Reduced 1/f noise in p-Si0.3Ge0.7 metamorphic metal–oxide–semiconductor field-effect transistor

We have demonstrated reduced 1/f low-frequency noise in sub-µm metamorphic high Ge content p-Si0.3Ge0.7 metal–oxide–semiconductor field-effect transistors (MOSFETs) at 293 K. Three times lower normalized power spectral density (NPSD) SID/ID2 of drain current fluctuations over the 1–100 Hz range at VDS = –50 mV and VG–Vth = –1.5 V was measured for a 0.55 µm effective gate length p-Si0.3Ge0.7 MOSFET compared with a p-Si MOSFET. Performed quantitative analysis clearly demonstrates the importance of carrier number fluctuations and correlated mobility fluctuations (CMFs) components of 1/f noise for p-Si surface channel MOSFETs, and the absence of CMFs for p-Si0.3Ge0.7 buried channel MOSFETs. This explains the reduced NPSD for p-Si0.3Ge0.7 MOSFETs in strong inversion

A climate change simulation starting from 1935

Due to restrictions in the available computing resources and a lack of suitable observational data, transient climate change experiments with global coupled ocean-atmosphere models have been started from an initial state at equilibrium with the present day forcing. The historical development of greenhouse gas forcing from the onset of industrialization until the present has therefore been neglected. Studies with simplified models have shown that this "cold start" error leads to a serious underestimation of the anthropogenic global warming. In the present study, a 150-year integration has been carried out with a global coupled ocean-atmosphere model starting from the greenhouse gas concentration observed in 1935, i.e., at an early time of industrialization. The model was forced with observed greenhouse gas concentrations up to 1985, and with the equivalent C02 concentrations stipulated in Scenario A ("Business as Usual") of the Intergovernmental Panel on Climate Change from 1985 to 2085. The early starting date alleviates some of the cold start problems. The global mean near surface temperature change in 2085 is about 0.3 K (ca. 10) higher in the early industrialization experiment than in an integration with the same model and identical Scenario A greenhouse gas forcing, but with a start date in 1985. Comparisons between the experiments with early and late start dates show considerable differences in the amplitude of the regional climate change patterns, particularly for sea level. The early industrialization experiment can be used to obtain a first estimate of the detection time for a greenhouse-gas-induced near-surface temperature signal. Detection time estimates are obtained using globally and zonally averaged data from the experiment and a long control run, as well as principal component time series describing the evolution of the dominant signal and noise modes. The latter approach yields the earliest detection time (in the decade 1990-2000) for the time-evolving near-surface temperature signal. For global-mean temperatures or for temperatures averaged between 45°N and 45°S, the signal detection times are in the decades 2015-2025 and 2005-2015, respectively. The reduction of the "cold start" error in the early industrialization experiment makes it possible to separate the near-surface temperature signal from the noise about one decade earlier than in the experiment starting in 1985. We stress that these detection times are only valid in the context of the coupled model's internally-generated natural variability, which possibly underestimates low frequency fluctuations and does not incorporate the variance associated with changes in external forcing factors, such as anthropogenic sulfate aerosols, solar variability or volcanic dust. © 1995 Springer-Verlag

Monte Carlo climate change forecasts with a global coupled ocean-atmosphere model

Four time-dependent greenhouse warming experiments were performed with the same global coupled atmosphere-ocean model, but with each simulation using initial conditions from different ''snapshots'' of the control run climate. The radiative forcing - the increase in equivalent CO2 concentrations from 19852035 specified in the Intergovernmental Panel on Climate Change (IPCC) scenario A - was identical in all four 50-year integrations. This approach to climate change experiments is called the Monte Carlo technique and is analogous to a similar experimental set-up used in the field of extended range weather forecasting. Despite the limitation of a very small sample size, this approach enables the estimation of both a mean response and the ''between-experiment'' variability, information which is not available from a single integration. The use of multiple realizations provides insights into the stability of the response, both spatially, seasonally and in terms of different climate variables. The results indicate that the time evolution of the global mean warming signal is strongly dependent on the initial state of the climate system. While the individual members of the ensemble show considerable variation in the pattern and amplitude of near-surface temperature change after 50 years, the ensemble mean climate change pattern closely resembles that obtained in a 100-year integration performed with the same model. In global mean terms, the climate change signals for near surface temperature, the hydrological. cycle and sea level significantly exceed the variability among the members of the ensemble. Due to the high internal variability of the modelled climate system, the estimated detection time of the global mean temperature change signal is uncertain by at least one decade. While the ensemble mean surface temperature and sea level fields show regionally significant responses to greenhouse-gas forcing, it is not possible to identify a significant response in the precipitation and soil moisture fields, variables which are spatially noisy and characterized by large variability between the individual integrations

Epstein–Barr virus-encoded microRNA miR-BART2 down-regulates the viral DNA polymerase BALF5

MicroRNAs (miRNAs) have been implicated in sequence-specific cleavage, translational repression or deadenylation of specific target mRNAs resulting in post-transcriptional gene silencing. Epstein–Barr virus (EBV) encodes 23 miRNAs of unknown function. Here we show that the EBV-encoded miRNA miR-BART2 down-regulates the viral DNA polymerase BALF5. MiR-BART2 guides cleavage within the 3′-untranslated region (3′UTR) of BALF5 by virtue of its complete complementarity to its target. Induction of the lytic viral replication cycle results in a reduction of the level of miR-BART2 with a strong concomitant decrease of cleavage of the BALF5 3′UTR. Expression of miR-BART2 down-regulates the activity of a luciferase reporter gene containing the BALF5 3′UTR. Forced expression of miR-BART2 during lytic replication resulted in a 40–50% reduction of the level of BALF5 protein and a 20% reduction of the amount of virus released from EBV-infected cells. Our results are compatible with the notion that EBV-miR-BART2 inhibits transition from latent to lytic viral replication

Oligocene and early Miocene mammal biostratigraphy of the Valley of Lakes in Mongolia

The Taatsiin Gol Basin in Mongolia is a key area for understanding the evolution and dispersal of Central Asian mammal faunas during the Oligocene and early Miocene. After two decades of intense fieldwork, the area is extraordinarily well sampled and taxonomically well studied, yielding a large dataset of 19,042 specimens from 60 samples. The specimens represent 176 species-level and 99 genus-level taxa comprising 135 small mammal species and 47 large mammals. A detailed lithostratigraphy and new magnetostratigraphic and radiometric datings provide an excellent frame for these biotic data. Therefore, we test and evaluate the informal biozonation scheme that has been traditionally used for biostratigraphic correlations within the basin. Based on the analysis of the huge dataset, a formalised biostratigraphic scheme is proposed. It comprises the Cricetops dormitor Taxon Range Zone (Rupelian), subdivided into the Allosminthus khandae Taxon Range Subzone and the Huangomys frequens Abundance Subzone, the Amphechinus taatsiingolensis Abundance Zone (early Chattian), the Amphechinus major Taxon Range Zone (late Chattian), subdivided into the Yindirtemys deflexus Abundance Subzone and the Upper Amphechinus major T. R. Z., and the Tachyoryctoides kokonorensis Taxon Range Zone (Aquitanian). In statistical analyses, samples attributed to these biozones form distinct clusters, indicating that each biozone was also characterised by a distinct faunal type

Mechanisms of particles in sensitization, effector function and therapy of allergic disease

Humans have always been in contact with natural airborne particles from many sources including biologic particulate matter (PM) which can exhibit allergenic properties. With industrialization, anthropogenic and combustion-derived particles have become a major fraction. Currently, an ever-growing number of diverse and innovative materials containing engineered nanoparticles (NPs) are being developed with great expectations in technology and medicine. Nanomaterials have entered everyday products including cosmetics, textiles, electronics, sports equipment, as well as food, and food packaging. As part of natural evolution humans have adapted to the exposure to particulate matter, aiming to protect the individual's integrity and health. At the respiratory barrier, complications can arise, when allergic sensitization and pulmonary diseases occur in response to particle exposure. Particulate matter in the form of plant pollen, dust mites feces, animal dander, but also aerosols arising from industrial processes in occupational settings including diverse mixtures thereof can exert such effects. This review article gives an overview of the allergic immune response and addresses specifically the mechanisms of particulates in the context of allergic sensitization, effector function and therapy. In regard of the first theme (i), an overview on exposure to particulates and the functionalities of the relevant immune cells involved in allergic sensitization as well as their interactions in innate and adaptive responses are described. As relevant for human disease, we aim to outline (ii) the potential effector mechanisms that lead to the aggravation of an ongoing immune deviation (such as asthma, chronic obstructive pulmonary disease, etc.) by inhaled particulates, including NPs. Even though adverse effects can be exerted by (nano)particles, leading to allergic sensitization, and the exacerbation of allergic symptoms, promising potential has been shown for their use in (iii) therapeutic approaches of allergic disease, for example as adjuvants. Hence, allergen-specific immunotherapy (AIT) is introduced and the role of adjuvants such as alum as well as the current understanding of their mechanisms of action is reviewed. Finally, future prospects of nanomedicines in allergy treatment are described, which involve modern platform technologies combining immunomodulatory effects at several (immuno-)functional levels

Spin versus Lattice Polaron: Prediction for Electron-Doped CaMnO3

CaMnO3 is a simple bi-partite antiferromagnet(AF) which can be continuously electron-doped up to LaMnO3. Electrons enter the doubly degenerate E_g subshell with spins aligned to the S=3/2 core of Mn^4+ (T_2g^3)$. We take the Hubbard and Hund energies to be effectively infinite. Our model Hamiltonian has two E_g orbitals per Mn atom, nearest neighbor hopping, nearest neighbor exchange coupling of the S=3/2 cores, and electron-phonon coupling of Mn orbitals to adjacent oxygen atoms. We solve this model for light doping. Electrons are confined in local ferromagnetic (FM) regions (spin polarons) where there proceeds an interesting competition between spin polarization (spin polarons) which enlarges the polaron, and lattice polarization (Jahn-Teller polarons) which makes it smaller. A symmetric 7-atom ferromagnetic cluster (Mn_7^27+) is the stable result, with net spin S=2 relative to the undoped AF. The distorted oxygen positions around the electron are predicted. The model also predicts a critical doping x_c=0.045 where the polaronic insulator becomes unstable relative to a FM metal.Comment: 9 pages with 7 embedded postscript figures and 2 table

The E⊗eE\otimes e Jahn-Teller Polaron in Comparison with the Holstein Polaron

Based on an exact expression for the self-energy of the Jahn-Teller polaron, we find that symmetry of pseudospin rotation makes the vertex correction much less effective than that for the Holstein polaron. This ineffectiveness brings about a smaller effective mass m^* and a quantitatively differenent large-to-small polaron crossover, as examined by exact diagonalization in a two-site system. In the strong-coupling and antiadiabatic region, a rigorous analytic expression is found for m^*

Genome-wide identification of Ago2 binding sites from mouse embryonic stem cells with and without mature microRNAs

MicroRNAs (miRNAs) are 19–22-nucleotide noncoding RNAs that post-transcriptionally regulate mRNA targets. We have identified endogenous miRNA binding sites in mouse embryonic stem cells (mESCs), by performing photo-cross-linking immunoprecipitation using antibodies to Argonaute (Ago2) followed by deep sequencing of RNAs (CLIP-seq). We also performed CLIP-seq in Dicer[superscript −/−] mESCs that lack mature miRNAs, allowing us to define whether the association of Ago2 with the identified sites was miRNA dependent. A significantly enriched motif, GCACUU, was identified only in wild-type mESCs in 3′ untranslated and coding regions. This motif matches the seed of a miRNA family that constitutes ~68% of the mESC miRNA population. Unexpectedly, a G-rich motif was enriched in sequences cross-linked to Ago2 in both the presence and absence of miRNAs. Expression analysis and reporter assays confirmed that the seed-related motif confers miRNA-directed regulation on host mRNAs and that the G-rich motif can modulate this regulation.Leukemia & Lymphoma Society of AmericaUnited States. Public Health Service (Grant R01-GM34277)United States. Public Health Service (Grant R01-CA133404)National Cancer Institute (U.S.) (Grant P01-CA42063)National Cancer Institute (U.S.) Cancer Center Support (Grant P30-CA14051