DIA-TTS: Deep-Inherited Attention-Based Text-to-Speech Synthesizer.

Text-to-speech (TTS) synthesizers have been widely used as a vital assistive tool in various fields. Traditional sequence-to-sequence (seq2seq) TTS such as Tacotron2 uses a single soft attention mechanism for encoder and decoder alignment tasks, which is the biggest shortcoming that incorrectly or repeatedly generates words when dealing with long sentences. It may also generate sentences with run-on and wrong breaks regardless of punctuation marks, which causes the synthesized waveform to lack emotion and sound unnatural. In this paper, we propose an end-to-end neural generative TTS model that is based on the deep-inherited attention (DIA) mechanism along with an adjustable local-sensitive factor (LSF). The inheritance mechanism allows multiple iterations of the DIA by sharing the same training parameter, which tightens the token-frame correlation, as well as fastens the alignment process. In addition, LSF is adopted to enhance the context connection by expanding the DIA concentration region. In addition, a multi-RNN block is used in the decoder for better acoustic feature extraction and generation. Hidden-state information driven from the multi-RNN layers is utilized for attention alignment. The collaborative work of the DIA and multi-RNN layers contributes to outperformance in the high-quality prediction of the phrase breaks of the synthesized speech. We used WaveGlow as a vocoder for real-time, human-like audio synthesis. Human subjective experiments show that the DIA-TTS achieved a mean opinion score (MOS) of 4.48 in terms of naturalness. Ablation studies further prove the superiority of the DIA mechanism for the enhancement of phrase breaks and attention robustness.

Monitoring Response to Platelet-Rich Plasma in Patients with Alopecia Areata with Optical Coherence Tomography: A Case Series.

Alopecia areata (AA) is an autoimmune hair loss condition that is difficult to treat and frequently disruptive to the psychosocial well-being of patients. Platelet-rich plasma (PRP) is an innovative therapy that provides concentrated GFs that impart anti-inflammatory effects. Optical coherence tomography (OCT) is a noninvasive imaging modality with the potential for providing quantitative monitoring of AA response to PRP. Our objective is to share our experience using OCT to monitor the therapeutic progress of patients with AA treated with PRP. Two patients with patchy AA and one with alopecia universalis were treated with PRP three times at 6-week intervals as part of a larger clinical trial. Patients were followed from baseline to week 24 with OCT imaging. OCT demonstrates an increase in hair density associated with improvement in inflammation at week 24. Conversely, the patient with alopecia universalis did not experience any significant change in follicular activity. This case series exemplifies the potential of PRP in inflammatory regulation as well as hair regrowth in patchy AA, whereas there is no notable advantage in alopecia universalis. Our findings add evidence on the possible value of OCT in quantitatively assessing hair growth progress throughout a treatment course.

Viscosity monitoring during hemodiluted blood coagulation using optical coherence elastography.

Rapid and accurate clot diagnostic systems are needed for the assessment of hemodiluted blood coagulation. We develop a real-time optical coherence elastography (OCE) system, which measures the attenuation coefficient of a compressional wave induced by a piezoelectric transducer (PZT) in a drop of blood using optical coherence tomography (OCT), for the determination of viscous properties during the dynamic whole blood coagulation process. Changes in the viscous properties increase the attenuation coefficient of the sample. Consequently, dynamic blood coagulation status can be monitored by relating changes of the attenuation coefficient to clinically relevant coagulation metrics, including the initial coagulation time and the clot formation rate. This system was used to characterize the influence of activator kaolin and the influence of hemodilution with either NaCl 0.9% or hydroxyethyl starch (HES) 6% on blood coagulation. The results show that PZT-OCE is sensitive to coagulation abnormalities and is able to characterize blood coagulation status based on viscosity-related attenuation coefficient measurements. PZT-OCE can be used for point-of-care testing for diagnosis of coagulation disorders and monitoring of therapies.

The effect of melanin on in vivo optical coherence tomography of the skin in a multiethnic cohort.

BACKGROUND: Noninvasive real-time assessment of living tissue is quickly becoming invaluable for bolstering histologic and dermatoscopic measures of cutaneous conditions. While many skin researchers have explored the utility of noninvasive imaging in inflammatory and malignant skin conditions, there is yet to be a definitive and direct assessment of the effects of melanin on the quality of optical coherence tomography (OCT) imaging and its accuracy in multiethnic patient populations. We conducted a study to evaluate the effects of melanin on the quality of in vivo OCT imaging. METHODS: Volunteers of all Fitzpatrick skin types were imaged once in five skin regions. Images were analyzed for quality, defined quantitatively as depreciation of light as it passes through the depth of skin, and qualitatively as depth and contrast ranked by blinded clinicians. RESULTS: Our analysis of sixteen subjects shows that there is a significant difference in quantitative OCT image quality between light (Fitzpatrick I-III) and dark (IV-VI) skin types for both epidermal (p 0.0328) and dermal levels (p 0.0021). However, there was no significant difference in qualitative blinded rater measures of image clarity (p 0.11) or perceived depth (p 0.13). CONCLUSION: Based on our definition of image quality, our study shows that OCT images taken from darker skin types have slightly lower quality than those taken from lighter skin. However, because blinded rater assessment showed no differences in clarity or perceived depth, we conclude that OCT may be used without hesitation for manual visualization of skin and its appendages in all Fitzpatrick skin types. Further studies are required to more extensively characterize the effects of melanin on OCT imaging. Lasers Surg. Med. 51:407-411, 2019. © 2019 Wiley Periodicals, Inc.

Multimodality endoscopic optical coherence tomography and fluorescence imaging technology for visualization of layered architecture and subsurface microvasculature.

Endoscopic imaging technologies, such as endoscopic optical coherence tomography (OCT) and near-infrared fluorescence, have been used to investigate vascular and morphological changes as hallmarks of early cancer in the gastrointestinal tract. Here we developed a high-speed multimodality endoscopic OCT and fluorescence imaging system. Using this system, the architectural morphology and vasculature of the rectum wall were obtained simultaneously from a Sprague Dawley rat in vivo. This multimodality imaging strategy in a single imaging system permits the use of a single imaging probe, thereby improving prognosis by early detection and reducing costs.

Coaxial excitation longitudinal shear wave measurement for quantitative elasticity assessment using phase-resolved optical coherence elastography.

Optical coherence elastography (OCE) is an emerging imaging modality for the assessment of mechanical properties in soft tissues. Transverse shear wave measurements using OCE can quantify the elastic moduli perpendicular to the force direction, however, missing the elastic information along the force direction. In this study, we developed coaxial excitation longitudinal shear wave measurements for quantification of elastic moduli along the force direction using M-scans. Incorporating Rayleigh wave measurements using non-coaxial lateral scans into longitudinal shear wave measurements, directionally dependent elastic properties can be quantified along the force direction and perpendicular to the force direction. Therefore, the reported system has the capability to image elasticity of anisotropic biological tissues.

SR-TTS: a rhyme-based end-to-end speech synthesis system.

Deep learning has significantly advanced text-to-speech (TTS) systems. These neural network-based systems have enhanced speech synthesis quality and are increasingly vital in applications like human-computer interaction. However, conventional TTS models still face challenges, as the synthesized speeches often lack naturalness and expressiveness. Additionally, the slow inference speed, reflecting low efficiency, contributes to the reduced voice quality. This paper introduces SynthRhythm-TTS (SR-TTS), an optimized Transformer-based structure designed to enhance synthesized speech. SR-TTS not only improves phonological quality and naturalness but also accelerates the speech generation process, thereby increasing inference efficiency. SR-TTS contains an encoder, a rhythm coordinator, and a decoder. In particular, a pre-duration predictor within the cadence coordinator and a self-attention-based feature predictor work together to enhance the naturalness and articulatory accuracy of speech. In addition, the introduction of causal convolution enhances the consistency of the time series. The cross-linguistic capability of SR-TTS is validated by training it on both English and Chinese corpora. Human evaluation shows that SR-TTS outperforms existing techniques in terms of speech quality and naturalness of expression. This technology is particularly suitable for applications that require high-quality natural speech, such as intelligent assistants, speech synthesized podcasts, and human-computer interaction.

Ultralow-cost piezoelectric sensor constructed by thermal compression bonding for long-term biomechanical signal monitoring in chronic mental disorders.

Wearable bioelectronic devices, which circumvent issues related to the large size and high cost of clinical equipment, have emerged as powerful tools for the auxiliary diagnosis and long-term monitoring of chronic psychiatric diseases. Current devices often integrate multiple intricate and expensive devices to ensure accurate diagnosis. However, their high cost and complexity hinder widespread clinical application and long-term user compliance. Herein, we developed an ultralow-cost poly(vinylidene fluoride)/zinc oxide nanofiber film-based piezoelectric sensor in a thermal compression bonding process. Our piezoelectric sensor exhibits remarkable sensitivity (13.4 mV N-1), rapid response (8 ms), and exceptional stability over 2000 compression/release cycles, all at a negligibly low fabrication cost. We demonstrate that pulse wave, blink, and speech signals can be acquired by the sensor, proposing a single biomechanical modality to monitor multiple physiological traits associated with bipolar disorder. This ultralow-cost and mass-producible piezoelectric sensor paves the way for extensive long-term monitoring and immediate feedback for bipolar disorder management.

Double total variation (DTV) regularization and Improved adaptive moment estimation (IADAM) optimization method for fast MR image reconstruction.

BACKGROUND AND OBJECTIVE: Compressed sensing has been extensively studied as an advanced technique for fast MR image reconstruction. Current reconstruction algorithms often use total variation as the regularization term. Traditional total variation can easily lead to a staircase effect because it only pays attention to the variational information of the horizontal and vertical subbands. METHODS: In this paper, we propose a novel algorithm to reduce the staircase effect by increasing the variational information of the two diagonal subbands, which named Double Total Variation (DTV). We optimize the conjugate gradient algorithm by Improved Adaptive Moment Estimation (IADAM) as the solution algorithm. RESULTS: MR images of three body parts (head, knee and ankle) were used for simulations under different acceleration factor conditions. The conjugate gradient and fast conjugate gradient series algorithms were selected for comparison experiments. The results showed that the improved adaptive moment estimation conjugate gradient combined with DTV achieves the best reconstruction performance, therefore proved the superiority of DTV. After that, 64 different MR images of the three body parts were further simulated and the results demonstrated the general superiority from the proposed algorithm. CONCLUSIONS: The results of this study support that the proposed method may facilitate the development of the research field of image reconstruction algorithms and provide ideas for other algorithmic improvements.

Efficient Pause Extraction and Encode Strategy for Alzheimer's Disease Detection Using Only Acoustic Features from Spontaneous Speech.

Clinical studies have shown that speech pauses can reflect the cognitive function differences between Alzheimer's Disease (AD) and non-AD patients, while the value of pause information in AD detection has not been fully explored. Herein, we propose a speech pause feature extraction and encoding strategy for only acoustic-signal-based AD detection. First, a voice activity detection (VAD) method was constructed to detect pause/non-pause feature and encode it to binary pause sequences that are easier to calculate. Then, an ensemble machine-learning-based approach was proposed for the classification of AD from the participants' spontaneous speech, based on the VAD Pause feature sequence and common acoustic feature sets (ComParE and eGeMAPS). The proposed pause feature sequence was verified in five machine-learning models. The validation data included two public challenge datasets (ADReSS and ADReSSo, English voice) and a local dataset (10 audio recordings containing five patients and five controls, Chinese voice). Results showed that the VAD Pause feature was more effective than common feature sets (ComParE: 6373 features and eGeMAPS: 88 features) for AD classification, and that the ensemble method improved the accuracy by more than 5% compared to several baseline methods (8% on the ADReSS dataset; 5.9% on the ADReSSo dataset). Moreover, the pause-sequence-based AD detection method could achieve 80% accuracy on the local dataset. Our study further demonstrated the potential of pause information in speech-based AD detection, and also contributed to a more accessible and general pause feature extraction and encoding method for AD detection.

Rapid classification of micro-particles using multi-angle dynamic light scatting and machine learning approach.

The rapid classification of micro-particles has a vast range of applications in biomedical sciences and technology. In the given study, a prototype has been developed for the rapid detection of particle size using multi-angle dynamic light scattering and a machine learning approach by applying a support vector machine. The device consisted of three major parts: a laser light, an assembly of twelve sensors, and a data acquisition system. The laser light with a wavelength of 660 nm was directed towards the prepared sample. The twelve different photosensors were arranged symmetrically surrounding the testing sample to acquire the scattered light. The position of the photosensor was based on the Mie scattering theory to detect the maximum light scattering. In this study, three different spherical microparticles with sizes of 1, 2, and 4 µm were analyzed for the classification. The real-time light scattering signals were collected from each sample for 30 min. The power spectrum feature was evaluated from the acquired waveforms, and then recursive feature elimination was utilized to filter the features with the highest correlation. The machine learning classifiers were trained using the features with optimum conditions and the classification accuracies were evaluated. The results showed higher classification accuracies of 94.41%, 94.20%, and 96.12% for the particle sizes of 1, 2, and 4 µm, respectively. The given method depicted an overall classification accuracy of 95.38%. The acquired results showed that the developed system can detect microparticles within the range of 1-4 µm, with detection limit of 0.025 mg/ml. Therefore, the current study validated the performance of the device, and the given technique can be further applied in clinical applications for the detection of microbial particles.

Nanoscale thermal transport across an GaAs/AlGaAs heterostructure interface.

We studied the thermal transport across a GaAs/AlGaAs interface using time-resolved Reflection High Energy Electron Diffraction. The lattice temperature change of the GaAs nanofilm was directly monitored and numerically simulated using diffusive heat equations based on Fourier's Law. The extracted thermal boundary resistances (TBRs) were found to decrease with increasing lattice temperature imbalance across the interface. The TBRs were found to agree well with the Diffuse Mismatch Model in the diffusive transport region, but showed evidence of further decrease at temperatures higher than Debye temperature, opening up questions about the mechanisms governing heat transfer at interfaces between very similar semiconductor nanoscale materials under highly non-equilibrium conditions.

Simultaneously imaging and quantifying in vivo mechanical properties of crystalline lens and cornea using optical coherence elastography with acoustic radiation force excitation.

The crystalline lens and cornea comprise the eye's optical system for focusing light in human vision. The changes in biomechanical properties of the lens and cornea are closely associated with common diseases, including presbyopia and cataract. Currently, most in vivo elasticity studies of the anterior eye focus on the measurement of the cornea, while lens measurement remains challenging. To better understand the anterior segment of the eye, we developed an optical coherence elastography system utilizing acoustic radiation force excitation to simultaneously assess the elasticities of the crystalline lens and the cornea in vivo. A swept light source was integrated into the system to provide an enhanced imaging range that covers both the lens and the cornea. Additionally, the oblique imaging approach combined with orthogonal excitation also improved the image quality. The system was tested through first ex vivo and then in vivo experiments using a rabbit model. The elasticities of corneal and lens tissue in an excised normal whole-globe and a cold cataract model were measured to reveal that cataractous lenses have a higher Young's modulus. Simultaneous in vivo elasticity measurements of the lens and cornea were performed in a rabbit model to demonstrate the correlations between elasticity and intraocular pressure and between elasticity and age. To the best of our knowledge, we demonstrated the first in vivo elasticity of imaging of both the lens and cornea using acoustic radiation force-optical coherence elastography, thereby providing a potential powerful clinical tool to advance ophthalmic research in disorders affecting the lens and the cornea.

Associations of amygdala volume and shape with transactive response DNA-binding protein 43 (TDP-43) pathology in a community cohort of older adults.

Transactive response DNA-binding protein 43 (TDP-43) pathology is common in old age and is strongly associated with cognitive decline and dementia above and beyond contributions from other neuropathologies. TDP-43 pathology in aging typically originates in the amygdala, a brain region also affected by other age-related neuropathologies such as Alzheimer's pathology. The purpose of this study was two-fold: to determine the independent effects of TDP-43 pathology on the volume, as well as shape, of the amygdala in a community cohort of older adults, and to determine the contribution of amygdala volume to the variance of the rate of cognitive decline after accounting for the contributions of neuropathologies and demographics. Cerebral hemispheres from 198 participants of the Rush Memory and Aging Project and the Religious Orders Study were imaged with MRI ex vivo and underwent neuropathologic examination. Measures of amygdala volume and shape were extracted for all participants. Regression models controlling for neuropathologies and demographics showed an independent negative association of TDP-43 with the volume of the amygdala. Shape analysis revealed a unique pattern of amygdala deformation associated with TDP-43 pathology. Finally, mixed-effects models showed that amygdala volume explained an additional portion of the variance of the rate of decline in global cognition, episodic memory, semantic memory, and perceptual speed, above and beyond what was explained by demographics and neuropathologies.

In-vivo 3D corneal elasticity using air-coupled ultrasound optical coherence elastography.

Corneal elasticity can resist elastic deformations under intraocular pressure to maintain normal corneal shape, which has a great influence on corneal refractive function. Elastography can measure tissue elasticity and provide a powerful tool for clinical diagnosis. Air-coupled ultrasound optical coherence elastography (OCE) has been used in the quantification of ex-vivo corneal elasticity. However, in-vivo imaging of the cornea remains a challenge. The 3D air-coupled ultrasound OCE with an axial motion artifacts correction algorithm was developed to distinguish the in-vivo cornea vibration from the axial eye motion in anesthetized rabbits and visualize the elastic wave propagation clearly. The elastic wave group velocity of in-vivo rabbit cornea was measured to be 5.96 ± 0.55 m/s, which agrees with other studies. The results show the potential of 3D air-coupled ultrasound OCE with an axial motion artifacts correction algorithm for quantitative in-vivo assessment of corneal elasticity.

Retrospective analysis of epidemiology and prognostic factors for candidemia at a hospital in China, 2000-2009.

The incidence of candidemia has increased in recent years. This paper reports a retrospective analysis of 270 cases of candidemia occurring from January 2000 to December 2009 at a teaching hospital in China. Demographic and clinical data were collected from patient medical records and the hospital's laboratory database. Candida albicans (35.9%) was the most prevalent species isolated, followed by C. tropicalis (21.8%) and C. glabrata (13.0%). Antifungal susceptibilities to fluconazole, flucytosine, and amphotericin B tended to decline over the study period. The most common risk factors were the presence of central venous catheters, endotracheal intubation, hypoproteinemia, renal failure, and concurrent bacteremia. In the 181 (67.0%) patients who died during hospitalization, endotracheal intubation, hypoproteinemia, and C. albicans were the major factors associated with mortality. This study highlights the importance of considering the possibility of invasive Candida infection in patients exposed to these risk factors.