Pub Date : 2023-05-26DOI: 10.1016/j.adt.2023.101586
Haadi Umer , Yuri Ralchenko , Igor Bray , Dmitry V. Fursa
A comprehensive set of cross sections for electron scattering from the ground and first four excited states of tin has been calculated using the Relativistic Convergent Close-Coupling method. Elastic scattering, momentum transfer, total scattering, and total-inelastic scattering cross sections have been produced for the , and states of atomic tin over a projectile energy range of 0.1 eV to 1000 eV. Over the same projectile energy range, state-resolved cross sections for excitations to the , , and manifolds from the ground and first four excited states of tin are presented. Total single-ionisation cross sections have been calculated which account for the direct ionisation of electrons in the valence and closed shells, as well as indirect contributions from excitation auto-ionisation. These ionisation cross sections are presented for projectile energies up to 1000 eV. Maxwellian rate coefficients have been calculated for all studied transitions over electron temperatures ranging from 0.5 eV to 200 eV and fitted with simple formulas. The fit coefficients are tabulated for use in modelling applications.
用相对论收敛紧密耦合的方法计算了锡的电子从地面和前四个激发态散射的截面。在0.1 eV ~ 1000 eV的抛射能量范围内，得到了原子锡的5p23P0、1、2、1D2和1so0态的弹性散射、动量传递、总散射和总非弹性散射截面。在相同的抛射能量范围内，给出了从锡的基态和前四个激发态激发到5p2、5p6s、5p5d和5p6p流形的态分辨截面。计算了总单电离截面，其中包括价态5p和闭合5s壳层电子的直接电离，以及激发自电离的间接贡献。这些电离截面给出了能量高达1000 eV的抛射体。在0.5 eV到200 eV的电子温度范围内，计算了所有研究跃迁的麦克斯韦速率系数，并用简单的公式拟合。拟合系数已制成表格，以供建模应用使用。
{"title":"Electron scattering cross sections for the ground and excited states of tin","authors":"Haadi Umer , Yuri Ralchenko , Igor Bray , Dmitry V. Fursa","doi":"10.1016/j.adt.2023.101586","DOIUrl":"10.1016/j.adt.2023.101586","url":null,"abstract":"<div><p><span>A comprehensive set of cross sections for electron scattering from the ground and first four excited states of tin has been calculated using the Relativistic Convergent Close-Coupling method. Elastic scattering, momentum transfer, total scattering, and total-inelastic scattering cross sections have been produced for the </span><span><math><mrow><mn>5</mn><msup><mrow><mi>p</mi></mrow><mrow><mn>2</mn></mrow></msup></mrow></math></span>\u0000<span><math><mrow><msup><mrow></mrow><mrow><mn>3</mn></mrow></msup><msub><mrow><mi>P</mi></mrow><mrow><mn>0</mn><mo>,</mo><mn>1</mn><mo>,</mo><mn>2</mn></mrow></msub></mrow></math></span>, <span><math><mrow><msup><mrow></mrow><mrow><mn>1</mn></mrow></msup><msub><mrow><mi>D</mi></mrow><mrow><mn>2</mn></mrow></msub></mrow></math></span> and <span><math><mrow><msup><mrow></mrow><mrow><mn>1</mn></mrow></msup><msub><mrow><mi>S</mi></mrow><mrow><mn>0</mn></mrow></msub></mrow></math></span> states of atomic tin over a projectile energy range of 0.1 eV to 1000 eV. Over the same projectile energy range, state-resolved cross sections for excitations to the <span><math><mrow><mn>5</mn><msup><mrow><mi>p</mi></mrow><mrow><mn>2</mn></mrow></msup></mrow></math></span>, <span><math><mrow><mn>5</mn><mi>p</mi><mn>6</mn><mi>s</mi></mrow></math></span>, <span><math><mrow><mn>5</mn><mi>p</mi><mn>5</mn><mi>d</mi></mrow></math></span> and <span><math><mrow><mn>5</mn><mi>p</mi><mn>6</mn><mi>p</mi></mrow></math></span> manifolds from the ground and first four excited states of tin are presented. Total single-ionisation cross sections have been calculated which account for the direct ionisation of electrons in the valence <span><math><mrow><mn>5</mn><mi>p</mi></mrow></math></span> and closed <span><math><mrow><mn>5</mn><mi>s</mi></mrow></math></span><span><span> shells, as well as indirect contributions from excitation auto-ionisation. These ionisation cross sections are presented for projectile energies up to 1000 eV. Maxwellian rate coefficients have been calculated for all studied transitions over </span>electron temperatures ranging from 0.5 eV to 200 eV and fitted with simple formulas. The fit coefficients are tabulated for use in modelling applications.</span></p></div>","PeriodicalId":55580,"journal":{"name":"Atomic Data and Nuclear Data Tables","volume":"154 ","pages":"Article 101586"},"PeriodicalIF":1.8,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44142778","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}
Jihye Park, S. Na, Jung-Sook Yoon, Seoree Kim, S. Chun, Jae Jun Kim, Young-Du Kim, Young‐Ho Ahn, Keunsoo Kang, Y. Ko
MicroRNA transcriptomes from fresh tumors and the adjacent normal tissues were profiled in 10 Korean patients diagnosed with lung adenocarcinoma using a next-generation sequencing (NGS) technique called miRNA-seq. The sequencing quality was assessed using FastQC, and low-quality or adapter-contaminated portions of the reads were removed using Trim Galore. Quality-assured reads were analyzed using miRDeep2 and Bowtie. The abundance of known miRNAs was estimated using the reads per million (RPM) normalization method. Subsequently, using DESeq2 and Wx, we identified differentially expressed miRNAs and potential miRNA biomarkers for lung adenocarcinoma tissues compared to adjacent normal tissues, respectively. We defined reliable miRNA biomarkers for lung adenocarcinoma as those detected by both methods. The miRNA-seq data are available in the Gene Expression Omnibus (GEO) database under accession number GSE196633, and all processed data can be accessed via the Mendeley data website.
利用新一代测序(NGS)技术miRNA-seq，对10名确诊为肺腺癌的韩国患者的新肿瘤和邻近正常组织的MicroRNA转录组进行了分析。使用FastQC评估测序质量，使用Trim Galore去除低质量或适配器污染的读取部分。使用miRDeep2和Bowtie分析有质量保证的读数。使用reads per million (RPM)归一化方法估计已知mirna的丰度。随后，我们使用DESeq2和Wx分别鉴定了肺腺癌组织与邻近正常组织相比差异表达的miRNA和潜在的miRNA生物标志物。我们将两种方法检测到的肺腺癌miRNA生物标志物定义为可靠的。miRNA-seq数据可在Gene Expression Omnibus (GEO)数据库中获得，登录号为GSE196633，所有处理后的数据可通过Mendeley数据网站访问。
{"title":"MicroRNA Profiling of Fresh Lung Adenocarcinoma and Adjacent Normal Tissues from Ten Korean Patients Using miRNA-Seq","authors":"Jihye Park, S. Na, Jung-Sook Yoon, Seoree Kim, S. Chun, Jae Jun Kim, Young-Du Kim, Young‐Ho Ahn, Keunsoo Kang, Y. Ko","doi":"10.3390/data8060094","DOIUrl":"https://doi.org/10.3390/data8060094","url":null,"abstract":"MicroRNA transcriptomes from fresh tumors and the adjacent normal tissues were profiled in 10 Korean patients diagnosed with lung adenocarcinoma using a next-generation sequencing (NGS) technique called miRNA-seq. The sequencing quality was assessed using FastQC, and low-quality or adapter-contaminated portions of the reads were removed using Trim Galore. Quality-assured reads were analyzed using miRDeep2 and Bowtie. The abundance of known miRNAs was estimated using the reads per million (RPM) normalization method. Subsequently, using DESeq2 and Wx, we identified differentially expressed miRNAs and potential miRNA biomarkers for lung adenocarcinoma tissues compared to adjacent normal tissues, respectively. We defined reliable miRNA biomarkers for lung adenocarcinoma as those detected by both methods. The miRNA-seq data are available in the Gene Expression Omnibus (GEO) database under accession number GSE196633, and all processed data can be accessed via the Mendeley data website.","PeriodicalId":55580,"journal":{"name":"Atomic Data and Nuclear Data Tables","volume":"98 1","pages":"94"},"PeriodicalIF":1.8,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89110342","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}
P. Inostroza, Eric Carmona, Å. Arrhenius, M. Krauss, W. Brack, T. Backhaus
The aquatic environment faces increasing threats from a variety of unregulated organic chemicals originating from human activities, collectively known as chemicals of emerging concern (CECs). These include pharmaceuticals, personal-care products, pesticides, surfactants, industrial chemicals, and their transformation products. CECs enter aquatic environments through various sources, including effluents from wastewater treatment plants, industrial facilities, runoff from agricultural and residential areas, as well as accidental spills. Data on the occurrence of CECs in the marine environment are scarce, and more information is needed to assess the chemical and ecological status of water bodies, and to prioritize toxic chemicals for further studies or risk assessment. In this study, we describe a monitoring campaign targeting CECs in surface waters at the Swedish west coast using, for the first time, an on-site large volume solid phase extraction (LVSPE) device. We detected up to 80 and 227 CECs in marine sites and the wastewater treatment plant (WWTP) effluent, respectively. The dataset will contribute to defining pollution fingerprints and assessing the chemical status of marine and freshwater systems affected by industrial hubs, agricultural areas, and the discharge of urban wastewater.
{"title":"Target Screening of Chemicals of Emerging Concern (CECs) in Surface Waters of the Swedish West Coast","authors":"P. Inostroza, Eric Carmona, Å. Arrhenius, M. Krauss, W. Brack, T. Backhaus","doi":"10.3390/data8060093","DOIUrl":"https://doi.org/10.3390/data8060093","url":null,"abstract":"The aquatic environment faces increasing threats from a variety of unregulated organic chemicals originating from human activities, collectively known as chemicals of emerging concern (CECs). These include pharmaceuticals, personal-care products, pesticides, surfactants, industrial chemicals, and their transformation products. CECs enter aquatic environments through various sources, including effluents from wastewater treatment plants, industrial facilities, runoff from agricultural and residential areas, as well as accidental spills. Data on the occurrence of CECs in the marine environment are scarce, and more information is needed to assess the chemical and ecological status of water bodies, and to prioritize toxic chemicals for further studies or risk assessment. In this study, we describe a monitoring campaign targeting CECs in surface waters at the Swedish west coast using, for the first time, an on-site large volume solid phase extraction (LVSPE) device. We detected up to 80 and 227 CECs in marine sites and the wastewater treatment plant (WWTP) effluent, respectively. The dataset will contribute to defining pollution fingerprints and assessing the chemical status of marine and freshwater systems affected by industrial hubs, agricultural areas, and the discharge of urban wastewater.","PeriodicalId":55580,"journal":{"name":"Atomic Data and Nuclear Data Tables","volume":"1 1","pages":"93"},"PeriodicalIF":1.8,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90874411","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}
Jihye Park, Kyuho Kang, Y. Son, Kwang Seok Kim, Keunsoo Kang, Hae-June Lee
Low-dose radiation refers to exposure to ionizing radiation at levels that are generally considered safe and not expected to cause immediate health effects. However, the effects of low-dose radiation are still not fully understood, and research in this area is ongoing. In this study, we investigated the alterations in gene expression profiles of human aortic endothelial cells (HAECs) and diabetic human aortic endothelial cells (T2D-HAECs) derived from patients with type 2 diabetes. To this end, we used RNA-seq to profile the transcriptomes of cells exposed to varying doses of low-dose radiation (0.1 Gy, 0.5 Gy, and 2.0 Gy) and compared them to a control group with no radiation exposure. Differentially expressed genes and enriched pathways were identified using the DESeq2 and gene set enrichment analysis (GSEA) methods, respectively. The data generated in this study are publicly available through the gene expression omnibus (GEO) database with the accession number GSE228572. This study provides a valuable resource for examining the effects of low-dose radiation on HAECs and T2D-HAECs, thereby contributing to a better understanding of the potential human health risks associated with low-dose radiation exposure.
{"title":"Low-Dose Radiation-Induced Transcriptomic Changes in Diabetic Aortic Endothelial Cells","authors":"Jihye Park, Kyuho Kang, Y. Son, Kwang Seok Kim, Keunsoo Kang, Hae-June Lee","doi":"10.3390/data8050092","DOIUrl":"https://doi.org/10.3390/data8050092","url":null,"abstract":"Low-dose radiation refers to exposure to ionizing radiation at levels that are generally considered safe and not expected to cause immediate health effects. However, the effects of low-dose radiation are still not fully understood, and research in this area is ongoing. In this study, we investigated the alterations in gene expression profiles of human aortic endothelial cells (HAECs) and diabetic human aortic endothelial cells (T2D-HAECs) derived from patients with type 2 diabetes. To this end, we used RNA-seq to profile the transcriptomes of cells exposed to varying doses of low-dose radiation (0.1 Gy, 0.5 Gy, and 2.0 Gy) and compared them to a control group with no radiation exposure. Differentially expressed genes and enriched pathways were identified using the DESeq2 and gene set enrichment analysis (GSEA) methods, respectively. The data generated in this study are publicly available through the gene expression omnibus (GEO) database with the accession number GSE228572. This study provides a valuable resource for examining the effects of low-dose radiation on HAECs and T2D-HAECs, thereby contributing to a better understanding of the potential human health risks associated with low-dose radiation exposure.","PeriodicalId":55580,"journal":{"name":"Atomic Data and Nuclear Data Tables","volume":"8 1","pages":"92"},"PeriodicalIF":1.8,"publicationDate":"2023-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80145840","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}
A. Soloviev, A. Petrunin, Sofia Gvozdik, R. Sidorov
This paper presents a set of various geological and geophysical data for the Arctic zone, including some detailed models for the eastern part of the Russian Arctic zone. This hard-to-access territory has a complex geological structure, which is poorly studied by direct geophysical methods. Therefore, these data can be used in an integrative analysis for different purposes. These are the gravity field, heat flow, and various seismic tomography models. The gravity field data include several reductions calculated during our preceding studies, which are more appropriate for the study of the Earth’s interiors than the initial free air anomalies. Specifically, these are the Bouguer, isostatic, and decompensative gravity anomalies. A surface heat flow map included in the dataset is based on a joint inversion of multiple geophysical data constrained by the observations from the International Heat Flow Commission catalog. Available seismic tomography models were analyzed to select the best one for further investigation. We provide the models for the sedimentary cover and the Moho depth, which are significantly improved compared to the existing ones. The database provides a basis for qualitative and quantitative analysis of the region.
{"title":"A Set of Geophysical Fields for Modeling of the Lithosphere Structure and Dynamics in the Russian Arctic Zone","authors":"A. Soloviev, A. Petrunin, Sofia Gvozdik, R. Sidorov","doi":"10.3390/data8050091","DOIUrl":"https://doi.org/10.3390/data8050091","url":null,"abstract":"This paper presents a set of various geological and geophysical data for the Arctic zone, including some detailed models for the eastern part of the Russian Arctic zone. This hard-to-access territory has a complex geological structure, which is poorly studied by direct geophysical methods. Therefore, these data can be used in an integrative analysis for different purposes. These are the gravity field, heat flow, and various seismic tomography models. The gravity field data include several reductions calculated during our preceding studies, which are more appropriate for the study of the Earth’s interiors than the initial free air anomalies. Specifically, these are the Bouguer, isostatic, and decompensative gravity anomalies. A surface heat flow map included in the dataset is based on a joint inversion of multiple geophysical data constrained by the observations from the International Heat Flow Commission catalog. Available seismic tomography models were analyzed to select the best one for further investigation. We provide the models for the sedimentary cover and the Moho depth, which are significantly improved compared to the existing ones. The database provides a basis for qualitative and quantitative analysis of the region.","PeriodicalId":55580,"journal":{"name":"Atomic Data and Nuclear Data Tables","volume":"1 1","pages":"91"},"PeriodicalIF":1.8,"publicationDate":"2023-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84657817","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}
The number of reviews from customers on travel websites and platforms is quickly increasing. They provide people with the ability to write reviews about their experience with respect to service quality, location, room, and cleanliness, thereby helping others before booking hotels. Many people fail to consider hotel bookings because the numerous reviews take a long time to read, and many are in a non-native language. Thus, hotel businesses need an efficient process to analyze and categorize the polarity of reviews as positive, negative, or neutral. In particular, low-resource languages such as Thai have greater limitations in terms of resources to classify sentiment polarity. In this paper, a sentiment analysis method is proposed for Thai sentiment classification in the hotel domain. Firstly, the Word2Vec technique (the continuous bag-of-words (CBOW) and skip-gram approaches) was applied to create word embeddings of different vector dimensions. Secondly, each word embedding model was combined with deep learning (DL) models to observe the impact of each word vector dimension result. We compared the performance of nine DL models (CNN, LSTM, Bi-LSTM, GRU, Bi-GRU, CNN-LSTM, CNN-BiLSTM, CNN-GRU, and CNN-BiGRU) with different numbers of layers to evaluate their performance in polarity classification. The dataset was classified using the FastText and BERT pre-trained models to carry out the sentiment polarity classification. Finally, our experimental results show that the WangchanBERTa model slightly improved the accuracy, producing a value of 0.9225, and the skip-gram and CNN model combination outperformed other DL models, reaching an accuracy of 0.9170. From the experiments, we found that the word vector dimensions, hyperparameter values, and the number of layers of the DL models affected the performance of sentiment classification. Our research provides guidance for setting suitable hyperparameter values to improve the accuracy of sentiment classification for the Thai language in the hotel domain.
{"title":"An Efficient Deep Learning for Thai Sentiment Analysis","authors":"Nattawat Khamphakdee, Pusadee Seresangtakul","doi":"10.3390/data8050090","DOIUrl":"https://doi.org/10.3390/data8050090","url":null,"abstract":"The number of reviews from customers on travel websites and platforms is quickly increasing. They provide people with the ability to write reviews about their experience with respect to service quality, location, room, and cleanliness, thereby helping others before booking hotels. Many people fail to consider hotel bookings because the numerous reviews take a long time to read, and many are in a non-native language. Thus, hotel businesses need an efficient process to analyze and categorize the polarity of reviews as positive, negative, or neutral. In particular, low-resource languages such as Thai have greater limitations in terms of resources to classify sentiment polarity. In this paper, a sentiment analysis method is proposed for Thai sentiment classification in the hotel domain. Firstly, the Word2Vec technique (the continuous bag-of-words (CBOW) and skip-gram approaches) was applied to create word embeddings of different vector dimensions. Secondly, each word embedding model was combined with deep learning (DL) models to observe the impact of each word vector dimension result. We compared the performance of nine DL models (CNN, LSTM, Bi-LSTM, GRU, Bi-GRU, CNN-LSTM, CNN-BiLSTM, CNN-GRU, and CNN-BiGRU) with different numbers of layers to evaluate their performance in polarity classification. The dataset was classified using the FastText and BERT pre-trained models to carry out the sentiment polarity classification. Finally, our experimental results show that the WangchanBERTa model slightly improved the accuracy, producing a value of 0.9225, and the skip-gram and CNN model combination outperformed other DL models, reaching an accuracy of 0.9170. From the experiments, we found that the word vector dimensions, hyperparameter values, and the number of layers of the DL models affected the performance of sentiment classification. Our research provides guidance for setting suitable hyperparameter values to improve the accuracy of sentiment classification for the Thai language in the hotel domain.","PeriodicalId":55580,"journal":{"name":"Atomic Data and Nuclear Data Tables","volume":"08 1","pages":"90"},"PeriodicalIF":1.8,"publicationDate":"2023-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86201794","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}
This paper presents a unique and extensive dataset containing over 33 million entries with pairs in the form “spelling error → correction” from ispravi.me, the most popular Croatian online spellchecking service, collected since 2008. The dataset, compiled from the contribution of nearly 900,000 users, is a valuable resource for researchers and developers in the field of natural language processing (NLP), improving spellcheck accuracy, and language learning applications. The dataset may be used to accomplish several goals: (1) improving spellchecking accuracy by incorporating common user corrections and reducing false positives and negatives; (2) helping language learners identify common errors and learn correct spelling through targeted feedback; (3) analyzing data trends and patterns to uncover the most common spelling errors and their underlying causes; (4) identifying and evaluating factors that influence typing input; (5) improving NLP applications such as text recognition and machine translation. Tasks specific to the Croatian language include the creation of a letter-level confusion matrix and the refinement of word suggestions based on historical usage of the service. This comprehensive dataset provides researchers and practitioners with a wealth of information, opening the path for advancements in spellchecking, language learning, and NLP applications in the Croatian language.
{"title":"A Comprehensive Dataset of Spelling Errors and Users' Corrections in Croatian Language","authors":"G. Gledec, M. Horvat, M. Mikuc, B. Blašković","doi":"10.3390/data8050089","DOIUrl":"https://doi.org/10.3390/data8050089","url":null,"abstract":"This paper presents a unique and extensive dataset containing over 33 million entries with pairs in the form “spelling error → correction” from ispravi.me, the most popular Croatian online spellchecking service, collected since 2008. The dataset, compiled from the contribution of nearly 900,000 users, is a valuable resource for researchers and developers in the field of natural language processing (NLP), improving spellcheck accuracy, and language learning applications. The dataset may be used to accomplish several goals: (1) improving spellchecking accuracy by incorporating common user corrections and reducing false positives and negatives; (2) helping language learners identify common errors and learn correct spelling through targeted feedback; (3) analyzing data trends and patterns to uncover the most common spelling errors and their underlying causes; (4) identifying and evaluating factors that influence typing input; (5) improving NLP applications such as text recognition and machine translation. Tasks specific to the Croatian language include the creation of a letter-level confusion matrix and the refinement of word suggestions based on historical usage of the service. This comprehensive dataset provides researchers and practitioners with a wealth of information, opening the path for advancements in spellchecking, language learning, and NLP applications in the Croatian language.","PeriodicalId":55580,"journal":{"name":"Atomic Data and Nuclear Data Tables","volume":"22 1","pages":"89"},"PeriodicalIF":1.8,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78999940","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}
A. Maulit, A. Nugumanova, Kurmash Apayev, Y. Baiburin, M. Sutula
This study introduces a dataset of crop imagery captured during the 2022 growing season in the Eastern Kazakhstan region. The images were acquired using a multispectral camera mounted on an unmanned aerial vehicle (DJI Phantom 4). The agricultural land, encompassing 27 hectares and cultivated with wheat, barley, and soybean, was subjected to five aerial multispectral photography sessions throughout the growing season. This facilitated thorough monitoring of the most important phenological stages of crop development in the experimental design, which consisted of 27 plots, each covering one hectare. The collected imagery underwent enhancement and expansion, integrating a sixth band that embodies the normalized difference vegetation index (NDVI) values in conjunction with the original five multispectral bands (Blue, Green, Red, Red Edge, and Near Infrared Red). This amplification enables a more effective evaluation of vegetation health and growth, rendering the enriched dataset a valuable resource for the progression and validation of crop monitoring and yield prediction models, as well as for the exploration of precision agriculture methodologies.
{"title":"A Multispectral UAV Imagery Dataset of Wheat, Soybean and Barley Crops in East Kazakhstan","authors":"A. Maulit, A. Nugumanova, Kurmash Apayev, Y. Baiburin, M. Sutula","doi":"10.3390/data8050088","DOIUrl":"https://doi.org/10.3390/data8050088","url":null,"abstract":"This study introduces a dataset of crop imagery captured during the 2022 growing season in the Eastern Kazakhstan region. The images were acquired using a multispectral camera mounted on an unmanned aerial vehicle (DJI Phantom 4). The agricultural land, encompassing 27 hectares and cultivated with wheat, barley, and soybean, was subjected to five aerial multispectral photography sessions throughout the growing season. This facilitated thorough monitoring of the most important phenological stages of crop development in the experimental design, which consisted of 27 plots, each covering one hectare. The collected imagery underwent enhancement and expansion, integrating a sixth band that embodies the normalized difference vegetation index (NDVI) values in conjunction with the original five multispectral bands (Blue, Green, Red, Red Edge, and Near Infrared Red). This amplification enables a more effective evaluation of vegetation health and growth, rendering the enriched dataset a valuable resource for the progression and validation of crop monitoring and yield prediction models, as well as for the exploration of precision agriculture methodologies.","PeriodicalId":55580,"journal":{"name":"Atomic Data and Nuclear Data Tables","volume":"323 1","pages":"88"},"PeriodicalIF":1.8,"publicationDate":"2023-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75041647","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}
V. Shvartz, Eldar Sizhazhev, M. Sokolskaya, S. Koroleva, Soslan T. Enginoev, S. Kruchinova, Elena Shvartz, E. Golukhova
Many previous studies have demonstrated that transcutaneous vagus nerve stimulation (VNS) has the potential to exhibit therapeutic effects similar to its invasive counterpart. An objective assessment of VNS requires a reliable biomarker of successful vagal activation. Although many potential biomarkers have been proposed, most studies have focused on heart rate variability (HRV). Despite the physiological rationale for HRV as a biomarker for assessing vagal stimulation, data on its effects on HRV are equivocal. To further advance this field, future studies investigating VNS should contain adequate methodological specifics that make it possible to compare the results between studies, to replicate studies, and to enhance the safety of study participants. This article describes the design and methodology of a randomized study evaluating the effect of short-term noninvasive stimulation of the auricular branch of the vagus nerve on parameters of HRV. Primary records of rhythmograms of all the subjects, as well as a dataset with clinical, instrumental, and laboratory data of all the current study subjects are in the public domain for possible secondary analysis to all interested researchers. The physiological interpretation of the obtained data is not considered in the article.
{"title":"The Effect of Short-Term Transcutaneous Electrical Stimulation of Auricular Vagus Nerve on Parameters of Heart Rate Variability","authors":"V. Shvartz, Eldar Sizhazhev, M. Sokolskaya, S. Koroleva, Soslan T. Enginoev, S. Kruchinova, Elena Shvartz, E. Golukhova","doi":"10.3390/data8050087","DOIUrl":"https://doi.org/10.3390/data8050087","url":null,"abstract":"Many previous studies have demonstrated that transcutaneous vagus nerve stimulation (VNS) has the potential to exhibit therapeutic effects similar to its invasive counterpart. An objective assessment of VNS requires a reliable biomarker of successful vagal activation. Although many potential biomarkers have been proposed, most studies have focused on heart rate variability (HRV). Despite the physiological rationale for HRV as a biomarker for assessing vagal stimulation, data on its effects on HRV are equivocal. To further advance this field, future studies investigating VNS should contain adequate methodological specifics that make it possible to compare the results between studies, to replicate studies, and to enhance the safety of study participants. This article describes the design and methodology of a randomized study evaluating the effect of short-term noninvasive stimulation of the auricular branch of the vagus nerve on parameters of HRV. Primary records of rhythmograms of all the subjects, as well as a dataset with clinical, instrumental, and laboratory data of all the current study subjects are in the public domain for possible secondary analysis to all interested researchers. The physiological interpretation of the obtained data is not considered in the article.","PeriodicalId":55580,"journal":{"name":"Atomic Data and Nuclear Data Tables","volume":"5 1","pages":"87"},"PeriodicalIF":1.8,"publicationDate":"2023-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87312891","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}
S. Strautiņa, I. Kalnina, E. Kaufmane, K. Sudars, I. Namatēvs, Arturs Nikulins, Edgars Edelmers
The RaspberrySet dataset is a valuable resource for those working in the field of agriculture, particularly in the selection and breeding of ecologically adaptable berry cultivars. This is because long-term changes in temperature and weather patterns have made it increasingly important for crops to be able to adapt to their environment. To assess the suitability of different cultivars or to make yield predictions, it is necessary to describe and evaluate berries’ characteristics at various growth stages. This process is typically carried out visually, but it can be time-consuming and labor-intensive, requiring significant expert knowledge. The RaspberrySet dataset was created to assist with this process, and it includes images of raspberry berries at five different stages of development. These stages are flower buds, flowers, unripe berries, and ripe berries. All these stages of raspberry images classified buds, damaged buds, flowers, unripe berries, and ripe berries and were annotated using ground truth ROI and presented in YOLO format. The dataset includes 2039 high-resolution RGB images, with a total of 46,659 annotations provided by experts using Label Studio software (1.7.1). The images were taken in various weather conditions, at different times of the day, and from different angles, and they include fully visible buds, flowers, berries, and partially obscured buds. This dataset is intended to improve the efficiency of berry breeding and yield estimation and to identify the raspberry phenotype more accurately. It may also be useful for breeding other fruit crops, as it allows for the reliable detection and phenotyping of yield components at different stages of development. By providing a homogenized dataset of images taken on-site at the Institute of Horticulture in Dobele, Latvia, the RaspberrySet dataset offers a valuable resource for those working in horticulture.
覆盆子集数据集是农业领域工作人员的宝贵资源，特别是在生态适应性浆果品种的选择和育种方面。这是因为温度和天气模式的长期变化使得作物适应环境的能力变得越来越重要。为了评价不同品种的适宜性或进行产量预测，有必要描述和评价不同生育期浆果的特性。这个过程通常是可视化的，但它可能是耗时和劳动密集型的，需要大量的专家知识。树莓集数据集的创建是为了帮助这个过程，它包括树莓在五个不同的发展阶段的图像。这些阶段是花蕾、花朵、未成熟的浆果和成熟的浆果。这些阶段的覆盆子图像对芽、破损芽、花、未成熟浆果和成熟浆果进行分类，并使用ground truth ROI进行标注，以YOLO格式呈现。该数据集包括2039张高分辨率RGB图像，专家使用Label Studio软件(1.7.1)提供了46,659条注释。这些照片是在不同的天气条件下，在一天中的不同时间，从不同的角度拍摄的，其中包括完全可见的花蕾，花朵，浆果和部分模糊的花蕾。该数据集旨在提高覆盆子育种和产量估计的效率，并更准确地识别覆盆子表型。它也可能对其他水果作物的育种有用，因为它允许在不同发育阶段对产量成分进行可靠的检测和表型分析。通过提供在拉脱维亚多贝勒园艺研究所现场拍摄的图像的均匀化数据集，覆盆子集数据集为园艺工作者提供了宝贵的资源。
{"title":"RaspberrySet: Dataset of Annotated Raspberry Images for Object Detection","authors":"S. Strautiņa, I. Kalnina, E. Kaufmane, K. Sudars, I. Namatēvs, Arturs Nikulins, Edgars Edelmers","doi":"10.3390/data8050086","DOIUrl":"https://doi.org/10.3390/data8050086","url":null,"abstract":"The RaspberrySet dataset is a valuable resource for those working in the field of agriculture, particularly in the selection and breeding of ecologically adaptable berry cultivars. This is because long-term changes in temperature and weather patterns have made it increasingly important for crops to be able to adapt to their environment. To assess the suitability of different cultivars or to make yield predictions, it is necessary to describe and evaluate berries’ characteristics at various growth stages. This process is typically carried out visually, but it can be time-consuming and labor-intensive, requiring significant expert knowledge. The RaspberrySet dataset was created to assist with this process, and it includes images of raspberry berries at five different stages of development. These stages are flower buds, flowers, unripe berries, and ripe berries. All these stages of raspberry images classified buds, damaged buds, flowers, unripe berries, and ripe berries and were annotated using ground truth ROI and presented in YOLO format. The dataset includes 2039 high-resolution RGB images, with a total of 46,659 annotations provided by experts using Label Studio software (1.7.1). The images were taken in various weather conditions, at different times of the day, and from different angles, and they include fully visible buds, flowers, berries, and partially obscured buds. This dataset is intended to improve the efficiency of berry breeding and yield estimation and to identify the raspberry phenotype more accurately. It may also be useful for breeding other fruit crops, as it allows for the reliable detection and phenotyping of yield components at different stages of development. By providing a homogenized dataset of images taken on-site at the Institute of Horticulture in Dobele, Latvia, the RaspberrySet dataset offers a valuable resource for those working in horticulture.","PeriodicalId":55580,"journal":{"name":"Atomic Data and Nuclear Data Tables","volume":"160 1","pages":"86"},"PeriodicalIF":1.8,"publicationDate":"2023-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76754764","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}
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