AlphaPilot: autonomous drone racing

Autonomous Robots - This paper presents a novel system for autonomous, vision-based drone racing combining learned data abstraction, nonlinear filtering, and time-optimal trajectory planning. The...     

Neural network based non-invasive method to detect anemia from images of eye conjunctiva

Detection of anemia can be done by examining the hemoglobin concentration level in the blood using complete blood count, which is an invasive, time-consuming, and costly technique. Preliminary methods for detecting anemia include examining the color of the palpebral conjunctiva, which is a non-invasive method, but color perception may vary from person to person. This study aims to develop a computerized non-invasive technique for anemia detection. We propose a novel machine learning model using the artificial neural network to detect anemic patients from the images of eye conjunctiva. Since limited and small dataset has been used in the earlier approaches, this may cause over fitting of the model. We have improved the number of available training images using image augmentation techniques. To standardize a non-invasive method, we have used computer vision algorithms for preprocessing and feature extraction. This article derives the backpropagation rules mathematically for adjusting the weights for the proposed neural network model. After hyper parameter tuning and using the mathematically derived backpropagation rules, the model was able to achieve the best accuracy of 97.00% with sensitivity 99.21% and specificity 95.42% on the created dataset.     

Dielectric,electrical, and rheological characterization of graphene‐filled polystyrene nanocomposites

A series of nanographene filled polystyrene (GPS) nanocomposites was prepared by in situ polymerization of styrene in the laboratory. The concentration of graphene was changed in the step of 0.25 wt% and a total of eight composites (including control) were prepared to obtain a threshold concentration of graphene. These composites, prepared by in situ polymerization followed by compression moulding, were characterized for their structural (using XRD), morphological (SEM), thermal (DSC, TGA, DTGA), dielectric behavior (ɛ', ɛ''') and DC conductivity. It was observed that the thermal stability as well as electrical and rheological properties of graphene‐polystyrene nanocomposites significantly improved due to the homogeneous dispersion, intercalation and exfoliation of the graphene layers in the Polystyrene matrix. It was also observed that at room temperature dielectric constant (ε′) decreased with increasing concentration of graphene and reached a minimum at a certain filler concentration of 0.25 wt% (PSG025) when frequency is kept constant. Rheological study showed an improvement in the storage modulus (G′) with incorporation of graphene as nanofiller. Loss modulus (G′) and complex viscosity (η*) also increased with increasing graphene weight percentage. Relaxation time also increased at high graphene loading because of the pseudo‐solid like behavior of polymer melt. POLYM. COMPOS., 34:2082–2093, 2013. © 2013 Society of Plastics Engineers     

High Na+ conducting Na3Zr2Si2PO12/Na2Si2O5 composites as solid electrolytes for Na+ batteries

Sodium superionic conductor Na₃Zr₂Si₂PO₁₂ (NZSP) is a promising material as a solid electrolyte for sodium-ion batteries. The highest conductivity of ∼1.0 mS/cm at room temperature (RT) was reported for the compound with a Na content of approximately 3.3 per formula unit (f. u.) and when the material is synthesized with a final sintering temperature ≥1220°C. Herein, we propose a new synthesis method to enhance the conductivity of the NZSP by liquid-phase sintering with the optimum amount of additive of amorphous-Na₂Si₂O₅. In this regard, a series of composite materials were prepared by mixing Na₃Zr₂Si₂PO₁₂ with amorphous-Na₂Si₂O₅ (NZSP/NS-x wt.%; with x = 0.0, 2.5, 5.0, 7.5, 10.0) and sintering at a lower temperature of 1150°C. Enhanced conductivity of 1.7 mS/cm at RT has been achieved for the Na₃Zr₂Si₂PO₁₂/Na₂Si₂O₅-5.0 wt.% (NZSP/NS-5.0) composite. The effects of additives on the NZSP phase formation, microstructure, and ion conductivity have been investigated by XRD, MAS NMR, SEM, and impedance spectroscopy. Our study demonstrates that the higher conductivity of the NZSP/NS-5.0 composite is caused by the combined effect of increased Na content in the NZSP phase (by diffusion of Na⁺ ions from the liquid phase of NS to bare NZSP phase), higher density, and microstructures with lesser pores.     

Application of Lipase from Marine Bacteria Bacillus sonorensis as an Additive in Detergent Formulation

The efficacy of lipase (triacylglycerol acylhydrolases EC 3.1.1.3) as a detergent additive from a newly isolated marine halophilic bacteria Bacillus sonorensis from marine clams Paphia malabarica collected in the Kalbadevi Estuary, Mumbai, has been assessed and reported. In terms of activity and stability, the lipase exhibited maximum activity in alkaline conditions and was observed to be stable over a temperature range from room temperature to 60 °C. The activity of the lipase increased in the presence of surfactants and detergents. Due to these properties of the lipase from marine bacteria, it was used as an additive in detergents to study its efficiency at corn oil removal from fabrics. The washing studies indicated that the efficiency of corn oil removal from the cotton fabrics increased by 20 % when lipase was incorporated in the detergent as compared to the treatment with detergent alone. The lipase was also capable of removing corn oil from natural as well as synthetic fabrics dyed with a respective, preferred class of dyes.     

Synthesis of CdS and alloyed CdMnS nanocrystals using aqueous foams

Certain surfactant-stabilized aqueous foams provide a potentially efficient and simple chemical route for the synthesis of various nanomaterials with controllable structure, size, and shape. In the present work, a one-step process for the synthesis of CdS and Cd1-xMn(x)S (0 < x < 10) nanocrystals has been described. Aqueous CdCl2 and the aerosol-OT solutions are homogeneously mixed together and thereafter, nitrogen is bubbled through this solution to produce stable aqueous foam. After drainage of the foam, the freestanding dry foam consisting of cadmium cations electrostatically complexed with the anionic aerosol-OT molecules at the liquid-gas interface is treated with H2S vapor. The foam turns yellowish-orange and collapses, in the process yielding CdS nanoclusters of variable morphology. This morphology variation is appropriately attributed to growth of the CdS as well as alloyed Cd1-xMn(x)S nanoparticles in different regions of the foam contributing to the varying topological structure. Optical absorption spectra of both CdS and Cd1-xMn(x)S nanoparticles clearly show a well-defined exciton absorption feature around 450 nm due to quantum confinement effects. The interesting band edge emission characteristics of these AOT-capped CdS and Cd1-xMn(x)S nanoparticles produced in the foam are discussed with respect to their size and shape. Particular interest in the present novel aqueous foam approach arises due to the fact that the cubic zincblende CdS and alloyed Cd1-xMn(x)S nanocrystals could easily be obtained even under ambient experimental conditions itself.     

Synthetic Utility of (Propargyl)dicobalt Hexacarbonyl Cations. A New Cyclopentenone Annelation

The regiospecific alkylation of cyclic ketones and TMS enol ethers by the cobalt-stabilized propargyl cations 1 followed by demetalation and regiospecific acetylene hydration proceeds in good overall yield to produce 1,4-diketones. The latter are efficiently cyclized in the presence of base to annelated cyclopentenones.     

Stepwise Degradable Nanocarriers Enabled Cascade Delivery for Synergistic Cancer Therapy

Hypoxia‐activated prodrugs have brought new opportunities for safe and effective tumor ablation, but their therapeutic efficacy is limited by insufficient activation in tumor microenvironments. Herein, a novel cascade delivery system with tandem functions by integrating a hypoxia‐activated prodrug (AQ4N) and glucose oxidase (GOx) is designed to improve its efficacy. Innovative yolk–shell organosilica nanoparticles with a tetrasulfide bridged composition, a small‐pore yolk, and a large‐pore shell featuring a shell‐to‐yolk stepwise degradability are constructed as a carrier for AQ4N and GOx, one enzyme that catalyzes the oxidation of glucose to produce hydrogen peroxide. The glutathione (GSH) is depleted by tetrasulfide bond in the framework and induces shell degradation for fast release of GOx, which in turn induces starvation (glucose removal), oxidative cytotoxicity (H₂O₂ production and GSH depletion), and hypoxia (oxygen consumption). Finally, the hypoxia activates the liberated prodrug AQ4N for chemotherapy. The cascading and synergistic functions including GSH depletion, starvation, oxidative cytotoxicity, and chemotherapy lead to improved performance in tumor inhibition and antimetastasis.     

Pre-trained convolutional neural networks as feature extractors for diagnosis of breast cancer using histopathology

Several researchers are trying to develop different computer-aided diagnosis system for breast cancer employing machine learning (ML) methods. The inputs to these ML algorithms are labeled histopathological images which have complex visual patterns. So, it is difficult to identify quality features for cancer diagnosis. The pre-trained Convolutional Neural Networks (CNNs) have recently emerged as an unsupervised feature extractor. However, a limited investigation has been done for breast cancer recognition using histopathology images with CNN as a feature extractor. This work investigates ten different pre-trained CNNs for extracting the features from breast cancer histopathology images. The breast cancer histopathological images are obtained from publicly available BreakHis dataset. The classification models for the different feature sets, which are obtained using different pre-trained CNNs in consideration, are developed using a linear support vector machine. The proposed method outperforms the other state of art methods for cancer detection, which can be observed from the results obtained.