Automated Prediction of Malignant Melanoma using Two-Stage Convolutional Neural Network.

PURPOSE: A skin lesion refers to an area of the skin that exhibits anomalous growth or distinctive visual characteristics compared to the surrounding skin. Benign skin lesions are noncancerous and generally pose no threat. These irregular skin growths can vary in appearance. On the other hand, malignant skin lesions correspond to skin cancer, which happens to be the most prevalent form of cancer in the United States. Skin cancer involves the unusual proliferation of skin cells anywhere on the body. The conventional method for detecting skin cancer is relatively more painful. METHODS: This work involves the automated prediction of skin cancer and its types using two stage Convolutional Neural Network (CNN). The first stage of CNN extracts low level features and second stage extracts high level features. Feature selection is done using these two CNN and ABCD (Asymmetry, Border irregularity, Colour variation, and Diameter) technique. The features extracted from the two CNNs are fused with ABCD features and fed into classifiers for the final prediction. The classifiers employed in this work include ensemble learning methods such as gradient boosting and XG boost, as well as machine learning classifiers like decision trees and logistic regression. This methodology is evaluated using the International Skin Imaging Collaboration (ISIC) 2018 and 2019 dataset. RESULTS: As a result, the first stage CNN which is used for creation of new dataset achieved an accuracy of 97.92%. Second stage CNN which is used for feature selection achieved an accuracy of 98.86%. Classification results are obtained for both with and without fusion of features. CONCLUSION: Therefore, two stage prediction model achieved better results with feature fusion.

Coupling Single-Ni-Atom with Ni-Co Alloy Nanoparticle for Synergistically Enhanced Oxygen Reduction Reaction.

Developing nonprecious metal-based oxygen reduction reaction (ORR) electrocatalysts with superior activity and durability is crucial for commercializing proton-exchange membrane (PEM) fuel cells. Herein, we report a metal-organic framework (MOF)-derived unique N-doped hollow carbon structure (NiCo/hNC), comprising of atomically dispersed single-Ni-atom (NiN4) and small NiCo alloy nanoparticles (NPs), for highly efficient and durable ORR catalysis in both alkaline and acidic electrolytes. Density functional theory (DFT) calculations reveal the strong coupling between NiN4 and NiCo NPs, favoring the direct 4e- transfer ORR process by lengthening the adsorbed O-O bond. Moreover, NiCo/hNC as a cathode electrode in PEM fuel cells delivered a stable performance. Our findings not only furnish the fundamental understanding of the structure-activity relationship but also shed light on designing advanced ORR catalysts.

An anonymization-based privacy-preserving data collection protocol for digital health data.

Digital health data collection is vital for healthcare and medical research. But it contains sensitive information about patients, which makes it challenging. To collect health data without privacy breaches, it must be secured between the data owner and the collector. Existing data collection research studies have too stringent assumptions such as using a third-party anonymizer or a private channel amid the data owner and the collector. These studies are more susceptible to privacy attacks due to third-party involvement, which makes them less applicable for privacy-preserving healthcare data collection. This article proposes a novel privacy-preserving data collection protocol that anonymizes healthcare data without using a third-party anonymizer or a private channel for data transmission. A clustering-based k-anonymity model was adopted to efficiently prevent identity disclosure attacks, and the communication between the data owner and the collector is restricted to some elected representatives of each equivalent group of data owners. We also identified a privacy attack, known as "leader collusion", in which the elected representatives may collaborate to violate an individual's privacy. We propose solutions for such collisions and sensitive attribute protection. A greedy heuristic method is devised to efficiently handle the data owners who join or depart the anonymization process dynamically. Furthermore, we present the potential privacy attacks on the proposed protocol and theoretical analysis. Extensive experiments are conducted in real-world datasets, and the results suggest that our solution outperforms the state-of-the-art techniques in terms of privacy protection and computational complexity.

Health Informatics: Engaging Modern Healthcare Units: A Brief Overview.

In the current scenario, with a large amount of unstructured data, Health Informatics is gaining traction, allowing Healthcare Units to leverage and make meaningful insights for doctors and decision-makers with relevant information to scale operations and predict the future view of treatments via Information Systems Communication. Now, around the world, massive amounts of data are being collected and analyzed for better patient diagnosis and treatment, improving public health systems and assisting government agencies in designing and implementing public health policies, instilling confidence in future generations who want to use better public health systems. This article provides an overview of the HL7 FHIR Architecture, including the workflow state, linkages, and various informatics approaches used in healthcare units. The article discusses future trends and directions in Health Informatics for successful application to provide public health safety. With the advancement of technology, healthcare units face new issues that must be addressed with appropriate adoption policies and standards.

FractalCovNet architecture for COVID-19 Chest X-ray image Classification and CT-scan image Segmentation.

Precise and fast diagnosis of COVID-19 cases play a vital role in early stage of medical treatment and prevention. Automatic detection of COVID-19 cases using the chest X-ray images and chest CT-scan images will be helpful to reduce the impact of this pandemic on the human society. We have developed a novel FractalCovNet architecture using Fractal blocks and U-Net for segmentation of chest CT-scan images to localize the lesion region. The same FractalCovNet architecture is also used for classification of chest X-ray images using transfer learning. We have compared the segmentation results using various model such as U-Net, DenseUNet, Segnet, ResnetUNet, and FCN. We have also compared the classification results with various models like ResNet5-, Xception, InceptionResNetV2, VGG-16 and DenseNet architectures. The proposed FractalCovNet model is able to predict the COVID-19 lesion with high F-measure and precision values compared to the other state-of-the-art methods. Thus the proposed model can accurately predict the COVID-19 cases and discover lesion regions in chest CT without the manual annotations of lesions for every suspected individual. An easily-trained and high-performance deep learning model provides a fast way to identify COVID-19 patients, which is beneficial to control the outbreak of SARS-II-COV.

Which Transition Metal Atoms Can Be Embedded into Two-Dimensional Molybdenum Dichalcogenides and Add Magnetism?

As compared to bulk solids, large surface-to-volume ratio of two-dimensional (2D) materials may open new opportunities for postsynthesis introduction of impurities into these systems by, for example, vapor deposition. However, it does not work for graphene or h-BN, as the dopant atoms prefer clustering on the surface of the material instead of getting integrated into the atomic network. Using extensive first-principles calculations, we show that counterintuitively most transition metal (TM) atoms can be embedded into the atomic network of the pristine molybdenum dichalcogenides (MoDCs) upon atom deposition at moderate temperatures either as interstitials or substitutional impurities, especially in MoTe2, which has the largest spacing between the host atoms. We further demonstrate that many impurity configurations have localized magnetic moments. By analyzing the trends in energetics and values of the magnetic moments across the periodic table, we rationalize the results through the values of TM atomic radii and the number of (s + d) electrons available for bonding and suggest the most promising TMs for inducing magnetism in MoDCs. Our results are in line with the available experimental data and should further guide the experimental effort toward a simple postsynthesis doping of 2D MoDCs and adding new functionalities to these materials.

dz2 orbital-mediated bound magnetic polarons in ferromagnetic Ce-doped BaTiO3 nanoparticles and their enriched two-photon absorption cross-section.

The enriched ferromagnetism and two-photon absorption (TPA) cross-section of perovskite BaTiO3 nanoparticles are indispensable for magnetic and optical data storage applications. In this work, hydrothermally synthesized Ce-doped BaTiO3 nanoparticles exhibited the maximum room temperature ferromagnetism (4.26 × 10-3 emu g-1) at 4 mol% due to the increase in oxygen vacancies, as evidenced by X-ray photoelectron and electron spin resonance spectroscopy and density functional theory (DFT) calculations. Hence, the oxygen vacancy-constituted bound magnetic polaron (BMP) model was invoked to explain the enhancement in ferromagnetism. The BMP theoretical model indicated an increase in BMP magnetization (M0, 3.0 to 4.8 × 10-3 emu g-1) and true spontaneous moment per BMP (meff, 4 to 9.88 × 10-4 emu) upon Ce doping. DFT calculations showed that BMPs mediate via the Ti dz2 orbitals, leading to ferromagnetism. Besides, it is known that the magnetic moment induced by Ce at the Ba site is higher than Ce at the Ti site in the presence of oxygen vacancies. The open aperture Z-scan technique displayed the highest TPA coefficient, ß (7.08 × 10-10 m W-1), and TPA cross-section, σTPA (455 × 104 GM), at 4 mol% of Ce as a result of the robust TPA-induced excited state absorption. The large σTPA is attributed to the longer excited state lifetime, τ (7.63 ns), of the charge carriers created by oxygen vacancies and Ce ions, which encounter several electronic transitions in the excited sub-states.

Fluorine-enriched mesoporous carbon as efficient oxygen reduction catalyst: understanding the defects in porous matrix and fuel cell applications.

Herein, fluorine enrichment in mesoporous carbon (F-MC) was explored to introduce maximum charge polarization in the porous matrix, which is beneficial for the preferential orientation of O2 molecules and their subsequent reduction. Ex situ doping of F to porous carbon derived from phloroglucinol-formaldehyde resin using Pluronic F-127 as a structure-directing agent is standardized. The optimized F-MC catalyst exhibited excellent electrocatalytic activity towards the oxygen reduction reaction (ORR) in alkaline media (0.1 M KOH) with an onset potential of -0.10 V vs. SCE and diffusion-limiting current of 4.87 mA cm-2, while displaying only about 50 mV overpotential in the half-wave region compared to Pt-C (40 wt%). In the stability test, the catalyst showed only 10 mV negative shift in its half-wave potential after 10 000 potential cycles. The rotating ring disk electrode (RRDE) experiments revealed that F-MC follows the most preferable 4e - pathway (n = 3.61) with a moderate peroxide (HO2 -) yield. This was further supported by density functional theory calculations and also deeply explains the existence of defects being beneficial for the ORR. The F-MC catalyst owing to its promising ORR activity and long-term electrochemical stability can be viewed as a potential alternative ORR catalyst for anion exchange membrane fuel cell applications.

Borophene layers on an Al(111) surface - the finding of a borophene layer with hexagonal double chains and B9 nonagons using ab initio calculations.

We studied the stability of several borophene layers on an Al(111) surface and found a structure called 9R using ab initio calculations. This layer competes with χ3 and ß12 borophene layers and is made up of boron nonagons that form a network of hexagonal boron double chains. Remarkably, it has no B6 hexagon unlike other borophene layers. All three layers lie significantly lower in energy than the honeycomb layer recently reported on the Al(111) surface [W. Li, et al., Sci. Bull., 2018, 63, 282]. We discuss the structural stability and electronic structures of different borophene layers in light of the role of the filling factor f of boron atoms in boron hexagons in a honeycomb layer as well as charge transfer from the Al substrate to the borophene layer as obtained from the Bader charge analysis. The electron localization function shows that the 9R layer has two-center bonding within the nonagon rings and three-center bonding between the rings. Calculations of the phonon spectra show that a free 9R layer is dynamically stable raising the hope of its isolation. The electronic structure shows that in all cases the borophene layer is metallic.

Unveiling the multifunctional roles of hitherto known capping ligand oleic acid as blue emitter and sensitizer in tuning the emission colour to white in red-emitting phosphors.

Capping ligands are vital in stabilizing various nanostructures and semiconductor quantum dots in which unusual optical properties, especially white light emission, have been realized. Oleic acid (OA) is a widely used capping ligand. Here, we report blue emission from OA in its free molecular form and further demonstrate this by anchoring OA over the surfaces of Al2O3, ZnAl2O4(ZA), ZnAl2O4:Eu3+ (ZA:Eu3+), and Y2O3:Eu3+. White light emission was observed from OA-modified ZA:Eu3+ nanophosphor due to mixing of broad blue emission of OA and red emission of Eu3+ through energy transfer from OA to Eu3+. A detailed study revealed the characteristic binding modes of OA and their dependence on Eu3+ concentration, structural inversion in ZA, and the optical properties and surface states in the pristine and OA-modified ZA:Eu3+. First principles density functional theory calculations were employed to provide an insight into the HOMO-LUMO levels of OA molecule and, electronic structure of pristine and OA-modified ZA surface. The binding of OA with the ZA:xEu3+ surface changes from bridging bidentate to chelating bidentate with increasing Eu3+ concentration in the lattice. The surface binding nature of the carboxylate group with the optimized surface of ZA and the creation of mid-gap states were deduced theoretically by using butanoic acid instead of OA. The blue emission from OA and its mixing with Eu3+ emission was further confirmed experimentally by anchoring it over Y2O3:Eu3+ red phosphor. These results show the multifunctional roles of OA as capping ligand, blue emitter and sensitizer in tuning the emission colour of red phosphors into white.

Tuning of intrinsic antiferromagnetic to ferromagnetic ordering in microporous α-MnO2 by inducing tensile strain.

By employing first principles density functional calculations, we investigated an α-MnO2 compound with a tunnel framework, which provides an eminent platform to alter the intrinsic antiferromagnetic (AFM) to ferromagnetic (FM) ordering, through the introduction of chemical or mechanical tensile strain. Our calculations further showed that the strength of FM ordering increases until 10% triaxial tensile strain. Since long range FM ordering is induced, it is realized to be superior as compared to the experimentally observed short-range FM ordering in oxygen-deficient compound. The driving force behind this superior effect is understood from the unusual electron occupancy in Mn atoms as a result of tetrahedral distortion in the MnO6 octahedra and an increase in the sp3 character of the oxygen atoms. Thus, the α-MnO2 compound belongs to a class of materials that exhibit good potential for piezomagnetic applications.

First principles modeling of Mo6S9 nanowires via condensation of Mo4S6 clusters and the effect of iodine doping on structural and electronic properties.

By employing first principles DFT calculations, we propose a new stable model for Mo6S9 nanowires (NWs) obtained by condensing tetrahedral Mo4S6 clusters rather than octahedral Mo6S8 clusters, which are known as magic clusters in the Mo-S polyhedral cluster family. The pristine NW is found to be metallic and its local structure and physical properties can be tuned by doping of iodine atoms. This doping increases the number of Mo-Mo bonds in the NW, thus, Mo4 tetrahedra are initially fused to the Mo6 octahedron, and then, to the Mo8 dodecahedron. Further, a close correlation among the Mo-Mo bonding in the local structure, mechanical and electronic properties, is observed from our study. Finally, the stability of the pristine and iodine doped Mo8S12-xIx NW structures obtained from condensation of Mo4 tetrahedra are found to be quite comparable with that of already reported Mo6S9-xIx NWs with Mo6 octahedra as building blocks.

Effect of temperature abuse on frozen army rations: Part 2: Predicting microbial spoilage.

Numerically simulated heat transfer model of frozen US military rations was combined with microbial kinetics to predict the microbial spoilage of the food products, during two possible temperature abuse scenarios. An army breakfast menu box containing five different food items was selected for conducting this research. One of the food item in the menu box, beefsteak, was chosen for detailed microbial study. A microbial predictive tool was used to identify and evaluate the kinetics of the most prone microorganism that can grow in a beefsteak. Numerical predictions suggested that the food items exposed to external temperatures ranging from 20°C to 40°C can be allowed to stay at those temperatures for maximum times of 28.7h to 11.9h, respectively. The food items can be allowed to stay inside the broken freezer for a maximum time of 186h, to ensure microbial safety in the case of freezer failure.

Effect of temperature abuse on frozen army rations. Part 1: Developing a heat transfer numerical model based on thermo-physical properties of food.

Numerical simulation was carried out to predict the effect of external temperature conditions on thermal behavior of frozen US military rations, during storage and transportation. An army breakfast menu box containing beefsteaks, concentrated orange juice, peppers & onions, French toast, and Danishes, was selected for conducting this study. Thermo-physical properties of each food item were characterized using their composition and differential scanning calorimeter (DSC). Apparent heat capacity method was used to account for the latent heat of phase change during simulation of thawing and freezing. Numerically simulated results were experimentally validated using a gel-based model food system and the food items in the menu box. The average deviation between numerically predicted temperature and experimentally measured temperature for the model food system was approximately 1°C and for the targeted food items the deviation ranged from 2°C to 5°C, depending on the food item.

Atomic structure and edge magnetism in MoS(2+x) parallelogram shaped platelets.

The structural, electronic, and magnetic properties of MoS(2+x) parallelogram shaped platelets having m and n Mo atoms on the adjoining edges have been studied using first principles calculations and by varying m and n from 1 to 6. These platelets have 100% S coverage on two adjoining edges while 50% S coverage on the other two edges. The structural stability of the platelets increases with size but the highest occupied molecular orbital-lowest unoccupied molecular orbital (HOMO-LUMO) energy gap in general decreases. There is a triangular metallic corner at the intersection of 100% S covered edges of the platelets when m = n. On the other hand magnetism is observed on the 50% S covered edges of the platelets for the sizes greater than that of the (3,4) platelet. The magnetic moments mainly arise from the undercoordinated S(2c) atoms at the 50% S covered edges rather than from Mo atoms. The criteria for the existence of the magnetic moments on S(2c) atoms are suggested and the electronic structure of the platelets on the edges as well as inside is discussed.

Evaluation of Luteolin in the Prevention of N-nitrosodiethylamine-induced Hepatocellular Carcinoma Using Animal Model System.

Hepatocellular carcinoma (HCC) is one of the commonest tumors worldwide. The treatment of HCC is vital for disease diagnosis and prognosis, as the liver is the most important organ controlling metabolic functions. Now-a-days, western folklore medicines are largely dependent on the phyto compounds which are highly effective in therapy and with low side effects. Luteolin is a flavonoid (3,4,5,7-Tetrahydro flavones) possess anti-inflammatory, anticancer and anti allergic property. The present study evaluates the efficacy of luteolin against N-nitrosodiethylamine (DEN) induced HCC in albino rats. In the highlight of the above, luteolin was evaluated for its efficacy against DEN induced HCC in male Wistar albino rats. The Biochemical parameters such as tissue damaging enzymes viz., AST, ALP, LDH and γ-GT, enzymatic antioxidants viz., SOD, CAT, GSH and GPx and histopathological changes have been estimated. The tissue damaging enzymes were found to be high in DEN alone treated group whereas the enzymatic antioxidants decreased destructively. Severe lesions and cirrhosis were observed in the toxin (DEN alone) treated group. The luteolin treated DEN group altered the tissue damaging enzymes and the enzymatic antioxidants. The damaged lesion in the histoarchitecture of DEN treated rat liver was almost completely restored. Finally this study strongly demonstrates that luteolin has potent curative property against HCC in albino rats.

Analytical properties of p-[N,N-bis(2-chloroethyl)amino]benzaldehyde thiosemicarbazone: spectrophotometric determination of palladium(II) in alloys, catalysts, and complexes.

p-[N,N-bis(2-chloroethyl)amino]benzaldehyde thiosemicarbazone (CEABT) is proposed as a new, sensitive, and selective analytical reagent for the spectrophotometric determination of palladium(II). The reagent reacts with palladium(II) in the pH range 1-2 to form a yellow-colored complex. Beer's law is obeyed in the concentration range up to 2.64 µg cm(-3). The optimum concentration range for minimum photometric error as determined by Ringbom's plot method is 0.48-2.40 µg cm(-3). The yellowish Pd(II)-reagent complex shows a maximum absorbance at 395 nm, with molar absorptivity of 4.05×10(4) dm3 mol(-1) cm(-1) and Sandell's sensitivity of the complex from Beer's data, for D=0.001, is 0.0026 µg cm(-2). The composition of the Pd(II)-CEABT reagent complex is found to be 1:2 (M-L). The interference of various cations and anions in the method were studied. The proposed method was successfully used for the determination of Pd(II) in alloys, catalysts, complexes, water samples, and synthetic alloy mixtures with a fair degree of accuracy.

A rapid extractive spectrophotometric determination of copper(II) in environmental samples, alloys, complexes and pharmaceutical samples using 4-[N,N(dimethyl)amino]benzaldehyde thiosemicarbazone.

4-[N,N-(Dimethyl)amino]benzaldehyde thiosemicarbazone (DMABT) is proposed as an analytical reagent for the extractive spectrophotometric determination of copper(II). DMABT forms yellow colored complex with copper(II) in the pH range 4.4-5.4. Beer's law is obeyed in the concentration range up to 4.7 µg mL(-1). The optimum concentration range for minimum photometric error as determined by Ringbom plot method is 1.2-3.8 µg mL(-1). The yellowish Cu(II)-DMABT complex shows a maximum absorbance at 420 nm, with molar absorptivity of 1.72 × 10(4)dm(3) mol(-1) cm(-1) and Sandell's sensitivity of the complex obtained from Beer's data is 0.0036 µg cm(-2). The composition of the Cu(II)-DMABT complex is found to be 1:2 (M/L). The interference of various cations and anions in the method were studied. Thus the method can be employed for the determination of trace amount of copper(II) in water, alloys and other natural samples of significant importance.

Spectrophotometric determination of platinum(IV) in alloys, complexes, environmental, and pharmaceutical samples using 4-[N,N-(diethyl)amino] benzaldehyde thiosemicarbazone.

4-[N,N-(Diethyl)amino] benzaldehyde thiosemicarbazone (DEABT) is proposed as an analytical reagent for the spectrophotometric determination of platinum(IV). The DEABT forms 1:2 yellow complex with Pt(IV), which is sparingly soluble in water and completely soluble in water-ethanol-DMF medium. The Pt(IV)-DEABT complex shows maximum absorbance at 405 nm. Beer's law is valid up to 7.80 µg cm(-3), and optimum concentration range for the determination of platinum(IV) is 0.48-7.02 µg cm(-3). The molar absorptivity and Sandell's sensitivity of the method are found to be 1.755 × 10(4) dm(3) mol(-1) cm(-1) and 0.0012 µg cm(-2), respectively. The relative error and coefficient of variation (n=6) for the method does not exceed ± 0.43% and 0.35%, respectively. Since the method tolerates a number of metal ions commonly associated with platinum, it can be employed for the determination of platinum in environmental samples, pharmaceutical samples, alloys, catalysts, and complexes. The method is rapid as the Pt(IV)-DEABT complex is soluble in water-ethanol-DMF medium and not requiring any time consuming extraction method for the complex.

Effect of cadmium on lactate dehyrogenase isoenzyme, succinate dehydrogenase and Na(+)-K(+)-ATPase in liver tissue of rat.

Cadmium is known to be an environmental and industrial pollutant. Exposure to cadmium is known to affect various tissues. The purpose of this study is to determine the toxic effects of cadmium on lactate dehydrogenase (LDH) isoenzymes. Administration of cadmium chloride (3 mg kg(-1)) resulted in the reduction of LDH4 fraction of liver tissue indicating the inhibitory effect of cadmium. The LDH1 LDH3 and LDH5 fractions showed decreasing trend initially but there was a significant increase later In contrast the LDH2 fraction showed increasing trend after 24 hr from the last dosage it was elevated after 30 days. The total activity of LDH in liver showed gradual reduction in both groups. The activity of succinate dehydrogenase (SDH) the mitochondrial enzyme has been observed to be inhibited by cadmium with the possibility of interfering with energy transport mechanism. Na(+)- K(+)-ATPase activity of liver also showed similar decrease after cadmium administration which may lead to general deficit in cell membrane transport. As cadmium shows drastic decrease in all the enzymes studied, the LDH2 fraction which sharply rises from the control may be used as a marker enzyme to asses the liver injury.