Plant growth promoting rhizobacteria (PGPR) with 1-aminocyclopropane-1-carboxylic acid (ACC) deaminase activity has the potential to promote plant growth and development under adverse environmental ...conditions. In the present study, rhizobacterial strains were isolated from Garlic (
) rhizosphere and were screened
ACC deaminase activity in DF salt minimal media supplemented with 3 mM ACC. Out of six isolates, two could degrade ACC into α-ketobutyrate, exhibiting ACC deaminase activity producing more than ∼1500 nmol of α-ketobutyrate mg protein
h
, and assessed for other plant growth promoting (PGP) functions including indole acetic acid production (greater than ∼30 μg/ml), siderophore, Ammonia, Hydrogen cyanide production and inorganic Ca
(PO
)
(∼85 mg/L) and ZnSO
solubilization. Besides facilitating multifarious PGP activities, these two isolates augmented
stress tolerance in response to 6% w/v NaCl salt stress and drought stress (-0.73 Mpa). The strains ACC02 and ACC06 were identified
and
sp., respectively on the basis of 16S rDNA gene sequence analysis and were evaluated for growth promoting potential in French bean seedlings under non-saline and salinity stress conditions through pot experiments. The seed bacterization by ACC02 and ACC06 revealed that treatment of plants with bacterial isolates in the form of consortia significantly declined (∼60%) stress stimulated ethylene levels and its associated growth inhibition by virtue of their ACC deaminase activity. The consortia treatment alleviated the negative effects of salinity stress and increased root length (110%), root fresh weight (∼45%), shoot length (60%), shoot fresh weight (255%), root biomass (220%), shoot biomass (425%), and total chlorophyll content (∼57%) of French bean seedlings subjected to salinity stress.
Many individuals with disabilities face barriers to meaningful employment. Legislation has been put in place to ensure employment equity for individuals with disabilities in Canada. However, little ...is known about the employment profile and experiences of people with seeing disabilities.
The objectives of our research study were to explore the employment rates of people with seeing disabilities in Canada, the factors associated with being employed, and supports and barriers that affect their work participation.
We used the nationally representative data from the Canadian Survey on Disability (CSD) 2017, collected by Statistics Canada. The CSD is a national cross-sectional survey of Canadians 15 years of age and above who face a functional limitation due to a health-related condition, representing more than 6 million (n = 6,246,640) Canadians. Our analyses focused on people who reported having a seeing disability. A subset of the complete dataset was created, focusing on individuals with a seeing disability. Weighted descriptive analyses were performed using SPSS. Multivariate logistic regression analyses were conducted for individuals between 25-64 years of age to identify predictors of employment.
Out of the estimated 892,220 working-age adults (25-64 years) with a seeing disability who were represented by the survey, 54% were employed, 6% were unemployed and 40% were not in the labour force. Early onset of seeing disability (OR: 1.33; 95% CI: 1.32-1.35), less severe seeing disability (OR: 1.51; 95% CI: 1.49-1.53), education above high school (OR: 2.00; 95% CI: 1.97-2.02) and daily use of the internet (OR: 2.46; 95% CI: 2.41-2.51) were positively related with employment. The top three employment accommodations that were needed and were made available included: modified work hours (45%); work from home (38.5%) and a modified workstation (37%). The top three needed but least available accommodations were technical aids (14%), communication aids (22%) and a computer with specialized software or adaptation (27%). Overall, 26% reported that an accommodation was required but was not made available by the employer. While 75% of individuals with a seeing disability were out of the labour force due to their condition, the remaining identified barriers that prevented them from working which included (top 3): (i) too few jobs available (20%); (ii) inadequate training/experience (19%), (iii) past attempts at finding employment were unsuccessful (19%).
Adults with seeing disability in Canada experience lower labour force participation than the general population. Rigorous programs are required to assist them with the job search, job retraining and workplace accommodations. It is important for governments to improve efforts towards inclusive education and develop strategies that promote digital literacy of employees and job seekers with visual impairments. Although accessibility legislations have been put in place, programs should be established that provide accessibility solutions for various employers, enabling them to hire individuals with different abilities.
In this study, principal components analysis (PCA) was performed to identify air pollution sources and tree based ensemble learning models were constructed to predict the urban air quality of Lucknow ...(India) using the air quality and meteorological databases pertaining to a period of five years. PCA identified vehicular emissions and fuel combustion as major air pollution sources. The air quality indices revealed the air quality unhealthy during the summer and winter. Ensemble models were constructed to discriminate between the seasonal air qualities, factors responsible for discrimination, and to predict the air quality indices. Accordingly, single decision tree (SDT), decision tree forest (DTF), and decision treeboost (DTB) were constructed and their generalization and predictive performance was evaluated in terms of several statistical parameters and compared with conventional machine learning benchmark, support vector machines (SVM). The DT and SVM models discriminated the seasonal air quality rendering misclassification rate (MR) of 8.32% (SDT); 4.12% (DTF); 5.62% (DTB), and 6.18% (SVM), respectively in complete data. The AQI and CAQI regression models yielded a correlation between measured and predicted values and root mean squared error of 0.901, 6.67 and 0.825, 9.45 (SDT); 0.951, 4.85 and 0.922, 6.56 (DTF); 0.959, 4.38 and 0.929, 6.30 (DTB); 0.890, 7.00 and 0.836, 9.16 (SVR) in complete data. The DTF and DTB models outperformed the SVM both in classification and regression which could be attributed to the incorporation of the bagging and boosting algorithms in these models. The proposed ensemble models successfully predicted the urban ambient air quality and can be used as effective tools for its management.
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•Developed tree ensemble models for seasonal discrimination and air quality prediction.•PCA used to identify air pollution sources; air quality indices used for health risk.•Bagging and boosting algorithms enhanced predictive ability of ensemble models.•Ensemble classification and regression models performed better than SVMs.•Proposed models can be used as tools for air quality prediction and management.
Abstract
Targeted drug delivery is one such precision method of delivering medication inside the human body which can vanquish all the limitations of the conventional chemotherapeutic techniques. In ...the present study, two types of nanoparticles (NPs) were chosen for the in-vitro pH-responsive release study of the drug, Imatinib, namely anatase Titanium Dioxide nanoparticles (TiO
2
NPs) and iron-capped TiO
2
NPs, designated as Fe@TiO
2
NPs. The novelty of this work lies behind the use of commercially available iron supplement ‘Autrin’ meant for human consumption, as the material to coat the TiO
2
NPs to synthesize Fe@TiO
2
NPs. The synthesized NPs were analyzed by XRD, HR‐TEM, SAED, EDX and VSM. UV–Vis spectroscopy was performed for absorption studies. Fe@TiO
2
NPs showed superparamagnetic behavior and thus they are able to ensure the facile transfer of Imatinib via external magnetic fields. The results obtained from in-vitro drug release studies depicted that both TiO
2
NPs and Fe@TiO
2
NPs showed a controlled pH-sensitive delivery of the loaded Imatinib molecules. Moreover, both types of NPs do not result in the formation of ROS under human physiological conditions. These results can lay the foundation to the development of efficacious targeted drug delivery systems in the healthcare sector.
The present study demonstrates plant growth promotion and induction of systemic resistance in pea (
) plant against
f.sp.
by two bacterial endophytes,
OS_12 and
OS_25 isolated from leaves of
Linn. ...The endophytes were evaluated for their antagonistic potential against three phytopathogens
,
f. sp.
, and
by dual culture assay. Maximum inhibition of
f. sp.
was observed by strains OS_12 and OS_25 among all root rot pathogens. Scanning electron microscopy of dual culture indicated hyphal distortion and destruction in the case of
f. sp.
. Further, volatile organic compounds (VOCs) were identified by gas chromatography-mass spectrometry (GC-MS). The GC-MS detected eight bioactive compounds from hexane extracts for instance, Dodecanoic acid, Tetra decanoic acid, L-ascorbic acid,
-13-Octadecanoic acid, Octadecanoic acid. Both the endophytes exhibited multifarious plant growth promoting traits such as indole acetic production (30-33 μg IAA ml
), phosphate solubilization, and siderophore and ammonia production. Pot trials were conducted to assess the efficacy of endophytes in field conditions. A significant reduction in disease mortality rate and enhancement of growth parameters was observed in pea plants treated with consortium of endophytes OS_12 and OS_25 challenged with
f.sp.
infection. The endophytic strains elicited induced systemic resistance (ISR) in pathogen challenged pea plants by enhancing activities of Phenylalanine ammonia lyase (PAL), peroxidase (PO), polyphenol oxidase (PPO), ascorbate oxidase (AO), catalase (CAT) and total phenolic content. The endophytes reduced the oxidative stress as revealed by decrease in malondialdehyde (MDA) content and subsequently, lipid peroxidation in host plant leaves. Robust root colonization of pea seedlings by endophytes was observed by scanning electron microscopy (SEM) and fluorescence microscopy. Thus, plant growth promoting endophytic
and
can be further exploited through bio-formulations for sustainable protection of crops against root rot diseases as bio-control agents.
Selenium (Se) is an essential micronutrient for humans and animals, but lead to toxicity when taken in excessive amounts. Plants are the main source of dietary Se, but essentiality of Se for plants ...is still controversial. However, Se at low doses protects the plants from variety of abiotic stresses such as cold, drought, desiccation, and metal stress. In animals, Se acts as an antioxidant and helps in reproduction, immune responses, thyroid hormone metabolism. Selenium is chemically similar to sulfur, hence taken up inside the plants via sulfur transporters present inside root plasma membrane, metabolized via sulfur assimilatory pathway, and volatilized into atmosphere. Selenium induced oxidative stress, distorted protein structure and function, are the main causes of Se toxicity in plants at high doses. Plants can play vital role in overcoming Se deficiency and Se toxicity in different regions of the world, hence, detailed mechanism of Se metabolism inside the plants is necessary for designing effective Se phytoremediation and biofortification strategies.
Flying Ad hoc Networks have emerged as a promising technology for number of real-time applications. However, the flexible and unstructured characteristics of these networks make them vulnerable to ...security threats posed by malicious nodes, such as denial of service attacks, node impersonation, and information breaches. Another major issue is the consideration of those nodes being unable to prove their trustworthiness due to factors like hardware or software failure, or by link interruptions, during the processing of detection of false nodes in the network. The existing mechanisms encompassing encryption, authentication, and intrusion detection highlight limitations to secure real-time applications and services due to the high speed of flying nodes and the absence of fixed network structures. To overcome these constraints, this research paper incorporates a novel framework for evaluating and improving the security of network by introducing an innovative cluster-based approach. Moreover, it presents a fuzzy model that dynamically estimates the trust levels of both individual nodes and clusters, by assigning weight to the parameters to address vulnerabilities. Additionally, a trust reconfiguration mechanism is further proposed to address the issue of nodes unable to substantiate their trust by providing them with additional chances based on the collective trust from previous evaluations. Further, the paper incorporates a dynamic reputation system to proficiently identify and separate malicious and selfish nodes from the network. Simulation results indicate a significant improvement in performance metrics, with a considerable reduction in delay and drop ratio by 41.46% and 36.37%, respectively, while the sufficient rise of 54.71% and 46.05% in throughput and coverage, respectively, comparing with the considered state-of-art.
A comprehensive safety evaluation of chemicals should require toxicity assessment in both the aquatic and terrestrial test species. Due to the application practices and nature of chemical pesticides, ...the avian toxicity testing is considered as an essential requirement in the risk assessment process. In this study, tree-based multispecies QSAR (quantitative-structure activity relationship) models were constructed for predicting the avian toxicity of pesticides using a set of nine descriptors derived directly from the chemical structures and following the OECD guidelines. Accordingly, the Bobwhite quail toxicity data was used to construct the QSAR models (SDT, DTF, DTB) and were externally validated using the toxicity data in four other test species (Mallard duck, Ring-necked pheasant, Japanese quail, House sparrow). Prior to the model development, the diversity in the chemical structures and end-point were verified. The external predictive power of the QSAR models was tested through rigorous validation deriving a wide series of statistical checks. Intercorrelation analysis and PCA methods provided information on the association of the molecular descriptors related to MW and topology. The S36 and MW were the most influential descriptors identified by DTF and DTB models. The DTF and DTB performed better than the SDT model and yielded a correlation (R 2) of 0.945 and 0.966 between the measured and predicted toxicity values in test data array. Both these models also performed well in four other test species (R 2 > 0.918). ChemoTyper was used to identify the substructure alerts responsible for the avian toxicity. The results suggest for the appropriateness of the developed QSAR models to reliably predict the toxicity of pesticides in multiple avian test species and can be useful tools in screening the new chemical pesticides for regulatory purposes.
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