Instituto Tecnológico de Querétaro

Injection-molding purges are heterogeneous, bulky residues whose uncertain composition and irregular geometry hinder direct reinsertion, making cold shredding costly and maintenance-intensive. This work develops a low-infrastructure solar-assisted pre-processing route using a PMMA Fresnel lens to induce controlled sub-onset softening and enable clean shear cutting without destructive thermal histories. The sub-onset softening is here defined into a viscoelastically active range (at or above Tg for the amorphous phase) while remaining below the melting onset (Tm, onset) and below the onset of thermal degradation (Td, onset). The station was engineered via QFD and risk-oriented design tools, while a weighted Pugh matrix selected shear cutting over saw-based alternatives. A screening factorial DOE showed that lens height, angle, and their interaction significantly govern focal-spot diameter and receiver temperature, yielding linear relations for conservative set-point selection. Receiver benchmarking further indicated that copper reaches substantially higher temperatures than graphite under identical exposure conditions, supporting copper as the simplest, rapid-heating receiver. Under DOE-calibrated operation, tear-free shear cutting was achieved across representative purge families (PP–ABS, PC–ABS–PP, PA66, PA66-filler, and POM) without forced convection. From a recycling and waste-management perspective, the approach converts bulky purge scrap into mill-compatible feedstock with reduced mechanical resistance, lowering tool wear and fines generation, accelerating downsizing, and limiting stockpiling that elevates combustible-inventory fire risk. Overall, the proposed DOE-calibrated, operator-friendly framework improves recycling feasibility by enabling safer handling, more stable preprocessing throughput, and reduced reliance on disposal or long-term storage for heterogeneous industrial purges.

This research addresses the increasing need for efficient energy management in residential settings in response to the increasing global energy demands, focusing on the integration of artificial intelligence to identify energy burdens. We employ and compare some machine learning models, like Decision Trees, K-nearest neighbors, and Feedforward Neural Networks, with a primary focus on electrical current as a key parameter. The Fine K-NN model shows notable efficiency, achieving an accuracy of 99.1% in the identification of active household appliances using a single sensor. Our methodology encompasses rigorous data acquisition and preprocessing under controlled experimental conditions, ensuring the integrity and reliability of our results. This study contributes to the field by illustrating the effectiveness of specific AI models in energy management under controlled conditions, paving the way for future advancements in AI-driven energy conservation strategies.

The present comparative bibliometric study (2020-2025) of the Scopus and WoS databases on Generative Artificial Intelligence (GenAI) reveals accelerated growth, concentrating more than 95% of the production and reaching its peak impact in 2025. Thematically, the intersection of communication and technology/education dominates. Geographically, the United States leads production, but Asia-Pacific institutions (Hong Kong) are key. The field of GenAI is a massive trend driven by concentrated collaboration between North America and Asia. Smart citations: https://scite.ai/reports/10.61467/2007.1558.2026.v17i2.1281Dimensions.Open Alex.

The agave wilt associated with Fusarium oxysporum (Fox) is a major disease of blue agave (Agave tequilana Weber var. azul), used to produce “Tequila” in Mexico. Little is known about the A. tequilana-F. oxysporum interaction yet understanding defense mechanisms against the pathogen is necessary for control strategies. During early Fox infection, plants trigger defense mechanisms to interrupt the compatible interaction, while Fox’s pathogenesis mechanism interacts with plant response. This study evaluated plant defense mechanisms induced by Fox in A. tequilana and their interaction with fungal pathogenesis. For this, an A. tequilana pathogenic strain (FPA), and the non-A. tequilana pathogenic strains FNPA and FOL were utilized. Early defense mechanisms evaluated were hypersensitive response (HR) and cell wall strengthening in agave roots. Resistance mechanisms evaluated included pathogenesis-related proteins (PR proteins), phytoanticipins and phytoalexins. For early defense, induced HR was greater with FPA than other strains. Cell wall strengthening was found in agave roots, plants responded differentially to different strains. Initial response to FPA and FOL was similar in PR proteins, phytoalexins and phytoanticipins production. However, the response differentiated with FOL over time, indicating an incompatible interaction. The study identified effective and ineffective defense responses of A. tequilana to Fox infection, where FPA exhibited compatibility and caused unregulated ROS and PCD, early inhibition of PR activity, extensive lignification, and saponin detoxification. In contrast, this study unveiled incompatible interactions (FNPA and FOL) because of limited colonization, localized HR with suppressed ROS, early and sustained POX activation, significant callose accumulation, moderate lignification, and phenol–saponin dynamics that help in tissue containment and recovery.

The rapid evolution of innovative materials and their 4D printing on fabrics allows textiles to change shape or properties when exposed to external stimuli. This work reviews the fundamentals of 4D printing, briefly revisiting additive manufacturing technology and materials, as both are extensively described in various articles and reviews. It also outlines the advancements in smart textiles and their functionality as multifunctional fabrics. The review focuses primarily on reviewing the technical foundations and emerging applications of 4D-printed smart polymers and their integration onto passive textiles for smart applications. Finally, a critical review is presented, emphasizing the numerous individual developments undertaken not only in academia but also by young students, independent engineers, and entrepreneurs who showcase their progress and various challenges through social media. Easy access to knowledge, digital communication, and an interest in creating new materials and structures with a relatively low budget will allow the advancement and development of 4D printing processing strategies for functional materials, promoting the creation of intelligent and adaptive textile systems.

Lemna minor is an aquatic plant with a high growth rate, which can cause problems in freshwater bodies. In this work, Lemna minor was valorized for the development of bifunctional electrocatalysts for rechargeable and flexible zinc–air batteries (FZABs), by synthesizing cobalt‐doped and cobalt–manganese co‐doped electrocatalysts (L‐Co and L‐CoMn). Raman spectroscopy revealed structural disorder, particularly in L‐Co, which was further confirmed by TEM and attributed to a high density of surface defects. Moreover, TEM and STEM imaging indicated the formation of both spinel nanoparticles and atomically dispersed metal sites, which together with surface defects, contributed to the electrocatalytic activity. Electrochemical tests showed that L‐Co exhibited superior activity in the oxygen reduction reaction, while L‐CoMn demonstrated enhanced activity for the oxygen evolution reaction, achieving a low overpotential of 1.56 V at 10 mA cm −2 . When used as bifunctional electrocatalysts in FZABs, the L‐Co presented better performance, higher cycling stability (>100 cycles), and improved capability to operate at elevated current densities, while achieving an areal specific capacity of 14.7 mA.h cm −2 . These results demonstrate the potential of Lemna minor valorization for applications in electrochemical and sustainable energy technologies.

En este trabajo, se presenta un controlador por modo deslizante Super-Twisting en tiempo continuo (ST-SMC) con el fin de regular la temperatura y concentración en un reactor continuo de tanque agitado (CSTR). La metodología propuesta mejora la robustez y la suavidad de la señal de control usando un marco de estabilidad de Lyapunov y una estructura derivativa filtrada que atenúa oscilaciones sin afectar la convergencia en tiempo finito. A diferencia de los controladores PID y modos deslizantes clásicos, el diseño propuesto mantiene un seguimiento robusto ante incertidumbres paramétricas, no linealidades y perturbaciones no coincidentes. Las simulaciones en MATLAB-Simulink muestran reducciones de 42% en ISE, 37% en IAE y más del 80% en oscilaciones. El análisis de Lyapunov garantiza la estabilidad global y la convergencia en tiempo finito. Por lo tanto, la estrategia logra un equilibrio entre robustez, adaptabilidad y suavidad, constituyéndose como una alternativa sólida para la implementación en tiempo real en procesos termoquímicos no lineales, donde los controladores tradicionales no aseguran simultáneamente estabilidad y eficiencia energética.