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Crude oil prices are susceptible to a variety of elements, including military, political, financial, and diplomatic forces, resulting in price fluctuations that are random, abrupt, and chaotic. Based on the chaotic nature of crude oil price series, this paper proposes a model for predicting crude oil prices that incorporates variational modal decomposition algorithm (VMD), phase space reconstruction technique (PSR), convolutional neural network (CNN), and bidirectional long and short-term memory network (BiLSTM). Specifically, the noises in the original data are removed using VMD. Next, the crude oil price is reconstructed using PSR. Then the reconstructed and denoised phase space is fed into the CNN-BiLSTM model for multi-step predictions. The empirical results show that the proposed model achieves the lowest MAPEs as 0.662%, 2.283%, 3.829%, and 4.44% and the lowest MSEs as 0.335, 3.942, 10.047 and 13.681. The Diebold Mariano (DM) test also demonstrates the proposed model's superiority in the domain of crude oil price forecasting. [ABSTRACT FROM AUTHOR]

In recent years, E-learning has gained immense popularity as a prominent mode of education. However, accurately recommending learning resources from a vast amount of data remains a significant challenge. This study addresses two primary challenges impacting recommendation performance. Firstly, an imbalance exists between the abundance of available learning resources and the limited interaction behavior of learners. Secondly, the existing algorithms often overlook dynamic preference information, focusing primarily on learners' short-term, static preferences only by learning interactive behavior but disregarding the multi-correlation between learning resources and learners. To tackle these challenges, we propose MkEGC (Multi-knowledge Enhanced Graph Convolution), a novel framework for learning resource recommendation. We approach the recommendation process as a Markov decision process. Initially, we construct a dual knowledge graph convolutional network, operating in learning resource-knowledge and learner-knowledge domains. This network facilitates the extraction of vector features from learning resources, enhances the learner vector representation, and captures higher-order preferences. Subsequently, we design hierarchical and attention weighting strategies to effectively extract latent hierarchical information from the knowledge graph. Finally, we integrate the learning resource state, the learning interaction state, and the sequence state to represent a multi-dimensional learner-state within the Markov decision framework, enabling prise learning resource recommendations. To validate the effectiveness of MkEGC, we conduct extensive experiments, comparing multiple sets of metrics with six state-of-the-art recommendation algorithms, utilizing two real-world datasets. • Exploring learners' long-term preference changes. • Optimizing the extraction ability of learners' behavioral latent characteristics. • Devising a novel multi-dimensional learner state representation method. • Employing hierarchical weighted and attention-weighted strategies. [ABSTRACT FROM AUTHOR]

[Display omitted] • In 2 O 3 and SnO 2 form an n-n heterojunction, which improves the gas-sensitive properties of SnO 2. • In 2 O 3 grows in situ on SnO 2 , and the composite has a unique hedgehog-like nanoflower morphology with abundant oxygen vacancies. • Improved gas-sensitizing properties attributed to the change in charge density. • Formation of heterojunction leads to In 2 O 3 -SnO 2 composites with higher electron transfer capacity and accelerated charge transfer kinetics. The In 2 O 3 -SnO 2 heterojunction nanostructures resembling hedgehogs were synthesized through hydrothermal method and physical stirring for acetone detection. SEM and TEM characterization showed that the composites were SnO 2 nanosheets (NSs) assembled into a flower-like morphology with In 2 O 3 particles grown in situ on the NSs. The In 2 O 3 -SnO 2 sensor has excellent vapor sensitivity compared to pure SnO 2. At an optimal temperature of 260 ℃, the In 2 O 3 -SnO 2 sensor achieves a response value of 19.4 for acetone vapors at a concentration of 100 ppm. The composites still exhibit excellent gas-sensitized performance at low concentration (100 ppb). The improved gas-sensitized performance of In 2 O 3 -SnO 2 composites is attributed to the sea urchin-like nanoflower morphology enriched with oxygen vacancies and the formation of n-n heterojunctions. To further substantiate its enhancing mechanism, the adsorption behavior of acetone molecules on the fabricated composite material was investigated through the utilization of density functional theory (DFT). This study confirms the enhanced gas sensing performance of In 2 O 3 -SnO 2 heterojunction composites towards acetone and elucidates the enhancement mechanism by DFT calculations. [ABSTRACT FROM AUTHOR]

Abstract In statistical modeling, quadratic model including both main effects and interactions has drawn a large deal of attentions from researchers in many scientific fields. Researchers have found that it is extremely significant to maintain the heredity principle such as strong or weak heredity principle among variables when demanding sparsity in quadratic model. The reason why heredity principle is preferred is that model following logic structure is invariant to any scale transformation and is more stable when implementing forecasting and classification task. Although a large bore have studied quadratic models, most of them focus on the model performances in a regression problem and no systematically comparison are made in terms of classification accuracy. This paper investigates and studies group regularized estimation under structural hierarchy for classification (C-GRESH). In computation, a fast and simple-to-implement algorithm is designed with theoretical guarantee of its convergence. Furthermore, an accelerated gradient method is applied to speed up the convergence. Theoretically, we have shown the adaptive version of the proposed approach is able to achieve oracle property which includes asymptotic normality and model selection consistency. Simulation examples and real data examples including microarray gene expression datasets are shown to demonstrate the efficiency and superior performances of the proposed method over other existing competitors. Highlights • C-GRESH model which achieve SH or WH principle is proposed. • A fast algorithm is designed with theoretical guarantee its convergence. • SCV-RIC is proposed and utilized to optimize the regularization parameters. • Oracle property of adaptive C-GRESH is shown. [ABSTRACT FROM AUTHOR]

The influence on the seismic behavior of RC shear walls by axial loads is evaluated and the observed damage in the earthquake damage investigation of RC shear walls is reproduced in this paper. Six RC shear walls with aspect ratio of 2 were analyzed by the method of nonlinear finite element under different axial load ratios, and the suggested modeling techniques and the accuracy of the numerical method were verified. The seismic performance of shear walls including load–displacement responses, ductility performance, stiffness degradation and energy dissipation capacity were discussed. The analysis results indicate that axial load has a significant effect on the seismic performance of RC shear walls. On the basis of this, the qualitative and quantitative relationships between the development of material damage and the deterioration of component performance were analyzed. It realizes the cross-scale conversion of damage information about structural components of RC shear wall from the local material scale to the component scale. Then the cross-scale refinement model of damage evolution of RC shear walls in the whole process was established, simplified and verified. The results show that, the refinement model can explain the development and distribution of damage evolution of RC shear walls in the whole process quickly and easily. The research results can provide a reference for the refinement of seismic design, damage assessment and reinforcement of RC shear walls. [ABSTRACT FROM AUTHOR]

Prediction and dimension reduction play increasingly significant roles in high-dimensional data analysis; however, they suffer from model inaccuracy, selection inconsistency and a prohibitively expensive computational cost as the model dimension increases exponentially. Although a support vector machine (SVM) is one of the most powerful forecasting approaches that are widely used by the research community, it does not provide an interpretable model that violates the principle of Occam’s razor. In classical regression problems, a penalized linear SVM model for the dimension reduction task has been investigated in the linear feature space under the assumption that the underlying true model is linear. In this paper, the penalized kernel SVM (PKSVM) model is proposed and investigated combining with a SVM information criterion (SVMIC) for the dimension reduction task in the nonlinear kernel space using radial basis function for prediction and model representation. Instead of pursuing sparsity in the original feature space of the SVM, dimension reduction is performed in the kernel feature space. Computationally, a fast and simple-to-implement algorithm is derived. Furthermore, both SVMIC and cross-validation are utilized to select the kernel and regularization parameters to guarantee the model consistency. Real data applications including microarray data analysis and global solar radiation forecasting are provided. The first application selected significant components in genetic study and the important data information is extracted for grid-connected photovoltaic installations in the second application. The proposed dimension reduction technique avoids the model redundancy which is of great importance for knowledge discovery. [ABSTRACT FROM AUTHOR]

Effective and accurate forecasting of solar radiation plays a critically important role in the design of grid-connected photovoltaic installations. However, this is an extremely challenging task because of inconsistencies in variable selection and the prohibitively expensive computational cost as the number of variables increases. Although the support vector machine (SVM) can be applied to forecast solar radiation, it includes a large number of redundant variables. With the intent of establishing an interpretable model, a penalized SVM has been proposed. However, these penalized approaches shrink the estimate, which results in inaccurate results. In order to overcome these drawbacks and improve the accuracy of forecasting, this study develops a novel approach referred to as “forward regression on the quadratic kernel support vector machine” (QKSVM-FR) for building a quadratic regression model using forward regression to select the important variables for forecasting the global horizontal radiation in the Tibet Autonomous Region. A fast and simple-to-implement computational algorithm is derived to perform the variable selection and forecasting tasks simultaneously. Furthermore, the SVM information criterion is utilized to select the kernel parameter to guarantee model consistency. The results of experiments directly confirm the outstanding forecasting performance of the proposed QKSVM-FR method compared to other existing methods. [ABSTRACT FROM AUTHOR]

Natural and artificial nucleases have extensive applications in biotechnology and biomedicine. The exploration of protein with potential DNA cleavage activity also inspires the design of artificial nuclease and helps to understand the physiological process of DNA damage. In this study, we engineered four human cytochrome c (Cyt c) mutants (N52S, N52A, I81N, and I81D Cyt c), which showed enhanced DNA cleavage activity and degradation in comparison with WT Cyt c , especially under acidic conditions. The mechanism assays revealed that the superoxide (O 2 •−) plays an important role in the nuclease reaction. The kinetic assays showed that the peroxidase activity of the I81D Cyt c mutant enhanced up to 9-fold at pH 5. This study suggests that the mutations of Ile81 and Asn52 in Ω-loop C/D are critical for the nuclease activity of Cyt c , which may have physiological significance in DNA damage and potential applications in biomedicine. [Display omitted] • Four human cytochrome c (Cyt c) mutants (N52S, N52A, I81N, and I81D Cyt c) were engineered. • The DNA cleavage/degradation activity follows the order of N52A > N52S > I81N > I81D > WT Cyt c. • The superoxide (O 2 •−) plays an important role in the nuclease reaction of Cyt c mutants. • Ile81 and Asn52 in the in Ω-loop C/D of Cyt c plays a critical role in the regulation of the protein structure and function. • Cyt c may have physiological significance in DNA damage and potential applications in biomedicine. [ABSTRACT FROM AUTHOR]

Various applications of forecasting effective global horizontal irradiance play increasingly vital role in grid-connected photovoltaic installations, but suffer from forecasting inaccuracy and prohibitively expensive computational cost. Although Support Vector Machine (SVM) is one of the most powerful forecasting approaches, it does not provide an interpretable model. This motivates penalized variable selection methods to be introduced to SVM to select important variables. However, in some forecasting problems, there are some underlying logic or hierarchical structure such as heredity principle among the variables. Penalized Kernel SVM approaches do not take heredity principles into consideration when enforcing sparsity. This paper investigates structural variable selection in Kernel SVM based approach which pursues heredity principle and sparsity simultaneously. To achieve heredity principle, both optimization and procedure based structural variable selection approaches are studied in the Kernel SVM. Computationally, we derive fast and simple-to-implement algorithms to perform structural variable selection and solar irradiance forecasting. Furthermore, Support Vector Machines Information Criterion is utilized to select the kernel parameters to guarantee the model consistency. Real data experiments directly reveal that our proposed KSVM-SVS based approach following heredity principle delivers superior performances in terms of forecasting accuracy comparing with other competitors. [ABSTRACT FROM AUTHOR]

Forecasting of effective solar irradiation has developed a huge interest in recent decades, mainly due to its various applications in grid connect photovoltaic installations. This paper develops and investigates an ensemble learning based multistage intelligent approach to forecast 5 days global horizontal radiation at four given locations of India. The two-way interaction model is considered with purpose of detecting the associated correlation between the features. The main structure of the novel method is the ensemble learning, which is based on Divide and Conquer principle, is applied to enhance the forecasting accuracy and model stability. An efficient feature selection method LASSO is performed in the input space with the regularization parameter selected by Cross-Validation. A weight vector which best represents the importance of each individual model in ensemble system is provided by glowworm swarm optimization. The combination of feature selection and parameter selection are helpful in creating the diversity of the ensemble learning. In order to illustrate the validity of the proposed method, the datasets at four different locations of the India are split into training and test datasets. The results of the real data experiments demonstrate the efficiency and efficacy of the proposed method comparing with other competitors. [ABSTRACT FROM AUTHOR]

For a portion of the power which is generated by grid connected photovoltaic installations, an effective solar irradiation forecasting approach must be crucial to ensure the quality and the security of power grid. This paper develops and investigates a novel model to forecast 30 daily global solar radiation at four given locations of the United States. Eclat data mining algorithm is first presented to discover association rules between solar radiation and several meteorological factors laying a theoretical foundation for these correlative factors as input vectors. An effective and innovative intelligent optimization model based on nonlinear support vector machine and hard penalty function is proposed to forecast solar radiation by converting support vector machine into a regularization problem with ridge penalty, adding a hard penalty function to select the number of radial basis functions, and using glowworm swarm optimization algorithm to determine the optimal parameters of the model. In order to illustrate our validity of the proposed method, the datasets at four sites of the United States are split to into training data and test data, separately. The experiment results reveal that the proposed model delivers the best forecasting performances comparing with other competitors. [ABSTRACT FROM AUTHOR]

Heme proteins have recently emerged as promising artificial metalloenzymes for catalyzing diverse reactions. In this report, L29E Mb, a single mutant of myoglobin (Mb), was reconstituted by replacing the heme with a sodium copper cholorophyllin (CuCP) to form a new green artificial enzyme (named CuCP-L29E Mb). The reconstituted protein CuCP-L29E Mb was found to exhibit hydrolytic DNA cleavage activity, which was not depending on O 2. In addition, Mg2+ ion could effectively promote the DNA cleavage activity of CuCP-L29E Mb. Wild-type (WT) Mb reconstituted with CuCP (named CuCP-WT Mb) did not show DNA cleavage activity under the same conditions. This study suggests that both Mg2+ and the ligand Glu29 are critical for the nuclease activity and the artificial nuclease of Mg2+-CuCP-L29E Mb may have potential applications in the future. The single mutant of myoglobin (L29E Mb) was reconstituted with a sodium copper cholorophyllin (CuCP) to form a new green artificial enzyme, which was shown to exhibit excellent hydrolytic DNA cleavage activity and Mg2+ ion could further promote the activity. [Display omitted] • A new artificial enzyme was obtained by replacing the heme with a chlorophyllin (CuCP) in L29E myoglobin (Mb). • The reconstituted protein exhibits excellent hydrolytic DNA cleavage activity. • Glu29 is crucial for the DNA cleavage activity of CuCP-L29E Mb. • Mg2+ ion can enhance activity of the artificial nuclease of CuCP-L29E Mb. [ABSTRACT FROM AUTHOR]

• The controller-extensible HSP based on Matlab-OpenSees frameworks is developed. • The developed Matlab-OpenSees interface has good communication flexibilities. • The hybrid test results verify the accuracy and robustness of the developed HSP. • A series of hybrid tests on viscoelastically damped frame structures are conducted. Most of hybrid simulation platforms (HSPs) that use OpenSees for structural hybrid testing research are developed based on OpenFresco framework software. Although OpenFresco is mature and reliable, it can only communicate with specific hydraulic servo actuator control systems, which limits the diversity and flexibility of HSP development. Matlab has powerful independent development functions, and has a wide range of communication interface advantages with many finite element software and actuator control systems. Therefore, Matlab can be used as the communication medium between OpenSees and actuator control system in this study. Firstly, the controller-extensible HSP based on Matlab-OpenSees frameworks is developed. Then, the core establishment details of HSP, including core architecture, hardware system, and DELTA-Matlab-OpenSees system, are analyzed and described in detail. Next, the dynamic loading tests on the spring components are carried out when the HSP is subjected to continuously changing working conditions in the wide frequency domain and displacement amplitude domain. The comparative analysis results on the target displacement curve and the measured displacement curve verify the accuracy and robustness of the inner control loop of HSP. Next, the hybrid tests on a three-story reinforced concrete frame structure with linear springs are implemented under different seismic wave excitations. The comparative research on the hybrid test results and time-history analysis results verifies the accuracy and robustness of the developed HSP (outer control loop) in this study. Lastly, on this basis, a series of hybrid tests on viscoelastically damped frame structures are conducted under different seismic wave excitations. The test results truly reveal the control rule on the seismic response of reinforced concrete frame structures affected by viscoelastic dampers. [ABSTRACT FROM AUTHOR]

Glutaminyl cyclase (QC) plays an important role in the pathogenesis of Alzheimer’s disease (AD) and can be a potential target for the development of novel anti-AD agents. However, the study of QC inhibitors are still less. Here, phenol-4′ (R1-), C5-OH (R2-) and C7-OH (R3-) modified apigenin derivatives were synthesized as a new class of human QC (hQC) inhibitors. The efficacy investigation of these compounds was performed by spectrophotometric assessment and the structure–activity relationship (SAR) was evaluated. Molecular docking was also carried out to analyze the binding mode of the synthesized flavonoid to the active site of hQC. [ABSTRACT FROM AUTHOR]

The thermoelectric performance of DNA duplex chains (G:C)–(T:A) n –(G:C) 3 is studied by a tight-binding ladder model. The quantum interferences due to intra- and inter-strand couplings can greatly enhance the thermopower effect in long systems. The peak value of Seebeck coefficient increases exponentially with n while the charge transfer rate remains almost constant for n > 3 as previously measured. Big figure of merit ( ZT ) might be available for large n . This result is applicable to other wire molecules having similar structure. [ABSTRACT FROM AUTHOR]

An ultra performance liquid chromatography tandem mass spectrometry (UPLC–MS/MS) was developed and validated for the determination and pharmacokinetic investigation of songorine in rat plasma. Sample preparation was accomplished through a simple one-step deproteinization procedure with 0.2 mL of acetonitrile to a 0.1 mL plasma sample. Plasma samples were separated by UPLC on an Acquity UPLC BEH C18 column using a mobile phase consisting of acetonitrile-0.1% formic acid in water with gradient elution. The total run time was 3.0 min and the elution of songorine was at 1.68 min. The detection was performed on a triple quadrupole tandem mass spectrometer equipped with positive-ion electrospray ionization (ESI) by multiple reaction monitoring (MRM) of the transitions at m/z 358.3 → 340.3 for songorine and m/z 237.2 → 194.3 for carbamazepine (internal standard). The calibration curve was linear over the range of 1–1000 ng/mL with a lower limit of quantitation (LLOQ) of 1.0 ng/mL. Mean recovery of songorine in plasma was in the range of 75.2–87.5%. The intra- and inter-day precision (RSD) was between 3.1–8.5% and 4.3–9.6% and the intra- and inter-day accuracy (RE) ranged from −4.0 to 8.9% and −9.0 to 6.7%. This method was successfully applied in pharmacokinetic study after intravenous administration of 5.0 mg/kg songorine in rats. [ABSTRACT FROM AUTHOR]

Due to the scarcity of equipment and the high costs of maintenance, far fewer observations of solar radiation are made than observations of temperature, precipitation and other weather factors. Therefore, it is increasingly important to study several relevant meteorological factors to accurately forecast solar radiation. For this research, monthly average global solar radiation and 12 meteorological parameters from 1998 to 2010 at four sites in the United States were collected. Pearson correlation coefficients and Apriori association rules were successfully used to analyze correlations between the data, which provided a basis for these relative parameters as input variables. Two effective and innovative methods were developed to forecast monthly average global solar radiation by converting a RBF neural network into a multiple linear regression problem, adding a hard-ridge penalty to reduce the number of nodes in the hidden layer, and applying intelligent optimization algorithms, such as the cuckoo search algorithm (CS) and differential evolution (DE), to determine the optimal center and scale parameters. The experimental results show that the proposed models produce much more accurate forecasts than other models. [ABSTRACT FROM AUTHOR]

AdpA serves as the global transcription factor in the A-factor regulatory cascade, controlling the secondary metabolism and morphological differentiation of the filamentous bacterium Streptomyces griseus. AdpA binds to over 500 operator regions with the consensus sequence 5'-TGGCSNGWWY-3' (where S is G or C, W is A or T, Y is T or C, and N is any nucleotide). However, it is still obscure how AdpA can control hundreds of genes. To elucidate the structural basis of this tolerant DNA recognition by AdpA, we focused on the interaction between the DNA-binding domain of AdpA (AdpA-DBD), which consists of two helix-turn-helix motifs, and a target duplex DNA containing the consensus sequence 5'-TGGCGGGTTC-3'. The crystal structure of the AdpA-DBD-DNA complex and the mutant analysis of AdpA-DBD revealed its unique manner of DNA recognition, whereby only two arginine residues directly recognize the consensus sequence, explaining the strict recognition of G and C at positions 2 and 4, respectively, and the tolerant recognition of other positions of the consensus sequence. AdpA-DBD confers tolerant DNA sequence specificity to AdpA, allowing it to control hundreds of genes as a global transcription factor. [ABSTRACT FROM AUTHOR]

Highlights: [•] This study uses Sliding T-test and Sliding F-test to do mutation tests. [•] Tests results recommend to develop a perfect monitoring system for wind farms. [•] Four probability density functions are used to evaluate wind speed and power. [•] Three intelligent optimization algorithms estimate Weibull’s parameters. [•] Three assessment indexes are used to choose the most fitting wind turbine. [ABSTRACT FROM AUTHOR]

To reveal the failure mechanism of resonance effect on long-periodic structures, the spectrum characterization of nonlinear and non-stationary long-periodic ground movements are studied. Firstly, the period and energy characterizations about IMFs (intrinsic mode functions) of ground movements are analyzed. Then, an energy-weighted average period is proposed to indicate the long-periodic characterization on different types of ground movements. Lastly, the simplified method on the low-frequency time history for long-periodic ground movements is proposed and verified. The research conclusions show that, various Hilbert amplitude spectra analysis can expose all the inherent information of nonlinear and non-stationary long-periodic ground movement accurately and comprehensively. The proposed periodic parameter that characterizes different earthquake classifications can help to efficiently and conveniently filter out long-period ground movements, and it also can be used as a quantitative indicator to identify long-period ground movements. The suggested simplified method can facilitate in-depth and accurate analysis of the low-frequency components of long-periodic ground movements. Effective and accurate evaluation on the low-frequency components of long-periodic ground movements plays the key role to uncover the nonlinear dynamic behavior of long-periodic structures, and it is of great scientific research significance in the field of earthquake engineering and structural engineering. • The spectrum characterizations of long-periodic ground movement can make up for the deficiencies of linear signals analysis. • The suggested periodic parameter can be used as a quantitative indicator to identify long-period ground movements. • The proposed simplified method can facilitate in-depth and accurate analysis on the long-periodic ground movements. [ABSTRACT FROM AUTHOR]

[Display omitted] • AMPK inhibition markedly decreases neuronal injury and infarct size after cerebral I/R. • AMPK inhibition alleviates neuronal apoptosis after cerebral I/R. • The neuroprotective effects involved in the suppressed expression of cyt c and AIF. • These positive results provided a better understanding of underlying mechanisms of stroke. Stroke is a major public health problem with an imperative need for a more effective and tolerated therapy. Neuroprotective therapy may be an effective therapeutic intervention for stroke. The morbidity and mortality of stroke-induced secondary brain injury is mainly caused by neuronal apoptosis, which can be executed in a caspase-dependent or apoptosis inducing factor (AIF)–dependent manner. As apoptosis is an energy-dependent process with a relative time delay, abnormal energy metabolism could be a significant and fundamental pathophysiological basis of stroke. To our knowledge, convincible evidences that AMPK inhibition exerts neuroprotection in cerebral ischemia injury via anti-apoptosis remain to be investigated. Accordingly, the aims of this study were to investigate the protective effects of AMPK inhibitor BML-275 on cerebral ischemic/reperfusion (I/R) injury and to elucidate the underlying mechanisms. Cerebral ischemia was induced by transient middle cerebral artery occlusion (tMCAO) in male C57BL/6 mice. The therapeutic effects of BML-275 were evaluated by infarct sizes, neurological scores and the proportion of apoptotic neurons after 24 h of reperfusion. The cell apoptosis markers cyt c and AIF were also evaluated. The results showed that intraperitoneally administration of BML-275 alleviate the cerebral infarction, neurological deficit and neuronal apoptosis induced by MCAO. BML-275 simultaneously induces anti-apoptosis and decreases the expression of cyt c and AIF. This study supports the hypothesis that anti-apoptosis is one of potential neuroprotective strategies for the treatment of stroke. [ABSTRACT FROM AUTHOR]

Dietary selenium (Se) deficiency causes muscular dystrophy in various species, but the molecular mechanism remains unclear. Our objectives were to investigate: 7) if dietary Se deficiency induced different amounts of oxidative stress, lipic peroxidation, and cell apoptosis in 3 skeletal muscles; and 2) if the distribution and expression of 4 endoplasmic reticulum (ER) resident selenoprotein genes (Sepn1, Selk, Sels, and Selt) were related to oxidative damages in these muscles. Two groups of day-old layer chicks (n = 60/group) were fed a corn-soy basal diet (33 µg Se/kg; produced in the Se-deficient area of Heilongjiang, China) or the diet supplemented with Se (as sodium selenite) at 0.15 mg/kg for 55 d. Dietary Se deficiency resulted in accelerated (P < 0.05) cell apoptosis that was associated with decreased glutathione peroxidase activity and elevated lipid peroxidation in these muscles. All these responses were stronger in the pectoral muscle than in the thigh and wing muscles (P < 0.05). Relative distribution of the 4 ER resident selenoprotein gene mRNA amounts and their responses to dietary Se deficiency were consistent with the resultant oxidative stress and cell apoptosis in the 3 muscles. Expression of Sepn1, Sels. and Selt in these muscles was correlated with (r > 0.72; P< 0.05) that of Sepsecs encoding a key enzyme for biosynthesis of selenocysteine (selenocysteinyl-tRNA synthase). In conclusion, the pectoral muscle demonstrated unique expression patterns of the ER resident selenoprotein genes and GPx activity, along with elevated susceptibility to oxidative cell death, compared with the other skeletal muscles. These features might help explain why it is a primary target of Se deficiency diseases in chicks. [ABSTRACT FROM AUTHOR]

Abstract: The use of X-ray scattering techniques in pharmaceutical science is increasing, in part through increased collaborations with the materials science community, and through increased availability of instrumentation, particularly synchrotron sources. The ability to understand not only the biopharmaceutical outcome, but also arguably, more importantly, the structural aspects of drugs and drug delivery systems, is essential to progressing pharmaceutical science; this review serves as an introduction to the major techniques and the wide range of areas in which X-ray scattering may be applied in understanding and controlling structure in pharmaceutical systems. [Copyright &y& Elsevier]

Abstract: Half-hourly electricity price in power system are volatile, electricity price forecast is significant information which can help market managers and participants involved in electricity market to prepare their corresponding bidding strategies to maximize their benefits and utilities. However, the fluctuation of electricity price depends on the common effect of many factors and there is a very complicated random in its evolution process. Therefore, it is difficult to forecast half-hourly prices with traditional only one model for different behaviors of half-hourly prices. This paper proposes the improved forecasting model that detaches high volatility and daily seasonality for electricity price of New South Wales in Australia based on Empirical Mode Decomposition, Seasonal Adjustment and Autoregressive Integrated Moving Average. The prediction errors are analyzed and compared with the ones obtained from the traditional Seasonal Autoregressive Integrated Moving Average model. The comparisons demonstrate that the proposed model can improve the prediction accuracy noticeably. [Copyright &y& Elsevier]

Abstract: When boiling occurs in a micro-channel, the growing bubbles could be confined. They expand both upstream and downstream and cause flow instability in the form of flow fluctuations. The instability occurs frequently when the Bond number of the fluid in the micro-channel is less than unity. To reduce the flow instability, installation of an inlet orifice at the upstream or the micro-channel expanding at the downstream are found to be effective. A generalized instability model for micro-channels was established, which includes the effects of both inlet orifice and channel expansion. Experiments of evaporating water in 48 parallel micro-channels with 353μm hydraulic diameter were conducted, and the generalized instability criterion was validated. [Copyright &y& Elsevier]

The intracellular localization of signaling proteins is critical in directing their interactions with both upstream and downstream signaling cascade components. While initially described as a cyclin kinase inhibitor, p21Waf1/Cip1 has since been shown to have bimodal effects on cell cycle progression and cell proliferation, and evidence is emerging that intracellular localization of this protein plays a role in directing its signaling properties by dictating its interactions with downstream molecules. Since we have previously demonstrated a pro-apoptotic and cell cycle inhibitory effect of p21 attenuation after transfection of antisense p21 oligodeoxynucleotides (ODN) in several cell lines, we asked whether cytosolic p21 mediates a positive effect on vascular smooth muscle (VSM) cell cycle transit. We now show that transfection of a nuclear-localization signal deficient (ΔNLS) p21 construct into VSM cells results in increased cytosolic levels of p21 and causes increased cell cycle transit as measured by [3H]thymidine incorporation. Thus, at least in VSM cells, cytosolic localization of p21 is a means by which this signaling protein transmits pro-mitogenic signals to the proteins responsible for G1/S transition. Furthermore, compartmentalization of p21 may help explain the biphasic nature of p21 in a variety of cell types and may lead to therapeutic advances directed at modulating pathologic cell growth in vascular diseases and cancer. [Copyright &y& Elsevier]

Most of hybrid test researches utilizing OpenSees are based on the hybrid test system framework software OpenFresco. Such software is convenient but can only be connected to specific test control systems, which limits the widespread application of hybrid test. In this paper, a new hybrid test system based on Matlab-OpenSees combined programming is developed, and the details of hybrid test system including core architecture, test facilities and Matlab-OpenSees system are described. Then, the performance verification of test facilities and Matlab-OpenSees system is conducted. Next, the mechanical properties of viscoelastic damper are tested under different amplitudes, frequencies and temperatures. Finally, the hybrid tests of three-dimensional viscoelastic damping structures are implemented by the developed hybrid test system for the first time. The feasibility and accuracy of hybrid test system based on Matlab-OpenSees combined programming are verified by the seismic response comparison of viscoelastic damping structures obtained by the hybrid test and the finite element numerical simulation. A good damping effect of viscoelastic dampers on the structures under earthquake excitation is demonstrated by comparing the results of the damped and undamped structure. • A new hybrid test system based on Matlab-OpenSees combined programming is established. • The Matlab-OpenSees interface is developed based on TCP/IP communication protocol and network communication principle. • The test facilities can high-precisely track the displacement commands and meet the requirements of displacement control in hybrid test. [ABSTRACT FROM AUTHOR]

The aim of this study was to investigate the performance of ethanolic extract from Morus alba L. leaves (MLEE) in preserving chilled pork under retail conditions. The four treatments were 5 mg/mL sodium benzoate solution (SB), 1 mg/mL MLEE solution (high-concentration MLEE; HM), 0.5 mg/mL MLEE solution (low-concentration MLEE; LM), and 0 mg/mL MLEE solution (C). The quality characteristics, pH, thiobarbituric acid reactive substances values, metmyoglobin, total volatile basic nitrogen, and number of microbes of MLEE-treated chilled pork stored at 4 °C for 9 days were consistent with those obtained by the SB treatment and lower than those obtained by the C treatment. Sensory analyses showed that treatment of pork with MLEE did not have a negative impact on its sensory characteristics. MLEE can extend the shelf life of chilled pork from 3 days to 6 days (9 days) in first-class (second-class) fresh meat. Results suggest that MLEE could be a candidate resource in the preservation of chilled pork. • MLEE can extend the shelf life of chilled pork. • Panelists can accept the MLEE-treated pork. • Gram-positive Bacillus was one of the main inducements of meat deterioration. • MLEE could be a candidate resource in the preservation of chilled pork. [ABSTRACT FROM AUTHOR]

Imbalanced data can always be observed in our daily life and various practical tasks. A lot of well-constructed machine learning methodologies may produce ineffective performance, when conducted on this kind of data. This originates from the produced high training biases that towards the majority class instances. Among all the solutions of this problem, data generation of the minority class is always considered the most effective approach. However, in all the previous works, data are always processed sample-wisely and the distribution of each single data attribute is never noticed. So, in this paper, to estimate the mechanism of how each attribute contributes to its label, we explore the potential connection between the two items by Conditional Generative Adversarial Networks (CGAN) separately and individually. Then, the constructed new instances are purified by a designed attribute-based minimax filter and the survivors are concatenated to form the eventual generated data. In other words, different from the CGAN based data generation way, the proposed approach improves it by additionally considering all the single attribute patterns of the data that to construct new instances. In addition, we extend the binary class imbalanced learning framework to multiple class one. In the experimental part, the improved model is compared against GAN, CGAN and some other standard multiple-class oversampling algorithms on several widely used datasets. Results, in terms of four common measurements, have shown that the proposed approach can produce comparable and always superior performance when compared with the competitors. [ABSTRACT FROM AUTHOR]

• Peptidic TRF2 inhibitors with C-terminal modifications were reported. • Binding affinities were improved and peptidic characteristics were decreased. • Binding mode of the designed compounds was predicted. Telomeric repeat binding factor 2 (TRF2) plays an important role in protecting telomeres from being recognized as DNA breaks. TRF2 performs its telomere protecting functions partially by recruiting a number of accessory proteins to telomeres through its TRF homology (TFRH) domain. Identification of small molecular compounds which can bind to the TRFH domain of TRF2 and block the interactions between TRF2 and its associated proteins is crucial for elucidating the molecular mechanisms of these protein–protein interactions. Using a previously identified peptidic mimetic of Apollo TBM as a lead compound, we designed and synthesized a series of novel TRF2 inhibitors by non-peptidic modifications of the N -terminal residues. These compounds can maintain the binding affinities to TRF2 but have much reduced peptidic characteristics compared to the lead compound. [ABSTRACT FROM AUTHOR]

• Cyclin B protein is present in the immature oocytes, and undergoes increased expression at GVBD in both crab and prawn. • Cyclin B protein relocate from the cytoplasm to the nucleus during oocytes meiotic maturation. • Similar expression pattern of the cyclin B protein was found in the oocyte maturation of the prawn and the crab. Cyclin B functions as a regulatory protein through association with its catalytic partner Cdc2 kinase forming M−phase promoting factor (MPF), which plays a central role in the meiotic maturation of oocyte. To gain insight into the molecular events, we here cloned a cyclin B cDNA from the ovary of the prawn Macrobrachium rosenbergii and compared its spatial–temporal expression patterns during oocyte maturation with those of crab Eriocheir sinensis. The prawn cyclin B cDNA encodes a 398 amino acid protein with predicted molecular weight of 45.16 kDa. Immunodetection of cyclin B protein by Western blot showed that a target band of approximately 53 kDa protein in the prawn ovaries at both late vitellogenesis (lVt) and germinal vesicle breakdown (GVBD) stages, whereas a 41 kDa band was present in the crab ovaries. Cyclin B protein expression changes indicating that the newly synthesis of cyclin B proteins could be required for GVBD in both prawn and crab. Immunohistochemical analysis revealed that both the prawn and crab cyclin B proteins, were localized in the ooplasm of previtellogenic oocytes, then relocated into germinal vesicle at vitellogenesis stage and localized on meiotic spindle at M phase. These similar behaviors suggested that the prawn and the crab cyclin B proteins associated with Cdc2 kinase have conserved roles in inducing GVBD and regulating the formation of meiotic spindle. The similar expression patterns of the cyclin B proteins during oocyte maturation implicated that the molecular mechanisms for MPF activation could be identical between the prawn and the crab. [ABSTRACT FROM AUTHOR]

• A user-programmable hybrid simulation platform is established. • The methods for solving equation for viscoelastically damped structures are proposed. • The reliability of the hybrid simulation platform to test nonlinear systems is verified. • A series of hybrid simulation experiments for viscoelastically damped structures are implemented. To truly reflect the influence on structural seismic response control using viscoelastic dampers with strong nonlinear properties and reduce the cost and difficulty of experimental research, a new user-programmable hybrid simulation platform is developed. The core implementation details of this platform, including the core architecture, software system, and testing setup, are described. To better realize accuracy and stability of the hybrid simulation experiment, methods for solving the equivalent force equilibrium equation for hybrid simulation experiments on viscoelastically damped structures are proposed. Then, the mechanical properties of the experimental substructure (viscoelastic damper) are tested under different temperatures, amplitudes and frequencies, and the mathematical model parameters of the experimental substructure are identified. A seismic response comparison of viscoelastically damped structures obtained by the hybrid simulation experiment and the time history analysis verifies the robustness and reliability of the hybrid simulation platform to test nonlinear systems. Lastly, a series of hybrid simulation experiments for viscoelastically damped structures under different temperatures, seismic intensities and seismic waves are implemented using this hybrid simulation platform for the first time. The experimental results reveal the influence on structural seismic response control by viscoelastic damper under different temperatures, seismic intensities and seismic waves. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to investigate and characterize the performance changes of viscoelastic materials (VEMs) in viscoelastic (VE) devices used for structure vibration control due to the influence of aggressive environmental conditions during long-term service. To this end, a series of thermal-oxidative (TO) aging experiments are conducted on the developed VEMs, variation of microstructure and macroscopic mechanical behaviors of TO aged VEMs are tested and analyzed. The molecular chain network of VEMs that can be simplified into elastic chain network and free chain network is described by the architecture of microsphere model, a physics-informed data-driven model is proposed to reflect the mechanical properties of TO aged VEMs, in which the physics-informed neural network (PINN) theory is incorporated to describe the statistical characteristics of molecular chains and the reaction rate of TO aging. Based on the experimental data, implementation and validation of the proposed model are conducted on the mechanical properties of VEMs under varying aging levels. The experimental results suggest that TO aging could alter molecular chain structure of VEMs from the microscopic level, leading to an increase in crosslinking degree and modulus, and the degeneration of deformation ability and energy-dissipation capacity for VEMs. The verifications reveal that the proposed model possesses high accuracy in characterizing the mechanical properties and energy-dissipation capability of VEMs under different aging levels, which preliminarily proofs the potential of PINN theory in reflecting the complex mechanical behaviors of VEMs. • The microstructural and mechanical changes in VEMs are studied by TO aging tests. • TO aging can enhance VEMs' modulus and degrade their deformable and energy-dissipation capacity. • A physics-informed data-driven model is proposed to reflect mechanical behaviors of TO aged VEMs. [ABSTRACT FROM AUTHOR]

• An advanced frame structure system retrofitted by adding haunch viscoelastic damping braces is presented. • The seismic behavior and rebar strain at key locations of CFs and VFs are discussed. • A comparative study on the damage evolution about two types of frames at the material scale is carried out. • The addition of HVEDB guarantees the seismic design requirements of "strong nodes and weak components. To upgrade the existing RC frame structure system with insufficient seismic design and improve the seismic design of the RC frame structures, a novel and advanced frame structure system retrofitted by adding haunch viscoelastic damping braces (HVEDB) is presented in this study based on the good energy dissipation performance, the low-cost and non-invasive addition of viscoelastic dampers. For a comprehensive and systematic research of this new structure system, the seismic behavior of ten RC frames and another ten RC frames added by HVEDB with the axial load ratio (ALR) of 0.1–1.0 are carried out under horizontal sinusoidal steady-state excitation loading, including the hysteretic behavior, load-bearing capacity, stiffness degradation, energy dissipation capacity, additional damping ratio and rebar strain at key locations. On this basis, four reasonable damage indicators at the material scale are proposed, and a comparative study on the damage evolution about two types of frames at the material scale in the whole process is carried out. The study results show that the addition of HVEDB can greatly improve the seismic performance such as load-bearing capacity, lateral stiffness, deformation capability and energy dissipation, and it changes the failure mode of the RC frames. The HVEDB can provide the effective protection for the beam-column joints by transferring the damage region from the beam-column joint to the frame beam successfully, which guarantee the seismic design requirements of "strong nodes and weak components" avoiding the brittle failure mode of frame structure under high ALR. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • Addition of herbicides causes structural changes to liquid crystalline nanoparticles. • Agrochemical emulsions interact with liquid crystalline systems when mixed. • Herbicide transfer to liquid crystalline systems is altered upon temperature change. Abstract The use of liquid crystalline nanoparticles as potential agrochemical delivery agents or adjuvant systems is gaining traction due to the possibility that the systems can enhance penetration of the active and increase adhesion of the formulation to the leaf, increasing overall efficacy and decreasing the harmful environmental impact. However the interaction between liquid crystalline nanoparticles and active products is not well understood. Using small angle X-ray scattering we investigated the structural changes that occur to liquid crystalline nanoparticles upon addition of three common herbicides, 2,4-D 2-ethylhexyl ester, bromoxynil octanoate and haloxyfop-p-methyl ester active agrochemicals in the form of emulsions. It was found that the hydrophobic herbicides induced structural changes to varying degrees when pre-mixed with liquid crystalline forming lipids (phytantriol and glycerol monooleate) and also during dynamic mixing as emulsions. [ABSTRACT FROM AUTHOR]

Articular cartilage is susceptible to impact injury. Impact may occur during events ranging from trauma to surgical insertion of an OsteoChondral Graft (OCG) into an OsteoChondral Recipient site (OCR). To evaluate energy density as a mediator of cartilage damage, a specialized drop tower apparatus was used to impact adult bovine samples while measuring contact force, cartilage surface displacement, and OCG advancement. When a single impact was applied to an isolated (non-inserted) OCG, force and surface displacement each rose monotonically and then declined. In each of five sequential impacts of increasing magnitude, applied to insert an OCG into an OCR, force rose rapidly to an initial peak, with minimal OCG advancement, and then to a second prolonged peak, with distinctive oscillations. Energy delivered to cartilage was confirmed to be higher with larger drop height and mass, and found to be lower with an interposed cushion or OCG insertion into an OCR. For both single and multiple impacts, the total energy density delivered to the articular cartilage correlated to damage, quantified as total crack length. The corresponding fracture toughness of the articular cartilage was 12.0 mJ/mm 2 . Thus, the biomechanics of OCG insertion exhibits distinctive features compared to OCG impact without insertion, with energy delivery to the articular cartilage being a factor highly correlated with damage. [ABSTRACT FROM AUTHOR]

As one of promising renewable energy, wind energy has an important position in the field of energy market and it has been always used to generate electricity, thus, the high precision wind speed forecasting is important but challenging for power generation system. Many researchers have devoted their attention to establish efficient wind speed forecasting models, limited by the structure of original models and database, these models could not solve overfitting problem very well and it is rare that a single wind speed forecasting model is always best in all cases since each model has its own particular strengths and weaknesses. The combining method, composed of multiple forecasting models, is regarded as a type of outstanding approach to take advantage of strengths of each model. However, the properties of the individual forecasting models may vary over time, which leads to poorly performance of the combining method using fixed weights, thus, it is more appropriate to allow the combining weights to change according to the time-varying underlying process. This study develops a reliable combination model for wind speed forecasting based on an improved Adaboost algorithm named time-vary-forecasting-effectiveness (TW-FE-Adaboost) algorithm in order to improve the overall forecasting accuracy. In the proposed model, concept drift is firstly used to deal with wind speed time series mainly because the contributions of samples which are varying with time, the second order forecasting effectiveness is used to measure the performance of weak learners. Then, the multi-step ahead forecasting for each site is conducted using TW-FE-Adaboost model in which the input-output sample pairs are determined in a reasonable way. Finally, the ultimate forecast result of wind speed is obtained by aggregating the forecast result of each weak learner. The proposed model is tested using four sites wind speed series collected in Hexi corridor from wind farms located in northwest of China. The experimental results show that the proposed model outperforms all other comparison models in this paper, which demonstrates that the proposed model has superior performances for wind speed forecasting. [ABSTRACT FROM AUTHOR]

This paper investigates the structural behavior of a typical three-dimensional steel frame-concrete slab substructure (3D composite floor subassembly) subject to a penultimate interior column removal scenario. A two-by-two bay composite floor subassembly is one-third downscaled and quasi-statically pushed down to failure by a specially designed twelve-point loading tree in displacement control mode. Unlike the previous studies where progressive collapse propagates vertically, the current study reveals the possibility of horizontal progressive collapse of 3D composite floor structures that characterized by losing stability of the exterior column. The load-displacement relationships, failure modes, deformation pattern and beam end rotations of the test specimen are presented in detail. Based on the test results, the three load-transferring mechanisms, including flexural action, catenary action and tensile membrane action, are determined and discussed. Besides, the test results are compared with previous test results subject to interior column, edge column and corner column removal scenarios, based on which a structural design and analysis strategy of normal composite buildings against progressive collapse are recommended in this study. • This paper presents a large-scale experimental study on progressive collapse behavior of 3D composite floor subassembly under the penultimate interior column removal scenario; • Flexural action dominates in resisting progressive collapse of 3D composite floor subassembly after losing the penultimate interior column, which contributes by up to 70% of the total resistances; • Tensile membrane action is found to contribute by around 20% - 25% of the total collapse resistances under the penultimate interior column removal scenario; • The exterior column under the penultimate interior column removal scenario is susceptible to failure by losing stability due to the significant second-order effect; • A structural design and analysis strategy is recommended for normal composite buildings against progressive collapse. [ABSTRACT FROM AUTHOR]

Hyperglycemic stress can directly lead to neuronal damage. The mechanosensitive ion channel PIEZO1 can be activated in response to hyperglycemia, but its role in hyperglycemic neurotoxicity is unclear. The role of PIEZO1 in hyperglycemic neurotoxicity was explored by constructing a hyperglycemic mouse model and a high-glucose HT22 cell model. The results showed that PIEZO1 was significantly upregulated in response to high glucose stress. In vitro experiments have shown that high glucose stress induces changes in neuronal cell morphology and membrane tension, a key mechanism for PIEZO1 activation. In addition, high glucose stress upregulates serum/glucocorticoid-regulated kinase-1 (SGK1) and activates PIEZO1 through the Ca2+ pool and store-operated calcium entry (SOCE). PIEZO1-mediated Ca2+ influx further enhances SGK1 and SOCE, inducing intracellular Ca2+ peaks in neurons. PIEZO1 mediated intracellular Ca2+ elevation leads to calcium/calmodulin-dependent protein kinase 2α (CaMK2α) overactivation, which promotes oxidative stress and apoptosis signalling through p-CaMK2α/ERK/CREB and ox-CaMK2α/MAPK p38/NFκB p65 pathways, subsequently inducing synaptic damage and cognitive impairment in mice. The intron miR-107 of pantothenic kinase 1 (PANK1) is highly expressed in the brain and has been found to target PIEZO1 and SGK1. The PANK1 receptor is activated by peroxisome proliferator-activated receptor α (PPARα), an activator known to upregulate miR-107 levels in the brain. The clinically used lipid-lowering drug bezafibrate, a known PPARα activator, may upregulate miR-107 through the PPARɑ/PANK1 pathway, thereby inhibiting PIEZO1 and improving hyperglycemia-induced neuronal cell damage. This study provides a new idea for the pathogenesis and drug treatment of hyperglycemic neurotoxicity and diabetes-related cognitive dysfunction. [Display omitted] • PIEZO1 is upregulated by hyperglycemia，participates in hyperglycemic neurotoxicity. • Changes in osmotic pressure and membrane tension activate PIEZO1. • SGK1/SOCE/PIEZO1 forms a positive feedback loop, promoting Ca2+ influx. • PIEZO1 regulates CaMK2α signalling and participates in hyperglycemic neurotoxicity. • Bezafibrate inhibits PIEZO1 through the PPARα/PANK1/miR-107 alleviate neurotoxicity. [ABSTRACT FROM AUTHOR]

• A SH0 wave directivity model is proposed to predict the displacement wavefield generated by a rectangular d24 PZT. • The model is validated through multi-physics FE simulation and experiments. • The model can serve as a tool for directivity modelling of rectangular PZT. • A size optimization method is introduced to design the d24 PZT for effectively generating bidirectional SH0 waves. Generating directional guided waves helps to avoid unwanted reflections while providing location information for defects. Bidirectional waves focus wave beams in two opposite directions, which can be applied for generating circumferential zero-order shear horizontal (SH0) waves for large-diameter pipe inspection. In this paper, a novel method for generating bidirectional SH0 waves through size optimization using face-shear (d 24) lead zirconate titanate (PZT) transducer is proposed. A theoretical model is established based on the shear-lag model and the Huygens principle, which describes the generation and propagation of SH0 waves in thin plate by bonded d 24 PZT transducer. The theoretical model is validated by multi-physics finite element (FE) simulation results in terms of SH0 displacement wavefield. Based on the theoretical model, the performance of bidirectional SH0 wave generation is studied. The maximum bidirectional ratio that can be achieved by d 24 PZT within a size range (1–25 mm) under a five-cycle sinusoid tone-burst excitation at a center frequency range (50–300 kHz) is studied. Results show that over 20 dB effect can be achieved at the PZT with a specific aspect ratio. Laboratory experiments are conducted using d 24 PZT transducers at 50–300 kHz to validate the effect of bidirectional wave generation in practical detection scenarios. Experimental results show effects of over 20 dB within a certain frequency range can be achieved when using a PZT with a large aspect ratio, which agree well with the theoretical predictions. [ABSTRACT FROM AUTHOR]

[Display omitted] • Supplement ω3-PUFA can improve LPS induced neuroinflammation and cognitive impairment in mice. • ω3-PUFA enhances the expression of miR-107 in the brain, thereby inhibiting LPS induced PIEZO1 activation and NFκB signal transduction. • PIEZO1 knockdown inhibited LPS induced activation of microglia and astrocytes, as well as the release of pro-inflammatory factors. MiR-107 is reduced in sepsis and associated with inflammation regulation. Dietary supplementation with polyunsaturated fatty acids (ω3-PUFA) can increase the expression of miR-107; this study investigated whether the ω3-PUFA can effectively inhibit neuroinflammation and improve cognitive function by regulating miR-107 in the brain. The LPS-induced mouse model of neuroinflammation and the BV2 cell inflammatory model were used to evaluate the effects of ω3-PUFA on miR-107 expression and inflammation. Intraventricular injection of Agomir and Antagomir was used to modulate miR-107 expression. HE and Nissl staining for analyzing hippocampal neuronal damage, immunofluorescence analysis for glial activation, RT-qPCR, and Western blot were conducted to examine miR-107 expression and inflammation signalling. The result shows that LPS successfully induced the mouse neuroinflammation model and BV2 cell inflammation model. Supplementation of ω3-PUFA effectively reduced the secretion of pro-inflammatory factors TNFα, IL1β, and IL6 induced by LPS, improved cognitive function impairment, and increased miR-107 expression in the brain. Overexpression of miR-107 in the brain inhibited the nuclear factor κB (NFκB) pro-inflammatory signalling pathway by targeting PIEZO1, thus suppressing microglial and astrocyte activation and reducing the release of inflammatory mediators, which alleviated neuroinflammatory damage and improved cognitive function in mice. miR-107, as an intron of PANK1, PANK1 is subject to PPAR α Adjust. ω3-PUFA can activate PPARα, but ω3-PUFA upregulates brain miR-107, and PPARα/PANK1-related pathways may not be synchronized, and further research is needed to confirm the specific mechanism by which ω3-PUFA upregulates miR-107. The miR-107/PIEZO1/NFκB p65 pathway represents a novel mechanism underlying the improvement of neuroinflammation by ω3-PUFA. [ABSTRACT FROM AUTHOR]

Lipid-based liquid crystalline materials are being developed as drug delivery systems. However, the use of these materials for delivery of large macromolecules is currently hindered by the small size of the water channels in these structures limiting control over diffusion behaviour. The addition of the hydration-modulating agent, sucrose stearate, to phytantriol cubic phase under excess water conditions incrementally increased the size of these water channels. Inclusion of oleic acid enabled further control of swelling and de-swelling of the matrix via a pH triggerable system where at low pH the hexagonal phase is present and at higher pH the cubic phase is present. Fine control over the release of various sized model macromolecules is demonstrated, indicating future application to controlled loading and release of large macromolecules such as antibodies. [ABSTRACT FROM AUTHOR]

Due to atmospheric pollution from fossil fuels, the reduction of wind turbine costs, and the rise of the low-carbon economy, wind energy conversion systems have become one of the most significant forms of new energy in China. Therefore, to reduce investment risk and maximize profits, it is necessary to assess wind resources before building large wind farms. This paper develops a comprehensive system containing four steps to evaluate the potential of wind resources at two sites in Xilin Gol League and at additional two sites in Alxa League of Inner Mongolia, China: (1) By calculating the total scores of three indexes, including the effective wind power density (EWPD), wind available time (WAT) and population density (PD), an indexes method is applied to assess the theoretical wind energy potential from 2001 to 2010. (2) To judge the fluctuations in the wind speed, the Fisher optimal partition method and the Jonckheere–Terpstra test are used to analyze the changes in the average monthly and yearly wind speeds from 2001 to 2010. (3) Three probability density functions, i.e., Weibull, Gamma and Lognormal, are used to assess the wind speed frequency distribution in 2010. To enhance the evaluation accuracy, three intelligent optimization parameter estimation algorithms, i.e., the particle swarm optimization algorithm (PSO), differential evolution algorithm (DE) and ant colony algorithm (ACO), are used to estimate the parameters of these distributions. (4) It is helpful to analyze the wind characteristics when assessing wind resources and selecting wind turbines. Therefore, the optimal frequency distribution based on the best parameter estimation method can be chosen to calculate the wind power density, the most probable wind speed and the wind speed carrying the maximum energy. The experimental results show that Site 1 and Site 4 are more suitable for large wind farms than Site 2 or Site 3. [ABSTRACT FROM AUTHOR]

Maintenance of male reproductive function depends on normal sperm generation during which process Sertoli cells play a vital role. Studies found that fine particulate matter (PM) causes decreased male sperm quality, mechanism of which unestablished. We aim to investigate the definite mechanism of PM impairment on male reproduction. Male Sprague-Dawley rats were daily exposed to normal saline (NS) or PM 2.5 with the doses of 9 mg/kg.b.w and 24 mg/kg.b.w. via intratracheal instillation for seven weeks. Reproductive function was tested by mating test and semen analysis after last exposure. Testes were collected to assess changes in histomorphology, and biomarkers including connexin 43 (Cx43), superoxide dismutase (SOD), phosphatidylinositol 3-kinase (PI3K) and phosphorylated protein kinase B (p-Akt). Male rats exposed to PM 2.5 showed noticeable decreased fertility, significantly reduced sperm count, increased sperm abnormality rate and severe testicular damage in histomorphology. After PM 2.5 exposure, the levels of Cx43 was significantly downregulated, and SOD was upregulated and downregulated significantly with different dose, respectively. Protein expression of PI3K and p-Akt dramatically enhanced, and the later one being located in Sertoli cells, the upward or declining trend was in dose dependent. PM 2.5 exposure leads to oxidative stress impairment via PI3K/Akt signaling pathway on male reproduction in rats. [ABSTRACT FROM AUTHOR]

Ethnopharmacological relevance The in vivo effects of traditional herbal medicines are generally mediated by multiple bioactive components. The main constituents of Lotus Plumule are alkaloids such as liensinine, isoliensinine and neferine. In this study, a simple, sensitive, and robust analytical method based on ultra-performance liquid chromatography tandem mass spectrometry (UPLC–MS/MS) has been developed for the determination of the three alkaloids in rat plasma using carbamazepine as internal standard (IS). Materials and Methods After precipitation of the proteins with acetonitrile, chromatography was performed on an Acquity UPLC BEH C18 column (2.1 mm×50 mm, 1.7 μm particle size) using a gradient elution with 0.1% formic acid in water and acetonitrile. Mass spectrometry involved positive electrospray ionization and multiple reaction monitoring (MRM) of the transitions at m / z 611.7→206.2 for liensinine, 611.3→192.2 for isoliensinine, 625.2→206.1 for neferine and m / z 237.1→194.2 for IS. Results The method was linear over the concentration range 5–1000 ng/mL with a lower limit of quantifof 5 ng/mL for each alkaloid. Inter- and intra-day precision (RSD%) were all within 11.4% and the accuracy (RE%) were equal or lower than 10.4%. Recoveries were more than 75.3% and matrix effects were not significant. Stability studies showed that the three alkaloids were stable under a variety of storage conditions. Conclusion The method was successfully applied to a pharmacokinetic study involving intravenous administration of liensinine, isoliensinine and neferine to rats. [ABSTRACT FROM AUTHOR]

As the energy crisis becomes a greater concern, wind energy, as one of the most promising renewable energy resources, becomes more widely used. Thus, wind energy forecasting plays an important role in wind energy utilization, especially wind speed forecasting, which is a vital component of wind energy management. In view of its importance, numerous wind speed forecasts have been proposed, each with advantages and disadvantages. Searching for more effective wind speed forecasts in wind energy management is a challenging task. As proposed, combined models have desirable forecasting abilities for wind speed. This paper reviewed the combined models for wind speed predictions and classified the combined wind speed forecasting approaches. To further study the combined models, two combination models, the no negative constraint theory (NNCT) combination model and the artificial intelligence algorithm combination model, are proposed. The hourly average wind speed data of three wind turbines in the Chengde region of China are used to illustrate the effectiveness of the proposed combination models, and the results show that the proposed combination models can always provide desirable forecasting results compared to the existing traditional combination models. [ABSTRACT FROM AUTHOR]

Thermoresponsive, particle-loaded, Poloxamer 407 (P407)–Pluronic-R® (25R4) or chitosan-methyl cellulose (MC) formulations were developed as single-dose, sustained release vaccines. The sol–gels, loaded either with a particulate vaccine (cubosomes) or soluble antigen (ovalbumin) and adjuvants (Quil A and monophosphoryl lipid A), were free-flowing liquids at room temperature and formed stable gels at physiological temperatures. Rheological results showed that both systems meet the criteria of being thermoresponsive gels. The P407–25R4 sol–gels did not significantly sustain the release of antigen in vivo while the chitosan-MC sol–gels sustained the release of antigen up to at least 14 days after administration. The chitosan-MC sol–gels stimulated both cellular and humoral responses. The inclusion of cubosomes in the sol–gels did not provide a definitive beneficial effect. Further analysis of the formulations with small-angle X-ray scattering (SAXS) revealed that while cubosomes were stable in chitosan-MC gels they were not stable in P407–25R4 formulations. The reason for the mixed response to cubosome-loaded vehicles requires more investigation, however it appears that the cubosomes did not facilitate synchronous vaccine release and may in fact retard release, reducing efficacy in some cases. From these results, chitosan-MC sol–gels show potential as sustained release vaccine delivery systems, as compared to the P407–25R4 system that had a limited ability to sustain antigen release. [ABSTRACT FROM AUTHOR]