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Abstract Maximum Entropy Method (MEM) is one of powerful tools for material science. We developed the program Z-MEM for evaluation of electron and nuclear density distribution by MEM analysis and Fourier synthesis. This code is designed by the multi-threading library OpenMP, so that the calculation performance is significantly improvements for MEM analysis. Z-MEM is bundled in Z-Rietveld , which is Rietveld software for X-ray and neutron powder diffraction, via the application programming interface (API). Since Z-MEM have equipped with the graphical user interface operations, users can perform from Rietveld refinement to MEM analysis seamlessly. [ABSTRACT FROM AUTHOR]

The scratch performance of semi-crystalline polymers is highly dependent on the crystalline morphology. To study the effect of thermal annealing on the scratch behavior of Polylactide (PLA), a series of scratch tests were conducted on multilayer assembled PLAs, which had been annealed for different time. It was found that greatly delayed critical damage including groove formation and ploughing was achieved, accompanied with obviously suppressed surface cracking and deformation following the increase of annealing time. The structural evolution during the annealing process was further investigated for better construction of structure-property relationship, which implied that the higher crystallinity and tensile strength originating from the perfection of crystalline morphology, played a significant role in restraining the surface deformation and cracking during the scratch process. [ABSTRACT FROM AUTHOR]

In the Three Gorges Reservoir area (TGRA), landslides typically exhibit slow-moving characteristic deformations in response to seasonal changes in precipitation and reservoir level. This study proposed an optimal combination of methods in which the frequency components of decomposed inducing factors are considered for predicting landslide displacement. In preprocessing, the monitored surface displacements are decomposed into trend displacement and periodic displacement components via ensemble empirical mode decomposition (EEMD); the time series of the inducing factors (rainfall and reservoir level) were reconstructed and decomposed into high- and low-frequency time series via complete ensemble empirical mode decomposition (CEEMD) and t -test methods, among which two dominant inducing factors are identified by analyzing the longest common subsequence (LCSS) distance of the normalized data. In the prediction of the periodic displacement component, three optimal methods that use the support vector regression (SVR) model have been considered for comparison: the artificial bee colony (ABC) algorithm, the genetic algorithm (GA) and particle swarm optimization (PSO). The results demonstrate that the combination of CEEMD-LCSS reconstruction and ABC-SVR yields a robust model with remarkable prediction performance, which can increase the prediction accuracy of landslide displacements by 54% at most in the evaluation of RMSE. [ABSTRACT FROM AUTHOR]

[Display omitted] • A novel nanopeptide is self-assembled from maize tetrapeptide anchored AuNPs. • Nanopeptide has a neuroprotective effect on l -glutamate-induced extracellular model. • Nanopeptides have therapeutic effects on murine Alzheimer's disease models. • Nanopeptides may reduce model injury through the Nrf2/Keap1 signaling pathway. Nanopeptide assembled from peptide-anchored nanoparticles possess an enormous research potential in the field of cellular medicine and disease treatment. The aim of this study was to explore the neuroprotective effects of maize tetrapeptide anchored gold nanoparticles against l -glutamic acid-induced PC12 cell apoptosis and a murine Alzheimer's disease model induced by aluminum chloride and d -galactose. The results revealed that the nanopeptide antioxidant inhibited intracellular ROS accumulation and promoted cell differentiation than that of maize bioactive tetrapeptide. Compared with untreated Alzheimer's disease model mice, nanopeptide administration shortened the escape latency time in a water maze test and improved the movements in the autonomic activity test. After 16 days of nanopeptide administration, the central cholinergic system function of acetylcholine and cholineacetyltransferase were enhanced, and the level of acetylcholinesterase was reduced. It also increased superoxide dismutase and glutathione peroxidase activity in sera and hypothalami. Moreover, nanopeptide treatment upregulated cerebral nuclear factor erythroid 2-related factor 2 and heme-oxygenase-1 and downregulated kelch-like ECH-associated protein 1 relative to untreated Alzheimer's disease model mice. Thus, the novel nanopeptide is expected to be used as the neuroprotective agent to prevent Alzheimer's disease. [ABSTRACT FROM AUTHOR]

[Display omitted] The timely suppression of inflammatory mediator production and mitigation of their effects on pancreatic acinar cells are crucial for the successful management of acute pancreatitis. To achieve effective treatment, we present a novel approach utilizing cysteine modified PEG nanoparticles for both precise accumulation at the site of pancreatitis and specific targeting of acinar cells. Methylprednisolone, a nonsteroidal anti-inflammatory drug, was tailored to enhance its circulation time in the bloodstream, preferentially accumulate in the pancreas and enhance cell uptake efficiency by acinar cells through specifically targeting L-Type amino acid transporter 1. The nanosystem significantly downregulated pro-inflammatory cytokines in plasma, resulting in the effective suppression of inflammation in acinar cells within an acute pancreatitis rat model. The utilization of the dual targeted therapy strategy holds considerable potential for the clinical management of pancreatitis. [ABSTRACT FROM AUTHOR]

The rice heading stage is an essential phase of rice production as it directly affects the rice yield. This paper transforms the issue of rice heading stage automatic observation into the problem of rice spike detection and proposes a new method for automatic observation of the rice heading stage. Rice spike detection is achieved using a new multi-classifier cascade method comprised of the following steps: First, SVM with color feature as input is utilized to distinguish the rice spike image patches from the background patches (leaf, soil, water, etc.); Second, a gradient histogram method is applied to remove the yellow leaf patches from consideration; Third, a convolutional neural network (CNN) is utilized to further reduce the false positive rate. The arrival of the rice heading stage is determined by the number of the detected spike patches. To evaluate the proposed method, it was applied to the automatic rice heading stage observation of six image sequences collected by the designed observation device between 2011 and 2013. In the experiment, the proposed method produced similar results to the conventional manual observation method in determining the arrival of the rice heading stage. The differences between the proposed method and manual way were within two days. Experiments demonstrated that the proposed method is an effective approach of automatic observation of the rice heading stage in paddy fields and can be utilized to replace the manual observation. [ABSTRACT FROM AUTHOR]

Legionella pneumophila is the main causative agent of Legionnaires' disease, which is a severe multi-system disease with pneumonia as the primary manifestation. We designed a recombinant Mip-PilE-FlaA dominant epitopes vaccine against Legionella pneumophila to prevent the disease and evaluated its immunogenicity and protective immunity. The protein structures of Mip, PilE and FlaA were analyzed using a computer, and the gene sequences of the dominant epitopes of the three proteins were selected to construct and optimize the vaccine. The optimized mip , pilE , flaA and recombinant mip-pilE-flaA gene sequences were cloned, expressed and purified. The purified proteins were used as dominant epitopes vaccines to immunize BALB/c mice and determine the protective immunity and immunogenicity of these purified proteins. The identification confirmed that the recombinant mip-pilE-flaA was successfully cloned and expressed. ELISA revealed that the Mip-PilE-FlaA group produced the highest IgG response, and this protein may considerably improve the production of some cytokines in BALB/c mice. Histopathology analyses of lungs from mice immunized with Mip-PilE-FlaA revealed a certain protective effect. Our work demonstrated that the recombinant dominant epitopes of Mip-PilE-FlaA exhibited strong immunogenicity and immune protection, and this protein may be an efficient epitopes vaccine candidate against Legionella pneumophila. [ABSTRACT FROM AUTHOR]

Background The sensitivity and specificity of noninvasive prenatal testing (NIPT) for detection of sex chromosome aneuploidies (SCAs) compared to common autosomal trisomies are significantly lower. We speculated that in addition to altered maternal X chromosome karyotype, maternal X chromosome copy number variations (CNVs) may also contribute to discordant NIPT SCA results. Methods Clinical NIPT was performed for pregnant women at a single hospital. Copy number variation sequencing (CNV-Seq) was used to identify and quantitate the copy number of maternal X chromosome CNVs for each positive SCA pregnancy. Results Two out of 25 SCA positive NIPT samples had slightly abnormal ChrX/ChrY z-scores and were referred for invasive test confirmation. However, fetal karyotypes were found to be normal. CNV-Seq analysis of the maternal white blood cell DNA archived from the original two NIPT blood samples identified small CNVs spanning the STS gene, which is associated with X-linked ichthyosis. Correcting for the altered plasma levels of X chromosome DNA caused by the two CNVs and, taking into consideration the phenotypic consequences for X-linked disease, both fetuses were diagnosed as normal. Conclusions Maternal DNA sequencing is recommended for all positive NIPT SCA results to avoid unnecessary referral for invasive testing and also to evaluate the risk to the fetus of X-linked disease. [ABSTRACT FROM AUTHOR]

This paper compares the performance of five popular machine learning methods, namely, particle swarm optimization–extreme learning machine (PSO–ELM), particle swarm optimization–kernel extreme learning machine (PSO–KELM), particle swarm optimization–support vector machine (PSO–SVM), particle swarm optimization–least squares support vector machine (PSO–LSSVM), and long short-term memory neural network (LSTM), in the prediction of reservoir landslide displacement. The Baishuihe, Shuping, and Baijiabao landslides in the Three Gorges reservoir area of China were used for case studies. Cumulative displacement was decomposed into trend displacement and periodic displacement by the Hodrick–Prescott filter. The double exponential smoothing method and the five machine learning methods were used to predict the trend and periodic displacement, respectively. The five machine learning methods are compared in three aspects: highest single prediction accuracy, mean prediction accuracy, and prediction stability. The results show that no method performed the best for all three aspects in the three landslide cases. LSTM and PSO–ELM achieved better single prediction accuracy, but worse mean prediction accuracy and stability. PSO–KELM, PSO–LSSVM, and PSO–SVM always yielded consistent predictions with slight variations. On the whole, PSO–KELM and PSO–LSSVM are recommended for their superior mean prediction accuracy and prediction stability. • The performances of machine learning methods depend on the selected evaluation index and reservoir landslide case. • Using single prediction accuracy for evaluating the superiority of machine learning methods may be unreliable. • PSO-KELM and PSO-LSSVM are recommended for their superior mean prediction accuracy and prediction stability. [ABSTRACT FROM AUTHOR]

Abstract: Oxide ion conduction and phase transition phenomena have been investigated on La2−xPbxMo2O9−x/2 solid solutions (x≤0.6). X-ray and neutron diffraction experiments as well as thermal analyses indicate that a single phase of high-temperature polymorph (β-phase) is preserved down to room temperature for the composition of x≥0.06. In the solid solution range, ionic conductivity gradually decreases with Pb-substitution. Such phase transition and ionic conduction properties of La2−xPbxMo2O9−x/2 are quite similar to the Bi-substituted system, La2−xBixMo2O9, although ionic conductivity at lower temperatures is slightly higher in the former system than the latter with the same-amount of substitution. Room temperature neutron diffraction experiment suggests that oxide-ion deficiency is introduced mainly into O2 site by the charge compensation with Pb-substitution, which would contribute to a little enhancement in conductivity compared with Bi-substituted samples along with the variation of nearest O2 O3 bond length. [Copyright &y& Elsevier]

Abstract: The phase relationship of the TbO1.81–Mn3O4–Fe2O3 pseudo-ternary system synthesized at 1200°C was determined using X-ray and neutron diffraction method. Four solid solutions, Mn3−3 x Fe3 x O4 (0.00⩽ x ⩽0.278), Mn3−3 x Fe3 x O4 (0.291⩽ x ⩽0.667), Mn2−2 x Fe2 x O3 (0.89⩽ x ⩽1.00), and (Tb1− y Mn z Fe x )(Fe w Mn1− w )O3 (1−y + x + z ⩽1, 0.00⩽ w ⩽1.00) were found along with six two-phase regions and three three-phase regions. The boundaries were determined by several different methods such as phase disappearing, the Vigard’s law, and the lever rule. [Copyright &y& Elsevier]

The search for new materials that could improve the energy density of Li-ion batteries (LIB) is one of today's most challenging issues. Recently, cation-disordered lithium-excess metal oxides have emerged as a promising new class of cathode materials for LIB, due to their high reversible capacities and nice structural stability. However, a full structural model of the Li-transition metal (TM) sharing sublattice and the origin of short range ordering (SRO) of cations requires further investigation. In this work, we put forward a Monte Carlo strategy of building cation-disordered rocksalt material supercell models. The cations of Li 1.0 Ti 0.5 Ni 0.5 O 2 (LTNO) are placed at the FCC sublattice sites with the constraint of Pauling's electroneutrality rule, instead of a random way. This constraint causes the Li-Ti and Ni-Ni clustering. Based on this model, we discussed the relationship between the SRO, the local distorting, the theoretical capacity and the order-disorder strengths. A unified understanding of these factors in cation-disordered materials may enable a better design of disordered-electrode materials with high capacity and high energy density. • In this work, we described a Monte Carlo strategy to build the model of cation-disordered material Li 1.0 Ti 0.5 Ni 0.5 O 2. The cations are distributed at the FCC sublattice with a constraint of Pauling's electroneutrality rule, instead of a random way. The model is relaxed by an atomistic force field to get into the thermal equilibrium. • We conclude that the electroneutrality causes the short-range ordering (SRO) in the cation sublattice and results the Li-Ti and Ni-Ni clustering. • The SRO is favoured by the lattice completeness and lower the local distortion of the cations. But it also decreases the content of 0-TM channels and the capacities of the materials. So we can expect for a more 'disordered' material with larger capacity. The energy calculation shows that this can be done by sintering the materials at higher temperatures which has been proved by several experiments. [ABSTRACT FROM AUTHOR]

Assessing the influence of the impact pressure exerted on surrounding rock mass by potential debris flows is one of the challenges in a mountain tunnel construction project. This paper proposes an effective mathematical model for the assessment of impact pressure exerted by debris flows on obstacles. The characteristics of the new model are analyzed, and the parameters determination method for the new model are deduced. Also, a new method for dynamic reliability analysis of the rock mass surrounding tunnels is proposed and is constituted into three key steps. First, by inputting impact pressure of debris flows generated by the aforementioned new model, the FLAC3D is used as the dynamic analysis engine to obtain the time-varying stress distribution of surrounding rock mass during the impact of debris flow. Second, the factor of safety (FOS) contours of surrounding rock mass are generated based on element states using the maximum tensile stress criterion and the Mohr-Coulomb yield criterion. Third, by using the time-varying contours of the FOS, a failure probability and a reliability index are obtained from a reliability perspective. A case study shows the complete analysis process and confirms the effectiveness of the above methodology. In sum, this paper provides new ideas, new methods, and a reference example for evaluating the influence of dynamic impact exerted by debris flows on the rock mass surrounding tunnels. • A novel mathematical model is proposed for the assessment of impact pressure exerted by debris flows on obstacles. • A new method is proposed for dynamic reliability analysis of the rock mass surrounding tunnels. • The instantaneous factor of safety (FOS) of each element of the rock mass surrounding tunnels is applied based on the maximum tensile stress criterion and the Mohr-Coulomb yield criterion. • The failure probability and the reliability index of the rock mass surrounding tunnels are obtained based on space-time-varied stress fields. [ABSTRACT FROM AUTHOR]

Here, we propose a new two-dimensional (2D) monolayer YS 2 and investigate its properties as electrode material for Li-ion and Na-ion batteries (LIBs and NIBs), by combining the density functional theory (DFT) and the crystal structure prediction techniques. The results of phonon dispersion and ab-initio molecular dynamics (AIMD) simulations confirm that it is dynamically and thermally stable. The adsorption energies of Li and Na on YS 2 are −2.038 and −1.939 eV, respectively. Besides, the superior electrical conductivity is maintained during the whole lithiation/sodiumation process. The calculated diffusion energy barriers for Li and Na on this YS 2 monolayer are 0.33 and 0.24 eV, respectively, demonstrating a fast ion transfer rate. The theoretical specific capacities for Li and Na adatoms on YS 2 are both 350 mA h g−1, comparable to the graphite electrode. These features indicate that 2D YS 2 monolayer could be considered as a promising electrode material for both LIBs and NIBs. Unlabelled Image • We predicted a new 2D transition metal disulfide (TMD), namely, YS 2 monolayer. • The YS 2 keeps metallic during the whole lithiation/sodiumation process. • The diffusion barrier of Li-ion (Na-ion) for YS 2 is 0.33 (0.24) eV. • The theoretical specific capacities for Li and Na atoms on YS 2 are both 350 mA h g−1. [ABSTRACT FROM AUTHOR]