The LISA company data contain information on Dutch companies, aggregated on a municipal or other level, or in the form of microdata. The data have a geographical (location) and socioeconomic component (employment in a sector).

Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

The Netherlands data center physical security market is experiencing robust growth, projected to reach €53.40 million in 2025 and maintain a Compound Annual Growth Rate (CAGR) of 12.70% from 2025 to 2033. This significant expansion is driven by several key factors. The increasing reliance on digital infrastructure across various sectors, from finance and healthcare to government and e-commerce, necessitates enhanced security measures for data centers. Rising cyber threats and data breaches are prompting organizations to invest heavily in robust physical security solutions, encompassing access control systems, surveillance technologies (CCTV, video analytics), intrusion detection, and perimeter security. Furthermore, the growing adoption of cloud computing and the expansion of data center infrastructure within the Netherlands are further fueling market growth. Stringent data privacy regulations, such as GDPR, also play a crucial role, compelling companies to invest in advanced security solutions to ensure compliance. The market is witnessing a notable shift towards integrated security systems, leveraging technologies like AI and IoT for enhanced monitoring and threat detection. Leading players in the Netherlands data center physical security market, including Honeywell International Inc, ABB Ltd, Securitas Technology, Cisco Systems Inc, Siemens AG, Johnson Controls, Milestone Systems AS, Schneider Electric, Bosch Sicherheitssysteme GmbH, Axis Communications AB, and Hikvision, are continuously developing and deploying advanced solutions to cater to the evolving needs of data center operators. Competition is intense, with companies focusing on innovation, strategic partnerships, and mergers & acquisitions to gain market share. While the market faces challenges such as initial high investment costs for sophisticated security systems, the long-term benefits of enhanced security and compliance outweigh these concerns, promoting sustained market growth over the forecast period. The market's future growth trajectory is promising, supported by ongoing technological advancements, increased awareness of cyber security risks, and the continuous expansion of the data center landscape within the Netherlands. Key drivers for this market are: Increase in the Demand for Energy-Efficient and Cost-Effective Data Centers, Increasing Security Concerns is Driving the Market's Growth. Potential restraints include: High Costs Associated with Physical Security Infrastructure. Notable trends are: The IT and Telecommunication Segment Holds a Major Share in the Market.

This digitally compiled map includes geology, geologic provinces, and oil and gas fields of South America. The map is part of a worldwide series on CD-ROM by World Energy Project released of the U.S. Geological Survey . The goal of the project is to assess the undiscovered, technically recoverable oil and gas resources of the world and report these results by the year 2000. For data management purposes the world is divided into eight energy regions corresponding approximately to the economic regions of the world as defined by the U.S. Department of State. South America (Region 6) includes Argentina, Bolivia, Brazil, Chile, Columbia, Ecuador, Falkland Islands, French Guiana, Guyuna, Netherlands, Netherlands Antilles, Paraguay, Peru, Suriname, Trinidad and Tobago, Uruguay, and Venezuela. Each region is then further divided into geologic provinces on the basis of natural geologic entities and may include a dominant structural element or a number of contiguous elements. Some provinces contain multiple genetically related basins. Geologic province boundaries for the South America are delineated using data from a number of geologic maps, and other tectonic and geographic data (see References). Offshore province boundaries are defined by the 4000 meter bathymetric contour. Each province is assigned a unique number; the first digit is the region number. It is attempted to number the provinces in geographical groups; onshore, offshore, and combined on and offshore. The list of the provinces sorted by Code is shown in Adobe Acrobat samgeo.pdf file (see section V below). Oil and gas field data from Petroconsultants International Data Corporation worldwide oil and gas field database are allocated to these provinces. The geologic provinces are being further subdivided into petroleum systems and assessment units in order to appraise the undiscovered petroleum potential of selected provinces of the world. Specific details of the data sources and map compilation are given in the metadata file on this CD-ROM. Smaller stratigraphic subdivisions of Phanerozoic rock are combined to simplify the map and to maintain consistency with other maps of the series. Precambrian rocks are undivided. Oil and gas field markers represent field centerpoints published with permission from Petroconsultants International Data Corp.,1996 database. This map is compiled using Environmental Systems Research Institute, Inc. (ESRI) ARC/INFO software. Political boundaries and cartographic representations on this map were taken, with permission, from ESRI's ArcWorld 1:3M digital coverages, have no political significance, and are displayed as general reference only. Portions of this database covering the coastline and country boundaries contain intellectual property of Environmental Systems Research Institute, Inc. (ESRI), and are used herein with permission. Copyright 1992 and 1996, Environmental Systems Research Institute, Inc. All rights reserved.

Graph and download economic data for Geographical Outreach: Number of Institutions, Other Financial Corporations, Insurance Corporations for Netherlands (NLDFCIOFINUM) from 2004 to 2024 about Netherlands, finance companies, companies, finance, insurance, financial, and corporate.

Success.ai’s Company Financial Data for European Financial Professionals provides a comprehensive dataset tailored for businesses looking to connect with financial leaders, analysts, and decision-makers across Europe. Covering roles such as CFOs, accountants, financial consultants, and investment managers, this dataset offers verified contact details, firmographic insights, and actionable professional histories.

With access to over 170 million verified professional profiles, Success.ai ensures your outreach, market research, and partnership strategies are driven by accurate, continuously updated, and AI-validated data. Backed by our Best Price Guarantee, this solution is indispensable for navigating the fast-paced European financial landscape.

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The complex and dynamic history of the Anatolian Peninsula during the Pleistocene set the stage for species diversification. However, the evolutionary history of biodiversity in the region is shrouded by the challenges of studying species divergence in the recent, dynamic past. Here we study the Poecilimon bosphoricus (PB) species group to understand how the bush crickets’ diversification and the region’s complex history are coupled. Specifically, using sequences of two mitochondrial and two nuclear gene segments from over 500 individuals for a comprehensive set of taxa with extensive geographic sampling, we infer the phylogenetic and geographic setting of species divergence. In addition, we use the molecular data to examine hypothesized species boundaries that were defined morphologically. Our analyses of the timing of divergence confirm the recent origin of the PB complex, indicating its diversification coincided with the dynamic geology and climate of the Pleistocene. Moreover, the geography of divergence suggests a history of fragmentation followed by admixture of populations, suggestive of a ring species. However, the evolutionary history based on genetic divergence conflicts with morphologically defined species boundaries, raising the prospect that incipient species divergences may be relatively ephemeral. As such, the morphological differences observed in the PB complex may not be sufficient to have prevented homogenizing gene flow in the past. Alternatively, with the recent origin of the complex, the lack of time for lineage sorting may underlie the discord between morphological species boundaries and genetic differentiation. Under either hypothesis, geography – not taxonomy – is the best predictor of genetic divergence. Methods Individuals from almost all of the currently recognized species of the P. bosphoricus species group (Orthoptera, Tettigonidae; Phaneropterinae) were collected across the total geographic ranges of the species group during 2015–2019. The only exception is for P. athos that is isolated to the Athos Peninsula, Greece. DNA was extracted from the muscle of the hind femur with a proteinase K digestion and following the salt/isopropanol protocol (Aljanabi and Martinez, 1997). We amplified and sequenced the mitochondrial genes cytochrome C oxidase subunit I (COI) and nicotinamide adenine dinucleotide subunit 2 (ND2), and two nuclear ribosomal internal transcribed spacers of 5.8S rDNA, hereafter referred to as ITS; for details see supplementary material. Both strands were sequenced on a 23 ABI 3730XL DNA analyser by Macrogen Europe (Macrogen Inc., Amsterdam, the Netherlands). GenBank accession numbers of sequences are given in the article. Contigs from the forward and reverse sequences were visualized using SEQUENCHER v.4.1.4 (Gene-Codes Corp.) and aligned using MAFFT v.7.245 (Katoh and Standley, 2013) online version (http://align.bmr.kyushuu.ac.jp/mafft/online/server/) with the default setups (FFT-NS-i strategy, scoring matrix 200PAM (k = 2), gap opening penalty = 1.53). The numt probability of the COI and ND2 sequences was assessed following the criteria of Kaya and Çıplak (2018). Because the mtDNA and nuclear loci were not sequenced in each individual, datasets for each of the mitochondrial (COI and ND2) and nuclear loci (ITS) were analysed separately; concatenating across loci is not possible without a significant reduction in individuals and geographic coverage (e.g., some localities were sequenced for COI but not ND2, or some individuals had only ITS sequences). For example, 565, 849 and 678 individuals were sequenced for COI, ND2 and ITS, respectively, versus 381 individuals with sequences of COI and ND2 (for details about sequences see Table S1 and Table S3). We recognize this is not ideal; however, given our study is focused on the geography of divergence, our priority is on including all individuals so analyses were then run separately for each gene. Moreover, concatenating the data with the systemic pattern of missing data would introduce an unwanted bias that is undesirable. Unique haplotypes and their frequencies were identified by DNASP v.5 (Librado and Rozas, 2009) and the nucleotide composition, the number of variable sites, and indels were calculated with MEGA v.X (Kumar et al., 2016) for each locus. Saturation probabilities of single gene datasets were assessed using DAMBE v.7 (Xia, 2018). Phylogenetic relationships were estimated by maximum likelihood (ML) and Bayesian methods using RAxML (Stamatakis, 2006) via CIPRES with 1000 replicates and MRBAYES v.3.2.2 (Ronquist et al., 2012). To estimate divergence times, branch lengths were estimated using a molecular clock in BEAST v.2.6.1 (Bouckaert et al., 2019). Each BEAST analysis was run with a relaxed lognormal clock, linked site GTR and gamma model using 4 discrete gamma categories, linked Yule tree model for 100 million generations sampling every 10000 generations. The maximum clade credibility trees were built using TREEANNOTATOR implemented in BEAST, discarding the initial 25% samples as burn-in samples.

description: Files included are original data inputs on stream fishes (fish_data_OEPA_2012.csv), water chemistry (OEPA_WATER_2012.csv), geographic data (NHD_Plus_StreamCat); modeling files for generating predictions from the original data, including the R code (MVP_R_Final.txt) and Stan code (MV_Probit_Stan_Final.txt); and the model output file containing predictions for all NHDPlus catchments in the East Fork Little Miami River watershed (MVP_EFLMR_cooc_Final). This dataset is associated with the following publication: Martin, R., E. Waits, and C. Nietch. Empirically-based modeling and mapping to consider the co-occurrence of ecological receptors and stressors. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 613(614): 1228-1239, (2018).; abstract: Files included are original data inputs on stream fishes (fish_data_OEPA_2012.csv), water chemistry (OEPA_WATER_2012.csv), geographic data (NHD_Plus_StreamCat); modeling files for generating predictions from the original data, including the R code (MVP_R_Final.txt) and Stan code (MV_Probit_Stan_Final.txt); and the model output file containing predictions for all NHDPlus catchments in the East Fork Little Miami River watershed (MVP_EFLMR_cooc_Final). This dataset is associated with the following publication: Martin, R., E. Waits, and C. Nietch. Empirically-based modeling and mapping to consider the co-occurrence of ecological receptors and stressors. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 613(614): 1228-1239, (2018).

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The heavy fuel oil market size will decrease by USD 52.68 billion during 2020-2024, and the market’s growth momentum will accelerate during the forecast period.

This report provides a detailed analysis of the market by end-user (shipping and others) and geography (APAC, Europe, MEA, North America, and South America). Also, the report analyzes the market’s competitive landscape and offers information on several market vendors, including BP Plc, Chevron Corp., Exxon Mobil Corp., Indian Oil Corp. Ltd., Neste Oyj, PetroChina Co. Ltd., Qatar Petroleum, Rosneft Oil Co., Royal Dutch Shell Plc, and TOTAL SA.

Market Overview

Market Competitive Analysis

The market is fragmented, and the degree of fragmentation will remain the same during the forecast period. PetroChina Co. Ltd., Qatar Petroleum, Rosneft Oil Co., Royal Dutch Shell Plc, and TOTAL SA are some of the major market participants. Although the rising seaborne trade will offer growth opportunities, the implementation of MARPOL regulations will challenge the growth of the market participants. To make the most of the opportunities, market vendors should focus more on the growth prospects in the fast-growing segments, while maintaining their positions in the slow-growing segments.

To help clients improve their market position, this heavy fuel oil market forecast report provides a detailed analysis of the market leaders and offers information on the competencies and capacities of these companies. The report also covers details on the market’s competitive landscape and offers information on the products offered by various companies. Moreover, this heavy fuel oil market analysis report also provides information on the upcoming trends and challenges that will influence market growth. This will help companies create strategies to make the most of future growth opportunities.

This report provides information on the production, sustainability, and prospects of several leading companies, including:

• BP Plc
• Chevron Corp.
• Exxon Mobil Corp.
• Indian Oil Corp. Ltd.
• Neste Oyj
• PetroChina Co. Ltd.
• Qatar Petroleum
• Rosneft Oil Co.
• Royal Dutch Shell Plc
• TOTAL SA

Heavy Fuel Oil Market: Segmentation by Region

APAC had the largest heavy fuel oil market share in 2019. The growing requirement for energy and the growth in seaborne trade will influence the demand for heavy fuel oil in this region.

37% of the market’s decremental growth will originate from APAC during the forecast period. Singapore and China are the key markets for heavy fuel oil in APAC.

Heavy Fuel Oil Market: Segmentation by End-user

Heavy oil is highly preferred in the marine segment as the energy obtained from burning heavy fuel oil inside a combustion chamber rotates the propeller of the ship, thus propelling the vessel.

Market growth in this segment will be slower than the growth of the market in the others’ segment. This report provides an accurate prediction of the contribution of all the segments to the growth of the heavy fuel oil market size.

Heavy Fuel Oil Market: Key Drivers and Trends

The increasing industrialization and liberalization of national economies have fueled the demand for consumer products, thus enhancing trade activities. Heavy fuel oil is mainly used in the shipping industry as marine fuel. It is used to generate motion as well as heat and has high density and viscosity. Furthermore, seaborne transport is a key component of globalization that enables international trade and support supply chains, and also plays a crucial role in cross-border transportation. It further nurtures industrial development by supporting manufacturing growth, bringing together consumers and industries, and promoting regional economic and trade integration. Additionally, the growth in the availability of shipping data and application of Big data analytics in the shipping industry also provides greater visibility into the market as well as the pricing trends. The rise in seaborne trade activities will significantly influence the growth of the heavy fuel oil market during the forecast period.

• Scrubbers are used to remove particulate matters and harmful gases, which are generated as a result of combustion processes in marine engines in order to implement pollution control into the environment.
• Com

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The gear oil market size has the potential to grow by USD 1.14 billion during 2020-2024, and the market’s growth momentum will accelerate during the forecast period.

This report provides a detailed analysis of the market by end-user (transportation, and industrial) and geography (APAC, Europe, MEA, North America, and South America). Also, the report analyzes the market’s competitive landscape and offers information on several market vendors, including BP Plc, Chevron Corp., China National Petroleum Corp., China Petroleum & Chemical Corp., Exxon Mobil Corp., FUCHS PETROLUB SE, Idemitsu Kosan Co. Ltd., PJSC LUKOIL, Royal Dutch Shell Plc, and TOTAL SA.

Market Overview

Market Competitive Analysis

The market is fragmented, and the degree of fragmentation will remain the same during the forecast period. The vendors are focusing on constructing new plants in new locations to expand their market presence and increase their revenue share. FUCHS PETROLUB SE, Idemitsu Kosan Co. Ltd., PJSC LUKOIL, Royal Dutch Shell Plc, and TOTAL SA are some of the major market participants. Although the growing demand for fully synthetic gear oil will offer immense growth opportunities, the growing demand for automatic transmission systems will challenge the growth of the market participants. To make the most of the opportunities, market vendors should focus more on the growth prospects in the fast-growing segments, while maintaining their positions in the slow-growing segments.

To help clients improve their market position, this gear oil market forecast report provides a detailed analysis of the market leaders and offers information on the competencies and capacities of these companies. The report also covers details on the market’s competitive landscape and offers information on the products offered by various companies. Moreover, this report also provides information on the upcoming gear oil market trends and challenges that will influence market growth. This will help companies create strategies to make the most of future growth opportunities.

This gear oil market analysis report provides information on the production, sustainability, and prospects of several leading companies, including:

• BP Plc
• Chevron Corp.
• China National Petroleum Corp.
• China Petroleum & Chemical Corp.
• Exxon Mobil Corp.
• FUCHS PETROLUB SE
• Idemitsu Kosan Co. Ltd.
• PJSC LUKOIL
• Royal Dutch Shell Plc
• TOTAL SA

Gear Oil Market: Segmentation by Region

APAC accounted for the largest gear oil market share in 2019, and the region will offer several growth opportunities to market vendors during the forecast period. The strong presence of manufacturing facilities will significantly influence gear oil market growth in this region.

56% of the market’s growth will originate from APAC during the forecast period. China, India, Japan, and South Korea are the key markets for gear oil in APAC. Market growth in this region will be slower than the growth of the market in MEA and South America.

Gear Oil Market: Segmentation by End-user

Gear oil is an essential lubricant for automobiles with a manual transmission as it protects gear components and permits smooth gear-shifting. Moreover, gear oil provides a wide service temperature range, including excellent low-temperature characteristics for cold weather operations.

Market growth in the transportation segment will be slower than the growth of the market in the industrial segment. This report provides an accurate prediction of the contribution of all the segments to the growth of the gear oil market size.

Gear Oil Market: Key Drivers and Trends

The global gear oil market is driven by the growing demand for advanced gear oils such as semi-synthetic gear oil and fully synthetic gear oil. The addition of advanced additives and chemicals in fully synthetic gear oil increases their demand in automotive industry. Moreover, the demand for gear oil that withstands very low or high temperatures, extremely high loads, and extraordinary ambient conditions makes synthetic gear oil an ideal choice in industrial applications. Additionally, synthetic gear oil uses a superior quality synthetic base stock, with advanced additives and lubricants.

Furthermore, fully synthetic gear oil helps gears combat