cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/8s67xk4sxx.1
title: Clinical predictors and immuno-inflammatory indices for sepsis risk after ureteroscopic lithotripsy

description: This dataset contains de-identified clinical records of patients who underwent ureteroscopic lithotripsy (URSL) at Shanghai Tenth People‘s Hospital] between January 2023 and June 2025. The primary objective is to support the development and validation of predictive models for postoperative sepsis, with a specific focus on evaluating the incremental value of a novel Systemic Immune-Inflammatory Complex Index (SIICI) against established indices (SII, SIRI, PIV).

The dataset comprises preoperative, intraoperative, and postoperative variables for 803 patients, including [57] cases diagnosed with sepsis according to Sepsis-3 criteria (qSOFA ≥2) and [746] non-sepsis controls.

**Key variables include:**

* **Demographics:** Age, sex, BMI, comorbidities (hypertension, diabetes).

* **Preoperative Laboratory Tests:** C-reactive protein (CRP), white blood cell count (WBC), neutrophil, lymphocyte, monocyte, platelet counts, albumin, creatinine, uric acid.

* **Calculated Immuno-inflammatory Indices:** SIICI, SII, SIRI, PIV (formulas provided in the associated publication).

* **Surgical & Stone Characteristics:** Operation time &gt;60 min, hydronephrosis, maximum stone diameter &gt;1.5 cm.

* **Urinalysis & Microbiology:** Urine nitrite, leukocyte esterase, urine WBC count, urine culture status.

* **Outcome:** Postoperative sepsis (binary: Yes/No).

The unique value of this dataset lies in the preoperative calculation of the SIICI index, allowing for head-to-head comparison with other indices for early sepsis risk stratification. It is particularly valuable for researchers in urology, critical care, and clinical informatics working on predictive analytics, biomarker evaluation, and clinical decision support tool development.
DOI: 10.17632/8fmyknfd7v
title: FRMC Study: Anonymised Survey Data and Reproducible Analysis Code

description: This dataset contains anonymised survey responses and the full reproducible analysis code for the study “Future Rewards Maximize Curiosity (FRMC): Value Orientations and Future Reward Expectation Value (FREV) as drivers of sustained engagement under negative gameplay experiences.” The package includes (i) cleaned participant-level data, (ii) code to reproduce all reported analyses, tables, and figures, and (iii) supporting documentation (codebook/README). All personal identifiers have been removed; variables are described in the accompanying codebook. The dataset is shared for peer review and replication purposes.
DOI: 10.17632/8fmyknfd7v.1
title: FRMC Study: Anonymised Survey Data and Reproducible Analysis Code

description: This dataset contains anonymised survey responses and the full reproducible analysis code for the study “Future Rewards Maximize Curiosity (FRMC): Value Orientations and Future Reward Expectation Value (FREV) as drivers of sustained engagement under negative gameplay experiences.” The package includes (i) cleaned participant-level data, (ii) code to reproduce all reported analyses, tables, and figures, and (iii) supporting documentation (codebook/README). All personal identifiers have been removed; variables are described in the accompanying codebook. The dataset is shared for peer review and replication purposes.
DOI: 10.17632/hxdhnmv4mr
title: Open-Source Energy Profiling Platform for IoT & Edge-ML Devices

description: This repository contains the hardware design files, firmware, and validation data for a low-cost, real-time energy measurement system designed for Internet of Things (IoT) and Edge Machine Learning (Edge-ML) applications. The platform consists of two integrated subsystems:1. Measurement System (Profiler)Architecture: Based on the ESP32-S3 and INA226 sensors, enhanced with an external 16-bit ADC (ADS1115) and precision voltage reference for superior signal stability.Dual-Range Input:Low-Range: Optimized for sleep currents and logic levels (up to 15 V). Includes a voltage stabilization circuit for the DUT.High-Range: Supports higher power loads (up to 30 V) with current sensing capabilities up to 8 A (peak/burst) and 3 A (continuous).Features: Hardware synchronization triggers, UART metadata logging, and dual NTC temperature monitoring (ambient + device). Data is stored locally on microSD cards.2. Validation Node (formerly Test System)An autonomous, battery-powered IoT testbed designed to generate reproducible dynamic workloads.Features a user interface (OLED + Rotary Encoder) to configure computational intensity.Implements a Linear Regression training task (Red Wine Quality dataset) to validate the profiling system's ability to correlate energy consumption with algorithmic performance ($R^2$, MSE).Repository Contents:Hardware: Schematic diagrams, PCB layouts (Autodesk Fusion 360), and Gerber files.BOM: Complete Bill of Materials with supplier links (focus on low-cost accessibility).Firmware: Source code for both the Measurement System and the Validation Node (Arduino/C++).Data: Raw validation datasets validating the system's linearity and dynamic response.

The second system is an IoT test module designed to validate the performance of the measurement and profiling system. This module communicates and synchronizes with the measurement unit, enabling the profiling of energy consumption according to the computational tasks performed. As an example, a linear regression algorithm was implemented to evaluate energy behavior during the execution of processes with varying computational complexity.

Both systems can be assembled using low-cost components and are suitable for energy consumption characterization in open hardware-based IoT devices. The accompanying project files include the complete list of required components with supplier links, the schematic diagrams and PCB designs developed in Autodesk Fusion 360, the firmware for both systems, and the data files obtained during a test of the IoT system running the linear regression algorithm, used to validate the measurement platform.
DOI: 10.17632/hxdhnmv4mr.3
title: Open-Source Energy Profiling Platform for IoT & Edge-ML Devices

description: This repository contains the hardware design files, firmware, and validation data for a low-cost, real-time energy measurement system designed for Internet of Things (IoT) and Edge Machine Learning (Edge-ML) applications. The platform consists of two integrated subsystems:1. Measurement System (Profiler)Architecture: Based on the ESP32-S3 and INA226 sensors, enhanced with an external 16-bit ADC (ADS1115) and precision voltage reference for superior signal stability.Dual-Range Input:Low-Range: Optimized for sleep currents and logic levels (up to 15 V). Includes a voltage stabilization circuit for the DUT.High-Range: Supports higher power loads (up to 30 V) with current sensing capabilities up to 8 A (peak/burst) and 3 A (continuous).Features: Hardware synchronization triggers, UART metadata logging, and dual NTC temperature monitoring (ambient + device). Data is stored locally on microSD cards.2. Validation Node (formerly Test System)An autonomous, battery-powered IoT testbed designed to generate reproducible dynamic workloads.Features a user interface (OLED + Rotary Encoder) to configure computational intensity.Implements a Linear Regression training task (Red Wine Quality dataset) to validate the profiling system's ability to correlate energy consumption with algorithmic performance ($R^2$, MSE).Repository Contents:Hardware: Schematic diagrams, PCB layouts (Autodesk Fusion 360), and Gerber files.BOM: Complete Bill of Materials with supplier links (focus on low-cost accessibility).Firmware: Source code for both the Measurement System and the Validation Node (Arduino/C++).Data: Raw validation datasets validating the system's linearity and dynamic response.

The second system is an IoT test module designed to validate the performance of the measurement and profiling system. This module communicates and synchronizes with the measurement unit, enabling the profiling of energy consumption according to the computational tasks performed. As an example, a linear regression algorithm was implemented to evaluate energy behavior during the execution of processes with varying computational complexity.

Both systems can be assembled using low-cost components and are suitable for energy consumption characterization in open hardware-based IoT devices. The accompanying project files include the complete list of required components with supplier links, the schematic diagrams and PCB designs developed in Autodesk Fusion 360, the firmware for both systems, and the data files obtained during a test of the IoT system running the linear regression algorithm, used to validate the measurement platform.
DOI: 10.15468/dl.ek2brv
title: Occurrence Download

description: A dataset containing 175685 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (Malaysia, Brunei Darussalam, Cambodia, Timor-Leste, Indonesia, Lao People’s Democratic Republic, Myanmar, Philippines, Singapore, Viet Nam, Thailand, Papua New Guinea)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Polypodiopsida",
 "Year 1000-2026"
 ]
}

 The dataset includes 175685 records from 156 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001985-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/z9x6n8676b.1
title: Replication Folder for "Impact of pension insurance and health insurance on pension savings"

description: This replication folder contains the necessary codes to replicate the quantitative results of the paper.
DOI: 10.17632/xxxz27j2hc
title: Original data for "Evidence for weakened solar activity found in the Chang’E-5 and Chang’E-6 lunar soils"

description: Original data for "Evidence for weakened solar activity found in the Chang’E-5 and Chang’E-6 lunar soils"
DOI: 10.17632/xxxz27j2hc.1
title: Original data for "Evidence for weakened solar activity found in the Chang’E-5 and Chang’E-6 lunar soils"

description: Original data for "Evidence for weakened solar activity found in the Chang’E-5 and Chang’E-6 lunar soils"
DOI: 10.17632/7gh4jknpw8
title: Biochar exacerbate nitrogen

description: Biochar exacerbate nitrogen loss in drought-affected soil with green manure application
DOI: 10.17632/7gh4jknpw8.1
title: Biochar exacerbate nitrogen

description: Biochar exacerbate nitrogen loss in drought-affected soil with green manure application
DOI: 10.17632/xwpz76cf8g
title: Raw data of Technical and economic feasibility of composting recalcitrant olive oil industry wastes for the production of organic amendments and bio-based fertilisers (Torrés-Ginés et al.)

description: Raw data of Technical and economic feasibility of composting recalcitrant olive oil industry wastes for the production of organic amendments and bio-based fertilisers (Torrés-Ginés et al.). It includes composting data like temperature profiles, pH, moisture, EC, TOC, NT, TOC/TN, mineral nitrogen, germination index, organic matter, WSC, WSCH, WSPH, fats, PAH and the economic estimation of nutrient content
DOI: 10.17632/xwpz76cf8g.1
title: Raw data of Technical and economic feasibility of composting recalcitrant olive oil industry wastes for the production of organic amendments and bio-based fertilisers (Torrés-Ginés et al.)

description: Raw data of Technical and economic feasibility of composting recalcitrant olive oil industry wastes for the production of organic amendments and bio-based fertilisers (Torrés-Ginés et al.). It includes composting data like temperature profiles, pH, moisture, EC, TOC, NT, TOC/TN, mineral nitrogen, germination index, organic matter, WSC, WSCH, WSPH, fats, PAH and the economic estimation of nutrient content
DOI: 10.5281/zenodo.18530983
title: SPT_SWSSB_data
DOI: 10.17632/j8f8wxgfsb.1
title: Fine-tuning ERK activity enables proliferation-differentiation balance during lineage specification

description: The dataset includes several folders containing all raw data and supporting materials associated with the manuscript. The folders entitled “Figure” and “Supplement Figure” contain the raw data used to generate all main and supplementary figures, respectively. Subfolders labeled Figure 1–Figure 5 and Figure S1–Figure S5 correspond to individual figures in the manuscript and are organized by figure panels. These folders include Excel files with quantitative raw data, as well as original immunofluorescence images and western blot images used for figure preparation. The “Supplementary Video” folder contains three subfolders (Video S1–S3) with the corresponding video files. The “Figure R data” folder provides additional supporting data, including karyotype analyses and sequencing validation results for the cell lines used in this study. The file “material and method list.xlsx” contains primer information, and the “BioRender license” folder includes materials related to schematic figures created using BioRender.
Within the Figure and Supplement Figure directories, some datasets are provided in MATLAB .mat format, representing quantitative measurements derived from image analyses. Corresponding MATLAB scripts (labeled as “script”) are included to facilitate data visualization and reproduction of the published figures. Users can reproduce the reported results by running these scripts in MATLAB after specifying the correct data file paths. For example, Figure 1A can be reproduced using the file PSC_TBXT_ERK(data).mat together with the script Heatmap_for_signal(script).m after updating the file path accordingly.
DOI: 10.17632/m2g7sv5w77
title: The Great Rewiring: How Generative AI Reshapes the Global Robotics Ecosystem from Vertical Silos to Multivocal Platforms

description: The processed dataset (alliance network edge lists) and the Python source code used for data cleaning and network construction
DOI: 10.17632/m2g7sv5w77.1
title: The Great Rewiring: How Generative AI Reshapes the Global Robotics Ecosystem from Vertical Silos to Multivocal Platforms

description: The processed dataset (alliance network edge lists) and the Python source code used for data cleaning and network construction
DOI: 10.17632/3t93twk9ht
title: Dataset for "Widespread spring discharge drives major water-salt-heat fluxes in salt marshes"

description: This Dataset includes two sheets, showing the properties of all springs (position, area, temperature difference, and elevation) recognized by UAV-based thermal infrared imaging during winter 2023 and summer 2024, respectively. Data were collected from six tidal creeks along the muddy coast of Jiangsu Province, East China, including Dafeng Port (DFP), North Chuandong 1 and 2 (NCD1 and NCD2), South Chuandong (SCD), and Jianggang 1 and 2 (JG1 and JG2).
DOI: 10.17632/3t93twk9ht.1
title: Dataset for "Widespread spring discharge drives major water-salt-heat fluxes in salt marshes"

description: This Dataset includes two sheets, showing the properties of all springs (position, area, temperature difference, and elevation) recognized by UAV-based thermal infrared imaging during winter 2023 and summer 2024, respectively. Data were collected from six tidal creeks along the muddy coast of Jiangsu Province, East China, including Dafeng Port (DFP), North Chuandong 1 and 2 (NCD1 and NCD2), South Chuandong (SCD), and Jianggang 1 and 2 (JG1 and JG2).
DOI: 10.17632/pjf2tdm2tf
title: Decision Transformer ablation study dataset and figures

description: Intermediate datasets, figures and interactive plotly figures in html format for the different ablation studies carried out in the context of "A Diagnostic Framework for Auditing Decision Logic in Transformer-Based Portfolio Allocation", including but not limited to:

- All Figures in the main manuscript, appendices and supplementary materials.;
- Additional figures on risk-free asset (CASH) importance and attribution
- Selected interactive plots in HTML to allow in-depth investigation;
- Intermediate data in CSV format of feature significance, attributions, Kruskal-Wallis computations, Kendall's Tau computations, summary tables and significance stats both globally and per market regime.
- Pickled results of failure mode comparison between the best and worst performing models.
DOI: 10.60707/95bp-6f60
title: Analysis of sample OREX-800045-103 by scanning electron microscopy (SEM) at Curtin University, Western Australia, including SE and BSE imaging, EDS element maps, and EBSD maps and data.
DOI: 10.17632/pjf2tdm2tf.1
title: Decision Transformer ablation study dataset and figures

description: Intermediate datasets, figures and interactive plotly figures in html format for the different ablation studies carried out in the context of "A Diagnostic Framework for Auditing Decision Logic in Transformer-Based Portfolio Allocation", including but not limited to:

- All Figures in the main manuscript, appendices and supplementary materials.;
- Additional figures on risk-free asset (CASH) importance and attribution
- Selected interactive plots in HTML to allow in-depth investigation;
- Intermediate data in CSV format of feature significance, attributions, Kruskal-Wallis computations, Kendall's Tau computations, summary tables and significance stats both globally and per market regime.
- Pickled results of failure mode comparison between the best and worst performing models.
DOI: 10.60707/tqj3-pt76
title: Analysis of sample OREX-800045-103 by scanning electron microscopy (SEM) at Curtin University, Western Australia, including SE and BSE imaging, EDS element maps, and EBSD maps and data.
DOI: 10.17632/t6zxmpwmmd
title: Impact of Intraoperative Binaural Beats on remifentanil requirement during remimazolam-based general anesthesia: a randomized controlled trial

description: Purpose: Binaural beats (BB) may influence anxiety and anesthetic requirements through brainwave entrainment. This study investigated the effect of intraoperative BB on remifentanil requirements during remimazolam-based general anesthesia maintenance 
Methods: In a randomized, prospective, single-center study, Seventy-two patients were randomly allocated to two groups: the BB group (B group, n=36) or control group (C group, n=36). The B group listened to BB (4-Hz frequency difference) intraoperatively, while the control group did not. The primary outcome was remifentanil dosage during anesthesia. Secondary outcomes included remimazolam dosage per hour per kg, hemodynamic stability, postoperative pain scores, and EEG spectral analysis. Postoperative pain scores were assessed using the numerical rating scale (NRS), and time-normalized AUC values (AUC per hour) over the first 24 postoperative hours were calculated.
Results: The B group required significantly less remifentanil dosage (8.52 ± 3.39 vs. 11.48 ± 3.68 µg/kg/h, P&lt;0.001). Remimazolam dosage was also lower in the B group (1.01 ± 0.17 vs. 1.11 ± 0.22 mg/kg/h, P=0.031). The incidence of hypotension was lower in the B group (11% vs. 33%, P=0.047). No significant differences were observed in most EEG spectral bands. Time-normalized postoperative pain burden, expressed as NRS AUC per hour, was significantly lower in the BB group both at rest (2.6 ± 1.0 vs. 3.4 ± 1.0, P = 0.001) and during coughing (2.8 ± 1.0 vs. 3.7 ± 1.2, P &lt; 0.001).
Conclusion: Intraoperative BB were associated with reduced remifentanil requirements and improved hemodynamic stability in patients undergoing remimazolam-based general anesthesia. While EEG changes were limited, these findings suggest that binaural beats may serve as a useful adjunct during anesthesia maintenance.
DOI: 10.17632/t6zxmpwmmd.2
title: Impact of Intraoperative Binaural Beats on remifentanil requirement during remimazolam-based general anesthesia: a randomized controlled trial

description: Purpose: Binaural beats (BB) may influence anxiety and anesthetic requirements through brainwave entrainment. This study investigated the effect of intraoperative BB on remifentanil requirements during remimazolam-based general anesthesia maintenance 
Methods: In a randomized, prospective, single-center study, Seventy-two patients were randomly allocated to two groups: the BB group (B group, n=36) or control group (C group, n=36). The B group listened to BB (4-Hz frequency difference) intraoperatively, while the control group did not. The primary outcome was remifentanil dosage during anesthesia. Secondary outcomes included remimazolam dosage per hour per kg, hemodynamic stability, postoperative pain scores, and EEG spectral analysis. Postoperative pain scores were assessed using the numerical rating scale (NRS), and time-normalized AUC values (AUC per hour) over the first 24 postoperative hours were calculated.
Results: The B group required significantly less remifentanil dosage (8.52 ± 3.39 vs. 11.48 ± 3.68 µg/kg/h, P&lt;0.001). Remimazolam dosage was also lower in the B group (1.01 ± 0.17 vs. 1.11 ± 0.22 mg/kg/h, P=0.031). The incidence of hypotension was lower in the B group (11% vs. 33%, P=0.047). No significant differences were observed in most EEG spectral bands. Time-normalized postoperative pain burden, expressed as NRS AUC per hour, was significantly lower in the BB group both at rest (2.6 ± 1.0 vs. 3.4 ± 1.0, P = 0.001) and during coughing (2.8 ± 1.0 vs. 3.7 ± 1.2, P &lt; 0.001).
Conclusion: Intraoperative BB were associated with reduced remifentanil requirements and improved hemodynamic stability in patients undergoing remimazolam-based general anesthesia. While EEG changes were limited, these findings suggest that binaural beats may serve as a useful adjunct during anesthesia maintenance.
DOI: 10.17632/yk26scykws
title: Excel Sheet Updated

description: Hoja de Excel con los resultados de la evaluación de LLMs vs URLs. 

Juan Carlos Andújar Romera.
Trabajo Fin de Grado Ingeniería de la Ciberseguridad URJC.
DOI: 10.60707/rvz8-vw77
title: Analysis of sample OREX-800045-103 by scanning electron microscopy (SEM) at Curtin University, Western Australia, including SE and BSE imaging, EDS element maps, and EBSD maps and data.
DOI: 10.17632/yk26scykws.1
title: Excel Sheet Updated

description: Hoja de Excel con los resultados de la evaluación de LLMs vs URLs. 

Juan Carlos Andújar Romera.
Trabajo Fin de Grado Ingeniería de la Ciberseguridad URJC.
DOI: 10.60707/yzch-v066
title: Analysis of sample OREX-800045-103 by scanning electron microscopy (SEM) at Curtin University, Western Australia, including SE and BSE imaging, EDS element maps, and EBSD maps and data.
DOI: 10.17632/vndwhf4cwk
title: Spatial heterogeneity of bioavailable phosphorus in mangrove soils and the role of glomalin-related soil protein in phosphorus sequestration
DOI: 10.17632/vndwhf4cwk.1
title: Spatial heterogeneity of bioavailable phosphorus in mangrove soils and the role of glomalin-related soil protein in phosphorus sequestration
DOI: 10.15468/dl.rfvujp
title: Occurrence Download

description: A dataset containing 24117 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Amaranthus deflexus"
 ]
}

 The dataset includes 24117 records from 595 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002005-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.p7hszy
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Campanula medium L.",
 "HasCoordinate is true",
 "Country is Japan",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0188244-220831081235567/datasets/export for details.