Visual pathways from the perspective of cost functions and multi-task deep neural networks

Vision research has been shaped by the seminal insight that we can understand the higher-tier visual cortex from the perspective of multiple functional pathways with different goals. In this paper, we try to give a computational account of the functional organization of this system by reasoning from the perspective of multi-task deep neural networks. Machine learning has shown that tasks become easier to solve when they are decomposed into subtasks with their own cost function. We hypothesize that the visual system optimizes multiple cost functions of unrelated tasks and this causes the emergence of a ventral pathway dedicated to vision for perception, and a dorsal pathway dedicated to vision for action. To evaluate the functional organization in multi-task deep neural networks, we propose a method that measures the contribution of a unit towards each task, applying it to two networks that have been trained on either two related or two unrelated tasks, using an identical stimulus set. Results show that the network trained on the unrelated tasks shows a decreasing degree of feature representation sharing towards higher-tier layers while the network trained on related tasks uniformly shows high degree of sharing. We conjecture that the method we propose can be used to analyze the anatomical and functional organization of the visual system and beyond. We predict that the degree to which tasks are related is a good descriptor of the degree to which they share downstream cortical-units.Comment: 16 pages, 5 figure

Magnetic resonance imaging analysis of the bioabsorbable Milagro™ interference screw for graft fixation in anterior cruciate ligament reconstruction

Ligament graft fixation with bioabsorbable interference screws is a standard procedure in cruciate ligament replacement. Previous screw designs may resorb incompletely, and can cause osteolysis and sterile cysts despite being implanted for several years. The aim of this study was to examine the in vivo degradation and biocompatibility of the new Milagro™ interference screw (Mitek, Norderstedt, Germany). The Milagro™ interference screw is made of 30% ß-TCP (TriCalcium phosphate) and 70% PLGA (Poly-lactic-co-glycolic acid). In the period between June 2005 and February 2006, 38 patients underwent graft fixation with Milagro™ screws in our hospital. Arthroscopic ACL reconstruction was performed using hamstring tendon grafts in all the patients. MR imaging was performed on 12 randomly selected patients out of the total of 38 at 3, 6 and 12 months after surgery. During the examination, the volume loss of the screw, tunnel enlargement, presence of osteolysis, fluid lines, edema and postoperative screw replacement by bone tissue were evaluated. There was no edema or signs of inflammation around the bone tunnels. At 3, 6 and 12 months, the tibial screws showed an average volume loss of 0, 8.1% (±7.9%) and 82.6% (±17.2%, P < 0.05), respectively. The femoral screws showed volume losses of 2.5% (±2.1%), 31.3% (±21.6%) and 92.02% (±6.3%, P < 0.05), respectively. The femoral tunnel enlargement was 47.4% (±43.8%) of the original bone tunnel volume after 12 months, and the mean tunnel volume of the tibial tunnel was −9.5% (±58.1%) compared to the original tunnel. Bone ingrowth was observed in all the patients. In conclusion, the resorption behaviour of the Milagro™ screw is closely linked to the graft healing process. The screws were rapidly resorbed after 6 months and, at 12 months, only the screw remnants were detectable. Moreover, the Milagro™ screw is biocompatible and osteoconductive, promoting bone ingrowth during resorption. Tunnel enlargement is not prevented in the first months but is reduced by bone ingrowth after 12 months

A closure model with plumes I. The solar convection

Oscillations of stellar p modes, excited by turbulent convection, are investigated. We take into account the asymmetry of the up and downflows created by turbulent plumes through an adapted closure model. In a companion paper, we apply it to the formalism of excitation of solar p modes developed by Samadi & Goupil 2001. Using results from 3D numerical simulations of the upper most part of the solar convection zone, we show that the two-scale-mass-flux model (TFM) is valid only for quasi-laminar or highly skewed flows (Gryanik & Hartmann 2002). We build a generalized-Two-scale-Mass-Flux Model (GTFM) model which takes into account both the skew introduced by the presence of two flows and the effects of turbulence in each flow. In order to apply the GTFM to the solar case, we introduce the plume dynamics as modelled by Rieutord & Zahn (1995) and construct a Closure Model with Plumes (CMP). When comparing with 3D simulation results, the CMP improves the agreement for the fourth order moments, by approximatively a factor of two compared with the use of the quasi-normal approximation or a skewness computed with the classical TFM. The asymmetry of turbulent convection in the solar case has an important impact on the vertical-velocity fourth-order moment which has to be accounted for by models. The CMP is a significant improvement and is expected to improve the modelling of solar p-mode excitation.Comment: 13 pages, accepted for publication in A&

Towards a multisensor station for automated biodiversity monitoring

Rapid changes of the biosphere observed in recent years are caused by both small and large scale drivers, like shifts in temperature, transformations in land-use, or changes in the energy budget of systems. While the latter processes are easily quantifiable, documentation of the loss of biodiversity and community structure is more difficult. Changes in organismal abundance and diversity are barely documented. Censuses of species are usually fragmentary and inferred by often spatially, temporally and ecologically unsatisfactory simple species lists for individual study sites. Thus, detrimental global processes and their drivers often remain unrevealed. A major impediment to monitoring species diversity is the lack of human taxonomic expertise that is implicitly required for large-scale and fine-grained assessments. Another is the large amount of personnel and associated costs needed to cover large scales, or the inaccessibility of remote but nonetheless affected areas. To overcome these limitations we propose a network of Automated Multisensor stations for Monitoring of species Diversity (AMMODs) to pave the way for a new generation of biodiversity assessment centers. This network combines cutting-edge technologies with biodiversity informatics and expert systems that conserve expert knowledge. Each AMMOD station combines autonomous samplers for insects, pollen and spores, audio recorders for vocalizing animals, sensors for volatile organic compounds emitted by plants (pVOCs) and camera traps for mammals and small invertebrates. AMMODs are largely self-containing and have the ability to pre-process data (e.g. for noise filtering) prior to transmission to receiver stations for storage, integration and analyses. Installation on sites that are difficult to access require a sophisticated and challenging system design with optimum balance between power requirements, bandwidth for data transmission, required service, and operation under all environmental conditions for years. An important prerequisite for automated species identification are databases of DNA barcodes, animal sounds, for pVOCs, and images used as training data for automated species identification. AMMOD stations thus become a key component to advance the field of biodiversity monitoring for research and policy by delivering biodiversity data at an unprecedented spatial and temporal resolution. (C) 2022 Published by Elsevier GmbH on behalf of Gesellschaft fur Okologie

The Infrared Array Camera (IRAC) for the Spitzer Space Telescope

The Infrared Array Camera (IRAC) is one of three focal plane instruments in the Spitzer Space Telescope. IRAC is a four-channel camera that obtains simultaneous broad-band images at 3.6, 4.5, 5.8, and 8.0 microns. Two nearly adjacent 5.2x5.2 arcmin fields of view in the focal plane are viewed by the four channels in pairs (3.6 and 5.8 microns; 4.5 and 8 microns). All four detector arrays in the camera are 256x256 pixels in size, with the two shorter wavelength channels using InSb and the two longer wavelength channels using Si:As IBC detectors. IRAC is a powerful survey instrument because of its high sensitivity, large field of view, and four-color imaging. This paper summarizes the in-flight scientific, technical, and operational performance of IRAC.Comment: 7 pages, 3 figures. Accepted for publication in the ApJS. A higher resolution version is at http://cfa-www.harvard.edu/irac/publication