Search

Investigating the global time-varying gravity field mainly depends on GRACE/GRACE-FO gravity data. However, satellite gravity data exhibit low spatial resolution and signal distortion. Satellite altimetry is an important technique for observing the global ocean and provides many consecutive years of data, which enables the study of high-resolution marine gravity variations. This study aims to construct a high-resolution marine gravity change rate (MGCR) model using multi-satellite altimetry data. Initially, multi-satellite altimetry data and ocean temperature–salinity data from 1993 to 2019 are utilized to estimate the altimetry sea level change rate (SLCR) and steric SLCR, respectively. Subsequently, the mass-term SLCR is calculated. Finally, based on the mass-term SLCR, the global MGCR model on 5′ × 5′ grids (SDUST2020MGCR) is constructed by applying the spherical harmonic function method and mass load theory. Comparisons and analyses are conducted between SDUST2020MGCR and GRACE2020MGCR resolved from GRACE/GRACE-FO gravity data. The spatial distribution characteristics of SDUST2020MGCR and GRACE2020MGCR are similar in the sea areas where gravity changes significantly, such as the eastern seas of Japan, the western seas of the Nicobar Islands, and the southern seas of Greenland. The statistical mean values of SDUST2020MGCR and GRACE2020MGCR in global and local oceans are all positive, indicating that MGCR is rising. Nonetheless, differences in spatial distribution and statistical results exist between SDUST2020MGCR and GRACE2020MGCR, primarily attributable to spatial resolution disparities among altimetry data, ocean temperature–salinity data, and GRACE/GRACE-FO data. Compared with GRACE2020MGCR, SDUST2020MGCR has higher spatial resolution and excludes stripe noise and leakage errors. The high-resolution MGCR model constructed using altimetry data can reflect the long-term marine gravity change in more detail, which is helpful in studying seawater mass migration and its associated geophysical processes. The SDUST2020MGCR model data are available at https://doi.org/10.5281/zenodo.10701641 (Zhu et al., 2024).

Climate field reconstruction (CFR) refers to the estimation of spatiotemporal climate fields (such as surface temperature) from a collection of pointwise paleoclimate proxy datasets. Such reconstructions can provide rich information on climate dynamics and provide an out-of-sample validation of climate models. However, most CFR workflows are complex and time-consuming, as they involve (i) preprocessing of the proxy records, climate model simulations, and instrumental observations; (ii) application of one or more statistical methods; and (iii) analysis and visualization of the reconstruction results. Historically, this process has lacked transparency and accessibility, limiting reproducibility and experimentation by non-specialists. This article presents an open-source and object-oriented Python package called cfr that aims to make CFR workflows easy to understand and conduct, saving climatologists from technical details and facilitating efficient and reproducible research. cfr provides user-friendly utilities for common CFR tasks such as proxy and climate data analysis and visualization, proxy system modeling, and modularized workflows for multiple reconstruction methods, enabling methodological intercomparisons within the same framework. The package is supported with extensive documentation of the application programming interface (API) and a growing number of tutorial notebooks illustrating its usage. As an example, we present two cfr-driven reconstruction experiments using the PAGES 2k temperature database applying the last millennium reanalysis (LMR) paleoclimate data assimilation (PDA) framework and the graphical expectation–maximization (GraphEM) algorithm, respectively.

Compressed Sensing (CS) has been shown to be an effective technique for improving the resolution of inverse synthetic aperture radar (ISAR) imaging and reducing the hardware requirements of radar systems. In this paper, our focus is on the l_p 0 p 1 model, which is a well-known non-convex and non-Lipschitz regularization model in the field of compressed sensing. In this study, we propose a novel algorithm, namely the Accelerated Iterative Support Shrinking with Full Linearization (AISSFL) algorithm, which aims to solve the l_p regularization model for ISAR imaging. The AISSFL algorithm draws inspiration from the Majorization-Minimization (MM) iteration algorithm and integrates the principles of support shrinkage and Nestrove's acceleration technique. The algorithm employed in this study demonstrates simplicity and efficiency. Numerical experiments demonstrate that AISSFL performs well in the field of ISAR imaging.

Integration of information from multi-sensor can provide navigation systems with reliable estimates of their own states, which overcomes shortage of standalone sensors. State estimation approaches, which can be categorized into filtering-based and optimization-based methods, provide the means to fuse information from various sensors with different principles to estimate the system's position, orientation, and other navigation parameters accurately. Recent researches have shown that optimization-based frameworks outperform filtering-based ones in terms of accuracy. However, both methods are based on maximum likelihood estimation (MLE) and, assuming Gaussian noise, should be theoretically equivalent. In this paper, we comprehensively and theoretically analyse the differences between the two methods, including algorithms and strategies. Our simulated experiments based on visual odometry (VO) indicate that filtering-based approaches are equal to optimization-based ones in accuracy when employing the same strategies and under the premise of the same measurements and observation model. Therefore, future research on sensor-fusion navigation problems should concentrate on strategies rather than state estimation methods.

Global navigation satellite system (GNSS) can provide global, precise, and continuous positioning in open-sky environments. However, urban environments with frequent outliers and cycle slips degrade the traditional Extended Kalman Filter (EKF) positioning performance. The susceptibility of EKF to outliers is attributed to its inherent structure. To mitigate, the GNSS positioning based on the Factor Graph Optimization (FGO) structure is adopted. FGO can enhance time correlation among observations and enable the updating of historical information, thereby improving resistance against outliers. In this study, we proposed a single-differenced GNSS-FGO model instead of the double-differenced model to preserve the sparsity of FGO, and outlier detection and PAR methods are employed to ensure urban positioning performance. To evaluate the proposed structure, experiments are conducted in both urban and open-sky environments. The results demonstrate the improvement of positioning accuracy and reliability, compared to EKF.

Reanalysis data play a vital role in weather and climate study as well as meteorological resource development and application. In this work, the East Asia Reanalysis System (EARS) was developed using the Weather Research and Forecasting (WRF) model and the Gridpoint Statistical Interpolations (GSI) data assimilation system. The regional reanalysis system is forced by the European Centre for Medium-Range Weather Forecasts (ECMWF) global reanalysis ERA-Interim data at 6 h intervals. Hourly surface observations are assimilated by the Four-Dimension Data Assimilation (FDDA) scheme during the WRF model integration; upper observations are assimilated in three-dimensional variational data assimilation (3D-VAR) mode at the analysis moment. It should be highlighted that many of the assimilated observations have not been used in other reanalysis systems. The reanalysis runs from 1980 to 2018, producing a regional reanalysis dataset covering East Asia and surrounding areas at 12 km horizontal resolution, 74 sigma levels, and 3 h intervals. Finally, an evaluation of EARS has been performed with respect to the root mean square error (RMSE), based on the 10-year (2008–2017) observational data. Compared to the global reanalysis data of ERA-Interim, the regional reanalysis data of EARS are closer to the observations in terms of RMSE in both surface and upper-level fields. The present study provides evidence for substantial improvements seen in EARS compared to the ERA-Interim reanalysis fields over East Asia. The study also demonstrates the potential use of the EARS data for applications over East Asia and proposes further plans to provide the latest reanalysis in real-time operation mode. Simple data and updated information are available on Zenodo at https://doi.org/10.5281/zenodo.7404918 (Yin et al., 2022), and the full datasets are publicly accessible on the Data-as-a-Service platform of the China Meteorological Administration (CMA) at http://data.cma.cn (last access: 19 May 2023).

The estimation of daily variations in aerosol concentrations using meteorological data is meaningful and challenging, given the need for accurate air quality forecasts and assessments. In this study, a 3×50-layer spatiotemporal deep learning (DL) model is proposed to link synoptic variations in aerosol concentrations and meteorology, thereby building a “deep” Weather Index for Aerosols (deepWIA). The model was trained and validated using 7 years of data and tested in January–April 2022. The index successfully reproduced the variation in daily PM2.5 observations in China. The coefficient of determination between PM2.5 concentrations calculated from the index and observation was 0.72, with a root mean square error (RMSE) of 16.5 µg m−3. The DeepWIA performed better than Weather Forecast and Research (WRF)-Chem simulations for eight aerosol-polluted cities in China. The simulating power of the model also outperformed commonly used PM2.5 concentration retrieval models based on random forest (RF), extreme gradient boost (XGB), and multilayer perceptron (MLP). The index and the DL model can be used as robust tools for estimating daily variations in aerosol concentrations.

Electrochemical ozone production (EOP) is an attractive technology for disinfection and sterilization purposes. This work reports a study on the EOP performance of the solid polymer electrolyte (SPE) electrolyzer, including the optimization of electrode configuration and operation conditions. It is proven that the EOP performance is highly affected by electrode configuration. Tests using BDDs with different B/C ratios demonstrate that BDD-4.9 provides more reaction sites and faster electron transfer rate, exhibiting a high electrocatalytic activity for EOP. Regarding electrode thickness, 0.54 mm in thickness is the most suitable for the EOP from the perspective of less power consumption. Moreover, operation conditions were evaluated. It was found that increasing water flow rate is an effective strategy for promoting ozone dissolution, and within the present experimental range, the water flow rate of 63 L·h−1 was identified. Meanwhile, through the study of all processes occurring inside the electrolyzer at higher current densities, the optimum current density was determined to be 125 mA·cm−2. Based on these results, ozone water presents excellent performance in the killing of Escherichia coli with high inoculum concentrations, indicating potential application performance in the field of environment. HIGHLIGHTS Ozone production by electrochemical technology.; The SPE electrolyzer with specially designed clamping system served as the ozone reactor.; Using a boron-doped diamond (BDD) as the electrode material.; The SPE electrolyzer can continuously and effectively produce ozone by a flow-through system with low energy consumption.; Ozone water shows a considerable bactericidal effect on different concentrations of E. coli.;

Abstract Background Metabolic syndrome (MetS) is a complex of interrelated risk factors, including central adiposity, increased blood pressure, hyperglycemia, elevated triglyceride levels and low high-density lipoprotein. Few studies have reported the genetic variants in the Sirt1 and Nrf2 genes (Sirt1 rs7895833 A > G, Sirt1 rs2273773 C > T and Nrf2 rs6721961 C > A) that increase the risk of type 2 diabetes mellitus and are correlated with some glycemic and metabolic traits in the Chinese Han population. Methods Our study recruited 141 individuals with MetS and 549 individuals without MetS to investigate the associations between three single nucleotide polymorphisms (SNPs) of Sirt1 and Nrf2 and the risk of MetS in a Chinese Han population using the PCR-CTPP method. Results This research showed that the risk of MetS was 2.41 times higher for the AA genotype (P = 0.038) and 1.94 times higher for the AG genotype (P = 0.016) compared with carriers of the GG genotype. The serum levels of low-density lipoprotein cholesterol and HOMA-IR were significantly higher (P

Manganese (Mn) excess is a major abiotic stress for plant growth. In the present study, we investigated the effects of Mn on photosynthesis in Ligustrum lucidum and Melia azedarach leaves using chlorophyll fluorescence transients. Both plant species were exposed to two Mn concentrations (0.5 and 1 mmol) for 10 and 30 d. Results showed that excess Mn significantly inhibited photosynthesis. With the increase of Mn concentration and stress time, the inhibition was more serious. Mn stress impaired PSII at the donor and the acceptor side by damaging the oxygen-evolving complex and limiting electron transport downstream of QA in both trees. A significant decline in 820 nm reflection curve absorption was observed in M. azedarach, suggesting that the oxidization-reduction reactions in PSI were inhibited but this phenomenon was not observed in L. lucidum. Therefore, excess Mn impaired the whole electron transport chain associated with inactive PSII reaction centers in Ligustrum lucidum and inhibited oxidization-reduction reactions in PSI in M. azedarach.

Abstract The hybrid phased multiple‐input‐multiple‐output (MIMO) radar with subarray partition can provide the transmit coherent gain of phased array and the waveform diversity of MIMO radar. The current researches mainly focus on the different subarray partition schemes of the transmit array. In this letter, a full phased‐MIMO (FPMIMO) radar with equally overlapped subarrays is introduced, and a robust adaptive transmit/receive beamforming algorithm is proposed based on the virtual interference‐plus‐noise covariance matrix (INCM) reconstruction and the virtual steering vector estimation. In the FPMIMO radar, the conventional beamforming is used for the signal transmission and reception on each subarray, and all subarrays can be assumed as a uniform linear array. Based on the presumed uniform linear array, the virtual INCM can be reconstructed by Eigen‐decomposition of the reconstructed INCM, and the virtual steering vector can be obtained by the estimated steering vector. With fewer antenna elements and sampling channels in the FPMIMO radar, simulation results demonstrate better performance of the proposed algorithm in a wide range of input signal‐to‐noise ratio.

Data clustering is the process of identifying natural groupings or clusters based on a certain similarity measure in muti-dimensional data. Aiming at the dynamic clustering problem where the number of clusters cannot be determined in advance, a hybrid dynamic clustering method based on the marine predators algorithm (MPA) and particle swarm optimization (PSO) algorithm was proposed. The position update strategy of the PSO algorithm was used to make up for the lack of MPA in global searching. The fixed-length coding strategy with the real number coding method was used to deal with the variable length clustering optimization problem, and the unfeasible solution processing strategy and the penalty function strategy are adopted to improve the performance of the algorithm and achieve simultaneous optimization of the number of clusters and cluster centers. The proposed MPA-PSO algorithm with PSO algorithm, MPA, Differential Evolution (DE) algorithm, Spotted Hyena Optimizer (SHO), Lightning Searching Algorithm (LSA) and Equilibrium Optimizer (EO) are adopted to carry out the clustering simulation experiments on four artificial data sets and six real data sets (Iris, Wine, Wisconsin breast cancer, Vowel, Seeds, and Wdbc) in UCI databases. Three performance indicators (the number of clusters, ARI and Accuracy) are used to evaluate the clustering results. The experimental results show that the proposed method can not only successfully find the correct number of clusters, but also obtain stable results for most test problems.

Abstract Background While the physical and chemical properties of airborne particulate matter (PM) have been extensively studied, their associated microbiome remains largely unexplored. Here, we performed a longitudinal metagenomic survey of 106 samples of airborne PM2.5 and PM10 in Beijing over a period of 6 months in 2012 and 2013, including those from several historically severe smog events. Results We observed that the microbiome composition and functional potential were conserved between PM2.5 and PM10, although considerable temporal variations existed. Among the airborne microorganisms, Propionibacterium acnes, Escherichia coli, Acinetobacter lwoffii, Lactobacillus amylovorus, and Lactobacillus reuteri dominated, along with several viral species. We further identified an extensive repertoire of genes involved in antibiotic resistance and detoxification, including transporters, transpeptidases, and thioredoxins. Sample stratification based on Air Quality Index (AQI) demonstrated that many microbial species, including those associated with human, dog, and mouse feces, exhibit AQI-dependent incidence dynamics. The phylogenetic and functional diversity of air microbiome is comparable to those of soil and water environments, as its composition likely derives from a wide variety of sources. Conclusions Airborne particulate matter accommodates rich and dynamic microbial communities, including a range of microbial elements that are associated with potential health consequences.

Salicylic acid (SA) is an important plant hormone involved in the activation of defense responses against environmental stresses. However, there are still large of unsolved mysteries about how SA pretreatment affects the establishment of plant stress tolerance. In this study, application of SA at different concentrations and different times were conducted to investigate their effects on the response of Arabidopsis seedlings to salt stress. The pretreatment with 10 or 20 μM SA for more than 6 h promoted Arabidopsis seedlings resistance to salt stress. On the other hand, pretreatment with 200 μM SA reduced Arabidopsis resistance to salt stress and aggravated oxidative damage to the seedlings. At all concentrations used, SA pretreatment inhibited the total respiration and promoted reactive oxygen species (ROS) generation. However, the ROS content in 10 or 20 μM SA pretreated seedlings decreased to the basal level within 6 h and high activities of antioxidant enzymes and alternative oxidase were maintained. Notably, the SA-enhanced salt stress resistance was significantly impaired by blocking alternative oxidase (AOX) pathway. Our findings indicate that SA-mediated salt stress response is in a dose- and time-dependent manner and that the effects were related to the induction of AOX capacity and antioxidant system.

Using the GPS data service platform of China seismological bureau to get the ZTD separated ZWD data pair and the content in the air, and by detecting the O3 value in the air is an effective method to analyze and study the thunderstorm weather.This paper collected the four foundations of the beibu gulf region GPS station in 10 days in August 2019 data, through ZWD numerical and O3 values after consolidation, the classification of the training and testing, in XGboost algorithm, manual adjustment method is compared with grid search method, and the results show that the model of manual adjustment method is superior to grid search model and the default model in accuracy and AUC value.

Ant Lion Optimizer (ALO) is a new meta-heuristic algorithm that simulates the ant lion predator mechanism in nature. Five main steps of hunting include: random walks of ants, building traps, trapping in antlion's pits, sliding ants towards antlion, catching prey and re-building pits. As the predator radius of antlion decreases with the number of iterations, there is an unbalanced between the ant lion optimizer between exploration and exploitation, and it is easy to fall into the local optimal solution. An improved ant lion optimizer based on spiral complex path searching pattern is proposed, where eight spiral paths (Hypotrochoid, Rose spiral curve, Logarithmic spiral curve, Archimedes spiral curve, Epitrochoid, Inverse spiral curve, Cycloid, Overshoot parameter setting of the spiral) searching strategies were adopted to improve the diversity of the population and the ability of the algorithm to balance exploration and exploitation. The proposed algorithm can accelerate the convergence speed of ALO and improve its performance. The algorithm is verified by simulation experiments in three parts. Firstly, 28 function optimization problems were adopted to test the optimization performance of the improved ALO. Secondly, it is applied to the lightest design engineering problem of pressure vessels. Finally, the spiral complex path searching patterns are introduced into the muti-objective ALO and 4 typical muti-objective functions are optimized. Simulation results show that the superior performance of the proposed algorithm for exploiting the optimum and it has advantages in terms of exploration. The improved algorithm can better solve function optimization, classical engineering problems with constraints and multi-objective function optimization problems. The improved ALO based on the spiral complex path searching mode has the characteristics of balanced exploration and exploitation, fast convergence speed and high precision.

The grasshopper optimization algorithm (GOA) is a new meta-heuristic algorithm inspired by the behavior of grasshopper groups. Aiming at the shortcomings of poor development ability and low convergence accuracy of GOA, this paper introduces the gravity search operator into the optimization process of GOA to improve the grasshopper's global exploration and avoid falling into local optimum in advance. At the same time, a pigeon search operator-landmark operator is introduced to improve and balance the algorithm's exploration and development capabilities. In order to verify the validity of the improved algorithm, this paper will adopts the gravity search operator and a deterrent landmark operator hybrid grasshoppers algorithm (HGOA) with basic grasshopper algorithm (GOA), particle swarm optimization (PSO) algorithm, sine and cosine algorithm (SCA), moth-flame optimization (MFO) algorithm, salp swarm algorithm (SSA), and bat algorithm (BA) to optimize 28 test functions. And the analysis and comparison of the obtained statistical data results finally show that the proposed improved grasshopper algorithm has better optimization ability.

Grey wolf optimizer (GWO) is a new meta-heuristic algorithm. The GWO algorithm mimics the leadership hierarchy and hunting mechanism of grey wolves in nature. Three main stages of hunting include: encircling, tracking and attacking. It is easy to fall into local optimum when used to optimize high-dimensional data, and there is imbalance between exploration and exploitation. An improved grey wolf optimizer based on tracking mode and seeking mode is proposed to improve the diversity of the population and the ability of the algorithm to balance exploration and exploitation. The algorithm is verified by simulation experiments in three parts. Firstly, the proposed grey wolf optimizer based on tracking mode (TGWO), the improved grey wolf optimizer based on seeking mode (SGWO), the improved grey wolf optimizer based on tracking and seeking mode (TSGWO), Grey Wolf Optimizer (GWO), Particle Swarm Optimization (PSO), Salp Swarm Algorithm (SSA), Sine Cosine Algorithm (SCA), Ant Lion Optimizer (ALO), Whale Optimization Algorithm (WOA) and Moth-flame Optimization (MFO) are adopted to optimize 21 typical benchmark functions respectively, and the obtained statistical simulation results are compared; Secondly, the improved algorithm proposed in this paper is compared with Binary Grey Wolf Optimizer (BGWO), Hybrid PSOGWO Optimization (PSOGWO) and GWO Algorithm Integrated with Cuckoo Search (GWOCS); Finally, it is applied to the lightest design engineering problem of pressure vessels. Simulation results show that the superior performance of the proposed algorithm for exploiting the optimum and it has advantages in terms of exploration. The improved grey wolf optimizer based on tracking mode and seeking mode can better solve function optimization and classical engineering problems with constraints. It was found the improved grey wolf optimizer based on tracking mode has the high precision and the characteristics of balanced exploration and exploitation.

Aiming at predicting the key economic and technical indicators (Granularity and Ore content)in the grinding production process, the extreme learning machine (ELM) soft-sensor model with different activation functions on grinding process optimized by improved black hole (BH) algorithm was proposed. Based on the selected auxiliary variables for the soft-sensor model of the grinding, the KPCA method is used to reduce the dimensionality of the high-dimensional data. In order to investigate the influence of different activation functions on the prediction accuracy of the ELM model, seven continuous function (Arctan, Hardim, Morlet, ReLu, Sigma, Sin and Tanh) are used as the activation function of the ELM neural network to establish soft-sensor models respectively. For the shortcomings that ELM model weights and offset values are arbitrarily given so as to result in the low prediction accuracy and low reliability, an improved BH algorithm based on the golden sine operator and the Levy flight operator (GSLBH) was used to optimize the parameters of the ELM neural network. Simulation results show that the model has better generalization and prediction accuracy, and can meet the real-time control requirements of the grinding process.

Clustering as an unsupervised learning method is a process of dividing a data object or observation object into a subset, that is to classify the data through observation learning instead of example learning without the guidance of the prior class label information. Bat algorithm (BA) is a swarm intelligence optimization algorithm inspired by bat's ultrasonic echo localization foraging behavior, but it has the disadvantages of being easily trapped into local minima and not being highly accurate. So an improved bat algorithm was proposed. In the global search, a Gaussian-like convergence factor is added, and five different convergence factors are proposed to improve the global optimization ability of the algorithm. In the local search, the hunting mechanism of the whale optimization algorithm (WOA) and the sine position updating strategy are adopted to improve the local optimization ability of the algorithm. This paper compares the clustering effect of the improved bat algorithm with bat algorithm, flower pollination algorithm (FPA), harmony search (HS) algorithm, whale optimization algorithm and particle swarm optimization (PSO) algorithm on seven real data sets under six different convergence factors. The simulation results show that the clustering effect of the improved bat algorithm is superior to other intelligent optimization algorithms.

Small intestinal epithelium homeostasis involves four principal cell types: enterocytes, goblet, enteroendocrine and Paneth cells. Epidermal growth factor (EGF) has been shown to affect enterocyte differentiation. This study determined the effect of dietary EGF on goblet, enteroendocrine and Paneth cell differentiation in piglet small intestine and potential mechanisms. Forty-two weaned piglets were used in a 2 × 3 factorial design; the major factors were time post-weaning (days 7 and 14) and dietary treatment (0, 200 or 400 µg/kg EGF supplementation). The numbers of goblet and enteroendocrine cells were generally greater with the increase in time post-weaning. Moreover, the supplementation of 200 µg/kg EGF increased (P < 0.01) the number of goblet and enteroendocrine cells in villus and crypt of the piglet small intestine as compared with the control. Dietary supplementation with 200 µg/kg EGF enhanced (P < 0.05) abundances of differentiation-related genes atonal homologue 1, mucin 2 and intestinal trefoil factor 3 messenger RNA (mRNA) as compared with the control. Piglets fed 200 or 400 µg/kg EGF diet had increased (P < 0.05) abundances of growth factor-independent 1, SAM pointed domain containing ETS transcription factor and pancreatic and duodenal homeobox 1 mRNA, but decreased the abundance (P < 0.01) of E74 like ETS transcription factor 3 mRNA as compared with the control. Animals receiving 400 µg/kg EGF diets had enhanced (P < 0.05) abundances of neurogenin3 and SRY-box containing gene 9 mRNA as compared with the control. The mRNA abundance and protein expression of lysozyme, a marker of Paneth cell, were also increased (P < 0.05) in those animals. As compared with the control, dietary supplementation with 200 µg/kg EGF increased the abundance of EGF receptor mRNA and the ratio of non-phospho(p)-β-catenin/β-catenin (P < 0.05) in villus epithelial cells at days 7 and 14. This ratio in crypt epithelial cells was higher (P < 0.05) on the both 200 and 400 µg/kg EGF groups during the same period. Our results demonstrated that dietary EGF stimulated goblet, enteroendocrine and Paneth cell differentiation in piglets during the post-weaning period, partly through EGFR and Wnt/β-catenin signalling.

Purpose The current study investigated the therapeutic potential of transcranial direct current stimulation (tDCS) on speech intelligibility, speech-related physiological and vocal functions among post-stroke dysarthric patients. Method Nine chronic post-stroke dysarthric patients were randomly assigned to the stimulation or sham group. The stimulation group received 2mA of anodal tDCS over the left inferior primary motor cortex for 15 minutes, while the sham group received 30s of stimulation under the same settings. All the participants received 10 daily 15 minutes of individualized speech therapy targeting their dominant phonological process or phonemes with the greatest difficulty. The outcome measures included (1) perceptual analysis of single words, passage reading and diadochokinetic rate, (2) acoustic analysis of a sustained vowel, and (3) kinematic analysis of rapid syllable repetitions and syllable production in sentence, conducted before and after the treatment. Results The results revealed that both the stimulation and sham groups had improved perceptual speech intelligibility at the word level, reduced short rushes of speech during passage reading, improved rate during alternating motion rate, AMR-kha1, and improved articulatory kinematics in AMR-tha1 and syllables /tha1/ and /kha1/ production in sentence. Compared to the sham group, the stimulation group showed significant improvement in articulatory kinematics in AMR-kha1 and syllable /kha1/ production in sentence. The findings also showed that anodal stimulation led to reduced shimmer value in sustained vowel /a/ phonation, positive changes in articulatory kinematics in AMR-tha1 and syllables /pha1/ and /kha1/ production in sentence at the post treatment measure. In addition to positive effects on articulatory control, reduced perturbation of voice amplitude documented in the stimulation group post treatment suggests possible tDCS effects on the vocal function. Conclusions The current study documented the beneficial effects of anodal tDCS over the primary motor cortex on speech production and suggested that combined tDCS and speech therapy may promote recovery from post-stroke dysarthria.

Abstract Coronary heart disease (CHD) has been associated with significant morbidity and mortality worldwide. Although remain controversial, several studies have demonstrated the association of M. pneumoniae infections with atherosclerosis. We evaluated the possible association of mycoplasma infections in patients diagnosed with atherosclerosis by ELISA and PCR methods. Atherosclerotic tissue samples and blood samples were collected for the detection of mycoplasma antibodies (IgA) by ELISA from the 97 patients with coronary artery disease (CAD). M. pneumoniae specific IgA, IgG and IgM were measured by using the Anti-M. pneumoniae IgA/IgG/IgM ELISA. Detection of M. pneumoniae targeting the P1 adhesion gene was performed by PCR Acute infection of M. pneumoniae was diagnosed in 43.3% (42) of patients by PCR. The M. pneumoniae specific antibodies were detected in 36.1% (35) of patients. Twenty-five (25.8%) cases had IgG antibodies, 15 (15.5%) cases had IgM antibodies, 3 (3.1%) cases had IgA antibodies, 10 (10.3%) cases had both IgM + IgG antibodies and 1 (1%) case of each had IgM + IgA and IgG + IgA antibodies. None of the cases was positive for all three antibodies. A Pearson correlation coefficient analysis revealed an excellent correlation between the PCR and the serological results (r=0.921, p70 years of age. Our study reported an unusually higher prevalence of M. pneumoniae by serological tests (36.1%) and PCR (43.3%). Although the hypothesis of the association of M. pneumoniae and CAD is yet to be proven, the unusually high prevalence of M. pneumoniae in CAD patients indicates an association, if not, in the development of atherosclerosis.

Bombyx mori nucleopolyhedrovirus (BmNPV) is one of the main pathogens causing serious economic losses in sericulture. However, the molecular mechanism of silkworm resistance to BmNPV is still largely unclear, and the differences in the anti-BmNPV response between silkworms of different genders have been rarely studied. In this study, BmNPV resistant strain NB and BmNPV sensitive strain 306 of different genders were used as experimental materials to inoculate BmNPV, and their transcriptomes were sequenced to analyze their response to BmNPV. Eighteen genes specifically differentially expressed in NB after BmNPV inoculation were finally obtained through transcriptomic analysis, fourteen of which were up-regulated and four were down-regulated, suggesting that they might be related to BmNPV resistance. Among them, the expression abundance of eight genes were higher in males than in females, and one gene was in the contrary. These genes suggested that there were certain differences in the anti-BmNPV response between silkworms of different genders. This study provided a new understanding of the molecular mechanism of silkworm resistance to BmNPV and the differences in the anti-BmNPV response between silkworms of different genders, and laid a foundation for future prevention and control of BmNPV.

The influence of Pb and Zn on chlorophyll (Chl) fluorescence and plant growth of one-year-old Koelreuteria paniculata and Zelkova schneideriana young plants was investigated. Pb and Zn contents in plant organs were measured. The results showed Pb and Zn stress decreased photochemical quenching and quantum efficiency of PSII, but increased energy dissipation in the tested plants. At the same time, maximum net photosynthetic rate, maximum quantum use efficiency, and organ biomass were reduced. Under the same concentration of heavy metals, the damage induced by Zn toxicity was more serious than that of Pb. Pb was less accumulated in leaves, with a mild effect on photosynthesis. Zn was mostly accumulated in leaves and strongly disturbed chloroplast functioning and affected photosynthesis. Pb and Zn had different pathway to influence biomass production, and both tested plants might use different mechanisms of action for heavy metal stress resistance.

Cluster analysis refers to the process of grouping a collection of physical or abstract objects into multiple classes of similar objects. Determining the optimal classification number of a data set is the key to the clustering problem, that is to say whether the data set can be effectively partitioned. Cluster validity study is a process of establishing clustering effectiveness indicators, evaluating clustering quality and determining the optimal number of clusters. A validity function of fuzzy C-means (FCM) clustering algorithm is proposed by adopting the division of intra-class compactness and inter-class separation, whose minimum represents the best clustering. Then, the proposed validity function on FCM clustering algorithm is compared with the known typical validity functions by carrying out simulation experiments to compare the related clustering performance. Three data sets are adopted to carry out FCM clustering, which includes three classical data sets, two artificial data sets and six real data sets in UCI database. Simulation experimental results show that the proposed validity function can effectively partition the data set.

Recent years, invertebrate animals with clear genetic background and completed genome sequence have become very popular in biological research. Insulin and insulin-like peptides (ILPs) are a class of peptides having important physiological functions, including promotion of cell proliferation and differentiation, and body growth and development. To date, many invertebrates have been identified with multiple ILP families, whose structures and functions have become increasingly clear to scientists. This review summarizes the ILPs identified in the model Lepidopteran insect Bombyx mori, in the aspects of structures and classification, functions and pathways. A brief discussion on the ILPs from several other model insects, including Drosophila melanogaster, Aedes aegypti, and Apis mellifera, was also included.

Previously our research group used the microarray analysis and suppression subtractive hybridization technologies to find a Bombyx mori resistance related gene (NCBI ID: NP_001153678.1) to B. mori nucleopolyhedrovirus (BmNPV) and the gene was named Bm123. But there are no more confirmatory studies about Bm123. In this study, BmNPV resistant strain NB, susceptible strain 306, hybrid group 306♀×NB♂ (resistant strain) and NB♀×306♂ (resistant strain) were analyzed by transcriptomic sequencing and Weighted Gene Co-expression Network Work Analysis (WGCNA) to verify the new gene Bm123 function. Correlation analysis between the WGCNA data and phenotype showed that Bm123 is a gene in ME Turquoise module. This module has a strong correlation with disease resistance phenotype (correlation coefficient is 0.753, P value is 0.0047), indicating that Bm123 is a correlated gene with anti-BmNPV. The full length of Bm123 gene was 691 bp, which is not similar with any sequences of other species in NCBI database. But the Bm123 protein contained the transcriptional activator (multiprotein bridge factor 2, MBF2) domain in the 34 to 122 amino acid sequence, closely to Tribolium castaneum by the evolutionary relationship analysis. The BmNPV resistance function, developmental expression pattern and tissue expression pattern of Bm123 were analyzed by using silkworm resistant strain BC10 (screened by eight backcross and two generation of NB and 306 through hybridization and selfing method, each generation is constructed from the feed by adding BmNPV), NB and sensitive strain 306. It was found that after infection with orally BmNPV, the mRNA and protein levels of Bm123 were up-regulated in the midgut of BC10 and NB, and almost not expressed in 306, indicating that Bm123 was a gene associated with resistance to BmNPV. Bm123 protein expression in various tissues of silkworm (fat body, hemolymph, midgut, epidermis, testis, ovary, malpighian tubule and silk gland) was analyzed. It was found that Bm123 was highly expressed in the midgut and malpighian tubule, while the expression in other tissues was lower. Analysis of Bm123 expression in different development stages of silkworm (eggs, 1st to 5th instar larvae, pupae and moth) found that the expression level of Bm123 increased in the 3rd, 4th and 5th instar. The expression level of Bm123 decreased during the pupae and moth stages. It was speculated that the expression of Bm123 was related to the evolution of resistance genes in silkworm. In situ hybridization showed that the Bm123 gene of BC10 was localized in the nucleus of columnar epithelial cells of the midgut, suggesting that Bm123 protein interacts with BmNPV in the silkworm cell nucleus.

Abstract Ultra‐low frequency (ULF) waves can effectively accelerate ring current ions through drift‐bounce resonance. Conventional theories have been developed to understand this resonance since the dawn of the space age, which usually assume ULF waves are quasi‐steady in time. However, ULF waves would experience growth and damping stages in the real magnetosphere, which requires an adjustment of the conventional theories. Here, we attempt to reveal how ions respond to evolving ULF waves. By analyzing an event observed by Van Allen Probe A and reproducing the observations via simulation, we find the phase shift of ion flux oscillation across resonant pitch angles varies with time, when wave growth and damping cannot be neglected. As a result, the inclination angle of stripes in pitch angle spectrogram varies with time, causing “fishbone‐like” pitch angle structures. One should take into account such ion behaviors when considering the role of drift‐bounce resonance in the real magnetosphere.

Abstract Background Glaciers cover ~ 10% of land but are among the least explored environments on Earth. The basal portion of glaciers often harbors unique aquatic microbial ecosystems in the absence of sunlight, and knowledge on the microbial community structures and their metabolic potential is very limited. Here, we provide insights into the microbial lifestyle present at the base of the Matanuska Glacier, Alaska. Results DNA and RNA were extracted from samples of the Matanuska Glacier basal ice. Using Illumina MiSeq and HiSeq sequencing, we investigated the microbial diversity with the metagenomic shotgun reads and 16S ribosomal RNA data. We further assembled 9 partial and draft bacterial genomes from the metagenomic assembly, and identified key metabolic pathways such as sulfur oxidation and nitrification. Collectively, our analyses suggest a prevalence of lithotrophic and heterotrophic metabolisms in the subglacial microbiome. Conclusion Our results present the first metagenomic assembly and bacterial draft genomes for a subglacial environment. These results extend our understanding of the chemical and biological processes in subglacial environments critically influenced by global climate change.

Producing ultrastable metallic glasses has always been associated with substrates heated close to the glass transition temperature. Here, the authors show that reducing the deposition rate of the metallic glass on a cold substrate produces ultrastable metallic glasses with remarkably improved stability.

SAR interferograms are often contaminated by random noises related to temporal decorrelation, geometrical decorrelation and thermal noises, which makes the fringes obscured and greatly decreases the density of the coherent target and the accuracy of InSAR deformation results, especially for the landslide monitoring in vegetated region and in rainy season. Two different SAR interferogram filtering methods, that is Goldstein filter and homogeneous pixels filter, for one specific landslide are compared. The results show that homogeneous pixels filter is better than Goldstein one for small-scale loess landslide monitoring, which can increase the density of monitoring points. Moreover, the precision of InSAR result can reach millimeter by comparing with GPS time series measurements.

The deformation monitoring of active landslides is of great importance for the safety of human lives and properties. And twodimensional deformation result can give us more thoughts on the landslide type and deformation process. In this study, multidimensional small baseline subsets (MSBAS) technique is introduced and tested to compute two-dimensional deformation rate and time series for both east-west and vertical deformation of Xinyuan No.2 landslide by simultaneously processing ascending and descending TerraSAR-X data acquired from January 2016 to November 2016. Results show not only the spatiotemporal characteristics of this landslides, but the retrogressive loess landslide failure mode is revealed for the first time with the two-dimensional deformation.

Filter samples of fine particulate matters were collected at four sites in northern China (urban, rural, and mountain) in summer and winter, and the contents of nine nitrated phenols were quantified in the laboratory with the use of ultra-high-performance liquid chromatography coupled with mass spectrometry. During the sampling periods, the concentrations of particulate nitrated phenols exhibited distinct temporal and spatial variation. On average, the total concentration of particulate nitrated phenols in urban Jinan in the wintertime reached 48.4 ng m−3, and those in the summertime were 9.8, 5.7, 5.9, and 2.5 ng m−3 in urban Jinan, rural Yucheng and Wangdu, and Mt. Tai, respectively. The elevated concentrations of nitrated phenols in wintertime and in urban areas demonstrate the apparent influences of anthropogenic sources. The positive matrix factorization receptor model was then applied to determine the origins of particulate nitrated phenols in northern China. The five major source factors were traffic, coal combustion, biomass burning, secondary formation, and aged coal combustion plume. Among them, coal combustion played a vital role, especially at the urban site in the wintertime, with a contribution of around 55 %. In the summertime, the observed nitrated phenols were highly influenced by aged coal combustion plumes at all of the sampling sites. Meanwhile, in remote areas, contributions from secondary formation were significant. Further correlation analysis indicates that nitrosalicylic acids were produced mostly from secondary formation that was dominated by NO2 nitration.

Twenty-six strains of bacteria were obtained by random sampling previously in our lab. The most pathogenic strains were identified as Bacillus cereus through toxicity assessment of silkworm. Silkworm larvae were killed within 12 h of injection of B. cereus. The changes in cytoplasm and cell membrane caused by the infection were observed by Histopathological examination; these were obvious at 6 - 10 h after injection of the bacteria, indicating its acute pathogenicity. The differential protein spots of silkworms in the treatment group and control group were detected by two-dimensional electrophoresis. Five kinds of silkworm protein were identified in fat body tissue; of these, four proteins were up-regulated and one was down-regulated. Thirteen silkworm proteins were detected in midgut tissues; of these, six proteins were up-regulated and expression of seven proteins was down-regulated. After biological analysis, a 14-3-3zeta protein was expressed in both tissues, and several other up-regulated proteins were found to be involved in the anti-inflammatory, immune, phagocytotic and metabolic pathways of the body, indicating that the host had an emergency response to B. cereus injection. The down-regulated proteins were associated with cell biofilm stability, signal transduction and detoxification, respectively. The protein expression was verified by fluorescence quantitative PCR. The results showed that the expression of proteins was consistent with the changes in gene expression.

The gene FRIGIDA (FRI) is floral repressor and plays a key role in the timing of Arabidopsis flowering. To study the function of FRI-like genes in bamboo, we isolated a FRI family gene from bamboo Phyllostachys violascens and named it PvFRI-L. Sequence alignment and phylogenetic analysis show that the PvFRI-L protein belongs to the FRL3 (III) subfamily from monocots and contains a conserved FRIGIDA domain. PvFRI-L was located in the nucleus of onion epidermal cells. PvFRI-L was expressed in all tested organs of flowering and non-flowering bamboo plants with a higher expression in non-flowering than in flowering plants. Overexpression of PvFRI-L in Arabidopsis caused late flowering by downregulating flowering locus T and upregulating flowering locus C. A P-box, the binding site involved in gibberellin response, was found only in the promoter region of PvFRI-L but not in that of FRI. Furthermore, PvFRI-L expression in the leaves of Ph. violascens seedlings was downregulated with gibberellic acid treatment. Taking together, our observation suggests that PvFRI-L may be flowering repressor and its delaying floral timing may be regulated by gibberellic acid in bamboo.

Several studies have been performed to elucidate the role of brassinosteroids (BRs) in plant growth and development. However, information on the role of BR signaling in nutrient uptake is limited. This study explores the relationship between BRs and ammonium transporter 1 (AMT1) expression in Arabidopsis roots. We found that BR treatment reduced the expression of AMT1 genes and that a BR receptor BRI1 mutant bri1-5 reversed its BR-repressed expression. Furthermore, the BR signaling transcription factor, BES1, regulates AMT1 expression in roots. NH4 +-mediated repression of AMT1;1, AMT1;2, and AMT1;3 was suppressed in a gain-of-function BES1 mutant (bes1-D). This mutant was more sensitive to methyl-ammonium and contained a higher ammonium content compared to wild-type plants. However, BES1 failed to bind E-box elements present in the promoter region of the AMT1 genes. Furthermore, NH4 +-mediated glutamine synthetase (GS) and glutamine oxoglutarate aminotransferase (GOGAT) gene expressions were partially inhibited, and GS activity was slightly lower in the bes1-D mutant relative to that observed in wild-type En2 roots. NH4 +-mediated AMT1 suppressions are known to be caused by N-metabolites rather than NH4 + itself, and glutamine application inhibited AMT1 expression in both En2 and bes1-D indicating that BES1 activation inhibited NH4 +-mediated GS/GOGAT induction, which might in turn inhibit AMT1 repression. In conclusion, the present study demonstrates that BR regulated nitrogen uptake and assimilation via the BR signaling pathway.

Bombyx mori bidensovirus (BmBDV) and Bombyx mori nucleopolyhedrovirus (BmNPV) are serious pathogens of Bombyx mori. In this study, we reported the changes of transcription level of several immune genes, including bmi, argo, dicer, cap1, cap3 and car, in Bombyx mori midgut after exposure to BmBDV or BmNPV. Silkworm strains 798 (anti-BmBDV) and 306 (susceptible to BmBDV) were subjected to BmBDV infection, and NB (anti-BmNPV) and HUABA (35) (susceptible to BmNPV) were subjected to BmNPV infection. The results showed that the transcription levels differ largely among different silkworm strains, and that the extent to which the gene transcriptions were affected by the viruses was different. However, both BmNPV and BmBDV viruses can reverse the transcription patterns of these genes when the silkworms were administered with the viruses compared with those control groups. The transcript levels of bmi and dicer were decreased in 798 and 306 strains that were inoculated with BmBDV compared with their respective controls, but were increased in NB and HUABA (35) inoculated with BmNPV. The transcript levels of argo and cap3 were risen in 798, 306 and NB strains when inoculated with their respective viruses, but were decreased in HUABA (35) strain. The transcript levels of cap1 were risen in all silkworm strains, while the levels of car were decreased in 798, 306 and HUABA (35) strains, and increased in NB strain when inoculated with their respective viruses. These findings may contribute to more in-depth understanding on functions of these genes in virus infection and proliferation.

Beta-relaxation in glasses is commonly attributed to the confined motions of constituent atoms in nanosized domains, but there is no direct evidence so far. Here, Zhu et al. show the correlation between the evolution of spatial heterogeneity at nanoscale and beta-relaxation below glass transition point.

X Chen* , F Zhu* , P Lü, S Ma, A Nouara, Y Yang, K Chen * These authors contributed equally to this work Institute of Life Sciences, Jiangsu University, Zhenjiang, 212013, Jiangsu, P.R. China Accepted March 10, 2016 Abstract Insulin/Insulin-like growth factors play important roles in promoting proliferation, differentiation, growth and development of organisms. In this article, bioinformatics analysis was performed to locate and identify the Bombyx mori insulin-like peptide (BmILP) gene, which had two introns, three exons, and a predicted signal peptide at the front, and it also determined that BmILP was the same to the gene Bombyxin Z1, a member of the bombyxin family. Both the full-length BmILP gene and the gene without the signal peptide expressed mainly existed in inclusion body forms at different induction conditions and it was noted that the signal peptide had significant influence on the expression level. In addition, protein-protein interaction experiments suggested that there was interaction between BmILP and the autophagy-related protein Atg8, indicating that BmILP may play a role in immunity. It was found was that BmILP predominantly produced by the ovary among different tissues in the silkworm. Particularly, the adult females had higher expression levels than the adult males, and the expression level appeared to be the highest in the mated female moths, suggesting that BmILP may be a key factor in the regulation of egg maturation in Bombyx mori.