A taxonomic, genetic and ecological data resource for the vascular plants of Britain and Ireland

The vascular flora of Britain and Ireland is among the most extensively studied in the world, but the current knowledge base is fragmentary, with taxonomic, ecological and genetic information scattered across different resources. Here we present the first comprehensive data repository of native and alien species optimized for fast and easy online access for ecological, evolutionary and conservation analyses. The inventory is based on the most recent reference flora of Britain and Ireland, with taxon names linked to unique Kew taxon identifiers and DNA barcode data. Our data resource for 3,227 species and 26 traits includes existing and unpublished genome sizes, chromosome numbers and life strategy and life-form assessments, along with existing data on functional traits, species distribution metrics, hybrid propensity, associated biomes, realized niche description, native status and geographic origin of alien species. This resource will facilitate both fundamental and applied research and enhance our understanding of the flora’s composition and temporal changes to inform conservation efforts in the face of ongoing climate change and biodiversity loss.

Synthetic Data Resource and Benchmarks for Time Cell Analysis and Detection Algorithms

Hippocampal CA1 cells take part in reliable, time-locked activity sequences in tasks that involve an association between stimuli, in a manner that tiles the interval between the stimuli. Such cells have been termed time cells. Here we adopt a first-principles approach to comparing diverse analysis and detection algorithms for identifying time cells. We developed a resource for generating synthetic activity datasets using calcium signals recorded in vivo from mouse hippocampus using 2-photon imaging, for template response waveforms. We assigned known, ground truth values for properties of time cells in this synthetic dataset, including noise, timing imprecision, hit-trial ratio and calcium event width. These datasets were the input to a pipeline for testing multiple algorithms for time cell detection to determine the conditions for which they were best suited, and evaluate their effective operating ranges. We find that most algorithms are sensitive to noise. Only a few methods benefit from larger event widths. Reassuringly, most methods are insensitive to timing imprecision, and exhibit successful time cell detection even at low hit trial ratios. Importantly, all methods show good concordance in identifying cells as time cells.

Applications of Big Data and Green IoT-Enabling Technologies for Smart Cities

In recent years, enormous amounts of digital data have been generated. In parallel, data collection, storage, and analysis technologies have developed. Recently, there has been an increasing trend of people moving towards urban areas. By 2030 more than 60% of the world's population will live in an urban environment. Urban areas are big data resource because they include millions of citizens, technological devices, and vehicles which generate data continuously. Besides, rapid urbanization brings many challenges, such as environmental pollution, traffic congestion, health problems, energy management, etc. Some policies for countries are required to cope with urbanization problems. One of these policies is to build smart cities. Smart cities integrate information and communication technology and various physical devices connected to the network (the internet of things or IoT) to both improve the quality of government services and citizen welfare. This chapter presents a literature review of big data, smart cities, IoT, green-IoT concepts, using technology and methods, and applications worldwide.

The BioImage Archive - home of life-sciences microscopy data

Despite the importance of data resources in genomics and structural biology, until now there has been no central archive for biological data for all imaging modalities. The BioImage Archive is a new data resource at the European Bioinformatics Institute (EMBL-EBI) designed to fill this gap. It accepts bioimaging data associated with publication in any format, from any imaging modality at any scale, as well as reference datasets. The BioImage Archive will improve reproducibility of published studies that derive results from image data. In addition, providing reference datasets to the scientific community reduces duplication of effort and allows downstream analysis to focus on a consistent set of data. The BioImage Archive will also help to generate new insights through reuse of existing data to answer new biological questions, or provision of training, testing and benchmarking data for image analysis tool development. The Archive is available at https://www.ebi.ac.uk/bioimage-archive/.

Remote Sensing Big Data Analysis of the Lower Yellow River Ecological Environment Based on Internet of Things

This paper collects data on the ecological environment of the lower Yellow River through an IoT approach and provides an in-depth analysis of the ecological remote sensing big data. An impervious fusion of multisource remote sensing data cooperation and multimachine learning algorithm cooperation is proposed. The water surface extraction method has improved the extraction accuracy of the construction land and rural settlements in the Yellow River Delta. The data system, big data management platform, and application scenarios of the environmental data resource center are designed specifically, respectively. Based on the spherical mesh information structure to sort out environmental data, an environmental data system containing data characteristics such as information source, timeliness, and presentation is formed. According to the characteristics of various types of environmental data, the corresponding data access, storage, and analysis support system is designed to form the big data management platform. Strengthen the construction of ecological interception projects for farmland receding water. Speed up the construction of sewage treatment facilities. Carry out waste and sewage pipeline network investigation, speed up the construction of urban sewage collection pipeline network, and improve the waste and sewage collection rate and treatment rate. The management platform adopts the Hadoop framework, which is conducive to the storage of massive data and the utilization of unstructured data. Combined with the relevant national policy requirements and the current environmental protection work status, the application scenarios of environmental big data in environmental decision-making, supervision, and public services are sorted out to form a complete data resource center framework. Gray correlation analysis is used to identify the key influencing factors of different types of cities to elaborate the contents of the construction of water ecological civilization in different types of cities and to build a framework of ideas for the construction of urban water ecological civilization to improve the health of urban water ecological civilization. To realize the sustainable development of the lower reaches of the Yellow River, blind logging and reclamation should be avoided in the process of land development, and more efforts should be made to protect tamarisk scrub and reed scrub, which are vegetation communities with positive effects on the regional ecological environment. In urban planning, the proportion of green area and water area within the city should be reasonably increased, so that the city can develop towards a livable city that is more conducive to human-land harmony and sustainability.

Bert-Based Latent Semantic Analysis (Bert-LSA): A Case Study on Geospatial Data Technology and Application Trend Analysis

Geospatial data is an indispensable data resource for research and applications in many fields. The technologies and applications related to geospatial data are constantly advancing and updating, so identifying the technologies and applications among them will help foster and fund further innovation. Through topic analysis, new research hotspots can be discovered by understanding the whole development process of a topic. At present, the main methods to determine topics are peer review and bibliometrics, however they just review relevant literature or perform simple frequency analysis. This paper proposes a new topic discovery method, which combines a word embedding method, based on a pre-trained model, Bert, and a spherical k-means clustering algorithm, and applies the similarity between literature and topics to assign literature to different topics. The proposed method was applied to 266 pieces of literature related to geospatial data over the past five years. First, according to the number of publications, the trend analysis of technologies and applications related to geospatial data in several leading countries was conducted. Then, the consistency of the proposed method and the existing method PLSA (Probabilistic Latent Semantic Analysis) was evaluated by using two similar consistency evaluation indicators (i.e., U-Mass and NMPI). The results show that the method proposed in this paper can well reveal text content, determine development trends, and produce more coherent topics, and that the overall performance of Bert-LSA is better than PLSA using NPMI and U-Mass. This method is not limited to trend analysis using the data in this paper; it can also be used for the topic analysis of other types of texts.

Building and Using Data Resources for Research on Job Characteristics, Health, and Retirement

A growing literature seeks to understand the relationship between the experience of work and important later-life outcomes. Rich longitudinal measurement of both sides of this equation in datasets such as the Health and Retirement Study (HRS) have made this research possible. These data take the form of self-reported experiences of work (such as physical demands, job flexibility, job satisfaction etc.). Increasingly, researchers are looking to add potentially complementary information on the work environment available in the Occupational Information Network (O*NET) database through a linkage using occupation and industry codes in the survey data. The session talks will describe research conducted using O*NET linked with HRS data as well as ongoing work to create a new data resource that will allow other researchers to undertake research with O*NET-HRS linked data. Each presentation will include some discussion of both the value and limits of using the linkage to O*NET. Carpenter will provide a detailed description a new project linking the 2019 O*NET data to the HRS for public use.This presentation explains the types of variables that will be made available in the O*NET-HRS occupation project and will provide examples for how the measures can be used in longitudinal HRS studies. Using O*NET-HRS linked data, Carr will present on work examining the role of preretirement job complexity in alternative retirement paths and cognitive performance. Helppie-McFall will used the linked data to discuss the role of mismatch between demands of work and workers’ ability to meet those demands in retirement decisions.

Creating a Public Data Resource: The HRS-O*NET Linkage

Few longitudinal studies provide detailed information about the characteristics of the jobs older workers engage in, limiting the ability to evaluate the potential consequences of extended working lives. In this session, we introduce a new project linking the 2019 O*NET taxonomy and corresponding data to the Health and Retirement Study for public use. We describe the procedures taken to develop an O*NET linkage to be released to HRS users in the form of a publicly available data file, allowing aging researchers to evaluate detailed aspects of occupations in the 50+ population. We explain the types of variables that will be made available in the O*NET-HRS occupation project, and provide examples for how the measures can be used in longitudinal HRS studies.

Proses Manajemen Peserta Didik di SMA Binaan Universitas

<p><strong>Abstract:</strong> The writing of this article aims to analyze and describe of process student management of university’s senior high school. Method in this research is descriptive qualitative, the technique of collecting data through interview, observation, and documentation, and were data analysed by interactive model, trouhg reduction, display, and conclution. Subjects as data resource in this research were researcher, principal, and vice principal of student. Finding of this research indicates the student management process held by cooperation between school and university in auditing in every functions of student management.</p><strong>Abstrak:</strong> Penulisan artikel ini bermaksud untuk menganalisa dan mendeskripsikan proses manajemen peserta didik di SMA binaan universitas. Metode penelitian menggunakan kualitatif deskriptif, teknik pengumpulan data menggunakan observasi wawancara, observasi, dan dokumentasi, selanjutnya dianalisis dengan model interaktif melalui reduksi, penyampaian, dan konklusi. Subjek dalam penelitian ini adalah peneliti, kepala sekolah, wakil kepala kesiswaan, dan tenaga pendidik. Temuan dari penelitian ini menunjukan bahwa proses manajemen peserta didik dilaksanakan melibatkan kerjasama dengan universitas dalam pegauditan setiap fungsi dalam manajemen peserta didik.

Prinsip Kesantunan Ujaran Berbahasa dalam Interaksi Siswa Sekolah Dasar

<p><strong>Abstract:</strong> This research aims to describe impositive act (Requesting, asking, ruling and rejecting), the politeness in language and politeness principle that is used by the student in their interaction. The data collecion process uses recording techniques to get recording data when research is being run. The researcher also uses interview technique to ensure and give valid data. Transcript of recording, Interview result and field note are the data of research. Research data resource is taken from the student, teacher, and parents. The result of observation shows that there are four politeness principle. They are kurmat maxim or respect, andhap ashor maxim or humble, <em>empan papan</em> maxim or aware of the place, <em>tepa selira</em> maxim or tolerance maxim.</p><strong>Abstrak:<em> </em></strong>Tujuan penelitian ini ialah untuk mendeskripsikan tindak impositif (meminta, bertanya memerintah dan menolak) kesantunan berbahasa, serta prinsip kesantunan dalam interaksi siswa. Proses pengumpulan data menggunakan, alat bantu <em>recorder </em>untuk mengambil data rekaman saat kegiatan penelitian, serta menggunakan teknik wawancara untuk memastikan dan memberikan hasil yang valid. Data penelitian ialah transkrip rekaman, hasil wawancara serta catatan lapangan. Penelitian ini menggunakan sumber data melalui siswa, guru, dan orangtua. Hasil yang telah diteliti mendapatkan empat prinsip tindak ujar kesantunan dalam berbahasa, yakni maksim <em>kurmat </em>atau hormat, maksim <em>andhap asor </em>atau rendah hati, maksim <em>empan papan </em>atau sadar akan tempat, dan maksim <em>tepa selira </em>atau tenggang rasa.