cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.16313978
title: "Sensory Dopamine Architecture: A Neurophenomenological Framework for Somatic Pleasure"

description: Copyright Đinh Thiên Anh © 2025 Creative Commons Attribution 4.0 International





Độ sâu thần kinh tỉ lệ nghịch với khả năng tạo khoái cảm âm tính.




Tần số – nhịp điệu lực chạm phải thuận với độ sâu thần kinh.




Lực tỉ lệ thuận với độ sâu thần kinh.




Neural depth is inversely proportional to the capacity for generating negative-valence pleasure (e.g., teasing, delayed contact).




The frequency and rhythm of tactile stimulation must correspond to the depth of the targeted neural receptors.




Stimulation force is directly proportional to the neural depth required for effective sensory response.



1:33PM22/7/2025 hà nội  (Effective Penetrative Length)

Giới thiệu khái niệm *Chiều dài thâm nhập hiệu quả (EPL)* — được định nghĩa là khoảng cách có thể đo được từ đầu quy đầu đến gốc bìu — để biểu thị độ sâu thực tế của việc đưa dương vật vào trong khi giao hợp.

Không giống như các phép đo thông thường (chiều dài ấn xương), tiêu chuẩn được đề xuất này phản ánh chiều dài tiếp xúc chức năng thực sự, tính đến các hạn chế giải phẫu thực tế trong quá trình thâm nhập.

Chúng tôi lập luận rằng EPL tương quan tốt hơn với phản hồi cảm giác dopaminergic và nên được xem xét trong các nghiên cứu tình dục thực thể trong tương lai.

 introduces the concept of *Effective Penetrative Length (EPL)* — defined as the measurable distance from the tip of the glans penis to the base at the scrotal junction — to represent the actual depth of insertion possible during intercourse.

Unlike conventional metrics (bone-pressed length), this proposed standard reflects the true functional contact length, accounting for real-world anatomical constraints during penetration.

We argue that EPL better correlates with dopaminergic sensory feedback, and should be considered in future embodied sexual studies.

cái bãi này còn nữa nhưng tôi lười quá  , tiền thời gian để làm không đủ
DOI: 10.15468/dl.a5xwbp
title: Occurrence Download

description: A dataset containing 0 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 (Rana temporaria)",
 "Country is one of (Algeria, Angola, Benin, Botswana, British Indian Ocean Territory, Burkina Faso, Burundi, Cabo Verde, Cameroon, Central African Republic, Chad, Comoros, Congo, Congo, Democratic Republic of the, Côte d’Ivoire, Djibouti, Egypt, Equatorial Guinea, Eritrea, Eswatini, Ethiopia, French Southern Territories, Gabon, Gambia, Ghana, Guinea, Guinea-Bissau, Kenya, Lesotho, Liberia, Libya, Madagascar, Malawi, Mali, Mauritania, Mauritius, Mayotte, Morocco, Mozambique, Namibia, Niger, Nigeria, Réunion, Rwanda, Saint Helena, Ascension and Tristan da Cunha, Sao Tome and Principe, Senegal, Seychelles, Sierra Leone, Somalia, South Africa, South Sudan, Sudan, Tanzania, United Republic of, Togo, Tunisia, Uganda, Western Sahara, Zambia, Zimbabwe)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028271-250717081556266/datasets/export for details.
DOI: 10.15468/dl.jkjtsj
title: Occurrence Download

description: A dataset containing 33 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Vernonia pteropoda",
 "HasCoordinate is true",
 "Geometry POLYGON ((-17.66889 -35.11691, 51.34702 -35.11691, 51.34702 37.62, -17.66889 37.62, -17.66889 -35.11691))"
 ]
}

 The dataset includes 33 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028269-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.r9cqyf
title: Occurrence Download

description: A dataset containing 0 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 (Rana temporaria)",
 "Country is one of (American Samoa, Australia, Christmas Island, Cocos (Keeling) Islands, Cook Islands, Fiji, French Polynesia, Guam, Heard Island and McDonald Islands, Kiribati, Marshall Islands, Micronesia (Federated States of), Nauru, New Caledonia, New Zealand, Niue, Norfolk Island, Northern Mariana Islands, Palau, Papua New Guinea, Pitcairn, Samoa, Solomon Islands, Tokelau, Tonga, Tuvalu, United States Minor Outlying Islands, Vanuatu, Wallis and Futuna)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028272-250717081556266/datasets/export for details.
DOI: 10.5281/zenodo.16317944
title: AI-assisted sensor system for real-time monitoring of surgical hand disinfectant healthcare efficacy

description: Surgical hand disinfection is one of the most effective methods of preventing Surgical Site Infections (SSIs). However, the traditional methods of monitoring SSIs are microbiological culture testing and monitoring staff compliance, both of which can be subjective and delayed. For this purpose, this research introduces an AI-assisted sensor system that retrieves information about the surgical hand disinfectant's effectiveness in real time through machine learning, biosensors, and IoT-based analytics. The methodology uses a novel approach by employing phytochemical biosensors that can assess residual disinfectant coverage and subsequent bacterial contamination through fluorescence spectroscopy and impedance microbiology. The sensor data using clinical bacterial culture datasets is used for post-disinfection bacterium persistence assessment during deep learning. When the AI systems detect insufficient disinfection measures, the system alerts the personnel. This feedback is provided immediately to foster constant compliance with WHO hand hygiene recommendations. The Hybrid AI-sensor framework proposed in this research provided additional detection accuracy using Temporal Convolutional Networks (TCNs) and Hypergraph Neural Networks (HGNNs) to detect sensor data streams.
DOI: 10.5281/zenodo.16317945
title: AI-assisted sensor system for real-time monitoring of surgical hand disinfectant healthcare efficacy

description: Surgical hand disinfection is one of the most effective methods of preventing Surgical Site Infections (SSIs). However, the traditional methods of monitoring SSIs are microbiological culture testing and monitoring staff compliance, both of which can be subjective and delayed. For this purpose, this research introduces an AI-assisted sensor system that retrieves information about the surgical hand disinfectant's effectiveness in real time through machine learning, biosensors, and IoT-based analytics. The methodology uses a novel approach by employing phytochemical biosensors that can assess residual disinfectant coverage and subsequent bacterial contamination through fluorescence spectroscopy and impedance microbiology. The sensor data using clinical bacterial culture datasets is used for post-disinfection bacterium persistence assessment during deep learning. When the AI systems detect insufficient disinfection measures, the system alerts the personnel. This feedback is provided immediately to foster constant compliance with WHO hand hygiene recommendations. The Hybrid AI-sensor framework proposed in this research provided additional detection accuracy using Temporal Convolutional Networks (TCNs) and Hypergraph Neural Networks (HGNNs) to detect sensor data streams.
DOI: 10.5281/zenodo.16316068
title: AI Optimization for Real-Time Butterfly Classification: Enhancing Image Processing for Field Applications

description: Dataset for project https://gitlab.com/petrkrojcigr/butterfly-detection-and-classification/-/tree/main
DOI: 10.5281/zenodo.16316069
title: AI Optimization for Real-Time Butterfly Classification: Enhancing Image Processing for Field Applications

description: Dataset for project https://gitlab.com/petrkrojcigr/butterfly-detection-and-classification/-/tree/main
DOI: 10.6084/m9.figshare.29610470
title: Legal_Cases_eHealth

description: Legal_Cases_eHealth_Norway 2015-2025
DOI: 10.6084/m9.figshare.29610470.v1
title: Legal_Cases_eHealth

description: Legal_Cases_eHealth_Norway 2015-2025
DOI: 10.15468/dl.d694x6
title: Occurrence Download

description: A dataset containing 5347 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Artemisia verlotiorum",
 "Country is Switzerland",
 "HasCoordinate is true"
 ]
}

 The dataset includes 5347 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028274-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pjsmn3
title: Occurrence Download

description: A dataset containing 2706 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Eucalyptus"
 ]
}

 The dataset includes 2706 records from 42 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028275-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.35szuf
title: Occurrence Download

description: A dataset containing 6189 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Gladiolus illyricus"
 ]
}

 The dataset includes 6189 records from 189 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028273-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh0166903.10fu
title: SH0166903.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0166904.10fu
title: SH0166904.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0166905.10fu
title: SH0166905.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0166906.10fu
title: SH0166906.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0166907.10fu
title: SH0166907.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0166908.10fu
title: SH0166908.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0166909.10fu
title: SH0166909.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.5281/zenodo.18197045
title: 3I Atlas Carrier of Null Spot Energy Leakage - RJW

description: 3I Atlas. Let's face it, 3I ATLAS has an energy source at its core. If you look at the evidence you can see that. Want to know what powers it? You have only to look and see the evidence once. That reveal will open your eyes to see the evidence across the universe again and again. Speculative, sure, but when evidence mounts again and again, speculative starts leaning towards a mechanism. I see this mechanism explaining so much in our solar system. From the sun to beyond the heliosphere.

So the heating of the sun's corona via anti-matter annihilation to every magnetically aligned body in our solar system and when even look at as a whole the plasma that Voyager flew through beyond our solar system. Where was this plasma? Beyond our solar system's magnetic fields and before the interstellar magnetic fields. A null spot between the fields. This explains so much that we observe but do not explain well. Look for magnetic null spots between magnetic norths and souths magnetic poles. Look for the heating that these spots contain. Gamma will be close by. Surprise! It's universal. Even the source of what turns on stars and the power source of supernova explosions and black hole jets. 3I Atlas has the mechanism. Shielded by nickel, almost pure nickel. The gamma when it's done getting through that shell appears as X-rays. The annihilation energy comes out its poles and keeps its pole heading towards the sun magnetically aligned. The pulses of lightning along its tail is the field lines it's crossing that are reinforcing the mechanism in its core. Sorry people, too many facts aligning with the mechanism. Look close. You will see what we consider to be dark matter bleeding from the 5th dimension into our 4D reality. This also is the mechanism that turns on stars. Look at the stellar nursery that JWST imaged a couple weeks ago. Too early for fusion, but the IR was off the scale. Why? Anti-matter annihilation energy. The mechanism shining loud and proud. More evidence. Read on and decide for yourself. Thanks for reading and remember. Physics is elegance or it's wrong. RJW
DOI: 10.5281/zenodo.18197046
title: 3I Atlas Carrier of Null Spot Energy Leakage - RJW

description: 3I Atlas. Let's face it, 3I ATLAS has an energy source at its core. If you look at the evidence you can see that. Want to know what powers it? You have only to look and see the evidence once. That reveal will open your eyes to see the evidence across the universe again and again. Speculative, sure, but when evidence mounts again and again, speculative starts leaning towards a mechanism. I see this mechanism explaining so much in our solar system. From the sun to beyond the heliosphere.

So the heating of the sun's corona via anti-matter annihilation to every magnetically aligned body in our solar system and when even look at as a whole the plasma that Voyager flew through beyond our solar system. Where was this plasma? Beyond our solar system's magnetic fields and before the interstellar magnetic fields. A null spot between the fields. This explains so much that we observe but do not explain well. Look for magnetic null spots between magnetic norths and souths magnetic poles. Look for the heating that these spots contain. Gamma will be close by. Surprise! It's universal. Even the source of what turns on stars and the power source of supernova explosions and black hole jets. 3I Atlas has the mechanism. Shielded by nickel, almost pure nickel. The gamma when it's done getting through that shell appears as X-rays. The annihilation energy comes out its poles and keeps its pole heading towards the sun magnetically aligned. The pulses of lightning along its tail is the field lines it's crossing that are reinforcing the mechanism in its core. Sorry people, too many facts aligning with the mechanism. Look close. You will see what we consider to be dark matter bleeding from the 5th dimension into our 4D reality. This also is the mechanism that turns on stars. Look at the stellar nursery that JWST imaged a couple weeks ago. Too early for fusion, but the IR was off the scale. Why? Anti-matter annihilation energy. The mechanism shining loud and proud. More evidence. Read on and decide for yourself. Thanks for reading and remember. Physics is elegance or it's wrong. RJW
DOI: 10.15156/bio/sh0166910.10fu
title: SH0166910.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.