True Channel Research Articles

Selective-collective scalable locomotion control of helical magnetic swimmers within confined channels using global magnetic fields

Achieving selective-individual and collective control over multiple magnetic microrobots remains a formidable challenge. Existing techniques for controlling identical magnetic swimmers are often limited to two-dimensional, small working spaces, while heterogeneous swimmers can only be controlled in small numbers without the option for collective control. In this study, we present a purely magnetic control methodology for the selective-scalable locomotion of helical magnetic swimmers within confined channels. By employing a unique gradient field distribution, referred to as the "selection field," along with space-uniform rotating fields, we establish a "selection volume" that allows swimmers within it to fully rotate, while those outside remain stationary. We explore various conditions of the selection volume to analyze the locomotion dynamics of the swimmers in relation to the position of the selection volume. Experimental results demonstrate the selective-scalable locomotion of identical robots, ranging from one to an arbitrary number (N) of robots, as well as their selective-individual manipulation for multitasking applications. Furthermore, compatibility of the proposed method with different magnetic torque-driven robots is exemplified through the selective control of rolling robots. Moreover, three-dimensional selective-scalable control is also demonstrated for four swimmers in a quasi-three-dimensional channel, as well as for two swimmers within a true three-dimensional channel.

Niclosamide does not modulate airway epithelial function through blocking of the calcium activated chloride channel, TMEM16A.

Niclosamide and benzbromarone have been described as inhibitors of the calcium activated chloride channel, TMEM16A, and on this basis have been considered and tested as clinical candidates for the treatment of airway diseases. However, both compounds have previously demonstrated activity on a range of additional biological targets and it is unclear from the literature to what extent any activity on TMEM16A may contribute to efficacy in these models of airway disease. The aim of the present study was therefore to examine the pharmacology and selectivity of these clinical candidates together with a structurally unrelated TMEM16A blocker, Ani9, in a range of functional assays to better appreciate the putative role of TMEM16A in the regulation of both epithelial ion transport and the development of an airway epithelial mucus secretory phenoptype. Benzbromarone and Ani9 both attenuated recombinant TMEM16A activity in patch clamp studies, whereas in contrast, niclosamide induced a paradoxical potentiation of the TMEM16A-mediated current. Niclosamide and benzbromarone were also demonstrated to attenuate receptor-dependent increases in intracellular Ca2+ levels ([Ca2+]i) which likely contributed to their concomitant attenuation of the Ca2+-stimulated short-circuit current responses of FRT-TMEM16A and primary human bronchial epithelial (HBE) cells. In contrast, Ani9 attenuated the Ca2+-stimulated short-circuit current responses of both cell systems without influencing [Ca2+]i which supports a true channel blocking mechanism for this compound. Additional studies using HBE cells revealed effects of both niclosamide and benzbromarone on global ion transport processes (absorptive and secretory) as well as signs of toxicity (elevated LDH levels, loss of transepithelial resistance) that were not shared by Ani9. Ani9 also failed to influence the IL-13 induced differentiation of HBE towards a goblet cell rich, mucus hypersecreting epithelium, whereas niclosamide and benzbromarone attenuated numbers of both goblet and multiciliated cells, that would be consistent with cellular toxicity. Together these data challenge the description of niclosamide as a TMEM16A blocker and illustrate a range of off-target effects of both niclosamide and benzbromarone which may contribute to the reported activity in models of airway function.

The role of potassium channels in tumours of the gastrointestinal tract: a focus on the human ether-à-go-go related gene 1 channels.

Potassium channels are often dysregulated in tumours of the gastrointestinal (GI) tract. Among them, the voltage-dependent channel KV 11.1, also known as human ether-à-go-go related gene 1 (hERG1), is frequently expressed in tumours and precancerous lesions of the GI tract. In precancerous lesions, hERG1 behaves as a progression factor, contributing to identifying those patients whose lesions can progress towards true cancers. In advanced cancers, such as colorectal and pancreatic cancer, a high hERG1 expression represents a negative prognostic factor, contributing to identifying high risk patients. The only exception is represented by neuroendocrine cancers of both the ileum and the pancreas, where hERG1 represents a positive prognostic factor for survival. In GI tumours, hERG1 can function either as a true channel, allowing outward potassium ion flux and membrane repolarisation, or in a non-canonical, non-conductive way. This occurs because, in cancer, hERG1 forms complexes with different plasma membrane and cytosolic proteins, instead of classical accessory subunits. In particular, hERG1 forms a complex with the β1subunit of integrin receptors: the hERG1-β1 complex. Growth and chemokine receptors, small GTPases, phosphoinositide 3-kinase, as well as other ion transporters or channels, are also recruited in the hERG1-β1 complex. The formation of multiprotein channel complexes represents an emerging mechanism allowing functional channel networking in both excitable and non-excitable cells. hERG1 represents a prototype of how multiprotein complexes operate in tumours, that is, giving rise to signalling hubs which can transmit and modulate signals arising from the tumour microenvironment, hence contributing to tumour progression and malignancy.

Massive MIMO Codebook Design Using Gaussian Mixture Model Based Clustering

The codebook design is the most essential core technique in constrained feedback massive multi-input multi-output (MIMO) system communications. MIMO vectors have been generally isotropic or evenly distributed in traditional codebook designs. In this paper, Gaussian mixture model (GMM) based clustering codebook design is proposed, which is inspired by the strong classification and analytical abilities of clustering techniques. Huge quantities of channel state information (CSI) are initially saved as entry data of the clustering process. Further, split into N number of clusters based on the shortest distance. The centroids part of clustering has been utilized for constructing a codebook with statistic channel information, with an average distance that is the shortest towards the true channel data. The enhanced GMM based clustering codebook design outperforms traditional methods, particularly in the situations of non-uniform distribution of channels as demonstrated via simulation results which match theoretical analyses concerning achievable rate. The proposed GMM based clustering codebook design is compared with DFT-based clustering codebook design and k-means based clustering codebook design.

Federated Online Deep Learning for CSIT and CSIR Estimation of FDD Multi-User Massive MIMO Systems

In this paper, we propose a federated online training framework for deep neural network (DNN)-based channel estimation (CE) in frequency-division duplexing (FDD) multi-user massive multiple-input multiple-output (MU-MIMO) systems. The proposed DNN consists of two stages, where Stage-I explores the partial common sparsity structure among the users, while Stage-II estimates the channel state information (CSI) with reduced pilot overhead leveraging the common support information provided by Stage-I. To realize online training, we first propose three axioms for a legitimate online loss function, based on which we develop the federated online training algorithm with convergence analysis. The proposed two-tier DNN is trained online at the base station (BS) based on real-time pilot measurements distributively fed back from the users without the need of true channel labels, and the estimates for the CSI at the transmitter (CSIT) can be simultaneously generated in real-time. Meanwhile, the weights of Stage-II can be broadcasted to the users for real-time estimation of the CSI at the receiver (CSIR) at each user. Simulation shows that the proposed solution achieves higher CE performance than traditional compressive sensing (CS)-based algorithms while enjoying much faster computation. The solution is also robust to the channel model mismatches induced by the change of propagation environment, and is able to track the time-varying channel model.

An Asymptotically MSE-Optimal Estimator Based on Gaussian Mixture Models

This paper investigates a channel estimator based on Gaussian mixture models (GMMs) in the context of linear inverse problems with additive Gaussian noise. We fit a GMM to given channel samples to obtain an analytic probability density function (PDF) which approximates the true channel PDF. Then, a conditional mean estimator (CME) corresponding to this approximating PDF is computed in closed form and used as an approximation of the optimal CME based on the true channel PDF. This optimal CME cannot be calculated analytically because the true channel PDF is generally unknown. We present mild conditions which allow us to prove the convergence of the GMM-based CME to the optimal CME as the number of GMM components is increased. Additionally, we investigate the estimator's computational complexity and present simplifications based on common model-based insights. Further, we study the estimator's behavior in numerical experiments including multiple-input multiple-output (MIMO) and wideband systems.

Wideband Channel Estimation With a Generative Adversarial Network

Communication at high carrier frequencies such as millimeter wave (mmWave) and terahertz (THz) requires channel estimation for very large bandwidths at low SNR. Hence, allocating an orthogonal pilot tone for each coherence bandwidth leads to excessive number of pilots. We leverage generative adversarial networks (GANs) to accurately estimate frequency selective channels with few pilots at low SNR. The proposed estimator first learns to produce channel samples from the true but unknown channel distribution via training the generative network, and then uses this trained network as a prior to estimate the current channel by optimizing the network's input vector in light of the current received signal. Our results show that at an SNR of -5 dB, even if a transceiver with one-bit phase shifters is employed, our design achieves the same channel estimation error as an LS estimator with SNR = 20 dB or the LMMSE estimator at 2.5 dB, both with fully digital architectures. Additionally, the GAN-based estimator reduces the required number of pilots by about 70% without significantly increasing the estimation error and required SNR. We also show that the generative network does not appear to require retraining even if the number of clusters and rays change considerably.

Online Deep Neural Networks for MmWave Massive MIMO Channel Estimation With Arbitrary Array Geometry

In this paper, we propose an online training framework for mmWave Massive MIMO channel estimation (CE) with limited pilots, where the training is based on real-time received pilot samples from the base station without requiring knowledge of the true channel. To realize this, we propose four axioms for a legitimate online loss function, based on which we develop a model-free online training algorithm with convergence analysis. Simulation shows that the proposed online deep neural network (DNN) achieves comparable CE accuracy to model-based compressive sensing (CS) algorithms, while enjoying much faster computation. In addition, the proposed method is robust to various model mismatches and can adapt to the change of the underlying propagation environment.

Quo vadimus? Fundamental problems of developing hybrid prostheses of thoracic aorta

This article is a review briefly characterizing the state of the art of hybrid surgery of the thoracic aorta using the frozen elephant trunk technique worldwide and in Russia, also discussing unsolved problems of fundamental science, being key issues in creation of new models of hybrid prostheses of the thoracic aorta. The main attention is paid to the problem of radial stiffness of the stent-graft portion of the prosthesis. Performed is a detailed analysis of the factors influencing this characteristic of the sent graft: shape, size and number of cells of the stent element, thickness of the nitinol wire it is made of, method of edge connection, nitinol properties depending on the alloy grade and methods of thermoforming. It is shown that excessive stiffness leads to the development of d-SINE syndrome. This is followed by discussing the problem of optimal stiffness of stent grafts, based on the design of stent graft elements and elastic properties of the wall of the true channel of a dissecting aortic aneurysm. Also proposed is an approach to solving the problem of d-SINE, consisting in creation of conical stent grafts and/or a gradual decrease of radial stiffness of stent elements in the direction of the distal portion. Comprehensively addressed are disadvantages of the graft portion of the prosthesis, in 95% of items made of polyethylene terephthalate fiber: susceptibility to degradation associated with manufacturing defects and intraoperative microdamages, abrasive effect in the zone of contact with stent elements, partial postoperative hydrolysis and an inflammatory reaction to a foreign body, often being clinically pronounced. Also touched upon are certain aspects of creating hermetic coatings of the graft portion, with the use of vancomycin possessing low cytotoxicity as part of an antibacterial component being promising. As a whole, it is demonstrated that advances in creating a novel generation of hybrid prostheses should be associated with new approaches and materials, to be obtained at the junction of medicine and fundamental sciences.

Low-Complexity Soft-Output MIMO Detectors Based on Optimal Channel Puncturing

Channel puncturing transforms a multiple-input multiple-output (MIMO) channel into a sparse lower-triangular form using the so-called WL decomposition scheme in order to reduce tree-based detection complexity. We propose computationally efficient soft-output detectors based on two forms of channel puncturing: augmented and two-sided. The augmented WL detector (AWLD) employs a punctured channel derived by triangularizing the true channel in augmented form, followed by left-sided Gaussian elimination. The two-sided WL detector (dubbed WLZ) employs right-sided reduction and left-sided elimination to puncture the channel. We prove that augmented channel puncturing is optimal in maximizing the lower-bound on the achievable information rate (AIR) based on a new mismatched detection model. We show that the AWLD decomposes into an MMSE prefilter and channel gain compensation stages, followed by a regular WL detector (WLD) that computes least-squares soft-decision estimates. Similarly, WLZ decomposes into a pre-processing reduction step followed by WLD. AWLD attains the same performance as the existing AIR-based partial marginalization (PM) detector, but with less computational complexity. We empirically show that WLZ attains the best complexity-performance tradeoff among tree-based detectors.

Ensuring Dynamic Accuracy of Aircraft’s Air Data System with Motionless Flush-Mounted Receiver of Flow

The article views, that draw-backs of aircraft’s traditional air data systems (ADS), built based installed in incoming air flow and installed outside the fuselage the pitot tube booms, temperature braking receivers, vane sensors of incidence angle and gliding angle are eliminated in original ADS with motionless flush-mounted receiver of flow. The functional scheme of aircraft’s air data system with motionless flush-mounted receiver of flow, built based on the original ion-mark sensor of aerodynamic angle and true airspeed, on receiving board of which the hole-receiver is installed to perceive the static pressure of incoming air flow. Models of operator sensitivity and dynamic errors of instrumentation channels due to random stationary atmospheric turbulence and random flow pulsations at location of the ion-mark sensor on fuselage of the aircraft are presented. Recommended to use the optimal linear Wiener filter, the synthesis method of which is revealed on example of the true airspeed instrumentation channel to reduce the stationary dynamic errors of instrumentation channels of air data system with motionless flush-mounted receiver due to atmospheric turbulence. Recommended to use the principle of integration to reduce the stationary random dynamic errors of instrumentation channels of air data system with motionless flush-mounted receiver due to flow pulsations near fuselage at location of ion-mark sensor. Proposed to use aeromechanical measuring and computing system built based VIMI method with Luenberger observer as an additional component of integrated air data system. Integrated system simulates the movement of aircraft in this flight mode and by flight parameters measured with high accuracy using flush-mounted receivers "restores" air signals included in equations of movement of aircraft. The structure, method and algorithms for determining air signals in channels of aeromechanical measuring and computing system with a Luenberger observer are presented. Using the example of true airspeed measurement, the analysis and quantitative assessment of residual dynamic error of integrating channel of integrated aircraft’s air data system with motionless flush-mounted receiver of flow is carried out.

Bounding and Estimating the Classical Information Rate of Quantum Channels With Memory

We consider the scenario of classical communication over a finite-dimensional quantum channel with memory using a separable-state input ensemble and local output measurements. We propose algorithms for estimating the information rate of such communication setups, along with algorithms for bounding the information rate based on so-called auxiliary channels. Some of the algorithms are extensions of their counterparts for (classical) finite-state-machine channels. Notably, we discuss suitable graphical models for doing the relevant computations. Moreover, the auxiliary channels are learned in a data-driven approach; i.e., only input/output sequences of the true channel are needed, but not the channel model of the true channel.

Training Optimization for Hybrid MIMO Communication Systems

Channel estimation is conceived for hybrid multiple-input multiple-output (MIMO) communication systems. Both mean square error minimization and mutual information maximization are used as our performance metrics and a pair of low-complexity channel estimation schemes are proposed. In each scheme, the training sequence and the analog matrices of the transmitter and receiver are jointly optimized. We commence by designing the optimal training sequences and analog matrices for the first scheme. Upon relying on the resultant optimal structures, the training optimization problems are substantially simplified and the nonconvexity resulting from the analog matrices can be overcome. In the second scheme, the channel estimation and data transmission share the same analog matrices, which beneficially reduces the overhead of optimizing the associated analog matrices. Therefore, a composite channel matrix is estimated instead of the true channel matrix. By exploiting the statistical optimization framework advocated, the analog matrices can be designed independently of the training sequence. Based on the resultant analog matrices, the training sequence can then be efficiently designed according to diverse channel statistics and performance metrics. Finally, we conclude by quantifying the performance benefits of the proposed estimation schemes.

Maximum Correntropy Criterion Based l1-Iterative Wiener Filter for Sparse Channel Estimation Robust to Impulsive Noise

In this paper, we propose a new sparse channel estimator robust to impulsive noise environments. For this kind of estimator, the convex regularized recursive maximum correntropy (CR-RMC) algorithm has been proposed. However, this method requires information about the true sparse channel to find the regularization coefficient for the convex regularization penalty term. In addition, the CR-RMC has a numerical instability in the finite-precision cases that is linked to the inversion of the auto-covariance matrix. We propose a new method for sparse channel estimation robust to impulsive noise environments using an iterative Wiener filter. The proposed algorithm does not need information about the true sparse channel to obtain the regularization coefficient for the convex regularization penalty term. It is also numerically more robust, because it does not require the inverse of the auto-covariance matrix.

Dissection-related carotid-cavernous fistula (CCF) following surgical revascularization of chronic internal carotid artery occlusion: a new subtype of CCF and proposed management

BackgroundThe development of carotid-cavernous fistulas (CCFs) during surgical recanalization of chronic internal carotid artery occlusion (ICAO) may be secondary to severe ICA dissection rather than a focal tear of the cavernous ICA seen in typical traumatic CCFs. The purpose of this study is to investigate the causal relationship between the CCFs and severe ICA dissections and to characterize technical outcomes after treatment with stenting.MethodsFive patients underwent treatment with self-expanding stents due to intraprocedural CCF and ICA dissection following surgical removal of ICAO plaque. The stents were telescopically placed via true channel of the dissection. Safety of the procedure was evaluated with 30-day stroke and death rate. Procedural success was determined by the efficacy of CCF obliteration and ICAO recanalization with angiography.ResultsAll CCFs were associated with spiral and long segmental dissection from the cervical to cavernous ICA. After stenting, successful dissection reconstruction with TICI 3 was achieved in all patients, with complete (n = 4) or partial CCF (n = 1) obliteration. No patient had CCF syndrome, stroke, or death during follow-up of 6 to 37 months; but one patient had pulsatile tinnitus, which resolved 1 year later. Angiography at 6 to 24 months demonstrated CCF obliteration in all 5 patients and durable ICA patency in 4 patients.ConclusionsIntraprocedural CCFs with spiral and cervical-to-cavernous ICA dissection during ICAO surgery are dissection-related because of successful obliteration after stenting for dissection reconstruction. Self-expanding stenting through true channel of the dissection, serving as implanting stent-autograft, may be an optimal therapy for the atypical CCF complication from ICAO surgery.

Double Emergency Pulmonary Embolism and Aortic Dissection: About a Clinical Case

Introduction: Pulmonary embolism and aortic dissection are two formidable cardiovascular emergencies. Their exceptional association has a poor prognosis with very high mortality. The aim of our study was to report the case of a 31-year-old patient with pulmonary embolism associated with De Bakey’s type I aortic dissection, admitted to the cardiology department of Kati University Hospital. Case Presentation: We report the case of a young patient of 31 with no known cardiovascular history, on estrogen-progestogen contraception for 10 years, who consults for a left basal thoracic pain of increasing intensity, a whitish productive cough, hemoptysis and dyspnea stage III. She was admitted to the cardiology department, transthoracic cardiac ultrasound objectified aortic insufficiency, dissection of the aorta, the presence of the intimal flap, the false and the true channel, dilation of the right cavities with HTAP. The chest CT scan revealed bilateral lobar and segmental pulmonary embolism, De Bakey’s type I aortic dissection. Medical treatment was instituted for hemodynamic stabilization at the end of sending her to a center specializing in cardiovascular surgery for better management; unfortunately she succumbed before the preparations for her evacuation were finished. Conclusion: The pulmonary embolism associated with aortic dissection constitutes a medical emergence of rare incidence in a cardiological environment;if the diagnosis was quickly made in our patient, the lack of technical platform made management difficult.

Depolarizing Channel Mismatch and Estimation Protocols for Quantum Turbo Codes

Quantum turbo codes (QTC) have shown excellent error correction capabilities in the setting of quantum communication, achieving a performance less than 1 dB away from their corresponding hashing bounds. Decoding for QTCs typically assumes that perfect knowledge about the channel is available at the decoder. However, in realistic systems, such information must be estimated, and thus, there exists a mismatch between the true channel information and the estimated one. In this article, we first heuristically study the sensitivity of QTCs to such mismatch. Then, existing estimation protocols for the depolarizing channel are presented and applied in an off-line manner to provide bounds on how the use of off-line estimation techniques affects the error correction capabilities of QTCs. Finally, we present an on-line estimation method for the depolarizing probability, which, different from off-line estimation techniques, neither requires extra qubits, nor increases the latency. The application of the proposed method results in a performance similar to that obtained with QTCs using perfect channel information, while requiring less stringent conditions on the variability of the channel than off-line estimation techniques.

Robust Improper Signaling for Two-User SISO Interference Channels

It has been shown that improper Gaussian signaling (IGS) can improve the performance of wireless interference-limited systems when perfect channel-state information (CSI) is available. In this paper, we investigate the robustness of IGS against imperfect CSI on the transmitter side in a two-user single-input single-output (SISO) interference channel (IC) as well as in a SISO Z-IC, when interference is treated as noise. We assume that the true channel coefficients belong to a known region around the channel estimates, which we call the uncertainty region. Following a worst-case robustness approach, we study the rate-region boundary of the IC for the worst channel in the uncertainty region. For the two-user IC, we derive a robust design in closed form, which is independent of the phase of the channels by allowing only one of the users to transmit IGS. For the Z-IC, we provide a closed-form design for the transmission parameters by considering an enlarged uncertainty region and allowing both users to employ IGS. In both cases, the IGS-based designs are ensured to perform no worse than proper Gaussian signaling. Furthermore, we show, through numerical examples, that the proposed robust designs significantly outperform non-robust solutions.

Regularization Factor Selection Method for l1-Regularized RLS and Its Modification against Uncertainty in the Regularization Factor

This paper presents a new l1-RLS method to estimate a sparse impulse response estimation. A new regularization factor calculation method is proposed for l1-RLS that requires no information of the true channel response in advance. In addition, we also derive a new model to compensate for uncertainty in the regularization factor. The results of the estimation for many different kinds of sparse impulse responses show that the proposed method without a priori channel information is comparable to the conventional method with a priori channel information.

Effects of Jamming Attacks on a Control System With Energy Harvesting

We consider the problem of control and remote state estimation with battery constraints and energy harvesting at the sensor (transmitter) under DoS/jamming attacks. We derive the optimal non-causal energy allocation policy that depends on current properties of the channel and on future energy usage. The performance of this policy is analyzed under jamming attacks on the wireless channel, in which the assumed and the true channel gains differ, and we show that the resulting control cost is not monotonic with respect to the assumed channel gain used in the transmission policy. Additionally, we show that, in case there exists a stabilizing policy, then the optimal causal policy ensures stability of the estimation process. The results were illustrated for non-causal and causal energy allocation policies under different jamming attacks.