Ice accretion and accumulation may cause a severe problem in many disparate fields from aircraft to electrical transmission lines. Super-hydrophobic (SHP) surfaces can have a potential anti-icing ...application due to their extreme water repellency. However, there is a lack in the characterization of icing behavior of these surfaces. Moreover, durability is a major concern for this kind of coatings. One class of super-hydrophobic surfaces is constituted by hierarchical structures, in which a micrometric roughness is combined with a nanometric roughness and finally covered by a low energy chemical finishing. In the present work, we experimentally investigated how the micrometric roughness of the aluminum alloy surface can influence the hierarchical micro-nanostructure and the consequent hydrophobic and anti-icing properties, especially in terms of durability. Aluminum alloy samples were sandblasted or polished to generate a different micrometric roughness. The following steps to obtain a hierarchical super-hydrophobic structure (nano-roughness and final low energy chemical treatment) were kept constant for all samples. The hydrophobic properties were characterized at room and low temperatures and the anti-icing behavior was measured by shear stress tests. Several repetitions of the shear stress measurement on the same samples and icing- thaw cycles were conducted to study the durability of the coatings. This work describes an easy, fast and economic process to obtain super-hydrophobic materials with durable anti-icing properties, with interesting applications in many industrial fields.
•Icephobic aluminum is obtained by roughening, boiling and coating the surfaces.•Different roughness treatments cause different hydrophobic and icephobic properties.•Hydrophobicity at low temperature gives clues of the icephobicity of the samples.•The sandblasted samples have a promisingly durable icephobicity.
The use and creation of machine‐learning‐based solutions to solve problems or reduce their computational costs are becoming increasingly widespread in many domains. Deep Learning plays a large part ...in this growth. However, it has drawbacks such as a lack of explainability and behaving as a black‐box model. During the last few years, Visual Analytics has provided several proposals to cope with these drawbacks, supporting the emerging eXplainable Deep Learning field. This survey aims to (i) systematically report the contributions of Visual Analytics for eXplainable Deep Learning; (ii) spot gaps and challenges; (iii) serve as an anthology of visual analytical solutions ready to be exploited and put into operation by the Deep Learning community (architects, trainers and end users) and (iv) prove the degree of maturity, ease of integration and results for specific domains. The survey concludes by identifying future research challenges and bridging activities that are helpful to strengthen the role of Visual Analytics as effective support for eXplainable Deep Learning and to foster the adoption of Visual Analytics solutions in the eXplainable Deep Learning community. An interactive explorable version of this survey is available online at https://aware‐diag‐sapienza.github.io/VA4XDL.
This survey systematically reports the contributions of Visual Analytics for eXplainable Deep Learning, spots gaps, serves as an anthology of visual analytical solutions ready to be exploited by the Deep Learning community, proves the degree of maturity, ease of integration, results for specific domains and finally identifies future research challenges.
Visualizing contextual information to a map often comes at the expense of overplotting issues. Especially for use cases with relevant map features in the immediate vicinity of an information to add, ...occlusion of the relevant map context should be avoided. We present SurgeryCuts, a map manipulation technique for the creation of additional canvas area for contextual visualizations on maps. SurgeryCuts is occlusion‐free and does not shift, zoom or alter the map viewport. Instead, relevant parts of the map can be cut apart. The affected area is controlledly distorted using a parameterizable warping function fading out the map distortion depending on the distance to the cut. We define extended metrics for our approach and compare to related approaches. As well, we demonstrate the applicability of our approach at the example of tangible use cases and a comparative user study.
Know Your Body Through Intrinsic Goals Mannella, Francesco; Santucci, Vieri G; Somogyi, Eszter ...
Frontiers in neurorobotics,
07/2018, Letnik:
12
Journal Article
Recenzirano
Odprti dostop
The first "object" that newborn children play with is their own body. This activity allows them to autonomously form a sensorimotor map of their own body and a repertoire of actions supporting future ...cognitive and motor development. Here we propose the theoretical hypothesis, operationalized as a computational model, that this acquisition of body knowledge is not guided by random motor-babbling, but rather by autonomously generated goals formed on the basis of intrinsic motivations. Motor exploration leads the agent to discover and form representations of the possible sensory events it can cause with its own actions. When the agent realizes the possibility of improving the competence to re-activate those representations, it is intrinsically motivated to select and pursue them as goals. The model is based on four components: (1) a self-organizing neural network, modulated by competence-based intrinsic motivations, that acquires abstract representations of experienced sensory (touch) changes; (2) a selector that selects the goal to pursue, and the motor resources to train to pursue it, on the basis of competence improvement; (3) an echo-state neural network that controls and learns, through goal-accomplishment and competence, the agent's motor skills; (4) a predictor of the accomplishment of the selected goals generating the competence-based intrinsic motivation signals. The model is tested as the controller of a simulated simple planar robot composed of a torso and two kinematic 3-DoF 2D arms. The robot explores its body covered by touch sensors by moving its arms. The results, which might be used to guide future empirical experiments, show how the system converges to goals and motor skills allowing it to touch the different parts of own body and how the morphology of the body affects the formed goals. The convergence is strongly dependent on competence-based intrinsic motivations affecting not only skill learning and the selection of formed goals, but also the formation of the goal representations themselves.
The occurrence of brain parenchymal signal-intensity changes within the drainage territory of developmental venous anomalies (DVAs) in the absence of cavernous malformations (CMs) has been ...incompletely assessed. This study was performed to evaluate the prevalence of brain parenchymal signal-intensity abnormalities subjacent to DVA, correlating with DVA morphology and location.
One hundred sixty-four patients with brain MR imaging with contrast studies performed from July 2005 through June 2006 formed the study group. The examinations were reviewed and data were collected regarding the following: location, depth, size of draining vein, associated increased signal intensity on fluid-attenuated inversion recovery and T2-weighted images, associated CMs, and associated signal intensity on gradient recalled-echo sequences.
Of the 175 DVAs identified, 28 had associated signal-intensity abnormalities in the drainage territory. Seven of 28 DVAs with signal-intensity abnormalities were excluded because of significant adjacent white matter signal-intensity changes related to other pathology overlapping the drainage territory. Of the remaining DVAs imaged in this study, 21/168 (12.5%) had subjacent signal-intensity abnormalities. An adjusted prevalence rate of 9/115 (7.8%) was obtained by excluding patients with white matter disease more than minimal in degree. Periventricular location and older age were associated with DVA signal-intensity abnormality.
Signal-intensity abnormalities detectable by standard clinical MR images were identified in association with 12.5% of consecutively identified DVAs. Excluding patients with significant underlying white matter disease, we adjusted the prevalence to 7.8%. The etiology of the signal-intensity changes is unclear but may be related to edema, gliosis, or leukoaraiosis secondary to altered hemodynamics in the drainage area.
The objective of this study is to describe infections in a specialized burns intensive care unit from 1993 to 1999. The criteria for admission to the unit are: children with burns involving at least ...10% or adults with burns involving at least 20% of total body surface; burns affecting face, perineum or feet; suspected or proven airway injury; electric or chemical burns; age less than one year or above 50; or pre-existing disease with any extent of burns. Surveillance of hospital-acquired infection was prospective. Hospital-acquired infection criteria used were those modified from the Centers for Disease Control and Prevention. Diagnosis of infection using skin biopsy was not done. Over the study period, 320 patients were admitted to our burns intensive care unit. One hundred and seventy-five (55%) developed 388 hospital-acquired infections. The rate for vascular catheter-associated bloodstream infections was 34 per 1000 central line-days. The rate of ventilator associated pneumonia was 26 infections per 1000 ventilator-days. Primary bloodstream was the most common infection with 189 episodes (49%); followed by 83 burn wound infections (21%) and 56 pneumonias (14%). In 76% of these infections and in 97% of the primary bloodstream infections, aetiological agents were identified. The micro-organisms causing infections were S taphylococcus aureus (24%), Pseudomonas aeruginosa (18%),Acinetobacter spp. (14%) and coagulase-negative staphylococci (12%). Candida spp. caused 8% of infections. Gram-positive and Gram-negative organisms exhibited resistance to most antimicrobial agents used for therapy. During the first three days of hospitalization in the burns intensive care unit there were eight infections caused by S. aureus and three of these were resistant to oxacillin. These data provide background information regarding extensive burn patients on which decisions for control and prevention of hospital-acquired infections can be made.
Background:
Concussion symptoms in adolescents typically resolve within 4 weeks. However, 20 – 30% of adolescents experience a prolonged recovery. Abnormalities in tracts implicated in visuospatial ...attention and emotional regulation (i.e., inferior longitudinal fasciculus, ILF; inferior fronto-occipital fasciculus, IFOF; uncinate fasciculus; UF) have been consistently reported in concussion; yet, to date, there are no objective markers of prolonged recovery in adolescents. Here, we evaluated the utility of diffusion MRI in outcome prediction. Forty-two adolescents (12.1 – 17.9 years; female: 44.0%) underwent a diffusion Magnetic Resonance Imaging (dMRI) protocol within the first 10 days of concussion. Based on days of injury until medical clearance, adolescents were then categorized into SHORT (<28 days;
N
= 21) or LONG (>28 days;
N
= 21) recovery time. Fractional anisotropy (FA) in the ILF, IFOF, UF, and/or concussion symptoms were used as predictors of recovery time (SHORT, LONG). Forty-two age- and sex-matched healthy controls served as reference. Higher FA in the ILF (
left
: adjusted odds ratio; AOR = 0.36, 95% CI = 0.15 – 0.91,
P
= 0.030;
right
: AOR = 0.28, 95% CI = 0.10 – 0.83,
P
= 0.021), IFOF (
left:
AOR = 0.21, 95% CI = 0.07 – 0.66,
P
= 0.008;
right
: AOR = 0.30, 95% CI = 0.11 – 0.83,
P
= 0.020), and UF (
left
: AOR = 0.26, 95% CI = 0.09 – 0.74,
P
= 0.011;
right:
AOR = 0.28, 95% CI = 0.10 – 0.73,
P
= 0.010) was associated with SHORT recovery. In additional analyses, while adolescents with SHORT recovery did not differ from HC, those with LONG recovery showed lower FA in the ILF and IFOF (
P
< 0.014). Notably, inclusion of dMRI findings increased the sensitivity and specificity (AUC = 0.93) of a prediction model including clinical variables only (AUC = 0.75). Our findings indicate that higher FA in long associative tracts (especially ILF) might inform a more objective and accurate prognosis for recovery time in adolescents following concussion.
Superhydrophobic ice-phobic zinc surfaces Balordi, M.; Pini, F.; Santucci de Magistris, G.
Surfaces and interfaces,
June 2022, 2022-06-00, Letnik:
30
Journal Article
Recenzirano
Odprti dostop
Zinc plating of steel is widely used in many industrial fields to create a protective layer from corrosion and environmental attack, but suffers from wetting and icing issues.
This work presents a ...simple and scalable process to obtain superhydrophobic and ice-phobic zinc surfaces, prepared by growing ZnO Nanorods in a short (<30’) hydrothermal treatment at 90 °C. The further coating with stearic acid or fluoroalkylsilane leads to surfaces with static contact angles higher than 165° and tilting angles as low as 1°. A clear correlation was found between wettability and ice adhesion and excellent ice-phobic performances were shown for all the superhydrophobic samples reaching shear stress values lower than 10 kPa.
Durability was assessed and samples maintain part of their properties after 30 days of immersion in wet chemicals. An easy recovery process can further enhance the ice-phobicity.
An important issue of recent neuroscientific research is to understand the functional role of the phasic release of dopamine in the striatum, and in particular its relation to reinforcement learning. ...The literature is split between two alternative hypotheses: one considers phasic dopamine as a reward prediction error similar to the computational TD-error, whose function is to guide an animal to maximize future rewards; the other holds that phasic dopamine is a sensory prediction error signal that lets the animal discover and acquire novel actions. In this paper we propose an original hypothesis that integrates these two contrasting positions: according to our view phasic dopamine represents a TD-like reinforcement prediction error learning signal determined by both unexpected changes in the environment (temporary, intrinsic reinforcements) and biological rewards (permanent, extrinsic reinforcements). Accordingly, dopamine plays the functional role of driving both the discovery and acquisition of novel actions and the maximization of future rewards. To validate our hypothesis we perform a series of experiments with a simulated robotic system that has to learn different skills in order to get rewards. We compare different versions of the system in which we vary the composition of the learning signal. The results show that only the system reinforced by both extrinsic and intrinsic reinforcements is able to reach high performance in sufficiently complex conditions.
Humans and other biological agents are able to autonomously learn and cache different skills in the absence of any biological pressure or any assigned task. In this respect, Intrinsic Motivations ...(i.e., motivations not connected to reward-related stimuli) play a cardinal role in animal learning, and can be considered as a fundamental tool for developing more autonomous and more adaptive artificial agents. In this work, we provide an exhaustive analysis of a scarcely investigated problem: which kind of IM reinforcement signal is the most suitable for driving the acquisition of multiple skills in the shortest time? To this purpose we implemented an artificial agent with a hierarchical architecture that allows to learn and cache different skills. We tested the system in a setup with continuous states and actions, in particular, with a kinematic robotic arm that has to learn different reaching tasks. We compare the results of different versions of the system driven by several different intrinsic motivation signals. The results show (a) that intrinsic reinforcements purely based on the knowledge of the system are not appropriate to guide the acquisition of multiple skills, and (b) that the stronger the link between the IM signal and the competence of the system, the better the performance.
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