This programs derives a table of secular change in magnetic declination for a specified point in the conterminous United States. It utilizes the USD polynomial and the IGRF spherical harmonic models. 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.

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Exports - Electric Calculator (Includes Pocket-Size Data Recorde in China increased to 28047 USD THO in December from 26276 USD THO in November of 2019. This dataset includes a chart with historical data for China Exports of Electric Calculator (includes Pocket-s.

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Hungary - Harmonised index of consumer prices (HICP): Calculators and other information processing equipment was 132.82 points in December of 2023, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Hungary - Harmonised index of consumer prices (HICP): Calculators and other information processing equipment - last updated from the EUROSTAT on June of 2025. Historically, Hungary - Harmonised index of consumer prices (HICP): Calculators and other information processing equipment reached a record high of 132.82 points in December of 2023 and a record low of 98.84 points in August of 2015.

Interannual Electricity Demand Calculator

Large parts of this code were originally developed by Lieke van der Most (University of Groningen) in the EU renewable energy modelling framework and release under MIT license. The original version of the code can be found here and is referenced below as [1]. This model has been validated against historical electricity demand data reported on the ENTSO-E transparancy platform.

We have made the following adjustments to the original version:

generate hourly instead of daily electricity consumption profiles

use snakemake for workflow management

trim repository to demand-related code and data

adjust code to accept cutouts from atlite for weather data

Purpose

Variations in weather conditions affect electricity demand patterns. This workflow generates country-level electricity consumption time series based on weather data using analysis by Lieke van der Most correlating historical electricity demand to temperature. This workflow first calculates a daily electricity demand based on the regression model developed in [1]. Subsequently, cumulative daily electricity demands are disaggregated using a hourly profile sampled from a random historical day (that is the same weekday) from the Open Power System Database. The resulting output/demand_hourly.csv file is compatible with the open-source electricity system model PyPSA-Eur.

Holidays are treated like weekend days. Data on national holidays across Europe are obtained using another repository by Aleksander Grochowicz and others that similarly computes artificial electricity demand time series: github.com/aleks-g/multidecade-data. The holidays are stored at input_files/noworkday.csv.

Installation and Usage

Clone the Repository

Download the demand_calculator repository using git.

/some/other/path % cd /some/path/without/spaces /some/path/without/spaces % git clone https://github.com/martacki/demand_calculator.git

Install Dependencies with conda/mamba

Use conda or mamba to install the required packages listed in environment.yaml.

The environment can be installed and activated using

.../demand_calculator % conda env create -f environment.yaml .../demand_calculator % conda activate demand

Retrieve Input Data

The only required additional input files are ERA5 cutouts which can be recycled from the PyPSA-Eur weather data deposit on Zenodo. Place the file europe-2013-era5.nc in the following location (and rename!):

./input_files/cutouts/europe-era5-2013.nc

Cutouts for other weather years than 2013 can be built using the build_cutout rule from the PyPSA-Eur repository.

Run the Workflow

This repository uses snakemake for workflow management. To run the complete workflow, execute:

.../demand_calculator % snakemake -jall all

After successfully running the workflow, the output files will be located in output/energy_demand named demand_hourly_{yr}.csv.

The years to compute can be modified directly in the Snakefile.

License

The file demand_hourly.csv is released under CC-BY-4.0 license.

The file src.zip is released under MIT license.

Changelog

2024-03-15: Extended date range from 1941 to 2023.

China Calculator & Currency Special Equipment: Loss Amount: Year to Date data was reported at 0.187 RMB bn in Oct 2015. This records a decrease from the previous number of 0.193 RMB bn for Sep 2015. China Calculator & Currency Special Equipment: Loss Amount: Year to Date data is updated monthly, averaging 0.097 RMB bn from Dec 2003 (Median) to Oct 2015, with 97 observations. The data reached an all-time high of 0.214 RMB bn in Aug 2015 and a record low of 0.015 RMB bn in Dec 2010. China Calculator & Currency Special Equipment: Loss Amount: Year to Date data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Industrial Sector – Table CN.BHW: Culture and Office Machinery: Calculator and Currency Special Equipment.

CN: Calculator & Currency Special Equipment: YoY: Loss Amount: ytd data was reported at 95.392 % in Oct 2015. This records an increase from the previous number of 73.142 % for Sep 2015. CN: Calculator & Currency Special Equipment: YoY: Loss Amount: ytd data is updated monthly, averaging 24.531 % from Jan 2006 (Median) to Oct 2015, with 89 observations. The data reached an all-time high of 345.086 % in Nov 2011 and a record low of -61.110 % in Nov 2007. CN: Calculator & Currency Special Equipment: YoY: Loss Amount: ytd data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Industrial Sector – Table CN.BHW: Culture and Office Machinery: Calculator and Currency Special Equipment.

China Calculator & Currency Special Equipment: YoY: Total Liability data was reported at 4.160 % in Oct 2015. This records a decrease from the previous number of 10.761 % for Sep 2015. China Calculator & Currency Special Equipment: YoY: Total Liability data is updated monthly, averaging 12.315 % from Jan 2006 (Median) to Oct 2015, with 89 observations. The data reached an all-time high of 58.280 % in Nov 2010 and a record low of -5.220 % in Nov 2008. China Calculator & Currency Special Equipment: YoY: Total Liability data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Industrial Sector – Table CN.BHW: Culture and Office Machinery: Calculator and Currency Special Equipment.

Euro Area - Harmonised index of consumer prices (HICP): Calculators and other information processing equipment was 100.99 points in May of 2025, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Euro Area - Harmonised index of consumer prices (HICP): Calculators and other information processing equipment - last updated from the EUROSTAT on July of 2025. Historically, Euro Area - Harmonised index of consumer prices (HICP): Calculators and other information processing equipment reached a record high of 109.44 points in April of 2023 and a record low of 90.43 points in October of 2019.

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Construction Calculators Market Outlook

The global construction calculators market size was valued at approximately USD 1.2 billion in 2023 and is projected to reach USD 2.3 billion by 2032, growing at a compound annual growth rate (CAGR) of 7.2%. The growth of this market is primarily driven by increasing construction activities worldwide, technological advancements in calculator functionalities, and the growing demand for precision and efficiency in construction projects.

One of the major growth factors for the construction calculators market is the rising construction activities across the globe, especially in developing regions such as Asia-Pacific and Latin America. The boom in infrastructure projects, residential complexes, and commercial buildings necessitates the need for accurate and efficient calculation tools. Construction calculators provide precise measurements and estimates, helping to reduce wastage and cost overruns, which are critical in large-scale construction projects.

Technological advancements have significantly enhanced the functionalities of construction calculators, making them more versatile and user-friendly. Modern calculators are equipped with advanced features such as unit conversions, material estimates, cost calculations, and integration with other digital tools. These advancements have made construction calculators indispensable for professionals who require accurate and quick calculations on-site or in the office. The integration of software-based calculators with smartphones and other portable devices has further propelled their adoption.

Another important growth driver is the increasing emphasis on cost-efficiency and project management in the construction industry. With rising material costs and labor expenses, construction firms are under immense pressure to optimize resources and minimize errors. Construction calculators play a crucial role in this by providing precise measurements that can prevent costly mistakes. Additionally, they help in planning and budgeting, which is essential for project success. The growing trend of digitalization in the construction sector is also contributing to the market growth.

From a regional perspective, North America currently holds a significant share of the construction calculators market due to the well-established construction industry and high adoption rates of advanced technologies. However, the Asia-Pacific region is expected to witness the highest growth rate during the forecast period, driven by rapid urbanization, increasing infrastructure investments, and the expansion of residential and commercial construction activities. Europe and Latin America are also projected to experience steady growth owing to the modernization of construction practices and increased focus on sustainable building solutions.

Product Type Analysis

The product type segment in the construction calculators market is broadly categorized into handheld calculators, desktop calculators, and software-based calculators. Each of these categories caters to specific needs and preferences within the construction industry. Handheld calculators are highly portable and convenient for on-site use, making them popular among contractors and engineers who need quick and reliable calculations. These devices typically come with robust features that can handle various construction-related measurements, including area, volume, and material estimates.

Desktop calculators, on the other hand, are designed for office use and are often favored by architects and project managers who require detailed and complex calculations. These calculators offer more comprehensive functions and larger screens, making it easier to input and review data. The stability and durability of desktop calculators make them suitable for long-term use in office environments. They often come with additional functionalities such as historical data storage and connectivity options, enhancing their utility in extensive project planning and management.

Software-based calculators represent the most advanced segment within the product type category. These are often integrated into construction management software and can be accessed via computers, tablets, and smartphones. Software-based calculators offer unparalleled flexibility and functionality, including real-time updates, cloud storage, and integration with other digital tools like BIM (Building Information Modeling) and CAD (Computer-Aided Design) software. They are particularly useful for large projects that require comprehensive data analysis and collaboration among mult

Psoriatic arthritis (PsA) affects approximately one in five individuals with psoriasis. Early identification of patients with psoriasis at risk of developing PsA is crucial to prevent poor prognosis. We established a derivation cohort comprising 1,661 patients with psoriasis from 49 hospitals. Clinical and demographic variables ascertained at hospital admission were screened using the Least Absolute Shrinkage and Selection Operator and logistic regression to construct a prediction model and a new web-based calculator. Ultimately, six significant independent predictors were identified: history of unexplained swollen joints (odds ratio [OR]: 5.814, 95% confidence interval [95% CI]: 3.304–10.117; p< 0.001), history of arthritis (OR: 3.543, 95% CI: 1.982–6.246; p< 0.001), history of unexplained swollen and painful fingers or toes (OR: 2.707, 95% CI: 1.463–4.915; p = 0.001), nail involvement (OR: 1.907, 95% CI: 1.235–2.912; p = 0.003), hyperlipidemia (OR: 4.265, 95% CI: 0.921–15.493; p = 0.042), and prolonged topical use of glucocorticosteroids (OR: 1.581, 95% CI: 1.052–2.384, p = 0.028). The web-based calculator derived from this model can assist clinicians in promptly determining the probability of developing PsA in patients with psoriasis, thereby facilitating improved clinical decision-making.

Inflation Rate in Taiwan decreased to 1.37 percent in June from 1.55 percent in May of 2025. This dataset provides the latest reported value for - Taiwan Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.