Labyrinthine function is tightly coupled to proper homeostasis. This includes appropriate blood flow that is under strict autoregulatory control. Perturbations in labyrinthine microcirculation can lead to significant cochlear and/or vestibular dysfunction. The etiology of many otologic disorders, including sudden sensorineural hearing loss, presbyacusis, noise-induced hearing loss, and certain vestibulopathies, are suspected of being related to alterations in blood flow. It looks as if the ear listens to the heart and the heart beats in our ears.

Oral cancer is a subtype of head and neck cancer, is any cancerous tissue growth located in the oral cavity.It may arise as a primary lesion originating in any of the oral tissues, by metastasis from a distant site of origin, or by extension from a neighboring anatomic structure, such as the nasal cavity or the oral cancers may originate in any of the tissues of the mouth.There are several types of oral cancers, but around 90% are squamous cell carcinomas, originating in the tissues that line the mouth and lips. Oral or mouth cancer most commonly involves the tongue. It may also occur on the floor of the mouth, cheek lining, gingiva (gums), lips, or palate (roof of the mouth).

The universal use of herbicides in agriculture creates a necessary to study the effect of these chemicals on non-target organisms such as algae, which are sensitive to herbicides where they share with higher plants many common characters. So this book aimed at studying the effect of two herbicides glyphosate and clodinafop-propargyl which are currently used in Egypt on soil algae, as well as, to study the effect of these herbicides on the growth and some metabolic activities of some algae such as Scenedesmus quadricauda (Chlorophyta) and Merismopedia glauca (Cyanophyta) which isolated from the soil.

One of the inherent modeling problems in structural engineering is creep of quasi-brittle materials (e.g., concrete and masonry). The creep strain represents the non-instantaneous strain that occurs with time when the stress is sustained. Several creep models with limited accuracy have been developed within the last few decades to predict creep of concrete and masonry structures. The stochastic nature of creep deformation and its reliance on a large number of uncontrolled parameters (e.g., relative humidity, age of loading, stress level) makes the process of prediction difficult, and yet accurate mathematical model almost impossible. This study investigates the potential use of Dynamic Neural Network (DNN) for predicting creep of structural masonry. The main motive of use DNN is that DNN could memorize the sequential or time-varying patterns while training process. Thus, DNN becomes more capable of capturing the time-dependent of creep deformation than the static networks. The results showed that the developed DNN models are able to predict the creep deformation with an excellent level of accuracy compared with that of conventional methods and the static networks models.