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"Kumar, Dhirendra"
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Determination of optimal daily light integral (DLI) for indoor cultivation of iceberg lettuce in an indigenous vertical hydroponic system
The indoor cultivation of lettuce in a vertical hydroponic system (VHS) under artificial lighting is an energy-intensive process incurring a high energy cost. This study determines the optimal daily light integral (DLI) as a function of photoperiod on the physiological, morphological, and nutritional parameters, as well as the resource use efficiency of iceberg lettuce (cv. Glendana) grown in an indoor VHS. Seedlings were grown in a photoperiod of 12 h, 16 h, and 20 h with a photosynthetic photon flux density (PPFD) of 200 µmol m
−2
s
−1
using white LED lights. The results obtained were compared with VHS without artificial lights inside the greenhouse. The DLI values for 12 h, 16 h, and 20 h were 8.64, 11.5, and 14.4 mol m
−2
day
−1
, respectively. The shoot fresh weight at harvest increased from 275.5 to 393 g as the DLI increased from 8.64 to 11.5 mol m
−2
day
−1
. DLI of 14.4 mol m
−2
day
−1
had a negative impact on fresh weight, dry weight, and leaf area. The transition from VHS without artificial lights to VHS with artificial lights resulted in a 60% increase in fresh weight. Significantly higher water use efficiency of 71 g FW/L and energy use efficiency of 206.31 g FW/kWh were observed under a DLI of 11.5 mol m
−2
day
−1
. The study recommends an optimal DLI of 11.5 mol m
−2
day
−1
for iceberg lettuce grown in an indoor vertical hydroponic system.
Journal Article
Mechanisms of Pathogenic Candida Species to Evade the Host Complement Attack
species are common colonizers of the human skin, vagina, and the gut. As human commensals,
species do not cause any notable damage in healthy individuals; however, in certain conditions they can initiate a wide range of diseases such as chronic disseminated candidiasis, endocarditis, vaginitis, meningitis, and endophthalmitis. The incidence of
caused infections has increased worldwide, with mortality rates exceeding 70% in certain patient populations.
, and
are responsible for more than 90% of
-related infections. Interestingly, the host immune response against these closely related fungi varies. As part of the innate immune system, complement proteins play a crucial role in host defense, protecting the host by lysing pathogens or by increasing their phagocytosis by phagocytes through opsonization. This review summarizes interactions of host complement proteins with pathogenic
species, including
and non
species such as
. We will also highlight the various ways of complement activation, describe the antifungal effects of complement cascades and explore the mechanisms adopted by members of pathogenic
species for evading complement attack.
Journal Article
Consumer electronics based smart technologies for enhanced terahertz healthcare having an integration of split learning with medical imaging
The proposed work contains three major contribution, such as smart data collection, optimized training algorithm and integrating Bayesian approach with split learning to make privacy of the patent data. By integrating consumer electronics device such as wearable devices, and the Internet of Things (IoT) taking THz image, perform EM algorithm as training, used newly proposed slit learning method the technology promises enhanced imaging depth and improved tissue contrast, thereby enabling early and accurate disease detection the breast cancer disease. In our hybrid algorithm, the breast cancer model achieves an accuracy of 97.5 percent over 100 epochs, surpassing the less accurate old models which required a higher number of epochs, such as 165.
Journal Article
Multivariate stability analysis to select elite rice (Oryza sativa L.) genotypes for grain yield, zinc and Iron
The present study was conducted to evaluate 30 rice genotypes at three different locations in eastern Uttar Pradesh during the Wet- 2020–21 and determine the impact of GEI on grain yield (tha
-1
), days to 50% flowering, grain Fe content (PPM), and grain Zn content (PPM). The study also aimed to identify the genotypes that displayed the best performance according to the multi-trait stability index (MTSI), multi-trait genotype-ideotype distance index (MGIDI), and factor analysis and ideotype-design (FAI-BLUP) index. AMMI analysis demonstrated significant variation for environment (E), genotype (G), and genotype-by-environment interaction (GEI) (P < 0.01) for all the studied traits. The AMMI1 biplot showed that PC1 explained the majority of the variation for GY (77.6%), DTF (90.5%), Fe (73.5%), and Zn (86.8%), helping to identify stable and high-performing genotypes. AMMI2 biplot further resolved complex GEI patterns, highlighting genotypes with specific adaptability to individual environments. The GGE biplot revealed clear “which-won-where” patterns for GY, DTF, Fe, and Zn, explaining 94.37%, 99.71%, 83.49%, and 96.93% of GEI variation, respectively. BLUP analysis using a linear mixed model revealed significant GEI effects for GY, DTF, Fe, and Zn across 30 rice genotypes in three environments. Low heritability was observed for Fe (28.2%) and moderate for GY (54.4%) and Zn (56.4%), while DTF showed high heritability with strong genotypic accuracy. Genotype G7 was identified as stable, early, high-yielding, and rich in Fe based on HMGV, RPGV, and HMRPGV indices. The MTSI, MGIDI and FAI-BLUP analysis revealed that BHU-SKS-1 (G15) and IR105696 -1–2-3–1-1–1 -B (G9) were the most stable and best mean performer for high grain yield and high grain Fe & Zn content, while IR 108,195–3-1–1-2 (G7) was the most stable and best mean performer for high grain yield and high grain Fe content with early flowering.
Journal Article
Silicon Supplementation Alleviates the Salinity Stress in Wheat Plants by Enhancing the Plant Water Status, Photosynthetic Pigments, Proline Content and Antioxidant Enzyme Activities
Silicon (Si) is the most abundant element on earth after oxygen and is very important for plant growth under stress conditions. In the present study, we inspected the role of Si in the mitigation of the negative effect of salt stress at three concentrations (40 mM, 80 mM, and 120 mM NaCl) in two wheat varieties (KRL-210 and WH-1105) with or without Si (0 mM and 2 mM) treatment. Our results showed that photosynthetic pigments, chlorophyll stability index, relative water content, protein content, and carbohydrate content were reduced at all three salt stress concentrations in both wheat varieties. Moreover, lipid peroxidation, proline content, phenol content, and electrolyte leakage significantly increased under salinity stress. The antioxidant enzyme activities, like catalase and peroxidase, were significantly enhanced under salinity in both leaves and roots; however, SOD activity was drastically decreased under salt stress in both leaves and roots. These negative effects of salinity were more pronounced in WH-1105, as KRL-210 is a salt-tolerant wheat variety. On the other hand, supplementation of Si improved the photosynthetic pigments, relative water, protein, and carbohydrate contents in both varieties. In addition, proline content, MDA content, and electrolyte leakage were shown to decline following Si application under salt stress. It was found that applying Si enhanced the antioxidant enzyme activities under stress conditions. Si showed better results in WH-1105 than in KRL-210. Furthermore, Si was found to be more effective at a salt concentration of 120 mM compared to low salt concentrations (40 mM, 80 mM), indicating that it significantly improved plant growth under stressed conditions. Our experimental findings will open a new area of research in Si application for the identification and implication of novel genes involved in enhancing salinity tolerance.
Journal Article
Engineering Aspects of Incidence, Prevalence, and Management of Osteoarthritis: A Review
The knee is the biggest and complicated lower extremity joint that supports mobility and the entire weight of the human body and lies between the hip joint and ankle joint. Osteoarthritis (OA) is the most common joint disease in the knee among various musculoskeletal disorders globally, with an age-associated increase in incidence and prevalence. Health monitoring of the knee joints in daily life, and early OA diagnosis is challenging and draws attention to the various methods of diagnosis for this irreversible disease. In this review, electronic databases have been searched from inception for a detailed study about knee OA and its management. It focuses on various sensor technologies and different semi-invasive and non-invasive diagnosis methods with their limitations. In the last decade, various researchers have engrossed their attention to the potential of piezoelectric-based acoustic sensors to fabricate a wearable device for OA and its management. A sensor-based wearable device using vibroarthrography as a tool can be an appropriate solution for early-stage disease detection. We firmly believe that wearable technology for the detection of OA in daily life activities will play a significant role in managing this disease and help to reduce the chances of total knee replacements.
Journal Article
Computational Advances in Ionic Liquid Applications for Green Chemistry: A Critical Review of Lignin Processing and Machine Learning Approaches
The valorization and dissolution of lignin using ionic liquids (ILs) is critical for developing sustainable biorefineries and a circular bioeconomy. This review aims to critically assess the current state of computational and machine learning methods for understanding and optimizing IL-based lignin dissolution and valorization processes reported since 2022. The paper examines various computational approaches, from quantum chemistry to machine learning, highlighting their strengths, limitations, and recent advances in predicting and optimizing lignin-IL interactions. Key themes include the challenges in accurately modeling lignin’s complex structure, the development of efficient screening methodologies for ionic liquids to enhance lignin dissolution and valorization processes, and the integration of machine learning with quantum calculations. These computational advances will drive progress in IL-based lignin valorization by providing deeper molecular-level insights and facilitating the rapid screening of novel IL-lignin systems.
Journal Article
Methyl Salicylate Is a Critical Mobile Signal for Plant Systemic Acquired Resistance
In plants, the mobile signal for systemic acquired resistance (SAR), an organism-wide state of enhanced defense to subsequent infections, has been elusive. By stimulating immune responses in mosaic tobacco plants created by grafting different genetic backgrounds, we showed that the methyl salicylate (MeSA) esterase activity of salicylic acid-binding protein 2 (SABP2), which converts MeSA into salicylic acid (SA), is required for SAR signal perception in systemic tissue, the tissue that does not receive the primary (initial) infection. Moreover, in plants expressing mutant SABP2 with unregulated MeSA esterase activity in SAR signal-generating, primary infected leaves, SAR was compromised and the associated increase in MeSA levels was suppressed in primary infected leaves, their phloem exudates, and systemic leaves. SAR was also blocked when SA methyl transferase (which converts SA to MeSA) was silenced in primary infected leaves, and MeSA treatment of lower leaves induced SAR in upper untreated leaves. Therefore, we conclude that MeSA is a SAR signal in tobacco.
Journal Article
EDM-based analysis of Fe-based shape memory alloys using Cu-W electrodes with multiple output optimization and microstructural validation
Shape Memory Alloys (SMAs) are pivotal in diverse industrial applications due to their exceptional properties, including actuation, biocompatibility, and adaptability in aerospace, biomedical, and military domains. However, their complex machinability often leads to high costs and suboptimal surface quality when processed using traditional methods. Using Response Surface Methodology (RSM) with a Central Composite Design (CCD), this study evaluated the effects of input parameters, including pulse on time (T
on
), pulse off time (T
off
), peak current (Ip), and gap voltage (GV), on material wear responses during Electrical Discharge Machining (EDM). Fe-based Shape Memory Alloys (SMAs) were machined using a Cu-tungsten electrode to investigate the wear characteristics of both workpieces and tool electrodes. Results revealed that Workpiece Material Removal Rate (WOW) ranged from 11.30 to 65.17 mm³/min, and Tool Wear Rate (WOTE) varied from 0.0062 to 0.01127 g/min. Scanning Electron Microscopy (SEM) of machined surfaces showcased craters, micro-cracks, and recast layers, elucidating the correlation between process parameters and surface integrity. Multi-objective optimization using the desirability approach identified optimal conditions for balancing machining efficiency and surface quality. This research provides a comprehensive understanding of the EDM process for Fe-based SMAs, paving the way for improved machinability and expanded industrial applications.
Journal Article