MECCANO: A Multimodal Egocentric Dataset for Humans Behavior Understanding in the Industrial-like Domain

Wearable cameras allow to acquire images and videos from the user's perspective. These data can be processed to understand humans behavior. Despite human behavior analysis has been thoroughly investigated in third person vision, it is still understudied in egocentric settings and in particular in industrial scenarios. To encourage research in this field, we present MECCANO, a multimodal dataset of egocentric videos to study humans behavior understanding in industrial-like settings. The multimodality is characterized by the presence of gaze signals, depth maps and RGB videos acquired simultaneously with a custom headset. The dataset has been explicitly labeled for fundamental tasks in the context of human behavior understanding from a first person view, such as recognizing and anticipating human-object interactions. With the MECCANO dataset, we explored five different tasks including 1) Action Recognition, 2) Active Objects Detection and Recognition, 3) Egocentric Human-Objects Interaction Detection, 4) Action Anticipation and 5) Next-Active Objects Detection. We propose a benchmark aimed to study human behavior in the considered industrial-like scenario which demonstrates that the investigated tasks and the considered scenario are challenging for state-of-the-art algorithms. To support research in this field, we publicy release the dataset at https://iplab.dmi.unict.it/MECCANO/.Comment: arXiv admin note: text overlap with arXiv:2010.0565

StillFast: An End-to-End Approach for Short-Term Object Interaction Anticipation

Anticipation problem has been studied considering different aspects such as predicting humans' locations, predicting hands and objects trajectories, and forecasting actions and human-object interactions. In this paper, we studied the short-term object interaction anticipation problem from the egocentric point of view, proposing a new end-to-end architecture named StillFast. Our approach simultaneously processes a still image and a video detecting and localizing next-active objects, predicting the verb which describes the future interaction and determining when the interaction will start. Experiments on the large-scale egocentric dataset EGO4D show that our method outperformed state-of-the-art approaches on the considered task. Our method is ranked first in the public leaderboard of the EGO4D short term object interaction anticipation challenge 2022. Please see the project web page for code and additional details: https://iplab.dmi.unict.it/stillfast/

The photovoltaic greenhouses : a union between sustainable development and agriculture

The purpose of this study is to show the efficiency of introducing PV systems in greenhouses from the point of view of agriculture, from the technological point of view and from the economic point of view. The nursery greenhouses are the main sector in which PV may develop. Greenhouses in fact have qualities that a photovoltaic system needs: the right exposure to direct sunlight and large areas available. If we add to this to the fact that many ornamental plants need shading systems, it is possible to understand how the use of the roofs of greenhouses like structures on which to apply the photovoltaic panels in place of traditional plastic film cover, avoids the use of shading nets or painting and is an excellent investment for the nursery. For horticulture action instead the shading action of the solar panels is a limiting factor for crop growth. Experiments of cultivation of rocket under photovoltaic greenhouse are in progress; the first results show a qualitatively higher than that grown in traditional greenhouses, even if the shelf life is less. The conclusions of this work thus tend to highlight how the technical, functional and aesthetic components of photovoltaic technology coincide with structural components and means of agricultural production, allowing to boost farm income, diversifying income: from the cultivation of vegetables, from the production of ornamental plants, and from the production of electricity.Alternative Technologies Ltd., Energy Investment Ltd, JMV Vibro Blocks Ltd., Solar Engineering Ltd. and Solar Solutions Ltd.peer-reviewe

Eccentricity evolution during planet–disc interaction

During the process of planet formation, the planet\u2013disc interactions might excite (or damp) the orbital eccentricity of the planet. In this paper, we present two long (t 3c 3 7 105 orbits) numerical simulations: (a) one (with a relatively light disc, Md/Mp = 0.2), where the eccentricity initially stalls before growing at later times and (b) one (with a more massive disc, Md/Mp = 0.65) with fast growth and a late decrease of the eccentricity. We recover the well-known result that a more massive disc promotes a faster initial growth of the planet eccentricity. However, at late times the planet eccentricity decreases in the massive disc case, but increases in the light disc case. Both simulations show periodic eccentricity oscillations superimposed on a growing/decreasing trend and a rapid transition between fast and slow pericentre precession. The peculiar and contrasting evolution of the eccentricity of both planet and disc in the two simulations can be understood by invoking a simple toy model where the disc is treated as a second point-like gravitating body, subject to secular planet\u2013planet interaction and eccentricity pumping/damping provided by the disc. We show how the counterintuitive result that the more massive simulation produces a lower planet eccentricity at late times can be understood in terms of the different ratios of the disc-to-planet angular momentum in the two simulations. In our interpretation, at late times the planet eccentricity can increase more in low-mass discs rather than in high-mass discs, contrary to previous claims in the literature

ENIGMA-51: Towards a Fine-Grained Understanding of Human-Object Interactions in Industrial Scenarios

ENIGMA-51 is a new egocentric dataset acquired in a real industrial domain by 19 subjects who followed instructions to complete the repair of electrical boards using industrial tools (e.g., electric screwdriver) and electronic instruments (e.g., oscilloscope). The 51 sequences are densely annotated with a rich set of labels that enable the systematic study of human-object interactions in the industrial domain. We provide benchmarks on four tasks related to human-object interactions: 1) untrimmed action detection, 2) egocentric human-object interaction detection, 3) short-term object interaction anticipation and 4) natural language understanding of intents and entities. Baseline results show that the ENIGMA-51 dataset poses a challenging benchmark to study human-object interactions in industrial scenarios. We publicly release the dataset at: https://iplab.dmi.unict.it/ENIGMA-51/

An Outlook into the Future of Egocentric Vision

What will the future be? We wonder! In this survey, we explore the gap between current research in egocentric vision and the ever-anticipated future, where wearable computing, with outward facing cameras and digital overlays, is expected to be integrated in our every day lives. To understand this gap, the article starts by envisaging the future through character-based stories, showcasing through examples the limitations of current technology. We then provide a mapping between this future and previously defined research tasks. For each task, we survey its seminal works, current state-of-the-art methodologies and available datasets, then reflect on shortcomings that limit its applicability to future research. Note that this survey focuses on software models for egocentric vision, independent of any specific hardware. The paper concludes with recommendations for areas of immediate explorations so as to unlock our path to the future always-on, personalised and life-enhancing egocentric vision.Comment: We invite comments, suggestions and corrections here: https://openreview.net/forum?id=V3974SUk1

Myo-inositol in autoimmune thyroiditis, and hypothyroidism

Myo-inositol (Myo-Ins) plays an important role in thyroid function and autoimmunity. Myo-Ins is the precursor for the synthesis of phosphoinositides, which takes part in the phosphatidylinositol (PtdIns) signal transduction pathway, and plays a decisive role in several cellular processes. In the thyroid cells, PtdIns is involved in the intracellular thyroid-stimulating hormone (TSH) signaling, via Phosphatidylinositol (3,4,5)-trisphosphate (PtdIns(3,4,5)P3) (PIP-3). Moreover, the phosphatidyl inositol 3 kinases (PI3K) family of lipid kinases regulates diverse aspects of T, B, and Tregs lymphocyte behaviour. Different mouse models deficient for the molecules involved in the PIP3 pathway suggest that impairment of PIP3 signaling leads to dysregulation of immune responses and, sometimes, autoimmunity. Studies have shown that cytokines modulate Myo-Ins in thyroid cells. Moreover, clinical studies have shown that after treatment with Myo-inositol plus seleniomethionine (Myo-Ins + Se), TSH levels significantly declined in patients with subclinical hypothyroidism due to autoimmune thyroiditis. The treatment was accompanied by a decline of antithyroid autoantibodies. After treatment serum CXCL10 levels declined, confirming the immune-modulatory effect of Myo-Ins. Additional research is necessary in larger population to evaluate the effect on the quality of life, and to study the mechanism of the effect on chemokines