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It is widely accepted that the famous Tartini's third tone, i.e., the appearance of an additional third tone of lower frequency when playing a dyad on the violin, is a subjective phenomenon generated by the listener's cochlear nonlinearity. However, the recent demonstration that additional tones of audible amplitude can also be generated by the violin itself during playing of a dyad (violin combination tones), raises the question if these tones might have influenced Tartini's third sound perception. The experiments reported here were made to ascertain this possibility. To this end, following Tartini experiments, several dyads played by either one violin or two violins playing one note of the dyad each, were recorded. The analysis of the spectra shows that violin combination tones are present in all the dyads investigated, but exclusively when the dyad is played by a single violin and not when the same dyad is played by two violins. Tartini found the third tones to be the same in both conditions, which means that violin combination tones in his experiments were either absent or too small to affect the perception of the subjective third tones arising from cochlear distortion.

Drawing an inspiration from behavioral studies of human decision making, we propose here a more general and flexible parametric framework for reinforcement learning that extends standard Q-learning to a two-stream model for processing positive and negative rewards, and allows to incorporate a wide range of reward-processing biases -- an important component of human decision making which can help us better understand a wide spectrum of multi-agent interactions in complex real-world socioeconomic systems, as well as various neuropsychiatric conditions associated with disruptions in normal reward processing. From the computational perspective, we observe that the proposed Split-QL model and its clinically inspired variants consistently outperform standard Q-Learning and SARSA methods, as well as recently proposed Double Q-Learning approaches, on simulated tasks with particular reward distributions, a real-world dataset capturing human decision-making in gambling tasks, and the Pac-Man game in a lifelong learning setting across different reward stationarities., Published in AAMAS 2020 as a full paper. This article supersedes our work arXiv:1706.02897 into RL setting and extends extensively into RL games, cognitive modeling, and gambling tasks in lifelong learning setting

Background: Angiopoietin 1 and 2 regulate angiogenesis and vascular remodelling by interacting with the tyrosine kinase receptor Tie2, and inhibition of angiogenesis has shown promise in the treatment of ovarian cancer. We aimed to assess whether trebananib, a peptibody that inhibits binding of angiopoietin 1 and 2 to Tie2, improved progression-free survival when added to carboplatin and paclitaxel as first-line therapy in advanced epithelial ovarian, primary fallopian tube, or peritoneal cancer in a phase 3 clinical trial. Methods: TRINOVA-3, a multicentre, multinational, phase 3, double-blind study, was done at 206 investigational sites (hospitals and cancer centres)in 14 countries. Eligible patients were aged 18 years or older with biopsy-confirmed International Federation of Gynecology and Obstetrics (FIGO)stage III to IV epithelial ovarian, primary peritoneal, or fallopian tube cancers, and an ECOG performance status of 0 or 1. Eligible patients were randomly assigned (2:1)using a permuted block method (block size of six patients)to receive six cycles of paclitaxel (175 mg/m2)and carboplatin (area under the serum concentration-time curve 5 or 6)every 3 weeks, plus weekly intravenous trebananib 15 mg/kg or placebo. Maintenance therapy with trebananib or placebo continued for up to 18 additional months. The primary endpoint was progression-free survival, as assessed by the investigators, in the intention-to-treat population. Safety analyses included patients who received at least one dose of study treatment. This trial is registered with ClinicalTrials.gov, number NCT01493505, and is complete. Findings: Between Jan 30, 2012, and Feb 25, 2014, 1164 patients were screened and 1015 eligible patients were randomly allocated to treatment (678 to trebananib and 337 to placebo). After a median follow-up of 27·4 months (IQR 17·7–34·2), 626 patients had progression-free survival events (405 [60%]of 678 in the trebananib group and 221 [66%]of 337 in the placebo group). Median progression-free survival did not differ between the trebananib group (15·9 months [15·0–17·6])and the placebo group (15·0 months [12·6–16·1])groups (hazard ratio 0·93 [95% CI 0·79–1·09]; p=0·36). 512 (76%)of 675 patients in the trebananib group and 237 (71%)of 336 in the placebo group had grade 3 or worse treatment-emergent adverse events; of which the most common events were neutropenia (trebananib 238 [35%]vs placebo 126 [38%])anaemia (76 [11%]vs 40 [12%]), and leucopenia (81 [12%]vs 35 [10%]). 269 (40%)patients in the trebananib group and 104 (31%)in the placebo group had serious adverse events. Two fatal adverse events in the trebananib group were considered related to trebananib, paclitaxel, and carboplatin (lung infection and neutropenic colitis); two were considered to be related to paclitaxel and carboplatin (general physical health deterioration and platelet count decreased). No treatment-related fatal adverse events occurred in the placebo group. Interpretation: Trebananib plus carboplatin and paclitaxel did not improve progression-free survival as first-line treatment for advanced ovarian cancer. The combination of trebananib plus carboplatin and paclitaxel did not produce new safety signals. These results show that trebananib in combination with carboplatin and paclitaxel is minimally effective in this patient population. Funding: Amgen. © 2019 Elsevier Ltd

Actomyosin ATP hydrolysis occurring during muscle contraction releases inorganic phosphate [Pi] in the myoplasm. High [Pi] reduces force and affects force kinetics in skinned muscle fibres at low temperature. These effects decrease at high temperature, raising the question of their importance under physiological conditions.This study provides the first analysis of the effects of Pi on muscle performance in intact mammalian fibres at physiological temperature. Myoplasmic [Pi] was raised by fatiguing the fibres with a series of tetanic contractions.[Pi] increase reduces muscular force mainly by decreasing the force of the single molecular motor, the crossbridge, and alters the crossbridge response to fast length perturbation indicating faster kinetics.These results are in agreement with schemes of actomyosin ATPase and the crossbridge cycle including a low‐ or no‐force state and show that fibre length changes perturb the Pi‐sensitive force generation of the crossbridge cycle.

The CEFLES2 campaign during the Carbo Europe Regional Experiment Strategy was designed to provide simultaneous airborne measurements of solar induced fluorescence and CO2 fluxes. It was combined with extensive ground-based quantification of leaf- and canopy-level processes in support of ESA's Candidate Earth Explorer Mission of the "Fluorescence Explorer" (FLEX). The aim of this campaign was to test if fluorescence signal detected from an airborne platform can be used to improve estimates of plant mediated exchange on the mesoscale. Canopy fluorescence was quantified from four airborne platforms using a combination of novel sensors: (i) the prototype airborne sensor AirFLEX quantified fluorescence in the oxygen A and B bands, (ii) a hyperspectral spectrometer (ASD) measured reflectance along transects during 12 day courses, (iii) spatially high resolution georeferenced hyperspectral data cubes containing the whole optical spectrum and the thermal region were gathered with an AHS sensor, and (iv) the first employment of the high performance imaging spectrometer HYPER delivered spatially explicit and multi-temporal transects across the whole region. During three measurement periods in April, June and September 2007 structural, functional and radiometric characteristics of more than 20 different vegetation types in the Les Landes region, Southwest France, were extensively characterized on the ground. The campaign concept focussed especially on quantifying plant mediated exchange processes (photosynthetic electron transport, CO2 uptake, evapotranspiration) and fluorescence emission. The comparison between passive sun-induced fluorescence and active laser-induced fluorescence was performed on a corn canopy in the daily cycle and under desiccation stress. Both techniques show good agreement in detecting stress induced fluorescence change at the 760 nm band. On the large scale, airborne and ground-level measurements of fluorescence were compared on several vegetation types supporting the scaling of this novel remote sensing signal. The multi-scale design of the four airborne radiometric measurements along with extensive ground activities fosters a nested approach to quantify photosynthetic efficiency and gross primary productivity (GPP) from passive fluorescence.

This volume is a collection of contributions from the 5th Workshop on Machine Learning and Interpretation in Neuroimaging (MLINI) at the Neural Information Processing Systems (NIPS 2015) conference. Modern multivariate statistical methods developed in the rapidly growing field of machine learning are being increasingly applied to various problems in neuroimaging, from cognitive state detection to clinical diagnosis and prognosis. Multivariate pattern analysis methods are designed to examine complex relationships between high-dimensional signals, such as brain images, and outcomes of interest, such as the category of a stimulus, a type of a mental state of a subject, or a specific mental disorder. Such techniques are in contrast with the traditional mass-univariate approaches that dominated neuroimaging in the past and treated each individual imaging measurement in isolation. We believe that machine learning has a prominent role in shaping how questions in neuroscience are framed, and that the machine-learning mind set is now entering modern psychology and behavioral studies. It is also equally important that practical applications in these fields motivate a rapidly evolving line or research in the machine learning community. In parallel, there is an intense interest in learning more about brain function in the context of rich naturalistic environments and scenes. Efforts to go beyond highly specific paradigms that pinpoint a single function, towards schemes for measuring the interaction with natural and more varied scene are made. The goal of the workshop is to pinpoint the most pressing issues and common challenges across the neuroscience, neuroimaging, psychology and machine learning fields, and to sketch future directions and open questions in the light of novel methodology.

Vegetation in many arid and semiarid shrublands is frequently arranged in patches with high plant-cover (shrub patches) interspersed in a low-cover herbaceous matrix (inter-shrub areas). We hypothesized that (a) livestock grazing is an important determinant of such spatial patterns of vegetation, and (b) redistribution of soil resources associated with shrub patches helps in the recovery of vegetation in inter-shrub areas. To test these hypotheses we (a) used line transects to compare spatial variations in vegetation, soil microtopography, and soil physicochemical properties in grazed areas and areas protected from grazing since 1970, (b) added sediment and seeds to inter-shrub areas, and (c) measured resource redistribution after a wildfire. Results were consistent with the hypotheses. They indicated greater spatial heterogeneity in vegetation, soil microtopography and soil physicochemical properties in grazed areas than in protected areas, and that addition of sediment and seeds or redistribution of soil resources from shrub patches after a wildfire enhanced re-establishment of vegetation in degraded inter-shrub areas. As a synthesis, a conceptual model of degradation and recovery processes in semi-arid shrublands of Northern Patagonia is presented. Fil: Kröpfl, A. I.. Universidad Nacional del Comahue. Centro Universidad Región Zona Atlántica; Argentina Fil: Cecchi, G. A.. Instituto Nacional de Tecnología Agropecuaria; Argentina Fil: Villasuso, N. M.. Universidad Nacional del Comahue. Centro Universidad Región Zona Atlántica; Argentina Fil: Distel, Roberto Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Centro de Recursos Naturales Renovables de la Zona Semiárida(i); Argentina