Large-Scale Clustering of Cosmic Voids

We study the clustering of voids using $N$-body simulations and simple theoretical models. The excursion-set formalism describes fairly well the abundance of voids identified with the watershed algorithm, although the void formation threshold required is quite different from the spherical collapse value. The void cross bias $b_{\rm c}$ is measured and its large-scale value is found to be consistent with the peak background split results. A simple fitting formula for $b_{\rm c}$ is found. We model the void auto-power spectrum taking into account the void biasing and exclusion effect. A good fit to the simulation data is obtained for voids with radii $\gtrsim$ 30 Mpc/$h$, especially when the void biasing model is extended to 1-loop order. However, the best-fit bias parameters do not agree well with the peak-background split results. Being able to fit the void auto-power spectrum is particularly important not only because it is the direct observable in galaxy surveys, but also our method enables us to treat the bias parameters as nuisance parameters, which are sensitive to the techniques used to identify voids.Comment: 20 pages, 14 figures, minor changes to match published versio

Sarcoidosis Presenting as Acute Respiratory Distress Syndrome.

Sarcoidosis is a multisystem granulomatous disease of unknown origin. It typically involves the lungs and mediastinal lymph nodes in a chronic fashion. However, acute syndrome has been reported possibly in response to systemic release of proinflammatory cytokines. Acute pulmonary manifestations, especially acute respiratory failure or acute respiratory distress syndrome, remain extremely uncommon in individuals without a prior diagnosis. We present the case of a 41-year-old African American female, who presented with ARDS. An extensive workup into the cause of her illness remained negative, and she subsequently succumbed to her illness. A diagnosis of sarcoidosis was made upon autopsy, after exclusion of other granulomatous illness. The case highlights the need to consider this uncommon diagnosis in patients with unexplained ARDS to guide therapy

Measuring nonlocal Lagrangian peak bias

We investigate nonlocal Lagrangian bias contributions involving gradients of the linear density field, for which we have predictions from the excursion set peak formalism. We begin by writing down a bias expansion which includes all the bias terms, including the nonlocal ones. Having checked that the model furnishes a reasonable fit to the halo mass function, we develop a 1-point cross-correlation technique to measure bias factors associated with 2-distributed quantities. We validate the method with numerical realizations of peaks of Gaussian random fields before we apply it to N-body simulations. We focus on the lowest (quadratic) order nonlocal contributions. We can reproduce our measurement of \chi_{10} if we allow for an offset between the Lagrangian halo center-of-mass and the peak position. The sign and magnitude of \chi_{10} is consistent with Lagrangian haloes sitting near linear density maxima. The resulting contribution to the halo bias can safely be ignored for M = 10^13 Msun/h, but could become relevant at larger halo masses. For the second nonlocal bias \chi_{01} however, we measure a much larger magnitude than predicted by our model. We speculate that some of this discrepancy might originate from nonlocal Lagrangian contributions induced by nonspherical collapse.Comment: (v2): presentation clarified. agreement with the simulation improved. accepted for publication. 11 pages, 8 figure

Running the Domain: Truth, Rumours, and the Decision-Making of the Shimazu Warrior Family in 16th Century Japan

Using the Uwai Kakuken nikki, a diary kept by the middle-ranking warrior Uwai Kakuken from 1574 to 1586, this dissertation examines some fundamental factors that contributed to the political decision-making process of the Shimazu family in late sixteenth century Japan. In order to achieve this, this dissertation focuses on the Shimazu family’s communication system responsible for the gathering and delivery of information and military intelligence, and the management of rumours circulating within the entire Shimazu administration. Through the close reading and analysis of several key events in the Uwai Kakuken nikki, this dissertation argues that some of the primary factors affecting the decision-making process of the Shimazu family included the personal interests of the individual warriors involved in each instance and the perceived will of the deities as divined through lottery. Rather than acting in adherence to abstract notions of morality, loyalty, or truth, warriors often exploited the shortcomings of the communication system and the ambiguity of factual information in order to further their individual agendas. In the administration’s decision-making process, many warriors were interested in boosting their legitimacy, but at the same time, they were also concerned about protecting their siblings and children from harm. The argument pushes back against the language of loyalty appearing in and promoted by law codes and military tales of premodern Japan. Beyond the pursuit of one’s immediate interests, warriors also made decisions based heavily on their spiritual beliefs. Spiritual acts like the kuji played an important role in influencing the way the Shimazu administration made military decisions in this period. Through the exploration of the Uwai Kakuken nikki, the findings of this dissertation show that the samurai often prioritized their individual interests as a way to manage the volatile social and political situation of sixteenth century Japan. To that end, decisions were made with the aim of balancing the many variables and limited resources a warrior had access to at any given time, while also allowing a warrior to maximize his own interests.PHDHistoryUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/163042/1/vwch_1.pd

Range-Free Localization with the Radical Line

Due to hardware and computational constraints, wireless sensor networks (WSNs) normally do not take measurements of time-of-arrival or time-difference-of-arrival for rangebased localization. Instead, WSNs in some applications use rangefree localization for simple but less accurate determination of sensor positions. A well-known algorithm for this purpose is the centroid algorithm. This paper presents a range-free localization technique based on the radical line of intersecting circles. This technique provides greater accuracy than the centroid algorithm, at the expense of a slight increase in computational load. Simulation results show that for the scenarios studied, the radical line method can give an approximately 2 to 30% increase in accuracy over the centroid algorithm, depending on whether or not the anchors have identical ranges, and on the value of DOI.Comment: Proc. IEEE ICC'10, Cape Town, South Africa, May, 201

Flash-point prediction for binary partially miscible mixtures of flammable solvents

Flash point is the most important variable used to characterize fire and explosion hazard of liquids. Herein, partially miscible mixtures are presented within the context of liquid-liquid extraction processes. This paper describes development of a model for predicting the flash point of binary partially miscible mixtures of flammable solvents. To confirm the predictive efficacy of the derived flash points, the model was verified by comparing the predicted values with the experimental data for the studied mixtures: methanol + octane; methanol + decane; acetone + decane; methanol + 2,2,4-trimethylpentane; and, ethanol + tetradecane. Our results reveal that immiscibility in the two liquid phases should not be ignored in the prediction of flash point. Overall, the predictive results of this proposed model describe the experimental data well. Based on this evidence, therefore, it appears reasonable to suggest potential application for our model in assessment of fire and explosion hazards, and development of inherently safer designs for chemical processes containing binary partially miscible mixtures of flammable solvents

USING A K-NEAREST NEIGHBORS MACHINE LEARNING APPROACH TO DETECT CYBERATTACKS ON THE NAVY SMART GRID

In 2019, the Naval Facilities Engineering Command (NAVFAC) deployed the Navy smart grid across multiple bases in the United States. The smart grid can improve the reliability, availability, and efficiency of electricity supply. While this brings about immense benefit, placing the grid on a network connected to the internet increases the threat of cyberattacks aimed at intelligence collection, disruption, and destruction. In this thesis, we propose an Intrusion Detection System (IDS) for the NAVFAC smart grid. This IDS comprises a feature extractor, classifier, anomaly detector, and response manager. We use the K-Nearest Neighbors machine learning algorithm to show that various attacks (web attacks, FTP/SSH attacks, DOS, DDOS and port scanning) can be grouped into broader attack classes of Active, Denial, and Probe for appropriate response management. We also show that in order to reduce the load on the security operations center (SOC), the accuracy of the classifier can be maximized by optimizing the value of k, which is the number of data points nearest to the sample under consideration that decides the class assigned.http://archive.org/details/usingaknearestne1094566054Outstanding ThesisCommander, Republic of Singapore NavyApproved for public release. distribution is unlimite