Oceanic and terrestrial origin of precipitation over 50 major world river basins: Implications for the occurrence of drought.

The terrestrial and oceanic origins of precipitation over 50 major river basins worldwide were investigated for the period 1980-2018. For this purpose, we used a Lagrangian approximation that calculates the humidity that results in precipitation from the entire ocean area (ocean component of the precipitation, PLO) and the entire land area (land component, PLT) as well as the sum of both components (Lagrangian precipitation, PL). PL and its components were highly correlated with precipitation over the basins, where PLT accounted for >50 % of the PL in most of them. This confirmed the importance assigned by previous studies to terrestrial recycling of precipitation and moisture transport within the continents. However, the amount of PLO in almost all North American river basins was highlighted. The assessment of drought conditions through the Standardized Precipitation Index (SPI) at a temporal scale of 1- and 3-months revealed the number of drought episodes that affected each river basin, especially the Amazon, Congo, and Nile, because of the lower number of episodes but higher average severity and duration. A direct relationship between the severity of drought episodes and the respective severity computed on the oceanic and terrestrial SPI series was also found for the majority of basins. This highlights the influence of the severity of the SPI of oceanic origin for most basins in North America. However, for certain basins, we found an inverse relationship between the severity of drought and the associated severity according to the SPI of oceanic or terrestrial origin, thus highlighting the principal drought attribution. Additionally, a copula analysis provided new information that illustrates the estimated conditional probability of drought for each river basin in relation to the occurrence of drought conditions of oceanic or terrestrial origin, which revealed the possible main driver of drought severity in each river basin.

Using a multilayer perceptron in intraocular lens power calculation.

PURPOSE: To determine the capabilities of a multilayer perceptron (MLP) for calculating the power of an intraocular lens (IOL) to be implanted and in achieving a given postoperative stable refraction. SETTING: Cuban Institute of Ophthalmology, Havana, Cuba. DESIGN: Retrospective review. METHODS: The study comprised data of patients who had uneventful phacoemulsification cataract surgery with implantation of a biconvex acrylic foldable IOL (type RYCF, model Ocuflex) in the capsular bag over 6 years. Exclusion criteria were previous intraocular or refractive corneal surgery, any corneal disease, pathological or complicated cataracts, intraoperative complications, preoperative astigmatism beyond 3.0 diopters (D), postoperative corrected distance visual acuity worse than 20/40, missing postoperative refractive information, eyes with an axial length (AL) shorter than 19.36 mm, eyes with an AL longer than 27.0 mm, average corneal keratometry (K) power lower than 36.0 D or higher than 50.9 D, and refractive surprises greater than ±3.0 D. The data were used to train an MLP to predict the value of the IOL power required for attaining a given postoperative refraction. Using AL, K value, and predicted and real postoperative refraction as input data, the output of the MLP was the IOL power. RESULTS: The study comprised 15 728 eyes of 15 728 patients. The trained neural networks predicted the value of the implanted IOL with an error less than 0.5 D in more than 95% of patients, even for a case in which a surgeon was not included in the training process. CONCLUSIONS: The accuracy attained by the trained MLP is high, indicating the feasibility of a prospective study leading to a new method of predicting the IOL power in refractive surgery with an error lower than the current prediction methods.