Post Activation Potentiation of Back Squat and Trap Bar Deadlift on Acute Sprint Performance

Please refer to the pdf version of the abstract located adjacent to the title

A Fast Algorithm Finding the Shortest Reset Words

In this paper we present a new fast algorithm finding minimal reset words for finite synchronizing automata. The problem is know to be computationally hard, and our algorithm is exponential. Yet, it is faster than the algorithms used so far and it works well in practice. The main idea is to use a bidirectional BFS and radix (Patricia) tries to store and compare resulted subsets. We give both theoretical and practical arguments showing that the branching factor is reduced efficiently. As a practical test we perform an experimental study of the length of the shortest reset word for random automata with $n$ states and 2 input letters. We follow Skvorsov and Tipikin, who have performed such a study using a SAT solver and considering automata up to $n=100$ states. With our algorithm we are able to consider much larger sample of automata with up to $n=300$ states. In particular, we obtain a new more precise estimation of the expected length of the shortest reset word $\approx 2.5\sqrt{n-5}$.Comment: COCOON 2013. The final publication is available at http://link.springer.com/chapter/10.1007%2F978-3-642-38768-5_1

Correlation Structures of Correlated Binomial Models and Implied Default Distribution

We show how to analyze and interpret the correlation structures, the conditional expectation values and correlation coefficients of exchangeable Bernoulli random variables. We study implied default distributions for the iTraxx-CJ tranches and some popular probabilistic models, including the Gaussian copula model, Beta binomial distribution model and long-range Ising model. We interpret the differences in their profiles in terms of the correlation structures. The implied default distribution has singular correlation structures, reflecting the credit market implications. We point out two possible origins of the singular behavior.Comment: 16 pages, 7 figure

An Agent-Based Model of Collective Emotions in Online Communities

We develop a agent-based framework to model the emergence of collective emotions, which is applied to online communities. Agents individual emotions are described by their valence and arousal. Using the concept of Brownian agents, these variables change according to a stochastic dynamics, which also considers the feedback from online communication. Agents generate emotional information, which is stored and distributed in a field modeling the online medium. This field affects the emotional states of agents in a non-linear manner. We derive conditions for the emergence of collective emotions, observable in a bimodal valence distribution. Dependent on a saturated or a superlinear feedback between the information field and the agent's arousal, we further identify scenarios where collective emotions only appear once or in a repeated manner. The analytical results are illustrated by agent-based computer simulations. Our framework provides testable hypotheses about the emergence of collective emotions, which can be verified by data from online communities.Comment: European Physical Journal B (in press), version 2 with extended introduction, clarification

Low cobalt inventories in the Amundsen and Ross seas driven by high demand for labile cobalt uptake among native phytoplankton communities

Cobalt (Co) is a scarce but essential micronutrient for marine plankton in the Southern Ocean and coastal Antarctic seas, where dissolved cobalt (dCo) concentrations can be extremely low. This study presents total dCo and labile dCo distributions measured via shipboard voltammetry in the Amundsen Sea, the Ross Sea and Terra Nova Bay during the CICLOPS (Cobalamin and Iron Co-Limitation of Phytoplankton Species) expedition. A significantly smaller dCo inventory was observed during the 2017/2018 CICLOPS expedition compared to two 2005/2006 expeditions to the Ross Sea conducted over a decade earlier. The dCo inventory loss (∼ 10–20 pM) was present in both the surface and deep ocean and was attributed to the loss of labile dCo, resulting in the near-complete complexation of dCo by strong ligands in the photic zone. A changing dCo inventory in Antarctic coastal seas could be driven by the alleviation of iron (Fe) limitation in coastal areas, where the flux of Fe-rich sediments from melting ice shelves and deep sediment resuspension may have shifted the region towards vitamin B12 and/or zinc (Zn) limitation, both of which are likely to increase the demand for Co among marine plankton. High demand for Zn by phytoplankton can result in increased Co and cadmium (Cd) uptake because these metals often share the same metal uptake transporters. This study compared the magnitudes and ratios of Zn, Cd and Co uptake (ρ) across upper-ocean profiles and the observed order-of-magnitude uptake trends (ρZn &gt; ρCd &gt; ρCo) that paralleled the trace metal concentrations in seawater. High rates of Co and Zn uptake were observed throughout the region, and the speciation of available Co and Zn appeared to influence trends in dissolved metal : phosphate stoichiometry and uptake rates over depth. Multi-year loss of the dCo inventory throughout the water column may be explained by an increase in Co uptake into particulate organic matter and subsequently an increased flux of Co into sediments via sinking and burial. This perturbation of the Southern Ocean Co biogeochemical cycle could signal changes in the nutrient limitation regimes, phytoplankton bloom composition and carbon sequestration sink of the Southern Ocean.</p

Observation of magnetic vortex pairs at room temperature in a planar {\alpha}-Fe2O3/Co heterostructure

Vortices are among the simplest topological structures, and occur whenever a flow field `whirls' around a one-dimensional core. They are ubiquitous to many branches of physics, from fluid dynamics to superconductivity and superfluidity, and are even predicted by some unified theories of particle interactions, where they might explain some of the largest-scale structures seen in today's Universe. In the crystalline state, vortex formation is rare, since it is generally hampered by long-range interactions: in ferroic materials (ferromagnetic and ferroelectric), vortices are only observed when the effects of the dipole-dipole interaction is modified by confinement at the nanoscale, or when the parameter associated with the vorticity does not couple directly with strain. Here, we present the discovery of a novel form of vortices in antiferromagnetic (AFM) hematite ($\alpha$-Fe$_2$O$_3$) epitaxial films, in which the primary whirling parameter is the staggered magnetisation. Remarkably, ferromagnetic (FM) topological objects with the same vorticity and winding number of the $\alpha$-Fe$_2$O$_3$ vortices are imprinted onto an ultra-thin Co ferromagnetic over-layer by interfacial exchange. Our data suggest that the ferromagnetic vortices may be merons (half-skyrmions, carrying an out-of-plane core magnetisation), and indicate that the vortex/meron pairs can be manipulated by the application of an in-plane magnetic field, H$_{\parallel}$, giving rise to large-scale vortex-antivortex annihilation.Comment: 16 pages, 4 figure

Using a runway paradigm to assess the relative strength of rats' motivations for enrichment objects

Laboratory animals should be provided with enrichment objects in their cages; however, it is first necessary to test whether the proposed enrichment objects provide benefits that increase the animals’ welfare. The two main paradigms currently used to assess proposed enrichment objects are the choice test, which is limited to determining relative frequency of choice, and consumer demand studies, which can indicate the strength of a preference but are complex to design. Here, we propose a third methodology: a runway paradigm, which can be used to assess the strength of an animal’s motivation for enrichment objects, is simpler to use than consumer demand studies, and is faster to complete than typical choice tests. Time spent with objects in a standard choice test was used to rank several enrichment objects in order to compare with the ranking found in our runway paradigm. The rats ran significantly more times, ran faster, and interacted longer with objects with which they had previously spent the most time. It was concluded that this simple methodology is suitable for measuring rats’ motivation to reach enrichment objects. This can be used to assess the preference for different types of enrichment objects or to measure reward system processes

Emergence of good conduct, scaling and Zipf laws in human behavioral sequences in an online world

We study behavioral action sequences of players in a massive multiplayer online game. In their virtual life players use eight basic actions which allow them to interact with each other. These actions are communication, trade, establishing or breaking friendships and enmities, attack, and punishment. We measure the probabilities for these actions conditional on previous taken and received actions and find a dramatic increase of negative behavior immediately after receiving negative actions. Similarly, positive behavior is intensified by receiving positive actions. We observe a tendency towards anti-persistence in communication sequences. Classifying actions as positive (good) and negative (bad) allows us to define binary 'world lines' of lives of individuals. Positive and negative actions are persistent and occur in clusters, indicated by large scaling exponents alpha~0.87 of the mean square displacement of the world lines. For all eight action types we find strong signs for high levels of repetitiveness, especially for negative actions. We partition behavioral sequences into segments of length n (behavioral `words' and 'motifs') and study their statistical properties. We find two approximate power laws in the word ranking distribution, one with an exponent of kappa-1 for the ranks up to 100, and another with a lower exponent for higher ranks. The Shannon n-tuple redundancy yields large values and increases in terms of word length, further underscoring the non-trivial statistical properties of behavioral sequences. On the collective, societal level the timeseries of particular actions per day can be understood by a simple mean-reverting log-normal model.Comment: 6 pages, 5 figure

Positive words carry less information than negative words

We show that the frequency of word use is not only determined by the word length \cite{Zipf1935} and the average information content \cite{Piantadosi2011}, but also by its emotional content. We have analyzed three established lexica of affective word usage in English, German, and Spanish, to verify that these lexica have a neutral, unbiased, emotional content. Taking into account the frequency of word usage, we find that words with a positive emotional content are more frequently used. This lends support to Pollyanna hypothesis \cite{Boucher1969} that there should be a positive bias in human expression. We also find that negative words contain more information than positive words, as the informativeness of a word increases uniformly with its valence decrease. Our findings support earlier conjectures about (i) the relation between word frequency and information content, and (ii) the impact of positive emotions on communication and social links.Comment: 16 pages, 3 figures, 3 table