Magnification Ratio Research Articles

The abundance of clustered primordial black holes from quasar microlensing

While elementary particles are the favored candidate for the elusive dark matter, primordial black holes (PBHs) have also been considered to fill that role. Gravitational microlensing is a very well-suited tool to detect and measure the abundance of compact objects in galaxies. Previous studies based on quasar microlensing exclude a significant presence of substellar to intermediate-mass black holes (BHs; $ 100M_ However, these studies were based on a spatially uniform distribution of BHs while, according to current theories of PBH formation, they are expected to appear in clusters. We study the impact of clustering in microlensing flux magnification, finding that at large scales clusters act like giant pseudo-particles, strongly affecting the emission coming from the broad-line region, which can no longer be used to define the zero microlensing baseline. As an alternative, we set this baseline from the intrinsic magnification ratios of quasar images predicted by macro lens models and compared them with the observed flux ratios in emission lines, infrared, and radio. The (magnitude) differences are the flux-ratio anomalies attributable to microlensing, which we estimate for 35 image pairs corresponding to 12 lens systems. A Bayesian analysis indicates that the observed anomalies are incompatible with the existence of a significant population of clustered PBHs. Furthermore, we find that more compact clusters exhibit a stronger microlensing impact. Consequently, we conclude that clustering makes the existence of a significant population of BHs in the substellar to intermediate mass range even more unlikely.

Design method for zoom systems based on magnification ratio modulation of afocal off-axis three-mirror anastigmat systems

Design method for zoom systems based on magnification ratio modulation of afocal off-axis three-mirror anastigmat systems

Development of a single photon emission microscope system with ∼200 μm spatial resolution

With a low-energy pinhole gamma camera, spatial resolution is primarily determined by the intrinsic spatial resolution of the imaging detector, the pinhole diameter, and the magnification ratio of the collimator. However, the pinhole diameter has traditionally been limited to around 1 mm due to manufacturing difficulties with tungsten. To overcome this limitation and enhance the spatial resolution of the pinhole gamma camera, we fabricated a pinhole with a diameter of 0.1 mm. This pinhole was then combined with a YAP(Ce) imaging detector to create an ultrahigh-resolution pinhole gamma camera. The imaging detector consisted of a 38 mm × 38 mm × 1 mm thick YAP(Ce) plate, optically coupled to a 2-inch square flat panel photomultiplier tube (FP-PMT) with a 1 mm thick light guide. The intrinsic spatial resolution of the YAP(Ce) imaging detector was approximately 1.4 mm FWHM for 60 keV gamma photons. The YAP(Ce) imaging detector was encased in a tungsten shield, and the 0.1 mm diameter pinhole collimator was positioned 100 mm from the imaging detector surface. With a magnification ratio of 10 at 10 mm from the pinhole center, the spatial resolution improved to approximately 0.2 mm (200 μm) at 10 mm from the pinhole center using the developed pinhole gamma camera. The system sensitivity was approximately 0.001%. High-resolution transmission images of various subjects were obtained. The developed ultrahigh-resolution pinhole gamma camera was named the “single-photon emission microscope.” This device will be valuable for applications requiring ultrahigh resolution in single-photon gamma or X-ray imaging.

PRO-SSRGAN: stable super-resolution generative adversarial network based on parameter reconstructive optimization on Gaofen-5 remote-sensing images

ABSTRACT Advances in hardware capabilities and big data technologies over the past decade have enabled the application of deep learning techniques to address the challenge of super-resolution in remote-sensing images. Recently, while deep-learning-based methods have outperformed traditional methods, the abundance of information in remote-sensing images creates an imbalance between performance and computational resource consumption in current deep-learning-based methods. This paper introduces a stable super-resolution algorithm based on parameter reconstructive optimization to address these issues. First, based on the stable super-resolution generative adversarial network (SSRGAN), the algorithm employs a generator with networks using residual connections to reconstruct images with enhanced resolution. Next, it extracts content, adversarial, and regularization losses using the discriminator from a stable super-resolution generative adversarial network, which in turn guides the training of the network. Finally, upon completion of training, structural re-parameterization is conducted to optimize the multi-branch trained network into a plain inference network. This inference network can serve as an individual new generator. The results of qualitative and quantitative experimental comparisons with the models Bicubic, super-resolution convolutional neural network, very deep super-resolution convolutional network, deep recursive residual network, super-resolution generative adversarial network (SRGAN), enhanced SRGAN, and stable SRGAN on the Gaofen-5 AHSI satellite dataset suggest that this algorithm achieves improved evaluation indices with a 4× magnification ratio, reaching a peak signal-to-noise ratio of 30.7207 dB and structural similarity index measure of 0.8178. Compared with the trained but unconverted generator, which can also work independently, implementing re-parameterization results in approximately a 10% reduction in the number of parameters, indicating lower resource consumption, while the reconstruction effect is minimally influenced. Furthermore, the super-resolution results exhibit richer detail, increased contrast, and better scene adaptability.

Design and Testing of a Compliant ZTTΘ Positional Adjustment System with Hybrid Amplification.

This article presents the design, analysis, and prototype testing of a four-degrees-of-freedom (4-DoFs) spatial pose adjustment system (SPAS) that achieves high-precision positioning with 4-DoFs (Z/Tip/Tilt/Θ). The system employs a piezoelectric-driven amplification mechanism that combines a bridge lever hybrid amplification mechanism, a double four-bar guide mechanism, and a multi-level lever symmetric rotation mechanism. By integrating these mechanisms, the system achieves low coupling, high stiffness, and wide stroke range. Analytical modeling and finite element analysis are employed to optimize geometric parameters. A prototype is fabricated, and its performance is verified through testing. The results indicate that the Z-direction feed microstroke is 327.37 μm, the yaw motion angle around the X and Y axes is 3.462 mrad, and the rotation motion angle around the Z axis is 12.684 mrad. The x-axis and y-axis motion magnification ratio can reach 7.43. Closed-loop decoupling control experiments for multiple-input-multiple-outputs (MIMO) systems using inverse kinematics and proportional-integral-derivative feedback controllers were conducted. The results show that the Z-direction positioning accuracy is ±100 nm, the X and Y axis yaw motion accuracy is ±2 μrad, and the Z-axis rotation accuracy is ±25 μrad. Due to the ZTTΘ mechanism, the design proved to be feasible and advantageous, demonstrating its potential for precision machining and micro-nano manipulation.

Submerged flow over various shapes of piano key weir

The weir, an essential element of dams utilized for floodwater management, plays a crucial role in human life. Over the years, nonlinear weirs have advanced into Piano Key Weirs (PKWs). These PKWs provide enhanced discharge efficiency, a reduced structural footprint, and heightened cost-effectiveness. PKWs possess a sophisticated structure defined by numerous geometric parameters. The impact of these parameters on the discharge capacity is of paramount significance. This study aims to experimentally investigate the hydraulic of submerged PKWs with different plan shapes, including triangular, trapezoidal, and rectangular, with apex width to cycle width ratio of (A/w) of 0, 0.25, and 0.5, and magnification ratio (B/w) of 1, 2, and 3, respectively. The results indicate that submergence depends on the shape and size of the PKW. Furthermore, the efficiency of the PKW increases as the ratio of approach flow head to weir height (Ho⁄P) decreases and B⁄w increases. The influence of the shape of the PKW on the performance of the weir is more pronounced at higher values of B/w. Additionally, the order of the highest discharge coefficient values follows a pattern from the trapezoidal to triangular and rectangular PKWs. Specifically, for B⁄w = 2, the trapezoidal PKW exhibits an approximate improvement of 6 and 15 % in the discharge efficiency compared to the triangular and rectangular PKWs, respectively. A new equation was developed to predict the discharge coefficient for different shapes of PKWs under various hydraulic conditions. Based on the experimental data, this study offers valuable insights into the hydraulic behavior and discharge coefficient of PKWs. This research significantly contributes to enhancing our understanding and optimizing the performance of submerged PKWs in water management systems.

Measurement of Postoperative Apical Vertebral Rotation Using Radiographic Images in Adolescent Idiopathic Scoliosis-Quantitative Evaluation Using Inverse Trigonometric Functions.

Conventional methods for analyzing vertebral rotation are limited to postoperative patients who underwent posterior fusion. A previous methodology calculated vertebral rotation using inverse trigonometric functions based on the length of the pedicle screw (PS). Accordingly, this study evaluates rotational deformity in patients with postoperative adolescent idiopathic scoliosis (AIS) using inverse trigonometric functions. This retrospective single-center study includes patients with AIS who underwent posterior fusion surgery. Postoperative radiography and computed tomography (CT) scans were retrospectively evaluated. The magnification ratio was calculated using the rod diameter (δ=lateral/frontal rod diameter), and the visible screw lengths were measured using radiographs. The rotation angle was calculated using the apex of the main curve and the lower instrumented vertebra (LIV) (rotation angle=tan-1 (lateral PS length/(δ×frontal PS length))) immediately following the surgery as well as two and five years postoperatively. The correlation between the direct CT measurement and postoperative rotation angle progression was investigated. The crankshaft phenomenon (CSP) and distal adding-on (DAO) were evaluated as postoperative deformities. CSP was defined as a 5° increase in rotation angle. Seventy-eight patients (age: 15.3±2.0 years, eight boys and seventy girls) were included. The rotation angle was strongly correlated with CT rotation measurements (r=0.87). The mean rotation angle at the apex and LIV did not change within five years postoperatively (mean: 0.5±3.6° and 0.4±3.4°, respectively). CSP and DAO were observed in 6.4% and 3.8% of patients, respectively. The inverse trigonometric method is useful to quantitatively evaluate the postoperative rotation angle and identify CSP.

Quasar Microlensing Statistics and Flux-ratio Anomalies in Lens Models

Precise lens modeling is a critical step in time delay studies of multiply imaged quasars, which are key for measuring some important cosmological parameters (especially H 0). However, lens models (in particular those semi-automatically generated) often show discrepancies with the observed flux ratios between the different quasar images. These flux-ratio anomalies are usually explained through differential effects between images (mainly microlensing) that alter the intrinsic magnification ratios predicted by the models. To check this hypothesis, we collect direct measurements of microlensing to obtain the histogram of microlensing magnifications. We compare this histogram with recently published model flux-ratio anomalies and conclude that they cannot be statistically explained by microlensing. The average value of the model anomalies (0.74 mag) significantly exceeds the mean impact of microlensing (0.33 mag). Moreover, the histogram of model anomalies presents a significant tail with high anomalies (∣Δm∣ ≥ 0.7 mag), which is completely unexpected from the statistics of microlensing observations. Microlensing simulations neither predict the high mean nor the fat tail of the histogram of model anomalies. We perform several statistical tests which exclude that microlensing can explain the observed flux-ratio anomalies (although Kolmogorov–Smirnov, which is less sensitive to the tail of the distributions, is not always conclusive). Thus, microlensing cannot statistically explain the bulk of flux-ratio anomalies, and models may explore different alternatives to try to reduce them. In particular, we propose to complement photometric observations with accurate flux ratios of the broad emission lines obtained from integral field spectroscopy to check and, ideally, constrain lens models.

Single-shot deterministic complex amplitude imaging with a single-layer metalens.

Conventional imaging systems can only capture light intensity. Meanwhile, the lost phase information may be critical for a variety of applications such as label-free microscopy and optical metrology. Existing phase retrieval techniques typically require a bulky setup, multiframe measurements, or prior information of the target scene. Here, we proposed an extremely compact system for complex amplitude imaging, leveraging the extreme versatility of a single-layer metalens to generate spatially multiplexed and polarization phase-shifted point spread functions. Combining the metalens with a polarization camera, the system can simultaneously record four polarization shearing interference patterns along both in-plane directions, thus allowing the deterministic reconstruction of the complex amplitude light field in a single shot. Using an incoherent light-emitting diode as the illumination, we experimentally demonstrated speckle-noise-free complex amplitude imaging for both static and moving objects with tailored magnification ratio and field of view. The miniaturized and robust system may open the door for complex amplitude imaging in portable devices for point-of-care applications.

Achieving low-frequency and high-speed motion based on bionic seal principle for piezoelectric actuator

In this paper, a novel stepping piezoelectric actuator with a compact structure is proposed, which is based on bionic seal principle. It consists of a bridge-type amplification mechanism (BAM) and a diamond-shaped amplification mechanism (DAM). The control signal adopts the square wave, so that the BAM and the DAM move in coordination, and the mechanism drives the mover without backward motion. Through theoretical analysis and finite element analysis (FEA), the displacement magnification ratio of the structure is calculated, and the size of the structure is preliminarily optimized. Finally, a test prototype is made for experimental verification. According to the experiment, urged by the input signal with the frequency of 2 Hz and the amplitude of 150 V to the BAM and DAM, the maximum speed of forward and reverse are 229.2 μm/s and 212.25 μm/s, respectively. It can reach a resolution of 42.1 nm in forward motion and 204.7 nm in reverse. When the load in the vertical direction reaches 50 N, it can still output a stable displacement motion curve. According to the displacement-time curves and the calculation of the moving speed under different voltages, frequencies, and loads, it is proved that this actuator has good low-frequency and high-speed driving performance.

Spatial resolution improvement by a super-resolution technique depending on training process in the background-orientated schlieren analyses

The effectiveness of the enhanced deep super-resolution network (EDSR), which is a super-resolution technique based on the deep convolutional neural network, is investigated for the improvement of spatial resolution during a background-orientated schlieren (BOS) analysis, and its suitable training process in the EDSR method is clarified. Consequently, a training dataset consisting of the simple dot patterns leads to a better image quality due to super-resolution because the image captured in the BOS measurement shows the similar dot patterns. When the image is enlarged at a large magnification ratio, it is important to adjust an image size in the training dataset individually for each magnification ratio, thereby obtaining a good estimation accuracy of the pixel displacement in the BOS analysis. A measurement error is improved by 62% compared with that of the Bicubic method, which is a classical spatial resolution improvement technique at the magnification ratio of 8. The present result shows that the EDSR method with the best training conditions provides a reasonable pixel displacement vector field up to the magnification ratio of 8 for the BOS analysis; however, its effectiveness depends on flow structure.

Optimization of a YAP(Ce) prompt X-ray camera for imaging with spot scanning proton beams at clinical dose levels

Prompt secondary electron bremsstrahlung X-ray (prompt X-ray) imaging using a low-energy X-ray camera is a promising method for observing the beam shape from outside a subject. However, it has sometimes been necessary to conduct such imaging at a higher dose than the clinical level to acquire images with acceptable quality. To solve this problem, we optimized a prompt X-ray imaging system to use for spot scanning proton therapy system. The new camera had more than one order higher sensitivity to image several types of beams, including those at the clinical dose level. The optimized prompt X-ray imaging system uses a 4 mm diameter pinhole collimator to increase sensitivity, and it is combined with a larger YAP(Ce) scintillator to increase the magnification ratio and thus improve spatial resolution. We used a list-mode data-acquisition system with high count rate capability. Prompt X-ray images were acquired by irradiating a water phantom with proton beams from the spot scanning proton therapy system. Measurements were taken for pencil beams, spread-out Bragg peak (SOBP) beams, and a beam utilized in actual clinical therapy. For all of the beams, we could measure scanning spot images within a spill and evaluate the ranges for the accumulated images at the clinical dose level. From the list-mode data, we measured the temporarily altered positions of the scanning beams as well as the accumulations of the prompt X-ray images. The optimized prompt X-ray imaging system could improve sensitivity while maintaining better spatial resolution. The new system realized prompt X-ray imaging at the clinical dose level and holds promise for future clinical imaging of prompt X-rays.

The multi-scale fusion reconstruction algorithm of CT and CL

Computed tomography (CT) is a widely used nondestructive testing (NDT) technique for material research, paleontology research and other fields. However, it is difficult for CT to reconstruct flat objects at high magnification ratios. Computed laminography (CL) enables high-resolution imaging for flat objects due to its unique scanning geometry. A challenging task for CL image reconstruction is to deal with the cross-section artifacts resulting from the incomplete projection data acquired from the CL scan. An effective multi-scale fusion reconstruction algorithm of CT and CL was proposed in this paper. The algorithm combining the advantages of the two scanning geometries, low-resolution CT data was used to compensate for the data missing in CL projection domain, and the cross-section artifacts were reduced. Experiments on paleontological fossils and multilayer printed circuit boards (PCB) were performed, where CT and CL data from different systems and scanning conditions. The results showed that the method can effectively suppress the cross-section artifacts of CL and obtain high-resolution reconstructed images.

A deep learning framework to scale linear facial measurements to actual size using horizontal visible iris diameter: a study on an Iranian population

Digital images allow for the objective evaluation of facial appearance and abnormalities as well as treatment outcomes and stability. With the advancement of technology, manual clinical measurements can be replaced with fully automatic photographic assessments. However, obtaining millimetric measurements on photographs does not provide clinicians with their actual value due to different image magnification ratios. A deep learning tool was developed to estimate linear measurements on images with unknown magnification using the iris diameter. A framework was designed to segment the eyes’ iris and calculate the horizontal visible iris diameter (HVID) in pixels. A constant value of 12.2 mm was assigned as the HVID value in all the photographs. A vertical and a horizontal distance were measured in pixels on photographs of 94 subjects and were estimated in millimeters by calculating the magnification ratio using HVID. Manual measurement of the distances was conducted on the subjects and the actual and estimated amounts were compared using Bland–Altman analysis. The obtained error was calculated as mean absolute percentage error (MAPE) of 2.9% and 4.3% in horizontal and vertical measurements. Our study shows that due to the consistent size and narrow range of HVID values, the iris diameter can be used as a reliable scale to calibrate the magnification of the images to obtain precise measurements in further research.

A three-stage amplification piezoelectric-actuated micro-gripper with adjustable output displacement: design, modeling, and experimental evaluation

Abstract With the development of science and technology, the performance requirements of micro-gripper are getting higher and higher. Therefore, this paper designs a new piezoelectric-driven micro-gripper with large and adjustable output displacement, which can adjust the output range and compensate the errors caused by flexible mechanism. By adjusting the output displacement, the micro-components of different sizes can be clamped. The three-stage amplification mechanism is adopted, which utilizes triangle and lever amplification. Using the pseudo-rigid body method, the flexible hinge is analyzed; the statics, kinematics and dynamics models are established. Through finite element method, the magnification ratio of the micro-gripper is obtained, then the structure of the micro-gripper is further optimized. The output displacement and the magnification of the single-arm of the micro-gripper under 135 V are 223.8 μm and 24.2 times, respectively. This paper provides a basis for the wide application of micro-gripper.

A novel design for stepped spillway using staggered labyrinth trapezoidal steps

Stepped spillways are water structures that have attracted researchers' attention recently. There are many studies on the flow characteristics of different step geometry. In this study, trapezoidal labyrinth-shaped stepped spillways were designed in-line and staggered, and their energy dissipation rates were investigated numerically. OpenFOAM software and the k-ω SST turbulence model were used for numerical analyses. According to the results, the energy dissipation performance of the two-cycle trapezoidal labyrinth step spillway was about 20% higher than the classical one. It was observed that the effective crest length of the trapezoidal steps did not affect the energy dissipation rate much, and the staggered designed steps were more successful than the in-line designed ones. In addition, with the increase in the number of cycles in the same magnification ratio, more energy is dissipated at low flow rates. At the same time, two-cycle labyrinth steps are more effective at high flow rates.

The Impact of Ground Irregular Sedimentary Structure on the Seismic Motion Amplification Characteristics: A case study in Tottori, Japan

The amplification characteristics of seismic motion are determined by the ground structure. In design practice, the ground is assumed to be horizontally stratified. However, the actual ground forms irregular sedimentary structures and the propagation direction of the seismic motion in the soil changes in a complicated way. Thus, the actual amplification factor of seismic motion is dramatically different from the value assumed in design practice. This phenomenon is called the multidimensional effect. The present study targeted at a seismic observation point in Tottori Prefecture, Japan, and estimated the irregular ground structures based on the microtremor observation results. With this ground structure model, Finite Element Analysis (FEA) was conducted and the amplification factors were compared with those determined assuming horizontal stratification. When there is no ground nonlinearity, the multidimensional effect of the ground was more notable in points with thick sedimentary strata, where the peak amplification factor according to the FEA was 1.9 to 3.6 times larger than when horizontal stratification was assumed. In points with thin sedimentary strata, the peak amplification factor ratio was 2.1–2.4. First-order peak frequency was different between cases with irregular ground structures and with horizontal stratification. Furthermore, when the nonlinearity of the ground was evident, the multidimensional effect on the peak amplification factor was not as noticeable as when the ground behaved linearly. The peak magnification ratio due to the multidimensional effect was found to be 2.3. The results of this study show that the amplification characteristics of the seismic motion considered in design practice are likely to be on the dangerous side when the ground is not horizontally stratified.

The Magnificent Five Images of Supernova Refsdal: Time Delay and Magnification Measurements

In late 2014, four images of supernova (SN) “Refsdal,” the first known example of a strongly lensed SN with multiple resolved images, were detected in the MACS J1149 galaxy-cluster field. Following the images’ discovery, the SN was predicted to reappear within hundreds of days at a new position ∼8″ away in the field. The observed reappearance in late 2015 makes it possible to carry out Refsdal’s original proposal to use a multiply imaged SN to measure the Hubble constant H 0, since the time delay between appearances should vary inversely with H 0. Moreover, the position, brightness, and timing of the reappearance enable a novel test of the blind predictions of galaxy-cluster models, which are typically constrained only by the positions of multiply imaged galaxies. We have developed a new photometry pipeline that uses DOLPHOT to measure the fluxes of the five images of SN Refsdal from difference images. We apply four separate techniques to perform a blind measurement of the relative time delays and magnification ratios between the last image SX and the earlier images S1–S4. We measure the relative time delay of SX–S1 to be days and the relative magnification to be . This corresponds to a 1.5% precision on the time delay and 17% precision for the magnification ratios and includes uncertainties due to millilensing and microlensing. In an accompanying paper, we place initial and blind constraints on the value of the Hubble constant.

Estimating the energy dissipation of flow passing over triangular and trapezoidal plan weirs using the GMDH model

Abstract Weirs are one of the most common hydraulic structures used in water engineering projects. In this research, a group method of data handling (GMDH) was developed to estimate the energy dissipation of the flow passing over the labyrinth weirs with triangular and trapezoidal plans. To compare the performance of this model with other types of soft computing models, a multilayer perceptron neural network (MLPNN) was developed. The dimensionless parameters derived from dimensional analysis, including the relative upstream head (ho/P), the number of cycles (Ncy), the Froude number ( Fr), and the magnification ratio (Mr) were used as input variables. The error statistical indicators of the GMDH model in the training phase were R2 = 0.913, RMSE = 0.010, and in the testing phase were R2 = 0.829, RMSE = 0.015. The error statistical indicators of the MLPNN in the training phase were R2 = 0.957, RMSE = 0.007, and in the testing phase were R2 = 0.945, RMSE = 0.009. Examining the structure of the GMDH network shows that ho/P, Ncy, and Mr play more meaningful roles in the development network.

Data-driven segmentation of cortical calcium dynamics.

Demixing signals in transcranial videos of neuronal calcium flux across the cerebral hemispheres is a key step before mapping features of cortical organization. Here we demonstrate that independent component analysis can optimally recover neural signal content in widefield recordings of neuronal cortical calcium dynamics captured at a minimum sampling rate of 1.5×106 pixels per one-hundred millisecond frame for seventeen minutes with a magnification ratio of 1:1. We show that a set of spatial and temporal metrics obtained from the components can be used to build a random forest classifier, which separates neural activity and artifact components automatically at human performance. Using this data, we establish functional segmentation of the mouse cortex to provide a map of ~115 domains per hemisphere, in which extracted time courses maximally represent the underlying signal in each recording. Domain maps revealed substantial regional motifs, with higher order cortical regions presenting large, eccentric domains compared with smaller, more circular ones in primary sensory areas. This workflow of data-driven video decomposition and machine classification of signal sources can greatly enhance high quality mapping of complex cerebral dynamics.