Tree pruning in the structural approach to vowel reduction and lenition

The article scrutinises several vowel reduction and lenition phenomena by employing a model of syntax-like structural representations, i.e. Government Phonology 2.0. In contrast to the standard GP model, whereby lenition and vowel reduction can be viewed as shortening, element suppression or status switching, the structural approach employs the procedure of tree pruning with a heavily limited role of melodic annotation. This paper will take a closer look at node removal with special attention to its trajectory. In particular, two basic directionalities are considered: top-down and bottom-up. The former has been proposed to account for vowel reduction whereby the highest positions are deleted retaining the head and potentially its sister. The acquisition of plosives and fricatives points to the latter trajectory, which disposes of nodes closer to the head. However, the choice of positions that are targeted in weak contexts might be also related to the inherently encoded hierarchy of terminal nodes within the constituents in question.

How to plug out of the networks in jeopardy of ASF, Covid-19, social media or markets toxicity

Aim: In our research, we examine universal properties of the global network whose structure represents a real-world network that might be later extended to social media, commodity market or countries under the infl uence of diseases like Covid-19 or ASF.Methods: We propose quasi-epidemiological agent-based model of virus spread on a network. Firstly, we consider countries represented by subnetworks that have a scale-free structure achieved by the preferential attachment construction with a node hierarchy and binary edges. The global network of countries is a complete, directed, weighted network of thesesubnetworks connected by their capitals and divided into cultural and geographical proximity. Viruses with a defi ned strength or aggressiveness occur independently at one of the nodes of a selected subnetwork and correspond to a piece of products or messages or diseases.Results and conclusion: We analyse dynamics set by varying parameter values and observe a variety of phenomena including local and global pandemics and the existence of an epidemic threshold in the subnetworks. These phenomena have been also shown fromindividual users points of view because the node removal from the network might have impact on its nearest neighbours differently. The selective participation in global network is proposed here to avoid side effects when the global network has been fully connected and no longer divided into clusters.

Optimal Network Destruction Strategy with Heterogeneous Cost under Cascading Failure Model

By studying an attacker’s strategy, defenders can better understand their own weaknesses and prepare a response to potential threats in advance. Recent studies on complex networks using the cascading failure model have revealed that removing critical nodes in the network will seriously threaten network security due to the cascading effect. The conventional strategy is to maximize the declining network performance by removing as few nodes as possible, but this ignores the difference in node removal costs and the impact of the removal order on network performance. Having considered all factors, including the cost heterogeneity and removal order of nodes, this paper proposes a destruction strategy that maximizes the declining network performance under a constraint based on the removal costs. First, we propose a heterogeneous cost model to describe the removal cost of each node. A hybrid directed simulated annealing and tabu search algorithm is then devised to determine the optimal sequence of nodes for removal. To speed up the search efficiency of the simulated annealing algorithm, this paper proposes an innovative directed disturbance strategy based on the average cost. After each annealing iteration, the tabu search algorithm is used to adjust the order of node removal. Finally, the effectiveness and convergence of the proposed algorithm are evaluated through extensive experiments on simulated and real networks. As the cost heterogeneity increases, we find that the impact of low-cost nodes on network security becomes larger.

Criminal networks analysis in missing data scenarios through graph distances

Data collected in criminal investigations may suffer from issues like: (i) incompleteness, due to the covert nature of criminal organizations; (ii) incorrectness, caused by either unintentional data collection errors or intentional deception by criminals; (iii) inconsistency, when the same information is collected into law enforcement databases multiple times, or in different formats. In this paper we analyze nine real criminal networks of different nature (i.e., Mafia networks, criminal street gangs and terrorist organizations) in order to quantify the impact of incomplete data, and to determine which network type is most affected by it. The networks are firstly pruned using two specific methods: (i) random edge removal, simulating the scenario in which the Law Enforcement Agencies fail to intercept some calls, or to spot sporadic meetings among suspects; (ii) node removal, modeling the situation in which some suspects cannot be intercepted or investigated. Finally we compute spectral distances (i.e., Adjacency, Laplacian and normalized Laplacian Spectral Distances) and matrix distances (i.e., Root Euclidean Distance) between the complete and pruned networks, which we compare using statistical analysis. Our investigation identifies two main features: first, the overall understanding of the criminal networks remains high even with incomplete data on criminal interactions (i.e., when 10% of edges are removed); second, removing even a small fraction of suspects not investigated (i.e., 2% of nodes are removed) may lead to significant misinterpretation of the overall network.

Efficacy of Videoendoscopic Inguinal Femoral Lymphadenectomy for Management of Metastatic Skin Melanoma

Aim. Assessment of the utility and advantage of videoendoscopic inguinal femoral lymphadenectomy (VE-LAD) over the standard open technique (OLAD) in patients with malignant skin melanoma and metastatic lesions of regional inguinal and/or femoral lymph nodes.Materials and methods. The Saint-Petersburg Clinical Research Centre for Specialty Medical Aid in Oncology managed 86 inguinal femoral LADs in melanoma patients over 2013–2016. VE-LAD was rendered in 48 (54.7 %) cases, and OLAD otherwise.Results and discussion. A total of 72 patients were included in the study. VE-LAD was performed in 48 (54.7 %) cases, and OLAD otherwise. An average VE-LAD duration was 90 (60 to 160) min. Severe complications were observed in 4/48 (8 %) VE-LAD and 16/24 (66 %) OLAD cases, which reveals a significantly lower complication rate in the study cohort (chi-square p > 0.000). Lymphorrhoea was shorter in the study cohort (> 7 days in 5 patients vs. 3/24 and > 14 days only in 11/24 OLAD cases; chi-square p > 0.000). No significant differences in relapse-free survival were observed between the cohorts, with higher absolute values of 22.6 months in the VE-LAD (95 % CI 14.8–30.4, p = 0.087) vs. 9.4 months (95 % CI 0.0–18.9, p = 0.087) in OLAD cohort. A median OS was 52.3 months (95 % CI 30.5–74.1, p = 0.996) in the VE-LAD vs. 39.9 months (95 % CI 30.6–49.2, p = 0.996) in OLAD cohort.Conclusion. Videoendoscopic inguinal femoral lymphadenectomy allows a radical inguinal femoral lymph node removal alike in conventional surgical dissection. Our results indicate the method performance towards reduced postoperative wound complications. The oncological indicators are comparable to the traditional surgery cohort.

Vaginal Natural Orifice Transluminal Endoscopic Surgery for Gynecologic and Gynecologic Oncology Procedures

Vaginal Natural Orifice Transluminal Endoscopic Surgery (vNOTES) is an exciting new procedure that combines the best of laparoscopic and transvaginal surgery. The skills of a laparoscopic surgeon are applied to this approach which offers several advantages over traditional laparoscopy. First, the recovery of a vaginal procedure is shorter and less painful. Second, there is no abdominal incision which avoids potential for wound infection, herniation, pain and unsightly scarring. Third, the surgeon is seated with more comfortable ergonomics than traditional laparoscopy. Fourth, the blood supply is controlled very early in the procedure reducing overall blood loss. Fifth, the specimen for removal is quite close to the operator which enables less crossing of instruments and allows larger scopes with better illumination to be used. Finally, where traditional laparoscopy progresses to a smaller and smaller surgical area as the operation proceeds deeper into the pelvis, vNOTES is continually moving out of the pelvis with greater room for specimen manipulation and visualization. Advantages over traditional transvaginal surgery include the ability to examine the entire abdomen, the safety of direct visualization of the pedicles for adnexal removal, and the ability to perform abdominal procedures including lymph node removal, omentectomy, appendectomy, and biopsies not previously available to the vaginal approach.

Tracing Topic Transitions with Temporal Graph Clusters

Twitter serves as a data source for many Natural Language Processing (NLP) tasks. It can be challenging to identify topics on Twitter due to continuous updating data stream. In this paper, we present an unsupervised graph based framework to identify the evolution of sub-topics within two weeks of real-world Twitter data. We first employ a Markov Clustering Algorithm (MCL) with a node removal method to identify optimal graph clusters from temporal Graph-of-Words (GoW). Subsequently, we model the clustering transitions between the temporal graphs to identify the topic evolution. Finally, the transition flows generated from both computational approach and human annotations are compared to ensure the validity of our framework.

Vaginal Natural Orifice Transluminal Endoscopic Surgery (vNOTES) for Low-grade Endometrial Cancer: The First Fifty Patients

Study Objective: To review our experience with low-grade endometrial cancer managed with vaginal natural orifice transluminal endoscopic surgery (vNOTES) to determine the feasibility of this approach. Design: Retrospective review of the first fifty cases of endometrial cancer treated by vNOTES Setting: Academic University Population: Fifty consecutive cases of vNOTES management of women with low-grade endometrial cancer were reviewed to detail patient characteristics, operative procedures and outcomes, complications and follow-up. Methods: Patients underwent vNOTES hysterectomy and bilateral salpingo-oophorectomy. If Mayo criteria for lymphadenectomy were met, a laparoscopic lymph node removal was performed. Main Results: Mean age was 63 (33-90); mean BMI was 35.4 (22-58). In 44 women, both tubes and ovaries were removed via vNOTES. Three women had their ovaries retained due to early age, one woman had exploration for removal of an ovary with metastatic disease, and two women had neither tubes nor ovaries removed due to atresia and inability to identify these organs. Two patients underwent laparoscopic lymphadenectomy on the bases of frozen section evaluation. Mean operative time was 98 minutes (30-215). Fourteen patients were discharged the day of surgery; 34 discharged after overnight observation; hospitalization was prolonged in one patient due to ileus and one patient underwent laparotomy 30 hours after vNOTES for bleeding. Conclusion: VNOTES is a feasible management strategy for women with low-grade endometrial cancer. It permits laparoscopic inspection of the abdomen and direct visualization of vascular pedicles. It can provide a rapid recovery with minimal discomfort and no visible scar.

High-order interactions maintain or enhance structural robustness of a coffee agroecosystem network

The capacity of highly diverse systems to prevail has proven difficult to explain. In addition to methodological issues, the inherent complexity of ecosystems and issues like multicausality, non-linearity and context-specificity make it hard to establish general and unidirectional explanations. Nevertheless, in recent years, high order interactions have been increasingly discussed as a mechanism that benefits the functioning of highly diverse ecosystems and may add to the mechanisms that explain their persistence. Until now, this idea has been explored by means of hypothetical simulated networks. Here, we test this idea using an updated and empirically documented network for a coffee agroecosystem. We identify potentially key nodes and measure network robustness in the face of node removal with and without incorporation of high order interactions. We find that the system’s robustness is either increased or unaffected by the addition of high order interactions, in contrast with randomized counterparts with similar structural characteristics. We also propose a method for representing networks with high order interactions as ordinary graphs and a method for measuring their robustness.HighlightsThe robustness of a coffee-associated ecological network is either increased or unaffected by the incorporation of high order interactions.A method is proposed for representing high order interactions in ordinary networks.A method is proposed to measure the robustness of networks with high order interactions.High order interactions may promote the persistence of diverse ecosystems.