Gaining instructional design expertise through self-designing, using, and evaluationg a performance support system

In order to gain instructional design (ID) expertise, the author self-designs and uses an instructional design performance support system (IDPSS). The recursive, dynamical, and systematic process of designing, using, and evaluating the IDPSS has effectively engaged the author in learning ID knowledge and skills. Three tools are designed and used: the consilience of learning theory tool, the ID competency tool, and the design-based research (DBR) tool. The media format includes not only computer software, such as Excel and OneNote, but also traditional pen and paper. The author evaluates and synthesizes relevant ID knowledge, and creates specific models guiding her practice. She tries to create her own instructional theory model through systematically drawing useful implications from various learning theories. This learning process is characterized by five modes of thinking: enactive, iconic, story-telling, mathematical-thinking, and formal academic writing. The author self-reflects on her learning experience by discussing a few misconceptions she has encountered, and how she has tried to correct the misconceptions. The author designs a framework for her proposed approach to gain ID expertise, and hopes that it can be applicable to other instructional designers. Two other instructional designers have tried this approach in a small scope, and have contributed to building the framework. As the current project tries to initiate a DBR project, a real DBR project will rely on the efforts of many instructional designers who can try this approach over a long period of time. The author discusses the potential for creating a standard DBR documenting instrument

First-principles study of oxygen vacancy defects in orthorhombic Hf0.5_{0.5}Zr0.5_{0.5}O2_2/SiO2_2/Si gate stack

The gate defect of the ferroelectric HfO$_2$-based Si field-effect transistor (Si FeFET) plays a dominant role in its reliability issue. The first-principles calculations are an effective method for the atomic-scale understanding of gate defects. However, the first-principles study on the defects of FeFET gate stacks, i.e., metal/orthorhombic-Hf$_{0.5}$Zr$_{0.5}$O$_2$/SiO$_2$/Si structure, has not been reported so far. The key challenge is the construction of metal/orthorhombic-Hf$_{0.5}$Zr$_{0.5}$O$_2$/SiO$_2$/Si gate stack models. Here, we use the Hf$_{0.5}$Zr$_{0.5}$O$_2$(130) high-index crystal face as the orthorhombic ferroelectric layer and construct a robust atomic structure of the orthorhombic-Hf$_{0.5}$Zr$_{0.5}$O$_2$/SiO$_2$/Si gate stack without any gap states. Its high structural stability is ascribed to the insulated interface. The calculated band offsets show that this gate structure is of the type-I band alignment. Furthermore, the formation energies and charge transition levels (CTLs) of defects reveal that the oxygen vacancy defects are more favorable to form compared with other defects such as oxygen interstitial and Hf/Zr vacancy, and their CTLs are mainly localized near the Si conduction band minimum and valence band maximum, in agreement with the reported experimental results. The oxygen vacancy defects are responsible for charge trapping/de-trapping behavior in Si FeFET. This work provides an insight into gate defects and paves the way to carry out the first-principles study of ferroelectric HfO$_2$-based Si FeFET.Comment: 18 pages, 5 figure

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

The Relationship between the Community Structure and Function of Bacterioplankton and the Environmental Response in Qingcaosha Reservoir

Phytoplankton and bacterioplankton play a vital role in the structure and function of aquatic ecosystems, and their activity is closely linked to water eutrophication. However, few researchers have considered the temporal and spatial succession of phytoplankton and bacterioplankton, and their responses to environmental factors. The temporal and spatial succession of bacterioplankton and their ecological interaction with phytoplankton and water quality were analyzed using 16S rDNA high-throughput sequencing for their identification, and the functions of bacterioplankton were predicted. The results showed that the dominant classes of bacterioplankton in the Qingcaosha Reservoir were Gammaproteobacteria, Alphaproteobacteria, Actinomycetes, Acidimicrobiia, and Cyanobacteria. In addition, the Shannon diversity indexes were compared, and the results showed significant temporal differences based on monthly averaged value, although no significant spatial difference. The community structure was found to be mainly influenced by phytoplankton density and biomass, dissolved oxygen, and electrical conductivity. The presence of Pseudomonas and Legionella was positively correlated with that of Pseudanabaena sp., and Sphingomonas and Paragonimus with Melosira granulata. On the contrary, the presence of Planctomycetes was negatively correlated with Melosira granulata, as was Deinococcus-Thermus with Cyclotella sp. The relative abundance of denitrifying bacteria decreased from April to December, while the abundance of nitrogen-fixing bacteria increased. This study provides a scientific basis for understanding the ecological interactions between bacteria, algae, and water quality in reservoir ecosystems

Responses of growth and photosynthetic fluorescent characteristics in Ottelia acuminata to a water-depth gradient

To assess the response of Ottelia acuminata to a water-depth gradient, we investigated the plant growth and leaf photosynthesis by setting three water depths (0.5, 1.0, and 1.5 m) in situ in Yilong Lake, Yunnan Province, China. The results showed that the growth and photosynthetic fluorescent characteristics of O. acuminata exhibited different responses to the water-depth gradient. The plant height, fresh weight, root length, and leaf number of O. acuminata, varied significantly with changes in the water depth. With regard to the photosynthetic fluorescent characteristics of leaves, the maximum quantum yield half-saturation light intensity and fluorescence parameter of photosystem II markedly improved with increasing water depth. The increase of photosynthetically active radiation resulted in a decreased photochemical quenching coefficient (qP). In contrast, the nonphotochemical quenching coefficient was relatively high in the leaves of O. acuminata in shallow water under high photosynthetically active radiation. The chlorophyll content of the leaves varied significantly with changes in the water depth. Higher chlorophyll a, chlorophyll b, and carotenoid contents were detected in the leaves of O. acuminata at the water depth of 1.5 m. The results of the growth and photosynthetic fluorescent characteristics of O. acuminata indicate a better protection mechanism against high light in the leaves of O. acuminata in shallow water and a higher photosynthetic efficiency, as well as a greater photosynthetic potential, in the leaves of O. acuminata in deep water

A Modified 2-D Notch Filter Based on Image Segmentation for RFI Mitigation in Synthetic Aperture Radar

Synthetic aperture radar (SAR), as an active microwave sensor, can inevitably receive radio frequency interference (RFI) generated by various electromagnetic equipment. When the SAR system receives RFI, it will affect SAR imaging and limit the application of SAR images. As a kind of RFI mitigation method, notch filtering method is a classical method with high efficiency and robust performance. However, the notch filtering methods pay no attention to the protection of useful signals. This paper proposed a modified 2-D notch filter based on image segmentation for RFI mitigation with signal-protected capability. (1) The adaptive gamma correction (AGC) approach was utilized to enhance the SAR image with RFI in the range-frequency and azimuth-time domain. (2) The modified selective binary and Gaussian filtering regularized level set (SBGFRLS) model was utilized to further process the image after AGC to accurately extract the contour of the useful signals with interference, which is more conducive to protecting the useful signals without interference. (3) The Generalized Singular Value Thresholding (GSVT) based low-rank sparse decomposition (LRSD) model was utilized to separate the RFI signals and the useful signals. Then, the useful signals were restored to the raw data. The simulation experiments and measured data experiments show that the proposed method can effectively mitigate RFI and protect the useful signals whether there are RFI with single source or multiple sources

A Stepwise Optimal Design of a Dynamic Vibration Absorber with Tunable Resonant Frequency

A new kind of dynamic vibration absorber (DVA) with tunable resonant frequency is presented. The kinematics differential equation about it is built and the stepwise optimization is performed. Firstly, four main system parameters involving the ratios of mass m, natural frequency f, vibration frequency g and damping z are solved by small-step-search method to obtain optimal steady state amplitude. Secondly, the sizing optimization of the dynamic vibration absorber is proceeded to search an optimal damping effect based on the optimal parameters (g, m, z, f). And such the damping effect is simulated in a flat structure, and the results show that the working frequency band and damping effect of the DVA after optimization won 20 % of the effect of ascension compared with that before optimization