The objective of this paper is to study the stability of SIS epidemic model involving treatment. Two types of such eco-epidemiological models are introduced and analyzed. Boundedness of the system is established. The local and global dynamical behaviors are performed. The conditions of persistence of the models are derived.

Background: The aim of this study was to measure the radiopacity (RO) of modified microhybrid composite resins by adding 2 types of nanofillers (Zinc Oxide and Calcium Carbonate) in two concentrations 3% and 5% and comparing them to unmodified microhybrid composite resins and to nanofilled composite resin. Materials and Methods: Two types of composite resin were used (Microhybrid composite MH Quadrent anterior shine and Nanofilled composite resin Filtek Z350 XT), for each tested group five disk-shaped specimens (1-mm-thick and 15 mm diameter) were fabricated. The material samples were radiographed together with the aluminum step wedge. The density of the specimens was determined with a transmission densitometer and was expressed in term of

In this article, we introduce a class of modules that is analogous of generalized extending modules. First  we define a module M to be a generalized ECS if and only if for each ec-closed submodule A of M, there exists a direct summand D of M such that  is singular, and then we locate generalized ECS between the other extending generalizations. After that we present some of characterizations of generalized ECS condition. Finally, we show that the direct sum of a generalized ECS need not be generalized ECS and deal with decompositions for be generalized ECS concept.

    In this article, the research presents a general overview of deep learning-based AVSS (audio-visual source separation) systems. AVSS has achieved exceptional results in a number of areas, including decreasing noise levels, boosting speech recognition, and improving audio quality. The advantages and disadvantages of each deep learning model are discussed throughout the research as it reviews various current experiments on AVSS. The TCD TIMIT dataset (which contains top-notch audio and video recordings created especially for speech recognition tasks) and the Voxceleb dataset (a sizable collection of brief audio-visual clips with human speech) are just a couple of the useful datasets summarized in the paper that can be used to test A

The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog

The Internet of Things (IoT) is an information network that connects gadgets and sensors to allow new autonomous tasks. The Industrial Internet of Things (IIoT) refers to the integration of IoT with industrial applications. Some vital infrastructures, such as water delivery networks, use IIoT. The scattered topology of IIoT and resource limits of edge computing provide new difficulties to traditional data storage, transport, and security protection with the rapid expansion of the IIoT. In this paper, a recovery mechanism to recover the edge network failure is proposed by considering repair cost and computational demands. The NP-hard problem was divided into interdependent major and minor problems that could be solved in polynomial t