Sedimentary architecture models of deepwater turbidite channel systems in the Niger Delta continental slope,West Africa

This paper studied an architecture model of turbidite channel systems based on the shallow- layer high resolution 3D seismic information in the deepwater area in the Niger Delta continental slope, West Africa as a prototype model. Different types of channel systems were identified and the corresponding architecture models were established. The controlling factors, evaluation criteria and spatial distribution of different channel systems were analyzed. This study shows that turbidite channel systems of West Africa could be classified into three types; confined, semi-confined and unconfined, according to the condition of canyon and the levees on both sides. Oil one hand, along the transport direction, channel system evolves from confined to unconfined. Within channel systems, channel complexes, including two types of incised and enveloped, are the most important reservoir bodies. On the other hand, there is a channel complex evolution from incised to enveloped vertically. The geological factors exert impacts of different levels on the architecture of the turbidite channels in different sedimentary systems or even within the same system.

Formation of Nucleolar Channel System in Human Endometrium in vitro is Independent of Progesterone

Objective To determine whether formation of the nucleolar channel system (NCS) in human endometrium depends on the presence of progesteronal steroids. Materials & Methods Tissues of late proliferative endometrium were obtained from 5 normally cycling women of reproductive age. Half of each tissue was cultured in the DMEM medium containing diethylstilbesterol (25 μg/mL) plus medroxyprogesterone acetate (25 μg/mL) (E + P culture). As a control, the other half was cultured in the medium alone. After 100 h incubation, the tissues were assessed for the formation of NCS with transmission electron microscope.Results NCS was observed in the endometrial epithelium treated with E + P or the medium alone. Moreover, giant mitochondria and glycogen accumulation were both seen in epithelia derived from both types of cultures.Conclusion Progesterone would be not indispensable for the formation of NCS in human endometrium. Transition of proliferative endometrium to the secretory stage in vitro could occur even in the absence of both estrogen and progesterone.

Sedimentary elements,evolutions and controlling factors of the Miocene channel system:a case study of the deep-water Taranaki Basin in New Zealand

Deep-water channel systems are important petroleum reservoirs,and many have been discovered worldwide.Understanding deep-water channel sedimentary elements and evolution is helpful for deep-sea petroleum exploration and development.Based on high-resolution 3D seismic data,the Miocene channel system in the deep-water Taranaki Basin,New Zealand,was analyzed by using seismic interpretation techniques such as interlayer attribute extraction and strata slicing.The channel system was divided into five composite channels(CC-I to CC-V)according to four secondary level channel boundaries,and sedimentary elements such as channels,slump deposits,inner levees,mass transport deposits,and hemipelagic drape deposits were identified in the channel system.The morphological characteristics of several composite channels exhibited stark variances,and the overall morphology of the composite channels changed from relatively straight to highly sinuous to relatively straight.The evolution of the composite channels involved a gradual and repeated process of erosion and filling,and the composite channels could be divided into three evolutionary stages:initial erosion-filling,later erosion-filling(multistage),and channel abandonment.The middle Miocene channel system may have formed as a consequence of combined regional tectonic activity and global climatic change,and its intricate morphological alterations may have been influenced by the channel's ability to self-regulate and gravity flow properties.When studying the sedimentary evolution of a large-scale deep-water channel system in the Taranaki Basin during the Oligocene-Miocene,which transitioned from a passive margin to plate convergence,it can be understood how tectonic activity affected the channel and can also provide a theoretical reference for the evolution of the deepwater channels in areas with similar tectonic conversion environments around the world.

Seismic stratigraphy of the Qiongdongnan deep sea channel system,northwest South China Sea

Based on more than 4000 km 2D seismic data and seismic stratigraphic analysis, we discussed the extent and formation mechanism of the Qiongdongnan deep sea channel. The Qiongdongnan deep sea channel is a large incised channel which extends from the east boundary of the Yinggehai Basin, through the whole Qiongdongnan and the Xisha trough, and terminates in the western part of the northwest subbasin of South China Sea. It is more than 570 km long and 4–8 km wide. The chaotic (or continuous) middle (or high) amplitude, middle (or high) continuity seismic facies of the channel reflect the different lithological distribution of the channel. The channel formed as a complex result of global sea level drop during early Pliocene, large scale of sediment supply to the Yinggehai Basin, inversion event of the Red River strike-slip fault, and tilted direction of the Qiongdongnan Basin. The large scale of sediment supply from Red River caused the shelf break of the Yinggehai Basin to move torwards the S and SE direction and developed large scale of prograding wedge from the Miocene, and the inversion of the Red River strike-slip fault induced the sediment slump which formed the Qiongdongnan deep sea channel.

Origin and fate of the nucleolar channel system of normal human endometrium^1

Human normal endometrium was examined in ultrathin sections. Nucleolar channel system (NCS) appeared in the endometrial epithelial cells during the early and mid secretory phase of menstrual cycle. The NCS was a hollow ball like structure of different sizes and was composed of 2 to 5 rows of tubules embedded in an amorphous matrix. On its surface there were numerous electron dense particles resembling ribosonies. It was usually located within or associated with the nucleolus. Sometimes, it was close to the nuclear envelope or protruding out from the nucleus. On occasion, NCS with simplified structure was found in the perinuclear cytoplasm. Concepts concerning the genesis, involution and function(s) of the NCS were discussed.

Modelling Impact of Dredging and Dumping in Ebb-Flood Channel Systems

For a channel-shoal system in a funnel-shaped basin the impact of dredging and dumping is investigated using a complex process-based model. First, the residual flow and sediment transport circulations are analysed for the channel-shoal pattern, which has emerged after a longterm model simulation. Results are compared to the Western Scheldt estuary, which forms the inspiration for this study. Subsequently, different dredge and dump scenarios are modelled, according to a conceptual model, in which ebb- and flood-channels and enclosed shoals form morphodynamic units (cells) with their own sediment circulation. Model results show that dumping sediment in a channel further reduces the channel depth and induces erosion in the opposite channel, which enhances tilting of the cross-section of the cell and eventually can lead to the degeneration of a multiple channel system into a single channel. The impact of different dredging and dumping cases agrees with results from a stability analysis. This means that this type of model applied to a realistic geometry can potentially be used for better prediction of the impact of human interventions.

Annual pattern of zooplankton communities and their environmental response in a subtropical maritime channel system in the northern Bay of Bengal, Bangladesh

Zooplankton plays an important role in aquatic food webs by fluxing of energy from primary producer to subsequent trophic levels in the food chain. The annual pattern of zooplankton communities and potential environmental drivers were studied in the Kohelia channel, Bangladesh from summer 2014 to spring 2015.Samples were collected using net at a depth of 1 m. A total of 32 species belonged to 18 orders, 27 families and 15 taxonomic groups were identified. Of these species, 22 distributed in all four seasons of which 8 were dominant and highly contributing to the total communities. Species number peaked in summer next to winter and fall in spring while maximum abundance was in summer and minimum in spring. Multivariate analyses showed that there was a clear annual pattern in the zooplankton communities. Species diversity and evenness peaked in spring but fall in autumn while the high value of species richness was found in winter. Biological-environmental best matching（BIO-ENV） analyses conformed that community pattern of zooplankton was mainly driven by transparency salinity, and temperature individually or combined with water nutrients. These results demonstrate that annual pattern of the zooplankton community shaped by channel environmental factors in subtropical channel ecosystems, thus might be used for community-based subtropical coastal water bioassessment.

Principle of Line Configuration and Monte-Carlo Simulation for Shared Multi-Channel System

Based on the steady-state solution of finite-state birth and death process, the principle of line configuration for shared multi-channel system is analyzed. Call congestion ratio equation and channel utilization ratio equation are deduced, and visualized data analysis is presented. The analy-sis indicates that, calculated with the proposed equations, the overestimate for call congestion ratio and channel utilization ratio can be rectified, and thereby the cost of channels can be saved by 2000 in a small system.With MATLAB programming, line configuration methods are provided. In order to generally and intuitively show the dynamic running of the system, and to analyze,promote and improve it, the system is simulated using M/M/n/n/m queuing model and Monte-Carlo method. In addition, the simulation validates the correctness of the theoretical analysis and optimizing configuration method.

Seismic Imaging and Reservoir Architecture of Sub-Marine Channel Systems Offshore West Nile Delta of Egypt

Offshore Nile Delta gas reservoirs are dominated by slope-channel systems of Plio-Pleistocene age. High-quality, three-dimensional seismic imaging has significantly helped in defining the geomorphology and architectures of these channels. Integrating seismic, logs and core data from four wells resulted in understanding of different stages of channel development and reservoir quality. The studied reservoirs that are largely controlled by episodes of transgressive-regressive events resulted in deposition of fine grained sediment and shale. Sienna channel complex consists of unconfined channel system with clearly defined development stages. The stages include amalgamated or stacked channels followed by channel abandonment phases and local flooding events. The depositional pattern continued through the Late Pliocene-Pleistocene. SimSat-P1 and SimSat-P2 reservoirs are characterized by isolated sand bodies, most probably relics of fan depositional setting. The depositional scenario that is largely controlled by successive transgression and flooding events resulted in deposition of interbedded, sheet-like, fine grained sediment and shale.

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.

Ultimately Bounded Output Feedback Control for Networked Nonlinear Systems With Unreliable Communication Channel: A Buffer-Aided Strategy

This paper concerns ultimately bounded output-feedback control problems for networked systems with unknown nonlinear dynamics. Sensor-to-observer signal transmission is facilitated over networks that has communication constraints.These transmissions are carried out over an unreliable communication channel. In order to enhance the utilization rate of measurement data, a buffer-aided strategy is novelly employed to store historical measurements when communication networks are inaccessible. Using the neural network technique, a novel observer-based controller is introduced to address effects of signal transmission behaviors and unknown nonlinear dynamics.Through the application of stochastic analysis and Lyapunov stability, a joint framework is constructed for analyzing resultant system performance under the introduced controller. Subsequently, existence conditions for the desired output-feedback controller are delineated. The required parameters for the observerbased controller are then determined by resolving some specific matrix inequalities. Finally, a simulation example is showcased to confirm method efficacy.

CNN Channel Attention Intrusion Detection SystemUsing NSL-KDD Dataset

Intrusion detection systems(IDS)are essential in the field of cybersecurity because they protect networks from a wide range of online threats.The goal of this research is to meet the urgent need for small-footprint,highly-adaptable Network Intrusion Detection Systems(NIDS)that can identify anomalies.The NSL-KDD dataset is used in the study;it is a sizable collection comprising 43 variables with the label’s“attack”and“level.”It proposes a novel approach to intrusion detection based on the combination of channel attention and convolutional neural networks(CNN).Furthermore,this dataset makes it easier to conduct a thorough assessment of the suggested intrusion detection strategy.Furthermore,maintaining operating efficiency while improving detection accuracy is the primary goal of this work.Moreover,typical NIDS examines both risky and typical behavior using a variety of techniques.On the NSL-KDD dataset,our CNN-based approach achieves an astounding 99.728%accuracy rate when paired with channel attention.Compared to previous approaches such as ensemble learning,CNN,RBM(Boltzmann machine),ANN,hybrid auto-encoders with CNN,MCNN,and ANN,and adaptive algorithms,our solution significantly improves intrusion detection performance.Moreover,the results highlight the effectiveness of our suggested method in improving intrusion detection precision,signifying a noteworthy advancement in this field.Subsequent efforts will focus on strengthening and expanding our approach in order to counteract growing cyberthreats and adjust to changing network circumstances.

Channel Estimation for Reconfigurable Intelligent Surface Aided Multiuser Millimeter-Wave/THz Systems

It is assumed that reconfigurable intelligent surface(RIS)is a key technology to enable the potential of mmWave communications.The passivity of the RIS makes channel estimation difficult because the channel can only be measured at the transceiver and not at the RIS.In this paper,we propose a novel separate channel estimator via exploiting the cascaded sparsity in the continuously valued angular domain of the cascaded channel for the RIS-enabled millimeter-wave/Tera-Hz systems,i.e.,the two-stage estimation method where the cascaded channel is separated into the base station(BS)-RIS and the RIS-user(UE)ones.Specifically,we first reveal the cascaded sparsity,i.e.,the sparsity exists in the hybrid angular domains of BS-RIS and the RIS-UEs separated channels,to construct the specific sparsity structure for RIS enabled multi-user systems.Then,we formulate the channel estimation problem using atomic norm minimization(ANM)to enhance the proposed sparsity structure in the continuous angular domains,where a low-complexity channel estimator via Alternating Direction Method of Multipliers(ADMM)is proposed.Simulation findings demonstrate that the proposed channel estimator outperforms the current state-of-the-arts in terms of performance.

Channel estimation in integrated radar and communication systems with power amplifier distortion

To reduce the negative impact of the power amplifier(PA)nonlinear distortion caused by the orthogonal frequency division multiplexing(OFDM)waveform with high peak-to-average power ratio(PAPR)in integrated radar and communication(RadCom)systems is studied,the channel estimation in passive sensing scenarios.Adaptive channel estimation methods are proposed based on different pilot patterns,considering nonlinear distortion and channel sparsity.The proposed methods achieve sparse channel results by manipulating the least squares(LS)frequency-domain channel estimation results to preserve the most significant taps.The decision-aided method is used to optimize the sparse channel results to reduce the effect of nonlinear distortion.Numerical results show that the channel estimation performance of the proposed methods is better than that of the conventional methods under different pilot patterns.In addition,the bit error rate performance in communication and passive radar detection performance show that the proposed methods have good comprehensive performance.

UAMP-Based Delay-Doppler Channel Estimation for OTFS Systems

Orthogonal time frequency space(OTFS)technique, which modulates data symbols in the delayDoppler(DD) domain, presents a potential solution for supporting reliable information transmission in highmobility vehicular networks. In this paper, we study the issues of DD channel estimation for OTFS in the presence of fractional Doppler. We first propose a channel estimation algorithm with both low complexity and high accuracy based on the unitary approximate message passing(UAMP), which exploits the structured sparsity of the effective DD domain channel using hidden Markov model(HMM). The empirical state evolution(SE) analysis is then leveraged to predict the performance of our proposed algorithm. To refine the hyperparameters in the proposed algorithm,we derive the update criterion for the hyperparameters through the expectation-maximization(EM) algorithm. Finally, Our simulation results demonstrate that our proposed algorithm can achieve a significant gain over various baseline schemes.

Influence of the Channel Design on the Heat Exchange Characteristics of Pulsating Flows in the Supply System of an Engine

Heat engines based on reciprocating machines remain in demand as energy converters in a variety of industries around the world.The aim of the study was to evaluate the gas-dynamic,consumable and heat exchange characteristics of non-stationary air flows in a supply system with transverse profiling of valve channels based on experimental studies.Valve channels with cross sections in the form of a circle,square and triangle were used to control the consumable and heat exchange characteristics of the flows in the supply system of the reciprocatingengine model.The article presents data on changes in local velocity,volumetric airflow and instantaneous heat transfer coefficient of non-stationary airflow in supply systems with different valve channel designs.A spectral analysis of the pulsations of the local heat transfer coefficient was also performed.The Nusselt number was calculated for the studied supply systems.The figured valve channels lead to an increase in the volumetric airflow through the supply systemupto32%comparedwiththe basic configuration.The useof a square valve channel leads to suppression of heat transfer(drop is about 15%)compared to the basic supply system,and the use of a triangular valve channel causes an intensification of heat transfer(growth is about 17.5%).The obtained data can be useful for refining mathematical models,adjusting machine learning algorithms,and improving design methods for supply systems of reciprocating machines to improve their technical,economic,and environmental characteristics.

Tensor Decomposition-Based Channel Estimation and Sensing for Millimeter Wave MIMO-OFDM V2I Systems

An integrated sensing and communication(ISAC)scheme for a millimeter wave(mmWave)multiple-input multiple-output orthogonal frequency division multiplexing(MIMO-OFDM)Vehicle-to-Infrastructure(V2I)system is presented,in which both the access point(AP)and the vehicle are equipped with large antenna arrays and employ hybrid analog and digital beamforming structures to compensate the path loss,meanwhile compromise between hardware complexity and system performance.Based on the sparse scattering nature of the mmWave channel,the received signal at the AP is organized to a four-order tensor by the introduced novel frame structure.A CANDECOMP/PARAFAC(CP)decomposition-based method is proposed for time-varying channel parameter extraction,including angles of departure/arrival(AoDs/AoAs),Doppler shift,time delay and path gain.Then leveraging the estimates of channel parameters,a nonlinear weighted least-square problem is proposed to recover the location accurately,heading and velocity of vehicles.Simulation results show that the proposed methods are effective and efficient in time-varying channel estimation and vehicle sensing in mmWave MIMOOFDM V2I systems.

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.

Closed BER expression of multi-user DS UWB systemsin indoor fading channel

The bit error rate （BER） performance of multi-user direct spreading bi-phase shift keying （DSBPSK） direct impulse ultra wideband （UWB） systems is analyzed and simulated based on a statistical indoor multi-path fading channel model. The BER of the system is theoretically derived and given in closed form, which is expressed in terms of channel parameters and system parameters such as pulse width parameter, pulse repeat period, user number and pulse waveform. With this BER expression, the effect of these parameters on the system performance can be evaluated in a uniform way. Simulation results well match the theory numerical results, and prove that the multi-access interference （MAI） of DS-BPSK UWB is a normal distribution.