Narrow linewidth laser based on a sidewall grating active distributed Bragg reflector.

We demonstrated a narrow linewidth semiconductor laser based on a deep-etched sidewall grating active distributed Bragg reflector (SG-ADBR). The coupling coefficients and reflectance were numerically simulated for deep-etched fifth-order SG-ADBR, and a reflectance of 0.86 with a bandwidth of 1.04 nm was obtained by the finite element method for a 500-period SG-ADBR. Then the fifth-order SG-ADBR lasers were fabricated using projection i-line lithography processes. Single-mode lasing at 1537.9 nm was obtained with a high side-mode suppression ratio (SMSR) of 65 dB, and a continuous tuning range of 10.3 nm was verified with SMSRs greater than 53 dB. Furthermore, the frequency noise power spectral density was characterized, from which a Lorentzian linewidth of 288 kHz was obtained.

Directly modulated deformed-square-FP coupled-cavity laser with intracavity-mode photon-photon resonance.

We propose and demonstrate a high-speed directly modulated laser based on a hybrid deformed-square-FP coupled cavity (DFC), aiming for a compact-size low-cost light source in next-generation optical communication systems. The deformed square microcavity is directly connected to the FP cavity and utilized as a wavelength-sensitive reflector with a comb-like and narrow-peak reflection spectrum for selecting the lasing mode, which can greatly improve the single-mode yield of the laser and the quality (Q) factor of the coupled mode. By optimizing the device design and operating condition, the modulation bandwidth of the DFC laser can be enhanced due to the intracavity-mode photon-photon resonance effect. Our experimental results show an enhancement of 3-dB modulation bandwidth from 19.3 GHz to 30 GHz and a clear eye diagram at a modulation rate of 25 Gbps.

Feedback insensitivity in a self-chaotic microcavity laser.

Insensitivity to external optical feedback is experimentally demonstrated in a self-chaotic deformed square microcavity laser for the first time, to the best of our knowledge. Both the optical and radio frequency (RF) spectra of the microlaser remain unaffected for external optical feedback with feedback strength as high as 9.9 dB. In addition, the autocorrelation function curve exhibits no time-delayed peaks. The insensitivity makes the self-chaotic microcavity laser promising for applications in feedback-insensitive optical sources.

Optical time domain reflectometry based on a self-chaotic circular-sided microcavity laser.

A self-chaotic circular-sided square microcavity laser, with a chaos bandwidth of 12.9 GHz and a flatness of ±3d B, was applied in optical time domain reflectometry (OTDR). Using the broadband chaos laser, we demonstrated a range resolution of 4.5 mm and a 25-km detection distance experimentally. The solitary wide-bandwidth microcavity chaos laser, without the extra correlation peaks in optical feedback chaotic lasers, has shown potential advantages for correlation OTDR in practical application.

A nursing note-aware deep neural network for predicting mortality risk after hospital discharge.

BACKGROUND: ICU readmissions and post-discharge mortality pose significant challenges. Previous studies used EHRs and machine learning models, but mostly focused on structured data. Nursing records contain crucial unstructured information, but their utilization is challenging. Natural language processing (NLP) can extract structured features from clinical text. This study proposes the Crucial Nursing Description Extractor (CNDE) to predict post-ICU discharge mortality rates and identify high-risk patients for unplanned readmission by analyzing electronic nursing records. OBJECTIVE: Developed a deep neural network (NurnaNet) with the ability to perceive nursing records, combined with a bio-clinical medicine pre-trained language model (BioClinicalBERT) to analyze the electronic health records (EHRs) in the MIMIC III dataset to predict the death of patients within six month and two year risk. DESIGN: A cohort and system development design was used. SETTING(S): Based on data extracted from MIMIC-III, a database of critically ill in the US between 2001 and 2012, the results were analyzed. PARTICIPANTS: We calculated patients' age using admission time and date of birth information from the MIMIC dataset. Patients under 18 or over 89 years old, or who died in the hospital, were excluded. We analyzed 16,973 nursing records from patients' ICU stays. METHODS: We have developed a technology called the Crucial Nursing Description Extractor (CNDE), which extracts key content from text. We use the logarithmic likelihood ratio to extract keywords and combine BioClinicalBERT. We predict the survival of discharged patients after six months and two years and evaluate the performance of the model using precision, recall, the F1-score, the receiver operating characteristic curve (ROC curve), the area under the curve (AUC), and the precision-recall curve (PR curve). RESULTS: The research findings indicate that NurnaNet achieved good F1-scores (0.67030, 0.70874) within six months and two years. Compared to using BioClinicalBERT alone, there was an improvement in performance of 2.05 % and 1.08 % for predictions within six months and two years, respectively. CONCLUSIONS: CNDE can effectively reduce long-form records and extract key content. NurnaNet has a good F1-score in analyzing the data of nursing records, which helps to identify the risk of death of patients after leaving the hospital and adjust the regular follow-up and treatment plan of relevant medical care as soon as possible.

Dual-modal radiomics nomogram based on contrast-enhanced ultrasound to improve differential diagnostic accuracy and reduce unnecessary biopsy rate in ACR TI-RADS 4-5 thyroid nodules.

BACKGROUND: American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-RADS, TR) 4 and 5 thyroid nodules (TNs) demonstrate much more complicated and overlapping risk characteristics than TR1-3 and have a rather wide range of malignancy possibilities (> 5%), which may cause overdiagnosis or misdiagnosis. This study was designed to establish and validate a dual-modal ultrasound (US) radiomics nomogram integrating B-mode ultrasound (BMUS) and contrast-enhanced ultrasound (CEUS) imaging to improve differential diagnostic accuracy and reduce unnecessary fine needle aspiration biopsy (FNAB) rates in TR 4-5 TNs. METHODS: A retrospective dataset of 312 pathologically confirmed TR4-5 TNs from 269 patients was collected for our study. Data were randomly divided into a training dataset of 219 TNs and a validation dataset of 93 TNs. Radiomics characteristics were derived from the BMUS and CEUS images. After feature reduction, the BMUS and CEUS radiomics scores (Rad-score) were built. A multivariate logistic regression analysis was conducted incorporating both Rad-scores and clinical/US data, and a radiomics nomogram was subsequently developed. The performance of the radiomics nomogram was evaluated using calibration, discrimination, and clinical usefulness, and the unnecessary FNAB rate was also calculated. RESULTS: BMUS Rad-score, CEUS Rad-score, age, shape, margin, and enhancement direction were significant independent predictors associated with malignant TR4-5 TNs. The radiomics nomogram involving the six variables exhibited excellent calibration and discrimination in the training and validation cohorts, with an AUC of 0.873 (95% CI, 0.821-0.925) and 0.851 (95% CI, 0.764-0.938), respectively. The marked improvements in the net reclassification index and integrated discriminatory improvement suggested that the BMUS and CEUS Rad-scores could be valuable indicators for distinguishing benign from malignant TR4-5 TNs. Decision curve analysis demonstrated that our developed radiomics nomogram was an instrumental tool for clinical decision-making. Using the radiomics nomogram, the unnecessary FNAB rate decreased from 35.3 to 14.5% in the training cohort and from 41.5 to 17.7% in the validation cohorts compared with ACR TI-RADS. CONCLUSION: The dual-modal US radiomics nomogram revealed superior discrimination accuracy and considerably decreased unnecessary FNAB rates in benign and malignant TR4-5 TNs. It could guide further examination or treatment options.