Resonant Raman of OH/OD vibrations and photoluminescence studies in LiTaO3 thin film

Resonant Raman spectra (RRS) of O-H and O-D vibration and libration modes, their combinations and higher harmonics have been observed in LiTaO3 polycrystalline thin films. RRS peaks are superimposed on photoluminescence (PL) spectrum. Monochromatic light from a xenon lamp is used as excitation source. PL spectrum shows two broad peaks, first near the band gap in UV (4.4-4.8eV) and another in the sub band gap region (< 4.0 eV). Band gap PL along with RRS peaks are reported for the first time. Photoluminescence excitation spectrum (PLE) shows a peak at 4.8 eV. Peak positions and full width at half maximum (FWHM) of RRS peaks depend upon the excitation energy. Dispersions of the fundamental and the third harmonic of the stretching mode of O-H with excitation energy are about 800 cm-1/eV and 2000 cm-1/eV respectively. This dispersion is much higher than reported in any other material.Comment: 20 page

Tuning cracks by exploiting the shape of particles and external magnetic field

Drying of a colloidal dispersion usually leads to the formation of particulate film with random cracks. The cracks in particulate film can have periodic arrangement with tuneable spacing and are known to be useful for practical applications such as for fabrication of lithographic templates and nano-channels. Various methodology has been adopted to generate the parallel and ordered cracks, the common one is via applying an external field such as magnetic field or electric field. We report here the controlled manipulation of crack orientation for colloidal films consisting of magnetically active particle (hematite ellipsoids), using an external magnetic field. Drying sessile drop experiments are performed in the presence and absence of magnetic field and a coffee ring like particle deposits are observed. The dried region consists of circular cracks in the absence of field while linear cracks (along the chord of the ring) in the presence of field. Moreover, we found that the crack orientations can be systematically altered by tuning magnetic field strength. We conjecture that the competition between the hydrodynamic torque and magnetic torque experienced by the particles during the drying of colloidal dispersion decides the final orientation of the particles and the cracks. The alteration of crack direction by controlling the orientation of ellipsoids in the particulate films by application of magnetic field is presented in detail. Please click Additional Files below to see the full abstract

Effective Image Clustering with Differential Evolution Technique

The paper presents a novel approach of clustering image datasets with differential evolution (DE) technique. The differential evolution is a parallel direct search population based optimization method. From our simulations it is found that DE is able to optimize the quality measures of clusters of image datasets. To claim the superiority of DE based clustering we have compared the outcomes of DE with the classical K-means and popular Particle Swarm Optimization (PSO) algorithms for the same datasets. The comparisons results reveal the suitability of DE for image clustering in all image datasets

Elevated Liver Biochemistries in Hospitalized Chinese Patients with Severe COVID-19: Systematic Review and Meta-analysis.

BACKGROUND & AIMS:Several recent studies have reported an abnormal liver chemistry profile among patients with coronavirus disease 2019 (COVID-19), although its clinical significance remains unknown. APPROACH & RESULTS:This novel systematic review and meta-analysis identified six studies of 586 patients delineating liver chemistries among patients with severe/critical illness versus mild cases of COVID-19 infection. Patients with severe/critical illness with COVID-19 infection have increased prevalence of coronary artery disease (CAD), cerebrovascular disease, and chronic obstructive pulmonary disease (COPD) as compared to mild cases. A significant association between severe/critical COVID-19 infections with elevations in aspartate aminotransferase (AST) (pooled mean difference [MD], 11.70 U/L; 95% confidence interval [CI], 2.97, 20.43; P = 0.009), elevated total bilirubin (pooled MD, 0.14 mg/dL; 95% CI, 0.06, 0.22; P = 0.0005), and decreased albumin (pooled MD, -0.68 g/L; 95% CI, -0.81, -0.55; P \u3c 0.00001) was noted. There was also a trend toward elevated alanine aminotransferase (ALT) levels among these severe cases (pooled MD, 8.84 U/L; 95% CI, -2.28, 19.97; P = 0.12); however, this did not reach statistical significance. More severe/critically ill cases were associated with leukocytosis, neutrophilia, lymphopenia, elevated creatinine kinase, elevated lactate dehydrogenase (LDH), and elevated prothrombin time (PT). CONCLUSIONS:Comorbidities, including CAD, cerebrovascular disease, and COPD, are more prevalent in hospitalized Chinese patients with severe/critical illness from COVID-19, and these patients are more likely to manifest with abnormal liver chemistries. Further prospective studies are crucial to understand the pathophysiologic mechanisms underlying the hepatic manifestations of the novel COVID-19 infection and its clinical significance

Ergonomics of Farm Women in Manual Paddy Threshing

Thin-layer drying experiments with Roselle (Hibiscus sabdariffa .L) were carried out in a constant temperature and humidity chamber. Four temperatures (35, 45, 55, and 65°C) and five relative humidities (30, 35, 40, 45, and 50%RH) were tested. Statistical analysis on twelve thinlayer drying model proved the superiority of two-term exponential model. The objectives of this work were to evaluate and validate the two-term exponential model; besides, examine the effects of the drying conditions on the drying rate and constant. Validation of the developed model was done using two criterions, plotting of the predicted against experimental moisture contents and the residual versus predicted moisture content. The average values of the drying constant (k) and coefficient (a) weA study was taken up to have a comparative study on the ergonomics of farm women in pedal threshing with single and double operators (N =15) and to suggest modifications for further reduction of human drudgery. The mean HR work was found to be 135.9 ± 1.3 and 121.2 ±1.0 beats/min respectively with single and double operators; a significant (P < 0.01) reduction of 10.82 %. The corresponding work pulse (Δ HR) was 65.7 ± 0.9 and 51.5 ± 1.6 beats/min. The Δ HR was more than the allowable limit of 40 beats/min. HR work steadied after 6 minutes of threshing and there was complete recovery of HR after 6 minutes with double operators and 8 minutes with single operator. The increase in HR/kg of grain threshed was found to be 146.4 ± 4.4 and 76.0 ± 4.1 in case of single and double operators respectively; a significant reduction of 48 %. The workload decreased by 13.5 % with double operators but was still higher than the allowable limit of 35 % of VO2 max. The energy expenditure rate (ERR) was 18.9 ± 0.4 kJ/min with single operator and reduced to 16.6 ± 0.3 kJ/min with double operators. The total cardiac cost of work (TCCW) and physiological cost of work (PCW) reduced by 19.84 and 20 % with double operators. No significant variation of blood lactate accumulation between single and double operators was observed. The pedal force required was 232.3 ± 7.0 N and 199.7 ± 5.8 N in case of single operator and double operators respectively but was higher than the mean leg strength of the women of the eastern region of India. Higher pedal force application with double operators increased the number strokes/min (96/min) leading to a 51.15 % increase in output capacity of the thresher per hour per person. An increase of length of the pedal by 2 cm was suggested to reduce the force requirement. The length of the threshing drum can be reduced from 60.5 cm to 40 cm to be used by single operator or it can be increased to 75 cm to comfortably accommodate two persons.e 0.009167 and 0.776132, respectively

Deep-learning framework to detect lung abnormality - A study with chest X-Ray and lung CT scan images

Lung abnormalities are highly risky conditions in humans. The early diagnosis of lung abnormalities is essential to reduce the risk by enabling quick and efficient treatment. This research work aims to propose a Deep-Learning (DL) framework to examine lung pneumonia and cancer. This work proposes two different DL techniques to assess the considered problem: (i) The initial DL method, named a modified AlexNet (MAN), is proposed to classify chest X-Ray images into normal and pneumonia class. In the MAN, the classification is implemented using with Support Vector Machine (SVM), and its performance is compared against Softmax. Further, its performance is validated with other pre-trained DL techniques, such as AlexNet, VGG16, VGG19 and ResNet50. (ii) The second DL work implements a fusion of handcrafted and learned features in the MAN to improve classification accuracy during lung cancer assessment. This work employs serial fusion and Principal Component Analysis (PCA) based features selection to enhance the feature vector. The performance of this DL frame work is tested using benchmark lung cancer CT images of LIDC-IDRI and classification accuracy (97.27%) is attained. (c) 2019 Elsevier B.V

Modern microwave methods in solid state inorganic materials chemistry: from fundamentals to manufacturing

No abstract available