Effect of non-magnetic Al3+ doping on structural,optical, electrical,dielectric and magnetic properties of BiFeO3 ceramics

Pure BiFeO₃ (BFO) and Al doped BFO samples were synthesized via citrate precursor method and sintered at 500 °C for two hours. Effect of Al doping on the structural, optical, electrical, dielectric and magnetic properties were investigated. X-ray diffraction (XRD) confirmed the distorted rhombohedral structure without any merging of peaks which indicates no structural transformation. Average crystallite size was found to be in the range 28–39 nm. Field emission scanning electron microscopy (FESEM) images illustrated the dense, agglomerated, spherically shaped with reduced grain size nanoparticles. Increased value of dielectric constant with low dielectric tangent loss was observed for the Al doped BFO samples. The value of dielectric constant was found to be 51 at 100 kHz for x = 0.1 sample. Temperature dependent dielectric constant showed a dielectric anomaly, indicating the antiferromagnetic transition. The remanent polarization and the corresponding coercive field for x = 0.1 was found to be 0.0625 µC/cm² and 56.154 kV/cm at an operating voltage of 1000 V. The improved electrical properties with low leakage current density were ascribed to the stabilization of the pervoskite structure and reduced oxygen vacancies.     

Neither human immunodeficiency virus-1 (HIV-1) nor HIV-2 infects most-primitive human hematopoietic stem cells as assessed in long-term bone marrow cultures

Phenylglyoxylate (benzoylformate) is an intermediate in the anoxic metabolism of phenylalanine and phenylacetate. It is formed by alpha-oxidation of phenylacetyl-CoA. Phenylglyoxylate is oxidatively decarboxylated by phenylglyoxylate-oxidoreductase to benzoyl-CoA, a central intermediate of anaerobic aromatic metabolism. The phenylglyoxylate oxidizing enzyme activity in the denitrifying bacterium Azoarcus evansii was induced during anaerobic growth with phenylalanine, phenylacetate and phenylglyoxylate, but not with benzoate. The new enzyme phenylglyoxylate:acceptor oxidoreductase was purified and studied. The oxygen-sensitive enzyme reduced both NAD+ and viologen dyes. It was composed of five subunits of approximately 50, 48, 43, 24, and 11.5 kDa; the native mass as determined by gel filtration was 370 kDa, suggesting an alpha2 beta2 gamma2 delta2 epsilon2 composition. Phenylglyoxylate:acceptor oxidoreductase exhibited an ultraviolet/visible spectrum characteristic for an iron-sulfur protein and contained 35 +/- 4 mol Fe, 36 +/- 4 mol acid-labile sulfur, and 1.1 +/- 0.2 mol FAD/mol. The enzyme was specific for phenylglyoxylate (Km 45 microM) and coenzyme A (Km 55 microM); 2-oxoisovalerate was oxidized with 15% of the rate. The turnover number with benzyl viologen at 37 degrees C was 46 s(-1) at the optimal pH of 8. The enzyme catalyzed a NAD(P)H:viologen dye transhydrogenation reaction, NAD(H) being the preferred coenzyme. It also catalyzed an isotope exchange between CO2 and the carboxyl group of the substrate. The data are consistent with the following hypothesis. The enzyme complex consists of a core enzyme of four subunits with the composition alpha2 beta2 gamma2 delta2, as reported for archaeal 2-oxoacid:ferredoxin oxidoreductases; this complex is able to reduce viologen dyes. The holoenzyme contains in addition an epsilon2 unit that catalyzes the transfer of electrons from a small ferredoxin-like subunit of the core complex to NAD+; this unit also catalyzes the transhydrogenase reaction, carries FAD and resembles ferredoxin:NAD(P)+-oxidoreductase.     

AI-enabled farm-friendly automatic machine for washing,image-based sorting,and weight grading of citrus fruits: Design optimization,performance evaluation,and ergonomic assessment

The modernization of postharvest operations and penetration of emerging technologies in horticultural processing have provided intelligent solutions for reducing postharvest losses. Work environmental and occupational health issues require immediate attention as the awkward posture and continuous drudgery-prone on-farm sorting and grading activities may lead to musculoskeletal disorders. The main objective of this study was to develop an automatic farm-friendly machine for real-time citrus fruit washing, image-based sorting, and weight grading; designed optimally and equipped with an embedded system comprising a lightweight convolutional neural network (CNN) model. Also included in this study was a thorough ergonomic assessment of the developed machine in a real work environment. The parametric choice of the fruit washing and singulation system was performed by employing computational fluid dynamics modeling and response surface methodology designed optimization. It was observed that under steady-state conditions, the water jet would arrive at a velocity of 11.36 m/s which would eventually suit a singulation conveyor with a slope of 25°. A noninvasive grading and sorting approach for citrus fruits is presented in this paper that leverages deep learning to classify the fruits into “accept” and “reject” classes. The custom lightweight CNN model “SortNet” has shown excellent classification results with an overall accuracy of 97.6%. The ergonomic evaluation shows that the average body part discomfort score in case of operating an automatic fruit grading machine was much lower (12.3 ± 2.0) than the traditional method (30.9 ± 3.3). Further, in the case of machine operation, the percentage load on the muscles ranged from 28.67 to 34.31 reflecting that subjects can work for longer duration on the machine without fatigue as compared with the traditional manual operation.