The prediction of recurrence and survival of patients with Dukes’ B colorectal cancer after curative resection with immunohistochemical detection of Survivin and Livin expressions

Objective: To detect the expressions of Survivin and Livin in Dukes’ B colorectal cancer tissues and analyze the prognosis after curative resection. Methods: The expressions of Survivin and Livin were evaluated immunohistochemically in Dukes’ B colorectal cancer specimens from 81 patients after curative resection of the tumor. Their correlations to clinical characters and survival were also explored. Results: The positive rates of Survivin and Livin in colorectal cancer tissues were significantly higher than those in normal colorectal tissues (58.0% vs. 16.7% and 45.7% vs. 8.3% respectively, P < 0.05). The expressions of Survivin and Livin were not related to gender, tumor site, primary size, T stage, pathologic category, and degree of differentiation (P > 0.05), and no relationship was found between the expressions of Survivin and Livin (P > 0.05). The expression rate of Survivin in patients older than 50 years was higher than that in patients younger than 50 years (70.6% vs. 36.7%, P < 0.05). Both Survivin and Livin were related to recurrence and/or metastasis (P = 0.02 and P = 0.001, respectively), and shorter survival (P = 0.039 and P = 0.001, respectively). Cox multivariate analysis showed T4 and positive Livin expression were independent prognostic factors (P = 0.002 and P = 0.047, respectively). Conclusion: Survivin and Livin are over-expressed in Dukes’ B colorectal cancer tissues and are positively related to recurrence and/or metastasis and poor prognosis after curative resection of the tumor.

Analysis on Technical Measures on Energy Saving and Consumption Reducing During Stevia Sugar Production

Based on the analysis of actual energy consumptions during stevia sugar production,practical measures were proposed to save energy（ gas,water and powder） consumption and reduce cost through waste heat recycle and utilization,process improvement,equipment operation efficiency,application of newly energysaving equipment,and some project applications were provided as case study for some techniques and methods adopted in the production.

Bluetooth Low Energy Device Identification Based on Link Layer Broadcast Packet Fingerprinting

With the rapid development of the Internet of Things(IoT),wireless technology has become an indispensable part of modern computing platforms and embedded systems.Wireless device fingerprint identification is deemed as a promising solution towards enhancing the security of device access authentication and communication process in the IoT scenario.However,the extraction of features from the network layer and its upper layers often confront restrictions from specific devices:the association with a certain wireless network and the access to the plaintext of the payload.Meanwhile,Bluetooth Low Energy(BLE)packets have been encrypted above the link layer,which makes those features difficult to extract.To tackle these problems,we introduce a novel method to identify BLE devices based on the fingerprint features in the data link layer.Initially,the BLE packets are collected through a receiver based on software-defined radio technology.Then,fields that reflect device differences in BLE broadcast packets are extracted through traffic analysis.Finally,a MultiLayer Perceptron(MLP)model is employed to recognize the category of BLE devices.An experimental result on a dataset with 15 types of BLE devices shows that the identification accuracy of the proposed method can reach 99.8%,which accomplishes better performance over previous work.