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To achieve the goals of the Paris Agreement on climate change, governments around the world must shift to renewable energy (RE) to drastically reduce their CO2 emissions within the next 10-30 years. The development of effective strategies for RE integratio ...
There are 377 Krüppel-associated box (KRAB) domain-containing zinc finger proteins (KZFPs) in the human genome, making them the largest family of transcription factors. KZFPs are defined by a N-terminal KRAB domain and several zinc-finger domains arranged ...
Artificial intelligence and machine learning algorithms have become ubiquitous. Although they offer a wide range of benefits, their adoption in decision-critical fields is limited by their lack of interpretability, particularly with textual data. Moreover, ...
Lysine L-lactylation [K(L-la)] is a newly discovered histone mark stimulated under conditions of high glycolysis, such as the Warburg effect. K(L-la) is associated with functions that are different from the widely studied histone acetylation. While K(L-la) ...
This dataset contains corrected particle number concentration data measured during the year long MOSAiC expedition from October 2019 to September 2020. The measurement was performed in the Swiss aerosol container on the D-deck of Research Vessel Polarstern ...
Research problem: Housing is responsible for a considerable part of global resource consumption. In Switzerland, it accounts for almost one third of the country's CO2 emissions and half of the total energy demand. Thus, housing plays an important role in t ...
Although decoding the content of mental states is currently unachievable, technologies such as neural interfaces, affective computing systems, and digital behavioral technologies enable increasingly reliable statistical associations between certain data pa ...
Engineering and computational advances have opened many new avenues in cancer research, particularly when being exploited in interdisciplinary approaches. For example, the combination of microfluidics, novel sequencing technologies, and computational analy ...
We provide a computationally and statistically efficient method for estimating the parameters of a stochastic covariance model observed on a regular spatial grid in any number of dimensions. Our proposed method, which we call the Debiased Spatial Whittle l ...
We consider the problem of enhancing user privacy in common data analysis and machine learning development tasks, such as data annotation and inspection, by substituting the real data with samples from a generative adversarial network. We propose employing ...
