Conventional Schemes Research Articles

Noise‐Like Pulse Seeded Supercontinuum Generation: An In‐Depth Review For High‐Energy Flat Broadband Sources

AbstractAs the need for compact, cost‐effective, and reliable laser sources continues to rise, fiber lasers have gained widespread interest in science and technology. In recent years, passively mode‐locked fiber lasers (PMLFLs) have emerged as pivotal tools for generating ultrashort pulses, propelling advancements across various domains including communication, manufacturing, medicine, defense, and security. Amongst the various types of lasing states supported by a PMFL, the emphasis in this review is on the noise‐like pulses (NLP) and their potential applications in supercontinuum generation (SCG). Interestingly, the quasi‐stationary operation of the NLP envelope containing numerous chaotic sub‐pulses has facilitated relatively high energy and broad bandwidth compared to standard mode‐locked laser pulses. Moreover, the NLP generation goes beyond a specific cavity arrangement, the nature of mode‐locking or cavity dispersion. Therefore, through this review, the foremost aim is to report the differences in NLPs across various experimental settings reported so far and highlight the strategies beneficial for high‐energy and broadband NLP development directly from a fiber oscillator. Secondly, the application of NLP as a seed laser is examined to stimulate SCG in different types of fibers, underlining the improved supercontinuum characteristics over the conventional ultrashort pulse pumping schemes. Finally, the benefit of NLP‐seeded SCG for various bio‐medical and industrial applications are highlighted, thanks to the broader and flatter continuum achievable through compact experimental settings.

On weighted sum‐rate maximization of full‐duplex systems in presence of STAR‐RIS

AbstractReflecting intelligent surface (RIS) is one of the key enabling technologies for beyond fifth generation wireless networks to further improve coverage, spectral‐ and energy‐efficiency of wireless networks. Recently, a novel simultaneous transmission and reflection RIS (STAR‐RIS) technology is introduced which enables more degrees‐of‐freedom in simultaneously serving users in reflection and transmission regions of RIS. This paper investigates a STAR‐RIS assisted two‐user full‐duplex communication system, wherein multi‐antenna base station (BS) and single‐antenna users are subject to maximum power constraints. Firstly, weighted sum rates are computed for three well‐known STAR‐RIS protocols, e.g. energy splitting, mode selection, and time splitting. Then, for each of the cases, weighted sum rate optimization problem is investigated to find optimal resource allocations, i.e. base station's precoding and combining matrices, coefficients of STAR‐RIS, and power allocations. The optimization problem is transferred into multiple convex sub‐problems using equivalent weighted minimum mean‐square‐error forms. Also, by use of the successive convex approximation method, tunable parameters of the STAR‐RIS are optimized. Although the original problem is a non‐convex one, proposed iterative alternating technique achieves an acceptable sub‐optimal performance. Finally, performance of the system is analysed and compared to some baselines to highlight superiority of the STAR‐RIS compared to the conventional RIS schemes.

Seamless Connectivity with Fuzzy-Based Unmanned Aerial Vehicle for VANET in Congested Zone

Providing seamless connectivity during transit in vehicular ad hoc networks (VANETs) is the most promising and challenging task. In VANET, the vehicles are able to communicate with other vehicles and also with the infrastructure units such as road side unit (RSU). The coverage range of RSU is not sufficient to cover the whole road. The vehicle can drive to an area which is not covered by any of the RSUs, and it is termed as congested zone (CZ). This will extremely lead to traffic congestion and maximize blocking probability. In order to provide connectivity between the road segments and to avoid long delay in message transmission, unmanned aerial vehicles (UAVs) are placed in CZs, which act as relay nodes. To enhance the connectivity of the vehicles, a fuzzy-based UAV-assisted handoff scheme (F-UAV-HO) is proposed in this work. By adopting fuzzy, the unwanted participation of UAV is limited in non-congested traffic, thereby saving the battery resource. To validate the proposed work, the simulations are executed in Network Simulator 2.35. The proposed system outperforms other conventional UAV-assisted schemes in congested traffic in terms of average end-to-end delay, PDR and throughput.

A high robust control scheme of grid‐side converter for DFIG system

AbstractIn this study, a high robust control—second‐order sliding‐mode control (SOSMC) scheme is proposed to improve the DC‐link voltage dynamic performance of the grid‐side converter (GSC) for the doubly‐fed induction generator (DFIG) system under the wind turbine power disturbance and DC‐link capacitance parameter disturbance. In general, the wind speed is change with the environment and further has an effect on the power generation of the DFIG system. Besides, the capacitance of DC‐link capacitor may change with the working condition. To address this issue, a SOSMC scheme is proposed to replace the conventional proportional integral (PI) control for the DC‐link voltage controller of the GSC for the DFIG system in this study. By using the non‐linear SOSMC controller, the DFIG system is robust to the disturbance of the wind speed and the parameter of DC‐link capacitance. Compared with the conventional PI control scheme, the DFIG system with the proposed SOSMC scheme is much more robust, which has been verified in the MATLAB/Simulink platform.

First-principles study on the lithiation process of amorphous SiO anode for Li-ion batteries with Bayesian optimization.

Amorphous silicon monoxide (a-SiO), which contains Si atoms with various valence states, has attracted much attention as a high-performance anode material for lithium (Li) ion batteries (LIBs). Although current experiments have provided some information during charge/discharge cycles, further investigation of structural changes at the atomic scale is needed. To investigate the lithiation process of a-SiO using first-principles simulations and machine learning techniques, we developed a computational code employing Bayesian optimization to efficiently identify stable sites for Li insertion in the large search-space of amorphous models to reproduce the actual lithiation process and compared this approach to the conventional random scheme by applying it to an a-SiO model previously generated with neural network potentials. The lithiation process based on Bayesian optimization resulted in lower formation energies compared to the conventional random scheme, indicating a more stable structure. During lithiation, Li atoms tended to enter the silicon (Si) phase after the SiO2 phase, in agreement with experimental results. We analyzed the structural changes and observed significant differences in the structural evolution between the conventional and new schemes. Our study highlights the significant influence of the lithiation process on the structural transformation of a-SiO materials, which in turn affects the reversible capacity of the material. These findings will provide a framework for improving the performance and lifetime of a-SiO materials.

Performance of Atrial Fibrillation Burden Trends for Stroke Risk Stratification.

Atrial fibrillation (AF) is associated with an increased risk of stroke, yet the limitations of conventional monitoring have restricted our understanding of AF burden risk thresholds. Predictive algorithms incorporating continuous AF burden measures may be useful for predicting stroke. This study evaluated the performance of temporal AF burden trends as predictors of stroke from a large cohort with insertable cardiac monitors. Using deidentified data from Optum Clinformatics Data Mart (2007-2019) linked with the Medtronic CareLink insertable cardiac monitor database, we identified patients with an insertable cardiac monitor for AF management (n=1197), suspected AF (n=1611), and cryptogenic stroke (n=2205). Daily AF burden was transformed into simple moving averages, and temporal AF burden trends were defined as the comparison of unique simple moving average pairs. Classification trees were used to predict ischemic stroke, and AF burden significance was quantified using bootstrapped mean variable importance. Of 5013 patients (age, 69.2±11.7 years; 50% male; CHA2DS2-VASc, 3.7±1.9) who met inclusion criteria, 869 had an ischemic stroke over 2 409 437 days total follow-up. Prior stroke or transient ischemic attack (variable importance, 13.13) was the number 1 predictor of future stroke followed by no prior diagnosis of AF (7.35) and AF burden trends in follow-up (2.59). Temporal proximity of AF and risk of stroke differed by device indication (simple moving averages: AF management, <8 days and suspected AF and cryptogenic stroke, 8-21 days). Together, baseline characteristics and AF burden trends performed optimally for the area under the receiver operating characteristic curve (0.73), specificity (0.70), and relative risk (5.00). AF burden trends may provide incremental prognostic value as leading indicators of stroke risk compared with conventional schemes.

Necessity of orthogonal basis vectors for the two-anyon problem in a one-dimensional lattice* *Supported by National Science Foundation of China (Grant Nos. 12074340 and 12474492) and the Science Foundation of Zhejiang Sci-Tech University (Grants No. 20062098-Y, 19062463-Y and 22062344-Y).

Few-body physics for anyons has been intensively studied within the anyon-Hubbard model, including the quantum walk and Bloch oscillations of two-anyon states. Recently, theoretical and experimental simulations of two-anyon states in a one-dimensional lattice have been carried out by expanding the wavefunction in terms of non-orthogonal basis vectors, resulting in non-physical degrees of freedom. In the present work, we deduce finite difference equations for the two-anyon state in a one-dimensional lattice by solving the Schrödinger equation with orthogonal and complete basis vectors. Such an orthogonal scheme gives all the orthogonal physical eigenstates, while the conventional (non-orthogonal) method produces many non-physical redundant eigensolutions whose components violate the anyonic commutation relations. The dynamical property of the two-anyon states in a sufficiently large lattice is investigated and compared in both the orthogonal and conventional schemes. For initial states with two anyons at the same site or two (next-)neighboring sites, we observe the same dynamical behavior in both schemes, including the revival probability, probability density function and two-body correlation. For other initial states, the conventional scheme produces erroneous states that no longer obey the anyonic relations. The period of Bloch oscillations in the pseudo-fermionic limit has been found to be twice that in the bosonic limit, while these oscillations disappear at other statistical parameters. Our findings are vital for quantum simulations of few-body anyonic physics in lattice models.

Power Quality Improvement Using a Novel Simplified Adaptive Control of Solar PV Integrated Shunt Active Power Filter

ABSTRACTPower quality improvement in grid‐tied solar photovoltaic (PV) system is one of the emergent current research trends. To address the power quality concern, shunt active power filters (SAPF) are widely deployed and researched in grid‐tied PV systems. This paper presents a simplified adaptive transversal (SAT)‐filter control scheme for the two‐stage PV‐SAPF system. The proposed control has the ability to improve different power quality indices. Also, it features faster operation under steady‐state and under dynamic conditions, better dc‐offset rejection ability due to estimation of the accurate fundamental component of the load current. To justify the effectiveness of the proposed control scheme, a thorough comparison is carried out with different conventional and adaptive control schemes. Simulations and extensive experimental analysis are carried out under severe transient conditions such as balanced‐unbalanced supply, sudden load, and irradiation change scenario.

Extreme time extrapolation capabilities and thermodynamic consistency of physics-inspired neural networks for the 3D microstructure evolution of materials via Cahn–Hilliard flow

Abstract A Convolutional Recurrent Neural Network (CRNN) is trained to reproduce the evolution of the spinodal decomposition process in three dimensions as described by the Cahn–Hilliard equation. A specialized, physics-inspired architecture is proven to provide close accordance between the predicted evolutions and the ground truth ones obtained via conventional integration schemes. The method can accurately reproduce the evolution of microstructures not represented in the training set at a fraction of the computational costs. Extremely long-time extrapolation capabilities are achieved, up to reaching the theoretically expected equilibrium state of the system, consisting of a layered, phase-separated morphology, despite the training set containing only relatively-short, initial phases of the evolution. Quantitative accordance with the decay rate of the free energy is also demonstrated up to the late coarsening stages, proving that this class of machine learning approaches can become a new and powerful tool for the long timescale and high throughput simulation of materials, while retaining thermodynamic consistency and high-accuracy.

Modification, validation and comparison of Naples prognostic score to determine in-hospital mortality in ST-segment elevation myocardial infarction.

The relationship between inflammatory status and poor outcomes in acute coronary syndromes is a significant area of current research. This study investigates the association between in-hospital mortality and the modified Naples prognostic score (mNPS) as well as other inflammatory biomarkers in STEMI patients. This single-centre, cross-sectional study included 2576 consecutive STEMI patients who underwent primary percutaneous coronary intervention between January 2022 and November 2023. Participants were randomly divided into derivation and validation cohorts in a 6:4 ratio. The following inflammatory indices were calculated: pan-immune-inflammation value (PIV), systemic immune-inflammation-index (SII), systemic inflammation-response index (SIRI) and conventional NPS. The mNPS was derived by integrating hs-CRP into the conventional NPS. The performance of these indices in determining in-hospital mortality was assessed using regression, calibration, discrimination, reclassification and decision curve analyses. Inflammatory biomarkers, including PIV, SII, SIRI, NPS and mNPS, were significantly higher in patients who died during in-hospital follow-up compared to those discharged alive in both the derivation and validation cohorts. Multivariable logistic regression analyses were performed separately for the derivation and validation cohorts. In the derivation cohort, mNPS was associated with in-hospital mortality (aOR = 1.490, p < .001). Similarly, in the validation cohort, mNPS was associated with in-hospital mortality (aOR = 2.023, p < .001). mNPS demonstrated better discriminative and reclassification power than other inflammatory markers (p < .05 for all). Additionally, regression models incorporating mNPS were well-calibrated and showed net clinical benefit in both cohorts. mNPS may be a stronger predictor of in-hospital mortality in STEMI patients compared to the conventional scheme and other inflammatory indices.

All-Epitaxial Self-Assembly of Silicon Color Centers Confined Within Sub-Nanometer Thin Layers Using Ultra-Low Temperature Epitaxy.

Silicon-based color-centers (SiCCs) have recently emerged as quantum-light sources that can be combined with telecom-range Si Photonics platforms. Unfortunately, using conventional SiCC fabrication schemes, deterministic control over the vertical emitter position is impossible due to the stochastic nature of the required ion-implantation(s). To overcome this bottleneck toward high-yield integration, a radically innovative creation method is demonstrated for various SiCCs with excellent optical quality, solely relying on the epitaxial growth of Si and C-doped Si at atypically-low temperatures in an ultra-clean growth environment. These telecom emitters can be confined within sub-nm thick epilayers embedded within a highly crystalline Si matrix at arbitrary vertical positions. Tuning growth conditions and doping, different well-known SiCC types can be selectively created, including W-centers, T-centers, G-centers, and, especially, a so far unidentified derivative of the latter, introduced as G'-center. The zero-phonon emission from G'-centers at ≈1300nm can be conveniently tuned by the C-concentration, leading to a systematic wavelength shift and linewidth narrowing toward low emitter densities, which makes both, the epitaxy-based fabrication and the G'-center particularly promising as integrable Si-based single-photon sources and spin-photon interfaces.

General synthetic iterative scheme for non-equilibrium dense gas flows

The recently-developed general synthetic iterative scheme (GSIS), which is tailored for non-equilibrium dilute gas, has been extended to find the steady-state solutions of the non-equilibrium dense gas flows based on the Shakhov-Enskog model, resolving the problems of slow convergence and requirement of ultra-fine grids in near-continuum flows that exist in the conventional iterative scheme. The key ingredient of GSIS is the tight coupling of the mesoscopic kinetic equation and the macroscopic synthetic equations that are exactly derived from the kinetic equation. On the one hand, high-order terms computed from the velocity distribution function provide the higher-order constitutive relations describing the non-equilibrium effects for the macroscopic synthetic equations. On the other hand, the macroscopic quantities obtained from the macroscopic synthetic equations are used to guide the evolution of the velocity distribution function in the kinetic equation. The efficiency and accuracy of GSIS are demonstrated in several test cases, including the shock wave passing through a cylinder and the pressure-driven dense gas flows passing through parallel plates and porous media. The effects of denseness are analyzed in a wide range of gas rarefaction.

Hybrid Beamforming Structure Using Grouping with Reduced Number of Phase Shifters in Multi-User MISO

This paper proposes a novel hybrid beamforming (HBF) structure for gain-aware grouping transmit antennas and users in multiuser multiple-input single-output (MU-MISO) systems. In the conventional HBF structure, all transmit antennas form a beam to each user. In this case, the gain of each antenna varies depending on the location of the base station and each user, and the transmit power after the digital beamformer is allocated to the antenna with the smallest gain. Signals transmitted from antennas with small gains are susceptible to noise and interference. Therefore, this paper proposes an HBF structure in which only the antenna with the highest gain forms the beam for each user. In the proposed scheme, the transmitting antennas are grouped and the beam is formed only by the group of antennas with the highest gain for each user. Simulation results show that the proposed scheme can reduce the number of phase shifters used on the transmit side compared to the conventional HBF scheme while maintaining sum-rate performance when the number of transmit antennas and users are the same. It was also shown that there is a trade-off between the reduction in the number of phase shifters used to form the beam and the improvement in performance as the number of transmit antennas increases. Furthermore, it is shown that when antenna selection is used, although there is a trade-off between the number of phase shifters and performance improvement, the number of phase shifters can be reduced while maintaining performance even when the number of transmit antennas increases.

Manipulation of high-fidelity sidebands under Large detuning by Floquet technology: application to Multi-Mode Cooling

Abstract The Floquet technology, a powerful way to manipulate quantum states, is employed to drive sidebands transition under large detuning. Our results demonstrate that high fidelities over 99% can be achieved through optimizing suitable modulation frequencies under large detuning. We observe high-fidelity transitions within a high bandwidth by utilizing a single modulation frequency and reveal this capability is due to the emergence of a flat-band structure in the bandwidth range. The key finding of high-fidelity sideband manipulation under large detuning is experimentally confirmed in nuclear magnetic resonance platform. Finally, we propose a new parallel sideband cooling scheme that enables simultaneous cooling of multiple motional modes. This approach improves the cooling rate compared to conventional schemes with fixed laser frequency and power, and eliminates the need for mode-specific addressing. Our Floquet parallel scheme is applicable to any harmonic oscillator system and is not limited by bandwidth in theory.

Error performance of DF cooperative SMTs with I/Q imbalance over Beckmann fading channels

The direct down-conversion principle, which has generally been used in the design of multiple-input multiple-output (MIMO) schemes, including space modulation techniques (SMTs), is attractive to researchers because of its low cost, low power consumption with fewer components, flexible and simple structure. However, hardware imperfections such as in-phase (I) and quadrature-phase (Q) imbalance (IQI) negatively affect the performance of the systems with direct down-conversion in practice. On the other hand, cooperative communication is a promising technology that can be utilized in the design of future wireless networks due to its significant advantages such as increasing system reliability, extending network coverage, reducing channel degradation, and providing high quality of service. In this study, SMT-based methods are integrated into cooperative systems, and a flexible and comprehensive model is presented that is applicable to many channel structures. Specifically, the error performance analysis of space shift keying (SSK), spatial modulation (SM), and quadrature SM (QSM) systems in the presence of IQI in decode-and-forward (DF) cooperative communication is carried out by analytical derivations and computer simulations over generalized Beckmann fading channels. The obtained results show that the performance of SMT-based DF cooperative systems is superior to the conventional schemes, and the effects of receiver IQI can be eliminated by optimal detector designs.

χ (2)-induced artifact overwhelming the third-order signal in 2D Raman-THz spectroscopy of non-centrosymmetric materials.

Through comprehensive data analysis, we demonstrate that a χ(2)-induced artifact, arising from imperfect balancing in the conventional electro-optic sampling detection scheme, contributes significantly to the measured signal in 2D Raman-THz spectroscopy of non-centrosymmetric materials. The artifact is a product of two 1D responses, overwhelming the desired 2D response. We confirm that by analyzing the 2D Raman-THz response of an x-cut beta barium borate crystal. We furthermore show that this artifact can be effectively suppressed by implementing a special detection scheme. We successfully isolate the desired third-order 2D Raman-THz response, revealing a distinct cross-peak feature, whose frequency position suggests the coupling between two crystal phonons.

An advanced symbol detection approach for MIMO-FBMC/OQAM scheme based on migrating birds optimization algorithm

Application of multiple-input multiple-output (MIMO) technology to the filter bank multicarrier/offset quadrate amplitude modulation (FBMC/OQAM) system provides great improvements on its robustness to channel fading effects. Nevertheless, the unique qualities of MIMO-FBMC/OQAM scheme do not make any sense without solving the symbol detection problem on its receiver part. To this end, an efficient symbol detecting strategy having the capability of recovering the transmitted symbol sequences with the highest accuracy is needed for the related system. Maximum likelihood (ML) detector is known with its excellent symbol detection performance in the literature. However, due to the usage of exhaustive search procedure, the computational complexity of the ML detector reaches extremely high levels with the increase of antenna size and modulation order. On the other hand, in the case that the exhaustive search procedure is substituted with the symbol optimization process, it becomes possible to achieve a large amount of complexity reduction in the conventional ML scheme without compromising too much on its symbol detection performance. In order to carry out an efficient symbol optimization in discrete space, we propose migrating birds optimization (MBO) algorithm based on cyclic bit flipping procedure in this paper. By virtue of employing the proposed MBO algorithm reinforced by the cyclic bit flipping mechanism for optimizing the symbol sequences, the computational complexity of the conventional ML is reduced to quite low levels. The percentages of complexity reduction achieved by the proposed scheme over the classical ML for 4 × 4, 6 × 6 and 8 × 8 MIMO configurations are equal to 29.688%, 87.188% and 98.299%, respectively. In addition to these huge complexity gains, an efficient symbol detection performance quite near to that of conventional ML is obtained thanks to the usage of aforementioned MBO-based symbol optimization procedure.

Joint LPI waveform and passive beamforming design for FDA-MIMO-DFRC systems

Dual-functional Radar-Communication (DFRC) systems have been recognized as one of the most promising technologies in the field of wireless communications. Nevertheless, the low probability of intercept (LPI) performance in the DFRC systems cannot be overlooked. Based on the frequency diverse array multiple-input–multiple output (FDA-MIMO) radar, a DFRC system is proposed to enhance target detection in clutter environment and achieve desirable LPI against an underlying hostile interceptor. The issue can be cast into an optimization problem that maximizes the radar signal-to-interference-plus-noise ratio (SINR) while satisfying the communication quality-of-service (QoS) requirement of each user under one of three metrics, the required LPI performance and the constant-modulus waveform constraint. To solve this challenging problem, we reformulate it into an equivalent but more tractable form by resorting to an auxiliary variable. Subsequently, we employ the alternative direction method of multipliers (ADMM) and majorization-minimization (MM) algorithms to solve the resultant problem. Simulation results validate that the proposed LPI FDA-MIMO-DFRC scheme exhibits superior sensing performance over the conventional scheme with MIMO.

Optimized wide area backup for distance relay tele-protection with security adjustment

Tele-protection schemes efficiently clear faults at line ends, but failures in the telecommunication link or relay malfunction can cause delayed fault clearance, network instability and significant power loss. Hence, this paper presents a reliable protection method as a backup for tele-protection schemes which is designed based on nearby distance relays zone pickup. The proposed protective method introduces a novel ability to adjust sensitivity to fault events through a security factor index. This method can adapt to network uncertainties or changes in topology, using one-step calculation of optimal values based on the least square error method and provides the fast adaptation to network changes. In addition, it enables the fault detection even if a relay fails at one of the faulted line terminals. Performance evaluation of the proposed method has been done based on the reliability indices through a wide simulation of fault scenarios on the IEEE 9-bus system. Considering the possible uncertainties, the test results have shown that the proposed method is more efficient with 98.5 % dependability compared to the conventional tele-protection schemes. While this index is evaluated at 90 % and 92.5 % in the PUTT and POTT schemes, respectively.

Demonstration of 4-quadrant analog in-memory matrix multiplication in a single modulation

Analog in-memory computing (AIMC) leverages the inherent physical characteristics of resistive memory devices to execute computational operations, notably matrix-vector multiplications (MVMs). However, executing MVMs using a single-phase reading scheme to reduce latency necessitates the simultaneous application of both positive and negative voltages across resistive memory devices. This degrades the accuracy of the computation due to the dependence of the device conductance on the voltage polarity. Here, we demonstrate the realization of a 4-quadrant MVM in a single modulation by developing analog and digital calibration procedures to mitigate the conductance polarity dependence, fully implemented on a multi-core AIMC chip based on phase-change memory. With this approach, we experimentally demonstrate accurate neural network inference and similarity search tasks using one or multiple cores of the chip, at 4 times higher MVM throughput and energy efficiency than the conventional four-phase reading scheme.