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On the Robustness of LSD Layouts in the Presence of Neighbor Effects
No full textIn this paper we study the status of four non isomorphic Latin Square Designs (LSDs) of order four while finding out the optimal covariate matrices underlying the LSDs with and without Neighbor Effects (NEs). In these LSDs we consider the four sided NEs viz., leftsided, right-sided, top-sided and bottom-sided in the presence of covariates’ effects. We utilize a circular model as was introduced by Kunert. Without NEs each of the four LSDs has six optimal covariate matrices whereas in the presence of the four-sided NEs the results are not as expected, for all the four LSDs
Perceived Mental Health among Identified Talented and Nonidentified Students from Indian Villages, Towns, and Cities During the COVID-19 Pandemic
No full textThe present study investigates the perception of experience of depression, anxiety, and stress (DAS) among young adults (18–22 years of age) from different locales in India during the global COVID-19 pandemic. The sample included 1,020 participants (603 males and 417 females) with 470 identified talented students (ITS) and 550 nonidentified students (NiS) from Indian villages, towns, and cities. multivariate analysis of variance and ordinal logistic regression analysis were carried out to understand the differences between the various subcategories and the probability of having high negative emotional states among those groups. Results point toward varying levels of DAS depending on whether they were ITS or NiS, whether male or female, and whether they came from Indian villages, towns, or cities. Both similarities and dissimilarities with other studies were observed, and the results provide insights into the effect of the pandemic on the mental health of young adults in India. The importance of developing psychological support systems for all students is implicated in the findings of the study
Prevalence of long COVID symptoms in Haryana, India: a cross-sectional follow-up study
No full textBackground: Emerging research indicates growing concern over long COVID globally, although there have been limited studies that estimate population burden. We aimed to estimate the burden of long COVID in three districts of Haryana, India, using an opportunity to link a seroprevalence study to follow-up survey of symptoms associated with long COVID. Methods: We used a population-based seroprevalence survey for COVID-19 conducted in September 2021 across Haryana, India. Adults from three purposively selected districts (Rohtak, Gurugram, and Jhajjar) were eligible to participate; 2205 of 3213 consented to participate in a survey on health status. Trained investigators administered a structured questionnaire that included demographic characteristics, self-reported symptoms of illness in the last six months before the survey, mental health, and history of COVID-19. Findings: Unadjusted regression estimates indicated positive correlations between symptomatic complaints and COVID-19 exposure, suggesting lingering effects of COVID-19 in this population. The overall physical morbidity index was higher among those who tested positive for COVID-19, as was the incidence of new cases. However, both morbidity and incidence became statistically insignificant after adjustment for multiple comparisons. Cough emerged as the only statistically significant individual persistent symptom. Sex-stratified analyses indicated significant estimates only for physical morbidity in women. Interpretation: This study is one of the first from India that uses a large population-based sample to examine longer term repercussions of COVID infections. The burden of long COVID should primarily be addressed in clinical settings, where specialised treatment for individual cases continues to evolve. Our analyses also provide insight into the size and nature of studies required to assess the population-level burden of long COVID. Funding: This paper was produced under the auspices of the Lancet COVID 19 Commission India Task Force, which was supported financially by the Reliance Foundation. The Lancet COVID 19 Commission was set up in July 2020 and submitted its final report by October 2022. This report by the India Task Force was prepared during the same period
Resolving the Singularity by Looking at the Dot and Demonstrating the Undecidability of the Continuum Hypothesis
No full textEinsteinian gravity, of which Newtonian gravity is a part, is fraught with the problem of singularity that has been established as a theorem by Hawking and Penrose. The hypothesis that founds the basis of both Einsteinian and Newtonian theories of gravity is that bodies with unequal magnitudes of masses fall with the same acceleration under the gravity of a source object. Since, the Einstein’s equations is one of the assumptions that underlies the proof of the singularity theorem, therefore, the above hypothesis is implicitly one of the founding pillars of the same. In this work, I demonstrate how one can possibly write a non-singular theory of gravity which manifests that the above mentioned hypothesis is only valid in an approximate sense in the “large distance” scenario. To mention a specific instance, under the gravity of the earth, a 5 kg and a 500 kg fall with accelerations which differ by approximately 113.148×10-32 meter/sec2 and the more massive object falls with less acceleration. Further, I demonstrate why the concept of gravitational field is not definable in the “small distance” regime which automatically justifies why the Einstein’s and Newton’s theories fail to provide any “small distance” analysis. In course of writing down this theory, I demonstrate why the continuum hypothesis as spelled out by Goedel, is undecidable. The theory has several aspects which provide the following realizations: (i) Descartes’ self-skepticism concerning exact representation of numbers by drawing lines (ii) Born’s wish of taking into account “natural uncertainty in all observations” while describing “a physical situation” by means of “real numbers” (iii) Klein’s vision of having “a fusion of arithmetic and geometry” where “a point is replaced by a small spot” (iv) Goedel’s assertion about “non-standard analysis, in some version” being “the analysis of the future”
Review of applications of artificial intelligence (AI) methods in crop research
No full textSophisticated and modern crop improvement techniques can bridge the gap for feeding the ever-increasing population. Artificial intelligence (AI) refers to the simulation of human intelligence in machines, which refers to the application of computational algorithms, machine learning (ML) and deep learning (DL) techniques. This is aimed to generalise patterns and relationships from historical data, employing various mathematical optimisation techniques thus making prediction models for facilitating selection of superior genotypes. These techniques are less resource intensive and can solve the problem based on the analysis of large-scale phenotypic datasets. ML for genomic selection (GS) uses high-throughput genotyping technologies to gather genetic information on a large number of markers across the genome. The prediction of GS models is based on the mathematical relation between genotypic and phenotypic data from the training population. ML techniques have emerged as powerful tools for genome editing through analysing large-scale genomic data and facilitating the development of accurate prediction models. Precise phenotyping is a prerequisite to advance crop breeding for solving agricultural production–related issues. ML algorithms can solve this problem through generating predictive models, based on the analysis of large-scale phenotypic datasets. DL models also have the potential reliability of precise phenotyping. This review provides a comprehensive overview on various ML and DL models, their applications, potential to enhance the efficiency, specificity and safety towards advanced crop improvement protocols such as genomic selection, genome editing, along with phenotypic prediction to promote accelerated breeding
Single-domain magnetic particles with motion behavior under electromagnetic AC and DC fields are a fatal cargo in Metropolitan Mexico City pediatric and young adult early Alzheimer, Parkinson, frontotemporal lobar degeneration and amyotrophic lateral sclerosis and in ALS patients
No full textMetropolitan Mexico City (MMC) children and young adults exhibit overlapping Alzheimer and Parkinsons’ diseases (AD, PD) and TAR DNA-binding protein 43 pathology with magnetic ultrafine particulate matter (UFPM) and industrial nanoparticles (NPs). We studied magnetophoresis, electron microscopy and energy-dispersive X-ray spectrometry in 203 brain samples from 14 children, 27 adults, and 27 ALS cases/controls. Saturation isothermal remanent magnetization (SIRM), capturing magnetically unstable FeNPs ̴ 20nm, was higher in caudate, thalamus, hippocampus, putamen, and motor regions with subcortical vs. cortical higher SIRM in MMC ≤ 40y. Motion behavior was associated with magnetic exposures 25–100 mT and children exhibited IRM saturated curves at 50–300 mT associated to change in NPs position and/or orientation in situ. Targeted magnetic profiles moving under AC/AD magnetic fields could distinguish ALS vs. controls. Motor neuron magnetic NPs accumulation potentially interferes with action potentials, ion channels, nuclear pores and enhances the membrane insertion process when coated with lipopolysaccharides. TEM and EDX showed 7–20 nm NP Fe, Ti, Co, Ni, V, Hg, W, Al, Zn, Ag, Si, S, Br, Ce, La, and Pr in abnormal neural and vascular organelles. Brain accumulation of magnetic unstable particles start in childhood and cytotoxic, hyperthermia, free radical formation, and NPs motion associated to 30–50 μT (DC magnetic fields) are critical given ubiquitous electric and magnetic fields exposures could induce motion behavior and neural damage. Magnetic UFPM/NPs are a fatal brain cargo in children’s brains, and a preventable AD, PD, FTLD, ALS environmental threat. Billions of people are at risk. We are clearly poisoning ourselves
Special section: Best papers of the international conference on pattern recognition and artificial intelligence (ICPRAI) 2022
No full textStructural control on formation of polygonal rims of impact craters in Thaumasia Minor, Mars
No full textIt has been known for almost a century that the surfaces of rocky planets contain polygonal-shaped, circular, or elliptical craters. Researchers have hypothesized that pre-existing structurally weak planes, such as faults or fractures, in the vicinity of the impact, are responsible for polygonal patterns of the crater rims. Thaumasia Minor, Mars, which is a heavily deformed late-Noachian terrain with craters of various morphologies, including polygonal impact craters (PICs), is the present area of study to understand the geological control behind the polygonal shapes of the crater rims. A population of 45 carefully chosen polygonal craters are mapped and compared with morphotectonic structures such as graben, wrinkle ridges, and dykes. To discern the relationship between the features, the study uses trends, statistical and spatial analyses of orientation data, and other parameters such as crater diameter and crater excavation depth. Also, to understand the factors affecting PIC formation, 12 earlier studied craters in East Coprates Planum, a region adjacent to the Thaumasia Minor, are studied again. The study proposes two possible geological controls on PIC formation. The study also suggests that graben have more control over smaller PICs while larger PICs are controlled by wrinkle ridges