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Non-Schmid effects in a representative refractory multi-principal element alloy (MPEA), MoNbTi, are investigated using molecular statics (MS) and phase field dislocation dynamics (PFDD). In addition to imposing a statistical distribution for the energetic barrier to slip, incorporating properties of the screw dislocation core is critical in capturing the wide range of MS-predicted non-Schmid effects. PFDD energy terms are enhanced to better capture the varying screw dislocation core-widths under loading as informed by MS. These enhancements demonstrate that incorporating the details of screw dislocation cores, in different chemical environments, has the strongest effect on representing the MS-predicted range of non-Schmid effects.Impact StatementVarying degrees of non-Schmid effects, unique to refractory MPEAs, are studied for the first time using atomistic and mesoscale models and are shown to result from environment-dependent properties of screw dislocation cores.

Abstract Methylation patterns in cell-free DNA (cfDNA) have emerged as a promising genomic feature for detecting the presence of cancer and determining its origin. The purpose of this study was to evaluate the diagnostic performance of methylation-sensitive restriction enzyme digestion followed by sequencing (MRE-Seq) using cfDNA, and to investigate the cancer signal origin (CSO) of the cancer using a deep neural network (DNN) analyses for liquid biopsy of colorectal and lung cancer. We developed a selective MRE-Seq method with DNN learning-based prediction model using demethylated-sequence-depth patterns from 63,266 CpG sites using SacII enzyme digestion. A total of 191 patients with stage I–IV cancers (95 lung cancers and 96 colorectal cancers) and 126 noncancer participants were enrolled in this study. Our study showed an area under the receiver operating characteristic curve (AUC) of 0.978 with a sensitivity of 78.1% for colorectal cancer, and an AUC of 0.956 with a sensitivity of 66.3% for lung cancer, both at a specificity of 99.2%. For colorectal cancer, sensitivities for stages I–IV ranged from 76.2 to 83.3% while for lung cancer, sensitivities for stages I–IV ranged from 44.4 to 78.9%, both again at a specificity of 99.2%. The CSO model's true-positive rates were 94.4% and 89.9% for colorectal and lung cancers, respectively. The MRE-Seq was found to be a useful method for detecting global hypomethylation patterns in liquid biopsy samples and accurately diagnosing colorectal and lung cancers, as well as determining CSO of the cancer using DNN analysis. Trial registration: This trial was registered at ClinicalTrials.gov (registration number: NCT 04253509) for lung cancer on 5 February 2020, https://clinicaltrials.gov/ct2/show/NCT04253509 . Colorectal cancer samples were retrospectively registered at CRIS (Clinical Research Information Service, registration number: KCT0008037) on 23 December 2022, https://cris.nih.go.kr , https://who.init/ictrp . Healthy control samples were retrospectively registered.

One of the remarkable choices for active smart window technology is adopting a metal active layer via reversible metal electrodeposition (RME). As the metal layer efficiently blocks the solar energy gain, even a hundred-nanometer-thick scale, RME-based smart window has great attention. Recent developments are mainly focused on the various cases of electrolyte components and composition meeting technological standards. As metal nanostructures formed through the RME process involve plasmonic phenomena, advanced analysis, including plasmonic optics, which is beyond Beer–Lambert’s law, should be considered. However, as there is a lack of debates on the plasmonic optics applied to RME smart window technology, as research is mainly conducted through an exhaustive process. In this paper, in order to provide insight into the RME-based smart window development and alleviate the unclear part of plasmonic optics applied to the field, finite-difference time-domain electromagnetic simulations are conducted. In total, two extremely low-quality (Cr) and high-quality (Mg) plasmonic materials based on a nanoparticle array are considered as a metal medium. In addition, optical effects caused by the metal active layer, electrolyte, and nanoparticle embedment are investigated in detail. Overall simulations suggest that the effective refractive index is a decisive factor in the performance of RME-based smart windows.

Perovskite solar cells (PSCs) have been significantly improved by utilizing an inorganic hole-transporting layer (HTL), such as nickel oxide. Despite the promising properties, there are still limitations due to defects. Recently, research on self-assembled monolayers (SAMs) is being actively conducted, which shows promise in reducing defects and enhancing device performance. In this study, we successfully engineered a p-i-n perovskite solar cell structure utilizing HC-A1 and HC-A4 molecules. These SAM molecules were found to enhance the grain morphology and uniformity of the perovskite film, which are critical factors in determining optical properties and device performance. Notably, HC-A4 demonstrated superior performance due to its distinct hydrophilic properties with a contact angle of 50.3°, attributable to its unique functional groups. Overall, the HC-A4-applied film exhibited efficient carrier extraction properties, attaining a carrier lifetime of 117.33 ns. Furthermore, HC-A4 contributed to superior device performance, achieving the highest device efficiency of 20% and demonstrating outstanding thermal stability over 300 h.

The growth of digital media usage has accelerated the development of big data technology. According to the agenda-setting theory, news media inform the public regarding major agendas and business cycles. This study investigated 168,786 news documents from 2016 to 2020 related the South Korea fashion business using Python. A total of 19 topics were extracted through latent Dirichlet allocation and then transformed into structured data using a time series approach to analyze significant changes in trends. The results indicate that major fashion industry topics include business management strategies to increase sales, diversification of the retail structure, influence of CEOs, and merchandise marketing activities. Thereafter, statistically significant hot and cold topics were derived to identify the shifts in topic themes. This study expands the fashion business contexts with agenda-setting theory through big data time series analyses and can be referenced for the government agencies to support fashion industry policies.

The goal of this study was to examine the effect of engaging students in socially engaged art (SEA) education to create 3D virtual worlds for fostering creative problem-solving (CPS) skills. The study was conducted with 135 students (aged 16) of boys’ high school in Korea who participated in the SEA program through four stages: Stage 1- appreciation and interpretation of artwork about social issues; Stage 2 - discussion on the potential solution to the selected social issue; Stage 3 - creating a 3D virtual world k to express proposed solutions; and Stage 4 - experiencing and sharing 3D virtual worlds. The following research questions guided the study: (1) What is the effect of SEA education with VR on students’ CPS? (2) How are the students’ CPS as expressed in their artifact (essay and VR work)? (3) What are the relationships between students’ CPS and their artifact (essay and VR work)? For data collection, we administered the instrument to measure students’ CPS skills in three areas (higher-order thinking, divergent thinking, and problem-solving) and also evaluated student essays and VR work to examine CPS specific to art education. Overall, the results indicate that the students improved their CPS skills significantly after participating in the SEA program. The CPS skills had significant relationships with the essay scores, whereas only one significant relationship was found between CPS and VR work. This study provides empirical findings concerning how the formal school curriculum can introduce students to an authentic context concerning social issues through artmaking practices with VR.

Brain aging is a complex biological process that is affected by both genetic background and environment. The transcriptomic analysis of aged human and rodent brains has been applied to identify age-associated molecular and cellular processes for which intervention could possibly restore declining brain functions induced by aging. However, whether these age-associated genetic alterations are indeed involved in the healthy aging of the brain remains unclear. We herein characterized a naturally occurring, extremely long-lived (34 months of age) but healthy mouse group retaining well-preserved motor functions. Strikingly, these long-lived mice maintained tyrosine hydroxylase expression and dopaminergic fiber densities, even in the presence of persistent neuroinflammation and expression of aging markers. Combined with Endeavor gene prioritization, we identified the following midbrain-specific longevity-associated genes in the midbrain of these mice: aimp2, hexb, cacybp, akt2, nrf1, axin1, wwp2, sp2, dnajb9, notch, traf7, and lrp1. A detailed biochemical analysis of the midbrain of these long-lived mice confirmed the increased expression of Nrf1 and the activation of Akt1 and 2. Interestingly, dopaminergic neuroprotective and age-associated E3 ubiquitin ligase parkin expression was retained at high levels in the aforementioned midbrains, possibly supporting the suppression of its toxic substrates AIMP2 and PARIS. In contrast, the 24-month-old mice with dopaminergic neurite deficits failed to maintain parkin expression in the midbrain. AIMP2-induced cytotoxicity, mitochondrial stress, and neurite toxicity can be prevented by overexpression of parkin, Akt1, and Nrf1 in SH-SY5Y and PC12 cells, and basal expression of parkin, Akt1, and Nrf1 is required for maintenance of mitochondrial function and neurite integrity in PC12 cells. Taken together, this longevity-associated pathway could be a potential target of intervention to maintain nigrostriatal dopaminergic fibers and motor ability to ensure healthy longevity.

Abstract After the development of Web 2.0 and social networks, analyzing consumers’ responses and opinions in real-time became profoundly important to gain business insights. This study aims to identify consumers’ preferences and perceptions of genderless fashion trends by text-mining, Latent Dirichlet Allocation-based topic modeling, and time-series linear regression analysis. Unstructured text data from consumer-posted sources, such as blogs and online communities, were collected from January 1, 2018 to December 31, 2020. We examined 9722 posts that included the keyword “genderless fashion” with Python 3.7 software. Results showed that consumers were interested in fragrances, fashion, and beauty brands and products. In particular, 18 topics were extracted: 13 were classified as fashion categories and 5 were derived from beauty and fragrance sectors. Examining the genderless fashion trend development among consumers from 2018 to 2020, “perfume and scent” was revealed as the hot topic, whereas “bags,” “all-in-one skin care,” and “set-up suit” were cold topics, declining in popularity among consumers. The findings contribute to contemporary fashion trends and provide in-depth knowledge about consumers’ perceptions using big data analysis methods and offer insights into product development strategies.

Early detection of lung cancer is crucial for patient survival and treatment. Recent advancements in next-generation sequencing (NGS) analysis enable cell-free DNA (cfDNA) liquid biopsy to detect changes, like chromosomal rearrangements, somatic mutations, and copy number variations (CNVs), in cancer. Machine learning (ML) analysis using cancer markers is a highly promising tool for identifying patterns and anomalies in cancers, making the development of ML-based analysis methods essential. We collected blood samples from 92 lung cancer patients and 80 healthy individuals to analyze the distinction between them. The detection of lung cancer markers Cyfra21 and carcinoembryonic antigen (CEA) in blood revealed significant differences between patients and controls. We performed machine learning analysis to obtain AUC values via Adaptive Boosting (AdaBoost), Multi-Layer Perceptron (MLP), and Logistic Regression (LR) using cancer markers, cfDNA concentrations, and CNV screening. Furthermore, combining the analysis of all multi-omics data for ML showed higher AUC values compared with analyzing each element separately, suggesting the potential for a highly accurate diagnosis of cancer. Overall, our results from ML analysis using multi-omics data obtained from blood demonstrate a remarkable ability of the model to distinguish between lung cancer and healthy individuals, highlighting the potential for a diagnostic model against lung cancer.

Abstract Flexible displays on a polyimide (PI) substrate are widely regarded as a promising next-generation display technology due to their versatility in various applications. Among other bendable materials used as display panel substrates, PI is especially suitable for flexible displays for its high glass transition temperature and low coefficient of thermal expansion. PI cured under various temperatures (260 °C, 360 °C, and 460 °C) was implemented in metal–insulator–metal (MIM) capacitors, amorphous indium gallium zinc oxide (a-IGZO) thin-film transistors (TFT), and actual display panels to analyze device stability and panel product characteristics. Through electrical analysis of the MIM capacitor, it was confirmed that the charging effect in the PI substrates intensified as the PI curing temperature increased. The threshold voltage shift (ΔVth) of the samples was found to increase with rising curing temperature under negative bias temperature stress (NBTS) due to the charging effect. Our analyses also show that increasing ΔVth exacerbates the image sticking phenomenon observed in display panels. These findings ultimately present a direct correlation between the curing temperature of polyimide substrates and the panel image sticking phenomenon, which could provide an insight into the improvement of future PI-substrate-based displays.

The aggregation of aminoacyl transfer RNA synthetase complex-interacting multifunctional protein-2 (AIMP2) accelerates α-synuclein aggregation via direct interaction, leading to enhanced dopaminergic neurotoxicity in Parkinson’s disease (PD). Thus, it would be beneficial to prevent AIMP2 aggregation to suppress α-synucleinopathy in PD. In this study, we screened small compounds that could inhibit the in vitro aggregation of AIMP2 using a 1909 small-compound library. The AIMP2 inhibitors (SAI-04, 06, and 08) with the most effective inhibition of AIMP2 aggregation bind to AIMP2, disaggregate the pre-formed AIMP2 aggregates, and prevented AIMP2/α-synuclein coaggregation and cytotoxicity in SH-SY5Y cells. Moreover, AIMP2 inhibitors prevented α-synuclein preformed fibril (PFF)-induced pathological AIMP2 aggregation in both mouse cortical and embryonic stem cell-derived human dopaminergic neurons, thereby blocking PFF-induced α-synuclein aggregation and neurotoxicity. Collectively, our results suggest that the use of brain-permeable AIMP2 aggregation inhibitors may serve as an effective therapeutic strategy for α-synucleinopathy in PD.

The energetic sulfide vapor process on colloidal indium arsenide (InAs) quantum dots (QDs) for integrated optoelectronic devices is demonstrated. X‐ray photoemission spectroscopy supports the presence of sulfur on QD surface, which increases the air stability, and ultraviolet photoemission spectroscopy and field‐effect transistor analysis confirm n‐type charge transport of corresponding QD films with higher electron mobilities. Photoconductivity of the same devices in near‐infrared wavelength shows gate bias‐dependent recombination of photogenerated carriers, coming from charge accumulation and depletion transition of QD channels. The synergetic approach of the vapor process on colloidal QD solids opens a promising opportunity for scalable and complementary metal‐oxide semiconductor‐compatible optoelectronic devices.

Previous evidence suggests a potential dual impact of aging and vitamin B6 (B6) deficiency on polyunsaturated fatty acid (PUFA) metabolism; gender may influence PUFA biosynthesis. Perturbation of PUFA compositions during B6 deficiency could be linked to age-related health outcomes. However, little is known about the interrelationships between vitamin B6, PUFA, and gender in the older population. Therefore, we investigated whether gender-specific associations of B6 intake and plasma pyridoxal 5’-phosphate (PLP) concentration, respectively, with plasma PUFA concentrations and ratios (eicosapentaenoic acid (EPA), docosahexaenoic acid (DHA), arachidonic acid (AA), EPA + DHA, EPA/AA, and (EPA + DHA)/AA) existed in older adults. We further examined the relationships of adequate B6 status (PLP ≥ 20 nmol/L) with high (above median) plasma PUFA relative to deficient B6 status. This cross-sectional study analyzed 461 participants aged ≥60 years from NHANES 2003–2004. Nutrient intakes were assessed using two 24-h recalls and supplement questionnaires. PLP and PUFA concentrations were measured. Multivariate linear regression assessed the association of B6 intake and PLP with PUFA; multivariate logistic regression evaluated the relationship of adequate B6 status with high plasma PUFA, adjusting for demographic, socioeconomic, and dietary factors; physical activity; smoking; alcohol; medication; and BMI. There were interactions between gender and B6 intake on EPA (P-interaction = 0.008) and AA (P-interaction = 0.004) only, whereas no interaction existed between gender and PLP on PUFA. PLP was directly associated with EPA (β = 0.181, P = 0.002), DHA (β = 0.109, P = 0.005), EPA + DHA (β = 0.14, P = 0.002), EPA/AA (β = 0.186, P = 0.004), and (EPA + DHA)/AA (β = 0.13, P = 0.026). The odds of having high plasma EPA (adjusted (a) OR: 2.03, P = 0.049) and EPA/AA (aOR: 3.83, P < 0.0001) were greater in those with adequate B6 status compared to those with deficient B6 status. In conclusion, in US older adults, a higher PLP level was associated with a greater level of EPA, DHA, EPA + DHA, EPA/AA, and (EPA + DHA)/AA. Adequate B6 status was associated with high EPA and EPA/AA status. These findings suggest that sufficient vitamin B6 status may positively influence PUFA metabolism in older adults.