Abstract: Plastic pollution is a major issue of the current century. This waste is found in seas, freshwater, lakes, rivers, coastal areas, and soil. In this article, this article discusses the various sources of plastic pollution, including the manufacturing process of plastics and the addition of materials to improve their properties, as well as the use of single-use plastics that are not recyclable, in addition to burning and illegal waste disposal in the open. The impact on public health is through human exposure to toxins from plastics in the environment directly through inhaling dust and fumes, consuming contaminated food and drink, and skin contact. Indirectly, when marine creatures consume microplastics, they will find their way

Rotational Piezoelectric Energy Harvesting (RPZTEH) is widely used due to mechanical rotational input power availability in industrial and natural environments. This paper reviews the recent studies and research in RPZTEH based on its excitation elements and design and their influence on performance. It presents different groups for comparison according to their mechanical inputs and applications, such as fluid (air or water) movement, human motion, rotational vehicle tires, and other rotational operational principal including gears. The work emphasises the discussion of different types of excitations elements, such as mass weight, magnetic force, gravity force, centrifugal force, gears teeth, and impact force, to show their effect

Isatin is a heterocyclic molecule that belongs to one of the most important classes of organic compounds known as indolines. Isatin, isatin analogs, and their Schiff bases have recently attracted a lot of attention in medicinal chemistry. Isatin, itself, shows various biological activities such as antiviral, anticancer, antimicrobial, anti-inflammatory, analgesic, antioxidant, and anticonvulsant. Bis- Schiff bases containing isatin moiety have been known to possess a wide spectrum of pharmacological activities. This review offers up-to-date information on the most active isatin bis-Schiff bases, which would include anticancer, antimicrobial, antiviral, anticonvulsant, anti-inflammatory, and analgesic activities. These observations c

Ziegler and Nichols proposed the well-known Ziegler-Nichols method to tune the coefficients of PID controller. This tuning method is simple and gives fixed values for the coefficients which make PID controller have weak adaptabilities for the model parameters variation and changing in operating conditions. In order to achieve adaptive controller, the Neural Network (NN) self-tuning PID control is proposed in this paper which combines conventional PID controller and Neural Network learning capabilities. The proportional, integral and derivative (K_P, K_I, K_D) gains are self tuned on-line by the NN output which is obtained due to the error value on the desired output of the system under control. The conventio

The road transportation system is considered as major component of the infrastructure in any country, it affects the developments in economy and social activities. The Asphalt Concrete which is considered as the major pavement material for the road transportation system in Baghdad is subjected to continuous deterioration with time due to traffic loading and environmental conditions, it was felt that implementing a comprehensive pavement maintenance management system (PMMS), which should be capable for preserving the functional and structural conditions of pavement layers, is essential. This work presents the development of PMMS with Visual inspection technique for evaluating the Asphalt Concrete pavement surface condition; common types o

Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration

Recently, the phenomenon of the spread of fake news or misinformation in most fields has taken on a wide resonance in societies. Combating this phenomenon and detecting misleading information manually is rather boring, takes a long time, and impractical. It is therefore necessary to rely on the fields of artificial intelligence to solve this problem. As such, this study aims to use deep learning techniques to detect Arabic fake news based on Arabic dataset called the AraNews dataset. This dataset contains news articles covering multiple fields such as politics, economy, culture, sports and others. A Hybrid Deep Neural Network has been proposed to improve accuracy. This network focuses on the properties of both the Text-Convolution Neural