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Abstract Crop residues in agriculture pose disposal challenges and contribute to air pollution when burned. This study aims to use pigeonpea and maize stalks to produce biochar at different pyrolysis temperatures. Biochar can serve in carbon sequestration, as a soil amendment, and as an alternative fuel source. Pyrolysis was conducted at 400, 500, and 600 °C to examine the effects on physicochemical properties, fuel, and energy related properties. Increase in temperatures resulted in decrease of biochar yield, volatile matter, and O/C and H/C atomic ratios, while ash content and essential nutrients increased. Yield was observed to be higher in pigeonpea stalks derived biochar compared to maize stalks derived biochar at same pyrolysis temperatures. The yields of pigeonpea stalks derived biochar at 400 °C, 500 °C, and 600 °C are 34, 33 and 29%, respectively, and the yields of maize biomass-derived biochar at 400 °C, 500 °C, and 600 °C are 29, 28, and 26%, respectively. The organic carbon content is found to be higher in the biochar samples prepared at 600 °C, i.e., 10.44%, and 10.39% for pigeonpea and maize-derived biochar, respectively. The essential elements of biochar were increased with an increase in pyrolysis temperature except nitrogen which is conversely related to temperature. The biochar obtained through pyrolysis at 400 °C demonstrated superior characteristics compared to biochar produced at other temperatures. It exhibited a higher biochar yield, with approximately 84.60% for pigeonpea and 64.85% for maize fixed carbon content. Additionally, the energy retention efficiency was higher, reaching 67.33% for pigeonpea and 42.70% for maize-derived biochar at a pyrolysis temperature of 400 °C. The fixed carbon recovery efficiency was also notable at around 200.44% for PPS and 142.37% for maize biochar which is higher compared to biochar produced at other temperatures. Furthermore, the higher heating value (HHV) was approximately 30.75 MJ kg−1 for both the biochars, indicating their suitability as alternative solid fuels. A significant CO2 reduction potential of 84 CO2 eq kg−1 and 55 CO2 eq kg−1 was observed for pigeonpea and maize biochar, respectively. Hence, biochar is a promising and effective option for carbon sequestration, offering environmental benefits. Graphical Abstract

Parkinson’s disease (PD) is a progressive neurodegenerative disease with multiple motor and non-motor characteristics. PD patients commonly face vocal impairments during the early stages of the disease. Therefore, diagnosis systems based on vocal disorders are at the forefront of recent PD detection studies. Our study proposes two frameworks based on Convolutional Neural Networks to classify Parkinson’s disease (PD). In recent years, Convolutional Neural Networks (CNNs) have proven highly effective in various medical applications, particularly disease classification. However, standard CNN designs have significant limitations because they require extensive manual calibration and supervision, which can result in biases and poor performance in practical applications. This paper proposes the Self-Operating Convolutional Neural Network (SOCNN) in conjunction with Convergent Cross-Mapping (CCM) to address these issues. The SOCNN architecture is intended to modify its internal parameters automatically, eliminating the need for manual intervention during training and increasing the model’s adaptability to unknown data. Adopting CCM principles, we construct a seamless connection between the input and output domains, allowing for rapid information transfer and preservation, which are crucial for accurate disease classification. To this end, we construct causal networks, extract network features, and perform deep learning analysis to distinguish Parkinson’s disease patients (PD) from age and gender-matched healthy controls (HC). Using a large dataset of Parkinson’s Disease (PD) patients and healthy controls, the effectiveness of the proposed SOCNN with CCM is evaluated. Specifically, we use the SOCNN-CCM to compute the centrality of the network nodes, which act as features for the classification models. Extensive experiments are conducted to compare the SOCNN to conventional CNN models and innovative techniques. The results demonstrate that the SOCNN-CMM outperforms state-of-the-art in terms of accuracy, sensitivity, and specificity when classifying Parkinson’s patients, confirming its diagnostic potential.

Inconel 600, a Ni-based alloy was considered as a possible replacement for austenitic stainless steels for service at high temperatures in nitrogen containing atmosphere of the neutron detector. To obtain a fundamental understanding of the differences in the diffusivity of nitrogen in pure Fe and Ni lattices, molecular dynamics simulations were carried out. Based on the simulation of nitrogen trajectories in the temperature range of 1200–1400 K, pre-exponential factor, activation energy and jumping frequency were calculated and compared for fcc Ni and Fe. MD simulations confirmed that rate of diffusion of nitrogen is lower in Ni when compared to Fe, suggesting the replacement of austenitic steel with Inconel 600 for better performance of the detectors.

This work projects photoluminescence (PL) as an alternative technique to estimate the order of resistivity of zinc oxide (ZnO) thin films. ZnO thin films, deposited using chemical spray pyrolysis (CSP) by varying the deposition parameters like solvent, spray rate, pH of precursor, and so forth, have been used for this study. Variation in the deposition conditions has tremendous impact on the luminescence properties as well as resistivity. Two emissions could be recorded for all samples—the near band edge emission (NBE) at 380 nm and the deep level emission (DLE) at ~500 nm which are competing in nature. It is observed that the ratio of intensities of DLE to NBE (/) can be reduced by controlling oxygen incorporation in the sample. - measurements indicate that restricting oxygen incorporation reduces resistivity considerably. Variation of / and resistivity for samples prepared under different deposition conditions is similar in nature. / was always less than resistivity by an order for all samples. Thus from PL measurements alone, the order of resistivity of the samples can be estimated.

Background: Pulses play an important role in Indian agriculture for sustainable production, improvement in soil health and environmental safety. They are a cheaper source of protein to overcome malnutrition among vegetarians due to the presence of a high percentage of quality protein which is nearly three times more than that of cereals. They are more responsive to organic manures but indiscriminate and continuous use of chemical fertilizers has venomous effects on soil physical, chemical and biological properties thereby affecting the sustainability of crop production, besides causing environmental pollution. Methods: The experiment consists of 12 treatments comprising organic amendments laid out in RCBD (completely randomized block design) with three replications. The black gram variety TAU-1 was sown with a spacing of 45 cm x 10 cm. The recommended dose of phosphorus for black gram was supplemented with different combinations of soil organic manures with equal proportions based on their P content. The required quantity of organic manures viz., Farmyard manure, vermicompost, Ghanajeevamrutha were uniformly incorporated into the soil as per the treatment three weeks before sowing. The organic manures to be applied were quantified equivalent to RDF (20 kg N + 50 kg P2O5 + 0 kg K2O ha-1). Result: The studies showed that application of vermicompost+ghanajeevamrutha based on 100% RDP (Recommended dose of phosphorus)+Rhizobium+PSB (Phosphorus Solubilizing bacteria) recorded significantly higher plant height (87.67 cm), number of branches per plant (6.33), relative chlorophyll content (48.11) and dry matter (2740.00 kg ha-1) with higher concomitant seed quality parameters like seed index (10.25 g) and protein content (22.7%) as compared to others. This study has demonstrated the importance of the usage of organics for improving the growth and seed quality parameters in black gram. [ABSTRACT FROM AUTHOR]

Abstract A highly selective, sensitive caffeic acid (CA) detection based on calcium oxide nanoparticles (CaO NPs) derived from extract of Moringa oleifera leaves decorated graphitic carbon nitride covalently grafted poly vinyl alcohol (CaO/g-C3N4/PVA) nanocomposite modified glassy carbon electrode (GCE) was studied. A facile sonochemical method was adapted to synthesis nanomaterials and characterized by HR-TEM (High resolution transmission electron microscopy), FT-IR (Fourier transform infrared spectroscopy), XRD (X-ray diffraction), FE-SEM (Field emission scanning electron microscopy), EDX (Energy dispersive X-ray analysis), Mapping and BET (Brunauer-Emmett-Teller) analysis, and electrochemical techniques. The nanocomposite modified GCE exhibited an excellent catalytic performance to the oxidation of CA under optimized conditions owing to better electron transfer efficiency, conductivity and high surface area of the electrode material. The present electrochemical sensor showed high selectivity towards the determination of 10 µM CA in the presence of 100-fold higher concentrations of interferents. The modified CA sensor exhibited a wide sensing linear range from 0.01 µM to 70 µM and the detection limit (LOD) was found to be 0.0024 µM (S/N = 3) in 0.1 M phosphate buffer saline (PBS) as a supporting electrolyte at pH 7.0. The fabricated CA sensor provides an excellent stability, reproducibility and selectivity for the determination of CA. The modified CA sensor was applied to real blood plasma samples and obtained good recovery (97.6-100.1%) results.

Phycocyanin from Spirulina (blue-green algae) is used as photosensitizer to fabricate biosensitized solar cells (BSSC). Pigments are extracted in different solvents such as water, ethanol and acetone. Pure and silver-doped ZnO nanoparticles were prepared by simple microwave technology, and BSSCs were prepared by spin coating method. The structure, morphology, optical properties and electrochemistry of the prepared materials were examined by powder X-ray diffraction, field emission scanning electron microscopy (FE-SEM), transmission electron microscopy (TEM), ultraviolet-visible light spectroscopy and electrochemical impedance spectroscopy. The main observation of this research is the decrease of the energy band gap value due to doping of “Ag” ions, which will delay the recombination rate and increase the photovoltaic conversion efficiency by 2.87 % compared to pure ZnO nanoparticles (0.74 %). The photocurrent density-photo voltage (J-V) characteristics of fabricated BSSC using Pycocyanine pigments under various solvent-adsorbed conditions on nanocrystalline pure ZnO and Ag-doped ZnO film electrodes were carried out. The pigments in association with the water solution show the short-circuit photocurrent density Jsc of around 9.80 mA/cm2 and the open-circuit photovoltage Voc of 0.84 V, under an illumination intensity of 40 mW/cm2 respectively. The results of the present study reveals that “Ag” doped ZnO nanoparticles may be a promising candidate for the future BSSC applications.