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IntroductionThe increase in atmospheric CO2 concentration, which mainly is attributed to fossil-fuel combustion and deforestation, is often suggested as one of the prime causative factors toward accelerated global warming. This commends for sequestration of atmospheric carbon under terrestrial systems to partially offset fossil-fuel emissions. Concerning the same, agricultural sector presents an extensive opportunity, especially for countries such as India where over 55% of the population is engaged in the agriculture sector.MethodsSequestering atmospheric carbon in agriculture requires the adoption of climate-resilient alternative agriculture practices without compromising food security. The deliberated study highlights the options of alteration in current conventional farming practices and its economic evaluation for sequestrating carbon under two Climate Change (CC) scenarios, viz., RCP 4.5 and 8.5, over three temporal scales, i.e., 2020, 2030, and 2050. Considering the current land-use pattern and existing growth rate in land-use shifting, three land-use policies, namely, Business as Usual (BaU), Optimistic, and Pessimistic scenario, integrated with CC scenarios were contemplated. Six possible futuristic scenarios were generated for the assessment of carbon sequestration and its valuation following the Integrated Valuation of Ecosystem Services and Tradeoff (InVEST) model.ResultsThe results suggested that across the studied region adopting an optimistic policy over BaU and pessimistic scenario, carbon can sequestrate an additional 0.64 to 1.46 Mt. (2.35 to 5.36 million ton CO2e) having an economic value of 193.4 to 504.8 million USD.ResultsMoreover, the outcomes of the study are advocated for the policy of carbon credit in the agriculture sector, which shall contribute toward meeting various nationally determined contributions (NDCs) and sustainable development goals (SDGs) as well.

Rare Earth Zirconates with pyrochlore/flourite structure have attracted interests owing to their immense potential in modern technological applications. Among these, Lanthanum Zirconates are a promising top coat thermal barrier material and also a candidate nuclear waste host matrix for radionuclide immobilization. Despite its candidacy for these high-tech applications, the fundamental questions related to process—structure—property correlation still lacks a thorough understanding and this article is an attempt to bridge this gap. The current study investigates the microstructural characteristics of Lanthanum Zirconate powders synthesized using co-precipitation method under various pH, annealing temperature and hold durations. An evolution from disordered to ordered pyrochlore structure is observed at a relatively lower annealing temperature of 950 °C, as investigated through x-ray diffraction and Raman spectroscopy, confirmed via synchrotron investigations. Further examinations of the samples synthesized at varied pH conditions indicated a relatively high surface area and stable microstructure with a lower propensity for grain growth for the samples synthesized at pH 11. The comprehensive material microstructural information as a function of process conditions studied here is thought to be crucial for microstructure tailoring in both pristine and doped Lanthanum Zirconates.

A first-of-its-kind, inductively driven micro-particle (Pellet) accelerator and injector have been developed and operated successfully in ADITYA-U circular plasma operations, which may ably address the critical need for a suitable disruption control mechanism in ITER and future tokamak. The device combines the principles of electromagnetic induction, pulse power technology, impact, and fracture dynamics. It is designed to operate in a variety of environments, including atmospheric pressure and ultra-high vacuum. It can also accommodate a wide range of pellet quantities, sizes, and materials and can adjust the pellets’ velocities over a coarse and fine range. The device has a modular design such that the maximum velocity can be increased by increasing the number of modules. A cluster of lithium titanate/carbonate (Li _2 TiO _3 /Li _2 CO _3 ) impurity particles with variable particle sizes, weighing ∼50–200 mg are injected with velocities of the order of ∼200 m s ^−1 during the current plateau in ADITYA-U tokamak. This leads to a complete collapse of the plasma current within ∼5–6 ms of triggering the injector. The current quench time is dependent on the amount of impurity injected as well as the compound, with Li _2 TiO _3 injection causing a faster current quench than Li _2 CO _3 injection, as more power is radiated in the case of Li _2 TiO _3 . The increase in radiation due to the macro-particle injection starts in the plasma core, while the soft x-ray emission indicates that the entire plasma core collapses at once.

Malaria, dengue and leptospirosis are three tropical infectious diseases that present with severe hematological derangement causing significant morbidity and mortality, especially during the seasonal monsoons. During the course of these infectious diseases, circulating red blood cells are imperiled to the direct ill-effects of the infectious pathogen in the body as well as to the pro-inflammatory cytokines generated as a consequence of the infection. RBCs when exposed to such inflammatory and/or pathogenic milieu are susceptible to injuries such as RBC programmed eryptosis or RBC programmed necrosis. This research aimed to explore the Raman spectra of live red cells that were extracted from patients infected with malaria, dengue, and leptospirosis. Red cells were optically trapped and micro-Raman probed using a 785 nm Diode laser. RBCs from samples of all three diseases displayed Raman signatures that were significantly altered from the normal/healthy. Distinct spectral markers that were common across all the four groups were obtained from various standardized multivariate analytical methods. Following comprehensive examination of multiple studies, we propose these spectral wavenumbers as “Raman markers of RBC injury.” Findings in our study display that anemia-triggering infections can inflict variations in the healthy status of red cells, easily identifiable by selectively analyzing specific Raman markers. Additionally, this study also highlights relevant statistical tools that can be utilized to study Raman spectral data from biological samples which could help identify the very significant Raman peaks from the spectral band. This approach of RBC analysis can foster a better understanding of red cell behavior and their alterations exhibited in health and disease.

Over the past decade, the artificial neural networks domain has seen a considerable embracement of deep neural networks among many applications. However, deep neural networks are typically computationally complex and consume high power, hindering their applicability for resource-constrained applications, such as self-driving vehicles, drones, and robotics. Spiking neural networks, often employed to bridge the gap between machine learning and neuroscience fields, are considered a promising solution for resource-constrained applications. Since deploying spiking neural networks on traditional von-Newman architectures requires significant processing time and high power, typically, neuromorphic hardware is created to execute spiking neural networks. The objective of neuromorphic devices is to mimic the distinctive functionalities of the human brain in terms of energy efficiency, computational power, and robust learning. Furthermore, natural language processing, a machine learning technique, has been widely utilized to aid machines in comprehending human language. However, natural language processing techniques cannot also be deployed efficiently on traditional computing platforms. In this research work, we strive to enhance the natural language processing traits/abilities by harnessing and integrating the SNNs traits, as well as deploying the integrated solution on neuromorphic hardware, efficiently and effectively. To facilitate this endeavor, we propose a novel, unique, and efficient sentiment analysis model created using a large-scale SNN model on SpiNNaker neuromorphic hardware that responds to user inputs. SpiNNaker neuromorphic hardware typically can simulate large spiking neural networks in real time and consumes low power. We initially create an artificial neural networks model, and then train the model using an Internet Movie Database (IMDB) dataset. Next, the pre-trained artificial neural networks model is converted into our proposed spiking neural networks model, called a spiking sentiment analysis (SSA) model. Our SSA model using SpiNNaker, called SSA-SpiNNaker, is created in such a way to respond to user inputs with a positive or negative response. Our proposed SSA-SpiNNaker model achieves 100% accuracy and only consumes 3970 Joules of energy, while processing around 10,000 words and predicting a positive/negative review. Our experimental results and analysis demonstrate that by leveraging the parallel and distributed capabilities of SpiNNaker, our proposed SSA-SpiNNaker model achieves better performance compared to artificial neural networks models. Our investigation into existing works revealed that no similar models exist in the published literature, demonstrating the uniqueness of our proposed model. Our proposed work would offer a synergy between SNNs and NLP within the neuromorphic computing domain, in order to address many challenges in this domain, including computational complexity and power consumption. Our proposed model would not only enhance the capabilities of sentiment analysis but also contribute to the advancement of brain-inspired computing. Our proposed model could be utilized in other resource-constrained and low-power applications, such as robotics, autonomous, and smart systems.

Papaya ringspot virus (PRSV) is a significant threat to global papaya cultivation, causing ringspot disease, and it belongs to the species Papaya ringspot virus, genus Potyvirus, and family Potyviridae. This study aimed to assess the occurrence and severity of papaya ringspot disease (PRSD) in major papaya-growing districts of Karnataka, India, from 2019 to 2021. The incidence of disease in the surveyed districts ranged from 50.5 to 100.0 percent, exhibiting typical PRSV symptoms. 74 PRSV infected samples were tested using specific primers in RT-PCR, confirming the presence of the virus. The complete genome sequence of a representative isolate (PRSV-BGK: OL677454) was determined, showing the highest nucleotide identity (nt) (95.8%) with the PRSV-HYD (KP743981) isolate from Telangana, India. It also shared an amino acid (aa) identity (96.5%) with the PRSV-Pune VC (MF405299) isolate from Maharashtra, India. Based on phylogenetic and species demarcation criteria, the PRSV-BGK isolate was considered a variant of the reported species and designated as PRSV-[IN:Kar:Bgk:Pap:21]. Furthermore, recombination analysis revealed four unique recombination breakpoint events in the genomic region, except for the region from HC-Pro to VPg, which is highly conserved. Interestingly, more recombination events were detected within the first 1710 nt, suggesting that the 5’ UTR and P1 regions play an essential role in shaping the PRSV genome. To manage PRSD, a field experiment was conducted over two seasons, testing various treatments, including insecticides, biorationals, and a seaweed extract with micronutrients, alone or in combination. The best treatment involved eight sprays of insecticides and micronutrients at 30-day intervals, resulting in no PRSD incidence up to 180 days after transplanting (DAT). This treatment also exhibited superior growth, yield, and yield parameters, with the highest cost–benefit ratio (1:3.54) and net return. Furthermore, a module comprising 12 sprays of insecticides and micronutrients at 20-day intervals proved to be the most effective in reducing disease incidence and enhancing plant growth, flowering, and fruiting attributes, resulting in a maximized yield of 192.56 t/ha.

The incidence and severity of begomovirus diseases have been increasing around the world recently, and the ridge gourd [Luffa acutangula (Roxb.) L.] is the latest example of a crop that has become highly susceptible to the outbreak of the tomato leaf curl New Delhi virus (ToLCNDV, genus Begomovirus) in India. Accurate diagnosis of causal agents is important in designing disease management strategies. In this study the coat protein (CP) gene from a ToLCNDV-Rg ridge gourd isolate was used to produce polyclonal antibodies (ToLCNDV-Rg-CP-PAb) in a rabbit. The antibodies successfully detected a 30.5 kDa ToLCNDV-Rg-CP in extracts of symptomatic ridge gourd leaf samples by several assays, such as Western Blotting (WB), Dot Immuno Binding Assay (DIBA), Direct Antigen Coating Enzyme Linked Immuno Sorbent Assay (DAC-ELISA), Immuno Capture Polymerase Chain Reaction (IC-PCR), and Immuno Capture Loop-Mediated Isothermal Amplification (IC-LAMP) assays. However, none of the negative samples tested positive in either of the detection methods. Among all the methods tested, the immunocapture assay, IC-LAMP, was the most sensitive in detecting ToLCNDV-Rg. Furthermore, antibodies generated in this study also detected other commonly occurring begomoviruses in South India, such as tomato leaf curl Palampur virus and squash leaf curl China virus in cucurbits. Together, ToLCNDV-Rg-CP-PAb can be used for detecting at least three species of begomoviruses infecting cucurbits. The obtained antibodies will contribute to monitoring disease outbreaks in multiple crops.

Papaya (Carica papaya L.) is one of the most important fruit crops grown in tropical and subtropical regions of the world. Papaya leaf curl disease is one of the greatest concerns next to Papaya ring spot disease for India and the world. A survey was conducted during the year 2019 to 2021 for assessing the leaf curl disease incidence in five major papaya-growing districts of Karnataka State, India. The incidence ranged from 10 to 21 percent, with plants expressing typical begomovirus symptoms. Thirty-two virus-infected papaya samples (PLC-1 to PLC-32), collected from different farmer’s fields, gave positive amplification for begomovirus detection. Based on the partial genome analysis, 13 representative papaya leaf curl isolates were selected for complete genome amplification by rolling circle DNA amplification (RCA). The RCA products were cloned, sequenced and analyzed. Based on the analysis and strain classification criteria for begomoviruses, five isolates (PLC-2, 3, 9, 11 and 18) were considered variants of Chilli leaf curl virus (ChiLCV). Isolate PLC-22 is considered a strain of ChiLCV, with 93.5% nt identity sharing. Similarly, isolate PLC-28 is considered a strain of Croton yellow vine mosaic virus (CYVMV), and isolates PLC-25 and PLC-31 were considered as strains of Papaya leaf curl virus (PaLCuV). Among the remaining four isolates, three (PLC-1, PLC-4 and PLC-7) share more than 91% nt identity among them and less than 91% nt identity with all other reported begomovirus isolates. Hence, they are considered to be isolates of the novel begomovirus, and the name Papaya leaf curl Bagalkote virus [India:Karnataka:Bagalkote:Papaya:2021] is proposed. One isolate (PLC-32) is also found to be distinct from all other begomovirus isolates, including the isolates in the current study also considered to be novel begomovirus, for which we propose the name Papaya leaf curl Haveri virus [India:Karnataka:Haveri:Papaya:2021]. The putative recombination analysis of all 13 papaya isolates showed that a major part of the viral genome was likely descended from the begomoviruses reported previously. This is the first report on the diversity and a distribution of the begomoviruses infecting papaya in Karnataka, India. The current investigation results revealed five major papaya-infecting begomoviruses (PaLCuBKV, ChiLCV, PaLCuV, CYVMV and PaLCuHV) in the sampled regions.

The research conducted to estimate the potential economic benefit from adoption of drought tolerant soybean (Glycine max (L.) Merr.) variety NRC-7 in Indore district of Madhya Pradesh, where majority of area is under rainfed system. In this study, the potential economic benefit in terms of economic surplus and risk reduction was estimated for NRC-7 and alternative varieties, JS-93-05 and JS 95-60. NRC-7 requires less cost of cultivation compared to other two varieties, and withstands stress condition. In normal condition, the economic surplus for NRC-7 was ₹ 686 million per year, and that of, JS-93-05 and JS 95-60 is about ₹ 3161 million, ₹ 6291 million, respectively. For NRC-7, the risk reduction benefit was to the level of ₹ 547 million, which accounted for about 83.8% of total benefits for that variety. On per ha basis, NRC 7 performs well over the other two varieties in reducing the fluctuation in income of farmers. So there is a need to develop and increase the awareness of abiotic stress tolerant varieties to cope up with the income fluctuation due to weather risks.

Derangements in bilirubin metabolism and/or dysfunctions in the hepato-biliary system lead to the unhealthy buildup of bilirubin in blood, resulting in jaundice. During the course of this disorder, circulating red cells are invariably subjected to toxic effects of serum bilirubin and an array of inflammatory compounds. This study aimed to investigate the vibrational spectroscopy of live red cells in jaundice using micro-Raman spectroscopy combined with optical-trap. Red cells from blood samples of healthy volunteers and patients with jaundice were optically immobilized and micro-Raman probed using a 785 nm diode laser. Raman signatures from red cells in jaundice exhibited significant variations from the normal and the spectral-markers were obtained from multivariate analytical methods. This research gives insightful views on how different pathologies can act as “stress-milieus” for red cells in circulation, possibly impeding their normal functions and also exasperating anemia. Raman spectroscopy, an emerging bio-analytical technique, is sensitive in detecting molecular-conformations in situ, at cellular-levels and in real-time. This study could pave way in understanding fundamental red cell behavior in different diseases by analyzing Raman markers.

Background and Aims: Pre-emptive analgesia using caudal epidural technique is an underutilized technique in lumbosacral spine surgery patients. We intend to study if pre-emptive analgesia with a single caudal epidural injection of ropivacaine is an effective method of postoperative analgesia by assessing the quality and duration of pain relief and intraoperative opioid requirement. Material and Methods: Eighty patients undergoing lumbosacral spine surgeries by the posterior approach were randomized to ropivacaine (R) group (n = 40) and saline (S) group (n = 40). Patients in R group received caudal epidural injection of 20 ml of 0.2% ropivacaine for surgeries at or below L5 lumbar spine and 25 ml of 0.2% ropivacaine for surgeries between L2 and L5 lumbar spine. Patients in S group received similar amounts of normal saline. Patients were monitored in the immediate postoperative period and at 4, 8, 12, and 24 hours for pain using visual analogue scale (VAS) scale. Time to rescue analgesia and intraoperative fentanyl requirement were noted. Results: The demographics, duration of anesthesia, and hemodynamic variables were comparable in both groups. The mean intraoperative fentanyl requirement (P = 0.001) and mean VAS scores were significantly lower in the R group in the immediate postoperative period, (P < 0.001), 4 hours (P < 0.001), 8 hours (P = 0.009), 12 hours (P = 0.007), and 24 hours (P = 0.046) postoperatively. The mean time to rescue analgesia was significantly longer in the R group (P < 0.001) compared to S group. No hemodynamic or neurological side-effects were observed in the groups. Conclusion: Pre-emptive analgesia with caudal epidural injection of ropivacaine is a safe and effective method of postoperative analgesia.

Estimation of gene expression levels plays a crucial role in understanding the function of the target gene(s). Intersample variance in gene expression can be more precisely measured if transcripts levels are accurately normalized. Normalization is pre-requisite step prior to the determination of candidate gene expression by qPCR. In this study conducted at ICAR-Central Institute for Cotton Research, Nagpur during 2015–16, six candidate reference genes, viz. actin4 (ACT4), actin7(ACT7), RNA Helicase (RNAH), Serine/threonine-protein phosphatase PP2A-1(PP2A1), ubiquitin7 (UBQ7) and α tubulin (αTUB) were systematically analysed for their expression patterns in different tissues pertaining to three development stages of cotton namely seedling, early reproductive and fiber development. The study has identified actin-4/actin-7/ubiquitin-7 as the most ideal reference genes for fiber development stages whereas actin-4/ ubiquitin-7 and actin-7/RNA helicases for seedling and early reproductive development stages, respectively. Validation of identified reference genes for relative expression analysis of Gacobl9, a COBRA-like protein, demonstrated their usefulness in qPCR analysis in Gossypium arboreum.

The institutional credit has always been perceived as a critical factor for agricultural development in India through complementing working capital, easing liquidity and investment constraints. The present study has examined the trends and regional variations in institutional credit flow to agriculture in India for the period 1991–92 to 2016–17 using compound annual growth rate. Further, impact of institutional credit on agricultural productivity was also assessed using panel data regression. The study is based on the secondary data collected from various published sources. Results indicated that institutional credit to agriculture in real terms has registered a significant positive growth during the past four decades and the highest annual growth was observed during 2001–02 to 2010–11. Scheduled commercial banks have emerged as the dominant source of agricultural credit. However, cooperative banks are still the major sources of production credit. Regional analysis showed that southern states had access to highest production and investment credit per hectare, while eastern and northeastern states had the least credit outreach per hectare. Panel data regression model testified that institutional credit has a significant and positive impact on agricultural productivity. Therefore, the study has suggested for better access to credit of smallholders especially in eastern, western and north eastern states through simplification of procedures.

Eryptosis is the suicidal destruction-process of erythrocytes, much like apoptosis of nucleated cells, in the course of which the stressed red cell undergoes cell-shrinkage, vesiculation and externalization of membrane phosphatidylserine. Currently, there exist numerous methods to detect eryptosis, both morphometrically and biochemically. This study aimed to design a simple but sensitive, automated computerized approach to instantaneously detect eryptotic red cells and quantify their hallmark morphological characteristics. Red cells from 17 healthy volunteers were exposed to normal Ringer and hyperosmotic stress with sodium chloride, following which morphometric comparisons were conducted from their photomicrographs. The proposed method was found to significantly detect and differentiate normal and eryptotic red cells, based on variations in their structural markers. The receiver operating characteristic curve analysis for each of the markers showed a significant discriminatory accuracy with high sensitivity, specificity and area under the curve values. The software-based technique was then validated with RBCs in malaria. This model, quantifies eryptosis morphometrically in real-time, with minimal manual intervention, providing a new window to explore eryptosis triggered by different stressors and diseases and can find wide application in laboratories of hematology, blood banks and medical research.

Madhya Pradesh is the major producer of soybean in India. Being predominantly rainfed, the state faces high risks in its cultivation. The study undertook a primary survey in Madhya Pradesh to analyze the risk perception of farmers, elucidate the strategies followed by farmers to adapt with the risk and to identify the factors influencing their adoption. The results infer that late onset of monsoon, erratic rainfall and pest and diseases were the major risks. The major risks were related to untimely rainfall, drought and biotic factors like diseases and pest. The major adaptation strategies adopted were intercropping (49%), crop insurance (45%), micro irrigation (17%) and varietal diversification (39%). The study discerns need to develop drought tolerant varieties for rainfed regions, low cost micro-irrigation systems, enhanced credit availability to the farmers and promotion of crop insurance to adapt with production risks.

Straight back syndrome is a congenital skeletal abnormality of the upper dorsal spine. This clinical case describes a 29-year-old woman with atypical chest pain and a changing murmur that was attributed to dynamic right ventricular outflow tract obstruction on echocardiography. (Level of Difficulty: Intermediate.)

Rhino-orbitocerebral mucormycosis (ROCM) is a fungal infection commonly affecting individuals with diabetes and those in immunocompromised states. However, infections caused by Apophysomyces elegans can involve immunocompetent individuals. The invasion pattern of cerebral mucormycosis is somewhat predictable and may occur by direct invasion or hematogenous spread. Perineural spread of the disease is unusual. Here, we report the first case of perineural extension of ROCM caused by A. elegans along the trigeminal nerve in a 25-year-old immunocompetent, nondiabetic individual.