Dementia in LMICs may be a syndemic: a "Population Neuroscience–Dementia Syndemics" framework links women’s risk to interacting diseases, stress pathways, and structural factors like poverty and environment
You might wonder why not just put everything that is “infrastructure related” in a dedicated directory inside the Business-Module. That’s the approach often taken in many designs in the wild, but the problem with such a weak separation is that it tends to erode (and after many months you discover that a business class peeks messages in a broker). Another problem is that it’s much harder to find the boundary for unit tests (whereas with BM and IM separated, you can just assume that the public API of BM is what should be unit tested).
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即将召开的十四届全国人大四次会议对于动员全国各族人民更加紧密地团结在以习近平同志为核心的党中央周围，凝心聚力贯彻落实党中央决策部署，确保“十五五”开好局、起好步，具有重要意义。站在新起点，踏上新征程，十四届全国人大及其常委会将坚持以习近平新时代中国特色社会主义思想为指导，深刻领悟“两个确立”的决定性意义，增强“四个意识”、坚定“四个自信”、做到“两个维护”，认真履行宪法法律赋予的职责，坚持好、完善好、运行好人民代表大会制度，为以中国式现代化全面推进强国建设、民族复兴伟业提供坚实制度保障、汇聚奋进力量。
春节假期，无锡街头张灯结彩，地下5米的220千伏惠拈线电缆隧道内阴暗湿冷，何光华手持红外测温仪，沿着电缆逐段扫描。这条深埋地下的电缆，是连接马山算力中心与无锡乃至更广阔区域数字经济的“能量动脉”。
Many people reading this will call bullshit on the performance improvement metrics, and honestly, fair. I too thought the agents would stumble in hilarious ways trying, but they did not. To demonstrate that I am not bullshitting, I also decided to release a more simple Rust-with-Python-bindings project today: nndex, an in-memory vector “store” that is designed to retrieve the exact nearest neighbors as fast as possible (and has fast approximate NN too), and is now available open-sourced on GitHub. This leverages the dot product which is one of the simplest matrix ops and is therefore heavily optimized by existing libraries such as Python’s numpy…and yet after a few optimization passes, it tied numpy even though numpy leverages BLAS libraries for maximum mathematical performance. Naturally, I instructed Opus to also add support for BLAS with more optimization passes and it now is 1-5x numpy’s speed in the single-query case and much faster with batch prediction. 3 It’s so fast that even though I also added GPU support for testing, it’s mostly ineffective below 100k rows due to the GPU dispatch overhead being greater than the actual retrieval speed.