Dissolved iron (DFe) concentrations of 40 profile stations and 7 surface stations were measured directly on board by an automated Flow Injection Analysis (FIA) after a modified method of De Jong et al. 1998. In addition, unfiltered samples from 17 profiles and 7 surface stations were acidified and stored to determine the total Fe concentrations in the NIOZ laboratory after 6-12 months of dissolution (see table 1). Filtered (0.2µm) and acidified (pH 1.8) seawater was concentrated on a column containing aminodiacetid acid (IDA). This material binds only transition metals and not the interfering salts. After washing the column with ultra pure water, the column is eluted with diluted acid. After mixing with luminol, peroxide and ammonium, the oxidation of luminol with peroxide is catalyzed by iron and a blue light is produced and detected with a photon counter. The amount of iron is calculated using a standard calibration line, where a known amount of iron is added to low iron containing seawater. Using this calibration line a number of counts per nM iron is obtained. Samples were analyzed in duplicate sample bottles, each of which was measured in triplicate, and average DFe concentrations and standard deviation are given. Concentrations of DFe measured on the NBP0901 cruise ranged from 30 pM up to 0.7 nM. The standard deviation varied between 0% and 10% (the latter being exceptional), but was generally < 5% in samples with DFe concentrations higher than 0.1nM. Since samples containing less than 0.1nM DFe are near the detection limit of the system; the standard deviation of these measurements was sometimes high (<30%).

 The average blank was determined at 0.024nM±0.010nM and was defined as a sample loaded for 10 seconds and measured daily. The average limit of detection, 0.009±0.008 was defined as 3*standard deviation of the mean blank and measured daily. To better understand the day to day variation duplicate sample bottles were measured at least 24h later. The differences between these measurements were rather large, in the order of 5-20%, while the largest differences were measured in samples with low DFe concentrations. To correct for this day to day variation a so-called lab standard sample was measured daily. All data will be corrected for the mean average of this value after the cruise and all data presented so far are uncorrected for this day to day variation. The consistency of the FIA system over the course of the day was verified using a drift standard. The drift was observed to be less than 7% and no corrections have been made for this drift. A certified SAFe standard (Johnson et al. 2007) for the long term consistency and absolute accuracy was measured at a regular basis. 

 Preliminary results
 The profile from station 16 clearly shows high iron input near the PIG (Fig. 5). DFe concentrations are high throughout the entire water column and indicate a constant input of DFe into the polynya. Profile 107, which is in the central Pine Island Polynya, shows much lower values throughout the first 300 meter which can be explained by the high phytoplankton abundance in the surface water. DFe concentrations during a transect from Pine Island Glacier (PIG) (101 S,30W) through the central Pine Island Polynya in north westwards direction clearly show the high DFe concentrations near the PIG and the rapid decrease of the DFe in the polynya, especially in waters shallower than 50m (Fig. 6). Extreme low DFe values in the central polynya correlate with the biological productive area as observed from the fluorometer data and Chl a measurements.

Estimates of annual household income for the four income types for Middle layer Super Output Areas, or local areas, in England and Wales.

The global Drilling Fluid Equipment (DFE) market is experiencing robust growth, driven by increasing oil and gas exploration activities, expanding geothermal energy projects, and the rising demand for water well drilling. While precise market size figures for 2019-2024 aren't provided, assuming a conservative market size of $5 billion in 2025 and a CAGR of, let's say, 6% (a reasonable estimate given industry trends), the market is projected to reach approximately $7.1 billion by 2033. This growth is fueled by technological advancements in DFE, leading to improved efficiency and reduced operational costs. Key segments like pumps, valves, and pressure gauges are expected to contribute significantly to this expansion. The increasing adoption of automation and digitalization in drilling operations further enhances the market outlook. However, challenges such as fluctuating oil prices and stringent environmental regulations could act as restraints on market growth. Regional analysis suggests strong growth potential in Asia-Pacific and the Middle East & Africa regions, driven by substantial investments in energy infrastructure development. North America and Europe, while mature markets, continue to contribute significantly to the overall market size, albeit at a potentially slower growth rate than emerging markets. The competitive landscape is relatively concentrated, with major players like National Oilwell Varco and GN Solids Control holding significant market share. However, the presence of several smaller, specialized companies indicates opportunities for niche players focusing on specific DFE segments or technologies. Further growth will depend on the success of these companies in innovation, especially in environmentally friendly and cost-effective solutions, and successful adaptation to the changing demands of global energy markets. Successful companies will likely adapt to the evolving regulatory landscape and offer equipment that aligns with sustainability goals. This comprehensive report provides an in-depth analysis of the global Drilling Fluid Equipment (DFE) market, projected to be valued at $12 billion in 2024, experiencing a Compound Annual Growth Rate (CAGR) of approximately 6% over the next decade. This detailed study examines market dynamics, key players, technological advancements, and future growth prospects, utilizing meticulous research and data-driven insights to offer strategic recommendations for businesses operating within this sector. The report delves into diverse aspects, including market segmentation, competitive landscape, and regional variations, providing a holistic understanding of the DFE market.

This study assessed the abundance of dissolved iron (DFe) in Iowa’s lakes. The micronutrient iron has been noted to play a crucial role in regulating phytoplankton growth, however most studies have focused on large lakes with persistent phytoplankton blooms that are known to undergo iron limitation, such as Lake Erie. There are few datasets of DFe in lakes, especially those that are smaller and susceptible to phytoplankton blooms. In order to assess the spatial distribution of DFe in lakes throughout Iowa, this study obtained DFe measurements over a suite of recreational lakes over a summer season in 2018. Weekly monitoring of DFe (for 15 weeks) was conducted to assess temporal trends.

Small population statistics giving key characteristics of people in specific small population groups such as individual ethnic groups, or those with a specific country of birth - for local authorities above a disclosure control threshold.

A dataset of all the meta-data for all of the datasets available through the data.gov.uk service. This is provided as a zipped CSV or JSON file. It is published nightly.

Updates: 27 Sep 2017: we've moved all the previous dumps to an S3 bucket at https://dgu-ckan-metadata-dumps.s3-eu-west-1.amazonaws.com/ - This link is now listed here as a data file.

From 13/10/16 we added .v2.jsonl dump, which is set to replace the .json dump (which will be discontinued after a 3 month transition). This is produced using 'ckanapi dump'. It provides an enhanced version of each dataset ('validated', or what you get from package_show in CKAN API v3 - the old json was the unvalidated version). This now includes full details of the organization the dataset is in, rather than just the owner_id. Plus it includes the results of the archival & qa for each dataset and resource, showing whether the link is broken, detected format and stars of openness. It also benefits from being json lines http://jsonlines.org/ format, so you don't need to load the whole thing into memory to parse the json - just a line at a time.

On 12/1/2015 the organizations of the CSV was changed:

• Before this date, each dataset was one line, and resources added as numbered columns. Since a dataset may have up to 300 resources, it ends up with 1025 columns, which is wider than many versions of Excel and Libreoffice will open. And the uncompressed size of 170Mb is more than most will deal with too. It is suggested you load it into a database, ahandle it with a python or ruby script, or use tools such as Refine or Google Fusion Tables.

• After this date, the datasets are provided in one CSV and resources in another. On occasions that you want to join them, you can join them using the (dataset) "Name" column. These are now manageable in spreadsheet software.

You can also use the standard CKAN API if you want to search or get a small section of the data. Please respect the traffic limits in the API: http://data.gov.uk/terms-and-conditions

The global Drilling Fluid Equipment (DFE) market, valued at $1391.1 million in 2025, is projected to experience robust growth, driven by a Compound Annual Growth Rate (CAGR) of 6.3% from 2025 to 2033. This expansion is fueled by the increasing demand for oil and gas exploration and production, coupled with the growing adoption of enhanced oil recovery techniques. The surge in unconventional resource extraction, such as shale gas and tight oil, further stimulates market growth. Technological advancements, including the development of more efficient and environmentally friendly drilling fluids and equipment, are also key drivers. Specific segments like pumps and drilling fluid manifolds are expected to witness higher growth rates compared to others, reflecting the crucial role they play in drilling operations. Geographic expansion, particularly in emerging economies with significant exploration activities, such as those in the Asia-Pacific region (notably China and India), contributes to the market's upward trajectory. However, fluctuating oil prices and stringent environmental regulations pose challenges to market expansion. Despite these constraints, the long-term outlook remains positive, driven by the continuous need for energy resources and technological innovations within the industry. The competitive landscape of the DFE market is characterized by the presence of both established multinational corporations and specialized regional players. National Oilwell Varco, GN Solids Control, and other prominent companies hold significant market shares, leveraging their established brand reputation, technological expertise, and extensive global distribution networks. However, smaller, specialized companies are gaining traction by offering innovative products and solutions catering to niche market segments. The market's future will likely witness increased mergers and acquisitions, further consolidating the industry. Furthermore, the emphasis on sustainability and the development of eco-friendly drilling fluids are shaping product innovation, demanding greater efficiency and reduced environmental impact from DFE manufacturers. This drive towards sustainable solutions is a critical aspect of future market growth, prompting ongoing research and development efforts across the industry.

in 2021, 6.1% of small and medium enterprises (SMEs) with employees and 4.9% of SMEs without employees were 'majority led' by people from an ethnic minority

Monthly dataset showing change in sales and jobs recorded by Xero, an online accounting software platform. This dataset is updated on a quarterly basis. These are official statistics in development. Source: Xero.

Figures for maintained primary, secondary and special schools are as confirmed by Local Authorities as part of the data checking exercise.

Figures for CTCs, academies and non-maintained special schools are as reported by schools and are unconfirmed.

National totals, regional totals and totals across school types have been rounded to the nearest 10.

Includes middle schools as deemed.

The number of permanent exclusions expressed as a percentage of the number (headcount) pupils in Primary, Secondary and Special schools, excluding dually registered pupils in special schools in January 2007.

x less than 5, or a rate based on less than 5.

Figures have been rounded to the nearest 10.

See more on statistics on excluded pupils on the DfE website or read more on permanent and fixed-period exclusions on the DfE website.

Breaking down local authority level annual gross value added (GVA) statistics to lower levels of geography. These are official statistics in development.

Average (median) house prices and sale counts by dwelling type for local authorities, parliamentary constituencies and middle layer super output areas, 1995 to 2014.

This dataset provides a list of the tests undertaken by APHA testing laboratories on samples from Small Ruminants in 2010 paid for by statutory exotic viruses surveillance and research contracts. The dataset includes the following fields: Year; Species class; Species; Test code; test description; Number of tests (the volume of tests performed in the 12 month period).

This dataset provides a list of the tests undertaken by APHA testing laboratories on Small Ruminants samples in 2007 paid for by international trade surveillance contracts. The dataset includes the following fields: Year; Species class; Species; Test code; test description; Number of tests (the volume of tests performed in the 12 month period).

The emergence of drug resistant pathogens is a serious public health problem. It is a long-standing goal to predict rates of resistance evolution and design optimal treatment strategies accordingly. To this end, it is crucial to reveal the underlying causes of drug-specific differences in the evolutionary dynamics leading to resistance. However, it remains largely unknown why the rates of resistance evolution via spontaneous mutations and the diversity of mutational paths vary substantially between drugs. Here we comprehensively quantify the distribution of fitness effects (DFE) of mutations, a key determinant of evolutionary dynamics, in the presence of eight antibiotics representing the main modes of action. Using precise high-throughput fitness measurements for genome-wide Escherichia coli gene deletion strains, we find that the width of the DFE varies dramatically between antibiotics and, contrary to conventional wisdom, for some drugs the DFE width is lower than in the absence of stress. We show that this previously underappreciated divergence in DFE width among antibiotics is largely caused by their distinct drug-specific dose-response characteristics. Unlike the DFE, the magnitude of the changes in tolerated drug concentration resulting from genome-wide mutations is similar for most drugs but exceptionally small for the antibiotic nitrofurantoin, i.e., mutations generally have considerably smaller resistance effects for nitrofurantoin than for other drugs. A population genetics model predicts that resistance evolution for drugs with this property is severely limited and confined to reproducible mutational paths. We tested this prediction in laboratory evolution experiments using the “morbidostat”, a device for evolving bacteria in well-controlled drug environments. Nitrofurantoin resistance indeed evolved extremely slowly via reproducible mutations—an almost paradoxical behavior since this drug causes DNA damage and increases the mutation rate. Overall, we identified novel quantitative characteristics of the evolutionary landscape that provide the conceptual foundation for predicting the dynamics of drug resistance evolution.

This dataset provides a list of the tests undertaken by APHA testing laboratories on small ruminant samples in 2011 paid for by tuberculosis surveillance and research contracts. The dataset includes the following fields: Year; Species class; Species; Test code; test description; Number of tests (the volume of tests performed in the 12 month period).