The effect of bandwidth in scale-free network traffic

We model information traffic on scale-free networks by introducing the bandwidth as the delivering ability of links. We focus on the effects of bandwidth on the packet delivering ability of the traffic system to better understand traffic dynamic in real network systems. Such ability can be measured by a phase transition from free flow to congestion. Two cases of node capacity C are considered, i.e., C=constant and C is proportional to the node's degree. We figured out the decrease of the handling ability of the system together with the movement of the optimal local routing coefficient $\alpha_c$, induced by the restriction of bandwidth. Interestingly, for low bandwidth, the same optimal value of $\alpha_c$ emerges for both cases of node capacity. We investigate the number of packets of each node in the free flow state and provide analytical explanations for the optimal value of $\alpha_c$. Average packets traveling time is also studied. Our study may be useful for evaluating the overall efficiency of networked traffic systems, and for allevating traffic jam in such systems.Comment: 6 pages, 4 figure

JOR: A Journal-guided Reconstruction Optimization for RAID-Structured Storage Systems

This paper proposes a simple and practical RAID reconstruction optimization scheme, called JOurnal-guided Reconstruction (JOR). JOR exploits the fact that significant portions of data blocks in typical disk arrays are unused. JOR monitors the storage space utilization status at the block level to guide the reconstruction process so that only failed data on the used stripes is recovered to the spare disk. In JOR, data consistency is ensured by the requirement that all blocks in a disk array be initialized to zero (written with value zero) during synchronization while all blocks in the spare disk also be initialized to zero in the background. JOR can be easily incorporated into any existing reconstruction approach to optimize it, because the former is independent of and orthogonal to the latter. Experimental results obtained from our JOR prototype implementation demonstrate that JOR reduces reconstruction times of two state-of-the-art reconstruction schemes by an amount that is approximately proportional to the percentage of unused storage space while ensuring data consistency

Prognostic value of log odds of positive lymph nodes, lymph node ratio, and N stage in patients with colorectal signet ring cell carcinoma: A retrospective cohort study

AimLittle attention has been paid in the prognosis of colorectal signet ring cell carcinoma (SRCC). This study aims to explore the predictive capacity of log odds of positive lymph nodes (LODDS), lymph node ratio (LNR), and pN stage in the prognosis of patients with colorectal SRCC.MethodsA retrospective cohort study was designed, and data were extracted from the Surveillance, Epidemiology and End Results (SEER) database. Data on demographic characteristics, clinicopathological features, and treatment were extracted. Outcomes were overall survival (OS) and cancer-specific survival (CSS). Association of LODDS, LNR, and pN stage with OS and CSS were explored using Cox proportional hazard model and Cox competing risk model, respectively, with results showing as hazard ratio and 95% confidence interval (CI). Predictive performance of LODDS, LNR, and pN stage in OS and CSS was assessed by calculating C-index.ResultsA total of 2,198 patients were included in this study. LODDS, LNR, and pN stage were associated with the OS and CSS of colorectal SRCC patients (all P < 0.05). LODDS showed a good performance in the OS (C-index: 0.704, 95% CI: 0.690–0.718), which was superior to LNR (C-index: 0.657, 95% CI: 0.643–0.671) and pN stage (C-index: 0.643, 95% CI: 0.629–0.657). The C-index of LODDS, LNR, and pN stage for CSS was 0.733 (95% CI: 0.719–0.747), 0.713 (95% CI: 0.697–0.729), and 0.667 (95% CI: 0.651–0.683), respectively.ConclusionsLODDS displayed a better predictive capacity in the OS and CSS than LNR and pN stage, indicating that LODDS may be effective to predict the prognosis of colorectal SRCC in the clinic

Ecosystem visualization and analysis of Chinese prefabricated housing industry

Prefabricated housing has proven to achieve high quality, reduce costs and improve housing environmental performance. While prefabricated housing has been widely constructed in many jurisdictions, it is still in its infancy in China. However, the prefabrication sector in China is in transition as the macro environment is changing and new participants are expected to enter architecture, engineering and construction (AEC) industry who will have to work cooperatively as well as competitively with the existed companies. Such changes and strategic activities have impacts on every participant within the ecosystem. A better understanding of the whole industry as well as the participants’ strategic positioning will help companies develop their survival strategies. This paper aims to establish the prefabricated housing ecosystem in China based on the business ecosystem theory and to analyze the interrelationships among the major participants. A conceptual model of the ecosystem is established through literature review. Subsequently, the social network analysis (SNA) approach is employed to quantitatively analyze the strategic relationships between property developers and contractors who have adopted prefabrication in their residential projects. Finally, Node XL software is used for visualization and data analysis. Through the SNA measurements, the top 3 property developers and contractors are identified and several clusters are uncovered, which suggests a cooperation tendency among local actors