Builds resilience to: increased drought, water scarcity, and heat stress that affect crop yields and farmer incomes. The technology can absorb water up to 150 times its weight and release it over a long period of time to maintain soil moisture. EF Polymer Private Limited (India) produces a naturally biodegradable water retention polymer for soil conditioning.Builds resilience to: extreme weather events and weather volatility that affect crop yields and farmer incomes. Their solution is used by agricultural economists, agricultural engineers, financial institutions, farmers and more. This enables farmers to adapt to changing climatic conditions due to climate change. Crop2X Private Limited (Pakistan) is a precision agritech startup that provides weather forecast and water information that can help farmers increase production while minimizing inputs.Builds resilience to: increased drought and water scarcity that affect crop irrigation. Their services help detect groundwater zones remotely, without fieldwork, helping farmers identify the optimum location for digging a well with high precision, less effort, and at lower cost. Aumsat Technologies LLP (India) provides satellite-based, AI-enabled hydrological analysis for locating, predicting, and forecasting groundwater resources.(Agriculture, Risk Analytics/Management, Insurance) Builds resilience to: extreme weather events and weather volatility that affect crop yields, crop prices, and farmer incomes. Their end-to-end data analytics platform increases the resilience of smallholder farmers by assessing the frequency and intensity of natural calamities and their impacts on crop yields and price. Agtuall (India) provides affordable crop price risk management solutions for smallholder farmers across the world.Builds resilience to: increased drought and water scarcity that affect residential and commercial water use. Absolute Water (India) increases the availability and quality of water in areas projected to experience water stress by organically treating and converting raw sewage wastewater into potable water through a system that naturally degrades pollutants and converts it into nutrients. The 16 startups in the cohort were selected out of more than 300 applicants, representing 10 countries across Asia and Africa. There is tremendous promise in identifying and funding local ventures whose successes can be scaled to meet climate adaptation needs around the world,” said Gustavo Fonseca, Director of Programs at the Global Environment Facility. “We are delighted to see these startups get support through the ASAP Accelerator, and look forward to continued connections between climate resilience innovators in developing countries and financing for them. Additional support is provided by Conservation International and the Inter-American Development Bank. “Through the ASAP Accelerator, we aim to give these entrepreneurs the tools to scale their impact and connect to a global network working to develop solutions that address the impacts of climate change.”ĪSAP is a grant-funded initiative led by The Lightsmith Group, in partnership with Village Capital, and with the support of the Global Environment Facility’s Special Climate Change Fund. “We’re excited to announce this cohort of companies, all of whom are providing their customers with an array of climate adaptation solutions across Africa and Asia,” said Brian Parham, ASAP Program Director at Lightsmith. During the ASAP accelerator program, the 16 companies will work with industry experts, investors, and ecosystem partners to develop the networks and tools they need to attract investment, grow their businesses, and increase their climate adaptation impacts. The 16 startups were selected from more than 300 applicants and have developed technologies in water, agriculture, risk analytics, supply chain, infrastructure, and insurance that can support adaptation and resilience to climate change.ĪSAP seeks to build a global ecosystem for small- to medium-sized companies in emerging markets that have technologies, products, and services that can be used to adapt and build resilience to the impacts of climate change. NEW YORK, NEW YORK & WASHINGTON, D.C., 12 April 2022 – The Lightsmith Group (“Lightsmith”) and Village Capital announced today that 16 startups were selected to participate in a new environmental accelerator called “ ASAP”, or the Adaptation SME Accelerator Project, focused on innovative climate adaptation ventures in Asia and Africa. Accelerator Partnership Program will accelerate 16 startups that are providing climate adaptation and resilience solutions in Asia and Africa.
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Precipitation is the formation of a solid in a solution or inside another solid during a chemical reaction. The acid base reaction results in the formation of salt (neutral in nature) and water. An acid-base reaction occurs, when an acid reacts with equal quantity of base. Neutralization reactions are a specific kind of double displacement reaction. This results in the formation of product molecule.ĭouble displacement reactions can be further classified as neutralization, precipitation and gas formation reactions. The reactants changes into ions when dissolved in water and there is an exchange of ions in solution. The general equation which represents a double displacement reaction can be written as:ĭouble displacement reactions generally take place in aqueous solutions in which the ions precipitate and there is an exchange of ions.įor example, on mixing a solution of barium chloride with sodium sulphate, a white precipitate of barium sulphate is immediately formed. During this reaction, the cations and anions of two different compounds switch places, forming two entirely different compounds. The Theoryĭouble displacement reactions may be defined as the chemical reactions in which one component each of both the reacting molecules is exchanged to form the products. To perform a double displacement reaction using sodium sulphate and barium chloride solutions. In the case of non-object Series, the NumPy dtype is translated to its Arrow equivalent. The column types in the resulting Arrow Table are inferred from the dtypes of the pandas.Series in theĭataFrame. Use preserve_index=True to force it to be stored as a column.Ĭonvert pandas.DataFrame to a pyarrow.Table to create a Dataset. The default of None will store the index as a column, except for RangeIndex which is stored as metadata only. Whether to store the index as an additional column in the resulting Dataset. Not all fields are known on construction and may be updated later.ĭataset information, like description, citation, etc. See the constructor arguments and properties for a full list. Keyword arguments to be passed to the BuilderConfig and used in the DatasetBuilder.ĭatasetInfo documents datasets, including its name, version, and features. * *config_kwargs (additional keyword arguments).Each template casts the dataset’s Features to standardized column names and types as detailed in datasets.tasks. The task templates to prepare the dataset for during training and evaluation. The combined size in bytes of all files associated with the dataset (downloaded files + Arrow files). The combined size in bytes of the Arrow tables for all splits. Size of the dataset in bytes after post-processing, if any. post_processing_size ( int, optional).The size of the files to download to generate the dataset, in bytes. The mapping between the URL to download the dataset’s checksums and corresponding metadata. The mapping between split name and metadata. The name of the configuration derived from BuilderConfig. It is also the snake_case version of the dataset builder class name. Usually matched to the corresponding script name. The name of the GeneratorBasedBuilder subclass used to create the dataset. Specifies the input feature and the label for supervised learning if applicable for the dataset (legacy from TFDS). supervised_keys ( SupervisedKeysData, optional).For example, it can contain the information of an index. Information regarding the resources of a possible post-processing of a dataset. post_processed ( PostProcessedInfo, optional).The features used to specify the dataset’s column types. It can be the name of the license or a paragraph containing the terms of the license. A URL to the official homepage for the dataset. |