Pneumonia Detection in Chest X-Ray Images : Handling Class Imbalance

People all over the globe are affected by pneumonia but deaths due to it are highest in Sub-Saharan Asia and South Asia. In recent years, the overall incidence and mortality rate of pneumonia regardless of the utilization of effective vaccines and compelling antibiotics has escalated. Thus, pneumonia remains a disease that needs spry prevention and treatment. The widespread prevalence of pneumonia has caused the research community to come up with a framework that helps detect, diagnose and analyze diseases accurately and promptly. One of the major hurdles faced by the Artificial Intelligence (AI) research community is the lack of publicly available datasets for chest diseases, including pneumonia . Secondly, few of the available datasets are highly imbalanced (normal examples are over sampled, while samples with ailment are in severe minority) making the problem even more challenging. In this article we present a novel framework for the detection of pneumonia. The novelty of the proposed methodology lies in the tackling of class imbalance problem. The Generative Adversarial Network (GAN), specifically a combination of Deep Convolutional Generative Adversarial Network (DCGAN) and Wasserstein GAN gradient penalty (WGAN-GP) was applied on the minority class ``Pneumonia'' for augmentation, whereas Random Under-Sampling (RUS) was done on the majority class ``No Findings'' to deal with the imbalance problem. The ChestX-Ray8 dataset, one of the biggest datasets, is used to validate the performance of the proposed framework. The learning phase is completed using transfer learning on state-of-the-art deep learning models i.e. ResNet-50, Xception, and VGG-16. Results obtained exceed state-of-the-art

X-ray time lag evaluation of MAXI J1820+070 with a differential cross-correlation analysis

MAXI J1820$+$070 is a transient black hole binary (BHB) discovered on 2018 March 11. The unprecedented rich statistics brought by the NICER X-ray telescope allows detailed timing analysis up to $\sim$1~kHz uncompromised by the photon shot noise. To estimate the time lags, the Fourier analysis was applied, which led to two different conclusions for the system configuration; one supporting the lamp-post configuration with a stable accretion disk extending close to the innermost stable circular orbit and the other supporting the truncated accretion disk contracting with time. Using the same data set, we present the results based on the cross-correlation function (CCF). The CCF is calculated between two different X-ray bands and one side is subtracted from the other side, which we call the differential CCF (dCCF). The soft and hard lags respectively of $\sim$0.03 and 3~s are clearly identified without being diluted by the spectral mixture, demonstrating the effectiveness of the dCCF analysis. The evolution of these lags is tracked, along with spectral changes for the first 120~days since the discovery. Both the dCCF and spectral fitting results are interpreted that the soft lag is a reverberation lag between the Comptonized emission and the soft excess emission and that the hard lag is between the disk black body emission and the Comptonized emission. The evolution of these lags is in line with the picture of the truncated disk contracting with time.Comment: 12 pages, 12 figure

Association between fat distribution and iron status among Qatari obese adults

Background: The prevalence of obesity in Qatar has reached an alarming rate. In addition, high prevalence of iron deficiency (ID) and iron deficiency anemia (IDA) was observed in Gulf countries. In the early 1960's an inverse relationship between plasma iron and adiposity was reported. To date, no data exist to elucidate the relationship between iron status and obesity among Qatari population

Effect of graphene oxide loading on cobalt oxide performance as electrocatalyst for methanol oxidation reaction

In this paper, cobalt oxide with graphene oxide included were prepared using a straightforward hydrothermal approach in this study for the electrocatalytic oxidation of methanol. Scanning electron microscopy (SEM), and X-ray diffraction (XRD), FTIR, and XPS techniques were used to evaluate the produced cobalt oxide with graphene oxide. Cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) techniques were used to examine the electrochemical behaviour of an electrode modified with GO-CO3O4. In regard to the oxidation of methanol in an alkaline medium, the electrocatalytic performances of electrodes modified with graphene oxide at various graphene oxide weight percentages were examined. The grapheme oxide, and cobalt oxide modified electrodes, the GO-CO3O4 modified electrode displayed higher current density brought on by the oxidation of methanol

Bimetallic Prussian Blue Analogues: An Efficient Electrode Alternative for Energy Storage Applications

In the past few years Prussian Blue Analogues (PBAs), as advanced metal organic framework compounds, have gathered a lot of attention due to its three-dimensional structural network and properties. PBAs are famous for their multitasking ability as they have shown an efficient role in scientific research and development with their excellent performance in various fields like, electrochemical sensors, photocatalysis, electrocatalysis, and energy storage applications. Apart from their high-tech productivity, PBAs also have some other advantages associated to them such as benign nature, economical and facile synthesis, extensive surface properties, higher theoretical capacity and exceptional electrochemical behavior which makes it more promising material for energy storage application. To further tune its properties according to the application of interest, the chemical modification by metal incorporation is the most commonly adopted strategy. For this purpose, the major research is done in the synthesis of bimetallic PBAs. The presence of metal atoms with different oxidation states can bring about dramatic reinforcements like finer microstructures with better crystallographic features, ultimately giving rise to more stable electrochemical behavior. In this article, we aim to list out all the bimetallic PBAswith focus on the synergistic effect of more than one metal within the structure of PBA and thorough analysis of their electrochemical properties in energy storage applications

Review: Two-dimensional layered material based electrodes for lithium ion and sodium ion batteries

Energy crisis is a worldwide problem due to the current conventional resources which are depleting and are causing great environmental concerns. Among many feasible solutions, rechargeable batteries are considered as a powerful alternative to these conventional energy resources. Lithium and sodium ion batteries are one of the best energy storage systems which provide greater cyclic stability and better charge–discharge capacity. These metal ion batteries have achieved great attention and are being used in a range of applications from small electronic devices to electric vehicles. An overall enhancement of metallic ion storage and transportation is the current concern and focus of the researchers. Many electrode materials are tried and tested in this regard which provided great deal of structural and functional improvement. Two dimensional layered materials have also gained much attraction recently in energy storage application due to their higher surface to volume ratio. There are a number of layered structures which have been developed and electrochemically tested as anode or cathode for both lithium and sodium ion batteries. Materials like graphene based structures, transition metal chalcogenides (TMDCs), MXenes, nitrides, Molybdenum Sulfide and organic frameworks showed promising results as electrode for lithium and sodium ion batteries. In this work, an effort is done to cover all these electrode materials along with their complete structural analysis and a thorough evaluation of their electrochemical activity in energy storage systems

StEduCov: An Explored and Benchmarked Dataset on Stance Detection in Tweets towards Online Education during COVID-19 Pandemic

In this paper, we present StEduCov, an annotated dataset for the analysis of stances toward online education during the COVID-19 pandemic. StEduCov consists of 16,572 tweets gathered over 15 months, from March 2020 to May 2021, using the Twitter API. The tweets were manually annotated into the classes agree, disagreeor neutral. We performed benchmarking on the dataset using state-of-the-art and traditional machine learning models. Specifically, we trained deep learning models-bidirectional encoder representations from transformers, long short-term memory, convolutional neural networks, attention-based biLSTM and Naive Bayes SVM-in addition to naive Bayes, logistic regression, support vector machines, decision trees, K-nearest neighbor and random forest. The average accuracy in the 10-fold cross-validation of these models ranged from 75% to (Formula presented.) % and from (Formula presented.) % to 68% for binary and multi-class stance classifications, respectively. Performances were affected by high vocabulary overlaps between classes and unreliable transfer learning using deep models pre-trained on general texts in relation to specific domains such as COVID-19 and distance education. 2022 by the authors.Scopu

Improved rate capability and long cycle life of metal-organic framework derived TiO2 @V2O5 composite as an efficient cathode for sodium-ion batteries

Vanadium oxide on carbon nanoporous structure (V2O5/C) as a potential cathode material for sodium-ion batteries (SIBs) offers significant specific capacities in energy storage systems but suffers from slow ionic diffusivity upon long cycling at higher current rates, thereby generally resulting in substandard electrochemical performance. This study suggests a facile strategy to enhance the electrochemical performance of V2O5/C as a cathode in sodium-ion batteries via titanium (Ti) doping using the pre-synthesized Ti-doped vanadium-based metal-organic framework template (V-MIL-101) as the precursor, which can be converted into a sophisticated core-shell type structure in which titania nanoparticle-based shell surrounds the vanadium oxide with a porous carbon-based octahedral core. Structural characterization reveals that Ti-doping forms a protective layer around vanadium based MIL-101 octahedrons that, upon pyrolysis, preserves the octahedral geometry and transforms into a nanoporous core-shell structure. It also greatly enhances the electrochemical performance as a cathode for SIBs. The titania-doped vanadium oxide structures represent higher specific capacities than the undoped vanadium oxide cathode, whereas among all the titania-doped samples, the 3 wt% TiO2@V2O5/C exhibited a much higher reversible capacity of 276.2 mAh/g as compared to the other cathode samples at 0.1C current rate and was able to retain a capacity of 250.1 mAh/g with a high coulombic efficiency after 200 cycles. Titanium species induce the formation of oxygen vacancies and V+5 species, which enhance the electrode's electric conductivity and ion diffusion—the stable octahedrons with a porous structure and carbon hybridisation in 3 wt% TiO2@V2O5/C could facilitate ion/electron transfer through shortened diffusion pathways

Assessment of medication prescription errors and their contributory factors in major cities of Punjab Province, Pakistan: A cross-sectional survey

Purpose: To evaluate the prescription errors and their contributory factors in Punjab, Pakistan.Methods: An observational, cross-sectional study was conducted in 12 major cities of Punjab, Pakistan. A total of 1,184 prescriptions were collected from patients using a convenient sampling method from homes, pharmacies, clinics, and hospitals. The data were presented in frequency and percentage using descriptive statistics. To determine the association between the variables assessed, Chi-square (X2) test was used.Results: A total of 1,184 prescriptions were analyzed; 432 of them (36.5 %) were from prescribers who are graduate degree holders, and 752 (63.5 %) from prescribers who are post-graduate degree holders. The most commonly missing parameters in the prescriptions were the age of the patients (835 representing 29.4 %), signatures of the prescribers (755 representing 26.5 %), and prefix (622 representing 21.9 %). The number of prescription errors was significantly correlated to prescriber qualification (p = 0.001). The prescription errors were more common in age groups of prescribers: 21 - 30 years (654 representing 23.0 %), and 31 - 40 years (1,012 representing 35.6 %) (p = 0.001). The higher number of prescription errors by post-graduate prescribers working in teaching hospitals can be attributed to the higher patient load and lack of continuing medical education programs for the prescribers.Conclusion: The government should take necessary measures for the implementation of electronic prescribing systems, and devise mechanisms for the uniform distribution of patient load amongst the prescribers working in different hospitals. Keywords: Prescription error, Prescribers, Patient load, Continuing medical education, Electronic prescribin