In recent years, many institutions have announced the significance of software development for countries, societies, and individuals. In developing software, various unpredictable problems are often ...encountered, especially in developing large-scale and complex software. To reduce the possibility of these problems occurring, it is important for students to apply software engineering technology to scientifically define the criteria, models, and procedures needed in the software development process. Therefore, it is important to cultivate students to learn software engineering concepts and technologies. However, since the course duration is limited by the semester, most teachers can only conduct a teacher-centered learning environment to teach theoretical concepts to students. Most students cannot achieve high-order thinking skills and apply software engineering technology to solve practical problems after learning in this environment. As mentioned above, the aim of this study is to apply an innovative pedagogy, called a flipped classroom, to conduct a learner-centered learning environment in a software engineering course. Moreover, a smart learning diagnosis system was developed to support this pedagogy in this course. An experiment was conducted on a software engineering course at a university in Taiwan to investigate the effectiveness of the proposed approach. The students in the experimental group learned with the flipped-classroom learning approach, while the students in the control group learned with the traditional-classroom learning approach. The experimental results show that, in comparison with the traditional-classroom learning approach, the proposed approach significantly improved the students' learning achievement, learning motivation, learning attitude, and problem solving ability.
•This study proposed a flipped classroom with a smart learning diagnosis system.•An experiment was conducted in a software engineering course.•The proposed approach is helpful to students in improving learning performance.•Most students showed positive perceptions toward the usage of the proposed system.
Abstract
Pulmonary fibrosis (PF) is a major public health problem with limited therapeutic options. There is a clear need to identify novel mediators of PF to develop effective therapeutics. Here we ...show that an ER protein disulfide isomerase, thioredoxin domain containing 5 (TXNDC5), is highly upregulated in the lung tissues from both patients with idiopathic pulmonary fibrosis and a mouse model of bleomycin (BLM)-induced PF. Global deletion of
Txndc5
markedly reduces the extent of PF and preserves lung function in mice following BLM treatment. Mechanistic investigations demonstrate that TXNDC5 promotes fibrogenesis by enhancing TGFβ1 signaling through direct binding with and stabilization of TGFBR1 in lung fibroblasts. Moreover, TGFβ1 stimulation is shown to upregulate TXNDC5 via ER stress/ATF6-dependent transcriptional control in lung fibroblasts. Inducing fibroblast-specific deletion of
Txndc5
mitigates the progression of BLM-induced PF and lung function deterioration. Targeting TXNDC5, therefore, could be a novel therapeutic approach against PF.
MicroRNAs (miRNAs) are small non-coding RNAs of approximately 22 nucleotides, which negatively regulate the gene expression at the post-transcriptional level. This study describes an update of the ...miRTarBase (http://miRTarBase.mbc.nctu.edu.tw/) that provides information about experimentally validated miRNA-target interactions (MTIs). The latest update of the miRTarBase expanded it to identify systematically Argonaute-miRNA-RNA interactions from 138 crosslinking and immunoprecipitation sequencing (CLIP-seq) data sets that were generated by 21 independent studies. The database contains 4966 articles, 7439 strongly validated MTIs (using reporter assays or western blots) and 348 007 MTIs from CLIP-seq. The number of MTIs in the miRTarBase has increased around 7-fold since the 2014 miRTarBase update. The miRNA and gene expression profiles from The Cancer Genome Atlas (TCGA) are integrated to provide an effective overview of this exponential growth in the miRNA experimental data. These improvements make the miRTarBase one of the more comprehensively annotated, experimentally validated miRNA-target interactions databases and motivate additional miRNA research efforts.
Vibrational spectroscopy has been widely used to investigate various structural aspects of the glass network, and there are a plethora of papers reporting subtle but consistent changes in infrared ...and Raman spectral features of glass upon alterations of glass compositions, thermal histories, mechanical stresses, or surface treatments. However, interpretations of such spectral features are still obscured due to the lack of well‐established physical principles accurately describing vibrational modes of the non‐crystalline glass network. Due to the non‐equilibrium nature of the glass network, three‐dimensionally connected without any long‐range orders, vibrational spectral features of glass cannot be interpreted using the analogy with those of isolated molecular moieties or crystalline counterparts. This feature article explains why such comparisons are outdated and describes the recent advances made from theoretical calculations of vibrational spectral features of amorphous networks or comparisons of computational results with experimental data. For the interpretation of vibrational spectral features of silica and silicate glasses, the following empirical relationships are suggested: (i) the intensity‐weighted peak position of the Si‐O‐Si stretch mode negatively correlates with the weighted average of the Si‐O bond length distribution, and (ii) the broad band of the Si‐O‐Si bending mode negatively correlates with the Si‐O‐Si bond angle distribution. Selected examples of vibrational spectroscopic imaging of surface defects are discussed to deliberate the implication of these findings in the structure‐property relationship of silica and silicate glass materials. Unanswered questions and continuing research challenges are identified.
Both experimental results and theoretical models suggest the decisive role of the filler–matrix interfaces on the dielectric, piezoelectric, pyroelectric, and electrocaloric properties of ...ferroelectric polymer nanocomposites. However, there remains a lack of direct structural evidence to support the so‐called interfacial effect in dielectric nanocomposites. Here, a chemical mapping of the interfacial coupling between the nanofiller and the polymer matrix in ferroelectric polymer nanocomposites by combining atomic force microscopy–infrared spectroscopy (AFM–IR) with first‐principles calculations and phase‐field simulations is provided. The addition of ceramic fillers into a ferroelectric polymer leads to augmentation of the local conformational disorder in the vicinity of the interface, resulting in the local stabilization of the all‐trans conformation (i.e., the polar β phase). The formation of highly polar and inhomogeneous interfacial regions, which is further enhanced with a decrease of the filler size, has been identified experimentally and verified by phase‐field simulations and density functional theory (DFT) calculations. This work offers unprecedented structural insights into the configurational disorder‐induced interfacial effect and will enable rational design and molecular engineering of the filler–matrix interfaces of electroactive polymer nanocomposites to boost their collective properties.
Using atomic force microscopy–infrared spectroscopy together with first‐principles calculations and phase field simulations, a spatial structure analysis of the filler–matrix interfaces in ferroelectric polymer nanocomposites is provided. The unprecedented insights into the interfacial coupling effect at the molecular level would enable interfacial engineering strategies to realize improved properties and unlock new functionalities of the nanocomposites.
Abstract
Subhalo abundance matching (SHAM) has played an important role in improving our understanding of how galaxies populate their host dark matter halos. In essence, the SHAM framework is to find ...a dark matter halo property that best correlates with an attribute of galaxies, such as stellar mass. The peak value of the maximum circular velocity (
V
max
) a halo/subhalo has ever attained throughout its lifetime,
V
peak
, has been a popular choice for SHAM. A recent study by Tonnesen & Ostriker suggested that quantity
ϕ
, which combines the present-day
V
max
and the peak value of halo dark matter mass, performs better in predicting stellar mass than
V
peak
. Inspired by their approach, in this work, we find that further improvement can be achieved by a quantity
ψ
5
that combines the 90th percentile of
V
max
a halo/subhalo has ever achieved with the 60th percentile of the dark matter halo time variation rate. Tests based on the simulation TNG300 of the IllustrisTNG project show that our new SHAM scheme, with just three free parameters, can improve the stellar mass prediction and mass-dependent clustering by 15% and 18% from
ϕ
, respectively, over the redshift range
z
= 0–2.
Abstract
We present
piXedfit
, pixelized spectral energy distribution (SED) fitting, a Python package that provides tools for analyzing spatially resolved properties of galaxies using multiband ...imaging data alone or in combination with integral field spectroscopy (IFS) data. It has six modules that can handle all tasks in the spatially resolved SED fitting. The SED-fitting module uses the Bayesian inference technique with two kinds of posterior sampling methods: Markov Chain Monte Carlo (MCMC) and random dense sampling of parameter space (RDSPS). We test the performance of the SED-fitting module using mock SEDs of simulated galaxies from IllustrisTNG. The SED fitting with both posterior sampling methods can recover physical properties and star formation histories of the IllustrisTNG galaxies well. We further test the performance of
piXedfit
modules by analyzing 20 galaxies observed by the CALIFA and MaNGA surveys. The data are comprised of 12-band imaging data from the Galaxy Evolution Explorer, SDSS, 2MASS, and WISE and the IFS data from CALIFA or MaNGA. The
piXedfit
package can spatially match (in resolution and sampling) the imaging and IFS data. By fitting only the photometric SEDs,
piXedfit
can predict the spectral continuum,
D
n
4000, H
α
, and H
β
well. The star formation rate derived by
piXedfit
is consistent with that derived from H
α
emission. The RDSPS method gives equally good fitting results as the MCMC and is much faster. As a versatile tool,
piXedfit
is equipped with a parallel computing module for efficient analysis of large data sets and will be made publicly available (
https://github.com/aabdurrouf/piXedfit
).
The aim of software engineering education is to educate students in software technologies, developments, procedures, and scientific practices to enable them to cope with industrial demands. However, ...the implementation of software engineering education in traditional university classrooms is restricted by the semester structure, making it difficult to achieve a proper learning balance between theory and practice. To balance theoretical and practical learning, prior studies have indicated that flipped learning is a suitable classroom setting for students and teachers. In a flipped learning environment, it is important to enhance and capture students' learning performance before the class to facilitate teachers and students in proceeding with in-class instruction and learning. In this study, an e-book system named BookRoll was applied to support software engineering education in a flipped learning setting. The proposed approach supports and facilitates out-of-class and in-class learning by providing reading and learning analytic functions for teachers and students. To evaluate the proposed approach, two classes of students were allocated to an experimental group and a control group to participate in an experiment. In the flipped learning process, the experimental group was supported by the BookRoll system, while the control group did not use the BookRoll system. The results revealed that the proposed approach not only promoted students' learning achievements in software engineering education but also improved their learning motivation, attitude, and problem-solving ability. The reading behavior analysis further indicated that reading time was a statistically significant predictor of learning achievement.
Celotno besedilo
Dostopno za:
BFBNIB, DOBA, IZUM, KILJ, NMLJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Thermal tempering is an industrial process widely used to make soda lime silica (SLS) glass panels stronger and tougher. During the tempering process, the upper and bottom sides of the glass may ...experience different cooling rates, and thus, their properties could be different. This study characterized changes in surface composition and subsurface glass network structures as well as indentation and wear resistance properties of the air‐ and tin‐sides of 6‐mm‐thick SLS window panels faced toward the upper and sliding roller sides during thermal tempering. The results showed that although the chemical and structural differences detected with X‐ray photoelectron spectroscopy and specular reflection infrared spectroscopy are subtle, there are large differences in nanoindentation behaviors and mechanochemical wear properties of the SLS glass surface. The findings of this study provide further insights into the performance difference between the air‐ and tin‐sides of the SLS glass panel treated with thermal tempering.
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