A new multi-level algorithm for balanced partition problem on large scale directed graphs

Graph partition is a classical combinatorial optimization and graph theory problem, and it has a lot of applications, such as scientific computing, VLSI design and clustering etc. In this paper, we study the partition problem on large scale directed graphs under a new objective function, a new instance of graph partition problem. We firstly propose the modeling of this problem, then design an algorithm based on multi-level strategy and recursive partition method, and finally do a lot of simulation experiments. The experimental results verify the stability of our algorithm and show that our algorithm has the same good performance as METIS. In addition, our algorithm is better than METIS on unbalanced ratio.

A New Multi-level Algorithms for Balanced Partition Problem on Large Scale Directed Graphs

Graph partition is a classical combinatorial optimization and graph theory problem, and it has a lot of applications, such as scientific computing, VLSI design and clustering etc. In this paper, we study the partition problem on large scale directed graphs under a new objective function, a new case of graph partition problem. We firstly propose the modeling of this problem, then design an algorithm based on multi-level strategy and recursive partition method, and finally do a lot of simulation experiments. The experimental results verify the stability of our algorithm and show that our algorithm has the same good performance as METIS. In addition, our algorithm is better than METIS on unbalanced ratio.

2251. Estimating the Need for Novel Gram-Negative Active Antibiotics in US Hospitals

Background Assessing the unmet need for novel antibiotics could inform appropriate utilization, enrollment in trials and ensure balance in aligning incentives and investments in therapeutic development. Methods The Cerner Healthfacts electronic health record repository was queried to identify inpatient treatment opportunities for Gram-negative active agents (GNAA) displaying either difficult-to-treat resistance (DTR; resistance to all β-lactams including carbapenems and fluoroquinolones) or extended-spectrum cephalosporin resistance (ECR). The former was quantified by aggregating episodes of confirmed DTR infection (i.e., DTR strain isolated and concomitant antibiotic(s) received) or suspected (i.e., 1–2 days of empiric colistin/polymyxin-B or aminoglycosides and no DTR pathogen isolated). Aggregate days of therapy (DOT) were reported as a range, multiplying episodes by site-specific or uniform 14-day treatment durations, respectively. Recursive partition and cluster analyses were performed for hospital characteristics and contributions of outbreaks to DTR treatment opportunities, respectively. Results Between 2009 and 2015, across 2,996,271 encounters, 1,352 episodes of potential targeted treatment were identified, which combined with empiric treatment episodes, represent 39–138 DOT/10,000 encounters for a DTR-GNAA. Similarly, 9,535 episodes of potential targeted therapy for an ECR-GNAA were identified (representing 211-466 DOT/10,000 encounters). The most common candidate site and pathogens for DTR-GNAA were lower respiratory and A. baumannii and P. aeruginosa respectively; DTR bloodstream infections displayed the highest crude mortality at 45%. Enterobacteriaceae urinary infections dominated the ECR group. Teaching hospitals with ≥100 beds were the most likely to encounter a DTR infection; potential outbreaks contributed to 10.6% of DTR treatment opportunities. Conclusion The candidate population for new antibacterials directed against highly resistant GN infections with limited treatment options is small but critical, indicating a role for non-revenue-based strategies to develop more effective antibiotics, as well as mechanisms to support trials that address real-world unmet needs. Disclosures All authors: No reported disclosures.

An indoor Wi-Fi access points localization algorithm based on improved path loss model parameter calculation method and recursive partition

The localization accuracy of the existing methods for indoor Wi-Fi access points ranging-based localization depends on the accuracy of the received signal strength measured. Because the existing ranging-based methods are interfered by various indoor environmental factors, it is difficult to accurately measure the received signal strength, which leads to the problem of low localization accuracy of the indoor Wi-Fi access points. An indoor Wi-Fi access points localization algorithm based on improved path loss model parameter calculation method and recursive partition is proposed in this article. The algorithm recursively partitions the region where the target Wi-Fi access points are located according to the idea of quadtree partition, and partitions it into same sub-grids, which is sequentially performed until the sub-grids are smaller than the set threshold. The detection device is used at the detection location of the grids to measure the received signal strength, which is from the detection points to the target access point, the grid center point is used as the location of the candidate target access point, the parameters in the path loss model are calculated by using the signal strength differences between the detection points, and then the distances between the detection points and the target access point are calculated by using the signal strength values from the detection points to the target access point. Finally, the location of the target access point is estimated by executing a localization algorithm, and the location of the grid center point closest to the target access point is taken as the location of the target access point. The experimental results show that under the premise that the target access point can be found, the proposed algorithm reduces the use of the device and improves the localization accuracy compared with the typical localization method.

Impact of Delay in Treatment Initiation on Overall Survival in Laryngeal Cancers

Objective Delayed treatment significantly affects survival in head and neck cancer, but defining delays for specific subsites remains controversial. The purpose of this study is to elicit the time point for delay in treatment initiation in all laryngeal cancers using a large cohort of patients within the National Cancer Database (NCDB). Study Design A retrospective cohort study. Setting NCDB. Subjects and Methods Patients with laryngeal cancer within the NCDB from 2006 to 2014 were identified. A recursive partition analysis (RPA) was performed to identify the time point at which delay contributed to increased hazard. Patients were stratified into 3 groups: no delay, at risk, and overtly delayed. Kaplan-Meier method was used to compare overall survival of these cohorts. Multivariate logistic regression analysis was used to identify predictors of delay. A multivariate Cox regression model was used to identify the final covariates that significantly affect overall survival. Results RPA identified the threshold for delay becomes significant at 46 days and exceeds baseline hazard at 73 days. Delay beyond 73 days is associated with a 16.1-month decrease in median survival ( P < .001). To ensure this was not due to any confounding variables, a subsequent Cox multivariate regression confirmed a significantly increased adjusted hazard ratio (HR) for patients who were at risk or delayed (adjusted HR [confidence interval], 1.09 [1.04-1.15] and 1.26 [1.18-1.35], respectively). Conclusion Treatment of laryngeal cancer requires a multidisciplinary approach, and coordinating this care can take time. Our study highlights that delay beyond 46 to 73 days significantly affects survival and identifies patients experiencing these delays.

Weather During Critical Epidemiological Periods and Subsequent Severity of Powdery Mildew on Grape Berries

Recorded severity of grape powdery mildew on berries of untreated, susceptible hybrid cultivars varied from 0.2 to 50.5% across a 30-year period in Geneva, NY; within 7 of those years, cluster disease severity ranged from 3.42 to 99.5% on Vitis vinifera ‘Chardonnay’. Although existing temperature-driven risk models could not account for this annual variation, pan evaporation (Epan), an environmental variable influenced by the collective effects of temperature, vapor pressure deficit, solar radiation, and wind speed, did. Logistic regression analysis (LRA) was used to classify epidemics as either mild or severe. Recursive partition analysis (RPA) provided a simplified decision tree for calculation of powdery mildew risk and incorporated (i) an estimate of the relative primary inoculum levels based on temperatures in the previous late summer and (ii) the current season favorability for pathogen development during the grapevine phenological period critical for berry infection by Erysiphe necator. Although the LRA had fewer instances of misclassification, RPA provided a rapid means for seasonal risk classification. Both the RPA and LRA models are able to describe disease severity risk in real time or can be used to forecast risk, thereby allowing growers to adjust management programs in a responsive manner.

Investigating the association of cytoplasmic and nuclear HIF-2 expression with cancer specific survival (CSS) in clear cell renal cell carcinoma.

387 Background: Studies support the prognostic importance of HIF-2α for ccRCC. Interestingly, a recent study has implicated HIF-2α as part of a protein translational initiation complex, a cytoplasmic function that goes far beyond its role as a nuclear transcription factor. We hypothesized that both the absolute expression as well as the subcellular localization of HIF-2α would predict clinicopathological features and CSS in ccRCC. Methods: A tissue microarray (TMA) study was conducted on 308 ccRCC patients. Survival differences were investigated with the log rank test and associations with CSS with uni- and multivariate Cox regression analyses. Recursive partition tree analysis was used to identify relevant cutoff values. Results: The median follow-up was 2.29 years (IQR 11.82). The mean percentage of positive cells was 22.45±18.00 and 0.12 ± 0.29 for HIF-2α nuclear (N) and cytoplasmic (C), respectively. High HIF-2α N (cutoff>32%) expression was associated with smaller tumor sizes (p = 0.002) and less advanced Fuhrman grades (p = 0.044). To the contrary, tumors with high HIF-2α C (>0%) more often had lymph node (p = 0.004), distant metastases (p = 0.021), and higher Fuhrman grades (p<0.0001). Univariate analyses showed an association of high HIF-2α N (p = 0.035) with better CSS. This was not found when HIF-2α N was used as a continuous variable (p = 0.067). In contrast, HIF-2α C demonstrated an association with CSS when examined as both a continuous (p < 0.0001) and as a dichotomized variable (p < 0.0001). After adjustment for TNM stage, ECOG PS, and Fuhrman grade, both continuous (p < 0.0001) and dichotomized (p < 0.0001) HIF-2α C variables remained significant predictors of CSS, while neither HIF-2α N variable was retained. The ratio of HIF-2α C/N was the strongest predictor of CSS in multivariate analysis (p = 0.001; HR 4.83 [95% CI: 1.99 – 11.76]). Conclusions: Our investigation suggests an important role for HIF-2α as a cytoplasmic protein translational initiation complex in ccRCC. This novel observation warrants further molecular and genetic studies examining biological pathways that are involved in the tumor promotive properties of HIF-2α in the cytoplasm.