Situational adaptiveness of control orientation mediates relation between fixed-world view and youth well-being in three cultures

When proposing primary control (changing the world to fit self)/secondary control (changing self to fit the world) theory, Weisz et al. (1984) argued for the importance of the “serenity to accept the things I cannot change, the courage to change the things I can” (p. 967), and the wisdom to choose the right control strategy that fits the context. Although the dual processes of control theory generated hundreds of empirical studies, most of them focused on the dichotomy of PC and SC, with none of these tapped into the critical concept: individuals’ ability to know when to use what. This project addressed this issue by using scenario questions to study the impact of situationally adaptive control strategies on youth well-being. To understand the antecedents of youths’ preference for PC or SC, we also connected PCSC theory with Dweck’s implicit theory about the changeability of the world. We hypothesized that youths’ belief about the world’s changeability impacts how difficult it was for them to choose situationally adaptive control orientation, which then impacts their well-being. This study included adolescents and emerging adults between the ages of 18 and 28 years (Mean = 20.87 years) from the US (n = 98), China (n = 100), and Switzerland (n = 103). Participants answered a questionnaire including a measure of implicit theories about the fixedness of the external world, a scenario-based measure of control orientation, and several measures of well-being. Preliminary analyses of the scenario-based control orientation measures showed striking cross-cultural similarity of preferred control responses: while for three of the six scenarios primary control was the predominately chosen control response in all cultures, for the other three scenarios secondary control was the predominately chosen response. This suggested that youths across cultures are aware that some situations call for primary control, while others demand secondary control. We considered the control strategy winning the majority of the votes to be the strategy that is situationally adaptive. The results of a multi-group structural equation mediation model with the extent of belief in a fixed world as independent variable, the difficulties of carrying out the respective adaptive versus non-adaptive control responses as two mediating variables and the latent well-being variable as dependent variable showed a cross-culturally similar pattern of effects: a belief in a fixed world was significantly related to higher difficulties in carrying out the normative as well as the non-normative control response, but only the difficulty of carrying out the normative control response (be it primary control in situations where primary control is normative or secondary control in situations where secondary control is normative) was significantly related to a lower reported well-being (while the difficulty of carrying out the non-normative response was unrelated to well-being). While previous research focused on cross-cultural differences on the choice of PC or SC, this study shed light on the universal necessity of applying the right kind of control to fit the situation.

Atlantic hurricanes and associated insurance loss potentials in future climate scenarios: limitations of high-resolution AGCM simulations

Potential future changes in tropical cyclone (TC) characteristics are among the more serious regional threats of global climate change. Therefore, a better understanding of how anthropogenic climate change may affect TCs and how these changes translate in socio-economic impacts is required. Here, we apply a TC detection and tracking method that was developed for ERA-40 data to time-slice experiments of two atmospheric general circulation models, namely the fifth version of the European Centre model of Hamburg model (MPI, Hamburg, Germany, T213) and the Japan Meteorological Agency/ Meteorological research Institute model (MRI, Tsukuba city, Japan, TL959). For each model, two climate simulations are available: a control simulation for present-day conditions to evaluate the model against observations, and a scenario simulation to assess future changes. The evaluation of the control simulations shows that the number of intense storms is underestimated due to the model resolution. To overcome this deficiency, simulated cyclone intensities are scaled to the best track data leading to a better representation of the TC intensities. Both models project an increased number of major hurricanes and modified trajectories in their scenario simulations. These changes have an effect on the projected loss potentials. However, these state-of-the-art models still yield contradicting results, and therefore they are not yet suitable to provide robust estimates of losses due to uncertainties in simulated hurricane intensity, location and frequency.

Climate variability of the mid- and high-latitudes of the Southern Hemisphere in ensemble simulations from 1500 to 2000 AD

To increase the sparse knowledge of long-term Southern Hemisphere (SH) climate variability, we assess an ensemble of 4 transient simulations over the last 500 yr performed with a state-of-the-art atmosphere ocean general circulation model. The model is forced with reconstructions of solar irradiance, greenhouse gas (GHG) and volcanic aerosol concentrations. A 1990 control simulation shows that the model is able to represent the Southern Annular Mode (SAM), and to some extent the South Pacific Dipole (SPD) and the Zonal Wave 3 (ZW3). During the past 500 yr we find that SPD and ZW3 variability remain stable, whereas SAM shows a significant shift towards its positive state during the 20th century. Regional temperatures over South America are strongly influenced by changing both GHG concentrations and volcanic eruptions, whereas precipitation shows no significant response to the varying external forcing. For temperature this stands in contrast to proxy records, suggesting that SH climate is dominated by internal variability rather than external forcing. The underlying dynamics of the temperature changes generally point to a combination of several modes, thus, hampering the possibilities of regional reconstructing the modes from proxy records. The linear imprint of the external forcing is as expected, i.e. a warming for increase in the combined solar and GHG forcing and a cooling after volcanic eruptions. Dynamically, only the increase in SAM with increased combined forcing is simulated.

Reconstructing the subsurface ocean decadal variability using surface nudging in a perfect model framework

Initialising the ocean internal variability for decadal predictability studies is a new area of research and a variety of ad hoc methods are currently proposed. In this study, we explore how nudging with sea surface temperature (SST) and salinity (SSS) can reconstruct the threedimensional variability of the ocean in a perfect model framework. This approach builds on the hypothesis that oceanic processes themselves will transport the surface information into the ocean interior as seen in ocean-only simulations. Five nudged simulations are designed to reconstruct a 150 years ‘‘target’’ simulation, defined as a portion of a long control simulation. The nudged simulations differ by the variables restored to, SST or SST + SSS, and by the area where the nudging is applied. The strength of the heat flux feedback is diagnosed from observations and the restoring coefficients for SSS use the same time-scale. We observed that this choice prevents spurious convection at high latitudes and near sea-ice border when nudging both SST and SSS. In the tropics, nudging the SST is enough to reconstruct the tropical atmosphere circulation and the associated dynamical and thermodynamical impacts on the underlying ocean. In the tropical Pacific Ocean, the profiles for temperature show a significant correlation from the surface down to 2,000 m, due to dynamical adjustment of the isopycnals. At mid-tohigh latitudes, SSS nudging is required to reconstruct both the temperature and the salinity below the seasonal thermocline. This is particularly true in the North Atlantic where adding SSS nudging enables to reconstruct the deep convection regions of the target. By initiating a previously documented 20-year cycle of the model, the SST + SSS nudging is also able to reproduce most of the AMOC variations, a key source of decadal predictability. Reconstruction at depth does not significantly improve with amount of time spent nudging and the efficiency of the surface nudging rather depends on the period/events considered. The joint SST + SSS nudging applied verywhere is the most efficient approach. It ensures that the right water masses are formed at the right surface density, the subsequent circulation, subduction and deep convection further transporting them at depth. The results of this study underline the potential key role of SSS for decadal predictability and further make the case for sustained largescale observations of this field.

Contrasting interannual and multidecadal NAO variability

Decadal and longer timescale variability in the winter North Atlantic Oscillation (NAO) has considerable impact on regional climate, yet it remains unclear what fraction of this variability is potentially predictable. This study takes a new approach to this question by demonstrating clear physical differences between NAO variability on interannual-decadal (<30 year) and multidecadal (>30 year) timescales. It is shown that on the shorter timescale the NAO is dominated by variations in the latitude of the North Atlantic jet and storm track, whereas on the longer timescale it represents changes in their strength instead. NAO variability on the two timescales is associated with different dynamical behaviour in terms of eddy-mean flow interaction, Rossby wave breaking and blocking. The two timescales also exhibit different regional impacts on temperature and precipitation and different relationships to sea surface temperatures. These results are derived from linear regression analysis of the Twentieth Century and NCEP-NCAR reanalyses and of a high-resolution HiGEM General Circulation Model control simulation, with additional analysis of a long sea level pressure reconstruction. Evidence is presented for an influence of the ocean circulation on the longer timescale variability of the NAO, which is particularly clear in the model data. As well as providing new evidence of potential predictability, these findings are shown to have implications for the reconstruction and interpretation of long climate records.

Reconciling two alternative mechanisms behind bi-decadal variability in the North Atlantic

Understanding the preferential timescales of variability in the North Atlantic, usually associated with the Atlantic meridional overturning circulation (AMOC), is essential for the prospects for decadal prediction. However, the wide variety of mechanisms proposed from the analysis of climate simulations, potentially dependent on the models themselves, has stimulated the debate of which processes take place in reality. One mechanism receiving increasing attention, identified both in idealized models and observations, is a westward propagation of subsurface buoyancy anomalies that impact the AMOC through a basin-scale intensification of the zonal density gradient, enhancing the northward transport via thermal wind balance. In this study, we revisit a control simulation from the Institut Pierre-Simon Laplace Coupled Model 5A (IPSL-CM5A), characterized by a strong AMOC periodicity at 20 years, previously explained by an upper ocean–atmosphere–sea ice coupled mode driving convection activity south of Iceland. Our study shows that this mechanism interacts constructively with the basin-wide propagation in the subsurface. This constructive feedback may explain why bi-decadal variability is so intense in this coupled model as compared to others.

Regulatory mechanism of the light-activable allosteric switch LOV-TAP for the control of DNA binding: a computer simulation study

The spatio-temporal control of gene expression is fundamental to elucidate cell proliferation and deregulation phenomena in living systems. Novel approaches based on light-sensitive multiprotein complexes have recently been devised, showing promising perspectives for the noninvasive and reversible modulation of the DNA-transcriptional activity in vivo. This has lately been demonstrated in a striking way through the generation of the artificial protein construct light-oxygen-voltage (LOV)-tryptophan-activated protein (TAP), in which the LOV-2-Jα photoswitch of phototropin1 from Avena sativa (AsLOV2-Jα) has been ligated to the tryptophan-repressor (TrpR) protein from Escherichia coli. Although tremendous progress has been achieved on the generation of such protein constructs, a detailed understanding of their functioning as opto-genetical tools is still in its infancy. Here, we elucidate the early stages of the light-induced regulatory mechanism of LOV-TAP at the molecular level, using the noninvasive molecular dynamics simulation technique. More specifically, we find that Cys450-FMN-adduct formation in the AsLOV2-Jα-binding pocket after photoexcitation induces the cleavage of the peripheral Jα-helix from the LOV core, causing a change of its polarity and electrostatic attraction of the photoswitch onto the DNA surface. This goes along with the flexibilization through unfolding of a hairpin-like helix-loop-helix region interlinking the AsLOV2-Jα- and TrpR-domains, ultimately enabling the condensation of LOV-TAP onto the DNA surface. By contrast, in the dark state the AsLOV2-Jα photoswitch remains inactive and exerts a repulsive electrostatic force on the DNA surface. This leads to a distortion of the hairpin region, which finally relieves its tension by causing the disruption of LOV-TAP from the DNA.

Evaluation of control and surveillance strategies for classical swine fever using a simulation model

Classical swine fever (CSF) outbreaks can cause enormous losses in naïve pig populations. How to best minimize the economic damage and number of culled animals caused by CSF is therefore an important research area. The baseline CSF control strategy in the European Union and Switzerland consists of culling all animals in infected herds, movement restrictions for animals, material and people within a given distance to the infected herd and epidemiological tracing of transmission contacts. Additional disease control measures such as pre-emptive culling or vaccination have been recommended based on the results from several simulation models; however, these models were parameterized for areas with high animal densities. The objective of this study was to explore whether pre-emptive culling and emergency vaccination should also be recommended in low- to moderate-density areas such as Switzerland. Additionally, we studied the influence of initial outbreak conditions on outbreak severity to improve the efficiency of disease prevention and surveillance. A spatial, stochastic, individual-animal-based simulation model using all registered Swiss pig premises in 2009 (n=9770) was implemented to quantify these relationships. The model simulates within-herd and between-herd transmission (direct and indirect contacts and local area spread). By varying the four parameters (a) control measures, (b) index herd type (breeding, fattening, weaning or mixed herd), (c) detection delay for secondary cases during an outbreak and (d) contact tracing probability, 112 distinct scenarios were simulated. To assess the impact of scenarios on outbreak severity, daily transmission rates were compared between scenarios. Compared with the baseline strategy (stamping out and movement restrictions) vaccination and pre-emptive culling neither reduced outbreak size nor duration. Outbreaks starting in a herd with weaning piglets or fattening pigs caused higher losses regarding to the number of culled premises and were longer lasting than those starting in the two other index herd types. Similarly, larger transmission rates were estimated for these index herd type outbreaks. A longer detection delay resulted in more culled premises and longer duration and better transmission tracing increased the number of short outbreaks. Based on the simulation results, baseline control strategies seem sufficient to control CSF in low-medium animal-dense areas. Early detection of outbreaks is crucial and risk-based surveillance should be focused on weaning piglet and fattening pig premises.

An adaptive Newton-method based on a dynamical systems approach

The traditional Newton method for solving nonlinear operator equations in Banach spaces is discussed within the context of the continuous Newton method. This setting makes it possible to interpret the Newton method as a discrete dynamical system and thereby to cast it in the framework of an adaptive step size control procedure. In so doing, our goal is to reduce the chaotic behavior of the original method without losing its quadratic convergence property close to the roots. The performance of the modified scheme is illustrated with various examples from algebraic and differential equations.

An insulin infusion advisory system based on autotuning nonlinear model-predictive control

This paper aims at the development and evaluation of a personalized insulin infusion advisory system (IIAS), able to provide real-time estimations of the appropriate insulin infusion rate for type 1 diabetes mellitus (T1DM) patients using continuous glucose monitors and insulin pumps. The system is based on a nonlinear model-predictive controller (NMPC) that uses a personalized glucose-insulin metabolism model, consisting of two compartmental models and a recurrent neural network. The model takes as input patient's information regarding meal intake, glucose measurements, and insulin infusion rates, and provides glucose predictions. The predictions are fed to the NMPC, in order for the latter to estimate the optimum insulin infusion rates. An algorithm based on fuzzy logic has been developed for the on-line adaptation of the NMPC control parameters. The IIAS has been in silico evaluated using an appropriate simulation environment (UVa T1DM simulator). The IIAS was able to handle various meal profiles, fasting conditions, interpatient variability, intraday variation in physiological parameters, and errors in meal amount estimations.

Rapid parallel adaptive radiations from a single hybridogenic ancestral population

The Alpine lake whitefish (Coregonus lavaretus) species complex is a classic example of a recent radiation, associated with colonization of the Alpine lakes following the glacial retreat (less than 15 kyr BP). They have formed a unique array of endemic lake flocks, each with one to six described sympatric species differing in morphology, diet and reproductive ecology. Here, we present a genomic investigation of the relationships between and within the lake flocks. Comparing the signal between over 1000 AFLP loci and mitochondrial control region sequence data, we use phylogenetic tree-based and population genetic methods to reconstruct the phylogenetic history of the group and to delineate the principal centres of genetic diversity within the radiation. We find significant cytonuclear discordance showing that the genomically monophyletic Alpine whitefish clade arose from a hybrid swarm of at least two glacial refugial lineages. Within this radiation, we find seven extant genetic clusters centred on seven lake systems. Most interestingly, we find evidence of sympatric speciation within and parallel evolution of equivalent phenotypes among these lake systems. However, we also find the genetic signature of human-mediated gene flow and diversity loss within many lakes, highlighting the fragility of recent radiations.

Hybridization between distant lineages increases adaptive variation during a biological invasion: stickleback in Switzerland

The three-spined stickleback is a widespread Holarctic species complex that radiated from the sea into freshwaters after the retreat of the Pleistocene ice sheets. In Switzerland, sticklebacks were absent with the exception of the far northwest, but different introduced populations have expanded to occupy a wide range of habitats since the late 19th century. A well-studied adaptive phenotypic trait in sticklebacks is the number of lateral plates. With few exceptions, freshwater and marine populations in Europe are fixed for either the low plated phenotype or the fully plated phenotype, respectively. Switzerland, in contrast, harbours in close proximity the full range of phenotypic variation known from across the continent. We addressed the phylogeographic origins of Swiss sticklebacks using mitochondrial partial cytochrome b and control region sequences. We found only five different haplotypes but these originated from three distinct European regions, fixed for different plate phenotypes. These lineages occur largely in isolation at opposite ends of Switzerland, but co-occur in a large central part. Across the country, we found a strong correlation between a microsatellite linked to the high plate ectodysplasin allele and the mitochondrial haplotype from a region where the fully plated phenotype is fixed. Phylogenomic and population genomic analysis of 481 polymorphic amplified fragment length polymorphism loci indicate genetic admixture in the central part of the country. The same part of the country also carries elevated within-population phenotypic variation. We conclude that during the recent invasive range expansion of sticklebacks in Switzerland, adaptive and neutral between-population genetic variation was converted into within-population variation, raising the possibility that hybridization between colonizing lineages contributed to the ecological success of sticklebacks in Switzerland.

Real-time adaptive models for the personalized prediction of glycemic profile in type 1 diabetes patients

Prediction of glycemic profile is an important task for both early recognition of hypoglycemia and enhancement of the control algorithms for optimization of insulin infusion rate. Adaptive models for glucose prediction and recognition of hypoglycemia based on statistical and artificial intelligence techniques are presented.

Slc15a4, a gene required for pDC sensing of TLR ligands, is required to control persistent viral infection

Plasmacytoid dendritic cells (pDCs) are the major producers of type I IFN in response to viral infection and have been shown to direct both innate and adaptive immune responses in vitro. However, in vivo evidence for their role in viral infection is lacking. We evaluated the contribution of pDCs to acute and chronic virus infection using the feeble mouse model of pDC functional deficiency. We have previously demonstrated that feeble mice have a defect in TLR ligand sensing. Although pDCs were found to influence early cytokine secretion, they were not required for control of viremia in the acute phase of the infection. However, T cell priming was deficient in the absence of functional pDCs and the virus-specific immune response was hampered. Ultimately, infection persisted in feeble mice. We conclude that pDCs are likely required for efficient T cell priming and subsequent viral clearance. Our data suggest that reduced pDC functionality may lead to chronic infection.

A novel computer simulation method for simulating the multiscale transduction dynamics of signal proteins

Signal proteins are able to adapt their response to a change in the environment, governing in this way a broad variety of important cellular processes in living systems. While conventional molecular-dynamics (MD) techniques can be used to explore the early signaling pathway of these protein systems at atomistic resolution, the high computational costs limit their usefulness for the elucidation of the multiscale transduction dynamics of most signaling processes, occurring on experimental timescales. To cope with the problem, we present in this paper a novel multiscale-modeling method, based on a combination of the kinetic Monte-Carlo- and MD-technique, and demonstrate its suitability for investigating the signaling behavior of the photoswitch light-oxygen-voltage-2-Jα domain from Avena Sativa (AsLOV2-Jα) and an AsLOV2-Jα-regulated photoactivable Rac1-GTPase (PA-Rac1), recently employed to control the motility of cancer cells through light stimulus. More specifically, we show that their signaling pathways begin with a residual re-arrangement and subsequent H-bond formation of amino acids near to the flavin-mononucleotide chromophore, causing a coupling between β-strands and subsequent detachment of a peripheral α-helix from the AsLOV2-domain. In the case of the PA-Rac1 system we find that this latter process induces the release of the AsLOV2-inhibitor from the switchII-activation site of the GTPase, enabling signal activation through effector-protein binding. These applications demonstrate that our approach reliably reproduces the signaling pathways of complex signal proteins, ranging from nanoseconds up to seconds at affordable computational costs.