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Stripe is an American company that allows both private individuals and businesses to accept payments online. Companies using Stripe are commonly found in the US, UK and in the retail and SaaS industry. 50% of Stripe customers are in the US and 8% are in the UK. Stripe is mainly used by companies with 1-100 employees and 1M-100M dollars in revenue. Of all the customers that are using Stripe, a majority (70%) are small (<50 employees), 10% are large (>1000 employees) and 20% are medium-sized. Our Stripe usage data goes back up to 10 years.

Lead for Business tracks Stripe users across millions of companies worldwide and curates the companies who use Stripe with full company information including geography, industry, Revenue and more.

Comprehensive dataset of Stripe's supported countries, categorized by support level including 46 fully supported countries, 5 extended network countries, and 2 preview markets.

16500 Global import shipment records of Stripe Card with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.

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Over ** percent of all the websites in the world that use Stripe as a check-out option in 2023 originate from the United States. This according to data from an intelligence tool that tracks the adoption of certain technologies. The number for the U.S. is about as much as the number of websites for all of Europe combined. Japan's figure closely resembles that of Canada, potentially indicating that the Irish payment processor is used relatively often in Asia-Pacific compared to other parts of the world.

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Data reported in research published in Crop Science, “Mapping the quantitative field resistance to stripe rust in a hard winter wheat population ‘Overley’ × ‘Overland.’” Authors are Wardah Mustahsan, Mary J. Guttieri, Robert L. Bowden, Kimberley Garland-Campbell, Katherine Jordan, Guihua Bai, Guorong Zhang from USDA Agricultural Research Service and Kansas State University. This study was conducted to identify quantitative trait loci (QTL) associated with field resistance to stripe rust, also known as yellow rust (YR), in hard winter wheat. Stripe rust infection type and severity were rated in recombinant inbred lines (RILs, n=204) derived from a cross between hard red winter wheat cultivars ‘Overley’ and ‘Overland’ in replicated field trials in the Great Plains and Pacific Northwest. RILs (n=184) were genotyped with reduced representation sequencing to produce SNP markers from alignment to the ‘Chinese Spring’ reference sequence, IWGSC v2.1, and from alignment to the reference sequence for ‘Jagger’, which is a parent of Overley. Genetic linkage maps were developed independently from each set of SNP markers. QTL analysis identified genomic regions on chromosome arms 2AS, 2BS, 2BL, and 2DL that were associated with stripe rust resistance using multi-environment best linear unbiased predictors for stripe rust infection type and severity. Results for the two linkage maps were very similar. PCR-based SNP marker assays associated with the QTL regions were developed to efficiently identify these genomic regions in breeding populations.Field response to YR was evaluated in seven trials: Rossville, KS (2018 and 2019), Hays, KS (2019), Pullman, WA (2019 and 2020) and Central Ferry, WA (2019 and 2020). An augmented experimental design was used at Rossville, KS with highly replicated checks and two full replications of RILs (n=187 in 2018; n=204 in 2019). The field experiment at Hays was arranged in a partially replicated augmented design with one or two replications of each RIL (n=194). The parental checks (Overley and Overland) were represented in three blocks for each of the two field replications at Hays, and RILs were distributed among blocks; not all RILs were present in each replication. RILs were arranged in an augmented design with two replications at Pullman (n=204 RILs) and Central Ferry (n=155 RILs in 2019; n=204 in 2020). At Pullman and Central Ferry.The trials at Rossville, KS were inoculated using an inoculum consisting of equal parts of four isolates that were all virulent to Yr9. Two isolates were collected in Kansas in 2010 and had virulence to Yr17 but not QYr.tamu-2B. The other two isolates were from Kansas in 2012 and had virulence to QYr.tamu-2B, but not Yr17. Susceptible spreader rows (KS89180B, carrying Yr9) were inoculated several times during the tillering stage in the evenings with an ultra-low volume sprayer using a suspension of 2 mL of fresh urediniospores in 1 L of Soltrol 170 isoparaffin oil. Trials at Pullman, WA and Central Ferry, WA were evaluated under natural inoculum supplemented by a mixture of isolates collected in the previous field season. The trial at Hays, KS was evaluated under natural infection.Data collection at Rossville, KS began once the susceptible check (KS89180B) had an infection severity coverage of ~10% and continued until senescence. In Rossville, disease ratings (IT and SEV) were collected on 16, 22, and 28th of May 2019. Most ratings in Rossville were taken some time after heading from Zadoks stages 55 to 70. In Pullman, disease ratings were collected on July 1 and 12. In Central Ferry, disease ratings were taken on 12th and 18th of June 2019. The second rating date was used for subsequent statistical analysis. In Hays, disease ratings were taken on June 1, 2019, when the plants were in early booting or heading stages (Zadoks 31-41). Stripe rust evaluations were measured using two disease rating scales: IT (0-9; from no infection to highly susceptible, Line and Qayoum, 1992) and SEV based on visual estimation of the percent flag leaf area affected by the pathogen including associated chlorosis and necrosis (0-100%).DNA was extracted from seedlings, and genotyping-by-sequencing was conducted as described previously (Guttieri, 2020) on a subset of 189 lines (187 RILS and 2 parents) of which 23 RILs were F6-derived and 164 RILs were F9-derived. Single nucleotide polymorphisms (SNPs) were identified in parallel using reference-based calling in the TASSEL pipeline (Bradbury et al., 2007) using both the IWGSC v2.1 reference genome (Zhu et al., 2021) and the Jagger reference sequence (Wheat Genomes Project (http://www.10wheatgenomes.com/10-wheat-genomes-project-and-the-wheat-initiative/). The TASSEL pipeline was executed with the following parameters: minimum read count = 1, minimum quality score = 0, minimum locus coverage = 0.19, and minimum minor allele frequency = 0.005, minimum heterozygous proportion = 0, and removal of minor SNP states. The resulting SNP datasets from each reference sequence were filtered in TASSEL by taxa (RILs) and sites (SNPs). The RILs were filtered to include those RILs for which at least 20% sites were present. The sites were filtered to include sites for which > 60% of RILs were called, minor allele frequency (MAF) > 0.25, maximum allele frequency < 0.75, maximum heterozygous proportion = 0.25, and removal of minor SNP states. The ABH plugin in TASSEL was applied to this reduced dataset to identify parental genotypes.Resources in this dataset:Resource Title: Multilocation Stripe Rust Data File Name: MultiLocRawData_Yr.xslxResource Title: OvOv_CS_TasselSNPCalls File Name: KSM17-OvOv-parentsmerge1.hmp.txt Resource Description: Output of TASSEL GBS SNP calling pipeline using Chinese Spring v2 refseq. Starting point for map construction pipeline.Resource Title: OvOv GBS SNP Calls Jagger RefSeq File Name: KSM17-OvOv-Jaggerpmerge1.hmp.txt Resource Description: TASSEL output from reference-based SNP calling using the Jagger reference sequenceResource Title: QTL-Associated KASP Markers with IT and SEV BLUPs File Name: KASP_Data_IT_SEV.xlsx Resource Description: Multilocation best linear unbiased predictors (BLUPs) for stripe rust infection type and severity of recombinant inbred lines. KASP assay results for QTL-associated SNPs, coded Overley = 2, Overland = 0, Het = 1, Missing = "."

322 Global import shipment records of Stripe Multi with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.

Objective: To assess the impact of an interprofessional case-based training program to enhance clinical knowledge and confidence among clinicians working in high HIV-burden settings in sub-Saharan Africa (SSA) Setting: Health professions training institutions and their affiliated clinical training sites in 12 high HIV-burden countries in SSA. Participants: Cohort comprising pre-service and in-service learners, from diverse health professions, engaged in HIV service delivery. Intervention: A standardized, interprofessional, case-based curriculum designed to enhance HIV clinical competency, implemented between October 2019 and April 2020. Main outcome measures: The primary outcomes measured were knowledge and clinical confidence related to topics addressed in the curriculum. These outcomes were assessed using a standardized online assessment, completed before and after course completion. A secondary outcome was knowledge retention at least six months post-intervention, measured using the same standardized assessment, six months after training completion. We also sought to determine what lessons could be learned from this training program to inform interprofessional training in other contexts. Results: Data from 3027 learners were collected: together nurses (n=1145, 37.9%) and physicians (n=902, 29.8%) constituted the majority of participants; 58.1% were pre-service learners (n=1755) and 24.1% (n=727) had graduated from training within the prior year. Knowledge scores were significantly higher, post -participation compared to pre-participation, across all content domains, regardless of training level and cadre (all p<0.05). Among 188 learners (6.2%) who retook the test at >6 months, knowledge and self-reported confidence scores were greater compared to pre-course scores (all p<0.05). Conclusion: To our knowledge this is the largest interprofessional, multi-country training program established to improve HIV knowledge and clinical confidence among HCP workers in SSA. The findings are notable given the size and geographical reach and demonstration of sustained confidence and knowledge retention post course completion. The findings highlight the utility of interprofessional approaches to enhance clinical training in SSA. Methods The study was conducted using data from the STRIPE HIV program. The program was launched across 20 health professions training institutions in 14 countries in October 2019. All learners who completed a pre and post-test assessment for an in-person training conducted between October 1, 2019 and March 31, 2020, were included in the study. After April 2020, all training transitioned to online format given widespread restrictions on in-person learning related to the COVID-19 pandemic; these learners were excluded from this analysis. As previously described, training included 17 case-based modules, typically presented over two days, and was designed to foster interprofessional discussion and facilitate learning related to HIV clinical management, quality improvement and interprofessional collaborative practice. Training content included required modules on initiating HIV therapeutics in women of childbearing age (“HIV and Women”), management of opportunistic infections (“HIV-TB”), prevention of mother to child transmission (“PMTCT”) and pediatric HIV (“Paediatric Care”), in which all learners participated regardless of the stage of their career or professional cadre. These modules were all created by the study team which included local HIV practitioners and international and local educational experts. In addition to creation of the learning materials, the study team provided local educators at each partner institution with training resources to implement the course. These local partners were encouraged to ensure that each training course included a diverse mix of professional cadres and, where feasible, a mix of health professionals at different stages of their career (pre-service, post-graduate but within 12 months of graduation, and greater than 12 months post-graduation). The study team also provided training resources to facilitate training of local facilitators. The frequency of training courses offered, the ratio of learners to facilitators, mix of cadres and course timing were all determined by local partner institutions. Given scarcity of training resources, some health professions training institutions had to decline access for eligible candidates; in such circumstances, participation of early career professionals was prioritized over pre-service learners. Cohort: This was a convenience sample, including all learners who participated in the STRIPE HIV training program and had completed both pre- and post-training assessments during the study period. In addition to capturing learner demographic information, the assessment assessed learner (1) clinical and technical knowledge related to the learning objectives outlined in the program and (2) self-reported confidence in skills and abilities covered in the program, including (a) confidence to participate in HIV service delivery, specific to each cadre’s scope of practice, in the domains addressed in the course, (b) confidence to employ quality improvement tools and (c) confidence to practice as part of an interprofessional team. Knowledge was assessed using a series of domain-specific multiple-choice questions; all questions were the same for all participants regardless of training context, participant cadre, training institution, and country. Confidence was assessed on a four-point Likert-type scale, ranging from 1= “I feel uncomfortable with this topic/need supervision from my supervisor” to 4= “I feel very comfortable with this topic/without supervision as though in independent practice.” (Supplemental digital appendix). All learners completed the initial assessment at the time of program enrollment, typically within 24 hours of starting training. They then completed the same assessment immediately after completing the course, typically within 48 hours. For most participants, these pre and post program assessments were accessed on the training program’s website. However, for a small subset that did not have internet or computer access, assessments were completed on paper, and subsequently uploaded into the project database by local research staff. Starting in October 2020, we invited all participants to retake the same assessment at least six months after when they had participated in the program. This repeat assessment was administered electronically via email (Qualtrics, version XM; Provo, Utah; 2013). To increase uptake of this repeat assessment, all individuals who completed it were entered into a lottery to receive a US $50 prize voucher for internet data or airtime. Analysis: We only included data on learners for whom we had both pre-course and post-course assessment data, excluding those participants for whom we did not have both data points. For these eligible learners, we used descriptive statistics to summarize demographic characteristics of program participants, stratifying results by gender, health profession cadre and professional career stage (RStudio Version 1.3.1093). We separately analyzed (1) differences in pre-course and post-course knowledge and self-reported confidence using Wilcoxon signed-rank tests and (2) differences in knowledge and self-reported confidence between cadres and career stage using ANOVA and Tukey’s HSD test. For the subgroup of learners for whom both pre- and post-course assessment results were available, and who had also completed the post-course assessment >6 months after completion of the course, we calculated the change in levels of knowledge and self-reported confidence between the post > 6 months assessment and the pre-course assessment sores using Wilcoxon signed-rank test. We applied Wilcoxon signed-rank tests because distributions of assessment response variables were not normally distributed. All reported P values were two sided.

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This study presents the first set of maps and band-merged catalog from the Herschel Stripe 82 Survey (HerS). Observations at 250, 350, and 500 micron (µm) were taken with the Spectral and Photometric Imaging Receiver (SPIRE) instrument onboard the Herschel Space Observatory. HerS covers 79 square degrees along the SDSS Stripe 82 to an average depth of 13.0, 12.9, and 14.8 mJy beam^-1 (including confusion) at 250, 350, and 500 um, respectively. HerS was designed to measure correlations with external tracers of the dark matter density field, either point-like (i.e., galaxies selected from radio to X-ray) or extended (i.e., clusters and gravitational lensing), in order to measure the bias and redshift distribution of intensities of infrared-emitting dusty star-forming galaxies and active galactic nuclei. By locating HerS in Stripe 82, the authors maximize the overlap with available and upcoming cosmological surveys. The band-merged catalog contains 3.3 x 10⁴ sources detected at a significance of >~ 3 sigma (including confusion noise). The maps and catalog are available at http://www.astro.caltech.edu/hers/. This table contains the first HerS band-merged point source catalog based on observations covering 79 deg² in the equatorial Stripe 82, spanning 13 to 37 degrees (0^h 54^m to 2^h 24^m ) in RA, and -2 to +2 degrees in Declination. The SPIRE beams are 18.1, 25.2 and 36.6 arcseconds at 250, 350 and 500 um, respectively. The band-merged catalog was constructed, after filtering, with DESPHOT (Roseboom et al. 2010, MNRAS, 409, 48), using 250-um sources (extracted with STARFINDER: Diolaiti et al. 2000, A&AS, 147, 335) as positional priors. The authors included sources with S/N greater than 3, whose completeness is estimated to be 50% (see Figure 7 of the reference paper), with a false detection rate less than 1%, and which had reasonable residuals (i.e., chi² < 10). Next, they identified obviously extended sources - 24 in total - where their extended nature resulted in them being broken up into multiple components by the filter, and removed them. This results in a catalog with 32,815 sources at 250 um, of which 13,300 and 3,276 have similarly defined 3-sigma detections at 350 and 500 um, respectively. The authors expect a false positive rate of 1.2 +/- 0.2 deg^-2 : thus, across the 79 deg² of HerS, they expect 96 +/- 16 spurious sources. The following local extended sources were removed:

 Name, RA, DEC NGC 0493,20.537458,0.945361 UGC 00890,20.283333,1.373333 UGC 00892,20.319166,-0.544491 NGC 0428,18.232125,0.981556 NGC 0799,30.551407,-0.100629 NGC 0800,30.549358,-0.130432 NGC 0450,18.876840,-0.860973 NGC 0497,20.599064,-0.875207 NGC 0867,34.269910,1.244202 UGC 01725,33.607833,1.469833 NGC 0570,22.244325,-0.948996 UGC 00711,17.153750,1.641667 UGC 00726,17.489833,-1.749694 NGC 0550,21.677292,2.022361 NGC 0585,22.9255833,-0.9333056 UGC 01123,23.533209,-1.032286 2MASX J01434929-0048547,25.955091,-0.815256 NGC 0856,33.409831,-0.717287 UGC 01698,33.082019,-0.811513 CGCG 385-007,17.256708,1.378194 UGC 00790,18.657792,1.180167 2MFGC 01002,19.930083,1.630778 2MFGC 00979,19.642792,1.747889 UGC 00847,19.768317,-0.138572 

This database table was created by the HEASARC in March 2014 based on a FITS file (v2.0, uploaded Nov 18, 2013, of hers.catalogue_3sig250_no_extended.fits) containing the catalog which was obtained from the HerS web site, viz., http://www.astro.caltech.edu/hers/Catalogs.html. Some of the values for the name parameter in the HEASARC's implementation of this table were corrected in April 2018. This is a service provided by NASA HEASARC .

This dataset contains the predicted prices of the asset stripe + paradigm = tempo over the next 16 years. This data is calculated initially using a default 5 percent annual growth rate, and after page load, it features a sliding scale component where the user can then further adjust the growth rate to their own positive or negative projections. The maximum positive adjustable growth rate is 100 percent, and the minimum adjustable growth rate is -100 percent.

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This table contains some of the data from the latest release of the Stripe 82 X-ray (82X) survey point-source catalog, which currently covers 31.3 deg² of the Sloan Digital Sky Survey (SDSS) Stripe 82 Legacy field. In total, 6,181 unique X-ray sources are significantly detected with XMM-Newton (> 5 sigma) and Chandra (> 4.5 sigma). This 31 deg² catalog release includes data from XMM-Newton cycle AO 13, which approximately doubled the Stripe 82X survey area. The flux limits of the Stripe 82X survey are 8.7 x 10^-16 erg s^-1 cm^-2, 4.7 x 10^-15 erg s^-1 cm^-2, and 2.1 x 10^-15 erg s^-1 cm^=2^ in the soft (0.5 - 2.0 keV), hard (2 - 10 keV), and full (0.5 - 10 keV) bands, respectively, with approximate half-area survey flux limits of 5.4 x 10^-15 erg s^-1 cm^-2, 2.9 x 10^-14 erg s^-1 cm^-2, and 1.7 x 10^-14 erg s^-1 cm^-2, respectively. The authors matched the X-ray source lists to available multi-wavelength catalogs, including updated matches to the previous release of the Stripe 82X survey; 88% of the sample is matched to a multi-wavelength counterpart. Due to the wide area of Stripe 82X and rich ancillary multi-wavelength data, including coadded SDSS photometry, mid-infrared WISE coverage, near-infrared coverage from UKIDSS and VISTA Hemisphere Survey (VHS), ultraviolet coverage from GALEX, radio coverage from FIRST, and far-infrared coverage from Herschel, as well as existing ~30% optical spectroscopic completeness, this study is beginning to uncover rare objects, such as obscured high-luminosity active galactic nuclei at high redshift. The Stripe 82X point source catalog is a valuable data set for constraining how this population grows and evolves, as well as for studying how they interact with the galaxies in which they live. The authors derive the XMM-Newton number counts distribution and compare it with their previously reported Chandra log N - log S relations and other X-ray surveys. Throughout this study, the authors adopt a cosmology of H₀ = 70 km s^-1 Mpc^-1, Omega_M = 0.27, and Lambda = 0.73. The XMM-Newton and Chandra X-ray sources were matched with sources in the SDSS, WISE, UKIDSS, VHS, GALEX, FIRST and Herschel databases using the maximum likelihood estimator (MLE) method, as discussed in detail in Section 4 of the reference paper. This table contains the list of 1,146 Chandra sources detected in the SDSS Stripe 82. A related table SDSSS82XMM contains the list of 5,220 XMM-Newton sources detected in the SDSS Stripe 82. This table was initially created by the HEASARC in April 2014 based on the machine-readable version of the table ('Properties of SDSS Quasars Detected by Chandra') described in Appendix B1 of the reference paper (LaMassa et al. 2013, MNRAS, 436, 3581) which was obtained from the CDS (their catalog J/MNRAS/436/3581/ file chands82.dat). The present version was created by the HEASARC in January 2017 based on CDS Catalog J/ApJ/817/172 file chandra.dat. This is a service provided by NASA HEASARC .

Stripe is a global payment services provider. Founded in 2010, the solution allows online merchants and vendors to accept payments for products and services offered through their own websites and mobile apps, as well as for those offered through third-party online marketplaces and platforms. Stripe works on all web-enabled devices. Stripe has been deployed by a host of businesses globally, including online merchants, marketplaces, and platforms. Prominent brands that support Stripe include Grab, ShopStyle, Shopify, and Lyft. Read More

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Norway Imports: West Bank/Gaza Stripe data was reported at 0.000 NOK th in Jun 2018. This stayed constant from the previous number of 0.000 NOK th for May 2018. Norway Imports: West Bank/Gaza Stripe data is updated monthly, averaging 0.000 NOK th from Jan 1988 (Median) to Jun 2018, with 366 observations. Norway Imports: West Bank/Gaza Stripe data remains active status in CEIC and is reported by Statistics Norway. The data is categorized under Global Database’s Norway – Table NO.JA017: Imports: by Country.