Notes

autoBOT: evolving neuro-symbolic representations for explainable reduced source text message distinction.
The ongoing revolution of the natural sciences by the advent of machine learning and artificial intelligence sparked significant interest in the material science community in recent years. The intrinsically high dimensionality of the space of realizable materials makes traditional approaches ineffective for large-scale explorations. Pyrrolidinedithiocarbamate ammonium chemical structure Modern data science and machine learning tools developed for increasingly complicated problems are an attractive alternative. An imminent climate catastrophe calls for a clean energy transformation by overhauling current technologies within only several years of possible action available. Tackling this crisis requires the development of new materials at an unprecedented pace and scale. For example, organic photovoltaics have the potential to replace existing silicon-based materials to a large extent and open up new fields of application. In recent years, organic light-emitting diodes have emerged as state-of-the-art technology for digital screens and portable devices and are enabliscovery and derive material design strategies. Subsequently, our focus lies on the data-driven methodologies our group has developed and employed, elaborating on high-throughput virtual screening, inverse molecular design, Bayesian optimization, and supervised learning. We discuss the general ideas, their working principles, and their use cases with examples of successful implementations in data-driven material discovery and design efforts. Furthermore, we elaborate on potential pitfalls and remaining challenges of these methods. Finally, we provide a brief outlook for the field as we foresee increasing adaptation and implementation of large scale data-driven approaches in material discovery and design campaigns.Biological skin systems can perceive various external stimuli through ion transduction. Especially, the skin of some advanced organisms such as cephalopods can further promptly change body color by manipulating photonic nanostructures. However, the current skin-inspired soft iontronics lack the rapid full-color switching ability to respond to multiple stimuli including tension, pressure, and temperature. Here, an intelligent chromotropic iontronics with these fascinating functions is developed by constructing a biomimetic ultrastructure with anisotropic electrostatic repulsion. This skin-like chromotropic iontronics can synchronously realize electrical response and optical visualization to mechanical strain and tactile sensation by adjusting the ultrastructure in cooperation with ionic mechanotransduction. Notably, it can perform instantaneous geometric changes to thermal stimuli via an anisotropic electrostatic repulsion interior. Such a capability allows bionic skin to transduce temperature or infrared light into ionic signals and color changes in real time. The design of anisotropic photonic nanostructures expands the intelligent application for soft iontronics at higher levels, providing a concise, multifunctional, interactive sensing platform that dynamically displays stimuli information on its body.The coordination-driven self-assembly methodology has emerged over the last few decades as an extraordinarily versatile synthetic tool for obtaining discrete macrocyclic or cage structures. Rational approaches using large libraries of ligands and metal complexes have allowed researchers to reach more and more sophisticated discrete structures such as interlocked, chiral, or heteroleptic cages, and some of them are designed for guest binding applications. Efforts have been notably produced in controlling host-guest affinity with, in particular, an evident interest in targeting substrate transportation and subsequent delivering. Recent accomplishments in this direction were described from functional cages which can be addressed with light, pH, or through a chemical exchange. The case of a redox-stimulation has been much less explored. In this case, the charge state of the redox-active cavity can be controlled through an applied electrical potential or introduction of an appropriate oxidizing/reducing chemical aarkable ability of electron-rich, coordination-based self-assembled cavities to bind various types of guests and, importantly, to trigger their release through a redox-stimulus.Escherichiacoli has become the prominent cause of nosocomial pneumonia in recent years. In the meantime, some strains of E. coli have developed resistance to commonly used antibacterial drugs. The urinary bladder matrix (UBM) is a biologically derived scaffold material that has been used to promote site-appropriate tissue remodeling in a variety of body systems, partially through the modulation of the innate immune response. In this study, we seek to determine UBM efficacy in preventing bacterial pneumonia in mouse lungs using the Gram-negative bacterial strain E. coli. Our results show that the UBM prevented bacterial biofilm formation in both abiotic and biotic conditions through experimentation on polystyrene plates and culture on the apical surface of differentiated airway epithelial cells. Intratracheal treatment with UBM led to host protection from E. coli-induced respiratory infection in a murine pneumonia model. Transcriptomic analysis revealed the involvement of the enhanced host immune response in UBM-treated mice. Additionally, UBM-treated macrophages had an increased iNOS expression and enhanced phagocytosis activity. Therefore, the protection against E. coli-induced infection and the antibacterial function observed by UBM is potentially through both the anti-biofilm activity and enhanced host immunity following UBM treatment. Taken together, our results support further investigation of UBM as an alternative treatment to attenuate bacterial-induced respiratory infection.In order to circumvent the usual nucleation of randomly distributed tiny metallic dots photodeposited on TiO2 nanoparticles (NPs) induced by conventional UV lamps, we propose to synthesize well-controlled nanoheterodimers (NHDs) using lasers focused inside microfluidic reactors to strongly photoactivate redox reactions of active ions flowing along with nanoparticles in water solution. Since the flux of photons issued from a focused laser may be orders of magnitude higher than that reachable with classical lamps, the production of electron-hole pairs is tremendously increased, ensuring a large availability of carriers for the deposition and favoring the growth of a single metallic dot as compared to secondary nucleation events. We show that the growth of single silver or gold nanodots can be controlled by varying the beam intensity, the concentration of the metallic salt, and the flow velocity inside the microreactor. The confrontation to a build-in model of the metallic nanodot light-induced growth onto the surface of TiO2 NPs shows the emergence of a predictable "master behavior" on which individual growths obtained from various tested conditions do collapse.
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