Mid-infrared optical parametric amplifier using silicon nanophotonic waveguides

All-optical signal processing is envisioned as an approach to dramatically decrease power consumption and speed up performance of next-generation optical telecommunications networks. Nonlinear optical effects, such as four-wave mixing (FWM) and parametric gain, have long been explored to realize all-optical functions in glass fibers. An alternative approach is to employ nanoscale engineering of silicon waveguides to enhance the optical nonlinearities by up to five orders of magnitude, enabling integrated chip-scale all-optical signal processing. Previously, strong two-photon absorption (TPA) of the telecom-band pump has been a fundamental and unavoidable obstacle, limiting parametric gain to values on the order of a few dB. Here we demonstrate a silicon nanophotonic optical parametric amplifier exhibiting gain as large as 25.4 dB, by operating the pump in the mid-IR near one-half the band-gap energy (E~0.55eV, lambda~2200nm), at which parasitic TPA-related absorption vanishes. This gain is high enough to compensate all insertion losses, resulting in 13 dB net off-chip amplification. Furthermore, dispersion engineering dramatically increases the gain bandwidth to more than 220 nm, all realized using an ultra-compact 4 mm silicon chip. Beyond its significant relevance to all-optical signal processing, the broadband parametric gain also facilitates the simultaneous generation of multiple on-chip mid-IR sources through cascaded FWM, covering a 500 nm spectral range. Together, these results provide a foundation for the construction of silicon-based room-temperature mid-IR light sources including tunable chip-scale parametric oscillators, optical frequency combs, and supercontinuum generators

Non-thermal emission processes in massive binaries

In this paper, I present a general discussion of several astrophysical processes likely to play a role in the production of non-thermal emission in massive stars, with emphasis on massive binaries. Even though the discussion will start in the radio domain where the non-thermal emission was first detected, the census of physical processes involved in the non-thermal emission from massive stars shows that many spectral domains are concerned, from the radio to the very high energies. First, the theoretical aspects of the non-thermal emission from early-type stars will be addressed. The main topics that will be discussed are respectively the physics of individual stellar winds and their interaction in binary systems, the acceleration of relativistic electrons, the magnetic field of massive stars, and finally the non-thermal emission processes relevant to the case of massive stars. Second, this general qualitative discussion will be followed by a more quantitative one, devoted to the most probable scenario where non-thermal radio emitters are massive binaries. I will show how several stellar, wind and orbital parameters can be combined in order to make some semi-quantitative predictions on the high-energy counterpart to the non-thermal emission detected in the radio domain. These theoretical considerations will be followed by a census of results obtained so far, and related to this topic... (see paper for full abstract)Comment: 47 pages, 5 postscript figures, accepted for publication in Astronomy and Astrophysics Review. Astronomy and Astrophysics Review, in pres

Ramified rectilinear polygons: coordinatization by dendrons

Simple rectilinear polygons (i.e. rectilinear polygons without holes or cutpoints) can be regarded as finite rectangular cell complexes coordinatized by two finite dendrons. The intrinsic $l_1$-metric is thus inherited from the product of the two finite dendrons via an isometric embedding. The rectangular cell complexes that share this same embedding property are called ramified rectilinear polygons. The links of vertices in these cell complexes may be arbitrary bipartite graphs, in contrast to simple rectilinear polygons where the links of points are either 4-cycles or paths of length at most 3. Ramified rectilinear polygons are particular instances of rectangular complexes obtained from cube-free median graphs, or equivalently simply connected rectangular complexes with triangle-free links. The underlying graphs of finite ramified rectilinear polygons can be recognized among graphs in linear time by a Lexicographic Breadth-First-Search. Whereas the symmetry of a simple rectilinear polygon is very restricted (with automorphism group being a subgroup of the dihedral group $D_4$), ramified rectilinear polygons are universal: every finite group is the automorphism group of some ramified rectilinear polygon.Comment: 27 pages, 6 figure

Herbivory and eutrophication mediate grassland plant nutrient responses across a global climatic gradient

Plant stoichiometry, the relative concentration of elements, is a key regulator of ecosystem functioning and is also being altered by human activities. In this paper we sought to understand the global drivers of plant stoichiometry and compare the relative contribution of climatic vs. anthropogenic effects. We addressed this goal by measuring plant elemental (C, N, P and K) responses to eutrophication and vertebrate herbivore exclusion at eighteen sites on six continents. Across sites, climate and atmospheric N deposition emerged as strong predictors of plot‐level tissue nutrients, mediated by biomass and plant chemistry. Within sites, fertilization increased total plant nutrient pools, but results were contingent on soil fertility and the proportion of grass biomass relative to other functional types. Total plant nutrient pools diverged strongly in response to herbivore exclusion when fertilized; responses were largest in ungrazed plots at low rainfall, whereas herbivore grazing dampened the plant community nutrient responses to fertilization. Our study highlights (1) the importance of climate in determining plant nutrient concentrations mediated through effects on plant biomass, (2) that eutrophication affects grassland nutrient pools via both soil and atmospheric pathways and (3) that interactions among soils, herbivores and eutrophication drive plant nutrient responses at small scales, especially at water‐limited sites

X-Ray Spectroscopy of Stars

(abridged) Non-degenerate stars of essentially all spectral classes are soft X-ray sources. Low-mass stars on the cooler part of the main sequence and their pre-main sequence predecessors define the dominant stellar population in the galaxy by number. Their X-ray spectra are reminiscent, in the broadest sense, of X-ray spectra from the solar corona. X-ray emission from cool stars is indeed ascribed to magnetically trapped hot gas analogous to the solar coronal plasma. Coronal structure, its thermal stratification and geometric extent can be interpreted based on various spectral diagnostics. New features have been identified in pre-main sequence stars; some of these may be related to accretion shocks on the stellar surface, fluorescence on circumstellar disks due to X-ray irradiation, or shock heating in stellar outflows. Massive, hot stars clearly dominate the interaction with the galactic interstellar medium: they are the main sources of ionizing radiation, mechanical energy and chemical enrichment in galaxies. High-energy emission permits to probe some of the most important processes at work in these stars, and put constraints on their most peculiar feature: the stellar wind. Here, we review recent advances in our understanding of cool and hot stars through the study of X-ray spectra, in particular high-resolution spectra now available from XMM-Newton and Chandra. We address issues related to coronal structure, flares, the composition of coronal plasma, X-ray production in accretion streams and outflows, X-rays from single OB-type stars, massive binaries, magnetic hot objects and evolved WR stars.Comment: accepted for Astron. Astrophys. Rev., 98 journal pages, 30 figures (partly multiple); some corrections made after proof stag

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

The effector T cell response to influenza infection

Influenza virus infection induces a potent initial innate immune response, which serves to limit the extent of viral replication and virus spread. However, efficient (and eventual) viral clearance within the respiratory tract requires the subsequent activation, rapid proliferation, recruitment, and expression of effector activities by the adaptive immune system, consisting of antibody producing B cells and influenza-specific T lymphocytes with diverse functions. The ensuing effector activities of these T lymphocytes ultimately determine (along with antibodies) the capacity of the host to eliminate the viruses and the extent of tissue damage. In this review, we describe this effector T cell response to influenza virus infection. Based on information largely obtained in experimental settings (i.e., murine models), we will illustrate the factors regulating the induction of adaptive immune T cell responses to influenza, the effector activities displayed by these activated T cells, the mechanisms underlying the expression of these effector mechanisms, and the control of the activation/differentiation of these T cells, in situ, in the infected lungs

Cost-effectiveness of collaborative care for chronically ill patients with comorbid depressive disorder in the general hospital setting, a randomised controlled trial

Background. Depressive disorder is one of the most common disorders, and is highly prevalent in chronically ill patients. The presence of comorbid depression has a negative influence on quality of life, health care costs, self-care, morbidity, and mortality. Early diagnosis and well-organized treatment of depression has a positive influence on these aspects. Earlier research in the USA has reported good results with regard to the treatment of depression with a collaborative care approach and an antidepressant algorithm. In the UK 'Problem Solving Treatment' has proved to be feasible. However, in the general hospital setting this approach has not yet been evaluated. Methods/Design. CC: DIM (Collaborative Care: Depression Initiative in the Medical setting) is a two-armed randomised controlled trial with randomisation at patient level. The aim of the trial is to evaluate the treatment of depressive disorder in general hospitals in the Netherlands based on a collaborative care framework, including contracting, 'Problem Solving Treatment', antidepressant algorithm, and manual-guided self-help. 126 outpatients with diabetes mellitus, chronic obstructive pulmonary disease, or cardiovascular diseases will be randomised to either the intervention group or the control group. Patients will be included if they have been diagnosed with moderate to severe depression, based on the DSM-IV criteria in a two-step screening method. The intervention group will receive treatment based on the collaborative care approach; the control group will receive 'care as usual'. Baseline and follow-up measurements (after 3, 6, 9, and 12 months) will be performed by means of questionnaires. The primary outcome measure is severity of depressive symptoms, as measured with the PHQ-9. The secondary outcome measure is the cost-effectiveness of these treatments according to the TiC-P, the EuroQol and the SF-36. Discussion. Earlier research has indicated that depressive disorder is a chronic, mostly recurrent illness, which tends to cluster with physical comorbidity. Even though the treatment of depressive disorder based on the guidelines for depression is proven effective, these guidelines are often insufficiently adhered to. Collaborative care and 'Problem Solving Treatment' will be specifically tailored to patients with depressive disorders and evaluated in a general hospital setting in the Netherlands

Quantitative autoradiographic evaluation of the influence of protein dose on monoclonal antibody distribution in human ovarian adenocarcinoma xenografts

We studied the effect of monoclonal antibody protein dose on the uniformity of radioiodinated antibody distribution within tumor masses using quantitative autoradiography. Groups ( n = 11–13/group) of athymic nude mice with subcutaneous HTB77 human ovarian carcinoma xenografts were injected intraperitoneally with an 125 I-labeled anticarcinoma-associated antigen murine monoclonal antibody, 5G6.4, using a high or a low protein dose (500 µg or 5 µg). At 6 days post-injection the macroscopic and microscopic intratumoral biodistribution of radiolabeled antibody was determined. The degree of heterogeneity of the labeled antibody distribution within each tumor was quantified and expressed as the coefficient of variation (CV) of the activity levels in serial histological sections. Tumors from mice given the 500-µg protein doses had substantially lower CV values, 0.327±0.027, than did tumors from animals given 5-µg protein doses, 0.458±0.041, ( P = 0.0078), indicating that the higher protein dose resulted in more homogeneous distribution of radioactivity in tumors than did the lower dose. While the percentage of the injected dose reaching the tumor was comparable between groups, injecting the higher dose of protein resulted in significantly lower tumor to non-tumor uptake ratios than those obtained for the lower protein dose. These data indicate, in this system, that to achieve more uniform intratumoral antibody (and radiation for radioimmunotherapy) delivery, a relatively high protein dose must be administered. However, to obtain this increased uniformity, a substantial drop in tumor/background uptake ratios was seen. Quantitative autoradiographic evaluation of human tumor xenografts is a useful method to assess the intratumoral distribution of antibodies.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/46859/1/262_2005_Article_BF01789014.pd

Who Shares? Who Doesn't? Factors Associated with Openly Archiving Raw Research Data

Many initiatives encourage investigators to share their raw datasets in hopes of increasing research efficiency and quality. Despite these investments of time and money, we do not have a firm grasp of who openly shares raw research data, who doesn't, and which initiatives are correlated with high rates of data sharing. In this analysis I use bibliometric methods to identify patterns in the frequency with which investigators openly archive their raw gene expression microarray datasets after study publication