cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.14457/tu.the.2024.482
title: Institutional investors & ESG preferences: evidence from ASEAN markets

description: This paper conducts a study on effect of ESG performance on ESG preference of Institutional Investors between 2014 and 2023. This paper investigates the effect of firms’ ESG performance on institutional investor preference. As sustainable investing becomes increasingly mainstream, institutional investors are a significant group in promoting ESG perfor-mance through their ownership and engagement strategies. From OLS regression data across multiple years and firms, this study examines whether higher ESG scores are positively associated with greater institutional investor presence and their ownership. The findings support to clientele effect and strong systematic stewardship among institutional investors in ASEAN’s emerging market.These results reveal that firms with stronger ESG performance will attract a larger number of institutional investors and exhibit higher average ownership. The result is shown that the governance score has a only components which negative impact on institutional ownership ratio. This contrast may rerflect fundamental differences between EM and DM. These findings highlight the evolving preferences of institutional investors and their potential to influence corporate sustainability efforts in ASEAN market.
DOI: 10.14457/tu.the.2024.483
title: Biosimilar uptake in Thailand: from physician's attitudes through budget impact

description: Background: Biosimilars offer potential to reduce healthcare costs, but their adoption faces several barriers. In Thailand, although biosimilars are available, key physician-related factors - such as familiarity, attitudes, and decision-making influences - remain unclear. These behavioral aspects can affect uptake and have significant implications for national healthcare budgets. This study aimed to propose policy options to enhance biosimilar uptake and reduce budget impact.Methods: A three-phase approach was used. Phase 1 applied an extended analysis framework using survey data from Thai physicians to assess familiarity, attitudes, influencing factors, and sources of biosimilar information. Statistical tests examined associations and correlation strengths. Phase 2 conducted a budget impact analysis using trastuzumab for early-stage breast cancer as a case study, following ISPOR guidelines. Phase 3 proposed policy options based on integrated findings.Results: Eighty-two physicians participated. Medical specialty and self-assessed familiarity were significantly associated with biosimilar prescribing (p &lt; 0.05). 75.6% had adequate familiarity, and 69.5% showed favorable attitudes. However, attitude was not significantly associated with prescribing status. Familiarity and attitude were also not significantly correlated. Key influencing factors were efficacy data, safety information, and clinical guidelines. Main concerns included regulatory processes and post-marketing surveillance. The five-year budget impact was estimated at 24.63 million Thai Bath. Sensitivity analysis showed market share notably influenced outcomes including cost saving. Scenario analyses suggested that policy-driven uptake could enhance cost savings. Fourteen policy options were proposed, categorized into: (1) education and knowledge dissemination, (2) enabling environment for biosimilar use, and (3) building trust among stakeholders.Conclusions: While physicians generally showed positive familiarity and attitudes toward biosimilars, remaining gaps should be addressed to improve adoption and confidence. This study indicates that addressing behavioral barriers could support broader uptake, greater cost savings, and should improve patient access. The proposed policy options offer actionable strategies for promoting biosimilar use and achieving sustainable healthcare savings in Thailand.
DOI: 10.14457/tu.the.2024.484
title: A study of post-purchase stage in impulse buying

description: Impulse buying is a consumer behavior which is distinguished by a large amount of overall buying. As a social behavior it continues to increase, along with the advance of online shopping technology and new, easy forms of payment, such as credit cards or online payment protocols. Marketers pay close attention to it, since it leads to increased short-term sales and performance. Moreover, the study of impulse buying represents a significant portion of research into marketing and consumer behavior. However, it has consequences for both the customer and for the company. Customers have repeatedly reported having negative attitudes and emotions, such as guilt, regret, and self-blame, for their impulse-buying behaviors. Nevertheless, previous research has also reported diverse affective consequences of impulse buying. There are no studies that adequately provide empirical evidence to solve these incongruent affective consequences, which remain unexplainable. This dissertation provides a comprehensive study of the post-purchase stage of impulse buying, and aims to explain the conflicting consequences of that behavior. It employs cognitive appraisal theory to help explain which mechanisms are operating within the post-purchase stage of impulse buying. In other words, this study bridges the theory of cognitive appraisal to the behavior of impulse buying. This study provides reasons why cognitive appraisal theory is suited to the elucidation of impulse-buying phenomena. Chapter 1 (introduction) gives an overview and explains the significance of the dissertation. To address the research problem, chapter 2 (literature review) starts with a review of the existing literatures on impulse-buying behavior, with attention to conflicting findings; this is followed by a review of the relevant theories, especially the cognitive appraisal theory and its applicability to studies of consumption, such as impulse-buying phenomena. The chapter offers a model for study of post-purchase stage in impulse buying. Chapter 3 (methodology) describes the measurements, questionnaire development and pre-test for this study. Chapter 4 introduces analysis and findings. Chapter 5 provides discussions, conclusions, contribution and implication. In conclusion, this dissertation provides a comprehensive study of the post-purchase stage of impulse buying.
DOI: 10.25549/usctheses-ouc11399limi
title: Person-Directed Contractualism
DOI: 10.15468/dl.b9ttf7
title: Occurrence Download

description: A dataset containing 35 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((10.55341 7.93416,2.36431 -7.09649,9.55307 -14.95088,22.8656 -16.81464,28.85624 -0.3071,19.67059 8.34604,10.55341 7.93416))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Dalbergia micheliana De Wild."
 ]
}

 The dataset includes 35 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014683-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15584209
title: Integrated multi-omics profiling reveals the role of the DNA methylation landscape in shaping biological heterogeneity and clinical behaviour of metastatic melanoma.

description: ABSTRACT. Background. We developed an integrated multi-omics analysis in metastatic melanoma (MM) cohorts to associate DNA methylation profiles with tumor progression, survival, response to adjuvant immunotherapy, structure of the tumor immune microenvironment and transcriptional programs of immunity and melanoma differentiation. Methods. Lesions (n=191) from a fully annotated, retrospective cohort of 165 AJCC 8th Stage III and IV melanoma patients (EPICA cohort) were characterized by reduced representation bisulfite sequencing, RNA sequencing, whole exome sequencing, quantitative immunohistochemistry and multiplex immunofluorescence analysis. The TCGA melanoma datasets were used for validation. Pre-therapy lesions (n=28) from a cohort of MM patients treated with adjuvant immune checkpoint blockade were characterized for the DNA methylation profile.  Impact of a DNMT inhibitor on DNA methylation and transcriptomic profiles of melanoma cell lines was investigated by EPIC arrays and Clariom S arrays. Results. Four tumor subsets (i.e. DEMethylated, LOW, INTermediate and CIMP) with progressively increasing levels of DNA methylation were identified in EPICA, TCGA MM and TCGA primary melanoma cohorts. EPICA patients with LOW methylation tumors exhibited a significantly longer survival and a lower progression rate to more advanced AJCC stages, compared to patients with CIMP tumors. In an adjuvant immune checkpoint blockade cohort, patients with DEM/LOW pre-therapy lesions showed significantly longer relapse-free survival compared to those with INT/CIMP lesions. RNA-seq data analysis revealed that LOW and CIMP EPICA tumors showed opposite activation of master molecules influencing prognostic target genes, and differential expression of immunotherapy response and melanoma differentiation signatures. Compared to CIMP tumors, LOW lesions showed enrichment for CD8+ TCF-1+ PD-1+ TIM-3- pre-exhausted and CD8+ TCF-1- PD-1+ TIM-3+ exhausted T cells, more frequent retention of HLA Class I antigens and a de-differentiated melanoma phenotype. The differentiation and immune-related transcriptional features associated with LOW vs CIMP lesions were tumor-intrinsic programs retained in-vitro by melanoma cell lines. Consistently, treatment of differentiated melanoma cell lines with a DNMT inhibitor induced global DNA de-methylation, promoted de-differentiation and upregulated viral mimicry and IFNG predictive signatures of immunotherapy response.  Conclusions. These results reveal the biological, prognostic and therapeutic relevance of DNA methylation classes in MM and support methylome targeting strategies for precision immunotherapy.
DOI: 10.15468/dl.vxkqz6
title: Occurrence Download

description: A dataset containing 1081371 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((12.7851763191632 52.1234234050165, 13.8695460911873 52.1234234050165, 13.8695460911873 52.8541625341966, 12.7851763191632 52.8541625341966, 12.7851763191632 52.1234234050165))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 2015"
 ]
}

 The dataset includes 1081371 records from 85 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022050-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fsfckd
title: Occurrence Download

description: A dataset containing 2134 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Mussaenda erythrophylla Schumach. & Thonn."
 ]
}

 The dataset includes 2134 records from 184 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021876-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/5c3dykr6pt.1
title: BanglaOrna: A Smartphone Image Dataset of Traditional Bangladeshi Ornaments and Accessories

description: Traditional Bangladeshi ornaments and accessories—such as churi (terracotta bangles), tikli (filigree forehead ornaments), jhumka (bell-shaped earrings), and Komor Bicha (intricate waist chains)—are emblematic of the nation’s cultural heritage. Despite their anthropological and artistic value, no standardized dataset exists for computational research, hindering applications in heritage preservation, fashion technology, and ethnography.
We present BanglaOrna, the first comprehensive dataset of 2,028 high-resolution smartphone images documenting 30 categories of women’s traditional adornments, including kaaner duul (dangling earrings), haar (layered necklaces), and nakphul (bridal nose pins). Collected from Dhaka’s historic markets (New Market, Gausia Market) under diverse lighting and angles, the dataset reflects real-world variability in ornament styles and materials.
Images were captured using Redmi Note 14 Pro (200 MP), Redmi Note 14 (108 MP), and Redmi Note 12 Pro+ (200 MP), ensuring fine-grained detail for small, intricate designs. Each image is annotated in COCO format with bounding boxes and metadata. Augmentation techniques (rotation ±20°, brightness ±30%) were applied to improve model robustness.
BanglaOrna opens doors to: 
Training AI models for automated ornament classification and heritage documentation,
Supporting ethnographic research on regional design variations and 
Applications in virtual try-ons for e-commerce and digital museum archives.
DOI: 10.17632/5c3dykr6pt
title: BanglaOrna: A Smartphone Image Dataset of Traditional Bangladeshi Ornaments and Accessories

description: Traditional Bangladeshi ornaments and accessories—such as churi (terracotta bangles), tikli (filigree forehead ornaments), jhumka (bell-shaped earrings), and Komor Bicha (intricate waist chains)—are emblematic of the nation’s cultural heritage. Despite their anthropological and artistic value, no standardized dataset exists for computational research, hindering applications in heritage preservation, fashion technology, and ethnography.
We present BanglaOrna, the first comprehensive dataset with a total of 7,174 high-resolution smartphone images documenting 27 categories of women’s traditional adornments, including kaaner duul (dangling earrings), haar (layered necklaces), and nakphul (bridal nose pins). Collected from Dhaka’s historic markets (New Market, Gausia Market) under diverse lighting and angles, the dataset reflects real-world variability in ornament styles and materials.
Images were captured using Redmi Note 14 Pro (200 MP), Redmi Note 14 (108 MP), and Redmi Note 12 Pro+ (200 MP), ensuring fine-grained detail for small, intricate designs. Each image is annotated in COCO format with bounding boxes. Augmentation techniques (Horizontal and Vertical flip (50%), (±10 °) Horizontal and Vertical Shear,Brightness (±25%), Noise ( 0.5% )) were applied to improve model robustness.
BanglaOrna opens doors to: 
Training AI models for automated ornament classification and heritage documentation,
Supporting ethnographic research on regional design variations and 
Applications in virtual try-ons for e-commerce and digital museum archives.
DOI: 10.17632/5c3dykr6pt.2
title: BanglaOrna: A Smartphone Image Dataset of Traditional Bangladeshi Ornaments and Accessories

description: Traditional Bangladeshi ornaments and accessories—such as churi (terracotta bangles), tikli (filigree forehead ornaments), jhumka (bell-shaped earrings), and Komor Bicha (intricate waist chains)—are emblematic of the nation’s cultural heritage. Despite their anthropological and artistic value, no standardized dataset exists for computational research, hindering applications in heritage preservation, fashion technology, and ethnography.
We present BanglaOrna, the first comprehensive dataset with a total of 7,174 high-resolution smartphone images documenting 27 categories of women’s traditional adornments, including kaaner duul (dangling earrings), haar (layered necklaces), and nakphul (bridal nose pins). Collected from Dhaka’s historic markets (New Market, Gausia Market) under diverse lighting and angles, the dataset reflects real-world variability in ornament styles and materials.
Images were captured using Redmi Note 14 Pro (200 MP), Redmi Note 14 (108 MP), and Redmi Note 12 Pro+ (200 MP), ensuring fine-grained detail for small, intricate designs. Each image is annotated in COCO format with bounding boxes. Augmentation techniques (Horizontal and Vertical flip (50%), (±10 °) Horizontal and Vertical Shear,Brightness (±25%), Noise ( 0.5% )) were applied to improve model robustness.
BanglaOrna opens doors to: 
Training AI models for automated ornament classification and heritage documentation,
Supporting ethnographic research on regional design variations and 
Applications in virtual try-ons for e-commerce and digital museum archives.
DOI: 10.15468/dl.44gxfv
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is BOLD:AEF1811"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025622-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.m4tu9g
title: Occurrence Download

description: A dataset containing 1879150 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Turdus iliacus Linnaeus, 1758)",
 "Country is one of (Åland Islands, Albania, Andorra, Austria, Belarus, Belgium, Bosnia and Herzegovina, Bulgaria, Croatia, Czechia, Denmark, Estonia, Faroe Islands, Finland, France, Germany, Gibraltar, Greece, Guernsey, Holy See, Hungary, Iceland, Ireland, Isle of Man, Italy, Jersey, Latvia, Liechtenstein, Lithuania, Luxembourg, Malta, Moldova, Republic of, Monaco, Montenegro, Netherlands, North Macedonia, Norway, Poland, Portugal, Romania, Russian Federation, San Marino, Serbia, Slovakia, Slovenia, Spain, Svalbard and Jan Mayen, Sweden, Switzerland, Ukraine, United Kingdom of Great Britain and Northern Ireland)"
 ]
}

 The dataset includes 1879150 records from 1761 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018278-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.p3p33t
title: Occurrence Download

description: A dataset containing 60 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Ricinus communis",
 "Country is Japan",
 "HasCoordinate is true"
 ]
}

 The dataset includes 60 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025176-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fsehza
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Machine Observation)",
 "Country is Macao",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Pinopsida",
 "Year 1970-2024"
 ]
}

 The dataset includes 5 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025177-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/vgbzxpv7b8
title: Data set for "Large Language Models for Cue Detection in Multiple-Choice Questions"

description: This data folder contains several files associated with the manuscript currently entitled "Large Language Models for Cue Detection in Multiple-Choice Questions." Specifically, the following datasets and materials are included:

Raw Data Set: The raw dataset on which the analyses described in the manuscript were conducted.

Mean Cue Detection Performance per Model: A figure comparing the cue detection performance of three large language models (LLMs).

Mean Model Performance: A figure comparing the overall performance of the three LLMs in answering the multiple-choice questions.

Table 1_Prompt: The prompt used with all three LLMs to elicit answers to the multiple-choice questions and to identify cues.

Question Set Conceptual Paper: The multiple-choice questions that formed the basis for the conceptual framework of the manuscript.
DOI: 10.17632/vgbzxpv7b8.1
title: Data set for "Large Language Models for Cue Detection in Multiple-Choice Questions"

description: This data folder contains several files associated with the manuscript currently entitled "Large Language Models for Cue Detection in Multiple-Choice Questions." Specifically, the following datasets and materials are included:

Raw Data Set: The raw dataset on which the analyses described in the manuscript were conducted.

Mean Cue Detection Performance per Model: A figure comparing the cue detection performance of three large language models (LLMs).

Mean Model Performance: A figure comparing the overall performance of the three LLMs in answering the multiple-choice questions.

Table 1_Prompt: The prompt used with all three LLMs to elicit answers to the multiple-choice questions and to identify cues.

Question Set Conceptual Paper: The multiple-choice questions that formed the basis for the conceptual framework of the manuscript.
DOI: 10.15468/dl.ysd28g
title: Occurrence Download

description: A dataset containing 10 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Tinca tinca (Linnaeus, 1758)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((20.2855 -34.7533,20.509 -34.5676,20.509 -32.9007,17.7723 -32.9007,17.8156 -33.0786,18.3471 -33.7176,18.3748 -33.8287,18.2181 -34.0492,18.3197 -34.3408,18.4452 -34.429,18.5435 -34.4213,18.5872 -34.3667,18.5363 -34.167,18.7345 -34.1508,18.7216 -34.3637,18.7808 -34.4521,19.0289 -34.4206,19.0831 -34.4835,19.2655 -34.5017,19.2032 -34.6157,19.2394 -34.6926,19.375 -34.6963,19.6091 -34.8524,19.8251 -34.8396,19.9798 -34.9064,20.1081 -34.8731,20.1517 -34.7847,20.2855 -34.7533))"
 ]
}

 The dataset includes 10 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021886-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15601485
title: Birch and Swinnerton-Dyer Conjecture proof

description: Title: Clay Institute Version: Proof of the Birch and Swinnerton-Dyer Conjecture

Description:This document presents a formal and complete proof of the Birch and Swinnerton-Dyer Conjecture, one of the seven Millennium Prize Problems. The conjecture asserts that the rank of the group of rational points on an elliptic curve E over ℚ equals the order of vanishing of its L-function L(E, s) at s = 1.

Using the modularity of elliptic curves, descent via Selmer groups, Galois cohomology, and the finiteness of the Tate–Shafarevich group, the paper proves the equality between analytic and algebraic ranks. The argument incorporates the Gross–Zagier formula and Kolyvagin's work on Heegner points to bound ranks from both directions, resolving the conjecture in full alignment with rigorous mathematical expectations.

All claims, notation, and structures conform to modern standards in arithmetic geometry and are presented in a format ready for peer-reviewed consideration.

Keywords: Birch and Swinnerton-Dyer, Elliptic Curves, Mordell–Weil Group, L-functions, Selmer Groups, Galois Cohomology, Modular Forms, Millennium Problems, Clay Mathematics Institute