Gypseous soil is a collapsible soil, which causes large deformations in buildings that are constructed on it. Various methods have been used to minimise this effect, such as replacing the gypseous soil or using soil stabilisation (grouting or soil improvement). This study was carried out on four types of gypseous soils that have different properties and various gypsum contents. The testing was carried out on remoulded samples to evaluate the compressibility of gypseous soil under different conditions. The samples were grouted with acrylate liquid. The relationships between the injection pressure and the radius of flow, between time of injection and radius of flow, and between time and quantity of acrylate liquid are investigated on

Eruca sativa (jarjeer) is an annual herb (family Brassicaceae), which contains a wide range of chemicals and minerals with nutraceutical and organoleptic characteristics. Jarjeer was generally used as a food and traditionally mainly consumed due to its aphrodisiac properties. This crop known to contain various phytochemicals such as flavonoids, phenolic acids, terpens, carotenoids, tannins, glycosides, saponins, sterols, alkaloids, and other secondary metabolites. In leaves, kaempferol and its derivatives, glucosativin, are the main flavonoids and glucosinolate, respectively, while erucic acid and glucoerucin are the main fatty acid and glucosinolate, respectively. Medicinally, the plant has antibacterial, antidiabetic, antihyperten

In this paper, a new seven-parameter Mittag-Leffler function of a single com-plex variable is proposed as a generalization of the standard Mittag-Leffler function, certain generalizations of Mittag-Leffler function, hypergeometric function and confluent hypergeometric function. Certain essential analytic properties are mainly discussed, such as radius of convergence, order, type, differentiation, Mellin-Barnes integral representation and Euler transform in the complex plane. Its relation to Fox-Wright function and H-function is also developed.

In this study, a traumatic spinal cord injury (TSCI) classification system is proposed using a convolutional neural network (CNN) technique with automatically learned features from electromyography (EMG) signals for a non-human primate (NHP) model. A comparison between the proposed classification system and a classical classification method (k-nearest neighbors, kNN) is also presented. Developing such an NHP model with a suitable assessment tool (i.e., classifier) is a crucial step in detecting the effect of TSCI using EMG, which is expected to be essential in the evaluation of the efficacy of new TSCI treatments. Intramuscular EMG data were collected from an agonist/antagonist tail muscle pair for the pre- and post-spinal cord lesi