Markerless Human Motion Analysis

Measuring and understanding human motion is crucial in several domains, ranging from neuroscience, to rehabilitation and sports biomechanics. Quantitative information about human motion is fundamental to study how our Central Nervous System controls and organizes movements to functionally evaluate motor performance and deficits. In the last decades, the research in this field has made considerable progress. State-of-the-art technologies that provide useful and accurate quantitative measures rely on marker-based systems. Unfortunately, markers are intrusive and their number and location must be determined a priori. Also, marker-based systems require expensive laboratory settings with several infrared cameras. This could modify the naturalness of a subject\u2019s movements and induce discomfort. Last, but not less important, they are computationally expensive in time and space. Recent advances on markerless pose estimation based on computer vision and deep neural networks are opening the possibility of adopting efficient video-based methods for extracting movement information from RGB video data. In this contest, this thesis presents original contributions to the following objectives: (i) the implementation of a video-based markerless pipeline to quantitatively characterize human motion; (ii) the assessment of its accuracy if compared with a gold standard marker-based system; (iii) the application of the pipeline to different domains in order to verify its versatility, with a special focus on the characterization of the motion of preterm infants and on gait analysis. With the proposed approach we highlight that, starting only from RGB videos and leveraging computer vision and machine learning techniques, it is possible to extract reliable information characterizing human motion comparable to that obtained with gold standard marker-based systems

Asymmetries in extraction from nominal copular sentences: A challenging case study for NLP tools

In this paper we discuss two types of nominal copular sentences (Canonical and Inverse, Moro 1997) and we demonstrate how the peculiarities of these two configurations are hardly considered by standard NLP tools that are currently publicly available. Here we show that example-based MT tools (e.g. Google Translate) as well as other NLP tools (UDpipe, LinguA, Stanford Parser, and Google Cloud AI API) fail in capturing the critical distinctions between the two structures in the end producing both wrong analyses and, possibly as a consequence of a non-coherent (or missing) structural analysis, incorrect translations in the case of MT tools. To support the proposed analysis, we present also an empirical study showing that native speakers are indeed sensitive to the critical distinctions. This poses a sharp challenge for NLP tools that aim at being cognitively plausible or at least descriptively adequate (Chowdhury & Zamparelli 2018)

Prefrontal cortex activation upon a demanding virtual hand-controlled task: A new frontier for neuroergonomics

open9noFunctional near-infrared spectroscopy (fNIRS) is a non-invasive vascular-based functional neuroimaging technology that can assess, simultaneously from multiple cortical areas, concentration changes in oxygenated-deoxygenated hemoglobin at the level of the cortical microcirculation blood vessels. fNIRS, with its high degree of ecological validity and its very limited requirement of physical constraints to subjects, could represent a valid tool for monitoring cortical responses in the research field of neuroergonomics. In virtual reality (VR) real situations can be replicated with greater control than those obtainable in the real world. Therefore, VR is the ideal setting where studies about neuroergonomics applications can be performed. The aim of the present study was to investigate, by a 20-channel fNIRS system, the dorsolateral/ventrolateral prefrontal cortex (DLPFC/VLPFC) in subjects while performing a demanding VR hand-controlled task (HCT). Considering the complexity of the HCT, its execution should require the attentional resources allocation and the integration of different executive functions. The HCT simulates the interaction with a real, remotely-driven, system operating in a critical environment. The hand movements were captured by a high spatial and temporal resolution 3-dimensional (3D) hand-sensing device, the LEAP motion controller, a gesture-based control interface that could be used in VR for tele-operated applications. Fifteen University students were asked to guide, with their right hand/forearm, a virtual ball (VB) over a virtual route (VROU) reproducing a 42 m narrow road including some critical points. The subjects tried to travel as long as possible without making VB fall. The distance traveled by the guided VB was 70.2 ± 37.2 m. The less skilled subjects failed several times in guiding the VB over the VROU. Nevertheless, a bilateral VLPFC activation, in response to the HCT execution, was observed in all the subjects. No correlation was found between the distance traveled by the guided VB and the corresponding cortical activation. These results confirm the suitability of fNIRS technology to objectively evaluate cortical hemodynamic changes occurring in VR environments. Future studies could give a contribution to a better understanding of the cognitive mechanisms underlying human performance either in expert or non-expert operators during the simulation of different demanding/fatiguing activities.openCarrieri, Marika; Petracca, Andrea; Lancia, Stefania; Basso Moro, Sara; Brigadoi, Sabrina; Spezialetti, Matteo; Ferrari, Marco; Placidi, Giuseppe; Quaresima, ValentinaCarrieri, Marika; Petracca, Andrea; Lancia, Stefania; BASSO MORO, Sara; Brigadoi, Sabrina; Spezialetti, Matteo; Ferrari, Marco; Placidi, Giuseppe; Quaresima, Valentin

Profiling residential water users’ routines by eigenbehavior modelling

Developing effective demand-side management strategies is essential to meet future residential water demands, pursue water conservation, and reduce the costs for water utilities. The effectiveness of water demand management strategies relies on our understanding of water consumers’ behavior and their consumption habits and routines, which can be monitored through the deployment of smart metering technologies and the adoption of data analytics and machine learning techniques. This work contributes a novel modeling procedure, based on a combination of clustering and principal component analysis, which allows performing water users’ segmentation on the basis of their eigenbehaviors (i.e., recurrent water consumption behaviors) automatically identified from smart metered consumption data. The approach is tested against a dataset of smart metered water consumption data from 175 households in the municipality of Tegna (CH). Numerical results demonstrate the potential of the method for identifying typical profiles of water consumption, which constitute essential information to support residential water demand management

analysis of standard and innovative methods for allocating upstream and refinery ghg emissions to oil products

Alternative fuel policies need accurate and transparent methods to find the embedded carbon intensity of individual refinery products. This study investigates different ways of allocating greenhouse gases emissions deriving from refining and upstream crude oil supply. Allocation methods based on mass, energy content, economic value and, innovatively, added-value, are compared with the marginal refining emissions calculated by CONCAWE's linear-programming model to the average EU refinery, which has been adopted as reference in EU legislation. Beside the most important transportation fuels (gasoline, diesel, kerosene/jet fuel and heavy fuel oil), the analysis extends to petroleum coke and refinery hydrogen. Moreover, novel criteria, based on the implications due to hydrogen usage by each fuel pathway, have been introduced to test the consistency of the analyzed approaches

The Multifaceted Role of GPCRs in Amyotrophic Lateral Sclerosis: A New Therapeutic Perspective?

Amyotrophic lateral sclerosis (ALS) is a degenerating disease involving the motor neurons, which causes a progressive loss of movement ability, usually leading to death within 2 to 5 years from the diagnosis. Much effort has been put into research for an effective therapy for its eradication, but still, no cure is available. The only two drugs approved for this pathology, Riluzole and Edaravone, are onlyable to slow down the inevitable disease progression. As assessed in the literature, drug targets such as protein kinases have already been extensively examined as potential drug targets for ALS, with some molecules already in clinical trials. Here, we focus on the involvement of another very important and studied class of biological entities, G protein-coupled receptors (GPCRs), in the onset and progression of ALS. This workaimsto give an overview of what has been already discovered on the topic, providing useful information and insights that can be used by scientists all around the world who are putting efforts into the fight against this very important neurodegenerating disease

Numerical analysis of interseismic, coseismic and postseismic phases for normal and reverse faulting earthquakes in Italy

The preparation, initiation, and occurrence dynamics of earthquakes in Italy are governed by several frequently unknown physical mechanisms and parameters. Understanding these mechanisms is crucial for developing new techniques and approaches for earthquake monitoring and hazard assessments. Here, we develop a first-order numerical model simulating quasi-static crustal interseismic loading, coseismic brittle episodic dislocations, and postseismic relaxation for extensional and compressional earthquakes in Italy based on a common framework of lithostatic and tectonic forces. Our model includes an upper crust, where the fault is locked, and a deep crust, where the fault experiences steady shear. The results indicate that during the interseismic phase, the contrasting behavior between the upper locked fault segment and lower creeping fault segment generates a stretched volume at depth in the hanging wall via extensional tectonics while a contracted volume forms via compressional tectonics. The interseismic stress and strain gradients invert at the coseismic stage, with the interseismic dilated volume contracting during the coseismic stage, and vice versa. Moreover, interseismic stress gradients promote coseismic gravitational subsidence of the hanging wall for normal fault earthquakes and elastic uplift for reverse fault earthquakes. Finally, the postseismic relaxation is characterized by further ground subsidence and uplift for normal and reverse faulting earthquakes, respectively, which is consistent with the faulting style. The fault is the passive feature, with slipping generating the seismic waves, whereas the energy activating the movement is stored mostly in the hanging wall volume. The main source of energy for normal faulting and thrust is provided by the lithostatic load and elastic load, respectively

Chemical analysis and computed tomography of metallic inclusions in Roman glass to unveil ancient coloring methods

This paper describes the analysis of two near-spherical metallic inclusions partially incorporated within two Roman raw glass slags in order to elucidate the process that induced their formation and to determine whether their presence was related to ancient glass colouring processes. The theory of metallic scraps or powder being used in Roman times for glass-making and colouring purposes is widely accepted by the archaeological scientific community, although the assumption has been mainly based on oral traditions and documented medieval practices of glass processing. The analysis of the two inclusions, carried out by X-ray computed tomography, electrochemical analyses, and scanning electron microscopy, revealed their material composition, corrosion and internal structure. Results indicate that the two metallic bodies originated when, during the melting phase of glass, metal scraps were added to colour the material: the colloidal metal–glass system reached then a supersaturation condition and the latter ultimately induced metal expulsion and agglomeration. According to the authors’ knowledge, these two inclusions represent the first documented and studied finds directly associated with the ancient practise of adding metallic agents to colour glass, and their analysis provides clear insights into the use of metallic waste in the glass colouring process.This paper describes the analysis of two near-spherical metallic inclusions partially incorporated within two Roman raw glass slags in order to elucidate the process that induced their formation and to determine whether their presence was related to ancient glass colouring processes. The theory of metallic scraps or powder being used in Roman times for glass-making and colouring purposes is widely accepted by the archaeological scientific community, although the assumption has been mainly based on oral traditions and documented medieval practices of glass processing. The analysis of the two inclusions, carried out by X-ray computed tomography, electrochemical analyses, and scanning electron microscopy, revealed their material composition, corrosion and internal structure. Results indicate that the two metallic bodies originated when, during the melting phase of glass, metal scraps were added to colour the material: the colloidal metal-glass system reached then a supersaturation condition and the latter ultimately induced metal expulsion and agglomeration. According to the authors' knowledge, these two inclusions represent the first documented and studied finds directly associated with the ancient practise of adding metallic agents to colour glass, and their analysis provides clear insights into the use of metallic waste in the glass colouring process