Numerical and experimental verification of a theoretical model of ripple formation in ice growth under supercooled water film flow

Little is known about morphological instability of a solidification front during the crystal growth of a thin film of flowing supercooled liquid with a free surface: for example, the ring-like ripples on the surface of icicles. The length scale of the ripples is nearly 1 cm. Two theoretical models for the ripple formation mechanism have been proposed. However, these models lead to quite different results because of differences in the boundary conditions at the solid-liquid interface and liquid-air surface. The validity of the assumption used in the two models is numerically investigated and some of the theoretical predictions are compared with experiments.Comment: 30 pages, 9 figure

Query rewriting under linear EL knowledge bases

With the adoption of the recent SPARQL 1.1 standard, RDF databases are capable of directly answering more expressive queries than simple conjunctive queries. In this paper we exploit such capabilities to answer conjunctive queries (CQs) under ontologies expressed in the description logic called linear EL-lin, a restricted form of EL. In particular, we show a query answering algorithm that rewrites a given CQ into a conjunctive regular path query (CRPQ) which, evaluated on the given instance, returns the correct answer. Our technique is based on the representation of infinite unions of CQs by non-deterministic finite-state automata. Our results achieve optimal data complexity, as well as producing rewritings straightforwardly implementable in SPARQL 1.1

Multi-Player and Multi-Choice Quantum Game

We investigate a multi-player and multi-choice quantum game. We start from two-player and two-choice game and the result is better than its classical version. Then we extend it to N-player and N-choice cases. In the quantum domain, we provide a strategy with which players can always avoid the worst outcome. Also, by changing the value of the parameter of the initial state, the probabilities for players to obtain the best payoff will be much higher that in its classical version.Comment: 4 pages, 1 figur

Transcriptional regulation of the urokinase receptor (u-PAR) - A central molecule of invasion and metastasis

The phenomenon of tumor-associated proteolysis has been acknowledged as a decisive step in the progression of cancer. This short review focuses on the urokinase receptor (u-PAR), a central molecule involved in tumor-associated invasion and metastasis, and summarizes the transcriptional regulation of u-PAR. The urokinase receptor (u-PAR) is a heavily glycosylated cell surface protein and binds the serine protease urokinase specifically and with high affinity. It consists of three similar cysteine-rich repeats and is anchored to the cell membrane via a GPI-anchor. The u-PAR gene comprises 7 exons and is located on chromosome 19q13. Transcriptional activation of the u-PAR promoter region can be induced by binding of transcription factors (Sp1, AP-1, AP-2, NF-kappaB). One current study gives an example for transcriptional downregulation of u-PAR through a PEA3/ets transcriptional silencing element. Knowledge of the molecular regulation of this molecule in tumor cells could be very important for diagnosis and therapy in the near future

Climate impact research: Beyond patchwork

Despite significant progress in climate impact research, the narratives that science can presently piece together of a 2, 3, 4, or 5 °C warmer world remain fragmentary. Here we briefly review past undertakings to characterise comprehensively and quantify climate impacts based on multi-model approaches. We then report on the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), a community-driven effort to compare impact models across sectors and scales systematically, and to quantify the uncertainties along the chain from greenhouse gas emissions and climate input data to the modelling of climate impacts themselves. We show how ISI-MIP and similar efforts can substantially advance the science relevant to impacts, adaptation and vulnerability, and we outline the steps that need to be taken in order to make the most of the available modelling tools. We discuss pertinent limitations of these methods and how they could be tackled. We argue that it is time to consolidate the current patchwork of impact knowledge through integrated cross-sectoral assessments, and that the climate impact community is now in a favourable position to do so

Climate impact research: Beyond patchwork

Despite significant progress in climate impact research, the narratives that science can presently piece together of a 2, 3, 4, or 5 degrees C warmer world remain fragmentary. Here we briefly review past undertakings to characterise comprehensively and quantify climate impacts based on multi-model approaches. We then report on the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), a community-driven effort to compare impact models across sectors and scales systematically, and to quantify the uncertainties along the chain from greenhouse gas emissions and climate input data to the modelling of climate impacts themselves. We show how ISI-MIP and similar efforts can substantially advance the science relevant to impacts, adaptation and vulnerability, and we outline the steps that need to be taken in order to make the most of the available modelling tools. We discuss pertinent limitations of these methods and how they could be tackled. We argue that it is time to consolidate the current patchwork of impact knowledge through integrated cross-sectoral assessments, and that the climate impact community is now in a favourable position to do so

Identification of markers that functionally define a quiescent multiple myeloma cell sub-population surviving bortezomib treatment

The mechanisms allowing residual multiple myeloma (MM) cells to persist after bortezomib (Bz) treatment remain unclear. We hypothesized that studying the biology of bortezomib-surviving cells may reveal markers to identify these cells and survival signals to target and kill residual MM cells.We used H2B-GFP label retention, biochemical tools and in vitro and in vivo experiments to characterize growth arrest and the unfolded protein responses in quiescent Bz-surviving cells. We also tested the effect of a demethylating agent, 5-Azacytidine, on Bz-induced quiescence and whether inhibiting the chaperone GRP78/BiP (henceforth GRP78) with a specific toxin induced apoptosis in Bz-surviving cells. Finally, we used MM patient samples to test whether GRP78 levels might associate with disease progression. Statistical analysis employed t-test and Mann-Whitney tests at a 95% confidence.We report that Bz-surviving MM cells in vitro and in vivo enter quiescence characterized by p21(CIP1) upregulation. Bz-surviving MM cells also downregulated CDK6, Ki67 and P-Rb. H2B-GFP label retention showed that Bz-surviving MM cells are either slow-cycling or deeply quiescent. The Bz-induced quiescence was stabilized by low dose (500nM) of 5-azacytidine (Aza) pre-treatment, which also potentiated the initial Bz-induced apoptosis. We also found that expression of GRP78, an unfolded protein response (UPR) survival factor, persisted in MM quiescent cells. Importantly, GRP78 downregulation using a specific SubAB bacterial toxin killed Bz-surviving MM cells. Finally, quantification of Grp78(high)/CD138+ MM cells from patients suggested that high levels correlated with progressive disease.We conclude that Bz-surviving MM cells display a GRP78(HIGH)/p21(HIGH)/CDK6(LOW)/P-Rb(LOW) profile, and these markers may identify quiescent MM cells capable of fueling recurrences. We further conclude that Aza + Bz treatment of MM may represent a novel strategy to delay recurrences by enhancing Bz-induced apoptosis and quiescence stability.Alfred Adomako, Veronica Calvo, Noa Biran, Keren Osman, Ajai Chari, James C Paton, Adrienne W Paton, Kateri Moore, Denis M Schewe, and Julio A Aguirre-Ghis

Climate and southern Africa's water-energy-food nexus

In southern Africa, the connections between climate and the water-energy-food nexus are strong. Physical and socioeconomic exposure to climate is high in many areas and in crucial economic sectors. Spatial interdependence is also high, driven for example, by the regional extent of many climate anomalies and river basins and aquifers that span national boundaries. There is now strong evidence of the effects of individual climate anomalies, but associations between national rainfall and Gross Domestic Product and crop production remain relatively weak. The majority of climate models project decreases in annual precipitation for southern Africa, typically by as much as 20% by the 2080s. Impact models suggest these changes would propagate into reduced water availability and crop yields. Recognition of spatial and sectoral interdependencies should inform policies, institutions and investments for enhancing water, energy and food security. Three key political and economic instruments could be strengthened for this purpose; the Southern African Development Community, the Southern African Power Pool, and trade of agricultural products amounting to significant transfers of embedded water

Assume-Guarantee Synthesis for Concurrent Reactive Programs with Partial Information

Synthesis of program parts is very useful for concurrent systems. However, most synthesis approaches do not support common design tasks, like modifying a single process without having to re-synthesize or verify the whole system. Assume-guarantee synthesis (AGS) provides robustness against modifications of system parts, but thus far has been limited to the perfect information setting. This means that local variables cannot be hidden from other processes, which renders synthesis results cumbersome or even impossible to realize. We resolve this shortcoming by defining AGS in a partial information setting. We analyze the complexity and decidability in different settings, showing that the problem has a high worst-case complexity and is undecidable in many interesting cases. Based on these observations, we present a pragmatic algorithm based on bounded synthesis, and demonstrate its practical applicability on several examples

A framework for the cross-sectoral integration of multi-model impact projections: land use decisions under climate impacts uncertainties

Climate change and its impacts already pose considerable challenges for societies that will further increase with global warming (IPCC, 2014a, b). Uncertainties of the climatic response to greenhouse gas emissions include the potential passing of large-scale tipping points (e.g. Lenton et al., 2008; Levermann et al., 2012; Schellnhuber, 2010) and changes in extreme meteorological events (Field et al., 2012) with complex impacts on societies (Hallegatte et al., 2013). Thus climate change mitigation is considered a necessary societal response for avoiding uncontrollable impacts (Conference of the Parties, 2010). On the other hand, large-scale climate change mitigation itself implies fundamental changes in, for example, the global energy system. The associated challenges come on top of others that derive from equally important ethical imperatives like the fulfilment of increasing food demand that may draw on the same resources. For example, ensuring food security for a growing population may require an expansion of cropland, thereby reducing natural carbon sinks or the area available for bio-energy production. So far, available studies addressing this problem have relied on individual impact models, ignoring uncertainty in crop model and biome model projections. Here, we propose a probabilistic decision framework that allows for an evaluation of agricultural management and mitigation options in a multi-impactmodel setting. Based on simulations generated within the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), we outline how cross-sectorally consistent multi-model impact simulations could be used to generate the information required for robust decision making. Using an illustrative future land use pattern, we discuss the trade-off between potential gains in crop production and associated losses in natural carbon sinks in the new multiple crop- and biome-model setting. In addition, crop and water model simulations are combined to explore irrigation increases as one possible measure of agricultural intensification that could limit the expansion of cropland required in response to climate change and growing food demand. This example shows that current impact model uncertainties pose an important challenge to long-term mitigation planning and must not be ignored in long-term strategic decision making