Process-Oriented Evaluation of Climate and Weather Forecasting Models

Realistic climate and weather prediction models are necessary to produce confidence in projections of future climate over many decades and predictions for days to seasons. These models must be physically justified and validated for multiple weather and climate processes. A key opportunity to accelerate model improvement is greater incorporation of process-oriented diagnostics (PODs) into standard packages that can be applied during the model development process, allowing the application of diagnostics to be repeatable across multiple model versions and used as a benchmark for model improvement. A POD characterizes a specific physical process or emergent behavior that is related to the ability to simulate an observed phenomenon. This paper describes the outcomes of activities by the Model Diagnostics Task Force (MDTF) under the NOAA Climate Program Office (CPO) Modeling, Analysis, Predictions and Projections (MAPP) program to promote development of PODs and their application to climate and weather prediction models. MDTF and modeling center perspectives on the need for expanded process-oriented diagnosis of models are presented. Multiple PODs developed by the MDTF are summarized, and an open-source software framework developed by the MDTF to aid application of PODs to centers’ model development is presented in the context of other relevant community activities. The paper closes by discussing paths forward for the MDTF effort and for community process-oriented diagnosis

Classification of mild Parkinson’s disease: data augmentation of time-series gait data obtained via inertial measurement units

Abstract Data-augmentation methods have emerged as a viable approach for improving the state-of-the-art performances for classifying mild Parkinson’s disease using deep learning with time-series data from an inertial measurement unit, considering the limited amount of training datasets available in the medical field. This study investigated effective data-augmentation methods to classify mild Parkinson’s disease and healthy participants with deep learning using a time-series gait dataset recorded via a shank-worn inertial measurement unit. Four magnitude-domain-transformation and three time-domain-transformation data-augmentation methods, and four methods involving mixtures of the aforementioned methods were applied to a representative convolutional neural network for the classification, and their performances were compared. In terms of data-augmentation, compared with baseline classification accuracy without data-augmentation, the magnitude-domain transformation performed better than the time-domain transformation and mixed-data augmentation. In the magnitude-domain transformation, the rotation method significantly contributed to the best performance improvement, yielding accuracy and F1-score improvements of 5.5 and 5.9%, respectively. The augmented data could be varied while maintaining the features of the time-series data obtained via the sensor for detecting mild Parkinson’s in gait; this data attribute may have caused the aforementioned trend. Notably, the selection of appropriate data extensions will help improve the classification performance for mild Parkinson’s disease

Identification and characterization of ncRNA-associated ceRNA networks in Arabidopsis leaf development

Abstract Background Leaf development is a complex biological process that is accompanied by wide transcriptional changes. Many protein-coding genes have been characterized in plant leaves, but little attention has been given to noncoding RNAs (ncRNAs). Moreover, increasing evidence indicates that an intricate interplay among RNA species, including protein-coding RNAs and ncRNAs, exists in eukaryotic transcriptomes, however, it remains elusive in plant leaves. Results We detected novel ncRNAs, such as circular RNAs (circRNAs) and long noncoding RNAs (lncRNAs), and further constructed and analyzed their associated competitive endogenous RNA (ceRNA) networks in Arabidopsis leaves. Transcriptome profiling showed extensive changes during leaf development. In addition, comprehensive detection of circRNAs in other plant leaves suggested that circRNAs are widespread in plant leaves. To investigate the complex post-transcriptional interactions in Arabidopsis leaves, we constructed a global circRNA/lncRNA-associated ceRNA network. Functional analysis revealed that ceRNAs were highly correlated with leaf development. These ceRNAs could be divided into six clusters, which were enriched for different functional classes. Stage-specific ceRNA networks were further constructed and comparative analysis revealed different roles of stage common and specific hub ceRNAs. Conclusions Our results demonstrate that understanding the ceRNA interactions will lead insights into gene regulations implicated in leaf development

The roles of cross-talk epigenetic patterns in<i>Arabidopsis thaliana</i>

The epigenetic mechanisms, including histone modifications, DNA cytosine methylation, histone variants and noncoding RNAs (ncRNAs), play a key role in determining transcriptional outcomes. Recently, many studies have demonstrated that the different epigenetic mechanisms interplay with each other rather than work independently. In this article, we outline a framework for how different epigenetic mechanisms work with each other in Arabidopsis thaliana. We build a network of cross-talk between chromatin marks based on six classes of cross-talk interactions. The first pattern details coordinated modifications that act together to enhance or repress gene expression. The second pattern details bivalent modifications that act antagonistically toward gene expression. The third pattern is for unilateral promotion of one modification by the existence of another modification. The fourth pattern is for unilateral inhibition of one modification by another modification. The fifth pattern is for mutual inhibitory patterns. The sixth pattern is for epigenetic modifications that appear independent. We also explore the mutual regulation between chromatin marks and ncRNAs in various ways. These regulations can be divided into six parts: how ncRNA affects the binding of chromatin mark, such as miR2Epi, siR2Epi and lncR2Epi; how chromatin mark regulates ncRNA, such as Epi2miR, Epi2siR and Epi2lncR. A comprehensive network of cross-talk between different epigenetic mechanisms will help in fully understanding the functional roles and biological impacts of epigenetic regulation

Effects of Ar- and Ar/O2-plasma-treated amorphous and crystalline polymer surfaces revealed by ToF-SIMS and principal component analysis

The effects of argon (Ar) and a mixture of Ar and oxgyen(Ar/O2) plasmas on amorphous and semi-crystalline poly(bisphenol A hexane ether) thin films were investigated by time-of-flight secondary ion mass spectroscopy (ToF-SIMS) and principal component analysis (PCA). PCA results of the ToF-SIMS spectra indicate that an Ar/O2 plasma produced less physical sputtering and had a higher chemical reactivity than did an Ar plasma, regardless of whether an amorphous or a crystalline surface was involved. However, the chemical differences between the Ar- and Ar/O2-plasma-treated semi-crystalline films were much smaller. The observed results can be explained by the higher resistance of the polymer crystalline regions to physical sputtering and chemical etching. Copyright (c) 2013 John Wiley & Sons, Ltd

Hollow Interior Structure of Spin-Coated Polymer Thin Films Revealed by ToF-SIMS Three-Dimensional Imaging

Surface patterns were observed on spin-coated poly(bisphenol A decane ether) (BA-C10) films prepared with chloroform and tetrahydrofuran as the solvents. The interior structure of these surface patterns were analyzed using a time-of-flight secondary ion mass spectrometry (ToF-SIMS) equipped with a bismuth cluster source for ion imaging and a C-60(+) cluster source for depth profiling. For the first time, the surface patterns have been shown to be hollow rather than solid using ToF-SIMS three-dimensional (3D) analysis and optical techniques. Moreover, the microarea depth profiling analysis indicated that the hollow structure was sandwiched between two polymer layers rather than sitting on the substrate. The height of the hollow structure and the thicknesses of the polymer layers above and below the hollow structure were also estimated from the depth profiling results

The relationship between end-group concentrations and stability of spin-coated thin polymer films investigated by ToF-SIMS depth profiling

Stable and unstable spin-coated polymer films were prepared using various solvents and substrates. The relationship between polymer end-group concentrations and stability of spin-coated polymer films was revealed by time-of-flight secondary ion mass spectrometry depth profiling. A high concentration of bromine end groups at the interface between the polymer and the substrate helped to prevent the dewetting of films. In contrast, the bromine end groups were found to be more evenly distributed in unstable thin films. The extent to which the bromine end groups segregate to the interface depended on the competitive interactions between the polymer, the solvent and the substrate. Stronger polymer-solvent and solvent-substrate interactions prevented the segregation of the bromine end groups to the interface, resulting in unstable polymer films. Copyright (c) 2013 John Wiley & Sons, Ltd

Non-coding RNAs and Their Roles in Stress Response in Plants

Eukaryotic genomes encode thousands of non-coding RNAs (ncRNAs), which play crucial roles in transcriptional and post-transcriptional regulation of gene expression. Accumulating evidence indicates that ncRNAs, especially microRNAs (miRNAs) and long ncRNAs (lncRNAs), have emerged as key regulatory molecules in plant stress responses. In this review, we have summarized the current progress on the understanding of plant miRNA and lncRNA identification, characteristics, bioinformatics tools, and resources, and provided examples of mechanisms of miRNA- and lncRNA-mediated plant stress tolerance. Keywords: lncRNA, miRNA, Stress response, RNA-directed DNA methylation, Small RN