cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.10054803
title: Most bacterial gene families are biased toward specific chromosomal positions

description: The arrangement of genes along bacterial chromosomes influences their expression through growth rate-dependent gene copy number changes during DNA replication. While translation and transcription genes often cluster near the origin of replication, the extent of positional biases across gene families remains unclear. We hypothesized that natural selection broadly favors specific chromosomal positions to optimize growth rate-dependent expression. Analyzing 910 bacterial species and proteomics data from Escherichia coli and Bacillus subtilis, we find that about two-thirds of bacterial gene families are positionally biased, mainly near the origin or terminus of replication, with the strongest natural selection in fast-growing species. Our findings reveal chromosomal positioning as a fundamental mechanism for coordinating gene expression with growth rate, highlighting evolutionary constraints on bacterial genome architecture.
DOI: 10.5281/zenodo.10054804
title: Nearly half of all bacterial gene families are biased toward specific chromosomal positions

description: Many bacterial genes encoding components of the translation and transcription machinery occupy genomic positions close to the origin of genome replication. These positional biases are thought to result from selection for high expression levels, as genes close to the origin are the first to be duplicated after the initiation of DNA replication. However, recent work indicates that positional biases of RNA genes involved in translation have evolved to support optimal growth rate dependence of expression levels rather than high expression per se. We hypothesized that, more generally, natural selection may have favored the location of different genes at specific chromosomal positions to optimize the growth rate dependence of their relative gene copy numbers. Here we show that 49% of bacterial gene families are preferentially localized to specific chromosomal regions, with most families biased toward either the origin or the terminus of replication. From our hypothesis, we derive six specific predictions regarding the genes' chromosomal positioning and functional categories, as well as the minimum cellular doubling times. All six predictions are robustly supported by comparative genomic analyses of 773 bacterial species and by proteomics data from Escherichia coli and Bacillus subtilis. Our findings reveal a complex relationship between bacterial growth, resource allocation and genome organization, and they provide new insights into the physiological significance and potential functions of a large number of gene families.
DOI: 10.25934/pr00006053.17
title: Available IPD datapackage for study 'A Phase III, Open-Label, Multicenter, Randomized Study Evaluating the Efficacy and Safety of Atezolizumab (MPDL3280A, Anti-PD-L1 Antibody) in Combination With Carboplatin+Paclitaxel or Atezolizumab in Combination With Carboplatin+Nab-Paclitaxel Versus Carboplatin+Nab-Paclitaxel in Chemotherapy-Naive Patients With Stage IV Squamous Non-Small Cell Lung Cancer'

description: This randomized, open-label study will evaluate the safety and efficacy of atezolizumab (MPDL3280A) in combination with carboplatin + paclitaxel or carboplatin + nab-paclitaxel compared with treatment with carboplatin + nab-paclitaxel in chemotherapy-naive participants with Stage IV squamous NSCLC.
DOI: 10.5258/soton/d3358
title: Data supporting the thesis 'Simulations of rheological properties of lubricants under operational conditions'

description: The dataset is divided in

IDEAL : This folder contains the data regarding the result chapter on Ideal mixtures of two esters obtained via LAMMPS software. It contains the input files, output files, jupyter notebooks with the analysis as well as molecular dynamics trajectories and files to reproduce the simulations and data.

MIXTURE2: This folder contains the data regarding the mixture 2 (non-ideal mixtures result chapter) obtained via LAMMPS software. Specifically, it contains the input files, output files, jupyter notebooks with the analysis as well as molecular dynamics trajectories and files to reproduce the simulations and data.

MIXTURE2: This folder contains the data regarding the mixture 2 (non-ideal mixtures result chapter) obtained via LAMMPS software. Specifically, it contains the input files, output files, jupyter notebooks with the analysis as well as molecular dynamics trajectories and files to reproduce the simulations and data.

Bicyclo_Butylbenzene: This folder contains the data regarding the two of the component of the mixtures used in the non-ideal mixtures result chapter obtained via LAMMPS software. Specifically, it contains the input files, output files, jupyter notebooks with the analysis as well as molecular dynamics trajectories and files to reproduce the simulations and data.

Non_ideal_1_2_4GPa and non_ideal_1bar_05GPa : These folders contain the data regarding the mixture 1 of the non-ideal result chapter obtained via LAMMPS software. Specifically, it contains the input files, output files, jupyter notebooks with the analysis as well as molecular dynamics trajectories and files to reproduce the simulations and data.

CONFINED: This folder contains the data regarding the result chapter on confined system obtained via LAMMPS software. It contains the input files, output files, jupyter notebooks with the analysis as well as molecular dynamics trajectories and files to reproduce the simulations and data. Part of the data necessary to reproduce the data in chapter have been published in another thesis, ref. to doi:10.5258/SOTON/D2436

Hematite: This folder contains the data regarding the result chapter on hematite+zddp obtained via the ONETEP software. It contains the input files, output files, jupyter notebooks with the analysis as well as pseudopotential and any file needed to reproduce the work.

this large dataset 515GB is available 'on request' due to size. Please complete the request form at 
https://library.soton.ac.uk/datarequest
DOI: 10.5281/zenodo.14922157
title: Side Profile Tires Dataset

description: Description:







This Side Profile Tires Dataset consists of meticulously annotated images of tire side profiles, specifically designed for image segmentation tasks. Each tire has been manually labeled to ensure high accuracy, making this dataset ideal for training machine learning models focused on tire detection, classification, or related automotive applications.

The annotations are provided in the YOLO v5 format, leveraging the PyTorch framework for deep learning applications. The dataset offers a robust foundation for researchers and developers working on object detection, autonomous vehicles, quality control, or any project requiring precise tire identification from images.







Download Dataset









Data Collection and Labeling Process:



Manual Labeling: Every tire in the dataset has been individually labeled to guarantee that the annotations are highly precise, significantly reducing the margin of error in model training.

Annotation Format: YOLO v5 PyTorch format, a highly efficient and widely used format for real-time object detection systems.


Pre-processing Applied:



Auto-orientation: Pixel data has been automatically oriented, and EXIF orientation metadata has been stripped to ensure uniformity across all images, eliminating issues related to image orientation during processing.

Resizing: All images have been resized to 416×416 pixels using stretching to maintain compatibility with common object detection frameworks like YOLO. This resizing standardizes the image input size while preserving visual integrity.


Applications:



Automotive Industry: This dataset is suitable for automotive-focused AI models, including tire quality assessment, tread pattern recognition, and autonomous vehicle systems.

Surveillance and Security: Use cases in monitoring systems where identifying tires is crucial for vehicle recognition in parking lots or traffic management systems.

Manufacturing and Quality Control: Can be used in tire manufacturing processes to automate defect detection and classification.


Dataset Composition:



Number of Images: [Add specific number]

File Format: JPEG/PNG

Annotation Format: YOLO v5 PyTorch

Image Size: 416×416 (standardized across all images)


This dataset is sourced from Kaggle.
DOI: 10.5281/zenodo.14922158
title: Side Profile Tires Dataset

description: Description:







This Side Profile Tires Dataset consists of meticulously annotated images of tire side profiles, specifically designed for image segmentation tasks. Each tire has been manually labeled to ensure high accuracy, making this dataset ideal for training machine learning models focused on tire detection, classification, or related automotive applications.

The annotations are provided in the YOLO v5 format, leveraging the PyTorch framework for deep learning applications. The dataset offers a robust foundation for researchers and developers working on object detection, autonomous vehicles, quality control, or any project requiring precise tire identification from images.







Download Dataset









Data Collection and Labeling Process:



Manual Labeling: Every tire in the dataset has been individually labeled to guarantee that the annotations are highly precise, significantly reducing the margin of error in model training.

Annotation Format: YOLO v5 PyTorch format, a highly efficient and widely used format for real-time object detection systems.


Pre-processing Applied:



Auto-orientation: Pixel data has been automatically oriented, and EXIF orientation metadata has been stripped to ensure uniformity across all images, eliminating issues related to image orientation during processing.

Resizing: All images have been resized to 416×416 pixels using stretching to maintain compatibility with common object detection frameworks like YOLO. This resizing standardizes the image input size while preserving visual integrity.


Applications:



Automotive Industry: This dataset is suitable for automotive-focused AI models, including tire quality assessment, tread pattern recognition, and autonomous vehicle systems.

Surveillance and Security: Use cases in monitoring systems where identifying tires is crucial for vehicle recognition in parking lots or traffic management systems.

Manufacturing and Quality Control: Can be used in tire manufacturing processes to automate defect detection and classification.


Dataset Composition:



Number of Images: [Add specific number]

File Format: JPEG/PNG

Annotation Format: YOLO v5 PyTorch

Image Size: 416×416 (standardized across all images)


This dataset is sourced from Kaggle.
DOI: 10.15468/dl.temqnu
title: Occurrence Download

description: A dataset containing 1624765 species occurrences available in GBIF matching the query:
{
 "and" : [
 "CollectionCode is vannmiljo",
 "DatasetKey is Norwegian Biodiversity Information Centre - Other datasets"
 ]
}

 The dataset includes 1624765 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000058-250225085111116/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25934/pr00006051.18
title: Available IPD datapackage for study 'A Phase III, Open-Label, Randomized Study of Atezolizumab (MPDL3280A, Anti-PD-L1 Antibody) in Combination With Carboplatin+Paclitaxel With or Without Bevacizumab Compared With Carboplatin + Paclitaxel + Bevacizumab in Chemotherapy-Naïve Patients With Stage IV Non-Squamous Non-Small Cell Lung Cancer'

description: This randomized, open-label study will evaluate the safety and efficacy of atezolizumab (an engineered anti-programmed death-ligand 1 [PD-L1] antibody) in combination with carboplatin+paclitaxel with or without bevacizumab compared with treatment with carboplatin+paclitaxel+bevacizumab in chemotherapy-naïve participants with Stage IV non-squamous NSCLC. Participants will be randomized in a 1:1:1 ratio to Arm A (Atezolizumab+Carboplatin+Paclitaxel), Arm B (Atezolizumab+Carboplatin+Paclitaxel+Bevacizumab), or Arm C (Carboplatin+Paclitaxel+Bevacizumab).
DOI: 10.15468/dl.9hfbkf
title: Occurrence Download

description: A dataset containing 65 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Senecio carpetanus Boiss. & Reut.",
 "Geometry POLYGON((-4.57907617500001 39.884719509, -4.57907617500001 41.165844755, -3.05298331400002 41.165844755, -3.05298331400002 39.884719509, -4.57907617500001 39.884719509))"
 ]
}

 The dataset includes 65 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000061-250225085111116/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21227/fgj9-9b69
title: Diffraction images

description: High-precision displacement measurement plays a significant role in industrial manufacturing. Displacement measurement systems based on optical interference principles typically feature complex optical paths and high costs, with measurement accuracy largely dependent on the precision of the instruments and their stability in varying environments. Based on the sensitivity of optical diffraction patterns to the position of the diffracting object, this paper proposes a novel nano-scale displacement measurement method based on deep learning with diffraction images. The measurement system consists of a light source, diffraction aperture, and image sensor, featuring a simple structure and low cost. This method utilizes a deep learning model to establish a mapping relationship where diffraction images are the input and displacement values are the output. During operation, an image sensor captures the diffraction images and feeds them into the deep learning model to determine the displacement variation of the diffraction plate in the direction perpendicular to the optical axis.
DOI: 10.25934/pr00005794.22
title: Available IPD datapackage for study 'A Phase III, Open-Label, Multicenter, Randomized Study to Investigate the Efficacy and Safety of Atezolizumab (Anti-PD-L1 Antibody) Compared With Docetaxel in Patients With Non-Small Cell Lung Cancer After Failure With Platinum Containing Chemotherapy'

description: This global, multicenter, open-label, randomized, controlled study evaluated the efficacy and safety of atezolizumab (an anti-programmed death−ligand 1 [anti-PD-L1] antibody)compared with docetaxel in participants with locally advanced or metastatic non-small cell lung cancer (NSCLC) after failure with platinum-containing chemotherapy. Participants were randomized 1:1 to receive either docetaxel or atezolizumab. Treatment may continue as long as participants experienced clinical benefit as assessed by the investigator, i.e., in the absence of unacceptable toxicity or symptomatic deterioration attributed to disease progression.
DOI: 10.25934/pr00005793.13
title: Available IPD datapackage for study 'A Phase II, Open-label, Multicenter, Randomized Study to Investigate the Efficacy and Safety of MPDL3280A (Anti−PD-L1 Antibody) Compared With Docetaxel in Patients With Non−Small Cell Lung Cancer After Platinum Failure'

description: This multicenter, open-label, randomized study will evaluate the efficacy and safety of Atezolizumab compared with docetaxel in participants with advanced or metastatic non-small cell lung cancer after platinum failure. Participants will be randomized to receive either Atezolizumab 1200 milligram (mg) intravenously every 3 weeks or docetaxel 75 milligram per meter square (mg/m^2) intravenously every 3 weeks. Treatment with Atezolizumab may be continued as long as participants are experiencing clinical benefit as assessed by the investigator, i.e., in the absence of unacceptable toxicity or symptomatic deterioration attributed to disease progression.
DOI: 10.15468/dl.8dd9hy
title: Occurrence Download

description: A dataset containing 10 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Serapias cordigera L.",
 "Geometry POLYGON((-4.57907617500001 39.884719509, -4.57907617500001 41.165844755, -3.05298331400002 41.165844755, -3.05298331400002 39.884719509, -4.57907617500001 39.884719509))"
 ]
}

 The dataset includes 10 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000062-250225085111116/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.r74fwe
title: Occurrence Download

description: A dataset containing 92 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Chrysaora agulhensis Ras, Neethling, Engelbrecht, Morandini, Bayha, Skrypzeck & Gibbons, 2020",
 "Year 2020-2025"
 ]
}

 The dataset includes 92 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000063-250225085111116/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5834b9
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Serapias parviflora Parl.",
 "Geometry POLYGON((-4.57907617500001 39.884719509, -4.57907617500001 41.165844755, -3.05298331400002 41.165844755, -3.05298331400002 39.884719509, -4.57907617500001 39.884719509))"
 ]
}

 The dataset includes 5 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000064-250225085111116/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2kj4c8
title: Occurrence Download

description: A dataset containing 163 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is BLR",
 "TaxonKey is one of (Cinclidium stygium Sw., Helodium blandowii (F.Weber & D.Mohr) Warnst., Pseudobryum cinclidioides (Huebener) T.J.Kop., Hamatocaulis vernicosus (Mitt.) Hedenäs, Meesia triquetra (L. ex Jolycl.) Ångstr., Meesia uliginosa Hedw., Paludella squarrosa (Hedw.) Brid., Tomentypnum nitens (Hedw.) Loeske, Scorpidium cossonii (Schimp.) Hedenäs, Scorpidium scorpioides (Hedw.) Limpr., Drepanocladus polygamus (Schimp.) Hedenäs, Drepanocladus sendtneri (Schimp. ex H.Müll.) Warnst., Haplocladium microphyllum (Sw. ex Hedw.) Broth.)"
 ]
}

 The dataset includes 163 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000065-250225085111116/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2d4u6y
title: Occurrence Download

description: A dataset containing 144 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Epilasia hemilasia (Bunge) C.B.Clarke"
 ]
}

 The dataset includes 144 records from 26 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000068-250225085111116/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.27134016.v2
title: Detailed data_industrial solid waste in China.xlsx

description: Rapid industrialization of China generated great amount of industrial solid waste, causing significant environmental pressure. However, a complete temporal dataset of this waste in China is absent, due to unplanned collection effort or changing statistical standard. There is an urgent need to have a complete dataset of industrial solid waste generated each year, in order to come up with targeted policy for resource recovery, recycling, and circular economy initiatives. To fill the data gap, we collected the current available data and use six machine learning model to complete the dataset across 338 cities in China from 1990-2022. Bayesian optimization has been utilized to find the best model and enhance the predictive model's performance and resilience. Furthermore, we selected six dominant industrial waste that occupy the majority amount of the overall waste generation, and present the data at city-level. This dataset can provide policymakers with valuable insights into waste generation patterns, to address specific waste management challenges of different regions in China.
DOI: 10.15468/dl.5kakd4
title: Occurrence Download

description: A dataset containing 144 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Epilasia hemilasia (Bunge) C.B.Clarke"
 ]
}

 The dataset includes 144 records from 26 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000067-250225085111116/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.28483748
title: <b>Asymmetric responses of soil dissolved organic carbon and dissolved organic nitrogen to warming: a meta-analysis</b>

description: Soil dissolved organic carbon (DOC) and dissolved organic nitrogen (DON) play pivotal roles in regulating soil carbon and nitrogen cycles. The global effects of experimental warming on DOC and DON concentrations and their relationship (DOC:DON) remain uncertain. This study integrates a dataset containing 321 separate DOC and 187 DON independent experiments to address the magnitude and direction of warming's impact on DOC and DON, as well as the key driving factors. Our results indicated that while warming did not significantly affect DOC concentrations, it led to a notable increase in DON concentrations (8.84%), consequently reducing DOC:DON ratio by 10.79%. Soil moisture emerged as the most influential factor (19.0%) driving DOC responses to warming, whereas soil nitrate nitrogen was the primary driver (33.2%) of DON responses to warming. Soil ammonium nitrogen exhibited a positive linear relationship with the DOC:DON ratio, while soil nitrate nitrogen responded negatively as the DOC:DON ratio increased. Our results revealed the complex responses of carbon and nitrogen cycles to warming, including their decoupling patterns. This finding highlights the sensitivity and adaptability of soil carbon and nitrogen cycles to experimental warming, uncovers that warming could disrupt the soil carbon and nitrogen balance, potentially affecting ecosystem stability and function.
DOI: 10.15468/dl.87upzp
title: Occurrence Download

description: A dataset containing 144 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Epilasia hemilasia (Bunge) C.B.Clarke"
 ]
}

 The dataset includes 144 records from 26 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000069-250225085111116/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ysene2
title: Occurrence Download

description: A dataset containing 656742 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "Geometry POLYGON((117.1549 31.76578,124.13173 31.76578,124.13173 41.19382,117.1549 41.19382,117.1549 31.76578))",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 656742 records from 402 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000025-250225085111116/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.