Rescheduling rehabilitation sessions with answer set programming

The rehabilitation scheduling process consists of planning rehabilitation physiotherapy sessions for patients, by assigning proper operators to them in a certain time slot of a given day, taking into account several requirements and optimizations, e.g. patient’s preferences and operator’s work balancing. Being able to efficiently solve such problem is of upmost importance, in particular as a consequence of the COVID-19 pandemic that significantly increased rehabilitation’s needs. The problem has been recently successfully solved via a two-phase solution based on answer set programming (ASP). In this paper, we focus on the problem of rescheduling the rehabilitation sessions, which comes into play when the original schedule cannot be implemented, for reasons that involve the unavailability of operators and/or the absence of patients. We provide rescheduling solutions based on ASP for both phases, considering different scenarios. Results of experiments performed on real benchmarks, provided by ICS Maugeri, show that also the rescheduling problem can be solved in a satisfactory way. Finally, we present a web application that supports the usage of our solution

Solving rehabilitation scheduling problems via a two-phase ASP approach

A core part of the rehabilitation scheduling process consists of planning rehabilitation physiotherapy sessions for patients, by assigning proper operators to them in a certain time slot of a given day, taking into account several legal, medical and ethical requirements and optimizations, e.g., patient’s preferences and operator’s work balancing. Being able to efficiently solve such problem is of upmost importance, in particular after the COVID-19 pandemic that significantly increased rehabilitation’s needs. In this paper, we present a two-phase solution to rehabilitation scheduling based on Answer Set Programming, which proved to be an effective tool for solving practical scheduling problems. We first present a general encoding, and then add domain specific optimizations. Results of experiments performed on both synthetic and real benchmarks, the latter provided by ICS Maugeri, show the effectiveness of our solution as well as the impact of our domain specific optimization

EFO-LCI: A New Life Cycle Inventory Database of Forestry Operations in Europe

Life cycle assessment (LCA) has become a common methodology to analyze environmental impacts of forestry systems. Although LCA has been widely applied to forestry since the 90s, the LCAs are still often based on generic Life Cycle Inventory (LCI). With the purpose of improving LCA practices in the forestry sector, we developed a European Life Cycle Inventory of Forestry Operations (EFO-LCI) and analyzed the available information to check if within the European forestry sector national differences really exist. We classified the European forests on the basis of "Forest Units" (combinations of tree species and silvicultural practices). For each Forest Unit, we constructed the LCI of their forest management practices on the basis of a questionnaire filled out by national silvicultural experts. We analyzed the data reported to evaluate how they vary over Europe and how they affect LCA results and made freely available the inventory data collected for future use. The study shows important variability in rotation length, type of regeneration, amount and assortments of wood products harvested, and machinery used due to the differences in management practices. The existing variability on these activities sensibly affect LCA results of forestry practices and raw wood production. Although it is practically unfeasible to collect site-specific data for all the LCAs involving forest-based products, the use of less generic LCI data of forestry practice is desirable to improve the reliability of the studies. With the release of EFO-LCI we made a step toward the construction of regionalized LCI for the European forestry sector

A Survey on Design Methodologies for Accelerating Deep Learning on Heterogeneous Architectures

In recent years, the field of Deep Learning has seen many disruptive and impactful advancements. Given the increasing complexity of deep neural networks, the need for efficient hardware accelerators has become more and more pressing to design heterogeneous HPC platforms. The design of Deep Learning accelerators requires a multidisciplinary approach, combining expertise from several areas, spanning from computer architecture to approximate computing, computational models, and machine learning algorithms. Several methodologies and tools have been proposed to design accelerators for Deep Learning, including hardware-software co-design approaches, high-level synthesis methods, specific customized compilers, and methodologies for design space exploration, modeling, and simulation. These methodologies aim to maximize the exploitable parallelism and minimize data movement to achieve high performance and energy efficiency. This survey provides a holistic review of the most influential design methodologies and EDA tools proposed in recent years to implement Deep Learning accelerators, offering the reader a wide perspective in this rapidly evolving field. In particular, this work complements the previous survey proposed by the same authors in [203], which focuses on Deep Learning hardware accelerators for heterogeneous HPC platforms

Creating a Regional MODIS Satellite-Driven Net Primary Production Dataset for European Forests

Net primary production (NPP) is an important ecological metric for studying forest ecosystems and their carbon sequestration, for assessing the potential supply of food or timber and quantifying the impacts of climate change on ecosystems. The global MODIS NPP dataset using the MOD17 algorithm provides valuable information for monitoring NPP at 1-km resolution. Since coarse-resolution global climate data are used, the global dataset may contain uncertainties for Europe. We used a 1-km daily gridded European climate data set with the MOD17 algorithm to create the regional NPP dataset MODIS EURO. For evaluation of this new dataset, we compare MODIS EURO with terrestrial driven NPP from analyzing and harmonizing forest inventory data (NFI) from 196,434 plots in 12 European countries as well as the global MODIS NPP dataset for the years 2000 to 2012. Comparing these three NPP datasets, we found that the global MODIS NPP dataset differs from NFI NPP by 26%, while MODIS EURO only differs by 7%. MODIS EURO also agrees with NFI NPP across scales (from continental, regional to country) and gradients (elevation, location, tree age, dominant species, etc.). The agreement is particularly good for elevation, dominant species or tree height. This suggests that using improved climate data allows the MOD17 algorithm to provide realistic NPP estimates for Europe. Local discrepancies between MODIS EURO and NFI NPP can be related to differences in stand density due to forest management and the national carbon estimation methods. With this study, we provide a consistent, temporally continuous and spatially explicit productivity dataset for the years 2000 to 2012 on a 1-km resolution, which can be used to assess climate change impacts on ecosystems or the potential biomass supply of the European forests for an increasing bio-based economy. MODIS EURO data are made freely available at ftp://palantir.boku.ac.at/Public/MODIS_EURO.Peer reviewe

Continuous in situ measurements of volcanic gases with a diode-laser-based spectrometer: CO2 and H2O concentration and soil degassing at Vulcano (Aeolian islands: Italy)

We report on a continuous-measurement campaign carried out in Vulcano (Aeolian islands, Sicily), devoted to the simultaneous monitoring of CO2 and H2O concentrations. The measurements were performed with an absorption spectrometer based on a semiconductor laser source emitting around a 2-μm wavelength. The emitted radiation was selectively absorbed by two molecular ro-vibrational transitions specific of the investigated species. Data for CO2 and H2O concentrations, and CO2 soil diffusive flux using an accumulation chamber configuration, were collected at several interesting sampling points on the island (Porto Levante beach- PLB, Fossa Grande Crater – FOG- and Valley of Palizzi, PAL). CO2/H2O values, measured on the ground, are very similar (around 0.019 (± 0.006)) and comparable to the previous discrete detected values of 0.213 (Fumarole F5-La Fossa crater rim) and 0.012 (Fumarole VFS – Baia Levante beach) obtaid during the 1977–1993 heating phase of the crater fumaroles

Forest products: contribution to carbon storage and climate change mitigation

Climate change is one of the biggest threats for our earth. Mitigation of climate change is thus an urgent challenge our society needs to take up. Many benefits are provided by forests, and one is their potential to mitigate climate change. This mitigating effect can be achieved in many ways, for example increasing the stock of carbon in managed forests or replacing more emission-intensive goods with wood-based products. To maximize the climate mitigation potential of forest and wood products use it is important to correctly quantify their climate mitigating role. A tool to do so is life cycle assessment (LCA), which estimates the environmental burdens of services and goods over their entire life cycle. While this method has been widely used in the past in the forest sector, its application still poses many challenges. Here, we worked to improve the capability of LCA to be used as a tool to assess the climate mitigation potential of forests and wood products. This general context of the thesis is presented in chapter 1.In the first part of the thesis the challenge was addressed at a more generic LCA level.Chapter 2 focused on the collection and analysis of data on the current state of forest management practices in Europe. Based on the collected information the free and open EFO-LCI (European Forestry Operations Life Cycle Inventory) database was built. The collected data showed that European forests are quite diverse in many aspects like rotation length, amount and assortments of wood products harvested and machinery used in the interventions. This diversity in the management is also translated into different life cycle impacts. The variability of the input data proved to be an important factor in determining the variability of the Global Warming impact of raw wood production, with the estimated anthropogenic impacts ranging from 0.4 to 73.1 kg CO2eq/m3 in EFO-LCI and the biogenic impacts from 1.6 to 451.9 kg CO2eq/m3. The release of our regionalized inventory can serve to improve the accuracy of life cycle studies aiming at assessing the relative environmental role of wood production.Chapter 3 tackled the issue from a more general methodological viewpoint. The lack of temporal resolution in LCA, and of a methodology to solve the Life Cycle Inventory (LCI) dynamically, was addressed due to the relevance of the issue for the forestry sector. Network analysis and convolution were used in combination with the traditional matrix-based structure of life cycle inventory to both solve the LCI dynamically and consider time also in the impact assessment. Following the open source philosophy, the developed approach was also translated into a free and open software named Temporalis. The functioning of the method and the advantages of using a dynamic approach were illustrated with a real-case example. The dynamic life cycle of glulam was performed to show how considering its temporal information can offer new insights into the environmental role played by wood products. If was found that the temporal parameters (i.e. rotation length and product lifetime) used to model the dynamic of biogenic carbon fluxes can greatly influence the results which, for the same system, could range from -71 kg CO2eq 443 kg CO2eq when considering a temporal horizon of 20, from -901 kg CO2eq to 667 kg CO2eq when considering a temporal horizon of 100 years and from -546 kg CO2eq to -120 kg CO2eq when considering a temporal horizon of 500 years.In the second part, a more applied approach was followed.Chapter 4 combined the work of the previous two with other data and modelling approaches to assess how European forests would be affected by a change in the management strategies in terms of carbon fluxes, timber harvesting and climate change impact. It was found that timber production is a relatively efficient production chain, with an estimated GWP impact ranging from -1986 kg CO2eq/m3 harvested wood to -2989 kg CO2eq/m3 harvested wood depending on the year and the scenario. Looking at the overall performance of the system, changing management increases the climate change impact of the system at most of 11% by 2050, with this effect mostly driven by the increased emissions of soil carbon. In the study also the future wood demand was considered and this economic consideration proved to be a decisive factor in shaping the future evolution of European forests. In fact, the realizable changes in forest management were buffered by the constraint posed by the relative demand for timber.In chapter 5 a dynamic and consequential life cycle-based assessment framework to estimate the climate mitigation potential of actions and policies in the forest-wood sector was proposed and illustrated with an example. In the analyzed case-study it has been shown that the estimated net climate change impact of the systems could range from - 274 to -111 tonnes of CO2eq/ha/yr by the year 2030 in function of the methodological approach followed. The used accounting procedure influenced the estimated substitution effect which, eventually, was secondary in comparison to the benefits yield by the reduced climate change impact of the system. The results suggested that increasing the climate efficiency of the whole chain should be prioritized over the maximization of the substitution benefits.This work contributed to improving the quality and availability of the inventory data in the European forestry sector and provided a solution for the issue of temporal consideration in LCA, which allows dealing better with the long production cycles of the forestry-wood sector. It was also learnt that the theoretical mitigation potential of forest management might be constrained by the economy and that reducing the climate change impact of the wood sector rather than maximizing the substitution benefits might be the best climate strategy.Future research should, among others, focus on the better understating dynamic of wood in the wood sector, for which data are still way to scarce and very little is known about how the resource wood is effectively used along the chain.Doctorat en Sciencesinfo:eu-repo/semantics/nonPublishe

Approaches to evaluate the carbon neutrality of the forest value chain

info:eu-repo/semantics/publishe

Temporalis, a generic method and tool for dynamic Life Cycle Assessment

The limitations of the static nature of Life Cycle Assessment (LCA) are well known. To overcome the loss of temporal information due to the aggregation of flows in the Life Cycle Inventory (LCI), several dynamic LCA methodologies have been proposed. In this paper we present a new generic and operational methodology for dynamic LCA that allows for the introduction of temporal information in both in the inventory and the Life Cycle Impact Assessment (LCIA) phases. The method makes use of graph traversal and convolution to calculate the temporally differentiated inventory, and makes it possible to use several types of dynamic impact assessment. We describe our method and apply it to a cradle-to-grave dynamic LCA of a glued laminated timber (glulam) product. We also test the sensitivity of the global warming results to temporal explicit LCI data. There is a considerable difference in outcome between the static and dynamic approaches. We have implemented our framework in the free and open source software Temporalis that is fully operational and can be used with existing LCA databases.status: publishe

Life cycle assessment of Austrian and Slovenian raw wood production

Forestry will play an increasingly important role as a raw material contributor since climate change mitigation requires a shift from fossil-based materials to renewable, bio-based materials. Consequently, an increase in wood demand is expected. Slovenia has a forest coverage of 59% while almost half of Austria is covered by forest (43 %). In these countries, the forest-based sector has an important role. We look at the environmental impact of forestry in Slovenia and Austria under an increase in wood demand. This contribution has a twofold purpose: 1) to describe the environmental impact of Slovenian and Austrian forestry and forest products with a focus on sawlogs, and 2) to provide life cycle inventory data for Slovenian and Austrian forestry and importing countries for other LCA needs, for example, LCAs in the construction or biorefinery sectors and for benchmarking purposes. This contribution explores the use of the European Life Cycle Inventory of Forestry Operations (EFO-LCI) database [1]. The life cycle impact assessment applies the 16 impact categories as recommended by the European Commissions for LCA/Environmental Footprint in Europe [2] and provides additional indicators important for bio-based materials