A 1-bit electronically reconfigurable beam steerable metasurface reflectarray with multiple polarization manipulations

A 1-bit electronically controlled metasurface reflectarray is presented to achieve beam steering with multiple polarization manipulations. A metsurface unit cell loaded by two PIN diodes is designed. By switching the two PIN diodes between ON and OFF states, the isotropic and anisotropic reflections can be flexibly achieved. For either the isotropic reflection or the anisotropic reflection, the two operation states achieve the reflection coefficients with approximately equal magnitude and 180°out of phase, thus giving rise to the isotropic/anisotropic 1-bit metasurface unit cells. With the 1-bit unit cells, a 12-by-12 metasurface reflectarray is optimally designed and fabricated. Under either y-or x-polarized incident wave illumination, the reflectarray can achieve the co-polarized and cross-polarized beam scanning, respectively, with the peak gains of 20.08 d Bi and 17.26 d Bi within the scan range of about ±50°. With the right-handed circular polarization(RHCP) excitation, the left-handed circular polarization(LHCP) radiation with the peak gain of 16.98 d Bic can be achieved within the scan range of ±50°. Good agreement between the experimental results and the simulation results are observed for 2D beam steering and polarization manipulation capabilities.

Many faces of neuronal activity manipulation in Drosophila

Animals exhibit complex responses to external and internal stimuli.The information is computed by interconnected neurons that express numerous ion channels,which modulate the neuronal membrane potential.How can neuronal activity orchestrate complex motor patterns or allow learning from previous experience?To answer such questions,we need the ability not only to record,but also to modulate neuronal activity in both space(e.g.,neuronal subsets)and time.

Effects of different acupuncture manipulations on protein expression in the parietal cortex of spontaneously hypertensive rats

Objective: To analyze the effects of twirling reinforcing and reducing manipulations on protein expression in parietal cortex of spontaneously hypertensive rats(SHRs), and elucidate the main mechanisms and differences between two manipulations in hypertension treatment.Methods: Rats were randomly divided into the control, model, twirling reinforcing manipulation(TRFM),and twirling reducing manipulation(TRDM) groups. The control and model groups received catch and fixation stimulations once a day for 14 days. The TRFM and TRDM groups were intervened once a day for 20 min for 14 days. On days 0, 2, 6, 10, and 14 after acupuncture, rat systolic blood pressures(SBPs) were measured. Differential protein(DP) expression in the rat parietal cortices was detected. Thereafter, GO functional significance and KEGG pathway enrichment analyses were performed.Results: Compared with the model group, SBP of rats in the TRDM and TRFM groups decreased on days 6 and 10 of acupuncture, respectively(P=.009;P <.001). Moreover, SBP of the TRDM group was significantly lower than that of the TRFM group on days 10 and 14 of acupuncture(P=.015;P=.013).Compared with control group, 601 and 1040 DPs were up-and downregulated, respectively, in the model group. Compared with model group, 44 and 28 up-and downregulated DPs were expressed, respectively,in the TRFM group. Compared with model group, expression of 616 and 427 up-and downregulated DPs,respectively, was found in the TRDM group. After combining the results of GO and KEGG enrichment analyses, five and one pathways were found to be related to the central antihypertensive mechanism of the parietal cortex during twirling reducing and reinforcing manipulations, respectively.Conclusion: TRDM showed a more effective antihypertensive effect on SHRs than TRFM;this antihypertensive effect was related to the regulation of different proteins and their biological functions.

Temporal sequence Object-based CNN(TS-OCNN) for crop classification from fine resolution remote sensing image time-series

Accurate crop distribution mapping is required for crop yield prediction and field management. Due to rapid progress in remote sensing technology, fine spatial resolution(FSR) remotely sensed imagery now offers great opportunities for mapping crop types in great detail. However, within-class variance can hamper attempts to discriminate crop classes at fine resolutions. Multi-temporal FSR remotely sensed imagery provides a means of increasing crop classification from FSR imagery, although current methods do not exploit the available information fully. In this research, a novel Temporal Sequence Object-based Convolutional Neural Network(TS-OCNN) was proposed to classify agricultural crop type from FSR image time-series. An object-based CNN(OCNN) model was adopted in the TS-OCNN to classify images at the object level(i.e., segmented objects or crop parcels), thus, maintaining the precise boundary information of crop parcels. The combination of image time-series was first utilized as the input to the OCNN model to produce an ‘original’ or baseline classification. Then the single-date images were fed automatically into the deep learning model scene-by-scene in order of image acquisition date to increase successively the crop classification accuracy. By doing so, the joint information in the FSR multi-temporal observations and the unique individual information from the single-date images were exploited comprehensively for crop classification. The effectiveness of the proposed approach was investigated using multitemporal SAR and optical imagery, respectively, over two heterogeneous agricultural areas. The experimental results demonstrated that the newly proposed TS-OCNN approach consistently increased crop classification accuracy, and achieved the greatest accuracies(82.68% and 87.40%) in comparison with state-of-the-art benchmark methods, including the object-based CNN(OCNN)(81.63% and85.88%), object-based image analysis(OBIA)(78.21% and 84.83%), and standard pixel-wise CNN(79.18%and 82.90%). The proposed approach is the first known attempt to explore simultaneously the joint information from image time-series with the unique information from single-date images for crop classification using a deep learning framework. The TS-OCNN, therefore, represents a new approach for agricultural landscape classification from multi-temporal FSR imagery. Besides, it is readily generalizable to other landscapes(e.g., forest landscapes), with a wide application prospect.

Object-based classification of cloudy coastal areas using medium-resolution optical and SAR images for vulnerability assessment of marine disaster

Efficient and accurate access to coastal land cover information is of great significance for marine disaster prevention and mitigation.Although the popular and common sensors of land resource satellites provide free and valuable images to map the land cover,coastal areas often encounter significant cloud cover,especially in tropical areas,which makes the classification in those areas non-ideal.To solve this problem,we proposed a framework of combining medium-resolution optical images and synthetic aperture radar(SAR)data with the recently popular object-based image analysis(OBIA)method and used the Landsat Operational Land Imager(OLI)and Phased Array type L-band Synthetic Aperture Radar(PALSAR)images acquired in Singapore in 2017 as a case study.We designed experiments to confirm two critical factors of this framework:one is the segmentation scale that determines the average object size,and the other is the classification feature.Accuracy assessments of the land cover indicated that the optimal segmentation scale was between 40 and 80,and the features of the combination of OLI and SAR resulted in higher accuracy than any individual features,especially in areas with cloud cover.Based on the land cover generated by this framework,we assessed the vulnerability of the marine disasters of Singapore in 2008 and 2017 and found that the high-vulnerability areas mainly located in the southeast and increased by 118.97 km2 over the past decade.To clarify the disaster response plan for different geographical environments,we classified risk based on altitude and distance from shore.The newly increased high-vulnerability regions within 4 km offshore and below 30 m above sea level are at high risk;these regions may need to focus on strengthening disaster prevention construction.This study serves as a typical example of using remote sensing techniques for the vulnerability assessment of marine disasters,especially those in cloudy coastal areas.

An Object-based Approach for Two-level Gully Feature Mapping Using High-resolution DEM and Imagery： A Case Study on Hilly Loess Plateau Region, China

Gully feature mapping is an indispensable prerequisite for the motioning and control of gully erosion which is a widespread natural hazard. The increasing availability of high-resolution Digital Elevation Model(DEM) and remote sensing imagery, combined with developed object-based methods enables automatic gully feature mapping. But still few studies have specifically focused on gully feature mapping on different scales. In this study, an object-based approach to two-level gully feature mapping, including gully-affected areas and bank gullies, was developed and tested on 1-m DEM and Worldview-3 imagery of a catchment in the Chinese Loess Plateau. The methodology includes a sequence of data preparation, image segmentation, metric calculation, and random forest based classification. The results of the two-level mapping were based on a random forest model after investigating the effects of feature selection and class-imbalance problem. Results show that the segmentation strategy adopted in this paper which considers the topographic information and optimal parameter combination can improve the segmentation results. The distribution of the gully-affected area is closely related to topographic information, however, the spectral features are more dominant for bank gully mapping. The highest overall accuracy of the gully-affected area mapping was 93.06% with four topographic features. The highest overall accuracy of bank gully mapping is 78.5% when all features are adopted. The proposed approach is a creditable option for hierarchical mapping of gully feature information, which is suitable for the application in hily Loess Plateau region.

Source-sink relations and responses to sink-source manipulations during grain filling in wheat

The source-sink ratio during grain filling is a critical factor that affects crop yield in wheat,and the main objective of this study was to determine the source-sink relations at both the canopy scale and the individual culm level under two nitrogen(N)levels at the post-jointing stage.Nine widely-used cultivars were chosen for analyzing source-sink relations in southwestern China;and three typical cultivars of different plant types were subjected to artificial manipulation of the grain-filling source-sink ratio to supplement crop growth measurements.A field experiment was conducted over two consecutive seasons under two N rates(N+,150 kg ha^(-1);N-,60 kg ha^(-1)),and three manipulations were imposed after anthesis:control(Ct),removal of flag and penultimate leaves(Lr)and removal of spikelets on one side of each spike(Sr).The results showed that the single grain weights in the three cultivars were significantly decreased by Lr and increased by Sr,which demonstrated that wheat grain yield potential seems more source-limited than sink-limited during grain filling,but the source-sink balance was obviously changed by climatic variations and N deficient environments.Grain yield was highly associated with sink capacity(SICA),grain number,biomass,SPAD values,and leaf area index during grain filling,indicating a higher degree of source limitation with an increase in sink capacity.Therefore,source limitation should be taken into account by breeders when SICA is increased,especially under non-limiting conditions.Chuanmai 104,a half-compact type with a mid-sized spike and a long narrow upper leaf,showed relatively better performance in source-sink relations.Since this cultivar showed the characteristics of a lower reduction in grain weight after Lr,a larger increase after Sr,and a lower reduction in post-anthesis dry matter accumulation,then the greater current photosynthesis during grain filling contributed to the grain after source and sink manipulation.

Object-based Classification of Baltic Sea Ice Extent and Concentration in Winter 2011

The Baltic Sea is a brackish, mediterranean sea located in the middle latitudes of Europe. It is seasonally covered with ice. The ice covered areas during a typical winter are the Bothnian Bay, the Gulf of Finnland and the Gulf of Riga. Sea ice plays an important role in dynamic and thermodynamic processes and also has a strong impact on the heat budget of the sea. Also a large part of transport goes by sea, and there is a need to create ice charts to make the marine transport safe. Because of high cloudiness in winter season and small amount of light in the northern part of the Baltic Sea, radar data are the most important remote sensing source of sea ice information. The main goal of the following studies is classification of the Baltic sea ice cover using radar data. The ENVISAT ASAR （Advanced Synthetic Aperture Radar） acquires data in five different modes. In the following studies ASAR Wide Swath Mode data were used. The Wide Swath Mode, using the ScanSAR technique provides medium resolution images （150 m） over a swath of 405 kin, at HH or VV polarization. In following work data from February 13th, February 24th and April 6th, 2011, representing three different sea ice situations were chosen. OBIA （object-based image analysis） methods and texture parameters were used to create sea ice extent and sea ice concentration charts. Based on object-based methods, it can separate single sea ice floes within the ice pack and calculate more accurately sea ice concentration.

Development of a Generic Model for the Detection of Roof Materials Based on an Object-Based Approach Using WorldView-2 Satellite Imagery

The detection of impervious surface (IS) in heterogeneous urban areas is one of the most challenging tasks in urban remote sensing. One of the limitations in IS detection at the parcel level is the lack of sufficient training data. In this study, a generic model of spatial distribution of roof materials is considered to overcome this limitation. A generic model that is based on spectral, spatial and textural information which is extracted from available training data is proposed. An object-based approach is used to extract the information inherent in the image. Furthermore, linear discriminant analysis is used for dimensionality reduction and to discriminate between different spatial, spectral and textural attributes. The generic model is composed of a discriminant function based on linear combinations of the predictor variables that provide the best discrimination among the groups. The discriminate analysis result shows that of the 54 attributes extracted from the WorldView-2 image, only 13 attributes related to spatial, spectral and textural information are useful for discriminating different roof materials. Finally, this model is applied to different WorldView-2 images from different areas and proves that this model has good potential to predict roof materials from the WorldView-2 images without using training data.

Manipulations of micro/nanoparticles using gigahertz acoustic streaming tweezers

Contactless acoustic manipulation of micro/nanoscale particles has attracted considerable attention owing to its near independence of the physical and chemical properties of the targets,making it universally applicable to almost all biological systems.Thin-film bulk acoustic wave(BAW)resonators operating at gigahertz(GHz)frequencies have been demonstrated to generate localized high-speed microvortices through acoustic streaming effects.Benefitting from the strong drag forces of the high-speed vortices,BAW-enabled GHz acoustic streaming tweezers(AST)have been applied to the trapping and enrichment of particles ranging in size from micrometers to less than 100 nm.However,the behavior of particles in such 3D microvortex systems is still largely unknown.In this work,the particle behavior(trapping,enrichment,and separation)in GHz AST is studied by theoretical analyses,3D simulations,and microparticle tracking experiments.It is found that the particle motion in the vortices is determined mainly by the balance between the acoustic streaming drag force and the acoustic radiation force.This work can provide basic design principles for AST-based lab-on-a-chip systems for a variety of applications.

Integration of SAR Polarimetric Features and Multi-spectral Data for Object-Based Land Cover Classification

An object-based approach is proposed for land cover classification using optimal polarimetric parameters.The ability to identify targets is effectively enhanced by the integration of SAR and optical images.The innovation of the presented method can be summarized in the following two main points:①estimating polarimetric parameters(H-A-Alpha decomposition)through the optical image as a driver;②a multi-resolution segmentation based on the optical image only is deployed to refine classification results.The proposed method is verified by using Sentinel-1/2 datasets over the Bakersfield area,California.The results are compared against those from pixel-based SVM classification using the ground truth from the National Land Cover Database(NLCD).A detailed accuracy assessment complied with seven classes shows that the proposed method outperforms the conventional approach by around 10%,with an overall accuracy of 92.6%over regions with rich texture.

Object-Based vs. Pixel-Based Classification of Mangrove Forest Mapping in Vien An Dong Commune, Ngoc Hien District, Ca Mau Province Using VNREDSat-1 Images

Many researches have been performed comparing object-based classification (OBC) and pixel-based classification (PBC), particularly in classifying high-resolution satellite images. VNREDSat-1 is the first optical remote sensing satellite of Vietnam with resolution of 2.5 m (Panchromatic) and 10 m (Multispectral). The objective of this research is to compare two classification approaches using VNREDSat-1 image for mapping mangrove forest in Vien An Dong commune, Ngoc Hien district, Ca Mau province. ISODATA algorithm (in PBC method) and membership function classifier (in OBC method) were chosen to classify the same image. The results show that the overall accuracies of OBC and PBC are 73% and 62.16% respectively, and OBC solved the “salt and pepper” which is the main issue of PBC as well. Therefore, OBC is supposed to be the better approach to classify VNREDSat-1 for mapping mangrove forest in Ngoc Hien commune.

A single micro-LED manipulation system based on micro-gripper

Micro-LEDs(μLEDs)have advantages in terms of brightness,power consumption,and response speed.In addition,they can also be used as micro-sensors implanted in the body via flexible electronic skin.One of the key techniques involved in the fabrication ofμLED-based devices is transfer printing.Although numerous methods have been proposed for transfer printing,improving the yield ofμLED arrays is still a formidable task.In this paper,we propose a novel method for improving the yield ofμLED arrays transferred by the stamping method,using an innovative design of piezoelectrically driven asymmetric micro-gripper.Traditional grippers are too large to manipulateμLEDs,and therefore two micro-sized cantilevers are added at the gripper tips.AμLED manipulation system is constructed based on the micro-gripper together with a three-dimensional positioning system.Experimental results using this system show that it can be used successfully to manipulateμLED arrays.

Influence of Sancai and conventional acupuncture manipulations on injured sciatic nerve histomorphology and serum interleukin-6 expression

Acupuncture and moxibustion therapy non-specifically raises the pain threshold, relieves regional muscular tension, improves local blood circulation, accelerates elimination of algogenic substances such as acid metabolites, and promotes neural regeneration and functional rehabilitation. However, the effects of acupuncture are synthetically influenced by multiple factors, which vary with acu-puncture point, intensity, and manipulation. The present study explored the analgesic effects and mechanisms of specific Sancai acupuncture manipulation for sciatica. Results revealed that Sancai acupuncture manipulation significantly reduced inflammatory factor interleukin-6 expression in the blood serum of rats with sciatica, exhibited anti-inflammatory effects and promoted rehabilitation of injured nerves. In addition, Sancai acupuncture manipulation exhibited superior curative effects over conventional acupuncture manipulation.

Triboelectric‘electrostatic tweezers'for manipulating droplets on lubricated slippery surfaces prepared by femtosecond laser processing

The use of‘Electrostatic tweezers'is a promising tool for droplet manipulation,but it faces many limitations in manipulating droplets on superhydrophobic surfaces.Here,we achieve noncontact and multifunctional droplet manipulation on Nepenthes-inspired lubricated slippery surfaces via triboelectric electrostatic tweezers(TETs).The TET manipulation of droplets on a slippery surface has many advantages over electrostatic droplet manipulation on a superhydrophobic surface.The electrostatic field induces the redistribution of the charges inside the neutral droplet,which causes the triboelectric charged rod to drive the droplet to move forward under the electrostatic force.Positively or negatively charged droplets can also be driven by TET based on electrostatic attraction and repulsion.TET enables us to manipulate droplets under diverse conditions,including anti-gravity climb,suspended droplets,corrosive liquids,low-surface-tension liquids(e.g.ethanol with a surface tension of 22.3 mN·m^(-1)),different droplet volumes(from 100 nl to 0.5 ml),passing through narrow slits,sliding over damaged areas,on various solid substrates,and even droplets in an enclosed system.Various droplet-related applications,such as motion guidance,motion switching,droplet-based microreactions,surface cleaning,surface defogging,liquid sorting,and cell labeling,can be easily achieved with TETs.

Pre‑hatch thermal manipulation of embryos and post‑hatch baicalein supplementation mitigated heat stress in broiler chickens

Background High environmental temperatures induce heat stress in broiler chickens,affecting their health and pro-duction performance.Several dietary,managerial,and genetics strategies have been tested with some success in mitigating heat stress(HS)in broilers.Developing novel HS mitigation strategies for sustaining broiler production is critically needed.This study investigated the effects of pre-hatch thermal manipulation(TM)and post-hatch baica-lein supplementation on growth performance and health parameters in heat-stressed broilers.Results Six hundred fertile Cobb 500 eggs were incubated for 21 d.After candling on embryonic day(ED)10,238 eggs were thermally manipulated at 38.5℃ with 55%relative humidity(RH)from ED 12 to 18,then transferred to the hatcher(ED 19 to 21,standard temperature)and 236 eggs were incubated at a controlled temperature(37.5℃)till hatch.After hatch,180-day-old chicks from both groups were raised in 36 pens(n=10 birds/pen,6 replicates per treatment).The treatments were:1)Control,2)TM,3)control heat stress(CHS),4)thermal manipulation heat stress(TMHS),5)control heat stress supplement(CHSS),and 6)thermal manipulation heat stress supplement(TMHSS).All birds were raised under the standard environment for 21 d,followed by chronic heat stress from d 22 to 35(32–33℃ for 8 h)in the CHS,TMHS,CHSS,and TMHSS groups.A thermoneutral(22–24℃)environment was maintained in the Control and TM groups.RH was constant(50%±5%)throughout the trial.All the data were analyzed using one-way ANOVA in R and GraphPad software at P<0.05 and are presented as mean±SEM.Heat stress significantly decreased(P<0.05)the final body weight and ADG in CHS and TMHS groups compared to the other groups.Embryonic TM significantly increased(P<0.05)the expression of heat shock protein-related genes(HSP70,HSP90,and HSPH1)and antioxidant-related genes(GPX1 and TXN).TMHS birds showed a significant increment(P<0.05)in total cecal volatile fatty acid(VFA)concentration compared to the CHS birds.The cecal microbial analysis showed significant enrichment(P<0.05)in alpha and beta diversity and Coprococcus in the TMHSS group.Conclusions Pre-hatch TM and post-hatch baicalein supplementation in heat-stressed birds mitigate the detrimental effects of heat stress on chickens’growth performance,upregulate favorable gene expression,increase VFA produc-tion,and promote gut health by increasing beneficial microbial communities.

OBH-RSI:Object-Based Hierarchical Classification Using Remote Sensing Indices for Coastal Wetland

With the deterioration of the environment,it is imperative to protect coastal wetlands.Using multi-source remote sensing data and object-based hierarchical classification to classify coastal wetlands is an effective method.The object-based hierarchical classification using remote sensing indices(OBH-RSI)for coastal wetland is proposed to achieve fine classification of coastal wetland.First,the original categories are divided into four groups according to the category characteristics.Second,the training and test maps of each group are extracted according to the remote sensing indices.Third,four groups are passed through the classifier in order.Finally,the results of the four groups are combined to get the final classification result map.The experimental results demonstrate that the overall accuracy,average accuracy and kappa coefficient of the proposed strategy are over 94%using the Yellow River Delta dataset.

Object-based Analysis for Extraction of Dominant Tree Species

As forest is of great significance for our whole development and the sustainable plan is so focus on it. It is very urgent for us to have the whole distribution,stock volume and other related information about that. So the forest inventory program is on our schedule. Aiming at dealing with the problem in extraction of dominant tree species,we tested the highly hot method-object-based analysis. Based on the ALOS image data,we combined multi-resolution in e Cognition software and fuzzy classification algorithm. Through analyzing the segmentation results,we basically extract the spruce,the pine,the birch and the oak of the study area. Both the spectral and spatial characteristics were derived from those objects,and with the help of GLCM,we got the differences of each species. We use confusion matrix to do the Classification accuracy assessment compared with the actual ground data and this method showed a comparatively good precision as 87% with the kappa coefficient 0. 837.

Clinical Observation of 32 Cases of Scapulohumeral Periarthritis Treated by Manipulations and Acupuncture

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Cotton Genome Manipulations:Exploring Smart Tools,Novel Germplasm,and Elite Genes for Super Cotton Design

Plant regeneration is the first step to cotton biotechnology.We screened over 100 genotypes and found two genotypes,YZ-1 and Y668,which are very easy to regenerate.It takes about 5 to 6