Large Scale Spectral Clustering Using Approximate Commute Time Embedding

Spectral clustering is a novel clustering method which can detect complex shapes of data clusters. However, it requires the eigen decomposition of the graph Laplacian matrix, which is proportion to $O(n^3)$ and thus is not suitable for large scale systems. Recently, many methods have been proposed to accelerate the computational time of spectral clustering. These approximate methods usually involve sampling techniques by which a lot information of the original data may be lost. In this work, we propose a fast and accurate spectral clustering approach using an approximate commute time embedding, which is similar to the spectral embedding. The method does not require using any sampling technique and computing any eigenvector at all. Instead it uses random projection and a linear time solver to find the approximate embedding. The experiments in several synthetic and real datasets show that the proposed approach has better clustering quality and is faster than the state-of-the-art approximate spectral clustering methods

Histopathologic predictors of survival and recurrence in resected ampullary adenocarcinoma

Objective: The aim of the study was to define histopathologic characteristics that independently predict overall survival (OS) and disease-free survival (DFS), in patients who underwent resection of an ampullary adenocarcinoma with curative intent. Summary Background Data: A broad range of survival rates have been described for adenocarcinoma of the ampulla of Vater, presumably due to morphological heterogeneity which is a result of the different epitheliums ampullary adenocarcinoma can arise from (intestinal or pancreaticobiliary). Large series with homogenous patient selection are scarce. Methods: A retrospective multicenter cohort analysis of patients who underwent pancreatoduodenectomy for ampullary adenocarcinoma in 9 European tertiary referral centers between February 2006 and December 2017 was performed. Collected data included demographics, histopathologic details, survival, and recurrence. OS and DFS analyses were performed using Kaplan–Meier curves and Cox proportional hazard models. Results: Overall, 887 patients were included, with a mean age of 66 ± 10 years. The median OS was 64 months with 1-, 3-, 5-, and 10-year OS rates of 89%, 63%, 52%, and 37%, respectively. Histopathologic subtype, differentiation grade, lymphovascular invasion, perineural invasion, T-stage, N-stage, resection margin, and adjuvant chemotherapy were correlated with OS and DFS. N-stage (HR = 3.30 [2.09–5.21]), perineural invasion (HR = 1.50 [1.01–2.23]), and adjuvant chemotherapy (HR = 0.69 [0.48–0.97]) were independent predictors of OS in multivariable analysis, whereas DFS was only adversely predicted by N-stage (HR = 2.65 [1.65–4.27]). Conclusions: Independent predictors of OS in resected ampullary cancer were N-stage, perineural invasion, and adjuvant chemotherapy. N-stage was the only predictor of DFS. These findings improve predicting survival and recurrence after resection of ampullary adenocarcinoma

Estimating the New Keynesian Phillips Curve: A Vertical Production Chain Approach

It has become customary to estimate the New Keynesian Phillips Curve (NKPC) with GMM using a large instrument set that includes lags of variables that are ad hoc to the model. Researchers have also conventionally used real unit labor cost (RULC) as the proxy for real marginal cost, even though it is difficult to support its significance. This paper introduces a new proxy for the real marginal cost term as well as a new instrument set, both of which are based on the micro foundations of the vertical chain of production. I find that the new proxy, based on input prices as opposed to wages, provides a more robust and significant fit to the model. Instruments that are based on the vertical chain of production appear to be both more valid and relevant towards the model

Collapse risk and residual drift performance of steel buildings using post-tensioned MRFs and viscous dampers in near-fault regions

The potential of post-tensioned self-centering moment-resisting frames (SC-MRFs) and viscous dampers to reduce the collapse risk and improve the residual drift performance of steel buildings in near-fault regions is evaluated. For this purpose, a prototype steel building is designed using different seismic-resistant frames, i.e.: moment-resisting frames (MRFs); MRFs with viscous dampers; SC-MRFs; and SC-MRFs with viscous dampers. The frames are modeled in OpenSees where material and geometrical nonlinearities are taken into account as well as stiffness and strength deterioration. A database of 91 near-fault, pulse-like ground motions with varying pulse periods is used to conduct incremental dynamic analysis (IDA), in which each ground motion is scaled until collapse occurs. The probability of collapse and the probability of exceeding different residual story drift threshold values are calculated as a function of the ground motion intensity and the period of the velocity pulse. The results of IDA are then combined with probabilistic seismic hazard analysis models that account for near-fault directivity to assess and compare the collapse risk and the residual drift performance of the frames. The paper highlights the benefit of combining the post-tensioning and supplemental viscous damping technologies in the near-source. In particular, the SC-MRF with viscous dampers is found to achieve significant reductions in collapse risk and probability of exceedance of residual story drift threshold values compared to the MRF. © 2016 Springer Science+Business Media Dordrech

Determination of “borderline resectable” pancreatic cancer – A global assessment of 30 shades of grey

Background: Pancreatic ductal adenocarcinoma (PDAC) is an aggressive cancer with a poor prognosis. Accurate preoperative assessment using computed tomography (CT) to determine resectability is crucial in ensuring patients are offered the most appropriate therapeutic strategy. Despite the use of classification guidelines, any interobserver variability between reviewing surgeons and radiologists may confound decisions influencing patient treatment pathways. Methods: In this multicentre observational study, an international group of 96 clinicians (42 hepatopancreatobiliary surgeons and 54 radiologists) were surveyed and asked to report 30 pancreatic CT scans of pancreatic cancer deemed borderline at respective multidisciplinary meetings (MDM). The degree of interobserver agreement in resectability among radiologists and surgeons was assessed and subgroup regression analysis was performed. Results: Interobserver variability between reviewers was high with no unanimous agreement. Overall interobserver agreement was fair with a kappa value of 0.32 with a higher rate of agreement among radiologists over surgeons. Conclusion: Interobserver variability among radiologists and surgeons globally is high, calling into question the consistency of clinical decision making for patients with PDAC and suggesting that central review may be required for studies of neoadjuvant or adjuvant approaches in future as well as ongoing quality control initiatives, even amongst experts in the field

Postoperative complications after pancreatoduodenectomy for malignancy: results from the Recurrence After Whipple’s (RAW) study

Background Pancreatoduodenectomy (PD) is associated with significant postoperative morbidity. Surgeons should have a sound understanding of the potential complications for consenting and benchmarking purposes. Furthermore, preoperative identification of high-risk patients can guide patient selection and potentially allow for targeted prehabilitation and/or individualized treatment regimens. Using a large multicentre cohort, this study aimed to calculate the incidence of all PD complications and identify risk factors. Method Data were extracted from the Recurrence After Whipple’s (RAW) study, a retrospective cohort study of PD outcomes (29 centres from 8 countries, 2012–2015). The incidence and severity of all complications was recorded and potential risk factors for morbidity, major morbidity (Clavien–Dindo grade > IIIa), postoperative pancreatic fistula (POPF), post-pancreatectomy haemorrhage (PPH) and 90-day mortality were investigated. Results Among the 1348 included patients, overall morbidity, major morbidity, POPF, PPH and perioperative death affected 53 per cent (n = 720), 17 per cent (n = 228), 8 per cent (n = 108), 6 per cent (n = 84) and 4 per cent (n = 53), respectively. Following multivariable tests, a high BMI (P = 0.007), an ASA grade > II (P II patients were at increased risk of major morbidity (P < 0.0001), and a raised BMI correlated with a greater risk of POPF (P = 0.001). Conclusion In this multicentre study of PD outcomes, an ASA grade > II was a risk factor for major morbidity and a high BMI was a risk factor for POPF. Patients who are preoperatively identified to be high risk may benefit from targeted prehabilitation or individualized treatment regimens