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This study experimentally determines the relationship between the heat and mass transfer, in a crossflow configuration in which a ducted airflow passes through a planar water jet. An initial exploration using the Chilton-Colburn analogy resulted in a coefficient of determination of 0.72. On this basis, a re-examination of the heat and mass transfer processes by Buckingham's-π theorem and a least square analysis led to the proposal of a new dimensionless number referred to as the Lewis Number of Evaporation. A modified version of the Chilton-Colburn analogy incorporating the Lewis Number of Evaporation was developed leading to a coefficient of determination of 0.96.

The high incidence of stroke occurrence necessitates the understanding of its causes and possible ways for early prediction and prevention. In this respect, statistical methods offer the “big picture,” but they have a weak predictive ability at an individual level. This research proposes a new personalized modeling method based on computational spiking neural networks (SNN) for the identification of causal associations between clinical and environmental time series data that can be used to predict individual stroke events. The method is tested on 804 stroke patients. Given a clinical data set of patients who experienced a stroke in the past and the corresponding environmental time-series data for a selected time-window before the stroke event, the method identifies the clusters of individuals with a high risk for stroke under similar conditions. The methodology involves a pipeline of processes when creating a personalized model for an individual $$x$$ x : (1) selecting a group of individuals $$Gx$$ Gx with similar personal records to $$x$$ x ; (2) training a personalized SNN $$x$$ x model of several days of environmental data related to the $$Gx$$ Gx group to predict the risk of stroke for $$x$$ x at least one day earlier; (3) model interpretability through 3D visualization; (4) discovery of personalized predictive markers. The results are twofold, first proposing a new computational methodology and second presenting new findings. It is found that certain environmental factors, such as SO2, PM10, CO, and PM2.5, increase the risk of stroke if an individual $$x$$ x belongs to a certain cluster of people, characterized by a combination of family history of stroke and diabetes, overweight, vascular/heart disease, age, and other. For the used population data, the proposed method can predict accurately individual risk of stroke before the day of the stroke. The paper presents a new methodology for personalized machine learning methods to define subgroups of the population with a high risk of stroke and to predict early individual risk of the stroke event. This makes the proposed cognitive computation method useful to reduce morbidity and mortality in society. The method is broadly applicable for predicting individual risk of other diseases and mental health conditions.

The present study is concerned with desalinating the saline water, using the humidification dehumidification method. An open air open water cycle is chosen, whilst forced air circulation is applied. The system utilizes water and air heating technique. The energy required for heating the air is provided by solar radiation, while the required energy for heating the water is provided by electricity. The goals of this study are: a) To study different existing systems in the literature; b) To review the governing equations for each segment of the desalination unit; and c) To conduct and experiment on the above described humidification dehumidification desalination unit under North Cyprus winter conditions. The solar air heater placed to azimuth angle of -20, with a tilt angle of 45 . According to the experiment, the optimum flow rate for water stream is 4 Lt/min, while the air flow rate is 1.5m 3 /min. Besides, the inlet water temperature to the evaporator is kept at 55 • c. The maximum productivity of 1.55 Lt/day.m 2 is achieved for this condition. The present experiment implies that the maximum productivity is achieved with higher temperature of both air and water streams into the evaporator, higher flow rate for water and lower flow rate for air.