UAV Online Path Planning Algorithm in a Low Altitude Dangerous Environment

UAV online path-planning in a low altitude dangerous environment with dense obstacles, static threats (STs) and dynamic threats (DTs), is a complicated, dynamic, uncertain and real-time problem. We propose a novel method to solve the problem to get a feasible and safe path. Firstly STs are modeled based on intuitionistic fuzzy set (IFS) to express the uncertainties in STs. The methods for ST assessment and synthesizing are presented. A reachability set (RS) estimator of DT is developed based on rapidly-exploring random tree (RRT) to predict the threat of DT. Secondly a subgoal selector is proposed and integrated into the planning system to decrease the cost of planning, accelerate the path searching and reduce threats on a path. Receding horizon (RH) is introduced to solve the online path planning problem in a dynamic and partially unknown environment. A local path planner is constructed by improving dynamic domain rapidly-exploring random tree (DDRRT) to deal with complex obstacles. RRT∗ is embedded into the planner to optimize paths. The results of Monte Carlo simulation comparing the traditional methods prove that our algorithm behaves well on online path planning with high successful penetration probability. © 2014 Chinese Association of Automation.

Identification of botanical origin of Chinese unifloral honeys by free amino acid profiles and chemometric methods

The amino acid contents of five floral sources Chinese honeys(jujube, rape, chaste, acacia, and lungan) were measured using reversed phase high-performance liquid chromatography(RP-HPLC). The results showed that proline was the main amino acid in most of the analyzed samples. Phenylalanine presents at the highest content in chaste honey samples, and the total amino acid contents of chaste honeys were also significantly higher than those of other honey samples. Based on the amino acid contents, honey samples were classified using chemometric methods(cluster analysis(CA), principal component analysis(PCA), and discriminant analysis(DA)). According to the CA results, chaste honeys could be separated from other honeys, while the remaining samples were correctly grouped together when the chaste honey data were excluded. By using DA, the overall correct classification rate reached 100%. The results revealed that amino acid contents could potentially be used as indicators to identify the botanical origin of unifloral honeys.

Algorithm Research on Moving Object Detection of Surveillance Video Sequence

In video surveillance, there are many interference factors such as target changes, complex scenes, and target deformation in the moving object tracking. In order to resolve this issue, based on the comparative analysis of several common moving object detection methods, a moving object detection and recognition algorithm combined frame difference with background subtraction is presented in this paper. In the algorithm, we first calculate the average of the values of the gray of the continuous multi-frame image in the dynamic image, and then get background image obtained by the statistical average of the continuous image sequence, that is, the continuous interception of the N-frame images are summed, and find the average. In this case, weight of object information has been increasing, and also restrains the static background. Eventually the motion detection image contains both the target contour and more target information of the target contour point from the background image, so as to achieve separating the moving target from the image. The simulation results show the effectiveness of the proposed algorithm.

Endothelin-3 and glial fibrillary acidic protein expression in the frontal and parietal cortex of type-2 diabetic mice following ischemia-reperfusion injury

BACKGROUND： Patients with type-2 diabetes mellitus exhibit higher levels of plasma endothelin-1 （ET-1）. However, very few reports exist regarding altered endothelin-3 （ET-3） and ET-1 concentrations in brain tissue. OBJECTIVE： To observe expression changes of ET-3 and glial fibrillary acidic protein （GFAP） in the frontal and parietal cortex of type-2 diabetic mice following ischemia-reperfusion injury, with various reperfusion durations. DESIGN, TIME AND SETTING： Randomized controlled animal study. The experiment was conducted in the Xiangya Medical College of Central South University and the Third Xiangya Hospital between February 2002 and January 2003. MATERIALS： Sixty-six, adult, male, Kunming mice, weighing （30 ± 5） g, as well as rabbit anti-ET-3 polyclonal and rabbit anti-GFAP polyclonal antibodies, were provided by the Neurobiology Institute of Second Military Medical University in Japan. METHODS： Sixty-six mice were randomly divided into five groups： diabetes mellitus （DM, n = 6）, diabetes mellitus with ischemia-reperfusion （DM/IR, n = 24）, ischemia-reperfusion （IR, n = 24）, sham operation （SO, n = 6）, and control （n = 6）. MAIN OUTCOME MEASURES： Following ischemia-reperfusion for 1, 3, 5, and 10 days, respectively, expression of ET- 3 and GFAP was immunohistochemically measured in the frontal and parietal cortex. RESULTS： All 66 mice were included in the final result analysis. In the IR and DM/IR groups, ET-3- and GFAP-positive neurons increased in the frontal and parietal cortex in response to one day reperfusion, peaked at five days, and decreased at 10 days. ET-3 and GFAP expression was significantly greater in the DM/IR group after reperfusion for 1 day compared to the IR group. However, at other time points, there were no significant differences between the two groups. CONCLUSION： Brain ischemia-reperfusion injury results in overexpression of ET-3 and activation of astrocytes. Diabetes increases the number of ET-3- and GFAP-positive astrocytes in brain tissue of ischemia-reperfusion mice with the same reperfusion duration.

Analysis of Design Rainstorm Hydrograph Based on Asymmetrical Extreme Value Copula

In this paper,the maximum 1-hour rainfall( rain peak),the maximum 6-hour rainfall and the maximum 24-hour rainfall in the Caojiang River basin from 1967 to 2013 were taken as samples. The typical typhoon rainstorm hydrograph of joint distribution of rainfall in three periods was constructed based on the asymmetric Archimedean Gumbel-Hougaard extreme value Copula. The main conclusions were as follows:( 1) the design rainstorm value in the Caojiang River basin calculated by using the joint distribution of rainfall in three periods was larger than the design rainstorm value of the joint distribution in two periods and that of a single period. The design rainstorm process hydrograph amplified at the same frequency had the optimal overall effect,which provided a new idea and method for studying the design rainfall patterns.( 2) According to the maximum 24-hour rainfall,the risk rate of the multi-peak rainstorm process that the main peak was in the back was the highest,and the constructed typical design rainstorm process hydrograph was the most representative.( 3) " OR" joint return period of rainfall combination in three periods as the design criteria of a watershed was applicable to responding to the risk of rainfall and flood in this watershed.

Pedestrian wind flow prediction using spatial-frequency generative adversarial network

Pedestrian wind flow is a critical factor in designing livable residential environments under growing complex urban conditions.Predicting pedestrian wind flow during the early design stages is essential but currently suffers from inefficiencies in numerical simulations.Deep learning,particularly generative adversarial networks(GAN),has been increasingly adopted as an alternative method to provide efficient prediction of pedestrian wind flow.However,existing GAN-based wind flow prediction schemes have limitations due to the lack of considering the spatial and frequency characteristics of wind flow images.This study proposes a novel approach termed SFGAN,which embeds spatial and frequency characteristics to enhance pedestrian wind flow prediction.In the spatial domain,Gaussian blur is employed to decompose wind flow into components containing wind speed and distinguished flow edges,which are used as the embedded spatial characteristics.Detailed information of wind flow is obtained through discrete wavelet transformation and used as the embedded frequency characteristics.These spatial and frequency characteristics of wind flow are jointly utilized to enforce consistency between the predicted wind flow and ground truth during the training phase,thereby leading to enhanced predictions.Experimental results demonstrate that SFGAN clearly improves wind flow prediction,reducing Wind_MAE,Wind_RMSE and the Fréchet Inception Distance(FID)score by 5.35%,6.52%and 12.30%,compared to the previous best method,respectively.We also analyze the effectiveness of incorporating the spatial and frequency characteristics of wind flow in predicting pedestrian wind flow.SFGAN reduces errors in predicting wind flow at large error intervals and performs well in wake regions and regions surrounding buildings.The enhanced predictions provide a better understanding of performance variability,bringing insights at the early design stage to improve pedestrian wind comfort.The proposed spatial-frequency loss term is general and can be flexibly integrated with other generative models to enhance performance with only a slight computational cost.

Copper-based nanodots as efficient biomimetic antibiotics for the treatment of oral bacterial infections Author links open overlay panel

Oral infectious diseases caused by a variety of pathogenic bacteria seriously affect the quality of life.However,these diseases remain a clinical challenge because of the lack of simple,safe,and universal prophylactics.To address these limitations,we synthesize CuO_(x)nanodots(CuO_(x)NDs)with excellent Fenton-like reaction activity and utilize them in the treatment of oral bacterial infections.Different from other complicated approaches,CuO_(x)NDs are rationally prepared using a facile one-pot aqueous synthesis.In the presence of H_(2)O_(2),these well-developed CuO_(x)NDs can efficiently catalyze the generation of hydroxyl radicals(·OH)around oral pathogens,leading to the death of various bacteria.Meanwhile,results of biosafety indicate the high biocompatibility and extremely low toxicity of these CuO_(x)NDs.After understanding the admirable in vitro antibacterial effect of CuO_(x)NDs in the presence of H_(2)O_(2),we further explore their in vivo antibacterial performance on several classical animal models including oral mucosal wound model,intragingival bacteria-infected model,and the periodontal infection model.As expected,these CuO_(x)NDs with wide-spectrum antibacterial activity can serve as high-performance antibacterial reagents for the treatment of various oral bacterial infections with the help of H_(2)O_(2).In brief,current nanoplatform can act as efficient antibiotics against oral pathogens with broadening the biomedical applications of copper-based nanomaterials.

A MLP-Mixer and mixture of expert model for remaining useful life prediction of lithium-ion batteries

Accurately predicting the Remaining Useful Life(RUL)of lithium-ion batteries is crucial for battery management systems.Deep learning-based methods have been shown to be effective in predicting RUL by leveraging battery capacity time series data.However,the representation learning of features such as long-distance sequence dependencies and mutations in capacity time series still needs to be improved.To address this challenge,this paper proposes a novel deep learning model,the MLP-Mixer and Mixture of Expert(MMMe)model,for RUL prediction.The MMMe model leverages the Gated Recurrent Unit and Multi-Head Attention mechanism to encode the sequential data of battery capacity to capture the temporal features and a re-zero MLP-Mixer model to capture the high-level features.Additionally,we devise an ensemble predictor based on a Mixture-of-Experts(MoE)architecture to generate reliable RUL predictions.The experimental results on public datasets demonstrate that our proposed model significantly outperforms other existing methods,providing more reliable and precise RUL predictions while also accurately tracking the capacity degradation process.Our code and dataset are available at the website of github.

A structural and data-driven approach to engineering a plant cytochrome P450 enzyme

Functional manipulation of biosynthetic enzymes such as cytochrome P450 s(or P450 s) has attracted great interest in metabolic engineering of plant natural products.Cucurbitacins and mogrosides are plant triterpenoids that share the same backbone but display contrasting bioactivities.This structural and functional diversity of the two metabolites can be manipulated by engineering P450 s.However,the functional redesign of P450 s through directed evolution(DE) or structure-guided protein engineering is time consuming and challenging,often because of a lack of high-throughput screening methods and crystal structures of P450 s.In this study,we used an integrated approach combining computational protein design,evolutionary information,and experimental data-driven optimization to alter the substrate specificity of a multifunctional P450(CYP87 D20)from cucumber.After three rounds of iterative design and evaluation of 96 protein variants,CYP87 D20,which is involved in the cucurbitacin C biosynthetic pathway,was successfully transformed into a P450 mono-oxygenase that performs a single specific hydroxylation at C11 of cucurbitadienol.This integrated P450-engineering approach can be further applied to create a de novo pathway to produce mogrol,the precursor of the natural sweetener mogroside,or to alter the structural diversity of plant triterpenoids by functionally manipulating other P450 s.

Glycoside-specific metabolomics combined with precursor isotopic labeling for characterizing plant glycosyltransferases

Glycosylation by uridine diphosphate-dependent glycosyltransferases(UGTs)in plants contributes to the complexity and diversity of secondary metabolites.UGTs are generally promiscuous in their use of acceptors,making it challenging to reveal the function of UGTs in vivo.Here,we described an approach that combined glycoside-specific metabolomics and precursor isotopic labeling analysis to characterize UGTs in Arabidopsis.We revisited the UGT72E cluster,which has been reported to catalyze the glycosylation of monolignols.Glycoside-specific metabolomics analysis reduced the number of differentially accumulated metabolites in the ugt72e1e2e3 mutant by at least 90%compared with that from traditional untargeted metabolomics analysis.In addition to the two previously reported monolignol glycosides,a total of 62 glycosides showed reduced accumulation in the ugt72e1e2e3 mutant,22 of which were phenylalanine-derived glycosides,including 5-OH coniferyl alcohol-derived and lignan-derived glycosides,as confirmed by isotopic tracing of[^(13)C_(6)]-phenylalanine precursor.Our method revealed that UGT72Es could use coumarins as substrates,and genetic evidence showed that UGT72Es endowed plants with enhanced tolerance to low iron availability under alkaline conditions.Using the newly developed method,the function of UGT78D2 was also evaluated.These case studies suggest that this method can substantially contribute to the characterization of UGTs and efficiently investigate glycosylation processes,the complexity of which have been highly underestimated.

An ACE/CRIS-observation-based Galactic Cosmic Rays heavy nuclei spectra model Ⅱ

An observation-based Galactic Cosmic Ray(GCR)spectral model for heavy nuclei is developed.Zhao and Qin[J.Geophys.Res.Space Phys.118,1837(2013)]proposed an empirical elemental GCR spectra model for nuclear charge 5≤z≤28 over the energy range^30 to 500 Me V/nuc,which is proved to be successful in predicting yearly averaged GCR heavy nuclei spectra.Based on the latest highly statistically precise measurements from ACE/CRIS,a further elemental GCR model with monthly averaged spectra is presented.The model can reproduce the past and predict the future GCR intensity monthly by correlating model parameters with the continuous sunspot number(SSN)record.The effects of solar activity on GCR modulation are considered separately for odd and even solar cycles.Compared with other comprehensive GCR models,our modeling results are satisfyingly consistent with the GCR spectral measurements from ACE/SIS and IMP-8,and have comparable prediction accuracy as the Badhwar&O’Neill 2014 model.A detailed error analysis is also provided.Finally,the GCR carbon and iron nuclei fluxes for the subsequent two solar cycles(SC 25 and 26)are predicted and they show a potential trend in reduced flux amplitude,which is suspected to be relevant to possible weak solar cycles.

Tailored morphology and highly enhanced phonon transport in polymer fibers:a multiscale computational framework

Although tremendous efforts have been devoted to enhance thermal conductivity in polymer fibers,correlation between the thermal-drawing conditions and the resulting chain alignment,crystallinity,and phonon transport properties have remained obscure.Using a carefully trained coarse-grained force field,we systematically interrogate the thermal-drawing conditions of bulk polyethylene samples using large-scale molecular dynamics simulations.An optimal combination of moderate drawing temperature and strain rate is found to achieve highest degrees of chain alignment,crystallinity,and the resulting thermal conductivity.Such combination is rationalized by competing effects in viscoelastic relaxation and condensed to the Deborah number,a predictive metric for the thermal-drawing protocols,showing a delicate balance between stress localizations and chain diffusions.Upon tensile deformation,the thermal conductivity of amorphous polyethylene is enhanced to 80% of the theoretical limit,that is,its pure crystalline counterpart.An effective-medium-theory model,based on the serial-parallel heat conducting nature of semicrystalline polymers,is developed here to predict the impacts from both chain alignment and crystallinity on thermal conductivity.The enhancement in thermal conductivity is mainly attributed to the increases in the intrinsic phonon mean free path and the longitudinal group velocity.This work provides fundamental insights into the polymer thermal-drawing process and establishes a complete process–structure–property relationship for enhanced phonon transport in all-organic electronic devices and efficiency of polymeric heat dissipaters.

White Electroluminescence with Simultaneous Three-Color Emission from a Four-Armed Star-Shaped Single-Polymer System

A four-armed star-shaped single-polymer system with 4,7-bis（5-（4-（9H-carbazol-9-yl）phenyl）-4-hexylthio- phen-2-yl）benzo[c][1,2,5]thiadiazole （FTBT） as a red emissive core, polyfluorene （PF） as blue emissive arms and 1,3-benzo thiadiazole （BT） as green emissive dopants was designed and synthesized, in which red, green, and blue （RGB） emission balance can be achieved by adjusting the doping concentration of FTBT and BT discreetly. A typ- ical single-emissive-layer device （ITO/PEDOT：PSS/polymer/TPBI/LiF/Al） was studied and discussed, realizing a pure and stable white emission with a luminous efficiency （LE） of 1.59 cd·A^-1 and CIE coordinates of （0.31, 0.34）. The high-color-quality white electroluminescence of the devices could be mainly attributed to the suppressed in- termolecular interactions, and partial energy transfer from the blue PF arms to the red and green dopants.

High performance solid-state thermoelectric energy conversion via inorganic metal halide perovskites under tailored mechanical deformation

Solid-state thermoelectric energy conversion devices attract broad research interests because of their great promises in waste heat recycling,space power generation,deep water power generation,and temperature control,but the search for essential thermoelectric materials with high performance still remains a great challenge.As an emerging low cost,solution-processed thermoelectric material,inorganic metal halide perovskites CsPb(I_(1–x)Br_(x))_(3) under mechanical deformation is systematically investigated using the first-principle calculations and the Boltzmann transport theory.It is demonstrated that halogen mixing and mechanical deformation are efficient methods to tailor electronic structures and charge transport properties in CsPb(I_(1–x)Br_(x))_(3) synergistically.Halogen mixing leads to band splitting and anisotropic charge transport due to symmetry-breakinginduced intrinsic strains.Such band splitting reconstructs the band edge and can decrease the charge carrier effective mass,leading to excellent charge transport properties.Mechanical deformation can further push the orbital energies apart from each other in a more controllable manner,surpassing the impact from intrinsic strains.Both anisotropic charge transport properties and ZT values are sensitive to the direction and magnitude of strain,showing a wide range of variation from 20%to 400%(with a ZT value of up to 1.85)compared with unstrained cases.The power generation efficiency of the thermoelectric device can reach as high as approximately 12%using mixed halide perovskites under tailored mechanical deformation when the heat-source is at 500 K and the cold side is maintained at 300 K,surpassing the performance of many existing bulk thermoelectric materials.

Indirubin-30 -monoxime-loaded PLGA-PEG nanoparticles for potential Alzheimer's disease treatment

Alzheimer's disease(AD)is an irreversible neurodegenerative disorder,which is pathologically characterized by the deposits of β-amyloid(Aβ),and plays an important role in neuronal death.Indirubin-30-monoxime(I3M)showed neuroprotective effects against Aβ-induced neuronal apoptosis.However,the use of I3M in AD treatment is limited due to its low bioavailability.Herein,PLGA-PEG nanoparticles were synthesized for I3M loading.I3M could release sustainedly sustain release from the I3M-loaded PLGA-PEG nanoparticles(PLGA-PEG-I3M NPs)without obvious burst release.What's more,the PLGA-PEG-I3M NPs could significantly promote the uptake of I3M by PC12 cells through nanoparticle-mediated transport,and improve the efficacy of I3M on the inhibition of Aβfibrillization and oligomerization as well as the neuroprotective activity of I3M on Aβoligomers-induced neuronal death.Thus,the PLGA-PEG-I3M NPs may be a promising platform for AD therapy.