cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.57760/sciencedb.14917
title: Analyzing the Surface Passivity Effect of Germanium Oxynitride: A Comprehensive Approach through First Principles Simulation and Interface State Density
title: Analyzing the Surface Passivity Effect of Germanium Oxynitride: A Comprehensive Approach through First Principles Simulation and Interface State Density

description: High-purity germanium (HPGe) detectors, which are used for direct dark matter detection, have the advantages of a low threshold and excellent energy resolution. The surface passivation of HPGe has become crucial for achieving an extremely low energy threshold. In this study, first-principles simulations, passivation film preparation, and metal oxide semiconductor (MOS) capacitor characterization were combined to study surface passivation. Theoretical calculations of the energy band structure of the -H,-OH, and -NH2 passivation groups on the surface of Ge were performed, and the interface state density and potential with five different passivation groups with N/O atomic ratios were accurately analyzed to obtain a stable surface state. Based on the theoretical calculation results, the surface passivation layers of the Ge2ON2 film were prepared via magnetron sputtering in accordance with the optimum atomic ratio structure. The microstructure, C-V, and I-V electrical properties of the layers, and the passivation effect of the Al/Ge2ON2/Ge MOS were characterized to test the interface state density. The mean interface state density obtained by the Terman method was 8.4 × 1011 cm-2 eV-1. The processing of germanium oxynitrogen passivation films is expected to be used in direct dark matter detection of the HPGe detector surface passivation technology to reduce the detector leakage currents.
description: High-purity germanium (HPGe) detectors, which are used for direct dark matter detection, have the advantages of a low threshold and excellent energy resolution. The surface passivation of HPGe has become crucial for achieving an extremely low energy threshold. In this study, first-principles simulations, passivation film preparation, and metal oxide semiconductor (MOS) capacitor characterization were combined to study surface passivation. Theoretical calculations of the energy band structure of the -H,-OH, and -NH2 passivation groups on the surface of Ge were performed, and the interface state density and potential with five different passivation groups with N/O atomic ratios were accurately analyzed to obtain a stable surface state. Based on the theoretical calculation results, the surface passivation layers of the Ge2ON2 film were prepared via magnetron sputtering in accordance with the optimum atomic ratio structure. The microstructure, C-V, and I-V electrical properties of the layers, and the passivation effect of the Al/Ge2ON2/Ge MOS were characterized to test the interface state density. The mean interface state density obtained by the Terman method was 8.4 × 1011 cm-2 eV-1. The processing of germanium oxynitrogen passivation films is expected to be used in direct dark matter detection of the HPGe detector surface passivation technology to reduce the detector leakage currents.
DOI: 10.57760/sciencedb.14925
title: UAV above-ground biomass product of grassland at Tajikistan
title: 塔吉克斯坦草地无人机地上生物量产品

description: The data clusters have produced grass above ground biomass products based on drone optical images to invert five typical grassland areas: the BALHI, LUCHOB, ZIDDI, SHAHRISTON, and LAKHSH. 
description: The data clusters have produced grass above ground biomass products based on drone optical images to invert five typical grassland areas: the BALHI, LUCHOB, ZIDDI, SHAHRISTON, and LAKHSH.
DOI: 10.57760/sciencedb.j00186.00387
title: Dataset of sparse view neutron computed tomography based on 3D robust anisotropic diffusion filtering algorithm
title: Dataset of sparse view neutron computed tomography based on 3D robust anisotropic diffusion filtering algorithm

description: The dataset provides 3D image matrices obtained by reconstructing different models with FBP, OS-SART-SBTV, OS-SART-TV, and OS-SART-ADF algorithms.
description: The dataset provides 3D image matrices obtained by reconstructing different models with FBP, OS-SART-SBTV, OS-SART-TV, and OS-SART-ADF algorithms.
DOI: 10.57760/sciencedb.14945
title: The Data of Offline Reinforcement Learning Based on Prioritized Sampling Model
title: 基于优先采样模型的离线强化学习数据

description: Offline reinforcement learning algorithms realize the approximation of learned policy to behavior policy by reducing the distribution shift, but the data distribution of offline experience buffer often directly affects the quality of learned policy. In this paper, two offline prioritized sampling models including temporal difference error-based and martingale-based are proposed to improve the training effect of reinforcement learning agent. The temporal difference error-based sampling model enables agents to learn more experience data with inaccurate value estimation, thus deals with possible out of distribution states by estimating more accurate value functions. The martingale-based sampling model enables agents to learn more positive samples beneficial to policy optimization and reduces the impact of negative samples on value function iteration. Furthermore, the proposed offline prioritized sampling models are combined with the batch-constrained deep Q-learning (BCQ) respectively, to propose temporal difference error-based prioritized BCQ and martingale-based prioritized BCQ. Experimental results on D4RL and Torcs datasets show that the proposed two offline prioritized sampling models can be targeted to select the experience data that are conducive to value function estimation or policy optimization, so as to obtain higher rewards.
description: Offline reinforcement learning algorithms realize the approximation of learned policy to behavior policy by reducing the distribution shift, but the data distribution of offline experience buffer often directly affects the quality of learned policy. In this paper, two offline prioritized sampling models including temporal difference error-based and martingale-based are proposed to improve the training effect of reinforcement learning agent. The temporal difference error-based sampling model enables agents to learn more experience data with inaccurate value estimation, thus deals with possible out of distribution states by estimating more accurate value functions. The martingale-based sampling model enables agents to learn more positive samples beneficial to policy optimization and reduces the impact of negative samples on value function iteration. Furthermore, the proposed offline prioritized sampling models are combined with the batch-constrained deep Q-learning (BCQ) respectively, to propose temporal difference error-based prioritized BCQ and martingale-based prioritized BCQ. Experimental results on D4RL and Torcs datasets show that the proposed two offline prioritized sampling models can be targeted to select the experience data that are conducive to value function estimation or policy optimization, so as to obtain higher rewards.
DOI: 10.57760/sciencedb.j00133.00390
title: Ceramic Ware Types Dataset
title: 陶瓷器型数据集

description: This dataset includes ceramic vessel types such as moon holding bottles and rotating star bottles, with a total of 17265 ceramic vessel type images, covering 19 different vessel types. In the process of creating the dataset, this article divides the above dataset into training and testing sets in a ratio of 3:7. 
description: This dataset includes ceramic vessel types such as moon holding bottles and rotating star bottles, with a total of 17265 ceramic vessel type images, covering 19 different vessel types. In the process of creating the dataset, this article divides the above dataset into training and testing sets in a ratio of 3:7.
DOI: 10.57760/sciencedb.14949
title: E-commerce Marketing Text
title: 智能营销文本数据

description: The intelligent marketing text data of e-commerce platforms can be used to build intelligent marketing text generation models. 
description: The intelligent marketing text data of e-commerce platforms can be used to build intelligent marketing text generation models.
DOI: 10.57760/sciencedb.j00133.00392
title: Dataset for An Approach to Identify Technological Evolution Paths: Integrate Graph Embedding and Path Analysis
title: 一种技术演化路径识别方法：集成图嵌入和路径分析（数据集）

description: In the research paper "A Technology Evolution Path Identification Method: Integrating Graph Embedding and Path Analysis", the dataset used in the case study consists of five parts.UAV flight control technology patent data. This dataset contains 806 patents (time up to September 2023).UAV flight control technology patent citation data. The dataset collects 6525 patents.Patent citation network and patent type data. The data used to construct the patent citation network is collected in this data set, and the technology category of the patent is given.Patent abstracts text BERT vector data. This data collects patent abstract vectors obtained from BERT model training in our study, with 768 dimensions and a total of 6525.Patent vector data from our PatGraph model. This dataset collects the patent vector data obtained using the PatGraph model in our study, totaling 6525 patents, which is used to visualize the results through dimensionality reduction.
description: In the research paper "A Technology Evolution Path Identification Method: Integrating Graph Embedding and Path Analysis", the dataset used in the case study consists of five parts.UAV flight control technology patent data. This dataset contains 806 patents (time up to September 2023).UAV flight control technology patent citation data. The dataset collects 6525 patents.Patent citation network and patent type data. The data used to construct the patent citation network is collected in this data set, and the technology category of the patent is given.Patent abstracts text BERT vector data. This data collects patent abstract vectors obtained from BERT model training in our study, with 768 dimensions and a total of 6525.Patent vector data from our PatGraph model. This dataset collects the patent vector data obtained using the PatGraph model in our study, totaling 6525 patents, which is used to visualize the results through dimensionality reduction.
DOI: 10.57760/sciencedb.14948
title: Data set of 234 woven fabric samples regarding warp and weft wise fabric strength
title: Data set of 234 woven fabric samples regarding warp and weft wise fabric strength

description: There are two excel files consist of different columns such as warp yarn strength, weft yarn strength, ends per inch, picks per inch and warp-wise fabric strength or weft-wise fabric strength
description: There are two excel files consist of different columns such as warp yarn strength, weft yarn strength, ends per inch, picks per inch and warp-wise fabric strength or weft-wise fabric strength
DOI: 10.57760/sciencedb.14951
title: Image Retrieval Dataset for Rural Cultural Tourism
title: 乡村文旅图像检索数据集

description: A rural cultural tourism dataset that can be used for image retrieval of rural destinations.
description: A rural cultural tourism dataset that can be used for image retrieval of rural destinations.
DOI: 10.57760/sciencedb.14953
title: viable antibiotic resistome on microplastics in aquatic environment
title: viable antibiotic resistome on microplastics in aquatic environment

description: Microplastics (MPs) in the aquatic environment serve as ideal carriers for the attachment of antimicrobial resistance (AMR) and pathogens, which has attracted worldwide attention. However, the viable fractions on MPs, which are major contributors to the prevalence and dissemination of AMR, remains poorly understood. In this study, Propidium monoazide (PMA)-combined high-throughput quantitative PCR and amplicon sequencing were conducted to target the viable antibiotic resistome and microbial communities on three types of MPs from an urban river.
description: Microplastics (MPs) in the aquatic environment serve as ideal carriers for the attachment of antimicrobial resistance (AMR) and pathogens, which has attracted worldwide attention. However, the viable fractions on MPs, which are major contributors to the prevalence and dissemination of AMR, remains poorly understood. In this study, Propidium monoazide (PMA)-combined high-throughput quantitative PCR and amplicon sequencing were conducted to target the viable antibiotic resistome and microbial communities on three types of MPs from an urban river.
DOI: 10.57760/sciencedb.o00130.01315
title: Establishing a model for predicting type 2 diabetes mellitus with cognitive impairment
title: 建立一种2型糖尿病合并认知障碍的临床预测模型

description: 收集患者身高、体重、腰围、臀围、生活饮食习惯、糖尿病史等资料，并检测患者血清PDGFRβ、HDL-3、Nesfatin-1、GDF-15、FPN及1,5-AG水平，利用方差分析或KW检验，以是否合并MCI或De为结局，分析各组间各个指标的差异，采用多因素COX比例风险回归分析，筛选出T2DM并发MCI或De的独立危险因素，构建T2DM合并MCI或T2DM合并De的风险Nomogram模型，并按照7/3拆分原则构建训练集和验证集，评价各模型的效能。
description: 收集患者身高、体重、腰围、臀围、生活饮食习惯、糖尿病史等资料，并检测患者血清PDGFRβ、HDL-3、Nesfatin-1、GDF-15、FPN及1,5-AG水平，利用方差分析或KW检验，以是否合并MCI或De为结局，分析各组间各个指标的差异，采用多因素COX比例风险回归分析，筛选出T2DM并发MCI或De的独立危险因素，构建T2DM合并MCI或T2DM合并De的风险Nomogram模型，并按照7/3拆分原则构建训练集和验证集，评价各模型的效能。
DOI: 10.57760/sciencedb.14952
title: High-Precision Phase Extraction and Error Analysis of Ronchi Lateral Shearing Interferometry
title: Ronchi剪切干涉仪高精度相位提取及误差分析

description: Double-grating Ronchi lateral shearing interferometry is a primary method for measuring wavefront aberration at the exit pupil of a lithographic projection lens. It has the advantages of being reference-free, having a common path, and having a simple structure that can be easily integrated. This method is suitable for in-situ measurement of wavefront aberration in lithographic projection lens. Phase extraction is a crucial step in this method, as it directly affects the accuracy of the final wavefront aberration measurement. To suppress the interference of high diffraction orders in double-grating Ronchi shearing interferometry, a high-precision shear phase extraction algorithm is proposed. This algorithm can eliminate all high diffraction orders in the overlapping area between ±1st orders, thereby improving the accuracy of the shear phase extraction. The simulation results show that only high-frequency residuals exist in the shear phase extraction errors and are almost negligible, which indicates that the proposed algorithm can effectively eliminate all high diffraction orders theoretically. The experiment is carried out on double-grating Ronchi shearing interferometry system with a shear ratio of 0.058, and compared with the measurement result of dual-fiber point diffraction interferometer, both of the results have the same wavefront aberration distribution, which further verifies the effectiveness of the shear phase extraction algorithm.
description: Double-grating Ronchi lateral shearing interferometry is a primary method for measuring wavefront aberration at the exit pupil of a lithographic projection lens. It has the advantages of being reference-free, having a common path, and having a simple structure that can be easily integrated. This method is suitable for in-situ measurement of wavefront aberration in lithographic projection lens. Phase extraction is a crucial step in this method, as it directly affects the accuracy of the final wavefront aberration measurement. To suppress the interference of high diffraction orders in double-grating Ronchi shearing interferometry, a high-precision shear phase extraction algorithm is proposed. This algorithm can eliminate all high diffraction orders in the overlapping area between ±1st orders, thereby improving the accuracy of the shear phase extraction. The simulation results show that only high-frequency residuals exist in the shear phase extraction errors and are almost negligible, which indicates that the proposed algorithm can effectively eliminate all high diffraction orders theoretically. The experiment is carried out on double-grating Ronchi shearing interferometry system with a shear ratio of 0.058, and compared with the measurement result of dual-fiber point diffraction interferometer, both of the results have the same wavefront aberration distribution, which further verifies the effectiveness of the shear phase extraction algorithm.
DOI: 10.57760/sciencedb.14959
title: Mural dataset
title: Mural dataset

description: The dataset includes three types of murals, among which the Dunhuang mural data is sourced from the complete collection of the Dunhuang murals; Chinese unearthed murals come from the complete collection of murals unearthed in China; Temple murals are collected from the complete collection of Chinese temple murals. The visual feature set of Dunhuang murals, Temple murals, and Chinese unearthed murals was created by HSV, HOG, and BOW_ SIFT and ResNet50. And the text description of the mural includes the ID, name, location, and date.
description: The dataset includes three types of murals, among which the Dunhuang mural data is sourced from the complete collection of the Dunhuang murals; Chinese unearthed murals come from the complete collection of murals unearthed in China; Temple murals are collected from the complete collection of Chinese temple murals. The visual feature set of Dunhuang murals, Temple murals, and Chinese unearthed murals was created by HSV, HOG, and BOW_ SIFT and ResNet50. And the text description of the mural includes the ID, name, location, and date.
DOI: 10.57760/sciencedb.14957
title: Mechanical Properties for Polyurethane elastomers
title: Mechanical Properties for Polyurethane elastomers

description: This dataset contains Young’s modulus, tensile strength, and elongation at break for 643 polyurethane elastomers, and the associated 20 features for composition, processing and measurements. The regression model on the 20 features for the mechanical properties is up to 0.8.
description: This dataset contains Young’s modulus, tensile strength, and elongation at break for 643 polyurethane elastomers, and the associated 20 features for composition, processing and measurements. The regression model on the 20 features for the mechanical properties is up to 0.8.
DOI: 10.57760/sciencedb.j00133.00394
title: Zhihu Community Q&A Dataset on Internet Medical, Disease and Public Health Topics
title: 知乎社区互联网医疗、疾病和公共卫生话题问答数据集

description: The Q&A datasets were obtained from the topics of "Internet Healthcare", "Diseases", and "Public Health" in the Zhihu community. The data fields of each Q&A document include the topic, question title, question description, answer content, and label.
description: The Q&A datasets were obtained from the topics of "Internet Healthcare", "Diseases", and "Public Health" in the Zhihu community. The data fields of each Q&A document include the topic, question title, question description, answer content, and label.
DOI: 10.57760/sciencedb.space.01520
title: Dataset of the GNSS ionospheric total electron content at the Sanya station in 2018
title: Dataset of the GNSS ionospheric total electron content at the Sanya station in 2018

description: The use of satellite beacons to detect the ionosphere has a long history. In recent years, the establishment of multiple global navigation satellite systems (GNSS) has further improved the spatial and temporal coverage and resolution of ionospheric observations, making them the most widely used method in ionospheric research. In this paper, the GNSS ionospheric total electron content data of Sanya station in 2018 are selected as representative, and the inversion of ionospheric total electron content data carried out by the Institute of Geology and Geophysics, Chinese Academy of Sciences through the reception of multiple global navigation satellite signals is presented. The original observations of this data set are accurate and reliable, and the data sets are complete and continuous. It can be used to study the effects of solar activity, magnetic storms, etc. on the ionosphere, as well as ionospheric disturbances, ionospheric distribution characteristics and other related work. It can also provide data for technical applications such as satellite navigation and positioning.
description: The use of satellite beacons to detect the ionosphere has a long history. In recent years, the establishment of multiple global navigation satellite systems (GNSS) has further improved the spatial and temporal coverage and resolution of ionospheric observations, making them the most widely used method in ionospheric research. In this paper, the GNSS ionospheric total electron content data of Sanya station in 2018 are selected as representative, and the inversion of ionospheric total electron content data carried out by the Institute of Geology and Geophysics, Chinese Academy of Sciences through the reception of multiple global navigation satellite signals is presented. The original observations of this data set are accurate and reliable, and the data sets are complete and continuous. It can be used to study the effects of solar activity, magnetic storms, etc. on the ionosphere, as well as ionospheric disturbances, ionospheric distribution characteristics and other related work. It can also provide data for technical applications such as satellite navigation and positioning.
DOI: 10.57760/sciencedb.14967
title: Article Monitoring Applications with Process Mining
title: Article Monitoring Applications with Process Mining

description: These are the data sets utilized to write the article: Monitoring Applications with Process Mining
description: These are the data sets utilized to write the article: Monitoring Applications with Process Mining
DOI: 10.57760/sciencedb.14973
title: Market Orientation
title: Market Orientation

description: Market Orientation and Intellectual Capital on Business Performance Through Aesthetic Innovation in Food Souvenir Products
description: Market Orientation and Intellectual Capital on Business Performance Through Aesthetic Innovation in Food Souvenir Products
DOI: 10.57760/sciencedb.14976
title: Methane yield data from systematic review
title: Methane yield data from systematic review

description: This table presents data from a systematic review that examines the application of different pretreatments prior anaerobic digestion. It provides a concise summary of important findings, offering insights on methods to enhance methane production. This resource is valuable for researchers and practitioners seeking to optimize anaerobic digestion for increased efficiency and sustainable energy generation.
description: This table presents data from a systematic review that examines the application of different pretreatments prior anaerobic digestion. It provides a concise summary of important findings, offering insights on methods to enhance methane production. This resource is valuable for researchers and practitioners seeking to optimize anaerobic digestion for increased efficiency and sustainable energy generation.
DOI: 10.57760/sciencedb.14979
title: user behavior
title: 用户行为指标数据

description: Subjects use different search engines to complete different retrieval tasks, including retrieval style, retrieval style length, retrieval style construction time, retrieval style reconstruction, subjective satisfaction, and objective completion data 
description: Subjects use different search engines to complete different retrieval tasks, including retrieval style, retrieval style length, retrieval style construction time, retrieval style reconstruction, subjective satisfaction, and objective completion data
DOI: 10.57760/sciencedb.14980
title: search results
title: 检索结果回答文档汇总

description: Participants use different search engines to summarize answer documents for different retrieval tasks 
description: Participants use different search engines to summarize answer documents for different retrieval tasks