Atomic Data and Nuclear Data Tables最新文献

英文中文

Self-Reported Mental Health and Psychosocial Correlates during the COVID-19 Pandemic: Data from the General Population in Italy COVID-19大流行期间自我报告的心理健康和社会心理相关因素:来自意大利普通人群的数据

IF 1.8 3区物理与天体物理 Q2 PHYSICS, ATOMIC, MOLECULAR & CHEMICAL

Atomic Data and Nuclear Data Tables

Pub Date : 2023-06-16 DOI: 10.3390/data8060111

D. Marchetti, Roberta Maiella, Rocco Palumbo, Melissa D'Ettorre, Irene Ceccato, M. Colasanti, Adolfo Di Crosta, Pasquale La Malva, Emanuela Bartolini, Daniela Biasone, N. Mammarella, P. Porcelli, A. Domenico, M. Verrocchio

The COVID-19 pandemic tremendously impacted people’s day-to-day activities and mental health. This article describes the dataset used to investigate the psychological impact of the first national lockdown on the general Italian population. For this purpose, an online survey was disseminated via Qualtrics between 1 April and 20 April 2020, to record various socio-demographic and psychological variables. The measures included both validated (namely, the Impact of the Event Scale-Revised, the Perceived Stress Scale, the nine-item Patient Health Questionnaire, the seven-item Generalized Anxiety Disorder scale, the Big Five Inventory 10-Item, and the Whiteley Index-7) and ad hoc questionnaires (nine items to investigate in-group and out-group trust). The final sample comprised 4081 participants (18–85 years old). The dataset could be helpful to other researchers in understanding the psychological impact of the COVID-19 pandemic and its related preventive and protective measures. Furthermore, the present data might help shed some light on the role of individual differences in response to traumatic events. Finally, this dataset can increase the knowledge in investigating psychological distress, health anxiety, and personality traits.

COVID-19大流行极大地影响了人们的日常活动和心理健康。本文描述了用于调查第一次全国封锁对意大利普通人口心理影响的数据集。为此，在2020年4月1日至4月20日期间，通过Qualtrics发布了一项在线调查，以记录各种社会人口和心理变量。测量包括验证问卷(即事件量表的影响-修订，感知压力量表，9项患者健康问卷，7项广泛性焦虑障碍量表，大五量表10项和怀特利指数-7)和特设问卷(9项调查群体内和群体外信任)。最终样本包括4081名参与者(18-85岁)。该数据集可以帮助其他研究人员了解COVID-19大流行及其相关预防和保护措施的心理影响。此外，目前的数据可能有助于揭示个体差异在创伤性事件反应中的作用。最后，该数据集可以增加调查心理困扰，健康焦虑和人格特征的知识。

{"title":"Self-Reported Mental Health and Psychosocial Correlates during the COVID-19 Pandemic: Data from the General Population in Italy","authors":"D. Marchetti, Roberta Maiella, Rocco Palumbo, Melissa D'Ettorre, Irene Ceccato, M. Colasanti, Adolfo Di Crosta, Pasquale La Malva, Emanuela Bartolini, Daniela Biasone, N. Mammarella, P. Porcelli, A. Domenico, M. Verrocchio","doi":"10.3390/data8060111","DOIUrl":"https://doi.org/10.3390/data8060111","url":null,"abstract":"The COVID-19 pandemic tremendously impacted people’s day-to-day activities and mental health. This article describes the dataset used to investigate the psychological impact of the first national lockdown on the general Italian population. For this purpose, an online survey was disseminated via Qualtrics between 1 April and 20 April 2020, to record various socio-demographic and psychological variables. The measures included both validated (namely, the Impact of the Event Scale-Revised, the Perceived Stress Scale, the nine-item Patient Health Questionnaire, the seven-item Generalized Anxiety Disorder scale, the Big Five Inventory 10-Item, and the Whiteley Index-7) and ad hoc questionnaires (nine items to investigate in-group and out-group trust). The final sample comprised 4081 participants (18–85 years old). The dataset could be helpful to other researchers in understanding the psychological impact of the COVID-19 pandemic and its related preventive and protective measures. Furthermore, the present data might help shed some light on the role of individual differences in response to traumatic events. Finally, this dataset can increase the knowledge in investigating psychological distress, health anxiety, and personality traits.","PeriodicalId":55580,"journal":{"name":"Atomic Data and Nuclear Data Tables","volume":"39 1","pages":"111"},"PeriodicalIF":1.8,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72663858","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

How Expert Is the Crowd? Insights into Crowd Opinions on the Severity of Earthquake Damage 人群有多专业?民众对地震破坏程度的看法

IF 1.8 3区物理与天体物理 Q2 PHYSICS, ATOMIC, MOLECULAR & CHEMICAL

Atomic Data and Nuclear Data Tables

Pub Date : 2023-06-14 DOI: 10.3390/data8060108

M. Zohar, A. Salamon, C. Rapaport

The evaluation of earthquake damage is central to assessing its severity and damage characteristics. However, the methods of assessment encounter difficulties concerning the subjective judgments and interpretation of the evaluators. Thus, it is mainly geologists, seismologists, and engineers who perform this exhausting task. Here, we explore whether an evaluation made by semiskilled people and by the crowd is equivalent to the experts’ opinions and, thus, can be harnessed as part of the process. Therefore, we conducted surveys in which a cohort of graduate students studying natural hazards (n = 44) and an online crowd (n = 610) were asked to evaluate the level of severity of earthquake damage. The two outcome datasets were then compared with the evaluation made by two of the present authors, who are considered experts in the field. Interestingly, the evaluations of both the semiskilled cohort and the crowd were found to be fairly similar to those of the experts, thus suggesting that they can provide an interpretation close enough to an expert’s opinion on the severity level of earthquake damage. Such an understanding may indicate that although our analysis is preliminary and requires more case studies for this to be verified, there is vast potential encapsulated in crowd-sourced opinion on simple earthquake-related damage, especially if a large amount of data is to be handled.

震害评估是评估地震严重程度和震害特征的核心。然而，评估方法在评估者的主观判断和解释方面遇到困难。因此，主要是地质学家、地震学家和工程师来完成这项艰巨的任务。在这里，我们探讨由半熟练人员和人群做出的评估是否等同于专家的意见，因此，可以作为过程的一部分加以利用。因此，我们进行了一项调查，要求一群研究自然灾害的研究生(n = 44)和一群在线人群(n = 610)评估地震破坏的严重程度。然后将这两个结果数据集与两位被认为是该领域专家的现任作者所做的评估进行比较。有趣的是，对半熟练人群和普通人群的评估与专家的评估相当相似，因此表明他们可以提供足够接近专家对地震破坏严重程度的意见的解释。这样的理解可能表明，尽管我们的分析是初步的，需要更多的案例研究来验证，但在简单的地震相关损害的众包意见中蕴含着巨大的潜力，特别是在需要处理大量数据的情况下。

{"title":"How Expert Is the Crowd? Insights into Crowd Opinions on the Severity of Earthquake Damage","authors":"M. Zohar, A. Salamon, C. Rapaport","doi":"10.3390/data8060108","DOIUrl":"https://doi.org/10.3390/data8060108","url":null,"abstract":"The evaluation of earthquake damage is central to assessing its severity and damage characteristics. However, the methods of assessment encounter difficulties concerning the subjective judgments and interpretation of the evaluators. Thus, it is mainly geologists, seismologists, and engineers who perform this exhausting task. Here, we explore whether an evaluation made by semiskilled people and by the crowd is equivalent to the experts’ opinions and, thus, can be harnessed as part of the process. Therefore, we conducted surveys in which a cohort of graduate students studying natural hazards (n = 44) and an online crowd (n = 610) were asked to evaluate the level of severity of earthquake damage. The two outcome datasets were then compared with the evaluation made by two of the present authors, who are considered experts in the field. Interestingly, the evaluations of both the semiskilled cohort and the crowd were found to be fairly similar to those of the experts, thus suggesting that they can provide an interpretation close enough to an expert’s opinion on the severity level of earthquake damage. Such an understanding may indicate that although our analysis is preliminary and requires more case studies for this to be verified, there is vast potential encapsulated in crowd-sourced opinion on simple earthquake-related damage, especially if a large amount of data is to be handled.","PeriodicalId":55580,"journal":{"name":"Atomic Data and Nuclear Data Tables","volume":"22 1","pages":"108"},"PeriodicalIF":1.8,"publicationDate":"2023-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90904639","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dataset of Program Source Codes Solving Unique Programming Exercises Generated by Digital Teaching Assistant 数字助教生成的解决独特编程练习的程序源代码数据集

IF 1.8 3区物理与天体物理 Q2 PHYSICS, ATOMIC, MOLECULAR & CHEMICAL

Atomic Data and Nuclear Data Tables

Pub Date : 2023-06-14 DOI: 10.3390/data8060109

Liliya A. Demidova, E. Andrianova, Peter N. Sovietov, A. Gorchakov

This paper presents a dataset containing automatically collected source codes solving unique programming exercises of different types. The programming exercises were automatically generated by the Digital Teaching Assistant (DTA) system that automates a massive Python programming course at MIREA—Russian Technological University (RTU MIREA). Source codes of the small programs grouped by the type of the solved task can be used for benchmarking source code classification and clustering algorithms. Moreover, the data can be used for training intelligent program synthesizers or benchmarking mutation testing frameworks, and more applications are yet to be discovered. We describe the architecture of the DTA system, aiming to provide detailed insight regarding how and why the dataset was collected. In addition, we describe the algorithms responsible for source code analysis in the DTA system. These algorithms use vector representations of programs based on Markov chains, compute pairwise Jensen–Shannon divergences of programs, and apply hierarchical clustering algorithms in order to automatically discover high-level concepts used by students while solving unique tasks. The proposed approach can be incorporated into massive programming courses when there is a need to identify approaches implemented by students.

本文提出了一个包含自动收集的源代码的数据集，用于解决不同类型的独特编程练习。编程练习是由数字教学助理(DTA)系统自动生成的，该系统自动化了MIREA -俄罗斯技术大学(RTU MIREA)的大型Python编程课程。按解决任务类型分组的小程序源代码可用于对源代码分类和聚类算法进行基准测试。此外，这些数据还可以用于训练智能程序合成器或对标突变测试框架，还有更多的应用有待发现。我们描述了DTA系统的架构，旨在提供关于如何以及为什么收集数据集的详细见解。此外，我们还描述了DTA系统中负责源代码分析的算法。这些算法使用基于马尔可夫链的程序向量表示，计算程序的成对Jensen-Shannon散度，并应用分层聚类算法，以便在解决独特任务时自动发现学生使用的高级概念。当需要确定学生实施的方法时，建议的方法可以合并到大规模编程课程中。

{"title":"Dataset of Program Source Codes Solving Unique Programming Exercises Generated by Digital Teaching Assistant","authors":"Liliya A. Demidova, E. Andrianova, Peter N. Sovietov, A. Gorchakov","doi":"10.3390/data8060109","DOIUrl":"https://doi.org/10.3390/data8060109","url":null,"abstract":"This paper presents a dataset containing automatically collected source codes solving unique programming exercises of different types. The programming exercises were automatically generated by the Digital Teaching Assistant (DTA) system that automates a massive Python programming course at MIREA—Russian Technological University (RTU MIREA). Source codes of the small programs grouped by the type of the solved task can be used for benchmarking source code classification and clustering algorithms. Moreover, the data can be used for training intelligent program synthesizers or benchmarking mutation testing frameworks, and more applications are yet to be discovered. We describe the architecture of the DTA system, aiming to provide detailed insight regarding how and why the dataset was collected. In addition, we describe the algorithms responsible for source code analysis in the DTA system. These algorithms use vector representations of programs based on Markov chains, compute pairwise Jensen–Shannon divergences of programs, and apply hierarchical clustering algorithms in order to automatically discover high-level concepts used by students while solving unique tasks. The proposed approach can be incorporated into massive programming courses when there is a need to identify approaches implemented by students.","PeriodicalId":55580,"journal":{"name":"Atomic Data and Nuclear Data Tables","volume":"1 1","pages":"109"},"PeriodicalIF":1.8,"publicationDate":"2023-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74606324","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Assessing the Effectiveness of Masking and Encryption in Safeguarding the Identity of Social Media Publishers from Advanced Metadata Analysis 评估屏蔽和加密在保护社交媒体发布者身份免受高级元数据分析中的有效性

IF 1.8 3区物理与天体物理 Q2 PHYSICS, ATOMIC, MOLECULAR & CHEMICAL

Atomic Data and Nuclear Data Tables

Pub Date : 2023-06-13 DOI: 10.3390/data8060105

Mohammed Khader, M. Karam

Machine learning algorithms, such as KNN, SVM, MLP, RF, and MLR, are used to extract valuable information from shared digital data on social media platforms through their APIs in an effort to identify anonymous publishers or online users. This can leave these anonymous publishers vulnerable to privacy-related attacks, as identifying information can be revealed. Twitter is an example of such a platform where identifying anonymous users/publishers is made possible by using machine learning techniques. To provide these anonymous users with stronger protection, we have examined the effectiveness of these techniques when critical fields in the metadata are masked or encrypted using tweets (text and images) from Twitter. Our results show that SVM achieved the highest accuracy rate of 95.81% without using data masking or encryption, while SVM achieved the highest identity recognition rate of 50.24% when using data masking and AES encryption algorithm. This indicates that data masking and encryption of metadata of tweets (text and images) can provide promising protection for the anonymity of users’ identities.

机器学习算法，如KNN、SVM、MLP、RF和MLR，通过其api从社交媒体平台上共享的数字数据中提取有价值的信息，以识别匿名发布者或在线用户。这可能会使这些匿名发布者容易受到与隐私相关的攻击，因为身份信息可能会泄露。Twitter就是这样一个平台的例子，通过使用机器学习技术来识别匿名用户/发布者是可能的。为了向这些匿名用户提供更强的保护，我们研究了使用Twitter的tweet(文本和图像)屏蔽或加密元数据中的关键字段时这些技术的有效性。我们的研究结果表明，在不使用数据屏蔽和加密的情况下，SVM的识别率最高，达到95.81%，而在使用数据屏蔽和AES加密算法的情况下，SVM的身份识别率最高，达到50.24%。这表明对tweet元数据(文本和图像)进行数据屏蔽和加密可以为用户身份的匿名性提供很好的保护。

{"title":"Assessing the Effectiveness of Masking and Encryption in Safeguarding the Identity of Social Media Publishers from Advanced Metadata Analysis","authors":"Mohammed Khader, M. Karam","doi":"10.3390/data8060105","DOIUrl":"https://doi.org/10.3390/data8060105","url":null,"abstract":"Machine learning algorithms, such as KNN, SVM, MLP, RF, and MLR, are used to extract valuable information from shared digital data on social media platforms through their APIs in an effort to identify anonymous publishers or online users. This can leave these anonymous publishers vulnerable to privacy-related attacks, as identifying information can be revealed. Twitter is an example of such a platform where identifying anonymous users/publishers is made possible by using machine learning techniques. To provide these anonymous users with stronger protection, we have examined the effectiveness of these techniques when critical fields in the metadata are masked or encrypted using tweets (text and images) from Twitter. Our results show that SVM achieved the highest accuracy rate of 95.81% without using data masking or encryption, while SVM achieved the highest identity recognition rate of 50.24% when using data masking and AES encryption algorithm. This indicates that data masking and encryption of metadata of tweets (text and images) can provide promising protection for the anonymity of users’ identities.","PeriodicalId":55580,"journal":{"name":"Atomic Data and Nuclear Data Tables","volume":"331 1","pages":"105"},"PeriodicalIF":1.8,"publicationDate":"2023-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73145130","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Curated Dataset for Red Blood Cell Tracking from Video Sequences of Flow in Microfluidic Devices 从微流控装置中流动的视频序列中对红细胞跟踪的策划数据集

IF 1.8 3区物理与天体物理 Q2 PHYSICS, ATOMIC, MOLECULAR & CHEMICAL

Atomic Data and Nuclear Data Tables

Pub Date : 2023-06-13 DOI: 10.3390/data8060106

I. Cimrák, P. Tarábek, Frantisek Kajánek

This work presents a dataset comprising images, annotations, and velocity fields for benchmarking cell detection and cell tracking algorithms. The dataset includes two video sequences captured during laboratory experiments, showcasing the flow of red blood cells (RBC) in microfluidic channels. From the first video 300 frames and from the second video 150 frames are annotated with bounding boxes around the cells, as well as tracks depicting the movement of individual cells throughout the video. The dataset encompasses approximately 20,000 bounding boxes and 350 tracks. Additionally, computational fluid dynamics simulations were utilized to generate 2D velocity fields representing the flow within the channels. These velocity fields are included in the dataset. The velocity field has been employed to improve cell tracking by predicting the positions of cells across frames. The paper also provides a comprehensive discussion on the utilization of the flow matrix in the tracking steps.

这项工作提出了一个包含图像、注释和速度场的数据集，用于基准细胞检测和细胞跟踪算法。该数据集包括在实验室实验中捕获的两个视频序列，展示了微流体通道中红细胞(RBC)的流动。从第一个视频的300帧和第二个视频的150帧中，细胞周围标注了边界框，以及描述整个视频中单个细胞运动的轨迹。该数据集包含大约20,000个边界框和350条轨道。此外，利用计算流体动力学模拟生成了代表通道内流动的二维速度场。这些速度场包含在数据集中。速度场通过预测细胞在帧间的位置来改善细胞跟踪。本文还对流矩阵在跟踪步骤中的应用进行了全面的讨论。

引用次数: 0

A Preliminary Investigation of a Single Shock Impact on Italian Mortality Rates Using STMF Data: A Case Study of COVID-19 利用STMF数据对单一冲击对意大利死亡率影响的初步调查:以COVID-19为例

IF 1.8 3区物理与天体物理 Q2 PHYSICS, ATOMIC, MOLECULAR & CHEMICAL

Atomic Data and Nuclear Data Tables

Pub Date : 2023-06-13 DOI: 10.3390/data8060107

M. Carfora, A. Orlando

Mortality shocks, such as pandemics, threaten the consolidated longevity improvements, confirmed in the last decades for the majority of western countries. Indeed, just before the COVID-19 pandemic, mortality was falling for all ages, with a different behavior according to different ages and countries. It is indubitable that the changes in the population longevity induced by shock events, even transitory ones, affecting demographic projections, have financial implications in public spending as well as in pension plans and life insurance. The Short Term Mortality Fluctuations (STMF) data series, providing data of all-cause mortality fluctuations by week within each calendar year for 38 countries worldwide, offers a powerful tool to timely analyze the effects of the mortality shock caused by the COVID-19 pandemic on Italian mortality rates. This dataset, recently made available as a new component of the Human Mortality Database, is described and techniques for the integration of its data with the historical mortality time series are proposed. Then, to forecast mortality rates, the well-known stochastic mortality model proposed by Lee and Carter in 1992 is first considered, to be consistent with the internal processing of the Human Mortality Database, where exposures are estimated by the Lee–Carter model; empirical results are discussed both on the estimation of the model coefficients and on the forecast of the mortality rates. In detail, we show how the integration of the yearly aggregated STMF data in the HMD database allows the Lee–Carter model to capture the complex evolution of the Italian mortality rates, including the higher lethality for males and older people, in the years that follow a large shock event such as the COVID-19 pandemic. Finally, we discuss some key points concerning the improvement of existing models to take into account mortality shocks and evaluate their impact on future mortality dynamics.

死亡率的冲击，如流行病，威胁着大多数西方国家在过去几十年里所证实的整体寿命改善。事实上，就在2019冠状病毒病大流行之前，所有年龄段的死亡率都在下降，不同年龄和国家的死亡率有所不同。毫无疑问，影响人口预测的冲击事件所引起的人口寿命变化，即使是暂时的冲击事件，也对公共开支以及养恤金计划和人寿保险产生财政影响。短期死亡率波动(STMF)数据系列提供了全球38个国家在每个日历年内按周计算的全因死亡率波动数据，为及时分析COVID-19大流行造成的死亡率冲击对意大利死亡率的影响提供了有力工具。该数据集最近作为人类死亡率数据库的一个新组成部分提供了描述，并提出了将其数据与历史死亡率时间序列集成的技术。然后，为了预测死亡率，首先考虑由Lee和Carter于1992年提出的著名的随机死亡率模型，以与人类死亡率数据库的内部处理相一致，其中暴露是通过Lee - Carter模型估计的;本文从模型系数的估计和死亡率的预测两方面讨论了实证结果。详细地说，我们展示了如何在HMD数据库中整合年度汇总STMF数据，使Lee-Carter模型能够捕捉意大利死亡率的复杂演变，包括在2019冠状病毒病大流行等重大冲击事件发生后的几年中，男性和老年人的死亡率更高。最后，我们讨论了现有模型的改进要点，以考虑死亡率冲击并评估其对未来死亡率动态的影响。

{"title":"A Preliminary Investigation of a Single Shock Impact on Italian Mortality Rates Using STMF Data: A Case Study of COVID-19","authors":"M. Carfora, A. Orlando","doi":"10.3390/data8060107","DOIUrl":"https://doi.org/10.3390/data8060107","url":null,"abstract":"Mortality shocks, such as pandemics, threaten the consolidated longevity improvements, confirmed in the last decades for the majority of western countries. Indeed, just before the COVID-19 pandemic, mortality was falling for all ages, with a different behavior according to different ages and countries. It is indubitable that the changes in the population longevity induced by shock events, even transitory ones, affecting demographic projections, have financial implications in public spending as well as in pension plans and life insurance. The Short Term Mortality Fluctuations (STMF) data series, providing data of all-cause mortality fluctuations by week within each calendar year for 38 countries worldwide, offers a powerful tool to timely analyze the effects of the mortality shock caused by the COVID-19 pandemic on Italian mortality rates. This dataset, recently made available as a new component of the Human Mortality Database, is described and techniques for the integration of its data with the historical mortality time series are proposed. Then, to forecast mortality rates, the well-known stochastic mortality model proposed by Lee and Carter in 1992 is first considered, to be consistent with the internal processing of the Human Mortality Database, where exposures are estimated by the Lee–Carter model; empirical results are discussed both on the estimation of the model coefficients and on the forecast of the mortality rates. In detail, we show how the integration of the yearly aggregated STMF data in the HMD database allows the Lee–Carter model to capture the complex evolution of the Italian mortality rates, including the higher lethality for males and older people, in the years that follow a large shock event such as the COVID-19 pandemic. Finally, we discuss some key points concerning the improvement of existing models to take into account mortality shocks and evaluate their impact on future mortality dynamics.","PeriodicalId":55580,"journal":{"name":"Atomic Data and Nuclear Data Tables","volume":"44 1","pages":"107"},"PeriodicalIF":1.8,"publicationDate":"2023-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79409474","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Comparison of ARIMA and LSTM in Predicting Structural Deformation of Tunnels during Operation Period ARIMA与LSTM在隧道营运期结构变形预测中的比较

IF 1.8 3区物理与天体物理 Q2 PHYSICS, ATOMIC, MOLECULAR & CHEMICAL

Atomic Data and Nuclear Data Tables

Pub Date : 2023-06-13 DOI: 10.3390/data8060104

C. Duan, Min Hu, Hao Zhang

Accurately predicting the structural deformation trend of tunnels during operation is significant to improve the scientificity of tunnel safety maintenance. With the development of data science, structural deformation prediction methods based on time-series data have attracted attention. Auto Regressive Integrated Moving Average model (ARIMA) is a classical statistical analysis model, which is suitable for processing non-stationary time-series data. Long- and Short-Term Memory (LSTM) is a special cyclic neural network that can learn long-term dependent information in time series. Both are widely used in the field of temporal prediction. In view of the lack of time-series prediction in the tunnel deformation field, the body of this paper uses historical data of the Xinjian Road and the Dalian Road tunnel in Shanghai to propose a new way of modeling based on single points and road sections. ARIMA and LSTM models are applied in comprehensive experiments, and the results show that: (1) Both LSTM and ARIMA models have great performance for settlement and convergence deformation. (2) The overall robustness of ARIMA is better than that of LSTM, and it is more adaptable to the datasets. (3) The model prediction performance is closely related to the data quality. ARIMA has more stable performance under the lack of data volume, while LSTM has better performance with high-quality data and higher upper limit.

准确预测隧道运行过程中的结构变形趋势，对提高隧道安全维护的科学性具有重要意义。随着数据科学的发展，基于时间序列数据的结构变形预测方法受到了人们的关注。自回归积分移动平均模型(ARIMA)是一种经典的统计分析模型，适用于处理非平稳时间序列数据。长短期记忆(LSTM)是一种特殊的循环神经网络，可以学习时间序列中的长期依赖信息。两者都广泛应用于时间预测领域。针对隧道变形场缺乏时间序列预测的问题，本文主体利用上海新建路和大连路隧道的历史数据，提出了一种基于单点和路段的建模新方法。应用ARIMA和LSTM模型进行综合试验，结果表明:(1)LSTM和ARIMA模型均具有较好的沉降和收敛变形性能。(2) ARIMA的整体鲁棒性优于LSTM，对数据集的适应性更强。(3)模型的预测性能与数据质量密切相关。ARIMA在数据量不足的情况下性能更稳定，而LSTM在数据质量高、上限更高的情况下性能更好。

{"title":"Comparison of ARIMA and LSTM in Predicting Structural Deformation of Tunnels during Operation Period","authors":"C. Duan, Min Hu, Hao Zhang","doi":"10.3390/data8060104","DOIUrl":"https://doi.org/10.3390/data8060104","url":null,"abstract":"Accurately predicting the structural deformation trend of tunnels during operation is significant to improve the scientificity of tunnel safety maintenance. With the development of data science, structural deformation prediction methods based on time-series data have attracted attention. Auto Regressive Integrated Moving Average model (ARIMA) is a classical statistical analysis model, which is suitable for processing non-stationary time-series data. Long- and Short-Term Memory (LSTM) is a special cyclic neural network that can learn long-term dependent information in time series. Both are widely used in the field of temporal prediction. In view of the lack of time-series prediction in the tunnel deformation field, the body of this paper uses historical data of the Xinjian Road and the Dalian Road tunnel in Shanghai to propose a new way of modeling based on single points and road sections. ARIMA and LSTM models are applied in comprehensive experiments, and the results show that: (1) Both LSTM and ARIMA models have great performance for settlement and convergence deformation. (2) The overall robustness of ARIMA is better than that of LSTM, and it is more adaptable to the datasets. (3) The model prediction performance is closely related to the data quality. ARIMA has more stable performance under the lack of data volume, while LSTM has better performance with high-quality data and higher upper limit.","PeriodicalId":55580,"journal":{"name":"Atomic Data and Nuclear Data Tables","volume":"18 1","pages":"104"},"PeriodicalIF":1.8,"publicationDate":"2023-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81530484","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Theoretical level energies and transition data for 4p64d6, 4p54d7 and 4p64d54f configurations of W32+ ion W32+离子4p64d6、4p54d7和4p64d54f构型的理论能级和跃迁数据

IF 1.8 3区物理与天体物理 Q2 PHYSICS, ATOMIC, MOLECULAR & CHEMICAL

Atomic Data and Nuclear Data Tables

Pub Date : 2023-06-10 DOI: 10.1016/j.adt.2023.101597

R. Karpuškienė, R. Kisielius

The ab initio quasirelativistic approach developed specifically for the calculation of spectral parameters of highly charged ions has been used to determine transition data for the Mo-like tungsten ion W $^{32 +}$ . The configuration interaction method is utilized to include electron correlation effects. The relativistic effects are taken into account in the Breit–Pauli approximation. Level energies, radiative lifetimes $τ$ , Landé $g$ -factors are determined for the ground configuration 4p $^{6}$ 4d $^{6}$ and two excited configurations 4p $^{5}$ 4d $^{7}$ and 4p $^{6}$ 4d $^{5}$ 4f. The radiative transition wavelengths $λ$ , emission transition probabilities $A$ , weighted oscillator strengths $g f$ , and transition line strengths $S$ for the electric dipole, electric quadrupole, electric octupole, magnetic dipole, and magnetic quadrupole transitions among the fine-structure levels of these configurations are produced. The uncertainties of computed spectroscopic parameters are evaluated.

专门为计算高电荷离子的光谱参数而开发的从头算准相对论方法已用于确定类Mo钨离子W32+的跃迁数据。组态相互作用方法被用来包括电子相关效应。Breit–Pauli近似考虑了相对论效应。能级能量、辐射寿命τ、Landég因子是为基态4p64d6和两个激发态4p54d7和4p64d 54f确定的。产生了这些配置的精细结构能级之间的电偶极子、电四极、电八极、磁偶极子和磁四极跃迁的辐射跃迁波长λ、发射跃迁概率A、加权振荡器强度gf和跃迁线强度S。对计算的光谱参数的不确定性进行了评估。

{"title":"Theoretical level energies and transition data for 4p64d6, 4p54d7 and 4p64d54f configurations of W32+ ion","authors":"R. Karpuškienė, R. Kisielius","doi":"10.1016/j.adt.2023.101597","DOIUrl":"https://doi.org/10.1016/j.adt.2023.101597","url":null,"abstract":"<div>The ab initio quasirelativistic approach developed specifically for the calculation of spectral parameters of highly charged ions has been used to determine transition data for the Mo-like tungsten ion W<math><msup><mrow></mrow><mrow><mn>32</mn><mo>+</mo></mrow></msup></math>. The configuration interaction method is utilized to include electron correlation effects. The relativistic effects are taken into account in the Breit–Pauli approximation. Level energies, radiative lifetimes <math><mi>τ</mi></math>, Landé <math><mi>g</mi></math>-factors are determined for the ground configuration 4p<math><msup><mrow></mrow><mrow><mn>6</mn></mrow></msup></math>4d<math><msup><mrow></mrow><mrow><mn>6</mn></mrow></msup></math> and two excited configurations 4p<math><msup><mrow></mrow><mrow><mn>5</mn></mrow></msup></math>4d<math><msup><mrow></mrow><mrow><mn>7</mn></mrow></msup></math> and 4p<math><msup><mrow></mrow><mrow><mn>6</mn></mrow></msup></math>4d<math><msup><mrow></mrow><mrow><mn>5</mn></mrow></msup></math>4f. The radiative transition wavelengths <math><mi>λ</mi></math>, emission transition probabilities <math><mi>A</mi></math>, weighted oscillator strengths <math><mrow><mi>g</mi><mi>f</mi></mrow></math>, and transition line strengths <math><mi>S</mi></math> for the electric dipole, electric quadrupole, electric octupole, magnetic dipole, and magnetic quadrupole transitions among the fine-structure levels of these configurations are produced. The uncertainties of computed spectroscopic parameters are evaluated.</div>","PeriodicalId":55580,"journal":{"name":"Atomic Data and Nuclear Data Tables","volume":"154 ","pages":"Article 101597"},"PeriodicalIF":1.8,"publicationDate":"2023-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49743891","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Table of hyperfine anomaly in atomic systems — 2023 2023年原子系统超精细异常表

IF 1.8 3区物理与天体物理 Q2 PHYSICS, ATOMIC, MOLECULAR & CHEMICAL

Atomic Data and Nuclear Data Tables

Pub Date : 2023-06-09 DOI: 10.1016/j.adt.2023.101589

J.R. Persson

This table is an updated compilation of experimental values of the magnetic hyperfine anomaly in atomic and ionic systems. The literature search covers the period up to December 2022. A short discussion on general trends of the hyperfine anomaly and the theoretical developments is included.

该表是原子和离子系统中磁超精细异常实验值的最新汇编。文献检索涵盖了截至2022年12月的时期。简要讨论了超精细异常的一般趋势和理论发展。

引用次数: 0

Comment on “Atomic structure and electron impact excitation of Al-like ions (Ga–Br)” by HB Wang and G Jiang in At. Data Nucl. Data Tables 148 (2022) 101532 对《类al离子(Ga-Br)的原子结构和电子冲击激发》的评论数据诊断。数据表148 (2022)101532

IF 1.8 3区物理与天体物理 Q2 PHYSICS, ATOMIC, MOLECULAR & CHEMICAL

Atomic Data and Nuclear Data Tables

Pub Date : 2023-06-08 DOI: 10.1016/j.adt.2023.101588

Kanti M. Aggarwal, Ken W. Smith

In a recent paper, Wang and Jiang (At. Data Nucl. Data Tables 148 (2022) 101532) have reported data for energy levels, radiative rates (A-values), and effective collision strengths ( $Υ$ ) for some transitions of five Al-like ions, namely Ga XIX, Ge XX, As XXI, Se XXII, and Br XXIII. On a closer examination we find that their reported data for energy levels and A-values are generally correct, but not for $Υ$ . Their $Υ$ values, for all transitions (allowed or forbidden) and for all ions, invariably decrease at higher temperatures. This is mainly because they have adopted a limited range of electron energies for the calculations of collision strengths. We demonstrate this with our calculations with the Flexible Atomic Code (FAC), and conclude that their $Υ$ values are inaccurate, unreliable, and should not be adopted in any applications or modelling analysis.

在最近的一篇论文中，王和姜（At.Data Nucl.Data Tables 148（2022）101532）报道了五种类铝离子（即Ga XIX、Ge XX、As XXII、Se XXII和Br XXIII）的一些跃迁的能级、辐射率（a值）和有效碰撞强度（γ）的数据。在更仔细的检查中，我们发现他们报告的能级和a值的数据通常是正确的，但对γ来说不是。对于所有跃迁（允许或禁止）和所有离子，它们的γ值在更高的温度下总是会降低。这主要是因为他们采用了有限范围的电子能量来计算碰撞强度。我们用灵活原子代码（FAC）的计算证明了这一点，并得出结论，它们的γ值不准确、不可靠，不应用于任何应用或建模分析。

引用次数: 0

首页上一页

下一页尾页

类型

全部化学•材料生命科学医学物理工程技术环境•农林材料科学地球科学法学管理学化学环境科学与生态学计算机科学教育学经济学农林科学人文科学生物学数学物理与天体物理心理学综合性期刊其他工业工程理学历史学农学文学信息工程

数据库

全部 ACS Publications Elsevier ieeexplore Springer The Royal Society of Chemistry Wiley

期刊

Atomic Data and Nuclear Data Tables

全部 Acc. Chem. Res. ACS Applied Bio Materials ACS Appl. Electron. Mater. ACS Appl. Energy Mater. ACS Appl. Mater. Interfaces ACS Appl. Nano Mater. ACS Appl. Polym. Mater. ACS BIOMATER-SCI ENG ACS Catal. ACS Cent. Sci. ACS Chem. Biol. ACS Chemical Health & Safety ACS Chem. Neurosci. ACS Comb. Sci. ACS Earth Space Chem. ACS Energy Lett. ACS Infect. Dis. ACS Macro Lett. ACS Mater. Lett. ACS Med. Chem. Lett. ACS Nano ACS Omega ACS Photonics ACS Sens. ACS Sustainable Chem. Eng. ACS Synth. Biol. Anal. Chem. BIOCHEMISTRY-US Bioconjugate Chem. BIOMACROMOLECULES Chem. Res. Toxicol. Chem. Rev. Chem. Mater. CRYST GROWTH DES ENERG FUEL Environ. Sci. Technol. Environ. Sci. Technol. Lett. Eur. J. Inorg. Chem. IND ENG CHEM RES Inorg. Chem. J. Agric. Food. Chem. J. Chem. Eng. Data J. Chem. Educ. J. Chem. Inf. Model. J. Chem. Theory Comput. J. Med. Chem. J. Nat. Prod. J PROTEOME RES J. Am. Chem. Soc. LANGMUIR MACROMOLECULES Mol. Pharmaceutics Nano Lett. Org. Lett. ORG PROCESS RES DEV ORGANOMETALLICS J. Org. Chem. J. Phys. Chem. J. Phys. Chem. A J. Phys. Chem. B J. Phys. Chem. C J. Phys. Chem. Lett. Analyst Anal. Methods Biomater. Sci. Catal. Sci. Technol. Chem. Commun. Chem. Soc. Rev. CHEM EDUC RES PRACT CRYSTENGCOMM Dalton Trans. Energy Environ. Sci. ENVIRON SCI-NANO ENVIRON SCI-PROC IMP ENVIRON SCI-WAT RES Faraday Discuss. Food Funct. Green Chem. Inorg. Chem. Front. Integr. Biol. J. Anal. At. Spectrom. J. Mater. Chem. A J. Mater. Chem. B J. Mater. Chem. C Lab Chip Mater. Chem. Front. Mater. Horiz. MEDCHEMCOMM Metallomics Mol. Biosyst. Mol. Syst. Des. Eng. Nanoscale Nanoscale Horiz. Nat. Prod. Rep. New J. Chem. Org. Biomol. Chem. Org. Chem. Front. PHOTOCH PHOTOBIO SCI PCCP Polym. Chem.

﹀