{"data":[{"id":"10.5281/zenodo.21849021","type":"dois","attributes":{"doi":"10.5281/zenodo.21849021","identifiers":[{"identifier":"oai:zenodo.org:21849021","identifierType":"oai"}],"creators":[{"nameType":"Personal","givenName":"Michael","familyName":"Chin","name":"Chin, Michael","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","nameIdentifier":"0009-0003-3677-2635"}],"affiliation":[]}],"titles":[{"title":"Oscillatory Decay of Vorticity in High-Resolution DNS of 3D Navier-Stokes Equations: Evidence for Self-Frustration of Vortex Stretching"}],"publisher":"Zenodo","container":{},"publicationYear":2026,"subjects":[],"contributors":[],"dates":[{"date":"2026-08-07","dateType":"Issued"},{"date":"2026-08-08","dateType":"Issued"}],"language":"en","types":{"schemaOrg":"CreativeWork","resourceTypeGeneral":"Preprint","citeproc":"article","bibtex":"misc","ris":"GEN","resourceType":""},"relatedIdentifiers":[{"relationType":"IsVersionOf","relatedIdentifier":"10.5281/zenodo.21849020","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":[],"formats":[],"version":null,"rightsList":[{"rightsIdentifierScheme":"SPDX","rightsUri":"https://creativecommons.org/licenses/by/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rights":"Creative Commons Attribution 4.0 International","rightsIdentifier":"cc-by-4.0"},{"rightsUri":"http://rightsstatements.org/vocab/InC/1.0/","rights":"Michael Chin, 2026"}],"descriptions":[{"descriptionType":"Abstract","description":"We present a systematic numerical study of the 3D incompressible Navier-Stokes equations on T^3 = [0,2π)^3 at resolutions up to 1024^3, using a dealiased Fourier pseudo-spectral method. Three distinct initial conditions—a high-symmetry Kida-Pelz flow, anti-parallel vortex tubes, and a Hou-Luo vortex ring—are evolved at viscosity ν = 10^-4. In all cases, the maximum vorticity ‖ω‖_∞ exhibits growth → oscillation → decay, with the Beale-Kato-Majda (BKM) integral remaining finite. Energy spectrum analysis confirms adequate resolution (dx/η ≤ 1.87 \u003c 2.0) throughout the entire T=30 simulation. Direct computation of the vortex stretching term ω·S·ω reveals a self-frustration mechanism: (i) at peak vorticity, the stretch/compression ratio reverses from 1.41 to 0.96; (ii) in the decay phase, the vortex stretching functional S₄(t) decays exponentially with rate λ ≈ 0.33, yielding ∫S₄ \u003c ∞; (iii) at the maximum-vorticity point, ω·S·ω turns negative at t=20. Constantin-Fefferman direction analysis confirms cos²(ω, e₁) \u003c 0.5 throughout, with cos² → 0 at the vorticity peak. We prove a conditional regularity theorem (Theorem 1) under the exponential self-frustration condition (SFC''): if S₄(t) ≤ C₀e^(-λt), then the solution is globally smooth. The proof uses only the L⁴ vorticity equation, Nash's inequality, and Grönwall's lemma. Furthermore, we identify a group-theoretic origin of self-frustration in Kida flow: the discrete symmetry group restricts the solution to Λ_all (1/4 of Fourier modes), forbids 50% of triadic stretching interactions by parity, and forces the strain tensor to vanish (S=0) at peak-vorticity locations—providing a structural explanation for the observed exponential decay of S₄."}],"geoLocations":[],"fundingReferences":[],"url":"https://zenodo.org/doi/10.5281/zenodo.21849021","contentUrl":null,"metadataVersion":0,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"api","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":0,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":1,"created":"2026-08-09T13:18:21Z","registered":"2026-08-09T13:18:21Z","published":null,"updated":"2026-08-18T09:49:38Z"},"relationships":{"client":{"data":{"id":"cern.zenodo","type":"clients"}}}},{"id":"10.17632/m55t3nymt6.1","type":"dois","attributes":{"doi":"10.17632/m55t3nymt6.1","identifiers":[],"creators":[{"nameType":"Personal","affiliation":["Pontifícia Universidade Católica de Minas Gerais"],"givenName":"Marcello","familyName":"Barcellos","name":"Barcellos, 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The 2050 results are presented as ensemble median value along with their interquartile range (25th-75th percentiles). \n\n\n\n \n\n\n\n\n\ncountry_prices.xlsx Country-level producer prices by species (Cattle, Buffalo, Chicken, Duck, Goat, Horse, Pig, Sheep), reported as “Official” and “Official+Imputed” values for 2023. Units: USD tonne⁻¹\n\n\n\n \n\n\n\n\n\ncountry_animal_weight_kg.xlsx Country-level average live weight by species (Cattle, Buffalo, Chicken, Duck, Goat, Horse, Pig, Sheep), based on FAO (2003). Units: kg head⁻¹\n\n\n\n \n\n\n\n\n\ncountry_economic_risk_average_Dollar.xlsx Country-level potential economic value exposed to unsustainable blue-water consumption (1–3, 4–6, 7–9, 10–12 months per year), by species (Cattle, Buffalo, Chicken, Duck, Goat, Horse, Pig, Sheep), using the average of “Official” and “Official+Imputed” price series and considering baseline (2020), SSP1-2.6 (2050), and SSP5-8.5 (2050) scenarios. The 2050 results are presented as ensemble median value along with their interquartile range (25th-75th percentiles). Units: $ USD.\n\n\n\n \n\n\n\n\n\ncons_livestock_annual_2015_m3.tif Global 30 arc-minute GeoTIFF of annual direct livestock water consumption (drinking + service) for 2015. Units: m³ yr⁻¹\n\n\n\n \n\n\n\n\n\ncons_livestock_annual_2015_drinking_m3.tif Global 30 arc-minute GeoTIFF of annual livestock drinking-water consumption for 2015. Units: m³ yr⁻¹.\n\n\n\n \n\n\n\n\n\ncons_livestock_annual_2015_service_m3.tif Global 30 arc-minute GeoTIFF of annual livestock service-water consumption for 2015. 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The 2050 results are presented as ensemble median value along with their interquartile range (25th-75th percentiles). \n\n\n\n \n\n\n\n\n\ncountry_prices.xlsx Country-level producer prices by species (Cattle, Buffalo, Chicken, Duck, Goat, Horse, Pig, Sheep), reported as “Official” and “Official+Imputed” values for 2023. Units: USD tonne⁻¹\n\n\n\n \n\n\n\n\n\ncountry_animal_weight_kg.xlsx Country-level average live weight by species (Cattle, Buffalo, Chicken, Duck, Goat, Horse, Pig, Sheep), based on FAO (2003). Units: kg head⁻¹\n\n\n\n \n\n\n\n\n\ncountry_economic_risk_average_Dollar.xlsx Country-level potential economic value exposed to unsustainable blue-water consumption (1–3, 4–6, 7–9, 10–12 months per year), by species (Cattle, Buffalo, Chicken, Duck, Goat, Horse, Pig, Sheep), using the average of “Official” and “Official+Imputed” price series and considering baseline (2020), SSP1-2.6 (2050), and SSP5-8.5 (2050) scenarios. 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(#613)\n\nTagbot not working (#618)"}],"geoLocations":[],"fundingReferences":[],"url":"https://zenodo.org/doi/10.5281/zenodo.21992764","contentUrl":null,"metadataVersion":0,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"api","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":0,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":1,"created":"2026-08-18T09:49:19Z","registered":"2026-08-18T09:49:20Z","published":null,"updated":"2026-08-18T09:49:20Z"},"relationships":{"client":{"data":{"id":"cern.zenodo","type":"clients"}}}},{"id":"10.5061/dryad.g4f4qrg60","type":"dois","attributes":{"doi":"10.5061/dryad.g4f4qrg60","identifiers":[],"creators":[{"nameType":"Personal","affiliation":["University of Washington"],"name":"Maust, Autumn","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0009-0005-9108-8697"}]},{"nameType":"Personal","affiliation":["University of Washington"],"name":"Reese, Ellen","nameIdentifiers":[]},{"nameType":"Personal","affiliation":["University of Washington"],"name":"Strait, Madeleine","nameIdentifiers":[]},{"nameType":"Personal","affiliation":["University of Washington"],"name":"Tobin, Patrick","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-0237-7963"}]}],"titles":[{"title":"Data from: DNA metabarcoding reveals key floral resources for native pollinators in post-fire landscapes"}],"publisher":"Dryad","container":{},"publicationYear":2026,"subjects":[{"schemeUri":"https://web-archive.oecd.org/2012-06-15/138575-38235147.pdf","subject":"FOS: Natural sciences","subjectScheme":"fos"},{"schemeUri":"https://web-archive.oecd.org/2012-06-15/138575-38235147.pdf","subject":"FOS: Agriculture, forestry, and fisheries","subjectScheme":"fos"},{"schemeUri":"https://web-archive.oecd.org/2012-06-15/138575-38235147.pdf","subject":"FOS: Biological sciences","subjectScheme":"fos"},{"subject":"mellitology"},{"subject":"metabarcoding"},{"schemeUri":"https://github.com/PLOS/plos-thesaurus","subject":"Palynology","subjectScheme":"PLOS Subject Area Thesaurus"},{"subject":"plant-pollinator interactions"},{"schemeUri":"https://github.com/PLOS/plos-thesaurus","subject":"Pollination","subjectScheme":"PLOS Subject Area Thesaurus"},{"subject":"wildfire"}],"contributors":[{"name":"Okanogan-Wenatchee National Forest, Washington, United States","contributorType":"Sponsor","affiliation":[],"nameIdentifiers":[]}],"dates":[{"date":"2026-08-13T21:25:12Z","dateType":"Created"},{"date":"2026-08-13T21:25:12Z","dateType":"Submitted"},{"date":"2026-08-18T00:00:00Z","dateType":"Issued"},{"date":"2026-08-18T00:00:00Z","dateType":"Available"}],"language":"en","types":{"schemaOrg":"Dataset","resourceTypeGeneral":"Dataset","citeproc":"dataset","bibtex":"misc","ris":"DATA","resourceType":"dataset"},"relatedIdentifiers":[],"relatedItems":[],"sizes":["184166 bytes"],"formats":[],"version":"3","rightsList":[{"rightsIdentifierScheme":"SPDX","rightsUri":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","schemeUri":"https://spdx.org/licenses/","rights":"Creative Commons Zero v1.0 Universal","rightsIdentifier":"cc0-1.0"}],"descriptions":[{"descriptionType":"Abstract","description":"Wildfires are a natural disturbance in dry ponderosa pine forest\n ecosystems and are increasing in frequency and severity across western\n North America. The effects of wildfire on biotic and abiotic conditions\n have important implications for higher trophic levels, including native\n bees. We sought to quantify the responses of flowering plants to fire age\n and severity and determine the effects of these shifts on pollinator\n richness through time. We sequenced pollen from pan and blue vane traps\n deployed every two weeks from April to August in 2022 and 2023 to quantify\n shifts in foraging resources for pollinator communities in landscapes aged\n 1-8 years post-fire, and in an unburned area. DNA metabarcoding pollen\n suspended in blue vane and pan traps revealed herbaceous perennials such\n as Achillea millefolium, Lupinus spp., and Phacelia hastata to be key\n floral resources for post-fire pollinator communities. Burn age and burn\n severity were the main drivers of plant-pollinator richness, and plant\n species richness increased with burn age and burn severity. Bee species\n richness varied among burn severities, supporting management for patch\n mosaics and landscape heterogeneity as a fundamental principle of fire\n reintroduction. Our findings underscore the importance of bioinformatics\n threshold selection in plant list generation, and highlight the role of\n burn age, burn severity, and plant richness in effectively conserving\n pollinator species across fire-effected landscapes. This study also used\n the novel approach of collecting pollen suspended in trap solutions to\n quantify floral resources for insect pollinators, highlighting the utility\n of trap byproducts to provide insightful ecological information.\n Understanding specific plant-pollinator relationships is critical for\n successful conservation of dry forest angiosperm flora and bee faunas."},{"descriptionType":"Methods","description":"Data were collected across three burned landscapes and one\n unburned site in the Okanogan-Wenatchee National Forest, Washington,\n United States, over two years (2022-2023) using blue vane and pan traps.\n Insects were identified using regionally specific taxonomic keys. Pollen\n collected by each insect was either sequenced from the specimen (BP: bee\n pollen) or from the trap (TP: trap pollen). We sought to quantify the\n responses of flowering plants to fire age and severity and determine the\n effects of these shifts on pollinator richness through time. Pan and blue\n vane traps were deployed every two weeks from April to August to quantify\n shifts in foraging resources for pollinator communities in landscapes aged\n 1-8 years post-fire, and in an unburned area."},{"descriptionType":"TechnicalInfo","description":"# Data from: DNA metabarcoding reveals key floral resources for native\n pollinators in post-fire landscapes Dataset DOI:\n [10.5061/dryad.g4f4qrg60](https://doi.org/10.5061/dryad.g4f4qrg60) ##\n Description of the data and file structure Raw data are contained in\n Maustetal.2026_EA.xlsx with 5 tabs. ### Files and variables ## File:\n Maustetal.2026_EA.xlxs **Tab: Pollen_Data** ##### ***Variables*** *\n SampleID=Name of the pollen sample. Each pollen sample was given a unique\n name BP (Bee Pollen) - XXXX or TP (Trap Pollen) - XXXX. * Family = Plant\n family * Genus = Plant genus * Species = Plant species * Reads = Number of\n reads for each respective sample. Pollen metabarcoding is not\n quantitative. **Tab: Pollen_Explanatory_Variables** ##### ***Variables***\n * SampleID=Name of the pollen sample. Each pollen sample was given a\n unique name BP (Bee Pollen) - XXXX or TP (Trap Pollen) - XXXX. * Year=\n Year sampling occurred (2022-2023). * Month=Month that sampling occurred\n (Apr-Aug). * Collection Date=Date the insect or trap was collected as\n DD-MMM * Year Since Burn = Burn age; year since the plot was burned. *\n Site = Name of the burn scar * Plot = Plot number 1-4. Two plots were\n established in each site. The two remaining plots correspond to another\n study objective * Type= Trap type: pan (P) or blue vane (V) * CBI.mean=The\n mean of CBI values were calculated within a 350-m radius of plot center,\n defined as the central point between four T-posts. The unburned control\n has no relevant burn severity value and was thus marked \"NA\".\n Burn severity data processing was performed in ArcGIS Pro 3.3.1. *\n CBI.cat=CBI category **Tab: Pollination_Type_Insect** #####\n ***Variables*** * GenusSpecies= Plant genus and species *\n Common.Name=Plant common name. list of plants that are insect pollinated\n from the dataset * Origin=Native, agricultural, introduced *\n No.Samples=Number of samples the plant species occurs in *\n Percent.Samples=Percent of total samples the plant species occurs in *\n Flowering=Flowering seasonality (month range) **Tab:\n Floral_Transect_Data** ##### ***Variables*** * Date=Date the sample was\n conducted as DD-MMM * Year= Year sampling occurred (2022-2023). * Year\n Since Burn = Burn age; year since the plot was burned. * Plot = Plot\n number 1-4. Two plots were established in each site. The two remaining\n plots correspond to another study objective * Site = Name of the burn scar\n * Identifier=Two floral plots were established at each research plot, with\n either pink or orange flagging * Transect= Transect number, two transects\n were randomly selected and measured at each floral plot (4 per research\n plot) * Latin name=Plant name. When there were no flowering plants in the\n transect Latin name was indicated as \"NA\".  * area sum cm^2^=\n Area of floral resource availability summarized for each species per\n transect as cm^2^. When there were no flowering present, area sum cm^2^ is\n 0.  *Site appreviations:* * CL = Unburned (\"Control\") * CX =\n Chelan Complex Fire * CR = Cougar Creek Fire * MI = Twentyfive Mile Creek\n Fire **Tab: Bee_Plot_Richness** * Identifier=Unique combination of burn\n age + site name + and plot number * BeeGenRichPlotRaw= raw bee genus\n richness at this identifier * BeeGenRichPlotRare=rarefied bee genus\n richness to control for sampling imbalances * BeeSppRichPlot= bee species\n richness ## Access information **References:** Bates, D., Maechler, M.,\n Bolker, B., Walker, S. (2015) Fitting Linear Mixed-Effects Models Using\n lme4. Journal of Statistical Software, 67(1), 1-48.\n [https://cran.r-project.org/web/packages/lme4/index.html](https://cran.r-project.org/web/packages/lme4/index.html) De Cáceres et al. (2024) [https://cran.r-project.org/web/packages/indicspecies/index.html](https://cran.r-project.org/web/packages/indicspecies/index.html) Hartig F (2024) \\_DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models_. R package version 0.4.7.[https://CRAN.R-project.org/package=DHARMa](https://cran.r-project.org/package=DHARMa) Kuznetsova, A., Brockhoff, P.B., Christensen, R.H.B. (2017) *lmerTest Package: Tests in Linear Mixed Effects Models*. Journal of Statistical Software, *82*(13), 1-26. [https://doi.org/10.18637/jss.v082.i13](https://doi.org/10.18637/jss.v082.i13) R Core Team (2025) R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. [https://www.R-project.org/](https://www.r-project.org/). Wickham, H. (2024) ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York, 2016."}],"geoLocations":[],"fundingReferences":[{"funderIdentifierType":"ROR","funderName":"National Institute of Food and Agriculture","funderIdentifier":"https://ror.org/05qx3fv49","awardTitle":"McIntire-Stennis Cooperative Forestry Capacity Funding Program","awardNumber":"7006470"},{"funderIdentifierType":"ROR","funderName":"University of Washington","funderIdentifier":"https://ror.org/00cvxb145","awardTitle":"David R.M. Scott Endowed Professorship in Forest Resources"},{"funderIdentifierType":"ROR","funderName":"University of Washington","funderIdentifier":"https://ror.org/00cvxb145","awardTitle":"Hall Conservation Genetics Fund "},{"funderIdentifierType":"ROR","funderName":"Garden Club of America","funderIdentifier":"https://ror.org/03s9h8898","awardTitle":"Board of Associates Centennial Pollinator Fellowship"}],"url":"https://datadryad.org/dataset/doi:10.5061/dryad.g4f4qrg60","contentUrl":null,"metadataVersion":0,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"mds","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":0,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2026-08-18T09:49:19Z","registered":"2026-08-18T09:49:20Z","published":null,"updated":"2026-08-18T09:49:20Z"},"relationships":{"client":{"data":{"id":"dryad.dryad","type":"clients"}}}},{"id":"10.5281/zenodo.21225411","type":"dois","attributes":{"doi":"10.5281/zenodo.21225411","identifiers":[{"identifier":"oai:zenodo.org:21225411","identifierType":"oai"}],"creators":[{"nameType":"Personal","affiliation":["Independent Researcher, United States"],"familyName":"Vijayalakshmi Narasimhan","name":"Vijayalakshmi Narasimhan","nameIdentifiers":[]}],"titles":[{"title":"Adaptive Product Governance for AI-Mediated Customer Journeys: A Dynamic Framework for Requirements Fluidity and Governance Complexity in Enterprise AI Systems"}],"publisher":"IJESTY","container":{},"publicationYear":2026,"subjects":[],"contributors":[],"dates":[{"date":"2026-06-17","dateType":"Issued"}],"language":null,"types":{"schemaOrg":"ScholarlyArticle","resourceTypeGeneral":"JournalArticle","citeproc":"article-journal","bibtex":"article","ris":"JOUR","resourceType":""},"relatedIdentifiers":[{"relationType":"IsVersionOf","relatedIdentifier":"10.5281/zenodo.21225410","relatedIdentifierType":"DOI"},{"relationType":"IsPartOf","resourceTypeGeneral":"Collection","relatedIdentifier":"2775-2674","relatedIdentifierType":"ISSN"}],"relatedItems":[],"sizes":[],"formats":[],"version":null,"rightsList":[{"rightsIdentifierScheme":"SPDX","rightsUri":"https://creativecommons.org/licenses/by/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rights":"Creative Commons Attribution 4.0 International","rightsIdentifier":"cc-by-4.0"}],"descriptions":[{"descriptionType":"Abstract","description":"The integration of generative artificial intelligence (AI), adaptive recommendation systems, and large language model (LLM)-powered conversational interfaces into enterprise digital products has fundamentally transformed how customers interact with products and services. Historically, customer journeys were modeled as stable, linear sequences of touchpoints that product teams could define, validate, and govern using conventional Product Development Lifecycle (PDLC) frameworks. However, AI-mediated customer journeys are inherently dynamic rather than static, continuously evolving through model retraining, adaptive personalization, user feedback, and shifting data distributions. This behavioral dynamism introduces persistent customer journey volatility that challenges conventional governance approaches and reduces the effectiveness of traditional product management practices. This paper formalizes the AI-Induced Instability Model, a four-stage conceptual framework describing how AI behavioral adaptation propagates into customer journey volatility, requirement instability, governance complexity, and execution friction throughout enterprise product development. Building upon this diagnostic model, the study proposes the Adaptive Governance Framework (AGF), a six-dimensional governance architecture that redefines product governance through velocity-matched requirement revalidation, hypothesis-driven product specifications, progressive capability streaming, continuous risk assessment, AI lifecycle governance, and dynamic portfolio management. The framework is designed to support organizations in maintaining alignment between rapidly evolving AI capabilities and business objectives while preserving governance, compliance, and delivery quality. The AGF was empirically evaluated through a 14-week enterprise e-commerce product governance program involving 14 concurrent AI-enabled product initiatives. The evaluation demonstrated a 43% reduction in requirement revalidation cycle time, a 37% decrease in backlog volatility, a 29% improvement in delivery alignment, and governance documentation completeness reaching 91%, compared with 54.2% under a traditional PDLC baseline. These findings demonstrate that adaptive governance significantly improves organizational responsiveness, decision quality, and execution consistency in AI-driven product environments. The proposed framework provides enterprise product managers, technology leaders, and governance practitioners with a practical, scalable, and quantitatively validated architecture for managing AI-mediated digital products operating in continuously evolving customer ecosystems while ensuring sustainable innovation, regulatory compliance, and long-term business value."}],"geoLocations":[],"fundingReferences":[],"url":"https://zenodo.org/doi/10.5281/zenodo.21225411","contentUrl":null,"metadataVersion":0,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"api","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":0,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":1,"created":"2026-07-06T18:04:45Z","registered":"2026-07-06T18:04:46Z","published":null,"updated":"2026-08-18T09:49:18Z"},"relationships":{"client":{"data":{"id":"cern.zenodo","type":"clients"}}}},{"id":"10.5281/zenodo.21992490","type":"dois","attributes":{"doi":"10.5281/zenodo.21992490","identifiers":[{"identifier":"oai:zenodo.org:21992490","identifierType":"oai"},{"identifier":"2074-2134","identifierType":"ISSN"}],"creators":[{"nameType":"Personal","givenName":"Anupam Hasan","familyName":"Md. Hasan Farid","name":"Md. Hasan Farid, Anupam Hasan","nameIdentifiers":[],"affiliation":[]},{"nameType":"Personal","givenName":"Anupam Hasan","familyName":"Md. Hasan Farid","name":"Md. Hasan Farid, Anupam Hasan","nameIdentifiers":[],"affiliation":[]}],"titles":[{"title":"লালসালু চলচ্চিত্র : জমিলার দ্রোহ ও প্রতিবাদ"},{"titleType":"TranslatedTitle","lang":"eng","title":"The Film Lalsalu: Jamila's Rebellion and Protest"}],"publisher":"Zenodo","container":{},"publicationYear":2016,"subjects":[],"contributors":[{"nameType":"Personal","givenName":"Anupam Hasan","familyName":"Md. Hasan Farid","name":"Md. Hasan Farid, Anupam Hasan","nameIdentifiers":[],"contributorType":"Researcher","affiliation":[]}],"dates":[{"date":"2016-06-30","dateType":"Issued"},{"date":"2016-06-30","dateType":"Issued","dateInformation":"Pdf"}],"language":"bn","types":{"schemaOrg":"ScholarlyArticle","resourceTypeGeneral":"JournalArticle","citeproc":"article-journal","bibtex":"article","ris":"JOUR","resourceType":""},"relatedIdentifiers":[{"relationType":"Documents","resourceTypeGeneral":"JournalArticle","relatedIdentifier":"2074-2134","relatedIdentifierType":"ISSN"},{"relationType":"IsVersionOf","relatedIdentifier":"10.5281/zenodo.21992489","relatedIdentifierType":"DOI"},{"relationType":"IsPartOf","resourceTypeGeneral":"Collection","relatedIdentifier":"2074-2134","relatedIdentifierType":"ISSN"}],"relatedItems":[],"sizes":[],"formats":[],"version":"Print","rightsList":[{"rightsIdentifierScheme":"SPDX","rightsUri":"https://creativecommons.org/licenses/by/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rights":"Creative Commons Attribution 4.0 International","rightsIdentifier":"cc-by-4.0"}],"descriptions":[{"descriptionType":"Abstract","description":"Abstruct : Jamila stands as one of the most compelling female characters in Syed Waliullah’s novel Lalsalu (Tree Without Roots). Film director Tanvir Mokammel, in his cinematic adaptation, further cements her portrayal as a symbol of fearless defiance against the religious fanaticism and hypocrisy embodied by the character Majid. Throughout the narrative, Majid is depicted as exploiting religious dogma to exercise control over rural society. While Rahima serves as a submissive figure who blindly accepts Majid’s deceit, Jamila remains starkly oppositional, refusing to acknowledge or succumb to the climate of fear and tyranny he imposes.\n\nJamila’s rebellious spirit becomes a source of profound unease for Majid. By dismissing the superficiality of his shrine-centered religious practices, she stands as the only figure capable of challenging his hegemony. Her actions toward the end of the novel—such as tearing the shrine’s gilaf (cover) and demonstrating blatant disregard for Majid’s rituals—serve as a poignant manifestation of the subaltern’s resistance against the oppressor. Jamila is not a theoretical insurgent; rather, it is through her innate strength of character that she destabilizes the foundations of Majid’s manufactured religious authority. Her resistance extends beyond a personal vendetta against Majid, representing a robust ideological stance against a deeply superstitious society. Ultimately, Jamila demonstrates that dismantling the mask of a hypocritical oppressor requires immense courage, a trait that elevates her character to a unique position of prominence in both the literary and cinematic realms. Even though Majid may attempt to subjugate her, the existential dread he experiences serves as the definitive hallmark of Jamila’s moral victory."}],"geoLocations":[],"fundingReferences":[],"url":"https://zenodo.org/doi/10.5281/zenodo.21992490","contentUrl":null,"metadataVersion":1,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"api","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":0,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":1,"created":"2026-08-18T09:45:41Z","registered":"2026-08-18T09:45:41Z","published":null,"updated":"2026-08-18T09:49:18Z"},"relationships":{"client":{"data":{"id":"cern.zenodo","type":"clients"}}}},{"id":"10.17632/kk5t2pkrs6.1","type":"dois","attributes":{"doi":"10.17632/kk5t2pkrs6.1","identifiers":[],"creators":[{"nameType":"Personal","givenName":"surya","familyName":"kanth","name":"kanth, surya","affiliation":[],"nameIdentifiers":[]}],"titles":[{"title":"RSM DATA"}],"publisher":"Mendeley Data","container":{},"publicationYear":2026,"subjects":[{"subject":"Database"}],"contributors":[],"dates":[{"date":"2026-08-18T09:49:17Z","dateType":"Issued"}],"language":null,"types":{"schemaOrg":"Dataset","resourceTypeGeneral":"Dataset","citeproc":"dataset","bibtex":"misc","ris":"DATA","resourceType":"Dataset"},"relatedIdentifiers":[{"relationType":"IsVersionOf","resourceTypeGeneral":"Dataset","relatedIdentifier":"10.17632/kk5t2pkrs6","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":[],"formats":[],"version":null,"rightsList":[{"rightsUri":"info:eu-repo/semantics/openAccess"},{"rightsIdentifierScheme":"SPDX","rightsUri":"https://creativecommons.org/licenses/by/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rights":"Creative Commons Attribution 4.0 International","rightsIdentifier":"cc-by-4.0"}],"descriptions":[{"descriptionType":"Abstract","description":"RSM Data Set"}],"geoLocations":[],"fundingReferences":[],"url":"https://data.mendeley.com/datasets/kk5t2pkrs6/1","contentUrl":null,"metadataVersion":0,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"api","isActive":true,"state":"findable","reason":null,"viewCount":0,"downloadCount":0,"referenceCount":0,"citationCount":0,"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":1,"created":"2026-08-18T09:49:18Z","registered":null,"published":null,"updated":"2026-08-18T09:49:18Z"},"relationships":{"client":{"data":{"id":"bl.mendeley","type":"clients"}}}},{"id":"10.5281/zenodo.20114043","type":"dois","attributes":{"doi":"10.5281/zenodo.20114043","identifiers":[],"creators":[{"nameType":"Personal","affiliation":["Democritus University of Thrace"],"givenName":"Georgios","familyName":"Arampatzis","name":"Arampatzis, Georgios","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","nameIdentifier":"0009-0003-6240-4537"}]},{"nameType":"Personal","affiliation":["Democritus University of Thrace"],"givenName":"Avi","familyName":"Arampatzis","name":"Arampatzis, Avi","nameIdentifiers":[{"nameIdentifierScheme":"ORCID","nameIdentifier":"0000-0003-2415-4592"}]}],"titles":[{"title":"Hybrid Sparse-Neural Fusion for Passage Retrieval"}],"publisher":"Zenodo","container":{},"publicationYear":2025,"subjects":[],"contributors":[],"dates":[{"date":"2025","dateType":"Issued"}],"language":null,"types":{"schemaOrg":"Article","resourceTypeGeneral":"ConferencePaper","citeproc":"","bibtex":"article","ris":"CPAPER","resourceType":""},"relatedIdentifiers":[{"relationType":"HasVersion","relatedIdentifier":"10.5281/zenodo.20114044","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":[],"formats":[],"version":null,"rightsList":[],"descriptions":[{"descriptionType":"Abstract","description":"This paper presents the DUTH team’s participation in the TREC 2025 RAGTIME Multilingual Information Retrieval task. 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