The global Rosai-Dorfman Disease (RDD) Therapeutics market is expected to garner a market value of US$ 431 Million in 2023 and is expected to accumulate a market value of US$ 839.95 Million by registering a CAGR of 6.9% in the forecast period 2023 to 2033.

Report Attribute	Details
Expected Market Value (2023)	US$ 431 Million
Anticipated Forecast Value (2033)	US$ 839.95 Million
Projected Growth Rate (2023 to 2033)	6.9% CAGR

Report Scope

Report Attribute	Details
Market Value in 2023	US$ 431 Million
Market Value in 2033	US$ 839.95 Million
Growth Rate	CAGR of 6.9% from 2023 to 2033
Base Year for Estimation	2022
Historical Data	2018 to 2022
Forecast Period	2023 to 2033
Quantitative Units	Revenue in USD Million and CAGR from 2023 to 2033
Report Coverage	Revenue Forecast, Volume Forecast, Company Ranking, Competitive Landscape, Growth Factors, Trends and Pricing Analysis
Segments Covered	Drug Class Treatment End User Distribution Channel Region
Regions Covered	North America Latin America Europe South Asia East Asia Oceania MEA
Key Countries Profiled	USA Canada Brazil Mexico Rest of Latin America Germany United Kingdom France Spain Italy Rest of Europe India Malaysia Singapore Thailand Rest of South Asia China Japan South Korea Austria New Zealand GCC countries South Africa Israel Rest of MEA
Key Companies Profiled	Teva Pharmaceuticals Ltd. Zydus Pharmaceuticals, Inc. Sun Pharmaceuticals Industries Ltd. Advanz Pharmaceticals Novartis AG Mylan N.V. Aurobindo Pharma Dr. Reddy’s Laboratories Ltd Viatris Inc. Pfizer Inc.
Customization	Available Upon Request

Customs records of are available for RDD FREIGHT INTERNATIONAL CANADA INC. Learn about its Importer, supply capabilities and the countries to which it supplies goods

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Customs records of are available for RDD TECHNOLOGIES SHENZHEN KEDI JINGXING TECHNOLOGY CO.,LTD. Learn about its Importer, supply capabilities and the countries to which it supplies goods

Rdd Freight International Inc Company Export Import Records. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.

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Eximpedia Export import trade data lets you search trade data and active Exporters, Importers, Buyers, Suppliers, manufacturers exporters from over 209 countries

Eximpedia Export import trade data lets you search trade data and active Exporters, Importers, Buyers, Suppliers, manufacturers exporters from over 209 countries

Why are women strongly underrepresented in top political positions? We analyze the effect of party leaders' gender on their ability to capitalize on political power during negotiations to form a new government after elections. We leverage the as-if random assignment of a bargaining advantage in close local elections in Spain through a regression discontinuity design and find that women are about 25 percentage points less likely than men to secure the mayor's position when they win elections by a narrow margin, even if their parties manage to join the governing coalition anyway. This paper contributes to the understanding of the role of personal characteristics in the political process and has far-reaching implications for gender equality and the quality of democratic representation.

We will construct SciSpark, a scalable system for interactive model evaluation and for the rapid development of climate metrics and analyses. SciSpark directly leverages the Apache Spark technology and its notion of Resilient Distributed Datasets (RDDs). RDDs represent an immutable data set that can be reused across multi-stage operations, partitioned across multiple machines and automatically reconstructed if a partition is lost. The RDD notion directly enables the reuse of array data across multi-stage operations and it ensures data can be replicated, distributed and easily reconstructed in different storage tiers, e.g., memory for fast interactivity, SSDs for near real time availability and I/O oriented spinning disk for later operations. RDDs also allow Spark's performance to degrade gracefully when there is not sufficient memory available to the system. It may seem surprising to consider an in-memory solution for massive datasets, however a recent study found that at Facebook 96% of active jobs could have their entire data inputs in memory at the same time. In addition, it is worth noting that Spark has shown to be 100x faster in memory and 10x faster on disk than Apache Hadoop, the de facto industry platform for Big Data. Hadoop scales well and there are emerging examples of its use in NASA climate projects (e.g., Teng et al. and Schnase et al.) but as is being discovered in these projects, Hadoop is most suited for batch processing and long running operations. SciSpark contributes a Scientific RDD that corresponds to a multi-dimensional array representing a scientific measurement subset by space, or by time. Scientific RDDs can be created in a handful of ways by: (1) directly loading HDF and NetCDF data into Hadoop Distributed File System (HDFS); (2) creating a partition or split function that divides up a multi-dimensional array by space or time; (3) taking the results of a regridding operation or a climate metrics computation; or (4) telling SciSpark to cache an existing Scientific RDD (sRDD), keeping it cached in memory for data reuse between stages. Scientific RDDs will form the basis for a variety of advanced and interactive climate analyses, starting by default in memory, and then being cached and replicated to disk when not directly needed. SciSpark will also use the Shark interactive SQL technology that allows structured query language (SQL) to be used to store/retrieve RDDs; and will use Apache Mesos to be a good tenant in cloud environments interoperating with other data system frameworks (e.g., HDFS, iRODS, SciDB, etc.).

One of the key components of SciSpark is interactive sRDD visualizations and to accomplish this SciSpark delivers a user interface built around the Data Driven Documents (D3) framework. D3 is an immersive, javascript based technology that exploits the underlying Document Object Model (DOM) structure of the web to create histograms, cartographic displays and inspections of climate variables and statistics.

SciSpark is evaluated using several topical iterative scientific algorithms inspired by the NASA RCMES project including machine-learning (ML) based clustering of temperature PDFs and other quantities over North America, and graph-based algorithms for searching for Mesocale Convective Complexes in West Africa.

Odds of reporting modern contraceptive use by women’s characteristics and survey mode, using full FTF sample and FTF phone owner sample.