Relation between sequence and structure of HIV-1 protease inhibitor complexes: a model system for the analysis of protein flexibility.

The flexibility of different regions of HIV-1 protease was examined by using a database consisting of 73 X-ray structures that differ in terms of sequence, ligands or both. The root-mean-square differences of the backbone for the set of structures were shown to have the same variation with residue number as those obtained from molecular dynamics simulations, normal mode analyses and X-ray B-factors. This supports the idea that observed structural changes provide a measure of the inherent flexibility of the protein, although specific interactions between the protease and the ligand play a secondary role. The results suggest that the potential energy surface of the HIV-1 protease is characterized by many local minima with small energetic differences, some of which are sampled by the different X-ray structures of the HIV-1 protease complexes. Interdomain correlated motions were calculated from the structural fluctuations and the results were also in agreement with molecular dynamics simulations and normal mode analyses. Implications of the results for the drug-resistance engendered by mutations are discussed briefly.

Modeling of non-isothermalvapor membrane separation with thermodynamic models and generalized mass transfer equations

A rigorous unit operation model is developed for vapor membrane separation. The new model is able to describe temperature, pressure, and concentration dependent permeation as wellreal fluid effects in vapor and gas separation with hydrocarbon selective rubbery polymeric membranes. The permeation through the membrane is described by a separate treatment of sorption and diffusion within the membrane. The chemical engineering thermodynamics is used to describe the equilibrium sorption of vapors and gases in rubbery membranes with equation of state models for polymeric systems. Also a new modification of the UNIFAC model is proposed for this purpose. Various thermodynamic models are extensively compared in order to verify the models' ability to predict and correlate experimental vapor-liquid equilibrium data. The penetrant transport through the selective layer of the membrane is described with the generalized Maxwell-Stefan equations, which are able to account for thebulk flux contribution as well as the diffusive coupling effect. A method is described to compute and correlate binary penetrant¿membrane diffusion coefficients from the experimental permeability coefficients at different temperatures and pressures. A fluid flow model for spiral-wound modules is derived from the conservation equation of mass, momentum, and energy. The conservation equations are presented in a discretized form by using the control volume approach. A combination of the permeation model and the fluid flow model yields the desired rigorous model for vapor membrane separation. The model is implemented into an inhouse process simulator and so vapor membrane separation may be evaluated as an integralpart of a process flowsheet.

A priori parameterisation of the CERES soil-crop models and tests against several European data sets

Mechanistic soil-crop models have become indispensable tools to investigate the effect of management practices on the productivity or environmental impacts of arable crops. Ideally these models may claim to be universally applicable because they simulate the major processes governing the fate of inputs such as fertiliser nitrogen or pesticides. However, because they deal with complex systems and uncertain phenomena, site-specific calibration is usually a prerequisite to ensure their predictions are realistic. This statement implies that some experimental knowledge on the system to be simulated should be available prior to any modelling attempt, and raises a tremendous limitation to practical applications of models. Because the demand for more general simulation results is high, modellers have nevertheless taken the bold step of extrapolating a model tested within a limited sample of real conditions to a much larger domain. While methodological questions are often disregarded in this extrapolation process, they are specifically addressed in this paper, and in particular the issue of models a priori parameterisation. We thus implemented and tested a standard procedure to parameterize the soil components of a modified version of the CERES models. The procedure converts routinely-available soil properties into functional characteristics by means of pedo-transfer functions. The resulting predictions of soil water and nitrogen dynamics, as well as crop biomass, nitrogen content and leaf area index were compared to observations from trials conducted in five locations across Europe (southern Italy, northern Spain, northern France and northern Germany). In three cases, the model’s performance was judged acceptable when compared to experimental errors on the measurements, based on a test of the model’s root mean squared error (RMSE). Significant deviations between observations and model outputs were however noted in all sites, and could be ascribed to various model routines. In decreasing importance, these were: water balance, the turnover of soil organic matter, and crop N uptake. A better match to field observations could therefore be achieved by visually adjusting related parameters, such as field-capacity water content or the size of soil microbial biomass. As a result, model predictions fell within the measurement errors in all sites for most variables, and the model’s RMSE was within the range of published values for similar tests. We conclude that the proposed a priori method yields acceptable simulations with only a 50% probability, a figure which may be greatly increased through a posteriori calibration. Modellers should thus exercise caution when extrapolating their models to a large sample of pedo-climatic conditions for which they have only limited information.

Sensitivity analysis, dominant factors, and robustness of the ECETOC TRA v3, Stoffenmanager 4.5, and ART 1.5 occupational exposure models

Occupational exposure modeling is widely used in the context of the E.U. regulation on the registration, evaluation, authorization, and restriction of chemicals (REACH). First tier tools, such as European Centre for Ecotoxicology and TOxicology of Chemicals (ECETOC) targeted risk assessment (TRA) or Stoffenmanager, are used to screen a wide range of substances. Those of concern are investigated further using second tier tools, e.g., Advanced REACH Tool (ART). Local sensitivity analysis (SA) methods are used here to determine dominant factors for three models commonly used within the REACH framework: ECETOC TRA v3, Stoffenmanager 4.5, and ART 1.5. Based on the results of the SA, the robustness of the models is assessed. For ECETOC, the process category (PROC) is the most important factor. A failure to identify the correct PROC has severe consequences for the exposure estimate. Stoffenmanager is the most balanced model and decision making uncertainties in one modifying factor are less severe in Stoffenmanager. ART requires a careful evaluation of the decisions in the source compartment since it constitutes ∼75% of the total exposure range, which corresponds to an exposure estimate of 20-22 orders of magnitude. Our results indicate that there is a trade off between accuracy and precision of the models. Previous studies suggested that ART may lead to more accurate results in well-documented exposure situations. However, the choice of the adequate model should ultimately be determined by the quality of the available exposure data: if the practitioner is uncertain concerning two or more decisions in the entry parameters, Stoffenmanager may be more robust than ART.

Adaptations of Natural Killer Cells to Self-MHC Class I.

Natural Killer (NK) cells use germ line encoded receptors to detect diseased host cells. Despite the invariant recognition structures, NK cells have a significant ability to adapt to their surroundings, such as the presence or absence of MHC class I molecules. It has been assumed that this adaptation occurs during NK cell development, but recent findings show that mature NK cells can also adapt to the presence or absence of MHC class I molecules. Here, we summarize how NK cells adjust to changes in the expression of MHC class I molecules. We propose an extension of existing models, in which MHC class I recognition during NK cell development sequentially instructs and maintains NK cell function. The elucidation of the molecular basis of the two effects may identify ways to improve the fitness of NK cells and to prevent the loss of NK cell function due to persistent alterations in their environment.

The role of causal links in performance measurement models

Abstract Purpose: Several well-known managerial accounting performance measurement models rely on causal assumptions. Whilst users of the models express satisfaction and link them with improved organizational performance, academic research, of the realworld applications, shows few reliable statistical associations. This paper provides a discussion on the"problematic" of causality in a performance measurement setting. Design/methodology/approach: This is a conceptual study based on an analysis and synthesis of the literature from managerial accounting, organizational theory, strategic management and social scientific causal modelling. Findings: The analysis indicates that dynamic, complex and uncertain environments may challenge any reliance upon valid causal models. Due to cognitive limitations and judgmental biases, managers may fail to trace correct cause-and-effect understanding of the value creation in their organizations. However, even lacking this validity, causal models can support strategic learning and perform as organizational guides if they are able to mobilize managerial action. Research limitations/implications: Future research should highlight the characteristics necessary for elaboration of convincing and appealing causal models and the social process of their construction. Practical implications: Managers of organizations using causal models should be clear on the purposes of their particular models and their limitations. In particular, difficulties are observed in specifying detailed cause and effect relations and their potential for communicating and directing attention. They should therefore construct their models to suit the particular purpose envisaged. Originality/value: This paper provides an interdisciplinary and holistic view on the issue of causality in managerial accounting models.

The Value System of Consumer Board Packaging

Olemassa olevien teollisuuden rakenteiden ja arvoketjujen muutos on usein onnistuneiden liiketoimintainnovaatioiden takana. Yritysten tulisikin olla tietoisia rakenteista, jotka määrittelevät arvon jakaantumista niiden arvoketjuissa. Tämän työn tavoitteena oli tutkia ja arvioida kartongin pakkausketjujen rakenteita kartongintuottajalta aina kauppiaalle asti. Työn kuluessa yritysketjujen arviointia varten oli kehitettävä uudenlainen analysointityökalu. Työssä käsitellyt kartonkipakkausketjut olivat nestekartonkipakkaaminen, elintarvikepakkaaminen, lääkepakkaaminen sekä graafisten kartonkien ketju. Jokaista edellä mainituista ketjuista arvioitiin käyttämällä kehitettyä analysointityökalua. Työn merkittävin tulos on kehitetty työkalu, jolla pakkausketjuja sekä myös muita yritysketjuja on mahdollista analysoida. Kehitettyä työkalua käyttämällä oli mahdollista tehdä johtopäätöksiä vertikaalin integraation mahdollisuudesta sekä pakkausketjujen suotuisuudesta uusille bisnesmalleille. Sekä analysointityökalua että saatuja johtopäätöksiä voidaan käyttää hyväksi, kun kartongintuottaja suunnittelee tulevaisuuden toimenpiteitä.

Falsification and corroboration of conceptual hydrological models using geophysical data

Geophysical data may provide crucial information about hydrological properties, states, and processes that are difficult to obtain by other means. Large data sets can be acquired over widely different scales in a minimally invasive manner and at comparatively low costs, but their effective use in hydrology makes it necessary to understand the fidelity of geophysical models, the assumptions made in their construction, and the links between geophysical and hydrological properties. Geophysics has been applied for groundwater prospecting for almost a century, but it is only in the last 20 years that it is regularly used together with classical hydrological data to build predictive hydrological models. A largely unexplored venue for future work is to use geophysical data to falsify or rank competing conceptual hydrological models. A promising cornerstone for such a model selection strategy is the Bayes factor, but it can only be calculated reliably when considering the main sources of uncertainty throughout the hydrogeophysical parameter estimation process. Most classical geophysical imaging tools tend to favor models with smoothly varying property fields that are at odds with most conceptual hydrological models of interest. It is thus necessary to account for this bias or use alternative approaches in which proposed conceptual models are honored at all steps in the model building process.

Development of Customer Satisfaction Models for Electronics Engineering Company

Diplomityön tarkoituksena oli luoda ja kehittää kaksi asiakastyytyväisyysmallia asiakastyytyväisyyden mittaamisen aloittamiseksi ja toteuttamiseksi kohdeyrityksessä. Työ pohjautuu nykyisten tyytyväisyysprosessien analysointiin sekä työn teoriaosaan, joka käsittelee yksityiskohtaisesti niitä asioita, joita asiakastyytyväisyyden mittaamisessa ja prosessissa tulisi huomioida. Työssä tehdyn mallien tarkoituksen on auttaa kohdeyritystä hyödyntämään asiakastyytyväisyysmittauksen tuloksia paremmin liiketoiminnassa, sekä asiakkaiden keskuudessa. Työn yhtenä tavoitteena oli myös sopivan mittaustyökalun löytäminen ja suositteleminen kohdeyritykselle.Teorian ja analysoinnin pohjalta luotiin molemmat asiakastyytyväisyysmallit vastamaan kohdeyksiköiden tarpeita. Kun ulkoiset seikat, kuten mittaustavat, mittausinstrumentit, kyselylomakkeet ja vastaajaryhmät oli määritelty, keskityttiin tulosten analysointiin ja hyödyntämiseen, mikä korostui asiakassuuntautuneessa organisaatiossa. Työssä pohdittiin myös yhtenäisen asiakastyytyväisyysprosessin merkitystä ja etuja kohdeyrityksessä.

Impact of model complexity on cross-temporal transferability in Maxent species distribution models: An assessment using paleobotanical data

Maximum entropy modeling (Maxent) is a widely used algorithm for predicting species distributions across space and time. Properly assessing the uncertainty in such predictions is non-trivial and requires validation with independent datasets. Notably, model complexity (number of model parameters) remains a major concern in relation to overfitting and, hence, transferability of Maxent models. An emerging approach is to validate the cross-temporal transferability of model predictions using paleoecological data. In this study, we assess the effect of model complexity on the performance of Maxent projections across time using two European plant species (Alnus giutinosa (L.) Gaertn. and Corylus avellana L) with an extensive late Quaternary fossil record in Spain as a study case. We fit 110 models with different levels of complexity under present time and tested model performance using AUC (area under the receiver operating characteristic curve) and AlCc (corrected Akaike Information Criterion) through the standard procedure of randomly partitioning current occurrence data. We then compared these results to an independent validation by projecting the models to mid-Holocene (6000 years before present) climatic conditions in Spain to assess their ability to predict fossil pollen presence-absence and abundance. We find that calibrating Maxent models with default settings result in the generation of overly complex models. While model performance increased with model complexity when predicting current distributions, it was higher with intermediate complexity when predicting mid-Holocene distributions. Hence, models of intermediate complexity resulted in the best trade-off to predict species distributions across time. Reliable temporal model transferability is especially relevant for forecasting species distributions under future climate change. Consequently, species-specific model tuning should be used to find the best modeling settings to control for complexity, notably with paleoecological data to independently validate model projections. For cross-temporal projections of species distributions for which paleoecological data is not available, models of intermediate complexity should be selected.

Business models enhancing the diffusion of mobile Internet in emerging markets

Tämän tutkimuksen päätavoitteena oli selvittää, millaiset liiketoimintamallit soveltuvat mobiilin internet-liiketoiminnan harjoittamiseen kehittyvillä markkinoilla. Tavoitteena oli myös selvittää tekijöitä, jotka vaikuttavat mobiilin internetin diffuusioon. Tutkimus tehtiin käyttäen sekä kvantitatiivista että kvalitatiivista tutkimusmenetelmää. Klusterianalyysin avulla 40 Euroopan maasta muodostettiin sisäisesti homogeenisiä maaklustereita. Näiden klustereiden avulla oli mahdollista suunnitella erityyppisille markkinoille soveltuvat liiketoimintamallit. Haastatteluissa selvitettiin asiantuntijoiden näkemyksiä tekijöistä, jotka vaikuttavat mobiilin internetin diffuusioon kehittyvillä markkinoilla. Tutkimuksessa saatiin selville, että tärkeimmät liiketoimintamallin elementit kehittyvillä markkinoilla ovat hinnoittelu, arvotarjooma ja arvoverkko. Puutteellisen kiinteän verkon todettiin olevan yksi tärkeimmistä mobiilin internetin diffuusiota edistävistä tekijöistä kehittyvillä markkinoilla.

Molecular mechanism of a green-shifted, pH-dependent red fluorescent protein mKate variant.

Fluorescent proteins that can switch between distinct colors have contributed significantly to modern biomedical imaging technologies and molecular cell biology. Here we report the identification and biochemical analysis of a green-shifted red fluorescent protein variant GmKate, produced by the introduction of two mutations into mKate. Although the mutations decrease the overall brightness of the protein, GmKate is subject to pH-dependent, reversible green-to-red color conversion. At physiological pH, GmKate absorbs blue light (445 nm) and emits green fluorescence (525 nm). At pH above 9.0, GmKate absorbs 598 nm light and emits 646 nm, far-red fluorescence, similar to its sequence homolog mNeptune. Based on optical spectra and crystal structures of GmKate in its green and red states, the reversible color transition is attributed to the different protonation states of the cis-chromophore, an interpretation that was confirmed by quantum chemical calculations. Crystal structures reveal potential hydrogen bond networks around the chromophore that may facilitate the protonation switch, and indicate a molecular basis for the unusual bathochromic shift observed at high pH. This study provides mechanistic insights into the color tuning of mKate variants, which may aid the development of green-to-red color-convertible fluorescent sensors, and suggests GmKate as a prototype of genetically encoded pH sensors for biological studies.

Generative models of the human connectome.

The human connectome represents a network map of the brain's wiring diagram and the pattern into which its connections are organized is thought to play an important role in cognitive function. The generative rules that shape the topology of the human connectome remain incompletely understood. Earlier work in model organisms has suggested that wiring rules based on geometric relationships (distance) can account for many but likely not all topological features. Here we systematically explore a family of generative models of the human connectome that yield synthetic networks designed according to different wiring rules combining geometric and a broad range of topological factors. We find that a combination of geometric constraints with a homophilic attachment mechanism can create synthetic networks that closely match many topological characteristics of individual human connectomes, including features that were not included in the optimization of the generative model itself. We use these models to investigate a lifespan dataset and show that, with age, the model parameters undergo progressive changes, suggesting a rebalancing of the generative factors underlying the connectome across the lifespan.

Structure-Based, Rational Design of T Cell Receptors.

Adoptive cell transfer using engineered T cells is emerging as a promising treatment for metastatic melanoma. Such an approach allows one to introduce T cell receptor (TCR) modifications that, while maintaining the specificity for the targeted antigen, can enhance the binding and kinetic parameters for the interaction with peptides (p) bound to major histocompatibility complexes (MHC). Using the well-characterized 2C TCR/SIYR/H-2K(b) structure as a model system, we demonstrated that a binding free energy decomposition based on the MM-GBSA approach provides a detailed and reliable description of the TCR/pMHC interactions at the structural and thermodynamic levels. Starting from this result, we developed a new structure-based approach, to rationally design new TCR sequences, and applied it to the BC1 TCR targeting the HLA-A2 restricted NY-ESO-1157-165 cancer-testis epitope. Fifty-four percent of the designed sequence replacements exhibited improved pMHC binding as compared to the native TCR, with up to 150-fold increase in affinity, while preserving specificity. Genetically engineered CD8(+) T cells expressing these modified TCRs showed an improved functional activity compared to those expressing BC1 TCR. We measured maximum levels of activities for TCRs within the upper limit of natural affinity, K D = ∼1 - 5 μM. Beyond the affinity threshold at K D < 1 μM we observed an attenuation in cellular function, in line with the "half-life" model of T cell activation. Our computer-aided protein-engineering approach requires the 3D-structure of the TCR-pMHC complex of interest, which can be obtained from X-ray crystallography. We have also developed a homology modeling-based approach, TCRep 3D, to obtain accurate structural models of any TCR-pMHC complexes when experimental data is not available. Since the accuracy of the models depends on the prediction of the TCR orientation over pMHC, we have complemented the approach with a simplified rigid method to predict this orientation and successfully assessed it using all non-redundant TCR-pMHC crystal structures available. These methods potentially extend the use of our TCR engineering method to entire TCR repertoires for which no X-ray structure is available. We have also performed a steered molecular dynamics study of the unbinding of the TCR-pMHC complex to get a better understanding of how TCRs interact with pMHCs. This entire rational TCR design pipeline is now being used to produce rationally optimized TCRs for adoptive cell therapies of stage IV melanoma.

Asymptotic analysis of stock price densities and implied volatilities in mixed stochastic models

In this paper, we obtain sharp asymptotic formulas with error estimates for the Mellin con- volution of functions de ned on (0;1), and use these formulas to characterize the asymptotic behavior of marginal distribution densities of stock price processes in mixed stochastic models. Special examples of mixed models are jump-di usion models and stochastic volatility models with jumps. We apply our general results to the Heston model with double exponential jumps, and make a detailed analysis of the asymptotic behavior of the stock price density, the call option pricing function, and the implied volatility in this model. We also obtain similar results for the Heston model with jumps distributed according to the NIG law.