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.

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.

Simulation of wind-driven circulation and temperature in the near-shore region of southern Lake Michigan by using a channelized model

To enhance the efficiency of a pathogen forecasting model in the beach areas of southern Lake Michigan and to reduce the computation time, the near-shore current is approximated as a channelized flow parallel to the shorelines in clockwise or anti-clock- wise direction within the accuracy tolerance range. A channelized model with a curvilinear boundary can significantly reduce the computation effort, and at the same time achieve a good agreement between the predicted and measured water surface elevations, currents, and water temperatures. The sensitivity analysis results show that the suitable channel width for the near-shore region of southern Lake Michigan should be no less than 10 kin. The modeling results of the water temperature are much less sensitive to the channel width than those of the current velocity and the water surface elevation. The modeling results also show a close correlation between the speeds of the wind and the near-shore current. The current may fully respond the wind stress with a time lag of several hours. The correlation may provide an approximate estimation of the lake circulation under some wind conditions for a practical fore- casting purpose. More complex wind-current relationships need to be described with a more sophisticated hydrodynamic model. This verified model can be used for the pathogen forecasting in the near-shore regions of southern Lake Michigan in the future.

Potassium and calcium channels in different nerve cells act as therapeutic targets in neurological disorders

The central nervous system, information integration center of the body, is mainly composed of neurons and glial cells. The neuron is one of the most basic and important structural and functional units of the central nervous system, with sensory stimulation and excitation conduction functions. Astrocytes and microglia belong to the glial cell family, which is the main source of cytokines and represents the main defense system of the central nervous system. Nerve cells undergo neurotransmission or gliotransmission, which regulates neuronal activity via the ion channels, receptors, or transporters expressed on nerve cell membranes. Ion channels, composed of large transmembrane proteins, play crucial roles in maintaining nerve cell homeostasis. These channels are also important for control of the membrane potential and in the secretion of neurotransmitters. A variety of cellular functions and life activities, including functional regulation of the central nervous system, the generation and conduction of nerve excitation, the occurrence of receptor potential, heart pulsation, smooth muscle peristalsis, skeletal muscle contraction, and hormone secretion, are closely related to ion channels associated with passive transmembrane transport. Two types of ion channels in the central nervous system, potassium channels and calcium channels, are closely related to various neurological disorders, including Alzheimer's disease, Parkinson's disease, and epilepsy. Accordingly, various drugs that can affect these ion channels have been explored deeply to provide new directions for the treatment of these neurological disorders. In this review, we focus on the functions of potassium and calcium ion channels in different nerve cells and their involvement in neurological disorders such as Parkinson's disease, Alzheimer's disease, depression, epilepsy, autism, and rare disorders. We also describe several clinical drugs that target potassium or calcium channels in nerve cells and could be used to treat these disorders. We concluded that there are few clinical drugs that can improve the pathology these diseases by acting on potassium or calcium ions. Although a few novel ion-channelspecific modulators have been discovered, meaningful therapies have largely not yet been realized. The lack of target-specific drugs, their requirement to cross the blood–brain barrier, and their exact underlying mechanisms all need further attention. This review aims to explain the urgent problems that need research progress and provide comprehensive information aiming to arouse the research community's interest in the development of ion channel-targeting drugs and the identification of new therapeutic targets for that can increase the cure rate of nervous system diseases and reduce the occurrence of adverse reactions in other systems.

MixerKT:A Knowledge Tracing Model Based on Pure MLP Architecture

In the field of intelligent education,the integration of artificial intelligence,especially deep learning technologies,has garnered significant attention.Knowledge tracing(KT)plays a pivotal role in this field by predicting students’future performance through the analysis of historical interaction data,thereby assisting educators in evaluating knowledgemastery and tailoring instructional strategies.Traditional knowledge tracingmethods,largely based on Recurrent Neural Networks(RNNs)and Transformer models,primarily focus on capturing long-term interaction patterns in sequential data.However,these models may neglect crucial short-term dynamics and other relevant features.This paper introduces a novel approach to knowledge tracing by leveraging a pure Multilayer Perceptron(MLP)architecture.We proposeMixerKT,a knowledge tracing model based on theHyperMixer framework,which uniquely integrates global and localMixer feature extractors.This architecture enables more effective extraction of both long-terminteraction trends and recent learning behaviors,addressing limitations in currentmodels thatmay overlook these key aspects.Empirical evaluations on twowidely-used datasets,ASSIS Tments2009 and Algebra2005,demonstrate that MixerKT consistently outperforms several state-of-the-art models,including DKT,SAKT,and Separated Self-Attentive Neural Knowledge Tracing(SAINT).Specifically,MixerKT achieves higher prediction accuracy,highlighting its effectiveness in capturing the nuances of learners’knowledge states.These results indicate that our model provides a more comprehensive representation of student learning patterns,enhancing the ability to predict future performance with greater precision.

Engine Misfire Fault Detection Based on the Channel Attention Convolutional Model

To accurately diagnosemisfire faults in automotive engines,we propose a Channel Attention Convolutional Model,specifically the Squeeze-and-Excitation Networks(SENET),for classifying engine vibration signals and precisely pinpointing misfire faults.In the experiment,we established a total of 11 distinct states,encompassing the engine’s normal state,single-cylinder misfire faults,and dual-cylinder misfire faults for different cylinders.Data collection was facilitated by a highly sensitive acceleration signal collector with a high sampling rate of 20,840Hz.The collected data were methodically divided into training and testing sets based on different experimental groups to ensure generalization and prevent overlap between the two sets.The results revealed that,with a vibration acceleration sequence of 1000 time steps(approximately 50 ms)as input,the SENET model achieved a misfire fault detection accuracy of 99.8%.For comparison,we also trained and tested several commonly used models,including Long Short-Term Memory(LSTM),Transformer,and Multi-Scale Residual Networks(MSRESNET),yielding accuracy rates of 84%,79%,and 95%,respectively.This underscores the superior accuracy of the SENET model in detecting engine misfire faults compared to other models.Furthermore,the F1 scores for each type of recognition in the SENET model surpassed 0.98,outperforming the baseline models.Our analysis indicated that the misclassified samples in the LSTM and Transformer models’predictions were primarily due to intra-class misidentifications between single-cylinder and dual-cylinder misfire scenarios.To delve deeper,we conducted a visual analysis of the features extracted by the LSTM and SENET models using T-distributed Stochastic Neighbor Embedding(T-SNE)technology.The findings revealed that,in the LSTMmodel,data points of the same type tended to cluster together with significant overlap.Conversely,in the SENET model,data points of various types were more widely and evenly dispersed,demonstrating its effectiveness in distinguishing between different fault types.

Secure Channel Estimation Using Norm Estimation Model for 5G Next Generation Wireless Networks

The emergence of next generation networks(NextG),including 5G and beyond,is reshaping the technological landscape of cellular and mobile networks.These networks are sufficiently scaled to interconnect billions of users and devices.Researchers in academia and industry are focusing on technological advancements to achieve highspeed transmission,cell planning,and latency reduction to facilitate emerging applications such as virtual reality,the metaverse,smart cities,smart health,and autonomous vehicles.NextG continuously improves its network functionality to support these applications.Multiple input multiple output(MIMO)technology offers spectral efficiency,dependability,and overall performance in conjunctionwithNextG.This article proposes a secure channel estimation technique in MIMO topology using a norm-estimation model to provide comprehensive insights into protecting NextG network components against adversarial attacks.The technique aims to create long-lasting and secure NextG networks using this extended approach.The viability of MIMO applications and modern AI-driven methodologies to combat cybersecurity threats are explored in this research.Moreover,the proposed model demonstrates high performance in terms of reliability and accuracy,with a 20%reduction in the MalOut-RealOut-Diff metric compared to existing state-of-the-art techniques.

Brain-derived neurotrophic factor signaling in the neuromuscular junction during developmental axonal competition and synapse elimination

During the development of the nervous system,there is an overproduction of neurons and synapses.Hebbian competition between neighboring nerve endings and synapses performing different activity levels leads to their elimination or strengthening.We have extensively studied the involvement of the brain-derived neurotrophic factor-Tropomyosin-related kinase B receptor neurotrophic retrograde pathway,at the neuromuscular junction,in the axonal development and synapse elimination process versus the synapse consolidation.The purpose of this review is to describe the neurotrophic influence on developmental synapse elimination,in relation to other molecular pathways that we and others have found to regulate this process.In particular,we summarize our published results based on transmitter release analysis and axonal counts to show the different involvement of the presynaptic acetylcholine muscarinic autoreceptors,coupled to downstream serine-threonine protein kinases A and C(PKA and PKC)and voltage-gated calcium channels,at different nerve endings in developmental competition.The dynamic changes that occur simultaneously in several nerve terminals and synapses converge across a postsynaptic site,influence each other,and require careful studies to individualize the mechanisms of specific endings.We describe an activity-dependent balance(related to the extent of transmitter release)between the presynaptic muscarinic subtypes and the neurotrophin-mediated TrkB/p75NTR pathways that can influence the timing and fate of the competitive interactions between the different axon terminals.The downstream displacement of the PKA/PKC activity ratio to lower values,both in competing nerve terminals and at postsynaptic sites,plays a relevant role in controlling the elimination of supernumerary synapses.Finally,calcium entry through L-and P/Q-subtypes of voltage-gated calcium channels(both channels are present,together with the N-type channel in developing nerve terminals)contributes to reduce transmitter release and promote withdrawal of the most unfavorable nerve terminals during elimination(the weakest in acetylcholine release and those that have already become silent).The main findings contribute to a better understanding of punishment-rewarding interactions between nerve endings during development.Identifying the molecular targets and signaling pathways that allow synapse consolidation or withdrawal of synapses in different situations is important for potential therapies in neurodegenerative diseases.

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.

Cooperative Anti-Jamming and Interference Mitigation for UAV Networks: A Local Altruistic Game Approach

To improve the anti-jamming and interference mitigation ability of the UAV-aided communication systems, this paper investigates the channel selection optimization problem in face of both internal mutual interference and external malicious jamming. A cooperative anti-jamming and interference mitigation method based on local altruistic is proposed to optimize UAVs’ channel selection. Specifically, a Stackelberg game is modeled to formulate the confrontation relationship between UAVs and the jammer. A local altruistic game is modeled with each UAV considering the utilities of both itself and other UAVs. A distributed cooperative anti-jamming and interference mitigation algorithm is proposed to obtain the Stackelberg equilibrium. Finally, the convergence of the proposed algorithm and the impact of the transmission power on the system loss value are analyzed, and the anti-jamming performance of the proposed algorithm can be improved by around 64% compared with the existing algorithms.