The goal of this study is to better understand working memory and image schemata by examining five world records set by Paolo Fabiani in mental calculation and memorization. The purpose of the records is to demonstrate that the potential and limits of working memory are closely connected with image schemes. The tests were designed to highlight some specific features of image schemata. Some of these aspects are 1) using specific mental images to facilitate the calculation of large numbers; 2) the conversion from binary numbers to decimals and to count from bottom to top; 3) making arithmetic sums proceeding from left to right; 4) converting images into numbers and then “add” the images by thinking about numbers. We can considerably improve the performance of mental calculations by using knowledge of the operating mechanisms of the schemes.

This dataset contains the World Average Degree Days Database for the period 1964-2013. Follow datasource.kapsarc.org for timely data to advance energy economics research.*

Summary_64-13_freq=1D Average Degree Days of various indices for respective countries for the period 1964-2013, converted to a 1 day frequency

Summary_64-13_freq=6hrs Average Degree Days of various indices for respective countries for the period 1964-2013, calculated at 6 hrs frequency

T2m.hdd.18C Calculation of Heating Degree Days using plain temperature at 2 m elevation at Tref=18°C and frequency of 6 hrs

T2m.cdd.18C Calculation of Cooling Degree Days using plain temperature at 2 m elevation at Tref=18°C and frequency of 6 hrs

t2m.hdd.15.6C Calculation of Heating Degree Days using plain temperature at 2 m elevation at Tref=15.6°C and frequency of 6 hrs

t2m.hdd.18.3C Calculation of Heating Degree Days using plain temperature at 2 m elevation at Tref=18.3°C and frequency of 6 hrs

t2m.hdd.21.1C Calculation of Heating Degree Days using plain temperature at 2 m elevation at Tref=21.1°C and frequency of 6 hrs

t2m.cdd.15.6C Calculation of Cooling Degree Days using plain temperature at 2 m elevation at Tref=15.6°C and frequency of 6 hrs

t2m.cdd.18.3C Calculation of Cooling Degree Days using plain temperature at 2 m elevation at Tref=18.3°C and frequency of 6 hrs

t2m.cdd.21.1C Calculation of Cooling Degree Days using plain temperature at 2 m elevation at Tref=21.1°C and frequency of 6 hrs

t2m.hdd.60F Calculation of Heating Degree Days using plain temperature at 2 m elevation at Tref=60°F and frequency of 6 hrs

t2m.hdd.65F Calculation of Heating Degree Days using plain temperature at 2 m elevation at Tref=65°F and frequency of 6 hrs

t2m.hdd.70F Calculation of Heating Degree Days using plain temperature at 2 m elevation at Tref=70°F and frequency of 6 hrs

t2m.cdd.60F Calculation of Cooling Degree Days using plain temperature at 2 m elevation at Tref=60°F and frequency of 6 hrs

t2m.cdd.65F Calculation of Cooling Degree Days using plain temperature at 2 m elevation at Tref=65°F and frequency of 6 hrs

t2m.cdd.70F Calculation of Cooling Degree Days using plain temperature at 2 m elevation at Tref=70°F and frequency of 6 hrs

HI.hdd.57.56F Calculation of Heating Degree Days using the Heat Index at Tref=57.56°F and frequency of 6 hrs

HI.hdd.63.08F Calculation of Heating Degree Days using the Heat Index at Tref=63.08°F and frequency of 6 hrs

HI.hdd.68.58F Calculation of Heating Degree Days using the Heat Index at Tref=68.58°F and frequency of 6 hrs

HI.cdd.57.56F Calculation of Cooling Degree Days using the Heat Index at Tref=57.56°F and frequency of 6 hrs

HI.cdd.63.08F Calculation of Cooling Degree Days using the Heat Index at Tref=63.08°F and frequency of 6 hrs

HI.cdd.68.58F Calculation of Cooling Degree Days using the Heat Index at Tref=68.58°F and frequency of 6 hrs

HUM.hdd.13.98C Calculation of Heating Degree Days using the Humidex at Tref=13.98°C and frequency of 6 hrs

HUM.hdd.17.4C Calculation of Heating Degree Days using the Humidex at Tref=17.40°C and frequency of 6 hrs

HUM.hdd.21.09C Calculation of Heating Degree Days using the Humidex at Tref=21.09°C and frequency of 6 hrs

HUM.cdd.13.98C Calculation of Cooling Degree Days using the Humidex at Tref=13.98°C and frequency of 6 hrs

HUM.cdd.17.4C Calculation of Cooling Degree Days using the Humidex at Tref=17.40°C and frequency of 6 hrs

HUM.cdd.21.09C Calculation of Cooling Degree Days using the Humidex at Tref=21.09°C and frequency of 6 hrs

ESI.hdd.12.6C Calculation of Heating Degree Days using the Environmental Stress Index at Tref=12.6°C and frequency of 6 hrs

ESI.hdd.14.9C Calculation of Heating Degree Days using the Environmental Stress Index at Tref=14.9°C and frequency of 6 hrs

ESI.hdd.17.2C Calculation of Heating Degree Days using the Environmental Stress Index at Tref=17.2°C and frequency of 6 hrs

ESI.cdd.12.6C Calculation of Cooling Degree Days using the Environmental Stress Index at Tref=12.6°C and frequency of 6 hrs

ESI.cdd.14.9C Calculation of Cooling Degree Days using the Environmental Stress Index at Tref=14.9°C and frequency of 6 hrs

ESI.cdd.17.2C Calculation of Cooling Degree Days using the Environmental Stress Index at Tref=17.2°C and frequency of 6 hrs

Note:

Divide Degree Days by 4 to convert from 6 hrs to daily frequency

Math Calculation Software Market Outlook

The global Math Calculation Software market size was valued at approximately USD 2.8 billion in 2023 and is projected to reach USD 5.6 billion by 2032, growing at a compound annual growth rate (CAGR) of 7.5% during the forecast period. This growth is driven by the increasing need for advanced mathematical tools and software to support various applications across multiple industries, including education, engineering, research, and finance.

One of the primary growth factors contributing to the expansion of the Math Calculation Software market is the rising emphasis on STEM (Science, Technology, Engineering, and Mathematics) education worldwide. Governments and educational institutions are making significant investments in enhancing the quality of education by incorporating advanced technological tools, including sophisticated math calculation software. This trend is particularly prevalent in developed countries but is also gaining momentum in emerging economies, thereby fueling market growth.

Furthermore, the rapid advancements in technology, especially in artificial intelligence (AI) and machine learning (ML), are also propelling the demand for math calculation software. These technologies require robust mathematical models and algorithms, which in turn necessitate advanced calculation software. Industries such as engineering and finance are increasingly relying on these tools for precise data analysis, modeling, and forecasting, thereby contributing to market growth.

Another significant factor driving the market is the growing complexity of data and the need for accurate and efficient data analysis tools. With the explosion of big data and the increasing reliance on data-driven decision-making, enterprises across various sectors are turning to advanced math calculation software to process and analyze large datasets accurately. This trend is expected to continue, further boosting the market's expansion.

From a regional perspective, North America holds a significant share of the global Math Calculation Software market, driven by the high adoption rate of advanced technologies and substantial investments in education and research. However, Asia Pacific is anticipated to witness the highest growth rate during the forecast period, owing to the increasing focus on education and rapid industrialization in countries such as China and India. Europe also represents a substantial market share, driven by strong engineering and research sectors.

Component Analysis

The Math Calculation Software market is segmented into two primary components: software and services. The software segment encompasses a wide range of mathematical tools and applications designed to perform complex calculations, data analysis, and modeling. This segment has witnessed significant growth due to the increasing demand for advanced computational tools across various industries. Educational institutions, engineering firms, and research organizations are major consumers of math calculation software, leveraging it to enhance productivity and accuracy.

In addition to standalone mathematical software, there is a growing trend towards integrated solutions that combine math calculation capabilities with other functionalities such as data visualization, simulation, and AI-powered analytics. These integrated solutions offer a comprehensive toolset for users, further driving the adoption of math calculation software. The continuous development of user-friendly interfaces and features tailored to specific industry needs also contributes to the growth of the software segment.

The services segment includes consulting, implementation, and support services. As organizations increasingly adopt advanced math calculation software, the need for specialized services to ensure smooth deployment and operation becomes critical. Service providers offer expertise in customizing and integrating software solutions to meet specific organizational requirements. Additionally, ongoing support and maintenance services are essential to address any technical issues and ensure optimal software performance.

Moreover, training and education services are vital components of the services segment. As math calculation software becomes more sophisticated, users require training to maximize the software's potential. Service providers offer training programs to help users understand and effectively utilize the software, ensuring that organizations derive maximum value from their investment.

According to Cognitive Market Research, The Global Scientific Calculator market will grow at a compound annual growth rate (CAGR) of 5.80%from 2023 to 2030.

The demand for scientific calculator market is rising due to theincreasing popularity of handheld scientific calculators, which are valued for their compact size and user-friendly interface.
Demand for education remains higher in thescientific calculator market.
The solar cell calculator category held the highest scientific calculator market revenue share in 2023.
North America will continue to lead, whereas the Asia Pacific scientific calculator market will experience the strongest growth until 2030.

Increasing Emphasis on STEM Education to Provide Viable Market Output

The Scientific Calculator market is the rising emphasis on STEM (Science, Technology, Engineering, and Mathematics) education worldwide. Educational institutions, from schools to universities, are integrating STEM-focused curricula to prepare students for careers in fields like engineering, mathematics, computer science, and natural sciences. Scientific calculators are indispensable tools for students studying these subjects.

Texas Instruments Incorporated has unveiled an enhanced version of its TI-Nspire CX II line of graphing calculators. These calculators come with upgraded coding and math capabilities, providing users with improved functionality.

They enable complex calculations, graphing, and problem-solving, fostering a deeper understanding of scientific concepts. As the demand for STEM professionals continues to grow, the need for scientific calculators is escalating. Manufacturers are responding to this trend by developing calculators tailored specifically for STEM disciplines, incorporating advanced features such as multifunctionality, high-resolution screens, and compatibility with specialized software.

Technological Advancements and Integration of Graphing Capabilities to Propel Market Growth

The integration of advanced technological features, particularly graphing capabilities, is a significant driver in the Scientific Calculator market. Modern scientific calculators not only perform intricate calculations but also visualize data through interactive graphs and charts. This integration is invaluable for students and professionals in various fields, enabling them to comprehend complex mathematical relationships and analyze data effectively. Graphing calculators are widely used in fields such as engineering, physics, and statistics, allowing users to plot functions, analyze trends, and solve equations graphically. Moreover, the integration of touchscreen interfaces, intuitive software, and wireless connectivity has enhanced user experience, making these calculators more versatile and user-friendly.

Increasing Usage in Professional Fields Drives the Market

Market Dynamics Of the Scientific Calculator

Key Drivers for Scientific Calculator

Growing Need in Academic Institutions and STEM Education: In secondary and tertiary education, scientific calculators continue to be essential resources, particularly in STEM (science, technology, engineering, and mathematics) programs. They are in constant demand across international educational institutions due to their ability to handle complex functions, including logarithms, trigonometry, and statistical analysis, which makes them crucial for students getting ready for professional coursework and standardized tests. Exam regulations enforced by the government that promote non-programmable calculators: Exam boards in a number of nations prohibit the use of internet-enabled or programmable devices during exams. Many high school and college exams, particularly in Asia and Europe, require scientific calculators that meet these standards. Notwithstanding the widespread availability of digital alternatives, this regulatory framework encourages continued use.

Key Restraints for Scientific Calculator

Growing Use of Calculator Apps and Smartphones: In developed markets, students and casual users are no longer in need of physical calculators due to the increasing accessibility of smartphones and the availability of free scientific calculator applications. Sales are being impacted by this digital substitution, especially in urban areas where mobile device usage is prevalent. Cost Sensitivity in Markets Aware of Prices: The cost-effectiveness of electronic learning resources i...

Data contains 2022 world population data publised by the UN DESA for six most populous countries of the world. File also contains the analysis of decomposition of demographic indicators on population growth.

@youtube

Our National Footprint Accounts (NFAs) measure the ecological resource use and resource capacity of nations from 1961 to 2014. The calculations in the National Footprint Accounts are primarily based on United Nations data sets, including those published by the Food and Agriculture Organization, United Nations Commodity Trade Statistics Database, and the UN Statistics Division, as well as the International Energy Agency. The 2018 edition of the NFA features some exciting updates from last year’s 2017 edition, including data for more countries and improved data sources and methodology. Methodology changes:

1. Our conversion of carbon to CO2 increased in precision, which increased the world’s carbon footprint by approximately 1%.
2. We implemented a new data quality scoring system. This allowed us to publish data for more countries by omitting unreliable data for some years rather than the entire country’s Ecological Footprint timeline.
3. We used more precise data from the Global Carbon Project to calculate ocean carbon sequestration rates for 2014.

National Footprint Accounts 2018 Edition

To visualize our data in our data explorer click here. Dataset provides Ecological Footprint per capita data for years 1961-2014 in global hectares (gha). Ecological Footprint is a measure of how much area of biologically productive land and water an individual, population, or activity requires to produce all the resources it consumes and to absorb the waste it generates, using prevailing technology and resource management practices. The Ecological Footprint is measured in global hectares. Since trade is global, an individual or country's Footprint tracks area from all over the world. Without further specification, Ecological Footprint generally refers to the Ecological Footprint of consumption (rather than only production or export). Ecological Footprint is often referred to in short form as Footprint.

About this Dataset

This data includes total and per capita national biocapacity, ecological footprint of consumption, ecological footprint of production and total area in hectares. This dataset, however, does not include any of our yield factors (national or world) nor any equivalence factors. To view these click here.

Objectives

Revealing links between human consumption and other human behaviors, geographic characteristics, political landscapes,

Get involved

How can others contribute? - [ ] Join this table on other data.world datasets (prefereably country-level data) - [ ] Write queries - [ ] Create graphics - [ ] Post and share discoveries

External resources

• Data Explorer
• Footprint Website
• Calculate your own Ecological Footprint

This data package includes the underlying data and files to replicate the calculations, charts, and tables presented in World on the Move: The Changing Global Income Distribution and Its Implications for Consumption Patterns and Public Policies, PIIE Policy Brief 15-21. If you use the data, please cite as: Hellebrandt, Tomas, and Paolo Mauro. (2015). World on the Move: The Changing Global Income Distribution and Its Implications for Consumption Patterns and Public Policies. PIIE Policy Brief 15-21. Peterson Institute for International Economics.

The datasets and code presented in this Data in Brief article are related to the research article entitled "Comprehensiveness of conservation of useful wild plants: an operational indicator for biodiversity and sustainable development targets". The indicator methodology includes five main steps, each requiring and producing data, which are fully described and available here. These data include: species taxonomy, uses, and general geographic information (dataset 1); species occurrence data (dataset 2); global administrative areas data (dataset 3); eco-geographic predictors used in species distribution modeling (dataset 4); a world map raster file (dataset 5); species spatial distribution modeling outputs (dataset 6); ecoregion spatial data used in conservation analyses (dataset 7); protected area spatial data used in conservation analyses (dataset 8); and countries, sub-regions, and regions classifications data (dataset 9). These data are available at http://dx.doi.org/10.17632/2jxj4k32m2.1. In combination with the openly accessible methodology code (https://github.com/CIAT-DAPA/UsefulPlants-Indicator), these data facilitate indicator assessments and serve as a baseline against which future calculations of the indicator can be measured. The data can also contribute to other species distribution modeling, ecological research, and conservation analysis purposes. Resources in this dataset:Resource Title: Data for the calculation of an indicator of the comprehensiveness of conservation of useful wild plants - Mendeley dataset. File Name: Web Page, url: https://data.mendeley.com/datasets/2jxj4k32m2/1 Khoury, Colin K.; Amariles, Daniel; Soto, Jonatan; Diaz, Maria Victoria; Sotelo, Steven; Sosa, Chrystian C.; Ramírez-Villegas , Julian; Achicanoy, Harold; Castañeda-Álvarez , Nora P.; León, Blanca; Wiersema, John H. (2018), Data for the calculation of an indicator of the comprehensiveness of conservation of useful wild plants, Mendeley Data, v1. http://dx.doi.org/10.17632/2jxj4k32m2.1 The datasets presented here are related to the research article entitled “Comprehensiveness of conservation of useful wild plants: an operational indicator for biodiversity and sustainable development targets” (Khoury et al., 2019). The indicator methodology includes five main steps, each requiring and producing data, which are fully described and available here. These data include: species taxonomy, uses, and general geographic information (dataset 1); species occurrence data (dataset 2); global administrative areas data (dataset 3); eco-geographic predictors used in species distribution modeling (dataset 4); a world map raster file (dataset 5); species spatial distribution modeling outputs (dataset 6); ecoregion spatial data used in conservation analyses (dataset 7); protected area spatial data used in conservation analyses (dataset 8); and countries, sub-regions, and regions classifications data (dataset 9). These data are available at http://dx.doi.org/10.17632/2jxj4k32m2.1. In combination with the openly accessible methodology code (https://github.com/CIAT-DAPA/UsefulPlants-Indicator), these data facilitate indicator assessments and serve as a baseline against which future calculations of the indicator can be measured. The data can also contribute to other species distribution modeling, ecological research, and conservation analysis purposes.

The export market share is calculated by dividing the exports of the country by the total exports of the region/world (expressed as percentage in the database). The indicator measures the degree of importance of a country within the total exports of the region/world. For the calculation at current prices, the market share refers to the world trade (world export market share). Data on the values of exports of goods and services are compiled as part of the Balance of Payments of each country. The indicator is calculated as % of world total. Source of total world data used as denominator: International Monetary Fund (IMF).

Pocket Calculators Market Outlook

The global pocket calculators market size is projected to grow significantly, with an estimated CAGR of 6.2% from 2024 to 2032. In 2023, the market was valued at approximately $3.5 billion, and by 2032, it is expected to reach around $6.4 billion. This robust growth can be attributed to the continuous demand for calculators in education and business sectors, technological advancements in calculator functions, and the increasing prevalence of digital learning environments. The integration of advanced features and connectivity options in calculators is further expected to bolster market expansion during the forecast period.

One of the primary growth factors driving the pocket calculators market is the enduring necessity for dedicated calculation devices in educational settings. Despite the proliferation of multifunctional devices like smartphones and tablets, pocket calculators remain indispensable in schools and universities due to their specialized functionalities and ease of use in examination settings. Calculators designed specifically for educational use, such as scientific and graphing calculators, are integral to curricula in mathematics and science courses worldwide. The emphasis on STEM education globally continues to create a substantial demand for calculators, as they provide students with essential tools for learning complex mathematical concepts.

Another significant factor contributing to market growth is the advancements in calculator technology. Modern calculators now come with enhanced features such as programmable functions, connectivity with other devices, and cloud storage capabilities. These innovations have expanded the applications of calculators beyond traditional arithmetic functions to complex problem-solving tools used in various professional fields such as finance and engineering. The integration of graphing capabilities and data analysis functions has widened the appeal of calculators among professionals who require robust computational power on-the-go, further driving the market growth.

The rise of digital learning and remote education platforms has also positively impacted the demand for pocket calculators. As educational institutions adopt digital tools to facilitate learning, the need for reliable, non-disruptive devices like calculators has increased. This trend is prominent in regions with advanced technological infrastructures, where digital literacy is a priority. In addition, the convenience and affordability of pocket calculators make them a preferred choice for students and educators alike. The market is expected to benefit from ongoing investments in educational technology, which frequently incorporate calculators as integral tools for effective learning experiences.

Regionally, Asia Pacific is anticipated to witness the highest growth in the pocket calculators market. The region's rapid economic development, coupled with an expanding middle-class population, supports the growing demand for educational tools. Countries like China, India, and Japan are significant contributors to this growth, driven by large student populations and increasing investments in education. North America and Europe are also substantial markets due to their established education systems and consistent demand for educational aids. In contrast, the markets in Latin America and the Middle East & Africa are expected to experience moderate growth, influenced by their evolving educational landscapes and economic conditions.

Product Type Analysis

When dissecting the pocket calculators market by product type, it becomes evident that scientific calculators hold a significant share due to their extensive application in educational environments. Scientific calculators are indispensable tools for students and professionals dealing with subjects that require complex calculations such as physics, chemistry, and engineering. Their ability to perform a wide range of functions, including trigonometric, logarithmic, and exponential operations, makes them crucial in academic settings. The demand for scientific calculators is particularly high in regions with a strong emphasis on STEM education, and this segment is anticipated to continue its dominance over the forecast period.

Graphing calculators represent another vital segment within the pocket calculators market, catering to advanced educational and professional needs. These calculators are equipped with the capability to plot graphs and solve simultaneous equations, making them essential in higher-level mathematics and engineering courses. Their extensive functionality is p

The export market share is calculated by dividing the exports of the country by the total exports of the region/world (expressed as percentage in the database). The indicator measures the degree of importance of a country within the total exports of the region/world. For the calculation at current prices, the market share refers to the world trade (world export market share). Data on the values of exports of goods and services are compiled as part of the Balance of Payments of each country. The indicator is calculated as % of world total. Source of total world data used as denominator: International Monetary Fund (IMF).

Declination is calculated using the current International Geomagnetic Reference Field (IGRF) model. Declination is calculated using the current World Magnetic Model (WMM) or International Geomagnetic Reference Field (IGRF) model. While results are typically accurate to 30 minutes of arc, users should be aware that several environmental factors can cause disturbances in the magnetic field.

Statistics illustrates market overview of electronic calculators and pocket-size data recording, reproducing and displaying machines with calculating functions in the World from 2007 to 2024.

The Global Hunger Index (GHI) is a tool designed to comprehensively measure and track hunger globally, regionally, and by country. Each year, the International Food Policy Research Institute (IFPRI) calculates GHI scores in order to assess progress, or the lack thereof, in decreasing hunger. The GHI is designed to raise awareness and understanding of regional and country differences in the struggle against hunger. Since 2015, GHI scores have been calculated using a revised and improved formula. The revision replaces child underweight, previously the sole indicator of child undernutrition, with two indicators of child undernutrition—child wasting and child stunting—which are equally weighted in the GHI calculation. The revised formula also standardizes each of the component indicators to balance their contribution to the overall index and to changes in the GHI scores over time. The 2017 GHI has been calculated for 119 countries for which data on the four component indicators are available and where measuring hunger is considered most relevant. GHI scores are not calculated for some higher income countries where the prevalence of hunger is very low. The GHI is only as current as the data for its four component indicators. This year's GHI reflects the most recent available country-level data and from 2012 through 2016. It, therefore, reflects the hunger levels during this period rather than solely capturing conditions in 2017. The 1992, 2000, 2008, and 2017 GHI scores reflect the latest revised data for the four component indicators of the GHI. Where original source data were not available, the estimates of the GHI component indicators were based on the most recent data available. The four component indicators used to calculate the GHI scores draw upon data from the following sources: 1. Undernourishment: Updated data from the Food and Agriculture Organization of the United Nations (FAO) were used for the 1992, 2000, 2008, and 2017 GHI scores. Undernourishment data for the 2017 GHI are for 2014-2016. 2. Child wasting and stunting: The child undernutrition indicators of the GHI—child wasting and child stunting—include data from the joint database of United Nations Children's Fund (UNICEF), the World Health Organization (WHO), and the World Bank, and additional data from WHO's continuously updated Global Database on Child Growth and Malnutrition; the most recent Demographic and Health Survey (DHS) and Multiple Indicator Cluster Survey (MICS) reports; and statistical tables from UNICEF. For the 2017 GHI, data on child wasting and child stunting are for the latest year for which data are available in the period 2012-2016. 3. Child mortality: Updated data from the UN Inter-agency Group for Child Mortality Estimation were used for the 1992, 2000, 2008, and 2017 GHI scores. For the 2017 GHI, data on child mortality are from 2015. Resources related to 2017 Global Hunger Index 2017 Global Hunger Index Website 2017 Global Hunger Index Linked Open Data (LOD) 2017 Global Hunger Index Report

Electronic Calculator Market Outlook

The global electronic calculator market size in 2023 is estimated to be worth USD 15 billion, with a projected growth to USD 23 billion by 2032, reflecting a CAGR of approximately 4.9%. This consistent growth is driven by multiple factors including advancements in educational technology, increased need for specialized calculators in professional sectors, and the ongoing integration of calculators into various digital platforms. The demand for calculators is bolstered by their essential role in educational environments, business computations, and scientific researches, making them indispensable tools across multiple domains. The rising trend of digital education, combined with the growing accessibility of these devices due to technological advancements, further supports the market's expansion. Additionally, the shift towards remote learning and working conditions necessitates the use of reliable computational devices, thereby adding momentum to market growth.

One significant growth factor in the electronic calculator market is the increasing emphasis on STEM (Science, Technology, Engineering, and Mathematics) education. As educational institutions worldwide prioritize STEM curricula, the demand for scientific and graphing calculators, which are critical tools in these disciplines, has significantly risen. These calculators are integral for solving complex equations and problems, making them a staple in both high school and higher education environments. Furthermore, the integration of calculators in standardized testing and examinations ensures a steady demand among students and educational organizations. Additionally, many developing regions are ramping up their educational infrastructure, which includes the procurement of electronic calculators, thereby contributing to the market's growth.

Another driving force behind the market's growth is the increasing need for advanced calculators in various professional sectors. Fields such as finance, engineering, and scientific research require precise and specialized computational tools. Financial calculators, for instance, are essential for professionals dealing with investments, loans, and mortgages, as they provide functions tailored to financial computations. Similarly, industries involved in scientific research and engineering often rely on high-end calculators for data analysis, simulations, and problem-solving. The ongoing innovation and development of these specialized calculators cater to the evolving needs of professionals, thus sustaining demand and promoting market expansion.

The proliferation of online retail channels has also played a crucial role in expanding the electronic calculator market. With the growth of e-commerce platforms, consumers have greater access to a wide range of calculators, from basic to advanced models, at competitive prices. Online retail provides a convenient and hassle-free shopping experience, with detailed product specifications and customer reviews available at the click of a button. This shift towards digital shopping is not only prevalent in developed regions but is also rapidly gaining traction in emerging markets. Consequently, the expansion of online distribution channels has significantly contributed to the market's reach and accessibility, driving overall growth.

In the realm of educational tools, Calculator Rulers have emerged as a unique hybrid, combining the functionalities of a traditional ruler with basic calculating capabilities. This innovative tool is particularly beneficial in educational settings, where students can seamlessly transition between measuring and calculating without switching devices. The integration of Calculator Rulers into classroom environments supports hands-on learning, allowing students to engage in practical applications of mathematical concepts. As educational institutions continue to explore diverse teaching aids, the demand for multifunctional devices like Calculator Rulers is expected to grow, offering a blend of convenience and efficiency in learning processes.

Regionally, North America holds a substantial share of the electronic calculator market due to the presence of prominent educational institutions and a strong emphasis on technology-driven learning. The region's well-established education system and technological advancements create a conducive environment for the use of calculators in various educational and professional settings. Meanwhile, Asia Pacific is anticipated to witness the fastest growth, attributed to the increasing adop

The Magnetic Field Calculator will calculate the total magnetic field, including components (declination, inclination, horizontal intensity, northerly intensity, easterly intensity, vertical intensity) and the annual change for each. Each calculation is for a specific location, elevation and date or range of dates. The calculated result can be obtained from two separate geomagnetic models, the IGRF11 or the WMM2010. Declination is calculated using the current World Magnetic Model (WMM) or International Geomagnetic Reference Field (IGRF) model. While results are typically accurate to 30 minutes of arc, users should be aware that several environmental factors can cause disturbances in the magnetic field.

This is a hybrid gridded dataset of demographic data for the world, given as 5-year population bands at a 0.5 degree grid resolution.

This dataset combines the NASA SEDAC Gridded Population of the World version 4 (GPWv4) with the ISIMIP Histsoc gridded population data and the United Nations World Population Program (WPP) demographic modelling data.

Demographic fractions are given for the time period covered by the UN WPP model (1950-2050) while demographic totals are given for the time period covered by the combination of GPWv4 and Histsoc (1950-2020)

Method - demographic fractions

Demographic breakdown of country population by grid cell is calculated by combining the GPWv4 demographic data given for 2010 with the yearly country breakdowns from the UN WPP. This combines the spatial distribution of demographics from GPWv4 with the temporal trends from the UN WPP. This makes it possible to calculate exposure trends from 1980 to the present day.

To combine the UN WPP demographics with the GPWv4 demographics, we calculate for each country the proportional change in fraction of demographic in each age band relative to 2010 as:

\(\delta_{year,\ country,age}^{\text{wpp}} = f_{year,\ country,age}^{\text{wpp}}/f_{2010,country,age}^{\text{wpp}}\)

Where:

- \(\delta_{year,\ country,age}^{\text{wpp}}\) is the ratio of change in demographic for a given age and and country from the UN WPP dataset.

- \(f_{year,\ country,age}^{\text{wpp}}\) is the fraction of population in the UN WPP dataset for a given age band, country, and year.

- \(f_{2010,country,age}^{\text{wpp}}\) is the fraction of population in the UN WPP dataset for a given age band, country for the year 2020.

The gridded demographic fraction is then calculated relative to the 2010 demographic data given by GPWv4.

For each subset of cells corresponding to a given country c, the fraction of population in a given age band is calculated as:

\(f_{year,c,age}^{\text{gpw}} = \delta_{year,\ country,age}^{\text{wpp}}*f_{2010,c,\text{age}}^{\text{gpw}}\)

Where:

- \(f_{year,c,age}^{\text{gpw}}\) is the fraction of the population in a given age band for given year, for the grid cell c.

- \(f_{2010,c,age}^{\text{gpw}}\) is the fraction of the population in a given age band for 2010, for the grid cell c.

The matching between grid cells and country codes is performed using the GPWv4 gridded country code lookup data and country name lookup table. The final dataset is assembled by combining the cells from all countries into a single gridded time series. This time series covers the whole period from 1950-2050, corresponding to the data available in the UN WPP model.

Method - demographic totals

Total population data from 1950 to 1999 is drawn from ISIMIP Histsoc, while data from 2000-2020 is drawn from GPWv4. These two gridded time series are simply joined at the cut-over date to give a single dataset covering 1950-2020.

The total population per age band per cell is calculated by multiplying the population fractions by the population totals per grid cell.

Note that as the total population data only covers until 2020, the time span covered by the demographic population totals data is 1950-2020 (not 1950-2050).

Disclaimer

This dataset is a hybrid of different datasets with independent methodologies. No guarantees are made about the spatial or temporal consistency across dataset boundaries. The dataset may contain outlier points (e.g single cells with demographic fractions >1). This dataset is produced on a 'best effort' basis and has been found to be broadly consistent with other approaches, but may contain inconsistencies which not been identified.

Calculator Rulers Market Outlook

The global market size for calculator rulers is projected to grow significantly, with an estimated market value of USD 1.2 billion in 2023 and expected to reach approximately USD 2.4 billion by 2032, growing at a compound annual growth rate (CAGR) of 7.5% from 2024 to 2032. This growth can be attributed to the increasing integration of technology in educational and professional tools, along with the rising demand for multifunctional devices that streamline tasks and improve efficiency.

One of the primary growth factors driving the calculator rulers market is the increasing emphasis on STEM (Science, Technology, Engineering, and Mathematics) education across the globe. Educational institutions are continuously adopting advanced tools to enhance the learning experience, making calculator rulers a valuable addition to classrooms and laboratories. The integration of calculators with rulers not only provides students with a dual-function tool but also promotes the practical application of mathematical concepts, thereby boosting demand within the education sector.

In addition to education, the engineering and construction industries are significant contributors to the growth of the calculator rulers market. Professionals in these fields often require precise measurements and complex calculations, tasks that are simplified with the use of calculator rulers. The convergence of measurement tools with computational capabilities supports the efficient execution of engineering projects, ranging from small-scale designs to large infrastructure developments. This integration aids professionals in maintaining accuracy and efficiency, which is crucial for project success.

Moreover, advancements in technology have played a pivotal role in enhancing the features and functionalities of calculator rulers. Modern calculator rulers now come equipped with advanced computational abilities, graphical displays, and even connectivity options, such as Bluetooth and USB, which allow data transfer and integration with other devices. These technological improvements have made calculator rulers more versatile and user-friendly, catering to a broader audience, including hobbyists and DIY enthusiasts who seek multifunctional tools for personal projects.

From a regional perspective, North America and Europe are expected to dominate the calculator rulers market due to their well-established education systems and robust engineering and construction sectors. Additionally, Asia Pacific is anticipated to exhibit the highest growth rate, driven by the rapidly expanding educational infrastructure and increasing technological adoption in countries like China, India, and Japan. The rising demand for innovative educational tools in these regions is likely to further propel market growth.

Graphics Calculators, a subset of the calculator rulers market, have gained immense popularity due to their ability to perform complex mathematical computations and graphing functions. These devices are particularly favored in educational settings, where they aid in teaching subjects like calculus and algebra by allowing students to visualize mathematical concepts through graph plotting. The integration of graphics calculators with ruler functionalities offers a unique advantage, enabling users to perform precise measurements alongside advanced calculations. This dual capability enhances their utility in both academic and professional environments, making them indispensable tools for students and professionals alike.

Product Type Analysis

The calculator rulers market is segmented into three primary product types: scientific calculator rulers, graphing calculator rulers, and basic calculator rulers. Scientific calculator rulers are widely used in educational and professional settings requiring advanced mathematical functions, such as trigonometry, algebra, and calculus. These devices cater to high school and university students, as well as professionals in fields like engineering and physics, who require complex calculations in their work. The increased focus on STEM education is expected to drive demand for scientific calculator rulers, as they become essential tools for academic and professional success.

Graphing calculator rulers are another critical segment within this market, offering advanced features such as graph plotting, statistical analysis, and programmable functions. These devices are particularly popular among students a

The GRDC re-calculated in 2014 the Global Freshwater Fluxes into the World Oceans based on results from the global hydrological model WaterGAP (Doell et al., 2003) for 0.5° grid cell resolution. The annual freshwater fluxes for the 50 year period 1960 2009 and long-term means for the WMO climate normal periods 1961-1990 and 1971-2000 as well as for the entire period 1960 - 2009 are calculated for land areas associated with the UNEP GIWA Regions (UNEP, 2014) as well as from the 5° cells along the continent's coastlines. Freshwater fluxes calculated per 5° and 10° latitude bands show how much freshwater flows from a specific area into a specific ocean. The Global Freshwater Fluxes into the World Oceans are provided as a stand-alone Web Service. The edition of July 2014 replaces the calculation from 2009.

Files contain 5000 samples of AWARE characterization factors, as well as sampled independent data used in their calculations and selected intermediate results.

AWARE is a consensus-based method development to assess water use in LCA. It was developed by the WULCA UNEP/SETAC working group. Its characterization factors represent the relative Available WAter REmaining per area in a watershed, after the demand of humans and aquatic ecosystems has been met. It assesses the potential of water deprivation, to either humans or ecosystems, building on the assumption that the less water remaining available per area, the more likely another user will be deprived.

The code used to generate the samples can be found here: https://github.com/PascalLesage/aware_cf_calculator/

Samples were updated from v1.0 in 2020 to include model uncertainty associated with the choice of WaterGap as the global hydrological model (GHM).

The following datasets are supplied:

1) AWARE_characterization_factor_samples.zip

Actual characterization factors resulting from the Monte Carlo Simulation. Contains 4 zip files:

* monthly_cf.zip: contains 116,484 arrays of 5000 monthly characterization factor samples for each of 9707 watershed and for each month, in csv format. Names are cf_.csv, where is the watershed id and is the first three letters of the month ('jan', 'feb', etc.).


* average_agri_cf.zip: contains 9707 arrays of 5000 annual average, agricultural use, characterization factor samples for each watershed, in csv format. Names are cf_average_agri_.csv.


* average_non_agri_cf.zip: contains 9707 arrays of 5000 annual average, non-agricultural use, characterization factor samples for each watershed, in csv format. Names are cf_average_non_agri_.csv.


* average_unknown_cf.zip: contains 9707 arrays of 5000 annual average, unspecified use, characterization factor samples for each watershed, in csv format. Names are cf_average_unknown_.csv..

2) AWARE_base_data.xlsx

Excel file with the deterministic data, per watershed and per month, for each of the independent variables used in the calculation of AWARE characterization factors. Specifically, it includes:

  Monthly irrigation
    Description: irrigation water, per month, per basin
    Unit: m3/month
    Location in Excel doc: Irrigation
    File name once imported: irrigation.pickle
    table shape: (11050, 12)


  Non-irrigation hwc: electricity, domestic, livestock, manufacturing
    Description: non-irrigation uses of water
    Unit: m3/year
    Location in Excel doc: hwc_non_irrigation
    File name once imported: electricity.pickle, domestic.pickle,
      livestock.pickle, manufacturing.pickle
    table shape: 3 x (11050,)


  avail_delta
    Description: Difference between "pristine" natural availability
      reported in PastorXNatAvail and natural availability calculated
      from "Actual availability as received from WaterGap - after
      human consumption" (Avail!W:AH) plus HWC.
      This should be added to calculated water availability to
      get the water availability used for the calculation of EWR
    Unit: m3/month
    Location in Excel doc: avail_delta
    File name once imported: avail_delta.pickle
    table shape: (11050, 12)


  avail_net
    Description: Actual availability as received from WaterGap - after human consumption
    Unit: m3/month
    Location in Excel doc: avail_net
    File name once imported: avail_net.pickle
    table shape: (11050, 12)


  pastor
    Description: fraction of PRISTINE water availability that should be reserved for environment
    Unit: unitless
    Location in Excel doc: pastor
    File name once imported: pastor.pickle
    table shape: (11050, 12)


  area
    Description: area
    Unit: m2
    Location in Excel doc: area
    File name once imported: area.pickle
    table shape: (11050,)

It also includes:

• information (k values) on the distributions used for each variable (uncertainty tab)

• information (k values) on the model uncertainty (model uncertainty tab)

• two filters used to exclude watersheds that are either in Greenland (polar filter) or without data from the Pastor et al. (2014) method (122 cells), representing small coastal cells with no direct overlap (pastor filter). (filters tab)

3) independent_variable_samples.zip

Samples for each of the independent variables used in the calculation of characterization factors. Only random variables are contained. For all watershed or watershed-months without samples, the Monte Carlo simulation used the deterministic values found in the AWARE_base_data.xlsx file.

The files are in csv format. The first column contains the watershed id (BAS34S_ID) if the data is annual or the (BAS34S_ID, month) for data with a monthly resolution. the other 5000 columns contain the sampled data.

The names of the files are .

4) intermediate_variables.zip

Contains results of intermediate calculations, used in the calculation of characterization factors. The zip file contains 3 zip files:

* AMD_world_over_AMD_i.zip: contains 116,484 arrays (for each watershed-month) of 5000 calculated values of the ratio between the AMD (Availability Minus Demand) for the watershed-month and AMD_glo, the world weighted AMD average. Format is csv.
* AMD_world.zip: contains one array of 5000 calculated values of the world average AMD. Format is csv.


* HWC.zip: contains 116,484 arrays (for each watershed-month) of 5000 calculated values of the total Human Water Consumption. Format is csv.

5) watershedBAS34S_ID.zip

Contains the GIS files to link the watershed ids (BAS34S_ID) to actual spatial data.