Stabilization of 6H-Hexagonal SrMnO3 Polymorph by Al2O3 insertion

We demonstrate the structural evolution of polymorphic phases in Al₂O₃-inserted SrMnO₃ ceramics synthesized by solid state reaction. While the 4H-hexagonal phase is predominant in pure SrMnO₃ ceramics, a small amount of 6H-hexagonal polymorph is identified in addition to the primary 4H-hexagonal SrMnO₃ and the secondary hexagonal SrAl₂O₄ phases in the as-sintered ceramics, evidenced by x-ray diffraction and subsequent Rietveld refinement analyses. The existence of the 6H-hexagonal SrMnO₃ phase is corroborated using Raman spectroscopy. The chemical compositions and electronic structures of the Al₂O₃-inserted SrMnO₃ compounds are also examined using energy dispersive spectroscopy and x-ray photoelectron spectroscopy, respectively. The first-principles calculations reveal that there is no clear difference between the total energies of 4H- and 6H-hexagonal polymorphs regardless of the presence/absence of Sr and oxygen vacancies. Possible origins are discussed with the estimation of actual strain based on the refined lattice parameter of 6H SrMnO₃.     

Photoinitiated synthesis of poly(poly(ethylene glycol) methacrylate-co-diethyl amino ethyl methacrylate) superabsorbent hydrogels for dye adsorption

Random copolymers of poly(ethylene glycol) methacrylate (PEGM), and diethyl amino ethyl methacrylate (DEAEM) were synthesized at low, and high conversions by photoinitiation. Crosslinked poly(PEGM-co-DEAEM) samples were obtained, and characterized by FTIR, SEM, DSC, TGA, and elemental analyses. Swelling behavior of the copolymers revealed that the copolymers acted as superabsorbent hydrogels. The monomer reactivity ratios were calculated using Fineman Ross, Extended Kelen Tüdøs , and Mayo Lewis methods that gave r₁(PEGM) = 0.90, r₂(DEAEM) = 0.14 at low conversions. At high conversions r₁ and r₂ values were calculated as 1.01 and 0.40, respectively. Adsorption isotherms of methyl orange (MO) onto hydrogels were studied using Langmuir, Freundlich, and Temkin models. The experimental data fitted well with the Langmuir equation. The maximum adsorption capacity for MO was 212.7 mg g⁻¹ at pH = 3. The adsorption data gave best fit with the pseudo-second order kinetic model. Thermodynamic evaluation showed spontaneous nature for MO adsorption onto poly(PEGM-co-DEAEM) hydrogels. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47707.     

Automatic PV Grid Fault Detection System with IoT and LabVIEW as Data Logger

Fault detection of the photovoltaic (PV) grid is necessary to detect serious output power reduction to avoid PV modules’ damage. To identify the fault of the PV arrays, there is a necessity to implement an automatic system. In this IoT and LabVIEW-based automatic fault detection of 3 × 3 solar array, a PV system is proposed to control and monitor Internet connectivity remotely. Hardware component to automatically reconfigure the solar PV array from the series-parallel (SP) to the complete cross-linked array underneath partial shading conditions (PSC) is centered on the Atmega328 system to achieve maximum power. In the LabVIEW environment, an automated monitoring system is developed. The automatic monitoring system assesses the voltage drop losses present in the DC side of the PV generator and generates a decimal weighted value depending on the defective solar panels and transmits this value to the remote station through an RF modem, and provides an indicator of the faulty solar panel over the built-in Interface LabVIEW. The managing of this GUI indicator helps the monitoring system to generate a panel alert for damaged panels in the PV system. Node MCU in the receiver section enables transmission of the fault status of PV arrays via Internet connectivity. The IoT-based Blynk app is employed for visualizing the fault status of the 3 × 3 PV array. The dashboard of Blynk visualizes every array with the status.     

Deep Learning Approach for Analysis and Characterization of COVID-19

Early diagnosis of a pandemic disease like COVID-19 can help deal with a dire situation and help radiologists and other experts manage human resources more effectively. In a recent pandemic, laboratories perform diagnostics manually, which requires a lot of time and expertise of the laboratorial technicians to yield accurate results. Moreover, the cost of kits is high, and well-equipped labs are needed to perform this test. Therefore, other means of diagnosis is highly desirable. Radiography is one of the existing methods that finds its use in the diagnosis of COVID-19. The radiography observes change in Computed Tomography (CT) chest images of patients, developing a deep learning-based method to extract graphical features which are used for automated diagnosis of the disease ahead of laboratory-based testing. The proposed work suggests an Artificial Intelligence (AI) based technique for rapid diagnosis of COVID-19 from given volumetric chest CT images of patients by extracting its visual features and then using these features in the deep learning module. The proposed convolutional neural network aims to classify the infectious and non-infectious SARS-COV2 subjects. The proposed network utilizes 746 chests scanned CT images of 349 images belonging to COVID-19 positive cases, while 397 belong to negative cases of COVID-19. Our experiment resulted in an accuracy of 98.4%, sensitivity of 98.5%, specificity of 98.3%, precision of 97.1%, and F1-score of 97.8%. The additional parameters of classification error, mean absolute error (MAE), root-mean-square error (RMSE), and Matthew’s correlation coefficient (MCC) are used to evaluate our proposed work. The obtained result shows the outstanding performance for the classification of infectious and non-infectious for COVID-19 cases.     

Interleukin-1 Receptor Antagonist Reduces Neonatal Lipopolysaccharide-Induced Long-Lasting Neurobehavioral Deficits and Dopaminergic Neuronal Injury in Adult Rats

Our previous study showed that a single lipopolysaccharide (LPS) treatment to neonatal rats could induce a long-lasting neuroinflammatory response and dopaminergic system injury late in life. This is evidenced by a sustained activation of microglia and elevated interleukin-1β (IL-1β) levels, as well as reduced tyrosine hydroxylase (TH) expression in the substantia nigra (SN) of P70 rat brain. The object of the current study was to test whether co-administration of IL-1 receptor antagonist (IL-1ra) protects against LPS-induced neurological dysfunction later in life. LPS (1 mg/kg) with or without IL-1ra (0.1 mg/kg), or sterile saline was injected intracerebrally into postnatal day 5 (P5) Sprague-Dawley male rat pups. Motor behavioral tests were carried out from P7 to P70 with subsequent examination of brain injury. Our results showed that neonatal administration of IL-1ra significantly attenuated LPS-induced motor behavioral deficits, loss of TH immunoreactive neurons, as well as microglia activation in the SN of P70 rats. These data suggest that IL-1β may play a pivotal role in mediating a chronic neuroinflammation status by a single LPS exposure in early postnatal life, and blockading IL-1β might be a novel approach to protect the dopaminergic system against perinatal infection/inflammation exposure.     

The use of fine needle aspiration biopsy in the management of thyroid disease

Fine needle aspiration biopsy is now a first line investigation in thyroid disease. The purpose of this study was to evaluate the results of this technique in comparison with routine histopathology. A total of 593 aspirations over a four year period were included. There were 390 (65.7%) solitary nodules, 124 (20.9%) multinodular goiters, 66 (11.1%) diffuse goitres and 13 (2.2%) recurrent post thyroidectomy nodules. Radioisotope scanning in 386 cases showed 325 (84.2%) cold nodules, 54 (14.0%) warm nodules and 7 (1.8%) hot nodules. There were 458 (77.2%) colloid goitres and cysts, 14 cases of thyroiditis (2.2%) and 30 malignancies diagnosed on fine needle aspiration biopsy. In 19 cases (3.2%) a diagnosis of follicular neoplasm and in 29 cases (4.9%) a diagnosis of suspicious aspirate was made. Histological results were available in 176 cases. In 108 cases findings of histology and FNAB were compared with radioisotope scanning. A sensitivity of 92.8% and 42.8%, a specificity of 90.1% and 98.7% and accuracy index of 90.3% and 94.3% was found, when considering suspicious cases alternatively as positives and negatives. Surgery was recommended in all suspicious cases to prevent reduction in sensitivity of the technique. Fine needle aspiration biopsy was found to be a highly effective procedure which can obviate a lot of unnecessary surgery in thyroid lesions.     

The morphological variants of papillary carcinoma of the thyroid: a clinico-pathological study--AFIP experience. Armed Forces Institute of Pathology

The article describes results of an anatomo-clinical investigation using video-endoscopy and contact microvascular dopplerography in surgery of cerebral aneurysms. The endoscopic anatomy of cisterns of the cerebral base was studied in 36 corpses of adult humans. More than 200 video-endoscopic operative interventions were performed on sectional material. Video-endoscopy in combination with contact microvascular dopplerography was conducted in the clinic on 20 patients with aneurysms of the brain. Main advantages of endoscopy used in combination with microvascular dopplerography during clipping the aneurysm are formulated. Complex using the two methods described gives less volume of the access and traumaticity of the intervention but not less radical effect. It is a valuable and highly informative method which optimizes performing the operation and has less amount of postoperative complications.     

Novel Secure Pseudorandom Number Generator Based on Duffing Map

The fields of applied sciences and engineering require Pseudorandom Number Generators which exhibit useful statistical properties. In this paper, a novel algorithm for generating pseudorandom numbers has been proposed. This new algorithm is based on Duffing map. The aim of this paper is to generate pseudorandom bit streams based on chaotic map. The main objective is to find its potential to be used in applied sciences and engineering applications. To use this algorithm effectively in practical applications, the strength of this algorithm has been tested using various statistical tests like initial seed value, key sensitivity test, CPU performance test and pseudorandom orbit. The proposed pseudorandom number generator is further analyzed and evaluated with NIST statistical test suite. The results obtained from these experimental and statistical tests demonstrate and prove that the new generator has the potential to be applied successfully in mathematical sciences, applied physics, computer science and electrical engineering etc.     

Development of Wi-Fi Based Home Energy Monitoring System for Green Internet of Things

Green Internet of things (IoT) has been heralded as the next big thing waiting to be realized in energy-efficient ubiquitous computing. Green IoT revolves around increased machine-to-machine communications and encompasses energy-efficient wireless embedded sensors and actuators that assist in monitoring and controlling home appliances. Energy efficiency in home applications can be achieved by better monitoring of the specific energy consumption by the appliances. There are many wireless standards that can be adopted for the design of such embedded devices in IoT. These communication technologies cater to different requirements and are classified as the short-range and long-range ones. To select the best communication method, this paper surveys various IoT communication technologies and discusses the advantages and disadvantages to develop an energy monitoring system. An IoT device based on the Wi-Fi technology system is developed and tested for usage in the home energy monitoring environment. The performance of this system is then evaluated by the measurement of power consumption metrics. In the efficient deep-sleep mode, the system saves up to 0.3 W per cycle with an average power dissipation of less than 0.1 W/s.     

Secure Watermarking Scheme for Color DICOM Images in Telemedicine Applications

Teleradiology plays a vital role in the medical field, which permits transmitting medical and imaging data over a communication network. It ensures data reliability and provides convenient communication for clinical interpretation and diagnostic purposes. The transmission of this medical data over a network raises the problems of legal, ethical issues, privacy, and copyright authenticity. The copyright protection of medical images is a significant issue in the medical field. Watermarking schemes are used to address these issues. A gray-level or binary image is used as a watermark frequently in color image watermarking schemes. In this paper, the authors propose a novel non-blind medical image watermarking scheme based on 2-D Lifting Wavelet Transform (LWT), Multiresolution Singular Value Decomposition (MSVD), and LU factorization to improve the robustness and authenticity of medical images. In this scheme, multiple color watermarks are embedded into the colored DICOM (Digital Imaging and Communications in Medicine) images obtained from Color Doppler images (DICOM format), and the average results achieved by our proposed scheme is 46.84 db for Peak Signal-to-Noise Ratio (PSNR), 37.46 db for Signal-to-Noise Ratio (SNR), 0.99 for Quality of Image and 0.998 for Normalized Correlation for various image processing attacks. These results make our watermarking technique an ideal candidate for medical image watermarking.