SIRIS-Lab/unlabelled-sti-corpus huggingface dataset:
FUEL INJECTOR

A gas turbine engine fuel injector is disclosed having a plurality of fuel injection circuits that are structured to deliver fuel to air passageways. In one non-limiting embodiment, one of the fuel injection circuits includes a plain jet airblast injector that delivers fuel to an air passageway. In some applications the plain jet can extend across the air passageway and deliver a fuel to an opposite surface to form a fuel film. The fuel film can then be sheared between an air in the air passageway and an air in a nearby air passageway. Another of the fuel injection circuits includes a fuel filmer structured to deliver fuel to an air passageway that can then be sheared by an air in the air passageway and an air in the air passageway that included the plain jet airblast injector.
A Low Complexity Resource Allocation Algorithm for OFDMA Cooperative Relay Networks with Fairness and QoS Guaranteed

This paper proposes a new resource allocation algorithm for uplink OFDMA-based cooperative relay networks, assuming multiple user nodes, multiple relay nodes and a single destination. The aim is to maximise the total sum of the users' data rates, while guaranteeing fairness among them with different QoS requirements. Assuming perfect channel state information (CSI) at the resource allocation controller, the optimisation problem is formulated such that each user is assigned a weight factor based on its QoS requirements. The ones with higher weights are given higher priorities to select their resources (relay stations and subcarriers) first. Once the required QoS is achieved for all users, the weight factor for all users is reduced to a small uniform value. The remaining resources are then allocated to the users with higher instantaneous rates in order of magnitude. The results show that the proposed algorithm outperforms the greedy and static algorithms in terms of outage probability and fairness, and at the same time outperforms Jeong's algorithm by 58% in terms of total sum rate, with an average 74% reduction in system complexity.
Preparation and Characterization of Metronidazole-Surface Imprinted Microspheres MIP-PSSS/CPVA for Colon-Specific Drug Delivery System

In this paper, the use of molecular surface imprinted polymers (MIPs) in designing colon-specific drug delivery systems was investigated. MIPs were prepared on crosslinked polyvinyl alcohol microspheres (CPVA) with sodium 4-styrene sulfonate (SSS) as functional monomer, Metronidazole (MTZ) as template and N,N’-Methylene bisacrylamide (MBA) as crosslinking agent by utilizing cerium salt-hydroxyl group redox initiation system, obtaining MTZ molecular surface imprinted microspheres MIP-PSSS/CPVA. The MIP-PSSS/CPVA microspheres were further characterized by scanning electron microscope and batch binding method. Because there is strong electrostatic interactions between MTZ and monomer SSS, the MTZ molecular surface imprinting is quite successful, and the imprinted microspheres MIP-PSSS/CPVA possess high recognition selectivity and excellent combining affinity. The experimental results show that at pH 1, the MIP-PSSS/CPVA microspheres exhibit very strong binding ability for MTZ, and the binding capacity reache...
Hybrid Parks: Combining abilities, creating synergies and enhancing the performance of parks for sustainable local and regional development policies

Parks, both historic and modern, are intensively managed, high quality environments. They add to the attractiveness and success of cities and regions and to the quality of life for citizens and visitors.

The partnership includes many of those cities and regions energetically enhancing and using parks in a wider policy context such as economic development, rural diversification, protection of cultural heritage, landscapes and environment or urban renewal. Partnership also includes some “newcomers” which started similar policies recently.

They all acknowledge the unique resources of parks, the advantages of cooperation and the need to achieve additional economic, social and environmental benefits to diminish the risks of decline or loss caused by conflicting demands, budget reductions etc. Climate change is a growing threat whose effects are not fully clarified. It will affect park features and plants directly. It will attract more visitors using parks as comfort places. Finally parks
will be part of risk prevention strategies such as green corridors to mitigate climate change.

It is the project’s key objective that parks can fully be used for sustainable local and regional development and for policies to mitigate climate change by enhancing their abilities to better serve economic, social and environmental purposes; by combining the improved capacities to create synergies and to enhance performance and benefits; and by promoting guidance on how to relate the above with local and regional mitigation policies.

Such policies ensure that in each park different functions work "hand in hand". This can be compared with a hybrid car, where two sources of energy and engines are linked to use their individual advantages, to support each other and to enhance performance and sustainability. Analogously, the idea of “Hybrid Parks” came into being.

Activities cover the 3 pillars of sustainability by individual and interrelated activities, based on experiences and resources
of the partnership and the objectives of “Hybrid Parks”. Best practice studies include “Economy: Tourism and urban (re)development", “Social: Widening the audience" and “Environment: Public awareness”. Policies using parks for economic, environmental or social development are investigated in two workshops each. Another six, cross-cutting or "hybrid" workshops investigate how to combine these approaches to increase the contribution and synergies of parks to sustainable development policies and mitigation of climate change. Study tours to the UK (focus: economy), Sweden (social) and Lower Austria (environment) and four open conferences further support exchange and transfer. This feeds into improved skills, policies and regional development plans, championed by regional support teams.

The final conference presents the project report, with best practice case studies and the “Hybrid Parks Model” for integrated management of parks within sustainable development and climate change policies.
Mars sedimentary rock erosion rates constrained using crater counts, with applications to organic-matter preservation and to the global dust cycle

Small-crater counts on Mars light-toned sedimentary rock are often inconsistent with any isochron; these data are usually plotted then ignored. We show (using an 18-HiRISE-image, >10^4 crater dataset) that these non-isochron crater counts are often well-fit by a model where crater production is balanced by crater obliteration via steady exhumation. For these regions, we fit erosion rates. We infer that Mars light-toned sedimentary rocks typically erode at ~10^2 nm/yr, when averaged over 10 km^2 scales and 10^7-10^8 yr timescales. Crater-based erosion-rate determination is consistent with independent techniques, but can be applied to nearly all light-toned sedimentary rocks on Mars. Erosion is swift enough that radiolysis cannot destroy complex organic matter at some locations (e.g. paleolake deposits at SW Melas), but radiolysis is a severe problem at other locations (e.g. Oxia Planum). The data suggest that the relief of the Valles Marineris mounds is currently being reduced by wind erosion, and that dust production on Mars <3 Gya greatly exceeds the modern reservoir of mobile dust.
HMGB1genetic polymorphisms in oral squamous cell carcinoma and oral lichen planus patients

This study examined the single nucleotide polymorphisms (SNPs) in high-mobility group box 1 (HMGB1) gene in patients with oral squamous cell carcinoma (OSCC) and oral lichen planus (OLP).The study was conducted on 93 patients with OSCC, 53 patients with OLP, and 100 controls, all Caucasians of the same ethnicity, matched by age. HMGB1 genotypes for 4 SNPs, 2262G/A (rs1045411), 1177G/C (rs3742305), 3814C/G (rs2249825), and rs4540927, were assessed using TaqMan SNP Genotyping Assays, Applied Biosystems.The HMGB1 1177GG genotype was associated with lymph-node metastasis and tumor stage in OSCCs (P = 0.016 and P = 0.030, respectively). Genotype 1177GG resulted in poorer recurrence-free survival (RFS), P = 0.000. The 1177G/C polymorphism was an independent predictor of RFS compared to GG genotype, P = 0.001. The three polymorphisms were in linkage disequilibrium (LD). The AGC and GGC haplotypes were associated with an increased oral cancer risk, determined over the haplotype odds ratios (HOR = 13.316, P = 0.015, and HOR = 5.769, P = 0.029, respectively). The AGC haplotype was related to erosive OLP progression to OSCC (HOR = 12.179, P = 0.001).HMGB1 polymorphism 1177G/C could be associated with tumor progression and recurrence-free survival in patients with OSCC. The haplotypes of HMGB1 gene might be associated with susceptibility to OSCC and OLP progression to OSCC.
Effects of a JP-8 surrogate and its components on soot in laminar, N2-diluted ethylene co-flow diffusion flames from 1 to 5 atm

Abstract Experimental results are presented for changes in soot volume fraction resulting from the addition of a JP-8 surrogate and each of its components to a N 2 -diluted, C 2 H 4 co-flow diffusion flame. The surrogate, which consists of 77% n-dodecane and 23% m-xylene by volume, was designed to match the threshold soot index of a nominal JP-8 fuel. Total carbon flow rate was constant for all experiments; pre-vaporized liquid fuel was added at two different levels: 2.5% and 5% of the total carbon flow rate. Tests were conducted at pressures from 1 to 5 atm. The use of relatively small amounts of carbon from the liquid fuel resulted in a linear relationship between the peak soot volume fraction and the amount of carbon from the liquid fuel. In these experiments, the peak soot volume fraction was found to be vary with pressure according to a power-law relationship, consistent with prior work on pressure effects on soot. The surrogate fuel showed very similar trends to the JP-8, but yielded lower soot volume fractions. Simulation results for the flames with m-xylene capture the trends of increasing soot volume fraction with increasing carbon from the liquid fuel and with increasing pressure. However, the simulations show smaller increases than were observed in the experiments.
A method for estimating radiation interaction coefficients for tissues from single energy CT

A parametric model for the x-ray linear attenuation coefficient is used to describe the compositional dependence of Hounsfield numbers measured by medical CT scanners. Measurements with materials of known density and composition, that span and evenly sample the compositional range of tissues, are written as linear simultaneous equations and solved for model coefficients. An algorithm is identified for this purpose. Results are expressed as atomic cross-sections in units of barn per electron divided by the attenuation coefficient for water. With the CT scanner characterised, a virtual CT scan can be simulated to predict HN for tissues based upon their known density and composition. Similar calculations using the tabulations and mixture rule deliver attenuation coefficients and mass energy absorption coefficients for mono-energetic radiation 10 keV to 20 MeV. Results are presented for measurements with a radiotherapy CT simulator, the RMI-467 phantom with tissue substitute materials, plus common polymer materials and silicon. Published measurements with earlier generations of the phantom and tissue substitutes using different CT scanners are also considered. Measured atomic cross-sections differ from expectations for mono-energetic radiation due to the use of a filtered spectrum and energy integrating detection system. The cross-sections for different CT scanners are similar, without large variations with kVp. Results are presented showing the relationship between predicted HN for tissues, electron density and photon interaction coefficients for healthy tissues and mono-energetic radiation. A strategy is suggested for accommodating strongly attenuating materials such as calculi and metallic implants.
Bayesian inference and model selection for stochastic epidemics

The ultimate goal of this Fellowship, titled “Bayesian infEReNce And moDel sElecTion for sTochastic Epidemics” (BERNADETTE), is to train a talented researcher through a research project focused on the development of novel statistical methodology for the modeling of infectious diseases like COVID-19. The success of the interdisciplinary project will lead to a number of multidisciplinary innovations in epidemiology, Public Health policy and statistics, which will contribute to the timely identification of optimal disease control strategies. The Fellow – Dr. Lampros Bouranis – will be trained in the fields of statistics and epidemiology, receiving access to a unique training experience at the host – Department of Statistics, Athens University of Economics and Business (AUEB) – and co-hosts. The BERNADETTE outputs will be relevant to healthcare and the EU Epidemic intelligence, by: i) offering novel statistical methodology for the analysis of COVID-19 outbreak data and the description of a number of aspects of the underlying infection pathway of the disease, ii) quantifying the effect of non-pharmaceutical interventions based on an epidemic model, iii) allowing for the forecasting of future case number scenarios, iv) contributing in the assessment of the socio-economic impact of different response strategies for human epidemics in Europe in order to improve European preparedness planning and support decision-making in the framework of national epidemic preparedness plans. The BERNADETTE outputs will contribute to the enhancement of EU scientific excellence. Additionally, the project will enable the establishment of a long-term collaboration between the host and co-hosts, bringing the centers of European research excellence together.
Acquiring assembly skills by robot learning

Present-day industrial robots are made for the purpose of repeating several tasks thousands of times. What the
manufacturing industry needs instead is a robot that can do thousands of tasks, a few times. Programming a robot to solve
just one complex motor task has remained a challenging, costly and time-consuming task. In fact, it has become the key
bottleneck in industrial robotics. Empowering robots with the ability to autonomously learn such tasks is a promising
approach, and, in theory, machine learning has promised fully adaptive control algorithms which learn both by observation
and trial-and-error. However, to date, learning techniques have yet to fulfil this promise, as only few methods manage to
scale into the high-dimensional domains of manipulator robotics, or even the new upcoming trend of collaborative robots.
The goal of the AssemblySkills ERC PoC is to validate an autonomous skill learning system that enables industrial robots to
acquire and improve a rich set of motor skills. Using structured, modular control architectures is a promising concept to scale
robot learning to more complex real-world tasks. In such a modular control architecture, elemental building blocks – called
movement primitives, need to be adapted, sequenced or co-activated simultaneously. Within the ERC PoC AssemblySkills,
our goal is to group these modules into an industry-scale complete software package that can enable industrial robots to
learn new skills (particularly in assembly tasks). The value proposition of our ERC PoC is a cost-effective, novel machine
learning system that can unlock the potential of manufacturing robots by enabling them to learn to select, adapt and
sequence parametrized building blocks such as movement primitives. Our approach is unique in the sense that it can
acquire more than just a single desired trajectory as done in competing approaches, capable of save policy adaptation,
requires only little data and can explain the solution to the robot operator.
POLYMERIC CONCRETE ADMIXTURE CONTAINING A NEW CLASS OF SUPERPLASTICIZER POLYMERS

A novel admixture approach to be used in various concrete formulations as a means of modifying and enhancing performance of the concrete. This invention will provide benefits in a variety of ways, including enhanced control over concrete curing times, increased strength and beneficial changes in concrete formulations, particularly useful for specific applications.
Adaptive backstepping control of lightweight tower wind turbine

This paper investigates the feasibility of operating a wind turbine with lightweight tower in the full load region exploiting an adaptive nonlinear controller that allows the turbine to dynamically lean against the wind while maintaining nominal power output. The use of lightweight structures for towers and foundations would greatly reduce the construction cost of the wind turbine, however extra features ought be included in the control system architecture to avoid tower collapse. An adaptive backstepping collective pitch controller is proposed for tower point tracking control, i.e. to modify the angular deflection of the tower with respect to the vertical axis in response to variations in wind speed. The controller is shown to guarantee asymptotic tracking of the reference trajectory. The performance of the control system is evaluated through deterministic and stochastic simulations including an extreme wind gust event, and the feasibility of stabilizing the tower position while maintaining the rated power output is shown.
Personalised image-based computational modelling framework to forecast prostate cancer

Prostate cancer (PCa) is a major health problem among ageing men worldwide, especially in Europe. However, the medical management of PCa only offers limited individualisation and has led to significant overtreatment and undertreatment, which may compromise patient quality of life and survival respectively. 
Active surveillance is a clinical strategy in which patients with life-threatening PCa are directed to treatment while those with indolent tumours remain closely monitored via regular clinical tests and medical imaging. Multiparametric magnetic resonance imaging (mpMRI) provides high-quality data on PCa and is increasingly used in its diagnosis and surveillance, but computationally exploiting the wealth of data in these images to obtain precise information on tumour evolution to guide clinical management is an unresolved challenge. 
To address this timely issue, this project proposes to derive a personalised predictive mathematical model of PCa based on mpMRI to run organ-scale simulations that improve diagnosis and forecast the patient’s tumour evolution. The model will rely on robust biological and mechanical phenomena described via differential equations whose parameters are identified voxel-wise by solving an inverse problem using the patient’s clinical and mpMRI data at two dates. The model will then be validated by comparing simulation and actual data at a posterior date. The resulting predictive technology offers an unparalleled advance to personalise and optimise active surveillance for PCa, hence meeting many European Commission priorities for research in cancer.
The candidate has previously developed computational models and methods to study PCa growth in clinical scenarios. Building on this ideal background, this project will provide him with crucial scientific techniques and skills to become a leading independent researcher, produce high-impact oral and written communications, and start an active network of collaborations between the US and Europe.
Management of Cultural Heritage in the Central Europe Area

The area of central Europe, due to its history and the mix of different cultures and nations, is characterised by rich and diverse cultural heritage. Unfortunately, this valuable asset is underestimated as a key driver of the development for regional/local economies. A sophisticated and sustainable use of cultural heritage can be indeed especially vital for boosting the development of small- and medium-sized cities. The re-use and exploitation of renovated and revitalised built heritage represents an essential part in this context and should meet the 21st century specific needs as well as be adapted to new economic functions.

The challenges for managing cultural heritage in central Europe are to look for models that ensure better coordinated, integrated and systemic approaches of governance. Ways need also to be identified on how to involve private actors/additional financial sources, whereas the economic interest would match with the protection level of the particular site. The HERMAN project connects ten cities, regions and knowledge institutions that aim to improve the management and valorisation of cultural heritage to better exploit its economic potential. Within their cooperation project they will look for and implement good practices of other European cities that have already successfully implemented efficient solutions in cultural management.
Gardens of the Alps

In order to answer to the adaptation of Alpine tourism to climate changes, to develop activities of summer discoveries of the Alpine Massif by the valorisation of the natural heritage, JARDINALP project unit eight Alpine franco-italian botanic gardens: Garden of Charance, Lautaret, Paradisa, Castelsavoia, Chanousia, Saussurea, Valeria and botanic stations of Marguareis. _x000D_
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In each garden, and around of them, visitors follow discovery paths of the Alpine Massif’s flora. They also can, thanks to a common panel of instruments, discover the Alpine Natural Heritage, visit other gardens of the program and discover some sectors of Alpes which have an emblematic vegetation. _x000D_
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This networking of Alpine gardens furnish to public and local touristic actors an original and innovative cross-border product in synergy with other offers of the territory.
Measurement and instrumentation for cleaning and decommissioning operations

The goal of the MICADO project is to propose a cost-effective solution for non-destructing characterization of nuclear waste, implementing a digitization process that could become a referenced standard facilitating and harmonizing the methodology used for the in-field Waste Management and Dismantling & Decommissioning operations.
The D&D process of nuclear infrastructures demands methods for a full traceability of waste material to improve quality management and operational safety. Precise procedures provide twofold benefits: the optimization of costs, associated with D&D, and the minimization of the dose exposure to operators and personnel.
The absence of a consistent and straightforward solution to characterize all types of materials, along with the lack of an integrated solution for digitizing the enormous amount of data produced, is a critical issue. Now the systems rely on the operator’s ability to maintain high operational skills and quality assurance with precision measurements that unfortunately today very often are associating high uncertainties not allowing therefore a real optimization of the waste.
The utilization of several un-automatized instruments implies taking many notes and inserting them into specific ad-hoc format and on a database manually, without the possibility to combine data including previously available legacy data’s if present.
The RCMS Digi-Waste solution proposed in the MICADO project will result in a proven modular solution offering an opportunity to proactively develop a unified and standardized Waste NDA Characterization Procedure and Method that could become an international reference allowing all Nuclear Operators - Research Laboratories & Safety Authorities to facilitate their exchanges. 
The MICADO project involves some key EU players with major knowledge in nuclear waste having all in common the interest to converge in technologies, methods and implementing a full digitization process applied to nuclear waste management.