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The main function of ocular blood flow is to supply sufficient oxygen and nutrients to the eye. Local blood vessels resistance regulates overall blood distribution to the eye and can vary rapidly over time depending on ocular need. Under normal conditions, the relation between blood flow and perfusion pressure in the eye is autoregulated. Basically, autoregulation is a capacity to maintain a relatively constant level of blood flow in the presence of changes in ocular perfusion pressure and varied metabolic demand. In addition, ocular blood flow dysregulation has been demonstrated as an independent risk factor to many ocular diseases. For instance, ocular perfusion pressure plays key role in the progression of retinopathy such as glaucoma and diabetic retinopathy. In this review, different direct and indirect techniques to measure ocular blood flow and the effect of myogenic and neurogenic mechanisms on ocular blood flow are discussed. Moreover, ocular blood flow regulation in ocular disease will be described.

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Owing to its 100% theoretical salt rejection capability, membrane distillation (MD) has emerged as a promising seawater desalination approach to address freshwater scarcity. Ideal MD requires high vapor permeate flux established by cross-membrane temperature gradient (∆T) and excellent membrane durability. However, it’s difficult to maintain constant ∆T owing to inherent heat loss at feedwater side resulting from continuous water-to-vapor transition and prevent wetting transition-induced membrane fouling and scaling. Here, we develop a Ti3C2Tx MXene-engineered membrane that imparts efficient localized photothermal effect and strong water-repellency, achieving significant boost in freshwater production rate and stability. In addition to photothermal effect that circumvents heat loss, high electrically conductive Ti3C2Tx MXene also allows for self-assembly of uniform hierarchical polymeric nanospheres on its surface via electrostatic spraying, transforming intrinsic hydrophilicity into superhydrophobicity. This interfacial engineering renders energy-efficient and hypersaline-stable photothermal membrane distillation with a high water production rate under one sun irradiation.

In order to explore the characteristics of the evolution behavior of the time-varying relationships between multivariate time series, this paper proposes an algorithm to transfer this evolution process to a complex network. We take the causality patterns as nodes and the succeeding sequence relations between patterns as edges. We used four time series as sample data. The results of the analysis reveal some statistical evidences that the causalities between time series is in a dynamic process. It implicates that stationary long-term causalities are not suitable for some special situations. Some short-term causalities that our model recognized can be referenced to the dynamic adjustment of the decisions. The results also show that weighted degree of the nodes obeys power law distribution. This implies that a few types of causality patterns play a major role in the process of the transition and that international crude oil market is statistically significantly not random. The clustering effect appears in the transition process and different clusters have different transition characteristics which provide probability information for predicting the evolution of the causality. The approach presents a potential to analyze multivariate time series and provides important information for investors and decision makers.