Multiobjective Transmission Network Planning considering the Uncertainty and Correlation of Wind Power

In order to consider the uncertainty and correlation of wind power in multiobjective transmission network expansion planning (TNEP), this paper presents an extended point-estimation method to calculate the probabilistic power flow, based on which the correlative power outputs of wind farm are sampled and the uncertain multiobjective transmission network planning model is transformed into a solvable deterministic model. A modified epsilon multiobjective evolutionary algorithm is used to solve the above model and a well-distributed Pareto front is achieved, and then the final planning scheme can be obtained from the set of nondominated solutions by a fuzzy satisfied method. The proposed method only needs the first four statistical moments and correlation coefficients of the output power of wind farms as input information; the modeling of wind power is more precise by considering the correlation between wind farms, and it can be easily combined with the multiobjective transmission network planning model. Besides, as the self-adaptive probabilities of crossover and mutation are adopted, the global search capabilities of the proposed algorithm can be significantly improved while the probability of being stuck in the local optimum is effectively reduced. The accuracy and efficiency of the proposed method are validated by IEEE 24 as well as a real system

Who is the main caregiver of the mother during the doing-the-month : is there an association with postpartum depression?

Background: To examine the relationship between the main caregiver during the “doing-the-month” (a traditional Chinese practice which a mother is confined at home for 1 month after giving birth) and the risk of postpartum depression (PPD) in postnatal women. Methods: Participants were postnatal women stayed in hospital and women who attended the hospital for postpartum examination, at 14–60 days after delivery from November 1, 2013 to December 30, 2013. Postpartum depression status was assessed using the Edinburgh Postnatal Depression Scale. Univariate and multivariable logistic regressions were used to identify the associations between the main caregiver during “doing-the-month” and the risk of PPD in postnatal women. Results: One thousand three hundred twenty-five postnatal women with a mean (SD) age of 28 (4.58) years were included in the analyses. The median score (IQR) of PPD was 6.0 (2, 10) and the prevalence of PPD was 27%. Of these postnatal women, 44.5% were cared by their mother-in-law in the first month after delivery, 36.3% cared by own mother, 11.1% by “yuesao” or “maternity matron” and 8.1% by other relatives. No association was found between the main caregivers and the risk of PPD after multiple adjustments. Conclusions: Although no association between the main caregivers and the risk of PPD during doing-the-month was identified, considering the increasing prevalence of PPD in Chinese women, and the contradictions between traditional culture and latest scientific evidence for some of the doing-the-month practices, public health interventions aim to increase the awareness of PPD among caregivers and family members are warranted

212962^{1296} Exponentially Complex Quantum Many-Body Simulation via Scalable Deep Learning Method

For decades, people are developing efficient numerical methods for solving the challenging quantum many-body problem, whose Hilbert space grows exponentially with the size of the problem. However, this journey is far from over, as previous methods all have serious limitations. The recently developed deep learning methods provide a very promising new route to solve the long-standing quantum many-body problems. We report that a deep learning based simulation protocol can achieve the solution with state-of-the-art precision in the Hilbert space as large as $2^{1296}$ for spin system and $3^{144}$ for fermion system , using a HPC-AI hybrid framework on the new Sunway supercomputer. With highly scalability up to 40 million heterogeneous cores, our applications have measured 94% weak scaling efficiency and 72% strong scaling efficiency. The accomplishment of this work opens the door to simulate spin models and Fermion models on unprecedented lattice size with extreme high precision.Comment: Massive ground state optimizations of CNN-based wave-functions for $J1$-$J2$ model and $t$-$J$ model carried out on a heterogeneous cores supercompute

Seasonal influenza vaccination in China:Landscape of diverse regional reimbursement policy, and budget impact analysis

BACKGROUND: To explore the current landscape of seasonal influenza vaccination across China, and estimate the budget of implementing a national "free-at-the-point-of-care" vaccination program for priority populations recommended by the World Health Organization. METHODS: In 2014 and 2016, we conducted a survey across provincial Centers for Disease Control and Prevention to collect information on regional reimbursement policies for influenza vaccination, estimated the national uptake using distributed doses of influenza vaccines, and evaluated the budget using population size and vaccine cost obtained from official websites and literatures. RESULTS: Regular reimbursement policies for influenza vaccination are available in 61 mutually exclusive regions, comprising 8 provinces, 45 prefectures, and 8 counties, which were reimbursed by the local Government Financial Department or Basic Social Medical Insurance (BSMI). Finance-reimbursed vaccination was offered mainly for the elderly, and school children for free in Beijing, Dongli district in Tianjin, Karamay, Shenzhen and Xinxiang cities. BSMI-reimbursement policies were limited to specific medical insurance beneficiaries with distinct differences in the reimbursement fractions. The average national vaccination coverage was just 1.5-2.2% between 2004 and 2014. A free national vaccination program for priority populations (n=416million), would cost government US$ 757million (95% CI 726-789) annually (uptake rate=20%). CONCLUSIONS: An increasing number of regional governments have begun to pay, partially or fully, for influenza vaccination for selected groups. However, this small-scale policy approach has failed to increase national uptake. A free, nationwide vaccination program would require a substantial annual investment. A cost-effectiveness analysis is needed to identify the most efficient methods to improve coverage

Modeling and Analysis of Wave Energy Harvester with Symmetrically Distributed Galfenol Cantilever Beams

In response to the challenges of difficult energy supply and high costs in ocean wireless sensor networks, as well as the limited working cycle of chemical batteries, a cylindrical wave energy harvester with symmetrically distributed multi-cantilever beams was designed with Galfenol sheet as the core component. The dynamic equation of the device was established, and ANSYS transient dynamic simulations and Jiles-Atherton hysteresis model analysis were conducted to develop a mathematical model of the induced electromotive force of the Galfenol cantilever beam as a function of deformation. Experimental validation demonstrated that the simulated results of the cantilever beam deformation had an average error of less than 7% compared to the experimental results, while the average error between the theoretical and experimental values of the induced electromotive force of the device was around 15%, which preliminarily verifies the validity of the mathematical model of the device, and should be subject to further research and improvement

Deep learning representations for quantum many-body systems on heterogeneous hardware

The quantum many-body problems are important for condensed matter physics, however solving the problems are challenging because the Hilbert space grows exponentially with the size of the problem. The recently developed deep learning methods provide a promising new route to solve long-standing quantum many-body problems. We report that a deep learning based simulation can achieve solutions with competitive precision for the spin $J1$ – $J2$ model and fermionic t - J model, on rectangular lattices within periodic boundary conditions. The optimizations of the deep neural networks are performed on the heterogeneous platforms, such as the new generation Sunway supercomputer and the multi graphical-processing-unit clusters. Both high scalability and high performance are achieved within an AI-HPC hybrid framework. The accomplishment of this work opens the door to simulate spin and fermionic lattice models with state-of-the-art lattice size and precision

Hepatic Transcriptome Analysis Provides New Insight into the Lipid-Reducing Effect of Dietary Taurine in High–Fat Fed Groupers (Epinephelus coioides)

A transcriptome analysis was conducted to provide the first detailed overview of dietary taurine intervention on liver lipid accumulation caused by high–fat in groupers. After an eight-week feeding, the fish fed 15% fat diet (High–fat diet) had higher liver lipid contents vs. fish fed 10% fat diet (Control diet). 15% fat diet with 1% taurine (Taurine diet) improved weight gain and feed utilization, and decreased hepatosomatic index and liver lipid contents vs. the High–fat diet. In the comparison of the Control vs. High–fat groups, a total of 160 differentially expressed genes (DEGs) were identified, of which up- and down-regulated genes were 72 and 88, respectively. There were 49 identified DEGs with 26 and 23 of up- and down-regulated in the comparison to High–fat vs. Taurine. Several key genes, such as cysteine dioxygenase (CDO1), ADP–ribosylation factor 1/2 (ARF1_2), sodium/potassium–transporting ATPase subunit alpha (ATP1A), carnitine/acylcarnitine translocase (CACT), and calcium/calmodulin–dependent protein kinase II (CAMK) were obtained by enrichment for the above DEGs. These genes were enriched in taurine and hypotaurine metabolism, bile secretion, insulin secretion, phospholipase D signaling pathway, and thermogenesis pathways, respectively. The present study will also provide a new insight into the nutritional physiological function of taurine in farmed fish

Immunogenicity and Blocking Efficacy of Norovirus GII.4 Recombinant P Protein Vaccine

Noroviruses (NoVs) are the main cause of acute gastroenteritis in all ages worldwide. The aim of this study was to produce the recombinant P protein of norovirus and to demonstrate its blocking effect. In this study, the engineered strains were induced to express the P protein of NoVs GII.4, which was identified using SDS-PAGE and ELISA as having the capacity to bind to histo-blood group antigens (HBGAs). Rabbits were immunized to obtain neutralizing antibodies. ELISA and ISC-RT-qPCR were used to determine the blocking efficacy of the neutralizing antibody to human norovirus (HuNoV) and murine norovirus (MNV). The recombinant P protein (35 KD) was obtained, and the neutralizing antibody was successfully prepared. The neutralizing antibody could block the binding of the P protein and HuNoV to HBGAs. Neutralizing antibodies can also block MNV invasion into host cells RAW264.7. The recombinant P protein expressed in E. coli can induce antibodies to block HuNoV and MNV. The recombinant P protein of NoVs GII.4 has the value of vaccine development

A scoring model predicts hepatitis B e antigen seroconversion in chronic hepatitis B patients treated with nucleos(t)ide analogs: real-world clinical practice

Aim: This study developed and validated a non-invasive scoring model to predict 1-year hepatitis B e antigen (HBeAg) seroconversion in response to nucleos(t)ide analog (NA) treatment in NA-naïve patients with HBeAg-positive chronic hepatitis B (CHB). Methods: Baseline data from 1014 patients visiting the outpatient and inpatient clinics of Beijing Ditan Hospital, Capital Medical University, China between October 2008 and April 2015 were included. These patients received NAs for HBeAg-positive CHB. The patients were assigned randomly to the derivation (n = 710) and validation (n = 304) cohorts in a 7:3 ratio. A prediction scoring model was established based on univariate and multivariate Cox proportional hazards regression analyses to identify independent prediction factors. In the derivation cohort, the odds ratio of the predictors were converted to integer risk scores by rounding the quotient from dividing the odds ratio, and the final score was the sum of these values. The predictive accuracy of the scoring model was further assessed using Harrell’s concordance index (C-index). Results: The 1-year cumulative HBeAg seroconversion rates were 11.83% and 8.55% in the derivation and validation cohorts, respectively. In the derivation cohort, baseline pretreatment alanine aminotransferase (ALT), gamma-glutamyl transpeptidase (GGT), globulin (GLO), and quantitative HBeAg (qHBeAg) levels were independently associated with HBeAg seroconversion and were included in the scoring system. The model had good discrimination in the derivation and validation cohorts (C-index = 0.750, 95% confidence interval 0.694–0.806 and C-index = 0.776, 95% confidence interval 0.698–0.855, respectively). The prediction scores ranged from 0 to 4; scores of 0–1 and 2–4 identified patients with lower and higher levels of HBeAg seroconversion, respectively. Kaplan–Meier analysis was used to determine the 1-year cumulative HBeAg seroconversion rates in the two groups (scores of 0–1 and 2–4) of the primary cohort, and log-rank tests revealed a significant difference (4.87% vs. 20.9%, p < 0.0001). Conclusions: The 1-year prediction scoring model based on baseline levels of ALT, GGT, GLO, and qHBeAg offered a reliable predictive value for the response to NA therapy in a Chinese cohort