26 research outputs found
Silk reinforced with graphene or carbon nanotubes spun by spiders
Here, we report the production of silk incorporating graphene and carbon
nanotubes directly by spider spinning, after spraying spiders with the
corresponding aqueous dispersions. We observe a significant increment of the
mechanical properties with respect to the pristine silk, in terms of fracture
strength, Young's and toughness moduli. We measure a fracture strength up to
5.4 GPa, a Young's modulus up to 47.8 GPa and a toughness modulus up to 2.1
GPa, or 1567 J/g, which, to the best of our knowledge, is the highest reported
to date, even when compared to the current toughest knotted fibres. This
approach could be extended to other animals and plants and could lead to a new
class of bionic materials for ultimate applications
Language-enhanced RNR-Map: Querying Renderable Neural Radiance Field maps with natural language
We present Le-RNR-Map, a Language-enhanced Renderable Neural Radiance map for
Visual Navigation with natural language query prompts. The recently proposed
RNR-Map employs a grid structure comprising latent codes positioned at each
pixel. These latent codes, which are derived from image observation, enable: i)
image rendering given a camera pose, since they are converted to Neural
Radiance Field; ii) image navigation and localization with astonishing
accuracy. On top of this, we enhance RNR-Map with CLIP-based embedding latent
codes, allowing natural language search without additional label data. We
evaluate the effectiveness of this map in single and multi-object searches. We
also investigate its compatibility with a Large Language Model as an
"affordance query resolver". Code and videos are available at
https://intelligolabs.github.io/Le-RNR-Map/Comment: Accepted at ICCVW23 VLA
The role of low-energy electrons in the charging process of LISA test masses
The estimate of the total electron yield is fundamental for our understanding of the test-mass charging associated with cosmic rays in the Laser Interferometer Space Antenna (LISA) Pathfinder mission and in the forthcoming gravitational wave observatory LISA. To unveil the role of low energy electrons in this process owing to galactic and solar energetic particle events, in this work we study the interaction of keV and sub-keV electrons with a gold slab using a mixed Monte Carlo (MC) and ab-initio framework. We determine the energy spectrum of the electrons emerging from such a gold slab hit by a primary electron beam by considering the relevant energy loss mechanisms as well as the elastic scattering events. We also show that our results are consistent with experimental data and MC simulations carried out with the GEANT4-DNA toolkit
Designing Logic Tensor Networks for Visual Sudoku puzzle classification
Given the increasing importance of the neurosymbolic (NeSy) approach in artificial intelligence, there is a growing interest in studying benchmarks specifically designed to emphasize the ability of AI systems to combine low-level representation learning with high-level symbolic reasoning. One such recent benchmark is Visual Sudoku Puzzle Classification, that combines visual perception with relational constraints. In this work, we investigate the application of Logic Tensork Networks (LTNs) to the Visual Sudoku Classification task and discuss various alternatives in terms of logical constraint formulation, integration with the perceptual module and training procedure
Prevalence of HPV Infection in Racial-Ethnic Subgroups of Head and Neck Cancer Patients
The landscape of HPV infection in racial/ethnic subgroups of head and neck cancer (HNC) patients has not been evaluated carefully. In this study, a meta-analysis examined the prevalence of HPV in HNC patients of African ancestry. Additionally, a pooled analysis of subject-level data was also performed to investigate HPV prevalence and patterns of p16 (CDNK2A) expression amongst different racial groups. Eighteen publications (N = 798 Black HNC patients) were examined in the meta-analysis, and the pooled analysis included 29 datasets comprised of 3,129 HNC patients of diverse racial/ethnic background. The meta-analysis revealed that the prevalence of HPV16 was higher among Blacks with oropharyngeal cancer than Blacks with non-oropharyngeal cancer. However, there was great heterogeneity observed among studies (Q test P<0.0001). In the pooled analysis, after adjusting for each study, year of diagnosis, age, gender and smoking status, the prevalence of HPV16/18 in oropharyngeal cancer patients was highest in Whites (61.1%), followed by 58.0% in Blacks and 25.2% in Asians (P<0.0001). There was no statistically significant difference in HPV16/18 prevalence in non-oropharyngeal cancer by race (P=0.682). With regard to the pattern of HPV16/18 status and p16 expression, White patients had the highest proportion of HPV16/18+/p16+ oropharyngeal cancer (52.3%), while Asians and Blacks had significantly lower proportions (23.0% and 22.6%, respectively) [P <0.0001]. Our findings suggest that the pattern of HPV16/18 status and p16 expression in oropharyngeal cancer appears to differ by race and this may contribute to survival disparities
Prevalence of HPV infection in racial–ethnic subgroups of head and neck cancer patients
The landscape of human papillomavirus (HPV) infection in racial/ethnic subgroups of head and neck cancer (HNC) patients has not been evaluated carefully. In this study, a meta-analysis examined the prevalence of HPV in HNC patients of African ancestry. Additionally, a pooled analysis of subject-level data was also performed to investigate HPV prevalence and patterns of p16 (CDNK2A) expression amongst different racial groups. Eighteen publications (N=798 Black HNC patients) were examined in the meta-analysis, and the pooled analysis included 29 datasets comprised of 3129 HNC patients of diverse racial/ethnic background. The meta-analysis revealed that the prevalence of HPV16 was higher among Blacks with oropharyngeal cancer than Blacks with non-oropharyngeal cancer. However, there was great heterogeneity observed among studies (Q test P<0.0001). In the pooled analysis, after adjusting for each study, year of diagnosis, age, gender and smoking status, the prevalence of HPV16,18 in oropharyngeal cancer patients was highest in Whites (61.1%), followed by 58.0% in Blacks and 25.2% in Asians (P<0.0001). There was no statistically significant difference in HPV16,18 prevalence in non-oropharyngeal cancer by race (P=0.682). With regard to the pattern of HPV16,18 status and p16 expression, White patients had the highest proportion of HPV16,18+/p16+ oropharyngeal cancer (52.3%), while Asians and Blacks had significantly lower proportions (23.0 and 22.6%, respectively) [P<0.0001]. Our findings suggest that the pattern of HPV16,18 status and p16 expression in oropharyngeal cancer appears to differ by race and this may contribute to survival disparities
Global wealth disparities drive adherence to COVID-safe pathways in head and neck cancer surgery
Peer reviewe
Elettrocarbossilazione di bromobenzeni su catodi di argento
L’attivazione elettrochimica del legame carbonio-alogeno è un ambito ampiamente sfruttato in elettrochimica organica. La reazione è di grande interesse, poiché ha un ruolo importante in ambito sintetico e ambientale. Nell’ambito dell’interesse per i processi di elettrocarbossilazione di alogenuri organici, recentemente è stata dedicata una rilevante attenzione alla carbossilazione di composti aromatici, in particolare benzeni sostituiti, per la produzione di intermedi di chimica fine. I buoni risultati ottenuti per l’elettrocarbossilazione del bromobenzene su Ag, hanno suggerito la necessità di approfondire il meccanismo di tale processo e di estenderlo a bromobenzeni sostituiti. Innanzi sono stati indagati il comportamento voltammetrico del bromobenzene su diversi materiali catodici (Ag, Au, Cu, Pt, Pd, Ni, Zn, Fe, acciaio), per verificarne le potenzialità elettrocatalitiche ed individuare i materiali che hanno migliori capacità elettrocatalitiche, mediante il confronto con il comportamento su un materiale inerte come il glassy carbon (GC). Il migliori materiali catodici trovati sono l’argento, il rame e l’oro. Alla luce di questi risultati si è condotta l’indagine voltammetrica dei composti in esame su catodi di Ag. Una volta ottenute le informazioni dalle indagini voltammetriche, si sono condotti i processi di elettrocarbossilazione su diversi substrati per verificare la possibilità di realizzare carbossilazioni elettrocatalitiche su Ag.
I prodotti dell’ elettrocarbossilazione sono stati analizzati mediante tecnica HPLC.
I risultati mostrano rese buone, mediamente superiori al 50%, ma inferiori alle aspettative; inoltre è necessaria una più approfondita analisi circa le reazioni parassite che sfavoriscono il processo di elettrocarbossilazione
A Quantum Chemical Interpretation of Two-Dimensional Electronic Spectroscopy of Light-Harvesting Complexes
Nonlinear electronic spectroscopies represent one of the most powerful techniques to study complex multichromophoric architectures. For these systems, in fact, linear spectra are too congested to be used to disentangle the many coupled vibroelectronic processes that are activated. By using a 2D approach, instead, a clear picture can be achieved, but only when the recorded spectra are combined with a proper interpretative model. So far, this has been almost always achieved through parametrized exciton Hamiltonians that necessarily introduce biases and/or arbitrary assumptions. In this study, a first-principles approach is presented that combines accurate quantum chemical descriptions with state-of-the-art models for the environment through the use of atomistic and polarizable embeddings. Slow and fast bath dynamics, along with exciton transport between the pigments, are included. This approach is applied to the 2DES spectroscopy of the Light-Harvesting 2 (LH2) complex of purple bacteria. Simulations are extended over the entire visible-near-infrared spectral region to cover both carotenoid and bacteriochlorophyll signals. Our results provide an accurate description of excitonic properties and relaxation pathways, and give an unprecedented insight into the interpretation of the spectral signatures of the measured 2D signals
SCENE-pathy: Capturing the Visual Selective Attention of People Towards Scene Elements
We present SCENE-pathy, a dataset and a set of baselines to study the visual selective attention (VSA) of people towards the 3D scene in which they are located. In practice, VSA allows to discover which parts of the scene are most attractive for an individual. Capturing VSA is of primary importance in the fields of marketing, retail management, surveillance, and many others. So far, VSA analysis focused on very simple scenarios: a mall shelf or a tiny room, usually with a single subject involved. Our dataset, instead, considers a multi-person and much more complex 3D scenario, specifically a high-tech fair showroom presenting machines of an Industry 4.0 production line, where 25 subjects have been captured for 2Â min each when moving, observing the scene, and having social interactions. Also, the subjects filled out a questionnaire indicating which part of the scene was most interesting for them. Data acquisition was performed using Hololens 2 devices, which allowed us to get ground-truth data related to people's tracklets and gaze trajectories. Our proposed baselines capture VSA from the mere RGB video data and a 3D scene model, providing interpretable 3D heatmaps. In total, there are more than 100K RGB frames with, for each person, the annotated 3D head positions and the 3D gaze vectors. The dataset is available here: https://intelligolabs.github.io/scene-pathy