Studio al banco freni dinamico di un sistema frenante per vetture di F1

Partendo da quanto progettato in termini di impianto frenante di una vettura di F1 il lavoro si è sviluppato, con particolare attenzione alla messa a punto in termini di confrontabilità e veridicità, sulle informazioni fornite dalle analisi dati verificate al banco freno dinamico

ElGo – Electronic Goalkeeper: Making Football More Inclusive to People with Motor Impairments

Game is an essential aspect of a child's life and is a necessary activity for the creation of a gratifying and pleasant relationship towards life and the surrounding world. In general, playing with friends is an important activity at any age. Among games, an important role is played by sports practiced for recreational purpose, e.g. football, basketball, rugby, but for people with disabilities, a direct participation is often too difficult or impossible. Assistive technology has allowed or made more accessible participation to some games to users with disabilities, for example, videogames, but the gap is still very important for real sports. The idea at the base of ElGo is that a person with disabilities, in particular a child or a teenager, can live the game of football thanks to the possibility of controlling an electromechanic device having the role of a goalkeeper in a football match. Main Content. ElGo is composed by a dummy moving on an horizontal linear guide, placed near the goal line, and remotely controlled by the user standing in proximity of the field. The dummy is moved by an electrical motor operated by a motor control device and powered by rechargeable batteries, so that ElGo can be used also where no mains power system is available. The system is controlled by an electronic device, which also manages the user interface. ElGo can be operated in three modes: with only two switches (one for dummy right movement and one for left movement), with four switches (two speed grades for both directions) and with an analogue interface such as a linear potentiometer or a proportional joystick. Results. The presented device is currently developed as a prototype at the University of Pisa by a team composed of Professors, Graduates and Students of Electronic and Mechanical Engineering. The electronic subsystem has been almost completely realized, mechanical elements have been almost completely designed and the relevant procurement phase has started. Conclusion. ElGo expands the boundary of game for disabled people towards new experiences together with able-bodied persons; in this way people with disabilities will be able to participate to a very popular game such as football, not only using a videogame console but in a more physical and active way

A Comparison between Different Machine Learning Approaches Combined with Anodic Stripping Voltammetry for Copper Ions and pH Detection in Cell Culture Media

Recently, the scientific community has shown a great interest about the Organ-on-Chip (OoC) devices, a special kind of micro-fabricated platforms capable of recapitulating the human physiology implementing the traditional cell culture methods and the concept of in vivo studies. Copper ions represent a cellular micronutrient that must be monitored for its potential hazardous effects. The application of electrochemical analysis for heavy metal ions detection and quantification in commercial cell culture media presents several issues due to electrolyte complexity and interferents. In fact, to the best of our knowledge, there is a lack of applications and OoC devices that implement the Anodic Stripping Voltammetry as an ion dosing technique due to the reasons reported above. In fact, considering just the peak intensity value from the measurement, it turns out to be challenging to quantify ion concentration since other ions or molecules in the media may interfere with the measurement. With the aim to overcome these issues, the present work aims to develop an automated system based on machine learning algorithms and demonstrate the possibility to build a reliable forecasting model for copper ion concentration on three different commercial cell culture media (MEM, DMEM, F12). Effectively, combining electrochemical measurements with a multivariate machine learning algorithm leads to a higher classification accuracy. Two different pH media conditions, i.e., physiological (pH 7.4) and acidic (pH 4), were considered to establish how the electrolyte influences the measurement. The experimental datasets were obtained using square-wave anodic stripping voltammetry (SWASV) and were used to carry out a machine learning trained model. The proposed method led to a significant improvement in Cu2+ concentration detection accuracy (96.6% for the SVM model and 93.1% for the NB model in MEM) as well as being able to monitor the pH solution

Anodic Stripping Voltammetric Determination of Copper Ions in Cell Culture Media: From Transwell^® to Organ-on-Chip Systems

The integration of sensing devices into cell culture systems is a topic of great interest in the study of pathologies and complex biological mechanisms in real-time. In particular, the fit-for-purpose microfluidic devices called organ-on-chip (OoC), which host living engineered organs that mimic in vivo conditions, benefit greatly from the integration of sensors, enabling the monitoring of specific chemical-physical parameters that can be correlated with biological processes. In this context, copper is an essential trace element whose total concentration may be associated with specific pathologies, and it is therefore important to develop reliable analytical techniques in cell systems. Copper can be determined by using the anodic stripping voltammetry (ASV) technique, but its applicability in cell culture media presents several challenges. Therefore, in this work, the performance of ASV in cell culture media was evaluated, and an acidification protocol was tested to improve the voltammetric signal intensity. A Transwell® culture model with Caco-2 cells was used to test the applicability of the developed acidification protocol by performing an off-line measurement. Finally, a microfluidic device was designed in order to perform the acidification of the cell culture medium in an automated manner and then integrated with a silicon microelectrode to perform in situ measurements. The resulting sensor-integrated microfluidic chip could be used to monitor the concentration of copper or other ions concentration in an organ-on-chip model; these functionalities represent a great opportunity for the non-destructive strategic experiments required on biological systems under conditions close to those in vivo

Diabetes Affects Antibody Response to SARS-CoV-2 Vaccination in Older Residents of Long-term Care Facilities: Data From the GeroCovid Vax Study

Objective: Type 2 diabetes may affect the humoral immune response after vaccination, but data concerning coronavirus disease 19 (COVID-19) vaccines are scarce. We evaluated the impact of diabetes on antibody response to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccination in older residents of long-term care facilities (LTCFs) and tested for differences according to antidiabetic treatment. Research design and methods: For this analysis, 555 older residents of LTCFs participating in the GeroCovid Vax study were included. SARS-CoV-2 trimeric S immunoglobulin G (anti-S IgG) concentrations using chemiluminescent assays were tested before the first dose and after 2 and 6 months. The impact of diabetes on anti-S IgG levels was evaluated using linear mixed models, which included the interaction between time and presence of diabetes. A second model also considered diabetes treatment: no insulin therapy (including dietary only or use of oral antidiabetic agents) and insulin therapy (alone or in combination with oral antidiabetic agents). Results: The mean age of the sample was 82.1 years, 68.1% were women, and 25.2% had diabetes. In linear mixed models, presence of diabetes was associated with lower anti-S IgG levels at 2 (β = -0.20; 95% CI -0.34, -0.06) and 6 months (β = -0.22; 95% CI -0.37, -0.07) after the first vaccine dose. Compared with those without diabetes, residents with diabetes not using insulin had lower IgG levels at 2- and 6-month assessments (β = -0.24; 95% CI -0.43, -0.05 and β = -0.30; 95% CI -0.50, -0.10, respectively), whereas no differences were observed for those using insulin. Conclusions: Older residents of LTCFs with diabetes tended to have weaker antibody response to COVID-19 vaccination. Insulin treatment might buffer this effect and establish humoral immunity similar to that in individuals without diabetes