An experimental and theoretical investigation of three phase direct contact heat transfer by evaporation of refrigerant drops in an immiscible liquid has been carried out. Refrigerant Rl2 and R134a were used for the dispersed phase, while water and brine were the immiscible continuous phase. A numerical analysis is presented to predict the temperature distribution throughout the circular test column radially and axially is achieved. Experimental measurements of the temperature distribution have been compared with the numerical results and are discussed .A comparison between the experimental and theoretical results showed acceptable agreement and applicability of the derived equations. Comparison with other related work showed similar beh

A summary of zooplankton research done in Peruvian marine waters is presented. We first provide a brief overview of the evolution of zooplankton studies off Peru before reviewing zooplankton biodiversity, regional distribution, seasonal and interannual fluctuation, trophodynamics, secondary production, and modeling are some of these topics. We evaluate research on various meroplankton, macroplankton, mesoplankton, and microplankton groups and provide a list of species from both published and unpublished sources. Three regional zooplankton groups have been identified: A shelf group on the continental shelf dominated by Acartia tonsa and Centropages brachiatus; A slope group on the continental shelf with siphonophores, bivalves, foramin

    Land forms are result from interaction between lithosphere, atmosphere, hydrosphere and biosphere. Lithosphere composed of lithologic units and the main units of the study area are: limestone, marl, marley limestone, sandstone, pebbly sandstone, mudstone, claystone and secondary gypsum in addition to Quaternary sediments. Landforms of the study area can be subdivided according to their origin into many units: 1- Structural- denudational: plateau, mesas, hills, cliffs and wadis; 2- Denudational: desert pavement and mushroom rock; 3-Mass movements; 4- Solution: lake, salt marsh, piping caves; 5- Springs; 6- Fluvial: terraces, alluvial fan, infilled wadi, flood plain; 7- Drainage units; 8-Evaporational: sabkha, secondary

Markov chains are an application of stochastic models in operation research, helping the analysis and optimization of processes with random events and transitions. The method that will be deployed to obtain the transient solution to a Markov chain problem is an important part of this process. The present paper introduces a novel Ordinary Differential Equation (ODE) approach to solve the Markov chain problem. The probability distribution of a continuous-time Markov chain with an infinitesimal generator at a given time is considered, which is a resulting solution of the Chapman-Kolmogorov differential equation. This study presents a one-step second-derivative method with better accuracy in solving the first-order Initial Value Problem

The calculation. of the nuclear. charge. density. distributions. ρ(r) and root. mean. square. radius.( RMS ) by elastic. electron. scattering. of medium. mass. nuclei. such. as (⁹⁰Zr, ⁹²Mo) based. on the model. of the modified. shell. and the use of the probability. of occupation. on the surface. orbits. of level 2p, 2s eroding. shells. and 1g gaining. shells. The occupation probabilities of these states differ noticeably from the predictions of the SSM. We have found. an improvement. in the determination. of ground. charge. density. and this improvement. allow. more precise. identification. of (CDD) between. (⁹²Mo- ⁹⁰Zr) to illustrate the influence of the extra

Finger vein recognition and user identification is a relatively recent biometric recognition technology with a broad variety of applications, and biometric authentication is extensively employed in the information age. As one of the most essential authentication technologies available today, finger vein recognition captures our attention owing to its high level of security, dependability, and track record of performance. Embedded convolutional neural networks are based on the early or intermediate fusing of input. In early fusion, pictures are categorized according to their location in the input space. In this study, we employ a highly optimized network and late fusion rather than early fusion to create a Fusion convolutional neural network

Transformers are a specific category of neural network design. Transformers often depend on extensive pre-training on a large scale and exhibit a notable degree of computational complexity. The disadvantage of using this method is a significant increase in computational complexity, which necessitates a significant commitment of time and computing resources in order to successfully work with these models. Transformer networks possess the desirable benefit of extracting distant characteristics effectively via their self-attention mechanism. In this paper, the Global Self-Attention Transformer module is applied to tackle these issues. The model is based on a segmentation problem called Brain-GS that works as a mechanism and encompasses