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1886 research outputs found
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Replication data for "Exploring language impairment in Catalan-dominant bilinguals with primary progressive aphasia: preliminary data"
No full textThe dataset includes the results of 4 Catalan-speaking participants with primary progressive aphasia (PPA) who completed the Catalan Comprehensive Aphasia Test (CAT-CAT; Salmons et al., 2021). The participants were all bilingual speakers of Catalan and Spanish. The goal of the study is to investigate whether the CAT-CAT is useful to diagnose language deficits in Catalan-speaking individuals with PPA. The materials of the test can be found at https://ddd.uab.cat/record/250143 (2025-09-08
Replication Data for "Trickle-bed reactor for solid-substrate fermentation: overcoming nutrient distribution limitations in sophorolipid production"
No full textRaw data from a series of experiments aimed to evaluate the feasibility of producing sophorolipids in solid-state fermentation using trickle-bed reactors
Conjunt de dades de l'enquesta cultureESS: pràctiques SEE en centres d'art i creació rurals (Catalunya i Occitània, 2025)
No full textAquest conjunt de dades es va generar en el marc del projecte REC – Xarxa de Centres de Creació de l'Euroregió i forma part de la recerca cultureESS. Recopila respostes a enquestes i informació qualitativa de nou centres d'art i creació rurals de Catalunya i Occitània (juny 2025). El conjunt de dades aplica indicadors d'economia social i solidària (ESS) adaptats al sector cultural a través del qüestionari cultureESS, que cobreix 15 dimensions com la governança democràtica, la perspectiva feminista, les condicions laborals, la cooperació, la sostenibilitat ambiental i l'ancoratge territorial. També s'inclou les entrevistes realitzades a la gerència de les dues xarxes: XarxaProd (Catalunya) i Air de Midi (Occitània)
Replication data for "Reactor Engineering for Enhanced Multi-enzymatic CO₂ Conversion: Insights into Gas–Liquid Transfer in a Stirred-Tank Reactor"
No full textDataset related to the determination of the volumetric mass transfer coefficient (kLa) of CO₂ from a 24% CO₂ gas mixture, preparation of the co-immobilized bifunctional biocatalyst, multi-enzymatic CO₂ reduction under varying volumetric flow rates, CO₂ balance in capture and conversion processes, and process performance metrics
Replication data for "Subcutaneous administration of an endocrine-mimetic platform allows for prolonged tumor-uptake of a tumor-targeted protein"
No full textThe dataset includes the physicochemical and in vivo characterization data supporting the article “Subcutaneous administration of an endocrine-mimetic platform allows for prolonged tumor-uptake of a tumor-targeted protein.” It contains measurements of protein size, polydispersity, zeta potential, morphology, and release kinetics of zinc-induced secretory granules (SGs) obtained by DLS, FESEM, and TEM, as well as fluorescence-based biodistribution data in mice after subcutaneous, intramuscular, and intraperitoneal administration. The results demonstrate that subcutaneous administration ensures the most sustained protein release and highest tumor accumulation of the CXCR4-targeted T22-GFP-H6 protein
Replication data for: Multi-objective application placement in fog computing using graph neural network-based reinforcement learning
No full textThis dataset comprises a collection of synthetic application‐placement instance sets for heterogeneous cloud–edge/fog infrastructures, designed for the evaluation of single‐ and multi‐objective optimization strategies. Each instance describes:
- a directed acyclic graph (DAG) of interdependent services forming an application,
- a set of compute nodes (cloud, edge, fog) with resource capacities and connectivity latencies,
- resource demands of each service (e.g., CPU, memory), service‐to‐service dependency weights or communication cost,
- one or more placement solutions together with objective values (such as latency, energy consumption, deployment cost) generated by algorithms including the DRL model, a genetic algorithm (GA) and an NSGA-II multi‐objective heuristic.
The dataset is split into training and test sets and is generated via the provided instance_generator.py and generate_dataset.py scripts. It allows researchers to benchmark and compare placement algorithms in terms of Pareto-front coverage, convergence speed, and trade-offs between objectives.
Potential uses: Investigating learning‐based or heuristic algorithms for application placement, multi‐objective optimisation in the cloud/fog continuum, dependency‐aware placement of microservices, as well as enabling reproducibility and comparison across approaches