cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.28575158
title: Results for SAP-SAM in "Detecting Undesired Process Behavior by Means of Retrieval Augmented Generation"

description: This data collection contains all results for the SAP-SAM dataset for the used approach and baselines. Due to capacity limits of GitHub, they are published separately.
DOI: 10.15468/dl.kauwqc
title: Occurrence Download

description: A dataset containing 24 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Uganda",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Cynometra alexandri C.H.Wright"
 ]
}

 The dataset includes 24 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013628-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21227/7cwy-ks12
title: "Improve UAV accuracy and loss testing by leveraging the Laplace equation and enhanced experience replay using least recently used (LRU) memory."

description: "The need to enhance coverage and capacity in response to unpredictable situations facing telecommunication operators has become a significant topic of conversation. Ground-based stations often fail to provide adequate coverage and capacity when a user transitions from one coverage area to another due to obstacles that limit signal strength. To address this recurrent issue, we utilize Unmanned Aerial Vehicles (UAV) as airborne base stations that receive directives from a controller network via the x2 interface to assist users in blind spots. The controller employs the Shapley Additive Explanation to choose the appropriate UAV for serving users, while the UAV applies the Laplace equation and Slack variables to attain optimal signal quality. The challenge is modeled as a Markov Decision Process, with Deep Deterministic Policy Gradient (DDPG) and Recurrent Twin Delayed Deep Deterministic Policy Gradient (RTD3) used to solve it. Furthermore, we employ the least recently used mechanism to enhance prioritized experience replay memory, thereby improving the training process of DDPG and RTD3 to address the UAV and controller problem, respectively. Extensive simulations have been conducted, and the results are superior to the baselines."
DOI: 10.15468/dl.8wkvt7
title: Occurrence Download

description: A dataset containing 1462 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Styrax formosanus Matsum.)",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Living Specimen, Machine Observation, Literature Occurrence)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 1462 records from 26 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009466-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.18738/t8/tp6scx
title: Replication Data for: Temperature-dependent liquid water complex refractive index (V2 2026)

description: This is the complex refractive index (CRI) of liquid water dataset. Details are included in the README. The MATLAB code and its README is in the Opticon_SW_Jan20.zip.
DOI: 10.15468/dl.8xa2z9
title: Occurrence Download

description: A dataset containing 17031 records in GBIF matching the query:
SELECT
 '20' AS fish_cell,
 GBIF_MGRSCode(1000, decimalLatitude, decimalLongitude, 0) AS cell, -- NO randomization
 COUNT(DISTINCT speciesKey) AS species_richness
 FROM occurrence
 WHERE hasCoordinate = TRUE
 AND speciesKey IS NOT NULL
 AND NOT ARRAY_CONTAINS(issue, 'ZERO_COORDINATE')
 AND NOT ARRAY_CONTAINS(issue, 'COORDINATE_OUT_OF_RANGE')
 AND NOT ARRAY_CONTAINS(issue, 'COORDINATE_INVALID')
 AND NOT ARRAY_CONTAINS(issue, 'COUNTRY_COORDINATE_MISMATCH')
 AND decimalLatitude &gt;= -33.06103686093294
 AND decimalLatitude &lt;= -28.773895969281842
 AND decimalLongitude &gt;= -66.79339852040943
 AND decimalLongitude &lt;= -59.54300976905608
 AND "year" &gt;= 2015
 AND "year" &lt;= 2026
 AND (coordinateUncertaintyInMeters &lt;= 100 OR coordinateUncertaintyInMeters IS NULL)
 GROUP BY fish_cell, cell

 The dataset's 17031 records were derived from 76 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003008-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.s3c885
title: Occurrence Download

description: A dataset containing 851 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Country is United States of America",
 "Geometry POLYGON((-120.65382 34.90934,-120.52241 34.50403,-118.74012 34.025,-117.83961 33.58374,-117.18435 32.90979,-116.67761 32.83014,-116.95017 35.01727,-120.65382 34.90934))",
 "OccurrenceStatus is Present",
 "TaxonKey is Iris oratoria",
 "Year 1994-2026"
 ]
}

 The dataset includes 851 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003030-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ttgbe8
title: Occurrence Download

description: A dataset containing 162391 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "TaxonKey is Acanthephyra acutifrons",
 "TaxonKey is Acanthephyra curtirostris",
 "TaxonKey is Acanthephyra smithi",
 "TaxonKey is Acanthinula aculeata",
 "TaxonKey is Acanthodactylus boskianus",
 "TaxonKey is Acanthodactylus erythrurus",
 "TaxonKey is Acanthodactylus opheodurus",
 "TaxonKey is Acanthodactylus pardalis",
 "TaxonKey is Acanthodactylus schmidti",
 "TaxonKey is Acanthodactylus schreiberi",
 "TaxonKey is Acanthodactylus scutellatus",
 "TaxonKey is Acanthophis praelongus",
 "TaxonKey is Acartia clausi",
 "TaxonKey is Acartia latisetosa",
 "TaxonKey is Acartia longiremis",
 "TaxonKey is Acartia pacifica",
 "TaxonKey is Acartia tonsa",
 "TaxonKey is Acipenser gueldenstaedtii",
 "TaxonKey is Acipenser ruthenus"
 ]
 },
 "HasCoordinate is true"
 ]
}

 The dataset includes 162391 records from 646 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002928-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sj3zue
title: Occurrence Download

description: A dataset containing 756 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is CAS Ornithology (ORN)",
 "OccurrenceStatus is Present",
 "TaxonKey is Aphelocoma californica"
 ]
}

 The dataset includes 756 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003031-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.s4tuym
title: Occurrence Download

description: A dataset containing 641 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (Mexico, United States of America)",
 "TaxonKey is Herpailurus yagouaroundi"
 ]
}

 The dataset includes 641 records from 23 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003032-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.29104652
title: Characterization of monkeypox virus clade IIb lineage B1 strains in animal models: insights into virulence

description: Characterization of monkeypox virus clade IIb lineage B1 strains in animal models: insights into virulence
DOI: 10.6084/m9.figshare.29104652.v1
title: Characterization of monkeypox virus clade IIb lineage B1 strains in animal models: Insights into virulence

description: Characterization of monkeypox virus clade IIb lineage B1 strains in animal models: Insights into virulence
DOI: 10.6084/m9.figshare.29104652.v2
title: Characterization of monkeypox virus clade IIb lineage B1 strains in animal models: insights into virulence

description: Characterization of monkeypox virus clade IIb lineage B1 strains in animal models: insights into virulence
DOI: 10.6084/m9.figshare.31116231
title: Impression-Guided Interactive Personalized Color Exploration Framework for Dynamic Projection Mapping Makeup

description: Personalized makeup color exploration is crucial to enhance user experience in applications such as cosmetic recommendations. While virtual makeup offers accessible solutions for this exploration, traditional 2D overlay methods viewed through smartphone or tablet screens often lack realism and fail to precisely simulate how colors appear under real-world lighting. In contrast, Dynamic Projection Mapping (DPM) makeup provides greater realism by projecting colors onto the user’s face, enabling direct human observations. This paper focuses on personalized makeup color exploration using DPM. We propose a novel framework to help non-expert users efficiently find satisfying results in the vast space of color combinations. First, we introduce a text-to-makeup-color model that efficiently generates makeup colors based on impression text input. Then, we propose a projection-in-the-loop method to interactively refine makeup colors. Through this method, users can further match their personal preferences and suit their skin tone and lip color by directly observing the final effect on their faces. We validated our system through three evaluations: (1) an online survey (<i>N =</i> 100) and an impression-targeted experiment (<i>N =</i> 5) to verify feasibility and efficiency of the text-to-makeup-color model; (2) a simulated experiment to assess convergence performance in goal-oriented color search; and (3) a user study (<i>N =</i> 15) and an expert interview (<i>N =</i> 3) evaluating usability and user experience. Results show that our framework enables efficient and user-friendly makeup color exploration over baseline methods.
DOI: 10.6084/m9.figshare.31116231.v1
title: Impression-Guided Interactive Personalized Color Exploration Framework for Dynamic Projection Mapping Makeup

description: Personalized makeup color exploration is crucial to enhance user experience in applications such as cosmetic recommendations. While virtual makeup offers accessible solutions for this exploration, traditional 2D overlay methods viewed through smartphone or tablet screens often lack realism and fail to precisely simulate how colors appear under real-world lighting. In contrast, Dynamic Projection Mapping (DPM) makeup provides greater realism by projecting colors onto the user’s face, enabling direct human observations. This paper focuses on personalized makeup color exploration using DPM. We propose a novel framework to help non-expert users efficiently find satisfying results in the vast space of color combinations. First, we introduce a text-to-makeup-color model that efficiently generates makeup colors based on impression text input. Then, we propose a projection-in-the-loop method to interactively refine makeup colors. Through this method, users can further match their personal preferences and suit their skin tone and lip color by directly observing the final effect on their faces. We validated our system through three evaluations: (1) an online survey (<i>N =</i> 100) and an impression-targeted experiment (<i>N =</i> 5) to verify feasibility and efficiency of the text-to-makeup-color model; (2) a simulated experiment to assess convergence performance in goal-oriented color search; and (3) a user study (<i>N =</i> 15) and an expert interview (<i>N =</i> 3) evaluating usability and user experience. Results show that our framework enables efficient and user-friendly makeup color exploration over baseline methods.
DOI: 10.6084/m9.figshare.31116234
title: The Age of Human Comparison With AI: Development of AI Competence Anxiety Scale and AI Optimism Scale and Their Relationship With Generative AI Literacy and AI Self-Efficacy

description: The sudden penetration of artificial intelligence (AI) into daily life prompts individuals to compare their own competence with that of AI technologies. Moreover, the expectation that AI will bring many benefits keeps optimism about AI alive. Accordingly, we aimed to develop the AI Competence Anxiety Scale (AICAS) (in Studies I and II) and the AI Optimism Scale (AIOS) (in Studies III and IV) and to examine the serial mediating role of AI self-efficacy and AI optimism between generative AI (GenAI) literacy and AI competence anxiety (in Study V). Exploratory factor analysis revealed a single-factor structure for the AICAS and AIOS, and Item Response Theory found high discrimination of the items (Study I for AICAS and Study III for AIOS). Model fit values, convergent validity, composite reliability, and reliability coefficients of AICAS and AIOS were within the acceptance range (Study II for AICAS and Study IV for AIOS). As evidence of criterion-related validity, AI competence anxiety showed significant associations with AI anxiety and acceptance, whereas AI optimism was significantly related to digital well-being and AI self-efficacy. Study V found that AI self-efficacy and AI optimism mediated the relationship between GenAI literacy and AI competence anxiety. These results suggest that AICAS, for measuring AI competence anxiety, and AIOS for measuring AI optimism, are valuable and valid. They also suggest that GenAI literacy-based strategies have the potential to alleviate AI competence anxiety by enhancing AI self-efficacy and AI optimism.
DOI: 10.6084/m9.figshare.31116234.v1
title: The Age of Human Comparison With AI: Development of AI Competence Anxiety Scale and AI Optimism Scale and Their Relationship With Generative AI Literacy and AI Self-Efficacy

description: The sudden penetration of artificial intelligence (AI) into daily life prompts individuals to compare their own competence with that of AI technologies. Moreover, the expectation that AI will bring many benefits keeps optimism about AI alive. Accordingly, we aimed to develop the AI Competence Anxiety Scale (AICAS) (in Studies I and II) and the AI Optimism Scale (AIOS) (in Studies III and IV) and to examine the serial mediating role of AI self-efficacy and AI optimism between generative AI (GenAI) literacy and AI competence anxiety (in Study V). Exploratory factor analysis revealed a single-factor structure for the AICAS and AIOS, and Item Response Theory found high discrimination of the items (Study I for AICAS and Study III for AIOS). Model fit values, convergent validity, composite reliability, and reliability coefficients of AICAS and AIOS were within the acceptance range (Study II for AICAS and Study IV for AIOS). As evidence of criterion-related validity, AI competence anxiety showed significant associations with AI anxiety and acceptance, whereas AI optimism was significantly related to digital well-being and AI self-efficacy. Study V found that AI self-efficacy and AI optimism mediated the relationship between GenAI literacy and AI competence anxiety. These results suggest that AICAS, for measuring AI competence anxiety, and AIOS for measuring AI optimism, are valuable and valid. They also suggest that GenAI literacy-based strategies have the potential to alleviate AI competence anxiety by enhancing AI self-efficacy and AI optimism.
DOI: 10.15468/dl.28srxm
title: Occurrence Download

description: A dataset containing 122 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "OccurrenceStatus is Present",
 "TaxonKey is Flabellinopsis iodinea"
 ]
}

 The dataset includes 122 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003034-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tzcxqe
title: Occurrence Download

description: A dataset containing 2067 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Asia",
 "Country is Kazakhstan",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Passer montanus",
 "Year 2015-2026"
 ]
}

 The dataset includes 2067 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003035-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wpt9mf
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((100.732 1.97218, 100.661696 1.966612, 100.593124 1.950044, 100.527974 1.922885, 100.467851 1.885804, 100.414237 1.839715, 100.36845 1.785753, 100.331618 1.725247, 100.304648 1.659688, 100.288202 1.59069, 100.282685 1.519953, 100.288231 1.449218, 100.304703 1.380227, 100.331694 1.314678, 100.368539 1.254185, 100.41433 1.200237, 100.46794 1.154162, 100.52805 1.117094, 100.593179 1.089945, 100.661725 1.073384, 100.732 1.067818, 100.802275 1.073384, 100.870821 1.089945, 100.93595 1.117094, 100.99606 1.154162, 101.04967 1.200237, 101.095461 1.254185, 101.132306 1.314678, 101.159297 1.380227, 101.175769 1.449218, 101.181315 1.519953, 101.175798 1.59069, 101.159352 1.659688, 101.132382 1.725247, 101.09555 1.785753, 101.049763 1.839715, 100.996149 1.885804, 100.936026 1.922885, 100.870876 1.950044, 100.802304 1.966612, 100.732 1.97218))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003036-260120142942310/datasets/export for details.
DOI: 10.6084/m9.figshare.31113063
title: Time-Varying Path-Specific Direct and Indirect Effects: A Novel Approach to Examine Dynamic Behavioral Processes with Application to Smoking Cessation

description: Behavioral processes are often complex, and vary over time, requiring intensive longitudinal data to effectively capture the dynamic elements involved. For example, examining daily socio-behavioral and treatment adherence data collected during a smoking quit attempt, can reveal how, when, and why withdrawal symptoms change, offering insight into critical windows of relapse-risk in the cessation process. However, analytical methods (e.g., time-varying causal mediation methods), that can translate such intensive longitudinal data into time-varying causal effects remain limited, hindering a deeper understanding of these dynamic behavioral processes. We propose a new approach, augmented mediational g-formula with a two-step estimation strategy, to estimate time-varying causal (in)direct effects. Its performance was evaluated <i>via</i> simulation, comparing bias, precision, and alignment with the product-of-coefficients approach. The optimal approach identified by the simulation study was applied to data from the Wisconsin Smokers’ Health Study II, for assessing the effect of randomized pharmacological treatment assignment (exposure) on daily smoking cessation outcome(s), mediated <i>via</i> daily treatment adherence, in the presence of a time-varying confounder (daily stress). Daily stress was due to social contextual factors but not affected by the exposure. Within its scope, this study serves as a preliminary framework for studying the causal structure of time-varying bio-behavioral processes.
DOI: 10.6084/m9.figshare.31113063.v1
title: Time-Varying Path-Specific Direct and Indirect Effects: A Novel Approach to Examine Dynamic Behavioral Processes with Application to Smoking Cessation

description: Behavioral processes are often complex, and vary over time, requiring intensive longitudinal data to effectively capture the dynamic elements involved. For example, examining daily socio-behavioral and treatment adherence data collected during a smoking quit attempt, can reveal how, when, and why withdrawal symptoms change, offering insight into critical windows of relapse-risk in the cessation process. However, analytical methods (e.g., time-varying causal mediation methods), that can translate such intensive longitudinal data into time-varying causal effects remain limited, hindering a deeper understanding of these dynamic behavioral processes. We propose a new approach, augmented mediational g-formula with a two-step estimation strategy, to estimate time-varying causal (in)direct effects. Its performance was evaluated <i>via</i> simulation, comparing bias, precision, and alignment with the product-of-coefficients approach. The optimal approach identified by the simulation study was applied to data from the Wisconsin Smokers’ Health Study II, for assessing the effect of randomized pharmacological treatment assignment (exposure) on daily smoking cessation outcome(s), mediated <i>via</i> daily treatment adherence, in the presence of a time-varying confounder (daily stress). Daily stress was due to social contextual factors but not affected by the exposure. Within its scope, this study serves as a preliminary framework for studying the causal structure of time-varying bio-behavioral processes.
DOI: 10.15468/dl.xc6trj
title: Occurrence Download

description: A dataset containing 3764593 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Salmo trutta)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 3764593 records from 703 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002999-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.