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Earlier sources: Science
Science investigates the natural world through observation, experiments, and mathematical models. Explore papers and developments in biology, medicine, materials, neuroscience, physics, climate, and mathematics; a reported finding is not necessarily established consensus.
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 ↗1450 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.
- OpenAlex · Published · First archived
Genome-Wide Identification and Functional Validation of the Cold-Tolerance WRKY Transcription Factor in Sweetpotato ↗
Sweetpotato (Ipomoea batatas (L.) Lam.) is a vital global food crop whose production and geographical distribution are severely constrained by low-temperature stress. While WRKY transcription factors are known to regulate plant stress responses, their specific roles in sweetpotato cold tolerance remain largely unexplored. In this study, we conducted a genome-wide identification of the WRKY family in the hexaploid sweetpotato genome, identifying 476 IbWRKYs classified into three major groups and seven subgroups. Synteny analyses revealed that whole-genome duplication (WGD)/segmental duplication…
- OpenAlex · Published · First archived
Universal physics-informed machine learning framework for the prediction of porosity defects in high-power laser beam welding with different metallic materials ↗
High-power laser beam welding (LBW) is a widely used joining technique for metallic materials. However, porosity defects frequently arise during the process, leading to significant degradation of weld properties. Accurate prediction of porosity remains challenging due to the highly nonlinear and material-dependent underlying physics. In this study, a universal physics-informed machine learning framework is proposed to predict porosity levels in the LBW of aluminum and steel. Systematic LBW experiments were conducted to quantify porosity ratios across a broad parametric space. In parallel, a we…
- OpenAlex · Published · First archived
A Collective CRISPR-Cas12a Biosensing Platform for Effect-Based Screening of Pesticide Residues ↗
The simultaneous screening of multicomponent pesticide residues, rather than a single specific compound, remains a critical yet challenging frontier in safety surveillance, largely due to the inherent one-to-one recognition bottleneck in conventional aptamer- or antibody-based biosensors. Herein, we develop a collective CRISPR-Cas12a biosensing platform for effect-based screening of pesticide residues by integrating effect-based enzymatic recognition with PAM-independent CRISPR signal amplification. Rather than employing a dedicated aptamer or antibody for each pesticide, the proposed strategy…
- OpenAlex · Published · First archived
Hygroscopic behaviour and colour stability of 3D-printed and thermoformed aligner materials: an in vitro study ↗
Abstract Background Directly 3D-printed aligner materials have recently emerged as an alternative to established thermoformed clear aligners. The aim of this in vitro study was to investigate the colour stability, water sorption, and water solubility of directly 3D-printed aligner materials in comparison with an established thermoformed reference, as these properties are essential for clinical performance but currently insufficiently investigated for directly 3D-printed aligners. Methods Tera Harz TC-85DAC, Freeprint Aligner, Freeprint Aligner with digital polishing, Dental LT Clear V2 and one…
- OpenAlex · Published · First archived
A Physics-Guided Statistical Framework for Bearing Fault Diagnosis Under Unit Variability and Rotational Speed Uncertainty ↗
Reliable bearing fault diagnosis must differentiate between defects and normal-operation-condition variation. The predictor must remain accurate when shaft speed is uncertain. Conventional accuracy-driven models often ignore false-positive rates and fail to accurately locate faults on unseen bearings’ data. This study proposes a physics-guided statistical framework that integrates resolution-based order screening, envelope peak-to-floor evidence, search- and collision-matched empirical nulls, and conformal calibration against healthy reference data. A two-stage bearing-level rule detects abnor…
- OpenAlex · Published · First archived
Integrated Two-Step Membrane Chromatography for Robust and High-Throughput Plasmid DNA Purification ↗
Plasmid DNA (pDNA) is a key raw material for advanced therapeutic modalities, including gene therapy, mRNA production, and DNA vaccination, requiring efficient and scalable downstream processing strategies. Increasing demand places stringent requirements on purification processes in terms of yield, impurity removal, preservation of plasmid topology, and robustness at scale. Membrane chromatography offers significant advantages for pDNA purification due to convective mass transfer, enabling high binding capacity at short residence times and straightforward linear scale-up. For the first time, a…
- OpenAlex · Published · First archived
Development and Validation of Human-AI Collaborative Workflow in SNOMED CT Mapping of Bilingual Clinical Text ↗
Abstract Systematized Nomenclature of Medicine–Clinical Terminology (SNOMED CT) is the principal international standard for semantic interoperability of clinical information, but mapping free-text clinical narratives to SNOMED CT concepts remains labor-intensive. We developed a large language model agent system for mapping bilingual clinical text to SNOMED CT concepts and evaluated its effect on mapping accuracy and efficiency within a human-AI collaborative workflow. We designed a three-module agent system comprising translation, abbreviation expansion, and vector-based retrieval components,…
- OpenAlex · Published · First archived
Machine Learning for Screening Bioactive Compounds in Traditional Chinese Medicine: Computational Prediction, Multi-Omics Integration, and Clinical Translation Potential ↗
Identifying bioactive compounds in traditional Chinese medicine (TCM) requires computational prioritization to be connected with chemical and pharmacological evidence. This structured narrative and critical review examines machine learning applications in compound prediction, formula-compatibility analysis, multi-omics integration, and drug development and repurposing. Molecular fingerprints, graph and sequence representations, knowledge graphs, and generative models are discussed in relation to their intended endpoints and validation conditions. Studies are classified along two independent di…
- OpenAlex · Published · First archived
Low-Intensity Continuous Ultrasound vs. Traditional Ultrasound: A Systematic Review and Descriptive Analysis on Past and Future Gold Standards for Deep-Tissue Diathermy in Clinical Medicine ↗
Background/Objectives: The thermal effects of therapeutic ultrasound (US) have been utilized to promote musculoskeletal healing. However, the optimal combination of US parameters, while studied in the past, has yet to be updated with the advent of newer US modalities, including low-intensity continuous ultrasound (LICUS). The purpose of this study was to evaluate the effects of US frequency, intensity, and duration on changes in tissue temperature and to compare the thermal response between traditional US and LICUS. Methods: Following PRISMA guidelines, PubMed, Embase, and Web of Science were…
- OpenAlex · Published · First archived
Microfacet-based physics-driven framework for single-photon LiDAR rough-surface scattering and detection ↗
The scattering characteristics of rough surfaces play a fundamental role in single-photon LiDAR, remote sensing, and optical target characterization. Conventional electromagnetic models describe the underlying optical scattering process, whereas photon-counting statistics and detector response must be modeled separately to describe measurements in the single-photon regime. In this study, a unified simulation model for rough-surface scattering and single-photon detection is developed based on the microfacet model. The model incorporates laser emission, photon propagation, surface scattering, an…
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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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