SIRIS-Lab/unlabelled-sti-corpus huggingface dataset:
Visible light communication (vlc) application for mobile devices as control access, validation, master key or secure payment solution.

LightBee S.L. innovated the solution which uses LEDs installed in any transmitter to transmit binary codes by means of light modulation to an optical receiver which later decodes the light flash. The light is transmitted at a very high speed to avoid the possibility to distinguish values by video camera or human eye. It allows auto check-in and access control to private property or office only with the mobile information. 

The LightKey product based on Visible Light Communication (VLC) is very powerful and at the same time low cost technology, that can be adapted to grant safe access permission by using merely mobile device with the performance similar to intrusive and expensive NFC and RFID technologies. The set consists of Control Unit, Optical Receiver, mobile application and uses standard electronic lock. 

As there is an increasingly urgent need for authenticated entrance and the universal integration of mobile devices in our society is observed, LightKey has the chance to meet the broad range of innovative customers of the Access Control Market: private companies and independent users (hotels, complexes, condominiums, car makers) and public customers where security is a top priority (hospitals, banks, administration). 

When considering further proliferation of solid-state lighting (SSL), LED importance, the fact that nowadays technologies: NFC, Bluetooth, WIFI are subject of security problems related to data transmissions and moreover the increasing crime rate related to domestic burglary worldwide, VLC can become the most promising technology in terms of commercial viability. 

A full assessment of customer needs and the elaboration of a realistic business plan with in depth market feasibility study is the main objective of present Phase 1. After positive output following tasks will be addressed during Phase 2: analysis of remote communication, optical receiver optimization, integration with other technologies, certification, cloud service development.
Open dynamic manufacturing operating system for smart plug-and-produce automation components

Higher agility for the European Manufacturing Industry is the main MOTIVATION for the openMOS project. While automated systems are appealing to achieve high productivity and quality requirements, their sensitivity to change is becoming increasingly a bottleneck to substantial reduction of lot sizes and more frequent change-overs. 
The project VISION is to enable full economic sustainability of the production systems based on intelligent modular plug-and-produce equipment. To achieve this, it is focusing on three main innovation strands: 1) embedding plug-and-produce capabilities into automation devices, robots and machines, 2) enabling vertical and horizontal connectivity between plug-and-produce automation components and higher level control and business functions, and 3) creating a easily extendable and adaptable manufacturing operating system (MOS) that permits the easy introduction of new products, work orders and changes in the equipment and allows easy deployment of optimisation and changeover management strategies. The targeted INNOVATION is a common, openly accessible plug-and-produce system platform which allows all stakeholders in the automation system value chain to come together and jointly develop and exploit solutions. Therefore, the project is proposing to integrate well established plug-and-produce system concepts from many years of research in this field, into industrial-relevant technology platforms which have emerged in recent years. 
As the vast majority of components/ devices/ machine manufacturers and system integrators are SMEs, plug-and-produce can only be achieved by placing specific SME requirements at the forefront: solutions by, and for, SMEs.
The RTD approach will be driven by proposed industrial scenarios and pilot implementations which will be carried out to systematically test and validate the readiness of the targeted exploitable results in three key industrial sectors (white goods, automotive and electronics).
Development of an Information System for Natural Risk Management in the Mediterranean

Earthquakes, landslides, forest fires are a permanent threat for Greece, Sicily and Calabria, causing fatalities, material damage at regional, national and trans-national level. Especially earthquakes are the mostly feared by local populations, causing paralysis of local socio-economical activities. Landslides can be predicted and prevented by taking appropriate actions “a priori”. Earthquakes and forest fires are unpredictable but their physical consequences can be accurately predicted, thus allowing the enactment of effective prevention measures towards the reduction of vulnerability. Consequently, natural risks can be reduced or prevented through effective management.
Well-Being among european youth: the contribution of student teacher relationships in the secondary-school population

Creating environments that foster young people´s wellbeing is one of the current priorities for the European Union. Increasingly such efforts are conceptually framed through a focus on positive paradigms across the life course. 
Social science evidence indicates that supportive relationships with significant adults are important determinants of young people’s wellbeing and future life chances. Recently the significance of non-parental adults in shaping youth wellbeing has been examined. In this vein, WEY-CRISP focuses on the contribution of teachers to the construction and maintenance of wellbeing.
Understanding the significance of teacher connectedness for youth has been constrained by inconsistencies in definitions and measures. Consequently, the character of the contribution of such relationships to wellbeing (from teachers as complementary sources of instrumental support to key mentors for youth) is also unclear.  
WEY-CRISP will:
1.Investigate the determinants of teacher connectedness and potential for being a protective health factor, including diverse groups of youth (ethnicity, age, gender) and different contexts e.g. low parental support. 
2.Clarify on the nature of teacher connectedness and develop an effective measure for its assessment that taps into the main components for wellbeing.
3.Generate synergistic links between approaches in education and health research. 
The investigation will use a mixed methodology (quantitative and qualitative), including youth centred participatory research strategies. 
WEY-CRISP will link with a multidisciplinary, international network of experts on adolescence via the WHO (Europe) cross-national HBSC study, aiding in the maximization of the impact across the European Union and enhancing the European Research Area. The experienced researcher will access significant methodological training and career development opportunities including leadership skills via engagement with policy makers and researchers.
Small vessel diseases in a mechanistic perspective: targets for intervention affected pathways and mechanistic exploitation for prevention of stroke and dementia

Stroke and dementia rank among the most pressing health issues in Europe. Cerebral small vessel diseases (SVDs) have emerged as a central link between these two major co-morbidities. SVDs account for more than 30% of strokes and at least 40% of dementia cases. They encounter multiple distinct diseases that can be separated based on their underlying genetic defects, risk factors, and clinical presentations. Despite this profound impact on human health, there are no treatments with proven efficacy against SVDs. The applicants have made major progress in identifying key mechanisms involved in SVDs and their co-morbidities. We recently identified blood pressure variability as a major independent risk factor for multiple SVDs, stroke, and dementia and illuminated the roles of the blood brain barrier and the extracellular matrix in small vessel function. We further identified novel molecular pathways (TIMP3, LTBP1, TGFß) that are shared between different SVDs and thus point towards common mechanisms. This EU network, which brings together basic scientists and academic clinicians, will make use of novel animal models and expertly phenotyped patient cohorts to identify key mechanisms common to multiple SVDs and determine how these mechanisms contribute to individual SVDs. We will: i) identify common molecular, cellular, and physiological mechanisms that compromise the function of microvessels in different SVDs; ii) determine how these common mechanistic defects intersect to drive brain damage; and iii) validate the relevance of mechanisms through interventions in experimental systems (isolated microvessels and in vivo) and in patients (exploratory proof of concept trials). Our resources including novel animal models and state-of-the art technologies (e.g. proteomics & ultra-high field MRI) as well as expertise in clinical trials support the feasibility of the approach. In fact, studies by the applicants already revealed novel attractive targets for therapeutic intervention.
AGILE MANUFACTURING FOR COMPETITIVENESS AND PRODUCT INNOVATION

THE PROJECT HAS A DECLARED MANUFACTURING VOCATION, THUS FULLY INTEGRATING ITSELF INTO THE FIELD OF SPECIALISATION Â¿SMART MANUFACTURINGÂ¿. THE PROPOSING GROUP AIMS TO DEVELOP INTERDISCIPLINARY METHODOLOGIES AND APPROACHES, BASED ON THE ABILITY TO RAPIDLY AND FLEXIBLY CONVERT PRODUCTION PROCESSES AND LINES, AIMED AT INCREASING COMPETITIVENESS AND PRODUCT INNOVATION. IT IS THEREFORE AN INDUSTRIAL REACTION TO THE COVID-19 EMERGENCY, BUILT ON FLEXIBILITY, CONVERSION AND RESILIENCE, WHOSE RESULTS, HOWEVER, HAVE REPERCUSSIONS THAT GO BEYOND THE TEMPORAL LIMITS OF THE EMERGENCY, IN ORDER TO PLACE ITSELF IN A WIDER AREA OF CORPORATE COMPETITIVENESS FOLLOWING THE DICTATES OF THE NEW PARADIGM INDUSTRY 4.0. THE AGILE PROJECT INTRODUCES THESE THREE ASPECTS IN THE CONTEXT OF SPECIFICATIONS (AND WELL REPRESENTATIVE OF THE REGIONAL MANUFACTURING) TYPES OF PRODUCTION LINES: — FOUNDRY OF ALUMINIUM ALLOYS OF MAGNESIUM AND CAST IRON ALLOYS, — ROLLING
A Direct Differential Approach to Photometric Stereo with Perspective Viewing

Shape from shading and photometric stereo are two fundamental problems in computer vision aimed at reconstructing surface depth given either a single image taken under a known light source or multiple images taken under different illuminations from the same viewing angle. Whereas the former uses partial differential equation techniques to solve the image irradiance equation, the latter can be expressed as a linear system of equations in surface derivatives when three or more images are given. Therefore, it seems that current photometric stereo techniques do not extract all possible depth information from each image by itself. Extending our previous results on this problem, we consider the more realistic perspective projection of surfaces during the photographic process. Under this assumption, there is a unique weak solution (Lipschitz continuous) to the problem at hand, solving the well-known convex/concave ambiguity of the shape from shading problem. The main contribution of this paper is based on a new ...
Minimal Conditions for Protocell Stationary Growth

We show that self-replication of a chemical system encapsulated within a membrane growing from within is possible without any explicit feature such as autocatalysis or metabolic closure, and without the need for their emergence through complexity. We use a protocell model relying upon random conservative chemical reaction networks with arbitrary stoichiometry, and we investigate the protocell's capability for self-replication, for various numbers of reactions in the network. We elucidate the underlying mechanisms in terms of simple minimal conditions pertaining only to the topology of the embedded chemical reaction network. A necessary condition is that each moiety must be fed, and a sufficient condition is that each siphon is fed. Although these minimal conditions are purely topological, by further endowing conservative chemical reaction networks with thermodynamically consistent kinetics, we show that the growth rate tends to increase on increasing the Gibbs energy per unit molecular weight of the nutrient and on decreasing that of the membrane precursor.
Machine learning for particle physics

This project proposes to use modern Machine Learning (ML),  particularly Deep Learning (DL), as a breakthrough solution to address the scientific, technological, and financial challenges that High Energy Physics (HEP) will face in the decade ahead. The quest for new physics is increasing the complexity of the experiments and, consequently, the human and financial costs to operate these detectors, with experiments facing at best flat budgets. ML offers a way out of this impasse. With the development of DL, ML has successfully addressed tasks such as image recognition and text understanding, which eventually opened the way to automatizing complex tasks. These progresses have the potential to revolutionize HEP experimental techniques. We propose to apply cutting-edge ML technologies to HEP problems, paving the way to self-operating detectors, capable of visually inspecting events and identifying the physics process generating them, while monitoring the goodness of the data, the correct functioning of the detector components and, if any, the occurrence of anomalous events caused by unspecified new physics processes. We structure the work in a set of working packages, representing intermediate steps towards this final goal. We propose to apply ML to data taking, event identification, data-taking monitoring, and event reconstruction as intermediate steps toward using these techniques for unsupervised physics searches. The project resources will by used to create a team of computer scientists, who will carry on a systematic R&D program to apply  cutting-edge ML technology to HEP: reinforced learning, generative models, event indexing, data mining, anomaly and outliers detection, etc. Being hosted at CERN, the project will benefit from existing computing infrastructures, large datasets availability, the presence of local experts of each aspect of HEP, and established collaborations with private companies on hardware and software R&D.
Sulfate Attack According to the Quantity of Composition of Cement and Mineral Admixtures

The primary factors affecting concrete sulfate resistance are the chemical composition of the Portland cement, and the chemistry and quantity of mineral admixtures. To investigate the effect of those on the sulfate attack, the testing program involved several different mortar mixes using the standardized test, ASTM C1012. Four different cements were evaluated, including one Type I cement, two Type I-II cements, and one Type V cement. Mortar mixes were also made with mineral admixtures, as each cement was combined with three different types of mineral admixtures. One Class F fly ash, one Class C fly ash, and one ground granulated blast furnace slag (GGBFS) were added in various percent volumetric replacement levels. Expansion measurements were taken and investigated with the expansion criteria recommended by ASTM.
Modeling Paying Behavior in Game Social Networks

Online gaming is one of the largest industries on the Internet, generating tens of billions of dollars in revenues annually. One core problem in online game is to find and convert free users into paying customers, which is of great importance for the sustainable development of almost all online games. Although much research has been conducted, there are still several challenges that remain largely unsolved: What are the fundamental factors that trigger the users to pay? How does users? paying behavior influence each other in the game social network? How to design a prediction model to recognize those potential users who are likely to pay? In this paper, employing two large online games as the basis, we study how a user becomes a new paying user in the games. In particular, we examine how users' paying behavior influences each other in the game social network. We study this problem from various sociological perspectives including strong/weak ties, social structural diversity and social influence. Based on the discovered patterns, we propose a learning framework to predict potential new payers. The framework can learn a model using features associated with users and then use the social relationships between users to refine the learned model. We test the proposed framework using nearly 50 billion user activities from two real games. Our experiments show that the proposed framework significantly improves the prediction accuracy by up to 3-11% compared to several alternative methods. The study also unveils several intriguing social phenomena from the data. For example, influence indeed exists among users for the paying behavior. The likelihood of a user becoming a new paying user is 5 times higher than chance when he has 5 paying neighbors of strong tie. We have deployed the proposed algorithm into the game, and the Lift_Ratio has been improved up to 196% compared to the prior strategy.
Lighting instrument

The present invention aims at providing a blue-aimed phosphor powder which is more excellent in emission characteristic than the conventional rare-earth activated sialon phosphors and which is more excellent in durability than the conventional oxide phosphors. The solving means resides in: firing a starting material mixture in a nitrogen atmosphere at a temperature range between 1,500°C inclusive and 2,200°C inclusive, wherein the starting material mixture is a mixture of metallic compounds, and is capable of constituting a composition comprising M, A, Si, Al, O, and N (M is one kind or two or more kinds of element(s) selected from Mn, Ce, Nd, Sm, Eu, Tb, Dy, Ho, Er, Tm, and Yb; and A is one kind or two or more kinds of element(s) selected from C, Si, Ge, Sn, B, Ga, In, Mg, Ca, Sr, Ba, Sc, Y, La, Gd, Lu, Ti, Zr, Hf, Ta, and W) by firing; to obtain a phosphor which emits fluorescence having a peak at a wavelength within a range of 400nm to 700nm, by irradiation of an excitation source.
Assessment of human dermal exposure to microplastics additive chemicals and the risk arising from such exposure using innovative 3d-human skin equivalents

Dermplast is a multidisciplinary project that combines advanced environmental analytical chemistry with innovative 3D-human skin equivalent models (3D-HSE) to study the dermal absorption of toxic plastic additives (e.g. plasticizers and flame retardants) upon skin contact with microplastics (MPs) and assess the risk arising from such exposure.
Recent studies have revealed direct human exposure to MPs externally and internally, confirmed by detection of MPs in human stool. However, very little is known on the extent of human exposure to MPs via different pathways and the risk it poses to human health. While there is little evidence of adverse effects associated directly with exposure to pristine MPs, there is major concern over potential toxicity from released plastic additives (e.g. plasticizers and flame retardants), many of which have been associated with serious adverse effects including cancer. 
The main hypothesis that Dermplast tests is that MP additive chemicals can leach out into sweat and be absorbed through human skin; thus frequent contact with MPs can lead to significant body burdens of hazardous chemicals, with consequent adverse health impacts. 
This will be achieved using innovative 3D-HSE cultures as sustainable, efficient alternatives to animal/human tissues. The results will be applied to develop an advanced pharmacokinetic exposure model to estimate human uptake of toxic chemicals from dermal contact with MPs and assess the risk against current exposure guidelines and toxic endpoints for these chemicals.
With current research focused mainly on isolation and characterisation of MPs in different matrices (e.g. food, water and air), DermPlast will make substantial advances to the state-of-knowledge by providing novel insight into risk assessment of MPs exposure in humans. This will benefit public health and regulators by providing the essential knowledge base required to inform policies to control human exposure to MPs.
A new approach for the geological risk evaluation of coal resources through a geostatistical simulation

Estimations of mineral resources and ore reserves have been recently widely used by mining engineers and investors. The classification framework based on the prepared code by the Joint Ore Reserves Committee of The Australasian Institute of Mining and Metallurgy, Australian Institute of Geoscientists and Minerals Council of Australia (JORC code), which is one of the international standards for mineral resource and ore reserve reporting, provides a template system that conforms to international society requirements. Recent research has shown that an existing fault risk can affect the mineral resource and ore reserve estimation. According to this research, the faulted area that is involved in the effect on the estimated region is so extensive that it is not distinguishable. In this research, a new method called FGT (F for fault, G for grade and T for thickness) is introduced and presented for the estimation of mineral resources. The proposed method can provide an error map of a particular aspect of the combination of coal accumulation (G), fault risk (F) and thickness (T), and its output would categorise the mineral resources. This method was implemented in the Parvadeh Ш coal deposit, which is located in the eastern portion of Central Iran. The deposit contains five seams named B1, B2, C1, C2 and D; of these, C1 was selected as the most important seam in the exploratory grid analysis. Thus, C1 alone can reflect the properties of the Parvadeh Ш deposit. In this study, we compared the conventional method and the FGT method. This comparison indicated that the areas that should be rejected from the region in the FGT method are less and more distinguishable than those determined with the conventional method. Therefore, the inferred resources can be completely differentiated from the indicated and measured resources with a high resolution. The conventional method cannot distinguish between these three categories at this level of resolution. Therefore, the FGT approach has high precision in classifying the coal resource compared to the conventional method.
ELECTRODE ORIENTATION AND PARALLELISM ADJUSTMENT MECHANISM FOR PLASMA PROCESSING SYSTEMS

A mechanism for adjusting an orientation of an electrode in a plasma processing chamber is disclosed. The plasma processing chamber may be utilized to process at least a substrate, which may be inserted into the plasma processing chamber in an insertion direction. The mechanism may include a support plate disposed outside a chamber wall of the plasma processing chamber and pivoted relative to the chamber wall. The support plate may have a first thread. The mechanism may also include an adjustment screw having a second thread that engages the first thread. Turning the adjustment screw may cause translation of a portion of the support plate relative to the adjustment screw. The translation of the portion of the support plate may cause rotation of the support plate relative to the chamber wall, thereby rotating the electrode with respect to an axis that is orthogonal to the insertion direction.
PICCONALBICOCCO S.R.L.

DEPUIS 1922, UN MAGASIN DE RÉFÉRENCE POUR LES AMATEURS DE DESIGN ET D’AMEUBLEMENT. PICCONALBICOCCO, UNE ENTREPRISE DE VENTE AU DÉTAIL, PROPOSE DANS SES SALLES D’EXPOSITION UNE ÉQUIPE DE DESIGNERS EXPÉRIMENTÉS, CAPABLES DE CRÉER DES SOLUTIONS PERSONNALISÉES. IL SUIT ATTENTIVEMENT LES DÉVELOPPEMENTS DU CHANTIER, DE LA CONCEPTION TECHNIQUE AUX TRAVAUX DE MENUISERIE. CONCEPTION, EXCLUSIVITÉ ET CAPACITÉ À RÉALISER UN PROJET, MODIFIABLE ET EXTENSIBLE, CAPABLE DE LIVRER AU CLIENT UN PRODUIT UNIQUE ET INNOVANT: VOICI LES PRINCIPALES CARACTÉRISTIQUES DE PICCONALBICOCCO.