COVID-19 detection and disease progression visualization: Deep learning on chest X-rays for classification and coarse localization

Chest X-rays are playing an important role in the testing and diagnosis of COVID-19 disease in the recent pandemic. However, due to the limited amount of labelled medical images, automated classification of these images for positive and negative cases remains the biggest challenge in their reliable use in diagnosis and disease progression. We applied and implemented a transfer learning pipeline for classifying COVID-19 chest X-ray images from two publicly available chest X-ray datasets {https://github.com/ieee8023/covid-chestxray-dataset},{https://www.kaggle.com/paultimothymooney/chest-xray-pneumonia}}. The classifier effectively distinguishes inflammation in lungs due to COVID-19 and pneumonia (viral and bacterial) from the ones with no infection (normal). We have used multiple pre-trained convolutional backbones as the feature extractor and achieved an overall detection accuracy of 91.2% , 95.3%, 96.7% for the VGG16, ResNet50 and EfficientNetB0 backbones respectively. Additionally, we trained a generative adversarial framework (a cycleGAN) to generate and augment the minority COVID-19 class in our approach. For visual explanations and interpretation purposes, we visualized the regions of input that are important for predictions and a gradient class activation mapping (Grad-CAM) technique is used in the pipeline to produce a coarse localization map of the highlighted regions in the image. This activation map can be used to monitor affected lung regions during disease progression and severity stages

The use of demineralisation and torrefaction to improve the properties of biomass intended as a feedstock for fast pyrolysis

Pre-treatments of biomass were investigated to reduce its undesirable properties which may affect the quality of fast pyrolysis bio-oil. A pre-treatment sequence was developed in this study to incorporate both biomass demineralisation and torrefaction. Demineralisation was performed by dilute acid leaching, primarily to reduce the inorganic concentration in raw biomass, whereas torrefaction targeted a reduction of the carboxyl, moisture and oxygen content. The liquid produced during torrefaction was recycled back as the leaching reagent for demineralisation. This solution contained dilute organic acids; therefore, the viability of leaching with organic acids (acetic and formic acid) compared to commonly used mineral acids (sulphuric, nitric and hydrochloric acid) was validated. Synthetic leaching solutions reduced the inorganic content in raw biomass from 0.41 wt% to 0.14 wt% when leached with 1% formic acid and to 0.16 wt% when leached with 1% acetic acid, which was comparable to leaching with the mineral acids. Recycled torrefaction liquid that contained other acidic compounds in small quantities reduced the inorganic content to 0.14 wt%, suggesting it is effective to use the recycled torrefaction liquid as the leaching solution. From the experimental results, the optimal conditions for biomass torrefaction were 260 °C for 20 min to minimise the char formation during pyrolysis, based on the increase in the acid-insoluble fraction of the biomass. However, the torrefaction temperature may be increased to 280 °C if further reductions in acetyl and oxygen content are required. Higher temperatures are associated with severe biomass loss and the initiation of hydrogen loss. It should be noted that even at 280 °C, the oxygen reduction is minimal. If oxygen reduction is the principal target when pre-treating biomass, it is suggested that torrefaction alone is not a suitable method to obtain bio-oil with a low oxygen content due to the low pyrolysis yields obtainable. This study demonstrated that the combined use of demineralisation and torrefaction as biomass pre-treatments has the ability to decrease the inorganic, acetyl and moisture content of biomass, which reduces undesirable catalytic reactions during fast pyrolysis to improve the quality of bio-oil produced

Transfer learning for endoscopy disease detection and segmentation with mask-RCNN benchmark architecture

We proposed and implemented a disease detection and semantic segmentation pipeline using a modified mask-RCNN infrastructure model on the EDD2020 dataset1. On the images provided for the phase-I test dataset, for ’BE’, we achieved an average precision of 51.14%, for ’HGD’ and ’polyp’ it is 50%. However, the detection score for ’suspicious’ and ’cancer’ were low. For phase-I, we achieved a dice coefficient of 0.4562 and an F2 score of 0.4508. We noticed the missed and mis-classification was due to the imbalance between classes. Hence, we applied a selective and balanced augmentation stage in our architecture to provide more accurate detection and segmentation. We observed an increase in detection score to 0.29 on phase-II images after balancing the dataset from our phase-I detection score of 0.24. We achieved an improved semantic segmentation score of 0.62 from our phase-I score of 0.52

Optimización y evaluación de aceite de salvado de mijo (Setaria italica) mediante extracción supercrítica con dióxido de carbono

A Box-Behnken central composite design combined with the response surface methodology (RSM) was used to optimize the parameters of a supercritical fluid extraction (SFE) of foxtail millet bran oil (FMBO). Results showed that a maximum oil yield of 7.97% was achieved under the optimal conditions with an extracting pressure of 30.03MPa, extracting temperature of 47.93 °C; and an extraction time of 2.3 h. The quality of the oil obtained from SFE and solvent extraction (SE) was evaluated by proximate analysis to include physicochemical properties, fatty acids and sterol compounds. The FBMO obtained from SFE showed a much lower phospholipid (0.188 mg/g) content and a preferable color compared to the oil from SE, while it contained a higher content of total sterols, 1.55%. The thermal gravimetric analysis results showed one major regime of weight loss over a temperature range of 300–500 °C. The results show that FBMO obtained by SFE can be a promising nutritional source for food fortification and is understood to have more potentially healthy biological properties.Un diseño Box-Behnken combinado con la metodología de superficie de respuesta (RSM) se usó para optimizar los parámetros de extracción mediante fluido supercrítico (SFE) de aceite de salvado de mijo (FMBO). Los resultados mostraron que un rendimiento máximo de extracción de aceite del 7,97% se logró en las condiciones óptimas correspondientes a una presión de 30.03MPa, una temperatura 47.93 °C y un tiempo 2,3H. Además, se evaluó la calidad del aceite obtenido por SFE y mediante extracción con disolvente (SE) a partir de un análisis proximal que incluye propiedades fisicoquímicas, ácidos grasos y esteroles. El aceite de FBMO obtenido mediante SFE mostró un contenido mucho menor de fosfolípidos (0.188 mg/g) y un color mas aceptable que el aceite de la SE, mientras que contenía un mayor contenido de esteroles totales: 1,55%. El resultado del análisis térmico gravimétrico mostró un régimen importante de pérdida de peso durante un intervalo de temperatura de 300–500 °C. Los resultados muestran que FBMO obtenido por SFE puede ser una fuente nutricional prometedora para la fortificación de alimentos y se supone potencialmente que tiene mejores propiedades biológicas saludables

Modeling Cluster Production at the AGS

Deuteron coalescence, during relativistic nucleus-nucleus collisions, is carried out in a model incorporating a minimal quantal treatment of the formation of the cluster from its individual nucleons by evaluating the overlap of intial cascading nucleon wave packets with the final deuteron wave function. In one approach the nucleon and deuteron center of mass wave packet sizes are estimated dynamically for each coalescing pair using its past light-cone history in the underlying cascade, a procedure which yields a parameter free determination of the cluster yield. A modified version employing a global estimate of the deuteron formation probability, is identical to a general implementation of the Wigner function formalism but can differ from the most frequent realisation of the latter. Comparison is made both with the extensive existing E802 data for Si+Au at 14.6 GeV/c and with the Wigner formalism. A globally consistent picture of the Si+Au measurements is achieved. In light of the deuteron's evident fragility, information obtained from this analysis may be useful in establishing freeze-out volumes and help in heralding the presence of high-density phenomena in a baryon-rich environment.Comment: 31 pages REVTeX, 19 figures (4 oversized included as JPEG). For full postscript figures (LARGE): contact [email protected]

Critical Nature of Non-Fermi Liquid in Spin 3/2 Multipolar Kondo Model

A multipolar Kondo model of an impurity spin S_I=3/2 interacting with conduction electrons with spin s_c=3/2 is investigated using boundary conformal field theory. A two-channel Kondo (2CK) -like non-Fermi liquid (NFL) under the particle-hole symmetry is derived explicitly using a ``superspin absorption'' in the sector of a hidden symmetry, SO(5). We discuss the difference between the usual spin-1/2 2CK NFL fixed point and the present one. In particular, we find that, unlike the usual 2CK model, the low temperature impurity specific heat is proportional to temperature.Comment: 4 pages, 2 figure

Holographic Superconductors with Lifshitz Scaling

Black holes in asymptotically Lifshitz spacetime provide a window onto finite temperature effects in strongly coupled Lifshitz models. We add a Maxwell gauge field and charged matter to a recently proposed gravity dual of 2+1 dimensional Lifshitz theory. This gives rise to charged black holes with scalar hair, which correspond to the superconducting phase of holographic superconductors with z > 1 Lifshitz scaling. Along the way we analyze the global geometry of static, asymptotically Lifshitz black holes at arbitrary critical exponent z > 1. In all known exact solutions there is a null curvature singularity in the black hole region, and, by a general argument, the same applies to generic Lifshitz black holes.Comment: 23 pages, 4 figures; v2: added references; v3: matches published versio