Efficient channelized technology based on filter banks

With the appearance of novel radar signal with low intercept probability, the bandwidth of radar receiver is wider and wider. Wideband digital receiver becomes a research hotspot in the field of communication, radar and electronic reconnaissance, etc. As one of wideband digital receiver systems, digital channelized receiver has become a research emphasis due to the characteristics of full probability receiving and processing multiple signals. Digital channelized technology and signal sampling theory are deeply studied and an efficient channelized model is derived based on filter banks. The correctness of the model is verified by computer simulation The model has less computation compared with the traditional model, which is suitable for engineering application

Geomorphic Characteristics of Hillslope and Channelized Debris Flows: A Case Study in the Shitou Area of Central Taiwan

The data on the hillslope and channelized debris flows in the Shitou area of central Taiwan occurred during Typhoons Toraji and Nali in 2001 were applied in this paper. The geomorphic parameters, including the flow length, gully gradient, drainage area and form factor of the debris flows were determined by spatial analysis using a Geographic Information System (GIS) based on the data derived from field investigation, aerial photographs, and topographical maps. According to such determined geomorphic parameters, the threshold conditions and empirical equations, such as the relationship between the gully gradient and drainage area and that between gully length and drainage area and topographic parameter, are presented and used to distinguish the geomorphic characteristics between the channelized and hillslope debris flows.

Design and simulation of digital channelized receivers in fractional Fourier domain

An approach is proposed to realize a digital channelized receiver in the fractional Fourier domain （FRFD） for signal intercept applications. The presented architecture can be considered as a generalization of that in the traditional Fourier domain. Since the linear frequency modulation （LFM） signal has a good energy concentration in the FRFD, by choosing an appropriate fractional Fourier transform （FRFT） order, the presented architecture can concentrate the broadband LFM signal into only one sub-channel and that will prevent it from crossing several sub-channels. Thus the performance of the signal detection and parameter estimation after the sub-channel output will be improved significantly. The computational complexity is reduced enormously due to the implementation of the polyphase filter bank decomposition, thus the proposed architecture can be realized as efficiently as in the Fourier domain. The related simulation results are presented to verify the validity of the theories and methods involved in this paper.

Capacity Maximization Based Power Loading Analysis for Digital Channelized Satcom Systems

For digital channelized frequency division multiple access based satellite communication(SATCOM) systems,it is a challenging but critical issue to improve the transponder power and spectrum efficiency simultaneously under limited and non-linear high-power amplifier conditions.In this paper,different from the traditional link supportability designs aiming at minimizing the total transponder output power,a maximal sum Shannon capacity optimization objective is firstly raised subject to link supportability constraints.Furthermore,an efficient multilevel optimization(MO) algorithm is proposed to solve the considered optimization problem in the case of single link for each terminal.Moreover,in the case of multiple links for one terminal,an improved MO algorithm involving Golden section and discrete gradient searching procedures is proposed to optimize power allocation over all links.Finally,several numerical results are provided to demonstrate the effectiveness of our proposals.Comparison results show that,by the MO algorithm,not only all links' supportability can be guaranteed but also a larger sum capacity can be achieved with lower complexity.

Design and Implementation of Partial Shared Digital Channelized Receiver

A novel efficient partial sharing channelization structure with odd and even stacking is designed and implemented. There are two special designs in the proposed structure. Firstly, by the intensive channel overlap design, for non-cooperative wideband signals, the proposed structure can achieve good parameter estimation accuracy and high probability of complete interception.Secondly, based on the partial sharing design developed in this paper, the computation burden of the proposed structure can be greatly reduced compared with the traditional directly implemented structures. Experiments and numerical simulations are conducted to evaluate the proposed structure, which shows its improvements over traditional methods in terms of field programmable gate arrays(FPGA) resource consumption and parameter estimation accuracy.

A New Method of Assessing Environmental Flows in Channelized Urban Rivers

Assessing environmental flows （e-flows） for urban rivers is important for water resources planning and river protection, Many e-flow assessment methods have been established based on species＇ habitat pro- vision requirements and pollutant dilution requirements, To avoid flood risk, however, many urban rivers have been transformed into straight, trapezoidal-profiled concrete channels, leading to the disappearance of valuable species, With the construction of water pollution-control projects, pollutant inputs into rivers have been effectively controlled in some urban rivers, For these rivers, the e-flows determined by tradi- tional methods will be very small, and will consequently lead to a low priority being given to river pro- tection in future water resources allocation and management, To more effectively assess the e-flows of channelized urban rivers, we propose three e-flow degrees, according to longitudinal hydrological con- nectivity （high, medium, and low）, in addition to the pollutant dilution water requirement determined by the mass-balance equation, In the high connectivity scenario, the intent is for the e-flows to maintain flow velocity, which can ensure the self-purification of rivers and reduce algal blooms; in the medium connectivity scenario, the intent is for the e-flows to permanently maintain the longitudinal hydrological connectivity of rivers that are isolated into several ponds by means of weirs, in order to ensure the exchange of material, energy, and information in rivers; and in the low connectivity scenario, the intent is for the e-flows to intermittently connect isolated ponds every few days （which is designed to further reduce e-flows）, The proposed methods have been used in Shiwuli River, China, to demonstrate their effectiveness, The new methods can offer more precise and realistic e-flow results and can effectively direct the construction and management of e-flow supply projects,

Iterative static modeling of channelized reservoirs using history-matched facies probability data and rejection of training image

Most inverse reservoir modeling techniques require many forward simulations, and the posterior models cannot preserve geological features of prior models. This study proposes an iterative static modeling approach that utilizes dynamic data for rejecting an unsuitable training image(TI) among a set of TI candidates and for synthesizing history-matched pseudo-soft data. The proposed method is applied to two cases of channelized reservoirs, which have uncertainty in channel geometry such as direction, amplitude, and width. Distance-based clustering is applied to the initial models in total to select the qualified models efficiently. The mean of the qualified models is employed as a history-matched facies probability map in the next iteration of static models. Also, the most plausible TI is determined among TI candidates by rejecting other TIs during the iteration. The posterior models of the proposed method outperform updated models of ensemble Kalman filter(EnKF) and ensemble smoother(ES) because they describe the true facies connectivity with bimodal distribution and predict oil and water production with a reasonable range of uncertainty. In terms of simulation time, it requires 30 times of forward simulation in history matching, while the EnKF and ES need 9000 times and 200 times, respectively.

Experimental Study on the Mobility of Channelized Granular Mass Flow

Granular mass flows （e.g., debris flows/avalanches） in landslide-prone areas are of great concern because they often cause catastrophic disasters as a result of their long run-out distances and large impact forces. To investigate the factors influencing granular mass flow mobility, experimental tests were conducted in a flume model. Granular materials consisting of homogeneous sand and non- homogeneous sandy soil were used for studying particle size effects. Run-out tests with variable flow masses, water contents, and sloping channel confinement parameters were conducted as well. The results indicated that granular mass flow mobility was significantly influenced by the initial water content; a critical water content corresponding to the smallest flow mobility exists for different granular materials. An increase in the total flow mass generally induced a reduction in the travel angle （an increase in flow mobility）. Consistent with field observations, the travel angles for different granular materials decreased roughly in proportion to the logarithm of mass. The flume model tests illustrate that the measured travel angles increase as the proportion of fine particles increases. Interestingly, natural terrain possesses critical confinement characteristics for different granular mass flows.

Photonic radio frequency channelizers based on Kerr optical micro-combs

We review recent work on broadband RF channelizers based on integrated optical frequency Kerr micro-combs combined with passive micro-ring resonator filters,with microcombs having channel spacings of 200 and 49 GHz.This approach to realizing RF channelizers offers reduced complexity,size,and potential cost for a wide range of applications to microwave signal detection.

Small Mammal Habitat Use within Restored Riparian Habitats Adjacent to Channelized Streams in Mississippi

Riparian zones of channelized agricultural streams in northwestern Mississippi typically consist of narrow vegetative corridors low in habitat diversity and lacking riparian wetlands. Land clearing practices and stream channelization have led to the development of gully erosion and further fragmentation of these degraded riparian zones. Currently, installation of a gully erosion control structure (drop pipe) at the riparian zone-agricultural field interface leads to the incidental establishment of four riparian habitat types that differ in habitat area, vegetative structure, and pool size. Small mammals were sampled within four sites of each habitat type from June 1994 to July 1995. Small mammal diversity, abundance, and hispid cotton rat (Sigmodon hispidus) weight were the least within smallest Type I habitats with the least vegetative structural diversity and were the greatest within the larger Type II, III, or IV habitats having greater vegetative structural diversity and pool size. Small mammal diversity and abundance were the least in the summer 1994, increased in the fall 1994, and then declined later in our study. Hispid cotton rat abundance was the least in summer 1994, winter 1994, and spring 1995 and was the greatest in fall 1994 and summer 1995. Our results suggest that modifying the drop pipe installation design to facilitate the development of larger riparian habitats with greater vegetative structural diversity will provide the greatest benefits for small mammals.

A Non-Maximally Decimated Dynamic Reconfigurable Channelized Structure Based on Modulated Filter Bank

A structure of dynamic reconfigurable channelized filter bank is proposed in order to solve the problem that the uniform channelized receiver cannot receive the cross-channel and wideband signal. The dynamic reconfigurable channelized filter bank is divided into two parts-the analysis filter bank and the synthesis filter bank. The function of the analysis filter bank is to divide the received signal into several sub-signals according to the channel division. Then the sub-signals of each channel need to be detected and discriminated. At last, we use the sub-signals to reconstruct the original received signal by the synthesis filter bank. The analysis filter and the synthesis filter bank of the dynamic reconfigurable channelized filter bank are all efficient polyphase structures, so it can save more hardware resources and has extensive applicability. The structure is simulated by MATLAB and the simulation results verify the correctness of this structure.

神经元限制性沉默因子REST/NRSF参与调控癫痫作用及机制研究

目的探究神经元限制性沉默因子(REST/NRSF)参与调控癫痫作用及分子机制。方法采用免疫组织化学染色、免疫荧光、Western blot和qPCR检测癫痫患者病灶组织和海人藻酸(kainic acid,KA)癫痫小鼠海马脑区REST/NRSF表达水平的变化;采用病毒注射,脑电图记录和行为学方法检测在海马CA1区分别敲低或过表达REST/NRSF后对小鼠癫痫发作的影响。结果癫痫患者病灶REST/NRSF表达水平相对于脑外伤患者脑组织明显升高;KA模型组小鼠海马CA1区REST/NRSF蛋白和mRNA水平均明显升高,Kv7.2、Kv7.3钾通道mRNA表达水平明显下调;脑内注射NMDA兴奋海马脑区小鼠REST/NRSF表达水平明显上调;海马CA1区敲低REST/NRSF明显升高Kv7.2、Kv7.3钾通道mRNA表达水平,明显降低小鼠脑电图棘波、尖波发放频率以及癫痫发作等级;海马CA1区过表达REST/NRSF明显降低Kv7.2、Kv7.3钾通道mRNA表达水平,明显升高小鼠棘波、尖波发放频率,癫痫症状明显加重。结论小鼠海马脑区REST/NRSF通过转录调控Kv7.2、Kv7.3钾通道参与癫痫疾病发生发展。

Lithium-Ion Charged Polymer Channels Flattening Lithium Metal Anode

The concentration difference in the near-surface region of lithium metal is the main cause of lithium dendrite growth.Resolving this issue will be key to achieving high-performance lithium metal batteries(LMBs).Herein,we construct a lithium nitrate(LiNO_(3))-implanted electroactiveβphase polyvinylidene fluoride-co-hexafluoropropylene(PVDF-HFP)crystalline polymorph layer(PHL).The electronegatively charged polymer chains attain lithium ions on the surface to form lithium-ion charged channels.These channels act as reservoirs to sustainably release Li ions to recompense the ionic flux of electrolytes,decreasing the growth of lithium dendrites.The stretched molecular channels can also accelerate the transport of Li ions.The combined effects enable a high Coulombic efficiency of 97.0%for 250 cycles in lithium(Li)||copper(Cu)cell and a stable symmetric plating/stripping behavior over 2000 h at 3 mA cm^(-2)with ultrahigh Li utilization of 50%.Furthermore,the full cell coupled with PHL-Cu@Li anode and Li Fe PO_(4) cathode exhibits long-term cycle stability with high-capacity retention of 95.9%after 900 cycles.Impressively,the full cell paired with LiNi_(0.87)Co_(0.1)Mn_(0.03)O_(2)maintains a discharge capacity of 170.0 mAh g^(-1)with a capacity retention of 84.3%after 100 cycles even under harsh condition of ultralow N/P ratio of 0.83.This facile strategy will widen the potential application of LiNO_(3)in ester-based electrolyte for practical high-voltage LMBs.

Piezo1 channel exaggerates ferroptosis of nucleus pulposus cells by mediating mechanical stress-induced iron influx

To date,several molecules have been found to facilitate iron influx,while the types of iron influx channels remain to be elucidated.Here,Piezo1 channel was identified as a key iron transporter in response to mechanical stress.Piezo1-mediated iron overload disturbed iron metabolism and exaggerated ferroptosis in nucleus pulposus cells(NPCs).Importantly,Piezo1-induced iron influx was independent of the transferrin receptor(TFRC),a well-recognized iron gatekeeper.Furthermore,pharmacological inactivation of Piezo1 profoundly reduced iron accumulation,alleviated mitochondrial ROS,and suppressed ferroptotic alterations in stimulation of mechanical stress.Moreover,conditional knockout of Piezo1(Col2a1-CreERT Piezo1^(flox/flox))attenuated the mechanical injury-induced intervertebral disc degeneration(IVDD).Notably,the protective effect of Piezo1 deficiency in IVDD was dampened in Piezo1/Gpx4 conditional double knockout(cDKO)mice(Col2a1-CreERT Piezo1^(flox/flox)/Gpx4^(flox/flox)).These findings suggest that Piezo1 is a potential determinant of iron influx,indicating that the Piezo1-iron-ferroptosis axis might shed light on the treatment of mechanical stress-induced diseases.

Na^(+)/K^(+)-ATPase:ion pump,signal transducer,or cytoprotective protein,and novel biological functions

Na^(+)/K^(+)-ATPase is a transmembrane protein that has important roles in the maintenance of electrochemical gradients across cell membranes by transporting three Na^(+)out of and two K^(+)into cells.Additionally,Na^(+)/K^(+)-ATPase participates in Ca^(2+)-signaling transduction and neurotransmitter release by coordinating the ion concentration gradient across the cell membrane.Na^(+)/K^(+)-ATPase works synergistically with multiple ion channels in the cell membrane to form a dynamic network of ion homeostatic regulation and affects cellular communication by regulating chemical signals and the ion balance among different types of cells.Therefo re,it is not surprising that Na^(+)/K^(+)-ATPase dysfunction has emerged as a risk factor for a variety of neurological diseases.However,published studies have so far only elucidated the important roles of Na^(+)/K^(+)-ATPase dysfunction in disease development,and we are lacking detailed mechanisms to clarify how Na^(+)/K^(+)-ATPase affects cell function.Our recent studies revealed that membrane loss of Na^(+)/K^(+)-ATPase is a key mechanism in many neurological disorders,particularly stroke and Parkinson's disease.Stabilization of plasma membrane Na^(+)/K^(+)-ATPase with an antibody is a novel strategy to treat these diseases.For this reason,Na^(+)/K^(+)-ATPase acts not only as a simple ion pump but also as a sensor/regulator or cytoprotective protein,participating in signal transduction such as neuronal autophagy and apoptosis,and glial cell migration.Thus,the present review attempts to summarize the novel biological functions of Na^(+)/K^(+)-ATPase and Na^(+)/K^(+)-ATPase-related pathogenesis.The potential for novel strategies to treat Na^(+)/K^(+)-ATPase-related brain diseases will also be discussed.

Cav3.2 channel regulates cerebral ischemia/reperfusion injury:a promising target for intervention

Calcium influx into neurons triggers neuronal death during cerebral ischemia/reperfusion injury.Various calcium channels are involved in cerebral ischemia/reperfusion injury.Cav3.2 channel is a main subtype of T-type calcium channels.T-type calcium channel blockers,such as pimozide and mibefradil,have been shown to prevent cerebral ischemia/reperfusion injury-induced brain injury.However,the role of Cav3.2 channels in cerebral ischemia/reperfusion injury remains unclear.Here,in vitro and in vivo models of cerebral ischemia/reperfusion injury were established using middle cerebral artery occlusion in mice and high glucose hypoxia/reoxygenation exposure in primary hippocampal neurons.The results showed that Cav3.2 expression was significantly upregulated in injured hippocampal tissue and primary hippocampal neurons.We further established a Cav3.2 gene-knockout mouse model of cerebral ischemia/reperfusion injury.Cav3.2 knockout markedly reduced infarct volume and brain water content,and alleviated neurological dysfunction after cerebral ischemia/reperfusion injury.Additionally,Cav3.2 knockout attenuated cerebral ischemia/reperfusion injury-induced oxidative stress,inflammatory response,and neuronal apoptosis.In the hippocampus of Cav3.2-knockout mice,calcineurin overexpression offset the beneficial effect of Cav3.2 knockout after cerebral ischemia/reperfusion injury.These findings suggest that the neuroprotective function of Cav3.2 knockout is mediated by calcineurin/nuclear factor of activated T cells 3 signaling.Findings from this study suggest that Cav3.2 could be a promising target for treatment of cerebral ischemia/reperfusion injury.

Influence of variable viscosity and double diffusion on the convective stability of a nanofluid flow in an inclined porous channel

The influence of variable viscosity and double diffusion on the convective stability of a nanofluid flow in an inclined porous channel is investigated.The DarcyBrinkman model is used to characterize the fluid flow dynamics in porous materials.The analytical solutions are obtained for the unidirectional and completely developed flow.Based on a normal mode analysis,the generalized eigenvalue problem under a perturbed state is solved.The eigenvalue problem is then solved by the spectral method.Finally,the critical Rayleigh number with the corresponding wavenumber is evaluated at the assigned values of the other flow-governing parameters.The results show that increasing the Darcy number,the Lewis number,the Dufour parameter,or the Soret parameter increases the stability of the system,whereas increasing the inclination angle of the channel destabilizes the flow.Besides,the flow is the most unstable when the channel is vertically oriented.

Two-Staged Method for Ice Channel Identification Based on Image Segmentation and Corner Point Regression

Identification of the ice channel is the basic technology for developing intelligent ships in ice-covered waters,which is important to ensure the safety and economy of navigation.In the Arctic,merchant ships with low ice class often navigate in channels opened up by icebreakers.Navigation in the ice channel often depends on good maneuverability skills and abundant experience from the captain to a large extent.The ship may get stuck if steered into ice fields off the channel.Under this circumstance,it is very important to study how to identify the boundary lines of ice channels with a reliable method.In this paper,a two-staged ice channel identification method is developed based on image segmentation and corner point regression.The first stage employs the image segmentation method to extract channel regions.In the second stage,an intelligent corner regression network is proposed to extract the channel boundary lines from the channel region.A non-intelligent angle-based filtering and clustering method is proposed and compared with corner point regression network.The training and evaluation of the segmentation method and corner regression network are carried out on the synthetic and real ice channel dataset.The evaluation results show that the accuracy of the method using the corner point regression network in the second stage is achieved as high as 73.33%on the synthetic ice channel dataset and 70.66%on the real ice channel dataset,and the processing speed can reach up to 14.58frames per second.

Channel Correlation Based User Grouping Algorithm for Nonlinear Precoding Satellite Communication System

Low Earth Orbit(LEO)multibeam satellites will be widely used in the next generation of satellite communication systems,whose inter-beam interference will inevitably limit the performance of the whole system.Nonlinear precoding such as Tomlinson-Harashima precoding(THP)algorithm has been proved to be a promising technology to solve this problem,which has smaller noise amplification effect compared with linear precoding.However,the similarity of different user channels(defined as channel correlation)will degrade the performance of THP algorithm.In this paper,we qualitatively analyze the inter-beam interference in the whole process of LEO satellite over a specific coverage area,and the impact of channel correlation on Signal-to-Noise Ratio(SNR)of receivers when THP is applied.One user grouping algorithm is proposed based on the analysis of channel correlation,which could decrease the number of users with high channel correlation in each precoding group,thus improve the performance of THP.Furthermore,our algorithm is designed under the premise of co-frequency deployment and orthogonal frequency division multiplexing(OFDM),which leads to more users under severe inter-beam interference compared to the existing research on geostationary orbit satellites broadcasting systems.Simulation results show that the proposed user grouping algorithm possesses higher channel capacity and better bit error rate(BER)performance in high SNR conditions relative to existing works.

Deep learning for joint channel estimation and feedback in massive MIMO systems

The great potentials of massive Multiple-Input Multiple-Output(MIMO)in Frequency Division Duplex(FDD)mode can be fully exploited when the downlink Channel State Information(CSI)is available at base stations.However,the accurate CsI is difficult to obtain due to the large amount of feedback overhead caused by massive antennas.In this paper,we propose a deep learning based joint channel estimation and feedback framework,which comprehensively realizes the estimation,compression,and reconstruction of downlink channels in FDD massive MIMO systems.Two networks are constructed to perform estimation and feedback explicitly and implicitly.The explicit network adopts a multi-Signal-to-Noise-Ratios(SNRs)technique to obtain a single trained channel estimation subnet that works well with different SNRs and employs a deep residual network to reconstruct the channels,while the implicit network directly compresses pilots and sends them back to reduce network parameters.Quantization module is also designed to generate data-bearing bitstreams.Simulation results show that the two proposed networks exhibit excellent performance of reconstruction and are robust to different environments and quantization errors.