Coupling of transverse and longitudinal response in stiff polymers

The time-dependent transverse response of stiff polymers, represented as weakly-bending wormlike chains (WLCs), is well-understood on the linear level, where transverse degrees of freedom evolve independently from the longitudinal ones. We show that, beyond a characteristic time scale, the nonlinear coupling of transverse and longitudinal motion in an inextensible WLC significantly weakens the polymer response compared to the widely used linear response predictions. The corresponding feedback mechanism is rationalized by scaling arguments and quantified by a multiple scale approach that exploits an inherent separation of transverse and longitudinal correlation length scales. Crossover scaling laws and exact analytical and numerical solutions for characteristic response quantities are derived for different experimentally relevant setups. Our findings are applicable to cytoskeletal filaments as well as DNA under tension.Comment: 4 pages, 3 figures, 1 table; final versio

Spin fluctuations in the 0.7-anomaly in quantum point contacts

It has been argued that the 0.7 anomaly in quantum point contacts (QPCs) is due to an enhanced density of states at the top of the QPC-barrier (van Hove ridge), which strongly enhances the effects of interactions. Here, we analyze their effect on dynamical quantities. We find that they pin the van Hove ridge to the chemical potential when the QPC is subopen; cause a temperature dependence for the linear conductance that qualitatively agrees with experiment; strongly enhance the magnitude of the dynamical spin susceptibility; and significantly lengthen the QPC traversal time. We conclude that electrons traverse the QPC via a slowly fluctuating spin structure of finite spatial extent

Disruptive events in high-density cellular networks

Stochastic geometry models are used to study wireless networks, particularly cellular phone networks, but most of the research focuses on the typical user, often ignoring atypical events, which can be highly disruptive and of interest to network operators. We examine atypical events when a unexpected large proportion of users are disconnected or connected by proposing a hybrid approach based on ray launching simulation and point process theory. This work is motivated by recent results using large deviations theory applied to the signal-to-interference ratio. This theory provides a tool for the stochastic analysis of atypical but disruptive events, particularly when the density of transmitters is high. For a section of a European city, we introduce a new stochastic model of a single network cell that uses ray launching data generated with the open source RaLaNS package, giving deterministic path loss values. We collect statistics on the fraction of (dis)connected users in the uplink, and observe that the probability of an unexpected large proportion of disconnected users decreases exponentially when the transmitter density increases. This observation implies that denser networks become more stable in the sense that the probability of the fraction of (dis)connected users deviating from its mean, is exponentially small. We also empirically obtain and illustrate the density of users for network configurations in the disruptive event, which highlights the fact that such bottleneck behaviour not only stems from too many users at the cell boundary, but also from the near-far effect of many users in the immediate vicinity of the base station. We discuss the implications of these findings and outline possible future research directions.Comment: 8 pages, 11 figure

Extended Initiality for Typed Abstract Syntax

Initial Semantics aims at interpreting the syntax associated to a signature as the initial object of some category of 'models', yielding induction and recursion principles for abstract syntax. Zsid\'o proves an initiality result for simply-typed syntax: given a signature S, the abstract syntax associated to S constitutes the initial object in a category of models of S in monads. However, the iteration principle her theorem provides only accounts for translations between two languages over a fixed set of object types. We generalize Zsid\'o's notion of model such that object types may vary, yielding a larger category, while preserving initiality of the syntax therein. Thus we obtain an extended initiality theorem for typed abstract syntax, in which translations between terms over different types can be specified via the associated category-theoretic iteration operator as an initial morphism. Our definitions ensure that translations specified via initiality are type-safe, i.e. compatible with the typing in the source and target language in the obvious sense. Our main example is given via the propositions-as-types paradigm: we specify propositions and inference rules of classical and intuitionistic propositional logics through their respective typed signatures. Afterwards we use the category--theoretic iteration operator to specify a double negation translation from the former to the latter. A second example is given by the signature of PCF. For this particular case, we formalize the theorem in the proof assistant Coq. Afterwards we specify, via the category-theoretic iteration operator, translations from PCF to the untyped lambda calculus

Argon metastable dynamics in a filamentary jet micro-discharge at atmospheric pressure

Space and time resolved concentrations of Ar ($^{3}P_2$) metastable atoms at the exit of an atmospheric pressure radio-frequency micro-plasma jet were measured using tunable diode laser absorption spectroscopy. The discharge features a coaxial geometry with a hollow capillary as an inner electrode and a ceramic tube with metal ring as outer electrode. Absorption profiles of metastable atoms as well as optical emission measurements reveal the dynamics and the filamentary structure of the discharge. The average spatial distribution of Ar metastables is characterized with and without a target in front of the jet, showing that the target potential and therewith the electric field distribution substantially changes the filaments' expansion. Together with the detailed analysis of the ignition phase and the discharge's behavior under pulsed operation, the results give an insight into the excitation and de-excitation mechanisms

Transcranial electric stimulation for the investigation of speech perception and comprehension.

Transcranial electric stimulation (tES), comprising transcranial direct current stimulation (tDCS) and transcranial alternating current stimulation (tACS), involves applying weak electrical current to the scalp, which can be used to modulate membrane potentials and thereby modify neural activity. Critically, behavioural or perceptual consequences of this modulation provide evidence for a causal role of neural activity in the stimulated brain region for the observed outcome. We present tES as a tool for the investigation of which neural responses are necessary for successful speech perception and comprehension. We summarise existing studies, along with challenges that need to be overcome, potential solutions, and future directions. We conclude that, although standardised stimulation parameters still need to be established, tES is a promising tool for revealing the neural basis of speech processing. Future research can use this method to explore the causal role of brain regions and neural processes for the perception and comprehension of speech

A Self-Service Supporting Business Intelligence and Big Data Analytics Architecture

Self-service Business Intelligence (SSBI) is an emerging topic for many companies. Casual users should be enabled to independently build their own analyses and reports. This accelerates and simplifies the decision-making processes. Although recent studies began to discuss parts of a self-service environment, none of these present a comprehensive architecture. Following a design science research approach, this study proposes a new self-service oriented BI architecture in order to address this gap. Starting from an in-depth literature review, an initial model was developed and improved by qualitative data analysis from interviews with 18 BI and IT specialists form companies across different industries. The proposed architecture model demonstrates the interaction between introduced self-service elements with each other and with traditional BI components. For example, we look at the integration of collaboration rooms and a self-learning knowledge database that aims to be a source for a report recommender