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Purpose: Describe and analyze the trends of thyroid cancer incidence and mortality in Guangzhou, explore the potential influencing factors, and provide evidence for the government to formulate prevention and treatment measures. Methods: Incident and death cases of thyroid cancer were retrieved from the Guangzhou cancer registry. The joinpoint regression models were used to estimate the incidence and mortality trends. Age-period-cohort models were used to estimate the age, period, and cohort effects on the time trends. Grey correlation analysis was performed to explore possible connections between thyroid cancer and social factors. Results: A total of 15,955 new cases of thyroid cancer were registered in Guangzhou during 2004–2018, the age-standardized incidence rate (ASIR) of thyroid cancer increased from 4.29/105 in 2004 to 22.36/105 in 2018, with the average annual percentage change (AAPC) of 13.40%. The overall increase can be attributed to the increase in the incidence of papillary thyroid carcinoma (PTC), which was dominated by tumors <2 cm. The ASIR was higher in women (16.12/105) compared to men (5.46/105), and young and middle-aged individuals had higher incidence rates than older people. The number of thyroid cancer deaths registered between 2010 and 2018 was 356, and the age-standardized mortality rates (ASMRs) were stable (approximately 0.42/105). Men's ASMR (0.34/105) and women's (0.49/105) were similar, and those 60 and older had greater mortality. The period and cohort relative risks showed an overall increasing trend. Furthermore, there was a strong positive correlation between the ASIRs and social determinants. Conclusions: During the study period, the incidence rate of thyroid cancer among young and middle-aged people in Guangzhou showed a rapidly increasing trend, and the mortality was relatively stable. In the future, more effective preventive measures should be taken for this age group to reduce the burden of disease and avoid overdiagnosis. [ABSTRACT FROM AUTHOR]

Aiming to promote the control performance of traditional fixed-parameter model predictive control (MPC), a new longitudinal and lateral coupling path tracking control method for the autonomous vehicle is proposed. First, a dynamic model of the autonomous vehicle, which can describe the longitudinal and lateral motion states, is established. Secondly, both the tire side-slip angle and centroid side-slip angle constraints are introduced in the path tracking controller design, which improves the accuracy of the prediction model at high speed. Furthermore, the key parameters of the proposed path tracking controller are optimized. The simulation and experimental results show that compared with the traditional MPC tracking control method, the lateral error and directional error of the proposed optimized path tracking control method under high speed decrease by 19.17 % and 11.89 %, respectively, which improves the path tracking performance significantly. [ABSTRACT FROM AUTHOR]

The post-quantum security of electronic voting protocols such as lattice-based ones are based on the assumption of certain difficult computational problems, which cannot be solved by classical computers and have also not been solved by effective quantum algorithms until now. However, these voting protocols are still at risk of compromise with the development of quantum computing, and we call them passive defense voting protocols. By making use of the encrypted three-pass protocol configured by taking physical limits of quantum computing into account and the message authentication code with information theory security, we propose a new post-quantum voting (NPQV) protocol. The proposed protocol exhibits the following advantages: (1) The post-quantum security of NPQV protocol depends on the physical limits that are inherent to quantum computers, so NPQV remains secure with the development of quantum computing and thus we call it active defense voting protocol. NPQV is the first voting protocol with active defense capability. (2) NPQV protocol is suitable for voting with numerous candidates and voters and accommodates the situation in which multiple voters vote simultaneously. (3) NPQV satisfies all the seven security requirements for an electronic voting protocol, i.e. privacy, verifiability, completeness, robustness, eligibility, unreusability and fairness. Moreover, it remains secure under internal and external attacks. [ABSTRACT FROM AUTHOR]

With the help of fog computing theory, this paper proposes Cluster Routing Optimized Algorithm of Nonlinear Event Migration Strategy, CR-NEMS. First, the fog node is used for high computing power and control ability to match and schedule sensor nodes to make them evenly distributed to achieve the purpose of network energy balance. Secondly, the intelligent algorithm is adopted to optimize the data transmission link to reduce network delays and improve transmission efficiency. Thirdly, the routing optimization is achieved through the iterative change and update strategy of controllable parameters to improve the global traversal capability of the entire network. Finally, the simulation experiment shows that the algorithm is compatible with other algorithms under the conditions of data transmission in the entire network. Compared with the network delay, network energy and network lifetime, the proposed strategy reduces by 23.49%, 13.22% and 12.17% respectively. It verifies that the algorithm in this paper effectively balances the network energy while solving the routing optimization problem and resource allocation problem in the target area. [ABSTRACT FROM AUTHOR]

Objectives: To develop and evaluate machine learning models using baseline and restaging computed tomography (CT) for predicting and early detecting pathological downstaging (pDS) with neoadjuvant chemotherapy in advanced gastric cancer (AGC). Methods: We collected 292 AGC patients who received neoadjuvant chemotherapy. They were classified into (a) primary cohort (206 patients with 3–4 cycles chemotherapy) for model development and internal validation, (b) testing cohort I (46 patients with 3–4 cycles chemotherapy) for evaluating models' predictive ability before and after the complete course, and (c) testing cohort II (n = 40) for model evaluation on its performance at early treatment. We extracted 1,231 radiomics features from venous phase CT at baseline and restaging. We selected radiomics models based on 28 cross-combination models and measured the areas under the curve (AUC). Our prediction radiomics (PR) model is designed to predict pDS outcomes using baseline CT. Detection radiomics (DR) model is applied to restaging CT for early pDS detection. Results: PR model achieved promising outcomes in two testing cohorts (AUC 0.750, p =.009 and AUC 0.889, p =.000). DR model also showed a good predictive ability (AUC 0.922, p =.000 and AUC 0.850, p =.000), outperforming the commonly used RECIST method (NRI 39.5% and NRI 35.4%). Furthermore, the improved DR model with averaging outcome scores of PR and DR models showed boosted results in two testing cohorts (AUC 0.961, p =.000 and AUC 0.921, p =.000). Conclusions: CT-based radiomics models perform well on prediction and early detection tasks of pDS and can potentially assist surgical decision-making in AGC patients. Key Points: • Baseline contrast-enhanced computed tomography (CECT)-based radiomics features were predictive of pathological downstaging, allowing accurate identification of non-responders before therapy. • Restaging CECT-based radiomics features were predictive to achieve pDS after and even at an early stage of neoadjuvant chemotherapy. • Combination of baseline and restaging CECT-based radiomics features was promising for early detection and preoperative evaluation of pathological downstaging of AGC. [ABSTRACT FROM AUTHOR]