Aalto University

Assessing port infrastructure criticality and vulnerability for climate adaptation planning: Insights from three European ports

Climate change is increasing the intensity and frequency of extreme weather events, directly threatening critical port infrastructure and the stability of global supply chains. Effective adaptation planning requires systematic tools capable of identifying the most critical and cl...

Het-node2vec: second-order random walk sampling for heterogeneous graph embedding

Abstract Many real-world problems are naturally modeled as heterogeneous graphs, where nodes and edges represent multiple types of entities and relations. Existing learning models for heterogeneous graph representation usually depend on the computation of specific, user-defined h...

Defocus-Insensitive Microscopy via Spatial Phase Modulation Using End-to-End Learning

Abstract In optical microscopy, high spatial resolution comes at the cost of a short depth of field. This trade-off prevents the formation of sharp images of three-dimensional objects or objects moving in and out of focus. Moreover, it is often difficult to know the extent to whi...

A Narrative View of Curiosity in Organizations

How can managers be curious and incurious at the same time? This question emerged as a puzzling anomaly from interview data collected with operational managers and supervisors confronting early signals of platform-economy disruption. Rather than stable differences across responde...

Photodegradation of different nanocellulose substrates

Abstract The increased interest in the development of sustainable materials for printed electronics necessitates durability studies in their operating environments. Hence, in this paper, the effects of photodegradation on five different nanocellulose and four reference substrates...

Physics‐Guided Monte Carlo Surrogate Modeling for Optical Properties Inference and Spectral Prediction From Limited Experimental Data

ABSTRACT We present a physics‐guided neural framework that combines Monte Carlo simulations with experimental measurements to characterize optical properties and predict spectral responses at unseen conditions. The hybrid model jointly learns from simulations with complete optica...

Orchestrating Anion–π + Interactions to Accelerate Metal‐Free Room‐Temperature Phosphorescence

ABSTRACT Overcoming the long‐standing trade‐off between efficiency and radiative rate in metal‐free phosphorescence remains a central challenge in molecular photophysics and is pivotal for the next‐generation optoelectronic technologies. Here, we demonstrate that tuning the stren...

The narrow concept of technology and problems of transport: Contributions of Feenberg’s critical theory of technology to critiques of techno-rational transport planning

Transport planning and policymaking have been criticized for positivism and instrumentalism that ignore many social and political aspects of transport systems. Andrew Feenberg’s critical theory of technology argues that the way technologies are understood has a profound influence...

World’s population susceptible to water risks is concentrated in two of the 58 IPCC reference regions

The use of climate reference regions is a common practice in climate change research and impact assessment studies 1 , 2 , 3 , 4 , having been utilized especially within the context of the Intergovernmental Panel on Climate Change (IPCC)’s Assessment Reports (ARs) over the past 2...

CODAC: Constraint-based Deep Active Clustering

Abstract Constraint-based Deep Active Clustering (CODAC) integrates actively selected pairwise constraints into deep representation learning to efficiently improve existing cluster structures, even under tight query budgets. CODAC encodes the constraint information into the embed...

Effect of Electrolyte,Applied Voltage, and DNA Concentrationon the Translocation Dynamics of a Single-Stranded DNA through a Solid-StateNanopore

Abstract Solid-state nanopores enable label-free detection of biomolecules by monitoring ionic current modulations during molecular translocation. However, reliable measurements are often limited by rapid, poorly controlled translocation dynamics producing short, low-resolution s...

Tackling Challenges of Textile Recycling: Color Removalfrom Cotton Textile Waste via Sequential Reductive–OxidativeBleaching

Abstract An effective pathway for textile recycling could be the successful integration of the textile waste into a closed-loop system; however, one of the key challenges is the removal of color from textile waste. In this study, we developed a two-step reductive-oxidative treatm...

Is green the new normal? Understanding current sustainability practices in European residential property lending

Purpose The article studies how environmental sustainability impacts lending processes and conditions in the European residential credit markets, shaping the current green lending (GL) practices. Design/methodology/approach This study adopts an abductive research process with fiv...

Photovoltaic systems in the Nordics: A systematic review of techno-economic and life-cycle sustainability assessments

The rapid global deployment of photovoltaic (PV) technologies has increased the need for comprehensive evaluations of their technical performance, economic viability, and environmental compatibility. At high-latitudes, these assessments are essential due to low solar elevation an...

Deep learning-based surrogate model for generation of wood microstructures

A machine learning-based surrogate model for efficient wood microstructure generation compatible with a physics-based model is developed. The model is based on the U-Net neural network, a variant of convolutional neural network which, due to its architecture, is suitable for imag...

Could it be more than a toolbox? Defining a business model for artificial intelligence-driven general contractors

Purpose The purpose of this research is to address the potential of artificial intelligence (AI) to drive business models for general contractors. While AI is used for various tasks, its holistic impact on general contractors' business models remains unclear. Design/methodology/a...

Network-wide fine-grained passenger loading prediction via dynamic relational spatiotemporal deep graph neural networks

Accurate short-term prediction of onboard passenger loading is essential for enhancing public transport efficiency, passenger comfort, and operational resilience. However, existing models are mainly restricted to station-based passenger flow prediction, and they often struggle wi...