A grasshopper optimizer approach for feature selection and optimizing SVM parameters utilizing real biomedical data sets

Neural Computing and Applications - Support vector machines (SVM) are one of the important techniques used to solve classifications problems efficiently. Setting support vector machine kernel...     

Best path in mountain environment based on parallel A* algorithm and Apache Spark

The Journal of Supercomputing - Pathfinding problem has several applications in our life and widely used in virtual environments. It has different goals such as shortest path, secure path, or...     

Remote Sensing and GIS Application in the Detection of Environmental Degradation Indicators

The main aim of this research is to highlight the environment change indicators during the last 20 years in a representative area of the southern part of Iraq (Basrah Province was taken as a case) to understand the main causes which led to widespread environment degradation phenomena using a 1:250000 mapping scale. Remote sensing and GIS's software were used to classify Landsat TM in 1990 and Landsat ETM+ in 2003 imagery into five land use and land cover (LULC) classes: vegetation land, sand land, urban area, unused land, and water bodies. Supervised classification and Normalized Difference Vegetation Index (NDVI),Normalized Difference Build-up Index (NDBI), Normalized Difference Water Index (NDWI), Normalized Difference Salinity Index (NDSI), and Topsoil Grain Size Index (GSI) were adopted in this research and used respectively to retrieve its class boundary.The results showed a clear deterioration in vegetative cover (514.9 km2) and an increase of sand dune accumulations (438.6 km2),accounting for 10.1, and 10.6 percent, respectively, of the total study area. In addition, a decrease in the water bodies' area was detected (228.9 km2). Sand area accumulations had increased in the total study area, with an annual increasing expansion rate of(33.7 km2·yr-1)during the thirteen years covered by the study.It is therefore imperative that Iraqi government undertake a series of prudent actions now that will enable to be in the best possible position when the current environmental crisis ultimately passes.     

A cleaner enzymatic approach for producing non-phthalate plasticiser to replace toxic-based phthalates

Clean Technologies and Environmental Policy - Dioctyl phthalate (DOP) is industrially commonly used as a polyvinyl chloride (PVC) plasticiser. As DOP does not form a chemical link with PVC, it...     

IoT & AI Enabled Three-Phase Secure and Non-Invasive COVID 19 Diagnosis System

Corona is a viral disease that has taken the form of an epidemic and is causing havoc worldwide after its first appearance in the Wuhan state of China in December 2019. Due to the similarity in initial symptoms with viral fever, it is challenging to identify this virus initially. Non-detection of this virus at the early stage results in the death of the patient. Developing and densely populated countries face a scarcity of resources like hospitals, ventilators, oxygen, and healthcare workers. Technologies like the Internet of Things (IoT) and artificial intelligence can play a vital role in diagnosing the COVID-19 virus at an early stage. To minimize the spread of the pandemic, IoT-enabled devices can be used to collect patient’s data remotely in a secure manner. Collected data can be analyzed through a deep learning model to detect the presence of the COVID-19 virus. In this work, the authors have proposed a three-phase model to diagnose covid-19 by incorporating a chatbot, IoT, and deep learning technology. In phase one, an artificially assisted chatbot can guide an individual by asking about some common symptoms. In case of detection of even a single sign, the second phase of diagnosis can be considered, consisting of using a thermal scanner and pulse oximeter. In case of high temperature and low oxygen saturation levels, the third phase of diagnosis will be recommended, where chest radiography images can be analyzed through an AI-based model to diagnose the presence of the COVID-19 virus in the human body. The proposed model reduces human intervention through chatbot-based initial screening, sensor-based IoT devices, and deep learning-based X-ray analysis. It also helps in reducing the mortality rate by detecting the presence of the COVID-19 virus at an early stage.     

A hybrid job scheduling algorithm based on Tabu and Harmony search algorithms

The Journal of Supercomputing - Nowadays, cloud computing became a very important way of processing very large and complicated jobs and services. To serve millions of users with a high satisfaction...     

Constructal design of vertical multiscale triangular fins in natural convection

Constructal design of vertical multiscale triangular fins in natural convection is investigated in this paper. The design consists of two parts. The first part is for single-scale triangular fins. The objective in the first design is to reach to the highest heat transfer density from the fins for three fin angles (15°, 30°, and 45°). The single-scale fins are placed in a horizontal array and considered as isothermal fins. The degrees of freedom are the fin angle, and the fin-to-fin spacing. The constraint is the fin height. The second part is for multiscale fins where small fins are placed between the large fins which are optimized in the first part. In the second part, the angles of the large and small scales fins are kept constant at (15°). The optimal fin-to-fin spacing which is obtained in the first part is considered a constraint in the second part. The Rayleigh numbers in this design are (Ra = 10³, 10⁴, and 10⁵). The two-dimensional mass, momentum, and energy equations for natural convection are solved with the finite volume method. The results show that there is a benefit of placing the small-scale fins where the percentage increase in the heat transfer density is (10.22%) at (Ra = 10³), and (50.6%) at (Ra = 10⁵) due to existence of the small fins between the large fins.     

Novel Nitrogen-Based Chalcone Analogs Provoke Substantial Apoptosis in HER2-Positive Human Breast Cancer Cells via JNK and ERK1/ERK2 Signaling Pathways

Natural chalcones possess antitumor properties and play a role as inducers of apoptosis, antioxidants and cytotoxic compounds. We recently reported that novel nitrogen chalcone-based compounds, which were generated in our lab, have specific effects on triple-negative breast cancer cells. However, the outcome of these two new compounds on human epidermal growth factor receptor 2 (HER2)-positive breast cancer remains nascent. Thus, we herein investigated the effects of these compounds (DK-13 and DK-14) on two HER2-positive breast cancer cell lines, SKBR3 and ZR75. Our data revealed that these compounds inhibit cell proliferation, deregulate cell-cycle progression and significantly induce cell apoptosis in both cell lines. Furthermore, the two chalcone compounds cause a significant reduction in the cell invasion ability of SKBR3 and ZR75 cancer cells. In parallel, we found that DK-13 and DK-14 inhibit colony formation of both cell lines in comparison to their matched controls. On the other hand, we noticed that these two compounds can inhibit angiogenesis in the chorioallantoic membrane model. The molecular pathway analysis of chalcone compounds exposed cells revealed that these compounds inhibit the expression of both JNK1/2/3 and ERK1/2, the major plausible molecular pathways behind these events. Our findings implicate that DK-13 and DK-14 possess effective chemotherapeutic outcomes against HER2-positive breast cancer via the ERK1/2 and JNK1/2/3 signaling pathways.     

Electrophoretic deposition of hydroxyapatite‐shrimp crusts nanocomposite thin films for bone implant studies

Hydroxyapatite‐shrimp crusts nanocomposite thin films were deposited on titanium substrates by electrophoretic technique, under different preparation conditions, for bone implant applications. Fourier transform infrared spectrometer, atomic force microscope, X‐ray diffraction (XRD), optical microscope, and scanning electron microscope were employed to characterise the synthesised films. Vickers’ micro‐hardness measurements revealed a value of 502 HV for the hydroxyapatite films and 314.55 HV for the nanocomposite films. XRD results confirmed the polycrystalline nature of the hydroxyapatite and hydroxyapatite‐shrimp nanocomposite films. The in‐vitro bioactivity test of the synthesised films in simulated body fluid showed very low dissolution rate. Antibacterial activity of synthesised films was investigated against E. coli bacteria.Inspec keywords: electrophoretic coating techniques, thin films, nanocomposites, antibacterial activity, bone, prosthetics, nanomedicine, calcium compounds, bioceramics, nanofabrication, Fourier transform infrared spectra, atomic force microscopy, X‐ray diffraction, optical microscopy, scanning electron microscopy, Vickers hardness, microhardness, microorganisms, dissolvingOther keywords: Ti, Ca₁₀ (PO₄)₆ (OH)₂ , E. coli bacteria, antibacterial activity, dissolution rate, simulated body fluid, in‐vitro bioactivity test, polycrystalline nature, Vickers microhardness measurements, XRD, scanning electron microscopy, optical microscopy, X‐ray diffraction, atomic force microscopy, Fourier transform infrared spectrometer, bone implant applications, titanium substrates, hydroxyapatite‐shrimp crust nanocomposite thin films, electrophoretic deposition     

A hybrid system for Parkinson’s disease diagnosis using machine learning techniques

International Journal of Speech Technology - Parkinson’s disease is a neurodegenerative disorder that progresses slowly and its symptoms appear over time, so its early diagnosis is not easy....