The growth of the Internet since its inception has fueled strong demand and profitability for web design services, as both businesses and households increasingly conduct activities online. The pandemic accelerated this trend, forcing businesses to upgrade their digital presence amid lockdowns and remote work, which resulted in significant revenue gains for web designers in 2020. This trend continued in 2021 as the strong economic recovery boosted corporate profit and gave businesses greater funds to invest in the industry’s services. More recently, high inflation and rising interest rates have raised costs and curtailed demand, with some businesses opting for cheaper alternatives like templates rather than custom web design, contributing to a drop in revenue in 2022. Despite these challenges, rising stock prices linked to AI advancements pushed business income substantially upward, enabling further investment in web design through 2023 and 2024 and benefiting revenue. However, high inflation and rising interest rates have recently raised costs and curtailed demand, with some businesses opting for cheaper alternatives like templates rather than custom web design. In response to shifting client expectations, web designers now prioritize mobile-first design, rapid performance, personalization and interactive content. These adaptations, along with investments in new technologies, have allowed web designers—especially smaller ones—to differentiate themselves and sustain long-term growth. Overall, revenue for web design services companies has swelled at a CAGR of 2.3% over the past five years, reaching $47.4 billion in 2025. This includes a 1.5% rise in revenue in that year. Market saturation will limit revenue growth for website designers moving forward. With nearly all US adults now using the Internet, opportunities for finding new customers are dwindling as internet usage approaches universality. As a result, major providers may turn to mergers and acquisitions to maintain market share, while smaller companies will likely focus on niche markets or specific geographies to secure stable income. Additionally, tariffs imposed by the Trump administration could further restrain demand by increasing consumer prices, reducing disposable income and pushing the economy toward recession. In response, web designers may expand geographically to find new clients. Amid these headwinds, AI and automation technologies are transforming design workflows, increasing efficiency while fostering a greater need for skilled workers and enabling more tailored services. Companies are also adapting by prioritizing inclusivity and sustainability, attracting broader demographics and eco-conscious clients. Overall, revenue for web design services providers is forecast to inch upward at a CAGR of 1.1% over the next five years, reaching $49.9 billion in 2030.

In July 2023, the majority of browser web traffic in the Benelux region was generated via mobile phones. However, laptop and desktop devices accounted for over 46 percent of web traffic in the Netherlands. In Belgium, laptops and desktops accounted for approximately 38 percent of web traffic, and similar values were observed in Luxembourg as well.

A redesign of a traditional introductory statistics course was performed with the intent of increasing student success in the course without the extreme burden of implementing a flipped course. A study was then conducted to compare the new format (web-enhanced traditional) to the traditional format taught by the same professor with the same assignments, quizzes, and exams during the same semester. Students selected their own sections of the course to take but were not aware of the different class formats when they enrolled. Students in both course formats were similar demographically, with similar math ACT scores. It was found that students who participated in the web-enhanced traditional course were more successful in completing the course and performed better on course assessments than those students who participated in the traditional introductory statistics course. Supplementary materials for this article are available online.

Progressive Web App Platform Market Outlook

According to our latest research, the global Progressive Web App (PWA) Platform market size reached USD 2.19 billion in 2024, driven by the surging demand for seamless, app-like experiences on the web across multiple industries. The market is projected to grow at a robust CAGR of 13.7% from 2025 to 2033, reaching a forecasted value of USD 6.09 billion by 2033. The primary growth factor fueling this expansion is the accelerated digital transformation initiatives across sectors, as businesses seek to enhance customer engagement and optimize operational efficiency with reliable, high-performing web applications.

One of the most significant growth drivers in the Progressive Web App (PWA) Platform market is the increasing adoption of mobile devices and the corresponding demand for responsive, fast-loading web applications. PWAs combine the best features of native apps and traditional websites, delivering offline capabilities, push notifications, and home screen access without the need for app store downloads. This convergence of functionality is particularly attractive to enterprises aiming to reduce development costs and time-to-market, while simultaneously enhancing user engagement and retention. As organizations across retail, media, travel, and BFSI sectors prioritize omnichannel strategies, the adoption of PWA platforms is expected to proliferate, further propelling market growth.

Another key factor contributing to the marketÂ’s expansion is the rising necessity for cost-effective and scalable solutions, especially among small and medium enterprises (SMEs). Traditional native app development often requires significant investment in separate codebases for different operating systems, ongoing maintenance, and compliance with app store regulations. PWAs, on the other hand, offer a unified solution that can be deployed across various devices and platforms, significantly reducing development and operational costs. The flexibility and scalability of PWA platforms empower businesses to respond rapidly to changing market demands, introduce new features seamlessly, and reach a broader audience without the friction of app downloads, which is particularly critical in emerging markets with bandwidth constraints.

The evolving regulatory landscape and heightened emphasis on digital accessibility are also shaping the PWA platform market. Governments and industry bodies worldwide are mandating higher standards for web accessibility, data privacy, and security. PWAs are inherently designed to be accessible, responsive, and secure, aligning well with these regulatory requirements. Moreover, advancements in browser technologies and the growing ecosystem of PWA development tools and frameworks are lowering the technical barriers for enterprises to adopt this technology. This synergy between regulatory compliance, technological innovation, and user-centric design is expected to sustain the momentum of the PWA platform market over the forecast period.

Regionally, North America currently commands the largest share of the PWA platform market, owing to its advanced digital infrastructure, high smartphone penetration, and early adoption of emerging technologies by enterprises. However, Asia Pacific is anticipated to exhibit the fastest growth rate during the forecast period, driven by the rapid expansion of e-commerce, increasing internet penetration, and a burgeoning startup ecosystem. Europe also holds a significant market position, supported by strong regulatory frameworks and a focus on digital innovation. Meanwhile, Latin America and the Middle East & Africa are witnessing steady growth as enterprises in these regions embrace digital transformation to tap into new customer segments and streamline operations.

The integration of innovative tools like the Pager App is becoming increasingly relevant in the PWA ecosystem. As businesses seek to enhance their communication strategies, the Pager App offers a streamlined approach to managing alerts and notifications across various platforms. This tool is particularly beneficial for enterprises that require real-time updates and efficient communication channels, ensuring that critical information is delivered promptly to the right stakeholders. The Pager App's ability to integrate seamlessly with PWA platforms further enhances its utility, providi

The Web Portal Operation industry is highly concentrated, with three companies controlling almost the entire industry; the largest company in the industry, Alphabet Inc, has a market share greater than 90% in 2025. This market concentration has fostered significant advertising revenue but made it exceedingly difficult for smaller web portals to survive. Yet, the presence of local champions like Yandex in Russia and Seznam in the Czech Republic demonstrates that regional portals can find niches, particularly where differentiated content or national digital policies shape market dynamics. Search engines generate most, if not all, of their revenue from advertising. Technological growth has led to more households being connected to the internet and a boom in e-commerce has made the industry increasingly innovative. Over the past decade, a boost in the percentage of households with internet access across Europe has supported revenue expansion, while strengthening technological integration with daily life has boosted demand for web portals. Industry revenue is expected to swell at a compound annual rate of 17.4% over the five years through 2025, including growth of 15% in 2025, to reach €74.9 billion. While profit is high, it is projected to dip amid hiking operational pressures, changing advertising dynamics and heightened regulatory compliance costs. A greater proportion of transactions being carried out online has driven innovation in targeted digital advertising, with declines in rival advertising formats like print media and television expanding the focus on digital marketing as a core strategy. Market leaders have maintained dominance via exclusive agreements, like Google’s multi-billion-euro deals to remain the default search engine on Apple and Android devices, embedding themselves deeper into users’ daily digital interactions. At the same time, the rise of privacy-first search engines like DuckDuckGo, Ecosia and Qwant reflects shifting consumer attitudes toward data privacy and environmental impact. However, Google's status as the default search provider on most mainstream platforms, coupled with robust integration through Chrome and Google's broader ecosystem, has significantly constrained market entry for competitors, perpetuating the industry’s concentration. The rise of the mobile advertising market and the proliferation of mobile devices mean there are plenty of opportunities for search engines, which are expected to capitalise on these trends further moving forward. Smartphones could disrupt the industry's status quo, as the rising popularity of devices that don’t use Google as the default engine benefits other web portals. Technological advancements that incorporate user data are likely to make it easier to tailor advertisements and develop new ways of using consumer data. Initiatives like the European Search Perspective (EUSP) joint venture between Ecosia and Qwant signal the beginnings of intensified competition, especially around privacy and regional digital sovereignty. Nonetheless, industry growth is set to continue, fuelled by surging demand for localised, targeted digital advertising and heightened investment in mobile marketing. Industry revenue is forecast to jump at a compound annual rate of 20.4% over the five years through 2030 to reach €189.7 billion.

This web map features a detailed vector reference layer for the world that is overlaid on World Imagery. The web map is similar in content and style to the popular Imagery with Labels map, which uses layers with raster fused map cache. This map includes a vector tile layer that provides unique capabilities for customization and high-resolution display. This reference map uses a vector tile layer that includes highways, major roads, minor roads, railways, water features, cities, parks, landmarks, and administrative boundaries. This map is built using the same data sources used for other Esri basemaps. The World Imagery layer in this map provides one meter or better satellite and aerial imagery in many parts of the world and lower resolution satellite imagery worldwide.Use this Map This map is designed to be used as a basemap for overlaying other layers of information or as a stand-alone reference map. You can add layers to this web map and save as your own map. If you like, you can add this web map to a custom basemap gallery for others in your organization to use in creating web maps. If you would like to add this map as a layer in other maps you are creating, you may use the tile layer item referenced in this map. Customize this Map Because this map includes a vector tile layer, you can customize the map to change its content and symbology. You are able to turn on and off layers, change symbols for layers, switch to alternate local language (in some areas), and refine the treatment of disputed boundaries. See the Vector Basemap group for other vector web maps. For details on how to customize this map, please refer to these articles on the ArcGIS Online Blog.

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Offshore of Santa Cruz map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery seafloor-sediment and rock samplesdigital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Offshore of Santa Cruz map area data layers. Data layers are symbolized as shown on the associated map sheets.

About this dataset

Context

The dataset tabulates the Webb City population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Webb City across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2022, the population of Webb City was 60, a 1.69% increase year-by-year from 2021. Previously, in 2021, Webb City population was 59, a decline of 0.00% compared to a population of 59 in 2020. Over the last 20 plus years, between 2000 and 2022, population of Webb City decreased by 35. In this period, the peak population was 96 in the year 2002. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2022

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2022)
• Population: The population for the specific year for the Webb City is shown in this column.
• Year on Year Change: This column displays the change in Webb City population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Webb City Population by Year. You can refer the same here

The PATH Study was launched in 2011 to inform the Food and Drug Administration's regulatory activities under the Family Smoking Prevention and Tobacco Control Act (TCA). The PATH Study is a collaboration between the National Institute on Drug Abuse (NIDA), National Institutes of Health (NIH), and the Center for Tobacco Products (CTP), Food and Drug Administration (FDA). The study sampled over 150,000 mailing addresses across the United States to create a national sample of people who do and do not use tobacco. 45,971 adults and youth constitute the first (baseline) wave, Wave 1, of data collected by this longitudinal cohort study. These 45,971 adults and youth along with 7,207 "shadow youth" (youth ages 9 to 11 sampled at Wave 1) make up the 53,178 participants that constitute the Wave 1 Cohort. Respondents are asked to complete an interview at each follow-up wave. Youth who turn 18 by the current wave of data collection are considered "aged-up adults" and are invited to complete the Adult Interview. Additionally, "shadow youth" are considered "aged-up youth" upon turning 12 years old, when they are asked to complete an interview after parental consent. At Wave 4, a probability sample of 14,098 adults, youth, and shadow youth ages 10 to 11 was selected from the civilian, noninstitutionalized population (CNP) at the time of Wave 4. This sample was recruited from residential addresses not selected for Wave 1 in the same sampled Primary Sampling Units (PSUs) and segments using similar within-household sampling procedures. This "replenishment sample" was combined for estimation and analysis purposes with Wave 4 adult and youth respondents from the Wave 1 Cohort who were in the CNP at the time of Wave 4. This combined set of Wave 4 participants, 52,731 participants in total, forms the Wave 4 Cohort.At Wave 7, a probability sample of 14,863 adults, youth, and shadow youth ages 9 to 11 was selected from the CNP at the time of Wave 7. This sample was recruited from residential addresses not selected for Wave 1 or Wave 4 in the same sampled PSUs and segments using similar within-household sampling procedures. This "second replenishment sample" was combined for estimation and analysis purposes with the Wave 7 adult and youth respondents from the Wave 4 Cohorts who were at least age 15 and in the CNP at the time of Wave 7. This combined set of Wave 7 participants, 46,169 participants in total, forms the Wave 7 Cohort.Please refer to the Public-Use Files User Guide that provides further details about children designated as "shadow youth" and the formation of the Wave 1, Wave 4, and Wave 7 Cohorts. Wave 4.5 was a special data collection for youth only who were aged 12 to 17 at the time of the Wave 4.5 interview. Wave 4.5 was the fourth annual follow-up wave for those who were members of the Wave 1 Cohort. For those who were sampled at Wave 4, Wave 4.5 was the first annual follow-up wave.Wave 5.5, conducted in 2020, was a special data collection for Wave 4 Cohort youth and young adults ages 13 to 19 at the time of the Wave 5.5 interview. Also in 2020, a subsample of Wave 4 Cohort adults ages 20 and older were interviewed via the PATH Study Adult Telephone Survey (PATH-ATS).Wave 7.5 was a special collection for Wave 4 and Wave 7 Cohort youth and young adults ages 12 to 22 at the time of the Wave 7.5 interview. For those who were sampled at Wave 7, Wave 7.5 was the first annual follow-up wave. Dataset 1002 (DS1002) contains the data from the Wave 4.5 Youth and Parent Questionnaire. This file contains 1,395 variables and 13,131 cases. Of these cases, 11,378 are continuing youth having completed a prior Youth Interview. The other 1,753 cases are "aged-up youth" having previously been sampled as "shadow youth." Datasets 1112, 1212, and 1222, (DS1112, DS1212, and DS1222) are data files comprising the weight variables for Wave 4.5. The "all-waves" weight file contains weights for participants in the Wave 1 Cohort who completed a Wave 4.5 Youth Interview and completed interviews (if old enough to do so) or verified their information with the study (if not old enough to be interviewed) in Waves 1, 2, 3, and 4. There are two separate files with "single wave" weights: one for the Wave 1 Cohort and one for the Wave 4 Cohort. The "single-wave" weight file for the Wave 1 Cohort contains weights for youth who completed an interview in Wave 1 an

About this dataset

Context

The dataset presents the distribution of median household income among distinct age brackets of householders in Webb town. Based on the latest 2019-2023 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Webb town. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.

Key observations: Insights from 2023

In terms of income distribution across age cohorts, in Webb town, the median household income stands at $110,179 for householders within the 45 to 64 years age group, followed by $109,447 for the 25 to 44 years age group. Notably, householders within the 65 years and over age group, had the lowest median household income at $69,531.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Age groups classifications include:

• Under 25 years
• 25 to 44 years
• 45 to 64 years
• 65 years and over

Variables / Data Columns

• Age Of The Head Of Household: This column presents the age of the head of household
• Median Household Income: Median household income, in 2023 inflation-adjusted dollars for the specific age group

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Webb town median household income by age. You can refer the same here

PO.DAAC provides several ways to discover and access physical oceanography data, from the PO.DAAC Web Portal to FTP access to front-end user interfaces (see http://podaac.jpl.nasa.gov). That same data can also be discovered and accessed through PO.DAAC Web Services, enabling efficient machine-to-machine communication and data transfers.

Web Offset Printing Press Market Outlook

The global web offset printing press market size was valued at approximately USD 6.8 billion in 2023 and is expected to reach around USD 9.2 billion by 2032, registering a compound annual growth rate (CAGR) of 3.4% during the forecast period. This market growth is driven by increasing demand for high-volume printing, advancements in printing technology, and the expanding advertising industry.

One of the primary growth factors for the web offset printing press market is the consistent demand for high-volume, high-quality printing solutions. Web offset printing presses are renowned for their efficiency and ability to produce large runs of high-quality prints in a relatively short period. This makes them particularly appealing for applications such as newspapers, magazines, and advertising materials, which require quick turnaround times and consistent print quality. Additionally, the ongoing technological advancements in web offset printing presses, such as automated plate changing and enhanced ink control, are significantly boosting productivity and reducing waste, thereby driving market growth.

Another critical driver is the expansion of the advertising industry. Despite the digital shift, print media continues to play a significant role in advertising strategies worldwide. Print ads are perceived as more trustworthy and engaging, leading to sustained demand for printed advertising materials like brochures, flyers, and posters. This demand bolsters the need for efficient printing solutions provided by web offset presses. Furthermore, the versatility of these machines allows for a range of applications, from newspapers and magazines to packaging, which continues to support market growth.

Moreover, the rising demand for eco-friendly printing solutions is fueling innovation within the web offset printing press market. Manufacturers are increasingly focusing on developing presses that consume less energy, reduce waste, and use environmentally friendly inks. These advancements not only meet the regulatory standards but also appeal to environmentally conscious consumers and businesses. This shift towards sustainable practices is expected to create new growth avenues for the market.

Regionally, the market is expected to witness varied growth patterns. North America and Europe, being early adopters of advanced printing technologies, are likely to maintain a steady growth rate. However, the Asia Pacific region is expected to exhibit the highest growth rate, driven by the increasing industrialization, rising disposable incomes, and the expanding media and advertising sectors in countries like China and India. Latin America and the Middle East & Africa are also anticipated to witness moderate growth due to the steady demand for print media in these regions.

In addition to these advancements, the role of Post-press Equipment in the printing industry cannot be understated. Post-press operations, which include cutting, folding, binding, and finishing, are crucial for ensuring the final product meets the desired quality standards. As the demand for high-quality printed materials grows, so does the need for efficient and precise post-press equipment. These machines not only enhance the aesthetic appeal of printed materials but also improve their durability and functionality. The integration of advanced post-press equipment with web offset printing presses allows for seamless production processes, reducing turnaround times and increasing overall productivity. This synergy is particularly beneficial for commercial printers who need to deliver large volumes of high-quality prints swiftly.

Product Type Analysis

The web offset printing press market is segmented by product type into Coldset Web Offset Printing Press and Heatset Web Offset Printing Press. Coldset web offset printing presses are primarily used for printing newspapers, magazines, and other periodicals due to their cost-effectiveness and high efficiency. These presses use uncoated paper and dry the ink through absorption and evaporation. Coldset presses are particularly popular in regions with high newspaper circulation, providing a steady demand for this product segment.

On the other hand, Heatset web offset printing presses employ heat to dry the ink, allowing for the use of coated paper and resulting in higher-quality prints. This makes them suitable for printing high-end magazines, catalogs, and advertising materials

The following published OGC compliant WMTS services facilitate access to live geospatial data from the City of Toronto. All WMTS services are in Web Mercator projection. Orthorectified Aerial Imagery The following dataset provides access to the most current geometrically corrected (orthorectified) aerial photography for the City of Toronto. Previous year Orthoimagery is available through the links provided below. Historic Aerial Imagery These datasets are all sourced from scans of the original black and white aerial photography. These images have not gone through the same rigorous process that current aerial imagery goes through to create a seamless orthorectified image, corrected for the changes in elevation across the City. Due to this, the spatial accuracy of these datasets varies across the City. Be aware that there are known issues with some regions of data due to issues with the source data. These datasets intended use is to show land use changes over time and other similar tasks. It is not suitable for sub-metre level accuracy feature collection and is provided “as-is”. Aerial LiDAR - Hillshade A hillshade is a hypothetical illumination of a surface by determining illumination values for each cell in a raster. It is calculated by setting a position for a hypothetical light source and calculating the illumination values of each cell in relation to neighboring cells. It can be used to greatly enhance the visualization of a surface for analysis or graphical display, especially when using transparency. The City of Toronto publishes hillshades in both bare earth (no above-ground features included), and full-feature. Bare Earth Full Feature

Evaluating Decadal Changes in Groundwater Quality: Groundwater-quality data were collected from 5,000 wells between 1988-2001 (first decadal sampling event) by the National Water-Quality Assessment Project. Samples are collected in groups of 20-30 wells with similar characteristics called networks. About 1,500 of these wells in 67 networks were sampled again approximately 10 years later between 2002-2012 (second sampling event) to evaluate decadal changes in groundwater quality. Between 2012 and 2022 (third sampling event), a subset of these networks were sampled again, allowing additional results to be displayed on the web page: Decadal changes in groundwater quality (https://nawqatrends.wim.usgs.gov/decadal/). This is the seventh iteration of data added to the website. With the additional data, it is possible to evaluate changes in water quality between the 2nd and 3rd sampling events for 76 networks, changes in water quality between the 1st and 3rd sampling events for 63 networ ...

A study released in June 2025 that looked at about 82,000 websites found that Google was responsible for almost ** percent of the traffic generated to these domains. Direct traffic corresponded to around **** percent of the investigated websites' traffic volume. While traditional search engines like Bing and social networks like Facebook represented larger shares, ChatGPT overtook Reddit and LinkedIn with a slightly larger share, indicating an increase in traffic from these platforms.

Web Tension Controller Market Outlook

According to our latest research, the global web tension controller market size reached USD 1.36 billion in 2024, fueled by the rapid adoption of automation in manufacturing and processing industries. The market is expected to expand at a robust CAGR of 5.7% during the forecast period, reaching a projected value of USD 2.14 billion by 2033. The primary growth factor driving this market is the rising demand for precise tension control in various industrial processes, which ensures product quality, reduces material wastage, and enhances operational efficiency.

The growth of the web tension controller market is largely attributed to the increasing integration of advanced automation systems across diverse industries such as printing, packaging, textiles, and metals. As manufacturers strive for higher throughput, reduced downtime, and consistent product quality, the demand for sophisticated web tension controllers has surged. These controllers play a pivotal role in maintaining optimal tension in web materials, which is critical for processes involving continuous rolls of materials like paper, plastic, fabric, or metal. The evolution of Industry 4.0 and the proliferation of smart factories have further amplified the need for intelligent tension control solutions, driving investments in both hardware and software innovations within this market.

Another significant driver is the expansion of end-use industries, particularly in emerging economies. The growth of sectors like packaging and textiles in Asia Pacific, coupled with the rising adoption of automation in North America and Europe, has created a fertile ground for web tension controller manufacturers. Additionally, the push towards sustainability and waste reduction has encouraged industries to invest in precision control systems, minimizing material loss and energy consumption. The ongoing shift towards lightweight and flexible packaging materials, especially in the food and beverage and pharmaceutical sectors, has also necessitated the deployment of advanced web tension controllers to manage the unique handling requirements of these materials.

Technological advancements are reshaping the web tension controller market landscape. The integration of IoT, AI, and machine learning in tension control systems has enabled real-time monitoring, predictive maintenance, and remote diagnostics, significantly improving operational reliability and reducing unplanned downtimes. The development of user-friendly interfaces and the ability to seamlessly integrate with existing production lines have further enhanced the adoption rate of these controllers. As manufacturers increasingly prioritize digital transformation and data-driven decision-making, web tension controllers equipped with advanced connectivity and analytics capabilities are becoming essential tools for optimizing production efficiency and ensuring consistent product quality.

In the realm of web tension control, the role of a Web Guiding Sensor is indispensable. These sensors are pivotal in ensuring the precise alignment of web materials during processing, which is crucial for maintaining product quality and operational efficiency. By detecting the edge position of the material, Web Guiding Sensors provide real-time feedback to the control system, enabling automatic adjustments to correct any deviations. This not only enhances the accuracy of the tension control system but also minimizes material wastage and reduces the likelihood of defects. As industries continue to push for higher precision and automation, the integration of advanced Web Guiding Sensors becomes increasingly vital, supporting the seamless operation of sophisticated web tension controllers.

From a regional perspective, Asia Pacific remains the dominant market, accounting for over 42% of the global revenue in 2024, driven by the rapid industrialization of countries like China, India, and Southeast Asian nations. North America and Europe follow closely, benefiting from early adoption of automation technologies and a strong presence of established manufacturing sectors. Latin America and the Middle East & Africa are emerging as promising markets, fueled by growing investments in infrastructure and manufacturing capabilities. As global supply chains continue to evolve and industries seek to en

WELDUSSE.015 was decommissioned on December 2, 2019. Users are encouraged to use the improved monthly Global Web-Enabled Landsat Data (GWELD) Version 3, 3.1, and 3.2 datasets.NASA’s Web-Enabled Landsat Data (WELD) are generated from composited 30 meter (m) Landsat Enhanced Thematic Mapper Plus (ETM+) mosaics of the United States and Alaska from 2002 to 2012. The mosaics provide consistent data to derive land cover, geophysical, and biophysical products for regional assessments of surface dynamics for effective study of Earth system function. The Conterminous (CONUS) United States Seasonal (WELDUSSE) product include Top of Atmosphere (TOA) Reflectance and Brightness Temperature, along with the Normalized Difference Vegetation Index (NDVI) generated from Band 3 and Band 4 TOA Reflectance. WELDUSSE is distributed in Hierarchical Data Format 4 (HDF4).In the WELDUSSE products, seasons are defined as follows: Winter: December, January, February Spring: March, April, May Summer: June, July, August Autumn: September, October, NovemberThe WELD project is funded by the National Aeronautics and Space Administration (NASA) and is a collaboration between the United States Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center and the South Dakota State University (SDSU) Geospatial Sciences Center of Excellence (GSCE). Known Issues WELD Version 1.5 known issues can be found in the WELD Version 1.5 User Guide.Improvements/Changes from Previous Version Version 1.5 is the original version.

Context

I'm going straight to the point: I'm obsessed with Steven Wilson. I can't help it, I love his music. And I need more music with similar (almost identical) style. So, what I'm trying to solve here is, how to find songs that match SW's style with almost zero error?

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I'm aware that Spotify gives you recommendations, like similar artists and such. But that's not enough -- Spotify always gives you varied music. Progressive rock is a very broad genre, and I just want those songs that sound very, very similar to Steven Wilson or Porcupine Tree.

BTW, Porcupine Tree was Steven Wilson's band, and they both sound practically the same. I made an analysis where I checked their musical similarities.

Content

I'm using the Spotify web API to get the data. They have an amazingly rich amount of information, especially the audio features.

This repository has 5 datasets:

• StevenWilson.csv: contains Steven Wilson discography (65 songs)
• PorcupineTree.csv: 65 Porcupine Tree songs
• Complete Steven Wilson.csv: a merge between the past two datasets (Steven Wilson + Porcupine Tree)
• Train.csv: 200 songs used to train KNN. 100 are Steven Wilson songs and the rest are totally different songs
• Test.csv: 100 songs that may or may not be like Steven Wilson's. I picked this songs from various prog rock playlists and my Discover Weekly from Spotify.

Also, so far I've made two kernels:

• Comparing Steven Wilson and Porcupine Tree
• Finding songs that match SW's style using K-Nearest Neighbors

Data

There are 21 columns in the datasets.

Numerical: this columns were scraped using get_audio_features from the Spotify API.

• acousticness: a confidence measure from 0.0 to 1.0 of whether the track is acoustic; 1.0 represents high confidence the track is acoustic
• danceability: it describes how suitable a track is for dancing; a value of 0.0 is least danceable and 1.0 is most danceable
• duration_ms: the duration of the track in milliseconds
• energy: a measure from 0.0 to 1.0 and represents a perceptual measure of intensity and activity
• instrumentalness: predicts whether a track contains no vocals; values above 0.5 are intended to represent instrumental tracks, but confidence is higher as the value approaches 1.0
• liveness: detects the presence of an audience in the recording; 1.0 represents high confidence that the track was performed live
• loudness: the overall loudness of a track in decibels (dB)
• speechiness: detects the presence of spoken words in a track; the more exclusively speech-like the recording (e.g. talk show), the closer to 1.0 the attribute value
• tempo: the overall estimated tempo of a track in beats per minute (BPM)
• valence: a measure from 0.0 to 1.0 describing the musical positiveness; tracks with high valence sound more positive (e.g. happy, cheerful, euphoric), while tracks with low valence sound more negative (e.g. sad, depressed, angry)

Categorical: these features are categories represented as numbers.

• key: the musical key the track is in. e.g. 0 = C, 1 = C♯/D♭, 2 = D, and so on
• mode: mode indicates the modality (major or minor); major is represented by 1 and minor is 0
• time_signature: an estimated overall time signature of a track; it is a notational convention to specify how many beats are in each bar (or measure). e.g. 4/4, 4/3, 3/4, 8/4 etc.

Strings: these fields are mostly useless (except for name, album, artist and lyrics)

• id: the Spotify ID of the song
• name: name of the song
• album: album of the song
• artist: artist of the song
• uri: the Spotify URI of the song
• type: the type of the Spotify object
• track_href: the Spotify API link of the song
• analysis_url: the URL used for getting the audio features
• lyrics: lyrics of the song in lower case

Future

Ever been obsessed with a song? an album? an artist? I'm planning on building a web app that solves this. It will help you find music extremely similar to other.

This web map provides a detailed vector basemap for the world symbolized with a custom navigation map style that is designed for use during the day in mobile devices. The web map includes a vector tile layer that is similar in content to the popular World Street Map, which is delivered as a map service with raster fused map cache. This layer is delivered as a vector tile service that provides unique capabilities for customization, high-resolution display, and offline use in mobile devices. This vector tile layer is built using the same data sources used for the World Street Map and other Esri basemaps. The comprehensive street map includes highways, major roads, minor roads, railways, water features, cities, parks, landmarks, building footprints, and administrative boundaries. Alignment of boundaries is a presentation of the feature provided by our data vendors and does not imply endorsement by Esri or any governing authority.Use this MapThis map is designed to be used as a basemap for overlaying other layers of information or as a stand-alone reference map. You can add layers to this web map and save as your own map. If you like, you can add this web map to a custom basemap gallery for others in your organization to use in creating web maps. If you would like to add this map as a layer in other maps you are creating, you may use the tile layer item referenced in this map.Customize this MapBecause this map includes a vector tile layer, you can customize the map to change its content and symbology. You are able to turn on and off layers, change symbols for layers, switch to alternate local language (in some areas), and refine the treatment of disputed boundaries. See the Vector Basemap group for other vector web maps. For details on how to customize this map, please refer to these articles on the ArcGIS Online Blog.

About this dataset

Context

The dataset tabulates the Webb City population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Webb City. The dataset can be utilized to understand the population distribution of Webb City by age. For example, using this dataset, we can identify the largest age group in Webb City.

Key observations

The largest age group in Webb City, MO was for the group of age 5 to 9 years years with a population of 1,250 (9.51%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Webb City, MO was the 80 to 84 years years with a population of 255 (1.94%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Webb City is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Webb City total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Webb City Population by Age. You can refer the same here