The phase relation between sunspot numbers and soft X-ray flares

To better understand long-term flare activity, we present a statistical study on soft X-ray flares from May 1976 to May 2008. It is found that the smoothed monthly peak fluxes of C-class, M-class, and X-class flares have a very noticeable time lag of 13, 8, and 8 months in cycle 21 respectively with respect to the smoothed monthly sunspot numbers. There is no time lag between the sunspot numbers and M-class flares in cycle 22. However, there is a one-month time lag for C-class flares and a one-month time lead for X-class flares with regard to sunspot numbers in cycle 22. For cycle 23, the smoothed monthly peak fluxes of C-class, M-class, and X-class flares have a very noticeable time lag of one month, 5 months, and 21 months respectively with respect to sunspot numbers. If we take the three types of flares together, the smoothed monthly peak fluxes of soft X-ray flares have a time lag of 9 months in cycle 21, no time lag in cycle 22 and a characteristic time lag of 5 months in cycle 23 with respect to the smoothed monthly sunspot numbers. Furthermore, the correlation coefficients of the smoothed monthly peak fluxes of M-class and X-class flares and the smoothed monthly sunspot numbers are higher in cycle 22 than those in cycles 21 and 23. The correlation coefficients between the three kinds of soft X-ray flares in cycle 22 are higher than those in cycles 21 and 23. These findings may be instructive in predicting C-class, M-class, and X-class flares regarding sunspot numbers in the next cycle and the physical processes of energy storage and dissipation in the corona.Comment: 8 pages, 3 figures, Accepted for publication in Astrophysics & Space Scienc

Statistical classification of magnetic resonance images of brain employing random forest classifier

Data mining in brain imaging is an emerging field of high importance for providing prognosis, treatment, and a deeper understanding of how the brain functions. Dementia due to Alzheimer’s disease constitutes the fourth most common disorder among the elderly. Early detection of dementia and correct staging of the severity of dementia is critical to select the optional treatment. The present study was designed to classify and categorize brain images of dementia patients into three distinct classes ie, Normal, Moderately diseased, and Severe. Decision Forest Classifier was employed to classify the various Magnetic Resonance Images (MRIs) of dementia patients. Results of screening the MRIs are organized by classification and finally grouped into the three categories, ie, Normal, Moderate and Severe. Experimental results obtained indicated that the proposed method performs relatively well with the classification accuracy reaching nearly 99.32% in comparison with the already existing algorithms

Classification and treatment of different stages of alzheimer’s disease using various machine learning methods

There has been a steady rise in the number of patients suffering from Alzheimer’s disease (AD) all over the world. Medical diagnosis is an important but complicated task that should be performed accurately and efficiently and its automation would be very useful. The patient’s records are collected from National Institute on Aging, USA. The Sample consisted of initial visits of 496 subjects seen either as control or as patients. Patients were concerned about their memory at the National Institute on Aging. It also consisted of patients and caregiver interviews. This research work presents different models for the classification of different stages of Alzheimer’s disease using various machine learning methods such as Neural Networks, Multilayer Perceptron, Bagging, Decision tree, CANFIS and Genetic algorithms. The classification accuracy for CANFIS was found to be 99.55% which was found to be better when compared to other classification methods. Based on the outcome of classification accuracies, various management and treatment strategies such as pharmacotherapeutic and non pharmacotherapeutic interventions for mild, moderate and severe AD were elucidated, which can be of enormous use for the medical professionals in diagnosis and treatment of AD

Evaluation of global composite collection reveals agronomically superior germplasm accessions for chickpea improvement

The rich genetic diversity existing within exotic, indigenous, and diverse germplasm lays the foundation for the continuous improvement of crop cultivars. The composite collection has been suggested as a gateway to identifying superior germplasm for use in crop improvement programs. Here, a chickpea global composite collection was evaluated at five locations in India over two years for five agronomic traits to identify agronomically superior accessions. The desi, kabuli, and intermediate types of chickpea accessions differed significantly for plant height (PLHT) and 100-seed weight (100 SW). In contrast, the intermediate type differed substantially from kabuli for days to maturity (DM). Several highly significant trait correlations were detected across different locations. The most stable and promising accessions from each of the five locations were prioritised based on their superior performance over the best-performing check cultivar. Accordingly, the selected germplasm accessions of desi type showed up to 176% higher seed yield (SY), 29% lower flowering time, 21% fewer maturity days, 64% increase in PLHT, and 183% larger seeds than the check cultivar JG11 or Annigeri. The prioritised kabuli accessions displayed up to 270% more yield, 13% less flowering time, 8% fewer maturity days, 111% increase in PLHT, and 41% larger seeds over the check cultivar KAK2. While the intermediate type accessions had up to 169% better yield, 1% early flowering, 3% early maturity, 54% taller plants, and 25% bigger seeds over the check cultivar JG 11 or KAK2. These accessions can be utilised in chickpea improvement programs to develop high-yielding, early flowering, short duration, taller, and large-seeded varieties with a broad genetic base

Plant regulators and invertase activity in sugarcane at the beginning of the harvest season

Invertases play an essential role in partitioning photosynthates between storage and growth. The objective of this study was to evaluate the activity of acid and neutral invertases and the role they play in controlling the accumulation of sucrose in sugarcane as a result of the application of plant regulators in the beginning of the cropping season.A randomized block experimental design was adopted, with five replicates.The treatments consisted in the application of three plant regulators of the class of growth inhibitors (Sulfomethuron-methyl - 20g ha-1, Glyphosate - 0.4L ha-1, and Compounds from organic carboxylic radicals + Glyphosate - 1L ha-1 + 0.15L ha-1), in addition to a control (natural ripening).The acid and neutral invertase levels are affected in different ways and intensities, due to the active principle used as ripening agent and to the weather conditions.In sugarcane variety RB85-5453, with the conditions described in this experiment, it is suggested high levels of soluble acid invertase in relation to levels of neutral invertase; however, the first was characterized by high sucrose content in the stalks.Inverse correlation could be established for sugarcane variety RB85-5453 between soluble acid invertase levels and effective sucrose accumulation in the stalks

Associations of autozygosity with a broad range of human phenotypes

In many species, the offspring of related parents suffer reduced reproductive success, a phenomenon known as inbreeding depression. In humans, the importance of this effect has remained unclear, partly because reproduction between close relatives is both rare and frequently associated with confounding social factors. Here, using genomic inbreeding coefficients (FROH) for >1.4 million individuals, we show that FROH is significantly associated (p < 0.0005) with apparently deleterious changes in 32 out of 100 traits analysed. These changes are associated with runs of homozygosity (ROH), but not with common variant homozygosity, suggesting that genetic variants associated with inbreeding depression are predominantly rare. The effect on fertility is striking: FROH equivalent to the offspring of first cousins is associated with a 55% decrease [95% CI 44–66%] in the odds of having children. Finally, the effects of FROH are confirmed within full-sibling pairs, where the variation in FROH is independent of all environmental confounding

Curvature-bias corrections using a pseudomass method

Momentum measurements for very high momentum charged particles, such as muons from electroweak vector boson decays, are particularly susceptible to charge-dependent curvature biases that arise from misalignments of tracking detectors. Low momentum charged particles used in alignment procedures have limited sensitivity to coherent displacements of such detectors, and therefore are unable to fully constrain these misalignments to the precision necessary for studies of electroweak physics. Additional approaches are therefore required to understand and correct for these effects. In this paper the curvature biases present at the LHCb detector are studied using the pseudomass method in proton-proton collision data recorded at centre of mass energy √s = 13 TeV during 2016, 2017 and 2018. The biases are determined using Z → μ+μ- decays in intervals defined by the data-taking period, magnet polarity and muon direction. Correcting for these biases, which are typically at the 10-4 GeV-1 level, improves the Z → μ+μ- mass resolution by roughly 18% and eliminates several pathological trends in the kinematic-dependence of the mean dimuon invariant mass

Anemia prevalence in women of reproductive age in low- and middle-income countries between 2000 and 2018

Anemia is a globally widespread condition in women and is associated with reduced economic productivity and increased mortality worldwide. Here we map annual 2000–2018 geospatial estimates of anemia prevalence in women of reproductive age (15–49 years) across 82 low- and middle-income countries (LMICs), stratify anemia by severity and aggregate results to policy-relevant administrative and national levels. Additionally, we provide subnational disparity analyses to provide a comprehensive overview of anemia prevalence inequalities within these countries and predict progress toward the World Health Organization’s Global Nutrition Target (WHO GNT) to reduce anemia by half by 2030. Our results demonstrate widespread moderate improvements in overall anemia prevalence but identify only three LMICs with a high probability of achieving the WHO GNT by 2030 at a national scale, and no LMIC is expected to achieve the target in all their subnational administrative units. Our maps show where large within-country disparities occur, as well as areas likely to fall short of the WHO GNT, offering precision public health tools so that adequate resource allocation and subsequent interventions can be targeted to the most vulnerable populations.Peer reviewe

Measurement of the total cross section and ρ -parameter from elastic scattering in pp collisions at √s=13 TeV with the ATLAS detector

In a special run of the LHC with β⋆=2.5 km, proton–proton elastic-scattering events were recorded at s√=13 TeV with an integrated luminosity of 340 μb−1 using the ALFA subdetector of ATLAS in 2016. The elastic cross section was measured differentially in the Mandelstam t variable in the range from −t=2.5⋅10−4 GeV2 to −t=0.46 GeV2 using 6.9 million elastic-scattering candidates. This paper presents measurements of the total cross section σtot, parameters of the nuclear slope, and the ρ-parameter defined as the ratio of the real part to the imaginary part of the elastic-scattering amplitude in the limit t→0. These parameters are determined from a fit to the differential elastic cross section using the optical theorem and different parameterizations of the t-dependence. The results for σtot and ρ are σtot(pp→X)=104.7±1.1 mb ,ρ=0.098±0.011. The uncertainty in σtot is dominated by the luminosity measurement, and in ρ by imperfect knowledge of the detector alignment and by modelling of the nuclear amplitude.publishedVersio

Measurement of the CKM angle γ in the B0→DK *0 channel using self-conjugate D→ KS0h+ h- decays

A model-independent study of CP violation in B-0 -&gt; DK (*0) decays is presented using data corresponding to an integrated luminosity of 9 fb(-1) collected by the LHCb experiment at centre-of-mass energies of v s = 7, 8 and 13TeV. The CKM angle. is determined by examining the distributions of signal decays in phase-space bins of the self-conjugate D. K(S)(0)h(+) h(-) decays, where h = p, K. Observables related to CP violation are measured and the angle. is determined to be. = (49+22 -19).. Measurements of the amplitude ratio and strong-phase difference between the favoured and suppressed B-0 decays are also presented