Dual adaptive training of photonic neural networks

Photonic neural network (PNN) is a remarkable analog artificial intelligence (AI) accelerator that computes with photons instead of electrons to feature low latency, high energy efficiency, and high parallelism. However, the existing training approaches cannot address the extensive accumulation of systematic errors in large-scale PNNs, resulting in a significant decrease in model performance in physical systems. Here, we propose dual adaptive training (DAT) that allows the PNN model to adapt to substantial systematic errors and preserves its performance during the deployment. By introducing the systematic error prediction networks with task-similarity joint optimization, DAT achieves the high similarity mapping between the PNN numerical models and physical systems and high-accurate gradient calculations during the dual backpropagation training. We validated the effectiveness of DAT by using diffractive PNNs and interference-based PNNs on image classification tasks. DAT successfully trained large-scale PNNs under major systematic errors and preserved the model classification accuracies comparable to error-free systems. The results further demonstrated its superior performance over the state-of-the-art in situ training approaches. DAT provides critical support for constructing large-scale PNNs to achieve advanced architectures and can be generalized to other types of AI systems with analog computing errors.Comment: 31 pages, 11 figure

Air Stable Organic Salt As an n‑Type Dopant for Efficient and Stable Organic Light-Emitting Diodes

Air-stable and low-temperature-evaporable n-type dopants are highly desired for efficient and stable organic light-emitting diodes (OLEDs). In this work, 2-(2-Methoxyphenyl)-1,3-dimethyl-1H-benzoimidazol-3-ium iodide (<i>o</i>-MeO-DMBI-I), a thermally decomposable precursor of organic radical <i>o</i>-MeO-DMBI, has been employed as a novel n-type dopant in OLEDs, because of its air stability, low decomposition temperature, and lack of atom diffusion. The n-type electrical doping is evidenced by the rapid increase in current density of electron-only devices and the large improvement in conductivity, originated from increased electron concentration in electron-transport layer (ETL) and reduced electron injection barrier. A highly efficient and stable OLED is created using <i>o</i>-MeO-DMBI as an n-type dopant in Bphen. Compared with the control device with its high-temperature-evaporable n-type dopant cesium carbonate (Cs₂CO₃), <i>o</i>-MeO-DMBI-doped device showed an incredible boom in current efficiency from 28.6 to 42.2 cd/A. Moreover, the lifetime (<i>T</i>_70%) of <i>o</i>-MeO-DMBI-doped device is 45 h, more than 20 times longer than that of the Cs₂CO₃-doped device (2 h). The enhanced efficiency and stability are attributed to the improved balance of holes and electrons in the emissive layer, and the eliminated atom diffusion of cesium

Multi-omics characterization of a scoring system to quantify hypoxia patterns in patients with head and neck squamous cell carcinoma

Abstract Background The 5-year survival rate of patients with head and neck squamous cell carcinoma (HNSCC) remains  < 50%. Hypoxia patterns are a hallmark of HNSCC that are associated with its occurrence and progression. However, the precise role of hypoxia during HNSCC, such as the relationship between hypoxia, tumor immune landscape and cell communication orchestration remains largely unknown. The current study integrated data from bulk and single-cell RNA sequencing analyses to define the relationship between hypoxia and HNSCC. Methods A scoring system named the hypoxia score (HS) was constructed based on hypoxia-related genes (HRGs) expression. The predictive value of HS response for patient outcomes and different treatments was evaluated. Single-cell datasets and cell communication were utilized to rule out cell populations which hypoxia targeted on. Results The survival outcomes, immune/Estimate scores, responses to targeted inhibitors, and chemotherapeutic, and immunotherapy responses were distinct between a high HS group and a low HS group (all P < 0.05). Single-cell datasets showed different distributions of HS in immune cell populations (P < 0.05). Furthermore, HLA-DPA1/CD4 axis was identified as a unique interaction between CD4 + T Conv and pDC cells. Conclusions Altogether, the quantification for hypoxia patterns is a potential biomarker for prognosis, individualized chemotherapeutic and immunotherapy strategies. The portrait of cell communication characteristics over the HNSCC ecosystem enhances the understanding of hypoxia patterns in HNSCC

Survey on the scheme evaluation, opportunities and challenges of software defined‐information centric network

Abstract As a promising architecture of next‐generation network, software defined‐information centric network (SD‐ICN) inherits the advantages of software defined network (SDN) and information‐centric network (ICN) to enable flexible and fast content retrieval, especially in the current era of artificial intelligence. However, the existing researches mainly focus on a single respective in this field, which motivates in comprehensively providing a forward‐looking guidance and development direction for scholars and engineers. To this end, the latest developments of SD‐ICN is presented. First, the widely‐accepted concepts and impacts on traditional networks are introduced. Second, the shortcomings of SDN and ICN over conventional networks are respectively analyzed to illustrate the necessity of SD‐ICN. Third, based on extensive analysis and deep deliberation, a methodical taxonomy for existing combination studies is proposed. They are divided into SDN over ICN, ICN over SDN, and mutual immersive pattern. Fourth, the performances of three integration categories are compared and the limitations of related works are highlighted. Fifth, the maturity index from six development indicators are evaluated. Further, the maturity and practicality of these schemes are generalized. Based on the above studies and comparisons, the lessons learned by SDN and ICN developments are concluded. Finally, future research directions and opportunities are discussed for the readers

Processing Optimization of Typed Resources with Synchronized Storage and Computation Adaptation in Fog Computing

Wide application of the Internet of Things (IoT) system has been increasingly demanding more hardware facilities for processing various resources including data, information, and knowledge. With the rapid growth of generated resource quantity, it is difficult to adapt to this situation by using traditional cloud computing models. Fog computing enables storage and computing services to perform at the edge of the network to extend cloud computing. However, there are some problems such as restricted computation, limited storage, and expensive network bandwidth in Fog computing applications. It is a challenge to balance the distribution of network resources. We propose a processing optimization mechanism of typed resources with synchronized storage and computation adaptation in Fog computing. In this mechanism, we process typed resources in a wireless-network-based three-tier architecture consisting of Data Graph, Information Graph, and Knowledge Graph. The proposed mechanism aims to minimize processing cost over network, computation, and storage while maximizing the performance of processing in a business value driven manner. Simulation results show that the proposed approach improves the ratio of performance over user investment. Meanwhile, conversions between resource types deliver support for dynamically allocating network resources

Simultaneous Enhancement of Efficiency and Stability of Phosphorescent OLEDs Based on Efficient Förster Energy Transfer from Interface Exciplex

Exciplex forming cohosts have been widely adopted in phosphorescent organic light-emitting diodes (PHOLEDs), achieving high efficiency with low roll-off and low driving voltage. However, the influence of the exciplex-forming hosts on the lifetimes of the devices, which is one of the essential characteristics, remains unclear. Here, we compare the influence of the bulk exciplex and interface exciplex on the performances of the devices, demonstrating highly efficient orange PHOLEDs with long lifetime at low dopant concentration by efficient Förster energy transfer from the interface exciplex. A bipolar host, (3′-(4,6-diphenyl-1,3,5-triazin-2-yl)-(1,1′-biphenyl)-3-yl)-9-carbazole (CzTrz), was adopted to combine with a donor molecule, tris­(4-(9H-carbazol-9-yl)­phenyl)­amine (TCTA), to form exciplex. Devices with energy transfer from the interface exciplex achieve lifetime almost 2 orders of magnitude higher than the ones based on bulk exciplex as the host by avoiding the formation of the donor excited states. Moreover, a highest EQE of 27% was obtained at the dopant concentration as low as 3 wt % for a device with interface exciplex, which is favorable for reducing the cost of fabrication. We believe that our work may shed light on future development of ideal OLEDs with high efficiency, long-lifetime, low roll-off and low cost simultaneously