Greenhouse gas production in degrading ice-rich permafrost deposits in northeastern Siberia

Permafrost deposits have been a sink for atmospheric carbon for millennia. Thaw-erosional processes, however, can lead to rapid degradation of ice-rich permafrost and the release of substantial amounts of organic carbon (OC). The amount of the OC stored in these deposits and their potential to be microbially decomposed to the greenhouse gases carbon dioxide (CO2) and methane (CH4) depends on climatic and environmental conditions during deposition and the decomposition history before incorporation into the permafrost. Here, we examine potential greenhouse gas production in degrading ice-rich permafrost deposits from three locations in the northeast Siberian Laptev Sea region. The deposits span a period of about 55 kyr from the last glacial period and Holocene interglacial. Samples from all three locations were incubated under aerobic and anaerobic conditions for 134 days at 4 °C. Greenhouse gas production was generally higher in deposits from glacial periods, where 0.2–6.1% of the initially available OC was decomposed to CO2. In contrast, only 0.1–4.0% of initial OC were decomposed in permafrost deposits from the Holocene and the late glacial transition. Within the deposits from the Kargin interstadial period (Marine Isotope Stage 3), local depositional environments, especially soil moisture, also affected the preservation of OC. Sediments deposited under wet conditions contained more labile OC and thus produced more greenhouse gases than sediments deposited under drier conditions. To assess the greenhouse gas production potentials over longer periods, deposits from two locations were incubated for a total of 785 days. However, more than 50% of total CO2 production over 785 days occurred within the first 134 days under aerobic conditions while even 80% were produced over the same period under anaerobic conditions, which emphasizes the non-linearity of the OC decomposition processes. Methanogenesis was generally observed in active layer samples but only sporadically in permafrost samples and was several orders of magnitude smaller than CO2 production

Study of Magnetic Properties of A_2B^'NbO_6 (A=Ba,Sr, (BaSr): and B^'=Fe and Mn) double perovskites

We have studied the magnetic properties of Ba_2FeNbO_6 and Ba_2MnNbO_6. it is seen that Ba_2FeNbO_6 is an antiferromagnet with a weak ferromagnetic behaviour at 5K while Ba_2MnNbO_6 shows two magnetic transitions one at 45 K and the other at 12K. Electron spin resonance (ESR) measurements at room temperature show that the Mn compound does not show any Jahn-Teller distortion. It is also seen that the Neel temperature of the A_2FeNbO_6 (A=Ba,Sr, BaSr) compounds do not vary significantly. However variations in the average A-site ionic radius influence the formation of short range correlations that persist above T_N.Comment: 10 oages, 5 figures, MMM, to appear in J.Appl.Phy

Giant Magnetoelastic Effects in BaTiO3-based Extrinsic Multiferroic Hybrids

Extrinsic multiferroic hybrid structures consisting of ferromagnetic and ferroelectric layers elastically coupled to each other are promising due to their robust magnetoelectric effects even at room temperature. For a quantitative analysis of these magnetoelectric effects, a detailed knowledge of the piezoelectric and magnetoelastic behavior of both constituents as well as their mutual elastic coupling is mandatory. We here report on a theoretical and experimental study of the magnetic behavior of BaTiO3-based extrinsic multiferroic structures. An excellent agreement between molecular dynamics simulations and the experiments was found for Fe50Co50/BaTiO3 and Ni/BaTiO3 hybrid structures. This demonstrates that the magnetic behavior of extrinsic multiferroic hybrid structures can be determined by means of ab-initio calculations, allowing for the design of novel multiferroic hybrids

Vaccine Confidence and the Importance of an Interdisciplinary Approach.

Parental confidence in vaccines is waning. To sustain and improve childhood vaccine coverage rates, insights from multiple disciplines are needed to understand and address the socio-cultural factors contributing to decreased vaccine confidence and uptake

Magnetic moments of W 5d in Ca2CrWO6 and Sr2CrWO6 double perovskites

We have investigated the magnetic moment of the W ion in the ferrimagnetic double perovskites Sr2CrWO6 and Ca2CrWO6 by X-ray magnetic circular dichroism (XMCD) at the W L(2,3) edges. In both compounds a finite negative spin and positive orbital magnetic moment was detected. The experimental results are in good agreement with band-structure calculations for (Sr/Ca)2CrWO6 using the full-potential linear muffin-tin orbital method. It is remarkable, that the magnetic ordering temperature, TC, is correlated with the magnetic moment at the 'non-magnetic' W atom.Comment: accepted for publicatio

More accurate process understanding from process characterization studies using Monte Carlo simulation, regularized regression, and classification models

Establishment of an appropriate control strategy with defined operating ranges (OR) predicted to meet a target product profile is a critical component of commercializing new biologics under the Quality by Design (QbD) approach. Process characterization (PC) studies are performed to expand process understanding by achieving two main goals: 1) determining which process parameters have significant effects on quality attributes and 2) establishing models describing the relationships between these critical process parameters (CPP) and critical quality attributes (CQA). Risk assessment and design of experiments (DOE) techniques are effectively deployed in the industry to identify parameters to study and build process understanding. However, the true value of the data produced by these studies can be compromised by the inherent flaws with traditional data analysis techniques. In particular, p-value based methods such as stepwise regression are prone to generate false positives and overestimated parameter coefficients. Many of the deficiencies of traditional stepwise regression can be alleviated by applying Monte Carlo cross validation (MCCV) and simulations to stepwise algorithms. These methods can greatly enhance process understanding and assist in the selection of CPPs. Regularized regression methods such as LASSO, ridge, and elastic net are also designed to overcome many of the issues inherent in techniques based on ordinary least squares. However, a superior strategy is to build multiple models using a variety of techniques and use the insights gained from each to establish the relationships between CPPs and CQAs. Use of complementary methods during data analysis allows more informed decisions to be made during model construction. Please click Additional Files below to see the full abstract

Spin-glass-like behavior of Ge:Mn

We present a detailed study of the magnetic properties of low-temperature-molecular-beam-epitaxy grown Ge:Mn dilute magnetic semiconductor films. We find strong indications for a frozen state of Ge_{1-x}Mn_{x}, with freezing temperatures of T_f=12K and T_f=15K for samples with x=0.04 and x=0.2, respectively, determined from the difference between field-cooled and zero-field-cooled magnetization. For Ge_{0.96}Mn_{0.04}, ac susceptibility measurements show a peak around T_f, with the peak position T'_f shifting as a function of the driving frequency f by Delta T_f' / [T_f' Delta log f] ~ 0.06, whereas for sample Ge_{0.8}Mn_{0.2} a more complicated behavior is observed. Furthermore, both samples exhibit relaxation effects of the magnetization after switching the magnitude of the external magnetic field below T_f which are in qualitative agreement with the field- and zero-field-cooled magnetization measurements. These findings consistently show that Ge:Mn exhibits a frozen magnetic state at low temperatures and that it is not a conventional ferromagnet.Comment: Revised version contains extended interpretation of experimental dat