Externally-Contracted Multireference Configuration Interaction Method Using a DMRG Reference Wave Function.

The recent development of the density matrix renormalization group (DMRG) method in multireference quantum chemistry makes it practical to evaluate static correlation in a large active space, while dynamic correlation provides a critical correction to the DMRG reference for strong-correlated systems and is usually obtained using multireference perturbation (MRPT) or configuration interaction (MRCI) methods with internal contraction (ic) approximation. These methods can use an active space scalable to relatively larger size references than has previously been possible. However, they are still hardly applicable to systems with an active space larger than 30 orbitals and/or a large basis set because of high computation and storage costs of high-order reduced density matrices (RDMs) and the crucial dependence of the MRCI Hamiltonian dimension on the number of virtual orbitals.

Personalized prediction model for seizure-free epilepsy with levetiracetam therapy: a retrospective data analysis using support vector machine.

Aims: To predict the probability of a seizure-free (SF) state in patients with epilepsy (PWEs) after treatment with levetiracetam and to identify the clinical and electroencephalographic (EEG) factors that affect outcomes.

Methods: Retrospective analysis of PWEs treated with levetiracetam for 3 years identified 22 patients who were SF and 24 who were not. Before starting levetiracetam, 11 clinical factors and four EEG features (sample entropy of α, β, θ, δ) were identified.

Epidemiological shift and geographical heterogeneity in the burden of leptospirosis in China.

Background: Leptospirosis morbidity and mortality rates in China have decreased since the 2000s. Further analyses of the spatiotemporal and demographic changes occurring in the last decade and its implication on estimates of disease burden are required to inform intervention strategies. In this study, we quantified the epidemiological shift and geographical heterogeneity in the burden of leptospirosis during 2005-2015 in China.

Modeling Habitat Suitability of Migratory Birds from Remote Sensing Images Using Convolutional Neural Networks.

With the application of various data acquisition devices, a large number of animal movement data can be used to label presence data in remote sensing images and predict species distribution. In this paper, a two-stage classification approach for combining movement data and moderate-resolution remote sensing images was proposed. First, we introduced a new density-based clustering method to identify stopovers from migratory birds’ movement data and generated classification samples based on the clustering result.

Recurrent Transformation of Prior Knowledge Based Model for Human Motion Recognition.

Motion related human activity recognition using wearable sensors can potentially enable various useful daily applications. So far, most studies view it as a stand-alone mathematical classification problem without considering the physical nature and temporal information of human motions. Consequently, they suffer from data dependencies and encounter the curse of dimension and the overfitting issue.

RPiRLS: Quantitative Predictions of RNA Interacting with Any Protein of Known Sequence.

RNA-protein interactions (RPIs) have critical roles in numerous fundamental biological processes, such as post-transcriptional gene regulation, viral assembly, cellular defence and protein synthesis. As the number of available RNA-protein binding experimental data has increased rapidly due to high-throughput sequencing methods, it is now possible to measure and understand RNA-protein interactions by computational methods. In this study, we integrate a sequence-based derived kernel with regularized least squares to perform prediction.

Sources and distribution of microplastics in China's largest inland lake - Qinghai Lake.

Microplastic pollution was studied in China's largest inland lake - Qinghai Lake in this work. Microplastics were detected with abundance varies from 0.05 × 10 to 7.

[Exploiture and application of an internet-based Computation Platform for Integrative Pharmacology of Traditional Chinese Medicine].

Recently, integrative pharmacology(IP) has become a pivotal paradigm for the modernization of traditional Chinese medicines(TCM) and combinatorial drugs discovery, which is an interdisciplinary science for establishing the in vitro and in vivo correlation between absorption, distribution, metabolism, and excretion/pharmacokinetic(ADME/PK) profiles of TCM and the molecular networks of disease by the integration of the knowledge of multi-disciplinary and multi-stages. In the present study, an internet-based Computation Platform for IP of TCM(TCM-IP, www.tcmip.

A Parameter Communication Optimization Strategy for Distributed Machine Learning in Sensors.

In order to utilize the distributed characteristic of sensors, distributed machine learning has become the mainstream approach, but the different computing capability of sensors and network delays greatly influence the accuracy and the convergence rate of the machine learning model. Our paper describes a reasonable parameter communication optimization strategy to balance the training overhead and the communication overhead. We extend the fault tolerance of iterative-convergent machine learning algorithms and propose the Dynamic Finite Fault Tolerance (DFFT).

Efficient Reconstruction of CAS-CI-Type Wave Functions for a DMRG State Using Quantum Information Theory and a Genetic Algorithm.

We improve the methodology to construct a complete active space-configuration interaction (CAS-CI) expansion for density-matrix renormalization group (DMRG) wave functions using a matrix-product state representation, inspired by the sampling-reconstructed CAS [SR-CAS; Boguslawski , K. ; J. Chem.

Land cover change during a period of extensive landscape restoration in Ningxia Hui Autonomous Region, China.

Environmental change has been a topic of great interest over the last century due to its potential impact on ecosystem services that are fundamental for sustainable development and human well-being. Here, we assess and quantify the spatial and temporal variation in land cover in Ningxia Hui Autonomous Region (NHAR), China. With high-resolution (30m) imagery from Landsat 4/5-TM and 8-OLI for the entire region, land cover maps of the region were created to explore local land cover changes in a spatially explicit way.

Effectively explore metastable states of proteins by adaptive nonequilibrium driving simulations.

Nonequilibrium drivings applied in molecular dynamics (MD) simulations can efficiently extend the visiting range of protein conformations, but might compel systems to go far away from equilibrium and thus mainly explore irrelevant conformations. Here we propose a general method, called adaptive nonequilibrium simulation (ANES), to automatically adjust the external driving on the fly, based on the feedback of the short-time average response of system. Thus, the ANES approximately keeps the local equilibrium but efficiently accelerates the global motion.

MetaSpark: a spark-based distributed processing tool to recruit metagenomic reads to reference genomes.

Summary: With the advent of next-generation sequencing, traditional bioinformatics tools are challenged by massive raw metagenomic datasets. One of the bottlenecks of metagenomic studies is lack of large-scale and cloud computing suitable data analysis tools. In this paper, we proposed a Spark based tool, called MetaSpark, to recruit metagenomic reads to reference genomes.

World data centre for microorganisms: an information infrastructure to explore and utilize preserved microbial strains worldwide.

The World Data Centre for Microorganisms (WDCM) was established 50 years ago as the data center of the World Federation for Culture Collections (WFCC)-Microbial Resource Center (MIRCEN). WDCM aims to provide integrated information services using big data technology for microbial resource centers and microbiologists all over the world. Here, we provide an overview of WDCM including all of its integrated services.

A Visual Analytics Approach for Station-Based Air Quality Data.

With the deployment of multi-modality and large-scale sensor networks for monitoring air quality, we are now able to collect large and multi-dimensional spatio-temporal datasets. For these sensed data, we present a comprehensive visual analysis approach for air quality analysis. This approach integrates several visual methods, such as map-based views, calendar views, and trends views, to assist the analysis.

Ultra-fast single-file transport of a simple liquid beyond the collective behavior zone.

We use molecular dynamics simulations to analyze the single-file transport behavior of a simple liquid through a narrow membrane channel. With the decrease of the liquid-channel interaction, the liquid flow exhibits a remarkable maximum behavior owing to the competition of liquid-liquid and liquid-channel interactions. Surprisingly, this maximum flow is coupled to a sudden reduce of the liquid occupancy, where the liquid particle is moving through the channel alone at nearly constant velocity, rather than in a collective motion mode.

Achievable rate maximization for decode-and-forward MIMO-OFDM networks with an energy harvesting relay.

This paper investigates the system achievable rate for the multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) system with an energy harvesting (EH) relay. Firstly we propose two protocols, time switching-based decode-and-forward relaying (TSDFR) and a flexible power splitting-based DF relaying (PSDFR) protocol by considering two practical receiver architectures, to enable the simultaneous information processing and energy harvesting at the relay. In PSDFR protocol, we introduce a temporal parameter to describe the time division pattern between the two phases which makes the protocol more flexible and general.

Scaled Particle Theory for Multicomponent Hard Sphere Fluids Confined in Random Porous Media.

The formulation of scaled particle theory (SPT) is presented for a quite general model of fluids confined in a random porous media, i.e., a multicomponent hard sphere (HS) fluid in a multicomponent hard sphere or a multicomponent overlapping hard sphere (OHS) matrix.

A new method for discovering behavior patterns among animal movements.

Advanced satellite tracking technologies enable biologists to track animal movements at fine spatial and temporal scales. The resultant data present opportunities and challenges for understanding animal behavioral mechanisms. In this paper, we develop a new method to elucidate animal movement patterns from tracking data.

Temperature dependence of the transport of single-file water molecules through a hydrophobic channel.

Although great effort has been made on the transport properties of water molecules through nanometer channels, our understanding on the effect of some basic parameters are still rather poor. In this article, we use molecular dynamics simulations to study the temperature effect on the transport of single-file water molecules through a hydrophobic channel. Of particular interest is that the water flow and average translocation time both exhibit exponential relations with the temperature.

A comparison of risk modeling tools and a case study for human health risk assessment of volatile organic compounds in contaminated groundwater.

In order to promote the risk-based strategy in the investigation, assessment, and remediation of Chinese brownfield sites, the Health and Environmental Risk Assessment (HERA) software was developed. It is vital to validate the HERA model and compare the inter-model differences of HERA model against other available risk assessment tools. This paper discusses the similarities and differences between the Risk-Based Corrective Action (RBCA) Tool Kit and the HERA model by evaluating the health risk of organic contaminated groundwater sources for a chemical works in China for the first time.

On the Origin of Water Flow through Carbon Nanotubes.

The transport of water molecules through carbon nanotubes (CNTs) is of primary importance for understanding water-mediated biological activities as well as for the design of novel nanoporous materials. Herein, we analyze the water flow through CNTs by using molecular dynamics simulations with the hope of finding basic parameters determining the flow value. Of particular interest is that a simple equation as a function of water diffusion, occupancy and CNT size, can well describe the water flow through CNTs with different sizes.

gPGA: GPU Accelerated Population Genetics Analyses.

Background: The isolation with migration (IM) model is important for studies in population genetics and phylogeography. IM program applies the IM model to genetic data drawn from a pair of closely related populations or species based on Markov chain Monte Carlo (MCMC) simulations of gene genealogies. But computational burden of IM program has placed limits on its application.