Class, community, language and struggle: Hebrew against Yiddish in South Africa 1900-1914

Paper presented at the Wits History Workshop: The Making of Class, 9-14 February, 198

Dynamic communicability predicts infectiousness

Using real, time-dependent social interaction data, we look at correlations between some recently proposed dynamic centrality measures and summaries from large-scale epidemic simulations. The evolving network arises from email exchanges. The centrality measures, which are relatively inexpensive to compute, assign rankings to individual nodes based on their ability to broadcast information over the dynamic topology. We compare these with node rankings based on infectiousness that arise when a full stochastic SI simulation is performed over the dynamic network. More precisely, we look at the proportion of the network that a node is able to infect over a fixed time period, and the length of time that it takes for a node to infect half the network.We find that the dynamic centrality measures are an excellent, and inexpensive, proxy for the full simulation-based measures

Power system static and dynamic security studies for the 1st phase of Crete Island Interconnection

The island of Crete is currently served by an autonomous electrical system being fed by oil-fired (Heavy fuel or light Diesel oil) thermal power plants and renewables (wind and PVs). The peak load and annual electric energy consumption are approximately 600 MW and 3 TWh respectively; wind and photovoltaic parks contribute approximately 20% of the electricity needs of the island. Due to the expensive fuel used, the Cretan power system has very high electric energy generation cost compared to the Greek mainland. On the other side the limited size of the system poses severe limitations to the penetration of renewable energy sources, not allowing to further exploit the high wind and solar potential of the island. According to the Ten Year Network Development Plan (TYNDP) of the Greek TSO (Independent Power Transmission Operator S.A. IPTO S.A.), the interconnection of Crete to the mainland Transmission System of Greece will be realized through two links: A 150 kV HVAC link between the Peloponnese and the Crete (Phase I) and a HVDC link connecting the metropolitan area of Athens with Crete (Phase II). The total length of submarine and underground cable of the HVAC link will be approximately 174km; it is at the limits of the AC technology and the longest and deepest worldwide at 150 kV level. A number of studies have been conducted by a joint group of IPTO and Hellenic Electricity Distribution Network Operator (HEDNO) for the design of this interconnection. This paper presents briefly the power system static and dynamic studies conducted for the design of the AC link and its operation. Firstly, the paper presents the main results of the static security study regarding the calculation of the maximum power transfer capability of the link and the selection of the reactive power compensation scheme of the cable. Results from dynamic security analysis studies are also presented. The small-signal stability analysis concludes that a new (intra-area) electromechanical oscillation is introduced to the National System after the interconnection. The damping of the electromechanical oscillations is sufficient; however the operation of power system stabilizers at power plants located both at the mainland and at Crete power system can increase significantly the damping of important oscillation modes. Finally with respect to the risk of loss of synchronism after a significant disturbance in the system of Crete, such as a three-phase fault (“transient stability”)- enough safety margin is estimated by means of Critical Clearing Time calculations

Power system static and dynamic security studies for the 1st phase of Crete Island Interconnection

The island of Crete is currently served by an autonomous electrical system being fed by oil-fired (Heavy fuel or light Diesel oil) thermal power plants and renewables (wind and PVs). The peak load and annual electric energy consumption are approximately 600 MW and 3 TWh respectively; wind and photovoltaic parks contribute approximately 20% of the electricity needs of the island. Due to the expensive fuel used, the Cretan power system has very high electric energy generation cost compared to the Greek mainland. On the other side the limited size of the system poses severe limitations to the penetration of renewable energy sources, not allowing to further exploit the high wind and solar potential of the island. According to the Ten Year Network Development Plan (TYNDP) of the Greek TSO (Independent Power Transmission Operator S.A. IPTO S.A.), the interconnection of Crete to the mainland Transmission System of Greece will be realized through two links: A 150 kV HVAC link between the Peloponnese and the Crete (Phase I) and a HVDC link connecting the metropolitan area of Athens with Crete (Phase II). The total length of submarine and underground cable of the HVAC link will be approximately 174km; it is at the limits of the AC technology and the longest and deepest worldwide at 150 kV level. A number of studies have been conducted by a joint group of IPTO and Hellenic Electricity Distribution Network Operator (HEDNO) for the design of this interconnection. This paper presents briefly the power system static and dynamic studies conducted for the design of the AC link and its operation. Firstly, the paper presents the main results of the static security study regarding the calculation of the maximum power transfer capability of the link and the selection of the reactive power compensation scheme of the cable. Results from dynamic security analysis studies are also presented. The small-signal stability analysis concludes that a new (intra-area) electromechanical oscillation is introduced to the National System after the interconnection. The damping of the electromechanical oscillations is sufficient; however the operation of power system stabilizers at power plants located both at the mainland and at Crete power system can increase significantly the damping of important oscillation modes. Finally with respect to the risk of loss of synchronism after a significant disturbance in the system of Crete, such as a three-phase fault (“transient stability”)- enough safety margin is estimated by means of Critical Clearing Time calculations

Fournier's gangrene in a patient after third-degree burns: a case report

<p>Abstract</p> <p>Introduction</p> <p>Fournier's gangrene is characterized by tissue ischemia leading to rapidly progressing necrotizing fasciitis.</p> <p>Case presentation</p> <p>We present the case of a patient with Fournier's gangrene after third-degree burns. Clinical manifestations, laboratory results and treatment options are discussed.</p> <p>Conclusion</p> <p>Fournier's gangrene is a surgical emergency. Although it can be lethal, it is still a challenging situation in the field of surgical infections.</p

Predicting disease risks from highly imbalanced data using random forest

<p>Abstract</p> <p>Background</p> <p>We present a method utilizing Healthcare Cost and Utilization Project (HCUP) dataset for predicting disease risk of individuals based on their medical diagnosis history. The presented methodology may be incorporated in a variety of applications such as risk management, tailored health communication and decision support systems in healthcare.</p> <p>Methods</p> <p>We employed the National Inpatient Sample (NIS) data, which is publicly available through Healthcare Cost and Utilization Project (HCUP), to train random forest classifiers for disease prediction. Since the HCUP data is highly imbalanced, we employed an ensemble learning approach based on repeated random sub-sampling. This technique divides the training data into multiple sub-samples, while ensuring that each sub-sample is fully balanced. We compared the performance of support vector machine (SVM), bagging, boosting and RF to predict the risk of eight chronic diseases.</p> <p>Results</p> <p>We predicted eight disease categories. Overall, the RF ensemble learning method outperformed SVM, bagging and boosting in terms of the area under the receiver operating characteristic (ROC) curve (AUC). In addition, RF has the advantage of computing the importance of each variable in the classification process.</p> <p>Conclusions</p> <p>In combining repeated random sub-sampling with RF, we were able to overcome the class imbalance problem and achieve promising results. Using the national HCUP data set, we predicted eight disease categories with an average AUC of 88.79%.</p

Spatio-temporal Models of Lymphangiogenesis in Wound Healing

Several studies suggest that one possible cause of impaired wound healing is failed or insufficient lymphangiogenesis, that is the formation of new lymphatic capillaries. Although many mathematical models have been developed to describe the formation of blood capillaries (angiogenesis), very few have been proposed for the regeneration of the lymphatic network. Lymphangiogenesis is a markedly different process from angiogenesis, occurring at different times and in response to different chemical stimuli. Two main hypotheses have been proposed: 1) lymphatic capillaries sprout from existing interrupted ones at the edge of the wound in analogy to the blood angiogenesis case; 2) lymphatic endothelial cells first pool in the wound region following the lymph flow and then, once sufficiently populated, start to form a network. Here we present two PDE models describing lymphangiogenesis according to these two different hypotheses. Further, we include the effect of advection due to interstitial flow and lymph flow coming from open capillaries. The variables represent different cell densities and growth factor concentrations, and where possible the parameters are estimated from biological data. The models are then solved numerically and the results are compared with the available biological literature.Comment: 29 pages, 9 Figures, 6 Tables (39 figure files in total

Sparse matrix computations for dynamic network centrality

Time sliced networks describing human-human digital interactions are typically large and sparse. This is the case, for example, with pairwise connectivity describing social media, voice call or physical proximity, when measured over seconds, minutes or hours. However, if we wish to quantify and compare the overall time-dependent centrality of the network nodes, then we should account for the global flow of information through time. Because the time-dependent edge structure typically allows information to diffuse widely around the network, a natural summary of sparse but dynamic pairwise interactions will generally take the form of a large dense matrix. For this reason, computing nodal centralities for a timedependent network can be extremely expensive in terms of both computation and storage; much more so than for a single, static network. In this work, we focus on the case of dynamic communicability, which leads to broadcast and receive centrality measures. We derive a new algorithm for computing time-dependent centrality that works with a sparsified version of the dynamic communicability matrix. In this way, the computation and storage requirements are reduced to those of a sparse, static network at each time point. The new algorithm is justified from first principles and then tested on a large scale data set. We find that even with very stringent sparsity requirements (retaining no more than ten times the number of nonzeros in the individual time slices), the algorithm accurately reproduces the list of highly central nodes given by the underlying full system. This allows us to capture centrality over time with a minimal level of storage and with a cost that scales only linearly with the number of time points. We also describe and test three variants of the proposed algorithm that require fewer parameters and achieve a further reduction in the computational cost