Cue recognition and cue elaboration in learning from examples

This paper describes the processes used by students to learn from worked-out examples and by working through problems. Evidence is derived from protocols of students learning secondary school mathematics and physics. The students acquired knowledge from the examples in the form of productions (condition --&gt; action): first discovering conditions under which the actions are appropriate and then elaborating the conditions to enhance efficiency. Students devoted most of their attention to the condition side of the productions. Subsequently, they generalized the productions for broader application and acquired specialized productions for special problem classes.</p

Combining a Fuzzy Matter-Element Model with a Geographic Information System in Eco-Environmental Sensitivity and Distribution of Land Use Planning

Sustainable ecological and environmental development is the basis of regional development. The sensitivity classification of the ecological environment is the premise of its spatial distribution for land use planning. In this paper, a fuzzy matter-element model and factor-overlay method were employed to analyze the ecological sensitivity in Yicheng City. Four ecological indicators, including soil condition,, water condition,, atmospheric conditions and biodiversity were used to classify the ecological sensitivity. The results were categorized into five ranks: insensitive, slightly sensitive, moderately sensitive, highly sensitive and extremely sensitive zones. The spatial distribution map of environmental sensitivity for land use planning was obtained using GIS (Geographical Information System) techniques. The results illustrated that the extremely sensitive and highly sensitive areas accounted for 14.40% and 30.12% of the total area, respectively, while the moderately sensitive and slightly sensitive areas are 25.99% and 29.49%, respectively. The results provide the theoretical foundation for land use planning by categorizing all kinds of land types in Yicheng City

SeisCLIP: A seismology foundation model pre-trained by multi-modal data for multi-purpose seismic feature extraction

Training specific deep learning models for particular tasks is common across various domains within seismology. However, this approach encounters two limitations: inadequate labeled data for certain tasks and limited generalization across regions. To address these challenges, we develop SeisCLIP, a seismology foundation model trained through contrastive learning from multi-modal data. It consists of a transformer encoder for extracting crucial features from time-frequency seismic spectrum and an MLP encoder for integrating the phase and source information of the same event. These encoders are jointly pre-trained on a vast dataset and the spectrum encoder is subsequently fine-tuned on smaller datasets for various downstream tasks. Notably, SeisCLIP's performance surpasses that of baseline methods in event classification, localization, and focal mechanism analysis tasks, employing distinct datasets from different regions. In conclusion, SeisCLIP holds significant potential as a foundational model in the field of seismology, paving the way for innovative directions in foundation-model-based seismology research.Comment: 27 pages, 9 figures, 4 table

Optimization of sub-grid scale model for abrasive flow machining curved tube based on large eddy simulation

Abrasive flow machining technology is a new type of precision machining technology. Due to its unique rheological properties, it can process any complex structure and size parts to meet the requirements that conventional machining cannot meet. Combined with the turbulent flow characteristics of the abrasive flow, the large eddy simulation numerical method is used to simulate the machining process of the abrasive flow. The influence of different sub-grid scale models on the simulation results is discussed. Taking curved tube as the research object, the static pressure, dynamic pressure and velocity of different sub-grid models are analyzed to find the best sub-grid scale model. Large eddy simulation method is used to simulate the complex flow channel parts, and the best sub-grid scale model suitable for complex flow channels is determined, which reveals the grinding and polishing rule of abrasive flow and provides academic support for future research. Therefore, it has frontier and important research value

Topology searching algorithm for multi-port hybrid circuit breakers based on graph theory

Due to the significant advantages of low cost, integrated multi-port hybrid DC circuit breakers (M-HCBs) with a reduced number of devices have attracted extensive attention for fault blocking in multi-terminal VSC-HVDC system. However, the current topology exploration by researchers is random, uncertain, and time-consuming. In order to provide more new cost-effective topologies, this paper innovatively proposes a topology searching algorithm for the IGBT-type M-HCB and uses the concept of ‘roadblock’ to simplify the adjacency matrix. It can be used to significantly save time spent on proposing a new M-HCB topology because viable topologies can be quickly and rigorously carried out from a large number of directed graphs using computers. Performance characteristics of all derived topologies are simultaneously obtained, and a comparison can be easily conducted to meet the needs of actual application scenarios. A three-port M-HCB example-specific application is given, along with some detailed output topologies that prove the validity and feasibility of the proposed method

A low-cost current flow controlling interline hybrid circuit breaker combined with SCR and H-bridge sub-module

A massive number of DC circuit breaker is usually necessary to be installed to protect HVDC grids from DC faults, this will lead to high capital costs because large number of expensive IGBT-in-series are used. In this paper, an interline hybrid circuit breaker is proposed by the combination of SCR string and a small number of H-bridge modules (SCR-IHCB). The proposed SCR-IHCB has the capacity of blocking DC fault of two adjacent lines respectively by sharing only one main breaker branch (MB) mainly composed of low-cost SCR string and H-bridge module instead of IGBT-in-series string. The interline current flow control function is also integrated. Hence it has advantages of simple and compact topology, economical design compared with typical IGBT based HCB solutions. The operation process of the proposed SCR-IHCB is discussed in detail, and the performance is verified by MATLAB Simulink simulation and scale-down prototype experiment

An animal model of SARS produced by infection of Macaca mulatta with SARS coronavirus.

A new SARS animal model was established by inoculating SARS coronavirus (SARS-CoV) into rhesus macaques (Macaca mulatta) through the nasal cavity. Pathological pulmonary changes were successively detected on days 5-60 after virus inoculation. All eight animals showed a transient fever 2-3 days after inoculation. Immunological, molecular biological, and pathological studies support the establishment of this SARS animal model. Firstly, SARS-CoV-specific IgGs were detected in the sera of macaques from 11 to 60 days after inoculation. Secondly, SARS-CoV RNA could be detected in pharyngeal swab samples using nested RT-PCR in all infected animals from 5 days after virus inoculation. Finally, histopathological changes of interstitial pneumonia were found in the lungs during the 60 days after viral inoculation: these changes were less marked at later time points, indicating that an active healing process together with resolution of an acute inflammatory response was taking place in these animals. This animal model should provide insight into the mechanisms of SARS-CoV-related pulmonary disease and greatly facilitate the development of vaccines and therapeutics against SARS

Dickkopf-related protein 1 (Dkk1) regulates the accumulation and function of myeloid derived suppressor cells in cancer

Tumor–stroma interactions contribute to tumorigenesis. Tumor cells can educate the stroma at primary and distant sites to facilitate the recruitment of heterogeneous populations of immature myeloid cells, known as myeloid-derived suppressor cells (MDSCs). MDSCs suppress T cell responses and promote tumor proliferation. One outstanding question is how the local and distant stroma modulate MDSCs during tumor progression. Down-regulation of β-catenin is critical for MDSC accumulation and immune suppressive functions in mice and humans. Here, we demonstrate that stroma-derived Dickkopf-1 (Dkk1) targets β-catenin in MDSCs, thus exerting immune suppressive effects during tumor progression. Mice bearing extraskeletal tumors show significantly elevated levels of Dkk1 in bone microenvironment relative to tumor site. Strikingly, Dkk1 neutralization decreases tumor growth and MDSC numbers by rescuing β-catenin in these cells and restores T cell recruitment at the tumor site. Recombinant Dkk1 suppresses β-catenin target genes in MDSCs from mice and humans and anti-Dkk1 loses its antitumor effects in mice lacking β-catenin in myeloid cells or after depletion of MDSCs, demonstrating that Dkk1 directly targets MDSCs. Furthermore, we find a correlation between CD15(+) myeloid cells and Dkk1 in pancreatic cancer patients. We establish a novel immunomodulatory role for Dkk1 in regulating tumor-induced immune suppression via targeting β-catenin in MDSCs