Results 91 to 100 of about 5,365,252 (221)

Measuring the Social Discount Rate under Uncertainty: A Methodology and Application [PDF]

open access: yes
It is well recognised that the issue of the social rate of discount applies only to the gains from public investment that accrues to the public sector. When it comes to measurement, however, there is a problem: public investment in infrastructure and the
Syed Ahsan, Panagiotis Tsigaris
core  

Machine learning–driven design of catalytic processes for sulfur dioxide oxidation: Lessons from the trenches

open access: yesAIChE Journal, EarlyView.
Abstract Despite the growing use of ML in chemical engineering, the catalytic conversion of sulfur dioxide (SO2) to sulfur trioxide (SO3) remains underexplored from a data‐driven modeling perspective. This study evaluates an integrated workflow for literature‐derived SO2 oxidation data, combining data curation, preprocessing assessment, machine ...
Farough Agin   +2 more
wiley   +1 more source

The Impact of Education on the Subjective Discount Rate in Ugandan Villages [PDF]

open access: yes
Heterogeneity in time discounting may reinforce the existing barriers to save and invest faced by rural populations in developing countries. We elicit a subjective discount rate for a varied sample of Ugandan villagers.
Bauer, Michal, Chytilová, Julie
core  

AS‐pHopt: An Optimal pH Prediction Model Enhanced by Active Site of Enzymes

open access: yesAdvanced Intelligent Discovery, EarlyView.
To address the low accuracy of enzyme optimal pH (pHopt) prediction, this study develops active site‐based pHopt (AS‐pHopt), a prediction model enhanced by active site information and pseudo‐label prediction. Integrating key structural and physicochemical features affecting enzyme pHopt, AS‐pHopt uses Evolutionary Scale Modeling (ESM)‐2 with active ...
Wenxiang Song   +6 more
wiley   +1 more source

Spatially Informed Feature Selection and Machine Learning in Matrix‐Assisted Laser Desorption/Ionization Imaging for Cohort‐Scale Molecular Tissue Phenomics in Glioblastoma

open access: yesAdvanced Intelligent Discovery, EarlyView.
Matrix‐assisted laser desorption/ionization imaging‐based identification of reliable small molecule markers across heterogeneous glioblastoma cohorts is challenging with intensity‐only methods. We present spatially informed feature selection (SIFS), a spatially informed framework that prioritizes molecules consistently colocalizing with histopathology.
Shad A. Mohammed   +15 more
wiley   +1 more source

Cellular Material Network: A General Machine Learning Architecture for Predicting Mechanical Properties of Cellular Materials

open access: yesAdvanced Intelligent Systems, EarlyView.
This study introduces Cellular Material Network (CM‐Net), a pioneering machine learning architecture integrating physical information, to predict the mechanical properties of cellular materials. Comprehensive validation through simulations and experiments demonstrates its accuracy in predicting nonlinear behaviors, including initial peak compression ...
Sicong Zhou   +5 more
wiley   +1 more source

Uncertainty in Fisheries Economics: The Role of the Discount Rate [PDF]

open access: yes
Standard models of management of a single-species fishery generally assume that the biomass is of known size and that it is generated by a well-specified deterministic growth law.
Plourde, Charles, Bodell, Richard
core  

Exploiting Edge Semantics in Job Shop Scheduling Problem With Heterogeneous Graph Transformers

open access: yesAdvanced Intelligent Systems, EarlyView.
A heterogeneous graph transformer (HGT) is introduced for reinforcement learning‐based job shop scheduling by explicitly distinguishing precedence and machine‐contention relations through edge‐type‐specific attention. The proposed framework learns richer scheduling representations, improves decision quality over homogeneous graph models, and highlights
Bulent Soykan, Fatih Kasimoglu
wiley   +1 more source

AI Dependence as a Longitudinal Governance Problem

open access: yesAI &Innovation, EarlyView.
ABSTRACT Artificial intelligence governance typically focuses on whether people rely on AI appropriately during individual decisions. This Perspective addresses a different question: whether repeated AI use changes the capabilities and alternatives available to users and organisations over time.
Yiran Du
wiley   +1 more source

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