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One of the major goals of science education is preparing students to be scientifically literate. Argumentation is a core practice to promote both scientific literacy and science learning. However, incorporating argumentation into science teaching can be challenging for both teachers and students. The author introduces the Science Talk–Writing Heuristic as a teaching approach that science teachers can use to integrate literacy practices and science learning in an argumentative environment.

Accurate weather data are important for planning our day-to-day activities. In order to monitor and predict weather information, a two-phase weather management system is proposed, which combines information processing, bus mobility, sensors, and deep learning technologies to provide real-time weather monitoring in buses and stations and achieve weather forecasts through predictive models. Based on the sensing measurements from buses, this work incorporates the strengths of local information processing and moving buses for increasing the measurement coverage and supplying new sensing data. In Phase I, given the weather sensing data, the long short-term memory (LSTM) model and the multilayer perceptron (MLP) model are trained and verified using the data of temperature, humidity, and air pressure of the test environment. In Phase II, the trained learning model is applied to predict the time series of weather information. In order to assess the system performance, we compare the predicted weather data with the actual sensing measurements from the Environment Protection Administration (EPA) and Central Weather Bureau (CWB) of Taichung observation station to evaluate the prediction accuracy. The results show that the proposed system has reliable performance at weather monitoring and a good forecast for one-day weather prediction via the trained models.

Information literacy is crucial in learning from multiple digital texts. Understanding when and how cognitive processes are taxed in developing information literacy is urgent. Previous research mainly used log data, think-aloud protocols, or note-taking to explore digital reading processes, but fine-grained cognitive processes need further investigation. This study combines eye-tracking technology, click times, and essay writing to examine in-depth multiple-text reading. Forty post-secondary novices read multiple history texts and wrote essays expressing their opinions. They read two topics-one familiar and one unfamiliar-and were instructed to write either an argument or a summary. Each topic had four texts connected through hyperlinks, including three paragraphs: background, source, and content. Eye-movement data revealed that during early reading, novices allocated attention to different paragraphs depending on the task instruction. For the familiar topic, the argument group selectively reread content paragraphs longer for integration, while the summary group evenly distributed rereading time across paragraphs. Both groups had more source-content back-and-forth saccade counts. The argument group had more click times for hyperlink selection than the summary group. In their essays, the argument group produced more text-based inferences and higher-quality writing for both topics. Conversely, the summary group demonstrated the poorest comprehension quality for the familiar topic. This study provides educators with guidance on selecting appropriate reading materials for diverse students. Educators may assign argumentative tasks for familiar topics to deepen comprehension, and summary tasks for unfamiliar topics to reduce cognitive load and support learning. These insights contribute to cultivating information literacy through multiple-text reading.

Knowledge graphs gained popularity in recent years and have been useful for concept visualization and contextual information retrieval in various applications. However, constructing a knowledge graph by scraping long and complex unstructured texts for a new domain in the absence of a well-defined ontology or an existing labeled entity-relation dataset is difficult. Domains such as cybersecurity education can harness knowledge graphs to create a student-focused interactive and learning environment to teach cybersecurity. Learning cybersecurity involves gaining the knowledge of different attack and defense techniques, system setup and solving multi-facet complex real-world challenges that demand adaptive learning strategies and cognitive engagement. However, there are no standard datasets for the cybersecurity education domain. In this research work, we present a bottom-up approach to curate entity-relation pairs and construct knowledge graphs and question-answering models for cybersecurity education. To evaluate the impact of our new learning paradigm, we conducted surveys and interviews with students after each project to find the usefulness of bot and the knowledge graphs. Our results show that students found these tools informative for learning the core concepts and they used knowledge graphs as a visual reference to cross check the progress that helped them complete the project tasks.

The shifting emphases of new national curricula have placed more attention on knowledge generation approaches to learning. Such approaches are centered on the fundamental sense of generative learning where practices and tools for learning become the focus of the learning environment, rather than on the products of learning. This paper, building on from the previous review by Fiorella and Mayer (2015, 2016), focuses on a systematic review of doctoral and master theses of a knowledge generation approach to the learning of science called the science writing heuristic (SWH) approach. The outcomes of examining 81 theses show that students regardless of grade levels and cultural settings were significantly advantage in terms of content knowledge, critical thinking growth, and representational competency. The results also indicate that time in terms of engagement with the approach is critical for achieving student outcomes and for teachers to develop expertise with the approach. Questioning was also noted as being critical. Implications arising from the study are centered on the development and use of writing, the need for interactive dialogical environments, and the importance of questioning as critical elements for success.

NK2 Homeobox 1 (NKX2‐1) is a well‐characterized pathological marker that delineates lung adenocarcinoma (LUAD) progression. The advancement of LUAD is influenced by the immune tumor microenvironment through paracrine signaling. However, the involvement of NKX2‐1 in modeling the tumor immune microenvironment is still unclear. Here, the downregulation of NKX2‐1 is observed in high‐grade LUAD. Meanwhile, single‐cell RNA sequencing and Visium in situ capturing profiling revealed the recruitment and infiltration of neutrophils in orthotopic syngeneic tumors exhibiting strong cell‐cell communication through the activation of CXCLs/CXCR2 signaling. The depletion of NKX2‐1 triggered the expression and secretion of CXCL1, CXCL2, CXCL3, and CXCL5 in LUAD cells. Chemokine secretion is analyzed by chemokine array and validated by qRT‐PCR. ATAC‐seq revealed the restrictive regulation of NKX2‐1 on the promoters of CXCL1, CXCL2, and CXCL5 genes. This phenomenon led to increased tumor growth, and conversely, tumor growth decreased when inhibited by the CXCR2 antagonist SB225002. This study unveils how NKX2‐1 modulates the infiltration of tumor‐promoting neutrophils by inhibiting CXCLs/CXCR2‐dependent mechanisms. Hence, targeting CXCR2 in NKX2‐1‐low tumors is a potential antitumor therapy that may improve LUAD patient outcomes. An overview showing the utilization of unconventional molecular profiling techniques, such as Single‐cell RNA sequencing (scRNA‐seq) and Visium In situ Capturing, employed to unravel the modulatory role of NK2 homeobox 1 (NKX2‐1) within the immune microenvironment of lung adenocarcinoma (LUAD). The downregulation of NKX2‐1 triggers the expression and secretion of CXCL1, CXCL2, CXCL3, and CXCL5. This increases neutrophil recruitment and infiltration into LUAD tumors, thereby promoting cancer progression.

Mercury (Hg) is a serious environmental pollution threat to the planet. The accumulation of Hg in plants disrupts many cellular-level functions and inhibits growth and development, but the mechanism is not fully understood. To gain more insight into the cellular response to Hg, we performed a large-scale analysis of the rice transcriptome during Hg stress. Genes induced with short-term exposure represented functional categories of cell-wall formation, chemical detoxification, secondary metabolism, signal transduction and abiotic stress response. Moreover, Hg stress upregulated several genes involved in aromatic amino acids (Phe and Trp) and increased the level of free Phe and Trp content. Exogenous application of Phe and Trp to rice roots enhanced tolerance to Hg and effectively reduced Hg-induced production of reactive oxygen species. Hg induced calcium accumulation and activated mitogen-activated protein kinase. Further characterization of the Hg-responsive genes we identified may be helpful for better understanding the mechanisms of Hg in plants.

This study evaluates the impact of assimilating moderate resolution imaging spectroradiometer (MODIS) aerosol optical depth (AOD) data using different data assimilation (DA) methods on dust analyses and forecasts over North Africa and tropical North Atlantic. To do so, seven experiments are conducted using the Weather Research and Forecasting dust model and the Gridpoint Statistical Interpolation analysis system. Six of these experiments differ in whether or not AOD observations are assimilated and the DA method used, the latter of which includes the three‐dimensional variational (3D‐Var), ensemble square root filter (EnSRF), and hybrid methods. The seventh experiment, which allows us to assess the impact of assimilating deep blue AOD data, assimilates only dark target AOD data using the hybrid method. The assimilation of MODIS AOD data clearly improves AOD analyses and forecasts up to 48 hr in length. Results also show that assimilating deep blue data has a primarily positive effect on AOD analyses and forecasts over and downstream of the major North African source regions. Without assimilating deep blue data (assimilating dark target only), AOD assimilation only improves AOD forecasts for up to 30 hr. Of the three DA methods examined, the hybrid and EnSRF methods produce better AOD analyses and forecasts than the 3D‐Var method does. Despite the clear benefit of AOD assimilation for AOD analyses and forecasts, the lack of information regarding the vertical distribution of aerosols in AOD data means that AOD assimilation has very little positive effect on analyzed or forecasted vertical profiles of backscatter. Key Points Assimilating MODIS AOD data improves AOD forecasts up to 48 hr, but the improvement can last for only 30 hr when deep blue data are excluded The hybrid and EnSRF methods can produce better AOD analyses and forecasts than the 3D‐Var method does Assimilation of MODIS AOD data has very little impact on analyses and/or forecasts of aerosol backscatter profile

In this study, we revisit a heavy rainfall event over central Oahu in June 2003, during which a rare weak tornado occurred. We used a numerical model to analyze the meteorological conditions that led to the formation of the tornado. Previous studies on this event have analyzed convection initiation over the semiarid region using a numerical model with 1.5-km grids. By contrast, we used an ultra-high-resolution model to simulate the formation and movement of the tornado-like vortex. An appropriate grid size of 40 m, coupled with the large-eddy simulation method, successfully reproduced the weak vortex event. This simulation facilitated a detailed analysis of the vortex’s initialization and downstream movement, demonstrating the model’s effectiveness despite minor discrepancies in the tornado’s exact location. Our results indicated that the tornado event was influenced by the interactions among Oahu’s local land and sea breeze, thermally induced convective systems, and topography. A weak vortex formed near the ground due to downdrafts from the land-sea breeze and convective systems. Subsequently, through the coupling effect of the upper and lower layers, the incoming convective system exerted a suction effect that enhanced the upper-level downdrafts. This process allowed the tornado vortex to connect from the top to the bottom. Our findings may significantly improve numerical weather prediction, thereby assisting forecasters in accurately predicting similar weather events across tropical islands.

Electron signaling and oxygen level are vital for regulating neural‐cell fate and brain recovery. However, clinical challenges arise from the short half‐life and the difficulty of spatiotemporally controlled oxygen release and electric signals. In this study, a wireless‐charging sustained oxygen release from conductive microgels (SOCO) served as an antenna and an on‐demand O2 release for nerve regeneration is developed. Introducing “electromagnetic messenger”, using external alternating magnetic field (AMF) to enhance catalytic oxygen release and electrical stimulation to promote the reconstruction of blood vessels and neurons in vivo. SOCO also reduces TBI glial scarring by reducing activated microglia and stellate cells, promoting infiltration of new neurons. In whole‐brain analyses, effective somatostatin (Sst) production inhibits gamma‐aminobutyric acid (GABA) synthesis in injured areas, thereby improving brain function and behavioral recovery. Furthermore, spatial multiomics combined with single‐cell deconvolution analysis reveals the treatment reprogramming in vivo brain transcriptome of angiogenic markers (Il1a, Lgals3) and GABAergic pathway via modulation of GAD65/67 activity, guiding angiogenesis and neuronal regeneration. This in situ catalytic SOCO with noncontact AMF presents an “electromagnetic messenger”‐based therapeutics for reprogramming the neuro‐regeneration and brain function recovery in TBI. A wireless‐charging sustained oxygen release from conductive microgels (SOCO) served as an antenna and an on‐demand O2 release for nerve regeneration is developed. Introducing “electromagnetic messenger”, using external alternating magnetic field (AMF) to enhance catalytic oxygen release and electrical stimulation to promote the reconstruction of blood vessels and neurons in vivo.