Curriculum Design of Artificial Intelligence and Sustainability in Secondary School

Artificial Intelligence is revolutionizing numerous sectors with its transformative power, while at the same time, there is an increasing sense of urgency to address sustainability challenges. Despite the significance of both areas, secondary school curriculums still lack comprehensive integration of AI and sustainability education. This paper presents a curriculum designed to bridge this gap. The curriculum integrates progressive objectives, computational thinking competencies and system thinking components across five modules—awareness, knowledge, interaction, empowerment and ethics—to cater to varying learner levels. System thinking components help students understand sustainability in a holistic manner. Computational thinking competencies aim to cultivate computational thinkers to guide the design of curriculum activities

A SURVEY OF LUMINOUS HIGH-REDSHIFT QUASARS WITH SDSS AND WISE. II. THE BRIGHT END OF THE QUASAR LUMINOSITY FUNCTION AT z similar to 5

This is the second paper in a series on a new luminous z ~ 5 quasar survey using optical and near-infrared colors. Here we present a new determination of the bright end of the quasar luminosity function (QLF) at z ~ 5. Combining our 45 new quasars with previously known quasars that satisfy our selections, we construct the largest uniform luminous z ~ 5 quasar sample to date, with 99 quasars in the range of 4.7 ≤ z < 5.4 and −29 < M 1450 ≤ −26.8, within the Sloan Digital Sky Survey (SDSS) footprint. We use a modified 1/V a method including flux limit correction to derive a binned QLF, and we model the parametric QLF using maximum likelihood estimation. With the faint-end slope of the QLF fixed as α = −2.03 from previous deeper samples, the best fit of our QLF gives a flatter bright end slope β = −3.58 ± 0.24 and a fainter break magnitude ${M}_{1450}^{* }$ = −26.98 ± 0.23 than previous studies at similar redshift. Combined with previous work at lower and higher redshifts, our result is consistent with a luminosity evolution and density evolution model. Using the best-fit QLF, the contribution of quasars to the ionizing background at z ~ 5 is found to be 18%–45% with a clumping factor C of 2–5. Our sample suggests an evolution of radio loud fraction with optical luminosity but no obvious evolution with redshift

Gaia22dkvLb: A Microlensing Planet Potentially Accessible to Radial-Velocity Characterization

We report discovering an exoplanet from following up a microlensing event alerted by Gaia. The event Gaia22dkv is toward a nearby disk source at ~2.5 kpc rather than the traditional bulge microlensing fields. Our primary analysis yields a Jovian planet with M_p = 0.50 +/- 0.05 M_J at a projected orbital separation r_perp = 1.63 +/- 0.17 AU. The host is a turnoff star with mass 1.24 +/- 0.06 M_sun and distance of 1.35 +/- 0.09 kpc, and at r'~14, it is far brighter than any previously discovered microlensing planet host, opening up the opportunity of testing the microlensing model with radial velocity (RV) observations. RV data can be used to measure the planet's orbital period and eccentricity, and they also enable searching for inner planets of the microlensing cold Jupiter, as expected from the "inner-outer correlation" inferred from Kepler and RV discoveries. Furthermore, we show that Gaia astrometric microlensing will not only allow precise measurements of its angular Einstein radius theta_E, but also directly measure the microlens parallax vector and unambiguously break a geometric light-curve degeneracy, leading to definitive characterization of the lens system

Transcriptome profile analysis in spinal cord injury rats with transplantation of menstrual blood-derived stem cells

IntroductionMenstrual blood-derived stem cells (MenSCs) are vital in treating many degenerative and traumatic disorders. However, the underlying molecular mechanisms remain obscure in MenSCs-treating spinal cord injury (SCI) rats.MethodsMenSCs were adopted into the injured sites of rat spinal cords at day 7 post surgery and the tissues were harvested for total RNA sequencing analysis at day 21 after surgery to investigate the expression patterns of RNAs. The differentially expressed genes (DEGs) were analyzed with volcano and heatmap plot. DEGs were sequentially analyzed by weighted gene co-expression network, functional enrichment, and competitive endogenous RNAs (ceRNA) network analysis. Next, expression of selected miRNAs, lncRNAs, circRNAs and mRNAs were validated by quantitative real-time polymerase chain reaction (qRT-PCR). Bioinformatics packages and extra databases were enrolled to scoop the genes functions and their interaction relationships.ResultsA total of 89 lncRNAs, 65 circRNAs, 120 miRNAs and 422 mRNAs were significantly upregulated and 65 lncRNAs, 72 circRNAs, 74 miRNAs, and 190 mRNAs were significantly downregulated in the MenSCs treated rats compared to SCI ones. Current investigation revealed that MenSCs treatment improve the recovery of the injured rats and the most significantly involved pathways in SCI regeneration were cell adhesion molecules, nature killer cell mediated cytotoxicity, primary immunodeficiency, chemokine signaling pathway, T cell receptor signaling pathway and B cell receptor signaling pathway. Moreover, the lncRNA-miRNA-mRNA and circRNA-miRNA-mRNA ceRNA network of SCI was constructed. Finally, the protein-protein interaction (PPI) network was constructed using the top 100 DE mRNAs. The constructed PPI network included 47 nodes and 70 edges.DiscussionIn summary, the above results revealed the expression profile and potential functions of differentially expressed (DE) RNAs in the injured spinal cords of rats in the MenSCs-treated and SCI groups, and this study may provide new clues to understand the mechanisms of MenSCs in treating SCI

The 2nd competition on counter measures to 2D face spoofing attacks

Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. I. Chingovska, J. Yang, Z. Lei, D. Yi, S. Z. Li, O. Kahm, C. Glaser, N. Damer, A. Kuijper, A. Nouak, J. Komulainen, T. Pereira, S. Gupta, S. Khandelwal, S. Bansal, A. Rai, T. Krishna, D. Goyal, M.-A. Waris, H. Zhang, I. Ahmad, S. Kiranyaz, M. Gabbouj, R. Tronci, M. Pili, N. Sirena, F. Roli, J. Galbally, J. Fiérrez, A. Pinto, H. Pedrini, W. S. Schwartz, A. Rocha, A. Anjos, S. Marcel, "The 2nd competition on counter measures to 2D face spoofing attacks" in International Conference on Biometrics (ICB), Madrid (Spain), 2013, 1-6As a crucial security problem, anti-spoofing in biometrics, and particularly for the face modality, has achieved great progress in the recent years. Still, new threats arrive inform of better, more realistic and more sophisticated spoofing attacks. The objective of the 2nd Competition on Counter Measures to 2D Face Spoofing Attacks is to challenge researchers to create counter measures effectively detecting a variety of attacks. The submitted propositions are evaluated on the Replay-Attack database and the achieved results are presented in this paper.The authors would like to thank the Swiss Innovation Agency (CTI Project Replay) and the FP7 European TABULA RASA Project4 (257289) for their financial support

Fabricating higher-order functional DNA origami structures to reveal biological processes at multiple scales

Abstract DNA origami technology enables the precise assembly of well-defined two-dimensional and three-dimensional nanostructures with DNA, an inherently biocompatible material. Given their modularity and addressability, DNA origami objects can be used as scaffolds to fabricate larger higher-order structures with other functional biomolecules and engineer these molecules with nanometer precision. Over the past decade, these higher-order functional structures have shown potential as powerful tools to study the function of various bio-objects, revealing the corresponding biological processes, from the single-molecule level to the cell level. To inspire more creative and fantastic research, herein, we highlight seminal works in four emerging areas of bioapplications of higher-order DNA origami structures: (1) assisting in single-molecule studies, including protein structural analysis, biomolecule interaction analysis, and protein functional analysis, (2) manipulating lipid membranes, (3) directing cell behaviors, and (4) delivering drugs as smart nanocarriers. Finally, current challenges and opportunities in the fabrication and application of DNA origami-based functional structures are discussed

Adaptive Deep Clustering Network for Retinal Blood Vessel and Foveal Avascular Zone Segmentation

Optical coherence tomography angiography (OCTA) is a new non-invasive imaging technology that provides detailed visual information on retinal biomarkers, such as the retinal vessel (RV) and the foveal avascular zone (FAZ). Ophthalmologists use these biomarkers to detect various retinal diseases, including diabetic retinopathy (DR) and hypertensive retinopathy (HR). However, only limited study is available on the parallel segmentation of RV and FAZ, due to multi-scale vessel complexity, inhomogeneous image quality, and non-perfusion, leading to erroneous segmentation. In this paper, we proposed a new adaptive segmented deep clustering (ASDC) approach that reduces features and boosts clustering performance by combining a deep encoder–decoder network with K-means clustering. This approach involves segmenting the image into RV and FAZ parts using separate encoder–decoder models and then employing K-means clustering on each part separated by the encoder–decoder models to obtain the final refined segmentation. To deal with the inefficiency of the encoder–decoder network during the down-sampling phase, we used separate encoding and decoding for each task instead of combining them into a single task. In summary, our method can segment RV and FAZ in parallel by reducing computational complexity, obtaining more accurate interpretable results, and providing an adaptive approach for a wide range of OCTA biomarkers. Our approach achieved 96% accuracy and can adapt to other biomarkers, unlike current segmentation methods that rely on complex networks for a single biomarker