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In this paper, unlike many researches that focus on beam splitters based on gratings with symmetrical structures, an asymmetric grating with double-groove structure is proposed. Based on the double-groove grating, multi-port beam splitters including dual-port, three-port, and four-port, under normal incidence working at terahertz frequency are designed for both transverse-electric and transverse-magnetic polarizations. Rigorous couple-wave analysis and simulated annealing algorithm are employed to get the optimal parameters of the grating and accelerate the computing process. For the purpose of understanding the phenomenon of the beam incident, the finite element method is also applied to get the simulation result. It is proven that the proposed beam splitters all present great efficiency and uniformity on the energy distribution. High manufacturing tolerance of the beam splitters is also analyzed, which allows for greater flexibility in the fabrication process. Compared with beam splitters based on single-groove grating, multi-port beam splitters based on double grooves show great performance and universality. [ABSTRACT FROM AUTHOR]

In reality, wind power data are often accompanied by data losses, which can affect the accurate prediction of wind power and subsequently impact the real-time scheduling of the power system. Existing methods for recovering missing data primarily consider the environmental conditions of individual wind farms, thereby overlooking the spatiotemporal correlations between neighboring wind farms, which significantly compromise their recovery effectiveness. In this paper, a joint missing data recovery model based on power data from adjacent wind farms is proposed. At first, a spatial–temporal module (STM) is designed using a combination of graph convolution network and recurrent neural networks to learn spatiotemporal dependencies and similarities. Subsequently, to provide a solid computational foundation for the STM, a Euclidean-directed graph based on Granger causality is constructed to reflect the hidden spatiotemporal information in the data. Finally, comprehensive tests on data recovery for both missing completely at random and short-term continuous missing are conducted on a real-world dataset. The results demonstrate that the proposed model exhibits a significant advantage in missing data recovery compared to baseline models. [ABSTRACT FROM AUTHOR]

Heterogeneous image features are complementary, and feature fusion of heterogeneous images can increase position effectiveness of occluded apple targets. A YOLOfuse apple detection model based on RGB-D heterogeneous image feature fusion is proposed. Combining the CSPDarknet53-Tiny network on the basis of a YOLOv5s backbone network, a two-branch feature extraction network is formed for the extraction task of RGB-D heterogeneous images. The two-branch backbone network is fused to maximize the retention of useful features and reduce the computational effort. A coordinate attention (CA) module is embedded into the backbone network. The Soft-NMS algorithm is introduced, instead of the general NMS algorithm, to reduce the false suppression phenomenon of the algorithm on dense objects and reduce the missed position rate of obscured apples. It indicates that the YOLOfuse model has an AP value of 94.2% and a detection frame rate of 51.761 FPS. Comparing with the YOLOv5 s, m, l, and x4 versions as well as the YOLOv3, YOLOv4, YOLOv4-Tiny, and Faster RCNN on the test set, the results show that the AP value of the proposed model is 0.8, 2.4, 2.5, 2.3, and 2.2 percentage points higher than that of YOLOv5s, YOLOv3, YOLOv4, YOLOv4-Tiny, and Faster RCNN, respectively. Compared with YOLOv5m, YOLOv5l, and YOLOv5x, the speedups of 9.934FPS, 18.45FPS, and 23.159FPS are obtained in the detection frame rate, respectively, and the model are better in both of parameter's number and model size. The YOLOfuse model can effectively fuse RGB-D heterogeneous source image features to efficiently identify apple objects in a natural orchard environment and provide technical support for the vision system of picking robots. [ABSTRACT FROM AUTHOR]

With zeroth-order suppression, a double-groove reflective grating for dual-port reflection beam splitter is studied in this paper. Under normal incidence, the grating obtains great efficiencies for both TE and TM polarizations. The parameters of the double-groove grating are derived using rigorous coupled-wave analysis. The finite element method and the simulated annealing algorithm are also presented to make sure that the ideal parameters are obtained. Total efficiencies of 98.95% for TE polarization and 99.30% for TM polarization are realized at an incidence wavelength of 1550 nm. In the meantime, the efficiencies of TE polarization and TM polarization at ± 1st orders are 48.15% and 46.26%, while at zeroth order, they are being effectively suppressed at 2.41% and 6.56%. The suggested grating has exceptional qualities and performs admirably. [ABSTRACT FROM AUTHOR]

The non-invasive tissue adhesives with strong tissue adhesion and good biocompatibility are ideal for replacing traditional wound treatment methods such as sutures and needles. The self-healing hydrogels based on dynamic reversible crosslinking can recover their structure and function after damage, which is suitable for the application scenario of tissue adhesives. Herein, inspired by mussel adhesive proteins, we propose a facile strategy to achieve an injectable hydrogel (DACS hydrogel) by grafting dopamine (DOPA) onto hyaluronic acid (HA) and mixing it with carboxymethyl chitosan (CMCS) solution. The gelation time and rheological and swelling properties of the hydrogel can be controlled conveniently by adjusting the substitution degree of the catechol group and the concentration of raw materials. More importantly, the hydrogel exhibited rapid and highly efficient self-healing ability and excellent biodegradation and biocompatibility in vitro. Meanwhile, the hydrogel exhibited ~4-fold enhanced wet tissue adhesion strength (21.41 kPa) over the commercial fibrin glue. This kind of HA-based mussel biomimetic self-healing hydrogel is expected to be used as a multifunctional tissue adhesive material. [ABSTRACT FROM AUTHOR]

In heterogeneous image fusion problems, different imaging mechanisms have always existed between time-of-flight and visible light heterogeneous images which are collected by binocular acquisition systems in orchard environments. Determining how to enhance the fusion quality is key to the solution. A shortcoming of the pulse coupled neural network model is that parameters are limited by manual experience settings and cannot be terminated adaptively. The limitations are obvious during the ignition process, and include ignoring the impact of image changes and fluctuations on the results, pixel artifacts, area blurring, and the occurrence of unclear edges. Aiming at these problems, an image fusion method in a pulse coupled neural network transform domain guided by a saliency mechanism is proposed. A non-subsampled shearlet transform is used to decompose the accurately registered image; the time-of-flight low-frequency component, after multiple lighting segmentation using a pulse coupled neural network, is simplified to a first-order Markov situation. The significance function is defined as first-order Markov mutual information to measure the termination condition. A new momentum-driven multi-objective artificial bee colony algorithm is used to optimize the parameters of the link channel feedback term, link strength, and dynamic threshold attenuation factor. The low-frequency components of time-of-flight and color images, after multiple lighting segmentation using a pulse coupled neural network, are fused using the weighted average rule. The high-frequency components are fused using improved bilateral filters. The results show that the proposed algorithm has the best fusion effect on the time-of-flight confidence image and the corresponding visible light image collected in the natural scene, according to nine objective image evaluation indicators. It is suitable for the heterogeneous image fusion of complex orchard environments in natural landscapes. [ABSTRACT FROM AUTHOR]

Background: Social media has become an essential tool to implement risk communication, giving health information could gain more exposure by retweeting during the COVID-19 pandemic. Methods: Content analysis was conducted to scrutinize the official (national and provincial) public health agencies' Weibo posts (n = 4396) to identify features of information sources and message features (structure, style content). The Zero-Inflated Negative Binomial (ZINB) model was adopted to analyze the association between these features and the frequency of the retweeted messages. Results: Results indicated that features of source and health information, such as structure, style, and content, were correlated to retweeting. The results of IRR further suggested that compared to provincial accounts, messages from national health authorities' accounts gained more retweeting. Regarding the information features, messages with hashtags#, picture, video have been retweeted more often than messages without any of these features respectively, while messages with hyperlinks received fewer retweets than messages without hyperlinks. In terms of the information structure, messages with the sentiment (!) have been retweeted more frequently than messages without sentiment. Concerning content, messages containing severity, reassurance, efficacy, and action frame have been retweeted with higher frequency, while messages with uncertainty frames have been retweeted less often. Conclusions: Health organizations and medical professionals should pay close attention to the features of health information sources, structures, style, and content to satisfy the public's information needs and preferences to promote the public's health engagement. Designing suitable information systems and promoting health communication strategies during different pandemic stages may improve public awareness of the COVID-19, alleviate negative emotions, and promote preventive measures to curb the spread of the virus. [ABSTRACT FROM AUTHOR]

The present work investigates the coupling synchronization principle and stability in a vibrating system with two pairs counter-rotating unbalanced rotors (also called exciters). Based on Lagrange equations, the dimensionless coupling differential equations of motion of the system are deduced. The synchronization criterion of two pairs exciters stems from the averaging method, it satisfies the fact that the absolute value of dimensionless residual torque difference between arbitrary two driving motors is less than or equal to the maximum of their dimensionless coupling torques. The stability criterion of the synchronous states complies with Routh-Hurwitz principle. The coupling dynamic characteristics of the system are numerically analyzed in detail, including synchronization and stability ability, maximum of the coupling torque and phase relationship, etc. Some simulation results applying the Runge-Kutta algorithm are performed, it is shown that the motion states of the system can be classified into two types: sub-resonant state and super-resonant state. Generally in engineering, the ideal working points should be selected in sub-resonance region, in this case the expended energy can be saved relatively by 1/5–1/3, which is less than that in super-resonance region under the precondition of the same vibration amplitude value. [ABSTRACT FROM AUTHOR]

Glioblastoma (GB) is the most lethal form of primary brain neoplasm. TMZ is the first-line standard treatment, but the strong resistance constrains the efficacy in clinical use. GB contains glioma stem cells (GSCs), which contribute to TMZ resistance, promote cell survival evolvement, and repopulate the tumor mass. This review summarizes the TMZ-resistance mechanisms and discusses several potential therapies from the conservative opinion of GSC-targeted therapy orientation to the current view of TMZ resistance-aimed efficacy, which will provide an understanding of the role of heterogeneity in drug resistance and improve therapeutic efficacy in general. [ABSTRACT FROM AUTHOR]

[Display omitted] • First, in the field of computerized image analysis and agricultural vision, we propose a pulse coupled neural network orchard heterogeneous image fusion model for semantic segmentation of saliency regions. It effectively improves the accuracy of image segmentation in complex orchard scenes. • Second, we propose an improved DeepLabV3+ (IP-DeeplabV3 +) algorithm. It is incorporated with depth-separable convolution and feature fusion modules to semantically segment the visible image to obtain a mask with semantic information. • Third, we introduce tent chaos and ranking strategies into human mental search (TRHMS) algorithm to optimize the parameter adaption of pulse-coupled neural network for image fusion. • Fourth, four parameters of pulse coupled neural network (PCNN) are optimized through the proposed TRHMS algorithm. • Fifth, through a dual PCNN module, the proposed model improves the quality of heterogeneous source image fusion in complex orchard scenes, and fused images with clear targets and detailed information are obtained. The apple fruits captured from red green and blue (RGB) color camera cannot be accurately identified and localized under natural scenes of orchards due to lighting and shading. We propose a pulse coupled neural network (PCNN) orchard heterogeneous image fusion model for semantic segmentation of saliency regions. The purpose of the model is to improve the accuracy of image segmentation and the quality of heterogeneous source image fusion in complex orchard scenes. The model fuses the time of flight (ToF) and RGB images acquired from orchard scenes. This model consists of an orchard image semantic segmentation module, a parameter optimization module, and a dual PCNN image fusion module. Image semantic segmentation module extracts the significant regions of fruit targets in orchard images. And then, in parameter optimization module, we introduce tent chaos and ranking strategies into human mental search algorithm to optimize the parameters of PCNN model. Finally, we complete the fusion through a dual PCNN module. Six fusion algorithms were used to evaluate the fusion quality of public and self-built datasets. The results showed that the chaotic hierarchical mental search algorithm could better solve the problem of difficult-to-determine PCNN parameters. The improved DeeplabV3 + could also segment clearer and more complete apple regions. Compared with other six fusion algorithms, the fusion experimental results show that the fused images with clearer targets and more prominent textures could be obtained in the proposed model. The proposed model reduces the influence of light and other disturbing factors in fruit recognition. And the fused image contains rich and accurate image information, which is more in line with the perception habit of human eyes. [ABSTRACT FROM AUTHOR]

Parameter optimization of a hydrological model is intrinsically a high dimensional, nonlinear, multivariable, combinatorial optimization problem which involves a set of different objectives. Currently, the assessment of optimization results for the hydrological model is usually made through calculations and comparisons of objective function values of simulated and observed variables. Thus, the proper selection of objective functions' combination for model parameter optimization has an important impact on the hydrological forecasting. There exist various objective functions, and how to analyze and evaluate the objective function combinations for selecting the optimal parameters has not been studied in depth. Therefore, to select the proper objective function combination which can balance the trade-off among various design objectives and achieve the overall best benefit, a simple and convenient framework for the comparison of the influence of different objective function combinations on the optimization results is urgently needed. In this paper, various objective functions related to parameters optimization of hydrological models were collected from the literature and constructed to nine combinations. Then, a selection and evaluation framework of objective functions is proposed for hydrological model parameter optimization, in which a multiobjective artificial bee colony algorithm named RMOABC is employed to optimize the hydrological model and obtain the Pareto optimal solutions. The parameter optimization problem of the Xinanjiang hydrological model was taken as the application case for long-term runoff prediction in the Heihe River basin. Finally, the technique for order preference by similarity to ideal solution (TOPSIS) based on the entropy theory is adapted to sort the Pareto optimal solutions to compare these combinations of objective functions and obtain the comprehensive optimal objective functions' combination. The experiments results demonstrate that the combination 2 of objective functions can provide more comprehensive and reliable dominant options (i.e., parameter sets) for practical hydrological forecasting in the study area. The entropy-based method has been proved that it is effective to analyze and evaluate the performance of different combinations of objective functions and can provide more comprehensive and impersonal decision support for hydrological forecasting. [ABSTRACT FROM AUTHOR]

Protein arginine methylation is a prevalent posttranslational modification and protein arginine methyltransferases 6 (PRMT6) has been identified as a suppressor of TBK1/IRF3 in human and mammals. To explore the role of PRMT6 in teleost fish, PRMT6 homologue of black carp (Mylopharyngodon piceus) has been cloned and characterized in this study. Black carp PRMT6 (bcPRMT6) transcription in host cells varies in response to different stimuli and bcPRMT6 migrates around 43 kDa in the immunoblot assay. Like its mammalian counterpart, bcPRMT6 has been identified to distribute majorly in the nucleus through the immunofluorescent staining assay. bcPRMT6 shows little interferon (IFN) promoter-inducing activity in the reporter assay and bcPRMT6 shows no antiviral activity against either grass carp reovirus (GCRV) or spring viremia of carp virus (SVCV) in plaque assay. When co-expressed with bcPRMT6, the IFN promoter-inducing abilities of black carp TBK1 (bcTBK1) and IRF3/7 (bcIRF3/7) are fiercely attenuated. Accordingly, bcTBK1-mediated antiviral activity in EPC cells is obviously dampened by bcPRMT6. The interaction between bcPRMT6 and bcIRF3/7 has been identified by co-immunoprecipitation assay; however, no direct association between bcPRMT6 and bcTBK1 has been detected. Taken together, our data elucidates for the first time in teleost fish that PRMT6 suppresses TBK1-IRF3/7 signaling during host antiviral innate immune activation. • bcPRMT6 suppresses bcTBK1 and bcIRF3/7 mediated IFN production. • bcPRMT6 inhibits bcTBK1 mediated antiviral activity. • bcPRMT6 interacts with bcIRF3/7, but not with bcTBK1. [ABSTRACT FROM AUTHOR]

Parameter optimization methods for hydrological models have an important impact for the hydrological forecasting. To achieve the parameters' optimization and calibration for the distributed, conceptual watershed Xinanjiang model effectively and accurately, a multi-objective Artificial Bee Colony algorithm named RMOABC which adopts the mechanisms of regulation operator and Adaptive Grid is introduced in the paper. In the evolution of the algorithm, the regulation operator mechanism can balance the weights of local search and global search, and the Adaptive Grid mechanism is utilized to evaluate and maintain the Pareto solutions in the external archive. In the experiments, three commonly used multi-objective optimization algorithms, the NSGA-II, the ε-MOEA and the SMPSO, with the RMOABC algorithm were applied in Heihe River Basin, and the parameter optimization problem of Xinanjiang hydrological model was taken as the application case for long-term runoff prediction to validate and compare their performance. The experiments results showed the RMOABC algorithm can provide more comprehensive and reliable parameters sets for practical hydrological forecasting in the study area with lower execution time. [ABSTRACT FROM AUTHOR]

To improve the accuracy of short-term wind speed and power forecasts as well as reduce the impact of wind power uncertainty on the grid system, this study attempted to use wind speed observations to select the optimal numerical forecasting ensemble members that closely matched the actual wind speed within the forecast window. Those selected ensemble members then formed an optimized ensemble for training and testing machine learning models. Unlike the conventional method that relied solely on ensemble averaging, this method considered the forecast discrepancies among different ensemble members, avoided the introduction of members with large errors, and thus helped to improve wind speed prediction. The optimal number of ensemble members for wind farms with different altitudes and terrains in Henan and Gansu was determined based on the results of ensemble performance and sensitivity experiments. Comparative analyses demonstrated that the ensemble selection forecasts outperformed ensemble averaging in predicting wind speed fluctuations during different weather processes, closely aligning with actual wind speed observations. The sea-level pressure field estimates generated by the ensemble selection method exhibited a higher level of agreement with ERA5 data. Evaluation of wind speed and power prediction over eleven consecutive months in different wind farms showed that the ensemble selection method improved the accuracy of diurnal variation and monthly average wind speed compared to the original ensemble averaging method. Analysis of the observed data of upslope and downslope winds with different durations and speed changes in two wind farms showed that there were the most wind speed changes of 2 -4 m s-1 within 0-2 h and 2-4 h. Compared to ensemble averaging, the ensemble selection method significantly improved the prediction accuracy for these upslope and downslope winds. Furthermore, using the machine learning algorithm to train the optimal selection ensemble can further reduce the absolute deviation and root mean square error of wind speed, thereby effectively improving the accuracy of power prediction. [ABSTRACT FROM AUTHOR]

In order to prepare polyimide (PI) films with a low dielectric constant and excellent comprehensive performance, a two-step method was employed in this study to integrate β-cyclodextrin into a semi-aromatic fluorine-containing polyimide ternary system. By introducing trifluoromethyl groups to reduce the dielectric constant, the dielectric constant was further reduced to 2.55 at 10 MHz. Simultaneously, the film exhibited noteworthy thermal stability (a glass transition temperature exceeding 300 °C) and a high coefficient of thermal expansion. The material also demonstrated outstanding mechanical properties, boasting a strength of 122 MPa and a modulus of 2.2 GPa, along with high optical transparency (transmittance reaching up to 89% at 450 nm). Moreover, the inherent high transparency of colorless polyimide (CPI) combined with good stretchability contributed to the attainment of a low dielectric constant. This strategic approach not only opens up new opportunities for novel electroactive polymers but also holds potential applications in flexible displays, circuit printing, and chip packaging. [ABSTRACT FROM AUTHOR]

The artificial bee colony (ABC) algorithm has become one of the popular optimization metaheuristics and has been proven to perform better than many state-of-the-art algorithms for dealing with complex multiobjective optimization problems. However, the multiobjective artificial bee colony (MOABC) algorithm has not been integrated into the common multiobjective optimization frameworks which provide the integrated environments for understanding, reusing, implementation, and comparison of multiobjective algorithms. Therefore, a unified, flexible, configurable, and user-friendly MOABC algorithm framework is presented which combines a multiobjective ABC algorithm named RMOABC and the multiobjective evolution algorithms (MOEA) framework in this paper. The multiobjective optimization framework aims at the development, experimentation, and study of metaheuristics for solving multiobjective optimization problems. The framework was tested on the Walking Fish Group test suite, and a many-objective water resource planning problem was utilized for verification and application. The experiment’s results showed the framework can deal with practical multiobjective optimization problems more effectively and flexibly, can provide comprehensive and reliable parameters sets, and can complete reference, comparison, and analysis tasks among multiple optimization algorithms. [ABSTRACT FROM AUTHOR]

In order to effectively improve the data transmission efficiency of wireless sensor networks (WSN), a new wireless sensor network chain routing algorithm is proposed based on adaptive backoff-adjusted medium access control. At first, the optimal transmission back-off time of undetermined frames is estimated by the number of active nodes in this algorithm, and the performance evaluation index of WSN is presented with area coverage, transmission distance and residual energy. At the same time, the number of collisions and transmission attempt rate are given with adaptive backoff-adjusted medium access control, and the chain routing algorithm is build. Finally, the key factors influencing the algorithm are deeply studied through experimental platform and numerical simulation with MATLAB. The results show that, compared with the traditional chain routing algorithm and progressive best backoff algorithm, the algorithm has great advantages in terms of chaining efficiency, node life cycle and delay. [ABSTRACT FROM AUTHOR]

Type I interferons (IFN-Is) play an important role in the antiviral immune response in teleost fishes. In this study, one type I interferon (bcIFNb) from black carp ( Mylopharyngodon piceus ) has been cloned and characterized. The full-length cDNA of bcIFNb gene consists of 806 nucleotides and the predicted bcIFNb protein contains 188 amino acids. Basing on the cysteine number and evolutionary position, bcIFNb was classified into group II type I IFN. q-PCR analysis demonstrated that bcIFNb mRNA level varied in vivo and ex vivo in response to different stimuli. bcIFNb was detected in both the whole cell lysate and the supernatant media of HEK293T cells or EPC cells transfected with bcIFNb through immunoblot assay. IFN stimulated genes (ISGs) were greatly upregulated when the host cells were treated with the bcIFNb-containing conditioned media. EPC cells showed greatly enhanced antiviral ability when the cells were transfected with bcIFNb or treated with the bcIFNb-containing conditioned media before GCRV or SVCV infection. Glycosidase digestion analysis determined that bcIFNb was modified with N-linked glycosylation, which occurred on the Asn (N) of 92 site of this cytokine. The un-glycosylated mutant bcIFNb-N92Q presented the similar antiviral ability as that of wild type bcIFNb, which demonstrated that N-linked glycosylation did not contribute directly to the antiviral property of this fish cytokine. [ABSTRACT FROM AUTHOR]

A seven-port division is described via the connecting-slab-based reflective grating in this paper. The rigorous coupled wave analysis (RCWA) and simulated annealing algorithm (SAA) are chosen to analyze and optimize the performance of the grating. The total diffraction efficiency of TE and TM polarization is 96.75% and 95.53%, respectively. Besides, the target grating has good uniformity errors, which are reduced to 3.69% and 1.76% for TE and TM polarization, respectively. The modal method provides a physical explanation for the energy transformations within the target grating. Furthermore, the manufacturing tolerance is discussed for the seven-port division grating. Through analysis and discussion, various performances of the grating can be better demonstrated. Compared with most seven-port grating splitters reported previously, the grating in this paper achieves better diffraction efficiency uniformity and higher efficiency. [ABSTRACT FROM AUTHOR]

Dopamine- and cAMP-regulated phosphoprotein of 32 kDa (DARPP-32) play essential roles in dopamine (DA) transmission in the striatum. It is suggested that a link exists between muscarinic acetylcholine receptors (mAChRs) and DA/DARPP-32 signaling, but the molecular mechanisms mediating this relationship have not been elucidated. The predominant mAChRs subtypes in the striatum are M 1 and M 4 . In this study, we investigated the functions of these two receptors, particularly M 4 , in regulating cAMP production and DARPP-32 phosphorylation in rat striatal medium spiny neurons (MSNs). We used time-resolved fluorescence resonance energy transfer, immunofluorescence confocal microscopy, and western blot assays. In cultured intact MSNs, we confirmed that muscarinic M 1 and M 4 receptors were highly expressed. Notably, M 4 receptors were co-expressed with D 1 receptors in only a portion of the cultured MSNs. The nonselective muscarinic agonist oxotremorine M (OX) slightly enhanced cAMP production, but this effect was independent of M 1 or M 4 receptors. However, OX directly participated in DARPP-32 phosphorylation, phosphorylating DARPP-32 at Thr75 (the CDK5 site) and concomitantly de-phosphorylating DARPP-32 at Thr34 (the PKA site) in virtually cultured MSNs, whereas APO phosphorylated DARPP-32 at both Thr34 and Thr75. The OX-induced time-dependent increase in DARPP-32 phosphorylation at Thr75 was accompanied by increased p35 and CDK5 activity. Specifically, elevated immunoreactivity for phospho-DARPP-32-Thr75 and p35 was detected in M 4 receptor-expressing MSNs. Both genetic knockdown and pharmacologic inhibition of M 4 receptors with MT3, an M 4 receptor-selective antagonist, decreased the OX-induced DARPP-32-Thr75 phosphorylation in MSNs. These results indicate that the M 4 muscarinic receptor plays a critical role in modulating phosphorylation of DARPP-32-Thr75 in MSNs. The results suggest that M 4 receptor activation acts antagonistically with dopamine D 1 -like receptors within the striatum, and indicate that M 4 receptors may be a potential target for the treatment of Parkinson's disease and other relevant central nervous system disorders. [ABSTRACT FROM AUTHOR]

The preparation process of single-atom catalysts (SACs) PtHPCN-222 and the electrocatalytic mechanism of levodopa were shown in the following figure. The hollow-structure porphyrin zirconium-based MOF (HPCN-222) was prepared hydrothermal method, and developed HPCN-222 as support of single Pt atoms to prepare the SACs PtHPCN-222. The SACs PtHPCN-222 modified electrode (PtHPCN-222/GCE) was constructed to explore the electrocatalytic process of levodopa. [Display omitted] • Hollow-structure porphyrin zirconium-based MOF (HPCN-222) was developed as support of single Pt atoms. • The single-atom catalyst PtHPCN-222 was prepared to construct electrochemical sensing platform for levodopa detection. • The PtHPCN-222 exhibited a high specific surface area, high catalytic efficiency, good electrochemical activity and stability. • The PtHPCN-222/GCE sensor shows wide linear range, low detection limit, satisfactory selectivity and reasonable reproducibility. It is always an active research field to search for materials with high catalytic efficiency, and good electrochemical activity and stability to construct electrochemical sensing platform. This work developed a hollow-structure porphyrin zirconium-based MOF (HPCN-222) as support of single Pt atoms to prepare the single-atom catalysts (SACs) PtHPCN-222. The high specific surface area of HPCN-222 provided a large number of anchoring sites for immobilizing single Pt atoms and maximized their atomic utilization. The strong interaction between the support (HPCN-222) and Pt atom made single Pt atom disperse stably, and changed the electronic structure of Pt atom, thus enabling SACs PtHPCN-222 to achieve high catalytic efficiency and good electrochemical activity and stability. With levodopa as model target, the SACs PtHPCN-222 modified electrode (PtHPCN-222/GCE) was constructed to explore its high catalytic efficiency for biomolecules. It was demonstrated that PtHPCN-222/GCE has satisfactory selectivity and reasonable reproducibility for the detection of levodopa. Two linear ranges were obtained and they were 0.1–1.0 μM (R2 = 0.999) and 1–130 μM (R2 = 0.997). The detection limit was 3 nM (S/N = 3) and the sensitivity was 0.1066 μA⋅μM−1. Furthermore, the PtHPCN-222/GCE has reasonable recovery for the analysis of levodopa in human serum and extreme stability after being stored at 4 °C for 150 days, thus providing a highly efficient single-atom catalytic platform for bioanalysis. [ABSTRACT FROM AUTHOR]

The maximum power point tracking (MPPT) methods for the photovoltaic (PV) power system have been considered by the experts in the whole world. A review of different MPPT methods is discussed in this paper. Firstly, the main methods at uniform radiation that will be deliberated are Hill-Climbing (HC), Incremental Conductance (IncCond), Perturbation and Observation (P&O), Fuzzy-Logic (FL), and Neural Network (NN). However, these existing methods have several drawbacks such as slow tracking speed, low tracking efficiency, which fail to extract maximum power at complex partial shading. Then, the more recent MPPT methods at partial shading are discussed to find the best MPPT control strategy, such as the particle swarm optimization (PSO) algorithm, Cuckoo Search (CS) method, and Fibonacci line search scheme, etc. The advantages and shortcomings of abovementioned MPPT methods are compared to find the optimal MPPT during partial shading conditions. It is imagined that this article will be a source of valuable information for PV professionals to keep abreast with the latest progress in the PV power area, as well as for new researchers to get started on MPPT. [ABSTRACT FROM AUTHOR]

We intend to explain the phenomena of voluntary disclosure of a discriminated against characteristic by a worker in the labor market (or a relationship seeker in the relationship market). We assume that there are two types of employers (or relationship targets) – those who discriminate against the characteristic and those who do not – and that the discriminating employers would be less inclined to knowingly hire a discriminated against worker, and would also treat such a worker less favorably after hiring, than the nondiscriminating employers. Beforehand, workers do not know who the discriminating employers are, but a worker with the discriminated against characteristic can avoid the discriminating employers by voluntarily disclosing the characteristic – and he would disclose if the benefit from being more likely to be matched with a nondiscriminating employer exceeds the cost of being more likely to be unemployed. We also analyze the effect on the propensity to disclose from various factors including the constitutions and relative numbers of workers and employers, as well as the treatment gap toward the discriminated against worker by the two types of employers. [ABSTRACT FROM AUTHOR]

It is well known that the fixed pitch vertical axis wind turbine (FP-VAWT) has some disadvantages such as the low start-up torque and inefficient output efficiency. In this paper, the variable pitch vertical axis wind turbine (VP-VAWT) is analyzed to improve the output characteristics of FP-VAWT by discussing the force of the six blade H type vertical axis wind turbine (VAWT) under the stationary and rotating conditions using built the H-type VAWT model. First, the force of single blade at variable pitch and fixed pitch is analyzed, respectively. Then, the resultant force of six blades at different pitch is gained. Finally, a variable pitch control method based on a six blade H type VP-VAWT is proposed, moreover, the technical analysis and simulation results validate that the variable pitch method can improve the start-up torque of VAWT, and increase the utilization efficiency of wind energy, and reduce the blade oscillation, as comparable with that of FP-VAWT. [ABSTRACT FROM AUTHOR]

Aims This study aimed to evaluate the protective effect of licochalcone C against myocardial ischemia/reperfusion injury in rats. Main methods Left ventricular developed pressure (LVDP) and its maximum up/down rate (± dp / dt max ) were recorded as myocardial function. Levels of creatine kinase (CK), lactate dehydrogenase (LDH), malondialdehyde (MDA), superoxide dismutase (SOD), glutathione/glutathione disulfide (GSH/GSSG) ratio, and tumor necrosis factor-alpha (TNF-α) were determined by using enzyme-linked immunosorbent assay. Cell morphology was observed and mitochondrial damage was assessed by HE coloration and transmission electron microscopy, respectively. Cardiomyocyte apoptosis was determined by using terminal deoxynucleotidyl transferased UTP nick-end labeling (TUNEL). Key findings Pretreatment with licochalcone C significantly improved the recovery of LVDP and ± dp / dt max , and increased the levels of SOD and GSH/GSSG ratio. However, pretreatment with licochalcone C not only decreased the TUNEL-positive cell ratio and morphological changes, but also weaken the mitochondrial injury and the levels of CK, LDH, MDA, and TNF-α. Significance These results suggested an important function of licochalcone C extracted from traditional Chinese medicine in the cardioprotection via antioxidant, anti-inflammatory, and anti-apoptotic activities. [ABSTRACT FROM AUTHOR]

First, a novel current calculated (CC) principle is discussed in the study of the characteristics of the photovoltaic (PV) array under partial shading irradiation conditions. In this paper, the particle swarm optimization maximum power point tracking (MPPT) control method integrates with the proposed current calculated method to realize the rapid and accurate tracking efficiency for PV power under partial shading conditions. The proposed CC method is used as a tool to study the effects of partial shading and distribution of multiple peaks. In addition, the combined MPPT method is easy to gain the global peak of multiple PV arrays at complex partial shading. The experimental and simulation results prove the availability as compared with the traditional Perturbation and Observation method. [ABSTRACT FROM AUTHOR]

Ursolic acid (UA), a natural pentacyclic triterpenoid carboxylic acid distributed in medical herbs, exerts antitumor effects and is emerging as a promising compound for cancer prevention and therapy, but its excise mechanisms of action in colon cancer cells remains largely unknown. Here, we identified the molecular mechanisms by which UA inhibited cell proliferation and induced apoptosis in human colon cancer SW480 and LoVo cells. Treatment with UA led to significant inhibitions in cell viability and clone formation and changes in cell morphology and spreading. UA also suppressed colon cancer cell migration by inhibiting MMP9 and upregulating CDH1 expression. Further studies showed that UA inhibited the phosphorylation of Akt and ERK proteins. Pretreatment with an Akt or ERK-specific inhibitor considerably abrogated the proliferation inhibition by UA. UA also significantly inhibited colon cancer cell COX-2 expression and PGE2 production. Pretreatment with a COX-2 inhibitor (celecoxib) abrogated the UA-induced cell proliferation. Moreover, we found that UA effectively promoted NF-κB and p300 translocation from cell nuclei to cytoplasm, and attenuated the p300-mediated acetylation of NF-κB and CREB2. Pretreatment with a p300 inhibitor (roscovitine) abrogated the UA-induced cell proliferation, which is reversed by p300 overexpression. Furthermore, UA treatment induced colon cancer cell apoptosis, increased the cleavage of PARP, caspase-3 and 9, and trigged the release of cytochrome c from mitochondrial inter-membrane space into cytosol. These results indicate that UA inhibits cell proliferation and induces apoptosis in colon cancer cells through simultaneous modulation of the multiple signaling pathways such as MMP9/CDH1, Akt/ERK, COX-2/PGE2, p300/NF-κB/CREB2, and cytochrome c/caspase pathways. [ABSTRACT FROM AUTHOR]

Abstract: Background: Although short-term exposure to ambient particulate matter has increasingly been linked with cardiovascular diseases, it is not quite clear how physical characteristics of particles, such as particle size may be responsible for the association. This study aimed at investigating whether daily changes in number or mass concentrations of accurately size-segregated particles in the range of 3nm–10μm are associated with daily cardiovascular emergency room visits in Beijing, China. Methods: Cardiovascular emergency room visit counts, particle size distribution data, and meteorological data were collected from Mar. 2004 to Dec. 2006. Particle size distribution data was used to calculate particle number concentration in different size fractions, which were then converted to particle mass concentration assuming spherical particles. We applied a time-series analysis approach. We evaluated lagged associations between cardiovascular emergency room visits and particulate number and mass concentration using distributed lag non-linear models up to lag 10. We calculated percentage changes of cardiovascular emergency room visits, together with 95% confidence intervals (CI), in association with an interquartile range (IQR, difference between the third and first quartile) increase of 11-day or 2-day moving average number or mass concentration of particulate matter within each size fraction, assuming linear effects. We put interaction terms between season and 11-day or 2-day average particulate concentration in the models to estimate the modification of the particle effects by season. Results: We observed delayed associations between number concentration of ultrafine particles and cardiovascular emergency room visits, mainly from lag 4 to lag 10, mostly contributed by 10–30nm and 30–50nm particles. An IQR (9040cm−3) increase in 11-day average number concentration of ultrafine particles was associated with a 7.2% (1.1–13.7%) increase in total, and a 7.9% (0.5–15.9%) increase in severe cardiovascular emergency room visits. The delayed effects of particulate mass concentration were small. Regarding immediate effects, 2-day average number concentration of Aitken mode (30–100nm) particles had strongest effects. An IQR (2269cm−3) increase in 2-day average number concentration of 30–50nm particles led to a 2.4% (−1.5–6.5%) increase in total, and a 1.7% (−2.9–6.5%) increase in severe cardiovascular emergency room visits. The immediate effects of mass concentration came mainly from 1000–2500nm particles. An IQR (11.7μgm−3) increase in 2-day average mass concentration of 1000–2500nm particles led to an around 2.4% (0.4–4.4%) increase in total, and a 1.7% (−0.8–4.2%) increase in severe cardiovascular emergency room visits. The lagged effect curves of number and mass concentrations of 100–300nm particles or 300–1000nm particles were quite similar, indicating that using particulate number or mass concentrations seemed not to affect the cardiovascular effect (of particles within one size fraction). The effects of number concentration of ultrafine particles, sub-micrometer particles (3–1000nm) and 10–30nm particles were substantially higher in winter comparing with in summer. Conclusions: Elevated concentration levels of sub-micrometer particles were associated with increased cardiovascular morbidity. Ultrafine particles showed delayed effects, while accumulation mode (100–1000nm) particles showed immediate effects. Using number or mass concentrations did not affect the particle effects. [Copyright &y& Elsevier]

This paper studies how to infer the rate of pure time preference (ρ) from the Ramsey Rule when multiple asset returns exist due to uncertainty. Using a Generalized Uncertainty Ramsey Rule derived from a model that separates intertemporal substitution and risk aversion, we find that the U.S. historical data on consumption growth and asset returns imply that (i) for the reciprocal of the elasticity of intertemporal substitution less than or equal to one, ρ lies within ±1% from zero for a plausible range of the coefficient of relative risk aversion; and (ii) for the larger reciprocal of the elasticity of intertemporal substitution, ρ tends to be negative. These results contradict the widely-held belief in the environmental economics literature that the inferred ρ must be significantly larger than zero and suggest that it is appropriate to use ρ =0 as a benchmark for economic analysis of environmental policies. [Copyright &y& Elsevier]

Abstract: Background: While the link between particulate matter and cardiovascular mortality is well established, it is not fully investigated and understood which properties of the aerosol might be responsible for the health effects, especially in polluted mega-city areas. Objectives: Our goal was to explore the association between daily cardiovascular mortality and different particle metrics in the sub-micrometer range in Beijing, China. Methods: We obtained daily counts of cause-specific cardiovascular deaths in the Beijing urban area for the period March 2004 to August 2005. Concurrently, continuous measurements of particle number size distributions were performed. Particle number concentrations (NC) between 0.003μm and 0.8μm were converted to particle mass and surface area concentrations assuming spherical particles. Semi-parametric Poisson regression models adjusting for trend, seasonality, day of the week, and meteorology were used to estimate immediate, delayed and cumulative particle effects. Additionally, effect modification by air mass origin was investigated. Results: We observed associations between daily cardiovascular mortality and particle NC for a 2-days delay. Moreover, nearly all particle metrics showed 2-days delayed associations with ischemic heart disease mortality. The strongest association was found for particle NC in the size range 0.03–0.1μm (7.1% increase in daily mortality with a 95%-confidence interval of 2.9%–11.5%, per an increase of 6250particles/cm3). Results for surface and mass concentrations with a lag of two days indicated effect modification by air mass origin, whereas effects of particle NC were not modified. Conclusions: Results show an elevated risk of cardiovascular mortality in Beijing from short-term exposure to particulate air pollution in the sub-micrometer range. Results also indicate that locally produced smaller particles and regionally transported particles may exhibit different effects in Beijing. [Copyright &y& Elsevier]

Abstract: In this paper college admissions are based on test scores and students can exert two types of effort: real learning and exam preparation. The former improves skills but the latter is more effective in raising test scores. In this setting the students with the lowest skills are no longer the ones with the lowest aptitude, but instead are the ones closest to the borderline for college admission. Increased access to college leads to greater income inequality between college graduates and non-graduates. Overall, the ability to study for the test leads to higher expected test scores but lower skills. [Copyright &y& Elsevier]

Background: Associations between air temperature and mortality have been consistently observed in Europe and the United States; however, there is a lack of studies for Asian countries. Our study investigated the association between air temperature and cardio-respiratory mortality in the urban area of Beijing, China. Methods: Death counts for cardiovascular and respiratory diseases for adult residents (≥15 years), meteorological parameters and concentrations of particulate air pollution were obtained from January 2003 to August 2005. The effects of two-day and 15-day average temperatures were estimated by Poisson regression models, controlling for time trend, relative humidity and other confounders if necessary. Effects were explored for warm (April to September) and cold periods (October to March) separately. The lagged effects of daily temperature were investigated by polynomial distributed lag (PDL) models. Results: We observed a J-shaped exposure-response function only for 15-day average temperature and respiratory mortality in the warm period, with 21.3°C as the threshold temperature. All other exposure-response functions could be considered as linear. In the warm period, a 5°C increase of two-day average temperature was associated with a RR of 1.098 (95% confidence interval (95%CI): 1.057-1.140) for cardiovascular and 1.134 (95%CI: 1.050-1.224) for respiratory mortality; a 5°C decrease of 15-day average temperature was associated with a RR of 1.040 (95%CI: 0.990-1.093) for cardiovascular mortality. In the cold period, a 5°C increase of two-day average temperature was associated with a RR of 1.149 (95%CI: 1.078-1.224) for respiratory mortality; a 5°C decrease of 15-day average temperature was associated with a RR of 1.057 (95%CI: 1.022-1.094) for cardiovascular mortality. The effects remained robust after considering particles as additional confounders. Conclusions: Both increases and decreases in air temperature are associated with an increased risk of cardiovascular mortality. The effects of heat were immediate while the ones of cold became predominant with longer time lags. Increases in air temperature are also associated with an immediate increased risk of respiratory mortality. [ABSTRACT FROM AUTHOR]

Abstract: The Alchian–Allen theorem of “shipping the good apples out” (the AA theorem) is based on a law of relative demand which states that as the price ratio of one good to another becomes larger, the demand for the former good becomes smaller relative to the demand for the latter good. However, both the AA theorem and the law of relative demand have only been discussed in the context where a commodity group has just two quality-differentiable versions. This paper defines relative demands and investigates their properties for the more general situation where a commodity group consists of more than two similar but quality-differentiable brands. The results obtained extend the AA theorem and the law of relative demand. [ABSTRACT FROM AUTHOR]

This article develops a two-country monetary economy model in order to analyze the international monetary policy game between governments and the domestic monetary policy game between each government and its private sector. We prove that if governments can commit to their own private sectors, the cooperative equilibrium of the game between governments is for them to follow the Friedman rule. When governments lack such ability to commit, we find that the Friedman rule is more likely to be sustained in our open-economy model than in the closed-economy model of Ireland. ( JEL E31, E52, E61) [ABSTRACT FROM AUTHOR]

Using an overlapping generations model with endogenous but uncertain longevity, this article analyzes the effects of public old-age pensions on longevity choice and capital accumulation. When agents are not altruistic, increases in old-age pensions are longevity-neutral for golden rule economies and longevity-decreasing if interest rates exceed population growth, and saving effects are strictly negative. When agents are altruistic, longevity is independent of old-age pensions regardless of the interest rate-population growth relation. On the other hand, the longevity effect of a price subsidy on longevity extending expenditures or an advance in longevity extending technology is positive. [ABSTRACT FROM AUTHOR]

The tumor suppressor PTEN mainly inhibits the PI3K/Akt pathway in the cytoplasm and maintains DNA stability in the nucleus. The status of PTEN remains therapeutic effectiveness for chemoresistance of the DNA alkylating agent temozolomide (TMZ) in glioblastoma (GB). However, the underlying mechanisms of PTEN's interconnected role in the cytoplasm and nucleus in TMZ resistance are still unclear. In this study, we report that TMZ-induced PTEN nuclear import depends on PTEN ubiquitylation modification by Smurf1. The Smurf1 suppression decreases the TMZ-induced PTEN nuclear translocation and enhances the DNA damage. In addition, Smurf1 degrades cytoplasmic PTEN K289E (the nuclear-import-deficient PTEN mutant) to activate the PI3K/Akt pathway under TMZ treatment. Altogether, Smurf1 interconnectedly promotes PTEN nuclear function (DNA repair) and cytoplasmic function (activation of PI3K/Akt pathway) to resist TMZ. These results provide a proof-of-concept demonstration for a potential strategy to overcome the TMZ resistance in PTEN wild-type GB patients by targeting Smurf1. [ABSTRACT FROM AUTHOR]

[Display omitted] • Cyclodextrin was successfully covalently grafted to the surface of titanium dioxide. • Introduction of cyclodextrin improved the photocatalytic performance of titanium dioxide. • This modification increased the degradation efficiency of methyl bromide by 2.7 times. A photocatalytic system based on the cooperative effect of β-cyclodextrin (β-CD) was established. Here, β-CDs were covalently grafted onto the surface of TiO 2 nanoparticles through hexamethylene diisocyanate bonds. The structure and photocatalytic properties of the resulting photocatalysts were characterized by various analytical methods. This modification resulted in a 2.7-fold improvement in the degradation efficiency of the pure TiO 2 for methylene blue (MB) and showed good stability in cyclic degradation experiments. [ABSTRACT FROM AUTHOR]

The central nervous system (CNS) is the most delicate system in human body, with the most complex structure and function. It is vulnerable to trauma, infection, neurodegeneration and autoimmune diseases, and activates the immune system. An appropriate inflammatory response contributes to defence against invading microbes, whereas an excessive inflammatory response can aggravate tissue damage. The NLRP3 inflammasome was the first one studied in the brain. Once primed and activated, it completes the assembly of inflammasome (sensor NLRP3, adaptor ASC, and effector caspase-1), leading to caspase-1 activation and increased release of downstream inflammatory cytokines, as well as to pyroptosis. Cumulative studies have confirmed that NLRP3 plays an important role in regulating innate immunity and autoimmune diseases, and its inhibitors have shown good efficacy in animal models of various inflammatory diseases. In this review, we will briefly discuss the biological characteristics of NLRP3 inflammasome, summarize the recent advances and clinical impact of the NLRP3 inflammasome in infectious, inflammatory, immune, degenerative, genetic, and vascular diseases of CNS, and discuss the potential and challenges of NLRP3 as a therapeutic target for CNS diseases. [ABSTRACT FROM AUTHOR]

• Lung cancer (LC) mortality is still high in Xuanwei at present. • Delayed effect of indoor air pollution is still the major risk factor for LC. • The effect of tobacco use on LC gradually becomes more apparent. • In areas never used smoky coal, tobacco use was the main cause of LC. Indoor air pollution emitted by smoky coal combustion in unventilated fire pits used to cause high lung cancer mortality in Xuanwei. Stove improvements were implemented from the 1970s to the 1980s. However, the present lung cancer mortality rate in Xuanwei shows almost no significant declining trend. Tobacco use is another established risk factor for lung cancer. Smoking prevalence and secondhand smoke (SHS) exposure rate are both high in Xuanwei. Therefore, in this study we evaluated the relationship among indoor air pollution over 30 years ago, tobacco use, and lung cancer risk, to further explore the competitive effects of these two risk factors. A case-control study design was used. We constructed an unconditional logistic regression model to evaluate the relationship among indoor air pollution, tobacco use, and lung cancer risk, adjusting the covariates and with an interactive term between the two key variables. We further quantitatively assessed the maximum decrease in the indoor air pollution effect when facing competition from tobacco use via a sensitivity analysis. First, the effect of indoor air pollution on lung cancer without considering tobacco use was estimated. Then, we calculated a "bias factor" and divided the effect estimation by this factor. We found a strong delayed effect of indoor air pollution over 30 years ago in each subgroup with different tobacco use history. The effects of tobacco use were relatively small, but in areas without smoky coal combustion and indoor air pollution over 30 years prior, the lung cancer risk caused by tobacco use became much stronger and statistically significant. Moreover, we assessed that the effects of tobacco use on lung cancer could reduce a maximum of 18%-30% of the effects of indoor air pollution, but did not influence their statistical significance; the competitive effect from ever smoking was stronger than that from SHS exposure. At present in Xuanwei, delayed effect of the indoor air pollution over 30 years ago remains the major risk factor for lung cancer. Concomitantly, the adverse effect of tobacco use on lung cancer is becoming more apparent; local governments should start considering public health activities for smoking cessation promotion and SHS exposure prevention. [ABSTRACT FROM AUTHOR]

This paper proposes an improved Harmony Search algorithm, and gives the definition of the Global Sharing Factor of the Harmony Search (HS) algorithm. In the definition, the number of creations of the HS algorithm is applied to the sharing factor and calculated. In this algorithm, the natural harmony encoding method is used to encode the initial harmony, and the total path length of all vehicles is taken as the optimization objective function. A new harmony generation strategy is proposed as follows: each tone component in an evolution is calculated separately using the new learning strategy and update strategy. In the calculation process, the tone component is judged by whether it needs to be adjusted according to the adjustment strategy. In this way, the problems of singularity and randomness of the new harmony generation strategy of basic HS are solved to improve the diversity of algorithm solutions. Then, a new Harmony Search method with Global Sharing Factor based on natural number coding and decoding for the Vehicle Routing Problem (GSF-HS-VRP) is proposed. The improved Global Sharing Factor-Harmony Search-Vehicle Routing Problem (GSF-HS-VRP) algorithm is applied to capacity-limited vehicle path optimization problems compared with the HS, Improved Harmony Search (IHS), Global-best Harmony Search (GHS), and Self-adaptive Global Best Harmony Search (SGHS) algorithms. The small-scale data and Solomon examples were adopted as the experimental data. Compared with the other four algorithms, the GSF-HS-VRP algorithm has the shortest running time, more rapid convergence speed, and higher efficiency. In the multi-vehicle test, with the increase of the number of vehicles, the optimized path of the vehicle is more satisfied in relation to the actual needs of customers. The results showed that this method could effectively improve the optimization performance of the capacity-limited vehicle routing problem. [ABSTRACT FROM AUTHOR]

Interferon regulated factor 5 (IRF5) is a key regulator of inflammatory responses in human and mammals; however, its role in teleost remains largely unknown. In this study, IRF5 homologue of black carp (Mylopharyngodon piceus) has been cloned and characterized, which possesses conservation in structure and sequence to its mammalian counterparts. Black carp IRF5 (bcIRF5) was characterized as a predominantly cytosolic protein by immunofluorescent staining and showed little IFN promoter-inducing ability in reporter assay. The direct association between bcIRF5 and black carp TBK1 (bcTBK1) were identified through co-immunoprecipitation assay, and co-expressed bcIRF5 in EPC cells suppressed bcTBK1-mediated IFN promoter transcription in reporter assay. Surprisingly, the titer of grass carp reovirus (GCRV) in the media of EPC cells co-expressing bcIRF5 and bcTBK1 was obviously lower than that of EPC cells expressing bcTBK1 alone. It was interesting that expression of bcIRF5 and/or bcTBK1 in EPC cells showed little effect on cell growth; however, the survival ratio of EPC cells co-expressing bcTBK1 and bcIRF5 post GCRV infection was much lower than that of EPC cells expressing bcIRF5 or bcTBK1 alone. These results indicate that bcIRF5 negatively regulates bcTBK1-mediated IFN signaling in healthy cells; however, it correlates with bcTBK1 and triggers cell death to inhibit the virus replication during the innate immune activation. • bcIRF5 interacts with bcTBK1. • bcIRF5 inhibits bcTBK1-mediated IFN signaling in healthy cells. • bcIRF5 correlates with bcTBK1 to trigger cell death to inhibit the virus replication after virus infection. [ABSTRACT FROM AUTHOR]

In a recent publication in the journal Science of the Total Environment, Die Fang et al. (2016) reported health effects of current ambient PM 2.5 (particulate matters with aerodynamic diameters < 2.5 μm) pollution in 74 leading cities in China. It is a meaningful original study using the latest air quality surveillance data. However, we suppose their results may over-estimate the long-term exposure-response coefficients for per 10 μg/m 3 increase in PM 2.5 concentration. Moreover, we have concern about the linear relationship the authors assumed for long-term exposure to PM 2.5 and the health outcomes. We also have concern about the sufficiency of confounder adjustment. Our suggestions are mainly based on our previous research experience and previous literature. We believe that the debate is conducive to a more accurate and more reasonable estimation of the health effects of PM 2.5 . [ABSTRACT FROM AUTHOR]

In this paper, molecular dynamics (MD) simulation has been applied to study the influence of water medium on the nano-cutting process and the evolution of sub-surface defects of single-crystal γ-TiAl alloy. The effect of water medium in the result of cutting force and cutting temperature have been analysed and discussed in the machining process, while the function of common neighbour analysis (CNA) method has been used to research the chip removal mechanism, sub-surface defects and crystal structure changes. The results showed that the extrusion and shear effects of tool removed atoms from the surface of the workpiece. In the meantime, the cooling and lubricating effect of the water medium reduces the cutting temperature and cutting force. Especially, the temperature of the workpiece has a diffusion effect in the cutting process in the absence of the water medium. Some heat was taken away by the water medium, which lead to insufficient nucleation and migration of the dislocation, and high compressive stress was formed during cutting of water-bearing medium. [ABSTRACT FROM AUTHOR]

This article presents a model predictive control (MPC) coupled with an artificial potential field (APF) to resolve the trajectory tracking while considering the obstacle avoidance. In this article, the obstacle avoidance problem is solved by a local path planning based on the artificial potential field by constructing a virtual goal. A virtual goal is generated to produce an attractive force to guide the mobile robot to a collision-free space. The planned path is controlled by a proportional–integral–derivative (PID) controller to avoid collision. After arriving at the virtual goal, an off-line explicit MPC is calculated to obtain the optimal control inputs to track the reference trajectory. The simulation results show that the proposed method can be applied to control the mobile robot in the environment with one obstacle. [ABSTRACT FROM AUTHOR]

Accurate and complete digital elevation models (DEMs) play an important fundamental role in geospatial analysis, supporting various engineering applications, human activities, and scientific research. Interferometric synthetic aperture radar (InSAR) plays an increasingly important role in DEM generation. Nonetheless, owing to its inherent characteristics, gaps often appear in regions marked by significant topographical fluctuations, necessitating an extra void-filling process. Traditional void-filling methods have operated directly on preexisting data, succeeding in relatively flat terrain. When facing mountainous regions, there will always be gross errors in elevation values. Regrettably, conventional methods have often disregarded this vital consideration. To this end, this research proposes a DEM void-filling method based on incorporating elevation outlier detection. It accounts for the detection and removal of elevation outliers, thereby mitigating the shortcomings of existing methods and ensuring robust DEM restoration in mountainous terrains. Experiments were conducted to validate the method applicability using TanDEM-X data from Sichuan, China, Hebei, China, and Oregon, America. The results underscore the superiority of the proposed method. Three traditional methods are selected for comparison. The proposed method has different degrees of improvement in filling accuracy, depending on the void status of the local terrain. Compared with the delta surface fill (DSF) method, the root mean squared error (RMSE) of the filling results has improved by 7.87% to 51.87%. The qualitative and quantitative experiments demonstrate that the proposed method is promising for large-scale DEM void-filling tasks. [ABSTRACT FROM AUTHOR]

Identifying the sequence pattern in the radiation mutagenesis is essential for understanding the DNA molecular evolution. The present study aimed to establish an in vitro radiation mutagenesis model using naked DNA and to discover the sequence pattern of radiation-induced mutations. Human immunoglobulin heavy-chain variable region gene HVB was chosen as the targeted sequence. DNA molecules dissolved in water were irradiated with gamma rays (25Gy, 1 Gy/min), and four polymerases with different fidelity were used respectively for amplification. Ultra-sensitive next generation sequencing platform "EasyMF" was then employed to detect the mutation rate of all sites. Statistical analysis was performed using SAS9.4 with alpha 0.05. The main result of this study consisted of two parts. One was comparing of the effects of polymerase with different fidelity on ionizing radiation mutagenesis and establishing the in vitro model. Low fidelity DNA polymerases, Taq and Platinum® Taq DNA polymerase, could display the effects of radiation mutagenesis. However, due to the high error rate of Taq DNA polymerase, Platinum® Taq DNA polymerase was more suitable for studying the sequence pattern of radiation mutagenesis. Another was that mutation rates of individual nucleotides G, C and its doublet combination were significantly higher after radiation treatment. Our findings suggest the fidelity of polymerase could affect the radiation mutagenesis. The nucleotides of G, C and their doublet combination showed higher radiation mutability. The sequence analysis of the radiation-induced mutation was helpful for the study of the evolution of DNA molecules under radiation. In addition, the comparisons of the polymerases was helpful to understand the role of the polymerase in the DNA damage repair. • The in vitro radiation mutagenesis model using naked DNA was established. • Low fidelity DNA polymerases, Taq and Platinum® Taq DNA polymerase, could display the effects of radiation mutagenesis. • The nucleotides of G, C and their doublet combination showed higher radiation mutability. [ABSTRACT FROM AUTHOR]

In this paper, a triple-layer grating beam splitter with three-port output is designed. Through the combination of rigorous coupled-wave analysis (RCWA) and simulated annealing algorithms (SAA), the calculation and optimization of each parameter of the grating is carried out to make the diffraction efficiency of the grating meet the conditions. At the incident wavelength of 800 nm, the diffraction efficiencies of 0th order and ±1st order under TE polarization are 31.6% and 31.4%, respectively. The diffraction efficiencies of 0th order and ±1st order under TM polarization are 32.7% and 32.5%, respectively. It can be seen that not only the total diffraction efficiency under TE polarization and TM polarization exceeds 90%, but also the uniformity of diffraction efficiency at each order exceeds 99%. Finally, the influence of grating parameters and incident wave characteristics on diffraction efficiency is discussed. [ABSTRACT FROM AUTHOR]

Aiming at the low recognition effect of apple images captured in a natural scene, and the problem that the OTSU algorithm has a single threshold, lack of adaptability, easily caused noise interference, and over-segmentation, an apple image recognition multi-objective method based on the adaptive harmony search algorithm with simulation and creation is proposed in this paper. The new adaptive harmony search algorithm with simulation and creation expands the search space to maintain the diversity of the solution and accelerates the convergence of the algorithm. In the search process, the harmony tone simulation operator is used to make each harmony tone evolve towards the optimal harmony individual direction to ensure the global search ability of the algorithm. Despite no improvement in the evolution, the harmony tone creation operator is used to make each harmony tone to stay away from the current optimal harmony individual for extending the search space to maintain the diversity of solutions. The adaptive factor of the harmony tone was used to restrain random searching of the two operators to accelerate the convergence ability of the algorithm. The multi-objective optimization recognition method transforms the apple image recognition problem collected in the natural scene into a multi-objective optimization problem, and uses the new adaptive harmony search algorithm with simulation and creation as the image threshold search strategy. The maximum class variance and maximum entropy are chosen as the objective functions of the multi-objective optimization problem. Compared with HS, HIS, GHS, and SGHS algorithms, the experimental results showed that the improved algorithm has higher a convergence speed and accuracy, and maintains optimal performance in high-dimensional, large-scale harmony memory. The proposed multi-objective optimization recognition method obtains a set of non-dominated threshold solution sets, which is more flexible than the OTSU algorithm in the opportunity of threshold selection. The selected threshold has better adaptive characteristics and has good image segmentation results. [ABSTRACT FROM AUTHOR]

Edge computing is a promising paradigm to provide computing capabilities in close proximity to mobile devices in fifth-generation (5G) networks. However, most wireless sensor devices connected to the 5G network have limited battery life, and how to effectively reduce energy consumption and extend the network life cycle has become one of the hot problems in current research. Due to this motivation, an improved Stable Election Protocol (SEP), named Lightweight in Edge Computing-SEP (LEC-SEP) is proposed. LEC-SEP algorithm considers the heterogeneity of the initial energy of the nodes and the cluster head election is determined by the probability that the relative level of the initial energy and the residual energy. According to the influence of the number of cluster heads, the optimal clustering number is calculated to balance the network traffic. At the same time, the location of the base station is redefined to facilitate adding the edge server, which can store the data aggregated and fused by base station, providing powerful and real-time storage and computing power to effectively offload the pressure of the central cloud. The simulation results show that the energy consumption is well distributed in the proposed algorithm, and LEC-SEP algorithm achieves a longer stabilization period in the network than other typical clustering algorithms. The network life of LEC-SEP improved by 8.17% and 20.34% in comparison with the P-SEP algorithm and the IDEEC algorithm respectively. [ABSTRACT FROM AUTHOR]

One of the most challenging issues in HIV-associated neurocognitive disorders (HAND) caused by HIV-1 virotoxins and drug abuse is the lack of understanding the underlying mechanisms that are commonly associated with disorders of the blood-brain barrier (BBB), which mainly consists of brain microvascular endothelial cells (BMEC). Here, we hypothesized that Glycoprotein 120 (gp120), methamphetamine (METH) and nicotine (NT) can enhance amyloid-beta (Aβ) accumulation in BMEC through Alpha7 nicotinic acetylcholine receptor (α7 nAChR). Both in vitro (human BMEC) (HBMEC) and in vivo (mice) models of BBB were used to dissect the role of α7 nAChR in up-regulation of Aβ induced by gp120, METH and NT. Aβ release from and transport across HBMEC were significantly increased by these factors. Methyllycaconitine (MLA), an antagonist of α7 nAChR, could efficiently block these pathogenic effects. Furthermore, our animal data showed that these factors could significantly increase the levels of Aβ, Tau and Ubiquitin C-Terminal Hydrolase L1 (UCHL1) in mouse cerebrospinal fluid (CSF) and Aβ in the mouse brains. These pathogenicities were significantly reduced by MLA, suggesting that α7 nAChR may play an important role in neuropathology caused by gp120, METH and NT, which are the major pathogenic factors contributing to the pathogenesis of HAND. [ABSTRACT FROM AUTHOR]