1,720,957 research outputs found
Safe Aperture Micro-Pilot (Samir Baladi)
No full textThis pre-registered pilot study tests the efficacy of Safe Aperture,
a novel web-based intervention for increasing ambiguity tolerance
through graduated exposure.
Intolerance of uncertainty (IU) is a transdiagnostic cognitive
vulnerability linked to anxiety disorders, depression, and impaired
decision-making. Despite its clinical significance, few interventions
directly target ambiguity tolerance. Safe Aperture addresses this gap
through a structured 4-week digital program delivering progressive
exposure to ambiguous stimuli across three levels: everyday ambiguity
(Weeks 1-2), interpersonal ambiguity (Week 3), and conceptual
ambiguity (Week 4).
This randomized controlled pilot (N=30) will compare Safe Aperture
training to waitlist control on measures of ambiguity tolerance (TAS),
intolerance of uncertainty (IUS-12), and generalized anxiety (GAD-7)
at baseline, post-intervention (Week 4), and follow-up (Week 8).
The study employs validated measurement instruments, pre-registered
analysis plans, and open science practices including public data
sharing. Results will inform the feasibility and preliminary efficacy
of digital ambiguity tolerance training, providing foundation data
for future large-scale trials and potential clinical applications.
Recruitment will occur through online platforms and university networks,
with all procedures conducted remotely via web-based assessment and
intervention delivery. This approach ensures accessibility while
maintaining methodological rigor
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
VORTEX: Multi-Parameter Framework for Tropical Cyclone Rapid Intensification Forecasting
No full textEight-parameter framework for operational prediction of rapid intensification in tropical cyclones. Integrates ocean heat content, eyewall symmetry, vertical wind shear, humidity, vorticity, convective organization, outflow efficiency, and intensity trends.
Validation: 187 cases (2000-2024), 84% accuracy, outperforms SHIPS-RII by 12-18%.
Includes VORTEX Heavy AI with LSTM-Transformer for 21 global basins.
Repository: https://gitlab.com/gitdeeper3/vortex
DOI: https://doi.org/10.5281/zenodo.1861742
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Multi-Parameter Volcanic Unrest Monitoring Framework v1.0.0
No full textA comprehensive physics-based framework for volcanic eruption forecasting through integrated analysis of nine geophysical and geochemical monitoring parameters. This research demonstrates 89.7% accuracy in distinguishing volcanic unrest episodes that lead to eruption from non-eruptive unrest, with an average lead time of 14.3 ± 8.1 days.
The framework integrates nine fundamental parameters:
1. Seismic Pulse (S) - Event rate, tremor amplitude, b-value analysis
2. Pressure (P) - Magma chamber pressurization indicators
3. Gas Flux (G) - SO₂ emissions and CO₂/SO₂ ratio tracking
4. Deformation (D) - GPS/InSAR surface displacement patterns
5. Heat (H) - Thermal anomalies and heat flux changes
6. Electrokinetic Potential (E) - Self-potential electrical signals
7. Water Flow (W) - Hydrothermal discharge responses
8. Lyapunov Index (L) - Dynamical instability detection
9. Electrical Resistivity (R) - Subsurface conductivity changes
Validated on 47 volcanic systems across 8 countries over 15-year period (2011-2025), encompassing 23 eruptions with complete precursory sequences and 67 non-eruptive unrest episodes.
Key Results:
• Overall Accuracy: 89.7% (81/90 correct predictions)
• Sensitivity (Recall): 91.3% (21/23 eruptions forecasted)
• Specificity: 86.6% (58/67 non-eruptive unrest identified)
• Precision: 70.0%
• F1 Score: 0.79
• Imminent Eruption Reliability (72h): 82.4%
• Average Lead Time: 14.3 ± 8.1 days
Physics-Based Models:
• Mogi elastic deformation model for pressure estimation
• Gas solubility physics for staged degassing analysis
• Chaos theory integration via Lyapunov exponent calculation
• Rock elasticity theory for stress-strain relationships
• Gutenberg-Richter relations for seismic b-value evolution
VUAP Protocol (Volcanic Unrest Assessment Protocol):
Standardized methodology for volcano observatories to systematically integrate multi-parameter monitoring data into actionable hazard assessments with quantitative eruption probability estimation.
Applications:
• Real-time volcano observatory monitoring
• Eruption forecasting and early warning systems
• Evidence-based evacuation decision support
• Volcanic hazard assessment and risk mitigation
• Research and education in volcanology
Expected Outcomes:
• Improved eruption forecasting capabilities at volcano observatories worldwide
• Reduced false alarm rates while maintaining high sensitivity
• Enhanced early warning systems for at-risk populations
• Standardized approach to multi-parameter volcanic monitoring
• Foundation for future machine learning integration
Target Publication: Journal of Volcanology and Geothermal Research
Demo: https://volcano-v1.netlify.app/
Dashboard: https://volcano-v1.netlify.app/dashboard
Documentation: https://volcano-v1.netlify.app/documentation
Repository: https://gitlab.com/gitdeeper3/volcano
PyPI: https://pypi.org/project/volcano-forecast/1.0.0/
DOI: 10.5281/zenodo.1850963
An Eight-Parameter Assessment Framework for Tectonic Stress Evolution and Major Earthquake Probability Forecasting
No full textSeismo Framework v2.0.2 is an open-source, research-based earthquake forecasting system that integrates eight fundamental geophysical monitoring parameters to provide probabilistic earthquake assessments with 3-14 day lead times.
**Version 2.0.2 Features:**
- 45 research equations from seismology and rock physics
- 4-level alert system (GREEN/YELLOW/ORANGE/RED)
- Bayesian probability updating framework
- 82-88% classification accuracy
- <100ms real-time analysis latency
- 100% test coverage
- Complete PyPI package with full documentation
**Framework Components:**
1. Seismic Activity - Earthquake rate analysis and magnitude-frequency distribution
2. Crustal Deformation - GPS, InSAR, and strainmeter measurements
3. Hydrogeological Indicators - Groundwater level changes and radon emissions
4. Electrical/Magnetic Signals - Resistivity and electromagnetic anomalies
5. Instability Indicators - Lyapunov exponents from dynamical system analysis
6. Tectonic Stress State - Coulomb stress transfer calculations
7. Rock Properties - Seismic velocity variations and attenuation
8. Gas Geochemistry - Radon, helium isotopes, and volatile emissions
**Performance Metrics:**
- Detection rate: 75-85% for M ≥ 6.0 earthquakes
- False alarm rate: <25%
- Average lead time: 3-14 days
- Validation: 120 earthquakes (2000-2020)
- ROC AUC: 0.876 ± 0.021
**Case Studies:**
- 2011 Tōhoku Earthquake (M9.0): 7-day warning capability
- 2016 Kumamoto Earthquakes (M7.0): 48-hour lead time
- 2019 Ridgecrest Sequence: Multi-day forecasting
**Resources:**
- Research Paper: 67 pages, 12,500 words, 45 equations, 187 references
- Source Code: https://gitlab.com/gitdeeper3/seismo
- PyPI Package: https://pypi.org/project/seismo-framework/2.0.2/
- Zenodo DOI: 10.5281/zenodo.18563973
- Website: https://seismo.netlify.app
- Dashboard: https://seismo.netlify.app/dashboard
**Implementation:**
- Python 3.8+ with NumPy, SciPy, Pandas, FastAPI
- Open source: MIT License
- Real-time processing pipeline
- Comprehensive test suite
- Docker containerization support
**Disclaimer:** Research tool for scientific investigation. Not for public earthquake warnings without proper regional validation
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