Crops of the parkland – Yorkton, Saskatchewan

Non-Peer Reviewe

Dynamic Modulation of the Action Observation Network by Movement Familiarity

Contains fulltext : 139821.pdf (publisher's version ) (Open Access)When watching another person's actions, a network of sensorimotor brain regions, collectively termed the action observation network (AON), is engaged. Previous research suggests that the AON is more responsive when watching familiar compared with unfamiliar actions. However, most research into AON function is premised on comparisons of AON engagement during different types of task using univariate, magnitude- based approaches. To better understand the relationship between action familiarity and AON engagement, here we examine how observed movement familiarity modulates AON activity in humans using dynamic causal modeling, a type of effective connectivity analysis. Twenty- one subjects underwent fMRI scanning while viewing whole- body dance movements that varied in terms of their familiarity. Participants' task was to either predict the next posture the dancer's body would assume or to respond to a nonaction- related attentional control question. To assess individuals' familiarity with each movement, participants rated each video on a measure of visual familiarity after being scanned. Parametric analyses showed more activity in left middle temporal gyrus, inferior parietal lobule, and inferior frontal gyrus as videos were rated as increasingly familiar. These clusters of activity formed the regions of interest for dynamic causal modeling analyses, which revealed attenuation of effective connectivity bidirectionally between parietal and temporalAONnodes when participants observed videos they rated as increasingly familiar. As such, the findings provide partial support for a predictive coding model of the AON, as well as illuminate how action familiarity manipulations can be used to explore simulation based accounts of action understanding.12 p

Improving scenario methods in infrastructure planning: a case study of long distance travel and mobility in the uk under extreme weather uncertainty and a changing climate

This paper develops a mixed method approach to infrastructure planning through a United Kingdom (UK) case study examining the impact of a changing climate on long distance travel and mobility between London and Glasgow. A novel combination of a qualitative method - Systematic Qualitative Foresight (SQF) - and quantitative simulation using discrete choice stated preference methods is applied. The main dataset is a travel behaviour survey of over 2,000 residents of London and Glasgow. Three illustrative SQF-based scenarios are developed incorporating society, technology and climate dimensions. For each scenario, the choice of long-distance travel mode by two groups of respondents generated by cluster analysis is simulated using stated preference survey data to describe the choices likely to be made by actors within each scenario. We demonstrate the importance of considering a wide range of variables when creating instruments for infrastructure planning decisions. Our results show that weather-related disruption has consequences for travel behaviour, with a considerable number of travellers deciding not to travel despite the importance of their trip. However, the vast majority of travellers would still travel. This should be considered by policy makers, and those responsible for transport infrastructure, in order to increase its resilience to extreme weather and demand, and better devise contingencies plans to contain, and minimise, the effect of the disruptions on the users. The method described has wider implications for infrastructure planning, particularly in its ability to engage a broader range of stakeholders and to avoid linear models of prediction. By emphasising the creation of a plausible decision space, it offers the possibility of increased robustness and resilience in infrastructure planning

Visions, values, and videos: Revisiting envisionings in service of UbiComp design for the home

UbiComp has been envisioned to bring about a future dominated by calm computing technologies making our everyday lives ever more convenient. Yet the same vision has also attracted criticism for encouraging a solitary and passive lifestyle. The aim of this paper is to explore and elaborate these tensions further by examining the human values surrounding future domestic UbiComp solutions. Drawing on envisioning and contravisioning, we probe members of the public (N=28) through the presentation and focus group discussion of two contrasting animated video scenarios, where one is inspired by 'calm' and the other by 'engaging' visions of future UbiComp technology. By analysing the reasoning of our participants, we identify and elaborate a number of relevant values involved in balancing the two perspectives. In conclusion, we articulate practically applicable takeaways in the form of a set of key design questions and challenges

From Hurwitz numbers to Kontsevich-Witten tau-function: a connection by Virasoro operators

In this letter,we present our conjecture on the connection between the Kontsevich--Witten and the Hurwitz tau-functions. The conjectural formula connects these two tau-functions by means of the $GL(\infty)$ group element. An important feature of this group element is its simplicity: this is a group element of the Virasoro subalgebra of $gl(\infty)$. If proved, this conjecture would allow to derive the Virasoro constraints for the Hurwitz tau-function, which remain unknown in spite of existence of several matrix model representations, as well as to give an integrable operator description of the Kontsevich--Witten tau-function.Comment: 13 page

Quantum curves for Hitchin fibrations and the Eynard-Orantin theory

We generalize the topological recursion of Eynard-Orantin (2007) to the family of spectral curves of Hitchin fibrations. A spectral curve in the topological recursion, which is defined to be a complex plane curve, is replaced with a generic curve in the cotangent bundle $T^*C$ of an arbitrary smooth base curve $C$. We then prove that these spectral curves are quantizable, using the new formalism. More precisely, we construct the canonical generators of the formal $\hbar$-deformation family of $D$-modules over an arbitrary projective algebraic curve $C$ of genus greater than $1$, from the geometry of a prescribed family of smooth Hitchin spectral curves associated with the $SL(2,\mathbb{C})$-character variety of the fundamental group $\pi_1(C)$. We show that the semi-classical limit through the WKB approximation of these $\hbar$-deformed $D$-modules recovers the initial family of Hitchin spectral curves.Comment: 34 page

Boreal forest CO2 exchange and evapotranspiration predicted by nine ecosystem process models: Intermodel comparisons and relationships to field measurements

Nine ecosystem process models were used to predict CO2 and water vapor exchanges by a 150-year-old black spruce forest in central Canada during 1994–1996 to evaluate and improve the models. Three models had hourly time steps, five had daily time steps, and one had monthly time steps. Model input included site ecosystem characteristics and meteorology. Model predictions were compared to eddy covariance (EC) measurements of whole-ecosystem CO2exchange and evapotranspiration, to chamber measurements of nighttime moss-surface CO2release, and to ground-based estimates of annual gross primary production, net primary production, net ecosystem production (NEP), plant respiration, and decomposition. Model-model differences were apparent for all variables. Model-measurement agreement was good in some cases but poor in others. Modeled annual NEP ranged from −11 g C m−2 (weak CO2source) to 85 g C m−2 (moderate CO2 sink). The models generally predicted greater annual CO2sink activity than measured by EC, a discrepancy consistent with the fact that model parameterizations represented the more productive fraction of the EC tower “footprint.” At hourly to monthly timescales, predictions bracketed EC measurements so median predictions were similar to measurements, but there were quantitatively important model-measurement discrepancies found for all models at subannual timescales. For these models and input data, hourly time steps (and greater complexity) compared to daily time steps tended to improve model-measurement agreement for daily scale CO2 exchange and evapotranspiration (as judged by root-mean-squared error). Model time step and complexity played only small roles in monthly to annual predictions

Accurate sample assignment in a multiplexed, ultrasensitive, high-throughput sequencing assay for minimal residual disease

High-throughput sequencing (HTS) (next-generation sequencing) of the rearranged Ig and T-cell receptor genes promises to be less expensive and more sensitive than current methods of monitoring minimal residual disease (MRD) in patients with acute lymphoblastic leukemia. However, the adoption of new approaches by clinical laboratories requires careful evaluation of all potential sources of error and the development of strategies to ensure the highest accuracy. Timely and efficient clinical use of HTS platforms will depend on combining multiple samples (multiplexing) in each sequencing run. Here we examine the Ig heavy-chain gene HTS on the Illumina MiSeq platform for MRD. We identify errors associated with multiplexing that could potentially impact the accuracy of MRD analysis. We optimize a strategy that combines high-purity, sequence-optimized oligonucleotides, dual indexing, and an error-aware demultiplexing approach to minimize errors and maximize sensitivity. We present a probability-based, demultiplexing pipeline Error-Aware Demultiplexer that is suitable for all MiSeq strategies and accurately assigns samples to the correct identifier without excessive loss of data. Finally, using controls quantified by digital PCR, we show that HTS-MRD can accurately detect as few as 1 in 10(6) copies of specific leukemic MRD