Software for Visualization and Coordination of the Distributed Simulation Modeling Process

Simulation modeling projects commonly involve distributed team collaboration. It is currently difficult to perform collaboration in distributed modeling process for two reasons: 1) Simulation modeling in general requires modelers to manage complexities (such as tracking model revisions, recording scenario assumptions and organizing external artifacts) related to the model. 2) Distributed collaboration requires collaborators to maintain change awareness. While proper information technology support is known to lessen the difficulties of collaborations, there is limited software support for complexity management in generic modeling process and change awareness in distributed collaboration, therefore require tremendous amount of effort in management and communication. This thesis describes a new system that supports distributed modeling process. The system provides modeling repositories to help manage modeling complexities and a visual workspace to provide change awareness information. The system has been shown to substantially reduce modeling effort in distributed modeling, is extensible and easy to use

Fingerprint analysis of Resina Draconis by ultra-performance liquid chromatography

Abstract Background Resina Draconis, a bright red resin derived from Dracaena cochinchinensis, is a traditional medicine used in China. To improve its quality control approach, an ultra-performance liquid chromatography (UPLC) fingerprint method was developed for rapidly evaluating the quality of Resina Draconis. Methods The precision, repeatability and stability of the proposed UPLC method were validated in the study. Twelve batches of Resina Draconis samples from various sources were analyzed by the present UPLC method. Common peaks in the chromatograms were adopted to calculate their relative retention time and relative peak area. The chromatographic data were processed by Similarity Evaluation System for Chromatographic Fingerprint of Traditional Chinese Medicine software (Version 2004 A) for similarity analysis. Results The present UPLC method demonstrated a satisfactory precision, repeatability and stability. The analysis time of the present UPLC method was shortened to 30 min, compared with that of the conventional HPLC method was 50 min. The similarities of the 12 Resina Draconis samples were 0.976, 0.993, 0.955, 0.789, 0.989, 0.995, 0.794, 0.994, 0.847, 0.987, 0.997, 0.986, respectively, which indicated that the samples were certainly regionally different. The similarities of the 12 samples showed more similar pattern except for samples 4, 7 and 9. Such variation in similarity may presumably be attributed to differences in source. Conclusions Compared with the conventional HPLC method, the present UPLC method showed several advantages including shorter analysis time, higher resolution and better separation performance. The UPLC fingerprinting established in the present paper provides a valuable reference for the quality control of Resina Draconis

MOESM1 of Fingerprint analysis of Resina Draconis by ultra-performance liquid chromatography

Additional file 1: Table S1. The source of the tested samples

Self-supervised Implicit Glyph Attention for Text Recognition

The attention mechanism has become the de facto module in scene text recognition (STR) methods, due to its capability of extracting character-level representations. These methods can be summarized into implicit attention based and supervised attention based, depended on how the attention is computed, i.e., implicit attention and supervised attention are learned from sequence-level text annotations and character-level bounding box annotations, respectively. Implicit attention, as it may extract coarse or even incorrect spatial regions as character attention, is prone to suffering from an alignment-drifted issue. Supervised attention can alleviate the above issue, but it is category-specific, which requires extra laborious character-level bounding box annotations and would be memory-intensive when the number of character categories is large. To address the aforementioned issues, we propose a novel attention mechanism for STR, self-supervised implicit glyph attention (SIGA). SIGA delineates the glyph structures of text images by jointly self-supervised text segmentation and implicit attention alignment, which serve as the supervision to improve attention correctness without extra character-level annotations. Experimental results demonstrate that SIGA performs consistently and significantly better than previous attention-based STR methods, in terms of both attention correctness and final recognition performance on publicly available context benchmarks and our contributed contextless benchmarks

Analysis of spatial–temporal dynamic distribution and related factors of tuberculosis in China from 2008 to 2018

Abstract Through spatial–temporal scanning statistics, the spatial–temporal dynamic distribution of pulmonary tuberculosis incidence in 31 provinces and autonomous regions of China from 2008 to 2018 is obtained, and the related factors of spatial–temporal aggregation of tuberculosis in China are analyzed to provide strong scientific basis and data support for the prevention and control of pulmonary tuberculosis. This is a retrospective study, using spatial epidemiological methods to reveal the spatial–temporal clustering distribution characteristics of China's tuberculosis epidemic from 2008 to 2018, in which cases data comes from the China Center for Disease Control and prevention. Office Excel is used for general statistical description, and the single factor correlation analysis adopts χ 2 Test (or trend χ 2 Inspection). Retrospective discrete Poisson distribution space time scanning statistics of SaTScan 9.6 software are used to analyze the space time dynamic distribution of tuberculosis incidence in 31 provinces, cities and autonomous regions in China from 2008 to 2018. ArcGIS 10.2 software is used to visualize the results. The global spatial autocorrelation analysis adopts Moran's I of ArcGIS Map(Monte Carlo randomization simulation times of 999) is used to analyze high-risk areas, low-risk areas and high-low risk areas. From 2008 to 2018, 10,295,212 cases of pulmonary tuberculosis were reported in China, with an average annual incidence rate of 69.29/100,000 (95% CI: (69.29 ± 9.16)/100,000). The annual GDP (gross domestic product) of each province and city showed an upward trend year by year, and the number of annual medical institutions in each province and city showed a sharp increase in 2009, and then tended to be stable; From 2008 to 2018, the national spatiotemporal scanning statistics scanned a total of 6 clusters, including 23 provinces and cities. The national high-low spatiotemporal scanning statistics of the number of pulmonary tuberculosis cases scanned a total of 2 high-risk and low-risk clusters. The high-risk cluster included 8 provinces and cities, and the low-risk cluster included 12 provinces and cities. The global autocorrelation Moran's I index of the incidence rate of pulmonary tuberculosis in all provinces and cities was greater than the expected value (E (I) = −0.0333); The correlation analysis between the average annual GDP and the number of pulmonary tuberculosis cases in each province and city from 2008 to 2018 was statistically significant. From 2008 to 2018, the spatial and temporal scanning and statistical scanning areas of tuberculosis incidence in China were mainly concentrated in the northwest and southern regions of China. There is an obvious positive spatial correlation between the annual GDP distribution of each province and city, and the aggregation degree of the development level of each province and city is increasing year by year. There is a correlation between the average annual GDP of each province and the number of tuberculosis cases in the cluster area. There is no correlation between the number of medical institutions set up in each province and city and the number of pulmonary tuberculosis cases

Metal Phosphides Derived from Hydrotalcite Precursors toward the Selective Hydrogenation of Phenylacetylene

We report a new synthetic strategy for the fabrication of several supported nickel phosphides (Ni12P5, Ni2P, and NiP2) with particle size ranging from 5 to 15 nm via a two-step procedure: preparation of supported Ni particles from layered double hydroxide precursors, followed by a further reaction with a certain amount of red phosphorus. The selective hydrogenation of phenylacetylene over these metal phosphides was evaluated, and the as-prepared Ni2P/Al2O3 catalyst shows a much higher selectivity to styrene (up to 88.2%) than Ni12P5/Al2O3 (48.0%), NiP2/Al2O3 (65.9%), and Ni/Al2O3 (0.7%) catalysts. EXAFS and in situ IR measurements reveal that the incorporation of P increases the bond length of Ni-Ni, which imposes a key influence on the adsorption state of alkene intermediates: as the Ni-Ni bond length extends to 0.264 nm, the alkene intermediate undergoes di-pi(C=C) adsorption, facilitating its desorption and the resulting enhanced selectivity. Moreover, electron transfer occurs from Ni to P, as confirmed by EXAFS, XPS, and in situ CO-IR experiment, in which the positively charged Ni reduces the desorption energy of alkene and thus improves the reaction selectivity.</p

Dual-Wavelength High-Spectral-Resolution Lidar for Profiling Optical Properties of Aerosol and Cloud

A dual-wavelength high-spectral-resolution lidar (HSRL) based on an iodine absorption filter and a field-widened Michelson interferometer (FWMI) has been developed to profile backscatter and extinction coefficients of aerosols and clouds accurately. This instrument was tested and calibrated on multiple observations in Hangzhou and Zhoushan, respectively, from August 2018 to April 2019. This paper discusses the design and the internal calibration method of the lidar system in detail, with several typical cases of observations and the analysis of these data products. The optical properties of urban aerosols in Hangzhou and the evolvement of clouds in Zhoushan are presented, respectively

Dual-Wavelength High-Spectral-Resolution Lidar for Profiling Optical Properties of Aerosol and Cloud

A dual-wavelength high-spectral-resolution lidar (HSRL) based on an iodine absorption filter and a field-widened Michelson interferometer (FWMI) has been developed to profile backscatter and extinction coefficients of aerosols and clouds accurately. This instrument was tested and calibrated on multiple observations in Hangzhou and Zhoushan, respectively, from August 2018 to April 2019. This paper discusses the design and the internal calibration method of the lidar system in detail, with several typical cases of observations and the analysis of these data products. The optical properties of urban aerosols in Hangzhou and the evolvement of clouds in Zhoushan are presented, respectively

Experimental Determination of Lidar Overlap Profile Based on Dual Field-of-View High Spectral Resolution Lidar

This paper presents two approaches to calibrate the overlap factor under inhomogeneous atmospheric condition without critical assumption and delivers detailed analysis about the retrieval errors of overlap profile in High-Spectral-Resolution-Lidar (HSRL). The first method employs an additional optical subsystem with different field-of-view, that is dual field-of-view HSRL, for the retrieval of overlap profile. The second method takes advantage of the difference of the result between the HSRL and Klett method, that is about the retrieval of backscatter coefficient for uncorrected lidar signal, to correct overlap profile. Surprisingly, two methods show very high-level consistency and stability of the result. It is potential that this technique would be an excellent solution for experimental determination of lidar overlap in ground-based HSRL