Transmission Distortion Research Articles

Turbulence compensation with pix-to-pix generative adversarial networks in vector vortex beams

Orbital angular momentum (OAM) has significantly propelled free space optical communication (FSOC) towards achieving ultra-large transmission capacities, but mode-crosstalk in atmospheric turbulence limits its application. Here, we propose a proof-of-concept turbulence compensation approach utilizing pix-to-pix generative adversarial networks (pix2pixGAN) that does not rely on the wavefront sensor. The model captures the complex relationships between distorted optical fields and phase screens through extensive training, after which the phase screen is directly recovered from the well-trained model by identifying the corresponding distorted image to compensate for distortions. Using this model, the Strehl ratio improvement is measured at 35.7%, 8.9%, and 1.7% under three distinct turbulence conditions, respectively. Furthermore, the recognition of vector vortex beams (VVBs) integrating with the pix2pixGAN significantly improves average mode accuracy from 2% to over 99%. Additionally, the exploration of VVB-based communication further elucidates pix2pixGAN's role in enhancing communication quality. These findings suggest a potential advancement in developing a novel neural network-based strategy to compensate for transmission distortions under intense turbulence.

Genetic associations and parent-of-origin effects of PVRL1 in non-syndromic cleft lip with or without cleft palate across multiple ethnic populations.

This study investigated the associations of PVRL1 gene variants with non-syndromic cleft lip with or without cleft palate (NSCL/P) by evaluating transmission distortion and parent-of-origin (POO) effects in multiple ethnic populations. We conducted allelic and genotypic transmission disequilibrium tests (TDT) on 10 single-nucleotide variants (SNVs) in PVRL1 using data from 142 Korean families with an affected child. POO effects were analyzed using the POO likelihood ratio test, comparing transmission rates of maternally and paternally inherited alleles. To assess generalizability and ethnic heterogeneity, we compared results from Korean families with data from the Center for Craniofacial and Dental Genetics, which included 2,226 individuals from 497 European and 245 Asian trios. TDT analysis identified significant over-transmission of the rs7940667 (G361V) C allele in Korean families (p=0.007), a finding replicated in both Asian (p=6.5×10-7) and European families (p=1.6×10-10). Eight SNVs showed strong TDT evidence in larger Asian and European datasets after multiple comparison corrections (p<0.0073). Of these, 4 SNVs (rs7940667, rs7103685, rs7129848, and rs4409845) showed particularly robust association (p<5×10-8). POO analysis revealed significant maternal over-transmission of the rs10790330-A allele in Korean families (p=0.044). This finding was replicated in European families (p=9.0×10-4). Additionally, 3 other SNVs, rs7129848 (p=0.001) and the linked SNVs rs3935406 and rs10892434 (p=0.025), exhibited maternal over-transmission in the validation datasets. Our findings provide robust evidence supporting the associations of PVRL1 variants with NSCL/P susceptibility. Further research is necessary to explore the potential clinical applications of these findings.

Application of Lock-in Amplifier Technique in Signal Blind Source Separation

Abstract In the realm of signal processing, frequency error stands as a critical challenge that cannot be overlooked, particularly in scenarios characterized by noise disturbances and constantly changing environmental variables, as it significantly undermines the precision of waveform separation. Faced with a spectrum of frequency error phenomena stemming from hardware instability, such as clock drift, transmission distortion, and environmental changes, this paper proposes a waveform separation scheme centered around a core closed-loop control architecture aimed at addressing such challenges. Leveraging the high-performance STM32F407 microcontroller platform, the system harnesses the powerful algorithmic advantages of Fast Fourier Transform (FFT) to precisely locate and delineate the spectral characteristics of signals. Furthermore, we creatively integrate lock-in amplifier technology into the meticulously designed closed-loop control system, coupled with state-of-the-art zero-crossing detection algorithms for in-depth optimization. The research findings demonstrate outstanding signal-to-noise ratio performance within predefined target frequency bands for the separation device based on lock-in amplifier technology, showcasing not only remarkable resilience against interference but also the ability to accurately separate and reconstruct target signal components with high fidelity from complex and dynamic signal environments. This significantly enhances the robustness and accuracy of the entire system.

Optical and Structural Developments in Air Traffic Control Tower Glazing

With about 4,500 medium and large airports around the world, Air Traffic Control Towers (ATCT) are essential elements of our transport infrastructure. Safely orchestrating air traffic requires a perfect visibility of aircraft in all weather and lighting conditions. Aviation being a conservative field, towers are built or renovated using decades-old technologies, with disappointing results. Design parameters can be grouped in five categories: structural, blemishes, insulation, photometric and optical. Transcending country borders and traditions, we will detail each of these groups and explain the newest technical solutions available. This paper can be used as a checklist or design guide if you need to conceive an ATCT or other structures, such as an indoor observation deck or high-end retail storefront, where vision is paramount. Special attention will be given to visual distortion in transmission, haze, anisotropy, double image, reflection management, electrochromic, and glass-to-glass connections.

Together inbreeding and reproductive compensation favor lethal t-haplotypes.

Male mice who are heterozygous for distorting and non-distorting alleles at the t-haplotype transmit the driving t-haplotype around 90% of the time-a drastic departure from Mendelian expectations. This selfish act comes at a cost. The mechanism underlying transmission distortion in this system causes severe sterility in males homozygous for the drive alleles, ultimately preventing its fixation. Curiously, many driving t-haplotypes also induce embryonic lethality in both sexes when homozygous; however, this is neither universal nor a necessity for this distortion mechanism. Charlesworth provided an adaptive explanation for the evolution of lethal t-haplotypes in a population segregating for distorting and non-distorting t alleles-if mothers compensate by replacing dead embryos with new offspring (or by transferring energy to surviving offspring), a recessive lethal can be favored because it effectively allows mothers the opportunity to trade in infertile males for potentially fertile offspring. This model, however, requires near complete reproductive compensation for the invasion of the lethal t-haplotype and produces an equilibrium frequency of lethal drivers well below what is observed in nature. We show that low levels of systemic inbreeding, which we model as brother-sister mating, allow lethal t-haplotypes to invade with much lower levels of reproductive compensation. Furthermore, inbreeding allows these lethal haplotypes to largely displace the ancestral male-sterile haplotypes. Our results show that together inbreeding and reproductive compensation move expected equilibria closer to observed haplotype frequencies in natural populations and occur under lower, potentially more reasonable, parameters.

Meiotic drive against chromosome fusions in butterfly hybrids

Species frequently differ in the number and structure of chromosomes they harbor, but individuals that are heterozygous for chromosomal rearrangements may suffer from reduced fitness. Chromosomal rearrangements like fissions and fusions can hence serve as a mechanism for speciation between incipient lineages, but their evolution poses a paradox. How can rearrangements get fixed between populations if heterozygotes have reduced fitness? One solution is that this process predominantly occurs in small and isolated populations, where genetic drift can override natural selection. However, fixation is also more likely if a novel rearrangement is favored by a transmission bias, such as meiotic drive. Here, we investigate chromosomal transmission distortion in hybrids between two wood white (Leptidea sinapis) butterfly populations with extensive karyotype differences. Using data from two different crossing experiments, we uncover that there is a transmission bias favoring the ancestral chromosomal state for derived fusions, a result that shows that chromosome fusions actually can fix in populations despite being counteracted by meiotic drive. This means that meiotic drive not only can promote runaway chromosome number evolution and speciation, but also that it can be a conservative force acting against karyotypic change and the evolution of reproductive isolation. Based on our results, we suggest a mechanistic model for why chromosome fusion mutations may be opposed by meiotic drive and discuss factors contributing to karyotype evolution in Lepidoptera.

RAWIW: RAW Image Watermarking robust to ISP pipeline

Invisible image watermarking is essential for image copyright protection. Compared to RGB images, RAW format images use a higher dynamic range to capture the radiometric characteristics of the camera sensor, providing greater flexibility in post-processing and retouching. RAW images are considered the original format for distribution and image production, thus requiring copyright protection. Existing watermarking methods typically target RGB images, leaving a gap for RAW images. To address this issue, we propose the first deep learning-based RAWImage Watermarking (RAWIW) framework for copyright protection. Unlike RGB image watermarking, our method achieves cross-domain copyright protection. We directly embed copyright information into RAW images, which can be later extracted from the corresponding RGB images generated by different post-processing methods. To achieve end-to-end training of the framework, we integrate a neural network that simulates the Image Signal Processing (ISP) pipeline to handle the RAW-to-RGB conversion process. To further validate the generalization of our framework to traditional ISP pipelines and its robustness to transmission distortion, we adopt a distortion network. This network simulates noises introduced during the traditional ISP pipeline and transmission. Our extensive experiments demonstrate that RAWIW successfully achieves cross-domain copyright protection for RAW images while maintaining their visual quality and robustness to ISP pipeline distortions.

Distributed soft video transmission based on hybrid digital and analog scheme

This study presents a novel distributed soft video delivery scheme using hybrid digital and analog framework, which realizes a relatively lightweight encoder as well as good robustness. Specifically, after applying scalar quantization to the interframes, the scaled analog information (quantization error) and the scaled digital information (quantized source) are superimposed and then transmitted. In this way, the proposed scheme directly delivers pseudo-analog symbols over the orthogonal frequency division multiplexing (OFDM) channels and involves no complicated digital codec. Moreover, we utilize cross-frame correlation to implement a distributed paradigm which further reduces the encoder complexity since the complex motion estimation and compensation algorithms are transferred to the decoder. Accordingly, the power distortion optimization scheme, which resolve the allocation of power and the parameters optimization to achieve minimum transmission distortion, is proposed. To solve it, first, we formulate the power distortion expressions regarding quantization parameters and power allocation coefficients. Subsequently, we divide the problem into two sub-problems based on the fast coordinate descent method and further propose a greedy iterative algorithm to optimize them. We also develop a data-driven optimization algorithm based on deep learning that reduces the additional delay brought by the iterative optimization method. At the receiver, we estimate the quantization output and quantization error by the modified linear least squares estimation with the virtual noise variance. Based on the simulation results, the proposed framework has a better performance in terms of peak signal-to-noise ratio and structural similarity than the relevant cutting-edge schemes while maintaining good robustness.

Adaptive dispersion compensation using a photonic integrated circuit finite impulse response filter.

Optical equalization can be used for chromatic dispersion compensation in optical communication systems to improve the system performance; however, optical signal processing (OSP) is generally specifically designed for transmission channels, that is non-adaptive to dynamic transmission distortions compared with digital signal processing (DSP). In this contribution, we demonstrate optical equalization using a photonic integrated circuit (PIC) filter for chromatic dispersion compensation, with static and adaptive techniques: (a) the static optical equalizer is calibrated based on the known fiber dispersion and length, by using the fractional delay reference method; (b) the adaptive optical equalizer is updated iteratively to compensate transmission impairments based on a least-mean squares (LMS) algorithm. Experimental results show that both the static optical equalizer and the adaptive optical LMS equalizer can give an 18-dB Q-factor for a 14-Gbd QPSK signal transmitting over 30 km. To highlight the capability of the optical equalizers, we use simulations to show the improvement in dispersion compensating characteristics by implementing additional taps.

Anti-interference Technology of Multi-type Data Acquisition and Transmission Based on HPLC

With the development of the social economy, electricity consumption increases rapidly. A large amount of real-time electricity consumption data plays an important role in analyzing the power grid business. Monitoring power consumption performance through electricity consumption data is also an important indicator to improve power grid performance. By analyzing the characteristics of HPLC channels, such as capacitance characteristics, frequency loss characteristics, signal-to-noise ratio characteristics, line icing, and noise interference, the critical values of data transmission distortion caused by the characteristics of each channel were summarized. On this basis, it is concluded that suitable filters and amplifiers should be selected to improve the signal-to-noise ratio and the transmission quality of HPLC signals. Therefore, an anti-interference technology for data transmission based on HPLC is proposed. Finally, the application advantages and existing problems of HPLC technology in three-stream integration data acquisition and transmission are further explored.

High-Power Orbital Angular Momentum Beam Generation Using Adaptive Control System Based on Mode Selective Photonic Lantern

We demonstrate an all-fiber adaptive spatial control system with a mode selective photonic lantern as the core device to generate orbital angular momentum (OAM) modes. A 3×1 mode selective photonic lantern has been designed and fabricated, which can easily guide OAM modes. The stochastic parallel gradient descent (SPGD) algorithm is used to control the phase of each input channel. A stable OAM <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sub> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> mode with a mode purity of 0.98 is obtained in a 30/130 μm fiber, and a 50W stable quasi-OAM <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sub> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> mode beam is achieved after power scaling in a 42/250 μm output fiber. This system cannot only compensate the atmosphere turbulence effects on transmission distortion, but also be improved to generate switchable OAM modes with different topological charges, which provides great possibility of application in practical communication system.

A Graph Neural Network Learning Approach to Optimize RIS-Assisted Federated Learning

Over-the-air federated learning (FL) is a promising privacy-preserving edge artificial intelligence paradigm, where over-the-air computation enables spectral-efficient model aggregation by achieving simultaneous communication and aggregation. However, due to limited transmit power, the performance of over-the-air FL is limited by the device with the worst channel condition toward the edge server. In this paper, we leverage reconfigurable intelligent surface (RIS) to mitigate the communication bottleneck of over-the-air FL and explicitly characterize the corresponding convergence upper bound. The convergence analysis illustrates the detrimental impact of the accumulated aggregation error over all rounds and inspires us to formulate a time-average transmission distortion minimization problem by jointly optimizing the transceiver and RIS phase-shifts. To reduce the computation complexity and enhance the model aggregation accuracy, we develop a graph neural network (GNN) based learning algorithm to directly map channel coefficients to the optimized network parameters. By exploiting permutation equivalence and invariance properties of graphs, the parameter dimension of the proposed algorithm is independent of the number of edge devices, which reduces the computational complexity and improves the algorithmic scalability. Simulations show that the proposed algorithm speeds up the computation by three orders of magnitude compared to the baselines, while achieving performance superiority and algorithmic robustness.

Experimental study of the nonlinear distortion of non-reciprocal transmission in nonlinear parity-time symmetric LC resonators

At the broken phase of a parity-time (PT)-symmetric dimer where the coupling is weak, the eigenfrequencies are complex conjugate pairs with non-vanishing real parts, leading to oscillation magnitudes with an exponentially growing mode and an exponentially decaying mode. If the large oscillation magnitudes are clamped due to the nonlinear gain of the PT-symmetric dimer, the exponentially growing mode eventually enters the stable oscillations. It was recently demonstrated that such a phenomenon can be utilized for non-reciprocal transmission. The distortion induced by nonlinearity is critical for the non-reciprocal transmission. Here, we experimentally explore the nonlinear distortion in PT-symmetric inductor–capacitor resonators by utilizing discrete components on a printed circuit board. It demonstrates that the IIP3 (the output-referred third-order intercept point) can achieve as high as 38.7 dBm at the frequency of 14.5 MHz corresponding to the maximum forward transmission. The noise figure of the system is measured to be about 11.25 dB.

High-Density Linkage Map Constructed from a Skim Sequenced Diploid Potato Population Reveals Transmission Distortion and QTLs for Tuber Yield and Pollen Shed

The reinvention of potato, from a tetraploid clonal crop into a diploid seed-based hybrid crop, requires insight in the mutational load, recombination landscape, and the genetic basis of fertility. Genomics-based breeding and QTL discovery rely on efficient genotyping strategies such as skim sequencing, to gather genotypic information. The application of skim sequencing to full-sib population of non-inbred parents remains challenging. Here, we report on an R implementation of the OutcrossSeq pipeline for diploids. We applied this pipeline to a large diploid skim sequenced potato population. We used the resulting bin-markers for the construction of high-density parent specific linkage maps, highlighting variation in parental recombination rate and structural variations. We subsequently explored transmission ratio distortion and non-independent assortment of alleles, indicative of large-effect deleterious mutations. Finally, we identified QTLs for seedling tuber yield in pots and pollen shed. This study showcases the range of genetic analyses, from marker inference, identification of transmission ratio distortion, and linkage map construction to QTL mapping, resulting in new insights that contribute to breeding diploid potato.

A gene copy number arms race in action: X,Y-chromosome transmission distortion across a species barrier.

A remarkable gene copy number (CN) arms race system has recently been described in laboratory mice, where Slx;Slxl1 and Sly genes compete over transmission by altering the fertilization success of X and Y chromosome-bearing sperm, respectively. Here, we focus on this system in nature, where natural selection can counter CN/gene product escalation. Our model is house mouse subspecies hybridizing in Europe. In some regions, Y chromosomes of the Eastern subspecies have introgressed onto Western genomic backgrounds, accompanied by sex ratio distortion in favor of males, consistent with the inbred lines suggested mechanism: Overabundance of SLY protein expressed by invading Y chromosomes. We take Slx as representative of the X side of this arms race and measure Slx|Sly CN and expression across an "Invasion" transect where Ys introgress and a "Control" transect with negligible introgression. Since we found similar Slx|Sly ratios in both transects, SLY overabundance is unlikely to explain the introgression. However, Slx CN is relatively low in the introgression area, suggesting that Slx is less able to combat Sly effects here. Furthermore, deterministic changes in Slx;Sly expression proportions versus CN proportions suggest standing variation for trans regulation of Slx|Sly is being co-opted in nature where their arms race reduces population fitness.

LSH-based missing value prediction for abnormal traffic sensors with privacy protection in edge computing

Traffic flow prediction is an important part of intelligent transportation systems (ITS). However, sensor failures or the transmission distortion often occur in the process of data acquisition, which will inevitably cause the loss or abnormality of traffic flow data transmitted to the edge server. In this situation, it is necessary to share traffic flow data among different platforms. However, existing traffic flow prediction methods are facing two challenges in the process of traffic flow data sharing. First, user privacy is often leaked in the process of sharing traffic data on various platforms. Moreover, with the continuous updating of data, the efficiency and scalability of data sharing between different platforms will become lower and lower. In view of the above challenges, in this paper, we propose a novel prediction method for the missing traffic flow data caused by abnormal sensors, named ASMVP_{distr-LSH} based on distributed locality-sensitive hashing (LSH) technique. At last, a case study is presented to illustrate the feasibility and effectiveness of our approach ASMVP_{distr-LSH}.

Distortion in transmission of pathogenic SDHB- and SDHD-mutated alleles from parent to offspring.

Phaeochromocytoma and paraganglioma are highly heritable tumours; half of those associated with a germline mutation are caused by mutations in genes for Krebs's cycle enzymes, including succinate dehydrogenase (SDH). Inheritance of SDH alleles is assumed to be Mendelian (probability of 50% from each parent). The departure from transmission of parental alleles in a ratio of 1:1 is termed transmission ratio distortion (TRD). We sought to assess whether TRD occurs in the transmission of SDHB pathogenic variants (PVs). This study was conducted with 41 families of a discovery cohort from Royal North Shore Hospital, Australia, and 41 families from a validation cohort from St. Bartholomew's Hospital, United Kingdom (UK). Inclusion criteria were a clinically diagnosed SDHB PV and a pedigree available for at least two generations. TRD was assessed in 575 participants with the exact binomial test. The transmission ratio for SDHB PV was 0.59 (P = 0.005) in the discovery cohort, 0.67 (P < 0.001) in the validation cohort, and 0.63 (P < 0.001) in the combined cohort. No parent-of-origin effect was observed. TRD remained significant after adjusting for potential confounders: 0.67 (P < 0.001) excluding families with incomplete family size data; 0.58 (P < 0.001) when probands were excluded. TRD was also evident for SDHD PVs in a cohort of 81 patients from 13 families from the UK. The reason for TRD of SDHB and SDHD PVs is unknown, but we hypothesize a survival advantage selected during early embryogenesis. The existence of TRD for SDHB and SDHD has implications for reproductive counselling, and further research into the heterozygote state.

A method for low-coverage single-gamete sequence analysis demonstrates adherence to Mendel's first law across a large sample of human sperm.

Recently published single-cell sequencing data from individual human sperm (n=41,189; 969-3377 cells from each of 25 donors) offer an opportunity to investigate questions of inheritance with improved statistical power, but require new methods tailored to these extremely low-coverage data (∼0.01× per cell). To this end, we developed a method, named rhapsodi, that leverages sparse gamete genotype data to phase the diploid genomes of the donor individuals, impute missing gamete genotypes, and discover meiotic recombination breakpoints, benchmarking its performance across a wide range of study designs. We then applied rhapsodi to the sperm sequencing data to investigate adherence to Mendel's Law of Segregation, which states that the offspring of a diploid, heterozygous parent will inherit either allele with equal probability. While the vast majority of loci adhere to this rule, research in model and non-model organisms has uncovered numerous exceptions whereby 'selfish' alleles are disproportionately transmitted to the next generation. Evidence of such 'transmission distortion' (TD) in humans remains equivocal in part because scans of human pedigrees have been under-powered to detect small effects. After applying rhapsodi to the sperm data and scanning for evidence of TD, our results exhibited close concordance with binomial expectations under balanced transmission. Together, our work demonstrates that rhapsodi can facilitate novel uses of inferred genotype data and meiotic recombination events, while offering a powerful quantitative framework for testing for TD in other cohorts and study systems.

Travelling wave fault location approach for hybrid LCC-MMC-MTDC transmission line based on frequency modification algorithm

Line-commutated-converter (LCC) based and modular-multilevel-converter (MMC) based hybrid high-voltage direct-current (HVDC) transmission technology is already applied in actual power grid, which has the ability to avoid commutation failure issue. Besides, aiming to acquire high transmission capacity, the multi-terminal direct-current (MTDC) approach is adopted. Although the travelling wave (TW) fault location approach is widely applied in actual power grid, its adaptability for hybrid MTDC topology and transmission distortion are not well considered. Therefore, a novel TW fault location approach for LCC-MMC-MTDC transmission line based on frequency modification algorithm is proposed in this paper. Firstly, the complete frequency modification algorithm suitable for MTDC transmission system is described. Secondly, the novel TW fault location approach and its implementation scheme are given. Eventually, via PSCAD/EMTDC, a series of case studies are illustrated based on typical ±400 kV hybrid LCC-MMC-MTDC simulation model, which implying high robustness against fault location and grounding resistance issues.

Surge detection for smart grid power distribution using a regression-based signal processing model

The smart grid depends on cutting-edge internet and communication technology, which eliminates the need for human intervention and enhances automation of electricity distribution. Power connections convey actuator and monitoring signals to allow transmission distortions to be identified over long distances. This paper introduces a Surge-Detection Signal Processing Model (SDSPM) to augment the detection of signals in smart grids, which relies on the signal-to-distortion ratio observed between definite power distributions. A linear regression model provides decision-making support to prevent backdrops in smart grids. Through the use of this regression model, the measurement of definitive power distribution and surge occurrence means that backdrops and detection time can be reduced. The power surges and abnormal distribution are minimized, and the available power at each terminal is maximized. A 9.72% lower surge rate, an 11.86% higher distribution ratio, an 8.13% higher signal strength and an improvement in the detection rate of 12.92% were achieved.