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Precipitation Gravimetry01:03

Precipitation Gravimetry

Precipitation gravimetry is based on converting an analyte into a sparingly soluble precipitate, which is separated by filtration and weighed. An ideal precipitate should be pure, insoluble, of known composition, and easily filtered from the reaction mixture.
In determining nickel by gravimetric analysis, a precipitant of ethanolic dimethylglyoxime is added to a hot nickel salt solution. This is quickly followed by the dropwise addition of dilute ammonia solution until precipitation occurs. A...
Precipitation Processes01:12

Precipitation Processes

The experimental conditions in a gravimetric analysis should be optimized to maximize the particle size and purity of the obtained precipitate. Ideally, the concentration of the precipitating reagent should be low with effective stirring to maintain low relative supersaturation for the growth of large crystals. In homogeneous precipitation, the precipitant is slowly generated by a chemical reaction in the solution to avoid local reagent excesses. For example, urea decomposes gradually to...
Precipitation and Co-precipitation01:17

Precipitation and Co-precipitation

Precipitation and coprecipitation methods can be used to separate a mixture of ions in a solution. In qualitative inorganic analysis, ions that form sparingly soluble precipitates with the same reagent are separated based on the differences in solubility products. For example, consider the separation of Cu(II) and Fe(II) ions by precipitation as insoluble sulfides. First, copper(II) sulfide is precipitated by the addition of acidic H2S, where the dissociation of H2S is suppressed. Adding H2S...
Masonry Curtain Walls01:20

Masonry Curtain Walls

Masonry curtain walls employ brick or stone veneers supported by the building's structure to form an external cladding system that is both aesthetically appealing and functional. These walls are erected through two principal techniques, first by traditional layering of masonry units and second by using prefabricated panels. Traditional construction relies on steel shelf angles attached to the spandrel beam for support, with high-bond mortars ensuring secure attachment of masonry veneer units.
Design Example: Sustainability in Concrete Building01:26

Design Example: Sustainability in Concrete Building

As the construction industry moves towards more eco-friendly practices, concrete's adaptability and its ability to incorporate sustainable features make it a key material in the drive towards greener building solutions.
There are multiple approaches to achieve sustainability in a commercial concrete building. For instance, construct a concrete parking area under the building, utilizing pervious concrete paver blocks in open areas to facilitate rainwater collection through an underground cistern.

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Related Experiment Video

Updated: May 11, 2026

Isolating And Immunostaining Lymphocytes and Dendritic Cells from Murine Peyer's Patches
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Spatio-temporal Attention driven Rainfall Inference using Transformative Architecture (SARITA).

Ishan Sharma1, Sarita Azad2, Ankur Suri1,3

  • 1School of Mathematical & Statistical Sciences, Indian Institute of Technology Mandi, 175005, Mandi, India.

Scientific Reports
|December 24, 2025
PubMed
Summary
This summary is machine-generated.

Short-term rainfall forecasting in Northwest India is improving. A new model, SARITA, enhances hourly rainfall prediction accuracy by 25% using spatial correlations and an attention mechanism.

Keywords:
Deep LearningDeformable ConvLSTMHourly Rainfall ForecastingIndian MonsoonMoran’s ISpatial CorrelationSpatiotemporal Modeling

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Area of Science:

  • Hydrometeorology
  • Spatiotemporal modeling
  • Climate science

Background:

  • Short-term rainfall forecasting is crucial for managing extreme weather events like flash floods.
  • The Northwest Himalayan (NWH) region exhibits complex hourly rainfall patterns and declining trends (2019-2024).
  • Understanding spatial correlations in rainfall is key to improving forecast accuracy.

Purpose of the Study:

  • To analyze hourly rainfall patterns and spatial correlations in the NWH region.
  • To develop an advanced model for enhanced short-term rainfall forecasting.
  • To improve the detection of rainfall anomalies.

Main Methods:

  • Analysis of hourly rainfall data (2019-2024) in the NWH region.
  • Examination of spatial correlation decay across different altitudes and temporal lags.
  • Development and application of the SARITA model, integrating an attention-guided spatial correlation mechanism within a Deformable Convolutional Long Short-Term Memory (DConvLSTM) framework.

Main Results:

  • Significant decreasing trends in hourly rainfall observed in ~50% of the NWH region.
  • High-elevation areas show stronger initial correlations (>0.8) with rapid decay, while lower areas have gradual decay.
  • Rainfall variability typically dissipates within 6-7 hours; a high coherence belt exists in the central Himalayas.
  • SARITA model achieved a 25% improvement in hourly rainfall forecasts and a 3.5% improvement in anomaly detection over baseline models.

Conclusions:

  • The SARITA model effectively captures complex spatial-temporal rainfall dynamics in the NWH region.
  • Attention-guided spatial correlations significantly enhance short-term rainfall prediction and anomaly detection.
  • The findings provide a valuable tool for mitigating hydrometeorological risks in mountainous regions.