Developing data-driven solutions that address real-world problems requires understanding of these problems’ causes and how their interaction affects the outcome–often with only observational data. Causal Bayesian Networks (BN) have been proposed as a powerful method for discovering and representing the causal relationships from observational data as a Directed Acyclic Graph (DAG). BNs could be especially useful for research in global health in Lower and Middle Income Countries, where there is an increasing abundance of observational data that could be harnessed for policy making, program evaluation, and intervention design. However, BNs have not been widely adopted by global health professionals, and in real-world applications, confidence in the results of BNs generally remains inadequate. This is partially due to the inability to validate against some ground truth, as the true DAG is not available. This is especially problematic if a learned DAG conflicts with pre-existing domain doctrine. Here we conceptualize and demonstrate an idea of a “Causal Datasheet” that could approximate and document BN performance expectations for a given dataset, aiming to provide confidence and sample size requirements to practitioners. To generate results for such a Causal Datasheet, a tool was developed which can generate synthetic Bayesian networks and their associated synthetic datasets to mimic real-world datasets. The results given by well-known structure learning algorithms and a novel implementation of the OrderMCMC method using the Quotient Normalized Maximum Likelihood score were recorded. These results were used to populate the Causal Datasheet, and recommendations could be made dependent on whether expected performance met user-defined thresholds. We present our experience in the creation of Causal Datasheets to aid analysis decisions at different stages of the research process. First, one was deployed to help determine the appropriate sample size of a planned study of sexual and reproductive health in Madhya Pradesh, India. Second, a datasheet was created to estimate the performance of an existing maternal health survey we conducted in Uttar Pradesh, India. Third, we validated generated performance estimates and investigated current limitations on the well-known ALARM dataset. Our experience demonstrates the utility of the Causal Datasheet, which can help global health practitioners gain more confidence when applying BNs.

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• The current US Census Bureau world population estimate in June 2019 shows that the current global population is 7,577,130,400 people on Earth, which far exceeds the world population of 7.2 billion in 2015. Our estimate based on UN data shows the world's population surpassing 7.7 billion.
• China is the most populous country in the world with a population exceeding 1.4 billion. It is one of just two countries with a population of more than 1 billion, with India being the second. As of 2018, India has a population of over 1.355 billion people, and its population growth is expected to continue through at least 2050. By the year 2030, India is expected to become the most populous country in the world. This is because India’s population will grow, while China is projected to see a loss in population.
• The following 11 countries that are the most populous in the world each have populations exceeding 100 million. These include the United States, Indonesia, Brazil, Pakistan, Nigeria, Bangladesh, Russia, Mexico, Japan, Ethiopia, and the Philippines. Of these nations, all are expected to continue to grow except Russia and Japan, which will see their populations drop by 2030 before falling again significantly by 2050.
• Many other nations have populations of at least one million, while there are also countries that have just thousands. The smallest population in the world can be found in Vatican City, where only 801 people reside.
• In 2018, the world’s population growth rate was 1.12%. Every five years since the 1970s, the population growth rate has continued to fall. The world’s population is expected to continue to grow larger but at a much slower pace. By 2030, the population will exceed 8 billion. In 2040, this number will grow to more than 9 billion. In 2055, the number will rise to over 10 billion, and another billion people won’t be added until near the end of the century. The current annual population growth estimates from the United Nations are in the millions - estimating that over 80 million new lives are added yearly.
• This population growth will be significantly impacted by nine specific countries which are situated to contribute to the population growth more quickly than other nations. These nations include the Democratic Republic of the Congo, Ethiopia, India, Indonesia, Nigeria, Pakistan, Uganda, the United Republic of Tanzania, and the United States of America. Particularly of interest, India is on track to overtake China's position as the most populous country by 2030. Additionally, multiple nations within Africa are expected to double their populations before fertility rates begin to slow entirely.

Content

• In this Dataset, we have Historical Population data for every Country/Territory in the world by different parameters like Area Size of the Country/Territory, Name of the Continent, Name of the Capital, Density, Population Growth Rate, Ranking based on Population, World Population Percentage, etc. >Dataset Glossary (Column-Wise):
• Rank: Rank by Population.
• CCA3: 3 Digit Country/Territories Code.
• Country/Territories: Name of the Country/Territories.
• Capital: Name of the Capital.
• Continent: Name of the Continent.
• 2022 Population: Population of the Country/Territories in the year 2022.
• 2020 Population: Population of the Country/Territories in the year 2020.
• 2015 Population: Population of the Country/Territories in the year 2015.
• 2010 Population: Population of the Country/Territories in the year 2010.
• 2000 Population: Population of the Country/Territories in the year 2000.
• 1990 Population: Population of the Country/Territories in the year 1990.
• 1980 Population: Population of the Country/Territories in the year 1980.
• 1970 Population: Population of the Country/Territories in the year 1970.
• Area (km²): Area size of the Country/Territories in square kilometers.
• Density (per km²): Population Density per square kilometer.
• Growth Rate: Population Growth Rate by Country/Territories.
• World Population Percentage: The population percentage by each Country/Territories.

Get key insights from Market Research Intellect's Safety Data Sheet (SDS) Management Market Report, valued at USD 450 million in 2024, and forecast to grow to USD 1.2 billion by 2033, with a CAGR of 12.5% (2026-2033).

The Data Sheet lists all geopolitical entities with populations of 150,000 or more and all members of the UN. These include sovereign states, dependencies, overseas departments, and some territories whose status or boundaries may be undetermined or in dispute. Regional population totals are independently rounded and include small countries or areas not shown. Regional and world rates and percentages are weighted averages of countries for which data are available; regional averages are shown when data or estimates are available for at least three-quarters of the region's population. Variables include population, birth and death rate, rate of natural increase, population "doubling time", estimated population for 2010 and 2025, infant mortality rate, total fertility rate, population under age 15/over age 65, life expectancy at birth, urban population, contraceptive use, per capita GNP, and government view of current birth rate. NOTE: This file is a compilation of demographic data from various sources. The data values are the same as those published in PRB's World Data Sheet, but this file also contains some underlying population figures used to calculate the rates and percentages.

This database compiles information from various publically available battery cell datasheets to provide a centralized and accessible repository for technical details of various real-world battery cells, including specifications, performance metrics, and technical characteristics. Our project aims to streamline research efforts, support informed decision-making, and foster advancements in battery technology by collecting these datasheets. We do not assume any liability for the completeness, correctness, and accuracy of the information.

However, it is important to acknowledge the potential challenges of managing such a database given the still early, highly dynamic, and innovative battery market. Among others, ensuring data accuracy, data completeness, and timeliness is critical. Battery cell technologies are constantly evolving, requiring ongoing attention to maintain an up-to-date database with the latest specifications and cells. While we aimed to ensure that all records are complete, incomplete datasheets are limiting this effort and, thus, the full potential of the database. Last, standardization issues may present a challenge due to the absence of standardized reporting formats across manufacturers and countries. See "Notes" columns for comments. Unless otherwise stated, all values and parameters originate exclusively from the datasheets.

Last, we highlight that it is important to consider potential uncertainties when using the information provided in cell datasheets. The values shown are primarily derived from standardized test environments and conditions and may not accurately reflect the actual real-world performance of the cells, which may vary significantly depending on ambient conditions (foremost temperature) and charge-discharge load profiles specific to applications and embedded use cases.

Safety Data Sheet Management Market size was valued at USD 14.9 Billion in 2024 and is projected to reach USD 25.4 Billion by 2031, growing at a CAGR of 7.8 % during the forecast period 2024-2031.

Stringent Regulatory Requirements: Increasing global regulations and compliance standards for hazardous materials drive the need for efficient SDS management systems.

Workplace Safety Concerns: Workplace safety is a paramount concern for businesses across diverse industries. An increasing focus on employee health and well-being has led companies to adopt stringent safety measures. Safety Data Sheets (SDS) are integral to these measures, providing detailed information on the properties and handling of hazardous chemicals. Effective SDS management systems ensure that employees are well-informed about the risks and safe handling procedures associated with chemicals they work with. This not only helps in complying with Occupational Safety and Health Administration (OSHA) standards but also mitigates the financial and reputational risks associated with workplace accidents. The growing emphasis on creating safer work environments has driven companies to seek comprehensive SDS management solutions, thus propelling the market forward. Growth in Chemical Industry: The chemical industry is experiencing robust growth, driven by increasing demand from sectors such as pharmaceuticals, agriculture, and manufacturing. As the volume and variety of chemicals being produced and used escalate, so does the complexity of managing their safety data. Regulatory bodies mandate that up-to-date and accurate SDS be provided and maintained for chemicals, ensuring safe usage, handling, and disposal. Companies in the chemical industry are consequently investing in advanced SDS management systems to streamline compliance with these regulations, manage inventory, and ensure that safety information is readily accessible. This sector’s expansion significantly contributes to the growth of the SDS management market. Technological Advancements: Technological advancements in digital solutions have revolutionized the SDS management landscape. Innovations like cloud-based platforms, Artificial Intelligence (AI), and mobile applications have made it easier and more efficient to manage, access, and update safety data sheets. These technologies offer real-time updates, enhanced accuracy, and improved accessibility, thereby improving compliance and reducing administrative burdens. AI can automate the extraction and updating of safety data, while mobile applications allow for on-the-go access to critical safety information. These technological advancements not only enhance operational efficiency but also provide a competitive edge to businesses, making them a driving force in the market. Environmental Regulations: Environmental regulations across the globe are becoming increasingly stringent, compelling organizations to adopt robust compliance mechanisms. Regulatory frameworks such as the Globally Harmonized System (GHS) for Classification and Labelling of Chemicals necessitate that businesses maintain accurate and up-to-date SDS. Compliance with these regulations is critical to avoid hefty fines, legal repercussions, and potential operational shutdowns. The increasing enforcement of environmental laws and standards drives the demand for efficient SDS management systems that can handle complex regulations and ensure seamless compliance. As a result, regulatory pressure acts as a significant market driver, pushing organizations to invest in advanced SDS management solutions. Globalization of Supply Chains: International trade and complex supply chains require standardized and accessible SDS documentation across borders. Risk Management: Companies are increasingly adopting SDS management systems to mitigate risks associated with hazardous materials and ensure swift response in emergencies. Cost Efficiency: Automated SDS management systems reduce administrative burden, minimize errors, and save costs associated with manual data handling. Corporate Responsibility and Sustainability: Growing emphasis on corporate social responsibility and sustainability practices encourages companies to adopt comprehensive SDS management systems. Digital Transformation: The shift towards digital transformation in various industries propels the adoption of electronic SDS management solutions.

Dataset

This dataset was created by qwester

Released under Apache 2.0

Contents

Data sheet containing all mapped elliptical craters presented in the study by Ferguson et al., 2023 in Earth and Planetary Science Letters about Mimas.

Dataset

This dataset was created by Persian Cats

Contents

Dataset

This dataset was created by duong leminh

Contents

It contains the following files:

The data include the abundance and community compositions characterized using qPCR and metagenomic sequences. This dataset is associated with the following publication: Jeon, Y., I. Struewing, K. Clauson, N. Reetz, N. Fairchild, L. Goeres-Priest, T. Dreher, R. Labiosa, K. Carpenter, B. Rosen, E. Villegas, and J. Lu. Dominant Dolichospermum and microcystin production in Detroit Lake (Oregon, USA). Harmful Algae. Elsevier B.V., Amsterdam, NETHERLANDS, 142: 102802, (2025).

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This datasheet provides a comprehensive documentation of the ConfLab dataset.

Isolator Datasheet

## Overview

Isolator Datasheet is a dataset for object detection tasks - it contains Isolator annotations for 1,612 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

Patient Support Programmes (PSPs) are used by the pharmaceutical industry to provide education and support to consumers to overcome the challenges they face managing their condition and treatment. Whilst there is an increasing number of PSPs, limited information is available on whether these programmes contribute to safety signals. PSPs do not have a scientific hypothesis, nor are they governed by a protocol. However, by their nature, PSPs inevitably generate adverse event (AE) reports. The main goal of the research was to gather all Novartis-initiated PSPs for sacubitril/valsartan, followed by research in the company safety database to identify all AE reports emanating from these PSPs. Core data sheets (CDS) were reviewed to assess if these PSPs contributed to any new, regulatory-authority approved, validated signals. Overall, AEs entered into the safety database from PSPs confirmed no contribution to CDS updates. Detailed review of real-world data revealed tablet splitting or taking one higher dose tablet a day instead of twice daily. This research, and subsequent analyses, revealed that PSPs did not impact safety label changes for sacubitril/valsartan. It revealed an important finding concerning drug utilisation i.e. splitting of sacubitril/valsartan tablets to reduce cost. This finding suggests that PSPs may contribute important real-world data on patterns of medication usage. There remains a paucity of literature available on this topic, hence further research is required to assess if it would be worth designing PSPs for collecting data on drug utilisation and (lack of) efficacy. Such information from PSPs could be important for all stakeholders.

Global Safety Data Sheet - SDS market size 2025 was XX Million. Safety Data Sheet - SDS Industry compound annual growth rate (CAGR) will be XX% from 2025 till 2033.

Palynological data of the groups represented in the main diagram.

This Dataset is created to enable researchers to explore the traveling paths of nanoparticles in the human circulatory system (HCS).

BackgroundElexacaftor/Tezacaftor/Ivacaftor (ETI) has demonstrated significant efficacy in enhancing clinical outcomes for patients with cystic fibrosis (CF). Despite this, comprehensive post-marketing assessments of its adverse drug events (ADEs) remain insufficient. This study aims to analyze the ADEs associated with ETI using the U.S. FDA Adverse Event Reporting System (FAERS).MethodsWe conducted a pharmacovigilance analysis utilizing FAERS data from Q4 2019 to Q3 2024. Reports of ADEs related to ETI were extracted, and disproportionality analyses—including Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN), and Multi-item Gamma Poisson Shrinker (MGPS)—were employed to evaluate signal strength. Additionally, a time-to-onset (TTO) analysis was performed.ResultsA total of 28,366 ETI-related ADEs were identified, spanning 27 organ systems. We identified 322 positive signals, with signals consistent with the drug label including headache (702 cases, ROR 2.75), infective pulmonary exacerbation of CF (691 cases, ROR 384.24), rash (538 cases, ROR 2.72), and cough (507 cases, ROR 3.79). Unexpected signals were also noted, such as anxiety (494 cases, ROR 4.16), depression (364 cases, ROR 4.59), insomnia (281 cases ROR 2.83), nephrolithiasis (79 cases, ROR 3.63) and perinatal depression (4 cases, ROR 13.59). The TTO analysis indicated that the median onset of ADEs was 70 days, with 37.08% occurring within the first month. Subgroup analyses revealed that females exhibited a higher reporting rank for mental disorder and constipation, whereas in males, they were insomnia, abdominal pain, and nasopharyngitis.ConclusionThis study highlights both recognized and unexpected ADEs associated with ETI, underscoring the necessity for ongoing monitoring, particularly concerning psychiatric conditions. The subgroup analysis suggests a need for personalized treatment strategies to optimize patient care.