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Cell Rep 2022 Aug;40(6):111176

Allen Institute for Brain Science, Seattle, WA 98109, USA; Department of Neurosurgery, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA; Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA; Board of Governors Regenerative Medicine Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA; Center for Neural Science and Medicine, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA. Electronic address:

Which cell types constitute brain circuits is a fundamental question, but establishing the correspondence across cellular data modalities is challenging. Bio-realistic models allow probing cause-and-effect and linking seemingly disparate modalities. Here, we introduce a computational optimization workflow to generate 9,200 single-neuron models with active conductances. Read More

Nat Commun 2022 Aug 9;13(1):4657. Epub 2022 Aug 9.

Department of Electrical and Computer Engineering, Princeton University, Princeton, NJ, 08544, USA.

Executing quantum algorithms on error-corrected logical qubits is a critical step for scalable quantum computing, but the requisite numbers of qubits and physical error rates are demanding for current experimental hardware. Recently, the development of error correcting codes tailored to particular physical noise models has helped relax these requirements. In this work, we propose a qubit encoding and gate protocol for Yb neutral atom qubits that converts the dominant physical errors into erasures, that is, errors in known locations. Read More

Neural Netw 2022 Aug 1;154:346-359. Epub 2022 Aug 1.

Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russia. Electronic address:

A new approach called ABRF (the attention-based random forest) and its modifications for applying the attention mechanism to the random forest (RF) for regression and classification are proposed. The main idea behind the proposed ABRF models is to assign attention weights with trainable parameters to decision trees in a specific way. The attention weights depend on the distance between an instance, which falls into a corresponding leaf of a tree, and training instances, which fall in the same leaf. Read More

PLoS One 2022 9;17(8):e0272413. Epub 2022 Aug 9.

Harry Butler Institute, Murdoch University, Murdoch, WA, Australia.

Appropriate inspection protocols and mitigation strategies are a critical component of effective biosecurity measures, enabling implementation of sound management decisions. Statistical models to analyze biosecurity surveillance data are integral to this decision-making process. Our research focuses on analyzing border interception biosecurity data collected from a Class A Nature Reserve, Barrow Island, in Western Australia and the associated covariates describing both spatial and temporal interception patterns. Read More

ICS 2022 Jun 28;2022. Epub 2022 Jun 28.

University of South Florida, Tampa, FL, USA.

Due to the high level of parallelism, there are unique challenges in developing system software on massively parallel hardware such as GPUs. One such challenge is designing a dynamic memory allocator whose task is to allocate memory chunks to requesting threads at runtime. State-of-the-art GPU memory allocators maintain a global data structure holding metadata to facilitate allocation/deallocation. Read More