A new parallel framework of distributed SWAT calibration

With the development of large-scale hydrologic modeling, computational efficiency is becoming more and more important. Rapid modeling and analysis are needed to deal with emergency environmental disasters. The Soil and Water Assessment Tool （SWAT） is a popular hydrologic model, which is less applied in large-scale watershed simulation because of its sequential characteristics. For improving the computational efficiency of the SWAT model, we present a new parallel processing solution for hydrologic cycle and calibration based on MPI （Message Passing Interface）. We partitioned sub-basins during the processes based on a load balancing method Then the calibration was parallelized using a master-slave scheme, in which different input parameters were allocated to different processes to run the hydrologic cycle and compute the function value. Because of the slow convergence and local optimization of the SCE-UA （Shuffled Complex Evolution-developed by University of Arizona） algorithm in SWAT calibration, a genetic algorithm （GA） is developed to optimize the calibration step. Then by dividing the default communicator into several sub-communicators, all the hydrologic cycles were par- allelized in their own sub-communicators to achieve further acceleration. In this paper the results show speedups for the hydrologic cycle calculations, as well as in the optimized calibration step. In the case study, we tested the parallel hydrologic cycle by four processes, and got a speedup of 3.06. In the calibration section, after applying the GA optimization, with 10 cores, we got a speed increase of 8.0 in our GA parallel framework compared with the GA sequential calibration, which is much better than the original SWAT calibration. After the sub-communicators added, this process was speeded up even further. The study demonstrated that the GA parallel framework with multi-sub-communicators is an effective and efficient solution for the hydrologists in large scale hydrology simulations.

A Novel Retrograde AAV Variant for Functional Manipulation of Cortical Projection Neurons in Mice and Monkeys

Retrograde adeno-associated viruses(AAVs)are capable of infecting the axons of projection neurons and serve as a powerful tool for the anatomical and functional characterization of neural networks.However,few retro-grade AAV capsids have been shown to offer access to cor-tical projection neurons across different species and enable the manipulation of neural function in non-human primates(NHPs).Here,we report the development of a novel retro-grade AAV capsid,AAV-DJ8R,which efficiently labeled cortical projection neurons after local administration into the striatum of mice and macaques.In addition,intrastriatally injected AAV-DJ8R mediated opsin expression in the mouse motor cortex and induced robust behavioral alterations.Moreover,AAV-DJ8R markedly increased motor cortical neuron firing upon optogenetic light stimulation after viral delivery into the macaque putamen.These data demonstrate the usefulness of AAV-DJ8R as an efficient retrograde tracer for cortical projection neurons in rodents and NHPs and indicate its suitability for use in conducting functional interrogations.

Designing highly transparent cerium doped Y_(2)O_(3) ceramics with high mechanical and thermal properties for UV-shielding in extreme conditions

Ultraviolet(UV)radiation poses risks to both human health and organics.In response to the urgent demand for UV-shielding across various applications,extensive endeavors have been dedicated to developing UV-shielding materials spanning from wide-bandgap semiconductors to organo-inorganic composite films.However,existing UV shielding materials,though suitable for daily use,cannot meet the demands of extreme conditions.In this work,we incorporated CeO_(2)as a UV absorber into Y_(2)O_(3)transparent ceramics for UV-shielding.The effect of CeO_(2)concentration on the optical,mechanical,and thermal properties of Y_(2)O_(3)ceramics was systematically investigated.These findings indicate that CeO_(2)serves not only as a UV absorber but also as an effective sintering aid for Y_(2)O_(3)transparent ceramics.The 5 at%Ce-doped Y_(2)O_(3)transparent ceramics exhibit the optimal optical quality,with in-line transmittance of~77%at 800 nm.The introduction of Ce shifted the UV cutoff edge of Y_(2)O_(3)transparent ceramics from 250 to 375 nm,which was attributed to the visible band absorption of Ce^(4+).This shift grants UV shielding capabilities to Y_(2)O_(3)transparent ceramics,resulting in 100%shielding for ultraviolet C(UVC,100-280 nm)and ultraviolet B(UVB,280-320 nm)and~95%shielding for ultraviolet A(UVA,320-400 nm).The service stability(optical properties)under various corrosive conditions(acid,alkali,UV irradiation,and high temperature)was investigated,confirming the excellent stability of this transparent ceramic UV-shielding material.A comparison of the performance parameters of transparent ceramics with those of traditional UV shielding materials such as glasses,films,and coatings was conducted.Our work provides innovative design concepts and an effective solution for UVshielding materials for extreme conditions.

Gclust:A Parallel Clustering Tool for Microbial Genomic Data

The accelerating growth of the public microbial genomic data imposes substantial burden on the research community that uses such resources.Building databases for non-redundant reference sequences from massive microbial genomic data based on clustering analysis is essential.However,existing clustering algorithms perform poorly on long genomic sequences.In this article,we present Gclust,a parallel program for clustering complete or draft genomic sequences,where clustering is accelerated with a novel parallelization strategy and a fast sequence comparison algorithm using sparse suffix arrays(SSAs).Moreover,genome identity measures between two sequences are calculated based on their maximal exact matches(MEMs).In this paper,we demonstrate the high speed and clustering quality of Gclust by examining four genome sequence datasets.Gclust is freely available for non-commercial use at https://github.com/niu-lab/gclust.We also introduce a web server for clustering user-uploaded genomes at http://niulab.scgrid.cn/gclust.

Trans-synaptic Neural Circuit-Tracing with Neurotropic Viruses

A central objective in deciphering the nervous system in health and disease is to define the connections of neurons. The propensity of neurotropic viruses to spread among synaptically-linked neurons makes them ideal for mapping neural circuits. So far, several classes of viral neuronal tracers have become available and provide a powerful toolbox for delineating neural networks. In this paper, we review the recent developments of neurotropic viral tracers and highlight their unique properties in revealing patterns of neuronal connections.

A Novel Electric Dual Motor Transmission for Heavy Commercial Vehicles

As a vital vehicle part,the powertrain system is undergoing a fast transition towards electrification.The new integrated electric drive system has been widely used,especially for passenger cars.In this work,a novel electric dual motor transmission is proposed for heavy commercial vehicles.The transmission scheme is firstly introduced,which can achieve 9 different operating modes including 5 single motor modes and 4 dual motor modes.Then,the mode shift map with minimum energy consumption is designed based on the motor efficiency map and the proposed energy management strategy.The driving power is appropriately distributed between the two motors in dual motor modes under the condition of minimum power consumption.In addition,a coordinated control strategy is developed for mode shift control without power interruption.The results show that the electric dual motor transmission has advantages in power consumption and power shift ability compared with the conventional single motor automated manual transmission.

Optimal Timing of a Commonly-Used Rabies Virus for Neural Recording and Manipulation

Dear Editor,A fundamental goal of modern neuroscience is to dissect the neural circuits in the brain and understand their functions.As a powerful tool for anatomical studies,the genetically modified rabies virus(RV)SADAG(EnvA)has achieved great success in mapping presynaptic inputs to genetically marked neurons[1-3].

How Big Data and High-performance Computing Drive Brain Science

Brain science accelerates the study of intelligence and behavior,contributes fundamental insights into human cognition,and offers prospective treatments for brain disease.Faced with the challenges posed by imaging technologies and deep learning computational models,big data and high-performance computing(HPC)play essential roles in studying brain function,brain diseases,and large-scale brain models or connectomes.We review the driving forces behind big data and HPC methods applied to brain science,including deep learning,powerful data analysis capabilities,and computational performance solutions,each of which can be used to improve diagnostic accuracy and research output.This work reinforces predictions that big data and HPC will continue to improve brain science by making ultrahigh-performance analysis possible,by improving data standardization and sharing,and by providing new neuromorphic insights.