Lower limb stiffness estimation during running: the effect of using kinematic constraints in muscle force optimization algorithms

The focus of this paper is on the effect of muscle force optimization algorithms on the human lower limb stiffness estimation. By using a forward dynamic neuromusculoskeletal model coupled with a muscle short-range stiffness model we computed the human joint stiffness of the lower limb during running. The joint stiffness values are calculated using two different muscle force optimization procedures, namely: Toque-based and Torque/Kinematic-based algorithm. A comparison between the processed EMG signal and the corresponding estimated muscle forces with the two optimization algorithms is provided. We found that the two stiffness estimates are strongly influenced by the adopted algorithm. We observed different magnitude and timing of both the estimated muscle forces and joint stiffness time profile with respect to each gait phase, as function of the optimization algorithm used

Looking Under the Hood : Tools for Diagnosing your Question Answering Engine

In this paper we analyze two question answering tasks : the TREC-8 question answering task and a set of reading comprehension exams. First, we show that Q/A systems perform better when there are multiple answer opportunities per question. Next, we analyze common approaches to two subproblems: term overlap for answer sentence identification, and answer typing for short answer extraction. We present general tools for analyzing the strengths and limitations of techniques for these subproblems. Our results quantify the limitations of both term overlap and answer typing to distinguish between competing answer candidates.Comment: Revision of paper appearing in the Proceedings of the Workshop on Open-Domain Question Answerin

A comparative framework: how broadly applicable is a 'rigorous' critical junctures framework?

The paper tests Hogan and Doyle's (2007, 2008) framework for examining critical junctures. This framework sought to incorporate the concept of ideational change in understanding critical junctures. Until its development, frameworks utilized in identifying critical junctures were subjective, seeking only to identify crisis, and subsequent policy changes, arguing that one invariably led to the other, as both occurred around the same time. Hogan and Doyle (2007, 2008) hypothesized ideational change as an intermediating variable in their framework, determining if, and when, a crisis leads to radical policy change. Here we test this framework on cases similar to, but different from, those employed in developing the exemplar. This will enable us determine whether the framework's relegation of ideational change to a condition of crisis holds, or, if ideational change has more importance than is ascribed to it by this framework. This will also enable us determined if the framework itself is robust, and fit for the purposes it was designed to perform — identifying the nature of policy change

Abundance Measurements of Titan's Stratospheric HCN, HC3_3N, C3_3H4_4, and CH3_3CN from ALMA Observations

Previous investigations have employed more than 100 close observations of Titan by the Cassini orbiter to elucidate connections between the production and distribution of Titan's vast, organic-rich chemical inventory and its atmospheric dynamics. However, as Titan transitions into northern summer, the lack of incoming data from the Cassini orbiter presents a potential barrier to the continued study of seasonal changes in Titan's atmosphere. In our previous work (Thelen et al., 2018), we demonstrated that the Atacama Large Millimeter/submillimeter Array (ALMA) is well suited for measurements of Titan's atmosphere in the stratosphere and lower mesosphere (~100-500 km) through the use of spatially resolved (beam sizes <1'') flux calibration observations of Titan. Here, we derive vertical abundance profiles of four of Titan's trace atmospheric species from the same 3 independent spatial regions across Titan's disk during the same epoch (2012 to 2015): HCN, HC$_3$N, C$_3$H$_4$, and CH$_3$CN. We find that Titan's minor constituents exhibit large latitudinal variations, with enhanced abundances at high latitudes compared to equatorial measurements; this includes CH$_3$CN, which eluded previous detection by Cassini in the stratosphere, and thus spatially resolved abundance measurements were unattainable. Even over the short 3-year period, vertical profiles and integrated emission maps of these molecules allow us to observe temporal changes in Titan's atmospheric circulation during northern spring. Our derived abundance profiles are comparable to contemporary measurements from Cassini infrared observations, and we find additional evidence for subsidence of enriched air onto Titan's south pole during this time period. Continued observations of Titan with ALMA beyond the summer solstice will enable further study of how Titan's atmospheric composition and dynamics respond to seasonal changes.Comment: 15 pages, 16 figures, 2 tables. Accepted for publication in Icarus, September 201

Deep Depth From Focus

Depth from focus (DFF) is one of the classical ill-posed inverse problems in computer vision. Most approaches recover the depth at each pixel based on the focal setting which exhibits maximal sharpness. Yet, it is not obvious how to reliably estimate the sharpness level, particularly in low-textured areas. In this paper, we propose `Deep Depth From Focus (DDFF)' as the first end-to-end learning approach to this problem. One of the main challenges we face is the hunger for data of deep neural networks. In order to obtain a significant amount of focal stacks with corresponding groundtruth depth, we propose to leverage a light-field camera with a co-calibrated RGB-D sensor. This allows us to digitally create focal stacks of varying sizes. Compared to existing benchmarks our dataset is 25 times larger, enabling the use of machine learning for this inverse problem. We compare our results with state-of-the-art DFF methods and we also analyze the effect of several key deep architectural components. These experiments show that our proposed method `DDFFNet' achieves state-of-the-art performance in all scenes, reducing depth error by more than 75% compared to the classical DFF methods.Comment: accepted to Asian Conference on Computer Vision (ACCV) 201

The role of auditory cortices in the retrieval of single-trial auditory-visual object memories.

Single-trial encounters with multisensory stimuli affect both memory performance and early-latency brain responses to visual stimuli. Whether and how auditory cortices support memory processes based on single-trial multisensory learning is unknown and may differ qualitatively and quantitatively from comparable processes within visual cortices due to purported differences in memory capacities across the senses. We recorded event-related potentials (ERPs) as healthy adults (n = 18) performed a continuous recognition task in the auditory modality, discriminating initial (new) from repeated (old) sounds of environmental objects. Initial presentations were either unisensory or multisensory; the latter entailed synchronous presentation of a semantically congruent or a meaningless image. Repeated presentations were exclusively auditory, thus differing only according to the context in which the sound was initially encountered. Discrimination abilities (indexed by d') were increased for repeated sounds that were initially encountered with a semantically congruent image versus sounds initially encountered with either a meaningless or no image. Analyses of ERPs within an electrical neuroimaging framework revealed that early stages of auditory processing of repeated sounds were affected by prior single-trial multisensory contexts. These effects followed from significantly reduced activity within a distributed network, including the right superior temporal cortex, suggesting an inverse relationship between brain activity and behavioural outcome on this task. The present findings demonstrate how auditory cortices contribute to long-term effects of multisensory experiences on auditory object discrimination. We propose a new framework for the efficacy of multisensory processes to impact both current multisensory stimulus processing and unisensory discrimination abilities later in time

Visuomotor Entrainment and the Frequency-Dependent Response of Walking Balance to Perturbations

Visuomotor entrainment, or the synchronization of motor responses to visual stimuli, is a naturally emergent phenomenon in human standing. Our purpose was to investigate the prevalence and resolution of visuomotor entrainment in walking and the frequency-dependent response of walking balance to perturbations. We used a virtual reality environment to manipulate optical flow in ten healthy young adults during treadmill walking. A motion capture system recorded trunk, sacrum, and heel marker trajectories during a series of 3-min conditions in which we perturbed a virtual hallway mediolaterally with systematic changes in the driving frequencies of perceived motion. We quantified visuomotor entrainment using spectral analyses and changes in balance control using trunk sway, gait variability, and detrended fluctuation analyses (DFA). ML kinematics were highly sensitive to visual perturbations, and instinctively synchronized (i.e., entrained) to a broad range of driving frequencies of perceived ML motion. However, the influence of visual perturbations on metrics of walking balance was frequency-dependent and governed by their proximity to stride frequency. Specifically, we found that a driving frequency nearest to subjects' average stride frequency uniquely compromised trunk sway, gait variability, and step-to-step correlations. We conclude that visuomotor entrainment is a robust and naturally emerging phenomenon during human walking, involving coordinated and frequency-dependent adjustments in trunk sway and foot placement to maintain balance at the whole-body level. These findings provide mechanistic insight into how the visuomotor control of walking balance is disrupted by visual perturbations and important reference values for the emergence of balance deficits due to age, injury, or disease

Loss of CLN7 results in depletion of soluble lysosomal proteins and impaired mTOR reactivation

Defects in the MFSD8 gene encoding the lysosomal membrane protein CLN7 lead to CLN7 disease, a neurodegenerative lysosomal storage disorder belonging to the group of neuronal ceroid lipofuscinoses (NCLs). Here we have performed a SILAC-based quantitative analysis of the lysosomal proteome using Cln7-deficient mouse embryonic fibroblasts (MEFs) from a Cln7 knockout (ko) mouse model. From 3335 different proteins identified, we detected 56 soluble lysosomal proteins and 29 highly abundant lysosomal membrane proteins. Quantification revealed that the amounts of 12 different soluble lysosomal proteins were significantly reduced in Cln7 ko MEFs compared with wild type controls. One of the most significantly depleted lysosomal proteins was Cln5 protein that underlies another distinct NCL disorder. Expression analyses showed that the mRNA expression, biosynthesis, intracellular sorting and proteolytic processing of Cln5 were not affected, whereas the depletion of mature Cln5 protein was due to increased proteolytic degradation by cysteine proteases in Cln7 ko lysosomes. Considering the similar phenotypes of CLN5 and CLN7 patients, our data suggest that depletion of CLN5 may play an important part in the pathogenesis of CLN7 disease. In addition, we found a defect in the ability of Cln7 ko MEFs to adapt to starvation conditions as shown by impaired mammalian target of rapamycin complex 1 reactivation, reduced autolysosome tubulation and increased perinuclear accumulation of autolysosomes compared to controls. In summary, depletion of multiple soluble lysosomal proteins suggest a critical role of CLN7 for lysosomal function, which may contribute to the pathogenesis and progression of CLN7 disease