Smart antenna arrays with adaptive nulling capability are emerging as a promising solution to suppress the interference in radar applications and wireless communications in real time. Many adaptive nulling methods have been commonly used, such as controlling amplitude or/and phase excitations of the antenna elements and controlling the position of the elements. Generally, most adaptive nulling methods demand digital beamforming to create the correlation matrix from signals that arrived to array antennas. The digital beamforming is costly and needs frequent calibration; therefore, it does not appropriate for large antenna arrays. Among adaptive nulling methods, an array thinning does not require digital beamforming. It takes advantage of the adaptive algorithm to make the element active or inactive. In this paper, an IFT and Chebyshev techniques based random thinning are presented to suppress the interference adaptively by lowering the SLL or placing nulls toward the interference direction. The proposed method works with the antenna arrays that have transmit/receive modules (TRM) with RF switches. The results show the ability of both IFT and Chebyshev techniques to suppress the interference for the small array. In addition, the results indicate the superiority of IFT technique over Chebyshev in large arrays; it is considerably faster and more efficient (in terms of lowering the sidelobe levels and nulls formation) than the Chebyshev technique. The advantage of the proposed method is no digital beamforming is needed. Consequently, a considerable reduction in complexity, power consumption, and cost can be attained.
The interaction of electromagnetic (EM) waves with the COVID-19 virus is studied to define the frequencies that cause maximum energy absorption by the virus and the power level needed to cause a lethal temperature rise. The full-wave EM simulator is used to model the virus and study the effects of its size and dielectric properties on the absorbed power across a wide range of frequencies. The results confirm potential resonance conditions, where specific frequencies produce maximum absorption and subsequent temperature rise that can destroy the virus. Furthermore, the study confirms that maximum power deposition in the virus occurs at specific wavelengths depending on its size. Also, the simulation is used to find the power required to destroy the virus and determine the total power required to destroy it in an oral activity, such as coughing, made by infected individuals. Furthermore, the study explained why irradiation by UV-C band is effective to decrease virus activity or even eradicate it.
The aim of study is to measure osteoporosis in the right foot at the heel (calcaneus) by using the quantitative ultrasound (QUS) technique. It was measured (SOS, BUA, BQI, T-score and Z-score). While the usage of the DXA technique is measure the tissue thickness. Osteoporosis represents low bone mineral density (BMD). The heel of the foot (calcaneus) uses in QUS measurements because it contains a high ratio of trabecular bone. T-score is the predominant the diagnosis of osteoporosis used for adults, men and women over 50 years. From T-score can be to know the ratio of BMD, according to the WHO a T-score can be classified (Normal, Osteopenia and Osteoporosis). Age group 31-40 years was T-score for both sex (-0.667) is meaning (Normal bone). In the age group, 51-60 years was T-score (-1.60) for both sex represents (osteopenia). While age group 71-80 years T-score for females (-2.56) and males (-3.30), means that both males and females have (osteoporosis). P-value
The compact switched-capacitor converter with exponential gain and modular design has been adopted in this paper. Two approaches have been applied to improve the efficiency by providing multiple no-load voltages. The first modifies the switching strategy to bypass the gain of one or more stages. The second introduces modified design that provide additional no-load voltages through alternative current paths. The voltage regulation is implemented by two control loops: The outer loop is designed to produce the minimum feasible no-load voltage and the inner loop adjusts the duty ratio of the switching signals to regulate the voltage to meet the desired reference. Switched capacitor converters have been used as voltage multipliers with constant voltage gain. The efficiency of a switched capacitor converter depends on the ratio between regulated to unregulated output voltage. Therefore, output voltage adjustment of these converters causes a significant efficiency reduction. By providing multiple no-load voltages within the output voltage range the efficiency of the switched capacitor converter can be improved. The proposed design has been applied to a three-stage converter to provide six no-load voltages. Simulation results demonstrate that the average efficiency over the entire output voltage range is more than 90 % of its maximum efficiency of the unregulated switched capacitor converter which reflects the effectiveness of the proposed scheme. This paper offers an efficient method to regulate the voltage of a modular switched capacitor converter with exponential gain. The advantages of the proposed design are small number of added components, does not require additional sources and suitable for higher power range
With the widespread adoption of smart metres in the power sector, anomaly detection has become a critical tool for analysing customers' unusual consumption patterns and network traffic. Detecting anomalies in power consumption and communication is primarily a real‐time big data analytics issue regarding data mining along with a vast number of parallel streaming data from smart metres. In this study, an embedded Intrusion Detection and Prevention System (IDPS) is proposed as a Wifi‐based smart metre for Home Area Networks (HANs) in the Advanced Metering Infrastructure (AMI) network. So, the proposed system employs one machine learning model based on IDPS to guard the HAN network from various attacks that utilise the Message Queueing Telemetry Transport protocol between the smart metre and IoT sensors. Also, it uses two machine learning models to detect the abnormality in periodic and daily data metering respectively. So, multiple algorithms have been used to find the suitable algorithm for each of the three anomaly detection models. These models have been evaluated and tested using real data sets regarding resources usage and detection performance to demonstrate the efficiency and effectiveness of using machine learning algorithms in the built anomaly detection models. The experiments show that the anomaly detection models performed well for various abnormalities.
Background: COVID-19 disease was highly infectious causing a declaration of a global pandemic and the scientists believed that developing a safe and effective vaccine was the solution. Various vaccine candidates were announced by different health authorities. Many factors affect the acceptance of vaccines. This study aims to explore the perceptions, attitudes, and expectations of healthcare professionals (HCPs) toward COVID-19 vaccines. Method: A qualitative study approach was conducted by using face-to-face semi-structured interviews with HCPs in Mosul city, Iraq. Results: Twenty-five HCPs participated in the interviews. After qualitative analysis four main themes emerged: perception of vaccines; participants believed that vaccines were vital inventions, motivations to take the vaccine; most HCPs were motivated based on the scientific evidence regarding COVID-19 vaccines, expectations about the safety and efficacy of COVID-19 vaccines; participants had different opinions based on the type of the vaccine and the available data, side effects experienced; severe side effects were expected but only mild adverse reactions were experienced by the majority. Conclusion: HCPs had good knowledge about COVID-19 vaccines which was not affected by rumors and misin formation. In contrast to their expectations, the experienced side effects of the first and the second doses were mild to moderate in severity. The majority of HCPs based their choice of the vaccine on the efficacy and safety profile of the available options.
Objectives - to provide a view on the frequency, and the risk factors of placenta accreta spectrum disorders (PAS) in Nineveh Province, and to assess the morphological alterations associated with these disorders. A prospective and retrospective cross-sectional study was carried out on paraffinized blocks of 19 females, with gestational age ≥32 weeks, presented with peripartum haemorrhage and subjected to emergency hysterectomy at Maternity Teaching Hospitals, Nineveh Province, North of Iraq. Clinical data, including the mother's age and obstetrics history, were recorded when available. All cases were examined for the presence or absence of histological invasion of placentas supported by immunohistochemistry. The mean age of cases was 34.4±1.6 years by the dominance of the fourth decade. The mean gestational age at the time of diagnosis was 35.6±0.8 weeks. The PAS frequency was increasing and reaching up to 1.18 per 1000 live birth. About 60% of the cases gave a history of previous Cesarean section with or without a concomitant placenta previa. According to light microscopic examination, placenta accreta spectrum disorders were identified in 12(63.1%) cases. The immune expression of cytokeratin was significantly correlated with placental invasion, (p=0.001). The present study reveals an increase in the frequency of abnormal placentation in Nineveh Province. These disorders have well-known predisposing factors. The histo-pathological findings, other than interface decidual loss, may explain the abnormality in placental tissue implantation.
In locations where power is restricted, such as off-grid, solar, and generator-powered houses, considering the capacity of the power source is critical for the effectiveness of home automation systems. During regular power system outages, millions of houses all over the globe are reliant on a fixed current power supply to keep their lights on. In such circumstances, prioritizing and arranging the home's workload is essential. The goal of this paper is to decrease the amount of effort required by the user to manually control a gadget. To connect with the Raspberry Pi and the users, this system makes use of Google Assistant Software Development Kit (SDK), which is offered by Google. Users use voice commands to manage the devices in their homes, check the amount of current available, and chat to the Google Assistant to turn on/off the smart switch. This paper suggests using a sensor, Message Queuing Telemetry Transport (MQTT) protocol, a controller (OpenHAB open source), and an actuator in conjunction with each other (smart switch) has the capability of measuring and monitoring the entire power that is available and making choices based on that knowledge. Finally, the usage of Google Assistant as an artificial intelligence system makes end-user engagement with the smart home more pleasant. The proposed network was executed in both unlimited and limited power or electrical current modes to compare the standard unlimited smart home setup and our current control design. The system was programmed to function based on the proposed algorithm, with a 10 Ampere as a maximum available current. The water heater was considered a low priority load in this trial as a heavy load. In this system’s run, the smart controller was continuously monitoring the load, and when the total load reaches 10 Amperes or above it turns off the low priority loads. Thus, preventing the power supply overload.
Abstract. Fifty blood samples were collected from patients who were confirmed to have COVID-19 by conducting a diagnostic test using real-time RT-PCR for the direct qualitative detection of the Coronavirus when the patients attended the private clinics at Al Rabeea Private Hospital in Mosul for the period from the beginning of March to the end of May 2021. The patients’ ages range from17-59 years, with 23 males (46%), and 27 females (54%). The blood samples were taken before giving any type of treatment for blood culture, biochemical, and immunological tests. Bacteremia is investigated to determine the types of bacteria that cause bacteremia, biochemical tests such as D-dimer, S. Ferritin, CRP, Protein S, Protein C, FBS, LDH, Blood Urea, Serum Creatinine, SGOT & SGPT, and immunological tests such as blood group, IgG & IgM, IL-1B, IL-6, TNF-α alpha, ASOT, ESR, C3, and C4. In this study, the relationship between bacteremia and the types of biomarkers used is determined in addition to the relationship of bacteremia to the patient's age, sex, SPO2, and body temperature. More accurate comparison is also accomplished in cases of bacteremia by adopting the types of bacteria isolated if they were gram-positive or gram-negative. The results of this study show an increase in the severity of COVID-19 disease caused by a secondary bacterial infection. This is determined by measuring several biomarkers used in this study and also by performing bacteriological tests to document bacteremia by blood culture. Also, these results can be adopted in future studies concentrating on the molecular level to determine the genetic changes associated with viral infection with or without secondary bacterial infection to develop an effective treatment protocol. Key words. COVID-19, Blood culture, Bacteremia, Biomarkers.
Growth hormone deficiency is one of the major causes of short stature in children. It has been noted that hormonal treatment can be vindicated in short-stature children unless there are contraindications. This study aimed to investigate the impact of rhGH therapy duration on the increase of subjects' height at the end of therapy. Materials and methods: A retrospective longitudinal study of children diagnosed with short stature was followed. Participants aged between 5 and 15 years old who had their GH stimulation test done were included in the study. Collected data were patients' age, gender, rhGH therapy duration and height (cm) at presentation and the end of therapy. GH stimulation test readings and bone age were also gathered. Results: 129 children aged between 5-15 years of both gender were included in the study. They were grouped into three groups according to the duration of the received GH therapy: an 8-month group (n=25), a 14-month group (n=59) and 22-month group (n=45). No significant difference between males and females in regards to bone age, but the readings significantly increased with the increase in therapy duration (p<0.05). Growth hormone assay results were conversely reduced with the increase in GH therapy duration, with no significant difference between the two genders. Interestingly, an increase in the participant's height in the three treatment groups both males and females were reported. Overall, the increase in height was 7.08 cm, 12.58 cm and 20.84 cm in 8, 14 and 22-month groups (± 1.6, 3.3 and 4.3), respectively, a significant statistical difference between the three groups (p-value <0.05). This study provides evidence of the effect of long-term 22-month rhGH therapy on bone age and body height both in male and female children. Further prospective studies are required to assess the effect of the GH stimulation test on GH therapy.
One of the most prevalent over-the-counter cold and cough medications is the chlorpheniramine maleate (CPM)–ibuprofen (IBF) combination. A reversed-phase high-performance liquid chromatography (RP-HPLC) method was effectively optimized and developed for the simultaneous detection of chlorpheniramine maleate and ibuprofen in a pharmaceutical formulation. The mobile phase for the RP-HPLC method was an isocratic combination of acetonitrile and 0.01 M acetate buffer at pH 3.8 (55:45; v/v) on an Eclipse Plus C18 reversed phase column. An ultraviolet (UV) detector with a wavelength of 225 nm was used to detect the analytes at a flow rate of 1.0 mL/min. CPM and IBF were satisfactorily eluted, with mean retention times of 2.09 and 6.27 min, respectively. The approach was shown to be linear (R2 > 0.9998 for CPM and 0.9992 for IBF), precise (% RSD 3.02% for CPM and 3.48% for IBF), accurate (% recoveries 97.7–98.9% for CPM and 101–104.5% for IBF), specific, easy to use, sensitive, quick, and robust. Limits of detection (LODs) were found to be 10 and 27 μg/mL for CPM and IBF, respectively. Without interference from excipients, the validated method could be utilized in regular quality control analysis of various dosage combinations of hard gelatin capsules containing CPM and IBF.
Background and objective: Helicobacter pylori can be regarded as one of the most common causes of chronic gastritis, which affects more than half of the world’s population. This study aimed to assess the presence of H. pylori in patients with gastritis and its association with gastric inflammation and adenocarcinoma. Methods: The presence of H. pylori was detected by rapid urease test and histopathological tests using biopsy specimens. Data were analyzed using the GraphPad Software Statistical Package. Results: The mean age of patients ± SD was 47.41 ± 18.13 years. The age range was 13 to 90 years. Results showed a significant association between the intensity of H. pylori and inflammation (P = 0.001). The more the intensity of H. pylori, the more severe the inflammation was noticed. Patients with high intensity of H. pylori had positive lymphoid aggregates. The H. pylori positive for the rapid urease test and the hematoxylin and eosin (H&E) staining test were 95.2% and 96.3%, respectively. H. pylori infection was detected in more than 85% of patients with gastric adenocarcinoma. Conclusion: Histopathology and rapid urease tests are reliable diagnostic tools for detecting H. pylori. Results revealed a significant association of chronic active gastritis, mucosal lymphoid follicle formation, and adenocarcinoma with H. pylori infection.
In order to solve general seventh-order ordinary differential equations (ODEs), this study will develop an implicit block method with three points of the form y(7)(x) = f (x, y(x), y0(x), y00(x), y000(x), y(4)(x), y(5)(x), y(6)(x)) directly. The general implicit block method with Hermite interpolation in three points (GIBM3P) has been derived to solve general seventh-order initial value problems (IVPs) using the basic functions of Hermite interpolating polynomials. A block multi-step method is constructed to be suitable with the numerical approximation at three points. However, the construction of the new method has been presented while the numerical results of the implementations are used to prove the efficiency and the accuracy of the proposed method which compared with the RK and RKM numerical methods together to analytical method. We established the characteristics of the proposed method, including order and zero-stability. Applications of various IVP problems are also discussed, and the outcomes are very encouraging for the suggested approach. The proposed GIBM3P method yields more accurate numerical solutions to the test problems than the existing RK method, which are in good agreement with analytical and RKM method solutions.
The present work investigated numerically, using SCAPS software, the impact of conduction band alignment between the absorber and electron transport layer (ETL) on the perovskite solar cell performance. The conduction band alignment was tailored by inserting an interfacial thin layer between the absorber and ETL. The architecture of the proposed structure consists of CdS as an electron transport layer, MAPbI3 as an absorber layer, and the spiro-OMeTAD as a hole transport layer (HTL). Before inserting the interfacial layer, an adjustment of the doping density of ETL and HTL and the thickness of the perovskite solar layers have been optimized to obtain the best PSC performance. It was found that the best power conversion efficiency of 18% was obtained at a doping density of 10²² cm⁻³ for ETL and 10¹⁹ cm⁻³ for HTL and thickness of 250nm, 400nm, and 200nm for ETL, absorber, and HTL respectively. Individual interfacial layers, with different electron affinities, are sandwiched between the CdS/Perovskite layers to achieve different conduction band alignments. Based on the electron affinity of inserted layer, different structures from spike and cliff in the conduction band alignment were achieved. The results reveal that the inserted interfacial layer improved the solar cell performance when the inserted layer produce a spike-cliff conduction band offset at the absorber-interfacial layer interface and interfacial layer-ETL interface respectively.
Background: The global pandemic of coronavirus disease is a societal, economic, and publichealth crisis that is still underway. The spike glycoprotein of SARS-CoV-2 is one of the primary ingredients for virulence, tissue tropism, and host areas. Aim: This study aimed to determine mutations in the S protein of the Iraqi COVID-19 isolates. Full genome sequences of Iraqi strains were obtained from GISAID. Using statistical saturation mutagenesis and other informatics methods, we investigated 20 sequences of SARS-CoV-2 S protein missense mutation isolates in Iraq selected from NCBI. The following mutations were detected for all the strains under study compared to the wild type: L452R, A522V, E583D and D614G. The number of mutations in the strains was different depending on the location of the state from which the sample was collected The D614G mutation was found in 19 strains. One strain had three mutations, while the other was a wild form strain. The structure of the mutant protein changes dramatically, as does the energy of the atoms concerning the docking position, affecting the protein's stability. The mutation sites would improve the S protein's stability. Molecular docking of RBD-ACE2 is affected differently by residues L452R and A522V.
Electroencephalography (EEG) signals acquire a lot about the brain functionality, its different patterns employed in brain diseases recognition, and recently used in Brain Computer Interface (BCI) systems. Automatic recognition of these patterns gains a lot of attention nowadays. These EEG signals are contaminated with artifacts like eye and muscle movement artifacts. Fine tuning of these signals and automatic rejection of artifacts prior to feature extraction is straightforward. In this paper, a novel method for artifact cancelation based on signal statistics with modification of independent sources extracted by Independent Component Analysis (ICA) of EEG signals is suggested. Visual inspection of the reconstructed signals shows the validity of the proposed method in artifact rejection. Moreover, this method did not require any extra information channel attached with EEG signals.
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