Cascade failure analysis of power grid using new load distribution law and node removal rule

The work is supported in part by NSFC (Grant no. 61172070), IRT of Shaanxi Province (2013KCT-04), EPSRC (Grant no.Ep/1032606/1).

Cascade failure analysis of power grid using new load distribution law and node removal rule

The work is supported in part by NSFC (Grant no. 61172070), IRT of Shaanxi Province (2013KCT-04), EPSRC (Grant no.Ep/1032606/1).

Heuristics for the Critical Node Detection Problem in Large Complex Networks

Complex networks have recently attracted a significant amount of research attention due to their ability to model real world phenomena. One important problem often encountered is to limit diffusive processes spread over the network, for example mitigating pandemic disease or computer virus spread. A number of problem formulations have been proposed that aim to solve such problems based on desired network characteristics, such as maintaining the largest network component after node removal. The recently formulated critical node detection problem aims to remove a small subset of vertices from the network such that the residual network has minimum pairwise connectivity. Unfortunately, the problem is NP-hard and also the number of constraints is cubic in number of vertices, making very large scale problems impossible to solve with traditional mathematical programming techniques. Even many approximation algorithm strategies such as dynamic programming, evolutionary algorithms, etc. all are unusable for networks that contain thousands to millions of vertices. A computationally efficient and simple approach is required in such circumstances, but none currently exist. In this thesis, such an algorithm is proposed. The methodology is based on a depth-first search traversal of the network, and a specially designed ranking function that considers information local to each vertex. Due to the variety of network structures, a number of characteristics must be taken into consideration and combined into a single rank that measures the utility of removing each vertex. Since removing a vertex in sequential fashion impacts the network structure, an efficient post-processing algorithm is also proposed to quickly re-rank vertices. Experiments on a range of common complex network models with varying number of vertices are considered, in addition to real world networks. The proposed algorithm, DFSH, is shown to be highly competitive and often outperforms existing strategies such as Google PageRank for minimizing pairwise connectivity.

Upper-body morbidity following breast cancer treatment is common, may persist longer-term and adversely influences quality of life

Background: Impairments in upper-body function (UBF) are common following breast cancer. However, the relationship between arm morbidity and quality of life (QoL) remains unclear. This investigation uses longitudinal data to describe UBF in a population-based sample of women with breast cancer and examines its relationship with QoL. ---------- Methods: Australian women (n = 287) with unilateral breast cancer were assessed at three-monthly intervals, from six- to 18-months post-surgery (PS). Strength, endurance and flexibility were used to assess objective UBF, while the Disability of the Arm, Shoulder and Hand questionnaire and the Functional Assessment of Cancer Therapy- Breast questionnaire were used to assess self-reported UBF and QoL, respectively. ---------- Results: Although mean UBF improved over time, up to 41% of women revealed declines in UBF between sixand 18-months PS. Older age, lower socioeconomic position, treatment on the dominant side, mastectomy, more extensive lymph node removal and having lymphoedema each increased odds of declines in UBF by at least twofold (p < 0.05). Lower baseline and declines in perceived UBF between six- and 18-months PS were each associated with poorer QoL at 18-months PS (p < 0.05). ---------- Conclusions: Significant upper-body morbidity is experienced by many following breast cancer treatment, persisting longer term, and adversely influencing the QoL of breast cancer survivors.

Weight and weight change following breast cancer : evidence from a prospective, population-based, breast cancer cohort study

Background: While weight gain following breast cancer is considered common, results supporting these findings are dated. This work describes changes in body weight following breast cancer over 72 months, compares weight with normative data and explores whether weight changes over time are associated with personal, diagnostic, treatment or behavioral characteristics. Methods: A population-based sample of 287 Australian women diagnosed with early-stage invasive breast cancer was assessed prospectively at six, 12, 18 and 72 months post-surgery. Weight was clinically measured and linear mixed models were used to explore associations between weight and participant characteristics (collected via self-administered questionnaire). Those with BMI changes of one or more units were considered to have experienced clinically significant changes in weight. Results: More than half (57%) of participants were overweight or obese at 6 months post-surgery, and by 72 months post-surgery 68% of women were overweight or obese. Among those who gained more weight than age-matched norms, clinically significant weight gain between 6 and 18 months and 6 and 72 months post-surgery was observed in 24% and 39% of participants, respectively (median [range] weight gain: 3.9kg [2.0-11.3kg] and 5.2kg [0.6-28.7], respectively). Clinically-significant weight losses were observed in up to 24% of the sample (median [range] weight loss between 6 and 72 months post-surgery: -6.4kg [-1.9--24.6kg]). More extensive lymph node removal, being treated on the non-dominant side, receiving radiation therapy and lower physical activity levels at 6 months was associated with higher body weights post-breast cancer (group differences >3kg; all p<0.05). Conclusions: While average weight gain among breast cancer survivors in the long-term is small, subgroups of women experience greater gains linked with adverse health and above that experienced by age-matched counterparts. Weight change post-breast cancer is a contemporary public health issue and the integration of healthy weight education and support into standard breast cancer care has potential to significantly improve the length and quality of cancer survivorship.

Dynamics in large scale networks

In this thesis we study the properties of two large dynamic networks, the competition network of advertisers on the Google and Bing search engines and the dynamic network of friend relationships among avatars in the massively multiplayer online game (MMOG) Planetside 2. We are particularly interested in removal patterns in these networks. Our main finding is that in both of these networks the nodes which are most commonly removed are minor near isolated nodes. We also investigate the process of merging of two large networks using data captured during the merger of servers of Planetside 2. We found that the original network structures do not really merge but rather they get gradually replaced by newcomers not associated with the original structures. In the final part of the thesis we investigate the concept of motifs in the Barabási-Albert random graph. We establish some bounds on the number of motifs in this graph.

Resilience of protein-protein interaction networks as determined by their large-scale topological features

The relationship between the structure and function of biological networks constitutes a fundamental issue in systems biology. Particularly, the structure of protein-protein interaction networks is related to important biological functions. In this work, we investigated how such a resilience is determined by the large scale features of the respective networks. Four species are taken into account, namely yeast Saccharomyces cerevisiae, worm Caenorhabditis elegans, fly Drosophila melanogaster and Homo sapiens. We adopted two entropy-related measurements (degree entropy and dynamic entropy) in order to quantify the overall degree of robustness of these networks. We verified that while they exhibit similar structural variations under random node removal, they differ significantly when subjected to intentional attacks (hub removal). As a matter of fact, more complex species tended to exhibit more robust networks. More specifically, we quantified how six important measurements of the networks topology (namely clustering coefficient, average degree of neighbors, average shortest path length, diameter, assortativity coefficient, and slope of the power law degree distribution) correlated with the two entropy measurements. Our results revealed that the fraction of hubs and the average neighbor degree contribute significantly for the resilience of networks. In addition, the topological analysis of the removed hubs indicated that the presence of alternative paths between the proteins connected to hubs tend to reinforce resilience. The performed analysis helps to understand how resilience is underlain in networks and can be applied to the development of protein network models.

Subexponential Algorithm for d-Cluster Edge Deletion: Exception or Rule?

The correlation clustering problem is a fundamental problem in both theory and practice, and it involves identifying clusters of objects in a data set based on their similarity. A traditional modeling of this question as a graph theoretic problem involves associating vertices with data points and indicating similarity by adjacency. Clusters then correspond to cliques in the graph. The resulting optimization problem, Cluster Editing (and several variants) are very well-studied algorithmically. In many situations, however, translating clusters to cliques can be somewhat restrictive. A more flexible notion would be that of a structure where the vertices are mutually ``not too far apart'', without necessarily being adjacent. One such generalization is realized by structures called s-clubs, which are graphs of diameter at most s. In this work, we study the question of finding a set of at most k edges whose removal leaves us with a graph whose components are s-clubs. Recently, it has been shown that unless Exponential Time Hypothesis fail (ETH) fails Cluster Editing (whose components are 1-clubs) does not admit sub-exponential time algorithm STACS, 2013]. That is, there is no algorithm solving the problem in time 2 degrees((k))n(O(1)). However, surprisingly they show that when the number of cliques in the output graph is restricted to d, then the problem can be solved in time O(2(O(root dk)) + m + n). We show that this sub-exponential time algorithm for the fixed number of cliques is rather an exception than a rule. Our first result shows that assuming the ETH, there is no algorithm solving the s-Club Cluster Edge Deletion problem in time 2 degrees((k))n(O(1)). We show, further, that even the problem of deleting edges to obtain a graph with d s-clubs cannot be solved in time 2 degrees((k))n(O)(1) for any fixed s, d >= 2. This is a radical contrast from the situation established for cliques, where sub-exponential algorithms are known.

Is Pelvic Lymph Node Dissection Necessary in Patients with a Serum PSA<10ng/ml Undergoing Radical Prostatectomy for Prostate Cancer?

OBJECTIVE: Controversy persists concerning the role of pelvic lymph node dissection (PLND) in patients with preoperative PSA values <10ng/ml undergoing treatment for prostate cancer with a curative intent. The aim of this study was to determine the incidence of lymph node metastasis in this subgroup of patients. METHODS: Patients with clinically localized prostate cancer and a serum PSA<10ng/ml, without neoadjuvant hormonal or radiotherapy, with negative staging examinations who underwent radical retropubic prostatectomy with bilateral extended PLND and with >/=10 lymph nodes detected by the pathologist in the surgical specimen, were included in the study. RESULTS: A total of 231 patients with a median serum PSA of 6.7ng/ml (range 0.4-9.98) and a median age of 62 years (range 44-76) were evaluated. A median of 20 (range 10-72) nodes were removed per patient. Positive nodes were found in 26 of 231 patients (11%), the majority of which (81%) had a Gleason score >/=7 in the surgical specimen. Of the patients with a Gleason score >/=7 in the prostatectomy specimen 25% had positive nodes, whereas only 3% with a Gleason score node positive. CONCLUSIONS: The incidence of positive nodes in patients with clinically localized prostate cancer, a serum PSA<10ng/ml and a Gleason score >/=7 in the prostatectomy specimen was 25% after extended PLND. It seems that in this patient group extended PLND, including removal of nodes along the internal iliac vessels, is warranted.

Pelvic lymph node dissection in prostate cancer

CONTEXT: Pelvic lymph node dissection (PLND) is considered the most reliable procedure for the detection of lymph node metastases in prostate cancer (PCa); however, the therapeutic benefit of PLND in PCa management is currently under debate. OBJECTIVE: To systematically review the available literature concerning the role of PLND and its extent in PCa staging and outcome. All of the existing recommendations and staging tools determining the need for PLND were also assessed. Moreover, a systematic review was performed of the long-term outcome of node-positive patients stratified according to the extent of nodal invasion. EVIDENCE ACQUISITION: A Medline search was conducted to identify original and review articles as well as editorials addressing the significance of PLND in PCa. Keywords included prostate cancer, pelvic lymph node dissection, radical prostatectomy, imaging, and complications. Data from the selected studies focussing on the role of PLND in PCa staging and outcome were reviewed and discussed by all of the contributing authors. EVIDENCE SYNTHESIS: Despite recent advances in imaging techniques, PLND remains the most accurate staging procedure for the detection of lymph node invasion (LNI) in PCa. The rate of LNI increases with the extent of PLND. Extended PLND (ePLND; ie, removal of obturator, external iliac, hypogastric with or without presacral and common iliac nodes) significantly improves the detection of lymph node metastases compared with limited PLND (lPLND; ie, removal of obturator with or without external iliac nodes), which is associated with poor staging accuracy. Because not all patients with PCa are at the same risk of harbouring nodal metastases, several nomograms and tables have been developed and validated to identify candidates for PLND. These tools, however, are based mostly on findings derived from lPLND dissections performed in older patient series. According to these prediction models, a staging PLND might be omitted in low-risk PCa patients because of the low rate of lymph node metastases found, even after extended dissections (<8%). The outcome for patients with positive nodes is not necessarily poor. Indeed, patients with low-volume nodal metastases experience excellent survival rates, regardless of adjuvant treatment. But despite few retrospective studies reporting an association between PLND and PCa progression and survival, the exact impact of PLND on patient outcomes has not yet been clearly proven because of the lack of prospective randomised trials. CONCLUSIONS: On the basis of current data, we suggest that if a PLND is indicated, then it should be extended. Conversely, in view of the low rate of LNI among patients with low-risk PCa, a staging ePLND might be spared in this patient category. Whether this approach is also safe from oncologic perspectives is still unknown. Patients with low-volume nodal metastases have a good long-term prognosis; to what extent this prognosis is the result of a positive impact of PLND on PCa outcomes is still to be determined.

Removal of Limited Nodal Disease in Patients Undergoing Radical Prostatectomy: Long-Term Results Confirm a Chance for Cure

Abstract PURPOSE: In 2003 we reported on the outcomes of 88 patients with node positive disease who underwent radical prostatectomy and pelvic lymph node dissection (median 21 nodes) between 1989 and 1999. Patients with limited nodal disease appeared to have a good chance of long-term survival, even without immediate adjuvant therapy (androgen deprivation therapy and/or radiotherapy). In this study we update the followup in these patients and verify the reported projected probability of survival. MATERIALS AND METHODS: The projected 10-year cancer specific survival probability after the initially reported followup of 3.2 years was 60% for these patients with node positive disease. The outcome has been updated after a median followup of 15.6 years. RESULTS: Of the 39 patients with 1 positive node 7 (18%) remained biochemically relapse-free, 11 (28%) showed biochemical relapse only and 21 (54%) experienced clinical progression. Of these 39 patients 22 (57%) never required deferred androgen deprivation therapy and 12 (31%) died of prostate cancer. All patients with 2 (20) or more than 2 (29) positive nodes experienced biochemical relapse and only 5 (10%) of these 49 experienced no clinical progression. Of these 49 patients 39 (80%) received deferred androgen deprivation therapy. CONCLUSIONS: Biochemical relapse is likely in patients with limited nodal disease after radical prostatectomy and pelvic lymph node dissection, but for 47% of patients this does not imply death from prostate cancer. Patients with 1 positive node have a good (75%) 10-year cancer specific survival probability and a 20% chance of remaining biochemical relapse-free even without immediate adjuvant therapy.

The (n+1)/2 rule for dealiasing in the split-step Fourier methods for n-wave interactions

The aim of this letter is to demonstrate that complete removal of spectral aliasing occurring due to finite numerical bandwidth used in the split-step Fourier simulations of nonlinear interactions of optical waves can be achieved by enlarging each dimension of the spectral domain by a factor (n+1)/2, where n is the number of interacting waves. Alternatively, when using low-pass filtering for dealiasing this amounts to the need for filtering a 2/(n+1) fraction of each spectral dimension.