Design of an urban electric scooter

The usage of electric scooters in cities has increased in recent years and it will keep growing. However, nowadays they cause problems to pedestrians, who are not used to this new technology. Therefore, this project consists of developing a smart scooter capable of respecting pedestrians and providing a greater safety to the driver and to pedestrians as well. In this project, it has been improved a normal electric scooter in order to obtain a smart scooter. The final result is a scooter that can interact with the environment and adapt to it with intelligent features. For example, if a person is in front of the smart scooter, it can automatically reduce its speed to avoid an accident. To achieve that, it has been analysed different possibilities of scooters. Afterwards, the best smart scooter has been chosen and, finally, it has been developed. In addition, it has been studied the economic viability of the scooter and its environmental impact. On the other hand, in his project the smart scooter hasn’t been manufactured, it has only been designed. For this reason, this project focuses on the design, rather than on production. In spite of that, the smart scooter has been thought to be manufactured and it could perfectly be used as a model. Furthermore, it could also be useful to any research on Arduino, as it has been implemented to design the smart scooter. Finally, this project could be very helpful for future projects related to electric scooters and to develop new smart technologies

Automated Website Fingerprinting through Deep Learning

Several studies have shown that the network traffic that is generated by a visit to a website over Tor reveals information specific to the website through the timing and sizes of network packets. By capturing traffic traces between users and their Tor entry guard, a network eavesdropper can leverage this meta-data to reveal which website Tor users are visiting. The success of such attacks heavily depends on the particular set of traffic features that are used to construct the fingerprint. Typically, these features are manually engineered and, as such, any change introduced to the Tor network can render these carefully constructed features ineffective. In this paper, we show that an adversary can automate the feature engineering process, and thus automatically deanonymize Tor traffic by applying our novel method based on deep learning. We collect a dataset comprised of more than three million network traces, which is the largest dataset of web traffic ever used for website fingerprinting, and find that the performance achieved by our deep learning approaches is comparable to known methods which include various research efforts spanning over multiple years. The obtained success rate exceeds 96% for a closed world of 100 websites and 94% for our biggest closed world of 900 classes. In our open world evaluation, the most performant deep learning model is 2% more accurate than the state-of-the-art attack. Furthermore, we show that the implicit features automatically learned by our approach are far more resilient to dynamic changes of web content over time. We conclude that the ability to automatically construct the most relevant traffic features and perform accurate traffic recognition makes our deep learning based approach an efficient, flexible and robust technique for website fingerprinting.Comment: To appear in the 25th Symposium on Network and Distributed System Security (NDSS 2018

Benefits of rIX-FP prophylaxis in patients with Haemophilia B: real-world evidence from a Spanish reference centre

Haemophilia B; pharmacokinetic; Real world evidenceHemofilia B; Farmacocinética; Evidencia del mundo realHemofília B; Farmacocinètica; Evidència del món realStandard FIX prophylaxis for PWHB require frequent injections, which has led to the development of extended half-life products like rIX-FP (albutrepenonacog alfa) that has shown good efficacy in clinical studies. This ambispective study aims to report a real-world experience with rIX-FP in a Spanish centre with PWHB who switched from SHL-FIX or began prophylaxis with rIX-FP. Five PWHB were included in this study, Four PTP switched to rIX-FP with prophylaxis every 7 days whilst one PUP started with an every-14-days regimen. 3 PTPs extended their dosing intervals to every 14 days or every 21 days. In all PTPs, median annualized spontaneous and joint bleeding rates were maintained at 0.00 and median (range) of ABR was 0.92 (0.00–2.77) after switch to rIX-FP. Mean trough level with previous product was 3.68% (SD = 2.06), while it was 7.08% (SD = 3) with all rIX-FP dosing intervals. After switching to rIX-FP, all PTP reduced their annual infusion rate between 50 and 84% and their annual FIX consumption by 61% (59–67%). This is the first reported real-world experience with albutrepenonacog alfa in a small cohort in Spain and demonstrates good bleeding control together with a reduction of the infusion rate, factor consumption and higher through factor level than previous treatment

Internal hydration properties of single bacterial endospores probed by electrostatic force microscopy

We show that the internal hydration properties of single Bacillus cereus endospores in air under different relative humidity (RH) conditions can be determined through the measurement of its electric permittivity by means of quantitative electrostatic force microscopy (EFM). We show that an increase in the RH from 0% to 80% induces a large increase in the equivalent homogeneous relative electric permittivity of the bacterial endospores, from ∼4 up to ∼17, accompanied only by a small increase in the endospore height, of just a few nanometers. These results correlate the increase of the moisture content of the endospore with the corresponding increase of environmental RH. Three-dimensional finite element numerical calculations, which include the internal structure of the endospores, indicate that the moisture is mainly accumulated in the external layers of the endospore, hence preserving the core of the endospore at low hydration levels. This mechanism is different from what we observe for vegetative bacterial cells of the same species, in which the cell wall at high humid atmospheric conditions is not able to preserve the cytoplasmic region at low hydration levels. These results show the potential of quantitative EFM under environmental humidity control to study the hygroscopic properties of small-scale biological (and nonbiological) entities and to determine its internal hydration state. A better understanding of nanohygroscopic properties can be of relevance in the study of essential biological processes and in the design of bionanotechnological application