cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.57760/sciencedb.j00186.00192
title: Cone-beam computed tomography noise reduction method based on U-Net with convolutional block attention module in proton therapy
title: Cone-beam computed tomography noise reduction method based on U-Net with convolutional block attention module in proton therapy

description: those is the corresponding data of "Cone-beam computed tomography noise reduction method based on U-Net with convolutional block attention module in proton therapy".This data consist of network weight, analysis matlab data of CBAM-N-Net, and include the original picture of the paper. Network weight is pytorch structure that can directly be imported to generate whole network structure. And the analysis mat data is CT,CBCT,SCT data(U-Net, CBAM-U-Net) for dose calculation analysis which be saved as matlab files and can directly be imported in matRad. The matRad zip file is also uploaded in the files that need to be extracted in the matlab code list.
description: those is the corresponding data of "Cone-beam computed tomography noise reduction method based on U-Net with convolutional block attention module in proton therapy".This data consist of network weight, analysis matlab data of CBAM-N-Net, and include the original picture of the paper. Network weight is pytorch structure that can directly be imported to generate whole network structure. And the analysis mat data is CT,CBCT,SCT data(U-Net, CBAM-U-Net) for dose calculation analysis which be saved as matlab files and can directly be imported in matRad. The matRad zip file is also uploaded in the files that need to be extracted in the matlab code list.
DOI: 10.57760/sciencedb.09268
title: A dataset of assessment of the AR-based DSS project
title: A dataset of assessment of the AR-based DSS project

description: This file contains the data on the task completion time, error rate and usability scale evaluated when the operators used the AR-assisted DSS to complete their tasks.
description: This file contains the data on the task completion time, error rate and usability scale evaluated when the operators used the AR-assisted DSS to complete their tasks.
DOI: 10.57760/sciencedb.09271
title: Supplementary materials from: In silico design and evaluation of two distinct multi-epitope vaccines against bovine viral diarrhea virus
title: Supplementary materials from: In silico design and evaluation of two distinct multi-epitope vaccines against bovine viral diarrhea virus

description: Figure S1. E0 protein sequence alignment and epitope conservation analysis. Figure S2. E2 protein sequence alignment and epitope conservation analysis.
description: Figure S1. E0 protein sequence alignment and epitope conservation analysis. Figure S2. E2 protein sequence alignment and epitope conservation analysis.
DOI: 10.57760/sciencedb.j00133.00277
title: Paper Mill Dataset
title: 论文工厂数据集

description: This study created a new dataset that includes both normal and factory papers with similar themes. The author hopes to build a classification model on this dataset that is not affected by the topic of the paper and can identify potential features of the paper factory in terms of writing or article structure. This study collected all papers clearly marked as paper factories from withdrawal observation data, and as of December 31, 2022, a total of 1910 papers were obtained. Multiple open access platforms were used to supplement the metadata of the papers, including titles, authors, publication dates, and original DOIs. On this basis, the original PDFs (pre withdrawal published texts) of these papers were also collected using open access platforms. In the end, this study successfully obtained 1535 PDFs. In order to collect normal papers similar to existing paper factories, this study used PubMed The similar paper function provided by websites such as ConnectPapers allows for the collection of at least one unreleased paper on a similar topic as a normal paper for each factory paper, resulting in a total of 2398 normal papers found. Divide the dataset into training, validation, and testing sets in a 7:1.5:1.5 ratio. This article develops an automatic parsing tool for PDF files, which can parse the most common paper manuscript submission format PDF, analyze the byte stream of the file, read the corresponding text in structural order, and identify the text content of the paper title, abstract, and main body. 
description: This study created a new dataset that includes both normal and factory papers with similar themes. The author hopes to build a classification model on this dataset that is not affected by the topic of the paper and can identify potential features of the paper factory in terms of writing or article structure. This study collected all papers clearly marked as paper factories from withdrawal observation data, and as of December 31, 2022, a total of 1910 papers were obtained. Multiple open access platforms were used to supplement the metadata of the papers, including titles, authors, publication dates, and original DOIs. On this basis, the original PDFs (pre withdrawal published texts) of these papers were also collected using open access platforms. In the end, this study successfully obtained 1535 PDFs. In order to collect normal papers similar to existing paper factories, this study used PubMed The similar paper function provided by websites such as ConnectPapers allows for the collection of at least one unreleased paper on a similar topic as a normal paper for each factory paper, resulting in a total of 2398 normal papers found. Divide the dataset into training, validation, and testing sets in a 7:1.5:1.5 ratio. This article develops an automatic parsing tool for PDF files, which can parse the most common paper manuscript submission format PDF, analyze the byte stream of the file, read the corresponding text in structural order, and identify the text content of the paper title, abstract, and main body.
DOI: 10.57760/sciencedb.j00186.00203
title: Neutron resonance imaging dataset of Au, Ag, W, and other elements
title: Neutron resonance imaging dataset of Au, Ag, W, and other elements

description: we report the development of a 10B-doped MCP detector system and the neutron resonance imaging experiments at the Back-n neutron source. Individual heavy elements such as gold, silver, tungsten, and indium can be easily identified in the transmission images through their characteristic resonance peaks in the 1-100 eV energy range, and more difficult medium-weight elements such as iron, copper, and aluminum with resonance peaks in the 1-100 keV energy range can also be identified.
description: we report the development of a 10B-doped MCP detector system and the neutron resonance imaging experiments at the Back-n neutron source. Individual heavy elements such as gold, silver, tungsten, and indium can be easily identified in the transmission images through their characteristic resonance peaks in the 1-100 eV energy range, and more difficult medium-weight elements such as iron, copper, and aluminum with resonance peaks in the 1-100 keV energy range can also be identified.
DOI: 10.57760/sciencedb.09296
title: SEM Images, Raman, FTIR and XRD of PPy flowers
title: SEM Images, Raman, FTIR and XRD of PPy flowers

description: SEM images of PPy flowers along witth raw files of RAman, FTIR and XRD data.
description: SEM images of PPy flowers along witth raw files of RAman, FTIR and XRD data.
DOI: 10.57760/sciencedb.psych.00150
title: The cognitive mechanisms underlying the positive reactivity effect to recognition memory
title: 词汇再认记忆积极反应性效应的认知行为机制

description: Recently, a large number of studies have found that requiring learners to make learning judgments (JOLs) while learning can reactively change an individual's memory of the learned content, known as the reactivity effect. In pure list vocabulary learning tasks, doing JOL can improve vocabulary recognition memory and exhibit the positive reactivity effect. This study designs four studies to compare the cognitive mechanisms of the positive reactivity effect of vocabulary recognition memory (learning engagement enhancement theory vs. strategy change theory). Experiment 1 explores whether positive reactivity effects have transferability using the paradigm of interlacing JOL; Experiments 2-4 used different paradigms (decentralized learning paradigm, generative effect paradigm, and time-saving paradigm) to regulate different dimensions of learning engagement. The results indicate that (1) the positive reactivity effect induced by JOL is not transferable, and (2) changing learning engagement can regulate the positive reactivity effect. The above results provide experimental evidence that the theory of learning engagement enhancement may be a cognitive mechanism underlying the positive reactive effect of vocabulary recognition memory. 
description: Recently, a large number of studies have found that requiring learners to make learning judgments (JOLs) while learning can reactively change an individual's memory of the learned content, known as the reactivity effect. In pure list vocabulary learning tasks, doing JOL can improve vocabulary recognition memory and exhibit the positive reactivity effect. This study designs four studies to compare the cognitive mechanisms of the positive reactivity effect of vocabulary recognition memory (learning engagement enhancement theory vs. strategy change theory). Experiment 1 explores whether positive reactivity effects have transferability using the paradigm of interlacing JOL; Experiments 2-4 used different paradigms (decentralized learning paradigm, generative effect paradigm, and time-saving paradigm) to regulate different dimensions of learning engagement. The results indicate that (1) the positive reactivity effect induced by JOL is not transferable, and (2) changing learning engagement can regulate the positive reactivity effect. The above results provide experimental evidence that the theory of learning engagement enhancement may be a cognitive mechanism underlying the positive reactive effect of vocabulary recognition memory.
DOI: 10.57760/sciencedb.09295
title: Solidification and Differentiation of a Mushy Lunar Magma Ocean: 3D Numerical Modeling
title: Solidification and Differentiation of a Mushy Lunar Magma Ocean: 3D Numerical Modeling

description: Data used to plot Figures in the manuscript
description: Data used to plot Figures in the manuscript
DOI: 10.57760/sciencedb.09312
title: Raw datasets of the response of 10B-doped MCP to neutrons from eV to MeV
title: Raw datasets of the response of 10B-doped MCP to neutrons from eV to MeV

description: B-MCP with 10 mol% 10B was tested for its response to wide-energy neutrons from eV to MeV at the Back-n white neutron source at the China Spallation Neutron Source. The experiment used the common electronics and data acquisition systems of the Back-n facility. The output signals of the preamplifier were digitized by the readout electronics system with a 12 bit folding-ADC and a 1 GHz sampling rate. The system was triggered by the T0 signal from the proton beam monitor, and the threshold was set to 14.6 mV to filter the electronic noise. The sampling duration was set from 2 μs before the T0 trigger to 8 μ s after the T0 trigger, and the waveform of each neutron event was recorded. Because it is difficult for MCPs to distinguish between dark counts and neutron events, the B-MCP uses a voltage of -1750 V to keepthe dark counts below 0.1 cps/cm2. Each measurement took 10800 s to obtain accurate statistics. The data analysis was performed using the ROOT program developed by CERN.
description: B-MCP with 10 mol% 10B was tested for its response to wide-energy neutrons from eV to MeV at the Back-n white neutron source at the China Spallation Neutron Source. The experiment used the common electronics and data acquisition systems of the Back-n facility. The output signals of the preamplifier were digitized by the readout electronics system with a 12 bit folding-ADC and a 1 GHz sampling rate. The system was triggered by the T0 signal from the proton beam monitor, and the threshold was set to 14.6 mV to filter the electronic noise. The sampling duration was set from 2 μs before the T0 trigger to 8 μ s after the T0 trigger, and the waveform of each neutron event was recorded. Because it is difficult for MCPs to distinguish between dark counts and neutron events, the B-MCP uses a voltage of -1750 V to keepthe dark counts below 0.1 cps/cm2. Each measurement took 10800 s to obtain accurate statistics. The data analysis was performed using the ROOT program developed by CERN.
DOI: 10.57760/sciencedb.09320
title: Yellow River Station auroral data
title: Yellow River Station auroral data

description: 2017-01-01 09:00- 09:40 UT Yellow River Station aurora data 557.7 nm band2007-12-07 09:00-10:00 UT Yellow River Station aurora data 630.0 nm band
description: 2017-01-01 09:00- 09:40 UT Yellow River Station aurora data 557.7 nm band2007-12-07 09:00-10:00 UT Yellow River Station aurora data 630.0 nm band
DOI: 10.57760/sciencedb.space.00662
title: Dataset of size-frequency distribution(SFD) of double layered ejecta craters
title: Dataset of size-frequency distribution(SFD) of double layered ejecta craters

description: The resulting SCC files (used for dating) for individual DLE craters exported from ArcGIS with the “Crater Tools" in this study.
description: The resulting SCC files (used for dating) for individual DLE craters exported from ArcGIS with the “Crater Tools" in this study.
DOI: 10.57760/sciencedb.09336
title: LiDAR Ca+ density figure in Beijing on January 16, 2021
title: LiDAR Ca+ density figure in Beijing on January 16, 2021

description: LiDAR Ca+ density figure in Beijing on January 16, 2021
description: LiDAR Ca+ density figure in Beijing on January 16, 2021
DOI: 10.57760/sciencedb.j00001.00876
title: Dataset for Evaluating Soil Erosion in the Karst Peak-Cluster Depression Ecosystem of Southwestern Guangxi Based on Corrections for Desertification and Soil Loss Tolerance（2000-2020）
title: 基于石漠化和允许流失量修正的桂西南喀斯特峰丛洼地生态系统土壤侵蚀评估数据集（2000-2020）

description: This dataset includes soil erosion modulus maps of southwestern Guangxi from 2000 to 2020 and spatial distribution maps of rocky desertification degrees from 2001 to 2020. The dataset has a spatial resolution of 90 meters and a temporal resolution of one year. The projection type is UTM 48N with a central meridian of 108°, and the numerical unit is tons per hectare per year (t∙hm-2∙a-1). The dataset is saved as a ZIP compressed file named "Soil Erosion Assessment Dataset for the Karst Peak-Cluster Depression Ecosystem in Southwestern Guangxi Based on Rocky Desertification and Allowed Soil Loss Correction (2000-2020).zip". The compressed file size is 299.8MB. The files are named according to the corresponding year, for example, "SE_2001" represents the spatial distribution map of soil erosion modulus in southwestern Guangxi in 2001, and "RF_2010" represents the spatial distribution map of rocky desertification degree in 2010. There are a total of 41 files.
description: This dataset includes soil erosion modulus maps of southwestern Guangxi from 2000 to 2020 and spatial distribution maps of rocky desertification degrees from 2001 to 2020. The dataset has a spatial resolution of 90 meters and a temporal resolution of one year. The projection type is UTM 48N with a central meridian of 108°, and the numerical unit is tons per hectare per year (t∙hm-2∙a-1). The dataset is saved as a ZIP compressed file named "Soil Erosion Assessment Dataset for the Karst Peak-Cluster Depression Ecosystem in Southwestern Guangxi Based on Rocky Desertification and Allowed Soil Loss Correction (2000-2020).zip". The compressed file size is 299.8MB. The files are named according to the corresponding year, for example, "SE_2001" represents the spatial distribution map of soil erosion modulus in southwestern Guangxi in 2001, and "RF_2010" represents the spatial distribution map of rocky desertification degree in 2010. There are a total of 41 files.
DOI: 10.57760/sciencedb.09338
title: Code of "Multi-analyte approach combining cfDNA sequencing and protein testing for early ovarian cancer detection"
title: Code of "Multi-analyte approach combining cfDNA sequencing and protein testing for early ovarian cancer detection"

description: Non-invasive liquid biopsy is a promising strategy for ovarian cancer (OC) detection. We evaluated the feasibility and efficacy of a multi-analyte approach combining circulating tumor DNA (ctDNA) detection with protein biomarkers for early OC detection. There are codes used in R and Python.
description: Non-invasive liquid biopsy is a promising strategy for ovarian cancer (OC) detection. We evaluated the feasibility and efficacy of a multi-analyte approach combining circulating tumor DNA (ctDNA) detection with protein biomarkers for early OC detection. There are codes used in R and Python.
DOI: 10.57760/sciencedb.09345
title: Impact of vacuum on the preparation of nanoporous copper through transient joule heating vapor phase dealloying
title: Impact of vacuum on the preparation of nanoporous copper through transient joule heating vapor phase dealloying

description: Copper nano-porous materials are commonly used functional materials with wide applications in catalysis and energy storage. This study investigates the influence of different vacuum degrees on the preparation of copper nano-porous metals using a transient Joule heating device via vapor phase de-alloying (VPD), and tests their performance as current collectors for lithium-ion batteries. The results show that the pore size of porous copper prepared at 20 Pa is 100 nm, with uniform distribution, and the sample has the lowest Zn content and smallest interplanar spacing of crystal phases, exhibiting an electrochemical activity specific surface area 317.6 times that of H65 brass. Furthermore, lithium-ion batteries made from porous copper produced at different vacuum degrees achieve discharge capacities of 420 and 435 mAh·g-1, higher than commercial copper foil-based lithium-ion batteries (350 mAh·g-1). By adjusting different vacuum degrees, the electrochemical performance of porous copper current collectors can be effectively improved.
description: Copper nano-porous materials are commonly used functional materials with wide applications in catalysis and energy storage. This study investigates the influence of different vacuum degrees on the preparation of copper nano-porous metals using a transient Joule heating device via vapor phase de-alloying (VPD), and tests their performance as current collectors for lithium-ion batteries. The results show that the pore size of porous copper prepared at 20 Pa is 100 nm, with uniform distribution, and the sample has the lowest Zn content and smallest interplanar spacing of crystal phases, exhibiting an electrochemical activity specific surface area 317.6 times that of H65 brass. Furthermore, lithium-ion batteries made from porous copper produced at different vacuum degrees achieve discharge capacities of 420 and 435 mAh·g-1, higher than commercial copper foil-based lithium-ion batteries (350 mAh·g-1). By adjusting different vacuum degrees, the electrochemical performance of porous copper current collectors can be effectively improved.
DOI: 10.57760/sciencedb.09331
title: Monthly Product of Marine Chemical Data in Australian Waters from 2000 to 2022
title: Monthly Product of Marine Chemical Data in Australian Waters from 2000 to 2022

description: The marine chemical time-series products, which include total alkalinity, inorganic carbon, nitrate, phosphate, silicate, and pH, constitute a foundational support mechanism for the ongoing surveillance of oceanic chemical changes. These products play a critical role in facilitating research focused on dynamic monitoring of marine ecosystems and fostering sustainable oceanic development. The interpolation methods frequently prove low-effective on a large scale, resulting in data with extensive temporal and spatial expanses that are difficulty for applications aimed at monitoring large-scale ocean dynamics. A novel integration of the CANYON-B and random forest regression methods was explored in reconstructing the concentrations of these marine chemicals at the sea surface within Australia's Exclusive Economic Zone over the period from 2000 to 2022 on a 1-kilometre scale. The approach involves the amalgamation of multi-source in-situ ocean chemistry time-series observations with MODIS Terra ocean reflectance imagery and ocean water colour product distributions. This research highlights the substantial capabilities of machine learning for the large-scale reconstruction of ocean chemistry data, introducing a new, viable method for utilising in-situ measurements and optical imagery in reconstructing marine chemical elements, thereby significantly enhancing our ability to monitor large-scale ocean dynamics.
description: The marine chemical time-series products, which include total alkalinity, inorganic carbon, nitrate, phosphate, silicate, and pH, constitute a foundational support mechanism for the ongoing surveillance of oceanic chemical changes. These products play a critical role in facilitating research focused on dynamic monitoring of marine ecosystems and fostering sustainable oceanic development. The interpolation methods frequently prove low-effective on a large scale, resulting in data with extensive temporal and spatial expanses that are difficulty for applications aimed at monitoring large-scale ocean dynamics. A novel integration of the CANYON-B and random forest regression methods was explored in reconstructing the concentrations of these marine chemicals at the sea surface within Australia's Exclusive Economic Zone over the period from 2000 to 2022 on a 1-kilometre scale. The approach involves the amalgamation of multi-source in-situ ocean chemistry time-series observations with MODIS Terra ocean reflectance imagery and ocean water colour product distributions. This research highlights the substantial capabilities of machine learning for the large-scale reconstruction of ocean chemistry data, introducing a new, viable method for utilising in-situ measurements and optical imagery in reconstructing marine chemical elements, thereby significantly enhancing our ability to monitor large-scale ocean dynamics.