The Kresge early childhood interactive map contains data relating to early childhood and education. It is meant to help stakeholders better understand the early childhood landscape better.

This dataset is updated monthly based on the Assessor data of GEOPIN and TAXBILL. It is a full polygon dataset of the parcels with both GEOPIN and TAXBILL attached. This allows users to join to tabular data based on either field.

Election Results | Join Data from 2020 General Election. All election results are official and have been certified by the Crawford County Pennsylvania Election Board

It has recently been proposed that a key motivation for joining groups is the protection from negative consequences of undesirable outcomes. To test this claim we investigated how experienced outcomes triggering loss and regret impacted people’s tendency to decide alone or join a group, and how decisions differed when voluntarily made alone vs in group. Replicated across two experiments, participants (N=125 and N=496) selected whether to play alone or contribute their vote to a group decision. Next, they chose between two lotteries with different probabilities of winning and losing. The higher the negative outcome, the more participants switched from deciding alone to with others. When joining a group to choose the lottery, choices were less driven by outcome and regret anticipation. Moreover, negative outcomes experienced alone, not part of a group vote, led to worse subsequent choices than positive outcomes. These results suggest that the protective shield of the collective reduces the influence of negative emotions that may help individuals re-evaluate past choices.

Methods The data was collected online on Amazon Mechanical Turk and Prolific. It was processed and analyzed using Matlab and R.

This statistic shows the results of a survey conducted in the United Kingdom in 2017 on the reasons to join a rewards program. Some 72 percent of respondents stated that a reason to join a rewards program would be if they shop very often at the respective shop or make use of the respective service very often. The Survey Data Table for the Statista survey Couponing in the United Kingdom 2017 contains the complete tables for the survey including various column headings.

This dataset is about books and is filtered where the book is Pip Squeak joins the band, featuring 7 columns including author, BNB id, book, book publisher, and ISBN. The preview is ordered by publication date (descending).

NSO_SITE_SUMMARY_PUB_PT:This publication dataset joins the attributes and shape from NSO_SITE_PT to NSO_SUMMARY_TBL. The join between the two data objects is an outer join, which will result in a Site point record being duplicated for each Summary record it is related to. This data is only updated annually after the data entry has been completed for the previous years' field season.

This dataset is about books and is filtered where the book is Feedback : the hinge that joins teaching and learning, featuring 7 columns including author, BNB id, book, book publisher, and ISBN. The preview is ordered by publication date (descending).

The files contain replication codes that generate the tables in our paper "Joining Forces: The Spillover Effects of EPA Enforcement Actions and the Role of Socially Responsible Investors". As not all data is publicly available, we provide pseudo-observations of the datasets to understand the structure of the data and code.

According to a survey, 53 percent of Finns are in favor of Finland joining NATO. Nineteen percent are unsure about whether Finland should join the NATO, and 28 percent are against it.

Data collection for the survey started on Wednesday 23 February, the day before the Russian invasion of Ukraine.

Join Groups is a company. It is located in Cincinnati, the United States and was founded in 2014. The company is part of the Health Care sector, specifically in the Health Care Providers & Services industry.

Upcoming Changes: Please note that our parking system is being improved and this dataset may be disrupted. See more information here.\r
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This dataset contains spatial polygons which represent parking bays across the city. Each bay can also link to it's parking meter, and parking sensor information.\r
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How the data joins:\r
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There are three datasets that make up the live parking sensor release. They are the on-street parking bay sensors, on-street parking bays and the on-street car park bay information. \r
The way the datasets join is as follows. The on-street parking bay sensors join to the on-street parking bays by the marker_id attribute. The on-street parking bay sensors join to the on-street car park bay restrictions by the bay_id attribute. The on-street parking bays and the on-street car park bay information don’t currently join.\r
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Please see City of Melbourne's disclaimer regarding the use of this data. https://data.melbourne.vic.gov.au/stories/s/94s9-uahn

This data package includes the underlying data and files to replicate the calculations, charts, and tables presented in China Should Join the New Trans-Pacific Partnership, PIIE Policy Brief 19-1. If you use the data, please cite as: Petri, Peter A., and Michael G. Plummer. (2019). China Should Join the New Trans-Pacific Partnership. PIIE Policy Brief 19-1. Peterson Institute for International Economics.

Join Industrial Co Limited Company Export Import Records. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.

Feature layer generated from running the Join Features solution

Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

The code used for simulations and graphing is provided as plain txt file and is explained in the paper and in Appendix S1. The screening data set is provided as xlsx file and was generated by following the methods described in detail in the paper and in Appendix S1.

Premise: Both universal and family-specific targeted sequencing probe kits are becoming widely used for the reconstruction of phylogenetic relationships in angiosperms. Within the pantropical Ochnaceae, we show that with careful data filtering, universal kits are equally as capable in resolving intergeneric relationships as custom probe kits. Furthermore, we show the strength in combining data from both kits to mitigate bias and provide a more robust result to resolve evolutionary relationships. Methods: We sampled 23 Ochnaceae genera and used targeted sequencing with two probe kits, the universal Angiosperms353 kit, and a family-specific kit. We used maximum likelihood inference with a concatenated matrix of loci and multispecies-coalescence approaches to infer relationships in the family. We explored phylogenetic informativeness and the impact of missing data on resolution and tree support. Results: For the Angiosperms353 data set, the concatenation approach provided results more congruent with those of the Ochnaceae-specific data set. Filtering missing data was most impactful on the Angiosperms353 data set, with a relaxed threshold being the optimum scenario. The Ochnaceae-specific data set resolved consistent topologies using both inference methods, and no major improvements were obtained after data filtering. The merging of data obtained with the two kits resulted in a well-supported phylogenetic tree. Conclusions: The Angiosperms353 data set improved upon data filtering, and missing data played an important role in phylogenetic reconstruction. The Angiosperms353 data set resolved the phylogenetic backbone of Ochnaceae as equally well as the family-specific data set. All analyses indicated that both Sauvagesia L. and Campylospermum Tiegh. as currently circumscribed are polyphyletic and require revised delimitation. Methods Contig assembly and multiple sequence alignment: The following bioinformatic methods were conducted for both data sets. FastQC v. 0.11.7 (Andrews, 2010) was used to assess the quality of Illumina raw reads from the bait-enriched samples. The raw sequencing reads were then trimmed with Trimmomatic v.0.36 (Bolger et al., 2014) using the settings LEADING:20 TRAILING:20 SLIDINGWINDOW:4:20 MINLEN:36 to remove adapter sequences and portions of low quality. The HybPiper pipeline v.3 (Johnson et al., 2016) was used with default settings to process the quality-checked reads and recover the coding sequences for each locus. Outgroup sequences from the OneKP project (Wickett et al., 2014) were added to each data set. Paired reads of samples enriched with the Angiosperms353 baits and the Ochnaceae baits were mapped to targets using BLASTx option (Altschul et al., 1990) and their respective amino acid target file. The sequences obtained from the BLASTx option were used for subsequent analysis because it was found to recover longer sequences. Mapped reads were then assembled into contigs with SPAdes v3.13.1 (Bankevich et al., 2012), and the retrieve_sequences.py script from the HybPiper suite was used with the .aa flag to produce outputs of a single sequence per gene, which is selected using length, similarity, and coverage. HybPiper flags potential paralogs when multiple contigs are discovered mapping well to a single reference sequence. All loci flagged as potential paralogs were removed from downstream analyses. Subsequent analyses were performed using exon-only data. Sequence recovery for both data sets is listed in Appendix S2. The percentage of gene recovery was calculated using the sum of the captured length per genes per individual divided by the sum of the mean length of all loci. MAFFT v. 7.305b (Katoh et al., 2002) was used to align individual genes using the –auto flag. AMAS (Borowiec, 2016) was used to produce summary statistics for each alignment, evaluating the amount of missing data and the number of parsimony informative sites (Appendices S3 and S4). Phylogenetic inference: Both assembled data sets were individually analyzed using the following approaches. An additional data set was generated by combining the genes from both probe kits. The two target files were tested for gene overlap using BLASTx. Duplicate genes (7 genes) were removed, and all other recovered genes from both data sets were combined resulting in 620 individual loci. Where two species were available for a genus, the species with higher gene recovery from its respective probe kit was selected to represent the genus. Multispecies-coalescent (MSC) approach—The aligned exons were then used to infer individual maximum likelihood gene trees with IQTREE v.2.0 (Nguyen et al., 2015) with 1000 ultrafast bootstraps using the -bb option. Species trees were then inferred from the gene trees using ASTRAL-III v5.5.11 (Zhang et al., 2018) with the -t 2 option providing full annotation outputs, including quartet support to allow visualization of the main topology, and first and second alternative as pie charts on the phylogenetic tree reconstruction. Concatenation approach—An additional analysis was performed by concatenating exon alignments using AMAS for all loci. A species tree was generated from the concatenated exon alignments using IQTREE v.2.0, and then two measures of genealogical concordance were also calculated for each data set; gene concordance factor (gCF) and site concordance factor (sCF) using the options -gcf and -scf in IQTREE v.2.0 (Nguyen et al., 2015). The gCF and sCF values represent the percentage of gene trees containing that branch, and the number of alignment sites supporting that branch, respectively.

Property Cadastral Area Boundary is an aspatial table that identifies the CAD_AREA_BDY lines associated wtith a PROPERTY_POLYGON. VLAT consists of data representing Victoria's land parcels and properties.

This dataset s a raw superset of VMPROP_PROPERTY_CAD_AREA_BDY. It shows the current and retired states of each feature instance. It supports feature versioning (UFI_RETIRED).