PalaeoQUMP was headed by Prof Sandy Harrison of the University of Bristol, with co-investigators at the University of Southampton and Durham University, as part of QUEST (Quantifying and Understanding the Earth System). This dataset collection contains data from charcoal records that have been compiled for the Mediterranean, Black Sea-Caspian and Sea corridor region.

The Data Replication Software market is experiencing robust growth, driven by the increasing need for data protection, disaster recovery, and business continuity in an increasingly digital world. The market's expansion is fueled by several key factors, including the proliferation of cloud computing, the rise of big data, and stringent data governance regulations. Organizations are adopting data replication solutions to ensure data availability, minimize downtime, and comply with regulatory requirements. The growing adoption of hybrid and multi-cloud environments further boosts market demand, as businesses need efficient solutions to manage data across various platforms. Competition is intense, with established players like IBM and Hitachi competing against agile newcomers like Rubrik and Fivetran. The market is segmented by deployment type (on-premise, cloud), application type (database, file, application), and industry vertical. While the precise market size for 2025 isn't provided, based on industry reports and assuming a conservative CAGR of 15% (a reasonable estimate given the rapid technological advancements in this space), we can project a market size in the billions of dollars, with a steady growth trajectory throughout the forecast period (2025-2033). The market's growth is not without challenges. Integration complexities, especially in complex hybrid environments, can hinder adoption. Moreover, cost considerations, particularly around data storage and bandwidth, remain a significant restraint for some organizations. Future growth will likely depend on vendors' ability to offer seamless integration across various platforms, improved data security features to address growing concerns around data breaches, and cost-effective solutions catering to businesses of all sizes. The development of AI-powered data replication solutions capable of automating processes and optimizing resource allocation will be a key trend shaping the future of this market. The increasing demand for real-time data replication and data analytics integration will further drive innovation and market expansion in the coming years. The competitive landscape continues to evolve with mergers, acquisitions, and the emergence of innovative solutions.

.QUEST Whois Database, discover comprehensive ownership details, registration dates, and more for .QUEST TLD with Whois Data Center.

Quest Diagnostics is a leading provider of diagnostic information services. Quest Diagnostics offers a wide range of laboratory testing services designed to provide insights that help healthcare providers make better decisions about patient care. These services include routine blood tests, genetic testing, drug screening, and more specialized tests for various diseases and conditions. Quest Diagnostics serves a diverse clientele, including individual patients, physicians, hospitals, and employers. The Quest Diagnostics business model revolves around providing high-quality, timely, and accurate diagnostic information. Quest Diagnostics operates a vast network of laboratories and patient service centers, using advanced technology to ensure efficient and reliable testing. Quest Diagnostics generates revenue by charging fees for each test performed, often billing patients or their insurance providers. They also form strategic partnerships with healthcare providers and employers to offer comprehensive diagnostic solutions. You can download the complete list of key information about Quest Diagnostics locations, contact details, services offered, and geographical coordinates, beneficial for various applications like store locators, business analysis, and targeted marketing. The Quest Diagnostics data you can download includes:

Identification & Location:


  Store_ name, address, address_line_2, city, state, zip_code, latitude, longitude, geo_accuracy, country_code, county, 


Contact Information:


   Phone_number, fax_number


Operational Details & Services:


  Store_hours, 

QUEST projects both used and produced an immense variety of global data sets that needed to be shared efficiently between the project teams. These global synthesis data sets are also a key part of QUEST's legacy, providing a powerful way of communicating the results of QUEST among and beyond the UK Earth System research community. This dataset contains global Population Distribution (1990), Terrestrial Area and Country Name Information on a One by One Degree Grid Cell Basis.

One method of representing a high-rank tensor as a (hyper-)product of lower-rank tensors is the tensor hypercontraction (THC) method of Hohenstein et al. This strategy has been found to be useful for reducing the polynomial scaling of coupled-cluster methods by representation of a four-dimensional tensor of electron-repulsion integrals in terms of five two-dimensional matrices. Pierce et al. have already shown that the application of a robust form of THC to the particle–particle ladder (PPL) term reduces the cost of this term in couple-cluster singles and doubles (CCSD) from O(N6) to O(N5) with negligible errors in energy with respect to the density-fitted variant. In this work, we have implemented the least-squares variant of THC (LS-THC) which does not require a nonlinear tensor factorization, including the robust form (R-LS-THC), for the calculation of the excitation and electron attachment energies using equation-of-motion coupled cluster methods EOMEE-CCSD and EOMEA-CCSD, respectively. We have benchmarked the effect of the R-LS-THC-PPL approximation on excitation energies using the comprehensive QUEST database and the accuracy of electron attachment energies using the NAB22 database. We find that errors on the order of 1 meV are achievable with a reduction in total calculation time of approximately 5 ×.

The Database Replication Software market is experiencing robust growth, driven by the increasing need for high availability, disaster recovery, and data consistency across distributed systems. The market, estimated at $15 billion in 2025, is projected to witness a Compound Annual Growth Rate (CAGR) of 12% from 2025 to 2033, reaching approximately $45 billion by 2033. This expansion is fueled by several key factors. The burgeoning adoption of cloud computing necessitates robust data replication solutions to ensure seamless operation and data protection across multiple cloud environments. Furthermore, the growing volume and velocity of data generated by businesses across diverse sectors—finance, telecommunications, education, healthcare, and government—are compelling organizations to invest in advanced database replication software to manage and protect their critical information assets. The rising prevalence of real-time applications and the demand for low-latency data access further contribute to market growth. Key segments driving this growth include timestamp technology and log analysis technology, particularly in the financial and telecommunications sectors, which require stringent data integrity and high transaction processing capabilities. While factors such as the complexity of implementation and integration with existing systems can pose challenges, the overall market outlook remains positive, with continued innovation in replication technologies and increasing adoption across various industries expected to drive future growth. Significant regional variations exist. North America currently holds a substantial market share, fueled by early adoption of advanced technologies and a strong presence of major technology vendors. However, the Asia-Pacific region is poised for significant growth, driven by rapid digitalization, expanding IT infrastructure, and increasing investment in data centers. Europe is also a mature market with steady growth, while the Middle East and Africa regions are showing promising signs of expansion. The competitive landscape is characterized by the presence of established players such as IBM, Oracle, and Quest Software, along with emerging vendors offering innovative solutions. These companies are engaging in strategic partnerships, acquisitions, and product development to enhance their market positioning and cater to the evolving needs of businesses seeking efficient and reliable database replication solutions. The continued focus on security, scalability, and performance optimization will shape the future trajectory of the market.

The Database DevOps Software market is experiencing robust growth, driven by the increasing adoption of DevOps practices across organizations of all sizes and the rising demand for efficient database management solutions. The market, estimated at $2 billion in 2025, is projected to expand significantly over the forecast period (2025-2033), fueled by a compound annual growth rate (CAGR) of 15%. This growth is propelled by several key factors. The shift towards cloud-based infrastructure, offering scalability and cost-effectiveness, is a major driver. Furthermore, the growing complexity of databases and the need for automation in database deployments and management are pushing organizations to adopt Database DevOps solutions. Large enterprises are leading the adoption, but SMEs are also increasingly recognizing the value proposition, further contributing to market expansion. The demand for seamless integration with existing CI/CD pipelines and improved collaboration among development and operations teams is another key factor driving market growth. However, the market also faces certain restraints. The initial investment costs associated with implementing Database DevOps tools and the need for skilled professionals proficient in these tools can pose challenges for some organizations. Furthermore, integrating these tools into legacy systems can be complex and time-consuming, creating a barrier to entry for some businesses. Despite these challenges, the long-term benefits of improved efficiency, reduced risk, and faster deployment cycles are expected to outweigh the initial hurdles, ensuring continued market expansion. The market is segmented by application (Large Enterprises, SMEs) and type (Cloud-based, On-premise), with the cloud-based segment expected to dominate due to its inherent advantages in scalability, flexibility, and cost-optimization. Geographic expansion, particularly in rapidly developing economies in Asia-Pacific and other regions, presents substantial growth opportunities for market players.

This application, HistoryQuest DC, is an interactive GIS map that provides historical data on approximately 193,000 extant buildings in Washington, D.C. The map offers several operational layers of information for the user including historic data on individual buildings and historic districts, links to documentation on properties listed in the National Register of Historic Places, information on historic residential subdivisions, and the identification and boundaries of the L’Enfant Plan, and the city’s Squares, and Wards. The featured layer in the map—the Historical Data on DC Buildings—provides information from a variety of sources on original dates of construction, architects, owners and builders of the city’s historic buildings. The application also includes a Query tool that allows the user to analyze the historic data within a specified geographic area or city-wide.This application has evolved out of the DC Historical Building Permits Database, begun in 2002, is on-going. Requests to correct or add new information can be made using the “Propose Data Change” drop-down form located on the banner at the top of the map. For questions or concerns, contact the Historic Preservation Office at historic.preservation@dc.gov.

Complete list of all 72 Sonora Quest Laboratories POI locations in the the USA with name, geo-coded address, city, email, phone number etc for download in CSV format or via the API.

Market Analysis for Database Monitoring Software The global database monitoring software market is projected to reach USD 1580.5 million by 2033, exhibiting a CAGR of 5.6% during the forecast period of 2025-2033. The increasing need for real-time monitoring and performance optimization of databases, coupled with the proliferation of cloud-based deployments and advancements in artificial intelligence (AI) and machine learning (ML), are driving market growth. Key players in the market include Datadog, Solarwinds, PRTG Network Monitor, FusionReactor, Micro Focus, and Quest, among others. Market Segmentation and Regional Outlook The market is segmented based on type (Cloud Based, Web Based) and application (Large Enterprises, SMEs). Cloud-based solutions are gaining traction due to their scalability, flexibility, and cost-effectiveness. Large enterprises dominate the market, while SMEs are expected to witness significant growth over the forecast period. Geographically, North America holds a significant market share owing to the presence of numerous technology companies. However, Asia Pacific is anticipated to grow at the highest CAGR, driven by the rapid adoption of cloud-based solutions and the growing IT infrastructure in emerging economies. The global database monitoring software market is projected to reach USD 1.2 billion by 2026, exhibiting a CAGR of 10.2% during the forecast period. The increasing adoption of cloud-based database solutions, along with the growing need for real-time monitoring and analytics, is driving the market growth.

The Database Automation Systems market is experiencing robust growth, driven by the increasing complexity of databases, the rising demand for improved operational efficiency, and the need for enhanced data security. The market, estimated at $15 billion in 2025, is projected to witness a Compound Annual Growth Rate (CAGR) of 12% from 2025 to 2033, reaching an estimated $45 billion by 2033. This expansion is fueled by several key trends, including the widespread adoption of cloud-based database solutions, the growing popularity of DevOps methodologies, and the increasing focus on automation across various industries. The on-premise segment currently holds a significant market share, but cloud-based solutions are rapidly gaining traction due to their scalability, cost-effectiveness, and accessibility. The IT & Telecom sector is a major driver of market growth, followed by the Government and Transportation sectors. However, challenges such as the high initial investment costs associated with implementing database automation systems and the need for skilled professionals to manage these systems act as restraints. The geographical distribution of the market reflects a strong presence in North America, followed by Europe and Asia Pacific. North America’s dominance is attributed to early adoption of advanced technologies and a robust IT infrastructure. However, emerging economies in Asia Pacific, particularly India and China, are showing significant growth potential due to increasing digitalization and investments in IT infrastructure. The competitive landscape is characterized by a mix of established players like Oracle, IBM, and Microsoft, alongside specialized database automation vendors like Datavail and Quest Software. These companies are continuously innovating to enhance their offerings, focusing on AI-powered automation, improved integration with other IT tools, and enhanced security features to maintain their competitive edge.

Abstract

Nikkei Digital Media, Inc. (NIKKEI)

An online data retrieval service which gives access to a wide range of information, including companies' financial results, stock price data, bond price data, macroeconomic data, and industrial statistic data. It allows for complex and multivariable searches. Acquired by the Center on Japaneses Economy and Business

Usage

To make an appointment to use the database, please contact Emiko Mizumura at em2265@columbia.edu.

We reexamine ΔCCSD, a state-specific coupled-cluster (CC) with single and double excitations (CCSD) approach that targets excited states through the utilization of non-Aufbau determinants. This methodology is particularly efficient when dealing with doubly excited states, a domain in which the standard equation-of-motion CCSD (EOM-CCSD) formalism falls short. Our goal here to evaluate the effectiveness of ΔCCSD when applied to other types of excited states, comparing its consistency and accuracy with EOM-CCSD. To this end, we report a benchmark on excitation energies computed with the ΔCCSD and EOM-CCSD methods for a set of molecular excited-state energies that encompasses not only doubly excited states but also doublet–doublet transitions and (singlet and triplet) singly excited states of closed-shell systems. In the latter case, we rely on a minimalist version of multireference CC known as the two-determinant CCSD method to compute the excited states. Our data set, consisting of 276 excited states stemming from the quest database [Véril et al., WIREs Comput. Mol. Sci. 2021, 11, e1517], provides a significant base to draw general conclusions concerning the accuracy of ΔCCSD. Except for the doubly excited states, we found that ΔCCSD underperforms EOM-CCSD. For doublet–doublet transitions, the difference between the mean absolute errors (MAEs) of the two methodologies (of 0.10 and 0.07 eV) is less pronounced than that obtained for singly excited states of closed-shell systems (MAEs of 0.15 and 0.08 eV). This discrepancy is largely attributed to a greater number of excited states in the latter set exhibiting multiconfigurational characters, which are more challenging for ΔCCSD. We also found typically small improvements by employing state-specific optimized orbitals.

The Database Performance Monitoring (DPM) software and services market is experiencing robust growth, driven by the increasing complexity of database environments, the rise of cloud computing, and the escalating demand for real-time application performance insights. The market, estimated at $2 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 12% from 2025 to 2033, reaching approximately $6 billion by 2033. Key drivers include the need for proactive performance optimization to minimize downtime and improve application responsiveness, the adoption of sophisticated analytics for performance troubleshooting, and the expanding use of diverse database technologies across various industries. Trends such as the integration of Artificial Intelligence (AI) and Machine Learning (ML) for predictive analytics and automated remediation are further fueling market expansion. However, factors such as the high cost of implementation, the need for specialized expertise, and the complexity of integrating DPM tools with existing infrastructure pose challenges to market growth. The market is segmented by deployment type (cloud, on-premise), database type (relational, NoSQL), organization size (SMEs, large enterprises), and geographic region. Leading vendors include SolarWinds, IDERA, Quest Software, Datadog, AppDynamics, New Relic, Dynatrace, PRTG, Percona, SQL Sentry, BMC Software, VividCortex, ManageEngine, Oracle, and IBM, each vying for market share with varying offerings and strengths. The competitive landscape is characterized by both established players offering comprehensive suites and specialized niche providers focusing on specific database technologies or performance aspects. The increasing adoption of cloud-based DPM solutions is reshaping the market, offering scalability and cost-effectiveness. This trend, coupled with the growing importance of data security and compliance regulations, drives the demand for robust and secure DPM solutions capable of managing complex, distributed database environments. The future growth of the DPM market will depend heavily on continuous innovation in areas such as AI-powered anomaly detection, automated performance tuning, and seamless integration with cloud platforms, promising further market expansion and consolidation in the coming years.

Market Analysis of Database Performance Monitoring Systems The database performance monitoring system market is a rapidly growing segment of the IT infrastructure management (ITIM) industry. It is estimated to have been valued at USD XXX million in 2025 and is projected to reach USD XXX million by 2033, growing at a CAGR of XX% from 2025 to 2033. The market is driven by the increasing adoption of cloud computing, the proliferation of data, and the growing complexity of IT environments. Key trends in the market include the adoption of SaaS-based solutions, the integration of artificial intelligence (AI) and machine learning (ML), and the rise of cloud-native database performance monitoring solutions. Major vendors in the database performance monitoring systems market include IBM, Oracle, Microsoft, SolarWinds, SentryOne, Paessler, AppDynamics (Cisco Systems), IDERA, Inc., Red Gate Software, VividCortex, Quest Software, Blue Medora, Lepide, ManageEngine (Zoho Corporation), and eG Innovations. The market is fragmented, with several players offering a range of solutions to address the needs of different organizations. The North American region is expected to dominate the market, followed by Europe and Asia Pacific. The increasing adoption of cloud computing and the growing demand for data-driven insights are driving growth in the region.

This is a synthetic database widely used for evaluating the scalability of pattern mining patterns. This database is generated using IBM Data Quest generator.

The global storage management software market is experiencing robust growth, driven by the increasing adoption of cloud technologies, the exponential growth of data, and the rising need for robust data protection and recovery solutions across diverse sectors. The market, estimated at $25 billion in 2025, is projected to expand significantly over the forecast period (2025-2033), fueled by a compound annual growth rate (CAGR) of 15%. This growth is largely attributed to the escalating demand for efficient data management in industries like aerospace & defense, healthcare, and finance, where data security and compliance are paramount. The cloud-based storage management software segment is the fastest-growing, driven by its scalability, cost-effectiveness, and accessibility. This segment's dominance is further bolstered by the growing preference for hybrid cloud environments, requiring seamless integration between on-premise and cloud-based solutions. However, challenges such as data security breaches, vendor lock-in, and the complexity of managing diverse storage environments remain potential restraints. Significant regional variations exist, with North America currently holding the largest market share due to the high adoption of advanced technologies and robust IT infrastructure. However, regions like Asia-Pacific are demonstrating rapid growth, fueled by increasing digitalization and government initiatives promoting cloud adoption. The competitive landscape is highly fragmented, with established players like IBM, Dell, and Cisco competing with emerging technology providers. Strategic partnerships, acquisitions, and the development of innovative solutions, such as AI-powered data management tools, are key strategies employed by companies to maintain their competitive edge. The market is also witnessing the emergence of specialized solutions catering to specific industry needs, contributing to its further fragmentation and ongoing evolution. The increasing importance of data governance and compliance regulations is expected to further propel the adoption of sophisticated storage management software solutions.

We help Ontario athletes compete at national and international levels. Browse through a list of funding recipients.

ServerIndexed files used in Quest For Ortholgs Benchmarking Workflow (https://github.com/qfo/benchmark-webservice/tree/elixir). It contains the base reference data in darwin database format and some auxillary datastructures that define the genome information of the proteome dataset.