Quick Identification of ABC Trilayer Graphene at Nanoscale Resolution via a Near-field Optical Route

ABC-stacked trilayer graphene has exhibited a variety of correlated phenomena owing to its relatively flat bands and gate-tunable bandgap. However, convenient methods are still lacking for identifying ABC graphene with nanometer-scale resolution. Here we demonstrate that the scanning near-field optical microscope (SNOM) working in ambient conditions can provide quick recognition of ABC trilayer graphene with no ambiguity and excellent resolution (~20 nm). The recognition is based on the difference in their near-field infrared (IR) responses between the ABA and ABC trilayers. We show that in most frequencies, the response of the ABC trilayer is weaker than the ABA trilayer. However, near the graphene phonon frequency (~1585 cm-1), ABC's response increases dramatically when gated and exhibits a narrow and sharp Fano-shape resonant line, whereas the ABA trilayer is largely featherless. Consequently, the IR contrast between ABC and ABA becomes reversed and can even be striking (ABC/ABA~3) near the graphene phonon frequency. The observed near-field IR features can serve as a golden rule to quickly distinguish ABA and ABC trilayers with no ambiguity, which could largely advance the exploration of correlation physics in ABC-stacked trilayer graphene

Photochemical production of nitrous acid on glass sample manifold surface

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/94760/1/grl15858.pd

High-density genetic linkage mapping reveals low stability of QTLs across environments for economic traits in Eucalyptus

IntroductionEucalyptus urophylla, E. tereticornis and their hybrids are the most important commercial forest tree species in South China where they are grown for pulpwood and solid wood production. Construction of a fine-scale genetic linkage map and detecting quantitative trait loci (QTL) for economically important traits linked to these end-uses will facilitate identification of the main candidate genes and elucidate the regulatory mechanisms.MethodA high-density consensus map (a total of 2754 SNPs with 1359.18 cM) was constructed using genotyping by sequencing (GBS) on clonal progenies of E. urophylla × tereticornis hybrids. QTL mapping of growth and wood property traits were conducted in three common garden experiments, resulting in a total of 108 QTLs. A total of 1052 candidate genes were screened by the efficient combination of QTL mapping and transcriptome analysis.ResultsOnly ten QTLs were found to be stable across two environments, and only one (qSG10Stable mapped on chromosome 10, and associated with lignin syringyl-to-guaiacyl ratio) was stable across all three environments. Compared to other QTLs, qSG10Stable explained a very high level of phenotypic variation (18.4–23.6%), perhaps suggesting that QTLs with strong effects may be more stably inherited across multiple environments. Screened candidate genes were associated with some transcription factor families, such as TALE, which play an important role in the secondary growth of plant cell walls and the regulation of wood formation.DiscussionWhile QTLs such as qSG10Stable, found to be stable across three sites, appear to be comparatively uncommon, their identification is likely to be a key to practical QTL-based breeding. Further research involving clonally-replicated populations, deployed across multiple target planting sites, will be required to further elucidate QTL-by-environment interactions

Influence of academic stress and school bullying on self-harm behaviors among Chinese middle school students: The mediation effect of depression and anxiety

ObjectiveThe purpose of this study was to explore the relationship between academic stress, school bullying and self-harm behaviors among Chinese middle school students and to further explore the impact of anxiety and depression on this relationship.MethodsThe students (aged 12–16 years) in a middle school in Changsha city were invited to respond to a questionnaire through an online platform. The Patient Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder-7 (GAD-7) were used to assess the severity of anxiety and depressive symptoms, respectively. The experience of being bullied, academic stress, and self-harm behaviors were assessed using several questions on the basis of previous studies.ResultsA total of 1,313 middle school students completed the study, and 3.40% and 4.10% of them reported suicide attempts (SAs) and non-suicidal self-injury (NSSI), respectively. Univariate logistic regression analysis revealed that anxiety symptoms (OR = 1.23, 95% CI: 1.18–1.28; OR = 1.25, 95% CI: 1.19–1.31), depressive symptoms (OR = 1.20, 95% CI: 1.16–1.25; OR = 1.26, 95% CI: 1.20–1.31), school bullying (OR = 3.8, 95% CI: 2.11–6.89; OR = 2.76, 95% CI: 1.39–5.47), and academic stress (OR = 2.20, 95% CI: 1.27–3.80; OR = 3.80, 95% CI: 1.20–7.25) were common factors of NSSI and SAs. In addition, depressive symptoms showed a mediating effect on the association of school bullying and academic stress with SAs or NSSI, and anxiety symptoms showed a mediating effect on the association of school bullying and academic stress with NSSI only.ConclusionAppropriate strategies are needed to reduce academic pressure and prevent school bullying. Meanwhile, negative emotions such as depression and anxiety should be evaluated and intervened in to prevent self-harm behaviors among middle school students

Determination of photochemically produced hydroxyl radicals in seawater and freshwater

A variety of short-lived, reactive chemical species (i.e. free radicals and excited state species) are known to be photochemically produced in natural waters. Some of these transients may strongly affect chemical and biological processes, and they have been implicated in the degradation of organic pollutants and natural organic compounds in aqueous environments. Previous studies demonstrated that the highly reactive hydroxyl radical (OH) is photochemically formed in seawater. However, the quantitative importance of this key species in the sea has not been previously studied because of past analytical limitations. By using a highly sensitive probe based on α-H atom abstraction from methanol, we were able to measure production rates and steady-state concentrations of photochemically produced OH radicals in coastal and open ocean seawater and freshwaters. The validity of the method was tested by intercalibrating with an independent, OH-specific reaction, hydroxylation of benzoic acid, and also by competition kinetics experiments. Our OH production rates and steady-state concentrations for freshwaters are in excellent agreement with those measured by previous investigators for similar waters. In contrast, for seawater, the values we measured are 1–3 orders of magnitude higher than previously predicted by models, indicating that there is a major unknown photochemical OH source (s) in seawater

Research on Wear Detection of End Milling Cutter Edge Based on Image Stitching

Obtaining the complete wear state of the milling cutter during processing can help predict tool life and avoid the impact of tool breakage. A cylindrical model of tool collection is proposed, which uses the collected partial pictures of the side edge to construct a panoramic picture of tool wear. After evaluating the splicing accuracy, the fully convolutional neural network (FCN) segmentation algorithm of the VGG16 structure is used to segment the panorama of the side edge of the end mill after splicing. The FCN model is built using Tensorflow to complete the image segmentation training and testing of the side edge wear area. Experimental results show that the FCN model can segment the side wear image and effectively solve the illumination change problem and different tool wear differences. Compared with the Otsu threshold adaptive segmentation algorithm and K-means clustering algorithm, the error of the extracted wear value is 1.34% to 8.93%, and the average error rate is 5.23%. This method can obtain a more intuitive panorama of the cutter side edge wear of the end milling and provide technical support for improving tool utilization rate, machining quality, and tool selection and optimization

A lvq-based neural network anti-spam email approach

Abstract: Along with wide application of e-mail nowadays, many spare e-mails flood into people's email inboxes and bring catastrophe to their study and work. This paper presents a novel anti-spare e-mail filter based-LVQ network in terms of spare e-mails which are mainly made up of several kinds commercial or political spare emails at present. Our experiment has proved that the filter based on LVQ is superior to Bayes-based and BP-based approaches in total performances apparently