cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.57680/asep.0643046
title: Mikrofotografie sinice Trichormus
title: Micrograph of the cyanobacteria Trichormus

description: Mikrofotografie sinice Trichormus ve světelném a fluorescenčním mikroskopu pro stanovení fyziologického stavu buněk během přechodu z laboratorních podmínek k pilotní venkovní kultivaci tohoto kmene ve větším objemu (20L). Fotografováno na mikroskopu Olympus BX51.
description: Micrographs of the cyanobacterium Trichormus in a light and fluorescence microscope to determine the physiological state of the cells during the transition from laboratory conditions to pilot outdoor cultivation of this strain in a larger volume (20L). Photographed on an Olympus BX51 microscope.
DOI: 10.15468/jvtefa
title: PINK - Amphibia monitoring for the permanent surveillance of coastal areas in Flanders, Belgium

description: 'PINK - Amphibia monitoring for the permanent surveillance of coastal areas in Flanders, Belgium.' is a sample based species occurrence dataset published by the Research Institute for Nature and Forest (INBO). The dataset contains over 1900 occurrences sampled between 2007-04-03 and 2016-07-05 from 243 ponds near the Belgian coast. The dataset includes over 10 species, collected in the PINK Amphibia subset. The monitoring of these coastal areas is needed to secure the nature conservation at the Belgian coast. Issues with the dataset can be reported at https://github.com/LifeWatchINBO/dataset-pink-amphibia-events.The data are collected for the project PINK (Permanente Inventarisatie van de Natuurreservaten aan de Kust), which was commissioned by the Agency for Nature and Forest in 2007. The project started with the aim of mapping the natural values on the coast in a more systematic way. A first 3-year phase (PINK I) ran from 2008 to 2010, in which the methodology was set up and an initial assessment was conducted. A second phase (PINK II) ran from 2012 to 2014, which was a continuation of the main components of PINK I, with special attention for invasive species and grasshoppers. A third phase (PINK III) is running from 2014 to 2018. This dataset contains mainly Amphibia occurrences observed during PINK I and PINK II.To allow anyone to use this dataset, we have released the data to the public domain under a Creative Commons Zero waiver (http://creativecommons.org/publicdomain/zero/1.0/). We would appreciate however, if you read and follow these norms for data use (http://www.inbo.be/en/norms-for-data-use) and provide a link to the original dataset (https://doi.org/complete) whenever possible. If you use these data for a scientific paper, please cite the dataset following the applicable citation norms and/or consider us for co-authorship. We are always interested to know how you have used or visualized the data, or to provide more information, so please contact us via the contact information provided in the metadata, opendata@inbo.be or https://twitter.com/LifeWatchINBO.
DOI: 10.5281/zenodo.17899636
title: German Credit dataset
DOI: 10.5281/zenodo.17899637
title: German Credit dataset
DOI: 10.15468/dl.9utex2
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is United States of America",
 "StateProvince is Idaho",
 "TaxonKey is Bombus pensylvanicus"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0047142-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.usphf2
title: Occurrence Download

description: A dataset containing 1855 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Vespa mandarinia)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "Year is not null",
 "BasisOfRecord is one of (Human Observation, Occurrence evidence)",
 "Year is greater than or equal to 2010",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 1855 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0047143-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4rtfz9
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((105.551 -1.367819, 105.480717 -1.373385, 105.412163 -1.389945, 105.347026 -1.417093, 105.286909 -1.45416, 105.233291 -1.500233, 105.187492 -1.55418, 105.150641 -1.614671, 105.123644 -1.680219, 105.107167 -1.749209, 105.101617 -1.819944, 105.107132 -1.890681, 105.123578 -1.959679, 105.15055 -2.025239, 105.187386 -2.085746, 105.233179 -2.139709, 105.286803 -2.1858, 105.346936 -2.222882, 105.412098 -2.250042, 105.480682 -2.26661, 105.551 -2.272179, 105.621318 -2.26661, 105.689902 -2.250042, 105.755064 -2.222882, 105.815197 -2.1858, 105.868821 -2.139709, 105.914614 -2.085746, 105.95145 -2.025239, 105.978422 -1.959679, 105.994868 -1.890681, 106.000383 -1.819944, 105.994833 -1.749209, 105.978356 -1.680219, 105.951359 -1.614671, 105.914508 -1.55418, 105.868709 -1.500233, 105.815091 -1.45416, 105.754974 -1.417093, 105.689837 -1.389945, 105.621283 -1.373385, 105.551 -1.367819))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0047144-251120083545085/datasets/export for details.
DOI: 10.6084/m9.figshare.30860529
title: Toward efficient dielectric material discovery: a comparative evaluation of Transformer and AutoML-based inverse learning

description: The discovery of dielectric material compositions and processing parameters often relies on trial-and-error experimentation, which is time-consuming, costly, and labor-intensive. To accelerate this process, artificial intelligence (AI) provides data-driven solutions that enhance predictive accuracy while minimizing experimental overhead. This study compares two AI methodologies: Transformer and AutoML-based Inverse Learning, for recommending compositions and processes of dielectric materials using data from the https://www.matcenter.org/Ceramic Materials Information Bank. Results show that while both methods perform reliably, AutoML consistently outperforms Transformer models across all metrics. AutoML achieved RÂ<sup>2</sup> scores of 0.970 for component prediction and 0.978 for process prediction, with MAPE values of 1.4% and 1.1%, respectively. In contrast, Transformer models yielded lower RÂ<sup>2</sup> scores (0.952 and 0.934) and higher MAPE values (over 2.0%). To enhance model interpretability, SHAP (SHapley Additive exPlanations) analysis was conducted, providing insights into feature contributions and supporting the reliability of predictions. These findings demonstrate AutoML superior ability to handle tabular data and its effectiveness in capturing complex material-process relationships. The study establishes AutoML as a robust framework for accelerating material discovery. It highlights the importance of selecting architectures that are suited to the data structure in AI-driven materials science.
DOI: 10.6084/m9.figshare.30860529.v1
title: Toward efficient dielectric material discovery: a comparative evaluation of Transformer and AutoML-based inverse learning

description: The discovery of dielectric material compositions and processing parameters often relies on trial-and-error experimentation, which is time-consuming, costly, and labor-intensive. To accelerate this process, artificial intelligence (AI) provides data-driven solutions that enhance predictive accuracy while minimizing experimental overhead. This study compares two AI methodologies: Transformer and AutoML-based Inverse Learning, for recommending compositions and processes of dielectric materials using data from the https://www.matcenter.org/Ceramic Materials Information Bank. Results show that while both methods perform reliably, AutoML consistently outperforms Transformer models across all metrics. AutoML achieved RÂ<sup>2</sup> scores of 0.970 for component prediction and 0.978 for process prediction, with MAPE values of 1.4% and 1.1%, respectively. In contrast, Transformer models yielded lower RÂ<sup>2</sup> scores (0.952 and 0.934) and higher MAPE values (over 2.0%). To enhance model interpretability, SHAP (SHapley Additive exPlanations) analysis was conducted, providing insights into feature contributions and supporting the reliability of predictions. These findings demonstrate AutoML superior ability to handle tabular data and its effectiveness in capturing complex material-process relationships. The study establishes AutoML as a robust framework for accelerating material discovery. It highlights the importance of selecting architectures that are suited to the data structure in AI-driven materials science.
DOI: 10.6084/m9.figshare.29040377
title: Expression Significance and Prognostic Value of GPR27 in Ovarian Cancer

description: This study explored the prognostic role of GPR27 and its predictive value to platinum-based therapy in ovarian cancer. A survival analysis of GPR27, and the therapeutic response to platinum in ovarian cancer was investigated using data from the cancer genome atlas (TCGA) and Gene Expression Omnibus (GEO) databases. GPR27 expression was assessed using reverse transcription-polymerase chain reaction (RT-PCR) and immunohistochemistry. Database analysis and RT-PCR revealed over-expression of GPR27 mRNA in ovarian cancer tissues compared to normal ovarian tissues. Ovarian cancer patients with up-regulated GPR27 transcription were associated with better overall survival and disease-free survival compared to those with downregulated GPR27 mRNA in the TCGA dataset and Kaplan-Meier plot database (<i>N</i> = 1656). GPR27 demonstrated good predictive value for pathological response in patients with ovarian cancer receiving platinum-based therapy. The predictive performance for 6-month relapse-free survival was higher in endometrioid ovarian cancer (AUC:0.804) than that in serous ovarian cancer. GPR27 protein levels were significantly up-regulated in ovarian cancer tissues compared with normal ovarian tissue, and high GPR27 protein expression correlated with early-stage TNM. ROC analysis revealed that the GPR27 protein, quantified by the immunohistochemistry score, effectively predicted the response to platinum-based therapy response with an AUC of 0.7479 in our cohort. GPR27 was up-regulated in ovarian cancer, compared with that of normal ovarian tissue, and was strongly correlated with survival outcomes and response to platinum-based therapy. GPR27 may serve as a reliable biomarker for platinum -based therapy in ovarian cancer patients.
DOI: 10.6084/m9.figshare.29040377.v1
title: Expression Significance and Prognostic Value of GPR27 in Ovarian Cancer

description: This study explored the prognostic role of GPR27 and its predictive value to platinum-based therapy in ovarian cancer. A survival analysis of GPR27, and the therapeutic response to platinum in ovarian cancer was investigated using data from the cancer genome atlas (TCGA) and Gene Expression Omnibus (GEO) databases. GPR27 expression was assessed using reverse transcription-polymerase chain reaction (RT-PCR) and immunohistochemistry. Database analysis and RT-PCR revealed over-expression of GPR27 mRNA in ovarian cancer tissues compared to normal ovarian tissues. Ovarian cancer patients with up-regulated GPR27 transcription were associated with better overall survival and disease-free survival compared to those with downregulated GPR27 mRNA in the TCGA dataset and Kaplan-Meier plot database (<i>N</i> = 1656). GPR27 demonstrated good predictive value for pathological response in patients with ovarian cancer receiving platinum-based therapy. The predictive performance for 6-month relapse-free survival was higher in endometrioid ovarian cancer (AUC:0.804) than that in serous ovarian cancer. GPR27 protein levels were significantly up-regulated in ovarian cancer tissues compared with normal ovarian tissue, and high GPR27 protein expression correlated with early-stage TNM. ROC analysis revealed that the GPR27 protein, quantified by the immunohistochemistry score, effectively predicted the response to platinum-based therapy response with an AUC of 0.7479 in our cohort. GPR27 was up-regulated in ovarian cancer, compared with that of normal ovarian tissue, and was strongly correlated with survival outcomes and response to platinum-based therapy. GPR27 may serve as a reliable biomarker for platinum -based therapy in ovarian cancer patients.
DOI: 10.17630/764e7545-41b4-4a92-ab23-552a22050fe9
title: Data underpinning - 2′-Alkynylnucleotides: A sequence- and spin label-flexible strategy for EPR spectroscopy in DNA
DOI: 10.6084/m9.figshare.29040380
title: Prognostic Value of Inflammatory Markers in HBV-Related HCC After Hepatectomy Based on a Clinical Database

description: Hepatitis B virus (HBV) remains an important risk factor for hepatocellular carcinoma (HCC), and inflammation plays an essential role in tumor development. This study aimed to investigate the impact of inflammatory markers in the postoperative outcomes of patients with HBV-related HCC, providing valuable prognostic indicators after hepatectomy. We retrospectively analyzed 222 patients with HBV-related HCC after surgical resection. The ROC curve was used to calculate biomarker cutoff values. The Kaplan–Meier method was used to estimate overall survival (OS) and recurrence-free survival (RFS), and univariate and multivariate analyses were used to identify the prognostic factors. The Kaplan–Meier analysis revealed that patients with high albumin-bilirubin (ALBI) score, aspartate aminotransferase to platelet ratio index (APRI), and monocyte to lymphocyte ratio (MLR) had worse OS, while those with high ALBI score and MLR had shorter RFS. Multivariate Cox regression analysis identified alpha-fetoprotein &gt;400 ng/mL (hazard ratio [HR]: 2.447, 95% confidence interval [CI]: 1.273–4.706, <i>p</i> = 0.007), alanine aminotransferase (HR: 0.377, 95% CI: 0.171–0.834, <i>p</i> = 0.016), platelet to lymphocyte ratio (HR: 0.385, 95% CI: 0.196–0.755, <i>p</i> = 0.006), systemic inflammatory response index (HR: 1.844, 95% CI: 1.049–3.239, <i>p</i> = 0.033), ALBI score (HR: 1.808, 95% CI: 1.020–3.203, <i>p</i> = 0.043), APRI score (HR: 3.193, 95% CI: 1.662–6.137, <i>p</i> &lt; 0.001), tumor diameter (HR: 1.083, 95% CI: 1.012–1.160, <i>p</i> = 0.022), and portal vein tumor thrombosis (PVTT) (HR: 6.083, 95% CI: 2.774–13.338, <i>p</i> &lt; 0.0001) as independent predictors for OS. MLR (HR: 2.285, 95% CI: 1.290–4.048, <i>p</i> = 0.005) and PVTT (HR: 2.672, 95% CI: 1.280–5.579, <i>p</i> = 0.009) were confirmed as significant prognostic markers of RFS in patients with HBV-related HCC. ALBI score, APRI, and MLR are effective prognostic predictors in patients with HBV-related HCC after curative resection. Close monitoring and adjuvant therapies should be considered for high-risk patients.
DOI: 10.6084/m9.figshare.29040380.v1
title: Prognostic Value of Inflammatory Markers in HBV-Related HCC After Hepatectomy Based on a Clinical Database

description: Hepatitis B virus (HBV) remains an important risk factor for hepatocellular carcinoma (HCC), and inflammation plays an essential role in tumor development. This study aimed to investigate the impact of inflammatory markers in the postoperative outcomes of patients with HBV-related HCC, providing valuable prognostic indicators after hepatectomy. We retrospectively analyzed 222 patients with HBV-related HCC after surgical resection. The ROC curve was used to calculate biomarker cutoff values. The Kaplan–Meier method was used to estimate overall survival (OS) and recurrence-free survival (RFS), and univariate and multivariate analyses were used to identify the prognostic factors. The Kaplan–Meier analysis revealed that patients with high albumin-bilirubin (ALBI) score, aspartate aminotransferase to platelet ratio index (APRI), and monocyte to lymphocyte ratio (MLR) had worse OS, while those with high ALBI score and MLR had shorter RFS. Multivariate Cox regression analysis identified alpha-fetoprotein &gt;400 ng/mL (hazard ratio [HR]: 2.447, 95% confidence interval [CI]: 1.273–4.706, <i>p</i> = 0.007), alanine aminotransferase (HR: 0.377, 95% CI: 0.171–0.834, <i>p</i> = 0.016), platelet to lymphocyte ratio (HR: 0.385, 95% CI: 0.196–0.755, <i>p</i> = 0.006), systemic inflammatory response index (HR: 1.844, 95% CI: 1.049–3.239, <i>p</i> = 0.033), ALBI score (HR: 1.808, 95% CI: 1.020–3.203, <i>p</i> = 0.043), APRI score (HR: 3.193, 95% CI: 1.662–6.137, <i>p</i> &lt; 0.001), tumor diameter (HR: 1.083, 95% CI: 1.012–1.160, <i>p</i> = 0.022), and portal vein tumor thrombosis (PVTT) (HR: 6.083, 95% CI: 2.774–13.338, <i>p</i> &lt; 0.0001) as independent predictors for OS. MLR (HR: 2.285, 95% CI: 1.290–4.048, <i>p</i> = 0.005) and PVTT (HR: 2.672, 95% CI: 1.280–5.579, <i>p</i> = 0.009) were confirmed as significant prognostic markers of RFS in patients with HBV-related HCC. ALBI score, APRI, and MLR are effective prognostic predictors in patients with HBV-related HCC after curative resection. Close monitoring and adjuvant therapies should be considered for high-risk patients.
DOI: 10.6084/m9.figshare.28169634
title: Effect of Prior Bariatric Surgery on the Outcomes of Joint Arthroplasty: A Systematic Review and Meta-Analysis

description: Obesity is a risk factor for joint arthroplasty complications. With this systematic review and meta-analysis, we assessed whether a positive history of bariatric surgery influences postoperative outcomes in patients undergoing various types of joint arthroplasty. We conducted a comprehensive search database such as Scopus, PubMed, Medline Ovid, CNKI, and CENTRAL for studies comparing outcomes between patients undergoing arthroplasty with and without a history of bariatric surgery. We extracted data on short-term medical complications, venous thromboembolism (VTE), periprosthetic infections, superficial wound infections, hospital stay length, and operative time. We used the data to conduct meta-analyses using random-effects models and subgroup analyses based on the type of arthroplasty. Overall, 15 studies with nearly 150,000 participants were included. The analysis showed that prior bariatric surgery did not significantly affect overall medical complications post-arthroplasty, with OR of 0.968 (95%CI, 0.706-1.327). For VTE, the results similarly indicated no substantial difference, with an OR of 0.912 (95%CI, 0.644-1.291). In assessing periprosthetic infections, the OR was 0.754 (95%CI, 0.535-1.064), showing comparable rates between patients with and without a history of bariatric surgery. Regarding superficial wound infections, the analysis produced an OR of 2.390 (95%CI, 0.723-7.897), indicating variability but not statistical significance. Hospital stay length was reduced in patients with a history of bariatric surgery, reflected by SMD of −0.113 (95%CI, −0.221 to −0.005). Lastly, operative time also showed a significant reduction, with an SMD of −0.462 (95%CI, −0.865 to −0.059). Prior bariatric surgery does not reduce the risk of short-term complications post-arthroplasty, but it seems to reduce the hospital stay length and operative time. The effects vary significantly across different types of joint arthroplasty, suggesting a need for tailored preoperative assessments and care protocols. This systematic review and meta-analysis was registered at PROSPERO, with the number: CRD42024539052
DOI: 10.6084/m9.figshare.28169634.v1
title: Effect of Prior Bariatric Surgery on the Outcomes of Joint Arthroplasty: A Systematic Review and Meta-Analysis

description: Obesity is a risk factor for joint arthroplasty complications. With this systematic review and meta-analysis, we assessed whether a positive history of bariatric surgery influences postoperative outcomes in patients undergoing various types of joint arthroplasty. We conducted a comprehensive search database such as Scopus, PubMed, Medline Ovid, CNKI, and CENTRAL for studies comparing outcomes between patients undergoing arthroplasty with and without a history of bariatric surgery. We extracted data on short-term medical complications, venous thromboembolism (VTE), periprosthetic infections, superficial wound infections, hospital stay length, and operative time. We used the data to conduct meta-analyses using random-effects models and subgroup analyses based on the type of arthroplasty. Overall, 15 studies with nearly 150,000 participants were included. The analysis showed that prior bariatric surgery did not significantly affect overall medical complications post-arthroplasty, with OR of 0.968 (95%CI, 0.706-1.327). For VTE, the results similarly indicated no substantial difference, with an OR of 0.912 (95%CI, 0.644-1.291). In assessing periprosthetic infections, the OR was 0.754 (95%CI, 0.535-1.064), showing comparable rates between patients with and without a history of bariatric surgery. Regarding superficial wound infections, the analysis produced an OR of 2.390 (95%CI, 0.723-7.897), indicating variability but not statistical significance. Hospital stay length was reduced in patients with a history of bariatric surgery, reflected by SMD of −0.113 (95%CI, −0.221 to −0.005). Lastly, operative time also showed a significant reduction, with an SMD of −0.462 (95%CI, −0.865 to −0.059). Prior bariatric surgery does not reduce the risk of short-term complications post-arthroplasty, but it seems to reduce the hospital stay length and operative time. The effects vary significantly across different types of joint arthroplasty, suggesting a need for tailored preoperative assessments and care protocols. This systematic review and meta-analysis was registered at PROSPERO, with the number: CRD42024539052
DOI: 10.6084/m9.figshare.30022648
title: Feasibility and Prognostic Analysis of Neoadjuvant Therapy Followed by Breast-Conserving Surgery for Invasive Ductal Carcinoma Combined with Ductal Carcinoma in Situ

description: This study aim to investigate the oncological safety of neoadjuvant therapy (NAT) followed by breast-conserving surgery (BCS) for invasive ductal carcinoma (IDC) patients with the presence of ductal carcinoma <i>in situ</i> (DCIS) on pre-NAT biopsy. The data of women with IDC who underwent radical surgery between January 2013 and December 2021 were retrospectively reviewed from two institutions. The study endpoints were 5-year disease-free survival (DFS) and local recurrence-fee survival (LRFS). Overall, 994 eligible patients were enrolled. Patients with IDC with DCIS (<i>n</i> = 277) and patients undergoing BCS (<i>n</i> = 285) were selected separately for prognostic analysis. For patients with IDC with DCIS, the 5-year DFS (<i>p</i> = 0.517) and 5-year LRFS (<i>p</i> = 0.397) rates of the patients undergoing BCS were similar to those of patients undergoing mastectomy after propensity score matching. In addition, the 285 patients who underwent BCS were divided into the IDC + DCIS and IDC groups. The 5-year DFS (<i>p</i> = 0.394) and 5-year LRFS (<i>p</i> = 0.341) rates were similar between the IDC and IDC + DCIS groups. NAT followed by BCS combined with adjuvant radiotherapy is a safe and feasible treatment option in patients with IDC with DCIS under the premise of strict adherence to the surgical indications and adequate incision margins.