This dataset contains year-wise data of Cost Inflation Index (CII). The CII number is used to arrive at the inflation-adjusted cost price of assets transferred for computing long-term capital gains.

During the financial year 2023, the cost inflation index (CII) in India stood at ***. This was an increase from the previous year's figure of ***. The CII is used to compute an asset's inflation-adjusted cost price. It is used to assess the inflation value of assets like land, houses, jewelry etc.

During the financial year 2026, the cost inflation index (CII) in India stood at 376. This was an increase from the previous year's figure of 363. The CII is used to compute an asset's inflation-adjusted cost price. It is used to assess the inflation value of assets like land, houses, jewelry etc.

This index tracks timing complications across Rolex Daytona, Omega Speedmaster, Breitling Navitimer, TAG Heuer Monaco/Carrera, Patek Philippe chronographs, and AP Royal Oak Chronograph. It measures performance of racing-heritage and precision timing watches. Use this as a critical benchmark for motorsport-connected timepieces, vintage chronograph appreciation, and mechanical timing complication desirability.

Aerial photographs are retrievable on a frame by frame basis. The aerial photo inventory contains imagery from various sources that are now archived at the Earth Data Analysis Center.

Patterns of biodiversity, such as the increase toward the tropics and the peaked curve during ecological succession, are fundamental phenomena for ecology. Such patterns have multiple, interacting causes, but temperature emerges as a dominant factor across organisms from microbes to trees and mammals, and across terrestrial, marine, and freshwater environments. However, there is little consensus on the underlying mechanisms, even as global temperatures increase and the need to predict their effects becomes more pressing. The purpose of this project is to generate and test theory for how temperature impacts biodiversity through its effect on biochemical processes and metabolic rate. A combination of standardized surveys in the field and controlled experiments in the field and laboratory measure diversity of three taxa -- trees, invertebrates, and microbes -- and key biogeochemical processes of decomposition in seven forests distributed along a geographic gradient of increasing temperature from cold temperate to warm tropical. This dataset was based on trees contained in five Gentry plots set up at Harvard Forest by the Enquist Lab (PI, Brian Enquist) from the University of Arizona as part of a macrosystems biodiversity and latitude project supported by the National Science Foundation under Cooperative Agreement DEB#1065836. The CII stands for Crown Illumination Index, which is a ranked measure of how closed or open a canopy is. It was developed by Clark and Clark (1992), and focuses on the extent to which the crown of any sized tree receives overhead vertical light (directly above) and lateral light coming from the sides. For instance, a '5' corresponds to an exposed tree, a '1' to a completely shaded tree. Trees were classified by CII at Harvard Forest LTER by John Grady of the University of New Mexico.

*Wilcoxon signed-rank test;†Wilcoxon signed-rank test pair-wise comparison: Year 1 vs Baseline;§Wilcoxon signed-rank test pair-wise comparison: Year 2 vs Baseline;θWilcoxon signed-rank test pair-wise comparison: Year 1 vs Year 2.

Three-tier CSI Industry indices and respective symbols.

Construction Output Price Indices (OPIs) from January 2014 to June 2025, UK. Summary

From 2015 to 2024, the construction output prices of public and private housing increased by ***** percent in the United Kingdom (UK). Meanwhile, the prices of industrial buildings increased by ***** percent during that period, and infrastructure prices by ***** percent. Housing and industrial are the segments that increased the most during that period. Balfour Beatty ranked in the past years as the construction firm with the largest revenue in the UK.

Building construction price indexes (BCPI), percent change, by type of building and construction division. Quarterly data are available from the first quarter of 1982. The table presents quarter-over-quarter and year-over-year percentage changes for various aggregation levels. The base period for the index is (2017=100).

Consumer Price Index CPI in Pakistan decreased to 270.18 points in August from 271.94 points in July of 2025. This dataset provides - Pakistan Consumer Price Index (CPI) - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The application of QSAR along with other in silico tools like molecular docking, and molecular dynamics provide a lot of promise for finding new treatments for life-threatening diseases like Type 2 diabetes mellitus (T2DM). The present study is an attempt to develop Monte Carlo algorithm-based QSAR models using freely available CORAL software. The experimental data on the α-amylase inhibition by a series of benzothiazole-linked hydrazone/2,5-disubstituted-1,3,4-oxadiazole hybrids were selected as endpoint for the model generation. Initially, a total of eight QSAR models were built using correlation intensity index (CII) as a criterion of predictive potential. The model developed from split 6 using CII was the most reliable because of the highest numerical value of the determination coefficient of the validation set (r2VAL = 0.8739). The important structural fragments responsible for altering the endpoint were also extracted from the best-built model. With the goal of improved prediction quality and lower prediction errors, the validated models were used to build consensus models. Molecular docking was used to know the binding mode and pose of the selected derivatives. Further, to get insight into their metabolism by living beings, ADME studies were investigated using internet freeware, SwissADME.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

CII CI RESOURCES LIMITED

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

CII, Cognitive Impairment Index; EDSS, Expanded Disability Status Scale; SE, Standard Error; OR, Odds Ratio.

ABSTRACT The paper discusses the determination of inflation in Brazil, especially after the great recession of 2015-2016, to assess the adequacy of manipulating interest rates to control the rise in prices due to permanent cost pressure. The burden of using the interest rate to fight cost inflation is to create a highly conventional level of the real interest rate, which benefits the rentier class in a financialized economy. In the light of the post-Keynesian macroeconomics, a high-interest rate convention keeps the economy with a low growth rate and a low investment rate, which in the case of the Brazilian economy has resulted in a regression in the productive matrix and productivity stagnation, and both contribute to perpetuating cost pressures on prices. The empirical analysis corroborates the discussion about recent inflation having its origin in cost pressures over which the interest rate impact for its control is limited. We complement the empirical analysis by testing the response to the SELIC interest rate of the variables used to explain the fluctuation of market prices and administered prices: commodity price index, exchange rate and activity level. As expected, the impact of an increase in the interest rate appreciates the exchange rate, favouring inflation control and reducing the level of activity but has no impact on the commodity price index.

Dynamic GMM-regression results.

In 2021, the inflation rate of the cost of steel products in Australia was **** percent. This was the highest inflation rate of all construction materials in the country. On the other hand, construction materials like timber and metal products saw a inflation of **** percent and **** percent, respectively.

Clinicopathological characteristics according to colon inflammatory index.

Abbreviations: ARR = Annualized Relapse Rate; EDSS = Expanded Disability Status Scale; BDI = Beck Depression Inventory.