Block synchronization for quantum information

Locating the boundaries of consecutive blocks of quantum information is a fundamental building block for advanced quantum computation and quantum communication systems. We develop a coding theoretic method for properly locating boundaries of quantum information without relying on external synchronization when block synchronization is lost. The method also protects qubits from decoherence in a manner similar to conventional quantum error-correcting codes, seamlessly achieving synchronization recovery and error correction. A family of quantum codes that are simultaneously synchronizable and error-correcting is given through this approach.Comment: 7 pages, no figures, final accepted version for publication in Physical Review

Exclusive development of T cell neoplasms in mice transplanted with bone marrow expressing activated Notch alleles

Notch is a highly conserved transmembrane protein that is involved in cell fate decisions and is found in organisms ranging from Drosophila to humans. A human homologue of Notch, TAN1, was initially identified at the chromosomal breakpoint of a subset of T-cell lymphoblastic leukemias/lymphomas containing a t(7;9) chromosomal translocation; however, its role in oncogenesis has been unclear. Using a bone marrow reconstitution assay with cells containing retrovirally transduced TAN1 alleles, we analyzed the oncogenic potential of both nuclear and extranuclear forms of truncated TAN1 in hematopoietic cells. Although the Moloney leukemia virus long terminal repeat drives expression in most hematopoietic cell types, retroviruses encoding either form of the TAN1 protein induced clonal leukemias of exclusively immature T cell phenotypes in approximately 50% of transplanted animals. All tumors overexpressed truncated TAN1 of the size and subcellular localization predicted from the structure of the gene. These results show that TAN1 is an oncoprotein and suggest that truncation and overexpression are important determinants of transforming activity. Moreover, the murine tumors caused by TAN1 in the bone marrow transplant model are very similar to the TAN1-associated human tumors and suggest that TAN1 may be specifically oncotropic for T cells

Testing fluvial erosion models using the transient response of bedrock rivers to tectonic forcing in the Apennines, Italy

The transient response of bedrock rivers to a drop in base level can be used to discriminate between competing fluvial erosion models. However, some recent studies of bedrock erosion conclude that transient river long profiles can be approximately characterized by a transport‐limited erosion model, while other authors suggest that a detachment‐limited model best explains their field data. The difference is thought to be due to the relative volume of sediment being fluxed through the fluvial system. Using a pragmatic approach, we address this debate by testing the ability of end‐member fluvial erosion models to reproduce the well‐documented evolution of three catchments in the central Apennines (Italy) which have been perturbed to various extents by an independently constrained increase in relative uplift rate. The transport‐limited model is unable to account for the catchments’response to the increase in uplift rate, consistent with the observed low rates of sediment supply to the channels. Instead, a detachment‐limited model with a threshold corresponding to the field‐derived median grain size of the sediment plus a slope‐dependent channel width satisfactorily reproduces the overall convex long profiles along the studied rivers. Importantly, we find that the prefactor in the hydraulic scaling relationship is uplift dependent, leading to landscapes responding faster the higher the uplift rate, consistent with field observations. We conclude that a slope‐ dependent channel width and an entrainment/erosion threshold are necessary ingredients when modeling landscape evolution or mapping the distribution of fluvial erosion rates in areas where the rate of sediment supply to channels is low

Predicting the temporal activity patterns of new venues.

Estimating revenue and business demand of a newly opened venue is paramount as these early stages often involve critical decisions such as first rounds of staffing and resource allocation. Traditionally, this estimation has been performed through coarse-grained measures such as observing numbers in local venues or venues at similar places (e.g., coffee shops around another station in the same city). The advent of crowdsourced data from devices and services carried by individuals on a daily basis has opened up the possibility of performing better predictions of temporal visitation patterns for locations and venues. In this paper, using mobility data from Foursquare, a location-centric platform, we treat venue categories as proxies for urban activities and analyze how they become popular over time. The main contribution of this work is a prediction framework able to use characteristic temporal signatures of places together with k-nearest neighbor metrics capturing similarities among urban regions, to forecast weekly popularity dynamics of a new venue establishment in a city neighborhood. We further show how we are able to forecast the popularity of the new venue after one month following its opening by using locality and temporal similarity as features. For the evaluation of our approach we focus on London. We show that temporally similar areas of the city can be successfully used as inputs of predictions of the visit patterns of new venues, with an improvement of 41% compared to a random selection of wards as a training set for the prediction task. We apply these concepts of temporally similar areas and locality to the real-time predictions related to new venues and show that these features can effectively be used to predict the future trends of a venue. Our findings have the potential to impact the design of location-based technologies and decisions made by new business owners

One-Pot Synthesis of 2-Methylfurans from 3- (Trimethylsilyl)propargyl Acetates Promoted by Trimethylsilyl Trifluoromethanesulfonate

In the presence of trimethylsilyl trifluoromethanesulfonate (TMSOTf) and triethylamine, 3-(trimethylsilyl)propargyl carboxylates undergo a one-pot alkylation-cyclization- desilylation reaction with ketones to produce 2-methylfurans. Alkylation at 0 °C in methylene chloride, followed by acid-catalyzed cyclization at room temperature, provides the furans in 52-86% yield. Cyclization and desilylation appear to be promoted by triflic acid generated in situ from the exposure of the reaction mixture to water upon completion of the initial substitution reaction

An Alternative Interpretation of Statistical Mechanics

In this paper I propose an interpretation of classical statistical mechanics that centers on taking seriously the idea that probability measures represent complete states of statistical mechanical systems. I show how this leads naturally to the idea that the stochasticity of statistical mechanics is associated directly with the observables of the theory rather than with the microstates (as traditional accounts would have it). The usual assumption that microstates are representationally significant in the theory is therefore dispensable, a consequence which suggests interesting possibilities for developing non-equilibrium statistical mechanics and investigating inter-theoretic answers to the foundational questions of statistical mechanics

Predicting the temporal activity patterns of new venues

Estimating revenue and business demand of a newly opened venue is paramount as these early stages often involve critical decisions such as first rounds of staffing and resource allocation. Traditionally, this estimation has been performed through coarse-grained measures such as observing numbers in local venues or venues at similar places (e.g., coffee shops around another station in the same city). The advent of crowdsourced data from devices and services carried by individuals on a daily basis has opened up the possibility of performing better predictions of temporal visitation patterns for locations and venues. In this paper, using mobility data from Foursquare, a location-centric platform, we treat venue categories as proxies for urban activities and analyze how they become popular over time. The main contribution of this work is a prediction framework able to use characteristic temporal signatures of places together with k-nearest neighbor metrics capturing similarities among urban regions, to forecast weekly popularity dynamics of a new venue establishment in a city neighborhood. We further show how we are able to forecast the popularity of the new venue after one month following its opening by using locality and temporal similarity as features. For the evaluation of our approach we focus on London. We show that temporally similar areas of the city can be successfully used as inputs of predictions of the visit patterns of new venues, with an improvement of 41% compared to a random selection of wards as a training set for the prediction task. We apply these concepts of temporally similar areas and locality to the real-time predictions related to new venues and show that these features can effectively be used to predict the future trends of a venue. Our findings have the potential to impact the design of location-based technologies and decisions made by new business owners