Anhydrous ammonia is a cheaper source of nitrogen (N) fertiliser than granular urea for rice production, but it is not widely used in developing countries. It can only be applied pre-crop with any in-crop applications being applied in the form of urea. This 2-year study conducted in the Nile delta region of Egypt compared pre-crop anhydrous ammonia injected to a depth of 20 cm with broadcast urea

Image registration is the process of using a reference image to map the input images to match the corresponding images based on certain features. It has the ability to assist the physicians in the diagnosis and following up on the patient’s condition. One of the main challenges of the registration is that it takes a huge time to be computationally efficient, accurate, and robust as it can be

Catheters are life support devices. Human expertise is often required for the analysis of X-rays in order to achieve the best positioning without misplacement complications. Many hospitals in underprivileged regions around the world lack the sufficient radiology expertise to frequently process X-rays for patients with catheters and tubes. This deficiency may lead to infections, thrombosis, and

In this Letter we highlight some fundamental errors in the paper “Origin of the Curie–von Schweidler law and the fractional capacitor from time-varying capacitance” [J. Pow. Sources 532 (2022) 231309] by V. Pandey. In particular, with the use of the convolution integral of linear time-varying capacitance with the time-derivative of voltage (i.e. Eq (9) as suggested by the author), one ends up with

Background: Systemic lupus erythematosus (SLE) is an autoimmune disease with inflammatory nature. One of the leading causes of death in SLE patients is cardiovascular (CVS) morbidity. MiRNA-24 is highly expressed in vascular endothelial cells (VECs). This dysregulated expression pattern is associated with dysfunction or even damage of VECs and leads to the occurrence of cardiovascular diseases

Impedance spectroscopy has become a standard electroanalytical technique to study (bio)electrochemical and physiological systems. From an instrumentation point of view, the measurement of impedance can be carried out either in the frequency domain using the classical frequency sweep method or in the time domain using a variety of broadband signals. While time-domain techniques can be implemented

The purpose of this study is to investigate the gradual incorporation of deep learning in the dental healthcare system, offering an easy and efficient diagnosis. For that, an electronic search was conducted in the Institute of Electrical and Electronics Engineers (IEEE) Xplore, ScienceDirect, Journal of Dentistry, Health Informatics Journal, and other credible resources. The studies varied with

Large deep neural network (DNN) models are computation and memory intensive, which limits their deployment especially on edge devices. Therefore, pruning, quantization, data sparsity and data reuse have been applied to DNNs to reduce memory and computation complexity at the expense of some accuracy loss. The reduction in the bit-precision results in loss of information, and the aggressive bit

Deep Neural Networks (DNNs) are computationally and memory intensive, which present a big challenge for hardware, especially for resource-constrained devices such as Internet-of-Things (IoT) nodes. This paper introduces a new method to improve DNNs performance by fusing approximate computing with data reuse techniques for image recognition applications. First, starting from the pre-Trained network

The rapidity distribution of well-identified particles such as pions, kaons, protons and their antiparticles measured in AGS, SPS, and BRAHMS experiments (Au+Au collisions), at various energies spanning from higher energies sNN = 200 down to lower energies 2 GeV, are compared with that obtained from huge statistical ensembles of 100, 000 events generated from the Cosmic Ray Monte Carlo (CRMC) EPOS