The Canadian Clinical Drug Dataset is a drug terminology and coding system designed to allow the interchange of standardized drug and medical device information between diverse digital health systems. Some use cases include electronic prescribing, electronic medical records, medication reconciliation and analytics. It also provides for the classification and identification of defined groups of medications (called special groupings), such as narcotic and controlled drugs. It has the capacity to be used by knowledge-based vendors, clinicians, researchers, statistical users, government agencies, healthcare organisations and consumers. The data source for the CCDD is the Drug Product Database (DPD) which contains information on drugs approved by Health Canada. However, the data is modeled differently following the CCDD Editorial Guidelines which take into consideration international terminology standards. For example, DPD uses the dosage form, “tablet (delayed-release)”, whereas CCDD uses the equivalent term “gastro-resistant tablet.” The Canadian Clinical Drug Data Set does not replace the Health Canada Drug Product Database (DPD) but is published in addition to it. The scope of health products included in CCDD is limited to those classified as human in DPD (veterinary, radiopharmaceutical and disinfectant products are out of scope). Some exclusions apply within the human class but are subject to periodic review: For a full list of exclusions, please see the Scope section in the CCDD Editorial Guidelines. In addition, a limited number of medical devices that are commonly prescribed and dispensed at a community pharmacy are included. This data set was developed in collaboration with Canada Health Infoway and is also available in their Terminology Gateway at https://tgateway.infoway-inforoute.ca/ccdd.html (Free login required)

Number and percentage (%) of genes showing various expression patterns under normal and N-limiting conditions.

The number of people aged 65 years and older in Italy living with Alzheimer's disease and other dementias in Italy amounted to over *** million people in 2022. Each Center for Cognitive Disorders and Dementia (CCDD) was responsible for around ***** people with dementia in Italy. This ranged from ***** in Molise to *** in Calabria. This statistic displays the number of people living with dementias per one CCDD in Italy in 2022, by region.

The primary purpose of the CCD is to provide basic information on public elementary and secondary schools, local education agencies (LEAs), and state education agencies (SEAs) for each state, the District of Columbia, and the outlying territories with a U.S. relationship.

BackgroundHybrid weakness, a phenomenon opposite to heterosis, refers to inferior growth and development in a hybrid relative to its pure-line parents. Little attention has been paid to the phenomenological or mechanistic aspect of hybrid weakness, probably due to its rare occurrence.Methodology/Principal findingsHere, using a set of interspecific triploid F1 hybrids between Oryza sativa, ssp. japonica (genome AA) and a tetraploid wild rice species, O. alta (genome, CCDD), we investigated the phenotypic and physiological differences between the F1 hybrids and their parents under normal and nitrogen-limiting conditions. We quantified the expression levels of 21 key genes involved in three important pathways pertinent to the assayed phenotypic and physiological traits by real-time qRT-PCR. Further, we assayed expression partitioning of parental alleles for eight genes in the F1 hybrids relative to the in silico “hybrids” (parental cDNA mixture) under both normal and N-limiting conditions by using locus-specific cDNA pyrosequencing.Conclusions/SignificanceWe report that the F1 hybrids showed weakness in several phenotypic traits at the final seedling-stage compared with their corresponding mid-parent values (MPVs). Nine of the 21 studied genes showed contrasted expression levels between hybrids and parents (MPVs) under normal vs. N-limiting conditions. Interestingly, under N-limiting conditions, the overtly enhanced partitioning of maternal allele expression in the hybrids for eight assayed genes echo their attenuated hybrid weakness in phenotypes, an observation further bolstered by more resemblance of hybrids to the maternal parent under N-limiting conditions compared to normal conditions in a suite of measured physiological traits. Our observations suggest that both overall expression level and differential partitioning of parental alleles of critical genes contribute to condition-specific hybrid weakness.

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Number and percentage (%) of genes in the three pathways showing changes in expression pattern in N-limiting versus normal conditions.

Credit report of Fao Hadley Sheppard Ccdd C0w11 contains unique and detailed export import market intelligence with it's phone, email, Linkedin and details of each import and export shipment like product, quantity, price, buyer, supplier names, country and date of shipment.

Natural history specimen data linked to collectors and determiners held within, "University of South Florida Herbarium - Fungi excluding lichens". Claims or attributions were made on Bionomia by volunteer Scribes, https://bionomia.net/dataset/e0ff3ef6-ccdd-43e4-a307-05e9c299815b using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, https://gbif.org/dataset/e0ff3ef6-ccdd-43e4-a307-05e9c299815b. Formatted as a Frictionless Data package.

This dataset contains data-intensive quantum chemical electronic structure calculations for 80,593 organic molecules of the GDB-9-Ex dataset. Calculations were performed using the Equation of Motion Coupled Cluster (EOM-CCSD) first principles method using the ORCA software. It provides UV-vis spectra calculations of molecules with a high level of accuracy. The optical spectra behavior was collected based on the optimized molecular geometries in the DFTB method with 3ob parameters. All calculations utilized the def2-TZVP basis sets with the auxiliary def2/J and def2-TZVP/C basis sets. The similarity-transformed EOM-CCSD method that used domain-based local pair natural orbitals (DLPNO) approximation which constitutes the STEOM-DLPNO-CCSD method was used. This method is based on the STEOM approach and was found to make accurate predictions of transition energies for organic molecules. For the excitation energy calculations, the lowest 50 excitation states were calculated.

593 molecules. This dataset contains data-intensive quantum chemical electronic structure calculations for organic molecules of the GDB-9-Ex dataset. Calculations were performed using the Equation of Motion Coupled Cluster (EOM-CCSD) first principles method using the ORCA software. It provides UV-vis spectra calculations of molecules with a high level of accuracy.

This dataset tracks annual reduced-price lunch eligibility from 2013 to 2023 for Ccsd Virtual High School vs. Nevada and Clark County School District

Plant material used in the present study.

No description is available. Visit https://dataone.org/datasets/%7B54F4B36B-CCDD-4FC8-97A4-9FEA21D330A6%7D for complete metadata about this dataset.

This dataset tracks annual total students amount from 1987 to 2023 for Montmorency Ccsd #145

The global domestic waste sorting machine market is experiencing robust growth, driven by increasing urbanization, rising environmental concerns, and stringent government regulations regarding waste management. The market, currently valued at approximately $2.5 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 8% from 2025 to 2033. This growth is fueled by several key factors, including the escalating need for efficient waste recycling and resource recovery, technological advancements in sorting technologies (such as AI-powered systems and advanced sensor technologies), and increasing public awareness about sustainable waste management practices. The market is segmented by technology (CCD vision, laser vision, and others), application (government departments, industries, garbage disposal plants, and others), and geography, each demonstrating unique growth trajectories. For instance, the CCD vision segment is expected to dominate due to its cost-effectiveness and accuracy, while regions such as North America and Europe are leading the adoption due to established waste management infrastructure and stringent environmental regulations. However, the market's growth is not without its challenges. High initial investment costs for advanced sorting machines, the need for skilled labor to operate and maintain these systems, and the fluctuating prices of raw materials used in machine production pose potential restraints. Despite these hurdles, the long-term outlook for the domestic waste sorting machine market remains positive, largely driven by government initiatives promoting recycling and waste reduction, coupled with the increasing adoption of sustainable practices across various industries. This growth is expected to create significant opportunities for manufacturers, technology providers, and waste management companies involved in this sector. Technological innovations focusing on automation, efficiency, and reduced operating costs are expected to play a crucial role in shaping the future of this dynamic market.

The booming automatic garbage sorting system market is projected to reach $12.27 billion by 2033, with a CAGR of 12%. Discover key trends, drivers, and regional insights in this comprehensive market analysis, featuring leading companies like SUEZ and Stadler. Learn about CCD vision, laser vision, and other technologies transforming waste management.

The National Center for Education Statistics' (NCES) Education Demographic and Geographic Estimate (EDGE) program develops annually updated point locations (latitude and longitude) for public elementary and secondary schools included in the NCES Common Core of Data (CCD). The NCES EDGE program collaborates with the U.S. Census Bureau's Education Demographic, Geographic, and Economic Statistics (EDGE) Branch to develop point locations for schools reported in the annual CCD directory file. The CCD program annually collects administrative and fiscal data about all public schools, school districts, and state education agencies in the United States. The data are supplied by state education agency officials and include basic directory and contact information for schools and school districts, as well as characteristics about student demographics, number of teachers, school grade span, and various other administrative conditions. CCD school and agency point locations are derived from reported information about the physical location of schools and agency administrative offices. The point locations and administrative attributes in this data layer were developed from the 2017-2018 CCD collection. For more information about NCES school point data, see: https://nces.ed.gov/programs/edge/Geographic/SchoolLocations. For more information about these CCD attributes, as well as additional attributes not included, see: https://nces.ed.gov/ccd/files.asp.Notes:

-1 or M

Indicates that the data are missing.

-2 or N

Indicates that the data are not applicable.

-9

Indicates that the data do not meet NCES data quality standards.

All information contained in this file is in the public domain. Data users are advised to review NCES program documentation and feature class metadata to understand the limitations and appropriate use of these data.

This dataset tracks annual free lunch eligibility from 2013 to 2023 for Ccsd Virtual High School vs. Nevada and Clark County School District

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