Structure and Dynamics of Lithosphere and Asthenosphere in Asia: A Seismological Perspective

Knowledge of lithospheric structure is essential for understanding the impact of continental collision and oceanic subduction on surface tectonic configurations. Full-waveform tomographic images reveal lateral heterogeneities and anisotropy of the lithosphere and asthenosphere in Asia. Estimating lithospheric thickness from seismic velocity reductions at depth exhibits large variations underneath different tectonic units. The thickest cratonic roots are present beneath the Sichuan, Ordos, and Tarim basins and central India. Radial anisotropy signatures of 11 representative tectonic provinces uncover the different nature and geodynamic processes of their respective past and present deformation. The large-scale continental lithospheric deformation is characterized by low-velocity anomalies from the Himalayan Orogen to the Baikal rift zone in central Asia, coupled with the post-collision thickening of the crust. The horizontal low-velocity layer of ∼100–300 km depth extent below the lithosphere points toward the existence of the asthenosphere beneath East and Southeast Asia, with heterogeneous anisotropy indicative of channel flows

Evaluation of Rotor Structural and Aerodynamic Loads using Measured Blade Properties

The structural properties of Higher harmonic Aeroacoustic Rotor Test (HART I) blades have been measured using the original set of blades tested in the wind tunnel in 1994. A comprehensive rotor dynamics analysis is performed to address the effect of the measured blade properties on airloads, blade motions, and structural loads of the rotor. The measurements include bending and torsion stiffness, geometric offsets, and mass and inertia properties of the blade. The measured properties are correlated against the estimated values obtained initially by the manufacturer of the blades. The previously estimated blade properties showed consistently higher stiffnesses, up to 30% for the flap bending in the blade inboard root section. The measured offset between the center of gravity and the elastic axis is larger by about 5% chord length, as compared with the estimated value. The comprehensive rotor dynamics analysis was carried out using the measured blade property set for HART I rotor with and without HHC (Higher Harmonic Control) pitch inputs. A significant improvement on blade motions and structural loads is obtained with the measured blade properties

Quantitative Screening of Cervical Cancers for Low-Resource Settings: Pilot Study of Smartphone-Based Endoscopic Visual Inspection After Acetic Acid Using Machine Learning Techniques

Background: Approximately 90% of global cervical cancer (CC) is mostly found in low- and middle-income countries. In most cases, CC can be detected early through routine screening programs, including a cytology-based test. However, it is logistically difficult to offer this program in low-resource settings due to limited resources and infrastructure, and few trained experts. A visual inspection following the application of acetic acid (VIA) has been widely promoted and is routinely recommended as a viable form of CC screening in resource-constrained countries. Digital images of the cervix have been acquired during VIA procedure with better quality assurance and visualization, leading to higher diagnostic accuracy and reduction of the variability of detection rate. However, a colposcope is bulky, expensive, electricity-dependent, and needs routine maintenance, and to confirm the grade of abnormality through its images, a specialist must be present. Recently, smartphone-based imaging systems have made a significant impact on the practice of medicine by offering a cost-effective, rapid, and noninvasive method of evaluation. Furthermore, computer-aided analyses, including image processing-based methods and machine learning techniques, have also shown great potential for a high impact on medicinal evaluations

Disentangled dimensionality reduction for noise-robust speaker diarisation

The objective of this work is to train noise-robust speaker embeddings adapted for speaker diarisation. Speaker embeddings play a crucial role in the performance of diarisation systems, but they often capture spurious information such as noise and reverberation, adversely affecting performance. Our previous work has proposed an auto-encoder-based dimensionality reduction module to help remove the redundant information. However, they do not explicitly separate such information and have also been found to be sensitive to hyper-parameter values. To this end, we propose two contributions to overcome these issues: (i) a novel dimensionality reduction framework that can disentangle spurious information from the speaker embeddings; (ii) the use of a speech/non-speech indicator to prevent the speaker code from representing the background noise. Through a range of experiments conducted on four different datasets, our approach consistently demonstrates the state-of-the-art performance among models without system fusion.Comment: This paper was submitted to Interspeech202

anti-9,10-Di(1-naphth­yl)anthracene pyridine disolvate

In the title compound, C34H22·2C5H5N, there is a crystallographic inversion center in the middle of the anthracene ring system. The dihedral angle between the mean planes of the anthracene and naphthalene ring systems is 83.96 (4)°. The crystal structure is stabilized by weak inter­molecular C—H⋯N and C—H⋯π inter­actions

Rethinking Session Variability: Leveraging Session Embeddings for Session Robustness in Speaker Verification

In the field of speaker verification, session or channel variability poses a significant challenge. While many contemporary methods aim to disentangle session information from speaker embeddings, we introduce a novel approach using an additional embedding to represent the session information. This is achieved by training an auxiliary network appended to the speaker embedding extractor which remains fixed in this training process. This results in two similarity scores: one for the speakers information and one for the session information. The latter score acts as a compensator for the former that might be skewed due to session variations. Our extensive experiments demonstrate that session information can be effectively compensated without retraining of the embedding extractor