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Earlier sources: Artificial Intelligence
Artificial intelligence covers systems that learn from data, generate content, perceive their surroundings, or act toward a goal. Follow model research, agent tooling, evaluation, and the infrastructure used to build and run these systems.
SYMTRI organizes observations from public sources into a living map. Connections reflect shared subject matter; they do not establish causation or endorse a source.
Open in the map ↗5982 classified signals in the fourteen-day window. Recent momentum: steady. These counts include signals awaiting readable evidence.
Earlier sources
Up to ten sources with readable evidence, ordered by their feed timestamp. These archive sources can be older than the live fourteen-day window. This list is a sample, not a measure of total activity. Dates distinguish paper publication, repository creation, model/dataset activity, Hacker News posts, and KEV catalog additions. “First archived” records when SYMTRI first stored the signal.
- Hacker News · Posted on Hacker News · First archived
Chinese AI tool told researchers how to make bioweapons ↗
Hacker News discussion.
- OpenAlex · Published · First archived
Differentially expressed miRNA Cargo From Boar Seminal Extracellular Vesicles Is Linked With Motility Quality in AI Doses ↗
Sperm motility is a key parameter for male selection and is closely linked to male fertility status. miRNAs have been proposed as fertility biomarkers, and their regulatory effects on sperm motility have been previously investigated. In the present study, the miRNA cargo from three different sources, seminal extracellular vesicles, free transcripts in seminal plasma and spermatozoa, was analysed from semen samples with high motility and reduced motility. Three differentially expressed miRNAs were identified in seminal extracellular vesicles (miR-6529-5p, miR-146a-5p and miR-15a-5p), two in sem…
- OpenAlex · Published · First archived
Predicting freeway incident duration using machine learning ↗
Accurate prediction of freeway incident duration is important for traffic management and emergency resource allocation. This study evaluates 32 machine-learning model configurations using 828 incident records from the G2504 Hangzhou Ring Freeway in China. Four fixed feature sets containing the top 6, 11, 16, and 21 predictors were defined from a Minimum Redundancy Maximum Relevance (MRMR) ranking. Each feature setting was evaluated using a 15% hold-out test set, seven repeated random splits, and sevenfold cross-validation within the training subset. All 32 machine-learning models were tuned wi…
- OpenAlex · Published · First archived
Selective Alkaline Leaching of Mechanochemically Activated Spent LiCoO2 Cathodes: Taguchi Optimization and Machine-Learning-Assisted Interpretation ↗
Selective alkaline leaching was evaluated as a pre-separation step for mechanochemically activated spent LiCoO2 cathodes. An L16(44) Taguchi design was used to assess the effects of the NaOH concentration, temperature, leaching time, and liquid-to-solid ratio on Li, Al, and Co extraction. The NaOH concentration was identified as the dominant factor controlling Li and Al extraction, whereas Co dissolution remained strongly suppressed under alkaline conditions. The best experimentally verified condition (6 mol L−1 NaOH, 80 °C, 90 min, L:S = 30 mL g−1) resulted in 82.96% Li extraction, 35.26% tot…
- OpenAlex · Published · First archived
A hybrid 4-DoF control for bidirectional series half three-level CLLC converter with minimum RMS current in solid state transformer ↗
The bidirectional series half three-level CLLC (SHBCLLC) converter is an attractive option for solid state transformer due to its high efficiency and bidirectional power flow capability. However, existing variable-frequency and pulse width modulation (PWM) modulation exhibit large inductor RMS current. Additionally, PWM control methods fail to achieve ZVS across the entire operating range. To address this issue, a four-degrees-of-freedom control (4-DoF) modulation strategy is proposed in this paper. The proposed modulation scheme achieves lower RMS current and full-range ZVS operation, thereby…
- OpenAlex · Published · First archived
The Effectiveness of the ARAI-Land (AR-AI for Wetland Ecosystem) e-Module to Improve Students’ 6 C Skills in Chemistry Learning ↗
Abstract High school chemistry learning increasingly requires instructional designs that support both conceptual understanding and 21st-century competencies. This study examined the effectiveness of ARAI-Land, an augmented reality and artificial intelligence-based e-module contextualized within wetland ecosystems, for teaching reaction rates and developing students’ 6 C skills: critical thinking, creativity, collaboration, communication, character, and citizenship. The study employed an Educational Design Research approach, followed the ADDIE development model, and used a convergent mixed-meth…
- OpenAlex · Published · First archived
A Guided Implicit Generative Adversarial CNN–Transformer Framework for Class-Imbalanced Hyperspectral Image Classification ↗
Hyperspectral image (HSI) classification is important for land-cover recognition and remote-sensing scene analysis. However, class imbalance severely limits performance when minority classes contain only a few labeled samples, causing models to show strong overall results while failing to identify minority classes effectively. We propose a 3D guided implicit generative adversarial oversampling model (3D-GIGAMO), a generation–classification collaborative framework that alleviates class imbalance by producing class-conditioned minority-class patches for task-oriented oversampling, while learning…
- OpenAlex · Published · First archived
Screening Circular-Economy Reuse Pathways for Phosphate Mine Waste Rock with Explainable Machine Learning: A Proof of Concept from the Benguerir Mine, Morocco ↗
Phosphate mining secures the world’s fertilizer supply, yet it leaves behind large volumes of mine waste rock (MWR), most of which is stockpiled as a liability rather than managed as a resource. These stockpiles occupy land, affect local water quality, and represent a secondary resource left unused, at a cost to the sustainability of the sector. The practical obstacle to reuse is rarely a shortage of applications; it is the slow, sample-by-sample expert assessment needed to decide which material qualifies for which pathway. This study tests whether that decision step can be automated with the…
- OpenAlex · Published · First archived
Turning Free-to-Use Generative AI into Flipped-Interaction Intelligent Tutors: Exploring Student Engagement and Perceptions of Learning ↗
Abstract An engaging and cost-effective digital tool for developing subject-matter knowledge (SMK) could mitigate educational inequities in resource-constrained contexts. This case study explores the effectiveness of free generative artificial intelligence (GAI) platforms, prompted to function as a Flipped-Interaction Intelligent Tutoring System (FIITS), to promote science student-teacher SMK learning. Data were collected across a 10-week intervention from 42 third- and fourth-year natural and physical sciences student teachers at two campuses of a South African university. The students engage…
- OpenAlex · Published · First archived
Can Large Language Model-Based Chatbots Support Sustainable AI-Enhanced Education? Evidence from Young Learners’ Conceptions ↗
Understanding learners’ conceptions of artificial intelligence (AI)-supported learning can inform the sustainable integration of AI into education. This study examined primary school students’ conceptions of large language model-based (LLM-based) chatbots-supported learning and explored differences associated with learning motivation. Seventy-two students participated in learning activities designed around the CLEAR prompt-engineering framework. A mixed-methods approach combined the draw-and-write technique with questionnaires assessing learning motivation, self-efficacy, and critical thinking…
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How to assess evidence about Artificial Intelligence
Check each original source for its methods, release status, limitations, and supporting data. A repository announcement, a preprint, and a published study provide different kinds of evidence. SYMTRI’s subject classification helps discovery; it does not independently validate the source’s claims.
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