Entrepreneurial Opportunities and Threats in the Era of Grand Societal Challenges

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The Beijing 2022 Winter Olympic Games reimagined a fragment of the city's industrial heritage, showcasing it as a stage and a landscape for one of the most mediatised mega-events worldwide. Despite the contentious reactions to the use of the Shougang forme ...

The increasing demand for computing power and the emergence of heterogeneous computing architectures have driven the exploration of innovative techniques to address current limitations in both the compute and memory subsystems. One such solution is the use ...

Countless aspects of touch and closeness have been questioned in an unprecedented way during the recent Covid epidemic. Social practices as banal as greetings were both reflexively and practically challenged and sometimes deeply altered, resulting in painf ...

The dynamic landscape of sustainable smart cities is witnessing a signi ficant transformation due to the integration of emerging computational technologies and innovative models. These advancements are reshaping data -driven planning strategies, practices, ...

Virtual Memory (VM) is a critical programming abstraction that is widely used in various modern computing platforms. With the rise of datacenter computing and birth of planet-scale online services, the semantic and capacity requirements from memory have ev ...

Optical sensors and sensing technologies are playing a more and more important role in our modern world. From micro-probes to large devices used in such diverse areas like medical diagnosis, defense, monitoring of industrial and environmental conditions, o ...

Notions of surprise and novelty have been used in various experimental and theoretical studies across multiple brain areas and species. However, 'surprise' and 'novelty' refer to different quantities in different studies, which raises concerns about whethe ...

Tantalum is receiving increasing attention in the biomedical field due to its biocompatible nature and superior mechanical properties. However, the bioinert nature of tantalum still poses a challenge and limits its integration into the bone tissue. To addr ...

As the world’s population grows in cities, urban dwellers spend a large amount of time inside their home, making housing health ever more important. Critical for residents’ health, the interactions between indoor residential environments and outdoor enviro ...

Developments in computational omics technologies have provided new means to access the hidden diversity of natural products, unearthing new potential for drug discovery. In parallel, artificial intelligence approaches such as machine learning have led to e ...

Membrane technology is a growing tool for contaminants removal from polluted water. Although various types of polymeric membranes have been developed for water remediation, the common drawbacks like fouling, hydrophobicity and low mechanical strength are y ...

The use of digital tools has drastically increased in engineering education, accelerated by the COVID-19 pandemic. These tools generate important ethical issues, in particular in terms of privacy and fairness. However, very few teacher training programmes ...

Artificial Intelligence often relies on information obtained from others through crowdsourcing, federated learning, or data markets. It is crucial to ensure that this data is accurate. Over the past 20 years, a variety of incentive mechanisms have been dev ...

We address for the first time the problem of correcting group discriminations within a score function, while minimizing the individual error. Each group is described by a probability density function on the set of profiles. We first solve the problem analy ...

Metabolic "dark matter" describes currently unknown metabolic processes, which form a blind spot in our general understanding of metabolism and slow down the development of biosynthetic cell factories and naturally derived pharmaceuticals. Mapping the dark ...

Byzantine resilience emerged as a prominent topic within the distributed machine learning community. Essentially, the goal is to enhance distributed optimization algorithms, such as distributed SGD, in a way that guarantees convergence despite the presence ...

In recent years, the idea that the prediction of sensory input is one of the major computational goals of the nervous system led to the development of several large-scale theories of brain functioning, such as different versions of the Bayesian approach to ...

We propose a model for combining the Standard Model (SM) with gravity. It relies on a nonminimal coupling of the Higgs field to the Ricci scalar and on the Palatini formulation of gravity. Without introducing any new degrees of freedom in addition to those ...

Image classification has significantly improved using deep learning. This is mainly due to convolutional neural networks (CNNs) that are capable of learning rich feature extractors from large datasets. However, most deep learning classification methods are ...

This paper deals with the mathematical model that describes the function of the human heart. More specifically, it addresses the equations that express the electromechanical process, that is the mechanical deformation (contraction and relaxation) of the he ...

Entrepreneurial Opportunities and Threats in the Era of Grand Societal Challenges

Chat with Graph Search

The authentic city: uses of industrial heritage in large-scale regeneration projects, a comparative analysis

Intermediate Address Space: virtual memory optimization of heterogeneous architectures for cache-resident workloads

Touch and Closeness in Naturally Organized Activities

The synergistic interplay of artificial intelligence and digital twin in environmentally planning sustainable smart cities: A comprehensive systematic review

Rebooting Virtual Memory with Midgard

Roadmap on Optical Sensors

Surprise and novelty in the brain

Morphology of Nanostructured Tantalum Oxide Controls Stem Cell Differentiation and Improves Corrosion Behavior

Housing, street and health: a new systemic research framework

Artificial intelligence for natural product drug discovery

Advances in polymer-based nanocomposite membranes for water remediation: Preparation methods, critical issues and mechanisms

A Canvas for the Ethical Design of Learning Experiences with Digital Tools

Game-theoretic Mechanisms for Eliciting Accurate Information

Removing Algorithmic Discrimination (With Minimal Individual Error)

Expanding biochemical knowledge and illuminating metabolic dark matter with ATLASx

Byzantine Machine Learning Made Easy By Resilient Averaging of Momentums

Predictive brain: Addressing the level of representation by reviewing perceptual hysteresis

Standard model meets gravity: Electroweak symmetry breaking and inflation

Fidelity Estimation Improves Noisy-Image Classification with Pretrained Networks

Mathematical and numerical models for the cardiac electromechanical function