Graph and download economic data for Producer Price Index by Industry: Surgical Appliance and Supplies Manufacturing: Artificial Joints and Limbs (PCU33911333911321) from Jun 1983 to Sep 2025 about surgical, appliances, supplies, manufacturing, PPI, industry, inflation, price index, indexes, price, and USA.

Experimental evolution studies can be used to explore genomic response to artificial and natural selection. In such studies, loci that display larger allele frequency change than expected by genetic drift alone are assumed to be directly or indirectly associated with traits under selection. However, such studies report surprisingly many loci under selection, suggesting that current tests for allele frequency change may be subject to p-value inflation and hence be anti-conservative. One factor known from genome wide association (GWA) studies to cause p-value inflation is population stratification, such as relatedness among individuals. Here we suggest that by treating presence of an individual in a population after selection as a binary response variable, existing GWA methods can be used to account for relatedness when estimating allele frequency change. We show that accounting for relatedness like this effectively reduces false positives in tests for allele frequency change in simulated...

Russia Consumer Price Index (CPI): Prev Dec=100: Medical Services: Artificial Crown Making data was reported at 104.380 Prev Dec=100 in Dec 2018. This records an increase from the previous number of 104.270 Prev Dec=100 for Nov 2018. Russia Consumer Price Index (CPI): Prev Dec=100: Medical Services: Artificial Crown Making data is updated monthly, averaging 108.885 Prev Dec=100 from Jan 1995 (Median) to Dec 2018, with 288 observations. The data reached an all-time high of 250.500 Prev Dec=100 in Dec 1995 and a record low of 100.780 Prev Dec=100 in Jan 2017. Russia Consumer Price Index (CPI): Prev Dec=100: Medical Services: Artificial Crown Making data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Inflation – Table RU.IA020: Consumer Price Index: Previous December=100: Services.

Graph and download economic data for Producer Price Index by Industry: Artificial Fibers and Filaments Manufacturing (PCU325220325220) from Jan 1967 to Aug 2025 about fiber, manufacturing, PPI, industry, inflation, price index, indexes, price, and USA.

Russia Consumer Price Index (CPI): Same Mth PY=100: Medical Services: Artificial Crown Making data was reported at 104.380 Same Mth PY=100 in Dec 2018. This records a decrease from the previous number of 104.470 Same Mth PY=100 for Nov 2018. Russia Consumer Price Index (CPI): Same Mth PY=100: Medical Services: Artificial Crown Making data is updated monthly, averaging 116.575 Same Mth PY=100 from Jan 1995 (Median) to Dec 2018, with 288 observations. The data reached an all-time high of 301.170 Same Mth PY=100 in Apr 1995 and a record low of 103.470 Same Mth PY=100 in Jun 2017. Russia Consumer Price Index (CPI): Same Mth PY=100: Medical Services: Artificial Crown Making data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Inflation – Table RU.IA016: Consumer Price Index: Same Month Previous Year=100: Services.

Russia Consumer Price Index (CPI): Weights: Services: Medical Services: Artificial Crown Making data was reported at 0.240 % in 2019. This records an increase from the previous number of 0.228 % for 2018. Russia Consumer Price Index (CPI): Weights: Services: Medical Services: Artificial Crown Making data is updated yearly, averaging 0.232 % from Dec 2012 (Median) to 2019, with 8 observations. The data reached an all-time high of 0.240 % in 2019 and a record low of 0.180 % in 2012. Russia Consumer Price Index (CPI): Weights: Services: Medical Services: Artificial Crown Making data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Inflation – Table RU.IA027: Consumer Price Index: Weights.

Russia Consumer Price Index (CPI): Prev Dec=100: CL: Footwear: Female: Artificial Leather: Shoes data was reported at 102.450 Prev Dec=100 in Dec 2018. This records an increase from the previous number of 101.990 Prev Dec=100 for Nov 2018. Russia Consumer Price Index (CPI): Prev Dec=100: CL: Footwear: Female: Artificial Leather: Shoes data is updated monthly, averaging 104.220 Prev Dec=100 from Jan 1997 (Median) to Dec 2018, with 264 observations. The data reached an all-time high of 162.390 Prev Dec=100 in Dec 1999 and a record low of 99.750 Prev Dec=100 in Jan 2012. Russia Consumer Price Index (CPI): Prev Dec=100: CL: Footwear: Female: Artificial Leather: Shoes data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Inflation – Table RU.IA019: Consumer Price Index: Previous December=100: Non Food.

Consumer Price Indices (CPI) measure changes over time in general level of prices of goods and services that households acquire for the purpose of consumption. CPI numbers are widely used as a macroeconomic indicator of inflation, as a tool by governments and central banks for inflation targeting and for monitoring price stability, and as deflators in the national accounts. CPI is also used for indexing dearness allowance to employees for increase in prices. CPI is therefore considered as one of the most important economic indicators. For construction of CPI numbers, two requisite components are weighting diagrams (consumption patterns) and price data collected at regular intervals. The Central Statistics Office (CSO), Ministry of Statistics and Programme Implementation releases Consumer Price Indices (CPI) on base 2010=100 for all-India and States/UTs separately for rural, urban and combined every month with effect from January, 2011. The data is Published by Central Statistical Office and released on 12th of every month.

Social Inflation Analytics for Claims Market Outlook

According to our latest research, the global Social Inflation Analytics for Claims market size reached USD 1.32 billion in 2024, reflecting the rapid adoption of advanced analytics tools in the insurance and claims management industry. The market is anticipated to expand at a robust CAGR of 14.1% during the forecast period, reaching an estimated USD 3.65 billion by 2033. This strong growth trajectory is being driven by the increasing prevalence of social inflation, which is compelling insurers and related stakeholders to invest in sophisticated analytics solutions for mitigating risks, detecting fraud, and optimizing claims outcomes.

One of the primary growth factors fueling the Social Inflation Analytics for Claims market is the escalating complexity and frequency of insurance claims influenced by social inflation. Social inflation refers to the rising costs of insurance claims resulting from societal trends, such as increased litigation, larger jury awards, and evolving legal interpretations. As these factors become more pronounced, insurers are facing mounting pressure to accurately assess, manage, and predict the financial impact of claims. Advanced analytics tools, leveraging machine learning and artificial intelligence, are becoming essential for uncovering hidden patterns, identifying potential fraudulent activities, and streamlining the claims process. The need to maintain profitability and manage reserve allocations efficiently is prompting insurance companies and third-party administrators to adopt social inflation analytics at an accelerated pace.

Another significant driver is the growing regulatory scrutiny and compliance requirements in the insurance sector. Governments and regulatory bodies across the globe are implementing stricter guidelines to ensure transparency and fairness in claims processing. This has necessitated the deployment of analytics solutions capable of providing real-time insights, automated documentation, and comprehensive audit trails. By harnessing social inflation analytics, organizations can not only enhance their compliance posture but also proactively adapt to regulatory changes. Furthermore, the integration of analytics platforms with legacy insurance systems is enabling seamless data exchange and improved operational efficiencies, further propelling market growth.

Additionally, the surge in digital transformation initiatives across the insurance ecosystem is playing a pivotal role in market expansion. The proliferation of connected devices, the digitization of customer interactions, and the availability of large volumes of structured and unstructured data have created fertile ground for advanced analytics applications. Insurers are increasingly leveraging cloud-based analytics platforms to gain scalable, flexible, and cost-effective access to predictive models and real-time dashboards. These platforms enable organizations to respond swiftly to emerging social inflation trends, enhance customer experiences, and optimize claims settlements. The demand for on-demand analytics and the growing emphasis on data-driven decision-making are expected to sustain the momentum of the Social Inflation Analytics for Claims market over the coming years.

From a regional perspective, North America continues to dominate the Social Inflation Analytics for Claims market, accounting for the largest share in 2024. This leadership is attributed to the region's mature insurance industry, high litigation rates, and early adoption of advanced analytics technologies. Europe and Asia Pacific are also witnessing rapid growth, driven by rising insurance penetration, evolving regulatory landscapes, and increasing awareness of social inflation risks. The Middle East & Africa and Latin America, while smaller in market size, are expected to demonstrate significant potential as insurers in these regions intensify their focus on operational efficiency and risk mitigation. The global market outlook remains positive, with all regions poised to benefit from ongoing technological advancements and the growing imperative for robust claims analytics.

Graph and download economic data for Producer Price Index by Commodity: Miscellaneous Products: Artificial Joints and Limbs (WPU156301041) from Dec 2011 to Sep 2025 about miscellaneous, medical, commodities, PPI, inflation, price index, indexes, price, and USA.

Russia Consumer Price Index (CPI): Prev Dec=100: CL: Footwear: Female: Artificial Leather: Summer Shoes data was reported at 101.870 Prev Dec=100 in Dec 2018. This stayed constant from the previous number of 101.870 Prev Dec=100 for Nov 2018. Russia Consumer Price Index (CPI): Prev Dec=100: CL: Footwear: Female: Artificial Leather: Summer Shoes data is updated monthly, averaging 105.290 Prev Dec=100 from Jan 1995 (Median) to Dec 2018, with 288 observations. The data reached an all-time high of 205.170 Prev Dec=100 in Oct 1995 and a record low of 99.990 Prev Dec=100 in Jan 2017. Russia Consumer Price Index (CPI): Prev Dec=100: CL: Footwear: Female: Artificial Leather: Summer Shoes data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Inflation – Table RU.IA019: Consumer Price Index: Previous December=100: Non Food.

Russia Consumer Price Index (CPI): Prev Month=100: PC: Fancy Goods: Women Handbag: Artificial Leather data was reported at 99.930 Prev Mth=100 in Dec 2018. This records a decrease from the previous number of 100.270 Prev Mth=100 for Nov 2018. Russia Consumer Price Index (CPI): Prev Month=100: PC: Fancy Goods: Women Handbag: Artificial Leather data is updated monthly, averaging 100.745 Prev Mth=100 from Jan 1995 (Median) to Dec 2018, with 288 observations. The data reached an all-time high of 118.090 Prev Mth=100 in Sep 1998 and a record low of 99.880 Prev Mth=100 in Jul 2018. Russia Consumer Price Index (CPI): Prev Month=100: PC: Fancy Goods: Women Handbag: Artificial Leather data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Inflation – Table RU.IA010: Consumer Price Index: Previous Month=100: Non Food.

Russia Consumer Price Index (CPI): Prev Month=100: CL: Footwear: Female: Artificial Leather: Summer Shoes data was reported at 100.000 Prev Mth=100 in Dec 2018. This records an increase from the previous number of 99.900 Prev Mth=100 for Nov 2018. Russia Consumer Price Index (CPI): Prev Month=100: CL: Footwear: Female: Artificial Leather: Summer Shoes data is updated monthly, averaging 100.445 Prev Mth=100 from Jan 1995 (Median) to Dec 2018, with 288 observations. The data reached an all-time high of 116.660 Prev Mth=100 in Sep 1998 and a record low of 97.620 Prev Mth=100 in Nov 1995. Russia Consumer Price Index (CPI): Prev Month=100: CL: Footwear: Female: Artificial Leather: Summer Shoes data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Inflation – Table RU.IA010: Consumer Price Index: Previous Month=100: Non Food.

ABSTRACT The current Covid-19 pandemic has been the most discussed topic of the year, mostly about protection and ways to avoid dissemination of the virus. In the healthcare system, especially in the operating rooms, the viability of laparoscopic surgery was questioned, mostly because of the transmission through aerosol. This article tries to suggest a way to minimize risks of laparoscopic surgery, during this situation, by using electrostatic filters, a simple, effective and low cost alternative.

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.

Probabilistic AI: A New Approach to Artificial Intelligence

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

Smart Tire-Inflation Garage Robot Market Outlook

According to our latest research, the global smart tire-inflation garage robot market size reached USD 1.14 billion in 2024, reflecting robust momentum fuelled by increasing automation in automotive maintenance. The market is projected to grow at a CAGR of 13.2% from 2025 to 2033, reaching an estimated USD 3.44 billion by 2033. This growth is primarily driven by the rising adoption of intelligent vehicle service solutions, surging demand for enhanced vehicle safety, and the growing emphasis on convenience and efficiency in garage operations worldwide.

One of the primary growth factors for the smart tire-inflation garage robot market is the rapid technological advancement in automotive service equipment. As vehicles become more sophisticated, the need for precision in tire maintenance has become paramount. Smart tire-inflation robots leverage advanced sensors, artificial intelligence, and IoT connectivity to ensure optimal tire pressure, which directly impacts vehicle safety, fuel efficiency, and tire longevity. Automotive manufacturers and service providers are increasingly integrating these robots into their operations to minimize human error, reduce downtime, and provide consistent, high-quality service. The integration of predictive maintenance features and real-time diagnostics further enhances the value proposition of these systems, making them indispensable in modern garages and service centers.

Another significant driver is the growing consumer preference for automated and contactless vehicle services. The COVID-19 pandemic accelerated the adoption of contactless technologies across various industries, including automotive services. Consumers now expect minimal human intervention and faster turnaround times when it comes to routine vehicle maintenance. Smart tire-inflation garage robots address these expectations by automating the tire inflation process, reducing wait times, and ensuring a safer environment for both customers and service personnel. This shift in consumer behavior is prompting both independent garages and large automotive service chains to invest in automated solutions, further propelling market growth.

Additionally, regulatory initiatives aimed at improving road safety and reducing vehicular emissions are playing a crucial role in shaping the smart tire-inflation garage robot market. Governments across North America, Europe, and Asia Pacific are implementing stringent regulations regarding tire pressure monitoring and maintenance. These regulations not only mandate regular tire checks but also encourage the use of advanced technologies to ensure compliance. Smart tire-inflation robots, with their ability to deliver precise and consistent results, are increasingly being adopted to meet these regulatory requirements. The growing focus on sustainability and energy efficiency is also encouraging fleet operators and commercial vehicle owners to adopt automated tire maintenance solutions, thereby expanding the marketÂ’s addressable base.

In the realm of automotive innovation, the Smart Bicycle Tire Pressure Monitor is emerging as a pivotal technology, particularly for urban cyclists and eco-conscious commuters. This device offers real-time monitoring of tire pressure, ensuring optimal performance and safety on the road. As cities around the world continue to promote cycling as a sustainable mode of transportation, the demand for reliable tire maintenance solutions is on the rise. The integration of smart tire pressure monitors with mobile applications allows cyclists to receive instant alerts and maintenance reminders, enhancing their riding experience. Moreover, the ability to maintain proper tire pressure not only extends the lifespan of bicycle tires but also contributes to improved energy efficiency and reduced carbon footprint. As the market for smart tire-inflation solutions expands, the inclusion of bicycle-specific technologies is becoming increasingly significant, catering to the diverse needs of modern urban mobility.

From a regional perspective, Asia Pacific is emerging as the fastest-growing market for smart tire-inflation garage robots, driven by the rapid expansion of the automotive sector, increasing vehicle ownership, and rising investments in automotive infrastructure. North America and Europe continue t

Russia Consumer Price Index (CPI): Same Mth PY=100: PC: Fancy Goods: Women Handbag: Artificial Leather data was reported at 101.240 Same Mth PY=100 in Dec 2018. This records a decrease from the previous number of 101.540 Same Mth PY=100 for Nov 2018. Russia Consumer Price Index (CPI): Same Mth PY=100: PC: Fancy Goods: Women Handbag: Artificial Leather data is updated monthly, averaging 109.910 Same Mth PY=100 from Jan 1995 to Dec 2018, with 288 observations. The data reached an all-time high of 273.490 Same Mth PY=100 in Apr 1995 and a record low of 101.240 Same Mth PY=100 in Dec 2018. Russia Consumer Price Index (CPI): Same Mth PY=100: PC: Fancy Goods: Women Handbag: Artificial Leather data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Inflation – Table RU.IA015: Consumer Price Index: Same Month Previous Year=100: Non Food.

Graph and download economic data for Producer Price Index by Industry: Artificial Fibers and Filaments Manufacturing: Other Noncellulosic Organic Fibers, Including Polyamide, Polyolefin, and Producer-Textured (DISCONTINUED) (PCU32522032522029) from Jun 2011 to Dec 2017 about organic, fiber, manufacturing, PPI, industry, inflation, price index, indexes, price, and USA.

Description: This dataset provides information on the per capita income in Canada over various years. It includes data on the annual income earned per person in the country, which is useful for understanding economic trends and assessing changes in income levels over time.

Features:

Year: The specific year for which the per capita income data is recorded. Per Capita Income: The average income earned per person in Canada for the given year, typically measured in Canadian dollars. Usage:

Trend Analysis: Examine how per capita income has changed over the years and identify trends in economic growth or decline. Economic Research: Use the data to study the impact of economic policies, inflation, or other factors on individual income levels. Regional Comparisons: Compare per capita income data across different years to analyze economic disparities or improvements. Source: The data is sourced from national statistical agencies, economic reports, or governmental databases that track income and economic indicators.

Notes:

Ensure to verify the data for consistency and accuracy. Historical data may be adjusted for inflation to reflect real income changes.

Graph and download economic data for Producer Price Index by Commodity for Miscellaneous Products: Feathers, Plumes, and Artificial Trees and Flowers (DISCONTINUED) (WPU159A0303) from Dec 1998 to Dec 2009 about flower, miscellaneous, commodities, PPI, inflation, price index, indexes, price, and USA.