Exploring parameter sensitivities of the land surface using a locally coupled land-atmosphere model

This paper presents a multicriteria analysis that explores the sensitivity of the land surface to changes in both land and atmospheric parameters, in terms of reproducing surface heat fluxes and ground temperature; for the land parameters, offline sensitivity analyses were also conducted for comparison to infer the influence of land-atmosphere interactions. A simple "one-at-a-time" sensitivity analysis was conducted first to filter out some insensitive parameters, followed by a multicriteria sensitivity analysis using the multiobjective generalized sensitivity analysis algorithm. The models used were the locally coupled National Center for Atmospheric Research (NCAR) single-column community climate model and the offline NCAR land surface model, driven and evaluated by a summer intensive operational periods (IOP) data set from the southern Great Plains. As expected, the results show that land-atmosphere interactions (with or without land-atmosphere parameter interactions) can have significant influences on the sensitivity of the land surface to changes in the land parameters, and the single-criterion sensitivities can be significantly different from the multicriteria sensitivity. These findings are mostly model and data independent and can be generally useful, regardless of the model/data dependence of the sensitivities of individual parameters. The exceptionally high sensitivities of the selected atmospheric parameters in a multicriteria sense (and in particular for latent heat) appeal for adequate attention to the specification of effective values of these parameters in an atmospheric model. Overall, this study proposes an effective framework of multicriteria sensitivity analysis beneficial to future studies in the development and parameter estimation of other complex (offline or coupled) land surface models. Copyright 2004 by the American Geophysical Union

Analytical technology aided optimization and scale-up of impinging jet mixer for reactive crystallization process

Reactive crystallization is widely used in the manufacture of active pharmaceutical ingredients (APIs). Since APIs often have low solubility, traditional stirred tank reactors and the route of process operation and control using metastable zone width are not effective. The current work investigated the integration of an impinging jet mixer and a stirred tank crystallizer that can take advantage of both the reaction and crystallization characteristics, the focus being on design optimization and scale-up using process analytical techniques based on the Fourier transform Infrared spectroscopy and Focused Beam Reflectance Measurement, as well as X-ray diffraction and particle imaging Morphologi G3. The parameters for process operation and design of the impinging jet mixer were optimized. The research was carried out with reference to the manufacture of an antibiotic, sodium cefuroxime, firstly in a 1L reactor, then a 10L reactor. The crystals produced showed higher crystallinity, narrower size distribution, higher stability and purity

Measurement and Modeling of Wireless Off-Body Propagation Characteristics under Hospital Environment at 6-8.5 GHz

© 2013 IEEE. A measurement-based novel statistical path-loss model with a height-dependent factor and a body obstruction (BO) attenuation factor for off-body channel under a hospital environment at 6-8.5 GHz is proposed. The height-dependent factor is introduced to emulate different access point (AP) arrangement scenarios, and the BO factor is employed to describe the effect caused by different body-worn positions. The height-dependent path-loss exponent is validated to fluctuate from 2 to 4 with AP height increasing by employing both computer simulation and classical two-ray model theory. As further validated, the proposed model can provide more flexibility and higher accuracy compared with its existing counterparts. The presented channel model is expected to provide wireless link budget estimation and to further develop the physical layer algorithms for body-centric communication systems under hospital environments

Isolation and Characterization of Batatasin III and 3,4’- Dihydroxy-5-methoxybibenzyl: A Pair of Positional Isomers from Sunipia scariosa

Purpose: To isolate and characterize chemical compounds of biological importance from the whole plant of Sunipia scariosa.Methods: The whole plant of Sunipia scariosa was extracted with methanol (MeOH) and chromatographed on silica gel and sephadex LH-20 to afford the pure isolates. High perfomance liquild chromatography (HPLC) was used for further purification of the isolated compounds. Characterization ofthe isolated compounds was achieved by 1H and 13C nuclear magnetic resonance spectroscopy (NMR) and mass spectrometry (MS).Results: Batatasin III (3,3’-dihydroxy-5-methoxybibenzyl) and  3,4’-dihydroxy-5-methoxybibenzyl, a pair of positional isomers, were isolated from the whole plant of Sunipia scariosa. The yields of the two isomers were 60 and 40 %, respectively, from the mixture of two  compounds.Conclusion: Batatasin III and 3,4’-dihydroxy-5-methoxybibenzyl, a pair of positional isomers were successfully isolated from the whole plant of Sunipia scariosa for the first time.Keywords: Sunipia scariosa, Batatasin III, 3,4’-Dihydroxy-5-methoxybibenzyl, Isomer

Modular immune-homeostatic microparticles promote immune tolerance in mouse autoimmune models

The therapeutic goal for autoimmune diseases is disease antigen-specific immune tolerance without nonspecific immune suppression. However, it is a challenge to induce antigen-specific immune tolerance in a dysregulated immune system. In this study, we developed immune-homeostatic microparticles (IHMs) that treat multiple mouse models of autoimmunity via induction of apoptosis in activated T cells and reestablishment of regulatory T cells. Specifically, in an experimental model of colitis, IHMs rapidly released monocyte chemotactic protein-1 after intravenous administration, which recruited activated T cells and then induced their apoptosis by conjugated Fas ligand on the IHM surface. This triggered professional macrophages to ingest apoptotic T cells and produce high quantities of transforming growth factor-β, which drove regulatory T cell differentiation. Furthermore, the modular design of IHMs allowed IHMs to be engineered with the autoantigen peptides that can reduce disease in an experimental autoimmune encephalomyelitis mouse model and a nonobese diabetic mouse model. This was accomplished by sustained release of the autoantigens after induction of T cell apoptosis and transforming growth factor-β production by macrophages, which promoted to establish an immune tolerant environment. Thus, IHMs may be an efficient therapeutic strategy for autoimmune diseases through induction of apoptosis and reestablishment of tolerant immune responses

AlN/CrN multilayer structures with increased thermal stability

CrAlYN nanolayered coatings of greatly enhanced thermal stability have been developed by doping with levels of Y up to 9 at.%. This prevented the complete dissolution of the layered structure after annealing at 1100 °C in Ar for 1 h, commonly observed in coatings with little or no Y content, although the bilayer period increased from ~ 5 nm to ~ 10 nm. The improved thermal stability is attributed to the formation of a continuous YN layer between the CrN and AlN layers, reducing the rate of interdiffusion

Genome-wide signatures of convergent evolution in echolocating mammals

Evolution is typically thought to proceed through divergence of genes, proteins, and ultimately phenotypes(1-3). However, similar traits might also evolve convergently in unrelated taxa due to similar selection pressures(4,5). Adaptive phenotypic convergence is widespread in nature, and recent results from a handful of genes have suggested that this phenomenon is powerful enough to also drive recurrent evolution at the sequence level(6-9). Where homoplasious substitutions do occur these have long been considered the result of neutral processes. However, recent studies have demonstrated that adaptive convergent sequence evolution can be detected in vertebrates using statistical methods that model parallel evolution(9,10) although the extent to which sequence convergence between genera occurs across genomes is unknown. Here we analyse genomic sequence data in mammals that have independently evolved echolocation and show for the first time that convergence is not a rare process restricted to a handful of loci but is instead widespread, continuously distributed and commonly driven by natural selection acting on a small number of sites per locus. Systematic analyses of convergent sequence evolution in 805,053 amino acids within 2,326 orthologous coding gene sequences compared across 22 mammals (including four new bat genomes) revealed signatures consistent with convergence in nearly 200 loci. Strong and significant support for convergence among bats and the dolphin was seen in numerous genes linked to hearing or deafness, consistent with an involvement in echolocation. Surprisingly we also found convergence in many genes linked to vision: the convergent signal of many sensory genes was robustly correlated with the strength of natural selection. This first attempt to detect genome-wide convergent sequence evolution across divergent taxa reveals the phenomenon to be much more pervasive than previously recognised

An AUC-based Permutation Variable Importance Measure for Random Forests

The random forest (RF) method is a commonly used tool for classification with high dimensional data as well as for ranking candidate predictors based on the so-called random forest variable importance measures (VIMs). However the classification performance of RF is known to be suboptimal in case of strongly unbalanced data, i.e. data where response class sizes differ considerably. Suggestions were made to obtain better classification performance based either on sampling procedures or on cost sensitivity analyses. However to our knowledge the performance of the VIMs has not yet been examined in the case of unbalanced response classes. In this paper we explore the performance of the permutation VIM for unbalanced data settings and introduce an alternative permutation VIM based on the area under the curve (AUC) that is expected to be more robust towards class imbalance. We investigated the performance of the standard permutation VIM and of our novel AUC-based permutation VIM for different class imbalance levels using simulated data and real data. The results suggest that the standard permutation VIM loses its ability to discriminate between associated predictors and predictors not associated with the response for increasing class imbalance. It is outperformed by our new AUC-based permutation VIM for unbalanced data settings, while the performance of both VIMs is very similar in the case of balanced classes. The new AUC-based VIM is implemented in the R package party for the unbiased RF variant based on conditional inference trees. The codes implementing our study are available from the companion website: http://www.ibe.med.uni-muenchen.de/organisation/mitarbeiter/070_drittmittel/janitza/index.html

Supernatants from lymphocytes stimulated with Bacillus Calmette-Guerin can modify the antigenicity of tumours and stimulate allogeneic T-cell responses

BACKGROUND: Reduced expression of class 1 human leucocyte antigens (HLA1) is often a mechanism by which tumours evade surveillance by the host immune system. This is often associated with an immune function that is unable to mount appropriate responses against disease, which can result in a state that favours carcinogenesis. METHODS: In the current study, we have explored the effects of Bacillus Calmette-Guerin (BCG) on the cytokine output of leucocytes, which is a key determinant in generating antitumour action, and have also assessed the effect of these cytokine cocktails on HLA1 expression in solid tumour cell lines. RESULTS: BCG potently activated a broad range of leucocytes, and also enhanced the production of cytokines that were Th(1)-predominant. Supernatants from BCG-treated leucocytes significantly increased the expression of HLA1 on the surface of cancer cell lines, which correlated with increased cytolytic T-cell activity. We also showed that the increased HLA1 expression was associated with activation of intracellular signalling pathways, which was triggered by the increases in the Th(1)-cytokines interferon-γ and tumour necrosis factor-α, as counteracting their effects negated the enhancement. CONCLUSION: These studies reaffirm the role of BCG as a putative immunotherapy through their cytokine-modifying effects on leucocytes and their capacity to enhance tumour visibility