Synthesis of a Fe3O4-rGO-ZnO-catalyzed photo-Fenton system with enhanced photocatalytic performance

In this work, we designed a magnetically-separable Fe₃O₄-rGO-ZnO ternary catalyst, ZnO anchored on the surface of reduced graphene oxide (rGO)-wrapped Fe₃O₄ magnetic nanoparticles, where rGO, as an effective interlayer, can enhance the synergistic effect between ZnO and Fe₃O₄. The effects of three operational parameters, namely irradiation time, hydrogen peroxide dosage, and the catalyst dosage, on the photo-Fenton degradation of methylene blue and methyl orange were investigated. The results showed that the Fe₃O₄-rGO-ZnO had great potential for the destruction of organic compounds from wastewater using the Fenton chemical oxidation method at neutral pH. Repeatability of the photocatalytic activity after 5 cycles showed only a tiny drop in the catalytic efficiency.     

Surface Integrity Assessment Upon Electric Discharge Machining of Die Steel Using Non-Destructive Magnetic Barkhausen Noise Technique

Surface integrity characterization of manufactured component is very important as it significantly affects the in-service performance of the component. Till now, surface integrity was evaluated using conventional measurement technique like microhardness tester, X-ray diffraction, optical microscopy and surface roughness tester. But, this technique being laboratory based cannot be used for in-service monitoring of the surface integrity. The present study focuses on the characterization of surface integrity upon electric discharge machined sample using non-destructive magnetic Barkhausen noise technique. Electric discharge machining was performed in die-sinking mode on die steel using copper–tungsten electrode (negative polarity). Experiment was performed by selecting different levels of peak current, gap voltage and pulse on time. Surface integrity characteristics like microhardness change, residual stress, microstructural alteration and surface roughness were analysed using microhardness tester, X-ray diffraction, optical microscopy and surface roughness tester, respectively, and were then correlated with magnetic parameter like root mean square value and peak value obtained from Barkhausen noise signal. The results show a good correlation between magnetic parameter (RMS and Peak value) of Barkhausen noise with the microhardness and surface roughness of the machined sample.

     

A study on harvesting of PKL electricity

The efficiency of any electric cell or battery is very important. To keep it in mind it has been studied the columbic efficiency, voltaic efficiency and energy efficiency of a PKL (Pathor Kuchi Leaf) Quasi Voltaic Cell or Modified Voltaic Cell. It was found that the columbic efficiency data illustrated that this efficiency was lower comparing to other efficiencies may be the absence of salt bridge or separator between the electrodes. Because, our designed and fabricated PKL cell does not have any salt bridge. So that the internal resistance is lower than the traditional voltaic cell and as a result more current was found. The voltage and current changes with time and I–V characteristics for PKL unit cell, module, panel and array have also been studied. It is shown that the voltaic and energy efficiency have been studied. However, the highest efficiency was obtained for 40% PKL sap with 5% secondary salt in 55% aqueous solution, which implies that the concentration of PKL juice can play an important role regarding efficiency. It was also found that the average energy efficiency was 97.43% and it was also found that the average voltaic efficiency was 57.29%. Finally, morphological study FESEM (Field Emission Scanning Electron Microscopy) has also been performed. It is seen that the results confirmed that Zn was deposited on the Cu surface during the electro deposition process in PKL solution. Using AAS, it has been measured the concentration of [Cu²⁺] as a reactant ion and the concentration of [Zn²⁺] as a product ion those have been tabulated and graphically discussed. The variation of pH has also been studied with time and which was also tabulated and graphically discussed.

     

A hybrid knowledge and ensemble classification approach for prediction of venous thromboembolism

Clinical narratives such as progress summaries, lab reports, surgical reports, and other narrative texts contain key biomarkers about a patient's health. Evidence-based preventive medicine needs accurate semantic and sentiment analysis to extract and classify medical features as the input to appropriate machine learning classifiers. However, the traditional approach of using single classifiers is limited by the need for dimensionality reduction techniques, statistical feature correlation, a faster learning rate, and the lack of consideration of the semantic relations among features. Hence, extracting semantic and sentiment-based features from clinical text and combining multiple classifiers to create an ensemble intelligent system overcomes many limitations and provides a more robust prediction outcome. The selection of an appropriate approach and its interparameter dependency becomes key for the success of the ensemble method. This paper proposes a hybrid knowledge and ensemble learning framework for prediction of venous thromboembolism (VTE) diagnosis consisting of the following components: a VTE ontology, semantic extraction and sentiment assessment of risk factor framework, and an ensemble classifier. Therefore, a component-based analysis approach was adopted for evaluation using a data set of 250 clinical narratives where knowledge and ensemble achieved the following results with and without semantic extraction and sentiment assessment of risk factor, respectively: a precision of 81.8% and 62.9%, a recall of 81.8% and 57.6%, an F measure of 81.8% and 53.8%, and a receiving operating characteristic of 80.1% and 58.5% in identifying cases of VTE.     

Deliberately Losing Control of C−H Activation Processes in the Design of Small-Molecule-Fragment Arrays Targeting Peroxisomal Metabolism

Combined photochemical arylation, “nuisance effect” (S_NAr) reaction sequences have been employed in the design of small arrays for immediate deployment in medium-throughput X-ray protein–ligand structure determination. Reactions were deliberately allowed to run “out of control” in terms of selectivity; for example the ortho-arylation of 2-phenylpyridine gave five products resulting from mono- and bisarylations combined with S_NAr processes. As a result, a number of crystallographic hits against NUDT7, a key peroxisomal CoA ester hydrolase, have been identified.     

Investigation of structural,optical, electrical,and magnetic properties of Fe-doped La0.7Sr0.3MnO3 manganites

In this work, the physical properties of nanocrystalline samples of La_0.7Sr_0.3Mn_1−xFe_xO₃ (0.0 ≤ x ≤ 0.20) perovskite manganites synthesized by the reverse micelle (RM) technique were explored in detail. The phase purity, crystal structure, and crystallite size of the samples were determined using X-ray diffraction (XRD) and Fourier transform infrared (FTIR) spectroscopy. All the samples had rhombohedral crystal structure and crystallite size increased with increase in Fe content in La_0.7Sr_0.3MnO₃. The scanning electron micrographs (SEMs) exhibited smooth surface morphology and nonuniform shape of the particles. The optical properties studied using UV-visible absorption spectroscopy revealed a decrease in the absorbance and optical band gap with an increase in Fe content in La_0.7Sr_0.3MnO₃ compound. The temperature-dependent resistivity measurements revealed semiconducting nature of x = 0 and 0.1 samples up to the studied temperature range, while a metal-to-insulator transition was observed at higher Fe doping. Magnetic studies revealed weak ferromagnetism in all the samples and a reduction in the maximum magnetization with an increase in Fe content. A close correlation between electrical transport and magnetic properties was observed with the doping of Fe ion in La_0.7Sr_0.3MnO₃ at Mn site. These results advocate strong interactions associated with the double exchange mechanism among Fe³⁺ and Mn³⁺ ions.