Context Change Detection for an Ultra-Low Power Low-Resolution Ego-Vision Imager

With the increasing popularity of wearable cameras, such as GoPro or Narrative Clip, research on continuous activity monitoring from egocentric cameras has received a lot of attention. Research in hardware and software is devoted to find new efficient, stable and long-time running solutions; however, devices are too power-hungry for truly always-on operation, and are aggressively duty-cycled to achieve acceptable lifetimes. In this paper we present a wearable system for context change detection based on an egocentric camera with ultra-low power consumption that can collect data 24/7. Although the resolution of the captured images is low, experimental results in real scenarios demonstrate how our approach, based on Siamese Neural Networks, can achieve visual context awareness. In particular, we compare our solution with hand-crafted features and with state of art technique and propose a novel and challenging dataset composed of roughly 30000 low-resolution images

Inertial Sensor Based Modelling of Human Activity Classes: Feature Extraction and Multi-sensor Data Fusion Using Machine Learning Algorithms

Wearable inertial sensors are currently receiving pronounced interest due to applications in unconstrained daily life settings, ambulatory monitoring and pervasive computing systems. This research focuses on human activity recognition problem, in which inputs are multichannel time series signals acquired from a set of body-worn inertial sensors and outputs are automatically classified human activities. A general-purpose framework has been presented for designing and evaluating activity recognition system with six different activities using machine learning algorithms such as support vector machine (SVM) and artificial neural networks (ANN). Several feature selection methods were explored to make the recognition process faster by experimenting on the features extracted from the accelerometer and gyroscope time series data collected from a number of volunteers. In addition, a detailed discussion is presented to explore how different design parameters, for example, the number of features and data fusion from multiple sensor locations - impact on overall recognition performance

Spin dynamics of molecular nanomagnets fully unraveled by four-dimensional inelastic neutron scattering

Molecular nanomagnets are among the first examples of spin systems of finite size and have been test-beds for addressing a range of elusive but important phenomena in quantum dynamics. In fact, for short-enough timescales the spin wavefunctions evolve coherently according to the an appropriate cluster spin-Hamiltonian, whose structure can be tailored at the synthetic level to meet specific requirements. Unfortunately, to this point it has been impossible to determine the spin dynamics directly. If the molecule is sufficiently simple, the spin motion can be indirectly assessed by an approximate model Hamiltonian fitted to experimental measurements of various types. Here we show that recently-developed instrumentation yields the four-dimensional inelastic-neutron scattering function S(Q,E) in vast portions of reciprocal space and enables the spin dynamics to be determined with no need of any model Hamiltonian. We exploit the Cr8 antiferromagnetic ring as a benchmark to demonstrate the potential of this new approach. For the first time we extract a model-free picture of the quantum dynamics of a molecular nanomagnet. This allows us, for example, to examine how a quantum fluctuation propagates along the ring and to directly test the degree of validity of the N\'{e}el-vector-tunneling description of the spin dynamics

Modifications in Chemical, Physical and Mechanical Properties of Nebbiolo (Vitis vinifera L.) Grape Berries Induced by Mixed Virus Infection

Modifications in grape quality parameters induced by mixed infection with GFLV and GFkV, GLRaV-1and GVA, and GLRaV-3 and GVA in three Nebbiolo clones were compared against healthy plants of thesame clones in two experimental vineyards in Piemonte, northwest Italy. The aim of the study was toevaluate the effect of virus infection on the mechanical properties of the berry skin and the whole berry asassessed by texture analysis tests, and on the amount and quality of berry skin phenols. Differences wereobserved in grapevine vigour, yield and juice composition, depending on the viral status of the plants. Theanthocyanin profile of the vines infected with GFV and GFkV and those infected with GLRaV-1 and GVAshowed a lower percentage of the more stable tri-substituted malvidin-3-glucoside and a higher percentageof cyanidin and peonidin-3-glucosides. Texture analysis showed that the viruses may increase berry-skinthickness and reduce phenol extractability. These effects carry practical implications for wine quality

Physical activity characterization:Does one site fit all?

Background: It is evident that a growing number of studies advocate a wrist-worn accelerometer for the assessment of patterns of physical activity a priori, yet the veracity of this site rather than any other body-mounted location for its accuracy in classifying activity is hitherto unexplored. Objective: The objective of this review was to identify the relative accuracy with which physical activities can be classified according to accelerometer site and analytical technique. Methods: A search of electronic databases was conducted using Web of Science, PubMed and Google Scholar. This review included studies written in the English language, published between database inception and December 2017, which characterized physical activities using a single accelerometer and reported the accuracy of the technique. Results: A total of 118 articles were initially retrieved. After duplicates were removed and the remaining articles screened, 32 full-text articles were reviewed, resulting in the inclusion of 19 articles that met the eligibility criteria. Conclusion: There is no 'one site fits all' approach to the selection of accelerometer site location or analytical technique. Research design and focus should always inform the most suitable location of attachment, and should be driven by the type of activity being characterized

Codes and standards on computational wind engineering for structural design: State of art and recent trends

This paper first provides a wide overview about the design codes and standards covering the use of Computational Wind Engineering / Computational Fluid Dynamics (CWE/CFD) for wind-sensitive structures and built environment. Second, the paper sets out the basic assumptions and underlying concepts of the new Annex T "Simulations by Computational Fluid Dynamics (CFD/CWE)" of the revised version "Guide for the assessment of wind actions and effects on structures" issued by the Advisory Committee on Technical Recommendations for Constructions of the Italian National Research Council in February 2019 and drafted by the members of the Special Interest Group on Computational Wind Engineering of the Italian Association for Wind Engineering (ANIV-CWE). The same group is currently advising UNI CT021/SC1 in supporting the drafting of the new Annex K - "Derivation of design parameters from wind tunnel tests and numerical simulations" of the revised Eurocode 1: Actions on structures - Part 1-4: General actions - Wind actions. Finally, the paper outlines the subjects most open to development at the technical and applicative level

Classification of behaviour in housed dairy cows using an accelerometer-based activity monitoring system

Background Advances in bio-telemetry technology have made it possible to automatically monitor and classify behavioural activities in many animals, including domesticated species such as dairy cows. Automated behavioural classification has the potential to improve health and welfare monitoring processes as part of a Precision Livestock Farming approach. Recent studies have used accelerometers and pedometers to classify behavioural activities in dairy cows, but such approaches often cannot discriminate accurately between biologically important behaviours such as feeding, lying and standing or transition events between lying and standing. In this study we develop a decision-tree algorithm that uses tri-axial accelerometer data from a neck-mounted sensor to both classify biologically important behaviour in dairy cows and to detect transition events between lying and standing. Results Data were collected from six dairy cows that were monitored continuously for 36 h. Direct visual observations of each cow were used to validate the algorithm. Results show that the decision-tree algorithm is able to accurately classify three types of biologically relevant behaviours: lying (77.42 % sensitivity, 98.63 % precision), standing (88.00 % sensitivity, 55.00 % precision), and feeding (98.78 % sensitivity, 93.10 % precision). Transitions between standing and lying were also detected accurately with an average sensitivity of 96.45 % and an average precision of 87.50 %. The sensitivity and precision of the decision-tree algorithm matches the performance of more computationally intensive algorithms such as hidden Markov models and support vector machines. Conclusions Biologically important behavioural activities in housed dairy cows can be classified accurately using a simple decision-tree algorithm applied to data collected from a neck-mounted tri-axial accelerometer. The algorithm could form part of a real-time behavioural monitoring system in order to automatically detect dairy cow health and welfare status

Enhancing formate yield through electrochemical CO2 reduction using BiOCl and g-C3N4 hybrid catalyst

Electrochemical carbon dioxide (CO2) reduction with bismuth-based catalysts has been widely investigated in the recent few years. This is due to bismuth's ability to perform selective electrochemical CO2 reduction reaction (eCO2RR) to an important C1 product, the formate (HCOO–). However, boosting the performance of such catalysts is a continuous investigation. In this work, enhancing the active sites for eCO2RR is investigated by forming nanocomposites with graphitic carbon nitride (g-C3N4). BiOCl is synthesized by a simple wet-chemical approach in the presence of glycine as size-controlling agent and formed into nanocomposites, which were characterized by Scanning Electron Microscopy (SEM), X-ray diffraction (XRD), Raman spectroscopy, X-ray photoelectron spectroscopy (XPS), Infrared (IR) Spectroscopy and N2 physisorption. Linear Sweep Voltammetry (LSV) in argon and CO2-saturated atmosphere showed higher current values in the case of CO2. Chronoamperometries (CA) were recorded at −1.06 V vs Reversible Hydrogen Electrode (RHE) for 5400 s obtaining Faradic Efficiencies (FE) varying in the range of 70–77 % depending on the nanocomposites’ composition. In fact, 52.1 wt% BiOCl/g-C3N4 formed the highest yields for formate (with also the highest rate of formation of formate) together with a minimal production of H2 and CO. The effect of nano-structuration induced by glycine, used as a size-controlling agent, to form nanoplates was crucial: microplates of BiOCl produced without glycine showed an FE of 4 %, reaching 85 % in the case of the nanoplates. Post-electrocatalysis characterization revealed the possible role of Bi2O2CO3 as the active phase for eCO2RR

Proteome-wide observation of the phenomenon of life on the edge of solubility

To function effectively proteins must avoid aberrant aggregation, and hence they are expected to be expressed at concentrations safely below their solubility limits. By analyzing proteome-wide mass spectrometry data of Caenorhabditis elegans, however, we show that the levels of about three-quarters of the nearly 4, 000 proteins analyzed in adult animals are close to their intrinsic solubility limits, indeed exceeding them by about 10% on average. We next asked how aging and functional self-assembly influence these solubility limits. We found that despite the fact that the total quantity of proteins within the cellular environment remains approximately constant during aging, protein aggregation sharply increases between days 6 and 12 of adulthood, after the worms have reproduced, as individual proteins lose their stoichiometric balances and the cellular machinery that maintains solubility undergoes functional decline. These findings reveal that these proteins are highly prone to undergoing concentration-dependent phase separation, which on aging is rationalized in a decrease of their effective solubilities, in particular for proteins associated with translation, growth, reproduction, and the chaperone system