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/

Sinthesys and Characterization of New Luminescent Complexes Based on Copper(I) Iodide

Complexes based on metals with d10 configuration (Cu, Ag, Au) are currently in the focus of numerous research studies because of the demand for materials active in optoelectronic devices. The interest arises from the increasing demand of more-affordable complexes in preference to luminescent metal complexes based on precious and rare-earth metals, Ir, Pt or Os, which are often quite expensive and environmentally problematic, which complicates their usage in high-volume productions. The copper iodide complexes present several advantages, because compared to the corresponding clusters with Br- and Cl- tend to be more stable in air and show a more intense luminescence in the solid state. Most of the complexes studied are characterized by a remarkable high quantum yield in solid state, they are characterized by a large variety of coordination geometries which arise from the many possible combinations of coordination numbers (two, three and four) available for copper(I) and geometries that can be adopted by the halide ions (from terminal to m2- and up to m8-bridging); they present different excited states which can be of a ligand centered, charge transfer or, in the case of polynuclear compounds, even metal-centered nature; and finally the reagents are cheap and the synthetic procedures are easy and occur in few steps. Copper iodide complexes can have a 3XLCT emission band if we are in the presence of aromatic ligand and a 3CC if the distances between the metal centers are shorter than the sum of the van der Waals radii, that in the case of Cu is 2.8 Å. Furthermore due to the great differences in the geometries of CuI compounds, lots of different synthetic techniques, such as the solution methods, mechanochemical (grinding and liquid assisted grinding), solvothermal, vapour or liquid diffusion, need to be used

Exploiting Multimodal Synthetic Data for Egocentric Human-Object Interaction Detection in an Industrial Scenario

In this paper, we tackle the problem of Egocentric Human-Object Interaction (EHOI) detection in an industrial setting. To overcome the lack of public datasets in this context, we propose a pipeline and a tool for generating synthetic images of EHOIs paired with several annotations and data signals (e.g., depth maps or segmentation masks). Using the proposed pipeline, we present EgoISM-HOI a new multimodal dataset composed of synthetic EHOI images in an industrial environment with rich annotations of hands and objects. To demonstrate the utility and effectiveness of synthetic EHOI data produced by the proposed tool, we designed a new method that predicts and combines different multimodal signals to detect EHOIs in RGB images. Our study shows that exploiting synthetic data to pre-train the proposed method significantly improves performance when tested on real-world data. Moreover, to fully understand the usefulness of our method, we conducted an in-depth analysis in which we compared and highlighted the superiority of the proposed approach over different state-of-the-art class-agnostic methods. To support research in this field, we publicly release the datasets, source code, and pre-trained models at https://iplab.dmi.unict.it/egoism-hoi

Early Effects of P-15 on Human Bone Marrow Stem Cells

OBJECTIVES: Peptide-15 (P-15) is an analogue of the cell binding domain of collagen. P-15 has been shown to facilitate physiological to process in a way similar to collagen, to serve as anchorage for cells, and to promote the binding, migration and differentiation of cells. However, how P-15 alters osteoblast activity to promote bone formation is poorly understood. To study the osteoinductive properties of peptide P-15, we analyzed the expression levels of bone related genes in human mesenchymal stem cells treated with this biomaterial. MATERIAL AND METHODS: Using real time Reverse Transcription-Polymerase Chain Reaction the quantitative expression of specific genes, like transcriptional factors (RUNX2 and SP7), bone related genes (SPP1, COL1A1, COL3A1, BGLAP, ALPL, and FOSL1) and mesenchymal stem cells marker (ENG) were examined. RESULTS: P-15 causes a considerable induction of osteoblast transcriptional factor like osterix (SP7) and of the bone related genes osteopontin (SPP1) and osteocalcin (BGLAP). In contrast the expression of endoglin (ENG) was markedly decreased in stem cells treated with P-15 respect to untreated cells, indicating the differentiation effect of this biomaterial on stem cells. CONCLUSIONS: The present study shows the effect of P-15 on mesenchymal stem cells in the early differentiation stages: P-15 is an inducer of osteogenesis on human stem cells as indicated by the activation of bone related markers SP7, SPP1 and BGLAP.The results may allow a better understanding of the molecular mechanism of bone regeneration and as a model for comparing other materials with similar clinical effects

AgX-based hybrid coordination polymers: mechanochemical synthesis, structure and luminescence property characterization

Hybrid coordination polymers are interesting for their ability to converge the properties of both inorganic and organic systems in one single compound and recently attention has been focused on silver based hybrid coordination polymers due to their luminescence properties. We searched the CSD to establish the propensity of AgXL (X = Cl-, Br- and I-) with L as an organic ligand to form hybrid coordination polymers. About 800 AgXL structures are deposited in the CSD, with huge structural variability: indeed, it is possible to recognize some structural preferences based on the halide nature. The formation of an inorganic polymeric unit is favoured by iodide but it is also possible with the other halides. This research continues with the synthesis of AgX (X = I-, Br-) based coordination polymers with 2-, 3- and 4-picolylamine (n-pica) as ligands. By mechanochemical synthesis five new hybrid coordination polymers and one coordination polymer have been obtained and their structures determined. While [(AgI)(n-pica)](n) are not luminescent, [(AgBr)(n-pica)](n) emit and their profile depends on the crystallinity of the sample

Gastric adenocarcinoma cutaneous metastasis arising at a previous surgical drain site: a case report

<p>Abstract</p> <p>Introduction</p> <p>Skin metastasis from internal carcinoma rarely occurs. It has an incidence of 0.7 to 9% and it may be the first sign of an unknown malignancy. However, it can also occur during follow-up.</p> <p>Case presentation</p> <p>A 90-year-old female patient was admitted to our surgical division with a diagnosis of anemia from a bleeding gastric adenocarcinoma. She underwent a gastric resection and Billroth II retrocolic Hofmeister/Finsterer reconstruction. She developed an enteric fistula, which needed a permanent abdominal drain until the 60^thpostoperative day. After 12 months she was readmitted to our division with subacute small bowel obstruction and an erythematous swelling on the right side of the abdomen. Biopsies characterized it as a cutaneous metastasis from the gastric adenocarcinoma. No surgical therapy was performed given her poor clinical condition.</p> <p>Conclusion</p> <p>Skin metastasis from carcinomas of the upper gastrointestinal tract is very rare. Persisting erythematous nodules must be biopsied in order to diagnose cutaneous metastases and to recognize them early and start prompt therapy with anti-tumour agents before the occurrence of massive visceral metastases.</p

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/