Autism spectrum disorder (ASD) is a highly heritable and heterogeneous group of
neurodevelopmental phenotypes diagnosed in more than 1% of children. Common genetic variants …

The application of machine learning to predict materials’ properties usually requires a large
number of consistent data for training. However, experimental datasets of high quality are …

We present the largest exome sequencing study of autism spectrum disorder (ASD) to date (n
= 35,584 total samples, 11,986 with ASD). Using an enhanced analytical framework to …

Optical parametric amplification is a second-order nonlinear process whereby an optical
signal is amplified by a pump via the generation of an idler field 1 . This mechanism is …

Chitosan modification is an important method for the development of adsorbents that has
attracted considerable interest in recent years. In this regard, a new type of efficient Pb(II) …

In current deep learning paradigms, local training or the Standalone framework tends to
result in overfitting and thus low utility. This problem can be addressed by Distributed or …

Matching is a powerful statistical tool in design and analysis. Conventional two-group, or
bipartite, matching has been widely used in practice. However, its utility is limited to simpler …

Existing ferroptosis as an iron‐dependent form of regulated cell death primarily relies on
importing exogenous iron. However, the excessive employment of toxic materials may cause …

AT cell receptor (TCR) mediates antigen-induced signaling through its associated CD3ε, δ, γ,
and ζ, but the contributions of different CD3 chains remain elusive. Using quantitative mass …

In collaborative machine learning (CML), multiple agents pool their resources (eg, data)
together for a common learning task. In realistic CML settings where the agents are self-…