V5579 Sgr was a fast nova discovered in 2008 April 18.784 UT. We present the optical spectroscopic observations of the nova observed from the Castanet Tolosan, SMARTS, and CTIO observatories spanning over 2008 April 23 to 2015 May 11. The spectra are dominated by hydrogen Balmer, Fe II, and O I lines with P-Cygni profiles in the early phase, typical of an Fe II class nova. The spectra show He I and He II lines along with forbidden lines from N, Ar, S, and O in the nebular phase. The nova showed a pronounced dust formation episode that began about 20 days after the outburst. The dust temperature and mass were estimated using the WISE data from spectral energy distribution (SED) fits. The PAH-like features are also seen in the nova ejecta in the mid-infrared Gemini spectra taken 522 d after the discovery. Analysis of the light curve indicates values of $t_2$ and $t_3$ about 9 and 13 days, respectively, placing the nova in the category of fast nova. The best-fit cloudy model of the early decline phase JHK spectra obtained on 2008 May 3 and the nebular optical spectrum obtained on 2011 June 2 shows a hot white dwarf source with $T_{BB}$ $\sim$ 2.6 $\times$ 10$^5$ K having a luminosity of 9.8 $\times$ 10$^{36}$ ergs s$^{-1}$. Our abundance analysis shows that the ejecta is significantly enhanced relative to solar, O/H = 32.2, C/H = 15.5, and N/H = 40.0 in the early decline phase and O/H = 5.8, He/H = 1.5, and N/H = 22.0 in the nebular phase.

Background: Near-infrared spectroscopy regional cerebral oxygen saturation (rSO2) has gained interest as a raw parameter and as a basis for measuring cerebrovascular reactivity (CVR). This study aimed to identify threshold values of rSO2 and rSO2 based CVR at which outcomes worsened following traumatic brain injury (TBI). Methods: A retrospective multi-institutional cohort study was performed. The cerebral oxygen indices, COx (using rSO2 and cerebral perfusion pressure) as well as COx_a (using rSO2 and arterial blood pressure) were calculated for each patient. 2x2 tables were created grouping patients by alive/dead and favorable/unfavorable outcomes at various thresholds of COx and COx_a as well as rSO2 itself. Chi-square values were calculated to identify the most discriminative significant threshold. Results: In the cohort of 129 patients rSO2 did not have any statistically significant threshold value. For COx and COx_a, an optimal threshold value of 0.2 was identified for both survival and favorable outcomes with values above this associated with worse outcomes. Conclusions: In this study, raw rSO2was found to contain no significant prognostic information. However, rSO2 based indices of CVR, were found to have a uniform threshold of 0.2, above which clinical outcomes worsened. This study lays the groundwork to transition to less invasive means of continuously measuring CVR.

The paper addresses a critical challenge in System-of-Systems (SoS) simulations arising from the different granularity levels in SoS simulations, integrating non-coupled Discrete Element Method results into SoS-level Discrete Event Simulations using surrogate modeling. Illustrated with a wheel loader bucket use-case in mining, it enhances early design decision-making and lays the groundwork for improving SoS simulations in construction equipment design. This paves the way for broader research and application across diverse engineering design domains.

The rapid development of new technologies such as electrification, autonomy, and other contextual factors pose significant challenges to development teams in balancing competing aspects while developing value-robust solutions. One approach for achieving value robustness is designing for changeability. This paper presents a tradespace exploration from a Systems-of-Systems perspective to facilitate changeability assessment during early design stages. The approach is further demonstrated on a fleet of haulers operating in a mining site.

Innovation plays a vital role in ensuring sustainable mining operations. Electrification and autonomy are two significant trends, but their implementation brings complexity at vehicle and site levels. Therefore, it is crucial to understand how these technologies impact the overall site value creation. This paper suggests a hybrid approach that combines Agent-Based Simulation and vehicle dynamics modeling to explore site configurations. By regarding a mining site as a System-of-Systems, designers can concurrently test different designs to find the optimal combination for a specific scenario.

Normally, the reported gain of the microstrip patch antenna is within 8 dBi. Using properly located three shorting pins on three bisectors, the present work reports a method to convert the non-radiating TM11 mode of equilateral triangular patch antennas (ETPAs) to a deformed TM11 radiating mode. The boresight gain of ETPA operating in TM11 mode is enhanced from −10.75 to 12.1 dBi at 5.43 GHz. The boresight measured gain is further enhanced to 14.2 dBi at 5.52 GHz by using a triangular surface-mounted short horn (SMSH) of about ${{\lambda }}/5$ height. The aperture efficiency of the ETPA with the shorting pins is 84.2%. The aperture efficiency is further improved to 94.2% using the SMSH. The measured boresight cross-polarization and side-lobe level are −40 and −29 dB, respectively. The nature of the electricfield and surface current distribution is analyzed, using both the characteristic mode analysis method and high-frequency structure simulator, to understand the role of shorting pin and coaxial feed in converting the non-radiating TM11 mode to the radiating mode. A systematic design process also is presented for a fast design of shorting pin-loaded ETPA on the suitable substrate at a specified frequency.

Post 2004 tsunami and earthquake, the landmass of Andaman and Nicobar Islands (ANI's) experienced uplift (North Andaman and Mayabunder) and subsidence (South Andaman & Nicobar Islands). The altered geomorphology modified the tidal regime, which resulted in mangrove degradation in their current locations and the formation of new intertidal zones potential for mangrove colonization. Avicennia species; a pioneer in mangrove succession was expected to colonize such new intertidal zones. Therefore, to understand the colonization pattern of Avicennia species in these new intertidal zones and their distribution in the old forests, we surveyed 79 sites across ANI's (55 Andaman and 24 Nicobar Islands). Our survey confirms the presence of three Avicennia species namely A. marina, A. officinalis, and A. alba – a new distribution record to the ANI's. Further, A. marina was found to be the most widely distributed, and abundant among three Avicennia species (Relative Abundance (RA) – 97.92%; Relative Frequency (RF) – 68.75%). In contrast, A. officinalis (RA – 1.93%; RF – 26.25%) and A. alba (RA – 0.16%; RF – 5%) were found limited in their distribution and abundance. As per the IUCN Red List, the Avicennia population is decreasing globally, whereas, its population may increase significantly across ANI's due to the availability of vast new intertidal zones. Hence, Avicennia spp. can be utilized in the plantation programs to facilitate rapid colonization in the unvegetated potential mangrove habitats across ANI's. Such an effort will improve the mangrove ecosystem services that were hampered due to mangrove degradation by the 2004 tsunami.

OBJECTIVES/GOALS: The goal of the study is to provide insights into the use of machine learning methods as a means to predict heterogeneity of treatment effect (HTE) in participants of randomized clinical trials. METHODS/STUDY POPULATION: Using data from 2,441 participants enrolled in the ASPirin in Reducing Events in the Elderly (ASPREE) randomized controlled trial of daily low-dose aspirin vs placebo in the United States, we developed multivariable risk prediction models for the composite outcome of dementia, disability, or death. We used two machine learning techniques, decision trees and random forests, to develop novel non-parametric outcomes classifiers and generate risk-based subgroups. The comparator method was an extant semi-parametric proportional hazards predictive risk model. We then assessed HTE by examining the 5-year absolute risk reduction (ARR) of aspirin vs placebo in each risk subgroup. RESULTS/ANTICIPATED RESULTS: In the random forest classifier, the ARR at 5 years in the highest risk quintile was 13.7% (95% CI 3.1% to 24.4%). For the semi-parametric proportional hazards model, the ARR in the highest risk quintile was 15.1% (95% CI 4.0% to 26.3%). These results were comparable and provide evidence of the viability of internally developed parsimonious non-parametric machine learning models for HTE analysis. The decision tree model results (5-year ARR = 17.0%, 95% CI= -5.4% to 39.4% in the highest risk subgroup) exhibited more uncertainty in the results. DISCUSSION/SIGNIFICANCE: None of the models detected significant HTE on the relative scale; there was substantial HTE on the absolute scale in three of the models. Treatment benefit on the absolute scale may be regarded as bearing greater clinical importance and may be present even in the absence of benefit on the relative scale.

Bhakti is a remarkable existential tendency that shows itself in the rich expanse of the tradition originating from the Vedas. Recognized as a prize possession of the religions, philosophies, and culture of India, it has often won fascination and admiration from students of Eastern heritage. However, its nature, role, and history remain misunderstood and have not received all the attention they deserve. Its role as a gatherer of life, love, thought, and the divine is missed in its partial characterizations as “Hindu devotion” or “divine love” or “theism implicit in polytheism.” Its status as a perennial thematic concept of the Indian civilization is missed when its pervasiveness is overlooked by the cultural historians preoccupied primarily with its periodic eruptions. Furthermore, the philosophical role of bhakti is missed when it is deemed as an alternative to jnana (knowledge) rather than “the living of jnana.”

Precision healthcare is an emerging field of science that utilizes an individual’s health information, context, and genetics to provide more personalized diagnostics and treatments. In this manuscript, we leverage that concept and present a group of machine learning models for precision gaming. These predictive models guide adolescents through best practices related to their health. The use case deployed is for girls in India through a mobile application released in three different Indian states. To evaluate the usability of the models, experiments are designed and data (demographic, behavioral, and health-related) are collected. The experimental results are presented and discussed.

The ongoing servitization journey of the manufacturing industries instills a through-life perspective of value, where a combination of products and services is delivered to meet expectations. Often described as a product-service system (PSS), these systems are poised with many complexity aspects, introducing uncertainties during the design phase. Incorporating changeability is one of the known strategies to deal with such uncertainties, where the system changes in the face of uncertainty to sustain value, thereby achieving value robustness. While the theme of dealing with multiple uncertainties has been discussed since the inception of PSS, changeability is still poorly addressed. To bridge this gap, an integrative literature review is performed to outline various complexities aspects and their link to uncertainty from a PSS perspective. Also, the state-of-the-art approach to achieving value robustness is presented via changeability incorporation. Subsequently, a reference framework is proposed to guide decision-makers in changeability incorporation in PSS, especially during the early design stages.

High prevalence of anaemia is a severe public health problem in several low- and middle-income countries like India. A qualitative inquiry was designed to understand the perceptions of adolescents regarding anaemia and anaemia prevention measures. Convenience sampling was employed to recruit 39 adolescents (19 girls; 20 boys) from Tikari, India. Interviews were carried out in the local language, audio-recorded and transcribed verbatim. Hemoglobin concentration was also assessed from a single drop of capillary blood using the HemoCue, and the participants were asked to share their Science/Biology and Home Science textbooks. Interview data was analysed thematically. Descriptive statistics were used to examine the distributions of the hemoglobin data while textbooks were analysed using content analysis to verify the coverage of anaemia and anaemia-related matter. Seven themes were identified: (i) Poor understanding of the term anaemia; (ii) Minimal discussion about anaemia in classroom; (iii) Limited knowledge about symptoms of anaemia; (iv) Limited awareness about prevention and cure of anaemia; (v) Perception of iron folic acid and deworming tablets among students; (vi) Lack of contribution of health workers in the prevention of anaemia; (vii) No knowledge of ‘Anemia free India’ programme. More than half of the sample had anaemia (16.7% mild anaemia, 33.3% moderate anaemia, 2.8% severe anaemia). Content analysis revealed that there was limited discussion about anaemia in both Home Science and Science textbooks. Behavioural interventions should focus on inculcating healthy culinary and dietary practices and addressing the gaps in knowledge and understanding of anaemia and its prevention among adolescents.

In the face of climate change, developing resilient crops is crucial for global food security in the 21st century to feed a growing population. Lentil (Lens culinaris Medikus) plays a vital role in ensuring global food and nutritional security. Traits like early flowering enable the crop to mature faster, thereby shortening the growing window and reducing yield losses caused by moisture and heat stresses during the reproductive phase. However, issues like limited genetic diversity in this trait remain unaddressed. To address this gap, our study aims to comprehensively assess genetic variability and trait associations in 158 lentil accessions. In the present study, we observed significant variations for days to 50% flowering (67–90 days), days to maturity (109–122 days) and 100 seed weight (1.69–2.68 g) throughout a period of two consecutive years (2020–2021 and 2021–2022). The observed variability in these traits offers a valuable avenue for the improvement of lentil yield through targeted selection and hybridization. Additionally, correlation analysis showed negative correlation between days to 50% flowering and grain yield per plant, while plant height had a significant (P < 0.01) positive correlation with all traits except yield per plant. Furthermore, we identified specific germplasm with exceptional traits that hold significant potential for future breeding programmes. The genotypes EC 223197-A and EC 267696 were identified for early flowering with high yield, and other genotypes that were identified for various traits would serve as breeding material for the introgression of these traits into elite cultivars.