San Pablo Catholic University, known locally as Universidad Católica San Pablo (UCSP) is a private university in Arequipa, Peru. The university is owned by the Sodalitium Christianae Vitae.The university has two campuses, one in Salaverry avenue, and one in Campiña Paisajista urb..
A composite material with potential applications in the packaging industry was developed using leather shavings, scrap office paper, thermoplastic resin, and distilled water. The production process consisted of raw material preparation, the production of recycled paperboard sheets, and sheet finishing. An extreme vertex mixture design generated 13 samples to optimize the proportions of paper, leather shavings and resin, using tensile strength (ASTM D828-22) as the dependent variable. The optimal recycled paperboard formulation was 70wt.% paper, 5wt.% leather shavings, and 25wt.% resin. Physical tests were conducted to measure grammage (ISO 536), thickness (ISO 534), moisture content (TAPPI T 412), and water absorption (ISO 535-2023). Chemical analyses included scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy (FTIR) with attenuated total reflectance (ATR), thermogravimetric analysis (TGA), derivative thermogravimetry (DTG) and elemental chemical composition of the composite material. Compared with reference paperboard, the recycled paperboard exhibited lower moisture absorption but also reduced tensile strength. FTIR spectra confirmed cellulose-related bands and revealed the presence of collagen from leather, while TGA/DTG curves indicated slight shifts in degradation temperatures, reflecting reduced thermal stability due to leather incorporation. The recycled paperboard shows potential for sustainable packaging applications that demand moderate mechanical performance. However, the lower thermal stability and tensile strength may limit its use in high-stress demanding applications.
El trabajo doméstico es una actividad de alta exigencia, no solamente por la cantidad de labores del hogar y de cuidado de niñas, niños y personas mayores que usualmente involucra, sino también por una alta exigencia de trabajo emocional que debe ser realizado. Es una actividad subvalorada, asociada a lógicas de servilismo y esclavitud, que en el caso de América Latina, se inscribe en un pasado colonial que empleaba a etnias infravaloradas. En este contexto, bajo el lente analítico de la sociología de las emociones se analiza la gestión de emociones que trabajadoras domésticas migrantes realizan en Chile, a fin de adaptarse a una cultura emocional que le prescribe características de sumisión, obediencia y docilidad. Mediante entrevistas en profundidad, se analizan sus estrategias para gestionar las emociones en un contexto laboral altamente demandante. Concluimos que el trabajo emocional se intensifica por presentarse múltiples desigualdades interseccionadas, a la vez de adaptarse a una cultura emocional que no es la propia, lo que hemos denominado gestión emocional de ultra intensidad.
Robotic manipulation in open-world settings requires not only task execution but also the ability to detect and learn from failures. While recent advances in vision-language models (VLMs) and large language models (LLMs) have improved robots' spatial reasoning and problem-solving abilities, they still struggle with failure recognition, limiting their real-world applicability. We introduce AHA, an open-source VLM designed to detect and reason about failures in robotic manipulation using natural language. By framing failure detection as a free-form reasoning task, AHA identifies failures and provides detailed, adaptable explanations across different robots, tasks, and environments. We fine-tuned AHA using FailGen, a scalable framework that generates the first large-scale dataset of robotic failure trajectories, the AHA dataset. FailGen achieves this by procedurally perturbing successful demonstrations from simulation. Despite being trained solely on the AHA dataset, AHA generalizes effectively to real-world failure datasets, robotic systems, and unseen tasks. It surpasses the second-best model (GPT-4o in-context learning) by 10.3% and exceeds the average performance of six compared models including five state-of-the-art VLMs by 35.3% across multiple metrics and datasets. We integrate AHA into three manipulation frameworks that utilize LLMs/VLMs for reinforcement learning, task and motion planning, and zero-shot trajectory generation. AHA’s failure feedback enhances these policies' performances by refining dense reward functions, optimizing task planning, and improving sub-task verification, boosting task success rates by an average of 21.4% across all three tasks compared to GPT-4 models. Project page: https://aha-vlm.github.io
Creative experiences may enhance brain health, yet metrics and mechanisms remain elusive. We characterized brain health using brain clocks, which capture deviations from chronological age (i.e., accelerated or delayed brain aging). We combined M/EEG functional connectivity (N = 1,240) with machine learning support vector machines, whole-brain modeling, and Neurosynth metanalyses. From this framework, we reanalyzed previously published datasets of expert and matched non-expert participants in dance, music, visual arts, and video games, along with a pre/post-learning study (N = 232). We found delayed brain age across all domains and scalable effects (expertise>learning). The higher the level of expertise and performance, the greater the delay in brain age. Age-vulnerable brain hubs showed increased connectivity linked to creativity, particularly in areas related to expertise and creative experiences. Neurosynth analysis and computational modeling revealed plasticity-driven increases in brain efficiency and biophysical coupling, in creativity-specific delayed brain aging. Findings indicate a domain‑independent link between creativity and brain health.
Blood-based Alzheimer’s disease (AD) biomarkers have been increasingly employed for diagnostic, prognostic, and therapeutic monitoring purposes, due to accuracy in distinguishing AD pathophysiologic process. Compared to other p-tau isoforms, plasma p-tau217 exhibits stronger associations with AD hallmarks in CSF and brain. However, most studies have been conducted in non-Hispanic Whites, limiting our understanding of the performances and utility of these biomarkers across ethnicities. We examined a cohort of Peruvians from the GAPP study, a recently established cohort of Peruvian mestizos from Lima and indigenous groups from Southern Peru (Aymaras and Quechuas). We tested plasma levels of p-tau using the Quanterix Simoa ALZpathp-tau217 assay in 525 samples and tested the association between p-tau217 and clinical diagnosis (healthy controls n = 234 vs. AD n = 113) using generalized mixed regression models, adjusting for sex, age, education, APOE-e4 allele (fixed effects) and study site (random effect). We also tested biomarker levels in MCI (n = 178) vs. other groups. The receiver operating characteristics area under the curve (ROC-AUC) was used to evaluate the biomarker’s classification performances. Participants showed on average 80
