Altitudinal Variations of Ground Species in the Southern Aravalli regions of Rajasthan, India

Ground layer species sustain a variety of plants and animals; and maintain a healthy and resilient forest ecosystem by contributing to ecological functioning, structural support, and biodiversity. The western Indian Aravalli range is noted for its vegetation. Studies from these regions indicate that various environmental factors influence plant diversity and its distributions. The present study examines the impacts of altitude on ground species in Rajasthan's southern Aravalli hill ranges. We conducted field investigations year-round in Phulwari Ki Nal Wildlife Sanctuary, Kumbhalgarh Wildlife Sanctuary, and Sitamata Wildlife Sanctuary at different altitudes. A random transect method was used; five 1m2 plots were laid at every 250m interval. Species’ names and numbers were recorded from sampling plots. Sanctuary-wise species richness, density, and diversity were analyzed and related with altitude. The protected areas of Southern Aravalli do not follow an altitude-specific pattern in ground species distribution. Specific lower altitude ranges had the most species richness, density, and diversity. While altitude showed both positive and negative correlations with respect to ground species richness, diversity and density. The study findings help in conserving and preserving ground layer species in the Aravalli regions of Rajasthan

Tree species distributions in the Aravalli and Vindhya-Malwa regions of Gujarat and Rajasthan, India

The Aravalli and Vindhya-Malwa hills regions are known for their plant di versity. The plant species in these regions are affected by human threats and natural calamities. To understand the impacts on trees and their distri bution along these regions, the present study was conducted. Five protect ed areas were selected in the southern, central Aravalli, and Vindhya-Malwa regions of Gujarat and Rajasthan. The tree species were sampled during their seedling, sapling and mature tree stages. The nested plots method was used. Tree species in different growth stages were analysed, and distri bution specific to regions and across the landscapes were compared. Spe cific to regions, species richness was high in southern Aravalli compared to central Aravalli and Vindhya-Malwa regions. Across landscapes, the regions of southern Aravalli are significantly related to central Aravalli regions; the relationship between Aravalli and Vindhya-Malwa regions is not significant. Tree species distributions and establishment in these regions are affected by long-term threats like forest fire, selective removal of tree species, and cutting and lopping at the time of flowering and fruiting, which create varia tions in tree species at the regional and landscape level. Recommendations were given to preserve the tree species

Molecular characterization and assessment of genetic diversity of sorghum inbred lines

Selecting parents of diverse genetic base with contrasting phenotype is an important step in developing mapping populations for quantitative trait loci (QTL) detection and marker-assisted selection. We studied genetic diversity in 31 sorghum parents using 413 sorghum simple sequence repeats (SSR) markers. The polymorphism information content (PIC), a measure of gene diversity, varied from 0 to 0.92 with an average of 0.53 and was significantly correlated with number of alleles. The primers IS10215, IS10270 and IS10333 could differentiate all the 31 lines conclusively. Clustering analysis based on the genetic dissimilarity grouped the 31 parents into eight clusters and grouping was in good agreement with pedigree, race and geographic origin. Diverse pairs of sorghum parents were identified with contrast phenotype for various biotic and abiotic stresses with higher genetic diversity for developing recombinant inbred line (RIL) mapping populations to identify QTLs/genes for important traits in sorghum. One of the mapping populations resulted in the identification of QTLs for resistance to sorghum shoot fly and these QTL results were validated in a second mapping population.Key words: Simple sequence repeats (SSR) markers, genetic diversity, sorghum, mapping parents

Assessing the genetic diversity of Indian Kharif sorghum landraces through agro-morphological characterization (Sorghum bicolor L. Moench)

The agro-morphological characterization of local germplasm provides insight into existing diversity, enables the identification of desirable traits, and enhances crop improvement. The present study evaluated 96 kharif sorghum (Sorghum bicolor L. Moench) landraces and 6 checks using 20 agro-morphological traits at two locations, ICAR-IIMR in Hyderabad and Experimental Farm at Annamalai University in Annamalai Nagar, using alpha lattice design with 2 replications during 2021 kharif to assess genetic diversity. Results showed significant genetic variability among the 20 traits (P<0.01), providing opportunities for improvement. The high genotypic (GCV) and phenotypic components of variance (PCV) exhibited among the traits indicated their genetic determination and potential for improvement through breeding programs. High heritability and genetic advance also indicated the presence of additive genes, offering reliable improvement through trait selection. The correlation analysis showed a strong positive relationship between grain yield and several desirable traits, including panicle length, width, primary branch length, hundred seed weight, number of leaves, and total tillers per plant, indicating that grain yield can be improved by selecting accessions with desirable characteristics for these traits. The Cluster analysis using Euclidean distance revealed (four distinct clusters), with Cluster I being the most differentiated. These clusters may serve as valuable resources for hybridization programs. The PCA analysis indicated that the first three PCs accounted for 43.26% of the total variation and highlighted the key agro-morphological traits driving diversity. The results of this study demonstrated the significant genetic diversity among kharif sorghum landraces, providing a promising opportunity for varietal development programs.

Grey Relational Analysis and Anova to Determine the Optimum Process Parameters for Friction Stir Welding of Ti and Mg Alloys

The welding of Magnesium and Titanium and its alloys has continuously depicted a good challenge for designers and technologists. Ti and Mg alloys, particularly heat-treatable alloys, are difficult to join by fusion fastening techniques. The welding of dissimilar alloy such as Ti (Grade 2) and Mg (AZ91D) Alloy is an important problem during Friction Stir Welding (FSW). In this paper, the influence of Rotation speed (Rpm), Travel Speed (mm/min), Bottom Diameter Tool Pins (mm) and Tool Profiles of Ti and Mg alloy during FSW was investigated by Grey Relational Analysis and Anova was used to work out the foremost important Travel speed and feed rate affecting the Response. The primary and cooperation impact of the information factors on the normal reactions are examined. The expected values and measured values are genuinely close

Multifunctional ZnO nanorod-reduced graphene oxide hybrids nanocomposites for effective water remediation: Effective sunlight driven degradation of organic dyes and rapid heavy metal adsorption

We demonstrate the multi-functionality engineering on nanocomposite by combining one dimensional (1D) ZnO nanorod (NR) and two dimensional (2D) reduced graphene oxide (rGO) for efficient water remediation. Nano-engineered ZnO NR-rGO nanocomposites show efficient water remediation in terms of degradation of organic dyes and removal of heavy metal ions. Herein, we report on the fabrication of ZnO NR-rGO nanocomposite via a facile template-free hydrothermal route with an aim to improve the visible photocatalytic efficiency of the ZnO NR based nanocomposites. The structural and morphological features reveal that the rGO sheets are attached on the ZnO NRs and form a hybrid composite assembly. The surface enabled ZnO NR-rGO nanocomposites were used to degrade organic dye molecules (methylene blue (MB), methyl orange (MO) and rhodamine B (RhB)) under visible irradiation and adsorb Cu (II) and Co (II) ions from water through an adsorption process. The nanocomposite containing 7.5 wt% rGO and ZnO NRs shows a 4-fold enhancement in the visible photocatalytic activity and effective removal of Cu (II) and Co (II) ions from aqueous solution respectively. The photocatalytic performance is discussed in detail with respect to interaction between ZnO NRs and rGO sheets, light-harvesting properties of the nanocomposites. The effective experimental adsorption data also fit very well with the pseudo-second-order model which reveals the surface adsorption of metal ions. The results provide insight into a new method utilize for both visible photo degradation and adsorption for the removal of various wastewater pollutants. Construction of hybrid form of nanostructures delivers the effective catalytic properties with tunable functionalities for the water remediation. © 2017 Elsevier B.V

Improving Model's Interpretability and Reliability using Biomarkers

Accurate and interpretable diagnostic models are crucial in the safety-critical field of medicine. We investigate the interpretability of our proposed biomarker-based lung ultrasound diagnostic pipeline to enhance clinicians' diagnostic capabilities. The objective of this study is to assess whether explanations from a decision tree classifier, utilizing biomarkers, can improve users' ability to identify inaccurate model predictions compared to conventional saliency maps. Our findings demonstrate that decision tree explanations, based on clinically established biomarkers, can assist clinicians in detecting false positives, thus improving the reliability of diagnostic models in medicine.Comment: Accepted at BIAS 2023 Conferenc

Competing risks analysis for neutrophil to lymphocyte ratio as a predictor of diabetic retinopathy incidence in the Scottish population

Background Diabetic retinopathy (DR) is a major sight-threatening microvascular complication in individuals with diabetes. Systemic inflammation combined with oxidative stress is thought to capture most of the complexities involved in the pathology of diabetic retinopathy. A high level of neutrophil–lymphocyte ratio (NLR) is an indicator of abnormal immune system activity. Current estimates of the association of NLR with diabetes and its complications are almost entirely derived from cross-sectional studies, suggesting that the nature of the reported association may be more diagnostic than prognostic. Therefore, in the present study, we examined the utility of NLR as a biomarker to predict the incidence of DR in the Scottish population. Methods The incidence of DR was defined as the time to the first diagnosis of R1 or above grade in the Scottish retinopathy grading scheme from type 2 diabetes diagnosis. The effect of NLR and its interactions were explored using a competing risks survival model adjusting for other risk factors and accounting for deaths. The Fine and Gray subdistribution hazard model (FGR) was used to predict the effect of NLR on the incidence of DR. Results We analysed data from 23,531 individuals with complete covariate information. At 10 years, 8416 (35.8%) had developed DR and 2989 (12.7%) were lost to competing events (death) without developing DR and 12,126 individuals did not have DR. The median (interquartile range) level of NLR was 2.04 (1.5 to 2.7). The optimal NLR cut-off value to predict retinopathy incidence was 3.04. After accounting for competing risks at 10 years, the cumulative incidence of DR and deaths without DR were 50.7% and 21.9%, respectively. NLR was associated with incident DR in both Cause-specific hazard (CSH = 1.63; 95% CI: 1.28–2.07) and FGR models the subdistribution hazard (sHR = 2.24; 95% CI: 1.70–2.94). Both age and HbA1c were found to modulate the association between NLR and the risk of DR. Conclusions The current study suggests that NLR has a promising potential to predict DR incidence in the Scottish population, especially in individuals less than 65 years and in those with well-controlled glycaemic status

Competing risks analysis for neutrophil to lymphocyte ratio as a predictor of diabetic retinopathy incidence in the Scottish population

Background: Diabetic retinopathy (DR) is a major sight-threatening microvascular complication in individuals with diabetes. Systemic inflammation combined with oxidative stress is thought to capture most of the complexities involved in the pathology of diabetic retinopathy. A high level of neutrophil–lymphocyte ratio (NLR) is an indicator of abnormal immune system activity. Current estimates of the association of NLR with diabetes and its complications are almost entirely derived from cross-sectional studies, suggesting that the nature of the reported association may be more diagnostic than prognostic. Therefore, in the present study, we examined the utility of NLR as a biomarker to predict the incidence of DR in the Scottish population.Methods: The incidence of DR was defined as the time to the first diagnosis of R1 or above grade in the Scottish retinopathy grading scheme from type 2 diabetes diagnosis. The effect of NLR and its interactions were explored using a competing risks survival model adjusting for other risk factors and accounting for deaths. The Fine and Gray subdistribution hazard model (FGR) was used to predict the effect of NLR on the incidence of DR.Results: We analysed data from 23,531 individuals with complete covariate information. At 10 years, 8416 (35.8%) had developed DR and 2989 (12.7%) were lost to competing events (death) without developing DR and 12,126 individuals did not have DR. The median (interquartile range) level of NLR was 2.04 (1.5 to 2.7). The optimal NLR cut-off value to predict retinopathy incidence was 3.04. After accounting for competing risks at 10 years, the cumulative incidence of DR and deaths without DR were 50.7% and 21.9%, respectively. NLR was associated with incident DR in both Cause-specific hazard (CSH = 1.63; 95% CI: 1.28–2.07) and FGR models the subdistribution hazard (sHR = 2.24; 95% CI: 1.70–2.94). Both age and HbA 1c were found to modulate the association between NLR and the risk of DR.Conclusions: The current study suggests that NLR has a promising potential to predict DR incidence in the Scottish population, especially in individuals less than 65 years and in those with well-controlled glycaemic status.</p