Evolution of Grain Structure and Dynamic Precipitation during Hot Deformation in a Medium-Strength Al-Zn-Mg-Er-Zr Aluminum Alloy.

The hot deformation behavior of Al-Zn-Mg-Er-Zr alloy was investigated through an isothermal compression experiment at a strain rate ranging from 0.01 to 10 s-1 and temperature ranging from 350 to 500 °C. The constitutive equation of thermal deformation characteristics based on strain was established, and the microstructure (including grain, substructure and dynamic precipitation) under different deformation conditions was analyzed. It is shown that the steady-state flow stress can be described using the hyperbolic sinusoidal constitutive equation with a deformation activation energy of 160.03 kJ/mol. Two kinds of second phases exist in the deformed alloy; one is the η phase, whose size and quantity changes according to the deformation parameters, and the other is spherical Al3(Er, Zr) particles with good thermal stability. Both kinds of particles pin the dislocation. However, with a decrease in strain rate or increase in temperature, η phases coarsen and their density decreases, and their dislocation locking ability is weakened. However, the size of Al3(Er, Zr) particles does not change with the variation in deformation conditions. So, at higher deformation temperatures, Al3(Er, Zr) particles still pin dislocations and thus refine the subgrain and enhance the strength. Compared with the η phase, Al3(Er, Zr) particles are superior for dislocation locking during hot deformation. A strain rate ranging from 0.1 to 1 s-1 and a deformation temperature ranging from 450 to 500 °C form the safest hot working domain in the processing map.

Cluster analysis for the overall health status of elderly, multimorbid patients with diabetes.

Purpose: To evaluate the overall health status and health-related abilities and problems of elderly patients with diabetes and multimorbidity compared with those with diabetes only. Additionally, we aimed to identify different subgroups of elderly, multimorbid patients with diabetes. Methods: This cross-sectional study included 538 elderly patients with diabetes. The participants completed a series of questionnaires on self-rated health (SRH), diabetes self-management, self-efficacy, health literacy, depression, and diabetes distress. Differences in health-related abilities and problems were compared between elderly patients with diabetes and multimorbidity and those with diabetes only, with adjustments for covariates using propensity score matching. A cluster analysis was also performed to identify the overall health status subgroups of elderly, multimorbid patients with diabetes. Additionally, we conducted a multinomial logistic regression analysis to examine the predictors of health-related abilities and problem-cluster group membership. Results: Elderly patients with diabetes and multimorbidity experienced more health-related abilities and problems than those with diabetes only, particularly within the domains of depression (p < 0.001), and diabetes distress. The level of health literacy (p < 0.001) and self-management (p = 0.013) in elderly, multimorbid patients with diabetes was also significantly higher than that in elderly patients with diabetes only. Cluster analysis of elderly, multimorbid patients with diabetes revealed three distinct overall health status clusters. Multinomial logistic regression analysis indicated that age (OR = 1.090, p = 0.043), sex (OR = 0.503, p = 0.024), living situation (OR = 2.769, p = 0.011), BMI (OR = 0.838, p = 0.034), regular exercise (OR = 2.912, p = 0.041 in poor vs. good; OR = 3.510, p < 0.001 in intermediate vs. good), and cerebral infarction (OR = 26.280, p < 0.001) independently and significantly predicted cluster membership. Conclusion: Compared with elderly patients with diabetes only, those with diabetes and multimorbidity experienced more health-related abilities and problems within the domains of depression, and diabetes distress. Additionally, the level of health literacy and self-management in elderly, multimorbid patients with diabetes was significantly higher than that in those with diabetes only. Among the multimorbid diabetes group, old age, male sex, living without a partner, slightly lower BMIs, not exercising regularly, and experiencing cerebral infarctions were all positively correlated with worse overall health status.

Interactive Data Comics.

This paper investigates how to make data comics interactive. Data comics are an effective and versatile means for visual communication, leveraging the power of sequential narration and combined textual and visual content, while providing an overview of the storyline through panels assembled in expressive layouts. While a powerful static storytelling medium that works well on paper support, adding interactivity to data comics can enable non-linear storytelling, personalization, levels of details, explanations, and potentially enriched user experiences. This paper introduces a set of operations tailored to support data comics narrative goals that go beyond the traditional linear, immutable storyline curated by a story author. The goals and operations include adding and removing panels into pre-defined layouts to support branching, change of perspective, or access to detail-on-demand, as well as providing and modifying data, and interacting with data representation, to support personalization and reader-defined data focus. We propose a lightweight specification language, COMICSCRIPT, for designers to add such interactivity to static comics. To assess the viability of our authoring process, we recruited six professional illustrators, designers and data comics enthusiasts and asked them to craft an interactive comic, allowing us to understand authoring workflow and potential of our approach. We present examples of interactive comics in a gallery. This initial step towards understanding the design space of interactive comics can inform the design of creation tools and experiences for interactive storytelling.

A review on factors that affect surface charge accumulation and charge-induced surface flashover.

The surface charge accumulation is very likely to trigger the surface flashover, which limits the large-scale application of DC GIL/GIS. This article comprehensively reviews the effect of six factors, including insulator-electrode shape, surface roughness of the insulator and conductor, metal particles, temperature, humidity, and gas type, on the insulator surface charging property. Furthermore, three models i.e. 'analogous ineffective region' expansion model, charge cluster triggered surface flashover model, and synergistic model of adsorbed gas, revealing the mechanism of charge triggered surface flashover phenomenon are reviewed and discussed. Future work from the perspective of theoretical analysis and engineering application are suggested in this field.

Improving the Combustion Performance of a Hybrid Rocket Engine using a Novel Fuel Grain with a Nested Helical Structure.

A technique to improve the combustion performance of a hybrid rocket engine using a novel fuel grain structure is presented. This technique utilizes the different regression rates of acrylonitrile butadiene styrene and paraffin-based fuels, which increase the exchanges of both matter and energy by swirl flow and recirculation zones formed at the grooves between the adjacent vanes. The centrifugal casting technique is used to cast the paraffin-based fuel into an acrylonitrile butadiene styrene substrate made by three-dimensional printing. Using oxygen as the oxidizer, a series of tests were conducted to investigate the combustion performance of the novel fuel grain. In comparison to paraffin-based fuel grains, the fuel grain with a nested helical structure, which can be maintained throughout the combustion process, showed significant improvement in the regression rate and great potential in improvement of combustion efficiency.

Data Comics for Reporting Controlled User Studies in Human-Computer Interaction.

Inspired by data comics, this paper introduces a novel format for reporting controlled studies in the domain of human-computer interaction (HCI). While many studies in HCI follow similar steps in explaining hypotheses, laying out a study design, and reporting results, many of these decisions are buried in blocks of dense scientific text. We propose leveraging data comics as study reports to provide an open and glanceable view of studies by tightly integrating text and images, illustrating design decisions and key insights visually, resulting in visual narratives that can be compelling to non-scientists and researchers alike. Use cases of data comics study reports range from illustrations for non-scientific audiences to graphical abstracts, study summaries, technical talks, textbooks, teaching, blogs, supplementary submission material, and inclusion in scientific articles. This paper provides examples of data comics study reports alongside a graphical repertoire of examples, embedded in a framework of guidelines for creating comics reports which was iterated upon and evaluated through a series of collaborative design sessions.

A Three-Hierarchy Evaluation of Polarimetric Performance of GF-3, Compared with ALOS-2/PALSAR-2 and RADARSAT-2.

GaoFen-3 (GF-3) is the first Chinese civilian multi-polarization synthetic aperture radar (SAR) satellite, launched on 10 August of 2016, and put into operation at the end of January 2017. The polarimetric SAR (PolSAR) system of GF-3 is able to provide quad-polarization (quad-pol) images in a variety of geophysical research and applications. However, this ability increases the complexity of maintaining image quality and calibration. As a result, to evaluate the quality of polarimetric data, polarimetric signatures are necessary to guarantee accuracy. Compared with some other operational space-borne PolSAR systems, such as ALOS-2/PALSAR-2 (ALOS-2) and RADARSAT-2, GF-3 has less reported calibration and image quality files, forcing users to validate the quality of polarimetric imagery of GF-3 before quantitative applications. In this study, without the validation data obtained from a calibration infrastructure, an innovative, three-hierarchy strategy was proposed to assess PolSAR data quality, in which the performance of GF-3 data was evaluated with ALOS-2 and RADARSAT-2 data as references. Experimental results suggested that: (1) PolSAR data of GF-3 satisfied backscatter reciprocity, similar with that of RADARSAT-2; (2) most of the GF-3 PolSAR images had no signs of polarimetric distortion affecting decomposition, and the system of GF-3 may have been improved around May 2017; and (3) the classification accuracy of GF-3 varied from 75.0% to 91.4% because of changing image-acquiring situations. In conclusion, the proposed three-hierarchy approach has the ability to evaluate polarimetric performance. It proved that the residual polarimetric distortion of calibrated GF-3 PolSAR data remained at an insignificant level, with reference to that of ALOS-2 and RADARSAT-2, and imposed no significant impact on the polarimetric decomposition components and classification accuracy.

Causal relationship in the interaction between land cover change and underlying surface climate in the grassland ecosystems in China.

Land-climate interactions are driven by causal relations that are difficult to ascertain given the complexity and high dimensionality of the systems. Many methods of statistical and mechanistic models exist to identify and quantify the causality in such highly-interacting systems. Recent advances in remote sensing development allowed people to investigate the land-climate interaction with spatially and temporally continuous data. In this study, we present a new approach to measure how climatic factors interact with each other under land cover change. The quantification method is based on the correlation analysis of the different order derivatives, with the canonical mathematical definitions developed from the theories of system dynamics and practices of the macroscopic observations. We examined the causal relationship between the interacting variables on both spatial and temporal dimensions based on macroscopic observations of land cover change and surface climatic factors through a comparative study in the different grassland ecosystems of China. The results suggested that the interaction of land-climate could be used to explain the temporal lag effect in the comparison of the three grassland ecosystems. Significant spatial correlations between the vegetation and the climatic factors confirmed feedback mechanisms described in the theories of eco-climatology, while the uncertain temporal synchronicity reflects the causality among the key indicators. This has been rarely addressed before. Our research show that spatial correlations and the temporal synchronicity among key indicators of the land surface and climatic factors can be explained by a novel method of causality quantification using derivative analysis.