SIRIS-Lab/unlabelled-sti-corpus huggingface dataset:
Integration of migrants in the enlarged Europe and policies for the return of productive intellect

Immigration is a complex issue in the transition process of the old EU of the 15 to the eastward enlargement of the EU for both, the new EU border areas of today and for those regions that recently have or will become EU border areas. Within the CADSES area, immigration flows have to be managed by many regions and countries such as Veneto or Austria and recently also by the newly acceded countries. Parts of Poland, Slovakia and Hungary are now new border regions of the EU and face immigration-related problems while Romania and Serbia have experienced growing outflows of citizens towards EU Member States in recent years. The phenomenon means organisational and social challenges that have to be dealt with by better instruments and policies. MIGRALINK’s main goals are to strengthen transnational co-operation in the governance of immigration flows in and between the seven countries participating in the project (Italy, Austria, Hungary, Slovakia, Poland, Romania, and Serbia and Montenegro) and to provide immigrants with concrete return opportunities, offering appropriate training and entrepreneurship support, and hence contributing also to the economic and social development of poorer regions in the new EU Member States. A transnational network of public and private organisations concerned with immigration issues will be established and serve as a platform for exchanging information. It will also define potential return strategies for immigrants who then contribute to the development of their countries of origin. Moreover, a benchmark of strategies and services to foster the social inclusion of immigrants is planned.
Radiation-stimulated surface diffusion of adatoms on a tungsten {321} face

The surface erosion of tungsten bombarded with accelerated 5-keV helium atoms has been studied by the method of field-ion microscopy. Radiation-stimulated appearance of adatoms localized in the central region of terraces on the {321} W face has been observed. The distribution of W adatoms on {321} terraces is characterized by the presence of zones free of adatoms in the vicinity of atomic steps. The existence of “empty” zones upon irradiation is evidence of transient surface diffusion. The diffusion path lengths of adatoms on the {321} W face reach six interatomic distances and reveal anisotropy of the radiation-stimulated transient surface diffusion.
Develop an innovative computer system which understands contractual documents by applying artificial intelligence

Ginkgo Analytics want to develop a contract management solution which understands and interprets contracts from different sources (e,g. procurement, sales, projects, Human Resources). This solves the problem that contractual and legal knowledge is rarely available in sufficient capacity in most SMEs. Therefore a smart service is developed which is self-learning and understand contracts and provides legal advise. To achieve this goal an Innovation Associate is required which is capable to develop natural language processing algorithms using machine learning and deep learning technology. The solution can be used by all SMEs globally and can be applied to all contracts which manage value generation with a total volume of several Trillion EUR.
Teaching dancing with ideokinetic principles

Foreword by Lynn Martin vii Introduction ix Chapter 1. Beams of Light 1 Appendix: Lexicons of the Body 18 Chapter 2. Relaxation 21 Appendix: Constructive Rest by Lulu E. Sweigard 35 Chapter 3. Baking Biscuits and Kinesthesia 37 Appendix: The Dancer's Posture by Lulu E. Sweigard, with Introduction by Martha Hill 47 Chapter 4. Doctors, Dancing, and Ideokinesis 54 Appendix: Better Dancing through Better Body Balance by Lulu E. Sweigard 69 Chapter 5. Mirror, Mirror ... 73 Appendix: Accentuate the Positive ... 86 Chapter 6. Imagery and Habit 90 Appendix: Walking Bundles of Habit by William James 100 Chapter 7. More about Teaching Dancing 101 Appendix: Letter XI by Jean-Georges Noverre 113 References Cited 119 Author Index 123 Subject Index 125
Environmental Impacts of Tourism on a French Urban Coastal Destination: Perceptions of German and British Visitors

This study presents an evaluation of the environmental impacts of tourism on the city of Nice using two well-established marketing methods, importance–performance analysis (IPA) and the gap method. Environmental impacts are evaluated by visitors from the two main generating markets of the destination: UK and Germany. The analysis of 211 visitor surveys identified that most of the environmental attributes of the destination required management action. Using the gap method, marginal differences were found on visitors' importance and performance scores of environmental impacts. IPA revealed that most of the environmental impacts measured needed attention, irrespective of visitor nationality. The results suggest that IPA may be a more valuable destination performance assessment tool than using the gap method alone. Eleven importance and only five performance scores were evaluated significantly differently by German and British visitors. Implications for the use of IPA as a destination performance assessment tool and some environmental management strategies are suggested for Nice. Suggestions are also offered on communication strategies for the British and German markets to improve perceptions of the environmental quality of Nice.
STEFANO TRAVERSO

STEFANO TRAVERSO’S STUDIO HAS BEEN OPERATING SINCE 2007 AS AN ACCOUNTANT FOR COMPANIES AND PROFESSIONALS, SINCE 2015 HE HAS BEEN ENROLLED IN THE ASSOCIATION INT (NATIONAL TAX INSTITUTE) IN WHICH HE OPERATES ACTIVELY AND THANKS TO WHICH HE IS CONSTANTLY AND MANDATORYLY UPDATED FROM A REGULATORY POINT OF VIEW. CURRENTLY, IT IS POSSIBLE TO FORGE THE TITLE OF QUALIFIED TAXER, THANKS TO THE CERTIFICATE OF QUALITY ‘ISSUED BY THE ASSOCIATION ITSELF, AND THE TITLE OF CERTIFIED TAXMAN, THANKS TO THE CERTIFICATION OBTAINED IN DECEMBER OF 2019 FOLLOWING THE EXAMINATION SESSION OF THE KIWA CERTIFICATION COMPANY’.
NARROW BAND SYNCHRONIZATION SIGNAL

In order to address the needs of narrow band communication, eNB-based processing and/or UE-based processing is provided to achieve robust detection of cell ID and SFN timing location using NB-SSS. A base station constructs a NB-SSS signal using a root index of a Zadoff-Chu (ZC) sequence, a scrambling code, a cyclic shift or phase ramping sequence, and an interleaving sequence, wherein a combination of the ZC root index, the scrambling code index, the cyclic shift or phase ramping sequence index, and the interleaving sequence index signals information for a cell identifier (e.g., PCID) and frame timing. The ZC sequence used may be a long ZC sequence constructed to span a total number of tones allocated to an SSS sequence or may be a concatenation of multiple ZC sequences, wherein the concatenated ZC sequences span a total number of tones allocated to an SSS sequence.
Jiangxi Rural Culture Demand Research Under the Background of Revitalization and Development of the Central Soviet Area

Cultural construction in rural areas are in jiangxi province,farmers' entertainment life is monotonous,cultural undertakings funds inadequacy,run-down cultural facilities,weak cultural construction and cultural construction becomes a mere formality. Rural culture demand presents the demand for entertainment and leisure,demand for science and education,the demand of modern information,the demand for social activities and other layers. We should perfect the system of the rural cultural construction,develop the rural economy and broaden the financing channels,strengthen the rural cultural construction,adhere to the policy of developing agriculture science and education,and play the lead role of traditional culture,to solve the pressing needs of the current farmers to culture and the contradiction between the lack of cultural resources.
Innovative depalletiser for the automated feeding of signatures in the bookbinding industry.

D-PAL is an innovative depalletiser based on grip technology used for the stacks of signatures handling and feeding the hardcover bookbinding machine in the printing, bookbinding and graphics atrs industry. 
D-PAL will increase the competiveness of the printing industry by improving the workflows and by saving approx. 3.6% of the printing cost directly related to labour cost for depalletising. D-PAL reduces problems related to the Health and Safety of the workers, is easy to operate and avoids the quality defects due to human error factor due to repetitive tasks. D-PAL is able to depalletise at a speed of 3600-7000 books per hour with high precision, flexibility and versatility. D-PAL is adapted to current methods of automated palletising with paper separators between the layers and is 20% less expensive than competitive solutions. 
D-PAL has been developed by LARGOIKO S.L.L, a Spanish Mechatronics Engineering enterprise that designs and carries out the automatization of industrial processes, special machines or under demand since 1999.
European Union will be also impacted by D-PAL. D-PAL will be 100% manufactured in Europe (Spain) and it will attract foreign capital from USA.
D-PAL will have impact in our company, LARGOIKO. We have invested more than €0.4M and we will invest €1.55M more in this project to put into the market D-PAL by January 2019. According to our forecast, we will have revenues of €9,100,000 by year 2023 from sales of our D-PAL depalletiser. The ROI of the project will be 2.60. 
During Phase 1 execution, we will develop a feasibility study including a business plan to assess the technological feasibility and economic viability. The general aim of D-PAL project is put into the market 8 units of our D-PAL by 2019.
Dynamics of a Nonlocal Dispersal Model with a Nonlocal Reaction Term

In this paper, we study a class of nonlocal dispersal problem with a nonlocal term arising in population dynamics: [Formula: see text] where [Formula: see text] is a bounded domain, [Formula: see text], [Formula: see text] represents the nonlocal dispersal operator with continuous and non-negative dispersal kernel. The kernel [Formula: see text] is assumed to be non-negative and is allowed to have a degeneracy in a smooth subdomain [Formula: see text] of [Formula: see text]. When [Formula: see text] is either positive or vanishes in a subdomain, we respectively investigate the existence, multiplicity and asymptotical stability of positive steady states under the local/global variation of parameter by means of sub-supersolution method, Lyapunov–Schmidt reduction, and bifurcation theory.
Studies on substrate evaluation for mass multiplication of Trichoderma spp. and their plant growth promotion activity in tomato

The use of micro-organisms that antagonize plant pathogens (biological control) is risk-free when it results in enhancement of resident antagonists and with additional benefit, when it provides the plant growth promotion activity. Ninety per cent of such applications have been carried out with different strains of Trichoderma which have long been recognized as agents for the control of plant disease and for their ability to increase plant growth and development. Due to their antifungal and plant growth promotion properties, many Trichoderma spp. like T. asperellum, T. atroviride, T. harzianum, T. hamatum, T. koningii, T. virens and T. viride are widely used for biocontrol of plant diseases incited by fungal pathogens. In the present investigation, a set of 5 local isolates of Trichoderma harzianum from Madhya Pradesh were used for evaluating their plant growth promotion potential in tomato and it was observed that isolates were having differential inborn capability to provide growth promotion when supplemented as seed and seedling treatment. With the aim of development of commercial formulation for direct use by farmers, five small millet substrates were used and it was observed that barnyard millet maximum supported the colonization of Trichoderma spp. and served as economic source for its multiplication to develop commercial formulation under laboratory conditions.
Multiphoton microscopy and ultrafast spectroscopy: imaging meets quantum

In the quest to decipher the chain of life from molecules to cells, the biophysical questions being asked increasingly demand techniques that are capable of identifying specific biomolecules in their native environment at the smallest possible scale, and measuring their interactions quantitatively without perturbing the system under observation. Laser-based optical microscopy is a key technology to drive this progress in the 21st century. Still, many challenges remain in particular toward i) achieving imaging with biomolecular specificity without the artefacts from sample staining, ii) quantitative imaging, and iii) single molecule sensitivity. Progress toward biomolecular specificity at very high temporal resolution has been brought by the development of ultrafast two-dimensional electronic spectroscopy, able to address the importance of quantum coherences with the potential to unravel the fundamental machinery of Nature. Yet, measuring quantum phenomena with an optical microscope is technically challenging, and far from real-world biological applications. MUSIQ is designed as an innovative research and training network, where we will recruit 15 Early Stage Researchers to work toward the central ambitious goal of developing the next-generation optical microscopy exploiting quantum coherent nonlinear phenomena. The network brings together a unique team of 7 world-leading academics and 6 high tech companies at the forefront of optical microscopy and ultrafast laser technology developments merged with fundamental understanding of coherent light-matter interaction phenomena, development of quantitative image analysis tools, and biomedical/pharmaceutical real-world applications. MUSIQ will establish an intersectoral training and research programme at the physics/chemistry/life science interface with partners from 9 European countries, aimed at creating the next generation of skilled well-connected scientists that will pioneer the ‘quantum microscopes of tomorrow’.
Bayesian Network Based Fault Tolerance in Distributed Sensor Networks

A Distributed Sensor Network (DSN) consists of a set of sensors that are interconnected by a communication network. DSN is capable of acquiring and processing signals, communicating, and performing simple computational tasks. Such sensors can detect and collect data concerning any sign of node failure, earthquakes, floods and even a terrorist attack. Energy efficiency and fault-tolerance network control are the most important issues in the development of DSNs. In this work, two methods of fault tolerance are proposed: fault detection and recovery to achieve fault tolerance using Bayesian Networks (BNs). Bayesian Network is used to aid reasoning and decision making under uncertainty. The main objective of this work is to provide fault tolerance mechanism which is energy efficient and responsive to network using BNs. It is also used to detect energy depletion of node, link failure between nodes, and packet error in DSN. The proposed model is used to detect faults at node, sink and network level faults (link failure and packet error). The proposed fault recovery model is used to achieve fault tolerance by adjusting the network of the randomly deployed sensor nodes based on of its probabilities. Finally, the performance parameters for the proposed scheme are evaluated. Keywords—Bayesian network, distributed sensor networks, fault detection, fault tolerance, fault recovery, network control, routing.
Crib with artificial intelligence for asd diagnosis in neonatal intensive care units

Autism Spectrum Disorder (ASD) is a severe permanent neurodevelopmental disorder, affecting 1 in 59 children, worldwide. Researchers have reported a markedly increased prevalence of ASD in preterm populations. Performing early screening of ASD in Neonatal Intensive Care Units (NICUs) would be a unique opportunity to provide a prompt and proper intervention. However, no quantitative solutions are present in the literature. The project “Crib with ARtificial InteLLigence fOr ASD diagnosis in Neonatal intensive care units”  (ASD-carillon) aims to design, implement and validate a smart crib for analyzing visual preference and motor patterns in preterm infants in NICUs for early ASD screening. The smart crib integrates a Monitoring Framework, consisting of  RGB-D and thermal cameras, and sensors already available in NICUs (e.g., those in the cardiomonitor) for collecting infants data. The smart crib is equipped with an Artificial Intelligence (AI) engine, for processing these data and providing healthcare professionals with quantitative parameters for early ASD screening in NICUs. During the outgoing phase of the fellowship, the ER will benefit from the experience of Prof Zuomin Dong, from University of Victoria (UVic), in the field of sensors and intelligent system, to develop the Monitoring Framework and build the prototype of the smart crib. During the incoming phase,  she will collaborate with her main mentor, Prof Emanuele Frontoni from Università Politecnica delle Marche (UNIVPM), to refine the AI Engine. Expert neonatologists as well as neuropsychiatrists from UNIVPM and UVic will be involved as clinical collaborators of ASD-carillon. In the last decades, there has been an increasingly growing number of manuscripts dealing with AI in medicine, but the AI potential in the field of ASD screening in NICUs has not being unlocked, yet.  With ASD-carillon, the ER aims to fill this gap, while building the basis for a solid career in the field of AI in neonatology and ASD.
Online class imbalance learning for fault diagnosis of critical infrastructure systems

The aim of the project is to design and develop an online learning-based fault diagnosis engine with adaptation capabilities. This engine will monitor and analyse data arriving in real time from critical infrastructure (CI) systems, to accurately detect a potential fault and effectively isolate and identify its exact location. Modern society relies heavily on the availability and smooth operation of CI systems, such as electrical power systems, water distribution systems and telecommunication networks. In such large-scale, complex engineering systems when a failure occurs due to faults, it can have severe societal, health and economic consequences. The sequential arrival of data in CI systems calls for a fault diagnosis engine with adaptive behaviour to achieve and maintain optimal performance. However, the vast majority of existing work falls short on this requirement. This project will incorporate online learning capabilities to achieve adaptability and will also address class imbalance, a major challenge for learning systems, arising from the fact that faults are low probability events. Online class imbalance learning (OCIL) is an emerging research topic focusing on the combined challenges of online learning and class imbalance. We will shed light on supervised OCIL as very few methods currently deal with this problem and address for the first time the unsupervised and semi-supervised OCIL problems. The proposed algorithms will be evaluated in realistic fault diagnosis datasets from industrial partners and in an advanced Smart Buildings simulator allowing us to run sensor fault scenarios in large-scale multi-zone buildings. Furthermore, a prototype on sensor fault diagnosis will be delivered that will be evaluated on a physical Smart Buildings testbed to enable its efficient testing under realistic conditions. Overall, this novel and interdisciplinary project will provide invaluable insights on incorporating learning capabilities in CI systems fault diagnosis.
Increasing the scientific excellence and innovation capacity in data-driven simulation of the university of luxembourg

The overall aim of the DRIVEN project is to boost the scientific excellence and technology-transfer capacity in data-driven
simulation of the University of Luxembourg (UL) by creating a network with the high-quality Twinning partners: Institut
National de Recherche en Informatique et en Automatique (Inria), University of Limerick (ULIM) and University of Texas at Austin (UT Austin). To achieve this aim, the 3 year project will build upon the existing strong research and innovation base of UL and its Twinning partners.

To boost their scientific excellence and technology transfer capacity in data-driven simulation, the partners will implement a
research and innovation strategy focused on three sub-topics:

1. Mathematical foundations for data-driven simulations – UL with UT Austin,
2. Data-driven simulations for computer-assisted therapy – UL with Inria, and
3. Data-driven simulations for functional composite materials – UL with ULIM.

The research and innovation strategy takes into account the recent SWOT analysis of UL and has the following objectives:

• Objective 1: Strengthen UL’s research excellence in data-driven simulation
• Objective 2: Enhance the research and innovation capacity of UL and the Twinning partners
• Objective 3: Raise the research profile of UL and the Twinning Partners
• Objective 4: Contribute to the SMART Specialisation Strategy of Luxembourg
• Objective 5: Support research and innovation on a European level
In order to achieve these objectives, the consortium partners will implement a comprehensive set of measures via the
project’s work packages:

• Short term staff exchanges (WP1);
• Training workshops, conferences and summer schools (WP2);
• Dissemination and outreach (WP3).
Amyotrophic lateral sclerosis: Current perspectives from basic research to the clinic

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterized by progressive degeneration of upper and lower motoneurons, leading to muscle weakness and paralysis, and finally death. Considerable recent advances have been made in basic research and preclinical therapeutic attempts using experimental models, leading to increasing clinical and translational research in the context of this disease. In this review we aim to summarize the most relevant findings from a variety of aspects about ALS, including evaluation methods, animal models, pathophysiology, and clinical findings, with particular emphasis in understanding the role of every contributing mechanism to the disease for elucidating the causes underlying degeneration of motoneurons and the development of new therapeutic strategies.