This portal contains environmental radiological monitoring data collected in response to the nuclear emergency following the March 11th, 2011 Tohoku earthquake and tsunami. Available data sets include field measurements, field samples, and analysis results. It is designed to contain data sets from other large-scale response efforts should they occur.

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 enclosed package represents radiation data collected with the fixed-wing aircraft (C-12) from 17 March 2011 to 19 March 2011. The data were collected with an array of large thallium activated sodium iodide (NaI(T)) crystals and associated readout electronics to produce time and location referenced measurements. These results represent raw data that have been calibrated to physical units and validated. They do not include any further evaluation.

CERP funds have been used to implement projects in all 34 provinces with a significant portion of these funds used in the South and South West regional command areas. Projects included, but were not limited to, transportation, education, agriculture/irrigation, health care, water and sanitation, and economic, financial and management system improvements. Most CERP projects were relatively low cost and limited in time-duration.

The New York Times is releasing a series of data files with cumulative counts of coronavirus cases in the United States, at the state and county level, over time. We are compiling this time series data from state and local governments and health departments in an attempt to provide a complete record of the ongoing outbreak.

Since the first reported coronavirus case in Washington State on Jan. 21, 2020, The Times has tracked cases of coronavirus in real time as they were identified after testing. Because of the widespread shortage of testing, however, the data is necessarily limited in the picture it presents of the outbreak.

We have used this data to power our maps and reporting tracking the outbreak, and it is now being made available to the public in response to requests from researchers, scientists and government officials who would like access to the data to better understand the outbreak.

The data begins with the first reported coronavirus case in Washington State on Jan. 21, 2020. We will publish regular updates to the data in this repository.

United States Imports: Reaction Initiators & Accelerators, etc, n.e.s.o.i. data was reported at 25.627 USD mn in Jan 2025. This records an increase from the previous number of 22.151 USD mn for Dec 2024. United States Imports: Reaction Initiators & Accelerators, etc, n.e.s.o.i. data is updated monthly, averaging 17.260 USD mn from Jan 2002 (Median) to Jan 2025, with 277 observations. The data reached an all-time high of 49.789 USD mn in Jan 2018 and a record low of 5.617 USD mn in Nov 2003. United States Imports: Reaction Initiators & Accelerators, etc, n.e.s.o.i. data remains active status in CEIC and is reported by U.S. Census Bureau. The data is categorized under Global Database’s United States – Table US.JA132: Imports: by Commodity: 6 Digit HS Code: HS 30 to 48.

IGES Climate and Energy Area has gathered responses and comments from national and local governments, international organisations, leading companies/industry associations, NGOs, think tanks, etc. on the decision of the US to withdraw from the Paris Agreement announced by President Donald J. Trump on 1 June 2017 and compiled them into one tabulated list (it does not cover all the reactions and comments across the world, and the analysis below is within the scope of the list).The list can be accessed here: Reactions to the US decision to withdraw from the Paris AgreementAt the national level, comments came not only from developed countries such as G7 countries, Australia and New Zealand but also emerging countries such as China, India, Brazil, South Africa and Latin American countries. Almost all countries expressed their "disappointment" or “regret” against the US decision to withdraw from the Paris Agreement, and stated that they would continue their commitments to the climate actions under the Paris Agreement regardless of the US decision. According to the press, Russian President Vladimir Putin said "I wouldn’t start to condemn President Trump" and Polish deputy minister of energy commended President Trump’s decision, but there is no country which supported the US decision in their official statements.Out of 50 states in the US, 16 states are against the US decision to withdraw from the Paris Agreement, with all of those states representing 22% of US greenhouse gas emissions and about 40% of US Gross Domestic Product (GDP). On the contrary, there is no US state that supports the decision.Many leading companies, including energy and material-related companies, and industry associations including influential associations in Japan, Germany and the UK, expressed their "disappointment" and "regret" against the US decision, while indicating their support to the Paris Agreement, its emission reduction targets, and continuous commitments on climate actions. As a background to this, companies see climate change as a reality, and climate actions as investment opportunities. On the other hand, US coal industries expressed support for the decision by the Trump administration, but conversely there are no other companies that supported the decision other than them.Overall, there was no opinion that the US decision would cause the Paris Agreement to collapse nor that it would cause climate actions to be delayed. Also, a number of statements are using the phrase "decision to withdraw from the Paris Agreement" rather than "withdraw from the Paris Agreement", which accurately reflects the situation that the US will not withdraw from the Paris Agreement immediately.(Contact: ce-info@iges.or.jp) / Keywords: Climate Change【リソース】Fulltext

Chemical synthesis planning is a key aspect in many fields of chemistry, especially drug discovery. Recent implementations of machine learning and artificial intelligence techniques for retrosynthetic analysis have shown great potential to improve computational methods for synthesis planning. Herein, we present a multiscale, data-driven approach for retrosynthetic analysis with deep highway networks (DHN). We automatically extracted reaction rules (i.e., ways in which a molecule is produced) from a data set consisting of chemical reactions derived from U.S. patents. We performed the retrosynthetic reaction prediction task in two steps: first, we built a DHN model to predict which group of reactions (consisting of chemically similar reaction rules) was employed to produce a molecule. Once a reaction group was identified, a DHN trained on the subset of reactions within the identified reaction group, was employed to predict the transformation rule used to produce a molecule. To validate our approach, we predicted the first retrosynthetic reaction step for 40 approved drugs using our multiscale model and compared its predictive performance with a conventional model trained on all machine-extracted reaction rules employed as a control. Our multiscale approach showed a success rate of 82.9% at generating valid reactants from retrosynthetic reaction predictions. Comparatively, the control model trained on all machine-extracted reaction rules yielded a success rate of 58.5% on the validation set of 40 pharmaceutical molecules, indicating a significant statistical improvement with our approach to match known first synthetic reaction of the tested drugs in this study. While our multiscale approach was unable to outperform state-of-the-art rule-based systems curated by expert chemists, multiscale classification represents a marked enhancement in retrosynthetic analysis and can be easily adapted for use in a range of artificial intelligence strategies.

This dataset contains information about requests for animal assistance, relocation, and/or rescue completed by the Urban Park Rangers

An online survey conducted in the United States during the second quarter of 2021, showed that 34 percent of mobile gamers have clicked on the ads that appeared on the gaming apps. Ads on smartphones in general brought 36 percent of respondents to the brand's website. Moreover, 15 percent of mobile gamers downloaded the brand app after seeing the ad. And 13 percent of mobile internet users sent the link or a screenshot of the brand to someone else. The same survey also revealed that 53 percent of mobile gamers play while watching TV.

Multiple recent studies have focused on unraveling the content of the medicinal chemist’s toolbox. Here, we present an investigation of chemical reactions and molecules retrieved from U.S. patents over the past 40 years (1976–2015). We used a sophisticated text-mining pipeline to extract 1.15 million unique whole reaction schemes, including reaction roles and yields, from pharmaceutical patents. The reactions were assigned to well-known reaction types such as Wittig olefination or Buchwald–Hartwig amination using an expert system. Analyzing the evolution of reaction types over time, we observe the previously reported bias toward reaction classes like amide bond formations or Suzuki couplings. Our study also shows a steady increase in the number of different reaction types used in pharmaceutical patents but a trend toward lower median yield for some of the reaction classes. Finally, we found that today’s typical product molecule is larger, more hydrophobic, and more rigid than 40 years ago.

United States Imports: Reaction Initiators & Acceler & Catalyt Prep n.e.s.o.i data was reported at 133.916 USD mn in Jan 2025. This records an increase from the previous number of 103.490 USD mn for Dec 2024. United States Imports: Reaction Initiators & Acceler & Catalyt Prep n.e.s.o.i data is updated monthly, averaging 92.428 USD mn from Jan 2002 (Median) to Jan 2025, with 277 observations. The data reached an all-time high of 260.238 USD mn in Mar 2021 and a record low of 38.274 USD mn in Mar 2009. United States Imports: Reaction Initiators & Acceler & Catalyt Prep n.e.s.o.i data remains active status in CEIC and is reported by U.S. Census Bureau. The data is categorized under Global Database’s United States – Table US.JA129: Imports: by Commodity: 4 Digit HS Code.

United States Imports: cif: Reaction Initiators & Acceler & Catalyt Prep n.e.s.o.i data was reported at 135.929 USD mn in Jan 2025. This records an increase from the previous number of 105.171 USD mn for Dec 2024. United States Imports: cif: Reaction Initiators & Acceler & Catalyt Prep n.e.s.o.i data is updated monthly, averaging 93.962 USD mn from Jan 2002 (Median) to Jan 2025, with 277 observations. The data reached an all-time high of 262.750 USD mn in Mar 2021 and a record low of 38.954 USD mn in Mar 2009. United States Imports: cif: Reaction Initiators & Acceler & Catalyt Prep n.e.s.o.i data remains active status in CEIC and is reported by U.S. Census Bureau. The data is categorized under Global Database’s United States – Table US.JA129: Imports: by Commodity: 4 Digit HS Code.

FAERS database is designed to support the FDA’s post-marketing safety surveillance program for drug and therapeutic biologic products. The Reaction file contains all "Medical Dictionary for Regulatory Activities" (MedDRA) terms coded for the adverse event (1 or more).

Reaction SMILES dataset update (now 733K), each line in the file represents a valid reaction SMILES. Source material US patents (2005 - 2016) collection by Daniel Lowe with data enhancement. Source material also includes reaction SMILES drawn from the general literature. Also includes USPTO data from 2022 and 2023. All SMILES are valid by RDKit. Also see https://kmt.vander-lingen.nl

This project estimates hourly demand response availability across the continental U.S. for the year 2006. The resulting data set is disaggregated by balancing authority area, end use, and grid application. End uses include 14 categories across residential, commercial, industrial and municipal sectors. Grid applications include the 5 bulk power system services of regulation reserve, flexibility (or ramping) reserve, contingency reserve, energy, and capacity. Based on the physical requirements of the various bulk power system services and the estimated end use electric load shapes, potential availability of demand response is calculated and provided as a series of csv files.

Reactions extracted by text-mining from United States patents published between 1976 and September 2016. The reactions are available as CML or reaction SMILES. Note that the reactions SMILES are derived from the CML. The files can be unzipped using a program like 7-Zip.The reactions were extracted using an enhanced version of the reaction extraction code described in https://www.repository.cam.ac.uk/handle/1810/244727with LeadMine (https://www.nextmovesoftware.com/leadmine.html) used for chemical entity recognition.General tips:Duplicate reactions are frequent due to the same or highly similar text occurring in multiple patents, this is especially true when combining the applications and grant datasets, many reactions from applications will later appear in patent grants.Paragraph numbers are only present for 2005+ patent grants and patent applications.Multiple reactions can be extracted from the same paragraph.Atom maps in the reactions SMILES are derived using Epam's Indigo toolkit. While typically correct, the atom-maps are wrong in many cases and hence should not be entirely relied on.The reactions have been filtered to remove common cases of incorrectly extracted reactions:All product atoms must be accounted for by the atom-mappingThe product(s) must have >8 heavy atomsThe product must not be charged if it is a single componentThe number of products must be

In 2024, the number of data compromises in the United States stood at 3,158 cases. Meanwhile, over 1.35 billion individuals were affected in the same year by data compromises, including data breaches, leakage, and exposure. While these are three different events, they have one thing in common. As a result of all three incidents, the sensitive data is accessed by an unauthorized threat actor. Industries most vulnerable to data breaches Some industry sectors usually see more significant cases of private data violations than others. This is determined by the type and volume of the personal information organizations of these sectors store. In 2024 the financial services, healthcare, and professional services were the three industry sectors that recorded most data breaches. Overall, the number of healthcare data breaches in some industry sectors in the United States has gradually increased within the past few years. However, some sectors saw decrease. Largest data exposures worldwide In 2020, an adult streaming website, CAM4, experienced a leakage of nearly 11 billion records. This, by far, is the most extensive reported data leakage. This case, though, is unique because cyber security researchers found the vulnerability before the cyber criminals. The second-largest data breach is the Yahoo data breach, dating back to 2013. The company first reported about one billion exposed records, then later, in 2017, came up with an updated number of leaked records, which was three billion. In March 2018, the third biggest data breach happened, involving India’s national identification database Aadhaar. As a result of this incident, over 1.1 billion records were exposed.

The data available here identifies and describes a sampling of publicly available datasets about the 911 emergency response system. This list of datasets is a resource for researchers, civic technologists, activists, and journalists seeking to learn more about the 911 emergency response system. The list helps to identify relevant datasets that could be used to understand various types of 911 activity.

During the first quarter of 2021, the R911 NAT created a list of priority cities including the top 100 cities by population, all state capitals, and the 82 cities that are home to Code for America Brigades. The team then conducted internet searches for each city using terms like “911 calls for service” and “open 911 data.” The dataset and a codebook defining each of these fields are provided as .csv files within a zip file.

Note: this file does not contain the actual 911 datasets, which often number in the millions of records. The data_link field contains the URL of the site where each dataset is publicly available.

See also: The Reimagine 911 knowledge base at: https://reimagine-911.gitbook.io/knowledge-base

Contributors: This open data review was performed by the Code for America Reimagine 911 National Action Team. Contributing team members include: Aleks Hatfield, Brandon Bolton, Chizo Nwagwu, Dan Stormont, Elaine Chow, Em Spalti, Erica Pauls, Gio Sce, Gregory Janesch, Iva Momcheva, Ivelina Momcheva, Jamie Klenetsky Fay, Jason Trout, Jaya Prasad Jayakumar, Jennifer Miller, Jim Grenadier, Joanna Smith, Jonathan Melvin, Katlyn McGraw, Margaret Fine, Mariah Lynch, Micah Mutrux, Michelle Hoogenhout, Patina Herring, Peter Zeglen, Sarah Graham, Sebastian Barajas

The Vegetation-Ecosystem Modeling and Analysis Project (VEMAP) was a large, collaborative, multi-institutional, international effort whose goal was to evaluate the sensitivity of terrestrial ecosystem and vegetation processes to altered climate forcing and elevated atmospheric CO2. Phase 1 of the VEMAP project developed historical (1895-1993) data sets of observed climate, soils, and vegetation compatible with the requirements of ecosystem models and vegetation distribution models. See the VEMAP Phase 1 User's Guide for more information. Phase 2 developed historical (1895-1993) gridded data sets of climate (temperature, precipitation, solar radiation, humidity, and wind speed) and projected (1994-2100) gridded annual and monthly climate data sets using output from two climate system models (CCCma (Canadian Centre for Climate Modeling and Analysis) and Hadley Centre models). See the VEMAP Phase 2 User's Guide for additional background information.Two Phase 2 model experiments were run. First, a set of selected biogeochemical models and coupled biogeochemical-biogeographical models were run from 1895 to 1993 to compare model responses to the historical time series and current ecosystem biogeochemistry. Second, these same models were run on the projected 1994 to 2100 data to compare their ecological responses to transient scenarios of climate and atmospheric CO2 change. Model runs were performed for daily, monthly, and annual gridded data sets. The output of the annual model runs in VEMAP grid format are contained in this data set.The models investigated included five biogeochemical cycling models, which simulate plant production and nutrient cycles, but rely on a static land-cover type, and two dynamic global vegetation models (DGVMs) that combine biogeochemical cycling processes with dynamic biogeographical processes including succession and fire simulation.Biogeochemical Cycling ModelsBiome-BGC (BioGeochemical Cycles)CenturyCentury rxveg GTEC (Global Terrestrial Ecosystem Carbon Model)TEM (Terrestrial Ecosystem Model)Dynamic Global Vegetation ModelsLPJ (Lund-Potsdam-Jena MC1 (MC 5 modified Century)VEMAP 2 model intercomparison results have been published by Schimel et al.(2000), Bachelet et al. (2003) and Gordon and Famiglietti (2004). Related Data SetsAvailable on-line [http://www.daac.ornl.gov] from Oak Ridge National Laboratory Distributed Active Archive CenterVEMAP 2: U.S. ANNUAL CLIMATE, 1895-1993 VEMAP 2: U.S. MONTHLY CLIMATE, 1895-1993, VERSION 2 VEMAP 2: U.S. DAILY CLIMATE, 1895-1993 VEMAP 2: U.S. ANNUAL CLIMATE CHANGE SCENARIOS VEMAP 2: U.S. MONTHLY CLIMATE CHANGE SCENARIOS, VERSION 2 VEMAP 2: U.S. DAILY CLIMATE CHANGE SCENARIOS VEMAP 2: Annual Ecosystem Model Responses to U.S. Climate Change, 1994-2100