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Bo Li,1 Weiqing Wu,1 Aijun Liu,1 Lifeng Feng,1 Bin Li,1 Yong Mei,1 Li Tan,1 Chaoyang Zhang,2 Yangtao Tian1 1Department of Pancreatic Surgery, Shangluo Center Hospital, Shangluo, Shaanxi, 726000, People’s Republic of China; 2Department of Ultrasound Medicine, Shangluo Center Hospital, Shangluo, Shaanxi, 726000, People’s Republic of ChinaCorrespondence: Yangtao Tian, Department of Pancreatic Surgery, Shangluo Center Hospital, 37 Shangyang, Shangzhou, Shangluo, Shaanxi, 726000, People’s Republic of China, Email 928763821@qq.comBackground: Severe acute pancreatitis (SAP) can progress to lung and kidney dysfunction, and blood clotting within 48 hours of its onset, and is associated with a high mortality rate. The aim of this study was to establish a reliable diagnostic prediction model for the early stage of severe pancreatitis.Methods: The clinical data of patients diagnosed with acute pancreatitis from October 2017 to June 2022 at the Shangluo Central Hospital were collected. The risk factors were screened by least absolute shrinkage and selection operator (LASSO) regression analysis. A novel nomogram model was then established by multivariable logistic regression analysis.Results: The data of 436 patients with acute pancreatitis, 45 (10.3%) patients had progressed to SAP. Through univariate and LASSO regression analyses, the neutrophils (P < 0.001), albumin (P < 0.001), blood glucose (P < 0.001), serum calcium (P < 0.001), serum creatinine (P < 0.001), blood urea nitrogen (P < 0.001) and procalcitonin (P = 0.005) were identified as independent predictive factors for SAP. The nomogram built on the basis of these factors predicted SAP with sensitivity of 0.733, specificity of 0.9, positive predictive value of 0.458 and negative predictive value of 0.967. Furthermore, the concordance index of the nomogram reached 0.889 (95% CI, 0.837– 0.941), and the area under the curve (AUC) in receiver operating characteristic curve (ROC) analysis was signifi

Histopathology image analysis plays a crucial role in cancer diagnosis. However, training a clinically applicable segmentation algorithm requires pathologists to engage in labour-intensive labelling. In contrast, weakly supervised learning methods, which only require coarse-grained labels at the image level, can significantly reduce the labeling efforts. Unfortunately, while these methods perform reasonably well in slide-level prediction, their ability to locate cancerous regions, which is essential for many clinical applications, remains unsatisfactory. Previously, we proposed CAMEL, which achieves comparable results to those of fully supervised baselines in pixel-level segmentation. However, CAMEL requires 1,280x1,280 image-level binary annotations for positive WSIs. Here, we present CAMEL2, by introducing a threshold of the cancerous ratio for positive bags, it allows us to better utilize the information, consequently enabling us to scale up the image-level setting from 1,280x1,280 to 5,120x5,120 while maintaining the accuracy. Our results with various datasets, demonstrate that CAMEL2, with the help of 5,120x5,120 image-level binary annotations, which are easy to annotate, achieves comparable performance to that of a fully supervised baseline in both instance- and slide-level classifications., Comment: 41 pages, 13 figures, published in Advanced Intelligent Systems

Satellite and unmanned aerial vehicle (UAV) net-works have been introduced as enhanced approach to providedynamic control, massive connections and global coverage forfuture wireless communication systems. This paper considersa coordinated satellite-UAV communication system, where theUAV performs the environmental reconnaissance task with theassistance of satellite in a hostile jamming environment. To fulfillthis task, the UAV needs to realize autonomous trajectory controland upload the collected data to the satellite. With the aid ofthe uploading data, the satellite builds the environment situationmap integrating the beam quality, jamming status, and trafficdistribution. Accordingly, we propose a closed-loop anti-jammingdynamic trajectory optimization approach, which is divided intothree stages. Firstly, a coarse trajectory planning is made accord-ing to the limited prior information and preset points. Secondly,the flight control between two adjacent preset points is formulatedas a Markov decision process, and reinforcement learning (RL)based automatic flying control algorithms are proposed to explorethe unknown hostile environment and realize autonomous andprecise trajectory control. Thirdly, based on the collected dataduring the UAV’s flight, the satellite utilizes an environmentsituation estimating algorithm to build an environment situationmap, which is used to reselect the preset points for the first stageand provide better initialization for the RL process in the secondstage. Simulation results verify the validity and superiority of theproposed approach.

Satellite and unmanned aerial vehicle (UAV) net-works have been introduced as enhanced approach to providedynamic control, massive connections and global coverage forfuture wireless communication systems. This paper considersa coordinated satellite-UAV communication system, where theUAV performs the environmental reconnaissance task with theassistance of satellite in a hostile jamming environment. To fulfillthis task, the UAV needs to realize autonomous trajectory controland upload the collected data to the satellite. With the aid ofthe uploading data, the satellite builds the environment situationmap integrating the beam quality, jamming status, and trafficdistribution. Accordingly, we propose a closed-loop anti-jammingdynamic trajectory optimization approach, which is divided intothree stages. Firstly, a coarse trajectory planning is made accord-ing to the limited prior information and preset points. Secondly,the flight control between two adjacent preset points is formulatedas a Markov decision process, and reinforcement learning (RL)based automatic flying control algorithms are proposed to explorethe unknown hostile environment and realize autonomous andprecise trajectory control. Thirdly, based on the collected dataduring the UAV’s flight, the satellite utilizes an environmentsituation estimating algorithm to build an environment situationmap, which is used to reselect the preset points for the first stageand provide better initialization for the RL process in the secondstage. Simulation results verify the validity and superiority of theproposed approach.

Polar code, with explicit construction and recursive structure, is the latest breakthrough in channel coding field for its low-complexity and theoretically capacity-achieving property. Since polar codes can approach the maximum likelihood performance under successive cancellation list decoding (SCLD), its decoding performance can be evaluated by Bonferroni-type bounds (e.g., union bound) in which the Hamming weight spectrum will be used. Especially, the polar codewords with minimum Hamming weight (PC-MHW) are the most important item in that bound because they make major contributions to the decoding error pattern particularly at high signal-to-noise-ratio. In this work, we propose an efficient strategy for enumerating the PC-MHW and its number. By reviewing the inherent reason that PC-MHW can be generated by SCLD, we obtain some common features of PC-MHW captured by SCLD. Using these features, we introduce a concept of zero-capacity bit-channel to obtain a tight upper bound for the number of PC-MHW, whose computing complexity is sublinear with code length. Furthermore, we prove that the proposed upper bound is really the exact number of PC-MHW in most cases. Guided by the bound and its theoretical analysis, we devise an efficient SCLD-based method to enumerate PC-MHW, which requires less than half of the list size compared with the existing methods., Comment: 30 pages

Aijun Liu, Yongcheng Jiao, Huijun Ji, Zhiwen Zhang Department of Neurosurgery, First Affiliated Hospital of PLA General Hospital, Beijing, People’s Republic of China Objectives: The aim of this study is to present a case of successful relief of bilateral occipital neuralgia (ON) using unilateral occipital nerve stimulation (ONS) and to discuss the possible underlying mechanisms. Materials and methods: We present the case of a 59-year-old female patient with severe bilateral ON treated with unilateral ONS. We systematically reviewed previous studies of ONS for ON, discussing the possible mechanisms of ONS in the relief of ON. Results: The patient reported complete pain relief after consistent unilateral ONS during the follow-up period. The underlying mechanisms may be linked to the relationship between pain and several brain regions, including the pons, midbrain, and periaqueductal gray. Conclusion: ONS is an effective and safe option for treating ON. Future studies will be required to clarify the mechanisms by which unilateral occipital stimulation provided relief for bilateral neuralgia in this case. Keywords: occipital neuralgia, neuromodulation, peripheral nerve stimulation

In this paper a hybrid Network Coding Cooperation (hybrid-NCC) system is proposed to achieve both reliable transmission and high throughput in wireless networks. To balance the transmission reliability with throughput, the users are divided into cooperative sub-networks based on the geographical information, and the cooperation is implemented in each sub-network. After receiving signals from the cooperative partners, each user encodes them by exploiting hybrid network coding and then forwards the recoded symbols via the Link-Adaptive Regenerative (LAR) relaying. First, the Diversity-Multiplexing Tradeoff (DMT) is analyzed to demonstrate that the proposed system is bandwidth-efficient. Second, the Symbol Error Probability (SEP) is also derived, which shows that the proposed system achieves a higher reliability as compared to the traditional Complex Field Network Coding Cooperation (CFNCC). Moreover, because dedicated relays are not required, our proposed system can both reduce the costs and enhance the flexibility of the implementation. Finally, the analytical results are supported and validated by numerical simulations.

In this paper, we investigate the noncoherent iterative demodulation of coded continuous phase modulation (CPM) in frequency hopped (FH) systems. In this field, one important problem is that the complexity of the optimal demodulator is prohibitive unless the number of symbols per hop duration is very small. To solve this problem, we propose a novel demodulator, which reduces the complexity by applying phase quantization and exploiting the phase rotational invariance property of CPM signals. As shown by computational complexity analysis and numerical results, the proposed demodulator approaches the performance of the optimal demodulator, and provides considerable performance improvement over the existing solutions with the same computational complexity.

It has been shown that the multiple trellis code can perform better than the conventional trellis code over AWGN channels, at the cost of additional computations per trellis branch. Multiple trellis coded multi-h CPM schemes have been shown in the literature to have attractive power-bandwidth performance at the expense of increased receiver complexity. In this method, the multi-h format is made to be associated with the specific pattern and repeated rather than cyclically changed in time for successive symbol intervals, resulting in a longer effective length of the error event with better performance. It is well known that the rate (n-1)/n multiple trellis codes combined with 2^n-level CPM have good power-bandwidth performance. In this paper, a scheme combining rate 1/2 and 2/3 multiple trellis codes with 4- and 8-level multi-h CPM is shown to have better power-bandwidth performance over the upper bound than the scheme with single-h.

Signal to noise ratio (SNR) estimators are required for many radio engineering applications. In this paper, a SNR estimator based on the first and second order moments is derived and examined for constant envelop modulations over additive white Gaussian noise (AWGN) channel. In the first, a modification method is proposed to reduce the bias of conventional first and second order moments based SNR estimator. Then, in order to reduce hardware implementation complicity, multi segments of cubic polynomial are adopted to approximate the expression of the proposed SNR estimator which doesn’t have a close form solution. The approximate expression is very precise in the SNR range -10dB ~ 20 dB as illustrated by numerical simulation. Besides, practical hardware circuit is proposed for FPGA implementation. Simulation results show that the proposed SNR estimator has the lowest normalized bias and variance when compared with two other classic estimators.

Signal to noise ratio (SNR) estimators are required for many radio engineering applications. In this paper, a SNR estimator based on the first and second order moments is derived and examined for constant envelop modulations over additive white Gaussian noise (AWGN) channel. In the first, a modification method is proposed to reduce the bias of conventional first and second order moments based SNR estimator. Then, in order to reduce hardware implementation complicity, multi segments of cubic polynomial are adopted to approximate the expression of the proposed SNR estimator which doesn’t have a close form solution. The approximate expression is very precise in the SNR range -10dB ~ 20 dB as illustrated by numerical simulation. Besides, practical hardware circuit is proposed for FPGA implementation. Simulation results show that the proposed SNR estimator has the lowest normalized bias and variance when compared with two other classic estimators.

Purpose – This paper aims to explore the factors impacting and influencing the consumer's decision to purchase honey in a retail store. Design/methodology/approach – Data were collected from shopping mall intercepts in Perth, Western Australia, using a structured questionnaire. Exploratory factor analysis was used to identify the principal constructs which most influence the consumer's decision to purchase. On the basis of the ways in which honey was consumed within the household, cluster analysis was utilised to group the respondents into meaningful segments. Findings – In Perth, Western Australia, honey is primarily consumed as a spread or a sweetener on breakfast cereals and porridge. However, honey is also used as a marinade, in cakes and cookies and as a beverage. According to the way in which honey is consumed in the household, five clusters were identified. In purchasing honey from a retail store, exploratory factor analysis revealed three principal constructs which were most influential in the consumer's decision to purchase: brand reputation, origin and value for money. Ethnicity was found to have a significant influence on the way in which honey was consumed in the household and the importance of the three constructs extracted. Originality/value – This is one of the few studies that find a significant difference between Anglo Saxon and Asian consumers of honey.