cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/mtrb8d8sms.1
title: Collected Transcripts from interviews with residents of demolished areas (2024/25) in Kowloon City, Hong Kong

description: This dataset is a collection of interview transcripts from a 2024/2025 ethnographic interview project conducted in Kowloon City, Hong Kong. The area of Kowloon City concerned was the project area designated under the Hong Kong Urban Renewal Authority (URA) redevelopment scheme titled the, "Nga Tsin Wai Road / Carpenter Road Development Scheme (KC-017)." The area consisted of former factory buildings and Hong Kongese multi-use shop house buildings (Tong Lau) which were demolished beginning late 2024 through 2025. Investigators from The Hong Kong Polytechnic University School of Design and Department of Applied Social Sciences collaborated with the St. James Settlement social services organization to interview residents of the KC-017 project area before the residents were relocated and the buildings in the area were demolished.

Interviews transcripts from six project cases are available in this collection. These are the anonymized versions of the transcripts which have identifying information removed to protect the subjects of the research. Interview transcript files are named with a randomized case number (E.g., "KC201839") and the date or dates of the intervew(s) in the filename. Interviews lasted for 30 minutes to 60+ minutes each and concerned personal histories, housing conditions and practices, interactions with the URA, and other incidental topics. Transcripts were transcribed from interview audio in Cantonese into Traditional Chinese and thereafter translated into English. Two versions of each transcript are provided in this collection per case: one version includes both the Chinese transcript and the English translation; the other includes only the English translation for compatibility with analysis programs. 

The case numbers for interview transcripts correspond to the case numbers for 3D scan geometry published in this dataset: https://data.mendeley.com/drafts/gfmwkxpdns
The physical conditions recorded in the dataset above were the housing conditions where the interviewees lived at the time of the interviews published in these transcripts.
DOI: 10.5291/ill-data.crg-3298
title: Finite Size Effects in Amorphous Magnetic Reference Layers
DOI: 10.5291/ill-data.crg-3305
title: Structural correlations across the superconducting transition under high pressure in La2PrNi207 layered nickelate
DOI: 10.17632/thfx7cnt6w
title: FAKE NEWS IN THE DIGITAL ENVIRONMENT AND ITS NEGATIVE EFFECTS ON SOCIETY

description: In today's digital age, fake news is one of the most serious challenges to social security, politics and social relations. The rapid development of technology and technology has greatly benefited human life by expanding its range without time and space limitations, but at the same time, many negative effects and risks are increasing hour by minute and day by day. Fake news the process of intentionally or unintentionally spreading incorrect or false information online. Its main purpose is to change and confuse people's perception and opinion. Fake news is often activated during changes in international relations, geopolitical competition, internal and external social, political, and economic confrontations, public unrest, and any online. It is also the activity of broadcasting and distributing online news (content) that is purposefully misleading, with the aim of gaining financial and political benefits and advantages in traditional media, media and social networks.
DOI: 10.17632/thfx7cnt6w.4
title: FAKE NEWS IN THE DIGITAL ENVIRONMENT AND ITS NEGATIVE EFFECTS ON SOCIETY

description: In today's digital age, fake news is one of the most serious challenges to social security, politics and social relations. The rapid development of technology and technology has greatly benefited human life by expanding its range without time and space limitations, but at the same time, many negative effects and risks are increasing hour by minute and day by day. Fake news the process of intentionally or unintentionally spreading incorrect or false information online. Its main purpose is to change and confuse people's perception and opinion. Fake news is often activated during changes in international relations, geopolitical competition, internal and external social, political, and economic confrontations, public unrest, and any online. It is also the activity of broadcasting and distributing online news (content) that is purposefully misleading, with the aim of gaining financial and political benefits and advantages in traditional media, media and social networks.
DOI: 10.5291/ill-data.crg-3307
title: Electric-Field induced phase transitions in perovskite-based lead-free smart systems at low temperatures
DOI: 10.5291/ill-data.crg-3311
title: Magnetically-driven Arrhenius relaxation of the low temperature transition in Magnetite
DOI: 10.17632/skw8tjc82f.1
title: Multimodal_Cactaceae_Dataset_25

description: This data article presents a multimodal, non-invasive dataset documenting the physiology, growth, and phenological stages of Stenocereus queretaroensis (commonly known as pitayo), a columnar cactus of high agronomic, nutritional, and cultural importance in the arid and semi-arid regions of southern Zacatecas, Mexico. Although this species has traditionally been harvested from wild populations, initiatives for its controlled cultivation are emerging as part of regional efforts to improve fruit quality, extend shelf life, and ensure consistent production. However, controlled cultivation remains relatively rare and understudied, and there is a lack of systematic, publicly available data describing its developmental cycle and physiological responses under managed conditions.

To address this gap, we designed and executed a comprehensive data collection campaign between January and May 2025, spanning multiple phenological stages from vegetative growth through flowering and fruiting. A total of 109 healthy, fruit-bearing plants were selected according to inclusion criteria that prioritized structural integrity, absence of disease symptoms, and accessibility for imaging and in-field measurements. Data acquisition combined high-resolution multispectral drone imaging with ground-based spectrophotometry in the 400–700 nm range, enabling the capture of both canopy-level spatial information and precise point-based reflectance signatures.

Imaging was performed using a DJI Mavic 3M equipped with RGB and multispectral sensors. For each plant, one nadir RGB photograph and a corresponding set of multispectral captures were obtained. These data were processed to generate three complementary products: (i) original RGB images and baseline NDVI maps provided by the manufacturer’s software, (ii) spatially adjusted RGB frames cropped, scaled, and registered to NDVI outputs to ensure pixel-level alignment and allow region-of-interest (ROI) analysis, and (iii) recalculated NDVI images derived directly from NIR and Red bands to produce independent vegetation index maps. Spectral measurements were acquired with a YS45 field spectrophotometer using a standardized white reference for reflectance calibration. All spectral data were exported in .csv/.txt format and subsequently processed in MATLAB, where reflectance curves were stored as .mat files and plotted as PNG graphs for visual inspection.

Metadata for each sample include phenological stage, acquisition date and time, geographic coordinates, temperature, illumination conditions, and sensor configuration parameters. Together, these components form a hierarchically organized dataset that facilitates temporal tracking of individual plants and robust integration of image-derived features with field-collected spectra. Preprocessing steps included reflectance normalization, geometric registration of images, and standardization of file naming conventions, resulting in structured dataset ready for computational analysis.
DOI: 10.17632/cydnk2f2md
title: Tecnologies for National Security: IA contributions

description: This dataset corresponds to a scoping review on emerging technologies—such as artificial intelligence, advanced cybersecurity, remote sensing, and drones—employed to transform national security through improved threat detection and more efficient decision-making. It presents an international overview, comparing advancements and gaps among countries in areas such as robotics, communication infrastructures, surveillance, and space assets
DOI: 10.17632/cydnk2f2md.1
title: Tecnologies for National Security: IA contributions

description: This dataset corresponds to a scoping review on emerging technologies—such as artificial intelligence, advanced cybersecurity, remote sensing, and drones—employed to transform national security through improved threat detection and more efficient decision-making. It presents an international overview, comparing advancements and gaps among countries in areas such as robotics, communication infrastructures, surveillance, and space assets
DOI: 10.17632/fkn53ykdpx
title: Raw Dataset: antioxidant defense and Glycoliytic pathway enzymes assays in Sabellaria spinulosa (Leuckart, 1849)

description: Raw data related to antioxidant defense and Glycoliytic pathway enzymes assays conducted on wild specimens of Sabellaria spinulosa (Leuckart, 1849) sampled in the northern Adriatic Sea (Mediterranean Sea).

Table captions:
Table S1. List of the Enzymes and respective quantified values respectively for the two body sizes and sampling events.
Table S2. List of the single measurements of longitudinal bodysize for the two sampling events.
DOI: 10.5291/ill-data.crg-3317
title: Probing the chiral nematic structural organisation of cellulose nanocomposites with very small angle neutron scattering
DOI: 10.17632/fkn53ykdpx.1
title: Raw Dataset: antioxidant defense and Glycoliytic pathway enzymes assays in Sabellaria spinulosa (Leuckart, 1849)

description: Raw data related to antioxidant defense and Glycoliytic pathway enzymes assays conducted on wild specimens of Sabellaria spinulosa (Leuckart, 1849) sampled in the northern Adriatic Sea (Mediterranean Sea).

Table captions:
Table S1. List of the Enzymes and respective quantified values respectively for the two body sizes and sampling events.
Table S2. List of the single measurements of longitudinal bodysize for the two sampling events.
DOI: 10.5291/ill-data.crg-3319
title: Magnetic structure of CrOCl
DOI: 10.5291/ill-data.crg-3212
title: Search for hidden magnetic textures within the pseudogap state of Bi2(Sr,La)2CuO6+x
DOI: 10.5291/ill-data.crg-3278
title: Hunt for the supersolid phase in the Shastry-Sutherland lattice compound ErB4
DOI: 10.15468/dl.dykahs
title: Occurrence Download

description: A dataset containing 198847 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Observation, Machine Observation, Material sample, Human Observation, Material citation, Specimen, Living Specimen, Occurrence evidence)",
 "Country is Pakistan",
 "GadmGid is PAK.7_1"
 ]
}

 The dataset includes 198847 records from 246 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019153-250914085247600/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/hzg43f63k9
title: Combination of label-free SERS-based nanosensor and machine learning for diagnosis of cholangiocarcinoma

description: Early detection of cholangiocarcinoma (CCA) is vital for informing therapeutic strategies and predicting survival outcomes in patients. This study aims to demonstrate an accurate, label-free method for diagnosing CCA by analyzing a single drop of serum using surface-enhanced Raman spectroscopy (SERS) with silver nanorod substrate and applying machine learning (ML) to the data. Serum samples (n = 194) included those from CCA cases (n = 58), hepatocellular carcinoma (HCC, n = 48), liver metastases (LM, n = 44), and healthy individuals (HA, n = 44). A 2-µL drop of diluted serum (1:320) with with deionized water) was applied on a label-free silver nanorod SERS chip, and 49 points were randomly examined for each sample. The gathered Raman spectra were analyzed using principal component analysis to reduce their dimensionality, and then partial least-squares discriminant analysis was employed to identify diagnostic clusters. Among different ML models tested, Tthe integration of SERS and machine learningwith linear discriminant analysis (LDA) yielded a diagnostic accuracy of 81% for differentiation among cancers (CCA, HCC, LM) and HA as evaluated by train-test split method. Additionally, the area under the receiver operating characteristic curve achieved 0.95 for separating CCA, HCC, LM, and HA groups. Overall, the results indicate that the use of SERS-based diagnostic techniques in conjunction with machine learning has great potential for accurately distinguishing CCA from other liver cancers, such as HCC and LM. These surface-enhanced Raman spectra are ideally suited for developing cost-effective, clinically relevant, point-of-care diagnostic methods for community-based CCA screening.
DOI: 10.17632/hzg43f63k9.1
title: Combination of label-free SERS-based nanosensor and machine learning for diagnosis of cholangiocarcinoma

description: Early detection of cholangiocarcinoma (CCA) is vital for informing therapeutic strategies and predicting survival outcomes in patients. This study aims to demonstrate an accurate, label-free method for diagnosing CCA by analyzing a single drop of serum using surface-enhanced Raman spectroscopy (SERS) with silver nanorod substrate and applying machine learning (ML) to the data. Serum samples (n = 194) included those from CCA cases (n = 58), hepatocellular carcinoma (HCC, n = 48), liver metastases (LM, n = 44), and healthy individuals (HA, n = 44). A 2-µL drop of diluted serum (1:320) with with deionized water) was applied on a label-free silver nanorod SERS chip, and 49 points were randomly examined for each sample. The gathered Raman spectra were analyzed using principal component analysis to reduce their dimensionality, and then partial least-squares discriminant analysis was employed to identify diagnostic clusters. Among different ML models tested, Tthe integration of SERS and machine learningwith linear discriminant analysis (LDA) yielded a diagnostic accuracy of 81% for differentiation among cancers (CCA, HCC, LM) and HA as evaluated by train-test split method. Additionally, the area under the receiver operating characteristic curve achieved 0.95 for separating CCA, HCC, LM, and HA groups. Overall, the results indicate that the use of SERS-based diagnostic techniques in conjunction with machine learning has great potential for accurately distinguishing CCA from other liver cancers, such as HCC and LM. These surface-enhanced Raman spectra are ideally suited for developing cost-effective, clinically relevant, point-of-care diagnostic methods for community-based CCA screening.
DOI: 10.5291/ill-data.dir-330
title: X-ray and neutron scattering analyses of biopolymer membranes for Li-ion battery: investigate changes in structure with manufacturing and re
DOI: 10.17632/ggx4277ws9.1
title: Investigating hydrotropic agents in Itraconazole solid dispersion for improved solubility, dissolution, and oral bioavailability

description: The file contains supporting data for the research on Investigating hydrotropic agents in Itraconazole solid dispersion for improved solubility, dissolution, and oral bioavailability: defining molecular interaction by Setschenow constant, Falken-Hagen, Jones-Dole coefficient, Free energy of activation, Einstein, Vand, and Moulik equations.
DOI: 10.5291/ill-data.dir-399
title: How does charge correlation govern the viscoelastic properties of concentrated electrolytes?
DOI: 10.17632/ndwxv46pm9
title: Student Swimming Risk Behavior Intervention（1666）

description: A questionnaire survey was conducted in selected Chinese junior high schools, targeting 1,800 adolescents to assess their aquatic safety knowledge, sensation seeking level, aquatic safety skills, and high-risk swimming behaviors. After data collection and processing, 1,666 valid questionnaires were obtained (92.6%). Participants ranged in age from 14 ± 0.81 years, comprising 863 males (51.8%) and 803 females (48.2%). Grade distribution was as follows: 436 students (26.2%) in Grade 7, 621 students (37.3%) in Grade 8, and 609 students (36.6%) in Grade 9.
DOI: 10.17632/ndwxv46pm9.1
title: Student Swimming Risk Behavior Intervention（1666）

description: A questionnaire survey was conducted in selected Chinese junior high schools, targeting 1,800 adolescents to assess their aquatic safety knowledge, sensation seeking level, aquatic safety skills, and high-risk swimming behaviors. After data collection and processing, 1,666 valid questionnaires were obtained (92.6%). Participants ranged in age from 14 ± 0.81 years, comprising 863 males (51.8%) and 803 females (48.2%). Grade distribution was as follows: 436 students (26.2%) in Grade 7, 621 students (37.3%) in Grade 8, and 609 students (36.6%) in Grade 9.
DOI: 10.5291/ill-data.dir-384
title: Hydrogen adsorption on AL-ZN-MG-Cu alloys
DOI: 10.5291/ill-data.dir-386
title: Influence of sustainably derived carbon materials on the precipitation of lithium sulfide in lithium-Sulfur batteries
DOI: 10.5291/ill-data.dir-404
title: Shear Induced Gelation in Colloid-Polymer Suspensions
DOI: 10.17632/zndzygc3p3.1
title: QR4Change: A Smart QR-Based Civic Grievance Reporting System

description: This dataset has been curated to support research in computer vision applications for urban infrastructure and waste management. The data was collected from multiple sources, including open-source repositories, government portals, and an on-field visit in Pune (covering Kondhwa, Bibewadi, Swargate, and Market Yard).

The dataset is divided into two major classes:

Potholes Dataset: A total of 2,966 images, consisting of 1,004 pothole images and 1962 plain road (non-pothole) images.

Garbage Dataset: A total of 1,971 images, consisting of 712 extreme garbage dump images and 1,259 non-garbage images, sourced from open platforms and repositories.
DOI: 10.17632/kc58s75z4t
title: Replication Folder for Information diversity, collusion of informed traders and asset prices

description: Replication Folder for Information diversity, collusion of informed traders and asset prices.
DOI: 10.17632/kc58s75z4t.2
title: Replication Folder for Information diversity, collusion of informed traders and asset prices

description: Replication Folder for Information diversity, collusion of informed traders and asset prices.
DOI: 10.17632/n38xd7bvz4
title: Exploring Effective Pedagogy: A Comparative Analysis of Hands-On Experimental and Traditional Teaching Methods in the Elementary Science Curriculum

description: This study highlights the global issue of declining interest in physics, especially in under-resourced contexts such as Mongolia. While internet access to information has grown, it often replaces essential teacher-student interaction. We compared the effectiveness of hands-on physics experiments (HPE) and traditional instruction among 95 fourth-grade students, randomly assigned to experimental and control groups. Pre- and post-tests were administered, with follow-up recall assessments at 2 and 4 months. The experimental group outperformed the control group by 12.74% and 10.87% at each interval, respectively (p &lt; 0.05). These results demonstrate that HPE significantly improves long-term retention and engagement. The findings support the integration of low-cost experimental approaches in science education, particularly in resource-constrained settings.
DOI: 10.5291/ill-data.dir-406
title: Probing Anisotropic Nature of Chiral Fluctuations Reponsable for the Formation of skyrmion Lattice Phase in CU2OSEO3
DOI: 10.17632/n38xd7bvz4.1
title: Exploring Effective Pedagogy: A Comparative Analysis of Hands-On Experimental and Traditional Teaching Methods in the Elementary Science Curriculum

description: This study highlights the global issue of declining interest in physics, especially in under-resourced contexts such as Mongolia. While internet access to information has grown, it often replaces essential teacher-student interaction. We compared the effectiveness of hands-on physics experiments (HPE) and traditional instruction among 95 fourth-grade students, randomly assigned to experimental and control groups. Pre- and post-tests were administered, with follow-up recall assessments at 2 and 4 months. The experimental group outperformed the control group by 12.74% and 10.87% at each interval, respectively (p &lt; 0.05). These results demonstrate that HPE significantly improves long-term retention and engagement. The findings support the integration of low-cost experimental approaches in science education, particularly in resource-constrained settings.
DOI: 10.17632/zxbgvfjzs9
title: ALP-aca

description: The ALP Automatic Computing Algorithm, ALP-aca, is an open source Python library devoted to studying the phenomenology of Axion-Like Particles (ALPs) with masses in the ranges from 0.01 to 10 GeV. ALP-aca provides a flexible and comprehensive framework to define ALP couplings at arbitrary energy scales, perform Renormalisation Group evolution and matching down to the desired low energy scale,
and compute a large variety of ALP observables, with particular care to the meson decay sector. The package includes support for UV completions, experimental constraints, and visualisation tools, enabling both detailed analyses and broad parameter space exploration.
DOI: 10.17632/zxbgvfjzs9.1
title: ALP-aca

description: The ALP Automatic Computing Algorithm, ALP-aca, is an open source Python library devoted to studying the phenomenology of Axion-Like Particles (ALPs) with masses in the ranges from 0.01 to 10 GeV. ALP-aca provides a flexible and comprehensive framework to define ALP couplings at arbitrary energy scales, perform Renormalisation Group evolution and matching down to the desired low energy scale,
and compute a large variety of ALP observables, with particular care to the meson decay sector. The package includes support for UV completions, experimental constraints, and visualisation tools, enabling both detailed analyses and broad parameter space exploration.
DOI: 10.17632/zwf4tfy8d2
title: Influence of Land Use and Cover Change on the Distribution and Foraging Ecology of Grey Crowned Cranes (Balearica reg-ulorum gibbericeps) in the Rushebeya Wetland Catchment, Southwestern Uganda

description: This dataset supports a study on the effects of land use and land cover (LULC) changes on the distribution, habitat use, and foraging ecology of Grey Crowned Cranes in the Rushebeya Wetland Catchment. It includes observations of crane occurrence, foraging behavior, habitat type, and associated environmental variables
DOI: 10.5291/ill-data.easy-1494
title: Time-resolved simultaneous SANS/SAXS measurement for cyanobacterial circadian clock
DOI: 10.17632/zwf4tfy8d2.1
title: Influence of Land Use and Cover Change on the Distribution and Foraging Ecology of Grey Crowned Cranes (Balearica reg-ulorum gibbericeps) in the Rushebeya Wetland Catchment, Southwestern Uganda

description: This dataset supports a study on the effects of land use and land cover (LULC) changes on the distribution, habitat use, and foraging ecology of Grey Crowned Cranes in the Rushebeya Wetland Catchment. It includes observations of crane occurrence, foraging behavior, habitat type, and associated environmental variables
DOI: 10.5291/ill-data.easy-1498
title: The effect of antimicrobial agents on the lipid bilayer of exogenous pulmonary surfactant