Fast But Not Furious. When Sped Up Bit Rate of Information Drives Rule Induction

The language abilities of young and adult learners range from memorizing specific items to finding statistical regularities between them (item-bound generalization) and generalizing rules to novel instances (category-based generalization). Both external factors, such as input variability, and internal factors, such as cognitive limitations, have been shown to drive these abilities. However, the exact dynamics between these factors and circumstances under which rule induction emerges remain largely underspecified. Here, we extend our information-theoretic model (Radulescu et al., 2019), based on Shannon’s noisy-channel coding theory, which adds into the “formula” for rule induction the crucial dimension of time: the rate of encoding information by a time-sensitive mechanism. The goal of this study is to test the channel capacity-based hypothesis of our model: if the input entropy per second is higher than the maximum rate of information transmission (bits/second), which is determined by the channel capacity, the encoding method moves gradually from item-bound generalization to a more efficient category-based generalization, so as to avoid exceeding the channel capacity. We ran two artificial grammar experiments with adults, in which we sped up the bit rate of information transmission, crucially not by an arbitrary amount but by a factor calculated using the channel capacity formula on previous data. We found that increased bit rate of information transmission in a repetition-based XXY grammar drove the tendency of learners toward category-based generalization, as predicted by our model. Conversely, we found that increased bit rate of information transmission in complex non-adjacent dependency aXb grammar impeded the item-bound generalization of the specific a_b frames, and led to poorer learning, at least judging by our accuracy assessment method. This finding could show that, since increasing the bit rate of information precipitates a change from item-bound to category-based generalization, it impedes the item-bound generalization of the specific a_b frames, and that it facilitates category-based generalization both for the intervening Xs and possibly for a/b categories. Thus, sped up bit rate does not mean that an unrestrainedly increasing bit rate drives rule induction in any context, or grammar. Rather, it is the specific dynamics between the input entropy and the maximum rate of information transmission

Dynamic Strength of Titin's Z-Disk End

Titin is a giant filamentous protein traversing the half sarcomere of striated muscle with putative functions as diverse as providing structural template, generating elastic response, and sensing and relaying mechanical information. The Z-disk region of titin, which corresponds to the N-terminal end of the molecule, has been thought to be a hot spot for mechanosensing while also serving as anchorage for its sarcomeric attachment. Understanding the mechanics of titin's Z-disk region, particularly under the effect of binding proteins, is of great interest. Here we briefly review recent findings on the structure, molecular associations, and mechanics of titin's Z-disk region. In addition, we report experimental results on the dynamic strength of titin's Z1Z2 domains measured by nanomechanical manipulation of the chemical dimer of a recombinant protein fragment

Lokalna promjenljivost (nestalnost) mehaničkih svojstava tandemskih Ig/segmenata titina

The functionally elastic, I-band part of the myofibrillar protein titin (connectin) contains differentially expressed arrays of serially linked immunoglobulin (Ig)-like domains, the length and composition of which vary among the titin isoforms. The biological rationale of the differential expression as well as the contribution of the Ig domain mechanical characteristics to the overall mechanical behavior of titin are not exactly known. The paper briefly reviews the relevant works that have addressed the Ig-domain mechanics problems and presents the authors’ experimental approach to studying the mechanical behavior of Ig domains. The mechanics of an eight domain segment from the differentially expressed tandem Ig region of titin (I55-62) was studied with an atomic force microscope specially used for stretching single molecules, and the results were compared to known mechanical properties of other domains and segments.Funkcionalno elastična I-vrpca miofibrilarnoga proteina titina (konektina) sadrži razlicito izražene vrste serijski povezanih domena sličnih imunoglobulinu (Ig) čija se duljina i sastav razlikuju u pojedinim titinskim izoformama. Biološki razlozi diferencijalne ekspresije kao i doprinos mehaničkih svojstava domena koje su slične Ig ponašanju titina nisu u cjelosti poznati. U ovom su članku pregledno prikazani dosadašnji relevantni radovi koji se bave problemima mehaničkih svojstava Ig-domena te autorski eksperimentalni pristupi u istraživanju toga problema. U radu su također prikazani rezultati istraživanja mehaničkih svojstava diferencijalno eksprimiranoga tandemskoga Ig-područja titina (155-62), koji se sastoji od osam domena, pomoću mikroskopa atomske snage razlučivanja specijaliziranoga za rastezanje pojedinačne molekule. Ovim postupkom utvrđena mehanička svojstva ispitivanoga dijela titinske molekule uspoređena su s poznatim mehaničkim svojstvima drugih domena i segmenata

LINVIEW: Incremental View Maintenance for Complex Analytical Queries

Many analytics tasks and machine learning problems can be naturally expressed by iterative linear algebra programs. In this paper, we study the incremental view maintenance problem for such complex analytical queries. We develop a framework, called LINVIEW, for capturing deltas of linear algebra programs and understanding their computational cost. Linear algebra operations tend to cause an avalanche effect where even very local changes to the input matrices spread out and infect all of the intermediate results and the final view, causing incremental view maintenance to lose its performance benefit over re-evaluation. We develop techniques based on matrix factorizations to contain such epidemics of change. As a consequence, our techniques make incremental view maintenance of linear algebra practical and usually substantially cheaper than re-evaluation. We show, both analytically and experimentally, the usefulness of these techniques when applied to standard analytics tasks. Our evaluation demonstrates the efficiency of LINVIEW in generating parallel incremental programs that outperform re-evaluation techniques by more than an order of magnitude.Comment: 14 pages, SIGMO

Developed Adomian method for quadratic Kaluza-Klein relativity

We develop and modify the Adomian decomposition method (ADecM) to work for a new type of nonlinear matrix differential equations (MDE's) which arise in general relativity (GR) and possibly in other applications. The approach consists in modifying both the ADecM linear operator with highest order derivative and ADecM polynomials. We specialize in the case of a 4$\times$4 nonlinear MDE along with a scalar one describing stationary cylindrically symmetric metrics in quadratic 5-dimensional GR, derive some of their properties using ADecM and construct the \textit{most general unique power series solutions}. However, because of the constraint imposed on the MDE by the scalar one, the series solutions terminate in closed forms exhausting all possible solutions.Comment: 17 pages (minor changes in reference [30]

Using Performance Forecasting to Accelerate Elasticity

Cloud computing facilitates dynamic resource provisioning. The automation of resource management, known as elasticity, has been subject to much research. In this context, monitoring of a running service plays a crucial role, and adjustments are made when certain thresholds are crossed. On such occasions, it is common practice to simply add or remove resources. In this paper we investigate how we can predict the performance of a service to dynamically adjust allocated resources based on predictions. In other words, instead of “repairing” because a threshold has been crossed, we attempt to stay ahead and allocate an optimized amount of resources in advance. To do so, we need to have accurate predictive models that are based on workloads. We present our approach, based on the Universal Scalability Law, and discuss initial experiments

Asymptotic equivalence of discretely observed diffusion processes and their Euler scheme: small variance case

This paper establishes the global asymptotic equivalence, in the sense of the Le Cam $\Delta$-distance, between scalar diffusion models with unknown drift function and small variance on the one side, and nonparametric autoregressive models on the other side. The time horizon $T$ is kept fixed and both the cases of discrete and continuous observation of the path are treated. We allow non constant diffusion coefficient, bounded but possibly tending to zero. The asymptotic equivalences are established by constructing explicit equivalence mappings.Comment: 21 page