Robust, Ultrasmooth Fluorinated Lithium Metal Interphase Feasible via Lithiophilic Graphene Quantum Dots for Dendrite-Less Batteries.

Dendrite growth and in-homogeneous solid electrolyte interphase (SEI) buildup of Li metal anodes hinder the longtime discharge-charge cycling and safety in secondary metal batteries. Here, the authors report an in-situ restructured artificial lithium/electrolyte SEI exposing an ultrasmooth and thin layer mediated through graphene quantum dots (GQDs). The reformed artificial interphase comprises a mixture of organic/inorganic-rich compositions alike as mosaic interphase, albeit the synergistic effect mediated via hydroxylated GQDs involving redeposition-borne lithium, and its accumulated salts, facilitate a homogeneous and ultrasmooth near fluorine-rich interfacial environment ensuring a facile lithium-ion (Li-ion) diffusion and dendritic-free nature. As a result, symmetrical graphene dots-lithium cells enable a dendrite-less operation up to 2000 h with good cycling stability and capacity retention at current densities 1 and 5 mA cm-2 compared to bare lithium. The well-established fluorinated interface engenders a high reversible capacity and stable performance during the initial and long-term cycles upon configuring in lithium-sulfur (Li-S) cells. Thus, the authors' work illuminates the direction toward achieving dendritic-free smooth and robust metal anodes through manipulating and restructuring the critical SEI chemical components.

Using Transcriptome Analysis to Explore Gray Mold Resistance-Related Genes in Onion (Alliumcepa L.).

Gray mold disease caused by Botrytis in onions (Allium cepa L.) during growth and storage negatively affects their yield and quality. Exploring the genes related to gray mold resistance in onion and their application to the breeding of resistant onion lines will support effective and ecological control methods of the disease. Here, the genetic relationship of 54 onion lines based on random amplified polymorphic DNA (RAPD) and in vitro-cultured onion lines infected with gray mold were used for screening resistance and susceptibility traits. Two genetically related onion lines were selected, one with a resistant and one with a susceptible phenotype. In vitro gray mold infection was repeated with these two lines, and leaf samples were collected for gene expression studies in time series. Transcript sequences obtained by RNA sequencing were subjected to DEG analysis, variant analysis, and KEGG mapping. Among the KEGG pathways, 'α-linoleic acid metabolism' was selected because the comparison of the time series expression pattern of Jasmonate resistant 1 (JAR1), Coronatine-insensitive protein 1 (COI 1), and transcription factor MYC2 (MYC2) genes between the resistant and susceptible lines revealed its significant relationship with gray-mold-resistant phenotypes. Expression pattern and SNP of the selected genes were verified by quantitative real-time PCR and high-resolution melting (HRM) analysis, respectively. The results of this study will be useful for the development of molecular marker and finally breeding of gray-mold-resistant onions.

Gate-controlled gas sensor utilizing 1D-2D hybrid nanowires network.

Novel gas sensors that work at room temperature are attracting attention due to their low energy consumption and stability in the presence of toxic gases. However, the development of sensing characteristics at room temperature is still a primary challenge. Diverse reaction pathways and low adsorption energy for gas molecules are required to fabricate a gas sensor that works at room temperature with high sensitivity, selectivity, and efficiency. Therefore, we enhanced the gas sensing performance at room temperature by constructing hybridized nanostructure of 1D-2D hybrid of SnSe2 layers and SnO2 nanowire networks and by controlling the back-gate bias (Vg = 1.5 V). The response time was dramatically reduced by lowering the energy barrier for the adsorption on the reactive sites, which are controlled by the back gate. Consequently, we believe that this research could contribute to improving the performance of gas sensors that work at room temperature.

Comparison of Concrete Creep in Compression, Tension, and Bending under Drying Condition.

Three types of creep experiments of compression, tension, and bending were implemented to identify quantitative relations among the three types of creep under drying atmospheric conditions. In case of the bending creep experiment, two types of unreinforced concrete beams with similar dimensions were cast for use in the beam creep and shrinkage tests. The variations in the shrinkage strain within the beam depth were measured to evaluate the effect of the shrinkage variations on the bending creep strain. The beam creep strain measured within the beam depth was composed of uniform and skewed parts. The skewed parts of the creep strain were found to be dominant whereas the uniform parts were small enough to be neglected in the bending creep evaluation. This indicated that the compressive bending creep at the top surface was close to the tensile bending creep at the bottom surface. The ratios of tensile and bending creep strains to compressive creep strain were approximately 2.9 and 2.3, respectively, and the ratio of bending creep strain to tensile creep strain was approximately 0.8. Particular attention is laid on the close agreement between tensile and compressive bending creep strains even if the creep in tension is 2.9 times larger than the creep strain in compression.

Machine Learning Application for Rupture Risk Assessment in Small-Sized Intracranial Aneurysm.

The assessment of rupture probability is crucial to identifying at risk intracranial aneurysms (IA) in patients harboring multiple aneurysms. We aimed to develop a computer-assisted detection system for small-sized aneurysm ruptures using a convolutional neural network (CNN) based on images of three-dimensional digital subtraction angiography. A retrospective data set, including 368 patients, was used as a training cohort for the CNN using the TensorFlow platform. Aneurysm images in six directions were obtained from each patient and the region-of-interest in each image was extracted. The resulting CNN was prospectively tested in 272 patients and the sensitivity, specificity, overall accuracy, and receiver operating characteristics (ROC) were compared to a human evaluator. Our system showed a sensitivity of 78.76% (95% CI: 72.30%-84.30%), a specificity of 72.15% (95% CI: 60.93%-81.65%), and an overall diagnostic accuracy of 76.84% (95% CI: 71.36%-81.72%) in aneurysm rupture predictions. The area under the ROC (AUROC) in the CNN was 0.755 (95% CI: 0.699%-0.805%), better than that obtained from a human evaluator (AUROC: 0.537; p < 0.001). The CNN-based prediction system was feasible to assess rupture risk in small-sized aneurysms with diagnostic accuracy superior to human evaluators. Additional studies based on a large data set are necessary to enhance diagnostic accuracy and to facilitate clinical application.

Rate-Type Age-Dependent Constitutive Formulation of Concrete Loaded at an Early Age.

A general formulation framework for an age-dependent constitutive equation of concrete is presented to account for the development of the elastic modulus at an early age. This is achieved by expanding the total stress vs. strain relation with respect to the time-varying elastic modulus. Two types of constitutive formulation frameworks are derived depending on whether (or not) the time-varying effect of the elastic modulus was taken into account in the linearized series expansion. The causes for the age-dependent deformations under sustained loads are defined in the formulation based on the two internal mechanisms of delayed elasticity and the ageing phenomenon. The ageing phenomenon is incorporated in a conventional delayed strain concept in terms of the variable elastic modulus with time. Four cases of age-dependent constitutive equations are formulated within the presented formulation framework by employing different types of creep models. The mechanical characteristics of the terms that comprise the various constitutive equations are examined and compared. Numerical application of the time-dependent test results of cylindrical specimens indicate that the creep formulation that considered the elastic modulus development showed a good agreement with the experimental result while the formulation that did not consider the elastic modulus development underestimated the result by 15%.

Hyperuricemia and risk of increased arterial stiffness in healthy women based on health screening in Korean population.

Hyperuricemia is a risk factor for cardiovascular disease and is associated with increased arterial stiffness in high-risk populations. However, given the possible sex-related differences in the prevalence of hyperuricemia, the association between elevated serum uric acid (SUA) level and increased arterial stiffness has yielded conflicting results. We investigated the relationship between SUA and arterial stiffness in asymptomatic healthy subjects who underwent a health examination. Subjects who underwent a comprehensive health examination were enrolled. After exclusion of extensive confounding factors, 2,704 healthy subjects with coronary calcium score < 100 were evaluated in the final analysis. All subjects underwent brachial-ankle pulse wave velocity (baPWV) to detect arterial stiffness. The SUA was divided into quartiles for its association with arterial stiffness and was analyzed separately for men and women. The mean SUA level was significantly lower in women than in men. The baPWV was significantly elevated in subjects with the highest quartile of SUA in women, but not in men. After adjusting for age, smoking, systolic blood pressure, body mass index, estimated glomerular filtration rate, fasting plasma glucose, high-density lipoprotein-cholesterol, low-density lipoprotein-cholesterol, and coronary artery calcium score, the highest quartile of SUA in women was significantly associated with increased risk of high baPWV compared with the lowest quartile of SUA (OR = 1.7, p = 0.018), whereas in men, SUA level was not associated with high baPWV. Our study showed that elevated SUA is independently associated with increased baPWV in healthy Korean women, but not in men.

Measuring the value of air quality: application of the spatial hedonic model.

This study applies a hedonic model to assess the economic benefits of air quality improvement following the 1990 Clean Air Act Amendment at the county level in the lower 48 United States. An instrumental variable approach that combines geographically weighted regression and spatial autoregression methods (GWR-SEM) is adopted to simultaneously account for spatial heterogeneity and spatial autocorrelation. SEM mitigates spatial dependency while GWR addresses spatial heterogeneity by allowing response coefficients to vary across observations. Positive amenity values of improved air quality are found in four major clusters: (1) in East Kentucky and most of Georgia around the Southern Appalachian area; (2) in a few counties in Illinois; (3) on the border of Oklahoma and Kansas, on the border of Kansas and Nebraska, and in east Texas; and (4) in a few counties in Montana. Clusters of significant positive amenity values may exist because of a combination of intense air pollution and consumer awareness of diminishing air quality.

Valuation of spatial configurations and forest types in the southern appalachian highlands.

Site-specific estimates of the values of spatial configuration and forest composition are presented. Amenity values of forest patches are found to vary the most by urban and sprawling development patterns of specific areas and forest types. For example, smaller patches of deciduous forest are more highly valued in the urban and sprawling areas of Greensboro, North Carolina, whereas larger patches of deciduous forest are more highly valued in the urban and sprawling areas of Greenville, South Carolina. Within the Greenville and Greensboro areas, visible landscape complexity is highly valued for deciduous and evergreen forest patches, whereas lower visible landscape complexity, i.e., smoothly trimmed forest patch boundaries, is highly valued for mixed forest patches.