The leather industry is a major source of environmental pollution in India. The wastewater generated by leather industries contains very high pollution parameters due to the presence of a complex ...mixture of organic and inorganic pollutants even after the treatment at a Common Effluent Treatment Plant (CETP) and disturbs the ecological flora and fauna. The nature, characteristics and toxicity of CETP treated wastewater is yet to be fully elucidated. Thus, this study aims to characterize and evaluate the toxicity of CETP treated tannery wastewater collected from the Unnao district of Uttar Pradesh, India. In addition to measuring the physico-chemical parameters, the residual organic pollutants was identified by GC-MS analysis and phytotoxicity, cytotoxicity and genotoxicity of the treated wastewater was evaluated using Vigna radiata L. and Allium cepa L. Results showed that the treated wastewater contained very high pollution parameters (TDS 3850 mg/L, BOD 680 mg/L, COD-1300 mg/L). GC-MS analysis revealed the presence of various types of residual organic pollutants including benzoic acid, 3-4,-(T-butyl) Phenyl furan-2-5-dione, benzeneacetamide, resorcinol, dibutyl phthalate, and benzene-1,2,4-triol. Further, toxicological studies showed the phytotoxic nature of the wastewater as it inhibited seed germination in V. radiata L. and root growth of A. cepa. Genotoxicity was evidenced in the root tip cell of A. cepa where chromosomal aberrations (stickiness, chromosome loss, C-mitosis, and vagrant chromosome) and nuclear abnormalities like micronucleated and binucleated cells were observed. Thus, results suggested that it is not safe to discharge these wastewater into the environment.
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•Tannery wastewater rich in organic and inorganic pollutants.•Tannery wastewater possesses genotoxic and cytotoxic pollutants.•Phytotoxic nature of tannery wastewater was evaluated by Vigna radiata seeds.•Allium cepa chromosomal tests revealed genotoxic nature of treated tannery wastewater.•Wastewater also induced chromosomal aberrations and nuclear abnormalities in cells.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
•Dynamics of two-phase boiling flow in a setup designed to mimic boiling water nuclear reactors.•Time series from radioactive particle tracking (RPT) technique used.•Flow dynamics quantified using ...recurrence plots and recurrence quantification analysis.•Flow regimes characterized using different recurrence quantification analysis parameters.
Tracer particle position time series obtained by RPT experiments were used to quantify the changes in hydrodynamics induced by boiling flows in single and multiple rods assembly. The test section under consideration is a “scaled-down” version of a typical boiling water nuclear reactor (Advanced Heavy Water Reactor (AHWR) of the Department of Atomic Energy, India). The analysis of the above-mentioned time series was done by Recurrence Plots (RP) and Recurrence Quantification Analysis (RQA). Visual differences in the RPs were detected with changes in the inlet condition and heater rods configuration. The constructing feature of the recurrence plot can be categorized in two forms: local white areas (LWA) and local bold areas (LBA). However, the change cannot be quantified by visual observation, and for this quantification RQA parameters such as Recurrence Rate (RR), Determinism (DET), and Entropy (ENT) were used. Experimental results show that the increase in liquid flow rate, decrease in inlet liquid temperature, and increase in the number of the heater rods caused increased RR, increased DET, and increased ENT.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
•MABB for incorporating Pi2 and Pi54 in the background of PB1121 and PB6 from two donors.•MABB for incorporating xa13 and Xa21 in the background of PB1121 and PB6 from P1460.•Phenotypic selection ...prior to background selection was indespensible in isolating novel recombinants.•SNPs provide better insights into RPG recovery than that of SSR markers.•Pyramids were resistant for bacterial blight and blast with high yield in multilocation evaluation.
Marker assisted backcross breeding was employed to incorporate the blast resistance genes, Pi2 and Pi54 and bacterial blight (BB) resistance genes xa13 and Xa21 into the genetic background of Pusa Basmati 1121 (PB1121) and Pusa Basmati 6. Foreground selection for target gene(s) was followed by arduous phenotypic and background selection which fast-tracked the recovery of recurrent parent genome (RPG) to an extent of 95.8% in one of the near-isogenic lines (NILs) namely, Pusa 1728-23-33-31-56, which also showed high degree of resemblance to recurrent parent, PB6 in phenotype. The phenotypic selection prior to background selection provided an additional opportunity for identifying the novel recombinants viz., Pusa 1884-9-12-14 and Pusa 1884-3-9-175, superior to parental lines in terms of early maturity, higher yield and improved quality parameters. There was no significant difference between the RPG recovery estimated based on SSR or SNP markers, however, the panel of SNPs markers was considered as the better choice for background selection as it provided better genome coverage and included SNPs in the genic regions. Multi-location evaluation of NILs depicted their stable and high mean performance in comparison to the respective recurrent parents. The Pi2+Pi54 carrying NILs were effective in combating a pan-India panel of Magnaporthe oryzae isolates with high level of field resistance in northern, eastern and southern parts of India. Alongside, the PB1121-NILs and PB6-NILs carrying BB resistance genes xa13+Xa21 were resistant against Xanthomonas oryzae pv. oryzae races of north-western, southern and eastern parts of the country. Three of NILs developed in this study, have been promoted to final stage of testing during the Kharif 2015 in the Indian National Basmati Trial.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Fluidized beds are central to numerous applications such as drying, combustion, gasification, pyrolysis, CO2 utilization, mixing, and separation. The design and development of fluidized beds are ...still evolving owing to the complex hydrodynamics. Various experimental investigations and CFD simulations have been carried out to understand its hydrodynamics. Whereas the experimental approaches are very costly and limited to small scale, CFD modeling on the other hand requires significant computational resources and time. Thus, in this contribution, we propose a hybrid CFD-based ML model for estimating the hydrodynamics of fluidized beds. The CFD simulations of Taghipour et al., 2005 were performed and validated with the experimental measurements for a wide range of inlet gas velocities encompassing multiple flow regimes. A time-averaged simulation data of the CFD model was used for developing a Deep Neural Network (DNN) model. The hydrodynamic parameters, such as solid velocity field, volume fraction, and bed pressure drop, are predicted using the CFD-based DNN model. The results demonstrate that DNN has superior spatial learning capabilities and that, when used with CFD, it can reduce the computational power required without sacrificing accuracy. To evaluate the versatility of the CFDbased DNN model with different operating conditions and hydrodynamic parameters, independent data from (Cloete et al., 2013) and (Li and Zhang, 2013) were used for satisfactory validation.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
In line with the pursuit of clean and affordable energy, our study contributes to the United Nations Sustainable Development Goals (UNSDGs-7 and -13) and the global fight against climate change by ...offering evidence-based insights. We conducted a panel analysis of BRICS (Brazil, the Russian Federation, India, China, and South Africa) economies to investigate the relationship between financial development and renewable energy utilization. Our empirical findings highlight a positive statistical association between economic growth and renewable energy consumption, indicating that higher economic growth correlates with increased renewable energy adoption. Similarly, significant positive relationships are observed between the consumer price index and domestic credit with renewable energy consumption. Moreover, our study also uncovers a counterintuitive relationship between foreign direct investment and renewable energy consumption. These results provide valuable insights into the determinants of renewable energy consumption in BRICS countries. From a policy perspective, we advocate for robust strategies to promote the adoption and utilization of renewable energy sources alongside the implementation of policies encouraging the uptake of clean technologies. Such measures can spur economic growth and contribute to achieving low-carbon targets and sustainability goals within the BRICS economies. Practical steps, including incentives like feed-in tariffs and subsidies, can further enhance the cost-effectiveness of renewable energy adoption in the investigated bloc.
•Financial development plays a vital role in BRICS energy consumption patterns.•Economic growth displays a positive nexus with renewable energy consumption.•CPI and renewable energy reveals positive significant relationship.•Adoption of clean technologies option will spur economic growth in BRICS.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Despite the success of behavioral finance, the question of whether behavioral biases persist in the face of expertise is an oft-expressed concern. It becomes pertinent to explore if investor ...sophistication is associated with behavioral biases, as traders gain sophistication with experience and knowledge. The current study explores this relationship by proposing a new conceptualization of investors’ sophistication via the processes of learning and competition. The study empirically explores if herding and overconfidence biases are related to learning and competition, and thus, with investors’ sophistication via these aspects. Using data from equity investors from India (n = 257), the study employs ANOVA and multiple regression analysis through indicator function to form dummy variables for different categories. The results of the study conclude that diversification is significantly related to both the biases using ANOVA (F(3,253) = 3.081; p < 0.05) as well as multiple regression (p < 0.05). The other variables considered are found to be non-significant (p > 0.05) for both the biases. The study controls for all the other observed variables of the conceptual model to find out the effect of the change in the observed variables on the level of investor sophistication, making this study a novel and a distinct attempt.
Among many drugs that hold potential in COVID-19 pandemic, chloroquine (CQ), and its derivative hydroxychloroquine (HCQ) have generated unusual interest. With increasing usage, there has been growing ...concern about the prolongation of QTc interval and Torsades de Pointes (TdP) with HCQ, especially in combination with azithromycin.
This meta-analysis is planned to study the risk of QTc prolongation and Torsades de pointes (TdP) by a well-defined criterion for HCQ, CQ alone, and in combination with Azithromycin in patients with COVID-19.
A comprehensive literature search was made in two databases (PubMed, Embase). Three outcomes explored in the included studies were frequency of QTc > 500 ms (ms) or ΔQTc > 60 ms (Outcome 1), frequency of QTc > 500 ms (Outcome 2) and frequency of TdP (Outcome 3). Random effects method with inverse variance approach was used for computation of pooled summary and risk ratio.
A total of 13 studies comprising of 2138 patients were included in the final analysis. The pooled prevalence of outcome 1, outcome 2 and outcome 3 for HCQ, CQ with or without Azithromycin were 10.18% (5.59–17.82%, I2 – 92%), 10.22% (6.01–16.85%, I2 – 79%), and 0.72% (0.34–1.51, I2 – 0%) respectively. The prevalence of outcome 2 in subgroup analysis for HCQ and HCQ + Azithromycin was 7.25% (3.22–15.52, I2 – 59%) and 8.61% (4.52–15.79, I2 – 76%), respectively. The risk ratio (RR) for outcome 1 and outcome 2 between HCQ + Azithromycin and HCQ was 1.22 (0.77–1.93, I2 – 0%) & 1.51 (0.79–2.87, I2 – 13%), respectively and was not significant. Heterogeneity was noted statistically as well clinically (regimen types, patient numbers, study design, and outcome definition).
The use of HCQ/CQ is associated with a high prevalence of QTc prolongation. However, it is not associated with a high risk of TdP.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Bubble column reactors (BCRs) find extensive application in the chemical industry for facilitating three-phase reactions where most often solid-phase catalysts are employed alongside gaseous and ...liquid reactants. In these reactors, accurately identifying the prevailing hydrodynamic behavior is crucial for both design optimization and successful scale-up efforts. This research investigates the flow characteristics of solid–liquid–gas mixtures in cylindrical bubble columns through a comprehensive approach combining computational fluid dynamics (CFD) simulations and a CFD-based machine learning (ML) model. The three-phase Eulerian–Eulerian CFD simulations explored the effects of 5% and 20% solid loading with varying superficial gas velocities (0.1 and 0.2 m/s) on solid distribution. The obtained results align qualitatively with the experimental findings from the literature. A CFD–deep neural network (DNN) model is presented in a parallel study of a three-phase bubble column situation. By using a large data set obtained from CFD simulations, the deep neural network model is trained to accurately predict fluid dynamics closely resembling the CFD simulations. The ML architecture incorporates input data obtained from CFD results, thereby allowing the deep neural network to acquire knowledge and identify patterns in different fluid flow characteristics, such as velocity, pressure, and holdup. The tuning of hyperparameters is crucial for successful ML predictions (with R2 values 0.97 to 0.99) in the current CFD-DNN model. Additionally, a graphical user interface (GUI) on the basis of CFD-DNN has been developed for easy model handling. The CFD-DNN model showcases its capacity to forecast hydrodynamic parameters that were not used in the training process, hence diminishing computing expenses and simulation duration in comparison with conventional CFD techniques.
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IJS, KILJ, NUK, PNG, UL, UM
Background
Bakanae or foot rot disease caused by
Fusarium fujikuroi
teleomorph:
Gibberella fujikuroi
(Sawada) Ito is emerging as a serious disease in rice. The disease causes both quantitative and ...qualitative losses to the grains under the field conditions. Breeding for resistance to Bakanae disease is a promising strategy to manage this emerging disease. In this study, we used a population of 168 F
14
recombinant inbred lines (RILs) derived from two
indica
rice parents Pusa 1342, a highly resistant variety and Pusa Basmati 1121, a highly susceptible variety to map quantitative trait loci (QTLs) governing resistance against Bakanae disease.
Results
The disease reaction of 168 F
14
RILs were measured on the seedlings inoculated using
Fusarium fujikuroi
culture using high-throughput screening protocol under glasshouse conditions. Utilizing inclusive composite interval mapping, three QTLs governing resistance to Bakanae were identified, namely
qBK1.1
,
qBK1.2
and
qBK1.3
which accounted 4.76, 24.74 and 6.49 % of phenotypic variation, respectively. The major effect QTL designated
qBK1.2
was mapped in 0.26 Mb region between RM5336 and RM10153. A total of 55 annotated genes were identified within the identified QTL region
qBK1.2
.
Conclusions
The novel QTLs identified in this study are useful resource for efficiently breeding rice cultivars resistant to Bakanae disease. This is the first report on identification of QTLs governing resistance against Bakanae in rice using inclusive composite interval mapping strategy in a RIL population.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
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