University of Tolima

Acetamiprid (ACET), a neonicotinoid insecticide, is widely detected in aquatic and terrestrial ecosystems and has raised concern due to its environmental persistence, incomplete removal by conventional treatment processes, and the limited understanding of the ecotoxicological effects of its transformation products. In this study, the photocatalytic degradation of ACET was investigated using both a commercial formulation (Rescate 200SP, 20

We investigate the fluorescence dynamics of the rare-earth ions europium, terbium, and gadolinium, with particular emphasis on quantifying non-Markovian behavior. By employing fluorescence as a probe, we characterize deviations from memoryless dynamics and identify clear distinctions between Markovian and non-Markovian regimes. Our analysis demonstrates how these profiles manifest in optical spectroscopy, providing direct insight into system-environment interactions. Beyond their fundamental implications, these insights may support the rational design of rare-earth-doped materials for applications in multicolor phosphors, hybrid optoelectronic architectures, and emerging quantum sensing technologies.

In freshwater ecosystems, introducing exotic species has been a long-term problem, altering the flow of matter and energy in biotic communities. The effects of introduced organisms on aquatic ecosystems depend on the magnitude of the interactions between native and introduced species. Such interactions are complex and have been little studied in the Colombian Andean region. In this context, our study analyzed variations in the assembly of phytoperiphytic algal communities in streams with and without Oncorhynchus mykiss (rainbow trout) and under different types of vegetation cover (forests versus pastures and crops). A total density of 119,600 organisms/cm3 was recorded, distributed across four phyla, six classes, 22 orders, 31 families, and 41 genera. Of the four treatments evaluated, treatments three and four recorded the highest periphyton densities, with the Bacillariophyta division being the most present in all four treatments evaluated. No significant differences were found between treatments regarding the presence of rainbow trout in the streams. This study presents baseline information on the influence of the introduction of O. mykiss on the phytoperiphytic algal community in Andean streams.

Humanoid robots promise general-purpose assistance, yet real-world humanoid loco-manipulation remains challenging because it requires whole-body stability, end-effector dexterity, and contact-aware interaction under frequent contact changes. In this work, we study dexterous, contact-rich humanoid loco-manipulation. We first develop an RL-based lower-body controller that serves as the stability backbone for whole-body execution during complex manipulation. Built on this controller, we develop a VR-based whole-body humanoid data collection system that integrates dexterous hands and tactile sensing for contact-rich manipulation. We then propose Humanoid Transformer with Touch Dreaming (HTD), a multimodal encoder–decoder Transformer that models touch as a core modality alongside multi-view vision and proprioception. HTD is trained in a single stage with behavioral cloning augmented by touch dreaming: in addition to predicting action chunks, the policy predicts future hand-joint forces and future tactile latents, with tactile-latent targets provided by an exponential moving average target encoder without requiring a separate tactile pretraining stage. This encourages the policy to learn contact-aware representations for dexterous manipulation. Across five real-world contact-rich tasks, HTD achieves a 90.9

Image captions serve as efficient surrogates for visual content in multimodal systems such as retrieval, recommendation, multi-step agentic inference pipelines. Yet current evaluation practices miss a fundamental question: Can captions stand-in for images in real downstream tasks? We propose a utility-based benchmark, CaptionQA, to evaluate model-generated captions, where caption quality is measured by how well it supports downstream tasks. CaptionQA is an extensible domain-dependent benchmark covering 4 domains, Natural, Document, E-commerce, and Embodied AI, each with fine-grained taxonomies (25 top-level and 69 subcategories) that identify useful information for domain-specific tasks. CaptionQA builds 33,027 densely annotated multiple-choice questions (50.3 per image on average) that explicitly require visual information to answer, providing a comprehensive probe of caption utility. In our evaluation protocol, an LLM answers these questions using captions alone, directly measuring whether captions preserve image-level utility and are utilizable by a downstream LLM. Evaluating state-of-the-art MLLMs reveals substantial gaps between the image and its caption utility. Notably, models nearly identical on traditional image-QA benchmarks lower by up to 32\% in caption utility. We release CaptionQA along with an open-source pipeline for extension to new domains.