Green computing | EPFL Graph Search

Green computing, green IT (Information Technology), or ICT sustainability, is the study and practice of environmentally sustainable computing or IT. The goals of green computing are similar to green chemistry: reduce the use of hazardous materials, maximize energy efficiency during the product's lifetime, increase the recyclability or biodegradability of defunct products and factory waste. Green computing is important for all classes of systems, ranging from handheld systems to large-scale data centers. Many corporate IT departments have green computing initiatives to reduce the environmental effect of their IT operations. Yet it is also clear that the environmental footprint of the sector is significant, estimated at 5-9% of the world's total electricity use and more than 2% of all emissions. Data centres and telecommunications will need to become more energy efficient, reuse waste energy, and use more renewable energy sources to stay competitive. Some believe they can and should bec

The EBRAINS Hodgkin-Huxley Neuron Builder: An online resource for building data-driven neuron models

Shailesh Appukuttan, Luca Leonardo Bologna, Jean-Denis Georges Emile Courcol, Genrich Ivaska, Carmen Alina Lupascu, Michele Migliore

In the last decades, brain modeling has been established as a fundamental tool for understanding neural mechanisms and information processing in individual cells and circuits at different scales of observation. Building data-driven brain models requires the availability of experimental data and analysis tools as well as neural simulation environments and, often, large scale computing facilities. All these components are rarely found in a comprehensive framework and usually require ad hoc programming. To address this, we developed the EBRAINS Hodgkin-Huxley Neuron Builder (HHNB), a web resource for building single cell neural models via the extraction of activity features from electrophysiological traces, the optimization of the model parameters via a genetic algorithm executed on high performance computing facilities and the simulation of the optimized model in an interactive framework. Thanks to its inherent characteristics, the HHNB facilitates the data-driven model building workflow and its reproducibility, hence fostering a collaborative approach to brain modeling.

FRONTIERS MEDIA SA2022

Towards Seamless Continuation of Knowledge in Product Lifecycle Management

Apostolos Perdikakis

The current ICT for manufacturing landscape is characterized by scattered data formats, tools and processes dedicated to different phases in the product lifecycle. Due to the diversity of tools and data formats, manufacturing struggles to cope with new trends in this area. What is clearly missing in the current ICT landscape for manufacturing is an integrated, holistic view on data about products to be manufactured, resources (including human resources) and processes across the full product lifecycle. There is a need to formalize knowledge for the automatic integration in existing engineering tools. In this work ontology-based semantics were exploited to develop machine-understandable models, which are able to understand the meaning of the data and information they contain. The system developed using semantic web methods and tools is designed to support interoperability and data integration, as well as lead a way towards the usage of information contained in the system to extract useful knowledge. This knowledge may provide feedback for improving the design of future generations of products. Thus, the concept of seamless continuation of knowledge all along product-system lifecycles is introduced.The first step of this work was to study the state-of-the-art in PLM and Semantic web Technologies. This included theoretical background in concepts like Beginning Of Life (BOL), Middle Of Life (MOL) and End Of Life (EOL) regarding PLM as well as the definition and theoretical background of Ontologies and Semantic Web Technologies. After completing the study of theoretical background, more advanced research concepts and methodologies for both domains were thoroughly analysed. Examples include Closed Loop Lifecycle Management (CL2M) for PLM and NEON Method-ology for Ontology engineering. The next logical step followed was to find and discover relevant standards like STEP for PLM and W3C standards for Ontologies and Semantic Web Technologies. The engineering aspect of this study imposed the review of available tools both for PLM and Ontology Engineering. Ontology development tools like Protégé, TopBraid composer and Anzo Ontology editor were studied. More advanced software solutions for applications of the semantic web were also studied. Examples include Anzo Enterprise and the Open Semantic Framework. Inspiration also came from previous European projects like EC FP6 Promise. The problem of discontinuation, even after an Ontology model is created, is evident in most of the applications studied as background of this work. Ontology models have to be exploitable and that requires a framework of which they can be part of. The research for successful implementations of ontology driven frameworks was imperative. At first, the open seman-tic framework (osf) was the software stack that came into focus. After being thoroughly studied, it proved difficult to deploy and maintain, for it had still many problematic areas with its configuration and required people with very ad-vanced software skills (both in programing and system configuration). Nevertheless, the examples of use are promis-ing and give many ideas for exploitation. This finding triggered the efforts towards the definition and application of the solution proposed in this work, which has the following characteristics. First and most important, the solution is easy to deploy and maintain, since it is targeting SMEs and large enterprises that want to test the capabilities of the proposed[...]

EPFL2015

Development of a Transient Neural Interface for Minimally Invasive Recording and Stimulation

Adele Fanelli

Transient electronics enabling devices to safely disappear in the environment can be applied not only in green electronics, but also in bioelectronic medicine. Neural implants able to degrade harmlessly inside the body eliminate the need for removal surgery, allow for safe tissue remodelling, and potentially reduce inflammation responses and the chronic adverse reactions hindering device functionality and putting patients' health at risk. Sadly, current transient neurotechnology can be used only for very short-term applications. Fast degrading metals generally used to build these interfaces allow in fact for operations rarely longer than a few days, strongly limiting the available time window for collecting information or for a therapy to be finished.To solve this problem, we propose a transient, all-polymeric neural interface able to work for longer time scales. This would enable new applications of transient neurotechnology, such as recording of brain activity for a prolonged and more useful period of time before resection of epilepsy foci or tumours. The device consists of a polycaprolactone (PCL) scaffold with patterned poly 3,4-ethylene dioxythiophene : polystyrene sulfonate (PEDOT:PSS) traces and electrodes. In vivo neural recording demonstrated low noise levels for twelve weeks and histological analysis highlighted the cellular infiltration inside the PCL scaffold over time, hinting to potential tissue remodelling processes, which would not occur with a non-degradable device. To increase the device potential for a clinical translation, a minimally invasive procedure for its implantation has been proposed. The blood vasculature supplying the brain and nerves can be used as an access route to the neural tissue, offering a close enough location without direct damage to the tissue. By re-shaping the all-polymeric transient neural probe using a stent-inspired design, the new interface can be navigated through a 5Fr catheter and deployed inside 2 mm-diameter channels. Characterization showed promising electrodes endurance to pulsatile flow and prolonged stimulation, together with a good safety profile. This device can be used for neural recording or stimulation from within a blood vessel, for either central or peripheral nervous system. By simplifying the implantation procedure of the neural interface and maintaining its transiency, physicians and patients could feel more confident in applying innovative neurotechnology-based treatments, widening for example the access to deep brain stimulation therapy. To enable crossing of complex vasculature without wall ruptures caused by current manual push of guidewires, a new navigation paradigm for endovascular devices has been designed and tested on thin polyimide strips. A physiological pulsatile flow can propel these probes, even at curvatures as high as 0.25 mm-1, and low amplitude magnetic fields can steer their direction. Electrodes and sensors for temperature and flow can be embedded onto these micro-probes, for unprecedented local interrogation of deep vasculature regions. In conclusion, this thesis introduces new neural interfaces in the field of minimally invasive neurotechnology, reducing adverse effects and complications of non-degradable implants and open surgery. These devices and their concepts have the potential one day to be new tools of the bioelectronic medicine toolbox, contributing to the advancement of innovative treatments for neurodegenerative disorders.