Coordination in networks: An economic equilibrium analysis

Networks utilizing modern communication technologies can offer competitive advantages to those using them wisely. But due to the existence of network effects, planning and operating cooperation networks is difficult. In this paper, the strategic situation of individual agents deciding on network participation is analysed. A systematic equilibrium analysis using computer-based simulations reveals principal solution scenarios for network agents and shows that network cooperation problems might frequently be not as difficult to resolve as often feared. In particular, strategic situations are identified showing that a majority of individuals might be better off getting the optimal solution from a central principal and that in many cases simple information intermediation can solve the start-up problem notorious in network economics.     

Cardioprotective Signaling Pathways in Obese Mice Submitted to Regular Exercise: Effect on Oxysterols

Exercise induces cardioprotection against myocardial infarction, despite obesity, by restoring pro-survival pathways and increasing resistance of mitochondrial permeability transition pore (mPTP) opening at reperfusion. Among the mechanisms involved in the inactivation of these pathways, oxysterols appear interesting. Thus, we investigated the influence of regular exercise on the reperfusion injury salvage kinase (RISK) pathway, oxysterols, and mitochondria, in the absence of ischemia-reperfusion. We also studied 7β-hydroxycholesterol (7βOH) concentration (mass spectrometry) in human lean and obese subjects. Wild-type (WT) and obese (ob/ob) mice were assigned to sedentary conditions or regular treadmill exercise. Exercise significantly increased Akt phosphorylation, whereas 7βOH concentration was reduced. Moreover, exercise induced the translocation of PKCε from the cytosol to mitochondria. However, exercise did not affect the calcium concentration required to open mPTP in the mitochondria, neither in WT nor in ob/ob animals. Finally, human plasma 7βOH concentration was consistent with observations made in mice. In conclusion, regular exercise enhanced the RISK pathway by increasing kinase phosphorylation and PKCε translocation and decreasing 7βOH concentration. This activation needs the combination with stress conditions, i.e., ischemia-reperfusion, in order to inhibit mPTP opening at the onset of reperfusion. The human findings suggest 7βOH as a candidate marker for evaluating cardiovascular risk factors in obesity.     

The Pro-Inflammatory Deletion Allele of the NF-κB1 Polymorphism Is Characterized by a Depletion of Subunit p50 in Sepsis

The functionally important NF-κB1 promoter polymorphism (−94ins/delATTG) significantly shapes inflammation and impacts the outcome of sepsis. However, exploratory studies elucidating the molecular link of this genotype-dependent pattern are lacking. Accordingly, we analyzed lipopolysaccharide-stimulated peripheral blood mononuclear cells from both healthy volunteers (n = 20) and septic patients (n = 10). All individuals were genotyped for the −94ins/delATTG NF-κB1 promoter polymorphism. We found a diminished nuclear activity of the NF-κB subunit p50 in ID/DD genotypes after 48 h of lipopolysaccharide stimulation compared to II genotypes (p = 0.025). This was associated with higher TNF-α (p = 0.005) and interleukin 6 concentrations (p = 0.014) and an increased production of mitochondrial radical oxygen species in ID/DD genotypes (p = 0.001). Although ID/DD genotypes showed enhanced activation of mitochondrial biogenesis, they still had a significantly diminished cellular ATP content (p = 0.046) and lower mtDNA copy numbers (p = 0.010) compared to II genotypes. Strikingly, these findings were mirrored in peripheral blood mononuclear cells taken from septic patients. Our results emphasize the crucial aspect of considering NF-κB subunits in sepsis. We showed here that the deletion allele of the NF-κB1 (−94ins/delATTG) polymorphism was associated with the lower nuclear activity of subunit p50, which, in turn, was associated with aggravated inflammation and mitochondrial dysfunction.     

Coherent interaction of atoms with a beam of light confined in a light cage

Controlling coherent interaction between optical fields and quantum systems in scalable, integrated platforms is essential for quantum technologies. Miniaturise...     

Assessment of the MODIS LAI product for Australian ecosystems

The leaf area index (LAI) product from the Moderate Resolution Imaging Spectroradiometer (MODIS) is important for monitoring and modelling global change and terrestrial dynamics at many scales. The algorithm relies on spectral reflectances and a six biome land cover classification. Evaluation of the specific behaviour and performance of the product for regions of the globe such as Australia are needed to assist with product refinement and validation. We made an assessment of Collection 4 of the MODIS LAI product using four approaches: (a) assessment against a continental scale Structural Classification of Australian Vegetation (SCAV); (b) assessment against a continental scale land use classification (LUC); (c) assessment against historical field-based measurement of LAI collected prior to the Terra Mission; and (d) direct comparison of MODIS LAI with coincident field measurements of LAI, mostly from hemispherical photography. The MODIS LAI product produced a wide variety of geographically and structurally specific temporal response profiles between different classes and even for sub-groups within classes of the SCAV. Historical and concurrent field measurements indicated that MODIS LAI was giving reasonable estimates for LAI for most cover types and land use types, but that major overestimation of LAI occurs in some eastern Australian open forests and woodlands. The six biome structural land cover classification showed some significant deviations in class allocation compared to the SCAV particularly where grasslands are allocated to shrubland, savanna woodlands are allocated to shrubland, savanna and broadleaf forest, and open forests are allocated to savanna and broadleaf forest. The land cover and LAI products could benefit from some additional examination of Australian data addressing the structural representation of Eucalypt canopies in the “space of canopy realisation” for savanna and broadleaf forest classes.     

Effects of Combining Biofactors on Bioenergetic Parameters,Aβ Levels and Survival in Alzheimer Model Organisms

Increased amyloid beta (Aβ) levels and mitochondrial dysfunction (MD) in the human brain characterize Alzheimer disease (AD). Folic acid, magnesium and vitamin B6 are essential micro-nutrients that may provide neuroprotection. Bioenergetic parameters and amyloid precursor protein (APP) processing products were investigated in vitro in human neuroblastoma SH-SY5Y-APP695 cells, expressing neuronal APP, and in vivo, in the invertebrate Caenorhabditis elegans (CL2006 & GMC101) expressing muscular APP. Model organisms were incubated with either folic acid and magnesium-orotate (ID63) or folic acid, magnesium-orotate and vitamin B6 (ID64) in different concentrations. ID63 and ID64 reduced Aβ, soluble alpha APP (sAPPα), and lactate levels in SH-SY5Y-APP695 cells. The latter might be explained by enhanced expression of lactate dehydrogenase (LDHA). Micronutrient combinations had no effects on mitochondrial parameters in SH-SY5Y-APP695 cells. ID64 showed a significant life-prolonging effect in C. elegans CL2006. Incubation of GMC101 with ID63 significantly lowered Aβ aggregation. Both combinations significantly reduced paralysis and thus improved the phenotype in GMC101. Thus, the combinations of the tested biofactors are effective in pre-clinical models of AD by interfering with Aβ related pathways and glycolysis.     

Rule fitness and pathology in learning classifier systems

It has long been known that in some relatively simple reinforcement learning tasks traditional strength-based classifier systems will adapt poorly and show poor generalisation. In contrast, the more recent accuracy-based XCS, appears both to adapt and generalise well. In this work, we attribute the difference to what we call strong over general and fit over general rules. We begin by developing a taxonomy of rule types and considering the conditions under which they may occur. In order to do so an extreme simplification of the classifier system is made, which forces us toward qualitative rather than quantitative analysis. We begin with the basics, considering definitions for correct and incorrect actions, and then correct, incorrect, and overgeneral rules for both strength and accuracy-based fitness. The concept of strong overgeneral rules, which we claim are the Achilles' heel of strength-based classifier systems, are then analysed. It is shown that strong overgenerals depend on what we call biases in the reward function (or, in sequential tasks, the value function). We distinguish between strong and fit overgeneral rules, and show that although strong overgenerals are fit in a strength-based system called SB-XCS, they are not in XCS. Next we show how to design fit overgeneral rules for XCS (but not SB-XCS), by introducing biases in the variance of the reward function, and thus that each system has its own weakness. Finally, we give some consideration to the prevalence of reward and variance function bias, and note that non-trivial sequential tasks have highly biased value functions.     

Intruder alert! Optimization models for solving the mobile robot graph-clear problem

We develop optimization approaches to the graph-clear problem, a pursuit-evasion problem where mobile robots must clear a facility of intruders. The objective is to minimize the number of robots required. We contribute new formal results on progressive and contiguous assumptions and their impact on algorithm completeness. We present mixed-integer linear programming and constraint programming models, as well as new heuristic variants for the problem, comparing them to previously proposed heuristics. Our empirical work indicates that our heuristic variants improve on those from the literature, that constraint programming finds better solutions than the heuristics in run-times reasonable for the application, and that mixed-integer linear programming is superior for proving optimality. Given their performance and the appeal of the model-and-solve framework, we conclude that the proposed optimization methods are currently the most suitable for the graph-clear problem.