of surface conditions, the photo-induced rotational torque of center-tapered helicoid azo-LCNs can be transferred to interacting surfaces, as manifested by steep slope climbing and paddle-like swimming multimodal motilities. Finally, the authors demonstrate continuous curvilinear guidance of soft locomotors, bypassing obstacles and reaching desired destinations through real-time on-demand photo-steering.

Fluorometric Detection of SARS-CoV-2 Single-Nucleotide Variant L452R Using Ligation-Based Isothermal Gene Amplification

Since the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant was first discovered, several variants showing different infectivity and immune responses have emerged globally. As the conventional method, whole-genome sequencing following polymerase chain reaction (PCR) is currently used for diagnosis of SARS-CoV-2 mutations. However, these conventional PCR-based direct DNA sequencing methods are time-consuming, complicated, and require expensive DNA sequencing modules. Here, we developed a fluorometric method for the accurate detection of a single missense mutation of U to G in the spike (S) gene that changes leucine to arginine (L452R) in SARS-CoV-2 genomic RNA. Our method for the detection of single-nucleotide mutations (SNM) in the viral RNA genome includes RNA sequence-dependent DNA ligation and tandem isothermal gene amplification methods, such as strand displacement amplification (SDA) and rolling circle amplification (RCA) generating G-quadruplex (GQ). In the presence of SNM in the viral RNA, ligation of both ends of the probe DNAs occurs between 5'-phosphorylated hairpin DNA and linear probe DNA that can discriminate a single base mismatch. The ligated DNAs were then extended to generate long-stem hairpin DNAs that are subjected to the first isothermal gene amplification (SDA). SDA produces multitudes of short ssDNA from the long-stem hairpin DNAs, which then serve as primers by annealing to circular padlock DNA for the second isothermal gene amplification (RCA). RCA produces a long stretch of ssDNA containing GQ structures. Thioflavin T (ThT) is then intercalated into GQ and emits green fluorescence, which allows the fluorometric identification of SARS-CoV-2 variants. This fluorometric analysis sensitively distinguished SNM in the L452R variant of SARS-CoV-2 RNA as low as 10 pM within 2 h. Hence, this fluorometric detection method using ligation-assisted tandem isothermal gene amplification can be applied for the diagnosis of SARS-CoV-2 SNM variants with high accuracy and sensitivity, without the need for cumbersome whole-genome DNA sequencing.

Cellular Efficacy of Fattigated Nanoparticles and Real-Time ROS Occurrence Using Microfluidic Hepatocarcinoma Chip System: Effect of Anticancer Drug Solubility and Shear Stress

The objective of this study was to evaluate the effectiveness of organ-on-chip system investigating simultaneous cellular efficacy and real-time reactive oxygen species (ROS) occurrence of anticancer drug-loaded nanoparticles (NPs) using hepatocarcinoma cells (HepG2) chip system under static and hepatomimicking shear stress conditions (5 dyne/cm2). Then, the role of hepatomimetic shear stress exposed to HepG2 and drug solubility were compared. The highly soluble doxorubicin (DOX) and poorly soluble paclitaxel (PTX) were chosen. Fattigated NPs (AONs) were formed via self-assembly of amphiphilic albumin (HSA)-oleic acid conjugate (AOC). Then, drug-loaded AONs (DOX-AON or PTX-AON) were exposed to a serum-free HepG2 medium at 37 °C and 5% carbon dioxide for 24 h using a real-time ROS sensor chip-based microfluidic system. The cellular efficacy and simultaneous ROS occurrence of free drugs and drug-loaded AONs were compared. The cellular efficacy of drug-loaded AONs varied in a dose-dependent manner and were consistently correlated with real-time of ROS occurrence. Drug-loaded AONs increased the intracellular fluorescence intensity and decreased the cellular efficacy compared to free drugs under dynamic conditions. The half-maximal inhibitory concentration (IC50) values of free DOX (13.4 μg/mL) and PTX (54.44 μg/mL) under static conditions decreased to 11.79 and 38.43 μg/mL, respectively, under dynamic conditions. Furthermore, DOX- and PTX-AONs showed highly decreased IC50 values of 5.613 and 21.86 μg/mL, respectively, as compared to free drugs under dynamic conditions. It was evident that cellular efficacy and real-time ROS occurrence were well-correlated and highly dependent on the drug-loaded nanostructure, drug solubility and physiological shear stress.

Role of Oxygen in Amorphous Carbon Hard Mask Plasma Etching

In the current and next-generation Si-based semiconductor manufacturing processes, amorphous carbon layer (ACL) hard masks are garnering considerable attention for high-aspect-ratio (HAR) etching due to their outstanding physical properties. However, a current limitation is the lack of research on the etching characteristics of ACL hard masks under plasma etching conditions. Given the significant impact of hard mask etching on device quality and performance, a deeper understanding of the etching characteristics of ACL is necessary. This study aims to investigate the role of oxygen in the etching characteristics of an ACL hard mask in a complex gas mixture plasma etching process. Our results show that a small change of oxygen concentration (3.5-6.5%) can significantly alter the etch rate and profile of the ACL hard mask. Through our comprehensive plasma diagnostics and wafer-processing results, we have also proven a detailed mechanism for the role of the oxygen gas. This research provides a solution for achieving an outstanding etch profile in ACL hard masks with sub-micron scale and emphasizes the importance of controlling the oxygen concentration to optimize the plasma conditions for the desired etching characteristics.

Highly Efficient Van Der Waals Heterojunction on Graphdiyne toward the High-Performance Photodetector

Graphdiyne (GDY), a new 2D material, has recently proven excellent performance in photodetector applications due to its direct bandgap and high mobility. Different from the zero-gap of graphene, these preeminent properties made GDY emerge as a rising star for solving the bottleneck of graphene-based inefficient heterojunction. Herein, a highly effective graphdiyne/molybdenum (GDY/MoS2 ) type-II heterojunction in a charge separation is reported toward a high-performance photodetector. Characterized by robust electron repulsion of alkyne-rich skeleton, the GDY based junction facilitates the effective electron-hole pairs separation and transfer. This results in significant suppression of Auger recombination up to six times at the GDY/MoS2 interface compared with the pristine materials owing to an ultrafast hot hole transfer from MoS2 to GDY. GDY/MoS2 device demonstrates notable photovoltaic behavior with a short-circuit current of -1.3 × 10-5 A and a large open-circuit voltage of 0.23 V under visible irradiation. As a positive-charge-attracting magnet, under illumination, alkyne-rich framework induces positive photogating effect on the neighboring MoS2 , further enhancing photocurrent. Consequently, the device exhibits broadband detection (453-1064 nm) with a maximum responsivity of 78.5 A W-1 and a high speed of 50 µs. Results open up a new promising strategy using GDY toward effective junction for future optoelectronic applications.

Investigating the electrical crosstalk effect between pixels in high-resolution organic light-emitting diode microdisplays

Organic light-emitting diode (OLED) microdisplays have received great attention owing to their excellent performance for augmented reality/virtual reality devices applications. However, high pixel density of OLED microdisplay causes electrical crosstalk, resulting in color distortion. This study investigated the current crosstalk ratio and changes in the color gamut caused by electrical crosstalk between sub-pixels in high-resolution full-color OLED microdisplays. A pixel structure of 3147 pixels per inch (PPI) with four sub-pixels and a single-stack white OLED with red, green, and blue color filters were used for the electrical crosstalk simulation. The results showed that the sheet resistance of the top and bottom electrodes of OLEDs rarely affected the electrical crosstalk. However, the current crosstalk ratio increased dramatically and the color gamut decreased as the sheet resistance of the common organic layer decreased. Furthermore, the color gamut of the OLED microdisplay decreased as the pixel density of the panel increased from 200 to 5000 PPI. Additionally, we fabricated a sub-pixel circuit to measure the electrical crosstalk current using a 3147 PPI scale multi-finger-type pixel structure and compared it with the simulation result.

Synthesis of Aluminum-Based Metal-Organic Framework (MOF)-Derived Carbon Nanomaterials and Their Water Adsorption Isotherm

The characteristics of water vapor adsorption depend on the structure, porosity, and functional groups of the material. Metal-organic framework (MOF)-derived carbon (MDC) is a novel material that exhibits a high specific area and tunable pore sizes by exploiting the stable structure and porosity of pure MOF materials. Herein, two types of aluminum-based MOFs were used as precursors to synthesize hydrophobic microporous C-MDC and micro-mesoporous A-MDC via carbonization and activation depending on the type of ligands in the precursors. C-MDC and A-MDC have different pore characteristics and exhibit distinct water adsorption properties. C-MDC with hydrophobic properties and micropores exhibited negligible water adsorption (108.54 mgg-1) at relatively low pressures (P/P0~0.3) but showed a rapid increase in water adsorption ability (475.7 mgg-1) at relative pressures of about 0.6. A comparison with the isotherm model indicated that the results were consistent with the theories, which include site filling at low relative pressure and pore filling at high relative pressure. In particular, the Do-Do model specialized for type 5 showed excellent agreement.

Mesoporous Silica Particle as an RNA Adsorbent for Facile Purification of In Vitro-Transcribed RNA

Messenger RNA vaccines against SARS-CoV-2 hold great promise for the treatment of a wide range of diseases by using mRNA as a tool for generating vaccination antigens as well as therapeutic proteins in vivo. Increasing interest in mRNA preparation warrants reliable methods for in vitro transcription (IVT) of mRNA, which must entail the elimination of surplus side products such as immunogenic double-stranded RNA (dsRNA). We developed a facile method for the removal of dsRNA from in vitro transcribed RNA with mesoporous silica particles as RNA adsorbents. Various polyamines were tested for the facilitation of RNA adsorption onto mesoporous silica particles in the chromatography. Among the polyamines tested for RNA adsorption, spermidine showed a superior capability of RNA binding to the silica matrix. Mesoporous silica-adsorbed RNA was readily desorbed with elution buffer containing either salt, EDTA, or urea, possibly by disrupting electrostatic interaction and hydrogen bonding between RNA and the silica matrix. Purification of IVT RNA was enabled with the adsorption of RNA to mesoporous silica in a spermidine-containing buffer and subsequent elution with EDTA. By differing EDTA concentration in the eluting buffer, we demonstrated that at least 80% of the dsRNA can be removed from the mesoporous silica-adsorbed RNA. When compared with the cellulose-based removal of dsRNA from IVT RNA, the mesoporous silica-based purification of IVT RNA using spermidine and EDTA in binding and elution, respectively, exhibited more effective removal of dsRNA contaminants from IVT RNA. Thus, mRNA purification with mesoporous silica particles as RNA adsorbents is applicable for the facile preparation of nonimmunogenic RNA suitable for in vivo uses.

A performance evaluation of drug response prediction models for individual drugs

Drug response prediction is important to establish personalized medicine for cancer therapy. Model construction for predicting drug response (i.e., cell viability half-maximal inhibitory concentration [IC₅₀]) of an individual drug by inputting pharmacogenomics in disease models remains critical. Machine learning (ML) has been predominantly applied for prediction, despite the advent of deep learning (DL). Moreover, whether DL or traditional ML models are superior for predicting cell viability IC_50s has to be established. Herein, we constructed ML and DL drug response prediction models for 24 individual drugs and compared the performance of the models by employing gene expression and mutation profiles of cancer cell lines as input. We observed no significant difference in drug response prediction performance between DL and ML models for 24 drugs [root mean squared error (RMSE) ranging from 0.284 to 3.563 for DL and from 0.274 to 2.697 for ML; R² ranging from -7.405 to 0.331 for DL and from -8.113 to 0.470 for ML]. Among the 24 individual drugs, the ridge model of panobinostat exhibited the best performance (R² 0.470 and RMSE 0.623). Thus, we selected the ridge model of panobinostat for further application of explainable artificial intelligence (XAI). Using XAI, we further identified important genomic features for panobinostat response prediction in the ridge model, suggesting the genomic features of 22 genes. Based on our findings, results for an individual drug employing both DL and ML models were comparable. Our study confirms the applicability of drug response prediction models for individual drugs.

Validating a Korean Version of the Single-Item Burnout Measure for Evaluating Burnout Among Doctors

OBJECTIVE

It is essential to measure the effect of burnout on doctors because burnout can affect doctors' mental health as well as the functioning of medical practice. This study aims to validate a Korean version of the single-item burnout measure (SIBM), which was developed to quickly measure the level of burnout among doctors.

METHODS

Through an online survey, a self-report questionnaire was administered to 324 public health doctors in Korea. The Korean version of the SIBM was validated against the Maslach Burnout Inventory-General Survey (MBI-GS), the Patient Health Questionnaire-9 (PHQ-9), the Generalized Anxiety Disorder-7 (GAD-7) screening tool, the Perceived Stress Scale (PSS), and the Vaccination Attitudes Examination (VAX) scale. Pearson correlation coefficients and analysis of variance (ANOVA) were used to determine the association between the SIBM and other scales. ANOVA was additionally used to determine the associations between the subscales of the MBI-GS and those of the SIBM.

RESULTS

The correlation coefficient between the SIBM and the MBI-GS, PHQ-9, GAD-7, and PSS was positive (p<0.01), and the correlation coefficient between the SIBM and the VAX scale was not significant. Therefore, convergent and discriminant validity was verified. Exhaustion and cynicism, which were correlated with the SIBM, with r2=0.43 (p<0.01) and 0.48 (p<0.01), yielded R2 scores of 0.27 (p<0.01) and 0.20 (p<0.01) in ANOVA.

CONCLUSION

The Korean version of the SIBM is an appropriate screening tool for burnout. It can be evaluated in a short time, thereby enhancing continuous follow-up observations and response rates to burnout.