Multiband Handset Antenna System for UMTS/LTE/WLAN/Sub-6 5G and mmWave 5G Future Smartphones

In this paper, a new antenna system for rapidly emerging multifunction devices is presented. The proposed antenna system consists of four antenna components each one operating at different frequency bands separately. The designed antennas are isolated and integrated on a single substrate. The first antenna is designed to operate at 1920–2170 MHz covering the UMTS band, whereas the second antenna is proposed for the lower band 5G systems and WiMAX operating within the frequency range of 3.4–4.2 GHz. Furthermore, another antenna is designed to cover the higher band 5G system and the IEEE 820.11a WLAN within the frequency range of 5.1–5.85 GHz. Finally, a 28 GHz bowtie-based MIMO antenna array is designed and simulated for the mmWave future 5G mobile networks. The proposed antennas were designed and simulated by using CST microwave studio. The results showed that all of the proposed antennas exhibited excellent reflection characteristics below −20 dB at the resonant frequency and achieved high radiation efficiency reached 99% in some cases with a peak gain ranging between 4–6 dBi. The proposed antenna system helps smartphones to perform multitasks and achieve a better-quality operation especially with the enormous growth of IoT techniques

Blood storage impacts on the hematological indices of healthy subjects and patients with iron-deficiency anemia and beta-thalassemia – A comparative study

Background: There are scientific evidence confirmed specific changes in blood cell counts, reducing the efficacy and feasibly the safeness of blood transmission when storing blood at 4°C for 5 weeks or more. Objectives: The study aimed to investigate the effects of stored blood obtained from healthy subjects and patients with anemia due to iron deficiency and beta-thalassemia, on hematological indices. Materials and Methods: A total of 37 participants, consisting of 14 healthy subjects, 13 patients with iron-deficiency anemia, and 10 patients with beta-thalassemia minor, were recruited from Hiwa Hospital between November 2021 and July 2022. Blood samples were obtained from the participants and stored at 4°C for 5 weeks. Hematological indices, including red cell distribution, platelet distribution width, and mean platelet volume, were determined using a hematology analyzer at weekly intervals. Results: Blood storage caused significantly increased mean values of hematological indices among healthy subjects as well as among patients with iron-deficiency anemia and beta-thalassemia, although the pattern of changes was differed. Conclusions: The storage of whole blood significantly increased hematological indices, showing variations in both healthy subjects and patients with iron-deficiency anemia and beta-thalassemia. The pattern of raise in these hematological indices is specific to iron-deficiency anemia and thalassemia when compared with healthy subjects

Parallel Implementation of Systolic Array Design for Developing Medical Image Rotation

Many image-processing algorithms are particularly suited to parallel computing, as they process images that are difficult and time consuming to analyse. In particular, medical images of tissues tend to be very complex with great irregularity and variability in shapes. Furthermore, existing algorithms contain explicit parallelism, which can be efficiently exploited by processing arrays. A good example of an image processing operation is the geometric rotation of a rectangular bitmap. This paper presents a set of systolic array designs for implementing the geometric rotation algorithms of images on VLSI processing arrays. The examined algorithm performs a trigonometric transformation on each pixel in an image.  The design is implemented as a distributed computing system of networked computers using Parallel Virtual Machine (PVM) model. Each node (computer) in the network takes part in the task in hand – such as image processing – using message passing. Comments and conclusions about the implementation of the design as a distributed computing system are discussed. Keywords: parallel computing, distributed computing. PVM, image rotation, systolic array

Image Content Analysis Using Neural Networks and Genetic Algorithms

The analysis of digital images for content discovery is a process of identifying and classifying patterns and sub-images that can lead to recognizing contents of the processed image. The image content analysis system presented in this paper aims to provide the machine with the capability to simulate in some sense, a similar capability in human beings. The developed system consists of three levels. In the low level, image clustering is performed to extract features of the input data and to reduce dimensionality of the feature space. Classification of the scene images are carried out using a single layer neural network, trained through Kohonen's self-organizing algorithm, with conscience function, to produce a set of equi-probable weights vector. The intermediate level consists of two parts. In the first part an image is partitioned into homogeneous regions with respect to the connectivity property between pixels, which is an important concept used in establishing boundaries of objects and component regions in an image. For each component, connected components can be determined by a process of component labeling. In the second part, feature extraction process is performed to capture significant properties of objects present in the image. In the high level; extracted features and relations of each region in the image are matched against the stored object models using the genetic algorithm approach. The implemented system is used in the analysis and recognition of colored images that represent natural scenes. Keywords: genetic algorithms, neural networks, image segmentation, clustering, image content analysis

Diabetes Detection System by Mixing Supervised and Unsupervised Algorithms

Diabetes mellitus is also called gestational diabetes when a woman has high blood sugar while pregnant. It can show up at any time during pregnancy and cause problems for the mother and baby during or after the pregnancy. If the risks are found and dealt with as soon as possible, there is a chance that they can be reduced. The healthcare system is one of the many parts of our daily lives that are being rethought thanks to the creation of intelligent systems by machine learning algorithms. In this article, a hybrid prediction model is suggested to determine if a woman has gestational diabetes. The recommended model reduces the amount of data using the K-means clustering method. Predictions are made using several classification methods, such as decision trees, random forests, SVM, KNN, logistic regression, and naive Bayes. The results show that accuracy increases when clustering and classification are used together

Signal Modulation Recognition System Based on Different Signal Noise Rate Using Artificial Intelligent Approach

Everyone has paid much attention to modulation-type recognition in the past few years. There are many ways to find the modulation type, but only a few good ways to deal with signals with a lot of noise. This study comes up with a way to test how well different machine learning algorithms can handle noise when detecting digital and analogue modulations. This study looks at the four most common digital and analogue modulations: Phase Shift Keying, Quadrature Phase Shift Keying, Amplitude Modulation, and Morse Code. A signal noise rate from -10dB to +25dB is used to find these modulations. We used machine learning algorithms to determine the modulation type like Decision Tree, Random Forest, Support Vectors Machine, and k-nearest neighbours. After the IQ samples had been converted to the amplitude of samples and radio frequency format, the accuracy of each method looked good. Still, in the format of the sample phase, each algorithm's accuracy was less. The results show that the proposed method works to find the signals that have noises. When there is less noise, the random forest algorithm gives better results than SVM, but SVM gives better results when there is more noise

Correlation Between the Estimated and the Measured Serum Apolipoprotein –B100 in Kurd Subjects: A Trend to Establish a New Formula

Apolipoprotein B100 (ApoB100) provides a good assessment of atherogenic lipoproteins (very low, intermediate, and low-density lipoproteins (VLDL, IDL, and LDL)). There is evidence that polymorphism of ApoB100 was observed in many conditions and it links with obesity, diabetes mellitus hypertension, and chronic inflammation, which could be related to the broad field of the atherothrombotic process, and could be one of the leading causes of coronary artery disease (CAD). It can be computed using a formula that makes use of a measurement of non-high-density lipoprotein levels. This study aimed to derive an estimated equation of ApoB100 from the measured ApoB100 levels specific to the healthy subjects of Kurd race/ethnicity in the Kurdistan region of Iraq taking into consideration the gender-based effect and the status of fasting and postprandial effects. A total number of 45 healthy subjects (23 males and 22 females) were enrolled in the study. The following measurements were achieved: anthropometric indices, blood pressure, lipid profile, including ApoB100, and blood sugar. The biochemical measurements were carried out at fasting and postprandial states. Specific equations were derived for calculating the levels of ApoB100. Significant differences in the anthropometric indices, blood pressure, and lipid profile were observed between males and females. The calculated ApoB100 levels were significantly less than the measured ApoB100 levels in both genders and fasting and postprandial states. The estimated equations for ApoB100 for females have differed from that for males at fasting and postprandial states. The levels of ApoB100 can be determined instead of measuring it in the laboratory by using a specific equation for healthy Kurd people. These equations are gender and race/ethnicity based. The established equation of estimated ApoB100 levels in males differed from that in females which is attributed to the cardio-metabolic factors and higher levels of systolic and mean arterial blood pressures among males. Apo B level is a quantitative index of plasma atherogenic lipids in hypertensive patients who presented with dyslipidemia

Dickkopf-3: An Update on a Potential Regulator of the Tumor Microenvironment

Dickkopf-3 (Dkk-3) is a member of the Dickkopf family protein of secreted Wingless-related integration site (Wnt) antagonists that appears to modulate regulators of the host microenvironment. In contrast to the clear anti-tumorigenic effects of Dkk-3-based gene therapies, the role of endogenous Dkk-3 in cancer is context-dependent, with elevated expression associated with tumor promotion and suppression in different settings. The receptors and effectors that mediate the diverse effects of Dkk-3 have not been characterized in detail, contributing to an ongoing mystery of its mechanism of action. This review compares the various functions of Dkk-3 in the tumor microenvironment, where Dkk-3 has been found to be expressed by subpopulations of fibroblasts, endothelial, and immune cells, in addition to epithelial cells. We also discuss how the activation or inhibition of Dkk-3, depending on tumor type and context, might be used to treat different types of cancers

Sitagliptin ameliorates the progression of atherosclerosis via down regulation of the inflammatory and oxidative pathways

Back ground: Atherosclerosis is the major cause of death. The most common risk factors are hyperlipidemia, diabetes, and other factors like chronic infection and inflammation. Objective: This study was undertaken to assess the effect of sitagliptin on atherosclerosis via interfering with inflammatory and oxidative pathways. Materials and Methods: A total of 18 local domestic male rabbits were included in this study. The animals were randomly divided into three groups (6 rabbits in each group): Group I normal were fed with chow (oxiod) diet for 12 weeks. Group II were fed with 1% cholesterol enriched diet for 12 weeks. Group III rabbits fed with cholesterol enriched diet for 6 weeks, and then continued on cholesterol enriched diet and treated with sitagliptin 125 mg/kg/day orally for the next 6 weeks. Blood samples were collected at the start of the study, at 6 weeks of the study and then at the end of treatment to measure serum lipids profile, hsCRP and TNFα. At end of the study, the aorta was removed for measurement of MDA, glutathione and, aortic intima-media thickness. Results: Sitagliptin results in a significant reduction (p < 0.05) in serum level of total cholesterol (TC), triglycerides (TG), high sensitive C-reactive protein (hsCRP) and TNFα with a significant increase (p < 0.05) in serum HDL level. There was a significant reduction (p < 0.05) in aortic MDA, in comparison to the untreated control group. Furthermore, sitagliptin causes significant increment (p < 0.05) in aortic GSH in comparison to induced untreated group. Regarding histopathological results, sitagliptin results in a significant reduction (p < 0.05) in atherosclerotic lesions in comparison to the induced untreated group and significant reduction in aortic intima-media thickness (p < 0.05). Conclusion: Sitagliptin reduced atherosclerosis progression in hyperlipidemic rabbit via its effect on lipid parameters and interfering with inflammatory and oxidative stress