Data in Brief最新文献

{"title":"Complete chloroplast genome data of Trollius ledebourii Rehb, an important medicinal plant species","authors":"Bo Liu ,&nbsp;Lingyang Kong ,&nbsp;Yuhua Zhang ,&nbsp;Yu long Zhang ,&nbsp;Weichao Ren ,&nbsp;Xiubo Liu ,&nbsp;Jiao Xu ,&nbsp;Wei Ma","doi":"10.1016/j.dib.2025.111408","DOIUrl":"10.1016/j.dib.2025.111408","url":null,"abstract":"<div><div><em>Trollius ledebourii</em> Rehb<em>.</em> (commonly known as short petal golden lotus) Ic. Pl. Crit. 1825 is a perennial plant that belongs to the genus Trollius in the Ranunculaceae family. The complete genetic makeup of the short petal golden lotus determines its characteristic tetrad arrangement. The chloroplast genome of T. ledebourii is 160029 bp long, while the two reverse repeat sequences (IRa and IRb), large single copy region (LSC), and small single copy region (SSC) are 53162, 88487, and 18380 bp long, respectively. This chloroplast genome comprises 130 genes, including 85 protein-coding genes, 37 genes involved in tRNA production, and 8 genes responsible for rRNA synthesis. A phylogenetic analysis revealed that T. ledebourii and T. chinensis are closely related species. The complete chloroplast genome sequence of the short petal golden lotus will contribute to the advancement of molecular breeding, evolutionary analysis, and phylogenetic research pertaining to this species.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"59 ","pages":"Article 111408"},"PeriodicalIF":1.0,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143563102","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}

{"title":"Multifrequency low-level laser-assisted mastopexy in 231 consecutive patients: A dataset","authors":"Gabriel Cubillos-Valencia ,&nbsp;Neidalis Vasquez ,&nbsp;Andrés Miguel Ortegón Pulido ,&nbsp;Diego Rivera-Porras ,&nbsp;Julio Cesar Contreras-Velásquez ,&nbsp;Valmore Bermúdez","doi":"10.1016/j.dib.2025.111423","DOIUrl":"10.1016/j.dib.2025.111423","url":null,"abstract":"<div><div>Breast ptosis, the inferior displacement of the nipple–areola complex, is predominantly attributed to age-related collagen degradation within the breast parenchyma as a result of fibroblast senescence and postmenopausal estrogen depletion, which together result in skin ageing and mammary adipose tissue reduction. This Dataset reports the clinical information and measurements of 231 patients who underwent multifrequency low-level laser-assisted mastopexy. Data were collected prospectively between February 2021 and November 2023. All patients' references and identification data were anonymized to ensure compliance with Colombian legal regulations. Subsequently, data were translated from Spanish to English and stored in both .xls and .csv formats. This study aimed to evaluate the effect of the procedure on breast ptosis degree and the sternal notch to nipple distance (SNND) to assess the evolution of breast ptosis. This article presents demographic, personal, and familial history data, anthropometric measurements, breast ptosis degree classified according to the Regnault system, SNND measurements, and complications categorized using the Clavien-Dindo classification system.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"59 ","pages":"Article 111423"},"PeriodicalIF":1.0,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143529053","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}

{"title":"CORHOH: Text corpus of holocaust oral histories","authors":"Daban Q. Jaff","doi":"10.1016/j.dib.2025.111426","DOIUrl":"10.1016/j.dib.2025.111426","url":null,"abstract":"<div><div>This paper outlines the compilation and annotation process of CORHOH: Text CORpus of <strong>H</strong>olocaust <strong>O</strong>ral <strong>H</strong>istories. The corpus consists of 500 oral histories, each narrative form one survivor. The transcripts of the oral histories are retrieved from the <em>Let Them Speak Project</em> [1]. The transcripts are normalized and further annotated. The corpus offers rich metadata about both the testimony givers and the interviews. All technical content is removed, and a unique identifier is assigned to each question (posed by the interviewer) and answer (provided by the survivor). The corpus complies with the TEI guidelines [2]. The corpus includes 106,519 questions and 107,125 answers, making it easy to distinguish between the utterances that belong to the holocaust survivor or anyone else who is involved in the interview, primarily the interviewer. CORHOH is particularly suited for studies on trauma expression and psychological concepts embedded in survivors' narratives. Additionally, it offers potential for data mining to uncover patterns (e.g., migration trends) and supports natural language processing techniques, such as topic modelling, sentiment analysis, and named entity recognition. The CORHOH data is courtesy of the United States Holocaust Memorial Museum (USHMM) and is publicly available under the CC BY-NC-SA 4.0 license.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"59 ","pages":"Article 111426"},"PeriodicalIF":1.0,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143549923","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}

{"title":"Transcriptome dataset to investigate the effect of deep seawater on the gene expression and functional compounds of leaves of Ligularia stenocephala","authors":"Dewi Komang Anggita ,&nbsp;Bimpe Suliyat Azeez ,&nbsp;Se-Jin Oh ,&nbsp;Jong-Kuk Na","doi":"10.1016/j.dib.2025.111427","DOIUrl":"10.1016/j.dib.2025.111427","url":null,"abstract":"<div><div>Seawater is often applied to improve crop quality by supplying minerals to the crop. Due to high salt concentration of seawater, one of key factors for successful utilization of seawater in agriculture would be optimal dilution ratios, which can be determined by physiological and genomic studies. However, genomic studies of crops treated with seawater have rarely been investigated. <em>Ligularia stenocephala</em>, a vegetable and medicinal crop [<span><span>1</span></span>], is used to examine the genomic changes in response to the application of deep seawater (DSW) from 605 m depth. RNA sequencing was carried out for three different leaf samples of <em>L. stenocephala</em> treated with 0% (NT), 5% (DSW5), or 10% (DSW10) of DSW using the Illumina NovaSeq 6000 sequencing system. The RNA sequencing generated 38.1 million raw reads for NT, 29.2 for DSW5, and 30.5 for DSW10, respectively. The length of total raw reads was 2.94 (DSW5), 3.08 (DSW10), and 3.85 Gb (NT), while the total length of filtered clean reads ranged between 2.88 Gb (DSW5) and 3.75 Gb (NT). GC contents range between 42.9% (DSW5) and 43.58 (DSW10), while the Q20 quality score ranged between 98.63% (DSW10) and 98.66% (DSW5). Due to the lack of the reference genome for read mapping, the three transcriptome data from this study were merged to generate a reference transcriptome. The percentage of mapped reads ranged from 89.63 (DSW10) to 98.66% (DSW5). The data is accessible at NCBI BioProject: <span><span>PRJNA1149490</span><svg><path></path></svg></span>. These data provide invaluable information not only for understanding genes responsive to deep seawater application in crop cultivation but also for determining the optimal dilution ratio of DSW without causing salt stress on crops by examining expression profiles of stress-responsive genes.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"59 ","pages":"Article 111427"},"PeriodicalIF":1.0,"publicationDate":"2025-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143534457","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}

{"title":"Dataset on the long-term monitoring of foundation vertical deformations on medium-expansive soil","authors":"Hawkar Hashim Ibrahim,&nbsp;Rizgar Ali Hummadi","doi":"10.1016/j.dib.2025.111422","DOIUrl":"10.1016/j.dib.2025.111422","url":null,"abstract":"<div><div>This paper presents a complete data set from the long-term field monitoring of vertical deformation in four footings resting on medium-expansive soil. The four key variables (vertical deformation, daily average air temperature, weekly cumulative rainfall, and soil water content at a depth of 60 cm) were recorded over a period of 974 days. The vertical deformations were measured with high-precision dial gauges. At the same time, the advanced instruments, Bosch GLL 3-80 G Professional line laser and LEICA DNA 10 digital levels were cross-used for measurement to ensure the accuracy and reliability of the results. The data collection was designed to include the effects of expansive soil properties, such as swelling during wet seasons and shrinkage during dry seasons. This is necessary for understanding the soil-structure interaction under natural field conditions, which differs considerably from controlled laboratory studies. This dataset presents a great possibility of being reused by researchers to support further studies on soil-structure interaction, develop predictive models for expansive soils, and analyze long-term structural stability. It is particularly useful in developing machine learning algorithms that can be used to predict foundation behavior in response to different environmental conditions, optimize foundation designs on expansive soils, and specifically predict foundation heave. The availability of this dataset provides an invaluable resource in advancing geotechnical engineering research.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"59 ","pages":"Article 111422"},"PeriodicalIF":1.0,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143534478","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}

{"title":"Data of the crystal structure of xylose isomerase from Streptomyces avermitilis","authors":"Ki Hyun Nam","doi":"10.1016/j.dib.2025.111414","DOIUrl":"10.1016/j.dib.2025.111414","url":null,"abstract":"<div><div>Xylose isomerase (XI; also known as glucose isomerase) catalyzes the conversion of D-glucose and D-xylose to D-fructose and D-xylulose, respectively. XI is widely used in various industries, such as high-fructose corn syrup and bioethanol production. The discovery and characterization of novel XI variants are important to enhance the effective industrial applications of XI. Recently, the X-ray diffraction data for XI from <em>Streptomyces avermitilis</em> (SavXI) were collected at a synchrotron. The crystal structure of SavXI was determined using the molecular replacement method. The SavXI structure exhibited two unique metal-binding sites at the active site, diverse conformations, and a distinctive conformation of the C-terminal region compared to other XI homologs. This structural information extends the understanding of the molecular properties of the XI family. Here, information on the raw diffraction data images of SavXI, which were not presented in the previous study, is introduced. Detailed data collection and structure determination are reported for future XI structural analyses.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"59 ","pages":"Article 111414"},"PeriodicalIF":1.0,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143534459","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}

{"title":"Dataset on rbcL gene intra and inter-specific diversity and phylogenetic relationship of eggplants (Solanum species) in Southern Nigeria","authors":"Babafemi I. Ajiboye ,&nbsp;Jacob O. Popoola ,&nbsp;Angela O. Eni ,&nbsp;Conrad A. Omonhinmin","doi":"10.1016/j.dib.2025.111424","DOIUrl":"10.1016/j.dib.2025.111424","url":null,"abstract":"<div><div>Eggplant (<em>Solanum</em> sp.) is the third most widely cultivated solanaceous vegetable globally, and it is commonly consumed in Nigeria, particularly in Southern Nigeria, for its nutritious and medicinal fruit, leaves, and seeds. The taxon has recorded array of ethnobotanical uses ranging from food, medicine to cultural interactions in ceremonies. Despite the enormous range of a value, studies have shown decreasing eggplant varietal diversity, directly linked with cultivation preferences and activities, such as exchanging propagules within and between agroecological areas and farms. Additionally, the wide range of accessions in the taxa, morphological plasticity, and genetic similarity among accessions have resulted in the ambiguity and inconsistent phylogenetic classification of the taxa. The dataset consists of partial ribulose-1,5-bisphosphate carboxylase/oxygenase large subunit (<em>rbcL</em>) gene sequences, nucleotide compositions and amino acid profiles of 75 accessions of eggplants collected from across Southern Nigeria. The genetic information provided by the dataset offers insight into the genetic diversity and the phylogenetic relationships of the eggplant accessions, which could serve as a baseline for designing effective strategies for sustainable cultivation, conservation, utilisation, and improvement of the taxa.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"59 ","pages":"Article 111424"},"PeriodicalIF":1.0,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143549925","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}

{"title":"Gran canaria vegetation segmentation dataset from multi-year aerial imagery for environmental monitoring and conservation","authors":"José Salas-Cáceres ,&nbsp;Riccardo Balia ,&nbsp;Marcos Salas-Pascual ,&nbsp;Javier Lorenzo-Navarro ,&nbsp;Modesto Castrillón-Santana","doi":"10.1016/j.dib.2025.111419","DOIUrl":"10.1016/j.dib.2025.111419","url":null,"abstract":"<div><div>Vegetation maps are an essential tool for territorial planning, enabling the identification of areas requiring protection and facilitating the study of key ecosystem dynamics such as their evolution over time and the threats they face. These aspects are especially critical in island territories, where their fragmented nature and isolation from the mainland pose significant challenges to the development of such documentation. Traditionally, these maps have relied on local experts, requiring extensive fieldwork, significant time and financial resources. To address these challenges, a novel dataset focused on Gran Canaria (Canary Islands, Spain) is presented, designed to allow researchers to develop and test deep learning models that automatically generate vegetation maps using computer vision techniques.</div><div>This dataset is unique in the field of aerial image-based semantic segmentation, as it provides detailed annotations for 20 well-defined vegetation communities, going beyond the broad classifications commonly found in existing datasets (e.g., forests or grasslands). Additionally, an alternative version of the dataset includes five non-vegetal classes, such as water bodies, roads, or buildings to support more visually comprehensive segmentation tasks.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"59 ","pages":"Article 111419"},"PeriodicalIF":1.0,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143534458","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}

{"title":"ChatgaiyyaAlap: A dataset for conversion from Chittagonian dialect to standard Bangla","authors":"Sinthia Chowdhury ,&nbsp;Deawan Rakin Ahamed Remal ,&nbsp;Syed Tangim Pasha ,&nbsp;Ashraful Islam ,&nbsp;Sheak Rashed Haider Noori","doi":"10.1016/j.dib.2025.111413","DOIUrl":"10.1016/j.dib.2025.111413","url":null,"abstract":"<div><div>Bangla is one of the most used languages around the world with 240 million speakers. The standard Bangla language is the official language of people from Bangladesh and a few other parts outside Bangladesh, like West Bengal and Tripura. Although, people from different areas of Bangladesh do not use standard Bangla on a day-to-day basis. Instead, dialects of the Bangla language are used. The dialects of the Bangla language are quite diverse which includes the Rajshahi dialect, Sylheti dialect, Old Dhaka dialect, Chittagonian dialect, and many more. Nearly every division of Bangladesh has its unique dialect which adds linguistic diversity to the language. The main difference between the standard Bangla language and Chittagonian dialect is that it does not have any written form and the words vary from the standard Bangla. We built a dataset containing standard Bangla and one of its most used dialects: the Chittagonian dialect. Our dataset, “ChatgaiyyaAlap,” was created by combining 4012 unique sentences in standard Bangla with their Chittagonian translations, which were gathered from dramas, comments, and videos on YouTube and Facebook. In our dataset, we cleaned the data by removing emojis, punctuations, and unessential spaces. The dissimilarity in spelling as well as in sentence structure between standard Bangla and Chittagonian dialects, particularly in negative sentences can be clearly visible through this dataset. Additionally, to maintain the data accuracy, we developed a dictionary containing 1,500 standard Bangla words and their Chittagonian form. The dictionary showcases significant variation in the vocabulary of both languages and resolves ambiguities along with potential biases. To perform a word-to-word translation this dictionary would be useful, while for studying comparative linguistics and developing intelligent systems the ChatgaiyyaAlap dataset might assist the researchers. Moreover, this dataset can be utilized to train language models for linguistic translation.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"59 ","pages":"Article 111413"},"PeriodicalIF":1.0,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143528967","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}

{"title":"Drone-based dataset of annotated sunflower images from Bangladesh","authors":"Md. Shafayat Hossain,&nbsp;Mohammad Rifat Ahmmad Rashid,&nbsp;Md. Fahim,&nbsp;Tahzib-E-Alindo,&nbsp;Md Sawkat Ali,&nbsp;Maheen Islam,&nbsp;Mohammad Manzurul Islam,&nbsp;Md. Hasanul Ferdaus,&nbsp;Nishat Tasnim Niloy","doi":"10.1016/j.dib.2025.111417","DOIUrl":"10.1016/j.dib.2025.111417","url":null,"abstract":"<div><div>Accurate and automated detection of sunflower plants, along with assessments of their growth stages and health conditions, is crucial for enabling precision agriculture and improving crop management. In this work, we present a drone-based dataset of annotated sunflower images, derived from high-resolution videos captured at two distinct locations in Bangladesh. The original dataset comprises 1649 images extracted from drone footage of the BARI Surjomukhi-3 variety under various orientations, health conditions, and weather scenarios. After meticulous annotation using the Roboflow platform and augmentation with seven distinct techniques, the dataset expanded to 4286 images in Pascal VOC format. Detailed metadata—including geospatial coordinates, timestamped acquisition conditions, and camera settings—accompanies the dataset to support reproducibility and model generalization. By offering a comprehensive suite of annotated and augmented images, this dataset provides a valuable resource for developing and refining computer vision models geared toward sunflower detection, maturity evaluation, and yield prediction, ultimately advancing sustainable farming practices and decision-making tools in agricultural research.</div></div>","PeriodicalId":10973,"journal":{"name":"Data in Brief","volume":"59 ","pages":"Article 111417"},"PeriodicalIF":1.0,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143563101","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}