Search Results (12)

This paper addresses the challenges of solving the quantum many-body problem, particularly within nuclear physics, through the configuration interaction (CI) method. Large-scale shell model calculations often become computationally infeasible for systems with a large number of valence particles, requiring truncation techniques. We propose truncation methods for the nuclear shell model, in which angular momentum is conserved and rotational symmetry is restored. We introduce the monopole-interaction-based truncation and seniority truncation strategies, designed to reduce the dimension of the calculations. These truncations can be established by considering certain partitions based on their importance and selecting physically meaningful states. We examine these truncations for Sn, Xe, and Pb isotopes, demonstrating their effectiveness in overcoming computational limits. These truncations work well for systems with either a single type of valence nucleon or with both types. With these truncations, we are able to achieve good convergence for the energy at a very small portion of the total dimension. Full article

Background: This study aims to assess systemic risk factors in diabetes mellitus (DM) patients and predict diabetic retinopathy (DR) using a Random Forest (RF) classification model. Methods: We included DM patients presenting to the retina clinic for first-time DR screening. Data on age, gender, diabetes type, treatment history, DM control status, family history, pregnancy history, and systemic comorbidities were collected. DR and sight-threatening DR (STDR) were diagnosed via a dilated fundus examination. The dataset was split 80:20 into training and testing sets. The RF model was trained to detect DR and STDR separately, and its performance was evaluated using misclassification rates, sensitivity, and specificity. Results: Data from 1416 DM patients were analyzed. The RF model was trained on 1132 (80%) patients. The misclassification rates were 0% for DR and ~20% for STDR in the training set. External testing on 284 (20%) patients showed 100% accuracy, sensitivity, and specificity for DR detection. For STDR, the model achieved 76% (95% CI-70.7%–80.7%) accuracy, 53% (95% CI-39.2%–66.6%) sensitivity, and 80% (95% CI-74.6%–84.7%) specificity. Conclusions: The RF model effectively predicts DR in DM patients using systemic risk factors, potentially reducing unnecessary referrals for DR screening. However, further validation with diverse datasets is necessary to establish its reliability for clinical use. Full article

The air quality of the Himalayan region of India is deteriorating due to the increasing load of particulate matter that is emitted from various local and regional sources, as well as to the transit of dust-related pollutants from the Indo-Gangetic Plain (IGP) and surrounding areas. In this study, the mineralogical characteristics of coarse mode particulate matter (PM₁₀) was analyzed using the X-ray diffraction (XRD) technique from January to December 2019 over Nainital (29.39° N, 79.45° E; altitude: 1958 m above mean sea level), a central Himalayan region of India. XRD analysis of PM₁₀ samples showed the presence of clay minerals, crystalline silicate minerals, carbonate minerals, and asbestiform minerals. It was shown that quartz minerals with significant levels of crystallinity were present in all the samples. Other minerals that are contributing to the soil dust were also observed in the analysis (CaFe₂O₄, CaCO₃, CaMg(CO₃)₂, calcium ammonium silicate hydrate (C-A-S-H), gypsum, kaolinite, illite, augite, and montmorillonite). The minerals ammonium sulphate, hematite, and magnetite were also found in the samples and are suggested to be from biogenic and anthropogenic activities, including biomass burning, fuel combustion, vehicle exhaust, construction activities, etc. This study indicated that the majority of the minerals in PM₁₀ that were present in this Himalayan region are from soil/crustal dust. Full article

This study presents the source apportionment of coarse-mode particulate matter (PM₁₀) extracted by 3 receptor models (PCA/APCS, UNMIX, and PMF) at semi-urban sites of the Indian Himalayan region (IHR) during August 2018–December 2019. In this study, water-soluble inorganic ionic species (WSIIS), water-soluble organic carbon (WSOC), carbon fractions (organic carbon (OC) and elemental carbon (EC)), and trace elements of PM₁₀ were analyzed over the IHR. Nainital (62 ± 39 µg m⁻³) had the highest annual average mass concentration of PM₁₀ (average ± standard deviation at 1 σ), followed by Mohal Kullu (58 ± 32 µg m⁻³) and Darjeeling (54 ± 18 µg m⁻³). The annual total ∑WSIIS concentration order was as follows: Darjeeling (14.02 ± 10.01 µg m⁻³) > Mohal-Kullu (13.75 ± 10.21 µg m⁻³) > Nainital (10.20 ± 6.30 µg m⁻³), contributing to 15–30% of the PM₁₀ mass. The dominant secondary ions (NH₄⁺, SO₄²⁻, and NO₃⁻) suggest that the study sites were strongly influenced by anthropogenic sources from regional and long-range transport. Principal component analysis (PCA) with an absolute principal component score (APCS), UNMIX, and Positive Matrix Factorization (PMF) were used for source identification of PM₁₀ at the study sites of the IHR. All three models showed relatively similar results of source profiles for all study sites except their source number and percentage contribution. Overall, soil dust (SD), secondary aerosols (SAs), combustion (biomass burning (BB) + fossil fuel combustion (FFC): BB+FFC), and vehicular emissions (VEs) are the major sources of PM₁₀ identified by these models at all study sites. Air mass backward trajectories illustrated that PM₁₀, mainly attributed to dust-related aerosols, was transported from the Thar Desert, Indo-Gangetic Plain (IGP), and northwestern region of India (i.e., Punjab and Haryana) and Afghanistan to the IHR. Transported agricultural or residual burning plumes from the IGP and nearby areas significantly contribute to the concentration of carbonaceous aerosols (CAs) at study sites. Full article

The monkeypox disease is a zoonotic-infectious disease that transmits between animals and humans. It is caused by a double-stranded DNA virus belonging to the Orthopoxvirus genus that is closely related to the variola virus –the causative agent of smallpox. Although monkeypox infections were endemic to Western and Central Africa, the newly emerging monkeypox outbreak spread to more than 90 non-African countries. With the exception of the PCR-confirmed case of a return from Nigeria to the United Kingdom, the ongoing outbreak is largely unrelated to travel. In the most recent wave, cases are characteristically males in their thirties. Risk factors include close and particularly sexual contact with an infected person, and contact with fomites, infected animals or aerosolized-infectious material. Clinical diagnosis of monkeypox is confirmed with nucleic-acid amplification testing of samples originating from vesicles or genital lesions and using real-time or conventional PCR. Other methods, such as electron microscopy, immunohistochemistry, and virus culture are costly and time-consuming. In addition to timely diagnosis and contact tracing, restrictive measures to limit spread, such as isolation of infected patients, preventing contact with wild animals, and isolation of animals suspected to be viral reservoirs have shown promise. Although there are no specific treatments for monkeypox disease, the experience with smallpox suggests that the vaccinia vaccine, cidofovir, tecovirimat, and vaccinia immune globulin (IVG) may be beneficial for monkeypox treatment. In this review, we provide an update on the human-monkeypox disease with a special emphasis on its pathogenesis, prevention, diagnostics, and therapeutic measures. Full article

Diabetes is a major health challenge, and it is linked to a number of serious health issues, including cardiovascular disease (heart attack and stroke), diabetic nephropathy (kidney damage or failure), and birth defects. The detection of glucose has a direct and significant clinical importance in the management of diabetes. Herein, we demonstrate the application of in-situ synthesized Ti₂C-TiO₂ MXene nanocomposite for high throughput non-enzymatic electrochemical sensing of glucose. The nanocomposite was synthesized by controlled oxidation of Ti₂C-MXene nanosheets using H₂O₂ at room temperature_. The oxidation results in the opening up of Ti₂C-MXene nanosheets and the formation of TiO₂ nanocrystals on their surfaces as revealed in microscopic and spectroscopic analysis. Nanocomposite exhibited considerably high electrochemical response than parent Ti₂C MXene, and hence utilized as a novel electrode material for enzyme-free sensitive and specific detection of glucose. Developed nanocomposite-based non-enzymatic glucose sensor (NEGS) displays a wide linearity range (0.1 µM-200 µM, R² = 0.992), high sensitivity of 75.32 μA mM⁻¹ cm⁻², a low limit of detection (0.12 μM) and a rapid response time (~3s). NEGS has further shown a high level of repeatability and selectivity for glucose in serum spiked samples. The unveiled excellent sensing performance of NEGS is credited to synergistically improved electrochemical response of Ti₂C MXene and TiO₂ nanoparticles. All of these attributes highlight the potential of MXene nanocomposite as a next-generation NEGS for on the spot mass screening of diabetic patients. Full article

Carbonaceous aerosols play a significant role in the Earth’s atmospheric system by affecting visibility, the hydrological cycle, the climate, radiative forcing, and human health. The present study analyses PM₁₀ samples that were collected at three distinct urban locations (Mohal-Kullu, Nainital, and Darjeeling) over the Himalayan region of India during winter 2019. The mass concentrations of PM₁₀ were recorded as 51 ± 16 μg m⁻³, 38 ± 9 μg m⁻³, and 52 ± 18 μg m⁻³ for Mohal-Kullu, Nainital, and Darjeeling, respectively. Organic carbon (OC) dominated over elemental carbon (EC) and was found to be 50.2%, 42.8%, and 47% of total carbon (TC) at Mohal-Kullu, Nainital, and Darjeeling, respectively. The respective mass concentrations of carbonaceous species [OC, EC, water-soluble organic carbon (WSOC), and total carbonaceous aerosol (TCA)] were higher at Mohal-Kullu (OC: 11.1 ± 5.3, EC: 4.2 ± 1.9, WSOC: 5.3 ± 1.3 μg m⁻³, and TCA: 22.1 ± 10.4 μg m⁻³) followed by Darjeeling (OC: 5.4 ± 2.0, EC: 2.7 ± 1.0, WSOC: 3.9 ± 1.3 μg m⁻³, and TCA: 22.1 ± 10.4 μg m⁻³) and Nainital (OC: 2.9 ± 1.0, EC: 1.3 ± 0.6, WSOC: 2.1 ± 0.6 μg m⁻³, and TCA: 6.7 ± 2.4 μg m⁻³). The OC/EC and WSOC/OC ratio at Mohal-Kullu (2.6 ± 0.3, 0.6 ± 0.2), Nainital (2.0 ± 0.4, 0.7 ± 0.2), and Darjeeling (2.3 ± 0.5, 0.7 ± 0.2), respectively, indicates the dominance of fossil fuel combustion (coal and vehicular exhaust), with signified additional contribution from secondary organic carbon (SOC). Full article

The mega wheat variety HD2967 was improved for leaf and stripe rust resistance by marker-assisted backcross breeding. After its release in 2011, HD2967 became susceptible to stripe rust and moderately susceptible to leaf rust. The leaf rust resistance gene LrTrk was transferred into HD2967 from the durum wheat genotype Trinakria. Then, HD2967 was crossed with Trinakria to produce F₁ plant foreground selection for LrTrk and background selection for the recurrent parent genotype was carried out in BC₁F₁, BC₂F₁ and BC₂F₂ generations. Foreground selection was carried out with the linked marker Xgwm234, while polymorphic SSR markers between parents were used for background selection. Background selection resulted in the rapid recovery of the recurrent parent genome. A morphological evaluation of 6 near isogenic lines (NILs)—2 resistant to leaf and stripe rust, and 4 resistant to leaf rust only—showed no significant differences in yields among NILs and the recurrent parent HD2967. All of the 6 NILs showed the presence of 2NS/2AS translocation, carrying the linked genes Lr37/Sr38/Yr17 present in HD2967 and the targeted leaf rust resistance gene LrTrk. Two NILs also showed additional resistance to stripe rust. Therefore, these NILs with rust resistance and an at par yielding ability of H2967 can replace the susceptible cultivar HD2967 to reduce yield losses due to disease. Full article

Earthworms (EWs) could be a viable indicator of soil biology and agri-food system management. The influence of climate-smart agriculture (CSA)-based sustainable intensification practices (zero tillage, crop rotations, crop residue retention, and precision water and nutrients application) on earthworms’ (EWs) populations and soil physico-biochemical properties of rice-wheat cropping system in the Indo-Gangetic plains of South Asia was investigated. This study investigates the effect of 10-years adoption of various CSA practices on the abundance of earthworms and physical and biochemical properties of the soil and EWs’ casts (EWC). Five scenarios (Sc) were included: conventionally managed rice-wheat system (farmers’ practices, Sc1), CSA-based rice-wheat-mungbean system with flood irrigation (FI) (Sc2) and subsurface drip irrigation (SDI) (Sc3), CSA-based maize-wheat-mungbean system with FI (Sc4), and SDI (Sc5). Results revealed that EWs were absent under Sc1, while the 10-year adoption of CSA-based scenarios (mean of Sc2–5) increased EWs’ density and biomass to be 257.7 no. m⁻² and 36.05 g m⁻², respectively. CSA-based maize scenarios (Sc4 and Sc5) attained higher EWs’ density and biomass over rice-based CSA scenarios (Sc2 and Sc4). Also, SDI-based scenarios (Sc3 and Sc5) recorded higher EWs’ density and biomass over FI (Sc2 and Sc4). Maize-based CSA with SDI recorded the highest EWs’ density and EWs’ biomass. The higher total organic carbon in EWC (1.91%) than in the bulk soil of CSA-based scenarios (0.98%) and farmers’ practices (0.65%) suggests the shift of crop residue to a stable SOC (in EWC). EWC contained significant amounts of C and available NPK under CSA practices, which were nil under Sc1. All CSA-based scenarios attained higher enzymes activities over Sc1. CSA-based scenarios, in particular, maize-based scenarios using SDI, improved EWs’ proliferation, SOC, and nutrients storage (in soil and EWC) and showed a better choice for the IGP farmers with respect to C sequestration, soil quality, and nutrient availability. Full article

This study tested whether machine learning (ML) methods can effectively separate individual plants from complex 3D canopy laser scans as a prerequisite to analyzing particular plant features. For this, we scanned mung bean and chickpea crops with PlantEye (R) laser scanners. Firstly, we segmented the crop canopies from the background in 3D space using the Region Growing Segmentation algorithm. Then, Convolutional Neural Network (CNN) based ML algorithms were fine-tuned for plant counting. Application of the CNN-based (Convolutional Neural Network) processing architecture was possible only after we reduced the dimensionality of the data to 2D. This allowed for the identification of individual plants and their counting with an accuracy of 93.18% and 92.87% for mung bean and chickpea plants, respectively. These steps were connected to the phenotyping pipeline, which can now replace manual counting operations that are inefficient, costly, and error-prone. The use of CNN in this study was innovatively solved with dimensionality reduction, addition of height information as color, and consequent application of a 2D CNN-based approach. We found there to be a wide gap in the use of ML on 3D information. This gap will have to be addressed, especially for more complex plant feature extractions, which we intend to implement through further research. Full article

Heavy metal is released from many industries into water. Before the industrial wastewater is discharged, the contamination level should be reduced to meet the recommended level as prescribed by the local laws of a country. They may be poisonous or cancerous in origin. Their presence does not only damage people, but also animals and vegetation because of their mobility, toxicity, and non-biodegradability into aquatic ecosystems. The review comprehensively discusses the progress made by various adsorbents such as natural materials, synthetic, agricultural, biopolymers, and commercial for extraction of the metal ions such as Ni²⁺, Cu²⁺, Pb²⁺, Cd²⁺, As²⁺ and Zn²⁺ along with their adsorption mechanisms. The adsorption isotherm indicates the relation between the amount adsorbed by the adsorbent and the concentration. The Freundlich isotherm explains the effective physical adsorption of the solute particle from the solution on the adsorbent and Langmuir isotherm gives an idea about the effect of various factors on the adsorption process. The adsorption kinetics data provide valuable insights into the reaction pathways, the mechanism of the sorption reaction, and solute uptake. The pseudo-first-order and pseudo-second-order models were applied to describe the sorption kinetics. The presented information can be used for the development of bio-based water treatment strategies. Full article

This study is set on the background of a randomized control trial (RCT) in which intervention was carried to observe the effects of yoga/light exercise on the improvement in health and well-being among the elderly population. A longitudinal qualitative study was conducted as part of RCT interventions to explore the experience of the elderly practicing yoga/light exercise in relation to sedentary behavior in the Ujjain district of Madhya Pradesh, India. Participants of the RCT were selected for this study. Eighteen focus group discussions were conducted—six during each phase of RCT interventions (before, during, and after). The findings regarding motivating and demotivating factors in various phases of intervention were presented in three categories: experience and perception of the effects of yoga/light exercise on sedentary behavior (1) before, (2) during, and (3) after intervention. This study explores the positive effect of yoga/light exercise on sedentary behavior and subjective well-being on the elderly population. They were recognized to have undergone changes in their physical and emotional well-being by consistently practicing yoga/light exercise. The main driving factors were periodic health check-ups and the encouragement of qualified trainers without any cost. This study concludes with the notion that these interventions should be encouraged in the community to use physical exercise as a method to better control the physical and social effects of aging. Full article