13,482 research outputs found
Are we synchronised ? Measure synchrony in a team sport using a network of wireless accelerometers
No full textMovements synchronism is a key parameter for team sports. To determine whether human movements in rowing are synchronous or not, we developed a system that acquires signals through accelerometers and compares those signals using correlation. System components are tuned to reduce the delay between the time at which the action occurs and the one the system produces the output. We present an application to help training synchronized movements and use it to test the system with elite rowing athletes. The system generates the output within 500 ms from the moment of the movement
Using gait symmetry to virtually align a triaxial accelerometer during running and walking
No full textDuring running and walking the human centre of mass experiences a symmetric acceleration along the mediolateral direction. This reported work shows how to exploit this knowledge to correct misalignments of the axes of a trunk-mounted accelerometer with respect to the body axes. After vertical alignment, based on the gravitational component of the signal, the technique computes the virtual rotation angle of the axes lying in the horizontal plane. The chosen angle minimises the autocorrelation of the signal along the mediolateral direction
“Silencing the ribosomal locus of Saccharomyces cerevisiae: role of RNA polymerase I transcription and chromatin acetylation”
No full textDuring my PhD I investigated the transcriptional silencing occurring at the ribosomal DNA of
Saccharomyces cerevisiae.
In yeast the ribosomal locus (rDNA) is transcribed with high efficiency by RNA polymerase I (Pol I) and
III to synthetize ribosomal RNAs.
It has been discovered that RNA polymerase Pol II (Pol II) can also transcribe the ribosomal locus, at low
level, starting from cryptic promoters and generating non coding RNAs (ncRNAs). ncRNA transcription
leads to genome instability, measurable as extrachromosomal rDNA circles (ERCs) accumulation.
I studied the effect of Pol I transcription in the synthesis of ncRNA and in the rDNA chromatin structure,
employing yeast mutants differing in the Pol I transcriptional rate in order to find whether correlations exist
between Pol I activity and ncRNA synthesis.
I found that RNA polymerase I transcription is required to repress Pol II activity within rDNA. In Pol I
transcription mutants the synthesis of ncRNA is strongly enhanced and histone H3 and H4 acetylation
appears at the Pol II cryptic promoters. Morover, I described how nucleosome spacing and structure respond
differently to Pol I and Pol II transcription within the ribosomal gene cluster.
As post-doc I found that histone deacetylases (Rpd3p and Hst3p) and high mobility group proteins (Nhp6a
and b) regulate the rate of ncRNA and ERCs production at rDNA. Surprisingly every of these mutants has
an altered level of histone H4 lysine 16 (H4K16) acetylation.
The key role of this residue in the co-ordination of transcription and recombination at rDNA was further
demonstrated employing yeast strains characterized by histone H4K16Q/R substitutions
MABS validation through repeated execution and data mining analysis
No full textAgent Based Modelling is the most interesting and advanced approach for simulating a complex system: in a social context, the single parts and the whole are often very hard to describe in detail. Besides, there are agent based formalisms which allow to study the emergency of social behaviour with the creation and study of models, known as artificial societies. Thanks to the ever increasing computational power, it's been possible to use such models to create software, based on intelligent agents, which aggregate behaviour is complex and difficult to predict, and can be used in open and distributed systems. Data mining is born in the last decades in order to help users in finding useful knowledge from the otherwise overwhelming amount of data available nowadays from the web and the data collected every day by companies. Data Mining techniques can therefore be the keystone to reveal non-trivial knowledge expressed by the initial assumption used to build the micro-level of the model and the structure of the society of agents that emerged from the simulation
Estimation of Energy Consumption for TinyOS 2.x-Based Applications
No full textThe development of energy-efficient applications for wireless sensor networks requires mechanisms and tools for run-time monitoring of energy consumption. We propose a software framework that supports energy profiling of applications for the TinyOS 2.x platform. Measurements are obtained through the insertion of software probes within the code of the operating system. As a consequence, since the APIs are not changed, the programmer is not forced to modify the code of existing applications. The technique has been validated by comparing its results with the values registered by dedicated hardware
MARS, a Multi-Agent System for Assessing Rowers’ Coordination via Motion-Based Stigmergy
No full textA crucial aspect in rowing is having a synchronized, highly-efficient stroke. This is very difficult to obtain, due to the many interacting factors that each rower of the crew must perceive. Having a system that monitors and represents the crew coordination would be of great help to the coach during training sessions. In the literature, some methods already employ wireless sensors for capturing motion patterns that affect rowing performance. A challenging problem is to support the coach’s decisions at his same level of knowledge, using a limited number of sensors and avoiding the complexity of the biomechanical analysis of human movements. In this paper, we present a multi-agent information-processing system for on-water measuring of both the overall crew asynchrony and the individual rower asynchrony towards the crew. More specifically, in the system, the first level of processing is managed by marking agents, which release marks in a sensing space, according to the rowers’ motion. The accumulation of marks enables a stigmergic cooperation mechanism, generating collective marks, i.e., short-term memory structures in the sensing space. At the second level of processing, information provided by marks is observed by similarity agents, which associate a similarity degree with respect to optimal marks. Finally, the third level is managed by granulation agents, which extract asynchrony indicators for different purposes. The effectiveness of the system has been experimented on real-world scenarios. The study includes the problem statement and its characterization in the literature, as well as the proposed solving approach and initial experimental setting
On the use of Stochastic Activity Networks for an Energy-aware Simulation of Automatic Weather Stations
No full textAutomatic Weather Stations (AWSs) are embedded systems equipped with a number of sensors used to monitor harsh environments: glaciers and deserts. AWSs may also be equipped with some communication interfaces in order to enable remote access to data. These systems are generally far from power sources, and thus they are equipped with energy harvesting devices, wind turbines and solar panels, and storage devices, batteries. The design of an AWS represents a challenge, since designers have to maximize the sampled and transmitted data while considering the energy needs. We designed and implemented an energy-aware simulator of AWSs to support designers in the definition of the configuration of the system. The simulator relies on the Stochastic Activity Networks (SANs) formalism and has been developed using the Möbius tool. In this chapter we first show how we used SANs to model the components of an AWS, we then report results from validation experiments carried out by comparing the results of the simulator against a real-world AWS and finally show examples of its usage
Using stochastic activity networks to study the energy feasibility of automatic weather stations
No full textAutomatic Weather Stations (AWSs) are systems equipped with a number of environmental sensors and communication interfaces used to monitor harsh environments, such as glaciers and deserts. Designing such systems is challenging, since designers have to maximize the amount of sampled and transmitted data while considering the energy needs of the system that, in most cases, is powered by rechargeable batteries and exploits energy harvesting, e.g., solar cells and wind turbines. To support designers of AWSs in the definition of the software tasks and of the hardware configuration of the AWS we designed and implemented an energy-aware simulator of such systems. The simulator relies on the Stochastic Activity Networks (SANs) formalism and has been developed using the Mobius tool. In this paper we first show how we used the SAN formalism to model the various components of an AWS, we then report results from an experiment carried out to validate the simulator against a real-world AWS and we finally show some examples of usage of the proposed simulator
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