Imaging Plate Research Articles

A 45-degree ion-extraction photoelectron velocity map imaging apparatus coupled to the DUV-IR mass spectrometry and spectroscopy instrument

A photoelectron velocity-map imaging (VMI) apparatus has been developed from the DUV-IR photoionization mass spectrometry and spectroscopy instrument. A 45-degree plate-set is designed and combined with the upright reflection time-of-flight mass spectrometer (Re-TOFMS) to pick up target cluster anions and change their trajectory after the vertical reflection. Following the ion-extraction zone, the mass-selected cluster anions then pass through up-down and left-right trajectory adjustment and beam focus until the arrival at the photoelectron detachment zone to encounter the normal incidence of a pulsed UV laser. The detached electrons are subject to acceleration and detected by a dual micro-channel plate detector and imaging on the phosphor screen. This 45-degree ion-extraction photoelectron VMI setup not only expands the function of our DUV-IR instrument for structural chemistry but also facilitates the compatibility with the conventional upright reflection of TOFMS.

Plate Number Recognition based on Hybrid Techniques

Globally and locally, the number of vehicles is on the rise. It is becoming more and more challenging for authorities to track down specific vehicles. Automatic License Plate Recognition becomes an addition to transportation systems automation. Where the extraction of the vehicle license plate is done without human intervention. Identifying the precise place of a vehicle through its license plate number from moving images of the vehicle image is among the crucial activities for vehicle plate discovery systems. Artificial intelligence systems are connecting the gap between the physical world and digital world of automatic license plate detection. The proposed research uses machine learning to recognizing Arabic license plate numbers. An image of the vehicle number plate is captured and the detection is done by image processing, character segmentation which locates Arabic numeric characters on a number plate. The system recognizes the license plate number area and extracts the plate area from the vehicle image. The background color of the number plate identifies the vehicle types: (1) White color for private vehicle; (2) red color for bus and taxi; (3) blue color for governmental vehicle; (4) yellow color for trucks, tractors, and cranes; (5) black color for temporary license; and (6) green color for army. The recognition of Arabic numbers from license plates is achieved by two methods as (1) Google Tesseract OCR based recognition and (2) Machine Learning-based training and testing Arabic number character as K-nearest neighbors (kNN). The system has been tested on 90 images downloaded from the internet and captured from CCTV. Empirical outcomes show that the proposed system finds plate numbers as well as recognizes background color and Arabic number characters successfully. The overall success rates of plate localization and background color detection have been done. The overall success rate of plate localization and background color detection is 97.78%, and Arabic number detection in OCR is 45.56 % as well as in KNN is 92.22%.

A knock-on deuteron imager for measurements of fuel and hotspot asymmetry in direct-drive inertial confinement fusion implosions (invited).

A knock-on deuteron imager (KoDI) has been implemented to measure the fuel and hotspot asymmetry of cryogenic inertial confinement fusion implosions on OMEGA. Energetic neutrons produced by D-T fusion elastically scatter ("knock on") deuterons from the fuel layer with a probability that depends on ρR. Deuterons above 10MeV are produced by near-forward scattering, and imaging them is equivalent to time-integrated neutron imaging of the hotspot. Deuterons below 6MeV are produced by a combination of side scattering and ranging in the fuel, and encode information about the spatial distribution of the dense fuel. The KoDI instrument consists of a multi-penumbral aperture positioned 10-20cm from the implosion using a ten-inch manipulator and a detector pack at 350cm from the implosion to record penumbral images with magnification of up to 35×. Range filters and the intrinsic properties of CR-39 are used to distinguish different charged-particle images by energy along the same line of sight. Image plates fielded behind the CR-39 record a 10keV x-ray image using the same aperture. A maximum-likelihood reconstruction algorithm has been implemented to infer the source from the projected penumbral images. The effects of scattering and aperture charging on the instrument point-spread function are assessed. Synthetic data are used to validate the reconstruction algorithm and assess an appropriate termination criterion. Significant aperture charging has been observed in the initial experimental dataset, and increases with aperture distance from the implosion, consistent with a simple model of charging by laser-driven EMP.

Hard x-ray spectrometer calibrations using a portable120kV x-ray source.

A Cauchois transmission-crystal hard x-ray spectrometer was calibrated by using a portable, compact, battery-powered tungsten x-ray source having 120 peak kilovoltage. The source emission region was characterized by recording high-resolution 2D x-ray images and was found to be composed of three emission regions having a 400 µm overall extent. The absolutely calibrated source fluence was measured by using a calibrated silicon drift detector and was in good agreement with the spectrum calculated by the SpekPy code. High-resolution spectra of the W Kα and Kβ lines in the 57-70keV energy range were recorded on image plate detectors by the Cauchois spectrometer and provided excellent calibrations of the spectrometer's dispersion and spectral resolution. The minimal effect of the source size in the spectral lines recorded on the spectrometer's Rowland circle and the source-size broadening of the spatial lines recorded well beyond the Rowland circle were analyzed. The integrated reflectivity of the spectrometer's quartz (101) crystal was measured by using the absolutely calibrated 59.318keVW Kα1 spectral line emission and was in agreement with previous integrated reflectivity measurements performed at the National Institute of Standards and Technology. The well-characterized portable120kV x-ray source provides a convenient and cost-effective way to accurately calibrate the sensitivity, dispersion, spectral resolution, and source-size broadening in the spectra recorded by high-resolution x-ray spectrometers operating in the hard x-ray range. The absolutely calibrated source fluence can also be used to calibrate x-ray detectors at energies in the 40-100keV energy range.

Unsupervised Domain Adaptive Corner Detection in Vehicle Plate Images.

Rectification of vehicle plate images helps to improve the accuracy of license-plate recognition (LPR). It is a perspective-transformation process to project images as if taken from the front geometrically. To obtain the projection matrix, we require the (x, y) coordinates of four corner positions of plates in images. In this paper, we consider the problem of unsupervised domain adaptation for corner detection in plate images. We trained a model with plate images of one country, the source domain, and applied a domain adaptation scheme so that the model is able to work well on the plates of a different country, the target domain. For this study, we created a dataset of 22,096 Korea plate images with corner labels, which are source domain, and 6762 Philippines, which are target domain. To address this problem, we propose a heatmap-based corner-detection model, which outperforms existing scalar-regression methods, and an image classifier for mixed image of source and target images for domain adaptation. The proposed approach achieves better accuracy, which is 19.1% improvement if compared with baseline discriminator-based domain adaptation scheme.

Reduction of scratch or dirt artifacts on intraoral radiographs using dual imaging plates in image processing.

Artifacts including scratches and dirt artifacts on the digital intraoral radiographs finally contribute to making inaccurate diagnoses. The aim of this study was to reduce the incidence of artifacts using dual imaging plates (DIPs) in imaging processing. Conventional X-rays were taken of a porcine mandible embedded in acrylic resin using a DIP which consists of a front IP (FIP) and a back IP (BIP) with some scratches and dirt. The two images of the FIP and BIP were then synthesized and averaged to obtain a conventional DIP image. The following image processing method was used to make a DIP with artifact reduction (DIP+AR) image. A subtraction image of the FIP and BIP was constructed and the standard deviation (SD) was calculated. If the pixel value was over 3SD on the subtraction images, the pixel value of the DIP was swapped with the value on the opposite side of the non-artifact pixel. The conventional and DIP+AR images were also subjectively evaluated. Image processing to create a DIP+AR image was able to reduce the number of artifacts. Medians of number of artifacts evaluated were 2.00 [interquartile range (IQR), 2.50] in DIP images and 0.67 (IQR, 1.29) in DIP+AR images, indicating a significant reduction of number of artifacts in DIP+AR images. DIP+AR image processing can reduce the incidence of artifacts caused by scratches and dirt, and could extend the lifespan of the IP and contribute accurate diagnosis in oral radiology.

Car-Plate Image Enhancement by Using Median and Max Filters


 
 
 
 Nowadays, Optical Character recognition is one of the affected tools for recognition the plate of car from a still video or image in the intelligent transportation systems. The Optical Character Recognition accuracy incompletely depends on the input image quality. In this article, two efficient approaches are proposed to enhance the quality of the car plate image selected from video clips. To minimize the error rate the proposed technique is used even at low resolution image. Maximum, and median filters are used in this work to enhance the quality of image. These technique extend to collect the pixels of the consecutive frames of the video in filtering approaches. The error rate of the OCR is tested on fifty road and street video clips by decreasing the resolution of the images and filtering them with common and proposed filtering methods. The test results indicate that both proposed methods, improve the accuracy of OCR, and the highest reduction of error is obtained by the proposed temporal maximum filtering method.
 
 
 
 

Deep Learning Assisted Diagnosis of Onychomycosis on Whole-Slide Images.

Background: Onychomycosis numbers among the most common fungal infections in humans affecting finger- or toenails. Histology remains a frequently applied screening technique to diagnose onychomycosis. Screening slides for fungal elements can be time-consuming for pathologists, and sensitivity in cases with low amounts of fungi remains a concern. Convolutional neural networks (CNNs) have revolutionized image classification in recent years. The goal of our project was to evaluate if a U-NET-based segmentation approach as a subcategory of CNNs can be applied to detect fungal elements on digitized histologic sections of human nail specimens and to compare it with the performance of 11 board-certified dermatopathologists. Methods: In total, 664 corresponding H&E- and PAS-stained histologic whole-slide images (WSIs) of human nail plates from four different laboratories were digitized. Histologic structures were manually annotated. A U-NET image segmentation model was trained for binary segmentation on the dataset generated by annotated slides. Results: The U-NET algorithm detected 90.5% of WSIs with fungi, demonstrating a comparable sensitivity with that of the 11 board-certified dermatopathologists (sensitivity of 89.2%). Conclusions: Our results demonstrate that machine-learning-based algorithms applied to real-world clinical cases can produce comparable sensitivities to human pathologists. Our established U-NET may be used as a supportive diagnostic tool to preselect possible slides with fungal elements. Slides where fungal elements are indicated by our U-NET should be reevaluated by the pathologist to confirm or refute the diagnosis of onychomycosis.

Digitization of imaging plates from Guinier powder X-ray diffraction cameras.

A Guinier camera equipped with an imaging plate is used to investigate and eliminate the sources of instrumental errors affecting the quality of the obtained scanned Guinier data. A program with a graphical user interface is presented which converts the data of the scanned images into different standard file formats for powder X-ray patterns containing intensities, their standard deviations and the diffraction angles. The program also allows for manual and automatic correction of the 2θ scale against a known reference material. It is shown using LaB6 that the exported X-ray diffraction patterns provide a 2θ scale reproducible enough to allow for averaging diffractograms obtained from different exposures of the imaging plate for the same sample. As shown on a mixture of NaCl and sodalite, the quality of the produced data is sufficient for Rietveld refinement. The software including source code is made available under a free software license.

Biolum' RGB: A Low-Cost, Versatile, and Sensitive Bioluminescence Imaging Instrument for a Broad Range of Users.

Luminometer and imaging systems are used to detect and quantify low light produced by a broad range of bioluminescent proteins. Despite their everyday use in research, such instruments are costly and lack the flexibility to accommodate the variety of bioluminescence experiment formats that may require top or bottom signal acquisition, high or medium sensitivity, or multiple wavelength detection. To address the growing need for versatile technologies, we developed a highly customizable bioluminescence imager called Biolum' RGB that uses a consumer color digital camera with a high-aperture lens mounted at the bottom or top of a 3D-printed dark chamber and can quantify bioluminescence emission from cells grown in 384-well microplates and Petri dishes. Taking advantage of RGB detectors, Biolum' RGB can distinguish spectral signatures from various bioluminescence probes and quantify bioluminescence resonant energy transfer occurring during protein-protein interaction events. Although Biolum' RGB can be used with any smartphone, in particular for low bioluminescence signals, we recommend the use of recent digital cameras which offer better sensitivity and high signal/noise ratio. Altogether, Biolum' RGB combines the benefits of a plate reader and imager while providing better image resolution and faster acquisition speed, and as such, it offers an exciting alternative for any laboratory looking for a versatile, low-cost bioluminescence imaging instrument.

A dual-scale morphological filtering method for composite damage identification using FBP

Delamination is the main type of defect that reduces the performance of carbon fiber-reinforced polymer (CFRP) composite materials and can be detected by traditional linear ultrasonic methods. However, the traditional ultrasonic inspection method only analyzes its position through the waveform change, and it is difficult to intuitively and accurately study the specific shape and position of the defect in the form of images. This study obtains delamination defect images of CFRP composite plates through fan-beam ultrasonic computed tomography (UCT) and finite element simulation. The Filtered back-projection method based on UCT is used as the basic algorithm for reconstructing layered defect images of CFRP plates. To obtain accurate defect size and location, a novel dual-scale morphological filtering (DSMF) method combined with Canny operator is proposed for edge detection of delamination defects. The DSMF method alternately filters by combining two structuring elements of different sizes while suppressing noise as much as possible and preserving the edge details of the image. As the results verify, the use of the DSMF method combined with Canny edge-detection for edge detection significantly reduces the average recognition error from 16.83% to 4.37% compared to existing methods. The results show that the DSMF method can effectively reduce the influence of artifact interference and non-edge pixels on defect-recognition; thus, the size and contour information of the obtained defects are more accurate than existing methods. Experimental studies using realistic composite plates further validated the proposed method. The method of ultrasonic tomography combined with Canny edge detection based on a DSMF method can be well applied to edge detection and contour recognition of layered defects in CFRP materials.

Assessment and quantification of photostimulable phosphor plate artifacts

<h3>Background</h3> Photostimulable phosphor (PSP) plate artifacts can result in radiopaque areas superimposed over radiologic images, which can affect interpretation. There is currently no objective metric for artifact severity, which could help determine the impact on diagnostic interpretation. <h3>Objectives</h3> To develop a method to objectively quantify artifact severity on PSP plates. <h3>Study Design</h3> Artifacts were identified on clinically used and damaged PSP plates, and assessed using three parameters: surface area, intensity, and location. A grid system was used to quantify the surface area. For intensity, histogram analyses resulted in the development of pixel value thresholds. Location was binarized as grids within and outside a "critical zone." The critical zone is operationalized as an area within which carious lesions are more frequently identified. To define this area, unrestored interproximal carious lesions identified on 190 complementary metal oxide semiconductor (CMOS) images, acting as the artifact-free gold standard, were traced to create a heatmap. Together, these three metrics allowed for the development of an artifact scoring system. <h3>Results</h3> The image critical zone occupied 32.3% of the total sensor area. Two different peaks were identified on the plate histograms, which visually correlated with two distinct types of artifacts. Bending and phosphor degradation resulted in increased numbers of grids that were within a lower pixel value range (40 to 100). In comparison, scratches and surface peeling resulted in increased numbers of grids within a higher pixel value range (above 100). <h3>Conclusion</h3> An image "critical zone" was defined where carious lesions are imaged more frequently. Intensity and surface area have been combined to quantify artifact severity. These metrics allowed for the development of an artifact scoring system, which can then be used to assess the impact on image interpretation. This research lays the groundwork for the future development of a quality control protocol for PSP plates. <b>Statement of Ethical Review</b> Human/Animal subjects were used and this study was approved by an institutional ethics panel.

Cesium-137 and 137Cs/133Cs atom ratios in marine zooplankton off the east coast of Japan during 2012–2020 following the Fukushima Dai-ichi nuclear power plant accident

We measured the concentrations of cesium isotopes (133Cs, 134Cs, and 137Cs) in zooplankton samples collected in waters off the east coast of Japan from May 2015 to June 2020. By combining these data with those obtained previously from May 2012 to February 2015, we evaluated the long-term impacts of the Fukushima Dai-ichi Nuclear Power Plant accident on marine zooplankton. Relatively high 137Cs concentrations in zooplankton, exceeding 10 Bq/kg-dry weight, were sporadically observed until June 2016, regardless of year or station. After May–June 2017, 137Cs concentrations decreased to below 1 Bq/kg-dry at most stations, and by May 2020, concentrations were below 0.5 Bq/kg-dry except those off Fukushima Prefecture. Since the accident, the 137Cs/133Cs atom ratios of zooplankton samples were higher than those of ambient seawater until 2019, but in May–June 2020 the ratios matched those of seawater except off Fukushima Prefecture. Highly radioactive particles were not detected in zooplankton samples by autoradiography using imaging plates after May–June 2017, although they were before. Therefore, the persistence of elevated 137Cs/133Cs ratios in zooplankton relative to seawater for nine years after the accident was probably due to the incorporation of highly radioactive particles (cesium-bearing particles or clay-mineral aggregates with highly adsorbed radiocesium) onto/into zooplankton for several years after the accident. However, since at least May–June 2017, these elevated ratios have likely been caused by small highly radioactive particles (or larger particles disaggregated into small pieces) entering the ocean from land via rivers or directly discharged from the Fukushima Nuclear Power Plant. Microplastics enriched with radiocesium with higher 137Cs/133Cs ratios than seawater may have also contributed 137Cs to the zooplankton.

Pharmacological Comparative Characterization of REL-1017 (Esmethadone-HCl) and Other NMDAR Channel Blockers in Human Heterodimeric N-Methyl-D-Aspartate Receptors.

Excessive Ca2+ currents via N-methyl-D-aspartate receptors (NMDARs) have been implicated in many disorders. Uncompetitive NMDAR channel blockers are an emerging class of drugs in clinical use for major depressive disorder (MDD) and other neuropsychiatric diseases. The pharmacological characterization of uncompetitive NMDAR blockers in clinical use may improve our understanding of NMDAR function in physiology and pathology. REL-1017 (esmethadone-HCl), a novel uncompetitive NMDAR channel blocker in Phase 3 trials for the treatment of MDD, was characterized together with dextromethorphan, memantine, (±)-ketamine, and MK-801 in cell lines over-expressing NMDAR subtypes using fluorometric imaging plate reader (FLIPR), automated patch-clamp, and manual patch-clamp electrophysiology. In the absence of Mg2+, NMDAR subtypes NR1-2D were most sensitive to low, sub-μM glutamate concentrations in FLIPR experiments. FLIPR Ca2+ determination demonstrated low μM affinity of REL-1017 at NMDARs with minimal subtype preference. In automated and manual patch-clamp electrophysiological experiments, REL-1017 exhibited preference for the NR1-2D NMDAR subtype in the presence of 1 mM Mg2+ and 1 μM L-glutamate. Tau off and trapping characteristics were similar for (±)-ketamine and REL-1017. Results of radioligand binding assays in rat cortical neurons correlated with the estimated affinities obtained in FLIPR assays and in automated and manual patch-clamp assays. In silico studies of NMDARs in closed and open conformation indicate that REL-1017 has a higher preference for docking and undocking the open-channel conformation compared to ketamine. In conclusion, the pharmacological characteristics of REL-1017 at NMDARs, including relatively low affinity at the NMDAR, NR1-2D subtype preference in the presence of 1 mM Mg2+, tau off and degree of trapping similar to (±)-ketamine, and preferential docking and undocking of the open NMDAR, could all be important variables for understanding the rapid-onset antidepressant effects of REL-1017 without psychotomimetic side effects.

Analysis of image defects in digital intraoral radiography based on photostimulable phosphor plates.

In digital intraoral radiography (DIR), images with defects caused by the digital process are sometimes produced. Hence, we analyzed DIR images with defects taken using the photostimulable phosphor (PSP) plate method and then classified these images based on the causes of the defect. The aim of this study was to classify defects in DIR using the PSP plate system, and to discuss the causes of each type of defect and the methods that can prevent their occurrence. Images with defects due to the two PSP plate systems (Arcana and Arcana Mira) were selected and classified according to the defect. Image defects caused by geometrical techniques that occur in both the film and PSP plate methods were excluded from this study. Moreover, changes in the rate of occurrence of images with defects over time were analyzed in this study. The defects in images obtained by the PSP plate system were classified into six types, which were further divided into those caused by machine error or human error. Both types of error could influence the diagnostic performance. Machine error accidentally and rarely occurred; thus, the prevention of such errors is difficult. However, human error, especially errors caused by photo-induced discharge, could be prevented using appropriate measures. In DIR systems using the PSP plate method, human error should be prevented by education and training to improve operation.

Streptococcus pneumoniae Rapidly Translocate from the Nasopharynx through the Cribriform Plate to Invade the Outer Meninges.

ABSTRACTThe entry routes and translocation mechanisms of microorganisms or particulate materials into the central nervous system remain obscure We report here that Streptococcus pneumoniae (pneumococcus), or polystyrene microspheres of similar size, appear in the meninges of the dorsal cortex of mice within minutes of inhaled delivery. Recovery of viable bacteria from dissected tissue and fluorescence microscopy show that up to at least 72 h, pneumococci and microspheres were predominantly found in the outer of the two meninges: the pachymeninx. No pneumococci were found in blood or cerebrospinal fluid. Intravital imaging through the skull, aligned with flow cytometry showed recruitment and activation of LysM+ cells in the dorsal pachymeninx at 5 and 10 hours following intranasal infection. Imaging of the cribriform plate suggested that both pneumococci and microspheres entered through the foramina via an inward flow of fluid connecting the nose to the pachymeninx. Our findings bring new insight into the varied mechanisms of pneumococcal invasion of the central nervous system, but they are also pertinent to the delivery of drugs to the brain and the entry of airborne particulate matter into the cranium.

Rancang Bangun Sistem Kendali Pintu Pagar Otomatis Berbasis Pengolahan Citra Digital Pelat Nomor Kendaraan Menggunakan Metode Optical Character Recognition (OCR)

&lt;span&gt;The gate is the main access to enter and exit the vehicle. In general, the gate is opened and closed manually by humans so it takes time and effort. This study proposes the design of an automatic gate control system based on digital image processing of vehicle number plates using the Optical Character Recognition (OCR) method to be able to recognize vehicle number plates. The vehicle number plate image will be recorded by a USB camera and processed using MATLAB to recognize each character on the vehicle number plate. Then the results of processing the vehicle number plate image are compared with the number plate database that has been inputted into the system. If the number plate is registered in the database, MATLAB will forward the command to Arduino Uno to drive the servo motor to open the gate. From the test results, it takes 7 seconds to process the vehicle number plate image processing until the gate is open. The percentage of successful reading of vehicle number plate characters by the MATLAB system is 100% of the 6 number plates tested with an accuracy of 100%. This research can be recommended as an automatic gate control system for security in buildings and homes.&lt;/span&gt;

Calibration of image plate and back illuminated charge coupled device detectors at the thermal emission band of high Z target laser produced plasmas (80–800 eV)

We present a systematic method to absolutely calibrate detector efficiency vs photon energy using a laser produced plasma broadband x-ray source, a gold standard calibrated detector, and transmission gratings (TGs) as dispersive elements. Calibration uses one calibrated TG and a calibrated gold standard detector on one channel and a second calibrated TG and a detector to be calibrated on the other channel. Both channels simultaneously view the laser-produced plasma x-ray source from the same angle with respect to the laser beam and the planar target normal. Image plate detectors are calibrated for the first time at photon energies below 700 eV. Single shot simultaneous calibration of several detectors is possible, making this method an efficient and practical way to periodically calibrate detectors, using in-house capabilities of laser laboratories.

Car license plate segmentation and recognition system based on deep learning

Artificial intelligence techniques and computer vision techniques dealt with the issue of automatic license plate recognition (ALPR) that has many applications in important research field. In this paper, the method of recognizing the license plates of Iraqi cars was applied based on deep learning techniques convolutional neural network (CNN). The two database built to identifying Iraqi car plates. First database includes 2000 images of Arabic numbers and Arabic letters. Second database conations 1200 images of the Arabic names for Iraqi governorates. This paper used image-processing techniques to segmenting the numbers, letters and words from the car license plate images and then convert them into two databases that used to train the two CNN. These training CNN used to recognizing the vocabulary of the car license plate. The success rate of the numbers, letters and words recognition was 98%. The overall rate of success of this proposed system in all stages was 97%.

Development of a fully automated platform for agar-based measurement of viable bacterial growth.

Dynamic in vitro antibacterial studies provide valuable insight on effective dosing strategies prior to translating to in vivo models. Frequent sampling is required to monitor the pharmacodynamics (PD) of these studies, leading to significant work when quantifying the bacterial load of the samples. Spreading a bacterial suspension on agar to allow colony counting is a proven process for measuring very low levels of growth, but commercial automation equipment to handle agar plating and colony counting at scale is not readily available. We describe a process to greatly decrease the hands-on time required for PD assays by utilizing general-purpose liquid handling robots to plate bacteria and a custom-made plate imager to automate colony counting. The platform developed handles the biological assay from beginning to end as well as sample tracking at each step of the process. The process relies heavily on custom automation scheduling software to enable dynamic process decisions and coordinate data flow throughout. Using the described platform, we can efficiently quantify >100 PD samples per day while maintaining the necessary dynamic range of the assay. Alleviating the main bottleneck in the dynamic antibacterial studies has allowed us to accelerate the rate of experiments to provide antibacterial dosing data within shorter timelines.