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Mercury bromide (HgBr) has been used to develop acousto-optic tunable filters (AOTFs) because it has several advantages, including a high refractive index, a broad optical bandwidth, and a relatively high figure of merit. Therefore, the measurement of its birefringence is a highly important factor for ensuring AOTF quality. However, for single crystals, it is difficult (at the millimeter scale) to quantify the birefringence using an ellipsometer, as this equipment is only designed to conduct measurements on thin films. In this study, a simple birefringence measurement system for HgBr was developed based on Brewster's angle at the millimeter scale. The planar distributions of the HgBr crystal along the (100), (010), and (001) planes were used in the experiments. The developed measurement system can measure the reflected light intensity of the HgBr crystal depending on the incidence angles (rotations at 0.01125° steps) and can calculate the ordinary and extraordinary refractive indices and birefringence. The calculated birefringence of the HgBr crystal was 0.8548; this value exhibits an error of 0.64% compared with a value of 0.86 reported in the literature. The developed measurement system demonstrates the ability to be used to evaluate the quality of birefringent single crystals.
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http://dx.doi.org/10.3390/s23094208 | DOI Listing |
Mult Scler
September 2025
Neuroimaging Unit, Neuroimmunology Division, Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Neurology, VA Medical Center, TN Valley Healthcare System, Nashville, TN, USA.
Background: There is limited knowledge on the post-glymphatic structures such as the parasagittal dural (PSD) space and the arachnoid granulations (AGs) in multiple sclerosis (MS).
Objectives: To evaluate differences in volume and macromolecular content of PSD and AG between people with newly diagnosed MS (pwMS), clinically isolated syndrome (pwCIS), or radiologically isolated syndrome (pwRIS) and healthy controls (HCs) and their associations with clinical and radiological disease measures.
Methods: A total of 69 pwMS, pwCIS, pwRIS, and HCs underwent a 3.
Int J Gen Med
September 2025
Department of Neurology, Aerospace Center Hospital, Beijing, 100049, People's Republic of China.
Acute vestibular syndrome (AVS) is characterized by the sudden onset of dizziness or vertigo, accompanied by nausea, vomiting, gait instability, and nystagmus, lasting for more than 24 hours and often persisting for several days to weeks. Central AVS primarily involves central vestibular structures, such as the brainstem and cerebellum, and is most commonly caused by ischemic stroke in the posterior circulation. When acute posterior circulation infarction presents solely with isolated dizziness or vertigo, without other symptoms of central nervous system damage, it is often misdiagnosed as a peripheral vestibular disorder, this can lead to serious consequences.
View Article and Find Full Text PDFNeurotrauma Rep
August 2025
Department of Radiology, Weill Cornell Medicine; New York, New York, USA.
Traumatic brain injury (TBI) impairs attention and executive function, often through disrupted coordination between cognitive and autonomic systems. While electroencephalography (EEG) and pupillometry are widely used to assess neural and autonomic responses independently, little is known about how these systems interact in TBI. Understanding their coordination is essential to identify compensatory mechanisms that may support attention under conditions of neural inefficiency.
View Article and Find Full Text PDFFront Rehabil Sci
August 2025
Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, CA, United States.
Introduction: Spinal cord injury (SCI) presents a significant burden to patients, families, and the healthcare system. The ability to accurately predict functional outcomes for SCI patients is essential for optimizing rehabilitation strategies, guiding patient and family decision making, and improving patient care.
Methods: We conducted a retrospective analysis of 589 SCI patients admitted to a single acute rehabilitation facility and used the dataset to train advanced machine learning algorithms to predict patients' rehabilitation outcomes.