Mycodecolorization Activity of Pleurotus Citrinopileatus for Chemically Different Textile Dye Under Varied Aromatic Amino Acids and Trace Elements

In the present study, ligninolytic enzymes laccase (benzenediol: oxygen reductase EC; 1.10.3.2) and Manganese Peroxidase (Mn(II): hydrogen-peroxide oxidoreductase EC; 1.11.1.13) activity and of White Rot Fungi (WRF) Pleurotus citrinopileatus were enhanced with the application of trace metal i.e. Copper and Manganese at 25 ppm and 50 ppm followed by aromatic amino acids (Phenylalanine, Tryptophan and Tyrosine) at 0.02 μM and 0.4 μM. Laccase and MnP activity were 213.42U and 202.28U respectively, observed at 300ppm of Methyl Red supplemented with Tyrosine (0.2μM) followed by treatment of Tryptophan (198.45U and 195.16U) and Phenylalanine (195.85U and 188.15U). Maximum Laccase and MnP activity (Tyrosine treated) were revealed maximum decolorization of Phenol Red and Methyl Red (84.14% and 78.20%) followed by Phenylalanine (80.92% and 73.80%) and Trypatophan (71.22% and 70.12%).  The negative correlation of  Laccase and MnP activity was observed with a higher concentration (>50ppm) of trace metal in the medium, while at 25ppm of copper supplemented medium increase three-fold of Laccase activity (585.56U) as tyrosine medium and similarly, Manganese (25ppm) inosculated medium revealed three-fold more MnP activity (478.95U).  A lower amount of Cu hoists Laccase and MnP activity which decolorized 300ppm of Methyl Red and Phenol Red with maximum percent (92.3% and 88.15%) followed by Mn. Thus, Laccase and MnP enzymes both play an important role in decolorization of dyes, and its activity was enhanced with the application of lower concentration of trace metals followed by aromatic amino acids

Reduced major axis approach for correcting GPM/GMI radiometric biases to coincide with radiative transfer simulation

Correcting radiometric biases is crucial prior to the use of satellite observations in a physically based retrieval or data assimilation system. This study proposes an algorithm - RARMA (Radiometric Adjustment using Reduced Major Axis) for correcting the radiometric biases so that the observed radiances coincide with the simulation of a radiative transfer modeL The RARMA algorithm is a static bias correction algorithm, which is developed using the reduced major axis (RMA) regression approach, NOAA\u27s Community Radiative Transfer Model (CRTM) has been used as the basis of radiative transfer simulation for adjusting the observed radiometric biases. The algorithm is experimented and applied to the recently launched Global Precipitation Measurement (GPM) mission\u27s GPM Microwave Imager (GMI), Experimental results demonstrate that radiometric biases are apparent in the GMI instrument, The RARMA algorithm has been able to correct such radiometric biases and a significant reduction of observation residuals is revealed while assessing the performance of the algorithm, The experiment is currently tested on clear scenes and over the ocean surface, where, surface emissivity is relatively easier to model. with the help of a microwave emissivity model (FASTEM-5)

Robust broad spectral photodetection (UV-NIR) and ultra high responsivity investigated in nanosheets and nanowires of Bi2Te3 under harsh nano-milling conditions

Due to miniaturization of device dimensions, the next generations photodetector based devices are expected to be fabricated from robust nanostructured materials. Hence there is an utmost requirement of investigating exotic optoelectronic properties of nanodevices fabricated from new novel materials and testing their performances at harsh conditions. The recent advances on 2D layered materials indicate exciting progress on broad spectral photodetection (BSP) but still there is a great demand for fabricating ultra-high performance photodetectors made from single material sensing broad electromagnetic spectrum since the detection range 325 nm to 1550 nm is not covered by the conventional Si or InGaAs photodetectors. Alternatively, Bi2Te3 is a layered material, possesses exciting optoelectronic, thermoelectric, plasmonics properties. Here we report robust photoconductivity measurements on Bi2Te3 nanosheets and nanowires demonstrating BSP from UV to NIR. The nanosheets of Bi2Te3 show the best ultra-high photoresponsivity (~74 A/W at 1550 nm ). Further these nanosheets when transform into nanowires using harsh FIB milling conditions exhibit about one order enhancement in the photoresponsivity without affecting the performance of the device even after 4 months of storage at ambient conditions. An ultra-high photoresponsivity and BSP indicate exciting robust nature of topological insulator based nanodevices for optoelectronic applications.Comment: 14 pages, 6 figure

Assessment of carrot growth performance with inoculation of AsT-PGPR under arsenic infested zone

In the present study, the maximum rhizobacterial population was observed in Nutrient Agar (NA) (average; Cfu=135×106) followed by King’s-B (average; Cfu=57×106), Soil extract agar (SEA) (average; Cfu=11×106), and Trypticase soy agar (TSA) (average; Cfu=9×106). Screening of arsenic tolerant rhizobacterial isolate revealed that about 1% of the bacterial isolate was from Nutrient Agar and King’s-B survived at 20ppb arsenic concentration, while 0.8% and 0.7% survived from TSA and SEA media respectively. 50ppb arsenic tolerant rhizobacteria were screened for plant growth-promoting activity such as IAA, Phosphate solubilization, Siderophore production, ACC deaminase activity. Maximum IAA activity was observed in rhizobacterial isolates, isolated from all different media. P- solubilizer, Siderophore producer, ACC deaminase, proline, and TSS activities were observed in the isolates of NA media followed by King’s-B media. 50ppb tolerate best suitable PGP traits producing isolates were inoculated to observe carrot plant growth in the pot experiment, Interesting and significant (p<0.05) result were observed in King’s-B media producer isolates; (Pseudomonas) induces plant length, chlorophyll-a and chlorophyll-b content of the plant after 60 days followed by 30 days

Landscape transform and spatial metrics for mapping spatiotemporal land cover dynamics using Earth Observation data-sets

Analysis of Earth observation (EO) data, often combined with geographical information systems (GIS), allows monitoring of land cover dynamics over different ecosystems, including protected or conservation sites. The aim of this study is to use contemporary technologies such as EO and GIS in synergy with fragmentation analysis, to quantify the changes in the landscape of the Rajaji National Park (RNP) during the period of 19 years (1990–2009). Several statistics such as principal component analysis (PCA) and spatial metrics are used to understand the results. PCA analysis has produced two principal components (PC) and explained 84.1% of the total variance, first component (PC1) accounted for the 57.8% of the total variance while the second component (PC2) has accounted for the 26.3% of the total variance calculated from the core area metrics, distance metrics and shape metrics. Our results suggested that notable changes happened in the RNP landscape, evidencing the requirement of taking appropriate measures to conserve this natural ecosystem

Computed Tomography- and Radiography-Based Morphometric Analysis of the Lateral Mass of the Subaxial Cervical Spine in the Indian Population

Study DesignThis was a double-blinded cross-sectional study, which obtained no financial support for the research.PurposeTo obtain a detailed morphometry of the lateral mass of the subaxial cervical spine.Overview of LiteratureThe literature offers little data on the dimensions of the lateral mass of the subaxial cervical spine.MethodsWe assessed axial, sagittal, and coronal computed tomography (CT) cuts and anteroposterior and lateral X-rays of the lateral mass of the subaxial cervical spine of 104 patients (2,080 lateral masses) who presented to a tertiary care public hospital (King Edward Memorial Hospital, Mumbai) in a metropolitan city in India.ResultsFor a majority of the parameters, males and females significantly differed at all levels (p<0.05). Females consistently required higher (p<0.05) minimum lateral angulation and lateral angulation. While the minimum lateral angulation followed the order of C5<C4<C6<C3, the lateral angulation followed the order of C3<C5<C4<C6. The lateral mass becomes longer and narrower from C3 to C7. In axial cuts, the dimensions increased from C3 to C6. The sagittal cut thickness and diagonal length increased and the sagittal cut height decreased from C3 to C7. The sagittal cut height was consistently lower in the Indian population at all levels, especially at the C7 level, as compared with the Western population, thereby questioning the acceptance of a 3.5-mm lateral mass screw. A good correlation exists between X-ray- and CT-based assessments of the lateral mass.ConclusionsLarger lateral angulation is required for Indian patients, especially females. The screw length can be effectively calculated by analyzing the lateral X-ray. A CT scan should be reserved for specific indications, and a caution must be exercised while inserting C7 lateral mass screws

Reference Evapotranspiration Retrievals from a Mesoscale Model Based Weather Variables for Soil Moisture Deficit Estimation

Reference Evapotranspiration (ETo) and soil moisture deficit (SMD) are vital for understanding the hydrological processes, particularly in the context of sustainable water use efficiency in the globe. Precise estimation of ETo and SMD are required for developing appropriate forecasting systems, in hydrological modeling and also in precision agriculture. In this study, the surface temperature downscaled from Weather Research and Forecasting (WRF) model is used to estimate ETo using the boundary conditions that are provided by the European Center for Medium Range Weather Forecast (ECMWF). In order to understand the performance, the Hamon’s method is employed to estimate the ETo using the temperature from meteorological station and WRF derived variables. After estimating the ETo, a range of linear and non-linear models is utilized to retrieve SMD. The performance statistics such as RMSE, %Bias, and Nash Sutcliffe Efficiency (NSE) indicates that the exponential model (RMSE = 0.226; %Bias = −0.077; NSE = 0.616) is efficient for SMD estimation by using the Observed ETo in comparison to the other linear and non-linear models (RMSE range = 0.019–0.667; %Bias range = 2.821–6.894; NSE = 0.013–0.419) used in this study. On the other hand, in the scenario where SMD is estimated using WRF downscaled meteorological variables based ETo, the linear model is found promising (RMSE = 0.017; %Bias = 5.280; NSE = 0.448) as compared to the non-linear models (RMSE range = 0.022–0.707; %Bias range = −0.207–−6.088; NSE range = 0.013–0.149). Our findings also suggest that all the models are performing better during the growing season (RMSE range = 0.024–0.025; %Bias range = −4.982–−3.431; r = 0.245–0.281) than the non−growing season (RMSE range = 0.011–0.12; %Bias range = 33.073–32.701; r = 0.161–0.244) for SMD estimation