Large deviations of Rouse polymer chain: first passage problem

The purpose of this paper is to investigate several analytical methods of solving first passage (FP) problem for the Rouse model, a simplest model of a polymer chain. We show that this problem has to be treated as a multi-dimensional Kramers' problem, which presents rich and unexpected behavior. We first perform direct and forward-flux sampling (FFS) simulations, and measure the mean first-passage time $\tau(z)$ for the free end to reach a certain distance $z$ away from the origin. The results show that the mean FP time is getting faster if the Rouse chain is represented by more beads. Two scaling regimes of $\tau(z)$ are observed, with transition between them varying as a function of chain length. We use these simulations results to test two theoretical approaches. One is a well known asymptotic theory valid in the limit of zero temperature. We show that this limit corresponds to fully extended chain when each chain segment is stretched, which is not particularly realistic. A new theory based on the well known Freidlin-Wentzell theory is proposed, where dynamics is projected onto the minimal action path. The new theory predicts both scaling regimes correctly, but fails to get the correct numerical prefactor in the first regime. Combining our theory with the FFS simulations lead us to a simple analytical expression valid for all extensions and chain lengths. One of the applications of polymer FP problem occurs in the context of branched polymer rheology. In this paper, we consider the arm-retraction mechanism in the tube model, which maps exactly on the model we have solved. The results are compared to the Milner-McLeish theory without constraint release, which is found to overestimate FP time by a factor of 10 or more.

Do jumps matter for volatility forecasting? Evidence from energy markets

This paper characterizes the dynamics of jumps and analyzes their importance for volatility forecasting. Using high-frequency data on four prominent energy markets, we perform a model-free decomposition of realized variance into its continuous and discontinuous components. We find strong evidence of jumps in energy markets between 2007 and 2012. We then investigate the importance of jumps for volatility forecasting. To this end, we estimate and analyze the predictive ability of several Heterogenous Autoregressive (HAR) models that explicitly capture the dynamics of jumps. Conducting extensive in-sample and out-of-sample analyses, we establish that explicitly modeling jumps does not significantly improve forecast accuracy. Our results are broadly consistent across our four energy markets, forecasting horizons, and loss functions

An Ensemble Kalman Smoother for Nonlinear Dynamics

It is for mally proved that the general smoother for nonlinear dynamics can be for mulated as a sequential method, that is, obser vations can be assimilated sequentially during a for ward integration. The general filter can be derived from the smoother and it is shown that the general smoother and filter solutions at the final time become identical, as is expected from linear theor y. Then, a new smoother algorithm based on ensemble statistics is presented and examined in an example with the Lorenz equations. The new smoother can be computed as a sequential algorithm using only for ward-in-time model integrations. It bears a strong resemblance with the ensemble Kalman filter . The difference is that ever y time a new dataset is available during the for ward integration, an analysis is computed for all previous times up to this time. Thus, the first guess for the smoother is the ensemble Kalman filter solution, and the smoother estimate provides an improvement of this, as one would expect a smoother to do. The method is demonstrated in this paper in an intercomparison with the ensemble Kalman filter and the ensemble smoother introduced by van Leeuwen and Evensen, and it is shown to be superior in an application with the Lorenz equations. Finally , a discussion is given regarding the properties of the analysis schemes when strongly non-Gaussian distributions are used. It is shown that in these cases more sophisticated analysis schemes based on Bayesian statistics must be used.

Reliable but not home free? What framing effects mean for moral intuitions

Various studies show moral intuitions to be susceptible to framing effects. Many have argued that this susceptibility is a sign of unreliability and that this poses a methodological challenge for moral philosophy. Recently, doubt has been cast on this idea. It has been argued that extant evidence of framing effects does not show that moral intuitions have a unreliability problem. I argue that, even if the extant evidence suggests that moral intuitions are fairly stable with respect to what intuitions we have, the effect of framing on the strength of those intuitions still needs to be taken into account. I argue that this by itself poses a methodological challenge for moral philosophy.

Is behavioral ecology important for understanding and predicting population dynamics?

Population ecology is a discipline that studies changes in the number and composition (age, sex) of the individuals that form a population. Many of the mechanisms that generate these changes are associated with individual behavior, for example how individuals defend their territories, find mates or disperse. Therefore, it is important to model population dynamics considering the potential influence of behavior on the modeled dynamics. This study illustrates the diversity of behaviors that influence population dynamics describing several methods that allow integrating behavior into population models and range from simpler models that only consider the number of individuals to complex individual-based models that capture great levels of detail. A series of examples shows the importance of explicitly considering behavior in population modeling to avoid reaching erroneous conclusions. This integration is particularly relevant for conservation, as incorrect predictions regarding the dynamics of populations of conservation interest can lead to inadequate assessment and management. Improved predictions can favor effective protection of species and better use of the limited financial and human conservation resources.

Using Distributed Temperature Sensing to monitor field scale dynamics of ground surface temperature and related substrate heat flux

We present one of the first studies of the use of Distributed Temperature Sensing (DTS) along fibre-optic cables to purposely monitor spatial and temporal variations in ground surface temperature (GST) and soil temperature, and provide an estimate of the heat flux at the base of the canopy layer and in the soil. Our field site was at a groundwater-fed wet meadow in the Netherlands covered by a canopy layer (between 0-0.5 m thickness) consisting of grass and sedges. At this site, we ran a single cable across the surface in parallel 40 m sections spaced by 2 m, to create a 40×40 m monitoring field for GST. We also buried a short length (≈10 m) of cable to depth of 0.1±0.02 m to measure soil temperature. We monitored the temperature along the entire cable continuously over a two-day period and captured the diurnal course of GST, and how it was affected by rainfall and canopy structure. The diurnal GST range, as observed by the DTS system, varied between 20.94 and 35.08◦C; precipitation events acted to suppress the range of GST. The spatial distribution of GST correlated with canopy vegetation height during both day and night. Using estimates of thermal inertia, combined with a harmonic analysis of GST and soil temperature, substrate and soil-heat fluxes were determined. Our observations demonstrate how the use of DTS shows great promise in better characterising area-average substrate/soil heat flux, their spatiotemporal variability, and how this variability is affected by canopy structure. The DTS system is able to provide a much richer data set than could be obtained from point temperature sensors. Furthermore, substrate heat fluxes derived from GST measurements may be able to provide improved closure of the land surface energy balance in micrometeorological field studies. This will enhance our understanding of how hydrometeorological processes interact with near-surface heat fluxes.

Impact of atmospheric forcing data on simulations of the Laptev Sea polynya dynamics using the sea-ice ocean model FESOM

The polynyas of the Laptev Sea are regions of particular interest due to the strong formation of Arctic sea-ice. In order to simulate the polynya dynamics and to quantify ice production, we apply the Finite Element Sea-Ice Ocean Model FESOM. In previous simulations FESOM has been forced with daily atmospheric NCEP (National Centers for Environmental Prediction) 1. For the periods 1 April to 9 May 2008 and 1 January to 8 February 2009 we examine the impact of different forcing data: daily and 6-hourly NCEP reanalyses 1 (1.875° x 1.875°), 6-hourly NCEP reanalyses 2 (1.875° x 1.875°), 6-hourly analyses from the GME (Global Model of the German Weather Service) (0.5° x 0.5°) and high-resolution hourly COSMO (Consortium for Small-Scale Modeling) data (5 km x 5 km). In all FESOM simulations, except for those with 6-hourly and daily NCEP 1 data, the openings and closings of polynyas are simulated in principle agreement with satellite products. Over the fast-ice area the wind fields of all atmospheric data are similar and close to in situ measurements. Over the polynya areas, however, there are strong differences between the forcing data with respect to air temperature and turbulent heat flux. These differences have a strong impact on sea-ice production rates. Depending on the forcing fields polynya ice production ranges from 1.4 km3 to 7.8 km3 during 1 April to 9 May 2011 and from 25.7 km3 to 66.2 km3 during 1 January to 8 February 2009. Therefore, atmospheric forcing data with high spatial and temporal resolution which account for the presence of the polynyas are needed to reduce the uncertainty in quantifying ice production in polynyas.

Entrepreneurial dynamics and higher education institutions in the post-communist world

This study draws on the institutional and regional entrepreneurship literature to develop a conceptual framework that analyses the impact of higher education institutions on entrepreneurial dynamics. It is used to examine the cities of the Commonwealth of Independent States (CIS) during the period 1995–2008. Extending the multi-pillar institutional concept, it is found that higher education institutions play a prominent role in fostering entrepreneurial dynamics in CIS cities through multiple channels, including human capital development, cultivating a positive attitude towards entrepreneurship, affecting the perceptions of the knowledge and skills needed to start up a successful business, and knowledge spillovers.

Spatio-temporal variability of polynya dynamics and ice production in the Laptev Sea between the winters of 1979/80 and 2007/08

Polynyas in the Laptev Sea are examined with respect to recurrence and interannual wintertime ice production.We use a polynya classification method based on passive microwave satellite data to derive daily polynya area from long-term sea-ice concentrations. This provides insight into the spatial and temporal variability of open-water and thin-ice regions on the Laptev Sea Shelf. Using thermal infrared satellite data to derive an empirical thin-ice distribution within the thickness range from 0 to 20 cm, we calculate daily average surface heat loss and the resulting wintertime ice formation within the Laptev Sea polynyas between 1979 and 2008 using reanalysis data supplied by the National Centers for Environmental Prediction, USA, as atmospheric forcing. Results indicate that previous studies significantly overestimate the contribution of polynyas to the ice production in the Laptev Sea. Average wintertime ice production in polynyas amounts to approximately 55 km39 27% and is mostly determined by the polynya area, wind speed and associated large-scale circulation patterns. No trend in ice production could be detected in the period from 1979/80 to 2007/08.

Rhodosporidium toruloides cultivated in NaCl-enriched glucose-based media: adaptation dynamics and lipid production

In the present report and for the first time in the international literature, the impact of the addition of NaCl upon growth and lipid production on the oleaginous yeast Rhodosporidium toruloides was studied. Moreover, equally for first time, lipid production by R. toruloides was performed under non-aseptic conditions. Therefore, the potentiality of R. toruloides DSM 4444 to produce lipid in media containing several initial concentrations of NaCl with glucose employed as carbon source was studied. Preliminary batch-flask trials with increasing amounts of NaCl revealed the tolerance of the strain against NaCl content up to 6.0% (w/v). However, 4.0% (w/v) of NaCl stimulated lipid accumulation for this strain, by enhancing lipid production up to 71.3% (w/w) per dry cell weight. The same amount of NaCl was employed in pasteurized batch-flask cultures in order to investigate the role of the salt as bacterial inhibiting agent. The combination of NaCl and high glucose concentrations was found to satisfactorily suppress bacterial contamination of R. toruloides cultures under these conditions. Batch-bioreactor trials of the yeast in the same media with high glucose content (up to 150 g/L) resulted in satisfactory substrate assimilation, with almost linear kinetic profile for lipid production, regardless of the initial glucose concentration imposed. Finally, fed-batch bioreactor cultures led to the production of 37.2 g/L of biomass, accompanied by 64.5% (w/w) of lipid yield. Lipid yield per unit of glucose consumed received the very satisfactory value of 0.21 g/g, a value amongst the highest ones in the literature. The yeast lipid produced contained mainly oleic acid and to lesser extent palmitic and stearic acids, thus constituting a perfect starting material for “second generation” biodiesel

SHIMMER (1.0): a novel mathematical model for microbial and biogeochemical dynamics in glacier forefield ecosystems

SHIMMER (Soil biogeocHemIcal Model for Microbial Ecosystem Response) is a new numerical modelling framework designed to simulate microbial dynamics and biogeochemical cycling during initial ecosystem development in glacier forefield soils. However, it is also transferable to other extreme ecosystem types (such as desert soils or the surface of glaciers). The rationale for model development arises from decades of empirical observations in glacier forefields, and enables a quantitative and process focussed approach. Here, we provide a detailed description of SHIMMER, test its performance in two case study forefields: the Damma Glacier (Switzerland) and the Athabasca Glacier (Canada) and analyse sensitivity to identify the most sensitive and unconstrained model parameters. Results show that the accumulation of microbial biomass is highly dependent on variation in microbial growth and death rate constants, Q10 values, the active fraction of microbial biomass and the reactivity of organic matter. The model correctly predicts the rapid accumulation of microbial biomass observed during the initial stages of succession in the forefields of both the case study systems. Primary production is responsible for the initial build-up of labile substrate that subsequently supports heterotrophic growth. However, allochthonous contributions of organic matter, and nitrogen fixation, are important in sustaining this productivity. The development and application of SHIMMER also highlights aspects of these systems that require further empirical research: quantifying nutrient budgets and biogeochemical rates, exploring seasonality and microbial growth and cell death. This will lead to increased understanding of how glacier forefields contribute to global biogeochemical cycling and climate under future ice retreat.

Progress report from the strategic sanctuary for the destruction of free will

Progress Report from the Strategic Sanctuary for the Destruction of Free Will presents a new work combining film, music and installation that juxtaposes the setting of the institution with the aesthetics of psychedelia.Progress Report from the Strategic Sanctuary for the Destruction of Free Will is an installation, film and sound work that takes over the gallery. Using plain white card, it distorts the structure of the gallery’s architecture, producing a paranoid shrunken space. Inside this space, performers in cardboard costumes re-enact abstracted, broken gestures drawn from video documentation of acid trips, psychedelic dancing, rehab sessions and radical psychotherapy workshops. Progress Report from the Strategic Sanctuary for the Destruction of Free Will has been formed through Pil and Galia Kollectiv’s research into the anti-psychiatry movement, their interests in counter cultural movements and their studies around biopolitics and the proliferation of societal medication. In 1958, having had a life changing experience with LSD, former alcoholic Charles Dederich founded Synanon, a drug rehabilitation program based on residential care and an aggressive form of group therapy called ‘The Game’. The organisation gradually evolved into a controversial alternative community, described in a critical pamphlet as creating Strategic Sanctuaries for the Destruction of Free Will, “a subversive program for mixing delinquents and lefties”. In 1984, anti-psychiatrist R. D. Laing described tranquillizers as chemical straight jackets. With our growing understanding of the plasticity of the brain and the potential to shape it, the tension between liberation and control in the struggle over the mind continues to define our relationship to labour, culture and production. Interrogating these ideas, the exhibition poses the question of whether a collective body can overcome the solipsism of the incommunicable experience of the individual mind.

Long-lived excited-state dynamics of i-motif structures probed by time-resolved infrared spectroscopy

UV-generated excited states of cytosine (C) nucleobases are precursors to mutagenic photoproduct formation. The i-motif formed from C-rich sequences is known to exhibit high yields of long-lived excited states following UV absorption. Here the excited states of several i-motif structures have been characterized following 267 nm laser excitation using time-resolved infrared spectroscopy (TRIR). All structures possess a long-lived excited state of ~300 ps and notably in some cases decays greater than 1 ns are observed. These unusually long-lived lifetimes are attributed to the interdigitated DNA structure which prevents direct base stacking overlap.

Interactional dynamics in on-line and face-to-face peer-tutoring sessions for second language writers

This paper reports the results of a study comparing the interactional dynamics of face-to-face and on-line peer-tutoring in writing by university students in Hong Kong. Transcripts of face-to-face tutoring sessions, as well as logs of on-line sessions conducted by the same peer-tutors, were coded for speech functions using a system based on Halliday's functional-semantic view of dialogue. Results show considerable differences between the interactional dynamics in on-line and face-to-face tutoring sessions. In particular, face-to-face interactions involved more hierarchal encounters in which tutors took control of the discourse, whereas on-line interactions were more egalitarian, with clients controlling the discourse more. Differences were also found in the topics participants chose to focus on in the two modes, with issues of grammar, vocabulary, and style taking precedence in face-to-face sessions and more “global” writing concerns like content and process being discussed more in on-line sessions.