A state-of-the-art, systematic review of indoor environmental quality studies in work-from-home settings

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Modern integrated circuits are tiny yet incredibly complex technological artifacts, composed of millions and billions of individual structures working in unison. Managing their complexity and facilitating their design drove part of the co-evolution of mode ...

As large, data-driven artificial intelligence models become ubiquitous, guaranteeing high data quality is imperative for constructing models. Crowdsourcing, community sensing, and data filtering have long been the standard approaches to guaranteeing or imp ...

Digital technology has become an integral part of our lives, offering various benefits from communication and entertainment to education and productivity. However, its pervasive use has also raised concerns about its potential negative impact on users' wel ...

Load-bearing systems in buildings, significant in material use and embodied greenhouse gas emissions (EGHGE), have lacked detailed analysis on their environmental and functional relationships over time and space. This study evaluates the environmental impa ...

The recent geopolitical conflicts in Europe have underscored the vulnerability of the current energy system to the volatility of energy carrier prices. In the prospect of defining robust energy systems ensuring sustainable energy supply in the future, the ...

Surrogate-based optimization is widely used for aerodynamic shape optimization, and its effectiveness depends on representative sampling of the design space. However, traditional sampling methods are hard-pressed to effectively sample high-dimensional desi ...

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, ...

Gene regulatory networks (GRNs) play a crucial role in an organism's response to changing environmental conditions. Cellular behaviors typically result from the integration of multiple gene outputs, and their regulation often demands precise control of num ...

Statistical (machine-learning, ML) models are more and more often used in computational chemistry as a substitute to more expensive ab initio and parametrizable methods. While the ML algorithms are capable of learning physical laws implicitly from data, ad ...

Zoning reform is a crucial tool for cities to adapt to contemporary challenges. However, its implementation remains challenging. Property owners, with a vested interest in the value of their neighborhoods, are sensitive to local developments and the potent ...

Mechanical resonators are widely used in sensors, transducers and optomechanical systems, where mechanical dissipation sets the ultimate limit to performance. Over the past 15 years, the quality factors in strained mechanical resonators have increased by f ...

At room temperature, mechanical motion driven by the quantum backaction of light has been observed only in pioneering experiments in which an optical restoring force controls the oscillator stiffness1,2. For solid-state mechanical resonators in which oscil ...

In this work, various methods were used to improve the printability of a photocurable polyvinylsilazane resin filled with silicon nitride particles for digital light processing. The developed resin was used as a preceramic polymer for polymer-to-ceramic co ...

In this paper, we study sampling from a posterior derived from a neural network. We propose a new probabilistic model consisting of adding noise at every pre- and post-activation in the network, arguing that the resulting posterior can be sampled using an ...

Decisions about a current visual stimulus are systematically biased by recently encountered stimuli, a phenomenon known as serial dependence. In human vision, for instance, we tend to report the features of current images as more similar â i.e., an attra ...

Previous studies have shown that access to a satisfactory view to the outside with sufficient daylight is essential for building occupants' health and well-being. It has also been suggested that certain features of visual content improve view-out quality, ...

Federated Learning by nature is susceptible to low-quality, corrupted, or even malicious data that can severely degrade the quality of the learned model. Traditional techniques for data valuation cannot be applied as the data is never revealed. We present ...

In integrated ecosystem assessment projects, scenarios provide alternative images of environmental futures as orientation knowledge for opinion-forming and decision-making. Participatory scenario frameworks provide the methodological basis for ecosystem sc ...

The recent geopolitical conflicts in Europe highlighted the sensibility of the current energy system to the volatility of energy carrier prices. In the prospect of defining robust energy system configurations to ensure energy supply stability, it is necess ...

A crucial building block of responsible artificial intelligence is responsible data governance, including data collection. Its importance is also underlined in the latest EU regulations. The data should be of high quality, foremost correct and representati ...

A state-of-the-art, systematic review of indoor environmental quality studies in work-from-home settings

Chattez avec Graph Search

Graph generative deep learning models with an application to circuit topologies

Extensions of Peer Prediction Incentive Mechanisms

Understanding and Enhancing Digital Wellbeing Dimensions: Empirical Studies on Smartphone Usage Patterns and Recommendations of Micro-Informative Content

Multiscale Spatiotemporal Characterization of Embodied Environmental Performance of Building Structures in Geneva from 1850 to 2018

Identification of typical district configurations: A two-step global sensitivity analysis framework

DiffAirfoil: An Efficient Novel Airfoil Sampler Based on Latent Space Diffusion Model for Aerodynamic Shape Optimization

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

Quantitative characterization of the inorganic phosphate gene regulatory networks in S. cerevisiae and bottom up engineering an orthogonal gene network

Encoding quantum-chemical knowledge into machine-learning models of complex molecular properties

Spatial Modeling for Building Design Evaluation: from Visual Landscape Quality Assessment to Devaluation Risk Estimation

Ultrahigh-quality-factor micro- and nanomechanical resonators using dissipation dilution

Room-temperature quantum optomechanics using an ultralow noise cavity

Influence of Si3N4 fillers and pyrolysis profile on the microstructure of additively manufactured silicon carbonitride ceramics derived from polyvinylsilazane

Gibbs sampling the posterior of neural networks

Serial Dependence in Human Visual Perception and Decision-Making

Dynamism in the context of views out: A literature review

A Practical Influence Approximation for Privacy-Preserving Data Filtering in Federated Learning

Ecosystem Scenarios as Environmental Futures - Implications for Participatory Framework Designs Integrating Social Capital Formation and Natural Capital Preservation

Identification of typical district configurations: A two-step global sensitivity analysis framework

incentive Mechanism Design for Responsible Data Governance: A Large-Scale Field Experiment