Harmonic Drive (Germany)

High-density polyethylene’s (HDPE) chemical inertness, the foundation of its commercial success, renders it nearly impossible to chemically recycle. Furthermore, strict purity requirements limit mechanical recycling rates to ∼30% despite the legislative targets being 75%. Chemically recyclable polyolefin mimics containing cleavable ester linkages offer a solution, but their compatibility with commodity polyethylene waste streams remains unexplored, raising concerns that contamination could worsen rather than solve the global recycling crisis. Here, we demonstrate that HDPE-like polyesters (HDPE-like) exhibit complete miscibility with HDPE across all compositions (20–80 wt %), a crucial result given the expected difficulty to separate the HDPE-like from HDPE waste streams. Single melting transitions, cocrystallized lamellar structures, and retention of ductility confirm molecular-level mixing without mechanical failure. Strikingly, incorporation of just 20 wt %HDPE-like increases adhesion to aluminum by more than 10-fold (from 0.4 to 4.4 MPa), an effect that persists in postconsumer recycled HDPE, enabling upcycling of low-value waste into metal-laminate applications. Both components retain their recycling pathways: HDPE undergoes mechanical reprocessing, while HDPE-like achieves quantitative methanolysis to monomers that repolymerize with full property retention. By demonstrating that chemically recyclable polyesters can be miscible with, and functionally beneficial to, commodity polyolefins, this work establishes a dual-recycling framework where a contamination becomes a useful additive.

With the rapid growth of LLM-based chatbots and their applications in fields such as health, education, and entertainment, there is a growing interest in developing systems capable of mimicking human behavior through conversation and natural language interaction. These chatbots are available in several languages, such as English, French, and Spanish. Unfortunately, Arabic chatbots—especially those that understand Arabic dialects—are still very limited. In this paper, we develop a chatbot for the Moroccan Arabic dialect, specifically designed for the public sector, such as the fiscal domain and government administration. These institutions require tools to reduce communication loads, limit human assistance, and minimize the time needed to find documents or complete payment procedures. Our optimized chatbot combines recent technologies like LLMs and semantic similarity. It supports Moroccan citizens by providing responses in the Moroccan dialect (Darija), both in text and speech, without requiring extensive resources. It also supports other citizens in French, Spanish, and English. Our chatbot was tested in a real use case in the tax domain, and the results were satisfactory, especially considering the general complexity of the Arabic language and the particular challenges of the Moroccan dialect.

Abstract As cyber threats become increasingly automated and sophisticated, novel solutions must be introduced to improve defense of enterprise networks. Deep reinforcement learning (DRL) has demonstrated potential in mitigating these advanced threats. Single DRL agents have proven utility toward execution of autonomous cyber defense. Despite the success of employing single DRL agents, this approach presents significant limitations, especially regarding scalability within large enterprise networks. An attractive alternative to the single‐agent approach is the use of multi‐agent reinforcement learning (MARL). However, developing MARL agents is costly with few options for examining MARL cyber defense techniques against adversarial agents. This paper presents a MARL network security environment, the fourth iteration of the cyber autonomy gym for experimentation (CAGE) challenges. This challenge was specifically designed to test the efficacy of MARL algorithms in an enterprise network. Our work aims to evaluate the potential of MARL as a robust and scalable solution for autonomous network defense.

In our experiment, we want to observe how the plants grow when they are being covered,

Aging is a physiological process that involves a progressive decline in organ function, with loss of homeostasis and an increased likelihood of illness and death.This account focuses on classical perspectives on exosome biogenesis, and associated age-related changes.Due to their ability to transmit biological information between cells, this work also discusses the interaction of exosomes derived from mesenchymal cells, as a powerful adjunct in the treatment of combining Orofacial Harmonization techniques.The demand for aesthetic and rejuvenating treatments is increasing in society, therefore, every day, the search for orofacial harmonization increases exponentially with the aim of delaying aging.Orofacial harmonization is a set of procedures performed by dentists, which aims to achieve aesthetic and functional balance of the face.