Modulation format recognition in a UVLC system based on an ultra-lightweight model with communication-informed knowledge distillation.

Modulation format recognition (MFR) is a key technology for adaptive optical systems, but it faces significant challenges in underwater visible light communication (UVLC) due to the complex channel environment. Recent advances in deep learning have enabled remarkable achievements in image recognition, owing to the powerful feature extraction of neural networks (NN). However, the high computational complexity of NN limits their practicality in UVLC systems. This paper proposes a communication-informed knowledge distillation (CIKD) method that achieves high-precision and low-latency MFR with an ultra-lightweight student model. The student model consists of only one linear dense layer under a communication-informed auxiliary system and is trained under the guidance of a high-complexity and high-precision teacher model. The MFR task involves eight modulation formats: PAM4, QPSK, 8QAM-CIR, 8QAM-DIA, 16QAM, 16APSK, 32QAM, and 32APSK. Experimental results show that the student model based on CIKD can achieve comparable accuracy to the teacher model. After knowledge transfer, the prediction accuracy of the student model can be increased by up to 87%. Besides, it is worth noting that CIKD's inference accuracy can reach up to 100%. Moreover, the parameters constituting the student model in CIKD correspond to merely 18% of the parameters found in the teacher model, which facilitates the hardware deployment and online data processing of MFR algorithms in UVLC systems.

First-year outcomes of very low birth weight preterm singleton infants with hypoxemic respiratory failure treated with milrinone and inhaled nitric oxide (iNO) compared to iNO alone: A nationwide retrospective study.

BACKGROUND: Inhaled nitric oxide (iNO) has a beneficial effect on hypoxemic respiratory failure. The increased use of concurrent iNO and milrinone was observed. We aimed to report the trends of iNO use in the past 15 years in Taiwan and compare the first-year outcomes of combining iNO and milrinone to the iNO alone in very low birth weight preterm (VLBWP) infants under mechanical ventilation. METHODS: This nationwide cohort study enrolled preterm singleton infants with birth weight <1500g treated with iNO from 2004 to 2019. Infants were divided into two groups, with a combination of intravenous milrinone (Group 2, n = 166) and without milrinone (Group 1, n = 591). After propensity score matching (PSM), each group's sample size is 124. The primary outcomes were all-cause mortality and the respiratory condition, including ventilator use and duration. The secondary outcomes were preterm morbidities within one year after birth. RESULTS: After PSM, more infants in Group 2 needed inotropes. The mortality rate was significantly higher in Group 2 than in Group 1 from one month after birth till 1 year of age (55.1% vs. 13.5%) with the adjusted hazard ratio of 4.25 (95%CI = 2.42-7.47, p <0.001). For infants who died before 36 weeks of postmenstrual age (PMA), Group 2 had longer hospital stays compared to Group 1. For infants who survived after 36 weeks PMA, the incidence of moderate and severe bronchopulmonary dysplasia (BPD) was significantly higher in Group 2 than in Group 1. For infants who survived until one year of age, the incidence of pneumonia was significantly higher in Group 2 (28.30%) compared to Group 1 (12.62%) (p = 0.0153). CONCLUSION: Combined treatment of iNO and milrinone is increasingly applied in VLBWP infants in Taiwan. This retrospective study did not support the benefits of combining iNO and milrinone on one-year survival and BPD prevention. A future prospective study is warranted.

Study of equivalent circuit of GaN based laser chip and packaged laser.

High-speed GaN-based lasers play a pivotal role in visible light communication (VLC) systems; however, the causes of the limited modulation response of our fabricated laser diode (LD) are not fully understood. Accordingly, we constructed an equivalent circuit model for both the LD and its packaging. This model enabled us to analyze the series resistance and parallel capacitance of the LD at different injection currents. Experiments and simulations were performed to investigate the intrinsic responses of the LD. The series resistance and parallel capacitance are responsible for S21 roll-off at low frequencies. Determination of the packaging design parameters on the modulation response of a transistor outline (TO)-can packaged LD was investigated which is important to achieve the impedance match in the future. The value of each discrete component was determined by fitting the scattering parameters of the equivalent circuit model to the packaged LD. Reducing the series resistance and parallel capacitance improved the modulation response. Our study firstly illustrates the design and manufacture of violet-blue-green laser transmitters with a large modulation bandwidth for ultra-high-speed VLC from the point of the impedance influence.

Wide field-of-view laser-based white light transmitter for visible light communications.

The advancement demands of high-speed wireless data link ask for higher requirements on visible light communication (VLC), where wide coverage stands as a critical criterion. Here, we present the design and implementation of a transmitter structure capable of emitting a high-power wide-coverage white light laser. This laser source exhibits excellent stability, with an irradiation range extending to a half-angle of 20°. Its high brightness satisfies the needs of indoor illumination while maintaining excellent communication performance. Utilizing bit-loading discrete multi-tone modulation, a peak data transmission rate of 3.24 Gbps has been achieved, spanning 1 to 5 m. Remarkably, the data rates exceed 2.5 Gbps within a 40° range at a distance of 5 m, enabling a long-distance, wide coverage, high-speed VLC link for future mobile network applications.

Laser-Based Mobile Visible Light Communication System.

Mobile visible light communication (VLC) is key for integrating lighting and communication applications in the 6G era, yet there exists a notable gap in experimental research on mobile VLC. In this study, we introduce a mobile VLC system and investigate the impact of mobility speed on communication performance. Leveraging a laser-based light transmitter with a wide coverage, we enable a light fidelity (LiFi) system with a mobile receiving end. The system is capable of supporting distances from 1 m to 4 m without a lens and could maintain a transmission rate of 500 Mbps. The transmission is stable at distances of 1 m and 2 m, but an increase in distance and speed introduces interference to the system, leading to a rise in the Bit Error Rate (BER). The mobile VLC experimental system provides a viable solution to the issue of mobile access in the integration of lighting and communication applications, establishing a solid practical foundation for future research.

Representativeness of the PIONEER-HF and PARAGLIDE-HF in patients hospitalized with acute heart failure.

AIMS: The PIONEER-HF and PARAGLIDE-HF trials aimed to determine the efficacy and safety of the in-hospital initiation of sacubitril/valsartan in patients hospitalized for AHF. However, whether the inclusion and exclusion criteria of the trials apply to patients encountered in real-world routine care is unclear. This study aimed to investigate the applicability of the PIONEER-HF and PARAGLIDE-HF trials to real-world AHF patients. METHODS AND RESULTS: We identified 28 293 AHF hospitalized patients between August 2008 to August 2017 from the Chang Gung Research Database and classified them into four groups based on left ventricular ejection fraction (LVEF) and trial criteria. Cox proportional hazards models were used to compare the risk of HF hospitalization and cardiovascular (CV) death. We defined PIONEER-HF eligible (n = 3683) and non-eligible (n = 3502) patients with an LVEF ≤40%, and PARAGLIDE-HF eligible (n = 5191) and non-eligible (n = 5832) patients with an LVEF >40%. Over a mean follow-up of 3.5 years, the PIONEER-HF non-eligible and eligible groups exhibited similar rates of HF hospitalization and CV death (41.1% vs. 41.8%, adjusted hazard ratio [aHR]: 0.95; 95% CI: 0.88-1.04). No significant difference was found in the composite outcome between PARAGLIDE-HF non-eligible and eligible groups (36.7% vs. 38.6%; aHR: 0.97; 95% CI: 0.90-1.04). CONCLUSIONS: Using trial criteria, only 31.3% of AHF patients were eligible for sacubitril-valsartan. Yet, non-eligible patients demonstrated similar outcomes to eligible patients, indicating a need for further evaluation of sacubitril-valsartan benefits in non-eligible AHF patients.

Net-432-Gb/s/λ PS-PAM transmission based on advanced DSP and single DAC for 400†G/λ IM/DD links.

The escalating surge in datacenter traffic creates a pressing demand for augmenting the capacity of cost-effective intensity modulation and direct detection (IM/DD) systems. In this Letter, we report the demonstration of the single-lane 128-GBaud probabilistically shaped (PS)-PAM-20 IM/DD transmission using only a single digital-to-analog converter (DAC) for a net 400 G/λ system. Based on the advanced digital signal processing (DSP), we achieve net bitrates of up to 437 Gb/s for optical back-to-back and 432 Gb/s after the 0.5-km SSMF transmission in the C-band with 128-Gbaud PS-PAM-20 signals. This work is the latest demonstration on ultra-high-order PS-PAM signals achieving net bitrates exceeding 400 Gb/s despite symbol rate limitations. Notably, to the best of our knowledge, the realized net information rate ([net bitrate]/[symbol rate]) of 3.37 marks a new achievement within the domain of 400 G/λ IM/DD systems, with promising implications for enhancing bandwidth efficiency in the upcoming 1.6-Tb Ethernet scenario.

Analysis of outcomes and prognostic factor in acute type A aortic dissection complicated with preoperative shock: A single-center study.

BACKGROUND: Acute type A aortic dissection (ATAAD) is a critical cardiovascular emergency that requires prompt surgical intervention for preserving life, particularly in patients with critical preoperative status. This retrospective study aimed to investigate the clinical features, early and late outcomes, and prognostic factors in patients undergoing aortic repair surgery for ATAAD complicated with preoperative shock. METHODS: Between April 2007 and July 2020, 694 consecutive patients underwent emergency ATAAD repair at our institution, including 162 (23.3%) presenting with preoperative shock (systolic blood pressure <90 mm Hg), who were classified into the survivor (n = 125) and non-survivor (n = 37) groups according to whether they survived to hospital discharge. The clinical demographics, surgical information, and postoperative complications were compared. Five-year survival and freedom from reoperation rates of survivors were analyzed using the Kaplan-Meier actuarial method. Multivariate logistic regression analysis was used to identify independent risk factors for in-hospital mortality. RESULTS: The in-hospital surgical mortality rate in patients with ATAAD and shock was 22.8%. The non-survivor group showed higher rates of preoperative cardiopulmonary resuscitation, acute myocardial infarction, and cerebral infarction, and was associated with longer cardiopulmonary bypass time, higher rates of total arch replacement and intraoperative extracorporeal membrane oxygenation implementation. The non-survivor group had higher blood transfusion volumes and rates of malperfusion-related complications. Multivariate analysis revealed that preoperative cardiopulmonary resuscitation, prolonged cardiopulmonary bypass time, and total arch replacement were risk factors for in-hospital mortality. For patients who survived to discharge, the 5-year cumulative survival and freedom from aortic reoperation rates were 75.6% (95% confidence interval, 67.6%-83.6%) and 82.6% (95% confidence interval, 74.2%-91.1%), respectively. CONCLUSIONS: Preoperative shock in ATAAD is associated with a high risk of in-hospital mortality, particularly in patients who undergo cardiopulmonary resuscitation and complex aortic repair procedures with extended cardiopulmonary bypass. However, late outcomes are acceptable for patients who were stabilized through surgical treatment and survived to discharge.

A metasurface-based full-color circular auto-focusing Airy beam transmitter for stable high-speed underwater wireless optical communications.

Due to its unique intensity distribution, self-acceleration, and beam self-healing properties, Airy beam holds great potential for optical wireless communications in challenging channels, such as underwater environments. As a vital part of 6G wireless network, the Internet of Underwater Things requires high-stability, low-latency, and high-capacity underwater wireless optical communication (UWOC). Currently, the primary challenge of UWOC lies in the prevalent time-varying and complex channel characteristics. Conventional blue Gaussian beam-based systems face difficulties in underwater randomly perturbed links. In this work, we report a full-color circular auto-focusing Airy beams metasurface transmitter for reliable, large-capacity and long-distance UWOC links. The metasurface is designed to exhibits high polarization conversion efficiency over a wide band (440-640 nm), enabling an increased data transmission rate of 91% and reliable 4 K video transmission in wavelength division multiplexing (WDM) based UWOC data link. The successful application of this metasurface in challenging UWOC links establishes a foundation for underwater interconnection scenarios in 6G communication.

Neural-network-based carrier-less amplitude phase modulated signal generation and end-to-end optimization for fiber-terahertz integrated communication system.

In fiber-terahertz integrated communication systems, nonlinear distortion and inter-symbol interference (ISI) will degrade transmission performance. Pre-compensation is an efficient method to handle the channel distortion as it can avoid noise boosting during channel compensation and reduce receiver side signal processing algorithmic complexity at user-end (UE) considering the asymmetric access scenario. In this paper, we propose and experimentally demonstrate a neural-network (NN)-based carrier-less amplitude phase (CAP) modulated signal generation and end-to-end optimization method for a fiber-terahertz integrated communication system. The CAP signal is generated directly from quadrature amplitude modulation symbols and pre-compensated through a transmitter NN, which allows the receiver to demodulate the signal with simple linear digital signal process (DSP). In generating the CAP signal, the NN based transmitter learns a group of filters, which can generate, up-convert, and pre-compensate the signals. Based on the proposed method, a fiber-terahertz integration access system at 220 GHz is demonstrated and a sensitivity gain of 1.2 dB is achieved at a transmission speed of 50 Gbps and the forward error correction (FEC) bit error rate (BER) threshold of 1 × 10-2 compared with the baseline after 10-km fiber transmission and 1-m wireless delivering.

Multi-Gb/s visible light communication based on AlGaInP amber micro-LED.

Light-emitting diodes (LEDs), pivotal for solid-state illumination (SSL) and highly regarded as potential candidates in visible light communication (VLC) systems, have garnered significant interest as a solution to alleviate the congested radio frequency spectrum in next-generation communications. Addressing the challenge of extremely limited bandwidth due to the low response of phosphor in conventional illumination, our research focuses on an AlGaInP-based amber LED. This LED represents a promising avenue for phosphor-free, high-speed VLC applications when used in conjunction with the prevalent blue LED technology based on nitride materials. The fabricated AlGaInP amber LED, with a mesa diameter of 100 µm2, has undergone comprehensive optoelectronic property and transmission performance characterization. We have successfully demonstrated a proof-of-concept for VLC using the amber LED, achieving a data transmission rate of 2.94 Gb/s that complies with the forward-error-correction (FEC) standard of 3.8 × 10-3, utilizing adaptive bit and power loading with discrete multitone (BPL-DMT) modulation.

Neural-network-based end-to-end learning for adaptive optimization of two-dimensional signal generation in UVLC systems.

Visible light communication (VLC) benefits from the underwater blue-green window and holds immense potential for underwater wireless communication. In order to address the limitations of various equipment and harsh channel conditions in the underwater visible light communication (UVLC) system, the researchers proposed to use the method of autoencoder (AE) to tap the potential of the system. However, traditional AE schemes involve replacing the transmitting and receiving components of a communication system with a large multilayer perceptron (MLP) network, and they have significant drawbacks due to their reliance on a single network structure. In this paper, a novel 2D adaptive optimization autoencoder (2D-AOAE) framework is proposed to realize adaptive modulation and demodulation of two-dimensional signals. By implementing this scheme, we experimentally achieved a transmission rate of 2.85 Gbps over a 1.2-meter underwater VLC link. Compared to the traditional 32QAM UVLC system, the 2D-AOAE scheme demonstrated a 15.4% data rate increase. Moreover, the 2D-AOAE scheme exhibited a remarkable 73% improvement when compared to the UVLC system utilizing the traditional AE scheme. This significant enhancement highlights the superior performance and capabilities of the 2D-AOAE scheme in terms of transmission rate.

Minimalist Deployment of Neural Network Equalizers in a Bandwidth-Limited Optical Wireless Communication System with Knowledge Distillation.

An equalizer based on a recurrent neural network (RNN), especially with a bidirectional gated recurrent unit (biGRU) structure, is a good choice to deal with nonlinear damage and inter-symbol interference (ISI) in optical communication systems because of its excellent performance in processing time series information. However, its recursive structure prevents the parallelization of the computation, resulting in a low equalization rate. In order to improve the speed without compromising the equalization performance, we propose a minimalist 1D convolutional neural network (CNN) equalizer, which is reconverted from a biGRU with knowledge distillation (KD). In this work, we applied KD to regression problems and explain how KD helps students learn from teachers in solving regression problems. In addition, we compared the biGRU, 1D-CNN after KD and 1D-CNN without KD in terms of Q-factor and equalization velocity. The experimental data showed that the Q-factor of the 1D-CNN increased by 1 dB after KD learning from the biGRU, and KD increased the RoP sensitivity of the 1D-CNN by 0.89 dB with the HD-FEC threshold of 1 × 10-3. At the same time, compared with the biGRU, the proposed 1D-CNN equalizer reduced the computational time consumption by 97% and the number of trainable parameters by 99.3%, with only a 0.5 dB Q-factor penalty. The results demonstrate that the proposed minimalist 1D-CNN equalizer holds significant promise for future practical deployments in optical wireless communication systems.

Acute type a aortic intramural hematoma complicated with preoperative hemopericardium: early and late surgical outcome analyses.

BACKGROUND: Acute type A aortic intramural hematoma (ATAIMH) is a variant of acute type A aortic dissection (ATAAD), exhibiting an increased risk of hemopericardium and cardiac tamponade. It can be life-threatening without emergency treatment. However, comprehensive studies of the clinical features and surgical outcomes of preoperative hemopericardium in patients with ATAIMH remain scarce. This retrospective study aims to investigate the clinical features and early and late outcomes of patients who underwent aortic repair surgery for ATAIMH complicated with preoperative hemopericardium. METHODS: We investigated 132 consecutive patients who underwent emergency ATAIMH repair at this institution between February 2007 and August 2020. These patients were dichotomized into the hemopericardium (n = 58; 43.9%) and non-hemopericardium groups (n = 74; 56.1%). We compared the clinical demographics, surgical information, postoperative complications, 5-year cumulative survival rates, and freedom from reoperation rates. Furthermore, multivariable logistic regression analysis was utilized to identify independent risk factors for patients who underwent re-exploration for bleeding. RESULTS: In the hemopericardium group, 36.2% of patients presented with cardiac tamponade before surgery. Moreover, the hemopericardium group showed higher rates of preoperative shock and endotracheal intubation and was associated with an elevated incidence of intractable perioperative bleeding, necessitating delayed sternal closure for hemostasis. The hemopericardium group exhibited higher blood transfusion volumes and rates of re-exploration for bleeding following surgery. However, the 5-year survival (59.5% vs. 75.0%; P = 0.077) and freedom from reoperation rates (93.3% vs. 85.5%; P = 0.416) were comparable between both groups. Multivariable analysis revealed that hemopericardium, cardiopulmonary bypass time, and delayed sternal closure were the risk factors for bleeding re-exploration. CONCLUSIONS: The presence of hemopericardium in patients with ATAIMH is associated with an elevated incidence of cardiac tamponade and unstable preoperative hemodynamics, which could lead to perioperative bleeding tendencies and high complication rates. However, patients of ATAIMH complicated with hemopericardium undergoing aggressive surgical intervention exhibited long-term surgical outcomes comparable to those without hemopericardium.

Self-supervised dynamic learning for long-term high-fidelity image transmission through unstabilized diffusive media.

Multimode fiber (MMF) which supports parallel transmission of spatially distributed information is a promising platform for remote imaging and capacity-enhanced optical communication. However, the variability of the scattering MMF channel poses a challenge for achieving long-term accurate transmission over long distances, of which static optical propagation modeling with calibrated transmission matrix or data-driven learning will inevitably degenerate. In this paper, we present a self-supervised dynamic learning approach that achieves long-term, high-fidelity transmission of arbitrary optical fields through unstabilized MMFs. Multiple networks carrying both long- and short-term memory of the propagation model variations are adaptively updated and ensembled to achieve robust image recovery. We demonstrate >99.9% accuracy in the transmission of 1024 spatial degree-of-freedom over 1 km length MMFs lasting over 1000 seconds. The long-term high-fidelity capability enables compressive encoded transfer of high-resolution video with orders of throughput enhancement, offering insights for artificial intelligence promoted diffusive spatial transmission in practical applications.

Feature decoupled knowledge distillation enabled lightweight image transmission through multimode fibers.

Multimode fibers (MMF) show tremendous potential in transmitting high-capacity spatial information. However, the quality of multimode transmission is quite sensitive to inherent scattering characteristics of MMF and almost inevitable external perturbations. Previous research has shown that deep learning may break through this limitation, while deep neural networks are intricately designed with huge computational complexity. In this study, we propose a novel feature decoupled knowledge distillation (KD) framework for lightweight image transmission through MMF. In this framework, the frequency-principle-inspired feature decoupled module significantly improves image transmission quality and the lightweight student model can reach the performance of the sophisticated teacher model through KD. This work represents the first effort, to the best of our knowledge, that successfully applies a KD-based framework for image transmission through scattering media. Experimental results demonstrate that even with up to 93.4% reduction in model computational complexity, we can still achieve averaged Structure Similarity Index Measure (SSIM) of 0.76, 0.85, and 0.90 in Fashion-MNIST, EMNIST, and MNIST images respectively, which are very close to the performance of cumbersome teacher models. This work dramatically reduces the complexity of high-fidelity image transmission through MMF and holds broad prospects for applications in resource-constrained environments and hardware implementations.

113Gbps rainbow visible light laser communication system based on 10λ laser WDM emitting module in fiber-free space-fiber link.

With the advent of the sixth-generation mobile communication standard (6 G), the visible light communication (VLC) technology based on wavelength division multiplexing (WDM) technology can effectively solve the problem of shortage of spectrum resources and insufficient channel capacity. This paper introduces one of our technical achievements, namely the construction of a near-real-time visible light laser communication (VLLC) system based on WDM, which includes a self-designed 10-λ fully-packaged visible light laser emission module, 1 m multimode fiber - 0.175 m free space - 1 m multimode fiber optical transmission link, and receiver array. In the transmitter system, we adopt adaptive discrete multitone (DMT) modulation technique combined with Quadrature Amplitude Modulation (QAM) modulation scheme to obtain maximum spectral efficiency (SE). In the receiving system, we utilize the sparse-structured reservoir computing post-equalization algorithm to achieve superior equalization performance on the basis of the traditional post-equalization algorithm. The experimental results indicate that this quasi-real-time communication system has achieved a signal transmission rate of 113.175Gbps. To the best of our knowledge, this work has set a record in the field of high-speed visible light laser communication. Therefore, the laser communication system constructed by this work, with its flexibility in deployment and high-speed performance, demonstrates the significant potential application of visible light laser communication in data center interconnection and high-speed indoor access networks.

A versatile Wavelet-Enhanced CNN-Transformer for improved fluorescence microscopy image restoration.

Fluorescence microscopes are indispensable tools for the life science research community. Nevertheless, the presence of optical component limitations, coupled with the maximum photon budget that the specimen can tolerate, inevitably leads to a decline in imaging quality and a lack of useful signals. Therefore, image restoration becomes essential for ensuring high-quality and accurate analyses. This paper presents the Wavelet-Enhanced Convolutional-Transformer (WECT), a novel deep learning technique developed specifically for the purpose of reducing noise in microscopy images and attaining super-resolution. Unlike traditional approaches, WECT integrates wavelet transform and inverse-transform for multi-resolution image decomposition and reconstruction, resulting in an expanded receptive field for the network without compromising information integrity. Subsequently, multiple consecutive parallel CNN-Transformer modules are utilized to collaboratively model local and global dependencies, thus facilitating the extraction of more comprehensive and diversified deep features. In addition, the incorporation of generative adversarial networks (GANs) into WECT enhances its capacity to generate high perceptual quality microscopic images. Extensive experiments have demonstrated that the WECT framework outperforms current state-of-the-art restoration methods on real fluorescence microscopy data under various imaging modalities and conditions, in terms of quantitative and qualitative analysis.

Spatial pilot-aided fast-adapted framework for stable image transmission over long multi-mode fiber.

Multi-mode fiber (MMF) has emerged as a promising platform for spatial information transmission attributed to its high capacity. However, the scattering characteristic and time-varying nature of MMF pose challenges for long-term stable transmission. In this study, we propose a spatial pilot-aided learning framework for MMF image transmission, which effectively addresses these challenges and maintains accurate performance in practical applications. By inserting a few reference image frames into the transmitting image sequence and leveraging a fast-adapt network training scheme, our framework adaptively accommodates to the physical channel variations and enables online model update for continuous transmission. Experimented on 100 m length unstable MMFs, we demonstrate transmission accuracy exceeding 92% over hours, with pilot frame overhead around 2%. Our fast-adapt learning scheme requires training of less than 2% of network parameters and reduces the computation time by 70% compared to conventional tuning approaches. Additionally, we propose two pilot-insertion strategies and elaborately compare their applicability to a wide range of scenarios including continuous transmission, burst transmission and transmission after fiber re-plugging. The proposed spatial pilot-aided fast-adapt framework opens up the possibility for MMF spatial transmission in practical complicated applications.