The Hansen Global Forest Change version 1.7 datasets generated during and/or analysed during the current study are available in the earth engine partner’s website repository http://earthenginepartners.appspot.com/science-2013-global-forest. The datasets were developed by Hansen et al. (2013) in their paper "High-resolution global maps of 21st-century forest cover change". Science, 342 (6160), 850-853. https://doi.org/10.1126/science.1244693

The census of population in the Philippines, including the project populations, used in this study can be retrieved from the Philippine Statistics Authority (PSA) website https://psa.gov.ph/statistics/census/projected-population

The datasets were processed using an open source GIS software (QGIS version 3.16 Hannover) which can be downloaded from the QGIS website https://www.qgis.org/en/site/.

Abstract

The 2022 Philippines National Demographic and Health Survey (NDHS) was implemented by the Philippine Statistics Authority (PSA). Data collection took place from May 2 to June 22, 2022.

The primary objective of the 2022 NDHS is to provide up-to-date estimates of basic demographic and health indicators. Specifically, the NDHS collected information on fertility, fertility preferences, family planning practices, childhood mortality, maternal and child health, nutrition, knowledge and attitudes regarding HIV/AIDS, violence against women, child discipline, early childhood development, and other health issues.

The information collected through the NDHS is intended to assist policymakers and program managers in designing and evaluating programs and strategies for improving the health of the country’s population. The 2022 NDHS also provides indicators anchored to the attainment of the Sustainable Development Goals (SDGs) and the new Philippine Development Plan for 2023 to 2028.

Geographic coverage

National coverage

Analysis unit

• Household
• Individual
• Children age 0-5
• Woman age 15-49

Universe

The survey covered all de jure household members (usual residents), all women aged 15-49, and all children aged 0-4 resident in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling scheme provides data representative of the country as a whole, for urban and rural areas separately, and for each of the country’s administrative regions. The sample selection methodology for the 2022 NDHS was based on a two-stage stratified sample design using the Master Sample Frame (MSF) designed and compiled by the PSA. The MSF was constructed based on the listing of households from the 2010 Census of Population and Housing and updated based on the listing of households from the 2015 Census of Population. The first stage involved a systematic selection of 1,247 primary sampling units (PSUs) distributed by province or HUC. A PSU can be a barangay, a portion of a large barangay, or two or more adjacent small barangays.

In the second stage, an equal take of either 22 or 29 sample housing units were selected from each sampled PSU using systematic random sampling. In situations where a housing unit contained one to three households, all households were interviewed. In the rare situation where a housing unit contained more than three households, no more than three households were interviewed. The survey interviewers were instructed to interview only the preselected housing units. No replacements and no changes of the preselected housing units were allowed in the implementing stage in order to prevent bias. Survey weights were calculated, added to the data file, and applied so that weighted results are representative estimates of indicators at the regional and national levels.

All women age 15–49 who were either usual residents of the selected households or visitors who stayed in the households the night before the survey were eligible to be interviewed. Among women eligible for an individual interview, one woman per household was selected for a module on women’s safety.

For further details on sample design, see APPENDIX A of the final report.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Two questionnaires were used for the 2022 NDHS: the Household Questionnaire and the Woman’s Questionnaire. The questionnaires, based on The DHS Program’s model questionnaires, were adapted to reflect the population and health issues relevant to the Philippines. Input was solicited from various stakeholders representing government agencies, academe, and international agencies. The survey protocol was reviewed by the ICF Institutional Review Board.

After all questionnaires were finalized in English, they were translated into six major languages: Tagalog, Cebuano, Ilocano, Bikol, Hiligaynon, and Waray. The Household and Woman’s Questionnaires were programmed into tablet computers to allow for computer-assisted personal interviewing (CAPI) for data collection purposes, with the capability to choose any of the languages for each questionnaire.

Cleaning operations

Processing the 2022 NDHS data began almost as soon as fieldwork started, and data security procedures were in place in accordance with confidentiality of information as provided by Philippine laws. As data collection was completed in each PSU or cluster, all electronic data files were transferred securely via SyncCloud to a server maintained by the PSA Central Office in Quezon City. These data files were registered and checked for inconsistencies, incompleteness, and outliers. The field teams were alerted to any inconsistencies and errors while still in the area of assignment. Timely generation of field check tables allowed for effective monitoring of fieldwork, including tracking questionnaire completion rates. Only the field teams, project managers, and NDHS supervisors in the provincial, regional, and central offices were given access to the CAPI system and the SyncCloud server.

A team of secondary editors in the PSA Central Office carried out secondary editing, which involved resolving inconsistencies and recoding “other” responses; the former was conducted during data collection, and the latter was conducted following the completion of the fieldwork. Data editing was performed using the CSPro software package. The secondary editing of the data was completed in August 2022. The final cleaning of the data set was carried out by data processing specialists from The DHS Program in September 2022.

Response rate

A total of 35,470 households were selected for the 2022 NDHS sample, of which 30,621 were found to be occupied. Of the occupied households, 30,372 were successfully interviewed, yielding a response rate of 99%. In the interviewed households, 28,379 women age 15–49 were identified as eligible for individual interviews. Interviews were completed with 27,821 women, yielding a response rate of 98%.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors and (2) sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and in data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2022 Philippines National Demographic and Health Survey (2022 NDHS) to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2022 NDHS is only one of many samples that could have been selected from the same population, using the same design and identical size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

A sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95% of all possible samples of identical size and design.

If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2022 NDHS sample was the result of a multistage stratified design, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed in SAS using programs developed by ICF. These programs use the Taylor linearization method to estimate variances for survey estimates that are means, proportions, or ratios. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

A more detailed description of estimates of sampling errors are presented in APPENDIX B of the survey report.

Data appraisal

Data Quality Tables

• Household age distribution
• Age distribution of eligible and interviewed women
• Age displacement at age 14/15
• Age displacement at age 49/50
• Pregnancy outcomes by years preceding the survey
• Completeness of reporting
• Observation of handwashing facility
• School attendance by single year of age
• Vaccination cards photographed
• Population pyramid
• Five-year mortality rates

See details of the data quality tables in Appendix C of the final report.

City and municipal-level poverty estimates for 2012, 2009, and 2006

2012 City and Municipal-Level Small Area Poverty Estimates

Source: Philippine Statistics Authority, through a national government funded project on the generation of the 2012 small area estimates on poverty
http://www.nscb.gov.ph/announce/2014/PSA-NSCB_2012MunCity_Pov.asp
Note: Region V, Sorsogon, Bacon is in 2006 and 2009 data but not the 2012 data. According to Wikipedia, Sorgoson City was formed by merging the Bacon and Sorsogon towns.

City and Municipal-Level Poverty Estimates; 2006 and 2009

Source: NSCB/World Bank/AusAID Project on the Generation of the 2006 and 2009 City and Municipal Level Poverty Estimates
http://www.nscb.gov.ph/poverty/dataCharts.asp
PDF download
Note: The 2009 city and municipal level poverty estimates for ARMM were revised to reflect on the movement/creation of municipalities and barangays which were not considered in the preliminary estimation of the 2009 city and municipal level poverty estimates published in the NSCB website last 03 August 2013.

Column Header / Description

• Prelim_*year* / Preliminary (indicated by "TRUE" or "FALSE")
• Pov_*year* / Poverty Incidence
• SE_*year* / Standard Error
• CoV_*year* / Coefficient of Variation
• Con_90lower_*year* / 90% Confidence Interval Lower Limit
• Con_90upper_*year* / 90% Confidence Interval Upper Limit

A web map used for the Police Service Area Details web application.In addition to Police Districts, every resident lives in a Police Service Area (PSA), and every PSA has a team of police officers and officials assigned to it. Residents should get to know their PSA team members and learn how to work with them to fight crime and disorder in their neighborhoods. Each police district has between seven and nine PSAs. There are a total of 56 PSAs in the District of Columbia.Printable PDF versions of each district map are available on the district pages. Residents and visitors may also access the PSA Finder to easily locate a PSA and other resources within a geographic area. Just enter an address or place name and click the magnifying glass to search, or just click on the map. The results will provide the geopolitical and public safety information for the address; it will also display a map of the nearest police station(s).Each Police Service Area generally holds meetings once a month. To learn more about the meeting time and location in your PSA, please contact your Community Outreach Coordinator. To reach a coordinator, choose your police district from the list below. The coordinators are included as part of each district's Roster.Visit https://mpdc.dc.gov for more information.

Particle Size Analysis (PSA) data from Rona and Windsock closure area. The area was selected dut to the occurrence of sandy gravels, a biotope for which the scottish MPA project has very little information on within Scottish waters. The Windsock closure area was selected to add understanding to the management of marine protected areas. This was a Scottish Marine Protected Areas (SMPA) site identification survey.

BackgroundProstate-specific antigen (PSA) based screening for early detection of prostate cancer is common although it is associated with both benefits and potential harms (e.g., the risk of overdiagnosis). Evidence-based health information could help individuals make informed decisions about whether to undergo PSA testing or not. This evaluation aimed to determine whether the written health information materials available in Germany provide appropriate information for informed decision-making on PSA based screening.MethodsA list of criteria was developed and used to systematically assess the quality of information on the benefits and harms of prostate cancer screening included in written health information materials. Fourteen information materials identified by information requests and online searches were evaluated independently by two of three reviewers. Consensus was achieved with a third reviewer.ResultsOf the 14 information materials evaluated, 10 (71%) list the ability to reduce the absolute risk of death from prostate cancer as a benefit of PSA testing, 9 (64%) point out the risks of follow-up diagnostics, 13 (93%) describe the risks of the available prostate cancer treatments, and all 14 specify the risk of overdiagnosis. The minority provide numerical data on benefits and risks. Partially mismatched framing was identified in four cases: two information materials report only the relative frequencies of benefits, and two report only the absolute frequencies of harms. Half of the materials encouraged participation using downplaying or frightening language.ConclusionsThe majority of health information materials in Germany describe the benefits and harms of PSA based screening, including overdiagnosis, but often lack adequate balance, neutrality and numbers.

Particle Size Analysis (PSA) data from survey undertaken by Cefas and JNCC in January 2013 at the three Fladen Grounds pMPAs. This was a Scottish Marine Protected Areas (SMPA) site identification survey. The main aims were to confirm the presence of the Priority Marine Features and MPA Search Features recommended for protection within the pMPAs and to gather groundtruth data to compare benthic assemblages between, and within/outside, the sites.

Acrylic Pressure Sensitive Adhesives (PSA) Market Outlook

The global market size for Acrylic Pressure Sensitive Adhesives (PSA) was valued at approximately $9.4 billion in 2023 and is projected to reach around $14.8 billion by 2032, exhibiting a compound annual growth rate (CAGR) of 5.1% during the forecast period. This significant growth is driven by the increasing demand for efficient and versatile adhesive solutions across various industries such as packaging, automotive, and electronics, which are rapidly expanding due to technological advancements and rising consumer demand. The remarkable adhesion properties and versatility of acrylic PSAs make them an ideal choice for applications that require resilience and reliability, further propelling the market forward.

A key growth factor in the Acrylic PSA market is the burgeoning packaging industry, which is expanding due to the rise in e-commerce and the need for sustainable and efficient packaging solutions. Acrylic PSAs are widely used in the packaging industry for their strong bonding capabilities and environmental benefits compared to other adhesive types. As online shopping continues to grow, there is an increasing demand for reliable packaging solutions that ensure the safe delivery of products, thereby boosting the adoption of acrylic PSAs. Additionally, the growing focus on reducing carbon footprints is leading to a shift towards water-based acrylic PSAs, which are environmentally friendly and thus gaining popularity.

The automotive industry also plays a significant role in driving the demand for acrylic PSAs. With the automotive sector emphasizing lightweight and durable components, these adhesives are preferred for their ability to bond dissimilar materials, which is crucial for modern automotive design and manufacturing. The shifting trend towards electric vehicles and the incorporation of advanced electronics in automobiles further heighten the need for high-performance adhesive solutions, propelling the demand for acrylic PSAs. Moreover, the automotive industry's recovery post-pandemic and continued innovation in vehicle design are expected to sustain the demand for these adhesives.

In the electronics sector, the demand for acrylic PSAs is on the rise due to the continuous growth in consumer electronics and smart devices. Acrylic adhesives are crucial in the assembly and protection of electronic components due to their excellent thermal and chemical resistance properties. As the world moves towards more interconnected and smart technological solutions, the requirement for reliable adhesive applications in electronics will only increase. New product innovations and the evolution of high-performance gadgets necessitate adhesives that can withstand various operational environments, thereby enhancing the market growth for acrylic PSAs.

Regionally, the Asia Pacific is expected to dominate the Acrylic PSA market, driven by rapid industrialization, urbanization, and extensive manufacturing activities in countries like China and India. The region's robust automotive, electronics, and packaging sectors are key to this growth, supported by favorable government policies and economic developments. Other regions like North America and Europe are also significant markets due to technological advancements and a strong focus on research and development in adhesive technologies. However, the Middle East & Africa and Latin America show promising potential as emerging markets with increasing industrial activities and infrastructure development.

Type Analysis

The Acrylic Pressure Sensitive Adhesives market can be segmented by type into water-based, solvent-based, and others, each with distinct characteristics and application areas. Water-based acrylic PSAs are gaining traction due to the growing environmental concerns and regulatory pressures to reduce volatile organic compounds (VOCs). These adhesives utilize water as a carrier, making them a safer and more sustainable option compared to their solvent-based counterparts. The shift towards eco-friendly solutions is driving the demand for water-based acrylic PSAs in various industries, including packaging and graphics, where regulatory compliance and sustainable practices are critical considerations. Additionally, technological advancements in water-based adhesive formulations have improved their performance, further enhancing their appeal in the market.

Solvent-based acrylic PSAs, on the other hand, continue to hold a significant share of the market due to their superior adhesion properties and versatility in applications requiring high-performance solution

The Primary Service Area (PSA) dataset utilizes the text-based PSA descriptors to display ambulance service primary service areas as designated by the Minnesota Emergency Medical Services Regulatory Board (EMSRB). The EMS Regulatory Board is the state agency that licenses ambulance services in Minnesota. Each ambulance service is licensed to provide a certain level of care (basic life support, advanced life support or a combination). The level of care is largely dependent on the training level of the personnel. Each ambulance service is licensed to provide care in an assigned PSA which has defined geographic boundaries. In the event of a discrepancy between this information (data and text-based descriptions) and other sources, the text-based descriptor is the final determination of the Board. Any questions or proposed changes to PSA must be submitted to the EMSRB.
Website: https://mn.gov/emsrb
Phone number: (651) 201-2800 or (800) 747-2011

Primary Service Area designations are made in accordance with the provisions of the following Minnesota statutes:
https://www.revisor.mn.gov/statutes/cite/144E.06
https://www.revisor.mn.gov/statutes/cite/144E.07

This dataset is the authoritative source of ambulance service boundaries by Minnesota statute. PDFs of the text-based PSA descriptions are included in the file geodatabase version of this dataset. The shapefile version of this dataset does not include PDF attachments.

Input dataStatic copy of Remote Automated Weather Station (RAWS) locations from National Interagency Fire Center (https://data-nifc.opendata.arcgis.com/datasets/nifc::public-view-interagency-remote-automatic-weather-stations-raws/about), station identifiers and names quality controlled by geographic area lead.Static copy of Predictive Service Area (PSA) boundaries from the National Interagency Fire Center (https://data-nifc.opendata.arcgis.com/datasets/nifc::national-predictive-service-areas-psa-boundaries/about).Tables of key RAWS associated with each PSA and the historical percentiles of Energy Release Component (ERC) and Burning Index (BI). Exact data sources and methods vary by geographic area but generally include 20 years of observations for the full calendar year. All fire danger rating calculations in this service are standardized around fuel model Y (also known as “2016 forest”).Daily observations from the Weather Information Management System (WIMS) accessed at 16:30 Pacific: 1) most recent 3 days of daily observed weather, derived variables, ERC, and BI; and 2) next 3 days of daily forecasted ERC and BIAnalysisThe most recent day of observed and the next forecasted fire danger indices are converted to percentiles based on the historical percentile tables.Trend analysis categories determined by: 1) observed uses most recent daily observation compared to two days prior; 2) forecasted uses current day forecast compared to two days in the future; and 3) increase (>= +3), decrease (<= -3), or no change (< 3 diff) based on difference in absolute ERC or BI values, not percentiles.Aggregation to PSA: 1) non-reporting stations are ignored in calculations; 2) the PSA will be assigned a null value if it has no reporting stations, 3) simple means of RAWS percentiles; and 4) trends determined using simple means of index values from associated RAWS for equivalent time periods and same change thresholds (see above).

PSA GIS data from survey undertaken by Cefas and JNCC in January 2013 at the three Fladen Grounds pMPAs. This was a Scottish Marine Protected Areas (SMPA) site identification survey. The main aims were to confirm the presence of the Priority Marine Features and MPA Search Features recommended for protection within the pMPAs and to gather groundtruth data to compare benthic assemblages between, and within/outside, the sites.

The Professional Services Automation (PSA) market is experiencing robust growth, projected to reach $11.76 billion in 2025 and maintain a Compound Annual Growth Rate (CAGR) of 31.10% from 2025 to 2033. This expansion is driven by several key factors. Increasing demand for improved project management, resource allocation, and billing processes across various industries fuels the adoption of PSA solutions. Businesses are seeking greater efficiency, reduced operational costs, and enhanced client satisfaction, all achievable through automation. The shift towards cloud-based deployments offers scalability and accessibility, further driving market growth. Furthermore, the rising complexity of projects and the need for real-time data insights contribute to the PSA market's expansion. The BFSI (Banking, Financial Services, and Insurance), architecture, engineering, and construction, and legal sectors are leading adopters, showcasing the broad applicability of PSA software. However, the market faces challenges such as high initial investment costs and the need for robust integration with existing systems, potentially hindering adoption among smaller firms. The competitive landscape is dynamic, with numerous established players like Autotask Corporation (Datto Inc.), Mavenlink Inc., and Deltek Inc., alongside emerging innovative companies. The market segmentation reveals a strong preference for cloud-based solutions, reflecting the broader industry trend towards digital transformation. The strong CAGR suggests significant future opportunities, particularly in regions like Asia Pacific where adoption is growing rapidly. Continued innovation in areas such as AI-powered project forecasting and automated reporting will further propel the market forward. However, vendors need to focus on providing user-friendly interfaces and comprehensive training to maximize adoption and ensure long-term success. Future growth will depend on addressing the challenges of data security and integration while catering to the evolving needs of diverse industries. Recent developments include: February 2024: Deltek introduced new time-tracking and professional services automation tools tailored to empower government contractors in optimizing operational efficiency while adhering to regulatory standards. The Replicon Time Tracking for Government Contracting uses artificial intelligence to capture worktime information from various workforce collaboration applications, ensuring precise billing and payroll processing. This tool also provides a consolidated platform featuring compliance libraries for labor laws, robust project time tracking and scheduling capabilities, and secure AI-driven timesheet functionalities., July 2023: Rev.io acquired Tigerpaw, a software firm specializing in comprehensive professional services and business automation solutions for technology providers. Tigerpaw's portfolio includes CRM/PSA Software, Service Automation Management, Inventory Management, Payment Processing, Project Management, Software, Lead Generation, Business Automation, and Professional Services Automation. This strategic move significantly enhances Rev.io's presence in the managed services sector by integrating Tigerpaw's end-to-end PSA system, which covers account management, sales automation, project management, reporting, RMM integration, invoicing, field technical support, inventory tracking, and more. Rev.io is actively working to align Tigerpaw's operations and rebrand its offerings to effectively articulate the company's complete offering to a broader audience., October 2022 - Infor announced that Snellman, the Finnish and Swedish ready-made food and meat processor, will execute Infor's cloud-based enterprise resource planning (ERP) system built on Amazon Web Services (AWS) to sustain their future growth and new business development. According to the company, the advantages of the new CloudSuite system include automated version updates, secure maintenance, scalability of the cloud environment, following composable ERP thinking, and the ease and straightforward ability to add modular extensions as needed., March 2022 - Deltek announced that the company's new Costpoint 8.1 is now available. According to the company. Costpoint 8.1 brings more innovation and intelligence to the project accounting and resource-planning platform. Moreover, it enables automation and digitization of the entire project lifecycle and provides enhanced tracking and visibility into project cost data.. Key drivers for this market are: Growing Trend of Automation and Reduction in the Overall Cost, High Demand from Small and Medium Enterprise. Potential restraints include: Growing Trend of Automation and Reduction in the Overall Cost, High Demand from Small and Medium Enterprise. Notable trends are: BFSI Holds a Dominant Position in Professional Services Automation Market.

This graph presents the distribution of world production of the French group PSA Peugeot Citroën between 2015 and 2018, according to the assembly site. Thus, the site with the highest production in 2018 was at Sochaux in France, with a production volume of more than ******* units.

Abstract

The Republic of the Philippines is making great efforts to develop agriculture at a pace necessary to meet the food requirements of the fast-growing population. It has become necessary to use current agricultural statistics that will help present an accurate picture of the country's food situation. Especially important are the expected supply and consumption requirements of the people, particularly of meat products. The Commercial Livestock and Poultry Survey (CLPS) seeks to provide if but partially, such information.

The CLPS is one of the major regular activities of the Livestock and Poultry Statistics Division (LPSD) under the Economic Sector Statistics Service (ESSS) of the Philippine Statistics Authority (PSA). The CLPS is undertaken to provide an estimate on current inventory and supply and disposition of commercial livestock and poultry farms. The CLPS is done quarterly for swine, broiler, and layer while data collection for carabao, cattle, goat, duck and sheep is likewise conducted semi-annually. The information present here is related to the layer module.

The survey covers all provinces including Dinagat Islands and two (2) chartered cities (Davao City and Zamboanga City). Moreover, a separate structured questionnaire in the collection of the necessary information for each animal type is utilized. Estimates generated from the CLPS and the Backyard Livestock and Poultry Survey (BLPS) are aggregated to come up with the total Livestock and Poultry (L&P) estimates. The data generated was perceived to be useful as guide for the government and the private sector in making plans and decisions with respect to farm production and improvement of the livestock and poultry industry.

The data generated from this survey are disseminated through the country STAT website and featured in the Quarterly Commodity Special Releases and Annual Commodity Situation Reports released every May. The collection of data on this survey is undertaken by hired Statistical Researchers (SRs) while the electronic processing is done by the regular staff in the Provincial Statistical Offices (POs). The SRs are trained prior to field operations to ensure that the procedures and concepts are understood. The training includes mock interviews and dry-run exercises.

Geographic coverage

National Coverage

Analysis unit

Entreprises

Universe

The CLPS covers all livestock and poultry farms with commercial type of operation. Commercial farm refers to a farm or household operated by a farmer/household/operator that raises at least one of the following: 1. Livestock - Carabao (Water Buffaloes), Cattle, Swine and Goat 2. Poultry - Layer, Broiler and Duck

Also, it must satisfy at least one of the following criteria: 1. Livestock · at least 21 heads of adult and zero head of young · at least 41 heads of young animals and above · at least 10 heads of adult and 22 heads of young and above

1. Poultry · at least 500 layers, or 1,000 broilers and above · at least 100 layers and 100 broilers if raised in combination and above · at least 100 head of duck regardless of age

The survey also covers traders such as assemblers and distributors, etc.

Trader refers to a person or entity that buys and sells goods or commodities.

Assembler refers to a type of trader who sources and procures his/her stocks from contract growers or independent farmers in several barangays in a specific municipality, and transports the produce to a trading or market center.

Distributor refers to a trader who sells commodities to other traders and consumers.

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLE SELECTION PROCEDURE The sampling design used for each animal type are the same but are treated independently. The sampling design depends on the total number of commercial farms and the corresponding maximum housing capacities of the farms in the province. In provinces with less than 21 farms, all farms are completely enumerated. However, provinces with a large number of farms or those with 21 or more farms, stratification is applied using the Dalenius-Hodges method of stratification with the maximum housing capacity as stratification variable. The number of strata per province ranges from two (2) to four (4) depending on the heterogeneity or homogeneity of the maximum housing capacity. Sample allocation for each stratum is done using the Neyman procedure with coefficient of variation set at five percent (5%). A minimum of five (5) samples per stratum is allocated. A stratum may have less than 5 samples only if the total number of farms in that stratum is less than 5. Selection of samples from each stratum is done using simple random sampling.

The sample selection procedure is discussed as follows: 1. Rank all farms in ascending order according to their maximum housing capacity; 2. Delineate the stratum boundaries using Dalenius-Hodges method (unique stratum boundaries for each province are derived); 3. Determine the total number of commercial farms per stratum; 4. Allocate sample size for each stratum using Neyman procedure (a five percent (5%) coefficient of variation is assumed and a minimum of five (5) samples are taken when Nh = 5). For stratum with Nh<5, all farms in that stratum shall be enumerated; and 5. Select the required number of sample farms using the simple random sampling method.

For provinces where stratified sampling is employed, in case of non-response, adjustment of expansion factor is implemented by stratum and by animal type using the status of the sample commercial farms.

Comprehensive discussion on the estimation procedure is found in page 10 of the CLPS manual found in Related Materials.

Mode of data collection

Face-to-face paper [f2f]

Cleaning operations

For CLPS, editing is done in two (2) stage. The first stage of editing is done during the data collection. The Statistical Researcher, before leaving the premises of the sample commercial farm, shall do field editing. This activity involves assuring that all data items in the questionnaires are asked and that the answers were written down correctly. The second stage of editing is conducted by the supervisor upon the submission of accomplished questionnaires/forms by the SR called manual editing.

The system used in processing the data collected from this survey was developed by the Systems Development Division (SDD) of PSA. CSPro, the software used in most of the surveys of PSA, is utilized.

Using a pre-formatted template, consolidated estimates are generated through the Provincial Summary Worksheets (PSW-C). This worksheet presents data for each sample commercial farm, raw provincial total data and expanded provincial total estimates.

These estimates are transferred manually into an excel-based validation sheet called the "Supply-Disposition Worksheets" where the PSO, together with the L&P focal person, act as data analysts. To ensure the quality of data, the generated outputs shall undergo data review and validation. Data review involves internal checks of the data collected, consistency and completeness check of data items and detection and correction of identified errors. Data validation, on the other hand, ensures that the estimates generated are truly reflective of the current industry situation. It involves a thorough analysis of the generated estimates using auxiliary information. Auxiliary information includes animal dispersal from government programs, weather condition, price trends, import and export among others. Data review and validation is supported by the Electronic Data Review Workbook (EDRW) Compilation System. This is a tool used in reviewing and validating the L&P statistics and commonly termed as "Supply-Disposition (S-D) Technique".

The outputs of the CLPS together with BLPS undergo three (3) levels of data review and validation. The first stage is at the Provincial level known as the Provincial Data Review (PDR) followed by the second level which takes place at the RSSOs, known as the Regional Data Review (RDR). During the RDR, the RSSOs shall likewise review and validate the outputs of the provinces under its jurisdiction.

The third level of data review and validation and is the final level is conducted at the Central Office. All outputs sent by the RSSOs shall be consolidated by the LPSD commodity specialists to generate the final livestock and poultry statistical tables as input in the preparation of reports.

Response rate

The response rate for the survey ranged from 85-90%.

Data appraisal

To ensure the quality of its statistical services, the PSA has mainstreamed in its statistical system for generating production statistics, a quarterly data review and validation process. This is undertaken at the provincial, regional and national levels to incorporate the impact of events not captured in the survey. The data review process starts at the data collection stage and continues up to the processing and tabulation of results. However, data examination is formalized during the provincial data review since it is at this stage where the data at the province-level is analyzed as a whole. The process involves analyzing the survey data in terms of completeness, consistency among variables, trend and concentration of the data and presence of extreme observations. Correction of spotted errors in the data is done afterwards. The output of the process is a clean data file used in the re-computation of survey estimates. The estimates generated from the clean data set are thoroughly analyzed and validated with auxiliary information to incorporate the impact of information and events not captured by the survey. This

Particle Size Analysis (PSA) analysis data from Bassurelle Sandbanks SCI (CEND 03/13). This survey was carried out at Bassurelle Sandbank SCI on the Cefas Endeavour research vessel to collect additional information (acoustic and ground-truthing data) from the site to increase current knowledge of the distribution and heterogeneity of benthic habitats and communities present, to assist the development of future management advice and plans.

The global market for PSA Nitrogen Generators is experiencing steady growth, projected to reach $369 million in 2025 and maintain a Compound Annual Growth Rate (CAGR) of 2.4% from 2025 to 2033. This growth is fueled by increasing demand across diverse sectors. The food and beverage industry relies heavily on nitrogen for packaging and preservation, driving significant market share. The chemical industry also utilizes substantial quantities for various processes, contributing to this market’s expansion. Furthermore, the rise of on-site nitrogen generation, facilitated by advancements in PSA technology, offers cost-effective alternatives to bulk nitrogen supply, encouraging adoption across various applications. Stationary generators currently dominate the market, reflecting a preference for reliable, continuous nitrogen supply in many industrial settings. However, the mobile generator segment is gaining traction, driven by the need for portable nitrogen solutions in diverse field applications, such as construction and agriculture. While challenges like fluctuating raw material prices and stringent environmental regulations may exert some restraint on growth, the overall market outlook remains positive due to the expanding applications and ongoing technological innovations. Geographical distribution shows a concentration of demand in developed regions like North America and Europe, given the established industrial bases and robust infrastructure in these areas. However, significant growth potential exists in developing economies like those within Asia-Pacific, driven by industrialization and rising investments in infrastructure projects. Key players in the market, including Air Products and Chemicals, Anest Iwata, Atlas Copco, Holtec Gas Systems, Parker Hannifin Corp, and Huilin, are continuously innovating and expanding their product portfolios to cater to this growing demand and maintain a competitive edge. Future growth will likely be shaped by the development of more energy-efficient and compact PSA nitrogen generators, alongside increasing demand from emerging applications and sectors.

The Industrial Pressure Swing Adsorption (PSA) system market is experiencing robust growth, projected to reach a market size of $48.9 million in 2025 and maintain a Compound Annual Growth Rate (CAGR) of 5.7% from 2025 to 2033. This expansion is driven by increasing demand for on-site gas generation in various industries, particularly those requiring high-purity gases like nitrogen, oxygen, and hydrogen. The rising adoption of PSA systems stems from their cost-effectiveness compared to traditional gas supply methods, their energy efficiency, and their ability to provide a reliable and consistent gas supply. Furthermore, technological advancements leading to improved system efficiency and reduced operational costs are further fueling market growth. The single-stage PSA segment currently holds a larger market share due to its lower initial investment costs, but the multi-stage PSA segment is expected to witness faster growth due to its superior gas purity capabilities and suitability for specialized applications. Key players like Air Products, Linde, and Air Liquide are driving innovation and expanding their market presence through strategic partnerships, acquisitions, and technological advancements. Geographic growth is expected to be widespread, with North America and Asia Pacific representing significant markets, driven by industrial growth and government support for cleaner energy technologies. The restraints to market growth are primarily associated with the high initial capital expenditure required for system installation and the need for skilled personnel for operation and maintenance. However, these challenges are being mitigated through financing options, improved training programs, and the emergence of more compact and user-friendly PSA systems. The increasing focus on sustainability across various sectors, along with the stringent environmental regulations promoting cleaner production methods, presents a significant opportunity for PSA system adoption in the coming years. The market segmentation by application (nitrogen, oxygen, hydrogen generation) provides valuable insights for targeted market penetration strategies by manufacturers, with nitrogen generation currently dominating but significant growth potential observed in hydrogen production due to the increasing demand for fuel cell technology and green hydrogen initiatives.

Modular PSA Oxygen Generator Market Outlook

The global Modular PSA Oxygen Generator market size is anticipated to expand significantly from USD 1.2 billion in 2023 to approximately USD 2.7 billion by 2032, reflecting a robust CAGR of 9.3% during the forecast period. This growth can be attributed to the increasing demand for efficient and reliable oxygen supply systems across various sectors such as healthcare, industrial, and aerospace.

The primary growth factor driving the Modular PSA Oxygen Generator market is the rising need for oxygen in the healthcare sector. The COVID-19 pandemic has underscored the importance of adequate oxygen supply in hospitals and clinics worldwide, leading to increased investments in oxygen generation systems. Additionally, the growing prevalence of respiratory diseases, an aging population, and a surge in surgical procedures are contributing significantly to the demand for reliable oxygen sources, thereby boosting the market growth.

Another significant growth driver is the industrial sector, where oxygen is crucial for various applications such as metal cutting, welding, and chemical processing. Industries are increasingly adopting Modular PSA Oxygen Generators due to their cost-effectiveness, efficiency, and ability to produce high-purity oxygen on-site. This eliminates the need for frequent oxygen deliveries and reduces operational costs, further propelling the market's expansion.

The advancements in technology and innovations in PSA (Pressure Swing Adsorption) systems are also playing a crucial role in market growth. Modern Modular PSA Oxygen Generators are designed to be more energy-efficient and reliable, with enhanced automation and control features that make them suitable for a wide range of applications. The integration of IoT and smart monitoring systems allows for real-time tracking and maintenance, ensuring uninterrupted oxygen supply, which is vital for critical applications.

Regionally, North America holds a substantial share of the Modular PSA Oxygen Generator market, supported by well-established healthcare infrastructure and significant industrial activities. Europe follows closely, driven by stringent regulations concerning industrial emissions and a strong emphasis on healthcare improvement. The Asia Pacific region is expected to witness the fastest growth due to rapidly developing healthcare facilities, increasing industrial activities, and supportive government initiatives to enhance healthcare services and infrastructure.

In the healthcare sector, the integration of advanced technologies has led to the development of specialized equipment like the Rail-mounted Oxygen Pressure Regulator. This device plays a crucial role in ensuring precise control over oxygen delivery in medical settings, particularly in hospitals where space optimization and safety are paramount. By being rail-mounted, these regulators offer flexibility and ease of access, allowing healthcare professionals to efficiently manage oxygen flow to patients. The growing demand for such innovative solutions is driven by the need for enhanced patient care and the increasing complexity of medical procedures that require reliable oxygen supply systems.

Product Type Analysis

The Modular PSA Oxygen Generator market is segmented into portable and stationary types. Portable oxygen generators are designed for mobility, making them ideal for use in home healthcare settings and for patients requiring oxygen therapy while on the move. The demand for portable generators has surged due to the increasing prevalence of chronic respiratory diseases and the growing aging population, which often requires continuous oxygen support. Technological advancements in miniaturization and battery life have further enhanced the usability and convenience of portable units.

On the other hand, stationary oxygen generators are predominantly used in hospitals, industrial plants, and other facilities that require a continuous and large supply of oxygen. These systems are typically more robust and capable of producing higher volumes of oxygen compared to portable units. The stationary segment is expected to maintain a significant market share due to the growing demand for large-scale oxygen production in healthcare and industrial sectors. The ability to provide a reliable supply of high-purity oxygen makes stationary generators indispensable in critical settings.

ObjectiveThis study aimed to evaluate the awareness rate of prostate-specific antigen (PSA) among the general public in China and provide data about prostate cancer (PCa) for related scientific research.MethodsA cross-sectional survey of PSA awareness was conducted in multiple regional populations using an online questionnaire. The questionnaire included basic information, knowledge about PCa, the awareness rate and application of PSA, and future expectations toward applying PSA screening in clinical practice. The study applied the methods of Pearson chi-square analysis and Logistic regression analysis.ResultsA total of 493 valid questionnaires were included. Two hundred and nineteen respondents (44.4%) were males, and 274 (55.6%) were females. Of all respondents, 212 (43.0%) were under 20 years old, 147 (29.8%) were 20–30 years old, 74 (15.0%) were 30–40 years old, and 60 (12.2%) were over 40 years old. There are 310 people (62.9%) with medical educational background and 183 (37.1%) without. One hundred eighty-seven (37.9%) of the respondents were aware of PSA, and 306 (62.1%) were unaware of PSA. Statistically significant differences were obtained between the two groups regarding different ages, educational backgrounds, occupations, departments, and habits of knowing medical knowledge (all p < 0.05). In addition, the differences between the group of aware of PSA (AP) and the group unaware of PSA (UAP) in terms of whether they had been exposed to PSA screening and whether they had exposure to PCa patients or related knowledge were also observed (all p < 0.05). Age ≥30 years, medical educational background, understanding of medical knowledge, exposure to PCa patients or related knowledge, exposure to PSA screening, and status as a graduate student and above were independent factors for the occurrence of PSA awareness events (all p < 0.05). In addition, age ≥ 30 years, medical educational background, and awareness of PSA were independent factors for future expectations toward PSA (all p < 0.05).ConclusionsWe first analyzed the public awareness of PSA. Cognition degrees of PSA and PCa awareness vary among different populations in China. Therefore, we should designate corresponding widespread scientific educational programs for different populations to increase the awareness rate of PSA.