Master Ward Identity for Nonlocal Symmetries in D=2 Principal Chiral Models

We derive, in path integral approach, the (anomalous) master Ward identity associated with an infinite set of nonlocal conservation laws in two-dimensional principal chiral modelsComment: 12 pages, harvmac, minors correction

Activation of miR-9 by human papillomavirus in cervical cancer

Cervical cancer is the third most common cancer in women worldwide, leading to about 300,000 deaths each year. Most cervical cancers are caused by human papillomavirus (HPV) infection. However, persistent transcriptional activity of HPV oncogenes, which indicates active roles of HPV in cervical cancer maintenance and progression, has not been well characterized. Using our recently developed assays for comprehensive profiling of HPV E6/E7 transcripts, we have detected transcriptional activities of 10 high-risk HPV strains from 87 of the 101 cervical tumors included in the analysis. These HPV-positive patients had significantly better survival outcome compared with HPV-negative patients, indicating HPV transcriptional activity as a favorable prognostic marker for cervical cancer. Furthermore, we have determined microRNA (miRNA) expression changes that were correlated with tumor HPV status. Our profiling and functional analyses identified miR-9 as the most activated miRNA by HPV E6 in a p53-independent manner. Further target validation and functional studies showed that HPV-induced miR-9 activation led to significantly increased cell motility by downregulating multiple gene targets involved in cell migration. Thus, our work helps to understand the molecular mechanisms as well as identify potential therapeutic targets for cervical cancer and other HPV-induced cancers

Reinstated episodic context guides sampling-based decisions for reward.

How does experience inform decisions? In episodic sampling, decisions are guided by a few episodic memories of past choices. This process can yield choice patterns similar to model-free reinforcement learning; however, samples can vary from trial to trial, causing decisions to vary. Here we show that context retrieved during episodic sampling can cause choice behavior to deviate sharply from the predictions of reinforcement learning. Specifically, we show that, when a given memory is sampled, choices (in the present) are influenced by the properties of other decisions made in the same context as the sampled event. This effect is mediated by fMRI measures of context retrieval on each trial, suggesting a mechanism whereby cues trigger retrieval of context, which then triggers retrieval of other decisions from that context. This result establishes a new avenue by which experience can guide choice and, as such, has broad implications for the study of decisions

Forecasting Player Behavioral Data and Simulating in-Game Events

Understanding player behavior is fundamental in game data science. Video games evolve as players interact with the game, so being able to foresee player experience would help to ensure a successful game development. In particular, game developers need to evaluate beforehand the impact of in-game events. Simulation optimization of these events is crucial to increase player engagement and maximize monetization. We present an experimental analysis of several methods to forecast game-related variables, with two main aims: to obtain accurate predictions of in-app purchases and playtime in an operational production environment, and to perform simulations of in-game events in order to maximize sales and playtime. Our ultimate purpose is to take a step towards the data-driven development of games. The results suggest that, even though the performance of traditional approaches such as ARIMA is still better, the outcomes of state-of-the-art techniques like deep learning are promising. Deep learning comes up as a well-suited general model that could be used to forecast a variety of time series with different dynamic behaviors

The interface between silicon and a high-k oxide

The ability to follow Moore's Law has been the basis of the tremendous success of the semiconductor industry in the past decades. To date, the greatest challenge for device scaling is the required replacement of silicon dioxide-based gate oxides by high-k oxides in transistors. Around 2010 high-k oxides are required to have an atomically defined interface with silicon without any interfacial SiO2 layer. The first clean interface between silicon and a high-K oxide has been demonstrated by McKee et al. Nevertheless, the interfacial structure is still under debate. Here we report on first-principles calculations of the formation of the interface between silicon and SrTiO3 and its atomic structure. Based on insights into how the chemical environment affects the interface, a way to engineer seemingly intangible electrical properties to meet technological requirements is outlined. The interface structure and its chemistry provide guidance for the selection process of other high-k gate oxides and for controlling their growth. Our study also shows that atomic control of the interfacial structure can dramatically improve the electronic properties of the interface. The interface presented here serves as a model for a variety of other interfaces between high-k oxides and silicon.Comment: 10 pages, 2 figures (one color

PP-wave String Interactions from String Bit Model

We construct the string states $|O_{p}^J>_J$, $|O_{q}^{J_1}>_{{J_1}{J_2}}$ and $|O_{0}^{J_{1}J_{2}}>_{{J_1}{J_2}}$ in the Hilbert space of the quantum mechanical orbifold model so as to calculate the three point functions and the matrix elements of the light-cone Hamiltonian from the interacting string bit model. With these string states we show that the three point functions and the matrix elements of the Hamiltonian derived from the interacting string bit model up to $g^{2}_2$ order precisely match with those computed from the perturbative SYM theory in BMN limit.Comment: 20 pages, no figure, LaTeX, some changes made and references adde

Global Budget and Radiative Forcing of Black Carbon Aerosol: Constraints from Pole-to-Pole (HIPPO) Observations across the Pacific

We use a global chemical transport model (GEOS-Chem) to interpret aircraft curtain observations of black carbon (BC) aerosol over the Pacific from 85°N to 67°S during the 2009–2011 HIAPER (High-Performance Instrumented Airborne Platform for Environmental Research) Pole-to-Pole Observations (HIPPO) campaigns. Observed concentrations are very low, implying much more efficient scavenging than is usually implemented in models. Our simulation with a global source of $6.5 Tg a^{−1}$ and mean tropospheric lifetime of 4.2 days (versus 6.8 ± 1.8 days for the Aerosol Comparisons between Observations and Models (AeroCom) models) successfully simulates BC concentrations in source regions and continental outflow and captures the principal features of the HIPPO data but is still higher by a factor of 2 (1.48 for column loads) over the Pacific. It underestimates BC absorbing aerosol optical depths (AAODs) from the Aerosol Robotic Network by 32% on a global basis. Only 8.7% of global BC loading in GEOS-Chem is above 5 km, versus 21 ± 11% for the AeroCom models, with important implications for radiative forcing estimates. Our simulation yields a global BC burden of 77 Gg, a global mean BC AAOD of 0.0017, and a top-of-atmosphere direct radiative forcing (TOA DRF) of $0.19 W m^{−2}$, with a range of $0.17–0.31 W m^{−2}$ based on uncertainties in the BC atmospheric distribution. Our TOA DRF is lower than previous estimates $(0.27 \pm 0.06 W m^{−2}$ in AeroCom, $0.65–0.9 W m^{−2}$ in more recent studies). We argue that these previous estimates are biased high because of excessive BC concentrations over the oceans and in the free troposphere.Engineering and Applied Science

The influence of C3 and C4 vegetation on soil organic matter dynamics in contrasting semi-natural tropical ecosystems

Variations in the carbon isotopic composition of soil organic matter (SOM) in bulk and fractionated samples were used to assess the influence of C3 and C4 vegetation on SOM dynamics in semi-natural tropical ecosystems sampled along a precipitation gradient in West Africa. Differential patterns in SOM dynamics in C3/C4 mixed ecosystems occurred at various spatial scales. Relative changes in C=N ratios between two contrasting SOM fractions were used to evaluate potential site-scale differences in SOM dynamics between C3- and C4-dominated locations. These differences were strongly controlled by soil texture across the precipitation gradient, with a function driven by bulk 13C and sand content explaining 0.63 of the observed variability. The variation of 13C with soil depth indicated a greater accumulation of C3-derived carbon with increasing precipitation, with this trend also being strongly dependant on soil characteristics. The influence of vegetation thickening on SOM dynamics was also assessed in two adjacent, but structurally contrasting, transitional ecosystems occurring on comparable soils to minimise the confounding effects posed by climatic and edaphic factors. Radiocarbon analyses of sand-size aggregates yielded relatively short mean residence times ( ) even in deep soil layers, while the most stable SOM fraction associated with silt and clay exhibited shorter in the savanna woodland than in the neighbouring forest stand. These results, together with the vertical variation observed in 13C values, strongly suggest that both ecosystems are undergoing a rapid transition towards denser closed canopy formations.However, vegetation thickening varied in intensity at each site and exerted contrasting effects on SOM dynamics. Thisstudy shows that the interdependence between biotic and abiotic factors ultimately determine whether SOM dynamics of C3- and C4-derived vegetation are at variance in ecosystems where both vegetation types coexist. The results highlight the far-reaching implications that vegetation thickening may have for the stability of deep SOM. © 2015, Copernicus Publications