In response to ‘Six critical questions about smart spezialisation’

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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 ...

We live in an era defined by attempts to grapple with an ever-expanding array of grand societal challenges (GCs). These challenges comprise transformational social and environmental issues, such as environmental degradation and global pandemics, and the cr ...

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 ...

Security system designers favor worst-case security metrics, such as those derived from differential privacy (DP), due to the strong guarantees they provide. On the downside, these guarantees result in a high penalty on the system's performance. In this pa ...

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 ...

Second-order Moller-Plesset perturbation theory (MP2) is the most expedient wave function-based method for considering electron correlation in quantum chemical calculations and, as such, provides a cost-effective framework to assess the effects of basis se ...

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 ...

Computational chemistry aims to simulate reactions and molecular properties at the atomic scale, advancing the design of novel compounds and materials with economic, environmental, and societal implications. However, the field relies on approximate quantum ...

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 ...

Machine learning frameworks based on correlations of interatomic positions begin with a discretized description of the density of other atoms in the neighborhood of each atom in the system. Symmetry considerations support the use of spherical harmonics to ...

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 ...

Data-driven schemes that associate molecular and crystal structures with their microscopic properties share the need for a concise, effective description of the arrangement of their atomic constituents. Many types of models rely on descriptions of atom-cen ...

In this reply, we address the concerns that were raised about our paper on CsPbBr3 single crystals. M. Szafranski criticized the dielectric and DSC data in our original paper claiming that they were affected by the experimental artefacts or poor quality of ...

Computer systems designers are building cache hierarchies with higher capacity to capture the ever-increasing working sets of modern workloads. Cache hierarchies with higher capacity improve system performance but shift the performance bottleneck to addres ...

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 ...

In response to ‘Six critical questions about smart spezialisation’

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

Touch and Closeness in Naturally Organized Activities

Entrepreneurial Opportunities and Threats in the Era of Grand Societal Challenges

Rebooting Virtual Memory with Midgard

Bayes Security: A Not So Average Metric

Roadmap on Optical Sensors

Surprise and novelty in the brain

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

Plane Waves Versus Correlation-Consistent Basis Sets: A Comparison of MP2 Non-Covalent Interaction Energies in the Complete Basis Set Limit

Artificial intelligence for natural product drug discovery

Advancing Computational Chemistry with Stochastic and Artificial Intelligence Approaches

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

A smooth basis for atomistic machine learning

Game-theoretic Mechanisms for Eliciting Accurate Information

Removing Algorithmic Discrimination (With Minimal Individual Error)

Expanding biochemical knowledge and illuminating metabolic dark matter with ATLASx

Unified theory of atom-centered representations and message-passing machine-learning schemes

Rebooting Virtual Memory with Midgard

Mathematical and numerical models for the cardiac electromechanical function