Spatial Gain Research Articles

EMSIG: Uncovering Factors Influencing COVID-19 Vaccination Across Different Subgroups Characterized by Embedding-Based Spatial Information Gain

Background/Objectives: COVID-19 and its variants continue to pose significant threats to public health, with considerable uncertainty surrounding their impact. As of September 2024, the total number of deaths reached 8.8 million worldwide. Vaccination remains the most effective strategy for preventing COVID-19. However, vaccination rates in the Deep South, U.S., are notably lower than the national average due to various factors. Methods: To address this challenge, we developed the Embedding-based Spatial Information Gain (EMSIG) method, an innovative tool using machine learning techniques for subgroup modeling. EMSIG helps identify subgroups where participants share similar perceptions but exhibit high variance in COVID-19 vaccine doses. It introduces spatial information gain (SIG) to screen regions of interest (ROI) subgroups and reveals their specific concerns. Results: We analyzed survey data from 1020 participants in Alabama. EMSIG identified 16 factors encompassing COVID-19 hesitancy and trust in medical doctors, pharmacists, and public health authorities and revealed four distinct ROI subgroups. The five factors, including COVID-19 perceived detriment, fear, skepticism, side effects related to COVID-19, and communication with pharmacists, were commonly shared across at least three subgroups. A subgroup primarily composed of Democrats with a high flu-shot rate expressed concerns about pharmacist communication, government fairness, and responsibility. Another subgroup, characterized by older, white Republicans with a relatively low flu-shot rate, expressed concerns about doctor trust and the intelligence of public health authorities. Conclusions: EMSIG enhances our understanding of specific concerns across different demographics, characterizes these demographics, and informs targeted interventions to increase vaccination uptake and ensure equitable prevention strategies.

All-fiber spatial and wavelength gain-flattening of few-mode EDFA via mode selective coupler

The mode division multiplexing (MDM) technique together with wavelength division multiplexing (WDM) shows the great prospect to solve the capacity crunch of current standard single mode fiber (SSMF) transmission system. However, the modal and wavelength gain fluctuation fundamentally limit both the capacity and the reach of hybrid MDM-WDM transmission system. Here, we propose an all-fiber few-mode gain-flattening filter (FM-GFF) based on mode selective coupler (MSC), to effectively mitigate the gain fluctuation of few-mode erbium doped fiber amplifier (FM-EDFA) in both spatial and wavelength dimensions. With the help of genetic algorithm (GA), variable mode dependent loss spectra of cascaded MSCs can be efficiently obtained, according to the gain profile of the used FM-EDFA. Consequently, gain-flattening among all guided linearly polarized (LP) mode groups over the C-band can be realized. Simulation results reveal that, as for the spatial and wavelength gain flattening among 4/6-LP mode groups, only 5/7 cascaded MSCs are good enough to mitigate the modal and wavelength gain fluctuation from 9.89 dB and 11.79-dB to less than 0.38 dB and 0.46 dB over the C-band. Finally, we carry out experimental verification based on 2-LP mode groups gain flattening over C-band. When 3 cascaded MSCs are involved, the gain fluctuation of FM-EDFA over the C-band can be flattened from 2.46 dB to less than 0.96 dB.

Neural operators for robust output regulation of hyperbolic PDEs

The recently introduced neural operator (NO) has been employed as a gain approximator in the backstepping stabilization control of first-order hyperbolic and parabolic partial differential equation (PDE) systems. Due to the global approximation ability of the DeepONet, the NO provides approximate spatial gain function with arbitrary accuracy. The closed-loop system stability can be ensured by the backstepping controller involving the approximate gain with sufficiently small error. In this paper, the NO theory is leveraged to solve the robust output regulation problem for a class of uncertain hyperbolic PDE systems under the design framework of backstepping-based regulator. The NO is trained offline on a dataset containing a sufficient number of system parameters and corresponding prior solutions of the kernel equation, so as to generate feedback gain for the robust regulator. Once the NO is trained, the kernel equation does not need to be solved ever again, for any new system parameters that do not exceed the range of the training set. Based on the internal model principle, the regulator is inherently robust to a degree of parameter uncertainty and error in approximate gain. Therefore, the tracking error can still converge to 0 if the extended regulator equations are solvable and the parameter uncertainty leads to an asymptotically stable origin. We provide a series of theory proofs and a numerical test under the approximate control and observation gains to demonstrate the robust regulation problem. It is shown that the NO is almost three orders of magnitude faster than PDE solver in generating kernel function, and the loss remains on the order of 10−4 in the test. This provides an opportunity to use the NO methodology for accelerated gain scheduling regulation for PDEs with time-varying system parameters.

Spatial Information Entropy-Assisted Integrated Sensing and Communication for Integrated Satellite-Terrestrial Networks

To better meet communication needs, 6G proposes Integrated Satellite-Terrestrial Networks. Integrated Sensing and Communication (ISAC) is one of the key technologies of Integrated Satellite-Terrestrial Networks, which can reduce the energy consumption of the system, improve communication efficiency, and increase the utilization rate of spectrum resources. In the existing technology, the Modulated Wideband Converter (MWC) system can provide support for the miniaturization and intelligence of wireless device sensing and communication systems. Therefore, the MWC system can be used as a preliminary application of ISAC technology. However, the reconstruction effect of the conventional MWC system under the influence of noise is not stable. Therefore, we propose a signal processing optimization scheme for the MWC system based on spatial information entropy. First, the subsequent reconstruction algorithm is considered to require the dynamic and flexible processing of the sampled signals to reduce the influence of noise. Second, for the shortcomings of the original Orthogonal Matching Pursuit (OMP) algorithm, the concept of the genetic algorithm is used to optimize the algorithm by constructing the feature factor through spatial information gain and spatial information features. According to the simulation results, compared with the traditional MWC system, the scheme proposed in this paper is improved in all indicators.

5G Radiation Source Location Based on Passive Virtual Aperture Technology by Single-Satellite

With the development of 5th-Generation Mobile Communication (5G) technology and the deployment of low-Earth orbit satellites, using satellites to locate 5G radiation sources is of great significance in commerce and the military as an important task of integrated sensing and communication. Recently, passive virtual aperture technology has been introduced into passive location to improve accuracy, but the existing method, using matched filters to search the Doppler information to realize the location, has the disadvantages of high complexity and poor range resolution. In this paper, an improved 5G radiation source location based on a virtual aperture is proposed, which uses the improved Golden Section search-fractional Fourier algorithm (GSS-FRFT) to improve the existing passive virtual aperture location methods. First, the received signals are coherently accumulated to convert the time gain into spatial gain, and the subcarrier phase information is extracted by Fast Fourier Transform based on the 5G signal characteristics to obtain the azimuth signal. Then, an improved high-order GSS-FRFT algorithm is proposed to analyze the Doppler information, and signal focusing and satellite ephemeris data are used to estimate the effective velocity and solve the radiation source location. The simulation results show that the proposed method can improve the location accuracy compared with other single-satellite location methods and has high resolution, high accuracy and low complexity compared with the existing passive virtual aperture location method.

Spatial sensitivity synthesis based on alternate projection for the machine‐learning‐based coding digital receiving array

AbstractRecently, a novel low‐cost coding digital receiving array based on machine learning (ML‐CDRA) has been proposed to reduce the required radio frequency channels in modern wireless systems. The spatial sensitivity of ML‐CDRA is studied which describes the spatial accumulation gain in different directions. It is demonstrated that the spatial sensitivity is determined by the encoding network, decoding network, and beamforming criterion. To obtain the desired spatial sensitivity, a spatial sensitivity synthesis method is proposed based on the alternate projection by optimising the encoding network with the constraint of amplitude‐phase quantisation. Simulation results show that the proposed method can significantly improve the spatial sensitivity of ML‐CDRA. Furthermore, in the directions of interest, the spatial accumulation gain of ML‐CDRA can exceed the full‐channel digital receiving array.

Analytical modeling of the spray amplification of a spatially smoothed laser beam

Spatial amplification of the near-forward Brillouin scattering (FSBS) produced by a laser beam smoothed with a random phase plate (RPP) is considered by using a novel technique based on the central limit theorem [C. Ruyer et al., Phys. Rev. E 107, 035208 (2023)]. It is demonstrated that FSBS amplification proceeds over a length much larger than the longitudinal speckle correlation length and, under certain conditions, scales as a square of the average gain coefficient. Analytical expressions for the spatial gain are successfully compared with paraxial electromagnetic simulations, demonstrating that the beamlet correlation through ion-acoustic waves dominates the spatial growth for intense enough laser beams. The scattered wave aperture increases with the gain and can extend beyond the small angle scattering limit. These results open the way for developing reduced modeling of beam spray amplification in radiation hydrodynamics codes.

Ex-vivo validation of spatial gain sonography for the quantification of echo intensity in fascicle-aligned ultrasound images in ten anatomical muscles in Bos taurus

This study aimed to validate the concept of spatial gain sonography for quantifying texture-related echo intensity in B-mode ultrasound of skeletal muscle. Fifty-one bovine muscles were scanned postmortem using B-mode ultrasonography at varying fascicle probe angles (FPA). The relationship between mean gray values (MGV) and FPA was fitted with a sinusoidal and a linear function, the slope of which was defined as tilt echo gain (TEG). Macroscopic muscle cross sections were optically analyzed for intramuscular connective tissue (IMCT) content which was plotted against MGV at 0° FPA (MGV_00). MGV peaked at FPA 0°. Sine fits were superior to linear fits (adjusted r2-values 0.647 vs. 0.613), especially for larger FPAs. In mixed models, the pennation angle was related to TEG (P < 0.001) and MGV_00 (P = 0.035). Age was relevant for MGV_00 (P < 0.001), but not TEG (P > 0.10). The correlation between the IMCT percentage and MGV_00 was significant but weak (P = 0.026; adjusted r2 = 0.103). The relationship between fascicle probe angle and echo intensity in B-mode ultrasound can be modeled more accurately with a sinusoidal but more practically for clinical use with a linear fit. The peak mean gray value MGV_00 can be used to compare echo intensity across muscles without the bias of pennation angle.

Backward stimulated Brillouin scattering spatial gain with polarization, spatial, and temporal beam smoothing techniques

A recent study [Ruyer et al., Phys. Rev. E 107, 035208 (2023)] modeling the influence of a random phase plate on the backward stimulated Brillouin scattering growth is here supplemented with the effect of temporal and polarization smoothing. Our analytical predictions are validated by a large number of three dimensional Hera paraxial simulations for various beam smoothing techniques and relevant to most high energy laser facilities. Neglecting all non-linear effects apart from the pump depletion, we then reconstruct the system of differential equations that the backward stimulated Brillouin scattering convective amplification of a smoothed beam propagating in a non-homogeneous plasma satisfies. Its resolution is successfully confronted with our simulation data and prepares the accurate modeling, in a ray tracing scheme, of the effect of laser smoothing techniques on laser plasma instabilities.

Effect of Sound Source Location and Spatial Hearing on the Vestibulo-Ocular Reflex.

There have been conflicting results on the effect of auditory stimulation on the vestibulo-ocular reflex (VOR) with some studies indicating suppression, enhancement, or no effect. No studies to date have assessed the effect of sound source location on VOR gain or the relationship between spatial hearing ability and VOR gain. The purpose of the present study was to determine if VOR gain was affected by moving the location of the sound source within participants and to determine if these effects were related to spatial hearing ability. A between subjects repeated measures experimental design was utilized. Two groups of participants (adult and child) with normal otologic, vestibular, and neurologic function. 22 adults (20 female and 2 male; average age = 23 years) and 16 children (9 female and 7 male; average age = 7.5 years) were included in data analysis. VOR gain was measured using rotational chair stimulation in the following auditory conditions: silent, insert earphones, external loudspeaker at 0° azimuth rotating with participant, and external stationary speaker. Localization ability was measured using root mean square (RMS) error. Results indicated a significant effect for sound source location on VOR gain and VOR difference gain in both groups. RMS error was positively correlated for the moving and fixed sound source locations for both adults and children. VOR gain was significantly affected by location of the sound source. Findings suggest the presence and location of an auditory stimulus during rotational testing can alter results during the assessment.

Deep graph gated recurrent unit network-based spatial–temporal multi-task learning for intelligent information fusion of multiple sites with application in short-term spatial–temporal probabilistic forecast of photovoltaic power

Accurate photovoltaic (PV) power forecast is crucial for carbon neutrality. Current researches on PV power forecast mainly focus on using temporal information from single PV station, and the spatial information in multiple PV power stations are often neglected. To address this problem, this paper introduces Moran index to verify the spatial autocorrelation of PV power for the first time, uses Granger causality test and transfer entropy to reveal the spatial information gain in PV power forecast for the first time, and proposes a novel spatial–temporal probabilistic PV forecast method using deep Graph Gated Recurrent Unit (GraphGRU) network-based spatial–temporal multi-task learning and Kernel Density Estimation (KDE). Deep GraphGRU combines the advantages of Graph Convolutional Network (GCN) in spatial feature extraction and the advantages of Gated Recurrent Unit (GRU) network in temporal feature extraction, and thus has strong ability to extract spatial–temporal information in historical data of multiple different PV power stations. Through GraphGRU, temporal dependency information extracted from historical data of multiple PV stations can promote each other to improve the forecast accuracy of each PV stations. KDE is used for estimating the joint probabilistic density function and giving the spatial–temporal probabilistic confidence interval of PV power. Experiments were performed in the five-year actual PV power data from 11 provinces of Belgium and the three-year solar irradiation data from 12 places in China to verify the superiorities of the proposed method. Comparison with conventional spatial–temporal and temporal forecast methods show that the proposed GraphGRU-based spatial–temporal forecast method can extract the spatial–temporal information from multiple PV power stations well and significantly outperform conventional temporal forecast methods.

M-shaped beam profile output from an off-axis relay-imaging eight-pass Nd:glass laser preamplifier

In ultra-high-power/energy solid-state Nd:glass laser facilities, the gain distribution of the main amplifier system (MAS) is nonuniform owing to strong amplified spontaneous emissions in the MAS. A shaped beam profile from a preamplifier (PreAMP) should be set opposite to the gain profile in the MAS to obtain a high-power beam with an approximately flat beam profile. This flat beam profile can result in the high efficiency of the frequency-conversion crystals. In this study, the laser beam was spatially formatted as an M-shaped beam with precompensation (PreCOM) for the nonuniform gain profile of the MSA. Modulation of the cross-sectional gain distribution of the PreAMP was demonstrated by selecting the absorption coefficient of the Nd:glass rod and pump configuration. Using the proposed off-axis relay-imaging eight-pass amplifier, an M-shaped beam with an output pulse energy of 1 J and a repetition rate of 1 Hz was experimentally achieved. With an Nd3+ concentration of 1.2 wt% and Nd: glass rod diameter of 18 mm, an M-shaped beam profile with a 4.3:1 ratio of intensity at the margin to that at the center was successfully obtained. Such controllable M-shaped beams can be optionally introduced to the MAS to compensate for non-uniform spatial gain profiles.

Correlation-based passive localization: Linear system modeling and sparsity-aware optimization.

In underwater passive localization, matched field processing has faced mismatch challenges for many years. To overcome the mismatch, data-derived replicas have gained increasing popularity due to their better localization performance than parameter-based ones, among which the cross correlation-based replicas showed enhanced robustness against the spectral differences between the library and target vessels. However, cross correlation-based matching localizations result in high sidelobes and require enough frequency samples to eliminate grating lobes. This issue has been widely reported in the previous literature but has yet to be theoretically analyzed. In this work, we revisit the conventional correlation-based matching procedures and formulate the ambiguity surface as a least-norm solution of an underdetermined linear system. This formulation permits understanding the sidelobes from an optimization perspective. Based on this view, the high sidelobe challenge and requirement of measurements are systematically tackled by recasting the matching problem as a sparsity-aware optimization problem. The superiority of the proposed optimization approach is showcased through simulated data in the waveguide, microphone data in the air, and SWellEx-96 data. The linear system modeling is also extended to a distributed sensor network, profiting from the spatial gain brought by various azimuthal directions with respect to the source.

Performance Analysis of NOMA-Based Hybrid Satellite-Terrestrial Relay Networks With CCI

Hybrid satellite-terrestrial relay networks (HSTRNs) which exploit relay cooperative technology in the integrated system of satellites and terrestrial base stations (BSs) are expected to offer enhanced transmission performance benefited from the spatial gain of independent fading paths. To enable multi-user accessing and resource sharing among users, non-orthogonal multiple access (NOMA) technique can be applied in HSTRNs. In this paper, we consider a NOMA-based HSTRN where a satellite transmits signals to a relay base station (RBS) and a destination ground station (DGS), and RBS also serves a cellular user (CU) and DGS simultaneously by leveraging NOMA scheme. We assume that the satellite shares spectrum with a number of cellular small BSs (SBSs), hence SBSs will cause co-channel interference (CCI) to DGS, RBS and CU. We examine the transmission characteristics of the satellite and terrestrial links, and derive the closed-form expressions of the outage probability (OP) and average symbol error rate (ASER) of DGS and CU, respectively. Specially, we consider the effect of perfect and imperfect successive interference cancellation (SIC) on the ASER performance of CU. Then, considering the stochastic characteristics of satellite links and CCI, we analyze the mean energy efficiency (MEE) of the satellite and propose an optimal power allocation scheme which maximizes the MEE of the satellite and achieves system performance optimization. Simulation results demonstrate the effectiveness of the theoretical analysis and the proposed power allocation scheme.

The Effect of Pilot Reuse Factor on Massive MIMO Spectral Efficiency

Due to their much increased spatial resolution and array gain, large-scale antenna arrays have the potential to significantly enhance the spectral efficiency of wireless systems. Recent research in the area of massive Multiple-Input Multiple-Output (MIMO) antennas shows that user channels are enhanced as the number of antennas at the Base Stations (BSs) rises, allowing achieving high signal improvement with minimum inter-user interference. The combined effects of the pilot reuse factor and the BS number of antennas on average overall spectral efficiency in huge MIMO antennas will be investigated. To examine the SE of these receivers, several channel estimators will be utilized, including LMMSE, ZF, and MR methods. Theoretically, BS could offer a substantially higher average total SE if it had more antennas.

CardioGenesis4D: Interactive Morphological Transitions of Embryonic Heart Development in a Virtual Learning Environment.

In the embryonic human heart, complex dynamic shape changes take place in a short period of time on a microscopic scale, making this development difficult to visualize. However, spatial understanding of these processes is essential for students and future cardiologists to properly diagnose and treat congenital heart defects. Following a user centered approach, the most crucial embryological stages were identified and translated into a virtual reality learning environment (VRLE) to enable the understanding of the morphological transitions of these stages through advanced interactions. To address individual learning types, we implemented different features and evaluated the application regarding usability, perceived task load, and sense of presence in a user study. We also assessed spatial awareness and knowledge gain, and finally obtained feedback from domain experts. Overall, students and professionals rated the application positively. To minimize distraction from interactive learning content, such VRLEs should consider features for different learning types, allow for gradual habituation, and at the same time provide enough playful stimuli. Our work previews how VR can be integrated into a cardiac embryology education curriculum.

Influence of a random phase plate on the growth of the backward stimulated Brillouin scatter.

We derive the analytical dispersion relation of a high-energy laser beam's backward stimulated Brillouin scattering (BSBS) in a hot plasma, that accounts both for the random phase plate (RPP) induced spatial shaping and its associated phase randomness. Indeed, phase plates are mandatory in large laser facilities where a precise control of the focal spot size is required. While the focal spot size is well controlled, such techniques produce small scale intensity variations that can trigger laser-plasma instabilities such as BSBS. Quantifying the resulting instability variability is shown to be crucial for understanding accurately the backscattering temporal and spatial growth as well as the asymptotic reflectivity. Our model, validated by means of a large number of three-dimensional paraxial simulations and experimental data, offers three quantitative predictions. The first one addresses the temporal exponential growth of the reflectivity by deriving and solving the BSBS RPP dispersion relation. A large statistical variability of the temporal growth rate is shown to be directly related to the phase plate randomness. Then, we predict the portion of the beam's sectionthat is absolutely unstable, thus helping to precisely assess the validity of the vastly used convective analysis. Finally, a simple analytical correction to the plane wave spatial gain is extracted from our theory giving a practical and effective asymptotic reflectivity prediction that includes the impact of phase plates smoothing techniques. Hence, our study sheds light on the long-time studied BSBS, deleterious to many high-energy experimental studies related to the physics of inertial confinement fusion.

Coherent signal integration in multistatic radar systems using off-grid sparse estimation

This paper is concerned with the coherent integration of multistatic radar data for the purposes of maximising spatial processing gain for enhanced detection, location estimation for improved tracking, and target imaging for recognition and classification. A multistatic radar system here is defined generally as a set of multiple bistatic transmit-receive pairs, suitably synchronised in their combined operation. The underlying principle is the exploitation of aperture to achieve higher spatial resolution than is possible based upon bandwidth alone. The spatial resolution achieved is configuration-dependant and a system is configured appropriately for an application of interest. Starting with a coherent multistatic radar system signal model, an inverse problem is formulated and solved using sparse estimation with a fixed spatial grid. This provides approximate estimates for target point scatterer numbers and locations which may then be refined using an adaptive off-grid estimation technique. This allows the point scatterers in the signal model to adapt their locations to better fit the observed data and maximise coherent gain. Results are given in two dimensions for 5 co-planar transmit-receive pairs.

Correlating shipping noise on multiple beams

There has been much interest in using transiting surface ships as sources of opportunity for tomography and geo acoustic inversion. In tomography, it would be valuable to increase the ranges at which ship signatures can be processed by measuring times of arrival at the output of beamforming processes, which provide spatial processing gain. This additional gain may enable fainter multipath arrivals to be identified and exploited as additional paths to sample the ocean water column. This seems readily achievable when cross-correlating multiple vertical beams formed on a single vertical line array for example. However, cross-correlating beams from multiple arrays, vertical or horizontal, raises questions. In both cases, different beams may have different Doppler, which is manageable with a correlation process that includes Doppler compensation. But obeserving a ship from different vantage points may be problematic, if the ship signature is due to horizontally displaced noise sources distributed around the ship. We will present results of processing surface ships observed on single and multiple arrays and assess the use of such processing in ambient noise tomography.

Channel capacity limit of multi-beam satellite system

The requests of broadband coverage area and the expected user demand is satisfied by the satellite industry by using multiple spot beams of high throughput satellites with fixed multi-beam pattern and footprint planning. The technology core of high-throughput satellite is multi-beam technology, and the means to efficiently reuse spectrum is a full-frequency reuse scheme. In order to study the channel capacity limit of multi-beam satellite systems, the Wiener-Gaussian access model of terrestrial cellular systems is analyzed in this paper. This paper analyzes the Wiener-Gaussian access model of terrestrial cellular systems, then considers the difference between the spatial characteristics and gain characteristics of the multi-beam satellite system compared with the terrestrial cellular system, and proposes a Wiener model suitable for the multi-beam satellite communication system. On this basis, the channel capacity limit of multi-beam satellites under different fading conditions is deduced when using optimal linear precoding and minimum mean square error precoding. It provides theoretical support for the in-depth study of the channel capacity mechanism and system performance of multi-beam satellites.