cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.18443427
title: LINF_320020200

description: Protein of unknown function - conserved; Leishmania infantum (strain JPCM5)
DOI: 10.5281/zenodo.18443251
title: "Short-term effects of aquatic activities on sleep behaviors in children and adolescents"

description: Sleep and physical activity play an important role in the proper development of children. Water exercises support health, motor development, and physical fitness, as well as having a relaxing effect, reducing stress, and positively influencing the quality of sleep in children. The aim of the study was to check whether days on which water exercises were performed had a more beneficial effect on children's sleep compared to days without such activities.The study involved 138 children and adolescents aged 6 months to 18 years who participated in water activities appropriate for their age. Sleep was assessed using three methods: a sleep diary, the abridged Children's Sleep Habit Questionnaire (CSHQ-A), and the Sleep Self-Rating (SSR). The analysis compared the quality of sleep on the night after water activity with the night without such activity.
DOI: 10.5281/zenodo.18443250
title: "Short-term effects of aquatic activities on sleep behaviors in children and adolescents"

description: Sleep and physical activity play an important role in the proper development of children. Water exercises support health, motor development, and physical fitness, as well as having a relaxing effect, reducing stress, and positively influencing the quality of sleep in children. The aim of the study was to check whether days on which water exercises were performed had a more beneficial effect on children's sleep compared to days without such activities.The study involved 138 children and adolescents aged 6 months to 18 years who participated in water activities appropriate for their age. Sleep was assessed using three methods: a sleep diary, the abridged Children's Sleep Habit Questionnaire (CSHQ-A), and the Sleep Self-Rating (SSR). The analysis compared the quality of sleep on the night after water activity with the night without such activity.
DOI: 10.5281/zenodo.18443413
title: Path Independence and the Absence of Trajectories in Continuous Repulsive Volumetric Dynamics

description: The dynamics are governed entirely by instantaneous volumetric energy gradients, leading directly to a principle we term the Path Independence Principle (PPII), which dictates that physical outcomes depend solely on the current volumetric state, not on the history of intermediate states. This structure necessitates the emergence of phenomena conventionally ascribed to gravity as local manifestations of volumetric energy density fluxes. Consequently, trajectories are reinterpreted not as fundamental ontological entities, but as non-physical artifacts arising from specific, observer-dependent gauge choices in the description of the underlying continuous field evolution.
DOI: 10.5281/zenodo.18443412
title: Path Independence and the Absence of Trajectories in Continuous Repulsive Volumetric Dynamics

description: The dynamics are governed entirely by instantaneous volumetric energy gradients, leading directly to a principle we term the Path Independence Principle (PPII), which dictates that physical outcomes depend solely on the current volumetric state, not on the history of intermediate states. This structure necessitates the emergence of phenomena conventionally ascribed to gravity as local manifestations of volumetric energy density fluxes. Consequently, trajectories are reinterpreted not as fundamental ontological entities, but as non-physical artifacts arising from specific, observer-dependent gauge choices in the description of the underlying continuous field evolution.
DOI: 10.5281/zenodo.18443446
title: COMPARATIVEANALYSISOFTHELEXICALANDSEMANTICPROPERTIESOFUZBEKANDENGLISHANTHROPONYMS

description: This paper presents a detailed comparative analysis of Uzbek and English anthroponyms, focusing on their lexical and semantic properties. The study explores how linguistic, cultural, and historical factors shape personal naming traditions in both languages. By examining etymology, structure, motivation, and meaning, the article reveals how anthroponyms function as markers of identity, social values, and collective memory.
DOI: 10.5281/zenodo.18443445
title: COMPARATIVEANALYSISOFTHELEXICALANDSEMANTICPROPERTIESOFUZBEKANDENGLISHANTHROPONYMS

description: This paper presents a detailed comparative analysis of Uzbek and English anthroponyms, focusing on their lexical and semantic properties. The study explores how linguistic, cultural, and historical factors shape personal naming traditions in both languages. By examining etymology, structure, motivation, and meaning, the article reveals how anthroponyms function as markers of identity, social values, and collective memory.
DOI: 10.5281/zenodo.18443448
title: Lethal restaurant: the trophic ecology of a bird of prey in highway-fragmented landscapes
DOI: 10.5281/zenodo.18443447
title: Lethal restaurant: the trophic ecology of a bird of prey in highway-fragmented landscapes
DOI: 10.5281/zenodo.18443466
title: LINF_320020700

description: Protein of unknown function - conserved; Leishmania infantum (strain JPCM5)
DOI: 10.5281/zenodo.18443467
title: LINF_320020700

description: Protein of unknown function - conserved; Leishmania infantum (strain JPCM5)
DOI: 10.5281/zenodo.18442848
title: SuperDARN data in netCDF format (2009-Mar)

description: 2009-Mar SuperDARN radar data in netCDF format. These files were produced using version 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.


The RST is available here: https://github.com/SuperDARN/rst



The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation.
Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications.
A brief statement on how to acknowledge use of SuperDARN data is provided below.




Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication.
A listing of radars and PIs with contact information can be found here:
(SuperDARN Radar Overview)



Recommended form of acknowledgement for the use of SuperDARN data:



'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.6578914
title: SuperDARN data in netCDF format (2009-Mar)

description: 2009-Mar SuperDARN radar data in netCDF format. These files were produced using version 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.


The RST is available here: https://github.com/SuperDARN/rst



The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation.
Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications.
A brief statement on how to acknowledge use of SuperDARN data is provided below.




Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication.
A listing of radars and PIs with contact information can be found here:
(SuperDARN Radar Overview)



Recommended form of acknowledgement for the use of SuperDARN data:



'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.18443480
title: METHODSOFPSYCHOTHERAPYOFFEARANDPANICATTACKS

description: This article analyzes the psychological essence of fear and panic attacks, their causes, and methods of treatment using modern psychotherapeutic approaches. Panic attacks negatively affect a person's daily life, reduce social adaptation, and undermine the mental stability of the individual. The article covers the main psychotherapeutic methods, such as cognitive-behavioral therapy, psychoanalytic approach, gestalt therapy, relaxation and mindfulness techniques. The theoretical foundations and practical effectiveness of each method are briefly explained. The article also considers stress, traumatic experiences, negative thinking stereotypes and incorrect emotional reactions as factors that increase the risk of panic attacks. It is emphasized that in the process of psychotherapy, the patient's awareness of his own condition, the formation of emotional control and the development of adaptive thinking are of great importance. The article contains scientific and practical recommendations aimed at strengthening mental health, reducing panic attacks, and improving the quality of life and psychological well-being of a person.
DOI: 10.5281/zenodo.18443481
title: METHODSOFPSYCHOTHERAPYOFFEARANDPANICATTACKS

description: This article analyzes the psychological essence of fear and panic attacks, their causes, and methods of treatment using modern psychotherapeutic approaches. Panic attacks negatively affect a person's daily life, reduce social adaptation, and undermine the mental stability of the individual. The article covers the main psychotherapeutic methods, such as cognitive-behavioral therapy, psychoanalytic approach, gestalt therapy, relaxation and mindfulness techniques. The theoretical foundations and practical effectiveness of each method are briefly explained. The article also considers stress, traumatic experiences, negative thinking stereotypes and incorrect emotional reactions as factors that increase the risk of panic attacks. It is emphasized that in the process of psychotherapy, the patient's awareness of his own condition, the formation of emotional control and the development of adaptive thinking are of great importance. The article contains scientific and practical recommendations aimed at strengthening mental health, reducing panic attacks, and improving the quality of life and psychological well-being of a person.
DOI: 10.15468/dl.ncajsp
title: Occurrence Download

description: A dataset containing 66334 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Country is one of (United States of America, Canada, Norway, Russian Federation, Australia)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Megaptera novaeangliae",
 "Year 2024-2025"
 ]
}

 The dataset includes 66334 records from 22 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003555-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18443531
title: Millennials vs Gen Z Sustainable Consumption: How Environmental Knowledge, Environmental Care Attitude, Emotional Value, and Green Marketing affect Green Purchase Intention
DOI: 10.5281/zenodo.18443532
title: Millennials vs Gen Z Sustainable Consumption: How Environmental Knowledge, Environmental Care Attitude, Emotional Value, and Green Marketing affect Green Purchase Intention
DOI: 10.15468/dl.a67ytz
title: Occurrence Download

description: A dataset containing 5 records in GBIF matching the query:
SELECT
 kingdom,
 kingdomkey,
 phylum,
 phylumkey,
 class,
 classkey,
 "order",
 orderkey,
 family,
 familykey,
 genus,
 genuskey,
 species,
 specieskey,
 "year",
 IF(ISNULL(kingdomkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY kingdomkey, "year")) kingdomcount,
 IF(ISNULL(phylumkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY phylumkey, "year")) phylumcount,
 IF(ISNULL(classkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY classkey, "year")) classcount,
 IF(ISNULL(orderkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY orderkey, "year")) ordercount,
 IF(ISNULL(familykey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY familykey, "year")) familycount,
 IF(ISNULL(genuskey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY genuskey, "year")) genuscount,
 COUNT(*) occurrences,
 MIN(GBIF_TEMPORALUNCERTAINTY(eventdate, eventtime)) mintemporaluncertainty,
 MIN(COALESCE(coordinateuncertaintyinmeters, 1000)) mincoordinateuncertaintyinmeters
FROM
 occurrence
WHERE
 occurrence.countrycode IN ('CN', 'HK')
 AND GBIF_STRINGARRAYCONTAINS(occurrence.classifications['d7dddbf4-2cf0-4f39-9b2a-bb099caae36c'], '3089150', TRUE)
 AND occurrence.hasgeospatialissues = FALSE
 AND NOT GBIF_STRINGARRAYCONTAINS(occurrence.issue, 'TAXON_MATCH_FUZZY', TRUE)
 AND (occurrence.distancefromcentroidinmeters &gt;= 2000.0 OR occurrence.distancefromcentroidinmeters IS NULL)
 AND NOT occurrence.basisofrecord IN ('FOSSIL_SPECIMEN', 'LIVING_SPECIMEN')
 AND occurrence.occurrencestatus = 'PRESENT'
 AND (occurrence.classificationdetails['d7dddbf4-2cf0-4f39-9b2a-bb099caae36c']['specieskey'] &lt;&gt; '' AND occurrence."year" IS NOT NULL)
GROUP BY
 occurrence.kingdom,
 occurrence.kingdomkey,
 occurrence.phylum,
 occurrence.phylumkey,
 occurrence.class,
 occurrence.classkey,
 occurrence."order",
 occurrence.orderkey,
 occurrence.family,
 occurrence.familykey,
 occurrence.genus,
 occurrence.genuskey,
 occurrence.species,
 occurrence.specieskey,
 occurrence."year"

 The dataset's 5 records were derived from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003551-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18443522
title: INNOVATIVEEDUCATIONALDEVELOPMENTINPERIODOFTHEDIGITALIZATIONOFTHEEDUCATIONALPROCESS

description: This article describes the current structure of the education system in the Republic of Uzbekistan, which has been reformed over the past decade in accordance with the National Program for Personnel Training adopted in the country, the educational programs at various levels implemented in Uzbekistan, the qualifications awarded upon completion, and the educational documents confirming these qualifications.
DOI: 10.5281/zenodo.18443523
title: INNOVATIVEEDUCATIONALDEVELOPMENTINPERIODOFTHEDIGITALIZATIONOFTHEEDUCATIONALPROCESS

description: This article describes the current structure of the education system in the Republic of Uzbekistan, which has been reformed over the past decade in accordance with the National Program for Personnel Training adopted in the country, the educational programs at various levels implemented in Uzbekistan, the qualifications awarded upon completion, and the educational documents confirming these qualifications.
DOI: 10.6084/m9.figshare.30407806
title: <b>StitchingNet</b>, A dataset of 14.5K sewing stitch images for the industrial sewing process

description: <b>Motivation</b>In quality control, a sewing defect refers to inconsistencies in stitches when fabrics are joined together. To develop a method for detecting defects, having image datasets of sewing process data showing both normal and defective stitches is crucial. Even though digital transformation has been rapidly spreading in the manufacturing industry, the fashion industry has been slow to adopt it. The industry heavily relies on labor and is mostly made up of small and medium-sized enterprises (SMEs). Despite significant evolution in design and consumption trends, the garment manufacturing process still relies on outdated sewing machines and low-wage labor. Therefore, the fashion industry lacks well-equipped digital infrastructure like other sectors such as e-commerce and finance. Obtaining diverse and extensive datasets to effectively train recent deep learning models for the sewing process has been challenging due to the lack of monitoring functions on older sewing machines and the repetitive nature of work on the shop floor. Another challenge is that traditional industrial vision sensors for capturing images and detecting defects are costly and require additional computing equipment. This makes it challenging to integrate them with the existing sewing machine, which costs less than $1,000.<b>Dataset description</b>At clothing production sites, various types of sewing defects are a common occurrence. This dataset contains the conditions for defects for each major sewing defect, as determined by experienced sewing workers. The dataset includes data on 11 fabrics, with sewing conditions set for dataset generation by combining threads with similar or opposite fabric colors. This configuration is intended to reflect the color and composition conditions of several fabrics and threads in the dataset, enabling the training of robust deep learning models for sewing defect detection. The potential impact of this dataset on the field of computer vision and textile manufacturing is significant. We captured an average of 221 normal and 103 defective images of 10 cases for each fabric-thread combination.<b>Creation det</b><b>ails</b>Time period: 2022.11 - 2023.03Sewing machine: Brother S-7200C-403Vision sensor: Raspberry Pi Camera V2Image size: 224 x 224 pixelsFabrics used (total 11 types): A. Cotton, B. Linen, C. Denim, D. Velveteen, E. Polyester, F. Satin, G. Chiffon, H. Nylon, I. Jacquard, J. Oxford, and K. Polyester (coated)Threads used: Poly and CoreDefective classes (total 10 types): 1. Skipped stitch, 2. Broken stitch, 3. Pinched fabric, 4. Crooked seam, 5. Thread sagging, 6. Puckering, 7. Stain and damage, 8. Needle mark, 9. Bobbin thread pulling up, 10. Overlapped stitch<b>License</b>The StitchingNet is licensed under CC BY-NC 4.0. This means it is free for research updates and non-commercial use with proper attribution.
DOI: 10.6084/m9.figshare.30407806.v1
title: <b>StitchingNet</b>, A dataset of 14.5K sewing stitch images for the industrial sewing process

description: <b>Motivation</b>In quality control, a sewing defect refers to inconsistencies in stitches when fabrics are joined together. To develop a method for detecting defects, having image datasets of sewing process data showing both normal and defective stitches is crucial. Even though digital transformation has been rapidly spreading in the manufacturing industry, the fashion industry has been slow to adopt it. The industry heavily relies on labor and is mostly made up of small and medium-sized enterprises (SMEs). Despite significant evolution in design and consumption trends, the garment manufacturing process still relies on outdated sewing machines and low-wage labor. Therefore, the fashion industry lacks well-equipped digital infrastructure like other sectors such as e-commerce and finance. Obtaining diverse and extensive datasets to effectively train recent deep learning models for the sewing process has been challenging due to the lack of monitoring functions on older sewing machines and the repetitive nature of work on the shop floor. Another challenge is that traditional industrial vision sensors for capturing images and detecting defects are costly and require additional computing equipment. This makes it challenging to integrate them with the existing sewing machine, which costs less than $1,000.<b>Dataset description</b>At clothing production sites, various types of sewing defects are a common occurrence. This dataset contains the conditions for defects for each major sewing defect, as determined by experienced sewing workers. The dataset includes data on 11 fabrics, with sewing conditions set for dataset generation by combining threads with similar or opposite fabric colors. This configuration is intended to reflect the color and composition conditions of several fabrics and threads in the dataset, enabling the training of robust deep learning models for sewing defect detection. The potential impact of this dataset on the field of computer vision and textile manufacturing is significant. We captured an average of 221 normal and 103 defective images of 10 cases for each fabric-thread combination.<b>Creation det</b><b>ails</b>Time period: 2022.11 - 2023.03Sewing machine: Brother S-7200C-403Vision sensor: Raspberry Pi Camera V2Image size: 224 x 224 pixelsFabrics used (total 11 types): A. Cotton, B. Linen, C. Denim, D. Velveteen, E. Polyester, F. Satin, G. Chiffon, H. Nylon, I. Jacquard, J. Oxford, and K. Polyester (coated)Threads used: Poly and CoreDefective classes (total 10 types): 1. Skipped stitch, 2. Broken stitch, 3. Pinched fabric, 4. Crooked seam, 5. Thread sagging, 6. Puckering, 7. Stain and damage, 8. Needle mark, 9. Bobbin thread pulling up, 10. Overlapped stitch<b>License</b>The StitchingNet is licensed under CC BY-NC 4.0. This means it is free for research updates and non-commercial use with proper attribution.
DOI: 10.6084/m9.figshare.29227784
title: Results RG-EV.xlsx

description: Pediatric high-grade gliomas (pHGGs) account for 20% of childhood brain tumors and are associated with poor survival. Currently, pHGG detection relies on MRI, a costly and time-consuming procedure. Extracellular vesicles (EVs) carry molecular markers indicative of their cellular origin and can be isolated from various biofluids, offering an alternative approach. Recent studies showed that pHGGs contain cells that molecularly and morphologically resemble radial glia (RG), a type of neural progenitor. Given that RGs are normally exclusive to the developing brain, we hypothesized that EVs secreted from RG-like glioma cells serve as a pHGG biomarker. However, there are no established molecular markers to specifically detect RG-derived EVs. To address this, we first identified a combination of surface markers to differentiate EVs derived from RG-like glioma cells from those of non-RG cells. We next validated the expression of these markers in patient-derived cell lines. Analysis of EVs isolated from cell culture media confirmed the presence of these markers, along with other tumor-associated markers including targets of chimeric antigen receptor (CAR) T cell therapy. Taken together, our results showed that RG-derived EVs can be isolated and detected by the combination of markers, laying a groundwork for developing a novel EV-based biomarker for pHGGs.
DOI: 10.6084/m9.figshare.29227784.v1
title: Results RG-EV.xlsx

description: Pediatric high-grade gliomas (pHGGs) account for 20% of childhood brain tumors and are associated with poor survival. Currently, pHGG detection relies on MRI, a costly and time-consuming procedure. Extracellular vesicles (EVs) carry molecular markers indicative of their cellular origin and can be isolated from various biofluids, offering an alternative approach. Recent studies showed that pHGGs contain cells that molecularly and morphologically resemble radial glia (RG), a type of neural progenitor. Given that RGs are normally exclusive to the developing brain, we hypothesized that EVs secreted from RG-like glioma cells serve as a pHGG biomarker. However, there are no established molecular markers to specifically detect RG-derived EVs. To address this, we first identified a combination of surface markers to differentiate EVs derived from RG-like glioma cells from those of non-RG cells. We next validated the expression of these markers in patient-derived cell lines. Analysis of EVs isolated from cell culture media confirmed the presence of these markers, along with other tumor-associated markers including targets of chimeric antigen receptor (CAR) T cell therapy. Taken together, our results showed that RG-derived EVs can be isolated and detected by the combination of markers, laying a groundwork for developing a novel EV-based biomarker for pHGGs.