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Fundamental mode surface wave data have often been used to construct global shear velocity models of the upper mantle under the so-called 'path average approximation', an efficient approach from the computational point of view. With the advent of full-waveform inversion and numerical wavefield computations, such as afforded by the spectral element method, accounting for the effects of the crust accurately becomes challenging. Here, we assess the merits of accounting for crustal and uppermost mantle effects on surface and body waveforms using fundamental mode dispersion data and a smooth representation of the shallow structure. For this we take as reference a model obtained by full-waveform inversion and wavefield computations using the spectral element method, model SEMUCB-WM1 and compare the waveform fits of synthetics to different parts of three component observed teleseismic records, in the period band 32–300 s for body waves and 40–300 s for surface waves and their overtones for three different models. The latter are: a dispersion-only based model (model Disp_20s_iter5), and two models modified from SEMUCB-WM1 by successively replacing the top 200 km (model Merged _200 km) and top 80 km (model Merged _80 km), respectively, by a model constrained solely by fundamental mode surface wave dispersion data between periods of 20 and 150 s. The crustal part of these three models (resp. SEMUCB-WM1) is constrained from dispersion data in the period range 20–60 s (resp. 25–60 s), using the concept of homogenization which is tailored to simplify complex geological features, enhancing the computational efficiency of our seismic modelling. We evaluate the fits to observed waveforms provided by these three models compared to those of SEMUCB-WM1 by computing three component synthetics using the spectral element method for five globally distributed events recorded at 200+stations, using several measures of misfit. While fits to waveforms for model 3 are similar to those for SEMUCB-WM1, the other two models provide increasingly poorer fits as the distance travelled by the corresponding seismic wave increases and/or as it samples deeper in the mantle. In particular, models 1 and 2 are biased towards fast shear velocities, on average. Our results suggest that, given a comparable frequency band, models constructed using fundamental mode surface wave data alone and the path average approximation, fail to provide acceptable fits to the corresponding waveforms. However, the shallow part of such a 3-D radially anisotropic model can be a good starting model for further full waveform inversion using numerical wavefield computations. Moreover, the shallow part of such a model, including its smooth crustal model, and down to a maximum depth that depends on the frequency band considered, can be fixed in full-waveform inversion iterations for deeper structure. This can save significant computational time when higher resolution is sought in the deeper mantle. In the future, additional constraints for the construction of the homogenized model of the crust can be implemented from independent short period studies, either globally or regionally. [ABSTRACT FROM AUTHOR]

This study explores memristor-based true random number generators (TRNGs) through their evolution and optimization, stemming from the concept of memristors first introduced by Leon Chua in 1971 and realized in 2008. We will consider memristor TRNGs coming from various entropy sources for producing high-quality random numbers. However, we must take into account both their strengths and weaknesses. The comparison with CMOS-based TRNGs will serve as an illustration that memristor TRNGs stand out due to their simpler circuits and lower power consumption— thus leading us into a case study involving electroless YMnO3 (YMO) memristors as TRNG entropy sources that demonstrate good security properties by being able to produce unpredictable random numbers effectively. The end of our analysis sees us pinpointing challenges: post-processing algorithm optimization coupled with ensuring reliability over time for memristor-based TRNGs aimed at next-generation security applications. [ABSTRACT FROM AUTHOR]

Individuals with autism spectrum disorder (ASD) often experience lifelong social communication challenges and are more vulnerable to school bullying. Addressing their social difficulties and school bullying requires evidence‐based interventions. PEERS® (Program for the Education and Enrichment of Relational Skills) was adapted and translated for Taiwanese adolescents. This randomized controlled study aimed to examine the effectiveness of the Taiwanese version of PEERS® in reducing school bullying and enhancing social function among autistic adolescents. Twenty‐one autistic adolescents (mean age 14.29 ± 1.67 years; female n = 733.33%) were randomized to a treatment group (TG, n = 10) or a delayed treatment control group (DTG, n = 11). The outcome measures (school bullying, social challenges, social skills knowledge, and social skills performance) were assessed at baseline, post‐treatment, and follow‐up. The group and time interaction analyses revealed greater magnitudes of reduction in general school bullying (p < 0.001), victimization (p < 0.001), perpetration (p = 0.012), social challenges (p = 0.001), and peer conflicts (p < 0.001), and improvement in social knowledge (p < 0.001) in the TG group than the DTG group. The findings suggest that the PEERS® program tailored for Taiwanese adolescents is effective in reducing school bullying, decreasing social challenges, and enhancing social skills among autistic adolescents, with very large effect sizes (Cohen's d ranging from 1.19 to 2.88). Consequently, participation in the PEERS® program is recommended for adolescents with social difficulties to improve their social communication and interactions to offset school bullying and other social challenges related to adverse outcomes. Lay Summary: This study examined the effectiveness of the PEERS® program, adapted for Taiwanese autistic teenagers. The findings suggest that the program effectively improves social function and reduces the risk of bullying in school for these teens. Teenagers with social difficulties, especially those on the autism spectrum, should be encouraged to participate in the PEERS® program, which provides essential skills and strategies to cope with social difficulties and school bullying. [ABSTRACT FROM AUTHOR]

The optimal strategy for the microelimination of HCV within community settings remains ambiguous. We evaluated the percentage of participants who achieved linkage to care (LTC) following the conclusion of a screening campaign and examined the diverse factors influencing LTC among these individuals. The effectiveness of recall intervention for the non-LTC population and its barriers were analyzed. We initiated an HCV patient recall program to identify HCV participants who might not be treated after the HCV screening campaign. The program staff recalled HCV participants who were lost to follow-up via telephone from March 2019 to June 2019. They were informed of HCV treatment's importance, efficacy, availability, and safety. Among 185 participants infected with HCV, 109 (58.9%) obtained LTC. Compared with those who had LTC, those without LTC were older, had lower education levels, were less aware of their HCV infection, less frequently lived in urban areas, and had less health insurance. At the end of the recall program, 125 (67.6%) persons had linkage to care. The proportion of LTC increased by 8.7%. In total, 119 persons had an HCV RNA test, and 82 (68.9%) had viremia. Of the 82 patients with viremia, 78 (95.1%) received antiviral therapy, and 76 (97.4%) achieved a sustained virological response. After a community screening campaign, 59% of participants with anti-HCV-positive tests had LTC. The recall program increased this by 9%. However, 32% of HCV participants still could not be linked to care. Outreach care for non-LTC patients is a method worth trying in order to achieve the microelimination of HCV in rural communities. [ABSTRACT FROM AUTHOR]

Simple Summary: This study introduces a CT-based 3D reconstruction algorithm for measuring resection margins post sublobar resection in lung cancer patients. It aims to enhance accuracy and reproducibility, addressing the limitations of gross margin measurement. The findings show feasibility with a target registration error of <2.5 mm. This approach could revolutionize lung cancer treatment, facilitating prompt identification of patients with inadequate resection margins for timely post-operative adjuvant therapies. Sublobar resection has emerged as a standard treatment option for early-stage peripheral non-small cell lung cancer. Achieving an adequate resection margin is crucial to prevent local tumor recurrence. However, gross measurement of the resection margin may lack accuracy due to the elasticity of lung tissue and interobserver variability. Therefore, this study aimed to develop an objective measurement method, the CT-based 3D reconstruction algorithm, to quantify the resection margin following sublobar resection in lung cancer patients through pre- and post-operative CT image comparison. An automated subvascular matching technique was first developed to ensure accuracy and reproducibility in the matching process. Following the extraction of matched feature points, another key technique involves calculating the displacement field within the image. This is particularly important for mapping discontinuous deformation fields around the surgical resection area. A transformation based on thin-plate spline is used for medical image registration. Upon completing the final step of image registration, the distance at the resection margin was measured. After developing the CT-based 3D reconstruction algorithm, we included 12 cases for resection margin distance measurement, comprising 4 right middle lobectomies, 6 segmentectomies, and 2 wedge resections. The outcomes obtained with our method revealed that the target registration error for all cases was less than 2.5 mm. Our method demonstrated the feasibility of measuring the resection margin following sublobar resection in lung cancer patients through pre- and post-operative CT image comparison. Further validation with a multicenter, large cohort, and analysis of clinical outcome correlation is necessary in future studies. [ABSTRACT FROM AUTHOR]

Simple Summary: This study included 227 patients, among whom 27.7% (63/227) were diagnosed with tumors spread through air spaces (STASs), which have been shown to be associated with shorter recurrence-free survival and poor prognosis. A prediction model was developed to forecast tumor STAS in early-stage lung adenocarcinoma pathology images. The radiomics prediction model demonstrated good performance, with an AUC value of 0.83. This prediction model can assist pathologists in the diagnostic processes of clinical practice. The presence of spread through air spaces (STASs) in early-stage lung adenocarcinoma is a significant prognostic factor associated with disease recurrence and poor outcomes. Although current STAS detection methods rely on pathological examinations, the advent of artificial intelligence (AI) offers opportunities for automated histopathological image analysis. This study developed a deep learning (DL) model for STAS prediction and investigated the correlation between the prediction results and patient outcomes. To develop the DL-based STAS prediction model, 1053 digital pathology whole-slide images (WSIs) from the competition dataset were enrolled in the training set, and 227 WSIs from the National Taiwan University Hospital were enrolled for external validation. A YOLOv5-based framework comprising preprocessing, candidate detection, false-positive reduction, and patient-based prediction was proposed for STAS prediction. The model achieved an area under the curve (AUC) of 0.83 in predicting STAS presence, with 72% accuracy, 81% sensitivity, and 63% specificity. Additionally, the DL model demonstrated a prognostic value in disease-free survival compared to that of pathological evaluation. These findings suggest that DL-based STAS prediction could serve as an adjunctive screening tool and facilitate clinical decision-making in patients with early-stage lung adenocarcinoma. [ABSTRACT FROM AUTHOR]

Early-stage ventures often face bounded rationality from a lack of experience as well as limited resources. A strategic choice to patent a firm's innovations to prevent competitor infringement involves significant resource commitments. We hypothesise that for early-stage ventures, having a patent could create liability on short-term financial performance; however, higher levels of market orientation could overcome it. We find support for our hypotheses using a sample of early-stage ventures that apply to business accelerators for support. This study contributes to the extant literature on innovation and entrepreneurship, as well as on market orientation, to show that for early-stage ventures, a potential liability of patenting exists, but it can be mitigated by higher levels of market orientation. [ABSTRACT FROM AUTHOR]

Background: Sublobar resection is strongly associated with poor prognosis in early-stage lung adenocarcinoma, with the presence of tumor spread through air spaces (STAS). Thus, preoperative prediction of STAS is important for surgical planning. This study aimed to develop a STAS deep-learning (STAS-DL) prediction model in lung adenocarcinoma with tumor smaller than 3 cm and a consolidation-to-tumor (C/T) ratio less than 0.5. Methods: The study retrospectively enrolled of 581 patients from two institutions between 2015 and 2019. The STAS-DL model was developed to extract the feature of solid components through solid components gated (SCG) for predicting STAS. The STAS-DL model was assessed with external validation in the testing sets and compared with the deep-learning model without SCG (STAS-DLwoSCG), the radiomics-based model, the C/T ratio, and five thoracic surgeons. The performance of the models was evaluated using area under the curve (AUC), accuracy and standardized net benefit of the decision curve analysis. Results: The study evaluated 458 patients (institute 1) in the training set and 123 patients (institute 2) in the testing set. The proposed STAS-DL yielded the best performance compared with the other methods in the testing set, with an AUC of 0.82 and an accuracy of 74%, outperformed the STAS-DLwoSCG with an accuracy of 70%, and was superior to the physicians with an AUC of 0.68. Moreover, STAS-DL achieved the highest standardized net benefit compared with the other methods. Conclusion: The proposed STAS-DL model has great potential for the preoperative prediction of STAS and may support decision-making for surgical planning in early-stage, ground glass-predominant lung adenocarcinoma. [ABSTRACT FROM AUTHOR]

The spectral element method is currently the method of choice for computing accurate synthetic seismic wavefields in realistic 3-D earth models at the global scale. However, it requires significantly more computational time, compared to normal mode-based approximate methods. Source stacking, whereby multiple earthquake sources are aligned on their origin time and simultaneously triggered, can reduce the computational costs by several orders of magnitude. We present the results of synthetic tests performed on a realistic radially anisotropic 3-D model, slightly modified from model SEMUCB-WM1 with three component synthetic waveform 'data' for a duration of 10 000 s, and filtered at periods longer than 60 s, for a set of 273 events and 515 stations. We consider two definitions of the misfit function, one based on the stacked records at individual stations and another based on station-pair cross-correlations of the stacked records. The inverse step is performed using a Gauss–Newton approach where the gradient and Hessian are computed using normal mode perturbation theory. We investigate the retrieval of radially anisotropic long wavelength structure in the upper mantle in the depth range 100–800 km, after fixing the crust and uppermost mantle structure constrained by fundamental mode Love and Rayleigh wave dispersion data. The results show good performance using both definitions of the misfit function, even in the presence of realistic noise, with degraded amplitudes of lateral variations in the anisotropic parameter ξ. Interestingly, we show that we can retrieve the long wavelength structure in the upper mantle, when considering one or the other of three portions of the cross-correlation time series, corresponding to where we expect the energy from surface wave overtone, fundamental mode or a mixture of the two to be dominant, respectively. We also considered the issue of missing data, by randomly removing a successively larger proportion of the available synthetic data. We replace the missing data by synthetics computed in the current 3-D model using normal mode perturbation theory. The inversion results degrade with the proportion of missing data, especially for ξ , and we find that a data availability of 45 per cent or more leads to acceptable results. We also present a strategy for grouping events and stations to minimize the number of missing data in each group. This leads to an increased number of computations but can be significantly more efficient than conventional single-event-at-a-time inversion. We apply the grouping strategy to a real picking scenario, and show promising resolution capability despite the use of fewer waveforms and uneven ray path distribution. Source stacking approach can be used to rapidly obtain a starting 3-D model for more conventional full-waveform inversion at higher resolution, and to investigate assumptions made in the inversion, such as trade-offs between isotropic, anisotropic or anelastic structure, different model parametrizations or how crustal structure is accounted for. [ABSTRACT FROM AUTHOR]

Dengue is one of the world's most rapidly spreading mosquito-borne viral diseases. As it is found mostly in urban and semi-urban areas, urbanization and associated human activities that affect the environment and larval habitats could become risk factors (e.g., lane width, conditions of street ditches) for the spread of dengue. However, there are currently no systematic studies of micro-scale urbanization-based risk factors for the spread of dengue epidemics. We describe the study area, two micro-scale environmental risk factors associated with urbanization, and meteorological data. Since the observations involve spatial and temporal correlations, we also use some statistical methods for the analysis of spatial and spatial-temporal data for the relationship between urbanization and dengue. In this study, we analyzed data from Kaohsiung, a densely populated city in southern Taiwan, and found a positive correlation between environmental risk factors associated with urbanization (ditches positive for mosquito larvae and closely packed streets termed "dengue lanes") and clustering effects in dengue cases. The statistical analysis also revealed that the occurrence of positive ditches was significantly associated with that of dengue lanes in the study area. The relationship between climate variables and positive ditches was also analyzed in this paper, indicating a relationship between dengue and both rainfall and temperature, with temperature having a greater effect. Overall, this work is immediately relevant and applicable for policymakers in government, who will need to reduce these favorable habitats for vector-born disease spreaders and implement regulations for new urban constructions to thus reduce dengue spread in future outbreaks. [ABSTRACT FROM AUTHOR]

Introduction: An estimated 38 million people are living with human immunodeficiency virus (HIV) worldwide. Pharmacists are well positioned to provide care to patients with HIV, but gaps in HIV education among pharmacists exist. Recognizing the need to educate and prepare future pharmacists, a 2-credit advanced HIV elective course was created for Doctor of Pharmacy students at Washington State University College of Pharmacy and Pharmaceutical Sciences in the United States, and Masters of Clinical Pharmacy students from University of Western Cape School of Pharmacy in South Africa. Methods: Course topics included diagnosis and treatment of HIV in children and adults, management of common comorbidities, pre-exposure prophylaxis, pharmacogenetic applications, and antiretroviral drug-drug interactions. Course effectiveness was evaluated using student examination results. Student perceptions were evaluated using pre- and post-course self-assessments involving abilities, confidence, and attitudes toward caring for people living with HIV. Results: Student pharmacists demonstrated competency in HIV knowledge, demonstrated skills in application to clinical-based scenarios, and reported significantly improved confidence and abilities as well as positive changes in attitudes toward people with HIV. Conclusion: This course contributed to student learning across different student cohorts in an institutional program in the United States including successful execution of distance learning and clinical application for students at a program in South Africa. [ABSTRACT FROM AUTHOR]

The benefits of entrepreneurial mentorship are well documented, but there is limited research on how entrepreneurs connect with mentors, especially in digital settings. We partnered with an online platform that connects entrepreneurs to potential mentors to conduct a field experiment in online mentoring. Drawing on literature on entrepreneurial mentorship and Social Cognitive Theory, we compared the effects of three interventions on the likelihood of reaching out and making a connection with a mentor in a digital setting. We find that showing entrepreneurs a video of a successful mentor–mentee relationship increases the chances that they will reach out to a potential mentor but does not improve their chances of making a connection. These findings are more pronounced for female entrepreneurs. While not all entrepreneurs adopt the offered interventions, those that make the effort to learn to navigate the online platform and craft a suitable introductory message are successful in establishing a mentoring connection. We discuss these implications for both theory and practice. Plain English Summary: Showing entrepreneurs an example of a successful mentor–mentee relationship makes them more likely to reach out to a potential mentor, and even more so for women entrepreneurs. Additionally, entrepreneurs that make the effort to learn to navigate an online mentoring platform and craft a suitable introductory message are successful in establishing a mentoring connection. We partnered with a global online platform to test three interventions to encourage entrepreneurs to reach out to mentors. However, since many entrepreneurs did not take up the offered interventions, the real-world implications of these approaches are less positive, and overall result in few connections with mentors. We suggest that requiring entrepreneurs to undertake some basic training before engaging on online platforms may increase the barrier to entry but can ultimately lead to more meaningful connections with mentors. [ABSTRACT FROM AUTHOR]

CO2 reduction reactions (CO2RR) powered by renewable electricity can directly convert CO2 to hydrocarbons and fix the sustainable but intermittent energy (e. g., sunlight, wind, etc.) in stable and portable chemical fuels. Advanced catalysts boosting CO2RR with high activity, selectivity, and durability at low overpotentials are of great importance but still elusive. Here, we report that the ultrathin Pd‐Ag dendritic nanoplates (PdAg DNPs) exhibited boosted activity, selectivity, and stability for producing formate from CO2 at a very low overpotential in aqueous solutions under ambient conditions. As a result, the PdAg DNPs exhibited a Faradaic efficiency (FE) for formate of 91% and a cathodic energy efficiency (EE) of ∼90% at the potential of −0.2 V versus reversible hydrogen electrode (vs. RHE), showing significantly enhanced durability as compared with pure Pd catalysts. Our strategy represents a rational catalyst design by engineering the surface geometrical and electronic structures of metal nanocrystals and may find more applicability in future electrocatalysis. [ABSTRACT FROM AUTHOR]

Objective: To investigate the association between folate levels and the risk of gestational diabetes mellitus (GDM) risk during the whole pregnancy. Design: In this retrospective cohort study of pregnant women, serum folate levels were measured before 24 gestational weeks (GW). GDM was diagnosed between 24th and 28th GW based on the criteria of the International Association of Diabetes and Pregnancy Study Groups. General linear models were performed to examine the association of serum folate with plasma glucose (i.e. linear regressions) and risk of GDM (i.e. log-binomial regressions) after controlling for confounders. Restricted cubic spline regression was conducted to test the dosage–response relationship between serum folate and the risk of GDM. Setting: A sigle, urban hospital in Shanghai, China. Participants: A total of 42 478 women who received antenatal care from April 2013 to March 2017 were included. Results: Consistent positive associations were observed between serum folate and plasma glucose levels (fasting, 1-h, 2-h). The adjusted relative risks (RR) and 95 % CI of GDM across serum folate quartiles were 1·00 (reference), 1·15 (95 % CI (1·04, 1·26)), 1·40 (95 % CI (1·27, 1·54)) and 1·54 (95 % CI (1·40, 1·69)), respectively (P -for-trend < 0·001). The positive association between serum folate and GDM remained when stratified by vitamin B12 (adequate v. deficient groups) and the GW of serum folate measurement (≤13 GW v. >13 GWs) Conclusions: The findings of this study may provide important evidence for the public health and clinical guidelines of pregnancy folate supplementation in terms of GDM prevention. [ABSTRACT FROM AUTHOR]

Patients with non-alcoholic fatty liver disease (NAFLD) share similar pathophysiologies to those of patients with alcohol liver disease. Alcoholic metabolic enzyme-related genes (alcohol dehydrogenase 1B (ADH1B) and aldehyde dehydrogenase 2 (ALDH2)) may be associated with pathophysiology in NAFLD patients. In this study, the association between ADH1B/ALDH2 gene polymorphism and serum metabolic factors, body statures, and hepatic steatosis/fibrosis status was evaluated in patients with NAFLD. Using biochemistry data, abdominal ultrasonography, fibrosis evaluation (Kpa), and steatosis evaluation (CAP), ADH1B gene SNP rs1229984 and ALDH2 gene SNP rs671 polymorphism were analyzed in sixty-six patients from 1 January 2022 to 31 December 2022. The percentage of the mutant type (GA + AA) was 87.9% (58/66) in the ADH1B allele and 45.5% (30/66) in the ALDH2 allele. Patients with the mutant-type ADH1B/ALDH2 allele had higher values of alanine aminotransferase (ALT) than the wild type (β = 0.273, p = 0.04). No association was observed between body mass index, serum metabolic factors (sugar and lipid profile), CAP, kPa, and ADH1B/ALDH2. A high proportion of the mutant-type ADH1B allele (87.9%) and ALDH2 allele (45.5%) was observed in patients with NAFLD. No association was observed between ADH1B/ALDH2 allele, BMI, and hepatic steatosis/fibrosis. Patients with the mutant-type ADH1B/ALDH2 allele had higher values of ALT than those with the wild type. [ABSTRACT FROM AUTHOR]

This study uses a social construction perspective to examine how group affective tone develops. Longitudinal data were collected over 18 weeks from the weekly diaries of four teams with 24 university students. Narrative analysis revealed experiences of collectively shared patterns of affective states and the interaction contexts (i.e., affective events) that influenced group affective tone convergence. Emergent themes included topic selection, social support, and how effective team norms help members share positive emotions and moods. Social learning, positive emotional sharing, affective events, and behavioral regularities drive the narratives, leading to the emergence of a positive team affective tone. [ABSTRACT FROM AUTHOR]

Background: Factors of metabolic syndrome such as obesity are well‐known risk factors for gallstone disease (GSD). There are different indicators of obesity, including weight, body mass index, waist circumference, and waist‐to‐height ratio. The predictive ability of different obesity indicators for GSD remains unclear. Objective: To explore the most efficient predictor of GSD among the different anthropometric indicators of obesity. Methods: This population‐based cross‐sectional study included 2263 participants who completed a questionnaire detailing their demographics, medical history, and lifestyle between 2014 and 2017 in Taiwan. Blood samples were collected and physical examinations, including anthropometric measurements, were performed. Gallstone disease was ascertained using ultrasonography. Multivariate analyses were performed to identify independent risk factors for GSD. Results: The overall prevalence of GSD was 8.8%. According to the multivariate analysis, individuals with a waist‐to‐height ratio ≥0.5 (odds ratio|odds ratios (OR) = 1.65, 95% confidence interval (CI) = 1.10−2.48, p = 0.017) had an increased risk of GSD. Diabetes was the main risk factor for GSD in men (OR = 2.06, 95% CI = 1.17−3.65, p = 0.013). Among women, waist‐to‐height ratio >0.5 (OR = 1.76, 95% CI = 1.03−3.02, p = 0.040) and current hormone drug use (OR = 2.73, 95% CI = 1.09−6.84, p = 0.033) were significant risk factors for gallstones. Conclusion: GSD was independently associated with central obesity and exogenous hormone intake in women. Among the anthropometric indicators used to assess central obesity, waist‐to‐height ratio was the most accurate predictor of GSD. [ABSTRACT FROM AUTHOR]

Infrared-vacuum ultraviolet (IR-VUV) spectra of neutral dimethylamine clusters, (DMA)n (n = 2–5), were measured in the spectral range of 2600–3700 cm−1. The experimental IR-VUV spectra show NH stretch modes gradually redshift to 3200-3250 cm−1 with the increase in the cluster size and complex Fermi Resonance (FR) pattern of the CH3 group in the 2800–3000 cm−1 region. Ab initio anharmonic vibrational calculations were performed on low-energy conformers of (DMA)2 and (DMA)3 to examine vibrational coupling among CH/NH and to understand the Fermi resonance pattern in the observed spectra features. We found that the redshift of NH stretching mode with the size of DMA cluster is moderate, and the overtone of NH bending modes is expected to overlap in frequency with the CH stretching fundamental modes. The FR in CH3 groups is originated from the strong coupling between CH stretching fundamental and bending overtone within a CH3 group. Well-resolved experimental spectra also enable us to compare the performance of ab initio anharmonic algorithms at different levels. [ABSTRACT FROM AUTHOR]

BACKGROUND: Sorafenib and lenvatinib are tyrosine kinase inhibitors widely used in the targeted therapy to treat advanced hepatocellular carcinoma (aHCC). The GALNT14-rs9679162 genotype is a predictor of therapeutic outcome in multiple gastrointestinal cancers. OBJECTIVE: To investigate the predictive role of the GALNT14-rs9679162 genotype in aHCC treated with sorafenib or lenvatinib. METHODS: Totally 350 real-world patients with aHCC received sorafenib or lenvatinib were enrolled for GALNT14-rs9679162 genotyping and outcome analysis. Kaplan-Meier and Cox regression analysis were conducted to evaluate therapeutic outcomes. Cell-based assays were performed to determine the underlying mechanism. RESULTS: Kaplan-Meier and Cox regression analysis showed that the "GG" genotype was not associated with overall survival (OS) when all patients were included. However, it was associated with shorter OS in specific clinical subgroups, including anti-hepatitis C virus antibody-positive (n = 108; P = 0.005) and hepatitis B surface antigen-negative (n = 117; P = 0.002) patients. Intriguingly, hepatitis B virus X protein trans-suppressed the GALNT14 promoter, thereby reducing the elevated expression of GALNT14 in hepatoma cells, which partially contributed to the inability of the GALNT14-rs9679162 genotypes to predict the outcome of hepatitis B-related HCC. Finally, by analyzing the outcomes of 52 patients with aHCC treated with lenvatinib, patients with the "GG" genotype were associated with a favorable/shorter time-to-response (P = 0.013). CONCLUSIONS: The GALNT14-rs9679162 "GG" genotype predicted shorter OS in patients with HBsAg-negative aHCC treated with sorafenib, but predicted a favorable response in all patients with aHCC treated with lenvatinib. [ABSTRACT FROM AUTHOR]

Sorafenib is currently a targeted agent widely used in the treatment of advanced hepatocellular carcinoma (aHCC). However, to date there is still a lack of a reliable marker capable of predicting sorafenib therapeutic responses. Here, we conducted a genome-wide association study (GWAS) to identify candidate single-nucleotide polymorphism outcome predictors in aHCC patients. A total of 74 real-world sorafenib-treated aHCC patients were enrolled for GWAS and outcome analysis. GWAS showed that rs1010816 (p = 2.2 × 10−7) was associated with sorafenib therapeutic response in aHCC patients. Kaplan–Meier analysis indicated that the "TT" genotype was significantly associated with a favorable therapeutic response but not significantly associated with overall survival (OS). Univariate followed by multivariate Cox proportional hazard analysis showed that ascites, main portal vein thrombosis, lower platelet count, lower total sorafenib doses, higher PALBI score in model A and higher ALBI grade in model B were significantly associated with a shorter OS. Subgroup analysis showed that only in alcoholic aHCC patients treated by sorafenib, rs1010816 "TT" genotype was significantly associated with longer OS (p = 0.021). Sorafenib had a favorable therapeutic outcome in alcoholic aHCC patients carrying rs1010816 "TT" genotype. [ABSTRACT FROM AUTHOR]

Avatar actions can be captured using certain gesture sensors or can be predefined by game designers through desktop applications. In other words, developing an online avatar editor could be necessary to specify the detailed actions for use by people who are not game creators. Our research team proposed a web-based toolset, myKLA, to construct and design avatar actions with editor and player features. The goal of myKLA is to help users define the required behaviors of avatars within a set time frame without codes. We used cyber–physical system theory in a software reconstruction initiative. Additionally, an exchangeable JSON file format for predefining the avatar actions was opened and shared here. Furthermore, the cyclomatic complexity of the main code blocks in our toolset was measured and changed using the McCabe approach to fine-tune the performance. An algorithm was proposed for quickly calculating an integrated activity diagram from several sub-activity diagrams. Our research showed that it is easy to create an avatar head and embed it in other web-based applications for additional interaction utilization. Therefore, our findings will be useful in creating and designing new educational tools. [ABSTRACT FROM AUTHOR]

Simple Summary: To forecast the invasiveness of the increasingly detected pure ground glass nodules, 338 cases were included in this study. Among them, 22.8% (77/338) of patients with pGGN were diagnosed with invasive adenocarcinoma. There were no nodal metastases or recurrence during a mean 78-month follow-up. A radiomic prediction model was constructed to predict the tumor's invasiveness. The radiomic prediction model achieved good performance with an AUC of 0.7676. The prediction model can be used clinically in the treatment selection process. It remains a challenge to preoperatively forecast whether lung pure ground-glass nodules (pGGNs) have invasive components. We aimed to construct a radiomic model using tumor characteristics to predict the histologic subtype associated with pGGNs. We retrospectively reviewed clinicopathologic features of pGGNs resected in 338 patients with lung adenocarcinoma between 2011–2016 at a single institution. A radiomic prediction model based on forward sequential selection and logistic regression was constructed to differentiate adenocarcinoma in situ (AIS)/minimally invasive adenocarcinoma (MIA) from invasive adenocarcinoma. The study cohort included 133 (39.4%), 128 (37.9%), and 77 (22.8%) patients with AIS, MIA, and invasive adenocarcinoma (acinar 55.8%, lepidic 33.8%, papillary 10.4%), respectively. The majority (83.7%) underwent sublobar resection. There were no nodal metastases or tumor recurrence during a mean follow-up period of 78 months. Three radiomic features—cluster shade, homogeneity, and run-length variance—were identified as predictors of histologic subtype and were selected to construct a prediction model to classify the AIS/MIA and invasive adenocarcinoma groups. The model achieved accuracy, sensitivity, specificity, and AUC of 70.6%, 75.0%, 70.0%, and 0.7676, respectively. Applying the developed radiomic feature model to predict the histologic subtypes of pGGNs observed on CT scans can help clinically in the treatment selection process. [ABSTRACT FROM AUTHOR]

Elevated serum ferritin and uric acid levels are common in patients with fatty liver disease. This study assessed the association between serum ferritin and uric acid levels and liver fibrosis in subjects with lean metabolic dysfunction-associated fatty liver disease (MAFLD). This cross-sectional study used data from a community screening examination for metabolic syndrome from December 2018 to September 2019 at Keelung Chang Gung Memorial Hospital. Subjects with lean MAFLD were defined as those with a body mass index (BMI) < 23 kg/m2 and hepatic steatosis according to the MAFLD criteria. A total of 182 lean subjects were included and were divided into lean MAFLD and lean healthy groups. Serum ferritin and uric acid concentrations were positively correlated with liver fibrosis, regardless of whether FIB-4, APRI, or NFS were used as references. Univariate logistic regression analysis showed that age and uric acid were associated with advanced liver fibrosis. After adjusting for potential confounders, only uric acid level was statistically significant in predicting the advanced liver fibrosis (OR = 6.907 (1.111–42.94), p = 0.038) in the lean MAFLD group. We found that an elevated serum uric acid level is an independent factor associated with advanced liver fibrosis in lean MAFLD subjects by noninvasive fibrosis scores. [ABSTRACT FROM AUTHOR]

The development and commercialization of direct ethanol fuel cells requires active and durable electro-catalysts towards the ethanol oxidation reactions (EOR). Rational composition and morphology control of Pt-based alloy nanocrystals can not only enhance their EOR reactivity but also reduce the consumption of precious Pt. Herein, PtCu nanocubes (NCs)/CB enclosed by well-defined (100) facets were prepared by solution synthesis, exhibiting much higher mass activity (4.96 A mgPt−1) than PtCu nanoparticles (NPs)/CB with irregular shapes (3.26 A mgPt−1) and commercial Pt/C (1.67 A mgPt−1). CO stripping and in situ Fourier transform infrared spectroscopy (FTIR) experiments indicate that the alloying of Cu enhanced the adsorption of ethanol, accelerated the subsequent oxidation of intermediate species, and increased the resistance to CO poisoning of PtCu NCs/CB, as compared with commercial Pt/C. Therefore, alloying Pt with earth-abundant Cu under rational composition and surface control can optimize its surface and electronic structures and represents a promising strategy to promote the performance of electro-catalysts while reduce the use of precious metals. [ABSTRACT FROM AUTHOR]

CO2 reduction reactions (CO2RR) powered by renewable electricity can directly convert CO2 to hydrocarbons and fix the intermittent sustainable energy in portable chemical fuels. It is of great importance to develop advanced catalysts that can boost CO2RR with high activity, selectivity, and efficiency at low overpotentials. Here, we report the solution synthesis using H2O2 to modify the surface structures of gold multi-twinned nanoparticles (AuMPs) and create tensile surface steps. Calculations predicted significantly enhanced CO2 adsorption and boosted CO2RR capabilities with inhibited hydrogen evolution reaction activity for the tensile surface steps with modified electronic structure. The H2O2-treated AuMPs with surface steps and 3.83% tensile lattices showed much higher activity and selectivity at lower overpotentials for CO2RR than pristine gold nanoparticles. The CO-production current density reached about 98 mA cm−2 with a Faradaic efficiency of 95.7% at −0.30 V versus reversible hydrogen electrode in the flow cell, showing a half-cell energy efficiency as high as ∼83%. Our strategy represents a rational catalyst design by engineering the surface structures of metal nanoparticles and may find more applicability in future electrocatalysis. [ABSTRACT FROM AUTHOR]

Background: High-grade adenocarcinoma subtypes (micropapillary and solid) treated with sublobar resection have an unfavorable prognosis compared with those treated with lobectomy. We investigated the potential of incorporating solid attenuation component masks with deep learning in the prediction of high-grade components to optimize surgical strategy preoperatively. Methods: A total of 502 patients with pathologically confirmed high-grade adenocarcinomas were retrospectively enrolled between 2016 and 2020. The SACs attention DL model was developed to apply solid-attenuation-component-like subregion masks (tumor area ≥ − 190 HU) to guide the DL model for predicting high-grade subtypes. The SACA-DL was assessed using 5-fold cross-validation and external validation in the training and testing sets, respectively. The performance, which was evaluated using the area under the curve (AUC), was compared between SACA-DL and the DL model without SACs attention (DLwoSACs), the prior radiomics model, or the model based on the consolidation/tumor (C/T) diameter ratio. Results: We classified 313 and 189 patients into training and testing cohorts, respectively. The SACA-DL achieved an AUC of 0.91 for the cross-validation, which was significantly superior to those of the DLwoSACs (AUC = 0.88; P = 0.02), prior radiomics model (AUC = 0.85; P = 0.004), and C/T ratio (AUC = 0.84; P = 0.002). An AUC of 0.93 was achieved for external validation in the SACA-DL and was significantly better than those of the DLwoSACs (AUC = 0.89; P = 0.04), prior radiomics model (AUC = 0.85; P < 0.001), and C/T ratio (AUC = 0.85; P < 0.001). Conclusions: The combination of solid-attenuation-component-like subregion masks with the DL model is a promising approach for the preoperative prediction of high-grade adenocarcinoma subtypes. [ABSTRACT FROM AUTHOR]

Breast cancer is the most common cancer in women in the world. Statistics revealed the number of breast cancer patients less than 40 years of age increased over time. Clinical studies found there is a trend of yearly illness happening in younger patients, whose needs related to the illness are different from older patients. The purpose of this study was to explore the uncertainty and needs of patients in different age groups who were newly diagnosed with breast cancer. A descriptive cross-sectional survey study was adopted to recruit 128 patients. The Mishel's Uncertainty in Illness Scale (MUIS, Chinese version) and the Cancer Needs Questionnaire (short-form, CNQ-SF) were used to collect data. The results revealed that a patient's age and religion negatively correlated with illness uncertainty. A patient's age, educational level, work or not, and children's age correlated with needs for care. Age, illness uncertainty, and educational level were important predictors of the needs of care, with an explanatory power of 29.0%. In Conclusion, patients ≤40 years of age had greater illness uncertainty and needs for care than those who were >40 years of age. For younger patients newly diagnosed with cancer, medical professionals should take the initiative to provide detailed and complete information on breast cancer treatment plans, prognosis, and home self-care, which helps clarify the possible future treatments and results and further enables patients to acquire self-care skills and knowledge. [ABSTRACT FROM AUTHOR]

The strength of panel sheets can be increased by 2–3 times after hot stamping, and for high quality of hot stamped sheets, uniform cooling rate on the die face to quench the panel is needed. However, it is difficult for cooling water channels, commonly used for hot stamping dies, to dissipate heat evenly. In addition, dies are easily corroded by contact with water at high temperature. Thus, this study considers air cooling for the quenching process. The airflow can be applied to the sheet directly during the forming stage to cool and quench, eliminating difficulties with cooling channel design and providing more uniform cooling. Simulations and experiments were used to test the feasibility of air cooling for hot stamping with CSC-15B22 steel. A simple hot stamping tool with flat die face and either water or air cooling channels was used for testing, and results show that the both direct and indirect airflow can be used for hot stamping. With indirect air cooling, the cooling rate is sufficient for complete martensite transition, though the cooling rate is 40% lower than with indirect water cooling. To improve cooling efficiency of the air cooling system and obtain more uniform cooling, an air jet impingement cooling system (direct airflow cooling) was also tested. Results show that a similar cooling rate can be obtained in both indirect water cooling and the air jet impingement cooling. Thus, it is possible for air jet impingement cooling to provide hot stamping superior to water cooling. These results can be a reference for the design of new cooling systems for hot stamping dies. [ABSTRACT FROM AUTHOR]

Volunteer management practices have been shown to have positive effects on employees in terms of skill development, job success, organizational identity, and morale in the public, nonprofit, and corporate sectors. Despite considerable research on volunteering, questions remain about how management practices of volunteer programs may affect volunteer performance. Leveraging data comparing self-enrolled and corporate-recruited volunteer mentors into a large-scale online program for entrepreneurs, this study measures the impact of institutional support on volunteer intensity, persistence, and quality. It also presents a novel way to measure volunteer quality through sentiment analysis to measure the tone of online messages, an emerging statistical technique. Findings suggest that a high level of institutional support leads to higher quality mentor engagement, compared to self-enrolled volunteers, while a low level of support leads to mentor quality much lower than self-enrolled volunteers. [ABSTRACT FROM AUTHOR]

Modern industrial products require high precision and material strength. These have a greater effect on a die and so there is accelerating die failure during mass production. Die failure damages product accuracy so it must be detected in real time. This study develops a system that detects die failure directly from the servo press machine itself. The servo motor torque data and punch time data and press slide position data are used to detect the failure status of the die and punch. SUS304 and SAE1065 steel sheets were used as test pieces. The failure mode and the effect of failure on feedback data are studied to determine the feasibility of the detection mechanism. The results show that the punch time and the torque vary with the failure mode and failure grades. For SUS304 sheets, after 1000 cycles of artificial wear, the maximum torque is 9% greater than that for a punch that is not worn. For SAE1065 sheets, the torque is 4.4% greater for the same degree of punch failure. The punch time respectively increases by 26 ms and 22 ms for SUS304 and SAE1065. Using these results, a LabVIEW DAQ module with a servo stamping machine is used to construct an online wear detection system. The LabVIEW program is tested. The test results on the LabVIEW front panel agree well with previous results. This study shows that punch/die failure can be detected accurately using this real-time failure detection system. [ABSTRACT FROM AUTHOR]

The electrocatalytic properties of metal nanoparticles (NPs) strongly depend on their compositions and structures. Rational design of alloys and/or heterostructures provides additional approaches to modifying their surface geometric and electronic structures for optimized electrocatalytic performance. Here, a solution synthesis of freestanding intermetallic Au2Bi NPs, the heterostructures of Au2Bi/Bi hetero‐NPs, and their promoted electrocatalytic CO2 reduction reaction (CO2RR) performances were reported. It was revealed that the formation and in‐situ conversion of heterogeneous seeds (e. g., Au) were of vital importance for the formation of intermetallic Au2Bi and Au2Bi/Bi hetero‐NPs. It was also found that the Au components would act as the structure promoter moderating the binding strength for key intermediates on Bi surfaces. The alloying of Bi with Au and the formation of heterogeneous Au2Bi/Bi interfaces would create more surface active sites with modulated electronic structures and stronger adsorption strengths for key intermediates, promoting the CO2‐to‐HCOOH conversion with high activity and selectivity. This work presents a novel route for preparing intermetallic nanomaterials with modulated surface geometric/electric structures and promoting their electrocatalytic activities with alloying effects and interfacial effects. Such strategy may find wide application in catalyst design and synthesis for more electrocatalytic reactions. [ABSTRACT FROM AUTHOR]

Pulmonary hypertension should be preoperatively evaluated for optimal surgical planning to reduce surgical risk in lung cancer patients. Preoperative measurement of vascular diameter in computed tomography (CT) images is a noninvasive prediction method for pulmonary hypertension. However, the current estimation method, 2D manual arterial diameter measurement, may yield inaccurate results owing to low tissue contrast in non-contrast-enhanced CT (NECT). Furthermore, it provides an incomplete evaluation by measuring only the diameter of the arteries rather than the volume. To provide a more complete and accurate estimation, this study proposed a novel two-stage deep learning (DL) model for 3D aortic and pulmonary artery segmentation in NECT. In the first stage, a DL model was constructed to enhance the contrast of NECT; in the second stage, two DL models then applied the enhanced images for aorta and pulmonary artery segmentation. Overall, 179 patients were divided into contrast enhancement model (n = 59), segmentation model (n = 120), and testing (n = 20) groups. The performance of the proposed model was evaluated using Dice similarity coefficient (DSC). The proposed model could achieve 0.97 ± 0.66 and 0.93 ± 0.16 DSC for aortic and pulmonary artery segmentation, respectively. The proposed model may provide 3D diameter information of the arteries before surgery, facilitating the estimation of pulmonary hypertension and supporting preoperative surgical method selection based on the predicted surgical risks. [ABSTRACT FROM AUTHOR]

The presence of seismic anisotropy at the base of the Earth's mantle is well established, but there is no consensus on the deformation mechanisms in lower mantle minerals that could explain it. Strong anisotropy in magnesium post-perovskite (pPv) has been invoked, but different studies disagree on the dominant slip systems at play. Here, we aim to further constrain this by implementing the most recent results from atomistic models and high-pressure deformation experiments, coupled with a realistic composition and a 3-D geodynamic model, to compare the resulting deformation-induced anisotropy with seismic observations of the lowermost mantle. We account for forward and reverse phase transitions from bridgmanite (Pv) to pPv. We find that pPv with either dominant (001) or (010) slip can both explain the seismically observed anisotropy in colder regions where downwellings turn to horizontal flow, but only a model with dominant (001) slip matches seismic observations at the root of hotter large-scale upwellings. Allowing for partial melt does not change these conclusions, while it significantly increases the strength of anisotropy and reduces shear and compressional velocities at the base of upwellings. [ABSTRACT FROM AUTHOR]

In the era of rapid development in industry, an automatic production line is the fundamental and crucial mission for robotic pick-place. However, most production works for picking and placing workpieces are still manual operations in the stamping industry. Therefore, an intelligent system that is fully automatic with robotic pick-place instead of human labor needs to be developed. This study proposes a dynamic workpiece modeling integrated with a robotic arm based on two stereo vision scans using the fast point-feature histogram algorithm for the stamping industry. The point cloud models of workpieces are acquired by leveraging two depth cameras, type Azure Kinect Microsoft, after stereo calibration. The 6D poses of workpieces, including three translations and three rotations, can be estimated by applying algorithms for point cloud processing. After modeling the workpiece, a conveyor controlled by a microcontroller will deliver the dynamic workpiece to the robot. In order to accomplish this dynamic task, a formula related to the velocity of the conveyor and the moving speed of the robot is implemented. The average error of 6D pose information between our system and the practical measurement is lower than 7%. The performance of the proposed method and algorithm has been appraised on real experiments of a specified stamping workpiece. [ABSTRACT FROM AUTHOR]

This study aimed to analyze the association between elevated gamma‐glutamyl transpeptidase (GGT) and metabolic syndrome (MetS), hepatic steatosis, and fibrosis in patients with nonalcoholic fatty liver disease (NAFLD). From August 2013 to August 2018, a community‐based study was conducted in the northeastern part of Taiwan. Patients who underwent abdominal ultrasonography (US) and had no history of alcoholic liver disease were included. According to a US examination showing fatty liver degree, 1566 patients with NAFLD were divided into four groups: normal GGT, isolated GGT elevation, isolated alanine aminotransferase (ALT) elevation, and both GGT and ALT elevation groups. Further 1147 participants with normal serum ALT, GGT, and the abdominal US were included as the control group. GGT levels were associated with high sensitivity C‐reactive protein, lower adiponectin, diabetes mellitus, and chronic kidney disease. A stepwise increase in odds ratio (OR) for MetS was found in the normal GGT group (OR = 1.71), isolated GGT elevation group (OR = 3.06), isolated ALT elevation (OR = 4.00), and both GGT + ALT elevation group (OR = 4.17) than the control group. Linear regression analysis revealed a positive association between GGT/ALT value and hepatic steatosis degree, GGT value, and degree of hepatic fibrosis. Hence, GGT elevation is associated with MetS, hepatic steatosis, and fibrosis in patients with NAFLD. [ABSTRACT FROM AUTHOR]

Associations between hepatitis C virus (HCV) and chronic kidney disease (CKD) have been reported; however, differences of renal progression between general and CKD population remain to be elucidated in prospective studies. A total of 1179 participants, who have tested for anti-HCV antibody, were enrolled and prospectively followed for 3 years. The risks associated with HCV infection, in terms of incidence of CKD, annual estimated glomerular filtration rate (eGFR) changes and 50% decline of eGFR at 3-year from baseline, were compared between normal renal function subjects and CKD patients. Overall, 111 of 233 (47.6%) CKD patients and 167 of 946 (17.7%) non-CKD subjects had HCV infection. The crude incidence rates of CKD were 226.9 per 1000 person-years and 14.8 per 1000 person-years in in HCV and non-HCV infected patients, respectively. The adjusted hazard ratio of HCV infection for incident CKD was 7.9 (95% CI 5–12.7). The HCV-infected normal renal function subjects were independently associated with increased risks of eGFR decline in the 1-year, 2-year and 3-year, respectively. The risk associations remained significant in 50% decline of eGFR at 3 years models and in different subgroup analyses. The increases of risks of eGFR decline were also notorious among overall HCV-infected CKD patients. However, the risk associations were less prominent in subgroup analyses (elderly, women and diabetic patients). The findings highlighted the importance of viral diagnosis with not only prognostic but also public health implications for preserving kidney function. [ABSTRACT FROM AUTHOR]

Efficiently predicting the flow field and load in aerodynamic shape optimisation remains a highly challenging and relevant task. Deep learning methods have been of particular interest for such problems, due to their success in solving inverse problems in other fields. In the present study, U-net-based deep neural network (DNN) models are trained with high-fidelity datasets to infer flow fields, and then employed as surrogate models to carry out the shape optimisation problem, i.e. to find a minimal drag profile with a fixed cross-sectional area subjected to a two-dimensional steady laminar flow. A level-set method as well as Bézier curve method are used to parameterise the shape, while trained neural networks in conjunction with automatic differentiation are utilised to calculate the gradient flow in the optimisation framework. The optimised shapes and drag force values calculated from the flow fields predicted by the DNN models agree well with reference data obtained via a Navier–Stokes solver and from the literature, which demonstrates that the DNN models are capable not only of predicting flow field but also yielding satisfactory aerodynamic forces. This is particularly promising as the DNNs were not specifically trained to infer aerodynamic forces. In conjunction with a fast runtime, the DNN-based optimisation framework shows promise for general aerodynamic design problems. [ABSTRACT FROM AUTHOR]

A tailored tempering process, whereby the cooling rate for the sheet is controlled to form regions with very high strength and regions of reduced strength but increased ductility. In order to obtain the optimal mechanical properties for CSC-15B22 steel sheets that undergo tailored tempering, experimental and simulation method are used to examine the tempering process. The heated die section is heated from 150℃ to 500℃ to determine the effect of tooling temperature on the properties of the sheets. Results show that the section that is heated to a temperature of 150℃ is too strong to absorb energy due to an impact. The section that is heated to 500℃ shows a significant difference between the strength of the sheet for the heated and cooled sections of the tooling. The strength at the heated section is insufficient for vehicle B-pillars. For sheets that are heated to 350℃, a slight hot stamping effect is seen in the heated section of tooling. The strength of the steel sheet is increased and elongation is sufficient. An impact test result shows that if the tooling is heated to a temperature of 350℃, the formed steel sheet absorbs the greatest amount of impact energy. [ABSTRACT FROM AUTHOR]

Objectives: Near-pure lung adenocarcinoma (ADC) subtypes demonstrate strong stratification of radiomic values, providing basic information for pathological subtyping. We sought to predict the presence of high-grade (micropapillary and solid) components in lung ADCs using quantitative image analysis with near-pure radiomic values.Methods: Overall, 103 patients with lung ADCs of various histological subtypes were enrolled for 10-repetition, 3-fold cross-validation (cohort 1); 55 were enrolled for testing (cohort 2). Histogram and textural features on computed tomography (CT) images were assessed based on the "near-pure" pathological subtype data. Patch-wise high-grade likelihood prediction was performed for each voxel within the tumour region. The presence of high-grade components was then determined based on a volume percentage threshold of the high-grade likelihood area. To compare with quantitative approaches, consolidation/tumour (C/T) ratio was evaluated on CT images; we applied radiological invasiveness (C/T ratio > 0.5) for the prediction.Results: In cohort 1, patch-wise prediction, combined model (C/T ratio and patch-wise prediction), whole-lesion-based prediction (using only the "near-pure"-based prediction model), and radiological invasiveness achieved a sensitivity and specificity of 88.00 ± 2.33% and 75.75 ± 2.82%, 90.00 ± 0.00%, and 77.12 ± 2.67%, 66.67% and 90.41%, and 90.00% and 45.21%, respectively. The sensitivity and specificity, respectively, for cohort 2 were 100.0% and 95.35% using patch-wise prediction, 100.0% and 95.35% using combined model, 75.00% and 95.35% using whole-lesion-based prediction, and 100.0% and 69.77% using radiological invasiveness.Conclusion: Using near-pure radiomic features and patch-wise image analysis demonstrated high levels of sensitivity and moderate levels of specificity for high-grade ADC subtype-detecting.Key Points: • The radiomic values extracted from lung adenocarcinoma with "near-pure" histological subtypes provide useful information for high-grade (micropapillary and solid) components detection. • Using near-pure radiomic features and patch-wise image analysis, high-grade components of lung adenocarcinoma can be predicted with high sensitivity and moderate specificity. • Using near-pure radiomic features and patch-wise image analysis has potential role in facilitating the prediction of the presence of high-grade components in lung adenocarcinoma prior to surgical resection. [ABSTRACT FROM AUTHOR]

The demand for sustainable energy has motivated the development of artificial photosynthesis. Yet the catalyst and reaction interface designs for directly fixing permanent gases (e.g. CO2, O2, N2) into liquid fuels are still challenged by slow mass transfer and sluggish catalytic kinetics at the gas-liquid-solid boundary. Here, we report that gas-permeable metal-organic framework (MOF) membranes can modify the electronic structures and catalytic properties of metal single-atoms (SAs) to promote the diffusion, activation, and reduction of gas molecules (e.g. CO2, O2) and produce liquid fuels under visible light and mild conditions. With Ir SAs as active centers, the defect-engineered MOF (e.g. activated NH2-UiO-66) particles can reduce CO2 to HCOOH with an apparent quantum efficiency (AQE) of 2.51% at 420 nm on the gas-liquid-solid reaction interface. With promoted gas diffusion at the porous gas-solid interfaces, the gas-permeable SA/MOF membranes can directly convert humid CO2 gas into HCOOH with a near-unity selectivity and a significantly increased AQE of 15.76% at 420 nm. A similar strategy can be applied to the photocatalytic O2-to-H2O2 conversions, suggesting the wide applicability of our catalyst and reaction interface designs. Photoreduction of permanent gas faces challenges in reactant diffusion and activation at the three-phase interface. Here the authors showed porous metal-organic framework membranes decorated by metal single atoms can boost the photoreduction of CO2 and O2 at the high-throughput gas-solid interface. [ABSTRACT FROM AUTHOR]

Vibrational spectra of the methyl groups in mono-methylamine (MMA), dimethylamine (DMA), and trimethylamine (TMA) monomers and their clusters were measured in three experimental set-ups to capture their complex spectral features as a result of bend/umbrella-stretch Fermi resonance (FR). Multiple bands were observed between 2800 and 3000 cm−1 corresponding to the methyl groups for MMA and DMA. On the other hand, the corresponding spectrum of TMA is relatively simple, exhibiting only four prominent bands in the same frequency window, even though TMA has a larger number of methyl groups. The discrete variable representation (DVR) based ab initio anharmonic algorithm with potential energy surface (PES) at CCSD/aug-cc-pVDZ quality is able to capture all the experimentally observed spectral features across all three amines, and the constructed vibrational Hamiltonian was used to analyze the couplings that give rise to the observed FR patterns. It was observed that the vibrational coupling among CH stretch modes on different methyl groups is weak (less than 2 cm−1) and stronger vibrational coupling is found to localize within a methyl group. In MMA and DMA, the complex feature between 2850 and 2950 cm−1 is a consequence of closely packed overtone states that gain intensities by mixing with the stretching modes. The simplification of the spectral pattern of TMA can be understood by the red-shift of the symmetric CH3 stretching modes by about 80 cm−1 relative to MMA, which causes the symmetric CH3 stretch to shift outside the FR window. [ABSTRACT FROM AUTHOR]

The development of artificial synapses is inspired by the energy‐efficient recognition ability of the central nervous system of living organisms and is proposed for use as the basic building units of next‐generation neuromorphic computing networks. Herein, the perovskite/MoO3/Ag synaptic device exhibits very uniform electrical characteristics, a low operation voltage, and linear and repeatable analog switching. Important synaptic functions such as paired‐pulse facilitation (PPF) and short‐ and long‐term potentiation (STP/LTP) are all successfully and stably implemented in the device. The diffusion of Ag+ and I− ions is believed to contribute to the synaptic behavior of the device. Furthermore, the uniform and stable volatile characteristics are utilized in a proof‐of‐concept reservoir‐computing‐based simulation program using all the experimental parameters; the results strongly suggest that the neuromorphic computing that utilizes such components can simultaneously reduce the circuitry complexity and increase its recognition accuracy with noisy inputs. The findings of this work promise to significantly facilitate the utilization of highly homogeneous vacuum‐deposited perovskite/metal oxide structures in high‐performance neuromorphic computing systems. [ABSTRACT FROM AUTHOR]