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The consortium of S3E – Southern European Entrepreneurship Engine has officially launched the S3E Reverse for Solvers Open Call #1 targeting scaling start-ups and SMEs with deep tech solutions. Through S3E REVERSE, the project creates an Innovation and Technology Brokerage Program aiming at connecting corporates and public organisations (Challenge Organisations) with scale-ups, start-ups and SMEs (Solvers) that can address the identified challenges through their products, services, and solutions, based on deep tech and aligned to the Sustainable Development Goals (SDGs). The Solvers - SMEs and more mature start-ups - are invited to join the program, submitting their solutions, ideas and products that solve one or more of the 15 identified challenges. The Open Call for Solvers isavailable from 14 March (12.00 pm CET) until 15 May (17.00 pm CET).

Systemic innovation success in Europe lags behind its expectations as Europe spends most funding in basic research and development (R&D) while commercialization takes place in other regions such as the US or China. Therefore, this whitepaper aims to enhance the technology transfer for Deep Tech innovations in Europe through developing a framework for actors in Deep Tech ecosystems based on a case study analysis. For this, 25 actors from science and industry in three Deep Tech areas are analyzed – lithium-ion battery cells, semiconductors and electrolyzers. Based on a cross-industrial synthesis, recommendations for actions are derived building on the individual actors’ strengths and weaknesses. As Deep Tech is considered a disruptive technology with a high degree of uncertainty regarding its actual feasibility, investments in such technologies are associated with high risks but great economic and societal opportunities. To benefit from such high-risk investments, it is mandatory that sufficient support is provided from research all the way to commercialization. This technology transfer includes both public funding of fundamental research and private funding for scaling and commercializing innovations. In addition to insufficient risk capital in basic research, however, a lack of consistent funding on the path from research to commercialization can be observed in Europe. This gap phenomenon between public and private funding is often referred to as the Valley of Death. To foster the technology transfer for Deep Tech innovations, three needs for action are derived from the analyzed case studies: First, collaboration between actors should be strengthened to deliver Deep Tech innovations more effectively. Furthermore, a sufficient environment needs to be created in which the individual actors’ strengths complement each other optimally. Finally, protection spaces for intellectual property must be created to avoid legal disputes from the outset. By following these recommendations and taking the individual profiles of actors into account, the Valley of Death can be minimized.

S3E Call for Experts - Guidelines to Express Interest

The S3E one pager is a written pitch of our project.

S3E Open Call graphic material for promotion (Twitter)&nbsp

S3E Open Call graphic material for promotion (Linkedin)

The S3E press kit is an information pack that we have prepared for organisations and media that want to support the promotion of the S3E Open Call #1 and communicate the opportunity to potential beneficiaries about enrolling in tailored programs and services aiming at boosting the South European Deep Tech ecosystem. This document is suitable for all types of organisations.

The S3E START Open Call documents includethe Guidelines for Applicants and the Open Call Text and are mandatory to read and follow in order to apply for the S3E START Open Call for Researchers or Tech Transfer Offices. Any doubt, please contact the S3E Consortium through this Helpdesk.&nbsp

The S3E CHARGEOpen Call documents includetheGuidelines for Applicantsand theOpen Call Textand are mandatory to read and follow in order to apply for the S3E CHARGEOpen Call for Growth Start-ups Any doubt, please contact the S3E Consortium through thisHelpdesk.&nbsp

The S3E REVERSEOpen Call documents includetheGuidelines for Applicantsand theOpen Call Textand are mandatory to read and follow in order to apply for the S3E REVERSE Open Call for Challenge Organisations. Any doubt, please contact the S3E Consortium through thisHelpdesk.&nbsp

S3E – The Engine for South European Deep Tech – is a project funded by the European Commission that will accelerate Deep Tech solutions to improve the connectedness and efficiency of the entrepreneurship ecosystems in South European countries. The program is built around 3 innovative programs addressed at Research Teams, TTOs, start-ups, scaleups, SMEs and Corporates to access to Mentoring, Training, Networking and Brokerage services. The Open Call #1 launches on Nov 7th and S3E will support 150+ Deep Tech ventures throughout its complete run.&nbsp

South3E Joint Press Release Launchment of the project - September 2022

Background There is a pressing need for scalable healthcare solutions and a shift in the rehabilitation paradigm from hospitals to homes to tackle the increase in stroke incidence while reducing the practical and economic burden for patients, hospitals, and society. Digital health technologies can contribute to addressing this challenge; however, little is known about their effectiveness in at-home settings. In response, we have designed the RGS@home study to investigate the effectiveness, acceptance, and cost of a deep tech solution called the Rehabilitation Gaming System (RGS). RGS is a cloud-based system for delivering AI-enhanced rehabilitation using virtual reality, motion capture, and wearables that can be used in the hospital and at home. The core principles of the brain theory-based RGS intervention are to deliver rehabilitation exercises in the form of embodied, goal-oriented, and task-specific action. Methods The RGS@home study is a randomized longitudinal clinical trial designed to assess whether the combination of the RGS intervention with standard care is superior to standard care alone for the functional recovery of stroke patients at the hospital and at home. The study is conducted in collaboration with hospitals in Spain, Sweden, and France and includes inpatients and outpatients at subacute and chronic stages post-stroke. The intervention duration is 3 months with assessment at baseline and after 3, 6, and 12 months. The impact of RGS is evaluated in terms of quality of life measurements, usability, and acceptance using standardized clinical scales, together with health economic analysis. So far, one-third of the patients expected to participate in the study have been recruited (N = 90, mean age 60, days after stroke ≥ 30 days). The trial will end in July 2023. Discussion We predict an improvement in the patients’ recovery, high acceptance, and reduced costs due to a soft landing from the clinic to home rehabilitation. In addition, the data provided will allow us to assess whether the prescription of therapy at home can counteract deterioration and improve quality of life while also identifying new standards for online and remote assessment, diagnostics, and intervention across European hospitals. Trial registration ClinicalTrials.gov NCT04620707. Registered on November 3, 2020

The term "Deep Tech" is prevalent in industry but ill-defined. In this extended letter, we define Deep Tech (technology that is difficult to develop today, with the potential to become a pervasive and easy-to-implement basic need in the future) and consider its role in evolving businesses. We suggest how organizations can position themselves to take advantage of a coming wave of innovation, with emphasis placed on Creative Destruction's role (cannibalizing product lines) in creating sustaining enterprises. Understanding the diffusion of technical innovation from hard-to-implement exciter to commodity basic need will encourage leaders to rethink their current offerings to play in a future-thinking space setting these companies apart from the competition. We provide examples drawn from successful organizations.

Big Science Research Infrastructures (BSRIs) are tremendous sources of ‘deep-tech’ with the potential to foment alternative commercial applications in diverse industries. Yet, cultivating novel applications of BSRI technologies is not straightforward due to misalignment between their scientific mission, large technological risks, market uncertainties, and long development times. Given these challenges, research is needed to understand if- and how-serendipitous innovations can be purposefully developed from BSRIs. In this study, we analyse ATTRACT, a novel initiative funded by the European Commission's Horizon 2020 program, which funded 170 projects with €100,000 each to develop a proof-of-concept commercial application of BSRI technologies within one year. Our analysis of this dataset identifies three modes employed by researchers to come up with alternate applications: (1) combining different technologies, (2) applying technology into a different field, and (3) using artificial intelligence or machine learning. In a second step, we conducted multinomial logistic regressions using the project data, expert evaluations, and a questionnaire to identify the antecedents associated with the pursuit of each of the three modes. Our findings suggest that scientists and engineers develop many new ideas about novel potential applications of BSRI technologies in their daily work. The main value of ATTRACT is in facilitating project development through financial resources, brokering relationships with industrial partners, and facilitating the applications of technologies in domains outside of the immediate purview of BSRIs.

Amaç: Bu çalışma, derin teknoloji girişim kategorileri arasındaki benzerlikleri ve farklılıkları anlamayı ve derin teknoloji alanında bundan sonra gerçekleştirilecek akademik çalışmalar için bir başlangıç noktası olmayı amaçlamaktadır. Yöntem: İhtiyaçlar, kurucuların eğitim seviyesi ve finansman tipi gibi özelliklerin derin teknoloji kategorileri bazında nasıl değiştiğini anlamak amacıyla 126 derin teknoloji girişimi ile anket yapılmış ve hipotez testi uygulanmıştır. Bulgular: Derin teknoloji girişimlerinin bulunduğu lokasyon, kurucuların eğitim seviyesi, kurucuların geçmiş girişimcilik deneyimi ve derin teknoloji girişiminin satış ayak izi özelliklerinin derin teknoloji kategorisine göre farklılık gösterdiği görülmüştür. Sonuç ve Öneriler: Sonuçların, uygulayıcıların derin teknoloji girişimlerine yatırım yaparken veya onlarla iş birliği yaparken kararlarını daha doğru vermelerine yardımcı olması beklenmektedir. Benzer şekilde politika yapıcılar da derin teknoloji girişimciliği ekosistemini desteklemek için daha etkili politikalar geliştirmek için bu çalışmadan faydalanabilir. Özgün Değer: Bu çalışma şu açılardan özgündür; 1) akademik literatürde derin teknoloji tanımı yapılması 2) derin teknoloji özelliklerinin derin teknoloji kategorileriyle olan ilişkisinin anlaşılması 3) gelişmekte olan bir ülkede derin teknolojinin anlaşılması. Purpose: This study aims to understand the similarities and dissimilarities among categories of deep tech entrepreneurship and to be a starting point for academia to further explore the significance of the deep tech field. Methodology: We have surveyed 126 deep tech startups and used hypothesis testing to understand how attributes such as needs, education level of the founders, financing types differs based on deep tech startup categories. Findings: We have discovered that while the location of the deep tech startup, the education level of the founders, the past entrepreneurship experience of the founders, and the sales footprint characteristic of the deep tech startup vary according to the deep tech category, the needs of the deep tech startups are similar for each category. Practical Implications: The results are expected to help practitioners make their decisions more accurately while investing or collaborating with deep tech startups. Similarly, policymakers can use the results to develop more relevant policies to support the deep tech entrepreneurship ecosystem. Originality: This study is unique in terms of; 1) defining deep tech in academia 2) understanding how deep tech attributes are related with deep tech categories. 3) exploring deep tech in a developing country. Keywords: Deep Tech, Entrepreneurship, Startup

Amaç: Bu çalışma, derin teknoloji girişim kategorileri arasındaki benzerlikleri ve farklılıkları anlamayı ve derin teknoloji alanında bundan sonra gerçekleştirilecek akademik çalışmalar için bir başlangıç noktası olmayı amaçlamaktadır. Yöntem: İhtiyaçlar, kurucuların eğitim seviyesi ve finansman tipi gibi özelliklerin derin teknoloji kategorileri bazında nasıl değiştiğini anlamak amacıyla 126 derin teknoloji girişimi ile anket yapılmış ve hipotez testi uygulanmıştır. Bulgular: Derin teknoloji girişimlerinin bulunduğu lokasyon, kurucuların eğitim seviyesi, kurucuların geçmiş girişimcilik deneyimi ve derin teknoloji girişiminin satış ayak izi özelliklerinin derin teknoloji kategorisine göre farklılık gösterdiği görülmüştür. Sonuç ve Öneriler: Sonuçların, uygulayıcıların derin teknoloji girişimlerine yatırım yaparken veya onlarla iş birliği yaparken kararlarını daha doğru vermelerine yardımcı olması beklenmektedir. Benzer şekilde politika yapıcılar da derin teknoloji girişimciliği ekosistemini desteklemek için daha etkili politikalar geliştirmek için bu çalışmadan faydalanabilir. Özgün Değer: Bu çalışma şu açılardan özgündür; 1) akademik literatürde derin teknoloji tanımı yapılması 2) derin teknoloji özelliklerinin derin teknoloji kategorileriyle olan ilişkisinin anlaşılması 3) gelişmekte olan bir ülkede derin teknolojinin anlaşılması.

[ES] La serie «El rol de la inteligencia artificial y la computación distribuida en las aplicaciones IoT» contiene publicaciones sobre la teoría y aplicaciones de la computación distribuida y la inteligencia artificial en el Internet de las cosas. Prácticamente todas las disciplinas como la ingeniería, las ciencias naturales, la informática y las ciencias de la información, las TIC, la economía, los negocios, el comercio electrónico, el medio ambiente, la salud y las ciencias de la vida están cubiertas. La lista de temas abarca todas las áreas de los sistemas inteligentes modernos y la informática como: inteligencia computacional, soft computing incluyendo redes neuronales, inteligencia social, inteligencia ambiental, sistemas auto-organizados y adaptativos, computación centrada en el ser humano y centrada en el ser humano, sistemas de recomendación, control inteligente, robótica y mecatrónica, incluida la colaboración entre el ser humano y la máquina, paradigmas basados en el conocimiento, paradigmas de aprendizaje, ética de la máquina, análisis inteligente de datos, gestión del conocimiento, agentes inteligentes, toma de decisiones inteligentes y apoyo, seguridad de la red inteligente, gestión de la confianza, entretenimiento interactivo, inteligencia de la Web y multimedia. Las publicaciones en el marco de «El rol de la inteligencia artificial y la computación distribuida en las aplicaciones IoT» son principalmente las actas de seminarios, simposios y conferencias. Abarcan importantes novedades recientes en la materia, tanto de naturaleza fundacional como aplicable. Un importante rasgo característico de la serie es el corto tiempo de publicación. Esto permite una rápida y amplia difusión de los resultados de las investigaciones, [EN] The series «The Role of Artificial Intelligence and Distributed Computing in IoT Applications» contains publications on the theory and applications of distributed computing and artificial intelligence in the Internet of Things. Virtually all disciplines such as engineering, natural sciences, computer and information sciences, ICT, economics, business, e-commerce, environment, health and life sciences are covered. The list of topics covers all areas of modern intelligent systems and computer science: computational intelligence, soft computing including neural networks, social intelligence, ambient intelligence, self-organising and adaptive systems, human-centred and people-centred computing, recommendation systems, intelligent control, robotics and mechatronics including human-machine collaboration, knowledge-based paradigms, learning paradigms, machine ethics, intelligent data analysis, knowledge management, intelligent agents, intelligent decision making and support, intelligent network security, trust management, interactive entertainment, web intelligence, and multimedia. The publications in the framework of «The Role of Artificial Intelligence and Distributed Computing in IoT Applications» are mainly the proceedings of seminars, symposia and conferences. They cover important recent developments in the field, whether of a foundational or applicable character. An important feature of the series is the short publication time. This allows for the rapid and wide dissemination of research results.