Pub Date : 2024-09-18DOI: 10.1016/j.dib.2024.110953
Elvira Rodríguez-Ríos
The earthquake in Ecuador on 16 April 2016 generated large volumes of debris and waste. This dataset contains data on recovered and reused disaster materials. Data were collected through a census survey of the scrap dealers of earthquake 2016 debris and waste (n = 62). This dataset was compiled to demonstrate how earthquake waste was generated during the 2016 earthquake and compare it with the pre-disaster period 2015 and the 2019 current when the data were collected. The recovered disaster materials include plastic, metal, cardboard, paper, glass, other recyclable materials, and reused materials. Likewise, the database allows us to observe the time response of medium- and small-sized scrap businesses as scrap dealers engage in the commercial transaction of disaster materials, and this dataset shows the process phases of recovering disaster waste. In addition, the dataset includes profit perceptions and factual earnings from scrap businesses after an earthquake. Considering the significant volume of waste and debris generated, this database can provide useful data for evaluating disaster waste management as an important task in post-disaster recovery.
{"title":"Dataset on recovered waste post-earthquake 2016 in Manabi Province, Ecuador for recycling and reuse","authors":"Elvira Rodríguez-Ríos","doi":"10.1016/j.dib.2024.110953","DOIUrl":"10.1016/j.dib.2024.110953","url":null,"abstract":"<div><div>The earthquake in Ecuador on 16 April 2016 generated large volumes of debris and waste. This dataset contains data on recovered and reused disaster materials. Data were collected through a census survey of the scrap dealers of earthquake 2016 debris and waste (<em>n</em> = 62). This dataset was compiled to demonstrate how earthquake waste was generated during the 2016 earthquake and compare it with the pre-disaster period 2015 and the 2019 current when the data were collected. The recovered disaster materials include plastic, metal, cardboard, paper, glass, other recyclable materials, and reused materials. Likewise, the database allows us to observe the time response of medium- and small-sized scrap businesses as scrap dealers engage in the commercial transaction of disaster materials, and this dataset shows the process phases of recovering disaster waste. In addition, the dataset includes profit perceptions and factual earnings from scrap businesses after an earthquake. Considering the significant volume of waste and debris generated, this database can provide useful data for evaluating disaster waste management as an important task in post-disaster recovery.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142318643","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-17DOI: 10.1016/j.dib.2024.110934
Ishtiak Al Mamoon , Zakaria Shams Siam , Abdul Akhir Al Galib , Theophil Dango , Kalin Chakma , Pranto Dev , Rubyat Tasnuva Hasan , Muhammad E.H. Chowdhury
In the field of numismatics, classifying ancient coins, especially those that have diverse information and cultural heritage is a difficult task. Machine learning algorithms have recently made remarkable advancements in these types of tasks. However, these algorithms largely rely on relevant datasets. This article presents a novel dataset of ancient Gupta archer-type coin images, collected from verified private collections and three popular auction houses with their permission. The images exclusively comprise authentic specimens of ancient Gupta archer-type coins. We aim to establish a reliable resource that adheres to the highest standards of numismatic research. These coins, characterized by their distinctive archer motifs, present a significant challenge in terms of identification due to their scarcity and the intricate nature of their design. To address this, we meticulously curated a dataset by annotating each coin through a combination of visual examination and leveraging insights from numismatic literatures. These coins inherit ancient Indian archaeological insights, and studying these coins could provide insights into ancient Indian archaeology.
{"title":"A novel dataset of Gupta archer type coins for machine learning-based classification","authors":"Ishtiak Al Mamoon , Zakaria Shams Siam , Abdul Akhir Al Galib , Theophil Dango , Kalin Chakma , Pranto Dev , Rubyat Tasnuva Hasan , Muhammad E.H. Chowdhury","doi":"10.1016/j.dib.2024.110934","DOIUrl":"10.1016/j.dib.2024.110934","url":null,"abstract":"<div><div>In the field of numismatics, classifying ancient coins, especially those that have diverse information and cultural heritage is a difficult task. Machine learning algorithms have recently made remarkable advancements in these types of tasks. However, these algorithms largely rely on relevant datasets. This article presents a novel dataset of ancient Gupta archer-type coin images, collected from verified private collections and three popular auction houses with their permission. The images exclusively comprise authentic specimens of ancient Gupta archer-type coins. We aim to establish a reliable resource that adheres to the highest standards of numismatic research. These coins, characterized by their distinctive archer motifs, present a significant challenge in terms of identification due to their scarcity and the intricate nature of their design. To address this, we meticulously curated a dataset by annotating each coin through a combination of visual examination and leveraging insights from numismatic literatures. These coins inherit ancient Indian archaeological insights, and studying these coins could provide insights into ancient Indian archaeology.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142427209","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-17DOI: 10.1016/j.dib.2024.110950
Olumide T. Adeleke , Halleluyah O. Aworinde , Mary Oboh , Oladipo Oladosu , Alaba B. Ayenigba , Bukola Atobatele , Oludamola V. Adeleke , Tunde S. Oladipo , Segun Adebayo
Malaria remains a serious public health problem in many developing countries, particularly in Sub-Saharan Africa. Early detection and treatment of malaria are crucial in the fight against malaria in order to reduce morbidity and mortality, especially in the endemic regions. We set out to develop a simple, accurate, and efficient innovative diagnostic tool for malaria parasite identification that uses automated image processing to provide shorter diagnosis times while improving accuracy, efficiency, and standardization. Our primary goal in this study is to collect, curate, annotate and achieve blood smear images containing Plasmodium species for effective malaria diagnosis using Artificial Intelligent based system. The study curated 881 blood smear images which are categorized as positive and negative images.
{"title":"Dataset for a novel AI-powered diagnostic tool for Plasmodium parasite detection authors","authors":"Olumide T. Adeleke , Halleluyah O. Aworinde , Mary Oboh , Oladipo Oladosu , Alaba B. Ayenigba , Bukola Atobatele , Oludamola V. Adeleke , Tunde S. Oladipo , Segun Adebayo","doi":"10.1016/j.dib.2024.110950","DOIUrl":"10.1016/j.dib.2024.110950","url":null,"abstract":"<div><div>Malaria remains a serious public health problem in many developing countries, particularly in Sub-Saharan Africa. Early detection and treatment of malaria are crucial in the fight against malaria in order to reduce morbidity and mortality, especially in the endemic regions. We set out to develop a simple, accurate, and efficient innovative diagnostic tool for malaria parasite identification that uses automated image processing to provide shorter diagnosis times while improving accuracy, efficiency, and standardization. Our primary goal in this study is to collect, curate, annotate and achieve blood smear images containing Plasmodium species for effective malaria diagnosis using Artificial Intelligent based system. The study curated 881 blood smear images which are categorized as positive and negative images.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142427210","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-17DOI: 10.1016/j.dib.2024.110944
Martina Bozzola , Emilia Lamonaca , Fabio G. Santeramo
This data article describes a new dataset on measures of climate distance for trade analyses. The dataset contains, (i) time-varying measures of long-run climate conditions for twenty economies accounting for two-third of global agri-food exports and representatives of different prevailing climates, and (ii) the difference in long-run climate conditions between country-pairs, here defined as Climate Distance. Measures of long-run climate conditions are computed, for each year in the sample (1996 to 2015), as 30-years rolling averages of weather conditions (i.e., climate normals or climatologies) in each country. Our climate measures are based on elaboration of data collected from the World Bank's Climate Change Knowledge Portal (CCKP), containing historical information on weather conditions. We also provide data on bilateral trade flows, tariffs, and policies, as provided by publicly available datasets. Our measures of climate change allow a more precise evaluation of structural changes in trade routes associated with climate comparative advantages.
{"title":"A new dataset on climate distance for trade analyses","authors":"Martina Bozzola , Emilia Lamonaca , Fabio G. Santeramo","doi":"10.1016/j.dib.2024.110944","DOIUrl":"10.1016/j.dib.2024.110944","url":null,"abstract":"<div><div>This data article describes a new dataset on measures of climate distance for trade analyses. The dataset contains, (i) time-varying measures of long-run climate conditions for twenty economies accounting for two-third of global agri-food exports and representatives of different prevailing climates, and (ii) the difference in long-run climate conditions between country-pairs, here defined as <strong>Climate Distance</strong>. Measures of long-run climate conditions are computed, for each year in the sample (1996 to 2015), as 30-years rolling averages of weather conditions (i.e., climate normals or climatologies) in each country. Our climate measures are based on elaboration of data collected from the World Bank's Climate Change Knowledge Portal (CCKP), containing historical information on weather conditions. We also provide data on bilateral trade flows, tariffs, and policies, as provided by publicly available datasets. Our measures of climate change allow a more precise evaluation of structural changes in trade routes associated with climate comparative advantages.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142318524","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-16DOI: 10.1016/j.dib.2024.110952
Radoslav Stojchevski , Sara Velichkovikj , Jane Bogdanov , Nikola Hadzi-Petrushev , Mitko Mladenov , Leonid Poretsky , Dimiter Avtanski
This paper presents a dataset obtained from an RT2-qPCR array analysis of rat pancreatic RIN-m cells treated with two monocarbonyl analogs of curcumin (MACs), C66 and B2BrBC in the presence or absence of streptozotocin (STZ). The array quantified the expression of 84 genes associated with the onset, development, and progression of diabetes. This dataset provides information on the gene expression profiles of pancreatic cells modulated by two specific MACs in a diabetic context. The data can serve as a foundation for developing new hypotheses, designing follow-up experiments, and identifying novel targets for treatment. It can be used to investigate further the molecular mechanisms underlying the therapeutic effects of these MACs and in comparative studies using other experimental antidiabetic compounds.
{"title":"Impact of monocarbonyl analogs of curcumin (MACs) C66 and B2BrBC on the expression of diabetes-associated genes in streptozotocin-treated rat pancreatic RIN-m cells—Quantitative RT-PCR array data","authors":"Radoslav Stojchevski , Sara Velichkovikj , Jane Bogdanov , Nikola Hadzi-Petrushev , Mitko Mladenov , Leonid Poretsky , Dimiter Avtanski","doi":"10.1016/j.dib.2024.110952","DOIUrl":"10.1016/j.dib.2024.110952","url":null,"abstract":"<div><p>This paper presents a dataset obtained from an RT<sup>2</sup>-qPCR array analysis of rat pancreatic RIN-m cells treated with two monocarbonyl analogs of curcumin (MACs), C66 and B2BrBC in the presence or absence of streptozotocin (STZ). The array quantified the expression of 84 genes associated with the onset, development, and progression of diabetes. This dataset provides information on the gene expression profiles of pancreatic cells modulated by two specific MACs in a diabetic context. The data can serve as a foundation for developing new hypotheses, designing follow-up experiments, and identifying novel targets for treatment. It can be used to investigate further the molecular mechanisms underlying the therapeutic effects of these MACs and in comparative studies using other experimental antidiabetic compounds.</p></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2352340924009144/pdfft?md5=687ce4496efb2ab275729189ece9ef99&pid=1-s2.0-S2352340924009144-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142271107","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-15DOI: 10.1016/j.dib.2024.110914
Till Steiner , Franziska Schanbacher , Wolfram Lorenzen , Heike Enke , Elisabeth M.-L. Janssen , Timo H.J. Niedermeyer , Karl Gademann
The UV–vis absorbance spectra, molar extinction coefficients and circular dichroism spectra, as well as NMR and high resolution tandem mass spectrometry spectra were determined for two prominent secondary metabolites from cyanobacteria, namely anabaenopeptin A and anabaenopeptin B. The compounds were extracted from the cyanobacterium Planktothrix rubescens CBT929 and purified by flash chromatography and HPLC. Exact amounts of isolated compounds were assessed by quantitative 1H-NMR with internal calibrant ethyl 4-(dimethylamino)benzoate in DMSO‑d6 at 298 K with a recycle delay (d1) of 120 s. UV–vis absorbance spectra were recorded in methanol at room temperature. Molar extinction coefficients were determined at 278 nm as 4190 M−1 cm−1 and 2300 M−1 cm−1 in methanol for anabaenopeptin A and anabaenopeptin B, respectively. Circular dichroism spectra and secondary fragmentation mass spectra are also reported.
{"title":"UV–vis absorbance spectra, molar extinction coefficients and circular dichroism spectra for the two cyanobacterial metabolites anabaenopeptin A and anabaenopeptin B","authors":"Till Steiner , Franziska Schanbacher , Wolfram Lorenzen , Heike Enke , Elisabeth M.-L. Janssen , Timo H.J. Niedermeyer , Karl Gademann","doi":"10.1016/j.dib.2024.110914","DOIUrl":"10.1016/j.dib.2024.110914","url":null,"abstract":"<div><div>The UV–vis absorbance spectra, molar extinction coefficients and circular dichroism spectra, as well as NMR and high resolution tandem mass spectrometry spectra were determined for two prominent secondary metabolites from cyanobacteria, namely anabaenopeptin A and anabaenopeptin B. The compounds were extracted from the cyanobacterium <em>Planktothrix rubescens</em> CBT929 and purified by flash chromatography and HPLC. Exact amounts of isolated compounds were assessed by quantitative <sup>1</sup>H-NMR with internal calibrant ethyl 4-(dimethylamino)benzoate in DMSO‑<em>d<sub>6</sub></em> at 298 K with a recycle delay (d1) of 120 s. UV–vis absorbance spectra were recorded in methanol at room temperature. Molar extinction coefficients were determined at 278 nm as 4190 M<sup>−1</sup> cm<sup>−1</sup> and 2300 M<sup>−1</sup> cm<sup>−1</sup> in methanol for anabaenopeptin A and anabaenopeptin B, respectively. Circular dichroism spectra and secondary fragmentation mass spectra are also reported.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2024-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142318522","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-14DOI: 10.1016/j.dib.2024.110926
E. Petter Axelsson , Daniel Lussetti , F. Merlin Franco
Biocultural diversity is important for environmental justice, human wellbeing, and sustainable development. Yet it is threatened by landscape degradation and overexploitation. When species go extinct, there is a co-occurring loss of associated cultural elements, and marginalized cultures are the ones that suffer the most from these losses. Here, we present BioCultBase/Borneo, a database of local uses of plants and their cultural contexts from the biologically and culturally hyper-diverse island of Borneo. The database has been developed from secondary data extracted from scientific literature, but is intended to be a live repository that welcomes contributions from academics, researchers and the general public. BioCultBase/Borneo database currently covers 1319 confirmed plant species and plant parts used for 23 use categories. These uses are reported from 39 ethnic communities of Borneo, together representing at least 2242 unique ecocultural links. The ethnicities represented in the database cover 13 % of the 306 officially recognized ethnicities of Borneo. Developing the database further will enhance access to ecocultural data that can be used for developing policy and practises relevant for a broader range of peoples.
{"title":"A Bornean database of plant uses and their cultural contexts: Introducing BioCultBaseBorneo","authors":"E. Petter Axelsson , Daniel Lussetti , F. Merlin Franco","doi":"10.1016/j.dib.2024.110926","DOIUrl":"10.1016/j.dib.2024.110926","url":null,"abstract":"<div><p>Biocultural diversity is important for environmental justice, human wellbeing, and sustainable development. Yet it is threatened by landscape degradation and overexploitation. When species go extinct, there is a co-occurring loss of associated cultural elements, and marginalized cultures are the ones that suffer the most from these losses. Here, we present <em>BioCultBase/Bor</em>neo, a database of local uses of plants and their cultural contexts from the biologically and culturally hyper-diverse island of Borneo. The database has been developed from secondary data extracted from scientific literature, but is intended to be a live repository that welcomes contributions from academics, researchers and the general public. <em>BioCultBase/Bor</em>neo database currently covers 1319 confirmed plant species and plant parts used for 23 use categories. These uses are reported from 39 ethnic communities of Borneo, together representing at least 2242 unique ecocultural links. The ethnicities represented in the database cover 13 % of the 306 officially recognized ethnicities of Borneo. Developing the database further will enhance access to ecocultural data that can be used for developing policy and practises relevant for a broader range of peoples.</p></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2352340924008898/pdfft?md5=7ba6388d1d61eac1992177cb1f18de32&pid=1-s2.0-S2352340924008898-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142271105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-14DOI: 10.1016/j.dib.2024.110935
Bak Zaibah Fazal , Nurshafrina Aida Yahya , Clemente Michael Wong Vui Ling , Yew Chee Wei , Thean Chor Leow , Mardani Abdul Halim , Krishnan Nair Balakrishnan , Cahyo Budiman , Zarina Amin
Hot springs are known to harbor potentially unique microorganisms due to the extreme temperatures in which they thrive and their biotechnologically important enzymes that are active at high temperature, which are beneficial for various industries. Sabah, Malaysia, houses several hot springs, yet knowledge of their microbiological diversity remains limited. Here, the raw sequence data of bacterial communities in a hot spring through metagenomic analysis are revealed. The data were obtained by collecting water and sediment samples from Poring Hot Spring (PHS) in Ranau, Sabah, and their bacterial diversity was analyzed using 16S rRNA amplicon sequencing targeting the V3-V4 regions. The analysis identified bacterial diversity in both water and sediment samples, with 35 phyla, 76 families, and 90 genera in water, and 38 phyla, 114 families, and 128 genera in sediment. Proteobacteria dominated the water samples (87 %), while Cyanobacteria were most abundant in sediment samples (51 %). The most abundant genera in water were Tepidimonas, Hydrogenophilus and Methylothermus, whereas Geitlerinema, Calothrix and Nitrospira dominated the sediment. Sediment samples exhibited higher bacterial richness and diversity compared to water samples, as indicated by α-diversity analysis. Sequences and sample data are deposited in the NCBI Sequence Read Archive under Bioproject ID PRJNA982554 (Accession number: SRX20671661 to SRX20671666) at https://www.ncbi.nlm.nih.gov/Traces/study/?acc=PRJNA982554&o=acc_s%3Aa).
{"title":"16S rRNA metagenomics data on the bacterial communities in Poring Hot Spring, Sabah, Malaysia","authors":"Bak Zaibah Fazal , Nurshafrina Aida Yahya , Clemente Michael Wong Vui Ling , Yew Chee Wei , Thean Chor Leow , Mardani Abdul Halim , Krishnan Nair Balakrishnan , Cahyo Budiman , Zarina Amin","doi":"10.1016/j.dib.2024.110935","DOIUrl":"10.1016/j.dib.2024.110935","url":null,"abstract":"<div><div>Hot springs are known to harbor potentially unique microorganisms due to the extreme temperatures in which they thrive and their biotechnologically important enzymes that are active at high temperature, which are beneficial for various industries. Sabah, Malaysia, houses several hot springs, yet knowledge of their microbiological diversity remains limited. Here, the raw sequence data of bacterial communities in a hot spring through metagenomic analysis are revealed. The data were obtained by collecting water and sediment samples from Poring Hot Spring (PHS) in Ranau, Sabah, and their bacterial diversity was analyzed using 16S rRNA amplicon sequencing targeting the V3-V4 regions. The analysis identified bacterial diversity in both water and sediment samples, with 35 phyla, 76 families, and 90 genera in water, and 38 phyla, 114 families, and 128 genera in sediment. Proteobacteria dominated the water samples (87 %), while Cyanobacteria were most abundant in sediment samples (51 %). The most abundant genera in water were Tepidimonas, Hydrogenophilus and Methylothermus, whereas Geitlerinema, Calothrix and Nitrospira dominated the sediment. Sediment samples exhibited higher bacterial richness and diversity compared to water samples, as indicated by α-diversity analysis. Sequences and sample data are deposited in the NCBI Sequence Read Archive under Bioproject ID PRJNA982554 (Accession number: SRX20671661 to SRX20671666) at <span><span>https://www.ncbi.nlm.nih.gov/Traces/study/?acc=PRJNA982554&o=acc_s%3Aa</span><svg><path></path></svg></span>).</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142427216","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-14DOI: 10.1016/j.dib.2024.110948
Marina Vicens-Miquel , Philippe Tissot , Deidre D. Williams , Katherine F.A. Colburn , Matthew Kastl , Savannah Stephenson
The study of beach morphology holds significant importance in coastal management, offering insights into coastal and environmental processes. It involves analyzing physical characteristics and beach features such as profile shape, slope, sediment composition, and grain size, as well as changes in elevation due to both erosion and accretion over time. Furthermore, studying changes in beach morphology is essential in predicting and monitoring coastal inundation events, especially in the context of rising sea levels and subsidence in some areas. However, having access to high-frequency oblique imagery and beach elevation datasets to document and confirm coastal forcing events and understand their impact on beach morphology is a notable challenge. This paper describes a one-year dataset comprising bi-monthly topographic surveys and imagery collected daily at 30 min increments at the beach adjacent to Horace Caldwell Pier in Port Aransas, Texas. The data collection started in February 2023 and ended in January 2024. The dataset includes 18 topographic surveys, 6879 beach images, and ocean/wave videos that can be combined with colocated National Oceanic and Atmospheric Administration metocean measurements. The one-year temporal span of the dataset allows for the observation and analysis of seasonal variations, contributing to a deeper understanding of coastal dynamics in the study area. Furthermore, a study that combines survey measurements with camera imagery is rare and provides valuable information on conditions before, after, and between surveys and periods of inundation. The imagery enables monitoring of inundation events, while the topographic surveys facilitate the analysis of their impact on beach morphology, including beach erosion and accretion. Various products, including beach profiles, contours, slope maps, triangular irregular networks, and digital elevation models, were derived from the topographic dataset, allowing in depth analysis of beach morphology. Additionally, the dataset contains a time series of four wet/dry shoreline delineations per day and their corresponding elevation extracted by combining the imagery with the digital elevation models. Thus, this paper provides a high-frequency morphological dataset and a machine learning-ready dataset suitable for predicting coastal inundation.
{"title":"A high-resolution spatiotemporal morphological dataset: Port Aransas beach, Texas","authors":"Marina Vicens-Miquel , Philippe Tissot , Deidre D. Williams , Katherine F.A. Colburn , Matthew Kastl , Savannah Stephenson","doi":"10.1016/j.dib.2024.110948","DOIUrl":"10.1016/j.dib.2024.110948","url":null,"abstract":"<div><p>The study of beach morphology holds significant importance in coastal management, offering insights into coastal and environmental processes. It involves analyzing physical characteristics and beach features such as profile shape, slope, sediment composition, and grain size, as well as changes in elevation due to both erosion and accretion over time. Furthermore, studying changes in beach morphology is essential in predicting and monitoring coastal inundation events, especially in the context of rising sea levels and subsidence in some areas. However, having access to high-frequency oblique imagery and beach elevation datasets to document and confirm coastal forcing events and understand their impact on beach morphology is a notable challenge. This paper describes a one-year dataset comprising bi-monthly topographic surveys and imagery collected daily at 30 min increments at the beach adjacent to Horace Caldwell Pier in Port Aransas, Texas. The data collection started in February 2023 and ended in January 2024. The dataset includes 18 topographic surveys, 6879 beach images, and ocean/wave videos that can be combined with colocated National Oceanic and Atmospheric Administration metocean measurements. The one-year temporal span of the dataset allows for the observation and analysis of seasonal variations, contributing to a deeper understanding of coastal dynamics in the study area. Furthermore, a study that combines survey measurements with camera imagery is rare and provides valuable information on conditions before, after, and between surveys and periods of inundation. The imagery enables monitoring of inundation events, while the topographic surveys facilitate the analysis of their impact on beach morphology, including beach erosion and accretion. Various products, including beach profiles, contours, slope maps, triangular irregular networks, and digital elevation models, were derived from the topographic dataset, allowing in depth analysis of beach morphology. Additionally, the dataset contains a time series of four wet/dry shoreline delineations per day and their corresponding elevation extracted by combining the imagery with the digital elevation models. Thus, this paper provides a high-frequency morphological dataset and a machine learning-ready dataset suitable for predicting coastal inundation.</p></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2352340924009119/pdfft?md5=755e09fe607fb3ec1c814ad9f442d648&pid=1-s2.0-S2352340924009119-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142271732","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-14DOI: 10.1016/j.dib.2024.110942
Adalto Farias, Vanessa Seriacopi, Marcelo Otávio dos Santos, Ed Claudio Bordinassi
This article reports on a comprehensive dataset detailing positioning errors in a 3-axis milling center machine (MCM) with computer numerical control (CNC) specifically curated for thermal error compensation. The data, which includes separate datasets for the X, Y, and Z axes, was collected through systematic measurements using an interferometric laser (IL) system under monitored thermal conditions. Each axis's acquisition was recorded with a resolution to capture dynamic variations influenced by thermal fluctuations. Temperature measurements were obtained using resistance temperature detectors (RTD) installed in the bearing housings of each axis for monitoring of thermal conditions throughout the data collection process in each axis. The dataset comprises raw positional and error data for each axis alongside metadata describing parameters such as bearing temperature, heating cycle, and machine operating conditions. This dataset can potentially be a valuable resource for researchers, enabling them to develop and validate real-time thermal error compensation algorithms, thereby enhancing CNC machining precision for each axis independently and collectively. Furthermore, the dataset's structured format facilitates comparative studies across different machine configurations and operational contexts, contributing to advancements in manufacturing technology and improvements in process parameter design and optimization.
本文报告了一个综合数据集，该数据集详细描述了专门为热误差补偿而设计的计算机数控（CNC）三轴铣削中心机床（MCM）的定位误差。这些数据包括 X、Y 和 Z 轴的单独数据集，是在受监控的热条件下使用干涉激光 (IL) 系统通过系统测量收集的。每个轴的采集都以一定的分辨率进行记录，以捕捉受热波动影响的动态变化。使用安装在每个轴的轴承座中的电阻温度探测器（RTD）进行温度测量，以便在每个轴的整个数据采集过程中监控热条件。数据集包括每个轴的原始位置和误差数据，以及描述轴承温度、加热周期和机器运行条件等参数的元数据。该数据集可能会成为研究人员的宝贵资源，使他们能够开发和验证实时热误差补偿算法，从而提高每个轴的独立和集体数控加工精度。此外，数据集的结构化格式便于对不同的机器配置和操作环境进行比较研究，从而促进制造技术的进步以及工艺参数设计和优化的改进。
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