Hybrid Data-Driven and Analytical Model for Kinematic Control of a Surgical Robotic Tool

Accurate kinematic models are essential for effective control of surgical robots. For tendon driven robots, which is common for minimally invasive surgery, intrinsic nonlinearities are important to consider. Traditional analytical methods allow to build the kinematic model of the system by making certain assumptions and simplifications on the nonlinearities. Machine learning techniques, instead, allow to recover a more complex model based on the acquired data. However, analytical models are more generalisable, but can be over-simplified; data-driven models, on the other hand, can cater for more complex models, but are less generalisable and the result is highly affected by the training dataset. In this paper, we present a novel approach to combining analytical and data-driven approaches to model the kinematics of nonlinear tendon-driven surgical robots. Gaussian Process Regression (GPR) is used for learning the data-driven model and the proposed method is tested on both simulated data and real experimental data

Peering into YouTube's Abyss: Analyzing NSFL Content and Empowering Users with Collaborative Risk Annotations

In the present work, Youtube's NSFL contents are analyzed starting from a set of channels pertaining to a new Elsagate's wave (phenomenon highly representative of such deviant contents). However, the main focus of the work is to enhance users' agency w.r.t. both web surfing experience (through a collaborative risk annotation tool in the form of a Google Chrome extension) and data collection (thourgh a dedicated GUI realized in Python with Tkinter and Selenium). This seminal work will be followed up by further implementations of both the browser extension (through systematic updates of data by virtue of the peering nature of the project) and the data collection GUI which is now only implemented for YouTube and Reddit (by extending it to other online social networks), resulting in a long-term study of the phenomenon

Un codice del Teseida conservato a Philadelphia e un nuovo frammento del cantare della Guerra di Troia

Il presente studio offre una descrizione codicologica e paleografica aggiornata di un codice del Teseida di Giovanni Boccaccio prodotto in Toscana nell’ultimo quarto del xiv secolo e attualmente conservato nella collezione della University of Pennsylvania Rare Book & Manuscript Library di Philadelphia (MS Codex 254). Presenta inoltre la prima edizione e attribuzione di un breve frammento non precedentemente identificato del cantare trecentesco della Guerra di Troia trasmesso dall’ultima carta del codice e ascrive la sua origine ad un ambiente mercantesco toscano tra Trecento e Quattrocento

ShoCK! - Sharing of Computable Knowledge!

35th International Conference on Education and Research in Computer Aided Architectural Design in Europ

Infantile Childhood Onset of Spinocerebellar Ataxia Type 2

Spinocerebellar ataxia type 2 (SCA2) is a late-onset autosomal dominant cerebellar ataxia caused by triplet CAG/CTG expansion in the ATX2 gene. The initial symptoms usually appear when subjects are in their 30s. Pediatric onset is less common and usually associated with larger triplet expansions. We here report the case of a 1-year-old girl who presented with facial dysmorphism, dystonic features, developmental delay, and retinitis pigmentosa. She was diagnosed as carrying an expanded CAG/CTG tract (92 repeats) before a molecular diagnosis of SCA2 was made in her father. Facial dysmorphism associated with developmental delay and retinitis pigmentosa in early childhood should prompt a careful family investigation for ataxia and study of ATX2

Virological and immunological features of SARS-COV-2 infected children with distinct symptomatology

Background: Despite SARS-CoV-2 immunizations have started in most countries, children are not currently included in the vaccination programs, thus it remains crucial to define their anti-SARS-CoV-2 immune response in order to minimize the risk for other epidemic waves. This study seeks to provide a description of the virology ad anti-SARS-CoV-2 immunity in children with distinct symptomatology. Methods: Between March and July 2020, we recruited 15 SARS-CoV-2 asymptomatic (AS) and 51 symptomatic children (SY), stratified according to WHO clinical classification. We measured SARS-CoV-2 viral load using ddPCR and qPCR in longitudinally collected nasopharyngeal swabs samples. To define anti-SARS-CoV-2 antibodies we measured neutralization activity and total IgG load (Diasorin). We also evaluated antigen-specific B and CD8+T-cells, using a labelled S1+S2 protein and ICAM expression, respectively. Plasma protein profiling was performed with Olink. Results: Virological profiling showed that AS had lower viral load at diagnosis (p=0.004) and faster virus clearance (p=0.0002) compared to SY. Anti-SARS CoV-2 humoral and cellular response did not appear to be associated with the presence of symptoms. AS and SY showed similar titers of SARS-CoV-2 IgG, levels of neutralizing activity, and frequency of Ag-specific B and CD8+T-cells. Whereas pro-inflammatory plasma protein profile was associated to symptomatology. Conclusion: We demonstrated the development of anti-SARS-CoV-2 humoral and cellular response with any regards to symptomatology, suggesting the ability of both SY and AS to contribute towards herd immunity. The virological profiling of AS suggested that they have lower virus load associated with faster virus clearance

Virological and immunological features of SARS-COV-2 infected children with distinct symptomatology

Despite SARS-CoV-2 immunizations have started in most countries, children are not currently included in the vaccination programs, thus it remains crucial to define their anti-SARS-CoV-2 immune response in order to minimize the risk for other epidemic waves. This study seeks to provide a description of the virology ad anti-SARS-CoV-2 immunity in children with distinct symptomatology