Power Capacity Expansion Planning Considering Endogenous Technology Cost Learning

We present an power systems optimisation model for national-scale power supply capacity expansion considering endogenous technology cost reduction (ESO-XEL). The mixed-integer linear program minimises total system cost while complying with operational constraints, carbon emission targets, and ancillary service requirements. A data clustering technique and the relaxation of integer scheduling constraints is evaluated and applied to decrease the model solution time. Two cost learning curves for the different power technologies are derived: one assuming local learning effects, the other accounting for global knowledge spill-over. A piece-wise linear formulation allows the integration of the exponential learning curves into the ESO-XEL model. The model is applied to the UK power system in the time frame of 2015 to 2050. The consideration of cost learning effects moves optimal investment timings to earlier planning years and influences the competitiveness of technologies. In addition, the maximum capacity build rate parameter influences the share of power generation significantly; the possibility of rapid capacity build-up is more important for total system cost reduction by 2050 than accounting for technology cost reduction

Surgical wound infection: epidemiology, pathogenesis, diagnosis and management

Surgical wound infection remains a significant problem following an operation, although surveillance for such infections remains a challenge exacerbated by early discharge and outpatient surgery. The riskof such infections isdetermined by technical problems with the operation, particularly bleeding, the amount of devitalized tissue created, and the need for drains within the wound, as well as such metabolic factors as obesity and diabetes. Perioperative antibiotic prophylaxis can decrease the incidence of such infections further, but a technically perfect operation is even more important

Induced innovation in energy technologies and systems: a review of evidence and potential implications for CO2 mitigation

We conduct a systematic, interdisciplinary review of empirical literature assessing evidence on induced innovation in energy and related technologies. We explore links between demand-drivers (both market-wide and targeted); indicators of innovation (principally, patents); and outcomes (cost reduction, efficiency, and multi-sector/macro consequences). We build on existing reviews in different fields and assess over 200 papers containing original data analysis. Papers linking drivers to patents, and indicators of cumulative capacity to cost reductions (experience curves), dominate the literature. The former does not directly link patents to outcomes; the latter does not directly test for the causal impact of on cost reductions). Diverse other literatures provide additional evidence concerning the links between deployment, innovation activities, and outcomes. We derive three main conclusions. (1) Demand-pull forces enhance patenting; econometric studies find positive impacts in industry, electricity and transport sectors in all but a few specific cases. This applies to all drivers - general energy prices, carbon prices, and targeted interventions that build markets. (2) Technology costs decline with cumulative investment for almost every technology studied across all time periods, when controlled for other factors. Numerous lines of evidence point to dominant causality from at-scale deployment (prior to self-sustaining diffusion) to cost reduction in this relationship. (3) Overall Innovation is cumulative, multi-faceted, and self-reinforcing in its direction (path-dependent). We conclude with brief observations on implications for modeling and policy. In interpreting these results, we suggest distinguishing the economics of active deployment, from more passive diffusion processes, and draw the following implications. There is a role for policy diversity and experimentation, with evaluation of potential gains from innovation in the broadest sense. Consequently, endogenising innovation in large-scale models is important for deriving policy-relevant conclusions. Finally, seeking to relate quantitative economic evaluation to the qualitative socio-technical transitions literatures could be a fruitful area for future research

The Heat Kernel on AdS_3 and its Applications

We derive the heat kernel for arbitrary tensor fields on S^3 and (Euclidean) AdS_3 using a group theoretic approach. We use these results to also obtain the heat kernel on certain quotients of these spaces. In particular, we give a simple, explicit expression for the one loop determinant for a field of arbitrary spin s in thermal AdS_3. We apply this to the calculation of the one loop partition function of N=1 supergravity on AdS_3. We find that the answer factorizes into left- and right-moving super Virasoro characters built on the SL(2, C) invariant vacuum, as argued by Maloney and Witten on general grounds.Comment: 46 pages, LaTeX, v2: Reference adde

Separation of Anti-Proliferation and Anti-Apoptotic Functions of Retinoblastoma Protein through Targeted Mutations of Its A/B Domain

BACKGROUND: The human retinoblastoma susceptibility gene encodes a nuclear phosphoprotein RB, which is a negative regulator of cell proliferation. The growth suppression function of RB requires an evolutionarily conserved A/B domain that contains two distinct peptide-binding pockets. At the A/B interface is a binding site for the C-terminal trans-activation domain of E2F. Within the B-domain is a binding site for proteins containing the LxCxE peptide motif. METHODOLOGY/PRINCIPLE FINDINGS: Based on the crystal structure of the A/B domain, we have constructed an RB-K530A/N757F (KN) mutant to disrupt the E2F- and LxCxE-binding pockets. The RB-K530A (K) mutant is sufficient to inactivate the E2F-binding pocket, whereas the RB-N757F (N) mutant is sufficient to inactivate the LxCxE-binding pocket. Each single mutant inhibits cell proliferation, but the RB-KN double mutant is defective in growth suppression. Nevertheless, the RB-KN mutant is capable of reducing etoposide-induced apoptosis. CONCLUSION/SIGNIFICANCE: Previous studies have established that RB-dependent G1-arrest can confer resistance to DNA damage-induced apoptosis. Results from this study demonstrate that RB can also inhibit apoptosis independent of growth suppression

Additional Serine/Threonine Phosphorylation Reduces Binding Affinity but Preserves Interface Topography of Substrate Proteins to the c-Cbl TKB Domain

The E3-ubiquitin ligase, c-Cbl, is a multi-functional scaffolding protein that plays a pivotal role in controlling cell phenotype. As part of the ubiquitination and downregulation process, c-Cbl recognizes targets, such as tyrosine kinases and the Sprouty proteins, by binding to a conserved (NX/R)pY(S/T)XXP motif via its uniquely embedded SH2 domain (TKB domain). We previously outlined the mode of binding between the TKB domain and various substrate peptide motifs, including epidermal growth factor receptor (EGFR) and Sprouty2 (Spry2), and demonstrated that an intrapetidyl hydrogen bond forms between the (pY-1) arginine or (pY-2) asparagine and the phosphorylated tyrosine, which is crucial for binding. Recent reports demonstrated that, under certain types of stimulation, the serine/threonine residues at the pY+1 and/or pY+2 positions within this recognition motif of EGFR and Sprouty2 may be endogenously phosphorylated. Using structural and binding studies, we sought to determine whether this additional phosphorylation could affect the binding of the TKB domain to these peptides and consequently, whether the type of stimulation can dictate the degree to which substrates bind to c-Cbl. Here, we show that additional phosphorylation significantly reduces the binding affinity between the TKB domain and its target proteins, EGFR and Sprouty2, as compared to peptides bearing a single tyrosine phosphorylation. The crystal structure indicates that this is accomplished with minimal changes to the essential intrapeptidyl bond and that the reduced strength of the interaction is due to the charge repulsion between c-Cbl and the additional phosphate group. This obvious reduction in binding affinity, however, indicates that Cbl's interactions with its TKB-centered binding partners may be more favorable in the absence of Ser/Thr phosphorylation, which is stimulation and context specific in vivo. These results demonstrate the importance of understanding the environment in which certain residues are phosphorylated, and the necessity of including this in structural investigations

Role of Esrrg in the Fibrate-Mediated Regulation of Lipid Metabolism Genes in Human ApoA-I Transgenic Mice

We have used a new ApoA-I transgenic mouse model to identify by global gene expression profiling, candidate genes that affect lipid and lipoprotein metabolism in response to fenofibrate treatment. Multilevel bioinformatical analysis and stringent selection criteria (2-fold change, 0% false discovery rate) identified 267 significantly changed genes involved in several molecular pathways. The fenofibrate-treated group did not have significantly altered levels of hepatic human APOA-I mRNA and plasma ApoA-I compared with the control group. However, the treatment increased cholesterol levels to 1.95-fold mainly due to the increase in high-density lipoprotein (HDL) cholesterol. The observed changes in HDL are associated with the upregulation of genes involved in phospholipid biosynthesis and lipid hydrolysis, as well as phospholipid transfer protein. Significant upregulation was observed in genes involved in fatty acid transport and β-oxidation, but not in those of fatty acid and cholesterol biosynthesis, Krebs cycle and gluconeogenesis. Fenofibrate changed significantly the expression of seven transcription factors. The estrogen receptor-related gamma gene was upregulated 2.36-fold and had a significant positive correlation with genes of lipid and lipoprotein metabolism and mitochondrial functions, indicating an important role of this orphan receptor in mediating the fenofibrate-induced activation of a specific subset of its target genes.National Institutes of Health (HL48739 and HL68216); European Union (LSHM-CT-2006-0376331, LSHG-CT-2006-037277); the Biomedical Research Foundation of the Academy of Athens; the Hellenic Cardiological Society; the John F Kostopoulos Foundatio

Marginalization of end-use technologies in energy innovation for climate protection

Mitigating climate change requires directed innovation efforts to develop and deploy energy technologies. Innovation activities are directed towards the outcome of climate protection by public institutions, policies and resources that in turn shape market behaviour. We analyse diverse indicators of activity throughout the innovation system to assess these efforts. We find efficient end-use technologies contribute large potential emission reductions and provide higher social returns on investment than energy-supply technologies. Yet public institutions, policies and financial resources pervasively privilege energy-supply technologies. Directed innovation efforts are strikingly misaligned with the needs of an emissions-constrained world. Significantly greater effort is needed to develop the full potential of efficient end-use technologies

Scaling Relations and Overabundance of Massive Clusters at Z ≳ 1 from Weak-Lensing Studies with the Hubble Space Telescope

We present weak gravitational lensing analysis of 22 high-redshift (z 1) clusters based on Hubble Space Telescope images. Most clusters in our sample provide significant lensing signals and are well detected in their reconstructed two-dimensional mass maps. Combining the current results and our previous weak-lensing studies of five other high-z clusters, we compare gravitational lensing masses of these clusters with other observables. We revisit the question whether the presence of the most massive clusters in our sample is in tension with the current ΛCDM structure formation paradigm. We find that the lensing masses are tightly correlated with the gas temperatures and establish, for the first time, the lensing mass-temperature relation at z 1. For the power-law slope of the M-TX relation (MT α), we obtain α = 1.54 ± 0.23. This is consistent with the theoretical self-similar prediction α = 3/2 and with the results previously reported in the literature for much lower redshift samples. However, our normalization is lower than the previous results by 20%-30%, indicating that the normalization in the M-TX relation might evolve. After correcting for Eddington bias and updating the discovery area with a more conservative choice, we find that the existence of the most massive clusters in our sample still provides a tension with the current ΛCDM model. The combined probability of finding the four most massive clusters in this sample after the marginalization over cosmological parameters is less than 1%