Nonlinear optimization for a low-emittance storage ring.

A multi-objective genetic algorithm (MOGA) is a powerful global optimization tool, but its results are considerably affected by the crossover parameter ηc. Finding an appropriate ηc demands too much computing time because MOGA needs be run several times in order to find a good ηc. In this paper, a self-adaptive crossover parameter is introduced in a strategy to adopt a new ηc for every generation while running MOGA. This new scheme has also been adopted for a multi-generation Gaussian process optimization (MGGPO) when producing trial solutions. Compared with the existing MGGPO and MOGA, the MGGPO and MOGA with the new strategy show better performance in nonlinear optimization for the design of low-emittance storage rings.

Hard X-ray operation of X-ray gas monitors at the European XFEL.

X-ray gas monitors (XGMs) are operated at the European XFEL for non-invasive single-shot pulse energy measurements and average beam-position monitoring. The underlying measurement principle is the photo-ionization of rare gas atoms at low gas pressures and the detection of the photo-ions and photo-electrons created. These are essential for tuning and sustaining self-amplified spontaneous emission (SASE) operation, machine radiation safety, and sorting single-shot experimental data according to pulse energy. In this paper, the first results from XGM operation at photon energies up to 30 keV are presented, which are far beyond the original specification of this device. Here, the Huge Aperture MultiPlier (HAMP) is used for single-shot pulse energy measurements since the standard X-ray gas monitor detectors (XGMDs) do not provide a sufficient signal-to-noise ratio, even at the highest operating gas pressures. A single-shot correlation coefficient of 0.98 is measured between consecutive XGMs operated with HAMP, which is as good as measuring with the standard XGMD detectors. An intra-train non-linearity of the HAMP signal is discovered, and operation parameters to mitigate this effect are studied. The upper repetition rate limit of HAMP operation at 2.25 MHz is also determined. Finally, the possibilities and limits for future XGM operation at photon energies up to 50 keV are discussed.

TaMYB44-5A reduces drought tolerance by repressing transcription of TaRD22-3A in the abscisic acid signaling pathway.

MAIN CONCLUSION: TaMYB44-5A identified as a transcription factor negatively regulates drought tolerance in transgenic Arabidopsis. Drought can severely reduce yields throughout the wheat-growing season. Many studies have shown that R2R3-MYB transcription factors are involved in drought stress responses. In this study, the R2R3-MYB transcription factor MYB44-5A was identified in wheat (Triticum aestivum L.) and functionally analyzed. Three homologs of TaMYB44 were isolated, all of which localized to the nucleus. Overexpression of TaMYB44-5A reduced drought tolerance in Arabidopsis thaliana. Further analysis showed that TaMYB44-5A reduced the sensitivity of transgenic Arabidopsis to ABA. Genetic and transcriptional regulation analyses demonstrated that the expression levels of drought- and ABA-responsive genes were downregulated by TaMYB44-5A, and TaMYB44-5A directly bound to the MYB-binding site on the promoter to repress the transcription level of TaRD22-3A. Our results provide insights into a novel molecular pathway in which the R2R3-MYB transcription factor negatively regulates ABA signaling in response to drought stress.

DISP1 deficiency: Monoallelic and biallelic variants cause a spectrum of midline craniofacial malformations.

PURPOSE: DISP1 encodes a transmembrane protein that regulates the secretion of the morphogen, Sonic hedgehog, a deficiency of which is a major cause of holoprosencephaly (HPE). This disorder covers a spectrum of brain and midline craniofacial malformations. The objective of the present study was to better delineate the clinical phenotypes associated with division transporter dispatched-1 (DISP1) variants. METHODS: This study was based on the identification of at least 1 pathogenic variant of the DISP1 gene in individuals for whom detailed clinical data were available. RESULTS: A total of 23 DISP1 variants were identified in heterozygous, compound heterozygous or homozygous states in 25 individuals with midline craniofacial defects. Most cases were minor forms of HPE, with craniofacial features such as orofacial cleft, solitary median maxillary central incisor, and congenital nasal pyriform aperture stenosis. These individuals had either monoallelic loss-of-function variants or biallelic missense variants in DISP1. In individuals with severe HPE, the DISP1 variants were commonly found associated with a variant in another HPE-linked gene (ie, oligogenic inheritance). CONCLUSION: The genetic findings we have acquired demonstrate a significant involvement of DISP1 variants in the phenotypic spectrum of midline defects. This underlines its importance as a crucial element in the efficient secretion of Sonic hedgehog. We also demonstrated that the very rare solitary median maxillary central incisor and congenital nasal pyriform aperture stenosis combination is part of the DISP1-related phenotype. The present study highlights the clinical risks to be flagged up during genetic counseling after the discovery of a pathogenic DISP1 variant.

MdASMT9-mediated melatonin biosynthesis enhances basal thermotolerance in apple plants.

High temperatures negatively impact the yield and quality of fruit crops. Exogenous melatonin (MT) application has been shown to enhance heat tolerance, but the response of endogenous MT to heat stress, particularly in perennial fruit trees, remains unclear. The present study investigated the effects of high temperatures on transgenic apple plants overexpressing the MT biosynthesis gene N-acetylserotonin methyltransferase 9 (MdASMT9). Endogenous MT protected transgenic plants from heat stress by increasing antioxidant enzyme activity and scavenging reactive oxygen species (ROS), and protecting the chloroplasts from damage. Application of MT and overexpression of MdASMT9 also reduced abscisic acid accumulation through promoting MdWRKY33-mediated transcriptional inhibition of MdNCED1 and MdNCED3, thus inducing stomatal opening for better heat dissipation. Furthermore, MT-enhanced autophagic activity through promoting MdWRKY33-mediated transcriptional enhancement of MdATG18a under heat stress. These findings provide new insights into the regulation of endogenous MT and its role in improving basal thermotolerance in perennial fruit trees.

Unravelling the neglected role of ultraviolet radiation on stomata: A meta-analysis with implications for modelling ecosystem-climate interactions.

Stomata play a pivotal role in regulating gas exchange between plants and the atmosphere controlling water and carbon cycles. Accordingly, we investigated the impact of ultraviolet-B radiation, a neglected environmental factor varying with ongoing global change, on stomatal morphology and function by a Comprehensive Meta-Analysis. The overall UV effect at the leaf level is to decrease stomatal conductance, stomatal aperture and stomatal size, although stomatal density was increased. The significant decline in stomatal conductance is marked (6% in trees and >10% in grasses and herbs) in short-term experiments, with more modest decreases noted in long-term UV studies. Short-term experiments in growth chambers are not representative of long-term field UV effects on stomatal conductance. Important consequences of altered stomatal function are hypothesized. In the short term, UV-mediated stomatal closure may reduce carbon uptake but also water loss through transpiration, thereby alleviating deleterious effects of drought. However, in the long term, complex changes in stomatal aperture, size, and density may reduce the carbon sequestration capacity of plants and increase vegetation and land surface temperatures, potentially exacerbating negative effects of drought and/or heatwaves. Therefore, the expected future strength of carbon sink capacity in high-UV regions is likely overestimated.

Exploring the performance of the topological energy method for object and damage detection from noisy and poor databases.

In this work, we study the performance of numerical methods based on the computation of topological energies to process data from synthetic and real experiments where only noisy limited-view data corresponding to a few frequencies are available. We show numerical experiments in two problems of practical interest. The first one corresponds to experimental measurements of the electromagnetic scattering produced by different objects extracted from the Fresnel database. The second one is related to synthetic experiments in a simplified model where steel welding joints are acoustically tested to identify possible flaws (air bubbles and inclusions) produced during the welding process. This article is part of the theme issue 'Non-smooth variational problems with applications in mechanics'.

RotatedStomataNet: a deep rotated object detection network for directional stomata phenotype analysis.

KEY MESSAGE: Innovatively, we consider stomatal detection as rotated object detection and provide an end-to-end, batch, rotated, real-time stomatal density and aperture size intelligent detection and identification system, RotatedeStomataNet. Stomata acts as a pathway for air and water vapor in the course of respiration, transpiration, and other gas metabolism, so the stomata phenotype is important for plant growth and development. Intelligent detection of high-throughput stoma is a key issue. Nevertheless, currently available methods usually suffer from detection errors or cumbersome operations when facing densely and unevenly arranged stomata. The proposed RotatedStomataNet innovatively regards stomata detection as rotated object detection, enabling an end-to-end, real-time, and intelligent phenotype analysis of stomata and apertures. The system is constructed based on the Arabidopsis and maize stomatal data sets acquired destructively, and the maize stomatal data set acquired in a non-destructive way, enabling the one-stop automatic collection of phenotypic, such as the location, density, length, and width of stomata and apertures without step-by-step operations. The accuracy of this system to acquire stomata and apertures has been well demonstrated in monocotyledon and dicotyledon, such as Arabidopsis, soybean, wheat, and maize. The experimental results that the prediction results of the method are consistent with those of manual labeling. The test sets, the system code, and their usage are also given ( https://github.com/AITAhenu/RotatedStomataNet ).

Heated humidified high-flow nasal cannula: a new conservative approach for neonatal nasal stenosis.

PURPOSE: The aim of this study is to evaluate the efficacy of heated humidified high flow nasal cannula (HFNC) therapy as a conservative treatment option for newborns suffering from nasal stenosis, a condition that often leads to respiratory distress and feeding difficulties. Given the increasing utilization of HFNC in various upper and lower respiratory tract indications, characterized by its flow-based mechanism and minimal mucosal damage, we seek to investigate its potential benefits in this specific patient population. METHODS: A retrospective chart review of newborns with congenital nasal stenosis treated with HFNC for respiratory distress or feeding difficulties in a pediatric tertiary center between 2014 and 2022. Data were collected for demographic characteristics, clinical presentation and ventilatory requirements, pre and post HFNC application. RESULTS: Six infants with nasal stenosis were included in the study cohort. Five were diagnosed with congenital pyriform aperture stenosis, three of whom had additional midnasal stenosis. One patient had nasal synechiae. Two patients had failed surgical treatment and all patients failed conservative treatment prior to HFNC treatment. Following HFNC use, improvement was noted in oxygen saturations, heart and respiratory rates, meal volumes and weight. None of the patients required any additional sinonasal surgical treatment. No complications were observed. CONCLUSIONS: In this case series, we present the first documented use of HFNC treatment for nasal stenosis, showing favorable results. Further studies with a larger cohort, wider range of conditions and extended follow-up periods are needed to establish the risks and benefits of HFNC for neonatal nasal stenosis.

Utilizing collimated aperture with proton pencil beam scanning (PBS) for stereotactic radiotherapy.

PURPOSE: Proton stereotactic radiosurgery (PSRS) has emerged as an innovative proton therapy modality aimed at achieving precise dose delivery with minimal impact on healthy tissues. This study explores the dosimetric outcomes of PSRS in comparison to traditional intensity-modulated proton therapy (IMPT) by focusing on cases with small target volumes. A custom-made aperture system designed for proton therapy, specifically tailored to small target volumes, was developed and implemented for this investigation. METHODS: A prerequisite mechanical validation through an isocentricity test precedes dosimetric assessments, ensuring the seamless integration of mechanical and dosimetry analyses. Five patients were enrolled in the study, including two with choroid melanoma and three with arteriovenous malformations (AVM). Two treatment plans were meticulously executed for each patient, one utilizing a collimated aperture and the other without. Both plans were subjected to robust optimization, maintaining identical beam arrangements and consistent optimization parameters to account for setup errors of 2 mm and range uncertainties of 3.5%. Plan evaluation metrics encompassing the Heterogeneity Index (HI), Paddick Conformity Index (CIPaddick), Gradient Index (GI), and the R50% index to evaluate alterations in low-dose volume distribution. RESULTS: The comparative analysis between PSRS and traditional PBS treatment revealed no significant differences in plan outcomes, with both modalities demonstrating comparable target coverage. However, collimated apertures resulted in discernible improvements in dose conformity, dose fall-off, and reduced low-dose volume. CONCLUSIONS: This study underscores the advantageous impact of the aperture system on proton therapy, particularly in cases involving small target volumes.

Ultrasonic Imaging of Deeper Bone Defect Using Virtual Source Synthetic Aperture with Phased Shift Migration: A Phantom Study.

Ultrasound imaging for bone is a difficult task in the field of medical ultrasound. Compared with other phase array techniques, the synthetic aperture (SA) has a better lateral resolution but a limited imaging depth due to the limited ultrasonic energy emitted by the single emitter in each transmission. In contrast, the virtual source (VS) synthetic aperture allows a simultaneous multi-element emission and could provide a higher ultrasonic incident energy in each transmission. Therefore, the VS might achieve a high imaging quality at a deeper depth for bone imaging than the traditional SA. In this study, we proposed the virtual source phase shift migration (VS-PSM) method to achieve ultrasonic imaging of the deeper bone defect featured in the multilayer structure. The proposed VS-PSM method was validated using standard soft tissue phantom and printed bone phantom with artificial defects. The image quality was evaluated in terms of contrast-to-noise ratios (CNR) and amplitudes of scatters and defects at different imaging depths. The results showed that the VS-PSM method could achieve a high imaging quality of the soft tissues with a significant improvement in the scattering amplitude and without a significant sacrifice of the lateral and axial resolution. The PSM was superior to the DAS in suppressing the background noise in the images. Compared with the traditional SA-PSM, the VS-PSM method could image deeper bone defects at different ultrasonic frequencies, with an average improvement of 50% in CNR. In conclusion, this study demonstrated that the proposed VS-PSM method could image deeper bone defects and might help the diagnosis of bone disease using ultrasonic imaging.

Simulation of Modal Control of Metal Mode-Filtered Vertical-Cavity Surface-Emitting Laser.

In this study, a novel metal-dielectric film mode filter structure that can flexibly regulate the transverse mode inside vertical-cavity surface-emitting lasers (VCSELs) is proposed. The number, volume, and stability of transverse modes inside the VCSEL can be adjusted according to three key parameters-the oxide aperture, the metal aperture, and the distance between the oxide aperture and the metal aperture-to form a flexible window, and a new parameter is defined to describe the mode identification. This study provides a complete simulation theory basis and calculation method, which is of great significance for the optical mode control in VCSELs.

Simulation-Based Approach to the Matching of a Dielectric-Filled Circular Waveguide Aperture.

The circular waveguide aperture or open-end radiator, one of the canonical antenna elements, can be filled with a dielectric material for miniaturization. With dielectric filling, the aperture reflection increases and impedance matching is necessary. This paper presents a simple but innovative simulation-based approach to the aperture matching of a dielectric-filled circular waveguide aperture. By properly loading the aperture with two- or three-section dielectric rings, the impedance matching is possible over a wide frequency range starting slightly above the TE11-mode cutoff and continuing upward. The material for the aperture matching is the same as that filling the waveguide. The proposed matching structure is analyzed and optimized using a simulation tool for the dielectric constant εr of the filling material ranging from 1.8 to 10. For εr ≥ 5, the unmatched reflection coefficient ranges from -6.0 dB to -0.9 dB while the matched reflection coefficient is from -20.4 dB to -10.0 dB. The impedance matching has been achieved over more than an octave bandwidth.

An Airborne Arc Array Synthetic Aperture Radar Vibration Error Compensation Method.

Compared to conventional radars, arc array synthetic aperture radar (SAR) enables wide-area observation under ideal conditions. However, helicopters carrying arc array SAR platforms are generally smaller in size and more sensitive to vibration, which has a greater impact on the imaging quality. In this paper, the vibration error of the arc array SAR platform is investigated, and a vibration error model of the arc array SAR platform is established. Based on the study of the vibration error model, a vibration phase estimation and compensation algorithm based on the delayed conjugate multiplication method is proposed. In the first step, distance pulse pressure processing is performed on the echo signal. In the second step, the pulse pressure signals and their delays in the same distance unit are subjected to conjugate multiplication, and the phase of the signal after conjugate multiplication is extracted. The extracted phase is then amplitude- and phase-compensated to estimate the vibration phase. In the third step, the vibration phase is compensated in the azimuthal direction of the distance pulse pressure signal, and the pairwise echo is eliminated, which completes the compensation of the airborne arc array SAR vibration platform.

A SAR Ship Detection Method Based on Adversarial Training.

SAR (synthetic aperture radar) ship detection is a hot topic due to the breadth of its application. However, limited by the volume of the SAR image, the generalization ability of the detector is low, which makes it difficult to adapt to new scenes. Although many data augmentation methods-for example, clipping, pasting, and mixing-are used, the accuracy is improved little. In order to solve this problem, the adversarial training is used for data generation in this paper. Perturbation is added to the SAR image to generate new samples for training, and it can make the detector learn more abundant features and promote the robustness of the detector. By separating batch normalization between clean samples and disturbed images, the performance degradation on clean samples is avoided. By simultaneously perturbing and selecting large losses of classification and location, it can keep the detector adaptable to more confrontational samples. The optimization efficiency and results are improved through K-step average perturbation and one-step gradient descent. The experiments on different detectors show that the proposed method achieves 8%, 10%, and 17% AP (Average Precision) improvement on the SSDD, SAR-Ship-Dataset, and AIR-SARShip, compared to the traditional data augmentation methods.

Ship Detection in Synthetic Aperture Radar Images under Complex Geographical Environments, Based on Deep Learning and Morphological Networks.

Synthetic Aperture Radar (SAR) ship detection is applicable to various scenarios, such as maritime monitoring and navigational aids. However, the detection process is often prone to errors due to interferences from complex environmental factors like speckle noise, coastlines, and islands, which may result in false positives or missed detections. This article introduces a ship detection method for SAR images, which employs deep learning and morphological networks. Initially, adaptive preprocessing is carried out by a morphological network to enhance the edge features of ships and suppress background noise, thereby increasing detection accuracy. Subsequently, a coordinate channel attention module is integrated into the feature extraction network to improve the spatial awareness of the network toward ships, thus reducing the incidence of missed detections. Finally, a four-layer bidirectional feature pyramid network is designed, incorporating large-scale feature maps to capture detailed characteristics of ships, to enhance the detection capabilities of the network in complex geographic environments. Experiments were conducted using the publicly available SAR Ship Detection Dataset (SSDD) and High-Resolution SAR Image Dataset (HRSID). Compared with the baseline model YOLOX, the proposed method increased the recall by 3.11% and 0.22% for the SSDD and HRSID, respectively. Additionally, the mean Average Precision (mAP) improved by 0.7% and 0.36%, reaching 98.47% and 91.71% on these datasets. These results demonstrate the outstanding detection performance of our method.

A Novel Joint Motion Compensation Algorithm for ISAR Imaging Based on Entropy Minimization.

Space targets move in orbit at a very high speed, so in order to obtain high-quality imaging, high-speed motion compensation (HSMC) and translational motion compensation (TMC) are required. HSMC and TMC are usually adjacent, and the residual error of HSMC will reduce the accuracy of TMC. At the same time, under the condition of low signal-to-noise ratio (SNR), the accuracy of HSMC and TMC will also decrease, which brings challenges to high-quality ISAR imaging. Therefore, this paper proposes a joint ISAR motion compensation algorithm based on entropy minimization under low-SNR conditions. Firstly, the motion of the space target is analyzed, and the echo signal model is obtained. Then, the motion of the space target is modeled as a high-order polynomial, and a parameterized joint compensation model of high-speed motion and translational motion is established. Finally, taking the image entropy after joint motion compensation as the objective function, the red-tailed hawk-Nelder-Mead (RTH-NM) algorithm is used to estimate the target motion parameters, and the joint compensation is carried out. The experimental results of simulation data and real data verify the effectiveness and robustness of the proposed algorithm.

SAR Image Generation Method Using DH-GAN for Automatic Target Recognition.

In recent years, target recognition technology for synthetic aperture radar (SAR) images has witnessed significant advancements, particularly with the development of convolutional neural networks (CNNs). However, acquiring SAR images requires significant resources, both in terms of time and cost. Moreover, due to the inherent properties of radar sensors, SAR images are often marred by speckle noise, a form of high-frequency noise. To address this issue, we introduce a Generative Adversarial Network (GAN) with a dual discriminator and high-frequency pass filter, named DH-GAN, specifically designed for generating simulated images. DH-GAN produces images that emulate the high-frequency characteristics of real SAR images. Through power spectral density (PSD) analysis and experiments, we demonstrate the validity of the DH-GAN approach. The experimental results show that not only do the SAR image generated using DH-GAN closely resemble the high-frequency component of real SAR images, but the proficiency of CNNs in target recognition, when trained with these simulated images, is also notably enhanced.

Three-Dimensional Printed Annular Ring Aperture-Fed Antenna for Telecommunication and Biomedical Applications.

The design of the aperture-fed annular ring (AFAR) microstrip antenna is presented. This proposed design will ease the fabrication and usability of the 3D-printed and solderless 2D materials. This antenna consists of three layers: the patch, the slot within the ground plane as the power transfer medium, and the microstrip line as the feeding. The parameters of the proposed design are investigated using the finite element method FEM to achieve the 50 Ω impedance with the maximum front-to-back ratio of the radiation pattern. This study was performed based on four steps, each investigating one parameter at a time. These parameters were evaluated based on an initial design and prototype. The optimized design of 3D AFAR attained S11 around 17 dB with a front-to-back ratio of more than 30 dB and a gain of around 3.3 dBi. This design eases the process of using a manufacturing process that involves 3D-printed and 2D metallic materials for antenna applications.

Accurate Range Modeling for High-Resolution Spaceborne Synthetic Aperture Radar.

Spaceborne synthetic aperture radar (SAR) is an advanced microwave imaging technology that provides all-weather and all-day target information. However, as spaceborne SAR resolution improves, traditional echo signal models based on airborne SAR design become inadequate due to the curved orbit, Earth rotation, and increased propagation distance. In this study, we propose an accurate range model for high-resolution spaceborne SAR by analyzing motion trajectory and Doppler parameters from the perspective of the space geometry of spaceborne SAR. We evaluate the accuracy of existing range models and propose an advanced equivalent squint range model (AESRM) that accurately fits the actual range history and compensates for high-order term errors by introducing third-order and fourth-order error terms while maintaining the simplicity of the traditional model. The proposed AESRM's concise two-dimensional frequency spectrum form facilitates the design of imaging algorithms. Point target simulations confirm the effectiveness of the proposed AESRM, demonstrating significant improvements in fitting accuracy for range histories characterized by nonlinear trajectories. The developed AESRM provides a robust foundation for designing imaging algorithms and enables higher resolution and more accurate radar imaging.