College of San Mateo (CSM) is a public community college in San Mateo, California. It is part of the San Mateo County Community College District. College of San Mateo is located at the northern corridor of Silicon Valley and situated on a 153-acre site in the San Mateo hills. The campus was designed by architect John Carl Warnecke. The college currently serves approximately 10,000 day, evening and weekend students. The college offers 79 A.A./A.S. degree majors, 75 certificate programs and approximately 100 transfer areas and majors..
High-density electromyography (HD-EMG) has emerged as a powerful modality for decoding fine-grained neuromuscular activity, enabling real-time neural-machine interfaces (NMIs) for applications such as prosthetic control, rehabilitation, and augmented interaction. While deep learning approaches such as convolutional neural networks (CNNs)have demonstrated high classification accuracy for EMG-based gesture recognition, their deployment on embedded hardware remains a major challenge due to computational and memory constraints. This paper presents NeuroEdge, a real-time HD EMG-based NMI system that performs gesture recognition entirely on resource-constrained microcontrollers. The system features two custom-designed modules: the HD-EMG StreamBridge, a wireless communication interface that streams raw HD-EMG data from a Quattrocento amplifier to an ESP32 microcontroller; and the EdgeDL Inference Engine, a lightweight deep learning framework executing on a Sony Spresense microcontroller. A compact 1-dimensional CNN optimized for embedded inference processes, sliding windows of EMG data in real time. Data streaming and inference are pipelined and synchronized through an architecture that utilizes Direct Memory Access (DMA) for data transfer and Serial Peripheral Interface (SPI) burst communication between the ESP32 and Spresense, ensuring low-latency performance. Experimental results show that NeuroEdge achieves a real-time classification accuracy of 90
PyFR is an open-source cross-platform computational fluid dynamics framework based on the high-order Flux Reconstruction approach, specifically designed for undertaking high-accuracy scale-resolving simulations in the vicinity of complex engineering geometries. Since the initial release of PyFR v0.1.0 in 2013, a range of new capabilities have been added to the framework, with a view to enabling industrial adoption of the capability. This paper provides details of those enhancements as released in PyFR v2.0.3, explains efforts to grow an engaged developer and user community, and provides latest performance and scaling results on up to 1024 AMD Instinct MI250X accelerators of Frontier at ORNL (each with two GCDs), and up to 2048 NVIDIA GH200 GPUs on Alps at CSCS.
Creativity researchers sometimes employ linkography-a family of techniques involving the visualization and analysis of links between design moves-to make sense of people's behavior in creative contexts, but traditional linkography (which involves manual annotation of both moves and links) is so time-consuming that it is mostly applied at very small scales. Meanwhile, digital creativity support tools (e.g., text-to-image prompting tools) automatically capture vast numbers of user interaction traces, but these traces are not yet well understood. We introduce a means of quickly and automatically producing fuzzy linkographs of text-to-image prompting traces and apply this technique to a large corpus of traces collected from the live deployment of a commercial text-to-image tool. This allows us to uncover recurring linkographic structures in text-to-image prompting interactions; cluster traces to classify user behaviors into several distinct archetypes; and quickly sift through thousands of traces to surface structurally interesting episodes of prompting.
This paper explores how to promote consumer credit to boost household consumption and thus promote economic development. The authors point out that China's chronically high savings rate is not conducive to economic growth. Therefore, by increasing the use of consumer credit, the savings rate can be reduced and the consumption level can be raised. Through the perspective of behavioral economics, this paper proposes an experimental design to study the effects of simplified billing and incentives on consumers' use of consumer credit. The experimental results show that only when simplification and preference exist at the same time can consumers significantly increase their choice of consumer credit. In addition, consumers are paying more attention to transparency and actual offers when choosing consumer credit, rather than just simplification or offers themselves. This shows that in order to attract consumers effectively, consumer credit products need not only a clear and concise structure, but also attractive preferential policies. The study also found that age, gender, and education level were not significant in this experiment, suggesting that these demographic characteristics have less impact on consumer credit choices. Overall, the paper concludes that modern consumers are more inclined to choose credit products that are both simple and affordable, which can help boost consumption and thus further promote economic development.
Background: Eating disorder (ED) recovery is challenging, with high relapse rates and frequent treatment dissatisfaction. While standard treatments address symptoms, they may not adequately target underlying issues like diminished psychological agency, reward dysfunction (anhedonia), trauma impacts, and cultural influences. There is a need for integrated models that address these multifaceted components. This study protocol outlines research designed to investigate a novel "Empowered Recovery" framework, positing that fostering agency, particularly in dietary and physical activity choices within a trauma-informed and culturally sensitive context, is linked to reduced anhedonia and improved, sustainable well-being. Methods: This study will employ a cross-sectional, mixed-methods design. Adults (18+) currently in or within 5 years postED treatment will be recruited internationally via online platforms and advocacy organizations. Data collection will involve secure online surveys assessing demographics, ED/treatment history, trauma history (e.g., PC-PTSD-5), perceived agency in diet/activity, ED symptoms (e.g., EDE-Q 12), depression (PHQ-9), anxiety (GAD-7), anhedonia (e.g., SHAPS), well-being (e.g., WHO-5), interoceptive awareness (e.g., MAIA subscale), and perceived empowerment (e.g., HES). Semi-structured qualitative interviews (~15-20 participants) will explore experiences of agency, reward, trauma, and culture in depth. Quantitative data will be analyzed using descriptive statistics, correlations, and regression analyses. Qualitative data will undergo thematic analysis. Findings will be integrated to provide a comprehensive understanding of the relationships between agency, reward, context, and recovery. Discussion: This study is expected to provide empirical support for the "Empowered Recovery" framework, potentially identifying agency as a key mechanism influencing motivation and reward-related experiences in ED recovery. Findings could inform clinical practice by highlighting the therapeutic potential of prioritizing patient autonomy, trauma-informed care, and cultural sensitivity. It may also encourage a broader definition of recovery beyond symptom reduction. Potential challenges include online recruitment biases and reliance on self-report measures. Registration: This study protocol was preregistered on OSF Registries (DOI: https://doi.org/10.17605/OSF.IO/VZCNF) on May 1, 2025, registration pending final approval.
