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While neural networks (NNs) have achieved great results in various intelligent tasks like image classification and speech recognition, real-world scenarios have more applications beyond just NN processing like graph convolutional network (GCN) and deep-learning recommendation model (DLRM), which typically consist of sparse gathering (SpG) and sparse algebra (SpA). Their large application size leads to substantial data movement. Although the fusion of digital computing-in-memory (CIM) and multichip-module (MCM) can reduce data movement efficiently and scale out CIM's capacity in a high-yield solution, the MCM-CIM system raises new challenges for beyond-NN acceleration: SpG involves repeated off-chip DRAM access, interchiplet access, and redundant reduction operations; SpA suffers from inter-CIM workload imbalance and intra-CIM under-utilization. Thus, we design TensorCIM as the CIM processor chiplet with three corresponding features: 1) the redundancy-eliminated gathering manager (REGM) dynamically maintains frequently accessed features and reduction results in the CIM to eliminate redundant accesses and reductions; 2) the equal operation-based CIM initializer (EOCI) calculates effective multiply-accumulation (MAC) operations and initializes CIM macros with a balanced inter-CIM workload at the subarray level; and 3) the input-lookahead CIM (ILA-CIM) architecture looks ahead at future inputs to fully utilize CIM logic. The fabricated MCM-CIM system consumes only 3.7 nJ/Gather for the GCN model, achieving 8.3-TFLOPS/W algebra efficiency at FP32.

Indoor photovoltaics (IPVs) are garnering increasing attention from both the academic and industrial communities due to the pressing demand of the ecosystem of Internet-of-Things. All-polymer solar cells (all-PSCs), emerging as a sub-type of organic photovoltaics, with the merits of great film-forming properties, remarkable morphological and light stability, hold great promise to simultaneously achieve high efficiency and long-term operation in IPV's application. However, the dearth of polymer acceptors with medium-bandgap has impeded the rapid development of indoor all-PSCs. Herein, a highly efficient medium-bandgap polymer acceptor (PYFO-V) is reported through the synergistic effects of side chain engineering and linkage modulation and applied for indoor all-PSCs operation. As a result, the PM6:PYFO-V-based indoor all-PSC yields the highest efficiency of 27.1% under LED light condition, marking the highest value for reported binary indoor all-PSCs to date. More importantly, the blade-coated devices using non-halogenated solvent (o-xylene) maintain an efficiency of over 23%, demonstrating the potential for industry-scale fabrication. This work not only highlights the importance of fine-tuning intramolecular charge transfer effect and intrachain coplanarity in developing high-performance medium-bandgap polymer acceptors but also provides a highly efficient strategy for indoor all-PSC application. © 2024 The Author(s). Advanced Materials published by Wiley-VCH GmbH.

With plenty of popular and effective ternary organic solar cells (OSCs) construction strategies proposed and applied, its power conversion efficiencies (PCEs) have come to a new level of over 19% in single-junction devices. However, previous studies are heavily based in chloroform (CF) leaving behind substantial knowledge deficiencies in understanding the influence of solvent choice when introducing a third component. Herein, we present a case where a newly designed asymmetric small molecular acceptor using fluoro-methoxylated end-group modification strategy, named BTP-BO-3FO with enlarged bandgap, brings different morphological evolution and performance improvement effect on host system PM6:BTP-eC9, processed by CF and ortho-xylene (o-XY). With detailed analyses supported by a series of experiments, the best PCE of 19.24% for green solvent-processed OSCs is found to be a fruit of finely tuned crystalline ordering and general aggregation motif, which furthermore nourishes a favorable charge generation and recombination behavior. Likewise, over 19% PCE can be achieved by replacing spin-coating with blade coating for active layer deposition. This work focuses on understanding the commonly met yet frequently ignored issues when building ternary blends to demonstrate cutting-edge device performance, hence, will be instructive to other ternary OSC works in the future.[Figure not available: see fulltext.] © 2023, The Author(s).

Yuan Li,1,2 Xianxu Yang,3 Jiejie Lu,1 Kai Chen,3 Weiwei Wu,3 Ming Zhang,3 Wanni Li1 1Department of Cosmetic Dermatology, The Fifth People’s Hospital of Hainan Province, Haikou, Hainan, People’s Republic of China; 2Department of Dermatology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, People’s Republic of China; 3Department of Dermatology, The Fifth People’s Hospital of Hainan Province, Haikou, Hainan, People’s Republic of ChinaCorrespondence: Wanni Li, Department of Cosmetic Dermatology, The Fifth People’s Hospital of Hainan Province, No. 8 Longhua Road, Longhua District, Haikou, 570100, Hainan, People’s Republic of China, Email liwanni1204@outlook.comAbstract: Eosinophilic pustular folliculitis (EPF) is a rare skin disease. The typical skin lesions of classic EPF are localized on the upper limbs’ face, trunk, and extensor surfaces. However, when the skin lesions initially appear on the palms and soles, it is not easy to diagnose as EPF. Here, we report a case of a male patient who presented with erythematous plaques, pustules, and crusted erosions on the hands and feet, which were misdiagnosed as eczema ten years ago. Over ten years, the patient experienced recurrent erythematous patches with bumps and itching on the face, trunk, and extremities after improving the hand and foot lesions. A histopathological biopsy was performed to establish a definitive diagnosis, revealing pustules formed by eosinophilic infiltrates within the hair follicles. The diagnosis was confirmed as eosinophilic pustular folliculitis. The patient was treated with oral indomethacin at a dosage of 75mg/day, resulting in the disappearance of the skin lesions. After a 3-month follow-up, no recurrence was observed.Keywords: eosinophilic pustular folliculitis, indomethacin

On-device training for deep neural networks (DNN) has become a trend due to various user preferences and scenarios. The DNN training process consists of three phases, feedforward (FF), backpropagation (BP), and weight gradient (WG) update. WG takes about one-third of the computation in the whole training process. Current training accelerators usually ignore the special computation property of WG and process it in a way similar to FF/BP. Besides, the extensive data sparsity existing in WG, which brings opportunities to save computation, is not well explored. Nevertheless, exploiting the optimization opportunities would meet three underutilization problems, which are caused by (1) the mismatch between WG data dimensions and hardware parallelism, (2) the full sparsity, i.e., the sparsity of feature map (Fmap), error map (Emap), and gradient, and (3) the workload imbalance resulting from irregular sparsity. In this paper, we propose a specific architecture for sparse weight gradient (SWG) computation. The architecture is designed based on hierarchical unrolling and sparsity-aware (HUSA) dataflow to exploit the optimization opportunities of the special computation property and full data sparsity. In HUSA dataflow, the data dimensions are unrolled hierarchically on the hardware architecture. A valid-data trace (VDT) mechanism is embedded in the dataflow to avoid the underutilization caused by the two-sided input sparsity. The gradient is unrolled in PE to alleviate the underutilization induced by output sparsity while maintaining the data reuse opportunities. Besides, we design an intra- and inter-column balancer (IIBLC) to dynamically tackle the workload imbalance problem resulting from the irregular sparsity. Experimental results show that with HUSA dataflow exploiting the full sparsity, SWG achieves a speedup of 12.23x over state-of-the-art gradient computation architecture, TrainWare. SWG helps to improve the energy efficiency of the state-of-the-art training accelera

Herein, two emerging device optimization methods, solid additive and layer-by-layer (LBL) process, for organic solar cells (OSCs) are simultaneously studied. Through traditional blend cast and recently proposed identical solvent LBL cast, BDCB (2-monobromo-1,3-dichloro-bezene), a benzene derivative, is used to improve the device performance based on celebrity combination PM6:L8-BO. The results reveal that finely optimized BDCB concentration in PM6 solution can push the efficiency of LBL to 19.03% compared to blend cast with only 18.12% while the power conversion efficiency (PCE) changing trend is determined by BDCB's ratio in L8-BO's precursor. The morphology characterizations confirm there exists no significant stratification for LBL-processed devices, supported by a previously reported swelling-intercalation-phase separation (SIPS) model. Thereby, the solid additive's 2D optimization is considered a smart strategy for finely tuning the SIPS process, which results in various final morphology states. This work not only reports a cutting-edge efficiency for binary OSCs, but also new insight and deep understanding for LBL method-based morphology optimization strategy development.

Ride-hailing platforms have been facing the challenge of balancing demand and supply. Existing vehicle reposition techniques often treat drivers as homogeneous agents and relocate them deterministically, assuming compliance with the reposition. In this paper, we consider a more realistic and driver-centric scenario where drivers have unique cruising preferences and can decide whether to take the recommendation or not on their own. We propose i-Rebalance, a personalized vehicle reposition technique with deep reinforcement learning (DRL). i-Rebalance estimates drivers' decisions on accepting reposition recommendations through an on-field user study involving 99 real drivers. To optimize supply-demand balance and enhance preference satisfaction simultaneously, i-Rebalance has a sequential reposition strategy with dual DRL agents: Grid Agent to determine the reposition order of idle vehicles, and Vehicle Agent to provide personalized recommendations to each vehicle in the pre-defined order. This sequential learning strategy facilitates more effective policy training within a smaller action space compared to traditional joint-action methods. Evaluation of real-world trajectory data shows that i-Rebalance improves driver acceptance rate by 38.07% and total driver income by 9.97%.

Multimodal Transformers are emerging artificial intelligence (AI) models that comprehend a mixture of signals from different modalities like vision, natural language, and speech. The attention mechanism and massive matrix multiplications (MMs) cause high latency and energy. Prior work has shown that a digital computing-in-memory (CIM) network can be an efficient architecture to process Transformers while maintaining high accuracy. To further improve energy efficiency, attention-token-bit hybrid sparsity in multimodal Transformers can be exploited. The hybrid sparsity significantly reduces computation, but the irregularity also harms CIM utilization. To fully utilize the attention-token-bit hybrid sparsity of multimodal Transformers, we design a digital CIM-based accelerator called MulTCIM with three corresponding features: The long reuse elimination dynamically reshapes the attention pattern to improve CIM utilization. The runtime token pruner (RTP) removes insignificant tokens, and the modal-adaptive CIM network (MACN) exploits symmetric modal overlapping to reduce CIM idleness. The effective bitwidth-balanced CIM (EBB-CIM) macro balances input bits across in-memory multiply-accumulations (MACs) to reduce computation time. The fabricated MulTCIM consumes only 2.24 mu J/Token for the ViLBERT-base model, achieving 2.50x-5.91x lower energy than previous Transformer accelerators and digital CIM accelerators.

Applications such as Graph Convolutional Networks (GCNs) and Deep Learning Recommendation Models (DLRMs) have computational and data-movement requirements beyond those seen in typical NN processing. Such beyond-NN applications typically consist of Sparse Gathering (SpG) and Sparse Algebra (SpA). SpG comprises gathering and reducing tensors from sparsely distributed addresses (in GCN's aggregation phase and DLRM's embedding layer). SpA refers to NN-based sparse tensor multiplication for the gathered tensors (in GCN's combination phase and DLRM's fully-connected layer). Due to the large application size, data movement is the main bottleneck for beyond-NN acceleration. Digital Computing-In-Memory (CIM) is an efficient and precise architecture for reducing data movement [1-3]. Large-scale beyond-NN acceleration motivates the demand for scaling out digital CIM processors. However, a large monolithic chip has low-yield issues due to manufacturing defects [4], which are more severe for CIM's memory-intensive logic. A Multi-Chip-Module (MCM) provides a high-yield solution for CIM scaling by integrating multiple smaller chiplets in one package [5]. Fig. 16.4.1 shows a typical MCM-CIM system with 4 CIM chiplets, but it has two challenges for beyond-NN acceleration: 1) SpG involves repeated off-chip DRAM access, inter-chiplet access and redundant reduction operations, which increases inter-chiplet bandwidth requirements and processing latency. 2) SpA suffers from (2a) inter-CIM workload imbalance and (2b) intra-CIM under-utilization, due to irregular tensor sparsity. © 2023 IEEE.

Skeleton-based human action cognition (HAR) has drawn increasing attention recently. As an emerging approach for skeleton-based HAR tasks, Spatial-Temporal Graph Convolution Network (STGCN) achieves remarkable performance by fully exploiting the skeleton topology information via graph convolution. Unfortunately, existing GCN accelerators lose efficiency when processing STGCN models due to two limitations To overcome the limitations, this paper proposes STAR, an STGCN architecture for skeleton-based human action recognition. STAR is designed based on the characteristics of different computation phases in STGCN. For limitation (1), a spatial-temporal dimension consistent (STDC) dataflow is proposed to fully exploit the data reuse opportunities in all the different dimensions of STGCN. For limitation (2), we propose a node-wise exponent sharing scheme and a temporal-structured redundancy elimination mechanism, to exploit the inherent temporal redundancy specially introduced by STGCN. To further address the under-utilization induced by redundancy elimination, we design a dynamic data scheduler to manage the feature data storage and schedule the features and weights for valid computation in real time. STAR achieves 4.48 , 5.98 , 2.54 , and 103.88 energy savings on average over the HyGCN, AWB-GCN, TPU, and Jetson TX2 GPU. IEEE

This paper addresses a UAV path planning task that seeks to observe a set of objects while satisfying the observation quality constraint. A dynamic programming algorithm is proposed that enables the UAV to observe the target objects with shortest path while subjecting to the observation quality constraint. The objects have their own facing direction and restricted observation range. With an observing order, the algorithm achieves (1+$\epsilon$)-approximation ratio in theory and runs in polynomial time. The extensive results show that the algorithm produces near-optimal solutions, the effectiveness of which is also tested and proved in the Airsim simulator, a realistic virtual environment.

Efficient traffic signal control (TSC) has been one of the most useful ways for reducing urban road congestion. Key to the challenge of TSC includes 1) the essential of real-time signal decision, 2) the complexity in traffic dynamics, and 3) the network-level coordination. Recent efforts that applied reinforcement learning (RL) methods can query policies by mapping the traffic state to the signal decision in real-time, however, is inadequate for unexpected traffic flows. By observing real traffic information, online planning methods can compute the signal decisions in a responsive manner. We propose an explicit multiagent coordination (EMC)-based online planning methods that can satisfy adaptive, real-time and network-level TSC. By multiagent, we model each intersection as an autonomous agent, and the coordination efficiency is modeled by a cost (i.e., congestion index) function between neighbor intersections. By network-level coordination, each agent exchanges messages with respect to cost function with its neighbors in a fully decentralized manner. By real-time, the message passing procedure can interrupt at any time when the real time limit is reached and agents select the optimal signal decisions according to the current message. Moreover, we prove our EMC method can guarantee network stability by borrowing ideas from transportation domain. Finally, we test our EMC method in both synthetic and real road network datasets. Experimental results are encouraging: compared to RL and conventional transportation baselines, our EMC method performs reasonably well in terms of adapting to real-time traffic dynamics, minimizing vehicle travel time and scalability to city-scale road networks.

Jian Gong,1,2,* Weiwei Wu,3,* Liguo Qiu,1,2 Xi Wang,1,2 Jianwei Bao,1,2 Jinjing Wang,4 Lifang Cheng,1,2 Zhiyuan Fu,1,5 Fengming Hu1,2 1Department of Integrated Traditional Chinese and Western Medicine of Dermatology, Dermatology Hospital of Jiangxi Province, Nanchang, Jiangxi, People’s Republic of China; 2Jiangxi Provincial Clinical Research Center for Skin Diseases, Nanchang, Jiangxi, People’s Republic of China; 3Department of Plastic and Dermatological Surgery, The Fifth People’s Hospital of Hainan Province, Haikou, Hainan, People’s Republic of China; 4Clinical School of Medicine, Jiangxi University of Traditional Chinese Medicine, Nanchang, Jiangxi, People’s Republic of China; 5Department of Pharmacy, Dermatology Hospital of Jiangxi Province, Nanchang, Jiangxi, People’s Republic of China*These authors contributed equally to this workCorrespondence: Zhiyuan Fu, Department of Pharmacy, Dermatology Hospital of Jiangxi Province, Nanchang, Jiangxi, People’s Republic of China, Tel +86 13970827820, Fax +86-0791-85207512, Email 1074586168@qq.com Fengming Hu, Department of Integrated Traditional Chinese and Western Medicine of Dermatology, Dermatology Hospital of Jiangxi Province, Nanchang, Jiangxi, People’s Republic of China, Tel +86 13970935828, Fax +86-0791-85207512, Email 18970802429@163.comAbstract: Psoriasis is an immune-mediated chronic inflammatory dermatosis influenced by hereditary and environmental factors. Human immunodeficiency virus (HIV) infection affects the immune system and exacerbates psoriatic lesions. We report the case of a 33-year-old male patient diagnosed with psoriasis vulgaris, psoriatic arthritis and HIV infection. Acitretin capsules, etanercept and high-active antiretroviral therapy (HAART) were effective. Two months after etanercept was discontinued, his condition worsened. After switching to secukinumab combined with HAART, the symptoms of psoriatic arthritis resolved rapidly after four weeks, with a D

Weiwei Wu,1,* Lengbing Sun,2,3,* Jiejie Lu,2 Xianxu Yang,2 Qiao Liu,3,4 Junzhi Wang5 1Department of Plastic and Dermatological Surgery, The Fifth People’s Hospital of Hainan Province, Haikou, People’s Republic of China; 2Department of Dermatology, The Fifth People’s Hospital of Hainan Province, Haikou, People’s Republic of China; 3School of Clinical Medicine, Jiangxi University of Chinese Medicine, Nanchang, People’s Republic of China; 4Department of Dermatology,The Second Affiliated Hospital of Jiangxi University of Chinese Medicine, Nanchang, People’s Republic of China; 5First Affiliated Hospital of Heilongjiang University of Traditional Chinese Medicine, Harbin, People’s Republic of China*These authors contributed equally to this workCorrespondence: Qiao Liu; Junzhi Wang, Email drliuqiao@163.com; drvolodia@163.comAbstract: Verruciform xanthoma (VX) is a rare, benign, mucocutaneous, verrucous, papillary lesion. This paper retrospectively summarizes clinical and pathologic features of 32 vulvar verruciform xanthoma reported from China and abroad. The skin lesions are generally single, mainly in labia minora, clitoris and fourchette with partly extending to the groin, buttocks and anus. The possible inducing factors include long-term scratching, local itching, severe lymphedema or lymphangioma circumscriptum. Severe cutaneous trauma and chronic inflammation may be the main causes. Clinically, it can easily be misdiagnosed as condylomata acuminata, squamous cell carcinoma, bowenoid papulosis, etc. It is reported to be related to underlying disorders. The main treatment is complete resection.Keywords: verruciform xanthoma, vulvar, clinical features, immunohistochemistry, treatment, etiology

Lengbing Sun,1,2,* Jiejie Lu,1,* Ming Zhang,1 Xianxu Yang,1 Weiwei Wu,1 Qiao Liu2,3 1Department of Dermatology, The Fifth People’s Hospital of Hainan Province, Haikou, People’s Republic of China; 2School of Clinical Medicine, Jiangxi University of Chinese Medicine, Nanchang, People’s Republic of China; 3Department of Dermatology, The Second Affiliated Hospital of Jiangxi University of Traditional Chinese Medicine, Nanchang, People’s Republic of China*These authors contributed equally to this workCorrespondence: Weiwei WuDepartment of Dermatology, The Fifth People’s Hospital of Hainan Province, 33, Southern Road of Longkun, Qiongshan District, Haikou, 570206, Hainan, People’s Republic of ChinaTel +86-13647541729Email vigorwu@126.comQiao LiuDepartment of Dermatology, The Second Affiliated Hospital of Jiangxi University of Traditional Chinese Medicine, 511 Nangang Road, Qingshan Lake District, Nanchang, 330012, Jiangxi, People’s Republic of ChinaTel +86-13317913339Email drliuqiao@163.comBackground: Skin cancers are the most frequent types of all malignant tumours with increasing incidence rates. The incidence rate varies between different countries around the world.Objective: This study aimed to analyze the clinical–pathological characteristics of skin cancers in patients visited at the Department of Dermatology of the Fifth People’s Hospital of Hainan Province from China during the last 12 years.Methods: The hospital database was searched for patients with skin cancers over a period of 12 years (from January 1, 2009 to December 31, 2020), and a retrospective review was conducted and a descriptive data analysis was undertaken on patients.Results: A total of 755 specimens of skin cancers were confirmed during this period. The common skin cancers were basal cell carcinoma (341, 48.99%), followed by squamous cell carcinoma (148, 21.26%) and Bowen’s disease (109, 15.66%). Th

When deploying deep neural networks (DNNs) onto deep learning processors, we usually exploit mixed-precision quantization and voltage-frequency scaling to make tradeoffs among accuracy, latency, and energy. Conventional methods usually determine the quantization-voltage-frequency (QVF) policy before DNNs are deployed onto local devices. However, they are difficult to make optimal customizations for local user scenarios. In this article, we solve the problem by enabling on-device QVF tuning with a new deep learning processor architecture Evolver. Evolver has a QVF tuning mode to deploy DNNs with local customizations before normal execution. In this mode, Evolver uses reinforcement learning to search the optimal QVF policy based on direct hardware feedbacks from the chip itself. After that, Evolver runs the newly quantized DNN inference under the searched voltage and frequency. To improve the performance and energy efficiency of both training and inference, we introduce bidirectional speculation and runtime reconfiguration techniques into the architecture. To the best of our knowledge, Evolver is the first deep learning processor that utilizes on-device QVF tuning to achieve both customized and optimal DNN deployment. © 1966-2012 IEEE.

Age-of-Information (AoI) is an application layer metric that has been widely adopted to quantify the information freshness of each information source. However, few works address the impact of probabilistic transmission failures on satisfying the harsh AoI requirement of each source, which is of critical importance in a great number of wireless-powered real-time applications. In this paper, we investigate the transmission scheduling problem of maximizing throughput over wireless channels under different time-average AoI requirements for heterogeneous information sources. When the channel reliability for each source is known as prior, the global optimal transmission scheduling policy is proposed. Moreover, when channel reliabilities are unknown, it is modeled as an AoI-constrained Multi-Armed Bandit (MAB) problem. Then a learning algorithm that meets the AoI requirement with probability 1 and incurs up to O(K\sqrt{T\log T}) accumulated regret is proposed, where K is the number of arms/information sources, and T is the time horizon. Numerical results show that the accumulated regret of our learning algorithm is strictly bounded by K\sqrt{T\log T} and outperforms the AoI-constraint-aware baseline, and the AoI requirement of every source is robustly satisfied., Comment: technical errors are found in the proof

Yunfang Zhang,1,* Ming Zhang,2,* Jianping Xie,2 Weiwei Wu,2 Jiejie Lu2 1Department of Oncology, Hainan Provincial Hospital of TCM, Haikou, 570203, People’s Republic of China; 2Department of Dermatology, The Fifth People’s Hospital of Hainan Province, Branch of National Clinical Research Center for Skin and Immune Disease, Haikou, 570206, People’s Republic of China*These authors contributed equally to this workCorrespondence: Jiejie LuDepartment of Dermatology, The Fifth People’s Hospital of Hainan Province, Branch of National Clinical Research Center for Skin and Immune Disease, No. 33, Southern Road of Longkun, Haikou, 570206, People’s Republic of ChinaTel +86-13519816255Fax +86-898-66729550Email lujiejie677@163.comAbstract: Reports of immune-related adverse events caused by programmed cell death protein-1 inhibitor are becoming increasingly frequent. Herein, we report the first case of pemphigus herpetiformis-type drug reaction presented after the treatment of tislelizumab (6 cycles) in a primary non-small cell lung carcinoma patient. A 56-year-old Chinese man was referred to our department for pruritic annulare erythema and blister for two weeks. Histological finding revealed blister formation in the epidermis and eosinophilic infiltration in the blister fluid. Direct immunofluorescence showed intercellular deposition of IgG and C3 within the lower part of epidermis. Serum anti-intercellular antibodies were positive at 1:100 dilution. Based on history and clinicopathological correlation, herpetiformis-type drug-induced pemphigus was diagnosed, which was possibly be induced by tislelizumab. To the best to our knowledge, there is no report of pemphigus herpetiformis-type drug-induced reaction associated with programmed cell death protein-1 inhibitor treatment.Keywords: programmed cell death protein-1 inhibitor, tislelizumab, pemphigus herpetiformis, drug reaction

Yuanyuan Geng,1,* Weiwei Wu,2,3,* Rouyu Li,4– 6 Juan Xu,1 Ruixue Gu,1 Jiejie Lu,2 Wenai Zheng,7 Fei Zhao,1 Jianzhong Zhang,1 Jie Gong1 1National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, People’s Republic of China; 2Department of Dermatology, The Fifth People’s Hospital of Hainan Province, Haikou, People’s Republic of China; 3National Clinical Research Center for Skin and Immune Disease, Beijing, People’s Republic of China; 4Department of Dermatology, Peking University First Hospital, Beijing, People’s Republic of China; 5Beijing Key Laboratory of Molecular Diagnosis on Dermatoses, Beijing, People’s Republic of China; 6Research Center for Medical Mycology, Peking University, Beijing, People’s Republic of China; 7Department of Laboratory Medicine, The Fifth People’s Hospital of Hainan Province, Haikou, People’s Republic of China*These authors contributed equally to this workCorrespondence: Jie Gong Tel +86 10 5890 0368Email gongjie@icdc.cnBackground: Founder events have been observed among numerous plants and animal species living on oceanic islands due to the geographic separation of these islands and the small amount of original life they harbor. However, there has been little research on the ecological characteristics of pathogenic microorganisms on islands. Trichophyton rubrum ranks the most common isolated dermatophyte causing dermatophytosis in clinic and has become an epidemic strain worldwide in recent decades.Objective: To study the phylogenetic characteristics and the distribution pattern of genetic polymorphism of T. rubrum in China, which further provide theoretical basis for the prevention and control of T. rubrum.Methods: In the present study, we sequenced and analyzed the genetic characteristics of 204 T. rubrum isolates from Hainan Island and other sites in China. Phylogenetic analysis and genetic polymorphisms were studied based on

Xinjia Ou,1,* Ping Wang,2,* Wentao Chen,3 Weiwei Wu,2 Jiejie Lu2 1Department of Dermatology, Hainan Wanning People’s Hospital, Wanning, Hainan, People’s Republic of China; 2Department of Dermatology, The Fifth People’s Hospital of Hainan Province, Branch of National Clinical Research Center for Skin and Immune Disease, Haikou, Hainan, People’s Republic of China; 3Department of Dermatology, Hainan Provincial Anning Hospital, Haikou, Hainan, People’s Republic of China*These authors contributed equally to this workCorrespondence: Jiejie LuDepartment of Dermatology, The Fifth People’s Hospital of Hainan Province, Branch of National Clinical Research Center for Skin and Immune Disease, No. 33, Southern Road of Longkun, Qiongshan District, Haikou, 570206, Hainan, People’s Republic of ChinaTel +86-13519816255Fax +86-898-66729550Email lujiejie677@163.comAbstract: Porokeratosis ptychotropica is a rare form of porokeratosis characterized by dyskeratotic skin lesions around genital area or gluteal cleft. Herein, a case of porokeratosis ptychotropica was reported. The patient was a 35-year-old man, who complained of pruritic papules and plaques in the perianal and buttock region for thirteen years. On examination, well-demarcated brown plaques with a verrucous white surface and multiple satellite papules were located along the gluteal folds and buttocks sparing the anus. Histopathological examination was consistent with porokeratosis. Combined with clinical manifestations and histopathologic changes, the patient was diagnosed as porokeratosis ptychotropica. He was treated with oral acitretin 30mg/d and CO2 laser treatment, but the lesions showed no evident improvement after three months. Although it is not a new case, this condition is an extremely rare one that must be reviewed and emphasized. The dermatologist should keep porokeratosis ptychotropica in mind as one differential diagnosis for pruritic papules in the anogenital region.Keywor

Jiejie Lu, Weiwei Wu, Ming Zhang, Ping Wang, Mu Niu, Xianxu Yang Department of Dermatology, The Fifth People’s Hospital of Hainan Province, Branch of National Clinical Research Center for Skin and Immune Disease, Haikou, Hainan, People’s Republic of ChinaCorrespondence: Mu Niu; Xianxu YangDepartment of Dermatology, The Fifth People’s Hospital of Hainan Province, Branch of National Clinical Research Center for Skin and Immune Disease, No. 33, Southern Road of Longkun, Qiongshan District, Haikou, 570206, Hainan, People’s Republic of ChinaTel +86-18389485160; +86-13876300372Fax +86-898-66729550; +86-898-66729550Email 382219948@qq.com; 13876300372@139.comAbstract: Wells syndrome (WS), also known as eosinophilic cellulitis, is a rare inflammatory dermatosis of unknown etiology that typically presents with pruritic cellulitis-like plaques. The first line treatment options for WS are topical or systemic corticosteroids, however, the development of side effects of systemic corticosteroids usually led to a switch to the second line therapy. Here, we reported a rare case of facial Wells syndrome misdiagnosed with bacterial cellulitis. A 26-year-old female presented with a one-week history of erythematous, edematous and blushing plaques partially covered by bullae. A skin biopsy revealed diffuse infiltration of eosinophils in the entire dermis and “flame figures” compatible with WS. Initially, the patient was successfully treated with methylprednisolone. However, three month later, the disease relapsed. Because of weight gain and centripetal obesity, the patient refused to oral administration of methylprednisolone. Traditional Chinese Medicine tripterygium glycosides (TG) 60mg/day was prescribed and the lesions completely resolved after 4 weeks without any recurrence. Our case suggests that tripterygium glycosides may be a safe and effective treatment option for Wells syndrome.Keywords: Wells syndrome, tripterygium glycosides, facial cellulitis

The surface of nanowires is a source of interest mainly for electrical prospects. Thus, different surface chemical treatments were carried out to develop recipes to control the surface effect. In this work, we succeed in shifting and tuning the semiconductivity of a Si nanowire-based device from n- to p-type. This was accomplished by generating a hole transport layer at the surface by using an electrochemical reaction-based nonequilibrium position to enhance the impact of the surface charge transfer. This was completed by applying different annealing pulses at low temperature (below 400 °C) to reserve the hydrogen bonds at the surface. After each annealing pulse, the surface was characterized by XPS, Kelvin probe measurements, and conductivity measured by FET based on a single Si NW. The mechanism and conclusion were supported experimentally and theoretically. To this end, this strategy has been demonstrated as an essential tool which could pave a new road for regulating semiconductivity and for other low-dimensional nanomaterials.

Direction of arrival (DOA) estimation performance may degrade substantially when linear frequency modulation (LFM) signals are spectrally-overlapped in time-frequency (TF) domain. In order to solve this problem, the single-source TF points selection algorithm based on Wigner-Ville distribution (WVD) and Hough transform is studied in this paper. Firstly, the signal intersections in TF domain can be solved based on the Hough transform. Secondly, by removing multiple-source TF points at intersections according to the empirical threshold value which is calculated by using the statistical experiment method, we can get single-source TF points set. Then, based on the Euclidean distance operator, single-source TF points set belonging to each signal can be obtained according to the property that TF points of the same signal have the same eigenvector. Finally, the averaged spatial TF distribution matrix is constructed and DOA estimation is realized based on the multiple signal classification (MUSIC) algorithm. In this way, the proposed algorithm can resolve the TF non-disjoint LFM signals because it can automatically select single-source TF points set of each signal. Simulation results illustrate that the proposed algorithm possesses higher angular resolution and has pretty good DOA estimation precision compared with existing algorithms.

This paper examines flight delay propagation in air transport networks. Delays add to additional costs, inefficiencies, and unsustainable development. An integrated flight-based susceptible-infected-susceptible (FSIS) model was developed to analyse the flight delay process from a network-based perspective. The probability of flight delay propagation was determined using a translog model. The model was applied to an airline network consisting of thirty-three routes involving three airlines. The results show that the propagation probability is network-related and varies across different routes. The variation is related to the flight frequencies at airports, route distances, scheduled buffer times, and the propagated delay time. Whereas buffer time has a greater impact on smaller airports, flight movement has a greater impact on larger airports. Having a better understanding of how delays happen can help the development of strategies to avoid them. This will lead to less costs, higher efficiencies, and more sustainable airport and airline development.

In this paper, a novel method for microstrip filters with arbitrary passband design is proposed. A kind of stub-loaded microstrip filter with asymmetric structure is proposed. The mathematic function of total reflection coefficient at the input port of the filter is derived based on the reflection theory, an ultra-wide-band (UWB) filter which can work from 11GHz to 39GHz is fabricated and measured to verify that our function can calculate the reflection coefficient precisely. The procedure to design stub-loaded microstrip filters with arbitrary passbands is given in this paper, this design procedure is based on the Monte Carlo method. A bandpass filter (BPF) which can work on 7--9.5GHz is designed and measured as an example. The comparison between calculated dimensions and practical dimensions of this filter shows a satisfactory fitting degree. A low-pass filter (LPF) which can work below 4GHz is designed and compared with some prior arts in order to show that our proposed filter is simple in structure and small in size. By using our proposed method, the stub-loaded microstrip filter can be designed quickly and easily. Based on the results mentioned above, we can count that the method proposed in this paper has a good application in microstrip filter design.

This paper examines flight delay propagation in air transport networks. Delays add to additional costs, inefficiencies, and unsustainable development. An integrated flight-based susceptible-infected-susceptible (FSIS) model was developed to analyse the flight delay process from a network-based perspective. The probability of flight delay propagation was determined using a translog model. The model was applied to an airline network consisting of thirty-three routes involving three airlines. The results show that the propagation probability is network-related and varies across different routes. The variation is related to the flight frequencies at airports, route distances, scheduled buffer times, and the propagated delay time. Whereas buffer time has a greater impact on smaller airports, flight movement has a greater impact on larger airports. Having a better understanding of how delays happen can help the development of strategies to avoid them. This will lead to less costs, higher efficiencies, and more sustainable airport and airline development.

In the past decade, unmanned aerial vehicles (UAVs) have been widely used in various civilian applications, most of which only require a single UAV. In the near future, it is expected that more and more applications will be enabled by the cooperation of multiple UAVs. To facilitate such applications, it is desirable to utilize a general control platform for cooperative UAVs. However, existing open-source control platforms cannot fulfill such a demand because (1) they only support the leader-follower mode, which limits the design options for fleet control, (2) existing platforms can support only certain UAVs and thus lack of compatibility, and (3) these platforms cannot accurately simulate a flight mission, which may cause a big gap between simulation and real flight. To address these issues, we propose a general control and monitoring platform for cooperative UAV fleet, namely, CoUAV, which provides a set of core cooperation services of UAVs, including synchronization, connectivity management, path planning, energy simulation, etc. To verify the applicability of CoUAV, we design and develop a prototype and we use the new system to perform an emergency search application that aims to complete a task with the minimum flying time. To achieve this goal, we design and implement a path planning service that takes both the UAV network connectivity and coverage into consideration so as to maximize the efficiency of a fleet. Experimental results by both simulation and field test demonstrate that the proposed system is viable.

A method to design a kind of microstrip filters consisting of only opened stubs and shorted stubs is proposed in this paper. This method is based on the Theory of Small Reflections, and the equations to calculate dimensions of this type of filters is exhibited. Two filters developed by our method are simulated and fabricated. The first filter has a passband on 5~8GHz. The second one is a dual-band filter and can work on both 2.4GHz and 5.8GHz. By using our method, the designed filters only contain opened stubs and shorted stubs, therefore, it is easy to design and fabricate this type of filters. The comparison between calculated and measured reflection coefficient curves shows a satisfactory fitting degree, this manifestation verifies that the method in our paper has a good application in filter design. The position of transmission zeros about the second filter are investigated. All the results show that our method can be a good guidance in microstrip filter design.

Weiwei Wu,1 Li Wang,2 Lingling Wang,2 Yuangang Zu,2 Siying Wang,2 Peiyan Liu,2 Xiuhua Zhao2 1Key Laboratory of Saline-Alkali Vegetation Ecology Restoration in Oil Field (SAVER), Northeast Forestry University, Harbin, China; 2Key Laboratory of Forest Plant Ecology, Northeast Forestry University, Ministry of Education, Harbin, Heilongjiang, China Background: Honokiol is a bioactive lignanoid and has been utilized in traditional Chinese medicine for a long time. It exhibits several pharmacological properties, such as anticancer effects, anti-inflammatory effects, and antianxiety effects. However, the poor aqueous solubility of honokiol has impeded clinical applications. Materials and methods: In the present study, we adopted the liquid antisolvent precipitation (LAP) technique to prepare nanoparticles of honokiol for enhancement of solubility and bioavailability. Moreover, the honokiol nanoparticles obtained were investigated and evaluated in terms of morphology, physicochemical properties, saturation solubility, dissolution in vitro, bioavailability in vivo, toxicity, and the inhibitory effect on growth of HepG2 cells. Results: The obtained honokiol nanoparticles existed nearly in spherical shape and could be turned into amorphous structure by the LAP method. Moreover, the solubility of the honokiol nanoparticles was extremely higher than that of free honokiol, and the nanoparticle dissolution rate was also higher than that of free honokiol, which was about 20.41 times and 26.2 times than that of free honokiol in artificial gastric juice and in artificial intestinal juice. The area under the curve [AUC(0–t)] value of honokiol nanoparticles was about 6.52 times greater than that of free honokiol; therefore, the honokiol nanoparticles had a higher bioavailability than free honokiol but were innoxious to the organs of rats. Additionally, the honokiol nanoparticles exhibited a higher inhibition of HepG2 cells due to their lower IC50 compared to free honokiol. Co

A method to design a kind of microstrip filters consisting of only opened stubs and shorted stubs is proposed in this paper. This method is based on the Theory of Small Reflections, and the equations to calculate dimensions of this type of filters is exhibited. Two filters developed by our method are simulated and fabricated. The first filter has a passband on 5~8GHz. The second one is a dual-band filter and can work on both 2.4GHz and 5.8GHz. By using our method, the designed filters only contain opened stubs and shorted stubs, therefore, it is easy to design and fabricate this type of filters. The comparison between calculated and measured reflection coefficient curves shows a satisfactory fitting degree, this manifestation verifies that the method in our paper has a good application in filter design. The position of transmission zeros about the second filter are investigated. All the results show that our method can be a good guidance in microstrip filter design.

The growing size of convolutional neural networks (CNNs) requires large amounts of on-chip storage. In many CNN accelerators, their limited on-chip memory capacity causes massive off-chip memory access and leads to very high system energy consumption. Embedded DRAM (eDRAM), with higher density than SRAM, can be used to improve on-chip buffer capacity and reduce off-chip access. However, eDRAM requires periodic refresh to maintain data retention, which costs much energy consumption. Refresh is unnecessary if the data’s lifetime in eDRAM is shorter than the eDRAM’s retention time. Based on this principle, we propose a Retention-Aware Neural Acceleration (RANA) framework for CNN accelerators to save total system energy consumption with refresh-optimized eDRAM. The RANA framework includes three levels of techniques: a retention-aware training method, a hybrid computation pattern and a refresh-optimized eDRAM controller. At the training level, CNN’s error resilience is exploited in training to improve eDRAM’s tolerable retention time. At the scheduling level, RANA assigns each CNN layer with a computation pattern that consumes the lowest energy. At the architecture level, a refresh-optimized eDRAM controller is proposed to alleviate unnecessary refresh operations. We implement an evaluation platform to verify RANA. Owing to the RANA framework, 99.7% eDRAM refresh operations can be removed with negligible performance and accuracy loss. Compared with the conventional SRAM-based CNN accelerator, an eDRAM-based CNN accelerator strengthened by RANA can save 41.7% off-chip memory access and 66.2% system energy consumption, with the same area cost. © 2018 IEEE.

Weiwei Wu,1 Li Wang,2 Lingling Wang,2 Yuangang Zu,2 Siying Wang,2 Peiyan Liu,2 Xiuhua Zhao2 1Key Laboratory of Saline-Alkali Vegetation Ecology Restoration in Oil Field (SAVER), Northeast Forestry University, Harbin, China; 2Key Laboratory of Forest Plant Ecology, Northeast Forestry University, Ministry of Education, Harbin, Heilongjiang, China Background: Honokiol is a bioactive lignanoid and has been utilized in traditional Chinese medicine for a long time. It exhibits several pharmacological properties, such as anticancer effects, anti-inflammatory effects, and antianxiety effects. However, the poor aqueous solubility of honokiol has impeded clinical applications. Materials and methods: In the present study, we adopted the liquid antisolvent precipitation (LAP) technique to prepare nanoparticles of honokiol for enhancement of solubility and bioavailability. Moreover, the honokiol nanoparticles obtained were investigated and evaluated in terms of morphology, physicochemical properties, saturation solubility, dissolution in vitro, bioavailability in vivo, toxicity, and the inhibitory effect on growth of HepG2 cells. Results: The obtained honokiol nanoparticles existed nearly in spherical shape and could be turned into amorphous structure by the LAP method. Moreover, the solubility of the honokiol nanoparticles was extremely higher than that of free honokiol, and the nanoparticle dissolution rate was also higher than that of free honokiol, which was about 20.41 times and 26.2 times than that of free honokiol in artificial gastric juice and in artificial intestinal juice. The area under the curve [AUC(0–t)] value of honokiol nanoparticles was about 6.52 times greater than that of free honokiol; therefore, the honokiol nanoparticles had a higher bioavailability than free honokiol but were innoxious to the organs of rats. Additionally, the honokiol nanoparticles exhibited a higher inhibition of HepG2 cells due to their lower IC50 compared to free honokiol. Co

Airborne target's micro-motion such as rotation or vibration causes phase modulation, termed as micro-Doppler effect, into radar signals. The feature of micro-motion is one of the most obvious features for radar recognition in mid-course phase. In traditional works, it is assumed that the micro-motion of the scatterer is the same as the ballistic target. However, with the variation of the aspect angle of ISAR, the position of the scatterer changes. In this paper, the movement of a ballistic missile in mid-course is modeled and analyzed. A false target jamming method is proposed by combining the micro-motion modulation and the electromagnetic scattering modulation. Compared with the methods using ideal point models, our method is able to generate a vivid false target with structural information, micro-motion and variation of the scatterer's RCS. The micro-motion effect of the false target is presented through ISAR imaging and time-frequency analysis. The effectiveness and correctness of the algorithm is verified by simulation.

A geometrically symmetrical fractal structure is presented in this paper to provide an alternative approach for the miniaturization design of microstrip bandpass filters (BPFs). The generation process of the geometric geometry is described in detail, and a new fractal resonator called Greek-cross fractal resonator (GCFR) is produced by etching the proposed fractal configuration on the surface of the conventional dual-mode meandered loop resonator. Four microstrip BPFs based on the first four iterations GCFR are modeled and simulated. The simulation results show that with the increase of the number of iterations, the central frequency of the BPF is gradually moving towards the low frequency, which indicates that the proposed fractal resonator has the characteristic of miniaturization. In addition, the parameter optimization and surface current density distribution are also analyzed in order to better understand the performance of the BPF. Finally, a compact dual-mode BPF based on the third iteration GCFR is designed, fabricated and measured. The measurement results are in good agreement with the simulation ones.

Based on Dechirping algorithm and uniform circle array(UCA), a new 2-D direction of arrival (DOA) estimation algorithm of linear frequency modulation (LFM) signals is proposed in this paper. The algorithm uses the thought of Dechirping and regards the signal to be estimated which is received by the reference sensor as the reference signal and proceeds the difference frequency treatment with the signal received by each sensor. So the signal to be estimated becomes a single-frequency signal in each sensor. Then we transform the single-frequency signal to an isolated impulse through Fourier transform (FFT) and construct a new array data model based on the prominent parts of the impulse. Finally, we respectively use multiple signal classification (MUSIC) algorithm and rotational invariance technique (ESPRIT) algorithm to realize 2-D DOA estimation of LFM signals. The simulation results verify the effectiveness of the algorithm proposed.

In order to improve the direction-finding efficiency of the correlative interferometer and reduce the size of the lookup table, this paper proposes the one dimensional sorting lookup table-two dimensional linear interpolation (1DSLUT-2DLI) algorithm. Firstly, the uniform circular array (UCA) model is established and the direction finding (DF) theory of the correlative interferometer is analyzed. A new lookup table is obtained by proceeding the ascending order for the first dimensional phase differences and a one dimensional iterative filtering method is used to look up the new table to get the direction of arrival (DOA) estimation. Compared to the exist methods, the 1DSLUT algorithm can reduce the computational complexity greatly. Considering the burden of a big lookup table, this paper proposes the 2DLI algorithm. Through the Taylor expansion, the conclusion that the phase difference is approximately linear in a small angle range is obtained. So, the linear interpolation can be applied to calculate the phase differences in the azimuth direction and elevation direction. On this basis, we conclude the equations to get the DOA estimation using the 2DLI algorithm. In this way, the size of the lookup table is reduced greatly, which decreases the computational complexity greatly also. The numerical simulations verify the effectiveness of the 1DSLUT-2DLI algorithm and it can obtain a pretty high DOA estimation precision with a low computational complexity and a small lookup table.

In this paper, a novel rasorber with both Frequency Selective Surface and absorptive periodical structure is developed. This rasorber works as a radome and an absorber. Firstly, the design procedure of the unit cell of this rasorber is explained. Then, the characteristics of the manufactured rasorber are measured. The characteristics include the transmission/reflection coefficients of the rasorber, the radiation properties of the horn antenna covered by the novel rasorber and the scattering features of this rasorber. In the passband, the gain of the antenna with our rasorber radome is only 1~2 dB lower than the one of the horn antenna without any radome. Furthermore, the radome has little effect on the radiation patterns of the horn antenna. In the absorptive bands of the rasorber, the electric level of the scattered electromagnetic wave from the rasorber can be 16.5 dB lower than the one from a metallic plane with the same size as the rasorber. The feature proves that this rasorber can be a good candidate in the stealth radar radome area.

China has repeatedly been the subject of genetic studies to elucidate its prehistoric and historic demography. While some studies reported a genetic distinction between Northern and Southern Han Chinese, others showed a more clinal picture of small differences within China. Here, we investigated the distribution of Y chromosome variation along administrative as well as ethnic divisions in the mainland territory of the People's Republic of China, including 28 administrative regions and 19 recognized Chinese nationalities, to assess the impact of recent demographic processes. To this end, we analyzed 37,994 Y chromosomal 17-marker haplotype profiles from the YHRD database with respect to forensic diversity measures and genetic distance between groups defined by administrative boundaries and ethnic origin. We observed high diversity throughout all Chinese provinces and ethnicities. Some ethnicities, including most prominently Kazakhs and Tibetans, showed significant genetic differentiation from the Han and other groups. However, differences between provinces were, except for those located on the Tibetan plateau, less pronounced. This discrepancy is explicable by the sizeable presence of Han speakers, who showed high genetic homogeneity all across China, in nearly all studied provinces. Furthermore, we observed a continuous genetic North-South gradient in the Han, confirming previous reports of a clinal distribution of Y chromosome variation and being in notable concordance with the previously observed spatial distribution of autosomal variation. Our findings shed light on the demographic changes in China accrued by a fast-growing and increasingly mobile population.

Airborne target's micro-motion such as rotation or vibration causes phase modulation, termed as micro-Doppler effect, into radar signals. The feature of micro-motion is one of the most obvious features for radar recognition in mid-course phase. In traditional works, it is assumed that the micro-motion of the scatterer is the same as the ballistic target. However, with the variation of the aspect angle of ISAR, the position of the scatterer changes. In this paper, the movement of a ballistic missile in mid-course is modeled and analyzed. A false target jamming method is proposed by combining the micro-motion modulation and the electromagnetic scattering modulation. Compared with the methods using ideal point models, our method is able to generate a vivid false target with structural information, micro-motion and variation of the scatterer's RCS. The micro-motion effect of the false target is presented through ISAR imaging and time-frequency analysis. The effectiveness and correctness of the algorithm is verified by simulation.

Based on Dechirping algorithm and uniform circle array(UCA), a new 2-D direction of arrival (DOA) estimation algorithm of linear frequency modulation (LFM) signals is proposed in this paper. The algorithm uses the thought of Dechirping and regards the signal to be estimated which is received by the reference sensor as the reference signal and proceeds the difference frequency treatment with the signal received by each sensor. So the signal to be estimated becomes a single-frequency signal in each sensor. Then we transform the single-frequency signal to an isolated impulse through Fourier transform (FFT) and construct a new array data model based on the prominent parts of the impulse. Finally, we respectively use multiple signal classification (MUSIC) algorithm and rotational invariance technique (ESPRIT) algorithm to realize 2-D DOA estimation of LFM signals. The simulation results verify the effectiveness of the algorithm proposed.

A geometrically symmetrical fractal structure is presented in this paper to provide an alternative approach for the miniaturization design of microstrip bandpass filters (BPFs). The generation process of the geometric geometry is described in detail, and a new fractal resonator called Greek-cross fractal resonator (GCFR) is produced by etching the proposed fractal configuration on the surface of the conventional dual-mode meandered loop resonator. Four microstrip BPFs based on the first four iterations GCFR are modeled and simulated. The simulation results show that with the increase of the number of iterations, the central frequency of the BPF is gradually moving towards the low frequency, which indicates that the proposed fractal resonator has the characteristic of miniaturization. In addition, the parameter optimization and surface current density distribution are also analyzed in order to better understand the performance of the BPF. Finally, a compact dual-mode BPF based on the third iteration GCFR is designed, fabricated and measured. The measurement results are in good agreement with the simulation ones.

In this paper, a novel rasorber with both Frequency Selective Surface and absorptive periodical structure is developed. This rasorber works as a radome and an absorber. Firstly, the design procedure of the unit cell of this rasorber is explained. Then, the characteristics of the manufactured rasorber are measured. The characteristics include the transmission/reflection coefficients of the rasorber, the radiation properties of the horn antenna covered by the novel rasorber and the scattering features of this rasorber. In the passband, the gain of the antenna with our rasorber radome is only 1~2 dB lower than the one of the horn antenna without any radome. Furthermore, the radome has little effect on the radiation patterns of the horn antenna. In the absorptive bands of the rasorber, the electric level of the scattered electromagnetic wave from the rasorber can be 16.5 dB lower than the one from a metallic plane with the same size as the rasorber. The feature proves that this rasorber can be a good candidate in the stealth radar radome area.

In order to improve the direction-finding efficiency of the correlative interferometer and reduce the size of the lookup table, this paper proposes the one dimensional sorting lookup table-two dimensional linear interpolation (1DSLUT-2DLI) algorithm. Firstly, the uniform circular array (UCA) model is established and the direction finding (DF) theory of the correlative interferometer is analyzed. A new lookup table is obtained by proceeding the ascending order for the first dimensional phase differences and a one dimensional iterative filtering method is used to look up the new table to get the direction of arrival (DOA) estimation. Compared to the exist methods, the 1DSLUT algorithm can reduce the computational complexity greatly. Considering the burden of a big lookup table, this paper proposes the 2DLI algorithm. Through the Taylor expansion, the conclusion that the phase difference is approximately linear in a small angle range is obtained. So, the linear interpolation can be applied to calculate the phase differences in the azimuth direction and elevation direction. On this basis, we conclude the equations to get the DOA estimation using the 2DLI algorithm. In this way, the size of the lookup table is reduced greatly, which decreases the computational complexity greatly also. The numerical simulations verify the effectiveness of the 1DSLUT-2DLI algorithm and it can obtain a pretty high DOA estimation precision with a low computational complexity and a small lookup table.