Results 161 to 170 of about 35,579 (275)

In the Age of AI—Are National Models and Data Sets Still Important for Stream Flow Prediction?

Water Resources Research, Volume 62, Issue 10, October 2026.
Abstract Accurate streamflow prediction is critical for effective water resource management, and recent advances in deep learning and multi‐basin data sets have significantly improved model skill. Global deep‐learning models, trained on thousands of catchments have demonstrated strong generalization across diverse climates and continents.
Brett Snider, Ehsan Roshani
wiley   +1 more source

Comparative analysis of fecal microbial community diversity between Bactrian camels and Mongolian cattle based on 16S rRNA gene sequencing. [PDF]

Front Microbiol
Ma X, Ren W, Yang S, Liu M, Kong W, Xu X, Zhang L.   +6 more
europepmc   +1 more source

Risk Analysis of the Romanian Banking System – an Aggregated Balance Sheet Approach [PDF]

The paper presents a risk analysis for the current Romanian banking system. The analysis is conducted from the point of view of prudential rules and also from the point of view of Romanian banking system’s exposure to foreign funds, considering the ...
Liliana MOGA, Andrei STANCULESCU, Eugen MITRICA   +2 more
core  

Diagnosing Latent Storage Representations in LSTM Reservoir Release Policies

Water Resources Research, Volume 62, Issue 10, October 2026.
Abstract The influence of reservoirs on the water cycle introduces significant uncertainty for hydrologic prediction. The representation of reservoirs in hydrologic models ideally must be accurate, interpretable, and transferable across sites. Recent studies have highlighted the potential for data‐driven methods, including long short‐term memory (LSTM)
Matthew Chen, Jonathan D. Herman
wiley   +1 more source

Sexual Dimorphism and Aging Effects on Pituitary Gonadotroph Structure and Secretion in Dromedary Camels: Immunohistochemical and Ultrastructural Insights. [PDF]

Vet Sci
Jaspal SAS, Al-Khalaifah H, Shaukat MM, Shaukat R, Shaukat T, Naz S, Khan RU, Tufarelli V, Losacco C, Rossi L, Abdelrahman MM.   +10 more
europepmc   +1 more source

Loading camels

, 1900
Loading camels at Alice Springs telegraph station, Consie and Jack Bradshaw to the left.Date ...

core  

HydroDiffusion: Diffusion‐Based Probabilistic Streamflow Forecasting With a State Space Backbone

Water Resources Research, Volume 62, Issue 10, October 2026.
Abstract Recent advances have introduced diffusion models for probabilistic streamflow forecasting, demonstrating strong early flood‐warning skill. However, current implementations rely on Long Short‐Term Memory (LSTM) backbones and discrete‐time diffusion formulations.
Yihan Wang, Annan Yu, Lujun Zhang, Charuleka Varadharajan, N. Benjamin Erichson   +4 more
wiley   +1 more source

A Method Based on Nanobodies Against AMH to Establish Immunochromatography for Evaluation of Follicular Development in Bactrian Camels. [PDF]

Vet Sci
Wang L, Jin Y, Zhang G, Chen X, Ren H, Li L, Tian J, Mengke B, Li P, Ma Y, Qiqige C, Gao W, Liu G, Fan R.   +13 more
europepmc   +1 more source

Camels scooping

, 1930
Camels being used to scoop up dirt, NT, 193?.Unknown.Date ...

core  

Mass‐Conserving LSTM With Dual States for Streamflow Prediction: Separating Quickflow and Slow Storage

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 5, October 2026.
Abstract We introduce a Mass‐Conserving Long Short‐Term Memory with Dual States (MC‐LSTM‐DS) with the intention of separating short‐ and long‐term memory for predicting streamflow. It enforces water balance through a new partition gate on precipitation.
Saurabh Toraskar, M. Niranjannaik, Abhilash Singh, Kumar Gaurav   +3 more
wiley   +1 more source