SIRIS-Lab/unlabelled-sti-corpus huggingface dataset:
Circular Economy for SMEs

EU 2020 highlights that the EU and Member States should enable SMEs to turn environmental challenges into opportunities. Green growth can offer significant benefits, however as stated in the Small Business Act (EP 2014/2209 INI)) policy makers need to fully understand the potential of the green economy, whilst being aware of the barriers that SMEs face regarding the greening of their products, production processes, business practices and services. The circular economy is a key concept of the green economy, based on optimising systems rather than components, away from ‘Resource to Waste’ to resilient and productive circular systems. 

Strategic alliances between support organisations such as Ellen MacArthur Foundation, McKinsey Company, etc and multinational enterprises have been at the forefront of circular economy exploration and application.  SMEs rarely have the same access to knowledge networks to stay up to date with new technologies, or communicate with potential clients or investors. It is therefore key to understand how SMEs can exploit the opportunities of circular value chains. 

The CESME project address SME inclusion in the circular economy, by interregional meetings identifying good practices aiming to examine how best regional and local authorities and business development agencies can improve relevant policy instruments and design support packages to assist SMEs to enter the circular economy. Through the creation of a return on investment analysis quantifying the economic and social benefits of circular value chains as well as a white book guiding SMEs step by step into circular economy, the CESME partnership hopes to introduce new circular initiatives targeted SMEs. These initiatives will be implemented and tested for feedback and adaptation in order to be replicable tools across EU as well as monitored against their expected impact. Finally, this will lead to the improved effectiveness of the policy instruments addressed by the project partners.
Exploring the Sulfatase 1 Catch Bond Free Energy Landscape using Jarzynski’s Equality

In non-covalent biological adhesion, molecular bonds commonly exhibit a monotonously decreasing life time when subjected to tensile forces (slip bonds). In contrast, catch bonds behave counter intuitively, as they show an increased life time within a certain force interval. To date only a hand full of catch bond displaying systems have been identified. In order to unveil their nature, a number of structural and phenomenological models have been introduced. Regardless of the individual causes for catch bond behavior, it appears evident that the free energy landscapes of these interactions bear more than one binding state. Here, we investigated the catch bond interaction between the hydrophilic domain of the human cell surface sulfatase 1 (Sulf1HD) and its physiological substrate heparan sulfate (HS) by atomic force microscopy based single molecule force spectroscopy (AFM-SMFS). Using Jarzynski's equality, we estimated the associated Gibbs free energy and provide a comprehensive thermodynamic and kinetic characterization of Sulf1HD/HS interaction. Interestingly, the binding potential landscape exhibits two distinct potential wells which confirms the recently suggested two state binding. Even though structural data of Sulf1HD is lacking, our results allow to draft a detailed picture of the directed and processive desulfation of HS.
Safe, fast-charging long-life sodium-ion batteries for vehicles and power storage

Existing battery technologies face a number of serious issues that decades of research have not resolved – charging speed, lifespan, safety, supply chain pressures and environmental impact. 
Tiamat has developed a fast-charging, powerful, long-life sodium-ion (Na-ion) battery that is price-competitive with its lithium and lead acid equivalents.
Its batteries can transform the fast-charging market, replacing outdated technology in electric bikes, scooters, forklift trucks, industrial robots, power tools and buses as well as power storage and supply for home and grid.
Tiamat’s initial target market – which does not include mobile phones, laptops and tablets – was some 7 billion euros as of 2017 and is forecast to grow to at least 20 billion euros by 2025.
The company is the only start-up looking to commercialise a full Na-ion based product that can compete with Lithium-ion batteries in the same energy density category.
Its batteries directly challenge the decades-old, and arguably archaic lead-acid battery technology that is the automotive standard. 
Tiamat’s technology can be stored at zero Volts, making its products safe and easy to store, handle and transport. No copper, nickel or cobalt are used in the batteries – avoiding humanitarian and environmental issues associated with mining those elements.
We are partnering with cell integrators, major battery manufacturers and automotive companies to validate and test our batteries in a wide range of applications.
Tiamat has access to one of the most advanced battery research facilities in Europe and some of the world’s most accomplished energy storage scientists.
Evolution of superFeatures through genetic programming

: The success of automatic classification is intricately linked with an effective feature selection. Previous studies on the use of genetic programming (GP) to solve classification problems have highlighted its benefits, principally its inherent feature selection (a process that is often performed independent of a learning method). In this paper, the problem of classification is recast as a feature generation problem, where GP is used to evolve programs that allow non-linear combination of features to create superFeatures, from which classification tasks can be achieved fairly easily. In order to generate superFeatures robustly, the binary string fitness characterization along with the comparative partner selection strategy is introduced with the aim of promoting optimal convergence. The techniques introduced are applied to two illustrative problems first and then to the real-world problem of audio source classification, with competitive results.
SILICONE FOAM CONTROL AGENT

A method of making silicone-based foam control agents comprising: i) preparing a polysiloxane containing polymer by the polymerisation of siloxane containing monomers and/or oligomers in the presence of an inert organopolysiloxane and/or an organic fluid, a suitable catalyst and optionally an end-blocking agent; ii) where required quenching the polymerisation process; wherein the inert organopolysiloxane and/or organic fluid is substantially retained within the resulting diluted polysiloxane containing polymer; iii) introducing from 0.1 to 10 % by weight of a suitable filler prior to during or subsequent to step (i); iv) optionally introducing up to 5% by weight of a suitable silicone resin during or subsequent to step (i) and v) where required, adapting the foam control agent produced in steps (i) to (iv) into a suitable form of delivery therefor.
Changes in prevalence of diabetes mellitus in the Republic of Azerbaijan in 1994-2012 and prospects for 2030

Aim. To study the changes in prevalence of diabetes mellitus in the Republic of Azerbaijan in 1994-2012 and to predict the changes by 2030. Methods. The data of the number of patients with diabetes mellitus in the Republic of Azerbaijan were gained by analyzing official statistics of Ministry of Healthcare of the Azerbaijan Republic. The population of Azerbaijan in 1994-2012 was also analyzed. Microsoft Excel software package was used for prognosis calculation and graphical representation. Results. In 1994 40 438 patients with diabetes mellitus were registered in the Republic of Azerbaijan, in 2003 - 49 083 pa-tients, and in 2012 the number of patients with diabetes mellitus has reached 151 667 which was 375.06% compared to 1994 and 309.00% compared to 2003. Mid-annual change of the country’s population was calculated, with the gained data used for population prediction for 2030. According to the calculations, the number of officially registered patients with diabetes mellitus should reach 3.73% of the Azerbaijan Republic population by 2030. Conclusion. Statistical data show considerable growth in diabetes mellitus prevalence in the Republic of Azerbaijan. The prediction based on the last 9 years data allows to predict the increase of the number of officially registered patients with diabetes mellitus up to 380 178 patients by 2030, which will make 3.73% of the country’s population.
DISPOSITIF DE RETENUE POUR UN VANTAIL SEMI-FIXE

L'invention concerne un dispositif de retenue pour un vantail semi-fixe (2) coopérant avec un vantail mobile (1) pour fermer une ouverture. Ce dispositif comprend un deuxième organe de retenue (35) apte à occuper une position de référence (ZO) pour coopérer avec un premier organe de retenue (10) pour retenir le vantail semi-fixe (2) en position de fermeture, et à s'écarter de cette position (ZO) selon des premier et deuxième sens opposés (N, P) pour respectivement permettre une libération et un renforcement de cette coopération. Ce dispositif comprend également des premier et deuxième organes de commande (70, 40) apte à coopérer par effet de came pour solliciter le déplacement du deuxième organe de retenue (35) selon le deuxième sens (P), tandis que les premier et deuxième organes de retenue (10, 35) sont aptes à coopérer par effet de came pour solliciter le déplacement selon le premier sens (N). Le dispositif comprend en outre des moyens de rappel (60, 65) du deuxième organe de retenue (35) lorsqu'il est écarté de sa position de référence (Z0) selon un sens de déplacement quelconque parmi les premier et deuxième sens (N, P).
METHOD AND APPARATUS TO ACCOMMODATE BOTH A LEARN MODE OF OPERATION AND A PAIRING MODE OF OPERATION DURING A RELATIONSHIP-ESTABLISHMENT MODE OF OPERATION

A control circuit initiates a relationship-establishment mode of operation and operates in both a learn mode of operation and a pairing mode of operation. When the control circuit completes one of these modes of operation (for example, the learn mode of operation, the pairing mode of operation, or either) the relationship-establishment mode of operation can switch to only using the remaining mode of operation during a remainder of the relationship-establishment mode of operation. One can also disable a previously-established relationship for each of a first category of remote platforms (such as remote platforms that became authorized through a learn mode of operation) when the user presses a button. Upon then detecting a second end-user assertion of the end-user interface, the control circuit can further disable a previously-established relationship with each of a second category of remote platforms (such as remote platforms that became authorized through a pairing mode of operation).
Bioengineered hippocampal organoids for epilepsy treatment

Epilepsy is a life-threatening progressive disorder causing uncontrolled activity of the brain (seizure); it carries among the highest burden of disease and significant social stigma. Temporal lobe epilepsy (TLE) is the most frequent syndrome, the least responsive to medications and the most linked to severe psychiatric and cognitive co-morbidities. When drug resistance ensues, neurosurgery and deep-brain stimulation are invasive options to carefully consider. Thus, TLE treatment demands urgent innovative interventions. 

Is it possible to generate ‘replacement parts’ to heal the diseased brain? The idea of repairing the brain using engineered transplants is nowadays more appealing than ever thanks to the ground-breaking advent of ‘mini-brains in a dish’ (brain organoids). Remarkably, brain organoids can be derived from human stem cells, thus carrying unique potential for targeted studies. However, their application in regenerative medicine has yet to thrive. Therefore, the interaction of brain organoids with mammalian brain tissue remains unexplored.

In this project, I engage in the challenge of generating surrogate brain areas as transplants for epilepsy treatment. Specifically, I will focus on the hippocampus, a central structure in learning and memory which is crucially involved in TLE. I will push an unprecedented biohybrid design based on the synergetic exploitation of organoid technology and innovative neural engineering tools to pursue, for the first time ever, the establishment of a dialogue between engineered and mammalian brain tissue. 
The foundation of NEUROTILES stems in the emerging concept that brain repair strategies from regenerative medicine and neural engineering are distinct yet complementary. In the era of artificial intelligence and nanotechnology, NEUROTILES will promote a revolutionary framework for brain repair strategies and ultimately ignite the establishment of the novel field of ‘enhanced’ regenerative medicine.
All weather autonomous real logistics operations and demonstrations

Connected and automated vehicles can be seen as a revolution in the global automotive industry, bringing a new mobility paradigm and having a huge impact on several economic sectors such as logistics industry.
Significant progress has been made in the field of autonomous truck driving with numerous prototypes. However, challenges need to be addressed in order to ensure the uptake of this breakthrough technology and the future advent of an overall autonomous logistic chain. The deployment of autonomous heavy-duty vehicles is hindered by the current inabilities of these vehicles to work with the right safety and functional level for 24/7 availability (e.g. harsh weather conditions) and by the lack of harmonized regulatory framework.
This project aims at developing and enabling to deploy a safe autonomous transportation systems in a wide range of real-life use cases in a variety of different scenarios. This encompasses the development of autonomous driving system (ADS) capable of handling adverse environmental conditions such as heavy rain, snowfall, fog. The ADS solution will be based on multiple sensor modalities to address 24/7 availability. The ADS will then be integrated into multiple vehicle types used in low-speed areas.
Finally, these vehicles will be deployed, integrated and operated in a variety of real-life use cases to validate their value in the application and identify any limitations: forklift (un)loading in warehouses and industrial plants, hub-to-hub shuttle service on open road, automated baggage dispatching in airports, container transfer operations and vessel loading in ports.
Logistics operations will be optimized thanks to a new fleet management system that will act as a control tower, gathering all information from subsystems (vehicles, road sensors, etc.) to coordinate the operations and protect vulnerable road users. This work should then enable commercial exploitation of the technology and policy recommendations for certifications processes.
Prediction of fuel consumption of mining dump trucks: A neural networks approach

Abstract Fuel consumption of mining dump trucks accounts for about 30% of total energy use in surface mines. Moreover, a fleet of large dump trucks is the main source of greenhouse gas (GHG) generation. Modeling and prediction of fuel consumption per cycle is a valuable tool in assessing both energy costs and the resulting GHG generation. However, only a few studies have been published on fuel prediction in mining operations. In this paper, fuel consumption per cycle of operation was predicted using artificial neural networks (ANN) technique. Explanatory variables were: pay load, loading time, idled while loaded, loaded travel time, empty travel time, and idled while empty. The output variable was the amount of fuel consumed in one cycle. Mean absolute percentage error (MAPE) of 10% demonstrated applicability of ANN in prediction of the fuel consumption. The results demonstrated the considerable effect of mining trucks idle times in fuel consumption. A large portion of the unnecessary energy consumption and GHG generation, in this study, was solely due to avoidable idle times. This necessitates implementation of proper actions/remedies in form of both preventive and corrective actions.
Intrinsic self-healing polymers with a high E-modulus based on dynamic reversible urea bonds

One of the hardest self-healing polymers ever reported has been prepared using the reversible bonds of sterically hindered urea groups. Polymers that can re-form internal chemical links after being scratched or cracked are usually subject to design constraints that lower their mechanical strength. To overcome these constraints, Martin D. Hager and colleagues from Friedrich Schiller University Jena, Germany, created a series of poly(methacrylate) polymers bearing reversible urea units. By simply exposing the starting reagents to brief flashes of light, they prepared a cross-linked polymer featuring the urea units on the poly(methacrylate) chains resulting in mechanically tough materials. After optimizing the cross-link density, the team deliberately scratched the polymer and then heated it to begin the self-healing process. Temperatures of about 100 degree Celsius were sufficient to open urea bonds up and initiate material repair.
Introduction d’un nouveau produit — collection de vêtements de sport pour femme «NUANCE SPORT» société «OKAY»

OK veut lancer un nouveau produit sous le NUANCE SPORT — une ligne de vêtements de sport pour femmes. À cette fin, elle a l’intention d’acquérir des logiciels qui assurent l’automatisation des procédures technologiques dans la production de vêtements, ainsi que des machines et des équipements permettant une production de masse et répétitive, ainsi qu’une flotte de deux voitures pour la distribution de vêtements de sport féminins dans tout le pays à ses clients (la société compte environ 300 clients actifs).
Evolution and character of supra-salt faults in the Easternmost Hammerfest Basin, SW Barents Sea

Abstract This study investigates the evolution of supra-salt faults in the Eastern Hammerfest Basin using high–quality seismic reflection data. Traditional techniques of displacement analysis, including the variation of fault displacement (throw) against distance (x), depth (z), expansion and growth indices were adopted. Fault reactivation was assessed using bivariate plots of a) cumulative throw vs. age and b) throw (t) vs. depth of nine (9) representative faults. The interpreted faults are supra-salt crestal and synclinal faults striking NE, E and SE. These faults have complicated t-x and t-z plots and are characterized by considerable stratigraphic thickening in their downthrown section. Faults in the study area have developed over the salt structure since latest Paleozoic times; some of them were reactivated by Early to Middle Triassic through dip linkage of initially isolated fault sets. Along strike, the fault exhibit complex segmentation through coalescence of several subunits linked by local throw/displacement minima. Expansion and growth indices show that the faults of the study area developed during the deposition of Paleozoic to Early Cretaceous sediments by polycyclic growth involving both blind and syn-sedimentary activity. An important piece of information from this study is that fault propagation is controlled by lithological heterogeneity and that both lateral and vertical segmentation of faults are important for hydrocarbon migration within the Triassic to Late Cretaceous interval.
WAFER AREA PRESSURE CONTROL FOR PLASMA CONFINEMENT

A plasma processing chamber is provided which provides improved wafer area pressure control. The plasma processing chamber is a vacuum chamber with a device connected for generating and sustaining a plasma. Part of this device would be an etchant gas source and an exhaust port. A confinement ring defines an area above a wafer. The wafer area pressure is dependent on the pressure drop across the confinement ring. The confinement ring is part of a wafer area pressure control device that provides wafer area pressure control range greater than 100 %. Such a wafer area pressure control device may be three adjustable confinement rings and a confinement block on a holder that may be used to provide the desired wafer area pressure control.
Peroxisome proliferator-activated receptors (PPARs) and PPAR agonists: the ‘future’ in dermatology therapeutics?

Peroxisome proliferator-activated receptors (PPARs) are nuclear hormone receptors and comprise three different isoforms namely PPARα, PPARγ, and PPARβ/δ with PPARβ/δ being the predominant subtype in human keratinocytes. After binding with specific ligands, PPARs regulate gene expression, cell growth and differentiation, apoptosis, inflammatory responses, and tumorogenesis. PPARs also modulate a wide variety of skin functions including keratinocyte proliferation, epidermal barrier formation, wound healing, melanocyte proliferation, and sebum production. Recent studies have shown the importance of PPARs in the pathogenesis of many dermatological disorders. Clinical trials have suggested possible role of PPAR agonists in the management of various dermatoses ranging from acne vulgaris, psoriasis, hirsutism, and lipodystrophy to cutaneous malignancies including melanoma. This article is intended to be a primer for dermatologists in their understanding of clinical relevance of PPARs and PPAR agonists in dermatology therapeutics.
Backstepping-based neural adaptive control for saturated nonlinear systems

In this paper, neural adaptive backstepping control is investigated for a class of nonlinear systems with a saturated control input. To deal with the tracking problem in the face of input saturation, effective auxiliary systems are constructed, which generate signals preventing the stability of the closed-loop system, and the learning capabilities of adaptation laws from being destroyed. Radial basis function neural networks (RBF NNs) are used in the online learning of unknown dynamics. The semi-global bounded stability of the closed-loop system under the proposed control law is guaranteed by utilizing Lyapunov stability theory, and the system output tracks the desired curve with only small error. Simulation results demonstrate the effectiveness of the proposed control scheme.
Tenant Oriented Lock Granularity Adjustment Strategy in the Shared Storage Multi-tenant Database

SaaS is a perfect technology to achieve scale economy. It uses multi-tenant to allow database to share storage but with irregular load, untraceable transaction characteristics and so on. TOL mechanism provides one granularity between the upper coarse-grained granularity and the lower finegrained granularity for each tenant. But the granularity may not be the most suitable. We define the cluster method and the diffusion method to support the granularity adjustment for a single tenant. Cluster is to make the granularity adjust towards coarser while diffusion gains opposite effect. Because TOL takes advantage of data distribution in multi-tenant database, we combine several aspects when the adjustment strategy is established, including basic table plus extension table and transactions feature. It focuses on locating a more suitable granularity size for one tenant between coarse-grained and fine-grained. In addition, we give experiments indicating that the lock granularity adjustment method is feasible and the adjustment strategy is effective.