Magnetic moments of the low-lying JP= 1/2−J^P=\,1/2^-, 3/2−3/2^- Λ\Lambda resonances within the framework of the chiral quark model

The magnetic moments of the low-lying spin-parity $J^P=$ $1/2^-$, $3/2^-$ $\Lambda$ resonances, like, for example, $\Lambda(1405)$ $1/2^-$, $\Lambda(1520)$ $3/2^-$, as well as their transition magnetic moments, are calculated using the chiral quark model. The results found are compared with those obtained from the nonrelativistic quark model and those of unitary chiral theories, where some of these states are generated through the dynamics of two hadron coupled channels and their unitarization

Magnetic moments of the low-lying {1/2}^- octet baryon resonances

The magnetic moments of the negative parity octet resonances with spin {1/2}: $N^*$(1535), $N^*$(1650), $\Sigma^*$(1620), and $\Xi^*$(1690) have been calculated within the framework of the chiral constituent quark model. In this approach, the presence of the polarized $q\bar{q}$ pairs (or the meson cloud, in other words) is considered by using the Lagrangian for Goldstone boson emission from the constituent quarks. Further, the explicit contributions coming from the spin and orbital angular momentum, including the effects of the configurations mixing between the states with different spins, are obtained. The motivation for these calculations comes from the recent interest in experimental measurement of the magnetic moment of the ${S_{11}(1535)}$ resonance and of similar calculations being done within lattice quantum chromodynamics approaches. Our results can be compared with those expected to come from these sources.Comment: 17 pages, 2 table

ETA CARINAE'S THERMAL X-RAY TAIL MEASURED with XMM-Newton and NuSTAR

The evolved, massive highly eccentric binary system, η Car, underwent a periastron passage in the summer of 2014. We obtained two coordinated X-ray observations with XMM-Newton and NuSTAR during the elevated X-ray flux state and just before the X-ray minimum flux state around this passage. These NuSTAR observations clearly detected X-ray emission associated with η Car extending up to ∼50 keV for the first time. The NuSTAR spectrum above 10 keV can be fit with the bremsstrahlung tail from a kT ∼ 6 keV plasma. This temperature is ΔkT ∼ 2 keV higher than those measured from the iron K emission line complex, if the shocked gas is in collisional ionization equilibrium. This result may suggest that the companion star's pre-shock wind velocity is underestimated. The NuSTAR observation near the X-ray minimum state showed a gradual decline in the X-ray emission by 40% at energies above 5 keV in a day, the largest rate of change of the X-ray flux yet observed in individual η Car observations. The column density to the hardest emission component, NH ∼ 1024 H cm-2, marked one of the highest values ever observed for η Car, strongly suggesting increased obscuration of the wind-wind colliding X-ray emission by the thick primary stellar wind prior to superior conjunction. Neither observation detected the power-law component in the extremely hard band that INTEGRAL and Suzaku observed prior to 2011. If the non-detection by NuSTAR is caused by absorption, the power-law source must be small and located very near the wind-wind collision apex. Alternatively, it may be that the power-law source is not related to either η Car or the GeV γ-ray source

Uterine artery Doppler as a predictor of pre eclampsia - hospital based study

Aim: Study of early second trimester (13-16wks) uterine artery Doppler as predictor of pre eclampsia. Objective: To study whether early changes in uterine artery Doppler have better predictive value for preeclampsia as compared to gestational hypertension. To analyze the maternal and fetal outcome in cases with pre eclampsia vs gestational hypertension. Material & Methods: From 2009 to 2011, we conducted an institutional based study among 100 pregnant women. Uterine artery Doppler was done in the women in early second trimester during the antenatal visits at Niloufer Hospital. We measured and recorded the BP, urine analysis, complete blood work done in every antenatal visit. These women were followed up to their delivery. Data were analyzed and p<0.05 was considered significant. Results: Pre eclampsia developed in 31.25% of the pregnant women with bilateral uterine artery notching at 13-16 weeks of gestational age Odds ratio of patients developing hypertension with uterine artery notching is 6.6. Chi-square = 11.8, P value < 0.0005 (significant). This study has a sensitivity of 71.42%, specificity of 74.41%, positive predictive value of 31.25% and negative predictive value of 94.11% in predicting onset of preeclampsia in pregnancy. Conclusion: Uterine artery Doppler should be done routinely in all pregnant women as risk factors can be identified at an early stage where timely intervention can reduce the maternal and neonatal complications

Magnetic and optical properties of Fe doped crednerite CuMnO2

A geometrically frustrated magnetic CuMnO2 system has been investigated because of its rich magnetic properties. Neutron diffraction, synchrotron X-ray, magnetic, X-ray photoemission spectroscopy (XPS) and UV-Visible spectroscopy measurements have been carried out on CuMnO2 and 5% Fe doped CuMnO2 samples. Fe doping reduces the distortion. Moreover, Fe doping induces the ferromagnetic coupling between ab planes. The value of magnetization is increased with Fe doping but coercivity is decreased. These might be due to the direct Mn-Mn exchange and Mn-O-Cu-O-Mn super-super exchange interactions. The UV-Vis data indicate the appearance of new energy bands in these compounds. The XPS study indicates that Fe is in the 3+ state

Solar drying of herbal wealth in Eastern Himalaya: a review

Solar dryers have proven to be one of the best environmentally friendly approaches for drying purpose of medicinal plants and agricultural crops. Use of solar radiations in drying purpose of plant parts has proven economically as well as environmentally responsible and sensible application. Plants are the treasure of nature with hidden medicinal properties to treat diseases. Plant material should be processed properly for extraction of medicinal molecules in terms drying to decrease the manufacturing loss and to increase the standard of product. Cognizances of ethnobotanical knowledge on plant wealth are extremely beneficial in utilization and exploration of natural resources. Conventionally, low drying temperatures between 30-40°C, with economically beneficial techniques are required to protect sensitive active ingredients. Therefore, the objective of reviewing research in medicinal plant drying is to find out optimum drying temperature and best solar dryer for drying purposes of plant parts in terms of quality and drying costs. Rendering to human requisites, solar appliances for drying purposes will be used as the best alternative to standard sun-drying technique. This review focused on effective drying is demand of present scenario for the application of heat trapped from solar radiations for drying purpose in order to maintain the quality and active ingredients of plants. Conventionally, low drying temperatures between 30-40°C, with economically beneficial techniques are required to protect sensitive active ingredients. Indirect type of solar dryers can easily fulfill all the terms for dying plant products in terms of standard and yield

Uniting cheminformatics and chemical theory to predict the intrinsic aqueous solubility of crystalline druglike molecules

We present four models of solution free-energy prediction for druglike molecules utilizing cheminformatics descriptors and theoretically calculated thermodynamic values. We make predictions of solution free energy using physics-based theory alone and using machine learning/quantitative structure–property relationship (QSPR) models. We also develop machine learning models where the theoretical energies and cheminformatics descriptors are used as combined input. These models are used to predict solvation free energy. While direct theoretical calculation does not give accurate results in this approach, machine learning is able to give predictions with a root mean squared error (RMSE) of ~1.1 log S units in a 10-fold cross-validation for our Drug-Like-Solubility-100 (DLS-100) dataset of 100 druglike molecules. We find that a model built using energy terms from our theoretical methodology as descriptors is marginally less predictive than one built on Chemistry Development Kit (CDK) descriptors. Combining both sets of descriptors allows a further but very modest improvement in the predictions. However, in some cases, this is a statistically significant enhancement. These results suggest that there is little complementarity between the chemical information provided by these two sets of descriptors, despite their different sources and methods of calculation. Our machine learning models are also able to predict the well-known Solubility Challenge dataset with an RMSE value of 0.9–1.0 log S units.Publisher PDFPeer reviewe