Resolution Values Research Articles

Evaluation of inner ear malformation based on high-resolution CT and MRI

Objective:To explore the value of high resolution computed tomography（HRCT） combined with Magnetic Resonance Imaging（MRI） in the diagnosis of inner ear malformation. Methods:HRCT and MRI data of 82 patients with inner ear malformations were analyzed retrospectively. HRCT MPR and CPR reconstruction of the inner ear structure, facial nerve canal and oblique sagittal MRI reconstruction of the internal auditory canal were performed. The inner ear malformations were classified, the conditions of facial nerve canal and cochlear nerve were evaluated. The association between inner ear malformation and cochlear nerve dysplasia were analyzed by Chi-square test with continuity correction. Results:Among the 82 patients with inner ear malformations,there were 49 cases of bilateral symmetry, 11 cases of bilateral asymmetry and 22 cases of unilateral inner ear malformations. Respectively, the most prevalent types were IP-Ⅱ（42.96%）, dilatation of atrium aqueduct（18.31%） and malformations of atrium and semicircular canal 19.72%. Out of 50 cases of cochlear malformations,only 3 were isolated cochlear malformations, and the rest were accompanied by other malformations of varying degrees. In the 67 ears examined by MRI, 26（38.81%） had cochlear nerve deficiency（CND）, and the incidence of CND varied with different types of inner ear malformations. Out of 142 ears, 28（19.72%） had abnormalities of the facial nerve canal. Conclusion:HRCT combined with MRI can accurately distinguish the types of inner ear malformation and effectively evaluate the facial nerve canal and cochlear nerve, and further provides the important finger and Guide value for the clinician to formulate the reasonable treatment and the operation plan.

The Role of Citizenship Education on Enhancing the Promotion of Unity in Nigeria: Implication for Primary Education

Citizenship education, as a pedagogical approach, emphasizes the development of civic responsibility, tolerance, and national identity, which are essential for addressing the challenges posed by Nigeria's ethnic, cultural, and religious diversity. The study explores how the integration of citizenship education in primary schools helps inculcate values such as respect for diversity, patriotism, and conflict resolution skills among young learners. Using a survey research design, data were collected from 320 Nigeria Certificate in Education (NCE) students from Nwafor Orizu College of Education, Nsugbe, and Federal College of Education (Technical), Umunze, in Anambra State, Nigeria. Purposive random sampling was employed to select respondents from Social Studies, Economics, English, and Igbo Language departments. A structured questionnaire with 15 items on a 4-point Likert scale was used for data collection, and reliability was confirmed using the Pearson Product Moment Correlation Coefficient. Data analysis involved mean scores, with a cutoff of 2.50 for agreement. Findings revealed that ethnic hatred, religious intolerance, distrust, lack of basic education, and colonial policies are significant barriers to unity in Nigeria. Citizenship education was found to promote unity by enhancing the appreciation of diversity, instilling values of cooperation and tolerance, and equipping individuals with conflict resolution skills. However, challenges such as a lack of qualified teachers, insufficient instructional materials, and inadequate commitment from educators hinder its effectiveness. The findings highlight the importance of incorporating citizenship education into primary education to cultivate values that promote unity among young learners. The research findings imply the need for systematic transformation in the basic education curriculum, by integrating programs that comprehensively teach the values ​​of tolerance, cooperation, and conflict resolution.

Molecular Docking and Drug Kinetics Assessment for Structure-Based Drug Design of New Piperazine-Containing Hydrazone Derivatives as Effective Alzheimer Inhibitors

The neurodegenerative condition known as Alzheimer's disease (AD) impairs cognitive function and produces dementia in older people. The disease's precise mechanism is still a mystery. Four drugs are available. However, they all have a long list of adverse effects and only help people with their warning signs. Medicinal chemists are searching for ways to treat this disease. There is discussion about creating and using a new class of multifunctional small molecule inhibitors. The hydrazone scaffold was used to create a wide range of chemicals. This is because hydrazone derivatives may disrupt the self-assembly of amyloid beta (A), one of the factors that cause fibrils and oligomers. They may also reverse the effects of harmful compounds like free radicals on effective therapeutic agents like medications that penetrate the central nervous system. Structure-based drug design methods were used in this investigation. A protein target (code ID 4EY7) was selected based on published literature research and factors like a lower resolution value (2.35), no mutation, Homo sapiens, and the X-ray diffraction technique. Fifteen Hydrazone derivatives with increased interactions, higher binding scores, and improved drug-like properties and drug kinetic parameters were designed using the protein target, engineered to interact with compounds of interest (a lead compound with a higher binding energy). Promising pharmacotherapeutic drugs for AD treatment may be developed using the results of these investigations.

Comparison of Anti-Inflammatory Effects of Prednisolone versus Nepafenac 0.3% after Phacoemulsification and Intraocular Lens Implantation

Objective: To compare the anti-inflammatory effects and safety profiles of prednisolone acetate 1% and nepafenac 0.3% in patients undergoing phacoemulsification with intraocular lens implantation (IOL). Methods: This cross-sectional study was conducted at Sindh Institute of Ophthalmology and Visual Sciences, Hyderabad, Pakistan from December 2023 to July 2024. The study included patients underwent uneventful phacoemulsification with IOL implantation. Post-operative outcomes were assessed at a single follow-up conducted at 4 weeks. Primary efficacy endpoint was improvement in best-corrected visual acuity, measured as the reduction in Logarithmic Minimum angle of resolution (logMAR) values from baseline to follow-up. Clinically significant improvement was defined as a reduction of ≥0.2 logMAR units. Secondary outcomes included anterior chamber inflammation, graded using Standardization of Uveitis Nomenclature criteria, and incidence of adverse events. Results: Of total 324 patients, mean age was 64.77 ±9.27 years. Mean logMAR change from baseline to follow-up was 0.28 ±0.11 units in the Prednisolone group and 0.30 ±0.11 units in the Nepafenac group, with statistically significant difference (p-value 0.050). The findings of clinical improvement, showed that 121 (48.8%) patients achieved clinical improvement in the Prednisolone group and 127 (51.2%) in the Nepafenac group. The distribution of inflammation grades (0, 1+, 2+, 3+), was similar between the Prednisolone and Nepafenac groups. A total of 76 (23.4%) adverse events were reported, with 40 (52.6%) occurring in the Prednisolone group and 36 (47.4%) in the Nepafenac group. Conclusion: Both prednisolone acetate and nepafenac are effective and safe in managing post-operative inflammation and improving visual outcomes following phacoemulsification.

Using a convection-permitting climate model to assess wine grape productivity: two case studies in Italy

Abstract. The article explores the potential use of climate models to reproduce wine grape productivity at a local scale in Italy. To this end, both single and multiple regression approaches are used to link productivity data provided by two Italian wine consortia with bioclimatic indices. Temperature- and precipitation-based bioclimatic indices are computed using the observational dataset E-OBS, the high-resolution climate reanalysis product SPHERA, the regional climate model CNRM-ALADIN, and the kilometer-scale convection-permitting climate model CNRM-AROME. The multiple regression method outperforms the single regression systematically, enhancing the ability of bioclimatic indices to explain productivity variability. The results show that productivity is strongly tied to temperature-based bioclimatic indices in the area of the Consorzio per la tutela del Franciacorta in northern Italy, while for the Consorzio del Vino Nobile di Montepulciano area in central Italy both temperature- and precipitation-based indices are relevant. Climate models, providing similar results as E-OBS and SPHERA, appear to be a useful tool to explain productivity variance. In particular, the added value of convection-permitting resolution is evident when precipitation-based indices are considered. This assessment shows windows of opportunity for using climate models, especially at a convection-permitting scale, to investigate future climate change impact on wine production.

Application of Adaptive Search Window-Based Nonlocal Total Variation Filter in Low-Dose Computed Tomography Images: A Phantom Study

Computed tomography (CT) imaging using low-dose radiation effectively reduces radiation exposure; however, it introduces noise amplification in the resulting image. This study models an adaptive nonlocal total variation (NL-TV) algorithm that efficiently reduces noise in X-ray-based images and applies it to low-dose CT images. In this study, an AAPM CT performance phantom is used, and the resulting image is obtained by applying an annotation filter and a high-pitch protocol. The adaptive NL-TV filter was designed by applying the optimal window value calculated by confirming the difference between Gaussian filtering and the basic NL-TV approach. For quantitative image quality evaluation parameters, contrast-to-noise ratio (CNR), coefficient of variation (COV), and sigma value were used to confirm the noise reduction effectiveness and spatial resolution value. The CNR and COV values in low-dose CT images using the adaptive NL-TV filter, which performed an optimization process, improved by approximately 1.29 and 1.45 times, respectively, compared with conventional NL-TV. In addition, the adaptive NL-TV filter was able to acquire spatial resolution data that were similar to a CT image without applying noise reduction. In conclusion, the proposed NL-TV filter is feasible and effective in improving the quality of low-dose CT images.

42 mm large aperture variable-focus lens based on the liquid-membrane-liquid structure

Variable-focus lenses enable dynamic focus control and reduce the volume of the optical systems. However, few of them have been scaled up to large apertures of 10 mm, which limits their application scenarios. Here, a variable-focus lens prototype with a 42 mm large aperture based on the liquid-membrane-liquid structure was proposed and evaluated. The prototype shows a range of adjustable optical power at [−3 D, +3 D], and demonstrates high repeatability during the operation process. The average normalized modulation transfer function value for an imaging system shows 0.7904 in 17.204 lp/mm and 0.5439 in 34.409 lp/mm. The resolution values in horizontal and vertical directions are 8 lp/mm and 8.98 lp/mm, respectively. Besides, the millisecond-level response time of the prototype is achieved with a rising edge of 5.02 ms and a falling edge of 3.66 ms. The prototype demonstrates the application scenarios of variable-focus lenses for large aperture requirements with the potential for satisfactory performance, such as in wearable devices, machine vision systems, and so on.

The Climate Data for Adaptation and Vulnerability Assessments and the Spatial Interactions Downscaling Method

This study presents the spatial interactions downscaling (SPID) method and introduces the climate data for adaptation and vulnerability assessments (ClimAVA) dataset. SPID employs random forest models to capture the relationship between spatial patterns at global circulation model (GCM) resolution and fine-resolution pixel values. In summary, a random forest model is trained for each fine spatial resolution pixel of the reference data as the predictand, and nine pixels from the spatially resampled (coarser) version of the reference data at the GCM’s resolutions as predictors. Models are then utilized to downscale the bias-corrected GCM data. The ClimAVA-SW dataset offers a high-resolution (4 km), bias-corrected, downscaled future climate projection derived from seventeen CMIP6 GCMs. It includes three variables (daily precipitation, minimum and maximum temperature) for three shared socioeconomic pathways (SSP245, SSP370, SSP585) across the U.S. Southwest region. The ClimAVA dataset sets itself apart with the SPID method’s capacity to provide remarkable climate realism, high physical plausibility of change, and excellent representation of extreme events while maintaining user-friendliness and requiring relatively low computational resources.

Spatial resolution limit for a solid immersion lens

The solid immersion (SI) effect is widely used to increase the spatial resolution of optical focusing systems and even overcome the Abbe diffraction limit. Resolution enhancement offered by a SI lens is mostly a function of its geometry and refractive index nSI. While SI lenses are relatively well understood, the scaling of the resolution enhancement by such lenses is still a subject of debate, with some works reporting ≃nSI and ≃nSI2 dependencies for the hemispherical and hyperhemispherical SI lens configurations, respectively. In this paper, we offer a general argument for a resolution limit for SI optics and, then, verify it via the numerical analysis of the hemispherical and hyperhemispherical silicon SI lenses designed for the terahertz (THz) range. In fact, we find that there is no contradiction in the reported resolution enhancements ≃nSI and ≃nSI2; however, they happen in different operation regimes. We then demonstrate that the resolution values reported for the different SI lens arrangements in the visible (VIS), near-, and middle-infrared (NIR and MIR), as well as THz bands obey the derived limit. Our findings will be useful for the further design and applications of SI optics.

Device response principles and the impact on energy resolution of epitaxial quantum dot scintillators with monolithic photodetector integration

Epitaxial quantum dot (QD) scintillator crystals with picosecond-scale timing and high light yield have been created for medical imaging, high energy physics and national security applications. Monolithic photodetector (PD) integration enables the sensing of photons generated within the waveguiding crystal and allows a wide range of scintillator-photodetector coupling geometries. Until recently, these doubly novel devices have suffered from complex, high variance responses to monoenergetic sources which significantly reduces their precision and accuracy. The principles governing the overall device response have now been discerned and embodied by an expression derived within a geometrical optics framework which considers optical properties, surface roughness and photodetector coupling geometry. Response variation due to these factors was sufficiently reduced to obtain material-related energy resolution values of 2.4% with alpha particles. These findings place energy resolution alongside luminescence timescale, photon yield, and radiation hardness as outstanding properties of these engineered materials.

Evaluation of super resolution technology for digestive endoscopic images

ObjectThis study aims to evaluate the value of super resolution (SR) technology in augmenting the quality of digestive endoscopic images. MethodsIn the retrospective study, we employed two advanced SR models, i.e., SwimIR and ESRGAN. Two discrete datasets were utilized, with training conducted using the dataset of the First Affiliated Hospital of Soochow University (12,212 high-resolution images) and evaluation conducted using the HyperKvasir dataset (2,566 low-resolution images). Furthermore, an assessment of the impact of enhanced low-resolution images was conducted using a 5-point Likert scale from the perspectives of endoscopists. Finally, two endoscopic image classification tasks were employed to evaluate the effect of SR technology on computer vision (CV). ResultsSwinIR demonstrated superior performance, which achieved a PSNR of 32.60, an SSIM of 0.90, and a VIF of 0.47 in test set. 90 % of endoscopists supported that SR preprocessing moderately ameliorated the readability of endoscopic images. For CV, enhanced images bolstered the performance of convolutional neural networks, whether in the classification task of Barrett's esophagus (improved F1-score: 0.04) or Mayo Endoscopy Score (improved F1-score: 0.04). ConclusionsSR technology demonstrates the capacity to produce high-resolution endoscopic images. The approach enhanced clinical readability and CV models’ performance of low-resolution endoscopic images.

Effect of Different Fluorescence Iabelling Methods of the Actin Cytoskeleton for Storm Application

The Abbe limit was a major challenge in optical microscopy, making it difficult to observe microscopic biological structures. However, the development of STORM, a new fluorescence localization microscopy technique, has enabled much higher resolution imaging by causing dye molecules to blink under laser light. Advances in computational analysis have further improved image processing and resolution, leading to clearer observations and a better understanding of biological structures. Actin, a common protein in eukaryotic cells, forms F-actin, a filament involved in essential processes like cell division, migration, and muscle contraction. Fluorescence labeling is crucial for visualizing F-actin and other cellular structures, allowing scientists to study these important processes. This project explored two methods to visualize actin structures in Hela cells: phalloidin labeling with Alexa-647 dye and DNA-PAINT using GFP. ThunderSTORM analysis produced normalized images for both methods, and resolution values were calculated using FRC. The results indicated that phalloidin labeling provided higher resolution but lower-quality images, while DNA-PAINT with GFP offered better-quality images but with lower resolution.

SP8.11 - Conflict Resolution in Surgery

Abstract Aim In our study, we dive into perspectives gathered from academic and public investigations, shedding light on how patient safety is at risk when communication and professional behaviours crumble within surgical teams. Despite clear evidence, current educational paths for both undergraduates and postgraduates prioritise surgical knowledge and skills, sidelining the crucial aspects of effective teamwork and conflict resolution. The increasing diversity in the surgical workforce, paired with a spectrum of personalities, emphasises the urgency of evaluating the evidence base on how interpersonal conflict impacts and exploring effective interventions. This evaluation is pivotal for shaping the direction of future curricula. Methods We took a systematic approach, exploring databases using keywords like "conflict resolution," "surgery," and "healthcare professionals," and related terms. Following PRISMA guidelines, we analysed identified studies, resolving any discrepancies through collaborative discussions among reviewers. Results Sixty-three studies reveal the adverse effects of interpersonal conflict on healthcare professionals (HCPs), leading to stress, burnout, job dissatisfaction, and compromising team effectiveness and patient safety. Conflict causes were categorised into systemic and interpersonal factors, with resolution interventions focusing on improving communication skills, organising team-building workshops, and facilitating debriefing sessions. Despite recognising the value of conflict resolution, variations in strategies were noted across different surgical specialties. Conclusion This systematic review underlines interpersonal conflict within surgical teams as a significant threat to patient safety and the well-being of healthcare professionals. The literature exposes strategic diversity in reported educational interventions, advocating for the integration of formalised training in teamworking and conflict resolution—an often overlooked yet vital component in surgical curricula.

Preparation of DNA nanoflower-modified capillary silica monoliths for chiral separation.

Innovative chiral capillary silica monoliths (CSMs) were developed based on DNA nanoflowers (DNFs). Baseline separation of enantiomers such as atenolol, tyrosine, histidine, and nefopam was achieved by using DNF-modified CSMs, and the obtained resolution value was higher than 1.78. To further explore the effect of DNFs on enantioseparation, different types of chiral columns including DNA strand containing the complementary sequence of the template (DCT)-modified CSMs, DNF2-modified CSMs, and DNF3-modified CSMs were prepared as well. It was observed that DNF-modified CSMs displayed better chiral separation ability compared with DCT-based columns. The intra-day and inter-day repeatability of model analytes' retention time and resolution kept desirable relative standard deviation values of less than 8.28%. DNF2/DNF3-modified CSMs were able to achieve baseline separation of atenolol, propranolol, 2'-deoxyadenosine, and nefopam enantiomers. Molecular docking simulations were performed to investigate enantioselectivity mechanisms of DNA sequences for enantiomers. To indicate the successful construction of DNFs and DNF-modified CSMs, various charaterization approaches including scanning electron microscopy, agarose gel electrophoresis, dynamic light scattering analysis, electroosmotic flow, and Fourier-transform infrared spectroscopy were utilized. Moreover, the enantioseparation performance of DNF-modified CSMs was characterized in terms of sample volume, applied voltage, and buffer concentration. This work paves the way to applying DNF-based capillary electrochromatography microsystems for chiral separation.

Nationwide prospective audit for the evaluation of appendicitis risk prediction models in adults: right iliac fossa treatment (RIFT)-Turkey.

Appendicitis is the most prevalent surgical emergency. The negative appendicectomy rate and diagnostic uncertainty are important concerns. This study aimed to assess the effectiveness of current appendicitis risk prediction models in patients with acute right iliac fossa pain. A nationwide prospective observational study was conducted, including all consecutive adult patients who presented with right iliac fossa pain. Diagnostic, clinical and negative appendicectomy rate data were recorded. The Alvarado score, Appendicitis Inflammatory Response (AIR), Raja Isteri Pengiran Anak Saleha Appendicitis (RIPASA) and Adult Appendicitis Score systems were calculated with collected data to classify patients into risk categories. Diagnostic value and categorization performance were evaluated, with use of risk category-based metrics including 'true positive rate' (percentage of appendicitis patients in the highest risk category), 'failure rate' (percentage of patients with appendicitis in the lowest risk category) and 'categorization resolution' (true positive rate/failure rate). A total of 3358 patients from 84 centres were included. Female patients were less likely to undergo surgery than men (71.5% versus 82.5% respectively; relative risk 0.866, 95% c.i. 0.834 to 0.901, P < 0.001); with a three-fold higher negative appendicectomy rate (11.3% versus 4.1% respectively; relative risk 2.744, 95% c.i. 2.047 to 3.677, P < 0.001). Ultrasonography was utilized in 56.8% and computed tomography in 75.2% of all patients. The Adult Appendicitis Score had the best diagnostic performance for the whole population; however, only RIPASA was significant in men. All scoring systems were successful in females patients, but Adult Appendicitis Score had the highest area under the receiver operating characteristic curve value. The RIPASA and the Adult Appendicitis Score had the best categorization resolution values, complemented by their exceedingly low failure rates in both male and female patients. Alvarado and AIR had extremely high failure rates in men. The negative appendicectomy rate was low overall, but women had an almost three-fold higher negative appendicectomy rate despite lower likelihood to undergo surgery. The overuse of imaging tests, best exemplified by the 75.2% frequency of patients undergoing computed tomography, may lead to increased costs. Risk-scoring systems such as RIPASA and Adult Appendicitis Score appear to be superior to Alvarado and AIR.

Mechanical properties of Acropora cervicornis aragonite skeleton by using multiscale models based on micro-CT data

Corals, crucial for ocean ecosystems, face threats such as ocean acidification from global warming and pollution, which weaken their skeletons. This study focuses on Acropora cervicornis, known for its hard but fragile structure, requiring strength and flexibility to withstand the forces from climate-driven atmospheric events. An experiment using uniaxial mechanical loading from the initial stage to complete failure at a very low strain rate (1.2821 × 10−5 s−1) was conducted to ascertain the mechanical properties of corals. The geometric properties and Young's modulus were analysed based on various levels of micro-architectural details from micro-CT data, with resolution values influencing the measurements. The highest resolution model showed a Young's modulus approaching 22.265 GPa and porosity at 40.448%. Calibration of finite element models incorporating micro-architectural details enabled a precise comparison of parameter effects and more accurate results, highlighting the significance of resolution in modelling coral mechanical properties.

How does a dynamic surface roughness affect snowpack modeling?

The SNOWPACK model is a cryosphere model which incorporates several environmental model parameters, one of which being the aerodynamic roughness length (z0). The z0 is considered a static parameter, however, research has shown that the z0 of the surface is variable due to the changing nature of the snowpack surface throughout the winter season. This study highlights the sensitivity of the z0 within the SNOWPACK model based on the outputs of sublimation, SWE, and sensible heat. The z0 values were calculated in two ways, anemometrically (z0-A), using a wind profile, and geometrically (z0-G), measuring surface geometry. Calculated z0-A values were between 1.03 × 10−6 to 0.12 m. The z0-G values were calculated from a terrestrial lidar scan using various resolution values of post-process resolutions. These resolutions of 0.01, 0.1, and 1 m resulted in z0-G values of 0.26, 0.08, and 0.01 m, respectively. Therefore, as the resolution coarsened, the z0-G values decreased. Lastly, these calculated z0-G values, a variable run, using weekly measured z0-G values, and 0.002 (SNOWPACK default), 0.02, and 0.2 m values were incorporated into the SNOWPACK model. When applied, cumulative sublimation, SWE, and sensible heat outputs varied by 131%, −71%, and −49%, when compared to the default z0 value used within the model.

Kintex ultrascale’s multi-segment digital tapped delay lines with controlled characteristics for precise time-to-digital conversion

This paper describes an efficient method of designing and implementing in FPGA devices complex tapped delay lines (CTDL) with pico and sub-picosecond resolution. Achieving a higher resolution and better linearity is possible by appropriate selection of single time coding tapped delay lines (TDL) involved in creation of CDTL. The proposed TDL selection algorithm significantly optimizes the size of the device’s logical resources required to implement CDTL with assumed parameters and provides a proper selection scenario. Ultimately, the presented solution allows to create CTDLs with different user-defined configurations based on a fixed set of available logical resources. Therefore, it is particularly recommended for prototyping in smaller FPGA devices. In this work, we investigate how the order of line selection influences the increase of the multiple time coding lines resolution. Furthermore, we determine the relation between the equivalent resolution value and the number of TDLs involved. Obtained results allow to estimate the upper limit of resolution that can be achieved using a given technology. In addition, the ranges of resolutions achievable with a fixed number of lines is also examined. The presented research results have been performed on a Kintex UltraScale FPGA chip, manufactured by Xilinx in the 20-nm CMOS process.

Clinical boundary conditions for propagation-based X-ray phase contrast imaging: from bio-sample models targeting to clinical applications.

Typical propagation-based X-ray phase contrast imaging (PB-PCI) experiments using polyenergetic sources are tested in very ideal conditions: low-energy spectrum (mainly characteristic X-rays), small thickness and homogeneous materials considered weakly absorbing objects, large object-to-detector distance, long exposure times and non-clinical detector. Explore PB-PCI features using boundary conditions imposed by a low power polychromatic X-ray source (X-ray spectrum without characteristic X-rays), thick and heterogenous materials and a small area imaging detector with high low-detection radiation threshold, elements commonly found in a clinical scenario. A PB-PCI setup implemented using a microfocus X-ray source and a dental imaging detector was characterized in terms of different spectra and geometric parameters on the acquired images. Test phantoms containing fibers and homogeneous materials with close attenuation characteristics and animal bone and mixed soft tissues (bio-sample models) were analyzed. Contrast to Noise Ratio (CNR), system spatial resolution and Kerma values were obtained for all images. Phase contrast images showed CNR up to 15% higher than conventional contact images. Moreover, it is better seen when large magnifications (>3) and object-to-detector distances (>13 cm) were used. The influence of the spectrum was not appreciable due to the low efficiency of the detector (thin scintillator screen) at high energies. Despite the clinical boundary condition used in this work, regarding the X-ray spectrum, thick samples, and detection system, it was possible to acquire phase contrast images of biological samples.

Design, Modeling, and Testing of a Long-Stroke Fast Tool Servo Based on Corrugated Flexure Units.

To further enhance the performance of the fast tool servo (FTS) system in terms of stroke, load capacity, and application area, this paper proposes a novel fast tool servo device driven by a voice coil motor (VCM), based on a three-segment uniform corrugated flexure (CF) guiding mechanism, with a large stroke, high accuracy, and high dynamics. To describe the unified static characteristics of such device, the compliance matrix method is applied to establish its model, where the influence of CF beam structural parameters on the FTS device is investigated in detail. Furthermore, resolution and positioning accuracy tests are conducted to validate the features of the system. The testing results indicate that the maximum stroke of the FTS device is up to 3.5 mm and the positioning resolution values are 3.6 μm and 2.4 μm for positive and negative stroke, respectively, which further verifies the device's effectiveness and promising application prospect in ultra-precision microstructure machining.