Publisher Correction: Unified percolation scenario for the α and β processes in simple glass formers
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Family-based genome-wide association study designs for increased power and robustness
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Demand-side strategies enable rapid and deep cuts in buildings and transport emissions to 2050
Decarbonization of energy-using sectors is essential for tackling climate change. We use an ensemble of global integrated assessment models to assess CO2 emissions reduction potentials in buildings and transport, accounting for system interactions. We focus on three intervention strategies with distinct emphases: reducing or changing activity, improving technological efficiency and electrifying energy end use. We find that these strategies can reduce emissions by 51–85% in buildings and 37–91% in transport by 2050 relative to a current policies scenario (ranges indicate model variability). Electrification has the largest potential for direct emissions reductions in both sectors. Interactions between the policies and measures that comprise the three strategies have a modest overall effect on mitigation potentials. However, combining different strategies is strongly beneficial from an energy system perspective as lower electricity demand reduces the need for costly supply-side investments and infrastructure.
Improved radicchio seedling growth under CsPbI3 perovskite rooftop in a laboratory-scale greenhouse for Agrivoltaics application
Agrivoltaics, integrating photovoltaic systems with crop cultivation, demands semitransparent solar modules to mitigate soil shadowing. Perovskite Solar Cells (PSC) offer competitive efficiency, low fabrication costs, and high solar transmittance, making them suitable for agrivoltaic applications. However, the impact of PSC light filtering on plant growth and transcriptomics remains underexplored. This study investigates the viability and agronomic implications of the growth of radicchio seedlings (Cichorium intybus var. latifolium) in laboratory-scale greenhouses integrating Perovskites-coated rooftops. Eu-enriched CsPbI3 layers are chosen to provide semi-transparency and phase stability while radicchio has limited size and grows in pots. Despite the reduced light exposure, radicchio seedlings exhibit faster growth and larger leaves than in the reference, benefiting from specific spectral filtering. RNA-sequencing reveals differential gene expression patterns reflecting adaptive responses to environmental changes. Simulations of full PSC integration demonstrate a positive energy balance in greenhouses to cover annual energy needs for lighting, irrigation, and air conditioning.
Electric-field manipulation of magnetization in an insulating dilute ferromagnet through piezoelectromagnetic coupling
The electric field control of magnetization is of significant interest in materials science due to potential applications in many devices such as sensors, actuators, and magnetic memories. Here, we report magnetization changes generated by an electric field in ferromagnetic Ga1−xMnxN grown by molecular beam epitaxy. Two classes of phenomena have been revealed. First, over a wide range of magnetic fields, the magnetoelectric signal is odd in the electric field and reversible. Employing a macroscopic spin model and atomistic Landau-Lifshitz-Gilbert theory with Langevin dynamics, we demonstrate that the magnetoelectric response results from the inverse piezoelectric effect that changes the trigonal single-ion magnetocrystalline anisotropy. Second, in the metastable regime of ferromagnetic hystereses, the magnetoelectric effect becomes non-linear and irreversible in response to a time-dependent electric field, which can reorient the magnetization direction. Interestingly, our observations are similar to those reported for another dilute ferromagnetic semiconductor Crx(Bi1−ySby)1−xTe3, in which magnetization was monitored as a function of the gate electric field. Those results constitute experimental support for theories describing the effects of time-dependent perturbation upon glasses far from thermal equilibrium in terms of an enhanced effective temperature.
A unified acoustic-to-speech-to-language embedding space captures the neural basis of natural language processing in everyday conversations
This study introduces a unified computational framework connecting acoustic, speech and word-level linguistic structures to study the neural basis of everyday conversations in the human brain. We used electrocorticography to record neural signals across 100 h of speech production and comprehension as participants engaged in open-ended real-life conversations. We extracted low-level acoustic, mid-level speech and contextual word embeddings from a multimodal speech-to-text model (Whisper). We developed encoding models that linearly map these embeddings onto brain activity during speech production and comprehension. Remarkably, this model accurately predicts neural activity at each level of the language processing hierarchy across hours of new conversations not used in training the model. The internal processing hierarchy in the model is aligned with the cortical hierarchy for speech and language processing, where sensory and motor regions better align with the model’s speech embeddings, and higher-level language areas better align with the model’s language embeddings. The Whisper model captures the temporal sequence of language-to-speech encoding before word articulation (speech production) and speech-to-language encoding post articulation (speech comprehension). The embeddings learned by this model outperform symbolic models in capturing neural activity supporting natural speech and language. These findings support a paradigm shift towards unified computational models that capture the entire processing hierarchy for speech comprehension and production in real-world conversations.
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