A benchmark-driven modelling approach for evaluating deployment choices on a multicore architecture

The complexity of current and emerging high performance architectures provides users with options about how best to use the available resources, but makes predicting performance challenging. In this work a benchmark-driven performance modelling approach is outlined that is appro- priate for modern multicore architectures. The approach is demonstrated by constructing a model of a simple shallow water code on a Cray XE6 system, from application-specific benchmarks that illustrate precisely how architectural char- acteristics impact performance. The model is found to recre- ate observed scaling behaviour up to 16K cores, and used to predict optimal rank-core affinity strategies, exemplifying the type of problem such a model can be used for.

Magnetic resonance imaging of a randomized controlled trial investigating predictors of recovery following psychological treatment in adolescents with moderate to severe unipolar depression: study protocol for Magnetic Resonance - Improving Mood with Psychoanalytic and Cognitive Therapies (MR-IMPACT)

Background Major depressive disorders (MDD) are a debilitating and pervasive group of mental illnesses afflicting many millions of people resulting in the loss of 110 million working days and more than 2,500 suicides per annum. Adolescent MDD patients attending NHS clinics show high rates of recurrence into adult life. A meta-analysis of recent research shows that psychological treatments are not as efficacious as previously thought. Modest treatment outcomes of approximately 65% of cases responding suggest that aetiological and clinical heterogeneity may hamper the better use of existing therapies and discovery of more effective treatments. Information with respect to optimal treatment choice for individuals is lacking, with no validated biomarkers to aid therapeutic decision-making. Methods/Design Magnetic resonance-Improving Mood with Psychoanalytic and Cognitive Therapies, the MR-IMPACT study, plans to identify brain regions implicated in the pathophysiology of depressions and examine whether there are specific behavioural or neural markers predicting remission and/or subsequent relapse in a subsample of depressed adolescents recruited to the IMPACT randomised controlled trial (Registration # ISRCTN83033550). Discussion MR-IMPACT is an investigative biomarker component of the IMPACT pragmatic effectiveness trial. The aim of this investigation is to identify neural markers and regional indicators of the pathophysiology of and treatment response for MDD in adolescents. We anticipate that these data may enable more targeted treatment delivery by identifying those patients who may be optimal candidates for therapeutic response.

Present state of global wetland extent and wetland methane modelling: conclusions from a model inter-comparison project (WETCHIMP)

Global wetlands are believed to be climate sensitive, and are the largest natural emitters of methane (CH4). Increased wetland CH4 emissions could act as a positive feedback to future warming. The Wetland and Wetland CH4 Inter-comparison of Models Project (WETCHIMP) investigated our present ability to simulate large-scale wetland characteristics and corresponding CH4 emissions. To ensure inter-comparability, we used a common experimental protocol driving all models with the same climate and carbon dioxide (CO2) forcing datasets. The WETCHIMP experiments were conducted for model equilibrium states as well as transient simulations covering the last century. Sensitivity experiments investigated model response to changes in selected forcing inputs (precipitation, temperature, and atmospheric CO2 concentration). Ten models participated, covering the spectrum from simple to relatively complex, including models tailored either for regional or global simulations. The models also varied in methods to calculate wetland size and location, with some models simulating wetland area prognostically, while other models relied on remotely sensed inundation datasets, or an approach intermediate between the two. Four major conclusions emerged from the project. First, the suite of models demonstrate extensive disagreement in their simulations of wetland areal extent and CH4 emissions, in both space and time. Simple metrics of wetland area, such as the latitudinal gradient, show large variability, principally between models that use inundation dataset information and those that independently determine wetland area. Agreement between the models improves for zonally summed CH4 emissions, but large variation between the models remains. For annual global CH4 emissions, the models vary by ±40% of the all-model mean (190 Tg CH4 yr−1). Second, all models show a strong positive response to increased atmospheric CO2 concentrations (857 ppm) in both CH4 emissions and wetland area. In response to increasing global temperatures (+3.4 °C globally spatially uniform), on average, the models decreased wetland area and CH4 fluxes, primarily in the tropics, but the magnitude and sign of the response varied greatly. Models were least sensitive to increased global precipitation (+3.9 % globally spatially uniform) with a consistent small positive response in CH4 fluxes and wetland area. Results from the 20th century transient simulation show that interactions between climate forcings could have strong non-linear effects. Third, we presently do not have sufficient wetland methane observation datasets adequate to evaluate model fluxes at a spatial scale comparable to model grid cells (commonly 0.5°). This limitation severely restricts our ability to model global wetland CH4 emissions with confidence. Our simulated wetland extents are also difficult to evaluate due to extensive disagreements between wetland mapping and remotely sensed inundation datasets. Fourth, the large range in predicted CH4 emission rates leads to the conclusion that there is both substantial parameter and structural uncertainty in large-scale CH4 emission models, even after uncertainties in wetland areas are accounted for.

Present state of global wetland extent and wetland methane modelling: methodology of a model inter-comparison project (WETCHIMP)

The Wetland and Wetland CH4 Intercomparison of Models Project (WETCHIMP) was created to evaluate our present ability to simulate large-scale wetland characteristics and corresponding methane (CH4) emissions. A multi-model comparison is essential to evaluate the key uncertainties in the mechanisms and parameters leading to methane emissions. Ten modelling groups joined WETCHIMP to run eight global and two regional models with a common experimental protocol using the same climate and atmospheric carbon dioxide (CO2) forcing datasets. We reported the main conclusions from the intercomparison effort in a companion paper (Melton et al., 2013). Here we provide technical details for the six experiments, which included an equilibrium, a transient, and an optimized run plus three sensitivity experiments (temperature, precipitation, and atmospheric CO2 concentration). The diversity of approaches used by the models is summarized through a series of conceptual figures, and is used to evaluate the wide range of wetland extent and CH4 fluxes predicted by the models in the equilibrium run. We discuss relationships among the various approaches and patterns in consistencies of these model predictions. Within this group of models, there are three broad classes of methods used to estimate wetland extent: prescribed based on wetland distribution maps, prognostic relationships between hydrological states based on satellite observations, and explicit hydrological mass balances. A larger variety of approaches was used to estimate the net CH4 fluxes from wetland systems. Even though modelling of wetland extent and CH4 emissions has progressed significantly over recent decades, large uncertainties still exist when estimating CH4 emissions: there is little consensus on model structure or complexity due to knowledge gaps, different aims of the models, and the range of temporal and spatial resolutions of the models.

Asset liability modelling and pension schemes: the application of robust optimization to USS

This paper uses a novel numerical optimization technique - robust optimization - that is well suited to solving the asset-liability management (ALM) problem for pension schemes. It requires the estimation of fewer stochastic parameters, reduces estimation risk and adopts a prudent approach to asset allocation. This study is the first to apply it to a real-world pension scheme, and the first ALM model of a pension scheme to maximise the Sharpe ratio. We disaggregate pension liabilities into three components - active members, deferred members and pensioners, and transform the optimal asset allocation into the scheme’s projected contribution rate. The robust optimization model is extended to include liabilities and used to derive optimal investment policies for the Universities Superannuation Scheme (USS), benchmarked against the Sharpe and Tint, Bayes-Stein, and Black-Litterman models as well as the actual USS investment decisions. Over a 144 month out-of-sample period robust optimization is superior to the four benchmarks across 20 performance criteria, and has a remarkably stable asset allocation – essentially fix-mix. These conclusions are supported by six robustness checks.

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.

A mechanism for the formation of oxygen and iron bimodal radial distribution in the disc of our Galaxy

Recently, it has been proposed that there are two type Ia supernova progenitors: short-lived and long-lived. On the basis of this idea, we develop a theory of a unified mechanism for the formation of the bimodal radial distribution of iron and oxygen in the Galactic disc. The underlying cause for the formation of the fine structure of the radial abundance pattern is the influence of the spiral arms, specifically the combined effect of the corotation resonance and turbulent diffusion. From our modelling, we conclude that in order to explain the bimodal radial distributions simultaneously for oxygen and iron and to obtain approximately equal total iron output from different types of supernovae, the mean ejected iron mass per supernova event should be the same as quoted in the literature if the maximum mass of stars, which eject heavy elements, is 50 M(circle dot). For the upper mass limit of 70 M(circle dot), the production of iron by a type II supernova explosion should increase by about 1.5 times.

Can physical exercise during gestation attenuate the effects of a maternal perinatal low-protein diet on oxygen consumption in rats?

A protocol of physical exercise, based on maximal oxygen uptake ((V) over dot(O2max)), for female rats before and during pregnancy was developed to evaluate the impact of a low-protein diet on oxygen consumption during gestation and growth rate of the offspring. Virgin female Wistar rats were divided into four groups as follows: untrained (NT, n = 5); trained (T, n = 5); untrained with low-protein diet (NT+LP, n = 5); and trained with low-protein diet (T+LP, n = 5). Trained rats were submitted to a protocol of moderate physical training on a treadmill over a period of 4 weeks (5 days week(-1) and 60 min day(-1), at 65% of (V) over dot(O2max)). At confirmation of pregnancy, the intensity and duration of the exercise was reduced. Low-protein groups received an 8% casein diet, and their peers received a 17% casein diet. The birthweight and growth rate of the pups up to the 90th day were recorded. Oxygen consumption ((V) over dot(O2)), CO(2) production and respiratory exchange ratio (RER) were determined using an indirect open-circuit calorimeter. Exercise training increased. (V) over dot(O2max) by about 20% when compared with the initial values (45.6 +/- 1.0 ml kg(-1) min(-1)). During gestation, all groups showed a progressive reduction in the resting (V) over dot(O2) values. Dams in the NT+LP group showed lower values of resting (V) over dot(O2) than those in the NT group. The growth rate of pups from low-protein-fed mothers was around 50% lower than that of their respective controls. The T group showed an increase in body weight from the 60th day onwards, while the NT+LP group presented a reduced body weight from weaning onwards. In conclusion, physical training attenuated the impact of the low- protein

Reduced maximal oxygen consumption and overproduction of proinflammatory cytokines in athletes

Objective: It was the aim of this study to evaluate whether chronic pain in athletes is related to performance, measured by the maximum oxygen consumption and production of hormones and cytokines. Methods: Fifty-five athletes with a mean age of 31.9 +/- 4.2 years engaged in regular competition and showing no symptoms of acute inflammation, particularly fever, were studied. They were divided into 2 subgroups according to the occurrence of pain. Plasma concentrations of adrenaline, noradrenaline, cortisol, prolactin, growth hormone and dopamine were measured by radioimmunoassay, and the production of the cytokines interleukin (IL)-1, IL-2, IL-4, IL-6, tumor necrosis factor-alpha, interferon-alpha and prostaglandin E-2 by whole-blood culture. Maximal oxygen consumption was determined during an incremental treadmill test. Results: There was no change in the concentration of stress hormones, but the athletes with chronic pain showed a reduction in maximum oxygen consumption (22%) and total consumption at the anaerobic threshold (25%), as well as increased cytokine production. Increases of 2.7-, 8.1-, 1.7- and 3.7-fold were observed for IL-1, IL-2, tumor necrosis factor-alpha and interferon-alpha, respectively. Conclusions: Our data show that athletes with chronic pain have enhanced production of proinflammatory cytokines and lipid mediators and reduced performance in the ergospirometric test. Copyright (c) 2008 S. Karger AG, Basel.

Differential expression of apoptosis-related genes from death receptor pathway in chronic myeloproliferative diseases

Background Chronic myeloproliferative disorders (MPDs) are clonal haematopoietic stem cell malignancies characterised by an accumulation of mature myeloid cells in bone marrow and peripheral blood. Deregulation of the apoptotic machinery may be associated with MPD physiopathology. Aims To evaluate expression of death receptors` family members, mononuclear cell apoptosis resistance, and JAK2 allele burden. Subjects and Methods Bone marrow haematopoietic progenitor CD34 cells were separated using the Ficoll-hypaque protocol followed by the Miltenyi CD34 isolation kit, and peripheral blood leukocytes were separated by the Haes-Steril method. Total RNA was extracted by the Trizol method, the High Capacity Kit was used to synthesise cDNA, and real-time PCR was performed using SybrGreen in ABIPrism 7500 equipment. The results of gene expression quantification are given as 2(-Delta Delta Ct). The JAK2 V617F mutation was detected by real-time allelic discrimination PCR assay. Peripheral blood mononuclear cells (PBMCs) were isolated by the Ficoll-hypaque protocol and cultured in the presence of apoptosis inducers. Results In CD34 cells, there was mRNA overexpression for fas, faim and c-flip in polycythaemia vera (PV), essential thrombocythaemia (ET) and primary myelofibrosis (PMF), as well as fasl in PMF, and dr4 levels were increased in ET. In leukocytes, fas, c-flip and trail levels were increased in PV, and dr5 expression was decreased in ET. There was an association between dr5 and fasl expression and JAK2V617F mutation. PBMCs from patients with PV, ET or PMF showed resistance to apoptosis inducers. Conclusions The results indicate deregulation of apoptosis gene expression, which may be associated with MPD pathogenesis leading to accumulation of myeloid cells in MPDs.

Chronic exercise decreases cytokine production in healthy rat skeletal muscle

Skeletal muscle is the source of pro- and anti-inflammatory cytokines, and recently, it has been recognized as an important source of interleukin-6 (IL-6). Acute physical exercise is known to induce a pro-inflammatory cytokine profile in the plasma. However, the effect of chronic physical exercise in the production of pro- and anti-inflammatory cytokines by the skeletal muscle has never been examined. We assessed IL-6, TNF-alpha, IL-1 beta and IL-10 levels in the skeletal muscle of rats submitted to endurance training. Animals were randomly assigned to either a Sedentary group (S, n = 7) or an endurance exercise trained group (T, n = 8). Trained rats ran on a treadmill for 5 days week(-1) for 8 weeks (60% VO(2max)). Detection of IL-6, TNF-alpha, IL-1 beta and IL-10 protein expression was carried out by ELISA. We found decreased expression of IL-1 beta, IL-6, TNF-alpha and IL-10 (28%, 27%. 32% and 37%, respectively, p < 0.05) in the extensor digital longus (EDL) from T, when compared with S. In the soleus, IL-1 beta, TNF-alpha and IL-10 protein levels were similarly decreased (34%, 42% and 50%, respectively, p < 0.05) in T in relation to S, while IL-6 expression was not affected by the training protocol. In conclusion, exercise training induced decreased cytokine protein expression in the skeletal muscle. These data show that in healthy rats, 8-week moderate-intensity aerobic training down regulates skeletal muscle production of cytokines involved in the onset, maintenance and regulation of inflammation, and that the response is heterogeneous according to fibre composition. Copyright (C) 2009 John Wiley & Sons, Ltd.

The constrained compartmentalized knapsack problem: mathematical models and solution methods

The constrained compartmentalized knapsack problem can be seen as an extension of the constrained knapsack problem. However, the items are grouped into different classes so that the overall knapsack has to be divided into compartments, and each compartment is loaded with items from the same class. Moreover, building a compartment incurs a fixed cost and a fixed loss of the capacity in the original knapsack, and the compartments are lower and upper bounded. The objective is to maximize the total value of the items loaded in the overall knapsack minus the cost of the compartments. This problem has been formulated as an integer non-linear program, and in this paper, we reformulate the non-linear model as an integer linear master problem with a large number of variables. Some heuristics based on the solution of the restricted master problem are investigated. A new and more compact integer linear model is also presented, which can be solved by a branch-and-bound commercial solver that found most of the optimal solutions for the constrained compartmentalized knapsack problem. On the other hand, heuristics provide good solutions with low computational effort. (C) 2011 Elsevier BM. All rights reserved.

Serum amyloid A induces reactive oxygen species (ROS) production and proliferation of fibroblast

Serum amyloid A (SAA) levels are elevated highly in acute phase response and elevated slightly and persistently in chronic diseases such as rheumatoid arthritis and diabetes. Given that fibroblasts exert profound effects on progression of inflammatory chronic diseases, the aim of this study was to investigate the response of fibroblasts to SAA. A dose-dependent increase in O(2)(-) levels was observed by treatment of fibroblasts with SAA (r = 0.99 and P <= 0.001). In addition, the expression of p47-phox was up-regulated by SAA (P < 0.001) and diphenyliodonium (DPI), a nicotinamide adenine dinucleotide phosphate (NADPH) oxidase inhibitor, reduced the release of O(2)(-) by 50%. Also, SAA raised fibroblast proliferation (P < 0.001) and this effect was completely abolished by the addition of anti-oxidants (P < 0.001). These findings support the notion that, in chronic inflammatory sites, SAA activated fibroblast proliferation and ROS production.

Antioxidant therapy attenuates oxidative insult caused by benzonidazole in chronic Chagas` heart disease

Chronic chagasic cardiac patients are exposed to oxidative stress that apparently contributes to disease progression. Benznidazole (BZN) is the main drug used for the treatment of chagasic patients and its action involves the generation of reactive species. 41 patients with Chagas` heart disease were selected and biomarkers of oxidative stress were measured before and after 2 months of BZN treatment (5 mg/kg/day) and the subsequent antioxidant supplementation with vitamin E (800 UI/day) and C (500 mg/day) during 6 months. Patients were classified according to the modified Los Andes clinical hemodynamic classification in groups IA, IB, II and III, and the activity of superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GPx), glutathione S-transferase (GST) and glutathione reductase (GR), as well as the contents of reduced glutathione (GSH), thiobarbituric acid reactive species (TBARS), protein carbonyl (PC), vitamin E and C and nitric oxide (NO), myeloperoxidase (MPO) and adenosine deaminase (ADA) activities were measured in their blood. Excepting in group III, after BZN treatment SOD, CAT, GPx and GST activities as well as PC levels were enhanced while vitamin E levels were decreased in these groups. After antioxidant supplementation the activities of SOD, GPx and GR were decreased whereas PC, TBARS, NO, and GSH levels were decreased. In conclusion, BZN treatment promoted an oxidative insult in such patients while the antioxidant supplementation was able to attenuate this effect by increasing vitamin E levels, decreasing PC and TBARS levels, inhibiting SOD, GPx and GR activities as well as inflammatory markers, mainly in stages with less cardiac involvement. (C) 2009 Elsevier Ireland Ltd. All rights reserved.

The importance of body-mass exponent optimization for evaluation of performance capability in cross-country skiing

Introduction Performance in cross-country skiing is influenced by the skier’s ability to continuously produce propelling forces and force magnitude in relation to the net external forces. A surrogate indicator of the “power supply” in cross-country skiing would be a physiological variable that reflects an important performance-related capability, whereas the body mass itself is an indicator of the “power demand” experienced by the skier. To adequately evaluate an elite skier’s performance capability, it is essential to establish the optimal ratio between the physiological variable and body mass. The overall aim of this doctoral thesis was to investigate the importance of body-mass exponent optimization for the evaluation of performance capability in cross-country skiing. Methods In total, 83 elite cross-country skiers (56 men and 27 women) volunteered to participate in the four studies. The physiological variables of maximal oxygen uptake (V̇O2max) and oxygen uptake corresponding to a blood-lactate concentration of 4 mmol∙l-1 (V̇O2obla) were determined while treadmill roller skiing using the diagonal-stride technique; mean oxygen uptake (V̇O2dp) and upper-body power output (Ẇ) were determined during double-poling tests using a ski-ergometer. Competitive performance data for elite male skiers were collected from two 15-km classical-technique skiing competitions and a 1.25-km sprint prologue; additionally, a 2-km double-poling roller-skiing time trial using the double-poling technique was used as an indicator of upper-body performance capability among elite male and female junior skiers. Power-function modelling was used to explain the race and time-trial speeds based on the physiological variables and body mass. Results The optimal V̇O2max-to-mass ratios to explain 15-km race speed were V̇O2max divided by body mass raised to the 0.48 and 0.53 power, and these models explained 68% and 69% of the variance in mean skiing speed, respectively; moreover, the 95% confidence intervals (CI) for the body-mass exponents did not include either 0 or 1. For the modelling of race speed in the sprint prologue, body mass failed to contribute to the models based on V̇O2max, V̇O2obla, and V̇O2dp. The upper-body power output-to-body mass ratio that optimally explained time-trial speed was Ẇ ∙ m-0.57 and the model explained 63% of the variance in speed. Conclusions The results in this thesis suggest that V̇O2max divided by the square root of body mass should be used as an indicator of performance in 15-km classical-technique races among elite male skiers rather than the absolute or simple ratio-standard scaled expression. To optimally explain an elite male skier’s performance capability in sprint prologues, power-function models based on oxygen-uptake variables expressed absolutely are recommended. Moreover, to evaluate elite junior skiers’ performance capabilities in 2-km double-poling roller-skiing time trials, it is recommended that Ẇ divided by the square root of body mass should be used rather than absolute or simple ratio-standard scaled expression of power output.